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Jensen KM, Calhoun VD, Fu Z, Yang K, Faria AV, Ishizuka K, Sawa A, Andrés-Camazón P, Coffman BA, Seebold D, Turner JA, Salisbury DF, Iraji A. A whole-brain neuromark resting-state fMRI analysis of first-episode and early psychosis: Evidence of aberrant cortical-subcortical-cerebellar functional circuitry. Neuroimage Clin 2024; 41:103584. [PMID: 38422833 PMCID: PMC10944191 DOI: 10.1016/j.nicl.2024.103584] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 01/31/2024] [Accepted: 02/25/2024] [Indexed: 03/02/2024]
Abstract
Psychosis (including symptoms of delusions, hallucinations, and disorganized conduct/speech) is a main feature of schizophrenia and is frequently present in other major psychiatric illnesses. Studies in individuals with first-episode (FEP) and early psychosis (EP) have the potential to interpret aberrant connectivity associated with psychosis during a period with minimal influence from medication and other confounds. The current study uses a data-driven whole-brain approach to examine patterns of aberrant functional network connectivity (FNC) in a multi-site dataset comprising resting-state functional magnetic resonance images (rs-fMRI) from 117 individuals with FEP or EP and 130 individuals without a psychiatric disorder, as controls. Accounting for age, sex, race, head motion, and multiple imaging sites, differences in FNC were identified between psychosis and control participants in cortical (namely the inferior frontal gyrus, superior medial frontal gyrus, postcentral gyrus, supplementary motor area, posterior cingulate cortex, and superior and middle temporal gyri), subcortical (the caudate, thalamus, subthalamus, and hippocampus), and cerebellar regions. The prominent pattern of reduced cerebellar connectivity in psychosis is especially noteworthy, as most studies focus on cortical and subcortical regions, neglecting the cerebellum. The dysconnectivity reported here may indicate disruptions in cortical-subcortical-cerebellar circuitry involved in rudimentary cognitive functions which may serve as reliable correlates of psychosis.
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Affiliation(s)
- Kyle M Jensen
- Georgia State University, Atlanta, GA, USA; Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA.
| | - Vince D Calhoun
- Georgia State University, Atlanta, GA, USA; Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA
| | - Zening Fu
- Georgia State University, Atlanta, GA, USA; Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA
| | - Kun Yang
- Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Andreia V Faria
- Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Koko Ishizuka
- Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Akira Sawa
- Johns Hopkins University School of Medicine, Baltimore, MD, USA; Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Pablo Andrés-Camazón
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA; Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, Madrid, Spain
| | - Brian A Coffman
- University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Dylan Seebold
- University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Jessica A Turner
- Wexner Medical Center, The Ohio State University, Columbus, OH, USA
| | - Dean F Salisbury
- University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Armin Iraji
- Georgia State University, Atlanta, GA, USA; Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA
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He H, Yu Q, Du Y, Vergara V, Victor TA, Drevets WC, Savitz JB, Jiang T, Sui J, Calhoun VD. Resting-state functional network connectivity in prefrontal regions differs between unmedicated patients with bipolar and major depressive disorders. J Affect Disord 2016; 190:483-493. [PMID: 26551408 PMCID: PMC4684976 DOI: 10.1016/j.jad.2015.10.042] [Citation(s) in RCA: 66] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2015] [Revised: 09/06/2015] [Accepted: 10/22/2015] [Indexed: 02/04/2023]
Abstract
BACKGROUND Differentiating bipolar disorder (BD) from major depressive disorder (MDD) often poses a major clinical challenge, and optimal clinical care can be hindered by misdiagnoses. This study investigated the differences between BD and MDD in resting-state functional network connectivity (FNC) using a data-driven image analysis method. METHODS In this study, fMRI data were collected from unmedicated subjects including 13 BD, 40 MDD and 33 healthy controls (HC). The FNC was calculated between functional brain networks derived from fMRI using group independent component analysis (ICA). Group comparisons were performed on connectivity strengths and other graph measures of FNC matrices. RESULTS Statistical tests showed that, compared to MDD, the FNC in BD was characterized by more closely connected and more efficient topological structures as assessed by graph theory. The differences were found at both the whole-brain-level and the functional-network-level in prefrontal networks located in the dorsolateral/ventrolateral prefrontal cortex (DLPFC, VLPFC) and anterior cingulate cortex (ACC). Furthermore, interconnected structures in these networks in both patient groups were negatively associated with symptom severity on depression rating scales. LIMITATIONS As patients were unmedicated, the sample sizes were relatively small, although they were comparable to those in previous fMRI studies comparing BD and MDD. CONCLUSIONS Our results suggest that the differences in FNC of the PFC reflect distinct pathophysiological mechanisms in BD and MDD. Such findings ultimately may elucidate the neural pathways in which distinct functional changes can give rise to the clinical differences observed between these syndromes.
