Decoding internal state to predict behavior

The behavioral repertoire of any animal is ultimately determined by the activity of its brain cells. Yet, how exactly neural activity leads to actions remains unknown. Which patterns of neuronal activity trigger which behavior? How does an animal string together many actions to accomplish a goal? Understanding these processes will not be trivial, and will require deep insight into animal behavior, recordings of the activity of many neurons at once, and sophisticated mathematical models. We propose a collaboration among three laboratories to bring these techniques to bear on such fundamental questions in neuroscience. Working in mice, we will use a novel system to record the electrical activity of many neurons at once while simultaneously monitoring a freely-moving mouse’s posture in 3D. We can then use mathematical models to determine how neural activity relates to the mouse’s movements. We will specifically focus on a brain area known as the striatum, and look to see if the mouse’s voluntary choices to move are reflected in neural activity in the striatum. In this way, we can address the fundamental question of how an animal’s behavioral state is represented in neural circuits. Given the similarities in brain structure between mice and humans—though the mouse brain is of course far less complex—we expect our insights to apply to humans as well.

Bernardo Sabatini, Harvard Medical School

Ryan Adams, Harvard University

Sandeep Datta, Harvard Medical School