[Brainmap] Tal Kenet PhD, Title: Using MEG to decipher functional connectivity abnormalities in autism, and map the normal development of resting state networks

Using MEG to decipher functional connectivity abnormalities in autism, and map the normal development of resting state networks

In the first part of the talk, I will discuss our findings on abnormal cortical functional connectivity in autism. Like several other psychiatric and neurological disorders, autism has been characterized by abnormal functional connectivity. The nature of these abnormalities has been elusive though, with findings of both abnormally increased and decreased connectivity patterns, mostly using fMRI. Additionally, while it has been commonly thought that local functional connectivity is increased in autism, there was no direct evidence in support of this hypothesis. Using MEG, we are finding evidence that local functional connectivity is decreased, not increased, in autism. In parallel, we are finding evidence of increased long-range functional connectivity in the feedforward direction, alongside increased long-range functional connectivity in the feedback direction.

In the second part of the talk, I will discuss work in progress to map out resting state networks in normal development, from ages 7 to 29, with spectral specificity, using graph theory. While multiple groups have mapped this developmental path using fMRI, MEG makes it possible to separate between cortical resting state networks mediated by different frequency bands. We are finding distinctly different developmental trajectories in different frequency bands, impacting local and global efficiency, resilience, and small world properties of the networks differentially. Potential implications of these finding in normal development to developmental and psychiatric disorders will also be discussed.