ISSN: 2349-5162 | Impact Factor: 5.87

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Published in:

Volume 5 Issue 8
August-2018
eISSN: 2349-5162

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JETIRC006401

Page Number

496-502

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Title

AN ANALYSIS OF TECHNIQUES FOR FUNCTIONAL BRAIN CONNECTIVITY DETECTION ON fMRI

ISSN

2349-5162

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"AN ANALYSIS OF TECHNIQUES FOR FUNCTIONAL BRAIN CONNECTIVITY DETECTION ON fMRI", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 8, page no.496-502, August-2018, Available :http://www.jetir.org/papers/JETIRC006401.pdf

Abstract

Our brain is a complex integrative network of functionally linked brain regions. Multiple spatially distributed, but functionally linked brain regions continuously share information with each other, together forming interconnected resting-state communities. With the use of resting-state fMRI we can explore the functional connections of the brain network, using seed-based, ICA-based and/or cluster-based methods. Recent studies have shown that functional communication within the human brain is not just random, but organized according to an efficient topology that combines efficient local information processing with efficient global information integration. This integration of information may be facilitated by important hub-regions, as suggested by the observed heavy tailed connectivity distributions of functional brain networks. Interestingly, most pronounced functional connections are found between regions that are known to share a common function, suggesting that resting-state fMRI oscillations may reflect ongoing functional communication between brain regions during rest. Around eight resting-state networks have been consistently reported, overlapping the primary motor, visual and auditory network, the default mode network and known higher order attention networks. Functional connections of resting-state networks tend to be strongly related to structural white matter connections, suggesting the existence of an underlying structural core of functional connectivity networks in the human brain. Recently, the use of graph theory in combination with resting-state fMRI has provided a new platform to explore the overall structure of local and global functional connectivity in the human brain. To use functional magnetic resonance imaging (fMRI) to investigate functional connectivity, and hence, underlying neural networks, in never-treated, first-episode patients with schizophrenia using a word fluency paradigm known to activate prefrontal, anterior cingulated, and thalamic regions. Abnormal connectivity between the prefrontal cortex (PFC) and other brain regions has been demonstrated in chronic, medicated patients in previous positron emission tomography (PET) studies, but has not to our knowledge, previously been demonstrated using both first-episode, drug-naïve patients and fMRI technology.

Key Words

Brain connectivity, Brain network, FMRI

Cite This Article

"AN ANALYSIS OF TECHNIQUES FOR FUNCTIONAL BRAIN CONNECTIVITY DETECTION ON fMRI", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 8, page no. pp496-502, August-2018, Available at : http://www.jetir.org/papers/JETIRC006401.pdf

Publication Details

Published Paper ID: JETIRC006401
Registration ID: 184198
Published In: Volume 5 | Issue 8 | Year August-2018
DOI (Digital Object Identifier):
Page No: 496-502
ISSN Number: 2349-5162

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(Volume 5 | Issue 8 | August 2018 |Impact factor 5.87)

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Cite This Article

"AN ANALYSIS OF TECHNIQUES FOR FUNCTIONAL BRAIN CONNECTIVITY DETECTION ON fMRI", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 8, page no. pp496-502, August-2018, Available at : http://www.jetir.org/papers/JETIRC006401.pdf

Important Dates Related to Publication Procedure:
  • » Paper Submission Till: 29 August 2018.
  • » UGC and ISSN Approved Journal
  • » Review (Acceptance/Rejection) Notification: Within 02-04 Days.
  • » Paper Publish:Within 02-07 Days after submitting the all documents.
  • » Frequency: Monthly (12 issue Annually)
  • » Journal Type : Open Access
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Impact factor: 5.87