Neural responses in the primary visual cortex of the monkey during perceptual filling-in at the blind spot

The phenomenon of perceptual filling-in demonstrates that physical stimuli presented on the retina do not necessarily correspond to surface perception, and that our visual system has mechanisms with which to interpolate missing information in order to construct continuous surfaces. Among its various forms, filling-in at the blind spot is one of the most remarkable. To study the neural mechanisms involved in filling-in at the blind spot, we recently conducted a recording experiment aimed at determining whether the neurons in the primary visual cortex (V1) that represent the visual field corresponding to the blind spot are activated when filling-in occurs. We found that neurons located in deep layers of the V1, particularly layer 6, respond to large stimuli that cover the blind spot and induce perceptual filling-in. These neurons tended to have very large receptive fields, which extended out of the blind spot, and preferred relatively large stimuli. We believe that neurons in the V1 region representing the blind spot encode information essential for perceptual filling-in at the blind spot.     

A computational model of perceptual fill-in following retinal degeneration

The ablation of afferent input results in the reorganization of sensory and motor cortices. In the primary visual cortex (V1), binocular retinal lesions deprive a corresponding cortical region [lesion projection zone (LPZ)] of visual input. Nevertheless, neurons in the LPZ regain responsiveness by shifting their receptive fields (RFs) outside the retinal lesions; this re-emergence of neural activity is paralleled by the perceptual completion of disrupted visual input in human subjects with retinal damage. To determine whether V1 reorganization can account for perceptual fill-in, we developed a neural network model that simulates the cortical remapping in V1. The model shows that RF shifts mediated by the plexus of spatial- and orientation-dependent horizontal connections in V1 can engender filling-in that is both robust and consistent with psychophysical reports of perceptual completion. Our model suggests that V1 reorganization may underlie perceptual fill-in, and it predicts spatial relationships between the original and remapped RFs that can be tested experimentally. More generally, it provides a general explanation for adaptive functional changes following CNS lesions, based on the recruitment of existing cortical connections that are involved in normal integrative mechanisms.     

Cortical representation of space around the blind spot

The neural mechanism that mediates perceptual filling-in of the blind spot is still under discussion. One hypothesis proposes that the cortical representation of the blind spot is activated only under conditions that elicit perceptual filling-in and requires congruent stimulation on both sides of the blind spot. Alternatively, the passive remapping hypothesis proposes that inputs from regions surrounding the blind spot infiltrate the representation of the blind spot in cortex. This theory predicts that independent stimuli presented to the left and right of the blind spot should lead to neighboring/overlapping activations in visual cortex when the blind-spot eye is stimulated but separated activations when the fellow eye is stimulated. Using functional MRI, we directly tested the remapping hypothesis by presenting flickering checkerboard wedges to the left or right of the spatial location of the blind spot, either to the blind-spot eye or to the fellow eye. Irrespective of which eye was stimulated, we found separate activations corresponding to the left and right wedges. We identified the centroid of the activations on a cortical flat map and measured the distance between activations. Distance measures of the cortical gap across the blind spot were accurate and reliable (mean distance: 6-8 mm across subjects, SD approximately 1 mm within subjects). Contrary to the predictions of the remapping hypothesis, cortical distances between activations to the two wedges were equally large for the blind-spot eye and fellow eye in areas V1 and V2/V3. Remapping therefore appears unlikely to account for perceptual filling-in at an early cortical level.     

Spatio-temporal interactions and the spatial phase preferences of visual neurons

Summary We recorded single neuron responses in the cat's lateral geniculate nucleus (LGN) and visual cortex to compound stimuli composed of two sinusoidal gratings in a 21 frequency ratio. To probe visual receptive field symmetry, we varied the relative spatial phase of the two components and measured the effect on neuronal responses. We expected that on-center LGN neurons would respond best to gratings combined in positive cosine (bright bar) phase, while off-center LGN neurons would respond best to gratings combined in negative cosine (dark bar) phase. When drifting stimuli were used, cells' phase preferences were roughly 90 deg away from the expected values; when stationary, contrast-modulated stimuli were used, phase preferences were as originally predicted. Computer simulations showed that this discrepancy could be explained by taking into account the cells' temporal properties. Thus, tests using drifting stimuli confound the spatial structure of visual neural receptive fields with their temporal response characteristics. A small sample of data from cortical neurons reveals the same confound.     

