title: More Consistently Altered Connectivity Patterns for Cerebellum and Medial Temporal Lobes than for Amygdala and Striatum in Schizophrenia.
abstract: BACKGROUND
  Brain architecture can be divided into a cortico-thalamic system and modulatory "subcortical-cerebellar" systems containing key structures such as striatum, medial temporal lobes (MTLs), amygdala, and cerebellum. Subcortical-cerebellar systems are known to be altered in schizophrenia. In particular, intrinsic functional brain connectivity (iFC) between these systems has been consistently demonstrated in patients. While altered connectivity is known for each subcortical-cerebellar system separately, it is unknown whether subcortical-cerebellar systems' connectivity patterns with the cortico-thalamic system are comparably altered across systems, i.e., if separate subcortical-cerebellar systems' connectivity patterns are consistent across patients.
  
  
  METHODS
  To investigate this question, 18 patients with schizophrenia (3 unmedicated, 15 medicated with atypical antipsychotics) and 18 healthy controls were assessed by resting-state functional magnetic resonance imaging (fMRI). Independent component analysis of fMRI data revealed cortical intrinsic brain networks (NWs) with time courses representing proxies for cortico-thalamic system activity. Subcortical-cerebellar systems' activity was represented by fMRI-based time courses of selected regions-of-interest (ROIs; i.e., striatum, MTL, amygdala, cerebellum). Correlation analysis among ROI- and NWs-time courses yielded individual connectivity matrices [i.e., connectivity between NW and ROIs (allROIs-NW, separateROI-NW), only NWs (NWs-NWs), and only ROIs (allROIs-allROIs)] as main outcome measures, which were classified by support-vector-machine-based (SVM) leave-one-out cross-validation. Differences in classification accuracy were statistically evaluated for consistency across subjects and systems.
  
  
  RESULTS
  Correlation matrices based on allROIs-NWs yielded 91% classification accuracy, which was significantly superior to allROIs-allROIs and NWs-NWs (56 and 74%, respectively). Considering separate subcortical-cerebellar systems, cerebellum-NWs and MTL-NWs reached highest accuracy values with 91 and 85%, respectively, while those of striatum-NW and amygdala-NW were significantly lower with about 65% classification accuracy.
  
  
  CONCLUSIONS
  RESULTS provide initial evidence for differential consistency of altered intrinsic connectivity patterns between subcortical-cerebellar systems and the cortico-thalamic system. Data suggest that differential dysconnectivity patterns between subcortical-cerebellar and cortical systems might reflect different disease states or patient subgroups.
authors.affiliation: Department of Psychiatry, Technische Universität MünchenMünchen, Germany; TUM-Neuroimaging Center, Klinikum Rechts der Isar, Technische Universität MünchenMünchen, Germany; Klinik für Psychiatrie und Psychotherapie, Klinikum der Universität MünchenMünchen, Germany.
authors.forename: Henning
authors.initials: H
authors.lastname: Peters
authors.affiliation: School of Computer Science and Engineering, University of Electronic Science and Technology of ChinaChengdu, China; Big Data Research Center, University of Electronic Science and Technology of ChinaChengdu, China; Center for Information in BioMedicine, University of Electronic Science and Technology of ChinaChengdu, China.
authors.forename: Junming
authors.initials: J
authors.lastname: Shao
authors.affiliation: Department of Psychiatry, Technische Universität München München, Germany.
authors.forename: Martin
authors.initials: M
authors.lastname: Scherr
authors.affiliation: Department of Psychiatry, Technische Universität München München, Germany.
authors.forename: Dirk
authors.initials: D
authors.lastname: Schwerthöffer
authors.affiliation: Department of Neuroradiology, Technische Universität München München, Germany.
authors.forename: Claus
authors.initials: C
authors.lastname: Zimmer
authors.affiliation: Department of Psychiatry, Technische Universität München München, Germany.
authors.forename: Hans
authors.initials: H
authors.lastname: Förstl
authors.affiliation: Department of Psychiatry, Technische Universität München München, Germany.
authors.forename: Josef
authors.initials: J
authors.lastname: Bäuml
authors.affiliation: TUM-Neuroimaging Center, Klinikum Rechts der Isar, Technische Universität MünchenMünchen, Germany; Department of Neuroradiology, Technische Universität MünchenMünchen, Germany.
authors.forename: Afra
authors.initials: A
authors.lastname: Wohlschläger
authors.affiliation: TUM-Neuroimaging Center, Klinikum Rechts der Isar, Technische Universität MünchenMünchen, Germany; Department of Neuroradiology, Technische Universität MünchenMünchen, Germany; Department of Nuclear Medicine, Technische Universität MünchenMünchen, Germany.
authors.forename: Valentin
authors.initials: V
authors.lastname: Riedl
authors.affiliation: TUM-Neuroimaging Center, Klinikum Rechts der Isar, Technische Universität MünchenMünchen, Germany; Department of Neuroradiology, Technische Universität MünchenMünchen, Germany.
authors.forename: Kathrin
authors.initials: K
authors.lastname: Koch
authors.affiliation: Department of Psychiatry, Technische Universität MünchenMünchen, Germany; TUM-Neuroimaging Center, Klinikum Rechts der Isar, Technische Universität MünchenMünchen, Germany; Department of Neuroradiology, Technische Universität MünchenMünchen, Germany.
authors.forename: Christian
authors.initials: C
authors.lastname: Sorg
keywords: fMRI; functional connectivity (FC); multivariate pattern analysis; schizophrenia; subcortical; support vector machine