Neuron

Article

Synaptic and Network Mechanismsof Sparse and Reliable Visual Cortical Activityduring Nonclassical Receptive Field StimulationBilal Haider,1 Matthew R. Krause,1 Alvaro Duque,1 Yuguo Yu,1 Jonathan Touryan,1 James A. Mazer,1,3

and David A. McCormick1,2,3,*1Department of Neurobiology2Kavli Institute for NeuroscienceYale University School of Medicine, 333 Cedar Street, New Haven, CT 06510, USA3These authors contributed equally to this work

*Correspondence: david.mccormick@yale.edu

DOI 10.1016/j.neuron.2009.12.005

SUMMARY

During natural vision, the entire visual field is stimu-lated by images rich in spatiotemporal structure.Although many visual system studies restrict stimulito the classical receptive field (CRF), it is knownthat costimulation of the CRF and the surroundingnonclassical receptive field (nCRF) increases neu-ronal response sparseness. The cellular and networkmechanisms underlying increased response sparse-ness remain largely unexplored. Here we show thatcombined CRF + nCRF stimulation increases thesparseness, reliability, and precision of spiking andmembrane potential responses in classical regularspiking (RSC) pyramidal neurons of cat primary visualcortex. Conversely, fast-spiking interneurons exhibitincreased activity and decreased selectivity duringCRF + nCRF stimulation. The increased sparsenessand reliability of RSC neuron spiking is associatedwith increased inhibitory barrages and narrowervisually evoked synaptic potentials. Our experi-mental observations were replicated with a simplecomputational model, suggesting that network inter-actions among neuronal subtypes ultimately sharpenrecurrent excitation, producing specific and reliablevisual responses.

INTRODUCTION

Is the cortical code for sensory information redundant, or is it

sparse and efficient? One influential theory proposes that

sensory systems use highly selective stimulus representations

that optimize metabolic efficiency by minimizing the number of

action potentials (Barlow, 1972). Numerous studies have shown

that appropriate stimuli (e.g., high-contrast bright or dark bars)

placed in a restricted portion of the visual field increase the firing

rates of neurons in primary visual cortex; this area of maximal

sensitivity is termed the minimum response field or classical

receptive field (CRF; DeAngelis et al., 1993; Hubel and Wiesel,

1962; Movshon et al., 1978). However, stimulation of regions

adjacent to the CRF (collectively termed the nonclassical recep-

tive field, nCRF), where the same stimuli fail to elicit spikes, can

modulate responses to CRF stimuli in complex and often

nonlinear ways. Typically, costimulation of the CRF + nCRF

suppresses spiking responses compared with CRF stimulation

alone, although there are also examples of nCRF-mediated

contextual enhancement (Angelucci and Bressloff, 2006; Cava-

naugh et al., 2002a; Fitzpatrick, 2000; Gilbert et al., 1996; Jones

et al., 2001; Kapadia et al., 1995; Webb et al., 2005). Integrating

the modulatory properties of the nCRF with established pro-

perties of the CRF into a single model framework is an essen-

tial step toward a complete understanding of cortical infor-

mation coding and neuronal responsiveness (see Carandini

et al., 2005).

Recent studies in awake, behaving primates, motivated in part

by the efficient coding hypothesis, have suggested an alternative

framework for considering nCRF modulation of CRF activity.

During naturalistic visual stimulation of both the CRF + nCRF,

spiking responses in primary visual cortex are neither uniformly

suppressed nor facilitated, but instead display nonlinear modu-

lations resulting in a net increase in response sparseness (Vinje

and Gallant, 2000). In these studies and others, response

sparseness serves as a proxy for neural selectivity: a neuron

with increased sparseness responds to a more restricted set of

stimuli, and is thus more selective across the entire stimulus

set (Lehky et al., 2005; Olshausen and Field, 2004; Rolls and

Tovee, 1995; Tolhurst et al., 2009; Yao et al., 2007; Yen et al.,

2007). Compared with stimulation of the CRF alone, sparser

spike responses elicited by wide-field stimulation contain

specific epochs of both suppression and facilitation that, as

a whole, transmit more information about the stimulus (Vinje

and Gallant, 2002). However, it remains unclear how sparse

single-neuron responses can be reliably transmitted to down-

stream neurons in the face of typical trial-to-trial response vari-

ability (Shadlen and Newsome, 1998; Stein et al., 2005). It is

therefore critical to determine how the cortical network over-

comes this inherent response variability in order to generate

and transmit sparse neuronal responses during wide-field stim-

ulation.

One important observation that may help explain the origins of

sparse sensory coding is that the amplitude and timing of action

Neuron 65, 107–121, January 14, 2010 ª2010 Elsevier Inc. 107

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Selective and Reliable Spiking in Visual Cortex

potentials depends critically upon the connectivity and activity

levels of presynaptic excitatory and inhibitory neuronal subtypes

(Azouz et al., 1997; Bruno and Sakmann, 2006; Contreras and

Palmer, 2003; Silberberg and Markram, 2007; Swadlow, 2003;

Yoshimura and Callaway, 2005). The net pattern of activity

across the distributed network of presynaptic neuronal subpop-

ulations is collectively visible in a single neuron’s membrane

potential fluctuations, where the amplitude and precise timing

of excitatory and especially inhibitory potentials is a critical factor

in determining exactly when a given pyramidal neuron spikes

(Gabernet et al., 2005; Haider and McCormick, 2009; Hasen-

staub et al., 2005; Higley and Contreras, 2006; Pouille and Scan-

ziani, 2001; Wehr and Zador, 2003).

Here, we report that wide-field naturalistic stimulation of clas-

sical regular spiking (RSC) pyramidal neurons in cat primary

visual cortex both increased the amplitude of inhibitory postsyn-

aptic potentials (IPSPs) and increased the trial-to-trial reliability

of excitatory postsynaptic potentials (EPSPs). These synaptic

events were mirrored by spiking activity recorded in specific

excitatory and inhibitory neuronal subpopulations. Injection of

these recorded PSP sequences into a simple computational

model revealed that while both changes in IPSPs and EPSPs

contributed to the sparseness and reliability of spiking

responses during CRF + nCRF stimulation, IPSPs were the pri-

mary cause of increased neuronal sparseness, while the EPSPs

greatly enhanced trial-to-trial spike reliability and predominantly

shaped the overall spiking response. These combined excitatory

and inhibitory network interactions may ultimately explain the

highly selective and more reliable neuronal activity observed in

visual cortex in response to naturalistic sensory inputs.

RESULTS

Stimulus Presentation and Experimental ApproachWe performed extracellular and intracellular recordings in cat

primary visual cortex during presentation of naturalistic movie

sequences masked by circular apertures of two sizes. One

restricted the movie to the CRF (as defined quantitatively, see

Experimental Procedures and Supplemental Experimental

Procedures available online), while the other was larger and

resulted in costimulation of both the CRF and the surrounding

nCRF. Note that in both configurations visual stimulation within

the CRF was identical—only the size of the aperture was

changed (from a radius of 1X CRF to 3X CRF).

We first present results obtained from electrophysiologically

identified classical regular spiking (RSC) neurons, the most abun-

dant and most frequently recorded cortical neuronal subtype

(Nowak et al., 2003).

CRF + nCRF Stimulation of RSC Neurons IncreasesResponse Sparseness and Membrane HyperpolarizationIsolated CRF stimulation in a typical RSC neuron elicited robust

action potentials across repeated presentations of the stimulus

(Figures 1A and 1C). Both the temporal structure and amplitude

of this neuron’s response changed dramatically in response to

the larger CRF + nCRF stimulus (Figures 1B and 1D), including

a reduction in amplitude and change in stimulus frame eliciting

a maximal response (compare black and red arrowheads Fig-

108 Neuron 65, 107–121, January 14, 2010 ª2010 Elsevier Inc.

ures 1C and 1D). In addition, this neuron was markedly hyperpo-

larized during CRF + nCRF stimulation compared with CRF alone

stimulation (dashed lines in Figures 1A and 1B), while depolariz-

ing synaptic activity was sharper and more reliable across

repeated presentations during CRF + nCRF stimulation (Fig-

ure 1B), compared with CRF-alone stimulation (Figure 1A). As

a result, the neuron responded to fewer movie frames and

spiking responses were more transient and temporally precise.

