Synaptic integration in striate cortical simple cells

'Simplification' of responses of complex cells in cat striate cortex: suppressive surrounds and 'feedback' inactivation

In mammalian striate cortex (V1), two distinct functional classes of neurones, the so-called simple and complex cells, are routinely distinguished. They can be quantitatively differentiated from each other on the basis of the ratio between the phase-variant (F1) component and the mean firing rate (F0) of spike responses to luminance-modulated sinusoidal gratings (simple, F1/F0 > 1; complex, F1/F0 < 1). We investigated how recurrent cortico-cortical connections affect the spatial phase-variance of responses of V1 cells in the cat. F1/F0 ratios of the responses to optimally oriented drifting sine-wave gratings covering the classical receptive field (CRF) of single V1 cells were compared to those of: (1) responses to gratings covering the CRFs combined with gratings of different orientations presented to the 'silent' surrounds; and (2) responses to CRF stimulation during reversible inactivation of postero-temporal visual (PTV) cortex. For complex cells, the relative strength of the silent surround suppression on CRF-driven responses was positively correlated with the extent of increases in F1/F0 ratios. Inactivation of PTV cortex increased F1/F0 ratios of CRF-driven responses of complex cells only. Overall, activation of suppressive surrounds or inactivation of PTV 'converted' substantial proportions (50 and 30%, respectively) of complex cells into simple-like cells (F1/F0 > 1). Thus, the simple-complex distinction depends, at least partly, on information coming from the silent surrounds and/or feedback from 'higher-order' cortices. These results support the idea that simple and complex cells belong to the same basic cortical circuit and the spatial phase-variance of their responses depends on the relative strength of different synaptic inputs.

Laminar processing in the visual cortical column

Sensory regions of neocortex are organized as arrays of vertical columns composed of cells that share similar response properties, with the orientation columns of the cat's visual cortex being the best known example. Interest in how sensitivity to different stimulus features first emerges in the columns and how this selectivity is refined by subsequent processing has fueled decades of research. A natural starting point in approaching these issues is anatomy. Each column traverses the six cortical layers and each layer has a unique pattern of inputs, intrinsic connections and outputs. Thus, it makes sense to explore the possibility of corresponding laminar differences in sensory function, that is, to examine relationships between morphology and physiology. In addition, to help identify general patterns of cortical organization, it is useful to compare results obtained from different sensory systems and diverse species. The picture that emerges from such comparisons is that each cortical layer serves a distinct role in sensory function. Furthermore, different cortices appear to share some common strategies for processing information but also have specialized mechanisms adapted for the demands of specific sensory tasks.

Comparison Among Some Models of Orientation Selectivity

Several models exist for explaining primary visual cortex (V1) orientation tuning. The modified feedforward model (MFM) and the recurrent model (RM) are major examples. We have implemented these two models, at the same level of detail, alongside a few newer variations, and thoroughly compared their receptive-field structures. We found that antiphase inhibition in the MFM enhances both spatial phase information and orientation tuning, producing well-tuned simple cells. This remains true for a newer version of the MFM that incorporates untuned complex-cell inhibition. In contrast, when the recurrent connections in the RM are strong enough to produce typical V1 orientation tuning, they also eliminate spatial phase information, making the cells complex. Introducing phase specificity into the connections of the RM (as done in an original version of the RM) can make the cells phase sensitive, but the cells show an incorrect 90° peak shift of orientation tuning under opposite contrast signs. An inhibition-dominant version of the RM can generate well-tuned cells across the simple–complex spectrum, but it predicts that the net effect of cortical interactions is to suppress feedforward excitation across all orientations in simple cells. Finally, adding antiphase inhibition used in the MFM into the RM produces a most general model. We call this new model the modified recurrent model (MRM) and show that this model can also produce well-tuned cells throughout the simple–complex spectrum. Unlike the inhibition-dominant RM, the MRM is consistent with data from cat V1, suggesting that the net effect of cortical interactions is to boost simple cell responses at the preferred orientation. These results suggest that the MFM is well suited for explaining orientation tuning in simple cells, whereas the standard RM is for complex cells. The assignment of the RM to complex cells also avoids conflicts between the RM and the experiments of cortical inactivation (done on simple cells) and the spatial-frequency dependency of orientation tuning (found in simple cells). Because orientation-tuned V1 cells show a continuum of simple- to complex-cell behavior, the MRM provides the best description of V1 data.

