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Criel Y, Depuydt E, Miatton M, Santens P, van Mierlo P, De Letter M. Cortical Generators and Connections Underlying Phoneme Perception: A Mismatch Negativity and P300 Investigation. Brain Topogr 2024:10.1007/s10548-024-01065-z. [PMID: 38958833 DOI: 10.1007/s10548-024-01065-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Accepted: 06/19/2024] [Indexed: 07/04/2024]
Abstract
The cortical generators of the pure tone MMN and P300 have been thoroughly studied. Their nature and interaction with respect to phoneme perception, however, is poorly understood. Accordingly, the cortical sources and functional connections that underlie the MMN and P300 in relation to passive and active speech sound perception were identified. An inattentive and attentive phonemic oddball paradigm, eliciting a MMN and P300 respectively, were administered in 60 healthy adults during simultaneous high-density EEG recording. For both the MMN and P300, eLORETA source reconstruction was performed. The maximal cross-correlation was calculated between ROI-pairs to investigate inter-regional functional connectivity specific to passive and active deviant processing. MMN activation clusters were identified in the temporal (insula, superior temporal gyrus and temporal pole), frontal (rostral middle frontal and pars opercularis) and parietal (postcentral and supramarginal gyrus) cortex. Passive discrimination of deviant phonemes was aided by a network connecting right temporoparietal cortices to left frontal areas. For the P300, clusters with significantly higher activity were found in the frontal (caudal middle frontal and precentral), parietal (precuneus) and cingulate (posterior and isthmus) cortex. Significant intra- and interhemispheric connections between parietal, cingulate and occipital regions constituted the network governing active phonemic target detection. A predominantly bilateral network was found to underly both the MMN and P300. While passive phoneme discrimination is aided by a fronto-temporo-parietal network, active categorization calls on a network entailing fronto-parieto-cingulate cortices. Neural processing of phonemic contrasts, as reflected by the MMN and P300, does not appear to show pronounced lateralization to the language-dominant hemisphere.
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Affiliation(s)
- Yana Criel
- Department of Rehabilitation Sciences, Ghent University, Ghent, Belgium.
| | - Emma Depuydt
- Medical Imaging and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | - Marijke Miatton
- Department of Neurology, Ghent University Hospital, Ghent, Belgium
- Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Patrick Santens
- Department of Neurology, Ghent University Hospital, Ghent, Belgium
- Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Pieter van Mierlo
- Medical Imaging and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | - Miet De Letter
- Department of Rehabilitation Sciences, Ghent University, Ghent, Belgium
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Tseng YL, Su YK, Chou WJ, Miyakoshi M, Tsai CS, Li CJ, Lee SY, Wang LJ. Neural Network Dynamics and Brain Oscillations Underlying Aberrant Inhibitory Control in Internet Addiction. IEEE Trans Neural Syst Rehabil Eng 2024; 32:946-955. [PMID: 38335078 DOI: 10.1109/tnsre.2024.3363756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/12/2024]
Abstract
Previous studies have reported a role of alterations in the brain's inhibitory control mechanism in addiction. Mounting evidence from neuroimaging studies indicates that its key components can be evaluated with brain oscillations and connectivity during inhibitory control. In this study, we developed an internet-related stop-signal task with electroencephalography (EEG) signal recorded to investigate inhibitory control. Healthy controls and participants with Internet addiction were recruited to participate in the internet-related stop-signal task with 19-channel EEG signal recording, and the corresponding event-related potentials and spectral perturbations were analyzed. Brain effective connections were also evaluated using direct directed transfer function. The results showed that, relative to the healthy controls, participants with Internet addiction had increased Stop-P3 during inhibitory control, suggesting that they have an altered neural mechanism in impulsive control. Furthermore, participants with Internet addiction showed increased low-frequency synchronization and decreased alpha and beta desynchronization in the middle and right frontal regions compared to healthy controls. Aberrant brain effective connectivity was also observed, with increased occipital-parietal and intra-occipital connections, as well as decreased frontal-paracentral connection in participants with Internet addiction. These results suggest that physiological signals are essential in future implementations of cognitive assessment of Internet addiction to further investigate the underlying mechanisms and effective biomarkers.
