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Meneghetti N, Vannini E, Mazzoni A. Rodents' visual gamma as a biomarker of pathological neural conditions. J Physiol 2024; 602:1017-1048. [PMID: 38372352 DOI: 10.1113/jp283858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Accepted: 01/23/2024] [Indexed: 02/20/2024] Open
Abstract
Neural gamma oscillations (indicatively 30-100 Hz) are ubiquitous: they are associated with a broad range of functions in multiple cortical areas and across many animal species. Experimental and computational works established gamma rhythms as a global emergent property of neuronal networks generated by the balanced and coordinated interaction of excitation and inhibition. Coherently, gamma activity is strongly influenced by the alterations of synaptic dynamics which are often associated with pathological neural dysfunctions. We argue therefore that these oscillations are an optimal biomarker for probing the mechanism of cortical dysfunctions. Gamma oscillations are also highly sensitive to external stimuli in sensory cortices, especially the primary visual cortex (V1), where the stimulus dependence of gamma oscillations has been thoroughly investigated. Gamma manipulation by visual stimuli tuning is particularly easy in rodents, which have become a standard animal model for investigating the effects of network alterations on gamma oscillations. Overall, gamma in the rodents' visual cortex offers an accessible probe on dysfunctional information processing in pathological conditions. Beyond vision-related dysfunctions, alterations of gamma oscillations in rodents were indeed also reported in neural deficits such as migraine, epilepsy and neurodegenerative or neuropsychiatric conditions such as Alzheimer's, schizophrenia and autism spectrum disorders. Altogether, the connections between visual cortical gamma activity and physio-pathological conditions in rodent models underscore the potential of gamma oscillations as markers of neuronal (dys)functioning.
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Affiliation(s)
- Nicolò Meneghetti
- The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence for Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Eleonora Vannini
- Neuroscience Institute, National Research Council (CNR), Pisa, Italy
| | - Alberto Mazzoni
- The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence for Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
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Parker D, Trotti R, McDowell J, Keedy S, Keshavan M, Pearlson G, Gershon E, Ivleva E, Huang LY, Sauer K, Hill S, Sweeny J, Tamminga C, Clementz B. Differentiating Biomarker Features and Familial Characteristics of B-SNIP Psychosis Biotypes. RESEARCH SQUARE 2024:rs.3.rs-3702638. [PMID: 38260530 PMCID: PMC10802686 DOI: 10.21203/rs.3.rs-3702638/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Idiopathic psychosis shows considerable biological heterogeneity across cases. B-SNIP used psychosis-relevant biomarkers to identity psychosis Biotypes, which will aid etiological and targeted treatment investigations. Psychosis probands from the B-SNIP consortium (n = 1907), their first-degree biological relatives (n = 705), and healthy participants (n = 895) completed a biomarker battery composed of cognition, saccades, and auditory EEG measurements. ERP quantifications were substantially modified from previous iterations of this approach. Multivariate integration reduced multiple biomarker outcomes to 11 "bio-factors". Twenty-four different approaches indicated bio-factor data among probands were best distributed as three subgroups. Numerical taxonomy with k-means constructed psychosis Biotypes, and rand indices evaluated consistency of Biotype assignments. Psychosis subgroups, their non-psychotic first-degree relatives, and healthy individuals were compared across bio-factors. The three psychosis Biotypes differed significantly on all 11 bio-factors, especially prominent for general cognition, antisaccades, ERP magnitude, and intrinsic neural activity. Rand indices showed excellent consistency of clustering membership when samples included at least 1100 subjects. Canonical discriminant analysis described composite bio-factors that simplified group comparisons and captured neural dysregulation, neural vigor, and stimulus salience variates. Neural dysregulation captured Biotype-2, low neural vigor captured Biotype-1, and deviations of stimulus salience captured Biotype-3. First-degree relatives showed similar patterns as their Biotyped proband relatives on general cognition, antisaccades, ERP magnitudes, and intrinsic brain activity. Results extend previous efforts by the B-SNIP consortium to characterize biologically distinct psychosis Biotypes. They also show that at least 1100 observations are necessary to achieve consistent outcomes. First-degree relative data implicate specific bio-factor deviations to the subtype of their proband and may inform studies of genetic risk.
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Clementz BA, Chattopadhyay I, Trotti RL, Parker DA, Gershon ES, Hill SK, Ivleva EI, Keedy SK, Keshavan MS, McDowell JE, Pearlson GD, Tamminga CA, Gibbons RD. Clinical characterization and differentiation of B-SNIP psychosis Biotypes: Algorithmic Diagnostics for Efficient Prescription of Treatments (ADEPT)-1. Schizophr Res 2023; 260:143-151. [PMID: 37657281 PMCID: PMC10712427 DOI: 10.1016/j.schres.2023.08.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 08/08/2023] [Accepted: 08/09/2023] [Indexed: 09/03/2023]
Abstract
Clinically defined psychosis diagnoses are neurobiologically heterogeneous. The B-SNIP consortium identified and validated more neurobiologically homogeneous psychosis Biotypes using an extensive battery of neurocognitive and psychophysiological laboratory measures. However, typically the first step in any diagnostic evaluation is the clinical interview. In this project, we evaluated if psychosis Biotypes have clinical characteristics that can support their differentiation in addition to obtaining laboratory testing. Clinical interview data from 1907 individuals with a psychosis Biotype were used to create a diagnostic algorithm. The features were 58 ratings from standard clinical scales. Extremely randomized tree algorithms were used to evaluate sensitivity, specificity, and overall classification success. Biotype classification accuracy peaked at 91 % with the use of 57 items on average. A reduced feature set of 28 items, though, also showed 81 % classification accuracy. Using this reduced item set, we found that only 10-11 items achieved a one-vs-all (Biotype-1 or not, Biotype-2 or not, Biotype-3 or not) area under the sensitivity-specificity curve of .78 to .81. The top clinical characteristics for differentiating psychosis Biotypes, in order of importance, were (i) difficulty in abstract thinking, (ii) multiple indicators of social functioning, (iii) conceptual disorganization, (iv) severity of hallucinations, (v) stereotyped thinking, (vi) suspiciousness, (vii) unusual thought content, (viii) lack of spontaneous speech, and (ix) severity of delusions. These features were remarkably different from those that differentiated DSM psychosis diagnoses. This low-burden adaptive algorithm achieved reasonable classification accuracy and will support Biotype-specific etiological and treatment investigations even in under-resourced clinical and research environments.
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Affiliation(s)
- Brett A Clementz
- Department of Psychology, BioImaging Research Center, University of Georgia, Athens, GA 30602, United States of America.
| | - Ishanu Chattopadhyay
- Department of Medicine, Section of Hospital Medicine, University of Chicago, Chicago, IL, United States of America
| | - Rebekah L Trotti
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, United States of America
| | - David A Parker
- Department of Human Genetics, Emory University School of Medicine, Atlanta VA Medical Center, Atlanta, GA, United States of America
| | - Elliot S Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, United States of America
| | - S Kristian Hill
- Department of Psychology, Rosalind Franklin University of Medicine and Science, North Chicago, IL, United States of America
| | - Elena I Ivleva
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, United States of America
| | - Sarah K Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, United States of America
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, United States of America
| | - Jennifer E McDowell
- Department of Psychology, Owens Institute for Behavioral Research, University of Georgia, Athens, GA 30602, United States of America
| | - Godfrey D Pearlson
- Departments of Psychiatry and Neuroscience, Yale University, School of Medicine, New Haven, CT, United States of America; Olin NeuroPsychiatry Research Center, Institute of Living, Hartford, CT, United States of America
| | - Carol A Tamminga
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, United States of America
| | - Robert D Gibbons
- Center for Health Statistics, Departments of Medicine and Public Health Sciences, University of Chicago, Chicago, IL, United States of America
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Trotti RL, Parker DA, Sabatinelli D, Keshavan MS, Keedy SK, Gershon ES, Pearlson GD, Hill SK, Tamminga CA, McDowell JE, Clementz BA. Emotional scene processing in biotypes of psychosis. Psychiatry Res 2023; 324:115227. [PMID: 37121219 PMCID: PMC10175237 DOI: 10.1016/j.psychres.2023.115227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 04/14/2023] [Accepted: 04/23/2023] [Indexed: 05/02/2023]
Abstract
Social-emotional deficits in psychosis may be indexed by deviations in emotional scene processing, but event-related potential (ERP) studies indicate such deviations may not map cleanly to diagnostic categories. Neurobiologically defined psychosis subgroups offer an alternative that may better capture neurophysiological correlates of social-emotional deficits. The current study investigates emotional scene-elicited ERPs in Biotypes of psychosis in a large (N = 622), well-characterized sample. Electroencephalography was recorded in healthy persons (N = 129), Biotype-1 (N = 195), Biotype-2 (N = 131), and Biotype-3 (N = 167) psychosis cases. ERPs were measured from posterior and centroparietal scalp locations. Neural responses to emotional scenes were compared between healthy and psychosis groups. Multivariate group discrimination analyses resulted in two composite variates that differentiated groups. The first variate displayed large differences between low-cognition (Biotype-1, Biotype-2) and intact-cognition groups (Biotype-3, healthy persons). The second indicated a small-to-moderate distinction of Biotypes-2 and -3 from Biotype-1 and healthy persons. Two multivariate correlations were identified indicating associations between 1) self-reported emotional experience and generalized cognition and 2) socio-occupational functioning and late-stage emotional processing. Psychosis Biotypes displayed emotional processing deficits not apparent in DSM psychosis subgroups. Future translational research may benefit from exploring emotional scene processing in such neurobiologically-defined psychosis groups.