This neuron exhibited a net decrease in responsiveness

throughout the CRF + nCRF movie, although some peaks in

the peristimulus time spike histogram (PSTH) were only mildly

reduced (Figure 1C, closed arrows) while others were nearly

abolished (Figure 1C, open arrows). In other RSC neurons, the

effects of CRF + nCRF stimulation were more complex: some

frames elicited greater spiking activity in the CRF + nCRF con-

figuration, while other frames elicited reductions (Figure S1).

This finding, consistent with previous studies in awake, behaving

primates (Vinje and Gallant, 2000), suggests that dynamic, spa-

tiotemporally rich CRF + nCRF costimulation engages more

complex mechanisms than uniform response suppression.

To quantify these complex changes in responsiveness, we

compared the lifetime sparseness of spike responses in the

two stimulation conditions (see Experimental Procedures; see

also Vinje and Gallant, 2000; Willmore and Tolhurst, 2001).

Sparseness is a nonparametric measure of neuronal selectivity

that is a property of both the neuron and the stimulus set. For

a fixed stimulus set, sparseness can be computed without

knowledge of a neuron’s classical tuning properties (i.e., orienta-

tion, spatial frequency, and phase tuning) and thus provides

a robust metric for quantifying changes in selectivity without

requiring assumptions about, or complete measurements of,

the underlying spatiotemporal tuning profile of either the CRF

or the nCRF. The sparseness metric (S) we use here is bounded

between 0 and 1 (Vinje and Gallant, 2000); S approaches 0 for

nonselective neurons that respond equally to all movie frames

(dense coding) and approaches 1 for highly selective neurons,

where, in the limiting case, spikes are elicited by a single movie

frame (sparse coding). CRF + nCRF stimulation resulted in

a significantly sparser response compared with CRF alone stim-

ulation in all RSC neurons (Figure 1E; n = 13), with a population

average 23% increase in lifetime sparseness (Figure 1E; see

figure legends for all p values throughout). Importantly, we

observed the same pattern of increased sparseness in our extra-

cellular multiunit (MU) recording data (18% average increase in

sparseness; n = 16 MU recordings; Table S1), and we confirmed

that this effect was not simply due to CRF/nCRF boundary stim-

ulation (Table S1).

Interestingly, we observed a significant hyperpolarization in

10/13 RSC neurons (mean �1.6 mV) during CRF + nCRF stimu-

lation (Figure 1F; n = 13). Hyperpolarization appears to contribute

in part to increased selectivity, because hyperpolarizing neurons

with direct negative current injection during CRF movie presen-

tation also increased response selectivity. However, on average,

the rate of increase in sparseness with DC injection-induced

hyperpolarization during CRF-alone stimulation was much

less than that occurring during natural CRF + nCRF hyperpolar-

ization (0.07 DS per mV DC hyperpolarization, versus 0.22 DS per

mV with natural CRF + nCRF hyperpolarization; n = 10 RSC

Figure 1. Naturalistic Wide-Field Visual Stimula-

tion Increases Selectivity

(A) Intracellular responses of an RSC neuron to repeated

presentations (five) of a natural scene movie restricted to

the classical receptive field (CRF). Average membrane

potential (Vm) = –57.8 mV. Inset shows extent of the movie

overlying the CRF; mask was opaque during recordings.

The selectivity or sparseness index (S) was 0.29 ± 0.01

(mean and standard error of the mean [± SEM]

throughout).

(B) Responses to five repeats of the same movie with

a larger aperture that stimulated portions of the nonclas-

sical receptive field (nCRF) in addition to the CRF. Average

Vm = –65.7 mV. Sparseness increased to 0.72 ± 0.01. See

also Movie S1.

(C and D) Histograms of spiking responses to CRF stimu-

lation (black) and (D) combined CRF + nCRF stimulation

(red). Peak CRF response to best frame (45.9 Hz; black

arrowhead) occurs 1.4 s after movie onset. Peak CRF +

nCRF response (17.2 Hz; red arrowhead) occurs 0.6 s after

movie onset. Histograms appear twice (C and D) and are

overlaid to facilitate comparison. Note that CRF + nCRF

costimulation results in the suppression of some peaks

present in the CRF response (open arrows), while others

are less affected (closed arrows). See also Figure S1.

(E) Spiking responses became significantly more sparse

(see text) in all 13 neurons (inset), corresponding to

a 23% net increase in sparseness with combined

CRF + nCRF stimulation (SCRF + nCRF = 0.69 ± 0.02) com-

pared with CRF alone stimulation (SCRF = 0.56 ± 0.02;

p < 0.01) across the population of RSC neurons. See

also Tables S1 and S2.

(F) Neurons were significantly hyperpolarized (–1.6 mV on

average; 10/13 individually, inset) during CRF + nCRF

stimulation (Vm CRF + nCRF = –65.3 ± 0.4 mV; Vm CRF =

–63.7 ± 0.6 mV; p < 0.01) in comparison to CRF only

stimulation.

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Selective and Reliable Spiking in Visual Cortex

neurons; p < 0.01; data not shown; see Supplemental Informa-

tion), suggesting that additional mechanisms beyond simple

hyperpolarization must be involved in increasing neuronal

selectivity.

Isolated nCRF Stimulation of RSC NeuronsDoes Not Increase Selectivity or Elicit MembranePotential HyperpolarizationWe found that nCRF stimulation alone (annulus) cannot account

for the observed effects, because it did not significantly increase

average firing rates above spontaneous activity, in either intra-

cellularly recorded RSC neurons or in MU responses (Table

S2), nor did it result in a net change in the average membrane

potential compared with a blank screen (Table S2). However,

compared with spontaneous activity, there was a significant

increase in membrane potential standard deviation in RSC cells

during nCRF stimulation, indicative of increased synaptic

activity, consistent with previous reports (Monier et al., 2003).

Taken together, these observations indicate that nCRF costi-

mulation counterbalances much of the strong average depolar-

ization associated with CRF stimulation, either through a reduc-

tion in visually evoked EPSP, or an increase in IPSP, barrages.

CRF + nCRF Stimulation Increases the Amplitudeof IPSP BarragesTo examine the specific contributions of excitation and inhibition

to visual selectivity in RSC neurons, we pharmacologically

blocked several intrinsic neuronal conductances by including

QX-314 (blocks Na+ currents and the h-current) and Cs+ (blocks

K+ currents) in the intracellular recording electrode. We then com-

pared EPSPs and IPSPs evoked by CRF and CRF + nCRF stimu-

lation in neurons tonically hyperpolarized to around�75 mV (near

the reversal potential for GABAergic Cl� inhibition) or depolarized

to around 0 mV (near the reversal potential for glutamatergic exci-

tation) with intracellular current injection (see Experimental

Procedures). Stimulation of the CRF + nCRF resulted in a large

increase in average IPSP amplitude relative to CRF alone stimu-

lation (Figure 2A, blue trace; increase is downward for IPSPs),

with little or no effect on average EPSP amplitude (Figure 2B).

Across the population of RSC neurons (n = 9), we found a signifi-

cant increase in the overall amplitude of evoked IPSPs (Figure 2C,

blue, DIPSP = �1.99 ± 0.4 mV; 43.7 ± 12.0% increase) and no

significant difference in the overall amplitude of EPSPs evoked

by CRF + nCRF stimulation compared with CRF alone stimulation

(Figure 2C, red, DEPSP = 0.33 ± 0.2 mV; 4.9 ± 4.3% increase).

Neuron 65, 107–121, January 14, 2010 ª2010 Elsevier Inc. 109

Figure 2. Wide-Field Visual Stimulation Selectively Increases the Amplitude of Inhibitory Postsynaptic Potentials

(A) Average inhibitory postsynaptic potentials (IPSPs) recorded during 12 presentations of a naturalistic movie to the CRF (black traces) and to the CRF + nCRF

(blue). QX-314 and Cs+ in micropipette. Upper and lower thin traces indicate ± SEM. Dashed vertical line indicates movie onset, downward deflections indicate

IPSPs. Some IPSP barrages increase greatly (closed arrows), while others change little (open arrows). CRF + nCRF stimulation significantly increases average

IPSP amplitude (compared with average response during CRF stimulation) in this cell by –2.73 ± 0.51 mV (p < 0.01; recorded at 0 mV).

(B) In contrast to IPSPs, EPSPs (recorded at –75 mV) did not significantly differ in amplitude between the two conditions (–0.41 ± 0.61 mV; p > 0.1). The neuron

shown here is the same neuron as shown in Figures 1A and 1B after spike inactivation.

