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Transcranial alternating current stimulation (tACS) is an emerging non-invasive tool for modulating brain oscillations. There is evidence that weak oscillatory electrical stimulation during sleep can entrain cortical slow oscillations to improve the memory consolidation in rodents and humans. Using a novel method and a custom built stimulation device, automatic stimulation of slow oscillations in-phase with the endogenous activity in a real-time closed-loop setup is possible. Preliminary data from neuroplasticity experiments show a high detection performance of the proposed method, electrical measurements demonstrate the outstanding quality of the presented stimulation device.

Developing new standardized tools to characterize brain recording devices is critical to evaluate neural probes and for translation to clinical use. The signal-to-noise ratio (SNR) measurement is the gold standard for quantifying the performance of brain recording devices. Given the drawbacks with the SNR measure, our first objective was to devise a new method to calculate the SNR of neural signals to distinguish signal from noise. Our second objective was to apply this new SNR method to evaluate electrodes of three different materials (platinum black, Pt; carbon nanotubes, CNTs; and gold, Au) co-localized in tritrodes to record from the same cortical area using specifically designed multielectrode arrays. Hence, we devised an approach to calculate SNR at different frequencies based on the features of cortical slow oscillations (SO). Since SO consist in the alternation of silent periods (Down states) and active periods (Up states) of neuronal activity, we used these as noise and signal, respectively. The spectral SNR was computed as the power spectral density (PSD) of Up states (signal) divided by the PSD of Down states (noise). We found that Pt and CNTs electrodes have better recording performance than Au electrodes for the explored frequency range (5–1500 Hz). Together with two proposed SNR estimators for the lower and upper frequency limits, these results substantiate our SNR calculation at different frequency bands. Our results provide a new validated SNR measure that provides rich information of the performance of recording devices at different brain activity frequency bands (<1500 Hz). [ABSTRACT FROM AUTHOR]

The hyperpolarization-activated inward current, Ih, plays a key role in the generation of rhythmic activities in thalamocortical (TC) relay neurons. Cyclic nucleotides, like 3′,5′-cyclic adenosine monophosphate (cAMP), facilitate voltage-dependent activation of hyperpolarization-activated cyclic nucleotide-gated (HCN) channels by shifting the activation curve of Ih to more positive values and thereby terminating the rhythmic burst activity. The role of 3′,5′-cyclic guanosine monophosphate (cGMP) in modulation of Ih is not well understood. To determine the possible role of the nitric oxide (NO)-sensitive cGMP-forming guanylyl cyclase 2 (NO-GC2) in controlling the thalamic Ih, the voltage-dependency and cGMP/cAMP-sensitivity of Ih was analyzed in TC neurons of the dorsal part of the lateral geniculate nucleus (dLGN) in wild type (WT) and NO-GC2-deficit (NO-GC2−/−) mice. Whole cell voltage clamp recordings in brain slices revealed a more hyperpolarized half maximal activation (V1/2) of Ih in NO-GC2−/− TC neurons compared to WT. Different concentrations of 8-Br-cAMP/8-Br-cGMP induced dose-dependent positive shifts of V1/2 in both strains. Treatment of WT slices with lyase enzyme (adenylyl and guanylyl cyclases) inhibitors (SQ22536 and ODQ) resulted in further hyperpolarized V1/2. Under current clamp conditions NO-GC2−/− neurons exhibited a reduction in the Ih-dependent voltage sag and reduced action potential firing with hyperpolarizing and depolarizing current steps, respectively. Intrathalamic rhythmic bursting activity in brain slices and in a simplified mathematical model of the thalamic network was reduced in the absence of NO-GC2. In freely behaving NO-GC2−/− mice, delta and theta band activity was enhanced during active wakefulness (AW) as well as rapid eye movement (REM) sleep in cortical local field potential (LFP) in comparison to WT. These findings indicate that cGMP facilitates Ih activation and contributes to a tonic activity in TC neurons. On the network level basal cGMP production supports fast rhythmic activity in the cortex. [ABSTRACT FROM AUTHOR]

While it is a well-established finding that subjects' own names (SON) and familiar voices are salient during wakefulness, we here investigated processing of environmental stimuli during sleep including deep N3 and REM sleep. Besides the effects of sleep depth we investigated how sleep-specific EEG patterns (i.e. sleep spindles and slow oscillations [SOs]) relate to stimulus processing. Using 256-channel EEG we studied processing of auditory stimuli by means of event-related oscillatory responses (de-/synchronisation, ERD/ERS) and potentials (ERPs) in N  = 17 healthy sleepers. We varied stimulus salience by manipulating subjective (SON vs. unfamiliar name) and paralinguistic emotional relevance (familiar vs. unfamiliar voice, FV/UFV). Results reveal that evaluation of voice familiarity continues during all NREM sleep stages and even REM sleep suggesting a ‘sentinel processing mode’ of the human brain in the absence of wake-like consciousness. Especially UFV stimuli elicit larger responses in a 1–15 Hz range suggesting they continue being salient. Beyond this, we find that sleep spindles and the negative slope of SOs attenuate information processing. However, unlike previously suggested they do not uniformly inhibit information processing, but inhibition seems to be scaled to stimulus salience. [ABSTRACT FROM AUTHOR]

NMDA receptor (NMDAr) hypofunction has been widely used as a schizophrenia model. Decreased activation of NMDAr is associated with a disrupted excitation/inhibition balance in the prefrontal cortex and with alterations in gamma synchronization. Our aim was to investigate whether this phenomenon could be reproduced in the spontaneous oscillatory activity generated by the local prefrontal network in vitro and, if so, to explore the effects of antipsychotics on the resulting activity. Extracellular recordings were obtained from prefrontal cortex slices bathed in in vivo -like ACSF solution. Slow (<1 Hz) oscillations consisting of interspersed Up (active) and Down (silent) states spontaneously emerged. Fast-frequency oscillations (15–90 Hz) occurred during Up states. We explored the effects of the NMDAr antagonist MK-801 on the spontaneously generated activity. Bath-applied MK-801 induced a dose-dependent decrease in Up-state duration and in the frequency of Up states. However, the beta/gamma power during Up states significantly increased; this increase was in turn prevented by the antipsychotic drug clozapine. The increased beta/gamma power with NMDAr blockade implies that NMDAr activation in physiological conditions prevents hypersynchronization in this frequency range. High-frequency hypersynchronization following NMDAr blockade occurring in cortical slices suggests that—at least part of—the underlying mechanisms of this schizophrenia feature persist in the local cortical circuit, even in the absence of long-range cortical or subcortical inputs. The observed action of clozapine decreasing hypersynchronization in the local circuit may be one of the mechanisms of action of clozapine in preventing schizophrenia symptoms derived from NMDA hypofunction. [ABSTRACT FROM AUTHOR]

