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In recent years, a growing body of research uses Evidence Accumulation Models (EAMs) to study individual differences and group effects. This endeavor is challenging because fitting EAMs requires constraining one of the EAM parameters to be equal for all participants, which makes a strong and possibly unlikely assumption. Moreover, if this assumption is violated, differences or lack thereof may be wrongly found. To overcome this limitation, in this study, we introduce a new method that was originally suggested by van Maanen & Miletić (2021), which employs Bayesian hierarchical estimation. In this new method, we set the scale at the population level, thereby allowing for individual and group differences, which is realized by de facto fixing a population-level hyper-parameter through its priors. As proof of concept, we ran two successful parameter recovery studies using the Linear Ballistic Accumulation model. The results suggest that the new method can be reliably used to study individual and group differences using EAMs. We further show a case in which the new method reveals the true group differences whereas the classic method wrongly detects differences that are truly absent.

Rumination, which can be studied through its associated attentional biases, and is a part of the RDoC Negative Valence Systems constructs of Loss, has been proposed as a key transdiagnostic feature in depression. The current study uses eye tracking measurements to explore how different levels of brooding and reflection rumination interact with attentional biases in a non-clinical sample of high and low ruminators. Methodology: 123 adults were administered questionnaires of rumination, depression and participated in passive viewing task in which they watched sets of angry, happy, sad and neutral faces, while their eye movements were tracked. Findings indicate greater sustained attention toward sad and angry faces and away from happy faces among non-clinical individuals with high levels of brooding rumination, even when controlling for depression scores. The study adds further evidence that brooding rumination and attentional biases to negative stimuli are associated with one another. Behavioral parameters such as attention bias to help us to distinguish high ruminators among non-clinical sample.

The ability to learn abstract generalized structures of tasks is crucial for humans to adapt to changing environments and novel tasks. In a series of five experiments, we investigated this ability using a Rapid Instructed Task Learning paradigm (RITL) comprising short miniblocks, each involving two novel stimulus-response rules. Each miniblock included (a) instructions for the novel stimulus-response rules, (b) a NEXT phase involving a constant (familiar) intervening task (0–5 trials), (c) execution of the newly instructed rules (2 trials). The results show that including a NEXT phase (and hence, a prospective memory demand) led to relatively more robust abstract learning as indicated by increasingly faster responses with experiment progress. Multilevel modeling suggests that the prospective memory demand was just another aspect of the abstract task structure which has been learned.

Lifestyle dietary interventions are an essential practice in treating obesity, hence neural factors that may assist in predicting individual treatment success are of great significance. Here, in a prospective, open-label, three arms study, we examined the correlation between brain resting-state functional connectivity measured at baseline and weight loss following 6 months of lifestyle intervention in 92 overweight participants. We report a robust subnetwork composed mainly of sensory and motor cortical regions, whose edges correlated with future weight loss. This effect was found regardless of intervention group. Importantly, this main finding was further corroborated using a stringent connectivity-based prediction model assessed with cross-validation thus attesting to its robustness. The engagement of senso-motor regions in this subnetwork is consistent with the over-sensitivity to food cues theory of weight regulation. Finally, we tested an additional hypothesis regarding the role of brain-gastric interaction in this subnetwork, considering recent findings of a cortical network synchronized with gastric activity. Accordingly, we found a significant spatial overlap with the subnetwork reported in the present study. Moreover, power in the gastric basal electric frequency within our reported subnetwork negatively correlated with future weight loss. This finding was specific to the weight loss related subnetwork and to the gastric basal frequency. These findings should be further corroborated by combining direct recordings of gastric activity in future studies. Taken together, these intriguing results may have important implications for our understanding of the etiology of obesity and the mechanism of response to dietary intervention.

Feeling is an important aspect of core personality traits and affective-style. Here we implemented a new signal-detection-theory based model for feeling generation, involving two parameters: report-criterion (c), the level above which enough emotional evidence has gathered for intense feeling to appear, and evidence-differentiation (da), the ability to emotionally differentiate between (negative) triggers of varying intensity. Results indicate that a low c was related to Neuroticism but not to affective-style, yet a low da was related to limited access to emotion regulation strategies, but not to personality traits.

