Synaptic mechanism underlying development and function of neural circuits in rat primary auditory cortex

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SYNAPTIC MECHANISM UNDERLYING
DEVELOPMENT AND FUNCTION OF NEURAL
CIRCUITS IN RAT PRIMARY AUDITORY CORTEX

by
Yujiao Jennifer Sun

A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(PHYSIOLOGY AND BIOPHYSICS)
May 2013

Copyright 2013 Yujiao Jennifer Sun
2

Dedication
To my parents, for their unconditional support and
faith in me throughout all these years.

3

Acknowledgements
I owe my deepest gratitude to Dr. Li I Zhang, a talented scientist and great mentor, for his
patient guidance, constructive critiques, and encouragement towards my PhD training. He
has made available his support in a number of ways, enabling me to develop an
enthusiasm and deep understanding of the scientific subject as well as independent
thinking and research skills. I would also like to express my very great appreciation to
Dr. Huizhong Whit Tao, for her invaluable suggestions and warmhearted assistance both
academically and personally. I am always indebted to Dr. Zhang and Dr. Tao for
providing me this nourishing environment for my PhD training.
Special thanks should be given to my committee members, Dr. Sarah Bottjer, Dr. Robert
Chow, and Dr. Robert Farley, whose thoughtful advice enabled me to keep on track for
my qualifying exam and thesis defense. I am really grateful to them for their generous
support in my pursuit of an academic career.
This thesis work would not have been done without the help from my colleagues. Dr.
Baohua Liu gave me great guidance and sincere suggestions both in experimental
techniques and research methodology, Dr. Guangying Wu was the very first person who
helped me starting my own projects and his previous work contributed a lot, and Dr. Yi
Zhou, Leena Ali, and Kim Young helped me with many technical issues I encountered.
Finally, I feel blessed to have my family always standing by my side and supporting me
unconditionally. Their love and understanding make me walk through laugh and tears.
4

Table of Contents

Dedication .......................................................................................................................2
Acknowledgements .........................................................................................................3
List of Figures .................................................................................................................7
List of Tables...................................................................................................................8
Abstract ...........................................................................................................................9

1 Chapter 1: Introduction to Synaptic Circuitry Processing ...................................... 11
1.1 Processing Mechanism in Cortical Circuitry .................................................... 11
1.2 Principles of Electrophysiology ....................................................................... 12
1.2.1 Extracellular Single-unit and Multi-unit Recording..................................... 13
1.2.2 Current-clamp and Voltage-clamp Whole-cell Recording ........................... 14

1.3 Overview of Auditory System ......................................................................... 15
1.3.1 Animal Model for Circuitry Study .............................................................. 15
1.3.2 Auditory Pathway ....................................................................................... 15
1.3.3 Receptive Field of Auditory Neuron ........................................................... 17
1.3.4 Organization of Auditory Cortex ................................................................ 17

2 Chapter 2: Synaptic Mechanism of Corticofugal Neurons in Layer 5...................... 20
2.1 Background and Introduction........................................................................... 20
2.2 Methods and Materials .................................................................................... 23
2.2.1 Animal Preparation and Maintenance ......................................................... 23
2.2.2 Auditory Stimulation .................................................................................. 24
2.2.3 In-vivo Electrophysiological Recording ...................................................... 24
2.2.4 Cortical Silencing ....................................................................................... 25
2.2.5 Histochemistry ........................................................................................... 26
2.2.6 Data Analysis ............................................................................................. 27
2.2.7 Computational Modeling ............................................................................ 30
2.2.8 Statistical Analysis ..................................................................................... 31

2.3 Results............................................................................................................. 31
5

2.3.1 Intrinsic-Bursting and Regular-Spiking Neurons in Layer 5 ........................ 31
2.3.2 Subthreshold Responses Underlying the Broad Tuning of IB Neurons ........ 34
2.3.3 Excitatory and Inhibitory Inputs to Layer 5 Neurons................................... 39
2.3.4 A Synaptic Mechanism Underlying Broad Frequency Tuning..................... 43
2.3.5 Temporal Properties of Synaptic Inputs to L5 Neurons ............................... 44
2.3.6 Exploring the Layer 5 Circuits .................................................................... 47
2.3.7 Fast-spiking Inhibitory Neurons in Layer 5 ................................................. 51

2.4 Discussion ....................................................................................................... 54
2.4.1 Intrinsic-Bursting and Regular-Spiking Pyramidal Neurons in L5 .............. 54
2.4.2 Broadly-tuned Excitation with Narrowly-tuned Inhibition .......................... 55
2.4.3 Potential Feedforward Circuits in Layer 5................................................... 57
2.4.4 Functional Implications .............................................................................. 59
2.5 Summary ......................................................................................................... 60
3 Chapter 3: Synaptic Mechanism of Developmental Refinement in Layer 4 Neurons
62
3.1 Background and Introduction........................................................................... 62
3.2 Methods and Materials .................................................................................... 63
3.2.1 Animal Preparation .................................................................................... 63
3.2.2 In vivo Whole-Cell Voltage-Clamp Recording And Loose-Patch/Cell-
Attached Recording ............................................................................................... 64
3.2.3 Data Analysis ............................................................................................. 66

3.3 Results............................................................................................................. 69
3.3.1 Synaptic Models for Spiking Receptive Field Refinement of Sensory Neuron
during Development ............................................................................................... 69
3.3.2 High-Threshold but Balanced Synaptic Responses in Early Age ................. 70
3.3.3 Synaptic Receptive Field of Auditory Neuron at Later Stage ...................... 73
3.3.4 Differential Progression of Synaptic Excitation and Inhibition along
Development .......................................................................................................... 75
3.3.5 Sharpening of Excitatory Inputs Underlying Developmental Refinement of
Spike Receptive Field in A1 ................................................................................... 78

3.4 Summary ......................................................................................................... 80
3.5 Future Direction .............................................................................................. 82
6

3.5.1 Cortical Synaptic Mechanism Underlying Plasticity Induced by Early
Deprivation of Sound Inputs .................................................................................. 82
3.5.2 Contribution of Thalamocortical Excitation and Intracortical Excitation
during Developmental Refinement ......................................................................... 87

References ..................................................................................................................... 92

7

List of Figures
Figure 1.1 Integration of synaptic inputs. ....................................................................... 13
Figure 1.2 Functional and Laminar Organization of auditory cortex. ............................. 18
Figure 2.1 Response properties of RS and IB neurons in layer 5 of the rat A1. .............. 33
Figure 2.2 Subthreshold membrane potential responses of RS and IB neurons. .............. 36
Figure 2.3 Synaptic inputs to RS and IB neurons. .......................................................... 42
Figure 2.4 Temporal properties of synaptic inputs to different types of neurons. ............ 46
Figure 2.5 Direct thalamocortical input to IB neurons. ................................................... 50
Figure 2.6 Properties of fast-spiking inhibitory neurons in layer 5 and potential circuits.53
Figure 3.1The synaptic TRFs shortly after the onset of hearing. ..................................... 71
Figure 3.2 Synaptic TRFs at later developmental stages. ................................................ 74
Figure 3.3 Developmental change in spectral and temporal pattern of excitatory and
inhibitory input .............................................................................................................. 77
Figure 3.4 Synaptic mechanism underlying developmental refinement of spike TRFs in
A1. ................................................................................................................................ 79
Figure 3.5 A neuron from A1 of P30 rat exposed to noise from P9-28. .......................... 85
Figure 3.6 Synaptic inputs of a neuron from a P33 rat exposed to noise from P9-28 ....... 86
Figure 3.7 Revealing pure thalamocortical inputs in neurons with muscimol and
SCH50911. .................................................................................................................... 90
Figure 3.8 RFs of a Neuron Before and After Cortical Silencing. ................................... 91
8

List of Tables
Table 2.1 Comparison of IB and RS cell anatomy and electrphysiological preoperties. . 39
9

Abstract
A major question in brain sciences is how the brain develops into maturation, how it
perceives external sensory stimulation, and how it adapts in responses to the environment.
To address these questions, it is fundamental to dissect the cortical network structure and
its underlying circuitry mechanism. Specifically, in a local circuit, information is
processed vertically within a cortical column where the neuronal connectivity and
functionality are different among cortical layers. Using rat primary auditory cortex (A1)
as the research model, I studied the synaptic mechanism underlying circuitry function and
development by applying in vivo whole-cell patch-clamp recording to record excitatory
and inhibitory synaptic inputs driven by precisely controlled sound stimuli with different
combination of duration, frequency, and intensity.
In the first project of my dissertation, I explored the functional properties of the
corticofugal neurons in layer 5, which are shown to be part of Feedback/corticofugal
projections from A1 and play a role in modulating subcortical processing. I found that
intrinsic-bursting (IB) neurons, the layer 5 corticofugal neurons, exhibited early and
rather unselective spike responses to a wide range of frequencies. The exceptionally
broad spectral tuning of IB neurons was attributable to unusually broad excitatory inputs
with long temporal durations, and inhibitory inputs being more narrowly tuned than
excitatory inputs. This uncommon scenario of excitatory-inhibitory interplay was
attributed initially to a broad thalamocortical convergence onto IB neurons, which also
receive temporally prolonged intracortical excitatory input and feedforward inhibitory
10

input from more narrowly tuned fast-spiking neurons. In contrast, regular-spiking (RS)
neurons in layer 5, which are mainly corticocortical, exhibited sharp frequency tuning
similar as layer 4 pyramidal cells, with the underlying well-matched, more distantly
relayed excitation and inhibition. The functional dichotomy of layer 5 pyramidal neurons
suggests two distinct processing streams. The spectrally and temporally broad synaptic
integration in IB neurons may ensure robust feedback signals to facilitate subcortical
processing in a general manner.
In the second project of my dissertation, I turned to layer 4 neurons to study their
synaptic mechanism underlying progressive refinement of functional receptive fields
during development. In this study, I examined the developmental changes in frequency-
intensity tonal receptive fields (TRFs) of excitatory and inhibitory inputs to test three
potential synaptic circuit models underlying the functional development. I found rather
balanced excitation and inhibition at the earliest stage (P12) that tone-evoked cortical
responses can be detected, which suggests that a hardwired feedforward circuit exists
prior to the incoming of auditory input. During development, the spectral range of
excitatory and inhibitory inputs is initially broadened and then persists into adulthood.
The latter phase is accompanied with a significant functional modification of excitatory
inputs, resulting in a sharpening of excitatory tuning, and relatively broadly tuned
inhibition. Thus, the functional refinement of cortical neurons during development is
marked by a slight breakdown of pre-balanced excitation and inhibition. These results
suggest that functional refinement of cortical TRFs may not require elimination of
presynatpic inputs, but can be achieved through a fine adjustment of synaptic strengths.
11

Chapter 1: Introduction to Synaptic Circuitry Processing
1.1 Processing Mechanism in Cortical Circuitry
A major goal of neuroscience research is to understand how the mammalian brain
functions: how perception is generated, how behavior is controlled to adapt in response to
the environment during development, and how changes in brain structure result in
neurological and psychiatric disease. To address these questions, it is a fundamental step
to understand how the underlying circuitry is constructed and intertwined.
This daunting task can be made simpler because even the most complex circuits appear to
be based on functional modules or units that are stereotypical in their organization. Take
the example of the act of reading (Figure 1.1), there are several circuitry systems and
pathways involved. First, the sensory pathway, visual system, enables us to see the word,
and then there are central connections reaching to the frontal lobe for the comprehension
of the meaning. Also there is the descending motor pathway to control the eye movement
as we scan the page. Within each pathway, there are several centers or local circuits
where the information is received and processed vertically and horizontally and then
passed onto the next levels. And the building block within a local circuit is the neuron,
which receives inputs from its dendrites, integrates them in the somatic body, and decides
whether or not to generate a train of spike response and send it to the next group of
neurons.
12

And neurons communicate with each other through a specialized structure named
synapse, through which they can excite/inhibit the postsynaptic neurons by triggering an
electrical response in the latter.
In order to understand the overall function of the brain circuit, we need to investigate at
each of these levels using a variety of techniques and then analyze in an integrated
fashion. In my PhD studies, I have been focusing on the level of local circuit to dissect
the neural circuitry by studying the functional patterns of individual neurons and the
underlying synaptic basis shaping their response properties.

1.2 Principles of Electrophysiology
A single neuron can receive diverse inputs, excitatory and inhibitory, local and long-
range, through thousands of synapses made upon it by other neurons, then integrate those
inputs as the change of membrane potential, and decide whether or not to generate the
spike output to other neurons (Figure 0.1). With the technique of electrophysiology, we
can measure the intracellular or extracellular electrical activity of targeted neurons.
13

Figure 0.1 Integration of synaptic inputs.
A targeted neuron (excitatory neuron) receives integrate presynaptic inputs as the change of the
membrane potential, and, if passing the threshold, generate spiking responses to excite neurons
through synapses onto other neurons.

1.2.1 Extracellular Single-unit and Multi-unit Recording
Under the extracellular mode, the electrode tip is in continuity with the extracellular
space to pick up the field potentials outside cells. By advancing a fine-tipped
microelectrode close enough to a targeted neuron and loosely attach to it, we could
observe action potentials or spike output, which is generally considered to be the activity
of this one single cell. And this is termed single-unit recording.
Depending on the preparation and precise placement, an extracellular configuration may
also pick up the activity of several nearby cells simultaneously, and this is termed multi-
unit recording.
14

1.2.2 Current-clamp and Voltage-clamp Whole-cell Recording
After approaching a cell with a microelectrode to form a high resistance seal, cell
membrane can be broken by applying a small negative pressure, so that the
microelectrode can be inserted into the cell and electrolyte within the pipette may be
brought into fluid continuity with the cytoplasm to form a whole-cell environment. This
whole-cell mode allows very stable and direct recording of intracellular electrical activity
of a single cell.
Current-clamp technique allows us to measure the membrane potential change of targeted,
under normal condition or in response to injected current through the recording pipette.
Not only it could record the action potential, it could reveal the subthreshold activities of
the recorded neuron.
Voltage-clamp technique allows us to measure how much ionic current crosses a cell's
membrane at any given voltage. Because the excitatory ionotropic ligand-gated
neurotransmitter receptors, including glutamate receptors AMPA NMDA, are
nonselective cation channels that pass Na
+
and K
+
in nearly equal proportions, the current
mediated by these excitatory transmitters has an equilibrium potential close to 0 mV. On
the other hand, the inhibitory ionotropic ligand-gated neurotransmitter receptors that
carry Cl
-
, such as GABA
A
and glycine receptors, have equilibrium potentials close to the
resting potential (approximately -70 mV) in neurons. In this way, we would be able to
separately record the excitatory/ inhibitory synaptic inputs by clamping the membrane
voltage at the equilibrium potential of the other source of inputs.
15

1.3 Overview of Auditory System
1.3.1 Animal Model for Circuitry Study
The rat auditory cortex will be used as a primary model because it codes and processes
time-varying signals which can be precisely controlled, and thus is ideal for studying
functional circuits. Moreover, the auditory system is well developed in rats, with similar
anatomical, representational, and processing properties as in higher mammals, allowing
the generalization of circuitry principles. Last but not least, audition is essential for
communication and social behavior in rodents, so that studies of auditory cortical
processing will bear direct behavioral relevance.

