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Northall A, Doehler J, Weber M, Vielhaber S, Schreiber S, Kuehn E. Layer-specific vulnerability is a mechanism of topographic map aging. Neurobiol Aging 2023; 128:17-32. [PMID: 37141729 DOI: 10.1016/j.neurobiolaging.2023.04.002] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Revised: 03/29/2023] [Accepted: 04/02/2023] [Indexed: 05/06/2023]
Abstract
Topographic maps form a critical feature of cortical organization, yet are poorly described with respect to their microstructure in the living aging brain. We acquired quantitative structural and functional 7T-MRI data from younger and older adults to characterize layer-wise topographic maps of the primary motor cortex (M1). Using parcellation-inspired techniques, we show that quantitative T1 and Quantitative Susceptibility Maps values of the hand, face, and foot areas differ significantly, revealing microstructurally distinct cortical fields in M1. We show that these fields are distinct in older adults and that myelin borders between them do not degenerate. We further show that the output layer 5 of M1 shows a particular vulnerability to age-related increased iron, while layer 5 and the superficial layer show increased diamagnetic substance, likely reflecting calcifications. Taken together, we provide a novel 3D model of M1 microstructure, where body parts form distinct structural units, but layers show specific vulnerability toward increased iron and calcium in older adults. Our findings have implications for understanding sensorimotor organization and aging, in addition to topographic disease spread.
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Affiliation(s)
- Alicia Northall
- Institute for Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University Magdeburg, Saxony-Anhalt, Germany.
| | - Juliane Doehler
- Institute for Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University Magdeburg, Saxony-Anhalt, Germany
| | - Miriam Weber
- Department of Neurology, Otto-von-Guericke University Magdeburg, Magdeburg, Saxony-Anhalt, Germany
| | - Stefan Vielhaber
- Department of Neurology, Otto-von-Guericke University Magdeburg, Magdeburg, Saxony-Anhalt, Germany
| | - Stefanie Schreiber
- Department of Neurology, Otto-von-Guericke University Magdeburg, Magdeburg, Saxony-Anhalt, Germany; German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Saxony-Anhalt, Germany; Center for Behavioral Brain Sciences (CBBS) Magdeburg, Magdeburg, Saxony-Anhalt, Germany
| | - Esther Kuehn
- Institute for Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University Magdeburg, Saxony-Anhalt, Germany; German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Saxony-Anhalt, Germany; Center for Behavioral Brain Sciences (CBBS) Magdeburg, Magdeburg, Saxony-Anhalt, Germany; Hertie Institute for Clinical Brain Research, Tübingen, Germany
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2
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The Dorsolateral Prefrontal Cortex Presents Structural Variations Associated with Empathy and Emotion Regulation in Psychotherapists. Brain Topogr 2022; 35:613-626. [DOI: 10.1007/s10548-022-00910-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2021] [Accepted: 08/09/2022] [Indexed: 11/02/2022]
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3
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Kharabian Masouleh S, Eickhoff SB, Maleki Balajoo S, Nicolaisen-Sobesky E, Thirion B, Genon S. Empirical facts from search for replicable associations between cortical thickness and psychometric variables in healthy adults. Sci Rep 2022; 12:13286. [PMID: 35918502 PMCID: PMC9345926 DOI: 10.1038/s41598-022-17556-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 07/27/2022] [Indexed: 11/08/2022] Open
Abstract
The study of associations between inter-individual differences in brain structure and behaviour has a long history in psychology and neuroscience. Many associations between psychometric data, particularly intelligence and personality measures and local variations of brain structure have been reported. While the impact of such reported associations often goes beyond scientific communities, resonating in the public mind, their replicability is rarely evidenced. Previously, we have shown that associations between psychometric measures and estimates of grey matter volume (GMV) result in rarely replicated findings across large samples of healthy adults. However, the question remains if these observations are at least partly linked to the multidetermined nature of the variations in GMV, particularly within samples with wide age-range. Therefore, here we extended those evaluations and empirically investigated the replicability of associations of a broad range of psychometric variables and cortical thickness in a large cohort of healthy young adults. In line with our observations with GMV, our current analyses revealed low likelihood of significant associations and their rare replication across independent samples. We here discuss the implications of these findings within the context of accumulating evidence of the general poor replicability of structural-brain-behaviour associations, and more broadly of the replication crisis.
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Affiliation(s)
- Shahrzad Kharabian Masouleh
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany.
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Somayeh Maleki Balajoo
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Eliana Nicolaisen-Sobesky
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | | | - Sarah Genon
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany.
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
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4
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Linking interindividual variability in brain structure to behaviour. Nat Rev Neurosci 2022; 23:307-318. [PMID: 35365814 DOI: 10.1038/s41583-022-00584-7] [Citation(s) in RCA: 73] [Impact Index Per Article: 36.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/14/2022] [Indexed: 12/15/2022]
Abstract
What are the brain structural correlates of interindividual differences in behaviour? More than a decade ago, advances in structural MRI opened promising new avenues to address this question. The initial wave of research then progressively led to substantial conceptual and methodological shifts, and a replication crisis unveiled the limitations of traditional approaches, which involved searching for associations between local measurements of neuroanatomy and behavioural variables in small samples of healthy individuals. Given these methodological issues and growing scepticism regarding the idea of one-to-one mapping of psychological constructs to brain regions, new perspectives emerged. These not only embrace the multivariate nature of brain structure-behaviour relationships and promote generalizability but also embrace the representation of the relationships between brain structure and behavioural data by latent dimensions of interindividual variability. Here, we examine the past and present of the study of brain structure-behaviour associations in healthy populations and address current challenges and open questions for future investigations.
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5
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Camilleri JA, Eickhoff SB, Weis S, Chen J, Amunts J, Sotiras A, Genon S. A machine learning approach for the factorization of psychometric data with application to the Delis Kaplan Executive Function System. Sci Rep 2021; 11:16896. [PMID: 34413412 PMCID: PMC8377093 DOI: 10.1038/s41598-021-96342-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 08/09/2021] [Indexed: 02/07/2023] Open
Abstract
While a replicability crisis has shaken psychological sciences, the replicability of multivariate approaches for psychometric data factorization has received little attention. In particular, Exploratory Factor Analysis (EFA) is frequently promoted as the gold standard in psychological sciences. However, the application of EFA to executive functioning, a core concept in psychology and cognitive neuroscience, has led to divergent conceptual models. This heterogeneity severely limits the generalizability and replicability of findings. To tackle this issue, in this study, we propose to capitalize on a machine learning approach, OPNMF (Orthonormal Projective Non-Negative Factorization), and leverage internal cross-validation to promote generalizability to an independent dataset. We examined its application on the scores of 334 adults at the Delis-Kaplan Executive Function System (D-KEFS), while comparing to standard EFA and Principal Component Analysis (PCA). We further evaluated the replicability of the derived factorization across specific gender and age subsamples. Overall, OPNMF and PCA both converge towards a two-factor model as the best data-fit model. The derived factorization suggests a division between low-level and high-level executive functioning measures, a model further supported in subsamples. In contrast, EFA, highlighted a five-factor model which reflects the segregation of the D-KEFS battery into its main tasks while still clustering higher-level tasks together. However, this model was poorly supported in the subsamples. Thus, the parsimonious two-factors model revealed by OPNMF encompasses the more complex factorization yielded by EFA while enjoying higher generalizability. Hence, OPNMF provides a conceptually meaningful, technically robust, and generalizable factorization for psychometric tools.
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Affiliation(s)
- J A Camilleri
- Institute of Neuroscience and Medicine (INM-7 Brain and Behaviour), Forschungszentrum Jülich, Jülich, Germany.
- Institute of Systems Neuroscience, Heinrich-Heine University, Düsseldorf, Germany.
| | - S B Eickhoff
- Institute of Neuroscience and Medicine (INM-7 Brain and Behaviour), Forschungszentrum Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Heinrich-Heine University, Düsseldorf, Germany
| | - S Weis
- Institute of Neuroscience and Medicine (INM-7 Brain and Behaviour), Forschungszentrum Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Heinrich-Heine University, Düsseldorf, Germany
| | - J Chen
- Institute of Neuroscience and Medicine (INM-7 Brain and Behaviour), Forschungszentrum Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Heinrich-Heine University, Düsseldorf, Germany
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou, China
| | - J Amunts
- Institute of Neuroscience and Medicine (INM-7 Brain and Behaviour), Forschungszentrum Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Heinrich-Heine University, Düsseldorf, Germany
| | - A Sotiras
- Mallinckrodt Institute of Radiology, Institute for Informatics, Washington University in Saint Louis, Saint Louis, USA
| | - S Genon
- Institute of Neuroscience and Medicine (INM-7 Brain and Behaviour), Forschungszentrum Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Heinrich-Heine University, Düsseldorf, Germany
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6
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Dump the "dimorphism": Comprehensive synthesis of human brain studies reveals few male-female differences beyond size. Neurosci Biobehav Rev 2021; 125:667-697. [PMID: 33621637 DOI: 10.1016/j.neubiorev.2021.02.026] [Citation(s) in RCA: 153] [Impact Index Per Article: 51.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 01/01/2021] [Accepted: 02/16/2021] [Indexed: 12/21/2022]
Abstract
With the explosion of neuroimaging, differences between male and female brains have been exhaustively analyzed. Here we synthesize three decades of human MRI and postmortem data, emphasizing meta-analyses and other large studies, which collectively reveal few reliable sex/gender differences and a history of unreplicated claims. Males' brains are larger than females' from birth, stabilizing around 11 % in adults. This size difference accounts for other reproducible findings: higher white/gray matter ratio, intra- versus interhemispheric connectivity, and regional cortical and subcortical volumes in males. But when structural and lateralization differences are present independent of size, sex/gender explains only about 1% of total variance. Connectome differences and multivariate sex/gender prediction are largely based on brain size, and perform poorly across diverse populations. Task-based fMRI has especially failed to find reproducible activation differences between men and women in verbal, spatial or emotion processing due to high rates of false discovery. Overall, male/female brain differences appear trivial and population-specific. The human brain is not "sexually dimorphic."
