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Gupta RS, Light GA, Simmons AN, Harlé KM, Stout DM. Sex moderates the effect of anhedonia on parietal alpha asymmetry. J Psychiatr Res 2024; 177:97-101. [PMID: 39002532 DOI: 10.1016/j.jpsychires.2024.06.051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 06/23/2024] [Accepted: 06/28/2024] [Indexed: 07/15/2024]
Abstract
Anhedonia, a transdiagnostic symptom present in many neuropsychiatric disorders, differs in males and females. Parietal EEG alpha asymmetry is associated with reduced arousal and low positive emotionality, and is, therefore, a promising neurophysiologic biomarker of anhedonia. To date, however, no prior studies have determined whether this measure captures sex differences in anhedonic expression. This preliminary study (N = 36) investigated whether anhedonia severity is associated with EEG resting-state parietal alpha asymmetry in adults and whether sex moderates this relationship. Results showed that there was a significant moderating effect of sex such that, only for females, higher levels of anhedonia were associated with increased parietal alpha asymmetry. These findings suggest that parietal alpha asymmetry is a promising biomarker of anhedonia severity in female adults and reinforces the need to account for sex differences in future research.
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Affiliation(s)
- Resh S Gupta
- Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, 63130, USA.
| | - Gregory A Light
- Department of Psychiatry, University of California San Diego, La Jolla, CA, 92093, USA; Desert Pacific Mental Illness Research Education and Clinical Center, La Jolla, CA, USA
| | - Alan N Simmons
- Department of Psychiatry, University of California San Diego, La Jolla, CA, 92093, USA; Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, 92161, USA
| | - Katia M Harlé
- Department of Psychiatry, University of California San Diego, La Jolla, CA, 92093, USA; Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, 92161, USA
| | - Daniel M Stout
- Department of Psychiatry, University of California San Diego, La Jolla, CA, 92093, USA; Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, 92161, USA
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2
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Wang B, Li M, Haihambo N, Qiu Z, Sun M, Guo M, Zhao X, Han C. Characterizing Major Depressive Disorder (MDD) using alpha-band activity in resting-state electroencephalogram (EEG) combined with MATRICS Consensus Cognitive Battery (MCCB). J Affect Disord 2024; 355:254-264. [PMID: 38561155 DOI: 10.1016/j.jad.2024.03.145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/28/2023] [Revised: 03/24/2024] [Accepted: 03/25/2024] [Indexed: 04/04/2024]
Abstract
BACKGROUND The diagnosis of major depressive disorder (MDD) is commonly based on the subjective evaluation by experienced psychiatrists using clinical scales. Hence, it is particularly important to find more objective biomarkers to aid in diagnosis and further treatment. Alpha-band activity (7-13 Hz) is the most prominent component in resting electroencephalogram (EEG), which is also thought to be a potential biomarker. Recent studies have shown the existence of multiple sub-oscillations within the alpha band, with distinct neural underpinnings. However, the specific contribution of these alpha sub-oscillations to the diagnosis and treatment of MDD remains unclear. METHODS In this study, we recorded the resting-state EEG from MDD and HC populations in both open and closed-eye state conditions. We also assessed cognitive processing using the MATRICS Consensus Cognitive Battery (MCCB). RESULTS We found that the MDD group showed significantly higher power in the high alpha range (10.5-11.5 Hz) and lower power in the low alpha range (7-8.5 Hz) compared to the HC group. Notably, high alpha power in the MDD group is negatively correlated with working memory performance in MCCB, whereas no such correlation was found in the HC group. Furthermore, using five established classification algorithms, we discovered that combining alpha oscillations with MCCB scores as features yielded the highest classification accuracy compared to using EEG or MCCB scores alone. CONCLUSIONS Our results demonstrate the potential of sub-oscillations within the alpha frequency band as a potential distinct biomarker. When combined with psychological scales, they may provide guidance relevant for the diagnosis and treatment of MDD.
