Orientation tuning of input conductance, excitation, and inhibition in cat primary visual cortex

Invariant computations in local cortical networks with balanced excitation and inhibition

Cortical computations critically involve local neuronal circuits. The computations are often invariant across a cortical area yet are carried out by networks that can vary widely within an area according to its functional architecture. Here we demonstrate a mechanism by which orientation selectivity is computed invariantly in cat primary visual cortex across an orientation preference map that provides a wide diversity of local circuits. Visually evoked excitatory and inhibitory synaptic conductances are balanced exquisitely in cortical neurons and thus keep the spike response sharply tuned at all map locations. This functional balance derives from spatially isotropic local connectivity of both excitatory and inhibitory cells. Modeling results demonstrate that such covariation is a signature of recurrent rather than purely feed-forward processing and that the observed isotropic local circuit is sufficient to generate invariant spike tuning.

Bottom-up and top-down dynamics in visual cortex

A key emergent property of the primary visual cortex (V1) is the orientation selectivity of its neurons. Recent experiments demonstrate remarkable bottom-up and top-down plasticity in orientation networks of the adult cortex. The basis for such dynamics is the mechanism by which orientation tuning is created and maintained, by integration of thalamocortical and intracortical inputs. Intracellular measurements of excitatory and inhibitory synaptic conductances reveal that excitation and inhibition balance each other at all locations in the cortex. This balance is particularly critical at pinwheel centers of the orientation map, where neurons receive intracortical input from a wide diversity of local orientations. The orientation tuning of neurons in adult V1 changes systematically after short-term exposure to one stimulus orientation. Such reversible physiological shifts in tuning parallel the orientation tilt aftereffect observed psychophysically. Neurons at or near pinwheel centers show pronounced changes in orientation preference after adaptation with an oriented stimulus, while neurons in iso-orientation domains show minimal changes. Neurons in V1 of alert, behaving monkeys also exhibit short-term orientation plasticity after very brief adaptation with an oriented stimulus, on the time scale of visual fixation. Adaptation with stimuli that are orthogonal to a neuron's preferred orientation does not alter the preferred orientation but sharpens orientation tuning. Thus, successive fixation on dissimilar image patches, as happens during natural vision, combined with mechanisms of rapid cortical plasticity, actually improves orientation discrimination. Finally, natural vision involves judgements about where to look next, based on an internal model of the visual world. Experiments in behaving monkeys in which information about future stimulus locations can be acquired in one set of trials but not in another demonstrate that V1 neurons signal the acquisition of internal representations. Such Bayesian updating of responses based on statistical learning is fundamental for higher level vision, for deriving inferences about the structure of the visual world, and for the regulation of eye movements.

Drivers and modulators from push-pull and balanced synaptic input

In 1998, Sherman and Guillery proposed that there are two types of inputs to cortical neurons; drivers and modulators. These two forms of input are required to explain how, for example, sensory driven responses are controlled and modified by attention and other internally generated gating signals. One might imagine that driver signals are carried by fast ionotropic receptors, whereas modulators correspond to slower metabotropic receptors. Instead, we have proposed a novel mechanism by which both driver and modulator inputs could be carried by transmission through the same types of ionotropic receptors. In this scheme, the distinction between driver and modulator inputs is functional and changeable rather than anatomical and fixed. Driver inputs are carried by excitation and inhibition acting in a push-pull manner. This means that increases in excitation are accompanied by decreases in inhibition and vice versa. Modulators correspond to excitation and inhibition that covary so that they increase or decrease together. Theoretical and experimental work has shown that such an arrangement modulates the gain of a neuron, rather than driving it to respond. Constructing drivers and modulators in this manner allows individual excitatory synaptic inputs to play either role, and indeed to switch between roles, depending on how they are linked with inhibition.

Synaptic contributions to focal and widespread spatiotemporal dynamics in the isolated rat subiculum in vitro

The subiculum, which has a strategic position in controlling hippocampal activity, is receiving significant attention in epilepsy research. However, the functional organization of subicular circuits remains unknown. Here, we combined different recording and analytical methods to study focal and widespread population activity in the isolated subiculum in zero Mg2+ media. Patch and field recordings were combined to examine the contribution of different cell types to population activity. The properties of cells leading field activity were examined. Predictive factors for a cell to behave as leader included exhibiting the bursting phenotype, displaying a low firing threshold, and having more distal apical dendrites. A subset of bursting cells constituted the first glutamatergic type that led a recruitment process that subsequently activated additional excitatory as well as inhibitory cells. This defined a sequence of synaptic excitation and inhibition that was studied by measuring the associated conductance changes and the evolution of the composite reversal potential. It is shown that inhibition was time-locked to excitation, which shunted excitatory inputs and suppressed firing during focal activity. This was recorded extracellularly as a multi-unit ensemble of active cells, the spatial boundaries of which were controlled by inhibition in contrast to widespread epileptiform activity. Focal activity was not dependent on the preparation or the developmental state because it was also recorded under 5 mm [K+]o and in adult tissue. Our data indicate that the subicular networks can be spontaneously organized as leader-follower local circuits in which excitation is mainly driven by a subset of bursting cells and inhibition controls spatiotemporal firing.

A Learning Rule for Local Synaptic Interactions Between Excitation and Shunting Inhibition

The basic requirement for direction selectivity is a nonlinear interaction between two different inputs in space-time. In some models, the interaction is hypothesized to occur between excitation and inhibition of the shunting type in the neuron's dendritic tree. How can the required spatial specificity be acquired in an unsupervised manner? We here propose an activity-based, local learning model that can account for direction selectivity in visual cortex based on such a local veto operation and that depends on synaptically induced changes in intracellular calcium concentration. Our biophysical simulations suggest that a model cell with our learning algorithm can develop direction selectivity organically after unsupervised training. The learning rule is also applicable to a neuron with multiple-direction-selective subunits and to a pair of cells with opposite-direction selectivities and is stable under different starting conditions, delays, and velocities.

