The ventral lateral thalamus’ reactions to negative faces differ between levels of autistic traits
Poster No:
1069
Submission Type:
Abstract Submission
Authors:
Nicolas Lok1, Andy Chua1, Ryan Lim1, Adam Yeo1, Xiaoxiao Zheng2, Keith Kendrick3, Lizhu Luo1
Institutions:
1Nanyang Technological University, Singapore, Singapore, 2University of Electronic Science and Technology of China, Chengdu, Sichuan, 3University of Electronic Science and Technology of China (UESTC ), Chengdu, China
First Author:
Co-Author(s):
Introduction:
Individuals with Autism spectrum disorder (ASD) often find themselves challenged in the effective use of non-verbal cues to interpret emotions and make appropriate attributions to the actions of others (Pelzl et al., 2023). By comparing with typically developing (TD) individuals, previous studies on individuals with ASD have found altered activity in the bilateral thalamus and caudate (Aoki et al., 2015), amygdala and fusiform gyrus (Pelphrey et al., 2007), and the cerebellum (Siciliano & Clausi, 2020) when interpreting emotional faces. However, limited studies have investigated neural differences between TD individuals with varying levels of autistic traits. In this study, we examined neural responses to emotional faces in TD individuals with low versus high autistic traits.
Methods:
Task-based fMRI data were collected from a sample of 90 young adults (male = 47, mean age = 22 years) on a 3T GE Discovery MR 750 system. Participants underwent a total of 150 trials spread across three runs. In each trial, participants were first presented with a facial expression (happy, sad, angry, fearful, or neutral). Then, they were tasked to identify the most plausible emotion and rate its arousal based on the expression. Levels of autistic trait were assessed using the Autism Spectrum Quotient (ASQ).
To examine group-level differences in responses to emotional faces, the initial sample was further subdivided into two groups: low ASQ (n = 30, mean ASQ = 17) and high ASQ (n = 29, mean ASQ = 24) based on the 27-percent rule (Kelley, 1939). Both groups showed significant differences on ASQ scores (t = -18.09, p < 0.001).
The fMRI data were pre-processed and analysed using the SPM12 toolbox. Two sample t-tests were conducted to compare brain activation towards face emotions in both groups. Small volume correction at voxel-level p < 0.05 (FWE corrected) was applied using the ROI masks of thalamus, caudate, amygdala, fusiform gyrus, and the cerebellum, created from WFU PickAtlas toolbox using the AAL template.
To examine group-level differences in responses to emotional faces, the initial sample was further subdivided into two groups: low ASQ (n = 30, mean ASQ = 17) and high ASQ (n = 29, mean ASQ = 24) based on the 27-percent rule (Kelley, 1939). Both groups showed significant differences on ASQ scores (t = -18.09, p < 0.001).
The fMRI data were pre-processed and analysed using the SPM12 toolbox. Two sample t-tests were conducted to compare brain activation towards face emotions in both groups. Small volume correction at voxel-level p < 0.05 (FWE corrected) was applied using the ROI masks of thalamus, caudate, amygdala, fusiform gyrus, and the cerebellum, created from WFU PickAtlas toolbox using the AAL template.
·Fig 1. The fMRI task procedure for emotional face processing
Results:
There were no group differences in behavioural task performance. Both the low and high ASQ groups displayed high accuracy (mean = 0.92) and rated the faces as equally arousing across all emotion types. However, relative to the low ASQ group, the high ASQ group showed stronger activation in the left thalamus when processing negative emotions (k = 13, t = 3.70, pFWE = 0.035, x/y/z: -12 -10 8), but not for positive emotions. This was driven by stronger activation in high ASQ group in the left thalamus towards fearful faces (k = 27, t = 3.83, pFWE = 0.015, x/y/z: -12 -10 5) and angry faces (k = 41, t = 3.88, pFWE = 0.009, x/y/z: -15 -10 8), but not for sadness. No significant activations during emotional face processing were found in caudate, amygdala, fusiform gyrus or cerebellum.
On an exploratory note, the thalamus activation to angry faces were positively correlated with two ASQ subscales: attention switching (r = 0.35, p = 0.006) and communication (r = 0.29, p = 0.03). Similarly, stronger activation of the left thalamus when viewing fearful faces predicted higher attention switching (r = 0.33, p = 0.01) and communication problems (r = 0.30, p = 0.02).
