Shushruth Shushruth, Ph.D.

  • Assistant Professor, Neuroscience


Research summary:

Our main interest is in understanding how abstract properties of sensory information (say, the color of an object or its direction of motion) are stored and used to guide actions.

We are interested in abstraction for two reasons:

  • Abstraction is an essential substrate of thought, language and most higher order cognitive functions. It endows near infinite flexibility to our actions, allowing us to construct and follow instructions like "Press the red button if you saw something moving to the right". We investigate how such complex computations transpire in the neural networks of the brain. 
  • Abstraction is affected in psychiatric and neurological disorders of higher order cognition. By understanding the computations underlying abstraction, we hope to gain insights into their pathologies. We are particularly interested in thought disorders (e.g., Schizophrenia) and early dementia (e.g., MCI). 

            To study abstraction, we train animals to decide on abstract properties of ambiguous sensory stimuli. We record neural activity in their brain while they are making such decisions to understand the underlying computations. In parallel, we work with human patients, using the same behavioral tasks as the animals, to characterize deficits in abstract decision-making. Our ultimate goal is to develop animal models of these deficits using causal manipulation techniques (e.g., pharmacology and chemogenetics).

Representative publications:

  • Shushruth S et al. Sequential sampling from memory underlies action selection during abstract decision making. Current Biology (2022).
  • Jeurissen D*, Shushruth S*, et al. Deficits in decision-making induced by parietal cortex inactivation are compensated at two time scales. Neuron (2022). 

Lab Website: