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Dickinson A, Ryan D, McNaughton G, Levin A, Naples A, Borland H, Bernier R, Chawarska K, Dawson G, Dziura J, Faja S, Kleinhans N, Sugar C, Senturk D, Shic F, Webb SJ, McPartland JC, Jeste S. Parsing evoked and induced gamma response differences in Autism: A visual evoked potential study. Clin Neurophysiol 2024; 165:55-63. [PMID: 38959536 DOI: 10.1016/j.clinph.2024.05.015] [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: 02/06/2024] [Revised: 05/23/2024] [Accepted: 05/26/2024] [Indexed: 07/05/2024]
Abstract
OBJECTIVE Electroencephalography (EEG) measures of visual evoked potentials (VEPs) provide a targeted approach for investigating neural circuit dynamics. This study separately analyses phase-locked (evoked) and non-phase-locked (induced) gamma responses within the VEP to comprehensively investigate circuit differences in autism. METHODS We analyzed VEP data from 237 autistic and 114 typically developing (TD) children aged 6-11, collected through the Autism Biomarkers Consortium for Clinical Trials (ABC-CT). Evoked and induced gamma (30-90 Hz) responses were separately quantified using a wavelet-based time-frequency analysis, and group differences were evaluated using a permutation-based clustering procedure. RESULTS Autistic children exhibited reduced evoked gamma power but increased induced gamma power compared to TD peers. Group differences in induced responses showed the most prominent effect size and remained statistically significant after excluding outliers. CONCLUSIONS Our study corroborates recent research indicating diminished evoked gamma responses in children with autism. Additionally, we observed a pronounced increase in induced power. Building upon existing ABC-CT findings, these results highlight the potential to detect variations in gamma-related neural activity, despite the absence of significant group differences in time-domain VEP components. SIGNIFICANCE The contrasting patterns of decreased evoked and increased induced gamma activity in autistic children suggest that a combination of different EEG metrics may provide a clearer characterization of autism-related circuitry than individual markers alone.
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Affiliation(s)
- Abigail Dickinson
- Center for Autism Research and Treatment, Semel Institute for Neuroscience, University of California, Los Angeles, USA.
| | - Declan Ryan
- Center for Autism Research and Treatment, Semel Institute for Neuroscience, University of California, Los Angeles, USA
| | - Gabrielle McNaughton
- Center for Autism Research and Treatment, Semel Institute for Neuroscience, University of California, Los Angeles, USA
| | - April Levin
- Department of Neurology, Boston Children's Hospital, USA
| | - Adam Naples
- Yale Child Study Center, Yale University School of Medicine, USA
| | - Heather Borland
- Center for Child Health, Behavior, and Development, Seattle Children's Research Institute, USA
| | - Raphael Bernier
- Department of Psychiatry and Behavioral Sciences, University of Washington, USA
| | | | - Geraldine Dawson
- Duke Center for Autism and Brain Development, Duke University, USA
| | - James Dziura
- Emergency Medicine, Yale University, New Haven, CT, USA
| | - Susan Faja
- Department of Pediatrics, Boston Children's Hospital, USA
| | | | - Catherine Sugar
- Department of Biostatistics, University of California Los Angeles, Los Angeles, USA
| | - Damla Senturk
- Department of Biostatistics, University of California Los Angeles, Los Angeles, USA
| | - Frederick Shic
- Center for Child Health, Behavior, and Development, Seattle Children's Research Institute, USA
| | - Sara Jane Webb
- Center for Child Health, Behavior, and Development, Seattle Children's Research Institute, USA
| | | | - Shafali Jeste
- Department of Neurology, Children's Hospital of Los Angeles, USA
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Hou W, Cheng R, Zhao Z, Liao H, Li J. Atypical and variable attention patterns reveal reduced contextual priors in children with autism spectrum disorder. Autism Res 2024; 17:1572-1585. [PMID: 38975627 DOI: 10.1002/aur.3194] [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: 12/27/2023] [Accepted: 06/23/2024] [Indexed: 07/09/2024]
Abstract
Accumulating evidence suggests that individuals with autism spectrum disorder (ASD) show impairments in using contextual priors to predict others' actions and make intention inference. Yet less is known about whether and how children with ASD acquire contextual priors during action observation and how contextual priors relate to their action prediction and intention inference. To form proper contextual priors, individuals need to observe the social scenes in a reliable manner and focus on socially relevant information. By employing a data-driven scan path method and areas of interest (AOI)-based analysis, the current study investigated how contextual priors would relate to action prediction and intention understanding in 4-to-9-year-old children with ASD (N = 56) and typically developing (TD) children (N = 50) during free viewing of dynamic social scenes with different intentions. Results showed that children with ASD exhibited higher intra-subject variability when scanning social scenes and reduced attention to socially relevant areas. Moreover, children with high-level action prediction and intention understanding showed lower intra-subject variability and increased attention to socially relevant areas. These findings suggest that altered fixation patterns might restrain children with ASD from acquiring proper contextual priors, which has cascading downstream effects on their action prediction and intention understanding.
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Affiliation(s)
- Wenwen Hou
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Rong Cheng
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
- College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, China
| | - Zhong Zhao
- College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, China
| | - Haotian Liao
- College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, China
| | - Jing Li
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
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Cannon J, Cardinaux A, Bungert L, Li C, Sinha P. Reduced precision of motor and perceptual rhythmic timing in autistic adults. Heliyon 2024; 10:e34261. [PMID: 39082034 PMCID: PMC11284439 DOI: 10.1016/j.heliyon.2024.e34261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 06/23/2024] [Accepted: 07/05/2024] [Indexed: 08/02/2024] Open
Abstract
Recent results suggest that autistic individuals exhibit reduced accuracy compared to non-autistic peers in temporally coordinating their actions with predictable external cues, e.g., synchronizing finger taps to an auditory metronome. However, it is not yet clear whether these difficulties are driven primarily by motor differences or extend into perceptual rhythmic timing tasks. We recruited autistic and non-autistic participants for an online study testing both finger tapping synchronization and continuation as well as rhythmic time perception (anisochrony detection). We fractionated each participant's synchronization results into parameters representing error correction, motor noise, and internal time-keeper noise, and also investigated error-correcting responses to small metronome timing perturbations. Contrary to previous work, we did not find strong evidence for reduced synchronization error correction. However, we found compelling evidence for noisier internal rhythmic timekeeping in the synchronization, continuation, and perceptual components of the experiment. These results suggest that noisier internal rhythmic timing processes underlie some sensorimotor coordination challenges in autism.
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Affiliation(s)
- Jonathan Cannon
- Department of Psychology, Neuroscience & Behaviour, McMaster University, Hamilton, ON, Canada
| | - Annie Cardinaux
- Department of Brain & Cognitive Science, MIT, Cambridge, MA, USA
| | - Lindsay Bungert
- Department of Brain & Cognitive Science, MIT, Cambridge, MA, USA
| | - Cindy Li
- Department of Brain & Cognitive Science, MIT, Cambridge, MA, USA
- McGovern Institute, MIT, Cambridge, MA, USA
| | - Pawan Sinha
- Department of Brain & Cognitive Science, MIT, Cambridge, MA, USA
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Otten K, Edgar JC, Green HL, Mol K, McNamee M, Kuschner ES, Kim M, Liu S, Huang H, Nordt M, Konrad K, Chen Y. The maturation of infant and toddler visual cortex neural activity and associations with fine motor performance. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.11.598480. [PMID: 38915536 PMCID: PMC11195154 DOI: 10.1101/2024.06.11.598480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
Our understanding of how visual cortex neural processes mature during infancy and toddlerhood is limited. Using magnetoencephalography (MEG), the present study investigated the development of visual evoked responses (VERs) in both cross-sectional and longitudinal samples of infants and toddlers 2 months to 3 years. Brain space analyses focused on N1m and P1m latency, as well as the N1m-to-P1m amplitude. Associations between VER measures and developmental quotient (DQ) scores in the cognitive/visual and fine motor domains were also examined. Results showed a nonlinear decrease in N1m and P1m latency as a function of age, characterized by rapid changes followed by slower progression, with the N1m latency plateauing at 6-7 months and the P1m latency plateauing at 8-9 months. The N1m-to-P1m amplitude also exhibited a non-linear decrease, with strong responses observed in younger infants (∼2-3 months) and then a gradual decline. Associations between N1m and P1m latency and fine motor DQ scores were observed, suggesting that infants with faster visual processing may be better equipped to perform fine motor tasks. The present findings advance our understanding of the maturation of the infant visual system and highlight the relationship between the maturation of visual system and fine motor skills. Highlights The infant N1m and P1m latency shows a nonlinear decrease.N1m latency decreases precede P1m latency decreases.N1m-to-P1m amplitude shows a nonlinear decrease, with stronger responses in younger than older infants.N1m and P1m latency are associated with fine motor DQ.
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Brima T, Beker S, Prinsloo KD, Butler JS, Djukic A, Freedman EG, Molholm S, Foxe JJ. Probing a neural unreliability account of auditory sensory processing atypicalities in Rett Syndrome. J Neurodev Disord 2024; 16:28. [PMID: 38831410 PMCID: PMC11149250 DOI: 10.1186/s11689-024-09544-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Accepted: 05/21/2024] [Indexed: 06/05/2024] Open
Abstract
BACKGROUND In the search for objective tools to quantify neural function in Rett Syndrome (RTT), which are crucial in the evaluation of therapeutic efficacy in clinical trials, recordings of sensory-perceptual functioning using event-related potential (ERP) approaches have emerged as potentially powerful tools. Considerable work points to highly anomalous auditory evoked potentials (AEPs) in RTT. However, an assumption of the typical signal-averaging method used to derive these measures is "stationarity" of the underlying responses - i.e. neural responses to each input are highly stereotyped. An alternate possibility is that responses to repeated stimuli are highly variable in RTT. If so, this will significantly impact the validity of assumptions about underlying neural dysfunction, and likely lead to overestimation of underlying neuropathology. To assess this possibility, analyses at the single-trial level assessing signal-to-noise ratios (SNR), inter-trial variability (ITV) and inter-trial phase coherence (ITPC) are necessary. METHODS AEPs were recorded to simple 100 Hz tones from 18 RTT and 27 age-matched controls (Ages: 6-22 years). We applied standard AEP averaging, as well as measures of neuronal reliability at the single-trial level (i.e. SNR, ITV, ITPC). To separate signal-carrying components from non-neural noise sources, we also applied a denoising source separation (DSS) algorithm and then repeated the reliability measures. RESULTS Substantially increased ITV, lower SNRs, and reduced ITPC were observed in auditory responses of RTT participants, supporting a "neural unreliability" account. Application of the DSS technique made it clear that non-neural noise sources contribute to overestimation of the extent of processing deficits in RTT. Post-DSS, ITV measures were substantially reduced, so much so that pre-DSS ITV differences between RTT and TD populations were no longer detected. In the case of SNR and ITPC, DSS substantially improved these estimates in the RTT population, but robust differences between RTT and TD were still fully evident. CONCLUSIONS To accurately represent the degree of neural dysfunction in RTT using the ERP technique, a consideration of response reliability at the single-trial level is highly advised. Non-neural sources of noise lead to overestimation of the degree of pathological processing in RTT, and denoising source separation techniques during signal processing substantially ameliorate this issue.
