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Fogelson N, Diaz-Brage P. Altered directed connectivity during processing of predictive stimuli in psychiatric patient populations. Clin Neurophysiol 2021; 132:2739-2750. [PMID: 34571367 DOI: 10.1016/j.clinph.2021.07.025] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Revised: 07/06/2021] [Accepted: 07/20/2021] [Indexed: 10/20/2022]
Abstract
OBJECTIVES The study investigated the role of top-down versus bottom-up connectivity, during the processing of predictive information, in three different psychiatric disorders. METHODS Electroencephalography (EEG) was recorded during the performance of a task, which evaluates the ability to use predictive information in order to facilitate predictable versus random target detection. We evaluated EEG event-related directed connectivity, in patients with schizophrenia (SZ), major depressive disorder (MDD), and autism spectrum disorder (ASD), compared with healthy age-matched controls. Directed connectivity was evaluated using phase transfer entropy. RESULTS We showed that top-down frontal-parietal connectivity was weaker in SZ (theta and beta bands) and ASD (alpha band) compared to control subjects, during the processing of stimuli consisting of the predictive sequence. In SZ patients, top-down connectivity was also attenuated, during the processing of predictive targets in the beta frequency band. In contrast, compared with controls, MDD patients displayed an increased top-down flow of information, during the processing of predicted targets (alpha band). CONCLUSIONS The findings suggest that top-down frontal-parietal connectivity is altered differentially across three major psychiatric disorders, specifically during the processing of predictive stimuli. SIGNIFICANCE Altered top-down connectivity may contribute to the specific prediction deficits observed in each of the patient populations.
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Affiliation(s)
- Noa Fogelson
- EEG and Cognition Laboratory, Department of Humanities, University Rey Juan Carlos, Madrid, Spain.
| | - Pablo Diaz-Brage
- EEG and Cognition Laboratory, Department of Humanities, University Rey Juan Carlos, Madrid, Spain
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2
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Altered directed connectivity during processing of implicit versus explicit predictive stimuli in Parkinson's disease patients. Brain Cogn 2021; 152:105773. [PMID: 34225173 DOI: 10.1016/j.bandc.2021.105773] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Revised: 05/06/2021] [Accepted: 06/25/2021] [Indexed: 11/22/2022]
Abstract
The study investigated the role of top-down versus bottom-up connectivity, during the processing of implicit or explicit predictive information, in Parkinson's disease (PD). EEG was recorded during the performance of a task, which evaluated the ability to utilize either implicit or explicit predictive contextual information in order to facilitate the detection of predictable versus random targets. Thus, subjects performed an implicit and explicit session, where subjects were either unaware or made aware of a predictive sequence that signals the presentation of a subsequent target, respectively. We evaluated EEG event-related directed connectivity, in PD patients compared with healthy age-matched controls, using phase transfer entropy. PD patients showed increased top-down frontal-parietal connectivity, compared to control subjects, during the processing of the last (most informative) stimulus of the predictive sequence and of random standards, in the implicit and explicit session, respectively. These findings suggest that PD is associated with compensatory top-down connectivity, specifically during the processing of implicit predictive stimuli. During the explicit session, PD patients seem to allocate more attentional resources to non-informative standard stimuli, compared to controls. These connectivity changes shed further light on the cognitive deficits, associated with the processing of predictive contextual information, that are observed in PD patients.
