title: Distributed effects of methylphenidate on the network structure of the resting brain: a connectomic pattern classification analysis.
abstract: Methylphenidate is a psychostimulant medication that produces improvements in functions associated with multiple neurocognitive systems. To investigate the potentially distributed effects of methylphenidate on the brain's intrinsic network architecture, we coupled resting state imaging with multivariate pattern classification. In a within-subject, double-blind, placebo-controlled, randomized, counterbalanced, cross-over design, 32 healthy human volunteers received either methylphenidate or placebo prior to two fMRI resting state scans separated by approximately one week. Resting state connectomes were generated by placing regions of interest at regular intervals throughout the brain, and these connectomes were submitted for support vector machine analysis. We found that methylphenidate produces a distributed, reliably detected, multivariate neural signature. Methylphenidate effects were evident across multiple resting state networks, especially visual, somatomotor, and default networks. Methylphenidate reduced coupling within visual and somatomotor networks. In addition, default network exhibited decoupling with several task positive networks, consistent with methylphenidate modulation of the competitive relationship between these networks. These results suggest that connectivity changes within and between large-scale networks are potentially involved in the mechanisms by which methylphenidate improves attention functioning.
authors.affiliation: Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA. Electronic address: sripada@umich.edu.
authors.forename: Chandra Sekhar
authors.initials: CS
authors.lastname: Sripada
authors.affiliation: Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA.
authors.forename: Daniel
authors.initials: D
authors.lastname: Kessler
authors.affiliation: Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA; Department of Radiology, University of Michigan, Ann Arbor, MI, USA.
authors.forename: Robert
authors.initials: R
authors.lastname: Welsh
authors.affiliation: Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA.
authors.forename: Michael
authors.initials: M
authors.lastname: Angstadt
authors.affiliation: Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA; Mental Health Service, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA.
authors.forename: Israel
authors.initials: I
authors.lastname: Liberzon
authors.affiliation: Department of Psychiatry, University of Illinois at Chicago, USA.
authors.forename: K Luan
authors.initials: KL
authors.lastname: Phan
authors.affiliation: Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA; Department of Statistics, University of Michigan, Ann Arbor, MI, USA.
authors.forename: Clayton
authors.initials: C
authors.lastname: Scott
mesh_terms: D000293:Adolescent; D000328:Adult; D001921:Brain / Q000187:drug effects*; D000697:Central Nervous System Stimulants / Q000494:pharmacology*; D063132:Connectome; D018592:Cross-Over Studies; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008297:Male; D008774:Methylphenidate / Q000494:pharmacology*; D009434:Neural Pathways / Q000187:drug effects; D012146:Rest; D055815:Young Adult
chemical_list: D000697:Central Nervous System Stimulants; D008774:Methylphenidate
keywords: Connectome; Intrinsic connectivity networks; Methylphenidate; Multivariate pattern classification; Resting state; fMRI