(C) Population differences in EPSPs (red) and IPSPs (blue) evoked with CRF + nCRF stimulation, compared with CRF alone stimulation. All nine neurons were

determined to be RSC before spike inactivation. CRF + nCRF evoked IPSP barrages were significantly larger on average (blue, –1.99 ± 0.4 mV; 43.7 ± 12.0%

increase; p < 0.01) while EPSP barrages were not (0.33 ± 0.2 mV; 4.9 ± 4.3% increase; p > 0.1). Values are mean ± SEM.

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Selective and Reliable Spiking in Visual Cortex

CRF + nCRF Stimulation of Fast-Spiking InterneuronsDecreases Selectivity and Increases ResponseAmplitudeThe finding of increased visually evoked IPSPs barrages in RSC

neurons during CRF + nCRF stimulation suggests that this

change is partially driven by increased activity in one or more

subtypes of cortical inhibitory neurons. The only subtype of

inhibitory neuron unambiguously identifiable under our recording

conditions is the fast-spiking (FS) interneuron (Nowak et al.,

2003). Recordings from electrophysiologically identified FS

cells (Figure 3C inset) revealed increased firing rates and

decreased response sparseness during CRF + nCRF stimulation

(Figures 3A–3C and 4E). As with changes in RSC spiking activity,

CRF + nCRF stimulation elicited nonlinear changes in FS inter-

neuron activity (Figures 3B and 3C open arrows), as echoed by

nonlinear modulation of IPSPs recorded in RSC neurons (see

Supplemental Information).

CRF + nCRF Stimulation of Thin-Spike Regular-SpikingNeurons, like FS Interneurons, Results in DecreasedResponse Sparseness and Increased ResponseAmplitudeWhile searching for FS interneurons, we preferentially recorded

from neurons with thin action potentials, this being one of

several—but not the only—defining characteristic of FS interneu-

rons (Nowak et al., 2003). As a result, we also recorded from

a substantial fraction of neurons with unusually thin action poten-

tials that nonetheless exhibited spike frequency adaptation to

current pulse injection (Figure 4D, inset) with sustained firing rates

<200 Hz during the pulse. These neurons have previously been

110 Neuron 65, 107–121, January 14, 2010 ª2010 Elsevier Inc.

shown to belong to a subclass of regular spiking neurons termed

thin-spike regular-spiking neurons (RSTS; Figure S2; Nowak et al.,

2003). Intracellular labeling of these neurons revealed them to be

spiny pyramidal neurons (Figure S2), consistent with previous

reports (Nowak et al., 2003). RSTS cells are distinct from chatter-

ing neurons (which also display thin spikes) in that they do not

discharge intrinsic bursts of action potentials (Nowak et al.,

2003). The majority (11/15 or 73%) of RSTS neurons, like FS inter-

neurons, showed significantly increased firing rates (see below)

and decreased response sparseness during CRF + nCRF stimu-

lation (Figures 3D–3F).

FS and RSTS Neurons Are Functionally Distinctfrom RSC NeuronsNot only did these three classes of cells (RSC, FS, and RSTS)

exhibit differences in their response to wide-field visual stimula-

tion, but they also displayed unique biophysical properties. As

previously reported, both FS and RSTS neurons exhibit signifi-

cantly narrower spike widths (0.19 ± 0.01 and 0.24 ± 0.02 ms

at half height, respectively) and significantly faster membrane

time constants (t) compared with RSC neurons (Table S3; Nowak

et al., 2003). In addition, the power-law relationship between

visually evoked membrane potential changes and firing rate (An-

derson et al., 2000; Miller and Troyer, 2002) was significantly

steeper for FS neurons compared with either RSTS or RSC

neurons (Figure S3). This predicts that FS neurons will exhibit

greater nonlinear increases in firing rate for the same net depola-

rizing synaptic input than either RSC or RSTS pyramidal neurons.

Simple and complex cells were represented with similar

frequency across all three cell types (Table S3). We also

Figure 3. Fast-Spiking Interneurons and Thin-Spike Regular-Spiking Neurons Become More Active and Less Sparse during CRF + nCRF

Stimulation

(A) Intracellular responses of an electrophysiologically identified FS interneuron (inset, shows sustained firing rate >300 Hz in response to current pulse) during ten

trials of CRF stimulation (black).

(B) CRF + nCRF stimulation (red) elicits larger responses, compared with the CRF configuration (closed arrows).

(C) PSTHs from 15 repeated trials of CRF (black) and CRF + nCRF presentations (red) reveal elevated PSTH peaks (closed arrows), and the appearance of new

peaks (open arrow) during wide-field stimulation. FS interneuron population (n = 5 intracellular, n = 4 extracellular) significantly decreased response sparseness

(12%) with CRF + nCRF stimulation (SCRF = 0.48 ± 0.007; SCRF + nCRF = 0.43 ± 0.007; p < 0.01). Values are mean ± SEM.

(D) Intracellular response of an RSTS neuron (inset, adapting firing pattern to current pulse, rate�100 Hz, spike width at half height 0.25 ms) during five trials of CRF

stimulation (black).

(E) Response of same neuron to five trials of CRF + nCRF stimulation (red). Note increased action potential response (closed arrows) and addition of new

responses (open arrow).

(F) PSTH across 15 trials of CRF stimulation (black) and CRF + nCRF stimulation (red) reveals elevated PSTH peaks (closed arrow), along with addition of peaks

(open arrows) during wide-field stimulation. Inset, RSTS neuron population (n = 12 intracellular, 3 juxtacellular) significantly decreased sparseness (7% average

decrease; SCRF = 0.66 ± 0.006; SCRF + nCRF = 0.62 ± 0.005; p < 0.01) during CRF + nCRF stimulation. See Figure S2 for RSTS neurons, and Table S3 for biophysical

and functional response properties of cell classes. Values are mean ± SEM.

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Selective and Reliable Spiking in Visual Cortex

observed that the size of the CRF was significantly larger and the

response latency significantly shorter in FS and RSTS neurons

than in RSC neurons (Table S3). Together, these results demon-

strate that a neuron’s unique biophysical properties (i.e.,

neuronal subtype) along with its spatial and temporal integrative

properties are predictive of the response to wide-field visual

stimulation.

CRF + nCRF Stimulation of RSC Neurons IncreasesTrial-to-Trial Reliability of Evoked Synaptic and ActionPotential ResponsesThroughout our experiments, we repeatedly observed that trial-to-

trial response reliability of both subthreshold membrane potential

fluctuations and spike times increased during CRF + nCRF stimu-

lation (i.e., decreased variability across repeated trials; Figures 4A

and 4B; see alsoFigures 1A and 1B).Toquantifysubthreshold trial-

to-trial response reliability, we performed a pair-wise cross corre-

lation analysis of membrane potential (Vm) responses recorded on

each trial versus every other trial, within each RSC neuron, sepa-

rated by experimental condition (following digital spike removal,

see Supplemental Experimental Procedures). In RSC neurons we

observed an 81.4 ± 12.2% increase in mean membrane potential

reliability and a 298.1 ± 45.7% increase in spike train reliability

across trials during wide-field stimulation (Figure 4C). A similar

pattern of increased sparseness simultaneous with increased

trial-to-trial reliability was observed in our MU recordings (2-fold

reliability increase; n = 16 recordings; Figure S4).

Changes in Spiking Activity Reflect Changesin the Amplitude and Reliability of EPSPs and IPSPsEvoked by Wide-Field StimulationWe next examined whether the increase in membrane potential

reliability with wide-field stimulation resulted in increased reli-

ability of EPSPs, IPSPs, or both (see Figure 2). As expected,

Neuron 65, 107–121, January 14, 2010 ª2010 Elsevier Inc. 111

Figure 4. Correlated Activity in Subthreshold and

Spiking Responses in Distinct Excitatory Networks

Drives Increased Reliability of Visual Responses

during Wide-Field CRF + nCRF Stimulation

(A) Response of an RSC neuron to five natural movie

presentations to the CRF (current pulse response, inset).

Note the trial-to-trial variability of membrane potential

(Vm) response.

(B) Same neuron, responses to five trials of CRF + nCRF

movie. Across all 20 trials, there was a 21% increase in

the reliability of Vm across trials (inset; RVm = 0.68) and a

163% increase in reliability of spike responses (RSpikes =

0.29) compared with CRF stimulation (inset in 4A;

RVm = 0.56; RSpikes = 0.11; p < 0.01 for both comparisons).

Sparseness across all trials also significantly increased

(p < 0.01).

