Characterizing the hippocampal synaptic and sleep abnormalities of a mouse model of human chromosome 16p11.2 microdeletion

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Content i

Characterizing the Hippocampal Synaptic and Sleep
Abnormalities of a Mouse Model of Human Chromosome
16p11.2 Microdeletion

Hung-Chi Lu
A dissertation
presented to the faculty
of the USC Graduate School
in candidacy for the degree
Doctor of Philosophy
(Neuroscience)
Mentor: Di Tian

August 2018

© Copyright by Hung-Chi Lu, 2018.
All rights reserved.

ii

Acknowledgements
I wish to give my deepest acknowledgement to my adviser, Professor Di Tian, for his
excellent mentoring, constructive comments and warm encouragement throughout my
graduate study. Many thanks to my lab colleagues, especially John Raucci, Keith To,
Zhenliang Han, Juan Wang, for their experimental help, inspiring comments, and
friendship. Also, I wish to extend my gratefulness to my committee members, Dr. Dion
Dickman, Dr. Huizhong Tao, Dr. Sebastien Bouret, for their steady guidance throughout
my qualification exam and dissertation defense. I really appreciate their generous support
for my academic career. And most importantly, I extend my heartfelt appreciation to my
parents and my sister for their unconditional love and support.

iii

Table of Contents
Characterizing the Hippocampal Synaptic and Sleep Abnormalities of a Mouse Model of Human
Chromosome 16p11.2 Microdeletion ................................................................................................ i
Acknowledgements ......................................................................................................................... ii
Table of Contents ........................................................................................................................... iii
Chapter 1: Introduction ................................................................................................................... 1
1.1. Introduction ...................................................................................................................... 1
1.1.1. Autism spectrum disorders and copy number variations ......................................... 1
1.1.2. Human chromosome 16p11.2 microdeletion and mouse chromosome 7qF3 model . 1
1.1.3. Objectives and significances .................................................................................. 1
1.2. Figures, tables, and legends .............................................................................................. 3
Table 1.1. List of genes at human chromosome 16p11.2 that have putative or known CNS
functions. ......................................................................................................................... 3
Figure 1.1. Mouse chromosome 7qF3 and human chromosome 16p11.2 are syntenic. ...... 4
Chapter 2: Altered synaptic transmission and maturation of hippocampal CA1 neurons in a mouse
model of human chr16p11.2 microdeletion ...................................................................................... 5
2.1. Abstract ............................................................................................................................ 5
2.2. Introduction ...................................................................................................................... 5
2.2.1. Human chromosome 16p11.2 microdeletion ........................................................... 5
2.2.2. Alterations of hippocampus in chr7qF3 mutant mice .............................................. 6
2.2.3. Objectives and significances .................................................................................. 6
2.3. Materials and methods ...................................................................................................... 7
2.3.1. Animals: ................................................................................................................ 7
2.3.2. Electrophysiology: ................................................................................................. 7
2.3.3. Morphology: ........................................................................................................ 10
2.3.4. Statistical analysis: ............................................................................................... 11
2.4. Results ............................................................................................................................ 11
2.4.1. Altered intrinsic membrane properties and current-voltage relationship in mutant CA1
neurons .......................................................................................................................... 11
2.4.2. Altered synaptic transmission and spontaneous neuronal firing in mutant CA1 neurons
...................................................................................................................................... 12
2.4.3. Altered balance of excitation and inhibition in mutant CA1 neurons ..................... 13
2.4.4. Altered presynaptic neurotransmission and AMPAR-mediated current in mutant CA1
neurons .......................................................................................................................... 13
2.4.5. Altered spine density and number of dendritic branches in mutant CA1 neurons .. 15
2.4.6. Altered development and maturation of the Schaffer collateral-CA1 synapses ...... 16
2.5. Discussion ...................................................................................................................... 19
2.5.1. Mutant CA1 neurons show increased excitatory activities .................................... 19
iv

2.5.2. Mutant CA1 neurons exhibit perturbed E/I balance .............................................. 19
2.5.3. Mutant mice show accelerated maturation at the Schaffer collateral-CA1 synapses20
2.5.4. Investigate synaptic abnormalities in other brain regions and from acute microdeletion
mice............................................................................................................................... 21
2.6. Figures, tables, and legends ............................................................................................ 22
Table 2.1. Stimulation intensities used in the experiments where stimuli were applied to the
Schaffer collaterals. ....................................................................................................... 22
Figure 2.1. Altered intrinsic membrane properties and current-voltage relationship. ....... 23
Figure 2.2. Significant increases in excitatory synaptic activities in mutant CA1 neurons.24
Figure 2.3. Imbalance of excitation and inhibition in mutant CA1 neurons. .................... 25
Figure 2.4. Increased presynaptic transmission onto and postsynaptic AMPAR-mediated
response from mutant CA1 neurons. .............................................................................. 26
Figure 2.5. Increased extrasynaptic AMPAR in mutant CA1 neurons. ............................ 27
Figure 2.6. Altered spine density and number of dendritic branches in mutant CA1 neurons.
...................................................................................................................................... 28
Figure 2.7. Altered NR2A and NR2B current in mutant CA1 neurons. ........................... 29
Figure 2.8. Altered profiles of AMPAR-silent synapses in P13-15 mutant CA1 neurons. 30
Chapter 3: Altered sleep architecture and rapid eye movement (REM) sleep in a mouse model of human
chromosome 16p11.2 microdeletion .............................................................................................. 31
3.1. Abstract .......................................................................................................................... 31
3.2. Introduction .................................................................................................................... 31
3.2.1. Sleep disturbance in neurodevelopmental disorders .............................................. 31
3.2.2. Human chromosome 16p11.2 microdeletion ......................................................... 32
3.2.3. Oscillation patterns .............................................................................................. 33
3.2.4. Lateral paragigantocellular nucleus ...................................................................... 33
3.2.5. Objectives and significances ................................................................................ 34
3.3. Materials and methods .................................................................................................... 34
3.3.1. Animals: .............................................................................................................. 34
3.3.2. Surgery: ............................................................................................................... 34
3.3.3. Polysomnographic recording and sleep stage analysis: ......................................... 35
3.3.4. Retrograde labeling: ............................................................................................. 36
3.3.5. Electrophysiology: ............................................................................................... 36
3.3.6. Immunostaining: .................................................................................................. 37
3.3.7. Statistical analysis: ............................................................................................... 37
3.4. Results ............................................................................................................................ 38
3.4.1. Reduced NREM and REM sleep, and increased wakefulness in mutant mice ....... 38
3.4.2. Impaired NREM to REM transition and maintenance of REM sleep in mutant mice39
3.4.3. Altered oscillation patterns in mutant mice ........................................................... 40
3.4.4. Altered intrinsic membrane properties in mutant vlPAG-projecting GABAergic LPGi
v

neurons .......................................................................................................................... 42
3.5. Discussion ...................................................................................................................... 43
3.5.1. Reduction in daytime NREM sleep and slow-wave oscillation in the delta range .. 43
3.5.2. Reduced REM sleep and increased wakefulness time ........................................... 44
3.5.3. Reduced REM-associated theta oscillation ........................................................... 45
3.5.4. Reduction in wake-associated theta oscillation ..................................................... 47
3.5.5. Altered intrinsic membrane properties in vlPAG-projecting GABAergic LPGi neurons
...................................................................................................................................... 47
3.6. Figures, tables, and legends ............................................................................................ 49
Figure 3.1. Reduced NREM and REM sleep, and increased wakefulness in mutant mice.49
Figure 3.2. Bout analysis of REM and NREM sleep demonstrated impaired NREM to REM
transition and REM maintenance in mutant mice. .......................................................... 50
Figure 3.3. Power spectral analysis of oscillation classes and 1-Hz bins. ........................ 51
Figure 3.4. Altered intrinsic membrane properties but normal I-V curve in mutant vlPAG-
projecting GABAergic LPGi neurons............................................................................. 52
References .................................................................................................................................... 54

1

Chapter 1: Introduction
1.1. Introduction
1.1.1. Autism spectrum disorders and copy number variations
Autism spectrum disorders (ASDs) are characterized by significant impairment in social interaction,
verbal and non-verbal communication deficit, as well as repetitive and stereotyped interest and behavior.
Intellectual disability, anxiety disorder, and epilepsy are the common neurological comorbidities. ASDs
have a complex genetic landscape. So far, hundreds of genes and genetic loci are implicated in ASDs.
Copy number variations (CNVs) constitute a unique class of genetic abnormality in ASDs accounting
for 10-20% cases due to their genetic complexity, heterogeneous clinical presentation, and multiplex
pathogenic mechanisms (Levy et al., 2011; Malhotra and Sebat, 2012; Merikangas et al., 2015).

1.1.2. Human chromosome 16p11.2 microdeletion and mouse chromosome 7qF3 model
Human chromosome 16p11.2 microdeletion is one of the most common CNVs in ASDs (Sebat et al.,
2007; Marshall et al., 2008). The deleted region spans ~660kb in human and contains 27 protein-coding
genes; many of these genes are expressed in the brain and have a wide range of functions, such as cell-
cell adhesion, neurotransmitter release, signal transduction, transcriptional regulation, protein
degradation, and circuit development. The typical neurological abnormalities include intellectual
disability, language deficit, anxiety, attention-deficit hyperactivity disorder (ADHD), and epilepsy
(Hanson et al., 2010; Zufferey et al., 2012). The functions of a subset of genes are listed in Table 1.1. A
mouse model (Fig. 1.1), carrying heterozygous deletion of a syntenic region of human chr16p11.2
(mouse chr7qF3), demonstrated phenotypes recapitulating some of the neurobehavioral abnormalities as
individuals with chr16p11.2 microdeletion, providing a useful tool for studying how haploinsufficiency
of chr16p11.2 genes impacts brain development and function (Horev et al., 2011; Portmann et al., 2014;
Pucilowska et al., 2015; Tian et al., 2015). However, recently a human genetic study of family with ASD
and ID showed affected family members have deletions of only five genes. Together, they form the so-
called “critical region”, and attracted significant attention recently. At the behavioral level, the most
significant findings are learning and memory deficits, hyperactivity and anxiety phenotypes, such as
adult chr7qF3 mice exhibited deficits in hippocampus-associated learning in contextual fear-conditioning
and inhibitory avoidance test (Horev et al., 2011; Portmann et al., 2014; Pucilowska et al., 2015; Tian et
al., 2015).

1.1.3. Objectives and significances
Several published studies and our previous works have begun to reveal the synaptic dysfunctions in the
2

anatomical regions important for these behavioral abnormalities. For example, electrophysiological
studies showed synaptic transmission defects in the striatum and nucleus accumbens, and impaired
synaptic plasticity at Schaffer collateral–CA1 synapse in the hippocampus (Portmann et al., 2014; Tian
et al., 2015). Although these initial observations have provided a glimpse into the pathophysiology of the
hippocampal formation in chr7qF3 mice, in-depth analyses of the hippocampus at anatomical and
electrophysiological levels are lacking. For instance, although no gross abnormalities have been
identified in the mutant mice, the potential alterations at fine synaptic levels, such as synaptic number
and morphology, have not been studied. In addition, how chr16p11.2 microdeletion affects the
electrophysiological properties of individual neurons and connectivity has not been investigated.
Furthermore, a couple of published studies and our previous works also showed the deficits in KCTD13-
Cul3-RhoA pathway (Kctd13 is one of the gene in chr16p11.2 microdeletion region) in Drosophila, and
impaired γ-aminobutyric acidergic (GABAergic) medium spiny neurons (MSNs) dopamine signaling
and hyperactivity in chr7qF3 mice (Stavropoulos and Young, 2011; Pfeiffenberger and Allada, 2012;
Portmann et al., 2014), indicating the possible abnormalities in sleep phenotypes of this mouse model.
The goal in this dissertation is to dissect the alterations of hippocampal CA1 neurons and sleep
phenotypes in a mouse model of human chr16p11.2 microdeletion, and to explore the causal genes and
potential mechanisms. Toward this goal, I will demonstrate the results from electrophysiological
recordings in chapter 2, and present the results from sleep analyses in chapter 3.

3

1.2. Figures, tables, and legends
Table 1.1. List of genes at human chromosome 16p11.2 that have putative or known CNS functions.
Genes General Functions CNS Functions References
Coro1a
(Coronin-like protein A)
Actin binding protein; T-cell trafficking
Unknown; but a family member of Coronin 3, is
involved in brain morphogenesis
(Hasse et al., 2005; Mueller
et al., 2008)
Mapk3
(Erk1)
MAP kinase
MAPK pathway is involved in plasticity; Erk1
KO mice show mild learning deficits
(Selcher et al., 2001; Sweatt,
2004)
Ppp4c
(Protein phosphotase 4c)
Serine/threonine phosphatase 4 catalytic
subunit
Activate mTOR and NF-k B pathway; interact
with survival motor neuron complex
(Cohen et al., 2005)
Doc2 α
(C2 domain protein)
Ca
2+
-binding protein
Synaptic vesicle associated Ca
2+
-binding protein;
regulating vesicle release; KO mice show
impaired LTP and passive avoidance task
(Verhage et al., 1997;
Sakaguchi et al., 1998;
Groffen et al., 2006)
Taok2
(Thousand and one
kinase 2)
Serine/threonine kinase; activate
p38/JNK MAP kinase pathway
Activity-induced N-cadherin endocytosis (Huangfu et al., 2006)
Kctd13
Btb/Poz domain-containing adapter for
Cul3-mediated RhoA degradation protein
1
Protein turnover; may be involved in E3
ubiquitin ligase complex
(Crepel et al., 2011; Golzio et
al., 2012)
Sez6l2
(Seizure 6 like protein
2)
Transmembrane protein
Unknown; but Sez6 KO mice show excessive
short dendrites and neuritic branching
(Gunnersen et al., 2007)
Cdipt
(Phosphatidylinositol
synthase)
Catalyze biosynthesis of
phosphatidylinotiol
Unknown; but may be involved in PI3K
signaling pathway
(Saito et al., 1998; Nielsen et
al., 2008)
Mvp
(Major vault protein)
Structural protein in ribonucleoprotein
particles (vaults); associated with
microtubules; activate PI3K and MAPK
pathway
Unknown; may be involved in multi-drug
resistance in brain tumors; expressed in nucleus-
neurite axis; maybe involved in mRNA transport
(Kolli et al., 2004; Kim et al.,
2006; Steiner et al., 2006;
Paspalas et al., 2009)

4

Figure 1.1. Mouse chromosome 7qF3 and human chromosome 16p11.2 are syntenic.
Both the gene content and the order they are arranged on the chromosome are conserved between human and
mouse (Horev et al., 2011). Human genes are capitalized while mouse genes are lowercased. The five genes in
the putative critical region are labelled in red.

5

Chapter 2: Altered synaptic transmission and maturation of hippocampal
CA1 neurons in a mouse model of human chr16p11.2 microdeletion
2.1. Abstract
The pathophysiology of neurodevelopmental disorders is often observed early in infancy and toddlerhood.
Mouse models of syndromic disorders have provided insight regarding mechanisms of action, but most
studies have focused on characterization in juveniles and adults. Insight into developmental trajectories,
particularly those related to circuit and synaptic function, will likely yield important information
regarding disorder pathogenesis that leads to symptom progression. Chromosome 16p11.2 microdeletion
is one of the most common copy number variations associated with a spectrum of neurodevelopmental
disorders. Yet, how haploinsufficiency of chr16p11.2 affects early synaptic maturation and function is
unknown. To address this knowledge gap, the present study focused on three key components of circuit
formation and function—basal synaptic transmission, local circuit function, and maturation of
glutamatergic synapses—in developing hippocampal CA1 neurons in a chr16p11.2 microdeletion mouse
model. The data demonstrate increased excitability, imbalance in excitation and inhibition, and
accelerated maturation of glutamatergic synapses in heterozygous deletion mutant CA1 neurons. Given
the critical role of early synaptic development in shaping neuronal connectivity and circuitry formation,
these newly identified synaptic abnormalities in chr16p11.2 microdeletion mice may contribute to altered
developmental trajectory and function of the developing brain.

2.2. Introduction
2.2.1. Human chromosome 16p11.2 microdeletion
Chromosome copy number variations (CNVs) are frequently associated with neurodevelopmental
disorders, such as autism spectrum disorder (ASD), schizophrenia, and intellectual disability (ID) (Levy
et al., 2011; Malhotra and Sebat, 2012; Girirajan et al., 2013; Pinto et al., 2014). Microdeletion at human
chromosome 16p11.2 is one of the most common CNVs in ASD and accounts for approximately 0.5-
1.0% of ASD cases (Sebat et al., 2004; Kumar et al., 2008; Marshall et al., 2008; Weiss et al., 2008).
Human chr16p11.2 microdeletion is clinically heterogeneous, and the most common neurological
presentations are language deficits, intellectual impairment, ASD, anxiety, attention deficit hyperactivity
disorders (ADHD), and epilepsy (McCarthy et al., 2009; Hanson et al., 2010; Shinawi et al., 2010;
Zufferey et al., 2012). Despite the broad clinical heterogeneity, the high prevalence of neurological
deficits among individuals carrying the chr16p11.2 microdeletion indicates that genes in this region,
individually or collectively, play critical roles in neurodevelopment and brain function.
6

Several studies have revealed multiple abnormalities at behavioral, biochemical, transcriptional, and
electrophysiological levels in mouse models of human chr16p11.2 microdeletion (Horev et al., 2011;
Blumenthal et al., 2014; Portmann et al., 2014; Kusenda et al., 2015; Pucilowska et al., 2015; Tian et al.,
2015; Yang et al., 2015). Two investigations in zebrafish have also demonstrated the significance of
several candidate genes in the pathogenesis of chr16p11.2 microdeletion (Blaker-Lee et al., 2012; Golzio
et al., 2012). However, how the chr16p11.2 microdeletion affects early synapse development and
function have not been adequately studied.

2.2.2. Alterations of hippocampus in chr7qF3 mutant mice
Intellectual impairment is reported in a high percentage of patients with chr16p11.2 microdeletion. The
affected individuals typically present with learning disabilities and reduced intelligence quotient scores
(Hanson et al., 2010; Shinawi et al., 2010; Zufferey et al., 2012). Given the importance of the
hippocampus in learning, memory, and cognition (Squire and Wixted, 2011; Squire et al., 2015), and its
frequent involvement in patients with neurodevelopmental disorders, we hypothesize hippocampal
synaptic dysfunction plays a significant pathogenic role in intellectual impairment associated with
chr16p11.2 microdeletion (Boucher et al., 2012; Boronat et al., 2015; Bostrom et al., 2016). Consistent
with this hypothesis, a mouse model for human chr16p11.2 microdeletion, chr7qF3 mutant mice, exhibit
deficits in a hippocampus-associated learning task (Tian et al., 2015). In the same mouse model,
electrophysiological studies of the Schaffer collateral-CA1 synapses from P28-P35 mice demonstrated
normal α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR)-mediated synaptic
transmission and normal N-methyl-D-aspartate receptor (NMDAR)-mediated plasticity, but showed
altered metabotropic glutamate receptor (mGluR)-mediated synaptic plasticity (Tian et al., 2015). These
initial observations have provided important insights into the pathophysiology of the hippocampus in
juvenile chr7qF3 mutant mice, but the influence of the microdeletion on developmental maturation of
hippocampal synaptic transmission and function is still unknown. Recent reports show that the rate of
maturation of synapses at the hippocampal formation can be influenced by genes implicated in
neurodevelopmental disorders (Clement et al., 2012; Clement et al., 2013; Qiu et al., 2014; Peng et al.,
2016). Experiments that examine the effect of chr16p11.2 microdeletion on synapse development will
provide insights into developmental and adult circuit dysfunction, with relevance to human
pathophysiology.

