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Neural computation and dynamics

Neural computation and dynamics

To foster survival in a dynamic world, animals must be able to quickly adapt their behavior in response to unpredictable environments. The nervous system has the ability to assign the appropriate responses to sensory stimuli according to its internal state (e.g. the subjective perception of time, emotional states) or an external context (e.g. environmental demands, social conventions). For example, when you are at the stadium attending a game and happen to see an old friend a few seats away, you will not hesitate to say “Hello!” with a loud greeting. Instead, if the fortuitous encounter happened at a library, the same greeting would be barely whispered so not to disturb readers.

The research goal of the Neural Computation and Dynamics lab is to understand the neural basis of flexible behavior by developing computational models of brain circuits. To study the synaptic and circuit mechanisms that underlie flexible behavior we employ theoretical and numerical techniques from dynamical systems, physics, and machine learning. We collaborate with experimental labs around the world to draw inspiration from their work and to test our models.

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Some of the questions that motivate our work are


How does flexible behavior emerge from neuronal interactions?
How is information encoded in the spatio-temporal pattern of neural activity?
Which mechanisms allow multiple brain regions to exchange and integrate information during perception?
How are communication pathways in the brain affected by neurological disorders?
Which features shape neural dynamics during learning and development?
How do internal brain states modulate cognitive functions such as memory and perceptual decision-making?

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Open positions

We are hiring Ph.D. students and postdoctoral fellows. Please contact us for more information.