Pre-acquired functional connectivity predicts choice inconsistency

• Published in: The Journal of neuroscience Vol. 44; no. 18; p. e0453232024
• Main Authors: Madar, Asaf, Kurtz-David, Vered, Hakim, Adam, Levy, Dino J, Tavor, Ido
• Format: Journal Article
• Language: English
• Published: United States Society for Neuroscience 01.05.2024
• Subjects: Adult; Brain; Brain - diagnostic imaging; Brain - physiology; Brain mapping; Brain Mapping - methods; Choice Behavior - physiology; Connectome - methods; Engines; Female; Functional magnetic resonance imaging; Humans; Magnetic resonance; Magnetic resonance imaging; Magnetic Resonance Imaging - methods; Male; Nerve Net - diagnostic imaging; Nerve Net - physiology; Nervous system; Neural networks; Neural Pathways - diagnostic imaging; Neural Pathways - physiology; Neuroimaging; Predictions; Risk-Taking; Young Adult; choice inconsistency; functional connectivity; decision-making; predictive modeling
• ISSN: 0270-6474; 1529-2401; 1529-2401
• DOI: 10.1523/JNEUROSCI.0453-23.2024

Economic choice theories usually assume that humans maximize utility in their choices. However, studies have shown that humans make inconsistent choices, leading to suboptimal behavior, even without context dependent manipulations. Previous studies showed that activation in value and motor networks are associated with inconsistent choices at the moment of choice. Here we investigated if the neural predispositions, measured before a choice task, can predict choice inconsistency in a later risk choice task. Using functional connectivity (FC) measures from resting-state functional magnetic resonance imaging (rsfMRI), derived before any choice was made, we aimed to predict subjects’ inconsistency levels in a later-performed choice task. We hypothesized that rsfMRI FC measures extracted from value and motor brain areas would predict inconsistency. Forty subjects (21 females) completed a rsfMRI scan before performing a risky-choice task. We compared models that were trained on FC that included only hypothesized value and motor regions with models trained on whole-brain FC. We found that both model types significantly predicted inconsistency levels. Moreover, even the whole-brain models relied mostly on FC between value and motor areas. For external validation, we used a neural network pre-trained on FC matrices of 40,000 subjects and fine-tuned it on our data, and again showed significant predictions. Together, this shows that the tendency for choice inconsistency is predicted by predispositions of the nervous system, and that synchrony between the motor and value networks plays a crucial role in this tendency. Significance Statement Humans often make irrational, or inconsistent, choices in value-based decision-making. Studies have suggested potential sources for this suboptimal behavior in momentary brain activity during choice, emphasizing the role of value and motor areas in the process of inconsistent choice behavior. Here, we show that inconsistency is predicted by neural predispositions, evident even before any choice was made. We predict subjects’ inconsistency levels from brain connectivity measures derived before they perform any choice task and find that inconsistency is predicted by the synchrony between the value and motor brain networks. This suggests choice inconsistency is related to a-priori constraints of the nervous system, and that value and motor areas play a central role in this behavior.