Closed-Loop Slow-Wave tACS Improves Sleep-Dependent Long-Term Memory Generalization by Modulating Endogenous Oscillations

Investigating the Effects of Transcranial Alternating Current Stimulation on Cortical Oscillations and Network Dynamics

Transcranial electrical brain stimulation techniques like transcranial direct current (tDCS) and transcranial alternating current (tACS) have emerged as potential tools for treating neurological diseases by modulating cortical excitability. These techniques deliver small electric currents to the brain non-invasively through electrodes on the scalp. tDCS uses constant direct current which weakly alters the membrane voltage of cortical neurons, while tACS utilizes alternating current to target and enhance cortical oscillations, though the underlying mechanisms are not fully understood more specifically. To elucidate how tACS perturbs endogenous network dynamics, we simulated spiking neuron network models. We identified distinct roles of the depolarizing and hyperpolarizing phases in driving network activity towards and away from the strong nonlinearity provided by pyramidal neurons. Exploring resonance effects, we found matching tACS frequency to the network's endogenous resonance frequency creates greater entrainment. Based on this, we developed an algorithm to determine the network's endogenous frequency, phase, and amplitude, then deliver optimized tACS to entrain network oscillations. Together, these computational results provide mechanistic insight into the effects of tACS on network dynamics and could inform future closed-loop tACS systems that dynamically tune stimulation parameters to ongoing brain activity.

The effect of transcranial alternating current stimulation on cognitive flexibility and attention of children with intellectual disability: a case report

BACKGROUND

Intellectual disability is a neurodevelopmental disorder characterized by significant impairments in intellectual functioning and adaptive behavior. Cognitive flexibility and attention are crucial cognitive domains often affected in children with intellectual disability. This case report explores the novel use of transcranial alternating current stimulation, a noninvasive brain stimulation technique, to enhance these cognitive functions. The study's novelty lies in its focus on alpha-wave frequency transcranial alternating current stimulation targeting specific Brodmann areas and its potential sustained impact on cognitive flexibility and attention in the pediatric population with intellectual disability.

CASE PRESENTATION

The case study involved two elementary school students, both 7 years old with mild intellectual disability, one male and one female, both with Turkic ethnicity, from Shahid Fahmideh School for Exceptional Children in Khosrowshah, Iran. Both participants underwent a 2-week intervention with daily 20-minute sessions of transcranial alternating current stimulation at an alpha-wave frequency (10 Hz), targeting Brodmann areas F3 and P3. Cognitive flexibility and attention were assessed using the Wisconsin Card Sorting Test and the Clock Test, administered at four time points: pre-intervention, week 1, week 2, and 1 month post-intervention. Statistical analysis showed significant improvements in both Wisconsin Card Sorting Test and Clock Test scores for both participants compared with baseline, with sustained enhancement over time.

CONCLUSION

The findings from this case report indicate that transcranial alternating current stimulation may be a promising intervention for improving cognitive flexibility and attention in children with intellectual disability. The significant and sustained improvements observed suggest that transcranial alternating current stimulation could have a meaningful clinical impact on the cognitive development of this population. However, further research is needed to confirm the efficacy of transcranial alternating current stimulation and to explore its broader applicability and long-term effects in larger, more diverse populations.

Transcranial alternating current stimulation in affecting cognitive impairment in psychiatric disorders: a review

Transcranial alternating current stimulation (tACS) is a non-invasive brain stimulation method that, through its manipulation of endogenous oscillations, can affect cognition in healthy adults. Given the fact that both endogenous oscillations and cognition are impaired in various psychiatric diagnoses, tACS might represent a suitable intervention. We conducted a search of Pubmed and Web of Science databases and reviewed 27 studies where tACS is used in psychiatric diagnoses and cognition change is evaluated. TACS is a safe and well-tolerated intervention method, suitable for multiple-sessions protocols. It can be administered at home, individualized according to the patient''s anatomical and functional characteristics, or used as a marker of disease progression. The results are varying across diagnoses and applied protocols, with some protocols showing a long-term effect. However, the overall number of studies is small with a great variety of diagnoses and tACS parameters, such as electrode montage or used frequency. Precise mechanisms of tACS interaction with pathophysiological processes are only partially described and need further research. Currently, tACS seems to be a feasible method to alleviate cognitive impairment in psychiatric patients; however, a more robust confirmation of efficacy of potential protocols is needed to introduce it into clinical practise.

Spindle oscillations in communicating axons within a reconstituted hippocampal formation are strongest in CA3 without thalamus

Spindle-shaped waves of oscillations emerge in EEG scalp recordings during human and rodent non-REM sleep. The association of these 10-16 Hz oscillations with events during prior wakefulness suggests a role in memory consolidation. Human and rodent depth electrodes in the brain record strong spindles throughout the cortex and hippocampus, with possible origins in the thalamus. However, the source and targets of the spindle oscillations from the hippocampus are unclear. Here, we employed an in vitro reconstruction of four subregions of the hippocampal formation with separate microfluidic tunnels for single axon communication between subregions assembled on top of a microelectrode array. We recorded spontaneous 400-1000 ms long spindle waves at 10-16 Hz in single axons passing between subregions as well as from individual neurons in those subregions. Spindles were nested within slow waves. The highest amplitudes and most frequent occurrence suggest origins in CA3 neurons that send feed-forward axons into CA1 and feedback axons into DG. Spindles had 50-70% slower conduction velocities than spikes and were not phase-locked to spikes suggesting that spindle mechanisms are independent of action potentials. Therefore, consolidation of declarative-cognitive memories in the hippocampus may be separate from the more easily accessible consolidation of memories related to thalamic motor function.

Opportunities and obstacles in non-invasive brain stimulation

Non-invasive brain stimulation (NIBS) is a complex and multifaceted approach to modulating brain activity and holds the potential for broad accessibility. This work discusses the mechanisms of the four distinct approaches to modulating brain activity non-invasively: electrical currents, magnetic fields, light, and ultrasound. We examine the dual stochastic and deterministic nature of brain activity and its implications for NIBS, highlighting the challenges posed by inter-individual variability, nebulous dose-response relationships, potential biases and neuroanatomical heterogeneity. Looking forward, we propose five areas of opportunity for future research: closed-loop stimulation, consistent stimulation of the intended target region, reducing bias, multimodal approaches, and strategies to address low sample sizes.

A classification-based generative approach to selective targeting of global slow oscillations during sleep

Background

Given sleep's crucial role in health and cognition, numerous sleep-based brain interventions are being developed, aiming to enhance cognitive function, particularly memory consolidation, by improving sleep. Research has shown that Transcranial Alternating Current Stimulation (tACS) during sleep can enhance memory performance, especially when used in a closed-loop (cl-tACS) mode that coordinates with sleep slow oscillations (SOs, 0.5-1.5Hz). However, sleep tACS research is characterized by mixed results across individuals, which are often attributed to individual variability.

Objective/Hypothesis

This study targets a specific type of SOs, widespread on the electrode manifold in a short delay ("global SOs"), due to their close relationship with long-term memory consolidation. We propose a model-based approach to optimize cl-tACS paradigms, targeting global SOs not only by considering their temporal properties but also their spatial profile.

Methods

We introduce selective targeting of global SOs using a classification-based approach. We first estimate the current elicited by various stimulation paradigms, and optimize parameters to match currents found in natural sleep during a global SO. Then, we employ an ensemble classifier trained on sleep data to identify effective paradigms. Finally, the best stimulation protocol is determined based on classification performance.

Results

Our study introduces a model-driven cl-tACS approach that specifically targets global SOs, with the potential to extend to other brain dynamics. This method establishes a connection between brain dynamics and stimulation optimization.

Conclusion

Our research presents a novel approach to optimize cl-tACS during sleep, with a focus on targeting global SOs. This approach holds promise for improving cl-tACS not only for global SOs but also for other physiological events, benefiting both research and clinical applications in sleep and cognition.

