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Tansey R, Graff K, Rai S, Merrikh D, Godfrey KJ, Vanderwal T, Bray S. Development of human visual cortical function: A scoping review of task- and naturalistic-fMRI studies through the interactive specialization and maturational frameworks. Neurosci Biobehav Rev 2024; 162:105729. [PMID: 38763178 DOI: 10.1016/j.neubiorev.2024.105729] [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: 03/07/2024] [Revised: 05/12/2024] [Accepted: 05/14/2024] [Indexed: 05/21/2024]
Abstract
Overarching theories such as the interactive specialization and maturational frameworks have been proposed to describe human functional brain development. However, these frameworks have not yet been systematically examined across the fMRI literature. Visual processing is one of the most well-studied fields in neuroimaging, and research in this area has recently expanded to include naturalistic paradigms that facilitate study in younger age ranges, allowing for an in-depth critical appraisal of these frameworks across childhood. To this end, we conducted a scoping review of 94 developmental visual fMRI studies, including both traditional experimental task and naturalistic studies, across multiple sub-domains (early visual processing, category-specific higher order processing, naturalistic visual processing). We found that across domains, many studies reported progressive development, but few studies describe regressive or emergent changes necessary to fit the maturational or interactive specialization frameworks. Our findings suggest a need for the expansion of developmental frameworks and clearer reporting of both progressive and regressive changes, along with well-powered, longitudinal studies.
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Affiliation(s)
- Ryann Tansey
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada.
| | - Kirk Graff
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
| | - Shefali Rai
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Daria Merrikh
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Kate J Godfrey
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Tamara Vanderwal
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada; BC Children's Hospital Research Institute, Vancouver, BC, Canada
| | - Signe Bray
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; Department of Pediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
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2
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Kosakowski HL, Cohen MA, Herrera L, Nichoson I, Kanwisher N, Saxe R. Cortical Face-Selective Responses Emerge Early in Human Infancy. eNeuro 2024; 11:ENEURO.0117-24.2024. [PMID: 38871455 PMCID: PMC11258539 DOI: 10.1523/eneuro.0117-24.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Revised: 05/28/2024] [Accepted: 06/04/2024] [Indexed: 06/15/2024] Open
Abstract
In human adults, multiple cortical regions respond robustly to faces, including the occipital face area (OFA) and fusiform face area (FFA), implicated in face perception, and the superior temporal sulcus (STS) and medial prefrontal cortex (MPFC), implicated in higher-level social functions. When in development, does face selectivity arise in each of these regions? Here, we combined two awake infant functional magnetic resonance imaging (fMRI) datasets to create a sample size twice the size of previous reports (n = 65 infants; 2.6-9.6 months). Infants watched movies of faces, bodies, objects, and scenes, while fMRI data were collected. Despite variable amounts of data from each infant, individual subject whole-brain activation maps revealed responses to faces compared to nonface visual categories in the approximate location of OFA, FFA, STS, and MPFC. To determine the strength and nature of face selectivity in these regions, we used cross-validated functional region of interest analyses. Across this larger sample size, face responses in OFA, FFA, STS, and MPFC were significantly greater than responses to bodies, objects, and scenes. Even the youngest infants (2-5 months) showed significantly face-selective responses in FFA, STS, and MPFC, but not OFA. These results demonstrate that face selectivity is present in multiple cortical regions within months of birth, providing powerful constraints on theories of cortical development.
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Affiliation(s)
- Heather L Kosakowski
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts 02138
| | - Michael A Cohen
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
- Department of Psychology and Program in Neuroscience, Amherst College, Amherst, Massachusetts 01002
| | - Lyneé Herrera
- Psychology Department, University of Denver, Denver, Colorado 80210
| | - Isabel Nichoson
- Tulane Brain Institute, Tulane University, New Orleans, Louisiana 70118
| | - Nancy Kanwisher
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
| | - Rebecca Saxe
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
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Haartsen R, Mason L, Garces P, Gui A, Charman T, Tillmann J, Johnson MH, Buitelaar JK, Loth E, Murphy D, Jones EJH. Qualitative differences in the spatiotemporal brain states supporting configural face processing emerge in adolescence in autism. Cortex 2022; 155:13-29. [PMID: 35961249 DOI: 10.1016/j.cortex.2022.06.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Revised: 12/17/2021] [Accepted: 06/29/2022] [Indexed: 11/18/2022]
Abstract
BACKGROUND Studying the neural processing of faces can illuminate the mechanisms of compromised social expertise in autism. To resolve a longstanding debate, we examined whether differences in configural face processing in autism are underpinned by quantitative differences in the activation of typical face processing pathways, or the recruitment of non-typical neural systems. METHODS We investigated spatial and temporal characteristics of event-related EEG responses to upright and inverted faces in a large sample of children, adolescents, and adults with and without autism. We examined topographic analyses of variance and global field power to identify group differences in the spatial and temporal response to face inversion. We then examined how quasi-stable spatiotemporal profiles - microstates - are modulated by face orientation and diagnostic group. RESULTS Upright and inverted faces produced distinct profiles of topography and strength in the topographical analyses. These topographical profiles differed between diagnostic groups in adolescents, but not in children or adults. In the microstate analysis, the autistic group showed differences in the activation strength of normative microstates during early-stage processing at all ages, suggesting consistent quantitative differences in the operation of typical processing pathways; qualitative differences in microstate topographies during late-stage processing became prominent in adults, suggesting the increasing involvement of non-typical neural systems with processing time and over development. CONCLUSIONS These findings suggest that early difficulties with configural face processing may trigger later compensatory processes in autism that emerge in later development.
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Affiliation(s)
- Rianne Haartsen
- Centre for Brain and Cognitive Development, Birkbeck College, University of London, United Kingdom.
| | - Luke Mason
- Centre for Brain and Cognitive Development, Birkbeck College, University of London, United Kingdom
| | - Pilar Garces
- Roche Pharma Research and Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Basel, Switzerland
| | - Anna Gui
- Centre for Brain and Cognitive Development, Birkbeck College, University of London, United Kingdom
| | - Tony Charman
- Department of Psychology, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom; South London and Maudsley NHS Foundation Trust, Bethlem Royal Hospital, Kent, United Kingdom
| | - Julian Tillmann
- Roche Pharma Research and Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Basel, Switzerland
| | - Mark H Johnson
- Centre for Brain and Cognitive Development, Birkbeck College, University of London, United Kingdom; Department of Psychology, University of Cambridge, Cambridge, United Kingdom
| | - Jan K Buitelaar
- Radboud University Medical Centre, Donders Institute for Brain, Cognition and Behaviour, Department of Cognitive Neuroscience, Nijmegen, the Netherlands
| | - Eva Loth
- Department of Forensic and Neurodevelopmental Science, King's College London, United Kingdom
| | - Declan Murphy
- Department of Forensic and Neurodevelopmental Science, King's College London, United Kingdom
| | - Emily J H Jones
- Centre for Brain and Cognitive Development, Birkbeck College, University of London, United Kingdom
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Naumann S, Bayer M, Dziobek I. Preschoolers' Sensitivity to Negative and Positive Emotional Facial Expressions: An ERP Study. Front Psychol 2022; 13:828066. [PMID: 35712205 PMCID: PMC9197498 DOI: 10.3389/fpsyg.2022.828066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 04/28/2022] [Indexed: 11/13/2022] Open
Abstract
The study examined processing differences for facial expressions (happy, angry, or neutral) and their repetition with early (P1, N170) and late (P3) event-related potentials (ERPs) in young children (N = 33). EEG was recorded while children observed sequentially presented pairs of facial expressions, which were either the same (repeated trials) or differed in their emotion (novel trials). We also correlated ERP amplitude differences with parental and child measures of socio-emotional competence (emotion recognition, empathy). P1 amplitudes were increased for angry and happy as compared to neutral expressions. We also detected larger P3 amplitudes for angry expressions as compared to happy or neutral expressions. Repetition effects were evident at early and late processing stages marked by reduced P1 amplitudes for repeated vs. novel happy expressions, but enhanced P3 amplitudes for repeated vs. novel facial expressions. N170 amplitudes were neither modulated by facial expressions nor their repetition. None of the repetition effects were associated with measures of socio-emotional competence. Taken together, negative facial expressions led to increased neural activations in early and later processing stages, indicative of enhanced saliency to potential threating stimuli in young children. Processing of repeated facial expression seem to be differential for early and late neural stages: Reduced activation was detected at early neural processing stages particularly for happy faces, indicative of effective processing for an emotion, which is most familiar within this age range. Contrary to our hypothesis, enhanced activity for repeated vs. novel expression independent of a particular emotion were detected at later processing stages, which may be linked to the creation of new memory traces. Early and late repetition effects are discussed in light of developmental and perceptual differences as well as task-specific load.
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Affiliation(s)
- Sandra Naumann
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Psychology, Institute of Life Sciences, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Mareike Bayer
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Psychology, Institute of Life Sciences, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Isabel Dziobek
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Psychology, Institute of Life Sciences, Humboldt-Universität zu Berlin, Berlin, Germany
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5
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Tian X, Hao X, Song Y, Liu J. Homogenization of face neural representation during development. Dev Cogn Neurosci 2021; 52:101040. [PMID: 34837875 PMCID: PMC8637318 DOI: 10.1016/j.dcn.2021.101040] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 09/19/2021] [Accepted: 11/18/2021] [Indexed: 12/01/2022] Open
Abstract
Extensive studies have demonstrated that face processing ability develops gradually during development until adolescence. However, the underlying mechanism is unclear. One hypothesis is that children and adults represent faces in qualitatively different fashions with different group templates. An alternative hypothesis emphasizes the development as a quantitative change with a decrease of variation in representations. To test these hypotheses, we used between-participant correlation to measure activation pattern similarity both within and between late-childhood children and adults. We found that activation patterns for faces in the fusiform face area and occipital face area were less similar within the children group than within the adults group, indicating children had a greater variation in representing faces. Interestingly, the activation pattern similarity of children to their own group template was not significantly larger than that to adults' template, suggesting children and adults shared a template in representing faces. Further, the decrease in representation variance was likely a general principle in the ventral visual cortex, as a similar result was observed in a scene-selective region when perceiving scenes. Taken together, our study provides evidence that development of object representation may result from a homogenization process that shifts from greater variance in late-childhood to homogeneity in adults.
