A multiplicity of color-responsive cortical mechanisms revealed by the dynamics of cVEPs

Our results connect higher-order color mechanisms deduced from psychophysics with the known diversity of populations of double-opponent, color-responsive cells in V1. We used the chromatic visual evoked potential, the cVEP, to study responses in human visual cortex to equiluminant color patterns. Stimuli were modulated along three directions in color space: the cardinal directions, L-M and S, and along the line in color space from the white point to the color of the Red LED in the display screen (the Red direction). The Red direction is roughly intermediate between L-M and S in DKL space in cone-contrast coordinates. While cVEP response amplitude, latency, and width--and their dependences on cone contrast-- were similar in the L-M and Red directions, the Transientness of the Red response was significantly greater than for responses to stimuli in the L-M direction and in the S direction. This difference in response dynamics supports the concept that there are multiple, distinct neuronal populations, so-called higher- order color mechanisms, for color perception within human V1 cortex.

Distinct spatiotemporal mechanisms underlie extra-classical receptive field modulation in macaque V1 microcircuits

Complex scene perception depends upon the interaction between signals from the classical receptive field (CRF) and the extra-classical receptive field (eCRF) in primary visual cortex (V1) neurons. Although much is known about V1 eCRF properties, we do not yet know how the underlying mechanisms map onto the cortical microcircuit. We probed the spatio-temporal dynamics of eCRF modulation using a reverse correlation paradigm, and found three principal eCRF mechanisms: tuned-facilitation, untuned-suppression, and tuned-suppression. Each mechanism had a distinct timing and spatial profile. Laminar analysis showed that the timing, orientation-tuning, and strength of eCRF mechanisms had distinct signatures within magnocellular and parvocellular processing streams in the V1 microcircuit. The existence of multiple eCRF mechanisms provides new insights into how V1 responds to spatial context. Modeling revealed that the differences in timing and scale of these mechanisms predicted distinct patterns of net modulation, reconciling many previous disparate physiological and psychophysical findings.

Population rate-coding predicts correctly that human sound localization depends on sound intensity

Human sound localization is an important computation performed by the brain. Models of sound localization commonly assume that sound lateralization from interaural time differences is level invariant. Here we observe that two prevalent theories of sound localization make opposing predictions. The labelled-line model encodes location through tuned representations of spatial location and predicts that perceived direction is level invariant. In contrast, the hemispheric-difference model encodes location through spike-rate and predicts that perceived direction becomes medially biased at low sound levels. Here, behavioral experiments find that softer sounds are perceived closer to midline than louder sounds, favoring rate-coding models of human sound localization. Analogously, visual depth perception, which is based on interocular disparity, depends on the contrast of the target. The similar results in hearing and vision suggest that the brain may use a canonical computation of location: encoding perceived location through population spike rate relative to baseline.

Being able to localize sounds helps us make sense of the world around us. The brain works out sound direction by comparing the times of when sound reaches the left versus the right ear. This cue is known as interaural time difference, or ITD for short. But how exactly the brain decodes this information is still unknown.

The brain contains nerve cells that each show maximum activity in response to one particular ITD. One idea is that these nerve cells are arranged in the brain like a map from left to right, and that the brain then uses this map to estimate sound direction. This is known as the Jeffress model, after the scientist who first proposed it. There is some evidence that birds and alligators actually use a system like this to localize sounds, but no such map of nerve cells has yet been identified in mammals. An alternative possibility is that the brain compares activity across groups of ITD-sensitive nerve cells. One of the oldest and simplest ways to measure this is to compare nerve activity in the left and right hemispheres of the brain. This readout is known as the hemispheric difference model.

By analyzing data from published studies, Ihlefeld, Alamatsaz, and Shapley discovered that these two models make opposing predictions about the effects of volume. The Jeffress model predicts that the volume of a sound will not affect a person’s ability to localize it. By contrast, the hemispheric difference model predicts that very soft sounds will lead to systematic errors, so that for the same ITD, softer sounds are perceived closer towards the front than louder sounds. To investigate this further, Ihlefeld, Alamatsaz, and Shapley asked healthy volunteers to localize sounds of different volumes. The volunteers tended to mis-localize quieter sounds, believing them to be closer to the body’s midline than they actually were, which is inconsistent with the predictions of the Jeffress model.

These new findings also reveal key parallels to processing in the visual system. Visual areas of the brain estimate how far away an object is by comparing the input that reaches the two eyes. But these estimates are also systematically less accurate for low-contrast stimuli than for high-contrast ones, just as sound localization is less accurate for softer sounds than for louder ones. The idea that the brain uses the same basic strategy to localize both sights and sounds generates a number of predictions for future studies to test.

In Memoriam: David C. Gadsby, PhD

Andersen et al. commemorate the life of the eminent physiologist, David Gadsby.

Cortical Double-Opponent Cells in Color Perception: Perceptual Scaling and Chromatic Visual Evoked Potentials

In the early visual cortex V1, there are currently only two known neural substrates for color perception: single-opponent and double-opponent cells. Our aim was to explore the relative contributions of these neurons to color perception. We measured the perceptual scaling of color saturation for equiluminant color checkerboard patterns (designed to stimulate double-opponent neurons preferentially) and uniformly colored squares (designed to stimulate only single-opponent neurons) at several cone contrasts. The spatially integrative responses of single-opponent neurons would produce the same response magnitude for checkerboards as for uniform squares of the same space-averaged cone contrast. However, perceived saturation of color checkerboards was higher than for the corresponding squares. The perceptual results therefore imply that double-opponent cells are involved in color perception of patterns. We also measured the chromatic visual evoked potential (cVEP) produced by the same stimuli; checkerboard cVEPs were much larger than those for corresponding squares, implying that double-opponent cells also contribute to the cVEP response. The total Fourier power of the cVEP grew sublinearly with cone contrast. However, the 6-Hz Fourier component's power grew linearly with contrast-like saturation perception. This may also indicate that cortical coding of color depends on response dynamics.

Nonlinear dynamics of cortical responses to color in the human cVEP

The main finding of this paper is that the human visual cortex responds in a very nonlinear manner to the color contrast of pure color patterns. We examined human cortical responses to color checkerboard patterns at many color contrasts, measuring the chromatic visual evoked potential (cVEP) with a dense electrode array. Cortical topography of the cVEPs showed that they were localized near the posterior electrode at position Oz, indicating that the primary cortex (V1) was the major source of responses. The choice of fine spatial patterns as stimuli caused the cVEP response to be driven by double-opponent neurons in V1. The cVEP waveform revealed nonlinear color signal processing in the V1 cortex. The cVEP time-to-peak decreased and the waveform's shape was markedly narrower with increasing cone contrast. Comparison of the linear dynamics of retinal and lateral geniculate nucleus responses with the nonlinear dynamics of the cortical cVEP indicated that the nonlinear dynamics originated in the V1 cortex. The nature of the nonlinearity is a kind of automatic gain control that adjusts cortical dynamics to be faster when color contrast is greater.

