Morphometric Similarity Networks Detect Microscale Cortical Organization and Predict Inter-Individual Cognitive Variation

• Published in: Neuron (Cambridge, Mass.) Vol. 97; no. 1; pp. 231 - 247.e7
• Main Authors: Seidlitz, Jakob, Váša, František, Shinn, Maxwell, Romero-Garcia, Rafael, Whitaker, Kirstie J., Vértes, Petra E., Wagstyl, Konrad, Kirkpatrick Reardon, Paul, Clasen, Liv, Liu, Siyuan, Messinger, Adam, Leopold, David A., Fonagy, Peter, Dolan, Raymond J., Jones, Peter B., Goodyer, Ian M., Raznahan, Armin, Bullmore, Edward T.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 03.01.2018; Elsevier Limited
• Subjects: Animals; Brain mapping; Brain research; Cerebral Cortex - anatomy & histology; Cerebral Cortex - physiology; Cognition - physiology; Cognitive ability; connectome; Connectome - methods; Consortia; Cortex; cross-species; cytoarchitecture; Female; gene expression; Humans; Hypotheses; Intelligence - physiology; Macaca; macaque; Magnetic Resonance Imaging; Male; morphology; MRI; multi-modal; Neural networks; Neural Pathways - anatomy & histology; Neural Pathways - physiology; Neuroimaging; Neurosciences; NMR; Nuclear magnetic resonance; Variables; Young Adult; Young adults; macaque; morphology; MRI; cross-species; IQ; connectome; cytoarchitecture; multi-modal; gene expression
• ISSN: 0896-6273; 1097-4199; 1097-4199
• DOI: 10.1016/j.neuron.2017.11.039

Macroscopic cortical networks are important for cognitive function, but it remains challenging to construct anatomically plausible individual structural connectomes from human neuroimaging. We introduce a new technique for cortical network mapping based on inter-regional similarity of multiple morph...