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Haghighat H, Mirzarezaee M, Araabi BN, Khadem A. Functional Networks Abnormalities in Autism Spectrum Disorder: Age-Related Hypo and Hyper Connectivity. Brain Topogr 2021; 34:306-322. [PMID: 33905003 DOI: 10.1007/s10548-021-00831-7] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Accepted: 03/03/2021] [Indexed: 11/30/2022]
Abstract
Autism spectrum disorder (ASD) is a developmental disorder characterized by defects in social interaction. The past functional connectivity studies using resting-state fMRI have found both patterns of hypo-connectivity and hyper-connectivity in ASD and proposed the age as an important factor on functional connectivity disorders. However, this influence is not clearly characterized yet. Previous studies have often examined the functional connectivity disorders in particular brain regions in an age group or a mixture of age groups. The present study compares whole-brain within-connectivity and between-connectivity between ASD individuals and typically developing (TD) controls in three age groups including children (< 11 years), adolescents (11-18 years), and adults (> 18 years), each comprising 21 ASD individuals and 21 TD controls. The age groups were matched for age, Full IQ, and gender. Independent component analysis and dual regression were used to investigate within-connectivity. The full and partial correlations between ICs were used to investigate between-connectivity. Examination of the within-connectivity showed hyper-connectivity, especially in cerebellum and brainstem in ASD children but both hyper/hypo connectivity in adolescents and ASD adults. In ASD children, difference in the between-connectivity among default mode network (DMN), salience-executive network and fronto-parietal network were observed. There was also a negative correlation between DMN and temporal network. Full correlation comparison between ASD adolescents and TD individuals showed significant differences between cerebellum and DMN. Our results supported just the hyper-connectivity in childhood, but both hypo and hyper-connectivity after childhood and hypothesized that abnormal resting connections in ASD exist in the regions of the brain known to be involved in social cognition.
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Affiliation(s)
- Hossein Haghighat
- Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
| | - Mitra Mirzarezaee
- Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.
| | - Babak Nadjar Araabi
- Control and Intelligent Processing Center of Excellence, School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran
| | - Ali Khadem
- Department of Biomedical Engineering, Faculty of Electrical Engineering, K. N. Toosi University of Technology, Tehran, Iran
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4
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Mamashli F, Kozhemiako N, Khan S, Nunes AS, McGuiggan NM, Losh A, Joseph RM, Ahveninen J, Doesburg SM, Hämäläinen MS, Kenet T. Children with autism spectrum disorder show altered functional connectivity and abnormal maturation trajectories in response to inverted faces. Autism Res 2021; 14:1101-1114. [PMID: 33709531 DOI: 10.1002/aur.2497] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Accepted: 02/08/2021] [Indexed: 12/21/2022]
Abstract
The processing of information conveyed by faces is a critical component of social communication. While the neurophysiology of processing upright faces has been studied extensively in autism spectrum disorder (ASD), less is known about the neurophysiological abnormalities associated with processing inverted faces in ASD. We used magnetoencephalography (MEG) to study both long-range and local functional connectivity, with the latter assessed using local cross-frequency coupling, in response to inverted faces stimuli, in 7-18 years old individuals with ASD and age and IQ matched typically developing (TD) individuals. We found abnormally reduced coupling between the phase of the alpha rhythm and the amplitude of the gamma rhythm in the fusiform face area (FFA) in response to inverted faces, as well as reduced long-range functional connectivity between the FFA and the inferior frontal gyrus (IFG) in response to inverted faces in the ASD group. These group differences were absent in response to upright faces. The magnitude of functional connectivity between the FFA and the IFG was significantly correlated with the severity of ASD, and FFA-IFG long-range functional connectivity increased with age in TD group, but not in the ASD group. Our findings suggest that both local and long-range functional connectivity are abnormally reduced in children with ASD when processing inverted faces, and that the pattern of abnormalities associated with the processing of inverted faces differs from the pattern of upright faces in ASD, likely due to the presumed greater reliance on top-down regulations necessary for efficient processing of inverted faces. LAY SUMMARY: We found alterations in the neurophysiological responses to inverted faces in children with ASD, that were not reflected in the evoked responses, and were not observed in the responses to upright faces. These alterations included reduced local functional connectivity in the fusiform face area (FFA), and decreased long-range alpha-band modulated functional connectivity between the FFA and the left IFG. The magnitude of long-range functional connectivity between the FFA and the inferior frontal gyrus was correlated with the severity of ASD.