Local circuit inhibition in the cerebral cortex as the source of gain control and untuned suppression

Theoretical considerations have led to the concept that the cerebral cortex is operating in a balanced state in which synaptic excitation is approximately balanced by synaptic inhibition from the local cortical circuit. This paper is about the functional consequences of the balanced state in sensory cortex. One consequence is gain control: there is experimental evidence and theoretical support for the idea that local circuit inhibition acts as a local automatic gain control throughout the cortex. Second, inhibition increases cortical feature selectivity: many studies of different sensory cortical areas have reported that suppressive mechanisms contribute to feature selectivity. Synaptic inhibition from the local microcircuit should be untuned (or broadly tuned) for stimulus features because of the microarchitecture of the cortical microcircuit. Untuned inhibition probably is the source of Untuned Suppression that enhances feature selectivity. We studied inhibition's function in our experiments, guided by a neuronal network model, on orientation selectivity in the primary visual cortex, V1, of the Macaque monkey. Our results revealed that Untuned Suppression, generated by local circuit inhibition, is crucial for the generation of highly orientation-selective cells in V1 cortex.

Spatial distributions of cone inputs to cells of the parvocellular pathway investigated with cone-isolating gratings

Receptive fields of midget ganglion cells and parvocellular lateral geniculate nucleus (LGN) neurons show color-opponent responses because they receive antagonistic input from the middle- and long-wavelength sensitive cones. It has been controversial as to whether this opponency can derive from random connectivity; if receptive field centers of cells near the fovea are cone-specific due to midget morphology, this would confer some degree of color opponency even with random cone input to the surround. A simple test of this mixed surround hypothesis is to compare spatial frequency tuning curves for luminance gratings and gratings isolating cone input to the receptive field center. If tuning curves for luminance gratings were bandpass, then with the mixed surround hypothesis tuning curves for gratings isolating the receptive field center cone class should also be bandpass, but to a lesser extent than for luminance. Tuning curves for luminance, chromatic, and cone-isolating gratings were measured in macaque retinal ganglion cells and LGN cells. We defined and measured a bandpass index to compare luminance and center cone-isolating tuning curves. Midget retinal ganglion cells and parvocellular LGN cells had bandpass indices between 0.1 and 1 with luminance gratings, but the index was usually near 1 (meaning low-pass tuning) when the receptive field center cone class alone was modulated. This is strong evidence for a considerable degree of cone-specific input to the surround. A fraction of midget and parvocellular cells showed evidence of incomplete specificity. Fitting the data with receptive field models revealed considerable intercell variability, with indications in some cells of a more complex receptive structure than a simple difference of Gaussians model.

Linearity and non-linearity in cortical receptive fields

Visual neurons in striate (V1) cortex have been studied as feature detectors or as spatiotemporal filters. A useful way to distinguish between these two conceptual approaches is by studying the way in which visual signals are pooled across space and time. Many neurons in layer IV of striate cortex exhibit linear spatial summation and their response time course is consistent with linear temporal summation. Neurons in supragranular and infragranular layers sum signals in a non-linear manner. A particularly important non-linearity seen in many cortical complex cells is non-linear summation along an axis parallel to their preferred orientation. This leads to responsiveness to 'illusory contours', borders defined by texture differences only. These and other results on non-linear summation of chromatic and achromatic signals imply that V1 cortex performs sophisticated and complex image processing and is not simply an array of spatiotemporal filters.

A dynamic nonlinearity and spatial phase specificity in macaque V1 neurons

While studying the visual response dynamics of neurons in the macaque primary visual cortex (V1), we found a nonlinearity of temporal response that influences the visual functions of V1 neurons. Simple cells were recorded in all layers of V1; the nonlinearity was strongest in neurons located in layer 2/3. We recorded the spike responses to optimal sinusoidal gratings that were displayed for 100 ms, a temporal step response. The step responses were measured at many spatial phases of the grating stimulus. To judge whether simple cell behavior was consistent with linear temporal integration, the decay of the 100 ms step response at the preferred spatial phase was used to predict the step response at the opposite spatial phase. Responses in layers 4B and 4C were mostly consistent with a linear-plus-static-nonlinearity cascade model. However, this was not true in layer 2/3 where most cells had little or no step responses at the opposite spatial phase. Many layer 2/3 cells had transient preferred-phase responses but did not respond at the offset of the opposite-phase stimuli, indicating a dynamic nonlinearity. A different stimulus sequence, rapidly presented random sinusoids, also produced the same effect, with layer 2/3 simple cells exhibiting elevated spike rates in response to stimuli at one spatial phase but not 180 degrees away. The presence of a dynamic nonlinearity in the responses of V1 simple cells indicates that first-order analyses often capture only a fraction of neuronal behavior. The visual implication of our results is that simple cells in layer 2/3 are spatial phase-sensitive detectors that respond to contrast boundaries of one sign but not the opposite.

Effect of Stimulus Size on the Dynamics of Orientation Selectivity in Macaque V1

Previous research has established that orientation selectivity depends to a great extent on suppressive mechanisms in the visual cortex. In this study, we investigated the spatial organization and the time-course of these mechanisms. Stimuli were presented in circular windows of “optimal” and “large” radii. The two stimulus sizes were chosen based on an area-response function measured with drifting gratings at high contrast. The “optimal” size was defined as the smallest radius that elicited the peak response (average value of 0.45°), whereas “large” was defined as two to five times the optimal size. We found that the peak amplitude of tuned enhancement and untuned suppression varied <10% on average with stimulus radius, indicating that they are mainly concentrated in the classical receptive field. However, tuned suppression—in those cells that showed it—was significantly stronger with large stimuli, indicating that this component has a contribution from beyond the classical receptive field. These results imply that spatial context (in large stimuli) enhances orientation selectivity by increasing tuned suppression. We also characterized the time evolution of enhancement, of untuned suppression, and of tuned suppression. The time-course of tuned suppression was markedly slower in time-to-peak and longer in its persistence than untuned suppression. Therefore tuned suppression is likely to be generated by long-range recurrent connections or cortico-cortical feedback, whereas untuned suppression is mainly generated locally in V1.

Differences in real and illusory shape perception revealed by backward masking

Illusory contours (ICs) are thought to be a result of processes involved in the perceptual recovery of occluded surfaces. Here, we investigate the relationship between real and illusory contour perception using a shape discrimination task and backward masking paradigm. ICs can mask other ICs when times between mask onset and stimulus onset, or SOAs, are very long ( approximately 300 ms), but real contours (RCs) are not similarly effective. Masking is absent for RC masks at perceptually salient contrasts, as well as for those with contrast lowered to match the perceived brightness of the illusory surface. We also find that RCs are not masked at long SOAs, either by ICs or by other RCs. Finally, the masking seen between ICs can occur for different sizes of target and mask. The cross-size masking would not be expected if the masking were at a level sensitive to retinal contour location. The late masking therefore may be related to a higher level of processing of shape categories and surfaces, the level at which shapes defined by ICs and RCs are differentially represented.