Shunting inhibition in accessory optic system neurons

The interaction of excitatory and inhibitory inputs to the accessory optic system was studied with whole cell recordings in the turtle basal optic nucleus. Previous studies have shown that visual patterns, drifting in the same preferred direction, evoke excitatory and inhibitory postsynaptic events simultaneously. Analysis of the reversal potentials for these events and their pharmacological profile suggest that they are mediated by AMPA and GABA(A) receptors, respectively. Here, neurons were recorded to study nonlinear interaction between excitatory and inhibitory responses evoked by electrical microstimulation of the retina and pretectum, respectively. The responses to coincident activation of excitatory and inhibitory inputs exhibited membrane shunting in that the excitatory response amplitude, adjusted for changes in driving force, was attenuated during the onset of the inhibitory response. This nonlinear interaction was seen in many but not all stimulus pairings. In some cases, attenuation was followed by an augmentation of the excitatory response. For comparison, the size of the excitatory response was evaluated during a hyperpolarizing current pulse that directly modulated voltage-sensitive channels of a slow rectifying I(h) current. Injection of hyperpolarizing current did not cause the attenuation of the excitatory synaptic responses. We conclude that there is a nonlinear interaction between these excitatory and inhibitory synaptic currents that is not due to hyperpolarization itself, but probably is a result of their own synaptic conductance changes, i.e., shunting. Since these events are evoked by identical visual stimuli, this interaction may play a role in visual processing.

Integration of synaptic responses to neighboring whiskers in rat barrel cortex in vivo

Characterizing input integration at the single-cell level is a critical step to understanding cortical function, particularly when sensory stimuli are represented over wide cortical areas and single cells exhibit large receptive fields. To study synaptic integration of sensory inputs, we made intracellular recordings from the barrel cortex of anesthetized rats in vivo. For each cell, we deflected the principal whisker (PW) either alone or preceded by the deflection of a single adjacent whisker (AW) at an interval of 20 or 3 ms. At the 20-ms interval in all cases, prior AW deflection significantly suppressed the PW-evoked spike output and caused the underlying synaptic response to reach a peak Vm less depolarized than that arising from PW deflection alone. The decrease in peak Vm was not attributed to hyperpolarizing inhibition but to a divisive reduction in PW-evoked PSP amplitude. The reduction in amplitude was not a result of shunting inhibition but was mostly a result of removal of the synaptic drive, or disfacilitation. When the AW-PW interval was shortened to 3 ms, spike suppression was observed in a subset of the cells studied. In most cases, a divisive reduction in synaptic response amplitude was offset by summation with the preceding AW-evoked depolarization. To determine whether suppression is a general feature of synaptic integration by barrel cortex neurons, we also characterized the interaction of responses evoked by local electrical stimulation. In contrast to the whisker data, we found that responses to paired stimulation at the same intervals produced more spikes and reached a peak Vm more depolarized than the individual responses alone, suggesting that whisker-evoked suppression is not a result of postsynaptic mechanisms. Instead, we propose that cross-whisker response suppression depends on sensory-specific mechanisms at cortical and subcortical levels.

Interneurons of the neocortical inhibitory system

Mammals adapt to a rapidly changing world because of the sophisticated cognitive functions that are supported by the neocortex. The neocortex, which forms almost 80% of the human brain, seems to have arisen from repeated duplication of a stereotypical microcircuit template with subtle specializations for different brain regions and species. The quest to unravel the blueprint of this template started more than a century ago and has revealed an immensely intricate design. The largest obstacle is the daunting variety of inhibitory interneurons that are found in the circuit. This review focuses on the organizing principles that govern the diversity of inhibitory interneurons and their circuits.

A nonlinear model of the behavior of simple cells in visual cortex

Despite their structured receptive fields (RFs) and the strong linear components in their responses, most simple cells in mammalian visual cortex exhibit nonlinear behaviors. Besides the contrast-response function, nonlinearities are evident in various types of failure at superposition tasks, in the disagreement between direction indices computed from drifting and counterphase flickering gratings, in various forms of response suppression (including end- and side-stopping, spatial-frequency-specific inhibition and cross-orientation inhibition), in the advance of phase with increasing contrast, and in phase-insensitive and frequency-doubled responses to counterphase flickering gratings. These behaviors suggest that nonlinearities are involved in the operation of simple cells, but current models fail to explain them. A quantitative model is presented here that purports to describe basic and common principles of operation for all visual cortical cells. Simple cells are described as receiving afferents from multiple subunits that differ in their individual RFs and temporal impulse responses (TIRs). Subunits are independent and perform a spatial integration across their RFs followed by halfwave rectification and temporal convolution with their TIRs. This parallel operation yields a set of temporal functions representing each subunit's contribution to the membrane potential of the host cell, whose final form is given by the weighted sum of all subunits' contributions. By varying the number of subunits and their particular characteristics, different instances of the model are obtained each of which displays a different set of behaviors. Extensive simulation results are presented that illustrate how all of the reported nonlinear behaviors of simple cells arise from these multi-subunit organizations.

Amplification of trial-to-trial response variability by neurons in visual cortex

The visual cortex responds to repeated presentations of the same stimulus with high variability. Because the firing mechanism is remarkably noiseless, the source of this variability is thought to lie in the membrane potential fluctuations that result from summated synaptic input. Here this hypothesis is tested through measurements of membrane potential during visual stimulation. Surprisingly, trial-to-trial variability of membrane potential is found to be low. The ratio of variance to mean is much lower for membrane potential than for firing rate. The high variability of firing rate is explained by the threshold present in the function that converts inputs into firing rates. Given an input with small, constant noise, this function produces a firing rate with a large variance that grows with the mean. This model is validated on responses recorded both intracellularly and extracellularly. In neurons of visual cortex, thus, a simple deterministic mechanism amplifies the low variability of summated synaptic inputs into the large variability of firing rate. The computational advantages provided by this amplification are not known.

Comparison of different models of orientation selectivity based on distinct intracortical inhibition rules

Aim of this work is to present simple models of orientation selectivity in the visual cortex, which do not require massive computational effort. Three different models are compared, in order to gain deeper insight into the structure of cortical circuits generating inhibitory signals. All models represent a single hypercolumn. They differ as to the arrangement of inhibitory connections: in the first ("antiphase inhibition model") inhibition is in phase opposition with excitation, but with a similar orientation tuning; in the second ("in-phase inhibition model"), inhibition is in phase with excitation, but with larger orientation tuning. In these two models the orientation width of inhibition increases with contrast. Finally, a third model ("center-surround model") assumes that inhibition comes from the same cells providing excitation, hence the inhibition tuning is contrast-independent. All models, with suitable values of the intracortical synapse parameters, are able to mimic experimental results in the literature. A few differences are evident between the "center-surround model" and the other two, especially as to the dependence of cortical cell response on spatial frequency. The models can represent practical tools to test hypotheses on the disposition of cortical synapses avoiding massive computational efforts.