Focal administration of pharmacological agents during in vivo recordings is a useful technique to study the functional properties of neural microcircuits. However, the lack of visual control makes this task difficult and inaccurate, especially when targeting small and deep regions where spillover to neighboring regions is likely to occur. An additional problem with recording stability arises when combining focal drug administration with in vivo intracellular recordings, which are highly sensitive to mechanical vibrations. To address these technical issues, we designed a micro-holder that enables accurate local application of pharmacological agents during in vivo whole-cell recordings. The holder couples the recording and drug delivery pipettes with adjustable distance between the respective tips adapted to the experimental needs. To test the efficacy of the micro-holder we first performed whole-cell recordings in mouse primary somatosensory cortex (S1) with simultaneous extracellular recordings in S1 and motor cortex (M1), before and after local application of bicuculline methiodide (BMI 200 µM). The blockade of synaptic inhibition resulted in increased amplitudes and rising slopes of “Up states”, and shortening of their duration. We then checked the usability of the micro-holder in a deeper brain structure, the striatum. We applied tetrodotoxin (TTX 10 µM) during whole-cell recordings in the striatum, while simultaneously obtaining extracellular recordings in S1 and M1. The focal application of TTX in the striatum blocked Up states in the recorded striatal neurons, without affecting the cortical activity. We also describe two different approaches for precisely releasing the drugs without unwanted leakage along the pipette approach trajectory. [ABSTRACT FROM AUTHOR]

Slow oscillations of neuronal activity alternating between firing and silence are a hallmark of slow-wave sleep (SWS). These oscillations reflect the default activity present in all mammalian species, and are ubiquitous to anesthesia, brain slice preparations, and neuronal cultures. In all these cases, neuronal firing is highly synchronous within local circuits, suggesting that oscillation-synchronization coupling may be a governing principle of sleep physiology regardless of anatomical connectivity. To investigate whether this principle applies to overall brain organization, we recorded the activity of individual neurons from basal ganglia (BG) structures and the thalamocortical (TC) network over 70 full nights of natural sleep in two vervet monkeys. During SWS, BG neurons manifested slow oscillations (~0.5 Hz) in firing rate that were as prominent as in the TC network. However, in sharp contrast to any neural substrate explored thus far, the slow oscillations in all BG structures were completely desynchronized between individual neurons. Furthermore, whereas in the TC network single-cell spiking was locked to slow oscillations in the local field potential (LFP), the BG LFP exhibited only weak slow oscillatory activity and failed to entrain nearby cells. We thus show that synchrony is not inherent to slow oscillations, and propose that the BG desynchronization of slow oscillations could stem from its unique anatomy and functional connectivity. Finally, we posit that BG slowoscillation desynchronization may further the reemergence of slowoscillation traveling waves from multiple independent origins in the frontal cortex, thus significantly contributing to normal SWS. [ABSTRACT FROM AUTHOR]

Gamma oscillations are involved in long-range coupling of distant regions that support various cognitive operations. Here we show in adult male rats that synchronized bursts of gamma oscillations bind the hippocampus (HPC) and prefrontal cortex (mPFC) during slow oscillations and slow-wave sleep, a brain state that is central for consolidation of memory traces. These gamma bursts entrained the firing of the local HPC and ntPFC neuronal populations. Neurons of the nucleus reuniens (NR), which is a structural and functional hub between HPC and ntPFC, demonstrated a specific increase in their firing before gamma burst onset, suggesting their involvement in HPC-mPFC binding. Chemical inactivation of NR disrupted the temporal pattern of gamma bursts and their synchronization, as well as mPFC neuronal firing. We propose that the NR drives long-range hippocampo-prefrontal coupling via gamma bursts providing temporal windows for information exchange between the HPC and mPFC during slow-wave sleep. [ABSTRACT FROM AUTHOR]

Sleep is essential for our physical and mental well-being. During sleep, despite the paucity of overt behavior, our brain remains active and exhibits a wide range of coupled brain oscillations. In particular slow oscillations are characteristic for sleep, however whether they are directly involved in the functions of sleep, or are mere epiphenomena, is not yet fully understood. To disentangle the causality of these relationships, experiments utilizing techniques to detect and manipulate sleep oscillations in real-time are essential. In this review, we first overview the theoretical principles of closed-loop auditory stimulation (CLAS) as a method to study the role of slow oscillations in the functions of sleep. We then describe technical guidelines and best practices to perform CLAS and analyze results from such experiments. We further provide an overview of how CLAS has been used to investigate the causal role of slow oscillations in various sleep functions. We close by discussing important caveats, open questions, and potential topics for future research. • Slow oscillations during sleep associated with the functions of sleep. • Closed-loop auditory stimulation (CLAS) of sleep slow oscillations allow to modulate sleep function. • Procedural details between stimulation approaches differ, contributing to conflicting findings. • Basic principles and best practices for CLAS provide a unifying theoretical and practical manual for future research. [ABSTRACT FROM AUTHOR]

The senescence-accelerated mouse prone 8 (SAMP8) model is characterized by accelerated, progressive cognitive decline as well as Alzheimer’s disease (AD)-like neurodegenerative changes, and resembles the etiology of multicausal, sporadic late-onset/age-related AD in humans. Our aim was to find whether these AD-like pathological features, together with the cognitive deficits present in the SAMP8 strain, are accompanied by disturbances in cortical network activity with respect to control mice (SAM resistance 1, SAMR1) and, if so, how the alterations in cortical activity progress with age. For this purpose, we characterized the extracellular spontaneous oscillatory activity in different regions of the cerebral cortex of SAMP8 and SAMR1 mice under ketamine anesthesia at 5 and 7 months of age. Under these conditions, slow oscillations and fast rhythms generated in the cortical network were recorded and different parameters of these oscillations were quantified and compared between SAMP8 and their control, SAMR1 mice. The average frequency of slow oscillations in SAMP8 mice was decreased with respect to the control mice at both studied ages. An elongation of the silent periods or Down states was behind the decreased slow oscillatory frequency while the duration of active or Up states remained stable. SAMP8 mice also presented increased cycle variability and reduced high frequency components during Down states. During Up states, the power peak in the gamma range was displaced towards lower frequencies in all the cortical areas of SAMP8 with respect to control mice suggesting that the spectral profile of SAMP8 animals is shifted towards lower frequencies. This shift is reminiscent to one of the principal hallmarks of electroencephalography (EEG) abnormalities in patients with Alzheimer’s disease, and adds evidence in support of the suitability of the SAMP8 mouse as a model of this disease. Although some of the differences between SAMP8 and control mice were emphasized with age, the evolution of the studied parameters as SAMR1 mice got older indicates that the SAMR1 phenotype tends to converge with that of SAMP8 animals. To our knowledge, this is the first systematic characterization of the cortical slow and fast rhythms in the SAMP8 strain and it provides useful insights about the cellular and synaptic mechanisms underlying the reported alterations.

Introduction: Our aim was to perform a comparative study of short-term cardiovascular autonomic control in cardiac surgery patients who underwent coronary artery bypass grafting (CABG) or surgical correction of valvular heart disease (SCVHD). Methods: The synchronous 15 minutes records of heart rate variability (HRV) and finger's photoplethysmographic waveform variability (PPGV) were performed in 42 cardiac surgery patients (12 women) aged 61.8 ± 8.6 years (mean ± standard deviation), who underwent CABG, and 36 patients (16 women) aged 54.2 ± 14.9 years, who underwent SCVHD, before surgery and in 5-7 days after surgery. Conventional time and frequency domain measures of HRV and index S of synchronization between the slow oscillations in PPGV and HRV were analyzed. We also calculated personal dynamics of these indices after surgery. Results: We found no differences (P > 0.05) in all studied autonomic indices (preoperative and post-surgery) between studied patients' groups, except for the preoperative heart rate, which was higher in patients who underwent SCVHD (P = 0.013). We have shown a pronounced preoperative and post-surgery variability (magnitude of inter-quartile ranges) of all autonomic indices in studied patients. In the cluster analysis based on cardiovascular autonomic indices (preoperative and post-surgery), we divided all patients into two clusters (38 and 40 subjects) which did not differ in all clinical characteristics (except for the preoperative hematocrit, P = 0.038), index S, and all post-surgery HRV indices. First cluster (38 patients) had higher preoperative values of the HR, TP, HF, and HF%, and lower preoperative values of the LF% and LF/HF. Conclusion: The variability of cardiovascular autonomic indices in on-pump cardiac surgery patients (two characteristic clusters were identified based on preoperative indices) was not associated with their clinical characteristics and features of surgical procedure (including cardioplegia). [ABSTRACT FROM AUTHOR]

Slow oscillations have been suggested as the default emergent activity of the cortical network. This is a low complexity state that integrates neuronal, synaptic, and connectivity properties of the cortex. Shaped by variations of physiological parameters, slow oscillations provide information about the underlying healthy or pathological network. We review how this default activity is shaped, how it acts as a powerful attractor, and how getting out of it is necessary for the brain to recover the levels of complexity associated with conscious states. We propose that slow oscillations provide a robust unifying paradigm for the study of cortical function. [ABSTRACT FROM AUTHOR]

The senescence-accelerated mouse prone 8 (SAMP8) model is characterized by accelerated, progressive cognitive decline as well as Alzheimer's disease (AD)-like neurodegenerative changes, and resembles the etiology of multicausal, sporadic late-onset/age-related AD in humans. Our aim was to find whether these AD-like pathological features, together with the cognitive deficits present in the SAMP8 strain, are accompanied by disturbances in cortical network activity with respect to control mice (SAM resistance 1, SAMR1) and, if so, how the alterations in cortical activity progress with age. For this purpose, we characterized the extracellular spontaneous oscillatory activity in different regions of the cerebral cortex of SAMP8 and SAMR1 mice under ketamine anesthesia at 5 and 7 months of age. Under these conditions, slow oscillations and fast rhythms generated in the cortical network were recorded and different parameters of these oscillations were quantified and compared between SAMP8 and their control, SAMR1 mice. The average frequency of slow oscillations in SAMP8 mice was decreased with respect to the control mice at both studied ages. An elongation of the silent periods or Down states was behind the decreased slow oscillatory frequency while the duration of active or Up states remained stable. SAMP8 mice also presented increased cycle variability and reduced high frequency components during Down states. During Up states, the power peak in the gamma range was displaced towards lower frequencies in all the cortical areas of SAMP8 with respect to control mice suggesting that the spectral profile of SAMP8 animals is shifted towards lower frequencies. This shift is reminiscent to one of the principal hallmarks of electroencephalography (EEG) abnormalities in patients with Alzheimer,s disease, and adds evidence in support of the suitability of the SAMP8 mouse as a model of this disease. Although some of the differences between SAMP8 and control mice were emphasized with age, the evolution of the studied parameters as SAMR1 mice got older indicates that the SAMR1 phenotype tends to converge with that of SAMP8 animals. To our knowledge, this is the first systematic characterization of the cortical slow and fast rhythms in the SAMP8 strain and it provides useful insights about the cellular and synaptic mechanisms underlying the reported alterations. [ABSTRACT FROM AUTHOR]