2.2.3. Objectives and significances
In this study, we performed patch clamp recording on postnatal day 13-15 (P13-15) and P20-22
7

hippocampal CA1 neurons in wildtype and chr7qF3 mutant mice. We specifically characterized basal
synaptic transmission, local connectivity, and synaptic maturation, which are key parameters influencing
the formation and functions of the local circuitry of the hippocampus. The combined electrophysiological
and morphological data demonstrate increased excitability, imbalance in excitation and inhibition, and
accelerated maturation of glutamatergic synapses in chr7qF3 mutant mice.

2.3. Materials and methods
2.3.1. Animals:
Mice carrying a deletion of the syntenic region of human chr16p11.2 have been previously analyzed
(Horev et al., 2011; Blumenthal et al., 2014; Pucilowska et al., 2015; Tian et al., 2015). Mice used in this
study have been backcrossed onto the congenic C57BL6/N (Charles River) background for more than
20 generations. Wildtype (WT) and heterozygous mutant (Mut) mice were group-housed and kept on a
12:12 hr light:dark cycle with unrestricted access to food and water. All experimental procedures were
approved by the Institutional Animal Care and Use Committee at the Children’s Hospital Los Angeles
and conformed to NIH guidelines. The experimenter was blind to the genotypes in all experiments and
during data analysis.

2.3.2. Electrophysiology:
Whole-cell patch clamp recordings were performed on dorsal hippocampal CA1 neurons from P20-22
male mice in all experiments. In addition, P13-15 male mice were used in experiments designed to
investigate AMPA-silent synapses. Mice were euthanized by rapid decapitation and the brains were
immediately submerged in ice-cold high sucrose dissection buffer (HSDB) for 1 min. Three-hundred-
micron coronal sections were cut on a Leica VT1000 S vibratome in ice-cold HSDB, incubated in
artificial cerebrospinal fluid (aCSF) at 30°C for 15 min, then transferred to aCSF at
25°C. Slices were further recovered at room temperature for 1 hr before recording. HSDB was composed
of (in mM): 87 NaCl, 75 sucrose, 2.5 KCl, 1.2 NaH2PO4, 30 NaHCO3, 25 Glucose, 20 HEPES, 5 Na-
Ascorbate, 3 Na-Pyruvate, 2 Thiourea, 10 MgSO4, and 0.5 CaCl 2. aCSF was composed of (in mM): 119
NaCl, 2.5 KCl, 1 MgCl 2, 2 CaCl 2, 26 NaHCO3, 1.23 NaH2PO 4, and 10 Glucose. All buffers used in
dissection, recovery, and recording were supplemented with a mix of 95% O2 and 5% CO2 to maintain
the pH at 7.4. All recordings were performed in aCSF at room temperature with a Multiclamp 700B
microelectrode amplifier (Molecular Device, Sunnyvale, CA). Signals were low-pass filtered at a
frequency of 1k Hz and digitized at 10k Hz using Digidata 1440A amplifier and Clampex 10.7 software
(Molecular Device). Series resistance was monitored continuously during recording and experiments
were discarded if the measurement changed by >15%. All internal solutions (resistance 4–7 MΩ; pH 7.2-
7.4; osmolarity 290-300 mOsm) used in this study contained 6.7 mM biocytin and 80 µM Alexa-Fluor
594 hydrazide with the addition of other components as described below for individual experiments. In
experiments in which stimulations were applied, the stimulation intensities were recorded and reported
in Table 2.1. No differences were observed in the stimulation intensities for wildtype and mutant neurons
8

across all experiments except for the silent synapse measurement on neurons of P20-22. We consistently
placed the stimulating electrodes in the middle of the striatum radiatum and approximately 300 microns
from the recorded neurons, so the positioning effects on the evoked responses were minimized. All pulses
were 200 µs in duration and delivered at 15 sec inter pulse intervals unless otherwise specified. All data
were analyzed using Minianalysis (version 6.0.3. Synaptosoft Inc) or Clampfit software (version 10.7,
Molecular Device).

Current clamp recording was performed to measure the resting membrane potential (RMP) (Schiebe and
Jaeger, 1980; Graves et al., 2012). Specifically, after obtaining a gigaseal, the membrane was carefully
broken to avoid a leaking current larger than 50 pA. The membrane potentials were recorded for 10 min
and the measurements during the last 5 min were used to calculate the RMP. The electrodes were filled
with (in mM) 131 K-gluconate, 20 KCl, 8 NaCl, 10 HEPES, 2 EGTA, 2 NaATP, and 0.3 NaGTP. To
measure membrane resistance (Rm), series resistance (Rs), and membrane capacitance (Cm), neurons
were recorded for 15 min, and the measurements during the last 5 min were analyzed. Neurons were
discarded if the values of these three measurements fluctuated more than 15% from the average values
(Donnelly, 1994). The electrodes were filled with (in mM) 131 K-gluconate, 20 KCl, 8 NaCl, 10 HEPES,
2 EGTA, 2 NaA TP, and 0.3 NaGTP. To determine the current-voltage (I-V) curve, membrane current at
eleven voltage steps (-100, -80, -60, -40, -20, 0, 20, 40, 60, 80, 100 mV) were measured. Specifically,
neurons were held at each step for 400 ms. The initial peak current for the entire step and the average
current for the last 100 ms were analyzed. The voltage step cycle was repeated twice for each neuron and
the current measurements for each step were averaged and used for the data analysis. The electrodes were
filled with (in mM) 131 K-gluconate, 20 KCl, 8 NaCl, 10 HEPES, 2 EGTA, 2 NaA TP, and 0.3 NaGTP.

Spontaneous and miniature excitatory postsynaptic currents (sEPSCs and mEPSCs) were recorded
sequentially from the same neurons. Specifically, neurons were held at -70 mV and recorded for 15 min
in the presence of 50 µM picrotoxin (PTX) and 1 µM strychnine (Stry) to isolate sEPSCs. Immediately
afterwards, 200 nM tetrodotoxin (TTX) was added to aCSF and recording was continued for another 15
min to record mEPSCs. The recording electrodes were filled with (in mM) 131 K-gluconate, 20 KCl, 8
NaCl, 10 HEPES, 2 EGTA, 2 NaA TP , and 0.3 NaGTP . Spontaneous and miniature inhibitory postsynaptic
currents (sIPSCs and mIPSCs) were also recorded sequentially from the same neurons. Specifically,
neurons were held at -70 mV and recorded for 15 min in the presence of kynurenic acid (KA) to isolate
sIPSCs. Then 200 nM TTX was added to the aCSF and recording was continued for another 15 min to
record mIPSCs. The recording electrodes were filled with (in mM) 145 KCl, 10 NaCl, 1 MgCl 2, 10
HEPES, 2 EGTA, 2 NaATP, and 0.3 NaGTP. To investigate the excitability of CA1 neurons, action
potential frequency and current relationship (f-I) was determined (Sun et al., 2016). Specifically, eleven
9

current steps (0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100 pA; 2 s duration; 10 sec inter-stimulus interval)
were applied to neurons and the action potential frequency for each current step was calculated. The
electrodes were filled with (in mM) 131 K-gluconate, 20 KCl, 8 NaCl, 10 HEPES, 2 EGTA, 2 NaATP
and, 0.3 NaGTP.

Excitation/inhibition (E/I) ratios were determined by measuring excitatory and inhibitory input onto
individual CA1 neurons as described (Qiu et al., 2014). The SCs were stimulated with a series of pulses
to elicit either EPSCs or IPSCs. EPSCs were measured by evoking glutamate receptor mediated current
(derived from both AMPAR and NMDAR) at a holding potential of -40 mV (the reversal potential for
GABA receptor (GABAR) and glycine receptor (GlyR) mediated current). Each neuron received 20-30
stimulations at a 15 s inter-stimulus interval. Neurons were subsequently depolarized to 0 mV in the
presence of 50 μM KA to block GluR-mediated current. The resultant IPSCs were mediated by
monosynaptic inhibition through GABAR and GlyR. Again, each neuron received 20-30 stimulations at
a 15 s inter-stimulus interval. The E/I ratio onto the same neuron was calculated by dividing the peak
excitatory current (AMPAR plus NMDAR) by peak inhibitory (GABAR plus GlyR) current. The
recording electrodes were filled with (in mM) 120 CsMeSO4, 15 CsCl, 10 TEA-Cl, 8 NaCl, 10 HEPES,
2 EGTA, 5 QX-314, 4 MgA TP, 0.3 NaGTP, and 10 phosphocreatine.

Paired pulse ratio was determined by recording either single cell EPSCs or field EPSCs triggered by two
consecutive pulses (stimulus 1 and 2) at varying inter-stimulus-intervals (ISIs) of 25, 50, 75, 100, 200,
300, 500, and 1000 ms. Single-cell EPSCs were measured by evoking SCs at a holding potential of -70
mV, and field EPSCs were measured at 0 mV. PPR was calculated by dividing EPSC slope in response
to stimulus 2 by that to stimulus 1. The recording electrodes for single-cell EPSC recording were filled
with (in mM) 120 CsMeSO4, 15 CsCl, 10 TEA-Cl, 8 NaCl, 10 HEPES, 2 EGTA, 5 QX-314, 4 MgATP,
0.3 NaGTP, and 10 phosphocreatine. The recording electrodes for field EPSC recording (0.5-1.0 MΩ)
were filled with (in mM) 119 NaCl, 2.5 KCl, 1 MgSO4, 2 CaCl 2, 26 NaHCO3, 1.23 NaH2PO4, and 10
glucose. AMPAR-mediated current was measured by evoking SCs at a holding potential of -70 mV in
the presence of 50 µM PTX and 1 µM Stry to occlude inhibitory current. Each neuron received 20-30
stimulations. Then 50 µM DNQX was bath applied to block AMPARs. Once AMPAR current
disappeared, NMDAR current was isolated by depolarizing neurons at +40 mV. Each neuron received
20-30 stimulations. The AMPAR/NMDAR (A/N) current ratio onto a single neuron was calculated by
dividing the peak AMPAR current by peak NMDAR current. The recording electrodes were filled with
(in mM) 120 CsMeSO4, 15 CsCl, 10 TEA-Cl, 8 NaCl, 10 HEPES, 2 EGTA, 5 QX-314, 4 MgATP, 0.3
NaGTP, and 10 phosphocreatine. To determine the contribution of extrasynaptic AMPARs to mEPSCs,
10

we used a long-term potentiation (LTP) protocol to induce lateral diffusion of AMPARs (especially
GluR1) from extrasynaptic to the synaptic sites and recorded mEPSCs before and after LTP induction
(Rouach et al., 2005; Oh et al., 2006). Specifically, neurons were held at -70 mV and baseline mEPSCs
were recorded for 10 min in the presence of 50 µM PTX, 1 µM Stry, and 200 nM TTX. Then, PTX, Stry,
and TTX were washed out with ACSF for 5 min. Afterwards, stimulations of increasing intensities were
applied to Schaffer collaterals (SCs) to trigger evoked EPSCs; the stimulation intensities were determined
as those that induced stable responses. The TBSs consisted of two trains of stimuli delivered 20 s apart.
Each train was composed of 5 stimulus epochs 200 ms apart, with each epoch consisting of 5 pulses of
10-15 µA at 100 Hz. After TBS, PTX, Stry, and TTX were added back to ACSF and post-TBS mEPSCs
were recorded for 10 min after the reapplication of PTX, Stry, and TTX. The last 5 min of the recording
was analyzed. The electrodes (4–7 MΩ) were filled with (in mM) 131 K-gluconate, 20 KCl, 8 NaCl, 10
HEPES, 2 EGTA, 2 NaA TP, and 0.3 NaGTP.

For NR2A and NR2B quantification, NMDAR-mediated current was first measured by stimulating the
SCs at a holding potential of +40 mV in the presence of DNQX. Then 3 µM ifenprodil (IFN) was added
to the bath for 3 min to block NR2B-mediated current. 20 stimulations of SCs at 10 sec inter-stimulus
intervals were applied to measure both NMDAR-mediated and NR2A-mediated current. NR2B current
was calculated by subtracting NR2A from NMDAR current (peak or charge transfer). The NR2A/NR2B
ratio was calculated by dividing the peak NR2A current (or charge transfer) by the peak NR2B current
(or charge transfer). The recording electrodes were filled with (in mM) 120 CsMeSO4, 15 CsCl, 10 TEA-
Cl, 8 NaCl, 10 HEPES, 2 EGTA, 5 QX-314, 4 MgA TP, 0.3 NaGTP, and 10 phosphocreatine. To examine
AMPA-silent synapses, a minimum stimulation protocol was used to activate a small number of axons in
order to estimate the proportion of AMPA-silent synapses (Bateup et al., 2013; Qiu et al., 2014). First,
AMPAR current was measured at -70 mV in the presence of 50 µM PTX and 1 µM Stry. Stimulus
intensities were adjusted to produce successful AMPAR current interleaved with failures, such that the
percentages of successful responses were between 40-60%. Each neuron received 20 stimulations.
Afterwards, neurons were voltage clamped at +40 mV and 20 more compound current were recorded
under the same stimulation intensity as in AMPAR current measurement. The percentages of NMDAR-
only silent synapses were calculated by subtracting the failure rate of AMPAR current from that of the
compound current. The recording electrodes were filled with (in mM) 120 CsMeSO4, 15 CsCl, 10 TEA-
Cl, 8 NaCl, 10 HEPES, 2 EGTA, 5 QX-314, 4 MgA TP, 0.3 NaGTP, and 10 phosphocreatine.

2.3.3. Morphology:
For rapid Golgi staining, P20-22 male mice were transcardially perfused with 4% paraformaldehyde at
11

room temperature. Brains were removed, immersed in Rapid Golgi stain solution A+B (FD Rapid
GolgiStainTM) for 7 days, and transferred to solution C for destaining. Two days after destaining, 200
μm coronal sections were cut with a Leica VT1000 S vibratome, further processed in solutions E and F,
and mounted on positively charged glass slides with Permount (Fisher Scientific). All tissue sections
were kept in dark until imaging. Individual hippocampal CA1 neurons were imaged with a Zeiss LSM-
710 microscope using a 63x objective oil lens (NA=1.4) at a step of 0.2 μm along the Z-axis. Images
were imported into Fiji-ImageJ for visualization and analysis. A total of 4 wildtype and 4 mutant male
mice of P20-22 were subjected to spine quantification in the hippocampus. For both basal and apical
dendritic spine counting in wildtype hippocampal CA1 neurons, 4 mice, 13 neurons, and 39 dendrites,
were analyzed. For both basal and apical dendritic spine counting in mutant hippocampal CA1 neurons,
4 mice, 12 neurons, and 36 dendrites were analyzed. The analyzed apical dendrites of CA1 neurons were
the secondary apical dendrites and their branching points were located within 50-150 μm from the soma.
A spine was defined as a protrusion that was connected to and 0.4 μm above the dendritic surface adapted
from Holtmaat (Holtmaat et al., 2009). The averaged spine densities from multiple dendrites of the same
neuron were used in data presentation and statistical analysis (each neuron was an independent data point).

Sholl analysis is a method of quantitative analysis commonly used in neuronal studies to characterize the
morphological features and measure arbor complexity, likes dendrite or axon, of an imaged neuron by
counting the number of intersections per concentric shell with the same interval from the soma of target
neurons to the end of longest dendrites (Chowdhury et al., 2014; O'Neill et al., 2015). The CA1 neurons
from wildtype and mutant mice were backfilled with Alexa-Fluor 594 fluorescent dye first and then were
imaged by a Zeiss LSM-710 microscope using a 63x objective oil lens (NA=1.4) with 0.6x zoom out at
a step of 1 μm along the Z-axis. For the analytic part, concentric shells with 20-µm interval from
individual soma to the end of longest dendrite were drawn and the number of intersections between each
shell and basal or apical dendrites were counted for individual wildtype (n = 24 from 6 mice) and mutant
(n = 24 from 6 mice) CA1 neuron.

2.3.4. Statistical analysis:
Statistical analyses were performed using GraphPad software (version 6; La Jolla, California). Two-tailed
unpaired Student’s t-test was used for data analysis between WT and Mutant mice. All data are presented
as the average ± SEM (standard error of mean) values.

2.4. Results
2.4.1. Altered intrinsic membrane properties and current-voltage relationship in mutant CA1
neurons
We first investigated the intrinsic membrane properties of CA1 neurons. Mutant CA1 neurons showed a
12

mild elevation in RMP (Fig. 2.1A) (WT: -66.59±0.30 mV, 15 neurons from 5 mice; Mut: -64.80±0.22
mV, 15 neurons from 5 mice, ****P<0.0001). However, membrane resistance (Fig. 2.1B) (WT:
381.59±25.90 MOhm, 15 neurons from 5 mice; Mut: 376.24±26.36 MOhm, 15 neurons from 5 mice,
P>0.05), series resistance (Fig. 2.1C) (WT: 92.95±15.22 MOhm, 15 neurons from 5 mice; Mut:
75.36±14.24 MOhm, 15 neurons from 5 mice, P>0.05), and membrane capacitance (Fig. 2.1D) (WT:
43.42±4.27 pF, 15 neurons from 5 mice; Mut: 49.80±4.48 pF, 15 neurons from 5 mice, P>0.05) did not
differ significantly between wildtype and mutant CA1 neurons. These results indicated that the intrinsic
membrane properties were largely unaffected in mutant CA1 neurons.

Next, we applied a step-protocol to determine neuronal current-voltage (I-V) relationship (Fig. 2.1F-H).
We quantified both the peak current representing the responses of voltage-gated ion channels and
ionotropic receptors with fast kinetics, and the steady state current representing ligand-gated channels
and metabotropic receptors with slow kinetics (Fig. 2.1F). Mutant CA1 neurons showed slightly
increased peak current at each voltage step (Fig. 2.1G) (-100-+100 mV, *P<0.05), suggesting the
presence of small changes in the quantities and/or types of fast-responding ion channels and/or receptors.
In contrast, the steady state current was indistinguishable between wildtype and mutant CA1 neurons
(Fig. 2.1H) (-100-+100 mV, P>0.05), suggesting that the slow-response ligand-gated channels and
metabotropic receptors were unaltered in mutant CA1 neurons.

Taken together, the above studies revealed a small rise in RMP and mildly increased peak current of the
I-V curve in mutant CA1 neurons. Although these changes were small in magnitude, they could
contribute to the increased excitability of the mutant CA1 neurons.