Single closed-loop acoustic stimulation targeting memory consolidation suppressed hippocampal ripple and thalamo-cortical spindle activity in mice

Brain rhythms of sleep reflect neuronal activity underlying sleep-associated memory consolidation. The modulation of brain rhythms, such as the sleep slow oscillation (SO), is used both to investigate neurophysiological mechanisms as well as to measure the impact of sleep on presumed functional correlates. Previously, closed-loop acoustic stimulation in humans targeted to the SO Up-state successfully enhanced the slow oscillation rhythm and phase-dependent spindle activity, although effects on memory retention have varied. Here, we aim to disclose relations between stimulation-induced hippocampo-thalamo-cortical activity and retention performance on a hippocampus-dependent object-place recognition task in mice by applying acoustic stimulation at four estimated SO phases compared to sham condition. Across the 3-h retention interval at the beginning of the light phase closed-loop stimulation failed to improve retention significantly over sham. However, retention during SO Up-state stimulation was significantly higher than for another SO phase. At all SO phases, acoustic stimulation was accompanied by a sharp increase in ripple activity followed by about a second-long suppression of hippocampal sharp wave ripple and longer maintained suppression of thalamo-cortical spindle activity. Importantly, dynamics of SO-coupled hippocampal ripple activity distinguished SOUp-state stimulation. Non-rapid eye movement (NREM) sleep was not impacted by stimulation, yet preREM sleep duration was effected. Results reveal the complex effect of stimulation on the brain dynamics and support the use of closed-loop acoustic stimulation in mice to investigate the inter-regional mechanisms underlying memory consolidation.

Predicting the phase distribution during multi-channel transcranial alternating current stimulation in silico and in vivo

BACKGROUND

Transcranial alternating current stimulation (tACS) is a widely used noninvasive brain stimulation (NIBS) technique to affect neural activity. TACS experiments have been coupled with computational simulations to predict the electromagnetic fields within the brain. However, existing simulations are focused on the magnitude of the field. As the possibility of inducing the phase gradient in the brain using multiple tACS electrodes arises, a simulation framework is necessary to investigate and predict the phase gradient of electric fields during multi-channel tACS.

OBJECTIVE

Here, we develop such a framework for phasor simulation using phasor algebra and evaluate its accuracy using in vivo recordings in monkeys.

METHODS

We extract the phase and amplitude of electric fields from intracranial recordings in two monkeys during multi-channel tACS and compare them to those calculated by phasor analysis using finite element models.

RESULTS

Our findings demonstrate that simulated phases correspond well to measured phases (r = 0.9). Further, we systematically evaluated the impact of accurate electrode placement on modeling and data agreement. Finally, our framework can predict the amplitude distribution in measurements given calibrated tissues' conductivity.

CONCLUSIONS

Our validated general framework for simulating multi-phase, multi-electrode tACS provides a streamlined tool for principled planning of multi-channel tACS experiments.

Transcranial alternating current stimulation for the treatment of major depressive disorder: from basic mechanisms toward clinical applications

Non-pharmacological treatment is essential for patients with major depressive disorder (MDD) that is medication resistant or who are unable to take medications. Transcranial alternating current stimulation (tACS) is a non-invasive brain stimulation method that manipulates neural oscillations. In recent years, tACS has attracted substantial attention for its potential as an MDD treatment. This review summarizes the latest advances in tACS treatment for MDD and outlines future directions for promoting its clinical application. We first introduce the neurophysiological mechanism of tACS and its novel developments. In particular, two well-validated tACS techniques have high application potential: high-definition tACS targeting local brain oscillations and bifocal tACS modulating interarea functional connectivity. Accordingly, we summarize the underlying mechanisms of tACS modulation for MDD. We sort out the local oscillation abnormalities within the reward network and the interarea oscillatory synchronizations among multiple MDD-related networks in MDD patients, which provide potential modulation targets of tACS interventions. Furthermore, we review the latest clinical studies on tACS treatment for MDD, which were based on different modulation mechanisms and reported alleviations in MDD symptoms. Finally, we discuss the main challenges of current tACS treatments for MDD and outline future directions to improve intervention target selection, tACS implementation, and clinical validations.

Closing the loop between brain and electrical stimulation: towards precision neuromodulation treatments

One of the most critical challenges in using noninvasive brain stimulation (NIBS) techniques for the treatment of psychiatric and neurologic disorders is inter- and intra-individual variability in response to NIBS. Response variations in previous findings suggest that the one-size-fits-all approach does not seem the most appropriate option for enhancing stimulation outcomes. While there is a growing body of evidence for the feasibility and effectiveness of individualized NIBS approaches, the optimal way to achieve this is yet to be determined. Transcranial electrical stimulation (tES) is one of the NIBS techniques showing promising results in modulating treatment outcomes in several psychiatric and neurologic disorders, but it faces the same challenge for individual optimization. With new computational and methodological advances, tES can be integrated with real-time functional magnetic resonance imaging (rtfMRI) to establish closed-loop tES-fMRI for individually optimized neuromodulation. Closed-loop tES-fMRI systems aim to optimize stimulation parameters based on minimizing differences between the model of the current brain state and the desired value to maximize the expected clinical outcome. The methodological space to optimize closed-loop tES fMRI for clinical applications includes (1) stimulation vs. data acquisition timing, (2) fMRI context (task-based or resting-state), (3) inherent brain oscillations, (4) dose-response function, (5) brain target trait and state and (6) optimization algorithm. Closed-loop tES-fMRI technology has several advantages over non-individualized or open-loop systems to reshape the future of neuromodulation with objective optimization in a clinically relevant context such as drug cue reactivity for substance use disorder considering both inter and intra-individual variations. Using multi-level brain and behavior measures as input and desired outcomes to individualize stimulation parameters provides a framework for designing personalized tES protocols in precision psychiatry.

Using gamma-band transcranial alternating current stimulation (tACS) to improve sleep quality and cognition in patients with mild neurocognitive disorders due to Alzheimer's disease: A study protocol for a randomized controlled trial

BACKGROUND

Sleep disturbances are highly prevalent in patients with age-related neurodegenerative diseases, which severely affect cognition and even lead to accumulated β-amyloid. Encouraging results from recent studies on transcranial direct current stimulation (tDCS) showed moderate positive effects on sleep quality in preclinical Alzheimer's disease (AD). Compared to tDCS, transcranial alternating current stimulation (tACS) enables the entrainment of neuronal activity with optimized focality through injecting electric current with a specific frequency and has significant enhancement effects on slow wave activities.

METHODS AND DESIGN

This is a randomized, double-blind, sham-controlled clinical trial comparing 40 Hz tACS with tDCS in mild neurocognitive disorders due to AD with sleep disturbances. Magnetic resonance imaging (MRI) data is used to construct personalized realistic head model. Treatment outcomes, including sleep quality, cognitive performance and saliva Aβ levels will be conducted at baseline, 4th week, 8th week, 12th week and 24th week.

CONCLUSIONS

It is expected that the repeated gamma-band tACS will show significant improvements in sleep quality and cognitive functions compared to tDCS and sham tDCS. The findings will provide high-level evidence and guide further advanced studies in the field of neurodegenerative diseases and sleep medicine.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT05544201.

Design of a Sleep Modulation System with FPGA-Accelerated Deep Learning for Closed-loop Stage-Specific In-Phase Auditory Stimulation

Closed-loop sleep modulation is an emerging research paradigm to treat sleep disorders and enhance sleep benefits. However, two major barriers hinder the widespread application of this research paradigm. First, subjects often need to be wire-connected to rack-mount instrumentation for data acquisition, which negatively affects sleep quality. Second, conventional real-time sleep stage classification algorithms give limited performance. In this work, we conquer these two limitations by developing a sleep modulation system that supports closed-loop operations on the device. Sleep stage classification is performed using a lightweight deep learning (DL) model accelerated by a low-power field-programmable gate array (FPGA) device. The DL model uses a single channel electroencephalogram (EEG) as input. Two convolutional neural networks (CNNs) are used to capture general and detailed features, and a bidirectional long-short-term memory (LSTM) network is used to capture time-variant sequence features. An 8-bit quantization is used to reduce the computational cost without compromising performance. The DL model has been validated using a public sleep database containing 81 subjects, achieving a state-of-the-art classification accuracy of 85.8% and a F1-score of 79%. The developed model has also shown the potential to be generalized to different channels and input data lengths. Closed-loop in-phase auditory stimulation has been demonstrated on the test bench.

