Reward biases spontaneous neural reactivation during sleep

AbstractSleep favors the reactivation and consolidation of newly acquired memories. Yet, how our brain selects the noteworthy information to be reprocessed during sleep remains largely unknown. From an evolutionary perspective, individuals must retain information that promotes survival, such as avoiding dangers, finding food, or obtaining praise or money. Here, we test whether neural representations of rewarded (compared to non-rewarded) events have priority for reactivation during sleep. Using functional MRI and a brain decoding approach, we show that patterns of brain activity observed during waking behavior spontaneously reemerge during slow-wave sleep. Critically, we report a privileged reactivation of neural patterns previously associated with a rewarded task (i.e., winning at a complex game). Moreover, during sleep, activity in task-related brain regions correlates with better subsequent memory performance. Our study uncovers a neural mechanism whereby rewarded life experiences are preferentially replayed and consolidated while we sleep.

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0078 Influence of Light on Brain Activity Upon Waking From Slow Wave Sleep

SLEEP ◽

10.1093/sleep/zsaa056.076 ◽

2020 ◽

Vol 43 (Supplement_1) ◽

pp. A31-A32 ◽

Cited By ~ 1

Author(s):

E E Flynn-Evans ◽

C J Hilditch ◽

R Chachad ◽

K Bansal ◽

L R Wong ◽

...

Keyword(s):

Slow Wave ◽

Slow Wave Sleep ◽

Brain Activity ◽

Effective Connectivity ◽

Red Light ◽

Spectral Composition ◽

Brain Regions ◽

Graphical Analysis ◽

Sleep Inertia ◽

Temporal Persistence

Abstract Introduction Waking from sleep is associated with reduced alertness due to sleep inertia. Light acutely improves alertness during sleep deprivation. In this study we assessed the influence of light on brain activity and connectivity after waking from slow wave sleep (SWS). Methods Twelve participants kept an actigraphy-confirmed stable sleep schedule with 8.5 hours for five nights and five hours for one night prior to an overnight laboratory visit. Participants completed two three-minute Karolinska Drowsiness Tests (KDT) before going to bed at their habitual bedtime. They were monitored continuously using high-density EEG (32-channel; Brain Products GmbH). Participants were woken twice and exposed to red light (0.01 melanopic-lux; control) or blue-enriched light (63.62 melanopic-lux) for one hour, in a randomized order, following at least five minutes of SWS. EEG artifact were removed algorithmically and the spectral composition of each electrode (i.e., fast fourier transform, FFT) and effective connectivity (i.e., partial directed coherence, PDC) between each electrode were estimated. A graphical analysis was conducted to extract features relevant to the facilitation of efficient communication between electrodes. All data were averaged within frequency bins of interest that correspond to delta (1-3Hz), theta (4-7Hz), alpha (8-12Hz), and beta (13-25Hz) bands and expressed relative to the pre-sleep baseline. Results Compared to the pre-sleep baseline, participants exposed to blue-enriched light experienced reduced theta and alpha activity; however, these results were not significantly different from the control. In contrast, the communication of frontal electrodes significantly increased across all frequency bands compared to the control, and this effect was most prominent in the alpha (t(11)=3.80, p=.005) and beta bands (t(11)=3.92, p=.004). Conclusion Exposure to blue-enriched light immediately after waking from SWS may accelerate the process of waking and help to improve alertness by facilitating communication between brain regions. Future analyses will explore the temporal persistence and granularity of the communicative properties associated with this response. Support Naval Postgraduate School Grant. NASA Airspace Operations and Safety Program, System-Wide Safety Project.

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Local sleep homeostasis in the avian brain: convergence of sleep function in mammals and birds?

