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Orientation selectivity in the primary visual cortex (V1) is a receptive field property that is at once simple enough to make it amenable to experimental and theoretical approaches and yet complex enough to represent a significant transformation in the representation of the visual image. As a result, V1 has become an area of choice for studying cortical computation and its underlying mechanisms. Here we consider the receptive field properties of the simple cells in cat V1--the cells that receive direct input from thalamic relay cells--and explore how these properties, many of which are highly nonlinear, arise. We have found that many receptive field properties of V1 simple cells fall directly out of Hubel and Wiesel's feedforward model when the model incorporates realistic neuronal and synaptic mechanisms, including threshold, synaptic depression, response variability, and the membrane time constant.

SummaryContrast invariant orientation tuning in simple cells of the visual cortex depends critically on contrast dependent trial-to-trial variability in their membrane potential responses. This observation raises the question of whether this variability originates from within the cortical circuit or the feedforward inputs from the lateral geniculate nucleus (LGN). To distinguish between these two sources of variability, we first measured membrane potential responses while inactivating the surrounding cortex, and found that response variability was nearly unaffected. We then studied variability in the LGN, including contrast dependence, and the trial-to-trial correlation in responses between nearby neurons. Variability decreased significantly with contrast, whereas correlation changed little. When these experimentally measured parameters of variability were applied to a feedforward model of simple cells that included realistic mechanisms of synaptic integration, contrast-dependent, orientation independent variability emerged in the membrane potential responses. Analogous mechanisms might contribute to the stimulus dependence and propagation of variability throughout the neocortex.

In contrast to neurons of the lateral geniculate nucleus (LGN), neurons in the primary visual cortex (V1) are selective for the direction of visual motion. Cortical direction selectivity could emerge from the spatiotemporal configuration of inputs from thalamic cells, from intracortical inhibitory interactions, or from a combination of thalamic and intracortical interactions. To distinguish between these possibilities, we studied the effect of adaptation (prolonged visual stimulation) on the direction selectivity of intracellularly recorded cortical neurons. It is known that adaptation selectively reduces the responses of cortical neurons, while largely sparing the afferent LGN input. Adaptation can therefore be used as a tool to dissect the relative contribution of afferent and intracortical interactions to the generation of direction selectivity. In both simple and complex cells, adaptation caused a hyperpolarization of the resting membrane potential (−2.5 mV, simple cells, −0.95 mV complex cells). In simple cells, adaptation in either direction only slightly reduced the visually evoked depolarization; this reduction was similar for preferred and null directions. In complex cells, adaptation strongly reduced visual responses in a direction-dependent manner: the reduction was largest when the stimulus direction matched that of the adapting motion. As a result, adaptation caused changes in the direction selectivity of complex cells: direction selectivity was reduced after preferred direction adaptation and increased after null direction adaptation. Because adaptation in the null direction enhanced direction selectivity rather than reduced it, it seems unlikely that inhibition from the null direction is the primary mechanism for creating direction selectivity.

A previous study has suggested that complex cells perform a MAX-like operation on their inputs: when two bar stimuli are presented within the receptive field, regardless of their relative separation, the cell's response is similar in amplitude to the larger of the responses elicited by the individual stimuli. This description of complex cells seems at odds with the classical energy model in which complex cells receive input from multiple simple cells with overlapping receptive fields. The energy model predicts, and experiments have confirmed, that bar stimuli should facilitate or suppress one another depending on their relative separation. We have recorded intracellularly from a population of complex cells and studied their responses to paired bar stimuli in detail. A wide range of behavior was observed, from the more classical separation-dependent interactions to purely MAX-like responses. We also found that the more MAX-like a cell was, the broader its spatial-frequency tuning as measured with drifting gratings. These observations are consistent with energy models in which classical complex cells receive input from simple cells with similar preferred spatial frequencies, and MAX-like complex cells receive input from simple cells with disparate preferred spatial frequencies. Generalized energy models, then, can account for diverse modes of computation in cortical complex cells.

