Memory performance is crucial across the human life, from early education to age-related decline. A new study in PLOS Biology found that verbal learning can be enhanced by applying repetitive ...transcranial magnetic stimulation (rTMS) over the left prefrontal cortex.
Receiving research grants is among the highlights of an academic career, affirming previous accomplishments and enabling new research endeavours. Much of the process of acquiring research funding, ...however, belongs to the less favourite duties of many researchers: It is time consuming, often stressful and, in the majority of cases, unsuccessful. This resentment towards funding acquisition is backed up by empirical research: The current system to distribute research funding, via competitive calls for extensive research applications that undergo peer review, has repeatedly been shown to fail in its task to reliably rank proposals according to their merit, while at the same time being highly inefficient. The simplest, fairest and broadly supported alternative would be to distribute funding more equally across researchers, for example, by an increase of universities' base funding, thereby saving considerable time that can be spent on research instead. Here, I propose how to combine such a ‘funding flat rate’ model—or other efficient distribution strategies—with quality control through postponed, non‐competitive peer review using open science practices.
Memory skills strongly differ across the general population; however, little is known about the brain characteristics supporting superior memory performance. Here we assess functional brain network ...organization of 23 of the world’s most successful memory athletes and matched controls with fMRI during both task-free resting state baseline and active memory encoding. We demonstrate that, in a group of naive controls, functional connectivity changes induced by 6 weeks of mnemonic training were correlated with the network organization that distinguishes athletes from controls. During rest, this effect was mainly driven by connections between rather than within the visual, medial temporal lobe and default mode networks, whereas during task it was driven by connectivity within these networks. Similarity with memory athlete connectivity patterns predicted memory improvements up to 4 months after training. In conclusion, mnemonic training drives distributed rather than regional changes, reorganizing the brain’s functional network organization to enable superior memory performance.
•Memory champions show distributed functional brain network connectivity changes•Mnemonic strategies for superior memory can be learned by naive subjects•Mnemonic training induces similarity with memory champion brain connectivity•Brain network dynamics of this effect differ between task and resting state
Dresler et al. demonstrate that distributed functional brain network connectivity patterns differentiate the world’s leading memory athletes from intelligence-matched controls. Similar connectivity patterns could be induced through intense mnemonic training in naive subjects.
Abstract
A theoretical and empirical association between lucid dreaming and mindfulness, as well as lucid dreaming and nightmares has previously been observed; however, the relationship between ...nightmares and mindfulness has received surprisingly little attention. Here, we present the findings of two studies exploring the relation of nightmare frequency and distress with two components of mindfulness, termed presence and acceptance, as well as lucid dreaming. Study 1 (N = 338) consisted of a low percentage of frequent lucid dreamers whereas Study 2 (N = 187) consisted primarily of frequent lucid dreamers that used lucid dream induction training techniques and meditation. Across studies, nightmare-related variables showed a more robust association with mindful acceptance as opposed to mindful presence. Moreover, individuals with high levels of meditation expertise and practice of lucid dreaming induction techniques reported lower nightmare frequency. Finally, in Study 2, which consisted of frequent lucid dreamers, a positive correlation between lucid dreaming frequency and mindfulness was apparent. The present findings support the notion that wakeful mindfulness is associated with the quality of dreams and extend previous research by suggesting a disentangled role of the two facets of mindfulness in dream variation. This association remains open for experimental manipulation, the result of which could have clinical implications.
•We use a cross-validated method to predict cognitive performance from sleep EEG features.•Up to 10% of cognition variance is accounted for by sleep EEG features.•The most associated features are: ...NREM theta/sigma, REM beta.•Other EEG features add comparatively little information.•Demographics and health only account for part of the association.
