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Bashford-Largo J, Blair RJR, Blair KS, Dobbertin M, Elowsky J, Dominguez A, Hatch M, Bajaj S. Cortical volume alterations in the limbic network in adolescents with high reactive aggression. Dev Psychopathol 2024:1-9. [PMID: 38584251 DOI: 10.1017/s0954579424000750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Previous studies show aggression-related structural alterations in frontal and limbic brain regions. Most studies have focused on overall aggression, instead of its subtypes, and on specific regions instead of networks. This study aims to identify both brain networks and regions that are associated with reactive and proactive subtypes of aggression. Structural MRI data were collected from 340 adolescents (125 F/215 M) with a mean age of 16.29 (SD = 1.20). Aggression symptomology was indexed via the Reactive Proactive Aggression Questionnaire (RPQ). Freesurfer was used to estimate Cortical Volume (CV) from seven networks and regions within specific networks associated with aggression. Two multivariate analyses of covariance (MANCOVAs) were conducted on groups for low versus higher reactive and proactive RPQ scores. Our reactive aggression MANCOVA showed a main effect in CV [F(14,321) = 1.935, p = 0.022,ηp2 = 0.078] across all the 7-Networks. Unpacking this main effect revealed significant volumetric differences in the right Limbic Network (LN) (p = 0.029) and the Temporal Pole (p = 0.011), where adolescents in the higher reactive aggression group showed higher cortical volumes. Such findings are consistent with region/voxel-specific analyses that have associated atypical structure within the LN and reactive aggression. Moreover, the temporal pole is highly interconnected with regions important in the regulation and initiation of reactive aggression.
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Affiliation(s)
- Johannah Bashford-Largo
- Child and Family Translational Research Center, Boys Town National Research Hospital, Boys Town, NE, USA
- Center for Brain, Biology and Behavior, University of Nebraska-Lincoln, Lincoln, NE, USA
| | - R James R Blair
- Child and Adolescent Mental Health Centre, Mental Health Services, Capital Region of Denmark, Copenhagen, Denmark
| | - Karina S Blair
- Child and Family Translational Research Center, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Matthew Dobbertin
- Child and Family Translational Research Center, Boys Town National Research Hospital, Boys Town, NE, USA
- Child and Adolescent Psychiatric Inpatient Center, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Jaimie Elowsky
- Clinical Psychology Department, University of Nebraska-Lincoln, Lincoln, NE, USA
| | - Ahria Dominguez
- Clinical Health, Emotion, and Neuroscience (CHEN) Laboratory, Department of Neurological Sciences, College of Medicine, University of Nebraska Medical Center, Omaha, NE, USA
| | - Melissa Hatch
- Mind and Brain Health Laboratories (MBHL), Department of Neurological Sciences, College of Medicine, University of Nebraska Medical Center, Omaha, NE, USA
| | - Sahil Bajaj
- Department of Cancer Systems Imaging, MD Anderson Center, University of Texas, Houston, TX, USA
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2
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Li Y, Li C, Jiang L. Well-being is associated with cortical thickness network topology of human brain. BEHAVIORAL AND BRAIN FUNCTIONS : BBF 2023; 19:16. [PMID: 37749598 PMCID: PMC10521404 DOI: 10.1186/s12993-023-00219-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 09/18/2023] [Indexed: 09/27/2023]
Abstract
BACKGROUND Living a happy and meaningful life is an eternal topic in positive psychology, which is crucial for individuals' physical and mental health as well as social functioning. Well-being can be subdivided into pleasure attainment related hedonic well-being or emotional well-being, and self-actualization related eudaimonic well-being or psychological well-being plus social well-being. Previous studies have mostly focused on human brain morphological and functional mechanisms underlying different dimensions of well-being, but no study explored brain network mechanisms of well-being, especially in terms of topological properties of human brain morphological similarity network. METHODS Therefore, in the study, we collected 65 datasets including magnetic resonance imaging (MRI) and well-being data, and constructed human brain morphological network based on morphological distribution similarity of cortical thickness to explore the correlations between topological properties including network efficiency and centrality and different dimensions of well-being. RESULTS We found emotional well-being was negatively correlated with betweenness centrality in the visual network but positively correlated with eigenvector centrality in the precentral sulcus, while the total score of well-being was positively correlated with local efficiency in the posterior cingulate cortex of cortical thickness network. CONCLUSIONS Our findings demonstrated that different dimensions of well-being corresponded to different cortical hierarchies: hedonic well-being was involved in more preliminary cognitive processing stages including perceptual and attentional information processing, while hedonic and eudaimonic well-being might share common morphological similarity network mechanisms in the subsequent advanced cognitive processing stages.