Circuitry and the classification of simple and complex cells in V1

Based on a large-scale neural network model of striate cortex (V1), we present a simulation study of extra- and intracellular response modulations for drifting and contrast reversal grating stimuli. Specifically, we study the dependency of these modulations on the neural circuitry. We find that the frequently used ratio of the first harmonic to the mean response to classify simple and complex cells is highly insensitive to circuitry. Limited experimental sample size for the distribution of this measure makes it unsuitable for distinguishing whether the dichotomy of simple and complex cells originates from distinct LGN axon connectivity and/or local circuitry in V1. We show that a possible useful measure in this respect is the ratio of the intracellular second- to first-harmonic response for contrast reversal gratings. This measure is highly sensitive to neural circuitry and its distribution can be sampled with sufficient accuracy from a limited amount of experimental data. Further, the distribution of this measure is qualitatively similar to that of the subfield correlation coefficient, although it is more robust and easier to obtain experimentally.

A model of surround suppression through cortical feedback

Surround suppression occurs when a visual stimulus outside a neuron's classical receptive field causes a reduction in firing rate. It has become clear that several mechanisms are working together to induce center-surround effects such as surround suppression. While several models exist that rely on lateral connections within V1 to explain surround suppression, few have been proposed that show how cortical feedback might play a role. In this work, we propose a theory in which reductions in excitatory feedback contribute to a neuron's suppressed firing rate. We also provide a computational model that incorporates this idea.

Sustained attention and apical dendrite activity in recurrent circuits

Recurrent neural activity is a pervasive mode of cortical operations and is believed to underlie cognitive functions of working memory, attention, and the generation of spontaneous activity during sleep . It is proposed here that activity in corticothalamic recurrent circuits underlies the sustaining of attention, and that extended durations of attention are made possible by the stabilizing effects of electrical activity in long apical dendrites of pyramidal neurons. Using the cue-target delay task as a framework, the present paper describes sustained attention during the cue-target delay as activity in recurrent circuits involving layer 5/6 pyramidal neurons. At target onset, persistent activity in apical dendrites of layer 2/3 pyramidal neurons (projected from the recurrent circuits) can enhance the processing of incoming pulse trains at basal dendrites. Apical dendrite activity is assumed to modulate the soma processing of layer 2/3 and layer 5/6 pyramidal neurons at subthreshold voltage levels. The variability of successive soma depolarizations from the apical dendrite strongly influences the stability of activity in the corticothalamic recurrent circuit. Lower variability promotes higher stability. According to the present model of apical dendrite function, soma depolarizations can be reduced in variability and maintained within subthreshold levels by increasing the distance that EPSPs propagate along the apical dendrite. The close relationship between sustained attention and the electrical field potentials produced by repeated EPSP propagations in apical dendrites is supported in a brief review of sustained attention experiments that have employed measures of EEG, ERS/ERD, ERP, and LFP.

Mechanisms underlying cross-orientation suppression in cat visual cortex

In simple cells of the cat primary visual cortex, null-oriented stimuli, which by themselves evoke no response, can completely suppress the spiking response to optimally oriented stimuli. This cross-orientation suppression has been interpreted as evidence for cross-orientation inhibition: synaptic inhibition among cortical cells with different preferred orientations. In intracellular recordings from simple cells, however, we found that cross-oriented stimuli suppressed, rather than enhanced, synaptic inhibition and, at the same time, suppressed synaptic excitation. Much of the suppression of excitation could be accounted for by the behavior of geniculate relay cells: contrast saturation and rectification in relay cell responses, when applied to a linear feed-forward model, predicted cross-orientation suppression of the modulation (F1) component of excitation evoked in simple cells. In addition, we found that the suppression of the spike output of simple cells was almost twice the suppression of their synaptic inputs. Thus, cross-orientation suppression, like orientation selectivity, is strongly amplified by threshold.

A population-based model of the nonlinear dynamics of the thalamocortical feedback network displays intrinsic oscillations in the spindling (7-14 Hz) range

The thalamocortical network is modelled using the Wilson-Cowan equations for neuronal population activity. We show that this population model with biologically derived parameters possesses intrinsic nonlinear oscillatory dynamics, and that the frequency of oscillation lies within the spindle range. Spindle oscillations are an early sleep oscillation characterized by high-frequency bursts of action potentials followed by a period of quiescence, at a frequency of 7-14 Hz. Spindles are generally regarded as being generated by intrathalamic circuitry, as decorticated thalamic slices and the isolated thalamic reticular nucleus exhibit spindles. However, the role of cortical feedback has been shown to regulate and synchronize the oscillation. Previous modelling studies have mainly used conductance-based models and hence the mechanism relied upon the inclusion of ionic currents, particularly the T-type calcium current. Here we demonstrate that spindle-frequency oscillatory activity can also arise from the nonlinear dynamics of the thalamocortical circuit, and we use bifurcation analysis to examine the robustness of this oscillation in terms of the functional range of the parameters used in the model. The results suggest that the thalamocortical circuit has intrinsic nonlinear population dynamics which are capable of providing robust support for oscillatory activity within the frequency range of spindle oscillations.

