151
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The Impact of Focused Attention on Emotional Experience: A Functional MRI Investigation. COGNITIVE AFFECTIVE & BEHAVIORAL NEUROSCIENCE 2020; 20:1011-1026. [PMID: 32770316 DOI: 10.3758/s13415-020-00816-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Emotional well-being depends on the ability to adaptively cope with various emotional challenges. Most studies have investigated the neural mechanisms of emotion regulation strategies deployed relatively later in the timing of processing that leads to full emotional experiences. However, less is known about strategies that are engaged in earlier stages of emotion processing, such as those involving attentional deployment. We investigated the neural mechanisms associated with self-guided Focused Attention (FA) in mitigating subjective negative emotional experiences. Functional magnetic resonance imaging (fMRI) data were recorded while participants viewed a series of composite negative and neutral images with distinguishable foreground (FG) and background (BG) areas. Participants were instructed to focus either on the FG or BG components of the images, and then rated their emotional experiences. Behavioral results showed that FA was successful in decreasing emotional ratings for negative images viewed in BG Focus condition. At the neural level, the BG Focus was associated with increased activity in regions typically implicated in top-down executive control (dorsolateral prefrontal cortex and lateral parietal cortex) and decreased activity in regions linked to affective processing (amygdala and ventrolateral prefrontal cortex). Dissociable brain activity linked to FA also was identified in visual cortices, including between the parahippocampal and fusiform gyri, showing increased versus decreased activity, respectively, during the BG Focus. These findings complement the evidence from prior FA studies with recollected emotional memories as internal stimuli and further demonstrate the effectiveness of self-guided FA in mitigating negative emotional experiences associated with processing of external unpleasant stimuli.
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152
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Cwik JC, Vahle N, Woud ML, Potthoff D, Kessler H, Sartory G, Seitz RJ. Reduced gray matter volume in the left prefrontal, occipital, and temporal regions as predictors for posttraumatic stress disorder: a voxel-based morphometric study. Eur Arch Psychiatry Clin Neurosci 2020; 270:577-588. [PMID: 30937515 DOI: 10.1007/s00406-019-01011-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2018] [Accepted: 03/26/2019] [Indexed: 02/07/2023]
Abstract
The concept of acute stress disorder (ASD) was introduced as a diagnostic entity to improve the identification of traumatized people who are likely to develop posttraumatic stress disorder (PTSD). Neuroanatomical models suggest that changes in the prefrontal cortex, amygdala, and hippocampus play a role in the development of PTSD. Using voxel-based morphometry, this study aimed to investigate the predictive power of gray matter volume (GMV) alterations for developing PTSD. The GMVs of ASD patients (n = 21) were compared to those of PTSD patients (n = 17) and healthy controls (n = 18) in whole-brain and region-of-interest analyses. The GMV alterations seen in ASD patients shortly after the traumatic event (T1) were also correlated with PTSD symptom severity and symptom clusters 4 weeks later (T2). Compared with healthy controls, the ASD patients had significantly reduced GMV in the left visual cortex shortly after the traumatic event (T1) and in the left occipital and prefrontal regions 4 weeks later (T2); no significant differences in GMV were seen between the ASD and PTSD patients. Furthermore, a significant negative association was found between the GMV reduction in the left lateral temporal regions seen after the traumatic event (T1) and PTSD hyperarousal symptoms 4 weeks later (T2). Neither amygdala nor hippocampus alterations were predictive for the development of PTSD. These data suggest that gray matter deficiencies in the left hemispheric occipital and temporal regions in ASD patients may predict a liability for developing PTSD.
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Affiliation(s)
- Jan Christopher Cwik
- Department of Clinical Psychology and Psychotherapy, Faculty of Human Sciences, Universität zu Köln, Pohligstr. 1, 50969, Cologne, Germany. .,Faculty of Psychology, Mental Health Research and Treatment Center, Ruhr-Universität Bochum, Bochum, Germany.
| | - Nils Vahle
- Department of Psychology and Psychotherapy, University Witten/Herdecke, Witten, Germany
| | - Marcella Lydia Woud
- Faculty of Psychology, Mental Health Research and Treatment Center, Ruhr-Universität Bochum, Bochum, Germany
| | - Denise Potthoff
- Department of Neurology, Center for Neurology and Neuropsychiatry, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany
| | - Henrik Kessler
- Department of Psychosomatic Medicine and Psychotherapy, LWL University Hospital, Ruhr-Universität Bochum, Bochum, Germany
| | - Gudrun Sartory
- Department of Clinical Psychology and Psychotherapy, School of Human and Social Sciences, Bergische Universität Wuppertal, Wuppertal, Germany
| | - Rüdiger J Seitz
- Department of Neurology, Center for Neurology and Neuropsychiatry, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany
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153
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Demidenko MI, Huntley ED, Jahn A, Thomason ME, Monk CS, Keating DP. Cortical and subcortical response to the anticipation of reward in high and average/low risk-taking adolescents. Dev Cogn Neurosci 2020; 44:100798. [PMID: 32479377 PMCID: PMC7262007 DOI: 10.1016/j.dcn.2020.100798] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2020] [Revised: 05/05/2020] [Accepted: 05/15/2020] [Indexed: 12/28/2022] Open
Abstract
Since the first neurodevelopmental models that sought to explain the influx of risky behaviors during adolescence were proposed, there have been a number of revisions, variations and criticisms. Despite providing a strong multi-disciplinary heuristic to explain the development of risk behavior, extant models have not yet reliably isolated neural systems that underlie risk behaviors in adolescence. To address this gap, we screened 2017 adolescents from an ongoing longitudinal study that assessed 15-health risk behaviors, targeting 104 adolescents (Age Range: 17-to-21.4), characterized as high-or-average/low risk-taking. Participants completed the Monetary Incentive Delay (MID) fMRI task, examining reward anticipation to "big win" versus "neutral". We examined neural response variation associated with both baseline and longitudinal (multi-wave) risk classifications. Analyses included examination of a priori regions of interest (ROIs); and exploratory non-parametric, whole-brain analyses. Hypothesis-driven ROI analysis revealed no significant differences between high- and average/low-risk profiles using either baseline or multi-wave classification. Results of whole-brain analyses differed according to whether risk assessment was based on baseline or multi-wave data. Despite significant mean-level task activation, these results do not generalize prior neural substrates implicated in reward anticipation and adolescent risk-taking. Further, these data indicate that whole-brain differences may depend on how risk-behavior profiles are defined.
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Affiliation(s)
| | - Edward D Huntley
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, United States
| | - Andrew Jahn
- The Functional MRI Laboratory, University of Michigan, Ann Arbor, United States
| | - Moriah E Thomason
- Department of Child and Adolescent Psychiatry, New York University Langone, New York, United States
| | - Christopher S Monk
- Department of Psychology, University of Michigan, Ann Arbor, United States; Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, United States
| | - Daniel P Keating
- Department of Psychology, University of Michigan, Ann Arbor, United States; Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, United States
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154
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Wilkey ED, Conrad BN, Yeo DJ, Price GR. Shared Numerosity Representations Across Formats and Tasks Revealed with 7 Tesla fMRI: Decoding, Generalization, and Individual Differences in Behavior. Cereb Cortex Commun 2020; 1:tgaa038. [PMID: 34296107 PMCID: PMC8153058 DOI: 10.1093/texcom/tgaa038] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 06/19/2020] [Accepted: 07/22/2020] [Indexed: 01/28/2023] Open
Abstract
Debate continues on whether encoding of symbolic number is grounded in nonsymbolic numerical magnitudes. Nevertheless, fluency of perceiving both number formats, and translating between them, predicts math skills across the life span. Therefore, this study asked if numbers share cortical activation patterns across formats and tasks, and whether neural response to number predicts math-related behaviors. We analyzed patterns of neural activation using 7 Tesla functional magnetic resonance imaging in a sample of 39 healthy adults. Discrimination was successful between numerosities 2, 4, 6, and 8 dots and generalized to activation patterns of the same numerosities represented as Arabic digits in the bilateral parietal lobes and left inferior frontal gyrus (IFG) (and vice versa). This indicates that numerosity-specific neural resources are shared between formats. Generalization was also successful across tasks where participants either identified or compared numerosities in bilateral parietal lobes and IFG. Individual differences in decoding did not relate to performance on a number comparison task completed outside of the scanner, but generalization between formats and across tasks negatively related to math achievement in the parietal lobes. Together, these findings suggest that individual differences in representational specificity within format and task contexts relate to mathematical expertise.
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Affiliation(s)
- Eric D Wilkey
- Brain and Mind Institute, Western University, London, Ontario N6A5B7, Canada
| | - Benjamin N Conrad
- Department of Psychology and Human Development, Peabody College, Vanderbilt University, Nashville, TN 37203, USA
| | - Darren J Yeo
- Department of Psychology and Human Development, Peabody College, Vanderbilt University, Nashville, TN 37203, USA
- Division of Psychology, School of Social Sciences, Nanyang Technological University, 639818, Singapore
| | - Gavin R Price
- Department of Psychology and Human Development, Peabody College, Vanderbilt University, Nashville, TN 37203, USA
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155
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Szucs D, Ioannidis JP. Sample size evolution in neuroimaging research: An evaluation of highly-cited studies (1990-2012) and of latest practices (2017-2018) in high-impact journals. Neuroimage 2020; 221:117164. [PMID: 32679253 DOI: 10.1016/j.neuroimage.2020.117164] [Citation(s) in RCA: 193] [Impact Index Per Article: 48.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2019] [Revised: 07/07/2020] [Accepted: 07/09/2020] [Indexed: 11/18/2022] Open
Abstract
We evaluated 1038 of the most cited structural and functional (fMRI) magnetic resonance brain imaging papers (1161 studies) published during 1990-2012 and 270 papers (300 studies) published in top neuroimaging journals in 2017 and 2018. 96% of highly cited experimental fMRI studies had a single group of participants and these studies had median sample size of 12, highly cited clinical fMRI studies (with patient participants) had median sample size of 14.5, and clinical structural MRI studies had median sample size of 50. The sample size of highly cited experimental fMRI studies increased at a rate of 0.74 participant/year and this rate of increase was commensurate with the median sample sizes of neuroimaging studies published in top neuroimaging journals in 2017 (23 participants) and 2018 (24 participants). Only 4 of 131 papers in 2017 and 5 of 142 papers in 2018 had pre-study power calculations, most for single t-tests and correlations. Only 14% of highly cited papers reported the number of excluded participants whereas 49% of papers with their own data in 2017 and 2018 reported excluded participants. Publishers and funders should require pre-study power calculations necessitating the specification of effect sizes. The field should agree on universally required reporting standards. Reporting formats should be standardized so that crucial study parameters could be identified unequivocally.
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Affiliation(s)
- Denes Szucs
- University of Cambridge, Department of Psychology, UK.
| | - John Pa Ioannidis
- Meta-Research Innovation Center at Stanford (METRICS) and Department of Medicine, Department of Epidemiology and Population Health, Department of Biomedical Data Sciences, And Department of Statistics, Stanford University, Stanford, CA, USA
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156
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Morphofunctional Alterations of the Hypothalamus and Social Behavior in Autism Spectrum Disorders. Brain Sci 2020; 10:brainsci10070435. [PMID: 32650534 PMCID: PMC7408098 DOI: 10.3390/brainsci10070435] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Revised: 06/21/2020] [Accepted: 07/03/2020] [Indexed: 12/15/2022] Open
Abstract
An accumulating body of evidence indicates a tight relationship between the endocrine system and abnormal social behavior. Two evolutionarily conserved hypothalamic peptides, oxytocin and arginine-vasopressin, because of their extensively documented function in supporting and regulating affiliative and socio-emotional responses, have attracted great interest for their critical implications for autism spectrum disorders (ASD). A large number of controlled trials demonstrated that exogenous oxytocin or arginine-vasopressin administration can mitigate social behavior impairment in ASD. Furthermore, there exists long-standing evidence of severe socioemotional dysfunctions after hypothalamic lesions in animals and humans. However, despite the major role of the hypothalamus for the synthesis and release of oxytocin and vasopressin, and the evident hypothalamic implication in affiliative behavior in animals and humans, a rather small number of neuroimaging studies showed an association between this region and socioemotional responses in ASD. This review aims to provide a critical synthesis of evidences linking alterations of the hypothalamus with impaired social cognition and behavior in ASD by integrating results of both anatomical and functional studies in individuals with ASD as well as in healthy carriers of oxytocin receptor (OXTR) genetic risk variant for ASD. Current findings, although limited, indicate that morphofunctional anomalies are implicated in the pathophysiology of ASD and call for further investigations aiming to elucidate anatomical and functional properties of hypothalamic nuclei underlying atypical socioemotional behavior in ASD.
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157
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Borowiak K, von Kriegstein K. Intranasal oxytocin modulates brain responses to voice-identity recognition in typically developing individuals, but not in ASD. Transl Psychiatry 2020; 10:221. [PMID: 32636360 PMCID: PMC7341857 DOI: 10.1038/s41398-020-00903-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2019] [Revised: 06/05/2020] [Accepted: 06/08/2020] [Indexed: 11/09/2022] Open
Abstract
Faces and voices are prominent cues for person-identity recognition. Face recognition behavior and associated brain responses can be enhanced by intranasal administration of oxytocin. It is unknown whether oxytocin can also augment voice-identity recognition mechanisms. To find it out is particularly relevant for individuals who have difficulties recognizing voice identity such as individuals diagnosed with autism spectrum disorder (ASD). We conducted a combined behavioral and functional magnetic resonance imaging (fMRI) study to investigate voice-identity recognition following intranasal administration of oxytocin or placebo in a group of adults diagnosed with ASD (full-scale intelligence quotient > 85) and pairwise-matched typically developing (TD) controls. A single dose of 24 IU oxytocin was administered in a randomized, double-blind, placebo-controlled and cross-over design. In the control group, but not in the ASD group, administration of oxytocin compared to placebo increased responses to recognition of voice identity in contrast to speech in the right posterior superior temporal sulcus/gyrus (pSTS/G) - a region implicated in the perceptual analysis of voice-identity information. In the ASD group, the right pSTS/G responses were positively correlated with voice-identity recognition accuracy in the oxytocin condition, but not in the placebo condition. Oxytocin did not improve voice-identity recognition performance at the group level. The ASD compared to the control group had lower right pSTS/G responses to voice-identity recognition. Since ASD is known to have atypical pSTS/G, the results indicate that the potential of intranasal oxytocin to enhance mechanisms for voice-identity recognition might be variable and dependent on the functional integrity of this brain region.
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Affiliation(s)
- Kamila Borowiak
- Technische Universität Dresden, Bamberger Straße 7, 01187, Dresden, Germany.
- Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103, Leipzig, Germany.