1.3.2 Auditory Pathway
Sound is a sequence of mechanical waves that propagates through compressible media
such as air. The sound waves are picked up, amplified, and converted into electrical
impulses in the peripheral auditory system: the outer, middle and inner parts of the ear.
The outer ear consists of the pinna, concha, and external auditory meatus (ear canal),
which collects sound and sends it to the tympanic membrane (ear drum), the entrance of
the middle ear. The resulting movements of the eardrum are transmitted through the three
middle-ear ossicles (malleus, incus and stapes), where the sound pressure is amplified
through hydraulic mechanisms. The stapes is connected to the inner ear through a
16

window in the cochlea filled with liquid, where vibration is sensed and transformed into
electrical signals by the hair cells along the basilar membrane. The membrane vibrates in
response to sound, with the apex stimulated maximally by low frequency sound and the
base stimulated maximally by high frequency sound. This ordered projection of sound
input is named tonotopy, a particular case of topographic organization universal in all
sensory systems.
The neurotransmitter released at the basal end of the hair cells elicits an action potential
in the dendrites of auditory nerves, through which the recoded auditory information is
relayed to central auditory pathways: brainstem, midbrain, and thalamus, and primary
auditory receiving area within the neocortex.
Cochlear nuclei in the brainstem can be split into two regions: the ventral cochlear
nucleus (VCN), which primarily serves as a relay station for ascending auditory
information, and the dorsal cochlear nucleus (DCN) which not only projects to the central
nucleus of the Inferior Colliculus (ICC) but also receives efferent innervation from higher
order stations. Inferior Colliculus (IC) is the auditory center in the midbrain, which
integrates inputs from different sources, including olivary complex, lemniscal complex
and cochlear nuclei. They send their axons to the medial geniculate body (MGB) in the
thalamus. The MGB has three major divisions: ventral (MGBv), dorsal (MGBd) and
medial (MGBm). While the MGBd and MGBm also receive information from non-
auditory pathways, the MGBv provides major innervations to the primary auditory cortex
(A1). And from the auditory cortex, the afferent projection runs down to the MGB and IC,
17

which in turn modulates the downstream information processing at lower auditory
stations.

1.3.3 Receptive Field of Auditory Neuron
In the central auditory pathway, each neuron responds to sound stimulation with different
parameters. As a form of wave, the two most significant parameters of a tonal stimulation
are frequency and amplitude (intensity). For a single neuron, it responds to one specific
tonal frequency at the lowest intensity level, which is defined as its characteristic
frequency (CF) and intensity threshold. With higher intensity, it typically responds to a
wider range of frequencies, thus exhibiting a V shaped receptive field in the frequency-
intensity tuning map.

1.3.4 Organization of Auditory Cortex
As in other sensory system, auditory pathway has a topographic map well preserved from
peripheral site to auditory cortex. In the rat auditory cortex, there are five characterized
fields (Polley DB et al, 2007) with different features of tonotopic gradient, spectral tuning,
intensity tuning, and onset responses: primary auditory cortex (A1), the posterior auditory
field (PAF), the anterior auditory field (AAF), the ventral auditory field (VAF), and the
suprarhinal auditory field (SRAF). In particular, multiunit recordings confirmed that A1
18

exhibited well-tuned and short-latency responses, where the neural characteristic
frequency varies systematically from low to high along a posterior-to-anterior gradient
(Figure 0.2a).
Across cortical depth, there is a six-layered structure stereotypical in all cerebral cortices,
each with a different composition in terms of neural type, connectivity, and laminar
processing mechanism (Figure 0.2b).. Among them, layer 4 is the main target of
thalamocortical afferents, also known as the recipient layer. With different types of
stellate and pyramidal neurons, it receives the majority of excitatory thalamic inputs and
passes the information onto neurons within the same layer and other layers in the cortex.

Figure 0.2 Functional and Laminar Organization of auditory cortex.
a. Tonotopic map in rat auditory cortex (adapted from Polley et al, 2007) showing A1 exhibiting a
tonotopic gradient along the surface of the cortex, with colormap representing neural characteristic
frequency from lateroposterior to dorsal anterior; b. laminar organization in neocortex
demonstrating typical neurons in each layer with arrows representing input/ output sources.

19

Layer 2/3 contains predominantly small and medium-size pyramidal neurons, which in
turn receives innervation from layer 4 and send output to other cortical areas including
the contralateral cortices. Layer 5 is best known for their large pyramidal neurons, which
receives inputs from supragranular layers through their extended dendritic tufts and is the
principal source of subcortical efferent with the axons leaving the cortex and running
down to lower station, e.g. the midbrain, the basal ganglia, the brain stem and the spinal
cord. Layer 6 sends efferent fibers to the thalamus, establishing a very precise reciprocal
interconnection between the cortex and the thalamus.
This six-layer structure is stereotyped in the neocortex, with small variation along
different cortical systems, and thus is an ideal model to study the circuitry processing
mechanism in the local circuit.
20

Chapter 2: Synaptic Mechanism of Corticofugal Neurons in
Layer 5
1.4 Background and Introduction
Sensory systems often consist of both ascending and descending pathways. The
descending projections of sensory cortices, i.e. corticofugal projections, emanate from
layer 5 and layer 6 (Hoogland et al., 1987; Rouiller and Welker 1991; Deschê nes et al.
1994; Ojima 1994; Sherman and Guillery 2002; Rouiller and Durif, 2004). In the
auditory system, several lines of evidence suggest that layer 6 of the primary auditory
cortex (A1) projects back topographically to the first order thalamic nucleus, the ventral
medial geniculate body (MGBv), and may play a gain control function in the
transmission of information from the thalamus to the A1 (Villa et al., 1991; Ojima 1994;
Yu et al., 2004). On the other hand, layer 5 of the A1 projects to higher order thalamic
nuclei that innervate the secondary auditory cortex, driving responses in these thalamic
areas and forming an indirect route for the transfer of information from the A1 into the
higher order cortex (Ojima, 1994; Bourassa et al., 1995; Guillery, 1995; Sherman and
Guillery 2002). Layer 5 also projects to subthalamic nuclei such as the inferior colliculus
and cochlear nucleus (Games and Winer, 1988; Moriizumi and Hattori, 1991; Weedman
and Ryugo, 1996; Winer et al., 1998). By activating and silencing corticofugal
projections with electrical stimulation and pharmacological methods respectively,
previous studies have demonstrated that corticofugal projections are capable of
21

modulating auditory functions of subcortical neurons, e.g. by sharpening or shifting their
tuning curves in the frequency and time domains (Yan and Suga 1996; Zhang et al. 1997;
Zhang and Suga 1997). The corticofugal projections may also play an important role in
mediating learning/conditioning induced changes of auditory representations (Suga and
Ma, 2003; Zhang and Yan, 2008). Despite the demonstration of a functional involvement
of corticofugal projections, little is known about how these effects of corticofugal
projections on subcortical processing are achieved. To address this issue it is essential to
understand what information is specifically processed in corticofugal neurons and what
information is carried by the output corticofugal projections.
Based on morphological and electrophysiological properties, previous studies have
categorized two classes of layer 5 projection neurons in sensory cortices (Mitani et al.,
1985; Games and Winer, 1988; Larkman and Mason, 1990; Agmon and Connors, 1989;
Chagnac-Amitai et al., 1990; Kasper et al. 1994; Deschê nes et al., 1994; Nicoll et al.,
1996; Markram et al., 1997; Zhu and Connors, 1999; Hefti and Smith, 2000; Hattox and
Nelson, 2007). The intrinsic-bursting (IB) neurons are characterized by large cell bodies
and thick tufted apical dendrites reaching layer 1. They contribute to the corticofugal
projections to subcortical and subthalamic nuclei (Kelly and Wong, 1981; Games and
Winer, 1988; Ojima et al., 1992). The regular-spiking (RS) neurons exhibit smaller sized
somas and do not fire bursts. Their apical dendrites are slender and shorter, with fewer
oblique branches that end without terminal tufts. Their axons contribute to callosal
connections to the sensory cortex in the other hemisphere (Ruttgers et al., 1990; Games
and Winer 1988; Winer and Prieto, 2001). The auditory processing properties of the two
22

types of layer 5 (L5) projection neurons have not been well characterized. A few studies
suggest that layer 5 contains units that appear more broadly tuned than those in middle or
superficial layers (Abeles and Goldstein, 1970; Volkov and Galazjuk, 1991; Turner et al.,
2005; Wallace and Palmer, 2008; Atencio and Schreiner, 2010). However, the type of
recorded neurons was not well defined in these studies. In addition, the synaptic circuits
underlying the functions of L5 neurons are yet to be elucidated, although studies in
several cortical areas have shown that L5 neurons receive intracortically relayed input
from various layers (Briggs and Callaway, 2005; Yu et al., 2008; Llano and Sherman,
2009; Qiu et al., 2011), and that they may also receive ascending input from the thalamus
(Hefti and Smith, 2000; Wallace and Palmer, 2008; de Kock et al., 2007). In this study,
we utilized a set of in vivo patch-clamp recording techniques to investigate the frequency
representation of L5 neurons and the underlying synaptic inputs. We found that IB
neurons possessed much broader frequency-intensity tonal receptive fields (TRFs) than
RS and L4 pyramidal neurons. The weak selectivity of IB neurons can be attributed to an
unusually broad range of excitatory inputs they receive, and their inhibitory inputs
uncommonly being more narrowly tuned than their excitatory inputs. The wide range of
excitation in IB neurons is due to a broad convergence of thalamocortical inputs to these
neurons, and the narrower inhibition can be attributed to the relatively narrow tuning of
fast-spiking inhibitory neurons in layer 5. In addition, the temporal duration of excitatory
input to IB neurons is much broader than RS and L4 pyramidal neurons, resulting in long
lasting tone-evoked membrane depolarization responses. The broad spectral and
temporal integration of IB neurons indicates that L5 corticofugal projections may not
23

carry very specific auditory information, but the robust and fast responses of IB neurons
to sound stimuli suggest their potential roles in facilitating subcortical processing.

1.5 Methods and Materials
1.5.1 Animal Preparation and Maintenance
All experimental procedures used in this study were approved by the Animal Care and
Use Committee at the University of Southern California. Female adult Sprague-Dawley
rats (14-18 weeks) were anesthetized with ketamine (45mg/kg) and xylazine (6.4mg/kg),
followed by ketamine (10mg/kg) alone if needed. The body temperature was maintained
at 37.5C with a homeothermic blanket system (Harvard Apparatus). Atropine sulfate
(0.1mg/kg) and dexamethasone (0.25mg/kg) were applied to reduce brain edema and
viscosity of bronchial secretions, respectively. A tracheotomy and a cisternal draining
were performed to further minimize the bronchial secretion and brain edema. The
auditory cortex in the right hemisphere was exposed with craniotomy and durotomy, and
the ipsilateral ear canal was plugged with a cotton ball. Saline and ringer solution were
administered throughout the experiments to ensure the animal condition. Artificial
cerebrospinal fluid ACSF (in mM: NaCl 124, NaH
2
PO
4
1.2, KCl 2.5, NaHCO
3
24,
glucose 20, CaCl
2
2, MgCl
2
1) was applied on the cortical surface to maintain the cortical
hydration when necessary.
24

1.5.2 Auditory Stimulation
Experiments were carried out in a sound-insulated booth (Acoustic System).
Pseudorandom pure tone pips (50ms duration, 3ms ramp) were delivered through a
calibrated free field speaks towards the left ear, at 71 frequencies (0.5-64kHz at 0.1-
octave interval) and 8 sound intensities (0-70dB sound pressure level, 10 dB increments).

1.5.3 In-vivo Electrophysiological Recording
Extracellular multiunit recordings were made with parylene-coated tungsten electrode (2
M  ; FHC) at 450-500 m beneath pial surface to locate the primary auditory cortex as
previously described. After mapping of A1, neurons located at 700–900µ m below the pia,
corresponding to layer 5 of the auditory cortex (Winer et al., 2001; Games and Winer,
1988; Hefti and Smith, 2000; Lakatos et al., 2007; Zhou et al., 2010), were specifically
targeted. The locations of recordings were further confirmed in some experiments with
Nissl staining.
For voltage-clamp recording the intrapipette solution contained (in nM) 125 Cs-gluconate,
5 TEA-Cl, 4 MgATP, 0.3 GTP, 8 phosphocreatine, 10 HEPES, 10 EGTA, 2 CsCl, 0.5
QX-314, 0.75 MK-801 (pH=7.2). For current-clamp recording the solution contained (in
nM) 130 K-gluconate, 2 KCl, 1 CaCl
2
, 4 MgATP, 0.3 GTP, 8 phosphocreatine, 10
HEPES, 11 EGTA (pH=7.2). After a giga-ohm seal was formed between a patched
neuron and the patch pipette (electrode resistance 4-6M ), a negative pressure is applied
25

to the pipette tip to break the cell membrane and bring the recording to whole-cell mode.
The whole-cell and pipette capacitance were completely compensated and the series
resistance (20- 50M ) was compensated to achieve an effective value of 10-25 M .
Signals were filtered at 5kHz and sampled at 10kHz. Under current-clamp mode, cells
were recorded with no current injection. For voltage-clamp, cells were clamped at -80mV
and 0mV, which are the reversal potentials for inhibitory and excitatory currents,
respectively.
For cell-attached loose-patch recordings, glass pipette (electrode resistance 8-10M )
containing filtered ACSF was used. Instead of a giga-ohm seal, a 100-250M  seal was
formed between. The pipette capacitance was fully compensated with minimal distortion
of the recorded spike shape. The spike signals were filtered at 10kHz and sampled at
20kHz.
All data were recorded with an Axopatch 200B amplifier (Axon Instruments), acquired
and stored for off-line analysis on custom developed programs on Labview (National
instruments). In a few experiments, sequential cell-attached and whole-cell current-clamp
or voltage-clamp recordings were able to be performed.

1.5.4 Cortical Silencing
The cortex was pharmacologically silenced following the method established in our
previous study (Liu, et al., 2007). A cocktail of SCH50911 (6 mM; a specific antagonist
26

of GABA
B
receptors) and muscimol (4mM; an agonist of GABA
A
receptor) was used to
effectively silence a relatively large cortical region. The cocktail (dissolved in ACSF
containing Fast Green) was injected through a glass micropipette with a tip opening of 2–
3 μm in diameter. The pipette was inserted to a depth close to the recording site, around
700 μm. Solutions were injected under a pressure of 3–4 psi for 5 min. The injected
volume was estimated to be around 20 nl, as measured with mineral oil. The staining by
Fast Green was monitored under the surgical microscope, which covered a cortical area
with a radius of more than 500 μm by the end of the injection. Sometimes, target neurons
were mapped for the whole synaptic RFs, and then treated with cocktail drug and tested
with one intensity level (20dB above threshold) due to the limitation of time and stability.

1.5.5 Histochemistry
During a whole-cell recording, intrapipette biocytin or fluorescent dextran were diffused
through the cell body and dendrites. After the experiment, the animals received an
overdose of urethane and were perfused with physiological saline (0.9% NaCl, 200 ml)
followed by 750 ml of a fixative containing 4% paraformaldehyde plus 0.5%
glutaraldehyde in 0.1 M phosphate buffer (PB; pH 7.41). Brain sections were cut at 50-
100 μm with a vibrating microtome and serially collected in PB. Sections were then
thoroughly washed in PB before being incubated with avidin-biotin-peroxidase complex
(ABC; Vector labs) for at least 4 h. The injected tracer could then be revealed with the
27

appropriate substrate according to the standard method. To determine nuclear boundaries,
some sections were counterstained with Cresyl Violet.

