Prior Context and Individual Alpha Frequency Influence Predictive Processing during Language Comprehension.

The extent to which the brain predicts upcoming information during language processing remains controversial. To shed light on this debate, the present study reanalyzed [Nieuwland, M. S., Politzer-Ahles, S., Heyselaar, E., Segaert, K., Darley, E., Kazanina, N., et al. Large-scale replication study reveals a limit on probabilistic prediction in language comprehension. eLife, 7, e33468, 2018] replication of [DeLong, K. A., Urbach, T. P., & Kutas, M. Probabilistic word pre-activation during language comprehension inferred from electrical brain activity. Nature Neuroscience, 8, 1117-1121, 2005]. Participants (n = 356) viewed sentences containing articles and nouns of varying predictability, while their EEG was recorded. We measured ERPs preceding the critical words (namely, the semantic prediction potential), in conjunction with postword N400 patterns and individual neural metrics. ERP activity was compared with two measures of word predictability: cloze probability and lexical surprisal. In contrast to prior literature, semantic prediction potential amplitudes did not increase as cloze probability increased, suggesting that the component may not reflect prediction during natural language processing. Initial N400 results at the article provided evidence against phonological prediction in language, in line with Nieuwland and colleagues' findings. Strikingly, however, when the surprisal of the prior words in the sentence was included in the analysis, increases in article surprisal were associated with increased N400 amplitudes, consistent with prediction accounts. This relationship between surprisal and N400 amplitude was not observed when the surprisal of the two prior words was low, suggesting that expectation violations at the article may be overlooked under highly predictable conditions. Individual alpha frequency also modulated the relationship between article surprisal and the N400, emphasizing the importance of individual neural factors for prediction. The present study extends upon existing neurocognitive models of language and prediction more generally, by illuminating the flexible and subject-specific nature of predictive processing.

Consolidation and generalisation across sleep depend on individual EEG factors and sleep spindle density.

Sleep is involved in both the consolidation of discrete episodes, as well as the generalisation of acquired memories into schemata. Here, we have isolated early versus late periods of sleep in order to replicate previous behavioural findings and to demonstrate: i) that distinct sleep and sleep electroencephalography (EEG) factors influence the generalisation of learned information, and; ii) that the consolidation and generalisation of memory across sleep depends on individual alpha frequency (IAF) and strength of initial encoding. Subjects underwent a night-half protocol with polysomnography (PSG), and completed a Chinese character-English paired associates learning task. Recognition accuracy of learned word-pairs, the extent to which the subject was able to generalise this knowledge, and the extent of explicit transfer of knowledge were measured. Results demonstrate that quality of initial learning determined the relationship between sleep neurophysiology and outcome, with IAF modulating this effect. We also note an effect of IAF in modulating the effect of sleep spindles in determining generalisation of learned materials. Finally, we note a complex relationship between initial learning, IAF and sleep spindle density in determining when information will reach explicit awareness across sleep. Together, these data implicate encoding factors in subsequent offline processing, demonstrate a potential role for individual differences in the EEG and subsequently add to our understanding of the the conditions in which sleep may benefit both memory and learning.

Sleep influences neural representations of true and false memories: An event-related potential study.

Episodic memory is reconstructive and is thus prone to false memory formation. Although false memories are proposed to develop via associative processes, the nature of their neural representations, and the effect of sleep on false memory processing is currently unclear. The present research employed the Deese-Roediger-McDermott (DRM) paradigm and a daytime nap to determine whether semantic false memories and true memories could be differentiated using event-related potentials (ERPs). We also sought to illuminate the role of sleep in memory formation and learning. Healthy participants (N = 34, 28F, mean age = 23.23, range = 18-33) completed the learning phase of the DRM task followed by an immediate and a delayed recognition phase. The two recognition phases were separated by either a 2hr daytime nap or an equivalent wake period. Linear mixed modelling of effects at delayed recognition revealed larger LPC amplitudes for true memories in contrast to false memories for those in the wake group, and larger P300 amplitudes for false compared to true memories across sleep and wake groups. Larger LPC amplitudes for true memories were associated with enhanced true memory recognition following sleep, whilst larger P300 amplitudes were associated with similar true and false memory recognition rates. These findings are argued to reflect sleep's ability to promote memory generalisation associated with pattern completion, whilst also enhancing true memory recognition when memory traces have a strong episodic basis (linked to pattern separation). The present research suggests that true and false memories have differing neural profiles and are reflective of adaptive memory processes.