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7
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Santonja J, Martínez K, Román FJ, Escorial S, Quiroga MÁ, Álvarez-Linera J, Iturria-Medina Y, Santarnecchi E, Colom R. Brain resilience across the general cognitive ability distribution: Evidence from structural connectivity. Brain Struct Funct 2021; 226:845-859. [DOI: 10.1007/s00429-020-02213-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2020] [Accepted: 12/30/2020] [Indexed: 12/14/2022]
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8
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Linked patterns of biological and environmental covariation with brain structure in adolescence: a population-based longitudinal study. Mol Psychiatry 2021; 26:4905-4918. [PMID: 32444868 PMCID: PMC7981783 DOI: 10.1038/s41380-020-0757-x] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/02/2020] [Revised: 04/21/2020] [Accepted: 04/23/2020] [Indexed: 01/11/2023]
Abstract
Adolescence is a period of major brain reorganization shaped by biologically timed and by environmental factors. We sought to discover linked patterns of covariation between brain structural development and a wide array of these factors by leveraging data from the IMAGEN study, a longitudinal population-based cohort of adolescents. Brain structural measures and a comprehensive array of non-imaging features (relating to demographic, anthropometric, and psychosocial characteristics) were available on 1476 IMAGEN participants aged 14 years and from a subsample reassessed at age 19 years (n = 714). We applied sparse canonical correlation analyses (sCCA) to the cross-sectional and longitudinal data to extract modes with maximum covariation between neuroimaging and non-imaging measures. Separate sCCAs for cortical thickness, cortical surface area and subcortical volumes confirmed that each imaging phenotype was correlated with non-imaging features (sCCA r range: 0.30-0.65, all PFDR < 0.001). Total intracranial volume and global measures of cortical thickness and surface area had the highest canonical cross-loadings (|ρ| = 0.31-0.61). Age, physical growth and sex had the highest association with adolescent brain structure (|ρ| = 0.24-0.62); at baseline, further significant positive associations were noted for cognitive measures while negative associations were observed at both time points for prenatal parental smoking, life events, and negative affect and substance use in youth (|ρ| = 0.10-0.23). Sex, physical growth and age are the dominant influences on adolescent brain development. We highlight the persistent negative influences of prenatal parental smoking and youth substance use as they are modifiable and of relevance for public health initiatives.
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9
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Kharabian Masouleh S, Eickhoff SB, Zeighami Y, Lewis LB, Dahnke R, Gaser C, Chouinard-Decorte F, Lepage C, Scholtens LH, Hoffstaedter F, Glahn DC, Blangero J, Evans AC, Genon S, Valk SL. Influence of Processing Pipeline on Cortical Thickness Measurement. Cereb Cortex 2020; 30:5014-5027. [PMID: 32377664 PMCID: PMC7391418 DOI: 10.1093/cercor/bhaa097] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2019] [Revised: 03/21/2020] [Accepted: 03/23/2020] [Indexed: 11/13/2022] Open
Abstract
In recent years, replicability of neuroscientific findings, specifically those concerning correlates of morphological properties of gray matter (GM), have been subject of major scrutiny. Use of different processing pipelines and differences in their estimates of the macroscale GM may play an important role in this context. To address this issue, here, we investigated the cortical thickness estimates of three widely used pipelines. Based on analyses in two independent large-scale cohorts, we report high levels of within-pipeline reliability of the absolute cortical thickness-estimates and comparable spatial patterns of cortical thickness-estimates across all pipelines. Within each individual, absolute regional thickness differed between pipelines, indicating that in-vivo thickness measurements are only a proxy of actual thickness of the cortex, which shall only be compared within the same software package and thickness estimation technique. However, at group level, cortical thickness-estimates correlated strongly between pipelines, in most brain regions. The smallest between-pipeline correlations were observed in para-limbic areas and insula. These regions also demonstrated the highest interindividual variability and the lowest reliability of cortical thickness-estimates within each pipeline, suggesting that structural variations within these regions should be interpreted with caution.