1.5.6 Data Analysis
1.5.6.1 Synaptic Response Properties
Onset latency was identified as the time point at which response first exceeded two
standard deviations of baseline during the rapid rising phase. E/I ratio was calculated
using two methods: the ratio of the amplitude of excitatory and inhibitory traces, or the
ratio of the total charge of the two, which was the integration of the synaptic current
along the time scale Excitatory and inhibitory synaptic conductances were derived
according to (Borg-Graham et al., 1998; Zhang et al., 2003; Wehr and Zador, 2003; Liu,
et al., 2006):
∆I(t) = G
e
(t)(V(t) – E
e
) + G
i
(t)(V(t) – E
i
).
where ∆I is the amplitude of synaptic current at any time point, G
r
and E
r
are the resting
leaky conductance and resting membrane potential which were derived from the baseline
currents of each recording, , V is the holding voltage, and E
e
(0 mV) and E
i
(−80 mV) are
the reversal potentials. By holding the recorded cell at two different voltages, G
e
and G
i

were calculated from the equation. In this study, a corrected clamping voltage was used,
instead of the applied holding voltage V
h
. V(t) is corrected as V(t) = V
h
– R
s
× I(t), where R
s

28

was the effective series resistance. A 10 mV junction potential was corrected. The
analysis indicated that recorded synaptic currents (after subtraction of baseline) could be
simply used to compare excitatory and inhibitory tuning curves under our experimental
conditions.

1.5.6.2 Tone-evoked responses.
In cell-attached recordings, spikes could be detected without ambiguity because their
amplitudes were normally higher than 100 pA, while the baseline fluctuation was less
than 5 pA. Tone-driven spikes were counted within a 0-50 ms time window after the
onset of tones. The spike response latency was defined as the interval between the onset
of the tone and the time point where spike rate in the PSTH for all responses becomes
higher than the baseline level by 3 standard deviations of the baseline fluctuation. All the
synaptic responses were averaged by trials. The peak synaptic responses were analyzed
within a 0-100 ms time window after the tone onset. The onset latency of this average
trace was identified at the time point in the rising phase of the response wave form, where
the amplitude exceeded the baseline level by 2 standard deviations of the baseline
fluctuation. Only responses with onset latencies within 7-50 ms from the onset of tone
stimulus were considered in this study.

29

1.5.6.3 Tuning Curve Analysis
Tuning curves were reconstructed according to the pseudorandom array to present 568
testing stimuli in 71 frequencies at 8 intensities. Characteristic frequencies (CFs) were
defined as the frequency that evoked a reliable response at the lowest intensity level.
Tuning curve bandwidth was calculated 10dB above threshold (BW10) for loose-patch
recording and 20dB above threshold (BW20) for whole-cell recordings. The bandwidth
tuning was determined based on the continuity of the evoked responses in the frequency
domain, with a value greater than three standard deviations of the baseline fluctuation.
Because the base-level activity in the auditory cortex was relatively low, the spontaneous
activities and evoked responses were clearly distinguishable. To quantify the shape of the
synaptic tuning curve, an envelope curve was derived based on the peak amplitude of
each synaptic input within the total tuning curve using MATLAB software Envelope 1.1
(developed by Lei Wang, The MathWorks), and the half-peak bandwidth (50%BW) was
defined as the frequency ranges with responses greater than 50% of the maximum. (Sun
et al., 2010).

30

1.5.7 Computational Modeling
1.5.7.1 Deriving Membrane Potential from Synaptic Conductance
Membrane potential responses were derived from the recorded excitatory and inhibitory
responses based on an integrate-and-fire model (Liu et al., 2007; Zhou et al., 2010;
Somers et al. 1995):

where V
m
(t) is the membrane potential at time t, C the whole-cell capacitance, G
r
the
resting leaky conductance, E
r
the resting membrane potential. C was measured during
experiments and G
r
was calculated based on the equation G
r
= C*G
m
/C
m
, where G
m
, the
specific membrane conductance is 2e
-5
S/cm
2
, and C
m
, the specific membrane capacitance
is 1e
-6
F/cm
2
(Hines, 1993).
1.5.7.2 Modeling Frequency Tuning with Synaptic Current
The synaptic inputs to a pyramidal neuron in layer 5 were simulated by the following
equation (Zhang et al., 2003; Zhou et al., 2010):

I(t) is the modeled synaptic current; a is the amplitude factor; H(t) is the Heaviside step
function; t
0
is the onset delay of excitatory or inhibitory input. 
rise
and 
decay
define the
shape of the rising phase and decay of the synaptic current. The 
rise
and 
decay
were
     
decay
rise
t t
t t
e e t t H a t I


/ ) (
/ ) (
0
0
0
1
 
 
     
        ) ( ) ( ) ( ) ( ) ( ) ( ) ( t V E t V G E t V t G E t V t G
C
dt
dt t V
m r m r i m i e m e m
          
31

chosen by fitting the average shape of recorded synaptic responses with the above
function. The t
0
and a are chosen based on our experimental data.

1.5.8 Statistical Analysis
All statistical analysis was performed in OriginPro 8 and MATLAB 2010. Datasets were
first tested for normal distribution (p > 0.05) and equal variances before performing
appropriate parametric statistics. For two-group comparisons, most data were treated
with unpaired t-test. Only synaptic data from the same cells were treated with paired t-
test. For three or more group comparisons, one-way ANOVA was applied to test
significance and Scheffe test was used to further compare group means. Summarized
data were presented in figures as mean ± SD. K-means Cluster Analysis was applied to
the normalized data points, which were linearly transformed to have a mean of 0 and
variance of 1 in each dimension.

1.6 Results
1.6.1 Intrinsic-Bursting and Regular-Spiking Neurons in Layer 5
Although it has been well documented that L5 pyramidal neurons fall into two classes,
intrinsic-bursting and regular-spiking, their auditory response properties have not been
well characterized. In this study, we examined spike TRFs of L5 neurons in the A1 of
32

adult rats with in vivo cell-attached loose-patch recordings. The parameters of the
recordings were chosen to preferentially record from pyramidal neurons (see Materials
and Methods). For each recorded neuron, the spike TRF was mapped with 71 x 8 tonal
stimuli for three to ten repetitions. Two types of pyramidal neurons were distinguishable
based on their evoked spike patterns. In about half of the recorded neurons (16 out of 30),
tone bursts elicited transient spike responses to the stimulus onset with only one spike
evoked at most (Fig 2.1A, inset). For these neurons, a well-tuned V-shaped spike TRF
similar to that of layer 4 neurons was observed (Fig 2.1A, 1C, compare with Tan et al.,
2004; Wu et al., 2008). These neurons were putative RS neurons. In the other recorded
neurons (14 out of 30), tone bursts at characteristic frequency (CF) elicited a short burst
of spikes (usually containing 2 to 3 spikes) to the stimulus onset (Fig 2.1B, inset).
Spontaneous bursts were also observed in these cells (Fig 2.1B, inset), suggesting that
they might be IB neurons. For these neurons, the spike TRF was noticeably broad, and
occupied usually more than half of the testing frequency-intensity space above the
intensity threshold (Fig 2.1B, D).
33

Figure 0.1 Response properties of RS and IB neurons in layer 5 of the rat A1.
A, Spike TRF of an example RS neuron. Left, array of post-stimulus spike-time histograms (PSTHs)
for responses to pure tones of various frequencies and intensities. Each PSTH trace depicts the spike
response evoked by a 50ms tone, sampled over 5 trials. Right, color map depicts the average evoked
spike number in the frequency-intensity space. Inset, three example responses to the CF tone (at
70dB) are shown, with the red line denoting the stimulus duration (50ms). Example spontaneous
spikes outside the evoked response window are also shown on the right. The PSTH at the bottom was
generated from responses to all the tone stimuli (bin size = 1ms). B, An example IB neuron. Data are
presented in the same way as in A. Note that CF-tones evoked bursts of spikes, and that spontaneous
bursts were also observed in this neuron. Within the burst, the spike amplitude reduced over time.
C, Color maps for TRFs of another three RS neurons. D, Color maps for TRFs of another three IB
neurons. E, Average bandwidth at 10dB above the intensity threshold (BW10) of the spike TRF for
RS, IB and L4 pyramidal neurons. Cell number is indicated in the bar. ***p < 0.001, ANOVA and
post hoc test. F, Average spontaneous spike rate and evoked spike rate for RS and IB neurons. **p <
0.01, t-test. G, Average spike latency, defined as the interval between the onset of the tone and the
time point when spike rate in the PSTH for all responses becomes higher than the baseline level by 3
standard deviations of the baseline fluctuation. ***p < 0.001, ANOVA and post hoc test. H, Plot of
BW10 vs. spike latency. RS (black) and IB (red) neurons distinguished by the absence/presence of
bursting firing patterns were partitioned into two separate clusters by K-means clustering analysis.
Whiskers show mean ± SD.
34

As quantified by the bandwidth at 10 dB above the intensity threshold (BW10), the spike
TRF of putative IB neurons (identified by burst spiking in response to CF tones) was
significantly broader than that of putative RS neurons (identified by single spike activity)
as well as that of pyramidal cells in layer 4 (L4) (Fig 2.1E). In addition, the IB neurons
were distinct from the RS neurons by exhibiting higher levels of evoked and spontaneous
spiking activity (Fig 2.1F). The onset latency of CF-tone evoked spike responses of IB
neurons was significantly shorter than that of RS neurons, while it was similar as that of
L4 pyramidal cells (Fig 2.1G). This suggests that IB neurons may receive direct thalamic
input similar as L4 pyramidal cells, whereas RS neurons may be driven mainly by
cortical input. Based on the parameters of TRF bandwidth and spike response latency,
the putative RS and IB neurons distinguished by their spike patterns fell into two separate
clusters (Fig 2.1H), indicating that two classes of L5 pyramidal cells can be separated by
combined receptive field and temporal response properties.

1.6.2 Subthreshold Responses Underlying the Broad Tuning of IB Neurons
The differential level of frequency selectivity exhibited by the two types of L5 pyramidal
neurons (Fig 2.1E) can be explained by two possibilities. One direct explanation is that
the two types of cells receive input of different frequency ranges. On the other hand,
even if they receive input of similar ranges, a differential efficiency of transforming
synaptic input into spike output may still lead to different selectivity levels between the
cell classes (Cardin et al., 2007; Wu et al., 2008). To examine these potential
mechanisms, we carried out sequential cell-attached and whole-cell current-clamp
35

recordings from same neurons as to compare their spike and subthreshold receptive fields.
The whole-cell recording allowed staining of the cell and reconstructing its morphology
with histology (see Materials and Methods). In Figure 2.2A and B, two example cells are
shown. They were identified as RS and IB neuron respectively based on spike pattern
(upper panel, inset). Their dendritic morphologies (lower panel, inset) were also
consistent with those reported for RS and IB neurons respectively. The subthreshold
membrane potential TRF of the RS neuron (Fig 2.2A, lower panel) was well tuned and
looked similar to that of L4 pyramidal cells (compare with Tan et al., 2004; Wu et al.,
2008). In comparison, the IB neuron, which had a broad spike TRF and relatively high
spontaneous firing rate, exhibited an apparently broader subthreshold TRF than the RS
neuron (Fig 2.2B, lower panel). Summary of similarly recorded nine RS and eight IB
neurons shows that the average bandwidth of the subthreshold TRF at 20dB above the
intensity threshold (i.e. BW20) was much broader in IB than RS neurons (Fig 2.2C, upper
panel, gray). This result indicates that the exceptionally broad spike tuning of IB neurons
(Fig 2.1E and Fig 2.2C, upper panel, white) can be primarily attributed to a broader range
of synaptic inputs they receive compared to RS neurons.

36

Figure 0.2 Subthreshold membrane potential responses of RS and IB neurons.
A, Sequential cell-attached and current-clamp recordings from an example RS neuron. Top, spike
TRF (from one sample trial) recorded in the cell-attached mode. Color map depicts the average
spike number over 8 trials. Below the color map are example response traces to the CF tone and a
tone outside the TRF (NR tone). Boxed are 50 superimposed spike waveforms (3.5 ms trace), with
vertical lines and arrows denoting the trough-to-peak interval. Bottom, subthreshold membrane
potential responses recorded in the current-clamp mode (spikes were filtered out). Color map
depicts the average peak depolarization voltage (mV) over 4 trials. Below the color map is the
reconstructed morphology of this RS neuron. Note that the apical dendrite ended in layer 2/3. Scale
bar, 100µ m. B, Sequential cell-attached and current-clamp recordings from an example IB neuron.
Data are presented in the same way as in A. Note that this IB neuron had a tufted apical dendrite
reaching layer 1. C, Top, average bandwidth of spike (supra) and subthrehold (sub) response at
20dB above the intensity threshold of the subthreshold TRF (BW20). Bandwidth of spike response in
37

this measurement is consistent with BW10 in Fig 2.1E, since the threshold for spike response is
usually 10dB higher than that for subthreshold response. **p < 0.01, ***p < 0.001, t-test. Bottom,
Average onset latencies of spike and subthreshold depolarization responses. N = 9 for RS and 8 for
IB. D, Traces of evoked subthreshold responses of example RS and IB neurons. Traces are average
responses (of 4-6 repetitions) to tones at and near CF (± 0.2 octave) at 70dB. Red line denotes the
tone duration (50ms). Black line denotes the level of the resting potential (VR). Dash line marks the
half-peak duration of the depolarization response. Arrow marks the time point of 100 ms after the
tone onset. E, Average duration of the rising phase of the depolarization response (white), and half-
peak duration (gray). F, Dendritic morphologies and laminar locations of reconstructed cells. Scale
bar, 100µ m. G, Plot of cells in three dimensions. The three axes represent BW20, half-peak duration
and onset latency of depolarization responses. Data points were segregated into two clusters based
on K-means clustering analysis, which were consistent with the grouping based on spike patterns.
The RS and IB groups are outlined by pink and blue ovals respectively.

38

We next quantified the onset latency of membrane depolarization responses, which
presumably indicates the latency for the arrival of excitatory input. As shown in Fig 2.2C
(lower panel, gray), the onset latency of CF-tone evoked membrane depolarization
responses was significantly shorter in IB than RS neurons. This result directly provides
an explanation for the observation that the evoked spike responses of IB neurons
occurred earlier (Fig 2.1G and Fig 2.2C, lower panel, white). Notably, CF-tone evoked
depolarization responses in IB neurons sustained much longer than those in RS neurons
(Fig 2.2D). In latter cells a membrane hyperpolarization was observed following the
initial depolarization (Fig 2.2D, upper). The temporal duration of evoked depolarization
responses, measured at the level of 50% of maximum (i.e. half-peak duration), was 23.5
± 3.9 ms for RS neurons but 63.8 ± 15.6 ms (mean ± SD) for IB neurons (p < 0.001, t-test)
(Fig.2E, gray). This difference in response duration could be attributed primarily to a
difference in decay kinetics, since the duration for the response rising phase did not differ
significantly between the RS and IB neurons (Fig 2.2E, white). A number of successfully
reconstructed cell morphologies (Fig 2.2F) confirmed that the RS and IB neurons
identified by sensory-evoked spike patterns were non-tufted and thick-tufted pyramidal
cells respectively, consistent with previously reported morphologies of RS and IB
neurons distinguished by spike response patterns to current injections (Hefti and Smith,
2000). In general, IB neurons have a larger soma size, a longer apical dendrite and a
higher whole-cell capacitance than RS neurons (Table 2.1).

39

RS IB
Depth, μm 794.5± 64.8 (n=9) 803.7± 69.6(n=9)
Somatic area, μm
2

135.9± 26.1*** 245.2± 27.3
Apical dendritic length, μm

452.2± 66.9*** 670.0± 79.3
Capacitance, pF 16.2± 6.0* 47.4± 37.5
V
R
, mV

-62.5± 4.1 -60± 3.1
Table 0.1 Comparison of RS and IB cell anatomy and electrphysiological preoperties.

