Parallel processing by cortical inhibition enables context-
dependent behavior
Kishore V. Kuchibhotla
1,2
, Jonathan V. Gill
1,2
, Grace W. Lindsay
3
, Eleni S. Papadoyannis
1,2
,
Rachel E. Field
1,2
, Tom A. Hindmarsh Sten
1,2
, Kenneth D. Miller
3
, and Robert C.
Froemke
1,2,*
1
Skirball Institute, Neuroscience Institute, Departments of Otolaryngology, Neuroscience and
Physiology, New York University School of Medicine, New York, NY, 10016, USA
2
Center for Neural Science, New York University, New York, NY, 10003, USA
3
Center for Theoretical Neuroscience, Department of Neuroscience, Swartz Program in
Theoretical Neuroscience, Kavli Institute for Brain Science, Columbia University, New York, NY
10032, USA
Abstract
Physical features of sensory stimuli are fixed, but sensory perception is context-dependent. The
precise mechanisms that govern contextual modulation remain unknown. Here, we trained mice to
switch between two contexts: passively listening to pure tones vs. performing a recognition task
for the same stimuli. Two-photon imaging showed that many excitatory neurons in auditory cortex
were suppressed, while some cells became more active during behavior. Whole-cell recordings
showed that excitatory inputs were only modestly affected by context, but inhibition was more
sensitive, with PV, SOM+, and VIP+ interneurons balancing inhibition/disinhibition within the
network. Cholinergic modulation was involved in context-switching, with cholinergic axons
increasing activity during behavior and directly depolarizing inhibitory cells. Network modeling
captured these findings, but only when modulation coincidently drove all three interneuron
subtypes, ruling out either inhibition or disinhibition alone as sole mechanism for active
engagement. Parallel processing of cholinergic modulation by cortical interneurons therefore
enables context-dependent behavior.
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*
Correspondence to: robert.froemke@med.nyu.edu.
ACCESSION CODES
Not applicable
AUTHOR CONTRIBUTIONS
K.V.K. and R.C.F. designed experiments and wrote the manuscript. K.V.K., J.V.G., R.E.F, and E.S.P. conducted experiments. K.V.K.,
T.A.H.S. and J.V.G. performed analysis. G.W.L. and K.D.M. performed network modelling.
COMPETING FINANCIAL INTERESTS
The authors have no competing financial interests.
DATA AVAILABILITY STATEMENT
All code related to the modeling work is available at
http://froemkelab.med.nyu.edu/. The data that support the findings of this study
are available from the corresponding author upon request.
HHS Public Access
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Nat Neurosci
. Author manuscript; available in PMC 2017 April 30.
Published in final edited form as:
Nat Neurosci
. 2017 January ; 20(1): 62–71. doi:10.1038/nn.4436.
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INTRODUCTION
Sensory stimuli convey critical information about various types of opportunities and threats,
including access to nourishment, the presence of predators, or the needs of infants. The same
sensory stimulus, however, can have different meanings based on previous learned
associations and the contexts within which it is presented
1–9
. For example, in language
processing, the same words often have multiple meanings. Humans determine the meaning
of these words by integrating prior knowledge with context to converge on a relevant
interpretation
10,11
. How does the brain enable such interpretation of sensory cues based on
behavioral context? We propose that three network features would enable context-dependent
processing of external stimuli by neural circuits: some components must be stable and
provide a high fidelity representation of a sensory stimulus independent of context, other
components must be dynamic and rapidly adjust when context changes, and finally there
must be instructive signals that convey the global contextual milieu.
