Cross-Frequency Coupling as a Biomarker for Early Stroke Recovery.

BACKGROUND: The application of neuroimaging-based biomarkers in stroke has enriched our understanding of post-stroke recovery mechanisms, including alterations in functional connectivity based on synchronous oscillatory activity across various cortical regions. Phase-amplitude coupling, a type of cross-frequency coupling, may provide additional mechanistic insight. OBJECTIVE: To determine how the phase of prefrontal cortex delta (1-3 Hz) oscillatory activity mediates the amplitude of motor cortex beta (13-20 Hz) oscillations in individual's early post-stroke. METHODS: Participants admitted to an inpatient rehabilitation facility completed resting and task-based EEG recordings and motor assessments around the time of admission and discharge along with structural neuroimaging. Unimpaired controls completed EEG procedures during a single visit. Mixed-effects linear models were performed to assess within- and between-group differences in delta-beta prefrontomotor coupling. Associations between coupling and motor status and injury were also determined. RESULTS: Thirty individuals with stroke and 17 unimpaired controls participated. Coupling was greater during task versus rest conditions for all participants. Though coupling during affected extremity task performance decreased during hospitalization, coupling remained elevated at discharge compared to controls. Greater baseline coupling was associated with better motor status at admission and discharge and positively related to motor recovery. Coupling demonstrated both positive and negative associations with injury involving measures of lesion volume and overlap injury to anterior thalamic radiation, respectively. CONCLUSIONS: This work highlights the utility of prefrontomotor cross-frequency coupling as a potential motor status and recovery biomarker in stroke. The frequency- and region-specific neurocircuitry featured in this work may also facilitate novel treatment strategies in stroke.

Dependence of rhythmic activity and oddball effects in the rat cortex on the depth of sedation during dissociative anesthesia.

The reactions to novelty manifesting in mismatch negativity in the rat brain were studied. During dissociative anesthesia, mismatch negativity-like waves were recorded from the somatosensory cortex using an epidural 32-electrode array. Experimental animals: 7 wild-type Wistar rats and 3 transgenic rats. During high-dose anesthesia, deviant 1,500 Hz tones were presented randomly among many standard 1,000 Hz tones in the oddball paradigm. "Deviant minus standard_before_deviant" difference waves were calculated using both the classical method of Naatanen and method of cross-correlation of sub-averages. Both methods gave consistent results: an early phasic component of the N40 and later N100 to 200 (mismatch negativity itself) tonic component. The gamma and delta rhythms power and the frequency of down-states (suppressed activity periods) were assessed. In all rats, the amplitude of tonic component grew with increasing sedation depth. At the same time, a decrease in gamma power with a simultaneous increase in delta power and the frequency of down-states. The earlier phasic frontocentral component is associated with deviance detection, while the later tonic one over the auditory cortex reflects the orienting reaction. Under anesthesia, this slow mismatch negativity-like wave most likely reflects the tendency of the system to respond to any influences with delta waves, K-complexes and down-states, or produce them spontaneously.

Sleep Delta power, age, and sex effects in treatment-resistant depression.

Electroencephalographic (EEG) deficits in slow wave activity or Delta power (0.5-4 Hz) indicate disturbed sleep homeostasis and are hallmarks of depression. Sleep homeostasis is linked to restorative sleep and potential antidepressant response via non-rapid eye movement (NREM) slow wave sleep (SWS) during which neurons undergo essential repair and rejuvenation. Decreased Low Delta power (0.5-2 Hz) was previously reported in individuals with depression. This study investigated power levels in the Low Delta (0.5-<2 Hz), High Delta (2-4 Hz), and Total Delta (0.5-4 Hz) bands and their association with age, sex, and disrupted sleep in treatment-resistant depression (TRD). Mann-Whitney U tests were used to compare the nightly progressions of Total Delta, Low Delta, and High Delta in 100 individuals with TRD and 24 healthy volunteers (HVs). Polysomnographic parameters were also examined, including Total Sleep Time (TST), Sleep Efficiency (SE), and Wake after Sleep Onset (WASO). Individuals with TRD had lower Delta power during the first NREM episode (NREM1) than HVs. The deficiency was observed in the Low Delta band versus High Delta. Females with TRD had higher Delta power than males during the first NREM1 episode, with the most noticeable sex difference observed in Low Delta. In individuals with TRD, Low Delta power correlated with WASO and SE, and High Delta correlated with WASO. Low Delta power deficits in NREM1 were observed in older males with TRD, but not females. These results provide compelling evidence for a link between age, sex, Low Delta power, sleep homeostasis, and non-restorative sleep in TRD.