Based on three parameters (latency and temporal duration of evoked depolarization
responses, bandwidth of subthreshold TRFs), our identified IB and RS neurons could be
well partitioned into separate clusters (Fig 2.2G). Together, these results further support
the notion that RS and IB neurons can be functionally distinguished based on the spectral
broadness of synaptic input as well as response temporal properties.

1.6.3 Excitatory and Inhibitory Inputs to Layer 5 Neurons
Membrane potential responses reflect the result of the integration of excitatory and
inhibitory synaptic inputs. To further dissect the contribution of excitatory and inhibitory
inputs to the exceptionally broad tuning of IB neurons, we carried out whole-cell voltage-
clamp recordings (see Materials and Methods). By clamping the cell’s membrane
potential at -80mV and 0mV, excitatory and inhibitory synaptic TRFs were obtained
respectively. Since QX314, a blocker of voltage-gated sodium channels, was included in
the intracellular solution, bona fide spike responses of the recorded neurons could not be
40

experimentally assayed. Nevertheless, we would be able to predict cell type reasonably
well according to the result from sequential cell-attached and current-clamp recordings
(Fig 2.2G). Two example cells from voltage-clamp recordings are shown in Figure 2.3A
and B. The first cell exhibited well tuned excitatory and inhibitory responses that
matched to each other in the frequency-intensity space (Fig 2.3A), similar to L4
pyramidal cells (compare with Zhang et al., 2003; Tan et al., 2004; Wu et al., 2008; Sun
et al., 2010). The receptive field property of synaptic inputs suggests that the cell was a
RS neuron. In comparison, the second cell exhibited an extremely broad excitatory TRF
and temporally more prolonged excitatory responses (Fig 2.3B), suggesting that it was
likely an IB neuron. Noticeably, the inhibitory TRF of the cell looked narrower than its
excitatory counterpart (Fig 2.3B). Such narrower inhibition than excitation has not been
reported for auditory cortical neurons previously.
In order to distinguish cell types for the neurons recorded under the voltage-clamp mode,
we plotted the cells along three axes representing the onset latency and half-peak duration
of the CF-tone evoked excitatory response, and the half-maximum bandwidth of the
excitatory TRF at a level of 20dB above the intensity threshold (i.e. 50% BW20) (Fig
2.3C). The cells were partitioned into two clusters, which were then identified as RS and
IB neuron group respectively. We next compared excitatory and inhibitory tuning
properties between the RS and IB groups. Based on half-maximum bandwidth (50%
BW20), which has been considered to be a better measure of tuning sharpness than the
total frequency range (Wu et al., 2008; Sun et al., 2010), among RS, IB and L4 pyramidal
cells, IB neurons exhibited the broadest excitatory tuning (Fig 2.3D, upper panel, white).
41

The inhibitory tuning did not differ significantly between RS, IB and L4 pyramidal cells
(Fig 2.3D, upper panel, gray). Excitatory tuning was significantly broader than inhibitory
tuning in IB neurons, while it is sharper than inhibitory tuning in RS and L4 pyramidal
cells. In terms of total frequency range (BW20), excitation was also broader than
inhibition in IB neurons, whereas in RS and L4 pyramidal cells the range of excitation
was similar as inhibition (Fig 2.3D, lower panel). These results indicate that the broad
tuning of IB neurons can be attributed initially to the unusually broad range of excitatory
inputs they receive, and also raise the issue of whether the mismatch between the
excitatory and inhibitory tuning of IB neurons also influences their frequency selectivity.
42

Figure 0.3 Synaptic inputs to RS and IB neurons.
A, Excitatory (top) and inhibitory (bottom) TRFs (average of 3 trials) of a putative RS neuron
recorded under clamping voltages of -80mV and 0mV respectively. Color maps depict the peak
amplitude of synaptic currents (nA). Below the color map is an example response trace evoked by a
best-frequency tone at 70dB, with the red line denoting the stimulus duration (50ms). B, Excitatory
and inhibitory TRFs of a putative IB neuron. C, Plot of cells in three dimensions. The three axes
represent latency and half-peak duration of excitatory responses, and half-maximum bandwidth of
the excitatory TRF at 20dB above the intensity threshold (50% BW20). Cells were partitioned into
two separate clusters based on K-means clustering analysis, where were identified as RS (outlined by
pink) and IB (outlined by blue) group respectively. D, Average 50% BW20 (top) and BW20 (bottom)
of excitatory TRFs for the three types of neurons. #p < 0.05, ##p < 0.01, ###p < 0.001, paired t-test
for within-group comparisons. ***p < 0.001, ANOVA and post hoc test for between-group
comparisons. Bar = SE. E, Neuron modeling of membrane potential (Vm) response tuning under co-
tuned inhibition (top) and narrower inhibition (bottom). Left, boxed are the temporal profiles of the
modeled excitatory (red) and inhibitory (black) conductances (100ms trace, upper) and that of the
derived Vm response (lower). Middle, the frequency tuning curves of excitatory and inhibitory
inputs (G) are modeled with Gaussian functions. In the co-tuned inhibition, excitatory and
inhibitory tuning curves have a same bandwidth. In the narrower inhibition, the bandwidth of the
inhibitory tuning curve is narrower than the excitatory tuning curve. Right, the derived Vm
response tuning in the absence (magenta) or presence (cyan) of inhibition. Dash line denotes the level
of spike threshold (20mV above the resting potential).
43

1.6.4 A Synaptic Mechanism Underlying Broad Frequency Tuning
The narrower inhibition than excitation observed in IB neurons is unique, as along the
ascending auditory pathway inhibitory sidebands flanking the excitatory (or to be more
precise, spike) receptive field are widely observed in extracellular recording experiments
with two-tone suppression paradigms (Shamma and Symmes 1985; Shamma 1985; Sutter
et al., 1999; Zhang et al., 2003; Popescu and Polley 2010; Sadagopan and Wang 2010).
To understand how the spectral relationship between excitation and inhibition affects the
frequency tuning of output response, we applied a conductance-based neuron model to
simulate membrane potential (Vm) responses resulting from synaptic inputs of different
tuning patterns (see Materials and Methods). We adjusted the spectral relationship
between excitation and inhibition while fixing other parameters. Two scenarios were
tested: 1) co-tuned excitation and inhibition; 2) inhibition having a narrower frequency
range than excitation. As shown in the Figure 2.3E (upper panel), the co-tuned inhibition
apparently scaled down the Vm response tuning generated by excitation alone (compare
cyan to magenta), resulting in a sharpening of spike response tuning through the iceberg
effect (Wehr et al., 2003; Tan et al., 2004; Wu et al., 2008; Liu et al., 2011). When the
inhibitory tuning became narrower (Fig 2.3E, lower panel), the Vm response tuning was
broadened with a flattened peak. As a result, broader spike response tuning would be
generated compared with the first scenario, although the general level of Vm response
reduction was similar. The flattening of Vm response tuning could be attributed to an
increasing amplitude ratio of excitation over inhibition (i.e. E/I ratio) away from the
central peak of the frequency tuning. This modelling result demonstrates that the
44

unusually broad tuning of IB neurons can be attributed not only to a broad range of
excitatory inputs they receive, but also to the narrower inhibitory tuning than excitation.

1.6.5 Temporal Properties of Synaptic Inputs to L5 Neurons
As described earlier, IB neurons exhibited longer sustained depolarization responses than
RS neurons (Fig 2.2D). We further analyzed temporal profiles of synaptic responses.
We found that in RS neurons the CF-tone evoked excitatory conductance decayed
noticeably faster than the inhibitory conductance, whereas in IB neurons excitatory and
inhibitory conductances appeared to have more similar temporal profiles (Fig 2.4A, upper
panel). Quantifications of half-peak duration showed that IB neurons had much longer
lasting excitatory responses than RS and L4 pyramidal neurons (Fig 2.4B, white). The
temporal duration of inhibitory responses, in contrast, was not significantly different
between the cell types (Fig 2.4B, gray). Consistent with the current-clamp recording
result (Fig 2.2C, bottom panel), the onset latencies of synaptic responses (both excitatory
and inhibitory) of RS neurons were significantly longer than those of IB neurons, which
on the other hand were not different from their counterparts in L4 pyramidal cells (Fig
2.4C). In each type of cells, the onset latency of inhibition was slightly but significantly
longer (by ~ 2ms) than that of excitation (Fig 2.4C).
To understand how the observed temporal relationships between excitatory and inhibitory
responses might contribute to the differential time course of the Vm response, we applied
45

the neuron model described earlier to derive Vm responses resulting from experimentally
determined synaptic conductances (see Materials and Methods). As shown in Figure 4A
(lower panel), the derived Vm responses of RS neurons displayed only a transient
depolarization, which was followed quickly by a hyperpolarizing response. In contrast,
the derived Vm responses of IB neurons showed a much longer sustained depolarizing
response without signs of hyperpolarization. These simulation results essentially
recapitulate the experimentally observed temporal profiles of Vm responses in these two
types of cells (Fig 2.2D). The absence of a hyperpolarizing phase in IB neuron responses
cannot be simply attributed to a lower level of inhibition than in RS neurons, because the
E/I ratio (measured by peak amplitude) was not significantly different between the two
cell types (Fig 2.4D, white). In addition, even when we artificially lowered the level of
excitation (i.e. increased the relative level of inhibition), the derived Vm response of IB
neurons still exhibited a long-lasting depolarization (Fig 2.4E). Thus, the differential
temporal profiles of Vm responses of IB and RS neurons can be primarily attributed to
the different temporal relationships between excitation and inhibition.
46

Figure 0.4 Temporal properties of synaptic inputs to different types of neurons.
A, Top, normalized synaptic conductances (red for excitation, reversed in polarity) evoked by CF
tones for three RS and three IB neurons. Dash line marks the half-maximum level. Bottom, the Vm
response generated in the neuron model by integrating the synaptic conductances shown above.
Dash line labels the level of the resting potential. Red line indicates the tone duration (50ms). B,
Average half-peak duration of evoked excitatory (red) and inhibitory (black) conductances. Bar = SE.
##p < 0.01, paired t-test; **p < 0.01, ANOVA and post hoc test. The duration of inhibition was not
significantly different between groups (p > 0.1). C, Average onset latencies of CF-tone evoked
excitation and inhibition. Cell number is the same as in B. Bar = SE. D, E/I ratio of peak response
amplitude (white) or of integrated charge (gray). D, The excitatory response of an IB neuron was
artificially scaled down at different levels as to change E/I ratio (the E/I ratio value is given on top).
The resulting Vm response from integrating the excitation and inhibition shown in the upper panel
consistently exhibited prolonged depolarization.

47

1.6.6 Exploring the Layer 5 Circuits
The analysis of onset latencies of excitatory responses (Fig 2.4C) indicates that IB
neurons may receive direct thalamic input. To further confirm this point, we recorded
excitatory responses after silencing cortical spikes with a mixture of muscimol and
SCH90511 (Liu et al., 2007; Khibnik et al., 2010; Zhou et al., 2012). Extracellular
recordings confirmed that spikes throughout layer 4 to 6 and within a radius of 600µ m
were eliminated after cortical injections of the mixture (Fig 2.5A, B). Thalamic neuron
responses on the other hand were not significantly changed after cortical silencing (Fig
2.5A, C). In layer 5 of the silenced A1, two types of cells were observed. In 10 out of 18
neurons, tone-evoked excitatory responses were completely absent, although spontaneous
synaptic currents were still observed (Fig 2.5D, left panel). These neurons (called “L5
silenced”) did not receive excitatory input directly from the auditory thalamus. In the
other neurons (8 out of 18), evoked excitatory responses were present and formed a clear
TRF (Fig 2.5D, middle panel), indicating that these neurons (called “L5 active”), did
receive direct thalamic input. As a control, we also recorded from the major
thalamocortical recipient layer, layer 4. We confirmed that L4 neurons still received
excitatory input after silencing intracortical connections (Fig 2.5D, right panel). As
summarized in Figure 2.5E, the onset latency of CF-tone evoked excitatory responses of
the L5 active neurons was not different from that of IB neurons or of L4 pyramidal
neurons in the normal and silenced A1. This suggests that L5 active neurons are most
likely IB neurons, because the onset latency of excitatory responses of RS neurons is
known to be significantly longer (Fig 2.4C). Further supporting this notion, the
48

frequency range of excitatory responses of the L5 active neurons was also similar to that
of IB neurons in the normal A1 (Fig 2.5F), but was significantly broader than that of RS
neurons (p < 0.001, t-test) and L4 pyramidals (Fig 2.5F). Interestingly, the temporal
duration of excitatory responses of the L5 active neurons was much shorter compared to
IB neurons (Fig 2.5G), but was similar to that of L4 pyramidals in the silenced A1 (Fig
2.5G). This suggests that the thalamocortical input itself is relatively transient.
In a few experiments, we were able to examine excitatory responses in the same cell
before and after injecting the muscimol and SCH90511 mixture. This allowed us to
identify cell type according to the response and tuning properties before cortical silencing.
As shown in Figure 5H (left panel), the excitatory responses of a putative RS neuron
(based on a narrow range of excitatory input) were completely silenced after cortical
silencing. In contrast, the excitatory responses of a putative IB neuron, which exhibited a
much broader range of excitation, were retained after cortical silencing, although the
amplitudes became smaller (Fig 2.5H, middle panel). In addition, the temporal duration
of its excitatory response was apparently reduced (Fig 2.5H, middle panel, inset). The
change of excitatory responses in a L4 neuron was similar to that in the putative IB
neuron (Fig 2.5H, right panel). Notably, the frequency range of its excitatory responses
was not significantly changed, consistent with previous reports (Liu et al., 2007; Zhou et
al., 2012). We had successfully recorded from eight L5 cells before and after cortical
silencing. In 4 of them, excitatory responses were completely eliminated after cortical
silencing, while in the other 4 cells (“active”) responses were retained although reduced
in amplitude. The excitatory responses of the silenced cells exhibited significantly longer
49

onset latencies (Fig 2.5I, white), narrower frequency ranges (Fig 2.5J), and much shorter
temporal durations (Fig 2.5K) compared to the active cells. These data strongly suggest
that the silenced cells were RS neurons while the active cells were IB neurons. The
response onset latency for the active cells did not change after cortical silencing (Fig
2.5I), supporting the notion that the earliest excitatory response in IB neurons is due to
thalamocortical input. The response frequency range did not change either (Fig 2.5J),
indicating that the broad tuning of IB neurons can be attributed initially to a broad
thalamocortical convergence. Finally, the response temporal duration for the active cells
was largely reduced after cortical silencing (Fig 2.5K), further supporting the notion that
the thalamocortical input is in fact transient and that the long lasting excitatory response
of IB neurons is due to recruitment of intracortical inputs which collectively are
temporally prolonged.
50