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Affiliation(s)
- Bin Wang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing 100088, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, 100191 Beijing, China
| | - Meijia Li
- Faculty of Psychology and Center for Neuroscience, Vrije Universiteit Brussel, 1050 Brussels, Belgium
| | - Naem Haihambo
- Faculty of Psychology and Center for Neuroscience, Vrije Universiteit Brussel, 1050 Brussels, Belgium
| | - Zihan Qiu
- Avenues the World School Shenzhen Campus, Shenzhen 518000, China
| | - Meirong Sun
- School of Psychology, Beijing Sport University, Beijing 100084, China
| | - Mingrou Guo
- Department of Psychology, The Chinese University of Hong Kong, Hong Kong
| | - Xixi Zhao
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing 100088, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, 100191 Beijing, China.
| | - Chuanliang Han
- School of Biomedical Sciences and Gerald Choa Neuroscience Institute, The Chinese University of Hong Kong, Hong Kong.
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3
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Meijs H, Voetterl H, Sack AT, van Dijk H, De Wilde B, Van Hecke J, Niemegeers P, Gordon E, Luykx JJ, Arns M. A posterior-alpha ageing network is differentially associated with antidepressant effects of venlafaxine and rTMS. Eur Neuropsychopharmacol 2024; 79:7-16. [PMID: 38000196 DOI: 10.1016/j.euroneuro.2023.11.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2023] [Revised: 11/06/2023] [Accepted: 11/11/2023] [Indexed: 11/26/2023]
Abstract
Major depressive disorder (MDD) is a highly prevalent psychiatric disorder, but chances for remission largely decrease with each failed treatment attempt. It is therefore desirable to assign a given patient to the most promising individual treatment option as early as possible. We used a polygenic score (PGS) informed electroencephalography (EEG) data-driven approach to identify potential predictors for MDD treatment outcome. Post-hoc we conducted exploratory analyses in order to understand the results in depth. First, an EEG independent component analysis produced 54 functional brain networks in a large heterogeneous cohort of psychiatric patients (n = 4,045; 5-84 yrs.). Next, the network that was associated to PGS for antidepressant-response (PRS-AR) in an independent sample (n = 722) was selected: an age-related posterior alpha network that explained >60 % of EEG variance, and was highly stable over recording time. Translational analyses were performed in two other independent datasets to examine if the network was predictive of psychopharmacotherapy (n = 535) and/or repetitive transcranial magnetic stimulation (rTMS) and concomitant psychotherapy (PT; n = 186) outcome. The network predicted remission to venlafaxine (p = 0.015), resulting in a normalized positive predicted value (nPPV) of 138 %, and rTMS + PT - but in opposite direction for women (p = 0.002) relative to men (p = 0.018) - yielding a nPPV of 131 %. Blinded out-of-sample validations for venlafaxine (n = 29) and rTMS + PT (n = 36) confirmed the findings for venlafaxine, while results for rTMS + PT could not be replicated. These data suggest the existence of a relatively stable EEG posterior alpha aging network related to PGS-AR that has potential as MDD treatment predictor.
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Affiliation(s)
- Hannah Meijs
- Research Institute Brainclinics, Brainclinics Foundation, Nijmegen, The Netherlands; Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Helena Voetterl
- Research Institute Brainclinics, Brainclinics Foundation, Nijmegen, The Netherlands; Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Alexander T Sack
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Hanneke van Dijk
- Research Institute Brainclinics, Brainclinics Foundation, Nijmegen, The Netherlands
| | - Bieke De Wilde
- Department of Psychiatry, Ziekenhuis Netwerk Antwerpen (ZNA), Antwerp, Belgium
| | - Jan Van Hecke
- Department of Psychiatry, Ziekenhuis Netwerk Antwerpen (ZNA), Antwerp, Belgium
| | - Peter Niemegeers
- Department of Psychiatry, Ziekenhuis Netwerk Antwerpen (ZNA), Antwerp, Belgium
| | - Evian Gordon
- Brain Resource Ltd, San Francisco, CA, United States of America
| | - Jurjen J Luykx
- Research Institute Brainclinics, Brainclinics Foundation, Nijmegen, The Netherlands; Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Martijn Arns
- Research Institute Brainclinics, Brainclinics Foundation, Nijmegen, The Netherlands; Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands.