Coincident development and synchronization of sleep-dependent delta in the cortex and medulla.

In early development, active sleep is the predominant sleep state before it is supplanted by quiet sleep. In rats, the developmental increase in quiet sleep is accompanied by the sudden emergence of the cortical delta rhythm (0.5-4 Hz) around postnatal day 12 (P12). We sought to explain the emergence of the cortical delta by assessing developmental changes in the activity of the parafacial zone (PZ), a medullary structure thought to regulate quiet sleep in adults. We recorded from the PZ in P10 and P12 rats and predicted an age-related increase in neural activity during increasing periods of delta-rich cortical activity. Instead, during quiet sleep, we discovered sleep-dependent rhythmic spiking activity-with intervening periods of total silence-phase locked to a local delta rhythm. Moreover, PZ and cortical delta were coherent at P12 but not at P10. PZ delta was also phase locked to respiration, suggesting sleep-dependent modulation of PZ activity by respiratory pacemakers in the ventral medulla. Disconnecting the main olfactory bulbs from the cortex did not diminish cortical delta, indicating that the influence of respiration on delta at this age is not mediated indirectly through nasal breathing. Finally, we observed an increase in parvalbumin-expressing terminals in the PZ across these ages, supporting a role for local GABAergic inhibition in the PZ's rhythmicity. The unexpected discovery of delta-rhythmic neural activity in the medulla-when cortical delta is also emerging-provides a new perspective on the brainstem's role in regulating sleep and promoting long-range functional connectivity in early development.

Spatiotemporal EEG dynamics of the sleep onset process in preadolescence.

BACKGROUND: During preadolescence the sleep electroencephalography undergoes massive qualitative and quantitative modifications. Despite these relevant age-related peculiarities, the specific EEG pattern of the wake-sleep transition in preadolescence has not been exhaustively described. METHODS: The aim of the present study is to characterize regional and temporal electrophysiological features of the sleep onset (SO) process in a group of 23 preadolescents (9-14 years) and to compare the topographical pattern of slow wave activity and delta/beta ratio of preadolescents with the EEG pattern of young adults. RESULTS: Results showed in preadolescence the same dynamics known for adults, but with peculiarities in the delta and beta activity, likely associated with developmental cerebral modifications: the delta power showed a widespread increase during the SO with central maxima, and the lower bins of the beta activity showed a power increase after SO. Compared to adults, preadolescents during the SO exhibited higher delta power only in the slowest bins of the band: before SO slow delta activity was higher in prefrontal, frontal and occipital areas in preadolescents, and, after SO the younger group had higher slow delta activity in occipital areas. In preadolescents delta/beta ratio was higher in more posterior areas both before and after the wake-sleep transition and, after SO, preadolescents showed also a lower delta/beta ratio in frontal areas, compared to adults. CONCLUSION: Results point to a general higher homeostatic drive for the developing areas, consistently with plastic-related maturational modifications, that physiologically occur during preadolescence.

Neurovascular Coupling Analysis Based on Multivariate Variational Gaussian Process Convergent Cross-Mapping.

Neurovascular coupling (NVC) provides important insights into the intricate activity of brain functioning and may aid in the early diagnosis of brain diseases. Emerging evidences have shown that NVC could be assessed by the coupling between electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). However, this endeavor presents significant challenges due to the absence of standardized methodologies and reliable techniques for coupling analysis of these two modalities. In this study, we introduced a novel method, i.e., the collaborative multi-output variational Gaussian process convergent cross-mapping (CMVGP-CCM) approach to advance coupling analysis of EEG and fNIRS. To validate the robustness and reliability of the CMVGP-CCM method, we conducted extensive experiments using chaotic time series models with varying noise levels, sequence lengths, and causal driving strengths. In addition, we employed the CMVGP-CCM method to explore the NVC between EEG and fNIRS signals collected from 26 healthy participants using a working memory (WM) task. Results revealed a significant causal effect of EEG signals, particularly the delta, theta, and alpha frequency bands, on the fNIRS signals during WM. This influence was notably observed in the frontal lobe, and its strength exhibited a decline as cognitive demands increased. This study illuminates the complex connections between brain electrical activity and cerebral blood flow, offering new insights into the underlying NVC mechanisms of WM.

