Poster No:
315
Submission Type:
Abstract Submission
Authors:
Dorothea Floris1, Luigi Saccaro2, Farnaz Delavari3, Dawid Strzelczyk1, Bruno Hebling Vieira4, Camille Elleaume5, Nicolas Langer4
Institutions:
1University of Zurich, Zurich, Switzerland, 2University of Geneva, Geneva, Switzerland, 3Department of Radiology, Lausanne University Hospital (CHUV), Lausanne, Switzerland, 4University of Zurich, Zurich, Zurich, 5Universtiy of Zurich, Zurich, Switzerland
First Author:
Co-Author(s):
Farnaz Delavari
Department of Radiology, Lausanne University Hospital (CHUV)
Lausanne, Switzerland
Introduction:
Autism is primarily characterized by social difficulties. Differences in the way autistic individuals process faces have been examined at the neural level in core regions of the face processing network, such as the fusiform gyrus (FFG)1,2. While functional magnetic resonance imaging (fMRI) studies report different patterns of activation and connectivity within the FFG in autism1,4, prior research mainly addressed static functional properties across the whole FFG. How activity within the FFG and its functional subdivisions dynamically reconfigures with the rest of the brain in autistic compared to non-autistic individuals (NAI) remains unclear. Furthermore, typical sex differences in face processing exist with females outperforming males on emotional face recognition tasks5 and having a reduced right hemisphere dominance compared to males6. Also, in autism, sex differences have been implicated in regions and networks related to face processing7,8. Whether these sex difference in autism also extend to dynamic functional connectivity (dFC) of the FFG with the rest of the brain remains to be established. Using a recent extension of a dFC approach (micro-co-activation patterns [μCAPs] analysis9,10), we aimed to characterize both spatially and temporally the functional reconfigurations of the FFG with the rest of the brain in autistic compared to non-autistic males and females.
Methods:
We included 286 autistic individuals (208 males) and 228 NAI (146 males), aged 6–30 years from the large-scale EU-AIMS Longitudinal European Autism Project. We used resting-state fMRI data to derive data-driven, k-means-clustering based μCAPs using the left and right FFG as one seed region. Unlike conventional methods, μCAPs extract dynamic spatial patterns that reveal functional subdivisions of the seed region (i.e., FFG). Functional networks were characterized by overlapping them with the 17 Yeo networks. To assess the spatial overlap between the μCAP subdivisions within the FFG between autistic and NAI, we computed Dice coefficients and evaluated statistical significance with 10,000 permutations. We further compared the occurrences of the different μCAPs using linear mixed-effects models with diagnosis, sex, diagnosis-by-sex interaction, mean framewise displacement and age as fixed effects and acquisition site as random effect.
Results:
We derived six μCAPs co-activating with the ventral attention/somatomotor, dorsal attention, visual central, visual peripheral, limbic, and default mode network (DMN). All six μCAPs showed large spatial overlap between autistic and NAI (p>0.05). There was a significant sex-by-diagnosis interaction (t=2.61, p=0.009, pFDR=0.05) with NAI females exhibiting fewer occurrences of the DMN μCAP than NAI males (t=3.79, p=0.001), whereas autistic individuals did not show such sex difference (t=0.17, p=0.99).
Conclusions:
Using a novel dFC approach, we examined the spatial and temporal reconfigurations of the FFG in autism. Our findings revealed that autistic individuals do not differ from NAI in the spatial extent of FFG subdivisions co-activating with various brain networks. However, autistic males and females did not show sex differences in co-activation patterns between the FFG and DN as observed in NAI. These findings suggest that the typical sex differences in the dFC of face processing networks are attenuated in autism, highlighting the importance of considering sex-related variability when examining brain dynamics in autism.
Disorders of the Nervous System:
Neurodevelopmental/ Early Life (eg. ADHD, autism) 1
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural) 2
Keywords:
Autism
FUNCTIONAL MRI
Psychiatric Disorders
1|2Indicates the priority used for review
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Please indicate below if your study was a "resting state" or "task-activation” study.
Resting state
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Patients
Was this research conducted in the United States?
No
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel?
NOTE: Any human subjects studies without IRB approval will be automatically rejected.
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Were any animal research approved by the relevant IACUC or other animal research panel?
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Please indicate which methods were used in your research:
Functional MRI
Behavior
For human MRI, what field strength scanner do you use?
3.0T
Which processing packages did you use for your study?
SPM
FSL
Provide references using APA citation style.
1. Pierce, K., Müller, R. A., Ambrose, J., Allen, G. & Courchesne, E. Face processing occurs outside the fusiform ‘face area’ in autism: Evidence from functional MRI. Brain 124, (2001).
2. Dziobek, I., Bahnemann, M., Convit, A. & Heekeren, H. R. The role of the fusiform-amygdala system in the pathophysiology of Autism. Arch. Gen. Psychiatry 67, (2010).
3. Rosenke, M., van Hoof, R., van den Hurk, J., Grill-Spector, K. & Goebel, R. A Probabilistic Functional Atlas of Human Occipito-Temporal Visual Cortex. Cereb. Cortex 31, 603–619 (2021).
4. Floris, D. L. et al. A multimodal neural signature of face processing in autism within the fusiform gyrus. 2024.01.04.23300134 Preprint at https://doi.org/10.1101/2024.01.04.23300134 (2024).
5. Connolly, H. L., Lefevre, C. E., Young, A. W. & Lewis, G. J. Sex differences in emotion recognition: Evidence for a small overall female superiority on facial disgust. Emotion 19, 455–464 (2019).
6. Godard, O. & Fiori, N. Sex differences in face processing: Are women less lateralized and faster than men? Brain Cogn. 73, 167–175 (2010).
7. Floris, D. L. et al. Towards robust and replicable sex differences in the intrinsic brain function of autism. Mol. Autism 12, (2021).
8. Floris, D. L. et al. The Link Between Autism and Sex-Related Neuroanatomy, and Associated Cognition and Gene Expression. Am. J. Psychiatry 180, 50–64 (2023).
9. Delavari, F. et al. Thalamic contributions to psychosis susceptibility: Evidence from co‐activation patterns accounting for intra‐seed spatial variability (μCAPs). Hum. Brain Mapp. 45, e26649 (2024).
10. Saccaro, L. F., Delavari, F., Van De Ville, D. & Piguet, C. Hippocampal temporal dynamics and spatial heterogeneity unveil vulnerability markers in the offspring of bipolar patients. Bipolar Disord. (2024) doi:10.1111/bdi.13487.
No