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The Hopfield network, a point attractor network, is modified here to investigate the behavior of the resting state challenged with varying degrees of noise.

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NMikolajewicz/Hallucination-susceptible-Hopfield-network

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Hallucination-susceptible-Hopfield-network

Schizophrenia is a complex condition, affected by a multiplex of neuronal abnormalities that can lead to the manifestation of hallucinations.

This project explores these mechanisms and provides the rationale to reduce the underlying biological drivers to a single metric, a reduced signal to noise ratio (SNR).

The Hopfield network, a point attractor network, is modified here to investigate the behaviour of the resting state challenged with varying degrees of noise. If analogous attractor networks are present within the nervous system, a reduction in the SNR, which effectively reduces the barriers to traversing an energy landscape, may serve to explain how hyper excitability and spontaneous activation of internally stored states contribute to the manifestation of hallucinations in individuals affected by schizophrenia.

Refer to the FINAL REPORT document for a detailed description of methods and report of results.

Results reported in the FINAL REPORT can be reproduced by running the MAIN matlab script file.

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The Hopfield network, a point attractor network, is modified here to investigate the behavior of the resting state challenged with varying degrees of noise.

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