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Affiliation(s)
- Xue Tian
- Faculty of Psychology, Tianjin Normal University, Tianjin 300387, China
| | - Xin Hao
- Key Laboratory of Adolescent Cyberpsychology and Behavior, Ministry of Education, Central China Normal University, Wuhan, China; School of Psychology, Central China Normal University, Wuhan, China
| | - Yiying Song
- Faculty of Psychology, Beijing Normal University, Beijing 100875, China.
| | - Jia Liu
- Department of Psychology & Tsinghua Laboratory of Brain and Intelligence, Tsinghua University, Beijing 100084, China
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6
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Haartsen R, Mason L, Braithwaite EK, Del Bianco T, Johnson MH, Jones EJH. Reliability of an automated gaze-controlled paradigm for capturing neural responses during visual and face processing in toddlerhood. Dev Psychobiol 2021; 63:e22157. [PMID: 34674242 PMCID: PMC9293026 DOI: 10.1002/dev.22157] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Revised: 05/28/2021] [Accepted: 06/07/2021] [Indexed: 11/19/2022]
Abstract
Electroencephalography (EEG) has substantial potential value for examining individual differences during early development. Current challenges in developmental EEG research include high dropout rates and low trial numbers, which may in part be due to passive stimulus presentation. Comparability is challenged by idiosyncratic processing pipelines. We present a novel toolbox (“Braintools”) that uses gaze‐contingent stimulus presentation and an automated processing pipeline suitable for measuring visual processing through low‐density EEG recordings in the field. We tested the feasibility of this toolbox in 61 2.5‐ to 4‐year olds, and computed test–retest reliability (1‐ to 2‐week interval) of event‐related potentials (ERP) associated with visual (P1) and face processing (N290, P400). Feasibility was good, with 52 toddlers providing some EEG data at the first session. Reliability values for ERP features were moderate when derived from 20 trials; this would allow inclusion of 79% of the 61 toddlers for the P1 and 82% for the N290 and P400. P1 amplitude/latency were more reliable across sessions than for the N290 and P400. Amplitudes were generally more reliable than latencies. Automated and standardized solutions to collection and analysis of event‐related EEG data would allow efficient application in large‐scale global health studies, opening significant potential for examining individual differences in development.
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Affiliation(s)
- Rianne Haartsen
- Centre for Brain and Cognitive Development, Department of Psychological Sciences, Birkbeck, University of London, London, UK
| | - Luke Mason
- Centre for Brain and Cognitive Development, Department of Psychological Sciences, Birkbeck, University of London, London, UK
| | - Eleanor K Braithwaite
- Centre for Brain and Cognitive Development, Department of Psychological Sciences, Birkbeck, University of London, London, UK
| | - Teresa Del Bianco
- Centre for Brain and Cognitive Development, Department of Psychological Sciences, Birkbeck, University of London, London, UK
| | - Mark H Johnson
- Centre for Brain and Cognitive Development, Department of Psychological Sciences, Birkbeck, University of London, London, UK.,Department of Psychology, University of Cambridge, Cambridge, UK
| | - Emily J H Jones
- Centre for Brain and Cognitive Development, Department of Psychological Sciences, Birkbeck, University of London, London, UK
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7
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Chaarani B, Hahn S, Allgaier N, Adise S, Owens MM, Juliano AC, Yuan DK, Loso H, Ivanciu A, Albaugh MD, Dumas J, Mackey S, Laurent J, Ivanova M, Hagler DJ, Cornejo MD, Hatton S, Agrawal A, Aguinaldo L, Ahonen L, Aklin W, Anokhin AP, Arroyo J, Avenevoli S, Babcock D, Bagot K, Baker FC, Banich MT, Barch DM, Bartsch H, Baskin-Sommers A, Bjork JM, Blachman-Demner D, Bloch M, Bogdan R, Bookheimer SY, Breslin F, Brown S, Calabro FJ, Calhoun V, Casey BJ, Chang L, Clark DB, Cloak C, Constable RT, Constable K, Corley R, Cottler LB, Coxe S, Dagher RK, Dale AM, Dapretto M, Delcarmen-Wiggins R, Dick AS, Do EK, Dosenbach NUF, Dowling GJ, Edwards S, Ernst TM, Fair DA, Fan CC, Feczko E, Feldstein-Ewing SW, Florsheim P, Foxe JJ, Freedman EG, Friedman NP, Friedman-Hill S, Fuemmeler BF, Galvan A, Gee DG, Giedd J, Glantz M, Glaser P, Godino J, Gonzalez M, Gonzalez R, Grant S, Gray KM, Haist F, Harms MP, Hawes S, Heath AC, Heeringa S, Heitzeg MM, Hermosillo R, Herting MM, Hettema JM, Hewitt JK, Heyser C, Hoffman E, Howlett K, Huber RS, Huestis MA, Hyde LW, Iacono WG, Infante MA, Irfanoglu O, Isaiah A, Iyengar S, Jacobus J, James R, Jean-Francois B, Jernigan T, Karcher NR, Kaufman A, Kelley B, Kit B, Ksinan A, Kuperman J, Laird AR, Larson C, LeBlanc K, Lessov-Schlagger C, Lever N, Lewis DA, Lisdahl K, Little AR, Lopez M, Luciana M, Luna B, Madden PA, Maes HH, Makowski C, Marshall AT, Mason MJ, Matochik J, McCandliss BD, McGlade E, Montoya I, Morgan G, Morris A, Mulford C, Murray P, Nagel BJ, Neale MC, Neigh G, Nencka A, Noronha A, Nixon SJ, Palmer CE, Pariyadath V, Paulus MP, Pelham WE, Pfefferbaum D, Pierpaoli C, Prescot A, Prouty D, Puttler LI, Rajapaske N, Rapuano KM, Reeves G, Renshaw PF, Riedel MC, Rojas P, de la Rosa M, Rosenberg MD, Ross MJ, Sanchez M, Schirda C, Schloesser D, Schulenberg J, Sher KJ, Sheth C, Shilling PD, Simmons WK, Sowell ER, Speer N, Spittel M, Squeglia LM, Sripada C, Steinberg J, Striley C, Sutherland MT, Tanabe J, Tapert SF, Thompson W, Tomko RL, Uban KA, Vrieze S, Wade NE, Watts R, Weiss S, Wiens BA, Williams OD, Wilbur A, Wing D, Wolff-Hughes D, Yang R, Yurgelun-Todd DA, Zucker RA, Potter A, Garavan HP. Baseline brain function in the preadolescents of the ABCD Study. Nat Neurosci 2021; 24:1176-1186. [PMID: 34099922 PMCID: PMC8947197 DOI: 10.1038/s41593-021-00867-9] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2019] [Accepted: 04/30/2021] [Indexed: 02/05/2023]
Abstract
The Adolescent Brain Cognitive Development (ABCD) Study® is a 10-year longitudinal study of children recruited at ages 9 and 10. A battery of neuroimaging tasks are administered biennially to track neurodevelopment and identify individual differences in brain function. This study reports activation patterns from functional MRI (fMRI) tasks completed at baseline, which were designed to measure cognitive impulse control with a stop signal task (SST; N = 5,547), reward anticipation and receipt with a monetary incentive delay (MID) task (N = 6,657) and working memory and emotion reactivity with an emotional N-back (EN-back) task (N = 6,009). Further, we report the spatial reproducibility of activation patterns by assessing between-group vertex/voxelwise correlations of blood oxygen level-dependent (BOLD) activation. Analyses reveal robust brain activations that are consistent with the published literature, vary across fMRI tasks/contrasts and slightly correlate with individual behavioral performance on the tasks. These results establish the preadolescent brain function baseline, guide interpretation of cross-sectional analyses and will enable the investigation of longitudinal changes during adolescent development.
