Persistent neural activity often outlasts sensory stimulation, forming a bridge between perception and action. Such activity has been associated commonly with working memory, decision making, and action preparation under active task conditions. However, its existence and characteristics during passive states and sleep remain understudied. Using chronic high-density electrophysiology in freely behaving mice, we show that persistent population spiking activity in the mouse auditory cortical hierarchy enables decoding of past stimuli after their physical offset, during both wakefulness and natural sleep. Using time-resolved decoding, we demonstrate that in wakefulness, persistent representation decays uniformly across early sensory and association cortices. In contrast, sleep is associated with longer persistent stimulus representation in association cortex, while early auditory regions maintain shorter wake-like dynamics. These results reveal how the brain maintains sensory information across behavioral states and establish that persistent representation is a passive and state-dependent feature of sensory processing.

REM sleep behavior disorder (RBD), involving REM sleep without atonia (RSWA), is a prodromal marker of Parkinson’s disease (PD). We investigated whether RBD may represent the “tip of the iceberg” of pathology driving wider REM sleep disruptions. In this study, 25 early-stage, drug-naïve PD patients and 23 age-matched healthy controls underwent overnight polysomnography with high-density EEG (256 channels) to assess how sleep patterns relate to generalized motor learning (GML). PD patients showed no significant differences in overall sleep architecture but exhibited elevated RSWA levels, with 9 individuals (36% of the PD group) meeting criteria for excessive RSWA (PD+RSWA). Spectral analysis revealed increased occipital-parietal theta activity during REM sleep in PD+RSWA patients, which correlated with disease progression. In both healthy participants and PD patients, sleep benefited consolidation of overnight GML. However, only in PD patients, and particularly in PD+RSWA, REM sleep duration was negatively correlated with behavioral benefits in the GML task. These findings suggest that subtle REM sleep abnormalities extend beyond clinically defined RBD and may contribute to impaired sleep-dependent memory consolidation in early PD. REM sleep disruptions could serve as an early neurophysiological marker of disease progression and a potential target for therapeutic intervention.

The sleeping brain processes memory-related semantic information, yet decoding such content remains challenging. Combining a large, openly shared sleep EEG dataset with neural contrastive learning, Chen et al.,1 in this issue of Neuron, establish a promising framework for non-invasive decoding of the sleeping human mind.

Purpose:In anesthesia research and clinical practice, the level of consciousness is often assessed by stimulating subjects and observing their responses. It is possible that such stimulation alters the very state of consciousness being assessed. Whether this phenomenon is accompanied by specific cortical activities remains unknown. Here, we tested the effects of behavioral assessments on neuronal activity in the rat primary auditory cortex (A1) and perirhinal cortex (PrC). Methods:Neuronal spiking activity was recorded from microwire arrays targeting A1 and/or PrC in rats (n = 9), whilst presenting 40 Hz click-trains and gradually increasing infusion rates of propofol, remifentanil, ketamine or dexmedetomidine. We assessed righting reflex, pain withdrawal, whisking reflex, and corneal reflex every 12 minutes (every 360 auditory trials). We searched for significant changes in baseline firing rate and stimulus-evoked activities (where present) due to the behavioral assessments, by comparing 4 min intervals before and after the behavioral tests. Results:Out of 1004 units in 20 sessions, we found significantly elevated activity (p < 0.01) following behavioral tests in 32% and 20% of A1 auditory-responsive units and 8.6% and 5.3% of auditory-unresponsive units under propofol and dexmedetomidine, respectively, but not under remifentanil or ketamine. A higher proportion of units modulated their firing following behavioral tests in A1 compared to PrC, with median gains ranging from +0.23 to +1.06, depending on the specific response feature. Conclusion:Behavioral testing increases ongoing firing rate and responses to sounds in some cortical neurons. This increase is more prevalent in A1 than in PrC, mirroring clinical observations that patients exhibit basic responses under sedation, while complex processing, such as memory encoding, is impaired. The degree of neuronal modulation due to behavioral testing varies between anesthetic agents, mirroring their clinical phenotypes.