2.4.2. Altered synaptic transmission and spontaneous neuronal firing in mutant CA1 neurons
Next, we investigated the excitatory and inhibitory synaptic transmission by recording EPSCs and IPSCs,
respectively. Mutant CA1 neurons exhibited significantly increased sEPSC frequency (WT: 1.18±0.13
Hz, 24 neurons from 6 mice; Mut: 1.90±0.23 Hz, 22 neurons from 6 mice, **P<0.01) and mildly
increased mEPSC frequency (Fig. 2.2A, B) (WT: 0.63±0.06 Hz, 24 neurons from 6 mice; Mut: 0.98±0.14
Hz, 22 neurons from 6 mice, *P<0.05) without any changes in sEPSC amplitude (WT: 34.03±1.35 pA,
24 neurons from 6 mice; Mut: 34.91±1.75 pA, 22 neurons from 6 mice, P>0.05) or mEPSC amplitude
(Fig. 2.2A, C) (WT: 30.36±0.81 pA, 24 neurons from 6 mice; Mut: 31.16±1.24 pA, 22 neurons from 6
mice, P>0.05), indicating elevated excitatory synaptic transmission. In contrast, no difference was
observed in the frequency of sIPSCs or mIPSCs between wildtype and mutant CA1 neurons (Fig. 2.2D,
E) (sIPSC frequency: WT: 3.92±0.10 Hz, 27 neurons from 7 mice; Mut: 3.90±0.09 Hz, 19 neurons from
13

5 mice, P>0.05; mIPSC frequency: WT: 2.67±0.07 Hz, 27 neurons from 7 mice; Mut: 2.60±0.09 Hz, 19
neurons from 5 mice, P>0.05). There was a mild increase in sIPSC amplitude (Fig. 2.2D, F) (WT:
65.60±1.79 pA, 27 neurons from 7 mice; Mut: 72.01±1.78 pA, 19 neurons from 5 mice, *P<0.05),
whereas mIPSC amplitude was unchanged in mutant CA1 neurons (Fig. 2.2D, F) (WT: 45.35±1.05 pA,
27 neurons from 7 mice; Mut: 46.97±0.95 pA, 19 neurons from 5 mice, P>0.05).

We further determined excitability of CA1 neurons by studying the relationship between firing frequency
and injected current. The firing-current injection (f-I) curve demonstrated the frequencies of action
potentials (Fig. 2.2G, H) were significantly increased in mutant CA1 neurons at all current steps (0-100
pA) (the values for three representative current steps shown in Fig. 2G: WT: 10 pA, 0.64±0.23 Hz, 15
neurons from 5 mice; Mut: 1.67±0.28 Hz, 15 neurons from 5 mice, **P<0.01; 50 pA: WT: 7.19±0.28 Hz,
15 neurons from 5 mice; Mut: 8.41±0.32 Hz, 15 neurons from 5 mice, **P<0.01; 100 pA: WT:
12.63±0.28 Hz, 15 neurons from 5 mice; Mut: 13.83±0.32 Hz, 15 neurons from 5 mice, **P<0.01),
indicating increased excitability of the mutant CA1 neurons.

Taken together, the observations of significant elevation in EPSC frequency and increased action
potential frequencies in the presence of mild changes in IPSCs indicated overall increased activities at
the excitatory synapses in mutant CA1 neurons. They also suggested an imbalance of excitation and
inhibition. This prompted us to investigate whether E/I ratios were altered in mutant CA1 neurons.

2.4.3. Altered balance of excitation and inhibition in mutant CA1 neurons
To determine E/I ratio, we measured excitation and inhibition onto the same CA1 neurons using a
minimum stimulation intensity protocol (Bateup et al., 2013; Qiu et al., 2014). Stimulation of the SCs
evoked EPSCs and IPSCs at holding potentials of -40 mV and 0 mV , respectively (Fig. 2.3A). There was
a significant increase in evoked EPSCs (WT: -269.41±13.92 pA, 17 neurons from 5 mice; Mut: -
338.42±19.70 pA, 17 neurons from 5 mice, **P<0.01) and no change in evoked IPSCs (WT:
354.30±17.19 pA, 17 neurons from 5 mice; Mut: 358.60±12.34 pA, 17 neurons from 5 mice, P>0.05)
(Fig. 2.3B, C) in mutant CA1 neurons. In addition, E/I ratios, determined by dividing EPSCs by IPSCs
from the same CA1 neurons, were significantly elevated in mutant CA1 neurons (WT: 77.15±3.42%, 17
neurons from 5 mice; Mut: 93.92±4.24%, 17 neurons from 5 mice, **P<0.01) (Fig. 2.3D). These results
demonstrated significantly increased activities at the excitatory synapses, resulting in an imbalance
between excitation and inhibition in hippocampal CA1 neurons of chr7qF3 mice.

2.4.4. Altered presynaptic neurotransmission and AMPAR-mediated current in mutant CA1
14

neurons
The elevated excitation and E/I ratios in mutant CA1 neurons could come from two sources. First,
presynaptic transmission could be increased. Second, AMPAR- and/or NMDAR-mediated response
could be altered.

We first evaluated presynaptic transmission by measuring paired pulse ratios at the Schaffer collateral-
CA1 synapses using both single-cell patch clamp and field recording (Fig. 2.4A-D). In single-cell
recording, mutant CA1 neurons showed reduced paired pulse ratios at all interstimulus intervals (ISI of
25 ms, WT: 119.35±8.41%, 15 neurons from 5 mice; Mut: 86.93±3.01%, 15 neurons from 5 mice,
**P<0.01. ISI of 50 ms, WT: 128.93±9.18%, 15 neurons from 5 mice; Mut: 98.63±4.16%, 15 neurons
from 5 mice, **P<0.01. ISI of 75 ms, WT: 130.56±10.88%, 15 neurons from 5 mice; Mut: 100.11±2.49%,
15 neurons from 5 mice, *P<0.05) (Fig. 2.4A, B). Similar results were seen in field recording (ISI of 25
ms, WT: 184.50±5.82%, 16 neurons from 5 mice; Mut: 160.90±5.93%, 12 neurons from 4 mice,
**P<0.01. ISI of 50 ms, WT: 197.39±5.57%, 16 neurons from 5 mice; Mut: 172.79±6.00%, 12 neurons
from 4 mice, **P<0.01. ISI of 75 ms, WT: 187.07±5.11%, 16 neurons from 5 mice; Mut: 169.09±5.39%,
12 neurons from 4 mice, *P<0.05) (Fig. 2.4C, D). These results indicated that presynaptic
neurotransmitter release was increased at the Schaffer collateral-CA1 synapses.

We then measured AMPAR- and NMDAR-mediated currents at holding potentials of -70 mV and +40
mV in the presence AMPAR inhibitors at +40 mV, respectively (Fig. 2.4E). Mutant CA1 neurons
exhibited increased AMPAR-mediated current (Fig. 2.4F) (WT: -340.96±19.61 pA, 15 neurons from 5
mice; Mut: -451.13±26.66 pA, 15 neurons from 5 mice, **P<0.01) and no change in NMDAR-mediated
current (Fig. 2.4G) (WT: 491.74±30.51 pA, 15 neurons from 5 mice; Mut: 486.33±24.97 pA, 15 neurons
from 5 mice, P>0.05). In addition, the ratios of AMPAR-mediated and NMDA-mediated current were
significantly increased in mutant CA1 neurons (Fig. 2.4H) (WT: 70.23±2.59%, 15 neurons from 5 mice;
Mut: 93.24±3.47%, 15 neurons from 5 mice, ****P<0.0001). These results demonstrated that AMPAR-
mediated response was increased, whereas NMDAR-mediated response was unchanged, at the Schaffer
collateral-CA1 synapses from chr7qF3 mice.

The increase in evoked AMPAR-mediated response could result from an increase in presynaptic
neurotransmitter release, upregulated surface expression of AMPAR at the synaptic site, and/or an
elevated level of dendritic AMPAR at the extrasynaptic site (which can be activated under evoked
condition). The reductions in paired pulse ratios in mutant CA1 neurons (Fig. 2.4A-D) supported a
presynaptic mechanism. The unaltered mEPSC amplitude in mutant CA1 neurons (Fig. 2.2C) suggested
15

that the surface expression of AMPAR at the synaptic sites was unchanged.

To determine if mutant CA1 neurons contained a higher level of extrasynaptic AMPAR than the wildtype,
we applied theta burst stimulation (TBS) to induce lateral diffusion and measured mEPSCs before and
after TBS (Fig. 2.5A). The rationale is that the degree of lateral diffusion is proportional to the size of
the extrasynaptic AMPAR pool along the dendrites (Rouach et al., 2005; Oh et al., 2006; Makino and
Malinow, 2009). The amplitude of lateral diffusion can be calculated as the change in mEPSCs before
and after TBS (∆mEPSC
post-pre
). As shown in Fig. 2.5C, the pre-TBS mEPSC amplitudes were similar
between wildtype and mutant CA1 neurons (WT: 28.13±0.63 pA, 21 neurons from 7 mice; Mut:
29.69±0.46 pA, 21 neurons from 7 mice, P>0.05), consistent with the results described in Fig. 2.2.
Application of TBS resulted in a significant difference in mEPSC amplitude between the two genotypes
(Fig. 2.5C) (WT: 31.17±0.51 pA, 21 neurons from 7 mice; Mut: 34.82±0.72 pA, 21 neurons from 7 mice,
***P<0.001). More importantly, ∆mEPSC
post-pre
for mutant neurons were significantly higher than that
for the wildtype (Fig. 2.5D) (WT: 3.04±0.37 pA, 21 neurons from 7 mice; Mut: 5.45±0.60 pA, 21 neurons
from 7 mice, **P<0.01), indicating that more AMPARs were available at the postsynaptic site as the
result of TBS. In addition, mutant CA1 neurons showed higher mEPSC frequencies both before and after
TBS (Fig. 2.5E) (Pre-TBS, WT: 0.65±0.04 Hz, 21 neurons from 7 mice; Mut: 0.93±0.05 Hz, 21 neurons
from 7 mice, ***P<0.001; Post-TBS, WT: 0.87±0.04 Hz, 21 neurons from 7 mice; Mut: 1.19±0.08 Hz,
21 neurons from 7 mice, **P<0.01), indicating a higher rate of neurotransmitter release in the mutant
Schaffer collateral-CA1 synapses. To make sure the differential effect of TBS on the amplitudes of
∆mEPSC
post-pre
was not due to differences in stimulation intensity applied to wildtype and mutant neurons
during TBS, we recorded the stimulation intensities and found no difference (Table 2.1).

The results described in Fig. 2.5 were consistent with the hypothesis that mutant CA1 neurons contained
a higher level of dendritic AMPAR at the extrasynaptic site (Fig. 2.5F), and this, along with an increase
in presynaptic neurotransmitter release (Fig. 2.4A-D), contributed to the elevation of evoked AMPAR-
mediated responses in mutant CA1 neurons.

2.4.5. Altered spine density and number of dendritic branches in mutant CA1 neurons
Conversely, the potential alterations of morphological structures, such as dendritic spine density, spine
distribution, and dendritic branches may affect the electrophysiological properties of individual neurons
and connectivity. To determine if imbalance of excitation and inhibition onto mutant CA1 neurons
resulted from any changes at fine structural level, we quantified and compared the spine densities and
distribution in hippocampal CA1 neurons between wildtype and mutant mice. Fig. 2.6A showed the
16

representative images illustrating Golgi-stained dendrites and spines of CA1 neurons from wildtype and
mutant mice. We found that CA1 neurons from mutant mice had reduced spine density at both the basal
and secondary apical dendrites (Fig. 2.6B) (Basal, WT: 1.48±0.03 #/µm, 13 neurons from 4 mice; Mut:
1.23±0.02 #/µm, 12 neurons from 4 mice, ****P<0.0001; 2
nd
-Apical, WT: 1.85±0.02 #/µm, 13 neurons
from 4 mice; Mut: 1.57±0.04 #/µm, 12 neurons from 4 mice, ****P<0.0001). To determine if changes
in spine density vary along the dendrite, we quantified spine densities in 10 µm-segment increments
starting from the neuronal soma (for basal dendrites) or from the branching point (for secondary apical
dendrites). Segmental analyses in Fig. 2.6C, D showed that the differences in spine densities were
presented along almost the entire length of both the basal (10-110 µm, *P<0.05) and secondary apical
(10-80 µm, *P<0.05) dendrites from wildtype and mutant CA1 neurons, indicating a significant impact
of chr16p11.2 microdeletion on dendritic spine development.

Furthermore, in order to determine if changes in the number of dendritic branches, complexity , and length
vary along the dendrite, we also performed “Sholl analysis” in both wildtype and mutant CA1 neurons.
Fig. 2.6E showed the representative images illustrated from wildtype and mutant CA1 neurons backfilled
with Alexa-Fluor 594 fluorescent dye and the concentric shells with 20-µm intervals from individual
soma. As you can see in Fig. 2.6F-H, the significant differences in the number of intersections were
presented around the median length range of the total (80-280 µm, *P<0.05), basal (100-220 µm,
*P<0.05), and apical (80-280 µm, *P<0.05) dendrites from wildtype and mutant CA1 neurons,
suggesting the alteration of dendritic branches and complexity may relate to the postynaptic effect for
increased E/I ratio. The decreased spine density and increased dendritic branches in mutant CA1 neurons
also implies the possibility of earlier maturation (Romand et al., 2011; Johnson-Venkatesh et al., 2015;
Ramaswamy and Markram, 2015).

2.4.6. Altered development and maturation of the Schaffer collateral-CA1 synapses
Development and maturation of the Schaffer collateral-CA1 synapses is characterized by increases in
AMPAR expression (hence increased A/N ratio), switching of NMDAR subunit from NR2B to NR2A
(hence increased NR2A/NR2B current ratio), and reduction in AMPAR-silent synapses (Sans et al., 2000;
Tsien, 2000; Rauner and Kohr, 2011; Clement et al., 2012; Hanse et al., 2013; Qiu et al., 2014; Shipton
and Paulsen, 2014). Increased A/N ratios in mutant CA1 neurons (Fig. 2.4) suggest that maturation of
the Schaffer collateral-CA1 synapses might be altered. To test this hypothesis, we measured NR2A,
NR2B, and NR2A/NR2B ratios, and quantified AMPAR-silent synapses in wildtype and mutant CA1
neurons.

17

To measure NR2A and NR2B current, we first determined NMDAR-mediated current as aforementioned
(Fig. 2.4) and calculated both peak current and charge transfer (Fig. 2.7A, B). No differences were
observed in either parameter between wildtype and mutant CA1 neurons (peak current: WT:
420.85±23.63 pA, 24 neurons from 8 mice; Mut: 375.42±15.48 pA, 24 neurons from 8 mice, P>0.05;
charge transfer: WT: 34.08±1.64 pC, 24 neurons from 8 mice; Mut: 29.30±1.89 pC, 24 neurons from 8
mice, P>0.05) (Fig. 2.7C, D), consistent with data presented in Fig. 2.4. NR2A current, isolated by the
application of NR2B receptor blocker, IFN, did not demonstrate differences in peak current or charge
transfer between two genotypes (peak current: WT: 223.41±10.32 pA, 24 neurons from 8 mice; Mut:
229.87±8.70 pA, 24 neurons from 8 mice, P>0.05; charge transfer: WT: 19.53±0.81 pC, 24 neurons from
8 mice; Mut: 19.41±1.28 pC, 24 neurons from 8 mice, P>0.05) (Fig. 2.7B-D). However, NR2B currents,
calculated by both peak current and charge transfer, were significantly reduced in mutant CA1 neurons
(peak current: WT: 197.44±14.88 pA, 24 neurons from 8 mice; Mut: 145.55±10.03 pA, 24 neurons from
8 mice, **P<0.01; charge transfer: WT: 14.55±1.21 pC, 24 neurons from 8 mice; Mut: 9.89±0.92 pC, 24
neurons from 8 mice, **P<0.01) (Fig. 2.7B-D).

Furthermore, the percentages of NR2A and NR2B currents, measured by both peak current and charge
transfer, were significantly changed in mutant CA1 neurons (NR2A peak current: WT: 53.91±1.32%, 24
neurons from 8 mice; Mut: 61.73±1.42%, 24 neurons from 8 mice, ***P<0.001; NR2A charge transfer:
WT: 58.26±1.95%, 24 neurons from 8 mice; Mut: 66.67±1.76%, 24 neurons from 8 mice, **P<0.01;
NR2B peak current: WT: 46.09±1.32%, 24 neurons from 8 mice; Mut: 38.27±1.42%, 24 neurons from 8
mice, ***P<0.001; NR2B charge transfer: WT: 41.74±1.95%, 24 neurons from 8 mice; Mut:
33.33±1.76%, 24 neurons from 8 mice, **P<0.01) (Fig. 2.7E, F). In addition, NR2A to NR2B ratios
were increased in mutant CA1 neurons (peak current: WT: 121.85±7.54%, 24 neurons from 8 mice; Mut:
170.40±11.04%, 24 neurons from 8 mice, ***P<0.001; charge transfer: WT: 156.92±17.04%, 24 neurons
from 8 mice; Mut: 216.25±13.98%, 24 neurons from 8 mice, **P<0.01) (Fig. 2.7G). These results
indicated that although the total NMDAR-mediated current was unchanged, the contribution by NR2A
increased and NR2B decreased in mutant CA1 neurons. These findings were consistent with the idea that
NR2B to NR2A switch occurred earlier in the mutant Schaffer collateral-CA1 synapses.

AMPAR-silent synapses are characterized by the presence of NMDAR and absence of surface AMPAR
(Liao et al., 1995; Isaac et al., 1997; Tsien, 2000; Kerchner and Nicoll, 2008; Clement et al., 2012; Hanse
et al., 2013). Under patch clamp conditions, these synapses respond to stimulations at a holding potential
of +40 mV but not at -70 mV. Using a modified stimulation protocol as described (Bateup et al., 2013;
Qiu et al., 2014), we determined the percentages of silent synapses in both wildtype and mutant CA1
18

neurons (Fig. 2.8A) at two developmental time points, P13-15 and P20-22. Wildtype and mutant CA1
neurons from P13-15 mice showed no differences in failure rates at -70 mV (WT: 52.33±1.37%, 15
neurons from 5 mice; Mut: 49.17±1.16%, 18 neurons from 6 mice, P>0.05) or +40 mV (WT:
37.33±1.45%, 15 neurons from 5 mice; Mut: 38.06±0.92%, 18 neurons from 6 mice, P>0.05) (Fig. 2.8B-
D). However, mutant CA1 neurons demonstrated a significantly smaller change in failure rates than the
wildtype neurons between these two holding potentials (Fig. 2.8H) (WT: WT: 15.00±1.09 %, 15 neurons
from 5 mice; Mut: 11.11±0.76%, 18 neurons from 6 mice, **P<0.01), suggesting that the percentage of
AMPAR-silent synapses was lower in mutant CA1 neurons than in the wildtype neurons.

Similarly, wildtype and mutant CA1 neurons from P20-22 mice showed comparable failure rates at -70
mV (WT: 51.33±1.03%, 15 neurons from 5 mice; Mut: 48.75±1.09%, 12 neurons from 4 mice, P>0.05)
and +40 mV (WT: 41.00±0.87%, 15 neurons from 5 mice; Mut: 39.58±0.96%, 12 neurons from 4 mice,
P>0.05) (Fig. 2.8E-G). In contrast to P13-15, the differences in failure rates were statistically
indistinguishable between wildtype and mutant neurons (WT: 10.33±0.91%, 15 neurons from 5 mice;
Mut: 9.17±1.04%, 12 neurons from 4 mice P>0.05) (Fig. 2.8H), suggesting that the percentage of
AMPAR-silent synapses was similar in wildtype and mutant CA1 neurons at P20-22. It is worth
mentioning that the stimulation intensities used to achieve 40-60% successful responses were
significantly smaller for mutant CA1 neurons than for the wildtype (Table 2.1; WT: 10.21±0.27 µA; Mut:
9.02±0.33 uA, **P<0.01). This observation was consistent with the aforementioned results that
demonstrated increased presynaptic neurotransmitter release and elevated excitability of Schaffer
collateral-CA1 synapses (Fig. 2.2, 2.3, 2.4).

