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Tada M, Yagishita S, Uka T, Nishimura R, Kishigami T, Kirihara K, Koshiyama D, Usui K, Fujioka M, Araki T, Kasai K. From the Laboratory to the Real-World: The Role of Mismatch Negativity in Psychosis. Clin EEG Neurosci 2025; 56:60-71. [PMID: 39506274 DOI: 10.1177/15500594241294188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/08/2024]
Abstract
Mismatch negativity (MMN) has gained attention as a biomarker for psychosis and a translational intermediate phenotype in animal models of psychosis, including rodents and non-human primates. MMN has been linked to global functioning (Global Assessment of Functioning [GAF] score) and prognosis (psychosis onset or remission), suggesting that MMN reflects activities beyond auditory processing alone. This review examines the 45-year history of MMN from the perspective of psychiatric researchers and discusses current advances in computational and translational research on MMN, summarizing the current understanding of the MMN generation mechanism. We then address the essential question, "What do we observe through MMN?" Currently, we regard the relationship between global functioning in the real world and MMN as the key to answering this question. As a preliminary investigation, we analyzed the relationship between GAF as an objective variable and MMN, diagnosis, and basic epidemiological factors (age, sex, premorbid intelligence quotient) as explanatory variables (total n = 201, healthy controls: n = 41, patients with psychiatric disorders: n = 160) without assuming diagnostic categories. The relationship between functional outcomes and MMN was confirmed without a case-control design. Finally, we propose that new neurophysiological studies should acknowledge psychophysiological responses such as emotion, intention, and autonomic responses, as well as behavioral differences among participants beyond the dichotomy between healthy controls and patients. Measurements could be conducted in various settings from the participant's perspective. We discuss the potential for research investigating psychosis based on the interaction between individuals and the environment, using MMN as an illustrative model.
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Affiliation(s)
- Mariko Tada
- Department of Psychiatry and Behavioral Science, Graduate School of Medicine, Juntendo University Tokyo, Japan
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Sho Yagishita
- Department of Structural Physiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Takanori Uka
- Department of Integrative Physiology, Graduate School of Medicine, University of Yamanashi, Yamanashi, Japan
| | - Ryoichi Nishimura
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Taiki Kishigami
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Kenji Kirihara
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- Center for Coproduction of Inclusion, Diversity and Equity (IncluDE), The University of Tokyo, Tokyo, Japan
| | - Daisuke Koshiyama
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Kaori Usui
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- Department of Community Mental Health and Law, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Mao Fujioka
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Tsuyoshi Araki
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- The International Research Center for Neurointelligence (WPI-IRCN) at The University of Tokyo Institutes for Advanced Study (UTIAS), The University of Tokyo, Tokyo, Japan
- University of Tokyo Institute for Diversity & Adaptation of Human Mind (UTIDAHM), Tokyo, Japan
- Center for Diversity in Medical Education and Research, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Kiyoto Kasai
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- The International Research Center for Neurointelligence (WPI-IRCN) at The University of Tokyo Institutes for Advanced Study (UTIAS), The University of Tokyo, Tokyo, Japan
- University of Tokyo Institute for Diversity & Adaptation of Human Mind (UTIDAHM), Tokyo, Japan
- Center for Diversity in Medical Education and Research, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
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Erickson MA, Bansal S, Li C, Waltz J, Corlett P, Gold J. Differing Pattern of Mismatch Negativity Responses in Clinical and Nonclinical Voice Hearers Challenge Predictive Coding Accounts of Psychosis. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2025; 5:100394. [PMID: 39526022 PMCID: PMC11550737 DOI: 10.1016/j.bpsgos.2024.100394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2024] [Revised: 09/02/2024] [Accepted: 09/08/2024] [Indexed: 11/16/2024] Open
Abstract
Background Among people with schizophrenia (PSZ), reduced mismatch negativity (MMN) is conceptualized as evidence of disrupted prediction error signaling that underlies positive symptoms. However, this conceptualization has been challenged by observations that MMN and positive symptoms are often uncorrelated. In the current study, we tested the hypothesis that reduced MMN is associated with the presence of hallucinations and delusions specifically rather than the presence of a psychiatric illness. A second aim was to determine whether the strength of the association with positive symptoms increases for indices that reflect predictions at higher levels of abstraction. Methods Fifty-six PSZ, 34 nonclinical voice hearers, and 48 healthy comparison subjects (HCs) completed 2 MMN paradigms: one with a simple duration deviant type, and one with a higher-level, pattern-violation deviant type. We also measured the repetition positivity, which reflects the formation of auditory memory traces. Results We observed that although PSZ exhibited the expected pattern of significantly reduced duration MMN and reduced pattern-violation MMN at the trend level compared with HCs, nonclinical voice hearers exhibited a pattern of duration MMN and pattern-violation MMN amplitude that was statistically similar to that of HCs (ps > .64). Similarly, PSZ exhibited a significantly reduced repetition positivity slope compared with HCs in the duration condition and a trend-level reduction compared with HCs in the pattern-violation condition. Nonclinical voice hearers did not differ from either group in repetition positivity slope in either condition. Conclusions These results indicate that the MMN as a prediction error signal does not reflect processes relevant for the manifestation of hallucinations and delusions.