Sleep spindles in the healthy brain from birth through 18 years

STUDY OBJECTIVE

Sleep spindles are present from birth and reflect cognitive functions across the lifespan, but normative values for this cognitive biomarker across development are lacking. This study aims to establish normative spindle features over development.

METHODS

All available normal 19-channel electroencephalograms from developmentally normal children between February 2002 and June 2021 in the MGH EEG lab were analyzed. Approximately, 20 000 spindles were hand-marked to train and validate an automated spindle detector across ages. Normative values for spindle rate, duration, frequency, refractory period, and interhemispheric lag are provided for each channel and each age.

RESULTS

Sleep EEGs from 567 developmentally normal children (range 0 days to 18 years) were included. The detector had excellent performance (F1 = 0.47). Maximal spindle activity is seen over central regions during infancy and adolescence and frontopolar regions during childhood. Spindle rate and duration increase nonlinearly, with the most rapid changes during the first 4 months of life and between ages 3 and 14 years. Peak spindle frequency follows a U-shaped curve and discrete frontal slow and central fast spindles are evident by 18 months. Spindle refractory periods decrease between ages 1 and 14 years while interhemispheric asynchrony decreases over the first 3 months of life and between ages 1 and 14 years.

CONCLUSIONS

These data provide age- and region-specific normative values for sleep spindles across development, where measures that deviate from these values can be considered pathological. As spindles provide a noninvasive biomarker for cognitive function across the lifespan, these normative measures can accelerate the discovery and diagnosis in neurodevelopmental disorders.

Experimental validation of computational models for the prediction of phase distribution during multi-channel transcranial alternating current stimulation

Transcranial alternating current stimulation (tACS) is a widely used noninvasive brain stimulation (NIBS) technique to affect neural activity. Neural oscillations exhibit phase-dependent associations with cognitive functions, and tools to manipulate local oscillatory phases can affect communication across remote brain regions. A recent study demonstrated that multi-channel tACS can generate electric fields with a phase gradient or traveling waves in the brain. Computational simulations using phasor algebra can predict the phase distribution inside the brain and aid in informing parameters in tACS experiments. However, experimental validation of computational models for multi-phase tACS is still lacking. Here, we develop such a framework for phasor simulation and evaluate its accuracy using in vivo recordings in nonhuman primates. We extract the phase and amplitude of electric fields from intracranial recordings in two monkeys during multi-channel tACS and compare them to those calculated by phasor analysis using finite element models. Our findings demonstrate that simulated phases correspond well to measured phases (r = 0.9). Further, we systematically evaluated the impact of accurate electrode placement on modeling and data agreement. Finally, our framework can predict the amplitude distribution in measurements given calibrated tissues’ conductivity. Our validated general framework for simulating multi-phase, multi-electrode tACS provides a streamlined tool for principled planning of multi-channel tACS experiments.

Neurophysiological mechanisms of transcranial alternating current stimulation

Neuronal oscillations are the primary basis for precise temporal coordination of neuronal processing and are linked to different brain functions. Transcranial alternating current stimulation (tACS) has demonstrated promising potential in improving cognition by entraining neural oscillations. Despite positive findings in recent decades, the results obtained are sometimes rife with variance and replicability problems, and the findings translation to humans is quite challenging. A thorough understanding of the mechanisms underlying tACS is necessitated for accurate interpretation of experimental results. Animal models are useful for understanding tACS mechanisms, optimizing parameter administration, and improving rational design for broad horizons of tACS. Here, we review recent electrophysiological advances in tACS from animal models, as well as discuss some critical issues for results coordination and translation. We hope to provide an overview of neurophysiological mechanisms and recommendations for future consideration to improve its validity, specificity, and reproducibility.

A circuit-level biomarker of Rett syndrome based on ectopic phase-amplitude coupling during slow-wave-sleep

Rett syndrome (RTT) is a neurodevelopmental disorder characterized by loss of purposeful hand use and spoken language following an initial period of normal development. Although much is known about the genetic and molecular underpinnings of RTT, less is known about the circuit-level etiopathology. Coupling of oscillations during slow-wave-sleep (SWS) underlies important neurocognitive processes in adulthood, yet its emergence has yet to be described in early typical development (TD) or in RTT. We therefore addressed these unknowns by describing SWS cross-frequency coupling in both RTT and early TD using a retrospective study design. We found that in TD, phase-amplitude coupling (PAC) during SWS was dominated by coupling of slow-wave (0.5-2 Hz) phase to theta amplitude (5-8 Hz, "SW:T") as well as slow-wave to spindle-range (12-15 Hz, "SW:S"). Coupling exhibited characteristic vertex-prominent spatial topography, which emerged during an early developmental window. This topography failed to develop in patients with RTT due to persistent ectopic coupling. Furthermore, we found that subtypes of RTT exhibit distinct PAC topographic profiles, and that ectopic PAC correlates with clinical severity. These findings suggest that altered PAC dynamics and spatial organization during SWS may underlie the circuit-level pathophysiology of RTT and suggest that ectopic coupling may contribute to RTT pathogenesis.

Closed-Loop tACS Delivered during Slow-Wave Sleep Reduces Retroactive Interference on a Paired-Associates Learning Task

Previous studies have found a benefit of closed-loop transcranial alternating current stimulation (CL-tACS) matched to ongoing slow-wave oscillations (SWO) during sleep on memory consolidation for words in a paired associates task (PAT). Here, we examined the effects of CL-tACS in a retroactive interference PAT (ri-PAT) paradigm, where additional stimuli were presented to increase interference and reduce memory performance. Thirty-one participants were tested on a PAT before sleep, and CL-tACS was applied over the right and left DLPFC (F3 and F4) vs. mastoids for five cycles after detection of the onset of each discrete event of SWO during sleep. Participants were awoken the following morning, learned a new PAT list, and then were tested on the original list. There was a significant effect of stimulation condition (p = 0.04297; Cohen’s d = 0.768), where verum stimulation resulted in reduced retroactive interference compared with sham and a significant interaction of encoding strength and stimulation condition (p = 0.03591). Planned simple effects testing within levels of encoding revealed a significant effect of stimulation only for low-encoders (p = 0.0066; Cohen’s d = 1.075) but not high-encoders. We demonstrate here for the first time that CL-tACS during sleep can enhance the protective benefits on retroactive interference in participants who have lower encoding aptitude.

Alpha oscillatory activity is causally linked to working memory retention

Although previous studies have reported correlations between alpha oscillations and the "retention" subprocess of working memory (WM), causal evidence has been limited in human neuroscience due to the lack of delicate modulation of human brain oscillations. Conventional transcranial alternating current stimulation (tACS) is not suitable for demonstrating the causal evidence for parietal alpha oscillations in WM retention because of its inability to modulate brain oscillations within a short period (i.e., the retention subprocess). Here, we developed an online phase-corrected tACS system capable of precisely correcting for the phase differences between tACS and concurrent endogenous oscillations. This system permits the modulation of brain oscillations at the target stimulation frequency within a short stimulation period and is here applied to empirically demonstrate that parietal alpha oscillations causally relate to WM retention. Our experimental design included both in-phase and anti-phase alpha-tACS applied to participants during the retention subprocess of a modified Sternberg paradigm. Compared to in-phase alpha-tACS, anti-phase alpha-tACS decreased both WM performance and alpha activity. These findings strongly support a causal link between alpha oscillations and WM retention and illustrate the broad application prospects of phase-corrected tACS.