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Affiliation(s)
- Shahrzad Kharabian Masouleh
- Research Centre Jülich, Institute of Neuroscience and Medicine (INM-7: Brain and Behavior), 52425, Jülich, Germany
| | - Simon B Eickhoff
- Research Centre Jülich, Institute of Neuroscience and Medicine (INM-7: Brain and Behavior), 52425, Jülich, Germany.,Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, 40225, Düsseldorf, Germany
| | - Yashar Zeighami
- Montreal Neurological Institute, McGill University, Quebec, H3A 2B4, Canada
| | - Lindsay B Lewis
- Montreal Neurological Institute, McGill University, Quebec, H3A 2B4, Canada
| | - Robert Dahnke
- Center of Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, 8000 Aarhus, Denmark.,Department of Psychiatry and Department of Neurology, Jena University Hospital, 07747 Jena, Germany
| | - Christian Gaser
- Department of Psychiatry and Department of Neurology, Jena University Hospital, 07747 Jena, Germany
| | | | - Claude Lepage
- Montreal Neurological Institute, McGill University, Quebec, H3A 2B4, Canada
| | | | - Felix Hoffstaedter
- Research Centre Jülich, Institute of Neuroscience and Medicine (INM-7: Brain and Behavior), 52425, Jülich, Germany
| | - David C Glahn
- Department of Psychiatry, Yale School of Medicine, New Haven, CT 06511, USA
| | - John Blangero
- South Texas Diabetes and Obesity Institute and Department of Human Genetics, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX 78520, USA
| | - Alan C Evans
- Montreal Neurological Institute, McGill University, Quebec, H3A 2B4, Canada
| | - Sarah Genon
- Research Centre Jülich, Institute of Neuroscience and Medicine (INM-7: Brain and Behavior), 52425, Jülich, Germany
| | - Sofie L Valk
- Research Centre Jülich, Institute of Neuroscience and Medicine (INM-7: Brain and Behavior), 52425, Jülich, Germany.,Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, 40225, Düsseldorf, Germany
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10
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Spanoudis G, Demetriou A. Mapping Mind-Brain Development: Towards a Comprehensive Theory. J Intell 2020; 8:E19. [PMID: 32357452 PMCID: PMC7713015 DOI: 10.3390/jintelligence8020019] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Revised: 04/13/2020] [Accepted: 04/20/2020] [Indexed: 12/12/2022] Open
Abstract
The relations between the developing mind and developing brain are explored. We outline a theory of intellectual development postulating that the mind comprises four systems of processes (domain-specific, attention and working memory, reasoning, and cognizance) developing in four cycles (episodic, realistic, rule-based, and principle-based representations, emerging at birth, 2, 6, and 11 years, respectively), with two phases in each. Changes in reasoning relate to processing efficiency in the first phase and working memory in the second phase. Awareness of mental processes is recycled with the changes in each cycle and drives their integration into the representational unit of the next cycle. Brain research shows that each type of processes is served by specialized brain networks. Domain-specific processes are rooted in sensory cortices; working memory processes are mainly rooted in hippocampal, parietal, and prefrontal cortices; abstraction and alignment processes are rooted in parietal, frontal, and prefrontal and medial cortices. Information entering these networks is available to awareness processes. Brain networks change along the four cycles, in precision, connectivity, and brain rhythms. Principles of mind-brain interaction are discussed.
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Affiliation(s)
- George Spanoudis
- Psychology Department, University of Cyprus, 1678 Nicosia, Cyprus
| | - Andreas Demetriou
- Department of Psychology, University of Nicosia, 1700 Nicosia, Cyprus;
- Cyprus Academy of Science, Letters, and Arts, 1700 Nicosia, Cyprus
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11
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Wang S, Zhao Y, Li J, Wang X, Luo K, Gong Q. Brain structure links trait conscientiousness to academic performance. Sci Rep 2019; 9:12168. [PMID: 31434943 PMCID: PMC6704183 DOI: 10.1038/s41598-019-48704-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2018] [Accepted: 07/31/2019] [Indexed: 02/05/2023] Open
Abstract
In the long history of identifying factors to predict academic performance, conscientiousness, a so-called ‘big five’ personality trait describing self-regulation and goal-directed behavior, has emerged as a stable predictor for this purpose. However, the neuroanatomical substrates of trait conscientiousness and the underlying brain mechanism linking trait conscientiousness and academic performance are still largely unknown. Here, we examined these issues in 148 high school students within the same grade by estimating cortical gray matter volume (GMV) utilizing a voxel-based morphometry method based on structural magnetic resonance imaging. A whole-brain regression analysis showed that trait conscientiousness was positively associated with the GMV in the bilateral superior parietal lobe (SPL) and was negatively associated with the GMV in the right middle frontal gyrus (MFG). Furthermore, mediation analysis revealed that trait conscientiousness mediated the influences of the SPL and MFG volume on academic performance. Importantly, our results persisted even when we adjusted for general intelligence, family socioeconomic status and ‘big five’ personality traits other than conscientiousness. Altogether, our study suggests that the GMV in the frontoparietal network is a neurostructural marker of adolescents’ conscientiousness and reveals a potential brain-personality-achievement pathway for predicting academic performance in which gray matter structures affect academic performance through trait conscientiousness.
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Affiliation(s)
- Song Wang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, China.,Department of Psychoradiology, Chengdu Mental Health Center, Chengdu, 610036, China.,Psychoradiology Research Unit of Chinese Academy of Medical Sciences (2018RU011), West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Yajun Zhao
- School of Sociology and Psychology, Southwest Minzu University, Chengdu, 610041, China
| | - Jingguang Li
- College of Education, Dali University, Dali, 671003, China
| | - Xu Wang
- School of Life Sciences, Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Kui Luo
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, China. .,Department of Psychoradiology, Chengdu Mental Health Center, Chengdu, 610036, China. .,Psychoradiology Research Unit of Chinese Academy of Medical Sciences (2018RU011), West China Hospital of Sichuan University, Chengdu, 610041, China.