The effects of sleep restriction and sleep deprivation in producing false memories.

False memory has been claimed to be the result of an associative process of generalisation, as well as to be representative of memory errors. These can occur at any stage of memory encoding, consolidation, or retrieval, albeit through varied mechanisms. The aim of this paper is to experimentally determine: (i) if cognitive dysfunction brought about by sleep loss at the time of stimulus encoding can influence false memory production; and (ii) whether this relationship holds across sensory modalities. Subjects undertook both the Deese-Roedigger-McDermott (DRM) false memory task and a visual task designed to produce false memories. Performance was measured while subjects were well-rested (9h Time in Bed or TIB), and then again when subjects were either sleep restricted (4h TIB for 4 nights) or sleep deprived (30h total SD). Results indicate (1) that partial and total sleep loss produced equivalent effects in terms of false and veridical verbal memory, (2) that subjects performed worse after sleep loss (regardless of whether this was partial or total sleep loss) on cued recognition-based false and veridical verbal memory tasks, and that sleep loss interfered with subjects' ability to recall veridical, but not false memories under free recall conditions, and (3) that there were no effects of sleep loss on a visual false memory task. This is argued to represent the dysfunction and slow repair of an online verbal associative process in the brain following inadequate sleep.

Considerations towards a neurobiologically-informed EEG measurement of sleepiness.

Sleep is a daily experience across humans and other species, yet our understanding of how and why we sleep is presently incomplete. This is particularly prevalent in research examining the neurophysiological measurement of sleepiness in humans, where several electroencephalogram (EEG) phenomena have been linked with prolonged wakefulness. This leaves researchers without a solid basis for the measurement of homeostatic sleep need and complicates our understanding of the nature of sleep. Recent theoretical and technical advances may allow for a greater understanding of the neurobiological basis of homeostatic sleep need: this may result from increases in neuronal excitability and shifts in excitation/inhibition balance in neuronal circuits and can potentially be directly measured via the aperiodic component of the EEG. Here, we review the literature on EEG-derived markers of sleepiness in humans and argue that changes in these electrophysiological markers may actually result from neuronal activity represented by changes in aperiodic markers. We argue for the use of aperiodic markers derived from the EEG in predicting sleepiness and suggest areas for future research based on these.

The Influence of Focused Attention and Open Monitoring Mindfulness Meditation States on True and False Memory.

Previous investigations into the effect of mindfulness meditation on false memory have reported mixed findings. One potential issue is that mindfulness meditation involves different styles that establish distinct cognitive control states. The present work aimed to address this issue by comparing the effects of single-session focused attention (FAM) and open monitoring (OMM) mindfulness meditation styles on true and false memory recall. Strengthened cognitive control states associated with FAM were predicted to increase true memory recall and decrease false memory recall. Conversely, weakened cognitive control established by OMM was predicted to increase false memory recall. Thirty-four meditation-naïve participants (23 females, mean age = 23.4 years, range = 18-33) first completed pre-meditation learning and recall phases of the Deese-Roediger-McDermott (DRM) task. Participants then completed a single session of FAM or OMM prior to a second, post-meditation, round of DRM task learning and recall phases with a novel word list. Finally, participants completed a recognition test with true and false memory, and distractor words. Both FAM and OMM groups demonstrated significant increase in false memory recall between pre- and post-meditation recall tests but these groups did not differ with respect to true and false memory recall and recognition. The present findings are consistent with previous reports of increased false memory arising from mindfulness meditation. Distinct cognitive control states associated with FAM and OMM states do not result in distinct true and false memory formation, at least in meditation-naïve adults.

Neural and cognitive correlates of performance in dynamic multi-modal settings.