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Affiliation(s)
- R L Trotti
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA.
| | - D A Parker
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - D Sabatinelli
- Department of Psychology, University of Georgia, Athens, GA, USA
| | - M S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - S K Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA
| | - E S Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA
| | - G D Pearlson
- Institute of Living, Hartford Hospital, Hartford, CT, USA
| | - S K Hill
- Department of Psychology, Rosalind Franklin University, North Chicago, IL, USA
| | - C A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - J E McDowell
- Department of Psychology, University of Georgia, Athens, GA, USA
| | - B A Clementz
- Department of Psychology, University of Georgia, Athens, GA, USA
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5
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Clementz BA, Parker DA, Trotti RL, McDowell JE, Keedy SK, Keshavan MS, Pearlson GD, Gershon ES, Ivleva EI, Huang LY, Hill SK, Sweeney JA, Thomas O, Hudgens-Haney M, Gibbons RD, Tamminga CA. Psychosis Biotypes: Replication and Validation from the B-SNIP Consortium. Schizophr Bull 2022; 48:56-68. [PMID: 34409449 PMCID: PMC8781330 DOI: 10.1093/schbul/sbab090] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Current clinical phenomenological diagnosis in psychiatry neither captures biologically homologous disease entities nor allows for individualized treatment prescriptions based on neurobiology. In this report, we studied two large samples of cases with schizophrenia, schizoaffective, and bipolar I disorder with psychosis, presentations with clinical features of hallucinations, delusions, thought disorder, affective, or negative symptoms. A biomarker approach to subtyping psychosis cases (called psychosis Biotypes) captured neurobiological homology that was missed by conventional clinical diagnoses. Two samples (called "B-SNIP1" with 711 psychosis and 274 healthy persons, and the "replication sample" with 717 psychosis and 198 healthy persons) showed that 44 individual biomarkers, drawn from general cognition (BACS), motor inhibitory (stop signal), saccadic system (pro- and anti-saccades), and auditory EEG/ERP (paired-stimuli and oddball) tasks of psychosis-relevant brain functions were replicable (r's from .96-.99) and temporally stable (r's from .76-.95). Using numerical taxonomy (k-means clustering) with nine groups of integrated biomarker characteristics (called bio-factors) yielded three Biotypes that were virtually identical between the two samples and showed highly similar case assignments to subgroups based on cross-validations (88.5%-89%). Biotypes-1 and -2 shared poor cognition. Biotype-1 was further characterized by low neural response magnitudes, while Biotype-2 was further characterized by overactive neural responses and poor sensory motor inhibition. Biotype-3 was nearly normal on all bio-factors. Construct validation of Biotype EEG/ERP neurophysiology using measures of intrinsic neural activity and auditory steady state stimulation highlighted the robustness of these outcomes. Psychosis Biotypes may yield meaningful neurobiological targets for treatments and etiological investigations.
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Affiliation(s)
- Brett A Clementz
- Departments of Psychology and Neuroscience, BioImaging Research Center, University of Georgia, Athens, GA, USA
| | - David A Parker
- Departments of Psychology and Neuroscience, BioImaging Research Center, University of Georgia, Athens, GA, USA
| | - Rebekah L Trotti
- Departments of Psychology and Neuroscience, BioImaging Research Center, University of Georgia, Athens, GA, USA
| | - Jennifer E McDowell
- Departments of Psychology and Neuroscience, BioImaging Research Center, University of Georgia, Athens, GA, USA
| | - Sarah K Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Godfrey D Pearlson
- Departments of Psychiatry and Neuroscience, Yale University School of Medicine, New Haven, CT, USA
- Institute of Living, Hartford Healthcare Corp, Hartford, CT, USA
| | - Elliot S Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA
| | - Elena I Ivleva
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, USA
| | - Ling-Yu Huang
- Departments of Psychology and Neuroscience, BioImaging Research Center, University of Georgia, Athens, GA, USA
| | - S Kristian Hill
- Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago, IL, USA
| | - John A Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Olivia Thomas
- Departments of Psychology and Neuroscience, BioImaging Research Center, University of Georgia, Athens, GA, USA
| | | | - Robert D Gibbons
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA
| | - Carol A Tamminga
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, USA
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Parker DA, Trotti RL, McDowell JE, Keedy SK, Hill SK, Gershon ES, Ivleva EI, Pearlson GD, Keshavan MS, Tamminga CA, Clementz BA. Auditory Oddball Responses Across the Schizophrenia-Bipolar Spectrum and Their Relationship to Cognitive and Clinical Features. Am J Psychiatry 2021; 178:952-964. [PMID: 34407624 DOI: 10.1176/appi.ajp.2021.20071043] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
OBJECTIVE Neural activations during auditory oddball tasks may be endophenotypes for psychosis and bipolar disorder. The authors investigated oddball neural deviations that discriminate multiple diagnostic groups across the schizophrenia-bipolar spectrum (schizophrenia, schizoaffective disorder, psychotic bipolar disorder, and nonpsychotic bipolar disorder) and clarified their relationship to clinical and cognitive features. METHODS Auditory oddball responses to standard and target tones from 64 sensor EEG recordings were compared across patients with psychosis (total N=597; schizophrenia, N=225; schizoaffective disorder, N=201; bipolar disorder with psychosis, N=171), patients with bipolar disorder without psychosis (N=66), and healthy comparison subjects (N=415) from the second iteration of the Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP2) study. EEG activity was analyzed in voltage and in the time-frequency domain (low, beta, and gamma bands). Event-related potentials (ERPs) were compared with those from an independent sample collected during the first iteration of B-SNIP (B-SNIP1; healthy subjects, N=211; psychosis group, N=526) to establish the repeatability of complex oddball ERPs across multiple psychosis syndromes (r values >0.94 between B-SNIP1 and B-SNIP2). RESULTS Twenty-six EEG features differentiated the groups; they were used in discriminant and correlational analyses. EEG variables from the N100, P300, and low-frequency ranges separated the groups along a diagnostic continuum from healthy to bipolar disorder with psychosis/bipolar disorder without psychosis to schizoaffective disorder/schizophrenia and were strongly related to general cognitive function (r=0.91). P50 responses to standard trials and early beta/gamma frequency responses separated the bipolar disorder without psychosis group from the bipolar disorder with psychosis group. P200, N200, and late beta/gamma frequency responses separated the two bipolar disorder groups from the other groups. CONCLUSIONS Neural deviations during auditory processing are related to psychosis history and bipolar disorder. There is a powerful transdiagnostic relationship between severity of these neural deviations and general cognitive performance. These results have implications for understanding the neurobiology of clinical syndromes across the schizophrenia-bipolar spectrum that may have an impact on future biomarker research.
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Affiliation(s)
- David A Parker
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
| | - Rebekah L Trotti
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
| | - Jennifer E McDowell
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
| | - Sarah K Keedy
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
| | - S Kristian Hill
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
| | - Elliot S Gershon
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
| | - Elena I Ivleva
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
| | - Godfrey D Pearlson
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
| | - Matcheri S Keshavan
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
| | - Carol A Tamminga
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
| | - Brett A Clementz
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens (Parker, Trotti, McDowell, Clementz); Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago (Keedy, Gershon); Department of Psychology, Rosalind Franklin University of Medicine and Science, Chicago (Hill); Department of Psychiatry, UT Southwestern Medical Center, Dallas (Ivleva, Tamminga); Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, Conn. (Pearlson); Olin Center, Institute of Living, Hartford Healthcare Corporation, Hartford, Conn. (Pearlson); and Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Cambridge, Mass. (Keshavan)
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7
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Van Derveer AB, Bastos G, Ferrell AD, Gallimore CG, Greene ML, Holmes JT, Kubricka V, Ross JM, Hamm JP. A Role for Somatostatin-Positive Interneurons in Neuro-Oscillatory and Information Processing Deficits in Schizophrenia. Schizophr Bull 2021; 47:1385-1398. [PMID: 33370434 PMCID: PMC8379548 DOI: 10.1093/schbul/sbaa184] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Alterations in neocortical GABAergic interneurons (INs) have been affiliated with neuropsychiatric diseases, including schizophrenia (SZ). Significant progress has been made linking the function of a specific subtype of GABAergic cells, parvalbumin (PV) positive INs, to altered gamma-band oscillations, which, in turn, underlie perceptual and feedforward information processing in cortical circuits. Here, we review a smaller but growing volume of literature focusing on a separate subtype of neocortical GABAergic INs, somatostatin (SST) positive INs. Despite sharing similar neurodevelopmental origins, SSTs exhibit distinct morphology and physiology from PVs. Like PVs, SSTs are altered in postmortem brain samples from multiple neocortical regions in SZ, although basic and translational research into consequences of SST dysfunction has been relatively sparse. We highlight a growing body of work in rodents, which now indicates that SSTs may also underlie specific aspects of cortical circuit function, namely low-frequency oscillations, disinhibition, and mediation of cortico-cortical feedback. SSTs may thereby support the coordination of local cortical information processing with more global spatial, temporal, and behavioral context, including predictive coding and working memory. These functions are notably deficient in some cases of SZ, as well as other neuropsychiatric disorders, emphasizing the importance of focusing on SSTs in future translational studies. Finally, we highlight the challenges that remain, including subtypes within the SST class.
