The brain is a complex system processing information in a highly distributed, parallel manner. At the microscopic scale, this information is encoded by groups of individual neurons. These local microcircuits are interconnected within larger scale circuits across the brain and the dynamic information exchange across these multiple organization levels is likely to be crucial for brain function.
Despite its importance, very little is known about how neurons exchange information across these scales and it is important, to this extent, to complement the work done by experimental neuroscientists with modelling and data analysis tools.
During MoWS I have worked on the development of an information theoretical toolbox for the analysis of large-scale neural data. The software provides a comprehensive set of tools for researchers to analyze and understand the information processing properties of neural systems at various spatial scales, both in physiological and pathological conditions. This is important because understanding how a healthy brain processes information can help us understand diseases and disorders such as Autism Spectrum Disorders, Alzheimer's, Parkinson's, and Epilepsy.
The overall objectives of this research are to develop a set of tools that can be used to analyze large-scale neural data, and to provide insights into how the brain processes information. By doing so, this research can help researchers to better understand the neural mechanisms underlying brain function and dysfunction, which may ultimately lead to the development of better treatments for neurological diseases and disorders.
