Electroencephalography (EEG) is important in medical diagnostics and cognitive neuroscience for brain activity recording and understanding, but limited data availability restricts the application of machine learning methods for classification and prediction purposes. Therefore, our ultimate aim is to synthesize physiologically accurate EEG data using Generative Adversarial Networks (GANs). In this preliminary study, we first investigate how the choice of GAN hyperparameters influences the quality of simpler EEG-like generated signals. Thereto, we first created sinusoidal samples as target datasets with single (12 Hz), double (5, 12 Hz), or triple frequencies (5, 12, 28 Hz) and added Gaussian noise. We trained 2,592 models to generate fake sinusoidal samples and examined the effects of varying the hyperparameters batch size, learning rate of generator (LrG) and discriminator (LrD), and the number of epochs for vanilla GAN, Wasserstein GAN (WGAN), and WGAN with Gradient Penalty (WGAN-GP). We compared the distributions of relevant target and fake signal features, such as amplitude, phase, and signal-to-noise ratio, using the Kolmogorov-Smirnov test. Our results showed that WGAN-GP models had better training stability for sinusoidal sample generation compared to WGAN, and significantly outperformed vanilla GAN. Smaller batch sizes accelerated convergence at a fixed number of epochs. Matching LrG and LrD balanced networks during training. Increasing the number of epochs (up to 100) enhanced performance. We conclude that the WGAN-GP model provides the best quality signals, when hyperparameters, particularly learning rate, are well tuned. We therefore propose that effective combinations of hyperparameters enhance training stability and performance of GANs for EEG signal generation.

The sense of self is a multidimensional feature of human experience. Different dimensions of self-experience can change drastically during altered states of consciousness induced through meditation or psychedelic drugs, as well as in a variety of mental disorders. Some experienced meditation practitioners are able to modulate their sense of self deliberately, which allows for a direct comparison between an active and suspended sense of self. Meditation therefore has the potential to serve as a model-system for alterations in the sense of self. The current study aims to identify a neural marker of such meditation-induced alterations in the sense of self based on magnetoencephalography (MEG) recordings of meditation practitioners (N = 41). Participants alternated between a state of reduced sense of self, termed self-boundary dissolution, a resting state and a control meditation state of maintaining their sense of self. Machine learning methods were used to find multivariate patterns of brain activity which distinguish these states on a single-trial basis. Source band power and Lempel-Ziv complexity features allowed to predict the mental state from MEG recordings with significantly above-chance accuracy (> 0.5). The highest performance was obtained for the self-boundary dissolution versus rest classification based on Lempel-Ziv complexity, which showed an average accuracy of ~0.64 when training and testing were performed on data from the same individual (within-participant prediction) and ~0.57 when models trained on one group of individuals were tested on different participants (across-participant prediction). Potential applications include decoded neurofeedback, for example, for clinical treatments of disorders of the sense of self, or for assistance in meditation training.

A central challenge in neuroscience is to establish meaningful links between subjective experience and brain activity. Neurofeedback of meditation states has been proposed as a way to address this challenge by creating a real-time loop between neural signals and first-person experience. Here, the introspective and self-regulation capacities of experienced meditators are harnessed to dynamically alter consciousness while exploring relationships with a feedback signal. Previous work using visual feedback of posterior cingulate gamma activity demonstrated a negative relationship with moment-to-moment experience in effortless awareness. In a first confirmatory study we replicate this neuro-experiential correspondance and ask whether it generalizes to auditory feedback, whether neurofeedback supports regulation beyond meditation alone, and to what extent observed effects reflect neural rather than non-neural sources. In a second exploratory study, we evaluate the feasibility of regulating and establishing neuro-experiential correspondances for three additional neural markers (source localized alpha, beta and theta power). Across 17 (study 1) and 12 (study 2) high-density EEG sessions, experienced meditators (n=9 study 1 and n=4 study 2) received visual and auditory feedback (study 1) or only auditory feedback (study 2) of source-localized brain activity. Participants were blind to which signal direction corresponded to deeper meditation, which was randomly flipped across 12 repeated trials. In each trial they identified the direction by comparing their meditation experience to the feedback. Gamma feedback (study 1) showed significantly above-chance accuracy for identifying the expected feedback direction, both for auditory and visual feedback. Feedback based on alpha, beta and theta power (study 2) did not yield significant effects. Across studies, phenomenological interviews revealed differential patterns of enacted meditative gestures, with “letting go of effort and control” dominant in the gamma condition, consistent with the previous characterization of effortless awareness. For the gamma condition, follow-up whole-brain source localization showed that the posterior cingulate cortex contributed only marginally to the effect and additional control analyses suggested potential muscular confounds. We thus replicate the correspondence between effortless awareness and posterior cingulate gamma activity, but also highlight the risk that our own and previous findings are driven by muscle activity. The absence of reliable neuro-experiential associations for other frequency bands less prone to muscle contamination further strengthens these concerns and highlights the intricacies in establishing real-time correspondences between brain activity and subjective experience.

