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Öztürk D, Aydoğan S, Kök İ, Akın Bülbül I, Özdemir S, Özdemir S, Akay D. Linguistic summarization of visual attention and developmental functioning of young children with autism spectrum disorder. Health Inf Sci Syst 2024; 12:39. [PMID: 39022602 PMCID: PMC11252111 DOI: 10.1007/s13755-024-00297-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Accepted: 07/06/2024] [Indexed: 07/20/2024] Open
Abstract
Diagnosing autism spectrum disorder (ASD) in children poses significant challenges due to its complex nature and impact on social communication development. While numerous data analytics techniques have been proposed for ASD evaluation, the process remains time-consuming and lacks clarity. Eye tracking (ET) data has emerged as a valuable resource for ASD risk assessment, yet existing literature predominantly focuses on predictive methods rather than descriptive techniques that offer human-friendly insights. Interpretation of ET data and Bayley scales, a widely used assessment tool, is challenging for ASD assessment of children. It should be understood clearly to perform better analytic tasks on ASD screening. Therefore, this study addresses this gap by employing linguistic summarization techniques to generate easily understandable summaries from raw ET data and Bayley scales. By integrating ET data and Bayley scores, the study aims to improve the identification of children with ASD from typically developing children (TD). Notably, this research represents one of the pioneering efforts to linguistically summarize ET data alongside Bayley scales, presenting comparative results between children with ASD and TD. Through linguistic summarization, this study facilitates the creation of simple, natural language statements, offering a first and unique approach to enhance ASD screening and contribute to our understanding of neurodevelopmental disorders.
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Affiliation(s)
- Demet Öztürk
- Department of Industrial Engineering, Gazi University, Ankara, Turkey
| | - Sena Aydoğan
- Department of Industrial Engineering, Gazi University, Ankara, Turkey
| | - İbrahim Kök
- Department of Computer Engineering, Pamukkale University, Denizli, Turkey
| | - Işık Akın Bülbül
- Department of Special Education, Gazi University, Ankara, Turkey
| | - Selda Özdemir
- Department of Special Education, Hacettepe University, Ankara, Turkey
| | - Suat Özdemir
- Department of Computer Engineering, Hacettepe University, Ankara, Turkey
| | - Diyar Akay
- Department of Industrial Engineering, Hacettepe University, Ankara, Turkey
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2
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Xie X, Zhou R, Fang Z, Zhang Y, Wang Q, Liu X. Seeing beyond words: Visualizing autism spectrum disorder biomarker insights. Heliyon 2024; 10:e30420. [PMID: 38694128 PMCID: PMC11061761 DOI: 10.1016/j.heliyon.2024.e30420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Revised: 04/24/2024] [Accepted: 04/25/2024] [Indexed: 05/04/2024] Open
Abstract
Objective This study employs bibliometric and visual analysis to elucidate global research trends in Autism Spectrum Disorder (ASD) biomarkers, identify critical research focal points, and discuss the potential integration of diverse biomarker modalities for precise ASD assessment. Methods A comprehensive bibliometric analysis was conducted using data from the Web of Science Core Collection database until December 31, 2022. Visualization tools, including R, VOSviewer, CiteSpace, and gCLUTO, were utilized to examine collaborative networks, co-citation patterns, and keyword associations among countries, institutions, authors, journals, documents, and keywords. Results ASD biomarker research emerged in 2004, accumulating a corpus of 4348 documents by December 31, 2022. The United States, with 1574 publications and an H-index of 213, emerged as the most prolific and influential country. The University of California, Davis, contributed significantly with 346 publications and an H-index of 69, making it the leading institution. Concerning journals, the Journal of Autism and Developmental Disorders, Autism Research, and PLOS ONE were the top three publishers of ASD biomarker-related articles among a total of 1140 academic journals. Co-citation and keyword analyses revealed research hotspots in genetics, imaging, oxidative stress, neuroinflammation, gut microbiota, and eye tracking. Emerging topics included "DNA methylation," "eye tracking," "metabolomics," and "resting-state fMRI." Conclusion The field of ASD biomarker research is dynamically evolving. Future endeavors should prioritize individual stratification, methodological standardization, the harmonious integration of biomarker modalities, and longitudinal studies to advance the precision of ASD diagnosis and treatment.
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Affiliation(s)
- Xinyue Xie
- The First Affiliated Hospital of Henan University of Chinese Medicine, Pediatrics Hospital, Zhengzhou, Henan, 450000, China
- Henan University of Chinese Medicine, School of Pediatrics, Zhengzhou, Henan, 450046, China
| | - Rongyi Zhou
- The First Affiliated Hospital of Henan University of Chinese Medicine, Pediatrics Hospital, Zhengzhou, Henan, 450000, China
- Henan University of Chinese Medicine, School of Pediatrics, Zhengzhou, Henan, 450046, China
| | - Zihan Fang
- Henan University of Chinese Medicine, School of Pediatrics, Zhengzhou, Henan, 450046, China
| | - Yongting Zhang
- The First Affiliated Hospital of Henan University of Chinese Medicine, Pediatrics Hospital, Zhengzhou, Henan, 450000, China
- Henan University of Chinese Medicine, School of Pediatrics, Zhengzhou, Henan, 450046, China
| | - Qirong Wang
- Henan University of Chinese Medicine, School of Pediatrics, Zhengzhou, Henan, 450046, China
| | - Xiaomian Liu
- Henan University of Chinese Medicine, School of Medicine, Zhengzhou, Henan, 450046, China
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3
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Kulke L. Coregistration of EEG and eye-tracking in infants and developing populations. Atten Percept Psychophys 2024:10.3758/s13414-024-02857-y. [PMID: 38388851 DOI: 10.3758/s13414-024-02857-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/06/2024] [Indexed: 02/24/2024]
Abstract
Infants cannot be instructed where to look; therefore, infant researchers rely on observation of their participant's gaze to make inferences about their cognitive processes. They therefore started studying infant attention in the real world from early on. Developmental researchers were early adopters of methods combining observations of gaze and behaviour with electroencephalography (EEG) to study attention and other cognitive functions. However, the direct combination of eye-tracking methods and EEG to test infants is still rare, as it includes specific challenges. The current article reviews the development of co-registration research in infancy. It points out specific challenges of co-registration in infant research and suggests ways to overcome them. It ends with recommendations for implementing the co-registration of EEG and eye-tracking in infant research to maximise the benefits of the two measures and their combination and to orient on Open Science principles while doing so. In summary, this work shows that the co-registration of EEG and eye-tracking in infant research can be beneficial to studying natural and real-world behaviour despite its challenges.
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Affiliation(s)
- Louisa Kulke
- Department of Developmental Psychology with Educational Psychology, University of Bremen, Hochschulring 18, 28359, Bremen, Germany.
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4
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Giari G, Vignali L, Xu Y, Bottini R. MEG frequency tagging reveals a grid-like code during attentional movements. Cell Rep 2023; 42:113209. [PMID: 37804506 DOI: 10.1016/j.celrep.2023.113209] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 08/25/2023] [Accepted: 09/18/2023] [Indexed: 10/09/2023] Open
Abstract
Grid-cells firing fields tile the environment with a 6-fold periodicity during both locomotion and visual exploration. Here, we tested, in humans, whether movements of covert attention elicit grid-like coding using frequency tagging. Participants observed visual trajectories presented sequentially at fixed rate, allowing different spatial periodicities (e.g., 4-, 6-, and 8-fold) to have corresponding temporal periodicities (e.g., 1, 1.5, and 2 Hz), thus resulting in distinct spectral responses. We found a higher response for the (grid-like) 6-fold periodicity and localized this effect in medial-temporal sources. In a control experiment featuring the same temporal periodicity but lacking spatial structure, the 6-fold effect did not emerge, suggesting its dependency on spatial movements of attention. We report evidence that grid-like signals in the human medial-temporal lobe can be elicited by covert attentional movements and suggest that attentional coding may provide a suitable mechanism to support the activation of cognitive maps during conceptual navigation.
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Affiliation(s)
- Giuliano Giari
- Center for Mind/Brain Sciences (CIMeC), University of Trento, 38123 Trento, Italy.
| | - Lorenzo Vignali
- Center for Mind/Brain Sciences (CIMeC), University of Trento, 38123 Trento, Italy
| | - Yangwen Xu
- Center for Mind/Brain Sciences (CIMeC), University of Trento, 38123 Trento, Italy
| | - Roberto Bottini
- Center for Mind/Brain Sciences (CIMeC), University of Trento, 38123 Trento, Italy.
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5
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Sun B, Wang B, Wei Z, Feng Z, Wu ZL, Yassin W, Stone WS, Lin Y, Kong XJ. Identification of diagnostic markers for ASD: a restrictive interest analysis based on EEG combined with eye tracking. Front Neurosci 2023; 17:1236637. [PMID: 37886678 PMCID: PMC10598595 DOI: 10.3389/fnins.2023.1236637] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 09/12/2023] [Indexed: 10/28/2023] Open
Abstract
Electroencephalography (EEG) functional connectivity (EFC) and eye tracking (ET) have been explored as objective screening methods for autism spectrum disorder (ASD), but no study has yet evaluated restricted and repetitive behavior (RRBs) simultaneously to infer early ASD diagnosis. Typically developing (TD) children (n = 27) and ASD (n = 32), age- and sex-matched, were evaluated with EFC and ET simultaneously, using the restricted interest stimulus paradigm. Network-based machine learning prediction (NBS-predict) was used to identify ASD. Correlations between EFC, ET, and Autism Diagnostic Observation Schedule-Second Edition (ADOS-2) were performed. The Area Under the Curve (AUC) of receiver-operating characteristics (ROC) was measured to evaluate the predictive performance. Under high restrictive interest stimuli (HRIS), ASD children have significantly higher α band connectivity and significantly more total fixation time (TFT)/pupil enlargement of ET relative to TD children (p = 0.04299). These biomarkers were not only significantly positively correlated with each other (R = 0.716, p = 8.26e-4), but also with ADOS total scores (R = 0.749, p = 34e-4) and RRBs sub-score (R = 0.770, p = 1.87e-4) for EFC (R = 0.641, p = 0.0148) for TFT. The accuracy of NBS-predict in identifying ASD was 63.4%. ROC curve demonstrated TFT with 91 and 90% sensitivity, and 78.7% and 77.4% specificity for ADOS total and RRB sub-scores, respectively. Simultaneous EFC and ET evaluation in ASD is highly correlated with RRB symptoms measured by ADOS-2. NBS-predict of EFC offered a direct prediction of ASD. The use of both EFC and ET improve early ASD diagnosis.
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Affiliation(s)
- Binbin Sun
- Shenzhen Maternity and Child Healthcare Hospital, Southern Medical University, Shenzhen, China
| | - Bryan Wang
- Martinos Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
- Department of English and Creative Writing, Brandeis University, Waltham, MA, United States
| | - Zhen Wei
- Shenzhen Maternity and Child Healthcare Hospital, Southern Medical University, Shenzhen, China
| | - Zhe Feng
- Shenzhen Maternity and Child Healthcare Hospital, Southern Medical University, Shenzhen, China
| | - Zhi-Liu Wu
- Shenzhen Maternity and Child Healthcare Hospital, Southern Medical University, Shenzhen, China
| | - Walid Yassin
- Martinos Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
- McLean Hospital, Harvard Medical School, Belmont, MA, United States
- Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States
| | - William S. Stone
- Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States
| | - Yan Lin
- Shenzhen Maternity and Child Healthcare Hospital, Southern Medical University, Shenzhen, China
| | - Xue-Jun Kong
- Martinos Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
- Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States
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6
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Dimmock S, O'Donnell C, Houghton C. Bayesian analysis of phase data in EEG and MEG. eLife 2023; 12:e84602. [PMID: 37698464 PMCID: PMC10588985 DOI: 10.7554/elife.84602] [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: 10/31/2022] [Accepted: 09/11/2023] [Indexed: 09/13/2023] Open
Abstract
Electroencephalography and magnetoencephalography recordings are non-invasive and temporally precise, making them invaluable tools in the investigation of neural responses in humans. However, these recordings are noisy, both because the neuronal electrodynamics involved produces a muffled signal and because the neuronal processes of interest compete with numerous other processes, from blinking to day-dreaming. One fruitful response to this noisiness has been to use stimuli with a specific frequency and to look for the signal of interest in the response at that frequency. Typically this signal involves measuring the coherence of response phase: here, a Bayesian approach to measuring phase coherence is described. This Bayesian approach is illustrated using two examples from neurolinguistics and its properties are explored using simulated data. We suggest that the Bayesian approach is more descriptive than traditional statistical approaches because it provides an explicit, interpretable generative model of how the data arises. It is also more data-efficient: it detects stimulus-related differences for smaller participant numbers than the standard approach.