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Affiliation(s)
- Fahimeh Mamashli
- Athinoula A. Martinos Center for Biomedical Imaging, MGH/HST, Charlestown, Massachusetts, USA.,Department of Radiology, MGH, Harvard Medical School, Boston, Massachusetts, USA
| | - Nataliia Kozhemiako
- Department of Neurology, MGH, Harvard Medical School, Boston, Massachusetts, USA.,Department of Biomedical Physiology and Kinesiology, Simon Fraser University, Vancouver, British Columbia, Canada
| | - Sheraz Khan
- Athinoula A. Martinos Center for Biomedical Imaging, MGH/HST, Charlestown, Massachusetts, USA.,Department of Radiology, MGH, Harvard Medical School, Boston, Massachusetts, USA
| | - Adonay S Nunes
- Department of Neurology, MGH, Harvard Medical School, Boston, Massachusetts, USA.,Department of Biomedical Physiology and Kinesiology, Simon Fraser University, Vancouver, British Columbia, Canada
| | - Nicole M McGuiggan
- Athinoula A. Martinos Center for Biomedical Imaging, MGH/HST, Charlestown, Massachusetts, USA
| | - Ainsley Losh
- Athinoula A. Martinos Center for Biomedical Imaging, MGH/HST, Charlestown, Massachusetts, USA.,Department of Neurology, MGH, Harvard Medical School, Boston, Massachusetts, USA
| | - Robert M Joseph
- Department of Anatomy and Neurobiology, Boston University, Boston, Massachusetts, USA
| | - Jyrki Ahveninen
- Athinoula A. Martinos Center for Biomedical Imaging, MGH/HST, Charlestown, Massachusetts, USA.,Department of Radiology, MGH, Harvard Medical School, Boston, Massachusetts, USA
| | - Sam M Doesburg
- Department of Biomedical Physiology and Kinesiology, Simon Fraser University, Vancouver, British Columbia, Canada.,Behavioral and Cognitive Neuroscience Institute, Simon Fraser University, Vancouver, British Columbia, Canada
| | - Matti S Hämäläinen
- Athinoula A. Martinos Center for Biomedical Imaging, MGH/HST, Charlestown, Massachusetts, USA.,Department of Radiology, MGH, Harvard Medical School, Boston, Massachusetts, USA
| | - Tal Kenet
- Athinoula A. Martinos Center for Biomedical Imaging, MGH/HST, Charlestown, Massachusetts, USA.,Department of Neurology, MGH, Harvard Medical School, Boston, Massachusetts, USA
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5
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Hasanzadeh F, Mohebbi M, Rostami R. Graph theory analysis of directed functional brain networks in major depressive disorder based on EEG signal. J Neural Eng 2020; 17:026010. [DOI: 10.1088/1741-2552/ab7613] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
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6
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McVoy M, Lytle S, Fulchiero E, Aebi ME, Adeleye O, Sajatovic M. A systematic review of quantitative EEG as a possible biomarker in child psychiatric disorders. Psychiatry Res 2019; 279:331-344. [PMID: 31300243 DOI: 10.1016/j.psychres.2019.07.004] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Revised: 06/25/2019] [Accepted: 07/01/2019] [Indexed: 11/15/2022]
Abstract
Quantitative EEG (qEEG) has emerged as a potential intermediate biomarker for diagnostic clarification in mental illness. This systematic review examines published studies that used qEEG in youth with psychiatric illness between 1996 and 2017. We conducted a comprehensive database search of CINAHL, PubMed, and Cochrane using the following keywords: "quantitative EEG" and depression (MDD), anxiety, attention-deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), eating disorder, conduct, substance use, schizophrenia, post-traumatic stress disorder, and panic disorder. Our search yielded 516 titles; 33 met final inclusion criteria, producing a total of 2268 youth aged 4-18. qEEG was most frequently studied as a potential diagnostic tool in pediatric mental illness; few studies assessed treatment response. Studies show higher theta/beta ratio in ADHD vs healthy controls (HC). The most consistent finding in ASD was decreased coherence in ASD vs HC. Studies show MDD has lower temporal coherence and interhemispheric coherence in sleep EEGs than HC. Further research is needed in the areas of mood, anxiety, ASD, and relationship to treatment. It remains unknown if abnormalities in qEEG are nonspecific markers of pediatric psychiatric illness or if they have the potential to differentiate types of psychopathology.
