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Nenadić I, Schröder Y, Hoffmann J, Evermann U, Pfarr JK, Bergmann A, Hohmann DM, Keil B, Abu-Akel A, Stroth S, Kamp-Becker I, Jansen A, Grezellschak S, Meller T. Superior temporal sulcus folding, functional network connectivity, and autistic-like traits in a non-clinical population. Mol Autism 2024; 15:44. [PMID: 39380071 PMCID: PMC11463051 DOI: 10.1186/s13229-024-00623-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 09/17/2024] [Indexed: 10/10/2024] Open
Abstract
BACKGROUND Autistic-like traits (ALT) are prevalent across the general population and might be linked to some facets of a broader autism spectrum disorder (ASD) phenotype. Recent studies suggest an association of these traits with both genetic and brain structural markers in non-autistic individuals, showing similar spatial location of findings observed in ASD and thus suggesting a potential neurobiological continuum. METHODS In this study, we first tested an association of ALTs (assessed with the AQ questionnaire) with cortical complexity, a cortical surface marker of early neurodevelopment, and then the association with disrupted functional connectivity. We analysed structural T1-weighted and resting-state functional MRI scans in 250 psychiatrically healthy individuals without a history of early developmental disorders, in a first step using the CAT12 toolbox for cortical complexity analysis and in a second step we used regional cortical complexity findings to apply the CONN toolbox for seed-based functional connectivity analysis. RESULTS Our findings show a significant negative correlation of both AQ total and AQ attention switching subscores with left superior temporal sulcus (STS) cortical folding complexity, with the former being significantly correlated with STS to left lateral occipital cortex connectivity, while the latter showed significant positive correlation of STS to left inferior/middle frontal gyrus connectivity (n = 233; all p < 0.05, FWE cluster-level corrected). Additional analyses also revealed a significant correlation of AQ attention to detail subscores with STS to left lateral occipital cortex connectivity. LIMITATIONS Phenotyping might affect association results (e.g. choice of inventories); in addition, our study was limited to subclinical expressions of autistic-like traits. CONCLUSIONS Our findings provide further evidence for biological correlates of ALT even in the absence of clinical ASD, while establishing a link between structural variation of early developmental origin and functional connectivity.
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Affiliation(s)
- Igor Nenadić
- Cognitive Neuropsychiatry Lab, Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Rudolf-Bultmann-Str. 8, 35037, Marburg, Germany.
- Center for Mind, Brain, and Behavior (CMBB), University of Marburg, Justus Liebig University Gießen, and Technical University of Darmstadt, Hans-Meerwein-Straße 6, 35032, Marburg, Germany.
- Marburg University Hospital - UKGM, Marburg, Germany.
- LOEWE Center DYNAMIC, University of Marburg, Marburg, Germany.
| | - Yvonne Schröder
- Cognitive Neuropsychiatry Lab, Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Rudolf-Bultmann-Str. 8, 35037, Marburg, Germany
| | - Jonas Hoffmann
- Cognitive Neuropsychiatry Lab, Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Rudolf-Bultmann-Str. 8, 35037, Marburg, Germany
| | - Ulrika Evermann
- Cognitive Neuropsychiatry Lab, Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Rudolf-Bultmann-Str. 8, 35037, Marburg, Germany
- Center for Mind, Brain, and Behavior (CMBB), University of Marburg, Justus Liebig University Gießen, and Technical University of Darmstadt, Hans-Meerwein-Straße 6, 35032, Marburg, Germany
| | - Julia-Katharina Pfarr
- Cognitive Neuropsychiatry Lab, Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Rudolf-Bultmann-Str. 8, 35037, Marburg, Germany
- Center for Mind, Brain, and Behavior (CMBB), University of Marburg, Justus Liebig University Gießen, and Technical University of Darmstadt, Hans-Meerwein-Straße 6, 35032, Marburg, Germany
| | - Aliénor Bergmann
- Cognitive Neuropsychiatry Lab, Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Rudolf-Bultmann-Str. 8, 35037, Marburg, Germany
| | - Daniela Michelle Hohmann
- Cognitive Neuropsychiatry Lab, Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Rudolf-Bultmann-Str. 8, 35037, Marburg, Germany
- Center for Mind, Brain, and Behavior (CMBB), University of Marburg, Justus Liebig University Gießen, and Technical University of Darmstadt, Hans-Meerwein-Straße 6, 35032, Marburg, Germany
| | - Boris Keil
- Center for Mind, Brain, and Behavior (CMBB), University of Marburg, Justus Liebig University Gießen, and Technical University of Darmstadt, Hans-Meerwein-Straße 6, 35032, Marburg, Germany
- Institute of Medical Physics and Radiation Protection, Department of Life Science Engineering, TH Mittelhessen University of Applied Sciences, Giessen, Germany
- LOEWE Research Cluster for Advanced Medical Physics in Imaging and Therapy (ADMIT), TH Mittelhessen University of Applied Sciences, 35390, Giessen, Germany
- Department of Diagnostic and Interventional Radiology, University Hospital Marburg, Philipps-Universität Marburg, Marburg, Germany
| | - Ahmad Abu-Akel
- School of Psychological Sciences, University of Haifa, Haifa, Israel
- The Haifa Brain and Behavior Hub (HBBH), University of Haifa, Haifa, Israel
| | - Sanna Stroth
- Center for Mind, Brain, and Behavior (CMBB), University of Marburg, Justus Liebig University Gießen, and Technical University of Darmstadt, Hans-Meerwein-Straße 6, 35032, Marburg, Germany
- Department of Child and Adolescent Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
| | - Inge Kamp-Becker
- Center for Mind, Brain, and Behavior (CMBB), University of Marburg, Justus Liebig University Gießen, and Technical University of Darmstadt, Hans-Meerwein-Straße 6, 35032, Marburg, Germany
- Department of Child and Adolescent Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
| | - Andreas Jansen
- Center for Mind, Brain, and Behavior (CMBB), University of Marburg, Justus Liebig University Gießen, and Technical University of Darmstadt, Hans-Meerwein-Straße 6, 35032, Marburg, Germany
- BrainImaging Core Facility, School of Medicine, Philipps-Universität Marburg, Marburg, Germany
| | - Sarah Grezellschak
- Cognitive Neuropsychiatry Lab, Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Rudolf-Bultmann-Str. 8, 35037, Marburg, Germany
| | - Tina Meller
- Cognitive Neuropsychiatry Lab, Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Rudolf-Bultmann-Str. 8, 35037, Marburg, Germany
- Center for Mind, Brain, and Behavior (CMBB), University of Marburg, Justus Liebig University Gießen, and Technical University of Darmstadt, Hans-Meerwein-Straße 6, 35032, Marburg, Germany
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Proshina E, Deynekina T, Martynova O. Neurogenetics of Brain Connectivity: Current Approaches to the Study (Review). Sovrem Tekhnologii Med 2024; 16:66-76. [PMID: 39421629 PMCID: PMC11482091 DOI: 10.17691/stm2024.16.1.07] [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: 08/07/2023] [Indexed: 10/19/2024] Open
Abstract
Owing to the advances of neuroimaging techniques, a number of functional brain networks associated both with specific functions and the state of relative inactivity has been distinguished. A sufficient bulk of information has been accumulated on changes in connectivity (links between brain regions) in psychopathologies, for example, depression, schizophrenia, autism. Their genetic markers are being actively investigated using a candidate-gene approach or a genome-wide association study. At the same time, there is not much data considering connectivity as an intermediate link in the genotype-pathology chain, although it seems to be a reliable endophenotype, since it demonstrates a high stability and high heritability. In the present review, we consider the results of investigations devoted to the search for biomarkers, molecular and genetic associations of functional, partially anatomical, and effective connectivity. The main approaches to the evaluation of connectivity neurogenetics have been described, as well as specific genetic variants, for which the association with brain connectivity in psychiatric pathologies has been detected.