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Affiliation(s)
- Sydney Dimmock
- Faculty of Engineering, University of BristolBristolUnited Kingdom
| | - Cian O'Donnell
- Faculty of Engineering, University of BristolBristolUnited Kingdom
- School of Computing, Engineering & Intelligent Systems, Ulster UniversityDerry/LondonderryUnited Kingdom
| | - Conor Houghton
- Faculty of Engineering, University of BristolBristolUnited Kingdom
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7
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Oomen D, Cracco E, Brass M, Wiersema JR. EEG frequency tagging evidence of intact social interaction recognition in adults with autism. Autism Res 2023. [PMID: 37040541 DOI: 10.1002/aur.2929] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Accepted: 03/10/2023] [Indexed: 04/13/2023]
Abstract
To explain the social difficulties in autism, many studies have been conducted on social stimuli processing. However, this research has mostly used basic social stimuli (e.g., eyes, faces, hands, single agent), not resembling the complexity of what we encounter in our daily social lives and what people with autism experience difficulties with. Third-party social interactions are complex stimuli that we come across often and are also highly relevant for social functioning. Interestingly, the existing behavioral studies point to altered social interaction processing in autism. However, it is not clear whether this is due to altered recognition or altered interpretation of social interactions. Here, we specifically investigated the recognition of social interaction in adults with and without autism. More precisely, we measured neural responses to social scenes depicting either social interaction or not with an electroencephalogram frequency tagging task and compared these responses between adults with and without autism (N = 61). The results revealed an enhanced response to social scenes with interaction, replicating previous findings in a neurotypical sample. Crucially, this effect was found in both groups, with no difference between them. This suggests that social interaction recognition is not atypical in adults with autism. Taken together with the previous behavioral evidence, our study thus suggests that individuals with autism are able to recognize social interactions, but that they might not extract the same information from those interactions or that they might use the extracted information differently.
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Affiliation(s)
- Danna Oomen
- Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium
- EXPLORA, Ghent University, Ghent, Belgium
| | - Emiel Cracco
- Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium
- EXPLORA, Ghent University, Ghent, Belgium
| | - Marcel Brass
- EXPLORA, Ghent University, Ghent, Belgium
- Department of Experimental Psychology, Ghent University, Ghent, Belgium
- School of Mind and Brain/Department of Psychology, Humboldt Universität zu Berlin, Berlin, Germany
| | - Jan R Wiersema
- Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium
- EXPLORA, Ghent University, Ghent, Belgium
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8
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Zhang S, Chen D, Tang Y, Li X. Learning graph-based relationship of dual-modal features towards subject adaptive ASD assessment. Neurocomputing 2023. [DOI: 10.1016/j.neucom.2022.10.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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9
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Ding N, Zhong Y, Li J, Xiao Q, Zhang S, Xia H. Visual preference of plant features in different living environments using eye tracking and EEG. PLoS One 2022; 17:e0279596. [PMID: 36584138 PMCID: PMC9803246 DOI: 10.1371/journal.pone.0279596] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2021] [Accepted: 12/12/2022] [Indexed: 12/31/2022] Open
Abstract
Plants play a very important role in landscape construction. In order to explore whether different living environment will affect people's preference for the structural features of plant organs, this study examined 26 villagers and 33 college students as the participants, and pictures of leaves, flowers and fruits of plants as the stimulus to conduct eye-tracking and EEG detection experiments. We found that eye movement indicators can explain people's visual preferences, but they are unable to find differences in preferences between groups. EEG indicators can make up for this deficiency, which further reveals the difference in psychological and physiological responses between the two groups when viewing stimuli. The final results show that the villagers and the students liked leaves best, preferring aciculiform and leathery leaves; solitary, purple and capitulum flowers; and medium-sized, spathulate, black and pear fruits. In addition, it was found that the overall attention of the villagers when watching stimuli was far lower than that of the students, but the degree of meditation was higher. With regard to eye movement and EEG, the total duration of fixations is highly positively correlated with the number of fixations, and the average pupil size has a weak negative correlation with attention. On the contrary, the average duration of fixations has a weak positive correlation with meditation. Generally speaking, we believe that Photinia×fraseri, Metasequoia glyptostroboides, Photinia serratifolia, Koelreuteria bipinnata and Cunninghamia lanceolata are superior landscape building plants in rural areas and on campuses; Pinus thunbergii, Myrica rubra, Camellia japonica and other plants with obvious features and bright colours are also the first choice in rural landscapes; and Yulania biondii, Cercis chinensis, Hibiscus mutabilis and other plants with simple structures are the first choice in campus landscapes. This study is of great significance for selecting plants for landscape construction and management according to different environments and local conditions.
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Affiliation(s)
- Ningning Ding
- Central South University of Forestry and Technology, Changsha, China
| | - Yongde Zhong
- Central South University of Forestry and Technology, Changsha, China,National Forestry and Grassland Administration State Forestry Administration Engineering Research Center for Forest Tourism, Changsha, China,* E-mail:
| | - Jiaxiang Li
- Central South University of Forestry and Technology, Changsha, China
| | - Qiong Xiao
- Central South University of Forestry and Technology, Changsha, China
| | - Shuangquan Zhang
- Central South University of Forestry and Technology, Changsha, China
| | - Hongling Xia
- Hunan Urban Construction College, Xiangtan, China
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10
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Qiao Z, Van der Donck S, Moerkerke M, Dlhosova T, Vettori S, Dzhelyova M, van Winkel R, Alaerts K, Boets B. Frequency-Tagging EEG of Superimposed Social and Non-Social Visual Stimulation Streams Provides No Support for Social Salience Enhancement after Intranasal Oxytocin Administration. Brain Sci 2022; 12:brainsci12091224. [PMID: 36138960 PMCID: PMC9496939 DOI: 10.3390/brainsci12091224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Revised: 08/31/2022] [Accepted: 09/06/2022] [Indexed: 11/16/2022] Open
Abstract
The social salience hypothesis proposes that the neuropeptide oxytocin (OT) can impact human social behavior by modulating the salience of social cues. Here, frequency-tagging EEG was used to quantify the neural responses to social versus non-social stimuli while administering a single dose of OT (24 IU) versus placebo treatment. Specifically, two streams of faces and houses were superimposed on one another, with each stream of stimuli tagged with a particular presentation rate (i.e., 6 and 7.5 Hz or vice versa). These distinctive frequency tags allowed unambiguously disentangling and objectively quantifying the respective neural responses elicited by the different streams of stimuli. This study involved a double-blind, placebo-controlled, cross-over trial with 31 healthy adult men. Based on four trials of 60 s, we detected robust frequency-tagged neural responses in each individual, with entrainment to faces being more pronounced in lateral occipito-temporal regions and entrainment to houses being focused in medial occipital regions. However, contrary to our expectation, a single dose of OT did not modulate these stimulus-driven neural responses, not in terms of enhanced social processing nor in terms of generally enhanced information salience. Bayesian analyses formally confirmed these null findings. Possibly, the baseline ceiling level performance of these neurotypical adult participants as well as the personal irrelevance of the applied stimulation streams might have hindered the observation of any OT effect.
