Belief about nicotine selectively modulates value and reward prediction error signals in smokers

Abstract

Little is known about how prior beliefs impact biophysically described processes in the presence of neuroactive drugs, which presents a profound challenge to the understanding of the mechanisms and treatments of addiction. We engineered smokers' prior beliefs about the presence of nicotine in a cigarette smoked before a functional magnetic resonance imaging session where subjects carried out a sequential choice task. Using a model-based approach, we show that smokers' beliefs about nicotine specifically modulated learning signals (value and reward prediction error) defined by a computational model of mesolimbic dopamine systems. Belief of "no nicotine in cigarette" (compared with "nicotine in cigarette") strongly diminished neural responses in the striatum to value and reward prediction errors and reduced the impact of both on smokers' choices. These effects of belief could not be explained by global changes in visual attention and were specific to value and reward prediction errors. Thus, by modulating the expression of computationally explicit signals important for valuation and choice, beliefs can override the physical presence of a potent neuroactive compound like nicotine. These selective effects of belief demonstrate that belief can modulate model-based parameters important for learning. The implications of these findings may be far ranging because belief-dependent effects on learning signals could impact a host of other behaviors in addiction as well as in other mental health problems.

Keywords: belief; dopamine; fMRI; nicotine addiction; reinforcement learning.

Fig. 1.

Experimental procedure. Twenty-four smokers completed four sessions of fMRI scanning in four separate visits. In each session, subjects were given a denicotinized cigarette or a cigarette with nicotine (cigarettes: placebo vs. nicotine) to smoke and were told that the cigarette had no nicotine or had nicotine (belief: told no nicotine vs. told nicotine). Immediately after smoking, subjects performed a sequential investment task in the scanner where they made 20 investment decisions $b_t$ (0 ∼ 100% of current running total, number displayed on lower left side of the screen, e.g., $104) during each market, for a total of 10 markets. Market return $r_t$ was displayed on the lower right side of the screen (e.g., −1.2%). Carbon monoxide (CO) levels were measured both in the beginning and at the end of the experiment (Materials and Methods and Fig. S2).

Fig. 2.

Impact of belief on the value signal $r_t$. (A) Beliefs about nicotine modulated $r_t$-related ventral striatum activation (P_FWE < 0.05; displayed at P < 0.001 uncorrected for visualization). (B) Region of interest analysis (peaks [−12, 8, −6] and [12, 10, −6]; Table S2) (39) confirmed whole-brain results shown in A. (C) The weight of market return $r_t$ on choice behavior (next bet $b_{t+1}$) was significantly reduced when told no nicotine than told nicotine, despite the presence of nicotine in both conditions. (D) Bayesian analysis confirmed the separation between the posterior distributions of the behavioral regression coefficient of market return $r_t$ of told nicotine and told no nicotine. ***P < 0.001. Data are represented as mean ± SEM.

Fig. 3.

Impact of belief on the reward prediction error signal $T{D}_t$. (A) Beliefs about nicotine modulated $T{D}_t$-related striatum activation (P_FWE < 0.05; displayed at P < 0.001 uncorrected for visualization). (B) Region of interest analysis (peaks [−18, 0, −8] and [12, 8, −2]; Table S2) (39) confirmed whole-brain results shown in A. (C) The weight of reward prediction error $T{D}_t$ on choice behavior (next bet $b_{t+1}$) was significantly reduced when told no nicotine than told nicotine, in the presence of nicotine. (D) Bayesian analysis confirmed the separation between the posterior distributions of the behavioral regression coefficient of reward prediction error $T{D}_t$ of told nicotine and told no nicotine. ***P < 0.001. Data are represented as mean ± SEM.

Fig. 4.

Belief did not modulate neural activities in visual attentional regions. (A) Whole-brain analysis of the market reveal regressor suggests that smokers showed equivalent levels of activations in occipito-temporal visual areas and fronto-parietal regions involved in attention when told no nicotine and told nicotine (P_FWE < 0.05, displayed at P < 0.001 uncorrected for visualization, Table S6; no significant activation in contrast image even at P < 0.01 uncorrected). (B) ROI analysis based on an independent dataset (39) confirmed that belief about nicotine did not significantly modulate neural activities in temporal, parietal, and frontal ROIs: inferior temporal gyrus [48, −62, −2], inferior parietal lobule [30, −54, 48], and inferior frontal gyrus [52, 12, 20] (all Ps > 0.1; details in Materials and Methods and Table S7).