- Berlin School of Mind and Brain, Humboldt University of Berlin, Luisenstraße 56, 10117, Berlin, Germany.
| | - Katharina von Kriegstein
- Technische Universität Dresden, Bamberger Straße 7, 01187, Dresden, Germany
- Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103, Leipzig, Germany
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158
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Sousa H, Almeida S, Bessa J, Pereira MG. The Developmental Trajectory of Cancer-Related Cognitive Impairment in Breast Cancer Patients: A Systematic Review of Longitudinal Neuroimaging Studies. Neuropsychol Rev 2020; 30:287-309. [PMID: 32607817 DOI: 10.1007/s11065-020-09441-9] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2019] [Accepted: 05/12/2020] [Indexed: 01/21/2023]
Abstract
This systematic review explored the neurobiological mechanisms underlying the clinical time course of cancer-related cognitive impairment (CRCI) in breast cancer patients through the review of longitudinal neuroimaging studies. Before chemotherapy, results reported no evidence for neuropsychological, structural (gray matter) and brain perfusion changes. However, functional brain alterations were evident and revealed a frontoparietal hyperactivation during working memory tasks. Fatigue and number of days since surgery were the two suggested confounding factors. Acutely after chemotherapy, this review found no evidence for neuropsychological changes while suggesting a pattern of frontal structural, perfusion and functional brain abnormalities. These findings seemed to be dependent on age, menopausal status at baseline, and fMRI task performed. Years after chemotherapy, results revealed evidence of partial neuropsychological, structural, and functional brain recovery. Regarding brain abnormality, this review suggested that it may begin quite early in the disease course, be more prominent shortly after chemotherapy and partially recover over time. Several hypotheses underlying these changes were discussed. The present review also provided important information for developing a time-specific treatment and prevention strategies and for the consideration of functional neuroimaging as a relevant tool for CRCI diagnosis, clinical monitoring, and intervention studies. The findings also suggested the need to implement studies with longitudinal designs, including a pre-treatment assessment, since cross-sectional studies were not able to detect this pattern of recovery over time, supporting only the theory of brain abnormalities, in breast cancer survivors.
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Affiliation(s)
- Helena Sousa
- Family Health & Illness Research Group, School of Psychology, University of Minho, Campus de Gualtar, 4710-057, Braga, Portugal
- Research Center in Psychology (CIPsi), School of Psychology, University of Minho, Campus de Gualtar, 4710-057, Braga, Portugal
| | - Susana Almeida
- Research Center in Psychology (CIPsi), School of Psychology, University of Minho, Campus de Gualtar, 4710-057, Braga, Portugal
- Psycho-Oncology Service, Portuguese Institute of Oncology, Porto, Portugal; Cuf Hospital, Porto; Faculty of Medicine, University of Porto, Braga, Portugal
| | - João Bessa
- Research Center in Psychology (CIPsi), School of Psychology, University of Minho, Campus de Gualtar, 4710-057, Braga, Portugal
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal
- ICVS/3B's - PT Government Associate Laboratory, Guimarães, Braga, Portugal
| | - M Graça Pereira
- Family Health & Illness Research Group, School of Psychology, University of Minho, Campus de Gualtar, 4710-057, Braga, Portugal.
- Research Center in Psychology (CIPsi), School of Psychology, University of Minho, Campus de Gualtar, 4710-057, Braga, Portugal.
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159
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Keysers C, Gazzola V, Wagenmakers EJ. Using Bayes factor hypothesis testing in neuroscience to establish evidence of absence. Nat Neurosci 2020; 23:788-799. [PMID: 32601411 PMCID: PMC7610527 DOI: 10.1038/s41593-020-0660-4] [Citation(s) in RCA: 296] [Impact Index Per Article: 74.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Accepted: 05/21/2020] [Indexed: 11/09/2022]
Abstract
Most neuroscientists would agree that for brain research to progress, we have to know which experimental manipulations have no effect as much as we must identify those that do have an effect. The dominant statistical approaches used in neuroscience rely on P values and can establish the latter but not the former. This makes non-significant findings difficult to interpret: do they support the null hypothesis or are they simply not informative? Here we show how Bayesian hypothesis testing can be used in neuroscience studies to establish both whether there is evidence of absence and whether there is absence of evidence. Through simple tutorial-style examples of Bayesian t-tests and ANOVA using the open-source project JASP, this article aims to empower neuroscientists to use this approach to provide compelling and rigorous evidence for the absence of an effect.
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Affiliation(s)
- Christian Keysers
- Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands.
- Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands.
| | - Valeria Gazzola
- Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands
- Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands
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160
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Weber S, Hausmann M, Kane P, Weis S. The relationship between language ability and brain activity across language processes and modalities. Neuropsychologia 2020; 146:107536. [PMID: 32590019 DOI: 10.1016/j.neuropsychologia.2020.107536] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2019] [Revised: 03/03/2020] [Accepted: 06/12/2020] [Indexed: 01/22/2023]
Abstract
Existing neuroimaging studies on the relationship between language ability and brain activity have found contradictory evidence: On the one hand, increased activity with higher language ability has been interpreted as deeper or more adaptive language processing. On the other hand, decreased activity with higher language ability has been interpreted as more efficient language processing. In contrast to previous studies, the current study investigated the relationship between language ability and neural activity across different language processes and modalities while keeping non-linguistic cognitive task demands to a minimum. fMRI data were collected from 22 healthy adults performing a sentence listening task, a sentence reading task and a phonological production task. Outside the MRI scanner, language ability was assessed with the verbal scale of the Wechsler Abbreviated Scale of Intelligence (WASI-II) and a verbal fluency task. As expected, sentence comprehension activated the left anterior temporal lobe while phonological processing activated the left inferior frontal gyrus. Higher language ability was associated with increased activity in the left temporal lobe during auditory sentence processing and with increased activity in the left frontal lobe during phonological processing, reflected in both, higher intensity and greater extent of activations. Evidence for decreased activity with higher language ability was less consistent and restricted to verbal fluency. Together, the results predominantly support the hypothesis of deeper language processing in individuals with higher language ability. The consistency of results across language processes, modalities, and brain regions suggests a general positive link between language abilities and brain activity within the core language network. However, a negative relationship seems to exist for non-linguistic cognitive functions located outside the language network.
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Affiliation(s)
- Sarah Weber
- Department of Psychology, Durham University, UK; Department of Biological and Medical Psychology, University of Bergen, Norway.
| | | | | | - Susanne Weis
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
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161
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Wang S, Zhao Y, Li J, Lai H, Qiu C, Pan N, Gong Q. Neurostructural correlates of hope: dispositional hope mediates the impact of the SMA gray matter volume on subjective well-being in late adolescence. Soc Cogn Affect Neurosci 2020; 15:395-404. [PMID: 32378710 PMCID: PMC7308655 DOI: 10.1093/scan/nsaa046] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Revised: 02/26/2020] [Accepted: 03/27/2020] [Indexed: 02/05/2023] Open
Abstract
There has been increasing interest in identifying factors to predict subjective well-being in the emerging field of positive psychology over the past two decades. Dispositional hope, which reflects one's goal-directed tendencies, including both pathway thinking (planning to meet goals) and agency thinking (goal-directed determination), has emerged as a stable predictor for subjective well-being. However, the neurobiological substrates of dispositional hope and the brain-hope mechanism for predicting subjective well-being remain unclear. Here, we examined these issues in 231 high school graduates within the same grade by estimating cortical gray matter volume (GMV) utilizing a voxel-based morphometry method based on structural magnetic resonance imaging. Whole-brain regression analyses and prediction analyses showed that higher dispositional hope was stably associated with greater GMV in the left supplementary motor area (SMA). Furthermore, mediation analyses revealed that dispositional hope mediated the relation between left SMA volume and subjective well-being. Critically, our results were obtained after adjusting for age, sex, family socioeconomic status and total GMV. Altogether, our study presents novel evidence for the neuroanatomical basis of dispositional hope and suggests an underlying indirect effect of dispositional hope on the link between brain gray matter structure and subjective well-being.
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Affiliation(s)
- Song Wang
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
- Psychoradiology Research Unit of Chinese Academy of Medical Sciences (2018RU011), the Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu 610041, China
- Department of Psychoradiology, Chengdu Mental Health Center, Chengdu 610036, China
| | - Yajun Zhao
- School of Sociology and Psychology, Southwest Minzu University, Chengdu 610041, China
| | - Jingguang Li
- College of Teacher Education, Dali University, Dali 671003, China
| | - Han Lai
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
- Psychoradiology Research Unit of Chinese Academy of Medical Sciences (2018RU011), the Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Chen Qiu
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
- Department of Psychology, The Faculty of Social Science, The University of Hong Kong, Pokfulam 999077, Hong Kong
| | - Nanfang Pan
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
- Psychoradiology Research Unit of Chinese Academy of Medical Sciences (2018RU011), the Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Qiyong Gong
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
- Psychoradiology Research Unit of Chinese Academy of Medical Sciences (2018RU011), the Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu 610041, China
- Department of Psychoradiology, Chengdu Mental Health Center, Chengdu 610036, China
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162
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Hoogeveen S, Snoek L, van Elk M. Religious belief and cognitive conflict sensitivity: A preregistered fMRI study. Cortex 2020; 129:247-265. [PMID: 32535377 DOI: 10.1016/j.cortex.2020.04.011] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Revised: 03/23/2020] [Accepted: 04/03/2020] [Indexed: 12/16/2022]
Abstract
In the current preregistered fMRI study, we investigated the relationship between religiosity and behavioral and neural mechanisms of conflict processing, as a conceptual replication of the study by Inzlicht et al., (2009). Participants (N=193) performed a gender-Stroop task and afterwards completed standardized measures to assess their religiosity. As expected, the task induced cognitive conflict at the behavioral level and at a neural level this was reflected in increased activity in the anterior cingulate cortex (ACC). However, individual differences in religiosity were not related to performance on the Stroop task as measured in accuracy and interference effects, nor to neural markers of response conflict (correct responses vs. errors) or informational conflict (congruent vs. incongruent stimuli). Overall, we obtained moderate to strong evidence in favor of the null hypotheses that religiosity is unrelated to cognitive conflict sensitivity. We discuss the implications for the neuroscience of religion and emphasize the importance of designing studies that more directly implicate religious concepts and behaviors in an ecologically valid manner.
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Affiliation(s)
- Suzanne Hoogeveen
- University of Amsterdam, Department of Social Psychology, 1001, NK Amsterdam, the Netherlands.
| | - Lukas Snoek
- University of Amsterdam, Department of Brain and Cognition, 1001, NK Amsterdam, the Netherlands.
| | - Michiel van Elk
- University of Amsterdam, Department of Social Psychology, 1001, NK Amsterdam, the Netherlands.
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163
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Monti RP, Gibberd A, Roy S, Nunes M, Lorenz R, Leech R, Ogawa T, Kawanabe M, Hyvärinen A. Interpretable brain age prediction using linear latent variable models of functional connectivity. PLoS One 2020; 15:e0232296. [PMID: 32520931 PMCID: PMC7286502 DOI: 10.1371/journal.pone.0232296] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Accepted: 04/11/2020] [Indexed: 01/02/2023] Open
Abstract
Neuroimaging-driven prediction of brain age, defined as the predicted biological age of a subject using only brain imaging data, is an exciting avenue of research. In this work we seek to build models of brain age based on functional connectivity while prioritizing model interpretability and understanding. This way, the models serve to both provide accurate estimates of brain age as well as allow us to investigate changes in functional connectivity which occur during the ageing process. The methods proposed in this work consist of a two-step procedure: first, linear latent variable models, such as PCA and its extensions, are employed to learn reproducible functional connectivity networks present across a cohort of subjects. The activity within each network is subsequently employed as a feature in a linear regression model to predict brain age. The proposed framework is employed on the data from the CamCAN repository and the inferred brain age models are further demonstrated to generalize using data from two open-access repositories: the Human Connectome Project and the ATR Wide-Age-Range.
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Affiliation(s)
- Ricardo Pio Monti
- Gatsby Computational Neuroscience Unit, University College London, London, United Kingdom
- RIKEN Center for Advanced Intelligence Project (AIP), Kyoto, Japan
- * E-mail:
| | - Alex Gibberd
- Department of Mathematics & Statistics, Lancaster University, Bailrigg, United Kingdom
| | - Sandipan Roy
- Department of Mathematical Sciences, University of Bath, Bath, United Kingdom
| | - Matthew Nunes
- Department of Mathematical Sciences, University of Bath, Bath, United Kingdom
| | - Romy Lorenz
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom
- Department of Psychology, Stanford University, Stanford, CA, United States of America
| | - Robert Leech
- Centre for Neuroimaging Science, Kings College London, London, United Kingdom
| | - Takeshi Ogawa
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International (ATR), Kyoto, Japan
| | - Motoaki Kawanabe
- RIKEN Center for Advanced Intelligence Project (AIP), Kyoto, Japan
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International (ATR), Kyoto, Japan
| | - Aapo Hyvärinen
- Université Paris-Saclay, Inria, 91190 Palaiseau, France
- Department of Computer Science and HIIT, University of Helsinki, Helsinki, Finland
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164
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Kantonen T, Karjalainen T, Isojärvi J, Nuutila P, Tuisku J, Rinne J, Hietala J, Kaasinen V, Kalliokoski K, Scheinin H, Hirvonen J, Vehtari A, Nummenmaa L. Interindividual variability and lateralization of μ-opioid receptors in the human brain. Neuroimage 2020; 217:116922. [PMID: 32407992 DOI: 10.1016/j.neuroimage.2020.116922] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Revised: 04/29/2020] [Accepted: 05/01/2020] [Indexed: 12/19/2022] Open
Abstract
Alterations in the brain's μ-opioid receptor (MOR) system have been associated with several neuropsychiatric disorders. Central MOR availability also varies considerably in healthy individuals. Multiple epidemiological factors have been proposed to influence the MOR system, but due to small sample sizes the magnitude of their influence remains inconclusive. We compiled [11C]carfentanil positron emission tomography scans from 204 individuals with no neurologic or psychiatric disorders, and estimated the effects of sex, age, body mass index (BMI) and smoking on [11C]carfentanil binding potential using between-subject regression analysis. We also examined hemispheric differences in MOR availability. Older age was associated with increase in MOR availability in frontotemporal areas but decrease in amygdala, thalamus, and nucleus accumbens. The age-dependent increase was stronger in males. MOR availability was globally lowered in smokers but independent of BMI. Finally, MOR availability was higher in the right versus the left hemisphere. The presently observed variation in MOR availability may explain why some individuals are prone to develop MOR-linked pathological states, such as chronic pain or psychiatric disorders. Lateralized MOR system may reflect hemispheric work specialization in central emotion and pain processes.
