title: Networks with lateral connectivity. I. dynamic properties mediated by the balance of intrinsic excitation and inhibition.
abstract: 1. We studied the rapid dynamic changes of neuron response properties in the somatosensory cortex by the use of computer simulations. The model consists of three feedforward layers of spiking neurons, corresponding to skin, subcortex, and cortex structures. Measurements and analysis of model activity throughout this work are similar to those used in neurophysiological experiments. 2. The effects of various parameters on response properties of model neurons were investigated. The most important parameters were the lateral excitation and inhibition in the simulated cortical network. 3. The balance between excitation and inhibition is a key factor in determining the stability of the network model. There is a large excitation-inhibition (E-I) parameter region within which the model can stably respond to inputs. 4. The input-output relations and receptive field (RF) sizes of simulated neurons are modifiable by the E-I balance. The shapes of RFs are determined by both feedforward projections and the spatial distribution of lateral connections. 5. We simulated changes in temporal and spatial properties of neurons in response to manipulations that mimic bicuculine methiodide or glutamate application to the cortex. Simulation results agreed well with experimental data, suggesting that cortical transmitter levels play an important role in the dynamic responses of the neural net through their effects on E-I balance. 6. With parameters of the model set to an inhibition-dominant scheme, the model was able to reproduce experimentally observed rapid RF expansions that follow cortical lesion or input denervation. Simulation results also suggested that spontaneous inputs to a sensory system can serve as a source of tonic inhibition in the cortex. 7. We conclude that lateral connections could produce and maintain a cortical network having dynamic properties without the need to invoke synaptic plasticity. Individual neuron properties could be modified by changing the balance of cortical layer excitation and inhibition. 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.
authors.affiliation: Department of Neuroscience, University of Pennsylvania, Philadelphia 19104, USA.
authors.forename: J
authors.initials: J
authors.lastname: Xing
authors.forename: G L
authors.initials: GL
authors.lastname: Gerstein
mesh_terms: D000344:Afferent Pathways / Q000502:physiology; D000818:Animals; D007839:Functional Laterality / Q000502:physiology*; D006801:Humans; D009433:Neural Inhibition / Q000502:physiology*; D016571:Neural Networks, Computer; D009474:Neurons / Q000502:physiology; D011984:Sensory Receptor Cells / Q000502:physiology; D012867:Skin / Q000294:innervation; D013003:Somatosensory Cortex / Q000502:physiology*; D009435:Synaptic Transmission / Q000502:physiology*; D005680:gamma-Aminobutyric Acid / Q000502:physiology
chemical_list: D005680:gamma-Aminobutyric Acid