Kayvon Daie

This study uses biologically realistic simulations to show that cortical circuit stability and information integration increase with hierarchy, linked to increased connectivity and SST cell proportion.

This study shows how rapid learning in mice involves structured changes in motor cortex connectivity, rerouting preparatory activity to control a conditioned neuron.

The paper shows that neural activity in non-task-coding dimensions can drive behavior through transient amplification, challenging the assumption that only task-relevant dimensions are behaviorally significant.

This study shows that motor memories are stably retained in mice through context-specific neural representations, which protect existing memories during new learning.

The paper maps functional connectivity in the motor cortex of mice during naturalistic reward-seeking behavior, revealing columnar architecture and hub neurons that influence neighboring cells.

The paper shows that feedforward amplification in recurrent neural networks explains paradoxical neural coding in motor cortex, where early low-selectivity activity influences behavior more than late high-selectivity activity.

This study shows that two BCI learning phenomena can be explained by gradient-based optimization, without requiring special mechanisms.

The paper uses targeted photostimulation in mice to investigate neural circuits underlying short-term memory, revealing recurrent interactions and modular organization in the anterior-lateral motor cortex.

The paper compares neuronal population dynamics measured via calcium imaging and electrophysiology, finding discrepancies that are partially resolved by spike inference algorithms and highlighting the value of forward modeling.

This study compares SiPMs and GaAsP PMT for two-photon imaging, finding SiPMs match PMT signal-to-noise ratio at typical calcium imaging rates and outperform at higher rates.