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12
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Stussman BJ, Nahin RL, Čeko M. Fibromyalgia patients and healthy volunteers express difficulties and variability in rating experimental pain: a qualitative study. Scand J Pain 2018; 18:657-666. [PMID: 30098290 DOI: 10.1515/sjpain-2018-0085] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2018] [Accepted: 07/13/2018] [Indexed: 01/30/2023]
Abstract
Background and aims Despite the enormous body of literature spanning more than 50 years describing results of pain experiments, very few have used qualitative methods to explore subjects' thoughts while scoring experimental painful stimuli, and none in the available literature have used qualitative interviews to do so. The current study examined how participants in experimental pain research delineate pain ratings to better understand the unique influences of the experimental setting on pain scores. An additional aim was to highlight how individuals with fibromyalgia and healthy volunteers are differently influenced by characteristics of the experimental setting. Methods This was an inductive, qualitative study in which individual, semi-structured interviews were performed with 31 fibromyalgia patients and 44 healthy volunteers. Participants had taken part in a pain experiment during which a thermode was used to induce painful heat stimuli on two skin areas. There were two primary interview questions analyzed for this report: (1) "Thinking back to when you were getting the heat pain on your leg, what were you thinking about when deciding on your pain score?" and (2) Participants who said that it was difficult to decide on a pain score were asked to, "Describe what made it difficult to choose a number." Thematic analysis was used to generate conceptual categories from textual data and find common themes. Results Three notable differences were found between fibromyalgia patients and healthy volunteers: (1) using current daily pain as a benchmark was seen more in patients, (2) wanting to appear strong in front of the study investigators was more common in healthy volunteers, and (3) becoming mentally fatigued from rating many stimuli was more common for fibromyalgia patients. Thoughts while scoring pain included: (1) comparing with previous or current pain, (2) self-monitoring of one's ability to endure the pain, (3) focusing on the physical aspects of the pain, (4) knowing the experimental setting is safe, (5) focusing on the pain scale as an anchor, and (6) desire to appear strong. Additionally, five difficulties in scoring experimental pain were identified: (1) falling asleep, (2) mentally fatigued, (3) feeling as though they were guessing, (4) having to make a quick decision, and (5) difficulty in being consistent. Conclusions This study provides insights into the thoughts of participants in experimental pain research studies. Participants were distracted and influenced by the experimental setting and some factors differed for fibromyalgia patients versus healthy volunteers. Implications Understanding the ways in which the experimental setting influences pain ratings may help pain researchers better design and interpret studies. Researchers can use these findings to mitigate difficulties for participants in experimental research to add to its validity.
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Affiliation(s)
- Barbara J Stussman
- 6707 Democracy Boulevard, Suite 401, Bethesda, MD 20892, USA, Phone: +301 402-5867, Fax: +301-480-2419.,National Center for Complementary and Integrative Health, National Institutes of Health, Bethesda, MD 20814-9692, USA
| | - Richard L Nahin
- National Center for Complementary and Integrative Health, National Institutes of Health, Bethesda, MD 20814-9692, USA
| | - Marta Čeko
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO 80309, USA
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13
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Euler MJ. Intelligence and uncertainty: Implications of hierarchical predictive processing for the neuroscience of cognitive ability. Neurosci Biobehav Rev 2018; 94:93-112. [PMID: 30153441 DOI: 10.1016/j.neubiorev.2018.08.013] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2018] [Revised: 06/02/2018] [Accepted: 08/23/2018] [Indexed: 12/15/2022]
Abstract
Hierarchical predictive processing (PP) has recently emerged as a candidate theoretical paradigm for neurobehavioral research. To date, PP has found support through its success in offering compelling explanations for a number of perceptual, cognitive, and psychiatric phenomena, as well as from accumulating neurophysiological evidence. However, its implications for understanding intelligence and its neural basis have received relatively little attention. The present review outlines the key tenets and evidence for PP, and assesses its implications for intelligence research. It is argued that PP suggests indeterminacy as a unifying principle from which to investigate the cognitive hierarchy and brain-ability correlations. The resulting framework not only accommodates prominent psychometric models of intelligence, but also incorporates key findings from neuroanatomical and functional activation research, and motivates new predictions via the mechanisms of prediction-error minimization. Because PP also suggests unique neural signatures of experience-dependent activity, it may also help clarify environmental contributions to intellectual development. It is concluded that PP represents a plausible, integrative framework that could enhance progress in the neuroscience of intelligence.
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Affiliation(s)
- Matthew J Euler
- Department of Psychology, University of Utah, 380 S. 1530 E. Rm. 502, Salt Lake City, UT, 84112, USA.