(C) Trial-to-trial membrane potential response reliability

of RSC neuron population (n = 13) significantly increases

with CRF + nCRF stimulation (Vm RCRF = 0.26 ± 0.01; Vm

RCRF + nCRF = 0.31 ± 0.01; p < 0.01) in parallel with

increased reliability of spike responses in these same

neurons (spikes RCRF = 0.12 ± 0.01; spikes RCRF + nCRF =

0.18 ± 0.01; p < 0.01). Values are mean ± SEM. See also

Figure S4 for similar results in MU recordings.

(D) Isolated EPSPs significantly increase reliability (by

70%) with CRF + nCRF stimulation (EPSP RCRF = 0.16 ±

0.01; EPSP RCRF + nCRF = 0.27 ± 0.02; p < 0.01), while

IPSP reliability does not significantly change (IPSP RCRF =

0.14 ± 0.01; IPSP RCRF + nCRF = 0.13 ± 0.01; p > 0.1).

(E) Normalized firing rates of both FS and RSTS neurons

increase significantly with CRF + nCRF stimulation

(22.8 ± 6.3% and 26.8 ± 12.5%, respectively; p < 0.01,

sign test), while normalized firing rates of RSC neurons

decrease significantly with CRF + nCRF stimulation

(–21.2 ± 13.4%; p < 0.01, sign test). Firing rates normalized

to CRF alone average firing rates for each neuron (FS:

7.6 ± 1.8 Hz; RSTS: 2.8 ± 0.7 Hz; RSC: 1.8 ± 1.2 Hz).

(F) RSTS neurons significantly decrease their spike-train

reliability (black and red, left) with CRF + nCRF stimulation,

(RCRF = 0.37 ± 0.02; RCRF + nCRF = 0.30 ± 0.02; p < 0.01)

while FS neurons maintain high spike-train reliability

(black and blue, right) with CRF + nCRF stimulation,

(RCRF = 0.29 ± 0.02; RCRF + nCRF = 0.28 ± 0.02; p > 0.1).

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Selective and Reliable Spiking in Visual Cortex

trial-to-trial reliability of both EPSPs and IPSPs was significantly

greater than expected from temporally shuffled data (data

not shown), but surprisingly, the peak IPSP reliability was unal-

tered between the two stimulus conditions (Figure 4D, black

and blue bars). However, for these same neurons, trial-to-trial

EPSP reliability significantly increased (by nearly 70%) during

CRF + nCRF stimulation (Figure 4D, black and red bars).

We wondered whether the unique properties of the different

neuronal subtypes discussed above (Table S3) could underlie

the increase in hyperpolarization (Figure 1F) and IPSP ampli-

tudes (Figure 2C) without an accompanying change in IPSP reli-

ability (Figure 4D). We re-examined the activity levels in each cell

type, and found the average firing rates of both FS and RSTS

neurons increased significantly during CRF + nCRF stimulation

(FS: 22.8 ± 6.3%; RSTS: 26.8 ± 12.5%; normalized by average

rate during CRF stimulation; Figure 4E, red). While not signifi-

cantly different from each other, these increases were signifi-

cantly greater than the change in normalized firing rate for RSC

neurons, which decreased significantly (�21.2 ± 13.4%) during

CRF + nCRF stimulation (Figure 4E, black).

112 Neuron 65, 107–121, January 14, 2010 ª2010 Elsevier Inc.

Interestingly, like IPSP reliability in RSC neurons, the high reli-

ability of FS interneuron spike trains was not altered by CRF +

nCRF stimulation (Figure 4F; black and blue). In addition, the

spike train reliability of RSTS neurons decreased significantly

during CRF + nCRF stimulation (Figure 4F; red and blue).

Note, however, that although RSTS neurons showed a relative

decrease in trial-to-trial reliability during CRF + nCRF stimula-

tion, RSTS neurons were consistently more reliable than RSC

neurons under similar stimulation conditions (cf. Figure 4C).

Increased Temporal Precision of RSC Spiking IsAssociated with Sharper Synaptic ResponsesThe results presented thus far suggest that increased EPSP reli-

ability in RSC neurons may be due to increased spiking reliability

in other RSC pyramidal neurons within the cortical network.

However, it is also possible that increased reliability arises

from increased temporal precision of spikes across the popula-

tion of RSC neurons. In many neurons, peaks in the PSTH

became sharper in the CRF + nCRF condition compared with

the CRF condition (e.g., Figures 1D, 4A, and 4B), suggesting

Figure 5. Temporal Precision of Spike Responses in RSC Neurons

Increases with CRF + nCRF Stimulation and Is Associated with Nar-

rowing of the Underlying Synaptic Events

(A) Width of the autocovariance function of a representative RSC neuron’s

PSTH is significantly (35%) narrower with combined CRF + nCRF stimulation

(red) compared with CRF alone stimulation (black). Across the population of

RSC neurons (n = 13), there was a significant narrowing (by 33%) of the average

event in the PSTH with combined CRF + nCRF stimulation (181.6 ± 15.6 ms,

red bar) compared with CRF alone stimulation (272.4 ± 23.9 ms, black bar;

p < 0.01). See also Figure S5 for interspike interval histograms. Values are

mean ± SEM.

(B) Spike-triggered average of Vm in these same neurons reveals a narrower

synaptic potential underlying spikes, and more rapid prespike trajectory

(from –179 ms to threshold) with CRF + nCRF stimulation compared with

CRF alone stimulation (dV/dt CRF = 0.062 ± 0.002 mV/ms; dV/dt CRF + nCRF =

0.073 ± 0.002 mV/ms; p < 0.01). Traces aligned at spike threshold voltage

before averaging (0 on ordinate). Inset shows that spike threshold is also

significantly lower with wide-field stimulation (Threshold CRF + nCRF =

�55.1 ± 0.2 mV; Threshold CRF = –54.2 ± 0.2 mV; p < 0.01). All data for

n = 13 RSC neurons (mean ± SEM).

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Selective and Reliable Spiking in Visual Cortex

an increase in temporal precision. To quantify this observation

we computed the change in width of the central peak of the

PSTH’s autocovariance function between the two stimulation

conditions (e.g., Desbordes et al., 2008). Because the typical

RSC PSTH exhibited a few peaks interrupted by periods of

relative silence (e.g., Figures 4A, 4B, and S2), this method

adequately captures the temporal extent of the average PSTH

event, which is the summed spike activity elicited by a few select

movie frames across trials.

The average half-width of the central peak of the PSTH auto-

covariance function (see Supplemental Experimental Proce-

dures) significantly decreased during CRF + nCRF stimulation

(87.5 ms; 35%) in a representative RSC neuron (Figure 5A, inset)

and by 33% in the RSC population (Figure 5A; n = 13). The

increase in PSTH precision was also associated with a reduced

mean and modal interspike interval, corresponding to an

increase in instantaneous firing rates for select portions of RSC

spike trains strongly driven by specific movie frames (Figure S5;

see also Figure S2).

Is increased spike time precision across trials accompanied

by a decrease in the width of the synaptic barrages triggering

spikes? We calculated the spike-triggered average (STA) of Vm

across the population of RSC neurons (n = 13) in response to

CRF and CRF + nCRF stimulation. Membrane potential STAs

were systematically sharper in the CRF + nCRF condition (Fig-

ure 5B; red versus black), and accompanied by an increase in

the average rate of change of Vm (dV/dt) for the rising phase of

Vm trajectory to spike threshold (Figure 5B). This change does

not appear to result from a hyperpolarization-induced increase

in driving force on EPSPs, because DC-induced hyperpolariza-

tion of RSC neurons during CRF alone presentation did not result

in the same degree of STA sharpening seen during CRF + nCRF

stimulation (n = 10 RSC neurons; data not shown).

Consistent with the finding of a more hyperpolarized mem-

brane potential prior to spike initiation and a faster prespike

dV/dt, actual spike thresholds (defined as the voltage at the

peak of the second derivative of Vm) were significantly lower

across the population of RSC neurons during CRF + nCRF stim-

ulation compared with CRF-alone stimulation (Figure 5B; see

also Azouz and Gray, 2003).

Interaction of Synaptic Excitation and Inhibition LargelyExplains Changes in Spike Responses duringCRF + nCRF StimulationOur experimental results demonstrate that in RSC neurons IPSPs

become stronger without changes in reliability during CRF +

nCRF stimulation, while conversely, EPSPs become more reli-

able with no change in average amplitude. How do these two

factors contribute to changes in spike train sparseness and

reliability?

