Journal of Neurophysiology, Vol 67, Issue 4 981-995, Copyright © 1992 by APS

ARTICLES

Cortical oscillations and temporal interactions in a computer simulation of piriform cortex

M. Wilson and J. M. Bower
Computation and Neural Systems Program, California Institute of Technology, Pasadena 91125.

1. A large-scale computer model of the piriform cortex was constructed on the basis of the known anatomic and physiological organization of this region. 2. The oscillatory field potential and electroencephalographic (EEG) activity generated by the model was compared with actual physiological results. The model was able to produce patterns of activity similar to those recorded physiologically in response to both weak and strong electrical shocks to the afferent input. The model also generated activity patterns similar to EEGs recorded in behaving animals. 3. In addition to replicating known physiological responses, it has been possible to use the simulations to explore the interactions of network components that might underlie these responses. This analysis suggests that the physiological properties of the cortex are dependent on the complex interaction of both network and cellular properties. In particular, we have found that the relationship between conduction velocities in intrinsic cortical fiber systems and the time constants of excitatory and inhibitory effects are critical for replicating physiological results. 4. Analysis of the model also suggests a correspondence between the 40-Hz oscillatory patterns of activity induced by low levels of odor-like stimulation and oscillatory patterns seen in lightly anesthetized cortex in response to weak electrical shocks to the afferent fiber system. 5. The specific relationships we have found between the different components of the model also support several speculations on their functional significance. The simulations suggest that during each 40-Hz cycle of EEG activity there is a convergence in rostral cortex of afferent information from the olfactory bulb and recurrent association fiber information from caudal cortex. This convergence could underlie an iterative process central to the recognition of complex olfactory stimuli.

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