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Affiliation(s)
- Yubin Li
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, No. 16 Lincui Road, Chaoyang District, Beijing, 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Shijingshan, Beijing, China
| | - Chunlin Li
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, No. 16 Lincui Road, Chaoyang District, Beijing, 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Shijingshan, Beijing, China
| | - Lili Jiang
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, No. 16 Lincui Road, Chaoyang District, Beijing, 100101, China.
- Department of Psychology, University of Chinese Academy of Sciences, Shijingshan, Beijing, China.
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3
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MacSweeney N, Louvet P, Zafar S, Chan SWY, Kwong ASF, Lawrie SM, Romaniuk L, Whalley HC. Keeping up with the kids: the value of co-production in the study of irritability in youth depression and its underlying neural circuitry. Front Behav Neurosci 2023; 17:1124940. [PMID: 37397127 PMCID: PMC10310302 DOI: 10.3389/fnbeh.2023.1124940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 05/30/2023] [Indexed: 07/04/2023] Open
Abstract
Irritability is a core symptom of adolescent depression, characterized by an increased proneness to anger or frustration. Irritability in youth is associated with future mental health problems and impaired social functioning, suggesting that it may be an early indicator of emotion regulation difficulties. Adolescence is a period during which behavior is significantly impacted by one's environment. However, existing research on the neural basis of irritability typically use experimental paradigms that overlook the social context in which irritability occurs. Here, we bring together current findings on irritability in adolescent depression and the associated neurobiology and highlight directions for future research. Specifically, we emphasize the importance of co-produced research with young people as a means to improve the construct and ecological validity of research within the field. Ensuring that our research design and methodology accurately reflect to lives of young people today lays a strong foundation upon which to better understand adolescent depression and identify tractable targets for intervention.
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Affiliation(s)
- Niamh MacSweeney
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway
| | - Perrine Louvet
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Simal Zafar
- School of Life Sciences, University of Glasgow, Glasgow, United Kingdom
| | - Stella W. Y. Chan
- School of Psychology and Clinical Language Sciences, University of Reading, Reading, United Kingdom
| | - Alex S. F. Kwong
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Stephen M. Lawrie
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Liana Romaniuk
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Heather C. Whalley
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
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4
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Alfeo AL, Zippo AG, Catrambone V, Cimino MGCA, Toschi N, Valenza G. From local counterfactuals to global feature importance: efficient, robust, and model-agnostic explanations for brain connectivity networks. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2023; 236:107550. [PMID: 37086584 DOI: 10.1016/j.cmpb.2023.107550] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 04/14/2023] [Accepted: 04/14/2023] [Indexed: 05/03/2023]
Abstract
BACKGROUND Explainable artificial intelligence (XAI) is a technology that can enhance trust in mental state classifications by providing explanations for the reasoning behind artificial intelligence (AI) models outputs, especially for high-dimensional and highly-correlated brain signals. Feature importance and counterfactual explanations are two common approaches to generate these explanations, but both have drawbacks. While feature importance methods, such as shapley additive explanations (SHAP), can be computationally expensive and sensitive to feature correlation, counterfactual explanations only explain a single outcome instead of the entire model. METHODS To overcome these limitations, we propose a new procedure for computing global feature importance that involves aggregating local counterfactual explanations. This approach is specifically tailored to fMRI signals and is based on the hypothesis that instances close to the decision boundary and their counterfactuals mainly differ in the features identified as most important for the downstream classification task. We refer to this proposed feature importance measure as Boundary Crossing Solo Ratio (BoCSoR), since it quantifies the frequency with which a change in each feature in isolation leads to a change in classification outcome, i.e., the crossing of the model's decision boundary. RESULTS AND CONCLUSIONS Experimental results on synthetic data and real publicly available fMRI data from the Human Connect project show that the proposed BoCSoR measure is more robust to feature correlation and less computationally expensive than state-of-the-art methods. Additionally, it is equally effective in providing an explanation for the behavior of any AI model for brain signals. These properties are crucial for medical decision support systems, where many different features are often extracted from the same physiological measures and a gold standard is absent. Consequently, computing feature importance may become computationally expensive, and there may be a high probability of mutual correlation among features, leading to unreliable results from state-of-the-art XAI methods.