A multiscale symbolic approach to decoding delta and ripple oscillation bands as biomarkers for epileptiform discharges.

We use a multiscale symbolic approach to study the complex dynamics of temporal lobe refractory epilepsy employing high-resolution intracranial electroencephalogram (iEEG). We consider the basal and preictal phases and meticulously analyze the dynamics across frequency bands, focusing on high-frequency oscillations up to 240 Hz. Our results reveal significant periodicities and critical time scales within neural dynamics across frequency bands. By bandpass filtering neural signals into delta, theta, alpha, beta, gamma, and ripple high-frequency bands (HFO), each associated with specific neural processes, we examine the distinct nonlinear dynamics. Our method introduces a reliable approach to pinpoint intrinsic time lag scales τ within frequency bands of the basal and preictal signals, which are crucial for the study of refractory epilepsy. Using metrics such as permutation entropy (H), Fisher information (F), and complexity (C), we explore nonlinear patterns within iEEG signals. We reveal the intrinsic τmax that maximize complexity within each frequency band, unveiling the nonlinear subtle patterns of the temporal structures within the basal and preictal signal. Examining the H×F and C×F values allows us to identify differences in the delta band and a band between 200 and 220 Hz (HFO 6) when comparing basal and preictal signals. Differences in Fisher information in the delta and HFO 6 bands before seizures highlight their role in capturing important system dynamics. This offers new perspectives on the intricate relationship between delta oscillations and HFO waves in patients with focal epilepsy, highlighting the importance of these patterns and their potential as biomarkers.

Delta-band Activity Underlies Referential Meaning Representation during Pronoun Resolution.

Human language offers a variety of ways to create meaning, one of which is referring to entities, objects, or events in the world. One such meaning maker is understanding to whom or to what a pronoun in a discourse refers to. To understand a pronoun, the brain must access matching entities or concepts that have been encoded in memory from previous linguistic context. Models of language processing propose that internally stored linguistic concepts, accessed via exogenous cues such as phonological input of a word, are represented as (a)synchronous activities across a population of neurons active at specific frequency bands. Converging evidence suggests that delta band activity (1-3 Hz) is involved in temporal and representational integration during sentence processing. Moreover, recent advances in the neurobiology of memory suggest that recollection engages neural dynamics similar to those which occurred during memory encoding. Integrating from these two research lines, we here tested the hypothesis that neural dynamic patterns, especially in delta frequency range, underlying referential meaning representation, would be reinstated during pronoun resolution. By leveraging neural decoding techniques (i.e., representational similarity analysis) on a magnetoencephalogram data set acquired during a naturalistic story-listening task, we provide evidence that delta-band activity underlies referential meaning representation. Our findings suggest that, during spoken language comprehension, endogenous linguistic representations such as referential concepts may be proactively retrieved and represented via activation of their underlying dynamic neural patterns.

Association of Disrupted Delta Wave Activity During Sleep With Long-Term Cardiovascular Disease and Mortality.