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Affiliation(s)
- B Chaarani
- Department of Psychiatry, University of Vermont, Burlington, VT, USA.
| | - S Hahn
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - N Allgaier
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - S Adise
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - M M Owens
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - A C Juliano
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - D K Yuan
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - H Loso
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - A Ivanciu
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - M D Albaugh
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - J Dumas
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - S Mackey
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - J Laurent
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - M Ivanova
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - D J Hagler
- University of California, San Diego, La Jolla, CA, USA
| | - M D Cornejo
- Institute of Physics UC, Pontificia Universidad Catolica de Chile, Pontificia, Chile
| | - S Hatton
- University of California, San Diego, La Jolla, CA, USA
| | - A Agrawal
- Department of Psychiatry, Washington University in Saint Louis, St. Louis, MO, USA
| | - L Aguinaldo
- University of California, San Diego, La Jolla, CA, USA
| | - L Ahonen
- University of Pittsburgh, Pittsburgh, PA, USA
| | - W Aklin
- National Institute on Drug Abuse, Bethesda, MD, USA
| | - A P Anokhin
- Department of Psychiatry, Washington University in Saint Louis, St. Louis, MO, USA
| | - J Arroyo
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD, USA
| | - S Avenevoli
- National Institute of Mental Health, Bethesda, MD, USA
| | - D Babcock
- National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - K Bagot
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - F C Baker
- SRI International, Menlo Park, CA, USA
| | - M T Banich
- University of Colorado, Boulder, CO, USA
| | - D M Barch
- Department of Psychiatry, Washington University in Saint Louis, St. Louis, MO, USA
| | - H Bartsch
- Haukeland University Hospital, Bergen, Norway
| | | | - J M Bjork
- Virginia Commonwealth University, Richmond, VA, USA
| | - D Blachman-Demner
- NIH Office of Behavioral and Social Sciences Research, Bethesda, MD, USA
| | - M Bloch
- National Cancer Institute, Bethesda, MD, USA
| | - R Bogdan
- Department of Psychiatry, Washington University in Saint Louis, St. Louis, MO, USA
| | | | - F Breslin
- Laureate Institute for Brain Research, Tulsa, OK, USA
| | - S Brown
- University of California, San Diego, La Jolla, CA, USA
| | - F J Calabro
- University of Pittsburgh, Pittsburgh, PA, USA
| | - V Calhoun
- University of Colorado, Boulder, CO, USA
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | | | - L Chang
- University of Maryland School of Medicine, Baltimore, MD, USA
| | - D B Clark
- University of Pittsburgh, Pittsburgh, PA, USA
| | - C Cloak
- University of Maryland School of Medicine, Baltimore, MD, USA
| | | | - K Constable
- National Institute on Drug Abuse, Bethesda, MD, USA
| | - R Corley
- University of Colorado, Boulder, CO, USA
| | | | - S Coxe
- Florida International University, Miami, FL, USA
| | - R K Dagher
- National Institute on Minority Health and Health Disparities, Bethesda, MD, USA
| | - A M Dale
- University of California, San Diego, La Jolla, CA, USA
| | - M Dapretto
- University of California, Los Angeles, CA, USA
| | | | - A S Dick
- Florida International University, Miami, FL, USA
| | - E K Do
- Virginia Commonwealth University, Richmond, VA, USA
| | - N U F Dosenbach
- Department of Psychiatry, Washington University in Saint Louis, St. Louis, MO, USA
| | - G J Dowling
- National Institute on Drug Abuse, Bethesda, MD, USA
| | - S Edwards
- University of Maryland School of Medicine, Baltimore, MD, USA
| | - T M Ernst
- University of Maryland School of Medicine, Baltimore, MD, USA
| | - D A Fair
- Oregon Health & Science University, Portland, OR, USA
| | - C C Fan
- Department of Psychiatry, Washington University in Saint Louis, St. Louis, MO, USA
| | - E Feczko
- Oregon Health & Science University, Portland, OR, USA
| | | | | | - J J Foxe
- University of Rochester, Rochester, NY, USA
| | | | | | | | | | - A Galvan
- University of California, Los Angeles, CA, USA
| | - D G Gee
- Yale University, New Haven, CT, USA
| | - J Giedd
- University of California, San Diego, La Jolla, CA, USA
| | - M Glantz
- National Institute on Drug Abuse, Bethesda, MD, USA
| | - P Glaser
- Department of Psychiatry, Washington University in Saint Louis, St. Louis, MO, USA
| | - J Godino
- University of California, San Diego, La Jolla, CA, USA
| | - M Gonzalez
- Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - R Gonzalez
- Florida International University, Miami, FL, USA
| | - S Grant
- National Institute on Drug Abuse, Bethesda, MD, USA
| | - K M Gray
- Medical University of South Carolina, Charleston, SC, USA
| | - F Haist
- University of California, San Diego, La Jolla, CA, USA
| | - M P Harms
- Department of Psychiatry, Washington University in Saint Louis, St. Louis, MO, USA
| | - S Hawes
- Florida International University, Miami, FL, USA
| | - A C Heath
- University of California, San Diego, La Jolla, CA, USA
| | - S Heeringa
- University of Michigan, Ann Arbor, MI, USA
| | | | - R Hermosillo
- Oregon Health & Science University, Portland, OR, USA
| | - M M Herting
- University of Southern California, Los Angeles, CA, USA
| | - J M Hettema
- Virginia Commonwealth University, Richmond, VA, USA
| | - J K Hewitt
- University of Colorado, Boulder, CO, USA
| | - C Heyser
- University of California, San Diego, La Jolla, CA, USA
| | - E Hoffman
- National Institute on Drug Abuse, Bethesda, MD, USA
| | - K Howlett
- National Institute on Drug Abuse, Bethesda, MD, USA
| | - R S Huber
- University of Utah, Salt Lake City, UT, USA
| | - M A Huestis
- Thomas Jefferson University, Philadelphia, PA, USA
| | - L W Hyde
- University of Michigan, Ann Arbor, MI, USA
| | - W G Iacono
- University of Minnesota, Minneapolis, MN, USA
| | - M A Infante
- University of California, San Diego, La Jolla, CA, USA
| | - O Irfanoglu
- National Institute of Biomedical Imaging and Bioengineering, Bethesda, MD, USA
| | - A Isaiah
- University of Maryland School of Medicine, Baltimore, MD, USA
| | - S Iyengar
- National Endowment for the Arts, Washington DC, USA
| | - J Jacobus
- University of California, San Diego, La Jolla, CA, USA
| | - R James
- Virginia Commonwealth University, Richmond, VA, USA
| | - B Jean-Francois
- National Institute on Minority Health and Health Disparities, Bethesda, MD, USA
| | - T Jernigan
- University of California, San Diego, La Jolla, CA, USA
| | - N R Karcher
- Department of Psychiatry, Washington University in Saint Louis, St. Louis, MO, USA
| | - A Kaufman
- National Cancer Institute, Bethesda, MD, USA
| | - B Kelley
- National Institute of Justice, Washington DC, USA
| | - B Kit
- National Heart, Lung, and Blood Institute, Bethesda, MD, USA
| | - A Ksinan
- Virginia Commonwealth University, Richmond, VA, USA
| | - J Kuperman
- University of California, San Diego, La Jolla, CA, USA
| | - A R Laird
- Florida International University, Miami, FL, USA
| | - C Larson
- University of Wisconsin, Milwaukee, WI, USA
| | - K LeBlanc
- National Institute on Drug Abuse, Bethesda, MD, USA
| | - C Lessov-Schlagger
- Department of Psychiatry, Washington University in Saint Louis, St. Louis, MO, USA
| | - N Lever
- University of Maryland School of Medicine, Baltimore, MD, USA
| | - D A Lewis
- University of Pittsburgh, Pittsburgh, PA, USA
| | - K Lisdahl
- University of Wisconsin, Milwaukee, WI, USA
| | - A R Little
- National Institute on Drug Abuse, Bethesda, MD, USA
| | - M Lopez
- National Institute on Drug Abuse, Bethesda, MD, USA
| | - M Luciana
- University of Minnesota, Minneapolis, MN, USA
| | - B Luna
- University of Pittsburgh, Pittsburgh, PA, USA
| | - P A Madden
- Department of Psychiatry, Washington University in Saint Louis, St. Louis, MO, USA
| | - H H Maes
- Virginia Commonwealth University, Richmond, VA, USA
| | - C Makowski
- University of California, San Diego, La Jolla, CA, USA
| | - A T Marshall
- Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - M J Mason
- University of Tennessee, Knoxville, TN, USA
| | - J Matochik
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD, USA
| | | | - E McGlade
- University of Utah, Salt Lake City, UT, USA
| | - I Montoya
- National Institute on Drug Abuse, Bethesda, MD, USA
| | - G Morgan
- National Cancer Institute, Bethesda, MD, USA
| | - A Morris
- Oklahoma State University, Stillwater, OK, USA
| | - C Mulford
- National Institute on Drug Abuse, Bethesda, MD, USA
| | - P Murray
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD, USA
| | - B J Nagel
- Oregon Health & Science University, Portland, OR, USA
| | - M C Neale
- Virginia Commonwealth University, Richmond, VA, USA
| | - G Neigh
- Virginia Commonwealth University, Richmond, VA, USA
| | - A Nencka
- Medical College of Wisconsin, Milwaukee, WI, USA
| | - A Noronha
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD, USA
| | - S J Nixon
- University of Florida, Gainesville, FL, USA
| | - C E Palmer
- University of California, San Diego, La Jolla, CA, USA
| | - V Pariyadath
- National Institute on Drug Abuse, Bethesda, MD, USA
| | - M P Paulus
- Laureate Institute for Brain Research, Tulsa, OK, USA
| | - W E Pelham
- Florida International University, Miami, FL, USA
| | | | - C Pierpaoli
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD, USA
| | - A Prescot
- University of Utah, Salt Lake City, UT, USA
| | - D Prouty
- SRI International, Menlo Park, CA, USA
| | | | - N Rajapaske
- National Institute on Minority Health and Health Disparities, Bethesda, MD, USA
| | | | - G Reeves
- University of Maryland School of Medicine, Baltimore, MD, USA
| | | | - M C Riedel
- Florida International University, Miami, FL, USA
| | - P Rojas
- Florida International University, Miami, FL, USA
| | - M de la Rosa
- Florida International University, Miami, FL, USA
| | | | - M J Ross
- University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - M Sanchez
- Florida International University, Miami, FL, USA
| | - C Schirda
- University of Pittsburgh, Pittsburgh, PA, USA
| | - D Schloesser
- NIH Office of Behavioral and Social Sciences Research, Bethesda, MD, USA
| | | | - K J Sher
- University of Missouri, Columbia, MO, USA
| | - C Sheth
- University of Utah, Salt Lake City, UT, USA
| | - P D Shilling
- University of California, San Diego, La Jolla, CA, USA
| | - W K Simmons
- Laureate Institute for Brain Research, Tulsa, OK, USA
| | - E R Sowell
- Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - N Speer
- University of Colorado, Boulder, CO, USA
| | - M Spittel
- NIH Office of Behavioral and Social Sciences Research, Bethesda, MD, USA
| | - L M Squeglia
- Medical University of South Carolina, Charleston, SC, USA
| | - C Sripada
- University of Michigan, Ann Arbor, MI, USA
| | - J Steinberg
- Virginia Commonwealth University, Richmond, VA, USA
| | - C Striley
- University of Florida, Gainesville, FL, USA
| | | | - J Tanabe
- University of Colorado, Boulder, CO, USA
| | - S F Tapert
- University of California, San Diego, La Jolla, CA, USA
| | - W Thompson
- University of California, San Diego, La Jolla, CA, USA
| | - R L Tomko
- Medical University of South Carolina, Charleston, SC, USA
| | - K A Uban
- University of California, Irvine, CA, USA
| | - S Vrieze
- University of Minnesota, Minneapolis, MN, USA
| | - N E Wade
- University of California, San Diego, La Jolla, CA, USA
| | - R Watts
- Yale University, New Haven, CT, USA
| | - S Weiss
- National Institute on Drug Abuse, Bethesda, MD, USA
| | - B A Wiens
- University of Florida, Gainesville, FL, USA
| | - O D Williams
- Florida International University, Miami, FL, USA
| | - A Wilbur
- SRI International, Menlo Park, CA, USA
| | - D Wing
- University of California, San Diego, La Jolla, CA, USA
| | - D Wolff-Hughes
- NIH Office of Behavioral and Social Sciences Research, Bethesda, MD, USA
| | - R Yang
- University of California, San Diego, La Jolla, CA, USA
| | | | - R A Zucker
- University of Michigan, Ann Arbor, MI, USA
| | - A Potter
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - H P Garavan
- Department of Psychiatry, University of Vermont, Burlington, VT, USA.