Figure 0.5 Direct thalamocortical input to IB neurons.
A, Color maps of example multi-unit spike TRFs in cortical layers 4,5,6 and in the MGBv of the
thalamus before and after cortical injection of the muscimol mixture. Color represents spike number.
Color scale (from left to right): 17, 18, 8, 11 for maximum. B, Remaining number of evoked spikes
after cortical silencing (in percentage of the initial spike number) at different laminar locations vs.
horizontal distance away from the injection site. N = 3 for each. Bar = SE. C, Percentage change in
evoked spike number and bandwidth of multi-unit spike TRF in the MGBv. N= 3. Bar = SE. D,
Excitatory TRFs of three example cells recorded in the silenced A1. Note that in the L5 silenced
neuron spontaneous excitatory currents were observed in some trials. Color map depicts the average
peak amplitude of excitatory current over 3 trials. Color scale (from left to right): 40/50/40pA for
maximum. Enlarged traces (100ms, to the best-frequency tone at 70dB) in the insets are to show the
response temporal profile. E, Summary of excitatory onset latency for IB neurons in the normal A1,
L5 active neurons in the silenced A1, L4 neurons in the normal and silenced A1. Cell number is
indicated. Bar = SE. F, Summary of BW20 of excitatory TRFs. ***p < 0.001, t-test. Cell number is
the same as in E. G, Summary of half-peak duration of CF-tone evoked excitatory responses. H,
Tone-evoked excitatory responses (at a level of 20dB above the intensity threshold) in the same
neuron before and after cortical silencing. Color map depicts the tuning. Color scale: 100/80/80pA
for maximum. I, Summary of onset latency of CF-tone evoked excitatory responses before and after
cortical silencing for active (putative IB) neurons and silenced (putative RS) neurons. Bar = SEM.
*p < 0.05, ANOVA. J, Summary of BW20 of excitatory TRFs. K, Summary of half-peak duration of
CF-tone evoked excitatory responses.
51

1.6.7 Fast-spiking Inhibitory Neurons in Layer 5
In each of the three cell classes, the onset latency of inhibition was found to be about 2ms
longer than that of excitation (Fig 2.4C), suggesting that the relay of inhibitory input
involved at least one more layer of synapses than the early excitatory input. With regard
to IB neurons, their inhibitory input could be potentially from local inhibitory neurons
innervated by thalamic axons, which would provide disynaptic feedforward inhibition
(Wu et al., 2008; Zhou et al., 2010). In layer 5, parvalbumin-positive fast-spiking (FS)
inhibitory neurons are the major inhibitory cell type, accounting for about 60% of total
inhibitory neurons (Kawaguchi and Kubota, 1997; Gonchar et al., 2007). Using
recording pipettes with small tips, we specifically searched and recorded from layer 5 FS
neurons, which were identified by their stereotyped narrow spike waveforms (Swadlow
1989; Wu et al., 2008; Liu et al., 2009; Atencio and Schreiner 2008). In order to compare
the spike and subthreshold TRFs of FS neurons, we made whole-cell current-clamp
recording after identifying the cell type in the cell-attached mode. Robust spike TRFs
were observed in all the 7 successfully recorded FS neurons (Fig 2.6A, upper panel as an
example). Spikes of the FS neurons displayed a trough-to-peak interval (TPI) of 0.31 ±
0.03 ms (mean ± SD), whereas for pyramidal neurons it was 0.73 ± 0.17 ms (Fig 2.6B).
In addition, the trough/peak amplitude ratio was much lower for spikes of FS than
pyramidal neurons (1.4 ± 0.1 for FS, 4.0 ± 1.4 for pyramidal, p < 0.0001, t-test, n = 8 and
14 respectively). FS neurons could also fire bursts in response to tones, but different
from IB neurons the amplitude of FS neuron spikes within a burst did not reduce over
time (Fig 2.6A, upper panel, inset). The ratio of the second spike amplitude over the first
52

spike amplitude was 0.96 ± 0.02 for FS neurons and 0.78 ± 0.07 for IB neurons (p <
0.001, t-test, n = 8 and 14 respectively). These electrophysiological signatures allowed a
reliable separation of FS cells from pyramidal cells. Furthermore, the reconstructed
morphologies of FS cells indicated that they had non-pyramidal cell morphologies with
short radially extending dendrites (Fig 2.6C), consistent with their inhibitory cell type.
As summarized in Figure 2.6D (gray), FS neurons were significantly more narrowly
tuned than IB neurons, due at least partially to the fact that FS neurons receive a narrower
range of excitatory input than IB neurons (Fig 2.6D, white). Importantly, the frequency
range of spike responses of FS neurons was much narrower compared to that of
excitatory inputs to IB neurons (Fig 2.6D), indicating that these FS neurons are
potentially capable of sending the inhibition that is more narrowly tuned than excitation
to IB neurons. Finally, the onset latency of depolarization responses of FS neurons was
similar to IB and L4 pyramidal neurons (Fig 2.6E, white), suggesting that these FS
neurons also received direct thalamic input. Noticeably, the latency of spike responses of
FS neurons was significantly shorter than IB neurons (Fig 2.6E, gray). This result
indicates that the generation of evoked spikes in FS neurons is faster than in IB neurons.
Therefore these FS neurons can provide feedforward inhibitory input to IB neurons.
53

Figure 0.6 Properties of fast-spiking inhibitory neurons in layer 5 and potential circuits.
A, Sequential cell-attached and current-clamp recordings from a FS neuron. Top, spike TRF (one
trial) recorded in the cell-attached mode. Color map is the average spike TRF over 7 trials. Inset,
example spike response traces to the CF tone and a tone outside the TRF. Note that the spike
amplitude did not reduce within a burst. Boxed are 50 superimposed spike wave forms. Note that
the spike shape is narrower than that of pyramidal cells. The trough-to-peak interval (TPI) was 0.3
ms for this FS neuron. Bottom, subthreshold TRF recorded in the current-clamp mode. B,
Summary of TPI of spike waveform for RS, IB and FS neurons. Bar = SE. ***p < 0.001, ANOVA.
C, Dendritic morphologies of 3 reconstructed L5 FS neurons. Scale, 50µ m. D, Average bandwidths
of spike and subthreshold TRFs for IB and FS neurons in sequential cell-attached and current-clamp
recordings. E, Comparison of onset latencies of spike and subthreshold depolarization responses
between cell classes. ##p < 0.01, ###p < 0.001, ANOVA and post hoc test for between-group
comparisons. *p < 0.05, t-test. F, A model for layer 5 circuits. IB neurons receive direct thalamic
input and feedforward inhibitory input from layer 5 FS neurons, as well as polysynaptic excitatory
input from upper layers and possibly within layer 5. RS neurons receive polysynaptic excitation
from upper layers and possibly within layer 5. Their inhibitory input is likely from interneurons (IN)
other than FS neurons, which are not directly driven by thalamic input. The size of arrows depicts
the tuning broadness of input. Red arrows represent excitatory input, and blue arrows represent
inhibitory input.
54

1.7 Discussion
1.7.1 Intrinsic-Bursting and Regular-Spiking Pyramidal Neurons in L5
The two types of L5 pyramidal neurons (IB and RS) in the auditory cortex have been
previously identified based on their distinctive morphological and biophysical properties
(e.g. Hefti and Smith, 2000). Anatomical studies further indicate that IB neurons
contribute to corticofugal projections, while RS neurons contribute to callosal and
corticostriatal connections (Kelly and Wong, 1981; Games and Winer, 1988; Ojima et al.,
1992; Markram et al., 1997; Llano and Sherman, 2009). However, due to technical
difficulties in identifying and recording from different cortical neurons in vivo, how
auditory information is processed in these two types of L5 neurons remains largely
unknown. Although several studies have shown that layer 5 contains units that appear
more broadly tuned than those in middle or superficial layers (Abeles and Goldstein,
1970; Volkov and Galazjuk, 1991; Turner et al., 2005; Wallace and Palmer, 2008;
Atencio and Schreiner, 2010), the type of recorded neurons has not been well defined.
Since corticofugal projections are suggested to play a role in modulating subcortical
processing, understanding the processing properties of IB neurons will generate
important insights into the function of these feedback projections. In this study, the
application of cell-attached recordings allowed us to record well-isolated single-unit
spikes specifically from the patched neuron (Wu et al., 2008; Zhou et al., 2010). The
sequential membrane-breaking to form the whole-cell configuration then allowed the
intracellular labelling of the recorded neurons. Our electrophysiological and
55

morphological data are largely consistent with the previous results. We are thus able to
conclude that IB neurons can fire bursts of spikes in their sensory-evoked and
spontaneous activity, while RS neurons only exhibit individual spikes. IB neurons
possess unusually broad frequency tunings, while RS neurons show normally sized tonal
receptive fields comparable to those of L4 pyramidal cells. The different frequency
tuning properties of IB and RS neurons, together with their distinct projection targets,
suggest that they may play different roles in the transfer of auditory information.

1.7.2 Broadly-tuned Excitation with Narrowly-tuned Inhibition
Among pyramidal neurons in different layers of the A1, IB neurons appear to possess the
broadest spike TRF, or the weakest frequency selectivity. Their receptive fields are even
broader than FS inhibitory neurons. Besides the spectral range of excitation, another
important factor contributing to the broad tuning of IB neurons is that their inhibitory
input is more narrowly tuned than excitatory input. This seems a peculiar scenario of
excitatory-inhibitory interplay, different from the previously proposed “balanced
inhibition” and “lateral inhibition” models. Intracellular recording studies often reported
approximately balanced excitation and inhibition underlying TRFs in the cortex (Zhang
et al., 2003; Wehr and Zador, 2003; Tan et al., 2004; Wu et al., 2008; Tan et al., 2009;
Zhou et al., 2010; Dorrn et al., 2010; Sun et al., 2010). The balance is characterized by
similar spectral ranges of excitation and inhibition as well as a covariation of excitatory
and inhibitory response amplitudes. Balanced/co-tuned inhibition can sharpen frequency
56

tuning through the iceberg effect (Wehr and Zador, 2003). On a finer scale, the shape of
inhibitory tuning is broader than excitatory tuning in both L4 pyramidal cells and L5 RS
neurons (Fig 2.3D, and also see Wu et al., 2008; Sun et al., 2010), which can lead to a
further sharpening of spike response tuning (Wu et al., 2008; Zhang et al., 2011). Along
the ascending auditory pathway, extracellular recordings often revealed inhibitory
sidebands flanking the excitatory TRF (Ding and Voigt 1997; Shamma 1985; Sutter et al.,
1999; Zhang et al., 2003; Popescu and Polley 2010; Sadagopan and Wang 2010; Pollak et
al., 2011). The inhibitory sidebands are often interpreted as inhibition possessing a
broader spectral range than excitation (i.e. lateral inhibition). Recently, modelling work
has suggested that balanced inhibition and lateral inhibition can both occur in the same
cortical circuit, depending on circuit configurations (Levy and Reyes, 2011). To our
knowledge, this study is the first to demonstrate that the spectral range of inhibition can
be in fact narrower than excitation. Although the broad tuning of IB neurons first
originates from a wide range of thalamocortical input, our modelling results demonstrate
that inhibition being narrower than excitation leads to a flattened tuning peak, which
would further reduce the selectivity of IB neurons. Since there is no difference in E/I
ratio between IB and RS neurons (Fig 2.4D), the broad tuning of IB neurons cannot be
further attributed to a relatively weaker inhibition. Our results highlight the notion that
the simplified scenario of balanced excitation and inhibition cannot be applied to all
cortical neurons, and that the detailed tuning relationship between excitation and
inhibition is cell-type dependent.
57

1.7.3 Potential Feedforward Circuits in Layer 5
Previously whether layer 5 neurons receive direct thalamic input has not been
conclusively tested. Some supporting evidence was given by the earliest sensory-evoked
spike responses occurring in some layer 5 cells (Wallace and Palmer, 2008; de Kock et
al., 2007) and seemingly monosynaptic responses in some IB neurons evoked by
stimulating thalamocortical tracts in slice preparations (Hefti and Smith, 2000). Short
response delays however are only suggestive of monosynaptic connections. It is not clear
if thalamic axons projecting into different layers have the same action potential
conduction speed or not. In this study, the analysis of excitatory synaptic responses
before and after cortical silencing in the same cell more convincingly demonstrates that
IB neurons receive direct thalamic input, whereas RS neurons do not. In addition, based
on the onset latency of spike responses, thalamic afferents appear to directly excite IB
neurons without the need of intracortical relay from other layers. Nevertheless, the
temporally prolonged intracortical inputs facilitate the bursting firing of IB neurons. The
frequency range of thalamic input to IB neurons is as broad as that of their total
excitatory input (Fig 2.5J), indicating that the broad thalamocortical convergence onto IB
neurons (which is broader than that onto L4 pyramidal cells) fundamentally determines
their exceptionally broad tuning. It is interesting to note that the level of thalamocortical
convergence is also layer- or cell-type specific.
Although the differential spectral ranges of excitation and inhibition are unexpected, a
widely observed feature of cortical responses, i.e. the stereotyped temporal sequence of
58

excitation followed by inhibition (Zhang et al., 2003; Wehr and Zador, 2003; Tan et al.,
2004), is preserved in layer 5. The brief delay of inhibition relative to excitation (Fig
2.4C) suggests a feedforward circuit at least for the early synaptic inputs to IB neurons as
well as RS neurons (Fig 2.6F). IB neurons receive excitation from an unusually broad
range of thalamic afferents, which drives early spiking of these neurons. The transiency
of thalamic input but the temporal broadness of summed excitation to IB neurons
suggests that these cells receive late prolonged inputs relayed intracortically from various
layers. This notion is supported by the in vitro results of mapping intracortical
connectivity with glutamate uncaging methods (Briggs and Callaway, 2005; Yu et al.,
2008; Llano and Sherman, 2009; Qiu et al., 2011; Jacob et al., 2012). Glutamate
uncaging experiments also show that L5 pyramidal neurons receive inhibitory input
predominantly from neurons within layer 5 (Llano and Sherman, 2009). We found that
FS neurons, the major inhibitory cell in layer 5, receive a narrower range of thalamic
input than IB neurons. Because they exhibit more narrowly tuned receptive fields and
earlier evoked spikes than IB neurons, these FS neurons are capable of providing fast
feedforward inhibition to IB neurons that is more narrowly tuned than excitation.
Different from IB neurons, RS neurons do not receive direct thalamic input. Instead, they
receive polysynaptic excitatory inputs from upper 1ayers and possibly from other RS
neurons in layer 5 (Hefti and Smith, 2000; Llano and Sherman, 2009; Jacob et al., 2012).
Since inhibition in RS neurons is much more delayed compared to spiking of L5 FS
neurons (Fig 2.6E), the inhibitory neurons innervating the RS neurons are likely other
types of inhibitory cells which are driven by intracortical input as well (Fig 2.6F).
59

1.7.4 Functional Implications
The functional dichotomy as revealed in IB and RS neurons suggests two distinct streams
of information processing in layer 5, with the outputs sent to different targets. IB neurons
send signals to higher-order thalamic nuclei and other subcortical nuclei, and RS neurons
send signals to the contralateral cortex. The spectrally and temporally broad integration
in IB neurons demonstrated in this study suggests a set of potential functions of the
signals carried by L5 corticofugal projections. First, direct thalamic input and an early
onset of spiking enable IB neurons to rapidly send corticofugal signals almost at the same
time as cortex starts processing. Second, the temporally prolonged excitation and the
intrinsic bursting property of IB neurons ensure a robust signal. Third, the L5
corticofugal projections in large part terminate in the nontonotopic higher-order thalamic
neuclei which connect to higher-order cortices (Winer, 2005). It has been suggested that
this cortical-thalamo-cortical route provides an efferent copy of motor commands sent
from lower cortical areas to higher cortical areas for the refinement of such commands
(Sherman, 2007). Under this functional context, the broad tuning of IB neurons suggests
that spectrally precise information may not be as important as a fast relay of information.
Finally, we speculate that corticofugal input modulates responses in midbrain and
brainstem nuclei in a more general manner, e.g. by elevating cell excitability or
synchronizing cell activity (Destexhe et al., 1998), which may be important for inducing
plasticity during conditioning (Suga and Ma, 2003).
60

