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Behavioral Sciences
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Neurophysiological, Neuroimaging, and Neuropsychological Predictors of Human Alcoholism and Risk
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Neurophysiological, Neuroimaging, and Neuropsychological Predictors of Human Alcoholism and Risk

A special issue of Behavioral Sciences (ISSN 2076-328X).

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 33104

Special Issue Editor

Dr. Chella Kamarajan

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Guest Editor
Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
Interests: brain electrophysiology (EEG, ERP, ERO); alcohol use disorder (AUD); addiction; neuropsychology; cognitive functions; brain connectivity
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

It is my great pleasure to invite you to contribute an article to a Special Issue on "Neurophysiological, neuroimaging, and neuropsychological predictors of human alcoholism and risk". Over the last several decades, brain electrophysiological measures, such as Electroencephalogram (EEG) and Event-Related Potentials/Oscillations (ERP/ERO), as well as neuroimaging and neuropsychological measures have immensely contributed to our understanding of neural mechanisms underlying various psychiatric disorders, including alcohol use disorder (AUD). This Special Issue will feature articles that explore the utility of these neural measures to determine the effects of alcohol use (e.g., regular drinking, social drinking, binge/heavy drinking, and chronic drinking) on brain structure and function and/or to predict risk for developing AUD and other outcomes (e.g., other drug use and externalizing/internalizing traits) across various demographic characteristics (age, gender, ethnicity, etc.). Although this Special Issue will be primarily focused on Neurophysiological, neuroimaging, and neuropsychological studies, other related methods and applications (e.g., MEG and neurofeedback, brain stimulation, neurogenetics, etc.) in alcoholism will also be considered for publication. We also intend to publish a few articles dedicated to a systematic review and/or a meta-analysis that addresses a specific topic of neural measures in alcoholism (e.g., ERP findings in binge drinkers, fMRI findings in chronic AUD, functional connectivity predictors of risk to develop alcohol use disorder, etc.) as part of this Special Issue. The authors may choose the specific topic from their area of expertise. The journal Behavioral Sciences has no restrictions on the length of manuscripts, provided that the text is concise and comprehensive. For an overview of manuscript preparation and submission, authors are advised to refer to the "Instructions for Authors" at: https://www.mdpi.com/journal/behavsci/instructions.

Dr. Chella Kamarajan
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Behavioral Sciences is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • electroencephalogram (EEG)
  • event-related potential (ERP)
  • event-related oscillation (ERO)
  • Magnetic Resonance Imaging (MRI)
  • Diffusion Tensor Imaging (DTI)
  • Functional MRI (fMRI)
  • functional connectivity
  • Resting state networks
  • Tractography
  • spectral Power
  • amplitude
  • frequency bands
  • signal Processing
  • coherence
  • synchrony
  • LORETA
  • current source density (CSD)
  • Fourier transform
  • wavelet transform
  • S-transform
  • time-frequency representation
  • alcoholism
  • alcohol use disorder (AUD)
  • binge drinking
  • social drinking
  • heavy drinking
  • chronic drinking
  • children/offspring of alcoholics
  • high-risk individuals
  • Family history
  • externalizing traits/disorders
  • internalizing traits/disorders
  • cognitive processing
  • affective processing
  • attentional processing
  • reward processing
  • linguistic processing

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Published Papers (8 papers)