Proceedings of The Royal Society B Biological Sciences ◽

10.1098/rspb.2010.2316 ◽

2011 ◽

Vol 278 (1717) ◽

pp. 2419-2428 ◽

Cited By ~ 72

Author(s):

John A. Lesku ◽

Alexei L. Vyssotski ◽

Dolores Martinez-Gonzalez ◽

Christiane Wilzeck ◽

Niels C. Rattenborg

Keyword(s):

Slow Wave ◽

Rem Sleep ◽

Visual Processing ◽

Slow Wave Sleep ◽

Brain Activity ◽

Brain Regions ◽

Avian Brain ◽

Brain Functioning ◽

Sleep Homeostasis ◽

Local Sleep

The function of the brain activity that defines slow wave sleep (SWS) and rapid eye movement (REM) sleep in mammals is unknown. During SWS, the level of electroencephalogram slow wave activity (SWA or 0.5–4.5 Hz power density) increases and decreases as a function of prior time spent awake and asleep, respectively. Such dynamics occur in response to waking brain use, as SWA increases locally in brain regions used more extensively during prior wakefulness. Thus, SWA is thought to reflect homeostatically regulated processes potentially tied to maintaining optimal brain functioning. Interestingly, birds also engage in SWS and REM sleep, a similarity that arose via convergent evolution, as sleeping reptiles and amphibians do not show similar brain activity. Although birds deprived of sleep show global increases in SWA during subsequent sleep, it is unclear whether avian sleep is likewise regulated locally. Here, we provide, to our knowledge, the first electrophysiological evidence for local sleep homeostasis in the avian brain. After staying awake watching David Attenborough's The Life of Birds with only one eye, SWA and the slope of slow waves (a purported marker of synaptic strength) increased only in the hyperpallium—a primary visual processing region—neurologically connected to the stimulated eye. Asymmetries were specific to the hyperpallium, as the non-visual mesopallium showed a symmetric increase in SWA and wave slope. Thus, hypotheses for the function of mammalian SWS that rely on local sleep homeostasis may apply also to birds.

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Inefficient Encoding as an Explanation for Age-Related Deficits in Recollection-Based Processing

Journal of Psychophysiology ◽

10.1027/0269-8803/a000122 ◽

2014 ◽

Vol 28 (3) ◽

pp. 148-161 ◽

Cited By ~ 12

Author(s):

David Friedman ◽

Ray Johnson

Keyword(s):

Older Adults ◽

Young Adults ◽

Cognitive Processes ◽

Brain Activity ◽

Memory Performance ◽

Brain Regions ◽

Semantic Retrieval ◽

Age Related ◽

The Face ◽

Episodic Memories

A cardinal feature of aging is a decline in episodic memory (EM). Nevertheless, there is evidence that some older adults may be able to “compensate” for failures in recollection-based processing by recruiting brain regions and cognitive processes not normally recruited by the young. We review the evidence suggesting that age-related declines in EM performance and recollection-related brain activity (left-parietal EM effect; LPEM) are due to altered processing at encoding. We describe results from our laboratory on differences in encoding- and retrieval-related activity between young and older adults. We then show that, relative to the young, in older adults brain activity at encoding is reduced over a brain region believed to be crucial for successful semantic elaboration in a 400–1,400-ms interval (left inferior prefrontal cortex, LIPFC; Johnson, Nessler, & Friedman, 2013 ; Nessler, Friedman, Johnson, & Bersick, 2007 ; Nessler, Johnson, Bersick, & Friedman, 2006 ). This reduced brain activity is associated with diminished subsequent recognition-memory performance and the LPEM at retrieval. We provide evidence for this premise by demonstrating that disrupting encoding-related processes during this 400–1,400-ms interval in young adults affords causal support for the hypothesis that the reduction over LIPFC during encoding produces the hallmarks of an age-related EM deficit: normal semantic retrieval at encoding, reduced subsequent episodic recognition accuracy, free recall, and the LPEM. Finally, we show that the reduced LPEM in young adults is associated with “additional” brain activity over similar brain areas as those activated when older adults show deficient retrieval. Hence, rather than supporting the compensation hypothesis, these data are more consistent with the scaffolding hypothesis, in which the recruitment of additional cognitive processes is an adaptive response across the life span in the face of momentary increases in task demand due to poorly-encoded episodic memories.