Shunting inhibition, a silent step in visual cortical computation

Brain computation, in the early visual system, is often considered as a hierarchical process in which features extracted in a given sensory relay are not present in previous stages of integration. In particular, orientation preference and its fine tuning selectivity are functional properties shared by most cortical cells and they are not observed at the preceding geniculate stage. A classical problem is identifying the mechanisms and circuitry underlying these computations. Several organizational principles have been proposed, giving different weights to the feedforward thalamocortical drive or to intracortical recurrent architectures. Within this context, an important issue is whether intracortical inhibition is fundamental for the genesis of stimulus selectivity, or rather normalizes spike response tuning with respect to other features such as stimulus strength or contrast, without influencing the selectivity bias and preference expressed in the excitatory input alone. We review here experimental observations concerning the presence or absence of inhibitory input evoked by non-preferred orientation/directions. Intracellular current clamp and voltage clamp recordings are analyzed in the light of new methods allowing us (1) to increase the visibility of inhibitory input, and (2) to continuously measure the visually evoked dynamics of input conductances. We conclude that there exists a diversity of synaptic input combinations generating the same profile of spike-based orientation selectivity, and that this diversity most likely reflects anatomical non-homogeneities in input sampling provided by the local context of the columnar and lateral intracortical network in which the considered cortical cell is embedded.

Synaptic responses to whisker deflections in rat barrel cortex as a function of cortical layer and stimulus intensity

To study the synaptic and spike responses of barrel cortex neurons as a function of cortical layer and stimulus intensity, we recorded intracellularly in vivo from barbiturate anesthetized rats while increasing the velocity-acceleration of the whisker deflection. Granular (Gr; layer 4) cells had the EPSP with the shortest peak and onset latency, whereas supragranular (SGr; layers 2-3) cells had the EPSP with longest duration and slowest rate of rise. Infragranular (Igr; layers 5-6) cells had intermediate values, and thus each layer was unique. The spike response peak of Gr cells was followed by IGr and then by SGr cells. In all cells, depolarization reduced the duration and amplitude of the response, but only in Gr cells did it reveal an early IPSP that cut short the EPSP. This early IPSP was associated with a large decrease in input resistance and an apparent reversal potential below spike threshold; consequently, synaptic integration in Gr cells was limited to the initial 5-7 msec of the response. In contrast, in SGr and IGr cells, results suggest an overlap in time of the EPSP and IPSP, with a small drop in input resistance and an apparent reversal potential above spike threshold, facilitating input integration for up to 20 msec. Decreasing stimulus intensity (velocity-acceleration) reduced the amplitude and increased the peak latency of the response without altering its synaptic composition. We propose that layer 4 circuits are better suited to perform coincidence detection, whereas supra and infragranular circuits are better designed for input integration.

A silicon early visual system as a model animal

Examples that show the transfer of our basic knowledge of brain function into practical electronic models are rare. Here we present a user-friendly silicon model of the early visual system that contributes to animal welfare. The silicon chip emulates the neurons in the visual system by using analog Very Large Scale Integration (aVLSI) circuits. It substitutes for a live animal in experiment design and lecture demonstrations. The neurons on this chip display properties that are central to biological vision: receptive fields, spike coding, adaptation, band-pass filtering, and complementary signaling. Unlike previous laboratory devices whose complexity was limited by the use of discrete components on printed circuit boards, this battery-powered chip is a self-contained patch of the visual system. The realistic responses of the chip's cells and the self-contained adjustment-free correct operation of the chip suggest the possibility of implementation of similar circuits for visual prosthetics.

A method to estimate synaptic conductances from membrane potential fluctuations

In neocortical neurons, network activity can activate a large number of synaptic inputs, resulting in highly irregular subthreshold membrane potential (V(m)) fluctuations, commonly called "synaptic noise." This activity contains information about the underlying network dynamics, but it is not easy to extract network properties from such complex and irregular activity. Here, we propose a method to estimate properties of network activity from intracellular recordings and test this method using theoretical and experimental approaches. The method is based on the analytic expression of the subthreshold V(m) distribution at steady state in conductance-based models. Fitting this analytic expression to V(m) distributions obtained from intracellular recordings provides estimates of the mean and variance of excitatory and inhibitory conductances. We test the accuracy of these estimates against computational models of increasing complexity. We also test the method using dynamic-clamp recordings of neocortical neurons in vitro. By using an on-line analysis procedure, we show that the measured conductances from spontaneous network activity can be used to re-create artificial states equivalent to real network activity. This approach should be applicable to intracellular recordings during different network states in vivo, providing a characterization of the global properties of synaptic conductances and possible insight into the underlying network mechanisms.

Neuronal integration of synaptic input in the fluctuation-driven regime

During sensory stimulation, visual cortical neurons undergo massive synaptic bombardment. This increases their input conductance, and action potentials mainly result from membrane potential fluctuations. To understand the response properties of neurons operating in this regime, we studied a model neuron with synaptic inputs represented by transient membrane conductance changes. We show that with a simultaneous increase of excitation and inhibition, the firing rate first increases, reaches a maximum, and then decreases at higher input rates. Comodulation of excitation and inhibition, therefore, does not provide a straightforward way of controlling the neuronal firing rate, in contrast to coding mechanisms postulated previously. The synaptically induced conductance increase plays a key role in this effect: it decreases firing rate by shunting membrane potential fluctuations, and increases it by reducing the membrane time constant, allowing for faster membrane potential transients. These findings do not depend on details of the model and, hence, are relevant to cells of other cortical areas as well.

Large-scale modeling of the primary visual cortex: influence of cortical architecture upon neuronal response

A large-scale computational model of a local patch of input layer 4 [Formula: see text] of the primary visual cortex (V1) of the macaque monkey, together with a coarse-grained reduction of the model, are used to understand potential effects of cortical architecture upon neuronal performance. Both the large-scale point neuron model and its asymptotic reduction are described. The work focuses upon orientation preference and selectivity, and upon the spatial distribution of neuronal responses across the cortical layer. Emphasis is given to the role of cortical architecture (the geometry of synaptic connectivity, of the ordered and disordered structure of input feature maps, and of their interplay) as mechanisms underlying cortical responses within the model. Specifically: (i) Distinct characteristics of model neuronal responses (firing rates and orientation selectivity) as they depend upon the neuron's location within the cortical layer relative to the pinwheel centers of the map of orientation preference; (ii) A time independent (DC) elevation in cortico-cortical conductances within the model, in contrast to a "push-pull" antagonism between excitation and inhibition; (iii) The use of asymptotic analysis to unveil mechanisms which underly these performances of the model; (iv) A discussion of emerging experimental data. The work illustrates that large-scale scientific computation--coupled together with analytical reduction, mathematical analysis, and experimental data, can provide significant understanding and intuition about the possible mechanisms of cortical response. It also illustrates that the idealization which is a necessary part of theoretical modeling can outline in sharp relief the consequences of differing alternative interpretations and mechanisms--with final arbiter being a body of experimental evidence whose measurements address the consequences of these analyses.

