The callosal dilemma: explaining diaschisis in the context of hemispheric rivalry via a neural network model.

It is often suggested that a major factor in diaschisis is the loss of transcallosal excitation to the intact hemisphere from the lesioned one. However, there is long-standing disagreement in the broader experimental literature about whether transcallosal interhemispheric influences in the human brain are primarily excitatory or inhibitory. Some experimental data are apparently better explained by assuming inhibitory callosal influences. Past neural network models attempting to explore this issue have encountered the same dilemma: in intact models, inhibitory callosal influences best explain strong cerebral lateralization like that occurring with language, but in lesioned models, excitatory callosal influences best explain experimentally observed hemispheric activation patterns following brain damage. We have now developed a single neural network model that can account for both types of data, i.e., both diaschisis and strong hemisphere specialization in the normal brain, by combining excitatory callosal influences with subcortical cross-midline inhibitory interactions. The results suggest that subcortical competitive processes may be a more important factor in cerebral specialization than is generally recognized.

Interhemispheric effects of simulated lesions in a neural model of single-word reading.

A neural model consisting of paired cerebral hemispheric regions interacting via homotopic callosal connections was trained to generate pronunciations for 50 monosyllabic words. Lateralization of this task occurred readily when different underlying cortical asymmetries were present. Following simulated focal cortical lesions of systematically varied sizes, acute changes in the distribution of cortical activation were found to be most consistent with experimental data when interhemispheric interactions were assumed to be excitatory. During subsequent recovery, the contribution of the unlesioned hemispheric region to performance improvement was a function of both the amount of preexisting lateralization and the side and size of the lesion. These results are discussed in the context of unresolved issues concerning the mechanisms underlying language lateralization, the nature of interhemispheric interactions, and the role of the nondominant hemisphere in recovery from adult aphasia.

Computational studies of lateralization of phoneme sequence generation.

The mechanisms underlying cerebral lateralization of language are poorly understood. Asymmetries in the size of hemispheric regions and other factors have been suggested as possible underlying causal factors, and the corpus callosum (interhemispheric connections) has also been postulated to play a role. To examine these issues, we created a neural model consisting of paired cerebral hemispheric regions interacting via the corpus callosum. The model was trained to generate the correct sequence of phonemes for 50 monosyllabic words (simulated reading aloud) under a variety of assumptions about hemispheric asymmetries and callosal effects. After training, the ability of the full model and each hemisphere acting alone to perform this task was measured. Lateralization occurred readily toward the side having larger size, higher excitability, or higher-learning-rate parameter. Lateralization appeared most readily and intensely with strongly inhibitory callosal connections, supporting past arguments that the effective functionality of the corpus callosum is inhibitory. Many of the results are interpretable as the outcome of a "race to learn" between the model's two hemispheric regions, leading to the concept that asymmetric hemispheric plasticity is a critical common causative factor in lateralization. To our knowledge, this is the first computational model to demonstrate spontaneous lateralization of function, and it suggests that such models can be useful for understanding the mechanisms of cerebral lateralization.