Personalized connectome fingerprints: Their importance in cognition from childhood to adult years
| Autor: | Barbara K. Marebwa, Chris Rorden, John Delgaizo, Julius Fridriksson, Brent C. Munsell, Ezequiel Gleichgerrcht, Eric Hofesmann, John H. Gilmore, Carrie R. McDonald, Leonardo Bonilha, Niels K. Focke, Martin Styner |
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| Rok vydání: | 2020 |
| Předmět: |
Adult
Male Human Development Cognitive Neuroscience Intelligence Developmental cognitive neuroscience Neuroimaging Computational biology 050105 experimental psychology lcsh:RC321-571 Machine Learning Young Adult 03 medical and health sciences Cognition 0302 clinical medicine medicine Humans Learning 0501 psychology and cognitive sciences Neurological identity and function lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry Aged Developmental quotient Structural connectivity 05 social sciences Fingerprint (computing) Infant Human brain Middle Aged Magnetic Resonance Imaging White Matter medicine.anatomical_structure Neurology Child Preschool Connectome fingerprinting Neural network architecture Connectome Developmental neuroscience Network analysis Female Nerve Net Psychology 030217 neurology & neurosurgery Critical set |
| Zdroj: | NeuroImage, Vol 221, Iss, Pp 117122-(2020) |
| DOI: | 10.17615/ba8v-c710 |
| Popis: | Structural neural network architecture patterns in the human brain could be related to individual differences in phenotype, behavior, genetic determinants, and clinical outcomes from neuropsychiatric disorders. Recent studies have indicated that a personalized neural (brain) fingerprint can be identified from structural brain connectomes. However, the accuracy, reproducibility and translational potential of personalized fingerprints in terms of cognition is not yet fully determined. In this study, we introduce a dynamic connectome modeling approach to identify a critical set of white matter subnetworks that can be used as a personalized fingerprint. Several individual variable assessments were performed that demonstrate the accuracy and practicality of personalized fingerprint, specifically predicting the identity and IQ of middle age adults, and the developmental quotient in toddlers. Our findings suggest the fingerprint found by our dynamic modeling approach is sufficient for differentiation between individuals, and is also capable of predicting general intellectual ability across human development. © 2020 The AuthorsSignificance Statement We demonstrate that white matter connections obtained from high resolution medical imaging data form a personalized fingerprint is capable of estimating individual identity and neurodevelopmental variables across human life-span. This important finding provides strong evidence to support the concept of neurological identity and function through human brain connectome mapping. |
| Databáze: | OpenAIRE |
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