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This dataset contains three repeated measures of a standard reward-based reinforcement-learning task from 29 healthy male individuals who participated in three experimental sessions exploring cognitive placebo effects on reward learning. The dataset includes behavioural data (accuracy, reaction times) during learning and transfer, estimates of model-free computational analysis, self-reported arousal values, and expectations about the interventions' efficacy. The data were collected in 2014 at the Department of Clinical Neurophysiology, University Medical Center Goettingen, Germany. The data collection and formal analysis used a triple-blind study design as participants, operator and analyst were unaware of conditions. A github repository contains data and analyses for the paper "Placebo Intervention Enhances Reward Learning in Healthy Individuals". The dataset can be used for further analysis, reference, validation studies, teaching purposes, and collaborative research. [ABSTRACT FROM AUTHOR]

The article offers information on a research related to large-scale networks in the brain and their significance conducted by R.M. Braga and colleagues. It mentions that these networks are commonly referred to as intrinsic connectivity networks (ICN's). It informs that ICNs are extracted by functional connectivity analyses of functional magnetic resonance imaging data using techniques like seed-based correlation maps.

Aberrant belief updating due to misestimation of uncertainty and an increased perception of the world as volatile (i.e., unstable) has been found in autism and psychotic disorders. Pupil dilation tracks events that warrant belief updating, likely reflecting the adjustment of neural gain. However, whether subclinical autistic or psychotic symptoms affect this adjustment and how they relate to learning in volatile environments remains to be unraveled. We investigated the relationship between behavioral and pupillometric markers of subjective volatility (i.e., experience of the world as unstable), autistic traits, and psychotic-like experiences in 52 neurotypical adults with a probabilistic reversal learning task. Computational modeling revealed that participants with higher psychotic-like experience scores overestimated volatility in low-volatile task periods. This was not the case for participants scoring high on autistic-like traits, who instead showed a diminished adaptation of choice-switching behavior in response to risk. Pupillometric data indicated that individuals with higher autistic- or psychotic-like trait and experience scores differentiated less between events that warrant belief updating and those that do not when volatility was high. These findings are in line with misestimation of uncertainty accounts of psychosis and autism spectrum disorders and indicate that aberrancies are already present at the subclinical level., (© 2023. The Author(s).)

Mind wandering (MW) is a heterogeneous construct involving task-unrelated thoughts. Recently, the interest in modulating MW propensity via non-invasive brain stimulation techniques has increased. Single-session transcranial direct current stimulation (tDCS) in healthy controls has led to mixed results in modulating MW propensity, possibly due to methodological heterogeneity. Therefore, our aim was to conduct a systematic meta-analysis to examine the influence of left dorsolateral prefrontal cortex (lDLPFC) and right inferior parietal lobule (rIPL) targeted tDCS on MW propensity. Importantly, by computational modeling of tDCS-induced electric fields, we accounted for differences in tDCS-dose across studies that varied strongly in their applied methodology. Fifteen single-session, sham-controlled tDCS studies published until October 2021 were included. All studies involved healthy adult participants and used cognitive tasks combined with MW thought-probes. Heterogeneity in tDCS electrode placement, stimulation polarity and intensity were controlled for by means of electric field simulations, while overall methodological quality was assessed via an extended risk of bias (RoB) assessment. We found that RoB was the strongest predictor of study outcomes. Moreover, the rIPL was the most promising cortical area for influencing MW, with stronger anodal electric fields in this region being negatively associated with MW propensity. Electric field strength in the lDLPFC was not related to MW propensity. We identified several severe methodological problems that could have contributed to overestimated effect sizes in this literature, an issue that needs urgent attention in future research in this area. Overall, there is no reliable evidence for tDCS influencing MW in the healthy. However, the analysis also revealed that increasing neural excitability in the rIPL via tDCS might be associated with reduced MW propensity. In an exploratory approach, we also found some indication that targeting prefrontal regions outside the lDLPFC with tDCS could lead to increased MW propensity., Competing Interests: Declaration of Competing Interest None., (Copyright © 2023. Published by Elsevier Inc.)