SummarySimple cells in primary visual cortex exhibit contrast-invariant orientation tuning, in seeming contradiction to feed-forward models that rely on lateral geniculate nucleus (LGN) input alone. Contrast invariance has therefore been thought to depend on the presence of intracortical lateral inhibition. In vivo intracellular recordings instead suggest that contrast invariance can be explained by three properties of the excitatory pathway. (1) Depolarizations evoked by orthogonal stimuli are determined by the amount of excitation a cell receives from the LGN, relative to the excitation it receives from other cortical cells. (2) Depolarizations evoked by preferred stimuli saturate at lower contrasts than the spike output of LGN relay cells. (3) Visual stimuli evoke contrast-dependent changes in trial-to-trial variability, which lead to contrast-dependent changes in the relationship between membrane potential and spike rate. Thus, high-contrast, orthogonally oriented stimuli that evoke significant depolarizations evoke few spikes. Together these mechanisms, without lateral inhibition, can account for contrast-invariant stimulus selectivity.

How can neural activity propagate through cortical networks built with weak, stochastic synapses? We find precise repetitions of spontaneous patterns of synaptic inputs in neocortical neurons in vivo and in vitro. These patterns repeat after minutes, maintaining millisecond accuracy. Calcium imaging of slices reveals reactivation of sequences of cells during the occurrence of repeated intracellular synaptic patterns. The spontaneous activity drifts with time, engaging different cells. Sequences of active neurons have distinct spatial structures and are repeated in the same order over tens of seconds, revealing modular temporal dynamics. Higher order sequences are replayed with compressed timing.

Feedforward models of visual cortex appear to be inconsistent with a well-known property of cortical cells: contrast invariance of orientation tuning. The models' fixed threshold broadens orientation tuning as contrast increases, whereas in real cells tuning width is invariant with contrast. We have compared the orientation tuning of spike and membrane potential responses in single cells. Both are contrast invariant, yet a threshold-linear relation applied to the membrane potential accurately predicts the orientation tuning of spike responses. The key to this apparent paradox lies in the noisiness of the membrane potential. Responses that are subthreshold on average are still capable of generating spikes on individual trials. Unlike the iceberg effect, contrast invariance remains intact even as threshold narrows orientation selectivity. Noise may, by extension, smooth the average relation between membrane potential and spike rate throughout the brain.

Membrane potentials of cortical neurons fluctuate between a hyperpolarized ('down') state and a depolarized ('up') state which may be separated by up to 30 mV, reflecting rapid but infrequent transitions between two patterns of synaptic input. Here we show that such fluctuations may contribute to representation of visual stimuli by cortical cells. In complex cells of anesthetized cats, where such fluctuations are most prominent, prolonged visual stimulation increased the probability of the up state. This probability increase was related to stimulus strength: its dependence on stimulus orientation and contrast matched each cell's averaged membrane potential. Thus large fluctuations in membrane potential are not simply noise on which visual responses are superimposed, but may provide a substrate for encoding sensory information.

