Title: Stochastic Neural Dynamics and Information Processing in the Autistic Brain
Speaker: Roberto Fernández Galán (Case Western Reserve University)
Abstract: I will show that large-scale brain dynamics at rest can be accurately modeled with a multivariate Ornstein-Uhlenbeck process (mOUP). This allows me to: 1) define functional connectivity in a rigorous way as the drift operator; 2) determine the stochastic inputs driving the brain as the stochastic term of the mOUP. Applying this method to magnetoencephalography (MEG) data from children with and without autism I found that functional connectivity in children with autism is mainly altered between frontal and parietal/occipital areas with increased excitation relative to controls. In addition, the spatial distribution of stochastic inputs is significantly more homogeneous and less complex. Determining the stochastic inputs also allows one to quantify the information gain, or the amount of information that the brain creates spontaneously at rest. The information gain is significantly higher in children with autism. Finally, I will discuss the relevance of these findings and their interpretation from a cognitive science perspective.