past events & lectures

  • 2016
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  • 2013
  • 2012
  • 2011
  • The Arnold Pfeffer Center for Neuropsychoanalysis

    Insights from the Resting Brain: Methods, Models and Applications

    Saturday, June 1, 2013
    10:00 AM

    Bharat Biswal, Ph.D.
    Professor, Biomedical Engineering, New Jersey Institute of Technology and Radiology, New Jersey Medical School

    will present on

    Insights from the Resting Brain: Methods, Models and Applications

    Discussant: Maggie Zellner, Ph.D.

    New York Psychoanalytic Society & Institute
    247 East 82nd Street (between 2nd and 3rd Avenues)
    The Marianne & Nicholas Young Auditorium


    Part 1:

    Part 2:

    Although it is being successfully implemented for exploration of the genome, discovery science has eluded the functional neuroimaging community. The core challenge remains the development of common paradigms for interrogating the myriad functional systems in the brain without the constraints of a priori hypotheses. Resting-state functional MRI (R-fMRI) constitutes a candidate approach capable of addressing this challenge. Imaging the brain during rest reveals large-amplitude spontaneous low-frequency (<0.1 Hz) fluctuations in the fMRI signal that are temporally correlated across functionally related areas. Referred to as functional connectivity, these correlations yield detailed maps of complex neural systems, collectively constituting an individual’s “functional connectome.” Reproducibility across datasets and individuals suggests the functional connectome has a common architecture, yet each individual’s functional connectome exhibits unique features, with stable, meaningful interindividual differences in connectivity patterns and strengths. Comprehensive mapping of the functional connectome, and its subsequent exploitation to discern genetic influences and brain–behavior relationships, will require multicenter collaborative datasets. Here we initiate this endeavor by gathering R-fMRI data from 1,414 volunteers collected independently at 35 international centers. We demonstrate a universal architecture of positive and negative functional connections, as well as consistent loci of inter-individual variability. Age and sex emerged as significant determinants. These results demonstrate that independent R-fMRI datasets can be aggregated and shared. High throughput R-fMRI can provide quantitative phenotypes for molecular genetic studies and biomarkers of developmental and pathological processes in the brain.

guidance • support • stress • anxiety • depression • conflict • hyperactivity • identity disorders • socialization • self-esteem •
guidance • support • stress • anxiety • depression • conflict • hyperactivity • identity disorders • socialization • self-esteem •
guidance • support • stress • anxiety • depression • conflict • hyperactivity • identity disorders • socialization • self-esteem •