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Resting‐State EEG Microstates Parallel Age‐Related Differences in Allocentric Spatial Working Memory Performance

Brain Topography ◽

10.1007/s10548-021-00835-3 ◽

2021 ◽

Author(s):

Adeline Jabès ◽

Giuliana Klencklen ◽

Paolo Ruggeri ◽

Christoph M. Michel ◽

Pamela Banta Lavenex ◽

...

Keyword(s):

Older Adults ◽

Working Memory ◽

Resting State ◽

Cognitive Aging ◽

Temporal Dynamics ◽

Spatial Working Memory ◽

Brain Activity ◽

Memory Performance ◽

Brain Regions ◽

Age Related

AbstractAlterations of resting-state EEG microstates have been associated with various neurological disorders and behavioral states. Interestingly, age-related differences in EEG microstate organization have also been reported, and it has been suggested that resting-state EEG activity may predict cognitive capacities in healthy individuals across the lifespan. In this exploratory study, we performed a microstate analysis of resting-state brain activity and tested allocentric spatial working memory performance in healthy adult individuals: twenty 25–30-year-olds and twenty-five 64–75-year-olds. We found a lower spatial working memory performance in older adults, as well as age-related differences in the five EEG microstate maps A, B, C, C′ and D, but especially in microstate maps C and C′. These two maps have been linked to neuronal activity in the frontal and parietal brain regions which are associated with working memory and attention, cognitive functions that have been shown to be sensitive to aging. Older adults exhibited lower global explained variance and occurrence of maps C and C′. Moreover, although there was a higher probability to transition from any map towards maps C, C′ and D in young and older adults, this probability was lower in older adults. Finally, although age-related differences in resting-state EEG microstates paralleled differences in allocentric spatial working memory performance, we found no evidence that any individual or combination of resting-state EEG microstate parameter(s) could reliably predict individual spatial working memory performance. Whether the temporal dynamics of EEG microstates may be used to assess healthy cognitive aging from resting-state brain activity requires further investigation.

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Bi-Temporal Anodal Transcranial Direct Current Stimulation during Slow-Wave Sleep Boosts Slow-Wave Density but Not Memory Consolidation

Brain Sciences ◽

10.3390/brainsci11040410 ◽

2021 ◽

Vol 11 (4) ◽

pp. 410

Author(s):

Simon Ruch ◽

Kristoffer Fehér ◽

Stephanie Homan ◽

Yosuke Morishima ◽

Sarah Maria Mueller ◽

...

Keyword(s):

Episodic Memory ◽

Slow Wave ◽

Direct Current ◽

Memory Consolidation ◽

Transcranial Direct Current Stimulation ◽

Slow Wave Sleep ◽

Memory Performance ◽

Direct Current Stimulation ◽

Sleep Parameters ◽

Episodic Memories

Slow-wave sleep (SWS) has been shown to promote long-term consolidation of episodic memories in hippocampo–neocortical networks. Previous research has aimed to modulate cortical sleep slow-waves and spindles to facilitate episodic memory consolidation. Here, we instead aimed to modulate hippocampal activity during slow-wave sleep using transcranial direct current stimulation in 18 healthy humans. A pair-associate episodic memory task was used to evaluate sleep-dependent memory consolidation with face–occupation stimuli. Pre- and post-nap retrieval was assessed as a measure of memory performance. Anodal stimulation with 2 mA was applied bilaterally over the lateral temporal cortex, motivated by its particularly extensive connections to the hippocampus. The participants slept in a magnetic resonance (MR)-simulator during the recordings to test the feasibility for a future MR-study. We used a sham-controlled, double-blind, counterbalanced randomized, within-subject crossover design. We show that stimulation vs. sham significantly increased slow-wave density and the temporal coupling of fast spindles and slow-waves. While retention of episodic memories across sleep was not affected across the entire sample of participants, it was impaired in participants with below-average pre-sleep memory performance. Hence, bi-temporal anodal direct current stimulation applied during sleep enhanced sleep parameters that are typically involved in memory consolidation, but it failed to improve memory consolidation and even tended to impair consolidation in poor learners. These findings suggest that artificially enhancing memory-related sleep parameters to improve memory consolidation can actually backfire in those participants who are in most need of memory improvement.