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Affiliation(s)
- Antonio Luca Alfeo
- Department of Information Engineering, University of Pisa, Largo Lucio Lazzarino, 1, Pisa, 56126, Italy; Bioengineering & Robotics Research Center E. Piaggio, University of Pisa, Largo Lucio Lazzarino, 1, Pisa, 56126, Italy.
| | - Antonio G Zippo
- Institute of Neuroscience, Consiglio Nazionale delle Ricerche, Via Raoul Follereau, 3, Vedano al Lambro (MB), 20854, Italy
| | - Vincenzo Catrambone
- Department of Information Engineering, University of Pisa, Largo Lucio Lazzarino, 1, Pisa, 56126, Italy; Bioengineering & Robotics Research Center E. Piaggio, University of Pisa, Largo Lucio Lazzarino, 1, Pisa, 56126, Italy
| | - Mario G C A Cimino
- Department of Information Engineering, University of Pisa, Largo Lucio Lazzarino, 1, Pisa, 56126, Italy; Bioengineering & Robotics Research Center E. Piaggio, University of Pisa, Largo Lucio Lazzarino, 1, Pisa, 56126, Italy
| | - Nicola Toschi
- Department of Biomedicine and Prevention, University of Rome Tor Vergata, Via Montpellier 1, Roma, 00133, Italy
| | - Gaetano Valenza
- Department of Information Engineering, University of Pisa, Largo Lucio Lazzarino, 1, Pisa, 56126, Italy; Bioengineering & Robotics Research Center E. Piaggio, University of Pisa, Largo Lucio Lazzarino, 1, Pisa, 56126, Italy
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5
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Grecucci A, Sorella S, Consolini J. Decoding individual differences in expressing and suppressing anger from structural brain networks: A supervised machine learning approach. Behav Brain Res 2023; 439:114245. [PMID: 36470420 DOI: 10.1016/j.bbr.2022.114245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 11/28/2022] [Accepted: 11/29/2022] [Indexed: 12/12/2022]
Abstract
Anger can be broken down into different elements: a transitory state (state anger), a stable personality feature (trait anger), a tendency to express it (anger-out), or to suppress it (anger-in), and the ability to regulate it (anger control). These elements are characterized by individual differences that vary across a continuum. Among them, the abilities to express and suppress anger are of particular relevance as they determine outcomes and enable successful anger management in daily situations. The aim of this study was to demonstrate that anger suppression and expression can be decoded by patterns of grey matter of specific well-known brain networks. To this aim, a supervised machine learning technique, known as Kernel Ridge Regression, was used to predict anger expression and suppression scores of 212 healthy subjects from the grey matter concentration. Results show that individual differences in anger suppression were predicted by two grey matter patterns associated with the Default-Mode Network and the Salience Network. Additionally, individual differences in anger expression were predicted by a circuit mainly involving subcortical and fronto-temporal regions when considering whole brain grey matter features. These results expand previous findings regarding the neural bases of anger by showing that individual differences in specific anger-related components can be predicted by the grey matter features of specific networks.
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Affiliation(s)
- Alessandro Grecucci
- Clinical and Affective Neuroscience Lab, Cli.A.N. Lab, Department of Psychology and Cognitive Sciences - DiPSCo, University of Trento, Rovereto, Italy; Center for Medical Sciences, CISMed, University of Trento, Trento, Italy.
| | - Sara Sorella
- Clinical and Affective Neuroscience Lab, Cli.A.N. Lab, Department of Psychology and Cognitive Sciences - DiPSCo, University of Trento, Rovereto, Italy.
| | - Jennifer Consolini
- Clinical and Affective Neuroscience Lab, Cli.A.N. Lab, Department of Psychology and Cognitive Sciences - DiPSCo, University of Trento, Rovereto, Italy.