Experimental isolation of EPSPs and IPSPs necessitates phar-

macological blockade of intrinsic conductances, making it

impossible to simultaneously record EPSPs, IPSPs, and spikes,

thereby preventing us from directly addressing this question (but

see Pospischil et al., 2007). Instead we turned to a simple leaky

integrate and fire (LIF) single-neuron model where we could

explore the relative contributions of recorded EPSPs and IPSPs

on the sparseness and reliability of spiking activity. Excitatory

and inhibitory conductances (Ge and Gi) were derived from our

recordings of isolated EPSPs and IPSPs, respectively, and

then simultaneously injected into the model LIF neuron at rest

(�65 mV; e.g., Figure 6C; see Supplemental Experimental

Procedures).

Neuron 65, 107–121, January 14, 2010 ª2010 Elsevier Inc. 113

Figure 6. Changes in Excitatory and Inhibitory Synaptic Barrages Drive Increased Sparseness and Reliability with Wide-Field Stimulation in

a Leaky Integrate and Fire Model Neuron

(A) Correction for input resistance (Rin) and capacitance (Cm) of the recorded neuron allows inference of synaptic currents (IPSC or EPSC) that underlie an indi-

vidual IPSP (left) or EPSP (right) amplitude-time series recorded in real neurons during CRF presentation. All traces in this figure were derived from data obtained

from the neuron illustrated in Figures 1 and 2.

(B) Injection of these IPSC or EPSC traces into a leaky integrate and fire (LIF) model with experimentally measured Rin and Cm reproduces the original recorded

IPSP (left) and EPSP (right) trace. Reconstructed example EPSP and IPSP amplitude-time series for CRF + nCRF stimulation shown in blue and red (lower traces).

(C) Excitatory and inhibitory conductances (Ge and Gi) derived from the reconstructed currents during CRF stimulation are injected into the LIF model cell at rest

(�65 mV).

(D) Matrix of Ge and Gi combinations that can be examined in the LIF model. Injection of Ge and Gi from the same conditions (e.g., within CRF or CRF + nCRF

stimulation) represents the control conditions (Da and Db). Mixing Ge and Gi obtained from different conditions represents our experimental manipulation

(Dc and Dd).

(Ea) LIF raster and PSTH in response to 60 simulated (E + I)CRF trials. Sparseness, S = 0.32 ± 0.002, spike-train reliability, RCRF = 0.33 ± 0.02. (Eb) LIF raster and

PSTH in response to 60 simulated (E + I)CRF + nCRF trials. Sparseness and spike-train reliability increase significantly (S = 0.70 ± 0.002, spike train RCRF + nCRF = 0.41

± 0.02; p < 0.01 for both comparisons to CRF simulations). Note nonlinear change in shape of PSTH: some peaks are enhanced (solid arrowheads) while others

are suppressed (open arrowhead). Correlation coefficient (r) of PSTH (E + I)CRF to PSTH (E + I)CRF + nCRF = 0.46 ± 0.02. (Ec) LIF raster and PSTH in response to 60

simulated (ECRF + ICRF + nCRF) trials. Sparseness increase significantly (S = 0.68 ± 0.002; p < 0.01) compared with (E + I)CRF. Spike-train reliability decreased signif-

icantly in comparison to (E + I)CRF simulations. (ECRF + ICRF + nCRF) R = 0.33 ± 0.02; p < 0.01. Correlation coefficient (r) of PSTH (ECRF + ICRF + nCRF) to PSTH

(E + I)CRF + nCRF = 0.47 ± 0.02. (Ed) LIF raster and PSTH in response to 60 simulated (ECRF + nCRF + ICRF) trials. Sparseness increased (S = 0.53 ± 0.002; p <

0.01), although significantly less than in (ECRF + ICRF + nCRF) simulation. However, spike-train reliability increased significantly in comparison to (ECRF + ICRF +

nCRF) simulation (p < 0.01), and was not significantly different from (E + I)CRF simulations, (ECRF + nCRF + ICRF) R = 0.40 ± 0.02; p > 0.1. Correlation coefficient

of PSTH (ECRF + nCRF + ICRF) to PSTH (E + I)CRF + nCRF = 0.97 ± 0.02, a significant (106%, p < 0.01) increase compared with (ECRF + nCRF + ICRF) simulations.

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Selective and Reliable Spiking in Visual Cortex

How well does combined Ge and Gi injection into the LIF model

replicate a real neuron’s spiking response? We examined this by

utilizing spiking responses recorded from an RSC neuron prior to

onset of action potential inactivation (Figure 1). Ge and Gi

conductance traces were derived for this same neuron based

on responses to the same movie, but after blockade of intrinsic

conductances, as described above (Figure 2). Ge and Gi were

derived by compensating for the resistive-capacitive properties

114 Neuron 65, 107–121, January 14, 2010 ª2010 Elsevier Inc.

of the recorded neuron at the actual holding potentials used to

record EPSPs and IPSPs (Figure 6A; see Nowak et al., 1997).

The full amplitude-time series of the underlying conductance

(Ge or Gi) was then calculated from the amplitudes of the recon-

structed synaptic currents and the instantaneous membrane

potential driving force. Each derived Ge and Gi time series was

then injected into an LIF model neuron matched in input resis-

tance and membrane time constant to the recorded neuron.

Neuron

Selective and Reliable Spiking in Visual Cortex

The model neuron’s membrane potential accurately replicated

the original IPSP and EPSP barrages, when injected at the same

holding potentials (cf. Figures 6A and 6B, top traces), confirming

the model’s basic validity. The same procedure was applied to

all single trial EPSP and IPSP responses in the CRF and CRF +

nCRF conditions, and used to construct a database of Ge and

Gi traces for CRF and CRF + nCRF stimulation. Individual Ge

and Gi conductance traces were drawn at random from the

database (within a given stimulus condition), and injected simulta-

neously into the model neuron at rest to generate simulated single

trial intracellular membrane potential and spike responses

(Figure 6C). This procedure was repeated for 60 unique combina-

tions of Ge and Gi sequences in each stimulus configuration.

As seen in Figure 6Ea, random combinations of Ge and Gi

sequences recorded during CRF-alone stimulation produce

simulated spike responses that are highly correlated with the

actual recorded spike response for the same neuron during

CRF stimulation (cf. Figure 1C; Model PSTH versus Actual

PSTH rCRF = 0.54 ± 0.006). The model neuron, like the real

neuron, showed a nonlinear change in the PSTH in response to

(E + I)CRF + nCRF injection (Figure 6Eb, arrows) and a dramatic

increase in response sparseness (compare Figures 6Ea and

6Eb and Figures 1C and 1D). Response sparseness of the model

neuron increased significantly during ‘‘wide-field’’ stimulation;

similarly, the trial-to-trial reliability of the spike trains increased

significantly in the (E + I)CRF + nCRF simulation. These computa-

tional results strongly suggest that increased spike train sparse-

ness and reliability (at rest) are largely accounted for by simply

combining the underlying excitatory and inhibitory conduc-

tances evoked by CRF + nCRF stimulation.

Simulations Support the Hypothesis that NetworkInhibition Drives Changes in Sparseness whileRecurrent Excitation Drives Changes in ReliabilityThe model was then used to examine the relative contributions of

excitation and inhibition upon sparseness and reliability during

CRF + nCRF stimulation. This was done by artificially pairing

Ge traces derived from CRF recordings with Gi traces derived

from CRF + nCRF recordings (Figure 6Dc; ECRF + ICRF + nCRF),

and vice versa. As evident in the PSTH, adding ICRF + nCRF trials

to ECRF trials significantly increased sparseness compared with

pairing of ICRF with ECRF trials, but did not significantly alter

spike-train reliability (Figure 6Ec).

However, when we paired Ge derived from CRF + nCRF

presentation with Gi derived from CRF recordings, we observed

a dramatic increase in the similarity of the PSTH to that con-

structed from the (E + I)CRF + nCRF trials, along with a significant

increase in the trial-to-trial reliability of the spiking responses

that was no different than the reliability of the spike trains in

the full (E + I)CRF + nCRF simulation. Conversely, the increase in

sparseness was significantly smaller than that observed in the

ECRF + ICRF + nCRF simulation. The results from this neuron

suggest that changes in Gi have a predominant effect on sparse-

ness, while changes in Ge have a predominant effect on spike

reliability and the similarity of PSTH structure to that occurring

normally under wide-field stimulation conditions.

