Neural Correlates of Human Fear Conditioning and Sources of Variability
Presented During:
Friday, June 27, 2025: 11:30 AM - 12:45 PM
Brisbane Convention & Exhibition Centre
Room:
P2 (Plaza Level)
Poster No:
1053
Submission Type:
Abstract Submission
Authors:
Hannah Savage1, Joaquim Radua2, Enric Vilajosana2, Alec Jamieson3, ENIGMA Anxiety Fear Conditioning Group4, Henrik Walter5, Paul Thompson6, Janna Marie Bas-Hoogendam7, Nynke Groenewold8, Dan Stein9, Nic Van der Wee10, Joseph Dunsmoor11, Andre Marquand12, Ben Harrison13, Miquel Fullana2
Institutions:
1Institute of Cognitive Neuroscience, London, United Kingdom, 2Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain, 3The University of Melbourne, Victoria, Australia, 4USA, USA, 5Charité–Universitätsmedizin Berlin, Berlin, Germany, 6University of Southern California, California, USA, 7Leiden University, Leiden, The Netherlands, 8University of Cape Town, Cape Town, South Africa, 9Dept of Psychiatry and Mental Health, University of Capetown, Capetown, South Africa, 10Leiden University Medical Center, Leiden, The Netherlands, 11University of Texis, Texas, USA, 12Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands, 13University of Melbourne, Victoria, Australia
First Author:
Co-Author(s):
Enric Vilajosana
Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)
Barcelona, Spain
Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)
Barcelona, Spain
Introduction:
Fear conditioning, also known as threat conditioning, is a psychological paradigm developed over a century ago, which models how the association between an initially neutral stimulus (conditioned stimulus, CS) and an innately aversive stimulus (unconditioned stimulus, US) is learned. It remains one of the most widely used and productive experimental models for investigating both normal and pathological fear and anxiety in humans (Beckers,
et al., 2023). Differences between the findings of prior studies, may be explained by individual differences, such as sociodemographic factors (e.g., age) and trait variables (e.g., trait anxiety), or task-specific variables, such as task instructions or the choice of aversive stimuli, that differ between studies, and are likely to modulate the neural correlates of fear conditioning (Lonsdorf et al., 2017).
et al., 2023). Differences between the findings of prior studies, may be explained by individual differences, such as sociodemographic factors (e.g., age) and trait variables (e.g., trait anxiety), or task-specific variables, such as task instructions or the choice of aversive stimuli, that differ between studies, and are likely to modulate the neural correlates of fear conditioning (Lonsdorf et al., 2017).
Methods:
In this study with pre-registered hypotheses and analyses we performed a large analysis of the neural correlates of Pavlovian fear conditioning acquisition and its sources of variability, using harmonised functional magnetic resonance imaging (fMRI) data from 2,199 individuals in nine countries, including 1,888 healthy controls and 311 individuals with anxiety-related and depressive disorders. We use both mega-analysis and normative modelling (Savage et al., 2024) to overcome prior challenges of combining heterogeneous datasets, to comprehensively disentangle sources of variation across multiple levels (Figure 1).
·Figure 1: Schematic indicating the levels of analysis
Results:
Replicating prior work (Fullana et al., 2016), we showed that brain regions robustly linked to conditioning can be broadly described as belonging to the "central autonomic–interoceptive" or "salience" networks (Figure 2A). While individual differences have small or nonsignificant associations with fear conditioning at the neural level, our work demonstrates that several task variables were associated with consistent effects across individuals. These included pre-task instructions about CS-US contingency (Figure 2B), the type of US (Figure 2C), the use of paradigms with multiple CSs (i.e., more than one CS+ or CS-), the reinforcement rate (i.e., percentage of CS+ followed by a US), and possible US confounding through inclusion of the US within the CS+>CS- contrast.
Additionally, brain activation during fear conditioning differed between healthy individuals and those with anxiety-related and depressive disorders, both at the group level and in the frequency of individual deviations identified through normative modelling (Figure 2D). Furthermore, using the individual deviation scores we were able to differentiate and classify individuals with PTSD and OCD with striking precision, as compared to individuals with GAD and SAD (Figure 2E). This suggests that the neural mechanisms engaged during a fear conditioning paradigm are specifically relevant to the psychopathology of, and to some extent, similarly altered across individuals with PTSD.
Additionally, brain activation during fear conditioning differed between healthy individuals and those with anxiety-related and depressive disorders, both at the group level and in the frequency of individual deviations identified through normative modelling (Figure 2D). Furthermore, using the individual deviation scores we were able to differentiate and classify individuals with PTSD and OCD with striking precision, as compared to individuals with GAD and SAD (Figure 2E). This suggests that the neural mechanisms engaged during a fear conditioning paradigm are specifically relevant to the psychopathology of, and to some extent, similarly altered across individuals with PTSD.
·Figure 2: Neural Correlates of Human Fear Conditioning (A), Sources of Variability (B,C) and Differences between individuals with anxiety-related disorder and healthy controls (D, E).
Conclusions:
With this work, we provide the largest analysis of the neural correlates of human fear conditioning and potential sources of variation to date. Our results confirm that human fear conditioning is a robust phenomenon at the neural level, and provide an overview of the influence of task design choices on elicited and predicted brain activation, which can be used to help interpret differences in the previous literature and should remind researchers of the potentially significant influence of task design choices. We found that there are overall differences in fear conditioning at the neural level between individuals with anxiety-related and depressive disorders and controls, and that a unique mechanism of PTSD psychopathology is well captured by fear conditioning paradigms, supporting the use of these models to study this disorder (Fullana, 2020)
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 2
Emotion, Motivation and Social Neuroscience:
Emotional Learning
Modeling and Analysis Methods:
Activation (eg. BOLD task-fMRI) 1
Classification and Predictive Modeling
Multivariate Approaches
Keywords:
Affective Disorders
Anxiety
Emotions
Learning
Machine Learning
Meta- Analysis
Modeling
Multivariate
Psychiatric Disorders
Other - Normative Modelling
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.
Fullana, M. A. et al., (2016). Neural signatures of human fear conditioning: An updated and extended meta-analysis of fMRI studies [Original Article]. Molecular psychiatry, 21, 500-508. https://doi.org/10.1038/mp.2015.88
Fullana, M. et al., (2020). Human fear conditioning: From neuroscience to the clinic. Behaviour Research and Therapy, 124, 103528-103534. https://doi.org/10.1016/j.brat.2019.103528
Lonsdorf, T. B., & Merz, C. J. (2017). More than just noise: Inter-individual differences in fear acquisition, extinction and return of fear in humans-Biological, experiential, temperamental factors, and methodological pitfalls. Neuroscience and Biobehavioral Reviews, 80, 703-728. https://doi.org/10.1016/j.neubiorev.2017.07.007
Savage, H. S. et al., (2024). Dissecting task-based fMRI activity using normative modelling: an application to the Emotional Face Matching Task. Communications Biology, 7(1), 888. https://doi.org/10.1038/s42003-024-06573-z