The mammalian auditory cortex is a major site of contextual modulation during acoustic
behaviors, such that task engagement alters the spiking of principal neurons even when there
is no change in the external sensory cue
1–4,12–18
. Whether or not a stimulus will produce
one or more action potentials depends on the strength and timing of excitatory and inhibitory
synaptic inputs. In the adult, excitatory and inhibitory inputs are correlated during passive
presentation of acoustic stimuli; this co-tuning and correlation of synaptic responses is
referred to as ‘excitatory-inhibitory balance’
19–24
. However, episodes of learning and
periods of heightened attention or arousal activate neuromodulatory systems that can lead to
the transient uncoupling of excitation from inhibition. This temporary period of increased
excitability is effective at inducing long-term modifications of synaptic strength and
receptive field organization
25–27
. For example, pairing stimulation of the cholinergic nucleus
basalis with presentation of an acoustic stimulus leads to long-term changes in receptive
field properties of auditory cortical neurons
28,29
, via changes in inhibition
25
. Cholinergic
activity also contributes to task performance by signaling positive and negative
reinforcement, potentially through cortical interneurons
6,30–32
. These links between
neuromodulation, inhibitory synaptic transmission, and behavioral changes may be a general
feature of nervous system organization. For example, a recent study showed that cholinergic
activation of dendritic inhibition in the hippocampus can enable fear learning
33
.
Context-dependent activity, however, requires rapid changes on a trial-to-trial basis.
Neuronal ensembles must adjust their firing rate in a reversible manner based solely on
contextual cues
2,4,13,15
. These types of context-dependent responses diverge from the
longer-term memory traces and reinforcement mechanisms that have been previously
described
6,25,30,33
but may co-opt some of the underlying circuitry. The relationship between
excitation and inhibition may simply scale (up or down) based on attentional demands.
However, such co-tuned scaling might restrict state-dependent flexibility. Instead, theoretical
work suggests that inhibitory inputs can be preferentially regulated by neuromodulation
34
.
These synaptic and circuit mechanisms have been difficult to resolve because of the need to
monitor complex input-output dynamics of excitatory, inhibitory and neuromodulatory
inputs. Here we take an integrative approach to measure, manipulate and model the impact
of behavioral engagement on a cortical circuit in behaving mice. We combine (i) cell-type
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specific two-photon calcium imaging to measure network output, (ii) whole-cell voltage-
clamp recordings of excitatory and inhibitory inputs, (iii) calcium imaging of cholinergic
axons to monitor neuromodulatory inputs, (iv) optogenetics to manipulate all core
components of the circuit, and (v) a theoretical model to integrate and test the robustness of
our findings.
RESULTS
A context-switching task that depends on the auditory cortex
To determine how behavioral context influence network dynamics, we trained head-fixed
mice on an active versus passive context-switching task using a block-based experimental
design (Fig. 1a, Supplementary Figure 1a). For the active listening context (“active
context”), we trained animals on an auditory go/no-go stimulus recognition task. Mice
learned to lick for a water reward provided through a lick tube after hearing the reinforced
conditioned stimulus (the target tone, Supplementary Figure 1b) and to withhold from
licking after hearing an unrewarded pure tone of a different frequency (the foil tone,
Supplementary Figure 1c). In the passive context, the lick tube was removed and mice were
exposed to the same sounds (target and foil) but animals did not produce a behavioral
response (Supplementary Video 1). Importantly, the absence of licking in the passive context
(i.e., the sensorimotor response in response to the target tone) was completely voluntary
since it was not reinforced with reward or punishment. The choice to behave was therefore
externally triggered by the presence or absence of the lick tube. This task required auditory
cortex, as bilateral muscimol infusions into auditory cortex significantly impaired behavioral
performance in the active context (Fig. 1b; n=3 animals, d′=3.0±0.2, muscimol d
′=0.8±0.3%, mean±s.e.m., p<0.05, Student’s paired two-tailed t-test).