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Affiliation(s)
- E.A. Proshina
- Researcher, Centre for Cognition & Decision Making, Institute for Cognitive Neurosciences; National Research University Higher School of Economics, 20 Myasnitskaya St., Moscow, 101000, Russia
| | - T.S. Deynekina
- Analyst; Center for Strategic Planning and Management of Biomedical Health Risks of the Federal Medical Biological Agency, 10 Pogodinskaya St., Moscow, 119121, Russia
| | - O.V. Martynova
- Deputy Director, Head of the Laboratory of Human Higher Nervous Activity; Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Sciences, 5A Butlerova St., Moscow, 117485, Russia, Associate Professor, Department of Biology and Biotechnology; National Research University Higher School of Economics, 20 Myasnitskaya St., Moscow, 101000, Russia
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Junttila M, Jussila K, Joskitt L, Ebeling H, Kielinen M, Loukusa S, Miettunen J, Mäntymaa M, Mattila ML. Factor analysis of the autism spectrum screening questionnaire in a population-based child sample. Nord J Psychiatry 2023; 77:696-705. [PMID: 37355342 DOI: 10.1080/08039488.2023.2225060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 03/27/2023] [Accepted: 06/02/2023] [Indexed: 06/26/2023]
Abstract
PURPOSE The aim of this study was to investigate several possible factor structures of the Autism Spectrum Screening Questionnaire (ASSQ). MATERIALS AND METHODS We used the 27-item screening tool for school-aged children in a general population of 8-year-old children (n = 3,538) and compared the occurring solutions to previously published factor models. RESULTS A one-factor solution and a four-factor solution were identified in Exploratory Factor Analysis (EFA) and confirmed with Confirmatory Factor Analysis (CFA), while two-, three-, five- and six-factor solutions were rejected. In CFA, our four-factor solution showed the best goodness-of-fit indexes when compared with factor models previously presented by Posserud et al. and Ehlers et al. CONCLUSIONS The results indicate a strong underlying connection between all ASSQ items which is elicited by the one-factor solution. Although as a screening tool, ASSQ is functioning with the unifactorial solution, the four factors can help to identify certain clusters of autism spectrum traits.
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Affiliation(s)
- Maria Junttila
- Child Psychiatry, Oulu University Hospital, Oulu, Finland
- Research Unit of Clinical Medicine, Child Psychiatry, University of Oulu, Oulu, Finland
| | - Katja Jussila
- Child Psychiatry, Oulu University Hospital, Oulu, Finland
- Research Unit of Clinical Medicine, Child Psychiatry, University of Oulu, Oulu, Finland
- Division of Psychology, VISE, Faculty of Education and Psychology, University of Oulu, Finland
| | - Leena Joskitt
- Child Psychiatry, Oulu University Hospital, Oulu, Finland
- Research Unit of Clinical Medicine, Child Psychiatry, University of Oulu, Oulu, Finland
| | - Hanna Ebeling
- Child Psychiatry, Oulu University Hospital, Oulu, Finland
- Research Unit of Clinical Medicine, Child Psychiatry, University of Oulu, Oulu, Finland
| | | | - Soile Loukusa
- Research Unit of Logopedics, University of Oulu, Finland
| | - Jouko Miettunen
- Research Unit of Population Health, University of Oulu, Finland
- Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Finland
| | - Mirjami Mäntymaa
- Child Psychiatry, Oulu University Hospital, Oulu, Finland
- Research Unit of Clinical Medicine, Child Psychiatry, University of Oulu, Oulu, Finland
| | - Marja-Leena Mattila
- Child Psychiatry, Oulu University Hospital, Oulu, Finland
- Research Unit of Clinical Medicine, Child Psychiatry, University of Oulu, Oulu, Finland
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Abnormal negative feedback processing in individuals with autistic traits in the Iowa gambling task: Evidence from behavior and event-related potentials. Int J Psychophysiol 2021; 165:36-46. [PMID: 33647381 DOI: 10.1016/j.ijpsycho.2021.02.018] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Revised: 02/22/2021] [Accepted: 02/23/2021] [Indexed: 11/23/2022]
Abstract
Value-based decision making plays an important role in social interaction. Previous studies have reported that individuals with autism spectrum disorder (ASD) exhibit deficits in terms of decision making. However, it is still unknown clearly whether individuals with high autistic traits within nonclinical populations employ abnormal neural substrates in value-based decision-making. To explore this issue, we investigated value-based decision making and its neural substrates in individuals with high and low autistic traits within a typically developing population who completed the revised Iowa gambling task (IGT) based on measurements of event-related potentials (ERPs). The IGT net scores were significantly lower in the group with high autistic traits than the group with low autistic traits in the fifth and sixth blocks. The ERP results showed that the feedback-related negativity (FRN) amplitude in individuals with high autistic traits allowed slight discrimination between positive and negative feedback in the low-risk option. The event-related spectral perturbations (ERSPs) and inter-trial coherence (ITC) of the theta-band frequency were also lower in the group with high autistic traits than the group with low autistic traits in the loss low-risk option. The results obtained in this study indicate that individuals with high autistic traits exhibit an unusual negative feedback process and relevant neural substrate. The FRN amplitude and theta-band oscillation may comprise a neural index of abnormal decision-making processes in individuals with high autistic traits. This study of a small sample may be considered an important step toward a more comprehensive understanding of the autism "spectrum" within a nonclinical population based on cognitive neuroscience.
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Paul S, Arora A, Midha R, Vu D, Roy PK, Belmonte MK. Autistic traits and individual brain differences: functional network efficiency reflects attentional and social impairments, structural nodal efficiencies index systemising and theory-of-mind skills. Mol Autism 2021; 12:3. [PMID: 33478557 PMCID: PMC7818759 DOI: 10.1186/s13229-020-00377-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2019] [Accepted: 09/02/2020] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Autism is characterised not only by impaired social cognitive 'empathising' but also by superior rule-based 'systemising'. These cognitive domains intertwine within the categorical diagnosis of autism, yet behavioural genetics suggest largely independent heritability, and separable brain mechanisms. We sought to determine whether quantitative behavioural measures of autistic traits are dimensionally associated with structural and functional brain network integrity, and whether brain bases of autistic traits vary independently across individuals. METHODS Thirty right-handed neurotypical adults (12 females) were administered psychometric (Social Responsiveness Scale, Autism Spectrum Quotient and Systemising Quotient) and behavioural (Attention Network Test and theory-of-mind reaction time) measures of autistic traits, and structurally (diffusion tensor imaging) and functionally (500 s of 2 Hz eyes-closed resting fMRI) derived graph-theoretic measures of efficiency of information integration were computed throughout the brain and within subregions. RESULTS Social impairment was positively associated with functional efficiency (r = .47, p = .006), globally and within temporo-parietal and prefrontal cortices. Delayed orienting of attention likewise was associated with greater functional efficiency (r = - .46, p = .0133). Systemising was positively associated with global structural efficiency (r = .38, p = 0.018), driven specifically by temporal pole; theory-of-mind reaction time was related to structural efficiency (r = - .40, p = 0.0153) within right supramarginal gyrus. LIMITATIONS Interpretation of these relationships is complicated by the many senses of the term 'connectivity', including functional, structural and computational; by the approximation inherent in group functional anatomical parcellations when confronted with individual variation in functional anatomy; and by the validity, sensitivity and specificity of the several survey and experimental behavioural measures applied as correlates of brain structure and function. CONCLUSIONS Functional connectivities highlight distributed networks associated with domain-general properties such as attentional orienting and social cognition broadly, associating more impaired behaviour with more efficient brain networks that may reflect heightened feedforward information flow subserving autistic strengths and deficits alike. Structural connectivity results highlight specific anatomical nodes of convergence, reflecting cognitive and neuroanatomical independence of systemising and theory-of-mind. In addition, this work shows that individual differences in theory-of-mind related to brain structure can be measured behaviourally, and offers neuroanatomical evidence to pin down the slippery construct of 'systemising' as the capacity to construct invariant contextual associations.