Cortical slow oscillations (0.1–1 Hz), which may play a role in memory consolidation, are a hallmark of non-rapid eye movement (NREM) sleep and also occur under anesthesia. During slow oscillations the neuronal network generates faster oscillations on the active Up-states and these nested oscillations are particularly prominent in the PFC. In rodents the medial prefrontal cortex (mPFC) consists of several subregions: anterior cingulate cortex (ACC), prelimbic (PrL), infralimbic (IL), and dorsal peduncular cortices (DP). Although each region has a distinct anatomy and function, it is not known whether slow or fast network oscillations differ between subregions in vivo. We have simultaneously recorded slow and fast network oscillations in all four subregions of the rodent mPFC under urethane anesthesia. Slow oscillations were synchronous between the mPFC subregions, and across the hemispheres, with no consistent amplitude difference between subregions. Delta (2–4 Hz) activity showed only small differences between subregions. However, oscillations in the spindle (6–15 Hz)-, beta (20–30 Hz), gamma (30–80 Hz)-, and high-gamma (80–150 Hz)-frequency bands were consistently larger in the dorsal regions (ACC and PrL) compared with ventral regions (IL and DP). In dorsal regions the peak power of spindle, beta, and gamma activity occurred early after onset of the Up-state. In the ventral regions, especially the DP, the oscillatory power in the spindle-, beta-, and gamma-frequency ranges peaked later in the Up-state. These results suggest variations in fast network oscillations within the mPFC that may reflect the different functions and connectivity of these subregions. [ABSTRACT FROM AUTHOR]

Studies using targeted memory reactivation have shown that presentation of auditory or olfactory contextual cues during sleep can bias hippocampal reactivations towards the preferential replay of the cue-associated material, thereby resulting in enhanced consolidation of that information. If the same cortical ensembles are indeed used for encoding and storage of a given piece of information, forcing the sleeping brain to re-engage in task-intrinsic information processing should disturb the natural ongoing consolidation processes and therefore impair possible sleep benefits. Here we aimed at recreating an integral part of the sensory experience of a motor skill in a daytime nap, by means of a tactile stimulation. We hypothesized that tampering with the tactile component of a motor skill during sleep would result in hindered performance at retest, due to interference between the highly congruent incoming stimuli and the core skill trace. Contrary to our predictions, the tactile stimulation did not influence neither speed nor accuracy, when compared to natural sleep. However, an exploratory sleep EEG analysis revealed stimulation-induced alterations in the abundance and cortical topography of slow oscillations and spindles. These findings suggest that despite the lack of a significant effect on motor behavior, tactile stimulation induced changes in EEG features suggestive of a possible uncoupling between the sleep oscillations thought to underlie consolidation processes, i.e. slow oscillations and sleep spindles. [ABSTRACT FROM AUTHOR]

Study Objectives: Healthy aging and many disorders show reduced sleep-dependent memory consolidation and corresponding alterations in non-rapid eye movement sleep oscillations. Yet sleep physiology remains a relatively neglected target for improving memory. We evaluated the effects of closed-loop auditory stimulation during sleep (CLASS) on slow oscillations (SOs), sleep spindles, and their coupling, all in relation to motor procedural memory consolidation., Methods: Twenty healthy young adults had two afternoon naps: one with auditory stimulation during SO upstates and another with no stimulation. Twelve returned for a third nap with stimulation at variable times in relation to SO upstates. In all sessions, participants trained on the motor sequence task prior to napping and were tested afterward., Results: Relative to epochs with no stimulation, upstate stimuli disrupted sleep and evoked SOs, spindles, and SO-coupled spindles. Stimuli that successfully evoked oscillations were delivered closer to the peak of the SO upstate and when spindle power was lower than stimuli that failed to evoke oscillations. Across conditions, participants showed similar significant post-nap performance improvement that correlated with the density of SO-coupled spindles., Conclusions: Despite its strong effects on sleep physiology, CLASS failed to enhance motor procedural memory. Our findings suggest methods to overcome this failure, including better sound calibration to preserve sleep continuity and the use of real-time predictive algorithms to more precisely target SO upstates and to avoid disrupting endogenous SO-coupled spindles and their mnemonic function. They motivate continued development of CLASS as an intervention to manipulate sleep oscillatory dynamics and improve memory., (© The Author(s) 2023. Published by Oxford University Press on behalf of Sleep Research Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

• Two reactivations are detected after TMR and each has distinct characteristics. • TMR elicits detectable reactivation when delivered on the up-going phase of SOs. • Slow oscillation morphologies can be used to determine when to deliver TMR. • Sleep spindle incidences can be used to time the delivery of TMR. Targeted memory reactivation (TMR) is a technique in which sensory cues associated with memories during wake are used to trigger memory reactivation during subsequent sleep. The characteristics of such cued reactivation, and the optimal placement of TMR cues, remain to be determined. We built an EEG classification pipeline that discriminated reactivation of right- and left-handed movements and found that cues which fall on the up-going transition of the slow oscillation (SO) are more likely to elicit a classifiable reactivation. We also used a novel machine learning pipeline to predict the likelihood of eliciting a classifiable reactivation after each TMR cue using the presence of spindles and features of SOs. Finally, we found that reactivations occurred either immediately after the cue or one second later. These findings greatly extend our understanding of memory reactivation and pave the way for development of wearable technologies to efficiently enhance memory through cueing in sleep. [ABSTRACT FROM AUTHOR]