Neural representation of the luminance and brightness of a uniform surface in the macaque primary visual cortex.

The perceived brightness of a surface is determined not only by the luminance of the surface (local information), but also by the luminance of its surround (global information). To better understand the neural representation of surface brightness, we investigated the effects of local and global luminance on the activity of neurons in the primary visual cortex (V1) of awake macaque monkeys. Single- and multiple-unit recordings were made from V1 while the monkeys were performing a visual fixation task. The classical receptive field of each neuron was identified as a region responding to a spot stimulus. Neural responses were assessed using homogeneous surfaces at least three times as large as the receptive field as stimuli. We first examined the sensitivity of neurons to variation in local surface luminance, while the luminance of the surround was held constant. The activity of a large majority of surface-responsive neurons (106/115) varied monotonically with changes in surface luminance; in some the dynamic range was over 3 log units. This monotonic relation between surface luminance and neural activity was more evident later in the stimulus period than early on. The effect of the global luminance on neural activity was then assessed in 81 of the surface-responsive neurons by varying the luminance of the surround while holding the luminance of the surface constant. The activity of one group of neurons (25/81) was unaffected by the luminance of the surround; these neurons appear to encode the physical luminance of a surface covering the receptive field. The responses of the other neurons were affected by the luminance of the surround. The effects of the luminances of the surface and the surround on the activities of 26 of these neurons were in the same direction (either increased or decreased), while the effects on the remaining 25 neurons were in opposite directions. The activities of the latter group of neurons seemed to parallel the perceived brightness of the surface, whereas the former seemed to encode the level of illumination. There were differences across different types of neurons with regard to the layer distribution. These findings indicate that global luminance information significantly modulates the activity of surface-responsive V1 neurons and that not only physical luminance, but also perceived brightness, of a homogeneous surface is represented in V1.     

Response characteristics of neurons in the pulvinar of awake cats to saccades and to visual stimulation

We studied responses of pulvinar neurons in awake cats that were allowed to execute spontaneous eye movements. Extracellular cell activity during saccades, saccade-like image shifts, and various stationary visual stimuli was recorded together with the animals' eye positions. All neurons analyzed had receptive fields that covered most of the central 80x80 degrees of the animals' visual field and did only respond to large (>20 degrees) visual stimuli. According to their response properties, recorded neurons were divided into three populations. The first group, termed "S neurons" (16%), responded when the animals performed saccades but were unresponsive to any of the visual stimuli tested. These neurons do not seem to receive a visual input that is strong enough to drive them. The second group, termed "V neurons" (51%), responded to various visual stimuli including saccade-like image motion when the eyes were stationary, but not when the animals executed saccades. V neurons therefore distinguish retinal image movements that are generated externally from internally generated image motion. Finally, "SV neurons" (31%) responded when the animals made saccades as well as to saccade-like image motion or to stationary stimuli. Although these neurons do not distinguish self-induced retinal image motion from motion generated by external stimulus movements, they must receive non-retinal motion-related input, because responses elicited by saccades had shorter latencies than responses to saccade-like stimulus movements. Only SV neurons resemble response properties of pretectal neurons that project to the pulvinar and that comprise the major subcortical visual input. The functional significance of pulvinar neuronal populations for visual and visuomotor information processing is discussed.     

Cortico-geniculate feedback linking the visual fields surrounding the blind spot in the cat

Previous studies have shown that neurons in layer 6 of V1 are activated by visual stimuli that induce perceptual filling-in at the blind spot (BS). As the main target of layer 6 neurons is the lateral geniculate nucleus (LGN), we speculate that the cortico-geniculate projection is involved in mediating filling-in at BS. To begin to test that hypothesis, we examined whether there is an anatomical basis for integration of visual signals from both sides of BS by cortico-geniculate feedback neurons in V1. We injected an anterograde tracer into a site adjacent to the region representing BS. We observed that numerous axons traverse the neuron-free gap that retinotopically corresponds to BS within LGN. This indicates that visual signals from one side of BS are conveyed to the opposite side via a feedback connection. Cortico-geniculate feedback projection may integrate visual signals from around BS and contribute to perceptual filling-in at BS.     