Neurocognitive, physiological, and biophysical effects of transcranial alternating current stimulation

Transcranial alternating current stimulation (tACS) can modulate human neural activity and behavior. Accordingly, tACS has vast potential for cognitive research and brain disorder therapies. The stimulation generates oscillating electric fields in the brain that can bias neural spike timing, causing changes in local neural oscillatory power and cross-frequency and cross-area coherence. tACS affects cognitive performance by modulating underlying single or nested brain rhythms, local or distal synchronization, and metabolic activity. Clinically, stimulation tailored to abnormal neural oscillations shows promising results in alleviating psychiatric and neurological symptoms. We summarize the findings of tACS mechanisms, its use for cognitive applications, and novel developments for personalized stimulation.

A Scalable Framework for Closed-Loop Neuromodulation with Deep Learning

Closed-loop neuromodulation measures dynamic neural or physiological activity to optimize interventions for clinical and nonclinical behavioral, cognitive, wellness, attentional, or general task performance enhancement. Conventional closed-loop stimulation approaches can contain biased biomarker detection (decoders and error-based triggering) and stimulation-type application. We present and verify a novel deep learning framework for designing and deploying flexible, data-driven, automated closed-loop neuromodulation that is scalable using diverse datasets, agnostic to stimulation technology (supporting multi-modal stimulation: tACS, tDCS, tFUS, TMS), and without the need for personalized ground-truth performance data. Our approach is based on identified periods of responsiveness - detected states that result in a change in performance when stimulation is applied compared to no stimulation. To demonstrate our framework, we acquire, analyze, and apply a data-driven approach to our open sourced GX dataset, which includes concurrent physiological (ECG, EOG) and neuronal (EEG) measures, paired with continuous vigilance/attention-fatigue tracking, and High-Definition transcranial electrical stimulation (HD-tES). Our framework's decision process for intervention application identified 88.26% of trials as correct applications, showed potential improvement with varying stimulation types, or missed opportunities to stimulate, whereas 11.25% of trials were predicted to stimulate at inopportune times. With emerging datasets and stimulation technologies, our unifying and integrative framework; leveraging deep learning (Convolutional Neural Networks - CNNs); demonstrates the adaptability and feasibility of automated multimodal neuromodulation for both clinical and nonclinical applications.

Somatostatin neuron contributions to cortical slow wave dysfunction in adult mice exposed to developmental ethanol

Introduction

Transitions between sleep and waking and sleep-dependent cortical oscillations are heavily dependent on GABAergic neurons. Importantly, GABAergic neurons are especially sensitive to developmental ethanol exposure, suggesting a potential unique vulnerability of sleep circuits to early ethanol. In fact, developmental ethanol exposure can produce long-lasting impairments in sleep, including increased sleep fragmentation and decreased delta wave amplitude. Here, we assessed the efficacy of optogenetic manipulations of somatostatin (SST) GABAergic neurons in the neocortex of adult mice exposed to saline or ethanol on P7, to modulate cortical slow-wave physiology.

Methods

SST-cre × Ai32 mice, which selectively express channel rhodopsin in SST neurons, were exposed to ethanol or saline on P7. This line expressed similar developmental ethanol induced loss of SST cortical neurons and sleep impairments as C57BL/6By mice. As adults, optical fibers were implanted targeting the prefrontal cortex (PFC) and telemetry electrodes were implanted in the neocortex to monitor slow-wave activity and sleep-wake states.

Results

Optical stimulation of PFC SST neurons evoked slow-wave potentials and long-latency single-unit excitation in saline treated mice but not in ethanol mice. Closed-loop optogenetic stimulation of PFC SST neuron activation on spontaneous slow-waves enhanced cortical delta oscillations, and this manipulation was more effective in saline mice than P7 ethanol mice.

Discussion

Together, these results suggest that SST cortical neurons may contribute to slow-wave impairment after developmental ethanol.

Closed-loop modulation of local slow oscillations in human NREM sleep

Slow-wave sleep is the deep non-rapid eye-movement (NREM) sleep stage that is most relevant for the recuperative function of sleep. Its defining property is the presence of slow oscillations (<2 Hz) in the scalp electroencephalogram (EEG). Slow oscillations are generated by a synchronous back and forth between highly active UP-states and silent DOWN-states in neocortical neurons. Growing evidence suggests that closed-loop sensory stimulation targeted at UP-states of EEG-defined slow oscillations can enhance the slow oscillatory activity, increase sleep depth, and boost sleep's recuperative functions. However, several studies failed to replicate such findings. Failed replications might be due to the use of conventional closed-loop stimulation algorithms that analyze the signal from one single electrode and thereby neglect the fact that slow oscillations vary with respect to their origins, distributions, and trajectories on the scalp. In particular, conventional algorithms nonspecifically target functionally heterogeneous UP-states of distinct origins. After all, slow oscillations at distinct sites of the scalp have been associated with distinct functions. Here we present a novel EEG-based closed-loop stimulation algorithm that allows targeting UP- and DOWN-states of distinct cerebral origins based on topographic analyses of the EEG: the topographic targeting of slow oscillations (TOPOSO) algorithm. We present evidence that the TOPOSO algorithm can detect and target local slow oscillations with specific, predefined voltage maps on the scalp in real-time. When compared to a more conventional, single-channel-based approach, TOPOSO leads to fewer but locally more specific stimulations in a simulation study. In a validation study with napping participants, TOPOSO targets auditory stimulation reliably at local UP-states over frontal, sensorimotor, and centro-parietal regions. Importantly, auditory stimulation temporarily enhanced the targeted local state. However, stimulation then elicited a standard frontal slow oscillation rather than local slow oscillations. The TOPOSO algorithm is suitable for the modulation and the study of the functions of local slow oscillations.

A model of autonomous interactions between hippocampus and neocortex driving sleep-dependent memory consolidation

How do we build up our knowledge of the world over time? Many theories of memory formation and consolidation have posited that the hippocampus stores new information, then "teaches" this information to the neocortex over time, especially during sleep. But it is unclear, mechanistically, how this actually works-How are these systems able to interact during periods with virtually no environmental input to accomplish useful learning and shifts in representation? We provide a framework for thinking about this question, with neural network model simulations serving as demonstrations. The model is composed of hippocampus and neocortical areas, which replay memories and interact with one another completely autonomously during simulated sleep. Oscillations are leveraged to support error-driven learning that leads to useful changes in memory representation and behavior. The model has a non-rapid eye movement (NREM) sleep stage, where dynamics between the hippocampus and neocortex are tightly coupled, with the hippocampus helping neocortex to reinstate high-fidelity versions of new attractors, and a REM sleep stage, where neocortex is able to more freely explore existing attractors. We find that alternating between NREM and REM sleep stages, which alternately focuses the model's replay on recent and remote information, facilitates graceful continual learning. We thus provide an account of how the hippocampus and neocortex can interact without any external input during sleep to drive useful new cortical learning and to protect old knowledge as new information is integrated.

A model of bi-directional interactions between complementary learning systems for memory consolidation of sequential experiences

The standard theory of memory consolidation posits a dual-store memory system: a fast-learning fast-decaying hippocampus that transfers memories to slow-learning long-term cortical storage. Hippocampal lesions interrupt this transfer, so recent memories are more likely to be lost than more remote memories. Existing models of memory consolidation that simulate this temporally graded retrograde amnesia operate only on static patterns or unitary variables as memories and study only one-way interaction from the hippocampus to the cortex. However, the mechanisms underlying the consolidation of episodes, which are sequential in nature and comprise multiple events, are not well-understood. The representation of learning for sequential experiences in the cortical-hippocampal network as a self-consistent dynamical system is not sufficiently addressed in prior models. Further, there is evidence for a bi-directional interaction between the two memory systems during offline periods, whereby the reactivation of waking neural patterns originating in the cortex triggers time-compressed sequential replays in the hippocampus, which in turn drive the consolidation of the pertinent sequence in the cortex. We have developed a computational model of memory encoding, consolidation, and recall for storing temporal sequences that explores the dynamics of this bi-directional interaction and time-compressed replays in four simulation experiments, providing novel insights into whether hippocampal learning needs to be suppressed for stable memory consolidation and into how new and old memories compete for limited replay opportunities during offline periods. The salience of experienced events, based on factors such as recency and frequency of use, is shown to have considerable impact on memory consolidation because it biases the relative probability that a particular event will be cued in the cortex during offline periods. In the presence of hippocampal learning during sleep, our model predicts that the fast-forgetting hippocampus can continually refresh the memory traces of a given episodic sequence if there are no competing experiences to be replayed.