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4
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Huang Y, Yi Y, Chen Q, Li H, Feng S, Zhou S, Zhang Z, Liu C, Li J, Lu Q, Zhang L, Han W, Wu F, Ning Y. Analysis of EEG features and study of automatic classification in first-episode and drug-naïve patients with major depressive disorder. BMC Psychiatry 2023; 23:832. [PMID: 37957613 PMCID: PMC10644563 DOI: 10.1186/s12888-023-05349-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 11/04/2023] [Indexed: 11/15/2023] Open
Abstract
BACKGROUND Major depressive disorder (MDD) has a high incidence and an unknown mechanism. There are no objective and sensitive indicators for clinical diagnosis. OBJECTIVE This study explored specific electrophysiological indicators and their role in the clinical diagnosis of MDD using machine learning. METHODS Forty first-episode and drug-naïve patients with MDD and forty healthy controls (HCs) were recruited. EEG data were collected from all subjects in the resting state with eyes closed for 10 min. The severity of MDD was assessed by the Hamilton Depression Rating Scale (HAMD-17). Machine learning analysis was used to identify the patients with MDD. RESULTS Compared to the HC group, the relative power of the low delta and theta bands was significantly higher in the right occipital region, and the relative power of the alpha band in the entire posterior occipital region was significantly lower in the MDD group. In the MDD group, the alpha band scalp functional connectivity was overall lower, while the scalp functional connectivity in the gamma band was significantly higher than that in the HC group. In the feature set of the relative power of the ROI in each band, the highest accuracy of 88.2% was achieved using the KNN classifier while using PCA feature selection. In the explanatory model using SHAP values, the top-ranking influence feature is the relative power of the alpha band in the left parietal region. CONCLUSIONS Our findings reveal that the abnormal EEG neural oscillations may reflect an imbalance of excitation, inhibition and hyperactivity in the cerebral cortex in first-episode and drug-naïve patients with MDD. The relative power of the alpha band in the left parietal region is expected to be an objective electrophysiological indicator of MDD.
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Affiliation(s)
- Yuanyuan Huang
- The First School of Clinical Medicine, Southern Medical University, Guangzhou, China
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Yun Yi
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Psychiatry, The Brain Hospital of Guangxi Zhuang Autonomous Region, Guangxi, China
| | - Qiang Chen
- Department of Psychiatry, The Brain Hospital of Guangxi Zhuang Autonomous Region, Guangxi, China
| | - Hehua Li
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Shixuan Feng
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Sumiao Zhou
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Ziyun Zhang
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Chenyu Liu
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Junhao Li
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Qiuling Lu
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Lida Zhang
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Wei Han
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Fengchun Wu
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China.
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China.
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, China.
| | - Yuping Ning
- The First School of Clinical Medicine, Southern Medical University, Guangzhou, China.
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China.
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China.
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, China.
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5
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Butler LB, Nooner KB. The Link between Suicidality and Electroencephalography Asymmetry: A Systematic Review and Meta-analysis. CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE : THE OFFICIAL SCIENTIFIC JOURNAL OF THE KOREAN COLLEGE OF NEUROPSYCHOPHARMACOLOGY 2023; 21:419-428. [PMID: 37424411 PMCID: PMC10335909 DOI: 10.9758/cpn.22.1043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 12/26/2022] [Indexed: 07/11/2023]
Abstract
As one of the leading causes of death globally, suicide has been researched extensively to better understand factors that confer risk or resilience for suicidality. Promising areas of the literature have focused on brain-based factors that might indicate susceptibility to suicide. Some studies have investigated the link between electroencephalography (EEG) asymmetry, referring to differences in electrical activity in the brain from the left to right hemisphere, and suicidality. The present study is a comprehensive review and meta-analysis of the literature to see if certain patterns in EEG asymmetry serve as a diathesis for suicidal thoughts and behaviors. The results of the current investigation found that EEG asymmetry was not systematically related to suicide based on the literature reviewed. While the present review does not rule out all brain-based factors, the findings suggest that EEG asymmetry may not be a biomarker for suicidality.