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Affiliation(s)
- Alice B Van Derveer
- Neuroscience Institute, Georgia State University, Petit Science Center, Atlanta, GA
| | - Georgia Bastos
- Neuroscience Institute, Georgia State University, Petit Science Center, Atlanta, GA
- Center for Neuroinflammation and Cardiometabolic Diseases, Georgia State University, Petit Science Center, Atlanta, GA
| | - Antanovia D Ferrell
- Neuroscience Institute, Georgia State University, Petit Science Center, Atlanta, GA
| | - Connor G Gallimore
- Neuroscience Institute, Georgia State University, Petit Science Center, Atlanta, GA
| | - Michelle L Greene
- Neuroscience Institute, Georgia State University, Petit Science Center, Atlanta, GA
| | - Jacob T Holmes
- Neuroscience Institute, Georgia State University, Petit Science Center, Atlanta, GA
| | - Vivien Kubricka
- Neuroscience Institute, Georgia State University, Petit Science Center, Atlanta, GA
| | - Jordan M Ross
- Neuroscience Institute, Georgia State University, Petit Science Center, Atlanta, GA
- Center for Behavioral Neuroscience, Georgia State University, Petit Science Center, Atlanta, GA
| | - Jordan P Hamm
- Neuroscience Institute, Georgia State University, Petit Science Center, Atlanta, GA
- Center for Neuroinflammation and Cardiometabolic Diseases, Georgia State University, Petit Science Center, Atlanta, GA
- Center for Behavioral Neuroscience, Georgia State University, Petit Science Center, Atlanta, GA
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Türközer HB, Ivleva EI, Palka J, Clementz BA, Shafee R, Pearlson GD, Sweeney JA, Keshavan MS, Gershon ES, Tamminga CA. Biomarker Profiles in Psychosis Risk Groups Within Unaffected Relatives Based on Familiality and Age. Schizophr Bull 2021; 47:1058-1067. [PMID: 33693883 PMCID: PMC8266584 DOI: 10.1093/schbul/sbab013] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Investigating biomarkers in unaffected relatives (UR) of individuals with psychotic disorders has already proven productive in research on psychosis neurobiology. However, there is considerable heterogeneity among UR based on features linked to psychosis vulnerability. Here, using the Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) dataset, we examined cognitive and neurophysiologic biomarkers in first-degree UR of psychosis probands, stratified by 2 widely used risk factors: familiality status of the respective proband (the presence or absence of a first- or second-degree relative with a history of psychotic disorder) and age (within or older than the common age range for developing psychosis). We investigated biomarkers that best differentiate the above specific risk subgroups. Additionally, we examined the relationship of biomarkers with Polygenic Risk Scores for Schizophrenia (PRSSCZ) in a subsample of Caucasian probands and healthy controls (HC). Our results demonstrate that the Brief Assessment of Cognition in Schizophrenia (BACS) score, antisaccade error (ASE) factor, and stop-signal task (SST) factor best differentiate UR (n = 169) from HC (n = 137) (P = .013). Biomarker profiles of UR of familial (n = 82) and non-familial (n = 83) probands were not significantly different. Furthermore, ASE and SST factors best differentiated younger UR (age ≤ 30) (n = 59) from older UR (n = 110) and HC from both age groups (age ≤ 30 years, n=49; age > 30 years, n = 88) (P < .001). In addition, BACS (r = -0.175, P = .006) and ASE factor (r = 0.188, P = .006) showed associations with PRSSCZ. Taken together, our findings indicate that cognitive biomarkers-"top-down inhibition" impairments in particular-may be of critical importance as indicators of psychosis vulnerability.
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Affiliation(s)
- Halide Bilge Türközer
- Department of Psychiatry, the University of Texas Southwestern Medical Center, Dallas, TX
| | - Elena I Ivleva
- Department of Psychiatry, the University of Texas Southwestern Medical Center, Dallas, TX
| | - Jayme Palka
- Department of Psychiatry, the University of Texas Southwestern Medical Center, Dallas, TX
| | - Brett A Clementz
- Department of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, GA
| | - Rebecca Shafee
- Department of Genetics, Harvard Medical School, Boston, MA
| | - Godfrey D Pearlson
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, CT
- Departments of Psychiatry and Neuroscience, Yale University, New Haven, CT
| | - John A Sweeney
- Department of Psychiatry, the University of Texas Southwestern Medical Center, Dallas, TX
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH
| | - Matcheri S Keshavan
- Department of Psychiatry and Cognitive Neurology, Beth Israel Deaconess Medical Center, Boston, MA
- Harvard Medical School, Boston, MA
| | - Elliot S Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL
| | - Carol A Tamminga
- Department of Psychiatry, the University of Texas Southwestern Medical Center, Dallas, TX
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9
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Oliver W, Parker D, Hetrick W, Clementz BA. Is a paired-stimuli configuration necessary to obtain typical evoked response differences in studies of psychosis? An MEG study. Biomark Neuropsychiatry 2021; 4. [DOI: 10.1016/j.bionps.2021.100033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
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10
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Tamminga CA, Clementz BA, Pearlson G, Keshavan M, Gershon ES, Ivleva EI, McDowell J, Meda SA, Keedy S, Calhoun VD, Lizano P, Bishop JR, Hudgens-Haney M, Alliey-Rodriguez N, Asif H, Gibbons R. Biotyping in psychosis: using multiple computational approaches with one data set. Neuropsychopharmacology 2021; 46:143-155. [PMID: 32979849 PMCID: PMC7689458 DOI: 10.1038/s41386-020-00849-8] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Revised: 08/24/2020] [Accepted: 08/26/2020] [Indexed: 12/15/2022]
Abstract
Focusing on biomarker identification and using biomarkers individually or in clusters to define biological subgroups in psychiatry requires a re-orientation from behavioral phenomenology to quantifying brain features, requiring big data approaches for data integration. Much still needs to be accomplished, not only to refine but also to build support for the application and customization of such an analytical phenotypic approach. In this review, we present some of what Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) has learned so far to guide future applications of multivariate phenotyping and their analyses to understanding psychosis. This paper describes several B-SNIP projects that use phenotype data and big data computations to generate novel outcomes and glimpse what phenotypes contribute to disease understanding and, with aspiration, to treatment. The source of the phenotypes varies from genetic data, structural neuroanatomic localization, immune markers, brain physiology, and cognition. We aim to see guiding principles emerge and areas of commonality revealed. And, we will need to demonstrate not only data stability but also the usefulness of biomarker information for subgroup identification enhancing target identification and treatment development.
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Affiliation(s)
- Carol A Tamminga
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, 75390, USA.
