Dataset Information

Dorsal anterior cingulate-brainstem ensemble as a reinforcement meta-learner.

ABSTRACT: Optimal decision-making is based on integrating information from several dimensions of decisional space (e.g., reward expectation, cost estimation, effort exertion). Despite considerable empirical and theoretical efforts, the computational and neural bases of such multidimensional integration have remained largely elusive. Here we propose that the current theoretical stalemate may be broken by considering the computational properties of a cortical-subcortical circuit involving the dorsal anterior cingulate cortex (dACC) and the brainstem neuromodulatory nuclei: ventral tegmental area (VTA) and locus coeruleus (LC). From this perspective, the dACC optimizes decisions about stimuli and actions, and using the same computational machinery, it also modulates cortical functions (meta-learning), via neuromodulatory control (VTA and LC). We implemented this theory in a novel neuro-computational model-the Reinforcement Meta Learner (RML). We outline how the RML captures critical empirical findings from an unprecedented range of theoretical domains, and parsimoniously integrates various previous proposals on dACC functioning.

SUBMITTER: Silvetti M

PROVIDER: S-EPMC6126878 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Dorsal anterior cingulate-brainstem ensemble as a reinforcement meta-learner.

Silvetti Massimo M Vassena Eliana E Abrahamse Elger E Verguts Tom T

PLoS computational biology 20180824 8

Optimal decision-making is based on integrating information from several dimensions of decisional space (e.g., reward expectation, cost estimation, effort exertion). Despite considerable empirical and theoretical efforts, the computational and neural bases of such multidimensional integration have remained largely elusive. Here we propose that the current theoretical stalemate may be broken by considering the computational properties of a cortical-subcortical circuit involving the dorsal anterio ...[more]

PMID: 30142152

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Project description:Cigarette smoking has a major impact on global health and morbidity, and positron emission tomographic research has provided evidence for reduced inflammation in the human brain associated with cigarette smoking. Given the consequences of inflammatory dysfunction for health, the question of whether cigarette smoking affects neuroinflammation warrants further investigation. The goal of this project therefore was to validate and extend evidence of hypoinflammation related to smoking, and to examine the potential contribution of inflammation to clinical features of smoking. Using magnetic resonance spectroscopy, we measured levels of neurometabolites that are putative neuroinflammatory markers. N-acetyl compounds (N-acetylaspartate + N-acetylaspartylglutamate), glutamate, creatine, choline-compounds (phosphocholine + glycerophosphocholine), and myo-inositol, have all been linked to neuroinflammation, but they have not been examined as such with respect to smoking. We tested whether people who smoke cigarettes have brain levels of these metabolites consistent with decreased neuroinflammation, and whether clinical features of smoking are associated with levels of these metabolites. The dorsal anterior cingulate cortex was chosen as the region-of-interest because of previous evidence linking it to smoking and related states. Fifty-four adults who smoked daily maintained overnight smoking abstinence before testing and were compared with 37 nonsmoking participants. Among the smoking participants, we tested for associations of metabolite levels with tobacco dependence, smoking history, craving, and withdrawal. Levels of N-acetyl compounds and glutamate were higher, whereas levels of creatine and choline compounds were lower in the smoking group as compared with the nonsmoking group. In the smoking group, glutamate and creatine levels correlated negatively with tobacco dependence, and creatine correlated negatively with lifetime smoking, but none of the metabolite levels correlated with craving or withdrawal. The findings indicate a link between smoking and a hypoinflammatory state in the brain, specifically in the dorsal anterior cingulate cortex. Smoking may thereby increase vulnerability to infection and brain injury.

Project description:Most cigarette smokers who wish to quit too often relapse within the first few days of abstinence, primarily due to the aversive aspects of the nicotine withdrawal syndrome (NWS), which remains poorly understood. Considerable research has suggested that the dorsal anterior cingulate cortex (dACC) plays a key role in nicotine dependence, with its functional connections between other brain regions altered as a function of trait addiction and state withdrawal. The flow of information between dACC and fronto-striatal regions is secured through different pathways, the vast majority of which are glutamatergic. As such, we investigated dACC activity using resting state functional connectivity (rsFC) with functional magnetic resonance imaging (fMRI) and glutamate (Glu) concentration with magnetic resonance spectroscopy (MRS). We also investigated the changes in adenosine levels in plasma during withdrawal as a surrogate for brain adenosine, which plays a role in fine-tuning synaptic glutamate transmission. Using a double-blind, placebo-controlled, randomized crossover design, nontreatment seeking smoking participants (N = 30) completed two imaging sessions, one while nicotine sated and another after 36 h nicotine abstinence. We observed reduced dACC Glu (P = 0.029) along with a significant reduction in plasma adenosine (P = 0.03) and adenosine monophosphate (AMP; P < 0.0001) concentrations during nicotine withdrawal in comparison with nicotine sated state. This withdrawal state manipulation also led to an increase in rsFC strength (P < 0.05) between dACC and several frontal cortical regions, including left superior frontal gyrus (LSFG), and right middle frontal gyrus (RMFG). Moreover, the state-trait changes in dACC Glu and rsFC strength between the dACC and both SFG and MFG were positively correlated (P = 0.012, and P = 0.007, respectively). Finally, the change in circuit strength between dACC and LSFG was negatively correlated with the change in withdrawal symptom manifestations as measured by the Wisconsin Smoking Withdrawal Scale (P = 0.04) and Tobacco Craving Questionnaire (P = 0.014). These multimodal imaging-behavioral findings reveal the complex cascade of changes induced by acute nicotine deprivation and call for further investigation into the potential utility of adenosine- and glutamate-signaling as novel therapeutic targets to treat the NWS.

Dataset Information

Dorsal anterior cingulate-brainstem ensemble as a reinforcement meta-learner.

Publications

Dorsal anterior cingulate-brainstem ensemble as a reinforcement meta-learner.

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