Studies of the emergence of shape representations in childhood have focused primarily on the ventral visual pathway. Importantly, however, there is increasing evidence that, in adults, the dorsal pathway also represents shape-based information. These dorsal representations follow a gradient with more posterior regions being more shape-sensitive than anterior regions and with representational similarity in some posterior regions that is equivalent to that observed in some ventral regions. To explore the emergence and nature of dorsal shape representations in development, we acquired both fMRI BOLD signals and behavioral data in children (aged 8–10 years) using a parametric image scrambling paradigm. Children exhibited adult-like large-scale organization of shape processing along both ventral and dorsal pathways. Also, as in adults, the activation profiles of children's posterior dorsal and ventral regions were correlated with recognition performance, reflecting a possible contribution of these signals to perception. There were age-related changes, however, with children being more affected by the distortion of shape information than adults, both behaviorally and neurally. These findings reveal that shape-processing mechanisms along both dorsal and ventral pathways are subject to a protracted developmental trajectory.

It is commonly believed that, in right-handed individuals, words and faces are processed by distinct neural systems: one in the left hemisphere (LH) for words and the other in the right hemisphere (RH) for faces. Emerging evidence suggests, however, that hemispheric selectivity for words and for faces may not be independent of each other. One recent account suggests that words become lateralized to the LH to interact more effectively with language regions, and subsequently, as a result of competition with words for representational space, faces become lateralized to the RH. On this interactive account, left-handed individuals, who as a group show greater variability with respect to hemispheric language dominance, might be expected to show greater variability in their degree of RH lateralization of faces as well. The current study uses behavioral measures and ERPs to compare the hemispheric specialization for both words and faces in right- and left-handed adult individuals. Although both right- and left-handed groups demonstrated LH over RH superiority in discrimination accuracy for words, only the right-handed group demonstrated RH over LH advantage in discrimination accuracy for faces. Consistent with this, increased right-handedness was related to an increase in RH superiority for face processing, as measured by the strength of the N170 ERP component. Interestingly, the degree of RH behavioral superiority for face processing and the amplitude of the RH N170 for faces could be predicted by the magnitude of the N170 ERP response to words in the LH. These results are discussed in terms of a theoretical account in which the typical RH face lateralization fails to emerge in individuals with atypical language lateralization because of weakened competition from the LH representation of words.

Although perseveration—the inappropriate repetition of previous responses—is quite common among patients with neurological damage, relatively few detailed computational accounts of its various forms have been put forth. A particularly well-documented variety involves the pattern of errors made by “optic aphasic” patients, who have a selective deficit in naming visually presented objects. Based on our previous work in modeling impaired reading via meaning in deep dyslexia, we develop a connectionist simulation of visual object naming. The major extension in the present work is the incorporation of short-term correlational weights that bias the network towards reproducing patterns of activity that have occurred on recently preceding trials. Under damage, the network replicates the complex semantic and perseverative effects found in the optic aphasic error pattern. Further analysis reveals that the perseverative effects are strongest when the lesions are near or within semantics, and are relatively mild when the preceding object evokes no response. Like optic aphasics, the network produces predominantly semantic rather than visual errors because, in contrast to reading, there is some structure in the mapping from visual to semantic representations for objects. Viewed together with the dyslexia simulations, the replication of complex empirical phenomena concerning impaired visual comprehension based on a small set of general connectionist principles strongly suggests that these principles provide important insights into the nature of semantic processing of visual information and its breakdown following brain damage.

Significant progress has been made in understanding vision by combining computational and neuroscientific constraints. However, for the most part these integrative approaches have been limited to low-level visual processing. Recent advances in our understanding of high-level vision in the two separate disciplines warrant an attempt to relate and integrate these results to extend our understanding of vision through object representation and recognition. This paper is an attempt to contribute to this goal, by using a computational framework arising out of computer vision research to organize and interpret human and primate neurophysiology and neuropsychology.