V1 response timing and surface filling-in

There is ample evidence from demonstrations such as color induction and stabilized images that information from surface boundaries plays a special role in determining the perception of surface interiors. Surface interiors appear to "fill-in." Psychophysical experiments also show that surface perception involves a slow scale-dependent process distinct from mechanisms involved in contour perception. The present experiments aimed to test the hypothesis that surface perception is associated with relatively slow scale-dependent neural filling-in. We found that responses in macaque primary visual cortex (V1) are slower to surface interiors than responses to optimal bar stimuli. Moreover, we found that the response to a surface interior is delayed relative to the response to the surface's border and the extent of the delay is proportional to the distance between a receptive field and the border. These findings are consistent with some forms of neural filling-in and suggest that V1 may provide the neural substrate for perceptual filling-in.     

Visual responses with and without fixation: neurons in premotor cortex encode spatial locations independently of eye position

 The ventral premotor cortex (PMv) of the macaque monkey contains neurons that respond both to visual and to tactile stimuli. For almost all of these “bimodal” cells, the visual receptive field is anchored to the tactile receptive field on the head or the arms, and remains stationary when the eyes fixate different locations. This study compared the responses of bimodal PMv neurons to a visual stimulus when the monkey was required to fixate a spot of light and when no fixation was required. Even when the monkey was not fixating and the eyes were moving, the visual receptive fields remained in the same location, near the associated tactile receptive field. For many of the neurons, the response to the visual stimulus was significantly larger when the monkey was not performing the fixation task. In control tests, the presence or absence of the fixation spot itself had little or no effect on the response to the visual stimulus. These results show that even when the monkey’s eye position is continuously changing, the neurons in PMv have visual receptive fields that are stable and fixed to the relevant body part. The reduction in response during fixation may reflect a shift of attention from the visual stimulus to the demands of the fixation task. Received: 8 April 1997 / Accepted: 16 July 1997     

Retrograde transneuronal transport of wheat-germ agglutinin to the retina from visual cortex in the cat

Summary The stability of visual perception despite eye movements suggests the existence, in the visual system, of neural elements able to recognize whether a movement of an image occurring in a particular part of the retina is the consequence of an actual movement that occurred in the visual field, or self-induced by an ocular movement while the object was still in the field of view. Recordings from single neurons in area V3A of awake macaque monkeys were made to check the existence of such a type of neurons (called real-motion cells; see Galletti et al. 1984, 1988) in this prestriate area of the visual cortex. A total of 119 neurons were recorded from area V3A. They were highly sensitive to the orientation of the visual stimuli, being on average more sensitive than V1 and V2 neurons. Almost all of them were sensitive to a large range of velocities of stimulus movement and about one half to the direction of it. In order to assess whether they gave different responses to the movement of a stimulus and to that of its retinal image alone (self-induced by an eye movement while the stimulus was still), a comparison was made between neuronal responses obtained when a moving stimulus swept a stationary receptive field (during steady fixation) and when a moving receptive field swept a stationary stimulus (during tracking eye movement). The receptive field stimulation at retinal level was physically the same in both cases, but only in the first was there actual movement of the visual stimulus. Control trials, where the monkeys performed tracking eye movements without any intentional receptive field stimulation, were also carried out. For a number of neurons, the test was repeated in darkness and against a textured visual background. Eighty-seven neurons were fully studied to assess whether they were real-motion cells. About 48% of them (42/87) showed significant differences between responses to stimulus versus eye movement. The great majority of these cells (36/42) were real-motion cells, in that they showed a weaker response to visual stimulation during tracking than to the actual stimulus movement during steady fixation. On average, the reduction in visual response during eye movement was 64.0 ± 15.7% (SD). Data obtained with a uniform visual background, together with those obtained in darkness and with textured background, indicate that real-motion cells receive an eye-motion input, either retinal or extraretinal in nature, probably acting presynaptically on the cell's visual input. In some cases, both retinal and extraretinal eye-motion inputs converge on the same real-motion cell. No correlation was observed between the real-motion behaviour and the sensitivity to either orientation or direction of movement of the visual stimulus used to activate the receptive field, nor with the retinotopic location of the receptive field. We suggest that the visual system uses real-motion cells in order to distinguish real from self-induced movements of retinal images, hence to recognize the actual movement in the visual field. Based on psychophysical data, the hypothesis has been advanced of an internal representation of the field of view, stable despite eye movement (cf. MacKay 1973). The real-motion cells may be neural elements of this network and we suggest that the visual system uses the output of this network to properly interpret the large number of sensory changes resulting from exploratory eye movements in a stable visual world.     

