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López-Caballero F, Curtis M, Coffman BA, Salisbury DF. Is source-resolved magnetoencephalographic mismatch negativity a viable biomarker for early psychosis? Eur J Neurosci 2024; 59:1889-1906. [PMID: 37537883 PMCID: PMC10837325 DOI: 10.1111/ejn.16107] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 07/04/2023] [Accepted: 07/20/2023] [Indexed: 08/05/2023]
Abstract
Mismatch negativity (MMN) is an auditory event-related response reflecting the pre-attentive detection of novel stimuli and is a biomarker of cortical dysfunction in schizophrenia (SZ). MMN to pitch (pMMN) and to duration (dMMN) deviant stimuli are impaired in chronic SZ, but it is less clear if MMN is reduced in first-episode SZ, with inconsistent findings in scalp-level EEG studies. Here, we investigated the neural generators of pMMN and dMMN with MEG recordings in 26 first-episode schizophrenia spectrum (FEsz) and 26 matched healthy controls (C). We projected MEG inverse solutions into precise functionally meaningful auditory cortex areas. MEG-derived MMN sources were in bilateral primary auditory cortex (A1) and belt areas. In A1, pMMN FEsz reduction showed a trend towards statistical significance (F(1,50) = 3.31; p = .07), and dMMN was reduced in FEsz (F(1,50) = 4.11; p = .04). Hypothesis-driven comparisons at each hemisphere revealed dMMN reduction in FEsz occurred in the left (t(56) = 2.23; p = .03; d = .61) but not right (t(56) = 1.02; p = .31; d = .28) hemisphere, with a moderate effect size. The added precision of MEG source solution with high-resolution MRI and parcellation of A1 may be requisite to detect the emerging pathophysiology and indicates a critical role for left hemisphere pathology at psychosis onset. However, the moderate effect size in left A1, albeit larger than reported in scalp MMN meta-analyses, casts doubt on the clinical utility of MMN for differential diagnosis, as a majority of patients will overlap with the healthy individual's distribution.
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Affiliation(s)
- Fran López-Caballero
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Mark Curtis
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Brian A Coffman
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Dean F Salisbury
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
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López-Caballero F, Auksztulewicz R, Howard Z, Rosch RE, Todd J, Salisbury DF. Computational Synaptic Modeling of Pitch and Duration Mismatch Negativity in First-Episode Psychosis Reveals Selective Dysfunction of the N-Methyl-D-Aspartate Receptor. Clin EEG Neurosci 2024:15500594241238294. [PMID: 38533562 DOI: 10.1177/15500594241238294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/28/2024]
Abstract
Mismatch negativity (MMN) to pitch (pMMN) and to duration (dMMN) deviant stimuli is significantly more attenuated in long-term psychotic illness compared to first-episode psychosis (FEP). It was recently shown that source-modeling of magnetically recorded MMN increases the detection of left auditory cortex MMN deficits in FEP, and that computational circuit modeling of electrically recorded MMN also reveals left-hemisphere auditory cortex abnormalities. Computational modeling using dynamic causal modeling (DCM) can also be used to infer synaptic activity from EEG-based scalp recordings. We measured pMMN and dMMN with EEG from 26 FEP and 26 matched healthy controls (HCs) and used a DCM conductance-based neural mass model including α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid, N-methyl-D-Aspartate (NMDA), and Gamma-aminobutyric acid receptors to identify any changes in effective connectivity and receptor rate constants in FEP. We modeled MMN sources in bilateral A1, superior temporal gyrus, and inferior frontal gyrus (IFG). No model parameters distinguished groups for pMMN. For dMMN, reduced NMDA receptor activity in right IFG in FEP was detected. This finding is in line with literature of prefrontal NMDA receptor hypofunction in chronic schizophrenia and suggests impaired NMDA-induced synaptic plasticity may be present at psychosis onset where scalp dMMN is only moderately reduced. To the best of our knowledge, this is the first report of impaired NMDA receptor activity in FEP found through computational modeling of dMMN and shows the potential of DCM to non-invasively reveal synaptic-level abnormalities that underly subtle functional auditory processing deficits in early psychosis.