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6
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Grisanzio KA, Flournoy JC, Mair P, Somerville LH. Shifting qualities of negative affective experience through adolescence: Age-related change and associations with functional outcomes. Emotion 2023; 23:278-288. [PMID: 35201792 PMCID: PMC9756137 DOI: 10.1037/emo0001079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
Research shows negative affect increases in healthy adolescents, and this normative change is paralleled by increasing risk for the onset of psychopathology. However, research is limited in characterizing qualitative differences in the type of negative affect experienced beyond the positive-negative valence dimension. In the current study, we establish the relationship between different forms of negative affect and functioning outcomes (i.e., different facets of social functioning and life satisfaction), and examine whether these forms of negative affect are differentially prevalent across late childhood and adolescence. Seven-hundred and 70 participants aged 8-17 years completed self-report measures that assessed a wide range of negative affective experiences. A factor analysis on the negative affect items revealed a four-factor solution that characterized the dimensions of affective experience, with factors reflecting general anxiety, anger, evaluative anxiety, and sadness. Generalized additive model approaches revealed general anxiety increased nonlinearly with age and was associated with decreased reports of emotional support, a facet of social functioning. Anger was associated with increased perceived hostility, perceived rejection, and decreased life satisfaction, and remained stable across the age range. Evaluative anxiety was associated with greater loneliness and increased linearly with increasing age. Sadness was associated with all outcome measures and showed nonlinear changes with age, with notable increases in midadolescence. These results show that subsuming these subtypes of negative affect under a singular concept may obscure meaningful relationships between affect, age, and functioning. Exploring diverse forms of negative affect may help refine theories of emotional development and ultimately inform windows of risk for psychopathology. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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7
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Dugré JR, Potvin S. Clarifying the role of Cortico-Cortical and Amygdalo-Cortical brain dysconnectivity associated with Conduct Problems. Neuroimage Clin 2023; 37:103346. [PMID: 36791489 PMCID: PMC9958059 DOI: 10.1016/j.nicl.2023.103346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2022] [Revised: 01/14/2023] [Accepted: 02/05/2023] [Indexed: 02/10/2023]
Abstract
A recent meta-analysis of resting-state functional connectivity studies revealed that individuals exhibiting antisocial behaviors or conduct problems may show disrupted brain connectivity in networks underpinning socio-affective and attentional processes. However, studies included in the meta-analysis generally rely on small sample sizes and substantially differ in terms of psychometric scales and neuroimaging methodologies. Therefore, we aimed to identify reliable functional brain connectivity alterations associated with severity of conduct problems using a large sample of adolescents and two measures of conduct problems. In a sample of 1416 children and adolescents, mass-univariate analyses of connectivity measures between 333 cortical parcels were conducted to examine the relationship between resting-state functional cortical-cortical connectome and the severity of conduct problems using the Child Behavior Checklist (CBCL) and the Strengths and Difficulties Questionnaire (SDQ). At a liberal threshold, results showed that the functional brain connectivity significantly associated with conduct problems largely differ between the two scales. Indeed, only 21 pairs of brain regions overlapped between the CBCL and SDQ. Permutation feature importance of these 21 brain connectivity measures revealed that connectivity between precentral/postcentral gyri and lateral prefrontal cortex (both ventral and dorsal) were the most important features in explaining variance in conduct problems. The current study highlights that psychometric measures may yield distinct functional connectivity results. Moreover, severity of conduct problems in children and adolescents was mainly associated with deficient functional connectivity of somatomotor and ventral attention networks indicating potential alterations in motor, cognitive and reward processes.
