Gloria Cecchini

The paper shows that locally balanced inhibition prevents synaptic weight over-strengthening in feedforward networks with Hebbian plasticity, maintaining robust learning when input-output correlations are weak.

This paper introduces a biophysically plausible decision-making model using interacting neural populations in cortical layer 2/3, tested on human and macaque experiments.

The paper shows that Hebbian learning explains reduced representational drift in hippocampal CA1 place cells after novel environment exposure by allocating synaptic resources to salient experiences.

The paper shows that representational drift is an inevitable result of ongoing memory storage in neuronal circuits.

This paper models how the brain computes delayed consequences in decision-making without explicit feedback, showing how neural dynamics and learning mechanisms adapt over time.

This study identifies spatiotemporal propagation indicators from cortical activity in mice to track stroke-induced motor deficits and recovery across different rehabilitation paradigms.