The endeavour to understand human cognition has largely relied upon investigation of task-related brain activity. However, resting-state brain activity can also offer insights into individual information processing and performance capabilities. Previous research has identified electroencephalographic resting-state characteristics (most prominently: the individual alpha frequency; IAF) that predict cognitive function. However, it has largely overlooked a second component of electrophysiological signals: aperiodic 1/ƒ activity. The current study examined how both oscillatory and aperiodic resting-state EEG measures, alongside traditional cognitive tests, can predict performance in a dynamic and complex, semi-naturalistic cognitive task. Participants' resting-state EEG was recorded prior to engaging in a Target Motion Analysis (TMA) task in a simulated submarine control room environment (CRUSE), which required participants to integrate dynamically changing information over time. We demonstrated that the relationship between IAF and cognitive performance extends from simple cognitive tasks (e.g., digit span) to complex, dynamic measures of information processing. Further, our results showed that individual 1/ƒ parameters (slope and intercept) differentially predicted performance across practice and testing sessions, whereby flatter slopes and higher intercepts were associated with improved performance during learning. In addition to the EEG predictors, we demonstrate a link between cognitive skills most closely related to the TMA task (i.e., spatial imagery) and subsequent performance. Overall, the current study highlights (1) how resting-state metrics - both oscillatory and aperiodic - have the potential to index higher-order cognitive capacity, while (2) emphasising the importance of examining these electrophysiological components within more dynamic settings and over time.

Theta Activity During Encoding Interacts With NREM Sleep Oscillations to Predict Memory Generalization.

Relatively little is known regarding the interaction between encoding-related neural activity and sleep-based memory consolidation. One suggestion is that a function of encoding-related theta power may be to "tag" memories for subsequent processing during sleep. This study aimed to extend previous work on the relationships between sleep spindles, slow oscillation-spindle coupling, and task-related theta activity with a combined Deese-Roediger-McDermott (DRM) and nap paradigm. This allowed us to examine the influence of task- and sleep-related oscillatory activity on the recognition of both encoded list words and associative theme words. Thirty-three participants (29 females, mean age = 23.2 years) learned and recognised DRM lists separated by either a 2 h wake or sleep period. Mixed-effects modelling revealed the sleep condition endorsed more associative theme words and fewer list words in comparison to the wake group. Encoding-related theta power was also found to influence sleep spindle density, and this interaction was predictive of memory outcomes. The influence of encoding-related theta was specific to sleep spindle density, and did not appear to influence the strength of slow oscillation-spindle coupling as it relates to memory outcomes. The finding of interactions between wakeful and sleep oscillatory-related activity in promoting memory and learning has important implications for theoretical models of sleep-based memory consolidation.

Task-related, intrinsic oscillatory and aperiodic neural activity predict performance in naturalistic team-based training scenarios.

Effective teams are essential for optimally functioning societies. However, little is known regarding the neural basis of two or more individuals engaging cooperatively in real-world tasks, such as in operational training environments. In this exploratory study, we recruited forty individuals paired as twenty dyads and recorded dual-EEG at rest and during realistic training scenarios of increasing complexity using virtual simulation systems. We estimated markers of intrinsic brain activity (i.e., individual alpha frequency and aperiodic activity), as well as task-related theta and alpha oscillations. Using nonlinear modelling and a logistic regression machine learning model, we found that resting-state EEG predicts performance and can also reliably differentiate between members within a dyad. Task-related theta and alpha activity during easy training tasks predicted later performance on complex training to a greater extent than prior behaviour. These findings complement laboratory-based research on both oscillatory and aperiodic activity in higher-order cognition and provide evidence that theta and alpha activity play a critical role in complex task performance in team environments.

Sleep spindles track cortical learning patterns for memory consolidation.

Memory consolidation-the transformation of labile memory traces into stable long-term representations-is facilitated by post-learning sleep. Computational and biophysical models suggest that sleep spindles may play a key mechanistic role for consolidation, igniting structural changes at cortical sites involved in prior learning. Here, we tested the resulting prediction that spindles are most pronounced over learning-related cortical areas and that the extent of this learning-spindle overlap predicts behavioral measures of memory consolidation. Using high-density scalp electroencephalography (EEG) and polysomnography (PSG) in healthy volunteers, we first identified cortical areas engaged during a temporospatial associative memory task (power decreases in the alpha/beta frequency range, 6-20 Hz). Critically, we found that participant-specific topographies (i.e., spatial distributions) of post-learning sleep spindle amplitude correlated with participant-specific learning topographies. Importantly, the extent to which spindles tracked learning patterns further predicted memory consolidation across participants. Our results provide empirical evidence for a role of post-learning sleep spindles in tracking learning networks, thereby facilitating memory consolidation.