| | - Brett A Clementz
- Departments of Psychology, Neuroscience, and BioImaging Research Center, University of Georgia, Athens, GA, 30602, USA
| | - Godfrey Pearlson
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, CT, USA
- Departments of Psychiatry & Neuroscience, Yale University, New Haven, CT, USA
| | - Macheri Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, United States
| | - Elliot S Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, 60637, USA
| | - Elena I Ivleva
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Jennifer McDowell
- Departments of Psychology, Neuroscience, and BioImaging Research Center, University of Georgia, Athens, GA, 30602, USA
| | - Shashwath A Meda
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, CT, USA
- Departments of Psychiatry & Neuroscience, Yale University, New Haven, CT, USA
| | - Sarah Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, 60637, USA
| | - Vince D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, USA
| | - Paulo Lizano
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, United States
| | - Jeffrey R Bishop
- Department of Experimental and Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, United States
- Department of Psychiatry, University of Minnesota Medical School, Minneapolis, MN, 55455, USA
| | | | - Ney Alliey-Rodriguez
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, 60637, USA
| | - Huma Asif
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, 60637, USA
| | - Robert Gibbons
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, 60637, USA
- Departments of Medicine and Public Health Sciences, University of Chicago, Chicago, Ill, USA
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11
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Parker DA, Trotti RL, McDowell JE, Keedy SK, Gershon ES, Ivleva EI, Pearlson GD, Keshavan MS, Tamminga CA, Sweeney JA, Clementz BA. Auditory paired-stimuli responses across the psychosis and bipolar spectrum and their relationship to clinical features. Biomark Neuropsychiatry 2020; 3:100014. [PMID: 36644018 PMCID: PMC9837793 DOI: 10.1016/j.bionps.2020.100014] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Abstract
Background EEG responses during auditory paired-stimuli paradigms are putative biomarkers of psychosis syndromes. The initial iteration of the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP1) showed unique and common patterns of abnormalities across schizophrenia (SZ), schizoaffective disorder (SAD), and bipolar disorder with psychosis (BDP). This study replicates those findings in new and large samples of psychosis cases and extends them to an important comparison group, bipolar disorder without psychosis (BDNP). Methods Paired stimuli responses from 64-sensor EEG recording were compared across psychosis (n = 597; SZ = 225, SAD = 201, BDP = 171), BDNP (n = 66), and healthy (n = 415) subjects from the second iteration of B-SNIP. EEG activity was analyzed in voltage and in the time-frequency domain. Principal component analysis (PCA) over sensors (sPCA) was used to efficiently capture EEG voltage responses to the paired stimuli. Evoked power was calculated via a Morlet wavelet procedure. A frequency PCA divided evoked power data into three frequency bands: Low (4-17 Hz), Beta (18-32 Hz), and Gamma (33-55 Hz). Each time-course (ERP Voltage, Low, Beta, and Gamma) were then segmented into 20 ms bins and analyzed for group differences. To efficiently summarize the multiple EEG components that best captured group differences we used multivariate discriminant and correlational analyses. This approach yields a reduced set of measures that may be useful in subsequent biomarker investigations. Results Group ANOVAs identified 17 time-ranges that showed significant group differences (p < .05 after FDR correction), constructively replicating B-SNIP1 findings. Multivariate linear discriminant analysis parsimoniously selected variables that best accounted for group differences: The P50 response to S1 and S2 uniquely separated BDNP from healthy and psychosis subjects (BDNP > all other groups); the S1 N100 response separated groups along an axis of psychopathology severity (HC > BDNP > BDP > SAD > SZ); the S1 P200 response indexed psychosis psychopathology (HC/BDNP > SAD/SZ/BDP); and the preparatory period to the S2 stimulus separated SZ from other groups (SZ > SAD/BDP>HC/BDNP).Canonical correlation identified an association between the neural responses during the S1 N100, S1 N200 and S2 preparatory period and PANSS positive symptoms and social functioning. The neural responses during the S1 P50 and S1 N100 were associated with PANSS Negative/General, MADRS and Young Mania symptoms. Conclusions This study constructively replicated prior B-SNIP1 research on auditory deviations observed during the paired stimuli task in SZ, SAD and BDP. Inclusion of a group of BDNP allows for the identification of biomarkers more closely related to affective versus nonaffective clinical phenotypes and neural distinctions between BDP and BDNP. Findings have implications for nosology and future translational work given that some biomarkers are shared across all psychosis and some are unique to affective syndromes.
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Affiliation(s)
| | | | - Jennifer E. McDowell
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Georgia
| | - Sarah K. Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, United States of America
| | - Elliot S. Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, United States of America
| | - Elena I. Ivleva
- Department of Psychiatry, UT Southwestern Medical Center, United States of America
| | - Godfrey D. Pearlson
- Neuroscience, Yale School of Medicine, Institute of Living, Hartford Hospital, United States of America
| | - Matcheri S. Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, United States of America
| | - Carol A. Tamminga
- Department of Psychiatry, UT Southwestern Medical Center, United States of America
| | - John A. Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, United States of America
| | - Brett A. Clementz
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Georgia, Corresponding author at: Psychology Department, 125 Jackson Street, Athens GA, 30601, Greece. (B.A. Clementz)
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12
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Hudgens-Haney ME, Clementz BA, Ivleva EI, Keshavan MS, Pearlson GD, Gershon ES, Keedy SK, Sweeney JA, Gaudoux F, Bunouf P, Canolle B, Tonner F, Gatti-McArthur S, Tamminga CA. Cognitive Impairment and Diminished Neural Responses Constitute a Biomarker Signature of Negative Symptoms in Psychosis. Schizophr Bull 2020; 46:1269-1281. [PMID: 32043133 PMCID: PMC7505197 DOI: 10.1093/schbul/sbaa001] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
The treatment of negative symptoms (NS) in psychosis represents an urgent unmet medical need given the significant functional impairment it contributes to psychosis syndromes. The lack of progress in treating NS is impacted by the lack of known pathophysiology or associated quantitative biomarkers, which could provide tools for research. This current analysis investigated potential associations between NS and an extensive battery of behavioral and brain-based biomarkers in 932 psychosis probands from the B-SNIP database. The current analyses examined associations between PANSS-defined NS and (1) cognition, (2) pro-/anti-saccades, (3) evoked and resting-state electroencephalography (EEG), (4) resting-state fMRI, and (5) tractography. Canonical correlation analyses yielded symptom-biomarker constructs separately for each biomarker modality. Biomarker modalities were integrated using canonical discriminant analysis to summarize the symptom-biomarker relationships into a "biomarker signature" for NS. Finally, distinct biomarker profiles for 2 NS domains ("diminished expression" vs "avolition/apathy") were computed using step-wise linear regression. NS were associated with cognitive impairment, diminished EEG response amplitudes, deviant resting-state activity, and oculomotor abnormalities. While a connection between NS and poor cognition has been established, association to neurophysiology is novel, suggesting directions for future mechanistic studies. Each biomarker modality was related to NS in distinct and complex ways, giving NS a rich, interconnected fingerprint and suggesting that any one biomarker modality may not adequately capture the full spectrum of symptomology.
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Affiliation(s)
| | - Brett A Clementz
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, GA
| | - Elena I Ivleva
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA
| | - Godfrey D Pearlson
- Departments of Psychiatry and Neurobiology, Yale University School of Medicine, New Haven, CT
- Institute of Living, Hartford Hospital, Hartford, CT
| | | | - Sarah K Keedy
- Department of Psychiatry, University of Chicago, Chicago, IL
| | - John A Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH
| | | | | | | | | | | | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX
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13
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Ross JM, Hamm JP. Cortical Microcircuit Mechanisms of Mismatch Negativity and Its Underlying Subcomponents. Front Neural Circuits 2020; 14:13. [PMID: 32296311 PMCID: PMC7137737 DOI: 10.3389/fncir.2020.00013] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Accepted: 03/17/2020] [Indexed: 12/11/2022] Open
Abstract
In the neocortex, neuronal processing of sensory events is significantly influenced by context. For instance, responses in sensory cortices are suppressed to repetitive or redundant stimuli, a phenomenon termed “stimulus-specific adaptation” (SSA). However, in a context in which that same stimulus is novel, or deviates from expectations, neuronal responses are augmented. This augmentation is termed “deviance detection” (DD). This contextual modulation of neural responses is fundamental for how the brain efficiently processes the sensory world to guide immediate and future behaviors. Notably, context modulation is deficient in some neuropsychiatric disorders such as schizophrenia (SZ), as quantified by reduced “mismatch negativity” (MMN), an electroencephalography waveform reflecting a combination of SSA and DD in sensory cortex. Although the role of NMDA-receptor function and other neuromodulatory systems on MMN is established, the precise microcircuit mechanisms of MMN and its underlying components, SSA and DD, remain unknown. When coupled with animal models, the development of powerful precision neurotechnologies over the past decade carries significant promise for making new progress into understanding the neurobiology of MMN with previously unreachable spatial resolution. Currently, rodent models represent the best tool for mechanistic study due to the vast genetic tools available. While quantifying human-like MMN waveforms in rodents is not straightforward, the “oddball” paradigms used to study it in humans and its underlying subcomponents (SSA/DD) are highly translatable across species. Here we summarize efforts published so far, with a focus on cortically measured SSA and DD in animals to maintain relevance to the classically measured MMN, which has cortical origins. While mechanistic studies that measure and contrast both components are sparse, we synthesize a potential set of microcircuit mechanisms from the existing rodent, primate, and human literature. While MMN and its subcomponents likely reflect several mechanisms across multiple brain regions, understanding fundamental microcircuit mechanisms is an important step to understand MMN as a whole. We hypothesize that SSA reflects adaptations occurring at synapses along the sensory-thalamocortical pathways, while DD depends on both SSA inherited from afferent inputs and resulting disinhibition of non-adapted neurons arising from the distinct physiology and wiring properties of local interneuronal subpopulations and NMDA-receptor function.