Human cognitive performance is a key function whose biological foundations have been partially revealed by genetic and brain imaging studies. The sleep electroencephalogram (EEG) is tightly linked to structural and functional features of the central nervous system and serves as another promising biomarker. We used data from MrOS, a large cohort of older men and cross-validated regularized regression to link sleep EEG features to cognitive performance in cross-sectional analyses. In independent validation samples 2.5–10% of variance in cognitive performance can be accounted for by sleep EEG features, depending on the covariates used. Demographic characteristics account for more covariance between sleep EEG and cognition than health variables, and consequently reduce this association by a greater degree, but even with the strictest covariate sets a statistically significant association is present. Sigma power in NREM and beta power in REM sleep were associated with better cognitive performance, while theta power in REM sleep was associated with worse performance, with no substantial effect of coherence and other sleep EEG metrics. Our findings show that cognitive performance is associated with the sleep EEG (r = 0.283), with the strongest effect ascribed to spindle-frequency activity. This association becomes weaker after adjusting for demographic (r = 0.186) and health variables (r = 0.155), but its resilience to covariate inclusion suggest that it also partially reflects trait-like differences in cognitive ability.
In an increasingly complex information society, demands for cognitive functioning are growing steadily. In recent years, numerous strategies to augment brain function have been proposed. Evidence for ...their efficacy (or lack thereof) and side effects has prompted discussions about ethical, societal, and medical implications. In the public debate, cognitive enhancement is often seen as a monolithic phenomenon. On a closer look, however, cognitive enhancement turns out to be a multifaceted concept: There is not one cognitive enhancer that augments brain function per se, but a great variety of interventions that can be clustered into biochemical, physical, and behavioral enhancement strategies. These cognitive enhancers differ in their mode of action, the cognitive domain they target, the time scale they work on, their availability and side effects, and how they differentially affect different groups of subjects. Here we disentangle the dimensions of cognitive enhancement, review prominent examples of cognitive enhancers that differ across these dimensions, and thereby provide a framework for both theoretical discussions and empirical research.
Introduction
Lucid dreaming opens the possibility to rehearse sport skills within a dream while sleeping (Peters et al. 2023; Stumbrys et al. 2016). But so far, no induction techniques have been ...developed to induce reliable lucid dreams. One potential technique is to apply external stimulation while a person is sleeping in order to send a hint into the dream which might enhance lucidity in the ongoing dream. Several studies have tested dream incorporation rates (DIR) with different stimuli and different results (Schredl, 2018), but none with a larger sample size and a within-design. Furthermore, in this study we wanted to explore body related stimulations to evoke in future studies lucid dreams.
Methods
10-Channel polysomnography and three different bodily stimulation methods were combined during three consecutive test nights with each night using one stimulation method (plus adaptation night). The three stimulation methods consisted of electrical forearm muscle stimulation (EMS), galvanic vestibular stimulation (GVS), and haptic vibration stimulation (HS). During REM sleep, one of the three stimuli was presented or a sham condition was applied in a counterbalanced order. The stimuli were followed by REM awakenings, resulting in corresponding verbal dream reports. With the help of those reports, the translation from a physical arm movement, vestibular sensation and vibration into the dream environment was investigated using dream content analysis. Movement of the dream arm, balance related activity and tactile or somatosensory sensations targeted the dream incorporations of EMS, GVS and HS respectively.
Results
Movement of the arm was present in 23.2%, 8.1% and 23.5% of EMS, GVS and HS dreams respectively. Balance-related activity was present in 6.1%, 7.9% and 5.8% of EMS, GVS and HS dreams respectively. Finally, tactile and somatosensory sensations were present in 13.6%, 0% and 6.3% of the EMS, GVS and HS dreams respectively. After correcting for sham condition, tactile and somatosensory sensations on the EMS dreams seem to be the strongest incorporation effect upon stimulation.
Discussion/Conclusion
We tested dream incorporation of three different stimulation methods using a within-design on a larger sample size, a method that has never been attempted before. GVS appears unsuccessful in altering dream content, but this might be confounded due to challenges in methodology. EMS evokes the most dream incorporation in the scale of tactile and somatosensory dream content followed by HS. The investigation of the incorporation of external kinesthetic stimulation into dream content represents a fundamental contribution to various scientific fields and could foster future research on lucid dream induction, enabling the further exploration of sport practice in a sleep state.