We repeated these Ge and Gi LIF simulations for all of the

neurons from which we recorded EPSPs and IPSPs (n = 9;

same as in Figure 2C), and the simulation results strongly paral-

leled many of our experimental observations. First, in every case

individually, and across the population, coinjection of Ge and Gi

derived from CRF + nCRF stimulation produced significantly

sparser (34%) and more reliable (27%) spike trains in compar-

ison to injection of Ge and Gi derived from CRF stimulation alone

(Figures 7A and 7B).

Second, spikes occurring in the CRF + nCRF simulations were

accompanied by significant narrowing of the width of the

average synaptic conductance preceding each spike. Further-

more, jittering the exact timing of the excitatory-inhibitory rela-

tionship by as little as 20 to 50 ms significantly decreased

spike-train reliability and sparseness, respectively (Figure S6).

Most importantly, by artificially recombining the influences of

CRF versus CRF + nCRF induced excitation and inhibition, we

found that changes in Gi during CRF + nCRF stimulation had

a predominant effect on increasing sparseness (Figure 7A), while

changes in Ge during CRF + nCRF stimulation had a predominant

effect on increasing spike-train reliability (Figure 7B). Moreover,

changes in Ge largely dictated the shape of the overall PSTHs

compared with those obtained with (E + I)CRF + nCRF stimulation

(Figure 7C). These results indicate that the synchronous interac-

tion of Ge and Gi induced by combined CRF + nCRF stimulation

largely replicates the effects observed in our recordings, with

enhanced inhibition contributing to increased sparseness, which

in turn facilitates more reliable and precise recurrent cortical

excitation that determines the overall spiking response.

DISCUSSION

We have demonstrated here that wide-field naturalistic visual

stimulation—simultaneously engaging the CRF + nCRF—not

only increases response sparseness in cat primary visual cor-

tex, but also significantly increases trial-to-trial reliability and

temporal precision. These effects arise as a consequence of

complex interactions between excitatory and inhibitory mecha-

nisms mediated by distinct neuronal subtypes. Wide-field visual

stimulation simultaneously increased activity of FS inhibitory

interneurons and increased IPSP amplitudes in RSC pyramidal

neurons. At the same time, in the same population of RSC

neurons, wide-field stimulation produced an increase in the

trial-to-trial reliability of both action potentials and underlying

EPSPs. Interestingly, the injection of excitatory and inhibitory

conductances (derived from actual recordings of RSC neuron

responses) into a simple model replicated these findings. This

suggests that changes in visually evoked synaptic potentials

during wide-field stimulation were largely responsible for the

observed increases in action potential sparseness and reliability

in RSC neurons. The simulations also revealed that increased

amplitudes of visually evoked IPSPs predominantly drove

increased neuronal sparseness, while increased EPSP reliability

predominantly drove increased action potential reliability.

Functional Interactions between Inhibitoryand Excitatory Networks Determines ResponseSparseness and ReliabilityCortical neuronal responses are determined in large part by the

precise amplitude-time course of barrages of excitatory and

Neuron 65, 107–121, January 14, 2010 ª2010 Elsevier Inc. 115

Figure 7. LIF Simulations Indicate that Network-Generated Inhibi-

tion Drives Increased Sparseness, while Network-Generated Excita-

tion Drives Increased Response Reliability

(A) LIF simulations derived from population of real neurons (n = 9; see

Figure 2) indicate that spike-train sparseness was significantly lower in the

(E + I)CRF + nCRF simulations compared with the three other simulation

conditions (S = 0.47 ± 0.04; colored asterisks indicate significant group

differences corrected for multiple comparisons). Response sparseness in

the ECRF + ICRF + nCRF simulations (blue; S = 0.65 ± 0.04) was not significantly

different than the (E + I)CRF + nCRF simulation (violet; S = 0.65 ± 0.03; p > 0.1),

but both of these groups displayed significantly larger response sparseness

than the ECRF + nCRF + ICRF simulations (red; S = 0.58 ± 0.03; p < 0.01

for both group comparisons). Colored asterisks indicate significant group

differences. Values are mean ± SEM.

(B) Conversely, trial-to-trial spike-train reliability is highest for the (E + I)CRF + nCRF

simulations (violet; R = 0.2 ± 0.007), and these spike trains were not significantly

more reliable than those in the ECRF + nCRF + ICRF simulations (red; R = 0.19 ±

0.007; p > 0.1). However, spike responses of both of these groups were signif-

icantly more reliable than the spike trains of the ECRF + ICRF + nCRF simulations

(blue; R = 0.17 ± 0.006; p < 0.01 for both group comparisons).

(C) Summary of LIF simulations shows that overall spiking pattern (PSTH) of

ECRF + nCRF + ICRF simulations is the most similar to (E + I)CRF + nCRF PSTH

(red; r = 0.74 ± 0.007), although the ECRF + ICRF + nCRF PSTH was significantly

more similar to the (E + I)CRF + nCRF PSTH (blue; r = 0.46 ± 0.008), as compared

with the similarity of the (E + I)CRF PSTH to the (E + I)CRF + nCRF PSTH (black;

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Selective and Reliable Spiking in Visual Cortex

116 Neuron 65, 107–121, January 14, 2010 ª2010 Elsevier Inc.

inhibitory synaptic potentials (Haider and McCormick, 2009;

Pouille and Scanziani, 2001; Tiesinga et al., 2008) interacting

with the intrinsic membrane properties of the neuron. Our

LIF simulations (necessarily absent of intrinsic conductances)

utilizing naturally occurring synaptic responses were able to

reproduce changes in sparseness and reliability as observed in

real RSC neurons. This suggests that the wide-field induced

changes in EPSPs and IPSPs, coupled with the nonlinear

dynamics of spike generation, are nearly sufficient to explain

increased spike-train sparseness and reliability during natural-

istic sensory stimulation.

At the level of synaptic potentials, one of the key mechanisms

contributing to increased sparseness of RSC pyramidal neurons

appears to be activation of cortical inhibitory networks, resulting

in an increase in the amplitude, and modulation of the timing, of

IPSP barrages. One component of enhanced inhibition that

may contribute to increased sparseness in RSC neurons is an

‘‘iceberg’’ effect (see Carandini, 2007 and references therein),

in which responses to weak synaptic inputs become sub-

threshold, while the strong inputs (which may be less numerous

than the weak ones) remain suprathreshold, resulting in an

increase in overall response sparseness. Although tonic hyper-

polarization via current injection does increase sparseness, this

increase is smaller (per mV of hyperpolarization) than that asso-

ciated with natural IPSP barrages generated during wide-field

stimulation. These results suggests that the precise timing of

wide-field activated IPSP barrages relative to the EPSPs evoked

by the same stimuli is an important factor in determining the

overall structure of synaptic potentials that shape neuronal

selectivity.

Supporting this hypothesis is the observation that the spike

triggered average membrane potential in RSC cells is sharper

and rises more rapidly during wide-field stimulation (Figure 5B).

Accordingly, our simulations demonstrate that the initiation of

action potentials in the wide-field condition is, on average, asso-

ciated with a more rapid increase in synaptic excitation with

a simultaneous decrease in inhibition (Figure S6; Hasenstaub

et al., 2005). Disrupting this temporal relationship between

wide-field elicited EPSP and IPSP barrages by tens of millisec-

onds significantly decreases sparseness and reliability in simula-

tions of CRF + nCRF spiking (Figure S6). These effects reflect the

importance of the average temporal relationship of excitation

and inhibition across trials; the timing and covariance of excita-

tion with inhibition is likely even more precise within a single trial

(Okun and Lampl, 2008).

Our simulations revealed that the changes in IPSPs elicited by

wide-field stimulation have a larger effect on sparseness than the

changes occurring in EPSPs (Figure 7). Conversely, changes in

EPSPs occurring with wide-field stimulation had a significantly

stronger effect on spike train reliability than the IPSPs. We

propose a simple scenario that may underlie the generation of

sparse yet reliable sensory responses during wide-field stimula-

tion (Figure 8). The increased activation of inhibitory neurons

results in an overall decrease in action potential responses to

r = 0.26 ± 0.007; p < 0.01 for all group comparisons). See also Figure S6 for

effects of manipulating timing of Gi relative to Ge.