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Affiliation(s)
- Tufikameni Brima
- The Frederick J. and Marion A. Schindler Cognitive Neurophysiology Laboratory, Ernest J. Del Monte Institute for Neuroscience & Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA
| | - Shlomit Beker
- The Cognitive Neurophysiology Laboratory, Departments of Pediatrics and Neuroscience, Albert Einstein College of Medicine & Montefiore Medical Center, Bronx, New York, USA
| | - Kevin D Prinsloo
- The Frederick J. and Marion A. Schindler Cognitive Neurophysiology Laboratory, Ernest J. Del Monte Institute for Neuroscience & Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA
| | - John S Butler
- School of Mathematical Sciences, Technological University Dublin, Kevin Street Campus, Dublin 8, Ireland
| | - Aleksandra Djukic
- Rett Syndrome Center, Department of Neurology, Albert Einstein College of Medicine & Montefiore Medical Center, Bronx, New York, USA
| | - Edward G Freedman
- The Frederick J. and Marion A. Schindler Cognitive Neurophysiology Laboratory, Ernest J. Del Monte Institute for Neuroscience & Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA
| | - Sophie Molholm
- The Frederick J. and Marion A. Schindler Cognitive Neurophysiology Laboratory, Ernest J. Del Monte Institute for Neuroscience & Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA
- The Cognitive Neurophysiology Laboratory, Departments of Pediatrics and Neuroscience, Albert Einstein College of Medicine & Montefiore Medical Center, Bronx, New York, USA
| | - John J Foxe
- The Frederick J. and Marion A. Schindler Cognitive Neurophysiology Laboratory, Ernest J. Del Monte Institute for Neuroscience & Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA.
- The Cognitive Neurophysiology Laboratory, Departments of Pediatrics and Neuroscience, Albert Einstein College of Medicine & Montefiore Medical Center, Bronx, New York, USA.
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Corina DP, Coffey-Corina S, Pierotti E, Mankel K, Miller LM. Electrophysiological study of visual processing in children with cochlear implants. Neuropsychologia 2024; 194:108774. [PMID: 38145800 DOI: 10.1016/j.neuropsychologia.2023.108774] [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: 08/15/2023] [Revised: 12/12/2023] [Accepted: 12/19/2023] [Indexed: 12/27/2023]
Abstract
Electrophysiological studies of congenitally deaf children and adults have reported atypical visual evoked potentials (VEPs) which have been associated with both behavioral enhancements of visual attention as well as poorer performance and outcomes in tests of spoken language speech processing. This pattern has often been interpreted as a maladaptive consequence of early auditory deprivation, whereby a remapping of auditory cortex by the visual system ultimately reduces resources necessary for optimal rehabilitative outcomes of spoken language acquisition and use. Making use of a novel electrophysiological paradigm, we compare VEPs in children with severe to profound congenital deafness who received a cochlear implant(s) prior to 31 months (n = 28) and typically developing age matched controls (n = 28). We observe amplitude enhancements and in some cases latency differences in occipitally expressed P1 and N1 VEP components in CI-using children as well as an early frontal negativity, N1a. We relate these findings to developmental factors such as chronological age and spoken language understanding. We further evaluate whether VEPs are additionally modulated by auditory stimulation. Collectively, these data provide a means to examine the extent to which atypical VEPs are consistent with prior accounts of maladaptive cross-modal plasticity. Our results support a view that VEP changes reflect alterations to visual-sensory attention and saliency mechanisms rather than a re-mapping of auditory cortex. The present data suggests that early auditory deprivation may have temporally prolonged effects on visual system processing even after activation and use of cochlear implant.
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Affiliation(s)
- David P Corina
- Center for Mind and Brain, University of California, Davis, USA; Department of Linguistics, University of California, Davis, USA; Department of Psychology, University of California, Davis, USA.
| | - S Coffey-Corina
- Center for Mind and Brain, University of California, Davis, USA
| | - E Pierotti
- Center for Mind and Brain, University of California, Davis, USA; Department of Psychology, University of California, Davis, USA
| | - Kelsey Mankel
- Center for Mind and Brain, University of California, Davis, USA
| | - Lee M Miller
- Center for Mind and Brain, University of California, Davis, USA; Department of Neurobiology, Physiology and Behavior, University of California, Davis, USA; Department of Otolaryngology / Head and Neck Surgery, University of California, Davis, USA
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Dwyer P, Vukusic S, Williams ZJ, Saron CD, Rivera SM. "Neural Noise" in Auditory Responses in Young Autistic and Neurotypical Children. J Autism Dev Disord 2024; 54:642-661. [PMID: 36434480 PMCID: PMC10209352 DOI: 10.1007/s10803-022-05797-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/13/2022] [Indexed: 11/27/2022]
Abstract
Elevated "neural noise" has been advanced as an explanation of autism and autistic sensory experiences. However, functional neuroimaging measures of neural noise may be vulnerable to contamination by recording noise. This study explored variability of electrophysiological responses to tones of different intensities in 127 autistic and 79 typically-developing children aged 2-5 years old. A rigorous data processing pipeline, including advanced visualizations of different signal sources that were maximally independent across different time lags, was used to identify and eliminate putative recording noise. Inter-trial variability was measured using median absolute deviations (MADs) of EEG amplitudes across trials and inter-trial phase coherence (ITPC). ITPC was elevated in autism in the 50 and 60 dB intensity conditions, suggesting diminished (rather than elevated) neural noise in autism, although reduced ITPC to soft 50 dB sounds was associated with increased loudness discomfort. Autistic and non-autistic participants did not differ in MADs, and indeed, the vast majority of the statistical tests examined in this study yielded no significant effects. These results appear inconsistent with the neural noise account.
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Affiliation(s)
- Patrick Dwyer
- Department of Psychology, UC Davis, Davis, CA, USA.
- Center for Mind and Brain, UC Davis, Davis, CA, USA.
- MIND Institute, UC Davis Health, Sacramento, CA, USA.
| | | | - Zachary J Williams
- Medical Scientist Training Program, Vanderbilt University School of Medicine, Nashville, TN, USA
- Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
- Frist Center for Autism and Innovation, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Kennedy Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Clifford D Saron
- Center for Mind and Brain, UC Davis, Davis, CA, USA
- MIND Institute, UC Davis Health, Sacramento, CA, USA
| | - Susan M Rivera
- Department of Psychology, UC Davis, Davis, CA, USA
- Center for Mind and Brain, UC Davis, Davis, CA, USA
- MIND Institute, UC Davis Health, Sacramento, CA, USA
- College of Behavioral and Social Sciences, University of Maryland, College Park, MD, USA
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Brima T, Beker S, Prinsloo KD, Butler JS, Djukic A, Freedman EG, Molholm S, Foxe JJ. Probing a neural unreliability account of auditory sensory processing atypicalities in Rett Syndrome. RESEARCH SQUARE 2024:rs.3.rs-3863341. [PMID: 38352397 PMCID: PMC10862956 DOI: 10.21203/rs.3.rs-3863341/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/22/2024]
Abstract
Background In the search for objective tools to quantify neural function in Rett Syndrome (RTT), which are crucial in the evaluation of therapeutic efficacy in clinical trials, recordings of sensory-perceptual functioning using event-related potential (ERP) approaches have emerged as potentially powerful tools. Considerable work points to highly anomalous auditory evoked potentials (AEPs) in RTT. However, an assumption of the typical signal-averaging method used to derive these measures is "stationarity" of the underlying responses - i.e. neural responses to each input are highly stereotyped. An alternate possibility is that responses to repeated stimuli are highly variable in RTT. If so, this will significantly impact the validity of assumptions about underlying neural dysfunction, and likely lead to overestimation of underlying neuropathology. To assess this possibility, analyses at the single-trial level assessing signal-to-noise ratios (SNR), inter-trial variability (ITV) and inter-trial phase coherence (ITPC) are necessary. Methods AEPs were recorded to simple 100Hz tones from 18 RTT and 27 age-matched controls (Ages: 6-22 years). We applied standard AEP averaging, as well as measures of neuronal reliability at the single-trial level (i.e. SNR, ITV, ITPC). To separate signal-carrying components from non-neural noise sources, we also applied a denoising source separation (DSS) algorithm and then repeated the reliability measures. Results Substantially increased ITV, lower SNRs, and reduced ITPC were observed in auditory responses of RTT participants, supporting a "neural unreliability" account. Application of the DSS technique made it clear that non-neural noise sources contribute to overestimation of the extent of processing deficits in RTT. Post-DSS, ITV measures were substantially reduced, so much so that pre-DSS ITV differences between RTT and TD populations were no longer detected. In the case of SNR and ITPC, DSS substantially improved these estimates in the RTT population, but robust differences between RTT and TD were still fully evident. Conclusions To accurately represent the degree of neural dysfunction in RTT using the ERP technique, a consideration of response reliability at the single-trial level is highly advised. Non-neural sources of noise lead to overestimation of the degree of pathological processing in RTT, and denoising source separation techniques during signal processing substantially ameliorate this issue.
