Dimitrios Pantazis

Holistic Imagery

The most widely used imaging method, functional magnetic resonance imaging (fMRI) provides precise information about where in the brain activity occurs, but it cannot detect with the same degree of precision when these events occur in the brain. This kind of temporal precision can be accomplished with magnetoencephalography (MEG), a tool developed at MIT and found in the Martinos Imaging Center at MIT.  Dimitrios Pantazis’ research helps to bridge the gap between spatial and temporal brain imaging data. Director of the MEG lab, Pantazis develops new methods for extracting neural representations from MEG data, and the development of multimodal imaging techniques that give more holistic information about brain function. Using such approaches, he gets insight into processes such as how the brain handles information in the ventral visual stream.

Ian Wickersham

Making Connections

Ian Wickersham develops genetic tools that provide more powerful and precise ways to study the organization of the brain. His lab invents techniques for targeting neurons based on their synaptic connectivity and gene expression patterns in order to cause them to express genes that allow the neurons to be studied and controlled by neuroscientists and clinicians. The goal of Wickersham’s work is to provide neuroscience with more effective ways of studying the brain, and potentially to provide clinical neurology with more effective ways of treating disorders of the brain.

Satrajit Ghosh

Personalized Medicine

A fundamental problem in psychiatry is that there are no biological markers for diagnosing mental illness or for indicating how best to treat it. Treatment decisions are based entirely on symptoms, and doctors and their patients will typically try one treatment, then if it does not work, try another, and perhaps another. Satrajit Ghosh hopes to change this picture, and his research suggests that individual brain scans and speaking patterns can hold valuable information for guiding psychiatrists and patients. His research group develops novel analytic platforms that use such information to create robust, predictive models around human health. Current areas include depression, suicide, anxiety disorders, autism, Parkinson’s disease, and brain tumors.