Rapid and reversible context-dependent changes in A1 network output
To determine how auditory cortex responds to the conditioned stimuli in both contexts, we
first imaged the activity of 1,595 neurons in cortical layer 2/3 in five mice in the two
different contexts. To select the target and foil tones, we performed two-photon imaging in
awake mice virally expressing GCaMP6s while presenting pure tones between 4–64 kHz at
70 dB sound pressure level (SPL) before behavioral training (Fig. 1c, d). We used two
criteria in selecting the stimuli: 1) the imaged focal planes had neurons with tone-evoked
calcium responses to the target and foil (Fig. 1c), and 2) both tones were within one octave
of each other (Fig. 1d). After selecting the target and foil, we conducted behavioral training
(Fig. 1e, Supplementary Figure 1d) until mice reliably responded to the target tone with
licking (hits) and withheld licking responses to the foil tone (correct rejects) (Fig. 1e, n=23
mice, d′=2.5±0.3, hit rate=92.5±1.7%, mean±s.e.m.). All mice reached threshold within 3–
13 sessions (Supplementary Figure 1d). All imaging data underwent a detailed motion-
correction protocol (see Experimental Procedures, Supplementary Figures 2–3,
Supplementary Videos 2–3) and were similar to established methods
33
.
We observed broad-based suppression of neural responses to both the target and foil tones
during the active context in a majority of neurons we imaged (Fig. 2a–d, n=135/227 target-
responsive cells, n=146/210 foil-responsive cells, neurons were tested for responsiveness by
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comparing tone-evoked response to baseline values, p<0.05, Student’s paired two-tailed t-
test), consistent with previous extracellular recordings
1,2,9
. Surprisingly, some neurons
showed an increase in activity during the task when compared to the responses in the passive
context (Fig. 2b–d, n=92/227 target-responsive cells, n=64/210 foil-responsive cells, p<0.05
for responsiveness per neuron, Student’s paired two-tailed t-test). A continuum of context-
dependent changes, from suppression to facilitation, was clear across animals (Fig. 2e;
p<0.001, Kolmogorov-Smirnov test). The continuum from broad suppression to selective
facilitation was also apparent when we restricted GCaMP6s expression to excitatory neurons
(Fig. 2f–h; n=620 neurons, n=142 responsive, 67% suppressed, 33% activated in the active
context).
Neurons responsive to either the target or foil tones showed a similar modulation by
behavioral context (median context modulation for target tones: −13.8±4.8%, median
context modulation for foils: −16.8±4.0%, median ± 95% confidence intervals, Fig. 2c, d,
bottom; dashed lines denote significance threshold generated from a shuffled dataset). This
indicates that task-related modulation was not due to expectation of reward on a given trial
or delivery of water. Changes in neural activity occurred rapidly, within 1–2 trials of
switching contexts (Supplementary Figure 4), supporting the existence of an ensemble-level
switch. Neurons whose best frequency was close to either the target or foil (best frequency
<0.25 octaves from target or foil; target, n=51 cells, foil, n=24 cells) were most likely to be
suppressed during the active context (Supplementary Figure 5). Conversely, neurons with
best frequencies that were further from the target or foil (best frequency ≥0.25 octaves from
target and foil) were more likely to be more responsive during the active context
(Supplementary Figure 5). Thus, behavioral context rapidly alters A1 responses, leading to a
continuum of response suppression and facilitation.
Cell-type specific activity profiles in auditory cortex
The activity of diverse inhibitory subpopulations may play a key role in generating the
network output phenotype of both suppression and facilitation. We focused on the three
interneuron subtypes that make up ~80% of cortical interneurons: PV-positive, SOM-
positive, and VIP-positive interneurons
35
. These three interneuron subtypes are thought to
make up a canonical cortical circuit
7,31,36
. To examine the responses of inhibitory cells, we
expressed GCaMP6s in
PV-tdTomato, SOM-tdTomato
or
VIP-tdTomato
mice and imaged 65
PV+, 159 SOM+ and 90 VIP+ layer 2/3 interneurons in A1 during active and passive
contexts (Fig. 3; cell inclusion approach in Supplementary Figure 6). In contrast to the
excitatory pool (Fig. 3b), inhibitory neurons showed robust change in baseline activity, with
VIP+ interneurons showing the largest changes, followed by SOM+ interneurons and then
PV+ interneurons (Fig. 3b). Tone-evoked responses were also modulated in all subtypes
with PV+ and SOM+ interneurons (Fig. 3c–f) preferring the active context unlike the
excitatory pool (Fig. 3c–d; ‘PV+’, n=31 tone-responsive PV+ interneurons, 19/31 increased
activity, p<0.01 compared to excitatory pool where 47/142 increased activity, Fisher’s exact
test; Fig. 3e–f, ‘SOM+’, n=20 tone-responsive SOM+ interneurons, 12/20 increased activity,
p<0.01 compared to excitatory pool where 47/142 increased activity, Fisher’s exact test).