Dynamic influences on coincidence detection in neocortical pyramidal neurons

The firing rate of neocortical pyramidal neurons is believed to represent primarily the average arrival rate of synaptic inputs; however, it has also been found to vary somewhat depending on the degree of synchrony among synaptic inputs. We investigated the ability of pyramidal neurons to perform coincidence detection, that is, to represent input timing in their firing rate, and explored some factors that influence that representation. We injected computer-generated simulated synaptic inputs into pyramidal neurons during whole-cell recordings, systematically altering the phase delay between two groups of periodic simulated input events. We explored how input intensity, the synaptic time course, inhibitory synaptic conductance, and input jitter influenced the firing rate representation of input timing. In agreement with computer modeling studies, we found that input synchronization increases firing rate when intensity is low but reduces firing rate when intensity is high. At high intensity, the effect of synchrony on firing rate could be switched from reducing to increasing firing rate by shortening the simulated excitatory synaptic time course, adding inhibition (using the dynamic clamp technique), or introducing a small input jitter. These opposite effects of synchrony may serve different computational functions: as a means of increasing firing rate it may be useful for efficient recruitment or for computing a continuous parameter, whereas as a means of decreasing firing rate it may provide gain control, which would allow redundant or excessive input to be ignored. Modulation of dynamic input properties may allow neurons to perform different operations depending on the task at hand.

Intracortical mechanism of stimulus-timing-dependent plasticity in visual cortical orientation tuning

Visual stimuli are known to induce various changes in the receptive field properties of adult cortical neurons, but the underlying mechanisms are not well understood. Repetitive pairing of stimuli at two orientations can induce a shift in cortical orientation tuning, with the direction and magnitude of the shift depending on the temporal order and interval between the pair. Although the temporal specificity of the effect on the order of tens of milliseconds strongly suggests spike-timing-dependent synaptic plasticity (STDP) as the underlying mechanism, it remains unclear whether the modification occurs within the cortex or at earlier stages of the visual pathway. In the present study, we examined the involvement of an intracortical mechanism in this functional modification. First, we measured interocular transfer of the shift induced by monocular conditioning. We found complete transfer of the effect at both the physiological and psychophysical levels, indicating that the modification occurs largely in the cortex. Second, we analyzed the spike timing of cortical neurons during conditioning and found it commensurate with the requirement of STDP. Finally, we compared the measured shift in orientation tuning with the prediction of a model circuit that exhibits STDP at intracortical connections. This model can account for not only the temporal specificity of the effect but also the dependence of the shift on both orientations in the conditioning pair. These results indicate that modification of intracortical connections is a key mechanism in the stimulus-timing-dependent plasticity in orientation tuning.

Local structural balance and functional interaction of excitatory and inhibitory synapses in hippocampal dendrites

Theoretical and experimental studies on the computation of neural networks suggest that neural computation results from a dynamic interplay of excitatory and inhibitory (E/I) synaptic inputs. Precisely how E/I synapses are organized structurally and functionally to facilitate meaningful interaction remains elusive. Here we show that E/I synapses are regulated across dendritic trees to maintain a constant ratio of inputs in cultured rat hippocampal neurons. This structural arrangement is accompanied by an E/I functional balance maintained by a 'push-pull' feedback regulatory mechanism that is capable of adjusting E/I efficacies in a coordinated fashion. We also found that during activity, inhibitory synapses can determine the impact of adjacent excitatory synapses only if they are colocalized on the same dendritic branch and are activated simultaneously. These fundamental relationships among E/I synapses provide organizational principles relevant to deciphering the structural and functional basis for neural computation within dendritic branches.

Tone-evoked excitatory and inhibitory synaptic conductances of primary auditory cortex neurons

In primary auditory cortex (AI) neurons, tones typically evoke a brief depolarization, which can lead to spiking, followed by a long-lasting hyperpolarization. The extent to which the hyperpolarization is due to synaptic inhibition has remained unclear. Here we report in vivo whole cell voltage-clamp measurements of tone-evoked excitatory and inhibitory synaptic conductances of AI neurons of the pentobarbital-anesthetized rat. Tones evoke an increase of excitatory synaptic conductance, followed by an increase of inhibitory synaptic conductance. The synaptic conductances can account for the gross time course of the typical membrane potential response. Synaptic excitation and inhibition have the same frequency tuning. As tone intensity increases, the amplitudes of synaptic excitation and inhibition increase, and the latency of synaptic excitation decreases. Our data indicate that the interaction of synaptic excitation and inhibition shapes the time course and frequency tuning of the spike responses of AI neurons.

Synaptic dynamics control the timing of neuronal excitation in the activated neocortical microcircuit

It is well established that sensory stimulation results in the activity of multiple functional columns in the neocortex. The manner in which neurones within each column are active in relation to each other is, however, not known. Multiple whole-cell recordings in activated neocortical slices from rat revealed diverse correlation profiles of excitatory synaptic input to different types of neurones. The specific correlation profile between any two neurones could be predicted by the settings of synaptic depression and facilitation at the input synapses. Simulations further showed that patterned activity is essential for synaptic dynamics to impose the temporal dispersion of excitatory input. We propose that synaptic dynamics choreograph neuronal activity within the neocortical microcircuit in a context-dependent manner.

Relationship between excitation and inhibition underlying size tuning and contextual response modulation in the cat primary visual cortex

In the primary visual cortex (V1), the single-neuron response to a grating stimulus placed in the classical receptive field (CRF) is suppressed by a similar stimulus presented in the CRF surround. To assess the input mechanism underlying the surround suppression, we tested the effects of iontophoretically administered GABA(A)-receptor antagonist, bicuculline methiodide (BMI), for the 46 V1 neurons in anesthetized cats. First, the stimulus-size tuning curves were studied, with or without BMI administration, for each neuron by changing the size of the grating patch. During the BMI administration, the shape of the normalized size tuning curve did not change considerably. Second, the dependency of surround suppression on the orientation of the surround grating was examined. In the control, the surround suppression showed the clear orientation tuning that peaked at an orientation the same as the optimal orientation of the CRF response. The BMI administration did not change the orientation dependency of surround suppression. We also estimated the relative contribution of excitation and inhibition to the size and orientation tuning of surround suppression. It was concluded that cortical excitation and inhibition were well balanced, having similar tuning profiles for both stimulus size and orientation of the surround grating. Furthermore, surround stimuli used for V1 neurons suppressed the CRF response of neurons in the lateral geniculate nucleus. These results suggest that surround suppression is not primarily attributable to the intracortical inhibition, but because of a reduction of thalamocortical inputs, which drive the cortical excitation and inhibition, and a subsequent decrease in the cortical excitatory interactions.

