Search

Neurofeedback has begun to attract the attention and scrutiny of the scientific and medical mainstream. Here, neurofeedback researchers present a consensus-derived checklist that aims to improve the reporting and experimental design standards in the field.

Neurofeedback has begun to attract the attention and scrutiny of the scientific and medical mainstream. Here, neurofeedback researchers present a consensus-derived checklist that aims to improve the reporting and experimental design standards in the field.

Meditation practices are often used to cultivate interoception or internally-oriented attention to bodily sensations, which may improve health via cognitive and emotional regulation of bodily signals. However, it remains unclear how meditation impacts internal attention (IA) states due to lack of measurement tools that can objectively assess mental states during meditation practice itself, and produce time estimates of internal focus at individual or group levels. To address these measurement gaps, we tested the feasibility of applying multi-voxel pattern analysis (MVPA) to single-subject fMRI data to: (1) learn and recognize internal attentional states relevant for meditation during a directed IA task; and (2) decode or estimate the presence of those IA states during an independent meditation session. Within a mixed sample of experienced meditators and novice controls (N = 16), we first used MVPA to develop single-subject brain classifiers for five modes of attention during an IA task in which subjects were specifically instructed to engage in one of five states [i.e., meditation-related states: breath attention, mind wandering (MW), and self-referential processing, and control states: attention to feet and sounds]. Using standard cross-validation procedures, MVPA classifiers were trained in five of six IA blocks for each subject, and predictive accuracy was tested on the independent sixth block (iterated until all volumes were tested, N = 2,160). Across participants, all five IA states were significantly recognized well above chance (>41% vs. 20% chance). At the individual level, IA states were recognized in most participants (87.5%), suggesting that recognition of IA neural patterns may be generalizable for most participants, particularly experienced meditators. Next, for those who showed accurate IA neural patterns, the originally trained classifiers were applied to a separate meditation run (10-min) to make an inference about the percentage time engaged in each IA state (breath attention, MW, or self-referential processing). Preliminary group-level analyses demonstrated that during meditation practice, participants spent more time attending to breath compared to MW or self-referential processing. This paradigm established the feasibility of using MVPA classifiers to objectively assess mental states during meditation at the participant level, which holds promise for improved measurement of internal attention states cultivated by meditation.

Mindfulness and compassion meditation are thought to cultivate prosocial behavior. However, the lack of diverse representation within both scientific and participant populations in contemplative neuroscience may limit generalizability and translation of prior findings. To address these issues, we propose a research framework called Intersectional Neuroscience which adapts research procedures to be more inclusive of under-represented groups. Intersectional Neuroscience builds inclusive processes into research design using two main approaches: 1) community engagement with diverse participants, and 2) individualized multivariate neuroscience methods to accommodate neural diversity. We tested the feasibility of this framework in partnership with a diverse U.S. meditation center (East Bay Meditation Center, Oakland, CA). Using focus group and community feedback, we adapted functional magnetic resonance imaging (fMRI) screening and recruitment procedures to be inclusive of participants from various under-represented groups, including racial and ethnic minorities, gender and sexual minorities, people with disabilities, neuropsychiatric disorders, and/or lower income. Using person-centered screening and study materials, we recruited and scanned 15 diverse meditators (80% racial/ethnic minorities, 53% gender and sexual minorities). The participants completed the EMBODY task - which applies individualized machine learning algorithms to fMRI data - to identify mental states during breath-focused meditation, a basic skill that stabilizes attention to support interoception and compassion. All 15 meditators' unique brain patterns were recognized by machine learning algorithms significantly above chance levels. These individualized brain patterns were used to decode the internal focus of attention throughout a 10-min breath-focused meditation period, specific to each meditator. These data were used to compile individual-level attention profiles during meditation, such as the percentage time attending to the breath, mind wandering, or engaging in self-referential processing. This study provides feasibility of employing an intersectional neuroscience approach to include diverse participants and develop individualized neural metrics of meditation practice. Through inclusion of more under-represented groups while developing reciprocal partnerships, intersectional neuroscience turns the research process into an embodied form of social action.

[This corrects the article DOI: 10.3389/fpsyg.2020.573134.].

An adaptive memory system should prioritize information surrounding a powerful learning event that may prove useful for predicting future meaningful events. The behavioral tagging hypothesis provides a mechanistic framework to interpret how weak experiences persist as durable memories through temporal association with a strong experience. Memories are composed of multiple elements, and different mnemonic aspects of the same experience may be uniquely affected by mechanisms that retroactively modulate a weakly encoded memory. Here, we investigated how emotional learning affects item and source memory for related events encoded close in time. Participants encoded trial-unique category exemplars before, during, and after Pavlovian fear conditioning. Selective retroactive enhancements in 24-h item memory were accompanied by a bias to misattribute items to the temporal context of fear conditioning. The strength of this source memory bias correlated with participants' retroactive item memory enhancement, and source misattribution to the emotional context predicted whether items were remembered overall. In the framework of behavioral tagging: Memory attribution was biased to the temporal context of the stronger event that provided the putative source of memory stabilization for the weaker event. We additionally found that fear conditioning selectively and retroactively enhanced stimulus typicality ratings for related items, and that stimulus typicality also predicted overall item memory. Collectively, these results provide new evidence that items related to emotional learning are misattributed to the temporal context of the emotional event and judged to be more representative of their semantic category. Both processes may facilitate memory retrieval for related events encoded close in time.