Circuits that build visual cortical receptive fields

Neural sensitivity to basic elements of the visual scene changes dramatically as information is handed from the thalamus to the primary visual cortex in cats. Famously, thalamic neurons are insensitive to stimulus orientation whereas their cortical targets easily resolve small changes in stimulus angle. There are two main types of cells in the visual cortex, simple and complex, defined by the structure of their receptive fields. Simple cells are thought to lay the groundwork for orientation selectivity. This review focuses on approaches that combine anatomy with physiology at the intracellular level, to explore the circuits that build simple receptive fields and that help to maintain neural sensitivity to stimulus features even when luminance contrast changes.

Local networks in visual cortex and their influence on neuronal responses and dynamics

Networks of neurons in the cerebral cortex generate complex outputs that are not simply predicted by their inputs. These emergent responses underlie the function of the cortex. Understanding how cortical networks carry out such transformations requires a description of the responses of individual neurons and of their networks at multiple levels of analysis. We focus on orientation selectivity in primary visual cortex as a model system to understand cortical network computations. Recent experiments in our laboratory and others provide significant insight into how cortical networks generate and maintain orientation selectivity. We first review evidence for the diversity of orientation tuning characteristics in visual cortex. We then describe experiments that combine optical imaging of orientation maps with intracellular and extracellular recordings from individual neurons at known locations in the orientation map. The data indicate that excitatory and inhibitory synaptic inputs are summed across the cortex in a manner that is consistent with simple rules of integration of local inputs. These rules arise from known anatomical projection patterns in visual cortex. We propose that the generation and plasticity of orientation tuning is strongly influenced by local cortical networks-the diversity of these properties arises in part from the diversity of neighbourhood features that derive from the orientation map.

Coding of color and form in the geniculostriate visual pathway (invited review)

We review how neurons in the principal pathway connecting the retina to the visual cortex represent information about the chromatic and spatial characteristics of the retinal image. Our examination focuses particularly on individual neurons: what are their visual properties, how might these properties arise, what do these properties tell us about visual signal transformations, and how might these properties be expressed in perception? Our discussion is inclined toward studies on old-world monkeys and where possible emphasizes quantitative work that has led to or illuminates models of visual signal processing.

Responses of V1 neurons to two-dimensional hermite functions

Neurons in primary visual cortex are widely considered to be oriented filters or energy detectors that perform one-dimensional feature analysis. The main deviations from this picture are generally thought to include gain controls and modulatory influences. Here we investigate receptive field (RF) properties of single neurons with localized two-dimensional stimuli, the two-dimensional Hermite functions (TDHs). TDHs can be grouped into distinct complete orthonormal bases that are matched in contrast energy, spatial extent, and spatial frequency content but differ in two-dimensional form, and thus can be used to probe spatially specific nonlinearities. Here we use two such bases: Cartesian TDHs, which resemble vignetted gratings and checkerboards, and polar TDHs, which resemble vignetted annuli and dartboards. Of 63 isolated units, 51 responded to TDH stimuli. In 37/51 units, we found significant differences in overall response size (21/51) or apparent RF shape (28/51) that depended on which basis set was used. Because of the properties of the TDH stimuli, these findings are inconsistent with simple feedforward nonlinearities and with many variants of energy models. Rather, they imply the presence of nonlinearities that are not local in either space or spatial frequency. Units showing these differences were present to a similar degree in cat and monkey, in simple and complex cells, and in supragranular, infragranular, and granular layers. We thus find a widely distributed neurophysiological substrate for two-dimensional spatial analysis at the earliest stages of cortical processing. Moreover, the population pattern of tuning to TDH functions suggests that V1 neurons sample not only orientations, but a larger space of two-dimensional form, in an even-handed manner.

Thalamocortical specificity and the synthesis of sensory cortical receptive fields

A persistent and fundamental question in sensory cortical physiology concerns the manner in which receptive fields of layer-4 neurons are synthesized from their thalamic inputs. According to a hierarchical model proposed more than 40 years ago, simple receptive fields in layer 4 of primary visual cortex originate from the convergence of highly specific thalamocortical inputs (e.g., geniculate inputs with on-center receptive fields overlap the on subregions of layer 4 simple cells). Here, we summarize studies in the visual cortex that provide support for this high specificity of thalamic input to visual cortical simple cells. In addition, we review studies of GABAergic interneurons in the somatosensory "barrel" cortex with receptive fields that are generated by a very different mechanism: the nonspecific convergence of thalamic inputs with different response properties. We hypothesize that these 2 modes of thalamocortical connectivity onto subpopulations of excitatory and inhibitory neurons constitute a general feature of sensory neocortex and account for much of the diversity seen in layer-4 receptive fields.