Visual cortex neurons of monkeys and cats: temporal dynamics of the spatial frequency response function

We measured the responses of striate cortex neurons as a function of spatial frequency on a fine time scale, over the course of an interval that is comparable to the duration of a single fixation (200 ms). Stationary gratings were flashed on for 200 ms and then off for 300 ms; the responses were analyzed at sequential 1-ms intervals. We found that 1) the preferred spatial frequency shifts through time from low frequencies to high frequencies, 2) the latency of the response increases as a function of spatial frequency, and 3) the poststimulus time histograms (PSTHs) are relatively shape-invariant across spatial frequency. The dynamic shifts in preferred spatial frequency appear to be a simple consequence of the latency shifts and the transient nature of the PSTH. The effects of these dynamic shifts on the coding of spatial frequency information are examined within the context of several different temporal integration strategies, and pattern-detection performance is determined as a function of the interval of integration, following response onset. The findings are considered within the context of related investigations as well as a number of functional issues: motion selectivity in depth, "coarse-to-fine" processing, direction selectivity, latency as a code for stimulus attributes, and behavioral response latency. Finally, we demonstrate that the results are qualitatively consistent with a simple feedforward model, similar to the one originally proposed in 1962 by Hubel and Wiesel, that incorporates measured differences in the response latencies and the receptive field sizes of different lateral geniculate nucleus inputs.

An egalitarian network model for the emergence of simple and complex cells in visual cortex

We explain how simple and complex cells arise in a large-scale neuronal network model of the primary visual cortex of the macaque. Our model consists of approximately 4000 integrate-and-fire, conductance-based point neurons, representing the cells in a small, 1-mm(2) patch of an input layer of the primary visual cortex. In the model the local connections are isotropic and nonspecific, and convergent input from the lateral geniculate nucleus confers cortical cells with orientation and spatial phase preference. The balance between lateral connections and lateral geniculate nucleus drive determines whether individual neurons in this recurrent circuit are simple or complex. The model reproduces qualitatively the experimentally observed distributions of both extracellular and intracellular measures of simple and complex response.

Differential arithmetic of shunting inhibition for voltage and spike rate in neocortical pyramidal cells

The main inhibitory neurotransmitter in the mammalian forebrain is gamma-amino butyric acid (GABA), which acts through A and B type receptors. GABAA receptors mediate inhibition via an increase in membrane conductance (shunting) and/or membrane potential hyperpolarization. Shunting inhibition is thought to decrease the gain between neural input and output, and thus to act as a divisor, but may do so only below the spike threshold. To investigate the role of shunting inhibition in neocortical neurons, whole-cell patch-clamp recordings were obtained from layer V pyramidal cells of somatosensory cortex in juvenile rats. Sub- and suprathreshold voltage responses were elicited by somatic step current injections and a shunting conductance was generated via a dynamic clamp. Increasing the dynamic clamp shunting conductance led to a parallel shift of the current-discharge curves and a reduced slope of the current-voltage relationship, i.e. a decrease of neural gain. Selective activation of GABAAA receptors with the competitive agonist isoguvacine or rises of endogenous GABA with the specific reuptake blocker nipecotic acid led to a proportional decrease of subthreshold membrane voltage, but a constant offset of discharge rates, thus acting like a shunting conductance. Similarly, isoguvacine and nipecotic acid decreased the gain of excitatory postsynaptic potentials. In all three experimental conditions, shunting inhibition divisively affected subthreshold voltages, while the time-averaged suprathreshold membrane potential was offset by a constant amount. I conclude that shunting inhibition in pyramidal cells has a dual impact on neural output: it is divisive for subthreshold voltages but subtractive for spike frequencies.

Balanced inhibition underlies tuning and sharpens spike timing in auditory cortex

Neurons in the primary auditory cortex are tuned to the intensity and specific frequencies of sounds, but the synaptic mechanisms underlying this tuning remain uncertain. Inhibition seems to have a functional role in the formation of cortical receptive fields, because stimuli often suppress similar or neighbouring responses, and pharmacological blockade of inhibition broadens tuning curves. Here we use whole-cell recordings in vivo to disentangle the roles of excitatory and inhibitory activity in the tone-evoked responses of single neurons in the auditory cortex. The excitatory and inhibitory receptive fields cover almost exactly the same areas, in contrast to the predictions of classical lateral inhibition models. Thus, although inhibition is typically as strong as excitation, it is not necessary to establish tuning, even in the receptive field surround. However, inhibition and excitation occurred in a precise and stereotyped temporal sequence: an initial barrage of excitatory input was rapidly quenched by inhibition, truncating the spiking response within a few (1-4) milliseconds. Balanced inhibition might thus serve to increase the temporal precision and thereby reduce the randomness of cortical operation, rather than to increase noise as has been proposed previously.

Different roles for simple-cell and complex-cell inhibition in V1

Previously, we proposed a model of the circuitry underlying simple-cell responses in cat primary visual cortex (V1) layer 4. We argued that the ordered arrangement of lateral geniculate nucleus inputs to a simple cell must be supplemented by a component of feedforward inhibition that is untuned for orientation and responds to high temporal frequencies to explain the sharp contrast-invariant orientation tuning and low-pass temporal frequency tuning of simple cells. The temporal tuning also requires a significant NMDA component in geniculocortical synapses. Recent experiments have revealed cat V1 layer 4 inhibitory neurons with two distinct types of receptive fields (RFs): complex RFs with mixed ON/OFF responses lacking in orientation tuning, and simple RFs with normal, sharp-orientation tuning (although, some respond to all orientations). We show that complex inhibitory neurons can provide the inhibition needed to explain simple-cell response properties. Given this complex cell inhibition, antiphase or "push-pull" inhibition from tuned simple inhibitory neurons acts to sharpen spatial frequency tuning, lower responses to low temporal frequency stimuli, and increase the stability of cortical activity.