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Editorial

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5 pages, 175 KiB  
Editorial
Neurophysiological, Neuroimaging, and Neuropsychological Predictors of Human Alcoholism and Risk
by Chella Kamarajan
Behav. Sci. 2023, 13(10), 790; https://doi.org/10.3390/bs13100790 - 22 Sep 2023
Viewed by 1602
Abstract
Over the last several decades, both brain electrophysiological measurements, such as electroencephalogram (EEG) and event-related potentials/oscillations (ERPs/EROs), and neuroimaging measures have immensely contributed to our understanding of neural mechanisms underlying various psychiatric disorders, including alcohol use disorder (AUD). This Special Issue was launched [...] Read more.
Over the last several decades, both brain electrophysiological measurements, such as electroencephalogram (EEG) and event-related potentials/oscillations (ERPs/EROs), and neuroimaging measures have immensely contributed to our understanding of neural mechanisms underlying various psychiatric disorders, including alcohol use disorder (AUD). This Special Issue was launched to invite research and review articles that explore the utility of these neural measures to determine the effects of alcohol use (e.g., regular drinking, social drinking, binge/heavy drinking, and chronic drinking) on brain structure and function and/or to predict risk for developing AUD and other outcomes (e.g., other drug use and externalizing/internalizing traits) across various demographic characteristics (age, gender, ethnicity, etc.). We received seven scholarly articles, each dealing with specialized topics, which contribute to enhancing our understanding of the brain mechanisms underlying AUD and its risk. The titles of the contributing articles are: (i) Random Forest Classification of Alcohol Use Disorder Using EEG Source Functional Connectivity, Neuropsychological Functioning, and Impulsivity Measures; (ii) Delta Event-Related Oscillations Are Related to a History of Extreme Binge Drinking in Adolescence and Lifetime Suicide Risk; (iii) Alcohol Use and Prefrontal Cortex Volume Trajectories in Young Adults with Mood Disorders and Associated Clinical Outcomes; (iv) Statistical Nonparametric fMRI Maps in the Analysis of Response Inhibition in Abstinent Individuals with History of Alcohol Use Disorder; (v) Differentiating Individuals with and without Alcohol Use Disorder Using Resting-State fMRI Functional Connectivity of Reward Network, Neuropsychological Performance, and Impulsivity Measures; (vi) Epigenetic Effects in HPA Axis Genes Associated with Cortical Thickness, ERP Components and SUD Outcome; and (vii) Predicting Alcohol-Related Memory Problems in Older Adults: A Machine Learning Study with Multi-Domain Features. This Special Issue contains a range of useful topics, covering the utility of EEG, MRI, neuropsychology, epigenetics, environmental, behavioral, and clinical measures related to outcomes, and biological risks related to AUD, which will be useful to alcohol researchers around the world. Full article
(This article belongs to the Special Issue Neurophysiological, Neuroimaging, and Neuropsychological Predictors of Human Alcoholism and Risk)

