Variation in the response latency of cat retinal ganglion cells

The mechanism of human color vision and potential implanted devices for artificial color vision

Vision plays a major role in perceiving external stimuli and information in our daily lives. The neural mechanism of color vision is complicated, involving the co-ordinated functions of a variety of cells, such as retinal cells and lateral geniculate nucleus cells, as well as multiple levels of the visual cortex. In this work, we reviewed the history of experimental and theoretical studies on this issue, from the fundamental functions of the individual cells of the visual system to the coding in the transmission of neural signals and sophisticated brain processes at different levels. We discuss various hypotheses, models, and theories related to the color vision mechanism and present some suggestions for developing novel implanted devices that may help restore color vision in visually impaired people or introduce artificial color vision to those who need it.

Multisensory integration in neurons of the medial pulvinar of macaque monkey

The pulvinar is a heterogeneous thalamic nucleus, which is well developed in primates. One of its subdivisions, the medial pulvinar, is connected to many cortical areas, including the visual, auditory, and somatosensory cortices, as well as with multisensory areas and premotor areas. However, except for the visual modality, little is known about its sensory functions. A hypothesis is that, as a region of convergence of information from different sensory modalities, the medial pulvinar plays a role in multisensory integration. To test this hypothesis, 2 macaque monkeys were trained to a fixation task and the responses of single-units to visual, auditory, and auditory-visual stimuli were examined. Analysis revealed auditory, visual, and multisensory neurons in the medial pulvinar. It also revealed multisensory integration in this structure, mainly suppressive (the audiovisual response is less than the strongest unisensory response) and subadditive (the audiovisual response is less than the sum of the auditory and the visual responses). These findings suggest that the medial pulvinar is involved in multisensory integration.

Neuronal Mechanisms of Visual Attention

Advances on several fronts have refined our understanding of the neuronal mechanisms of attention. This review focuses on recent progress in understanding visual attention through single-neuron recordings made in behaving subjects. Simultaneous recordings from populations of individual cells have shown that attention is associated with changes in the correlated firing of neurons that can enhance the quality of sensory representations. Other work has shown that sensory normalization mechanisms are important for explaining many aspects of how visual representations change with attention, and these mechanisms must be taken into account when evaluating attention-related neuronal modulations. Studies comparing different brain structures suggest that attention is composed of several cognitive processes, which might be controlled by different brain regions. Collectively, these and other recent findings provide a clearer picture of how representations in the visual system change when attention shifts from one target to another.

Spike-Triggered Covariance Analysis Reveals Phenomenological Diversity of Contrast Adaptation in the Retina

When visual contrast changes, retinal ganglion cells adapt by adjusting their sensitivity as well as their temporal filtering characteristics. The latter has classically been described by contrast-induced gain changes that depend on temporal frequency. Here, we explored a new perspective on contrast-induced changes in temporal filtering by using spike-triggered covariance analysis to extract multiple parallel temporal filters for individual ganglion cells. Based on multielectrode-array recordings from ganglion cells in the isolated salamander retina, we found that contrast adaptation of temporal filtering can largely be captured by contrast-invariant sets of filters with contrast-dependent weights. Moreover, differences among the ganglion cells in the filter sets and their contrast-dependent contributions allowed us to phenomenologically distinguish three types of filter changes. The first type is characterized by newly emerging features at higher contrast, which can be reproduced by computational models that contain response-triggered gain-control mechanisms. The second type follows from stronger adaptation in the Off pathway as compared to the On pathway in On-Off-type ganglion cells. Finally, we found that, in a subset of neurons, contrast-induced filter changes are governed by particularly strong spike-timing dynamics, in particular by pronounced stimulus-dependent latency shifts that can be observed in these cells. Together, our results show that the contrast dependence of temporal filtering in retinal ganglion cells has a multifaceted phenomenology and that a multi-filter analysis can provide a useful basis for capturing the underlying signal-processing dynamics.

Our sensory systems have to process stimuli under a wide range of environmental conditions. To cope with this challenge, the involved neurons adapt by adjusting their signal processing to the recently encountered intensity range. In the visual system, one finds, for example, that higher visual contrast leads to changes in how visual signals are temporally filtered, making signal processing faster and more band-pass-like at higher contrast. By analyzing signals from neurons in the retina of salamanders, we here found that these adaptation effects can be described by a fixed set of filters, independent of contrast, whose relative contributions change with contrast. Also, we found that different phenomena contribute to this adaptation. In particular, some cells change their relative sensitivity to light increments and light decrements, whereas other cells are influenced by a strong contrast-dependence of the exact timing of their responses. Our results show that contrast adaptation in the retina is not an entirely homogeneous phenomenon, and that models with multiple filters can help in characterizing sensory adaptation.