Barrages of synaptic activity control the gain and sensitivity of cortical neurons

Ongoing synaptic activity, ever present in cortical neurons, may vary widely in its amplitude and characteristics, potentially having a strong influence on neuronal processing. Intracellular recordings in layer 5 pyramidal cells in prefrontal and visual cortical slices maintained in vitro revealed spontaneous periods of synaptic bombardment. Testing the responsiveness of these cortical cells to synaptic inputs or the injection of artificial excitatory postsynaptic conductances of various amplitudes revealed that background synaptic activity dramatically increased the probability of response to small inputs, decreased the slope of the input-output curve, and decreased both the latency and jitter of action potential activation. Examining the effects of different components of synaptic barrages (namely, depolarization, increase in membrane conductance, and increase in membrane potential variance) revealed that the effects observed were dominated by the membrane depolarization and increase in variance. Depolarization increased the peak cross-correlation between injected complex in vivo-like waveforms through enhancement of responsiveness to small inputs, whereas increases in variance did so through a shift in firing mode from one of threshold detection to probabilistic discharge. These results indicate that rapid increases in neuronal responsiveness, as well as increases in spike timing precision, can be achieved through balanced barrages of excitatory and inhibitory synaptic activity.

Complex receptive fields in primary visual cortex

In the early 1960s, Hubel and Wiesel reported the first physiological description of cells in cat primary visual cortex. They distinguished two main cell types: simple cells and complex cells. Based on their distinct response properties, they suggested that the two cell types could represent two consecutive stages in receptive-field construction. Since the 1960s, new experimental and computational evidence provided serious alternatives to this hierarchical model. Parallel models put forward the idea that both simple and complex receptive fields could be built in parallel by direct geniculate inputs. Recurrent models suggested that simple cells and complex cells may not be different cell types after all. To this day, a consensus among hierarchical, parallel, and recurrent models has been difficult to attain; however, the circuitry used by all models is becoming increasingly similar. The authors review theoretical and experimental evidence for each line of models emphasizing their strengths and weaknesses.

Functionally distinct inhibitory neurons at the first stage of visual cortical processing

Here we explore inhibitory circuits at the thalamocortical stage of processing in layer 4 of the cat's visual cortex, focusing on the anatomy and physiology of the interneurons themselves. Our immediate aim was to explore the inhibitory mechanisms that contribute to orientation selectivity, perhaps the most dramatic response property to emerge across the thalamocortical synapse. The broader goal was to understand how inhibitory circuits operate. Using whole-cell recording in cats in vivo, we found that layer 4 contains two populations of inhibitory cells defined by receptive field class--simple and complex. The simple cells were selective for stimulus orientation, whereas the complex cells were not. Our observations help to explain how neurons become sensitive to stimulus orientation and maintain that selectivity as stimulus contrast changes. Overall, the work suggests that different sources of inhibition, either selective for specific features or broadly tuned, interact to provide appropriate representations of elements within the environment.

Rate models for conductance-based cortical neuronal networks

Population rate models provide powerful tools for investigating the principles that underlie the cooperative function of large neuronal systems. However, biophysical interpretations of these models have been ambiguous. Hence, their applicability to real neuronal systems and their experimental validation have been severely limited. In this work, we show that conductance-based models of large cortical neuronal networks can be described by simplified rate models, provided that the network state does not possess a high degree of synchrony. We first derive a precise mapping between the parameters of the rate equations and those of the conductance-based network models for time-independent inputs. This mapping is based on the assumption that the effect of increasing the cell's input conductance on its f-I curve is mainly subtractive. This assumption is confirmed by a single compartment Hodgkin-Huxley type model with a transient potassium A-current. This approach is applied to the study of a network model of a hypercolumn in primary visual cortex. We also explore extensions of the rate model to the dynamic domain by studying the firing-rate response of our conductance-based neuron to time-dependent noisy inputs. We show that the dynamics of this response can be approximated by a time-dependent second-order differential equation. This phenomenological single-cell rate model is used to calculate the response of a conductance-based network to time-dependent inputs.

Topography and synaptic shaping of direction selectivity in primary auditory cortex

The direction of frequency-modulated (FM) sweeps is an important temporal cue in animal and human communication. FM direction-selective neurons are found in the primary auditory cortex (A1), but their topography and the mechanisms underlying their selectivity remain largely unknown. Here we report that in the rat A1, direction selectivity is topographically ordered in parallel with characteristic frequency (CF): low CF neurons preferred upward sweeps, whereas high CF neurons preferred downward sweeps. The asymmetry of 'inhibitory sidebands', suppressive regions flanking the tonal receptive field (TRF) of the spike response, also co-varied with CF. In vivo whole-cell recordings showed that the direction selectivity already present in the synaptic inputs was enhanced by cortical synaptic inhibition, which suppressed the synaptic excitation of the non-preferred direction more than that of the preferred. The excitatory and inhibitory synaptic TRFs had identical spectral tuning, but with inhibition delayed relative to excitation. The spectral asymmetry of the synaptic TRFs co-varied with CF, as had direction selectivity and sideband asymmetry, and thus suggested a synaptic mechanism for the shaping of FM direction selectivity and its topographic ordering.

Inhibitory and excitatory mechanisms underlying auditory responses to learned vocalizations in the songbird nucleus HVC

Speech and birdsong require auditory feedback for their development and maintenance, necessitating precise auditory encoding of vocal sounds. In songbirds, the telencephalic song premotor nucleus HVC contains neurons that respond highly selectively to the bird's own song (BOS), a property distinguishing HVC from its auditory afferents. We examined the contribution of inhibitory and excitatory synaptic inputs to BOS-evoked firing in those HVC neurons innervating a pathway essential for audition-dependent vocal plasticity. Using in vivo intracellular techniques, we found that G protein-coupled, potassium-mediated inhibition, tuned to the BOS, interacts with BOS-tuned excitation through several mechanisms to shape neuronal firing patterns. Furthermore, in the absence of this inhibition, the response bias to the BOS increases, reminiscent of cancellation mechanisms in other sensorimotor systems.

Dynamics of orientation selectivity in the primary visual cortex and the importance of cortical inhibition

To test theories of orientation selectivity in primary visual cortex (V1), we have done experiments to measure the dynamics of orientation tuning of single neurons in the V1 cortex of macaque monkeys. Based on our dynamics results, we propose that a V1 cell's orientation selectivity is generated mainly by both tuned enhancement and global suppression. Enhancement near the preferred orientation is probably caused by feed-forward input from LGN (plus amplification by cortical-cortical interaction). Global suppression could be supplied by cortical inhibition. Additionally, in about 1/3 of V1 neurons (usually the most sharply tuned) there is tuned suppression, centered near the cell's preferred orientation but broader than tuned enhancement. These mechanisms also can explain important features of steady-state selectivity in the V1 neuron population. Furthermore, similar neuronal mechanisms may be used generally throughout the cerebral cortex.