Introduction: Pavlovian bias is an innate motivational tendency to approach rewards and remain passive in the face of punishment. The relative reliance on Pavlovian valuation has been found to increase when the perceived control over environmental reinforcers is compromised, leading to behavior resembling learned helplessness (LH)., Methods: Sixty healthy young adults underwent a Go-NoGo reinforcement learning task and received anodal high-definition transcranial direct current stimulation (HD-tDCS) over the medial prefrontal/dorsal anterior cingulate cortex in our randomized, double-blind, sham- controlled study. Furthermore, we evaluated changes in cue-locked mid-frontal theta power derived from simultaneous electroencephalography (EEG). We hypothesized that active stimulation would reduce Pavlovian bias during manipulation of outcome controllability, and the effect would be accompanied by stronger mid-frontal theta activity, representing arbitration between choice strategies in favor of instrumental relative to Pavlovian valuation., Results: We found a progressive decrease in Pavlovian bias during and after loss of control over feedback. Active HD-tDCS counteracted this effect while not affecting the mid-frontal theta signal., Discussion: The results were at odds with our hypotheses but also with previous findings reporting LH-like patterns during and after loss of control without brain stimulation. The discrepancy may be related to different protocols for the controllability manipulation. We argue that the subjective evaluation of task controllability is crucial in mediating the balance between Pavlovian and instrumental valuation during reinforcement learning and that the medial prefrontal/dorsal anterior cingulate cortex is a key region in this respect. These findings have implications for understanding the behavioral and neural underpinnings of LH in humans., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Sedlinská, Bolte, Melsæter, Mittner and Csifcsák.)

Mind wandering is ubiquitous in everyday life and has a pervasive and profound impact on task-related performance. A range of psychological processes have been proposed to underlie these performance-related decrements, including failures of executive control, volatile information processing, and shortcomings in selective attention to critical task-relevant stimuli. Despite progress in the development of such theories, existing descriptive analyses have limited capacity to discriminate between the theories. We propose a cognitive-model based analysis that simultaneously explains self-reported mind wandering and task performance. We quantitatively compare six explanations of poor performance in the presence of mind wandering. The competing theories are distinguished by whether there is an impact on executive control and, if so, how executive control acts on information processing, and whether there is an impact on volatility of information processing. Across two experiments using the sustained attention to response task, we find quantitative evidence that mind wandering is associated with two latent factors. Our strongest conclusion is that executive control is impaired: increased mind wandering is associated with reduced ability to inhibit habitual response tendencies. Our nuanced conclusion is that executive control deficits manifest in reduced ability to selectively attend to the information value of rare but task-critical events., (© 2022. The Author(s).)

Cognitive neuroscience has witnessed a surge of interest in investigating the neural correlates of the mind when it drifts away from an ongoing task and the external environment. To that end, functional neuroimaging research has consistently implicated the default mode network (DMN) and frontoparietal control network (FPCN) in mind-wandering. Yet, it remains unknown which subregions within these networks are necessary and how they facilitate mind-wandering. In this review, we synthesize evidence from lesion, transcranial direct current stimulation (tDCS), and intracranial electroencephalogram (iEEG) studies demonstrating the causal relevance of brain regions, and providing insights into the neuronal mechanism underlying mind-wandering. We propose that the integration of complementary approaches is the optimal strategy to establish a comprehensive understanding of the neural basis of mind-wandering., Competing Interests: Declaration of interests No interests are declared., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

This study was conducted to provide a better understanding of the role of electric field strength in the production of aftereffects in resting state scalp electroencephalography by repetitive transcranial magnetic stimulation (rTMS) in humans. We conducted two separate experiments in which we applied rTMS over the left parietal-occipital region. Prospective electric field simulation guided the choice of the individual stimulation intensities. In the main experiment, 16 participants received rhythmic and arrhythmic rTMS bursts at between ca. 20 and 50 mv / mm peak absolute electric field intensities. In the control experiment, another group of 16 participants received sham rTMS. To characterize the aftereffects, we estimated the alpha power (8-14 Hz) changes recorded in the inter-burst intervals, i.e., from 0.2 to 10 s after rTMS. We found aftereffects lasting up to two seconds after stimulation with ca. 35  mV / mm . Relative to baseline, alpha power was significantly reduced by the arrhythmic protocol, while there was no significant change with the rhythmic protocol. We found no significant long-term, i.e., up to 10-second, differences between the rhythmic and arrhythmic stimulation, or between the rhythmic and sham protocols. Weak arrhythmic rTMS induced short-lived alpha suppression during the inter-burst intervals., (Copyright © 2021 IBRO. Published by Elsevier Ltd. All rights reserved.)