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Parker DA, Cubells JF, Imes SL, Ruban GA, Henshey BT, Massa NM, Walker EF, Duncan EJ, Ousley OY. Deep psychophysiological phenotyping of adolescents and adults with 22q11.2 deletion syndrome: a multilevel approach to defining core disease processes. BMC Psychiatry 2023; 23:425. [PMID: 37312091 PMCID: PMC10262114 DOI: 10.1186/s12888-023-04888-5] [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: 03/31/2023] [Accepted: 05/18/2023] [Indexed: 06/15/2023] Open
Abstract
BACKGROUND 22q11.2 deletion syndrome (22q11.2DS) is the most common chromosomal interstitial-deletion disorder, occurring in approximately 1 in 2000 to 6000 live births. Affected individuals exhibit variable clinical phenotypes that can include velopharyngeal anomalies, heart defects, T-cell-related immune deficits, dysmorphic facial features, neurodevelopmental disorders, including autism, early cognitive decline, schizophrenia, and other psychiatric disorders. Developing comprehensive treatments for 22q11.2DS requires an understanding of both the psychophysiological and neural mechanisms driving clinical outcomes. Our project probes the core psychophysiological abnormalities of 22q11.2DS in parallel with molecular studies of stem cell-derived neurons to unravel the basic mechanisms and pathophysiology of 22q11.2-related psychiatric disorders, with a primary focus on psychotic disorders. Our study is guided by the central hypothesis that abnormal neural processing associates with psychophysiological processing and underlies clinical diagnosis and symptomatology. Here, we present the scientific background and justification for our study, sharing details of our study design and human data collection protocol. METHODS Our study is recruiting individuals with 22q11.2DS and healthy comparison subjects between the ages of 16 and 60 years. We are employing an extensive psychophysiological assessment battery (e.g., EEG, evoked potential measures, and acoustic startle) to assess fundamental sensory detection, attention, and reactivity. To complement these unbiased measures of cognitive processing, we will develop stem-cell derived neurons and examine neuronal phenotypes relevant to neurotransmission. Clinical characterization of our 22q11.2DS and control participants relies on diagnostic and research domain criteria assessments, including standard Axis-I diagnostic and neurocognitive measures, following from the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) and the North American Prodrome Longitudinal Study (NAPLS) batteries. We are also collecting measures of autism spectrum (ASD) and attention deficit/hyperactivity disorder (ADHD)-related symptoms. DISCUSSION Studying 22q11.2DS in adolescence and adulthood via deep phenotyping across multiple clinical and biological domains may significantly increase our knowledge of its core disease processes. Our manuscript describes our ongoing study's protocol in detail. These paradigms could be adapted by clinical researchers studying 22q11.2DS, other CNV/single gene disorders, or idiopathic psychiatric syndromes, as well as by basic researchers who plan to incorporate biobehavioral outcome measures into their studies of 22q11.2DS.
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Affiliation(s)
- David A Parker
- Department of Human Genetics, Emory University School of Medicine, Whitehead Biomedical Research Building 615 Michael Street Suite 301, Atlanta, GA, 30322, USA.
