Poster No:
953
Submission Type:
Abstract Submission
Authors:
Yubing Zhang1, Sarah Tashjian1
Institutions:
1University of Melbourne, Melbourne, Victoria
First Author:
Co-Author:
Introduction:
Safety learning is critical for survival as well as freeing up resources for other important non-defensive pursuits, such as eating, mating, and socialising. This ability is especially important for adolescents, as they are navigating a period where they need to explore their increasingly complex and uncertain environment (Somerville et al., 2017). At the same time, adolescents are still undergoing cognitive and neurobiological developments (Larsen & Luna, 2018), which might result in potential vulnerabilities in the discrimination and integration of safety- and threat-related information. Difficulties in evaluating safety could lead to either avoiding important growth opportunities due to excessive caution, or risking harm by engaging in unsafe behaviors. Safety is primarily studied as the inverse of external threat through conditioning, which increases as the probability or severity of harm decreases (Möller et al., 2006). However, human safety learning also involves identifying self-oriented protective resources (Tashjian et al., 2021). The present study investigated the role of external and self-oriented information in safety evaluation during adolescence.
Methods:
Functional MRI data were acquired from 33 participants (Mage = 14.88, ages 12-17, 19 females, 14 males) using a 7-Tesla MRI scanner (TR = 800 ms, TE = 22.2 ms, field of view = 208 mm, voxel size = 1.6 mm × 1.6 mm × 1.6 mm, flip angle = 45 degrees). During the scan, participants were instructed to imagine fictitious battles, in which they needed to fight against the animals (external threat) using the weapons they had (self-oriented protection). On each trial, participants were presented with one animal-weapon pair and were asked to make binary judgments about whether they thought they would win or lose the battle when they saw each stimulus. fMRI data were preprocessed using fMRIPrep 23.2.1 (Esteban et al., 2019) and statistically analyzed using the general linear model (GLM; Friston et al., 1994) implemented in FSL 6.0.7.13 (Jenkinson et al., 2012). A region-of-interest (ROI) analysis was further performed to investigate brain activation and task performance.
Results:
Behaviorally, adolescents were found to rely more on self-oriented protective information when making safety decisions in high-safety conditions. Neurally, there was increased activation in the left hippocampus for self-related safety signals compared to external threat signals. Moreover, hippocampus activation was positively associated with participants' accuracy in safety detection.
Conclusions:
The findings suggest that adolescents rely more on self-related protection to track safety. The hippocampus may play a crucial role in the accurate detection of safety by supporting contextual and associative memory processes during learning. Findings advance understanding of safety learning, its neurobiological underpinnings, and how it develops.
Higher Cognitive Functions:
Decision Making 2
Lifespan Development:
Early life, Adolescence, Aging 1
Modeling and Analysis Methods:
Activation (eg. BOLD task-fMRI)
Univariate Modeling
Novel Imaging Acquisition Methods:
BOLD fMRI
Keywords:
Development
FUNCTIONAL MRI
Univariate
Other - Safety Learning
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.
Task-activation
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Healthy subjects
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.
Yes
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.
Not applicable
Please indicate which methods were used in your research:
Functional MRI
For human MRI, what field strength scanner do you use?
7T
Which processing packages did you use for your study?
FSL
Provide references using APA citation style.
1. Esteban, O., Markiewicz, C. J., Blair, R. W., Moodie, C. A., Isik, A. I., Erramuzpe, A., Kent, J. D., Goncalves, M., DuPre, E., Snyder, M., Oya, H., Ghosh, S. S., Wright, J., Durnez, J., Poldrack, R. A., & Gorgolewski, K. J. (2019). fMRIPrep: A robust preprocessing pipeline for functional MRI. Nature Methods, 16(1), 111-116. https://doi.org/10.1101/306951
2. Friston, K. J., Holmes, A. P., Worsley, K. J., Poline, J. P., Frith, C. D., & Frackowiak, R. S. J. (1994). Statistical parametric maps in functional imaging: A general linear approach. Human Brain Mapping, 2(4), 189-210. https://doi.org/10.1002/hbm.460020402
3. Jenkinson, M., Beckmann, C. F., Behrens, T. E., Woolrich, M. W., & Smith, S. M. (2012). Fsl. Neuroimage, 62(2), 782-790. https://doi.org/10.1016/j.neuroimage.2011.09.015
4. Larsen, B., & Luna, B. (2018). Adolescence as a neurobiological critical period for the development of higher-order cognition. Neuroscience & Biobehavioral Reviews, 94, 179-195. https://doi.org/10.1016/j.neubiorev.2018.09.005
5. Möller, N., Hansson, S. O., & Peterson, M. (2006). Safety is more than the antonym of risk. Journal of Applied Philosophy, 23(4), 419-432. https://doi.org/10.1111/j.1468-5930.2006.00345.x
6. Somerville, L. H., Sasse, S. F., Garrad, M. C., Drysdale, A. T., Abi Akar, N., Insel, C., & Wilson, R. C. (2017). Charting the expansion of strategic exploratory behavior during adolescence. Journal of Experimental Psychology: General, 146(2), 155-164. https://doi.org/10.1037/xge0000250
7. Tashjian, S. M., Zbozinek, T. D., & Mobbs, D. (2021). A decision architecture for safety computations. Trends in Cognitive Sciences, 25(5), 342-354. https://doi.org/10.1016/j.tics.2021.01.013
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