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Affiliation(s)
- Molly McVoy
- Department of Child and Adolescent Psychiatry, University Hospitals Cleveland Medical Center, Cleveland, OH 44106, United States.
| | - Sarah Lytle
- Department of Child and Adolescent Psychiatry, University Hospitals Cleveland Medical Center, Cleveland, OH 44106, United States
| | - Erin Fulchiero
- Department of Child and Adolescent Psychiatry, University Hospitals Cleveland Medical Center, Cleveland, OH 44106, United States
| | - Michelle E Aebi
- Department of Psychiatry, Case Western Reserve University School of Medicine, Cleveland, OH 44106, United States; Neurological and Behavioral Outcomes Center, University Hospitals Cleveland Medical Center, Cleveland, OH, 44106, United States
| | - Olunfunke Adeleye
- Department of Child and Adolescent Psychiatry, University Hospitals Cleveland Medical Center, Cleveland, OH 44106, United States
| | - Martha Sajatovic
- Department of Psychiatry, Case Western Reserve University School of Medicine, Cleveland, OH 44106, United States; Neurological and Behavioral Outcomes Center, University Hospitals Cleveland Medical Center, Cleveland, OH, 44106, United States
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7
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EEG-based multi-feature fusion assessment for autism. J Clin Neurosci 2018; 56:101-107. [DOI: 10.1016/j.jocn.2018.06.049] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2018] [Accepted: 06/25/2018] [Indexed: 11/21/2022]
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8
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Crosato E, Jiang L, Lecheval V, Lizier JT, Wang XR, Tichit P, Theraulaz G, Prokopenko M. Informative and misinformative interactions in a school of fish. SWARM INTELLIGENCE 2018. [DOI: 10.1007/s11721-018-0157-x] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
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9
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Ochoa JF, Alonso JF, Duque JE, Tobón CA, Mañanas MA, Lopera F, Hernández AM. Successful Object Encoding Induces Increased Directed Connectivity in Presymptomatic Early-Onset Alzheimer's Disease. J Alzheimers Dis 2018; 55:1195-1205. [PMID: 27792014 PMCID: PMC5147495 DOI: 10.3233/jad-160803] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
BACKGROUND Recent studies report increases in neural activity in brain regions critical to episodic memory at preclinical stages of Alzheimer's disease (AD). Although electroencephalography (EEG) is widely used in AD studies, given its non-invasiveness and low cost, there is a need to translate the findings in other neuroimaging methods to EEG. OBJECTIVE To examine how the previous findings using functional magnetic resonance imaging (fMRI) at preclinical stage in presenilin-1 E280A mutation carriers could be assessed and extended, using EEG and a connectivity approach. METHODS EEG signals were acquired during resting and encoding in 30 normal cognitive young subjects, from an autosomal dominant early-onset AD kindred from Antioquia, Colombia. Regions of the brain previously reported as hyperactive were used for connectivity analysis. RESULTS Mutation carriers exhibited increasing connectivity at analyzed regions. Among them, the right precuneus exhibited the highest changes in connectivity. CONCLUSION Increased connectivity in hyperactive cerebral regions is seen in individuals, genetically-determined to develop AD, at preclinical stage. The use of a connectivity approach and a widely available neuroimaging technique opens the possibility to increase the use of EEG in early detection of preclinical AD.