Visual response properties of neurons in the parahippocampal cortex of monkeys

We examined visual response properties of single neurons in the parahippocampal (PH) cortex of alert monkeys using various visual stimuli (bars, geometrical shapes such as a circle, and images such as a human face) while the monkey fixated a spot for a juice reward. Of the investigated PH neurons 104 of 359 (29%) were found to be visually responsive. The investigation was focused on spatial and object aspects of visual processing. We investigated a visual receptive field (RF) property and a direction selectivity for a moving bar with respect to spatial processing. For half of these PH neurons (53%), the optimal stimulus position, where a visual stimulus elicited the maximal response, located peripherally, that is, with an eccentricity of more than 10 deg. More than 20% of these PH neurons had an RF that does not include the center of gaze. There were neurons in the PH cortex that appeared to convey motion signals. In addition, some PH neurons showed eye-position-dependent activity. With respect to object processing, we investigated selectivities for images, geographical shapes, orientations of a bar, and colors. For comparison purposes, we also examined responses of perirhinal (PR) neurons. PH neurons showed selective responses to these stimuli, but PR neurons were found to be more selective for images than PH neurons. These results suggest that the PH cortex is involved in both spatial and object processing, but less involved than the PR cortex in processing of complex images.     

‘Real-motion’ cells in visual area V2 of behaving macaque monkeys

Summary Extracellular recordings were made in area V2 of behaving macaque monkeys. Neurons were classified into three groups: non-oriented cells, oriented cells with antagonistic areas and oriented cells without antagonistic areas in their receptive field. All neurons were tested with standard visual stimulations in order to assess whether they gave different responses to the movement of a stimulus and to the movement of its retinal image alone, when the stimulus was motionless and the animal voluntarily moved its eyes. To do this, neuronal responses obtained when a moving stimulus swept a stationary receptive field (during steady fixation) and when a moving receptive field swept a stationary stimulus (during tracking eye movements), were compared. The receptive field stimulation at retinal level was physically the same in both cases, but only in the first was there actual movement of the visual stimulus. Control trials, where the monkeys performed tracking eye movements without any intentional receptive field stimulation, were also carried out. Out of a total of 263 neurons isolated in the central 10 deg representation of area V2, 101 were fully studied with the visual stimulation described above. Most of these (83/ 101; 82%) gave about the same response to the two situations. About 14% (14/101) gave a good response to stimulus movements during steady fixation and a very weak one to retinal image displacements of stationary stimuli during visual tracking. We have called neurons of this type real-motion cells (cf. Galletti et al. 1984). None of the non-oriented cells was a real-motion one, while about an equal percentage of real-motion cells was found among the oriented cells with and without antagonistic areas. Finally, we found only 4 neurons which showed behaviour opposite to that of real-motion cells, i.e. they showed a better response to displacement of the retinal image of stationary stimuli than to actual movement of stimuli. We suggest that real-motion cells might contribute to correctly evaluating movement in the visual field in spite of eye movements and that they might allow recognition of the movement of an object even if it moves across a non-patterned visual background. Present data on area V2, together with similar results observed in area V1 (Galletti et al. 1984; Battaglini et al. 1986), support the view that these two cortical areas analyse the movement in a parallel fashion along with many other characteristics of the visual stimulus.     

