Jyotika Bahuguna

Forschungszentrum Jülich, Indian Institute of Technology Hyderabad

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About

Jyotika Bahuguna’s research bridges computational neuroscience and robotics, with a primary focus on understanding the neural mechanisms underlying action selection and decision-making. Her most cited work, "Exploring the role of striatal D1 and D2 medium spiny neurons in action selection using a virtual robotic framework" (2018, 19 citations), provides a pioneering computational model that demonstrates how the direct and indirect pathways of the basal ganglia—mediated by D1 and D2 neurons—interact to resolve competition between motor programs. This work offers a biologically grounded framework for designing more adaptive robotic controllers. Earlier in her career, Bahuguna contributed to multi-robot systems with her paper "MDP based active localization for multiple robots" (2009, 3 citations), which introduced a Markov decision process approach to actively guide robots in disambiguating location hypotheses in feature-poor environments. Her interdisciplinary approach—combining reinforcement learning, neural modeling, and robotics—has made her a notable figure in neurorobotics. By translating insights from striatal circuitry into virtual robotic architectures, Bahuguna’s work not only advances our understanding of basal ganglia function but also inspires new algorithms for autonomous systems operating under uncertainty.