Resting-state aperiodic neural dynamics predict individual differences in visuomotor performance and learning.

An emerging body of work has demonstrated that resting-state non-oscillatory, or aperiodic, 1/f neural activity is a functional and behaviorally relevant marker of cognitive function capacity. In the motor domain, previous work has only applied 1/f analyses to investigations of motor coordination and performance measures. The value of aperiodic resting-state neural dynamics as a marker of individual visuomotor performance capacity remains unknown. Accordingly, the aim of this work was to investigate if individual 1/f intercept and slope parameters of aperiodic resting-state neural activity predict reaction time and perceptual sensitivity in an immersive virtual reality marksmanship task. The marksmanship task required speeded selection of target stimuli and avoidance of selecting non-target stimuli. Motor and perceptual demands were incrementally increased across task blocks and participants performed the task across three training sessions spanning one week. When motor demands were high, steeper individual 1/f slope predicted shorter reaction time. This relationship did not change with practice. Increased 1/f intercept and a steeper 1/f slope were associated with higher perceptual sensitivity, measured as d'. However, this association was only observed under the highest levels of perceptual demand and only in the initial exposure to these conditions. Individuals with a lower 1/f intercept and a shallower 1/f slope demonstrated the greatest gains in perceptual sensitivity from task practice. These findings demonstrate that individual differences in motor and perceptual performance can be accounted for with resting-state aperiodic neural dynamics. The 1/f aperiodic parameters are most informative in predicting visuomotor performance under complex and demanding task conditions. In addition to predicting capacity for high visuomotor performance with a novel task, 1/f aperiodic parameters might also be useful in predicting which individuals might derive the most improvements from practice.

Individual alpha frequency modulates sleep-related emotional memory consolidation.

Alpha-band oscillatory activity is involved in modulating memory and attention. However, few studies have investigated individual differences in oscillatory activity during the encoding of emotional memory, particularly in sleep paradigms where sleep is thought to play an active role in memory consolidation. The current study aimed to address the question of whether individual alpha frequency (IAF) modulates the consolidation of declarative memory across periods of sleep and wake. 22 participants aged 18-41 years (mean age = 25.77) viewed 120 emotionally valenced images (positive, negative, neutral) and completed a baseline memory task before a 2hr afternoon sleep opportunity and an equivalent period of wake. Following the sleep and wake conditions, participants were required to distinguish between 120 learned (target) images and 120 new (distractor) images. This method allowed us to delineate the role of different oscillatory components of sleep and wake states in the emotional modulation of memory. Linear mixed-effects models revealed interactions between IAF, rapid eye movement sleep theta power, and slow-wave sleep slow oscillatory density on memory outcomes. These results highlight the importance of individual factors in the EEG in modulating oscillatory-related memory consolidation and subsequent behavioural outcomes and test predictions proposed by models of sleep-based memory consolidation.

Augmented Reality as a Countermeasure for Sleep Deprivation.

Sleep deprivation is known to have serious deleterious effects on executive functioning and job performance. Augmented reality has an ability to place pertinent information at the fore, guiding visual focus and reducing instructional complexity. This paper presents a study to explore how spatial augmented reality instructions impact procedural task performance on sleep deprived users. The user study was conducted to examine performance on a procedural task at six time points over the course of a night of total sleep deprivation. Tasks were provided either by spatial augmented reality-based projections or on an adjacent monitor. The results indicate that participant errors significantly increased with the monitor condition when sleep deprived. The augmented reality condition exhibited a positive influence with participant errors and completion time having no significant increase when sleep deprived. The results of our study show that spatial augmented reality is an effective sleep deprivation countermeasure under laboratory conditions.

Complex associative memory processing and sleep: a systematic review and meta-analysis of behavioural evidence and underlying EEG mechanisms.

