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DTSTAMP:20250706T182158Z
DESCRIPTION:Artificial neural networks in visual neuroscience: towards a qu
 antitative explanation of visual object recognition in the brain\n\nPouya 
 Bashivan\, ºÃÉ«TV\n	Tuesday January 18\, 12-1pm\n	Zoom Link: http
 s://mcgill.zoom.us/j/85428056343\n\nAbstract: Within tens of milliseconds\
 , the neuronal networks in the primate brain process the patterns of light
  that strike the eyes in a series of six interconnected cortical areas cal
 led the ventral visual pathway. These areas form a necessary substrate for
  our ability to recognize objects and their relationships in the world. On
 e of the core scientific questions in visual neuroscience is concerned wit
 h the visual patterns that neurons at each level of processing along the v
 entral stream represent. In recent years\, artificial neural network (ANN)
  models have become increasingly more common in neuroscience studies aimin
 g at providing quantitative explanations for the patterns of neuronal resp
 onses observed in the animal brains. Despite their many shortcomings in ac
 hieving human-level visual perception\, the current ANN models are by far 
 our best quantitative models of the computations underlying biological vis
 ion. In this talk\, I will review some of our recent work in using ANN mod
 els to predict the neuronal responses in the human and nonhuman primate vi
 sual cortex and discuss how we have adopted these models to facilitate mor
 e quantitative explanations of how population activity across the visual c
 ortex gives rise to our perception of the world.\n\nRelevant publications:
 \n	https://www.science.org/doi/10.1126/science.aav9436\n	https://www.nature.
 com/articles/s41467-021-25409-6\n
DTSTART:20220118T170000Z
DTEND:20220118T180000Z
LOCATION:CA\, QC
SUMMARY:QLS Seminar Series - Pouya Bashivan
URL:/qls/channels/event/qls-seminar-series-pouya-bashi
 van-336008
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