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Electrophysiology as a theoretical and methodological hub for the neural sciences.
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- Author(s): Cavanagh JF;Cavanagh JF
- Source:
Psychophysiology [Psychophysiology] 2019 Feb; Vol. 56 (2), pp. e13314. Date of Electronic Publication: 2018 Dec 16.- Publication Type:
Journal Article; Review- Language:
English - Source:
- Additional Information
- Source: Publisher: Blackwell Country of Publication: United States NLM ID: 0142657 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1540-5958 (Electronic) Linking ISSN: 00485772 NLM ISO Abbreviation: Psychophysiology Subsets: MEDLINE
- Publication Information: Publication: Malden, MA : Blackwell
Original Publication: Baltimore, Williams & Wilkins. - Subject Terms: Electrophysiological Phenomena* ; Models, Neurological*; Electroencephalography/*methods ; Electrophysiology/*methods ; Neurosciences/*methods ; Translational Research, Biomedical/*methods; Animals ; Electroencephalography/trends ; Electrophysiology/trends ; Humans ; Neurosciences/trends ; Translational Research, Biomedical/trends
- Abstract: Electrophysiology is a direct measure of neuronal processes, and it is uniquely sensitive to canonical neural operations that underlie emergent psychological operations. These qualities make it well suited for discovery of aberrant neural mechanisms that underlie complicated disease states. This technique is routinely utilized in vitro, in vivo, and in outpatient neurological clinics, offering a translatable bridge between animal models and human patients. The bench-to-bedside potential of this approach is unparalleled, yet it also remains undeveloped due to the slow inertia of legacy techniques and interpretations. In this review, I discuss these strengths of the method, and I detail compelling reasons why future advancements can have a direct and tangible influence over clinical practice. I hope to motivate a blurring of traditional boundaries between preclinical, computational, imaging, and clinical fields by advancing electrophysiology as a common hub for methodological integration and theoretical advancement.
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Trends Neurosci. 2017 Apr;40(4):208-218. (PMID: 28314445) - Grant Information: P20 GM109089 United States GM NIGMS NIH HHS; UH2 MH109168 United States MH NIMH NIH HHS; 1P20GM109089-01A1 United States GM NIGMS NIH HHS; 1UH2MH109168-01 United States MH NIMH NIH HHS
- Contributed Indexing: Keywords: EEG; ERPs; computational modeling; neurology; psychiatry; translation
- Publication Date: Date Created: 20181218 Date Completed: 20200325 Latest Revision: 20240216
- Publication Date: 20240216
- Accession Number: PMC6687291
- Accession Number: 10.1111/psyp.13314
- Accession Number: 30556196
- Source:
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