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Affiliation(s)
- Jules R Dugré
- Research Center of the Institut Universitaire en Santé Mentale de Montréal, Montreal, Canada; Department of Psychiatry and Addictology, Faculty of Medicine, University of Montreal, Montreal, Canada.
| | - Stéphane Potvin
- Research Center of the Institut Universitaire en Santé Mentale de Montréal, Montreal, Canada; Department of Psychiatry and Addictology, Faculty of Medicine, University of Montreal, Montreal, Canada.
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8
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Sorella S, Vellani V, Siugzdaite R, Feraco P, Grecucci A. Structural and functional brain networks of individual differences in trait anger and anger control: An unsupervised machine learning study. Eur J Neurosci 2022; 55:510-527. [PMID: 34797003 PMCID: PMC9303475 DOI: 10.1111/ejn.15537] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Revised: 10/25/2021] [Accepted: 11/08/2021] [Indexed: 12/03/2022]
Abstract
The ability to experience, use and eventually control anger is crucial to maintain well-being and build healthy relationships. Despite its relevance, the neural mechanisms behind individual differences in experiencing and controlling anger are poorly understood. To elucidate these points, we employed an unsupervised machine learning approach based on independent component analysis to test the hypothesis that specific functional and structural networks are associated with individual differences in trait anger and anger control. Structural and functional resting state images of 71 subjects as well as their scores from the State-Trait Anger Expression Inventory entered the analyses. At a structural level, the concentration of grey matter in a network including ventromedial temporal areas, posterior cingulate, fusiform gyrus and cerebellum was associated with trait anger. The higher the concentration, the higher the proneness to experience anger in daily life due to the greater tendency to orient attention towards aversive events and interpret them with higher hostility. At a functional level, the activity of the default mode network (DMN) was associated with anger control. The higher the DMN temporal frequency, the stronger the exerted control over anger, thus extending previous evidence on the role of the DMN in regulating cognitive and emotional functions in the domain of anger. Taken together, these results show, for the first time, two specialized brain networks for encoding individual differences in trait anger and anger control.
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Affiliation(s)
- Sara Sorella
- Clinical and Affective Neuroscience Lab, Department of Psychology and Cognitive Sciences (DiPSCo)University of TrentoRoveretoItaly
| | - Valentina Vellani
- Affective Brain Lab, Department of Experimental PsychologyUniversity College LondonLondonUK
| | | | - Paola Feraco
- Department of Experimental, Diagnostic and Specialty Medicine (DIMES)University of BolognaBolognaItaly
| | - Alessandro Grecucci
- Clinical and Affective Neuroscience Lab, Department of Psychology and Cognitive Sciences (DiPSCo)University of TrentoRoveretoItaly,Centre for Medical Sciences (CISMed)University of TrentoTrentoItaly
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9
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Nielsen AN, Wakschlag LS, Norton ES. Linking irritability and functional brain networks: A transdiagnostic case for expanding consideration of development and environment in RDoC. Neurosci Biobehav Rev 2021; 129:231-244. [PMID: 34302863 PMCID: PMC8802626 DOI: 10.1016/j.neubiorev.2021.07.022] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Revised: 07/14/2021] [Accepted: 07/17/2021] [Indexed: 01/13/2023]
Abstract
The National Institute of Mental Health Research Domain Criteria (RDoC) framework promotes the dimensional and transdiagnostic operationalization of psychopathology, but consideration of the neurodevelopmental foundations of mental health problems requires deeper examination. Irritability, the dispositional tendency to angry emotion that has both mood and behavioral elements, is dimensional, transdiagnostic, and observable early in life-a promising target for the identification of early neural indicators or risk factors for psychopathology. Here, we examine functional brain networks linked to irritability from preschool to adulthood and discuss how development and early experience may influence these neural substrates. Functional connectivity measured with fMRI varies according to irritability and indicates the atypical coordination of several functional networks involved in emotion generation, emotion perception, attention, internalization, and cognitive control. We lay out an agenda to improve our understanding and detection of atypical brain:behavior patterns through advances in the characterization of both functional networks and irritability as well as the consideration and operationalization of developmental and early life environmental influences on this pathway.