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Brima T, Beker S, Prinsloo KD, Butler JS, Djukic A, Freedman EG, Molholm S, Foxe JJ. Probing a neural unreliability account of auditory sensory processing atypicalities in Rett Syndrome. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.01.25.24301723. [PMID: 38343802 PMCID: PMC10854351 DOI: 10.1101/2024.01.25.24301723] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/26/2024]
Abstract
Background In the search for objective tools to quantify neural function in Rett Syndrome (RTT), which are crucial in the evaluation of therapeutic efficacy in clinical trials, recordings of sensory-perceptual functioning using event-related potential (ERP) approaches have emerged as potentially powerful tools. Considerable work points to highly anomalous auditory evoked potentials (AEPs) in RTT. However, an assumption of the typical signal-averaging method used to derive these measures is "stationarity" of the underlying responses - i.e. neural responses to each input are highly stereotyped. An alternate possibility is that responses to repeated stimuli are highly variable in RTT. If so, this will significantly impact the validity of assumptions about underlying neural dysfunction, and likely lead to overestimation of underlying neuropathology. To assess this possibility, analyses at the single-trial level assessing signal-to-noise ratios (SNR), inter-trial variability (ITV) and inter-trial phase coherence (ITPC) are necessary. Methods AEPs were recorded to simple 100Hz tones from 18 RTT and 27 age-matched controls (Ages: 6-22 years). We applied standard AEP averaging, as well as measures of neuronal reliability at the single-trial level (i.e. SNR, ITV, ITPC). To separate signal-carrying components from non-neural noise sources, we also applied a denoising source separation (DSS) algorithm and then repeated the reliability measures. Results Substantially increased ITV, lower SNRs, and reduced ITPC were observed in auditory responses of RTT participants, supporting a "neural unreliability" account. Application of the DSS technique made it clear that non-neural noise sources contribute to overestimation of the extent of processing deficits in RTT. Post-DSS, ITV measures were substantially reduced, so much so that pre-DSS ITV differences between RTT and TD populations were no longer detected. In the case of SNR and ITPC, DSS substantially improved these estimates in the RTT population, but robust differences between RTT and TD were still fully evident. Conclusions To accurately represent the degree of neural dysfunction in RTT using the ERP technique, a consideration of response reliability at the single-trial level is highly advised. Non-neural sources of noise lead to overestimation of the degree of pathological processing in RTT, and denoising source separation techniques during signal processing substantially ameliorate this issue.
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Affiliation(s)
- Tufikameni Brima
- The Frederick J. and Marion A. Schindler Cognitive Neurophysiology Laboratory Ernest J. Del Monte Institute for Neuroscience &Department of Neuroscience University of Rochester School of Medicine and Dentistry Rochester, New York 14642, USA
| | - Shlomit Beker
- The Cognitive Neurophysiology Laboratory Departments of Pediatrics and Neuroscience Albert Einstein College of Medicine & Montefiore Medical Center Bronx, New York 10461, USA
| | - Kevin D. Prinsloo
- The Frederick J. and Marion A. Schindler Cognitive Neurophysiology Laboratory Ernest J. Del Monte Institute for Neuroscience &Department of Neuroscience University of Rochester School of Medicine and Dentistry Rochester, New York 14642, USA
| | - John S. Butler
- School of Mathematical Sciences Technological University Dublin Kevin Street Campus, Dublin 8, Ireland
| | - Aleksandra Djukic
- Rett Syndrome Center Department of Neurology Albert Einstein College of Medicine & Montefiore Medical Center Bronx, New York 10467, USA
| | - Edward G. Freedman
- The Frederick J. and Marion A. Schindler Cognitive Neurophysiology Laboratory Ernest J. Del Monte Institute for Neuroscience &Department of Neuroscience University of Rochester School of Medicine and Dentistry Rochester, New York 14642, USA
| | - Sophie Molholm
- The Frederick J. and Marion A. Schindler Cognitive Neurophysiology Laboratory Ernest J. Del Monte Institute for Neuroscience &Department of Neuroscience University of Rochester School of Medicine and Dentistry Rochester, New York 14642, USA
- The Cognitive Neurophysiology Laboratory Departments of Pediatrics and Neuroscience Albert Einstein College of Medicine & Montefiore Medical Center Bronx, New York 10461, USA
| | - John J. Foxe
- The Frederick J. and Marion A. Schindler Cognitive Neurophysiology Laboratory Ernest J. Del Monte Institute for Neuroscience &Department of Neuroscience University of Rochester School of Medicine and Dentistry Rochester, New York 14642, USA
- The Cognitive Neurophysiology Laboratory Departments of Pediatrics and Neuroscience Albert Einstein College of Medicine & Montefiore Medical Center Bronx, New York 10461, USA
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Bhaskaran AA, Gauvrit T, Vyas Y, Bony G, Ginger M, Frick A. Endogenous noise of neocortical neurons correlates with atypical sensory response variability in the Fmr1 -/y mouse model of autism. Nat Commun 2023; 14:7905. [PMID: 38036566 PMCID: PMC10689491 DOI: 10.1038/s41467-023-43777-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 11/20/2023] [Indexed: 12/02/2023] Open
Abstract
Excessive neural variability of sensory responses is a hallmark of atypical sensory processing in autistic individuals with cascading effects on other core autism symptoms but unknown neurobiological substrate. Here, by recording neocortical single neuron activity in a well-established mouse model of Fragile X syndrome and autism, we characterized atypical sensory processing and probed the role of endogenous noise sources in exaggerated response variability in males. The analysis of sensory stimulus evoked activity and spontaneous dynamics, as well as neuronal features, reveals a complex cellular and network phenotype. Neocortical sensory information processing is more variable and temporally imprecise. Increased trial-by-trial and inter-neuronal response variability is strongly related to key endogenous noise features, and may give rise to behavioural sensory responsiveness variability in autism. We provide a novel preclinical framework for understanding the sources of endogenous noise and its contribution to core autism symptoms, and for testing the functional consequences for mechanism-based manipulation of noise.
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Affiliation(s)
- Arjun A Bhaskaran
- INSERM, U1215 Neurocentre Magendie, 33077, Bordeaux, France
- University of Bordeaux, 33000, Bordeaux, France
- Department of Psychiatry, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada
| | - Théo Gauvrit
- INSERM, U1215 Neurocentre Magendie, 33077, Bordeaux, France
- University of Bordeaux, 33000, Bordeaux, France
| | - Yukti Vyas
- INSERM, U1215 Neurocentre Magendie, 33077, Bordeaux, France
- University of Bordeaux, 33000, Bordeaux, France
| | - Guillaume Bony
- INSERM, U1215 Neurocentre Magendie, 33077, Bordeaux, France
- University of Bordeaux, 33000, Bordeaux, France
| | - Melanie Ginger
- INSERM, U1215 Neurocentre Magendie, 33077, Bordeaux, France
- University of Bordeaux, 33000, Bordeaux, France
| | - Andreas Frick
- INSERM, U1215 Neurocentre Magendie, 33077, Bordeaux, France.
- University of Bordeaux, 33000, Bordeaux, France.
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Arnett AB, Gourdet G, Peisch V, Spaulding K, Ferrara E, Li V. The role of single trial variability in event related potentials in children with attention deficit hyperactivity disorder. Clin Neurophysiol 2023; 149:1-8. [PMID: 36841009 PMCID: PMC10101921 DOI: 10.1016/j.clinph.2023.01.021] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 01/21/2023] [Accepted: 01/27/2023] [Indexed: 02/17/2023]
Abstract
OBJECTIVE Children with attention deficit hyperactivity disorder (ADHD) show attenuated mean P3 component amplitudes compared to typically developing (TD) children. This finding may be the result of individual differences in P3 amplitudes, P3 latencies, and/or greater single trial variability (STV) in amplitude or latency, suggesting neural "noise." METHODS Event related potentials (ERPs) from 75 children with ADHD and 29 TD children were recorded with electroencephalography (EEG). Caregivers provided ratings on child ADHD symptoms. Single-trial ERP amplitudes and latencies were extracted from the P3 component time window during a visual oddball task. Additionally, we computed individual-centered and trial-centered P3 amplitudes to account for inter-individual and inter-trial variability in the timing of the P3 peak. RESULTS In line with prior research, greater ADHD symptom severity was associated with reduced mean P3 amplitude. This correlation was no longer significant after correcting for inter-trial differences in P3 latency. In contrast, greater ADHD symptom severity was associated with reduced STV in P3 amplitude. CONCLUSIONS Our results suggest that attenuated average P3 amplitude in ADHD samples is due to a consistent reduction in strength of the neurophysiological signal at the single trial level, as well as increased inter-trial variability in the timing of P3 peak amplitudes. The traditional method of extracting P3 amplitudes based on a single time window for all trials may not adequately capture variability in P3 latencies associated with ADHD. SIGNIFICANCE Inter- and intra-individual differences in brain signatures should be considered in models of neurobiological differences in neurodevelopmental samples.
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Affiliation(s)
- Anne B Arnett
- Division of Developmental Medicine, Boston Children's Hospital, Boston, MA, USA; Pediatrics, Harvard Medical School, Boston, MA, USA.
| | - Gaelle Gourdet
- Division of Developmental Medicine, Boston Children's Hospital, Boston, MA, USA
| | - Virginia Peisch
- Division of Developmental Medicine, Boston Children's Hospital, Boston, MA, USA
| | - Katherine Spaulding
- Division of Developmental Medicine, Boston Children's Hospital, Boston, MA, USA
| | - Erica Ferrara
- Division of Developmental Medicine, Boston Children's Hospital, Boston, MA, USA
| | - Vivian Li
- Division of Developmental Medicine, Boston Children's Hospital, Boston, MA, USA
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Webb SJ, Naples AJ, Levin AR, Hellemann G, Borland H, Benton J, Carlos C, McAllister T, Santhosh M, Seow H, Atyabi A, Bernier R, Chawarska K, Dawson G, Dziura J, Faja S, Jeste S, Murias M, Nelson CA, Sabatos-DeVito M, Senturk D, Shic F, Sugar CA, McPartland JC. The Autism Biomarkers Consortium for Clinical Trials: Initial Evaluation of a Battery of Candidate EEG Biomarkers. Am J Psychiatry 2023; 180:41-49. [PMID: 36000217 PMCID: PMC10027395 DOI: 10.1176/appi.ajp.21050485] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
OBJECTIVE Numerous candidate EEG biomarkers have been put forward for use in clinical research on autism spectrum disorder (ASD), but biomarker development has been hindered by limited attention to the psychometric properties of derived variables, inconsistent results across small studies, and variable methodology. The authors evaluated the basic psychometric properties of a battery of EEG assays for their potential suitability as biomarkers in clinical trials. METHODS This was a large, multisite, naturalistic study in 6- to 11-year-old children who either had an ASD diagnosis (N=280) or were typically developing (N=119). The authors evaluated an EEG battery composed of well-studied assays of resting-state activity, face perception (faces task), biological motion perception, and visual evoked potentials (VEPs). Biomarker psychometrics were evaluated in terms of acquisition rates, construct performance, and 6-week stability. Preliminary evaluation of use was explored through group discrimination and phenotypic correlations. RESULTS Three assays (resting state, faces task, and VEP) show promise in terms of acquisition rates and construct performance. Six-week stability values in the ASD group were moderate (intraclass correlations ≥0.66) for the faces task latency of the P1 and N170, the VEP amplitude of N1 and P1, and resting alpha power. Group discrimination and phenotype correlations were primarily observed for the faces task P1 and N170. CONCLUSIONS In the context of a large-scale, rigorous evaluation of candidate EEG biomarkers for use in ASD clinical trials, neural response to faces emerged as a promising biomarker for continued evaluation. Resting-state activity and VEP yielded mixed results. The study's biological motion perception assay failed to display construct performance. The results provide information about EEG biomarker performance that is relevant for the next stage of biomarker development efforts focused on context of use.