Interestingly, wildtype, but not mutant, CA1 neurons demonstrated a reduction in failure rate between
P13-15 and P20-22 (WT, P13-15: 15.00±1.09%, 15 neurons from 5 mice; WT, P20-22: 10.33±0.91%, 15
neurons from 5 mice, **P<0.01. Mut, P13-15: 11.11±0.76%, 18 neurons from 6 mice; Mut, P20-22:
9.17±1.04%, 12 neurons from 4 mice, P>0.05). This result suggested that while synapses onto wildtype
CA1 neurons underwent maturation between P13-15 and P20-22 with reduction of AMPAR-silent
synapses, those onto mutant CA1 neurons had already reached the developmental stage of P20-22 at the
age of P13-15 with regard to the status of AMPAR-silent synapses.

Taken together, the increased A/N ratio, relatively higher percentage of NR2A subunit current, and
reduced percentage of AMPAR-silent synapses at the mutant Schaffer collateral-CA1 synapses strongly
suggested that the developmental trajectory of these synapses was altered in mutant mice.

19

2.5. Discussion
Chromosome copy number variations are frequently associated with neurodevelopmental disorders
(Levy et al., 2011; Malhotra and Sebat, 2012; Girirajan et al., 2013; Pinto et al., 2014). The involved
chromosomal regions usually contain multiple genes with diverse functions. Characterization of mouse
models carrying syntenic deletions is a crucial step towards understanding the disease mechanism.

In this study, we investigated the synaptic physiology of developing hippocampal neurons in a mouse
model of human chr16p11.2 microdeletion (Horev et al., 2011). Using acute slice preparations, we
determined intrinsic membrane properties, basal synaptic transmission, and functions of two
predominant types of glutamatergic receptors, AMPAR and NMDAR. The results revealed three major
abnormalities in CA1 neurons from chr7qF3 mice.

2.5.1. Mutant CA1 neurons show increased excitatory activities
Several observations from our study support this conclusion: (1) the frequencies of both sEPSCs and
mEPSCs are elevated compared with wildtype neurons; (2) the action potential frequencies, determined
by the f-I curve, are increased at all injected current steps; and (3) AMPAR-mediated current is
augmented under stimulated condition. These changes in excitability most likely result from both
presynaptic and postsynaptic mechanisms. While increased mEPSC frequency and reduced paired pulse
ratios in mutant CA1 neurons support a presynaptic contribution, increased AMPAR-mediated current is
consistent with a postsynaptic mechanism. Because CA3 is one of the major afferents onto CA1, it is
plausible to speculate that increased excitatory activity may also be present in CA3 neurons, thus
contributing to the observed abnormalities in sEPSCs, mEPSCs, and paired pulse ratio in mutant CA1
neurons. Increased EPSCs and E/I ratio has been described in the striatum of an independent mouse
model of human 16p11.2 microdeletion by Portmann (Portmann et al., 2014). Similarly, our unpublished
study on the principal neurons of the basolateral amygdala nucleus also revealed increased excitatory
tone (Lu and Tian, unpublished observation). Together, these electrophysiological studies strongly
suggest that chr16p11.2 microdeletion results in increased excitation in several brain regions critical for
learning, memory and social behavior.

2.5.2. Mutant CA1 neurons exhibit perturbed E/I balance
The supporting evidence is: (1) under the basal condition, sEPSC and mEPSC frequencies in mutant CA1
neurons are significantly increased whereas sIPSC and mIPSC frequencies are unaffected; and (2) under
a stimulation condition, the evoked EPSC amplitude is increased, whereas the evoked IPSC amplitude is
unaltered. Perturbation of E/I balance is hypothesized as a synaptic mechanism for autism, and has been
20

supported by multiple studies (Rubenstein and Merzenich, 2003; Dani et al., 2005; Rippon et al., 2007;
Bateup et al., 2013; Rothwell et al., 2014). Recently, Mullins et al. expanded this hypothesis and proposed
that dysfunctional autoregulation is a general mechanism of ASD (Mullins et al., 2016). The authors
conceptualized autoregulation at various levels, including biochemical, structural, synaptic, and
transcriptional. Importantly, they redefined the concept of E/I balance as E/I coordination to reflect
unknown circuitry that contributes to the temporal complexity of excitation and inhibition. Although the
mechanism has yet to be determined, the perturbed E/I relationship seen in the hippocampal CA1 neurons
from chr7qF3 mice support the hypotheses by Rubenstein and Merzenith (Rubenstein and Merzenich,
2003) and Mullins (Mullins et al., 2016).

2.5.3. Mutant mice show accelerated maturation at the Schaffer collateral-CA1 synapses
Specifically, mutant CA1 neurons demonstrate: (1) increased A/N current ratio; (2) decreased spine
density and increased dendritic branches; (3) higher NR2A/NR2B subunit current ratio; and (4) a reduced
percentage of AMPAR-silent synapses. These results indicate that genes within the deleted region play
critical roles in the maturation of glutamatergic synapses in the hippocampus. It has been shown that a
gradual increase in AMPRA/NMDAR current ratio, spine density reduction and dendritic branch
elevation, NR2B to NR2A switching, and reduction of AMPAR-silent synapses, are the molecular events
that are critical milestones for developing hippocampal glutamatergic synapses (Clement et al., 2012;
Clement et al., 2013; Qiu et al., 2014; Johnson-Venkatesh et al., 2015). Disruption in the timing of these
key processes, as exemplified by SynGap1 and Met mutant mice, can have profound long-term
consequences on cognition and behavior (Clement et al., 2012; Muhia et al., 2012; Clement et al., 2013;
Qiu et al., 2014; Thompson and Levitt, 2015). Indeed, adult chr7qF3 mice exhibit deficits in
hippocampus-associated learning in contextual fear-conditioning and inhibitory avoidance test (Tian et
al., 2015), further supporting the hypothesis that alteration in the kinetics of hippocampal synaptic
development is a shared pathogenic mechanism among a subset of genetic abnormalities associated with
neurodevelopment and neuropsychiatric disorders.

Interestingly, a previous study using the same mouse model demonstrated normal presynaptic
neurotransmitter release and postsynaptic glutamatergic response at the Schaffer collateral-CA1 synapses
from P28-P35 mice (Tian et al., 2015). In contrast, the current study investigated synaptic functions and
revealed both presynaptic and postsynaptic changes in younger mice (P20-22). It has been reported that
genetic defects can impact synaptic functions within certain developmental windows, particularly during
the early stage of synapse formation and establishment (Bozdagi et al., 2012; Clement et al., 2012; Hsiao
et al., 2016). The findings from our studies of chr16p11.2 microdeletion at different ages in mice are
21

likewise in keeping with these examples, and highlight the importance of studying and understanding the
effect of mutations in a developmental context.

2.5.4. Investigate synaptic abnormalities in other brain regions and from acute microdeletion mice
A limitation of the current study is that we have only investigated the synaptic functions in a particular
neuronal population. Whether similar abnormalities are present in other synapses in different brain
regions needs further investigation. Another limitation is that this study does not aim to distinguish the
primary effect of the microdeletion on the synaptic function from the abnormal compensatory responses
to the initial alterations. Investigation of mice carrying a temporally and spatially modifiable
microdeletion will help to differentiate these two scenarios, thus deepening our understanding of the
temporal regulation of developmental processes and neural circuit origins of synaptic abnormalities
associated with chr16p11.2 microdeletion. In addition, the result in mice would have to be validated in
humans to establish the contributions of the microdeletion to specific pathophysiology.

In summary, this study has uncovered multiple synaptic abnormalities affecting basal neurotransmission,
local network activity, and synaptic development in a mouse model of the human chr16p11.2
microdeletion. The results indicate that genes within chr16p11.2 play important roles in regulating
synaptic development and function in the hippocampus. In addition, the abnormalities seen in chr7qF3
mice are in keeping with those found in several mouse models of syndromic and non-syndromic forms
of ASD and ID (Sudhof, 2008; Bhakar et al., 2012; Santoro et al., 2012; Ebrahimi-Fakhari and Sahin,
2015). In this context, our studies suggest that synaptic dysfunction is potentially one of the shared
mechanisms between ASD and ID associated with chromosome copy number variation and single gene
mutations.

22

2.6. Figures, tables, and legends
Table 2.1. Stimulation intensities used in the experiments where stimuli were applied to the Schaffer
collaterals.
Experiment Figure
WT (µA) Mut (µA)
P Value
Average SEM Average SEM
E/I ratio 3 11.56 0.469438 11.47 0.416724 0.889095
PPR (single cell) 4 13.10 0.289499 12.97 0.350057 0.77129
PPR (field) 4 31.13 1.193297 29.58 1.117752 0.368854
A/N ratio 4 13.17 0.35746 13.27 0.337592 0.840304
TBS-mEPSC 5 12.91 0.285614 12.96 0.297639 0.718755
NR2A/NR2B ratio 7 12.46 0.209884 12.64 0.205267 0.54467
Silent Synapse (P13-15) 8 9.55 0.381584 9.31 0.314558 0.624436
Silent Synapse (P20-22) 8 10.21 0.270954 9.02 0.326096 0.008701**

WT, wild type; Mut, mutant; E/I, excitatory/inhibitory; PPR, paired pulse ratio; A/N, AMPA/NMDA; TBS, theta-
burst stimulation; mEPSC, miniature excitatory postsynaptic current; P, postnatal day; SEM, standard error of
mean. **P<0.01.

23

Figure 2.1. Altered intrinsic membrane properties and current-voltage relationship.
(A) Resting membrane potential was mildly increased in mutant CA1 neurons (n = WT: 15 neurons from 5 mice;
Mut: 15 neurons from 5 mice). (B-D) Membrane resistance, series resistance, and membrane capacitance was
indistinguishable between wildtype and mutant CA1 neurons (n = WT: 15 neurons from 5 mice; Mut: 15 neurons
from 5 mice). (E) Representative image of a recorded CA1 neuron (backfilled with Alexa-Fluor 594). (F)
Representative traces of I-V curve in wildtype and mutant CA1 neurons. Both peak (denoted by arrows) and steady
state responses (the last 100 ms denoted by horizontal bars) were subjected to analysis. (G) Mild increase in peak
current response in mutant CA1 neurons (n = WT: 22 neurons from 7 mice; Mut: 18 neurons from 6 mice). (H)
Steady state responses were indistinguishable between wildtype and mutant CA1 neurons (n = WT: 22 neurons
from 7 mice; Mut: 18 neurons from 6 mice). In all figures described in this study, data were presented as Mean ±
SEM. Numbers in parentheses represent those of neurons (1st number) and mice (2nd number). Statistical
significance is determined by two-tailed, unpaired Student’s t-test for all panels. *P<0.05, **P<0.01, ***P<0.001,
****P<0.0001.

600
400
800
200
0
Rm (MOhm)
Membrane resistance
ns
WT (15/5)
Mut (15/5)
200
300
100
0
Rs (MOhm)
Series resistance
ns
WT (15/5)
Mut (15/5)
100
150
50
0
Cm (pF)
Membrane capacitance
ns
WT (15/5)
Mut (15/5)
5.0
2.5
7.5
-2.5
Current (nA)
IV curve (peak current)
*
WT (22/7)
Mut (18/6)
Voltage (mV)
0 50 100
* * * * * * * * *
-5.0
-50 -100
3.0
1.5
4.5
Current (nA)
IV curve (steady state)
WT (22/7)
Mut (18/6)
Voltage (mV)
0 50 100
-1.5
-50 -100
0
-1.5
-3.0
0.2 0.3 0.4
-4.5
0.5 0.1
Amplitude (nA)
sec
IV curve (WT)
0.6
6
4.5
3.0
1.5
0
-1.5
-3.0
0.2 0.3 0.4
-4.5
0.5 0.1
Amplitude (nA)
sec
IV curve (Mut)
0.6
6
4.5
3.0
1.5
(B) (C) (D) (E)
(F) (G) (H)
-20
-40
0
-60
-80
RMP (mV)
Resting membrane potential
****
WT (15/5)
Mut (15/5)
(A)
24

Figure 2.2. Significant increases in excitatory synaptic activities in mutant CA1 neurons.
(A) Representative traces of sEPSCs and mEPSCs in wildtype and mutant mice. (B) Both sEPSC and mEPSC
frequencies were increased in mutant mice (n = WT: 24 neurons from 6 mice; Mut: 22 neurons from 6 mice). (C)
sEPSC and mEPSC amplitudes were not changed in mutant mice (n = WT: 24 neurons from 6 mice; Mut: 22
neurons from 6 mice). (D) Representative traces of sIPSCs and mIPSCs in wildtype and mutant mice. (E) sIPSC
and mIPSC frequencies were indistinguishable between wildtype and mutant mice (n = WT: 27 neurons from 7
mice; Mut: 19 neurons from 5 mice). (F) sIPSC amplitude was mildly increased in mutant CA1 neurons, while
mIPSC amplitude was not changed (n = WT: 27 neurons from 7 mice; Mut: 19 neurons from 5 mice). (G)
Representative traces of action potential from wildtype and mutant CA1 neurons injected with 10, 50, 100 pA
currents. (H) Action potential frequencies were significantly increased in mutant CA1 neurons at all current steps
(n = WT: 15 neurons from 5 mice; Mut: 15 neurons from 5 mice).
(B) (C) (A)
(E)
EPSC frequency
EPSC frequency (Hz)
0
2
4
6
sEPSC mEPSC
**
1
3
5
*
sEPSC
mEPSC
WT Mut
sIPSC
mIPSC
WT Mut
30pA
50ms
WT (24/6)
Mut (22/6)
EPSC amplitude
EPSC amplitude (pA)
0
20
40
60
sEPSC mEPSC
ns
10
30
50
ns
WT (24/6)
Mut (22/6)
70
IPSC frequency
IPSC frequency (Hz)
sIPSC mIPSC
ns ns
WT (27/7)
Mut (19/5)
0
2
4
6
1
3
5
IPSC amplitude
IPSC amplitude (pA)
sIPSC mIPSC
ns
WT (27/7)
Mut (19/5)
0
40
80
120
20
60
100
(F) (D)
30pA
500ms
30pA
50ms
30pA
500ms
*
(G)
10
5
15
0
Firing frequency (Hz )
Action potential frequency
*
WT (15/5)
Mut (15/5)
Injected current (uA)
0 50 100
*
*
*
* *
*
*
(H)
*
*
*
*
*
*
*
*
*
*
*
*
WT
Mut
20mV
200ms
10 pA 50 pA 100 pA
10 pA 50 pA 100 pA
25

Figure 2.3. Imbalance of excitation and inhibition in mutant CA1 neurons.
(A) Experimental design to measure the evoked excitatory and inhibitory postsynaptic currents (eEPSCs/eIPSCs).
(B) Representative traces of eEPSCs and eIPSCs in wildtype and mutant mice. (C) eEPSCs were significantly
increased in mutant mice, whereas eIPSCs were indistinguishable between wildtype and mutant mice (n = WT: 17
neurons from 5 mice; Mut: 17 neurons from 5 mice). (D) The ratio of evoked excitatory (E) to inhibitory (I)
postsynaptic current was increased in mutant mice (n = WT: 17 neurons from 5 mice; Mut: 17 neurons from 5
mice).

(A)
(B) (C) (D)
400
200
-200
0.2 0.3 0.4
-400
0.5 0.1
Amplitude (pA)
eEPSC
eIPSC
sec
eEPSC/eIPSC ratio (Mut)
0
400
200
-200
0.2 0.3 0.4
-400
0.5 0.1
Amplitude (pA)
eEPSC
eIPSC
sec
eEPSC/eIPSC ratio (WT)
0
Post-synaptic current E/I ratio
Evoked post-synaptic current (pA)
Excitatory Inhibitory
Excitation/Inhibition ratio (%)
**
-800
-600
-400
-200
0
200
400
600
800
**
ns
0
50
100
150
WT (17/5)
Mut (17/5) WT (17/5)
Mut (17/5)
26

Figure 2.4. Increased presynaptic transmission onto and postsynaptic AMPAR-mediated response from
mutant CA1 neurons.
(A) Representative traces of paired pulse responses determined by patch clamp recording. (B) Paired pulse ratios
at different interstimulus intervals (ISIs) were reduced in mutant CA1 mice (n = WT: 15 neurons from 5 mice;
Mut: 15 neurons from 5 mice). (C) Representative traces of paired pulse responses determined by field recording.
(D) Paired pulse ratios at different interstimulus intervals (ISIs) were reduced in mutant CA1 mice (n = WT: 16
neurons from 5 mice; Mut: 12 neurons from 4 mice). (E) Experimental design to measure AMPAR-mediated and
NMDAR-mediated current (I AMPA and I NMDA). (F) Representative traces of I AMPA and I NMDA in wildtype and mutant
CA1 neurons. (G) Mutant CA1 neurons exhibited significantly increased AMPAR-mediated current and no change
in NMDAR-mediated current (n = WT: 15 neurons from 5 mice; Mut: 15 neurons from 5 mice). (H) Mutant CA1
neurons showed a significant increase in A/N ratios.
130
110
150
90
70
Ratio (%)
Paired pulse ratio (single cell)
*
WT (15/5)
Mut (15/5)
Interstimulus interval (ms)
0 500 1000
*
*
*
** * * *
*
*
180
150
210
120
90
Ratio (%)
Paired pulse ratio (field)
WT (16/5)
Mut (12/4)
Interstimulus interval (ms)
0 500 1000
*
*
*
*
* * * *
*
*
*
0
-0.5
-1.5
-2.0
Amplitude (nA)
Paired pulse ratio (field, WT)
-1.0
0.4 0.6 0.8 1.0 0.2 sec 1.2
0
-0.5
-1.5
-2.0
Amplitude (nA)
Paired pulse ratio (field, Mut)
-1.0
0.4 0.6 0.8 1.0 0.2 sec 1.2
0
-1.2
-1.8
Amplitude (nA)
Paired pulse ratio (single cell, WT)
-0.6
0.5 0.75 1.0 0.25 sec 1.25
0
-1.2
-1.8
Amplitude (nA)
Paired pulse ratio (single cell, Mut)
-0.6
0.5 0.75 1.0 0.25 sec 1.25
(A) (B)
(C) (D)
400
0
800
-400
-800
Amplitude (pA)
Glutamate receptor response
**
WT (15/5)
Mut (15/5)
ns
IAMPA (A) INMDA (N)
100
150
50
0
Ratio (%)
A/N ratio
WT (15/5)
Mut (15/5)
****
500
250
-250
0.2 0.3 0.4
-500
0.5 0.1
Amplitude (pA)
AMPA
NMDA
sec
IAMPA/INMDA (WT)
500
250
-250
0.2 0.3 0.4
-500
0.5 0.1
Amplitude (pA)
AMPA
NMDA
sec
IAMPA/INMDA (Mut)
0
0
(E)
(F) (G) (H)
27

Figure 2.5. Increased extrasynaptic AMPAR in mutant CA1 neurons.
(A) Experimental design to measure mEPSCs before and after TBS. (B) Representative traces of mEPSCs before
and after TBS in wildtype and mutant CA1 neurons. (C) mEPSC amplitude was indistinguishable between
wildtype and mutant CA1 neurons before TBS. However, mutant CA1 neurons showed increased mEPSC
amplitude compared with wildtype CA1 neurons after TBS (n = WT: 21 neurons from 7 mice; Mut: 21 neurons
from 7 mice). (D) ∆mEPSC
post-pre
was higher in mutant CA1 neurons compared with wildtype CA1 neurons (n =
WT: 21 neurons from 7 mice; Mut: 21 neurons from 7 mice). (E) mEPSC frequency was elevated in mutant CA1
neurons before and after TBS compared with wildtype CA1 neurons (n = WT: 21 neurons from 7 mice; Mut: 21
neurons from 7 mice). (F) Schematic of AMPAR distribution at the synaptic and extrasynaptic sites in wildtype
and mutant CA1 neurons before and after TBS.

