. Performance in visual discrimination tasks improves with practice. Although the psychophysical parameters of these improvements have suggested the involvement of early areas in visual cortex, there has been little direct study of the physiological correlates of such perceptual learning at the level of individual neurons. To examine how neuronal response properties in the early visual system may change with practice, we trained monkeys for more than 6 mo in an orientation discrimination task in which behaviorally relevant stimuli were restricted to a particular retinal location and oriented around a specific orientation. During training the monkeys' discrimination thresholds gradually improved to much better than those of naive monkeys or humans. Although this improvement was specific to the trained orientation, it showed little retinotopic specificity. The receptive field properties of single neurons from regions representing the trained location and a location in the opposite visual hemifield were measured in V1 and V2. In most respects the receptive field properties in the representations of the trained and untrained regions were indistinguishable. However, in the regions of V1 and V2 representing the trained location, there were slightly fewer neurons whose optimal orientation was near the trained orientation. This resulted in a small but significant decrease in the V1 population response to the trained orientation at the trained location. Consequently, the observed neuronal populations did not exhibit any orientation-specific biases sufficient to explain the orientation specificity of the behavioral improvement. Pooling models suggest that the behavioral improvement was accomplished with a task-dependent and orientation-selective pooling of unaltered signals from early visual neurons. These data suggest that, even for training with stimuli suited to the selectivities found in early areas of visual cortex, behavioral improvements can occur in the absence of pronounced changes in the physiology of those areas. I N T R O D U C T I O NThe improvement of sensory abilities with practice has been demonstrated for somatosensory, auditory, and visual stimuli in both animals and humans (Goldstone 1998). Studies of neurons in primary auditory and somatosensory cortex have revealed training-related changes in both the mapping of response properties across the cortical surface and the sensitivities of individual neurons. These changes suggest that adult cortex is remarkably plastic; training can increase the number of neurons whose selectivities correspond to the demands of the training task (Jenkins et al. 1990a;Recanzone et al. 1993) and can increase neuronal selectivity (Recanzone et al. 1992b).In primary visual cortex (V1) plasticity of neuronal response properties has also been observed during the course of normal development (Chapman and Stryker 1993;Crair et al. 1998;DeAngelis et al. 1993;Fregnac and Imbert 1978;Ghose et al. 1994b;LeVay et al. 1980;Sclar et al. 1985), in response to environmental modifications i...

Paying attention to a stimulus selectively increases the ability to process it. For example, when subjects attend to a specific region of a visual scene, their sensitivity to changes at that location increases. A large number of studies describe the behavioural consequences and neurophysiological correlates of attending to spatial locations. There has, in contrast, been little study of the allocation of attention over time. Because subjects can anticipate predictable events with great temporal precision, it seems probable that they might dynamically shift their attention when performing a familiar perceptual task whose constraints changed over time. We trained monkeys to respond to a stimulus change where the probability of occurrence changed over time. Recording from area V4 of the visual cortex in these animals, we found that the modulation of neuronal responses changed according to the probability of the change occurring at that instant. Thus, we show that the attentional modulation of sensory neurons reflects a subject's anticipation of the timing of behaviourally relevant events.

It is well established that multiple stimulus dimensions (e.g., orientation and spatial frequency) are mapped onto the surface of striate cortex. However, the detailed organization of neurons within a local region of striate cortex remains unclear. Within a vertical column, do all neurons have the same response selectivities? And if not, how do they most commonly differ and why? To address these questions, we recorded from nearby pairs of simple cells and made detailed spatiotemporal maps of their receptive fields. From these maps, we extracted and analyzed a variety of response metrics. Our results provide new insights into the local organization of striate cortex. First, we show that nearby neurons seldom have very similar receptive fields, when these fields are characterized in space and time. Thus, there may be less redundancy within a column than previously thought. Moreover, we show that correlated discharge increases with receptive field similarity; thus, the local dissimilarity between neurons may allow for noise reduction by response pooling. Second, we show that several response variables are clustered within striate cortex, including some that have not received much attention such as response latency and temporal frequency. We also demonstrate that other parameters are not clustered, including the spatial phase (or symmetry) of the receptive field. Third, we show that spatial phase is the single parameter that accounts for most of the difference between receptive fields of nearby neurons. We consider the implications of this local diversity of spatial phase for population coding and construction of higher-order receptive fields.

Signals relayed through the magnocellular layers of the LGN travel on axons with faster conduction speeds than those relayed through the parvocellular layers. As a result, magnocellular signals might reach cerebral cortex appreciably before parvocellular signals. The relative speed of these two channels cannot be accurately predicted based solely on axon conduction speeds, however. Other factors, such as different degrees of convergence in the magnocellular and parvocellular channels and the retinal circuits that feed them, can affect the time it takes for magnocellular and parvocellular signals to activate cortical neurons. We have investigated the relative timing of visual responses mediated by the magnocellular and parvocellular channels. We recorded individually from 78 magnocellular and 80 parvocellular neurons in the LGN of two anesthetized monkeys. Visual response latencies were measured for small spots of light of various intensities. Over a wide range of stimulus intensities the fastest magnocellular response latencies preceded the fastest parvocellular response latencies by about 10 ms. Because parvocellular neurons are far more numerous than magnocellular neurons, convergence in cortex could reduce the magnocellular advantage by allowing parvocellular signals to generate detectable responses sooner than expected based on the responses of individual parvocellular neurons. An analysis based on a simple model using neurophysiological data collected from the LGN shows that convergence in cortex could eliminate or reverse the magnocellular advantage. This observation calls into question inferences that have been made about ordinal relationships of neurons based on timing of responses.