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14
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Martínez K, Merchán-Naranjo J, Pina-Camacho L, Alemán-Gómez Y, Boada L, Fraguas D, Moreno C, Arango C, Janssen J, Parellada M. Atypical age-dependency of executive function and white matter microstructure in children and adolescents with autism spectrum disorders. Eur Child Adolesc Psychiatry 2017; 26:1361-1376. [PMID: 28447268 DOI: 10.1007/s00787-017-0990-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2016] [Accepted: 04/17/2017] [Indexed: 11/29/2022]
Abstract
Executive function (EF) performance is associated with measurements of white matter microstructure (WMS) in typical individuals. Impaired EF is a hallmark symptom of autism spectrum disorders (ASD) but it is unclear how impaired EF relates to variability in WMS. Twenty-one male youth (8-18 years) with ASD and without intellectual disability and twenty-one typical male participants (TP) matched for age, intelligence quotient, handedness, race and parental socioeconomic status were recruited. Five EF domains were assessed and several DTI-based measurements of WMS [fractional anisotropy (FA), mean diffusivity (MD) and radial diffusivity (RD)] were estimated for eighteen white matter tracts. The ASD group had lower scores for attention (F = 8.37, p = 0.006) and response inhibition (F = 13.09, p = 0.001). Age-dependent changes of EF performance and WMS measurements were present in TP but attenuated in the ASD group. The strongest diagnosis-by-age effect was found for forceps minor, left anterior thalamic radiation and left cingulum angular bundle (all p's ≤ 0.002). In these tracts subjects with ASD tended to have equal or increased FA and/or reduced MD and/or RD at younger ages while controls had increased FA and/or reduced MD and/or RD thereafter. Only for TP individuals, increased FA in the left anterior thalamic radiation was associated with better response inhibition, while reduced RD in forceps minor and left cingulum angular bundle was related to better problem solving and working memory performance respectively. These findings provide novel insight into the age-dependency of EF performance and WMS in ASD, which can be instructive to cognitive training programs.
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Affiliation(s)
- Kenia Martínez
- Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Madrid, Spain. .,Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Madrid, Spain. .,Ciber del área de Salud Mental (CIBERSAM), Madrid, Spain. .,Universidad Europea de Madrid, Madrid, Spain. .,Hospital Gregorio Marañón, Edificio prefabricado, entrada por Máiquez 9, 28009, Madrid, Spain.
| | - Jessica Merchán-Naranjo
- Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Madrid, Spain.,Ciber del área de Salud Mental (CIBERSAM), Madrid, Spain
| | - Laura Pina-Camacho
- Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Madrid, Spain.,Ciber del área de Salud Mental (CIBERSAM), Madrid, Spain.,Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Yasser Alemán-Gómez
- Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Madrid, Spain.,Ciber del área de Salud Mental (CIBERSAM), Madrid, Spain
| | - Leticia Boada
- Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Madrid, Spain.,Ciber del área de Salud Mental (CIBERSAM), Madrid, Spain
| | - David Fraguas
- Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Madrid, Spain.,Ciber del área de Salud Mental (CIBERSAM), Madrid, Spain
| | - Carmen Moreno
- Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Madrid, Spain.,Ciber del área de Salud Mental (CIBERSAM), Madrid, Spain
| | - Celso Arango
- Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Madrid, Spain.,Ciber del área de Salud Mental (CIBERSAM), Madrid, Spain.,Universidad Complutense de Madrid, Madrid, Spain
| | - Joost Janssen
- Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Madrid, Spain.,Ciber del área de Salud Mental (CIBERSAM), Madrid, Spain.,Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Mara Parellada
- Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Madrid, Spain.,Ciber del área de Salud Mental (CIBERSAM), Madrid, Spain.,Universidad Complutense de Madrid, Madrid, Spain
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15
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Global associations between regional gray matter volume and diverse complex cognitive functions: evidence from a large sample study. Sci Rep 2017; 7:10014. [PMID: 28855703 PMCID: PMC5577279 DOI: 10.1038/s41598-017-10104-8] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2017] [Accepted: 08/04/2017] [Indexed: 12/02/2022] Open
Abstract
Correlations between regional gray matter volume (rGMV) and psychometric test scores have been measured to investigate the neural bases for individual differences in complex cognitive abilities (CCAs). However, such studies have yielded different rGMV correlates of the same CCA. Based on the available evidence, we hypothesized that diverse CCAs are all positively but only weakly associated with rGMV in widespread brain areas. To test this hypothesis, we used the data from a large sample of healthy young adults [776 males and 560 females; mean age: 20.8 years, standard deviation (SD) = 0.8] and investigated associations between rGMV and scores on multiple CCA tasks (including non-verbal reasoning, verbal working memory, Stroop interference, and complex processing speed tasks involving spatial cognition and reasoning). Better performance scores on all tasks except non-verbal reasoning were associated with greater rGMV across widespread brain areas. The effect sizes of individual associations were generally low, consistent with our previous studies. The lack of strong correlations between rGMV and specific CCAs, combined with stringent corrections for multiple comparisons, may lead to different and diverse findings in the field.