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Affiliation(s)
- Laine B. Butler
- Department of Psychology, University of North Carolina Wilmington, Wilmington, NC, USA
| | - Kate B. Nooner
- Department of Psychology, University of North Carolina Wilmington, Wilmington, NC, USA
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6
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Tsai YC, Li CT, Juan CH. A review of critical brain oscillations in depression and the efficacy of transcranial magnetic stimulation treatment. Front Psychiatry 2023; 14:1073984. [PMID: 37260762 PMCID: PMC10228658 DOI: 10.3389/fpsyt.2023.1073984] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 04/11/2023] [Indexed: 06/02/2023] Open
Abstract
Repetitive transcranial magnetic stimulation (rTMS) and intermittent theta burst stimulation (iTBS) have been proven effective non-invasive treatments for patients with drug-resistant major depressive disorder (MDD). However, some depressed patients do not respond to these treatments. Therefore, the investigation of reliable and valid brain oscillations as potential indices for facilitating the precision of diagnosis and treatment protocols has become a critical issue. The current review focuses on brain oscillations that, mostly based on EEG power analysis and connectivity, distinguish between MDD and controls, responders and non-responders, and potential depression severity indices, prognostic indicators, and potential biomarkers for rTMS or iTBS treatment. The possible roles of each biomarker and the potential reasons for heterogeneous results are discussed, and the directions of future studies are proposed.
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Affiliation(s)
- Yi-Chun Tsai
- Institute of Cognitive Neuroscience, College of Health Sciences and Technology, National Central University, Taoyuan City, Taiwan
| | - Cheng-Ta Li
- Institute of Cognitive Neuroscience, College of Health Sciences and Technology, National Central University, Taoyuan City, Taiwan
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
- Institute of Brain Science, National Yang-Ming Chiao-Tung University, Taipei, Taiwan
- Division of Psychiatry, Faculty of Medicine, National Yang-Ming Chiao-Tung University, Taipei, Taiwan
| | - Chi-Hung Juan
- Institute of Cognitive Neuroscience, College of Health Sciences and Technology, National Central University, Taoyuan City, Taiwan
- Cognitive Intelligence and Precision Healthcare Center, National Central University, Taoyuan City, Taiwan
- Department of Psychology, Kaohsiung Medical University, Kaohsiung, Taiwan
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7
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Ippolito G, Bertaccini R, Tarasi L, Di Gregorio F, Trajkovic J, Battaglia S, Romei V. The Role of Alpha Oscillations among the Main Neuropsychiatric Disorders in the Adult and Developing Human Brain: Evidence from the Last 10 Years of Research. Biomedicines 2022; 10:biomedicines10123189. [PMID: 36551945 PMCID: PMC9775381 DOI: 10.3390/biomedicines10123189] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 12/03/2022] [Accepted: 12/05/2022] [Indexed: 12/14/2022] Open
Abstract
Alpha oscillations (7-13 Hz) are the dominant rhythm in both the resting and active brain. Accordingly, translational research has provided evidence for the involvement of aberrant alpha activity in the onset of symptomatological features underlying syndromes such as autism, schizophrenia, major depression, and Attention Deficit and Hyperactivity Disorder (ADHD). However, findings on the matter are difficult to reconcile due to the variety of paradigms, analyses, and clinical phenotypes at play, not to mention recent technical and methodological advances in this domain. Herein, we seek to address this issue by reviewing the literature gathered on this topic over the last ten years. For each neuropsychiatric disorder, a dedicated section will be provided, containing a concise account of the current models proposing characteristic alterations of alpha rhythms as a core mechanism to trigger the associated symptomatology, as well as a summary of the most relevant studies and scientific contributions issued throughout the last decade. We conclude with some advice and recommendations that might improve future inquiries within this field.