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Affiliation(s)
- Jordan M Ross
- Neuroscience Institute, Georgia State University, Atlanta, GA, United States.,Center for Behavioral Neuroscience, Georgia State University, Atlanta, GA, United States
| | - Jordan P Hamm
- Neuroscience Institute, Georgia State University, Atlanta, GA, United States.,Center for Behavioral Neuroscience, Georgia State University, Atlanta, GA, United States.,Center for Neuroinflammation and Cardiometabolic Diseases, Georgia State University, Atlanta, GA, United States
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14
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Intrinsic neural activity differences in psychosis biotypes: Findings from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) consortium. Biomark Neuropsychiatry 2019; 1:100002. [PMID: 36643612 PMCID: PMC9837786 DOI: 10.1016/j.bionps.2019.100002] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
Intro The Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) proposed "Biotypes," subgroups of psychosis cases with neuro-cognitive homology. Neural activity unbound to stimulus processing (nonspecific or intrinsic activity) was important for differentiating Biotypes, with Biotype-2 characterized by high nonspecific neural activity. A precise estimate of intrinsic activity (IA) was not included in the initial Biotypes characterization. This report hypothesizes intrinsic activity is a critical differentiating feature for psychosis Biotypes. Method Participants were recruited at B-SNIP sites and included probands with psychosis (schizophrenia, schizoaffective disorder, bipolar I disorder), their first-degree biological relatives, and healthy persons (N = 1338). Probands were also sub-grouped by psychosis Biotype. 10-sec inter-stimulus intervals during an auditory paired-stimuli task were used to quantify intrinsic activity from 64 EEG sensors. Single-trial power and connectivity measures at empirically derived frequency bands were quantified. Multivariate discriminant and correlational analyses were used to summarize variables that efficiently and maximally differentiated groups by conventional diagnoses and Biotypes and to determine their relationship to clinical and social functioning. Results Biotype-1 consistently exhibited low IA, and Biotype 2 exhibited high IA relative to healthy persons across power frequency bands (delta/theta, alpha, beta, gamma) and alpha band connectivity estimates. DSM groups did not differ from healthy persons on any IA measure. Discussion Psychosis Biotypes, but not DSM syndromes, were differentiated by intrinsic activity; Biotype-2 was uniquely characterized by an accentuation of this measure. Neurobiologically defined psychosis subgroups may facilitate the use of intrinsic activity in translation models aimed at developing effective treatments for psychosisrelevant deviations in neural modulation.
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15
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Parker DA, Hamm JP, McDowell JE, Keedy SK, Gershon ES, Ivleva EI, Pearlson GD, Keshavan MS, Tamminga CA, Sweeney JA, Clementz BA. Auditory steady-state EEG response across the schizo-bipolar spectrum. Schizophr Res 2019; 209:218-226. [PMID: 31080153 PMCID: PMC6661193 DOI: 10.1016/j.schres.2019.04.014] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/08/2019] [Revised: 04/15/2019] [Accepted: 04/18/2019] [Indexed: 11/29/2022]
Abstract
UNLABELLED Deviant auditory steady-state responses (aSSRs) in the gamma range (30-90 Hz) may be translational biomarkers for schizophrenia (SZ). This study tests whether aSSR deviations are (i) specific to SZ across the psychosis dimension, (ii) specific to particular frequency bands, and (iii) present in bipolar I disorder without psychosis (BDNP). METHODS Beta (20-), low- (40-), and high-gamma (80-Hz) aSSRs were measured with EEG and compared across 113 SZ, 105 schizoaffective disorder (SAD), 99 bipolar disorder with psychosis (BDP), 68 BDNP, and 137 healthy comparison subjects (HC). Standard aSSR measures (single-trial power [STP] and inter-trial phase coherence [ITC]), as well as evoked responses to stimulus onsets/offsets and pre-stimulus power, were quantified. Multivariate canonical discriminant analysis was used to summarize variables that efficiently and maximally differentiated groups. RESULTS (i) Psychosis groups showed reduced responses on ITC 20 Hz, STP/ITC 40 Hz, STP/ITC 80 Hz, indicating dimensional reductions in aSSR across the psychosis spectrum not specific to aSSR frequency. For the 40- and 80-Hz ITCs there was greater reduction in SZ compared to SAD, possibly indexing cortical disruptions linked to psychosis without mood symptoms. (ii) All probands had elevated pre-stimulus power, possibly compromising neural entrainment to the steady-state stimuli. (iii) Onset/Offset and 80 Hz ITC responses were most important for group discrimination and showed dimensional reduction across the schizo-bipolar spectrum. CONCLUSIONS Deviant aSSRs were found across the schizo-bipolar spectrum at multiple frequencies with psychosis status and severity linked to greatest reductions at low and high gamma.
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Affiliation(s)
- David A. Parker
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, GA, United States
| | - Jordan P. Hamm
- Neuroscience Institute, Georgia State University, Atlanta, GA, United States
| | - Jennifer E. McDowell
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, GA, United States
| | - Sarah K. Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, United States
| | - Elliot S. Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, United States
| | - Elena I. Ivleva
- Department of Psychiatry, UT-Southwestern Medical Center, Dallas, TX, United States
| | - Godfrey D. Pearlson
- Departments of Psychiatry and Neurobiology, Yale University School of Medicine, New Haven, CT, United States,Institute of Living, Hartford Hospital, Hartford, CT, United States
| | - Matcheri S. Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, United States
| | - Carol A. Tamminga
- Department of Psychiatry, UT-Southwestern Medical Center, Dallas, TX, United States
| | - John A. Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, United States
| | - Brett A. Clementz
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, GA, United States
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16
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Rodrigue AL, McDowell JE, Tandon N, Keshavan MS, Tamminga CA, Pearlson GD, Sweeney JA, Gibbons RD, Clementz BA. Multivariate Relationships Between Cognition and Brain Anatomy Across the Psychosis Spectrum. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2018; 3:992-1002. [PMID: 29759822 PMCID: PMC6167203 DOI: 10.1016/j.bpsc.2018.03.012] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2017] [Revised: 03/08/2018] [Accepted: 03/09/2018] [Indexed: 12/21/2022]
Abstract
BACKGROUND Cognitive and structural brain abnormalities range from mild to severe in psychosis. The relationships of specific cognitive functions to specific brain structures across the psychosis spectrum is less certain. METHODS Participants (n = 678) with bipolar, schizoaffective, or schizophrenia psychoses and healthy control subjects were recruited via the Bipolar-Schizophrenia Network for Intermediate Phenotypes. The Schizo-Bipolar Scale was used to create a psychosis continuum (from purely affective to purely nonaffective). Canonical correlation between 14 cognitive measures and structural brain measures (gray matter volume, cortical thickness, cortical surface area, and local gyrification indices) for 68 neocortical regions yielded constructs that defined shared cognition-brain structure relationships. Canonical discriminant analysis was used to integrate these constructs and efficiently summarize cognition-brain structure relationships across the psychosis continuum. RESULTS General cognition was associated with larger gray matter volumes and thicker cortices but smaller cortical surface area in frontoparietal regions. Working memory was associated with larger volume and surface area in frontotemporal regions. Faster response speed was associated with thicker frontal cortices. Constructs that captured general cognitive ability and working memory and their relationship to cortical volumes primarily defined an ordered psychosis spectrum (purely affective, least abnormal through purely nonaffective, and most abnormal). A construct that captured general cognitive ability and its relationship to cortical surface area differentiated purely affective cases from other groups. CONCLUSIONS General cognition and working memory with cortical volume deviations characterized more nonaffective psychoses. Alternatively, affective psychosis cases with general cognitive deficits had deviations in cortical surface area, perhaps accounting for heterogeneous findings across previous studies.
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Affiliation(s)
- Amanda L Rodrigue
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, Georgia
| | - Jennifer E McDowell
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, Georgia
| | - Neeraj Tandon
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Godfrey D Pearlson
- Departments of Psychiatry and Neuroscience, Yale University School of Medicine, New Haven, Connecticut; Olin Neuropsychiatry Research Center, Institute of Living, Hartford Hospital, Hartford, Connecticut
| | - John A Sweeney
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas; Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, Ohio
| | - Robert D Gibbons
- Department of Medicine and Public Health Sciences, University of Chicago, Chicago, Illinois
| | - Brett A Clementz
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, Georgia.