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8
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Plebanek DJ, James KH. Category structure guides the formation of neural representations. Exp Brain Res 2021; 239:1667-1684. [PMID: 33782786 DOI: 10.1007/s00221-021-06088-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Accepted: 03/13/2021] [Indexed: 11/27/2022]
Abstract
Perceptual variability is often viewed as having multiple benefits in object learning and categorization. Despite the abundant results demonstrating benefits such as increased transfer of knowledge, the neural mechanisms underlying variability as well as the developmental trajectories of how variability precipitates changes to category boundaries are unknown. By manipulating an individual's exposure to variability of novel, metrically organized categories during an fMRI-adaptation paradigm, we were able to assess the functional differences between similarity and variability in category learning and generalization across two time-points in development: adulthood (n = 14) and late childhood (n = 13). During this study, participants were repeatedly exposed to category members from different distributions. After a period of adaptation, a deviant stimulus that differed from the expected distribution was then presented. This deviant differed in either an invariant dimension (a feature that remained consistent throughout presentation was altered) or a similarity dimension (a feature that changed throughout exposure was changed in a new dimension). Our results can be summarized in three main findings: (1) Variability during exposure recruited the right fusiform gyrus to a greater extent than tight exposure. (2) Deviant items were generalized based on the exemplar distributions during exposure, although children only generalized items if provided variable exposure. (3) Variability influenced release to a greater extent in children than adults. These results are discussed in relation to the variability and category learning literature more broadly.
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Affiliation(s)
- Daniel J Plebanek
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Karin H James
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA.
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9
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Ando A, Parzer P, Kaess M, Schell S, Henze R, Delorme S, Stieltjes B, Resch F, Brunner R, Koenig J. Calendar age and puberty-related development of regional gray matter volume and white matter tracts during adolescence. Brain Struct Funct 2021; 226:927-937. [PMID: 33471191 PMCID: PMC7981330 DOI: 10.1007/s00429-020-02208-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Accepted: 12/22/2020] [Indexed: 01/25/2023]
Abstract
Background Adolescence is a critical time for brain development. Findings from previous studies have been inconsistent, failing to distinguish the influence of pubertal status and aging on brain maturation. The current study sought to address these inconsistencies, addressing the trajectories of pubertal development and aging by longitudinally tracking structural brain development during adolescence. Methods Two cohorts of healthy children were recruited (cohort 1: 9–10 years old; cohort 2: 12–13 years old at baseline). MRI data were acquired for gray matter volume and white matter tract measures. To determine whether age, pubertal status, both or their interaction best modelled longitudinal data, we compared four multi-level linear regression models to the null model (general brain growth indexed by total segmented volume) using Bayesian model selection. Results Data were collected at baseline (n = 116), 12 months (n = 97) and 24 months (n = 84) after baseline. Findings demonstrated that the development of most regional gray matter volume, and white matter tract measures, were best modelled by age. Interestingly, precentral and paracentral regions of the cortex, as well as the accumbens demonstrated significant preference for the pubertal status model. None of the white matter tract measures were better modelled by pubertal status. Limitations: The major limitation of this study is the two-cohort recruitment. Although this allowed a faster coverage of the age span, a complete per person trajectory over 6 years of development (9–15 years) could not be investigated. Conclusions Comparing the impact of age and pubertal status on regional gray matter volume and white matter tract measures, we found age to best predict longitudinal changes. Further longitudinal studies investigating the differential influence of puberty status and age on brain development in more diverse samples are needed to replicate the present results and address mechanisms underlying norm-variants in brain development. Supplementary Information The online version contains supplementary material available at 10.1007/s00429-020-02208-1.
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Affiliation(s)
- Ayaka Ando
- Section for Experimental Child and Adolescent Psychiatry, Department of Child and Adolescent Psychiatry, Centre for Psychosocial Medicine, University of Heidelberg, Blumenstr. 8, 69115, Heidelberg, Germany
| | - Peter Parzer
- Clinic for Child and Adolescent Psychiatry, Centre for Psychosocial Medicine, University of Heidelberg, Heidelberg, Germany
| | - Michael Kaess
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland.,Section for Translational Child and Adolescent Psychiatry, Department of Child and Adolescent Psychiatry, Centre for Psychosocial Medicine, University of Heidelberg, Heidelberg, Germany
| | - Susanne Schell
- Clinic for Child and Adolescent Psychiatry, Centre for Psychosocial Medicine, University of Heidelberg, Heidelberg, Germany
| | - Romy Henze
- Department of Psychiatry, Psychotherapy and Psychosomatics, Evangelisches Krankenhaus Königin Elisabeth Herzberge, Berlin, Germany.,Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany.,Clinical Psychology and Psychotherapy, Freie Universität Berlin, Berlin, Germany
| | - Stefan Delorme
- Department of Radiology, German Cancer Research Centre, Heidelberg, Germany
| | - Bram Stieltjes
- Department of Radiology, German Cancer Research Centre, Heidelberg, Germany.,Department of Radiology and Nuclear Medicine, Universitätsspital Basel, Basel, Switzerland
| | - Franz Resch
- Clinic for Child and Adolescent Psychiatry, Centre for Psychosocial Medicine, University of Heidelberg, Heidelberg, Germany
| | - Romuald Brunner
- Clinic for Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University of Regensburg, Regensburg, Germany
| | - Julian Koenig
- Section for Experimental Child and Adolescent Psychiatry, Department of Child and Adolescent Psychiatry, Centre for Psychosocial Medicine, University of Heidelberg, Blumenstr. 8, 69115, Heidelberg, Germany. .,University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland.
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10
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Lipp A, Cohen Kadosh K. Training the anxious brain: using fMRI-based neurofeedback to change brain activity in adolescence. Dev Med Child Neurol 2020; 62:1239-1244. [PMID: 32638360 DOI: 10.1111/dmcn.14611] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Revised: 04/20/2020] [Accepted: 05/20/2020] [Indexed: 12/17/2022]
Abstract
Anxiety disorders are a leading cause of morbidity and entail a lot of costs. Adolescence is characterized by social fears and poor emotion regulation abilities which together increase the likelihood of the emergence of anxiety disorders. This emotion dysregulation is potentially caused by the emotion regulating brain areas, such as the prefrontal cortex and temporal cortex, that are still undergoing developmental changes throughout late adolescence. Recently, new approaches have used functional magnetic resonance imaging-based neurofeedback to help participants gain control over emotion regulation brain networks by receiving real-time feedback on their brain activity and to use effective emotion regulation abilities. In this review, we provide an overview of the developmental changes in the brain and the corresponding behavioural changes, and explore how these can be influenced during adolescence using neurofeedback. We conclude that recent studies show promising results that children and adolescents can self-regulate emotion regulation brain networks thereby supporting the development of effective emotion regulation abilities. WHAT THIS PAPER ADDS: Functional magnetic resonance imaging-based neurofeedback can be used for brain self-regulation in development. The emotion regulation networks play a key role in treating social anxiety with neurofeedback.
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Affiliation(s)
- Annalisa Lipp
- School of Psychology, University of Surrey, Guildford, UK
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11
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Junge C, Valkenburg PM, Deković M, Branje S. The building blocks of social competence: Contributions of the Consortium of Individual Development. Dev Cogn Neurosci 2020; 45:100861. [PMID: 32957027 PMCID: PMC7509192 DOI: 10.1016/j.dcn.2020.100861] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Revised: 06/26/2020] [Accepted: 09/01/2020] [Indexed: 02/06/2023] Open
Abstract
Social competence refers to the ability to engage in meaningful interactions with others. It is a crucial skill potentially malleable to interventions. Nevertheless, it remains difficult to select which children, which periods in a child's life, and which underlying skills form optimal targets for interventions. Development of social competence is complex to characterize because (a) it is by nature context- dependent; (b) it is subserved by multiple relevant processes that develop at different times in a child's life; and (c) over the years multiple, possibly conflicting, ways have been coined to index a child's social competence. The current paper elaborates upon a theoretical model of social competence developed by Rose-Krasnor (Rose- Krasnor, 1997; Rose-Krasnor and Denham, 2009), and it makes concrete how underlying skills and the variety of contexts of social interaction are both relevant dimensions of social competence that might change over development. It then illustrates how the cohorts and work packages in the Consortium on Individual Development each provide empirical contributions necessary for testing this model on the development of social competence.
