Computational Approach to the Schizophrenia

It has been hypothesized that some schizophrenic phenomena are best understood in terms of abnormal interactions between different brain regions. Preliminary data suggest that during associative learning task hippocampus is involved in the encoding (learning) and the prefrontal cortex in the retrieval of associative memories. Specific changes in the fMRI activities have also been observed based on comparative studies between stable schizophrenia patients and healthy control subjects. Disconnectivity, observed between brain regions in schizophrenic patients could result from abnormal modulation of N-methyl-D-aspartate (NMDA)-dependent plasticity implicated in schizophrenia.


Cooperation with
Vaibhav A. Diwadkar

Our initial modeling efforts were directed toward a simple model to simulate the behavioral associative learning task, with model output as learning curves depicting performance over each iteration of recall. As will be evident, the model incorporates the separation between encoding/consolidation and cued recall while also retaining biological plausible relationships between model architecture and neural systems, as well as known learning parameters in the brain. In particular, the model accounts for (i) the separation between "where" and "what" regions (ii) reduced synaptic plasticity in schizophrenia and reduced cognitive capacity in schizophrenia.

A model has been built order to compare the (i) activities with the fMRI data; (ii) the performance with the behavioral data.

Publications:

P. Érdi, B. Ujfalussy, L. Zalányi, VA. Diwadkar: Computational approach to schizophrenia: Disconnection syndrome and dynamical pharmacology. In: A selection of papers of The BIOCOMP 2007 International Conference L. M. Ricciardi (ed.) Proceedings of the American Institute of Physics (accepted for publication)





bognor@kzoo.edu
Last update 23.04.2008.