1.8 Summary
For a long time, corticofugal projections from layer 5 of sensory cortices, a major
component of cortical descending pathways, are proposed to play a role in modulating
sensory processing in subcortical nuclei along the ascending pathway. However, how the
modulation by corticofugal projections is achieved remains largely unknown.
To address this issue, it is essential to first understand how information is processed in
layer 5 corticofugal neurons, what synaptic circuitry underlies this processing, and what
information is carried by the corticofugal projections. This requires in vivo dissection of
the functional synaptic circuitry associated with layer 5 corticofugal neurons, which has
not been done previously in any sensory cortices.
In this study, we specifically address this issue by applying in vivo whole-cell voltage-
clamp recordings from layer 5 neurons in the primary auditory cortex. To our surprise,
we found that intrinsic bursting neurons, the layer 5 corticofugal neurons, respond rather
unselectively to a very broad range of tone frequencies. These findings fundamentally
challenged a long-held view that corticofugal projections can exert a spectrally specific
modulation of subcortical auditory processing. Instead, based on this revealed nature of
information carried by corticofugal projections, our results support a concept that
corticofugal projections play a role in facilitating subcortical processing in a general
manner.
61

The rather unselective nature of layer 5 corticofugal neurons is further supported strongly
by the properties of their synaptic inputs. Our dissection of excitatory and inhibitory
inputs to layer 5 neurons made several important findings for the understanding of
cortical synaptic circuitry. First, the unusually broad range of excitation and the narrower
range of inhibition, which is an uncommon setting of excitatory-inhibitory interplay ever
revealed in the sensory system, serves a specific purpose to generate flat and broad
frequency tuning. Second, the spectral imbalance between excitation and inhibition
reveals the diversity of organizations of synaptic circuits in the cortex. Thus, the
previously proposed scenario of “balanced excitation and inhibition” should only apply to
specific groups of cortical neurons. Thirdly, based on the temporal and spectral properties
of excitatory and inhibitory synaptic inputs before and after cortical silencing, we
determined the respective thalamocortical and intracortical contributions to both intrinsic
bursting and regular spiking neurons in layer 5. These results further emphasize the
concept that cortical local circuits are specifically designed for achieving specific laminar
processing of auditory information.
The functional processing in layer 5 is previously poorly understood, as previous studies
have mostly focused on slice preparations. This comparative study of IB and RS neurons
in layer 5 demonstrates two distinct streams of information processing in layer 5. We
think that the findings of this study would be potentially important to our understanding
of functional cortical synaptic circuitry, and will have general impacts on systems and
computational neuroscience fields.
62

Chapter 3: Synaptic Mechanism of Developmental Refinement
in Layer 4 Neurons
1.9 Background and Introduction
Early studies on the functional development of the central auditory system have often
focused on sub-cortical auditory nuclei (Romean, 1997). There, development of
functional properties, such as auditory thresholds, the sharpening of tuning and tonotopy,
is determined primarily by the maturation state of the periphery (cochlea) and also
possibly by some central neuronal plasticity mechanism (Clopton and Winfield, 1976;
Sanes, and Constantine, 1983).
Relatively few studies have dedicated to auditory cortex. In cat (Brugge et al, 1988;
Bonham et al, 2004) or chinchilla (Pienkowski and Harrison, 2005), the auditory cortical
organization appears to develop precociously, with well established tonotopy before P14
or P3, respectively. In contrast, the tonotopic map in rat A1 arises from progressive
differentiation of an initial large tone-responsive zone during a postnatal period from P12
to P21, and is accompanied by progressive refinement of initial broadly tuned TRFs, as
examined in previous studies with multiunit recording methods (Zhang et al, 2001; Zhang
et al, 2002; Chang and Merzenich, 2003). These results are consistent with the consensus
that the formation of mature neuronal connections involves activity-dependent refinement
of initial circuits, leading to cortical functions adapted to environmental factors (Katz and
Shatz, 1996; Zhang and Poo, 2001). Thus, the rat is a useful model to investigate the
63

synaptic bases underlying the functional development of the auditory cortex, since it A1
undergoes protracted development during the postnatal period.
It is commonly known that, in different sensory systems during development, after the
initial circuit growth, cortical synaptic inputs usually experience a period of refinement,
through which some connections are weakened/eliminated while others are
stabilized/strengthened (Katz and Shatz, 1996; Lohof et al, 1996; Penn and Shatz, 1999).
Yet most of the evidence about cortical synaptic change during development is from
studies in acute slices (Dalva and Katz, 1994)) or morphological observations of axonal
and dendritic arbors (Katz and Crowley, 2002). Due to technical limitations, few studies
directly addressed the question how these synaptic changes during development affect the
functional responses of the cortical neurons. In this study, we directly correlated synaptic
changes to functional maturation of A1 neurons. The experiments were designed to
explore synaptic mechanisms underlying the progressive refinement of single-cell TRFs
during development.

1.10 Methods and Materials
1.10.1 Animal Preparation
All experimental procedures used in this study were approved under the Animal Care and
Use Committee at the University of Southern California. Experiments were performed in
a sound-proof booth (Acoustic Systems) as described before (Zhang et al, 2001; Tan et al,
64

2003; Wu et al, 2008). Sprague-Dawley rats from P12 to 3 months old were used in this
study. The animals were anaesthetized intraperitoneally with ketamine and xylazine
(ketamine: 45 mg kg
−1
; xylazine: 6.4 mg kg
−1
). Craniotomy and durotomy were performed
to expose the cortex. Extracellular recordings were made with Parylene-coated tungsten
microelectrodes (2 MΩ, FHC) at 500–600 µ m below the pia to locate the primary
auditory cortex as previously described(Zhang et al, 2001; Tan et al, 2003; Zhang et al,
2003). The cortical surface was covered with pre-warmed artificial cerebrospinal fluid (in
mM: NaCl 124, NaH
2
PO4 1.2, KCl 2.5, NaHCO
3
25, glucose 20, CaCl
2
2, MgCl
2
1).
Frequency–intensity receptive fields of tone-evoked responses were obtained with pure-
tone testing stimuli (0.5–64 kHz at 0.1-octave intervals, 25-ms duration, 3-ms ramp, a
total of 568 testing stimuli) at eight sound intensities (from 0 to 70 dB sound pressure
level, except for P12–P14 rats to which 20–90 dB were applied) delivered through a
calibrated free-field speaker.

1.10.2 In vivo Whole-Cell Voltage-Clamp Recording And Loose-Patch/Cell-
Attached Recording
After mapping of A1, whole-cell recordings (Zhang et al, 2003; Wehr and Zador, 2003;
Tan et al, 2004; Wu et al, 2008; Moore and Nelson, 1998; Margrie et al, 2002) were
obtained from neurons located at about 450–650 µ m below the pia, corresponding to the
input layer of the auditory cortex (Zhang et al, 2001). This was further confirmed in
several experiments with histology. We used agar (4%) to minimize cortical pulsation.
65

For voltage-clamp recordings, the pipette (4–7 MΩ) contained intracellular solution
containing the following (in mM): 125 Cs-gluconate, 5 TEA-Cl, 2 CsCl, 1 EGTA, 10
HEPES, 4 MgATP, 0.3 GTP, 10 phosphocreatine, 1.5 QX-314, pH 7.2. Recordings were
made with an Axopatch 200B amplifier (Molecular Devices). The whole-cell and pipette
capacitances (30–50 pF) were completely compensated and the initial series resistance
(20–50 MΩ) was compensated for 50–60% to achieve an effective series resistance of
10–25 MΩ. Signals were filtered at 5 kHz and sampled at 10 kHz. Only neurons with
initial resting membrane potentials more negative than −50 mV and with stable series
resistance (with less than 20% change during the course of the experiment) were used for
further analysis. About 50% of whole-cell recordings could be maintained in good quality
to complete at least one round of the experimental test. To obtain tone-evoked synaptic
conductances, neurons were clamped at −80 mV and then 0 mV (after correction of the
junction potential), which are around the reversal potentials for inhibitory and excitatory
currents, respectively. TRF mapping was repeated two or three times for each potential.
The whole-cell recording under our experimental condition (with relatively large pipette
tip-openings) targeted exclusively pyramidal neurons, which was also consistent with the
observations that most layer 4 excitatory neurons are pyramidal in the auditory cortex
(Smith, 2001; Richardson et al, 2009). The tone-evoked synaptic inputs were considered
to be reasonably clamped, based on the linearity of the current–voltage curves, as well as
the closeness of the reversible potential for the earliest component of tone-evoked
currents to that of excitatory currents. Loose-patch cell-attached recording was performed
as described previously

(Tan et al, 2004). Glass electrodes with the same opening size
66

containing artificial cerebrospinal fluid were used. The pipette capacitance was
completely compensated. A 100–250 MΩ seal was formed on the patched neuron. The
spike signal was filtered at 10 kHz and sampled at 20 kHz. Recording of spike TRFs was
repeated five to ten times for each cell, and the spike number evoked by the same tone
stimulus was averaged. All of the neurons recorded under this condition showed regular-
spike property, consistent with sampling bias towards excitatory neurons.

1.10.3 Data Analysis
Tone-evoked synaptic responses were identified according to their onset latencies and
peak amplitudes. The onset latencies were identified during the rising phase of the
response trace at the time point where the current amplitude exceeded two standard
deviations of baseline fluctuation. Only responses with latencies within 15–50 ms (for
young adults; 20–70 ms for early developmental stages) from the onset of tone stimulus,
and with peak amplitude larger than three standard deviations of baseline fluctuation,
were considered. The tone-evoked synaptic responses were normally clustered and
continuously distributed within the synaptic TRF. The suspected spontaneous responses,
especially those at peripheries of the TRFs, were further identified according to the
inconsistency of their appearance or of onset latencies between trials, or the drastic
change of onset latency from neighboring frequencies (that is, ± 0.1 octave if available, at
the same intensity). Because the base-level activity in the auditory cortex was relatively
low, the spontaneous synaptic currents were normally clearly distinguishable.
67

The TFRR at each testing intensity (above the threshold) was determined based on the
continuity of the putative evoked synaptic responses in the frequency domain. The
endings of the TFRR were determined by the appearance of two consecutive breaks of
evoked responses. It should be noted that above the intensity threshold synaptic responses
could be reliably elicited, although the amplitude varied between trials. At the intensity
threshold, the TFRR was the frequency range covering all the evoked responses. To
derive the bandwidth of the frequency tuning curve at the level of 50% of the maximum,
the peak amplitudes of synaptic inputs within the TFRR were fitted with an envelope
curve by using MATLAB software Envelope1.1 (developed by Lei Wang, The
MathWorks), which identifies the local maxima and minima in the raw data set and then
generates a smooth envelope with cubic Hermite interpolation. In this study, the intensity
threshold was defined by the lowest intensity level at which both excitatory and
inhibitory responses could be elicited.

MMI was calculated as the mean square error between the excitatory and inhibitory
tuning curves that were normalized to the maximum response amplitude:

where E
i
is the amplitude of the excitatory input evoked by an effective tone frequency, I
i

is the amplitude of the corresponding inhibitory response and n is the total number of
effective tone frequencies that elicit either significant excitatory or inhibitory responses.

 


  
n
i
i i
I E
n
MMI
1
2
1
68

Excitatory and inhibitory synaptic conductances were derived

according to (Borg-Graham,
1998; Anderson,2000)
I(t) = Gr(V(t) - Er) + Ge(t)(V(t) - Ee) + Gi(t)(V(t) - Ei)
I is the amplitude of synaptic current at any time point; G
r
and E
r
are the resting
conductance and resting membrane potential which were derived from the baseline
currents of each recording; G
e
and G
i
are the excitatory and inhibitory synaptic
conductance respectively; V is the holding voltage, and E
e
(0 mV) and E
i
(-70 mV) are
the reversal potentials. In this study, a corrected clamping voltage was used, instead of
the holding voltage applied (V
h
). V(t) is corrected as V(t) = V
h
– Rs*I(t), where Rs was
the effective series resistance. A 10 mV junction potential was corrected. By holding the
recorded cell at two different voltages, G
e
and G
i
were calculated from the equation. G
e

and G
i
reflect the strength of pure excitatory and inhibitory synaptic inputs, respectively.

Membrane potential and spike responses were derived from the derived excitatory and
inhibitory conductances based on an integrate-and-fire model (Somers et al, 1995):

where V
m
(t) is the membrane potential at time t, C the whole-cell capacitance, g
r
the
resting leaky conductance, E
r
the resting membrane potential (-65 to -60mV). To
simulate spike responses, 20mV above the resting membrane potential was set as the
spike threshold and a 10ms refractory period was used. Based on the synaptic inputs, a
tone stimulus only generated at most one spike. C was measured during experiments and
g
r
was calculated based on the equation g
r
= C*G
m
/C
m
, where G
m
, the specific membrane
        ) ( ) ( ) ( ) ( ) ( ) ( ) ( t V E t V G E t V t G E t V t G
C
dt
dt t V
m r m r i m i e m e m
          
69

conductance is 2e
-5
S/cm
2
, and C
m
, the specific membrane capacitance is 1e
-6
F/cm
2
(Liu
et al, 2010).

1.11 Results
1.11.1 Synaptic Models for Spiking Receptive Field Refinement of Sensory
Neuron during Development
To account for the refinement of spike receptive fields (that is, receptive fields of spiking/
suprathreshold responses) in sensory cortices during postnatal development, three
synaptic mechanisms can be proposed (Fig 3.1a). First, selective pruning of excitatory
inputs at receptive field peripheries reduces the total range of inputs. Second, modifying
the strengths of individual inputs, for example weakening the inputs at receptive field
peripheries, can effectively reduce the size of the spike receptive field without changing
the total input range. Third, broadening of the inhibitory tuning and/or strengthening of
inhibition can also effectively reduce the spike receptive field size. However, these
models could not be directly revealed by previous anatomical, extracellular recording or
cortical slice studies. It is also worth noting that although inhibition is proposed to play
an important role in regulating the critical period for cortical plasticity (Hensch, 2005),
how the inhibitory circuits undergo developmental changes has not been well elucidated.
In this study, we address these issues in the rat A1, the functional development of which
is marked by a progressive refinement of the tonotopic map and sharpening of spike
TRFs of neurons (Zhang et al, 2001; Chang and Merzenich, 2003). Synaptic TRFs in the
70

recipient layer 4 of the adult A1 are characterized by approximately balanced excitation
and inhibition as well as a stereotypic temporal delay of inhibition relative to excitation
(Zhang et al, 2003; Wehr and Zador, 2003; Tan et al, 2004; Wu et al, 2008), which can be
attributed to a tripartite thalamocortical feedforward circuit (Tan et al, 2004; Douglas &
Martin, 1991; Oswald,2006).