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Affiliation(s)
- Tatu Kantonen
- Turku PET Centre, University of Turku, Finland; Clinical Neurosciences, University of Turku and Turku University Hospital, Finland.
| | - Tomi Karjalainen
- Turku PET Centre, University of Turku, Finland; Turku PET Centre, Turku University Hospital, Finland
| | | | - Pirjo Nuutila
- Turku PET Centre, University of Turku, Finland; Department of Endocrinology, Turku University Hospital, Finland
| | | | - Juha Rinne
- Turku PET Centre, University of Turku, Finland; Clinical Neurosciences, University of Turku and Turku University Hospital, Finland
| | - Jarmo Hietala
- Turku PET Centre, University of Turku, Finland; Department of Psychiatry, University of Turku and Turku University Hospital, Finland
| | - Valtteri Kaasinen
- Turku PET Centre, University of Turku, Finland; Clinical Neurosciences, University of Turku and Turku University Hospital, Finland
| | | | | | | | - Aki Vehtari
- Helsinki Institute for Information Technology HIIT, Department of Computer Science, Aalto University, Finland
| | - Lauri Nummenmaa
- Turku PET Centre, University of Turku, Finland; Department of Psychology, University of Turku, Finland
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165
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Caria A. Mesocorticolimbic Interactions Mediate fMRI-Guided Regulation of Self-Generated Affective States. Brain Sci 2020; 10:brainsci10040223. [PMID: 32276411 PMCID: PMC7226604 DOI: 10.3390/brainsci10040223] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Revised: 04/03/2020] [Accepted: 04/04/2020] [Indexed: 11/16/2022] Open
Abstract
Increasing evidence shows that the generation and regulation of affective responses is associated with activity of large brain networks that also include phylogenetically older regions in the brainstem. Mesencephalic regions not only control autonomic responses but also participate in the modulation of autonomic, emotional, and motivational responses. The specific contribution of the midbrain to emotion regulation in humans remains elusive. Neuroimaging studies grounding on appraisal models of emotion emphasize a major role of prefrontal cortex in modulating emotion-related cortical and subcortical regions but usually neglect the contribution of the midbrain and other brainstem regions. Here, the role of mesolimbic and mesocortical networks in core affect generation and regulation was explored during emotion regulation guided by real-time fMRI feedback of the anterior insula activity. The fMRI and functional connectivity analysis revealed that the upper midbrain significantly contributes to emotion regulation in humans. Moreover, differential functional interactions between the dopaminergic mesocorticolimbic system and frontoparietal networks mediate up and down emotion regulatory processes. Finally, these findings further indicate the potential of real-time fMRI feedback approach in guiding core affect regulation.
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Affiliation(s)
- Andrea Caria
- Department of Psychology and Cognitive Sciences, University of Trento, Corso Bettini 33, 38068 Rovereto, Italy
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166
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Noble S, Scheinost D, Constable RT. Cluster failure or power failure? Evaluating sensitivity in cluster-level inference. Neuroimage 2020; 209:116468. [PMID: 31852625 PMCID: PMC8061745 DOI: 10.1016/j.neuroimage.2019.116468] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Revised: 12/12/2019] [Accepted: 12/13/2019] [Indexed: 01/19/2023] Open
Abstract
Pioneering work in human neuroscience has relied on the ability to map brain function using task-based fMRI, but the empirical validity of these inferential methods is still being characterized. A recent landmark study by Eklund and colleagues showed that popular multiple comparison corrections based on cluster extent suffer from unexpectedly low specificity (i.e., high false positive rate). Yet that study's focus on specificity, while important, is incomplete. The validity of a method depends also on its sensitivity (i.e., true positive rate or power), yet the sensitivity of cluster correction remains poorly understood. Here, we assessed the sensitivity of gold-standard nonparametric cluster correction by resampling real data from five tasks in the Human Connectome Project and comparing results with those from the full "ground truth" datasets (n = 480-493). Critically, we found that sensitivity after correction is lower than may be practical for many fMRI applications. In particular, sensitivity to medium-sized effects (|Cohen's d| = 0.5) was less than 20% across tasks on average, about three times smaller than without any correction. Furthermore, cluster extent correction exhibited a spatial bias in sensitivity that was independent of effect size. In comparison, correction based on the Threshold-Free Cluster Enhancement (TFCE) statistic approximately doubled sensitivity across tasks but increased spatial bias. These results suggest that we have, until now, only measured the tip of the iceberg in the activation-mapping literature due to our goal of limiting the familywise error rate through cluster extent-based inference. There is a need to revise our practices to improve sensitivity; we therefore conclude with a list of modern strategies to boost sensitivity while maintaining respectable specificity in future investigations.
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Affiliation(s)
- Stephanie Noble
- Interdepartmental Neuroscience Program, Yale University, USA; Department of Radiology and Biomedical Imaging, Yale School of Medicine, USA.
| | - Dustin Scheinost
- Interdepartmental Neuroscience Program, Yale University, USA; Department of Radiology and Biomedical Imaging, Yale School of Medicine, USA; Department of Statistics and Data Science, Yale University, USA; Child Study Center, Yale School of Medicine, USA
| | - R Todd Constable
- Interdepartmental Neuroscience Program, Yale University, USA; Department of Radiology and Biomedical Imaging, Yale School of Medicine, USA; Department of Neurosurgery, Yale School of Medicine, USA
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167
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Alberton BAV, Nichols TE, Gamba HR, Winkler AM. Multiple testing correction over contrasts for brain imaging. Neuroimage 2020; 216:116760. [PMID: 32201328 PMCID: PMC8191638 DOI: 10.1016/j.neuroimage.2020.116760] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2019] [Revised: 03/11/2020] [Accepted: 03/15/2020] [Indexed: 01/28/2023] Open
Abstract
The multiple testing problem arises not only when there are many voxels or vertices in an image representation of the brain, but also when multiple contrasts of parameter estimates (that represent hypotheses) are tested in the same general linear model. We argue that a correction for this multiplicity must be performed to avoid excess of false positives. Various methods for correction have been proposed in the literature, but few have been applied to brain imaging. Here we discuss and compare different methods to make such correction in different scenarios, showing that one classical and well known method is invalid, and argue that permutation is the best option to perform such correction due to its exactness and flexibility to handle a variety of common imaging situations.
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Affiliation(s)
- Bianca A V Alberton
- Graduate Program in Electrical and Computer Engineering, Universidade Tecnológica Federal Do Paraná, Curitiba, PR, Brazil.
| | | | - Humberto R Gamba
- Graduate Program in Electrical and Computer Engineering, Universidade Tecnológica Federal Do Paraná, Curitiba, PR, Brazil.
| | - Anderson M Winkler
- Graduate Program in Electrical and Computer Engineering, Universidade Tecnológica Federal Do Paraná, Curitiba, PR, Brazil; National Institute of Mental Health (nimh), National Institutes of Health (nih), Bethesda, MD, USA.
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168
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Cross ES, Riddoch KA, Pratts J, Titone S, Chaudhury B, Hortensius R. A neurocognitive investigation of the impact of socializing with a robot on empathy for pain. Philos Trans R Soc Lond B Biol Sci 2020; 374:20180034. [PMID: 30852995 DOI: 10.1098/rstb.2018.0034] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
To what extent can humans form social relationships with robots? In the present study, we combined functional neuroimaging with a robot socializing intervention to probe the flexibility of empathy, a core component of social relationships, towards robots. Twenty-six individuals underwent identical fMRI sessions before and after being issued a social robot to take home and interact with over the course of a week. While undergoing fMRI, participants observed videos of a human actor or a robot experiencing pain or pleasure in response to electrical stimulation. Repetition suppression of activity in the pain network, a collection of brain regions associated with empathy and emotional responding, was measured to test whether socializing with a social robot leads to greater overlap in neural mechanisms when observing human and robotic agents experiencing pain or pleasure. In contrast to our hypothesis, functional region-of-interest analyses revealed no change in neural overlap for agents after the socializing intervention. Similarly, no increase in activation when observing a robot experiencing pain emerged post-socializing. Whole-brain analysis showed that, before the socializing intervention, superior parietal and early visual regions are sensitive to novel agents, while after socializing, medial temporal regions show agent sensitivity. A region of the inferior parietal lobule was sensitive to novel emotions, but only during the pre-socializing scan session. Together, these findings suggest that a short socialization intervention with a social robot does not lead to discernible differences in empathy towards the robot, as measured by behavioural or brain responses. We discuss the extent to which long-term socialization with robots might shape social cognitive processes and ultimately our relationships with these machines. This article is part of the theme issue 'From social brains to social robots: applying neurocognitive insights to human-robot interaction'.
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Affiliation(s)
- Emily S Cross
- 1 Institute of Neuroscience and Psychology, School of Psychology, University of Glasgow , Glasgow G12 8QB , UK.,2 Wales Institute for Cognitive Neuroscience, School of Psychology, Bangor University , Bangor LL57 2AS , UK
| | - Katie A Riddoch
- 2 Wales Institute for Cognitive Neuroscience, School of Psychology, Bangor University , Bangor LL57 2AS , UK
| | - Jaydan Pratts
- 2 Wales Institute for Cognitive Neuroscience, School of Psychology, Bangor University , Bangor LL57 2AS , UK
| | - Simon Titone
- 2 Wales Institute for Cognitive Neuroscience, School of Psychology, Bangor University , Bangor LL57 2AS , UK
| | - Bishakha Chaudhury
- 1 Institute of Neuroscience and Psychology, School of Psychology, University of Glasgow , Glasgow G12 8QB , UK
| | - Ruud Hortensius
- 1 Institute of Neuroscience and Psychology, School of Psychology, University of Glasgow , Glasgow G12 8QB , UK
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169
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Borowiak K, Maguinness C, von Kriegstein K. Dorsal-movement and ventral-form regions are functionally connected during visual-speech recognition. Hum Brain Mapp 2020; 41:952-972. [PMID: 31749219 PMCID: PMC7267922 DOI: 10.1002/hbm.24852] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2019] [Revised: 09/03/2019] [Accepted: 10/21/2019] [Indexed: 01/17/2023] Open
Abstract
Faces convey social information such as emotion and speech. Facial emotion processing is supported via interactions between dorsal-movement and ventral-form visual cortex regions. Here, we explored, for the first time, whether similar dorsal-ventral interactions (assessed via functional connectivity), might also exist for visual-speech processing. We then examined whether altered dorsal-ventral connectivity is observed in adults with high-functioning autism spectrum disorder (ASD), a disorder associated with impaired visual-speech recognition. We acquired functional magnetic resonance imaging (fMRI) data with concurrent eye tracking in pairwise matched control and ASD participants. In both groups, dorsal-movement regions in the visual motion area 5 (V5/MT) and the temporal visual speech area (TVSA) were functionally connected to ventral-form regions (i.e., the occipital face area [OFA] and the fusiform face area [FFA]) during the recognition of visual speech, in contrast to the recognition of face identity. Notably, parts of this functional connectivity were decreased in the ASD group compared to the controls (i.e., right V5/MT-right OFA, left TVSA-left FFA). The results confirmed our hypothesis that functional connectivity between dorsal-movement and ventral-form regions exists during visual-speech processing. Its partial dysfunction in ASD might contribute to difficulties in the recognition of dynamic face information relevant for successful face-to-face communication.
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Affiliation(s)
- Kamila Borowiak
- Chair of Cognitive and Clinical Neuroscience, Faculty of Psychology, Technische Universität DresdenDresdenGermany
- Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- Berlin School of Mind and Brain, Humboldt University of BerlinBerlinGermany
| | - Corrina Maguinness
- Chair of Cognitive and Clinical Neuroscience, Faculty of Psychology, Technische Universität DresdenDresdenGermany
- Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Katharina von Kriegstein
- Chair of Cognitive and Clinical Neuroscience, Faculty of Psychology, Technische Universität DresdenDresdenGermany
- Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
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170
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Moessnang C, Baumeister S, Tillmann J, Goyard D, Charman T, Ambrosino S, Baron-Cohen S, Beckmann C, Bölte S, Bours C, Crawley D, Dell'Acqua F, Durston S, Ecker C, Frouin V, Hayward H, Holt R, Johnson M, Jones E, Lai MC, Lombardo MV, Mason L, Oldenhinkel M, Persico A, Cáceres ASJ, Spooren W, Loth E, Murphy DGM, Buitelaar JK, Banaschewski T, Brandeis D, Tost H, Meyer-Lindenberg A. Social brain activation during mentalizing in a large autism cohort: the Longitudinal European Autism Project. Mol Autism 2020; 11:17. [PMID: 32087753 PMCID: PMC7036196 DOI: 10.1186/s13229-020-0317-x] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Accepted: 01/23/2020] [Indexed: 12/14/2022] Open
Abstract
Background Autism spectrum disorder (ASD) is a neurodevelopmental condition with key deficits in social functioning. It is widely assumed that the biological underpinnings of social impairment are neurofunctional alterations in the “social brain,” a neural circuitry involved in inferring the mental state of a social partner. However, previous evidence comes from small-scale studies and findings have been mixed. We therefore carried out the to-date largest study on neural correlates of mentalizing in ASD. Methods As part of the Longitudinal European Autism Project, we performed functional magnetic resonance imaging at six European sites in a large, well-powered, and deeply phenotyped sample of individuals with ASD (N = 205) and typically developing (TD) individuals (N = 189) aged 6 to 30 years. We presented an animated shapes task to assess and comprehensively characterize social brain activation during mentalizing. We tested for effects of age, diagnosis, and their association with symptom measures, including a continuous measure of autistic traits. Results We observed robust effects of task. Within the ASD sample, autistic traits were moderately associated with functional activation in one of the key regions of the social brain, the dorsomedial prefrontal cortex. However, there were no significant effects of diagnosis on task performance and no effects of age and diagnosis on social brain responses. Besides a lack of mean group differences, our data provide no evidence for meaningful differences in the distribution of brain response measures. Extensive control analyses suggest that the lack of case-control differences was not due to a variety of potential confounders. Conclusions Contrary to prior reports, this large-scale study does not support the assumption that altered social brain activation during mentalizing forms a common neural marker of ASD, at least with the paradigm we employed. Yet, autistic individuals show socio-behavioral deficits. Our work therefore highlights the need to interrogate social brain function with other brain measures, such as connectivity and network-based approaches, using other paradigms, or applying complementary analysis approaches to assess individual differences in this heterogeneous condition.