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Affiliation(s)
- Molly A. Erickson
- Department of Psychiatry & Behavioral Neuroscience, University of Chicago Medical Center, Chicago, Illinois
| | - Sonia Bansal
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, Maryland
| | - Charlotte Li
- Department of Psychiatry & Behavioral Neuroscience, University of Chicago Medical Center, Chicago, Illinois
| | - James Waltz
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, Maryland
| | - Philip Corlett
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
| | - James Gold
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, Maryland
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Dang C, Luo X, Zhu Y, Li B, Feng Y, Xu C, Kang S, Yin G, Johnstone SJ, Wang Y, Song Y, Sun L. Automatic sensory change processing in adults with attention deficit and hyperactivity disorder: a visual mismatch negativity study. Eur Arch Psychiatry Clin Neurosci 2024; 274:1651-1660. [PMID: 37831221 DOI: 10.1007/s00406-023-01695-7] [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: 12/03/2022] [Accepted: 09/20/2023] [Indexed: 10/14/2023]
Abstract
In addition to higher-order executive functions, underlying sensory processing ability is also thought to play an important role in Attention-Deficit/Hyperactivity Disorder (AD/HD). An event-related potential feature, the mismatch negativity, reflects the ability of automatic sensory change processing and may be correlated with AD/HD symptoms and executive functions. This study aims to investigate the characteristics of visual mismatch negativity (vMMN) in adults with AD/HD. Twenty eight adults with AD/HD and 31 healthy controls were included in this study. These two groups were matched in age, IQ and sex. In addition, both groups completed psychiatric evaluations, a visual ERP task used to elicit vMMN, and psychological measures about AD/HD symptoms and day-to-day executive functions. Compared to trols, the late vMMN (230-330 ms) was significantly reduced in the AD/HD group. Correlation analyses showed that late vMMN was correlated with executive functions but not AD/HD symptoms. However, further mediation analyses showed that different executive functions had mediated the relationships between late vMMN and AD/HD symptoms. Our findings indicate that the late vMMN, reflecting automatic sensory change processing ability, was impaired in adults with AD/HD. This impairment could have negative impact on AD/HD symptoms via affecting day-to-day executive functions.
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Affiliation(s)
- Chen Dang
- Peking University Sixth Hospital, Institute of Mental Health, Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Xiangsheng Luo
- Peking University Sixth Hospital, Institute of Mental Health, Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Yu Zhu
- Peking University Sixth Hospital, Institute of Mental Health, Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Bingkun Li
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, China
| | - Yuan Feng
- Peking University Sixth Hospital, Institute of Mental Health, Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Chenyang Xu
- Peking University Sixth Hospital, Institute of Mental Health, Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Simin Kang
- Peking University Sixth Hospital, Institute of Mental Health, Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Gaohan Yin
- Peking University Sixth Hospital, Institute of Mental Health, Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Stuart J Johnstone
- School of Psychology, University of Wollongong, Wollongong, NSW, Australia
- Brain and Behavior Research Institute, University of Wollongong, Wollongong, NSW, Australia
| | - Yufeng Wang
- Peking University Sixth Hospital, Institute of Mental Health, Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Yan Song
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, China.
| | - Li Sun
- Peking University Sixth Hospital, Institute of Mental Health, Beijing, 100191, China.