On an exploratory note, the thalamus activation to angry faces were positively correlated with two ASQ subscales: attention switching (r = 0.35, p = 0.006) and communication (r = 0.29, p = 0.03). Similarly, stronger activation of the left thalamus when viewing fearful faces predicted higher attention switching (r = 0.33, p = 0.01) and communication problems (r = 0.30, p = 0.02).
·Fig 2. (A) The activation map of the left thalamus to emotional faces; and the parameter estimates when viewing (B) emotional, (C) angry, and (D) fearful faces in the high vs. low ASQ group.
Conclusions:
The thalamus is important for initial processing of sensory information and also plays a role in emotional regulation. Consistent with previous studies (Camodeca & Voelker, 2016; Maekawa et al., 2011), the current study suggests that individuals with high autistic traits may tend to rely more on automatic cognitive processes to interpret emotional stimuli (Aoki et al., 2015). Particularly in processing threatening and alerting stimuli, they might show higher sensitivity and potential emotional regulation problems.
Disorders of the Nervous System:
Neurodevelopmental/ Early Life (eg. ADHD, autism) 2
Emotion, Motivation and Social Neuroscience:
Emotional Perception
Modeling and Analysis Methods:
Activation (eg. BOLD task-fMRI) 1
Novel Imaging Acquisition Methods:
BOLD fMRI
Perception, Attention and Motor Behavior:
Perception: Visual
Keywords:
ADULTS
Autism
Emotions
FUNCTIONAL MRI
Sub-Cortical
Thalamus
1|2Indicates the priority used for review
Abstract Information
By submitting your proposal, you grant permission for the Organization for Human Brain Mapping (OHBM) to distribute your work in any format, including video, audio print and electronic text through OHBM OnDemand, social media channels, the OHBM website, or other electronic publications and media.
The Open Science Special Interest Group (OSSIG) is introducing a reproducibility challenge for OHBM 2025. This new initiative aims to enhance the reproducibility of scientific results and foster collaborations between labs. Teams will consist of a “source” party and a “reproducing” party, and will be evaluated on the success of their replication, the openness of the source work, and additional deliverables. Click here for more information. Propose your OHBM abstract(s) as source work for future OHBM meetings by selecting one of the following options:
Please indicate below if your study was a "resting state" or "task-activation” study.
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Was this research conducted in the United States?
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.
Were any animal research approved by the relevant IACUC or other animal research panel? NOTE: Any animal studies without IACUC approval will be automatically rejected.
Please indicate which methods were used in your research:
For human MRI, what field strength scanner do you use?
Which processing packages did you use for your study?
Provide references using APA citation style.
Camodeca, A., & Voelker, S. (2016). Automatic and controlled processing and the broad autism phenotype. Psychiatry Research, 235, 169–176. https://doi.org/10.1016/j.psychres.2015.11.012
Kelley, T. L. (1939). The selection of upper and lower groups for the validation of test items. Journal of Educational Psychology, 30(1), 17–24.
Maekawa, T., Tobimatsu, S., Inada, N., Oribe, N., Onitsuka, T., Kanba, S., & Kamio, Y. (2011). Top-down and bottom-up visual information processing of non-social stimuli in high-functioning autism spectrum disorder. Research in Autism Spectrum Disorders, 5(1), 201–209. https://doi.org/10.1016/j.rasd.2010.03.012
Pelphrey, K. A., Morris, J. P., McCarthy, G., & Labar, K. S. (2007). Perception of dynamic changes in facial affect and identity in autism. Social cognitive and affective neuroscience, 2(2), 140–149. https://doi.org/10.1093/scan/nsm010
Pelzl, M. A., Travers-Podmaniczky, G., Brück, C., Jacob, H., Hoffmann, J., Martinelli, A., Hölz, L., Wabersich-Flad, D., & Wildgruber, D. (2023). Reduced impact of nonverbal cues during integration of verbal and nonverbal emotional information in adults with high-functioning autism. Frontiers in Psychiatry, 13. https://doi.org/10.3389/fpsyt.2022.1069028
Siciliano, L., & Clausi, S. (2020). Implicit vs. Explicit emotion processing in autism spectrum disorders: An opinion on the role of the cerebellum. Frontiers in Psychology, 11. https://doi.org/10.3389/fpsyg.2020.00096