The beneficial influence of sleep on memory consolidation is well established; however, the mechanisms by which sleep can dynamically consolidate new memories into existing networks for the continued environmental adaptation of the individual are unclear. The role of sleep in complex associative memory is an emerging field and the literature has not yet been systematically reviewed. Here, we systematically review the published literature on the role of sleep in complex associative memory processing to determine (i) if there is reasonable published evidence to support an active role for sleep facilitating complex associative processes such rule and gist extraction and false memory; (ii) to determine which sleep physiological events and states impact these processes, and to quantify the strength of these relationships through meta-analysis. Twenty-seven studies in healthy adults were identified which combined indicate a moderate effect of sleep in facilitating associative memory as tested behaviourally. Studies which have measured sleep physiology have reported mixed findings. Significant associations between sleep electrophysiology and outcome appear to be based largely on mode of acquisition. We interpret these findings as supporting reactivation based models of associative processing.

Resiliency as a mediator of the impact of sleep on child and adolescent behavior.

BACKGROUND: Disturbed sleep is detrimental to child behavior; however, the precise means by which this association occurs is unclear. Sleep and resilience can theoretically share an underlying neural mechanism and therefore influence one another. However, the role of resilience in the association between sleep and behavior is not known. The associations between sleep, resilience, and problematic behavior in children and adolescents aged 7-18 years were investigated in this study. METHODS: A correlational design was used to determine the relationships between total sleep problems, indices of resilience, and internalizing and externalizing behaviors. RESULTS: Sleep problems and resiliency variables were strongly correlated, and further, sleep problems were found to be predictive of resiliency scores. Resiliency significantly mediated the relationship between increased sleep problems and both overall internalizing and externalizing behavior problems, and specifically, measures of depression and anxiety. CONCLUSION: Sleep impacted levels of resilience such that greater sleep disturbance reduced resilience and consequently increased problematic behavior, potentially predisposing individuals to psychopathology.

Estimating adolescent sleep patterns: parent reports versus adolescent self-report surveys, sleep diaries, and actigraphy.

BACKGROUND: In research and clinical contexts, parent reports are often used to gain information about the sleep patterns of their adolescents; however, the degree of concordance between parent reports and adolescent-derived measures is unclear. The present study compares parent estimates of adolescent sleep patterns with adolescent self-reports from surveys and sleep diaries, together with actigraphy. METHODS: A total of 308 adolescents (59% male) aged 13-17 years completed a school sleep habits survey during class time at school, followed by a 7-day sleep diary and wrist actigraphy. Parents completed the Sleep, Medical, Education and Family History Survey. RESULTS: Parents reported an idealized version of their adolescent's sleep, estimating significantly earlier bedtimes on both school nights and weekends, significantly later wake times on weekends, and significantly more sleep than either the adolescent self-reported survey, sleep diary, or actigraphic estimates. CONCLUSION: Parent reports indicate that the adolescent averages a near-optimal amount of sleep on school nights and a more than optimal amount of sleep on weekends. However, adolescent-derived averages indicate patterns of greater sleep restriction. These results illustrate the importance of using adolescent-derived estimates of sleep patterns in this age group and the importance of sleep education for both adolescents and their parents.

Sleep spindle activity and cognitive performance in healthy children.

STUDY OBJECTIVES: To investigate the association between indices of sleep spindle activity and cognitive performance in a sample of healthy children. DESIGN: Correlational. Intelligence (Stanford-Binet) and neurocognitive functioning (NEPSY) were assessed, with sleep variables being measured during overnight polysomnography. SETTING: Hospital sleep laboratory. PARTICIPANTS: Twenty-seven healthy children (mean age 8.19 y; 14 female, 13 male). INTERVENTIONS: N/A. MEASUREMENTS AND RESULTS: Participants underwent a single night of overnight polysomnography after completing measures of intelligence and neurocognitive functioning. Sleep spindles were visually identified by an experienced sleep scoring technician and separated algorithmically into fast (> 13 Hz) and slow spindle (< 13 Hz) categories. The number of fast spindles was significantly correlated with narrative memory (r(s) = 0.38) and sensorimotor functioning (-0.43). Mean central frequency of spindles was also significantly correlated with sensorimotor functioning (-0.41), planning ability (-0.41), and working memory (-0.54). CONCLUSIONS: Basal sleep spindle activity is associated with different aspects of cognitive performance in children. To the extent that these associations in a pediatric population are different from what is known in adult sleep may play an important role in development.