Mark Histed

Neural computation and information flow in brain networks

Decoding the role of cortical recurrent connectivity in memory, perception, and decision-making

My neuroscience research is focused on understanding neural computation and information flow in brain networks. We aim to understand how groups of neurons embedded in interconnected networks process information to create thoughts, decisions, and actions. We believe causal approaches are critical for understanding highly interconnected systems like the brain. We develop cutting-edge optical methods like two-photon stimulation, which uses laser holography to allow ‘writing’ patterns of neuron activity into the brain. I am bearish that AI will take over the world but bullish that AI will help us understand the brain — that is, we seek to relate function of AI systems and brains, because AI systems are an example of large-scale netowork computation, and principles of network computation we learn from artificial intelligence systems are likely to lead to better understanding of real brains. We believe understanding computations will link genes and circuits to behavior and mental health and lead to new therapies. More details on our approach and progress are on the Research page.