| | - Joseph F Cubells
- Department of Human Genetics; Emory Autism Center; Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, 1551 Shoup Court, Decatur, GA, 30033, USA
| | - Sid L Imes
- Department of Human Genetics, Emory University School of Medicine, Whitehead Biomedical Research Building 615 Michael Street Suite 301, Atlanta, GA, 30322, USA
| | - Gabrielle A Ruban
- Department of Human Genetics, Emory University School of Medicine, Whitehead Biomedical Research Building 615 Michael Street Suite 301, Atlanta, GA, 30322, USA
| | - Brett T Henshey
- Emory University, Whitehead Biomedical Research Building 615 Michael Street Suite 301, Atlanta, GA, 30322, USA
| | - Nicholas M Massa
- Atlanta Veterans Administration Health Care System, 1670 Clairmont Road, Decatur, GA, 30033, USA
| | - Elaine F Walker
- Department of Psychology, Emory University, Psychology and Interdisciplinary Sciences Building Suite 487, 36 Eagle Row, Atlanta, GA, 30322, USA
| | - Erica J Duncan
- Atlanta Veterans Administration Health Care System, 1670 Clairmont Road, Decatur, GA, 30033, USA
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Brain Health Center, 12 Executive Park Dr, Atlanta, GA, 30329, USA
| | - Opal Y Ousley
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, 1551 Shoup Court, Decatur, GA, USA
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Mahmut Y, Michael M, Jaelin R, Gregor L, Dost Ö. Decreased mismatch negativity and elevated frontal-lateral connectivity in first-episode psychosis. J Psychiatr Res 2021; 144:37-44. [PMID: 34592510 PMCID: PMC8665084 DOI: 10.1016/j.jpsychires.2021.09.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 07/30/2021] [Accepted: 09/22/2021] [Indexed: 11/15/2022]
Abstract
Decreased mismatch negativity (MMN) is a proposed biomarker for psychotic disorders. However, the magnitude of the effect appears to be attenuated in first-episode populations. Furthermore, how mismatch negativity amplitudes are related to brain connectivity in this population is unclear. In this study, we used high-density EEG to record duration-deviant MMN from 22 patients with first-episode psychosis (FEP) and 23 age-matched controls (HC). Consistent with past work, we found decreased MMN amplitude in FEP over a large area of the frontal scalp. We also found decreased latency over the occipital scalp. MMN amplitude was negatively correlated with antipsychotic dose. We used Granger causality to investigate directional connectivity between frontal, midline, left, and right scalp during MMN and found reduced connectivity in FEP compared to HC and following deviant stimuli compared to standard stimuli. FEP participants with smaller decreases in connectivity from standard to deviant stimuli had worse disorganization symptoms. On the other hand, connectivity from the front of the scalp following deviant stimuli was relatively preserved in FEP compared to controls. Our results suggest that a relative imbalance of bottom-up and top-down perceptual processing is present in the early stages of psychotic disorders.
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Affiliation(s)
- Yüksel Mahmut
- University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20251 Hamburg, Germany
| | - Murphy Michael
- Harvard Medical School, 25 Shattuck St, Boston, MA 02115,McLean Hospital, 115 Mill St Belmont, MA 02478
| | | | - Leicht Gregor
- University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20251 Hamburg, Germany
| | - Öngür Dost
- Harvard Medical School, 25 Shattuck St, Boston, MA 02115,McLean Hospital, 115 Mill St Belmont, MA 02478
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Chang Q, Li C, Tian Q, Bo Q, Zhang J, Xiong Y, Wang C. Classification of First-Episode Schizophrenia, Chronic Schizophrenia and Healthy Control Based on Brain Network of Mismatch Negativity by Graph Neural Network. IEEE Trans Neural Syst Rehabil Eng 2021; 29:1784-1794. [PMID: 34406943 DOI: 10.1109/tnsre.2021.3105669] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Mismatch negativity (MMN) has been consistently found deficit in schizophrenia, which was considered as a promising biomarker for assessing the impairments in pre-attentive auditory processing. However, the functional connectivity between brain regions based on MMN is not clear. This study provides an in-depth investigation in brain functional connectivity during MMN process among patients with first-episode schizophrenia (FESZ), chronic schizophrenia (CSZ) and healthy control (HC). Electroencephalography (EEG) data of 128 channels is recorded during frequency and duration MMN in 40 FESZ, 40 CSZ patients and 40 matched HC subjects. We reconstruct the cortical endogenous electrical activity from EEG recordings using exact low-resolution electromagnetic tomography and build functional brain networks based on source-level EEG data. Then, graph-theoretic features are extracted from the brain networks with the support vector machine (SVM) to classify FESZ, CSZ and HC groups, since the SVM has good generalization ability and robustness as a universally applicable nonlinear classifier. Furthermore, we introduce the graph neural network (GNN) model to directly learn for the network topology of brain network. Compared to HC, the damaged brain areas of CSZ are more extensive than FESZ, and the damaged area involved the auditory cortex. These results demonstrate the heterogeneity of the impacts of schizophrenia for different disease courses and the association between MMN and the auditory cortex. More importantly, the GNN classification results are significantly better than those of SVM, and hence the EEG-based GNN model of brain networks provides an effective method for discriminating among FESZ, CSZ and HC groups.
