Towards interoception as a transdiagnostic biomarker of health-harming disorders
Presented During:
Monday, June 24, 2024: 5:45 PM - 7:00 PM
COEX
Room:
Hall D 2
Poster No:
902
Submission Type:
Abstract Submission
Authors:
Micah Allen1, Francesca Fardo2, Leah Banellis3, Malthe Brændholt3, Niia Nikolova3
Institutions:
1Aarhus University, Lystrup, Denmark, 2Aarhus University, Aarhus, Denmark, 3Aarhus University, Aarhus, DK
First Author:
Co-Author(s):
Introduction:
Interoception, the process of sensing, monitoring, and regulating our internal, homeostatic rhythms, is experiencing a renaissance in neuroscience. Recent advancements in systems neuroscience and neurobiology are uncovering specific, and at times surprising, mechanisms of brain-body interaction. For instance, we've discovered that multi-organ interoceptive axes influence a broad range of brain processes, from global neural oscillations to domain-specific computations. However, our progress in integrating these insights has been hampered by methodological constraints in measuring interoception in humans. To address this, we've developed various computational and psychophysical tools to assess interoception across gastric, cardiac, and respiratory axes. In my talk, I'll share findings from our Visceral Mind Project, a comprehensive dataset of 530 participants, encompassing brain, body, mental health, and psychophysiological measures.
Methods:
In my presentation, I will present data from the Visceral Mind Project (VMP), a large-scale brain biobank with 530 participants, collected in Aarhus, Denmark. The VMP dataset offers comprehensive profiles that index various cognitive domains, with a special focus on computational indices of multi-modal predictive processing, affect, and interoception. It includes extensive mental health symptom inventories, lifestyle and well-being assessments, alongside numerous cognitive tasks paired with physiological measures such as respiration, pulse, and ECG.
The brain imaging component of the VMP is particularly rich, featuring quantitative MRI maps that detail cortical myelination and iron concentration using R2*, MT, and R1 mapping. Functional MRI and MEG data is also included, covering resting state, task-based, and naturalistic movie-watching conditions, complemented by a range of physiological measures such as electrogastrography, respiration, electrodermal response, pupillometry, and blood inflammatory markers. Additionally, we have gathered detailed interoceptive sensitivity and metacognition profiles for all participants using our validated Bayesian psychophysical approach.
The brain imaging component of the VMP is particularly rich, featuring quantitative MRI maps that detail cortical myelination and iron concentration using R2*, MT, and R1 mapping. Functional MRI and MEG data is also included, covering resting state, task-based, and naturalistic movie-watching conditions, complemented by a range of physiological measures such as electrogastrography, respiration, electrodermal response, pupillometry, and blood inflammatory markers. Additionally, we have gathered detailed interoceptive sensitivity and metacognition profiles for all participants using our validated Bayesian psychophysical approach.
·Overview of data in the Visceral Mind Project
·Overview of approach to gastric-brain fingerprinting
Results:
My presentation will explore three sets of results derived from the VMP dataset:
1. Cortical Markers of Respiratory Interoception and Metacognition: Here, we've used whole-brain voxel-based quantification techniques to identify brain-behavior biomarkers associated with respiratory interoception. This involves mapping out the cortical areas that are active in sensing and understanding the body's respiratory signals and their role in cognitive processes.
2. Psychiatric Symptom Fingerprints in the Stomach-Brain Axes: We've employed cross-validated canonical correlation analyses to pinpoint a robust biomarker of stomach-brain coupling. This biomarker is significant for its ability to index mental health symptoms, offering new insights into the complex relationship between gastrointestinal processes and psychiatric conditions.
3. Computational Modelling of Respiratory-Brain Interactions: Using hierarchical drift diffusion modelling, we've explored how respiratory rhythms influence neural gain during perceptual processing. This approach sheds light on the intricate ways respiratory patterns can impact brain function, particularly in the context of perception.
