Bringing together the fields of brain research and artificial intelligence to reveal the operating principles of the brain.
The Rajan lab uses mathematical and computational models based on data collected from neuroscience experiments to design an artificial system that performs realistic behaviors using only the biological machinery that the nervous system has access to. By ‘reverse engineering’ these artificial systems, we can reveal the dynamics behind the same behaviors in the real brain.
vision
The Rajan lab pioneers new techniques that combine machine learning/AI with biological insights to uncover the fundamental drivers of natural and artificial intelligence.
Our team merges multiple disciplines to tackle the biggest unsolved problems in neuroscience.
research
Social neuroscience research has focused mainly on paired organisms, missing a major aspect of social cognition: the moment-by-moment balancing of individual, social, and environmental factors when working in groups.
Defining the neural mechanisms for processing the informational complexity of social dynamics will translate to practical applications for human health, organizational well-being, and societal cohesion.
impact
Our models have the power to extend our understanding beyond a single experiment, task, or brain region.
Flexible models like ours reveal the underlying design principles of real brains responsible for producing and mediating time-varying behaviors.
Our integrative theories and models have the potential to transform the way we study the brain by making specific, quantifiable predictions.
Our models of simulated brain activity are based on real experimental data from real brains. Using experimental data to directly shape theoretical models, we are able to make better, quantifiable predictions about how brains are likely to behave under different conditions.
Research
Our lab works to understand how cognitive behaviors such as learning, remembering, and deciding emerge from multi-scale neural processes and how these processes are conserved across species.
People
We are a diverse group of scientists and engineers with a passion for the science of how the brain works and a deep commitment to open and inclusive science.
Publications
Our publications span studies on recurrent neural networks, reinforcement learning, and modeling tools that can be applied broadly in computational neuroscience.
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