Hillel Adesnik - How Neural Ensembles Integrate Sensory Information and Encode Perception Podcast Por  arte de portada

Hillel Adesnik - How Neural Ensembles Integrate Sensory Information and Encode Perception

Hillel Adesnik - How Neural Ensembles Integrate Sensory Information and Encode Perception

Escúchala gratis

Ver detalles del espectáculo

How do neural networks in the cerebral cortex transform incoming sensory information to generate perceptions of the world and elicit behavioral responses? This question is being tackled in the laboratory UC Berkeley Professor Hillel Adesnik whose research program is aimed at understanding exactly how microcircuits in the cerebral cortex process sensory information to generate perceptions and drive behavior. To achieve this goal he deploys cutting-edge optical, genetic, and electrophysiological methods to monitor and manipulate specific subsets of cortical neurons in awake behaving mice. In this episode Hillel talks about the organization of neural circuits in the visual cortex and how cortical microcircuits generate and modify sensory precepts. This research is moving the field closer to understanding the neurophysiological mechanisms by which incoming sensory information is integrated with stored information to produce decisions and actions.

LINKS

Adesnik laboratory at Berkeley

https://adesnik.berkeley.edu/

Lateral competition for cortical space by layer-specific horizontal circuits.

https://pmc.ncbi.nlm.nih.gov/articles/PMC2908490/pdf/nihms214939.pdf

Probing neural codes with two-photon holographic optogenetics.

https://pmc.ncbi.nlm.nih.gov/articles/PMC9793863/pdf/nihms-1753572.pdf

The logic of recurrent circuits in the primary visual cortex

https://pmc.ncbi.nlm.nih.gov/articles/PMC10774145/pdf/41593_2023_Article_1510.pdf

Recurrent pattern completion drives the neocortical representation of sensory inference

https://pmc.ncbi.nlm.nih.gov/articles/PMC12586158/pdf/41593_2025_Article_2055.pdf

Feature-tuned synaptic inputs to somatostatin interneurons drive context-dependent processing

https://pmc.ncbi.nlm.nih.gov/articles/PMC12919646/pdf/nihms-2132228.pdf

Todavía no hay opiniones