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Jurgiel J, Miyakoshi M, Dillon A, Piacentini J, Makeig S, Loo SK. Inhibitory control in children with tic disorder: aberrant fronto-parietal network activity and connectivity. Brain Commun 2021; 3:fcab067. [PMID: 33977267 PMCID: PMC8093924 DOI: 10.1093/braincomms/fcab067] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Revised: 02/23/2021] [Accepted: 02/26/2021] [Indexed: 12/03/2022] Open
Abstract
Chronic tic disorders, including Tourette syndrome, are typically thought to have deficits in cognitive inhibition and top down cognitive control due to the frequent and repetitive occurrence of tics, yet studies reporting task performance results have been equivocal. Despite similar behavioural performance, individuals with chronic tic disorder have exhibited aberrant patterns of neural activation in multiple frontal and parietal regions relative to healthy controls during inhibitory control paradigms. In addition to these top down attentional control regions, widespread alterations in brain activity across multiple neural networks have been reported. There is a dearth, however, of studies examining event-related connectivity during cognitive inhibitory paradigms among affected individuals. The goal of this study was to characterize neural oscillatory activity and effective connectivity, using a case–control design, among children with and without chronic tic disorder during performance of a cognitive inhibition task. Electroencephalogram data were recorded in a cohort of children aged 8–12 years old (60 with chronic tic disorder, 35 typically developing controls) while they performed a flanker task. While task accuracy did not differ by diagnosis, children with chronic tic disorder displayed significant cortical source-level, event-related spectral power differences during incongruent flanker trials, which required inhibitory control. Specifically, attenuated broad band oscillatory power modulation within the anterior cingulate cortex was observed relative to controls. Whole brain effective connectivity analyses indicated that children with chronic tic disorder exhibit greater information flow between the anterior cingulate and other fronto-parietal network hubs (midcingulate cortex and precuneus) relative to controls, who instead showed stronger connectivity between central and posterior nodes. Spectral power within the anterior cingulate was not significantly correlated with any connectivity edges, suggesting lower power and higher connectivity are independent (versus resultant) neural mechanisms. Significant correlations between clinical features, task performance and anterior cingulate spectral power and connectivity suggest this region is associated with tic impairment (r = −0.31, P = 0.03) and flanker task incongruent trial accuracy (r’s = −0.27 to −0.42, P’s = 0.0008–0.04). Attenuated activation of the anterior cingulate along with dysregulated information flow between and among nodes within the fronto-parietal attention network may be neural adaptations that result from frequent engagement of neural pathways needed for inhibitory control in chronic tic disorder.
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Affiliation(s)
- Joseph Jurgiel
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Makoto Miyakoshi
- Swartz Center for Neural Computation, University of California, San Diego, La Jolla, CA 92093, USA
| | - Andrea Dillon
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - John Piacentini
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Scott Makeig
- Swartz Center for Neural Computation, University of California, San Diego, La Jolla, CA 92093, USA
| | - Sandra K Loo
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA 90095, USA
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Koshiyama D, Thomas ML, Miyakoshi M, Joshi YB, Molina JL, Tanaka-Koshiyama K, Sprock J, Braff DL, Swerdlow NR, Light GA. Hierarchical Pathways from Sensory Processing to Cognitive, Clinical, and Functional Impairments in Schizophrenia. Schizophr Bull 2021; 47:373-385. [PMID: 32856089 PMCID: PMC7965084 DOI: 10.1093/schbul/sbaa116] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Cognitive impairment is a hallmark of schizophrenia and a robust predictor of functional outcomes. Impairments are found in all phases of the illness and are only moderately attenuated by currently approved therapeutics. Neurophysiological indices of sensory discrimination (ie, mismatch negativity (MMN) and P3a amplitudes) and gamma-band auditory steady-state response (ASSR; power and phase locking) are translational biomarkers widely used in the development of novel therapeutics for neuropsychiatric disorders. It is unclear whether laboratory-based EEG measures add explanatory power to well-established models that use only cognitive, clinical, and functional outcome measures. Moreover, it is unclear if measures of sensory discrimination and gamma-band ASSR uniquely contribute to putative causal pathways linking sensory discrimination, neurocognition, negative symptoms, and functional outcomes in schizophrenia. To answer these questions, hierarchical associations among sensory processing, neurocognition, clinical symptoms, and functional outcomes were assessed via structural equation modeling in a large sample of schizophrenia patients (n = 695) and healthy comparison subjects (n = 503). The results showed that the neurophysiologic indices of sensory discrimination and gamma-band ASSR both significantly contribute to and yield unique hierarchical, "bottom-up" effects on neurocognition, symptoms, and functioning. Measures of sensory discrimination showed direct effects on neurocognition and negative symptoms, while gamma-band ASSR had a direct effect on neurocognition in patients. Continued investigation of the neural mechanisms underlying abnormal networks of MMN/P3a and gamma-band ASSR is needed to clarify the pathophysiology of schizophrenia and the development of novel therapeutic interventions.