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Affiliation(s)
- Sara Jane Webb
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Adam J Naples
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - April R Levin
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Gerhard Hellemann
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Heather Borland
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Jessica Benton
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Carter Carlos
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Takumi McAllister
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Megha Santhosh
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Helen Seow
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Adham Atyabi
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Raphael Bernier
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Katarzyna Chawarska
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Geraldine Dawson
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - James Dziura
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Susan Faja
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Shafali Jeste
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Michael Murias
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Charles A Nelson
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Maura Sabatos-DeVito
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Damla Senturk
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Frederick Shic
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Catherine A Sugar
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - James C McPartland
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
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13
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Granerud G, Elvsåshagen T, Arntzen E, Juhasz K, Emilsen NM, Sønderby IE, Nærland T, Malt EA. A family study of symbolic learning and synaptic plasticity in autism spectrum disorder. Front Hum Neurosci 2022; 16:950922. [PMID: 36504626 PMCID: PMC9730282 DOI: 10.3389/fnhum.2022.950922] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 05/23/2022] [Indexed: 11/25/2022] Open
Abstract
The current study presents a male with autism spectrum disorder (ASD) and a 3q29 deletion, and three healthy first-degree relatives. Our magnetic resonance imaging (MRI) dataset included a healthy control subset. We describe a comprehensive multimodal approach, including equivalence class formation, neurocognitive testing, MRI, and electroencephalography (EEG)-based cortical plasticity, which can provide new insights into socio-communicative and learning impairments and neural underpinnings in ASD. On neurocognitive testing, the proband showed reduced processing speed, attending behavior, and executive function. He required more training trials in equivalence class training compared with family members and exhibited impaired priming of words compared with priming with images. The proband had smaller intracranial volume and surface area and a larger visual evoked potential (VEP) C1 amplitude than family members and intact long-term potentiation (LTP)-like visual cortex plasticity. Together, these results suggest that 3q29 deletion-related ASD is associated with impaired problem-solving strategies in complex socio-communicative and learning tasks, smaller intracranial and surface area, altered VEP amplitude, and normal LTP-like visual cortex plasticity. Further studies are needed to clarify whether this multimodal approach can be used to identify ASD subgroups with distinct neurobiological alterations and to uncover mechanisms underlying socio-communicative and learning impairments. Lay Summary: We studied learning, brain activity, and brain structure in a person with autism and a genetic aberration, and his close relatives. Compared with relatives, the person with autism required more training for learning, and visual learning was better than verbal learning. This person had some changes in the activity of the visual cortex, and the size and the surface area of the brain were reduced. Knowledge about learning and brain mechanisms is valuable for the development of training programs for individuals with autism.
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Affiliation(s)
- Guro Granerud
- Department of Adult Habilitation, Akershus University Hospital, Oslo, Norway,Department of Behavioral Science, Oslo Metropolitan University, Oslo, Norway,KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway,*Correspondence: Guro Granerud
| | - Torbjørn Elvsåshagen
- Norwegian Centre for Mental Disorders Research, Oslo University Hospital, Oslo, Norway,Department of Neurology, Oslo University Hospital, Oslo, Norway,Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Erik Arntzen
- Department of Behavioral Science, Oslo Metropolitan University, Oslo, Norway
| | - Katalin Juhasz
- Department of Adult Habilitation, Akershus University Hospital, Oslo, Norway
| | - Nina Merete Emilsen
- Department of Adult Habilitation, Akershus University Hospital, Oslo, Norway
| | - Ida Elken Sønderby
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway,Norwegian Centre for Mental Disorders Research, Oslo University Hospital, Oslo, Norway,Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - Terje Nærland
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway,NevSom Department of Rare Disorders and Disabilities, Oslo University Hospital, Oslo, Norway
| | - Eva Albertsen Malt
- Department of Adult Habilitation, Akershus University Hospital, Oslo, Norway,Institute of Clinical Medicine, Campus Ahus, University of Oslo, Oslo, Norway
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14
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Canu D, Ioannou C, Müller K, Martin B, Fleischhaker C, Biscaldi M, Beauducel A, Smyrnis N, van Elst LT, Klein C. Evidence towards a continuum of impairment across neurodevelopmental disorders from basic ocular-motor tasks. Sci Rep 2022; 12:16521. [PMID: 36192503 PMCID: PMC9530118 DOI: 10.1038/s41598-022-19661-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 09/01/2022] [Indexed: 11/18/2022] Open
Abstract
Findings of genetic overlap between Schizophrenia, Attention-Deficit/Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD) contributed to a renewed conceptualization of these disorders as laying on a continuum based on aetiological, pathophysiological and neurodevelopmental features. Given that cognitive impairments are core to their pathophysiology, we compared patients with schizophrenia, ADHD, ASD, and controls on ocular-motor and manual-motor tasks, challenging crucial cognitive processes. Group comparisons revealed inhibition deficits common to all disorders, increased intra-subject variability in schizophrenia and, to a lesser extent, ADHD as well as slowed processing in schizophrenia. Patterns of deviancies from controls exhibited strong correlations, along with differences that posited schizophrenia as the most impaired group, followed by ASD and ADHD. While vector correlations point towards a common neurodevelopmental continuum of impairment, vector levels suggest differences in the severity of such impairment. These findings argue towards a dimensional approach to Neurodevelopmental Disorders' pathophysiological mechanisms.
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Affiliation(s)
- Daniela Canu
- Department of Child and Adolescent Psychiatry, Psychotherapy, and Psychosomatics, Medical Centre - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
| | - Chara Ioannou
- Department of Child and Adolescent Psychiatry, Psychotherapy, and Psychosomatics, Medical Centre - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Katarina Müller
- Psychotherapeutisches Wohnheim für Junge Menschen Leppermühle, Buseck, Germany
| | - Berthold Martin
- Psychotherapeutisches Wohnheim für Junge Menschen Leppermühle, Buseck, Germany
| | - Christian Fleischhaker
- Department of Child and Adolescent Psychiatry, Psychotherapy, and Psychosomatics, Medical Centre - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Monica Biscaldi
- Department of Child and Adolescent Psychiatry, Psychotherapy, and Psychosomatics, Medical Centre - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | | | - Nikolaos Smyrnis
- 2nd Psychiatry Department, National and Kapodistrian University of Athens, Medical School, University General Hospital "ATTIKON", Athens, Greece
- Laboratory of Cognitive Neuroscience and Sensorimotor Control, University Mental Health, Neurosciences and Precision Medicine Research Institute «COSTAS STEFANIS», Athens, Greece
| | - Ludger Tebartz van Elst
- Department of Psychiatry and Psychotherapy, Medical Centre - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Christoph Klein
- Department of Child and Adolescent Psychiatry, Psychotherapy, and Psychosomatics, Medical Centre - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
- 2nd Psychiatry Department, National and Kapodistrian University of Athens, Medical School, University General Hospital "ATTIKON", Athens, Greece.
- Department of Child and Adolescent Psychiatry, Medical Faculty, University of Cologne, Cologne, Germany.
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15
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Dwyer P, Takarae Y, Zadeh I, Rivera SM, Saron CD. Multisensory integration and interactions across vision, hearing, and somatosensation in autism spectrum development and typical development. Neuropsychologia 2022; 175:108340. [PMID: 36028085 DOI: 10.1016/j.neuropsychologia.2022.108340] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 06/13/2022] [Accepted: 07/22/2022] [Indexed: 10/15/2022]
Abstract
Most prior studies of multisensory integration (MSI) in autism have measured MSI in only a single combination of modalities - typically audiovisual integration. The present study used onset reaction times (RTs) and 125-channel electroencephalography (EEG) to examine different forms of bimodal and trimodal MSI based on combinations of auditory (noise burst), somatosensory (finger tap), and visual (flash) stimuli presented in a spatially-aligned manner using a custom desktop apparatus. A total of 36 autistic and 19 non-autistic adolescents between the ages of 11-14 participated. Significant RT multisensory facilitation relative to summed unisensory RT was observed in both groups, as were significant differences between summed unisensory and multisensory ERPs. Although the present study's statistical approach was not intended to test effect latencies, these interactions may have begun as early as ∼45 ms, constituting "early" (<100 ms) MSI. RT and ERP measurements of MSI appeared independent of one another. Groups did not significantly differ in multisensory RT facilitation, but we found exploratory evidence of group differences in the magnitude of audiovisual interactions in ERPs. Future research should make greater efforts to explore MSI in under-represented populations, especially autistic people with intellectual disabilities and nonspeaking/minimally-verbal autistic people.