Figure 8. Schematic Diagram of Proposed

Excitatory-Inhibitory Interactions during

Wide-Field Visual Stimulation

(A) Local cortical networks composed of excit-

atory (white) and inhibitory (black) neurons form

interconnections with each other, with the great

majority of connectivity occurring among excit-

atory neurons. During CRF stimulation, both excit-

atory and inhibitory cell types are driven, with RSC

neurons and FS neurons generating elevated and

temporally varying responses (traces).

(B) Upon simultaneous engagement of the CRF

and nCRF, inhibitory interneurons become

strongly activated by increased excitatory drive

arising from a larger spatial distribution of inputs.

The increased depolarization and enhanced

synaptic fluctuations in interneurons are nonli-

nearly transformed into greater numbers of spikes

compared with excitatory neurons (inset at

center). This causes RSC neurons to receive

enhanced inhibitory synaptic barrages at specific

time points, which leads to increased sparseness and precision of visually evoked spike responses in RSC neurons. These sparser but less variable spikes

are amplified through the recurrent excitatory connections among RSC neurons in the local network (red synapse), which leads to more reliable and precise

sensory encoding across the ensemble of pyramidal neurons (red trace).

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Selective and Reliable Spiking in Visual Cortex

weak excitatory synaptic inputs to RSC cells. This results in an

increase in neuronal sparseness in individual RSC neurons.

Increased reliability emerges because action potentials that do

occur in RSC neurons happen preferentially during the peaks of

sharply depolarizing synaptic potentials, which are restricted to

narrower windows of time, resulting in less temporal jitter and

greater reliability in the generation of spikes (Rodriguez-Molina

et al., 2007). This increased spiking reliability and precision in

RSC neurons is communicated as reliable and sharper EPSPs

to postsynaptic neurons, many of which then further increase

spike reliability (and decrease temporal jitter) through a similar

mechanism. Reverberation or passing through multiple stages

of the recurrent cortical network could then result in strong

temporal sharpening of neural responses and increase the reli-

ability and selectivity of spiking across the population (Litvak

et al., 2003; Wang et al., 2006).

Mechanisms Underlying Increased Activity in InhibitoryCircuits during Wide-Field StimulationThe data presented here strongly support the idea that increased

IPSP amplitudes are a critical factor underlying increased

sparseness. Three changes that can increase the size of IPSP

barrages are: (1) An increase in the number, or intensity, of dis-

charging excitatory neurons presynaptic to the inhibitory

neurons; (2) an increase in the synchrony of activity within the

network of presynaptic excitatory neurons; and (3) a direct

increase in the activity level of the GABAergic inhibitory neurons

due to nonlinear response properties.

We recorded from two commonly encountered subtypes of

excitatory pyramidal cells: classical regular spiking (RSC) and

thin-spike regular spiking (RSTS) neurons (Nowak et al., 2003).

RSC pyramidal neurons, thought to be the most common cortical

subtype, decreased their average spike responses to wide-field

visual stimulation. By itself, this finding would suggest a reduced

excitatory drive of both pyramidal neurons and local GABAergic

neurons.

However, several key observations are at odds with this

inference. First, even though the overall firing rate of RSC

neurons decreased during wide-field stimulation, the response

to a subset of stimulus frames was often accompanied by

increased peak firing rates (e.g., Figures S1, S5) and was

more precise (Figure 5) and repeatable (Figure 4). This con-

certed increase in temporal precision and population reliability

could well facilitate intracortical synchrony, an especially effec-

tive driver of FS and non-FS GABAergic neurons (Jonas et al.,

2004; Kapfer et al., 2007). Second, RSTS pyramidal neurons

exhibited significantly increased mean and peak firing rates

during wide-field stimulation, perhaps contributing preferentially

to enhanced FS neuronal activity. Third, CRF + nCRF stimula-

tion necessarily activates a larger cortical area and therefore

increases the total number of active excitatory neurons in the

local cortical network. Many of these cells may be presynaptic

to local GABAergic neurons, or activate neurons that are so

(e.g., RSTS pyramidal cells). Although we could only record

from one subtype (FS) of cortical interneuron, we did find that

their receptive fields were larger than those of RSC neurons,

suggesting that at least some GABAergic neurons may prefer-

entially receive excitatory inputs from wider regions of sensory

space (Bruno and Simons, 2002; Liu et al., 2009; Wu et al.,

2008). These findings along with anatomical observations

suggest that the IPSPs we recorded from RSC neurons during

wide-field stimulation likely resulted from the activation of

local (i.e., within 2.5 mm of the recorded neuron) inhibitory inter-

neurons (Kisvarday and Eysel, 1993), which are themselves

driven by a diverse set of local and long-range excitatory con-

nections (Gilbert et al., 1996; Martin and Whitteridge, 1984;

McGuire et al., 1991) originating from both the CRF and nCRF

(Figure 8).

Perhaps the most important factor contributing to increased

inhibitory neuron activity is the relationship between membrane

potential and firing rate. In the presence of noisy synaptic

activity, this function takes the form of a power law: f = (V)x (Miller

Neuron 65, 107–121, January 14, 2010 ª2010 Elsevier Inc. 117

Neuron

Selective and Reliable Spiking in Visual Cortex

and Troyer, 2002). We found that FS interneurons exhibit a partic-

ularly steep power law relationship, with a relatively large expo-

nent compared with RSC neurons (Figure S3). As a result, FS

cells are likely to be more sensitive to and strongly activated

by the overall synaptic fluctuations provided by joint stimulation

of the CRF and nCRF (Figure 8).

One should keep in mind that although we only recorded from

FS interneurons, the effects of inhibition on RSC neurons arise

from a broad range of inhibitory neuron subtypes. Indeed, other

subtypes of interneurons also generate highly nonlinear

response enhancement to costimulation of multiple excitatory

pathways (e.g., Martinotti cells; Kapfer et al., 2007; Silberberg

and Markram, 2007). Clarification of the specific contributions

of the many inhibitory neuron subtypes to response selectivity

and reliability requires further investigation.

Implications of Increased Sparseness, Reliability,and PrecisionOne of the main observations of our study was that classical

regular spiking pyramidal neurons (RSC) simultaneously increase

their visual selectivity and reliability, while decreasing overall

firing rate, in response to wide-field visual stimulation. Similarly,

presentation of full field natural scenes in a temporal sequence

that replicates natural eye movements also generated synaptic

and action potential responses that are both reliable and sparse

in cat V1 (Yves Fregnac, Pierre Baudot, Manuel Levy, and Olivier

Marre, 2005, Cosyne meeting, abstract). This finding suggests

that, during natural vision, RSC neurons are more energetically

efficient (Niven and Laughlin, 2008), more selective (Figure 1D)

and reliable (Figure 4C), and consequently more informative per

spike (Vinje and Gallant, 2002). Our observations provide strong

support for the efficient sparse coding hypothesis (Barlow,

1972; Olshausen and Field, 2004; Vinje and Gallant, 2000, 2002).

The moment-to-moment demands of natural behavior depend

upon the reliability of neuronal responsiveness, and insights into

mechanisms that limit response variability are critical toward

understanding the nature of cortical computation. Indeed,

repeated presentations of identical stimuli can elicit highly vari-

able spike responses (Heggelund and Albus, 1978; Shadlen

and Newsome, 1998; Tiesinga et al., 2008). Although some

studies have shown that response reliability can be quite high

after controlling for factors such as eye movements or recording

mainly from input layers (Gur et al., 1997; Kara et al., 2000), in

general, the variability of cortical responses scales approxi-

mately with the mean (but see DeWeese and Zador, 2006;

Maimon and Assad, 2009). These conclusions are based on

recordings likely to be dominated by RSC neurons, because

they are by far the most commonly recorded cells in visual cortex

(but see Chen et al., 2008; Mitchell et al., 2007).

To our knowledge, the data presented here provide the first

mechanistic link between sparse sensory coding and increased

response reliability in visual cortex under naturalistic stimulus

conditions. These findings complement recent findings of sparse

cortical responses in several other species and sensory systems,

under a variety of experimental conditions (Greenberg et al.,

2008; Houweling and Brecht, 2008; Hromadka et al., 2008;

Waters and Helmchen, 2006). Although recent in vitro studies

have shown that response correlation necessarily increases as

118 Neuron 65, 107–121, January 14, 2010 ª2010 Elsevier Inc.

firing rates increase (de la Rocha et al., 2007), we show here

that sparse sensory responses, which exhibit increased effi-

ciency (i.e., fewer total action potentials), can be accompanied

by increased response reliability across trials. These findings

have broad implications for the nature of visual encoding, since

they demonstrate that increased sparseness (reflective of

increased stimulus selectivity) is also associated with higher

trial-to-trial response reliability to a more restricted set of stimuli.

