Synchronized oscillation in a modular neural network composed of columns

Abstract

The columnar organization is a ubiquitous feature in the cerebral cortex. In this study, a neural network model simulating the cortical columns has been constructed. When fed with random pulse input with constant rate, a column generates synchronized oscillations, with a frequency varying from 3 to 43 Hz depending on parameter values. The behavior of the model under periodic stimulation was studied and the input-output relationship was non-linear. When identical columns were sparsely interconnected, the column oscillator could be locked in synchrony. In a network composed of heterogeneous columns, the columns were organized by intrinsic properties and formed partially synchronized assemblies.Keywords: cortical column, synchronized oscillation, Rose-Hindmarsh model. DOI: 10.1360/03yc0240Since it was first reported in 1957 [1] , the columnar organization has been found in somatic sensory cortex, visual cortex, auditory cortex, motor cortex and association cortex of various different species including mice, rat, cats, rabbits, monkeys and humans [2] . These experimental findings strongly supported that the cortical columns are basic anatomical and physiological units of the cortex and suggested that columns might be of fundamental importance for the function of the brain [2,3] .Mathematical models were constructed and simulated to investigate the biological function of the column in the information processing in the brain. Wilson-Cowan model [4] is most frequently used to simulate the electrophysiological activities of the cortical columns in the previous studies. For example, Schuster et al. [5] proposed a columnar model to simulate the synchronized oscillation discovered in visual cortex. Jansen [6,7] presented a mathematical model of coupled cortical columns which produced EEG-like waveform and evoked potentials. Fukai [8] designed a network model in columnar structure to simulate visual pattern retrieval. Some of the column models are phase models which assume a column as an oscillator and simulate mere the phase of oscillating activities [9,10] .There has been few modeling of columns based on spiking single neurons. By replacing the single cell as the functional unit by multiple cells in cortical columns, an attractor network model was constructed and simulated to perform associative memory [11] . Hansel and Sompolinsky [12] constructed a hypercolumn model according to the physiological organization in the orientation columns in visual cortex. The synchronous and chaotic activities in the hypercolumn were studied and the model was used to explore the cortical mechanisms for orientation selectivity.

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