Factors determining the precision of the correlated firing generated by a monosynaptic connection in the cat visual pathway

Across the visual pathway, strong monosynaptic connections generate a precise correlated firing between presynaptic and postsynaptic neurons. The precision of this correlated firing is not the same within thalamus and visual cortex. While retinogeniculate connections generate a very narrow peak in the correlogram (peak width < 1 ms), the peaks generated by geniculocortical and corticocortical connections have usually a time course of several milliseconds. Several factors could explain these differences in timing precision such as the amplitude of the monosynaptic EPSP (excitatory postsynaptic potential), its time course or the contribution of polysynaptic inputs. While it is difficult to isolate the contribution of each factor in physiological experiments, a first approximation can be done in modelling studies. Here, we simulated two monosynaptically connected neurons to measure changes in their correlated firing as we independently modified different parameters of the connection. Our results suggest that the precision of the correlated firing generated by strong monosynaptic connections is mostly determined by the EPSP time course of the connection and much less by other factors. In addition, we show that a polysynaptic pathway is unlikely to emulate the correlated firing generated by a monosynaptic connection unless it generates EPSPs with very small latency jitter.

Characterization of synaptic conductances and integrative properties during electrically induced EEG-activated states in neocortical neurons in vivo

The activation of the electroencephalogram (EEG) is paralleled with an increase in the firing rate of cortical neurons, but little is known concerning the conductance state of their membrane and its impact on their integrative properties. Here, we combined in vivo intracellular recordings with computational models to investigate EEG-activated states induced by stimulation of the brain stem ascending arousal system. Electrical stimulation of the pedonculopontine tegmental (PPT) nucleus produced long-lasting (approximately 20 s) periods of desynchronized EEG activity similar to the EEG of awake animals. Intracellularly, PPT stimulation locked the membrane into a depolarized state, similar to the up-states seen during deep anesthesia. During these EEG-activated states, however, the input resistance was higher than that during up-states. Conductance measurements were performed using different methods, which all indicate that EEG-activated states were associated with a synaptic activity dominated by inhibitory conductances. These results were confirmed by computational models of reconstructed pyramidal neurons constrained by the corresponding intracellular recordings. These models indicate that, during EEG-activated states, neocortical neurons are in a high-conductance state consistent with a stochastic integrative mode. The amplitude and timing of somatic excitatory postsynaptic potentials were nearly independent of the position of the synapses in dendrites, suggesting that EEG-activated states are compatible with coding paradigms involving the precise timing of synaptic events.

LFP Power Spectra in V1 Cortex: The Graded Effect of Stimulus Contrast

We recorded local field potentials (LFPs) and single-unit activity simultaneously in the macaque primary visual cortex (V1) and studied their responses to drifting sinusoidal gratings that were chosen to be “optimal” for the single units. Over all stimulus conditions, the LFP spectra have much greater power in the low-frequency band (≤10 Hz) than higher frequencies and can be described as “1/f.” Analysis of the total power limited to the low, gamma (25–90 Hz), or broad (8–240 Hz) frequency bands of the LFP as a function of stimulus contrast indicates that the LFP power gradually increases with stimulus strength across a wide band in a manner roughly comparable to the increase in the simultaneously recorded spike activity. However, the low-frequency band power remains approximately constant across all stimulus contrasts. More specifically the gamma-band LFP power increases differentially more with respect to baseline than either higher or lower bands as stimulus contrast increases. At the highest stimulus contrasts, we report as others have previously, that the power spectrum of the LFP typically contains an obvious peak in the gamma-frequency band. The gamma-band peak emerges from the overall broadband enhancement in LFP power at stimulus contrasts where most single units' responses have begun to saturate. The temporal/spectral structures of the LFP located in the gamma band—which become most evident at the highest contrasts—provide additional constraints on potential mechanisms underlying the stimulus response properties of spiking neurons in V1.

