Reduced processing of afforded actions while observing mental content as ongoing mental phenomena.

While consciousness is typically considered equivalent to mental contents, certain meditation practices-including open monitoring (OM)-are said to enable a unique conscious state where meditators can experience mental content from a de-reified perspective as "ongoing phenomena." Phenomenologically, such a state is considered as reduction of intentionality, the mental act upon mental content. We hypothesised that this de-reified state would be characterised by reduced mental actional processing of affording objects. We recruited two groups of participants, meditators with long-term experience in cultivating a de-reified state, and demographically-matched novice meditators. Participants performed a task with images in two configurations-where objects did (high-affordance) and did not imply actions (low-affordance)-following both a baseline and OM-induced de-reified state, along with EEG recordings. While long-term meditators exhibited preferential processing of high-affordance images compared to low-affordance images during baseline, such an effect was abolished during the OM state, as hypothesised. For novices, however, the high-affordance configuration was preferred over the low-affordance one both during baseline and OM. Perceptual durations of objects across conditions positively correlated with the degree of µ-rhythm desynchronization, indicating that neural processing of affordance impacted perceptual awareness. Our results indicate that OM styles of meditation may help in mentally decoupling otherwise automatic cognitive processing of mental actions by affording objects.

Ready to help, no matter what you did: Responsibility attribution does not influence compassion in expert Buddhist practitioners.

Within western social psychology and neuroscience, compassion is described as being conditioned by cost-benefit appraisals, such as the attribution of responsibility for the causes of suffering. Buddhist traditions maintain the possibility of cultivating and embodying unconditioned and universal forms of compassion. Whereas a growing body of empirical literature suggests that Buddhist-inspired compassion-based programs foster prosociality and well-being in healthy and clinical populations, there is no evidence that such compassionate disposition toward others can become unconditioned from moral judgment. To address this question, we collected and integrated self-report and behavioral data from expert Buddhist practitioners and trained novices using a previously validated within-subject experiment that manipulates contextual information to influence moral judgment toward suffering others and a newly designed approach-avoidance task. We found that context manipulation impacted responsibility and blame attribution in both groups and that experts' reported willingness to help was higher and less influenced by context, compared to novices. Partial correlation networks highlighted a negative relationship between blame attribution and willingness to help in novices, but not in expert practitioners. Self-reported willingness to help was correlated to reaction times when approaching suffering stimuli. Approach behavior was modulated by context in novice, but not in experts. This study provides initial evidence of a dissociation between moral attributions and prosocial attitude in expert Buddhist practitioners and challenges established evolutionary accounts of compassion in western psychology. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Time-resolved dynamic computational modeling of human EEG recordings reveals gradients of generative mechanisms for the MMN response.

Despite attempts to unify the different theoretical accounts of the mismatch negativity (MMN), there is still an ongoing debate on the neurophysiological mechanisms underlying this complex brain response. On one hand, neuronal adaptation to recurrent stimuli is able to explain many of the observed properties of the MMN, such as its sensitivity to controlled experimental parameters. On the other hand, several modeling studies reported evidence in favor of Bayesian learning models for explaining the trial-to-trial dynamics of the human MMN. However, direct comparisons of these two main hypotheses are scarce, and previous modeling studies suffered from methodological limitations. Based on reports indicating spatial and temporal dissociation of physiological mechanisms within the timecourse of mismatch responses in animals, we hypothesized that different computational models would best fit different temporal phases of the human MMN. Using electroencephalographic data from two independent studies of a simple auditory oddball task (n = 82), we compared adaptation and Bayesian learning models' ability to explain the sequential dynamics of auditory deviance detection in a time-resolved fashion. We first ran simulations to evaluate the capacity of our design to dissociate the tested models and found that they were sufficiently distinguishable above a certain level of signal-to-noise ratio (SNR). In subjects with a sufficient SNR, our time-resolved approach revealed a temporal dissociation between the two model families, with high evidence for adaptation during the early MMN window (from 90 to 150-190 ms post-stimulus depending on the dataset) and for Bayesian learning later in time (170-180 ms or 200-220ms). In addition, Bayesian model averaging of fixed-parameter models within the adaptation family revealed a gradient of adaptation rates, resembling the anatomical gradient in the auditory cortical hierarchy reported in animal studies.

When do we become more distractible? Progressive evolution of different components of distractibility from early to late adulthood.

Distractibility determines the propensity to have one's attention captured by irrelevant information; it relies on a balance between voluntary and involuntary attention. We report a cross-sectional study that uses the competitive attention test to characterize patterns of attention across the adult life span from 21 to 86 years old. Several distractibility components were measured in 186 participants distributed within seven age groups. Results indicate that distractibility components follow distinct trajectories with aging: Voluntary orienting remains stable from 21 to 86 years old, sustained attention decreases after 30 years old, distraction progressively increases between 26 and 86 years old, and impulsivity is lower in older compared to younger adults. Increased distractibility in older age thus seems to result from a dominance of involuntary over voluntary attention processes, whose detrimental effect on performance is partly compensated by enhanced motor control. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

No effect of focused attention and open monitoring meditation on EEG auditory mismatch negativity in expert and novice practitioners.