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Affiliation(s)
- Zhiling Qiao
- Center for Clinical Psychiatry, Department of Neuroscience, KU Leuven, 3000 Leuven, Belgium
- Correspondence:
| | - Stephanie Van der Donck
- Center for Developmental Psychiatry, Department of Neurosciences, KU Leuven, 3000 Leuven, Belgium
- Leuven Autism Research (LAuRes), KU Leuven, 3000 Leuven, Belgium
| | - Matthijs Moerkerke
- Center for Developmental Psychiatry, Department of Neurosciences, KU Leuven, 3000 Leuven, Belgium
- Leuven Autism Research (LAuRes), KU Leuven, 3000 Leuven, Belgium
| | - Tereza Dlhosova
- Department of Psychology, Faculty of Arts, Masaryk University, 60200 Brno, Czech Republic
| | - Sofie Vettori
- Center for Developmental Psychiatry, Department of Neurosciences, KU Leuven, 3000 Leuven, Belgium
- Leuven Autism Research (LAuRes), KU Leuven, 3000 Leuven, Belgium
- Institute of Cognitive Sciences Marc Jeannerod, UMR5229, CNRS, University Claude Bernard Lyon1, 69675 Bron, France
| | - Milena Dzhelyova
- Institute of Research in Psychological Sciences, Université de Louvain, 1348 Louvain-la-Neuve, Belgium
| | - Ruud van Winkel
- Center for Clinical Psychiatry, Department of Neuroscience, KU Leuven, 3000 Leuven, Belgium
- UPC, KU Leuven, 3000 Leuven, Belgium
- Department of Psychiatry and Psychology, School for Mental Health and Neuroscience, Maastricht University, 6211 Maastricht, The Netherlands
| | - Kaat Alaerts
- Leuven Autism Research (LAuRes), KU Leuven, 3000 Leuven, Belgium
- Research Group for Neurorehabilitation, Department of Rehabilitation Sciences, KU Leuven, 3000 Leuven, Belgium
| | - Bart Boets
- Center for Developmental Psychiatry, Department of Neurosciences, KU Leuven, 3000 Leuven, Belgium
- Leuven Autism Research (LAuRes), KU Leuven, 3000 Leuven, Belgium
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11
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Garcés P, Baumeister S, Mason L, Chatham CH, Holiga S, Dukart J, Jones EJH, Banaschewski T, Baron-Cohen S, Bölte S, Buitelaar JK, Durston S, Oranje B, Persico AM, Beckmann CF, Bougeron T, Dell'Acqua F, Ecker C, Moessnang C, Charman T, Tillmann J, Murphy DGM, Johnson M, Loth E, Brandeis D, Hipp JF. Resting state EEG power spectrum and functional connectivity in autism: a cross-sectional analysis. Mol Autism 2022; 13:22. [PMID: 35585637 PMCID: PMC9118870 DOI: 10.1186/s13229-022-00500-x] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 05/06/2022] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND Understanding the development of the neuronal circuitry underlying autism spectrum disorder (ASD) is critical to shed light into its etiology and for the development of treatment options. Resting state EEG provides a window into spontaneous local and long-range neuronal synchronization and has been investigated in many ASD studies, but results are inconsistent. Unbiased investigation in large and comprehensive samples focusing on replicability is needed. METHODS We quantified resting state EEG alpha peak metrics, power spectrum (PS, 2-32 Hz) and functional connectivity (FC) in 411 children, adolescents and adults (n = 212 ASD, n = 199 neurotypicals [NT], all with IQ > 75). We performed analyses in source-space using individual head models derived from the participants' MRIs. We tested for differences in mean and variance between the ASD and NT groups for both PS and FC using linear mixed effects models accounting for age, sex, IQ and site effects. Then, we used machine learning to assess whether a multivariate combination of EEG features could better separate ASD and NT participants. All analyses were embedded within a train-validation approach (70%-30% split). RESULTS In the training dataset, we found an interaction between age and group for the reactivity to eye opening (p = .042 uncorrected), and a significant but weak multivariate ASD vs. NT classification performance for PS and FC (sensitivity 0.52-0.62, specificity 0.59-0.73). None of these findings replicated significantly in the validation dataset, although the effect size in the validation dataset overlapped with the prediction interval from the training dataset. LIMITATIONS The statistical power to detect weak effects-of the magnitude of those found in the training dataset-in the validation dataset is small, and we cannot fully conclude on the reproducibility of the training dataset's effects. CONCLUSIONS This suggests that PS and FC values in ASD and NT have a strong overlap, and that differences between both groups (in both mean and variance) have, at best, a small effect size. Larger studies would be needed to investigate and replicate such potential effects.
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Affiliation(s)
- Pilar Garcés
- Roche Pharma Research and Early Development, Neuroscience and Rare Diseases, Roche Innovation Center Basel, Basel, Switzerland.