1.11.2 High-Threshold but Balanced Synaptic Responses in Early Age
First, examination was performed to see whether there was an initial mismatch between
excitatory and inhibitory TRFs in early development, as suggested by a study in the
developing Xenopus retinotectal system (Tao et al, 2006). At postnatal day 12–13 (P12–
P13), the ear canals are just opened and auditory responses can first be detected in the A1
(Zhang et al, 2001; Chang and Merzenich, 2003). Surprisingly, at this stage right after the
onset of hearing, excitatory and inhibitory TRFs already appeared well matched in the
frequency–intensity space (Fig 3.1c). The intensity thresholds for evoking excitatory and
inhibitory responses were both notably high, mostly at or above 70 dB sound pressure
level (SPL). Comparison of excitatory and inhibitory tuning curves (that is, the envelope
of peak response amplitudes) revealed that they did not match well at the threshold
intensity (Fig 3.1d, 70 dB). However, at intensities above the threshold, they did match
reasonably well in terms of frequency range and shape (Fig 3.1d, 90 dB), like those
reported in the adult A1 (Zhang et al, 2003; Wehr and Zador, 2003; Tan et al, 2004).
71

Figure 0.1The synaptic TRFs shortly after the onset of hearing.
a, Three synaptic models for the functional refinement of sensory spike receptive fields (reduction in
the size of receptive fields). Curves represent tuning profiles of excitation (black) and inhibition (red)
along a sensory space. A pair of dotted vertical lines indicate the total response range of excitatory
inputs. I, pruning of peripheral excitatory inputs (that is, reduced total response range). II,
adjustment of input strengths without pruning of inputs. III, broadening and strengthening of
cortical inhibition. b, Current–voltage curves for a recorded A1 neuron. Inset, average traces of
synaptic currents (five repeats) of the neuron evoked by a noise stimulus. Average amplitude was
measured within the 1–2 ms (red) and 21–22 ms (black) windows after the onset of the average
synaptic response recorded at −80 mV. Correlation coefficient (r) is shown. c, TRFs of excitatory and
inhibitory inputs for an example P13 neuron. Arrays of traces depict the excitatory (−80 mV) and
inhibitory (0 mV) currents evoked by individual tone stimuli at various frequencies and intensities.
Red arrow marks the intensity threshold. Colour map depicts the peak amplitudes of tone-evoked
synaptic currents within the TRF. The example excitatory (black) and inhibitory (red) responses
evoked by the same tone (indicated by red dots) were enlarged. Dotted vertical lines mark the 75-ms
window for plotting individual small traces in the array. d, Frequency tuning curves of excitatory (E)
and inhibitory (I) inputs to the same cell as in b at two intensities: the threshold (70 dB) and 20 dB
above the threshold (90 dB). The starting and ending frequencies for the inhibitory tuning were
marked. Right, the tuning curves are normalized and superimposed (E, black, reversed in polarity).
Blue line indicates the half-peak level. e, Mismatch indices at threshold intensity (grey) and an
intensity of 20 dB above threshold (white). For two P12–P14 cells exhibiting an intensity threshold of
80 dB sound pressure level, MMI was derived at 10 dB above the threshold. *P < 0.005, paired t-test
(n = 8, 6 for P12–14 and adult, respectively). Error bar, s.d.
72

To quantify the degree of mismatch between the excitatory and inhibitory tuning curves,
a mismatch index (MMI; see Methods) is calculated. For a group of P12–P14 neurons,
MMI value was in general high for synaptic tuning curves at threshold intensity (Fig
3.1e). This, however, should not be simply interpreted as poorly matched excitatory and
inhibitory tunings; rather, it can be attributed to the unreliability of synaptic responses at
the threshold and the limited number of sampling trials. In fact, similarly high MMI
values at threshold intensity were also observed for adult neurons (Fig 3.1e). This argues
for the necessity of examining excitation–inhibition balance at intensity levels above
threshold. Indeed, at higher intensities, P12–P13 neurons exhibited low MMI values
comparable to adult neurons (Fig 3.1e), indicating that the excitation–inhibition balance
as observed in the adult A1 is already established at stages right after the onset of hearing.
Given that the intensity threshold for the auditory brainstem response (ABR) at P12–P13
is similarly high as the cortical response (70– 100 dB) (Blatchley, 1987; Geal-dor et al,
1993), the cortex and subcortical nuclei may not be effectively driven under usual
auditory environments at stages around the onset of hearing. Therefore the establishment
of excitation–inhibition balance is likely independent of auditory experience, reminiscent
of the formation of ocular dominance columns and orientation maps in the developing
visual cortex, which is independent of visual experience (Katz and Clowley, 2004). These
observations also support the previous hypothesis that at or even before the onset of
hearing, the hard wiring is already present between auditory nuclei in the ascending
pathway (Romand, 1997).
73

1.11.3 Synaptic Receptive Field of Auditory Neuron at Later Stage
We next examined older stages. Compared with P12–P13, the intensity threshold for
synaptic responses at P16 drastically reduced and the frequency–intensity area for
synaptic responses markedly expanded (Fig 3.2a). The intensity threshold did not appear
to decrease further after P16 (Fig 3.2b, c). For all the neurons, excitatory and inhibitory
synaptic TRFs appeared largely matched (Fig 3.2a–c). Comparing the synaptic tuning
curves at the same relative intensity level (Fig 3.2d), we did not observe appreciable
developmental changes in the total frequency response range (TFRR) of synaptic inputs
(see Methods). However, the shape of the excitatory tuning curve in relation to that of the
inhibitory tuning curve appeared quite different between P16 and P80. At P16, the
excitatory and inhibitory tuning curves both exhibited a broad peak, and they matched
exquisitely. At P80, the peak of the excitatory tuning curve appeared much sharpened,
whereas that of the inhibitory tuning curve remained broad (Fig 3.2d). Thus the
excitatory and inhibitory tuning curves at P80 appeared less matched. This observation of
a slight mismatch between excitatory and inhibitory tunings is consistent with our
previous report (Wu et al, 2008), which shows that a relatively broader inhibitory tuning
can generate an equivalent lateral inhibitory sharpening effect.
74

Figure 0.2 Synaptic TRFs at later developmental stages.
a–c, Synaptic TRFs of example neurons at P16 (a), P20 (b) and P80 (c), respectively. d, Frequency
tuning curves of excitatory and inhibitory inputs at the intensity of 20 dB above threshold for cells
shown in a–c. Presentation is the same as in Fig 3.1.
75

1.11.4 Differential Progression of Synaptic Excitation and Inhibition along
Development
To summarize the developmental changes in synaptic TRFs, neurons were grouped into
four developmental stages: stage 1 (ST1), from P12 to P14; ST2, from P15 to P18; ST3,
from P19 to P25; and ST4, P80 and older. There was a rapid decrease in intensity
threshold from ST1 to ST2 both for excitatory and inhibitory TRFs (Fig 3.3a). The
intensity threshold of the inhibitory TRF was mostly the same as that of the excitatory
TRF. It was slightly (10 dB) higher in only a small fraction of neurons. In parallel, the
intensity threshold of spike TRFs, as examined by cell-attached recordings (see Methods),
became lowered with development (Fig 3.3a), which is consistent with previous results
( Zhang et al, 2001; Chang and Merzenich, 2003). This change in intensity threshold is
likely attributed to the functional maturation of the periphery, because the intensity
threshold for ABR decreases from 70 to 100 dB at P12–P13 to 30–50 dB at P16
(Blatchley, 1987; Geal-dor et al,1993). The ranges of excitatory and inhibitory inputs
became enlarged from ST1 to ST2, as shown by the TFRRs at 10 dB above threshold
(Fig 3.3b). The TFRRs did not change further after ST2 (Fig 3.3b). The bandwidth of the
excitatory tuning curve at the level of 50%of the peak (BW50%) initially increased
fromST1 to ST2 (Fig 3.3c), consistent with the change in TFRR. However, after ST2, it
significantly decreased, indicating that the shape of the excitatory tuning curve is
sharpened without reducing the total range of inputs. In contrast, the half-peak bandwidth
of the inhibitory tuning curve remained stable after ST2 (Fig 3.3c), indicating that the
inhibitory tuning does not undergo a significant developmental sharpening. The
76

differential development of excitatory and inhibitory tunings leads to a slight breakdown
of the previously formed excitation–inhibition balance, as indicated by a significantly
higher MMI at ST4 than at ST2 (Fig 3.3d). At more mature stages, a relatively broader
inhibitory tuning was observed for neurons exhibiting various characteristic frequencies.
It is worth noting that despite the slight mismatch, excitation and inhibition are largely in
balance, as indicated by the strong correlation between their amplitudes.
We note that Dorrn et al. (2010) found the developmental establishment of balanced
excitation and inhibition in the auditory cortex was a protracted process, with a relatively
low level of co-tuning shortly after the onset of hearing. This apparently opposite
observation may be attributed to several differences in their experimental designs. First,
although our study focused on the thalamocortical circuit in layer 4, their recorded
neurons spanned layers 3–6 and exhibited surprisingly broad frequency ranges of
synaptic inputs cross all stages, apparently exceeding their 0.5–32 kHz testing range.
Second, they chose a fixed intensity (70 dB) for examining the co-tuning of excitation
and inhibition. The synaptic tuning/co-tuning may vary with the intensity level relative to
the threshold of synaptic TRFs, which decreases during development. Nevertheless, both
studies demonstrate that shortly after the onset of hearing, excitation and inhibition with
similar amplitudes and temporal relationship to adults have already engaged in auditory-
evoked responses.
We did not observe significant developmental changes in the ratio of peak amplitudes of
inhibition and excitation (I/E ratio) evoked by tones of preferred frequency, or in their
77

absolute amplitudes (Fig 3.3e). The onset latencies of excitatory and inhibitory responses
become shorter with age, whereas the relative delay of inhibition to the onset of
excitation (about 2 ms) remains more or less constant across different stages (Fig 3.3f),
further suggesting that the tripartite thalamocortical feedforward circuit is already formed
at the onset of hearing.

Figure 0.3 Developmental change in spectral and temporal pattern of excitatory and inhibitory input
a, Average intensity threshold of excitatory, inhibitory and spike TRFs. *Significantly higher
(P < 0.001), ANOVA with post-hoc test (n = 10, 10, 10, 10 for excitatory TRFs; n = 8, 8, 5, 6 for
inhibitory TRFs; and n = 7, 11, 6, 14 for spike TRFs examined by cell-attached recordings). b, TFRR
of excitatory and inhibitory inputs at 10 dB above intensity threshold. Data were from the same
recordings as in a. Solid symbols are average values and are connected with dashed lines for easier
comparisons between neighbouring groups (the same for c, e and f). *Significantly lower (P < 0.05),
ANOVA with post-hoc test. c, Half-peak bandwidths (BW50%) of the tuning curves in b. *Different
in excitation; #different in inhibition; P < 0.001, ANOVA with post-hoc test. d, Mismatch indices at
threshold intensity (grey) and 20 dB above threshold (white) at different stages (n = 8, 8, 5, 6). For
20 dB above threshold, ST2 is significantly lower than ST3 and ST4 (P < 0.05, ANOVA with post-hoc
test). For each stage, MMI at threshold is significantly higher than at 20 dB above threshold
(P < 0.005, paired t-test). e, Average peak amplitudes of evoked inhibitory and excitatory currents
from the same recordings as in a. The peak amplitude was determined by averaging five responses
around the best frequency at the highest intensity tested. The I/E ratio was first calculated for
individual cells with both excitatory and inhibitory TRFs recorded, and then averaged (circle, n = 8,
8, 5, 6, respectively). f, Onset latencies of synaptic responses, and the relative delay of inhibition. All
error bars, s.d.
78

1.11.5 Sharpening of Excitatory Inputs Underlying Developmental
Refinement of Spike Receptive Field in A1
The above data suggest that instead of a selective pruning of inputs at receptive field
peripheries, adjusting the strengths and tuning pattern of excitatory inputs may be a major
mechanism for the functional refinement of cortical TRFs.
To understand further the impacts of the observed synaptic changes on spike receptive
fields, we derived spike TRFs of the recorded neurons by integrating the experimentally
determined excitatory and inhibitory synaptic conductances in an integrate-and-fire
model. To estimate the accuracy of our method of deriving spike TRFs, sequential cell-
attached recording and whole-cell voltage-clamp recording were performed to obtain the
bona fide spike TRF and synaptic conductances from the same cell. As shown in one
example (Fig 3.4a), the spike TRF derived from the synaptic conductances was largely
consistent with the recorded spike TRF. For five experiments, the percentage deviation of
the bandwidth of the derived spike TRF at 10 dB above threshold from that of the
recorded spike TRF was 3.7% ± 10.0% (mean± s.d.), suggesting that in these recorded
cells the integration of synaptic inputs based on their spectrotemporal interactions could
provide a reasonable estimation of the spike output. The summary of bandwidths of the
derived spike TRFs shows that spike TRFs are first broadened from ST1 to ST2, and then
refined afterwards (Fig 3.4b). Furthermore, spike TRFs as examined by cell attached
recordings displayed the same developmental trend (Fig 3.4b). These results are
consistent with previous extracellular recording studies (Zhang et al, 2001; Chang, 2003;
79

de Villers-Sidan, 2007) indicating that the observed changes in the patterns of excitatory
and inhibitory inputs can largely explain the developmental refinement of spike TRFs.

Figure 0.4 Synaptic mechanism underlying developmental refinement of spike TRFs in A1.
a, An example cell with cell-attached recording followed by whole-cell recording. Top panels, the
excitatory (−80 mV) and inhibitory (0 mV) TRFs of the cell. Scale, 50 pA and 100 ms. Bottom left, the
recorded spike TRF. Bottom right, the TRF of derived membrane potential and spike responses.
Colour maps represent the peak amplitudes of synaptic inputs (top) and number of spikes evoked
(bottom). b, Bandwidths of spike TRFs derived and recorded from cells at different stages.
Bandwidth was measured at 10 dB above threshold. The value at ST2 is significantly higher (P = 0.1,
0.024, 0.014 between pairs of ST2–ST1, ST2–ST3 and ST2–ST4, respectively, for recorded TRFs (n =
7, 11, 6, 14); P = 0.004, 0.016, 0.015 for derived TRFs (n = 8, 8, 5, 6); ANOVA with post-hoc test).
Error bars, s.d. c, A developmental model. The excitatory tuning profile is developmentally
sharpened whereas the inhibitory tuning remains relatively stable. Vertical lines mark the total
range of inputs.
80

The developmental changes in the frequency response ranges and tuning profiles suggest
two phases of auditory cortical development: an initial expansion of the synaptic TRFs
and a later modification of the synaptic tuning profiles. The refinement of auditory spike
TRFs is mainly contributed by two factors (Fig 3.4c). First, instead of the generally
proposed reduction of the input range, modulation of the strengths of existing excitatory
inputs leads to a sharpening of the excitatory tuning profile. Second, the relatively stable
inhibitory tuning compared with the excitatory tuning results in a slight breakdown of the
previous excitation–inhibition balance, allowing a lateral inhibitory sharpening effect on
the spike TRF at more mature stages (Wu et al, 2008). Thus the modulation of excitatory
connections primarily guides the functional development of the auditory cortex, resulting
in sharply tuned frequency selectivity and a more distinctive frequency gradient in the
tonotopic map.