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Affiliation(s)
- Subhadip Paul
- MIND Research Network, 1101 Yale Blvd NE, Albuquerque, NM, 87106, USA.,National Brain Research Centre, NH-8, Nainwal Mode, Manesar, 122051, India
| | - Aditi Arora
- National Brain Research Centre, NH-8, Nainwal Mode, Manesar, 122051, India.,Centre for Cognitive Neuroscience, Universität Salzburg, Kapitelgasse 4-6, 5020, Salzburg, Austria
| | - Rashi Midha
- National Brain Research Centre, NH-8, Nainwal Mode, Manesar, 122051, India.,National Institute of Mental Health and Neuro Sciences, Hosur Road, Bangalore, 560029, India
| | - Dinh Vu
- Department of Psychology, University of Oslo, Harald Schjelderups hus, Forskningsveien 3A, 0373, Oslo, Norway.,Department of Psychology, Chaucer Bldg., Nottingham Trent University, Shakespeare Street, Nottingham, NG1 4FQ, UK
| | - Prasun K Roy
- National Brain Research Centre, NH-8, Nainwal Mode, Manesar, 122051, India.,School of Biomedical Engineering, Indian Institute of Technology (Banaras Hindu University), Varanasi, 221005, India
| | - Matthew K Belmonte
- National Brain Research Centre, NH-8, Nainwal Mode, Manesar, 122051, India. .,Department of Psychology, Chaucer Bldg., Nottingham Trent University, Shakespeare Street, Nottingham, NG1 4FQ, UK. .,The Com DEALL Trust, 224, 6th 'A' Main Road, near Specialist Hospital, 2nd Block, HRBR Layout, Bangalore, 560043, India.
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6
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Konečná B, Radošinská J, Keményová P, Repiská G. Detection of disease-associated microRNAs - application for autism spectrum disorders. Rev Neurosci 2020; 31:757-769. [PMID: 32813679 DOI: 10.1515/revneuro-2020-0015] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Accepted: 04/15/2020] [Indexed: 12/12/2022]
Abstract
Autism spectrum disorders (ASD) diagnostic procedure still lacks a uniform biological marker. This review gathers the information on microRNAs (miRNAs) specifically as a possible source of biomarkers of ASD. Extracellular vesicles, and their subset of exosomes, are believed to be a tool of cell-to-cell communication, and they are increasingly considered to be carriers of such a marker. The interest in studying miRNAs in extracellular vesicles grows in all fields of study and therefore should not be omitted in the field of neurodevelopmental disorders. The summary of miRNAs associated with brain cells and ASD either studied directly in the tissue or biofluids are gathered in this review. The heterogeneity in findings from different studies points out the fact that unified methods should be established, beginning with the determination of the accurate patient and control groups, through to sample collection, processing, and storage conditions. This review, based on the available literature, proposes the standardized approach to obtain the results that would not be affected by technical factors. Nowadays, the method of high-throughput sequencing seems to be the most optimal to analyze miRNAs. This should be followed by the uniformed bioinformatics procedure to avoid misvalidation. At the end, the proper validation of the obtained results is needed. With such an approach as is described in this review, it would be possible to obtain a reliable biomarker that would characterize the presence of ASD.
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Affiliation(s)
- Barbora Konečná
- Institute of Molecular Biomedicine, Faculty of Medicine, Comenius University in Bratislava, 811 08 Bratislava, Slovakia
| | - Jana Radošinská
- Institute of Physiology, Faculty of Medicine, Comenius University in Bratislava, 813 72 Bratislava, Slovakia
- Institute for Heart Research, Centre of Experimental Medicine, Slovak Academy of Sciences, 841 04 Bratislava, Slovakia
| | - Petra Keményová
- Institute of Physiology, Faculty of Medicine, Comenius University in Bratislava, 813 72 Bratislava, Slovakia
| | - Gabriela Repiská
- Institute of Physiology, Faculty of Medicine, Comenius University in Bratislava, 813 72 Bratislava, Slovakia
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Turnbull A, Garfinkel SN, Ho NSP, Critchley HD, Bernhardt BC, Jefferies E, Smallwood J. Word up - Experiential and neurocognitive evidence for associations between autistic symptomology and a preference for thinking in the form of words. Cortex 2020; 128:88-106. [PMID: 32325277 DOI: 10.1016/j.cortex.2020.02.019] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2019] [Revised: 12/06/2019] [Accepted: 02/06/2020] [Indexed: 01/08/2023]
Abstract
Autism symptomology has a profound impact on cognitive and affective functioning, yet we know relatively little about how it shapes patterns of ongoing thought. In an exploratory study in a large population of neurotypical individuals, we used experience sampling to characterise the relationship between ongoing cognition and self-reported autistic traits. We found that with increasing autistic symptom score, cognition was characterised by thinking more in words than images. Analysis of structural neuroimaging data found that autistic traits linked to social interaction were associated with greater cortical thickness in a region of lingual gyrus (LG) within the occipital cortex. Analysis of resting state functional neuroimaging data found autistic traits were associated with stronger connectivity between the LG and a region of motor cortex. Importantly, the strength of connectivity between the LG and motor cortex moderated the link between autistic symptoms and thinking in words: individuals showing higher connectivity showed a stronger association between autistic traits and thinking in words. Together we provide behavioural and neural evidence linking autistic traits to the tendency to think in words which may be rooted in underlying cortical organisation. These observations lay the groundwork for research into the form and content of self-generated thoughts in individuals with the established diagnosis of autism.
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Affiliation(s)
- Adam Turnbull
- Department of Psychology, University of York, York, United Kingdom.
| | - Sarah N Garfinkel
- Sackler Centre for Consciousness Science, University of Sussex, Brighton, United Kingdom
| | - Nerissa S P Ho
- Department of Psychology, University of York, York, United Kingdom
| | - Hugo D Critchley
- Sackler Centre for Consciousness Science, University of Sussex, Brighton, United Kingdom
| | - Boris C Bernhardt
- Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
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Abnormal EEG Power Spectrum in Individuals with High Autistic Personality Traits: an eLORETA Study. JOURNAL OF PSYCHOPATHOLOGY AND BEHAVIORAL ASSESSMENT 2019. [DOI: 10.1007/s10862-019-09777-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Brain Network Organization Correlates with Autistic Features in Preschoolers with Autism Spectrum Disorders and in Their Fathers: Preliminary Data from a DWI Analysis. J Clin Med 2019; 8:jcm8040487. [PMID: 30974902 PMCID: PMC6518033 DOI: 10.3390/jcm8040487] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2019] [Revised: 04/02/2019] [Accepted: 04/06/2019] [Indexed: 11/17/2022] Open
Abstract
Autism Spectrum Disorders (ASD) is a group of neurodevelopmental disorders that is characterized by an altered brain connectivity organization. Autistic traits below the clinical threshold (i.e., the broad autism phenotype; BAP) are frequent among first-degree relatives of subjects with ASD; however, little is known regarding whether subthreshold behavioral manifestations of ASD mirror also at the neuroanatomical level in parents of ASD probands. To this aim, we applied advanced diffusion network analysis to MRI of 16 dyads consisting of a child with ASD and his father in order to investigate: (i) the correlation between structural network organization and autistic features in preschoolers with ASD (all males; age range 1.5-5.2 years); (ii) the correlation between structural network organization and BAP features in the fathers of individuals with ASD (fath-ASD). Local network measures significantly correlated with autism severity in ASD children and with BAP traits in fath-ASD, while no significant association emerged when considering the global measures of brain connectivity. Notably, an overlap of some brain regions that are crucial for social functioning (cingulum, superior temporal gyrus, inferior temporal gyrus, middle frontal gyrus, frontal pole, and amygdala) in patients with ASD and fath-ASD was detected, suggesting an intergenerational transmission of these neural substrates. Overall, the results of this study may help in elucidating the neurostructural endophenotype of ASD, paving the way for bridging connections between underlying genetic and ASD symptomatology.