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Affiliation(s)
- Caroline Junge
- Departments of Developmental and Experimental Psychology, Utrecht University, Utrecht, the Netherlands.
| | - Patti M Valkenburg
- Amsterdam School of Communication Research ASCoR, University of Amsterdam, Amsterdam, the Netherlands
| | - Maja Deković
- Department of Clinical Child and Family Studies, Utrecht University, Utrecht, the Netherlands
| | - Susan Branje
- Department of Youth and Family, Utrecht University, Utrecht, the Netherlands
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12
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Luo L, Zhang Q, Wang J, Lin Q, Zhao B, Xu M, Langley C, Li H, Gao S. The baby schema effect in adolescence and its difference from that in adulthood. J Exp Child Psychol 2020; 198:104908. [PMID: 32600740 DOI: 10.1016/j.jecp.2020.104908] [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: 11/26/2019] [Revised: 05/12/2020] [Accepted: 05/13/2020] [Indexed: 01/10/2023]
Abstract
The baby schema effect induced by particular features of baby faces acts as an innate releasing mechanism that evokes positive emotions and instinctual behavioral responses. Our prior research in adults has revealed that this effect initially found in infancy extends into child faces. Adolescence is an important period involving development in various aspects of cognition, including face perception. Here, we investigated whether the extended baby schema effect we previously found in adult observers develops earlier-in adolescence-and how different it appears in adolescents as compared with in adults. In the current study, 76 adolescents and 77 adults were asked to judge the likeability of 148 neutral faces of infants and children (0.08-6.5 years of age) on 7-point scales. Results showed that both adolescents and adults perceived the faces of both infants and children younger than 4.6 years as more likeable relative to those of older children, indicating that the baby schema effect previously found in adulthood also occurs in adolescence. However, adolescents rated lower than adults toward the infant and child faces across all face ages, suggesting that this effect might be under development in adolescence. Overall, our findings provide new evidence for the development of face perception in adolescence and demonstrate age-related changes in innate releasing mechanisms in our protective and caretaking responses toward infants and children.
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Affiliation(s)
- Lizhu Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
| | - Qiang Zhang
- Department of Obstetrics and Gynecology, Chengdu Women's and Children's Central Hospital, Chengdu 610091, People's Republic of China
| | - Jiaojian Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
| | - Qiyuan Lin
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
| | - Bingmei Zhao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
| | - Min Xu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
| | - Christelle Langley
- Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, UK
| | - Hong Li
- Institute for Brain and Psychological Sciences, Sichuan Normal University, Chengdu 610068, People's Republic of China.
| | - Shan Gao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China; School of Foreign Languages, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China.
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13
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Biagianti B, Conelea C, Brambilla P, Bernstein G. A systematic review of treatments targeting cognitive biases in socially anxious adolescents: Special Section on "Translational and Neuroscience Studies in Affective Disorders" Section Editor, Maria Nobile MD, PhD. J Affect Disord 2020; 264:543-551. [PMID: 32056778 PMCID: PMC7024067 DOI: 10.1016/j.jad.2019.12.002] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/03/2019] [Revised: 11/13/2019] [Accepted: 12/02/2019] [Indexed: 12/30/2022]
Abstract
BACKGROUND Adolescence is a period of brain plasticity that is affected by social and affective stimuli. Adaptive neurodevelopmental changes in the context of complex social situations may precipitate or exacerbate cognitive biases (i.e., attention and/or interpretation biases) and predispose at-risk individuals to symptoms of social anxiety. METHODS This systematic review followed the PRISMA guidelines. Nine adolescent studies were examined including 3 studies using Cognitive Bias Modification Training (CBMT) to target attention biases (CBMT-A), 3 studies using CBMT to target interpretation biases (CBMT-I), and 3 aimed at reducing both attention and interpretation biases. RESULTS The studies of CBMT-A alone did not find significant effects on cognitive and clinical outcomes. However, studies of CBMT-I alone showed some improvement in interpretation bias. The combination of CBMT-A and CBMT-I appeared promising in reducing both attentionl and interpretation biases. LIMITATIONS The paucity of studies and the heterogeneity across studies (e.g., format of CBMT, assessment measures) limit the calculation of overall effect sizes and the examination of predictors, moderators, and mediators of outcome. CONCLUSIONS Technology-driven interventions such as CBMT have the potential to extend treatments outside the clinic setting and to augment current therapies for social anxiety. Further research is needed to develop CBMT procedures that optimize learning in group and real-world settings and to identify predictors of treatment response. Understanding the neural correlates of response to CBMT may help identify future targets for intervention.
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Affiliation(s)
- Bruno Biagianti
- Department of R&D, Posit Science Corporation, San Francisco, CA, USA; Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy.
| | - Christine Conelea
- Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - Paolo Brambilla
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy,Department of Neurosciences and Mental Health, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Gail Bernstein
- Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
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14
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Current progress in real-time functional magnetic resonance-based neurofeedback: Methodological challenges and achievements. Neuroimage 2019; 202:116107. [DOI: 10.1016/j.neuroimage.2019.116107] [Citation(s) in RCA: 55] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2018] [Revised: 07/26/2019] [Accepted: 08/16/2019] [Indexed: 12/21/2022] Open
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15
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Coureaud G, Letagneaux C, Thomas‐Danguin T, Romagny S. Developmental changes in elemental and configural perception of odor mixtures in young rabbits. Dev Psychobiol 2019; 62:471-483. [DOI: 10.1002/dev.21929] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2019] [Revised: 09/12/2019] [Accepted: 09/18/2019] [Indexed: 11/08/2022]
Affiliation(s)
- Gérard Coureaud
- Centre de Recherche en Neurosciences de Lyon (Lyon Neuroscience Research Center) INSERM U1028, CNRS UMR 5292 Université Claude Bernard Lyon 1 Centre Hospitalier le Vinatier ‐ Bâtiment Neurocampus Bron Cedex France
| | - Chloé Letagneaux
- Centre des Sciences du Goût et de l'Alimentation AgroSup Dijon, CNRS UMR 6265, INRA 1324 Université Bourgogne Franche‐Comté Dijon France
| | - Thierry Thomas‐Danguin
- Centre des Sciences du Goût et de l'Alimentation AgroSup Dijon, CNRS UMR 6265, INRA 1324 Université Bourgogne Franche‐Comté Dijon France
| | - Sébastien Romagny
- Centre des Sciences du Goût et de l'Alimentation AgroSup Dijon, CNRS UMR 6265, INRA 1324 Université Bourgogne Franche‐Comté Dijon France
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16
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Morningstar M, Grannis C, Mattson WI, Nelson EE. Associations Between Adolescents' Social Re-orientation Toward Peers Over Caregivers and Neural Response to Teenage Faces. Front Behav Neurosci 2019; 13:108. [PMID: 31178704 PMCID: PMC6544008 DOI: 10.3389/fnbeh.2019.00108] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2019] [Accepted: 05/02/2019] [Indexed: 12/29/2022] Open
Abstract
Adolescence is a period of intensive development in body, brain, and behavior. Potentiated by changes in hormones and neural response to social stimuli, teenagers undergo a process of social re-orientation away from their caregivers and toward expanding peer networks. The current study examines how relative relational closeness to peers (compared to parents) during adolescence is linked to neural response to the facial emotional expressions of other teenagers. Self-reported closeness with friends (same- and opposite-sex) and parents (mother and father), and neural response to facial stimuli during fMRI, were assessed in 8- to 19-year-old typically developing youth (n = 40, mean age = 13.90 years old, SD = 3.36; 25 female). Youth who reported greater relative closeness with peers than with parents showed decreased activation in the dorsolateral prefrontal cortex (dlPFC) during stimulus presentation, which may reflect lessened inhibitory control or regulatory response to peer-aged faces. Functional connectivity between the dlPFC and dorsal striatum was greatest in older youth who were closer to peers; in contrast, negative coupling between these regions was noted for both younger participants who were closer to peers and older participants who were closer to their parents. In addition, the association between relative closeness to peers and neural activation in regions of the social brain varied by emotion type and age. Results suggest that the re-orientation toward peers that occurs during adolescence is accompanied by changes in neural response to peer-aged social signals in social cognitive, prefrontal, and subcortical networks.
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Affiliation(s)
- Michele Morningstar
- Center for Biobehavioral Health, Nationwide Children’s Hospital, Columbus, OH, United States
- Department of Pediatrics, The Ohio State University, Columbus, OH, United States
| | - Connor Grannis
- Center for Biobehavioral Health, Nationwide Children’s Hospital, Columbus, OH, United States
| | - Whitney I. Mattson
- Center for Biobehavioral Health, Nationwide Children’s Hospital, Columbus, OH, United States
| | - Eric E. Nelson
- Center for Biobehavioral Health, Nationwide Children’s Hospital, Columbus, OH, United States
- Department of Pediatrics, The Ohio State University, Columbus, OH, United States
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17
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van Hoorn J, McCormick EM, Telzer EH. Moderate social sensitivity in a risky context supports adaptive decision making in adolescence: evidence from brain and behavior. Soc Cogn Affect Neurosci 2018. [PMID: 29529318 PMCID: PMC6007597 DOI: 10.1093/scan/nsy016] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
Adolescence is a time of increased social-affective sensitivity, which is often related to heightened health-risk behaviors. However, moderate levels of social sensitivity, relative to either low (social vacuum) or high levels (exceptionally attuned), may confer benefits as it facilitates effective navigation of the social world. The present fMRI study tested a curvilinear relationship between social sensitivity and adaptive decision-making. Participants (ages 12-16; N = 35) played the Social Analogue Risk Task, which measures participants' willingness to knock on doors in order to earn points. With each knock, the facial expression of the house's resident shifted from happy to somewhat angrier. If the resident became too angry, the door slammed and participants lost points. Social sensitivity was defined as the extent to which adolescents adjusted their risky choices based on shifting facial expressions. Results confirmed a curvilinear relationship between social sensitivity and self-reported adaptive decision-making at the behavioral and neural level. Moderate adolescent social sensitivity was modulated via heightened tracking of social cues in the temporoparietal junction, insula and dorsolateral prefrontal cortex and related to adaptive decision-making. These findings suggest that social-affective sensitivity may positively impact outcomes in adolescence and have implications for interventions to help adolescents reach mature social goals into adulthood.