Mind wandering reflects the shift in attentional focus from task-related cognition driven by external stimuli toward self-generated and internally-oriented thought processes. Although such task-unrelated thoughts (TUTs) are pervasive and detrimental to task performance, their underlying neural mechanisms are only modestly understood. To investigate TUTs with high spatial and temporal precision, we simultaneously measured fMRI, EEG, and pupillometry in healthy adults while they performed a sustained attention task with experience sampling probes. Features of interest were extracted from each modality at the single-trial level and fed to a support vector machine that was trained on the probe responses. Compared to task-focused attention, the neural signature of TUTs was characterized by weaker activity in the default mode network but elevated activity in its anticorrelated network, stronger functional coupling between these networks, widespread increase in alpha, theta, delta, but not beta, frequency power, predominantly reduced amplitudes of late, but not early, event-related potentials, and larger baseline pupil size. Particularly, information contained in dynamic interactions between large-scale cortical networks was predictive of transient changes in attentional focus above other modalities. Together, our results provide insight into the spatiotemporal dynamics of TUTs and the neural markers that may facilitate their detection., Competing Interests: Declaration of Competing Interest None., (Copyright © 2020. Published by Elsevier Inc.)

Repetitive transcranial magnetic stimulation (rTMS) is a potent tool for modulating endogenous oscillations in humans. The current standard method for rTMS defines the stimulation intensity based on the evoked liminal response in the visual or motor system (e.g., resting motor threshold). The key limitation of the current approach is that the magnitude of the resulting electric field remains elusive. A better characterization of the electric field strength induced by a given rTMS protocol is necessary in order to improve the understanding of the neural mechanisms of rTMS. In this study we used a novel approach, in which individualized prospective computational modeling of the induced electric field guided the choice of stimulation intensity. We consistently found that rhythmic rTMS protocols increased neural synchronization in the posterior alpha frequency band when measured simultaneously with scalp electroencephalography. We observed this effect already at electric field strengths of roughly half the lowest conventional field strength, which is 80% of the resting motor threshold. We conclude that rTMS can induce immediate electrophysiological effects at much weaker electric field strengths than previously thought.

The sustained attention to response task (SART) has been the primary method of studying the phenomenon of mind wandering. We develop and experimentally test the first integrated cognitive process model that quantitatively explains all stationary features of behavioral performance in the SART. The model assumes that performance is generated by a competitive race between a stimulus-related decision process and a stimulus-unrelated rhythmic response process. We propose that the stimulus-unrelated process entrains to timing regularities in the task environment, and is unconditionally triggered as a habit or 'insurance policy' to protect against the deleterious effects of mind wandering on ongoing task performance. For two SART experiments the model provided a quantitatively precise account of a range of previously reported trends in choice, response time and self-reported mind wandering data. It also accounted for three previously unidentified features of response time distributions that place critical constraints on cognitive models of performance in situations when people might engage in task-unrelated thoughts. Furthermore, the parameters of the rhythmic race model were meaningfully associated with participants' self-reported distraction, even though the model was never informed by these data. In a validation test, we disrupted the latent rhythmic component with a manipulation of inter-trial-interval variability, and showed that the architecture of the model provided insight into its counter-intuitive effect. We conclude that performance in the presence of mind wandering can be conceived as a competitive latent decision vs. rhythmic response process. We discuss how the rhythmic race model is not restricted to the study of distraction or mind wandering; it is applicable to any domain requiring repetitive responding where evidence accumulation is assumed to be an underlying principle of behavior., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Background: Transcranial direct current stimulation (tDCS) above the left dorsolateral prefrontal cortex (lDLPFC) has been widely used to improve symptoms of major depressive disorder (MDD). However, the effects of different stimulation protocols in the entire frontal lobe have not been investigated in a large sample including patient data., Methods: We used 38 head models created from structural magnetic resonance imaging data of 19 healthy adults and 19 MDD patients and applied computational modeling to simulate the spatial distribution of tDCS-induced electric fields (EFs) in 20 frontal regions. We evaluated effects of seven bipolar and two multi-electrode 4 × 1 tDCS protocols., Results: For bipolar montages, EFs were of comparable strength in the lDLPFC and in the medial prefrontal cortex (MPFC). Depending on stimulation parameters, EF cortical maps varied to a considerable degree, but were found to be similar in controls and patients. 4 × 1 montages produced more localized, albeit weaker effects., Limitations: White matter anisotropy was not modeled. The relationship between EF strength and clinical response to tDCS could not be evaluated., Conclusions: In addition to lDLPFC stimulation, excitability changes in the MPFC should also be considered as a potential mechanism underlying clinical efficacy of bipolar montages. MDD-associated anatomical variations are not likely to substantially influence current flow. Individual modeling of tDCS protocols can substantially improve cortical targeting. We make recommendations for future research to explicitly test the contribution of lDLPFC vs. MPFC stimulation to therapeutic outcomes of tDCS in this disorder., (Copyright © 2018 Elsevier B.V. All rights reserved.)