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Ota M, Matsuo J, Sato N, Teraishi T, Hori H, Hattori K, Kamio Y, Maikusa N, Matsuda H, Kunugi H. Relationship between Autistic Spectrum Trait and Regional Cerebral Blood Flow in Healthy Male Subjects. Psychiatry Investig 2018; 15:956-961. [PMID: 30205670 PMCID: PMC6212697 DOI: 10.30773/pi.2018.07.27] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2018] [Accepted: 07/27/2018] [Indexed: 12/27/2022] Open
Abstract
OBJECTIVE Autistic spectrum traits are postulated to lie on a continuum that extends between individuals with autism and individuals with typical development. The present study was carried out to investigate functional and network abnormalities associated with autistic spectrum trait in healthy male subjects. METHODS Subjects were 41 healthy male subjects who underwent the social responsiveness scale-adult (SRS-A) and magnetic resonance imaging. RESULTS There was significant positive correlation between the total score of SRS-A and the regional cerebral blood flow (CBF) in posterior cingulate cortex (PCC). Also, there were changes in functional network such as in cingulate corti, insula and fusiform cortex. Further, we also found the significant difference of functional networks between the healthy male subjects with high or low autistic spectrum trait, and these points were congruent with the previous perceptions derived from autistic-spectrum disorders. CONCLUSION These findings suggest a biological basis for the autistic spectrum trait and may be useful for the imaging marker of autism symptomatology.
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Affiliation(s)
- Miho Ota
- Department of Mental Disorder Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Junko Matsuo
- Department of Mental Disorder Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Noriko Sato
- Department of Radiology, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Toshiya Teraishi
- Department of Mental Disorder Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Hiroaki Hori
- Department of Mental Disorder Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Kotaro Hattori
- Department of Mental Disorder Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Yoko Kamio
- Department of Child and Adolescent Mental Health, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Norihide Maikusa
- Integrative Brain Imaging Center, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Hiroshi Matsuda
- Integrative Brain Imaging Center, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Hiroshi Kunugi
- Department of Mental Disorder Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, Japan
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11
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Alterations in resting state connectivity along the autism trait continuum: a twin study. Mol Psychiatry 2018; 23:1659-1665. [PMID: 28761079 DOI: 10.1038/mp.2017.160] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2017] [Revised: 05/16/2017] [Accepted: 06/19/2017] [Indexed: 01/03/2023]
Abstract
Autism spectrum disorder (ASD) has been found to be associated with alterations in resting state (RS) functional connectivity, including areas forming the default mode network (DMN) and salience network (SN). However, insufficient control for confounding genetic and environmental influences and other methodological issues limit the generalizability of previous findings. Moreover, it has been hypothesized that ASD might be marked by early hyper-connectivity followed by later hypo-connectivity. To date, only a few studies have explicitly tested age-related influences on RS connectivity alterations in ASD. Using a within-twin pair design (N=150 twins; 8-23 years), we examined altered RS connectivity between core regions of the DMN and SN in relation to autistic trait severity and age in a sample of monozygotic (MZ) and dizygotic (DZ) twins showing typical development, ASD or other neurodevelopmental conditions. Connectivity between core regions of the SN was stronger in twins with higher autistic traits compared to their co-twins. This effect was significant both in the total sample and in MZ twins alone, highlighting the effect of non-shared environmental factors on the link between SN-connectivity and autistic traits. While this link was strongest in children, we did not identify differences between age groups for the SN. In contrast, connectivity between core hubs of the DMN was negatively correlated with autistic traits in adolescents and showed a similar trend in adults but not in children. The results support hypotheses of age-dependent altered RS connectivity in ASD, making altered SN and DMN connectivity promising candidate biomarkers for ASD.
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Tillem S, van Dongen J, Brazil IA, Baskin-Sommers A. Psychopathic traits are differentially associated with efficiency of neural communication. Psychophysiology 2018; 55:e13194. [DOI: 10.1111/psyp.13194] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2017] [Revised: 03/17/2018] [Accepted: 04/04/2018] [Indexed: 11/30/2022]
Affiliation(s)
- Scott Tillem
- Yale University, Department of Psychology; New Haven Connecticut USA
| | - Josanne van Dongen
- Erasmus University Rotterdam, Department of Psychology, Education and Child Studies; Rotterdam The Netherlands
| | - Inti A. Brazil
- Radboud University, Donders Institute for Brain, Cognition and Behaviour; Nijmegen The Netherlands
- Forensic Psychiatric Centre Pompestichting; Nijmegen The Netherlands
- Collaborative Antwerp Psychiatric Research Institute (CAPRI), University of Antwerp; Antwerp Belgium
- Centre for Advances in Behavioural Science, Coventry University; Coventry United Kingdom
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13
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Messina A, Monda V, Sessa F, Valenzano A, Salerno M, Bitetti I, Precenzano F, Marotta R, Lavano F, Lavano SM, Salerno M, Maltese A, Roccella M, Parisi L, Ferrentino RI, Tripi G, Gallai B, Cibelli G, Monda M, Messina G, Carotenuto M. Sympathetic, Metabolic Adaptations, and Oxidative Stress in Autism Spectrum Disorders: How Far From Physiology? Front Physiol 2018; 9:261. [PMID: 29623047 PMCID: PMC5874307 DOI: 10.3389/fphys.2018.00261] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2018] [Accepted: 03/07/2018] [Indexed: 12/31/2022] Open
Abstract
Autism spectrum disorders (ASD) is a complex and multifaceted neurobehavioral syndrome with no specific cause still identified, despite the worldwide increasing (prevalence for 1,000 children from 6.7 to 14.6, between 2000 and 2012). Many biological and instrumental markers have been suggested as potential predictive factors for the precocious diagnosis during infancy and/or pediatric age. Many studies reported structural and functional abnormalities in the autonomic system in subjects with ASD. Sleep problems in ASD are a prominent feature, having an impact on the social interaction of the patient. Considering the role of orexins (A and B) in wake-sleep circadian rhythm, we could speculate that ASD subjects may present a dysregulation in orexinergic neurotransmission. Conversely, oxidative stress is implicated in the pathophysiology of many neurological disorders. Nonetheless, little is known about the linkage between oxidative stress and the occurrence or the progress of autism and autonomic functioning; some markers, such as heart rate (HR), heart rate variability (HRV), body temperature, and galvanic skin response (GSR), may be altered in the patient with this so complex disorder. In the present paper, we analyzed an autism case report, focusing on the rule of the sympathetic activity with the aim to suggest that it may be considered an important tool in ASD evaluation. The results of this case confirm our hypothesis even if further studies needed.