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Affiliation(s)
- Carolin Moessnang
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim / University of Heidelberg, Mannheim, Germany.
| | - Sarah Baumeister
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim / University of Heidelberg, Mannheim, Germany
| | - Julian Tillmann
- Department of Psychology, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.,Department of Applied Psychology: Health, Development, Enhancement, and Intervention, University of Vienna, Vienna, Australia
| | - David Goyard
- Neurospin Centre CEA, Saclay, Gif sur Yvette, France
| | - Tony Charman
- Department of Psychology, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Sara Ambrosino
- Department of Psychiatry, UMC Utrecht Brain Center, Utrecht, The Netherlands
| | - Simon Baron-Cohen
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Christian Beckmann
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands.,Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Sven Bölte
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institutet and Child and Adolescent Psychiatry, Stockholm Health Care Services, Stockholm County Council, Stockholm, Sweden.,Curtin Autism Research Group, School of Occupational Therapy, Social Work and Speech Pathology, Curtin University, Perth, Western Australia, Australia
| | - Carsten Bours
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands.,Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Daisy Crawley
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Flavio Dell'Acqua
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.,Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Sarah Durston
- Department of Psychiatry, UMC Utrecht Brain Center, Utrecht, The Netherlands
| | - Christine Ecker
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Frankfurt am Main, Goethe University, Frankfurt, Germany
| | | | - Hannah Hayward
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Rosemary Holt
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Mark Johnson
- Centre for Brain and Cognitive Development, Birkbeck, University of London, London, UK
| | - Emily Jones
- Centre for Brain and Cognitive Development, Birkbeck, University of London, London, UK
| | - Meng-Chuan Lai
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK.,Centre for Addiction and Mental Health and The Hospital for Sick Children, Department of Psychiatry, University of Toronto, Toronto, Canada.,Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan
| | - Michael V Lombardo
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK.,Department of Psychology, University of Cyprus, Nicosia, Cyprus
| | - Luke Mason
- Centre for Brain and Cognitive Development, Birkbeck, University of London, London, UK
| | - Marianne Oldenhinkel
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands.,Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Antonio Persico
- Child and Adolescent Neuropsychiatry Unit, "Gaetano Martino" University Hospital, University of Messina, Messina, Italy.,Mafalda Luce Center for Pervasive Developmental Disorders, University Campus Bio-Medico, Milan, Italy
| | - Antonia San José Cáceres
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Will Spooren
- Roche Pharmaceutical Research and Early Development, NORD Discovery and Translational Area, Roche Innovation Center Basel, Basel, Switzerland
| | - Eva Loth
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.,Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Declan G M Murphy
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.,Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Jan K Buitelaar
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands.,Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, The Netherlands.,Karakter Child and Adolescent Psychiatry University Centre, Nijmegen, The Netherlands
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim / University of Heidelberg, Mannheim, Germany
| | - Daniel Brandeis
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim / University of Heidelberg, Mannheim, Germany.,Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland.,Center for Integrative Human Physiology Zurich, University of Zurich, Zurich, Switzerland
| | - Heike Tost
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim / University of Heidelberg, Mannheim, Germany
| | - Andreas Meyer-Lindenberg
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim / University of Heidelberg, Mannheim, Germany
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171
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Bossier H, Roels SP, Seurinck R, Banaschewski T, Barker GJ, Bokde ALW, Quinlan EB, Desrivières S, Flor H, Grigis A, Garavan H, Gowland P, Heinz A, Ittermann B, Martinot JL, Artiges E, Nees F, Orfanos DP, Poustka L, Fröhner Dipl-Psych JH, Smolka MN, Walter H, Whelan R, Schumann G, Moerkerke B. The empirical replicability of task-based fMRI as a function of sample size. Neuroimage 2020; 212:116601. [PMID: 32036019 DOI: 10.1016/j.neuroimage.2020.116601] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2018] [Revised: 01/25/2020] [Accepted: 02/01/2020] [Indexed: 11/30/2022] Open
Abstract
Replicating results (i.e. obtaining consistent results using a new independent dataset) is an essential part of good science. As replicability has consequences for theories derived from empirical studies, it is of utmost importance to better understand the underlying mechanisms influencing it. A popular tool for non-invasive neuroimaging studies is functional magnetic resonance imaging (fMRI). While the effect of underpowered studies is well documented, the empirical assessment of the interplay between sample size and replicability of results for task-based fMRI studies remains limited. In this work, we extend existing work on this assessment in two ways. Firstly, we use a large database of 1400 subjects performing four types of tasks from the IMAGEN project to subsample a series of independent samples of increasing size. Secondly, replicability is evaluated using a multi-dimensional framework consisting of 3 different measures: (un)conditional test-retest reliability, coherence and stability. We demonstrate not only a positive effect of sample size, but also a trade-off between spatial resolution and replicability. When replicability is assessed voxelwise or when observing small areas of activation, a larger sample size than typically used in fMRI is required to replicate results. On the other hand, when focussing on clusters of voxels, we observe a higher replicability. In addition, we observe variability in the size of clusters of activation between experimental paradigms or contrasts of parameter estimates within these.
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Affiliation(s)
- Han Bossier
- Department of Data Analysis, Ghent University, Ghent, Belgium.
| | - Sanne P Roels
- Department of Data Analysis, Ghent University, Ghent, Belgium
| | - Ruth Seurinck
- Department of Data Analysis, Ghent University, Ghent, Belgium
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159, Mannheim, Germany
| | - Gareth J Barker
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, United Kingdom
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Ireland
| | - Erin Burke Quinlan
- Medical Research Council - Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, United Kingdom
| | - Sylvane Desrivières
- Medical Research Council - Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, United Kingdom
| | - Herta Flor
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany; Department of Psychology, School of Social Sciences, University of Mannheim, 68131, Mannheim, Germany
| | - Antoine Grigis
- NeuroSpin, CEA, Université Paris-Saclay, F-91191, Gif-sur-Yvette, France
| | - Hugh Garavan
- Departments of Psychiatry and Psychology, University of Vermont, 05405, Burlington, VT, USA
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, United Kingdom
| | - Andreas Heinz
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charitéplatz 1, Berlin, Germany
| | - Bernd Ittermann
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 "Neuroimaging & Psychiatry", University Paris Sud, University Paris Descartes, Sorbonne Paris Cité; and Maison de Solenn, Paris, France
| | - Eric Artiges
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 "Neuroimaging & Psychiatry", University Paris Sud, University Paris Descartes, Sorbonne Paris Cité; and Psychiatry Department 91G16, Orsay Hospital, France
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159, Mannheim, Germany; Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
| | | | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, von-Siebold-Str. 5, 37075, Göttingen, Germany
| | | | - Michael N Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Henrik Walter
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charitéplatz 1, Berlin, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Ireland
| | - Gunter Schumann
- Medical Research Council - Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, United Kingdom
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172
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Karjalainen T, Tuisku J, Santavirta S, Kantonen T, Bucci M, Tuominen L, Hirvonen J, Hietala J, Rinne JO, Nummenmaa L. Magia: Robust Automated Image Processing and Kinetic Modeling Toolbox for PET Neuroinformatics. Front Neuroinform 2020; 14:3. [PMID: 32116627 PMCID: PMC7012016 DOI: 10.3389/fninf.2020.00003] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Accepted: 01/15/2020] [Indexed: 11/13/2022] Open
Abstract
Processing of positron emission tomography (PET) data typically involves manual work, causing inter-operator variance. Here we introduce the Magia toolbox that enables processing of brain PET data with minimal user intervention. We investigated the accuracy of Magia with four tracers: [11C]carfentanil, [11C]raclopride, [11C]MADAM, and [11C]PiB. We used data from 30 control subjects for each tracer. Five operators manually delineated reference regions for each subject. The data were processed using Magia using the manually and automatically generated reference regions. We first assessed inter-operator variance resulting from the manual delineation of reference regions. We then compared the differences between the manually and automatically produced reference regions and the subsequently obtained binding potentials and standardized-uptake-value-ratios. The results show that manually produced reference regions can be remarkably different from each other, leading to substantial differences also in outcome measures. While the Magia-derived reference regions were anatomically different from the manual ones, Magia produced outcome measures highly consistent with the average of the manually obtained estimates. For [11C]carfentanil and [11C]PiB there was no bias, while for [11C]raclopride and [11C]MADAM Magia produced 3-5% higher binding potentials. Based on these results and considering the high inter-operator variance of the manual method, we conclude that Magia can be reliably used to process brain PET data.
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Affiliation(s)
- Tomi Karjalainen
- Turku PET Centre, University of Turku and Turku University Hospital, Turku, Finland
| | - Jouni Tuisku
- Turku PET Centre, University of Turku and Turku University Hospital, Turku, Finland
| | - Severi Santavirta
- Turku PET Centre, University of Turku and Turku University Hospital, Turku, Finland
| | - Tatu Kantonen
- Turku PET Centre, University of Turku and Turku University Hospital, Turku, Finland
| | - Marco Bucci
- Turku PET Centre, University of Turku and Turku University Hospital, Turku, Finland
| | - Lauri Tuominen
- The Royal’s Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada
| | - Jussi Hirvonen
- Turku PET Centre, University of Turku and Turku University Hospital, Turku, Finland
- Department of Radiology, University of Turku, Turku, Finland
| | - Jarmo Hietala
- Turku PET Centre, University of Turku and Turku University Hospital, Turku, Finland
- Department of Psychiatry, Faculty of Medicine, University of Turku and Turku University Hospital, Turku, Finland
| | - Juha O. Rinne
- Turku PET Centre, University of Turku and Turku University Hospital, Turku, Finland
- Division of Clinical Neurosciences, Turku University Hospital, Turku, Finland
| | - Lauri Nummenmaa
- Turku PET Centre, University of Turku and Turku University Hospital, Turku, Finland
- Department of Psychology, University of Turku, Turku, Finland
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173
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Chen G, Taylor PA, Cox RW, Pessoa L. Fighting or embracing multiplicity in neuroimaging? neighborhood leverage versus global calibration. Neuroimage 2020; 206:116320. [PMID: 31698079 PMCID: PMC6980934 DOI: 10.1016/j.neuroimage.2019.116320] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2019] [Revised: 10/23/2019] [Accepted: 10/27/2019] [Indexed: 01/24/2023] Open
Abstract
Neuroimaging faces the daunting challenge of multiple testing - an instance of multiplicity - that is associated with two other issues to some extent: low inference efficiency and poor reproducibility. Typically, the same statistical model is applied to each spatial unit independently in the approach of massively univariate modeling. In dealing with multiplicity, the general strategy employed in the field is the same regardless of the specifics: trust the local "unbiased" effect estimates while adjusting the extent of statistical evidence at the global level. However, in this approach, modeling efficiency is compromised because each spatial unit (e.g., voxel, region, matrix element) is treated as an isolated and independent entity during massively univariate modeling. In addition, the required step of multiple testing "correction" by taking into consideration spatial relatedness, or neighborhood leverage, can only partly recoup statistical efficiency, resulting in potentially excessive penalization as well as arbitrariness due to thresholding procedures. Moreover, the assigned statistical evidence at the global level heavily relies on the data space (whole brain or a small volume). The present paper reviews how Stein's paradox (1956) motivates a Bayesian multilevel (BML) approach that, rather than fighting multiplicity, embraces it to our advantage through a global calibration process among spatial units. Global calibration is accomplished via a Gaussian distribution for the cross-region effects whose properties are not a priori specified, but a posteriori determined by the data at hand through the BML model. Our framework therefore incorporates multiplicity as integral to the modeling structure, not a separate correction step. By turning multiplicity into a strength, we aim to achieve five goals: 1) improve the model efficiency with a higher predictive accuracy, 2) control the errors of incorrect magnitude and incorrect sign, 3) validate each model relative to competing candidates, 4) reduce the reliance and sensitivity on the choice of data space, and 5) encourage full results reporting. Our modeling proposal reverberates with recent proposals to eliminate the dichotomization of statistical evidence ("significant" vs. "non-significant"), to improve the interpretability of study findings, as well as to promote reporting the full gamut of results (not only "significant" ones), thereby enhancing research transparency and reproducibility.
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Affiliation(s)
- Gang Chen
- Scientific and Statistical Computing Core, National Institute of Mental Health, USA.
| | - Paul A Taylor
- Scientific and Statistical Computing Core, National Institute of Mental Health, USA
| | - Robert W Cox
- Scientific and Statistical Computing Core, National Institute of Mental Health, USA
| | - Luiz Pessoa
- Department of Psychology, University of Maryland, College Park, USA; Department of Electrical and Computer Engineering, University of Maryland, College Park, USA; Maryland Neuroimaging Center, University of Maryland, College Park, USA
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174
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van Elk M, Snoek L. The relationship between individual differences in gray matter volume and religiosity and mystical experiences: A preregistered voxel-based morphometry study. Eur J Neurosci 2020; 51:850-865. [PMID: 31465601 PMCID: PMC7079225 DOI: 10.1111/ejn.14563] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Revised: 08/18/2019] [Accepted: 08/27/2019] [Indexed: 01/03/2023]
Abstract
The neural substrates of religious belief and experience are an intriguing though contentious topic. Here, we had the unique opportunity to establish the relation between validated measures of religiosity and gray matter volume in a large sample of participants (N = 211). In this registered report, we conducted a confirmatory voxel-based morphometry analysis to test three central hypotheses regarding the relationship between religiosity and mystical experiences and gray matter volume. The preregisterered hypotheses, analysis plan, preprocessing and analysis code and statistical brain maps are all available from online repositories. By using a region-of-interest analysis, we found no evidence that religiosity is associated with a reduced volume of the orbito-frontal cortex and changes in the structure of the bilateral inferior parietal lobes. Neither did we find support for the notion that mystical experiences are associated with a reduced volume of the hippocampus, the right middle temporal gyrus or with the inferior parietal lobes. A whole-brain analysis furthermore indicated that no structural brain differences were found in association with religiosity and mystical experiences. We believe that the search for the neural correlates of religious beliefs and experiences should therefore shift focus from studying structural brain differences to a functional and multivariate approach.
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Affiliation(s)
- Michiel van Elk
- Department of PsychologyUniversity of AmsterdamAmsterdamThe Netherlands
- Amsterdam Brain and Cognition CenterUniversity of AmsterdamAmsterdamThe Netherlands
| | - Lukas Snoek
- Department of PsychologyUniversity of AmsterdamAmsterdamThe Netherlands
- Amsterdam Brain and Cognition CenterUniversity of AmsterdamAmsterdamThe Netherlands
- Spinoza Center for NeuroimagingRoyal Netherlands Academy of Arts and SciencesAmsterdamThe Netherlands
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175
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Lloyd D. The Musical Structure of Time in the Brain: Repetition, Rhythm, and Harmony in fMRI During Rest and Passive Movie Viewing. Front Comput Neurosci 2020; 13:98. [PMID: 32038214 PMCID: PMC6985279 DOI: 10.3389/fncom.2019.00098] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2018] [Accepted: 12/23/2019] [Indexed: 11/13/2022] Open
Abstract
Space generally overshadows time in the construction of theories in cognitive neuroscience. In this paper, we pivot from the spatial axes to the temporal, analyzing fMRI image series to reveal structures in time rather than space. To determine affinities among global brain patterns at different times, core concepts in network analysis (derived from graph theory) were applied temporally, as relations among brain images at every time point during an fMRI scanning epoch. To explore the temporal structures observed through this adaptation of network analysis, data from 180 subjects in the Human Connectome Project were examined, during two experimental conditions: passive movie viewing and rest. The temporal brain, like the spatial brain, exhibits a modular structure, where "modules" are intermittent (distributed in time). These temporal entities are here referred to as themes. Short sequences of themes - motifs - were studied in sequences from 4 to 11 s in length. Many motifs repeated at constant intervals, and are therefore rhythmic; rhythms, converted to frequencies, were often harmonic. We speculate that the structure and interaction of these global oscillations underwrites the capacity to experience and navigate a world which is both recognizably stable and noticeably changing at every moment - a temporal world. In its temporal structure, this brain-constituted world resembles music.