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Affiliation(s)
- Jorien van Hoorn
- Department of Psychology & Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Ethan M McCormick
- Department of Psychology & Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Eva H Telzer
- Department of Psychology & Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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18
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Bathelt J, Gathercole SE, Johnson A, Astle DE. Differences in brain morphology and working memory capacity across childhood. Dev Sci 2018; 21:e12579. [PMID: 28748537 PMCID: PMC5947821 DOI: 10.1111/desc.12579] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2016] [Accepted: 04/13/2017] [Indexed: 01/13/2023]
Abstract
Working memory (WM) skills are closely associated with learning progress in key areas such as reading and mathematics across childhood. As yet, however, little is known about how the brain systems underpinning WM develop over this critical developmental period. The current study investigated whether and how structural brain correlates of components of the working memory system change over development. Verbal and visuospatial short-term and working memory were assessed in 153 children between 5.58 and 15.92 years, and latent components of the working memory system were derived. Fractional anisotropy and cortical thickness maps were derived from T1-weighted and diffusion-weighted MRI and processed using eigenanatomy decomposition. There was a greater involvement of the corpus callosum and posterior temporal white matter in younger children for performance associated with the executive part of the working memory system. For older children, this was more closely linked with the thickness of the occipitotemporal cortex. These findings suggest that increasing specialization leads to shifts in the contribution of neural substrates over childhood, moving from an early dependence on a distributed system supported by long-range connections to later reliance on specialized local circuitry. Our findings demonstrate that despite the component factor structure being stable across childhood, the underlying brain systems supporting working memory change. Taking the age of the child into account, and not just their overall score, is likely to be critical for understanding the nature of the limitations on their working memory capacity.
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Affiliation(s)
- Joe Bathelt
- MRC Cognition and Brain Sciences UnitCambridgeUK
| | | | - Amy Johnson
- MRC Cognition and Brain Sciences UnitCambridgeUK
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Age-related increase of image-invariance in the fusiform face area. Dev Cogn Neurosci 2018; 31:46-57. [PMID: 29738921 PMCID: PMC6969195 DOI: 10.1016/j.dcn.2018.04.005] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2017] [Revised: 04/12/2018] [Accepted: 04/14/2018] [Indexed: 11/23/2022] Open
Abstract
Image invariance in the FFA increases from age seven to adulthood. These results are confirmed by two independent ROI analyses. Adaptation in the FFA relates to the ability to recognize a face in multiple images.
Face recognition undergoes prolonged development from childhood to adulthood, thereby raising the question which neural underpinnings are driving this development. Here, we address the development of the neural foundation of the ability to recognize a face across naturally varying images. Fourteen children (ages, 7–10) and 14 adults (ages, 20–23) watched images of either the same or different faces in a functional magnetic resonance imaging adaptation paradigm. The same face was either presented in exact image repetitions or in varying images. Additionally, a subset of participants completed a behavioral task, in which they decided if the face in consecutively presented images belonged to the same person. Results revealed age-related increases in neural sensitivity to face identity in the fusiform face area. Importantly, ventral temporal face-selective regions exhibited more image-invariance – as indicated by stronger adaptation for different images of the same person – in adults compared to children. Crucially, the amount of adaptation to face identity across varying images was correlated with the ability to recognize individual faces in different images. These results suggest that the increase of image-invariance in face-selective regions might be related to the development of face recognition skills.
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He W, Johnson BW. Development of face recognition: Dynamic causal modelling of MEG data. Dev Cogn Neurosci 2018; 30:13-22. [PMID: 29197727 PMCID: PMC6969123 DOI: 10.1016/j.dcn.2017.11.010] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2017] [Revised: 11/21/2017] [Accepted: 11/22/2017] [Indexed: 10/27/2022] Open
Abstract
Electrophysiological studies of adults indicate that brain activity is enhanced during viewing of repeated faces, at a latency of about 250 ms after the onset of the face (M250/N250). The present study aimed to determine if this effect was also present in preschool-aged children, whose brain activity was measured in a custom-sized pediatric MEG system. The results showed that, unlike adults, face repetition did not show any significant modulation of M250 amplitude in children; however children's M250 latencies were significantly faster for repeated than non-repeated faces. Dynamic causal modelling (DCM) of the M250 in both age groups tested the effects of face repetition within the core face network including the occipital face area (OFA), the fusiform face area (FFA), and the superior temporal sulcus (STS). DCM revealed that repetition of identical faces altered both forward and backward connections in children and adults; however the modulations involved inputs to both FFA and OFA in adults but only to OFA in children. These findings suggest that the amplitude-insensitivity of the immature M250 may be due to a weaker connection between the FFA and lower visual areas.
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Affiliation(s)
- Wei He
- Department of Cognitive Science, Macquarie University, New South Wales 2109, Australia; Australian Research Council Centre of Excellence in Cognition and Its Disorders, Macquarie University, New South Wales 2109, Australia.
| | - Blake W Johnson
- Department of Cognitive Science, Macquarie University, New South Wales 2109, Australia; Australian Research Council Centre of Excellence in Cognition and Its Disorders, Macquarie University, New South Wales 2109, Australia
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Priming Facial Gender and Emotional Valence: The Influence of Spatial Frequency on Face Perception in ASD. J Autism Dev Disord 2017; 47:927-946. [PMID: 28070789 DOI: 10.1007/s10803-016-3017-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
Adolescents with and without autism spectrum disorder (ASD) performed two priming experiments in which they implicitly processed a prime stimulus, containing high and/or low spatial frequency information, and then explicitly categorized a target face either as male/female (gender task) or as positive/negative (Valence task). Adolescents with ASD made more categorization errors than typically developing adolescents. They also showed an age-dependent improvement in categorization speed and had more difficulties with categorizing facial expressions than gender. However, in neither of the categorization tasks, we found group differences in the processing of coarse versus fine prime information. This contradicted our expectations, and indicated that the perceptual differences between adolescents with and without ASD critically depended on the processing time available for the primes.
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22
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Nelson EE. Learning through the ages: How the brain adapts to the social world across development. COGNITIVE DEVELOPMENT 2017. [DOI: 10.1016/j.cogdev.2017.02.013] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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23
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The Lateral Occipital Cortex Is Selective for Object Shape, Not Texture/Color, at Six Months. J Neurosci 2017; 37:3698-3703. [PMID: 28264984 DOI: 10.1523/jneurosci.3300-16.2017] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2016] [Revised: 01/04/2017] [Accepted: 02/08/2017] [Indexed: 11/21/2022] Open
Abstract
Understanding how the human visual system develops is crucial to understanding the nature and organization of our complex and varied visual representations. However, previous investigations of the development of the visual system using fMRI are primarily confined to a subset of the visual system (high-level vision: faces, scenes) and relatively late in visual development (starting at 4-5 years of age). The current study extends our understanding of human visual development by presenting the first systematic investigation of a mid-level visual region [the lateral occipital cortex (LOC)] in a population much younger than has been investigated in the past: 6 month olds. We use functional near-infrared spectroscopy (fNIRS), an emerging optical method for recording cortical hemodynamics, to perform neuroimaging with this very young population. Whereas previous fNIRS studies have suffered from imprecise neuroanatomical localization, we rely on the most rigorous MR coregistration of fNIRS data to date to image the infant LOC. We find surprising evidence that at 6 months the LOC has functional specialization that is highly similar to adults. Following Cant and Goodale (2007), we investigate whether the LOC tracks shape information and not other cues to object identity (e.g., texture/material). This finding extends evidence of LOC specialization from early childhood into infancy and earlier than developmental trajectories of high-level visual regions.SIGNIFICANCE STATEMENT Understanding visual development is crucial to understanding the nature of visual representations in the human brain. Previous studies of visual development have investigated children (4 years and older) and high-level visual areas. This study expands our knowledge of visual development by investigating the functional development of mid-level vision [lateral occipital cortex (LOC)] early in infancy. We find surprisingly adult-like functional specialization of the LOC by 6 months of age: infants exhibit shape selectivity, but not object selectivity, in this region.