Information tuning of populations of neurons in primary visual cortex

Neurons in macaque primary visual cortex (V1) show a diversity of orientation tuning properties, exhibiting a broad distribution of tuning width, baseline activity, peak response, and circular variance (CV). Here, we studied how the different tuning features affect the performance of these cells in discriminating between stimuli with different orientations. Previous studies of the orientation discrimination power of neurons in V1 focused on resolving two nearby orientations close to the psychophysical threshold of orientation discrimination. Here, we developed a theoretical framework, the information tuning curve, that measures the discrimination power of cells as a function of the orientation difference, deltatheta, of the two stimuli. This tuning curve also represents the mutual information between the neuronal responses and the stimulus orientation. We studied theoretically the dependence of the information tuning curve on the orientation tuning width, baseline, and peak responses. Of main interest is the finding that narrow orientation tuning is not necessarily optimal for all angular discrimination tasks. Instead, the optimal tuning width depends linearly on deltatheta. We applied our theory to study the discrimination performance of a population of 490 neurons in macaque V1. We found that a significant fraction of the neuronal population exhibits favorable tuning properties for large deltatheta. We also studied how the discrimination capability of neurons is distributed and compared several other measures of the orientation tuning such as CV with Chernoff distances for normalized tuning curves.

Effects of contrast and size on orientation discrimination

Motivated by the recent physiological finding that a neuron's receptive field can increase in size by a factor of 2-4-fold at low contrast [Nat. Neurosci. 2 (1999) 733, Proc. Natl. Acad. Sci. USA 96 (1999) 12073], we sought to examine whether a psychophysical task might reflect the contrast dependent changes in the size/structure of a receptive field. We postulate that since spatial summation is not contrast invariant, a task that relies on the spatial structure of a receptive field, such as orientation discrimination, should also be affected by changes in contrast. Previously, orientation discrimination thresholds have been reported to be roughly independent of the contrast of a stimulus for most of the visible range of contrasts [i.e. J. Neurophysiol. 57 (1987) 773, J. Opt. Soc. Am. 6 (1989) 713, Vis. Res. 30 (1990) 449, Vis. Res. 39 (1999) 1631]. Here, we found large improvements in orientation discrimination with contrast that were dependent on stimulus area. Furthermore, the apparent constancy of orientation discrimination for large area stimuli is possibly a result of a floor effect on the threshold. Therefore we conclude that there is not strong evidence for contrast invariant orientation discrimination. We interpret these results in the context of recent neurophysiological results about the expansion of cortical cells' receptive fields at low contrast.

A psychophysical correlate of contrast dependent changes in receptive field properties

Recent physiological investigations have demonstrated that a neuron's area of spatial summation can vary depending on stimulus contrast. Specifically, when the same stimulus is presented to a neuron at a low contrast, the area of summation (or neuron's receptive field) can increase by at least a factor of two, compared to that estimated with a high contrast stimulus. We sought to examine this phenomenon psychophysically by using an orientation discrimination task carried out in the presence of contextual stimuli. We have found previously that orientation discrimination thresholds for a sine-wave grating are elevated by the presence of a surround pattern of similar orientation (with an offset) and spatial frequency. However, when these patterns were separated by a gap of mean luminance exceeding roughly 1 deg, thresholds dropped to the level measured using the center pattern alone. Here, we examined the surround pattern's effect on orientation thresholds as a function of the contrast of the center and surround. We find that when both are presented at a low contrast, the detrimental influence of the surround on orientation thresholds is maintained over larger gap separations. We also find that the spatial frequency and orientation selectivity of the surround's masking effect on orientation thresholds is broader at low contrast than at high contrast. Although the results support the idea of a spatial reorganization of the mechanisms involved in the task at low contrast, these changes are insufficient, in and of themselves, to account for the data. We suggest that additional influences possibly reflecting image segmentation also affect performance.

Suppression of neural responses to nonoptimal stimuli correlates with tuning selectivity in macaque V1

Neural responses in primary visual cortex (area V1) are selective for the orientation and spatial frequency of luminance-modulated sinusoidal gratings. Selectivity could arise from enhancement of the cell's response by preferred stimuli, suppression by nonoptimal stimuli, or both. Here, we report that the majority of V1 neurons do not only elevate their activity in response to preferred stimuli, but their firing rates are also suppressed by nonoptimal stimuli. The magnitude of suppression is similar to that of enhancement. There is a tendency for net response suppression to peak at orientations near orthogonal to the optimal for the cell, but cases where suppression peaks at oblique orientations are observed as well. Interestingly, selectivity and suppression correlate in V1: orientation and spatial frequency selectivity are higher for neurons that are suppressed by nonoptimal stimuli than for cells that are not. This finding is consistent with the idea that suppression plays an important role in the generation of sharp cortical selectivity. We show that nonlinear suppression is required to account for the data. However, the precise structure of the neural circuitry generating the suppressive signal remains unresolved. Our results are consistent with both feedback and (nonlinear) feed-forward inhibition.

Contextual influences on orientation discrimination: binding local and global cues

We sought to determine how local and global features within an image interact by examining whether orientation discrimination thresholds could be modified by contextual information. In particular, we investigated how local orientation signals within an image are pooled together, and whether this pooling process is dependent on the global orientation content present in the image. We find that observers' orientation judgments depend on surround contextual information, with performance being optimal when the center and surround stimuli are clearly distinct. In cases where the center and surround were not clearly segregated, we report two sets of results. If there was an ambiguity regarding the perception of a global structure (i.e. a small mismatch between local cues), observers' performance was impaired. If there was no mismatch and local and global cues were consistent with the perception of a single surface, observers performed as well as in the distinct surfaces case. Although some of our results can be largely accounted for by interactions between differently oriented filters, other aspects are more difficult to reconcile with this explanation. We suggest that low level filtering constrains observers' performance, and that influences arising from image segmentation modify how local orientation signals are pooled together.

The relatively small decline in orientation acuity as stimulus size decreases

Orientation acuity was measured with circular patches of sinusoidal gratings of various sizes. Threshold estimates were lowest (acuity highest) for the largest size patch, and increased as the stimulus size was reduced, consistent with the results of many researchers using line stimuli. These results are compared with the predictions of a simple and widely accepted model of spatial vision whereby the output of independent feed-forward filters are combined to produce threshold estimates. Specifically, the rectified output of a number of independent filters (i.e. Gabors) spanning the stimulus space (i.e. orientation) are combined via Bayesian decision theory. This model cannot account quantitatively for the relatively low thresholds estimated for the small sized stimuli when compared to the thresholds measured with larger patches. Application of a comparable analysis, with preliminary measurements of neuronal responses from primary visual cortex replacing the response rectified Gabor filter's responses, provides a more reasonable account of behavioral acuity. This indicates a fundamental inadequacy of the feed-forward filter model in accounting for V1 neurons' role in perception.