Combined effects of motor response, sensory modality, and stimulus intensity on temporal reproduction

The ability to estimate a filled interval of time is affected by numerous non-temporal factors, such as the sensory modality, duration, and the intensity of the stimulus. Here we explore the role of modality (auditory or visual), stimulus intensity (low vs. high), and motor response speed on the ability to reproduce the duration of short (<1 s) filled intervals. In accordance with the literature, the reproduced duration was affected by both the modality and the intensity of the stimulus; longer reproduction times were generally observed for visual as compared to auditory stimuli, and for low as compared to high-intensity stimuli. We used general estimating equations in order to determine whether these factors independently affected participants' ability to reproduce a given duration, after eliminating the variability associated with reaction time, since it covaried with the reproduced durations. This analysis revealed that stimulus duration, modality, and intensity were all significant independent predictors of the reproduced durations. Additionally, duration interacted with intensity when reproducing auditory intervals. That is, after taking into account the general speeding-up effect that high-intensity stimuli have on responses, they seem to have an additional effect on the rate of the internal clock. These results support previous evidence suggesting that auditory and visual clocks run at different speeds.

Dynamic alignment models for neural coding

Recently, there have been remarkable advances in modeling the relationships between the sensory environment, neuronal responses, and behavior. However, most models cannot encompass variable stimulus-response relationships such as varying response latencies and state or context dependence of the neural code. Here, we consider response modeling as a dynamic alignment problem and model stimulus and response jointly by a mixed pair hidden Markov model (MPH). In MPHs, multiple stimulus-response relationships (e.g., receptive fields) are represented by different states or groups of states in a Markov chain. Each stimulus-response relationship features temporal flexibility, allowing modeling of variable response latencies, including noisy ones. We derive algorithms for learning of MPH parameters and for inference of spike response probabilities. We show that some linear-nonlinear Poisson cascade (LNP) models are a special case of MPHs. We demonstrate the efficiency and usefulness of MPHs in simulations of both jittered and switching spike responses to white noise and natural stimuli. Furthermore, we apply MPHs to extracellular single and multi-unit data recorded in cortical brain areas of singing birds to showcase a novel method for estimating response lag distributions. MPHs allow simultaneous estimation of receptive fields, latency statistics, and hidden state dynamics and so can help to uncover complex stimulus response relationships that are subject to variable timing and involve diverse neural codes.

The brain computes using electrical discharges of nerve cells, so called spikes. Specific sensory stimuli, for instance, tones, often lead to specific spiking patterns. The same is true for behavior: specific motor actions are generated by specific spiking patterns. The relationship between neural activity and stimuli or motor actions can be difficult to infer, because of dynamic dependencies and hidden nonlinearities. For instance, in a freely behaving animal a neuron could exhibit variable levels of sensory and motor involvements depending on the state of the animal and on current motor plans—a situation that cannot be accounted for by many existing models. Here we present a new type of model that is specifically designed to cope with such changing regularities. We outline the mathematical framework and show, through computer simulations and application to recorded neural data, how MPHs can advance our understanding of stimulus-response relationships.

Selectivity of direct and network-mediated stimulation of the retinal ganglion cells with epi-, sub- and intraretinal electrodes

OBJECTIVE

Intra-retinal placement of stimulating electrodes can provide close and stable proximity to target neurons. We assessed improvement in stimulation thresholds and selectivity of the direct and network-mediated retinal stimulation with intraretinal electrodes, compared to epiretinal and subretinal placements.

APPROACH

Stimulation thresholds of the retinal ganglion cells (RGCs) in wild-type rat retina were measured using the patch-clamp technique. Direct and network-mediated responses were discriminated using various synaptic blockers.