Jagadeesh, Bharathi, Heidi Sue Wheat, Leonid L. Kontsevich, Christopher W. Tyler, and David Ferster. Direction selectivity of synaptic potentials in simple cells of the cat visual cortex. J. Neurophysiol. 78: 2772–2789, 1997. The direction selectivity of simple cells in the visual cortex is generated at least in part by nonlinear mechanisms. If a neuron were spatially linear, its responses to moving stimuli could be predicted accurately from linear combinations of its responses to stationary stimuli presented at different positions within the receptive field. In extracellular recordings, this has not been found to be the case. Although the extracellular experiments demonstrate the presence of a nonlinearity, the cellular process underlying the nonlinearity, whether an early synaptic mechanism such as a shunting inhibition or simply the spike threshold at the output, is not known. To differentiate between these possibilities, we have recorded intracellularly from simple cells of the intact cat with the whole cell patch technique. A linear model of direction selectivity was used to analyze the synaptic potentials evoked by stationary sine-wave gratings. The model predicted the responses of cells to moving gratings with considerable accuracy. The degree of direction selectivity and the time course of the responses to moving gratings were both well matched by the model. The direction selectivity of the synaptic potentials was considerably smaller than that of the intracellularly recorded action potential, indicating that a nonlinear mechanism such as threshold enhances the direction selectivity of the cell's output over that of its synaptic inputs. At the input stage, however, the cells apparently sum their synaptic inputs in a highly linear fashion. A more constrained test of linearity of synaptic summation based on principal component analysis was applied to the responses of direction-selective cells to stationary gratings. The analysis confirms that the summation in these cells is highly linear. The principal component analysis is consistent with a model in which direction selectivity in cortical simple cells is generated by only two subunits, each with a different receptive-field position and response time course. The response time course for each of the two subunits is derived for four analyzed cells. Each derived subunit is linear in spatial summation, suggesting that the neurons that comprise each subunit are either geniculate X-cells or receive their primary synaptic input from X-cells. The amplitude of the response of each subunit is linearly related to the contrast of the stimulus. The subunits are nonlinear in the time domain, however: the response to a stationary stimulus whose contrast is modulated sinusoidally in time is nonsinusoidal. The principal component analysis does not exclude models of direction selectivity based on more than two subunits, but such higher-order models would have to include the constraint that the extra subunits form a smooth continuum of interpolation between the properties derived from the two subunit solution.

MORE than 30 years after Hubel and Wiesel1 first described orientation selectivity in the mammalian visual cortex, the mechanism that gives rise to this property is still controversial. Hubel and Wiesel1 proposed a simple model for the origin of orientation tuning, in which the circularly symmetrical receptive fields of neurons in the lateral geniculate nucleus that excite a cortical simple cell are arranged in rows. Since this model was proposed, several experiments2–6 and neuronal simulations7,8 have suggested that the connectivity between the lateral geniculate nucleus and the cortex is not well organized in an orientation-specific fashion, and that orientation tuning arises instead from extensive interactions within the cortex. To test these models we have recorded visually evoked synaptic potentials in simple cells while cooling the cortex9, which largely inactivates the cortical network, but leaves geniculate synaptic input functional. We report that the orientation tuning of these potentials is almost unaffected by cooling the cortex, in agreement with Hubel and Wiesel's original proposal1.

One of the more prosaic but necessary features of almost any information processing system is gain control. All such systems must have some way to adjust the relationship between input, which can vary dramatically depending on changes in the environment, and output, which is almost always required to remain within a limited range of amplitudes. While the volume control on a radio or the brightness control on a computer monitor are not the most exciting or highly touted features, imagine such devices without these forms of gain control. Many an engineer can attest to the large effort required to design automatic gain controls in telephones, cameras, and radio transmitters.

Intracellular recordings from simple cells of the cat visual cortex were used to test linear models for the generation of selectivity for the direction of visual motion. Direction selectivity has been thought to arise in part from nonlinear processes, as suggested by previous experiments that were based on extracellular recordings of action potentials. In intracellular recordings, however, the fluctuations in membrane potential evoked by moving stimuli were accurately predicted by the linear summation of responses to stationary stimuli. Nonlinear mechanisms were not required.

Neural responses are typically characterized by computing the mean firing rate, but response variability can exist across trials. Many studies have examined the effect of a stimulus on the mean response, but few have examined the effect on response variability. We measured neural variability in 13 extracellularly recorded datasets and one intracellularly recorded dataset from seven areas spanning the four cortical lobes in monkeys and cats. In every case, stimulus onset caused a decline in neural variability. This occurred even when the stimulus produced little change in mean firing rate. The variability decline was observed in membrane potential recordings, in the spiking of individual neurons and in correlated spiking variability measured with implanted 96-electrode arrays. The variability decline was observed for all stimuli tested, regardless of whether the animal was awake, behaving or anaesthetized. This widespread variability decline suggests a rather general property of cortex, that its state is stabilized by an input.