(C) (D) (B)
mEPSC frequency
mEPSC frequency (Hz)
Pre-TBS Post-TBS
**
Pre-TBS
mEPSC
Post-TBS
mEPSC
WT Mut
30pA
50ms
WT (21/7)
Mut (21/7)
mEPSC amplitude
mEPSC amplitude (pA)
0
20
Pre-TBS Post-TBS
ns
10
30
40
WT (21/7)
Mut (21/7)
50
30pA
500ms
***
0
1.0
0.5
1.5
2.0
2.5 ***
(A)
(E)
0
△ mEPSC amplitude (pA)
WT (21/7)
Mut (21/7)
6.0
3.0
12.0
9.0
△ mEPSC amplitude
**
15.0
(F)
post-pre
post-pre
28

Figure 2.6. Altered spine density and number of dendritic branches in mutant CA1 neurons.
(A) Representative images illustrating Golgi-stained dendrites and spines of CA1 neurons from wildtype and
mutant mice. (B) Mutant CA1 neurons had reduced spine density at both the basal and secondary apical dendrites
(n = WT: 13 neurons from 4 mice; Mut: 12 neurons from 4 mice). (C, D) Segmental analyses (10 µm) showed that
the differences in spine densities were presented along almost the entire length of both the basal (C) and secondary
apical (D) dendrites. (E) Representative images illustrating CA1 neurons from wildtype and mutant mice
backfilled with Alexa-Fluor 594 fluorescent dye and concentric shells with 20-µm interval from individual soma.
(F-H) Significant differences in number of intersections were presented around the median length range of the
total (F), basal (G), and apical (H) dendrites from wildtype and mutant CA1 neurons (n = WT: 24 neurons from 6
mice; Mut: 24 neurons from 6 mice).
(B) (A)
Spine density (number/um)
Basal 2nd Apical
****
WT (13/4)
Mut (12/4)
0
1.0
0.5
1.5
2.0
2.5
****
Basal
Basal
2nd Apical
2nd Apical
WT
WT
Mut
Mut
(C)
Spine density (number/um)
10 20
WT (13/4)
Mut (12/4)
0
1.0
2.0
3.0
30 40 70 80 50 60 90
Hippocampal spine density
Hippocampal spine density-2nd Apical
Distance from branching points (μm)
* *
*
*
*
*
*
*
*
*
*
* *
*
*
*
*
ns
(D)
Spine density (number/um)
10 20
WT (13/4)
Mut (12/4)
0
1.0
2.0
3.0
30 40 70 80 50 60 90
Hippocampal spine density-Basal
Distance from soma (μm)
* *
*
*
*
*
*
*
*
*
*
* *
*
*
*
ns
100 110 120
*
*
*
*
*
*
*
# of intersections
50 100
WT (24/6)
Mut (24/6)
0
10
20
40
150 200 350 250 300
Hippocampal dendrite number-Total
Distance from soma (μm)
* *
*
* *
*
*
*
*
* *
*
*
*
*
400
*
*
*
* *
*
(F)
(G)
(E)
30
# of intersections
50 100
WT (24/6)
Mut (24/6)
0
5
10
20
150 200 350 250 300
Hippocampal dendrite number-Basal
Distance from soma (μm)
* * * *
*
*
*
*
*
400
*
*
15
(H)
# of intersections
50 100
WT (24/6)
Mut (24/6)
0
5
10
20
150 200 350 250 300
Hippocampal dendrite number-Apical
Distance from soma (μm)
400
15
* * * * * *
*
* *
*
*
*
* *
*
WT Mut
29

Figure 2.7. Altered NR2A and NR2B current in mutant CA1 neurons.
(A) Experimental design to directly measure NMDAR- and NR2A-mediated current (I NMDA and I NR2A). (B)
Representative traces of I NMDA, I NR2A and I NR2B in wildtype and mutant CA1 neurons. Note: the dotted I NR2B traces
were derived from subtraction of I NR2A from I NMDA. (C) Peak amplitude of I NR2B (2B) was decreased, whereas peak
current of I NMDA (N) and I NR2A (2A) were not altered, in mutant CA1 neurons (n = WT: 24 neurons from 8 mice;
Mut: 24 neurons from 8 mice). (D) Charge transfer of I NR2B (2B) was decreased, whereas charge transfers of I NMDA
(N) and I NR2A (2A) were not altered, in mutant CA1 neurons (n = WT: 24 neurons from 8 mice; Mut: 24 neurons
from 8 mice). (E) The ratios of I NR2A/I NMDA (2A/NMDA) and I NR2B/I NMDA (2B/NMDA), measured by peak current,
were significantly altered in mutant CA1 neurons (n = WT: 24 neurons from 8 mice; Mut: 24 neurons from 8 mice).
(F) The ratios of I NR2A/I NMDA (2A/NMDA) and I NR2B/I NMDA (2B/NMDA), measured by charge transfer, were
significantly altered in mutant CA1 neurons (n = WT: 24 neurons from 8 mice; Mut: 24 neurons from 8 mice). (G)
The ratios of I NR2A/I NR2B (2A/2B) measured by both peak current and charge transfer, were increased in mutant
CA1 neurons (n = WT: 24 neurons from 8 mice; Mut: 24 neurons from 8 mice).

(C)
600
400
800
200
0
Amplitude (pA)
Peak current
**
WT (24/8)
Mut (24/8)
ns
INMDA (N) INR2A (2A) INR2B (2B)
ns
20
0
40
Charge transfer (pC)
Charge transfer
**
WT (24/8)
Mut (24/8)
ns
INMDA (N) INR2A (2A) INR2B (2B)
ns
60
Ratio (%)
Peak current
***
WT (24/8)
Mut (24/8)
2A/NMDA 2B/NMDA
***
Ratio (%)
Charge transfer
**
WT (24/8)
Mut (24/8)
2A/NMDA 2B/NMDA
**
(A)
(B)
(D)
(E) (F)
500
400
200
0.2 0.3 0.4
100
0.5 0.1
Amplitude (pA)
NMDA
sec
INMDA/INM2A/INR2B (WT)
0
NR2A
INMDA/INR2A/INR2B (Mut)
NR2B
300
500
400
200
0.2 0.3 0.4
100
0.5 0.1
Amplitude (pA)
NMDA
sec
0
NR2A
NR2B
300
100
0
75
50
Peak
***
450
0
300
Ratio (%)
NR2A/NR2B ratio
WT (24/8)
Mut (24/8)
Charge
150
**
(G)
25
100
0
75
50
25
30

Figure 2.8. Altered profiles of AMPAR-silent synapses in P13-15 mutant CA1 neurons.
(A) Experimental design to measure AMPAR-silent synapses. (B, C) Representative traces and scattered plots of
AMPAR-mediated (-70 mV) and compound (AMPAR- plus NMDA-mediated) current in wildtype (B) and mutant
(C) CA1 neurons at P13-15. (D, E) Representative traces and scattered plots of AMPAR-mediated (-70 mV) and
compound (AMPAR- plus NMDA-mediated) current in wildtype (D) and mutant (E) CA1 neurons at P22-22. (F,
G) Failure rates of wiltype and mutant CA1 neurons at potentials of -70 mV and +40 mV at P13-15 (F) (n = WT:
15 neurons from 5 mice; Mut: 18 neurons from 6 mice) and P20-22 (G) (n = WT: 15 neurons from 5 mice; Mut:
12 neurons from 4 mice). (The same neurons were connected by dotted lines.) (H) Changes in failure rates in
wildtype and mutant CA1 neurons from P13-15 and P20-22 mice. There were significant differences in changes
of failure rate between wildtype and mutant CA1 neurons at P13-15, but not P20-22. Wildtype, not mutant, CA1
neurons showed reduction of changes of failure rate between P13-15 (n = WT: 15 neurons from 5 mice; Mut: 18
neurons from 6 mice) and P20-22 (n = WT: 15 neurons from 5 mice; Mut: 12 neurons from 4 mice).

10
0
∆ Failure rate (%, F -70mV-F+40mV)
Change of failure rate
WT (15/5)
Mut (12/4)
ns
20
**
(A)
(B)
(F) (H)
75
25
0
Failure rate (%)
Failure rate (P20-22)
WT (15/5)
Mut (12/4)
50
-70 -70 +40 +40
75
25
0
Failure rate (%)
Failure rate (P13-15)
WT (15/5)
Mut (18/6)
50
-70 -70 +40 +40
(G)
70
35
-35
150
-70
300
Amplitude (pA)
Silent synapse (WT, P13-15)
0
Stimulus number
Success
Failure
-70mV
+40mV
0
70
35
-35
150
-70
300
Amplitude (pA)
Silent synapse (Mut, P13-15)
0
Stimulus number
Success
Failure
-70mV
+40mV
0
70
35
-35
150
-70
300
Amplitude (pA)
Silent synapse (WT, P20-22)
0
Stimulus number
Success
Failure
-70mV
+40mV
0
70
35
-35
150
-70
300
Amplitude (pA)
Silent synapse (Mut, P20-22)
0
Stimulus number
Success
Failure
-70mV
+40mV
0
20pA
10ms
20pA
10ms
WT, P13-15 Mut, P13-15
WT, P20-22 Mut, P20-22
(C)
(D) (E)
20pA
10ms
20pA
10ms
30
**
ns
P13-15 P20-22
WT (15/5)
Mut (18/6)
31

Chapter 3: Altered sleep architecture and rapid eye movement (REM)
sleep in a mouse model of human chromosome 16p11.2 microdeletion
3.1. Abstract
Sleep disturbance is very prevalent among patients with neurodevelopmental and neuropsychiatric
disorders, such as autism spectrum disorders (ASDs) and attention deficit-hyperactivity disorder
(ADHD). Evidence from genome-wide association studies indicates that chromosomal copy number
variations (CNVs) are associated with increased prevalence of these neurodevelopmental disorders.
Several studies on mouse models of chr16p11.2 microdeletion have demonstrated impairments in
synaptic transmission and local circuitry function in the hippocampus and striatum. However, it has not
been adequately addressed if chr16p11.2 microdeletion is associated with system level abnormalities in
mice, such as sleep and neuronal oscillation. To address this knowledge gap, the present study
investigated sleep architectures and oscillation patterns in a mouse model of human chr16p11.2
microdeletion. Polysomnographic recording revealed reduced non-rapid eye movement (NREM) sleep
and rapid eye movement (REM) sleep, decreased number of REM bouts, shortened REM epoch duration,
and altered NREM to REM transition in heterozygous mutant mice. The mutant mice also showed
significant alterations in EEG oscillation patterns, involving several frequency classes in different
vigilant states. In addition, the ventrolateral periaqueductal gray matter (vlPAG)-projecting GABAergic
neurons in lateral paragigantocellular nucleus (LPGi), one of the main REM-on center, from
heterozygous mutant mice were less excitable compared to wildtype neurons. In sum, our study
demonstrated significant differences in sleep architecture, oscillation patterns, and candidate nucleus in
the chr16p11.2 mouse model.

3.2. Introduction
3.2.1. Sleep disturbance in neurodevelopmental disorders
Sleep disturbance is common among patients with neurodevelopmental and neuropsychiatric disorders,
such as autism spectrum disorders (ASDs) (Wiggs and Stores, 2004; Goldman et al., 2009; Buckley et
al., 2010; Cohen et al., 2014; Accardo and Malow, 2015; Geoffray et al., 2016; Moore et al., 2017;
Souders et al., 2017), Asperger’s syndrome (Allik et al., 2006; Leveille et al., 2010), attention deficit
hyperactivity disorders (ADHDs) (Hvolby, 2015; Lunsford-Avery et al., 2016; Miano et al., 2016; Tsai
et al., 2016; Anand et al., 2017; Groenman et al., 2017), intellectual disability (ID) (Diomedi et al., 1999;
Harvey and Kennedy, 2002; Matson and Malone, 2006; Churchill et al., 2012), psychosis (Davies et al.,
2017; Poe et al., 2017), and schizophrenia (Manoach and Stickgold, 2015; Chan et al., 2017; Kaskie et
32

al., 2017). In these patient populations the prevalent clinical presentations include delayed sleep onset,
shortened total sleep, frequent wakening, day-time sleepiness, reduced or increased REM sleep (Ornitz
et al., 1969; Sheldon and Jacobsen, 1998; Diomedi et al., 1999; Buckley et al., 2010), periodic limb
movement syndrome (PLMS) (Sheldon and Jacobsen, 1998), and REM sleep behavioral disorder
(Thirumalai et al., 2002; Lloyd et al., 2012; Anand et al., 2017; Kaskie et al., 2017; Poe et al., 2017;
Souders et al., 2017). Polysomnography recordings have reported poor differentiation of sleep stage
(Tanguay et al., 1976; Segawa and Nomura, 1992; Diomedi et al., 1999), and changes in oscillation
patterns and regional coherence (Daoust et al., 2004; Miano et al., 2007; Leveille et al., 2010; Frohlich
et al., 2016). The comorbid sleep disturbance adversely affects the patient’s daily activities and have
been found to exacerbate the core symptoms of neurodevelopmental and neuropsychiatric disorders
(Schreck et al., 2004; Sadeh et al., 2007; Gruber et al., 2011; Limoges et al., 2013; Adams et al., 2014;
Lambert et al., 2016).

Rodent models of neurodevelopmental disorders (NDDs) frequently show abnormalities in sleep and
brain oscillation. The functions of the reported genes include, but are not limited to, cell-cell adhesion,
transcriptional regulation, protein degradation, and ligand- or voltage-gated channels (Ehlen et al., 2015;
Jaaro-Peled et al., 2016; Liu et al., 2017; Mesbah-Oskui et al., 2017; Thomas et al., 2017). For example,
Cntnap2 knockout mice exhibited sleep fragmentation and reduced spectral power in the alpha range
(Thomas et al., 2017). Maternal loss of the imprinted gene, Ube3a, altered sleep-wake distribution and
disrupted sleep homeostasis (Ehlen et al., 2015). Mice carrying R451C mutation of the neuroligin 3 gene
displayed changes in multiple frequency bands across several brain states, such as reduced NREM delta
power and higher REM beta power (Liu et al., 2017).

3.2.2. Human chromosome 16p11.2 microdeletion
The human chr16p11.2 microdeletion is one of the most common chromosome copy number variations
(CNVs) associated with NDDs (Sebat et al., 2004; Kumar et al., 2008; Marshall et al., 2008; Weiss et al.,
2008; McCarthy et al., 2009; Hanson et al., 2010; Shinawi et al., 2010; Zufferey et al., 2012). The most
common neurobehavioral presentations in the setting of this microdeletion are language deficit, ID, ASDs,
anxiety, ADHDs, and epilepsy (McCarthy et al., 2009; Hanson et al., 2010; Shinawi et al., 2010; Zufferey
et al., 2012). Additionally, sleep abnormalities have been anecdotally reported (Angelakos et al., 2017).
Several studies on mouse models of chr16p11.2 microdeletion have demonstrated impairments in
synaptic transmission and local circuitry function in the hippocampus (Tian et al., 2015; Lu et al., 2018)
and striatum (Portmann et al., 2014). However, it has not been adequately addressed if chr16p11.2
microdeletion is associated with system level abnormalities in mice, such as sleep behaviors and neuronal
33

oscillation. The mouse model of human chr16p11.2 microdeletion used in this study was the chr7qF3
mutant mouse strain, the same one mentioned in the previous two chapters.

3.2.3. Oscillation patterns
Different vigilance and sleep states, such as wakefulness, NREM, and REM, are characterized by
distinctive oscillation patterns. There are multiple main frequency classes that predominate in different
states. For example, delta wave is a high amplitude wave with a frequency of oscillation between 0.5–4
Hz, which dominates in NREM sleep, originates from the thalamus and multiple cortical regions (Maquet
et al., 1997; Feld and Born, 2017), and plays an important role in memory consolidation and homeostatic
compensation after sleep deprivation (El Helou et al., 2013; Hengen et al., 2016; Liu et al., 2017). Low
theta wave is between 4-6 Hz which appears between NREM to REM transition and could originate from
the cortex or hippocampus (Jego et al., 2013). Theta wave generates the theta rhythm between 6–9 Hz,
which dominates in REM sleep and originates from the medial septum and is observed strongly in the
hippocampus (Alonso and Llinas, 1989; Buzsaki, 2002; Wang, 2002), and is crucial for navigation and
memory formation (Buzsaki and Moser, 2013; Hutchison and Rathore, 2015; Chen and Wilson, 2017;
Eichenbaum, 2017). Alpha wave is between 9-12 Hz and predominantly originates from the occipital
lobe during wakeful relaxation with closed eyes (Palva and Palva, 2007; Klimesch, 2012), and may
indicate a semi-arousal period during REM sleep (Schwabedal et al., 2016). Beta wave is between 12–
30 Hz and mainly originates from the motor cortex (Baker, 2007; Pogosyan et al., 2009; Takahashi et al.,
2011), which is associated to active concentration and anxious thinking (Baumeister et al., 2008). Gamma
wave is between 30–100 Hz and largely originates from the thalamus and visual cortex (Llinas and Ribary,
1993; Hadjipapas et al., 2007; Gregoriou et al., 2009), which relates to consciousness in wake state and
dreaming in REM sleep with typical oscillations of 40 Hz (Llinas and Ribary, 1993; Crick and Koch,
2003; Melloni et al., 2007).

3.2.4. Lateral paragigantocellular nucleus
LPGi is located in the ventrolateral medulla and is known as a sympathoexcitatory area involved in the
control of cardiovascular function, such as blood pressure and heart rate, and respiratory function (Ross
et al., 1984; Guyenet et al., 1990; Dampney, 1994; Guyenet, 2000). LPGi has been proved to be an
important nucleus in the initiation and maintenance of REM sleep in some literatures by projecting fibers
from GABAergic neurons to the REM-off and NREM-on GABAergic vlPAG neurons to disinhibit the
REM-on glutamatergic neurons in sublaterodorsal tegmental nucleus (SLD) (Sapin et al., 2009; Clement
et al., 2011; Sirieix et al., 2012; Luppi et al., 2013; Weber et al., 2015). The disinhibited ascending
glutamatergic SLD REM-on neurons would in turn induce cortical activation via their projections to
34

intralaminar thalamic relay neurons in collaboration with wake/REM-on cholinergic and glutamatergic
neurons from the laterodorsal tegmental nucleus (LDT), pedunculopontine tegmental nuclei (PPT), and
the nucleus basalis (Luppi et al., 2013; Van Dort et al., 2015; Xu et al., 2015; Chung et al., 2017). There
are different types of neurons in LPGi, for example, GABAergic, glutamatergic, adrenergic,
serotoninergic, and glycinergic neurons (Paxinos et al., 2012; Sirieix et al., 2012). However, GABAergic
neurons are predominant and account for at least two-thirds of LPGi neurons (Sirieix et al., 2012). In
addition to projecting to vlPAG for REM sleep regulation, some GABAergic neurons project to cardiac
vagal neurons (CVNs) for REM sleep-dependent modulations in heart rate (Sapin et al., 2009;
Dergacheva et al., 2010; Weber et al., 2015).