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Affiliation(s)
- F López-Caballero
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - R Auksztulewicz
- Department of Education and Psychology, Freie Universität Berlin, Berlin, Germany
| | - Z Howard
- School of Psychological Science, University of Western Australia, Perth, Australia
| | - R E Rosch
- Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, UK
| | - J Todd
- School of Psychological Sciences, University of Newcastle, Callaghan, Australia
| | - D F Salisbury
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
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Cappotto D, Luo D, Lai HW, Peng F, Melloni L, Schnupp JWH, Auksztulewicz R. "What" and "when" predictions modulate auditory processing in a mutually congruent manner. Front Neurosci 2023; 17:1180066. [PMID: 37781257 PMCID: PMC10540699 DOI: 10.3389/fnins.2023.1180066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Accepted: 08/04/2023] [Indexed: 10/03/2023] Open
Abstract
Introduction Extracting regularities from ongoing stimulus streams to form predictions is crucial for adaptive behavior. Such regularities exist in terms of the content of the stimuli and their timing, both of which are known to interactively modulate sensory processing. In real-world stimulus streams such as music, regularities can occur at multiple levels, both in terms of contents (e.g., predictions relating to individual notes vs. their more complex groups) and timing (e.g., pertaining to timing between intervals vs. the overall beat of a musical phrase). However, it is unknown whether the brain integrates predictions in a manner that is mutually congruent (e.g., if "beat" timing predictions selectively interact with "what" predictions falling on pulses which define the beat), and whether integrating predictions in different timing conditions relies on dissociable neural correlates. Methods To address these questions, our study manipulated "what" and "when" predictions at different levels - (local) interval-defining and (global) beat-defining - within the same stimulus stream, while neural activity was recorded using electroencephalogram (EEG) in participants (N = 20) performing a repetition detection task. Results Our results reveal that temporal predictions based on beat or interval timing modulated mismatch responses to violations of "what" predictions happening at the predicted time points, and that these modulations were shared between types of temporal predictions in terms of the spatiotemporal distribution of EEG signals. Effective connectivity analysis using dynamic causal modeling showed that the integration of "what" and "when" predictions selectively increased connectivity at relatively late cortical processing stages, between the superior temporal gyrus and the fronto-parietal network. Discussion Taken together, these results suggest that the brain integrates different predictions with a high degree of mutual congruence, but in a shared and distributed cortical network. This finding contrasts with recent studies indicating separable mechanisms for beat-based and memory-based predictive processing.
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Affiliation(s)
- Drew Cappotto
- Department of Neuroscience, City University of Hong Kong, Kowloon, Hong Kong SAR, China
- Ear Institute, University College London, London, United Kingdom
| | - Dan Luo
- Department of Neuroscience, City University of Hong Kong, Kowloon, Hong Kong SAR, China
| | - Hiu Wai Lai
- Department of Neuroscience, City University of Hong Kong, Kowloon, Hong Kong SAR, China
| | - Fei Peng
- Department of Neuroscience, City University of Hong Kong, Kowloon, Hong Kong SAR, China
| | - Lucia Melloni
- Department of Neuroscience, Max Planck Institute for Empirical Aesthetics, Frankfurt am Main, Germany
- Department of Neurology, NYU Grossman School of Medicine, New York, NY, United States
| | | | - Ryszard Auksztulewicz
- Department of Neuroscience, City University of Hong Kong, Kowloon, Hong Kong SAR, China
- Department of Neuroscience, Max Planck Institute for Empirical Aesthetics, Frankfurt am Main, Germany
- Department of Education and Psychology, Freie Universität Berlin, Berlin, Germany
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Todd J, Salisbury D, Michie PT. Why mismatch negativity continues to hold potential in probing altered brain function in schizophrenia. PCN REPORTS : PSYCHIATRY AND CLINICAL NEUROSCIENCES 2023; 2:e144. [PMID: 38867817 PMCID: PMC11114358 DOI: 10.1002/pcn5.144] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 08/21/2023] [Accepted: 08/30/2023] [Indexed: 06/14/2024]
Abstract
The brain potential known as mismatch negativity (MMN) is one of the most studied indices of altered brain function in schizophrenia. This review looks at what has been learned about MMN in schizophrenia over the last three decades and why the level of interest and activity in this field of research remains strong. A diligent consideration of available evidence suggests that MMN can serve as a biomarker in schizophrenia, but perhaps not the kind of biomarker that early research supposed. This review concludes that MMN measurement is likely to be most useful as a monitoring and response biomarker enabling tracking of an underlying pathology and efficacy of interventions, respectively. The role of, and challenges presented by, pre-clinical models is discussed as well as the merits of different methodologies that can be brought to bear in pursuing a deeper understanding of pathophysiology that might explain smaller MMN in schizophrenia.