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.

Neurons in primary visual cortex exhibit several nonlinearities in their responses to visual stimuli, including response decrements to repeated stimuli, contrast-dependent phase advance, contrast saturation, and cross-orientation suppression. Thalamocortical synaptic depression has been implicated in these phenomena but has not been examined directly in visual cortexin vivo. We assessed depression of visual thalamocortical synapsesin vivousing 20-100 Hz trains of electrical stimuli delivered to the LGN. Cortical cells receiving direct input from the LGN, identified by short latency and low jitter of LGN-evoked PSPs, showed moderate reductions in PSP amplitude during the fastest trains. Cells receiving indirect input from the thalamus via other cortical excitatory neurons show a marked reduction in PSP amplitude during a train, which could be explained either by synaptic depression in corticocortical synapses or by an inhibition-mediated suppression of the firing of their afferents. Reducing spontaneous activity in the LGN (by retinal blockade) unmasked additional depression at the thalamocortical synapse but only for the first stimulus in the train. That is, the first PSP was increased in amplitude relative to the unblocked condition, but subsequent responses were essentially unchanged. Thus, the synapses are maintained at significant levels of depression by spontaneous activity. These findings constrain the role that thalamocortical depression can play in shaping cortical responses to visual stimuli.

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.

Spike responses for many cells of cat primary visual cortex are optimized for the length of a drifting grating stimulus. Stimuli that are longer or shorter than this optimal length elicit submaximal spike responses. To investigate the mechanisms responsible for this length tuning, we have recorded intracellularly from visual cortical neurons in the cat while presenting drifting grating stimuli of varying lengths. We have found that the membrane potential responses of the cells also exhibit length tuning, but that the suppression of spike responses at lengths longer than the preferred is 30-50% stronger than the corresponding suppression of the membrane potential responses. This difference may be attributed to the effects of spike threshold. Furthermore, using steady injected currents, we have measured changes in the excitatory and inhibitory components of input conductance evoked by stimuli of different lengths. We find that, compared with optimal stimuli, long stimuli evoke both an increase in inhibitory conductance and a decrease in excitatory conductance. These two mechanisms differ in their contrast sensitivity, resulting in stronger end stopping and shorter optimal lengths for high-contrast stimuli. These patterns suggest that response suppression for long stimuli is generated by a combination of active inhibition from stimuli outside the excitatory receptive field, as well as decreased excitation from other cortical cells that are themselves end-inhibited.

The origin of orientation selectivity in the responses of simple cells in cat visual cortex serves as a model problem for understanding cortical circuitry and computation. The feed-forward model posits that this selectivity arises simply from the arrangement of thalamic inputs to a simple cell. Much evidence, including a number of recent intracellular studies, supports a primary role of the thalamic inputs in determining simple cell response properties, including orientation tuning. This mechanism alone, however, cannot explain the invariance of orientation tuning to changes in stimulus contrast. Simple cells receive push-pull inhibition: ON inhibition in OFF subregions and vice versa. Addition of such inhibition to the feed-forward model can account for this contrast invariance, provided the inhibition is sufficiently strong. The predictions of “normalization” and “feedback” models are reviewed and compared with the predictions of this modified feed-forward model and with experimental results. The modified feed-forward and the feedback models ascribe fundamentally different functions to cortical processing.