Turning on and off recurrent balanced cortical activity

The vast majority of synaptic connections onto neurons in the cerebral cortex arise from other cortical neurons, both excitatory and inhibitory, forming local and distant 'recurrent' networks. Although this is a basic theme of cortical organization, its study has been limited largely to theoretical investigations, which predict that local recurrent networks show a proportionality or balance between recurrent excitation and inhibition, allowing the generation of stable periods of activity. This recurrent activity might underlie such diverse operations as short-term memory, the modulation of neuronal excitability with attention, and the generation of spontaneous activity during sleep. Here we show that local cortical circuits do indeed operate through a proportional balance of excitation and inhibition generated through local recurrent connections, and that the operation of such circuits can generate self-sustaining activity that can be turned on and off by synaptic inputs. These results confirm the long-hypothesized role of recurrent activity as a basic operation of the cerebral cortex.

Modeling reverse-phi motion-selective neurons in cortex: double synaptic-veto mechanism

Reverse-phi motion is the illusory reversal of perceived direction of movement when the stimulus contrast is reversed in successive frames. Livingstone, Tsao, and Conway (2000) showed that direction-selective cells in striate cortex of the alert macaque monkey showed reversed excitatory and inhibitory regions when two different contrast bars were flashed sequentially during a two-bar interaction analysis. While correlation or motion energy models predict the reverse-phi response, it is unclear how neurons can accomplish this. We carried out detailed biophysical simulations of a direction-selective cell model implementing a synaptic shunting scheme. Our results suggest that a simple synaptic-veto mechanism with strong direction selectivity for normal motion cannot account for the observed reverse-phi motion effect. Given the nature of reverse-phi motion, a direct interaction between the ON and OFF pathway, missing in the original shunting-inhibition model, it is essential to account for the reversal of response. We here propose a double synaptic-veto mechanism in which ON excitatory synapses are gated by both delayed ON inhibition at their null side and delayed OFF inhibition at their preferred side. The converse applies to OFF excitatory synapses. Mapping this scheme onto the dendrites of a direction-selective neuron permits the model to respond best to normal motion in its preferred direction and to reverse-phi motion in its null direction. Two-bar interaction maps showed reversed excitation and inhibition regions when two different contrast bars are presented.

Orientation and direction selectivity of synaptic inputs in visual cortical neurons: a diversity of combinations produces spike tuning

This intracellular study investigates synaptic mechanisms of orientation and direction selectivity in cat area 17. Visually evoked inhibition was analyzed in 88 cells by detecting spike suppression, hyperpolarization, and reduction of trial-to-trial variability of membrane potential. In 25 of these cells, inhibition visibility was enhanced by depolarization and spike inactivation and by direct measurement of synaptic conductances. We conclude that excitatory and inhibitory inputs share the tuning preference of spiking output in 60% of cases, whereas inhibition is tuned to a different orientation in 40% of cases. For this latter type of cells, conductance measurements showed that excitation shared either the preference of the spiking output or that of the inhibition. This diversity of input combinations may reflect inhomogeneities in functional intracortical connectivity regulated by correlation-based activity-dependent processes.

Adaptive coincidence detection and dynamic gain control in visual cortical neurons in vivo

Several theories have proposed a functional role for response synchronization in sensory perception. Critics of these theories have argued that selective synchronization is physiologically implausible when cortical networks operate at high levels of activity. Using intracellular recordings from visual cortex in vivo, in combination with numerical simulations, we find dynamic changes in spike threshold that reduce cellular sensitivity to slow depolarizations and concurrently increase the relative sensitivity to rapid depolarizations. Consistent with this, we find that spike activity and high-frequency fluctuations in membrane potential are closely correlated and that both are more tightly tuned for stimulus orientation than the mean membrane potential. These findings suggest that under high-input conditions the spike-generating mechanism adaptively enhances the sensitivity to synchronous inputs while simultaneously decreasing the sensitivity to temporally uncorrelated inputs.

Recruitment of local inhibitory networks by horizontal connections in layer 2/3 of ferret visual cortex

To investigate how neurons in cortical layer 2/3 integrate horizontal inputs arising from widely distributed sites, we combined intracellular recording and voltage-sensitive dye imaging to visualize the spatiotemporal dynamics of neuronal activity evoked by electrical stimulation of multiple sites in visual cortex. Individual stimuli evoked characteristic patterns of optical activity, while delivering stimuli at multiple sites generated interacting patterns in the regions of overlap. We observed that neurons in overlapping regions received convergent horizontal activation that generated nonlinear responses due to the emergence of large inhibitory potentials. The results indicate that co-activation of multiple sets of horizontal connections recruit strong inhibition from local inhibitory networks, causing marked deviations from simple linear integration.

Target and temporal pattern selection at neocortical synapses

We attempt to summarize the properties of cortical synaptic connections and the precision with which they select their targets in the context of information processing in cortical circuits. High-frequency presynaptic bursts result in rapidly depressing responses at most inputs onto spiny cells and onto some interneurons. These 'phasic' connections detect novelty and changes in the firing rate, but report frequency of maintained activity poorly. By contrast, facilitating inputs to interneurons that target dendrites produce little or no response at low frequencies, but a facilitating-augmenting response to maintained firing. The neurons activated, the cells they in turn target and the properties of those synapses determine which parts of the circuit are recruited and in what temporal pattern. Inhibitory interneurons provide both temporal and spatial tuning. The 'forward' flow from layer-4 excitatory neurons to layer 3 and from 3 to 5 activates predominantly pyramids. 'Back' projections, from 3 to 4 and 5 to 3, do not activate excitatory cells, but target interneurons. Despite, therefore, an increasing complexity in the information integrated as it is processed through these layers, there is little 'contamination' by 'back' projections. That layer 6 acts both as a primary input layer feeding excitation 'forward' to excitatory cells in other layers and as a higher-order layer with more integrated response properties feeding inhibition to layer 4 is discussed.

Synaptic integration by V1 neurons depends on location within the orientation map

Neurons in the primary visual cortex (V1) are organized into an orientation map consisting of orientation domains arranged radially around "pinwheel centers" at which the representations of all orientations converge. We have combined optical imaging of intrinsic signals with intracellular recordings to estimate the subthreshold inputs and spike outputs of neurons located near pinwheel centers or in orientation domains. We find that neurons near pinwheel centers have subthreshold responses to all stimulus orientations but spike responses to only a narrow range of orientations. Across the map, the selectivity of inputs covaries with the selectivity of orientations in the local cortical network, while the selectivity of spike outputs does not. Thus, the input-output transformation performed by V1 neurons is powerfully influenced by the local structure of the orientation map.

