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Carlson JM, Foley J, Fang L. Climate change on the brain: Neural correlates of climate anxiety. J Anxiety Disord 2024; 103:102848. [PMID: 38431988 DOI: 10.1016/j.janxdis.2024.102848] [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: 09/28/2023] [Revised: 02/06/2024] [Accepted: 02/19/2024] [Indexed: 03/05/2024]
Abstract
Climate change is a global crisis impacting individuals' mental health. Climate anxiety is an emerging area of interest within popular culture and the scientific community. Yet, little is known about the mechanisms underlying climate anxiety. We provide evidence that climate anxiety is related to gray matter volume in the midcingulate cortex as well as its level of functional connectivity with the insula cortex. These neuroanatomical and neurofunctional features of climate anxiety are involved in identifying and anticipating potential threats within the environment and preparing an appropriate action response to such threats. These neural correlates align with those observed in anxiety disorders. Yet, climate anxiety itself as well as the neural correlates of climate anxiety were related to pro-environmental behavior. This may suggest that the midcingulate and insula are part of a network linked to an adaptive aspect of climate anxiety in motivating behavioral engagement.
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Affiliation(s)
- Joshua M Carlson
- Department of Psychological Science, Northern Michigan University, Marquette, MI, USA.
| | - John Foley
- Department of Psychological Science, Northern Michigan University, Marquette, MI, USA
| | - Lin Fang
- Department of Psychological Science, Northern Michigan University, Marquette, MI, USA
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Guerra LTL, Rocha JM, Osório FDL, Bouso JC, Hallak JEC, Dos Santos RG. Biases in affective attention tasks in posttraumatic stress disorder patients: A systematic review of neuroimaging studies. Biol Psychol 2023; 183:108660. [PMID: 37597766 DOI: 10.1016/j.biopsycho.2023.108660] [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: 06/15/2023] [Revised: 07/24/2023] [Accepted: 08/16/2023] [Indexed: 08/21/2023]
Abstract
INTRODUCTION Posttraumatic stress disorder (PTSD) is characterized by alterations in emotional and cognitive processing. The current neurobiological model of PTSD posits that amygdala and prefrontal cortex functioning impairment underpins symptoms, such as altered emotional and cognitive processing. Additionally, these structures are key components of emotional and attention regulation. AIM This review sought to evaluate studies comparing PTSD group to non-PTSD controls performance in affective attention tasks during neuroimaging. RESULTS PTSD group behavioral performance when responding to affective stimuli differed from controls only in stroop-based tasks. However, neuroimaging techniques were able to identify brain activation differences even when behavioral differences were not present. Amygdala hyperactivation in PTSD patients was confirmed in most cases, but cortical networks results were not as consistent. More than a general reduction in activity, PTSD group data points out to impaired recruitment of ventral cortical structures and increased reliance on dorsal cortical structures during task performance. CONCLUSION Stroop-based tasks seem to be better at identifying differences in behavioral performance of PTSD individuals. PTSD individuals seems to present an altered brain activation pattern in affective attention tasks when compared to controls, where PTSD individuals seem to present enhanced amygdala activation and rely more on dorsal anterior cingulate cortex and posterior insula activation during tasks. The PROSPERO ID for this study is CRD42022355471.
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Affiliation(s)
- Lorena T L Guerra
- Department of Neurosciences and Behavior, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil.
| | - Juliana M Rocha
- Department of Neurosciences and Behavior, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil.
| | - Flávia de L Osório
- Department of Neurosciences and Behavior, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil; National Institute of Science and Technology Translational Medicine, Brazil.
| | - José C Bouso
- Department of Neurosciences and Behavior, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil; ICEERS Foundation, International Center for Ethnobotanical Education, Research and Services, Barcelona, Spain; Medical Anthopology Research Center, Universitat Rovira i Virgili, Tarragona, Spain.
| | - Jaime E C Hallak
- Department of Neurosciences and Behavior, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil; National Institute of Science and Technology Translational Medicine, Brazil; ICEERS Foundation, International Center for Ethnobotanical Education, Research and Services, Barcelona, Spain.
| | - Rafael G Dos Santos
- Department of Neurosciences and Behavior, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil; National Institute of Science and Technology Translational Medicine, Brazil; ICEERS Foundation, International Center for Ethnobotanical Education, Research and Services, Barcelona, Spain.