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17
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Hudgens-Haney ME, Ethridge LE, McDowell JE, Keedy SK, Pearlson GD, Tamminga CA, Keshavan MS, Sweeney JA, Clementz BA. Psychosis subgroups differ in intrinsic neural activity but not task-specific processing. Schizophr Res 2018; 195:222-230. [PMID: 28844436 PMCID: PMC5826774 DOI: 10.1016/j.schres.2017.08.023] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/25/2017] [Revised: 08/11/2017] [Accepted: 08/16/2017] [Indexed: 12/12/2022]
Abstract
Individuals with psychosis often show high levels of intrinsic, or nonspecific, neural activity, but attenuated stimulus-specific activity. Clementz et al. (2016) proposed that one subgroup of psychosis cases has accentuated intrinsic activity (Biotype-2's) and a different subgroup (Biotype-1's) has diminished intrinsic activity, with both groups exhibiting varying degrees of cognitive deficits. This model was studied by assessing neural activity in psychosis probands (N=105) during baseline and a 5second period in preparation for a pro-/anti-saccade task. Steady-state stimuli allowed real-time assessment of modulation of visuocortical investment to different target locations. Psychosis probands as a whole showed poor antisaccade performance. As expected, Biotype-1 showed diminished intrinsic neural activity and the worst behavior, and Biotype-2 showed accentuated intrinsic activity and less deviant behavior. Both of these groups also exhibited less dynamic oscillatory phase synchrony. Biotype-3 showed no neurophysiological differences from healthy individuals, despite a history of psychosis. Interestingly, all psychosis subgroups showed normal (i.e., not different from healthy) preparatory modulation of visuocortical investment as a function of cognitive demands, despite varying levels of task performance. Similar analyses conducted subgrouping cases by psychotic symptomatology revealed fewer and less consistent differences, including no intrinsic activity differences between any clinical subgroup and healthy individuals. This study illustrates that (i) differences in intrinsic neural activity may be a fundamental characteristic of psychosis and need to be evaluated separately from stimulus-specific responses, and (ii) grouping patients based on multidimensional classification using neurobiological data may have advantages for resolving heterogeneity and clarifying illness mechanisms relative to traditional psychiatric diagnoses.
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Affiliation(s)
- Matthew E. Hudgens-Haney
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, Georgia
| | - Lauren E. Ethridge
- Department of Pediatrics, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma,Department of Psychology, University of Oklahoma, Norman, Oklahoma
| | - Jennifer E. McDowell
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, Georgia
| | - Sarah K. Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, Illinois
| | - Godfrey D. Pearlson
- Departments of Psychiatry and Neurobiology, Yale University School of Medicine, New Haven, Connecticut,Institute of Living, Hartford Hospital, Hartford, Connecticut
| | | | | | - John A. Sweeney
- Department of Psychiatry, UT-Southwestern, Dallas, Texas,Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Ohio
| | - Brett A. Clementz
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, Georgia,To whom correspondence should be addressed: Brett A. Clementz, Ph.D. Psychology Department, Psychology Building, University of Georgia, Athens, GA 30602. , 706-542-2174
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18
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Altered Cortical Ensembles in Mouse Models of Schizophrenia. Neuron 2017; 94:153-167.e8. [PMID: 28384469 DOI: 10.1016/j.neuron.2017.03.019] [Citation(s) in RCA: 130] [Impact Index Per Article: 18.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2015] [Revised: 10/07/2016] [Accepted: 03/10/2017] [Indexed: 01/26/2023]
Abstract
In schizophrenia, brain-wide alterations have been identified at the molecular and cellular levels, yet how these phenomena affect cortical circuit activity remains unclear. We studied two mouse models of schizophrenia-relevant disease processes: chronic ketamine (KET) administration and Df(16)A+/-, modeling 22q11.2 microdeletions, a genetic variant highly penetrant for schizophrenia. Local field potential recordings in visual cortex confirmed gamma-band abnormalities similar to patient studies. Two-photon calcium imaging of local cortical populations revealed in both models a deficit in the reliability of neuronal coactivity patterns (ensembles), which was not a simple consequence of altered single-neuron activity. This effect was present in ongoing and sensory-evoked activity and was not replicated by acute ketamine administration or pharmacogenetic parvalbumin-interneuron suppression. These results are consistent with the hypothesis that schizophrenia is an "attractor" disease and demonstrate that degraded neuronal ensembles are a common consequence of diverse genetic, cellular, and synaptic alterations seen in chronic schizophrenia.
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Mokhtari M, Narayanan B, Hamm JP, Soh P, Calhoun VD, Ruaño G, Kocherla M, Windemuth A, Clementz BA, Tamminga CA, Sweeney JA, Keshavan MS, Pearlson GD. Multivariate Genetic Correlates of the Auditory Paired Stimuli-Based P2 Event-Related Potential in the Psychosis Dimension From the BSNIP Study. Schizophr Bull 2016; 42:851-62. [PMID: 26462502 PMCID: PMC4838080 DOI: 10.1093/schbul/sbv147] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
OBJECTIVE The complex molecular etiology of psychosis in schizophrenia (SZ) and psychotic bipolar disorder (PBP) is not well defined, presumably due to their multifactorial genetic architecture. Neurobiological correlates of psychosis can be identified through genetic associations of intermediate phenotypes such as event-related potential (ERP) from auditory paired stimulus processing (APSP). Various ERP components of APSP are heritable and aberrant in SZ, PBP and their relatives, but their multivariate genetic factors are less explored. METHODS We investigated the multivariate polygenic association of ERP from 64-sensor auditory paired stimulus data in 149 SZ, 209 PBP probands, and 99 healthy individuals from the multisite Bipolar-Schizophrenia Network on Intermediate Phenotypes study. Multivariate association of 64-channel APSP waveforms with a subset of 16 999 single nucleotide polymorphisms (SNPs) (reduced from 1 million SNP array) was examined using parallel independent component analysis (Para-ICA). Biological pathways associated with the genes were assessed using enrichment-based analysis tools. RESULTS Para-ICA identified 2 ERP components, of which one was significantly correlated with a genetic network comprising multiple linearly coupled gene variants that explained ~4% of the ERP phenotype variance. Enrichment analysis revealed epidermal growth factor, endocannabinoid signaling, glutamatergic synapse and maltohexaose transport associated with P2 component of the N1-P2 ERP waveform. This ERP component also showed deficits in SZ and PBP. CONCLUSIONS Aberrant P2 component in psychosis was associated with gene networks regulating several fundamental biologic functions, either general or specific to nervous system development. The pathways and processes underlying the gene clusters play a crucial role in brain function, plausibly implicated in psychosis.
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Affiliation(s)
- Mohammadreza Mokhtari
- Olin Neuropsychiatry Research Center, Hartford Hospital, Institute of Living, Hartford, CT
| | - Balaji Narayanan
- Olin Neuropsychiatry Research Center, Hartford Hospital, Institute of Living, Hartford, CT;
| | - Jordan P. Hamm
- Department of Psychology, University of Georgia, Athens, GA
| | - Pauline Soh
- Olin Neuropsychiatry Research Center, Hartford Hospital, Institute of Living, Hartford, CT
| | - Vince D. Calhoun
- Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM;,Image Analysis and MR Research Center, The Mind Research Network, Albuquerque, NM
| | - Gualberto Ruaño
- Genetics Research Center, Hartford Hospital, Hartford, CT;,Genomas Inc, Hartford, CT
| | - Mohan Kocherla
- Genetics Research Center, Hartford Hospital, Hartford, CT;,Genomas Inc, Hartford, CT
| | | | | | - Carol A. Tamminga
- Department of Psychiatry, UT Southwestern Medical School, Dallas, TX
| | - John A. Sweeney
- Department of Psychiatry, UT Southwestern Medical School, Dallas, TX
| | - Matcheri S. Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA
| | - Godfrey D. Pearlson
- Olin Neuropsychiatry Research Center, Hartford Hospital, Institute of Living, Hartford, CT;,Departments of Psychiatry and Neurobiology, Yale University School of Medicine, New Haven, CT
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20
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Greenwood TA, Light GA, Swerdlow NR, Calkins ME, Green MF, Gur RE, Gur RC, Lazzeroni LC, Nuechterlein KH, Olincy A, Radant AD, Seidman LJ, Siever LJ, Silverman JM, Stone WS, Sugar CA, Tsuang DW, Tsuang MT, Turetsky BI, Freedman R, Braff DL. Gating Deficit Heritability and Correlation With Increased Clinical Severity in Schizophrenia Patients With Positive Family History. Am J Psychiatry 2016; 173:385-91. [PMID: 26441157 PMCID: PMC4933520 DOI: 10.1176/appi.ajp.2015.15050605] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
OBJECTIVE The Consortium on the Genetics of Schizophrenia Family Study evaluated 12 primary and other supplementary neurocognitive and neurophysiological endophenotypes in schizophrenia probands and their families. Previous analyses of prepulse inhibition (PPI) and P50 gating measures in this sample revealed heritability estimates that were lower than expected based on earlier family studies. Here the authors investigated whether gating measures were more heritable in multiply affected families with a positive family history compared with families with only a single affected proband (singleton). METHOD A total of 296 nuclear families consisting of a schizophrenia proband, at least one unaffected sibling, and both parents underwent a comprehensive endophenotype and clinical characterization. The Family Interview for Genetic Studies was administered to all participants and used to obtain convergent psychiatric symptom information for additional first-degree relatives. Among the families, 97 were multiply affected, and 96 were singletons. RESULTS Both PPI and P50 gating displayed substantially increased heritability in the 97 multiply affected families (47% and 36%, respectively) compared with estimates derived from the entire sample of 296 families (29% and 20%, respectively). However, no evidence for heritability was observed for either measure in the 96 singleton families. Schizophrenia probands derived from the multiply affected families also displayed a significantly increased severity of clinical symptoms compared with those from singleton families. CONCLUSIONS PPI and P50 gating measures demonstrate substantially increased heritability in schizophrenia families with a higher genetic vulnerability for illness, providing further support for the commonality of genes underlying both schizophrenia and gating measures.
