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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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Individual identification and individual variability analysis based on cortical folding features in developing infant singletons and twins.

TL;DR: For twins study, it is shown that even for monozygotic twins with identical genes and similar developmental environments, their cortical folding features are unique enough for accurate individual identification; and in some high‐order association cortices, the differences between Monozygotic twin pairs are significantly lower than those between dizygotic twins.
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Tracking mood fluctuations with functional network patterns.

TL;DR: A comprehensive mapping between resting‐state functional connectivity (FC) patterns and subjective mood scales and one of the top‐ranked nodes in mood‐related network reconfiguration was the subgenual anterior cingulate cortex, an area commonly associated with mood regulation and dysregulation.
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Meta-matching as a simple framework to translate phenotypic predictive models from big to small data

TL;DR: In this article , meta-matching is applied to predict non-brain-imaging phenotypes from resting-state functional connectivity in small-scale studies, where a unique phenotype from a boutique study likely correlates with related phenotypes in some large-scale dataset.
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An isotropic EPI database and analytical pipelines for rat brain resting-state fMRI.

TL;DR: In this article, the authors proposed a high-spatial-resolution (0.4mm) isotropic, whole-brain EPI protocol for the rat brain using a horizontal slicing scheme that can maintain a functionally relevant repetition time (TR), avoid high gradient duty cycles, and offer unequivocal whole brain coverage.
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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