Reward and fictive prediction error signals in ventral striatum: asymmetry between factual and counterfactual processing.

Reward prediction error, the difference between the expected and obtained reward, is known to act as a reinforcement learning neural signal. In the current study, we propose a model fitting approach that combines behavioral and neural data to fit computational models of reinforcement learning. Briefly, we penalized subject-specific fitted parameters that moved away too far from the group median, except when that deviation led to an improvement in the model's fit to neural responses. By means of a probabilistic monetary learning task and fMRI, we compared our approach with standard model fitting methods. Q-learning outperformed actor-critic at both behavioral and neural level, although the inclusion of neuroimaging data into model fitting improved the fit of actor-critic models. We observed both action-value and state-value prediction error signals in the striatum, while standard model fitting approaches failed to capture state-value signals. Finally, left ventral striatum correlated with reward prediction error while right ventral striatum with fictive prediction error, suggesting a functional hemispheric asymmetry regarding prediction-error driven learning.

The effect of the AKT1 gene and cannabis use on cognitive performance in healthy subjects.

BACKGROUND: Evidence suggests that the AKT1 gene may modulate the degree to which cannabis use induces cognitive alterations in patients with a psychotic disorder. AIM: To examine the interplay between AKT1 and cannabis use in terms of the cognitive performance of the general population. METHODS: Our sample consisted of 389 Spanish university students. Sustained attention was measured via the Continuous Performance Test-Identical Pairs, immediate and delayed verbal memory with the Logical Memory subtest of the Wechsler Memory Scale, and working memory with the Wisconsin Card Sorting Test. Lifetime cannabis use frequency was assessed and individuals were classified as cannabis users or non-users. Two single nucleotide polymorphisms of the AKT1 gene were genotyped and, according to previous studies, each subject was defined as a carrier of two, one or no copies of the haplotype (rs2494732(C)-rs1130233(A)). Multiple linear regressions were conducted to test the effect of the genetic variability and cannabis use (and their interaction) on cognitive performance. RESULTS: An effect of the AKT1 haplotype was found on attention scores: individuals with two copies of the haplotype performed better (ß=0.18, p<0.001 (adjusted for false discovery rate)), while neither cannabis nor the AKT1-cannabis interaction was associated with attention. No effect of AKT1, cannabis or the AKT1-cannabis interaction was found on verbal memory or working memory. CONCLUSIONS: Our study provides additional evidence that AKT1 modulates cognitive performance. However, in our non-clinical sample, the previously reported interaction between cannabis use and the AKT1 gene was not replicated.