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Affiliation(s)
- Patrick Dwyer
- Department of Psychology, UC Davis, USA; Center for Mind and Brain, UC Davis, USA.
| | - Yukari Takarae
- Department of Neurosciences, UC San Diego, USA; Department of Psychology, San Diego State University, USA
| | | | - Susan M Rivera
- Department of Psychology, UC Davis, USA; Center for Mind and Brain, UC Davis, USA; MIND Institute, UC Davis, USA
| | - Clifford D Saron
- Center for Mind and Brain, UC Davis, USA; MIND Institute, UC Davis, USA
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16
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Ash RT, Palagina G, Fernandez-Leon JA, Park J, Seilheimer R, Lee S, Sabharwal J, Reyes F, Wang J, Lu D, Sarfraz M, Froudarakis E, Tolias AS, Wu SM, Smirnakis SM. Increased Reliability of Visually-Evoked Activity in Area V1 of the MECP2-Duplication Mouse Model of Autism. J Neurosci 2022; 42:6469-6482. [PMID: 35831173 PMCID: PMC9398540 DOI: 10.1523/jneurosci.0654-22.2022] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2022] [Revised: 05/15/2022] [Accepted: 06/02/2022] [Indexed: 11/21/2022] Open
Abstract
Atypical sensory processing is now thought to be a core feature of the autism spectrum. Influential theories have proposed that both increased and decreased neural response reliability within sensory systems could underlie altered sensory processing in autism. Here, we report evidence for abnormally increased reliability of visual-evoked responses in layer 2/3 neurons of adult male and female primary visual cortex in the MECP2-duplication syndrome animal model of autism. Increased response reliability was due in part to decreased response amplitude, decreased fluctuations in endogenous activity, and an abnormal decoupling of visual-evoked activity from endogenous activity. Similar to what was observed neuronally, the optokinetic reflex occurred more reliably at low contrasts in mutant mice compared with controls. Retinal responses did not explain our observations. These data suggest that the circuit mechanisms for combining sensory-evoked and endogenous signal and noise processes may be altered in this form of syndromic autism.SIGNIFICANCE STATEMENT Atypical sensory processing is now thought to be a core feature of the autism spectrum. Influential theories have proposed that both increased and decreased neural response reliability within sensory systems could underlie altered sensory processing in autism. Here, we report evidence for abnormally increased reliability of visual-evoked responses in primary visual cortex of the animal model for MECP2-duplication syndrome, a high-penetrance single-gene cause of autism. Visual-evoked activity was abnormally decoupled from endogenous activity in mutant mice, suggesting in line with the influential "hypo-priors" theory of autism that sensory priors embedded in endogenous activity may have less influence on perception in autism.
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Affiliation(s)
- Ryan T Ash
- Department of Psychiatry, Stanford University School of Medicine, Stanford, California 94305
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115
- Department of Neuroscience, Baylor College of Medicine, Houston, Texas 77030
| | - Ganna Palagina
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115
| | - Jose A Fernandez-Leon
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115
- Department of Neuroscience, Baylor College of Medicine, Houston, Texas 77030
- Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires and Instituto de Investigación en Tecnología Informática Avanzada, Exact Sciences Faculty-Universidad Nacional del Centro de la Provincia de Buenos Aires, Tandil, Argentina
| | - Jiyoung Park
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115
- Program in Structural and Computational Biology and Molecular Biophysics, Baylor College of Medicine, Houston, Texas 77030
| | - Rob Seilheimer
- Program in Structural and Computational Biology and Molecular Biophysics, Baylor College of Medicine, Houston, Texas 77030
- Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Sangkyun Lee
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115
| | - Jasdeep Sabharwal
- Department of Neuroscience, Baylor College of Medicine, Houston, Texas 77030
- Wilmer Eye Institute, Johns Hopkins University, Baltimore, Maryland 21205
| | - Fredy Reyes
- Department of Neuroscience, Baylor College of Medicine, Houston, Texas 77030
| | - Jing Wang
- Department of Ophthalmology, Baylor College of Medicine, Houston, Texas 77030
| | - Dylan Lu
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115
| | - Muhammad Sarfraz
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115
| | - Emmanouil Froudarakis
- Department of Neuroscience, Baylor College of Medicine, Houston, Texas 77030
- FORTH, Heraklion, Crete, Greece 70013
| | - Andreas S Tolias
- Department of Neuroscience, Baylor College of Medicine, Houston, Texas 77030
| | - Samuel M Wu
- Department of Neuroscience, Baylor College of Medicine, Houston, Texas 77030
- Department of Ophthalmology, Baylor College of Medicine, Houston, Texas 77030
| | - Stelios M Smirnakis
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115
- Department of Neuroscience, Baylor College of Medicine, Houston, Texas 77030
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17
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Sheela P, Puthankattil SD. MVME-RCMFDE framework for discerning hyper-responsivity in Autism Spectrum Disorders. Comput Biol Med 2022; 149:105958. [PMID: 36007291 DOI: 10.1016/j.compbiomed.2022.105958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 07/26/2022] [Accepted: 08/06/2022] [Indexed: 12/01/2022]
Abstract
BACKGROUND Autism Spectrum Disorder (ASD), characterized by impaired sensory processing, has a wide range of clinical heterogeneity, which handicaps effective therapeutic interventions. Therefore, it is imperative to develop potential mechanisms for delineating clinically meaningful subgroups, so as to provide individualised medical treatment. In this study, an attempt is being made to differentiate the hyper-responsive subgroup from ASD by analysing the complexity pattern of Visual Evoked Potentials (VEPs), recorded from a group of 30 ASD participants, in the presence of vertical achromatic sinewave gratings at varying contrast conditions of low (5%), medium (50%) and high (90%). METHOD This study proposes a new diagnostic framework incorporating a novel signal decomposition method termed as Modified Variational Mode Extraction (MVME) and a multiscale entropy approach. MVME segments the signal into five constituent modes with less spectral overlap in lower frequencies. Refined Composite Multiscale Fluctuation-based Dispersion entropy (RCMFDE) is extracted from these constituent modes, thereby facilitating the identification of hyper-responsive subgroup in ASD. RESULTS When tested on both simulated and real VEPs, MVME displays appreciable performance in terms of root mean square error and minimal spectral overlap in the lower frequencies, in comparison with the other state-of-the-art techniques. Relative Complexity analysis with RCMFDE exhibits a rising trend in 43%-50% of ASD in modes 1, 2, 3 and 4. CONCLUSION The proposed MVME-RCMFDE approach is efficient in discriminating the hyper-responsive subgroup in ASD in multiple modes namely mode 1, 2, 3 and 4, which correspond to delta, theta, alpha and beta frequency bands of brain signals.
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Affiliation(s)
- Priyalakshmi Sheela
- Department of Electrical Engineering, National Institute of Technology, Calicut, 673601, Kerala, India
| | - Subha D Puthankattil
- Department of Electrical Engineering, National Institute of Technology, Calicut, 673601, Kerala, India.
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18
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Altered EEG variability on different time scales in participants with autism spectrum disorder: an exploratory study. Sci Rep 2022; 12:13068. [PMID: 35906301 PMCID: PMC9338240 DOI: 10.1038/s41598-022-17304-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 07/22/2022] [Indexed: 11/20/2022] Open
Abstract
One of the great challenges in psychiatry is finding reliable biomarkers that may allow for more accurate diagnosis and treatment of patients. Neural variability received increasing attention in recent years as a potential biomarker. In the present explorative study we investigated temporal variability in visually evoked EEG activity in a cohort of 16 adult participants with Asperger Syndrome (AS) and 19 neurotypical (NT) controls. Participants performed a visual oddball task using fine and coarse checkerboard stimuli. We investigated various measures of neural variability and found effects on multiple time scales. (1) As opposed to the previous studies, we found reduced inter-trial variability in the AS group compared to NT. (2) This effect builds up over the entire course of a 5-min experiment and (3) seems to be based on smaller variability of neural background activity in AS compared to NTs. The here reported variability effects come with considerably large effect sizes, making them promising candidates for potentially reliable biomarkers in psychiatric diagnostics. The observed pattern of universality across different time scales and stimulation conditions indicates trait-like effects. Further research with a new and larger set of participants are thus needed to verify or falsify our findings.
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19
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Ganin IP, Kaplan AY. Study of the human brain potentials variability effects in P300 based brain–computer interface. BULLETIN OF RUSSIAN STATE MEDICAL UNIVERSITY 2022. [DOI: 10.24075/brsmu.2022.033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
The P300-based brain–computer interfaces (P300 BCI) allow the user to select commands by focusing on them. The technology involves electroencephalographic (EEG) representation of the event-related potentials (ERP) that arise in response to repetitive external stimulation. Conventional procedures for ERP extraction and analysis imply that identical stimuli produce identical responses. However, the floating onset of EEG reactions is a known neurophysiological phenomenon. A failure to account for this source of variability may considerably skew the output and undermine the overall accuracy of the interface. This study aimed to analyze the effects of ERP variability in EEG reactions in order to minimize their influence on P300 BCI command classification accuracy. Healthy subjects aged 21–22 years (n = 12) were presented with a modified P300 BCI matrix moving with specified parameters within the working area. The results strongly support the inherent significance of ERP variability in P300 BCI environments. The correction of peak latencies in single EEG reactions provided a 1.5–2 fold increase in ERP amplitude with a concomitant enhancement of classification accuracy (from 71–78% to 92–95%, p < 0.0005). These effects were particularly pronounced in attention-demanding tasks with the highest matrix velocities. The findings underscore the importance of accounting for ERP variability in advanced BCI systems.
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Affiliation(s)
- IP Ganin
- Lomonosov Moscow State University, Moscow, Russia
| | - AYa Kaplan
- Lomonosov Moscow State University, Moscow, Russia
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20
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Heller Murray ES, Segawa J, Karahanoglu FI, Tocci C, Tourville JA, Nieto-Castanon A, Tager-Flusberg H, Manoach DS, Guenther FH. Increased Intra-Subject Variability of Neural Activity During Speech Production in People with Autism Spectrum Disorder. RESEARCH IN AUTISM SPECTRUM DISORDERS 2022; 94:101955. [PMID: 35601992 PMCID: PMC9119427 DOI: 10.1016/j.rasd.2022.101955] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Background Communication difficulties are a core deficit in many people with autism spectrum disorder (ASD). The current study evaluated neural activation in participants with ASD and neurotypical (NT) controls during a speech production task. Methods Neural activities of participants with ASD (N = 15, M = 16.7 years, language abilities ranged from low verbal abilities to verbally fluent) and NT controls (N = 12, M = 17.1 years) was examined using functional magnetic resonance imaging with a sparse-sampling paradigm. Results There were no differences between the ASD and NT groups in average speech activation or inter-subject run-to-run variability in speech activation. Intra-subject run-to-run neural variability was greater in the ASD group and was positively correlated with autism severity in cortical areas associated with speech. Conclusions These findings highlight the importance of understanding intra-subject neural variability in participants with ASD.