Research

Jump to: Editorial

25 pages, 2846 KiB  
Article
Predicting Alcohol-Related Memory Problems in Older Adults: A Machine Learning Study with Multi-Domain Features
by Chella Kamarajan, Ashwini K. Pandey, David B. Chorlian, Jacquelyn L. Meyers, Sivan Kinreich, Gayathri Pandey, Stacey Subbie-Saenz de Viteri, Jian Zhang, Weipeng Kuang, Peter B. Barr, Fazil Aliev, Andrey P. Anokhin, Martin H. Plawecki, Samuel Kuperman, Laura Almasy, Alison Merikangas, Sarah J. Brislin, Lance Bauer, Victor Hesselbrock, Grace Chan, John Kramer, Dongbing Lai, Sarah Hartz, Laura J. Bierut, Vivia V. McCutcheon, Kathleen K. Bucholz, Danielle M. Dick, Marc A. Schuckit, Howard J. Edenberg and Bernice Porjeszadd Show full author list remove Hide full author list
Behav. Sci. 2023, 13(5), 427; https://doi.org/10.3390/bs13050427 - 18 May 2023
Cited by 1 | Viewed by 2581
Abstract
Memory problems are common among older adults with a history of alcohol use disorder (AUD). Employing a machine learning framework, the current study investigates the use of multi-domain features to classify individuals with and without alcohol-induced memory problems. A group of 94 individuals [...] Read more.
Memory problems are common among older adults with a history of alcohol use disorder (AUD). Employing a machine learning framework, the current study investigates the use of multi-domain features to classify individuals with and without alcohol-induced memory problems. A group of 94 individuals (ages 50–81 years) with alcohol-induced memory problems (the memory group) were compared with a matched control group who did not have memory problems. The random forests model identified specific features from each domain that contributed to the classification of the memory group vs. the control group (AUC = 88.29%). Specifically, individuals from the memory group manifested a predominant pattern of hyperconnectivity across the default mode network regions except for some connections involving the anterior cingulate cortex, which were predominantly hypoconnected. Other significant contributing features were: (i) polygenic risk scores for AUD, (ii) alcohol consumption and related health consequences during the past five years, such as health problems, past negative experiences, withdrawal symptoms, and the largest number of drinks in a day during the past twelve months, and (iii) elevated neuroticism and increased harm avoidance, and fewer positive “uplift” life events. At the neural systems level, hyperconnectivity across the default mode network regions, including the connections across the hippocampal hub regions, in individuals with memory problems may indicate dysregulation in neural information processing. Overall, the study outlines the importance of utilizing multidomain features, consisting of resting-state brain connectivity data collected ~18 years ago, together with personality, life experiences, polygenic risk, and alcohol consumption and related consequences, to predict the alcohol-related memory problems that arise in later life. Full article
(This article belongs to the Special Issue Neurophysiological, Neuroimaging, and Neuropsychological Predictors of Human Alcoholism and Risk)
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19 pages, 1065 KiB  
Article
Epigenetic Effects in HPA Axis Genes Associated with Cortical Thickness, ERP Components and SUD Outcome
by Shirley Y. Hill, Jeannette L. Wellman, Nicholas Zezza, Stuart R. Steinhauer, Vinod Sharma and Brian Holmes
Behav. Sci. 2022, 12(10), 347; https://doi.org/10.3390/bs12100347 - 20 Sep 2022
Cited by 5 | Viewed by 2186
Abstract
Association between familial loading for alcohol use disorders (AUD) and event-related potentials (ERPs) suggests a genetic basis for these oscillations though much less is known about epigenetic pathways influenced by environmental variation. Early life adversity (ELA) influences negative outcomes much later in life. [...] Read more.
Association between familial loading for alcohol use disorders (AUD) and event-related potentials (ERPs) suggests a genetic basis for these oscillations though much less is known about epigenetic pathways influenced by environmental variation. Early life adversity (ELA) influences negative outcomes much later in life. The stress-activated neuropeptide corticotropin-releasing hormone (CRH) contributes to the deleterious effects of ELA on brain structure and function in animals. Accordingly, we hypothesized that ELA would be related to cortical thickness and electrophysiological characteristics through an epigenetic effect on CRH receptor type-1 (CRHR1) methylation. A total of 217 adolescent and young adult participants from either multiplex alcohol dependence or control families were scanned using magnetic resonance imaging (MRI) at 3T and cortical thickness was determined. Longitudinal follow-up across childhood, adolescence, and young adulthood provided developmental ERP data and measures of adversity. Blood samples for genetic and epigenetic analyses were obtained in childhood. Cortical