Instability in attractor neural network dynamics and schizophrenia
Building on a theory of hippocampal function in episodic memory, and on a stochastic dynamics approach to integrate-and-fire neuronal attractor networks that can implement short and long term memory, implications for understanding the stability of such systems in schizophrenia are described. A decrease in the NMDA receptor conductances, consistent with hypofunction of the NMDA receptor system in schizophrenia, reduces the depth of the attractor basins, decreases the stability of short term memory states and increases distractibility. The cognitive symptoms of schizophrenia such as distractibility, working memory deficits or poor attention could be caused by this instability of attractor states in prefrontal cortical networks. Lower firing rates are also produced, and in the orbitofrontal and anterior cingulate cortex could account for the negative symptoms including a reduction of emotion. Decreasing the GABA as well as the NMDA conductances produces not only switches between the attractor states, but also jumps from spontaneous activity into one of the attractors. This is related to the positive symptoms of schizophrenia including delusions, paranoia, and hallucinations, which may arise because the basins of attraction are shallow and there is instability in temporal lobe memory networks, leading thoughts to move too freely round the attractor energy landscape.
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