BACKGROUND: Delta wave activity is a prominent feature of deep sleep, which is significantly associated with sleep quality. OBJECTIVES: The authors hypothesized that delta wave activity disruption during sleep could predict long-term cardiovascular disease (CVD) and CVD mortality risk. METHODS: The authors used a comprehensive power spectral entropy-based method to assess delta wave activity during sleep based on overnight polysomnograms in 4,058 participants in the SHHS (Sleep Heart Health Study) and 2,193 participants in the MrOS (Osteoporotic Fractures in Men Study) Sleep study. RESULTS: During 11.0 ± 2.8 years of follow-up in SHHS, 729 participants had incident CVD and 192 participants died due to CVD. During 15.5 ± 4.4 years of follow-up in MrOS, 547 participants had incident CVD, and 391 died due to CVD. In multivariable Cox regression models, lower delta wave entropy during sleep was associated with higher risk of coronary heart disease (SHHS: HR: 1.46; 95% CI: 1.02-2.06; P = 0.03; MrOS: HR: 1.79; 95% CI: 1.17-2.73; P < 0.01), CVD (SHHS: HR: 1.60; 95% CI: 1.21-2.11; P < 0.01; MrOS: HR: 1.43; 95% CI: 1.00-2.05; P = 0.05), and CVD mortality (SHHS: HR: 1.94; 95% CI: 1.18-3.18; P < 0.01; MrOS: HR: 1.66; 95% CI: 1.12-2.47; P = 0.01) after adjusting for covariates. The Shapley Additive Explanations method indicates that low delta wave entropy was more predictive of coronary heart disease, CVD, and CVD mortality risks than conventional sleep parameters. CONCLUSIONS: The results suggest that delta wave activity disruption during sleep may be a useful metric to identify those at increased risk for CVD and CVD mortality.

Preoperative recovery sleep ameliorates postoperative cognitive dysfunction aggravated by sleep fragmentation in aged mice by enhancing EEG delta-wave activity and LFP theta oscillation in hippocampal CA1.

Sleep fragmentation (SF) is a common sleep problem experienced during the perioperative period by older adults, and is associated with postoperative cognitive dysfunction (POCD). Increasing evidence indicates that delta-wave activity during non-rapid eye movement (NREM) sleep is involved in sleep-dependent memory consolidation and that hippocampal theta oscillations are related to spatial exploratory memory. Recovery sleep (RS), a self-regulated state of sleep homeostasis, enhances delta-wave power and memory performance in sleep-deprived older mice. However, it remains unclear whether RS therapy has a positive effect on cognitive changes following SF in older mouse models. Therefore, this study aimed to explore whether preoperative RS can alleviate cognitive deficits in aged mice with SF. A model of preoperative 24-h SF combined with exploratory laparotomy-induced POCD was established in 18-month-old mice. Aged mice were treated with preoperative 6-h RS following SF and postoperative 6-h RS following surgery, respectively. The changes in hippocampus-dependent cognitive function were investigated using behavioral tests, electroencephalography (EEG), local field potential (LFP), magnetic resonance imaging, and neuromorphology. Mice that underwent 24-h SF combined with surgery exhibited severe spatial memory impairment; impaired cognitive performance could be alleviated by preoperative RS treatment. In addition, preoperative RS increased NREM sleep; enhanced EEG delta-wave activity and LFP theta oscillation in the hippocampal CA1; and improved hippocampal perfusion, microstructural integrity, and neuronal damage. Taken together, these results provide evidence that preoperative RS may ameliorate the severity of POCD aggravated by SF by enhancing delta slow-wave activity and hippocampal theta oscillation, and by ameliorating the reduction in regional cerebral blood flow and white matter microstructure integrity in the hippocampus.

Driver drowsiness estimation using EEG signals with a dynamical encoder-decoder modeling framework.

Drowsiness is a leading cause of accidents on the road as it negatively affects the driver's ability to safely operate a vehicle. Neural activity recorded by EEG electrodes is a widely used physiological correlate of driver drowsiness. This paper presents a novel dynamical modeling solution to estimate the instantaneous level of the driver drowsiness using EEG signals, where the PERcentage of eyelid CLOSure (PERCLOS) is employed as the ground truth of driver drowsiness. Applying our proposed modeling framework, we find neural features present in EEG data that encode PERCLOS. In the decoding phase, we use a Bayesian filtering solution to estimate the PERCLOS level over time. A data set that comprises 18 driving tests, conducted by 13 drivers, has been used to investigate the performance of the proposed framework. The modeling performance in estimation of PERCLOS provides robust and repeatable results in tests with manual and automated driving modes by an average RMSE of 0.117 (at a PERCLOS range of 0 to 1) and average High Probability Density percentage of 62.5%. We further hypothesized that there are biomarkers that encode the PERCLOS across different driving tests and participants. Using this solution, we identified possible biomarkers such as Theta and Delta powers. Results show that about 73% and 66% of the Theta and Delta powers which are selected as biomarkers are increasing as PERCLOS grows during the driving test. We argue that the proposed method is a robust and reliable solution to estimate drowsiness in real-time which opens the door in utilizing EEG-based measures in driver drowsiness detection systems.

