Santiago Galella

The paper shows that random connectivity in neural networks preserves representational similarity despite activity drift, applicable to biological circuits.

This study examines neural representations in task-switching feedforward networks using context biases, finding that they transition from parallel processing to independent subnetworks, similar to cortical processing.

The paper demonstrates that recurrent neuronal networks in C. elegans can exhibit long-term memory through complex dynamics without requiring hard-wired modules.