Time-dependent activation of feed-forward inhibition in a looming-sensitive neuron

The lobula giant movement detector (LGMD) is an identified neuron in the locust visual system that responds preferentially to objects approaching on a collision course with the animal. For such looming stimuli, the LGMD firing rate gradually increases, peaks, and decays toward the end of approach. The LGMD receives both excitatory and feed-forward inhibitory inputs on distinct branches of its dendritic tree, but little is known about the contribution of feed-forward inhibition to its response properties. We used picrotoxin, a chloride channel blocker, to selectively block feed-forward inhibition to the LGMD. We then computed differences in firing rate and membrane potential between control and picrotoxin conditions to study the activation of feed-forward inhibition. For looming stimuli, a significant activation of inhibition was observed early, as objects exceeded on average approximately 23 degrees in angular extent at the retina. Inhibition then increased in parallel with excitation over the remainder of approach trials. Experiments in which the final angular size of the approaching objects was systematically varied revealed that the relative activation of excitation and inhibition remains well balanced over most of the course of looming trials. Feed-forward inhibition actively contributed to the termination of the response to approaching objects and was particularly effective for large or slowly moving objects. Suddenly appearing and receding objects activated excitation and feed-forward inhibition nearly simultaneously, in contrast to looming stimuli. Under these conditions, the activation of excitation and feed-forward inhibition was weaker than for approaching objects, suggesting that both are preferentially tuned to approaching objects. These results support a phenomenological model of multiplication within the LGMD and provide new constraints for biophysical models of its responses to looming and receding stimuli.

Modulation of synaptic transmission in neocortex by network activities

Neocortical neurons integrate inputs from thousands of presynaptic neurons that fire in vivo with frequencies that can reach 20 Hz. An important issue in understanding cortical integration is to determine the actual impact of presynaptic firing on postsynaptic neuron in the context of an active network. We used dual intracellular recordings from synaptically connected neurons or microstimulation to study the properties of spontaneous and evoked single-axon excitatory postsynaptic potentials (EPSPs) in vivo, in barbiturate or ketamine-xylazine anaesthetized cats. We found that active states of the cortical network were associated with higher variability and decrease in amplitude and duration of the EPSPs owing to a shunting effect. Moreover, the number of apparent failures markedly increased during active states as compared with silent states. Single-axon EPSPs in vivo showed mainly paired-pulse facilitation, and the paired-pulse ratio increased during active states as compare to silent states, suggesting a decrease in release probability during active states. Raising extracellular Ca(2+) concentration to 2.5-3.0 mm by reverse microdialysis reduced the number of apparent failures and significantly increased the mean amplitude of individual synaptic potentials. Quantitative analysis of spontaneous synaptic activity suggested that the proportion of presynaptic activity that impact at the soma of a cortical neuron in vivo was low because of a high failure rate, a shunting effect and probably dendritic filtering. We conclude that during active states of cortical network, the efficacy of synaptic transmission in individual synapses is low, thus safe transmission of information requires synchronized activity of a large population of presynaptic neurons.

Direction selectivity of excitation and inhibition in simple cells of the cat primary visual cortex

Direction selectivity in simple cells of primary visual cortex, defined from their spike responses, cannot be predicted using linear models. It has been suggested that the shunting inhibition evoked by visual stimulation is responsible for the nonlinear component of direction selectivity. Cortical inhibition would suppress a neuron's firing when stimuli move in the nonpreferred direction, but would allow responses to stimuli in the preferred direction. Models of direction selectivity based solely on input from the lateral geniculate nucleus, however, propose that the nonlinear response is caused by spike threshold. By extracting excitatory and inhibitory components of synaptic inputs from intracellular records obtained in vivo, we demonstrate that excitation and inhibition are tuned for the same direction, but differ in relative timing. Further, membrane potential responses combine in a linear fashion. Spike threshold, however, quantitatively accounts for the nonlinear component of direction selectivity, amplifying the direction selectivity of spike output relative to that of synaptic inputs.

Membrane potential and response properties of populations of cortical neurons in the high conductance state

Because of intense synaptic activity, cortical neurons are in a high conductance state. We show that this state has important consequences on the properties of a population of independent model neurons with conductance-based synapses. Using an adiabaticlike approximation we study both the membrane potential and the firing probability distributions across the population. We find that the latter is bimodal in such a way that at any particular moment some neurons are inactive while others are active. The population rate and the response variability are also characterized.

