A neurocomputational approach to delusions

Neuronal networks process information in parallel. The cortex can be viewed as a computational surface that creates and maintains dynamic maps of representations of important sensorimotor and higher-level aspects of the environment and the organism. Its functions can be modeled by a particular type of neural network, the self-organizing feature map. Most importantly, representations of information in the cortex and in these maps have been demonstrated to change dynamically according to the salience and frequency of the input. This feature is referred to as neuroplasticity. The fact that general operational characteristics of computational maps in the cortex can be fine-tuned according to specific processing needs is referred to as neuromodulation. Within this framework of cortical maps and their computational models, acute and chronic delusions are discussed in terms of neuromodulation and neuroplasticity. This neurocomputational approach provides new insights into the phenomena in question, is detailed enough to allow empirical testing, and has therapeutic implications.