From oscillatory transcranial current stimulation to scalp EEG changes: a biophysical and physiological modeling study

Modulation of Visually Induced Self-motion Illusions by α Transcranial Electric Stimulation over the Superior Parietal Cortex

The growing popularity of virtual reality systems has led to a renewed interest in understanding the neurophysiological correlates of the illusion of self-motion (vection), a phenomenon that can be both intentionally induced or avoided in such systems, depending on the application. Recent research has highlighted the modulation of α power oscillations over the superior parietal cortex during vection, suggesting the occurrence of inhibitory mechanisms in the sensorimotor and vestibular functional networks to resolve the inherent visuo-vestibular conflict. The present study aims to further explore this relationship and investigate whether neuromodulating these waves could causally affect the quality of vection. In a crossover design, 22 healthy volunteers received high amplitude and focused α-tACS (transcranial alternating current stimulation) over the superior parietal cortex while experiencing visually induced vection triggered by optokinetic stimulation. The tACS was tuned to each participant's individual α peak frequency, with θ-tACS and sham stimulation serving as controls. Overall, participants experienced better quality vection during α-tACS compared with control θ-tACS and sham stimulations, as quantified by the intensity of vection. The observed neuromodulation supports a causal relationship between parietal α oscillations and visually induced self-motion illusions, with their entrainment triggering overinhibition of the conflict within the sensorimotor and vestibular functional networks. These results confirm the potential of noninvasive brain stimulation for modulating visuo-vestibular conflicts, which could help to enhance the sense of presence in virtual reality environments.

Efficacy of transcranial alternating current stimulation for schizophrenia treatment: A systematic review

BACKGROUND

Transcranial alternating current stimulation (tACS) is an innovative noninvasive technique in brain stimulation that involves applying a low-intensity electrical current to the scalp. And increasing evidence has revealed its potential in schizophrenia treatment.

OBJECTIVE

This systematic review aimed to evaluate the efficacy of tACS as a novel neurostimulation technique for improving cognitive impairment and alleviating psychotic symptoms in schizophrenia. Additionally, this review attempted to explore the impact of stimulation parameters on the effectiveness of tACS treatment.

METHODS

A systematic literature search was conducted across five databases, including Web of Science, Embase, PubMed, CENTRAL, and PsycINFO, to identify studies investigating the use of tACS in schizophrenia. Only studies that involved the experimental use of tACS in patients with schizophrenia were included in this review.

RESULTS

Nineteen studies were included in this review. The most frequently used current intensities were 2 mA and 1 mA, and the most commonly used frequencies were alpha (10 Hz), theta (4.5 Hz and 6 Hz), and gamma (40 Hz). Some studies showed that tACS may have a potential therapeutic effect by improving cognitive functions in various cognitive domains and/or ameliorating negative symptoms, hallucinations, and delusions in patients with schizophrenia, while others showed no significant change. These studies also implicated that tACS treatment is safe and well tolerated.

CONCLUSIONS

Overall, this systematic review suggests that tACS has promise as a novel, effective, and adjunctive treatment approach for treating schizophrenia. Future research is needed to determine the optimal parameters of tACS for treating this complex disorder.

Understanding the effects of cortical gyrification in tACS: insights from experiments and computational models

The alpha rhythm is often associated with relaxed wakefulness or idling and is altered by various factors. Abnormalities in the alpha rhythm have been linked to several neurological and psychiatric disorders, including Alzheimer's disease. Transcranial alternating current stimulation (tACS) has been proposed as a potential tool to restore a disrupted alpha rhythm in the brain by stimulating at the individual alpha frequency (IAF), although some research has produced contradictory results. In this study, we applied an IAF-tACS protocol over parieto-occipital areas to a sample of healthy subjects and measured its effects over the power spectra. Additionally, we used computational models to get a deeper understanding of the results observed in the experiment. Both experimental and numerical results showed an increase in alpha power of 8.02% with respect to the sham condition in a widespread set of regions in the cortex, excluding some expected parietal regions. This result could be partially explained by taking into account the orientation of the electric field with respect to the columnar structures of the cortex, showing that the gyrification in parietal regions could generate effects in opposite directions (hyper-/depolarization) at the same time in specific brain regions. Additionally, we used a network model of spiking neuronal populations to explore the effects that these opposite polarities could have on neural activity, and we found that the best predictor of alpha power was the average of the normal components of the electric field. To sum up, our study sheds light on the mechanisms underlying tACS brain activity modulation, using both empirical and computational approaches. Non-invasive brain stimulation techniques hold promise for treating brain disorders, but further research is needed to fully understand and control their effects on brain dynamics and cognition. Our findings contribute to this growing body of research and provide a foundation for future studies aimed at optimizing the use of non-invasive brain stimulation in clinical settings.