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Affiliation(s)
- Elizabeth S. Heller Murray
- Boston University, Department of Speech, Language, & Hearing Sciences, 635 Commonwealth Avenue, Boston, MA, 02215
| | - Jennifer Segawa
- Boston University, Department of Speech, Language, & Hearing Sciences, 635 Commonwealth Avenue, Boston, MA, 02215
| | - F. Isik Karahanoglu
- Massachusetts General Hospital, Department of Psychiatry, Harvard Medical School, 55 Fruit Street, Boston, MA, 02215
| | - Catherine Tocci
- Massachusetts General Hospital, Department of Psychiatry, Harvard Medical School, 55 Fruit Street, Boston, MA, 02215
| | - Jason A. Tourville
- Boston University, Department of Speech, Language, & Hearing Sciences, 635 Commonwealth Avenue, Boston, MA, 02215
| | - Alfonso Nieto-Castanon
- Boston University, Department of Speech, Language, & Hearing Sciences, 635 Commonwealth Avenue, Boston, MA, 02215
| | - Helen Tager-Flusberg
- Boston University, Department of Psychological and Brain Sciences, 64 Cummington Mall Boston, MA, 02115
| | - Dara S. Manoach
- Massachusetts General Hospital, Department of Psychiatry, Harvard Medical School, 55 Fruit Street, Boston, MA, 02215
- Athinoula A. Martinos Center for Biomedical Imaging, 149 13th Street, Room 2618, Charlestown, MA 02129
| | - Frank H. Guenther
- Boston University, Department of Speech, Language, & Hearing Sciences, 635 Commonwealth Avenue, Boston, MA, 02215
- Boston University, Department of Biomedical Engineering, 44 Cummington Mall Boston, MA, 02115
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21
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Neklyudova A, Smirnov K, Rebreikina A, Martynova O, Sysoeva O. Electrophysiological and Behavioral Evidence for Hyper- and Hyposensitivity in Rare Genetic Syndromes Associated with Autism. Genes (Basel) 2022; 13:671. [PMID: 35456477 PMCID: PMC9027402 DOI: 10.3390/genes13040671] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Revised: 03/29/2022] [Accepted: 04/05/2022] [Indexed: 01/27/2023] Open
Abstract
Our study reviewed abnormalities in spontaneous, as well as event-related, brain activity in syndromes with a known genetic underpinning that are associated with autistic symptomatology. Based on behavioral and neurophysiological evidence, we tentatively subdivided the syndromes on primarily hyper-sensitive (Fragile X, Angelman) and hypo-sensitive (Phelan-McDermid, Rett, Tuberous Sclerosis, Neurofibromatosis 1), pointing to the way of segregation of heterogeneous idiopathic ASD, that includes both hyper-sensitive and hypo-sensitive individuals. This segmentation links abnormalities in different genes, such as FMR1, UBE3A, GABRB3, GABRA5, GABRG3, SHANK3, MECP2, TSC1, TSC2, and NF1, that are causative to the above-mentioned syndromes and associated with synaptic transmission and cell growth, as well as with translational and transcriptional regulation and with sensory sensitivity. Excitation/inhibition imbalance related to GABAergic signaling, and the interplay of tonic and phasic inhibition in different brain regions might underlie this relationship. However, more research is needed. As most genetic syndromes are very rare, future investigations in this field will benefit from multi-site collaboration with a common protocol for electrophysiological and event-related potential (EEG/ERP) research that should include an investigation into all modalities and stages of sensory processing, as well as potential biomarkers of GABAergic signaling (such as 40-Hz ASSR).
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Affiliation(s)
- Anastasia Neklyudova
- Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Science, 117485 Moscow, Russia; (A.N.); (K.S.); (A.R.); (O.M.)
| | - Kirill Smirnov
- Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Science, 117485 Moscow, Russia; (A.N.); (K.S.); (A.R.); (O.M.)
| | - Anna Rebreikina
- Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Science, 117485 Moscow, Russia; (A.N.); (K.S.); (A.R.); (O.M.)
- Sirius Center for Cognitive Research, Sirius University of Science and Technology, 354340 Sochi, Russia
| | - Olga Martynova
- Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Science, 117485 Moscow, Russia; (A.N.); (K.S.); (A.R.); (O.M.)
| | - Olga Sysoeva
- Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Science, 117485 Moscow, Russia; (A.N.); (K.S.); (A.R.); (O.M.)
- Sirius Center for Cognitive Research, Sirius University of Science and Technology, 354340 Sochi, Russia
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22
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van Noordt S, Desjardins JA, Elsabbagh M. Inter-trial theta phase consistency during face processing in infants is associated with later emerging autism. Autism Res 2022; 15:834-846. [PMID: 35348304 DOI: 10.1002/aur.2701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 01/08/2022] [Accepted: 01/30/2022] [Indexed: 11/05/2022]
Abstract
A growing body of research suggests that consistency in cortical activity may be a promising neurophysiological marker of autism spectrum disorder (ASD). In the current study we examined inter-trial coherence, a measure of phase consistency across trials, in the theta range (t-ITC: 3-6 Hz), as theta has been implicated in the processing of social and emotional stimuli in infants and adults. The sample included infants who had an older sibling with a confirmed ASD diagnosis and typically developing (TD) infants with no family history of ASD. The data were collected as part of the British Autism Study of Infant Siblings (BASIS) study. Infants between 6 and 10 months of age (Mage = 7.34, SDage = 1.21) performed a visual face processing task that included faces and scrambled, "face noise", stimuli. Follow-up assessments in higher likelihood infants were completed at 24 and again at 36 months to determine diagnostic outcomes. Analysis focused on posterior t-ITC during early (0-200 ms) and late (200-500 ms) visual processing stages commonly investigated in infant studies. t-ITC over posterior scalp regions during late stage face processing was significantly higher in TD and higher likelihood infants without ASD (HRA-), indicating reduced consistency in theta-band responses in higher likelihood infants who eventually receive a diagnosis of ASD (HRA+). These findings indicate that the temporal dynamics of theta during face processing relate to ASD outcomes. Reduced consistency of oscillatory dynamics at basic levels of infant sensory processing could have downstream effects on learning and social communication. LAY SUMMARY: We examined the consistency in brain responses to faces in infants at lower or higher familial likelihood for autism. Our results show that the consistency of EEG responses was lower during face processing in higher likelihood infants who eventually received a diagnosis of autism. These findings highlight that reduced consistency in brain activity during face processing in the first year of life is related to emerging autism.
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Affiliation(s)
- Stefon van Noordt
- Department of Psychology, Mount Saint Vincent University, Halifax, Canada
| | - James A Desjardins
- Montreal Neurological Institute-Hospital, Azrieli Centre for Autism Research, McGill University, Montreal, Canada.,SHARCNET, Compute Ontario, Compute Canada
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- Centre for Brain and Cognitive Development, Department of Psychological Sciences, Birkbeck, University of London, London, UK
| | - Mayada Elsabbagh
- Montreal Neurological Institute-Hospital, Azrieli Centre for Autism Research, McGill University, Montreal, Canada
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23
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Abdulhay E, Alafeef M, Hadoush H, Venkataraman V, Arunkumar N. EMD-based analysis of complexity with dissociated EEG amplitude and frequency information: a data-driven robust tool -for Autism diagnosis- compared to multi-scale entropy approach. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2022; 19:5031-5054. [PMID: 35430852 DOI: 10.3934/mbe.2022235] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
OBJECTIVE Autism spectrum disorder (ASD) is usually characterised by altered social skills, repetitive behaviours, and difficulties in verbal/nonverbal communication. It has been reported that electroencephalograms (EEGs) in ASD are characterised by atypical complexity. The most commonly applied method in studies of ASD EEG complexity is multiscale entropy (MSE), where the sample entropy is evaluated across several scales. However, the accuracy of MSE-based classifications between ASD and neurotypical EEG activities is poor owing to several shortcomings in scale extraction and length, the overlap between amplitude and frequency information, and sensitivity to frequency. The present study proposes a novel, nonlinear, non-stationary, adaptive, data-driven, and accurate method for the classification of ASD and neurotypical groups based on EEG complexity and entropy without the shortcomings of MSE. APPROACH The proposed method is as follows: (a) each ASD and neurotypical EEG (122 subjects × 64 channels) is decomposed using empirical mode decomposition (EMD) to obtain the intrinsic components (intrinsic mode functions). (b) The extracted components are normalised through the direct quadrature procedure. (c) The Hilbert transforms of the components are computed. (d) The analytic counterparts of components (and normalised components) are found. (e) The instantaneous frequency function of each analytic normalised component is calculated. (f) The instantaneous amplitude function of each analytic component is calculated. (g) The Shannon entropy values of the instantaneous frequency and amplitude vectors are computed. (h) The entropy values are classified using a neural network (NN). (i) The achieved accuracy is compared to that obtained with MSE-based classification. (j) The consistency of the results of entropy 3D mapping with clinical data is assessed. MAIN RESULTS The results demonstrate that the proposed method outperforms MSE (accuracy: 66.4%), with an accuracy of 93.5%. Moreover, the entropy 3D mapping results are more consistent with the available clinical data regarding brain topography in ASD. SIGNIFICANCE This study presents a more robust alternative to MSE, which can be used for accurate classification of ASD/neurotypical as well as for the examination of EEG entropy across brain zones in ASD.
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Affiliation(s)
- Enas Abdulhay
- Biomedical Engineering department, Jordan University of Science and Technology, 22110 Irbid, Jordan
| | - Maha Alafeef
- Biomedical Engineering department, Jordan University of Science and Technology, 22110 Irbid, Jordan
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA
| | - Hikmat Hadoush
- Rehabilitation Sciences department, Jordan University of Science and Technology, 22110 Irbid, Jordan
| | - V Venkataraman
- Department of Mathematics, School of Arts, Science and Humanities, SASTRA Deemed University, Thanjavur, 613401, India
| | - N Arunkumar
- Biomedical Engineering department, Rathinam Technical Campus, Coimbatore, India
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The amplitude of fNIRS hemodynamic response in the visual cortex unmasks autistic traits in typically developing children. Transl Psychiatry 2022; 12:53. [PMID: 35136021 PMCID: PMC8826368 DOI: 10.1038/s41398-022-01820-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Revised: 01/17/2022] [Accepted: 01/19/2022] [Indexed: 12/21/2022] Open
Abstract
Autistic traits represent a continuum dimension across the population, with autism spectrum disorder (ASD) being the extreme end of the distribution. Accumulating evidence shows that neuroanatomical and neurofunctional profiles described in relatives of ASD individuals reflect an intermediate neurobiological pattern between the clinical population and healthy controls. This suggests that quantitative measures detecting autistic traits in the general population represent potential candidates for the development of biomarkers identifying early pathophysiological processes associated with ASD. Functional near-infrared spectroscopy (fNIRS) has been extensively employed to investigate neural development and function. In contrast, the potential of fNIRS to define reliable biomarkers of brain activity has been barely explored. Features of non-invasiveness, portability, ease of administration, and low-operating costs make fNIRS a suitable instrument to assess brain function for differential diagnosis, follow-up, analysis of treatment outcomes, and personalized medicine in several neurological conditions. Here, we introduce a novel standardized procedure with high entertaining value to measure hemodynamic responses (HDR) in the occipital cortex of adult subjects and children. We found that the variability of evoked HDR correlates with the autistic traits of children, assessed by the Autism-Spectrum Quotient. Interestingly, HDR amplitude was especially linked to social and communication features, representing the core symptoms of ASD. These findings establish a quick and easy strategy for measuring visually-evoked cortical activity with fNIRS that optimize the compliance of young subjects, setting the background for testing the diagnostic value of fNIRS visual measurements in the ASD clinical population.