The responsiveness of neurons in the primary visual cortex (V1) is substantially reduced after a few seconds of visual stimulation with an effective pattern. This phenomenon, called pattern adaptation, is uniquely cortical and is the likely substrate of a variety of perceptual after-effects. While adaptation to a given pattern reduces the responses of V1 neurons to all subsequently viewed test patterns, this reduction shows some specificity, being strongest when the adapting and test patterns are identical. This specificity may indicate that adaptation affects the interaction between groups of neurons that are jointly activated by the adapting stimulus. We investigated this possibility by studying the effects of adaptation to visual patterns containing one or both of two orientations--the preferred orientation for a cell, and the orientation orthogonal to it. Because neurons in the primary visual cortex are sharply tuned for orientation, stimulation with orthogonal orientations excites two largely distinct populations of neurons. With intracellular recordings of the membrane potential of cat V1 neurons, we found that adaptation to the orthogonal orientation alone does not evoke the hyperpolarization that is typical of adaptation to the preferred orientation. With extracellular recordings of the firing rate of macaque V1 neurons, we found that the responses were not reduced by adaptation to the orthogonal orientation alone nearly as much as by adaptation to the preferred orientation. In the macaque we also studied the effects of adaptation to plaids containing both the preferred and the orthogonal orientations. We found that adaptation to these stimuli could modify the interactions between orientations. It increased the amount of cross-orientation suppression displayed by some cells, even turning some cells that showed cross-orientation facilitation when adapted to a blank stimulus into cells that show cross-orientation suppression. This result suggests that pattern adaptation can affect the interaction between the groups of neurons tuned to the orthogonal orientations, either by increasing their mutual inhibition or by decreasing their mutual excitation.

The firing rate responses of neurons in the primary visual cortex grow with stimulus contrast, the variation in the luminance of an image relative to the mean luminance. These responses, however, are reduced after a cell is exposed for prolonged periods to high-contrast visual stimuli. This phenomenon, known as contrast adaptation, occurs in the cortex and is not present at earlier stages of visual processing. To investigate the cellular mechanisms underlying cortical adaptation, intracellular recordings were performed in the visual cortex of cats, and the effects of prolonged visual stimulation were studied. Surprisingly, contrast adaptation barely affected the stimulus-driven modulations in the membrane potential of cortical cells. Moreover, it did not produce sizable changes in membrane resistance. The major effect of adaptation, evident both in the presence and in the absence of a visual stimulus, was a tonic hyperpolarization. Adaptation affects a class of synaptic inputs, most likely excitatory in nature, that exert a tonic influence on cortical cells.

The electrical activity of neurons triggered by a stimulus is characterized by a large component of noise. In his Perspective, Ferster discusses new results which reveal that, in the cortex of the brain, noise is not just noise at all, but contains information reflecting the activity in other parts of the brain. Optical imaging of cortical neurons by Arieli et al ., reported in this week9s issue (p. 1868), provides this new conclusion about neural noise.

How does the brain code information? Ferster and Spruston weigh the evidence in favor of a rate code (that the rate of action-potential firing carries the key information) and a temporal code (in which the pattern of firing is crucial, not just the rate).

1. Nonlinearity of spatial summation in areas 17 and 18 of cat visual cortex was compared with the type of spatial nonlinearity that differentiates X and Y cells in the lateral geniculate nucleus (LGN) and retina. The comparisons were made to examine to what extent the information from X and Y cells may remain separated in higher visual centers. 2. Responses of simple cells in areas 17 and 18 were recorded while stationary, optimally oriented sinewave gratings were sinusoidally modulated within the receptive field of the cell. Both the spatial frequency and spatial phase of the stimulus were varied. 3. Y cells in the retina and LGN are defined by the presence of a specific form of spatial nonlinearity. When tested with contrast-modulated sinewave gratings of spatial frequencies about three-fold greater than the optimal, their responses are dominated by a frequency-doubled component. The amplitude of the frequency-doubled component is not dependent on the spatial phase of the stimulus. 4. Many simple cells in the cortex showed a form of spatial nonlinearity similar to the defining nonlinearity found in retinal and geniculate Y cells. A frequency-doubled response dominated at spatial frequencies more than threefold greater than the optimal spatial frequency. When this response was present, it was phase independent. 5. More than 50% of the simple cells in area 18 showed the Y-like spatial nonlinearity. Fewer than 10% of the simple cells in area 17 showed the Y-like spatial nonlinearity. 6. The virtual absence of Y-like nonlinearity in area 17 and its relative abundance in area 18 suggest that the functional separation between the parallel X and Y pathways remains distinct within areas 17 and 18 of cat visual cortex.