Objectives Mindfulness meditation is widely recognized for its individual psychological benefits, yet its interpersonal effects remain underexplored. This daily diary study examined whether and how mindfulness practice by one romantic partner influences the emotional well-being of their non-meditating partner. Methods Using a randomized controlled design, couples were assigned to either an 8-week mindfulness-based course condition (MBCC) or an active control—a positive psychology course condition (PPCC)—with only one partner participating in the intervention. Results Results from 32 MBCC couples and 27 PPCC couples indicated that course participants and their partners in the MBCC exhibited reductions in negative emotion over time. In addition, MBCC partners showed a significant increase in the mindfulness facet of nonreactivity, which was not observed in partners in the PPCC. Further analysis revealed that MBCC partners’ negative emotion was predicted by the previous day nonreactivity of their course participating partners. Conclusions These results highlight that nonreactivity may both be an important interpersonal outcome and mechanism of meditation interventions. Future research is needed to better understand the precise role of nonreactivity in relationships.

Thinking at the Edge is a philosophical method for systematically deepening thinking and exploring concepts from many different angles. The cognitive mechanisms through which Thinking at the Edge work are less clear. To explore these, this article will place Thinking at the Edge alongside another method that uses the body to think critically: Tibetan monastic debate. Tibetan monastic debate is a systematic way to explore topics focused on uncovering contradictions, and it does so in a way that uses the body as a method of expression and possibly also thinking. The neural and cognitive mechanisms underlying Tibetan monastic debate have recently begun to be elucidated. This article will start to analyse Thinking at the Edge, another embodied method, in a similar way. To do so, we will first describe each of these practices individually, and then describe their similarities and differences in terms of associated cognitive and affective mechanisms, including memory, attention, empathy and reasoning. We will give suggestions for a concrete research agenda that can verify the hypothesized cognitive mechanisms, and thereby clarify how both of these practices shape thinking.

Understanding the mechanisms underlying complex behaviours--such as reading, decision-making, and human-animal interactions--requires theoretical frameworks that capture real-world complexity while remaining interpretable. While psychological and cognitive sciences seem well-positioned to provide such frameworks, they are facing a confidence crisis. A key issue is the lack of robust, precise theories capable of guiding research. To address this, it has been suggested that computational or mathematical models should be developed to formalise tentative theories. Mathematical psychology and computational modelling offer the necessary tools and competencies, yet they are often either too opaque for domain experts without computational expertise or too simplistic for complex behaviours, frequently focusing on toy examples or highly controlled tasks. Here, we present key insights from a workshop where interdisciplinary teams tackled the challenge of modeling the mechanisms underlying complex behaviours through case studies on reading comprehension, autism-related categorisation, negotiation, and human-wildlife conflict. Five key considerations emerged: (1) defining the problem, (2) forming and maintaining a team, (3) selecting the modelling approach(es), (4) implementing the model(s), and (5) making practical decisions and evaluating the model(s). These aspects are interdependent, each influencing the others. Addressing the challenge of modelling complex behaviour requires a community approach: fostering interdisciplinary collaboration, adopting transparent modelling practices, and embracing iterative refinement. By bridging theoretical and practical gaps, computational modelling can move beyond simplified problems to better capture real-world cognition and behaviour.