thickness and visual ERP components were analyzed for their association and tested for familial risk group differences. Visual P300 amplitude at Pz and cortical thickness of the left lateral orbitofrontal region (LOFC), were significantly related to risk group status. LOFC cortical thickness showed a negative correlation with CRHR1 methylation status and with childhood total stress scores from the Life Stressors and Social Resources Inventory (LISRES). Stress scores were also significantly related to P300 amplitude recorded in childhood. The present results suggest that early life adversity reflected in greater total LISRES stress scores in childhood can impact the methylation of the CRHR1 gene with implications for brain development as seen in cortical thickness and electrophysiological signals emanating from particular brain regions. Full article
(This article belongs to the Special Issue Neurophysiological, Neuroimaging, and Neuropsychological Predictors of Human Alcoholism and Risk)
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26 pages, 5261 KiB  
Article
Differentiating Individuals with and without Alcohol Use Disorder Using Resting-State fMRI Functional Connectivity of Reward Network, Neuropsychological Performance, and Impulsivity Measures
by Chella Kamarajan, Babak A. Ardekani, Ashwini K. Pandey, Sivan Kinreich, Gayathri Pandey, David B. Chorlian, Jacquelyn L. Meyers, Jian Zhang, Elaine Bermudez, Weipeng Kuang, Arthur T. Stimus and Bernice Porjesz
Behav. Sci. 2022, 12(5), 128; https://doi.org/10.3390/bs12050128 - 28 Apr 2022
Cited by 7 | Viewed by 3933
Abstract
Individuals with alcohol use disorder (AUD) may manifest an array of neural and behavioral abnormalities, including altered brain networks, impaired neurocognitive functioning, and heightened impulsivity. Using multidomain measures, the current study aimed to identify specific features that can differentiate individuals with AUD from [...] Read more.
Individuals with alcohol use disorder (AUD) may manifest an array of neural and behavioral abnormalities, including altered brain networks, impaired neurocognitive functioning, and heightened impulsivity. Using multidomain measures, the current study aimed to identify specific features that can differentiate individuals with AUD from healthy controls (CTL), utilizing a random forests (RF) classification model. Features included fMRI-based resting-state functional connectivity (rsFC) across the reward network, neuropsychological task performance, and behavioral impulsivity scores, collected from thirty abstinent adult males with prior history of AUD and thirty CTL individuals without a history of AUD. It was found that the RF model achieved a classification accuracy of 86.67% (AUC = 93%) and identified key features of FC and impulsivity that significantly contributed to classifying AUD from CTL individuals. Impulsivity scores were the topmost predictors, followed by twelve rsFC features involving seventeen key reward regions in the brain, such as the ventral tegmental area, nucleus accumbens, anterior insula, anterior cingulate cortex, and other cortical and subcortical structures. Individuals with AUD manifested significant differences in impulsivity and alterations in functional connectivity relative to controls. Specifically, AUD showed heightened impulsivity and hypoconnectivity in nine connections across 13 regions and hyperconnectivity in three connections involving six regions. Relative to controls, visuo-spatial short-term working memory was also found to be impaired in AUD. In conclusion, specific multidomain features of brain connectivity, impulsivity, and neuropsychological performance can be used in a machine learning framework to effectively classify AUD individuals from healthy controls. Full article
(This article belongs to the Special Issue Neurophysiological, Neuroimaging, and Neuropsychological Predictors of Human Alcoholism and Risk)
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23 pages, 4866 KiB  
Article
Statistical Nonparametric fMRI Maps in the Analysis of Response Inhibition in Abstinent Individuals with History of Alcohol Use Disorder
by Ashwini Kumar Pandey, Babak Assai Ardekani, Kelly Nicole-Helen Byrne, Chella Kamarajan, Jian Zhang, Gayathri Pandey, Jacquelyn Leigh Meyers, Sivan Kinreich, David Balin Chorlian, Weipeng Kuang, Arthur T. Stimus and Bernice Porjesz
Behav. Sci. 2022, 12(5), 121; https://doi.org/10.3390/bs12050121 - 21 Apr 2022
Cited by 1 | Viewed by 3674
Abstract
Inhibitory impairments may persist after abstinence in individuals with alcohol use disorder (AUD). Using traditional statistical parametric mapping (SPM) fMRI analysis, which requires data to satisfy parametric assumptions often difficult to satisfy in biophysical system as brain, studies have reported equivocal findings on [...] Read more.