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Selection of stimulus parameters for enhancing slow wave sleep events with a Neural-field theory thalamocortical computational model

10.1101/2021.02.03.429528 ◽

2021 ◽

Author(s):

Felipe A. Torres ◽

Patricio Orio ◽

María-José Escobar

Keyword(s):

Computational Model ◽

Slow Wave ◽

Memory Consolidation ◽

Closed Loop ◽

Slow Wave Sleep ◽

Brain Activity ◽

Sensory Stimulation ◽

Sleep Spindles ◽

Slow Oscillations ◽

Closed Loop Stimulation

AbstractSlow-wave sleep cortical brain activity, conformed by slow-oscillations and sleep spindles, plays a key role in memory consolidation. The increase of the power of the slow-wave events, obtained by auditory sensory stimulation, positively correlates to memory consolidation performance. However, little is known about the experimental protocol maximizing this effect, which could be induced by the power of slow-oscillation, the number of sleep spindles, or the timing of both events’ co-occurrence. Using a mean-field model of thalamocortical activity, we studied the effect of several stimulation protocols, varying the pulse shape, duration, amplitude, and frequency, as well as a target-phase using a closed-loop approach. We evaluated the effect of these parameters on slow-oscillations (SO) and sleep-spindles (SP), considering: (i) the power at the frequency bands of interest, (ii) the number of SO and SP, (iii) co-occurrences between SO and SP, and (iv) synchronization of SP with the up-peak of the SO. The first three targets are maximized using a decreasing ramp pulse with a pulse duration of 50 ms. Also, we observed a reduction in the number of SO when increasing the stimulus energy by rising its amplitude. To assess the target-phase parameter, we applied closed-loop stimulation at 0º, 45º, and 90º of the phase of the narrow-band filtered ongoing activity, at 0.85 Hz as central frequency. The 0º stimulation produces better results in the power and number of SO and SP than the rhythmic or aleatory stimulation. On the other hand, stimulating at 45º or 90º change the timing distribution of spindles centers but with fewer co-occurrences than rhythmic and 0º phase. Finally, we propose the application of closed-loop stimulation at the rising zero-cross point using pulses with a decreasing ramp shape and 50 ms of duration for future experimental work.Author summaryDuring the non-REM (NREM) phase of sleep, events that are known as slow oscillations (SO) and spindles (SP) can be detected by EEG. These events have been associated with the consolidation of declarative memories and learning. Thus, there is an ongoing interest in promoting them during sleep by non-invasive manipulations such as sensory stimulation. In this paper, we used a computational model of brain activity that generates SO and SP, to investigate which type of sensory stimulus –shape, amplitude, duration, periodicity– would be optimal for increasing the events’ frequency and their co-occurrence. We found that a decreasing ramp of 50 ms duration is the most effective. The effectiveness increases when the stimulus pulse is delivered in a closed-loop configuration triggering the pulse at a target phase of the ongoing SO activity. A desirable secondary effect is to promote SPs at the rising phase of the SO oscillation.