It is possible to generate artificial EEG signals using generative adversarial networks (GANs), but the physiological plausibility of these signals is not always considered, even though plausibility is important for the trustworthiness of generated EEG. Here, for the first time, we investigate how two key factors, input noise type (white vs. 1/f) and event-related potential (ERP)-based penalties, affect the plausibility of EEG trials generation, using a Wasserstein GAN with gradient penalty (WGAN-GP). ERP penalties were introduced as loss terms to penalize excessive high-frequency oscillations, thereby suppressing them during training. We evaluated physiological plausibility through visual inspection of ERP waveforms and power spectra (PS), statistical comparisons of EEG features (bandpower, entropy, P3 amplitude and latency, Petrosian fractal dimension, and Hjorth complexity), dimensional similarity by principal component analysis, t-distributed stochastic neighbor embedding, kernel density estimation, and decomposition of periodic and aperiodic components. Results show that WGAN-GP models using 1/f noise input preserved spectral characteristics better than white noise models, which introduced high-frequency oscillations. ERP-based penalties reduced these oscillations in white noise models, especially the 0.5-5 Hz bandpass-filtered ERP penalty, improving ERP waveforms and PS. However, ERP penalties with 1/f noise models sometimes disrupted the PS. In summary, using white noise and a 0.5-5 Hz passband penalty best reproduced ERP waveforms and PS, while using 1/f noise and a 0.5-3 Hz passband penalty achieved the most physiologically plausible feature distributions. There is a trade-off between learning time and frequency domain features. Input noise and ERP penalties must be aligned with the intended application.

In this study, we set out to examine whether monastic debate practice can help with emotion regulation and reduce the experience of negative affect. Research on traditional contemplative practices—including mindfulness, loving-kindness meditation, and yoga—shows that they influence emotion regulation and emotional experience. However, systematic reasoning, appraisal, and emotion regulation in a social context are not usually part of these practices. Here, we investigated another contemplative practice called \textit{Monastic Debate}, a Buddhist practice based purely on logic and reasoning that follows stringent rules established by Indian and later Tibetan masters. Monastic debate is a practice in which the practitioner seeks to improve their understanding of Buddhist philosophy by engaging in a precisely described process of reasoning in interaction with one or more others. We recruited novice practitioners (non-monks) from a month-long winter debate retreat. During the experiment, participants completed the Difficulties in Emotion Regulation Scale (DERS) and the Positive and Negative Affect Schedule (PANAS). We observed a significant reduction in difficulty regulating emotions in our retreat group compared to the control group. Particularly, three subscales of DERS including nonacceptance, impulse and strategies showed a significant reduction for retreat group in comparison to control group. We did not observe any significant differences in positive or negative emotional experiences between the retreat and control groups. The results suggest that the logical ability developed in a non-monastic population by participating in a one-month monastic debate practice can help improve the ability to regulate emotions.

Self-referential processing has been shown to increase spontaneous thoughts and impair memory performance relative to processing non-self-related information. However, it remains unclear whether increased vulnerability to depression interacts with self-referential processing to exacerbate maladaptive spontaneous thinking and further impair cognitive performance. In the present study, 46 participants (Mage = 23.65 years, 67.4

A recent method gaining influence in social neuroscience is “hyperscanning”: the simultaneous recording of two or more participants’ brains. As inter-brain synchronization (IBS) in EEG has been reported during an increasing number of social behaviors and across brain regions and frequencies, new questions have emerged about whether this synchronization reflects an active exchange of information mediated by the coupling of sensorimotor and perceptual systems across individuals, or whether it reflects incidental similarities in brain response to shared stimuli and common task demands. To help disentangle the different interpretations of IBS in EEG, we review the various experimental design and analysis choices which could potentially explain different findings. Specifically, we build on previous suggestions that findings may depend on different levels of in(ter)dependence and timing demands in various social tasks. We also suggest standard practices in experimental design and analysis to control for different interpretations of IBS while also making these interpretations explicit.

