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DTSTART:20210328T030000
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BEGIN:VEVENT
DTSTAMP:20260406T024137Z
UID:1616162400@ist.ac.at
DTSTART:20210319T150000
DTEND:20210319T160000
DESCRIPTION:Speaker: Ashok Litwin-Kumar\nhosted by Basile Confavreux\nAbstr
 act: Since the theories of Marr\, Ito\, and Albus\, the cerebellum has pro
 vided an attractive well-characterized model system to investigate biologi
 cal mechanisms of learning. In recent years\, theories have been developed
  that provide a normative account for many features of the anatomy and fun
 ction of cerebellar cortex and cerebellum-like systems\, including the dis
 tribution of parallel fiber-Purkinje cell synaptic weights\, the expansion
  in neuron number of the granule cell layer and their synaptic in-degree\,
  and sparse coding by granule cells. Typically\, these theories focus on t
 he learning of random mappings between uncorrelated inputs and binary outp
 uts\, an assumption that may be reasonable for certain forms of associativ
 e conditioning but is also quite far from accounting for the important rol
 e the cerebellum plays in the control of smooth movements. I will discuss 
 in-progress work with Marjorie Xie\, Samuel Muscinelli\, and Kameron Decke
 r Harris generalizing these learning theories to correlated inputs and gen
 eral classes of smooth input-output mappings. Our studies build on earlier
  work in theoretical neuroscience as well as recent advances in the kernel
  theory of wide neural networks. They illuminate the role of pre-expansion
  structures in processing input stimuli and the significance of sparse gra
 nule cell activity. If there is time\, I will also discuss preliminary wor
 k with Jack Lindsey extending these theories beyond cerebellum-like struct
 ures to recurrent networks.
LOCATION:Online\, ISTA
ORGANIZER:
SUMMARY:Ashok Litwin-Kumar: Generalizing theories of cerebellum-like learni
 ng
URL:https://talks-calendar.ista.ac.at/events/3097
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