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Visual mismatch negativity (vMMN): A review and meta-analysis of studies in psychiatric and neurological disorders
J. Kremláček, K. Kreegipuu, A. Tales, P. Astikainen, N. Põldver, R. Näätänen, G. Stefanics,
Jazyk angličtina Země Itálie
Typ dokumentu časopisecké články, metaanalýza, přehledy, práce podpořená grantem
- MeSH
- duševní poruchy patofyziologie MeSH
- elektroencefalografie metody MeSH
- evokované potenciály fyziologie MeSH
- lidé MeSH
- mozek fyziologie patofyziologie MeSH
- nemoci nervového systému patofyziologie MeSH
- zraková percepce fyziologie MeSH
- zrakové evokované potenciály fyziologie MeSH
- zvířata MeSH
- Check Tag
- lidé MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- metaanalýza MeSH
- práce podpořená grantem MeSH
- přehledy MeSH
The visual mismatch negativity (vMMN) response is an event-related potential (ERP) component, which is automatically elicited by events that violate predictions based on prior events. VMMN experiments use visual stimulus repetition to induce predictions, and vMMN is obtained by subtracting the response to rare unpredicted stimuli from those to frequent stimuli. One increasingly popular interpretation of the mismatch response postulates that vMMN, similar to its auditory counterpart (aMMN), represents a prediction error response generated by cortical mechanisms forming probabilistic representations of sensory signals. Here we discuss the physiological and theoretical basis of vMMN and review thirty-three studies from the emerging field of its clinical applications, presenting a meta-analysis of findings in schizophrenia, mood disorders, substance abuse, neurodegenerative disorders, developmental disorders, deafness, panic disorder and hypertension. Furthermore, we include reports on aging and maturation as they bear upon many clinically relevant conditions. Surveying the literature we found that vMMN is altered in several clinical populations which is in line with aMMN findings. An important potential advantage of vMMN however is that it allows the investigation of deficits in predictive processing in cognitive domains which rely primarily on visual information; a principal sensory modality and thus of vital importance in environmental information processing and response, and a modality which arguably may be more sensitive to some pathological changes. However, due to the relative infancy of research in vMMN compared to aMMN in clinical populations its potential for clinical application is not yet fully appreciated. The aim of this review and meta-analysis therefore is to present, in a detailed systematic manner, the findings from clinically-based vMMN studies, to discuss their potential impact and application, to raise awareness of this measure and to improve our understanding of disease upon fundamental aspects of visual information processing.
Center of Functionally Integrative Neuroscience University of Aarhus Aarhus Denmark
Department of Psychology College of Human and Health Sciences Swansea University Swansea Wales UK
Department of Psychology University of Jyväskylä Jyväskylä Finland
Doctoral School of Behavioural Social and Health Sciences University of Tartu Tartu Estonia
Citace poskytuje Crossref.org
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- $a Kremláček, Jan $u Department of Pathological Physiology, Faculty of Medicine in Hradec Kralove, Charles University in Prague, Hradec Kralove, Czech Republic; Department of Neurology, Faculty of Medicine, Charles University in Prague, University Hospital Hradec Kralove, Hradec Kralove, Czech Republic. Electronic address: jan.kremlacek@lfhk.cuni.cz.
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- $a The visual mismatch negativity (vMMN) response is an event-related potential (ERP) component, which is automatically elicited by events that violate predictions based on prior events. VMMN experiments use visual stimulus repetition to induce predictions, and vMMN is obtained by subtracting the response to rare unpredicted stimuli from those to frequent stimuli. One increasingly popular interpretation of the mismatch response postulates that vMMN, similar to its auditory counterpart (aMMN), represents a prediction error response generated by cortical mechanisms forming probabilistic representations of sensory signals. Here we discuss the physiological and theoretical basis of vMMN and review thirty-three studies from the emerging field of its clinical applications, presenting a meta-analysis of findings in schizophrenia, mood disorders, substance abuse, neurodegenerative disorders, developmental disorders, deafness, panic disorder and hypertension. Furthermore, we include reports on aging and maturation as they bear upon many clinically relevant conditions. Surveying the literature we found that vMMN is altered in several clinical populations which is in line with aMMN findings. An important potential advantage of vMMN however is that it allows the investigation of deficits in predictive processing in cognitive domains which rely primarily on visual information; a principal sensory modality and thus of vital importance in environmental information processing and response, and a modality which arguably may be more sensitive to some pathological changes. However, due to the relative infancy of research in vMMN compared to aMMN in clinical populations its potential for clinical application is not yet fully appreciated. The aim of this review and meta-analysis therefore is to present, in a detailed systematic manner, the findings from clinically-based vMMN studies, to discuss their potential impact and application, to raise awareness of this measure and to improve our understanding of disease upon fundamental aspects of visual information processing.
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- $a Näätänen, Risto $u Institute of Psychology, University of Tartu, Tartu, Estonia; Center of Functionally Integrative Neuroscience (CFIN), University of Aarhus, Aarhus, Denmark; Cognitive Brain Research Unit (CBRU), Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland. Electronic address: risto.naatanen@helsinki.fi.
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- $a Stefanics, Gábor $u Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich & ETH Zurich, Zurich, Switzerland; Laboratory for Social and Neural Systems Research, Department of Economics, University of Zurich, Zurich, Switzerland. Electronic address: stefanics@biomed.ee.ethz.ch.
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