While VIP+ interneurons showed the strongest baseline modulation, tone-evoked responses
from VIP+ interneurons were muted in comparison and preferred the passive context, similar
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to excitatory neurons (Fig. 3g, h). Thus, cortical interneurons are highly sensitive to
behavioral context in unique ways suggesting that local inhibition may gate contextual
information.
Synaptic inhibition acts as a switch to gate the flow of contextual information
Given the context-dependent neural output dynamics observed in inhibitory and excitatory
networks, we wondered whether changes in excitatory-inhibitory balance might underlie the
shifts in network activity. Balanced inhibition helps to control overall excitability and
information processing. It may be a general property of developed cortical circuits in the
auditory system
20,24,26
and other sensory modalities
23,35
. Co-tuning of inhibition with
excitation may be disrupted in epochs of high attention or arousal and differentially affect
inhibitory transmission or inhibitory neuron activity
25,34,38–40
. Behavioral context might
modulate both tone-evoked excitation and inhibition in the same direction (increasing or
decreasing excitatory and inhibitory inputs together). Alternatively, changes in context might
transiently disrupt excitatory-inhibitory balance, enhancing perceptual salience by selective
modulation of either excitation or inhibition.
We tested these hypotheses by measuring synaptic activity onto putative excitatory neurons
with whole-cell voltage-clamp recordings in behaving animals (Fig. 4a). We measured
excitatory and inhibitory postsynaptic currents (EPSCs and IPSCs) in both the active and
passive contexts (n=12 cells, n=4 mice). We observed significantly more context-dependent
changes in IPSCs than EPSCs (Fig. 4b–e). Interestingly, the sign of inhibitory modulation
was heterogeneous. In some cells, the active context enhanced tone-evoked inhibition (Fig.
4b–d), whereas inhibition was decreased in other cells, with an overall broader distribution
of inhibitory changes (Fig. 4d). Comparing the absolute values of inhibitory vs. excitatory
changes revealed that during the active context, IPSC amplitudes were more than twice as
affected as EPSC amplitudes (Fig. 4e, ΔIPSC: 34.9±4.1%, ΔEPSC: 16.1±3.5%, n=12 cells,
p<0.009, Student’s paired two-tailed t-test, green circles denote significant changes in
currents; ΔIPSC median p-value per cell is 0.03; ΔEPSC median p-value is 0.30; Student’s
paired two-tailed t-test within neuron). Tone-evoked EPSCs and IPSCs in behaving animals
could be measured before the onset of licking, providing further evidence that motor-related
suppression was not confounding our experiments.
We predicted firing rates using an integrate-and-fire model with our measured IPSCs and
EPSCs. We observed both functional classes of neurons (activated and suppressed) that we
observed with calcium imaging (Supplementary Figure 7a–c, n=5 neurons showing
suppression, p<0.01, two-sided Wilcoxon rank sum test for active versus passive context;
Supplementary Figure 7d–f, n=2 neurons showing activation, p<0.01, two-sided Wilcoxon
rank sum test; n=5 neurons with no significant change in model-derived spiking). In two
instances, we were able to record spiking activity in cell-attached configuration in the same
cells where we later measured IPSCs and EPSCs after breaking in (Supplementary Figure
7g–i). In both cases, the IPSC context modulation governed whether neuronal spiking was
suppressed (Supplementary Figure 7h) or activated (Supplementary Figure 7i) in the active
context. Moreover, the measured spiking output (Supplementary Figure 7g–i, top row) was
similar to the predicted spiking output calculated from the synaptic measurements
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