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1. Cortical Markers of Respiratory Interoception and Metacognition: Here, we've used whole-brain voxel-based quantification techniques to identify brain-behavior biomarkers associated with respiratory interoception. This involves mapping out the cortical areas that are active in sensing and understanding the body's respiratory signals and their role in cognitive processes.
2. Psychiatric Symptom Fingerprints in the Stomach-Brain Axes: We've employed cross-validated canonical correlation analyses to pinpoint a robust biomarker of stomach-brain coupling. This biomarker is significant for its ability to index mental health symptoms, offering new insights into the complex relationship between gastrointestinal processes and psychiatric conditions.
3. Computational Modelling of Respiratory-Brain Interactions: Using hierarchical drift diffusion modelling, we've explored how respiratory rhythms influence neural gain during perceptual processing. This approach sheds light on the intricate ways respiratory patterns can impact brain function, particularly in the context of perception.
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Conclusions:
The VMP represents a major milestone in the cognitive and computational neuiroscience of interoception and brain-body interaction. The project has enabled us to develop a variety of open-source tools for quantifying these domains, and offers the community with both a unique data library and set of tools for engaging with it. Our findings underscore the importance of brain-body interaction for mental and health-harming disorders and points towards new computational theories of interoception.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia)
Emotion, Motivation and Social Neuroscience:
Emotional Learning
Emotional Perception
Higher Cognitive Functions:
Decision Making 1
Neuroinformatics and Data Sharing:
Databasing and Data Sharing 2
Keywords:
Emotions
Meta-Cognition
Perception
Psychiatric Disorders
Other - interoception
1|2Indicates the priority used for review
Provide references using author date format
Allen, M. (2023). The Tell-Tale Heart: Interoceptive Precision and Ecological Fear Experiences. PsyArXiv. https://doi.org/10.31234/osf.io/ngamx
Allen, M., Levy, A., Parr, T., & Friston, K. J. (2022). In the Body’s Eye: The computational anatomy of interoceptive inference. PLOS Computational Biology, 18(9), e1010490. https://doi.org/10.1371/journal.pcbi.1010490
Allen, M., Varga, S., & Heck, D. H. (2022). Respiratory rhythms of the predictive mind. Psychological Review. https://doi.org/10.1037/rev0000391
Legrand, N., & Allen, M. (2022). Systole: A python package for cardiac signal synchrony and analysis. Journal of Open Source Software, 7(69), 3832.
Legrand, N., Nikolova, N., Correa, C., Brændholt, M., Stuckert, A., Kildahl, N., Vejlø, M., Fardo, F., & Allen, M. (2022). The heart rate discrimination task: A psychophysical method to estimate the accuracy and precision of interoceptive beliefs. Biological Psychology, 168, 108239. https://doi.org/10.1016/j.biopsycho.2021.108239
Luettich, A., Sievers, C., Alfaro Almagro, F., Allen, M., Jbabdi, S., Smith, S. M., & Pattinson, K. T. S. (2023). Functional connectivity between interoceptive brain regions is associated with distinct health-related domains: A population-based neuroimaging study. Human Brain Mapping, 44(8), 3210–3221. https://doi.org/10.1002/hbm.26275
Nikolova, N., Harrison, O., Toohey, S., Brændholt, M., Legrand, N., Correa, C., Vejlø, M., Jensen, M. S., Fardo, F., & Allen, M. (2022). The respiratory resistance sensitivity task: An automated method for quantifying respiratory interoception and metacognition. Biological Psychology, 170, 108325. https://doi.org/10.1016/j.biopsycho.2022.108325
Schoeller, F., Horowitz, A., Maes, P., Jain, A., Reggente, N., Christov-Moore, L., Trousselard, M., Klein, A., Barca, L., Pezzulo, G., Allen, M., Adrien, V., Miller, M., Salomon, R., Riva, G., DiLernia, D., Tsakiris, M., Verdonk, C., Chalah, M. A., … Friston, K. (2022). Interoceptive technologies for clinical neuroscience. PsyArXiv. https://doi.org/10.31234/osf.io/sqr6z