Visual function and brain organization in non-decussating retinal-fugal fibre syndrome

Functional neuroimaging, psychophysical and electrophysiological investigations were performed in a patient with non-decussating retinal-fugal fibre syndrome, an inborn achiasmatic state in which the retinal projections of each eye map entirely to the ipsilateral primary visual cortex. Functional magnetic resonance imaging (fMRI) studies showed that for monocularly presented simple visual stimuli, only the ipsilateral striate cortex was activated. Within each hemisphere's striate cortex, the representation of the two hemifields overlapped extensively. Despite this gross miswiring, visual functions that require precise geometrical information (such as vernier acuity) were normal, and there was no evidence for the confounding of visual information between the overlapping ipsi-lateral and contralateral representations. Contrast sensitivity and velocity judgments were abnormal, but their dependence on the orientation and velocity of the targets suggests that this deficit was due to ocular instabilities, rather than the miswiring per se. There were no asymmetries in performance observed in visual search, visual naming or illusory contour perception. fMRI analysis of the latter two tasks under monocular viewing conditions indicated extensive bilateral activation of striate and prestriate areas. Thus, the remarkably normal visual behavior achieved by this patient is a result of both the plasticity of visual pathways, and efficient transfer of information between the hemispheres.

Illusory contour perception and amodal boundary completion: evidence of a dissociation following callosotomy

A fundamental problem in form perception is how the visual system can link together spatially separated contour fragments to form the percept of a unitary shape. Illusory contours and amodal completion are two phenomena that demonstrate this linking process. In the present study we investigate these phenomena in the divided hemispheres of two callosotomy ("split-brain") patients. The data suggest that dissociable neural mechanisms are responsible for the generation of illusory contours and amodal completion. Although both cerebral hemispheres appear to be equally capable of perceiving illusory contours, amodal completion is more readily utilized by the right hemisphere. These results suggest that illusory contours may be attributable to low-level visual processes common to both hemispheres, whereas amodal completion reflects a higher-level, lateralized process.

Functional organization of owl monkey lateral geniculate nucleus and visual cortex

The nocturnal, New World owl monkey (Aotus trivirgatus) has a rod-dominated retina containing only a single cone type, supporting only the most rudimentary color vision. However, it does have well-developed magnocellular (M) and parvocellular (P) retinostriate pathways and striate cortical architecture [as defined by the pattern of staining for the activity-dependent marker cytochrome oxidase (CO)] similar to that seen in diurnal primates. We recorded from single neurons in anesthetized, paralyzed owl monkeys using drifting, luminance-modulated sinusoidal gratings, comparing receptive field properties of M and P neurons in the lateral geniculate nucleus and in V1 neurons assigned to CO "blob," "edge," and "interblob" regions and across layers. Tested with achromatic stimuli, the receptive field properties of M and P neurons resembled those reported for other primates. The contrast sensitivity of P cells in the owl monkey was similar to that of P cells in the macaque, but the contrast sensitivities of M cells in the owl monkey were markedly lower than those in the macaque. We found no differences in eye dominance, orientation, or spatial frequency tuning, temporal frequency tuning, or contrast response for V1 neurons assigned to different CO compartments; we did find fewer direction-selective cells in blobs than in other compartments. We noticed laminar differences in some receptive field properties. Cells in the supragranular layers preferred higher spatial and lower temporal frequencies and had lower contrast sensitivity than did cells in the granular and infragranular layers. Our data suggest that the receptive field properties across functional compartments in V1 are quite homogeneous, inconsistent with the notion that CO blobs anatomically segregate signals from different functional "streams."

The use of m-sequences in the analysis of visual neurons: linear receptive field properties

We have used Sutter's (1987) spatiotemporal m-sequence method to map the receptive fields of neurons in the visual system of the cat. The stimulus consisted of a grid of 16 x 16 square regions, each of which was modulated in time by a pseudorandom binary signal, known as an m-sequence. Several strategies for displaying the m-sequence stimulus are presented. The results of the method are illustrated with two examples. For both geniculate neurons and cortical simple cells, the measurement of first-order response properties with the m-sequence method provided a detailed characterization of classical receptive-field structures. First, we measured a spatiotemporal map of both the center and surround of a Y-cell in the lateral geniculate nucleus (LGN). The time courses of the center responses was biphasic: OFF at short latencies, ON at longer latencies. The surround was also biphasic--ON then OFF--but somewhat slower. Second, we mapped the response properties of an area 17 directional simple cell. The response dynamics of the ON and OFF subregions varied considerably; the time to peak ranged over more than a factor of two. This spatiotemporal inseparability is related to the cell's directional selectivity (Reid et al., 1987, 1991; McLean & Palmer, 1989; McLean et al., 1994). The detail with which the time course of response can be measured at many different positions is one of the strengths of the m-sequence method.

Temporal-frequency selectivity in monkey visual cortex

We investigated the dynamics of neurons in the striate cortex (V1) and the lateral geniculate nucleus (LGN) to study the transformation in temporal-frequency tuning between the LGN and V1. Furthermore, we compared the temporal-frequency tuning of simple with that of complex cells and direction-selective cells with nondirection-selective cells, in order to determine whether there are significant differences in temporal-frequency tuning among distinct functional classes of cells within V1. In addition, we compared the cells in the primary input layers of V1 (4a, 4c alpha, and 4c beta) with cells in the layers that are predominantly second and higher order (2, 3, 4b, 5, and 6). We measured temporal-frequency responses to drifting sinusoidal gratings. For LGN neurons and simple cells, we used the amplitude and phase of the fundamental response. For complex cells, the elevation of impulse rate (F0) to a drifting grating was the response measure. There is significant low-pass filtering between the LGN and the input layers of V1 accompanied by a small, 3-ms increase in visual delay. There is further low-pass filtering between V1 input layers and the second- and higher-order neurons in V1. This results in an average decrease in high cutoff temporal-frequency between the LGN and V1 output layers of about 20 Hz and an increase in average visual latency of about 12-14 ms. One of the most salient results is the increased diversity of the dynamic properties seen in V1 when compared to the cells of the lateral geniculate, possibly reflecting specialization of function among cells in V1. Simple and complex cells had distributions of temporal-frequency tuning properties that were similar to each other. Direction-selective and nondirection-selective cells had similar preferred and high cutoff temporal frequencies, but direction-selective cells were almost exclusively band-pass while nondirection-selective cells distributed equally between band-pass and low-pass categories. Integration time, a measure of visual delay, was about 10 ms longer for V1 than LGN. In V1 there was a relatively broad distribution of integration times from 40-80 ms for simple cells and 60-100 ms for complex cells while in the LGN the distribution was narrower.

