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SUMMARY:IC Colloquium : The complex brain representations involved in natu
 ral reading
DTSTART:20150202T101500
DTEND:20150202T113000
DTSTAMP:20260407T105545Z
UID:b2f6b647e4d23ef7722fe21c7dfbc362471afc06a2473b20942f3f29
CATEGORIES:Conferences - Seminars
DESCRIPTION:By : Leila Wehbe - Carnegie Mellon University\nIC Faculty cand
 idateAbstract : \nHow is information organized in the brain during natural
  reading? Where and when do the required processes occur\, such as perceiv
 ing the individual words and combining them with the previous words? How a
 re different types of information represented\, such as semantics\, syntax
  or higher-level narrative structure? Due to the complexity of language\, 
 most brain imaging studies have concentrated on one aspect of language pro
 cessing\, and usually use highly controlled stimuli. Such artificial stimu
 li might lead to conclusions that do not generalize beyond the experimenta
 l setting. My research revolves around studying the complex parallel proce
 ss involved when participants read a natural text in a close to normal set
 ting.\nMy approach uses natural language processing to model the content o
 f the stimulus text\, and machine learning tools to relate it to the activ
 ity of different brain regions and make inferences on their roles. I will 
 describe results from an fMRI reading experiment that allowed us to constr
 uct a map detailing how different regions of the brain participate in diff
 erent reading sub-processes. I will also describe a Magnetoencephalography
  study that suggests a time-line for how meaning is built and updated whil
 e reading. This approach is broadly applicable to studying higher-level fu
 nctions\, and could help us understand individual differences in behavior 
 by relating them to differences in the organization of information in the 
 brain. It might also enable us to build better statistical language models
  that incorporate brain imaging data in their learning phase.Bio :\nLeila 
 Wehbe is a PhD student in Machine Learning at Carnegie Mellon University. 
 She is advised by Tom Mitchell. Her research interests include the neurobi
 ology of language\, naturalistic brain imaging\, combining natural languag
 e processing with brain imaging of language and nonparametric hypothesis t
 esting methods.  She received her BE in Electrical and Computer Engineeri
 ng from the American University of Beirut.More information
LOCATION:BC 420 https://plan.epfl.ch/?room==BC%20420
STATUS:CONFIRMED
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