Significance:Accurate monitoring of pupil size and gaze direction is critical in clinical and research contexts; however, current pupillometry methods require open eyes, limiting their use in patients under anesthesia, sedation, or sleep. Short-wave infrared (SWIR) imaging enables noninvasive closed-eye pupillometry, but challenges remain due to eyelid glare, gaze variability, and low signal-to-noise ratio (SNR). Aim:We aimed to enhance closed-eye pupillometry by integrating polarization filters into the SWIR imaging system and developing improved algorithms for pupil localization and gaze direction estimation under natural closed-eye conditions. Approach:Experiments were conducted on healthy volunteers using SWIR imaging with different polarizer configurations (parallel, partially crossed, crossed, and no polarizers). Pupillary light reflexes (PLR) were recorded under open- and closed-eye conditions with both forward fixation and varying gaze directions. Image analysis incorporated brightness difference imaging and statistical modeling to evaluate maximal brightness change and SNR. Results:In open-eye settings, parallel polarizers produced the strongest PLR signal, but in closed-eye conditions, crossed polarizers significantly improved image quality by suppressing eyelid glare. The crossed configuration yielded the highest PLR brightness change and SNR compared with parallel or no polarizers, enabling reliable pupil localization across multiple gaze directions. Improved algorithms allowed robust PLR detection even under natural eyelid closure and variable gaze positions. Conclusions:Integrating crossed polarizers into SWIR-based pupillometry substantially enhances signal fidelity and pupil localization through closed eyelids. This approach overcomes major limitations of previous methods and enables accurate, touchless pupillometry in clinically relevant conditions. These advances pave the way for applications in anesthesiology, sleep medicine, and neurocritical care.

Human memory is typically studied by direct questioning, and the recollection of events is investigated through verbal reports. Thus, current research confounds memory per-se with its report. Critically, the ability to investigate memory retrieval in populations with deficient verbal ability is limited. Here, using the MEGA (Memory Episode Gaze Anticipation) paradigm, we show that monitoring anticipatory gaze using eye tracking can quantify memory retrieval without verbal report. Upon repeated viewing of movie clips, eye gaze patterns anticipating salient events can quantify their memory traces seconds before these events appear on the screen. A series of five experiments with a total of 145 participants using either tailor-made animations or naturalistic movies consistently reveal that accumulated gaze proximity to the event can index memory. Machine learning-based classification can identify whether a given viewing is associated with memory for the event based on single-trial data of gaze features. Detailed comparison to verbal reports establishes that anticipatory gaze marks recollection of associative memory about the event, whereas pupil dilation captures familiarity. Finally, anticipatory gaze reveals beneficial effects of sleep on memory retrieval without verbal report, illustrating its broad applicability across cognitive research and clinical domains.

INTRODUCTION:Alzheimer's disease (AD) disrupts human sleep architecture more severely than normal aging. However, it remains unclear how AD changes oscillatory neural activity during sleep, and whether such changes foreshadow cognitive decline in AD. METHODS:We used high-density electroencephalography sleep recordings in 55 participants: (1) 21 healthy older adults, (2) 28 patients with amnestic mild cognitive impairment (aMCI)-a prodromal AD stage, and (3) 6 AD patients. RESULTS:Cognitive performance robustly decreases with the slow wave (SW) trough amplitude and its synchronization across broad frontocentral cortical areas. Thus, across the AD spectrum, slow wave synchrony declines with cognition, as in normal aging, but at an accelerated pace. Moreover, delayed rapid eye movement (REM) sleep onset in aMCI and AD patients was associated with deficient SW activity, suggesting insufficiently restorative non-REM sleep. DISCUSSION:These findings suggest that impaired slow waves are closely linked to cognitive impairment and mark disrupted neural activity in AD progression. HIGHLIGHTS:Detailed analysis of high-density sleep electroencephalography was performed in amnestic mild cognitive impairment and Alzheimer's disease (AD) patients. Cognitive status robustly correlates with slow wave trough and its cortical spread. Delayed rapid eye movement sleep onset associated with AD correlates with diminished slow wave troughs. Impaired slow waves mark progressively disrupted neural activity in prodromal AD.

The locus coeruleus-norepinephrine (LC-NE) system regulates arousal and awakening; however, it remains unclear whether the LC does this in a global or circuit-specific manner. We hypothesized that sensory-evoked awakenings are predominantly regulated by specific LC-NE efferent pathways. Anatomical, physiological, and functional modularities of LC-NE pathways involving the mouse basal forebrain (BF) and pontine reticular nucleus (PRN) were tested. We found partial anatomical segregation between the LC → PRN and LC → BF circuits. Extracellular NE dynamics in BF and PRN exhibited distinct sound-evoked activation during sleep, including a fast sound-evoked NE peak specific to PRN. Causal optogenetic interrogation of LC efferent pathways, by retro-channelrhodopsin (ChR2) activation or Platynereis dumerilii ciliary opsin (PdCO) silencing of synapses in target regions, revealed a role for early LC → PRN activity in driving arousal and sound-evoked awakenings. Together, our results uncover a role for early LC-NE PRN activity in connecting sensory and arousal pathways and establish LC heterogeneity in regulating arousal.