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Affiliation(s)
- Antonietta Messina
- Department of Experimental Medicine, Section of Human Physiology and Unit of Dietetics and Sports Medicine, Università degli Studi della Campania "Luigi Vanvitelli", Naples, Italy
| | - Vincenzo Monda
- Department of Experimental Medicine, Section of Human Physiology and Unit of Dietetics and Sports Medicine, Università degli Studi della Campania "Luigi Vanvitelli", Naples, Italy
| | - Francesco Sessa
- Department of Clinical and Experimental Medicine, University of Foggia, Foggia, Italy
| | - Anna Valenzano
- Department of Clinical and Experimental Medicine, University of Foggia, Foggia, Italy
| | - Monica Salerno
- Department of Clinical and Experimental Medicine, University of Foggia, Foggia, Italy
| | - Ilaria Bitetti
- Clinic of Child and Adolescent Neuropsychiatry, Department of Mental Health, Physical and Preventive Medicine, Università degli Studi della Campania "Luigi Vanvitelli", Naples, Italy
| | - Francesco Precenzano
- Clinic of Child and Adolescent Neuropsychiatry, Department of Mental Health, Physical and Preventive Medicine, Università degli Studi della Campania "Luigi Vanvitelli", Naples, Italy
| | - Rosa Marotta
- Department of Health Sciences, University "Magna Graecia", Catanzaro, Italy
| | - Francesco Lavano
- Department of Health Sciences, University "Magna Graecia", Catanzaro, Italy
| | - Serena M Lavano
- Department of Health Sciences, University "Magna Graecia", Catanzaro, Italy
| | - Margherita Salerno
- Child Neuropsychiatry, Department of Psychology and Pedagogical Sciences, University of Palermo, Palermo, Italy
| | - Agata Maltese
- Child Neuropsychiatry, Department of Psychology and Pedagogical Sciences, University of Palermo, Palermo, Italy
| | - Michele Roccella
- Child Neuropsychiatry, Department of Psychology and Pedagogical Sciences, University of Palermo, Palermo, Italy
| | - Lucia Parisi
- Child Neuropsychiatry, Department of Psychology and Pedagogical Sciences, University of Palermo, Palermo, Italy
| | - Roberta I Ferrentino
- Clinic of Child and Adolescent Neuropsychiatry, Department of Mental Health, Physical and Preventive Medicine, Università degli Studi della Campania "Luigi Vanvitelli", Naples, Italy
| | - Gabriele Tripi
- Childhood Psychiatric Service for Neurodevelopmentals Disorders, Chinon, France
| | - Beatrice Gallai
- Department of Surgical and Biomedical Sciences, University of Perugia, Perugia, Italy
| | - Giuseppe Cibelli
- Department of Clinical and Experimental Medicine, University of Foggia, Foggia, Italy
| | - Marcellino Monda
- Department of Experimental Medicine, Section of Human Physiology and Unit of Dietetics and Sports Medicine, Università degli Studi della Campania "Luigi Vanvitelli", Naples, Italy
| | - Giovanni Messina
- Department of Clinical and Experimental Medicine, University of Foggia, Foggia, Italy
| | - Marco Carotenuto
- Clinic of Child and Adolescent Neuropsychiatry, Department of Mental Health, Physical and Preventive Medicine, Università degli Studi della Campania "Luigi Vanvitelli", Naples, Italy
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Blanken LME, Muetzel RL, Jaddoe VWV, Verhulst FC, van der Lugt A, Tiemeier H, White T. White matter microstructure in children with autistic traits. Psychiatry Res Neuroimaging 2017; 263:127-134. [PMID: 28384486 DOI: 10.1016/j.pscychresns.2017.03.015] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2016] [Revised: 02/15/2017] [Accepted: 03/20/2017] [Indexed: 12/11/2022]
Abstract
Autism spectrum disorder (ASD) is thought to arise from aberrant development of connections in the brain. Previous studies have identified differences in white matter microstructure in children with ASD, offering support to such hypotheses. While ASD is thought to represent the severe end of a spectrum of traits, there are no studies evaluating white matter microstructure in relation to autistic traits in children from the general population. In a population-based sample of 604 6-to-10 year-old children, we assessed the relation between a continuous measure of autistic traits and white matter microstructure, using both probabilistic tractography and Tract-Based Spatial Statistics (TBSS). Using the TBSS approach, a cluster in the left superior longitudinal fasciculus (SLF) was identified where autistic traits negatively associated with fractional anisotropy (FA). In addition, two clusters of lower axial diffusion were identified; one in the corpus callosum and another in the corticospinal tract. Part of the findings remained when excluding children with ASD and were paralleled with similar, trend-level differences in 19 children with ASD, compared to matched controls. This study showed localized associations between autistic traits on a continuum and white matter microstructure, which could indicate a continuum of the neurobiology along the spectrum of autistic symptoms.
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Affiliation(s)
- Laura M E Blanken
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC - Sophia, Rotterdam, the Netherlands; The Generation R Study Group, Erasmus MC - Sophia, Rotterdam, The Netherlands
| | - Ryan L Muetzel
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC - Sophia, Rotterdam, the Netherlands; The Generation R Study Group, Erasmus MC - Sophia, Rotterdam, The Netherlands
| | - Vincent W V Jaddoe
- The Generation R Study Group, Erasmus MC - Sophia, Rotterdam, The Netherlands; Department of Pediatrics, Erasmus MC - Sophia, Rotterdam, The Netherlands; Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - Frank C Verhulst
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC - Sophia, Rotterdam, the Netherlands
| | | | - Henning Tiemeier
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC - Sophia, Rotterdam, the Netherlands; Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands; Department of Psychiatry, Erasmus MC, Rotterdam, The Netherlands
| | - Tonya White
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC - Sophia, Rotterdam, the Netherlands; Department of Radiology, Erasmus MC, Rotterdam, The Netherlands.
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Gernsbacher MA, Stevenson JL, Dern S. Specificity, contexts, and reference groups matter when assessing autistic traits. PLoS One 2017; 12:e0171931. [PMID: 28192464 PMCID: PMC5305234 DOI: 10.1371/journal.pone.0171931] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2016] [Accepted: 01/29/2017] [Indexed: 12/18/2022] Open
Abstract
Many of the personality and behavioral traits (e.g., social imperviousness, directness in conversation, lack of imagination, affinity for solitude, difficulty displaying emotions) that are known to be sensitive to context (with whom?) and reference group (according to whom?) also appear in questionnaire-based assessments of autistic traits. Therefore, two experiments investigated the effects of specifying contexts and reference groups when assessing autistic traits in autistic and non-autistic participants. Experiment 1 (124 autistic and 124 non-autistic participants) demonstrated that context matters when assessing autistic traits (F(1,244) = 267.5, p < .001, η2p = .523). When the context of the Broad Autism Phenotype Questionnaire was specified as the participants’ out-group (e.g., “I like being around non-autistic people” or “I like being around autistic people”), both autistic and non-autistic participants self-reported having more autistic traits; when the context was specified as the participants’ in-group, participants reported having fewer autistic traits. Experiment 2 (82 autistic and 82 non-autistic participants) demonstrated that reference group matters when assessing autistic traits (F(2,160) = 94.38, p < .001, η2p = .541). When the reference group on the Social Responsiveness Scale was specified as the participants’ out-group (e.g., “According to non-autistic people, I have unusual eye contact”), autistic participants reported having more autistic traits; when the reference group was their in-group, autistic participants reported having fewer autistic traits. Non-autistic participants appeared insensitive to reference group on the Social Responsiveness Scale. Exploratory analyses suggested that when neither the context nor the reference group is specified (for assessing autistic traits on the Autism-Spectrum Quotient), both autistic and non-autistic participants use the majority (“non-autistic people”) as the implied context and reference group.
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Affiliation(s)
- Morton Ann Gernsbacher
- Department of Psychology, University of Wisconsin–Madison, Madison, Wisconsin, United States of America
- * E-mail:
| | - Jennifer L. Stevenson
- Department of Psychology, Ursinus College, Collegeville, Pennsylvania, United States of America
| | - Sebastian Dern
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
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Zhang Z, Telesford QK, Giusti C, Lim KO, Bassett DS. Choosing Wavelet Methods, Filters, and Lengths for Functional Brain Network Construction. PLoS One 2016; 11:e0157243. [PMID: 27355202 PMCID: PMC4927172 DOI: 10.1371/journal.pone.0157243] [Citation(s) in RCA: 58] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2016] [Accepted: 05/26/2016] [Indexed: 11/19/2022] Open
Abstract
Wavelet methods are widely used to decompose fMRI, EEG, or MEG signals into time series representing neurophysiological activity in fixed frequency bands. Using these time series, one can estimate frequency-band specific functional connectivity between sensors or regions of interest, and thereby construct functional brain networks that can be examined from a graph theoretic perspective. Despite their common use, however, practical guidelines for the choice of wavelet method, filter, and length have remained largely undelineated. Here, we explicitly explore the effects of wavelet method (MODWT vs. DWT), wavelet filter (Daubechies Extremal Phase, Daubechies Least Asymmetric, and Coiflet families), and wavelet length (2 to 24)—each essential parameters in wavelet-based methods—on the estimated values of graph metrics and in their sensitivity to alterations in psychiatric disease. We observe that the MODWT method produces less variable estimates than the DWT method. We also observe that the length of the wavelet filter chosen has a greater impact on the estimated values of graph metrics than the type of wavelet chosen. Furthermore, wavelet length impacts the sensitivity of the method to detect differences between health and disease and tunes classification accuracy. Collectively, our results suggest that the choice of wavelet method and length significantly alters the reliability and sensitivity of these methods in estimating values of metrics drawn from graph theory. They furthermore demonstrate the importance of reporting the choices utilized in neuroimaging studies and support the utility of exploring wavelet parameters to maximize classification accuracy in the development of biomarkers of psychiatric disease and neurological disorders.