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Affiliation(s)
- Hao He
- The Mind Research Network & Lovelace Biomedical and Environmental Research Institute, Albuquerque, NM, USA, Electrical and Computer Engineering Department, University of New Mexico, Albuquerque, NM, USA
| | - Qingbao Yu
- The Mind Research Network & Lovelace Biomedical and Environmental Research Institute, Albuquerque, NM, USA
| | - Yuhui Du
- The Mind Research Network & Lovelace Biomedical and Environmental Research Institute, Albuquerque, NM, USA, School of Information and Communication Engineering, North University of China, Taiyuan, China
| | - Victor Vergara
- The Mind Research Network & Lovelace Biomedical and Environmental Research Institute, Albuquerque, NM, USA
| | | | - Wayne C. Drevets
- Janssen Pharmaceuticals of Johnson & Johnson, Inc., Titusville, NJ, USA
| | | | - Tianzi Jiang
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Jing Sui
- The Mind Research Network & Lovelace Biomedical and Environmental Research Institute, Albuquerque, NM, USA; Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China; CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Beijing, China.
| | - Vince D. Calhoun
- The Mind Research Network & Lovelace Biomedical and Environmental Research Institute, Albuquerque, NM, USA, Electrical and Computer Engineering Department, University of New Mexico, Albuquerque, NM, USA, Department of Psychiatry, Yale University, New Haven, CT, USA,Address for Correspondence: Jing Sui, Vince D. Calhoun, The Mind Research Network, 1101 Yale Blvd, NE, Albuquerque, NM, 87106, ,
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Hunter MA, Coffman BA, Gasparovic C, Calhoun VD, Trumbo MC, Clark VP. Baseline effects of transcranial direct current stimulation on glutamatergic neurotransmission and large-scale network connectivity. Brain Res 2015; 1594:92-107. [PMID: 25312829 PMCID: PMC4358793 DOI: 10.1016/j.brainres.2014.09.066] [Citation(s) in RCA: 86] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2014] [Revised: 09/11/2014] [Accepted: 09/28/2014] [Indexed: 01/01/2023]
Abstract
Transcranial direct current stimulation (tDCS) modulates glutamatergic neurotransmission and can be utilized as a novel treatment intervention for a multitude of populations. However, the exact mechanism by which tDCS modulates the brain׳s neural architecture, from the micro to macro scales, have yet to be investigated. Using a within-subjects design, resting-state functional magnetic resonance imaging (rs-fMRI) and proton magnetic resonance spectroscopy ((1)H MRS) were performed immediately before and after the administration of anodal tDCS over right parietal cortex. Group independent component analysis (ICA) was used to decompose fMRI scans into 75 brain networks, from which 12 resting-state networks were identified that had significant voxel-wise functional connectivity to anatomical regions of interest. (1)H MRS was used to obtain estimates of combined glutamate and glutamine (Glx) concentrations from bilateral intraparietal sulcus. Paired sample t-tests showed significantly increased Glx under the anodal electrode, but not in homologous regions of the contralateral hemisphere. Increases of within-network connectivity were observed within the superior parietal, inferior parietal, left frontal-parietal, salience and cerebellar intrinsic networks, and decreases in connectivity were observed in the anterior cingulate and the basal ganglia (p<0.05, FDR-corrected). Individual differences in Glx concentrations predicted network connectivity in most of these networks. The observed relationships between glutamatergic neurotransmission and network connectivity may be used to guide future tDCS protocols that aim to target and alter neuroplastic mechanisms in healthy individuals as well as those with psychiatric and neurologic disorders.
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Affiliation(s)
- Michael A Hunter
- Psychology Clinical Neuroscience Center, The University of New Mexico, Albuquerque, NM, USA; Department of Psychology, The University of New Mexico, NM, USA; The Mind Research Network, Albuquerque, NM, USA; Department of Psychiatry, The University of New Mexico School of Medicine, Albuquerque, NM, USA
| | - Brian A Coffman
- Psychology Clinical Neuroscience Center, The University of New Mexico, Albuquerque, NM, USA; Department of Psychology, The University of New Mexico, NM, USA; The Mind Research Network, Albuquerque, NM, USA
| | | | - Vince D Calhoun
- The Mind Research Network, Albuquerque, NM, USA; Department of Psychiatry, The University of New Mexico School of Medicine, Albuquerque, NM, USA; Department of Neurosciences, The University of New Mexico, Albuquerque, NM, USA; Department of Electrical and Computer Engineering, The University of New Mexico, Albuquerque, NM, USA
| | - Michael C Trumbo
- Psychology Clinical Neuroscience Center, The University of New Mexico, Albuquerque, NM, USA; Department of Psychology, The University of New Mexico, NM, USA; The Mind Research Network, Albuquerque, NM, USA
| | - Vincent P Clark
- Psychology Clinical Neuroscience Center, The University of New Mexico, Albuquerque, NM, USA; Department of Psychology, The University of New Mexico, NM, USA; The Mind Research Network, Albuquerque, NM, USA; Department of Neurosciences, The University of New Mexico, Albuquerque, NM, USA.
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