MAIN RESULTS

Three types of RGC responses were identified: short latency (SL, τ < 5 ms) originating in RGCs, medium latency (ML, 3 < τ < 70 ms) originating in the inner nuclear layer and long latency (LL, τ > 40 ms) originating in photoreceptors. Cathodic epiretinal stimulation exhibited the lowest threshold for direct RGC response and the highest direct selectivity (network/direct thresholds ratio), exceeding a factor of 3 with pulse durations below 0.5 ms. For network-mediated stimulation, the lowest threshold was obtained with anodic pulses in OPL position, and its network selectivity (direct/network thresholds ratio) increased with pulse duration, exceeding a factor of 4 at 10 ms. Latency of all three types of responses decreased with increasing strength of the stimulus.

SIGNIFICANCE

These results define the optimal range of pulse durations, pulse polarities and electrode placement for the retinal prostheses aiming at direct or network-mediated stimulation of RGCs.

Attention influences single unit and local field potential response latencies in visual cortical area V4

Many previous studies have demonstrated that changes in selective attention can alter the response magnitude of visual cortical neurons, but there has been little evidence for attention affecting response latency. Small latency differences, though hard to detect, can potentially be of functional importance, and may also give insight into the mechanisms of neuronal computation. We therefore reexamined the effect of attention on the response latency of both single units and the local field potential (LFP) in primate visual cortical area V4. We find that attention does produce small (1-2 ms) but significant reductions in the latency of both the spiking and LFP responses. Though attention, like contrast elevation, reduces response latencies, we find that the two have different effects on the magnitude of the LFP. Contrast elevations increase and attention decreases the magnitude of the initial deflection of the stimulus-evoked LFP. Both contrast elevation and attention increase the magnitude of the spiking response. We speculate that latencies may be reduced at higher contrast because stronger stimulus inputs drive neurons more rapidly to spiking threshold, while attention may reduce latencies by placing neurons in a more depolarized state closer to threshold before stimulus onset.

Short-time scale dynamics in the responses to multiple stimuli in visual cortex

Many previous studies have used the presentation of multiple stimuli in the receptive fields (RFs) of visual cortical neurons to explore how neurons might operate on multiple inputs. Most of these experiments have used two fixed stimulus locations within the RF of each neuron. Here the effects of using different positions within the RF of a neuron were explored. The stimuli were presented singly at one of six locations, and also at 15 pair-wise combinations, for 24 V2 cortical neurons in two macaque monkeys. There was considerable variability in how pairs of stimuli interacted within the receptive field of any given neuron: changing the position of the stimuli could result in enhancement, winner-take-all, or suppression relative to the strongest response to a stimulus presented by itself. Across the population of neurons there was no correlation between response strength and response latency. However, for many stimulus pairs the response latency was tightly locked to the shortest response latency of any single stimulus presented by itself independent of changes in response magnitude. In other words, a stimulus that by itself elicited a relatively long latency response, would often affect the magnitude of the response to a pair of stimuli, but not change the latency. These results may provide constraints on the development of models of cortical information processing.

Preparation for voluntary movement in healthy and clinical populations: evidence from startle

In this review we provide a summary of the observations made regarding advance preparation of the motor system when presenting a startling acoustic stimulus (SAS) during various movement tasks. The predominant finding from these studies is that if the participant is prepared to make a particular movement a SAS can act to directly and quickly trigger the prepared action. A similar effect has recently been shown in patients with Parkinson's disease. This "StartReact" effect has been shown to be a robust indicator of advance motor programming as it can involuntarily release whatever movement has been prepared. We review the historical origins of the StartReact effect and the experimental results detailing circumstances where advance preparation occurs, when it occurs, and how these processes change with practice for both healthy and clinical populations. Data from some of these startle experiments has called into question some of the previously held hypotheses and assumptions with respect to the nature of response preparation and initiation, and how the SAS results in early response expression. As such, a secondary focus is to review previous hypotheses and introduce an updated model of how the SAS may interact with response preparation and initiation channels from a neurophysiological perspective.

Robust sensory gating in the cortical visual evoked potential using two spatially separated stimuli

OBJECTIVE

Sensory gating has been reported to be either absent or weak in the cortical visual evoked potential (VEP) response to diffuse or spatially overlapping stimuli. In this study, the authors evaluated sensory gating to two spatially separated visual stimuli.

METHODS

Spatially separated stimuli were presented either singly or in combination at the same or different onset times and the VEP recorded at either Oz, or O1 and O2, referenced to Cz.

RESULTS

When one visual stimulus is flashed on, the VEP response to another non-overlapping stimulus is almost completely suppressed.