Boosting psychological change: Combining non-invasive brain stimulation with psychotherapy

Mental health disorders and substance use disorders are a leading cause of morbidity and mortality worldwide, and one of the most important challenges for public health systems. While evidence-based psychotherapy is generally pursued to address mental health challenges, psychological change is often hampered by non-adherence to treatments, relapses, and practical barriers (e.g., time, cost). In recent decades, Non-invasive brain stimulation (NIBS) techniques have emerged as promising tools to directly target dysfunctional neural circuitry and promote long-lasting plastic changes. While the therapeutic efficacy of NIBS protocols for mental illnesses has been established, neuromodulatory interventions might also be employed to support the processes activated by psychotherapy. Indeed, combining psychotherapy with NIBS might help tailor the treatment to the patient's unique characteristics and therapeutic goal, and would allow more direct control of the neuronal changes induced by therapy. Herein, we overview emerging evidence on the use of NIBS to enhance the psychotherapeutic effect, while highlighting the next steps in advancing clinical and research methods toward personalized intervention approaches.

Alterations of sleep oscillations in Alzheimer's disease: A potential role for GABAergic neurons in the cortex, hippocampus, and thalamus

Sleep abnormalities are widely reported in patients with Alzheimer's disease (AD) and are linked to cognitive impairments. Sleep abnormalities could be potential biomarkers to detect AD since they are often observed at the preclinical stage. Moreover, sleep could be a target for early intervention to prevent or slow AD progression. Thus, here we review changes in brain oscillations observed during sleep, their connection to AD pathophysiology and the role of specific brain circuits. Slow oscillations (0.1-1 Hz), sleep spindles (8-15 Hz) and their coupling during non-REM sleep are consistently reduced in studies of patients and in AD mouse models although the timing and magnitude of these alterations depends on the pathophysiological changes and the animal model studied. Changes in delta (1-4 Hz) activity are more variable. Animal studies suggest that hippocampal sharp-wave ripples (100-250 Hz) are also affected. Reductions in REM sleep amount and slower oscillations during REM are seen in patients but less consistently in animal models. Thus, changes in a variety of sleep oscillations could impact sleep-dependent memory consolidation or restorative functions of sleep. Recent mechanistic studies suggest that alterations in the activity of GABAergic neurons in the cortex, hippocampus and thalamic reticular nucleus mediate sleep oscillatory changes in AD and represent a potential target for intervention. Longitudinal studies of the timing of AD-related sleep abnormalities with respect to pathology and dysfunction of specific neural networks are needed to identify translationally relevant biomarkers and guide early intervention strategies to prevent or delay AD progression.

Developing control-theoretic objectives for large-scale brain dynamics and cognitive enhancement

The development of technologies for brain stimulation provides a means for scientists and clinicians to directly actuate the brain and nervous system. Brain stimulation has shown intriguing potential in terms of modifying particular symptom clusters in patients and behavioral characteristics of subjects. The stage is thus set for optimization of these techniques and the pursuit of more nuanced stimulation objectives, including the modification of complex cognitive functions such as memory and attention. Control theory and engineering will play a key role in the development of these methods, guiding computational and algorithmic strategies for stimulation. In particular, realizing this goal will require new development of frameworks that allow for controlling not only brain activity, but also latent dynamics that underlie neural computation and information processing. In the current opinion, we review recent progress in brain stimulation and outline challenges and potential research pathways associated with exogenous control of cognitive function.

Electrophysiological Correlates of Response Time in a Vigilant Attention Task

Early detection of a deficit in vigilant attention can allow for user notification or intervention. In this paper, Electrophysiological correlates of vigilant attention from a random-dot motion task were explored. Using only frontal (Fz) and parietal (Pz) EEG channels, spectral features of response time were determined. Notably, significant differ-ences in high-beta, gamma and alpha frequency bands were found between fast and slow reaction times. These results are interpreted in line with the relevant literature on arousal, off-task thought and active visuospatial attentional suppression. The presence of response-locked time-domain features was analysed. However, motor-related features obfuscated these features.

Breaking the boundaries of interacting with the human brain using adaptive closed-loop stimulation

The human brain is arguably one of the most complex systems in nature. To understand how it operates, it is essential to understand the link between neural activity and behavior. Experimental investigation of that link requires tools to interact with neural activity during behavior. Human neuroscience, however, has been severely bottlenecked by the limitations of these tools. While invasive methods can support highly specific interaction with brain activity during behavior, their applicability in human neuroscience is limited. Despite extensive development in the last decades, noninvasive alternatives have lacked spatial specificity and yielded results that are commonly fraught with variability and replicability issues, along with relatively limited understanding of the neural mechanisms involved. Here we provide a comprehensive review of the state-of-the-art in interacting with human brain activity and highlight current limitations and recent efforts to overcome these limitations. Beyond crucial technical and scientific advancements in electromagnetic brain stimulation, new frontiers in interacting with human brain activity such as task-irrelevant sensory stimulation and focal ultrasound stimulation are introduced. Finally, we argue that, along with technological improvements and breakthroughs in noninvasive methods, a paradigm shift towards adaptive closed-loop stimulation will be a critical step for advancing human neuroscience.

Resting-state electroencephalography (EEG) biomarkers of chronic neuropathic pain. A systematic review

Diagnosis and management of chronic neuropathic pain are challenging, leading to current efforts to characterize 'objective' biomarkers of pain using imaging or neurophysiological techniques, such as electroencephalography (EEG). A systematic literature review was conducted in PubMed-Medline and Web-of-Science until October 2021 to identify EEG biomarkers of chronic neuropathic pain in humans. The risk of bias was assessed by the Newcastle-Ottawa-Scale. Experimental, provoked, or chronic non-neuropathic pain studies were excluded. We identified 14 studies, in which resting-state EEG spectral analysis was compared between patients with pain related to a neurological disease and patients with the same disease but without pain or healthy controls. From these heterogeneous exploratory studies, some conclusions can be drawn, even if they must be weighted by the fact that confounding factors, such as medication and association with anxio-depressive disorders, are generally not taken into account. Overall, EEG signal power was increased in the θ band (4-7Hz) and possibly in the high-β band (20-30Hz), but decreased in the high-α-low-β band (10-20Hz) in the presence of ongoing neuropathic pain, while increased γ band oscillations were not evidenced, unlike in experimental pain. Consequently, the dominant peak frequency was decreased in the θ-α band and increased in the whole-β band in neuropathic pain patients. Disappointingly, pain intensity correlated with various EEG changes across studies, with no consistent trend. This review also discusses the location of regional pain-related EEG changes in the pain connectome, as the perspectives offered by advanced techniques of EEG signal analysis (source location, connectivity, or classification methods based on artificial intelligence). The biomarkers provided by resting-state EEG are of particular interest for optimizing the treatment of chronic neuropathic pain by neuromodulation techniques, such as transcranial alternating current stimulation or neurofeedback procedures.