Background synaptic conductance and precision of EPSP-spike coupling at pyramidal cells

The temporal precision of converting excitatory postsynaptic potentials (EPSPs) into spikes at pyramidal cells is critical for the coding of information in the cortex. Several in vitro studies have shown that voltage-dependent conductances in pyramidal cells can prolong the EPSP time course resulting in an imprecise EPSP-spike coupling. We have used dynamic-clamp techniques to mimic the in vivo background synaptic conductance in cortical slices and investigated how the ongoing synaptic activity may affect the EPSP time course near threshold and the EPSP spike coupling. We report here that background synaptic conductance dramatically diminished the depolarization related prolongation of the EPSPs in pyramidal cells and improved the precision of spike timing. Furthermore, we found that background synaptic conductance can affect the interaction among action potentials in a spike train. Thus the level of ongoing synaptic activity in the cortex may regulate the capacity of pyramidal cells to process temporal information.

Receptive field structure varies with layer in the primary visual cortex

Here we ask whether visual response pattern varies with position in the cortical microcircuit by comparing the structure of receptive fields recorded from the different layers of the cat's primary visual cortex. We used whole-cell recording in vivo to show the spatial distribution of visually evoked excitatory and inhibitory inputs and to stain individual neurons. We quantified the distribution of 'On' and 'Off' responses and the presence of spatially opponent excitation and inhibition within the receptive field. The thalamorecipient layers (4 and upper 6) were dominated by simple cells, as defined by two criteria: they had separated On and Off subregions, and they had push-pull responses (in a given subregion, stimuli of the opposite contrast evoked responses of the opposite sign). Other types of response profile correlated with laminar location as well. Thus, connections unique to each visual cortical layer are likely to serve distinct functions.

Excitatory connections made by presynaptic cortico-cortical pyramidal cells in layer 6 of the neocortex

Paired intracellular recordings with biocytin labelling were made in slices of adult rat somatosensory and visual cortex and in cat visual cortex to examine the properties of synaptic connections made by layer 6 pyramidal cells, to determine whether cortico-cortical pyramids more commonly provide input to other layer 6 pyramids than cortico-thalamic cells, and whether these connections exhibit paired pulse and brief train depression. Pyramidal cells with cortico-cortical like morphology were 2-4 times more likely to innervate other pyramidal cells than were cortico-thalamic like cells, but less likely to innervate inhibitory interneurons. The excitatory postsynaptic potentials elicited by presynaptic, phasically firing cortico-cortical pyramids in all classes of postsynaptic infragranular layer pyramidal cells exhibited strong, presynaptically mediated paired pulse and brief train depression. Those with larger paired pulse ratios also exhibited post-tetanic potentiation, but this was accompanied by stronger paired pulse and brief train depression. Both the firing characteristics and the outputs of cortico-cortical pyramidal cells display pronounced phasic characteristics, indicating that these cells respond most effectively to and preferentially pass on information related to novelty.

Tonic excitation and inhibition of neurons: ambient transmitter sources and computational consequences

Tonic activation of excitatory and inhibitory receptors, by the ambient concentration of neurotransmitters in the extracellular space of the brain, has been suggested to underlie phenomena as diverse as relapse to cocaine use by reward pathways in the striatum, sparse coding of motor information in the cerebellum, and control of the development of the cerebral and cerebellar cortices. Here we assess the mechanisms which may determine the ambient levels of excitatory and inhibitory neurotransmitters, and consider their likely effect on information processing.

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.

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.

The contribution of spike threshold to the dichotomy of cortical simple and complex cells

The existence of two classes of cells, simple and complex, discovered by Hubel and Wiesel in 1962, is one of the fundamental features of cat primary visual cortex. A quantitative measure used to distinguish simple and complex cells is the ratio between modulated and unmodulated components of spike responses to drifting gratings, an index that forms a bimodal distribution. We have found that the modulation ratio, when derived from the subthreshold membrane potential instead of from spike rate, is unimodally distributed, but highly skewed. The distribution of the modulation ratio as derived from spike rate can, in turn, be predicted quantitatively by the nonlinear properties of spike threshold applied to the skewed distribution of the subthreshold modulation ratio. Threshold also increases the spatial segregation of ON and OFF regions of the receptive field, a defining attribute of simple cells. The distinction between simple and complex cells is therefore enhanced by threshold, much like the selectivity for stimulus features such as orientation and direction. In this case, however, a continuous distribution in the spatial organization of synaptic inputs is transformed into two distinct classes of cells.

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.

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.