Closed-loop acoustic stimulation (CLAS) during sleep has shown to boost slow wave (SW) amplitude and spindle power. Moreover, sleep SW have been classified based on different processes of neuronal synchronization. Thus, different types of SW events may have distinct functional roles and be differentially affected by external stimuli. However, the SW synchronization processes affected by CLAS are not well understood. Here, we studied the effect of CLAS on the dissociation of SW events based on two features of neuronal synchronization in the electroencephalogram (topological spread and wave slope). We evaluated and classified individual SW events of 14 healthy subjects during a CLAS stimulated (STM) and a control night (CNT). Three main categories of SW events were found denoting (C1) steep slope SW with global spread, (C2) flat-slope waves with localized spread and homeostatic decline, and (C3) multipeaked flat-slope events with global spread. Comparing between conditions, we found a consistent increase of event proportion and trough amplitudes for C1 events during the time of stimulation. Furthermore, we found similar increases in post-stimulus spectral power in θ, β, and σ frequencies for CNT vs STIM condition independently of sleep stage or SW categories. However, topological analysis showed differentiated spatial dynamics in N2 and N3 for SW categories and the co-occurrence with spindle events. Our findings support the existence of multiple types of SW with differential response to external stimuli and possible distinct neuronal mechanisms., (© The Author(s) 2023. Published by Oxford University Press on behalf of Sleep Research Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Behavioral inhibition, which is a later-developing executive function (EF) and anatomically located in prefrontal areas, is impaired in attention-deficit and hyperactivity disorder (ADHD). While optimal EFs have been shown to depend on efficient sleep in healthy subjects, the impact of sleep problems, frequently reported in ADHD, remains elusive. Findings of macroscopic sleep changes in ADHD are inconsistent, but there is emerging evidence for distinct microscopic changes with a focus on prefrontal cortical regions and non-rapid eye movement (non-REM) slow-wave sleep. Recently, slow oscillations (SO) during non-REM sleep were found to be less functional and, as such, may be involved in sleep-dependent memory impairments in ADHD. Objective: By augmenting slow-wave power through bilateral, slow oscillating transcranial direct current stimulation (so-tDCS, frequency = 0.75 Hz) during non-REM sleep, we aimed to improve daytime behavioral inhibition in children with ADHD. Methods: 14 boys (10-14 yrs) diagnosed with ADHD were included. In a randomized, double-blind, cross-over design, patients received so-tDCS either in the first or in the second experimental sleep night. Inhibition control was assessed with a visuomotor go/no-go task. Intrinsic alertness was assessed with a simple stimulus response task. To control for visuomotor performance, motor memory was assessed with a finger sequence tapping task. Results: SO-power was enhanced during early non-REM sleep, accompanied by slowed reaction times and decreased standard deviations of reaction times, in the go/no-go task after so-tDCS. In contrast, intrinsic alertness and motor memory performance were not improved by so-tDCS. Conclusion: Since behavioral inhibition but not intrinsic alertness or motor memory was improved by so-tDCS, our results suggest that lateral prefrontal slow oscillations during sleep might play a specific role for executive functioning in ADHD.

It is widely accepted that the fluctuations in resting state blood oxygenation level dependent (BOLD) functional MRI (fMRI) reflect baseline neuronal activation through neurovascular coupling; this data is used to infer functional connectivity in the human brain during rest. Consistent activation patterns, i.e. resting state networks (RSN) are seen across groups, conditions, and even species. In this study, we show that some of these patterns can also be generated from the dynamic, systemic, non-neuronal physiological low frequency oscillations (sLFOs) in the BOLD signal alone. We have previously used multimodal imaging to demonstrate the wide presence of the same sLFOs in the brain (BOLD) and periphery with different time delays. This study shows that these sLFOs from BOLD signals alone can give rise to stable spatial patterns, which can be detected during resting state analyses. We generated synthetic resting state data for 11 subjects based only on subject-specific, dynamic sLFO information obtained from resting state data using concurrent peripheral optical imaging or a novel recursive procedure. We compared the results obtained by performing a group independent component analysis (ICA) on this synthetic data (i.e. the result from simulation) to the results obtained from analysis of the real data. ICA detected most of the eight well-known RSNs, including visual, motor and default mode networks, in both the real and the synthetic data sets. These findings suggest that RSNs may reflect, to some extent, vascular anatomy associated with systemic fluctuations, rather than neuronal connectivity.

The recurrent circuitry of the cerebral cortex generates an emergent pattern of activity that is organized into rhythmic periods of firing and silence referred to as slow oscillations (ca 1 Hz). Slow oscillations not only are dominant during slow wave sleep and deep anaesthesia, but also can be generated by the isolated cortical network in vitro, being a sort of default activity of the cortical network. The cortex is densely and reciprocally connected with subcortical structures and, as a result, the slow oscillations in situ are the result of an interplay between cortex and thalamus. Due to this reciprocal connectivity and interplay, the mechanism responsible for the initiation of waves in the corticothalamocortical loop during slow oscillations is still a matter of debate. The prevalent view is that infragranular layers of the cortex, where the highest firing rates are found, are leading the periods of activity or Up states, from where activity rapidly spreads to all cortical layers and subcortical structures such as the thalamus. However, other authors support that the slow wave activity is an emergent property of corticothalamocortical networks defining the origin of this activity as a balance between cortical and thalamic contributions. To determine the directionality of the information flow between different layers of the cortex and the connected thalamus during spontaneous activity we obtained multilayer local field potentials from the rat visual cortex and from its connected thalamus, the lateral geniculate nucleus, during deep anaesthesia. We analyzed directionality of information flow between thalamus, cortical infragranular layers (5 and 6) and supragranular layers (2/3) by means of three information theoretical indicators: transfer entropy, symbolic transfer entropy and transcript mutual information. These three indicators coincided in finding that infragranular layers lead the information flow during slow oscillations both towards supragranular layers and towards the thalamus.

We present a closed-loop system able to set the frequency of slow oscillations dynamics observed in acute preparation of ferret cortical slices. The biological activity is recorded through a single electrode, is analyzed on-line and steered through the injection of a DC current of variable intensity. The system guarantees artifacts removal, minimal gaps in the data acquisition and proved to be robust to slice heterogeneities. To achieve such a control we designed a custom programmable stimulator ensuring low-noise and accurate tuning over low current levels. For data recording and analysis we rely on commercial acquisition and software tools. The result is a flexible and reliable system that ensures control over in vitro slow oscillation frequency. Our tool opens new possibilities for the investigation of slow-wave dynamics which have been associated with memory consolidation and whose alteration are observed in different pathologies such as neurodegenerative diseases.