| | - Sarah Baumeister
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Luke Mason
- Department of Psychological Sciences, Centre for Brain and Cognitive Development, Birkbeck, University of London, London, UK
| | - Christopher H Chatham
- Roche Pharma Research and Early Development, Neuroscience and Rare Diseases, Roche Innovation Center Basel, Basel, Switzerland
| | - Stefan Holiga
- Roche Pharma Research and Early Development, Neuroscience and Rare Diseases, Roche Innovation Center Basel, Basel, Switzerland
| | - Juergen Dukart
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.,Medical Faculty, Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Emily J H Jones
- Department of Psychological Sciences, Centre for Brain and Cognitive Development, Birkbeck, University of London, London, UK
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Simon Baron-Cohen
- Department of Psychiatry, Autism Research Centre, University of Cambridge, Cambridge, UK
| | - Sven Bölte
- Department of Women's and Children's Health, Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Karolinska Institutet and Child and Adolescent Psychiatry, Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden.,Curtin Autism Research Group, Curtin School of Allied Health, Curtin University, Perth, WA, Australia
| | - Jan K Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboudumc, Nijmegen, The Netherlands
| | - Sarah Durston
- Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Bob Oranje
- Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Antonio M Persico
- Interdepartmental Program "Autism 0-90", "G. Martino" University Hospital, University of Messina, Messina, Italy
| | - Christian F Beckmann
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboudumc, Nijmegen, The Netherlands
| | - Thomas Bougeron
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, Université de Paris, Paris, France
| | - Flavio Dell'Acqua
- Institute of Psychiatry, Psychology and Neuroscience, King's College, London, UK
| | - Christine Ecker
- Institute of Psychiatry, Psychology and Neuroscience, King's College, London, UK.,Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital, Goethe University, Frankfurt am Main, Germany
| | - Carolin Moessnang
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Tony Charman
- Institute of Psychiatry, Psychology and Neuroscience, King's College, London, UK
| | - Julian Tillmann
- Roche Pharma Research and Early Development, Neuroscience and Rare Diseases, Roche Innovation Center Basel, Basel, Switzerland
| | - Declan G M Murphy
- Institute of Psychiatry, Psychology and Neuroscience, King's College, London, UK
| | - Mark Johnson
- Department of Psychological Sciences, Centre for Brain and Cognitive Development, Birkbeck, University of London, London, UK
| | - Eva Loth
- Institute of Psychiatry, Psychology and Neuroscience, King's College, London, UK
| | - Daniel Brandeis
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.,Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zurich, Zurich, Switzerland.,Neuroscience Center Zurich, University and ETH Zurich, Zurich, Switzerland
| | - Joerg F Hipp
- Roche Pharma Research and Early Development, Neuroscience and Rare Diseases, Roche Innovation Center Basel, Basel, Switzerland
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12
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Marotta A, Aranda-Martín B, De Cono M, Ballesteros-Duperón MÁ, Casagrande M, Lupiáñez J. Integration of Facial Expression and Gaze Direction in Individuals with a High Level of Autistic Traits. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:2798. [PMID: 35270490 PMCID: PMC8910540 DOI: 10.3390/ijerph19052798] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 02/18/2022] [Accepted: 02/19/2022] [Indexed: 12/10/2022]
Abstract
BACKGROUND We investigated whether individuals with high levels of autistic traits integrate relevant communicative signals, such as facial expression, when decoding eye-gaze direction. METHODS Students with high vs. low scores on the Autism Spectrum Quotient (AQ) performed a task in which they responded to the eye directions of faces, presented on the left or the right side of a screen, portraying different emotional expressions. RESULTS In both groups, the identification of gaze direction was faster when the eyes were directed towards the center of the scene. However, in the low AQ group, this effect was larger for happy faces than for neutral faces or faces showing other emotional expressions, whereas participants from high AQ group were not affected by emotional expressions. CONCLUSIONS These results suggest that individuals with more autistic traits may not integrate multiple communicative signals based on their emotional value.
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Affiliation(s)
- Andrea Marotta
- Department of Experimental Psychology and Mind, Brain and Behavior Research Center (CIMCYC), University of Granada, 18071 Granada, Spain;
| | - Belén Aranda-Martín
- Department of Experimental Psychology and Mind, Brain and Behavior Research Center (CIMCYC), University of Granada, 18071 Granada, Spain;
| | - Marco De Cono
- Department of Psychobiology and Mind, Brain and Behavior Research Center (CIMCYC), University of Granada, 18071 Granada, Spain; (M.D.C.); (M.Á.B.-D.)
| | - María Ángeles Ballesteros-Duperón
- Department of Psychobiology and Mind, Brain and Behavior Research Center (CIMCYC), University of Granada, 18071 Granada, Spain; (M.D.C.); (M.Á.B.-D.)
| | - Maria Casagrande
- Dipartimento di Psicologia Dinamica e Clinica, Sapienza Università di Roma, 00185 Rome, Italy;
| | - Juan Lupiáñez
- Department of Experimental Psychology and Mind, Brain and Behavior Research Center (CIMCYC), University of Granada, 18071 Granada, Spain;
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13
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Figueira JSB, Kutlu E, Scott LS, Keil A. The FreqTag toolbox: A principled approach to analyzing electrophysiological time series in frequency tagging paradigms. Dev Cogn Neurosci 2022; 54:101066. [PMID: 35184025 PMCID: PMC8861396 DOI: 10.1016/j.dcn.2022.101066] [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: 05/31/2021] [Revised: 10/13/2021] [Accepted: 01/13/2022] [Indexed: 11/25/2022] Open
Abstract
Steady-state visual evoked potential (ssVEP) frequency tagging is an increasingly used method in electrophysiological studies of visual attention and perception. Frequency tagging is suitable for studies examining a wide range of populations, including infants and children. Frequency tagging involves the presentation of different elements of a visual array at different temporal rates, thus using stimulus timing to “tag” the brain response to a given element by means of a unique time signature. Leveraging the strength of the ssVEP frequency tagging method to isolate brain responses to concurrently presented and spatially overlapping visual objects requires specific signal processing methods. Here, we introduce the FreqTag suite of functions, an open source MATLAB toolbox. The purpose of the FreqTag toolbox is three-fold. First, it will equip users with a set of transparent and reproducible analytical tools for the analysis of ssVEP data. Second, the toolbox is designed to illustrate fundamental features of frequency domain and time-frequency domain approaches. Finally, decision criteria for the application of different functions and analyses are described. To promote reproducibility, raw algorithms are provided in a modular fashion, without additional hidden functions or transformations. This approach is intended to facilitate a fundamental understanding of the transformations and algorithmic steps in FreqTag, and to allow users to visualize and test each step in the toolbox.
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14
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Alcañiz M, Chicchi-Giglioli IA, Carrasco-Ribelles LA, Marín-Morales J, Minissi ME, Teruel-García G, Sirera M, Abad L. Eye gaze as a biomarker in the recognition of autism spectrum disorder using virtual reality and machine learning: A proof of concept for diagnosis. Autism Res 2021; 15:131-145. [PMID: 34811930 DOI: 10.1002/aur.2636] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Revised: 10/13/2021] [Accepted: 10/28/2021] [Indexed: 12/11/2022]
Abstract
The core symptoms of autism spectrum disorder (ASD) mainly relate to social communication and interactions. ASD assessment involves expert observations in neutral settings, which introduces limitations and biases related to lack of objectivity and does not capture performance in real-world settings. To overcome these limitations, advances in technologies (e.g., virtual reality) and sensors (e.g., eye-tracking tools) have been used to create realistic simulated environments and track eye movements, enriching assessments with more objective data than can be obtained via traditional measures. This study aimed to distinguish between autistic and typically developing children using visual attention behaviors through an eye-tracking paradigm in a virtual environment as a measure of attunement to and extraction of socially relevant information. The 55 children participated. Autistic children presented a higher number of frames, both overall and per scenario, and showed higher visual preferences for adults over children, as well as specific preferences for adults' rather than children's faces on which looked more at bodies. A set of multivariate supervised machine learning models were developed using recursive feature selection to recognize ASD based on extracted eye gaze features. The models achieved up to 86% accuracy (sensitivity = 91%) in recognizing autistic children. Our results should be taken as preliminary due to the relatively small sample size and the lack of an external replication dataset. However, to our knowledge, this constitutes a first proof of concept in the combined use of virtual reality, eye-tracking tools, and machine learning for ASD recognition. LAY SUMMARY: Core symptoms in children with ASD involve social communication and interaction. ASD assessment includes expert observations in neutral settings, which show limitations and biases related to lack of objectivity and do not capture performance in real settings. To overcome these limitations, this work aimed to distinguish between autistic and typically developing children in visual attention behaviors through an eye-tracking paradigm in a virtual environment as a measure of attunement to, and extraction of, socially relevant information.