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Soares SC, Maior RS, Isbell LA, Tomaz C, Nishijo H. Fast Detector/First Responder: Interactions between the Superior Colliculus-Pulvinar Pathway and Stimuli Relevant to Primates. Front Neurosci 2017; 11:67. [PMID: 28261046 PMCID: PMC5314318 DOI: 10.3389/fnins.2017.00067] [Citation(s) in RCA: 49] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2016] [Accepted: 01/30/2017] [Indexed: 12/17/2022] Open
Abstract
Primates are distinguished from other mammals by their heavy reliance on the visual sense, which occurred as a result of natural selection continually favoring those individuals whose visual systems were more responsive to challenges in the natural world. Here we describe two independent but also interrelated visual systems, one cortical and the other subcortical, both of which have been modified and expanded in primates for different functions. Available evidence suggests that while the cortical visual system mainly functions to give primates the ability to assess and adjust to fluid social and ecological environments, the subcortical visual system appears to function as a rapid detector and first responder when time is of the essence, i.e., when survival requires very quick action. We focus here on the subcortical visual system with a review of behavioral and neurophysiological evidence that demonstrates its sensitivity to particular, often emotionally charged, ecological and social stimuli, i.e., snakes and fearful and aggressive facial expressions in conspecifics. We also review the literature on subcortical involvement during another, less emotional, situation that requires rapid detection and response-visually guided reaching and grasping during locomotion-to further emphasize our argument that the subcortical visual system evolved as a rapid detector/first responder, a function that remains in place today. Finally, we argue that investigating deficits in this subcortical system may provide greater understanding of Parkinson's disease and Autism Spectrum disorders (ASD).
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Affiliation(s)
- Sandra C. Soares
- Department of Education and Psychology, CINTESIS.UA, University of AveiroAveiro, Portugal
- Division of Psychology, Department of Clinical Neuroscience, Karolinska InstituteStockholm, Sweden
- William James Research Center, Instituto Superior de Psicologia AplicadaLisbon, Portugal
| | - Rafael S. Maior
- Division of Psychology, Department of Clinical Neuroscience, Karolinska InstituteStockholm, Sweden
- Department of Physiological Sciences, Primate Center, Institute of Biology, University of BrasíliaBrasília, Brazil
| | - Lynne A. Isbell
- Department of Anthropology, University of California, DavisDavis, CA, USA
| | - Carlos Tomaz
- Department of Physiological Sciences, Primate Center, Institute of Biology, University of BrasíliaBrasília, Brazil
- Ceuma University, Neuroscience Research CoordinationSão Luis, Brazil
| | - Hisao Nishijo
- System Emotional Science, Graduate School of Medicine and Pharmaceutical Sciences, University of ToyamaToyama, Japan
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25
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Perception and recognition of faces in adolescence. Sci Rep 2016; 6:33497. [PMID: 27647477 PMCID: PMC5028728 DOI: 10.1038/srep33497] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2016] [Accepted: 08/26/2016] [Indexed: 12/03/2022] Open
Abstract
Most studies on the development of face cognition abilities have focussed on childhood, with early maturation accounts contending that face cognition abilities are mature by 3–5 years. Late maturation accounts, in contrast, propose that some aspects of face cognition are not mature until at least 10 years. Here, we measured face memory and face perception, two core face cognition abilities, in 661 participants (397 females) in four age groups (younger adolescents (11.27–13.38 years); mid-adolescents (13.39–15.89 years); older adolescents (15.90–18.00 years); and adults (18.01–33.15 years)) while controlling for differences in general cognitive ability. We showed that both face cognition abilities mature relatively late, at around 16 years, with a female advantage in face memory, but not in face perception, both in adolescence and adulthood. Late maturation in the face perception task was driven mainly by protracted development in identity perception, while gaze perception abilities were already comparatively mature in early adolescence. These improvements in the ability to memorize, recognize and perceive faces during adolescence may be related to increasing exploratory behaviour and exposure to novel faces during this period of life.
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26
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Nordt M, Hoehl S, Weigelt S. The use of repetition suppression paradigms in developmental cognitive neuroscience. Cortex 2016; 80:61-75. [DOI: 10.1016/j.cortex.2016.04.002] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2015] [Revised: 02/29/2016] [Accepted: 04/04/2016] [Indexed: 10/21/2022]
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Social re-orientation and brain development: An expanded and updated view. Dev Cogn Neurosci 2015; 17:118-27. [PMID: 26777136 PMCID: PMC6990069 DOI: 10.1016/j.dcn.2015.12.008] [Citation(s) in RCA: 242] [Impact Index Per Article: 26.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2014] [Revised: 06/12/2015] [Accepted: 12/19/2015] [Indexed: 12/30/2022] Open
Abstract
We expand our adolescent re-orientation model to include other developmental periods. We review neuroimaging literature on social information processing. We combine human and animal based approaches to social behavior.
Social development has been the focus of a great deal of neuroscience based research over the past decade. In this review, we focus on providing a framework for understanding how changes in facets of social development may correspond with changes in brain function. We argue that (1) distinct phases of social behavior emerge based on whether the organizing social force is the mother, peer play, peer integration, or romantic intimacy; (2) each phase is marked by a high degree of affect-driven motivation that elicits a distinct response in subcortical structures; (3) activity generated by these structures interacts with circuits in prefrontal cortex that guide executive functions, and occipital and temporal lobe circuits, which generate specific sensory and perceptual social representations. We propose that the direction, magnitude and duration of interaction among these affective, executive, and perceptual systems may relate to distinct sensitive periods across development that contribute to establishing long-term patterns of brain function and behavior.
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28
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Cohen Kadosh K, Krause B, King AJ, Near J, Cohen Kadosh R. Linking GABA and glutamate levels to cognitive skill acquisition during development. Hum Brain Mapp 2015; 36:4334-45. [PMID: 26350618 PMCID: PMC4832309 DOI: 10.1002/hbm.22921] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2015] [Revised: 07/06/2015] [Accepted: 07/16/2015] [Indexed: 11/07/2022] Open
Abstract
Developmental adjustments in the balance of excitation and inhibition are thought to constrain the plasticity of sensory areas of the cortex. It is unknown however, how changes in excitatory or inhibitory neurochemical expression (glutamate, γ-aminobutyric acid (GABA)) contribute to skill acquisition during development. Here we used single-voxel proton magnetic resonance spectroscopy (1H-MRS) to reveal how differences in cortical glutamate vs. GABA ratios relate to face proficiency and working memory abilities in children and adults. We show that higher glutamate levels in the inferior frontal gyrus correlated positively with face processing proficiency in the children, but not the adults, an effect which was independent of age-dependent differences in underlying cortical gray matter. Moreover, we found that glutamate/GABA levels and gray matter volume are dissociated at the different maturational stages. These findings suggest that increased excitation during development is linked to neuroplasticity and the acquisition of new cognitive skills. They also offer a new, neurochemical approach to investigating the relationship between cognitive performance and brain development across the lifespan.
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Affiliation(s)
- Kathrin Cohen Kadosh
- Department of Experimental PsychologyUniversity of OxfordOxfordUnited Kingdom
- Department of PsychologyInstitute of Psychiatry King's College LondonLondonUnited Kingdom
| | - Beatrix Krause
- Department of Experimental PsychologyUniversity of OxfordOxfordUnited Kingdom
| | - Andrew J. King
- Department of Physiology, Anatomy and GeneticsUniversity of OxfordOxfordUnited Kingdom
| | - Jamie Near
- Department of PsychiatryMcGill UniversityMontrealCanada
| | - Roi Cohen Kadosh
- Department of Experimental PsychologyUniversity of OxfordOxfordUnited Kingdom
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29
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Adolescence as a Sensitive Period of Brain Development. Trends Cogn Sci 2015; 19:558-566. [DOI: 10.1016/j.tics.2015.07.008] [Citation(s) in RCA: 479] [Impact Index Per Article: 53.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2015] [Revised: 07/20/2015] [Accepted: 07/24/2015] [Indexed: 01/17/2023]
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30
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Wiggins JL, Adleman NE, Kim P, Oakes AH, Hsu D, Reynolds RC, Chen G, Pine DS, Brotman MA, Leibenluft E. Developmental differences in the neural mechanisms of facial emotion labeling. Soc Cogn Affect Neurosci 2015; 11:172-81. [PMID: 26245836 DOI: 10.1093/scan/nsv101] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2015] [Accepted: 07/30/2015] [Indexed: 11/12/2022] Open
Abstract
Adolescence is a time of increased risk for the onset of psychological disorders associated with deficits in face emotion labeling. We used functional magnetic resonance imaging (fMRI) to examine age-related differences in brain activation while adolescents and adults labeled the emotion on fearful, happy and angry faces of varying intensities [0% (i.e. neutral), 50%, 75%, 100%]. Adolescents and adults did not differ on accuracy to label emotions. In the superior temporal sulcus, ventrolateral prefrontal cortex and middle temporal gyrus, adults show an inverted-U-shaped response to increasing intensities of fearful faces and a U-shaped response to increasing intensities of happy faces, whereas adolescents show the opposite patterns. In addition, adults, but not adolescents, show greater inferior occipital gyrus activation to negative (angry, fearful) vs positive (happy) emotions. In sum, when subjects classify subtly varying facial emotions, developmental differences manifest in several 'ventral stream' brain regions. Charting the typical developmental course of the brain mechanisms of socioemotional processes, such as facial emotion labeling, is an important focus for developmental psychopathology research.
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Affiliation(s)
- Jillian Lee Wiggins
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA,
| | - Nancy E Adleman
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA, Department of Psychology, The Catholic University of America, Washington, D.C., 20064, USA
| | - Pilyoung Kim
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA, Department of Psychology, University of Denver, Denver, CO, 80208, USA, and
| | - Allison H Oakes
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - Derek Hsu
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - Richard C Reynolds
- Scientific and Statistical Computing Core, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - Gang Chen
- Scientific and Statistical Computing Core, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - Daniel S Pine
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - Melissa A Brotman
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - Ellen Leibenluft
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
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31
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Nomi JS, Uddin LQ. Face processing in autism spectrum disorders: From brain regions to brain networks. Neuropsychologia 2015; 71:201-16. [PMID: 25829246 PMCID: PMC4506751 DOI: 10.1016/j.neuropsychologia.2015.03.029] [Citation(s) in RCA: 92] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2014] [Revised: 02/25/2015] [Accepted: 03/27/2015] [Indexed: 10/23/2022]
Abstract
Autism spectrum disorder (ASD) is characterized by reduced attention to social stimuli including the human face. This hypo-responsiveness to stimuli that are engaging to typically developing individuals may result from dysfunctioning motivation, reward, and attention systems in the brain. Here we review an emerging neuroimaging literature that emphasizes a shift from focusing on hypo-activation of isolated brain regions such as the fusiform gyrus, amygdala, and superior temporal sulcus in ASD to a more holistic approach to understanding face perception as a process supported by distributed cortical and subcortical brain networks. We summarize evidence for atypical activation patterns within brain networks that may contribute to social deficits characteristic of the disorder. We conclude by pointing to gaps in the literature and future directions that will continue to shed light on aspects of face processing in autism that are still under-examined. In particular, we highlight the need for more developmental studies and studies examining ecologically valid and naturalistic social stimuli.