The role of the default-mode network (DMN) in the emergence of mind wandering and task-unrelated thought has been studied extensively. In parallel work, mind wandering has been associated with neuromodulation via the locus coeruleus (LC) norepinephrine (LC-NE) system. Here we propose a neural model that links the two systems in an integrative framework. The model attempts to explain how dynamic changes in brain systems give rise to the subjective experience of mind wandering. The model implies a neural and conceptual distinction between an off-focus state and an active mind-wandering state and provides a potential neural grounding for well-known cognitive theories of mind wandering. Finally, the proposed neural model of mind wandering generates precise, testable predictions at neural and behavioral levels., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Background: Several studies have demonstrated the effect of guided Internet-based cognitive behavioral therapy (ICBT) for depression. However, ICBT is not suitable for all depressed patients and there is a considerable level of nonresponse. Research on predictors and moderators of outcome in ICBT is inconclusive., Objective: This paper explored predictors of response to an intervention combining the Web-based program MoodGYM and face-to-face therapist guidance in a sample of primary care patients with mild to moderate depressive symptoms., Methods: Participants (N=106) aged between 18 and 65 years were recruited from primary care and randomly allocated to a treatment condition or to a delayed treatment condition. The intervention included the Norwegian version of the MoodGYM program, face-to-face guidance from a psychologist, and reminder emails. In this paper, data from the treatment phase of the 2 groups was merged to increase the sample size (n=82). Outcome was improvement in depressive symptoms during treatment as assessed with the Beck Depression Inventory-II (BDI-II). Predictors included demographic variables, severity variables (eg, number of depressive episodes and pretreatment depression and anxiety severity), cognitive variables (eg, dysfunctional thinking), module completion, and treatment expectancy and motivation. Using Bayesian analysis, predictors of response were explored with a latent-class approach and by analyzing whether predictors affected the slope of response., Results: A 2-class model distinguished well between responders (74%, 61/82) and nonresponders (26%, 21/82). Our results indicate that having had more depressive episodes, being married or cohabiting, and scoring higher on a measure of life satisfaction had high odds for positively affecting the probability of response. Higher levels of dysfunctional thinking had high odds for a negative effect on the probability of responding. Prediction of the slope of response yielded largely similar results. Bayes factors indicated substantial evidence that being married or cohabiting predicted a more positive treatment response. The effects of life satisfaction and number of depressive episodes were more uncertain. There was substantial evidence that several variables were unrelated to treatment response, including gender, age, and pretreatment symptoms of depression and anxiety., Conclusions: Treatment response to ICBT with face-to-face guidance may be comparable across varying levels of depressive severity and irrespective of the presence and severity of comorbid anxiety. Being married or cohabiting, reporting higher life satisfaction, and having had more depressive episodes may predict a more favorable response, whereas higher levels of dysfunctional thinking may be a predictor of poorer response. More studies exploring predictors and moderators of Internet-based treatments are needed to inform for whom this treatment is most effective., Trial Registration: Australian New Zealand Clinical Trials Registry number: ACTRN12610000257066; https://www.anzctr.org.au/trial_view.aspx?id=335255 (Archived by WebCite at http://www.webcitation.org/6GR48iZH4).

Introduction: There is growing evidence from neuro-computational studies that instrumental learning involves the dynamic interaction of a computationally rigid, low-level striatal and a more flexible, high-level prefrontal component., Methods: To evaluate the role of the prefrontal cortex in instrumental learning, we applied anodal transcranial direct current stimulation (tDCS) optimized for the left dorsolateral prefrontal cortex, by using realistic MR-derived finite element model-based electric field simulations. In a study with a double-blind, sham-controlled, repeated-measures design, sixteen male participants performed a probabilistic learning task while receiving anodal and sham tDCS in a counterbalanced order., Results: Compared to sham tDCS, anodal tDCS significantly increased the amount of maladaptive shifting behavior after optimal outcomes during learning when reward probabilities were highly dissociable. Derived parameters of the Q-learning computational model further revealed a significantly increased model parameter that was sensitive to random action selection in the anodal compared to the sham tDCS session, whereas the learning rate parameter was not influenced significantly by tDCS., Conclusion: These results congruently indicate that prefrontal tDCS during instrumental learning increased randomness of choice, possibly reflecting the influence of the cognitive prefrontal component., (Copyright © 2014 Elsevier Ltd. All rights reserved.)