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Affiliation(s)
- Daisuke Koshiyama
- Department of Psychiatry, University of California San Diego, La Jolla, CA
| | - Michael L Thomas
- Department of Psychiatry, University of California San Diego, La Jolla, CA
- Department of Psychology, Colorado State University, Fort Collins, CO
| | - Makoto Miyakoshi
- Swartz Center for Neural Computation, University of California San Diego, La Jolla, CA
| | - Yash B Joshi
- 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, San Diego, CA
| | - Juan L Molina
- Department of Psychiatry, University of California San Diego, La Jolla, CA
| | | | - Joyce Sprock
- Department of Psychiatry, University of California San Diego, La Jolla, CA
| | - David L Braff
- Department of Psychiatry, University of California San Diego, La Jolla, CA
| | - Neal R Swerdlow
- Department of Psychiatry, University of California San Diego, La Jolla, CA
| | - 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, San Diego, CA
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Miyakoshi M, Gehrke L, Gramann K, Makeig S, Iversen J. The AudioMaze: An EEG and motion capture study of human spatial navigation in sparse augmented reality. Eur J Neurosci 2021; 54:8283-8307. [PMID: 33497490 DOI: 10.1111/ejn.15131] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Revised: 12/21/2020] [Accepted: 01/19/2021] [Indexed: 12/22/2022]
Abstract
Spatial navigation is one of the fundamental cognitive functions central to survival in most animals. Studies in humans investigating the neural foundations of spatial navigation traditionally use stationary, desk-top protocols revealing the hippocampus, parahippocampal place area (PPA), and retrosplenial complex to be involved in navigation. However, brain dynamics, while freely navigating the real world remain poorly understood. To address this issue, we developed a novel paradigm, the AudioMaze, in which participants freely explore a room-sized virtual maze, while EEG is recorded synchronized to motion capture. Participants (n = 16) were blindfolded and explored different mazes, each in three successive trials, using their right hand as a probe to "feel" for virtual maze walls. When their hand "neared" a virtual wall, they received directional noise feedback. Evidence for spatial learning include shortening of time spent and an increase of movement velocity as the same maze was repeatedly explored. Theta-band EEG power in or near the right lingual gyrus, the posterior portion of the PPA, decreased across trials, potentially reflecting the spatial learning. Effective connectivity analysis revealed directed information flow from the lingual gyrus to the midcingulate cortex, which may indicate an updating process that integrates spatial information with future action. To conclude, we found behavioral evidence of navigational learning in a sparse-AR environment, and a neural correlate of navigational learning was found near the lingual gyrus.
