Anandita De

Control of cortical population activity with patterned microstimulation

This paper introduces REACH-Ctrl, a data-driven method for real-time control of cortical population activity using microstimulation and multi-electrode recordings, achieving high accuracy in macaque prefrontal cortex.

Towards model-based design of causal manipulations of brain circuits with high spatiotemporal precision

The paper introduces a method to design spatiotemporal stimulation patterns for neural circuits using dynamical systems and data-driven approaches to improve efficacy and selectivity.

Population-level temporal decoding and dynamical structure in frontostriatal circuits during decision making

The paper decodes temporal dynamics in frontostriatal circuits during decision making, identifying two dynamical motifs and a selective reorganization in the frontal orienting field at decision commitment.

Common population codes produce extremely nonlinear neural manifolds

The paper shows that neural population activity data from common coding schemes form highly nonlinear manifolds, making linear methods like PCA ineffective for capturing true structure.

Computational Model for Biological Neural Network for Localisation of Sound in the Vertical Plane

The paper develops a computational rate model of a neural network involved in vertical sound localization and shows it reproduces neuronal responses to different sound types.