People routinely make poor choices, despite knowledge of negative consequences. The authors found that individuals with anorexia nervosa, who make maladaptive food choices to the point of starvation, engaged the dorsal striatum more than healthy controls when making choices about what to eat, and that activity in fronto-striatal circuits was correlated with their actual food consumption in a meal the next day.
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We thank J. Schebendach for guidance and support for the laboratory meals and nutritional analyses. This research was supported in part by the Global Foundation for Eating Disorders and the US National Institute for Mental Health (R01 MH079397, K23 MH076195).
The authors declare no competing financial interests.
Integrated supplementary information
Behavior in Health and Taste rating phases (n = 42). (a) When rating items for “Healthiness,” both groups rated the high-fat items lower (F(1,40) = 802.9, P = 4.3*10-28). AN additionally rated foods lower overall (F(1,40) = 10.10, P = 0.003). (b) When rating the items for “Tastiness,” AN rate food as less tasty (F(1,40) = 10.07, P = 0.000007), an effect that is more pronounced when rating high-fat foods (Group X Food Type interaction: F(1,40) = 5.21, P = 0.028). (c) Logistic regression of Health and Taste ratings on choice. Among the HCs, choice was more influenced by taste than by health (χ2 = 75.64, P < 0.000001), whereas AN choices were influenced by both taste and health (χ2 = 0.22, P = 0.64). (d) Multilevel linear regression of Taste on Health ratings showed that Healthiness and Tastiness were relatively independent in HC, whereas there was a significantly greater association between Health and Taste ratings in AN than in HC (z = 5.3, P = 0.02). (e) HC slowed responses when rating Healthiness of high-fat foods, whereas AN slowed responses when rating Tastiness of high-fat foods (when adjusting for overall group differences in RT; Rating phase X Food type X Group interaction F(1,40) = 11.81, P = 0.001). (f) When asked directly, most HC found Taste easier to rate, whereas most AN found Health easier to rate (proportions significantly different, χ2(1, N = 40) = 10.15, P = 0.002). Data are mean ± s.e.m. (abe); Data are fixed effects coefficients ± s.e. (cd).
Assessing “self-control” use across participants (n = 42). (a) A conflict between Health and Taste ratings creates choice trials with opportunity for self-control (examples outlined in pink): Choosing healthy, less tasty options or not choosing unhealthy, tasty options reflects self-controlled choices. Health-Taste rating alignment leaves no opportunity for self-control (examples outlined in orange). (b) On trials with opportunity for self-control, individuals with AN exercised self-control on a greater proportion of trials relative to Controls (t(33.88) = –4.89, P = 0.000024). However, individuals with AN had significantly fewer trials with opportunity for self-control (t(40) = 3.1, P = 0.004; MHC = 27.8 ± 7.2; MAN = 19.9 ± 9.3). This was likely due to greater alignment between Healthiness and Tastiness across items in AN (See Supplementary Fig. 1d). Thus, changes in valuation according to Health and Taste in AN resulted in diminished need for self-control, suggesting an alternate strategy for making food decisions. (c) Response times when opting for or against self-controlled choices. As expected, HC slowed down when making self-controlled choices, whereas individuals with AN sped up (Group X Self-control use interaction: χ2(1, N = 41) = 4.78, P = 0.03; 1 AN participant had no valid trials for this analysis). Response times on trials where no self-control was needed are shown for comparison (orange bars). Thus, for AN, in contrast to HC, engaging “self-control” did not result in a response time cost. Note that the low number of trials involving self-control precluded fMRI data analysis of self-control trials. Such analyses depend both on trials where self-control was required and deployed as well as trials where self-control was required but not deployed. Only 16 participants (8 HC, 8 AN) had 4 or more trials in each self-control bin. Data are mean ± s.e.m.
(a) To assess the specificity of the differences observed between HC and AN related to food choices, values were extracted from the cluster identified in the choice analysis (Fig. 2b). No significant differences between HC and AN were found for Health or Taste ratings in the dorsal striatum region that showed a significant difference in the Choice phase (Health: t(40) = –0.81, P = 0.42, n = 42; Taste: t(39) = –0.41, P = 0.68, n = 41). Thus, the difference between groups in the dorsal striatum was specific to the Choice phase. Note that this ROI analysis is independent as the region was identified based on activity in the Choice phase. Data are mean ± s.e.m. (b) Parametric analysis of choice ratings for low fat and high fat trials separately within the caudate cluster identified in contrast between AN and HC reported in the manuscript (Fig. 2b, n = 42). There was a significant difference between AN and HC for low fat (t(40) = –2.29, P = 0.028) but not for high fat (t(40) = –1.396, P = 0.170) trials. There were no significant differences between high and low fat trials within the HC (t(20) = -1.03, P = 0.32) or AN group (t(20) = –0.87, P = 0.40). Data are mean ± s.e.m. (c) Choice phase response bin analysis within the caudate cluster identified in contrast between AN and HC reported in the manuscript (Fig. 2b, n = 42). Data were extracted for each response bin (1-5), to further assess whether the response in the dorsal striatum increased with increasing decision strength in the Choice phase or instead reflected a binary “Yes”/”No” response to the test food over the Reference food. Data are mean ± s.e.m.
(a) BOLD activity in regions of the vmPFC correlated with trial-by-trial choice values in both HC (left) and AN (middle) groups, with no significant difference between them (right) (FWE-corrected P < 0.05 whole-brain, cluster-forming threshold Z > 2.3, n = 42). Results from whole-brain analysis in both groups are displayed. Images and coordinates in Montreal Neurological Institute (MNI) space and radiological orientation (Right = Left). To further probe the lack of group differences within vmPFC, we performed an independent analysis using ROIs identified in previous studies of value based choice (ROIs displayed in blue): (b) Hare et al.; MNI coordinates = [3 51 3] (t(40) = 0.23, P = 0.82), and (c) Bartra et al. meta-analysis (t(40) = 0.52, P = 0.61). Data are mean ± s.e.m.
We assessed vmPFC responses in the Health and Taste rating phases using the same region identified by Hare et al (2009); MNI coordinates = [3 51 3]. (a) There were no significant differences in BOLD response between the HC and the AN group in the Health (t(40) = 1.44, P = 0.16, n = 42) or Taste phase (t(39) = 0.26, P = 0.54, n = 41). Data are mean ± s.e.m. (b) BOLD signal during the Health and Choice phases were significantly correlated in the AN group (r = 0.44, P = 0.046); BOLD signal during Taste and Choice phases were significantly correlated in the HC group (r = 0.49, P = 0.024).
Supplementary Figure 6 Fronto-striatal connectivity on low-fat and high-fat food trials in Anorexia Nervosa.
(a) Fronto-striatal connectivity for low-fat foods was significantly negatively correlated with food intake in AN (r(14) = –0.51, P = 0.04, n = 16), (b) whereas connectivity for high-fat foods showed a trend towards a positive correlation with real food intake (r(14) = 0.44, P = 0.09, n = 16). Robust regressions including the participants who binge-ate yielded the same pattern of associations between eating behavior and connectivity on low-fat food trials (t(17) = 2.04, P = 0.057, n = 19) and high-fat food trials (t(17) = –1.92, P = 0.072, n = 19).
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Foerde, K., Steinglass, J., Shohamy, D. et al. Neural mechanisms supporting maladaptive food choices in anorexia nervosa. Nat Neurosci 18, 1571–1573 (2015). https://doi.org/10.1038/nn.4136
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