Studies of human perception have shown early cortical signals for primary information encoding, and later signals for higher order processing. An important late signal is the cortical event-related desynchronization (ERD) in the alpha (8-12 Hz) and beta (12-30 Hz) frequency band, which has been linked to human perceptual awareness. Detailed mechanistic investigation of the ERD would be greatly facilitated by availability of a suitable animal model. We conducted local field potential recordings in the mouse frontal association cortex (FrA), thalamic intralaminar centrolateral nucleus (CL), primary auditory cortex (A1), and primary visual cortex (V1) during two auditory tasks. Fully audible brief 50 ms stimuli with both tasks produced early broadband gamma (30-100 Hz) frequency activity at 0-250ms, followed by a late cortical alpha/beta ERD 250-750 ms after stimulus onset. The ERD was statistically significant in FrA and A1, but not in V1. Interestingly, a significant ERD was also observed in thalamic CL. The magnitude of the ERD at full stimulus intensity, and the slope of the relationship between stimulus intensity versus ERD magnitude, were both largest in FrA, and smaller in CL and A1. Conversely, for early broadband gamma activity the magnitude at full intensity and slopes were largest in A1, smaller in CL and smaller still in FrA. These findings strongly support mice as a promising platform for further investigation of the ERD to better understand the origin and function of this robust yet understudied electrophysiological phenomenon.

Sleep research uses electroencephalography (EEG) to infer brain activity in health and disease. Beyond standard sleep scoring, there is growing interest in advanced EEG analysis that requires extensive preprocessing to improve the signal-to-noise ratio and specialized analysis algorithms. While many EEG software packages exist, sleep research has unique needs (e.g., specific artifacts, event detection). Currently, sleep investigators use different libraries for specific tasks in a 'fragmented' configuration that is inefficient, prone to errors, and requires the learning of multiple software environments. This complexity creates a barrier for beginners. Here, we present SleepEEGpy, an open-source Python package that simplifies sleep EEG preprocessing and analysis. SleepEEGpy builds on MNE-Python, PyPREP, YASA, and SpecParam to offer an all-in-one, beginner-friendly package for comprehensive sleep EEG research, including (i) cleaning, (ii) independent component analysis, (iii) sleep event detection, (iv) spectral feature analysis, and visualization tools. A dedicated dashboard provides an overview to evaluate data and preprocessing, serving as an initial step prior to detailed analysis. We demonstrate SleepEEGpy's functionalities using overnight high-density EEG data from healthy participants, revealing characteristic activity signatures typical of each vigilance state: alpha oscillations in wakefulness, spindles and slow waves in NREM sleep, and theta activity in REM sleep. We hope that this software will be adopted and further developed by the sleep research community, and constitute a useful entry point tool for beginners in sleep EEG research.

Studies of human perception have shown early cortical signals for primary information encoding, and later signals for higher order processing. An important late signal is the cortical event-related desynchronization (ERD) in the alpha (8-12Hz) and beta (12-30Hz) frequency band, which has been linked to human perceptual awareness. Detailed mechanistic investigation of the ERD would be greatly facilitated by availability of a suitable animal model. We conducted local field potential recordings in the mouse frontal association cortex (FrA), thalamic intralaminar centrolateral nucleus (Cl), primary auditory cortex (A1), and primary visual cortex (V1) during two auditory tasks. Fully audible brief 50 ms stimuli with both tasks produced early broadband gamma (30-100Hz) frequency activity at 0-250ms, followed by a late cortical alpha/beta ERD 250 - 750 ms after stimulus onset. The ERD was statistically significant in FrA and A1, but not in V1. Interestingly, a significant ERD was also observed in thalamic Cl. The magnitude of the ERD at full stimulus intensity, and the slope of the relationship between stimulus intensity versus ERD magnitude, were both largest in FrA, and smaller in Cl and A1. Conversely, for early broadband gamma activity the magnitude at full intensity and slopes were largest in A1, smaller in Cl and smaller still in FrA. These findings suggest that mice, like humans, process perceptual signals in hierarchically organized corticothalamic networks, and strongly support mice as a promising platform for further investigation of the ERD to better understand the origin and function of this robust yet understudied electrophysiological phenomenon. ### Competing Interest Statement The authors have declared no competing interest.

