title: Spatial firing patterns of auditory neuron network modelling by computer simulation.
abstract: This communication examines, in digital computer simulated network, input signals and response patterns established at excitatory neurons' level i.e. the membrane potential of neuron soma. It is restricted to spatial patterns of the auditory neuron networks and time factor for nervous conduction and transmission is neglected compared with long maintained membrane potentials of neuron somas. The model analyzes the change in the spatial patterns of the membrane potential in the two dimensional networks of the auditory system. In order to evaluate the contribution of the various parameters, it is started that the simplest model has only one parameter, lateral inhibition. The other parameters are then added, one at a time, to successive models. The lateral inhibition is a necessary condition in the auditory nervous system if any sharpening of the response areas in the single neurons is to occur. A necessary condition for the validity of the model is that is should be applicable to the other senses such as vision and chemical patterns, taste. The threshold feature of auditory neurons aids in producing a sharpening in the neuron of the auditory relay nuclei. It does this clipping the spatial response patterns in one dimensional arrays of excitatory neurons. Recurrent inhibition seems a necessary condition in the sensory nervous system that any kinds of input signals are to be preserved over a wide range of stimulus intensity. In other words, this network has a wide dynamic range against any kinds of input signals. A simple self-recurrent negative feedback does not contribute to the sharpening, but more complex socalled averaged type does. A neuron network is capable of responding stably to stimuli with a wide range of intensity and with any kind of spatial patterns if there is a simple negative feedback mechanism. When there is no negative feedback, input signals soon disappear or saturate in the neuron network. Therefore, recurrent inhibition is the most important mechanism. Spontaneous activity appears to aid in the sharpening by providing a kind of contrast, that is by reducting the amount of activity in neurons adjacent to the excitatory area. Moreover, the effect of spontaneous activity in the model seems to make repples around the excitatory area and suggests that an introduction of activity at any stage of the networks, from whatever source for example reticulum formation and thalamus, might appreciably alter the response patterns at subsequent neuron network. This suggests that the mechanism of the consciousness that might be controlled by the thalamus and or reticular formation. These two dimensional neuron networks may be expanded to three dimensional neuron networks. The former might simulate the auditory nervous system while the latter might simulate the visual system.
mesh_terms: D000818:Animals; D001303:Auditory Cortex / Q000502:physiology; D001306:Auditory Pathways / Q000502:physiology*; D001309:Auditory Threshold / Q000502:physiology; D003201:Computers; D004056:Differential Threshold; D005246:Feedback; D006801:Humans; D008564:Membrane Potentials; D008959:Models, Neurological; D009433:Neural Inhibition; D009474:Neurons / Q000502:physiology*; D009475:Neurons, Afferent / Q000502:physiology; D009435:Synaptic Transmission