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25
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Jasim H, Hamdan F, Shareef H. Visual evoked potential findings and correlation between visual evoked potential and clinical severity in children with autism spectrum disorder. MEDICAL JOURNAL OF BABYLON 2022. [DOI: 10.4103/mjbl.mjbl_88_21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
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26
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Brittenham C, Gordon J, Zemon VM, Siper PM. Objective frequency analysis of transient visual evoked potentials in autistic children. Autism Res 2021; 15:464-480. [PMID: 34908250 DOI: 10.1002/aur.2654] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 12/02/2021] [Accepted: 12/05/2021] [Indexed: 11/06/2022]
Abstract
Visual evoked potentials (VEPs) provide a means to examine neural mechanisms in autism with high temporal resolution. Conventional VEP analysis relies on subjective inspection of a few points (peaks and troughs) in the time-domain waveform. The current study applied power spectral analysis and magnitude-squared coherence (MSC) statistics (frequency-domain measures) to VEPs recorded during 1-minute runs and with a recently developed short-duration technique that allow for objective examination of the responses (Zemon & Gordon, European Journal of Neuroscience, 2018, 48, 1765-1788) from nonautistic and autistic children. Results indicate that, for both groups, early time-domain measures (P60 , N75 , P100 ) are highly correlated with middle- and high-frequency (14-28 and 30-48 Hz, respectively) mechanisms, and late measures are highly correlated with a low-frequency (6-12 Hz) mechanism. One frequency-domain measure (power in the middle-frequency band) is capable of predicting the key amplitude measure (N75 -P100 ) with high accuracy. MSC and power measures were combined to yield separate measures of signal and noise strength to evaluate alternate hypotheses in autism. Linear mixed-effects modeling demonstrated selective differences in early time-domain and middle-to-high frequency-domain measures in autistic children as compared to nonautistic children given both recording techniques, implicating weaker excitatory input to the cortex. Receiver-operating-characteristic curve analysis showed predictive diagnostic accuracy for middle- and high-frequency bands based on MSC. These findings support the value of frequency analysis measures (power spectral analysis and MSC) in the objective examination of neural differences in autism. LAY SUMMARY: Visual evoked potentials (VEPs) are used to assess neural mechanisms. Typically, VEPs are analyzed by subjective examination of time-series waveforms; but here objective techniques were applied to quantify VEP frequency components to investigate neural differences between autistic and nonautistic children. The objective measures demonstrate group differences in brain function that point to weaker excitatory input to the cortex in autism.
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Affiliation(s)
- Chloe Brittenham
- Department of Psychology, The Graduate Center, City University of New York, New York, New York, USA
| | - James Gordon
- Department of Psychology, Hunter College, New York, New York, USA
| | - Vance M Zemon
- Ferkauf Graduate School of Psychology, Yeshiva University, Bronx, New York, USA
| | - Paige M Siper
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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27
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King JL, Parada FJ. Using mobile brain/body imaging to advance research in arts, health, and related therapeutics. Eur J Neurosci 2021; 54:8364-8380. [PMID: 33999462 PMCID: PMC9291922 DOI: 10.1111/ejn.15313] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Revised: 05/03/2021] [Accepted: 05/06/2021] [Indexed: 11/26/2022]
Abstract
The uses of mobile brain/body imaging (MoBI) are expanding and allow for more direct study of the neurophysiological signals associated with behavior in psychotherapeutic encounters. Neuroaesthetics is concerned with the cognitive and neural basis of art appreciation, and scientific correlations are being made in the field that might help to clarify theories claimed in the creative arts therapies. Yet, most neuroaesthetics studies are confined to the laboratory and do not propose a translation for research methods and clinical applications. The creative arts therapies have a long history of clinical success with various patient populations and will benefit from increased scientific explanation to support intervention strategies. Examining the brain dynamics and motor behaviors that are associated with the higher complex processes involved in artistic expression offers MoBI as a promising instrumentation to move forward in linking ideas from neuroaesthetics to the creative arts therapies. Tracking brain dynamics in association with behavioral change allows for more objective and quantitative physiological monitors to evaluate, and together with subjective patient reports provides insight into the psychological mechanisms of change in treatment. We outline a framework that shows how MoBI can be used to study the effectiveness of creative arts therapy interventions motivated by the 4E approach to cognition with a focus on visual art therapy. The article illuminates how a new partnership among the fields of art therapy, neuroscience, and neuroaesthetics might work together within the 4E/MoBI framework in efforts to advance transdisciplinary research for clinical health populations.
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Affiliation(s)
- Juliet L. King
- Department of Art TherapyThe George Washington UniversityWashingtonDCUSA
- Department of NeurologyIndiana University School of MedicineIndianapolisIndianaUSA
| | - Francisco J. Parada
- Centro de Estudios en Neurociencia Humana y Neuropsicología. Facultad de PsicologíaUniversidad Diego PortalesSantiagoChile
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28
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Beker S, Foxe JJ, Venticinque J, Bates J, Ridgeway EM, Schaaf RC, Molholm S. Looking for consistency in an uncertain world: test-retest reliability of neurophysiological and behavioral readouts in autism. J Neurodev Disord 2021; 13:43. [PMID: 34592931 PMCID: PMC8483424 DOI: 10.1186/s11689-021-09383-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Accepted: 07/23/2021] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Autism spectrum disorders (ASD) are associated with altered sensory processing and perception. Scalp recordings of electrical brain activity time-locked to sensory events (event-related potentials; ERPs) provide precise information on the time-course of related altered neural activity, and can be used to model the cortical loci of the underlying neural networks. Establishing the test-retest reliability of these sensory brain responses in ASD is critical to their use as biomarkers of neural dysfunction in this population. METHODS EEG and behavioral data were acquired from 33 children diagnosed with ASD aged 6-9.4 years old, while they performed a child-friendly task at two different time-points, separated by an average of 5.2 months. In two blocked conditions, participants responded to the occurrence of an auditory target that was either preceded or not by repeating visual stimuli. Intraclass correlation coefficients (ICCs) were used to assess test-retest reliability of measures of sensory (auditory and visual) ERPs and performance, for the two experimental conditions. To assess the degree of reliability of the variability of responses within individuals, this analysis was performed on the variance of the measurements, in addition to their means. This yielded a total of 24 measures for which ICCs were calculated. RESULTS The data yielded significant good ICC values for 10 of the 24 measurements. These spanned across behavioral and ERPs data, experimental conditions, and mean as well as variance measures. Measures of the visual evoked responses accounted for a disproportionately large number of the significant ICCs; follow-up analyses suggested that the contribution of a greater number of trials to the visual compared to the auditory ERP partially accounted for this. CONCLUSIONS This analysis reveals that sensory ERPs and related behavior can be highly reliable across multiple measurement time-points in ASD. The data further suggest that the inter-trial and inter-participant variability reported in the ASD literature likely represents replicable individual participant neural processing differences. The stability of these neuronal readouts supports their use as biomarkers in clinical and translational studies on ASD. Given the minimum interval between test/retest sessions across our cohort, we also conclude that for the tested age-range of ~ 6 to 9.4 years, these reliability measures are valid for at least a 3-month interval. Limitations related to EEG task demands and study length in the context of a clinical trial are considered.
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Affiliation(s)
- Shlomit Beker
- The Cognitive Neurophysiology Laboratory, Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY, USA
| | - John J Foxe
- The Cognitive Neurophysiology Laboratory, Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY, USA
- The Cognitive Neurophysiology Laboratory, The Ernest J. Del Monte Institute for Neuroscience, Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA
| | - John Venticinque
- School of Medicine, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Juliana Bates
- The Cognitive Neurophysiology Laboratory, Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Elizabeth M Ridgeway
- The Cognitive Neurophysiology Laboratory, Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Roseann C Schaaf
- Department of Occupational Therapy, Jefferson College of Health Professions Faculty, Farber Institute for Neurosciences Thomas Jefferson University Philadelphia, Philadelphia, USA
| | - Sophie Molholm
- The Cognitive Neurophysiology Laboratory, Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY, USA.
- Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY, USA.
- The Cognitive Neurophysiology Laboratory, The Ernest J. Del Monte Institute for Neuroscience, Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA.
- Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, Bronx, NY, USA.
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29
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Mihaylova MS, Bocheva NB, Totev TT, Staykova SN. Visual Noise Effect on Contour Integration and Gaze Allocation in Autism Spectrum Disorder. Front Neurosci 2021; 15:623663. [PMID: 33633537 PMCID: PMC7900628 DOI: 10.3389/fnins.2021.623663] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Accepted: 01/07/2021] [Indexed: 11/13/2022] Open
Abstract
Contradictory results have been obtained in the studies that compare contour integration abilities in Autism Spectrum Disorders (ASDs) and typically developing individuals. The present study aimed to explore the limiting factors of contour integration ability in ASD and verify the role of the external visual noise by a combination of psychophysical and eye-tracking approaches. To this aim, 24 children and adolescents with ASD and 32 age-matched participants with typical development had to detect the presence of contour embedded among similar Gabor elements in a Yes/No procedure. The results obtained showed that the responses in the group with ASD were not only less accurate but also were significantly slower compared to the control group at all noise levels. The detection performance depended on the group differences in addition to the effect of the intellectual functioning of the participants from both groups. The comparison of the agreement and accuracy of the responses in the double-pass experiment showed that the results of the participants with ASD are more affected by the increase of the external noise. It turned out that the internal noise depends on the level of the added external noise: the difference between the two groups was non-significant at the low external noise and significant at the high external noise. In accordance with the psychophysical results, the eye-tracking data indicated a larger gaze allocation area in the group with autism. These findings may imply higher positional uncertainty in ASD due to the inability to maintain the information of the contour location from previous presentations and interference from noise elements in the contour vicinity. Psychophysical and eye-tracking data suggest lower efficiency in using stimulus information in the ASD group that could be caused by fixation instability and noisy and unstable perceptual template that affects noise filtering.