CONCLUSIONS

The VEP does not reflect the bulk activation of retinotopically organized visual cortex, but rather it primarily reflects a distributed mode of visual cortical activity that only indicates that at least one visual stimulus was presented, and not how many or in what order.

SIGNIFICANCE

Other studies performing intracortical recordings of the local field potential (LFP) in visual cortex have identified a slow-distributed component that exhibits the same nonlinearity found here in the VEP, suggesting that these two phenomena are related.

The response dynamics of rabbit retinal ganglion cells to simulated blur

Retinal ganglion cells (RGCs) are highly sensitive to changes in contrast, which is crucial for the detection of edges in a visual scene. However, in the natural environment, edges do not just vary in contrast, but edges also vary in the degree of blur, which can be caused by distance from the plane of fixation, motion, and shadows. Hence, blur is as much a characteristic of an edge as luminance contrast, yet its effects on the responses of RGCs are largely unexplored.We examined the responses of rabbit RGCs to sharp edges varying by contrast and also to high-contrast edges varying by blur. The width of the blur profile ranged from 0.73 to 13.05 deg of visual angle. For most RGCs, blurring a high-contrast edge produced the same pattern of reduction of response strength and increase in latency as decreasing the contrast of a sharp edge. In support of this, we found a significant correlation between the amount of blur required to reduce the response by 50% and the size of the receptive fields, suggesting that blur may operate by reducing the range of luminance values within the receptive field. These RGCs cannot individually encode for blur, and blur could only be estimated by comparing the responses of populations of neurons with different receptive field sizes. However, some RGCs showed a different pattern of changes in latency and magnitude with changes in contrast and blur; these neurons could encode blur directly.We also tested whether the response of a RGC to a blurred edge was linear, that is, whether the response of a neuron to a sharp edge was equal to the response to a blurred edge plus the response to the missing spatial components that were the difference between a sharp and blurred edge. Brisk-sustained cells were more linear; however, brisk-transient cells exhibited both linear and nonlinear behavior.

Spatial and temporal features of synaptic to discharge receptive field transformation in cat area 17

The aim of the present study was to characterize the spatial and temporal features of synaptic and discharge receptive fields (RFs), and to quantify their relationships, in cat area 17. For this purpose, neurons were recorded intracellularly while high-frequency flashing bars were used to generate RFs maps for synaptic and spiking responses. Comparison of the maps shows that some features of the discharge RFs depended strongly on those of the synaptic RFs, whereas others were less dependent. Spiking RF duration depended poorly and spiking RF amplitude depended moderately on those of the underlying synaptic RFs. At the other extreme, the optimal spatial frequency and phase of the discharge RFs in simple cells were almost entirely inherited from those of the synaptic RFs. Subfield width, in both simple and complex cells, was less for spiking responses compared with synaptic responses, but synaptic to discharge width ratio was relatively variable from cell to cell. When considering the whole RF of simple cells, additional variability in width ratio resulted from the presence of additional synaptic subfields that remained subthreshold. Due to these additional, subthreshold subfields, spatial frequency tuning predicted from synaptic RFs appears sharper than that predicted from spiking RFs. Excitatory subfield overlap in spiking RFs was well predicted by subfield overlap at the synaptic level. When examined in different regions of the RF, latencies appeared to be quite variable, but this variability showed negligible dependence on distance from the RF center. Nevertheless, spiking response latency faithfully reflected synaptic response latency.

Chronic stroke and aging: the impact of acoustic stimulus intensity on fractionated reaction time

In control samples, intense acoustic "go" stimuli accelerate the central and peripheral motor processes that compose simple reaction time movements. The goal of the current study was to determine whether movements that are initiated to intense acoustic cues facilitate simple reaction times in (1) adults with chronic stroke as compared to age matched controls and (2) in older as compared to younger adults. EMG and force data were collected from three groups (stroke, older adults, and younger adults) during a ballistic wrist and finger extension task. Movements were made to the onset of 80 dB and 107 dB acoustic cues and simple reaction times were fractionated into premotor and motor components. The present findings offer two important contributions to the literature. First, increases in stimulus intensity led to faster motor times in the impaired limb of stroke subjects. Second, increased stimulus intensity led to faster premotor reaction times across all groups, although an age rather than a stroke-specific motor deficit was evidenced, with the younger control group displaying significantly faster premotor times. Findings are integrated with previous evidence concerning post stroke corticospinal tract integrity and are interpreted via mechanisms which address stroke and age-related changes in motoneurons and activity in motor units.

