Atypical Recruitment of the Salience Network in Autistic Adults During an Face Matching Task
Poster No:
296
Submission Type:
Abstract Submission
Authors:
Yan Ge1, Tobias Whelan1, Mihail Dimitrov1, Claire Ellis1, Francesca Moruzzi1, Johanna Kangas1, Francesca Ponteduro1, Nermin Khalil1, Sunniva Fenn-Moltu1,2, Nicolaas Puts1,3,4, Eileen Daly1, Declan Murphy1,5,4, Grainne McAlonan1,4,3, Dafnis Batalle1,2,4
Institutions:
1Dept of Forensic and Neurodevelopmental Sciences, King's College London, London, United Kingdom, 2Centre for the Developing Brain, King's College London, London, United Kingdom, 3MRC Centre for Neurodevelopmental Disorders, King’s College London, London, United Kingdom, 4NIHR Maudsley Biomedical Research Centre (BRC), London, United Kingdom, 5The Institute for Translational Neurodevelopment, King's College London, London, United Kingdom
First Author:
Yan Ge
Dept of Forensic and Neurodevelopmental Sciences, King's College London
London, United Kingdom
Dept of Forensic and Neurodevelopmental Sciences, King's College London
London, United Kingdom
Co-Author(s):
Tobias Whelan
Dept of Forensic and Neurodevelopmental Sciences, King's College London
London, United Kingdom
Dept of Forensic and Neurodevelopmental Sciences, King's College London
London, United Kingdom
Mihail Dimitrov
Dept of Forensic and Neurodevelopmental Sciences, King's College London
London, United Kingdom
Dept of Forensic and Neurodevelopmental Sciences, King's College London
London, United Kingdom
Claire Ellis
Dept of Forensic and Neurodevelopmental Sciences, King's College London
London, United Kingdom
Dept of Forensic and Neurodevelopmental Sciences, King's College London
London, United Kingdom
Francesca Moruzzi
Dept of Forensic and Neurodevelopmental Sciences, King's College London
London, United Kingdom
Dept of Forensic and Neurodevelopmental Sciences, King's College London
London, United Kingdom
Johanna Kangas
Dept of Forensic and Neurodevelopmental Sciences, King's College London
London, United Kingdom
Dept of Forensic and Neurodevelopmental Sciences, King's College London
London, United Kingdom
Francesca Ponteduro
Dept of Forensic and Neurodevelopmental Sciences, King's College London
London, United Kingdom
Dept of Forensic and Neurodevelopmental Sciences, King's College London
London, United Kingdom
Nermin Khalil
Dept of Forensic and Neurodevelopmental Sciences, King's College London
London, United Kingdom
Dept of Forensic and Neurodevelopmental Sciences, King's College London
London, United Kingdom
Sunniva Fenn-Moltu
Dept of Forensic and Neurodevelopmental Sciences, King's College London|Centre for the Developing Brain, King's College London
London, United Kingdom|London, United Kingdom
Dept of Forensic and Neurodevelopmental Sciences, King's College London|Centre for the Developing Brain, King's College London
London, United Kingdom|London, United Kingdom
Nicolaas Puts
Dept of Forensic and Neurodevelopmental Sciences, King's College London|MRC Centre for Neurodevelopmental Disorders, King’s College London|NIHR Maudsley Biomedical Research Centre (BRC)
London, United Kingdom|London, United Kingdom|London, United Kingdom
Dept of Forensic and Neurodevelopmental Sciences, King's College London|MRC Centre for Neurodevelopmental Disorders, King’s College London|NIHR Maudsley Biomedical Research Centre (BRC)
London, United Kingdom|London, United Kingdom|London, United Kingdom
Eileen Daly
Dept of Forensic and Neurodevelopmental Sciences, King's College London
London, United Kingdom
Dept of Forensic and Neurodevelopmental Sciences, King's College London
London, United Kingdom
Declan Murphy
Dept of Forensic and Neurodevelopmental Sciences, King's College London|The Institute for Translational Neurodevelopment, King's College London|NIHR Maudsley Biomedical Research Centre (BRC)
London, United Kingdom|London, United Kingdom|London, United Kingdom
Dept of Forensic and Neurodevelopmental Sciences, King's College London|The Institute for Translational Neurodevelopment, King's College London|NIHR Maudsley Biomedical Research Centre (BRC)
London, United Kingdom|London, United Kingdom|London, United Kingdom
Grainne McAlonan
Dept of Forensic and Neurodevelopmental Sciences, King's College London|NIHR Maudsley Biomedical Research Centre (BRC)|MRC Centre for Neurodevelopmental Disorders, King’s College London
London, United Kingdom|London, United Kingdom|London, United Kingdom
Dept of Forensic and Neurodevelopmental Sciences, King's College London|NIHR Maudsley Biomedical Research Centre (BRC)|MRC Centre for Neurodevelopmental Disorders, King’s College London
London, United Kingdom|London, United Kingdom|London, United Kingdom
Dafnis Batalle
Dept of Forensic and Neurodevelopmental Sciences, King's College London|Centre for the Developing Brain, King's College London|NIHR Maudsley Biomedical Research Centre (BRC)
London, United Kingdom|London, United Kingdom|London, United Kingdom
Dept of Forensic and Neurodevelopmental Sciences, King's College London|Centre for the Developing Brain, King's College London|NIHR Maudsley Biomedical Research Centre (BRC)
London, United Kingdom|London, United Kingdom|London, United Kingdom
Introduction:
Autism is a neurodevelopmental condition characterised by difficulties in social communication and interaction. Processing of facial expressions is crucial for social communication and interaction and is thought to be altered in autistic individuals (Sasson, 2006). However, inconsistent results have been reported regarding differences in brain activation, measured by blood oxygen level dependent (BOLD) fMRI, between autistic and non-autistic adults when processing emotional faces (Langenbach et al., 2024). This may in part depend on the focus of analyses and, for example, in addition to face-specific circuits, processing of facial expressions incorporates whole-brain intrinsic connectivity networks (ICNs) (Nomi et al., 2015). ICNs are large-scale spatial patterns of coherent BOLD fluctuation among distinct brain regions, supporting cognitive functions and emotional regulation. The engagement of whole-brain ICNs during emotional face processing has been relatively underexplored in autism. The current study aims to examine and validate differences in both face specific activation and ICN engagement with whole-brain data-driven methods during an emotional face matching task.
