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SUMMARY:Extracting Single-Trial Views of Brain Activity
DTSTART:20090420T161500
DTSTAMP:20260511T165328Z
UID:a92777ea72c8636c7678e28bf0a2e517574d2fb39ba65a9994365c1e
CATEGORIES:Conferences - Seminars
DESCRIPTION:Dr. Byron Yu\, Stanford University & Gatsby Computational Neur
 oscience Unit\, UCL\nAdvances in neural recording technologies (including 
 multi-electrode arrays and optical imaging techniques) have transformed sy
 stems neuroscience from a field that is data-limited to one that is limite
 d by the available analytical methods.  While we have well-established met
 hods for studying the activity of one or perhaps a pair of neurons\, we ar
 e currently unprepared to deal with the activity of the tens to hundreds o
 f neurons that we can now monitor simultaneously.  To make further scienti
 fic progress with the ever-growing volume of neural data being collected\,
  new analytical methods are needed that can leverage the simultaneous reco
 rding of large populations of neurons.  In this talk\, I will take a step 
 in this direction by describing how low-dimensional "neural trajectories" 
 can be extracted on a single-trial basis from the noisy\, high-dimensional
  recorded activity.  Using premotor cortical activity\, I will show how th
 e developed methods provide a powerful way to study neural population dyna
 mics and their relationship to the subject's behavior on a single-trial ba
 sis.  Such an approach has the potential to further our understanding of n
 eural mechanisms and uncover computational principles employed by the brai
 n.  I will then discuss how such basic scientific discoveries have importa
 nt biomedical implications -- in particular for the development of brain-c
 omputer interfaces\, which aim to assist paralyzed patients by translating
  their thoughts into actions in the real world.\n\nByron Yu's homepage
LOCATION:INM202
STATUS:CONFIRMED
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