On temporal codes and the spatiotemporal response of neurons in the lateral geniculate nucleus

1. The present work relates recent experimental studies of the temporal coding of visual stimuli (McClurkin, Optican, Richmond, and Gawne, Science 253: 675, 1991) to the measurements of the spatiotemporal receptive fields of neurons within the lateral geniculate of primate. 2. We analyze both new and previously described magnocellular and parvocellular single units. The spatiotemporal impulse response function of the unit, defined as the time-resolved average firing rate in response to a weak stimulus flashed at a given location and time, is characterized by the singular value decomposition. This analysis allows one to represent the impulse response by a small number, two to three, of spatial and temporal modes. Both magnocellular and parvocellular units are weakly nonseparable, with major and minor modes that account, respectively, for approximately 78 and 22% of the response. The major temporal mode for both types is essentially identical for the first 100 ms. At later times the response of magnocellular units changes sign and decays slowly, whereas the response of parvocellular units decays relatively rapidly. 3. The spatiotemporal impulse response function completely determines the response of a unit to an arbitrary stimulus when linear response theory is valid. Using the measured impulse response, combined with a rectifying neuronal input-output relation, we calculate the responses to a complete set of spatial luminance patterns constructed of "Walsh" functions. Our predicted temporal responses are in qualitative agreement with those reported for parvocellular units (McClurkin, Optican, Richmond, and Gawne, J. Neurophysiol. 66: 794, 1991). Under the additional assumptions of Poisson statistics for the probability of spiking and a plausible background firing rate, we predict the performance of a unit in the Walsh pattern discrimination task as quantified by mutual information. Our prediction is again consistent with the reported results. 4. Last, we consider the issue of temporal coding within linear response. For stimuli presented for fixed time intervals, the singular value decomposition provides a natural relation between the temporal modes of the neuronal response and the spatial pattern of the stimulus. Although it is tempting to interpret each temporal mode as an independent channel that encodes orthogonal features of the stimulus, successively higher order modes are increasingly unreliable and do not significantly increase the discrimination capabilities of the unit.

Macaque V1 neurons can signal 'illusory' contours

We describe here a new view of primary visual cortex (V1) based on measurements of neural responses in V1 to patterns called 'illusory contours' (Fig. 1a, b). Detection of an object's boundary contours is a fundamental visual task. Boundary contours are defined by discontinuities not only in luminance and colour, but also in texture, disparity and motion. Two theoretical approaches can account for illusory contour perception. The cognitive approach emphasizes top-down processes. An alternative emphasizes bottom-up processing. This latter view is supported by (1) stimulus constraints for illusory contour perception and (2) the discovery by von der Heydt and Peterhans of neurons in extrastriate visual area V2 (but not in V1) of macaque monkeys that respond to illusory contours. Using stimuli different from those used previously, we found illusory contour responses in about half the neurons studied in V1 of macaque monkeys. Therefore, there are neurons as early as V1 with the computational power to detect illusory contours and to help distinguish figure from ground.

Broadband temporal stimuli decrease the integration time of neurons in cat striate cortex

We have studied the responses of striate cortical neurons to stimuli whose contrast is modulated in time by either a single sinusoid or by the sum of eight sinusoids. The sum-of-sinusoids stimulus resembles white noise and has been used to study the linear and nonlinear dynamics of retinal ganglion cells (Victor et al., 1977). In cortical neurons, we have found different linear and second-order responses to single-sinusoid and sum-of-sinusoids inputs. Specifically, while the responsivity near the optimal temporal frequency is lower for the sum-of-sinusoids stimulus, the responsivity at higher temporal frequencies is relatively greater. Along with this change in the response amplitudes, there is a systematic change in the time course of responses. For complex cells, the integration time, the effective delay due to a combination of actual delays and low-pass filter stages, changes from a median of 85 ms with single sinusoids to 57 ms with a sum of sinusoids. For simple cells, the integration times for single sinusoids range from 44-100 ms, but cluster tightly around 40 ms for the sum-of-sinusoids stimulus. The change in time constant would argue that the increased sensitivity to high frequencies cannot be explained by a static threshold, but must be caused by a fundamental alteration in the response dynamics. These effects are not seen in the retina (Shapley & Victor, 1981) and are most likely cortical in origin.

Spatial structure of cone inputs to receptive fields in primate lateral geniculate nucleus

Human colour vision depends on three classes of cone photoreceptors, those sensitive to short (S), medium (M) or long (L) wavelengths, and on how signals from these cones are combined by neurons in the retina and brain. Macaque monkey colour vision is similar to human, and the receptive fields of macaque visual neurons have been used as an animal model of human colour processing. P retinal ganglion cells and parvocellular neurons are colour-selective neurons in macaque retina and lateral geniculate nucleus. Interactions between cone signals feeding into these neurons are still unclear. On the basis of experimental results with chromatic adaptation, excitatory and inhibitory inputs from L and M cones onto P cells (and parvocellular neurons) were thought to be quite specific (Fig. 1a). But these experiments with spatially diffuse adaptation did not rule out the 'mixed-surround' hypothesis: that there might be one cone-specific mechanism, the receptive field centre, and a surround mechanism connected to all cone types indiscriminately (Fig. 1e). Recent work has tended to support the mixed-surround hypothesis. We report here the development of new stimuli to measure spatial maps of the linear L-, M- and S-cone inputs to test the hypothesis definitively. Our measurements contradict the mixed-surround hypothesis and imply cone specificity in both centre and surround.

Directional selectivity and spatiotemporal structure of receptive fields of simple cells in cat striate cortex

1. Simple cells in cat striate cortex were studied with a number of stimulation paradigms to explore the extent to which linear mechanisms determine direction selectivity. For each paradigm, our aim was to predict the selectivity for the direction of moving stimuli given only the responses to stationary stimuli. We have found that the prediction robustly determines the direction and magnitude of the preferred response but overestimates the nonpreferred response. 2. The main paradigm consisted of comparing the responses of simple cells to contrast reversal sinusoidal gratings with their responses to drifting gratings (of the same orientation, contrast, and spatial and temporal frequencies) in both directions of motion. Although it is known that simple cells display spatiotemporally inseparable responses to contrast reversal gratings, this spatiotemporal inseparability is demonstrated here to predict a certain amount of direction selectivity under the assumption that simple cells sum their inputs linearly. 3. The linear prediction of the directional index (DI), a quantitative measure of the degree of direction selectivity, was compared with the measured DI obtained from the responses to drifting gratings. The median value of the ratio of the two was 0.30, indicating that there is a significant nonlinear component to direction selectivity. 4. The absolute magnitudes of the responses to gratings moving in both directions of motion were compared with the linear predictions as well. Whereas the preferred direction response showed only a slight amount of facilitation compared with the linear prediction, there was a significant amount of nonlinear suppression in the nonpreferred direction. 5. Spatiotemporal inseparability was demonstrated also with stationary temporally modulated bars. The time course of response to these bars was different for different positions in the receptive field. The degree of spatiotemporal inseparability measured with sinusoidally modulated bars agreed quantitatively with that measured in experiments with stationary gratings. 6. A linear prediction of the responses to drifting luminance borders was compared with the actual responses. As with the grating experiments, the prediction was qualitatively accurate, giving the correct preferred direction but underestimating the magnitude of direction selectivity observed.(ABSTRACT TRUNCATED AT 400 WORDS)

