Neural Network Simulation of Somatosensory Representational Plasticity

The brain represents the skin surface as a topographic map in the somatosensory cortex. This map has been shown experimentally to be modifiable in a use-dependent fashion throughout life. We present a neural network simulation of the competitive dynamics underlying this cortical plasticity by detailed analysis of receptive field properties of model neurons during simulations of skin coactivation, cortical lesion, digit amputation and nerve section. 1 INTRODUCTION Plasticity of adult somatosensory cortical maps has been demonstrated experimentally in a variety of maps and species (Kass, et al., 1983; Wall, 1988). This report focuses on modelling primary somatosensory cortical plasticity in the adult monkey. We model the long-term consequences of four specific experiments, taken in pairs. With the first pair, behaviorally controlled stimulation of restricted skin surfaces (Jenkins, et al., 1990) and induced cortical lesions (Jenkins and Merzenich, 1987), we demonstrate that Hebbian-type dynamics is sufficient to account for the inverse relationship between cortical magnification (area of cortical map representing a unit area of skin) and receptive field size (skin surface which when stimulated excites a cortical unit) (Sur, et al., 1980; Grajski and Merzenich, 1990). These results are obtained with several variations of the basic model. We conclude that relying solely on cortical magnification and receptive field size will not disambiguate the contributions of each of the myriad circuits known to occur in the brain. With the second pair, digit amputation (Merzenich, et al., 1984) and peripheral nerve cut (without regeneration) (Merzenich, ct al., 1983), we explore the role of local excitatory connections in the model Neural Network Simulation of Somatosensory Representational Plasticity S3