Coordinating actions with others is thought to require Theory of Mind (ToM): the ability to take perspective by attributing underlying intentions and beliefs to observed behavior. However, researchers have yet to establish a causal role for specific cognitive processes in coordinated action. Since working memory load impairs ToM in single-participant paradigms, we tested whether load manipulation affects two-person coordination. We used EEG to measure P3, an assessment of working memory encoding, as well as inter-brain synchronization (IBS), which is thought to capture mutual adjustment of behavior and mental states during coordinated action. In a computerized coordination task, dyads were presented with novel abstract images and tried selecting the same image, with selections shown at the end of each trial. High working memory load was implemented by a concurrent n-back task. Compared with a low-load control condition, high load significantly diminished coordination performance and P3 amplitude. A significant relationship between P3 and performance was found. Load did not affect IBS, nor did IBS affect performance. These findings suggest a causal role for working memory in two-person coordination, adding to a growing body of evidence challenging earlier claims that social alignment is domain-specific and does not require executive control in adults.

Background Major Depressive Disorder (MDD) is one of the most prevalent psychiatric disorders, and involves high relapse rates in which persistent negative thinking and rumination (i.e., perseverative cognition [PC]) play an important role. Positive fantasizing and mindfulness are common evidence-based psychological interventions that have been shown to effectively reduce PC and subsequent depressive relapse. How the interventions cause changes in PC over time, is unknown, but likely differ between the two. Whereas fantasizing may change the valence of thought content, mindfulness may operate through disengaging from automatic thought patterns. Comparing mechanisms of both interventions in a clinical sample and a non-clinical sample can give insight into the effectivity of interventions for different individuals. The current study aims to 1) test whether momentary psychological and psychophysiological indices of PC are differentially affected by positive fantasizing versus mindfulness-based interventions, 2) test whether the mechanisms of change by which fantasizing and mindfulness affect PC differ between remitted MDD versus never-depressed (ND) individuals, and 3) explore potential moderators of the main effects of the two interventions (i.e., what works for whom). Methods In this cross-over trial of fantasizing versus mindfulness interventions, we will include 50 remitted MDD and 50 ND individuals. Before the start of the measurements, participants complete several individual characteristics. Daily-life diary measures of thoughts and feelings (using an experience sampling method), behavioural measures of spontaneous thoughts (using the Sustained Attention to Response Task), actigraphy, physiological measures (impedance cardiography, electrocardiography, and electroencephalogram), and measures of depressive mood (self-report questionnaires) are performed during the week before (pre-) the interventions and the week during (peri-) the interventions. After a wash-out of at least one month, pre- and peri-intervention measures for the second intervention are repeated. Discussion This is the first study integrating self-reports, behavioural-, and physiological measures capturing dynamics at multiple time scales to examine the differential mechanisms of change in PC by psychological interventions in individuals remitted from multiple MDD episodes and ND individuals. Unravelling how therapeutic techniques affect PC in remitted individuals might generate insights that allows development of personalised targeted relapse prevention interventions. Trial registration ClinicalTrials.gov: NCT06145984, November 16, 2023.

In our previous study (Newman et al., in press, SCAN), dyad performance in a coordination task was shown to be amenable to manipulations of processes that underpin perspective-taking, namely working memory. When we diminished resources commonly implicated in observational perspective-taking, coordination performance also diminished. In this study, we expand on these findings to test whether performance could be improved by bolstering such resources. Participant dyads performed an iterated turn-based pure coordination task before and after one of three brief (~10 minute) interventions: focused-attention meditation (which has been shown to improve working memory), loving-kindness meditation (which increases integration of self- and other-oriented perspectives), or a neutral control. Using intermittent thought probes, we also assessed the degree to which participants across interventions engaged in mind-wandering, as well as the degree to which their attention was oriented towards either self-generated or other-generated actions. We found no significant differences in the effects of the interventions on mean coordination performance or thought probe responses. The loving-kindness meditation marginally enhanced trial-by-trial improvement in performance time-series when compared to the control. Dyads performed significantly better when other-oriented and showed greater convergence on shared decision rules over time than when self-oriented. On-task thought marginally decreased the number of trials needed for participants to align their responses, with significantly better performance on initial trials when on-task compared to when mind-wandering. This study demonstrates the particular importance of orienting attention beyond self-generated response in order to mutually adapt actions and mental states to achieve shared goals in iterated social coordination.