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Affiliation(s)
- Mariano Alcañiz
- Instituto de Investigación e Innovación en Bioingeniería (i3B), Universitat Politécnica de Valencia, Valencia, Spain
| | - Irene Alice Chicchi-Giglioli
- Instituto de Investigación e Innovación en Bioingeniería (i3B), Universitat Politécnica de Valencia, Valencia, Spain
| | - Lucía A Carrasco-Ribelles
- Instituto de Investigación e Innovación en Bioingeniería (i3B), Universitat Politécnica de Valencia, Valencia, Spain.,Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Javier Marín-Morales
- Instituto de Investigación e Innovación en Bioingeniería (i3B), Universitat Politécnica de Valencia, Valencia, Spain
| | - Maria Eleonora Minissi
- Instituto de Investigación e Innovación en Bioingeniería (i3B), Universitat Politécnica de Valencia, Valencia, Spain
| | - Gonzalo Teruel-García
- Instituto de Investigación e Innovación en Bioingeniería (i3B), Universitat Politécnica de Valencia, Valencia, Spain
| | - Marian Sirera
- Red Cenit, Centros de Desarrollo Cognitivo, Valencia, Spain
| | - Luis Abad
- Red Cenit, Centros de Desarrollo Cognitivo, Valencia, Spain
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15
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McCracken JT, Anagnostou E, Arango C, Dawson G, Farchione T, Mantua V, McPartland J, Murphy D, Pandina G, Veenstra-VanderWeele J. Drug development for Autism Spectrum Disorder (ASD): Progress, challenges, and future directions. Eur Neuropsychopharmacol 2021; 48:3-31. [PMID: 34158222 PMCID: PMC10062405 DOI: 10.1016/j.euroneuro.2021.05.010] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 05/13/2021] [Accepted: 05/18/2021] [Indexed: 12/11/2022]
Abstract
In 2017, facing lack of progress and failures encountered in targeted drug development for Autism Spectrum Disorder (ASD) and related neurodevelopmental disorders, the ISCTM with the ECNP created the ASD Working Group charged to identify barriers to progress and recommending research strategies for the field to gain traction. Working Group international academic, regulatory and industry representatives held multiple in-person meetings, teleconferences, and subgroup communications to gather a wide range of perspectives on lessons learned from extant studies, current challenges, and paths for fundamental advances in ASD therapeutics. This overview delineates the barriers identified, and outlines major goals for next generation biomedical intervention development in ASD. Current challenges for ASD research are many: heterogeneity, lack of validated biomarkers, need for improved endpoints, prioritizing molecular targets, comorbidities, and more. The Working Group emphasized cautious but unwavering optimism for therapeutic progress for ASD core features given advances in the basic neuroscience of ASD and related disorders. Leveraging genetic data, intermediate phenotypes, digital phenotyping, big database discovery, refined endpoints, and earlier intervention, the prospects for breakthrough treatments are substantial. Recommendations include new priorities for expanded research funding to overcome challenges in translational clinical ASD therapeutic research.
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Affiliation(s)
- James T McCracken
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA 90024, United States.
| | | | - Celso Arango
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Univesitario Gregorio Maranon, and School of Medicine, Universidad Complutense de Madrid, CIBERSAM, Madrid, Spain
| | - Geraldine Dawson
- Duke University Medical Center, Durham, North Carolina, United States
| | - Tiffany Farchione
- Food and Drug Administration, Silver Spring, Maryland, United States
| | - Valentina Mantua
- Food and Drug Administration, Silver Spring, Maryland, United States
| | | | - Declan Murphy
- Institute of Psychiatry, Psychology and Neuroscience, King's College De Crespigny Park, Denmark Hill, London SE5 8AF, United Kingdom
| | - Gahan Pandina
- Neuroscience Therapeutic Area, Janssen Research & Development, Pennington, New Jersey, United States
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16
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Zhang S, Chen D, Tang Y, Zhang L. Children ASD Evaluation Through Joint Analysis of EEG and Eye-Tracking Recordings With Graph Convolution Network. Front Hum Neurosci 2021; 15:651349. [PMID: 34113244 PMCID: PMC8185139 DOI: 10.3389/fnhum.2021.651349] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2021] [Accepted: 03/19/2021] [Indexed: 11/13/2022] Open
Abstract
Recent advances in neuroscience indicate that analysis of bio-signals such as rest state electroencephalogram (EEG) and eye-tracking data can provide more reliable evaluation of children autism spectrum disorder (ASD) than traditional methods of behavior measurement relying on scales do. However, the effectiveness of the new approaches still lags behind the increasing requirement in clinical or educational practices as the “bio-marker” information carried by the bio-signal of a single-modality is likely insufficient or distorted. This study proposes an approach to joint analysis of EEG and eye-tracking for children ASD evaluation. The approach focuses on deep fusion of the features in two modalities as no explicit correlations between the original bio-signals are available, which also limits the performance of existing methods along this direction. First, the synchronization measures, information entropy, and time-frequency features of the multi-channel EEG are derived. Then a random forest applies to the eye-tracking recordings of the same subjects to single out the most significant features. A graph convolutional network (GCN) model then naturally fuses the two group of features to differentiate the children with ASD from the typically developed (TD) subjects. Experiments have been carried out on the two types of the bio-signals collected from 42 children (21 ASD and 21 TD subjects, 3–6 years old). The results indicate that (1) the proposed approach can achieve an accuracy of 95% in ASD detection, and (2) strong correlations exist between the two bio-signals collected even asynchronously, in particular the EEG synchronization against the face related/joint attentions in terms of covariance.