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A functional MRI study of presurgical cognitive deficits in glioma patients

Neuro-Oncology Practice ◽

10.1093/nop/npaa059 ◽

2020 ◽

Author(s):

Irena T Schouwenaars ◽

Miek J de Dreu ◽

Geert-Jan M Rutten ◽

Nick F Ramsey ◽

Johan M Jansma

Keyword(s):

Functional Mri ◽

Cognitive Deficits ◽

Brain Activity ◽

Neuropsychological Testing ◽

Region Of Interest ◽

High Grade Glioma ◽

Brain Regions ◽

Brain State ◽

Low Grade ◽

Activity Levels

Abstract Background The main goal of this functional MRI (fMRI) study was to examine whether cognitive deficits in glioma patients prior to treatment are associated with abnormal brain activity in either the central executive network (CEN) or default mode network (DMN). Methods Forty-six glioma patients, and 23 group-matched healthy controls (HCs) participated in this fMRI experiment, performing an N-back task. Additionally, cognitive profiles of patients were evaluated outside the scanner. A region of interest–based analysis was used to compare brain activity in CEN and DMN between groups. Post hoc analyses were performed to evaluate differences between low-grade glioma (LGG) and high-grade glioma (HGG) patients. Results In-scanner performance was lower in glioma patients compared to HCs. Neuropsychological testing indicated cognitive impairment in LGG as well as HGG patients. fMRI results revealed normal CEN activation in glioma patients, whereas patients showed reduced DMN deactivation compared to HCs. Brain activity levels did not differ between LGG and HGG patients. Conclusions Our study suggests that cognitive deficits in glioma patients prior to treatment are associated with reduced responsiveness of the DMN, but not with abnormal CEN activation. These results suggest that cognitive deficits in glioma patients reflect a reduced capacity to achieve a brain state necessary for normal cognitive performance, rather than abnormal functioning of executive brain regions. Solely focusing on increases in brain activity may well be insufficient if we want to understand the underlying brain mechanism of cognitive impairments in patients, as our results indicate the importance of assessing deactivation.

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0084 Sleep Consolidates Incidentally Encoded Information After Deep but Not Shallow Encoding

SLEEP ◽

10.1093/sleep/zsaa056.082 ◽

2020 ◽

Vol 43 (Supplement_1) ◽

pp. A34-A34

Author(s):

E M Wernette ◽

K M Fenn

Keyword(s):

Slow Wave ◽

Memory Consolidation ◽

Slow Wave Sleep ◽

Declarative Memory ◽

Memory Performance ◽

Memory Test ◽

Memory Traces ◽

Incidental Encoding ◽

The Relationship ◽

With Memory

Abstract Introduction Slow wave sleep (SWS) strengthens declarative memory for information studied for a later test. However, research on the effect of sleep on information that is not intentionally remembered is scare. Previous research from our lab suggests sleep consolidates some, but not all, information that has been encoded incidentally, meaning that it has been acted on but not intentionally remembered. It remains unclear what determines which information benefits from sleep-dependent consolidation processes and what aspects of sleep are related to these mnemonic benefits. In two experiments, we test the hypothesis that sleep consolidates strong but not weak memory traces following incidental encoding, and assess the relationship between memory performance and objective sleep characteristics. Methods In Experiment 1, participants rated words one (weak traces) or three times (strong traces) in a deep or shallow incidental encoding task. Participants either rated words on a scale from ‘concrete’ to ‘abstract’ (deep) or counted the vowels in the words (shallow). Following a 12-hour period containing sleep or wakefulness, participants took a surprise memory test. In Experiment 2, participants rated words one or three times in the deep encoding task, received an 8-hour sleep opportunity with polysomnography, and took the surprise memory test. Results In Experiment 1, participants remembered words better after sleep than wake regardless of whether words were encoded one or three times, but only after deep encoding. Sleep did not consolidate information following shallow encoding. Experiment 2 is ongoing, but we predict that the amount of SWS will correlate positively with memory. Conclusion Results thus far suggest sleep may have consolidated information based on the strength of memory traces. Because deep encoding results in stronger memory traces than shallow encoding, this work is broadly consistent with theories of memory consolidation that predict sleep is more beneficial for strong memory traces than weak, such as the synaptic downscaling hypothesis. Support N/A

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