Depressed individuals are commonly known to suffer from low mood. Less attention is paid to their decision-making deficiencies, consisting of indecisiveness and biased judgments. Many theories attempt to explain these impairments by focusing on reduced sensitivity to reward and punishment or biased information processing. Beyond these accounts, the present study explores another scenario, namely, whether the occurrence of sticky thinking-the occurrence of thoughts that are difficult to disengage from-could be a cause for the disruption of the decision-making process in individuals with depression. To test this hypothesis, we utilized the drift-diffusion model to investigate the influence of sticky thinking on the accumulation of evidence during a task commonly used to measure spontaneous thinking-the Sustained Attention to Response Task. Results showed that the more vulnerable group-specifically those with higher levels of repetitive negative thinking and depressive symptoms, including rumination-performed less accurately than the less vulnerable group. The more vulnerable group also showed a lower speed of evidence accumulation as evidenced by a decrease in the drift rate according to the drift-diffusion model. Moreover, the more vulnerable group exhibited prolonged nondecision time when more sticky thoughts occurred. At the neural level, we found that stronger alpha-band power marked more sticky thinking. We also demonstrated that the lower drift rate in the more vulnerable group, compared to the less vulnerable group, was exclusive to moments when the alpha-band power was higher than average. In summary, the study supported the idea that sticky thinking could explain the decision-making impairment among individuals who are more vulnerable to depression and worry. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Ruminative thinking, characterized by a recurrent focus on negative and self-related thought, is a key cognitive vulnerability marker of depression and therefore a key individual difference variable. This study aimed to develop a computational cognitive model of rumination focusing on the organization and retrieval of information in memory, and how these mechanisms differ in individuals prone to rumination and individuals less prone to rumination. Adaptive Control of Thought-Rational (ACT-R) was used to develop a rumination mode by adding memory chunks with negative valence to the declarative memory. In addition, their strength of association was increased to simulate recurrent negative focus, thereby making it harder to disengage from. The ACT-R models were validated by comparing them against two empirical datasets containing data from control and depressed participants. Our general and ruminative models were able to recreate the benchmarks of free recall while matching the behavior exhibited by the control and the depressed participants, respectively. Our study shows that it is possible to build a computational theory of rumination that can accurately simulate the differences in free recall dynamics between control and depressed individuals. Such a model could enable a more fine-tuned investigation of underlying cognitive mechanisms of depression and potentially help to improve interventions by allowing them to more specifically target key mechanisms that instigate and maintain depression.

Major Depressive Disorder (MDD) is associated with cognitive control deficits that often persist after remission, affecting daily life functioning and increasing relapse risk. Residual symptoms such as negative affect and low motivation may impede cognitive control and thereby hamper goal directed behavior, and as such functioning in daily life. This study examined whether goal-directed behavior, for which we took compliance in responding to daily questionnaires in an experience sampling method (ESM) study as a proxy, 1) could reflect cognitive control allocation, 2) differs over time in individuals with remitted MDD compared to never-depressed (ND) individuals, and 3) relates to factors associated with cognitive control allocation and depressive vulnerability, including positive and negative affect, rumination, sleep quality, motivation, and lack of interest. Remitted MDD (rMDD) and ND individuals participated in three studies with daily (5 to 10) ESM measurements over a period of two weeks to four months. ESM compliance (calculated as the mean response rate and variability (SD) in response rate), inhibitory control (assessed with the Sustained Attention to Response Task), and factors related to depressive relapse vulnerability (positive and negative affect, rumination, sleep quality, motivation, and lack of interest) were assessed. Kendall’s correlations and Linear Mixed Effect models examined the relationships between ESM compliance, inhibitory control, and depressive vulnerability factors. Linear mixed effect models showed no evidence for a relationship (∆AIC below -2) between lab-based cognitive control and compliance. However, correlational analyses showed a positive relationship between mean compliance and inhibitory control [τb = .32, p=0.002; BF10=23.1] and a negative relationship between compliance variability and inhibitory control [τb = -.28, p=0.005; BF10=8.7]. The strength of the correlation was comparable to negative affect, which was also found to relate to mean compliance [τb = -0.20; p below 0.001; BF10=2091.4] and compliance variability [τb = 0.20; p below 0.001; BF10=1896.3]. Changes in compliance over days did not differ between rMDD and ND individuals (∆AIC below -2). No significant associations between compliance and other vulnerability factors were observed (p below 0.05).These findings indicate mixed evidence for ESM compliance as a reflection of cognitive control, with correlations suggesting that cognitive control and negative affect are associated with compliance. No significant associations with other vulnerability factors were found. Future research could explore the utility of ESM compliance in assessing cognitive control and goal pursuit using an optimized design for that question.