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Affiliation(s)
- Shasha Zhang
- School of Computer Science, Wuhan University, Wuhan, China
| | - Dan Chen
- School of Computer Science, Wuhan University, Wuhan, China
| | - Yunbo Tang
- School of Computer Science, Wuhan University, Wuhan, China
| | - Lei Zhang
- School of Computer Science, Wuhan University, Wuhan, China
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17
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Alexithymia explains atypical spatiotemporal dynamics of eye gaze in autism. Cognition 2021; 212:104710. [PMID: 33862441 DOI: 10.1016/j.cognition.2021.104710] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Revised: 03/24/2021] [Accepted: 03/26/2021] [Indexed: 11/23/2022]
Abstract
Recognition of emotional facial expressions is considered to be atypical in autism. This difficulty is thought to be due to the way that facial expressions are visually explored. Evidence for atypical visual exploration of emotional faces in autism is, however, equivocal. We propose that, where observed, atypical visual exploration of emotional facial expressions is due to alexithymia, a distinct but frequently co-occurring condition. In this eye-tracking study we tested the alexithymia hypothesis using a number of recent methodological advances to study eye gaze during several emotion processing tasks (emotion recognition, intensity judgements, free gaze), in 25 adults with, and 45 without, autism. A multilevel polynomial modelling strategy was used to describe the spatiotemporal dynamics of eye gaze to emotional facial expressions. Converging evidence from traditional and novel analysis methods revealed that atypical gaze to the eyes is best predicted by alexithymia in both autistic and non-autistic individuals. Information theoretic analyses also revealed differential effects of task on gaze patterns as a function of alexithymia, but not autism. These findings highlight factors underlying atypical emotion processing in autistic individuals, with wide-ranging implications for emotion research.
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18
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Van der Donck S, Vettori S, Dzhelyova M, Mahdi SS, Claes P, Steyaert J, Boets B. Investigating automatic emotion processing in boys with autism via eye tracking and facial mimicry recordings. Autism Res 2021; 14:1404-1420. [PMID: 33704930 DOI: 10.1002/aur.2490] [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: 09/24/2020] [Accepted: 02/08/2021] [Indexed: 11/08/2022]
Abstract
Difficulties in automatic emotion processing in individuals with autism spectrum disorder (ASD) might remain concealed in behavioral studies due to compensatory strategies. To gain more insight in the mechanisms underlying facial emotion recognition, we recorded eye tracking and facial mimicry data of 20 school-aged boys with ASD and 20 matched typically developing controls while performing an explicit emotion recognition task. Proportional looking times to specific face regions (eyes, nose, and mouth) and face exploration dynamics were analyzed. In addition, facial mimicry was assessed. Boys with ASD and controls were equally capable to recognize expressions and did not differ in proportional looking times, and number and duration of fixations. Yet, specific facial expressions elicited particular gaze patterns, especially within the control group. Both groups showed similar face scanning dynamics, although boys with ASD demonstrated smaller saccadic amplitudes. Regarding the facial mimicry, we found no emotion specific facial responses and no group differences in the responses to the displayed facial expressions. Our results indicate that boys with and without ASD employ similar eye gaze strategies to recognize facial expressions. Smaller saccadic amplitudes in boys with ASD might indicate a less exploratory face processing strategy. Yet, this slightly more persistent visual scanning behavior in boys with ASD does not imply less efficient emotion information processing, given the similar behavioral performance. Results on the facial mimicry data indicate similar facial responses to emotional faces in boys with and without ASD. LAY SUMMARY: We investigated (i) whether boys with and without autism apply different face exploration strategies when recognizing facial expressions and (ii) whether they mimic the displayed facial expression to a similar extent. We found that boys with and without ASD recognize facial expressions equally well, and that both groups show similar facial reactions to the displayed facial emotions. Yet, boys with ASD visually explored the faces slightly less than the boys without ASD.
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Affiliation(s)
- Stephanie Van der Donck
- Center for Developmental Psychiatry, Department of Neurosciences, KU Leuven, Leuven, Belgium.,Leuven Autism Research (LAuRes), KU Leuven, Leuven, Belgium
| | - Sofie Vettori
- Center for Developmental Psychiatry, Department of Neurosciences, KU Leuven, Leuven, Belgium.,Leuven Autism Research (LAuRes), KU Leuven, Leuven, Belgium
| | - Milena Dzhelyova
- Institute of Research in Psychological Sciences, Institute of Neuroscience, Université de Louvain, Louvain-La-Neuve, Belgium
| | - Soha Sadat Mahdi
- Medical Imaging Research Center, MIRC, Leuven, Belgium.,Department of Electrical Engineering (ESAT/PSI), KU Leuven, Leuven, Belgium
| | - Peter Claes
- Medical Imaging Research Center, MIRC, Leuven, Belgium.,Department of Electrical Engineering (ESAT/PSI), KU Leuven, Leuven, Belgium.,Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Jean Steyaert
- Center for Developmental Psychiatry, Department of Neurosciences, KU Leuven, Leuven, Belgium.,Leuven Autism Research (LAuRes), KU Leuven, Leuven, Belgium
| | - Bart Boets
- Center for Developmental Psychiatry, Department of Neurosciences, KU Leuven, Leuven, Belgium.,Leuven Autism Research (LAuRes), KU Leuven, Leuven, Belgium
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19
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Tan G, Xu K, Liu J, Liu H. A Trend on Autism Spectrum Disorder Research: Eye Tracking-EEG Correlative Analytics. IEEE Trans Cogn Dev Syst 2021. [DOI: 10.1109/tcds.2021.3102646] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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20
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Vettori S, Van der Donck S, Nys J, Moors P, Van Wesemael T, Steyaert J, Rossion B, Dzhelyova M, Boets B. Combined frequency-tagging EEG and eye-tracking measures provide no support for the "excess mouth/diminished eye attention" hypothesis in autism. Mol Autism 2020; 11:94. [PMID: 33228763 PMCID: PMC7686749 DOI: 10.1186/s13229-020-00396-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Accepted: 11/02/2020] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Scanning faces is important for social interactions. Difficulty with the social use of eye contact constitutes one of the clinical symptoms of autism spectrum disorder (ASD). It has been suggested that individuals with ASD look less at the eyes and more at the mouth than typically developing (TD) individuals, possibly due to gaze aversion or gaze indifference. However, eye-tracking evidence for this hypothesis is mixed. While gaze patterns convey information about overt orienting processes, it is unclear how this is manifested at the neural level and how relative covert attention to the eyes and mouth of faces might be affected in ASD. METHODS We used frequency-tagging EEG in combination with eye tracking, while participants watched fast flickering faces for 1-min stimulation sequences. The upper and lower halves of the faces were presented at 6 Hz and 7.5 Hz or vice versa in different stimulation sequences, allowing to objectively disentangle the neural saliency of the eyes versus mouth region of a perceived face. We tested 21 boys with ASD (8-12 years old) and 21 TD control boys, matched for age and IQ. RESULTS Both groups looked longer at the eyes than the mouth, without any group difference in relative fixation duration to these features. TD boys looked significantly more to the nose, while the ASD boys looked more outside the face. EEG neural saliency data partly followed this pattern: neural responses to the upper or lower face half were not different between groups, but in the TD group, neural responses to the lower face halves were larger than responses to the upper part. Face exploration dynamics showed that TD individuals mostly maintained fixations within the same facial region, whereas individuals with ASD switched more often between the face parts. LIMITATIONS Replication in large and independent samples may be needed to validate exploratory results. CONCLUSIONS Combined eye-tracking and frequency-tagged neural responses show no support for the excess mouth/diminished eye gaze hypothesis in ASD. The more exploratory face scanning style observed in ASD might be related to their increased feature-based face processing style.