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Affiliation(s)
- Makoto Miyakoshi
- Swartz Center for Neural Computation, Institute for Neural Computation, University of California San Diego, CA, USA
| | - Lukas Gehrke
- FG Biopsychologie und Neuroergonomie, Technische Universität Berlin, Berlin, Germany
| | - Klaus Gramann
- FG Biopsychologie und Neuroergonomie, Technische Universität Berlin, Berlin, Germany.,School of Computer Science, University of Technology Sydney, Sydney, Australia
| | - Scott Makeig
- Swartz Center for Neural Computation, Institute for Neural Computation, University of California San Diego, CA, USA
| | - John Iversen
- Swartz Center for Neural Computation, Institute for Neural Computation, University of California San Diego, CA, USA
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Sources of the frontocentral mismatch negativity and P3a responses in schizophrenia patients and healthy comparison subjects. Int J Psychophysiol 2021; 161:76-85. [PMID: 33453303 DOI: 10.1016/j.ijpsycho.2021.01.005] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Revised: 01/06/2021] [Accepted: 01/06/2021] [Indexed: 11/23/2022]
Abstract
BACKGROUND Mismatch negativity (MMN) and P3a are event-related potential measures of early auditory information processing that are increasingly used as translational biomarkers in the development of treatments for neuropsychiatric disorders. These responses are reduced in schizophrenia patients over the frontocentral scalp electrodes and are associated with important domains of cognitive and psychosocial functioning. While MMN and P3a responses are generated by a dynamic network of cortical sources distributed across the temporal and frontal brain regions, it is not clear how these sources independently contribute to MMN and P3a at the primary frontocentral scalp electrode or to abnormalities observed in schizophrenia. This study aimed to determine the independent source contributions and characterize the magnitude of impairment in source-level MMN and P3a responses in schizophrenia patients. METHODS A novel method was applied to back-project the contributions of 11 independent cortical source components to Fz, the primary scalp sensor that is used in clinical studies, in n = 589 schizophrenia patients and n = 449 healthy comparison subjects. RESULTS The groups showed comparable individual source contributions underlying both MMN and P3a responses at Fz. Source-level responses revealed an increasing magnitude of impairment in schizophrenia patients from the temporal to more frontal sources. CONCLUSIONS Schizophrenia patients have a normal architecture of source contributions that are accompanied by widespread abnormalities in source resolved mismatch and P3a responses, with more prominent deficits detected from the frontal sources. Quantification of source contributions and source-level responses accelerates clarification of the neural networks underlying MMN reduction at Fz in schizophrenia patients.
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Koshiyama D, Miyakoshi M, Tanaka-Koshiyama K, Joshi YB, Molina JL, Sprock J, Braff DL, Light GA. Neurophysiologic Characterization of Resting State Connectivity Abnormalities in Schizophrenia Patients. Front Psychiatry 2020; 11:608154. [PMID: 33329160 PMCID: PMC7729083 DOI: 10.3389/fpsyt.2020.608154] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2020] [Accepted: 11/04/2020] [Indexed: 12/24/2022] Open
Abstract
Background: Patients with schizophrenia show abnormal spontaneous oscillatory activity in scalp-level electroencephalographic (EEG) responses across multiple frequency bands. While oscillations play an essential role in the transmission of information across neural networks, few studies have assessed the frequency-specific dynamics across cortical source networks at rest. Identification of the neural sources and their dynamic interactions may improve our understanding of core pathophysiologic abnormalities associated with the neuropsychiatric disorders. Methods: A novel multivector autoregressive modeling approach for assessing effective connectivity among cortical sources was developed and applied to resting-state EEG recordings obtained from n = 139 schizophrenia patients and n = 126 healthy comparison subjects. Results: Two primary abnormalities in resting-state networks were detected in schizophrenia patients. The first network involved the middle frontal and fusiform gyri and a region near the calcarine sulcus. The second network involved the cingulate gyrus and the Rolandic operculum (a region that includes the auditory cortex). Conclusions: Schizophrenia patients show widespread patterns of hyper-connectivity across a distributed network of the frontal, temporal, and occipital brain regions. Results highlight a novel approach for characterizing alterations in connectivity in the neuropsychiatric patient populations. Further mechanistic characterization of network functioning is needed to clarify the pathophysiology of neuropsychiatric and neurological diseases.
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Affiliation(s)
- Daisuke Koshiyama
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
| | - Makoto Miyakoshi
- Swartz Center for Neural Computation, University of California, San Diego, La Jolla, CA, United States
| | | | - Yash B Joshi
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
| | - Juan L Molina
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
| | - Joyce Sprock
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
| | - David L Braff
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
| | - Gregory A Light
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States.,VISN-22 Mental Illness, Research, Education and Clinical Center, VA San Diego Healthcare System, San Diego, CA, United States
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