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Affiliation(s)
- John Fredy Ochoa
- Bioinstrumentation and Clinical Engineering Research Group, Bioengineering Program, Universidad de Antioquia UdeA, Calle 70 No. 52-21, Medellín, Colombia
| | - Joan Francesc Alonso
- Department of Automatic Control (ESAII), Biomedical Engineering Research Center (CREB), Universitat Politènica de Catalunya (UPC), Barcelona, Spain.,Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Spain
| | - Jon Edinson Duque
- Bioinstrumentation and Clinical Engineering Research Group, Bioengineering Program, Universidad de Antioquia UdeA, Calle 70 No. 52-21, Medellín, Colombia
| | - Carlos Andrés Tobón
- Neuroscience Group of Antioquia, Medical School, Universidad de Antioquia UdeA, Calle 70 No. 52-21, Medellín, Colombia.,Neuropsychology and Behavior group, Medical School, Universidad de Antioquia UdeA, Calle 70 No. 52-21, Medellín, Colombia
| | - Miguel Angel Mañanas
- Department of Automatic Control (ESAII), Biomedical Engineering Research Center (CREB), Universitat Politènica de Catalunya (UPC), Barcelona, Spain.,Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Spain
| | - Francisco Lopera
- Neuroscience Group of Antioquia, Medical School, Universidad de Antioquia UdeA, Calle 70 No. 52-21, Medellín, Colombia
| | - Alher Mauricio Hernández
- Bioinstrumentation and Clinical Engineering Research Group, Bioengineering Program, Universidad de Antioquia UdeA, Calle 70 No. 52-21, Medellín, Colombia
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10
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O’Reilly C, Lewis JD, Elsabbagh M. Is functional brain connectivity atypical in autism? A systematic review of EEG and MEG studies. PLoS One 2017; 12:e0175870. [PMID: 28467487 PMCID: PMC5414938 DOI: 10.1371/journal.pone.0175870] [Citation(s) in RCA: 176] [Impact Index Per Article: 25.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2016] [Accepted: 03/31/2017] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Although it is well recognized that autism is associated with altered patterns of over- and under-connectivity, specifics are still a matter of debate. Little has been done so far to synthesize available literature using whole-brain electroencephalography (EEG) and magnetoencephalography (MEG) recordings. OBJECTIVES 1) To systematically review the literature on EEG/MEG functional and effective connectivity in autism spectrum disorder (ASD), 2) to synthesize and critically appraise findings related with the hypothesis that ASD is characterized by long-range underconnectivity and local overconnectivity, and 3) to provide, based on the literature, an analysis of tentative factors that are likely to mediate association between ASD and atypical connectivity (e.g., development, topography, lateralization). METHODS Literature reviews were done using PubMed and PsychInfo databases. Abstracts were screened, and only relevant articles were analyzed based on the objectives of this paper. Special attention was paid to the methodological characteristics that could have created variability in outcomes reported between studies. RESULTS Our synthesis provides relatively strong support for long-range underconnectivity in ASD, whereas the status of local connectivity remains unclear. This observation was also mirrored by a similar relationship with lower frequencies being often associated with underconnectivity and higher frequencies being associated with both under- and over-connectivity. Putting together these observations, we propose that ASD is characterized by a general trend toward an under-expression of lower-band wide-spread integrative processes compensated by more focal, higher-frequency, locally specialized, and segregated processes. Further investigation is, however, needed to corroborate the conclusion and its generalizability across different tasks. Of note, abnormal lateralization in ASD, specifically an elevated left-over-right EEG and MEG functional connectivity ratio, has been also reported consistently across studies. CONCLUSIONS The large variability in study samples and methodology makes a systematic quantitative analysis (i.e. meta-analysis) of this body of research impossible. Nevertheless, a general trend supporting the hypothesis of long-range functional underconnectivity can be observed. Further research is necessary to more confidently determine the status of the hypothesis of short-range overconnectivity. Frequency-band specific patterns and their relationships with known symptoms of autism also need to be further clarified.