Suppression of auditory cortical activities in awake cats by pure tone stimuli

Based on the time courses of excitatory spike-responses to pure-tone stimuli, neurons in the primary auditory cortex (A1) of awake cats have been classified into the phasic cell (P-cell), the tonic cell (T-cell), and the phasic-tonic cell (PT-cell). In the present study, taking advantage of the presence of the spontaneous spike-activities of A1 neurons in awake animals, time courses of suppressive spike-responses to pure-tone stimuli were studied by constructing spectro-temporal spike-activity diagrams. In P-cell, the suppression and excitation temporally alternated and spectrally co-occurred, restricting excitatory spike-responses within narrow temporal limits but not setting the spectral limits. In T-cell, the suppression and excitation spectrally alternated and temporally co-occurred, restricting excitatory frequency-tuning but not setting the time limits. PT-cell has mixed response properties of P- and T-cells. The findings suggest that: (1) P-cell analyzes temporal information of the sound without active spectral limits, (2) T-cell analyzes spectral information without limits of time, and (3) PT-cell analyzes spectrally and temporally complex auditory information. Taken in the light of recent findings that the shift of the balance of the synaptic excitation and inhibition results in the spike-activity modulation of the cerebral cortical neurons, it is suggested that the temporal shift of the balance of the excitation and inhibition works in P-cell; the spectral shift, in T-cell; and the combination of the temporal and spectral shifts, in PT-cell, underlying the functional differences between cell-types.

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.

A simple cell model with dominating opponent inhibition for robust image processing

The extraction of oriented contrast information by cortical simple cells is a fundamental step in early visual processing. The orientation selectivity originates at least partly from the input of lateral geniculate nuclei neurons with properly aligned receptive fields. In the present article, we investigate the feedforward interactions between on- and off-pathways. Based on physiological evidence we propose a push-pull model with dominating opponent inhibition (DOI). We show that the model can account for empirical data on simple cells, such as contrast-invariant orientation tuning, sharpening of orientation tuning with increasing inhibition, and strong response decrements to stimuli with luminance gradient reversal. With identical parameter settings, we apply the model for the processing of synthetic and real world images. We show that the model with DOI can robustly extract oriented contrast information from noisy input. More important, noise is adaptively suppressed, i.e. the model simple cells do not respond to homogeneous regions of different noise levels, while remaining sensitive to small contrast changes. The image processing results reveal a possible functional role of the strong inhibition as observed empirically, namely to adaptively suppress responses to noisy input.

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.

Shorter latencies for motion trajectories than for flashes in population responses of cat primary visual cortex

Psychophysical evidence in humans indicates that localization is different for stationary flashed and coherently moving objects. To address how the primary visual cortex represents object position we used a population approach that pools spiking activity of many neurones in cat area 17. In response to flashed stationary squares (0.4 deg) we obtained localized activity distributions in visual field coordinates, which we referred to as profiles across a 'population receptive field' (PRF). We here show how motion trajectories can be derived from activity across the PRF and how the representation of moving and flashed stimuli differs in position. We found that motion was represented by peaks of population activity that followed the stimulus with a speed-dependent lag. However, time-to-peak latencies were shorter by approximately 16 ms compared to the population responses to stationary flashes. In addition, motion representation showed a directional bias, as latencies were more reduced for peripheral-to-central motion compared to the opposite direction. We suggest that a moving stimulus provides 'preactivation' that allows more rapid processing than for a single flash event.

Synaptic Interactions Between Thalamic and Cortical Inputs Onto Cortical Neurons In Vivo

To study the interactions between thalamic and cortical inputs onto neocortical neurons, we used paired-pulse stimulation (PPS) of thalamic and cortical inputs as well as PPS of two cortical or two thalamic inputs that converged, at different time intervals, onto intracellularly recorded cortical and thalamocortical neurons in anesthetized cats. PPS of homosynaptic cortico-cortical pathways produced facilitation, depression, or no significant effects in cortical pathways, whereas cortical responses to thalamocortical inputs were mostly facilitated at both short and long intervals. By contrast, heterosynaptic interactions between either cortical and thalamic, or thalamic and cortical, inputs generally produced decreases in the peak amplitudes and depolarization area of evoked excitatory postsynaptic potentials (EPSPs), with maximal effect at ∼10 ms and lasting from 60 to 100 ms. All neurons tested with thalamic followed by cortical stimuli showed a decrease in the apparent input resistance ( Rin), the time course of which paralleled that of decreased responses, suggesting that shunting is the factor accounting for EPSP's decrease. Only half of neurons tested with cortical followed by thalamic stimuli displayed changes in Rin. Spike shunting in the thalamus may account for those cases in which decreased synaptic responsiveness of cortical neurons was not associated with decreased Rin because thalamocortical neurons showed decreased firing probability during cortical stimulation. These results suggest a short-lasting but strong shunting between thalamocortical and cortical inputs onto cortical neurons.

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.

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.