Methods:
An fMRI dataset was acquired during an adapted emotional face matching task (Hariri et al., 2002) from autistic (n=25) and non-autistic (n=32) adults (mean age ± standard deviation = 29.37 ± 8.66). During the scan, participants viewed a target image (upper panel) and two comparison images (lower panel) and indicated the matching image via button press. Stimuli included sex-balanced emotional faces as experimental conditions and geometric shapes as controls. To obtain the average BOLD response to emotional faces among participants, we used double gamma Hemodynamic Response Function models to obtain brain regions showing stronger or weaker subject-level BOLD activation responding to emotional faces compared to shapes. Second-level permutation tests were performed to compare the BOLD response between autistic and non-autistic groups. Then, to analyse the engagement of ICNs, we identified 15 ICNs with group-level independent component analysis (Figure 1) and performed dual regression to obtain subject-specific ICN spatial maps corresponding to group-level ICNs (Nickerson et al., 2017). Whole-brain random permutation tests were performed to compare the spatial maps between autistic and non-autistic adults. All permutation tests were implemented using the FSL randomise function (Winkler et al., 2014) and controlled for sex, age, and motion (mean framewise displacement).
Results:
In line with previous literature, we found a stronger BOLD response to emotional faces than to shapes in fusiform gyrus, visual cortex, and amygdala in the combined cohort of autistic and non-autistic participants (Figure 2A) (familywise error (FWE)-corrected p < .025). There was no significant difference in BOLD response between autistic and non-autistic adults with whole-brain comparisons. Regarding the engagement of ICNs, non-autistic participants exhibited significantly stronger contributions of the presupplementary motor area and anterior cingulate cortex in the salience network (SN) than autistic participants (FWE-corrected p < .025) (Figure 2B).
Conclusions:
In brief, autistic adults did not exhibit altered BOLD response to emotional faces but did show under-recruitment of multiple brain regions in the salience network. Thus, atypical recruitment of the SN, which processes and integrates sensory information, may contribute to some of the challenges or differences experienced by autistic people when dealing with facial expressions (rather than more direct differences in neural responses in fusiform gyrus, visual cortex, and amygdala). Further analysis of the dynamic reconfiguration of ICNs during face-matching tasks, instead of average ICN activity across the scan acquisition period, may help us elucidate whether atypical recruitment of the SN is associated with constant low response or atypical fluctuation.
Disorders of the Nervous System:
Neurodevelopmental/ Early Life (eg. ADHD, autism) 1
Emotion, Motivation and Social Neuroscience:
Emotional Perception
Modeling and Analysis Methods:
Activation (eg. BOLD task-fMRI)
fMRI Connectivity and Network Modeling 2
Novel Imaging Acquisition Methods:
BOLD fMRI
Keywords:
ADULTS
Autism
Emotions
FUNCTIONAL MRI
1|2Indicates the priority used for review
Abstract Information
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Provide references using APA citation style.
Langenbach, B. P., Grotegerd, D., Mulders, P. C. R., Tendolkar, I., van Oort, J., Duyser, F., van Eijndhoven, P., Vrijsen, J. N., Dannlowski, U., Kampmann, Z., & Koelkebeck, K. (2024). Autistic and non-autistic individuals show the same amygdala activity during emotional face processing. Molecular Autism, 15(1), 2.
Nickerson, L. D., Smith, S. M., Öngür, D., & Beckmann, C. F. (2017). Using Dual Regression to Investigate Network Shape and Amplitude in Functional Connectivity Analyses. Frontiers in Neuroscience, 11. https://doi.org/10.3389/fnins.2017.00115
Nomi, J. S., & Uddin, L. Q. (2015). Face processing in autism spectrum disorders: From brain regions to brain networks. Neuropsychologia, 71, 201–216.
Sasson, N. J. (2006). The Development of Face Processing in Autism. Journal of Autism and Developmental Disorders, 36(3), 381–394.
Winkler, A. M., Ridgway, G. R., Webster, M. A., Smith, S. M., & Nichols, T. E. (2014). Permutation inference for the general linear model. NeuroImage, 92, 381–397.