The auditory mismatch negativity (MMN) is a well characterized event-related potential component which has gained recent attention in theoretical models describing the impact of various styles of mindfulness meditation on attentional processes and perceptual inference. Previous findings highlighted a distinct modulation of the MMN amplitude by different meditation practices and degrees of expertise. In the present study, we attempted to replicate results from the recent literature with a data sample that allowed for increased statistical power compared to previous experiments. Relying on traditional frequentist analysis, we found no effect of focused attention and open monitoring meditation on the auditory MMN amplitude compared to a control condition (silent movie) in expert or novice practitioners (all p > 0.17), providing a non-replication of our previous work (Fucci et al. 2018). Using a Bayesian approach, we found strong evidence against an interaction effect on the MMN amplitude between expertise groups and meditation practices (BF01 = 11.0), strong evidence against effects of either meditation practices compared to the control condition (BF01 between 11.9 and 16.1) and moderate evidence against an effect of expertise during meditation (BF01 between 5.3 and 7.9). On the other hand, we replicated previous evidence of increased alpha oscillatory power during meditation practices compared to a control state (p < 0.001). We discuss our null findings in relation to factors that could undermine the replicability of previous research on this subject, namely low statistical power, use of flexible analysis methods and a possible publication bias leading to a misrepresentation of the available evidence.

Cognitive Defusion Is a Core Cognitive Mechanism for the Sensory-Affective Uncoupling of Pain During Mindfulness Meditation.

OBJECTIVE: Mindfulness meditation can downregulate the experience of pain. However, its specific underlying regulatory mechanisms are still largely unknown. Here, we aimed to investigate the role of cognitive defusion-a form of psychological distancing from internal experiences-in mindfulness-based pain regulation. METHODS: We implemented a thermal heat paradigm that was designed to amplify the cognitive-affective aspects of pain in 43 novice meditators (2-day formal training; 51.2% women; 53.2 ± 7.0 years old) and 27 expert meditators (>10,000-hour practice; 44.4% women; 51.9 ± 8.4 years old). We collected pain intensity and unpleasantness reports and trait measures of pain catastrophizing assessed by the Pain Catastrophizing Scale (PCS), cognitive defusion assessed by the Drexel Defusion Scale (DDS), and cognitive fusion assessed by the Cognitive Fusion Questionnaire, as well as of several other constructs commonly reported in the literature. RESULTS: Experts reported lower PCS (6.9 ± 5.2 versus 17.2 ± 8.5, p < .001) but higher DDS (39.4 ± 6.4 versus 28.9 ± 6.6, p < .001) than novices. Across participants, the PCS and DDS were negatively correlated and shared unique variance that survived adjusting for other mindfulness-related and cognitive-emotional constructs (ß = -0.64, p < .001). Conversely, the relationships between PCS and other commonly reported constructs did not seem specific, as none of the relationships survived adjusting for DDS (adjusted ß < 0.25, p > .05). Further supporting the relevance of DDS to pain, both the DDS and PCS specifically predicted pain unpleasantness as opposed to pain intensity. However, DDS seemed to be a more specific predictor of unpleasantness than PCS, as the relationship between DDS and unpleasantness survived adjusting for PCS (adjusted ß = -0.33, p = .016), but not vice versa (adjusted ß = 0.20, p = .162). We also found that the Cognitive Fusion Questionnaire showed a similar pattern of associations with PCS and pain self-reports to what was found for the DDS, although these associations were less consistent. CONCLUSIONS: Collectively, these findings highlight the central role of cognitive defusion in mindfulness-based pain regulation.

Pain regulation during mindfulness meditation: Phenomenological fingerprints in novices and experts practitioners.

BACKGROUND: The way people respond to pain is based on psychological mechanisms, beliefs and expectations. Mindfulness meditation (MM) has been shown to regulate pain and mental suffering through different mechanisms such as positive reappraisal, attentional and emotional regulation. Yet, subjective experience and meaning of pain in connection with MM are still largely unexplored. METHODS: The present mixed-methods study combined an interpretative-phenomenological qualitative approach with an experimental thermal pain paradigm to explore and compare the meaning of experiencing pain in 32 novices who received short meditation training and 30 experts in meditation practice (more than 10, 000 hr in life). We collected the qualitative data during in-depth semi-structured interviews where we probed participants' response strategies. During the pain task, we collected self-reports of intensity and unpleasantness, while after the task we collected self-reports of avoidance, openness, vividness and blissfulness. RESULTS: Five phenomenological clusters (PhC) emerged from the interviews, including three which described pain as an unpleasant sensation calling for: (1) experiential avoidance-suppression, (2) volitional agency-distanciation, or (3) a positive cognitive reappraisal and flexibility. Two additional clusters (4-5), containing mostly expert meditators, thematized pain sensation as an opportunity to gain metacognitive insights about mental processes, and to deconstruct one's suffering through these insights. PhC5 further integrates these insights with the recognition that suffering is part of the shared human experience and with the aspiration to relieve others from suffering. Each PhC was correlated to a unique profile of self-reports during the pain paradigm. CONCLUSION: These findings need to be replicated in patients and practicing MM. They also warrant the integration of this mixed-method approach with brain imaging data to refine the experiential neuroscience of pain. SIGNIFICANCE: We compared the meaning of experiencing and regulating pain in novices and expert meditators using qualitative interviews. We identified five phenomenological clusters describing relevant features implicated in pain response strategies and meditation. These clusters were organized along a pseudo-gradient, which captured meditation expertise and predicted self-reports related to a pain paradigm and psychometric scales associated with pain and its regulation. These findings advance our understanding of the metacognitive mechanisms and beliefs underlying mindfulness meditation and can inform pain treatment strategies.