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Affiliation(s)
- Dan Lloyd
- Department of Philosophy and Program in Neuroscience, Trinity College, Hartford, CT, United States
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176
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Franssen S, Jansen A, van den Hurk J, Roebroeck A, Roefs A. Power of mind: Attentional focus rather than palatability dominates neural responding to visual food stimuli in females with overweight. Appetite 2020; 148:104609. [PMID: 31954729 DOI: 10.1016/j.appet.2020.104609] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Revised: 01/10/2020] [Accepted: 01/10/2020] [Indexed: 11/26/2022]
Abstract
Research investigating neural responses to visual food stimuli has produced inconsistent results. Crucially, high-caloric palatable foods have a double-sided nature - they are often craved but are also considered unhealthy - which may have contributed to the inconsistency in the literature. Taking this double-sided nature into account in the current study, neural responses to individually tailored palatable and unpalatable high caloric food stimuli were measured, while participants' (females with overweight: n = 23) attentional focus was manipulated to be either hedonic or neutral. Notably, results showed that the level of neural activity was not significantly different for palatable than for unpalatable food stimuli. Instead, independent of food palatability, several brain regions (including regions in the mesocorticolimbic system) responded more strongly when attentional focus was hedonic than when neutral (p < 0.05, cluster-based FWE corrected). Multivariate analyses showed that food palatability could be decoded from multi-voxel patterns of neural activity (p < 0.05, FDR corrected), mostly with a hedonic attentional focus. These findings illustrate that the level of neural activity might not be proportionate to the palatability of foods, but that food palatability can be decoded from multi-voxel patterns of neural activity. Moreover, they underline the importance of considering attentional focus when measuring food-related neural responses.
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Affiliation(s)
- Sieske Franssen
- Department of Clinical Psychological Science, Faculty of Psychology and Neuroscience, Maastricht University, 6200 MD, Maastricht, the Netherlands.
| | - Anita Jansen
- Department of Clinical Psychological Science, Faculty of Psychology and Neuroscience, Maastricht University, 6200 MD, Maastricht, the Netherlands
| | - Job van den Hurk
- Scannexus, 6229 EV, Maastricht, the Netherlands; Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, 6200 MD, Maastricht, the Netherlands
| | - Alard Roebroeck
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, 6200 MD, Maastricht, the Netherlands
| | - Anne Roefs
- Department of Clinical Psychological Science, Faculty of Psychology and Neuroscience, Maastricht University, 6200 MD, Maastricht, the Netherlands
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177
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Degryse J, Moerkerke B. A likelihood ratio approach for functional localization in fMRI. J Neurosci Methods 2020; 330:108417. [PMID: 31628960 DOI: 10.1016/j.jneumeth.2019.108417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2019] [Revised: 08/27/2019] [Accepted: 08/27/2019] [Indexed: 11/17/2022]
Abstract
BACKGROUND To increase power when analyzing fMRI data, researchers often define functional regions of interest (fROIs). It is crucial that this fROI is defined with an optimal balance between both false positives and false negatives to ensure maximal spatial accuracy and to avoid potentially biased results in the main fMRI experiment. Additionally, since the fROI is defined in each subject separately, the used method should attune to the general level of activation of the individual. NEW METHOD We investigate the benefits of the maximized likelihood ratio (mLR) method. This method is based on the likelihood paradigm where likelihood ratios are used to reflect relative statistical evidence in favor of an a priori defined practically relevant alternative hypothesis as compared to the null hypothesis of no activation. RESULTS Through both simulations and real data, we show that the mLR method provides cumulative evidence for voxels that are active with an effect size that is larger than the one a priori defined in the alternative. Furthermore, an optimal balance between Type I and Type II errors is achieved when the alternative is an underestimation of the true effect size. COMPARISON WITH EXISTING METHODS The mLR method is compared with false discovery rate corrected null hypothesis significance testing and regular likelihood ratio testing. It performs as good as or outperformed both methods in both detection of practically relevant voxels and the trade- off between false positives and false negatives. CONCLUSIONS The mLR method provides fROIs that are both spatially accurate and practically relevant.
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Affiliation(s)
- Jasper Degryse
- Department of Data Analysis, Ghent University, H. Dunantlaan 1, 9000 Gent, Belgium.
| | - Beatrijs Moerkerke
- Department of Data Analysis, Ghent University, H. Dunantlaan 1, 9000 Gent, Belgium.
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178
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Suh JS, Minuzzi L, Raamana PR, Davis A, Hall GB, Harris J, Hassel S, Zamyadi M, Arnott SR, Alders GL, Sassi RB, Milev R, Lam RW, MacQueen GM, Strother SC, Kennedy SH, Frey BN. An investigation of cortical thickness and antidepressant response in major depressive disorder: A CAN-BIND study report. NEUROIMAGE-CLINICAL 2020; 25:102178. [PMID: 32036277 PMCID: PMC7011077 DOI: 10.1016/j.nicl.2020.102178] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/18/2019] [Revised: 11/25/2019] [Accepted: 01/10/2020] [Indexed: 11/28/2022]
Abstract
Major depressive disorder (MDD) is considered a highly heterogeneous clinical and neurobiological mental disorder. We employed a novel layered treatment design to investigate whether cortical thickness features at baseline differentiated treatment responders from non-responders after 8 and 16 weeks of a standardized sequential antidepressant treatment. Secondary analyses examined baseline differences between MDD and controls as a replication analysis and longitudinal changes in thickness after 8 weeks of escitalopram treatment. 181 MDD and 95 healthy comparison (HC) participants were studied. After 8 weeks of escitalopram treatment (10-20 mg/d, flexible dosage), responders (>50% decrease in Montgomery-Åsberg Depression Scale score) were continued on escitalopram; non-responders received adjunctive aripiprazole (2-10 mg/d, flexible dosage). MDD participants were classified into subgroups according to their response profiles at weeks 8 and 16. Baseline group differences in cortical thickness were analyzed with FreeSurfer between HC and MDD groups as well as between response groups. Two-stage longitudinal processing was used to investigate 8-week escitalopram treatment-related changes in cortical thickness. Compared to HC, the MDD group exhibited thinner cortex in the left rostral middle frontal cortex [MNI(X,Y,Z=-29,9,54.5,-7.7); CWP=0.0002]. No baseline differences in cortical thickness were observed between responders and non-responders based on week-8 or week-16 response profile. No changes in cortical thickness was observed after 8 weeks of escitalopram monotherapy. In a two-step 16-week sequential clinical trial we found that baseline cortical thickness does not appear to be associated to clinical response to pharmacotherapy at 8 or 16 weeks.
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Affiliation(s)
- Jee Su Suh
- Neuroscience Graduate Program, McMaster University, Hamilton, ON, Canada; Mood Disorders Program and Women's Health Concerns Clinic, St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada
| | - Luciano Minuzzi
- Neuroscience Graduate Program, McMaster University, Hamilton, ON, Canada; Mood Disorders Program and Women's Health Concerns Clinic, St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada; Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - Pradeep Reddy Raamana
- Rotman Research Institute, Baycrest Health Sciences; Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Andrew Davis
- Department of Psychology, Neuroscience and Behaviour, McMaster University, Hamilton, ON, Canada
| | - Geoffrey B Hall
- Department of Psychology, Neuroscience and Behaviour, McMaster University, Hamilton, ON, Canada
| | - Jacqueline Harris
- Department of Computing Science, University of Alberta, Edmonton, AB, Canada
| | - Stefanie Hassel
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; Mathison Centre for Mental Health Research and Education, University of Calgary, Calgary, AB, Canada
| | - Mojdeh Zamyadi
- Rotman Research Institute, Baycrest Health Sciences; Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Stephen R Arnott
- Rotman Research Institute, Baycrest Health Sciences; Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Gésine L Alders
- Neuroscience Graduate Program, McMaster University, Hamilton, ON, Canada; Mood Disorders Program and Women's Health Concerns Clinic, St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada
| | - Roberto B Sassi
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - Roumen Milev
- Departments of Psychiatry and Psychology, Queen's University and Providence Care Hospital, Kingston, ON, Canada
| | - Raymond W Lam
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Glenda M MacQueen
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; Mathison Centre for Mental Health Research and Education, University of Calgary, Calgary, AB, Canada
| | - Stephen C Strother
- Rotman Research Institute, Baycrest Health Sciences; Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Sidney H Kennedy
- Canadian Biomarker Integration Network for Depression, St. Michael's Hospital, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Benicio N Frey
- Neuroscience Graduate Program, McMaster University, Hamilton, ON, Canada; Mood Disorders Program and Women's Health Concerns Clinic, St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada; Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada.
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179
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Borja Jimenez KC, Abdelgabar AR, De Angelis L, McKay LS, Keysers C, Gazzola V. Changes in brain activity following the voluntary control of empathy. Neuroimage 2020; 216:116529. [PMID: 31931155 DOI: 10.1016/j.neuroimage.2020.116529] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2019] [Revised: 12/19/2019] [Accepted: 01/07/2020] [Indexed: 01/10/2023] Open
Abstract
In neuroscience, empathy is often conceived as relatively automatic. The voluntary control that people can exert on brain mechanisms that map the emotions of others onto our own emotions has received comparatively less attention. Here, we therefore measured brain activity while participants watched emotional Hollywood movies under two different instructions: to rate the main characters' emotions by empathizing with them, or to do so while keeping a detached perspective. We found that participants yielded highly consistent and similar ratings of emotions under both conditions. Using intersubject correlation-based analyses we found that, when encouraged to empathize, participants' brain activity in limbic (including cingulate and putamen) and somatomotor regions (including premotor, SI and SII) synchronized more during the movie than when encouraged to detach. Using intersubject functional connectivity we found that comparing the empathic and detached perspectives revealed widespread increases in functional connectivity between large scale networks. Our findings contribute to the increasing awareness that we have voluntary control over the neural mechanisms through which we process the emotions of others.
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Affiliation(s)
- K C Borja Jimenez
- Social Brain Lab, Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, Meibergdreef 47, 1105 BA, Amsterdam, the Netherlands
| | - A R Abdelgabar
- Social Brain Lab, Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, Meibergdreef 47, 1105 BA, Amsterdam, the Netherlands
| | - L De Angelis
- Social Brain Lab, Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, Meibergdreef 47, 1105 BA, Amsterdam, the Netherlands
| | - L S McKay
- Social Brain Lab, Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, Meibergdreef 47, 1105 BA, Amsterdam, the Netherlands; Current Address: Division of Psychology, School of Education & Social Sciences, University of the West of Scotland, High Street, Paisley, PA1 2BE, UK
| | - C Keysers
- Social Brain Lab, Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, Meibergdreef 47, 1105 BA, Amsterdam, the Netherlands; Department of Psychology, University of Amsterdam, Nieuwe Achtergracht 166, 1018, WV, Amsterdam, the Netherlands
| | - V Gazzola
- Social Brain Lab, Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, Meibergdreef 47, 1105 BA, Amsterdam, the Netherlands; Department of Psychology, University of Amsterdam, Nieuwe Achtergracht 166, 1018, WV, Amsterdam, the Netherlands.
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180
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Hidalgo-Lopez E, Mueller K, Harris T, Aichhorn M, Sacher J, Pletzer B. Human menstrual cycle variation in subcortical functional brain connectivity: a multimodal analysis approach. Brain Struct Funct 2020; 225:591-605. [PMID: 31894405 PMCID: PMC7046575 DOI: 10.1007/s00429-019-02019-z] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2019] [Accepted: 12/18/2019] [Indexed: 12/18/2022]
Abstract
Increasing evidence suggests that endogenous sex steroid changes affect human brain functional connectivity, which could be obtained by resting-state fMRI (RS-fMRI). Nevertheless, RS studies on the menstrual cycle (MC) are underrepresented and yield inconsistent results. We attribute these inconsistencies to the use of various methods in exploratory approaches and small sample sizes. Hormonal fluctuations along the MC likely elicit subtle changes that, however, may still have profound impact on network dynamics when affecting key brain nodes. To address these issues, we propose a ROI-based multimodal analysis approach focusing on areas of high functional relevance to adequately capture these changes. To that end, sixty naturally cycling women underwent RS-fMRI in three different cycle phases and we performed the following analyses: (1) group-independent component analyses to identify intrinsic connectivity networks, (2) eigenvector centrality (EC) as a measure of centrality in the global connectivity hierarchy, (3) amplitude of low-frequency fluctuations (ALFF) as a measure of oscillatory activity and (4) seed-based analyses to investigate functional connectivity from the ROIs. For (2)–(4), we applied a hypothesis-driven ROI approach in the hippocampus, caudate and putamen. In the luteal phase, we found (1) decreased intrinsic connectivity of the right angular gyrus with the default mode network, (2) heightened EC for the hippocampus, and (3) increased ALFF for the caudate. Furthermore, we observed (4) stronger putamen–thalamic connectivity during the luteal phase and stronger fronto-striatal connectivity during the pre-ovulatory phase. This hormonal modulation of connectivity dynamics may underlie behavioural, emotional and sensorimotor changes along the MC.
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Affiliation(s)
- Esmeralda Hidalgo-Lopez
- Department of Psychology and Centre for Cognitive Neuroscience, University of Salzburg, Hellbrunnerstr. 34, 5020, Salzburg, Austria.
| | - Karsten Mueller
- Methods and Development Group Nuclear Magnetic Resonance, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstrasse 1a, 04103, Leipzig, Germany
| | - TiAnni Harris
- Department of Psychology and Centre for Cognitive Neuroscience, University of Salzburg, Hellbrunnerstr. 34, 5020, Salzburg, Austria
| | - Markus Aichhorn
- Department of Psychology and Centre for Cognitive Neuroscience, University of Salzburg, Hellbrunnerstr. 34, 5020, Salzburg, Austria
| | - Julia Sacher
- Research Group EGG (Emotions and neuroimaGinG)-Laboratory, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstrasse 1a, 04103, Leipzig, Germany.,Clinic for Cognitive Neurology, University Hospital Leipzig, Liebigstrasse 16, 04103, Leipzig, Germany
| | - Belinda Pletzer
- Department of Psychology and Centre for Cognitive Neuroscience, University of Salzburg, Hellbrunnerstr. 34, 5020, Salzburg, Austria.
