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Mental Activity as the Bridge between Neural Biomarkers and Symptoms of Psychiatric Illness

The Research Domain Criteria (RDoC) initiative challenges researchers to build neurobehavioral models of psychiatric illness with the hope that such models identify better targets that will yield more effective treatment. However, a guide for building such models was not provided and symptom heterog...

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Autores principales: Riddle, Justin, Frohlich, Flavio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10311940/
https://www.ncbi.nlm.nih.gov/pubmed/35861807
http://dx.doi.org/10.1177/15500594221112417
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author Riddle, Justin
Frohlich, Flavio
author_facet Riddle, Justin
Frohlich, Flavio
author_sort Riddle, Justin
collection PubMed
description The Research Domain Criteria (RDoC) initiative challenges researchers to build neurobehavioral models of psychiatric illness with the hope that such models identify better targets that will yield more effective treatment. However, a guide for building such models was not provided and symptom heterogeneity within Diagnostic Statistical Manual categories has hampered progress in identifying endophenotypes that underlie mental illness. We propose that the best chance to discover viable biomarkers and treatment targets for psychiatric illness is to investigate a triangle of relationships: severity of a specific psychiatric symptom that correlates to mental activity that correlates to a neural activity signature. We propose that this is the minimal model complexity required to advance the field of psychiatry. With an understanding of how neural activity relates to the experience of the patient, a genuine understanding for how treatment imparts its therapeutic effect is possible. After the discovery of this three-fold relationship, causal testing is required in which the neural activity pattern is directly enhanced or suppressed to provide causal, instead of just correlational, evidence for the biomarker. We suggest using non-invasive brain stimulation (NIBS) as these techniques provide tools to precisely manipulate spatial and temporal activity patterns. We detail how this approach enabled the discovery of two orthogonal electroencephalography (EEG) activity patterns associated with anhedonia and anxiosomatic symptoms in depression that can serve as future treatment targets. Altogether, we propose a systematic approach for building neurobehavioral models for dimensional psychiatry.
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spelling pubmed-103119402023-07-01 Mental Activity as the Bridge between Neural Biomarkers and Symptoms of Psychiatric Illness Riddle, Justin Frohlich, Flavio Clin EEG Neurosci Special Issue: Update on Neural Oscillations in Neuropsychiatric Disorders The Research Domain Criteria (RDoC) initiative challenges researchers to build neurobehavioral models of psychiatric illness with the hope that such models identify better targets that will yield more effective treatment. However, a guide for building such models was not provided and symptom heterogeneity within Diagnostic Statistical Manual categories has hampered progress in identifying endophenotypes that underlie mental illness. We propose that the best chance to discover viable biomarkers and treatment targets for psychiatric illness is to investigate a triangle of relationships: severity of a specific psychiatric symptom that correlates to mental activity that correlates to a neural activity signature. We propose that this is the minimal model complexity required to advance the field of psychiatry. With an understanding of how neural activity relates to the experience of the patient, a genuine understanding for how treatment imparts its therapeutic effect is possible. After the discovery of this three-fold relationship, causal testing is required in which the neural activity pattern is directly enhanced or suppressed to provide causal, instead of just correlational, evidence for the biomarker. We suggest using non-invasive brain stimulation (NIBS) as these techniques provide tools to precisely manipulate spatial and temporal activity patterns. We detail how this approach enabled the discovery of two orthogonal electroencephalography (EEG) activity patterns associated with anhedonia and anxiosomatic symptoms in depression that can serve as future treatment targets. Altogether, we propose a systematic approach for building neurobehavioral models for dimensional psychiatry. SAGE Publications 2022-07-21 2023-07 /pmc/articles/PMC10311940/ /pubmed/35861807 http://dx.doi.org/10.1177/15500594221112417 Text en © EEG and Clinical Neuroscience Society (ECNS) 2022 https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Special Issue: Update on Neural Oscillations in Neuropsychiatric Disorders
Riddle, Justin
Frohlich, Flavio
Mental Activity as the Bridge between Neural Biomarkers and Symptoms of Psychiatric Illness
title Mental Activity as the Bridge between Neural Biomarkers and Symptoms of Psychiatric Illness
title_full Mental Activity as the Bridge between Neural Biomarkers and Symptoms of Psychiatric Illness
title_fullStr Mental Activity as the Bridge between Neural Biomarkers and Symptoms of Psychiatric Illness
title_full_unstemmed Mental Activity as the Bridge between Neural Biomarkers and Symptoms of Psychiatric Illness
title_short Mental Activity as the Bridge between Neural Biomarkers and Symptoms of Psychiatric Illness
title_sort mental activity as the bridge between neural biomarkers and symptoms of psychiatric illness
topic Special Issue: Update on Neural Oscillations in Neuropsychiatric Disorders
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10311940/
https://www.ncbi.nlm.nih.gov/pubmed/35861807
http://dx.doi.org/10.1177/15500594221112417
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