Gender differences in apparent motion perception

Distance disparity is a strong cue to element correspondence in apparent motion. Using a 2-AFC paradigm we have previously shown that shape similarity also plays a role. We now demonstrate a small gender difference in these effects: women are more sensitive to distance disparity, whereas men are more sensitive to differences in shape. Furthermore, in the competing presence of a shape cue, women's sensitivity to distance decreases while men's sensitivity is unaffected. These observations may be related to putative gender differences in the 'form' and 'motion-spatial relations' cortical pathways.

Fine structure of receptive-field centers of X and Y cells of the cat

We investigated the fine structure of receptive field centers of X and Y cells of the retina and lateral geniculate nucleus of the cat using sinusoidal grating stimuli of high spatial frequency. By measuring orientation tuning and spatial-frequency tuning at multiple orientations, the two-dimensional sensitivity distribution was examined. We found that receptive-field centers typically have multiple sensitivity peaks that can be modeled as several spatially offset subunits. A subunit structure was found in both X and Y cells, with an average number of subunits per receptive-field center of approximately 2.9 in X cells and approximately 4.6 in Y cells. In X cells these subunits may correspond to individual cone bipolar inputs. In Y cells, the subunits may reflect the structure of the dendritic tree. The observation of the subunit structure of the receptive-field center, in conjunction with manipulation of the retinal wiring through pharmacological intervention, may provide a new tool for probing the circuitry of the retina.

Light adaptation in the primate retina: analysis of changes in gain and dynamics of monkey retinal ganglion cells

The responses of monkey retinal ganglion cells to sinusoidal stimuli of various temporal frequencies were measured and analyzed at a number of mean light levels. Temporal modulation tuning functions (TMTFs) were measured at each mean level by varying the drift rate of a sine-wave grating of fixed spatial frequency and contrast. The changes seen in ganglion cell temporal responses with changes in adaptation state were similar to those observed in human subjects and in turtle horizontal cells and cones tested with sinusoidally flickering stimuli; "Weber's Law" behavior was seen at low temporal frequencies but not at higher temporal frequencies. Temporal responses were analyzed in two ways: (1) at each light level, the TMTFs were fit by a model consisting of a cascade of low- and high-pass filters; (2) the family of TMTFs collected over a range of light levels for a given cell was fit by a linear negative feedback model in which the gain of the feedback was proportional to the mean light level. Analysis (1) revealed that the temporal responses of one class of monkey ganglion cells (M cells) were more phasic at both photopic and mesopic light levels than the responses of P ganglion cells. In analysis (2), the linear negative feedback model accounted reasonably well for changes in gain and dynamics seen in three P cells and one M cell. From the feedback model, it was possible to estimate the light level at which the dark-adapted gain of the cone pathways in the primate retina fell by a factor of two. This value was two to three orders of magnitude lower than the value estimated from recordings of isolated monkey cones. Thus, while a model which includes a single stage of negative feedback can account for the changes in gain and dynamics associated with light adaptation in the photopic and mesopic ranges of vision, the underlying physical mechanisms are unknown and may involve elements in the primate retina other than the cone.

Background light and the contrast gain of primate P and M retinal ganglion cells

Retinal ganglion cells projecting to the monkey lateral geniculate nucleus fall into two classes: those projecting to the magnocellular layers of the nucleus (M cells) have a higher contrast gain to luminance patterns at photopic levels of retinal illumination than those projecting to the parvocellular layers (P cells). We report here that this difference in luminance contrast gain between M and P cells is maintained at low levels of mean retinal illumination. In fact, our results suggest that in the mesopic and scotopic ranges of mean illumination, the M-cell/magnocellular pathway is the predominant conveyor of information about spatial contrast to the visual cortex.

Linear mechanisms of directional selectivity in simple cells of cat striate cortex

The role of linear spatial summation in the directional selectivity of simple cells in cat striate cortex was investigated. The experimental paradigm consisted of comparing the response to drifting grating stimuli with linear predictions based on the response to stationary contrast-reversing gratings. The spatial phase dependence of the response to contrast-reversing gratings was consistent with a high degree of linearity of spatial summation within the receptive fields. Furthermore, the preferred direction predicted from the response to stationary gratings generally agreed with the measurements made with drifting gratings. The amount of directional selectivity predicted was, on average, about half the measured value, indicating that nonlinear mechanisms act in concert with linear mechanisms in determining the overall directional selectivity.

Contrast affects the transmission of visual information through the mammalian lateral geniculate nucleus

1. We recorded with one electrode action potentials of single principal cells in the lateral geniculate nucleus (l.g.n.) of cats and monkeys, together with their retinal inputs, recorded as synaptic potentials (S potentials; Bishop, Burke & Davis, 1958; Cleland, Dubin & Levick, 1971; Kaplan & Shapley, 1984). 2. We studied the effect of stimulus contrast on the transmission of visual information from the retina to the l.g.n., compared the spontaneous discharge of l.g.n. cells with that of their retinal inputs, and studied the driven (modulated) and maintained (unmodulated) discharge of l.g.n. neurones and their retinal drives. 3. The spontaneous discharge of l.g.n. cells was considerably lower than that of their retinal drives. 4. The maintained (unmodulated) discharge of l.g.n. cells during stimulation was lower than that of their retinal drives, and was largely unaffected by the stimulus contrast. 5. The responses of both the retinal input and l.g.n. cells increased with contrast, but at different rates: a given increment of contrast caused a larger increment of response in the retinal input than in the l.g.n. target cells. 6. The transmission ratio (l.g.n. response/retinal response) for most cells depended upon the stimulus contrast. This dependence indicates the presence of a non-linear contrast gain control. 7. The amount by which the l.g.n. attenuated the retinal input depended upon the temporal frequency, and, to a lesser extent, upon the spatial frequency of the stimulus. 8. The effect of contrast on signal transmission between the retina and l.g.n. was essentially the same in the macaque monkey as in the cat. 9. The attenuation of the retinal input by the l.g.n. contrast gain control could serve to prevent saturation and extend the dynamic range of cortical units, which probably receive input from several l.g.n. units.