3.2.5. Objectives and significances
In this study, we investigated sleep architectures and oscillation patterns in a mouse model of human
chr16p11.2 microdeletion. Polysomnographic recording revealed reduced REM and NREM sleep,
decreased number of REM bouts, shortened REM epoch duration, and altered NREM to REM transition
in heterozygous mutant mice. The mutant mice also showed significant alterations in EEG oscillation
patterns, involving several frequency classes in different vigilant states. In addition, the REM-on center
LPGi neurons from heterozygous mutant mice were less excitable compared to wildtype neurons. In
summary, our study demonstrated significant differences in sleep architecture, oscillation patterns, and
candidate nucleus in the chr16p11.2 mouse model.

3.3. Materials and methods
3.3.1. Animals:
Mice carrying a deletion of the syntenic region of human chr16p11.2 have been previously analyzed
(Horev et al., 2011; Blumenthal et al., 2014; Pucilowska et al., 2015; Tian et al., 2015; Angelakos et al.,
2017; Lu et al., 2018). Mice used in this study have been backcrossed onto the congenic C57BL/6N
(Charles River) background for more than 20 generations. Wildtype (WT) and heterozygous mutant (Mut)
mice were generated by breeding wildtype female with mutant male mice. Both wildtype and mutant
mice were group-housed and kept on a 12:12 hr light:dark cycle with unrestricted access to food and
water. All experimental procedures were approved by the Institutional Animal Care and Use Committee
at the Children’s Hospital Los Angeles and conformed to NIH guidelines. The experimenters were blind
to the genotypes in all experiments and during data analysis.

3.3.2. Surgery:
35

Male heterozygous mutant mice of 6-7 weeks were first anesthetized with 3% isoflurane under a flow
rate of 3 ml/min for 3 min. After eye ointment was applied and the scalp was shaved, isoflurane was
maintained at 2% at a flow rate of 1 ml/min for the remaining procedure. A small amount of normal
saline solution containing 1% lidocaine and 0.1% epinephrine was injected under the scalp and a small
area of scalp was excised to expose the skull. The soft tissue overlying the skull was removed and the
skull was cleaned with 70% ethanol. Three stainless steel micro screws (0.6 mm in diameter) were
inserted into the skull with the tips in the epidural space. Two screws were placed over the frontal cortex
(1.0 mm anterior to bregma and 1.0 mm lateral to the midline), and the third was over the parietal cortex
(2.5 mm posterior to bregma and 1.5 mm lateral to the midline). The left fontal screw was used as ground.
The EEG activity was the differential values of the right frontal and left parietal cortex. The screws were
secured using cyanoacrylate glue and connected to a headmount (Pinnacle Technology, KS; #8402-SS)
via silver wires. Two stainless steel wires, which were built into the headmount by the manufacturer,
were inserted into the trapezius muscle for electromyographic recording. Dental cement was applied to
the skull to form a protective cap for the surgical field, micro screws, and headmount. Post-surgical mice
were given analgesics for 3 days and monitored for any signs of infection and discomfort.

3.3.3. Polysomnographic recording and sleep stage analysis:
Two to three weeks after surgery, mice were habituated for 5 days to custom-built cages (polypropylene,
30 cm in diameter and 25 cm high) and sound-attenuated boxes located in a dedicated sleep recording
room. Then preamplifiers (Pinnacle Technology, KS; 8406-SL) were connected to the headmount, and
mice were habituated for an additional 5 days before recording was initiated. Recording was performed
for two consecutive days. EEG signals were band-filtered between 0.5 Hz and 200 Hz, and sampled at
400 Hz. EMG signals were likewise filtered between 0.5 Hz and 200 Hz, and sampled at 200 Hz.

Recordings from two consecutive days were scored for sleep stage analysis. Each parameter reported in
this manuscript was the average of the two days. Sleep stages were first scored by an automated software
using “threshold scoring” (Sirenia Sleep Pro, Pinnacle Technology). They were further scored manually
by two experimenters. A consensus was reached for each animal before further analysis proceeded. Four-
second window epochs were chosen for all sleep scoring. The awake state was characterized by high
EMG and low amplitude asynchronized EEG on the power spectrum. NREM was characterized by low
to absent EMG, high delta frequency, and low theta frequency oscillation. REM was characterized by
absent EMG, high theta frequency, and low delta frequency oscillation. The post-scoring data and the
performed Fourier space power spectrum analysis were further analyzed by two MATLAB-based
custom-written software programs; one for sleep architecture analysis, and the other for oscillation
36

pattern analysis. One wildtype mouse used for sleep architecture analysis was excluded from power
analysis due to an increased number of artifacts during wakefulness.

3.3.4. Retrograde labeling:
Retrograde labeling of LPGi neurons was achieved by injecting Cholera Toxin Subunit B (Alexa Fluor
TM

488 Conjugate (CTB-488), ThermoFisher Scientific, Cat# C22841) into vlPAG of P23-P25 male
wildtype and mutant littermates. Anesthesia was performed in the same manner as in surgeries for
polysomnographic recording. 75 nl of 5% CTB-488, diluted in phosphate buffered saline (PBS), was
injected bilaterally into vlPAG (1.0 mm posterior to Lambda, 0.6 mm lateral to the midline, and 2.3 mm
deep) at a speed of 75 nl/min. After injection of the specified volume, the injection needle was kept at
the injection site for extra 2 min before being withdrawn slowly out of the brain. Post-surgical mice were
given analgesics for 3 days and monitored for any signs of infection and discomfort.

3.3.5. Electrophysiology:
After 6-10 days of recovery from surgery, whole-cell patch clamp recordings were performed on CTB-
labeling LPGi neurons from male wildtype and mutant mice. Mice were euthanized by rapid decapitation
and the brains were immediately submerged in ice-cold high sucrose dissection buffer (HSDB) for 1 min.
Two-hundred-micron coronal sections were cut on a Leica VT1000 S vibratome in ice-cold HSDB,
incubated in NMDG recovery buffer (NRB) at 30°C for 15 min, then transferred to artificial cerebrospinal
fluid (aCSF) at 25°C. Slices were further recovered at room temperature for 1 hr before recording. During
the recording, slices were continuously perfused with oxygenated aCSF at a flow rate of 2 ml/min and at
room temperature, then viewed under infrared differential interference contrast (IR-DIC) and fluorescent
illumination. The LPGi neurons located within the ventral medulla selected for whole-cell patching were
identified by the presence of CTB-488 visualized by superimposing the fluorescent and IR-DIC optics.
HSDB was composed of (in mM): 87 NaCl, 75 sucrose, 2.5 KCl, 1.2 NaH2PO 4, 30 NaHCO3, 25 Glucose,
20 HEPES, 5 Na-Ascorbate, 3 Na-Pyruvate, 2 Thiourea, 10 MgSO4, and 0.5 CaCl 2. NRB was composed
of (in mM): 92 NMDG, 92 HCl, 2.5 KCl, 1.2 NaH2PO4, 30 NaHCO3, 25 Glucose, 20 HEPES, 5 Na-
Ascorbate, 3 Na-Pyruvate, 2 Thiourea, 10 MgSO4, and 0.5 CaCl 2. aCSF was composed of (in mM): 119
NaCl, 2.5 KCl, 1 MgCl 2, 2 CaCl 2, 26 NaHCO3, 1.23 NaH2PO 4, and 10 Glucose. All buffers used in
dissection, recovery, and recording were supplemented with a mix of 95% O2 and 5% CO2 to maintain
the pH at 7.4. All recordings were performed in aCSF at room temperature with a Multiclamp 700B
microelectrode amplifier (Molecular Device, Sunnyvale, CA). Signals were low-pass filtered at a
frequency of 1k Hz and digitized at 10k Hz using Digidata 1440A amplifier and Clampex 10.7 software
(Molecular Device). Series resistance was monitored continuously during recording and experiments
were discarded if the measurement changed by >15%. All internal solutions (resistance 4–7 MΩ; pH 7.2-
7.4; osmolarity 290-300 mOsm) used in this study contained 6.7 mM biocytin and 80 µM Alexa-Fluor
594 hydrazide. All data was analyzed using Minianalysis (version 6.0.3. Synaptosoft Inc) or Clampfit
37

software (version 10.7, Molecular Device).

Current clamp recording was performed to measure the resting membrane potential (RMP) (Schiebe and
Jaeger, 1980; Graves et al., 2012). Specifically, after obtaining a gigaseal, the membrane was carefully
broken to avoid a leaking current larger than 50 pA. The membrane potentials were recorded for 10 min
and the measurements during the last 5 min were used to calculate the RMP. The electrodes were filled
with (in mM) 131 K-gluconate, 20 KCl, 8 NaCl, 10 HEPES, 2 EGTA, 2 NaATP, and 0.3 NaGTP. To
measure membrane resistance (Rm), series resistance (Rs), and membrane capacitance (Cm), neurons
were recorded for 15 min, and the measurements during the last 5 min were analyzed. Neurons were
discarded if the values of these three measurements fluctuated more than 15% from the average values
(Donnelly, 1994). The electrodes were filled with (in mM) 131 K-gluconate, 20 KCl, 8 NaCl, 10 HEPES,
2 EGTA, 2 NaATP, and 0.3 NaGTP. To determine the current-voltage (I-V) curve, membrane current at
eleven voltage steps (-100, -80, -60, -40, -20, 0, 20, 40, 60, 80, 100 mV) were measured. Specifically,
neurons were held at each step for 400 ms. The initial peak current for the entire step and the average
current for the last 100 ms were analyzed. The voltage step cycle was repeated twice for each neuron and
the current measurements for each step were averaged and used for the data analysis. The electrodes were
filled with (in mM) 131 K-gluconate, 20 KCl, 8 NaCl, 10 HEPES, 2 EGTA, 2 NaATP, and 0.3 NaGTP.

3.3.6. Immunostaining:
For post-recording staining, slices were fixed in freshly prepared 4% PFA diluted in 1x PBS for 30 min
immediately after recording. They were transferred to 1x PBS and stored at 4 ℃ until staining. Dual
staining for biocytin (which was diffused into patched neurons during recording) and for Cre protein (to
confirm that the patched neurons were GABAergic) was performed at room temperature unless otherwise
mentioned on all slices containing patched neurons. Slices were first washed with 1x PBST three times
(5 min per wash); they were incubated in 1x PBST + 5% normal donkey serum for 1 hr; they were then
incubated with AMCA–avidin D (dilution: 1/200; Vector Laboratories, Cat# A-2008) and monoclonal
rabbit anti-Cre antibody (dilution: 1/200; Synaptic System, Cat# 257003) at 4 ℃. After overnight
incubation, slices were washed in 1x PBST three times (5 min per wash); they were then incubated with
donkey anti-rabbit secondary antibody conjugated with Alexa Fluor
TM
594 (dilution: 1/200; Jackson
ImmunoResearch, Cat# 611-585-215). After 2 hr, slices were washed in 1x PBST three times (5 min per
wash), 1x PBS two times (5 min per wash), and mounted on slides with Fluoromount-G mounting media
without DAPI (SouthernBiotech, Cat# 0100-01) and coverslipped.

3.3.7. Statistical analysis:
38

Statistical analyses were performed using GraphPad software (version 6; La Jolla, California). Two-
tailed unpaired Student’s t-test was used for data analysis between wildtype and mutant mice. All data
are presented as the average ± SEM (standard error of mean) values.

3.4. Results
3.4.1. Reduced NREM and REM sleep, and increased wakefulness in mutant mice
We first determined the amount of time wildtype and mutant mice spent awake and asleep (total sleep)
by EMG and then further examined the EEG while asleep to determine NREM and REM sleep durations.
During the day, mutant mice showed reduced total (WT: 442.73±9.06 min, 10 mice; Mut: 391.00±11.26
min, 9 mice, **P<0.01), NREM (WT: 381.48±8.84 min, 10 mice; Mut: 351.13±8.06 min, 9 mice,
*P<0.05), and REM (WT: 61.26±1.52 min, 10 mice; Mut: 39.42±3.75 min, 9 mice, ****P<0.0001) sleep
(Fig. 3.1B-D), and a concurrent increase in total wakefulness (Fig. 3.1A) (WT: 277.28±9.06 min, 10
mice; Mut: 328.75±11.26 min, 9 mice, **P<0.01). During the night, these differences were more
pronounced (Fig. 3.1A-D) (Wake: WT: 511.48±14.45 min, 10 mice; Mut: 631.73±5.50 min, 9 mice,
****P<0.0001; Sleep: WT: 208.50±14.45 min, 10 mice; Mut: 87.93±5.50 min, 9 mice, ****P<0.0001;
NREM: WT: 192.38±13.81 min, 10 mice; Mut: 83.08±4.99 min, 9 mice, ****P<0.0001; REM: WT:
16.15±0.92 min, 10 mice; Mut: 4.41±0.69 min, 9 mice, ****P<0.0001) and this pattern of differences
persisted for the full 24 hr measurements (Fig. 3.1A-D) (Wake: WT: 788.73±21.78 min, 10 mice; Mut:
960.50±10.54 min, 9 mice, ****P<0.0001; Sleep: WT: 651.25±21.78 min, 10 mice; Mut: 478.93±10.54
min, 9 mice, ****P<0.0001; NREM: WT: 573.85±21.03 min, 10 mice; Mut: 434.20±8.21 min, 9 mice,
****P<0.0001; REM: WT: 77.41±2.00 min, 10 mice; Mut: 43.84±3.61 min, 9 mice, ****P<0.0001). We
also calculated the percentages of REM sleep relative to total sleep (Fig. 3.1E) (24Hr: WT: 11.73±0.49%,
10 mice; Mut: 9.07±0.76%, 9 mice, **P<0.01; Day: WT: 14.20±0.58%, 10 mice; Mut: 9.87±0.81%, 9
mice, ***P<0.001; Night: WT: 7.91±0.49%, 10 mice; Mut: 4.87±0.49%, 9 mice, ***P<0.001) and to
NREM sleep (Fig. 3.1F) (24Hr: WT: 13.63±0.73%, 10 mice; Mut: 9.95±0.75%, 9 mice, **P<0.01; Day:
WT: 16.10±0.60%, 10 mice; Mut: 10.97±0.91%, 9 mice, ***P<0.001; Night: WT: 8.37±0.61%, 10 mice;
Mut: 5.40±0.74%, 9 mice, ***P<0.001) and found both were significantly lower in mutant mice
compared with wildtype mice, suggesting that the reduction of REM sleep was not dependent on the total
or NREM sleep duration but resulted from significant decrease of REM sleep time itself in mutant mice.

We further examined the time-course of wake/sleep states in 2-hr intervals to identify the time window(s)
in which mutant mice differed from wildtype mice (Fig. 3.1G-J). We found that the average values for
both the total (Fig. 3.1H) (ZT2-4, 12-24, **P<0.01; ZT4-6, 8-10, *P<0.05) and NREM sleep (Fig. 3.1I)
(ZT12-24, **P<0.01; ZT2-6, *P<0.05) were lower, while for wakefulness (Fig. 3.1G) (ZT2-4, 12-24,
39

**P<0.01; ZT4-6, 8-10, *P<0.05) were higher in mutant mice for several daytime windows (particularly
in the early half) and every nighttime window. More significantly, the REM sleep was shorter in mutant
mice for all time segments across the 24 hr recording (Fig. 3.1J) (ZT0-24, **P<0.01), indicating the most
dramatic alteration at daytime is REM sleep, compared to other vigilance states.

3.4.2. Impaired NREM to REM transition and maintenance of REM sleep in mutant mice
One abnormality found in mutant mice was the significant reduction in REM sleep (Fig. 3.1D-F, J). This
could be due to a reduction in the number of REM episodes (bout number) and/or duration of each REM
episode (bout duration). To differentiate these two possibilities, we quantified bout number and bout
duration for mutant and wildtype mice for each type of wake/sleep state. As shown in Fig. 3.2, during
the day, mutant mice were indistinguishable from wildtype mice in the number of wake (WT:
142.70±6.48 #, 10 mice; Mut: 145.39±8.96 #, 9 mice, P>0.05), sleep (WT: 142.70±6.48 #, 10 mice; Mut:
145.39±8.96 #, 9 mice, P>0.05), and NREM (WT: 142.70±6.48 #, 10 mice; Mut: 145.39±8.96 #, 9 mice,
P>0.05) bouts (Fig. 3.2A, B), but showed a reduced number of REM bouts (Fig. 3.2C) (WT: 46.54±1.76
#, 10 mice; Mut: 39.73±2.47 #, 9 mice, *P<0.05) and lower REM/NREM bout number ratios (Fig. 3.2D)
(WT: 32.79±1.30%, 10 mice; Mut: 26.79±1.52%, 9 mice, *P<0.05). During the night, mutant mice
displayed reduced wake (WT: 73.65±8.34 #, 10 mice; Mut: 34.23±3.26 #, 9 mice, ***P<0.001), sleep
(WT: 73.65±8.34 #, 10 mice; Mut: 34.23±3.26 #, 9 mice, ***P<0.001), NREM (WT: 73.65±8.34 #, 10
mice; Mut: 34.23±3.26 #, 9 mice, ***P<0.001), and REM (WT: 15.15±1.21 #, 10 mice; Mut: 5.75±0.99
#, 9 mice, ****P<0.0001) bout numbers, and REM/NREM bout number ratios (Fig. 3.2A-D) (WT:
21.94±2.10%, 10 mice; Mut: 15.39±2.19%, 9 mice, *P<0.05). In addition, mutant mice showed increased
wake bout duration (Fig. 3.2E) (Day: WT: 130.45±12.49 sec, 10 mice; Mut: 221.85±30.39 sec, 9 mice,
*P<0.05; Night: WT: 436.55±57.69 sec, 10 mice; Mut: 930.73±76.29 sec, 9 mice, ****P<0.0001; 24Hr:
WT: 224.20±19.75 sec, 10 mice; Mut: 347.90±26.96 sec, 9 mice, **P<0.01) and reduced REM bout
duration (Fig. 3.2H) (Day: WT: 80.51±3.02 sec, 10 mice; Mut: 60.67±3.19 sec, 9 mice, ***P<0.001;
Night: WT: 66.60±2.71 sec, 10 mice; Mut: 49.74±4.48 sec, 9 mice, ***P<0.001; 24Hr: WT: 76.28±2.80
sec, 10 mice; Mut: 60.00±3.02 sec, 9 mice, **P<0.01) at daytime, during nighttime, and across the entire
24 hr recording. In contrast, mutant mice were statistically indistinguishable from wildtype mice in total
sleep bout duration (Fig. 3.2F) (Day: WT: 191.41±9.92 sec, 10 mice; Mut: 167.33±8.24 sec, 9 mice,
P>0.05; Night: WT: 179.54±10.52 sec, 10 mice; Mut: 172.36±11.94 sec, 9 mice, P>0.05; 24Hr: WT:
186.62±9.88 sec, 10 mice; Mut: 166.62±9.12 sec, 9 mice, P>0.05) and NREM bout duration (Fig. 3.2G)
(Day: WT: 164.68±8.98 sec, 10 mice; Mut: 150.67±7.86 sec, 9 mice, P>0.05; Night: WT: 165.41±9.86
sec, 10 mice; Mut: 163.10±11.69 sec, 9 mice, P>0.05; 24Hr: WT: 163.78±9.09 sec, 10 mice; Mut:
151.28±8.65 sec, 9 mice, P>0.05). It is worth mentioning that the significantly increased nighttime wake
40

bout duration (Fig. 3.2E) was largely due to the presence of multiple episodes of wakefulness with long
duration at night, particularly during the first half of the night (Fig. 3.1G).

