NETWORKS WITH LATERAL CONNECTIVITY .1. DYNAMIC PROPERTIES MEDIATED BYTHE BALANCE OF INTRINSIC EXCITATION AND INHIBITION

1. We studied the rapid dynamic changes of neuron response properties in the somatosensory cortex by the use of computer simulations. The mo del consists of three feedforward layers of spiking neurons, correspon ding to skin, subcortex, and cortex structures. Measurements and analy sis of model activity throughout this work are similar to those used i n neurophysiological experiments. 2. The effects of various parameters on response properties of model neurons were investigated. The most i mportant parameters were the lateral excitation and inhibition in the simulated cortical network. 3. The balance between excitation and inhi bition is a key factor in determining the stability of the network mod el. There is a large excitation-inhibition (E-I) parameter region with in which the model can stably respond to inputs. 4. The input-output r elations and receptive field (RF) sizes of simulated neurons are modif iable by the E-I balance. The shapes of RFs are determined by both fee dforward projections and the spatial distribution of lateral connectio ns.5. We simulated changes in temporal and spatial properties of neuro ns in response to manipulations that mimic bicuculine methiodide or gl utamate application to the cortex. Simulation results agreed well with experimental data, suggesting that cortical transmitter levels play a n important role in the dynamic responses of the neural net through th eir effects on E-I balance. 6. With parameters of the model set to an inhibition-dominant scheme, the model was able to reproduce experiment ally observed rapid RF expansions that follow cortical lesion or input denervation. Simulation results also suggested that spontaneous input s to a sensory system can serve as a source of tonic inhibition in the cortex. 7. We conclude that lateral connections could produce and mai ntain a cortical network having dynamic properties without the need to invoke synaptic plasticity. Individual neuron properties could be mod ified by changing the balance of cortical layer excitation and inhibit ion. In a real brain, this could be achieved either by changing levels of cortical transmitter (gamma-aminobutyric acid, for example) or by changing tonic background input to the cortical network.