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Abado E, Okon-Singer H, Aue T. Neurophysiological mechanisms underlying cognitive biases to emotional information: Latest developments and new directions. Biol Psychol 2023; 177:108486. [PMID: 36626959 DOI: 10.1016/j.biopsycho.2023.108486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Accepted: 01/05/2023] [Indexed: 01/09/2023]
Affiliation(s)
- Elinor Abado
- School of Psychological Sciences, University of Haifa, Haifa, Israel; The Integrated Brain and Behavior Research Center (IBBRC), University of Haifa, Haifa, Israel.
| | - Hadas Okon-Singer
- School of Psychological Sciences, University of Haifa, Haifa, Israel; The Integrated Brain and Behavior Research Center (IBBRC), University of Haifa, Haifa, Israel
| | - Tatjana Aue
- Institute of Psychology, University of Bern, Bern, Switzerland
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Fang L, Andrzejewski JA, Carlson JM. The gray matter morphology associated with the electrophysiological response to errors in individuals with high trait anxiety. Int J Psychophysiol 2023; 184:76-83. [PMID: 36581044 PMCID: PMC10125723 DOI: 10.1016/j.ijpsycho.2022.12.007] [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] [Received: 08/18/2022] [Revised: 12/19/2022] [Accepted: 12/21/2022] [Indexed: 12/28/2022]
Abstract
Enhanced error monitoring has been associated with higher levels of anxiety. This has been consistently demonstrated in its most reliable electrophysiological index, the error-related negativity (ERN), such that increased ERN is related with elevated anxiety symptomology. However, it is still unclear whether the structural properties of the brain are associated with individual differences in ERN amplitude. Moreover, the relationship between ERN and anxiety has recently been suggested to be moderated by sex, but the degree to which sex moderates the association between brain structure and ERN amplitude is unknown. The present study investigated the association between gray matter volume (GMV) and ERN amplitude in individuals with high trait anxiety (N = 98) as well as the role of sex in moderating this association. The ERN was elicited from a flanker task, whereas structural MRI images were obtained from whole brain structural T1-weighted MRI scans. The results of voxel-based morphometry analyses showed that the relationship between ERN difference scores and GMV was moderated by sex in the dorsal anterior cingulate cortex (dACC). This sex difference was derived from a negative correlation between ERN difference scores and dACC GMV in females and a positive correlation in males. Our findings are in accordance with the critical role of the dACC serving as a neural substrate of error monitoring. It also provides further evidence for sex-specific associations with brain structures related to error monitoring.
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Affiliation(s)
- Lin Fang
- Department of Psychological Science, Northern Michigan University, Marquette, MI, USA.
| | - Jeremy A Andrzejewski
- Department of Psychological Science, Northern Michigan University, Marquette, MI, USA
| | - Joshua M Carlson
- Department of Psychological Science, Northern Michigan University, Marquette, MI, USA
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Baggio T, Grecucci A, Meconi F, Messina I. Anxious Brains: A Combined Data Fusion Machine Learning Approach to Predict Trait Anxiety from Morphometric Features. SENSORS (BASEL, SWITZERLAND) 2023; 23:610. [PMID: 36679404 PMCID: PMC9863274 DOI: 10.3390/s23020610] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 12/30/2022] [Accepted: 01/01/2023] [Indexed: 06/17/2023]
Abstract
Trait anxiety relates to the steady propensity to experience and report negative emotions and thoughts such as fear and worries across different situations, along with a stable perception of the environment as characterized by threatening stimuli. Previous studies have tried to investigate neuroanatomical features related to anxiety mostly using univariate analyses and thus giving rise to contrasting results. The aim of this study is to build a predictive model of individual differences in trait anxiety from brain morphometric features, by taking advantage of a combined data fusion machine learning approach to allow generalization to new cases. Additionally, we aimed to perform a network analysis to test the hypothesis that anxiety-related networks have a central role in modulating other networks not strictly associated with anxiety. Finally, we wanted to test the hypothesis that trait anxiety was associated with specific cognitive emotion regulation strategies, and whether anxiety may decrease with ageing. Structural brain images of 158 participants were first decomposed into independent covarying gray and white matter networks with a data fusion unsupervised machine learning approach (Parallel ICA). Then, supervised machine learning (decision tree) and backward regression were used to extract and test the generalizability of a predictive model of trait anxiety. Two covarying gray and white matter independent networks successfully predicted trait anxiety. The first network included mainly parietal and temporal regions such as the postcentral gyrus, the precuneus, and the middle and superior temporal gyrus, while the second network included frontal and parietal regions such as the superior and middle temporal gyrus, the anterior cingulate, and the precuneus. We also found that trait anxiety was positively associated with catastrophizing, rumination, other- and self-blame, and negatively associated with positive refocusing and reappraisal. Moreover, trait anxiety was negatively associated with age. This paper provides new insights regarding the prediction of individual differences in trait anxiety from brain and psychological features and can pave the way for future diagnostic predictive models of anxiety.
