The adult brain shows remarkable plasticity, as demonstrated by the improvement in fine sensorial discriminations after intensive practice. The behavioural aspects of such perceptual learning are well documented, especially in the visual system. Specificity for stimulus attributes clearly implicates an early cortical site, where receptive fields retain fine selectivity for these attributes; however, the neuronal correlates of a simple visual discrimination task remained unidentified. Here we report electrophysiological correlates in the primary visual cortex (V1) of monkeys for learning orientation identification. We link the behavioural improvement in this type of learning to an improved neuronal performance of trained compared to naive neurons. Improved long-term neuronal performance resulted from changes in the characteristics of orientation tuning of individual neurons. More particularly, the slope of the orientation tuning curve that was measured at the trained orientation increased only for the subgroup of trained neurons most likely to code the orientation identified by the monkey. No modifications of the tuning curve were observed for orientations for which the monkey had not been trained. Thus training induces a specific and efficient increase in neuronal sensitivity in V1.

fMRI-based adaptation paradigms (fMR-A) have been used to infer neuronal stimulus selectivities in humans. Inferring neuronal selectivities from fMR-A, however, requires an understanding of the relationship between the stimulus selectivity of neuronal adaptation and responses. We studied this relationship by recording single cells in macaque inferior temporal (IT) cortex, an area that shows fMRI adaptation. Repetition of identical object images reduced the responsiveness of single IT neurons. Presentation of an image to which the neuron was unresponsive did not alter the response to a subsequent image that activated the neuron. Successive presentation of two different images to which the neuron responded similarly produced adaptation, but less so than the repeated presentation of an image. The neuronal adaptation at the single-cell level showed a greater degree of stimulus selectivity than the responses. This complicates the interpretation of fMR-A paradigms when inferring neuronal selectivity.

1. Human perceptual learning in discrimination of the oblique orientation was studied using psychophysical methods. Subjects were trained daily to improve their ability to identify the orientation of a circular 2-5 deg diameter unidimensional noise field. Dramatic improvements in sensitivity to contour orientation occurred over a period of 15-20 days. The improved performance persisted for several months. Improvement was more evident between daily sessions than within sessions. This was partly due to fatigue interfering with the learning effect. Moreover, a consolidation period seemed to be required. 2. Improvement was restricted to the position of the stimulus being trained. This position dependency of the learning effect proved very precise. After training at a specific stimulus position, merely displacing the stimulus to an adjacent position caused a marked increase in thresholds.3. No transfer of the training effect was observed between orientations. Following a shift of 90 deg away from the trained orientation, performance fell, even below the initial level. 4. We observed complete to almost complete transfer between the two eyes. 5. Our results suggest plastic changes at a level of the visual processing stream where input from both eyes has come together, but where generalization for spatial localization and orientation has not yet occurred.

articlesThe capacity to categorize stimuli is fundamental to all living organisms 1,2 . Theories of categorization agree upon the importance of the similarity between stimuli to account for many aspects of categorization performance [3][4][5] . However, it is not straightforward to compute the degree of similarity between stimuli that can vary across a high number of dimensions, like complex shapes. Fortunately, the similarities among a set of complex stimuli can often be described in a more compact way [6][7][8] . Indeed, stimuli from many behaviorally relevant sets can be represented in a low-dimensional representation space in which the proximity between stimuli is related to their similarity. For example, by presenting the randomly ordered shapes of Fig. 1d in a particular order (Fig. 1a-c), the similarities can be easily described by a twodimensional square-like configuration. Several behavioral studies that have varied complex shape differences parametrically revealed that primates are able to represent the similarities between shapes in a low-dimensional representation space without ever seeing these stimuli in their parametric configuration 9-12 .Here we aim to study directly the neural basis of these lowdimensional representation spaces. Object recognition and categorization in macaques is thought to depend on the inferotemporal cortex (IT) 13,14 . Single IT neurons are selective for moderately complex object features 15 , but several studies have found little relationship between the similarities between complex objects and the responses of single IT neurons 16,17 . However, one needs to manipulate shape similarity parametrically to investigate how the responses of IT neurons to complex stimuli are related to the proximity of these stimuli in a low-dimensional space. Thus, we investigated whether the response pattern across a population of IT neurons can reveal a low-dimensional and faithful representation of shape similarity using parameterized shapes. Behavioral studies with parameterized shapes have shown that the similarities among these complex stimuli can be represented using a low number of dimensions. Using psychophysical measurements and single-cell recordings in macaque inferotemporal (IT) cortex, we found an agreement between low-dimensional parametric configurations of shapes and the representation of shape similarity at the behavioral and neuronal level. The shape configurations, computed from both the perceived and neuron-based similarities, revealed a low number of dimensions and contained the same stimulus order as the parametric configurations. However, at a metric level, the behavioral and neural representations deviated consistently from the parametric configurations. These findings suggest an ordinally faithful but metrically biased representation of shape similarity in IT.As the analysis of the visual input in the visual system is highly nonlinear, the neuronal representation space could deviate from the configurations in parameter space in several ways. Previous psychophysical stu...

Recent findings in dorsal visual stream areas and computational work raise the question whether neurons at the end station of the ventral visual stream can code for stimulus position. The authors provide the first detailed, quantitative data on the spatial sensitivity of neurons in the anterior part of the inferior temporal cortex (area TE) in awake, fixating monkeys. They observed a large variation in receptive field (RF) size (ranging from 2.8 degrees to 26 degrees ). TE neurons differed in their optimal position, with a bias toward the foveal position. Moreover, the RF profiles of most TE neurons could be fitted well with a two-dimensional Gaussian function. Most neurons had only one region of high sensitivity and showed a smooth decline in sensitivity toward more distal positions. In addition, the authors investigated some of the possible determinants of such spatial sensitivity. First, testing with low-pass filtered versions of the stimuli revealed that the general preference for the foveal position and the size of the RFs was not due simply to TE neurons receiving input with a lower spatial resolution at more eccentric positions. The foveal position was still preferred after intense low-pass filtering. Second, although an increase in stimulus size consistently broadened spatial sensitivity profiles, it did not change the qualitative features of these profiles. Moreover, size selectivity of TE neurons was generally position invariant. Overall, the results suggest that TE neurons can code for the position of stimuli in the central region of the visual field.