Non-invasive brain stimulation and neuroenhancement

Attempts to enhance human memory and learning ability have a long tradition in science. This topic has recently gained substantial attention because of the increasing percentage of older individuals worldwide and the predicted rise of age-associated cognitive decline in brain functions. Transcranial brain stimulation methods, such as transcranial magnetic (TMS) and transcranial electric (tES) stimulation, have been extensively used in an effort to improve cognitive functions in humans. Here we summarize the available data on low-intensity tES for this purpose, in comparison to repetitive TMS and some pharmacological agents, such as caffeine and nicotine. There is no single area in the brain stimulation field in which only positive outcomes have been reported. For self-directed tES devices, how to restrict variability with regard to efficacy is an essential aspect of device design and function. As with any technique, reproducible outcomes depend on the equipment and how well this is matched to the experience and skill of the operator. For self-administered non-invasive brain stimulation, this requires device designs that rigorously incorporate human operator factors. The wide parameter space of non-invasive brain stimulation, including dose (e.g., duration, intensity (current density), number of repetitions), inclusion/exclusion (e.g., subject's age), and homeostatic effects, administration of tasks before and during stimulation, and, most importantly, placebo or nocebo effects, have to be taken into account. The outcomes of stimulation are expected to depend on these parameters and should be strictly controlled. The consensus among experts is that low-intensity tES is safe as long as tested and accepted protocols (including, for example, dose, inclusion/exclusion) are followed and devices are used which follow established engineering risk-management procedures. Devices and protocols that allow stimulation outside these parameters cannot claim to be "safe" where they are applying stimulation beyond that examined in published studies that also investigated potential side effects. Brain stimulation devices marketed for consumer use are distinct from medical devices because they do not make medical claims and are therefore not necessarily subject to the same level of regulation as medical devices (i.e., by government agencies tasked with regulating medical devices). Manufacturers must follow ethical and best practices in marketing tES stimulators, including not misleading users by referencing effects from human trials using devices and protocols not similar to theirs.

Novel Non-invasive Transcranial Electrical Stimulation for Parkinson's Disease

Conventional transcranial electrical stimulation (tES) is a non-invasive method to modulate brain activity and has been extensively used in the treatment of Parkinson's disease (PD). Despite promising prospects, the efficacy of conventional tES in PD treatment is highly variable across different studies. Therefore, many have tried to optimize tES for an improved therapeutic efficacy by developing novel tES intervention strategies. Until now, these novel clinical interventions have not been discussed or reviewed in the context of PD therapy. In this review, we focused on the efficacy of these novel strategies in PD mitigation, classified them into three categories based on their distinct technical approach to circumvent conventional tES problems. The first category has novel stimulation modes to target different modulating mechanisms, expanding the rang of stimulation choices hence enabling the ability to modulate complex brain circuit or functional networks. The second category applies tES as a supplementary intervention for PD hence amplifies neurological or behavioral improvements. Lastly, the closed loop tES stimulation can provide self-adaptive individualized stimulation, which enables a more specialized intervention. In summary, these novel tES have validated potential in both alleviating PD symptoms and improving understanding of the pathophysiological mechanisms of PD. However, to assure wide clinical used of tES therapy for PD patients, further large-scale trials are required.

Entrainment and Spike-Timing Dependent Plasticity – A Review of Proposed Mechanisms of Transcranial Alternating Current Stimulation

Specific frequency bands of neural oscillations have been correlated with a range of cognitive and behavioral effects (e.g., memory and attention). The causal role of specific frequencies may be investigated using transcranial alternating current stimulation (tACS), a non-invasive brain stimulation method. TACS involves applying a sinusoidal current between two or more electrodes attached on the scalp, above neural regions that are implicated in cognitive processes of interest. The theorized mechanisms by which tACS affects neural oscillations have implications for the exact stimulation frequency used, as well as its anticipated effects. This review outlines two main mechanisms that are thought to underlie tACS effects – entrainment, and spike-timing dependent plasticity (STDP). Entrainment suggests that the stimulated frequency synchronizes the ongoing neural oscillations, and is thought to be most effective when the stimulated frequency is at or close to the endogenous frequency of the targeted neural network. STDP suggests that stimulation leads to synaptic changes based on the timing of neuronal firing in the target neural network. According to the principles of STDP, synaptic strength is thought to increase when pre-synaptic events occur prior to post-synaptic events (referred to as long-term potentiation, LTP). Conversely, when post-synaptic events occur prior to pre-synaptic events, synapses are thought to be weakened (referred to as long-term depression, LTD). In this review, we summarize the theoretical frameworks and critically review the tACS evidence for each hypothesis. We also discuss whether each mechanism alone can account for tACS effects or whether a combined account is necessary.

Local sleep: A new concept in brain plasticity

Traditionally, sleep and wakefulness have been considered as two global, mutually exclusive states. However, this view has been challenged by the discovery that sleep and wakefulness are actually locally regulated and that islands of these two states may often coexist in the same individual. Importantly, such a local regulation seems to be the key for many essential functions of sleep, including the maintenance of cognitive efficiency and the consolidation of new skills and memories. Indeed, local changes in sleep-related oscillations occur in brain areas that are used and involved in learning during wakefulness. In turn, these changes directly modulate experience-dependent brain adaptations and the consolidation of newly acquired memories. In line with these observations, alterations in the regional balance between wake- and sleep-like activity have been shown to accompany many pathologic conditions, including psychiatric and neurologic disorders. In the last decade, experimental research has started to shed light on the mechanisms involved in the local regulation of sleep and wakefulness. The results of this research have opened new avenues of investigation regarding the function of sleep and have revealed novel potential targets for the treatment of several pathologic conditions.

Electric hearing and tinnitus suppression by noninvasive ear stimulation

While noninvasive brain stimulation is convenient and cost effective, its utility is limited by the substantial distance between scalp electrodes and their intended neural targets in the head. The tympanic membrane, or eardrum, is a thin flap of skin deep in an orifice of the head that may serve as a port for improved efficiency of noninvasive stimulation. Here we chose the cochlea as a target because it resides in the densest bone of the skull and is adjacent to many deep-brain-stimulation structures. We also tested the hypothesis that noninvasive electric stimulation of the cochlea may restore neural activities that are missing in acoustic stimulation. We placed an electrode in the ear canal or on the tympanic membrane in 25 human adults (10 females) and compared their stimulation efficiency by characterizing the electrically-evoked auditory sensation. Relative to ear canal stimulation, tympanic membrane stimulation was four times more likely to produce an auditory percept, required eight times lower electric current to reach the threshold and produced two-to-four times more linear suprathreshold responses. We further measured tinnitus suppression in 14 of the 25 subjects who had chronic tinnitus. Compared with ear canal stimulation, tympanic membrane stimulation doubled both the probability (22% vs. 55%) and the amount (-15% vs. -34%) of tinnitus suppression. These findings extended previous work comparing evoked perception and tinnitus suppression between electrodes placed in the ear canal and on the scalp. Together, the previous and present results suggest that the efficiency of conventional scalp-based noninvasive electric stimulation can be improved by at least one order of magnitude via tympanic membrane stimulation. This increased efficiency is most likely due to the shortened distance between the electrode placed on the tympanic membrane and the targeted cochlea. The present findings have implications for the management of tinnitus by offering a potential alternative to interventions using invasive electrical stimulation such as cochlear implantation, or other non-invasive transcranial electrical stimulation methods.

Central nervous system physiology

This is the second chapter of the series on the use of clinical neurophysiology for the study of movement disorders. It focusses on methods that can be used to probe neural circuits in brain and spinal cord. These include use of spinal and supraspinal reflexes to probe the integrity of transmission in specific pathways; transcranial methods of brain stimulation such as transcranial magnetic stimulation and transcranial direct current stimulation, which activate or modulate (respectively) the activity of populations of central neurones; EEG methods, both in conjunction with brain stimulation or with behavioural measures that record the activity of populations of central neurones; and pure behavioural measures that allow us to build conceptual models of motor control. The methods are discussed mainly in relation to work on healthy individuals. Later chapters will focus specifically on changes caused by pathology.

Brain connectivity alterations during sleep by closed-loop transcranial neurostimulation predict metamemory sensitivity

Metamemory involves the ability to correctly judge the accuracy of our memories. The retrieval of memories can be improved using transcranial electrical stimulation (tES) during sleep, but evidence for improvements to metamemory sensitivity is limited. Applying tES can enhance sleep-dependent memory consolidation, which along with metamemory requires the coordination of activity across distributed neural systems, suggesting that examining functional connectivity is important for understanding these processes. Nevertheless, little research has examined how functional connectivity modulations relate to overnight changes in metamemory sensitivity. Here, we developed a closed-loop short-duration tES method, time-locked to up-states of ongoing slow-wave oscillations, to cue specific memory replays in humans. We measured electroencephalographic (EEG) coherence changes following stimulation pulses, and characterized network alterations with graph theoretic metrics. Using machine learning techniques, we show that pulsed tES elicited network changes in multiple frequency bands, including increased connectivity in the theta band and increased efficiency in the spindle band. Additionally, stimulation-induced changes in beta-band path length were predictive of overnight changes in metamemory sensitivity. These findings add new insights into the growing literature investigating increases in memory performance through brain stimulation during sleep, and highlight the importance of examining functional connectivity to explain its effects.