Linear mechanism of orientation tuning in the retina and lateral geniculate nucleus of the cat

1. The orientation tuning of lateral geniculate nucleus (LGN) neurons and retinal ganglion cells (recorded as S potentials in the LGN) was investigated with drifting grating stimuli. 2. Results were compared with a quantitative model, in which receptive fields were constructed from linear, elliptical Gaussian center and surround subunits, and responses could be predicted to gratings of any spatial frequency at any orientation. 3. The orientation tuning of X and Y retinal ganglion cells and LGN neurons was shown to result from the linear mechanism of receptive-field elongation, as data from these cells could be well fit with this model. 4. The responses of LGN neurons and their input retinal ganglion cells were compared. The orientation tuning of LGN neurons was found to be a reflection of the tuning of their retinal inputs, showing that neither intrageniculate neural interactions nor the corticogeniculate projection play any role in LGN orientation selectivity.

The primate retina contains two types of ganglion cells, with high and low contrast sensitivity

Previously, we discovered that the broadband cells in the two magnocellular (large cell) layers of the monkey lateral geniculate nucleus (LGN) are much more sensitive to luminance contrast than are the color-sensitive cells in the four parvocellular (small cell) layers. We now report that this large difference in contrast sensitivity is due not to LGN circuitry but to differences in sensitivity of the retinal ganglion cells that provide excitatory synaptic input to the LGN neurons. This means that the parallel analysis of color and luminance in the visual scene begins in the retina, probably at a retinal site distal to the ganglion cells.

Retinal light adaptation--evidence for a feedback mechanism

Light adaptation is the adjustment of retinal response properties to variations in ambient illumination. It enables the encoding of visual information over a millionfold intensity range, from moonlight to broad daylight, despite the relatively small dynamic range of response of visual neurones. We have studied the effects of light adaptation on the dynamics and sensitivity of visual responses of neurones in the turtle retina, by measuring the responses of horizontal cells in the retina to light which was modulated with a sinusoidal time course around various mean levels. As a quantitative measure of the transduction from light to neural signals, we calculated the gain of response at each frequency. Gain is defined as the amplitude of the modulated response component divided by the amplitude of light modulation. We report here that the gain (mV photon-1) at low temporal frequencies decreased as the mean light level increased. Over a 2 log-unit range of mean light levels, low-frequency gain was inversely proportional to the mean light level, as in Weber's law. However, at high temporal frequencies, the gain was almost independent of mean light level. Our results are reminiscent of Kelly's results on human temporal-frequency sensitivity in various states of light adaptation. We found that a family of horizontal-cell temporal frequency responses, measured at various mean light levels, could be accounted for by a negative feedback model in which the feedback strength is proportional to mean light level.

X and Y cells in the lateral geniculate nucleus of macaque monkeys

1. Cells of the lateral geniculate nucleus (l.g.n.) in macaque monkeys were sorted into two functional groups on the basis of spatial summation of visually evoked neural signals. 2. Cells were called X cells if their responses to contrast reversal of fine sine gratings were at the fundamental temporal modulation frequency with null positions one quarter of a cycle away from positions for peak response. Cells were called Y cells if their responses to such stimuli were at twice the modulation frequency and were approximately independent of spatial phase. 3. Ninety-nine percent of the cells in the four dorsal parvocellular layers of the l.g.n. were X cells; about seventy-five percent of the cells in the two ventral magnocellular layers were also X cells. The remainder were Y cells. 4. We confirmed previous findings that magnocellular cells had a shorter latency of response to electrical stimulation of the optic chiasm. 5. Magnocellular cells had much higher contrast sensitivities than did parvocellular cells. 6. Therefore, two distinct classes of X cells exist in the macaque l.g.n.: parvocellular X cells and magnocellular X cells. The great difference in their properties suggests that they have different functions in vision. The Y cells in the magnocellular layers form a third functional group with spatial properties distinctly different from the X cells. 7. We propose that the magnocellular layers of the macaque monkey's l.g.n. may be homologous to the A and A1 layers of the cat's l.g.n.

How the contrast gain control modifies the frequency responses of cat retinal ganglion cells

1. A model is proposed for the effect of contrast on the first-order frequency responses of cat retinal ganglion cells. The model consists of several cascaded low pass filters ('leaky integrators') followed by a single stage of negative feed-back. 2. Values of time constants and gain of the components in this model were chosen to approximate (with least-squared deviation) experimentally measured first-order frequency responses. In the experiments used for the analysis, the visual stimulus was a sine grating modulated by a sum of sinusoids. 3. For both X cells and Y cells, the over-all gain and the time constants of the cascade of low pass filters were insensitive to contrast. 4. In all cells, the gain-bandwidth product of the negative feed-back loop was markedly increased with increasing contrast. 5. The effect of stimulation in the periphery of the receptive fields on the first-order frequency response to a centrally placed spot was identical to the effect of increasing contrast in the grating experiments. In all cases, the gain-bandwidth product of the negative feed-back loop was the only model parameter affected by peripheral stimulation. 6. A similar effect of non-linear summation was investigated for two bars located in the receptive field periphery. 7. This analysis of the contrast gain control mechanism is compared with other models of retinal function.

The effect of contrast on the non-linear response of the Y cell

1. Second-order frequency responses were obtained from cat retinal ganglion cells of the Y type. The cells were stimulated by a spatial sine grating whose contrast was modulated in time by a sum of eight sinusoids. 2. Second-order frequency responses obtained at higher contrasts have a peak amplitude at higher input temporal frequency, and phase shifts, compared to their low-contrast counterparts. 3. This change in shape of the second-order frequency response is a departure from the prediction of the linear/static non-linear/linear sandwich model of the non-linear pathway in the cat retina. The departure is analysed by means of the hypothesis that the two filters of the sandwich model are parametric in contrast. 4. Most of the change in shape of the second-order frequency response with contrast is accounted for in terms of the sandwich model by changes in the transfer characteristics of the filter preceding the static non-linearity. 5. The effect of contrast on the second-order responses of Y cells is qualitatively similar in several ways to the effect of contrast on first-order responses. This suggests that the contrast gain control mechanism acts early in the retina, before linear and non-linear pathways have diverged.

The nonlinear pathway of Y ganglion cells in the cat retina

Retinal ganglion cells of the Y type in the cat retina produce two different types of response: linear and nonlinear. The nonlinear responses are generated by a separate and independent nonlinear pathway. The functional connectivity in this pathway is analyzed here by comparing the observed second-order frequency responses of Y cells with predictions of a "sandwich model" in which a static nonlinear stage is sandwiched between two linear filters. The model agrees well with the qualitative and quantitative features of the second-order responses. The prefilter in the model may well be the bipolar cells and the nonlinearity and postfilter in the model are probably associated with amacrine cells.

Receptive field mechanisms of cat X and Y retinal ganglion cells

We investigated receptive field properties of cat retinal ganglion cells with visual stimuli which were sinusoidal spatial gratings amplitude modulated in time by a sum of sinusoids. Neural responses were analyzed into the Fourier components at the input frequencies and the components at sum and difference frequencies. The first-order frequency response of X cells had a marked spatial phase and spatial frequency dependence which could be explained in terms of linear interactions between center and surround mechanisms in the receptive field. The second-order frequency response of X cells was much smaller than the first-order frequency response at all spatial frequencies. The spatial phase and spatial frequency dependence of the first-order frequency response in Y cells in some ways resembled that of X cells. However, the Y first-order response declined to zero at a much lower spatial frequency than in X cells. Furthermore, the second-order frequency response was larger in Y cells; the second-order frequency components became the dominant part of the response for patterns of high spatial frequency. This implies that the receptive field center and surround mechanisms are physiologically quite different in Y cells from those in X cells, and that the Y cells also receive excitatory drive from an additional nonlinear receptive field mechanism.

Nonlinear spatial summation and the contrast gain control of cat retinal ganglion cells

1. We studied how responses to visual stimuli at spatially separated locations were combined by cat retinal ganglion cells. 2. The temporal signal which modulated the stimuli was a sum of sinusoids. Fourier analysis of the ganglion cell impulse train yielded first order responses at the modulation frequencies, and second order responses at sums and differences of the input frequencies. 3. Spatial stimuli were spots in the centre and periphery of the cell's receptive field. Four conditions of stimulation were used: centre alone, periphery alone, centre and periphery in phase, centre and periphery out of phase. 4. The effective first order response of the centre was defined as the response due to centre stimulation in the presence of periphery stimulation, but independent of the relative phases of the two regions. Likewise, the effective first order response of the periphery was defined as the response due to periphery in the presence of centre stimulation, but independent of the relative phases of the two regions. These effective responses may be calculated by addition and subtraction of the measured responses to the combined stimuli. 5. There was a consistent difference between the first order frequency kernal of the effective centre and the first order kernel of the centre alone. The amplitudes of the effective centre responses were diminished at low frequencies of modulation compared to the isolated centre responses. Also, the phase of the effective centre's response to high frequencies was advanced. Such non-linear interaction occurred in all ganglion cells, X or Y, but the effects were larger in Y cells. 6. In addition to spatially uniform stimuli in the periphery, spatial grating patterns were also used. These peripheral gratings affected the first order kernal of the centre even though the peripheral gratings produced no first order responses by themselves. 7. The temporal properties of the non-linear interaction of centre and periphery were probed by modulation in the periphery with single sinusoids. The most effective temporal frequencies for producing non-linear summation were: (a) 4-15 Hz when all the visual stimuli were spatially uniform, (b) 2-8 Hz when spatial grating patterns were used in the periphery. 8. The characteristics of non-linear spatial summation observed in these experiments are explained by the properties of the contrast gain control mechanism which we have previously postulated.

The effect of contrast on the transfer properties of cat retinal ganglion cells

1. Variation in stimulus contrast produces a marked effect on the dynamics of the cat retina. This contrast effect was investigated by measurement of the responses of X and Y ganglion cells. The stimuli were sine gratings or rectangular spots modulated by a temporal signal which was a sum of sinusoids. Fourier analysis of the neural response to such a stimulus allowed us to calculate first order and second order frequency kernels. 2. The first order frequency kernel of both X and Y ganglion cells became more sharply tuned at higher contrasts. The peak amplitude also shifted to higher temporal frequency at higher contrasts. Responses to low frequencies of modulation (less than 1 Hz) grew less than proportionally with contrast. However, response amplitudes at higher modulation frequencies (greater than 4 Hz) scaled approximately proportionally with contrast. Also, there was a marked phase advance in these latter components as contrast increased. 3. The contrast effect was significantly larger for Y cells than for X cells. 4. The first order frequency kernel was measured with single sine waves as well as with the sum of sinusoids as a modulation signal. The transfer function measured in this way was much less affected by increases in contrast. This implied that stimulus energy at one temporal frequency could affect the response amplitude and phase shift at another temporal frequency. 5. Direct proof was found that modulation at one frequency modifies the response at other frequencies. This was demonstrated by perturbation experiments in which the modulation stimulus was the sum of one strong perturbing sinusoid and seven weak test sinusoids. 6. The shape of the graph of the amplitude of the first order frequency kernel vs. temporal frequency did not depend on the amplitudes of the first order components, but rather on local retinal contrast. This was shown in an experiment with a sine grating placed at different positions in the visual field. The shape of the first order kernel did not vary with spatial phase, while the magnitudes of the first order responses varied greatly with spatial phase. 7. Models for the contrast gain control mechanism are considered in the Discussion.

The eel retina. Receptor classes and spectral mechanisms

Light and electron microscopy revealed that there are both rods and cones in the retina of the eel Anguilla rostrata. The rods predominate with a rod to cone ratio of 150:1. The spectral sensitivity of the dark-adapted eyecup ERG had a peak at about 520 nm and was well fit by a vitamin A2 nomogram pigment with a lambdamax = 520 nm. This agrees with the eel photopigment measurements of other investigators. This result implies that a single spectral mechanism--the rods--provides the input for the dark-adapted ERG. The spectral sensitivity of the ERG to flicker in the light-adapted eyecup preparation was shifted to longer wavelengths; it peaked at around 550 nm. However, there was evidence that this technique might not have completely eliminated rod intrusion. Rod responses were abolished in a bleached isolated retina preparation, in which it was shown that there were two classes of cone-like mechanisms, one with lambdamax of 550 nm and the other with lambdamax of less than 450 nm. Ganglion cell recording provided preliminary evidence for opponent-color processing. Horizontal cells were only of the L type with both rod and cone inputs.

The eel retina. Ganglion cell classes and spatial mechanisms

We have been able to separate optic fibers in the eye of the eel Anguilla rostrata into two distinct classes on the basis of spatial summation properties. X fibers, the first class, are like X ganglion cells in the cat: they have null positions for contrast reversal sine gratings; they respond at the modulation frequency; and many have a strong surround mechanism. X fibers, the second class, respond with an "on-off" response to local stimulation, to diffuse light modulation, to coarse drifting gratings, and to contrast reversal gratings. We have put forward a model for the receptive field of X fibers which involves two subunits, with rectification before the subunits add their signals. This model accounts for many of the quirks of X fibers.

Nonlinear analysis of cat retinal ganglion cells in the frequency domain

We have analyzed the responses of cat retinal ganglion cells to luminosity gratings that are modulated in time by a sum of sinusoids. A judicious choice of the component temporal frequencies permits a separation of the linear and second-order nonlinear components. Y cell responses show harmonic generation and intermodulation distortion over a wide frequency range. These nonlinear components predominate over the linear components for certain types of spatial stimuli. Nonlinear components in X cells are greatly diminished in comparison. The character of the nonlinear responses provides strong constraints on prospective models for the nonlinear pathway of the Y cell.