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Affiliation(s)
- Giuseppe Ippolito
- Centro Studi e Ricerche in Neuroscienze Cognitive, Dipartimento di Psicologia, Alma Mater Studiorum—Università di Bologna, 47521 Cesena, Italy
| | - Riccardo Bertaccini
- Centro Studi e Ricerche in Neuroscienze Cognitive, Dipartimento di Psicologia, Alma Mater Studiorum—Università di Bologna, 47521 Cesena, Italy
| | - Luca Tarasi
- Centro Studi e Ricerche in Neuroscienze Cognitive, Dipartimento di Psicologia, Alma Mater Studiorum—Università di Bologna, 47521 Cesena, Italy
| | - Francesco Di Gregorio
- UO Medicina Riabilitativa e Neuroriabilitazione, Azienda Unità Sanitaria Locale, 40133 Bologna, Italy
| | - Jelena Trajkovic
- Centro Studi e Ricerche in Neuroscienze Cognitive, Dipartimento di Psicologia, Alma Mater Studiorum—Università di Bologna, 47521 Cesena, Italy
| | - Simone Battaglia
- Centro Studi e Ricerche in Neuroscienze Cognitive, Dipartimento di Psicologia, Alma Mater Studiorum—Università di Bologna, 47521 Cesena, Italy
- Dipartimento di Psicologia, Università di Torino, 10124 Torino, Italy
| | - Vincenzo Romei
- Centro Studi e Ricerche in Neuroscienze Cognitive, Dipartimento di Psicologia, Alma Mater Studiorum—Università di Bologna, 47521 Cesena, Italy
- Correspondence:
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8
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Freschl J, Azizi LA, Balboa L, Kaldy Z, Blaser E. The development of peak alpha frequency from infancy to adolescence and its role in visual temporal processing: A meta-analysis. Dev Cogn Neurosci 2022; 57:101146. [PMID: 35973361 PMCID: PMC9399966 DOI: 10.1016/j.dcn.2022.101146] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 07/21/2022] [Accepted: 08/08/2022] [Indexed: 01/19/2023] Open
Abstract
While it has been shown that alpha frequency increases over development (Stroganova et al., 1999), a precise trajectory has not yet been specified, making it challenging to constrain theories linking alpha rhythms to perceptual development. We conducted a comprehensive review of studies measuring resting-state occipital peak alpha frequency (PAF, the frequency exhibiting maximum power) from birth to 18 years of age. From 889 potentially relevant studies, we identified 40 reporting PAF (109 samples; 3882 subjects). A nonlinear regression revealed that PAF increases quickly in early childhood (from 6.1 Hz at 6 months to 8.4 Hz at 5 years) and levels off in adolescence (9.7 Hz at 13 years), with an asymptote at 10.1 Hz. We found no effect of resting state procedure (eyes-open versus eyes-closed) or biological sex. PAF has been implicated as a clock on visual temporal processing, with faster frequencies associated with higher visual temporal resolution. Psychophysical studies have shown that temporal resolution reaches adult levels by 5 years of age (Freschl et al., 2019, 2020). The fact that PAF reaches the adult range of 8-12 Hz by that age strengthens the link between PAF and temporal resolution.
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Affiliation(s)
- Julie Freschl
- University of Massachusetts Boston, Boston, MA, USA; Smith-Kettlewell Eye Research Institute, San Francisco, CA, USA.
| | | | | | - Zsuzsa Kaldy
- University of Massachusetts Boston, Boston, MA, USA
| | - Erik Blaser
- University of Massachusetts Boston, Boston, MA, USA
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9
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Liang M, Lomayesva S, Isham EA. Dissociable Roles of Theta and Alpha in Sub-Second and Supra-Second Time Reproduction: An Investigation of their Links to Depression and Anxiety. TIMING & TIME PERCEPTION 2022. [DOI: 10.1163/22134468-bja10061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
Abstract
A growing collection of observations has demonstrated the presence of multiple neural oscillations participating in human temporal cognition and psychiatric pathologies such as depression and anxiety. However, there remains a gap in the literature regarding the specific roles of these neural oscillations during interval timing, and how these oscillatory activities might vary with the different levels of mental health. The current study examined the participation of the frontal midline theta and occipital alpha oscillations, both of which are prevalent cortical oscillatory markers frequently reported in working memory and time perception paradigms. Participants performed a time reproduction task in the sub- (400, 600, 800 ms) and supra-second timescales (1600, 1800, 2000 ms) while undergoing scalp EEG recordings. Anxiety and depression levels were measured via self-report mental health inventories. Time–frequency analysis of scalp EEG revealed that both frontal midline and occipital alpha oscillations were engaged during the encoding of the durations. Furthermore, we observed that the correlational relationship between frontal midline theta power and the reproduction performance in the sub-second range was modulated by state anxiety. In contrast, the correlational relationship between occipital alpha and the reproduction performance of supra-second intervals was modulated by depression and trait anxiety. The results offer insights on how alpha and theta oscillations differentially play a role in interval timing and how mental health further differentially relates these neural oscillations to sub- and supra-second timescales.