Overgeneralization of negative experiences, in which aversive responses spread to otherwise safe stimuli, often co-occurs with sleep disruption, and both are central features of anxiety and posttraumatic stress disorder (PTSD). Here, we show that sleep shifts emotional generalization away from the negative and toward the positive. Across three experiments combining behavior, fMRI, and sleep electrophysiology, participants learned to associate three faces with positive, negative, or neutral outcomes. Participants were tested using morphed faces that blended the original stimuli in varying proportions. Immediate generalization was assessed post-learning, and delayed generalization was assessed after overnight sleep or daytime wakefulness. Behaviorally, we found that sleep selectively promotes positive generalization, whereas prolonged daytime wakefulness favors generalization of the negative face. In the fMRI scanner, amygdala and limbic activity during outcome processing predicted stronger immediate generalization of the negative face, and subsequent shift from negative to positive face generalization that occurred only after sleep. Overnight sleep spindle activity, extracted from high-density sleep EEG, positively correlated both with positive face generalization and with the shift from negative to positive generalization following sleep. These findings reveal a potential neural mechanism by which sleep attenuates negative bias and enhances positive representations, suggesting a potential method to buffer against maladaptive generalization in anxiety and PTSD. ### Competing Interest Statement The authors have declared no competing interest.

The neural processes that change when falling asleep are only partially understood. At the cortical level, features of both spontaneous neural activity and sensory responses change between wakefulness and sleep. For example, in the early auditory cortex, sleep increases the occurrence of postonset silent (OFF) periods and elevates population synchrony. However, it remains unknown whether such changes occur abruptly or gradually around sleep onset and awakening. Here, we recorded spontaneous and sound-evoked neuronal spiking activity in the early auditory cortex along with polysomnography during thousands of episodes when male rats fell asleep or woke up. We found that when falling asleep, stimulus-induced neuronal silent periods (OFF periods), characteristic of nonrapid eye movement sleep, increased within a few seconds around sleep onset. In contrast, a gradual increase in neuronal population synchrony built up over tens of seconds until reaching maximal levels. EEG auditory-evoked potentials likely representing stimulus-triggered "K-complexes" changed along with postonset neuronal firing, whereas ongoing EEG slow-wave activity was associated with neuronal population synchrony. Similar effects, but with opposite direction, were observed around awakenings. The results highlight late stimulus-induced neuronal silence as a key feature changing abruptly around transitions between vigilance states, likely reflecting neuronal bistability and manifesting also in EEG-evoked potentials. More generally, these findings emphasize the added value of going beyond monitoring ongoing activity and perturbing the nervous system to reveal its state-an insight that could also help guide the development of more sensitive noninvasive monitors of falling asleep in humans.

Human memory is typically studied by direct questioning, and the recollection of events is investigated through verbal reports. Thus, current research confounds memory per-se with its report. Critically, the ability to investigate memory retrieval in populations with deficient verbal ability is limited. Here, using the MEGA (Memory Episode Gaze Anticipation) paradigm, we show that monitoring anticipatory gaze using eye tracking can quantify memory retrieval without verbal report. Upon repeated viewing of movie clips, eye gaze patterns anticipating salient events can quantify their memory traces seconds before these events appear on the screen. A series of experiments with a total of 126 participants using either tailor-made animations or naturalistic movies consistently reveal that accumulated gaze proximity to the event can index memory. Machine learning-based classification can identify whether a given viewing is associated with memory for the event based on single-trial data of gaze features. Detailed comparison to verbal reports establishes that anticipatory gaze marks recollection of associative memory about the event, whereas pupil dilation captures familiarity. Finally, anticipatory gaze reveals beneficial effects of sleep on memory retrieval without verbal report, illustrating its broad applicability across cognitive research and clinical domains. ### Competing Interest Statement The authors have declared no competing interest.