Serial dependence has shown seemingly contradictory effects on visual perception and working memory. While serial dependence promotes perpetual and mnemonic stability, it biases behavioral reports toward prior information. The neural mechanisms that drive both biasing and adaptive stabilizing effects are not well understood. We proposed and tested a reactivation and integration mechanism that can account for these contradictory effects. We used multivariate pattern analyses of EEG data (26 human participants, 17 females, 9 males) to examine the reactivation of prior reported orientation during the delay period of a visual working memory task. The reactivation strength of prior reports, but not prior sensory items, was predictive of the magnitude of serial dependency biases. These reactivated representations integrated with the representation of the current memory item and improved the ability to decode the current contents of memory. Overall, our data provide convergent evidence suggesting that prior reports in a visual working memory task are reactivated on the subsequent trial and become integrated with current memory representations. This similarity-dependent reactivation mechanism drives both report biasing and stabilization effects attributed to serial dependence in working memory. [ABSTRACT FROM AUTHOR]

The sensory recruitment hypothesis conceptualizes information in working memory as being activated representations of information in long-term memory. Accordingly, changes made to an item in working memory would be expected to influence its subsequent retention. Here, we tested the hypothesis that suppressing information from working memory, which can reduce short-term access to that information, may also alter its long-term neural representation. We obtained fMRI data (n = 25; 13 female / 12 male participants) while participants completed a working memory removal task with scene images as stimuli, followed by a final surprise recognition test of the examined items. We applied a multivariate pattern analysis to the data to quantify the engagement of suppression on each trial, to track the contents of working memory during suppression, and to assess representational changes afterward. Our analysis confirms previous reports that suppression of information in working memory involves focused attention to target and remove unwanted information. Furthermore, our findings provide new evidence that even a single dose of suppression of an item in working memory can (if engaged with sufficient strength) produce lasting changes in its neural representation, particularly weakening the unique, item-specific features, which leads to forgetting. Our study sheds light on the underlying mechanisms that contribute to the suppression of unwanted thoughts and highlights the dynamic interplay between working memory and long-term memory. [ABSTRACT FROM AUTHOR]

Recently, multi-voxel pattern analysis has verified that information can be removed from working memory (WM) via three distinct operations replacement, suppression, or clearing compared to information being maintained (Kim et al., 2020). While univariate analyses and classifier importance maps in Kim et al. (2020) identified brain regions that contribute to these operations, they did not elucidate whether these regions represent the operations similarly or uniquely. Using Leiden-community-detection on a sample of 55 humans (17 male), we identified four brain networks, each of which has a unique configuration of multi-voxel activity patterns by which it represents these WM operations. The visual network (VN) shows similar multi-voxel patterns for maintain and replace, which are highly dissimilar from suppress and clear, suggesting this network differentiates whether an item is held in WM or not. The somatomotor network (SMN) shows a distinct multi-voxel pattern for clear relative to the other operations, indicating the uniqueness of this operation. The default mode network (DMN) has distinct patterns for suppress and clear, but these two operations are more similar to each other than to maintain and replace, a pattern intermediate to that of the VN and SMN. The frontoparietal control network (FPCN) displays distinct multi-voxel patterns for each of the four operations, suggesting that this network likely plays an important role in implementing theseWMoperations. These results indicate that the operations involved in removing information fromWMcan be performed in parallel by distinct brain networks, each of which has a particular configuration by which they represent these operations. [ABSTRACT FROM AUTHOR]

Perceptual distraction distorts visual working memory representations. Previous research has shown that memory responses are systematically biased toward visual distractors that are similar to the memoranda. However, it remains unclear whether the prioritization of one working memory representation over another reduces the impact of perceptual distractors. In five behavioral experiments, we used different forms of retrospective cues (indicating the likelihood of testing each item and/or the reward for responding correctly to each item) to manipulate the prioritization of items in working memory before visual distraction. We examined the effects of distraction with nonparametric analyses and a novel distractor intrusion model. We found that memory responses were more precise (lower absolute response errors and stronger memory signals) for items that were prioritized. However, these prioritized items were not immune to distraction, and their memory responses were biased toward the visual distractors to the same degree as were unprioritized items. Our findings demonstrate that the benefits associated with prioritization in working memory do not include protection from distraction biases. [ABSTRACT FROM AUTHOR]

It is widely assumed that the short-term retention of information is accomplished via maintenance of an active neural trace. However, we demonstrate that memory can be preserved across a brief delay despite the apparent loss of sustained representations. Delay period activity may, in fact, reflect the focus of attention, rather than STM. We unconfounded attention and memory by causing external and internal shifts of attention away from items that were being actively retained. Multivariate pattern analysis of fMRI indicated that only items within the focus of attention elicited an active neural trace. Activity corresponding to representations of items outside the focus quickly dropped to baseline. Nevertheless, this information was remembered after a brief delay. Our data also show that refocusing attention toward a previously unattended memory item can reactivate its neural signature. The loss of sustained activity has long been thought to indicate a disruption of STM, but our results suggest that, even for small memory loads not exceeding the capacity limits of STM, the active maintenance of a stimulus representation may not be necessary for its short-term retention.