Inhibitory impairments may persist after abstinence in individuals with alcohol use disorder (AUD). Using traditional statistical parametric mapping (SPM) fMRI analysis, which requires data to satisfy parametric assumptions often difficult to satisfy in biophysical system as brain, studies have reported equivocal findings on brain areas responsible for response inhibition, and activation abnormalities during inhibition found in AUD persist after abstinence. Research is warranted using newer analysis approaches. fMRI scans were acquired during a Go/NoGo task from 30 abstinent male AUD and 30 healthy control participants with the objectives being (1) to characterize neuronal substrates associated with response inhibition using a rigorous nonparametric permutation-based fMRI analysis and (2) to determine whether these regions were differentially activated between abstinent AUD and control participants. A blood oxygen level dependent contrast analysis showed significant activation in several right cortical regions and deactivation in some left cortical regions during successful inhibition. The largest source of variance in activation level was due to group differences. The findings provide evidence of cortical substrates employed during response inhibition. The largest variance was explained by lower activation in inhibition as well as ventral attentional cortical networks in abstinent individuals with AUD, which were not found to be associated with length of abstinence, age, or impulsiveness. Full article
(This article belongs to the Special Issue Neurophysiological, Neuroimaging, and Neuropsychological Predictors of Human Alcoholism and Risk)
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16 pages, 509 KiB  
Article
Alcohol Use and Prefrontal Cortex Volume Trajectories in Young Adults with Mood Disorders and Associated Clinical Outcomes
by Dylan E. Kirsch, Valeria Tretyak, Vanessa Le, Ansley Huffman, Kim Fromme, Stephen M. Strakowski and Elizabeth T.C. Lippard
Behav. Sci. 2022, 12(3), 57; https://doi.org/10.3390/bs12030057 - 22 Feb 2022
Cited by 2 | Viewed by 3336
Abstract
(1) Background: Alcohol use in the course of mood disorders is associated with worse clinical outcomes. The mechanisms by which alcohol use alters the course of illness are unclear but may relate to prefrontal cortical (PFC) sensitivity to alcohol. We investigated associations between [...] Read more.
(1) Background: Alcohol use in the course of mood disorders is associated with worse clinical outcomes. The mechanisms by which alcohol use alters the course of illness are unclear but may relate to prefrontal cortical (PFC) sensitivity to alcohol. We investigated associations between alcohol use and PFC structural trajectories in young adults with a mood disorder compared to typically developing peers. (2) Methods: 41 young adults (24 with a mood disorder, agemean = 21 ± 2 years) completed clinical evaluations, assessment of alcohol use, and two structural MRI scans approximately one year apart. Freesurfer was used to segment PFC regions of interest (ROIs) (anterior cingulate, orbitofrontal cortex, and frontal pole). Effects of group, alcohol use, time, and interactions among these variables on PFC ROIs at baseline and follow-up were modeled. Associations were examined between alcohol use and longitudinal changes in PFC ROIs with prospective mood. (3) Results: Greater alcohol use was prospectively associated with decreased frontal pole volume in participants with a mood disorder, but not typically developing comparison participants (time-by-group-by-alcohol interaction; p = 0.007); however, this interaction became a statistical trend in a sensitivity analysis excluding one outlier in terms of alcohol use. Greater alcohol use and a decrease in frontal pole volume related to longer duration of major depression during follow-up (p’s < 0.05). (4) Conclusion: Preliminary findings support more research on alcohol use, PFC trajectories, and depression recurrence in young adults with a mood disorder including individuals with heavier drinking patterns. Full article
(This article belongs to the Special Issue Neurophysiological, Neuroimaging, and Neuropsychological Predictors of Human Alcoholism and Risk)
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20 pages, 1267 KiB  
Article
Delta Event-Related Oscillations Are Related to a History of Extreme Binge Drinking in Adolescence and Lifetime Suicide Risk
by Cindy L. Ehlers, Derek N. Wills, Katherine J. Karriker-Jaffe, David A. Gilder, Evelyn Phillips and Rebecca A. Bernert
Behav. Sci. 2020, 10(10), 154; https://doi.org/10.3390/bs10100154 - 7 Oct 2020
Cited by 9 | Viewed by 3431
Abstract
Alcohol exposure typically begins in adolescence, and heavy binge drinking is associated with health risk behaviors. Event-related oscillations (EROs) may represent sensitive biomarkers or endophenotypes for early alcohol exposure as well as other risk behaviors such as suicidal thoughts and actions. In this [...] Read more.