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181
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Dufford AJ, Kim P, Evans GW. The impact of childhood poverty on brain health: Emerging evidence from neuroimaging across the lifespan. INTERNATIONAL REVIEW OF NEUROBIOLOGY 2020; 150:77-105. [DOI: 10.1016/bs.irn.2019.12.001] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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182
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Blair KS, Bashford-Largo J, Shah N, Lukoff J, Elowsky J, Vogel S, Emmert A, Zhang R, Dobbertin M, Pollak S, Blair JR. Sexual Abuse in Adolescents Is Associated With Atypically Increased Responsiveness Within Regions Implicated in Self-Referential and Emotional Processing to Approaching Animate Threats. Front Psychiatry 2020; 11:345. [PMID: 32612545 PMCID: PMC7308525 DOI: 10.3389/fpsyt.2020.00345] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/05/2019] [Accepted: 04/06/2020] [Indexed: 11/13/2022] Open
Abstract
Childhood sexual abuse is associated with significant subsequent pathology and neurodevelopmental disruption. In particular, childhood sexual abuse has been associated with heightened threat sensitivity. However, little work has directly investigated this issue. In this study, we examine the association of childhood sexual abuse to neural and behavioral responses to looming, threatening face stimuli. The study involved 23 adolescents with significant past sexual abuse and 24 comparison individuals matched on IQ, age, and sex. Participants were scanned during a looming threat task that involved negative and neutral, human faces and animals that appeared to either loom toward or recede from the participant. We found that adolescents who had been previously subjected to sexual abuse, relative to comparison adolescents, showed increased neural responses to threatening looming stimuli in regions including rostral and superior frontal gyrus as well as posterior cingulate gyrus. In addition, they were significantly more slowed by looming stimuli, particularly if these were human faces, than adolescents who had not been exposed. These data demonstrate that prior sexual abuse was associated with heightened neural responsiveness to looming threats in a series of regions beyond the amygdala. These data are interpreted within models of rostromedial frontal and posterior cingulate cortices that stress their role in self-referential emotional processing and emotional maintenance.
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Affiliation(s)
- Karina S Blair
- Center for Neurobehavioral Research, Boys Town National Research Hospital, Boys Town, NE, United States
| | - Johannah Bashford-Largo
- Center for Neurobehavioral Research, Boys Town National Research Hospital, Boys Town, NE, United States
| | - Niraj Shah
- Center for Neurobehavioral Research, Boys Town National Research Hospital, Boys Town, NE, United States
| | - Jennie Lukoff
- Center for Neurobehavioral Research, Boys Town National Research Hospital, Boys Town, NE, United States
| | - Jaimie Elowsky
- Center for Neurobehavioral Research, Boys Town National Research Hospital, Boys Town, NE, United States
| | - Steven Vogel
- Center for Neurobehavioral Research, Boys Town National Research Hospital, Boys Town, NE, United States
| | - Amanda Emmert
- Department of Psychiatry, Creighton University School of Medicine, Omaha, NE, United States
| | - Ru Zhang
- Center for Neurobehavioral Research, Boys Town National Research Hospital, Boys Town, NE, United States
| | - Matthew Dobbertin
- Center for Neurobehavioral Research, Boys Town National Research Hospital, Boys Town, NE, United States
| | - Seth Pollak
- Department of Psychology, University of Wisconsin, Madison, WI, United States
| | - James R Blair
- Center for Neurobehavioral Research, Boys Town National Research Hospital, Boys Town, NE, United States
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183
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Bowring A, Telschow F, Schwartzman A, Nichols TE. Spatial confidence sets for raw effect size images. Neuroimage 2019; 203:116187. [PMID: 31533067 PMCID: PMC6854455 DOI: 10.1016/j.neuroimage.2019.116187] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2019] [Revised: 09/09/2019] [Accepted: 09/11/2019] [Indexed: 01/22/2023] Open
Abstract
The mass-univariate approach for functional magnetic resonance imaging (fMRI) analysis remains a widely used statistical tool within neuroimaging. However, this method suffers from at least two fundamental limitations: First, with sufficient sample sizes there is high enough statistical power to reject the null hypothesis everywhere, making it difficult if not impossible to localize effects of interest. Second, with any sample size, when cluster-size inference is used a significant p-value only indicates that a cluster is larger than chance. Therefore, no notion of confidence is available to express the size or location of a cluster that could be expected with repeated sampling from the population. In this work, we address these issues by extending on a method proposed by Sommerfeld et al. (2018) (SSS) to develop spatial Confidence Sets (CSs) on clusters found in thresholded raw effect size maps. While hypothesis testing indicates where the null, i.e. a raw effect size of zero, can be rejected, the CSs give statements on the locations where raw effect sizes exceed, and fall short of, a non-zero threshold, providing both an upper and lower CS. While the method can be applied to any mass-univariate general linear model, we motivate the method in the context of blood-oxygen-level-dependent (BOLD) fMRI contrast maps for inference on percentage BOLD change raw effects. We propose several theoretical and practical implementation advancements to the original method formulated in SSS, delivering a procedure with superior performance in sample sizes as low as N=60. We validate the method with 3D Monte Carlo simulations that resemble fMRI data. Finally, we compute CSs for the Human Connectome Project working memory task contrast images, illustrating the brain regions that show a reliable %BOLD change for a given %BOLD threshold.
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Affiliation(s)
- Alexander Bowring
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Fabian Telschow
- Division of Biostatistics, University of California, San Diego, CA, USA
| | - Armin Schwartzman
- Division of Biostatistics, University of California, San Diego, CA, USA; Halicioğlu Data Science Institute, University of California, San Diego, USA
| | - Thomas E Nichols
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, Oxford, UK; Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Department of Statistics, University of Warwick, Coventry, UK.
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184
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Boukrina O, Kucukboyaci NE, Dobryakova E. Considerations of power and sample size in rehabilitation research. Int J Psychophysiol 2019; 154:6-14. [PMID: 31655185 DOI: 10.1016/j.ijpsycho.2019.08.009] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2018] [Revised: 05/22/2019] [Accepted: 08/23/2019] [Indexed: 01/26/2023]
Abstract
With the current emphasis on power and reproducibility, pressures are rising to increase sample sizes in rehabilitation research in order to reflect more accurate effect estimation and generalizable results. The conventional way of increasing power by enrolling more participants is less feasible in some fields of research. In particular, rehabilitation research faces considerable challenges in achieving this goal. We describe the specific challenges to increasing power by recruiting large sample sizes and obtaining large effects in rehabilitation research. Specifically, we discuss how variability within clinical populations, lack of common standards for selecting appropriate control groups; potentially reduced reliability of measurements of brain function in individuals recovering from a brain injury; biases involved in a priori effect size estimation, and higher budgetary and staffing requirements can influence considerations of sample and effect size in rehabilitation. We also describe solutions to these challenges, such as increased sampling per participant, improving experimental control, appropriate analyses, transparent result reporting and using innovative ways of harnessing the inherent variability of clinical populations. These solutions can improve statistical power and produce reliable and valid results even in the face of limited availability of large samples.
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Affiliation(s)
- Olga Boukrina
- Center for Stroke Rehabilitation Research, Kessler Foundation, West Orange, NJ, USA; Department of Physical Medicine and Rehabilitation, Rutgers-New Jersey Medical School, Newark, NJ, USA
| | - N Erkut Kucukboyaci
- Center for Traumatic Brain Injury Research, Kessler Foundation, East Hanover, NJ, USA; Department of Physical Medicine and Rehabilitation, Rutgers-New Jersey Medical School, Newark, NJ, USA
| | - Ekaterina Dobryakova
- Center for Traumatic Brain Injury Research, Kessler Foundation, East Hanover, NJ, USA; Department of Physical Medicine and Rehabilitation, Rutgers-New Jersey Medical School, Newark, NJ, USA.
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185
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Claussenius-Kalman H, Vaughn KA, Archila-Suerte P, Hernandez AE. Age of acquisition impacts the brain differently depending on neuroanatomical metric. Hum Brain Mapp 2019; 41:484-502. [PMID: 31600019 PMCID: PMC7267963 DOI: 10.1002/hbm.24817] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2018] [Revised: 08/23/2019] [Accepted: 09/23/2019] [Indexed: 12/24/2022] Open
Abstract
Although researchers generally agree that a certain set of brain areas underlie bilingual language processing, there is discrepancy regarding what effect timing of language acquisition has on these regions. We aimed to investigate the neuroanatomical correlates of age of acquisition (AoA), which has been examined previously, but with inconsistent results, likely influenced by methodological differences across studies. We analyzed gray matter density, volume, and thickness using whole-brain linear models in 334 bilinguals and monolinguals. Neuroanatomical correlates of AoA differed depending on gray matter metric. Relative to early bilinguals, late bilinguals had thicker cortex in language processing and cognitive control regions, and greater density in multiple frontal areas and the right middle temporal and supramarginal gyri. Early bilinguals had greater volume than late bilinguals in the left middle temporal gyrus. Overall, volume was the least sensitive to AoA-related differences. Multiple regions not classically implicated in dual-language processing were also found, which highlights the important role of whole-brain analyses in neuroscience. This is the first study to investigate AoA and gray matter thickness, volume, and density all in the same sample. We conclude that cognitive models of bilingualism should consider the roles of development and neuroanatomical metric in driving our understanding of bilingual and monolingual language organization.
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Affiliation(s)
| | - Kelly A Vaughn
- Department of Psychology, University of Houston, Houston, Texas
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186
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De Pauw R, Coppieters I, Caeyenberghs K, Kregel J, Aerts H, Lenoir D, Cagnie B. Associations between brain morphology and motor performance in chronic neck pain: A whole-brain surface-based morphometry approach. Hum Brain Mapp 2019; 40:4266-4278. [PMID: 31222905 PMCID: PMC6865716 DOI: 10.1002/hbm.24700] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2018] [Revised: 02/27/2019] [Accepted: 05/29/2019] [Indexed: 12/15/2022] Open
Abstract
Changes in brain morphology are hypothesized to be an underlying process that drive the widespread pain and motor impairment in patients with chronic neck pain. However, no earlier research assessed whole-brain cortical morphology in these patients. This case-control study assesses group-differences in whole-brain morphology between female healthy controls (HC; n = 34), and female patients with chronic idiopathic neck pain (CINP; n = 37) and whiplash-associated disorders (CWAD; n = 39). Additionally, the associations between whole-brain morphology and motor performance including balance, strength, and neuromuscular control were assessed. Cortical volume, thickness, and surface area were derived from high resolution T1-weighted images. T2*-weighted images were obtained to exclude traumatic brain injury. Vertex-wise general-linear-model-analysis revealed cortical thickening in the left precuneus and increased volume in the left superior parietal gyrus of patients with CINP compared to HC, and cortical thickening of the left superior parietal gyrus compared to HC and CWAD. Patients with CWAD showed a smaller cortical volume in the right precentral and superior temporal gyrus compared to HC. ANCOVA-analysis revealed worse neuromuscular control in CWAD compared to HC and CINP, and in CINP compared to HC. Patients with CWAD showed decreased levels of strength and sway area compared to CINP and HC. Partial correlation analysis revealed significant associations between the volume of the precentral gyrus, and neuromuscular control and strength together with an association between the volume of the superior temporal gyrus and strength. Our results emphasize the role of altered gray matter alterations in women with chronic neck pain, and its association with pain and motor impairment.
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Affiliation(s)
- Robby De Pauw
- Department of Rehabilitation Sciences, Faculty of Medicine and Health SciencesGhent UniversityGhentBelgium
| | - Iris Coppieters
- Physiotherapy‐ Human Physiology‐ and Anatomy KIMAVrije Universiteit BrusselBrusselsBelgium
- Pain in Motion International Research Group
| | - Karen Caeyenberghs
- School of Psychology, Faculty of Health SciencesAustralian Catholic UniversityBrisbaneQueenslandAustralia
| | - Jeroen Kregel
- Department of Rehabilitation Sciences, Faculty of Medicine and Health SciencesGhent UniversityGhentBelgium
- Physiotherapy‐ Human Physiology‐ and Anatomy KIMAVrije Universiteit BrusselBrusselsBelgium
- Pain in Motion International Research Group
| | - Hannelore Aerts
- Department of Data Analysis, Faculty of Psychology and Educational SciencesGhent UniversityGhentBelgium
| | - Dorine Lenoir
- Department of Rehabilitation Sciences, Faculty of Medicine and Health SciencesGhent UniversityGhentBelgium
- Physiotherapy‐ Human Physiology‐ and Anatomy KIMAVrije Universiteit BrusselBrusselsBelgium
- Pain in Motion International Research Group
| | - Barbara Cagnie
- Department of Rehabilitation Sciences, Faculty of Medicine and Health SciencesGhent UniversityGhentBelgium
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187
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Chen G, Xiao Y, Taylor PA, Rajendra JK, Riggins T, Geng F, Redcay E, Cox RW. Handling Multiplicity in Neuroimaging Through Bayesian Lenses with Multilevel Modeling. Neuroinformatics 2019; 17:515-545. [PMID: 30649677 PMCID: PMC6635105 DOI: 10.1007/s12021-018-9409-6] [Citation(s) in RCA: 45] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Here we address the current issues of inefficiency and over-penalization in the massively univariate approach followed by the correction for multiple testing, and propose a more efficient model that pools and shares information among brain regions. Using Bayesian multilevel (BML) modeling, we control two types of error that are more relevant than the conventional false positive rate (FPR): incorrect sign (type S) and incorrect magnitude (type M). BML also aims to achieve two goals: 1) improving modeling efficiency by having one integrative model and thereby dissolving the multiple testing issue, and 2) turning the focus of conventional null hypothesis significant testing (NHST) on FPR into quality control by calibrating type S errors while maintaining a reasonable level of inference efficiency. The performance and validity of this approach are demonstrated through an application at the region of interest (ROI) level, with all the regions on an equal footing: unlike the current approaches under NHST, small regions are not disadvantaged simply because of their physical size. In addition, compared to the massively univariate approach, BML may simultaneously achieve increased spatial specificity and inference efficiency, and promote results reporting in totality and transparency. The benefits of BML are illustrated in performance and quality checking using an experimental dataset. The methodology also avoids the current practice of sharp and arbitrary thresholding in the p-value funnel to which the multidimensional data are reduced. The BML approach with its auxiliary tools is available as part of the AFNI suite for general use.
