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Open AccessJournal ArticleDOI

Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity

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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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A longitudinal resource for studying connectome development and its psychiatric associations during childhood

TL;DR: The NKI-Rockland Sample Longitudinal Discovery of Brain Development Trajectories substudy (N = 369) is a 24- to 30-month multi-cohort longitudinal pediatric investigation (ages 6.0-17.0 at enrollment) carried out in a community-ascertained sample as discussed by the authors .
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Patterns of on-task thought in older age are associated with changes in functional connectivity between temporal and prefrontal regions.

TL;DR: The possibility that age‐related changes in off‐task thinking are correlated with changes in the intrinsic organisation of the brain is addressed, and lower connectivity between the same regions was linked to preserved performance on a creativity task in older individuals.
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Sensory and cognitive plasticity: implications for academic interventions

TL;DR: Drawing parallels between visual and cognitive intervention approaches is drawn, and research avenues that could inform educational practice in the future are suggested.
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Generation of Individual Whole-Brain Atlases With Resting-State fMRI Data Using Simultaneous Graph Computation and Parcellation.

TL;DR: This work proposes a novel individual subject-level parcellation approach based on whole-brain resting-state functional magnetic resonance imaging (fMRI) data that incorporates spatial information and multiple features of the supervoxels by energy minimization, simultaneously yielding an optimal graph and brainParcellation.
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.
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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.
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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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