Alcohol exposure typically begins in adolescence, and heavy binge drinking is associated with health risk behaviors. Event-related oscillations (EROs) may represent sensitive biomarkers or endophenotypes for early alcohol exposure as well as other risk behaviors such as suicidal thoughts and actions. In this study, young adults (age 18–30 years) of American Indian (AI) (n = 479) and Mexican American (MA) (n = 705) ancestry were clinically assessed, and EROs were generated to happy, sad and neutral faces. Extreme adolescent binge drinking (10+ drinks) was common (20%) in this population of AI/MA and associated with a significantly increased risk of a lifetime history of suicidal acts (SA, suicide attempts, deaths) but not suicidal thoughts (ST, ideation, plans). ST were reported among MA participants, whereas SA were more common among AI young adults. Extreme adolescent binge drinking was also associated with errors in detection of sad and neutral faces, increases in delta ERO energy, and decreases in phase locking (PL), particularly in parietal areas. A lifetime history of ST was associated with increases in delta ERO energy and PL, whereas SA were associated with decreases in both. These studies suggest that ERO measures may represent important potential biomarkers of adolescent extreme binge drinking and risk for suicidal behaviors. Full article
(This article belongs to the Special Issue Neurophysiological, Neuroimaging, and Neuropsychological Predictors of Human Alcoholism and Risk)
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32 pages, 5217 KiB  
Article
Random Forest Classification of Alcohol Use Disorder Using EEG Source Functional Connectivity, Neuropsychological Functioning, and Impulsivity Measures
by Chella Kamarajan, Babak A. Ardekani, Ashwini K. Pandey, David B. Chorlian, Sivan Kinreich, Gayathri Pandey, Jacquelyn L. Meyers, Jian Zhang, Weipeng Kuang, Arthur T. Stimus and Bernice Porjesz
Behav. Sci. 2020, 10(3), 62; https://doi.org/10.3390/bs10030062 - 1 Mar 2020
Cited by 21 | Viewed by 10506
Abstract
Individuals with alcohol use disorder (AUD) manifest a variety of impairments that can be attributed to alterations in specific brain networks. The current study aims to identify features of EEG-based functional connectivity, neuropsychological performance, and impulsivity that can classify individuals with AUD (N [...] Read more.
Individuals with alcohol use disorder (AUD) manifest a variety of impairments that can be attributed to alterations in specific brain networks. The current study aims to identify features of EEG-based functional connectivity, neuropsychological performance, and impulsivity that can classify individuals with AUD (N = 30) from unaffected controls (CTL, N = 30) using random forest classification. The features included were: (i) EEG source functional connectivity (FC) of the default mode network (DMN) derived using eLORETA algorithm, (ii) neuropsychological scores from the Tower of London test (TOLT) and the visual span test (VST), and (iii) impulsivity factors from the Barratt impulsiveness scale (BIS). The random forest model achieved a classification accuracy of 80% and identified 29 FC connections (among 66 connections per frequency band), 3 neuropsychological variables from VST (total number of correctly performed trials in forward and backward sequences and average time for correct trials in forward sequence) and all four impulsivity scores (motor, non-planning, attentional, and total) as significantly contributing to classifying individuals as either AUD or CTL. Although there was a significant age difference between the groups, most of the top variables that contributed to the classification were not significantly correlated with age. The AUD group showed a predominant pattern of hyperconnectivity among 25 of 29 significant connections, indicating aberrant network functioning during resting state suggestive of neural hyperexcitability and impulsivity. Further, parahippocampal hyperconnectivity with other DMN regions was identified as a major hub region dysregulated in AUD (13 connections overall), possibly due to neural damage from chronic drinking, which may give rise to cognitive impairments, including memory deficits and blackouts. Furthermore, hypoconnectivity observed in four connections (prefrontal nodes connecting posterior right-hemispheric regions) may indicate a weaker or fractured prefrontal connectivity with other regions, which may be related to impaired higher cognitive functions. The AUD group also showed poorer memory performance on the VST task and increased impulsivity in all factors compared to controls. Features from all three domains had significant associations with one another. These results indicate that dysregulated neural connectivity across the DMN regions, especially relating to hyperconnected parahippocampal hub as well as hypoconnected prefrontal hub, may potentially represent neurophysiological biomarkers of AUD, while poor visual memory performance and heightened impulsivity may serve as cognitive-behavioral indices of AUD. Full article
(This article belongs to the Special Issue Neurophysiological, Neuroimaging, and Neuropsychological Predictors of Human Alcoholism and Risk)
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