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Affiliation(s)
- Juanita Todd
- School of Psychological SciencesUniversity of NewcastleNewcastleNew South WalesAustralia
| | - Dean Salisbury
- Department of PsychiatryUniversity of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | - Patricia T. Michie
- School of Psychological SciencesUniversity of NewcastleNewcastleNew South WalesAustralia
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Goena J, Alústiza I, Vidal-Adroher C, Garcés MS, Fernández M, Molero P, García-Eulate R, Fernández-Seara M, Ortuño F. Time discrimination and change detection could share a common brain network: findings of a task-based fMRI study. Front Psychol 2023; 14:1110972. [PMID: 37529319 PMCID: PMC10390230 DOI: 10.3389/fpsyg.2023.1110972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 06/05/2023] [Indexed: 08/03/2023] Open
Abstract
Introduction Over the past few years, several studies have described the brain activation pattern related to both time discrimination (TD) and change detection processes. We hypothesize that both processes share a common brain network which may play a significant role in more complex cognitive processes. The main goal of this proof-of-concept study is to describe the pattern of brain activity involved in TD and oddball detection (OD) paradigms, and in processes requiring higher cognitive effort. Methods We designed an experimental task, including an auditory test tool to assess TD and OD paradigms, which was conducted under functional magnetic resonance imaging (fMRI) in 14 healthy participants. We added a cognitive control component into both paradigms in our test tool. We used the general linear model (GLM) to analyze the individual fMRI data images and the random effects model for group inference. Results We defined the areas of brain activation related to TD and OD paradigms. We performed a conjunction analysis of contrast TD (task > control) and OD (task > control) patterns, finding both similarities and significant differences between them. Discussion We conclude that change detection and other cognitive processes requiring an increase in cognitive effort require participation of overlapping functional and neuroanatomical components, suggesting the presence of a common time and change detection network. This is of particular relevance for future research on normal cognitive functioning in the healthy population, as well as for the study of cognitive impairment and clinical manifestations associated with various neuropsychiatric conditions such as schizophrenia.
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Affiliation(s)
- Javier Goena
- Department of Psychiatry and Clinical Psychology, Clínica Universidad de Navarra, Pamplona, Spain
- Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
- Department of Psychiatry, Basurto University Hospital, Bilbao, Spain
| | - Irene Alústiza
- Department of Psychiatry and Clinical Psychology, Clínica Universidad de Navarra, Pamplona, Spain
- Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
| | - Cristina Vidal-Adroher
- Department of Psychiatry and Clinical Psychology, Clínica Universidad de Navarra, Pamplona, Spain
- Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
| | - María Sol Garcés
- Department of Psychiatry and Clinical Psychology, Clínica Universidad de Navarra, Pamplona, Spain
- Colegio de Ciencias Sociales y Humanidades, Universidad San Francisco de Quito, Quito, Ecuador
- Instituto de Neurociencias, Universidad San Francisco de Quito, Quito, Ecuador
| | - Miguel Fernández
- Department of Radiology, Clínica Universidad de Navarra, Pamplona, Spain
| | - Patricio Molero
- Department of Psychiatry and Clinical Psychology, Clínica Universidad de Navarra, Pamplona, Spain
- Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
| | - Reyes García-Eulate
- Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
- Department of Radiology, Clínica Universidad de Navarra, Pamplona, Spain
| | - María Fernández-Seara
- Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
- Department of Radiology, Clínica Universidad de Navarra, Pamplona, Spain
| | - Felipe Ortuño
- Department of Psychiatry and Clinical Psychology, Clínica Universidad de Navarra, Pamplona, Spain
- Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
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