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Affiliation(s)
- Milena Slavcheva Mihaylova
- Department of Sensory Neurobiology, Institute of Neurobiology, Bulgarian Academy of Sciences, Sofia, Bulgaria
| | - Nadejda Bogdanova Bocheva
- Department of Sensory Neurobiology, Institute of Neurobiology, Bulgarian Academy of Sciences, Sofia, Bulgaria
| | - Tsvetalin Totev Totev
- Department of Sensory Neurobiology, Institute of Neurobiology, Bulgarian Academy of Sciences, Sofia, Bulgaria
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30
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Carmona-Serrano N, Moreno-Guerrero AJ, Marín-Marín JA, López-Belmonte J. Evolution of the Autism Literature and the Influence of Parents: A Scientific Mapping in Web of Science. Brain Sci 2021; 11:74. [PMID: 33429923 PMCID: PMC7827242 DOI: 10.3390/brainsci11010074] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2020] [Revised: 01/04/2021] [Accepted: 01/05/2021] [Indexed: 01/01/2023] Open
Abstract
Parents interventions are relevant to address autism spectrum disorder (ASD). The objective of this study is to analyze the importance and evolution of ASD and its relationship with the parents (ASD-PAR) in the publications indexed in Web of Science. For this, a bibliometric methodology has been used, based on a scientific mapping of the reported documents. We have worked with an analysis unit of 1381 documents. The results show that the beginnings of scientific production date back to 1971. There are two clearly differentiated moments in scientific production. A first moment (1971-2004), where the production volume is low. A second moment (2005-2019), where the volume of production increases considerably. Therefore, it can be said that the subject began to be relevant for the scientific community from 2005 to the present. The keyword match rate between set periods marks a high level of match between periods. It is concluded that the main focus of the research on ASD-PAR is on the stress that is generated in families with children with ASD, in addition to the family problems that the fact that these children also have behavior problems can cause.
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Affiliation(s)
| | | | | | - Jesús López-Belmonte
- Department of Didactics and School Organization, University of Granada, 51001 Ceuta, Spain;
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31
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Carmona-Serrano N, López-Belmonte J, López-Núñez JA, Moreno-Guerrero AJ. Trends in Autism Research in the Field of Education in Web of Science: A Bibliometric Study. Brain Sci 2020; 10:E1018. [PMID: 33371289 PMCID: PMC7767165 DOI: 10.3390/brainsci10121018] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Revised: 12/14/2020] [Accepted: 12/18/2020] [Indexed: 12/16/2022] Open
Abstract
Autism spectrum disorder (ASD) is conceived as a neurodevelopmental disorder. The scientific literature welcomes studies that reflect the possible singularities that people with ASD may present both in their daily lives and at an educational level. The main objective of this study is to analyze the scientific production on the term autism in Web of Science, focused on the educational field, in order to identify the research trends in this field of study. The intention is to offer researchers who study autism in the educational field some clear research directions. A bibliometric-type methodology was developed using the scientific mapping technique. For this purpose, a performance analysis and a co-word analysis were carried out. Work was conducted with an analysis unit of 5512 documents. The results show that the volume of production has been irregular from the beginning to the present. The collection of documents on the subject began to be relevant, in terms of the volume of production, from 2007, and this has persisted to the present. It is concluded that there are two lines of research. The first is the line focused on mothers of children with ASD and the second is the line of research focused on young people with ASD. In addition, since 2012, new lines of research have been generated, focused on the diagnosis and inclusion of these students in educational centers.
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Affiliation(s)
| | - Jesús López-Belmonte
- Department of Didactics and School Organization, University of Granada, 51001 Ceuta, Spain;
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32
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Carmona-Serrano N, López-Belmonte J, Cuesta-Gómez JL, Moreno-Guerrero AJ. Documentary Analysis of the Scientific Literature on Autism and Technology in Web of Science. Brain Sci 2020; 10:E985. [PMID: 33327633 PMCID: PMC7765105 DOI: 10.3390/brainsci10120985] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Revised: 11/29/2020] [Accepted: 12/11/2020] [Indexed: 12/26/2022] Open
Abstract
The objective of the study is to track the progression of the scientific literature on autism and the technology applied to this disorder. A bibliometric methodology has been used, based on a co-word analysis. The Web of Science database was chosen to perform the analysis of the literature. A unit of analysis of 1048 publications was configured. SciMAT software was used mainly for document analysis. The results indicate that the first studies appeared in 1992, but it was not until 2009 that the research volume increased considerably. The area of knowledge where these studies were compiled was rehabilitation, which marks the truly therapeutic nature of this type of study. One of the authors with the most studies, as well as the most relevant research, was Sarkar, N. Manuscripts were usually research articles written in English. It could be concluded that research in this field of study focused mainly on interventions carried out through the use of technological resources, with students or young people who present with ASD. This line of research, although not the only one, was the most relevant and the one that had aroused the most interest among the scientific community.
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Affiliation(s)
| | - Jesús López-Belmonte
- Department of Didactics and School Organization, University of Granada, 51001 Ceuta, Spain;
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Kovarski K, Caetta F, Mermillod M, Peyrin C, Perez C, Granjon L, Delorme R, Cartigny A, Zalla T, Chokron S. Emotional face recognition in autism and in cerebral visual impairments: In search for specificity. J Neuropsychol 2020; 15:235-252. [PMID: 32920927 DOI: 10.1111/jnp.12221] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Revised: 07/15/2020] [Indexed: 12/16/2022]
Abstract
Autism spectrum disorder (ASD) is characterized by difficulties in the social domain, but also by hyper- and hypo-reactivity. Atypical visual behaviours and processing have often been observed. Nevertheless, several similar signs are also identified in other clinical conditions including cerebral visual impairments (CVI). In the present study, we investigated emotional face categorization in groups of children with ASD and CVI by comparing each group to typically developing individuals (TD) in two tasks. Stimuli were either non-filtered or filtered by low- and high-spatial frequencies (LSF and HSF). All participants completed the autism spectrum quotient score (AQ) and a complete neurovisual evaluation. The results show that while both clinical groups presented difficulties in the emotional face recognition tasks and atypical processing of filtered stimuli, they did not differ from one another. Additionally, autistic traits were observed in the CVI group and symmetrically, some visual disturbances were present in the ASD group as measured via the AQ score and a neurovisual evaluation, respectively. The present study suggests the relevance of comparing ASD to CVI by showing that emotional face categorization difficulties should not be solely considered as autism-specific but merit investigation for potential dysfunction of the visual processing neural network. These results are of interest in both clinical and research perspectives, indicating that systematic visual examination is warranted for individuals with ASD.
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Affiliation(s)
- Klara Kovarski
- Institut de Neuropsychologie, Neurovision et Neurocognition, Hôpital Fondation Rothschild, Paris, France.,Université de Paris, CNRS, Integrative Neuroscience and Cognition Center, Paris, France, Paris, France
| | - Florent Caetta
- Institut de Neuropsychologie, Neurovision et Neurocognition, Hôpital Fondation Rothschild, Paris, France
| | - Martial Mermillod
- Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LPNC, Grenoble, France
| | - Carole Peyrin
- Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LPNC, Grenoble, France
| | - Céline Perez
- Institut de Neuropsychologie, Neurovision et Neurocognition, Hôpital Fondation Rothschild, Paris, France
| | - Lionel Granjon
- Université de Paris, CNRS, Integrative Neuroscience and Cognition Center, Paris, France, Paris, France
| | - Richard Delorme
- Department of Child and Adolescent Psychiatry, Assistance Publique-Hôpitaux de Paris, Robert Debré Hospital, Paris, France
| | - Ariane Cartigny
- Institut de Neuropsychologie, Neurovision et Neurocognition, Hôpital Fondation Rothschild, Paris, France.,Université de Paris, CNRS, Integrative Neuroscience and Cognition Center, Paris, France, Paris, France
| | - Tiziana Zalla
- Institut Jean Nicod, CNRS, Ecole Normale Supérieure, Paris, France
| | - Sylvie Chokron
- Institut de Neuropsychologie, Neurovision et Neurocognition, Hôpital Fondation Rothschild, Paris, France.,Université de Paris, CNRS, Integrative Neuroscience and Cognition Center, Paris, France, Paris, France
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ReSync: Correcting the trial-to-trial asynchrony of event-related brain potentials to improve neural response representation. J Neurosci Methods 2020; 339:108722. [PMID: 32278859 DOI: 10.1016/j.jneumeth.2020.108722] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Revised: 04/01/2020] [Accepted: 04/02/2020] [Indexed: 11/22/2022]
Abstract
BACKGROUND For various reasons, the brain response activities in electroencephalography (EEG) signals are not perfectly synchronized between trials with respect to event markers-a problem commonly referred to as latency jitter. Experimental technologies have been greatly advanced to reduce technical timing errors and thereby reduce jitter. However, there remain intrinsic sources of jitter that are difficult to remove. The problem becomes more complicated when multiple sub-components possess different degrees and features of jitter. The jitter issue renders trial-averaged ERP inaccurate and even misleading. Effective methods for correcting ERP distortion due to latency jitter are needed. NEW METHOD This study developed a simple and easy-to-use method and toolbox for correcting ERP jitter based on simple signal processing theories, named ReSync. ReSync can be used to correct multiple overlapping ERP sub-components with different degrees of jitter (including static sub-components) without their affecting each other. RESULTS The theories, principles, technical details, and limitations of ReSync are presented in this paper, along with a series of simulation and real data examples used to evaluate and validate the method. COMPARISON WITH EXISTING METHODS ReSync was conceptually compared with previous methods in the literature that are related to tackling of the jitter issue from theoretical, methodological, and technical perspectives. CONCLUSIONS Providing a novel approach to latency jitter estimation with automatic dominant frequency identification and integrated decomposition and reconstruction, the ReSync method was validated using both simulation and empirical data, and demonstrated to be an effective jitter-correction approach with implementational simplicity.
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