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Affiliation(s)
| | - Gregory A. Light
- Department of Psychiatry, University of California San Diego, La Jolla, CA,VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System
| | - Neal R. Swerdlow
- Department of Psychiatry, University of California San Diego, La Jolla, CA
| | - Monica E. Calkins
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA
| | - Michael F. Green
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA,VA Greater Los Angeles Healthcare System, Los Angeles, CA
| | - Raquel E. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA
| | - Ruben C. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA
| | - Laura C. Lazzeroni
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA
| | - Keith H. Nuechterlein
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA
| | - Ann Olincy
- Department of Psychiatry, University of Colorado Health Sciences Center, Denver, CO
| | - Allen D. Radant
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA,VA Puget Sound Health Care System, Seattle, WA
| | - Larry J. Seidman
- Department of Psychiatry, Harvard Medical School, Boston, MA,Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston, MA
| | - Larry J. Siever
- Department of Psychiatry, The Mount Sinai School of Medicine, New York, NY,James J. Peters VA Medical Center, New York, NY
| | - Jeremy M. Silverman
- Department of Psychiatry, The Mount Sinai School of Medicine, New York, NY,James J. Peters VA Medical Center, New York, NY
| | - William S. Stone
- Department of Psychiatry, Harvard Medical School, Boston, MA,Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston, MA
| | - Catherine A. Sugar
- Department of Biostatistics, University of California Los Angeles School of Public Health, Los Angeles, CA
| | - Debby W. Tsuang
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA,VA Puget Sound Health Care System, Seattle, WA
| | - Ming T. Tsuang
- Department of Psychiatry, University of California San Diego, La Jolla, CA,Center for Behavioral Genomics, and Institute for Genomic Medicine, University of California San Diego, La Jolla, CA,Harvard Institute of Psychiatric Epidemiology and Genetics, Boston, MA
| | - Bruce I. Turetsky
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA
| | - Robert Freedman
- Department of Psychiatry, University of Colorado Health Sciences Center, Denver, CO
| | - David L. Braff
- Department of Psychiatry, University of California San Diego, La Jolla, CA,VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System
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21
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Ethridge LE, White SP, Mosconi MW, Wang J, Byerly MJ, Sweeney JA. Reduced habituation of auditory evoked potentials indicate cortical hyper-excitability in Fragile X Syndrome. Transl Psychiatry 2016; 6:e787. [PMID: 27093069 PMCID: PMC4872406 DOI: 10.1038/tp.2016.48] [Citation(s) in RCA: 115] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/16/2015] [Revised: 02/11/2016] [Accepted: 02/15/2016] [Indexed: 11/09/2022] Open
Abstract
Sensory hypersensitivities are common, clinically distressing features of Fragile X Syndrome (FXS). Preclinical evidence suggests this abnormality may result from synaptic hyper-excitability in sensory systems. This model predicts reduced sensory habituation to repeated stimulus presentation. Fourteen adolescents and adults with FXS and 15 age-matched controls participated in a modified auditory gating task using trains of 4 identical tones during dense array electroencephalography (EEG). Event-related potential and single trial time-frequency analyses revealed decreased habituation of the N1 event-related potential response in FXS, and increased gamma power coupled with decreases in gamma phase-locking during the early-stimulus registration period. EEG abnormalities in FXS were associated with parent reports of heightened sensory sensitivities and social communication deficits. Reduced habituation and altered gamma power and phase-locking to auditory cues demonstrated here in FXS patients parallels preclinical findings with Fmr1 KO mice. Thus, the EEG abnormalities seen in FXS patients support the model of neocortical hyper-excitability in FXS, and may provide useful translational biomarkers for evaluating novel treatment strategies targeting its neural substrate.
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Affiliation(s)
- L E Ethridge
- Department of Pediatrics, Section on Developmental and Behavioral Pediatrics, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA,Department of Psychology, University of Oklahoma, Norman, OK, USA,Department of Pediatrics, Section on Developmental and Behavioral Pediatrics, University of Oklahoma Health Sciences Center, 1100 North East 13th Street, Nicholson Tower, Suite 4900, Oklahoma City, OK 73104, USA. E-mail:
| | - S P White
- Department of Psychiatry, Center for Autism and Developmental Disabilities, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - M W Mosconi
- Department of Psychiatry, Center for Autism and Developmental Disabilities, University of Texas Southwestern Medical Center, Dallas, TX, USA,Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX, USA,Departments of Applied Behavioral Science and Psychology, Schiefelbusch Institute for Life Span Studies and Clinical Child Psychology Program, University of Kansas, Lawrence, KS, USA
| | - J Wang
- Department of Psychiatry, Center for Autism and Developmental Disabilities, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - M J Byerly
- Department of Psychiatry, Center for Autism and Developmental Disabilities, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - J A Sweeney
- Department of Psychiatry, Center for Autism and Developmental Disabilities, University of Texas Southwestern Medical Center, Dallas, TX, USA,Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX, USA
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22
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Clementz BA, Sweeney JA, Hamm JP, Ivleva EI, Ethridge LE, Pearlson GD, Keshavan MS, Tamminga CA. Identification of Distinct Psychosis Biotypes Using Brain-Based Biomarkers. Am J Psychiatry 2016; 173:373-84. [PMID: 26651391 PMCID: PMC5314432 DOI: 10.1176/appi.ajp.2015.14091200] [Citation(s) in RCA: 466] [Impact Index Per Article: 58.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
OBJECTIVE Clinical phenomenology remains the primary means for classifying psychoses despite considerable evidence that this method incompletely captures biologically meaningful differentiations. Rather than relying on clinical diagnoses as the gold standard, this project drew on neurobiological heterogeneity among psychosis cases to delineate subgroups independent of their phenomenological manifestations. METHOD A large biomarker panel (neuropsychological, stop signal, saccadic control, and auditory stimulation paradigms) characterizing diverse aspects of brain function was collected on individuals with schizophrenia, schizoaffective disorder, and bipolar disorder with psychosis (N=711), their first-degree relatives (N=883), and demographically comparable healthy subjects (N=278). Biomarker variance across paradigms was exploited to create nine integrated variables that were used to capture neurobiological variance among the psychosis cases. Data on external validating measures (social functioning, structural magnetic resonance imaging, family biomarkers, and clinical information) were collected. RESULTS Multivariate taxometric analyses identified three neurobiologically distinct psychosis biotypes that did not respect clinical diagnosis boundaries. The same analysis procedure using clinical DSM diagnoses as the criteria was best described by a single severity continuum (schizophrenia worse than schizoaffective disorder worse than bipolar psychosis); this was not the case for biotypes. The external validating measures supported the distinctiveness of these subgroups compared with clinical diagnosis, highlighting a possible advantage of neurobiological versus clinical categorization schemes for differentiating psychotic disorders. CONCLUSIONS These data illustrate how multiple pathways may lead to clinically similar psychosis manifestations, and they provide explanations for the marked heterogeneity observed across laboratories on the same biomarker variables when DSM diagnoses are used as the gold standard.
