Computational studies of lateralization of phoneme sequence generation
Neural Computation
A Neural Network Model of Lateralization during Letter Identification
Journal of Cognitive Neuroscience
A Computational Model of Lateralization and Asymmetries in Cortical Maps
Neural Computation
Towards Novel Neuroscience-Inspired Computing
Emergent Neural Computational Architectures Based on Neuroscience - Towards Neuroscience-Inspired Computing
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Current understanding of the origins of cerebral specialization is fairly limited. This chapter summarizes some recent work developing and studying neural models that are intended to provide a better understanding of this issue. These computational models focus on emergent lateralization and also hemispheric interactions during recovery from simulated cortical lesions. The models, consisting of corresponding left and right cortical regions connected by the corpus callosum, handle tasks such as word reading and letter classification. The results demonstrate that it is relatively easy to simulate cerebral specialization and to show that the intact, non-lesioned hemisphere is often partially responsible for recovery. This work demonstrates that computational models can be a useful supplement to human and animal studies of hemispheric relations, and has implications for better understanding of modularity and robustness in neurocomputational systems in general.