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Affiliation(s)
- Gang Chen
- Scientific and Statistical Computing Core, National Institute of Mental Health, Bethesda, MD, USA.
| | - Yaqiong Xiao
- Department of Psychology, University of Maryland, College Park, MD, 20742, USA
| | - Paul A Taylor
- Scientific and Statistical Computing Core, National Institute of Mental Health, Bethesda, MD, USA
| | - Justin K Rajendra
- Scientific and Statistical Computing Core, National Institute of Mental Health, Bethesda, MD, USA
| | - Tracy Riggins
- Department of Psychology, University of Maryland, College Park, MD, 20742, USA
| | - Fengji Geng
- Department of Psychology, University of Maryland, College Park, MD, 20742, USA
| | - Elizabeth Redcay
- Department of Psychology, University of Maryland, College Park, MD, 20742, USA
| | - Robert W Cox
- Scientific and Statistical Computing Core, National Institute of Mental Health, Bethesda, MD, USA
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188
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Blain B, Schmit C, Aubry A, Hausswirth C, Le Meur Y, Pessiglione M. Neuro-computational Impact of Physical Training Overload on Economic Decision-Making. Curr Biol 2019; 29:3289-3297.e4. [PMID: 31564497 DOI: 10.1016/j.cub.2019.08.054] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2019] [Revised: 04/26/2019] [Accepted: 08/20/2019] [Indexed: 12/17/2022]
Abstract
Overtraining syndrome is a form of burnout, defined in endurance athletes by unexplained performance drop associated with intense fatigue sensation. Our working hypothesis is that the form of fatigue resulting from physical training overload might share some neural underpinnings with the form of fatigue observed after prolonged intellectual work, which was previously shown to affect the cognitive control brain system. Indeed, cognitive control may be required to prevent any impulsive behavior, including stopping physical effort when it hurts, despite the long-term goal of improving performance through intense training. To test this hypothesis, we induced a mild form of overtraining in a group of endurance athletes, which we compared to a group of normally trained athletes on behavioral tasks performed during fMRI scanning. At the behavioral level, training overload enhanced impulsivity in economic choice, which was captured by a bias favoring immediate over delayed rewards in our computational model. At the neural level, training overload resulted in diminished activation of the lateral prefrontal cortex, a key region of the cognitive control system, during economic choice. Our results therefore provide causal evidence for a functional link between enduring physical exercise and exerting cognitive control. Besides, the concept of cognitive control fatigue bridges the functional consequences of excessive physical training and intellectual work into a single neuro-computational mechanism, which might contribute to other clinical forms of burnout syndromes.
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Affiliation(s)
- Bastien Blain
- Motivation, Brain and Behavior Team, Centre de NeuroImagerie de Recherche, Institut du Cerveau et de la Moelle épinière, Hôpital de la Pitié-Salpêtrière, 75013 Paris, France; INSERM UMRS 1127, CNRS UMR 7225, Sorbonne Universités, 75005 Paris, France; Centre d'Economie de la Sorbonne, 75013 Paris, France; Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College, WC1B 5EH London, UK.
| | - Cyril Schmit
- Research Department, Laboratory of Sport, Expertise and Performance (EA 7370), French Institute of Sport, Expertise and Performance (INSEP), 75012 Paris, France; Laboratory LAMHESS (EA6312), University of Nice Sophia-Antipolis, 06108 Nice, France
| | - Anaël Aubry
- Research Department, Laboratory of Sport, Expertise and Performance (EA 7370), French Institute of Sport, Expertise and Performance (INSEP), 75012 Paris, France
| | - Christophe Hausswirth
- Laboratory LAMHESS (EA6312), University of Nice Sophia-Antipolis, 06108 Nice, France
| | - Yann Le Meur
- Research Department, Laboratory of Sport, Expertise and Performance (EA 7370), French Institute of Sport, Expertise and Performance (INSEP), 75012 Paris, France; Laboratory LAMHESS (EA6312), University of Nice Sophia-Antipolis, 06108 Nice, France
| | - Mathias Pessiglione
- Motivation, Brain and Behavior Team, Centre de NeuroImagerie de Recherche, Institut du Cerveau et de la Moelle épinière, Hôpital de la Pitié-Salpêtrière, 75013 Paris, France; INSERM UMRS 1127, CNRS UMR 7225, Sorbonne Universités, 75005 Paris, France.
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189
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Lake EMR, Finn ES, Noble SM, Vanderwal T, Shen X, Rosenberg MD, Spann MN, Chun MM, Scheinost D, Constable RT. The Functional Brain Organization of an Individual Allows Prediction of Measures of Social Abilities Transdiagnostically in Autism and Attention-Deficit/Hyperactivity Disorder. Biol Psychiatry 2019; 86:315-326. [PMID: 31010580 PMCID: PMC7311928 DOI: 10.1016/j.biopsych.2019.02.019] [Citation(s) in RCA: 67] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2018] [Revised: 02/01/2019] [Accepted: 02/02/2019] [Indexed: 12/17/2022]
Abstract
BACKGROUND Autism spectrum disorder and attention-deficit/hyperactivity disorder (ADHD) are associated with complex changes as revealed by functional magnetic resonance imaging. To date, neuroimaging-based models are not able to characterize individuals with sufficient sensitivity and specificity. Further, although evidence shows that ADHD traits occur in individuals with autism spectrum disorder, and autism spectrum disorder traits in individuals with ADHD, the neurofunctional basis of the overlap is undefined. METHODS Using individuals from the Autism Brain Imaging Data Exchange and ADHD-200, we apply a data-driven, subject-level approach, connectome-based predictive modeling, to resting-state functional magnetic resonance imaging data to identify brain-behavior associations that are predictive of symptom severity. We examine cross-diagnostic commonalities and differences. RESULTS Using leave-one-subject-out and split-half analyses, we define networks that predict Social Responsiveness Scale, Autism Diagnostic Observation Schedule, and ADHD Rating Scale scores and confirm that these networks generalize to novel subjects. Networks share minimal overlap of edges (<2%) but some common regions of high hubness (Brodmann areas 10, 11, and 21, cerebellum, and thalamus). Further, predicted Social Responsiveness Scale scores for individuals with ADHD are linked to ADHD symptoms, supporting the hypothesis that brain organization relevant to autism spectrum disorder severity shares a component associated with attention in ADHD. Predictive connections and high-hubness regions are found within a wide range of brain areas and across conventional networks. CONCLUSIONS An individual's functional connectivity profile contains information that supports dimensional, nonbinary classification in autism spectrum disorder and ADHD. Furthermore, we can determine disorder-specific and shared neurofunctional pathology using our method.
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Affiliation(s)
- Evelyn M R Lake
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, Yale University, New Haven, Connecticut.
| | - Emily S Finn
- Section on Functional Imaging Methods, National Institute of Mental Health, Bethesda, Maryland
| | - Stephanie M Noble
- Interdepartmental Neuroscience Program, Yale School of Medicine, Yale University, New Haven, Connecticut
| | - Tamara Vanderwal
- Yale Child Study Center, Yale School of Medicine, Yale University, New Haven, Connecticut
| | - Xilin Shen
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, Yale University, New Haven, Connecticut
| | - Monica D Rosenberg
- Department of Psychology, Yale School of Medicine, Yale University, New Haven, Connecticut; Department of Psychology, University of Chicago, Chicago, Illinois
| | - Marisa N Spann
- Department of Psychiatry, College of Physicians and Surgeons, Columbia University, New York, New York
| | - Marvin M Chun
- Interdepartmental Neuroscience Program, Yale School of Medicine, Yale University, New Haven, Connecticut; Department of Psychology, Yale School of Medicine, Yale University, New Haven, Connecticut; Department of Neurobiology, Yale School of Medicine, Yale University, New Haven, Connecticut
| | - Dustin Scheinost
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, Yale University, New Haven, Connecticut
| | - R Todd Constable
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, Yale University, New Haven, Connecticut; Interdepartmental Neuroscience Program, Yale School of Medicine, Yale University, New Haven, Connecticut; Department of Neurosurgery, Yale School of Medicine, Yale University, New Haven, Connecticut
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190
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Neuroimaging of pain in animal models: a review of recent literature. Pain Rep 2019; 4:e732. [PMID: 31579844 PMCID: PMC6728006 DOI: 10.1097/pr9.0000000000000732] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2018] [Revised: 02/06/2019] [Accepted: 02/12/2019] [Indexed: 01/19/2023] Open
Abstract
Neuroimaging of pain in animals allows us to better understand mechanisms of pain processing and modulation. In this review, we discuss recently published brain imaging studies in rats, mice, and monkeys, including functional magnetic resonance imaging (MRI), manganese-enhanced MRI, positron emission tomography, and electroencephalography. We provide an overview of innovations and limitations in neuroimaging techniques, as well as results of functional brain imaging studies of pain from January 1, 2016, to October 10, 2018. We then discuss how future investigations can address some bias and gaps in the field. Despite the limitations of neuroimaging techniques, the 28 studies reinforced that transition from acute to chronic pain entails considerable changes in brain function. Brain activations in acute pain were in areas more related to the sensory aspect of noxious stimulation, including primary somatosensory cortex, insula, cingulate cortex, thalamus, retrosplenial cortex, and periaqueductal gray. Pharmacological and nonpharmacological treatments modulated these brain regions in several pain models. On the other hand, in chronic pain models, brain activity was observed in regions commonly associated with emotion and motivation, including prefrontal cortex, anterior cingulate cortex, hippocampus, amygdala, basal ganglia, and nucleus accumbens. Neuroimaging of pain in animals holds great promise for advancing our knowledge of brain function and allowing us to expand human subject research. Additional research is needed to address effects of anesthesia, analysis approaches, sex bias and omission, and potential effects of development and aging.
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191
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Munson BA, Hernandez AE. Inconsistency of findings due to low power: A structural MRI study of bilingualism. BRAIN AND LANGUAGE 2019; 195:104642. [PMID: 31238122 PMCID: PMC8590736 DOI: 10.1016/j.bandl.2019.104642] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2019] [Revised: 06/08/2019] [Accepted: 06/08/2019] [Indexed: 06/09/2023]
Abstract
Research on structural brain differences between monolinguals and bilinguals remains inconsistent, and this has been proposed by some to be due in part to inadequate sample sizes. The aim of the present study is to reveal the expected degrees of uncertainty among neuroimaging findings by analyzing random samples of varying sizes from a larger-than-average sample. Bilinguals (n = 216) were compared with monolinguals (n = 146) using grey matter volume measures across region-of-interest tests. Variability among findings were compared with the true full-sample findings, and taken in the context of expected differences within the larger bilingualism neuroimaging literature. Results demonstrate excessive variability across the lowest sample sizes (e.g. samples totaling 20-80 participants), and this is explored through the trends of subsample outcomes and effect sizes across sample sizes. The results of this study illustrate the influences of power on expected variability among sample findings.
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Affiliation(s)
- Brandin A Munson
- Department of Health & Human Performance, University of Houston, United States.
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192
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The superior longitudinal fasciculus and its functional triple-network mechanisms in brooding. NEUROIMAGE-CLINICAL 2019; 24:101935. [PMID: 31352219 PMCID: PMC6664225 DOI: 10.1016/j.nicl.2019.101935] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/02/2019] [Revised: 07/10/2019] [Accepted: 07/13/2019] [Indexed: 12/16/2022]
Abstract
Brooding, which refers to a repetitive focus on one's distress, is associated with functional connectivity within Default-Mode, Salience, and Executive-Control networks (DMN; SN; ECN), comprising the so-called "triple-network" of attention. Individual differences in brain structure that might perseverate dysfunctional connectivity of brain networks associated with brooding are less clear, however. Using diffusion and functional Magnetic Resonance Imaging, we explored multimodal relationships between brooding severity, white-matter microstructure, and resting-state functional connectivity in depressed adults (N = 32-44), and then examined whether findings directly replicated in a demographically-similar, independent sample (N = 36-45). Among the fully-replicated results, three core findings emerged. First, brooding severity is associated with functional integration and segregation of the triple-network, particularly with a Precuneal subnetwork of the DMN. Second, microstructural asymmetry of the Superior Longitudinal Fasciculus (SLF) provides a robust structural connectivity basis for brooding and may account for over 20% of its severity (Discovery: adj. R2 = 0.18; Replication: adj. R2 = 0.22; MSE = 0.06, Predictive R2 = 0.22). Finally, microstructure of the right SLF and auxiliary white-matter is associated with the functional connectivity correlates of brooding, both within and between components of the triple-network (Discovery: adj. R2 = 0.21; Replication: adj. R2 = 0.18; MSE = 0.03, Predictive R2 = 0.21-0.22). By cross-validating multimodal discovery with replication, the present findings help to reproducibly unify disparate perspectives of brooding etiology. Based on that synthesis, our study reformulates brooding as a microstructural-functional connectivity neurophenotype.
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193
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Horien C, Greene AS, Constable RT, Scheinost D. Regions and Connections: Complementary Approaches to Characterize Brain Organization and Function. Neuroscientist 2019; 26:117-133. [PMID: 31304866 PMCID: PMC7079335 DOI: 10.1177/1073858419860115] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Functional magnetic resonance imaging has proved to be a powerful tool to characterize spatiotemporal patterns of human brain activity. Analysis methods broadly fall into two camps: those summarizing properties of a region and those measuring interactions among regions. Here we pose an unappreciated question in the field: What are the strengths and limitations of each approach to study fundamental neural processes? We explore the relative utility of region- and connection-based measures in the context of three topics of interest: neurobiological relevance, brain-behavior relationships, and individual differences in brain organization. In each section, we offer illustrative examples. We hope that this discussion offers a novel and useful framework to support efforts to better understand the macroscale functional organization of the brain and how it relates to behavior.
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Affiliation(s)
- Corey Horien
- Interdepartmental Neuroscience Program, Yale University School of Medicine, New Haven, CT, USA
| | - Abigail S Greene
- Interdepartmental Neuroscience Program, Yale University School of Medicine, New Haven, CT, USA
| | - R Todd Constable
- Interdepartmental Neuroscience Program, Yale University School of Medicine, New Haven, CT, USA.,Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA.,Department of Neurosurgery, Yale University School of Medicine, New Haven, CT, USA
| | - Dustin Scheinost
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA.,The Child Study Center, Yale University School of Medicine, New Haven, CT, USA.,Department of Statistics and Data Science, Yale University, USA
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194
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Peters L, Ansari D. Are specific learning disorders truly specific, and are they disorders? Trends Neurosci Educ 2019; 17:100115. [PMID: 31685130 DOI: 10.1016/j.tine.2019.100115] [Citation(s) in RCA: 52] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2018] [Revised: 05/30/2019] [Accepted: 07/05/2019] [Indexed: 12/12/2022]
Abstract
Specific learning disorders, such as dyslexia and dyscalculia, are frequently studied to inform our understanding of cognitive development, genetic mechanisms and brain function. In this Opinion Paper, we discuss limitations of this research approach, including the use of arbitrary criteria to select groups of children, heterogeneity within groups and overlap between domains of learning. By drawing on evidence from cognitive science, neuroscience and genetics, we propose an alternative, dimensional framework. We argue that we need to overcome the problems associated with a categorical approach by taking into account interacting factors at multiple levels of analysis that are associated with overlapping rather than entirely distinct domains of learning. We conclude that this research strategy will allow for a richer understanding of learning and development.