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Affiliation(s)
- Jason S Nomi
- Department of Psychology, University of Miami, Coral Gables, FL, United States.
| | - Lucina Q Uddin
- Department of Psychology, University of Miami, Coral Gables, FL, United States; Neuroscience Program, University of Miami Miller School of Medicine, Miami, FL, United States.
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32
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He W, Garrido MI, Sowman PF, Brock J, Johnson BW. Development of effective connectivity in the core network for face perception. Hum Brain Mapp 2015; 36:2161-73. [PMID: 25704356 DOI: 10.1002/hbm.22762] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2014] [Revised: 01/22/2015] [Accepted: 01/28/2015] [Indexed: 11/11/2022] Open
Abstract
This study measured effective connectivity within the core face network in young children using a paediatric magnetoencephalograph (MEG). Dynamic casual modeling (DCM) of brain responses was performed in a group of adults (N = 14) and a group of young children aged from 3 to 6 years (N = 15). Three candidate DCM models were tested, and the fits of the MEG data to the three models were compared at both individual and group levels. The results show that the connectivity structure of the core face network differs significantly between adults and children. Further, the relative strengths of face network connections were differentially modulated by experimental conditions in the two groups. These results support the interpretation that the core face network undergoes significant structural configuration and functional specialization between four years of age and adulthood.
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Affiliation(s)
- Wei He
- Department of Cognitive Science, Macquarie University, New South Wales, Australia; Australian Research Council Centre of Excellence in Cognition and Its Disorders, Macquarie University, New South Wales, Australia
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He W, Brock J, Johnson BW. Face processing in the brains of pre-school aged children measured with MEG. Neuroimage 2014; 106:317-27. [PMID: 25463467 DOI: 10.1016/j.neuroimage.2014.11.029] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2014] [Revised: 10/29/2014] [Accepted: 11/13/2014] [Indexed: 10/24/2022] Open
Abstract
There are two competing theories concerning the development of face perception: a late maturation account and an early maturation account. Magnetoencephalography (MEG) neuroimaging holds promise for adjudicating between the two opposing accounts by providing objective neurophysiological measures of face processing, with sufficient temporal resolution to isolate face-specific brain responses from those associated with other sensory, cognitive and motor processes. The current study used a customized child MEG system to measure M100 and M170 brain responses in 15 children aged three to six years while they viewed faces, cars and their phase-scrambled counterparts. Compared to adults tested using the same stimuli in a conventional MEG system, children showed significantly larger and later M100 responses. Children's M170 responses, derived by subtracting the responses to phase-scrambled images from the corresponding images (faces or cars) were delayed in latency but otherwise resembled the adult M170. This component has not been obtained in previous studies of young children tested using conventional adult MEG systems. However children did show a markedly reduced M170 response to cars in comparison to adults. This may reflect children's lack of expertise with cars relative to faces. Taken together, these data are in accord with recent behavioural and neuroimaging data that support early maturation of the basic face processing functions.
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Affiliation(s)
- Wei He
- Department of Cognitive Science, ARC Centre of Excellence in Cognition and its Disorders, Macquarie University, NSW 2109, Australia.
| | - Jon Brock
- Department of Cognitive Science, ARC Centre of Excellence in Cognition and its Disorders, Macquarie University, NSW 2109, Australia
| | - Blake W Johnson
- Department of Cognitive Science, ARC Centre of Excellence in Cognition and its Disorders, Macquarie University, NSW 2109, Australia
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Johnson MH, Senju A, Tomalski P. The two-process theory of face processing: modifications based on two decades of data from infants and adults. Neurosci Biobehav Rev 2014; 50:169-79. [PMID: 25454353 DOI: 10.1016/j.neubiorev.2014.10.009] [Citation(s) in RCA: 168] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2014] [Revised: 08/24/2014] [Accepted: 10/12/2014] [Indexed: 10/24/2022]
Abstract
Johnson and Morton (1991. Biology and Cognitive Development: The Case of Face Recognition. Blackwell, Oxford) used Gabriel Horn's work on the filial imprinting model to inspire a two-process theory of the development of face processing in humans. In this paper we review evidence accrued over the past two decades from infants and adults, and from other primates, that informs this two-process model. While work with newborns and infants has been broadly consistent with predictions from the model, further refinements and questions have been raised. With regard to adults, we discuss more recent evidence on the extension of the model to eye contact detection, and to subcortical face processing, reviewing functional imaging and patient studies. We conclude with discussion of outstanding caveats and future directions of research in this field.
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Affiliation(s)
- Mark H Johnson
- Centre for Brain & Cognitive Development, Birkbeck, University of London, Malet Street, London WC1E 7HX, UK.
| | - Atsushi Senju
- Centre for Brain & Cognitive Development, Birkbeck, University of London, Malet Street, London WC1E 7HX, UK
| | - Przemyslaw Tomalski
- Neurocognitive Development Lab, Faculty of Psychology, University of Warsaw, Stawki 5/7, 00-183 Warsaw, Poland
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35
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Cook R, Brewer R, Shah P, Bird G. Intact facial adaptation in autistic adults. Autism Res 2014; 7:481-90. [PMID: 24757172 DOI: 10.1002/aur.1381] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2013] [Accepted: 03/23/2014] [Indexed: 11/07/2022]
Abstract
Adaptation paradigms seek to bias subsequently viewed stimuli through prolonged exposure to an adapting stimulus, thereby giving rise to an aftereffect. Recent experiments have found that children with autism spectrum disorders (ASD) show reduced facial aftereffects, prompting some researchers to speculate that all individuals with ASD exhibit deficient facial adaptation. However, caution is required when generalizing findings from samples of children with ASD to the wider ASD population. The reduced facial aftereffects seen in child samples may instead reflect delayed or atypical developmental trajectories, whereby individuals with ASD are slower to develop adaptive mechanisms. In the present study, two experiments were conducted to determine whether high-functioning adults with ASD also show diminished aftereffects for facial identity and expression. In Experiment 1, using a procedure that minimized the contribution of low-level retinotopic adaptation, we observed substantial aftereffects comparable to those seen in matched controls, for both facial identity and expression. A similar pattern of results was seen in Experiment 2 using a revised procedure that increased the contribution of retinotopic adaptation to the facial aftereffects observed. That adults with autism can show robust facial aftereffects raises the possibility that group differences are seen only at particular points during development, and may not be a lifelong feature of the condition.
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Affiliation(s)
- Richard Cook
- Department of Psychology, City University London, London, United Kingdom
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Affiliation(s)
- Sarah-Jayne Blakemore
- Institute of Cognitive Neuroscience, University College London, London, WC1N 3HT United Kingdom;
| | - Kathryn L. Mills
- Institute of Cognitive Neuroscience, University College London, London, WC1N 3HT United Kingdom;
- Child Psychiatry Branch, National Institute of Mental Health, Bethesda, Maryland 20892
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37
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The building blocks of social communication. Adv Cogn Psychol 2013; 9:173-83. [PMID: 24605176 PMCID: PMC3902830 DOI: 10.2478/v10053-008-0145-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2013] [Accepted: 06/04/2013] [Indexed: 11/20/2022] Open
Abstract
In the present review, social communication will be discussed in the context of social cognition, and cold and hot cognition. The review presents research on prosody, processing of faces, multimodal processing of voice and face, and the impact of emotion on constructing semantic meaning. Since the focus of this mini review is on brain processes involved in these cognitive functions, the bulk of evidence presented will be from event related potential (ERP) studies as this methodology offers the best temporal resolution of cognitive events under study. The argument is made that social communication is accomplished via fast acting sensory processes and later, top down processes. Future directions both in terms of methodology and research questions are also discussed.
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38
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Distributed circuits, not circumscribed centers, mediate visual recognition. Trends Cogn Sci 2013; 17:210-9. [PMID: 23608364 DOI: 10.1016/j.tics.2013.03.007] [Citation(s) in RCA: 206] [Impact Index Per Article: 18.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2013] [Revised: 03/29/2013] [Accepted: 03/29/2013] [Indexed: 11/23/2022]
Abstract
Increasingly, the neural mechanisms that support visual cognition are being conceptualized as a distributed but integrated system, as opposed to a set of individual, specialized regions that each subserve a particular visual behavior. Consequently, there is an emerging emphasis on characterizing the functional, structural,and computational properties of these broad networks [corrected]. We present a novel theoretical perspective, which elucidates the developmental emergence, computational properties, and vulnerabilities of integrated circuits using face and word recognition as model domains. Additionally, we suggest that, rather than being disparate and independent, these neural circuits are overlapping and subject to the same computational constraints. Specifically, we argue that both word and face recognition rely on fine-grained visual representations but, by virtue of pressure to couple visual and language areas and to keep connection length short, the left hemisphere becomes more finely tuned for word recognition and, consequently, the right hemisphere becomes more finely tuned for face recognition. Thus, both hemispheres ultimately participate in both forms of visual recognition, but their respective contributions are asymmetrically weighted.
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