Accelerated Aging Characterizes the Early Stage of Alzheimer's Disease.

For Alzheimer's disease (AD), aging is the main risk factor, but whether cognitive impairments due to aging resemble early AD deficits is not yet defined. When working with mouse models of AD, the situation is just as complicated, because only a few studies track the progression of the disease at different ages, and most ignore how the aging process affects control mice. In this work, we addressed this problem by comparing the aging process of PS2APP (AD) and wild-type (WT) mice at the level of spontaneous brain electrical activity under anesthesia. Using local field potential recordings, obtained with a linear probe that traverses the posterior parietal cortex and the entire hippocampus, we analyzed how multiple electrical parameters are modified by aging in AD and WT mice. With this approach, we highlighted AD specific features that appear in young AD mice prior to plaque deposition or that are delayed at 12 and 16 months of age. Furthermore, we identified aging characteristics present in WT mice but also occurring prematurely in young AD mice. In short, we found that reduction in the relative power of slow oscillations (SO) and Low/High power imbalance are linked to an AD phenotype at its onset. The loss of SO connectivity and cortico-hippocampal coupling between SO and higher frequencies as well as the increase in UP-state and burst durations are found in young AD and old WT mice. We show evidence that the aging process is accelerated by the mutant PS2 itself and discuss such changes in relation to amyloidosis and gliosis.

Brain, interrupted: alpha/delta EEG ratio in survivors of pre- and post-natal adversity.

RESULTS: Young adults born at extremely low birth weight (prenatal adversity; N = 64, Mage = 23.14 years, SDage = 1.26 years) had a lower alpha/delta ratio score compared to normal birth weight controls (N = 76, Mage = 23.60 years, SDage = 1.09 years), while youth exposed to child maltreatment (postnatal adversity; N = 39, Mage = 16.18 years, SDage = 1.15) had a higher alpha/delta ratio compared to controls (N = 23, Mage = 16.00 years, SDage = 1.50 years). CONCLUSIONS: Our results suggest that being exposed to pre- and post-natal adversity may have different long-term consequences on brain development. We speculate that these differences might be associated with some of the different functional outcomes known to characterize each type of adverse experience.

Delta- and theta-band cortical tracking and phase-amplitude coupling to sung speech by infants.

The amplitude envelope of speech carries crucial low-frequency acoustic information that assists linguistic decoding at multiple time scales. Neurophysiological signals are known to track the amplitude envelope of adult-directed speech (ADS), particularly in the theta-band. Acoustic analysis of infant-directed speech (IDS) has revealed significantly greater modulation energy than ADS in an amplitude-modulation (AM) band centred on ∼2 Hz. Accordingly, cortical tracking of IDS by delta-band neural signals may be key to language acquisition. Speech also contains acoustic information within its higher-frequency bands (beta, gamma). Adult EEG and MEG studies reveal an oscillatory hierarchy, whereby low-frequency (delta, theta) neural phase dynamics temporally organize the amplitude of high-frequency signals (phase amplitude coupling, PAC). Whilst consensus is growing around the role of PAC in the matured adult brain, its role in the development of speech processing is unexplored. Here, we examined the presence and maturation of low-frequency (<12 Hz) cortical speech tracking in infants by recording EEG longitudinally from 60 participants when aged 4-, 7- and 11- months as they listened to nursery rhymes. After establishing stimulus-related neural signals in delta and theta, cortical tracking at each age was assessed in the delta, theta and alpha [control] bands using a multivariate temporal response function (mTRF) method. Delta-beta, delta-gamma, theta-beta and theta-gamma phase-amplitude coupling (PAC) was also assessed. Significant delta and theta but not alpha tracking was found. Significant PAC was present at all ages, with both delta and theta -driven coupling observed.

Delta-modulated cortical alpha oscillations support new knowledge generation through memory integration.

