Difference between revisions of "Store:EEMIde02"

(Created page with "=== Introduction === An important but outstanding issue in contemporary cognitive neuroscience is understanding the organizational properties of neural activity. For instance, is there a fundamental structure to the spatial–temporal patterns neural brain activity across different conditions? One common approach used to address this question is to examine the brain at “rest”. Measures such as functional connectivity, independent component analysis and graph theoreti...")
 
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  | autore2 = Womelsdorfb T
  | autore2 = Womelsdorfb T
  | autore3 = Allenc EA
  | autore3 = Allenc EA
  | autore4 = Bandettinie PA
  | autore4 = Bandettini PA
  | autore5 = Calhound VD
  | autore5 = Calhound VD
  | autore6 = Corbetta M
  | autore6 = Corbetta M

Revision as of 08:02, 4 December 2022

Introduction

An important but outstanding issue in contemporary cognitive neuroscience is understanding the organizational properties of neural activity. For instance, is there a fundamental structure to the spatial–temporal patterns neural brain activity across different conditions? One common approach used to address this question is to examine the brain at “rest”. Measures such as functional connectivity, independent component analysis and graph theoretic metrics, have been applied to data recorded using different imaging techniques (e.g., functional magnetic resonance imaging (fMRI) and electroencephalography (EEG)), to cluster brain areas that exhibit similar activity patterns. Numerous studies have shown that brain activity during “rest” can be grouped into distinct networks across[1][2]; such as sensory (visual and auditory), default mode, executive, salience, and attentional (ventral and dorsal) networks that have been reliably reproduced across thousands of participants[3], and are predictive of phenotypic measures like cognition and clinical diagnoses[4][5][6]. These results suggest these networks may be an intrinsic aspect of neural activity.

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