Human Frontal-Subcortical Circuit and Asymmetric Belief Updating

Abstract

How humans integrate information to form beliefs about reality is a question that has engaged scientists for centuries, yet the biological system supporting this process is not well understood. One of the most salient attributes of information is valence. Whether a piece of news is good or bad is critical in determining whether it will alter our beliefs. Here, we reveal a frontal-subcortical circuit in the left hemisphere that is simultaneously associated with enhanced integration of favorable information into beliefs and impaired integration of unfavorable information. Specifically, for favorable information, stronger white matter connectivity within this system, particularly between the left inferior frontal gyrus (IFG) and left subcortical regions (including the amygdala, hippocampus, thalamus, putamen, and pallidum), as well as insular cortex, is associated with greater change in belief. However, for unfavorable information, stronger connectivity within this system, particularly between the left IFG and left pallidum, putamen, and insular cortex, is associated with reduced change in beliefs. These novel results are consistent with models suggesting that partially separable processes govern learning from favorable and unfavorable information.

Significance statement: Beliefs of what may happen in the future are important, because they guide decisions and actions. Here, we illuminate how structural brain connectivity is related to the generation of subjective beliefs. We focus on how the valence of information is related to people's tendency to alter their beliefs. By quantifying the extent to which participants update their beliefs in response to desirable and undesirable information and relating those measures to the strength of white matter connectivity using diffusion tensor imaging, we characterize a left frontal-subcortical system that is associated simultaneously with greater belief updating in response to favorable information and reduced belief updating in response to unfavorable information. This neural architecture may allow valence to be incorporated into belief updating.

Keywords: DTI; belief updating; frontal-subcortical circuit; individual differences; valence; white-matter connectivity.

Figure 1.

Procedure. a, On each trial, participants were presented with a short description of one of 46 adverse events and asked to estimate how likely this event was to occur to them in the future. They were then presented with the base rate of the event occurring in a demographically similar population. The second session was the same as the first, except that the base rate of the event to occur was not presented. Examples of trials for which the participant's estimate was higher (b) or lower (c) than the base rate. Here, for illustration purposes only, the blue and red frames denote the participant's response (either a relative overestimation or underestimation, respectively), and the blue and red filled boxes denote information that calls for an adjustment in a favorable (b) or unfavorable (c) direction.

Figure 2.

Illustration of the main analysis steps. a, One of the three seed regions used in whole-brain probabilistic tractography analysis is portrayed in blue on an MNI template brain (seed was converted to individuals' DTI space). This seed includes voxels in the left IFG identified from our previous fMRI and TMS studies (Sharot et al., 2011, 2012). b, Visitation maps (tractography results) of two representative participants in subjects' (sbj) DTI space. Each visitation map was first normalized to MNI space. c, Tractography results for all subjects in MNI space. For visualization purposes, the mask is the sum of all the individual masks. Light blue represents voxels in which connectivity with the left IFG was observed in 100% of participants. Darker blue depicts voxels in which connectivity with the left IFG was observed in <100% of participants. d, Region in which connectivity with the left IFG was observed in at least 80% of the participants was used as a mask for cross-subject correlational analysis (all individual tractography results were normalized to MNI space and scaled for the size of the mask). For each voxel in the mask, a correlation analysis was performed between the fiber tract strength of that voxel with the left IFG and the asymmetric information integration score, while controlling for all noise regressors.

Figure 3.

White matter connectivity correlates with asymmetric information integration. a, 3D cluster in orange of fiber tracts in which strength seeded from the left IFG correlates positively with asymmetric information integration across participants. b, Cluster shown in a 3D brain. c, Cluster shown on sagittal, coronal, and axial planes portraying significant effects in the left pallidum, left putamen, left insula, left amygdala, left hippocampus, and left thalamus (whole-brain FWE corrected, p < 0.05).

Figure 4.

Teasing apart correlation results. Canonical correlational analysis was run to test whether the relationship between white matter connectivity and asymmetric information integration was driven by the net effect of asymmetric information integration or by independent contribution of update in response to favorable news and/or unfavorable. This analysis is equivalent to teasing apart an interaction effect. The graph shows β values from the canonical correlational analysis representing the relationship between fiber strength and update in response to favorable and unfavorable information while controlling for all covariates (see Materials and Methods). *p < 0.05.