Sleep-related consolidation of declarative memories, as well as associated neurophysiological events such as slow oscillatory and spindle activity, deteriorate in the course of aging. This process is accelerated in neurodegenerative disease. Transcranial slow oscillatory stimulation (so-tDCS) during sleep has been shown to enhance slow oscillatory brain activity and thereby improve memory consolidation in young subjects. Here, we investigated whether so-tDCS applied to older adults during an afternoon nap exerts similar effects. Eighteen older human subjects were assessed using visuo-spatial (picture memory, primary, and location memory) and verbal memory tasks before and after a 90-min nap either comprising weak so-tDCS at 0.75 Hz over fronto-central location or sham (no) stimulation in a within-subject design. Electroencephalographic activity was recorded throughout the naps and immediate effects of stimulation on brain activity were evaluated. Here, spectral power within three frequency bands of interest were computed, i.e., slow oscillatory activity, slow spindle and fast spindle activity; in 1-min stimulation-free intervals following 5 stimulation blocks. So-tDCS significantly increased frontal slow oscillatory activity as well as fast spindle activity, and significantly improved picture memory retention after sleep. Retention in the location memory subtask and in the verbal memory task was not affected. These findings may indicate a novel strategy to counteract cognitive decline in aging in a convenient manner during brief daytime naps. [ABSTRACT FROM AUTHOR]

The application of auditory clicks during non-rapid eye movement ( NREM) sleep phase-locked to the up state of the slow oscillation (closed-loop stimulation) has previously been shown to enhance the consolidation of declarative memories. We designed and applied sequences of three clicks during deep NREM sleep to achieve a quasi-phase-dependent open-loop stimulation. This stimulation was successful in eliciting slow oscillation power in the stimulation period. Although fast and slow spindle power were markedly decreased during the stimulation period, memory consolidation did not differ from control. During putative up states fast spindle power remained, however, at control levels. We conclude that concurrence of slow oscillations and fast spindles suffices to maintain memory consolidation at control levels despite an overall decreased spindle activity. [ABSTRACT FROM AUTHOR]

Objective An emerging paradigm for understanding how anesthetics induce altered arousal is relating receptor targeting in specific neural circuits to electroencephalogram (EEG) activity. Enhanced gamma amino-butyric acid A (GABA A ) inhibitory post-synaptic currents (IPSCs) manifest with large-amplitude slow (0.1–1 Hz) and frontally coherent alpha (8–12 Hz) EEG oscillations during general anesthesia. Therefore, we investigated the EEG signatures of modern day derivatives of ether (MDDE) anesthesia to assess the extent to which we could obtain insights into MDDE anesthetic mechanisms. Methods We retrospectively studied cases from our database in which patients received isoflurane anesthesia vs. isoflurane/ketamine anesthesia ( n = 10 each) or desflurane anesthesia vs. desflurane/ketamine anesthesia ( n = 9 each). We analyzed the EEG recordings with spectral power and coherence methods. Results Similar to known GABA A circuit level mechanisms, we found that MDDE anesthesia induced large amplitude slow and frontally coherent alpha oscillations. Additionally, MDDE anesthesia also induced frontally coherent theta (4–8 Hz) oscillations. Reduction of GABAergic IPSCs with ketamine resulted in beta/gamma (13–40 Hz) oscillations, and significantly reduced MDDE anesthesia-induced slow, theta and alpha oscillation power. Conclusions Large amplitude slow oscillations and coherent alpha and theta oscillations are moderated by ketamine during MDDE anesthesia. Significance These observations are consistent with the notion that GABA A circuit-level mechanisms are associated with MDDE anesthesia-induced unconsciousness. [ABSTRACT FROM AUTHOR]

Objectives Ketamine is an N-methyl- d -aspartate (NMDA) receptor antagonist commonly administered as a general anesthetic. However, neural circuit mechanisms to explain ketamine anesthesia-induced unconsciousness in humans are yet to be clearly defined. Disruption of frontal–parietal network connectivity has been proposed as a mechanism to explain this brain state. However, this mechanism was recently demonstrated at subanesthetic doses of ketamine in awake-patients. Therefore, we investigated whether there is an electroencephalogram (EEG) signature specific for ketamine anesthesia-induced unconsciousness. Methods We retrospectively studied the EEG in 12 patients who received ketamine for the induction of general anesthesia. We analyzed the EEG dynamics using power spectral and coherence methods. Results Following the administration of a bolus dose of ketamine to induce unconsciousness, we observed a “gamma burst” EEG pattern that consisted of alternating slow-delta (0.1–4 Hz) and gamma (∼27–40 Hz) oscillations. This pattern was also associated with increased theta oscillations (∼4–8 Hz) and decreased alpha/beta oscillations (∼10–24 Hz). Conclusions Ketamine anesthesia-induced unconsciousness is associated with a gamma burst EEG pattern. Significance The EEG signature of ketamine anesthesia-induced unconsciousness may offer new insights into NMDA circuit mechanisms for unconsciousness. [ABSTRACT FROM AUTHOR]

Gonadotropin-releasing hormone (GnRH) neurons exhibit at least two intrinsic modes of action potential burst firing, referred to as parabolic and irregular bursting. Parabolic bursting is characterized by a slow wave in membrane potential that can underlie periodic clusters of action potentials with increased interspike interval at the beginning and at the end of each cluster. Irregular bursting is characterized by clusters of action potentials that are separated by varying durations of interburst intervals and a relatively stable baseline potential. Based on recent studies of isolated ionic currents, a stochastic Hodgkin-Huxley (HH)-like model for the GnRH neuron is developed to reproduce each mode of burst firing with an appropriate set of conductances. Model outcomes for bursting are in agreement with the experimental recordings in terms of interburst interval, interspike interval, active phase duration, and other quantitative properties specific to each mode of bursting. The model also shows similar outcomes in membrane potential to those seen experimentally when tetrodotoxin (TTX) is used to block action potentials during bursting, and when estradiol transitions cells exhibiting slow oscillations to irregular bursting mode in vitro. Based on the parameter values used to reproduce each mode of bursting, the model suggests that GnRH neurons can switch between the two through changes in the maximum conductance of certain ionic currents, notably the slow inward Ca current I and the Ca -activated K current I. Bifurcation analysis of the model shows that both modes of bursting are similar from a dynamical systems perspective despite differences in burst characteristics. [ABSTRACT FROM AUTHOR]

Slow oscillations (SlO) of magnetoresistance is a convenient tool to measure electronic structure parameters in quasi-two-dimensional metals. We study the possibility to apply this method to multi-band conductors, e.g., to iron-based high-temperature superconducting materials. We show that SlO can be used to measure the interlayer transfer integral in multi-band conductors similar to single-band metals. In addition, the SlO allow to measure and compare the effective masses or the electron scattering rates in various bands. [ABSTRACT FROM AUTHOR]