When a cortical neuron receives synaptic input from both eyes, do the synaptic pathways that mediate the input from each eye match? In this study, inputs from the two eyes were compared by measuring the latencies of EPSPs and IPSPs evoked by electrical stimulation of the two optic nerves. For binocular neurons, these latencies invariably matched closely, indicating that the pathways from the two eyes contain the same number of synapses; monosynaptic input from lamina A of the lateral geniculate nucleus (LGN) is always matched by monosynaptic input from lamina A1. Conversely, polysynaptic input from one eye, either excitatory or inhibitory, is invariably accompanied by similar input from the other eye. In addition, the match between the two eyes in latency indicates that for each eye a synaptic potential is mediated by the same type of afferent, either X or Y.Judging from intracellular recording, 75% of the neurons studied were binocular, that is, EPSPs could be evoked from either eye. In the remaining 25%, EPSPs could be evoked from only one eye, in agreement with extracellular receptive field studies in which 30% of cortical neurons are monocular.

This study presents evidence that the X- and Y-cells described physiologically in the A laminae of the cat's dorsal lateral geniculate nucleus (LGN) are two morphologically distinct cell types recognizable in Golgi preparations. It is shown firstly that the three cell types seen in Golgi preparations of the A laminae (large and medium-sized principal cells and small interneurons-types 1,2 and 3 in the classification of Guillery, '66) may be identified in 1-mum Epon sections of osmicated material. While cell-diameter histograms prepared from serial 1-mum sections show a unimodal distribution of cell sizes, three populations can be distinguished if attention is paid to the presence or absence of large cytoplasmic inclusions (laminar bodies). These three populations consist of large cells lacking laminar bodies (Class I), medium-sized cells possessing laminar bodies (Class II) and small cells lacking them (Class III). That these three classes correspond to the three morphological types has been shown by (i) size comparisons, and (ii) direct demonstration of laminar bodies in the Golgi-impregnated cell bodies of Guillery's type 2 cells. Histograms prepared in this way for samples taken at various positions in the LGN show that the numbers of class II cells decline from the representation of the area centralis to the monocular segment. This decline is compensated by a corresponding rise in the numbers of class I cells. This pattern of distribution is similar to the physiologically observed distribution of X- and Y-cells, indicating that X-cells are likely to be class II cells and Y-cells class I cells. The cortical projections of the various cell types have been examined by the horseradish peroxidase method. Class II cells project to area 17 only. Most class I cells also project to area 17 only, but a few very large class I cells project to area 18. From our results, it appears that very few if any cells in the A laminae have branching axons supplying both 17 and 18. The class III cells do not project to the visual cortex, a finding consistent with their identification as interneurons. Class I and II cells are also found in lamina C and in the MIN. In both these regions there is a predominance of very large class I cells, which project to area 18. Laminae Cl-C3 contain small cells lacking laminar bodies. These cells may project to both areas 17 and 18 with branching axons. They are likely to correspond to Guillery's type 4 cells (small relay cells confined to the C laminae) and to the physiologically described W-cells. Long-term monocular deprivation causes cell shrinkage which is much more severe for class I than for class II cells. There is in addition a decrease in the relative numbers of class I cells. This decrease is found in binocular deprivation also. These observations provide an anatomical basis for the reported loss of Y-cells from deprived laminae of the LGN. It is suggested that the effects of deprivation on Y-cells may be accounted for in terms of competition for synaptic space.