Numerous studies have demonstrated a clear link between sleep and memory—namely, memories are consolidated during sleep, leading to more stable and long-lasting representations. We have previously shown that tagging episodes with specific patterns of brain stimulation during encoding and replaying those patterns during sleep can enhance this consolidation process to improve confidence and decision-making of memories (metamemory). Here, we extend this work to examine network-level brain changes that occur following stimulation during sleep that predict metamemory improvements. Using graph theoretic and machine-learning methods, we found that stimulation-induced changes in beta-band path length predicted overnight improvements in metamemory. This novel finding sheds new light on the neural mechanisms of memory consolidation and suggests potential applications for improving metamemory.

Effects of Transcranial Direct Current Stimulation on Cognitive and Affective Outcomes Using Virtual Stimuli: A Systematic Review

Transcranial direct current stimulation (tDCS) is a noninvasive form of brain stimulation used to influence neural activity. While early tDCS studies primarily used static stimuli, there is growing interest in dynamic stimulus presentations using virtual environments (VEs). This review attempts to convey the state of the field. This is not a quantitative meta-analysis as there are not yet enough studies following consistent protocols and/or reporting adequate data. In addition to reviewing the state of the literature, this review includes an exploratory analysis of the available data. Following preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines, studies were culled from several databases. Results from this review reveal differences between online and offline stimulation. While offline stimulation did not influence affective and cognitive outcomes, online stimulation led to small changes in affect and cognition. Future studies should include randomized controlled trials with larger samples. Furthermore, greater care needs to be applied to full data reporting (e.g., means, standard deviations, and data for their nonsignificant findings) to improve our understanding of the combined effects of virtual stimuli with tDCS.

A System-on-Chip for Closed-loop Optogenetic Sleep Modulation

Stimulation of target neuronal populations using optogenetic techniques during specific sleep stages has begun to elucidate the mechanisms and effects of sleep. To conduct closed-loop optogenetic sleep studies in untethered animals, we designed a fully integrated, low-power system-on-chip (SoC) for real-time sleep stage classification and stage-specific optical stimulation. The SoC consists of a 4-channel analog front-end for recording polysomnography signals, a mixed-signal machine-learning (ML) core, and a 16-channel optical stimulation back-end. A novel ML algorithm and innovative circuit design techniques improved the online classification performance while minimizing power consumption. The SoC was designed and simulated in 180 nm CMOS technology. In an evaluation using an expert labeled sleep database with 20 subjects, the SoC achieves a high sensitivity of 0.806 and a specificity of 0.947 in discriminating 5 sleep stages. Overall power consumption in continuous operation is 97 µW.

Cortical Responses to Vagus Nerve Stimulation Are Modulated by Brain State in Nonhuman Primates

Vagus nerve stimulation (VNS) has been tested as therapy for several brain disorders and as a means to modulate cortical excitability and brain plasticity. Cortical effects of VNS, manifesting as vagal-evoked potentials (VEPs), are thought to arise from activation of ascending cholinergic and noradrenergic systems. However, it is unknown whether those effects are modulated by brain state at the time of stimulation. In 2 freely behaving macaque monkeys, we delivered short trains of 5 pulses to the left cervical vagus nerve at different frequencies (5-300 Hz) while recording local field potentials (LFPs) from sites in contralateral prefrontal, sensorimotor and parietal cortical areas. Brain states were inferred from spectral components of LFPs and the presence of overt movement: active awake, resting awake, REM sleep and NREM sleep. VNS elicited VEPs in all sampled cortical areas. VEPs comprised early (<70 ms), intermediate (70-250 ms) and late (>250 ms) components. The magnitude of the intermediate and late components was largest during NREM sleep and smallest during wakefulness, whereas that of the early component was not modulated by brain state. VEPs during NREM were larger for stimuli delivered at the depolarized phase of ongoing delta oscillations. Higher pulsing frequencies generated larger VEPs. These short VNS trains did not affect brain state transitions during wakefulness or sleep. Our findings suggest that ongoing brain state modulates the evoked effects of VNS on cortical activity. This has implications for the role of ongoing cortical activity and brain state in shaping cortical responses to peripheral stimuli, for the modulation of vagal interoceptive signaling by cortical activity, and for the dose calibration of VNS therapies.

Effects of Slow Oscillatory Transcranial Alternating Current Stimulation on Motor Cortical Excitability Assessed by Transcranial Magnetic Stimulation

Converging evidence suggests that transcranial alternating current stimulation (tACS) may entrain endogenous neural oscillations to match the frequency and phase of the exogenously applied current and this entrainment may outlast the stimulation (although only for a few oscillatory cycles following the cessation of stimulation). However, observing entrainment in the electroencephalograph (EEG) during stimulation is extremely difficult due to the presence of complex tACS artifacts. The present study assessed entrainment to slow oscillatory (SO) tACS by measuring motor cortical excitability across different oscillatory phases during (i.e., online) and outlasting (i.e., offline) stimulation. 30 healthy participants received 60 trials of intermittent SO tACS (0.75 Hz; 16 s on/off interleaved) at an intensity of 2 mA peak-to-peak. Motor cortical excitability was assessed using transcranial magnetic stimulation (TMS) of the hand region of the primary motor cortex (M1_HAND) to induce motor evoked potentials (MEPs) in the contralateral thumb. MEPs were acquired at four time-points within each trial – early online, late online, early offline, and late offline – as well as at the start and end of the overall stimulation period (to probe longer-lasting aftereffects of tACS). A significant increase in MEP amplitude was observed from pre- to post-tACS (paired-sample t-test; t₂₉ = 2.64, P = 0.013, d = 0.48) and from the first to the last tACS block (t₂₉ = −2.93, P = 0.02, d = 0.54). However, no phase-dependent modulation of excitability was observed. Therefore, although SO tACS had a facilitatory effect on motor cortical excitability that outlasted stimulation, there was no evidence supporting entrainment of endogenous oscillations as the underlying mechanism.

Toward Predicting Human Performance Outcomes From Wearable Technologies: A Computational Modeling Approach

Wearable technologies for measuring digital and chemical physiology are pervading the consumer market and hold potential to reliably classify states of relevance to human performance including stress, sleep deprivation, and physical exertion. The ability to efficiently and accurately classify physiological states based on wearable devices is improving. However, the inherent variability of human behavior within and across individuals makes it challenging to predict how identified states influence human performance outcomes of relevance to military operations and other high-stakes domains. We describe a computational modeling approach to address this challenge, seeking to translate user states obtained from a variety of sources including wearable devices into relevant and actionable insights across the cognitive and physical domains. Three status predictors were considered: stress level, sleep status, and extent of physical exertion; these independent variables were used to predict three human performance outcomes: reaction time, executive function, and perceptuo-motor control. The approach provides a complete, conditional probabilistic model of the performance variables given the status predictors. Construction of the model leverages diverse raw data sources to estimate marginal probability density functions for each of six independent and dependent variables of interest using parametric modeling and maximum likelihood estimation. The joint distributions among variables were optimized using an adaptive LASSO approach based on the strength and directionality of conditional relationships (effect sizes) derived from meta-analyses of extant research. The model optimization process converged on solutions that maintain the integrity of the original marginal distributions and the directionality and robustness of conditional relationships. The modeling framework described provides a flexible and extensible solution for human performance prediction, affording efficient expansion with additional independent and dependent variables of interest, ingestion of new raw data, and extension to two- and three-way interactions among independent variables. Continuing work includes model expansion to multiple independent and dependent variables, real-time model stimulation by wearable devices, individualized and small-group prediction, and laboratory and field validation.