Differential effects of startle on reaction time for finger and arm movements

Recent studies using a reaction time (RT) task have reported that a preprogrammed response could be triggered directly by a startling acoustic stimulus (115-124 dB) presented along with the usual "go" signal. It has been suggested that details of the upcoming response could be stored subcortically and are accessible by the startle volley, directly eliciting the correct movement. However, certain muscles (e.g., intrinsic hand) are heavily dependent on cortico-motoneuronal connections and thus would not be directly subject to the subcortical startle volley in a similar way to muscles whose innervations include extensive reticular connections. In this study, 14 participants performed 75 trials in each of two tasks within a RT paradigm: an arm extension task and an index finger abduction task. In 12 trials within each task, the regular go stimulus (82 dB) was replaced with a 115-dB startling stimulus. Results showed that, in the arm task, the presence of a startle reaction led to significantly shorter latency arm movements compared with the effect of the increased stimulus intensity alone. In contrast, for the finger task, no additional decrease in RT caused by startle was observed. Taken together, these results suggest that only movements that involve muscles more strongly innervated by subcortical pathways are susceptible to response advancement by startle.

Complex Spike-Event Pattern of Transienton-offRetinal Ganglion Cells

on-off transient ganglion cells of the turtle retina show distinct spike-event patterns in response to abrupt intensity changes, such as during saccadic eye movements. These patterns consist of two main spike events, with the latency of each event showing a systematic dependency on stimulus contrast. Whereas the latency of the first event decreases monotonically with increasing contrast, as expected, the second event shows the shortest latency for intermediate contrasts and a longer latency for high and low contrasts. These spike-event patterns improve the discrimination of different light-intensity transitions based on ensemble responses of the on-off transient ganglion cell subpopulation. Although the discrimination results are far better than chance using either spike counts or latencies of the first spikes, they are further improved by using properties of the second spike event. The best classification results are obtained when spike rates and latencies of both events are considered in combination. Thus spike counts and temporal structure of retinal ganglion cells carry complementary information about the stimulus condition, and thus spike-event patterns could be an important aspect of retinal coding. To investigate the origin of the spike-event patterns in retinal ganglion cells, two computational models of retinal processing are compared. A linear–nonlinear model consisting of separate filters for on and off response components fails to reproduce the spike-event patterns. A more complex cascade filter model, however, accurately predicts the timing of the spike events by using a combination of gain control loop and spike rate adaptation.

Dissociations between reaction times and temporal order judgments: a diffusion model approach

A diffusion model for simple reaction time (RT) and temporal order judgment (TOJ) tasks was developed to account for a commonly observed dissociation between these 2 tasks: Most stimulus manipulations (e.g., intensity) have larger effects in RT tasks than in TOJ tasks. The model assumes that a detection criterion determines the level of sensory evidence needed to conclude that a stimulus has been presented. Analysis of the performance that would be achieved with different possible criterion settings revealed that performance was optimal with a lower criterion setting for the TOJ task than for the RT task. In addition, the model predicts that effects of stimulus manipulations should increase with the size of the detection criterion. Thus, the model suggests that commonly observed dissociations between RT and TOJ tasks may simply be due to performance optimization in the face of conflicting task demands.

Startle produces early response latencies that are distinct from stimulus intensity effects

Recent experiments pairing a startling stimulus with a simple reaction time (RT) task have shown that when participants are startled, a prepared movement was initiated earlier in comparison to voluntary initiation. It has been argued that the startle acts to trigger the response involuntarily. However, an alternative explanation is that the decrease in RT may be due to stimulus intensity effects, not involuntary triggering. Thus the aim of the current investigation was to determine if RT simply declined in a linear fashion with increasing stimulus intensity, or if there was a point at which RT dramatically decreased. In the present experiment participants completed 50 active wrist extension trials to a target in response to an auditory stimulus of varying stimulus intensity (83-123 dB). The presented data show that RTs associated with a startle response are separate from stimulus intensity facilitated responses. Furthermore, this startle facilitation is more highly associated with sternocleidomastoid electromyographic (EMG) activity, rather than the EMG from the widely used startle response indicator muscle orbicularis oculi.

