Predicting personality from network-based resting-state functional connectivity

Personality is associated with variation in all kinds of mental faculties, including affective, social, executive, and memory functioning. The intrinsic dynamics of neural networks underlying these mental functions are reflected in their functional connectivity at rest (RSFC). We, therefore, aimed t...

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Vydáno v:	Brain Structure and Function Ročník 223; číslo 6; s. 2699 - 2719
Hlavní autoři:	Nostro, Alessandra D., Müller, Veronika I., Varikuti, Deepthi P., Pläschke, Rachel N., Hoffstaedter, Felix, Langner, Robert, Patil, Kaustubh R., Eickhoff, Simon B.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Berlin/Heidelberg Springer Berlin Heidelberg 01.07.2018 Springer Nature B.V
Témata:	Adult Biomedical and Life Sciences Biomedicine Brain - diagnostic imaging Brain - physiology Brain Mapping Cell Biology Connectome Female Females Gender Humans Image Processing, Computer-Assisted Magnetic Resonance Imaging Male Males Memory Meta-Analysis as Topic Nerve Net - diagnostic imaging Nerve Net - physiology Nervous system Neural networks Neurology Neurosciences Neurosis Original Article Oxygen - blood Personality Personality - physiology Personality traits Rest Sex differences Social organization Young Adult Resting-state functional connectivity Gender differences Hormonal influence Machine learning NEO-FFI Functional networks
ISSN:	1863-2653, 1863-2661, 1863-2661, 0340-2061
On-line přístup:	Získat plný text
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