Probing the subcortical underpinnings of risky decisions with 7T fMRI
Poster No:
1037
Submission Type:
Abstract Submission
Authors:
Ettore Cerracchio1, Niek Steveson1, Anne Trutti1, Steven Miletić2, Birte Forstmann1
Institutions:
1University of Amsterdam, Amsterdam, North Holland, 2Leiden University, Leiden, South Holland
First Author:
Co-Author(s):
Introduction:
Risky decision-making is a hallmark of human behavior; however, most prior cognitive neuroscience research has primarily focused on cortical areas, leaving the involvement of small subcortical nuclei unexplored. This study aims to address this knowledge gap using a subcortex-optimized 7Tesla fMRI approach in healthy participants performing two risky decision-making tasks. In a within-subject design across two sessions, stimuli eliciting spatial memory to a different degree were used to probe the subcortical underpinnings of reward magnitude and explorative/exploitative behavior.
Methods:
Thirty-five (mean age: 22.9; std: 4.1) participants performed two variants of the same task that differed solely in the type of stimuli displayed (symbols vs. grids). In each trial, participants had to choose between two stimuli to accumulate points. Participants were informed that the stimuli's color indicated their reward magnitude according to a fixed color gradient, while each stimulus's unique reward probability had to be learned throughout the experiment. New stimuli were gradually introduced, while repeated stimuli were phased out. Participants completed 329 trials in 3 runs for each session and received a fixed monetary reward. A single echo 2D-EPI sequence was used to collect functional data. Subcortical probabilistic atlas maps were automatically delineated for each participant with the MASSP 2.0 algorithm (Bazin et al., 2020). The extracted BOLD time series data were probability-weighted by the mask and then averaged within each ROI. We fitted one ROI-wise GLM per task with two parametric regressors of interest: (1) a magnitude regressor, computed as the difference in reward magnitude between the chosen and unchosen stimulus, and (2) an exploration/exploitation regressor, computed as the difference in the number of times feedback was received on earlier trials for the chosen versus the unchosen stimulus. For each region of interest, participant-level regressors were estimated, and a Bayesian group-level t-test was performed to assess changes in BOLD activity.
Results:
We found weak evidence supporting neural activations covarying with reward magnitude difference in cornu Ammonis 1-3 during grids trials and in the caudate nucleus, internal globus pallidus, and putamen in symbols trials. We observed moderate evidence relating neural activity in the external globus pallidus with reward magnitude difference in symbols trials. Finally, we found no evidence of neural activity in our ROIs correlating with the exploration-exploitation tradeoff.
Conclusions:
This study set out to investigate the role of subcortical nuclei in risky decision-making. The 7T fMRI results revealed that activations in the cornu Ammonis 1-3, caudate nucleus (Smith et al., 2009), putamen, and internal and external globus pallidus (Addicott et al., 2014) traced the difference in reward magnitude between choice options. Specifically, the involvement of the hippocampal cornu Ammonis 1-3 subregions were only found in the grids task, suggesting this effect is likely driven by the spatial memory nature of the grids-like stimuli. We found no ROIs with neural activity correlating with the exploration-exploitation tradeoff despite previous studies have shown the thalamus, caudate nucleus, globus pallidus, locus coeruleus, putamen, and hippocampus to be involved in explorative/exploitative behavior (Addicott et al., 2014; Chakroun et al., 2020; Keren et al., 2009; Laureiro-Martínez et al., 2014, 2015). These findings suggest that the estimation of reward magnitude difference is carried out by several subcortical nuclei and that it might differ depending on visual stimuli's properties. This seems not to be the case for the exploration-exploitation tradeoff. Future joint-modeling of simultaneously estimating brain and behavior parameters of these risky decision-making tasks might be more sensitive to reveal the neural signatures of the subcortex.
Higher Cognitive Functions:
Decision Making 2
Modeling and Analysis Methods:
Activation (eg. BOLD task-fMRI) 1
Keywords:
Basal Ganglia
Cognition
FUNCTIONAL MRI
HIGH FIELD MR
Other - risky decision-making
1|2Indicates the priority used for review
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Provide references using APA citation style.
Bazin, P.-L., Alkemade, A., Mulder, M. J., Henry, A. G., & Forstmann, B. U. (2020). Multi-contrast anatomical subcortical structures parcellation. eLife, 9, e59430. https://doi.org/10.7554/eLife.59430
Chakroun, K., Mathar, D., Wiehler, A., Ganzer, F., & Peters, J. (2020). Dopaminergic modulation of the exploration/exploitation trade-off in human decision-making. eLife, 9, e51260. https://doi.org/10.7554/eLife.51260
Keren, N. I., Lozar, C. T., Harris, K. C., Morgan, P. S., & Eckert, M. A. (2009). In vivo mapping of the human locus coeruleus. NeuroImage, 47(4), 1261–1267. https://doi.org/10.1016/j.neuroimage.2009.06.012
Laureiro-Martínez, D., Brusoni, S., Canessa, N., & Zollo, M. (2015). Understanding the exploration–exploitation dilemma: An fMRI study of attention control and decision-making performance. Strategic Management Journal, 36(3), 319–338. https://doi.org/10.1002/smj.2221
Laureiro-Martínez, D., Canessa, N., Brusoni, S., Zollo, M., Hare, T., Alemanno, F., & Cappa, S. F. (2014). Frontopolar cortex and decision-making efficiency: Comparing brain activity of experts with different professional background during an exploration-exploitation task. Frontiers in Human Neuroscience, 7. https://doi.org/10.3389/fnhum.2013.00927
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