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Affiliation(s)
- Christian O’Reilly
- Douglas Mental Health University Institute, 6875 Boulevard Lasalle, Verdun, Canada
- Department of Psychiatry, McGill University, 1033 Pine Avenue West, Montreal, QC, Canada
| | - John D. Lewis
- McGill Center for Integrative Neuroscience, Montreal Neurological Institute, McGill University, 3801 University Street, Montréal, QC, Canada
| | - Mayada Elsabbagh
- Douglas Mental Health University Institute, 6875 Boulevard Lasalle, Verdun, Canada
- Department of Psychiatry, McGill University, 1033 Pine Avenue West, Montreal, QC, Canada
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11
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Mamashli F, Khan S, Bharadwaj H, Michmizos K, Ganesan S, Garel KLA, Ali Hashmi J, Herbert MR, Hämäläinen M, Kenet T. Auditory processing in noise is associated with complex patterns of disrupted functional connectivity in autism spectrum disorder. Autism Res 2016; 10:631-647. [PMID: 27910247 DOI: 10.1002/aur.1714] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2016] [Revised: 09/09/2016] [Accepted: 09/16/2016] [Indexed: 11/12/2022]
Abstract
Autism spectrum disorder (ASD) is associated with difficulty in processing speech in a noisy background, but the neural mechanisms that underlie this deficit have not been mapped. To address this question, we used magnetoencephalography to compare the cortical responses between ASD and typically developing (TD) individuals to a passive mismatch paradigm. We repeated the paradigm twice, once in a quiet background, and once in the presence of background noise. We focused on both the evoked mismatch field (MMF) response in temporal and frontal cortical locations, and functional connectivity with spectral specificity between those locations. In the quiet condition, we found common neural sources of the MMF response in both groups, in the right temporal gyrus and inferior frontal gyrus (IFG). In the noise condition, the MMF response in the right IFG was preserved in the TD group, but reduced relative to the quiet condition in ASD group. The MMF response in the right IFG also correlated with severity of ASD. Moreover, in noise, we found significantly reduced normalized coherence (deviant normalized by standard) in ASD relative to TD, in the beta band (14-25 Hz), between left temporal and left inferior frontal sub-regions. However, unnormalized coherence (coherence during deviant or standard) was significantly increased in ASD relative to TD, in multiple frequency bands. Our findings suggest increased recruitment of neural resources in ASD irrespective of the task difficulty, alongside a reduction in top-down modulations, usually mediated by the beta band, needed to mitigate the impact of noise on auditory processing. Autism Res 2016,. © 2016 International Society for Autism Research, Wiley Periodicals, Inc. Autism Res 2017, 10: 631-647. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.
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Affiliation(s)
- Fahimeh Mamashli
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts.,Athinoula A. Martinos Center for Biomedical Imaging, MGH/MIT/Harvard, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts
| | - Sheraz Khan
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts.,Athinoula A. Martinos Center for Biomedical Imaging, MGH/MIT/Harvard, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts.,McGovern Institute for Brain Research Massachusetts Institute of Technology, Boston, Massachusetts
| | - Hari Bharadwaj
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts.,Athinoula A. Martinos Center for Biomedical Imaging, MGH/MIT/Harvard, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts
| | - Konstantinos Michmizos
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts.,Athinoula A. Martinos Center for Biomedical Imaging, MGH/MIT/Harvard, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts.,McGovern Institute for Brain Research Massachusetts Institute of Technology, Boston, Massachusetts
| | - Santosh Ganesan
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts.,Athinoula A. Martinos Center for Biomedical Imaging, MGH/MIT/Harvard, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts
| | - Keri-Lee A Garel
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts.,Athinoula A. Martinos Center for Biomedical Imaging, MGH/MIT/Harvard, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts
| | - Javeria Ali Hashmi
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts.,Athinoula A. Martinos Center for Biomedical Imaging, MGH/MIT/Harvard, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts
| | - Martha R Herbert
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts.,Athinoula A. Martinos Center for Biomedical Imaging, MGH/MIT/Harvard, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts.,Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts.,Department of Neuroscience and Biomedical Engineering, Aalto University School of Science Espoo, Finland
| | - Matti Hämäläinen
- Athinoula A. Martinos Center for Biomedical Imaging, MGH/MIT/Harvard, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts
| | - Tal Kenet
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts.,Athinoula A. Martinos Center for Biomedical Imaging, MGH/MIT/Harvard, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts
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