1. The discharge of individual neurons in the visual cortex and lateral geniculate nucleus (LGN) of anesthetized and paralyzed cats and kittens was examined for the presence of oscillatory activity. Neural firing was evoked through the monoptic or dichoptic presentation of drifting gratings and random sequences of flashed bars. The degree to which different oscillatory frequencies were present in neural discharge was quantified by computation of the power spectra of impulse train responses. 2. Action potentials from single cells were recorded extracellularly and isolated on the basis of amplitude. Receptive-field properties of the neurons under study were characterized initially by their discharge in response to gratings of sinusoidal luminance. By varying orientation and spatial frequency, optimal stimulus characteristics were determined. Oscillation analysis was performed on spike trains acquired during repeated presentations of the optimal stimulus by identification of power spectra peaks in the frequency range of rhythmic potentials observed in electroencephalograph studies (30-80 Hz). The amplitude and frequency of the largest peak in this range was used to characterize oscillatory strength and frequency. All discharge in which the peak amplitude exceeded the high-frequency noise by a factor > 1.5 was classified as oscillatory. 3. Of the 342 cortical cells examined, 147 cells displayed oscillatory activity in the 30 to 80-Hz range during portions of their visual response. Sixty out of 169 simple cells, 82 out of 166 complex cells, and 5 out of 7 special complex cells exhibited oscillations. There was no laminar bias in the distribution of oscillatory cells; the proportions of oscillatory cells were similar in all layers. All oscillatory discharge was variable with respect to frequency and strength between successive presentations of the same optimal stimulus. In as little as 10 s, for example, peak frequencies shifted by a factor of two. For many cells, these trial-to-trial variations obscured detectable oscillations when all trials were averaged together. 4. The potential role of neuronal maturation in the generation of oscillatory activity was investigated by studying neuronal responses from kittens at 4 wk postnatal. Of the 80 kitten cells studied, 27 exhibited oscillatory discharge. Although oscillations in the kitten visual cortex spanned the same frequency range as that seen in the adult, oscillations in the midfrequency range (36-44 Hz) are more common in the adult cortex. 5. To explore the possibility that oscillations might play a functional role in vision, we investigated the dependence of oscillations on different stimulus parameters.(ABSTRACT TRUNCATED AT 400 WORDS)

Most of our understanding of the functional organization of human visual cortex comes from lesion and functional imaging studies and by extrapolation from results obtained by neuroanatomical and neurophysiological studies in nonhuman primates. Although some single-unit and field potential recordings have been made in human visual cortex, none has provided quantitative characterization of spatial receptive fields (RFs) of individual sites. Here we use subdural electrodes implanted for clinical purposes to quantitatively measure response properties in different regions of human visual cortex. We find significant differences in RF size, response latency, and response magnitude for sites in early visual areas, versus sites in later stages of both the dorsal and ventral streams. In addition, we use this technique to estimate the cortical magnification factor in early human visual cortex. The spatial and temporal resolution of cortical surface recordings suggest that this technique is well suited to examine further issues in visual processing in humans.

). In these studies, when preferred and nonpreferred stimuli are simultaneously presented, responses are much stronger when attention is directed to the preferred stimulus than when it is directed to the nonpreferred stimulus. In this study, we recorded neuronal responses from individual neurons in visual cortical area V4 to both single and paired stimuli with a variety of attentional allocations and stimulus combinations. For each neuron studied, we constructed a quantitative model of input summation and then tested various models of attention. In many neurons, we are able to explain neuronal responses across the entire range of stimuli and attentional allocations tested. Specifically, we are able to reconcile seemingly inconsistent observations of single and paired stimuli attentional modulation with a new model in which attention can facilitate or suppress specific inputs to a neuron but does not fundamentally alter the integration of these inputs.

Area V4 occupies a central position among the areas of the primate cerebral cortex involved with object recognition and analysis. Consistent with this role, neurons in V4 are selective for many visual attributes including color, orientation, and binocular disparity. However, it is uncertain whether cells within V4 are organized with respect to these properties. In this study we used in vivo optical imaging and electrophysiology in macaque visual cortex to show that cells that share certain physiological properties are indeed grouped together in V4. Our results revealed regions containing cells with common orientation selectivity. These regions were similar in size to those seen in V2 and much larger than those seen in V1 and were confirmed by appropriately targeted single-unit recording. Surprisingly, orientation organization visible through imaging was limited to the portion of V4 representing the central visual fields. Optical imaging also revealed a functional organization related to stimulus size. Size-sensitive regions (S regions) contained cells that were strongly suppressed by large stimuli. In contrast to V2, S regions in V4 contain orientation domains. These results suggest that V4 contains modular assemblies of cells related to particular aspects of form analysis. Such organization may contribute to the construction of object-based representations.