Colleen J. Gillon

The paper proposes a model of hippocampal pyramidal neurons that use predictive learning through dendritic compartments and synaptic plasticity to encode spatial and behaviorally relevant features.

This study tests if local neural circuits can generate predictive signals using a recurrent spiking network trained with local plasticity rules, replicating experimental prediction error patterns.

This study shows that sensory information increases in primary somatosensory cortex during learning, while choice information emerges later and relies on population coding.

The paper shows that cortical pyramidal neurons exhibit distinct unexpected event signals in somata and distal apical dendrites that change over days, suggesting a role in hierarchical computation.

The paper introduces VaLPACa, a variational ladder autoencoder that disentangles hierarchical dynamics in calcium imaging data by separating calcium flux from neural computation.