The ability to generate new knowledge depends on integration of separate information. For example, in one episode an individual may learn that apple seeds are called pips. In a separate episode, the individual may then learn that pips contain cyanide. Integration of the related facts in memory may then support derivation of the new knowledge that apple seeds contain cyanide. Past studies show that adults form relational memories that represent the commonalities among discrete events, and that such integrated representation supports the ability to infer new knowledge. Although these integrated representations are thought to result from linking separate memories to the same neuronal ensemble, the neural mechanisms that underlie formation of such linkages are not well understood. Here we examined whether self-derivation of new, integrated knowledge was supported by oscillatory coherence, a means of linking discrete neuronal ensembles. Cortical alpha coherence was greater when adults encoded new facts that could be integrated with existing knowledge, relative to encoding unrelated facts, particularly in participants who showed better performance on the subsequent test of knowledge generation via fact integration. In high performers, posterior alpha amplitude was also modulated by delta phase, a form of cross-frequency coupling previously implicated in coordinating information stored widely throughout the cortex. Examination of the timing and topography of these respective signatures suggested that these oscillatory dynamics work in concert to encode and represent new knowledge with respect to prior knowledge that is reactivated, thus revealing fundamental mechanisms through which related memories are linked into integrated knowledge structures.

Timing-dependent differential effects of unexpected events on error processing reveal the interactive dynamics of surprise and error processing.

When unexpected events occur during goal-directed behavior, they automatically trigger an orienting-related cascade of psychological and neural processes through which they influence behavior and cognition. If the unexpected event was caused by an action error, additional error-specific, strategic-related processes have been proposed to follow the initial orienting period. Little is known about the neural interactions between action errors and unexpected perceptual events, two instantiations of unexpected events, in these two putative stages of post-error processing. Here, we aimed to address this by investigating the electrophysiological dynamics associated with action errors and unexpected perceptual events using scalp EEG with a focus on the frontal midline (FM) delta-to-theta oscillations (1-8 Hz) indicative of the performance-monitoring system. Specifically, we examined how the timing of unexpected sounds would influence behavior and neural oscillations after action errors, depending on the length of the intertrial interval (ITI). Our data showed that unexpected sounds aggravated post-error decreases in accuracy when they occurred (1) immediately after errors (i.e., post-error orienting period), regardless of ITI and (2) immediately after the post-error stimulus (i.e., post-error strategic period), at short ITIs. Meanwhile, action errors and unexpected sounds independently produced increased FM delta-to-theta power during the post-error orienting period, regardless of ITIs. However, when unexpected sounds occurred during the post-error strategic period, action errors produced lower FM delta-to-theta power than correct responses, at short ITIs. These differential effects of unexpected events on behavior and FM delta-to-theta dynamics support the notion of the two post-error periods during which different processes are implemented.

Excitation of Putative Glutamatergic Neurons in the Rat Parabrachial Nucleus Region Reduces Delta Power during Dexmedetomidine but not Ketamine Anesthesia.

