Johnatan Aljadeff

This study investigates how the medial entorhinal cortex (mEC) maintains information during working memory, finding that low-dimensional neural dynamics, not limited to grid cells, support memory retention through recurring activity patterns.

This study investigates how neural circuits generate predictive representations for complex sensorimotor signals using recurrent networks and experimental validation.

The paper shows that stimulating specific M1 neurons in mice can induce learned movements and activity patterns, supporting M1's active role in motor learning.

This study shows that shallow peripheral preprocessing in Drosophila improves odor classification by shaping downstream connectivity and amplifying hedonic signals.

The paper investigates STDP under physiological Ca2+ concentrations and finds that plasticity rules change significantly, with specific activity regimes restoring classical STDP profiles.

This paper proposes a computational framework for cerebellar learning using perturbations and validates it with in vitro experiments, contradicting the current consensus on synaptic plasticity.