Isolated Rapid Eye Movement Sleep (REM) behaviour disorder (iRBD) is a prodromal sign of neurodegenerative disorders. Empirical findings point to a role of non-REM (NREM) sleep alterations in neurodegenerative processes. Therefore, the interest in NREM sleep electroencephalography (EEG) of iRBD is progressively increasing. The present review aims to provide an updated state of the art on NREM sleep electrophysiology in iRBD. First, we describe findings on NREM EEG power spectra. Then, we consider specific NREM sleep EEG hallmarks (i.e., slow waves, slow oscillations, K-complexes, sleep spindles). Finally, we focus on NREM sleep instability. The reviewed literature is small and heterogeneous, but rapidly growing. The most consistent findings point to alteration of sleep spindles and cyclic alternating pattern in RBD. A larger discrepancy characterized results on slow wave activity, but recent studies using a topographical approach provide promising results. Evidence on the relationship of NREM sleep alterations with neurodegenerative processes in iRBD, as well as longitudinal changes, are scarce. We discuss the main methodological limitations, highlighting possible future directions. • The literature on NREM sleep EEG in RBD is small and heterogenous but rapidly growing. • The most consistent findings point to an alteration of sleep spindles and CAP in RBD. • Albeit heterogeneous, alterations in the slow wave activity range have been observed. • The role of RBD-related NREM sleep alterations in neurodegeneration is unclear. • Longitudinal and topographical evaluations of NREM sleep EEG in RBD are needed. [ABSTRACT FROM AUTHOR]

Coherent network oscillations (< 0.1 Hz) linking distributed brain regions are commonly observed in the brain during both rest and task conditions. What oscillatory network exists and how network oscillations change in connectivity strength, frequency and direction when going from rest to explicit task are topics of recent inquiry. Here, we study network oscillations within the sensorimotor regions of able-bodied individuals using hemodynamic activity as measured by functional near-infrared spectroscopy (fNIRS). Using spectral interdependency methods, we examined how the supplementary motor area (SMA), the left premotor cortex (LPMC) and the left primary motor cortex (LM1) are bound as a network during extended resting state (RS) and between-tasks resting state (btRS), and how the activity of the network changes as participants execute left, right and bilateral hand (LH, RH and BH) finger movements. We found: (i) power, coherence and Granger causality spectra had significant peaks within the frequency band (0.01-0.04 Hz) during RS whereas the peaks shifted to a bit higher frequency range (0.04- 0.08 Hz) during btRS and finger movement tasks, (ii) there was significant bidirectional connectivity between all the nodes during RS and unidirectional connectivity from the LM1 to SMA and LM1 to LPMC during btRS, and (iii) the connections from SMA to LM1 and from LPMC to LM1 were significantly modulated in LH, RH and BH finger movements relative to btRS. The unidirectional connectivity from SMA to LM1 just before the actual task changed to the bidirectional connectivity during LH and BH finger movement. The unidirectionality could be associated with movement suppression and the bidirectionality with for preparation, sensorimotor update and controlled execution. These results underscore that fNIRS is an effective tool for monitoring spectral signatures of brain activity, which may serve as an important precursor before monitoring the recovery progress following brain injury.

Based on physiological models of neurovisceral integration, different studies have shown how cognitive processes modulate heart rate and how the heartbeat, on the other hand, modulates brain activity. We tried to further determine interactions between cardiac and electrical brain activity by means of EEG. We investigated how the heartbeat modulates EEG in 23 healthy controls from wakefulness to deep sleep and showed that frontocentral heartbeat evoked EEG amplitude and phase locking (as measured by intertrial phase locking), at about 300-400 ms after the R peak, decreased with increasing sleep depth with a renewed increase during REM sleep, which underpins the assumption that the heartbeat evoked positivity constitutes an active frontocortical response to the heartbeat. Additionally, we found that individual heart rate was correlated with the frequency of the EEG's spectral peak (i.e., alpha peak frequency during wakefulness). This correlation was strongest during wakefulness and declined linearly with increasing sleep depth. Furthermore, we show that the QRS complex modulates spindle phase possibly related to the correspondence between the frequency of the QRS complex and the spindle frequency of about 12-15 Hz. Finally, during deep sleep stages, a loose temporal coupling between heartbeats and slow oscillation (0.8 Hz) could be observed. These findings indicate that cardiac activity such as heart rate or individual heartbeats can modulate or be modulated by ongoing oscillatory brain activity. [ABSTRACT FROM AUTHOR]

The neocortex is a layered sheet across which a basic organization is thought to widely apply. The variety of spontaneous activity patterns is similar throughout the cortex, consistent with the notion of a basic cortical organization. However, the basic organization is only an outline which needs adjustments and additions to account for the structural and functional diversity across cortical layers and areas. Such diversity suggests that spontaneous activity is spatially diverse in any particular behavioral state. Accordingly, this review summarizes the laminar and areal diversity in cortical activity during fixation and slow oscillations, and the effects of attention, anesthesia and plasticity on the cortical distribution of spontaneous activity. Among questions that remain open, characterizing the spatial diversity in spontaneous membrane potential may help elucidate how differences in circuitry among cortical regions supports their varied functions. More work is also needed to understand whether cortical spontaneous activity not only reflects cortical circuitry, but also contributes to determining the outcome of plasticity, so that it is itself a factor shaping the functional diversity of the cortex. [ABSTRACT FROM AUTHOR]

Background: Behavioral inhibition, which is a later-developing executive function (EF) and anatomically located in prefrontal areas, is impaired in attention-deficit and hyperactivity disorder (ADHD). While optimal EFs have been shown to depend on efficient sleep in healthy subjects, the impact of sleep problems, frequently reported in ADHD, remains elusive. Findings of macroscopic sleep changes in ADHD are inconsistent, but there is emerging evidence for distinct microscopic changes with a focus on prefrontal cortical regions and non-rapid eye movement (non-REM) slow-wave sleep. Recently, slow oscillations (SO) during non-REM sleep were found to be less functional and, as such, may be involved in sleep-dependent memory impairments in ADHD. Objective: By augmenting slow-wave power through bilateral, slow oscillating transcranial direct current stimulation (so-tDCS, frequency = 0.75 Hz) during non-REM sleep, we aimed to improve daytime behavioral inhibition in children with ADHD. Methods: Fourteen boys (10-14 years) diagnosed with ADHD were included. In a randomized, double-blind, cross-over design, patients received so-tDCS either in the first or in the second experimental sleep night. Inhibition control was assessed with a visuomotor go/no-go task. Intrinsic alertness was assessed with a simple stimulus response task. To control for visuomotor performance, motor memory was assessed with a finger sequence tapping task. Results: SO-power was enhanced during early non-REM sleep, accompanied by slowed reaction times and decreased standard deviations of reaction times, in the go/no-go task after so-tDCS. In contrast, intrinsic alertness, and motor memory performance were not improved by so-tDCS. Conclusion: Since behavioral inhibition but not intrinsic alertness or motor memory was improved by so-tDCS, our results suggest that lateral prefrontal slow oscillations during sleep might play a specific role for executive functioning in ADHD. [ABSTRACT FROM AUTHOR]