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Affiliation(s)
- Brett A Clementz
- From the Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens; the Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas; the Departments of Psychiatry and Neurobiology, Yale University School of Medicine, New Haven, Conn., and the Institute of Living, Hartford Hospital, Hartford, Conn.; and the Department of Psychiatry, Harvard Medical School, Boston
| | - John A Sweeney
- From the Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens; the Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas; the Departments of Psychiatry and Neurobiology, Yale University School of Medicine, New Haven, Conn., and the Institute of Living, Hartford Hospital, Hartford, Conn.; and the Department of Psychiatry, Harvard Medical School, Boston
| | - Jordan P Hamm
- From the Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens; the Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas; the Departments of Psychiatry and Neurobiology, Yale University School of Medicine, New Haven, Conn., and the Institute of Living, Hartford Hospital, Hartford, Conn.; and the Department of Psychiatry, Harvard Medical School, Boston
| | - Elena I Ivleva
- From the Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens; the Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas; the Departments of Psychiatry and Neurobiology, Yale University School of Medicine, New Haven, Conn., and the Institute of Living, Hartford Hospital, Hartford, Conn.; and the Department of Psychiatry, Harvard Medical School, Boston
| | - Lauren E Ethridge
- From the Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens; the Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas; the Departments of Psychiatry and Neurobiology, Yale University School of Medicine, New Haven, Conn., and the Institute of Living, Hartford Hospital, Hartford, Conn.; and the Department of Psychiatry, Harvard Medical School, Boston
| | - Godfrey D Pearlson
- From the Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens; the Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas; the Departments of Psychiatry and Neurobiology, Yale University School of Medicine, New Haven, Conn., and the Institute of Living, Hartford Hospital, Hartford, Conn.; and the Department of Psychiatry, Harvard Medical School, Boston
| | - Matcheri S Keshavan
- From the Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens; the Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas; the Departments of Psychiatry and Neurobiology, Yale University School of Medicine, New Haven, Conn., and the Institute of Living, Hartford Hospital, Hartford, Conn.; and the Department of Psychiatry, Harvard Medical School, Boston
| | - Carol A Tamminga
- From the Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens; the Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas; the Departments of Psychiatry and Neurobiology, Yale University School of Medicine, New Haven, Conn., and the Institute of Living, Hartford Hospital, Hartford, Conn.; and the Department of Psychiatry, Harvard Medical School, Boston
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23
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Hayrynen LK, Hamm JP, Sponheim SR, Clementz BA. Frequency-specific disruptions of neuronal oscillations reveal aberrant auditory processing in schizophrenia. Psychophysiology 2016; 53:786-95. [PMID: 26933842 DOI: 10.1111/psyp.12635] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2015] [Accepted: 02/03/2016] [Indexed: 01/26/2023]
Abstract
Individuals with schizophrenia exhibit abnormalities in evoked brain responses in oddball paradigms. These could result from (a) insufficient salience-related cortical signaling (P300), (b) insufficient suppression of irrelevant aspects of the auditory environment, or (c) excessive neural noise. We tested whether disruption of ongoing auditory steady-state responses at predetermined frequencies informed which of these issues contribute to auditory stimulus relevance processing abnormalities in schizophrenia. Magnetoencephalography data were collected for 15 schizophrenia and 15 healthy subjects during an auditory oddball paradigm (25% targets; 1-s interstimulus interval). Auditory stimuli (pure tones: 1 kHz standards, 2 kHz targets) were administered during four continuous background (auditory steady-state) stimulation conditions: (1) no stimulation, (2) 24 Hz, (3) 40 Hz, and (4) 88 Hz. The modulation of the auditory steady-state response (aSSR) and the evoked responses to the transient stimuli were quantified and compared across groups. In comparison to healthy participants, the schizophrenia group showed greater disruption of the ongoing aSSR by targets regardless of steady-state frequency, and reduced amplitude of both M100 and M300 event-related field components. During the no-stimulation condition, schizophrenia patients showed accentuation of left hemisphere 40 Hz response to both standard and target stimuli, indicating an effort to enhance local stimulus processing. Together, these findings suggest abnormalities in auditory stimulus relevance processing in schizophrenia patients stem from insufficient amplification of salient stimuli.
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Affiliation(s)
- Lauren K Hayrynen
- Departments of Psychology and Neuroscience, University of Georgia, Athens, Georgia, USA
| | - Jordan P Hamm
- Departments of Psychology and Neuroscience, University of Georgia, Athens, Georgia, USA.,Department of Biological Sciences, Columbia University, New York, New York, USA
| | - Scott R Sponheim
- Minneapolis VA Health Care System, Minneapolis, Minnesota, USA.,Department of Psychiatry, University of Minnesota, Minneapolis, Minnesota, USA
| | - Brett A Clementz
- Departments of Psychology and Neuroscience, University of Georgia, Athens, Georgia, USA
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24
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Gershon ES, Grennan KS. Genetic and genomic analyses as a basis for new diagnostic nosologies. DIALOGUES IN CLINICAL NEUROSCIENCE 2015. [PMID: 25987865 PMCID: PMC4421903 DOI: 10.31887/dcns.2015.17.1/egershon] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
For schizophrenia, bipolar disorder, and autism, clinical descriptions are precise and reliable, but there is great overlap among diagnoses in associated genetic polymorphisms and rare variants, treatment response, and other phenomenological findings such as brain imaging. It is widely hoped that new diagnostic categories can be developed which are more precise and predictive of important features of illness, particularly response to pharmacological agents. It is the intent of this paper to describe the diagnostic implications of some current genetic findings, and to describe how the genetic associations with diagnosis may be teased apart into new associations with biologically coherent diagnostic entities and scales, based on the various functional aspects of the associated genes and functional genomic data.
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Affiliation(s)
- Elliot S Gershon
- Department of Psychiatry and Behavioral Neuroscience; Department of Human Genetics, University of Chicago, Illinois, USA
| | - Kay S Grennan
- Department of Psychiatry and Behavioral Neuroscience; University of Chicago, Illinois, USA
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25
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Pearlson GD. Etiologic, Phenomenologic, and Endophenotypic Overlap of Schizophrenia and Bipolar Disorder. Annu Rev Clin Psychol 2015; 11:251-81. [DOI: 10.1146/annurev-clinpsy-032814-112915] [Citation(s) in RCA: 91] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Godfrey D. Pearlson
- Departments of Psychiatry and Neurobiology, Yale University School of Medicine, New Haven, Connecticut 06510;
- Olin Neuropsychiatry Research Center, Hartford Healthcare Corporation, Hartford, Connecticut 06106
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26
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Fabiani M. The embodied brain. Psychophysiology 2014; 52:1-5. [DOI: 10.1111/psyp.12381] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2014] [Accepted: 10/17/2014] [Indexed: 12/19/2022]
Affiliation(s)
- Monica Fabiani
- Beckman Institute; University of Illinois at Urbana-Champaign; Urbana Illinois USA
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27
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Nathou C, Etard O, Simon G, Dollfus S. How do high- and low-frequency repetitive transcranial magnetic stimulations modulate the temporal cortex. Psychophysiology 2014; 52:192-8. [PMID: 25223883 DOI: 10.1111/psyp.12323] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2013] [Accepted: 07/30/2014] [Indexed: 11/27/2022]
Abstract
Few studies have examined the impact of repetitive transcranial magnetic stimulation (rTMS) on the cortical excitability of nonmotor cortices; current treatments often target the temporal or prefrontal cortex. We used auditory evoked potentials recorded in 24 healthy subjects to evaluate the neuromodulatory effects of low- and high-frequency rTMS in the temporal lobe. Both auditory evoked potential P50 amplitude, a marker of cortical excitability, and P50 ratio, a marker of sensory gating known to be impaired in patients with auditory verbal hallucinations, were compared before and after rTMS. We observed a similar effect after both stimulation frequencies, with a decrease in P50 amplitude and no significant effect on P50 ratio. Low- and high-frequency rTMS applied to the temporal lobe seemed to exert the same cortical neuromodulation effect, while auditory sensory gating may not be modulated by temporal rTMS.
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Affiliation(s)
- Clement Nathou
- CHU de Caen, Service de psychiatrie, Centre Esquirol, Caen, France; UCBN, UFR de Médecine, Caen, France; CNRS, UMR 6301, ISTCT, ISTS Group, GIP Cyceron, Caen, France
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28
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Carolus AM, Schubring D, Popov TG, Popova P, Miller GA, Rockstroh BS. Functional cognitive and cortical abnormalities in chronic and first-admission schizophrenia. Schizophr Res 2014; 157:40-7. [PMID: 24933246 DOI: 10.1016/j.schres.2014.05.012] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2013] [Revised: 04/24/2014] [Accepted: 05/07/2014] [Indexed: 11/19/2022]
Abstract
Evoked and induced event-related neural oscillations have recently been proposed as a key mechanism supporting higher-order cognition. Cognitive decay and abnormal electromagnetic sensory gating reliably distinguish schizophrenia (SZ) patients and healthy individuals, demonstrated in chronic (CHR) and first-admission (FA) patients. Not yet determined is whether altered event-related modulation of oscillatory activity is manifested at early stages of SZ, thus reflects and perhaps embodies the development of psychopathology, and provides a mechanism for the gating deficit. The present study compared behavioral and functional brain measures in CHR and FA samples. Cognitive test performance (MATRICS Consortium Cognitive Battery, MCCB), neuromagnetic event-related fields (M50 gating ratio), and oscillatory dynamics (evoked and induced modulation of 8-12Hz alpha) during a paired-click task were assessed in 35 CHR and 31 FA patients meeting the criteria for ICD-10 diagnoses of schizophrenia as well as 28 healthy comparison subjects (HC). Both patient groups displayed poorer cognitive performance, higher M50 ratio (poorer sensory gating), and less induced modulation of alpha activity than did HC. Induced alpha power decrease in bilateral posterior regions varied with M50 ratio in HC but not SZ, whereas orbitofrontal alpha power decrease was related to M50 ratio in SZ but not HC. Results suggest disruption of oscillatory dynamics at early stages of illness, which may contribute to deficient information sampling, memory updating, and higher cognitive functioning.
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Affiliation(s)
| | | | | | - Petia Popova
- Department of Psychology, University of Konstanz, Germany.
| | - Gregory A Miller
- Department of Psychology and Psychiatry, UCLA, USA; Department of Biobehavioral Sciences, UCLA, USA.
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