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Affiliation(s)
- Zitong Zhang
- Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - Qawi K. Telesford
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - Chad Giusti
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Warren Center for Network and Data Sciences, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - Kelvin O. Lim
- Department of Psychiatry, University of Minnesota, Minneapolis, MN 55455, United States of America
| | - Danielle S. Bassett
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- * E-mail:
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Cao M, Huang H, Peng Y, Dong Q, He Y. Toward Developmental Connectomics of the Human Brain. Front Neuroanat 2016; 10:25. [PMID: 27064378 PMCID: PMC4814555 DOI: 10.3389/fnana.2016.00025] [Citation(s) in RCA: 89] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2015] [Accepted: 02/29/2016] [Indexed: 12/23/2022] Open
Abstract
Imaging connectomics based on graph theory has become an effective and unique methodological framework for studying structural and functional connectivity patterns of the developing brain. Normal brain development is characterized by continuous and significant network evolution throughout infancy, childhood, and adolescence, following specific maturational patterns. Disruption of these normal changes is associated with neuropsychiatric developmental disorders, such as autism spectrum disorders or attention-deficit hyperactivity disorder. In this review, we focused on the recent progresses regarding typical and atypical development of human brain networks from birth to early adulthood, using a connectomic approach. Specifically, by the time of birth, structural networks already exhibit adult-like organization, with global efficient small-world and modular structures, as well as hub regions and rich-clubs acting as communication backbones. During development, the structure networks are fine-tuned, with increased global integration and robustness and decreased local segregation, as well as the strengthening of the hubs. In parallel, functional networks undergo more dramatic changes during maturation, with both increased integration and segregation during development, as brain hubs shift from primary regions to high order functioning regions, and the organization of modules transitions from a local anatomical emphasis to a more distributed architecture. These findings suggest that structural networks develop earlier than functional networks; meanwhile functional networks demonstrate more dramatic maturational changes with the evolution of structural networks serving as the anatomical backbone. In this review, we also highlighted topologically disorganized characteristics in structural and functional brain networks in several major developmental neuropsychiatric disorders (e.g., autism spectrum disorders, attention-deficit hyperactivity disorder and developmental dyslexia). Collectively, we showed that delineation of the brain network from a connectomics perspective offers a unique and refreshing view of both normal development and neuropsychiatric disorders.
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Affiliation(s)
- Miao Cao
- State Key Laboratory of Cognitive Neuroscience and Learning and International Data Group/McGovern Institute for Brain Research, Beijing Normal University Beijing, China
| | - Hao Huang
- Department of Radiology, Children's Hospital of PhiladelphiaPhiladelphia, PA, USA; Department of Radiology, Perelman School of Medicine, University of PennsylvaniaPhiladelphia, PA, USA
| | - Yun Peng
- Department of Radiology, Beijing Children's Hospital Affiliated to Capital Medical University Beijing, China
| | - Qi Dong
- State Key Laboratory of Cognitive Neuroscience and Learning and International Data Group/McGovern Institute for Brain Research, Beijing Normal University Beijing, China
| | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning and International Data Group/McGovern Institute for Brain Research, Beijing Normal University Beijing, China
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Saxe GN, Statnikov A, Fenyo D, Ren J, Li Z, Prasad M, Wall D, Bergman N, Briggs EC, Aliferis C. A Complex Systems Approach to Causal Discovery in Psychiatry. PLoS One 2016; 11:e0151174. [PMID: 27028297 PMCID: PMC4814084 DOI: 10.1371/journal.pone.0151174] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2015] [Accepted: 02/24/2016] [Indexed: 11/19/2022] Open
Abstract
Conventional research methodologies and data analytic approaches in psychiatric research are unable to reliably infer causal relations without experimental designs, or to make inferences about the functional properties of the complex systems in which psychiatric disorders are embedded. This article describes a series of studies to validate a novel hybrid computational approach–the Complex Systems-Causal Network (CS-CN) method–designed to integrate causal discovery within a complex systems framework for psychiatric research. The CS-CN method was first applied to an existing dataset on psychopathology in 163 children hospitalized with injuries (validation study). Next, it was applied to a much larger dataset of traumatized children (replication study). Finally, the CS-CN method was applied in a controlled experiment using a ‘gold standard’ dataset for causal discovery and compared with other methods for accurately detecting causal variables (resimulation controlled experiment). The CS-CN method successfully detected a causal network of 111 variables and 167 bivariate relations in the initial validation study. This causal network had well-defined adaptive properties and a set of variables was found that disproportionally contributed to these properties. Modeling the removal of these variables resulted in significant loss of adaptive properties. The CS-CN method was successfully applied in the replication study and performed better than traditional statistical methods, and similarly to state-of-the-art causal discovery algorithms in the causal detection experiment. The CS-CN method was validated, replicated, and yielded both novel and previously validated findings related to risk factors and potential treatments of psychiatric disorders. The novel approach yields both fine-grain (micro) and high-level (macro) insights and thus represents a promising approach for complex systems-oriented research in psychiatry.
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Affiliation(s)
- Glenn N. Saxe
- Department of Child and Adolescent Psychiatry, New York University School of Medicine, New York, New York, United States of America
- * E-mail:
| | - Alexander Statnikov
- Center for Health Informatics and Bioinformatics, New York University School of Medicine, New York, New York, United States of America
| | - David Fenyo
- Center for Health Informatics and Bioinformatics, New York University School of Medicine, New York, New York, United States of America
| | - Jiwen Ren
- Department of Child and Adolescent Psychiatry, New York University School of Medicine, New York, New York, United States of America
- Center for Health Informatics and Bioinformatics, New York University School of Medicine, New York, New York, United States of America
| | - Zhiguo Li
- Center for Health Informatics and Bioinformatics, New York University School of Medicine, New York, New York, United States of America
| | - Meera Prasad
- Memorial Sloan Kettering Cancer Center, New York, New York, United States of America
| | - Dennis Wall
- Systems Medicine in the Department of Pediatrics, Stanford University School of Medicine, Stanford, California, United States of America
| | - Nora Bergman
- Department of Child and Adolescent Psychiatry, New York University School of Medicine, New York, New York, United States of America
| | - Ernestine C. Briggs
- Department of Psychiatry, Duke University School of Medicine, Durham, North Carolina, United States of America
| | - Constantin Aliferis
- Institute for Health Informatics, University of Minnesota, Minneapolis, Minnesota, United States of America
- Department of Biostatistics, Vanderbilt University, Nashville, Tennessee, United States of America
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Goto M, Abe O, Miyati T, Yamasue H, Gomi T, Takeda T. Head Motion and Correction Methods in Resting-state Functional MRI. Magn Reson Med Sci 2015; 15:178-86. [PMID: 26701695 PMCID: PMC5600054 DOI: 10.2463/mrms.rev.2015-0060] [Citation(s) in RCA: 43] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
Abstract
Resting-state functional magnetic resonance imaging (RS-fMRI) is used to investigate brain functional connectivity at rest. However, noise from human physiological motion is an unresolved problem associated with this technique. Following the unexpected previous result that group differences in head motion between control and patient groups caused group differences in the resting-state network with RS-fMRI, we reviewed the effects of human physiological noise caused by subject motion, especially motion of the head, on functional connectivity at rest detected with RS-fMRI. The aim of the present study was to review head motion artifact with RS-fMRI, individual and patient population differences in head motion, and correction methods for head motion artifact with RS-fMRI. Numerous reports have described new methods [e.g., scrubbing, regional displacement interaction (RDI)] for motion correction on RS-fMRI, many of which have been successful in reducing this negative influence. However, the influence of head motion could not be entirely excluded by any of these published techniques. Therefore, in performing RS-fMRI studies, head motion of the participants should be quantified with measurement technique (e.g., framewise displacement). Development of a more effective correction method would improve the accuracy of RS-fMRI analysis.
