Kishore V. Kuchibhotla,PHD

Assistant Professor, Psychological and Brain Sciences, Neuroscience and Biomedical Engineering

Specialization: Neural circuits for context, learning and decision-making


Johns Hopkins University

Ames Hall 221

3400 N. Charles Street

Baltimore, MD 21218

More Info

Humans and other animals have a remarkable ability to flexibly adjust their actions based on external stimuli, environmental context and internal brain state. How does context influence learning and the expression of underlying knowledge?

Some context-dependent responses may be maladaptive; for example, anxiety may repress the recollection of information under stressful conditions. Others may be adaptive, enabling discretion and choice in the face of risk or opportunity. More broadly, contextual factors, related to brain state and cost-benefit calculations, weigh on behavioral decisions and impact the interpretation of self-reported knowledge. Thus, it is crucial to disambiguate the effects of context from knowledge when interpreting performance, particularly during learning.

My lab studies the neural circuits and dynamics that enable learning, with an emphasis on the role of context and brain state. We first aim to gain behavioral control of learning-related phenomena using quantitative assessment of mouse behavior. We then apply the modern tools of neuroscience to monitor, manipulate and model neural networks to determine how the brain implements learning-related computations. We have a particular interest in the role of neuromodulation, including cholinergic and noradrenergic, in cortical and subcortical circuits.

We also apply insights from neural circuit research to disease states. In Alzheimer’s disease (AD), for example, familiar contexts can trigger episodes of lucidity even when patients are deep in cognitive decline. AD may impinge on the learning processes we study, but in reverse. Knowledge may exist in the AD brain but become inaccessible. Can this ‘hidden’ knowledge be unlocked? These momentary retrievals may reflect activation of context-dependent mechanisms and could be ripe for therapeutic intervention to improve cognition. More generally, neuroscience research that introduces a robust dialectic between the study of healthy and diseased cognitive states will undoubtedly reveal deeper insights into both.


To advance neuroscience discovery by uniting neuroscience, engineering and computational data science to understand the structure and function of the brain.