Primate pupillary light reflex: receptive field characteristics of pretectal luminance neurons

This study examined the response properties of luminance neurons found within the pretectal olivary nucleus (PON), which is the pretectal nucleus that mediates the primate pupillary light reflex. We recorded the activity of 121 single units in alert, behaving rhesus monkeys trained to fixate a back-projected laser spot while a luminance stimulus was presented. The change in the firing rate of luminance neurons was measured as a function of changes in the size, retinal illuminance, and position of the stimulus. We found that these neurons possessed large receptive fields, which were sufficiently distinct that they could be placed into three classes. Approximately 40% of the PON luminance neurons responded well to stimuli presented in either the contralateral or ipsilateral hemifield. These neurons were classified as "bilateral" neurons. In the primate, retinal projections to the pretectum and other retinorecipient nuclei are organized such that direct retinal input can only account for the contralateral hemifield responses of these neurons. Thus the representation of the ipsilateral hemifield in "bilateral" PON cells must result from input from a nonretinal source. Approximately 30% of PON neurons responded only to stimuli presented in the contralateral hemifield. These neurons were classified as "contralateral" neurons. Finally, approximately 30% of PON neurons responded to stimuli presented at or near the animal's fixation point. These neurons were classified as "macular" neurons. The mean firing rates of all classes of neurons increased with increases in stimulus size and luminance within their receptive fields. The thresholds and magnitude of these responses closely matched those that would be appropriate for mediating the pupillary light reflex. In summary, these results suggest that all three classes of PON neurons contribute to the behaviorally observed pupillomotor field characteristics in which stimuli at the macular produce substantially larger pupillary responses than more peripheral stimuli. The contributions of "bilateral" and "contralateral" cells account for pupillary responses evoked by peripheral changes in luminance, whereas the contributions of all three cell classes account for the larger pupillary responses evoked by stimuli in the central visual field.     

Mapping of stimulus energy in primary visual cortex

A recent optical imaging study of primary visual cortex (V1) by Basole, White, and Fitzpatrick demonstrated that maps of preferred orientation depend on the choice of stimuli used to measure them. These authors measured population responses expressed as a function of the optimal orientation of long drifting bars. They then varied bar length, direction, and speed and found that stimuli of a same orientation can elicit different population responses and stimuli with different orientation can elicit similar population responses. We asked whether these results can be explained from known properties of V1 receptive fields. We implemented an "energy model" where a receptive field integrates stimulus energy over a region of three-dimensional frequency space. The population of receptive fields defines a volume of visibility, which covers all orientations and a plausible range of spatial and temporal frequencies. This energy model correctly predicts the population response to bars of different length, direction, and speed and explains the observations made with optical imaging. The model also readily explains a related phenomenon, the appearance of motion streaks for fast-moving dots. We conclude that the energy model can be applied to activation maps of V1 and predicts phenomena that may otherwise appear to be surprising. These results indicate that maps obtained with optical imaging reflect the layout of neurons selective for stimulus energy, not for isolated stimulus features such as orientation, direction, and speed.     

Central core control of developmental plasticity in the kitten visual cortex: I. Diencephalic lesions

Summary In five, dark-reared, 4-week-old kittens the posterior two thirds of the corpus callosum were split, and a lesion comprising the intralaminar nuclei was made of the left medial thalamic complex. In addition, the right eye was closed by suture. Postoperatively, the kittens showed abnormal orienting responses, neglecting visual stimuli presented in the hemifield contralateral to the side of the lesion. Sudden changes in light, sound, or somatosensory stimulation elicited orienting responses that all tended toward the side of the lesion. These massive symptoms faded within a few weeks but the kittens continued to neglect visual stimuli in the hemifield contralateral to the lesion when a second stimulus was presented simultaneously in the other hemifield. Electrophysiologic analysis of the visual cortex, performed after the end of the critical period, revealed marked interhemispheric differences. In the visual cortex of the normal hemisphere most neurons were monocular and responded exclusively to stimulation of the open eye, but otherwise had normal receptive field properties. In the visual cortex of the hemisphere containing the thalamic lesion, the majority of the neurons remained binocular. In addition, the selectivity for stimulus orientation and the vigor of responses to optimally aligned stimuli were subnormal on this side. Thus, the same retinal signals, which in the control hemisphere suppressed the pathways from the deprived eye and supported the development of normal receptive fields, failed to do either in the hemisphere containing the thalamic lesion. Apparently, experience-dependent changes in the visual cortex require both retinal stimulation and the functioning of diencephalic structures which modulate cortical excitability and control selective attention.     