1.12 Summary
This project provides us a unique opportunity to probe functional cortical synaptic inputs
at different developmental ages. By correlating the developmental change of synaptic
inputs to that of the auditory cortical representation and processing, we expect to reveal
logics that govern developmental refinement of these inputs that underlies the functional
maturation of cortical neurons. By extending this line of research to plasticity models,
we will address cortical synaptic mechanisms underlying the powerful plasticity observed
in the developing auditory cortex. We start at A1 pyramidal neurons in the input layers,
81

and hope to establish a solid base for our long-term goal of establishing an integral model
of cortical synaptic circuits and their development. This study will generate reports that
will potential implications for addressing hearing disorders during development.
In this study, we tried to address a most fundamental question in the functional
development of the sensory cortices, i.e. what are the synaptic/circuitry mechanisms
underlying the progressive refinement of functional properties of sensory cortical neurons
during development. Although this has been intensively studied for decades, the
limitation of previous approaches, either anatomy, extracellular recordings or brain slice
preparations, failed to reveal the synaptic and circuit mechanisms underlying the
functional responses in the developing cortex. This issue can only be addressed by
applying in vivo whole-cell recording techniques to cortical neurons at different
developmental ages, to reveal how the developmental changes in excitatory and
inhibitory circuits determine the functional refinement of the cortical responses.
We proposed three synaptic models at beginning of this study to account for the
refinement of receptive fields during sensory cortical development. First,
eliminating/pruning of initially established presynaptic excitatory connections. Second,
the modification of synaptic weights, e.g. weakening excitatory inputs at the RF
periphery will effectively reduce the size of spike RF. Third, broadening of inhibitory
tuning and/or strengthening of inhibitory inputs can also cause the decrease of spike RF
size. In fact, the first model is the most popular one in the field.
82

Interestingly, our findings demonstrate that the functional refinement results from the
second and third mechanisms through a fine-tuning of the strength of the excitatory
synaptic inputs, while elimination of presynaptic inputs is not evident. In addition, we
data also strongly demonstrate that from the earliest time that auditory cortical responses
can be detected, balanced excitation and inhibition has already been established. This
strongly indicates that the core cortical circuit (the canonical feedforward circuit) is
formed independent of auditory experience.

1.13 Future Direction
1.13.1 Cortical Synaptic Mechanism Underlying Plasticity Induced by Early
Deprivation of Sound Inputs
1.13.1.1 Background and Introduction
In previous studies, It is demonstrated that the formation of tonotopic maps in A1 is
specifically influenced by the rat pup’s early acoustic environment (Zhang et al, 2001;
Zhang et al, 2002; Chang and Merzenich, 2003; Nakahara et al, 2004). Experience-
dependent development of sensory cortices have been extensively studied in the visual
and somatosensory cortex, where it has been well documented that experience plays an
important instructive role in sculpting developing neuronal connections (Katz and Shatz,
1996; Zhang and Poo, 2001. The auditory cortex also undergoes experience-dependent
plasticity during development as well as in adulthood. Behaviorally important sound
83

stimuli can change the auditory cortical organization (Weinberger, 1995; Kilgard and
Merzenich,1998; Bao et al, 2001). Correlation between speech perception and early
language-specific speech exposure, and between perception of complex harmonic sound
and early music training, has manifested a powerful early capacity for complex-stimulus
specific cortical reorganization (Pantev, 1998). Rewiring of retinal inputs into the
auditory thalamus in the infant ferret or hamster leads to the formation of feature-
selective visual responses, retinotopic maps and orientation columns in the primary
auditory cortex (Sharma et al, 2000; von Melcher et al, 2000), consistent with the notion
that the functional organization of this cortical area is highly dependent on the specific
spectrotemporal structure of its predominant neuronal inputs. Auditory cortical plasticity
has also been well elucidated in human and animals with cochlear implantation (Kral et al,
2001).
In developing auditory cortex of rats, we have previously demonstrated that early
auditory experience during a critical developmental period plays an instructive role in the
formation of tonotopic map in A1, and that the impact of early experience persists into
adulthood(Zhang et al, 2001; Zhang et al, 2002; Chang and Merzenich, 2003; Nakahara
et al, 2004). Since responses in the auditory cortex reflect the processing and
representation along the auditory pathway leading up to and including the auditory cortex,
it remains unclear whether and how the auditory cortical synaptic inputs contributes to
the plasticity effects. Our goal here is to investigate whether early auditory experience
results in specific changes of cortical synaptic inputs of a single neuron, and how these
synaptic changes account for auditory cortical plasticity.
84

Our previous studies indicate that early pulsed-noise exposure with a high frequency
cutoff at 18 kHz results in specific changes in TRFs of multi-unit spikes (Zhang et al,
2002). In particular, by examining the broadening of bandwidth we demonstrated the
existence of a critical period for the experience-dependent modification of the developing
auditory cortex. Since no broadening of bandwidth was found in rats exposed to same
sound during in adulthood (Zhang et al, 2002), the critical period for the auditory cortical
development lies within P9-P28.
1.13.1.2 Experimental Procedures
Early exposure of rat pups to noise. Litters of 10 nine-day-old rats and their
mothers were placed in a sound-shielded test chamber from P9 to P28. An 8-h
light/16-h dark cycle was applied. Pulses of 50-ms noise (5-ms ramp) at 65-dB sound
pressure level (SPL) and with a high frequency cutoff at 18 kHz were applied from a
speaker placed about 15 cm above rats. They were delivered at 6 pulses-per-second
with 1-s intervals to minimize adaptation effects.
The intensity of noise stimuli was similar to the total SPL in the animal room, a putative
normal environment. No distortion or significant harmonic signal was found in the
chamber when stimulus was delivered. There was no abnormality in the behavior of
either the mother or pups during noise exposure. The weights of all pups were normal,
indicating normal lactation. In addition, the intensity thresholds of tone-evoked
responses in A1 of noise-reared rats did not show significant difference compared to
control rats, suggesting that the cochlear is normal. (Zhang et al, 2002).
85

1.13.1.3 Results
Broadened spike TRFs induced by noise-raised environment. To examine the
plasticity change induced by the noisy environment during critical period (P9-P28),
recordings were first made in layer 4 neurons of those early noise-exposed rats aging
from P30-35. We specifically targeted the high-frequency representation region in A1 to
investigate the spike TRF responses and found that these neurons demonstrated a much
broadened tuning bandwidth (Figure 0.5), consistent with previous multi-unit recordings.
(Zhang et al, 2002)
Compared with ST3 animals raised under normal acoustic environments, these noise-
exposed rats didn’t exhibit the progressive refinement from ST2 to ST3 during
development but rather preserved the unselectively broad tuning to a wide ranges of
frequency, especially in the high-frequency region, indicating the early acoustic
experience were critical and instructive for the functional maturation in auditory cortex.

Figure 0.5 A neuron from A1 of P30 rat exposed to noise from P9-28.
86

Synaptic Mechanism Underlying Experience-Dependent Plasticity. The plasticity of
spike TRFs can be attributed to specific interplay of synaptic excitatory and inhibitory
inputs. It is generally believed that activity-dependent modification of synaptic
connections is a basis for experience-dependent plasticity of cortical representation and
processing (Katz and Shatz, 1996; Zhang and Poo, 2001). Hence, we carried out in vivo
whole-cell recordings to determine how the changes of cortical synaptic inputs contribute
to the TRF plasticity.
A broader spiking frequency range could be elicited by a general increase in the strength
of excitatory inputs, which would be reflected by a broader half 50%BW at 20 dB above
intensity threshold.
Whether and how inhibitory connections undergo activity-dependent modifications
during development are still unclear (Chang, 2003; Gaiarsa et al, 2002). Some evidence
suggests that the developmental strengthening of GABAergic inhibitory connections may
be mediated by neurotrophin in an activity-dependent manner. This suggests that relative
deprivation of sensory inputs may result in weaker-than-normal cortical inhibitory
connections, leading to the broadening of spike TRFs.

Figure 0.6 Synaptic inputs of a neuron from a P33 rat exposed to noise from P9-28
87

To clarify which one or more changes could account for the induced-plasticity of
functional TRFs, we would need to record more neurons with excitatory and inhibitory
responses (one example case in Figure 0.6) and quantify both changes of synaptic tuning
and best-frequency, and compare the data with that for normal adults.

1.13.2 Contribution of Thalamocortical Excitation and Intracortical
Excitation during Developmental Refinement
1.13.2.1 Background and Introduction
A1 neurons in layer 4, the recipient layer, receive direct thalamocortical inputs and
intracortical inputs together. The synaptic inputs are the all thalamocortical inputs which
are excitatory, intracortical excitatory inputs, and intracortical inhibitory inputs. The
output of the neuron (either spikes or subthreshold membrane potential changes) will be
determined primarily by the strength and spectrotemporal interactions of all inputs
together. In previous project, we investigated with in vivo whole-cell recording to
separate excitatory and inhibitory synaptic inputs and determined that the sharpening of
excitatory inputs (thalamocortical and intracortical together) contribute to the functional
refinement during development.
However, it is still unclear how the developmental changes of excitation can be attributed
to that of thalamocortical and intracortical inputs. Previous studies in visual and
somatosensory cortex indicate that both thalamic and intracortical connections undergo
88

developmental regulation, as evidenced in the developmental changes of the
thalamocortical axonal arbors and dendritic arbors of cortical neurons (Katz and Shatz,
1996; Katz and Crowley, 2002), as well as in the range of horizontal synaptic connections
examined in cortical slices (Dalva and Katz, 1994). So here I will apply the cocktail drug
(Musimol and SCH50911) to prevent the cortical spiking output and reveal the pure
thalamocortical inputs, to first examine whether there is a reduction in the spectral range
of thalamocortical inputs during development, which is indicative of thalamocortical
projection pruning. And furthermore, I will study the synaptic patterns of thalamocortical
and intracortical excitation during development to quantitatively analyze their
contribution towards the functional refinement.

1.13.2.2 Experimental Procedures
Separating thalamocortical inputs from intracortical inputs. The cortex was
pharmacologically silenced following the method established in our previous study (Liu,
et al., 2007). A cocktail of SCH50911 (6 mM; a specific antagonist of GABA
B
receptors)
and muscimol (4mM; an agonist of GABA
A
receptor) was used to effectively silence a
relatively large cortical region. The cocktail (dissolved in ACSF containing Fast Green)
were injected through a glass micropipette with a tip opening of 2–3 μm in diameter. The
pipette was inserted to a depth close to the recording site, around 700 μm. Solutions were
injected under a pressure of 3–4 psi for 5 min. The injected volume was estimated to be
around 20 nl, as measured with mineral oil. The staining by Fast Green was monitored
89

under the surgical microscope, which covered a cortical area with a radius of more than
500 μm by the end of the injection. Target neurons were treated with cocktail drug and
mapped for pure synaptic RFs contributed by thalamocortical inputs alone. If both before
and after drug application neural RFs were mapped, conductances for intracortical
excitatory inputs were derived afterward.

1.13.2.3 Results
Change of thalamocortical inputs during development. To explain the refinement of
excitatory inputs from stage 2 (P15-P18) to stage 3(P19- P25), we first examined the pure
thalamocortical inputs in different developmental stages. After silencing the cortical
activities with muscimol and SCH50911, synaptic responses were recorded with whole-
cell voltage clamp. As shown in Figure 0.7, a stage2 neuron exhibited a broad and
unselective RF, which is consistent with the flattened tuning in normal status; a stage3
neuron showed similar range of responses, but with a slightly better tuning. These results
are in consistent with our previous observation that there is no reduction in the total
spectral range of excitatory inputs during development, which may indicate no reduction
of thalamocortical projections.
90

Figure 0.7 Revealing pure thalamocortical inputs in neurons with muscimol and SCH50911.
A. a P15 neuron after cortical silencing exhibited flattened tuning responses. B. a P21
neuron after cortical silencing also exhibited wake tuning responses

Contribution of thalamocortical inputs and intracortical inputs to functional
refinement. However, to what extent the thalamocortical inputs and intracortical inputs
account for the refinement tuning of the excitatory inputs is still unclear. In order to
directly compare the two sources of excitatory inputs we applied the whole-cell recording
in the same cells before and after cocktail drug application, so that we could map the
synaptic RFs contributed by both sources as well as pure thalamocortical inputs, and
afterward through subtraction we could derive pure intracortical excitatory inputs.
As shown in Figure 0.8, after removing the cortical inputs, a neuron demonstrated a RF
of similar tuning but with proportionally decreased amplitude, as indicated in the almost
overlapped envelope curves. Direct comparison before and after cortical silencing, there
was no significant change of tuning shape, so we could know that the frequency tuning of
this neuron is largely determined by the thalamocortical input alone.
With this methodology, we are going to characterize the neural RFs at different stages to
quantitatively examine the contribution of thalamocortical and intracortical inputs to the
functional refinement during development.
91

Figure 0.8 RFs of a neuron before and after cortical silencing.
Responses at 20 dB above threshold were taken out and envelopes of tuning amplitude
were derived and normalized to compare the tuning shape of two different conditions.

92

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Creator Sun, Yujiao Jennifer (author)

Core Title Synaptic mechanism underlying development and function of neural circuits in rat primary auditory cortex

Contributor Electronically uploaded by the author (provenance)

School Keck School of Medicine

Degree Doctor of Philosophy

Degree Program Physiology and Biophysics

Publication Date 01/28/2013

Defense Date 12/07/2012

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag auditory cortex,circuitry function,Development,electrophysiology,in vivo,OAI-PMH Harvest,rat,synaptic,whole-cell

Language English

Advisor Zhang, Li I. (committee chair), Bottjer,Sarah W. (committee member), Chow, Robert H. (committee member), Farley, Robert A. (committee member), Tao, Huizhong W. (committee member)

Creator Email j.suninchina@gmail.com,sun_inchina@yahoo.com

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Abstract (if available)

Abstract A major question in brain sciences is how the brain develops into maturation, how it perceives external sensory stimulation, and how it adapts in responses to the environment. To address these questions, it is fundamental to dissect the cortical network structure and its underlying circuitry mechanism. Specifically, in a local circuit, information is processed vertically within a cortical column where the neuronal connectivity and functionality are different among cortical layers. Using rat primary auditory cortex (A1) as the research model, I studied the synaptic mechanism underlying circuitry function and development by applying in vivo whole-cell patch-clamp recording to record excitatory and inhibitory synaptic inputs driven by precisely controlled sound stimuli with different combination of duration, frequency, and intensity. ❧ In the first project of my dissertation, I explored the functional properties of the corticofugal neurons in layer 5, which are shown to be part of Feedback/corticofugal projections from A1 and play a role in modulating subcortical processing. I found that intrinsic-bursting (IB) neurons, the layer 5 corticofugal neurons, exhibited early and rather unselective spike responses to a wide range of frequencies. The exceptionally broad spectral tuning of IB neurons was attributable to unusually broad excitatory inputs with long temporal durations, and inhibitory inputs being more narrowly tuned than excitatory inputs. This uncommon scenario of excitatory-inhibitory interplay was attributed initially to a broad thalamocortical convergence onto IB neurons, which also receive temporally prolonged intracortical excitatory input and feedforward inhibitory input from more narrowly tuned fast-spiking neurons. In contrast, regular-spiking (RS) neurons in layer 5, which are mainly corticocortical, exhibited sharp frequency tuning similar as layer 4 pyramidal cells, with the underlying well-matched, more distantly relayed excitation and inhibition. The functional dichotomy of layer 5 pyramidal neurons suggests two distinct processing streams. The spectrally and temporally broad synaptic integration in IB neurons may ensure robust feedback signals to facilitate subcortical processing in a general manner. ❧ In the second project of my dissertation, I turned to layer 4 neurons to study their synaptic mechanism underlying progressive refinement of functional receptive fields during development. In this study, I examined the developmental changes in frequency-intensity tonal receptive fields (TRFs) of excitatory and inhibitory inputs to test three potential synaptic circuit models underlying the functional development. I found rather balanced excitation and inhibition at the earliest stage (P12) that tone-evoked cortical responses can be detected, which suggests that a hardwired feedforward circuit exists prior to the incoming of auditory input. During development, the spectral range of excitatory and inhibitory inputs is initially broadened and then persists into adulthood. The latter phase is accompanied with a significant functional modification of excitatory inputs, resulting in a sharpening of excitatory tuning, and relatively broadly tuned inhibition. Thus, the functional refinement of cortical neurons during development is marked by a slight breakdown of pre-balanced excitation and inhibition. These results suggest that functional refinement of cortical TRFs may not require elimination of presynatpic inputs, but can be achieved through a fine adjustment of synaptic strengths.