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Affiliation(s)
- Sofie Vettori
- Center for Developmental Psychiatry, Department of Neurosciences, University of Leuven (KU Leuven), Leuven, Belgium.
- Leuven Autism Research (LAuRes), University of Leuven (KU Leuven), Leuven, Belgium.
| | - Stephanie Van der Donck
- Center for Developmental Psychiatry, Department of Neurosciences, University of Leuven (KU Leuven), Leuven, Belgium
- Leuven Autism Research (LAuRes), University of Leuven (KU Leuven), Leuven, Belgium
| | - Jannes Nys
- Department of Physics and Astronomy, Ghent University, Ghent, Belgium
- IDLab - Department of Computer Science, University of Antwerp - IMEC, Antwerp, Belgium
| | - Pieter Moors
- Laboratory of Experimental Psychology, University of Leuven (KU Leuven), Leuven, Belgium
| | - Tim Van Wesemael
- Department of Electrical Engineering (ESAT), Stadius Center for Dynamical Systems, Signal Processing and Data Analytics, Leuven, Belgium
| | - Jean Steyaert
- Center for Developmental Psychiatry, Department of Neurosciences, University of Leuven (KU Leuven), Leuven, Belgium
- Leuven Autism Research (LAuRes), University of Leuven (KU Leuven), Leuven, Belgium
| | - Bruno Rossion
- Institute of Research in Psychological Science, Institute of Neuroscience, University of Louvain, Louvain-La-Neuve, Belgium
- CNRS, CRAN - UMR 7039, Université de Lorraine, 54000, Nancy, France
- CHRU-Nancy, Service de Neurologie, Université de Lorraine, 54000, Nancy, France
| | - Milena Dzhelyova
- Leuven Autism Research (LAuRes), University of Leuven (KU Leuven), Leuven, Belgium
- Institute of Research in Psychological Science, Institute of Neuroscience, University of Louvain, Louvain-La-Neuve, Belgium
| | - Bart Boets
- Center for Developmental Psychiatry, Department of Neurosciences, University of Leuven (KU Leuven), Leuven, Belgium
- Leuven Autism Research (LAuRes), University of Leuven (KU Leuven), Leuven, Belgium
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21
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Vettori S, Dzhelyova M, Van der Donck S, Jacques C, Steyaert J, Rossion B, Boets B. Frequency-Tagging Electroencephalography of Superimposed Social and Non-Social Visual Stimulation Streams Reveals Reduced Saliency of Faces in Autism Spectrum Disorder. Front Psychiatry 2020; 11:332. [PMID: 32411029 PMCID: PMC7199527 DOI: 10.3389/fpsyt.2020.00332] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Accepted: 04/02/2020] [Indexed: 12/30/2022] Open
Abstract
Individuals with autism spectrum disorder (ASD) have difficulties with social communication and interaction. The social motivation hypothesis states that a reduced interest in social stimuli may partly underlie these difficulties. Thus far, however, it has been challenging to quantify individual differences in social orientation and interest, and to pinpoint the neural underpinnings of it. In this study, we tested the neural sensitivity for social versus non-social information in 21 boys with ASD (8-12 years old) and 21 typically developing (TD) control boys, matched for age and IQ, while children were engaged in an orthogonal task. We recorded electroencephalography (EEG) during fast periodic visual stimulation (FPVS) of social versus non-social stimuli to obtain an objective implicit neural measure of relative social bias. Streams of variable images of faces and houses were superimposed, and each stream of stimuli was tagged with a particular presentation rate (i.e., 6 and 7.5 Hz or vice versa). This frequency-tagging method allows disentangling the respective neural responses evoked by the different streams of stimuli. Moreover, by using superimposed stimuli, we controlled for possible effects of preferential looking, spatial attention, and disengagement. Based on four trials of 60 s, we observed a significant three-way interaction. In the control group, the frequency-tagged neural responses to faces were larger than those to houses, especially in lateral occipito-temporal channels, while the responses to houses were larger over medial occipital channels. In the ASD group, however, faces and houses did not elicit significantly different neural responses in any of the regions. Given the short recording time of the frequency-tagging paradigm with multiple simultaneous inputs and the robustness of the individual responses, the method could be used as a sensitive marker of social preference in a wide range of populations, including younger and challenging populations.
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Affiliation(s)
- Sofie Vettori
- Center for Developmental Psychiatry, Department of Neurosciences, KU Leuven, Leuven, Belgium
- Leuven Autism Research (LAuRes), KU Leuven, Leuven, Belgium
| | - Milena Dzhelyova
- Leuven Autism Research (LAuRes), KU Leuven, Leuven, Belgium
- Institute of Research in Psychological Science, Institute of Neuroscience, University of Louvain, Louvain-La-Neuve, Belgium
| | - Stephanie Van der Donck
- Center for Developmental Psychiatry, Department of Neurosciences, KU Leuven, Leuven, Belgium
- Leuven Autism Research (LAuRes), KU Leuven, Leuven, Belgium
| | - Corentin Jacques
- Center for Developmental Psychiatry, Department of Neurosciences, KU Leuven, Leuven, Belgium
- Institute of Research in Psychological Science, Institute of Neuroscience, University of Louvain, Louvain-La-Neuve, Belgium
| | - Jean Steyaert
- Center for Developmental Psychiatry, Department of Neurosciences, KU Leuven, Leuven, Belgium
- Leuven Autism Research (LAuRes), KU Leuven, Leuven, Belgium
| | - Bruno Rossion
- Institute of Research in Psychological Science, Institute of Neuroscience, University of Louvain, Louvain-La-Neuve, Belgium
- Université de Lorraine, CNRS, CRAN-UMR 7039, Nancy, France
- Université de Lorraine, CHRU-Service de Neurologie, Nancy, France
| | - Bart Boets
- Center for Developmental Psychiatry, Department of Neurosciences, KU Leuven, Leuven, Belgium
- Leuven Autism Research (LAuRes), KU Leuven, Leuven, Belgium
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22
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Rossion B. Biomarkers of Face Perception in Autism Spectrum Disorder: Time to Shift to Fast Periodic Visual Stimulation With Electroencephalography? BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2020; 5:258-260. [DOI: 10.1016/j.bpsc.2020.01.008] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Accepted: 01/28/2020] [Indexed: 11/25/2022]
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