Mindfulness meditation is related to sensory-affective uncoupling of pain in trained novice and expert practitioners.

BACKGROUND: Mindfulness meditation can alleviate acute and chronic pain. It has been proposed that mindfulness meditation reduces pain by uncoupling sensory and affective pain dimensions. However, studies to date have reported mixed results, possibly due to a diversity of styles of and expertise in mindfulness meditation. Furthermore, the interrelations between mindfulness meditation and pain catastrophizing during acute pain remain little known. METHODS: This cross-sectional study investigated the effect of a style of mindfulness meditation called Open Monitoring (OM) on sensory and affective pain experience by comparing novice (2-day formal training; average ~20 hr practice) to expert practitioners (>10.000 hr practice). We implemented a paradigm that was designed to amplify the cognitive-affective aspects of pain experience by the manipulation of pain anticipation and uncertainty of stimulus length (8 or 16 s thermal pain stimuli). We collected pain intensity and unpleasantness ratings and assessed trait pain catastrophizing with the Pain Catastrophizing Scale (PCS). RESULTS: Across groups, mindfulness meditation reduced unpleasantness, but not intensity ratings compared to attentional distraction. Experts reported a lower score on PCS, reduced amplification of unpleasantness by long painful stimuli, and larger sensory-affective uncoupling than novices particularly during long painful stimuli. In experts, meditation-induced uncoupling spilled over the control condition. Across groups and task conditions, a higher score on PCS predicted lower sensory-affective uncoupling during long painful stimuli and higher ratings of pain intensity during short painful stimuli. CONCLUSION: These findings suggest that mindfulness meditation specifically down-regulates pain affect as opposed to pain intensity, and that pain catastrophizing undermines sensory-affective uncoupling of pain. SIGNIFICANCE: In this study, we found that a style of mindfulness meditation referred to as OM reduced unpleasantness but not intensity ratings compared to attentional distraction in trained novice (state effect) and expert meditators (state and trait effects). We also observed that trait pain catastrophizing scores predicted this sensory-affective uncoupling. These findings advance our understanding of the cognitive mechanisms underlying mindfulness meditation and can inform treatment strategies for chronic pain.

Training novice practitioners to reliably report their meditation experience using shared phenomenological dimensions.

Empirical descriptions of the phenomenology of meditation states rely on practitioners' ability to provide accurate information on their experience. We present a meditation training protocol that was designed to equip naive participants with a theoretical background and experiential knowledge that would enable them to share their experience. Subsequently, novices carried on with daily practice during several weeks before participating in experiments. Using a neurophenomenological experiment designed to explore two different meditation states (focused attention and open monitoring), we found that self-reported phenomenological ratings (i) were sensitive to meditation states, (ii) reflected meditation dose and fatigue effects, and (iii) correlated with behavioral measures (variability of response time). Each of these effects was better predicted by features of participants' daily practice than by desirable responding. Our results provide evidence that novice practitioners can reliably report their experience along phenomenological dimensions and warrant the future investigation of this training protocol with a longitudinal design.

NeuroMap: A Spline-Based Interactive Open-Source Software for Spatiotemporal Mapping of 2D and 3D MEA Data.

A major characteristic of neural networks is the complexity of their organization at various spatial scales, from microscopic local circuits to macroscopic brain-scale areas. Understanding how neural information is processed thus entails the ability to study them at multiple scales simultaneously. This is made possible using microelectrodes array (MEA) technology. Indeed, high-density MEAs provide large-scale coverage (several square millimeters) of whole neural structures combined with microscopic resolution (about 50 µm) of unit activity. Yet, current options for spatiotemporal representation of MEA-collected data remain limited. Here we present NeuroMap, a new interactive Matlab-based software for spatiotemporal mapping of MEA data. NeuroMap uses thin plate spline interpolation, which provides several assets with respect to conventional mapping methods used currently. First, any MEA design can be considered, including 2D or 3D, regular or irregular, arrangements of electrodes. Second, spline interpolation allows the estimation of activity across the tissue with local extrema not necessarily at recording sites. Finally, this interpolation approach provides a straightforward analytical estimation of the spatial Laplacian for better current sources localization. In this software, coregistration of 2D MEA data on the anatomy of the neural tissue is made possible by fine matching of anatomical data with electrode positions using rigid-deformation-based correction of anatomical pictures. Overall, NeuroMap provides substantial material for detailed spatiotemporal analysis of MEA data. The package is distributed under GNU General Public License and available at http://sites.google.com/site/neuromapsoftware.