A key goal of model-based cognitive neuroscience is to estimate the trial-by-trial fluctuations of cognitive model parameters in order to link these fluctuations to brain signals. However, previously developed methods are limited by being difficult to implement, time-consuming, or model-specific. Here, we propose an easy, efficient and general approach to estimating trial-wise changes in parameters: Leave-One-Trial-Out (LOTO). The rationale behind LOTO is that the difference between parameter estimates for the complete dataset and for the dataset with one omitted trial reflects the parameter value in the omitted trial. We show that LOTO is superior to estimating parameter values from single trials and compare it to previously proposed approaches. Furthermore, the method makes it possible to distinguish true variability in a parameter from noise and from other sources of variability. In our view, the practicability and generality of LOTO will advance research on tracking fluctuations in latent cognitive variables and linking them to neural data.

The ability to efficiently perform actions immediately following instructions and without prior practice has previously been termed Rapid Instructed Task Learning (RITL). In addition, it was found that instructions are so powerful that they can produce automatic effects, reflected in activation of the instructions in an inappropriate task context. RITL is hypothesized to rely on limited working memory (WM) resources for holding not-yet implemented task rules. Similarly, automatic effects of instructions presumably reflect the operation of task rules kept in WM. Therefore, both were predicted to be influenced by WM load. However, while the involvement of WM in RITL is implicated from prior studies, evidence regarding WM involvement in instructions-based automaticity is mixed. In the current study, we manipulated WM load by increasing the number of novel task rules to be held in WM towards performance in the NEXT paradigm. In this task, participants performed a series of novel tasks presented in mini-blocks, each comprising a) instructions of novel task rules; b) a NEXT phase measuring the automatic activation of these instructed rules, in which participants advance the screen using a key-press; and c) a GO phase in which the new rules are first implemented and RITL is measured. In three experiments, we show a dissociation: While RITL (rule implementation) was impaired by increased WM load, the automatic effects of instructions were not robustly influenced by WM load. Theoretical implications are discussed.

Few studies have addressed action control training. In the current study, participants were trained over 19 days in an adaptive training task that demanded constant switching, maintenance and updating of novel action rules. Participants completed an executive functions battery before and after training that estimated processing speed, working memory updating, set-shifting, response inhibition and fluid intelligence. Participants in the training group showed greater improvement than a no-contact control group in processing speed, indicated by reduced reaction times in speeded classification tasks. No other systematic group differences were found across the different pre-post measurements. Ex-Gaussian fitting of the reaction-time distribution revealed that the reaction time reduction observed among trained participants was restricted to the right tail of the distribution, previously shown to be related to working memory. Furthermore, training effects were only found in classification tasks that required participants to maintain novel stimulus-response rules in mind, supporting the notion that the training improved working memory abilities. Training benefits were maintained in a 10-month follow-up, indicating relatively long-lasting effects. The authors conclude that training improved action-related working memory abilities.

Two experiments examined the relation between mindfulness practice and cognitive rigidity by using a variation of the Einstellung water jar task. Participants were required to use three hypothetical jars to obtain a specific amount of water. Initial problems were solvable by the same complex formula, but in later problems ("critical" or "trap" problems) solving was possible by an additional much simpler formula. A rigidity score was compiled through perseverance of the complex formula. In Experiment 1, experienced mindfulness meditators received significantly lower rigidity scores than non-meditators who had registered for their first meditation retreat. Similar results were obtained in randomized controlled Experiment 2 comparing non-meditators who underwent an eight meeting mindfulness program with a waiting list group. The authors conclude that mindfulness meditation reduces cognitive rigidity via the tendency to be "blinded" by experience. Results are discussed in light of the benefits of mindfulness practice regarding a reduced tendency to overlook novel and adaptive ways of responding due to past experience, both in and out of the clinical setting.

The notion that anger is linked to approach motivation received support from behavioral studies, which measured various motor responses to angering stimuli. However, none of these studies examined full body motions which characterize many if not most everyday instances of anger. The authors incorporate a novel behavioral motor task that tests motivational direction by measuring the reaction times of stepping forward and backward in response to the words "towards" and "away". The results show that, relative to anxiety and control conditions, anger induction resulted in a steeper approach-avoidance RT gradient which was shifted in favor of approach.

Studies have shown that task sets could be configured endogenously (i.e., on the basis of memory) according to an explicit sequence or exogenously according to a task cue. In two experiments, we examined whether an implicitly learned sequence could facilitate task set configuration without participants' intention. These experiments led to opposite conclusions regarding this question, but their methodology made it impossible to distinguish between the interpretations. Wealtered the task-switching paradigm by embedding a hidden task sequence, while randomizing all other aspects, including perceptual (i.e., task cues) and motor elements. We found that a sequence of tasks, proper, was learned implicitly and that the memory of that sequence endogenously facilitated task decision processes without the participants' explicit knowledge. [ABSTRACT FROM AUTHOR]