Visual motion response properties of neurons in dorsolateral pontine nucleus of alert monkey

1. In this study we sought to characterize the visual motion processing that exists in the dorsolateral pontine nucleus (DLPN) and make a comparison with the reported visual responses of the middle temporal (MT) and medial superior temporal (MST) areas of the monkey cerebral cortex. The DLPN is implicated as a component of the visuomotor interface involved with the regulation of smooth-pursuit eye movements, because it is a major terminus for afferents from MT and MST and also the source of efferents to cerebellar regions involved with eye-movement control. 2. Some DLPN cells were preferentially responsive to discrete (spot and bar) visual stimuli, or to large-field, random-dot pattern motion, or to both discrete and large-field visual motion. The results suggest differential input from localized regions of MT and MST. 3. The visual-motion responses of DLPN neurons were direction selective for 86% of the discrete visual responses and 95% of the large-field responses. Direction tuning bandwidths (full-width at 50% maximum response amplitude) averaged 107 degrees and 120 degrees for discrete and large-field visual motion responses, respectively. For the two visual response types, the direction index averaged 0.95 and 1.02, indicating that responses to stimuli moving in preferred directions were, on average, 20 and 50 times greater than responses to discrete or large-field stimulus movement in the opposite directions, respectively. 4. Most of the DLPN visual responses to movements of discrete visual stimuli exhibited increases in amplitude up to preferred retinal image speeds between 20 and 80 degrees/s, with an average preferred speed of 39 degrees/s. At higher speeds, the response amplitude of most units decreased, although a few units exhibited a broad saturation in response amplitude that was maintained up to at least 150 degrees/s before the response decreased. Over the range of speeds up to the preferred speeds, the sensitivity of DLPN neurons to discrete stimulus-related, retinal-image speed averaged 3.0 spikes/s per deg/s. The responses to large-field visual motion were less sensitive to retinal image speed and exhibited an average sensitivity of 1.4 spikes/s per deg/s before the visual response saturated. 5. DLPN and MT were quantitatively comparable with respect to degree of direction selectivity, retinal image speed tuning, and distribution of preferred speeds. Many DLPN receptive fields contained the fovea and were larger than those of MT and more like MST receptive fields in size.(ABSTRACT TRUNCATED AT 400 WORDS)     

Cortical synchronization suggests neural principles of visual feature grouping

Compositions of visual scenes are related here to neural signals in visual cortex and to cortical circuit models to understand neural mechanisms of perceptual feature grouping. Starting from the hypothesis that synchronization and decoupling of cortical gamma-activities (35-90 Hz) define the relations among visual objects, we concentrate on synchronization related to (1) static retinal stimulation during ocular fixation, and (2) transient stimulation by sudden shifts in object position. The synchronization hypothesis has been tested by analyzing signal correlations in visual cortex of monkeys with the following results: Static retinal stimuli induce loosely phase-coupled gamma-activities among neurons of an object's cortical representation. Patches of gamma-synchronization become decoupled across the representation of an object's contour, and thereby can code figure-ground segregation. Transient stimuli evoke synchronized volleys of stimulus-locked activities that are typically non-rhythmic and include low frequency components in addition to those in the gamma-range. It is argued that stimulus-induced and stimulus-locked synchronizations may play different roles in perceptual feature grouping.     