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Affiliation(s)
- Lien Peters
- Numerical Cognition Laboratory, Department of Psychology, Faculty of Education & Brain and Mind Institute, University of Western Ontario, Western Interdisciplinary Research Building, 1151 Richmond Street North, London, ON N6A 5B7, Canada.
| | - Daniel Ansari
- Numerical Cognition Laboratory, Department of Psychology, Faculty of Education & Brain and Mind Institute, University of Western Ontario, Western Interdisciplinary Research Building, 1151 Richmond Street North, London, ON N6A 5B7, Canada
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195
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Sanchis-Segura C, Ibañez-Gual MV, Adrián-Ventura J, Aguirre N, Gómez-Cruz ÁJ, Avila C, Forn C. Sex differences in gray matter volume: how many and how large are they really? Biol Sex Differ 2019; 10:32. [PMID: 31262342 PMCID: PMC6604149 DOI: 10.1186/s13293-019-0245-7] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Accepted: 06/06/2019] [Indexed: 11/17/2022] Open
Abstract
Background Studies assessing volumetric sex differences have provided contradictory results. Total intracranial volume (TIV) is a major confounding factor when estimating local volumes of interest (VOIs). We investigated how the number, size, and direction of sex differences in gray matter volume (GMv) vary depending on how TIV variation is statistically handled. Methods Sex differences in the GMv of 116 VOIs were assessed in 356 participants (171 females) without correcting for TIV variation or after adjusting the data with 5 different methods (VBM8 non-linear-only modulation, proportions, power-corrected-proportions, covariation, and the residuals method). The outcomes obtained with these procedures were compared to each other and to those obtained in three criterial subsamples, one comparing female-male pairs matched on their TIV and two others comparing groups of either females or males with large/small TIVs. Linear regression was used to quantify TIV effects on raw GMv and the efficacy of each method in controlling for them. Results Males had larger raw GMv than females in all brain areas, but these differences were driven by direct TIV-VOIs relationships and more closely resembled the differences observed between individuals with large/small TIVs of sex-specific subsamples than the sex differences observed in the TIV-matched subsample. All TIV-adjustment methods reduced the number of sex differences but their results were very different. The VBM8- and the proportions-adjustment methods inverted TIV-VOIs relationships and resulted in larger adjusted volumes in females, promoting sex differences largely attributable to TIV variation and very distinct from those observed in the TIV-matched subsample. The other three methods provided results unrelated to TIV and very similar to those of the TIV-matched subsample. In these datasets, sex differences were bidirectional and achieved satisfactory replication rates in 19 VOIs, but they were “small” (d < ∣0.38∣) and most of them faded away after correcting for multiple comparisons. Conclusions There is not just one answer to the question of how many and how large the sex differences in GMv are, but not all the possible answers are equally valid. When TIV effects are ruled out using appropriate adjustment methods, few sex differences (if any) remain statistically significant, and their size is quite reduced. Electronic supplementary material The online version of this article (10.1186/s13293-019-0245-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Carla Sanchis-Segura
- Departament de Psicologia bàsica, clínica i psicobiologia, Universitat Jaume I, Castelló, Spain.
| | | | - Jesús Adrián-Ventura
- Departament de Psicologia bàsica, clínica i psicobiologia, Universitat Jaume I, Castelló, Spain
| | - Naiara Aguirre
- Departament de Psicologia bàsica, clínica i psicobiologia, Universitat Jaume I, Castelló, Spain
| | | | - César Avila
- Departament de Psicologia bàsica, clínica i psicobiologia, Universitat Jaume I, Castelló, Spain
| | - Cristina Forn
- Departament de Psicologia bàsica, clínica i psicobiologia, Universitat Jaume I, Castelló, Spain
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196
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Seretny M, Murray SR, Whitaker L, Murnane J, Whalley H, Pernet C, Horne AW. The use of brain functional magnetic resonance imaging to determine the mechanism of action of gabapentin in managing chronic pelvic pain in women: a pilot study. BMJ Open 2019; 9:e026152. [PMID: 31248918 PMCID: PMC6597644 DOI: 10.1136/bmjopen-2018-026152] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/17/2023] Open
Abstract
OBJECTIVE To inform feasibility and design of a future randomised controlled trial (RCT) using brain functional MRI (fMRI) to determine the mechanism of action of gabapentin in managing chronic pelvic pain (CPP) in women. DESIGN Mechanistic study embedded in pilot RCT. SETTING University Hospital. PARTICIPANTS Twelve women (18-50 years) with CPP and no pelvic pathology (follow-up completed March 2014). INTERVENTION Oral gabapentin (300-2700 mg) or matched placebo. OUTCOME MEASURES After 12 weeks of treatment, participants underwent fMRI of the brain (Verio Siemens 3T MRI) during which noxious heat and punctate stimuli were delivered to the pelvis and arm. Outcome measures included pain (visual analogue scale), blood oxygen level dependent signal change and a semi-structured acceptability questionnaire at study completion prior to unblinding. RESULTS Full datasets were obtained for 11 participants. Following noxious heat to the abdomen, the gabapentin group (GG) had lower pain scores (Mean: 3.8 [SD 2.2]) than the placebo group (PG) (Mean: 5.8 [SD 0.9]). This was also the case for noxious heat to the arm with the GG having lower pain scores (Mean: 2.6 [SD 2.5]) than the PG (Mean: 6.2 [SD 1.1]). Seven out of 12 participants completed the acceptability questionnaire. 71% (five out of seven) described their participation in the fMRI study as positive; the remaining two rated it as a negative experience. CONCLUSIONS Incorporating brain fMRI in a future RCT to determine the mechanism of action of gabapentin in managing CPP in women was feasible and acceptable to most women. TRIAL REGISTRATION NUMBER ISRCTN70960777.
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Affiliation(s)
- Marta Seretny
- Edinburgh Cancer Research UK Centre, University of Edinburgh, Edinburgh, UK
| | - Sarah Rose Murray
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, UK
| | - Lucy Whitaker
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, UK
| | - Jonathan Murnane
- Queens Medical Research Institute and Edinburgh Imaging Facility (QMRI), University of Edinburgh, Edinburgh, UK
| | - Heather Whalley
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Cyril Pernet
- Queens Medical Research Institute and Edinburgh Imaging Facility (QMRI), University of Edinburgh, Edinburgh, UK
| | - Andrew W Horne
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, UK
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197
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Matheson GJ. We need to talk about reliability: making better use of test-retest studies for study design and interpretation. PeerJ 2019; 7:e6918. [PMID: 31179173 PMCID: PMC6536112 DOI: 10.7717/peerj.6918] [Citation(s) in RCA: 104] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2018] [Accepted: 04/07/2019] [Indexed: 12/31/2022] Open
Abstract
Neuroimaging, in addition to many other fields of clinical research, is both time-consuming and expensive, and recruitable patients can be scarce. These constraints limit the possibility of large-sample experimental designs, and often lead to statistically underpowered studies. This problem is exacerbated by the use of outcome measures whose accuracy is sometimes insufficient to answer the scientific questions posed. Reliability is usually assessed in validation studies using healthy participants, however these results are often not easily applicable to clinical studies examining different populations. I present a new method and tools for using summary statistics from previously published test-retest studies to approximate the reliability of outcomes in new samples. In this way, the feasibility of a new study can be assessed during planning stages, and before collecting any new data. An R package called relfeas also accompanies this article for performing these calculations. In summary, these methods and tools will allow researchers to avoid performing costly studies which are, by virtue of their design, unlikely to yield informative conclusions.
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Affiliation(s)
- Granville J. Matheson
- Department of Clinical Neuroscience, Center for Psychiatry Research, Karolinska Institutet and Stockholm County Council, Stockholm, Sweden
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198
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Owens MM, Hyatt CS, Gray JC, Carter NT, MacKillop J, Miller JD, Sweet LH. Cortical morphometry of the five-factor model of personality: findings from the Human Connectome Project full sample. Soc Cogn Affect Neurosci 2019; 14:381-395. [PMID: 30848280 PMCID: PMC6523439 DOI: 10.1093/scan/nsz017] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2018] [Revised: 02/24/2019] [Accepted: 03/05/2019] [Indexed: 12/30/2022] Open
Abstract
This study is a replication of an existing large study (N = 507) on the surface-based morphometric correlates of five-factor model (FFM) personality traits. The same methods were used as the original study in another large sample drawn from the same population (N = 597) with results then being aggregated from both samples (N = 1104), providing the largest investigation into the neuroanatomical correlates of FFM personality traits to date. Clusters of association between brain morphometry and each FFM trait are reported. For neuroticism, agreeableness, openness and conscientiousness clusters of association were found in the dorsolateral prefrontal cortex for at least one morphometric index. Morphometry in various other regions was also associated with each personality trait. While some regions found in the original study were confirmed in the replication and full samples, others were not, highlighting the importance of replicating even high-quality, well-powered studies. Effect sizes were very similar in the replication and whole samples as those found in the original study. As a whole, the current results provide the strongest evidence to date on the neuroanatomical correlates of personality and highlights challenges in using this approach to understanding the neural correlates of personality.
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Affiliation(s)
- Max M Owens
- Department of Psychology, University of Georgia, Athens, GA, USA
| | | | - Joshua C Gray
- Department of Medical and Clinical Psychology, Uniformed Services University, Bethesda, MD, USA
| | - Nathan T Carter
- Department of Psychology, University of Georgia, Athens, GA, USA
| | - James MacKillop
- Peter Boris Centre for Addiction Research, St. Joseph’s Healthcare Hamilton/McMaster University, West 5th Street, Hamilton, ON, Canada
| | - Joshua D Miller
- Department of Psychology, University of Georgia, Athens, GA, USA
| | - Lawrence H Sweet
- Department of Psychology, University of Georgia, Athens, GA, USA
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199
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Gentili C, Messerotti Benvenuti S, Lettieri G, Costa C, Cecchetti L. ROI and phobias: The effect of ROI approach on an ALE meta-analysis of specific phobias. Hum Brain Mapp 2019; 40:1814-1828. [PMID: 30548734 PMCID: PMC6865604 DOI: 10.1002/hbm.24492] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2018] [Revised: 11/23/2018] [Accepted: 11/28/2018] [Indexed: 12/22/2022] Open
Abstract
About 90% of fMRI findings on specific phobias (SP) include analysis of region of interest (ROI). This approach characterized by higher sensitivity may produce inflated results, particularly when findings are aggregated in meta-analytic maps. Here, we conducted a systematic review and activation likelihood estimation (ALE) meta-analysis on SP, testing the impact of the inclusion of ROI-based studies. ALE meta-analyses were carried out either including ROI-based results or focusing on whole-brain voxelwise studies exclusively. To assess the risk of bias in the neuroimaging field, we modified the Newcastle-Ottawa Scale (NOS) and measured the reliability of fMRI findings. Of the 31 selected investigations (564 patients and 485 controls) one-third did not motivate ROI selection: five studies did not report an explicit rationale, whereas four did not cite any specific reference in this regard. Analyses including ROI-based studies revealed differences between phobics and healthy subjects in several regions of the limbic circuit. However, when focusing on whole-brain analysis, only the anterior midcingulate cortex differentiated SP from controls. Notably, 13 studies were labeled with low risk of bias according to the adapted NOS. The inclusion of ROI-based results artificially inflates group differences in fMRI meta-analyses. Moreover, a priori, well-motivated selection of ROIs is desirable to improve quality and reproducibility in SP neuroimaging studies. Lastly, the use of modified NOS may represent a valuable way to assess and evaluate biases in fMRI studies: "low risk" of bias was reported for less than half of the included studies, indicating the need for better practices in fMRI.
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Affiliation(s)
- Claudio Gentili
- Department of General PsychologyUniversity of PadovaPadovaItaly
| | | | | | - Cristiano Costa
- Department of General PsychologyUniversity of PadovaPadovaItaly
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200
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Hong YW, Yoo Y, Han J, Wager TD, Woo CW. False-positive neuroimaging: Undisclosed flexibility in testing spatial hypotheses allows presenting anything as a replicated finding. Neuroimage 2019; 195:384-395. [PMID: 30946952 DOI: 10.1016/j.neuroimage.2019.03.070] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2018] [Revised: 03/27/2019] [Accepted: 03/28/2019] [Indexed: 11/27/2022] Open
Abstract
Hypothesis testing in neuroimaging studies relies heavily on treating named anatomical regions (e.g., "the amygdala") as unitary entities. Though data collection and analyses are conducted at the voxel level, inferences are often based on anatomical regions. The discrepancy between the unit of analysis and the unit of inference leads to ambiguity and flexibility in analyses that can create a false sense of reproducibility. For example, hypothesizing effects on "amygdala activity" does not provide a falsifiable and reproducible definition of precisely which voxels or which patterns of activation should be observed. Rather, it comprises a large number of unspecified sub-hypotheses, leaving room for flexible interpretation of findings, which we refer to as "model degrees of freedom." From a survey of 135 functional Magnetic Resonance Imaging studies in which researchers claimed replications of previous findings, we found that 42.2% of the studies did not report any quantitative evidence for replication such as activation peaks. Only 14.1% of the papers used exact coordinate-based or a priori pattern-based models. Of the studies that reported peak information, 42.9% of the 'replicated' findings had peak coordinates more than 15 mm away from the 'original' findings, suggesting that different brain locations were activated, even when studies claimed to replicate prior results. To reduce the flexible and qualitative region-level tests in neuroimaging studies, we recommend adopting quantitative spatial models and tests to assess the spatial reproducibility of findings. Techniques reviewed here include permutation tests on peak distance, Bayesian MANOVA, and a priori multivariate pattern-based models. These practices will help researchers to establish precise and falsifiable spatial hypotheses, promoting a cumulative science of neuroimaging.
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Affiliation(s)
- Yong-Wook Hong
- Center for Neuroscience Imaging Research, Institute for Basic Science, South Korea; Department of Biomedical Engineering, Sungkyunkwan University, South Korea
| | - Yejong Yoo
- Center for Neuroscience Imaging Research, Institute for Basic Science, South Korea; Department of Biology, Taylor University, United States
| | - Jihoon Han
- Center for Neuroscience Imaging Research, Institute for Basic Science, South Korea; Department of Biomedical Engineering, Sungkyunkwan University, South Korea
| | - Tor D Wager
- Department of Psychology and Neuroscience, University of Colorado Boulder, United States; Institute for Cognitive Sciences, University of Colorado Boulder, United States
| | - Choong-Wan Woo
- Center for Neuroscience Imaging Research, Institute for Basic Science, South Korea; Department of Biomedical Engineering, Sungkyunkwan University, South Korea.
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