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Open AccessJournal ArticleDOI

Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity

TLDR
In this article, the authors show that every individual has a unique pattern of functional connections between brain regions, which act as a fingerprint that can accurately identify the individual from a large group.
Abstract
This study shows that every individual has a unique pattern of functional connections between brain regions. This functional connectivity profile acts as a ‘fingerprint’ that can accurately identify the individual from a large group. Furthermore, an individual's connectivity profile can predict his or her level of fluid intelligence.

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Citations
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Journal ArticleDOI

A structural enriched functional network: An application to predict brain cognitive performance

TL;DR: In this article, a simplex regression model with graph-constrained Elastic Net was used to construct the functional networks enriched by the structural network. And the authors compared the constructed network characteristics of this approach with several state-of-the-art competing functional network models.
Posted ContentDOI

The Normative Modeling Framework for Computational Psychiatry

TL;DR: Normative modeling is an emerging and innovative framework for mapping individual differences at the level of a single subject or observation in relation to a reference model, which can then be used to make statistical inferences at the individual level as discussed by the authors.
Journal ArticleDOI

Linking Brain Biology to Intellectual Endowment: A Review on the Associations of Human Intelligence With Neuroimaging Data.

TL;DR: A review of recent findings on the associations of human intelligence with neuroimaging data can be found in this article, where the authors provide a survey of literature that has used multimodal DWI-fMRI to shed light on intelligence.
Journal ArticleDOI

Interindividual differences in matrix reasoning are linked to functional connectivity between brain regions nominated by Parieto-Frontal Integration Theory

TL;DR: This study is the first to identify specific connections from the P-FIT network whose functional connectivity strength at rest can be considered an indicator of intellectual capability.
Journal ArticleDOI

Predicting visual working memory with multimodal magnetic resonance imaging.

TL;DR: The usage of multimodal neuroimaging in combination with machine learning is proposed to reveal the neural mechanism of VWM across a large cohort and offer a solid and general foundation for comprehensively understanding the VWM process from the top down.
References
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Journal ArticleDOI

Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain

TL;DR: An anatomical parcellation of the spatially normalized single-subject high-resolution T1 volume provided by the Montreal Neurological Institute was performed and it is believed that this tool is an improvement for the macroscopical labeling of activated area compared to labeling assessed using the Talairach atlas brain.
Journal ArticleDOI

Complex network measures of brain connectivity: uses and interpretations.

TL;DR: Construction of brain networks from connectivity data is discussed and the most commonly used network measures of structural and functional connectivity are described, which variously detect functional integration and segregation, quantify centrality of individual brain regions or pathways, and test resilience of networks to insult.
Journal ArticleDOI

The organization of the human cerebral cortex estimated by intrinsic functional connectivity

TL;DR: In this paper, the organization of networks in the human cerebrum was explored using resting-state functional connectivity MRI data from 1,000 subjects and a clustering approach was employed to identify and replicate networks of functionally coupled regions across the cerebral cortex.
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