Overlapping visual response latency distributions in visual cortices and LP-pulvinar complex of the cat

The visual system of the cat is considered to be organized in both a serial and parallel manner. Studies of visual onset latencies generally suggest that parallel processing occurs throughout the dorsal stream. These studies are at odds with the proposed hierarchies of visual areas based on termination patterns of cortico-cortical projections. In previous studies, a variety of stimuli have been used to compute latencies, and this is problematic as latencies are known to depend on stimulus parameters. This could explain the discrepancy between latency and neuroanatomical based studies. Therefore, the first aim of the present study was to determine whether latencies increased along the hierarchy of visual areas when the same stimuli are used. In addition, the effect of stimulus complexity was assessed. Visual onset latencies were calculated for area 17, PMLS, AMLS, and AEV neurons. Latencies were also computed from neurons in the lateral posterior (LP)-pulvinar complex given the importance of this extrageniculate complex in cortical intercommunication. Latency distributions from all regions overlapped substantially, and no significant difference was present, regardless of the type of stimulus used. The onset latencies in the LP-pulvinar complex were comparable to those seen in cortical areas. The data suggest that the initial processing of information in the visual system is parallel, despite the presence of a neuroanatomical hierarchy. Simultaneous response onsets among cortical areas and the LP-pulvinar suggest that the latter is more than a simple relay station for information headed to cortex. The data are consistent with proposals of the LP-pulvinar as a center for the integration and distribution of information from/to multiple cortical areas.

On measuring the minimum detection time: a simple reaction time study in the time estimation paradigm

Kornblum's time estimation paradigm, together with the so-called 'race model', provides an appealing alternative for measuring the 'cut-off' which separates 'true' reaction times from anticipatory reaction times. However, the model is not precise enough to reveal the relation between the signal intensity and the 'cut-off'. Accordingly, Kornblum's model is extended with an emphasis on the measure of the 'cut-off'. Another aspect of the extension is to use a parametric method to analyse the data. In particular, it is assumed that the time estimation-induced latency is gamma distributed and the signal-induced latency is Weibull distributed, with the latter shifted by the 'cut-off'. The rationale behind the parametric assumption is discussed. For illustrative purposes, two pieces of experimental work are presented. Since the core of the race model is the assumption of an independent race between the time estimation process and the detection process, the first experiment tests whether, for the same signal intensity, the signal-induced latency distribution is invariant across different time intervals; the second experiment tests whether, for the same time interval, the time estimation-induced latency distribution is invariant across different signal intensity conditions. The data from the second experiment are also used to test various parametric assumptions in the model, which include the signal effect on the 'cut-off'. The new model fits the data well.

Single-unit responses to kinetic stimuli in New World monkey area V2: physiological characteristics of cue-invariant neurones

In order to investigate the neural processes underlying figure-ground segregation on the basis of motion, we studied the responses of neurones in the second visual area (V2) of marmoset monkeys to stimuli that moved against dynamic textured backgrounds. The stimuli were either "solid" bars, which were uniformly darker or lighter than the background's average, or kinetic ("camouflaged") bars, formed by textural elements that matched the spatial and temporal modulation of the background. Camouflaged bars were rendered visible only by the coherent motion of their textural elements. Using solid bars, we subdivided the population of marmoset V2 neurones into motion-selective (uni- and bi-directional units, 73.3% of the sample) and weakly-biased (26.7%) subpopulations. The motion selective subpopulation was further subdivided into cue-invariant neurones (units which demonstrated a similar selectivity for the direction of motion of the solid and camouflaged bars) and non-cue-invariant neurones (units which showed selectivity to the direction of motion of solid bars, but had weak or pandirectional responses to camouflaged bars). Cells with cue-invariant responses to these stimuli were as common in V2 as in the primary visual area (V1; approximately 40% of the population). In V2, neurones with cue-invariant and non-cue-invariant motion selectivity formed distinct populations in terms of classical response properties: cue-invariant neurones were characterized by a sharp axis of motion selectivity and extensive length summation, while the majority of non-cue-invariant neurones had broader motion selectivity and were end-stopped. In the light of previous studies, these different constellations of classical response properties suggest a correlation with more traditionally recognized categories of V2 units and modular compartments. The responses of V2 cells to kinetic stimuli were slightly delayed relative to their responses to luminance-defined stimuli.