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Affiliation(s)
- Masami Goto
- School of Allied Health Sciences, Kitasato University
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Tu PC, Hsu JW, Lan CC, Liu CC, Su TP, Chen YS. Structural and functional correlates of a quantitative autistic trait measured using the social responsive scale in neurotypical male adolescents. Autism Res 2015; 9:570-8. [DOI: 10.1002/aur.1535] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2015] [Accepted: 07/28/2015] [Indexed: 01/31/2023]
Affiliation(s)
- Pei-Chi Tu
- Department of Medical Research; Taipei Veterans General Hospital; Taipei 112 Taiwan
- Department of Psychiatry; Taipei Veterans General Hospital; Taipei 112 Taiwan
- Institute of Philosophy of Mind and Cognition, National Yang-Ming University; Taipei Taiwan
- Department of Psychiatry, Faculty of Medicine; National Yang-Ming University; Taipei Taiwan
| | - Ju-Wei Hsu
- Department of Psychiatry; Taipei Veterans General Hospital; Taipei 112 Taiwan
- Department of Psychiatry, Faculty of Medicine; National Yang-Ming University; Taipei Taiwan
| | - Chen-Chia Lan
- Department of Psychiatry; Taipei Municipal Gandau Hospital; Taipei Taiwan
| | - Chia-Chien Liu
- Department of Psychiatry; National Yang-Ming University Hospital; Yi-Lan Taiwan
| | - Tung-Ping Su
- Department of Psychiatry; Taipei Veterans General Hospital; Taipei 112 Taiwan
- Department of Psychiatry, Faculty of Medicine; National Yang-Ming University; Taipei Taiwan
| | - Ying-Sheue Chen
- Department of Psychiatry; Taipei Veterans General Hospital; Taipei 112 Taiwan
- Department of Psychiatry, Faculty of Medicine; National Yang-Ming University; Taipei Taiwan
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Ogletree BT, Morrow-Odom KL, Westling D. Understanding the brain-behaviour relationship in persons with ASD: implications for PECS as a treatment choice. Dev Neurorehabil 2015; 18:88-96. [PMID: 24063565 DOI: 10.3109/17518423.2013.833995] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
INTRODUCTION This article presents emerging neurological findings in Autism Spectrum Disorders (ASD) with particular attention to how this information might inform treatment practices addressing communication impairments. METHODS The article begins with a general discussion of the brain-behaviour relationship and moves to the presentation of recent research findings related to ASD. There is particular attention to individuals with autism who are either non-verbal or present emergent verbal abilities. RESULTS/DISCUSSION A specific communication treatment, the Picture Exchange Communication System (PECS), is presented as an example of an intervention that addresses the learner needs of many individuals with ASD. The success of PECS is discussed within the context of its fit with brain-based learner characteristics.
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Affiliation(s)
- Billy T Ogletree
- Department of Communication Sciences and Disorders, Western Carolina University , Cullowhee, NC , USA and
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Abstract
Psychiatric disorders disturb higher cognitive functions and severely compromise human health. However, the pathophysiological mechanisms underlying psychiatric disorders are very complex, and understanding these mechanisms remains a great challenge. Currently, many psychiatric disorders are hypothesized to reflect "faulty wiring" or aberrant connectivity in the brains. Imaging connectomics is arising as a promising methodological framework for describing the structural and functional connectivity patterns of the human brain. Recently, alterations of brain networks in the connectome have been reported in various psychiatric disorders, and these alterations may provide biomarkers for disease diagnosis and prognosis for the evaluation of treatment efficacy. Here, we summarize the current achievements in both the structural and functional connectomes in several major psychiatric disorders (eg, schizophrenia, attention-deficit/hyperactivity disorder, and autism) based on multi-modal neuroimaging data. We highlight the current progress in the identification of these alterations and the hypotheses concerning the aberrant brain networks in individuals with psychiatric disorders and discuss the research questions that might contribute to a further mechanistic understanding of these disorders from a connectomic perspective.
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Affiliation(s)
- Miao Cao
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, People's Republic of China
| | - Zhijiang Wang
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, People's Republic of China
| | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, People's Republic of China
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‘Subtypes’ in the Presentation of Autistic Traits in the General Adult Population. J Autism Dev Disord 2014; 45:1291-301. [DOI: 10.1007/s10803-014-2289-1] [Citation(s) in RCA: 47] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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Voxel-wise motion artifacts in population-level whole-brain connectivity analysis of resting-state FMRI. PLoS One 2014; 9:e104947. [PMID: 25188284 PMCID: PMC4154676 DOI: 10.1371/journal.pone.0104947] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2014] [Accepted: 07/17/2014] [Indexed: 02/01/2023] Open
Abstract
Functional Magnetic Resonance Imaging (fMRI) based brain connectivity analysis maps the functional networks of the brain by estimating the degree of synchronous neuronal activity between brain regions. Recent studies have demonstrated that "resting-state" fMRI-based brain connectivity conclusions may be erroneous when motion artifacts have a differential effect on fMRI BOLD signals for between group comparisons. A potential explanation could be that in-scanner displacement, due to rotational components, is not spatially constant in the whole brain. However, this localized nature of motion artifacts is poorly understood and is rarely considered in brain connectivity studies. In this study, we initially demonstrate the local correspondence between head displacement and the changes in the resting-state fMRI BOLD signal. Than, we investigate how connectivity strength is affected by the population-level variation in the spatial pattern of regional displacement. We introduce Regional Displacement Interaction (RDI), a new covariate parameter set for second-level connectivity analysis and demonstrate its effectiveness in reducing motion related confounds in comparisons of groups with different voxel-vise displacement pattern and preprocessed using various nuisance regression methods. The effect of using RDI as second-level covariate is than demonstrated in autism-related group comparisons. The relationship between the proposed method and some of the prevailing subject-level nuisance regression techniques is evaluated. Our results show that, depending on experimental design, treating in-scanner head motion as a global confound may not be appropriate. The degree of displacement is highly variable among various brain regions, both within and between subjects. These regional differences bias correlation-based measures of brain connectivity. The inclusion of the proposed second-level covariate into the analysis successfully reduces artifactual motion-related group differences and preserves real neuronal differences, as demonstrated by the autism-related comparisons.
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Zhou Y, Yu F, Duong T. Multiparametric MRI characterization and prediction in autism spectrum disorder using graph theory and machine learning. PLoS One 2014; 9:e90405. [PMID: 24922325 PMCID: PMC4055499 DOI: 10.1371/journal.pone.0090405] [Citation(s) in RCA: 58] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2013] [Accepted: 11/20/2013] [Indexed: 11/18/2022] Open
Abstract
This study employed graph theory and machine learning analysis of multiparametric MRI data to improve characterization and prediction in autism spectrum disorders (ASD). Data from 127 children with ASD (13.5±6.0 years) and 153 age- and gender-matched typically developing children (14.5±5.7 years) were selected from the multi-center Functional Connectome Project. Regional gray matter volume and cortical thickness increased, whereas white matter volume decreased in ASD compared to controls. Small-world network analysis of quantitative MRI data demonstrated decreased global efficiency based on gray matter cortical thickness but not with functional connectivity MRI (fcMRI) or volumetry. An integrative model of 22 quantitative imaging features was used for classification and prediction of phenotypic features that included the autism diagnostic observation schedule, the revised autism diagnostic interview, and intelligence quotient scores. Among the 22 imaging features, four (caudate volume, caudate-cortical functional connectivity and inferior frontal gyrus functional connectivity) were found to be highly informative, markedly improving classification and prediction accuracy when compared with the single imaging features. This approach could potentially serve as a biomarker in prognosis, diagnosis, and monitoring disease progression.