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Affiliation(s)
- Teresa Baggio
- Clinical and Affective Neuroscience Lab (CLI.A.N. Lab), Department of Psychology and Cognitive Sciences (DiPSCo), University of Trento, 38068 Rovereto, Italy
| | - Alessandro Grecucci
- Clinical and Affective Neuroscience Lab (CLI.A.N. Lab), Department of Psychology and Cognitive Sciences (DiPSCo), University of Trento, 38068 Rovereto, Italy
- Centre for Medical Sciences, CISMed, University of Trento, 38122 Trento, Italy
| | - Federica Meconi
- Clinical and Affective Neuroscience Lab (CLI.A.N. Lab), Department of Psychology and Cognitive Sciences (DiPSCo), University of Trento, 38068 Rovereto, Italy
| | - Irene Messina
- Clinical and Affective Neuroscience Lab (CLI.A.N. Lab), Department of Psychology and Cognitive Sciences (DiPSCo), University of Trento, 38068 Rovereto, Italy
- Department of Economics, Universitas Mercatorum, 00186 Rome, Italy
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Aday JS, Fang L, Carlson JM. Eye-size effects in the dot-probe task: Greater sclera exposure predicts delayed disengagement from fearful faces. PLoS One 2023; 18:e0285839. [PMID: 37195990 DOI: 10.1371/journal.pone.0285839] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Accepted: 05/03/2023] [Indexed: 05/19/2023] Open
Abstract
Fearful facial expressions are nonverbal and biologically salient signals of potential threat that automatically hold, capture, and direct observers' attention. They are characterized by enlarged eye whites and dilated pupils, and fearful eyes alone are sufficient to capture attention. The morphological properties of the eye region, such as sclera exposure, are thought to play an important role in nonverbal communication. Specifically, increased sclera exposure associated with fearful expressions has been shown to moderate how observers' shift their attention toward the direction of another's gaze. Yet, the extent to which variability in sclera exposure possibly impacts the capture and hold of attention by fearful faces is untested. To address this, a sample of 249 adults completed a dot-probe task of selective attention with fearful and neutral faces. The results suggested that (1) fearful faces were prioritized over neutral faces (i.e., they captured and held attention), (2) greater sclera exposure at target locations facilitated reaction times, and (3) attention was held by greater sclera exposure of fearful faces at task irrelevant locations resulting in delayed disengagement. Collectively, the results indicate that fearful facial expressions and sclera exposure modulate spatial attention through independent and interactive mechanisms. Sclera exposure appears to be an important facilitator of nonverbal communication and perhaps represents an understudied variable in social cognition more broadly.
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Affiliation(s)
- Jacob S Aday
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, California, United States of America
| | - Lin Fang
- Department of Psychological Science, Northern Michigan University, Marquette, Michigan, United States of America
| | - Joshua M Carlson
- Department of Psychological Science, Northern Michigan University, Marquette, Michigan, United States of America
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Zhao J, Zhou Z, Lin Z, Sun B, Wu X, Fu S. The Role of Attentional Bias Toward Negative Emotional Information and Social Anxiety in Problematic Social Media Use. J Psychosoc Nurs Ment Health Serv 2022:1-10. [DOI: 10.3928/02793695-20221122-02] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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The questionable validity of attention bias variability: Evidence from two conceptually unrelated cognitive tasks. JOURNAL OF AFFECTIVE DISORDERS REPORTS 2022; 10:100411. [PMID: 36684713 PMCID: PMC9851093 DOI: 10.1016/j.jadr.2022.100411] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023] Open
Abstract
Background Attention bias variability is thought to measure fluctuations in attention towards and away from threat-related information and is elevated in affective disorders. However, recent evidence suggests that attention bias variability may quantify general reaction time variability rather than attention bias behavior per se. Methods The current study calculated "attention bias variability" from two conceptually unrelated cognitive tasks: the dot-probe task (measuring attentional bias) and the arrow flanker task (measuring cognitive control). Results Attention bias variability measures were correlated across these unrelated tasks. Yet, when general reaction time variability was controlled, attention bias variability across tasks was no longer correlated. In addition, the reliability of attention bias variability measures decreased when controlling for general reaction time variability. Finally, although attention bias variability calculated from the dot-probe task initially correlated with anxious symptoms, this association was no longer significant when controlling for general reaction time variability. Limitations Our sample was comprised of high trait anxious individuals. Replication in clinical samples is warranted. Conclusions These findings collectively provide strong empirical evidence that attention bias variability is not a valid measure of attention-related behavior, but reflective of general reaction time variability more broadly.
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