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16
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Advances in Intelligence Research: What Should be Expected in the XXI Century (Questions & Answers). SPANISH JOURNAL OF PSYCHOLOGY 2016; 19:E92. [PMID: 27919295 DOI: 10.1017/sjp.2016.87] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Here I briefly delineate my view about the main question of this International Seminar, namely, what should we expecting from the XXI Century regarding the advancements in intelligence research. This view can be summarized as 'The Brain Connection' (TBC), meaning that neuroscience will be of paramount relevance for increasing our current knowledge related to the key question: why are some people smarter than others? We need answers to the issue of what happens in our brains when the genotype and the environment are integrated. The scientific community has devoted great research efforts, ranging from observable behavior to hidden genetics, but we are still far from having a clear general picture of what it means to be more or less intelligent. After the discussion held with the panel of experts participating in the seminar, it is concluded that advancements will be more solid and safe increasing the collaboration of scientists with shared research interests worldwide. Paralleling current sophisticated analyses of how the brain computes, nowadays science may embrace a network approach.
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17
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Ponsoda V, Martínez K, Pineda-Pardo JA, Abad FJ, Olea J, Román FJ, Barbey AK, Colom R. Structural brain connectivity and cognitive ability differences: A multivariate distance matrix regression analysis. Hum Brain Mapp 2016; 38:803-816. [PMID: 27726264 DOI: 10.1002/hbm.23419] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2015] [Revised: 07/21/2016] [Accepted: 09/23/2016] [Indexed: 11/11/2022] Open
Abstract
Neuroimaging research involves analyses of huge amounts of biological data that might or might not be related with cognition. This relationship is usually approached using univariate methods, and, therefore, correction methods are mandatory for reducing false positives. Nevertheless, the probability of false negatives is also increased. Multivariate frameworks have been proposed for helping to alleviate this balance. Here we apply multivariate distance matrix regression for the simultaneous analysis of biological and cognitive data, namely, structural connections among 82 brain regions and several latent factors estimating cognitive performance. We tested whether cognitive differences predict distances among individuals regarding their connectivity pattern. Beginning with 3,321 connections among regions, the 36 edges better predicted by the individuals' cognitive scores were selected. Cognitive scores were related to connectivity distances in both the full (3,321) and reduced (36) connectivity patterns. The selected edges connect regions distributed across the entire brain and the network defined by these edges supports high-order cognitive processes such as (a) (fluid) executive control, (b) (crystallized) recognition, learning, and language processing, and (c) visuospatial processing. This multivariate study suggests that one widespread, but limited number, of regions in the human brain, supports high-level cognitive ability differences. Hum Brain Mapp 38:803-816, 2017. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Vicente Ponsoda
- Facultad de Psicología, Universidad Autónoma de Madrid, Madrid, Spain
| | - Kenia Martínez
- Facultad de Psicología, Universidad Autónoma de Madrid, Madrid, Spain.,Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón (Madrid, Spain) and Instituto de Investigación Sanitaria Gregorio Marañón (IISGM) (Madrid, Spain) and Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM) (Madrid, Spain) and Universidad Europea de Madrid, Madrid, Spain
| | - José A Pineda-Pardo
- CINAC (Centro Integral de Neurociencias AC), HM Puerta del Sur, Hospitales de Madrid (Móstoles, Madrid, Spain) and CEU San Pablo University, Madrid, Spain
| | - Francisco J Abad
- Facultad de Psicología, Universidad Autónoma de Madrid, Madrid, Spain
| | - Julio Olea
- Facultad de Psicología, Universidad Autónoma de Madrid, Madrid, Spain
| | - Francisco J Román
- Facultad de Psicología, Universidad Autónoma de Madrid, Madrid, Spain.,Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana
| | - Aron K Barbey
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana
| | - Roberto Colom
- Facultad de Psicología, Universidad Autónoma de Madrid, Madrid, Spain
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18
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Lyden H, Gimbel SI, Del Piero L, Tsai AB, Sachs ME, Kaplan JT, Margolin G, Saxbe D. Associations between Family Adversity and Brain Volume in Adolescence: Manual vs. Automated Brain Segmentation Yields Different Results. Front Neurosci 2016; 10:398. [PMID: 27656121 PMCID: PMC5011142 DOI: 10.3389/fnins.2016.00398] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2016] [Accepted: 08/12/2016] [Indexed: 12/03/2022] Open
Abstract
Associations between brain structure and early adversity have been inconsistent in the literature. These inconsistencies may be partially due to methodological differences. Different methods of brain segmentation may produce different results, obscuring the relationship between early adversity and brain volume. Moreover, adolescence is a time of significant brain growth and certain brain areas have distinct rates of development, which may compromise the accuracy of automated segmentation approaches. In the current study, 23 adolescents participated in two waves of a longitudinal study. Family aggression was measured when the youths were 12 years old, and structural scans were acquired an average of 4 years later. Bilateral amygdalae and hippocampi were segmented using three different methods (manual tracing, FSL, and NeuroQuant). The segmentation estimates were compared, and linear regressions were run to assess the relationship between early family aggression exposure and all three volume segmentation estimates. Manual tracing results showed a positive relationship between family aggression and right amygdala volume, whereas FSL segmentation showed negative relationships between family aggression and both the left and right hippocampi. However, results indicate poor overlap between methods, and different associations were found between early family aggression exposure and brain volume depending on the segmentation method used.
