The Computation and Neural Systems (CNS) research initiative at UCLA's Semel Institute for Neurosciences and Human Behavior is a translational research program within the Laboratory of Brain, Behavior, and Pharmacology. We use innovative computational methods to understand how the systems of neurons in the brain support cognition, emotion, and behavior, and how things function differently when individuals experience neuropsychiatric disorders. We've developed new algorithms for analyzing the brain's electrical activity, and have applied existing algorithms in new contexts. In particular, our approaches integrate information about

• brain structure (from MRI scans, for example)
• brain function (e.g., EEG measures of brain waves, fMRI and PET information about regional brain activity), and
• cognitive function, emotional state, or behavior

In our examination of changes in the brain that occur during normal aging, we used mathematical models to examine how the functional connectivity between brain regions is interrupted by the "subclinical structural brain disease" (SSBD) that occurs as we grow older, and that this interruption can produce subtle problems with cognition (e.g., memory complaints). The computational approach has shed information on how data from these different domains -- structure, function, and performance -- can be integrated to understand the aging process (please see this recent publication).

Connectivity and disconnection may be important factors in the pathophysiology of psychiatric disorders. We have examined some of the evidence in a recent paper and plan to conduct additional prospective investigations to build in this direction.

We are actively researching how changes in signalling in the prefrontal region of the brain after one week of treatment with antidepressant medication can predict clinical improvement after two months of treatment. You can read more about the depression clinical research program (DepressionLA.com) online, including information about participating as a research subject.