Receptive-field properties of neurons in middle temporal visual area (MT) of owl monkeys

Response properties of single neurons in the middle temporal visual area (MT) of anesthetized owl monkeys were determined and quantified for flashed and moving bars of light under computer control for position, orientation, direction of movement, and speed. Receptive-field sizes, ranging from 4 to 25 degrees in width, were considerably larger than receptive fields with corresponding eccentricities in the striate cortex. Neurons were highly binocular with most cells equally or nearly equally activated by either eye. Neurons varied in selectivity for axis and direction of moving bars. Some neurons demonstrated little or no selectivity, others were bidirectional on a single axis, while the largest group was highly selective for direction with little or no response to bar movement opposite to the preferred direction. Over 70% of neurons were classified as highly selective and 90% showed some preference for direction and/or axis of stimulus movement. Neurons typically responded to bar movement only over a restricted range of velocities. The majority of neurons responded best to a particular velocity within the 5-60 degrees/s range, with marked attenuation of the response for velocities greater or less than the preferred. Some neurons failed to show significant response attenuation even at the lowest tested velocity, while other neurons preferred velocities of 100 degrees/s or more and failed to attenuate to the highest velocities. Response magnitude varied with stimulus dimensions. Increasing the length of the moving bar typically increased the magnitude of the response slightly until the stimulus exceeded the receptive-field borders. Other neurons responded less to increases in bar length within the excitatory receptive field. Neurons preferred narrow bars less than 1 degree in width, and marked reductions in responses characteristically occurred with wider stimuli. Moving patterns of randomly placed small dots were often as effective as or more effective than single bars in activating neurons. Selectivity for direction of movement remained for the dot pattern. for the dot pattern. Poststimulus time (PST) histograms of responses to bars flashed at a series of 21 different positions across the receptive field, in the "response-plane" format, indicated a spatially and temporally homogeneous receptive-field structure for nearly all neurons. Cells characteristically showed transient excitation at both stimulus onset and offset for all effective stimulus locations. Some cells responded mainly at bright stimulus onset or offset.     

Disparity-selective neurons in area V4 of macaque monkeys

Area V4 is an intermediate stage of the ventral visual pathway providing major input to the final stages in the inferior temporal cortex (IT). This pathway is involved in the processing of shape, color, and texture. IT neurons are also sensitive to horizontal binocular disparity, suggesting that binocular disparity is processed along the ventral visual pathway. In the present study, we examined the processing of binocular disparity information by V4 neurons. We recorded responses of V4 neurons to binocularly disparate stimuli. A population of V4 neurons modified their responses according to changes of stimulus disparity; neither monocular responses nor eye movements could account for this modulation. Disparity-tuning curves were similar for different locations within a neuron's receptive field. Neighboring neurons recorded using a single electrode displayed similar disparity-tuning properties. These findings indicate that a population of V4 neurons is selective for binocular disparity, invariant for the position of the stimulus within the receptive field. The finding that V4 neurons with similar disparity selectivity are clustered suggests the existence of functional modules for disparity processing in V4.     

Position selectivity in scene- and object-responsive occipitotemporal regions

Complex visual scenes preferentially activate several areas of the human brain, including the parahippocampal place area (PPA), the retrosplenial complex (RSC), and the transverse occipital sulcus (TOS). The sensitivity of neurons in these regions to the retinal position of stimuli is unknown, but could provide insight into their roles in scene perception and navigation. To address this issue, we used functional magnetic resonance imaging (fMRI) to measure neural responses evoked by sequences of scenes and objects confined to either the left or right visual hemifields. We also measured the level of adaptation produced when stimuli were either presented first in one hemifield and then repeated in the opposite hemifield or repeated in the same hemifield. Although overall responses in the PPA, RSC, and TOS tended to be higher for contralateral stimuli than for ipsilateral stimuli, all three regions exhibited position-invariant adaptation, insofar as the magnitude of adaptation did not depend on whether stimuli were repeated in the same or opposite hemifields. In contrast, object-selective regions showed significantly greater adaptation when objects were repeated in the same hemifield. These results suggest that neuronal receptive fields (RFs) in scene-selective regions span the vertical meridian, whereas RFs in object-selective regions do not. The PPA, RSC, and TOS may support scene perception and navigation by maintaining stable representations of large-scale features of the visual environment that are insensitive to the shifts in retinal stimulation that occur frequently during natural vision.