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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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Hyperalignment: Modeling Shared Information Encoded in Idiosyncratic Cortical Topographies

TL;DR: This Perspective presents the conceptual framework that motivates hyperalignment, its computational underpinnings for joint modeling of a common information space and idiosyncratic cortical topographies, and discuss implications for understanding the structure of cortical functional architecture.
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Context-Aware Generative Adversarial Privacy

TL;DR: This work introduces a novel context-aware privacy framework called GAP, which leverages recent advancements in generative adversarial networks to allow the data holder to learn privatization schemes from the dataset itself, and demonstrates that the framework can be easily applied in practice, even in the absence of dataset statistics.
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Network Mapping with GIMME.

TL;DR: Researchers will be equipped to begin analyzing the temporal dynamics of their heterogeneous time series data with GIMME, an automated network analysis approach for intensive longitudinal data.
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Evaluation of non-negative matrix factorization of grey matter in age prediction

TL;DR: A non‐negative matrix factorization (NNMF) approach is evaluated to provide a reduced, but also interpretable representation of GMV data in age prediction frameworks in healthy and clinical populations and its validation in clinical populations showed that the framework is sensitive to deviance from normal structural variations in pathological aging.
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Methylphenidate Modulates Functional Network Connectivity to Enhance Attention.

TL;DR: Results suggest that methylphenidate acts by modulating strength in functional brain networks related to attention, and that changing whole-brain connectivity patterns may help improve attention.
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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