Mechanisms underlying category learning in the human ventral occipito-temporal cortex.

The human ventral occipito-temporal cortex (VOTC) has evolved into specialized regions that process specific categories, such as words, tools, and animals. The formation of these areas is driven by bottom-up visual and top-down nonvisual experiences. However, the specific mechanisms through which top-down nonvisual experiences modulate category-specific regions in the VOTC are still unknown. To address this question, we conducted a study in which participants were trained for approximately 13 h to associate three sets of novel meaningless figures with different top-down nonvisual features: the wordlike category with word features, the non-wordlike category with nonword features, and the visual familiarity condition with no nonvisual features. Pre- and post-training functional MRI (fMRI) experiments were used to measure brain activity during stimulus presentation. Our results revealed that training induced a categorical preference for the two training categories within the VOTC. Moreover, the locations of two training category-specific regions exhibited a notable overlap. Remarkably, within the overlapping category-specific region, training resulted in a dissociation in activation intensity and pattern between the two training categories. These findings provide important insights into how different nonvisual categorical information is encoded in the human VOTC.

Hemispheric lateralization of language processing: insights from network-based symptom mapping and patient subgroups.

The hemispheric laterality of language processing has become a hot topic in modern neuroscience. Although most previous studies have reported left-lateralized language processing, other studies found it to be bilateral. A previous neurocomputational model has proposed a unified framework to explain that the above discrepancy might be from healthy and patient individuals. This model posits an initial symmetry but imbalanced capacity in language processing for healthy individuals, with this imbalance contributing to language recovery disparities following different hemispheric injuries. The present study investigated this model by analyzing the lateralization patterns of language subnetworks across multiple attributes with a group of 99 patients (compared to nonlanguage processing) and examining the lateralization patterns of language subnetworks in subgroups with damage to different hemispheres. Subnetworks were identified using a whole-brain network-based lesion-symptom mapping method, and the lateralization index was quantitatively measured. We found that all the subnetworks in language processing were left-lateralized, while subnetworks in nonlanguage processing had different lateralization patterns. Moreover, diverse hemisphere-injury subgroups exhibited distinct language recovery effects. These findings provide robust support for the proposed neurocomputational model of language processing.