The question was investigated whether longlasting transients of activity, observed to occur in the intact cerebral cortex (EEG slow (δ) waves and ‘K’ complexes) as well as in isolated tissues cultured in vitro, can also emerge in a model network of excitatory and inhibitory cells. We show that such transients can indeed occur even if the cells do not have built-in slow kinetics. For certain parameter settings, the network is in a bistable state in which periods of increased activity (long-lasting transients) alternate with minimal activity. Transients are triggered by spontaneously firing cells (‘noise’), which, rather than via a build-up of recurrent synaptic inhibition, also initiate their termination. During a transient, the network continually makes transitions from one equilibrium to another as a result of spontaneous firing until it is switched back to the quiescent state, i.e., after a variable period of time of noise-induced transitions the transient is terminated. If the network is small, activity can terminate even without inhibition. In large networks, inhibition keeps the network sensitive to spontaneously firing cells by holding it in the neighbourhood of a critical point between active and quiescent state.
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van Ooytien, A., van Pelt, J., Corner, M.A. et al. The emergence of long-lasting transients of activity in simple neural networks. Biol. Cybern. 67, 269–277 (1992). https://doi.org/10.1007/BF00204400
- Neural Network
- Cerebral Cortex
- Model Network
- Large Network
- Variable Period