To more precisely characterize REM duration and account for the decreased number of bouts of REM
sleep generated by the mutant mice overall, we quantified the distribution of bout durations in wildtype
and mutant mice, as a function of the total number of bouts of a given duration in cumulative 16-sec bins,
and the total percentage of bouts of a given duration. Mutant mice differ from wildtype mice both during
the day and night albeit in different patterns. During the day mutant mice had increased number (16-48
sec, *P<0.05) and percentage (16-48 sec, **P<0.01) of REM bouts with relatively short duration (Fig.
3.2I, J), and decreased REM bouts with relatively long duration (Fig. 3.2I, J) (Number: 96-176 sec,
**P<0.01; 176-256 sec, *P<0.05; Percentage: 96-176, 192-256 sec, *P<0.05). In contrast, at night,
mutant mice showed decreased number of REM bouts in almost all bins compared with wildtype mice
(Fig. 3.2K) (32-96, 112-128 sec, **P<0.01; 96-112, 128-208 sec, *P<0.05), with an increased percentage
of REM bouts only in the bin of shortest duration (Fig. 3.2L) (16-32 sec, *P<0.05).

REM sleep can be divided into initiation and maintenance phase (Jego et al., 2013; Weber et al., 2015;
Weber et al., 2018). Duration initiation, a NREM episode, characterized by high delta and low theta
oscillation (see below), is followed by REM episode with characteristic high theta and low delta. It was
noted that whereas 32.79±1.30% of the NREM episodes could be converted into REM episodes in
wildtype mice during the day (Fig. 3.2D), only 26.79±1.52% of the NREM episodes were converted into
REM episodes in mutant mice. This indicated that a larger fraction of NREM episodes were not converted
into REM in mutant mice compared with wildtype mice, suggesting that NREM to REM transition, hence
the initiation of REM, was deficient in mutant mice. Furthermore, mutant mice showed increased
numbers and percentages of short REM bouts while exhibiting the converse for the long REM bouts (Fig.
3.2I, J), suggesting the maintenance of REM sleep was likewise impaired in mutant mice during the day.

3.4.3. Altered oscillation patterns in mutant mice
Different vigilance and sleep states are characterized by distinctive oscillation patterns. The changes in
sleep structure described above in mutant mice prompted us to investigate the oscillation patterns using
power spectrum analysis. There are known specific frequency classes that are of interest in the EEG data
(e.g., delta, theta, and gamma). Thus, we analyzed the Fourier spectrum of the data using two approaches.
First, the scored EEG data was divided into awake, NREM, and REM sets of segments. Fourier analysis
was performed on each segment of each specific set, using a 1-Hz bin size. The power spectrum of each
set was calculated by summing the Fourier components of each segment of that set. The first analysis
41

evaluated the power in the known frequency classes of delta, low theta, theta, alpha, beta and gamma
EEG waves and normalized to the total power in individual vigilance states to acquire the relative power
for these classes between the wildtype and mutant mice (Fig. 3.3A-F). In the second analysis the entire
power spectra of the wildtype and mutant were compared for each set (Fig. 3.3G-L). Due to the 60 Hz
noise in our sleep recording, we only analyzed the frequency lower than 59 Hz for gamma wave.

As shown in Fig. 3.3, during the day, mutant mice showed reduced theta (WT: 19.80±0.59%, 9 mice;
Mut: 17.73±0.45%, 9 mice, **P<0.01) oscillation power during wakefulness, lower delta (WT:
37.29±1.07%, 9 mice; Mut: 34.65±0.55%, 9 mice, *P<0.05) oscillation power during NREM sleep, and
significantly decreased theta (WT: 35.12±1.57%, 9 mice; Mut: 27.79±1.44%, 9 mice, **P<0.01), and
increased beta (WT: 16.16±0.33%, 9 mice; Mut: 18.55±0.25%, 9 mice, ***P<0.001) and gamma (WT:
8.94±0.76%, 9 mice; Mut: 11.10±0.62%, 9 mice, *P<0.05) oscillation power during REM sleep (Fig.
3.3A-C). During the night, mutant mice displayed reductions in low theta (WT: 15.83±0.53%, 9 mice;
Mut: 13.91±0.60%, 9 mice, *P<0.05) and theta (WT: 20.50±0.63%, 9 mice; Mut: 17.10±0.48%, 9 mice,
***P<0.001), increased in gamma (WT: 14.64±1.10%, 9 mice; Mut: 18.61±1.20%, 9 mice, *P<0.05)
oscillation power during wakefulness, no changes in any frequency classes during NREM sleep, and
increased delta (WT: 20.35±1.02%, 9 mice; Mut: 23.80±0.92%, 9 mice, *P<0.05) and significantly
decreased theta (WT: 33.60±1.73%, 9 mice; Mut: 26.30±1.32%, 9 mice, **P<0.01) oscillation power
during REM sleep (Fig. 3.3D-F).

To verify and better characterize the frequency classes where mutant mice showed changes in oscillation
patterns, we examined the spectral plot between 0 to 59 Hz (Fig. 3.3G-L). The results closely matched
those from frequency class analysis in the low theta (day-wake and night-wake), theta (day-wake, day-
REM, night-wake, and night-REM), beta (day-REM), and gamma (day-REM and night-wake) oscillation
ranges. The results were also consistent in the delta oscillation (day-NREM and night-REM) range. It
was noted that some bins in day-NREM (Fig. 3.3H) (7-9, 26-32 Hz, *P<0.05), one in day-REM (Fig.
3.3I) (2-3 Hz, *P<0.05), one in night-NREM (Fig. 3.3K) (3-4 Hz, *P<0.05), and some in night-REM
(Fig. 3.3L) (15-21, 22-25 Hz, *P<0.05; 25-26 Hz, **P<0.01) displayed mild elevated oscillation power
in mutant mice compared to wildtype mice; however, since there were no differences in other 1-Hz bins
in these frequency ranges in NREM and REM (Fig. 3.3H, I, K, L), not enough differences could be
deduced from the frequency class analysis (Fig. 3.3B, C, E, F).

Taken together, our power analysis demonstrated aberrations in neuronal oscillation in multiple
frequency classes in several vigilance and sleep states. The most prominent findings were changes in
42

theta oscillation in both wake and REM sleep during both day and night, suggesting the neuronal
circuitries involved in theta oscillation are abnormal in mutant mice.

3.4.4. Altered intrinsic membrane properties in mutant vlPAG-projecting GABAergic LPGi
neurons
The vlPAG-projecting GABAergic neurons in LPGi play an important role in REM sleep regulation.
Optogenetic stimulation of these neurons increased REM sleep by increasing the probability of NREM-
REM transition and REM duration (Weber et al., 2015). Additionally, their firing activity correlated with
both the initiation and maintenance phase of REM sleep (W eber et al., 2018). W e speculated that impaired
initiation and maintenance of REM in mutant mice could result from impaired excitability of these
projection specific GABAergic neurons in LPGi. Since the intrinsic membrane properties are critical for
neuronal excitability, we conducted patch clamp recording to investigate the pertinent biophysical
parameters.

With the purpose to specifically patch vlPAG-projecting GABAergic LPGi neurons, we did surgeries in
GAD-Cre mice and injected fluorescent retrograde tracing dye CTB-488 in vlPAG nucleus (Fig. 3.4A,
B) (Paxinos and Franklin, 2004) to let it trace the projections from LPGi (Fig. 3.4C, D) (Paxinos and
Franklin, 2004), then CTB-labeling LPGi neurons were patched (Fig. 3.4E) and biocytin was routinely
included in the internal solution for post hoc immunostaining by Cre antibody (Fig. 3.4G, H) and AMCA-
avidin (Fig. 3.4F, H) to verify these patched neurons are GABAergic. Due to the predominant projections
from LPGi to vlPAG are GABAergic, the possibilities of CTB-labeling neurons exhibiting Cre-positive
staining are very high. In fact, the immunostaining results displayed that all 18 wildtype and 15 mutant
LPGi neurons we included in later analyses were Cre-positive neurons.

We performed several experiments to investigate the intrinsic membrane properties of LPGi neurons.
Mutant CA1 neurons showed a mild reduction in resting membrane potential (Fig. 3.4I) (WT: -
66.93±0.22 mV, 18 neurons from 6 mice; Mut: -68.26±0.22 mV, 15 neurons from 5 mice, ***P<0.001)
and a significant elevation in membrane resistance (Fig. 3.4J) (WT: 412.00±7.07 MOhm, 18 neurons
from 6 mice; Mut: 452.44±15.28 MOhm, 15 neurons from 5 mice, *P<0.05). However, series resistance
(Fig. 3.4K) (WT: 110.76±3.64 MOhm, 18 neurons from 6 mice; Mut: 111.67±3.38 MOhm, 15 neurons
from 5 mice, P>0.05) and membrane capacitance (Fig. 3.4L) (WT: 43.25±2.63 pF, 18 neurons from 6
mice; Mut: 43.08±1.63 pF, 15 neurons from 5 mice, P>0.05) did not differ significantly between wildtype
and mutant LPGi neurons. These results indicated that the intrinsic membrane properties were less
excitable in mutant vlPAG-projecting GABAergic LPGi neurons in resting state.
43

Next, we applied a step-protocol to determine neuronal current-voltage (I-V) relationship (Fig. 3.4M-O).
Both the peak current, representing the responses of voltage-gated ion channels and ionotropic receptors
with fast kinetics, and the steady state current, representing ligand-gated channels and metabotropic
receptors with slow kinetics, were quantified (Fig. 3.4M). Mutant CA1 neurons showed indistinguishable
peak (Fig. 3.4N) (-100-+100 mV, P>0.05) and steady state current (Fig. 3.4O) (-100-+100 mV, P>0.05)
at each voltage step between wildtype and mutant LPGi neurons, suggesting that both the quantities or
types of fast-responding ion channels (or receptors) and the slow-responding ligand-gated channels (or
metabotropic receptors) were unaltered in mutant vlPAG-projecting GABAergic LPGi neurons.

Taken together, the above studies revealed a small reduction in RMP and mildly increased Rm in mutant
vlPAG-projecting GABAergic LPGi neurons. Although these changes were small in magnitude, they
could contribute to the decreased excitability of the mutant LPGi neurons.

3.5. Discussion
Children with neurodevelopmental disorders often have sleep abnormalities. Sleep disorders have been
reported in individuals with chromosome 16p11.2 microdeletion (Angelakos et al., 2017). This study has
demonstrated several abnormalities in a mouse model of C57BL/6J and 129S1/SvImJ hybrid background
of the human chr16p11.2 microdeletion. Some of them are similar to our mutant mice, e.g., increased
wakefulness, decreased NREM sleep, increased number of wake bouts with long duration; while others
are different from ours, e.g., there are no differences in neither sleep architectures nor oscillation patterns
in REM state and increased alpha oscillation in wake state (Angelakos et al., 2017). These inconsistent
results are most likely due to the distinguished backgrounds between their mutant mice and ours. In our
study, we investigated sleep architecture, neuronal oscillation, and candidate nucleus in a mouse model
human chr16p11.2 microdeletion on a congenic C57BL/6N background. Our data revealed a wide range
of deviations in mutant mice. Below we discuss the major findings and potential underlying mechanisms
in the framework of the current knowledge of sleep regulation.

3.5.1. Reduction in daytime NREM sleep and slow-wave oscillation in the delta range
NREM sleep is critical for memory consolidation and synaptic homeostasis. NREM-associated memory
processing depends on highly coordinated interplay between thalamus-originated cortical slow wave
oscillation and hippocampal sharp waves and ripples (Feld and Born, 2017). For example, hippocampal
memory replay predominantly occurs during NREM sleep (Wilson and McNaughton, 1994). Slow wave
oscillation in the delta range during NREM provides an “up-state” in the cortex for the transfer of
44

memory traces “carried” by hippocampal sharp-waves and ripples (Clemens et al., 2007; Ji and Wilson,
2007; Staresina et al., 2015; Maingret et al., 2016; Feld and Born, 2017). There is strong evidence to
support the role of slow-wave oscillation in sleep-dependent memory formation and consolidation from
a study using trans-cranial direct current stimulations (tDCS). Increasing the duration and intensity of
slow-wave oscillation during NREM by tDCS augments recall of declarative memories, whereas
suppressing slow-wave oscillation strongly suppresses retention of declarative memories (Marshall et al.,
2011). Further, slow-wave oscillation during NREM has been shown to coordinate the flow of
information between distributed brain regions, and determine spike-timing dependent synaptic plasticity
by synchronizing cycles of excitability among them (Varela et al., 2001; Buzsaki, 2005; Levenstein et
al., 2017). Lastly, NREM sleep regulates homeostasis of cortical neuronal firing rate and thus facilitates
various forms of synaptic plasticity (Hengen et al., 2016; Levenstein et al., 2017).

Our study demonstrated mild reductions in NREM sleep time and in the power of slow-wave oscillation
in mutant mice. Since these changes are small, their direct impact on the behaviors in mutant mice cannot
be confidently assessed. However, given that NREM and its associated slow-wave oscillation are the
integral components of memory consolidation, neuronal homeostasis, and synaptic plasticity, they may
additively or synergistically affect these processes in the presence of abnormalities in other parts of the
relevant circuits.

3.5.2. Reduced REM sleep and increased wakefulness time
REM sleep is generated by the activation of REM-on neurons in lateral hypothalamic Melanin-
concentrating hormone (MCH) neurons (Verret et al., 2003; Hassani et al., 2009; Jego et al., 2013;
Tsunematsu et al., 2014), glutamatergic neurons in SLD (Lu et al., 2006; Sapin et al., 2009; Luppi et al.,
2011), and GABAergic neurons in the ventral medulla (Lu et al., 2006; Sirieix et al., 2012; Weber et al.,
2015; Weber et al., 2018), and coordinated silencing of wake-promoting neurons in the basal forebrain,
lateral hypothalamus, dorsal raphe nucleus (DRN), and locus coeruleus (LC) (Luppi et al., 2013; Weber
and Dan, 2016; Saper and Fuller, 2017). Transitioning from NREM to REM depends on silencing of
NREM-on neurons in vlPAG and lateral pontine tegmentum (LPT), and activation of REM-on neurons,
whereas termination of REM results from activation of wake-promoting neurons and silencing of REM-
on neurons (Luppi et al., 2013; Weber and Dan, 2016). For example, optogenetic studies showed that
activation of the lateral hypothalamic MCH neurons and ventral medullar, especially LPGi, GABAergic
neurons were necessary and sufficient for the initiation and maintenance of REM sleep (Jego et al., 2013;
Weber et al., 2015; Weber et al., 2018).

45

Our study demonstrated reductions in total sleep and increased wakefulness time, which were mild during
the day and significant at night in mutant mice. The time window where these changes were most
prominent was between ZT12-ZT18. In addition to increased nighttime arousal, mutant mice also showed
increased night-time locomotor activity in our previous open-field test results (data not shown).
Moreover, mutant mice displayed significantly reduced REM sleep during both day and night. Several
parameters suggested that the initiation and maintenance of REM was impaired in mutant mice. First,
the number of REM bouts and REM/NREM bout number ratios were lower in mutant mice. Second,
mutant mice had increased number and percentage of short REM episodes. Third, the number and
percentage of bouts with long REM duration was significantly lower in mutant mice. Based on the afore-
described circuitry mechanisms regulating different brain state, it is conceivable that shortening of REM
in mutant mice results from “weakening” of REM-on neurons and/or “strengthening” of wake-promoting
neurons. Future systematic studies of various nuclei and neurons involved in REM regulation will shed
light on the cellular and circuitry mechanisms for shortened REM sleep in mutant mice.

3.5.3. Reduced REM-associated theta oscillation
In addition to reduced REM sleep time, mutant mice also showed significant reductions in REM
associated theta oscillation during both day and night in mutant mice. Theta oscillation during REM sleep
can be recorded from multiple brain regions in rodents including the hippocampus, entorhinal cortex,
amygdala, supramammillary nuclei of the hypothalamus, and retrosplenial cortex (Buzsaki, 2002; Wang,
2002). The reciprocal loop between medial septum (MS) and the hippocampus is critical for theta rhythm
(Buzsaki, 2002; Wang, 2002; Tsanov, 2015). MS GABAergic neurons drive hippocampal theta
oscillation thus functioning as “rhythm generator” or “pace-makers”. The frequency and power of
hippocampal REM theta wave are determined by MS GABAergic neurons, the hippocampus and
entorhinal cortex (Alonso and Llinas, 1989; Buzsaki, 2002; Wang, 2002). In our study, theta oscillation
recorded from the parietal cortex during REM and wakefulness reflects the activity of the hippocampus.
The peak frequencies of theta rhythm were indistinguishable between wildtype and mutant mice,
suggesting that the “rhythm generator” function of MS GABAergic neurons in driving theta oscillation
in the hippocampus was intact in mutant mice. In contrast, mutant mice showed significantly reduced
theta power. Two possibilities may account for this phenotype.

First, the “current generator” function of MS GABAergic neurons was impaired in mutant mice, despite
their normal function as “rhythm generator”. Studies have shown that selective lesion and/or optogenetic
silencing of MS GABAergic neurons greatly reduce hippocampal theta power (Winson, 1978; Boyce et
al., 2016). It is thus conceivable that a reduction in the activity of MS GABAergic neurons, at either
46

ensemble or individual cellular level, may contribute to attenuated theta rhythm. The reduced MS
GABAergic activity could be due to anatomic and/or functional changes in mutant mice.

Second, the source of theta oscillation, i.e., the hippocampus, could be abnormal in mutant mice.
Specifically, the degree of synchronization and intrinsic properties of hippocampal neurons, as well as
the local inhibitory network were aberrant in mutant mice. It is known that hippocampal theta rhythm is
generated by synchronized synaptic activity in a continuous layer of neurons in CA3/CA1/subiculum,
and theta power is determined by the degree of synchronization, the strength of synaptic input, and the
tuning properties of inhibitory neurons (Buzsaki, 2002). Therefore, it is reasonable to speculate that these
factors were abnormal and led to attenuated theta power in mutant mice. Consistent with this idea, our
recent study demonstrated electrophysiological changes affecting hippocampal functions in mutant mice
(Lu et al., 2018), including increased excitability and elevated excitation to inhibition (E/I) ratio in the
absence of significant changes in inhibition in synapses onto the CA1 neurons (Lu et al., 2018). It is
conceivable that increased excitability and E/I ratio may decrease synchronization among CA1 neurons,
thus reducing theta power in mutant mice. Furthermore, we speculate that additional aberrations in
hippocampal neurons that affect synaptic inputs and synchronization are likely present in mutant mice.
Future in vivo characterization of the hippocampus will likely provide cellular and circuitry mechanisms
for altered theta oscillation in mutant mice.

What is the functional implication of altered theta oscillation in mutant mice? Hippocampal theta rhythm
during REM sleep has been proposed to be critical for consolidation of spatial memory and memory with
a strong emotion component (Hutchison and Rathore, 2015; Chen and Wilson, 2017). A study by Boyce
demonstrated that theta activity during REM sleep was required for memory consolidation in novel object
place recognition (NOPR) and contextual fear conditioning (CFC) (Boyce et al., 2016). Optogentic
silencing of MS GABAergic neurons during REM episode selectively reduced hippocampal theta
oscillation (without affecting other parameters of REM sleep) and resulted in impaired performance in
NOPR and CFD. Intriguingly, impaired contextual fear conditioning was reported in chr16p11.2
microdeletion mice (Tian et al., 2015). In light of our current study, which revealed reduced theta
oscillation in mutant mice, we hypothesize that reduction in theta rhythm may contribute to impaired
conditional fear memory in chr16p11.2 mice. As mentioned previously, one tantalizing possibility is that
impairment in MS GABAergic neurons as a current generator may be a contributing factor. Future studies
of the MS GABAergic neurons and their functions in mutant mice are needed to investigate this
possibility.