References
Peters, E., Golembiewski, S., Erlacher, D., & Dresler, M. (2023). Extending mental practice to sleep: Enhancing motor skills through lucid dreaming. Medical Hypotheses, 174, Article 111066. https://doi.org/10.1016/j.mehy.2023.111066
Schredl, M. (2018). Researching Dreams: The Fundamentals. Springer International. https://doi.org/10.1007/978-3-319-95453-0
Stumbrys, T., Erlacher, D., & Schredl, M. (2016). Effectiveness of motor practice in lucid dreams: A comparison with physical and mental practice. Journal of Sports Sciences, 34(1), 27–34. https://doi.org/10.1080/02640414.2015.1030342
Features of sleep were shown to reflect aging, typical sex differences and cognitive abilities of humans. However, these measures are characterized by redundancy and arbitrariness. Our present ...approach relies on the assumptions that the spontaneous human brain activity as reflected by the scalp-derived electroencephalogram (EEG) during non-rapid eye movement (NREM) sleep is characterized by arrhythmic, scale-free properties and is based on the power law scaling of the Fourier spectra with the additional consideration of the rhythmic, oscillatory waves at specific frequencies, including sleep spindles. Measures derived are the spectral intercept and slope, as well as the maximal spectral peak amplitude and frequency in the sleep spindle range, effectively reducing 191 spectral measures to 4, which were efficient in characterizing known age-effects, sex-differences and cognitive correlates of sleep EEG. Future clinical and basic studies are supposed to be significantly empowered by the efficient data reduction provided by our approach.
Graph theoretical analysis of functional magnetic resonance imaging (fMRI) time series has revealed a small-world organization of slow-frequency blood oxygen level-dependent (BOLD) signal ...fluctuations during wakeful resting. In this study, we used graph theoretical measures to explore how physiological changes during sleep are reflected in functional connectivity and small-world network properties of a large-scale, low-frequency functional brain network. Twenty-five young and healthy participants fell asleep during a 26.7 min fMRI scan with simultaneous polysomnography. A maximum overlap discrete wavelet transformation was applied to fMRI time series extracted from 90 cortical and subcortical regions in normalized space after residualization of the raw signal against unspecific sources of signal fluctuations; functional connectivity analysis focused on the slow-frequency BOLD signal fluctuations between 0.03 and 0.06 Hz. We observed that in the transition from wakefulness to light sleep, thalamocortical connectivity was sharply reduced, whereas corticocortical connectivity increased; corticocortical connectivity subsequently broke down in slow-wave sleep. Local clustering values were closest to random values in light sleep, whereas slow-wave sleep was characterized by the highest clustering ratio (gamma). Our findings support the hypothesis that changes in consciousness in the descent to sleep are subserved by reduced thalamocortical connectivity at sleep onset and a breakdown of general connectivity in slow-wave sleep, with both processes limiting the capacity of the brain to integrate information across functional modules.
Summary The benefit of sleep in general for memory consolidation is well known. The relevance of sleep characteristics and the influence of hormones are not well studied. We explored the effects of a ...nap on memory consolidation of motor (finger-tapping-task) and verbal (associated-word-pairs) tasks in following settings: A: young, healthy males and females during early-follicular phase ( n = 40) and B: females during mid-luteal and early-follicular phase in the menstrual cycle ( n = 15). We found a sex and in women a menstrual cycle effect on memory performance following a nap. Men performed significantly better after a nap and women did so only in the mid-luteal phase of their menstrual cycle. Only the men and the women in their mid-luteal phase experienced a significant increase in spindle activity after learning. Furthermore, in women estrogen correlated significantly with the offline change in declarative learning and progesterone with motor learning. The ratio of the 2nd and 4th digit, which has been associated to fetal sex hormones and cognitive sex differences, significantly predicted the average performance of the female subjects in the learning tasks. Our results demonstrate that sleep-related memory consolidation has a higher complexity and more influencing factors than previously assumed. There is a sex and menstrual cycle effect, which seems to be mediated by female hormones and sleep spindles. Further, contrary to previous reports, consolidation of a simple motor task can be induced by a 45 min NREM sleep nap, thus not dependent on REM sleep.
PDF
