To know, together.

Our goal is to understand human cognition.

Cognition :: cognoscere ::
co [together] + gnoscere [to know]

“Scientific interest in the brain originated in the magic of the mind. Neuroscience as a field then branched off into subfields studying the brain at different scales, using different tools and concepts, and affiliating with different neighboring disciplines. This has led to rapid progress in recent decades. Now is the time to reunite these subfields and together address the founding aspiration of neuroscience—to reveal the inner workings of the mind through an integrated understanding of the brain. Achieving this integration across scales, tools, and disciplines with data science will enable powerful new theories and insights about what makes us human.”

—Nicholas Turk-Browne, Director of the Wu Tsai Institute and Professor of Psychology

Our Story

Research

The Wu Tsai Institute supports three innovative research centers united by common purpose and shared resources, representing complementary perspectives on cognition.

Neurocognition and Behavior

How does the brain generate behavior? Cognition refers to dynamic aspects of the mind such as attending, remembering, deciding, and communicating. Deciphering how different systems in the brain support and modulate these processes could explain why we perform well at some times and struggle at others; identifying good and bad brain states could enable methods to gain better control of our mind.

Neurodevelopment and Plasticity

How does the brain change as it develops? Early in life countless molecules and cells assemble themselves into the circuits that underlie cognition. Exploring this remarkable ability of the brain to grow and adapt through experience could reveal how we store and retain knowledge; understanding how this plasticity works and why it decreases with age could be used to improve learning later in life.

Neurocomputation and Machine Intelligence

How does the brain compute cognition? Artificial models employ different architectures and algorithms to excel at specialized tasks. Using these models to translate and integrate neuroscience data across scales and techniques could uncover general principles of brain function; grounding models in these abstractions could imbue machine intelligence with the richness and flexibility of cognition.

An ambitious research enterprise devoted to the study of human cognition will supercharge Yale’s neuroscience initiative and position the university to reveal the brain in its full, dynamic complexity.

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