[BIC-announce] Séminaire UNF _ Mehraveh Salehi- jeudi 29 novembre 1pm

[Claude Godbout]

LES SÉMINAIRES DE L’UNF / SEMINAR UNF SERIES


Présentateur/ Speaker:

Mehraveh Salehi, Ph. D. 


Titre/  Title:

Individualized and state-specific human brain parcellation in multiple
scales.


Endroit/ Where:

CRIUGM – Local M6804 ( <http://www.criugm.qc.ca/en/contact.html>
http://www.criugm.qc.ca/en/contact.html)


Date/ When:

Jeudi 29 novembre, 13h-14h/ Thursday, November 29th 1pm-2pm


 

*La conférence sera présentée en anglais/The seminar will be presented in
English

 

 

Mehraveh Salehi is a Ph.D. candidate in Electrical Engineering department at
Yale University. She is currently working as a research intern at Google
DeepMind in Montreal. She earned her Bachelor degree in Electrical
Engineering from Sharif University of Technology, Tehran, Iran. Her research
lies at the intersection of statistical machine learning and computational
neuroscience. She is interested in developing models that relate human
behavior to individual brain connectivity patterns using optimization and
machine learning techniques. She has received a number of awards including
the Young Scientist Award from the International Conference on Medical Image
Computing and Computer Assisted Intervention 2017 (MICCAI), and the best
poster award from the BioImaging Sciences Retreat 2018. She is also the
recipient of Tananbaum Fellowship, Advanced Graduate Leadership Program
(AGLP) Fellowship, and CRA-Women Graduate Fellowship. 

 

Abstract:

The goal of human brain mapping has long been to delineate functionally
coherent regions in the brain and elucidate the functional role of these
regions. Previous work has shown great success on defining functionally
coherent regions at multiple scales, by grouping voxels into nodes and
further grouping those nodes to form communities or networks in the brain.
While majority of previous work has assumed fixed functional units across
individuals and states, we show that the parcellation of human brain is both
individual and state dependent. In this talk, I will first present a
recently developed individualized and state-specific parcellation technique
that utilizes submodular maximization of an exemplar-based utility function.
Then, I will cover the predictive models that estimate biological and
cognitive characteristics of individuals (including sex and IQ) as well as
their brain's cognitive state (approximated by the task condition as well as
the within-condition task performance), solely based on the features
extracted from these individualized parcellations. 

 

 

I hope to see you there / En espérant vous voir nombreux.

 

 

Pierre Bellec 

Associate professor/Professeur agrégé sous octroi, Département
d'informatique et de recherche opérationnelle ( <http://diro.umontreal.ca/>
DIRO)

Director/Directeur, Unité de Neuroimagerie Fonctionnelle (
<http://unf-montreal.ca> UNF)

Researcher/Chercheur Centre de recherche de l'institut Universitaire de
gériatrie de Montréal ( <http://www.criugm.qc.ca/> CRIUGM)

Université de Montréal, Montréal, Canada

Phone +1 514 713 5596  

 <http://simexp-lab.org/brainwiki/doku.php?id=pierrebellec> Coordinates/c
<http://simexp-lab.org/brainwiki/doku.php?id=pierrebellec> oordonnées.

 <http://simexp-lab.org> Laboratory/Laboratoire SIMEXP

 

 

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