The recurrent circuitry of the cerebral cortex generates an emergent pattern of activity that is organized into rhythmic periods of firing and silence referred to as slow oscillations (ca 1 Hz). Slow oscillations not only are dominant during slow wave sleep and deep anesthesia, but also can be generated by the isolated cortical network in vitro, being a sort of default activity of the cortical network. The cortex is densely and reciprocally connected with subcortical structures and, as a result, the slow oscillations in situ are the result of an interplay between cortex and thalamus. Due to this reciprocal connectivity and interplay, the mechanism responsible for the initiation of waves in the corticothalamocortical loop during slow oscillations is still a matter of debate. It was our objective to determine the directionality of the information flow between different layers of the cortex and the connected thalamus during spontaneous activity. With that purpose we obtained multilayer local field potentials from the rat visual cortex and from its connected thalamus, the lateral geniculate nucleus, during deep anaesthesia. We analyzed directionality of information flow between thalamus, cortical infragranular layers (5 and 6) and supragranular layers (2/3) by means of three information theoretical indicators: transfer entropy, symbolic transfer entropy and transcript mutual information. These three indicators coincided in finding that infragranular layers lead the information flow during slow oscillations both towards supragranular layers and towards the thalamus. [ABSTRACT FROM AUTHOR]

The < 1 Hz EEG slow oscillation (SO) is a hallmark of slow-wave sleep (SWS) and is critically involved in sleep-associated memory formation. Previous studies showed that SOs and associated memory function can be effectively enhanced by closed-loop auditory stimulation, when clicks are presented in synchrony with upcoming SO up states. However, increasing SOs and synchronized excitability also bear the risk of emerging seizure activity, suggesting the presence of mechanisms in the healthy brain that counter developing hypersynchronicity during SOs. Here, we aimed to test the limits of driving SOs through closed-loop auditory stimulation in healthy humans. Study I tested a "Driving stimulation" protocol (vs "Sham") in which trains of clicks were presented in synchrony with SO up states basically as long as an ongoing SO train was identified on-line. Study II compared Driving stimulation with a "2-Click" protocol where the maximum of stimuli delivered in a train was limited to two clicks. Stimulation was applied during SWS in the first 210 min of nocturnal sleep. Before and after sleep declarative word-pair memories were tested. Compared with the Sham control, Driving stimulation prolonged SO trains and enhanced SO amplitudes, phase-locked spindle activity, and overnight retention of word pairs (all ps < 0.05). Importantly, effects of Driving stimulation did not exceed those of 2-Click stimulation (p > 0.180), indicating the presence of a mechanism preventing the development of hypersynchronicity during SO activity. Assessment of temporal dynamics revealed a rapidly fading phase-locked spindle activity during repetitive click stimulation, suggesting that spindle refractoriness contributes to this protective mechanism. [ABSTRACT FROM AUTHOR]

Introduction Sleep complaints are common after mild traumatic brain injury (mTBI). While recent findings suggest that sleep macro-architecture is preserved in mTBI, features of non-rapid eye movement (NREM) sleep micro-architecture including electroencephalography (EEG) spectral power, slow waves (SW), and sleep spindles could be affected. This study aimed to compare NREM sleep in mTBI and healthy controls, and explore whether NREM sleep characteristics correlate with sleep complaints in these groups. Methods Thirty-four mTBI participants (mean age: 34.2 ± 11.9 yrs; post-injury delay: 10.5 ± 10.4 weeks) and 29 age-matched controls (mean age: 32.4 ± 8.2 yrs) were recruited for two consecutive nights of polysomnographic (PSG) recording. Spectral power was computed and SW and spindles were automatically detected in three derivations (F3, C3, O1) for the first three sleep cycles. Subjective sleep quality was assessed with the Pittsburgh Sleep Quality Index (PSQI). Results mTBI participants reported significant poorer sleep quality than controls on the PSQI and showed significant increases in beta power during NREM sleep at the occipital derivation only. Conversely, no group differences were found in SW and spindle characteristics. Interestingly, changes in NREM sleep characteristics were not associated with mTBI estimation of sleep quality. Conclusions Compared to controls, mTBI were found to have enhanced NREM beta power. However, these changes were not found to be associated with the subjective evaluation of sleep. While increases in beta bands during NREM sleep may be attributable to the occurrence of a brain injury, they could also be related to the presence of pain and anxiety as suggested in one prior study. [ABSTRACT FROM AUTHOR]

In response to stimulus changes, the firing rates of many neurons adapt, such that stimulus change is emphasized. Previous work has emphasized that rate adaptation can span a wide range of time scales and produce time scale invariant power law adaptation. However, neuronal rate adaptation is typically modeled using single time scale dynamics, and constructing a conductance-based model with arbitrary adaptation dynamics is nontrivial. Here, a modeling approach is developed in which firing rate adaptation, or spike frequency adaptation, can be understood as a filtering of slow stimulus statistics. Adaptation dynamics are modeled by a stimulus filter, and quantified by measuring the phase leads of the firing rate in response to varying input frequencies. Arbitrary adaptation dynamics are approximated by a set of weighted exponentials with parameters obtained by fitting to a desired filter. With this approach it is straightforward to assess the effect of multiple time scale adaptation dynamics on neural networks. To demonstrate this, single time scale and power law adaptation were added to a network model of local field potentials. Rate adaptation enhanced the slow oscillations of the network and flattened the output power spectrum, dampening intrinsic network frequencies. Thus, rate adaptation may play an important role in network dynamics. [ABSTRACT FROM AUTHOR]