The crossroads of anxiety: distinct neurophysiological maps for different symptomatic groups
Authors Gerez M, Suarez E, Serrano C, Castanedo L, Tello A
Received 31 May 2015
Accepted for publication 11 September 2015
Published 18 January 2016 Volume 2016:12 Pages 159—175
Checked for plagiarism Yes
Review by Single-blind
Peer reviewer comments 4
Editor who approved publication: Dr Roger Pinder
Montserrat Gerez,1–3 Enrique Suárez,2,3 Carlos Serrano,2,3 Lauro Castanedo,2 Armando Tello1,3
1Departamento de Neurofisiología Clínica, Hospital Español de México, Mexico City, Mexico; 2Departamento de Psiquiatría, Hospital Español de México, Mexico City, Mexico; 3Unidad de Postgrado, Universidad Nacional Autónoma de México, Mexico City, Mexico
Background: Despite the devastating impact of anxiety disorders (ADs) worldwide, long-lasting debates on causes and remedies have not solved the clinician’s puzzle: who should be treated and how? Psychiatric classifications conceptualize ADs as distinct entities, with strong support from neuroscience fields. Yet, comorbidity and pharmacological response suggest a single “serotonin dysfunction” dimension. Whether AD is one or several disorders goes beyond academic quarrels, and the distinction has therapeutic relevance. Addressing the underlying dysfunctions should improve treatment response. By its own nature, neurophysiology can be the best tool to address dysfunctional processes.
Purpose: To search for neurophysiological dysfunctions and differences among panic disorder (PD), agoraphobia-social-specific phobia, obsessive–compulsive disorder (OCD) and generalized anxiety disorder.
Methods: A sample population of 192 unmedicated patients and 30 aged-matched controls partook in this study. Hypothesis-related neurophysiological variables were combined into ten independent factors: 1) dysrhythmic patterns, 2) delta, 3) theta, 4) alpha, 5) beta (whole-head absolute power z-scores), 6) event-related potential (ERP) combined latency, 7) ERP combined amplitude (z-scores), 8) magnitude, 9) site, and 10) site of hyperactive networks. Combining single variables into representative factors was necessary because, as in all real-life phenomena, the complexity of interactive processes cannot be addressed through single variables and the multiplicity of potentially implicated variables would demand an extremely large sample size for statistical analysis.
Results: The nonparametric analysis correctly classified 81% of the sample. Dysrhythmic patterns, decreased delta, and increased beta differentiated AD from controls. Shorter ERP latencies were found in several individual patients, mostly from the OCD group. Hyperactivities were found at the right frontorbital-striatal network in OCD and at the panic circuit in PD.
Conclusions: Our findings support diffuse cortical instability in AD in general, with individual differences in information processing deficits and regional hyperactivities in OCD and PD. Study limitations and the rationale behind the variable selection and combination strategy will be discussed before addressing the therapeutic implications of our findings.
Keywords: anxiety disorders, dysrhythmic, epileptiform, ERP, EEG, LORETA
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