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Affiliation(s)
- Yongxia Zhou
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Fang Yu
- Research Imaging Institute, Departments of Ophthalmology, Radiology, Physiology, University of Texas Health Science Center, South Texas Veterans Health Care System, Department of Veterans Affairs, San Antonio, Texas, United States of America
| | - Timothy Duong
- Research Imaging Institute, Departments of Ophthalmology, Radiology, Physiology, University of Texas Health Science Center, South Texas Veterans Health Care System, Department of Veterans Affairs, San Antonio, Texas, United States of America
- * E-mail:
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Itahashi T, Yamada T, Watanabe H, Nakamura M, Jimbo D, Shioda S, Toriizuka K, Kato N, Hashimoto R. Altered network topologies and hub organization in adults with autism: a resting-state fMRI study. PLoS One 2014; 9:e94115. [PMID: 24714805 PMCID: PMC3979738 DOI: 10.1371/journal.pone.0094115] [Citation(s) in RCA: 103] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2014] [Accepted: 03/12/2014] [Indexed: 11/19/2022] Open
Abstract
Recent functional magnetic resonance imaging (fMRI) studies on autism spectrum condition (ASC) have identified dysfunctions in specific brain networks involved in social and non-social cognition that persist into adulthood. Although increasing numbers of fMRI studies have revealed atypical functional connectivity in the adult ASC brain, such functional alterations at the network level have not yet been fully characterized within the recently developed graph-theoretical framework. Here, we applied a graph-theoretical analysis to resting-state fMRI data acquired from 46 adults with ASC and 46 age- and gender-matched controls, to investigate the topological properties and organization of autistic brain network. Analyses of global metrics revealed that, relative to the controls, participants with ASC exhibited significant decreases in clustering coefficient and characteristic path length, indicating a shift towards randomized organization. Furthermore, analyses of local metrics revealed a significantly altered organization of the hub nodes in ASC, as shown by analyses of hub disruption indices using multiple local metrics and by a loss of "hubness" in several nodes (e.g., the bilateral superior temporal sulcus, right dorsolateral prefrontal cortex, and precuneus) that are critical for social and non-social cognitive functions. In particular, local metrics of the anterior cingulate cortex consistently showed significant negative correlations with the Autism-Spectrum Quotient score. Our results demonstrate altered patterns of global and local topological properties that may underlie impaired social and non-social cognition in ASC.
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Affiliation(s)
- Takashi Itahashi
- Department of Pharmacognosy and Phytochemistry, Showa University School of Pharmacy, Tokyo, Japan
| | - Takashi Yamada
- Department of Psychiatry, Showa University School of Medicine, Tokyo, Japan
| | - Hiromi Watanabe
- Department of Psychiatry, Showa University School of Medicine, Tokyo, Japan
| | - Motoaki Nakamura
- Department of Psychiatry, Showa University School of Medicine, Tokyo, Japan
- Kinko Hospital, Kanagawa Psychiatric Center, Kanagawa, Japan
| | - Daiki Jimbo
- Department of Anatomy, Showa University School of Medicine, Tokyo, Japan
| | - Seiji Shioda
- Department of Anatomy, Showa University School of Medicine, Tokyo, Japan
| | - Kazuo Toriizuka
- Department of Pharmacognosy and Phytochemistry, Showa University School of Pharmacy, Tokyo, Japan
| | - Nobumasa Kato
- Department of Psychiatry, Showa University School of Medicine, Tokyo, Japan
| | - Ryuichiro Hashimoto
- Department of Psychiatry, Showa University School of Medicine, Tokyo, Japan
- Department of Language Sciences, Graduate School of Humanities, Tokyo Metropolitan University, Tokyo, Japan
- * E-mail:
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Quantification of changes in language-related brain areas in autism spectrum disorders using large-scale network analysis. Int J Comput Assist Radiol Surg 2014; 9:357-65. [PMID: 24459035 DOI: 10.1007/s11548-014-0977-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2013] [Accepted: 01/09/2014] [Indexed: 12/21/2022]
Abstract
PURPOSE Diagnosis of autism spectrum disorders (ASD) is difficult, as symptoms vary greatly and are difficult to quantify objectively. Recent work has focused on the assessment of non-invasive diffusion tensor imaging-based biomarkers that reflect the microstructural characteristics of neuronal pathways in the brain. While tractography-based approaches typically analyze specific structures of interest, a graph-based large-scale network analysis of the connectome can yield comprehensive measures of larger-scale architectural patterns in the brain. Commonly applied global network indices, however, do not provide any specificity with respect to functional areas or anatomical structures. Aim of this work was to assess the concept of network centrality as a tool to perform locally specific analysis without disregarding the global network architecture and compare it to other popular network indices. METHODS We create connectome networks from fiber tractographies and parcellations of the human brain and compute global network indices as well as local indices for Wernicke's Area, Broca's Area and the Motor Cortex. Our approach was evaluated on 18 children suffering from ASD and 18 typically developed controls using magnetic resonance imaging-based cortical parcellations in combination with diffusion tensor imaging tractography. RESULTS We show that the network centrality of Wernicke's area is significantly (p<0.001) reduced in ASD, while the motor cortex, which was used as a control region, did not show significant alterations. This could reflect the reduced capacity for comprehension of language in ASD. CONCLUSIONS The betweenness centrality could potentially be an important metric in the development of future diagnostic tools in the clinical context of ASD diagnosis. Our results further demonstrate the applicability of large-scale network analysis tools in the domain of region-specific analysis with a potential application in many different psychological disorders.
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Rubinov M, Bullmore E. Fledgling pathoconnectomics of psychiatric disorders. Trends Cogn Sci 2013; 17:641-7. [DOI: 10.1016/j.tics.2013.10.007] [Citation(s) in RCA: 98] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2013] [Revised: 10/07/2013] [Accepted: 10/07/2013] [Indexed: 01/21/2023]
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Levit-Binnun N, Davidovitch M, Golland Y. Sensory and motor secondary symptoms as indicators of brain vulnerability. J Neurodev Disord 2013; 5:26. [PMID: 24063566 PMCID: PMC3849186 DOI: 10.1186/1866-1955-5-26] [Citation(s) in RCA: 46] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/13/2013] [Accepted: 09/04/2013] [Indexed: 01/20/2023] Open
Abstract
In addition to the primary symptoms that distinguish one disorder from the next, clinicians have identified, yet largely overlooked, another set of symptoms that appear across many disorders, termed secondary symptoms. In the emerging era of systems neuroscience, which highlights that many disorders share common deficits in global network features, the nonspecific nature of secondary symptoms should attract attention. Herein we provide a scholarly review of the literature on a subset of secondary symptoms––sensory and motor. We demonstrate that their pattern of appearance––across a wide range of psychopathologies, much before the full-blown disorder appears, and in healthy individuals who display a variety of negative symptoms––resembles the pattern of appearance of network abnormalities. We propose that sensory and motor secondary symptoms can be important indicators of underlying network aberrations and thus of vulnerable brain states putting individuals at risk for psychopathology following extreme circumstances.
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Affiliation(s)
- Nava Levit-Binnun
- Interdisciplinary Center (IDC), Sagol Unit for Applied Neuroscience, School of Psychology, POB 167, Herzliya 46150, Israel.
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