The claustrum has been linked to attention and sleep. We hypothesized that this reflects a shared function, determining responsiveness to stimuli, which spans the axis of engagement. To test this hypothesis, we recorded claustrum population dynamics from male mice during both sleep and an attentional task ('ENGAGE'). Heightened activity in claustrum neurons projecting to the anterior cingulate cortex (ACCp) corresponded to reduced sensory responsiveness during sleep. Similarly, in the ENGAGE task, heightened ACCp activity correlated with disengagement and behavioral lapses, while low ACCp activity correlated with hyper-engagement and impulsive errors. Chemogenetic elevation of ACCp activity reduced both awakenings during sleep and impulsive errors in the ENGAGE task. Furthermore, mice employing an exploration strategy in the task showed a stronger correlation between ACCp activity and performance compared to mice employing an exploitation strategy which reduced task complexity. Our results implicate ACCp claustrum neurons in restricting engagement during sleep and goal-directed behavior. Attention and sleep have been associated with the claustrum. Here authors pinpoint a cluster of neurons in the claustrum of male mice that dynamically determines engagement levels during both sleep and an attentional task.

Abstract Background Assessments of gaze direction (eye movements), pupil size, and the pupillary light reflex (PLR) are critical for neurological examination and neuroscience research and constitute a powerful tool in diverse clinical settings ranging from critical care through endocrinology and drug addiction to cardiology and psychiatry. However, current bedside pupillometry is typically intermittent, qualitative, manual, and limited to open-eye cases, restricting its use in sleep medicine, anesthesia, and intensive care. Methods We combined short-wave infrared (SWIR, ~0.9-1.7μm) imaging with image processing algorithms to perform rapid (~30 ms) pupillometry and eye tracking behind closed eyelids. Forty-three healthy volunteers participated in two experiments with PLR evoked by visible light stimuli or directing eye movements towards screen targets. Imaging was performed simultaneously on one eye closed, and the other open eye serving as ground truth. Data analysis was performed with a custom approach quantifying changes in brightness around the pupil area or with a deep learning U-NET-based procedure. Results Here we show that analysis of SWIR imaging data can successfully measure stimulus-evoked PLR in closed-eye conditions, revealing PLR events in single trials and significant PLRs in nearly all individual subjects, as well as estimating gaze direction. The neural net-based analysis could successfully use closed-eye SWIR data to recreate estimates of open-eye images and assess pupil size. Conclusions Continuous touchless monitoring of rapid dynamics in pupil size and gaze direction through closed eyes paves the way for developing devices with wide-ranging applications, fulfilling long-standing goals in clinical and research fields.

Sleep improves the consolidation and long-term stability of newly formed memories and associations. Most research on human declarative memory and its consolidation during sleep uses word-pair associations requiring exhaustive learning. In the present study, we present the visual paired association learning (vPAL) paradigm, in which participants learn new associations between images of celebrities and animals. The vPAL is based on a one-shot exposure that resembles learning in natural conditions. We tested if vPAL can reveal a role for sleep in memory consolidation by assessing the specificity of memory recognition, and the cued recall performance, before and after sleep. We found that a daytime nap improved the stability of recognition memory and discrimination abilities compared to identical intervals of wakefulness. By contrast, cued recall of associations did not exhibit significant sleep-dependent effects. High-density electroencephalography during naps further revealed an association between sleep spindle density and stability of recognition memory. Thus, the vPAL paradigm opens new avenues for future research on sleep and memory consolidation across ages and heterogeneous populations in health and disease.

An essential aspect of motor learning is generalizing procedural knowledge to facilitate skill acquisition across diverse conditions. Here, we examined the development of generalized motor learning during initial practice-dependent learning, and how distinct components of learning are consolidated over longer timescales during wakefulness or sleep. In the first experiment, a group of young healthy volunteers engaged in a novel motor sequence task over 36 h in a two-arm experimental design (either morning-evening-morning, or evening-morning-evening) aimed at controlling for circadian confounders. The findings unveiled an immediate, rapid generalization of sequential learning, accompanied by an additional long-timescale performance gain. Sleep modulated accuracy, but not speed, above and beyond equivalent wake intervals. To further elucidate the role of sleep across ages and under neurodegenerative disorders, a second experiment utilized the same task in a group of early-stage, drug-naïve individuals with Parkinson’s disease and in healthy individuals of comparable age. Participants with Parkinson’s disease exhibited comparable performance to their healthy age-matched group with the exception of reduced performance in recalling motor sequences, revealing a disease-related cognitive shortfall. In line with the results found in young subjects, both groups exhibited improved accuracy, but not speed, following a night of sleep. This result emphasizes the role of sleep in skill acquisition and provides a potential framework for deeper investigation of the intricate relationship between sleep, aging, Parkinson’s disease, and motor learning.