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Affiliation(s)
- Ashely N Nielsen
- Department of Medical Social Sciences, Northwestern University, Chicago, IL, United States; Institute for Innovations in Developmental Sciences, Northwestern University, Chicago, IL, United States.
| | - Lauren S Wakschlag
- Department of Medical Social Sciences, Northwestern University, Chicago, IL, United States; Institute for Innovations in Developmental Sciences, Northwestern University, Chicago, IL, United States
| | - Elizabeth S Norton
- Institute for Innovations in Developmental Sciences, Northwestern University, Chicago, IL, United States; Department of Communication Sciences and Disorders, Northwestern University, Evanston, IL, United States
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10
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Chester DS, Martelli AM, West SJ, Lasko EN, Brosnan P, Makhanova A, Meltzer AL, McNulty JK. Neural mechanisms of intimate partner aggression. Biol Psychol 2021; 165:108195. [PMID: 34592359 DOI: 10.1016/j.biopsycho.2021.108195] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Revised: 09/24/2021] [Accepted: 09/24/2021] [Indexed: 11/24/2022]
Abstract
People sometimes hurt those they profess to love; yet our understanding of intimate partner aggression (IPA) and its causes remains incomplete. We examined brain activity using functional magnetic resonance imaging (fMRI) in an ethnically and racially diverse sample of 50 female-male, monogamous romantic couples as they completed an aggression task against their intimate partner, a close friend, and a different-sex stranger. Laboratory and real-world IPA were uniquely associated with altered activity within and connectivity between cortical midline structures that subserve social cognition and the computation of value. Men's IPA most corresponded to lower posterior cingulate reactivity during provocation and women's IPA most corresponded to lower ventromedial prefrontal cortex activity during IPA itself. Actor-partner independence modeling suggested women's IPA may correspond to their male partner's neural reactivity to provocation. Broadly, these findings highlight the importance of self-regulatory functions of the medial cortex and away from effortful inhibition subserved by dorsolateral cortices.
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Affiliation(s)
- David S Chester
- Department of Psychology, Virginia Commonwealth University, Richmond, VA 23284, USA.
| | - Alexandra M Martelli
- Department of Psychology, Virginia Commonwealth University, Richmond, VA 23284, USA
| | - Samuel J West
- Department of Psychology, Virginia Commonwealth University, Richmond, VA 23284, USA
| | - Emily N Lasko
- Department of Psychology, Virginia Commonwealth University, Richmond, VA 23284, USA
| | - Phoebe Brosnan
- Department of Psychological & Brain Sciences, Boston University, Boston, MA 02215, USA
| | - Anastasia Makhanova
- Department of Psychological Science, University of Arkansas, Fayetteville, AR 72701, USA
| | - Andrea L Meltzer
- Department of Psychology, Florida State University, Tallahassee, FL 32306, USA
| | - James K McNulty
- Department of Psychology, Florida State University, Tallahassee, FL 32306, USA
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11
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Dugré JR, Potvin S. Impaired attentional and socio-affective networks in subjects with antisocial behaviors: a meta-analysis of resting-state functional connectivity studies. Psychol Med 2021; 51:1249-1259. [PMID: 33902772 DOI: 10.1017/s0033291721001525] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
In the past decade, there has been a growing interest in examining resting-state functional connectivity deficits in subjects with conduct and antisocial personality disorder. Through meta-analyses and literature reviews, extensive work has been done to characterize their abnormalities in brain activation during a wide range of functional magnetic resonance imaging (fMRI) tasks. However, there is currently no meta-analytical evidence regarding neural connectivity patterns during resting-state fMRI. Therefore, we conducted a coordinate-based meta-analysis of resting-state fMRI studies on individuals exhibiting antisocial behaviors. Of the retrieved studies, 18 used a seed-based connectivity approach (513 cases v. 488 controls), 20 employed a non-seed-based approach (453 cases v. 460 controls) and 20 included a correlational analysis between the severity of antisocial behaviors and connectivity patterns (3462 subjects). Meta-analysis on seed-based studies revealed significant connectivity deficits in the amygdala, middle cingulate cortex, ventral posterior cingulate cortex-precuneus, ventromedial and dorsomedial prefrontal cortex, premotor cortex, and superior parietal lobule. Additionally, non-seed-based meta-analysis showed increased connectivity in the ventral posterior cingulate cortex and decreased connectivity in the parietal operculum, calcarine cortex, and cuneus. Finally, we found meta-analytical evidence for negative relationship between the severity of antisocial behaviors and connectivity with the ventromedial prefrontal cortex. Functional characterization and meta-analytical connectivity modeling indicated that these findings overlapped with socio-affective and attentional processes. This further underscores the importance of these functions in the pathophysiology of conduct and antisocial personality disorders.