Biophysiologically plausible implementations of the maximum operation

Visual processing in the cortex can be characterized by a predominantly hierarchical architecture, in which specialized brain regions along the processing pathways extract visual features of increasing complexity, accompanied by greater invariance in stimulus properties such as size and position. Various studies have postulated that a nonlinear pooling function such as the maximum (MAX) operation could be fundamental in achieving such selectivity and invariance. In this article, we are concerned with neurally plausible mechanisms that may be involved in realizing the MAX operation. Different canonical models are proposed, each based on neural mechanisms that have been previously discussed in the context of cortical processing. Through simulations and mathematical analysis, we compare the performance and robustness of these mechanisms. We derive experimentally verifiable predictions for each model and discuss the relevant physiological considerations.

A synaptic explanation of suppression in visual cortex

The responses of neurons in the primary visual cortex (V1) are suppressed by mask stimuli that do not elicit responses if presented alone. This suppression is widely believed to be mediated by intracortical inhibition. As an alternative, we propose that it can be explained by thalamocortical synaptic depression. This explanation correctly predicts that suppression is monocular, immune to cortical adaptation, and occurs for mask stimuli that elicit responses in the thalamus but not in the cortex. Depression also explains other phenomena previously ascribed to intracortical inhibition. It explains why responses saturate at high stimulus contrast, whereas selectivity for orientation and spatial frequency is invariant with contrast. It explains why transient responses to flashed stimuli are nonlinear, whereas spatial summation is primarily linear. These results suggest that the very first synapses into the cortex, and not the cortical network, may account for important response properties of V1 neurons.

Adaptation and inhibition underlie responses to time-varying interaural phase cues in a model of inferior colliculus neurons

A mathematical model was developed for exploring the sensitivity of low-frequency inferior colliculus (IC) neurons to interaural phase disparity (IPD). The formulation involves a firing-rate-type model that does not include spikes per se. The model IC neuron receives IPD-tuned excitatory and inhibitory inputs (viewed as the output of a collection of cells in the medial superior olive). The model cell possesses cellular properties of firing rate adaptation and postinhibitory rebound (PIR). The descriptions of these mechanisms are biophysically reasonable, but only semi-quantitative. We seek to explain within a minimal model the experimentally observed mismatch between responses to IPD stimuli delivered dynamically and those delivered statically (McAlpine et al. 2000; Spitzer and Semple 1993). The model reproduces many features of the responses to static IPD presentations, binaural beat, and partial range sweep stimuli. These features include differences in responses to a stimulus presented in static or dynamic context: sharper tuning and phase shifts in response to binaural beats, and hysteresis and "rise-from-nowhere" in response to partial range sweeps. Our results suggest that dynamic response features are due to the structure of inputs and the presence of firing rate adaptation and PIR mechanism in IC cells, but do not depend on a specific biophysical mechanism. We demonstrate how the model's various components contribute to shaping the observed phenomena. For example, adaptation, PIR, and transmission delay shape phase advances and delays in responses to binaural beats, adaptation and PIR shape hysteresis in different ranges of IPD, and tuned inhibition underlies asymmetry in dynamic tuning properties. We also suggest experiments to test our modeling predictions: in vitro simulation of the binaural beat (phase advance at low beat frequencies, its dependence on firing rate), in vivo partial range sweep experiments (dependence of the hysteresis curve on parameters), and inhibition blocking experiments (to study inhibitory tuning properties by observation of phase shifts).

Diverse synaptic mechanisms generate direction selectivity in the rabbit retina

The synaptic conductance of the On-Off direction-selective ganglion cells was measured during visual stimulation to determine whether the direction selectivity is a property of the circuitry presynaptic to the ganglion cells or is generated by postsynaptic interaction of excitatory and inhibitory inputs. Three synaptic asymmetries were identified that contribute to the generation of direction-selective responses: (1) a presynaptic mechanism producing stronger excitation in the preferred direction, (2) a presynaptic mechanism producing stronger inhibition in the opposite direction, and (3) postsynaptic interaction of excitation with spatially offset inhibition. Although the on- and off-responses showed the same directional tuning, the off-response was generated by all three mechanisms, whereas the on-response was generated primarily by the two presynaptic mechanisms. The results indicate that, within a single neuron, different strategies are used within distinct dendritic arbors to accomplish the same neural computation.

States of high conductance in a large-scale model of the visual cortex

This paper reports on the consequences of large, activity dependent, synaptic conductances for neurons in a large-scale neuronal network model of the input layer 4Calpha of the Macaque primary visual cortex (Area V1). This high conductance state accounts for experimental observations about orientation selectivity, dynamics, and response magnitude (D. McLaughlin et al. (2000) Proc. Natl. Acad. Sci. USA 97: 8087-8092), and the linear dependence of Simple cells on visual stimuli (J. Wielaard et al. (2001) J. Neuroscience 21: 5203-5211). The source of large conductances in the model can be traced to inhibitory corticocortical synapses, and the model's predictions of large conductance changes are consistent with recent intracellular measurements (L. Borg-Graham et al. (1998) Nature 393: 369-373; J. Hirsch et al. (1998) J. Neuroscience 15: 9517-9528; J.S. Anderson et al. (2000) J. Neurophysiol. 84: 909-926). During visual stimulation, these conductances are large enough that their associated time-scales become the shortest in the model cortex, even below that of synaptic interactions. One consequence of this activity driven separation of time-scales is that a neuron responds very quickly to temporal changes in its synaptic drive, with its intracellular membrane potential tracking closely an effective reversal potential composed of the instantaneous synaptic inputs. From the effective potential and large synaptic conductance, the spiking activity of a cell can be expressed in an interesting and simplified manner, with the result suggesting how accurate and smoothly graded responses are achieved in the model network. Further, since neurons in this high-conductance state respond quickly, they are also good candidates as coincidence detectors and burst transmitters.

Suppression without inhibition in visual cortex

Neurons in primary visual cortex (V1) are thought to receive inhibition from other V1 neurons selective for a variety of orientations. Evidence for this inhibition is commonly found in cross-orientation suppression: responses of a V1 neuron to optimally oriented bars are suppressed by superimposed mask bars of different orientation. We show, however, that suppression is unlikely to result from intracortical inhibition. First, suppression can be obtained with masks drifting too rapidly to elicit much of a response in cortex. Second, suppression is immune to hyperpolarization (through visual adaptation) of cortical neurons responding to the mask. Signals mediating suppression might originate in thalamus, rather than in cortex. Thalamic neurons exhibit some suppression; additional suppression might arise from depression at thalamocortical synapses. The mechanisms of suppression are subcortical and possibly include the very first synapse into cortex.