47

3.5.4. Reduction in wake-associated theta oscillation
Interestingly, in addition to a reduction in REM theta, a decrease in theta rhythm was also present in
mutant mice during wakefulness. Awake theta rhythm occurs during active exploration, sniffing,
whisking, and rearing (Buzsaki, 2005; Mizuseki and Miyawaki, 2017). Theta rhythm recorded during
explorative locomotion is generated in the hippocampus and is critical for spatial encoding and memory
(Buzsaki and Moser, 2013; Eichenbaum et al., 2016; Chen and Wilson, 2017; Eichenbaum, 2017). The
cellular and physiological mechanisms are similar to those during REM sleep, although they differ in
properties such as theta-gamma coherence and phase relationship between theta rhythm and CA1 firing
(Poe et al., 2000; Montgomery et al., 2008; Mizuseki et al., 2011). Our study did not simultaneously
assess behavioral states and theta oscillation; therefore, it could not determine the behavioral correlate of
reduced theta power. Given the importance of theta rhythm in spatial encoding and memory, it would be
interesting to evaluate hippocampal theta oscillation in various spatial learning tasks, such as the Barnes
maze test, in mutant mice.

3.5.5. Altered intrinsic membrane properties in vlPAG-projecting GABAergic LPGi neurons
Our study demonstrated the RMP was mildly decreased while the Rm was statistically increased in
mutant vlPAG-projecting GABAergic LPGi neurons. The level of RMP and Rm will influence the
summative effects of input excitatory postsynaptic currents (EPSCs) and inhibitory postsynaptic currents
(IPSCs), the difficulty to reach the action potential threshold, the conductance and open probability of
channels and receptors on cell membrane, and the shunting inhibition from neighbor synapses (Hodgkin,
1947; Offner, 1972, 1973; Schiebe and Jaeger, 1980; Donnelly, 1994; Graves et al., 2012; Paulus and
Rothwell, 2016). Therefore, the lower RMP and higher Rm implies the less excitable and responding of
mutant LPGi neurons, indicating the inhibitory projection from LPGi to vlPAG would be weaker, hence,
strengthen the inhibition on SLD in mutant mice, and consequently reduce the length, frequency, and
duration of REM sleep and influence the expression of REM bouts. The unaltered Rs and Cm in mutant
LPGi neurons means the whole-cell patch clamp recordings were very stable and the surface areas of
LPGi were comparable between wildtype and mutant mice (Schiebe and Jaeger, 1980; Donnelly, 1994;
Gentet et al., 2000).

In contrast, there were no differences in peak and steady state current at each voltage step between
wildtype and mutant vlPAG-projecting GABAergic LPGi neurons, suggesting that both the amounts or
types of fast-responding ion channels (or receptors) and the slow-responding ligand-gated channels (or
metabotropic receptors) were similar between wildtype and mutant LPGi neurons (Magnuson et al., 1995;
Karmazinova and Lacinova, 2010). According to the previous results, the differences from RMP and Rm
48

may result from the alterations of sodium, potassium, calcium, or chloride leak channels, ion pumps
(transporters), or ion exchangers in resting state of LPGi neurons (Yu and Choi, 1997; Gadsby, 2009;
Ren, 2011). Further individual dissections and investigations of these leak channels and pumps would
provide more precise answers for altered intrinsic membrane properties in vlPAG-projecting GABAergic
LPGi neurons. In addition, other REM-on centers such as SLD, dorsal paragigantocellular nucleus
(DPGi), and MCH also contain GABAergic neurons projecting to vlPAG GABAergic neurons (Sapin et
al., 2009; Clement et al., 2011; Luppi et al., 2012; Sirieix et al., 2012; Luppi et al., 2013). Our future
targets are the alterations of intrinsic membrane properties and synaptic transmission of these REM-on
neurons.

In summary, this study uncovered a series of sleep and sleep-related perturbations in chr7qF3 mice. We
speculate that these phenotypes arise from altered functions of the circuitries regulating sleep, arousal,
and rhythmic activity of the brain. Given the fundamental functions of sleep in memory consolidation
and synaptic homeostasis in both rodent and human, the abnormalities observed in a mouse model of the
human chr16p11.2 may have significant clinical implications. Sleep studies in patients with chr16p11.2
microdeletion is needed to confirm and expand our observations. The results can be highly relevant to
understanding the potential role of sleep dysfunction in a wide range of neurodevelopmental disorders
and to inform effective treatment in individuals with chr16p11.2 microdeletion.

49

3.6. Figures, tables, and legends

Figure 3.1. Reduced NREM and REM sleep, and increased wakefulness in mutant mice.
(A-D) Mutant mice exhibited increased wakefulness time (A), reduced total sleep time (B), reduced NREM sleep
time (C), and reduced REM sleep time (D) (n = WT: 10 mice; Mut: 9 mice). (E-F) The ratios of REM to total
sleep time (E), and REM to NREM sleep time (F) were reduced in mutant mice. (G-J) The 2-hr time courses of
wake (G), total sleep (H), NREM sleep (I), and REM sleep (J) (n = WT: 10 mice; Mut: 9 mice). In all figures
described in this study, data were presented as Mean ± SEM. Numbers in parentheses represent those of neurons
(1st number) and mice (2nd number). Statistical significance is determined by two-tailed, unpaired Student’s t-test
for all panels. *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001.
Wake
Total time (min)
0
400
24Hr Day
200
600
800
1000
(A)
Night
****
WT (10)
Mut (9)
**** **
Sleep
Total time (min)
0
400
24Hr Day
200
600
800
1000
(B)
Night
**** **** **
NREM
Total time (min)
0
400
24Hr Day
200
600
800
1000
(C)
Night
**** **** *
REM
Total time (min)
0
40
24Hr Day
20
60
80
100
(D)
Night
**** **** ****
WT (10)
Mut (9)
WT (10)
Mut (9)
WT (10)
Mut (9)
(E) (F)
REM/Sleep
Total time ratio (%)
0
8
24Hr Day
4
12
16
20
Night
**
WT (10)
Mut (9)
*** ***
REM/NREM
Total time ratio (%)
24Hr Day Night
WT (10)
Mut (9)
0
8
4
12
16
20
** *** ***
(G)
(J)
0
50
100
150
0
50
100
150
Time (min)
0 2 4 6 8 10 12 14 16 18 20 22 24
0
10
20
Time (min)
0 2 4 6 8 10 12 14 16 18 20 22 24
5
15
Time (min)
Wake Sleep
NREM REM
* *
0 2 4 6 8 10 12 14 16 18 20 22 24
* * * * * * * * * *
* * * * * * * * * * * *
* * * * * *
* * * * * * * *
* *
* * * * * *
* * * * * * *
* * * * * * *
* * * * * * * * *
0
50
100
Time (min)
0 2 4 6 8 10 12 14 16 18 20 22 24
(H)
(I)
Zeitgeber time (hr) Zeitgeber time (hr)
Zeitgeber time (hr) Zeitgeber time (hr)
25
75
WT (10)
Mut (9)
WT (10)
Mut (9)
WT (10)
Mut (9)
WT (10)
Mut (9)
*
50

Figure 3.2. Bout analysis of REM and NREM sleep demonstrated impaired NREM to REM transition and
REM maintenance in mutant mice.
(A-C) Bout numbers of wake (total sleep) (A), NREM sleep (B), and REM sleep (C) (n = WT: 10 mice; Mut: 9
mice). (D) REM/NREM bout number ratio. (E-H) Bout durations of wake (E), total sleep (F), NREM sleep (G),
and REM sleep (H) (n = WT: 10 mice; Mut: 9 mice). (I-L) Distributions of REM bout number (I, K) and
normalized REM bout percentage (J, L) as a function of REM duration during the day (I, J) and night (K, L) (n
= WT: 10 mice; Mut: 9 mice).
(A) (B) (C) (D)
Wake (Sleep)
Bout number (#)
0
100
24Hr Day
50
150
200
250
(E)
Night
***
(F)
NREM
(G)
REM
Bout number (#)
0
40
24Hr Day
20
60
80
(H)
Night
*** ****
ns ns
Bout number (#)
0
100
24Hr Day
50
150
200
250
Night
***
ns ns
WT (10)
Mut (9)
WT (10)
Mut (9)
WT (10)
Mut (9)
Wake
Bout duration (sec)
0
400
24Hr Day
200
600
800
1000
Night
**
WT (10)
Mut (9)
**** *
Sleep
Bout duration (sec)
0
100
24Hr Day
50
150
200
250
Night
WT (10)
Mut (9)
ns ns ns
NREM
Bout duration (sec)
0
100
24Hr Day
50
150
200
250
Night
REM
Bout duration (sec)
0
40
24Hr Day
20
60
80
100
Night
** *** ***
WT (10)
Mut (9)
WT (10)
Mut (9)
ns ns ns
*
REM/NREM
Bout number ratio (%)
24Hr Day Night
WT (10)
Mut (9)
0
10
20
30
40
* * *
(I)
(L)
(J)
(K)
REM Distribution (day)
Number of epidose (#)
0 64 128 160 192 224 256
0
5
10
15
20
Bout duration (sec)
32 96
* * * * * * * * * * * *
* * * * *
WT (10)
Mut (9)
REM Distribution (day)
Percentage of total (%)
0
20
30
40
50
Bout duration (sec)
10
0 64 128 160 192 224 256 32 96
* * * * * * * * * * *
WT (10)
Mut (9)
REM Distribution (night)
Number of epidose (#)
0
1
2
3
4
Bout duration (sec)
5
0 64 128 160 192 224 256 32 96
* * * * * * * * * * *
* * * * *
WT (10)
Mut (9)
REM Distribution (night)
Percentage of total (%)
0
20
30
40
50
Bout duration (sec)
10
0 64 128 160 192 224 256 32 96
*
WT (10)
Mut (9)
* *
51

Figure 3.3. Power spectral analysis of oscillation classes and 1-Hz bins.
(A-C) Normalized day-time spectral analysis of oscillation classes during wake (A), NREM sleep (B), and REM
sleep (C). (D-F) Normalized night-time spectral analysis of oscillation classes during wake (D), NREM sleep (E),
and REM sleep (F) (n = WT: 9 mice; Mut: 9 mice). (G-I) Normalized day-time spectral analysis of 1-Hz bin during
wake (G), NREM sleep (H), and REM sleep (I). (J-L) Normalized night-time spectral analysis of 1-Hz bin during
wake (J), NREM sleep (K), and REM sleep (L) (n = WT: 9 mice; Mut: 9 mice).
Day-Wake
Relative Power (% Total Power)
0
20
10
30
40
50
**
(A)
ns
Day-REM
Relative Power (% Total Power)
0
20
10
30
40
50
**
(C)
ns ns ns
*** *
ns ns
Day-NREM
Relative Power (% Total Power)
0
20
10
30
40
50
(B)
ns ns
*
ns ns ns
Night-Wake
Relative Power (% Total Power)
0
20
10
30
40
50
***
(D)
ns
Night-REM
Relative Power (% Total Power)
0
20
10
30
40
50
**
(F)
ns ns ns
* * *
ns ns
Night-NREM
Relative Power (% Total Power)
0
20
10
30
40
50
(E)
ns ns ns ns ns ns ns
Day-Wake
Relative Power (% Total Power)
0
10
5
15
20
(G)
10 20 30 40 50 60
Frequency (Hz)
Day-NREM
Relative Power (% Total Power)
0
10
5
15
20
(H)
10 20 30 40 50 60
Frequency (Hz)
Day-REM
Relative Power (% Total Power)
0
10
5
15
20
(I)
10 20 30 40 50 60
Frequency (Hz)
Night-Wake
Relative Power (% Total Power)
0
10
5
15
20
(J)
10 20 30 40 50 60
Frequency (Hz)
Night-NREM
Relative Power (% Total Power)
0
10
5
15
20
(K)
10 20 30 40 50 60
Frequency (Hz)
Night-REM
Relative Power (% Total Power)
0
10
5
15
20
(L)
10 20 30 40 50 60
Frequency (Hz)
WT (9)
Mut (9)
WT (9)
Mut (9)
WT (9)
Mut (9)
WT (9)
Mut (9)
WT (9)
Mut (9)
WT (9)
Mut (9)
***
*
* * *
*** ************
* *** * *************************** * **
** ** ****** ***
* **
*
**
**
*
**********
********
**** ** * **
**
*
***
**
*
WT (9)
Mut (9)
WT (9)
Mut (9)
WT (9)
Mut (9)
WT (9)
Mut (9)
WT (9)
Mut (9)
WT (9)
Mut (9)
Delta
Low Theta
Theta
Alpha
Beta
Gamma
Delta
Low Theta
Theta
Alpha
Beta
Gamma
Delta
Low Theta
Theta
Alpha
Beta
Gamma
Delta
Low Theta
Theta
Alpha
Beta
Gamma
Delta
Low Theta
Theta
Alpha
Beta
Gamma
Delta
Low Theta
Theta
Alpha
Beta
Gamma
ns ns
* * * * * * *
*
**
*
*
52

Figure 3.4. Altered intrinsic membrane properties but normal I-V curve in mutant vlPAG-projecting
GABAergic LPGi neurons.
(A) Schematic location of dorsal pons highlighting vlPAG. (B) A representative fluorescent image showing
bilateral vlPAG injected with CTB-488. LDT and DRN were shown as reference. (C) Schematic location of
medulla demonstrating LPGi in ventral medulla. (D) A representative fluorescent image illustrating unilateral
LPGi labeled with retrograde CTB-488. Gigantocellular reticular nucleus (Gi), Inferior olivary nucleus (IO), and
nucleus ambiguus (Amb) were shown as reference. (E) A representative fluorescent image showing a CTP-488
labeled LPGi neuron under patch clamp recording, inset highlighted the neuron. (F) Post-recording detection of a
600
400
800
200
0
Rm (MOhm)
Membrane resistance
WT (18/6)
Mut (15/5)
100
50
200
0
Rs (MOhm)
Series resistance
ns
WT (18/6)
Mut (15/5)
50
25
100
0
Cm (pF)
Membrane capacitance
ns
WT (18/6)
Mut (15/5)
2.0
1.0
3.0
-1.0
Current (nA)
IV curve (peak current)
WT (18/6)
Mut (15/5)
Voltage (mV)
0.0 50 100
-2.0
-50 -100 Current (nA)
IV curve (steady state)
WT (18/6)
Mut (15/5)
Voltage (mV)
0.0 50 100 -50 -100
0.2 0.3 0.4 0.5 0.1
Amplitude (nA)
sec
IV curve (WT)
0.6
4.0
3.0
2.0
1.0
0.0
-1.0
-2.0
0.2 0.3 0.4 0.5 0.1
Amplitude (nA)
sec
IV curve (Mut)
0.6
(J) (K) (L)
(M)
(N) (O)
-20
-40
0
-60
-80
RMP (mV)
Resting membrane potential
***
WT (18/6)
Mut (15/5)
(I)
150
*
75
4.0
3.0
2.0
1.0
0.0
-1.0
-2.0
2.0
1.0
3.0
-1.0
4.0
(F) (G) (H) (E)
(B) (C) (D) (A)
LPGi
Amb
IO
Gi
vlPAG vlPAG
LDT LDT
DRN
53

patched neuron with AMCA-conjugated avidin. (G) Post-recording verification of Cre expression in the same
patched neuron as in (E, F). (H) A merged image from (F, G), colocalization of AMCA signal and Cre expression
confirmed that the patched neuron was indeed GABAergic. (I) RMP was mildly reduced in mutant LPGi neurons.
(J) Rm was increased in mutant LPGi neurons. (K, L) Rs and Cm were indistinguishable between wildtype and
mutant LPGi neurons. (M) Representative traces of I-V curve in wildtype and mutant LPGi neurons. Both peak
(denoted by arrows) and steady state responses (the last 100 ms denoted by horizontal bars) were subjected to
analysis. (N-O) No statistical differences were present between wildtype and mutant LPGi neurons in peak (M)
and steady state (N) current responses. Arrows and insets in (E-H) denoted and highlighted a patched neuron.
Scale bars are 200 μm in (A-D), and 30 μm in (E-H) (n = WT: 18 neurons from 6 mice; Mut: 15 neurons from 5
mice).
54

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Abstract (if available)

Abstract The pathophysiology of neurodevelopmental disorders is often observed early in infancy and toddlerhood. Mouse models of syndromic disorders have provided insight regarding mechanisms of action, but most studies have focused on characterization in juveniles and adults. Insight into developmental trajectories, particularly those related to circuit and synaptic function, will likely yield important information regarding disorder pathogenesis that leads to symptom progression. Chromosome 16p11.2 microdeletion is one of the most common copy number variations associated with a spectrum of neurodevelopmental disorders. Yet, how haploinsufficiency of chr16p11.2 affects early synaptic maturation and function is unknown. To address this knowledge gap, the present study focused on three key components of circuit formation and function—basal synaptic transmission, local circuit function, and maturation of glutamatergic synapses—in developing hippocampal CA1 neurons in a chr16p11.2 microdeletion mouse model. The data demonstrate increased excitability, imbalance in excitation and inhibition, and accelerated maturation of glutamatergic synapses in heterozygous deletion mutant CA1 neurons. Given the critical role of early synaptic development in shaping neuronal connectivity and circuitry formation, these newly identified synaptic abnormalities in chr16p11.2 microdeletion mice may contribute to altered developmental trajectory and function of the developing brain. ❧ Sleep disturbance is very prevalent among patients with neurodevelopmental and neuropsychiatric disorders, such as autism spectrum disorders (ASDs) and attention deficit-hyperactivity disorder (ADHD). Evidence from genome-wide association studies indicates that chromosomal copy number variations (CNVs) are associated with increased prevalence of these neurodevelopmental disorders. Several studies on mouse models of chr16p11.2 microdeletion have demonstrated impairments in synaptic transmission and local circuitry function in the hippocampus and striatum. However, it has not been adequately addressed if chr16p11.2 microdeletion is associated with system level abnormalities in mice, such as sleep and neuronal oscillation. To address this knowledge gap, the present study investigated sleep architectures and oscillation patterns in a mouse model of human chr16p11.2 microdeletion. Polysomnographic recording revealed reduced non-rapid eye movement (NREM) sleep and rapid eye movement (REM) sleep, decreased number of REM bouts, shortened REM epoch duration, and altered NREM to REM transition in heterozygous mutant mice. The mutant mice also showed significant alterations in EEG oscillation patterns, involving several frequency classes in different vigilant states. In addition, the ventrolateral periaqueductal gray matter (vlPAG)-projecting GABAergic neurons in lateral paragigantocellular nucleus (LPGi), one of the main REM-on center, from heterozygous mutant mice were less excitable compared to wildtype neurons. In sum, our study demonstrated significant differences in sleep architecture, oscillation patterns, and candidate nucleus in the chr16p11.2 mouse model.

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A million-plus neuron model of the hippocampal dentate gyrus: role of topography, inhibitory interneurons, and excitatory associational circuitry in determining spatio-temporal dynamics of granul...

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Core Title Characterizing the hippocampal synaptic and sleep abnormalities of a mouse model of human chromosome 16p11.2 microdeletion

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