Relationship to Previous Studies and Other SensorySystemsWe have identified a basic operational mode of visual cortical

circuits engaged by spatiotemporally rich wide-field stimulation,

as experienced during natural vision (David and Gallant, 2005;

Mazer and Gallant, 2003). Our work suggests that intracortical

inhibitory networks are critical for the generation of selective

and reliable visual responses during wide-field stimulation.

Specifically, we hypothesize that the intrinsic properties and

anatomical connectivity of FS and other types of interneurons,

as well as the RSTS subclass of pyramidal neuron, enable them

to rapidly integrate activity from horizontal connections and

shape the output of RSC pyramidal cells. We speculate that an

additional function of the excitatory-inhibitory network mecha-

nisms described here is to decorrelate neuronal responses

across cell classes (David and Gallant, 2005; Mazer and Gallant,

2003; Vinje and Gallant, 2000; Wang et al., 2003), ultimately

increasing coding bandwidth and efficiency (El Boustani et al.,

2009; Felsen et al., 2005; Olshausen and Field, 1996; Simoncelli,

2003; Vinje and Gallant, 2002), while simultaneously increasing

signal reliability across the population.

Our results are generally consistent with the large body of

extracellular recording literature indicating an overall suppres-

sion of CRF elicited responses with nCRF costimulation (Ange-

lucci and Bressloff, 2006; Bair et al., 2003; Cavanaugh et al.,

2002b; DeAngelis et al., 1994; Durand et al., 2007; Fitzpatrick,

2000; Jones et al., 2001; Webb et al., 2005), and increased

spiking selectivity driven by surround stimulation (Chen et al.,

2005; Okamoto et al., 2009). Our observations are also consis-

tent with studies showing that stimulus context modulates

both perceptual and neuronal sensitivity (Ito and Gilbert, 1999).

However, our results extend these findings by demonstrating

that wide-field visual stimulation with dynamic, spatiotemporally

rich stimuli drives highly specific network interactions among

distinct neuronal subtypes that ultimately lead to increases in

spike precision, spike reliability, and response sparseness in

the output of RSC pyramidal neurons.

Moreover, the results presented here during naturalistic stim-

ulation strongly implicate intracortical inhibitory potentials, at

least partially originating in FS interneurons, as a critical compo-

nent of these effects (cf. Anderson et al., 2001; Ozeki et al.,

2009). Although complex inhibitory modulations are not entirely

unexpected from a spatiotemporally rich and time-varying stim-

ulus, the network interactions described here among distinct

cortical neuronal subtypes that ultimately increase the reliability

and precision of the network response are not easily predicted

from existing studies of surround suppression. It is entirely

possible that the use of a spatiotemporally rich wide-field

(‘‘naturalistic’’) stimulus set puts the cortex in a more ‘‘transient’’

Neuron

Selective and Reliable Spiking in Visual Cortex

response regime that strongly engages inhibitory circuits

(Ozeki et al., 2009). Such dynamics certainly deserve further

investigation.

Finally, it is likely that the excitatory-inhibitory mechanisms

described here in visual cortex generalize across sensory sys-

tems, particularly under naturalistic stimulus conditions. Recent

studies of the rodent somatosensory system show that cortical

responses exhibit nonlinear modulation with multi-whisker stim-

ulation as compared with single whisker stimulation, and elicit

complex activity patterns across extended regions of barrel

cortex (Jacob et al., 2008). Studies of both mammalian auditory

cortex (Hromadka et al., 2008) and the avian song system (The-

unissen et al., 2001) indicate that neural responses are highly

selective for features present in natural sounds. Song generation

itself may be mediated by ‘‘ultra sparse’’ neuronal activity (Hahn-

loser et al., 2002). Although our results demonstrate the intracel-

lular and network mechanisms underlying enhanced selectivity

to ongoing wide-field visual stimulation, the exact interaction of

the spatiotemporal statistics of natural sensory stimulation with

the response properties of distinct neuronal subtypes merits

further investigation.

EXPERIMENTAL PROCEDURES

Animal Preparation and Electrophysiological Recordings

Briefly, young adult female cats were initially anesthetized with ketamine/xyla-

zine and then maintained on isoflurane vaporized in O2 for the duration of the

experiment. Standard surgical procedures for reducing respiratory and

cardiac pulsations were employed, and all experiments conformed to Yale

University IACUC standards. A craniotomy overlying Area 17 was performed,

the dura was dissected, and metal electrodes and/or beveled sharp glass

micropipettes (55–120 MU), filled with 2 M K+ acetate (for recording action

potentials) or filled with 25–50 mM Qx-314 and 2 M Cs+ acetate (to block

most intrinsic conductances; see Haider et al., 2006; Hasenstaub et al.,

2005) were advanced into the cortex. All action potential responses to natural

movies were recorded with zero current injection; EPSPs were recorded

near �80 mV and IPSPs were recorded near 0 mV.

Visual Stimulation

Neurons were characterized with computer assisted hand-mapping, then

quantitatively mapped using a two-dimensional (2D) sparse noise stimulus

(Jones and Palmer, 1987; Mazer et al., 2002) composed of light and dark

bars at each neuron’s preferred orientation on a linearized 19 inch CRT

(Siemens). Screen background was a uniform gray and bars were 100%

contrast. We designated the least-squares 2D circular fit of the half-maximal

spike response contour (or the half-maximal membrane potential response

in the experiments where spikes were inactivated) as the CRF. We then pre-

sented repeated segments of one of seven different long-duration (5–16 s;

without jumps or cuts) movies for 10–20 trials, and determined which frame

of the movie evoked the greatest number of spikes. We then selected this

frame and 1.5 s flanking each side of this frame to present as the 3 s ‘‘optimal’’

movie, as shown in all figures here. A mask of equal color and luminance with

the background occluded all portions of the movie save for a circle of diameter

equal to and centered over the CRF. This mask was enlarged to expose 3X the

CRF, and these stimuli were designated as the CRF + nCRF stimuli. In both

cases, the pixels presented in the CRF were identical over trials. Presentation

of CRF alone and CRF + nCRF stimuli were randomly interleaved. Movies were

digitized from commercial DVDs (Winged Migration, The Incredibles, Aeon

Flux), converted to grayscale and presented at 25–28 Hz.

Analysis

We quantified neural selectivity by computing lifetime response sparseness

(S), S = 1 � a, where a denotes the activity fraction, a = [Si (ri/n)]2/Si (ri2/n),

and ri is the response to the i-th frame of the movie, and n is the total number

of frames in the movie. Lifetime sparseness (S) is a metric of a single neuron’s

selectivity that is closely related to the kurtosis of the firing rate distribution. For

highly selective neurons, with maximal responses occurring primarily during

a single movie frame, the response distribution across all movie frames will

be highly peaked and S will approach 1.0 (Willmore and Tolhurst, 2001). Life-

time sparseness is different from population sparseness, which measures the

activity profile across an ensemble of neurons.

Real-time analysis and visual stimulation utilized custom written software in

Python (PyPE). All arithmetic means reported and plotted ± standard error of

the mean. All analyses, statistics and plots were generated with built-in and

custom functions in MATLAB (Mathworks). Unless explicitly noted, all p values

(a = 0.01) were calculated with the nonparametric Kruskal-Wallis analysis of

variance, with Tukey-Kramer correction in cases of multiple comparisons.

Throughout the main text and results, when statistical significance is

mentioned, p values and tests are presented in the appropriate portions of

the corresponding figure legends or tables, as relevant.

SUPPLEMENTAL INFORMATION

Supplemental Information includes six figures, three tables, one movie, and

Supplemental Experimental Procedures and can be found with this article

online at doi:10.1016/j.neuron.2009.12.005.

ACKNOWLEDGMENTS

The authors thank Flavio Frohlich and Kristy Sundberg for help during exper-

iments, and Carlos Maureira and Lionel Nowak for helpful suggestions. B.H.,

A.D., M.R.K., J.T., J.A.M., and D.A.M. performed experiments; B.H., M.R.K.,

J.T., and J.A.M., analyzed data; B.H., A.D., and M.R.K. performed histology;

Y.Y., B.H., and D.A.M. performed simulations; B.H., J.A.M. and D.A.M. wrote

the manuscript.

Accepted: November 25, 2009

Published: January 13, 2010

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