Networks with lateral connectivity. III. Plasticity and reorganization of somatosensory cortex

1. Mechanisms underlying cortical reorganizations were studied using a three-layered neural network model with neuronal groups already formed in the cortical layer. 2. Dynamic changes induced in cortex by behavioral training or intracortical microstimulation (ICMS) were simulated. Both manipulations resulted in reassembly of neuronal groups and formation of stimulus-dependent assemblies. Receptive fields of neurons and cortical representation of inputs also changed. Many neurons that had been weakly responsive or silent became active. 3. Several types of learning models were examined in simulating behavioral training, ICMS-induced dynamic changes, deafferentation, or cortical lesion. Each learning model most accurately reproduced features of experimental data from different manipulations, suggesting that more than one plasticity mechanism might be able to induce dynamic changes in cortex. 4. After skin or cortical stimulation ceased, as spontaneous activity continued, the stimulus-dependent assemblies gradually reverted into structure-dependent neuronal groups. However, relationships among individual neurons and identities of many neurons did not return to their original states. Thus a different set of neurons would be recruited by the same training stimulus sequence on its next presentation. 5. We also reproduced several typical long-term reorganizations caused by pathological manipulations such as cortical lesions, input loss, and digit fusion. 6. In summary, with Hebbian plasticity rules on lateral connections, the network model is capable of reproducing most characteristics of experiments on cortical reorganization. We propose that an important mechanism underlying cortical plastic changes is formation of temporary assemblies that are related to receipt of strongly synchronized localized input. Such stimulus-dependent assemblies can be dissolved by spontaneous activity after removal of the stimuli.