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Affiliation(s)
- Jules Roger Dugré
- Research Center of the Institut Universitaire en Santé Mentale de Montréal, Montreal, Quebec, Canada
- Department of Psychiatry and Addictology, Faculty of Medicine, University of Montreal, Montreal, Quebec, Canada
| | - Stéphane Potvin
- Research Center of the Institut Universitaire en Santé Mentale de Montréal, Montreal, Quebec, Canada
- Department of Psychiatry and Addictology, Faculty of Medicine, University of Montreal, Montreal, Quebec, Canada
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12
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Devaney KJ, Levin EJ, Tripathi V, Higgins JP, Lazar SW, Somers DC. Attention and Default Mode Network Assessments of Meditation Experience during Active Cognition and Rest. Brain Sci 2021; 11:566. [PMID: 33946661 PMCID: PMC8144977 DOI: 10.3390/brainsci11050566] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 04/23/2021] [Accepted: 04/24/2021] [Indexed: 11/16/2022] Open
Abstract
Meditation experience has previously been shown to improve performance on behavioral assessments of attention, but the neural bases of this improvement are unknown. Two prominent, strongly competing networks exist in the human cortex: a dorsal attention network, that is activated during focused attention, and a default mode network, that is suppressed during attentionally demanding tasks. Prior studies suggest that strong anti-correlations between these networks indicate good brain health. In addition, a third network, a ventral attention network, serves as a "circuit-breaker" that transiently disrupts and redirects focused attention to permit salient stimuli to capture attention. Here, we used functional magnetic resonance imaging to contrast cortical network activation between experienced focused attention Vipassana meditators and matched controls. Participants performed two attention tasks during scanning: a sustained attention task and an attention-capture task. Meditators demonstrated increased magnitude of differential activation in the dorsal attention vs. default mode network in a sustained attention task, relative to controls. In contrast, there were no evident attention network differences between meditators and controls in an attentional reorienting paradigm. A resting state functional connectivity analysis revealed a greater magnitude of anticorrelation between dorsal attention and default mode networks in the meditators as compared to both our local control group and a n = 168 Human Connectome Project dataset. These results demonstrate, with both task- and rest-based fMRI data, increased stability in sustained attention processes without an associated attentional capture cost in meditators. Task and resting-state results, which revealed stronger anticorrelations between dorsal attention and default mode networks in experienced mediators than in controls, are consistent with a brain health benefit of long-term meditation practice.
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Affiliation(s)
- Kathryn J. Devaney
- Department of Neurology, Harvard Medical School, Boston, MA 02115, USA
- Department of Psychological & Brain Sciences, Boston University, Boston, MA 02115, USA; (E.J.L.); (V.T.); (J.P.H.)
| | - Emily J. Levin
- Department of Psychological & Brain Sciences, Boston University, Boston, MA 02115, USA; (E.J.L.); (V.T.); (J.P.H.)
- Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, RI 02903, USA
| | - Vaibhav Tripathi
- Department of Psychological & Brain Sciences, Boston University, Boston, MA 02115, USA; (E.J.L.); (V.T.); (J.P.H.)
| | - James P. Higgins
- Department of Psychological & Brain Sciences, Boston University, Boston, MA 02115, USA; (E.J.L.); (V.T.); (J.P.H.)
- Department of Radiology, Northwestern University, Chicago, IL 60208, USA
| | - Sara W. Lazar
- Department of Radiology, Harvard Medical School, Boston, MA 02115, USA;
| | - David C. Somers
- Department of Psychological & Brain Sciences, Boston University, Boston, MA 02115, USA; (E.J.L.); (V.T.); (J.P.H.)
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