Neurons of the visual cortex of the cat were penetrated with intracellular electrodes and postsynaptic potentials evoked by visual stimuli recorded. By alternately polarizing the cell with steady current injected through the recording electrode, IPSPs and EPSPs could be recorded and analyzed independently. Hyperpolarizing current suppressed IPSPs and enhanced EPSPs by moving the membrane potential toward the IPSP equilibrium potential. Depolarizing the cell toward the EPSP equilibrium potential enhanced IPSP. The responses to electrical stimulation of the LGN, where EPSPs and IPSPs could be distinguished easily by virtue of their characteristic latencies and shapes, were used to set the current injection to the appropriate level to view the two types of synaptic potential. EPSPs were found to be well oriented in that maximal depolarizing responses could be evoked at only one stimulus orientation; rotating the stimulus orientation in either direction produced a fall in the EPSP response. IPSPs were also well tuned to orientation, and invariably the preferred orientations of EPSPs and IPSPs in any one cell were identical. In addition, no systematic difference in the width of tuning of the two types of potential was seen. This result has been obtained from penetrations of over 30 cortical cells, including those with simple and complex receptive fields It is concluded that orientation of cortical receptive fields is neither created nor sharpened by inhibition between neurons with different orientation preference. The function of inhibition evoked simultaneously with excitation by optimally oriented stimuli has yet to be determined, though it is likely to be the mechanism underlying other corticalreceptive field properties, such as direction selectivit and end-stopping.

Summary When the primary visual cortex (V1) is activated by sensory stimulation, what is the temporal correlation between the synaptic inputs to nearby neurons? This question underlies the origin of correlated activity, the mechanism of how visually evoked activity emerges and propagates in cortical circuits, and the relationship between spontaneous and evoked activity. Here, we have recorded membrane potential from pairs of V1 neurons in anesthetized cats and found that visual stimulation suppressed low-frequency membrane potential synchrony (0–10 Hz), and often increased synchrony at high frequencies (20–80 Hz). The increase in high-frequency synchrony occurred for neurons with similar orientation preferences and for neurons with different orientation preferences and occurred for a wide range of stimulus orientations. Thus, while only a subset of neurons spike in response to visual stimulation, a far larger proportion of the circuit is correlated with spiking activity through subthreshold, high-frequency synchronous activity that crosses functional domains.

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.

1. The retinal disparity sensitivity of neurones in areas 17 and 18 of the cat visual cortex was examined. The response of each cell to an optimally oriented slit was measured as disparity was varied orthogonally to the receptive field orientation. Eye movements were monitored with a binocular reference cell simultaneously recorded in area 17 (HubelWiesel, 1970).2. Two types of disparity-sensitive cells were found, similar to those observed in the monkey by PoggioFischer (1977). The first type, tuned excitatory cells, were usually binocular and had a sharp peak in their disparity-response curve. They responded maximally at the disparity that brought their receptive fields into superposition on the tangent screen. This disparity closely coincided with the disparity at which the reference cell's receptive fields were also superimposed. By analogy with the monkey this point was taken to be the fixation point, or 0 degrees . The second type, near and far cells, were most often monocular. They gave their weakest response (which was usually no response at all) at 0 degrees . On one side of 0 degrees the response grew linearly for up to 4 degrees and then remained at the maximum. On the other side of zero, it remained at the minimum for up to several degrees before rising towards the maximum.3. The receptive field organization of several disparity-sensitive cells was examined using the activity profile method of Henry, BishopCoombs (1969). The size and strength of the discrete excitatory and inhibitory regions of the receptive fields of a cell could quantitatively account for the shape of its disparity-response curve.4. The laminar distribution of disparity sensitivity as well as of several other receptive field properties in areas 17 and 18 was studied. The organization of the two areas was remarkably similar in many respects. There was a difference, however, in the proportions of the two types of disparity-sensitive cells in the two areas. Area 17 contained many more tuned excitatory cells than near and far cells, while area 18 had the reverse distribution. In addition, the cells in area 18 were sensitive to a much broader range of disparities. While both areas contain disparity-sensitive neurones, these differences suggest that they play different roles in depth vision.5. Recent psychophysical and neurophysiological evidence has led to a new model of stereopsis in which depth is signalled by the pooled activity of large groups of cells (Richards, 1971). The current results are consistent with this model.

