Forough Habibollahi

This paper develops a differentiation protocol to generate human hippocampal neurons and astrocytes in vitro, demonstrating long-term viability and electrophysiological complexity.

This study evaluates how neural architecture, network dynamics, and decoding methods affect handwritten digit classification using human iPSC-derived neuronal networks.

This study demonstrates that human neural organoids exhibit features of learning and memory by showing synaptic plasticity, criticality, and receptor expression.

The paper tests anti-seizure drugs on a synthetic neural system and finds carbamazepine improves gameplay metrics, linking glutamatergic inhibition to enhanced performance.

The paper shows that hippocampal neural networks approach criticality during a cognitive task but move away from criticality with memory impairment induced by scopolamine.

The paper shows that in vitro neuronal networks exhibit critical dynamics when receiving structured sensory input during a task, with better performance linked to proximity to critical states.

The paper demonstrates that in vitro neurons can learn and exhibit goal-directed behavior in a simulated game environment.

The paper introduces a neural network Poisson model to analyze neural spike train data and behavioral tasks, showing improved performance over previous methods.