Influence of contrast on orientation and temporal frequency tuning in ferret primary visual cortex

Neurons in primary visual cortex are highly sensitive to the contrast, orientation, and temporal frequency of a visual stimulus. These three stimulus properties can be varied independently of one another, raising the question of how they interact to influence neuronal responses. We recorded from individual neurons in ferret primary visual cortex to determine the influence of stimulus contrast on orientation tuning, temporal-frequency tuning, and latency to visual response. Results show that orientation-tuning bandwidth is not affected by contrast level. Thus neurons in ferret visual cortex display contrast-invariant orientation tuning. Stimulus contrast does, however, influence the structure of orientation-tuning curves as measures of circular variance vary inversely with contrast for both simple and complex cells. This change in circular variance depends, in part, on a contrast-dependent change in the ratio of null to preferred orientation responses. Stimulus contrast also has an influence on the temporal-frequency tuning of cortical neurons. Both simple and complex cells display a contrast-dependent rightward shift in their temporal frequency-tuning curves that results in an increase in the highest temporal frequency needed to produce a half-maximum response (TF(50)). Results show that the degree of the contrast-dependent increase in TF(50) is similar for cortical neurons and neurons in the lateral geniculate nucleus (LGN) and indicate that subcortical mechanisms likely play a major role in establishing the degree of effect displayed by downstream neurons. Finally, results show that LGN and cortical neurons experience a contrast-dependent phase advance in their visual response. This phase advance is most pronounced for cortical neurons indicating a role for both subcortical and cortical mechanisms.

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.

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.

Receptive field structure of burst and tonic firing in feline lateral geniculate nucleus

There are two recognised modes of firing activity in thalamic cells, burst and tonic. A low-threshold (LT) burst (referred to from now on as 'burst') comprises a small number of high-frequency action potentials riding the peak of a LT Ca(2+) spike which is preceded by a silent hyperpolarised state > 50 ms. This is traditionally viewed as a sleep-like phenomenon, with a shift to tonic mode at wake-up. However, bursts have also been seen in the wake state and may be a significant feature for full activation of recipient cortical cells. Here we show that for visual stimulation of anaesthetised cats, burst firing is restricted to a reduced area within the receptive field centre of lateral geniculate nucleus cells. Consistently, the receptive field size of all the recorded neurons decreased in size proportionally to the percentage of spikes in bursts versus tonic spikes, an effect that is further demonstrated with pharmacological manipulation. The role of this shrinkage may be distinct from that also seen in sleep-like states and we suggest that this is a mechanism that trades spatial resolution for security of information transfer.

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.

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.

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.

Multiplicative gain changes are induced by excitation or inhibition alone

We model the effects of excitation and inhibition on the gain of cortical neurons. Previous theoretical work has concluded that excitation or inhibition alone will not cause a multiplicative gain change in the curve of firing rate versus input current. However, such gain changes in vivo are measured in the curve of firing rate versus stimulus parameter. We find that when this curve is considered, and when the nonlinear relationships between stimulus parameter and input current and between input current and firing rate in vivo are taken into account, then simple excitation or inhibition alone can induce a multiplicative gain change. In particular, the power-law relationship between voltage and firing rate that is induced by neuronal noise is critical to this result. This suggests an unexpectedly simple mechanism that may underlie the gain modulations commonly observed in cortex. More generally, it suggests that a smaller input will multiplicatively modulate the gain of a larger one when both converge on a common cortical target.

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.

The receptive-field organization of simple cells in primary visual cortex of ferrets under natural scene stimulation

The responses of simple cells in primary visual cortex to sinusoidal gratings can primarily be predicted from their spatial receptive fields, as mapped using spots or bars. Although this quasilinearity is well documented, it is not clear whether it holds for complex natural stimuli. We recorded from simple cells in the primary visual cortex of anesthetized ferrets while stimulating with flashed digitized photographs of natural scenes. We applied standard reverse-correlation methods to quantify the average natural stimulus that invokes a neuronal response. Although these maps cannot be the receptive fields, we find that they still predict the preferred orientation of grating for each cell very well (r = 0.91); they do not predict the spatial-frequency tuning. Using a novel application of the linear reconstruction method called regularized pseudoinverse, we were able to recover high-resolution receptive-field maps from the responses to a relatively small number of natural scenes. These receptive-field maps not only predict the optimum orientation of each cell (r = 0.96) but also the spatial-frequency optimum (r = 0.89); the maps also predict the tuning bandwidths of many cells. Therefore, our first conclusion is that the tuning preferences of the cells are primarily linear and constant across stimulus type. However, when we used these maps to predict the actual responses of the cells to natural scenes, we did find evidence of expansive output nonlinearity and nonlinear influences from outside the classical receptive fields, orientation tuning, and spatial-frequency tuning.