BACKGROUND: Parabrachial nucleus excitation reduces cortical delta oscillation (0.5 to 4 Hz) power and recovery time associated with anesthetics that enhance γ-aminobutyric acid type A receptor action. The effects of parabrachial nucleus excitation on anesthetics with other molecular targets, such as dexmedetomidine and ketamine, remain unknown. The hypothesis was that parabrachial nucleus excitation would cause arousal during dexmedetomidine and ketamine anesthesia. METHODS: Designer Receptors Exclusively Activated by Designer Drugs were used to excite calcium/calmodulin-dependent protein kinase 2α-positive neurons in the parabrachial nucleus region of adult male rats without anesthesia (nine rats), with dexmedetomidine (low dose: 0.3 µg · kg-1 · min-1 for 45 min, eight rats; high dose: 4.5 µg · kg-1 · min-1 for 10 min, seven rats), or with ketamine (low dose: 2 mg · kg-1 · min-1 for 30 min, seven rats; high dose: 4 mg · kg-1 · min-1 for 15 min, eight rats). For control experiments (same rats and treatments), the Designer Receptors Exclusively Activated by Designer Drugs were not excited. The electroencephalogram and anesthesia recovery times were recorded and analyzed. RESULTS: Parabrachial nucleus excitation reduced delta power in the prefrontal electroencephalogram with low-dose dexmedetomidine for the 150-min analyzed period, excepting two brief periods (peak median bootstrapped difference [clozapine-N-oxide - saline] during dexmedetomidine infusion = -6.06 [99% CI = -12.36 to -1.48] dB, P = 0.007). However, parabrachial nucleus excitation was less effective at reducing delta power with high-dose dexmedetomidine and low- and high-dose ketamine (peak median bootstrapped differences during high-dose [dexmedetomidine, ketamine] infusions = [-1.93, -0.87] dB, 99% CI = [-4.16 to -0.56, -1.62 to -0.18] dB, P = [0.006, 0.019]; low-dose ketamine had no statistically significant decreases during the infusion). Recovery time differences with parabrachial nucleus excitation were not statistically significant for dexmedetomidine (median difference for [low, high] dose = [1.63, 11.01] min, 95% CI = [-20.06 to 14.14, -20.84 to 23.67] min, P = [0.945, 0.297]) nor low-dose ketamine (median difference = 12.82 [95% CI: -3.20 to 39.58] min, P = 0.109) but were significantly longer for high-dose ketamine (median difference = 11.38 [95% CI: 1.81 to 24.67] min, P = 0.016). CONCLUSIONS: These results suggest that the effectiveness of parabrachial nucleus excitation to change the neurophysiologic and behavioral effects of anesthesia depends on the anesthetic's molecular target.

A heuristic perspective on non-variational free energy modulation at the sleep-like edge.

BACKGROUND: The variational Free Energy Principle (FEP) establishes that a neural system minimizes a free energy function of their internal state through environmental sensing entailing beliefs about hidden states in their environment. PROBLEM: Because sensations are drastically reduced during sleep, it is still unclear how a self-organizing neural network can modulate free energy during sleep transitions. GOAL: To address this issue, we study how network's state-dependent changes in energy, entropy and free energy connect with changes at the synaptic level in the absence of sensing during a sleep-like transition. APPROACH: We use simulations of a physically plausible, environmentally isolated neuronal network that self-organize after inducing a thalamic input to show that the reduction of non-variational free energy depends sensitively upon thalamic input at a slow, rhythmic Poisson (delta) frequency due to spike timing dependent plasticity. METHODS: We define a non-variational free energy in terms of the relative difference between the energy and entropy of the network from the initial distribution (prior to activity dependent plasticity) to the nonequilibrium steady-state distribution (after plasticity). We repeated the analysis under different levels of thalamic drive - as defined by the number of cortical neurons in receipt of thalamic input. RESULTS: Entraining slow activity with thalamic input induces a transition from a gamma (awake-like state) to a delta (sleep-like state) mode of activity, which can be characterized through a modulation of network's energy and entropy (non-variational free energy) of the ensuing dynamics. The self-organizing response to low and high thalamic drive also showed characteristic differences in the spectrum of frequency content due to spike timing dependent plasticity. CONCLUSIONS: The modulation of this non-variational free energy in a network that self-organizes, seems to be an organizational network principle. This could open a window to new empirically testable hypotheses about state changes in a neural network.

Differential effect of sleep deprivation on place cell representations, sleep architecture, and memory in young and old mice.

Poor sleep quality is associated with age-related cognitive decline, and whether reversal of these alterations is possible is unknown. In this study, we report how sleep deprivation (SD) affects hippocampal representations, sleep patterns, and memory in young and old mice. After training in a hippocampus-dependent object-place recognition (OPR) task, control animals sleep ad libitum, although experimental animals undergo 5 h of SD, followed by recovery sleep. Young controls and old SD mice exhibit successful OPR memory, whereas young SD and old control mice are impaired. Successful performance is associated with two cellular phenotypes: (1) "context" cells, which remain stable throughout training and testing, and (2) "object configuration" cells, which remap when objects are introduced to the context and during testing. Additionally, effective memory correlates with spindle counts during non-rapid eye movement (NREM)/rapid eye movement (REM) sigma transitions. These results suggest SD may serve to ameliorate age-related memory deficits and allow hippocampal representations to adapt to changing environments.