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
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Ling X, Wang S, Zhang S, Li W, Zhang Q, Cai W, Li H. Contingent negative variation as an evaluation indicator of neurocognitive disorder after traumatic brain injury. Front Psychiatry 2023; 14:1255608. [PMID: 38169851 PMCID: PMC10758395 DOI: 10.3389/fpsyt.2023.1255608] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Accepted: 11/30/2023] [Indexed: 01/05/2024] Open
Abstract
Introduction Neurocognitive disorders are commonly observed in patients suffering from traumatic brain injury (TBI). Methods to assess neurocognitive disorders have thus drawn the general attention of the public, especially electrophysiology parameter such as contingent negative variation (CNV), which has been given more emphasis as a neurophysiological marker in event-related potentials (ERPs) for diagnosing a neurocognitive disorder and assessing its severity. The present study focused on the correlations between CNV parameters and levels of daily living activities and social function to explore the potential of CNV as an objective assessment tool. Methods Thirty-one patients with a diagnosis of neurocognitive disorder after a TBI according to ICD-10 were enrolled as the patient group, and 24 matched healthy volunteers were enrolled as the control group. The activity of daily living scale, functional activities questionnaire, social disability screening schedule, and scale of personality change following TBI were used to assess daily living activity and social function. Results The scale scores in patients were significantly higher than those in controls. Maximum amplitudes before S2 and during the post-imperative negative variation (PINV) period were also significantly higher in the patient group compared to the control group and were positively correlated with four scale scores. The duration of PINV at Fz and Cz was significantly shorter in the patient group than in the control group. The CNV return to baseline from a positive wave at electrode Fz and Cz occurred significantly earlier in the control group than in the patient group, while at Pz, the result showed the opposite. Conclusion Lower amplitudes of CNV were associated with more severe neurocognitive disorder and greater impairments in daily life abilities and social function. The duration of PINV and the latency of returning to baseline from a positive wave were correlated with the neurocognitive disorder to some extent. CNV could be used as an objective, electrophysiology-based parameter for evaluating the severity of the neurocognitive disorder and personality changes after TBI.
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Affiliation(s)
- Xindi Ling
- Shanghai Key Lab of Forensic Medicine, Key Lab of Forensic Science, Ministry of Justice, Shanghai Forensic Service Platform, Academy of Forensic Science, Shanghai, China
- Department of Forensic Medicine, School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Shujian Wang
- Shanghai Key Lab of Forensic Medicine, Key Lab of Forensic Science, Ministry of Justice, Shanghai Forensic Service Platform, Academy of Forensic Science, Shanghai, China
| | - Shengyu Zhang
- Shanghai Key Lab of Forensic Medicine, Key Lab of Forensic Science, Ministry of Justice, Shanghai Forensic Service Platform, Academy of Forensic Science, Shanghai, China
| | - Wen Li
- Shanghai Key Lab of Forensic Medicine, Key Lab of Forensic Science, Ministry of Justice, Shanghai Forensic Service Platform, Academy of Forensic Science, Shanghai, China
| | - Qinting Zhang
- Shanghai Key Lab of Forensic Medicine, Key Lab of Forensic Science, Ministry of Justice, Shanghai Forensic Service Platform, Academy of Forensic Science, Shanghai, China
| | - Weixiong Cai
- Shanghai Key Lab of Forensic Medicine, Key Lab of Forensic Science, Ministry of Justice, Shanghai Forensic Service Platform, Academy of Forensic Science, Shanghai, China
- Department of Forensic Medicine, School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Haozhe Li
- Shanghai Key Lab of Forensic Medicine, Key Lab of Forensic Science, Ministry of Justice, Shanghai Forensic Service Platform, Academy of Forensic Science, Shanghai, China
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