According to current theory, orientation selectivity in cortical simple cells is critically dependent on intracortical synaptic inhibition. In particular, it is thought that IPSPs evoked by stimuli of the nonpreferred orientation are required to prevent a neuron from responding to a broadly tuned excitatory input at any but the preferred orientation. Yet EPSPs recorded in simple cells are in themselves highly orientation-selective. How is this possible, when excitation arises primarily from relay cells of the lateral geniculate nucleus (LGN), which are largely insensitive to orientation? In this paper, the properties of EPSPs are compared with the predictions of a model of geniculate excitation of simple cells. The model, which is derived from the suggestions of Hubel and Wiesel (1962), relies on the now familiar arrangement of the receptive fields of presynaptic geniculate cells into lines parallel to the axis of orientation of the postsynaptic cell. Several properties of the EPSPs observed in simple cells, and the orientation tuning of simple cells observed in extracellular experiments, can be accounted for without resorting to intracortical inhibition.

Antidromic activation of layer 6 cortico-geniculate cells from the lateral geniculate nucleus (l.g.n.) was used to study synaptic effects mediated by their intracortical axon collaterals. A specific stimulation procedure, earlier shown to suppress geniculo-cortical synaptic effects and to enhance synaptic effects from layer 6 cell collaterals was employed to differentiate between inputs from the two pathways. Single cells in different cortical layers were recorded both extra- and intracellularly with glass micro-electrodes. Antidromic activation of cortico-geniculate cells at 10-16 Hz induced massive, usually repetitive, spike discharges in almost all cells in layers 2-5. The shortest latency for this synaptic activation (3.4-7.5 ms) was found for simple cells in layer 4. Cells in layers 2, 3 and 5 responded with progressively longer latencies. Cortico-geniculate cells in layer 6 were atypical in that hardly any responded with synaptic discharges to the stimulation. Intracellular recordings from layer 4 cells revealed, besides a monosynaptic excitatory post-synaptic potential (e.p.s.p.) from geniculo-cortical fibres, a late e.p.s.p. with a latency of 3.0-4.2 ms. This e.p.s.p. could only be evoked from stimulation sites within the A laminae of the l.g.n. in retinotopic register with the recording site in the cortex. No corresponding potential was obtained by stimulation of the optic tract or the superior colliculus. The threshold intensity for the late e.p.s.p. in layer 4 cells was much higher than for the geniculo-cortical e.p.s.p.s from the same stimulation sites, indicating that the effect was mediated by thin fibres. The late e.p.s.p.s increased dramatically in size with repetitive stimulation of the l.g.n. at frequencies above 7 Hz, while the geniculo-cortical e.p.s.p.s remained unchanged. In all these properties, the late e.p.s.p.s resemble similar e.p.s.p.s evoked monosynaptically in principal cells of the l.g.n. by orthodromic activation of cortico-geniculate fibres. Large e.p.s.p.s were evoked also in complex cells of layers 2, 3 and 5 and in simple cells of layer 6 upon antidromic stimulation of cortico-geniculate fibres. The sample included many efferent neurones, identified as projection cells by antidromic activation from extracortical stimulation sites. The latency and behaviour of the e.p.s.p.s in these cells indicate that the effect was mediated indirectly via layer 4 cells. Presumably, the excitation travelled along an earlier identified chain of neurones, going from layer 4 to layers 2 and 3, from there to layer 5 and then to layer 6.(ABSTRACT TRUNCATED AT 400 WORDS)