Eyeblink rate, a putative dopamine marker, predicts negative reinforcement learning by tDCS of the dlPFC

Learning bias predicts fear acquisition under stress but not cognitive flexibility

Individuals differ in their ability to learn from reinforcement and in avoiding punishment, which can be measured by the Probabilistic Selection Task (PST). Recently, some studies have demonstrated that this learning bias is regulated by the dopaminergic system, and that stress can differentially affect the use of positive (i.e., reinforcement) and negative (i.e., avoiding punishment) feedback. The current two studies examined whether performance on the PST can predict measures of goal-directed behaviour as assessed by a cognitive flexibility task (Wisconsin Card Sorting Test) and the acquisition of fear responses, when individuals are exposed to a stressor (Socially Evaluated Cold Pressor Test). A total of 26 and 59 healthy participants completed Experiments I and II, respectively. In those who were best at learning from reinforcement, stress increased the processing (i.e., higher skin conductance responses) of non-threatening stimuli during fear acquisition compared to the non-stressful condition, which was not recapitulated in those who were best at avoiding punishment. Additionally, PST performance did not interact with stress to modulate cognitive flexibility, although stress negatively impaired this domain, consistent with previous findings. Furthermore, independent of stress, both positive and negative learning biases were correlated with cognitive flexibility errors. Our results demonstrate that the PST has predictive value for better understanding the determinants of reinforcement and avoidance learning.

Transcranial direct current stimulation for bipolar depression: systematic reviews of clinical evidence and biological underpinnings

Despite multiple available treatments for bipolar depression (BD), many patients face sub-optimal responses. Transcranial direct current stimulation (tDCS) has been advocated in the management of different conditions, including BD, especially in treatment-resistant cases. The optimal dose and timing of tDCS, the mutual influence with other concurrently administered interventions, long-term efficacy, overall safety, and biological underpinnings nonetheless deserve additional assessment. The present study appraised the existing clinical evidence about tDCS for bipolar depression, delving into the putative biological underpinnings with a special emphasis on cellular and molecular levels, with the ultimate goal of providing a translational perspective on the matter. Two separate systematic reviews across the PubMed database since inception up to August 8^th 2022 were performed, with fourteen clinical and nineteen neurobiological eligible studies. The included clinical studies encompass 207 bipolar depression patients overall and consistently document the efficacy of tDCS, with a reduction in depression scores after treatment ranging from 18% to 92%. The RCT with the largest sample clearly showed a significant superiority of active stimulation over sham. Mild-to-moderate and transient adverse effects are attributed to tDCS across these studies. The review of neurobiological literature indicates that several molecular mechanisms may account for the antidepressant effect of tDCS in BD patients, including the action on calcium homeostasis in glial cells, the enhancement of LTP, the regulation of neurotrophic factors and inflammatory mediators, and the modulation of the expression of plasticity-related genes. To the best of our knowledge, this is the first study on the matter to concurrently provide a synthesis of the clinical evidence and an in-depth appraisal of the putative biological underpinnings, providing consistent support for the efficacy, safety, and tolerability of tDCS.

Modulating hierarchical learning by high-definition transcranial alternating current stimulation at theta frequency

Considerable evidence highlights the dorsolateral prefrontal cortex (DLPFC) as a key region for hierarchical (i.e. multilevel) learning. In a previous electroencephalography (EEG) study, we found that the low-level prediction errors were encoded by frontal theta oscillations (4-7 Hz), centered on right DLPFC (rDLPFC). However, the causal relationship between frontal theta oscillations and hierarchical learning remains poorly understood. To investigate this question, in the current study, participants received theta (6 Hz) and sham high-definition transcranial alternating current stimulation (HD-tACS) over the rDLPFC while performing the probabilistic reversal learning task. Behaviorally, theta tACS induced a significant reduction in accuracy for the stable environment, but not for the volatile environment, relative to the sham condition. Computationally, we implemented a combination of a hierarchical Bayesian learning and a decision model. Theta tACS induced a significant increase in low-level (i.e. probability-level) learning rate and uncertainty of low-level estimation relative to sham condition. Instead, the temperature parameter of the decision model, which represents (inverse) decision noise, was not significantly altered due to theta stimulation. These results indicate that theta frequency may modulate the (low-level) learning rate. Furthermore, environmental features (e.g. its stability) may determine whether learning is optimized as a result.