Pragathi Priyadharsini Balasubramani

This study examines cognitive strain in Mild Cognitive Impairment by analyzing behavioral and neural responses during a spatial navigation task under varying memory load.

This paper introduces a reinforcement learning-based deep neural network model to simulate multiple cognitive functions and demonstrates its potential as a testbench for cognitive impairment research.

The paper develops a reward decision-making task and analyzes behavioral, computational, and neural correlates of reward maximization and melioration using EEG in 186 healthy adults.

This paper introduces a mobile platform called BrainE for rapid, scalable EEG-based assessment of multiple cognitive tasks and demonstrates its reliability and sensitivity to neural plasticity and mental health symptoms.

The paper investigates shared neural mechanisms in orbitofrontal cortex for inhibition and economic choice using macaque neural recordings and decoders.

This study develops a computational model of the basal ganglia to simulate bipolar oscillations between positive and negative mood states by analyzing reward and risk sensitivity.

This study identifies distinct neural ensemble patterns in the orbitofrontal cortex that differentiate successful from failed inhibition during a stop signal task in macaques.

This study shows that orbitofrontal cortex activity predicts both economic choice and stopping in macaques, suggesting shared neural processes for these tasks.