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Affiliation(s)
- Mingli Liang
- Department of Psychology, University of Arizona, 1503 E. University Blvd, Tucson, AZ 85721, USA
| | - Sara Lomayesva
- Department of Psychology, University of Arizona, 1503 E. University Blvd, Tucson, AZ 85721, USA
| | - Eve A. Isham
- Department of Psychology, University of Arizona, 1503 E. University Blvd, Tucson, AZ 85721, USA
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10
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He Y, Yu Q, Yang T, Zhang Y, Zhang K, Jin X, Wu S, Gao X, Huang C, Cui X, Luo X. Abnormalities in Electroencephalographic Microstates Among Adolescents With First Episode Major Depressive Disorder. Front Psychiatry 2021; 12:775156. [PMID: 34975577 PMCID: PMC8718790 DOI: 10.3389/fpsyt.2021.775156] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 11/24/2021] [Indexed: 12/28/2022] Open
Abstract
Background: Recent studies have reported changes in the electroencephalograms (EEG) of patients with major depressive disorder (MDD). However, little research has explored EEG differences between adolescents with MDD and healthy controls, particularly EEG microstates differences. The aim of the current study was to characterize EEG microstate activity in adolescents with MDD and healthy controls (HCs). Methods: A total of 35 adolescents with MDD and 35 HCs were recruited in this study. The depressive symptoms were assessed by Hamilton Depression Scale (HAMD) and Children's Depression Inventory (CDI), and the anxiety symptoms were assessed by Chinese version of DSM-5 Level 2-Anxiety-Child scale. A 64-channel EEG was recorded for 5 min (eye closed, resting-state) and analyzed using microstate analysis. Microstate properties were compared between groups and correlated with patients' depression scores. Results: We found increased occurrence and contribution of microstate B in MDD patients compared to HCs, and decreased occurrence and contribution of microstate D in MDD patients compared to HCs. While no significant correlation between depression severity (HAMD score) and the microstate metrics (occurrence and contribution of microstate B and D) differing between MDD adolescents and HCs was found. Conclusions: Adolescents with MDD showed microstate B and microstate D changes. The obtained results may deepen our understanding of dynamic EEG changes among adolescents with MDD and provide some evidence of changes in brain development in adolescents with MDD.
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Affiliation(s)
- Yuqiong He
- National Clinical Research Center for Mental Disorders, Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Qianting Yu
- National Clinical Research Center for Mental Disorders, Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Tingyu Yang
- National Clinical Research Center for Mental Disorders, Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Yaru Zhang
- National Clinical Research Center for Mental Disorders, Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Kun Zhang
- National Clinical Research Center for Mental Disorders, Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Xingyue Jin
- National Clinical Research Center for Mental Disorders, Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Shuxian Wu
- National Clinical Research Center for Mental Disorders, Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Xueping Gao
- National Clinical Research Center for Mental Disorders, Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China.,Autism Center of the Second Xiangya Hospital, Central South University, Changsha, China
| | - Chunxiang Huang
- National Clinical Research Center for Mental Disorders, Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China.,Autism Center of the Second Xiangya Hospital, Central South University, Changsha, China
| | - Xilong Cui
- National Clinical Research Center for Mental Disorders, Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China.,Autism Center of the Second Xiangya Hospital, Central South University, Changsha, China
| | - Xuerong Luo
- National Clinical Research Center for Mental Disorders, Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China.,Autism Center of the Second Xiangya Hospital, Central South University, Changsha, China
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