Application of Transcranial Direct Current Stimulation in Psychiatry

Transcranial direct current stimulation (tDCS) is a neuromodulation technique, which noninvasively alters cortical excitability via weak polarizing currents between two electrodes placed on the scalp. Since it is comparably easy to handle, cheap to use and relatively well tolerated, tDCS has gained increasing interest in recent years. Based on well-known behavioral effects, a number of clinical studies have been performed in populations including patients with major depressive disorder followed by schizophrenia and substance use disorders, in sum with heterogeneous results with respect to efficacy. Nevertheless, the potential of tDCS must not be underestimated since it could be further improved by systematically investigating the various stimulation parameters to eventually increase clinical efficacy. The present article briefly explains the underlying physiology of tDCS, summarizes typical stimulation protocols and then reviews clinical efficacy for various psychiatric disorders as well as prevalent adverse effects. Future developments include combined and more complex interactions of tDCS with pharmacological or psychotherapeutic interventions. In particular, using computational models to individualize stimulation protocols, considering state dependency and applying closed-loop technologies will pave the way for tDCS-based personalized interventions as well as the development of home treatment settings promoting the role of tDCS as an effective treatment option for patients with mental health problems.

A novel closed-loop EEG-tDCS approach to promote responsiveness of patients in minimally conscious state: A study protocol

Transcranial direct current stimulation (tDCS) applied over the prefrontal cortex has been shown to improve behavioral responsiveness in patients with disorders of consciousness following severe brain injury, especially those in minimally conscious state (MCS). However, one potential barrier of clinical response to tDCS is the timing of stimulation with regard to the fluctuations of vigilance that characterize this population. Indeed, a previous study showed that the vigilance of MCS patients has periodic average cycles of 70 min (range 57-80 min), potentially preventing them to be in an optimal neural state to benefit from tDCS when applied randomly. To tackle this issue, we propose a new protocol to optimize the application of tDCS by selectively stimulating at high and low vigilance states. Electroencephalography (EEG) real-time spectral entropy will be used as a marker of vigilance and to trigger tDCS, in a closed-loop fashion. We will conduct a randomized controlled crossover clinical trial on 16 patients in prolonged MCS who will undergo three EEG-tDCS sessions 5 days apart (1. tDCS applied at high vigilance; 2. tDCS applied at low vigilance; 3. tDCS applied at a random moment). Behavioral effects will be assessed using the Coma Recovery Scale-Revised at baseline and right after the stimulations. EEG will be recorded throughout the session and for 30 min after the end of the stimulation. This unique and novel approach will provide patients' tailored treatment options, currently lacking in the field of disorders of consciousness.

Effects of Transcranial Alternating Current Stimulation and Neurofeedback on Alpha (EEG) Dynamics: A Review

Transcranial alternating current stimulation (tACS) and neurofeedback (NFB) are two different types of non-invasive neuromodulation techniques, which can modulate brain activity and improve brain functioning. In this review, we compared the current state of knowledge related to the mechanisms of tACS and NFB and their effects on electroencephalogram (EEG) activity (online period/stimulation period) and on aftereffects (offline period/post/stimulation period), including the duration of their persistence and potential behavioral benefits. Since alpha bandwidth has been broadly studied in NFB and in tACS research, the studies of NFB and tACS in modulating alpha bandwidth were selected for comparing the online and offline effects of these two neuromodulation techniques. The factors responsible for variability in the responsiveness of the modulated EEG activity by tACS and NFB were analyzed and compared too. Based on the current literature related to tACS and NFB, it can be concluded that tACS and NFB differ a lot in the mechanisms responsible for their effects on an online EEG activity but they possibly share the common universal mechanisms responsible for the induction of aftereffects in the targeted stimulated EEG band, namely Hebbian and homeostatic plasticity. Many studies of both neuromodulation techniques report the aftereffects connected to the behavioral benefits. The duration of persistence of aftereffects for NFB and tACS is comparable. In relation to the factors influencing responsiveness to tACS and NFB, significantly more types of factors were analyzed in the NFB studies compared to the tACS studies. Several common factors for both tACS and NFB have been already investigated. Based on these outcomes, we propose several new research directions regarding tACS and NFB.

The Neurophysiology of Sleep in Parkinson's Disease

Sleep disturbances are among the most common nonmotor complications of Parkinson's disease (PD), can present in prodromal stages, and progress with advancing disease. In addition to being a symptom of neurodegeneration, sleep disturbances may also contribute to disease progression. Currently, limited options exist to modulate sleep disturbances in PD. Studying the neurophysiological changes that affect sleep in PD at the cortical and subcortical level may yield new insights into mechanisms for reversal of sleep disruption. In this article, we review cortical and subcortical recording studies of sleep in PD with a particular focus on dissecting reported electrophysiological changes. These studies show that slow-wave sleep and rapid eye movement sleep are both notably disrupted in PD. We further explore the impact of these electrophysiological changes and discuss the potential for targeting sleep via stimulation therapy to modify PD-related motor and nonmotor symptoms. © 2021 International Parkinson and Movement Disorder Society.

A Comparison of Closed Loop vs. Fixed Frequency tACS on Modulating Brain Oscillations and Visual Detection

Transcranial alternating current stimulation has emerged as an effective tool for the exploration of brain oscillations. By applying a weak alternating current between electrodes placed on the scalp matched to the endogenous frequency, tACS enables the specific modulation of targeted brain oscillations This results in alterations in cognitive functions or persistent physiological changes. Most studies that utilize tACS determine a fixed stimulation frequency prior to the stimulation that is kept constant throughout the experiment. Yet it is known that brain rhythms can encounter shifts in their endogenous frequency. This could potentially move the ongoing brain oscillations into a frequency region where it is no longer affected by the stimulation, thereby decreasing or negating the effect of tACS. Such an effect of a mismatch between stimulation frequency and endogenous frequency on the outcome of stimulation has been shown before for the parietal alpha-activity. In this study, we employed an intermittent closed loop stimulation protocol, where the stimulation is divided into short epochs, between which an EEG is recorded and rapidly analyzed to determine a new stimulation frequency for the next stimulation epoch. This stimulation protocol was tested in a three-group study against a classical fixed stimulation protocol and a sham-treatment. We targeted the parietal alpha rhythm and hypothesized that this setup will ensure a constant close match between the frequencies of tACS and alpha activity. This closer match should lead to an increased modulation of detection of visual luminance changes depending on the phase of the tACS and an increased rise in alpha peak power post stimulation when compared to a protocol with fixed pre-determined stimulation frequency. Contrary to our hypothesis, our results show that only a fixed stimulation protocol leads to a persistent increase in post-stimulation alpha power as compared to sham. Furthermore, in none of the stimulated groups significant modulation of detection performance occurred. While the lack of behavioral effects is inconclusive due to the short selection of different phase bins and trials, the physiological results suggest that a constant stimulation with a fixed frequency is actually beneficial, when the goal is to produce persistent synaptic changes.

Human Body Rhythms in the Development of Non-Invasive Methods of Closed-Loop Adaptive Neurostimulation

The creation and improvement of non-invasive closed-loop brain stimulation technologies represent an exciting and rapidly expanding field of neuroscience. To identify the appropriate way to close the feedback loop in adaptive neurostimulation procedures, it was previously proposed to use on-line automatic sensory stimulation with the parameters modulated by the patient's own rhythmical processes, such as respiratory rate, heart rate, and electroencephalogram (EEG) rhythms. The current paper aims to analyze several recent studies demonstrating further development in this line of research. The advantages of using automatic closed-loop feedback from human endogenous rhythms in non-invasive adaptive neurostimulation procedures have been demonstrated for relaxation assistance, for the correction of stress-induced functional disturbances, for anxiety management, and for the cognitive rehabilitation of an individual. Several distinctive features of the approach are noted to delineate its further development.