Apoorva Bhandari

The paper investigates how task context is encoded in the brain using fMRI data, finding that context is widely represented across the cortex and interacts with specific brain regions involved in attention and control.

The paper shows the entorhinal cortex encodes a cognitive map of social networks, enabling social navigation and information diffusion tracking.

The paper investigates how transient high-dimensional neural geometry supports stable conjunctive subspaces for context-dependent action selection in humans using EEG decoding.

The paper shows that people build and refine cognitive maps of social networks through learning and rest, improving social navigation accuracy.

This study shows how the human lateral prefrontal cortex uses different geometric representations for flat and hierarchical tasks, enhancing separability and abstract encoding of task-relevant variables.

This study shows that uncertainty aversion leads to more differentiated semantic representations, reflected in neural activity patterns and behavioral outcomes.

This paper shows that positive noise correlations among similarly tuned neurons can improve the speed and robustness of readout learning in neural networks.

The paper investigates the neural mechanisms of control policy implementation by distinguishing it from rule learning using fMRI and behavioral experiments.

The paper estimates the base rate of decoding information from human prefrontal cortex BOLD signals and finds it significantly lower than visual sensory cortex.

The paper demonstrates that working memory gating policies can be transferred across task contexts, highlighting their role in flexible behavior and task generalization.