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Affiliation(s)
- Hannah Lyden
- Department of Psychology, University of Southern California Los Angeles, CA, USA
| | - Sarah I Gimbel
- Department of Psychology, Brain and Creativity Institute, University of Southern California Los Angeles, CA, USA
| | - Larissa Del Piero
- Department of Psychology, University of Southern California Los Angeles, CA, USA
| | - A Bryna Tsai
- Department of Psychology, University of Southern California Los Angeles, CA, USA
| | - Matthew E Sachs
- Department of Psychology, Brain and Creativity Institute, University of Southern California Los Angeles, CA, USA
| | - Jonas T Kaplan
- Department of Psychology, University of Southern CaliforniaLos Angeles, CA, USA; Department of Psychology, Brain and Creativity Institute, University of Southern CaliforniaLos Angeles, CA, USA
| | - Gayla Margolin
- Department of Psychology, University of Southern California Los Angeles, CA, USA
| | - Darby Saxbe
- Department of Psychology, University of Southern California Los Angeles, CA, USA
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19
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Colom R, Chuderski A, Santarnecchi E. Bridge Over Troubled Water: Commenting on Kovacs and Conway's Process Overlap Theory. PSYCHOLOGICAL INQUIRY 2016. [DOI: 10.1080/1047840x.2016.1181513] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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20
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Challenges in replicating brain-behavior correlations: Rejoinder to Kanai (2015) and Muhlert and Ridgway (2015). Cortex 2016. [DOI: 10.1016/j.cortex.2015.06.018] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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21
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Pineda-Pardo JA, Martínez K, Román FJ, Colom R. Structural efficiency within a parieto-frontal network and cognitive differences. INTELLIGENCE 2016. [DOI: 10.1016/j.intell.2015.12.002] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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22
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Reid AT, Lewis J, Bezgin G, Khundrakpam B, Eickhoff SB, McIntosh AR, Bellec P, Evans AC. A cross-modal, cross-species comparison of connectivity measures in the primate brain. Neuroimage 2015; 125:311-331. [PMID: 26515902 DOI: 10.1016/j.neuroimage.2015.10.057] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2015] [Revised: 10/16/2015] [Accepted: 10/22/2015] [Indexed: 12/23/2022] Open
Abstract
In systems neuroscience, the term "connectivity" has been defined in numerous ways, according to the particular empirical modality from which it is derived. Due to large differences in the phenomena measured by these modalities, the assumptions necessary to make inferences about axonal connections, and the limitations accompanying each, brain connectivity remains an elusive concept. Despite this, only a handful of studies have directly compared connectivity as inferred from multiple modalities, and there remains much ambiguity over what the term is actually referring to as a biological construct. Here, we perform a direct comparison based on the high-resolution and high-contrast Enhanced Nathan Klein Institute (NKI) Rockland Sample neuroimaging data set, and the CoCoMac database of tract tracing studies. We compare four types of commonly-used primate connectivity analyses: tract tracing experiments, compiled in CoCoMac; group-wise correlation of cortical thickness; tractographic networks computed from diffusion-weighted MRI (DWI); and correlational networks obtained from resting-state BOLD (fMRI). We find generally poor correspondence between all four modalities, in terms of correlated edge weights, binarized comparisons of thresholded networks, and clustering patterns. fMRI and DWI had the best agreement, followed by DWI and CoCoMac, while other comparisons showed striking divergence. Networks had the best correspondence for local ipsilateral and homotopic contralateral connections, and the worst correspondence for long-range and heterotopic contralateral connections. k-Means clustering highlighted the lowest cross-modal and cross-species consensus in lateral and medial temporal lobes, anterior cingulate, and the temporoparietal junction. Comparing the NKI results to those of the lower resolution/contrast International Consortium for Brain Imaging (ICBM) dataset, we find that the relative pattern of intermodal relationships is preserved, but the correspondence between human imaging connectomes is substantially better for NKI. These findings caution against using "connectivity" as an umbrella term for results derived from single empirical modalities, and suggest that any interpretation of these results should account for (and ideally help explain) the lack of multimodal correspondence.
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Affiliation(s)
- Andrew T Reid
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany.
| | - John Lewis
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada.
| | - Gleb Bezgin
- Rotman Research Institute of Baycrest Centre, University of Toronto, Toronto, ON, Canada.
| | - Budhachandra Khundrakpam
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada.
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany; Institute of Clinical Neuroscience and Medical Psychology, Heinrich Heine University, Düsseldorf, Germany.
| | - Anthony R McIntosh
- Rotman Research Institute of Baycrest Centre, University of Toronto, Toronto, ON, Canada.
| | - Pierre Bellec
- Centre de Recherche de l'Institut de Gériatrie de Montréal CRIUGM, Montreal, QC, Canada.
| | - Alan C Evans
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada.
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