Human performance shows substantial endogenous variability over time, and this variability is a robust marker of individual differences. Of growing interest to psychologists is the realisation that variability is not fully random, but often exhibits temporal dependencies. However, their measurement and interpretation come with several controversies. Furthermore, their potential benefit for studying individual differences in healthy and clinical populations remains unclear. Here, we gather new and archival datasets featuring 11 sensorimotor and cognitive tasks across 526 participants, to examine individual differences in temporal structures. We first investigate intra-individual repeatability of the most common measures of temporal structures — to test their potential for capturing stable individual differences. Secondly, we examine inter-individual differences in these measures using: (1) task performance assessed from the same data, (2) meta-cognitive ratings of on-taskness from thought probes occasionally presented throughout the task, and (3) self-assessed attention-deficit related traits. Across all datasets, autocorrelation at lag 1 and Power Spectra Density slope showed high intra-individual repeatability across sessions and correlated with task performance. The Detrended Fluctuation Analysis slope showed the same pattern, but less reliably. The long-term component (d) of the ARFIMA(1,d,1) model showed poor repeatability and no correlation to performance. Overall, these measures failed to show external validity when correlated with either mean subjective attentional state or self-assessed traits between participants. Thus, some measures of serial dependencies may be stable individual traits, but their usefulness in capturing individual differences in other constructs typically associated with variability in performance seems limited. We conclude with comprehensive recommendations for researchers.

We argue that many of the crises currently afflicting science can be associated with a present failure of science to sufficiently embody its own values. Here, we propose a response beyond mere crisis resolution based on the observation that an ethical framework of flourishing derived from the Buddhist tradition aligns surprisingly well with the values of science itself. This alignment, we argue, suggests a recasting of science from a competitively managed activity of knowledge production to a collaboratively organized moral practice that puts kindness and sharing at its core. We end by examining how Flourishing Science could be embodied in academic practice, from individual to organizational levels, and how that could help to arrive at a flourishing of scientists and science alike.

Mind-wandering, and specifically the frequency and content of mind-wandering, plays an important role in the psychological well-being of individuals. Repetitive negative thinking has been associated with a high risk to develop and maintain Major Depressive Disorder. We combined forces between psychiatry and cognitive sciences to investigate the adjustability of the content and characteristics of mind-wandering in individuals scoring high (n=42) or low (n=40) on their vulnerability for negative affect and depression. To assess the impact of mood induction on mind-wandering, participants performed a Sustained Attention to Response Task (SART) after a single session of positive fantasizing and a single session of stress induction in a cross-over design. Affective states were measured before and after the interventions. Results showed increased negative affect after stress, and increased positive and reduced negative affect after fantasizing. Thoughts were more on-task and future-related, and less negative after fantasizing compared to after stress. Individuals more susceptible to negative affect showed more off-task thinking after stress than after fantasizing compared to individuals low on this. These results suggest that stress-induced negative thinking underlying vulnerability for depression could be partially countered by fantasizing, which could inform the development of treatments for depression.