Global excitability and network structure in the human brain

We utilize a model of Wilson-Cowan oscillators to investigate structure-function relationships in the human brain by means of simulations of the spontaneous dynamics of brain networks generated through human connectome data. This allows us to establish relationships between the global excitability of such networks and global structural network quantities for connectomes of two different sizes for a number of individual subjects. We compare the qualitative behavior of such correlations between biological networks and shuffled networks, the latter generated by shuffling the pairwise connectivities of the former while preserving their distribution. Our results point towards a remarkable propensity of the brain to achieve a trade-off between low network wiring cost and strong functionality, and highlight the unique capacity of brain network topologies to exhibit a strong transition from an inactive state to a globally excited one.

A physical neural mass model framework for the analysis of oscillatory generators from laminar electrophysiological recordings

Cortical function emerges from the interactions of multi-scale networks that may be studied at a high level using neural mass models (NMM) that represent the mean activity of large numbers of neurons. Here, we provide first a new framework called laminar NMM, or LaNMM for short, where we combine conduction physics with NMMs to simulate electrophysiological measurements. Then, we employ this framework to infer the location of oscillatory generators from laminar-resolved data collected from the prefrontal cortex in the macaque monkey. We define a minimal model capable of generating coupled slow and fast oscillations, and we optimize LaNMM-specific parameters to fit multi-contact recordings. We rank the candidate models using an optimization function that evaluates the match between the functional connectivity (FC) of the model and data, where FC is defined by the covariance between bipolar voltage measurements at different cortical depths. The family of best solutions reproduces the FC of the observed electrophysiology by selecting locations of pyramidal cells and their synapses that result in the generation of fast activity at superficial layers and slow activity across most depths, in line with recent literature proposals. In closing, we discuss how this hybrid modeling framework can be more generally used to infer cortical circuitry.

Comparison between an exact and a heuristic neural mass model with second-order synapses

Neural mass models (NMMs) are designed to reproduce the collective dynamics of neuronal populations. A common framework for NMMs assumes heuristically that the output firing rate of a neural population can be described by a static nonlinear transfer function (NMM1). However, a recent exact mean-field theory for quadratic integrate-and-fire (QIF) neurons challenges this view by showing that the mean firing rate is not a static function of the neuronal state but follows two coupled nonlinear differential equations (NMM2). Here we analyze and compare these two descriptions in the presence of second-order synaptic dynamics. First, we derive the mathematical equivalence between the two models in the infinitely slow synapse limit, i.e., we show that NMM1 is an approximation of NMM2 in this regime. Next, we evaluate the applicability of this limit in the context of realistic physiological parameter values by analyzing the dynamics of models with inhibitory or excitatory synapses. We show that NMM1 fails to reproduce important dynamical features of the exact model, such as the self-sustained oscillations of an inhibitory interneuron QIF network. Furthermore, in the exact model but not in the limit one, stimulation of a pyramidal cell population induces resonant oscillatory activity whose peak frequency and amplitude increase with the self-coupling gain and the external excitatory input. This may play a role in the enhanced response of densely connected networks to weak uniform inputs, such as the electric fields produced by noninvasive brain stimulation.

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.

Towards a mesoscale physical modeling framework for stereotactic-EEG recordings

Objective.Stereotactic-electroencephalography (SEEG) and scalp EEG recordings can be modeled using mesoscale neural mass population models (NMMs). However, the relationship between those mathematical models and the physics of the measurements is unclear. In addition, it is challenging to represent SEEG data by combining NMMs and volume conductor models due to the intermediate spatial scale represented by these measurements.Approach.We provide a framework combining the multi-compartmental modeling formalism and a detailed geometrical model to simulate the transmembrane currents that appear in layer 3, 5 and 6 pyramidal cells due to a synaptic input. With this approach, it is possible to realistically simulate the current source density (CSD) depth profile inside a cortical patch due to inputs localized into a single cortical layer and the induced voltage measured by two SEEG contacts using a volume conductor model. Based on this approach, we built a framework to connect the activity of a NMM with a volume conductor model and we simulated an example of SEEG signal as a proof of concept.Main results.CSD depends strongly on the distribution of the synaptic inputs onto the different cortical layers and the equivalent current dipole strengths display substantial differences (of up to a factor of four in magnitude in our example). Thus, the inputs coming from different neural populations do not contribute equally to the electrophysiological recordings. A direct consequence of this is that the raw output of NMMs is not a good proxy for electrical recordings. We also show that the simplest CSD model that can accurately reproduce SEEG measurements can be constructed from discrete monopolar sources (one per cortical layer).Significance.Our results highlight the importance of including a physical model in NMMs to represent measurements. We provide a framework connecting microscale neuron models with the neural mass formalism and with physical models of the measurement process that can improve the accuracy of predicted electrophysiological recordings.

Effectiveness of Anodal otDCS Following with Anodal tDCS Rather than tDCS Alone for Increasing of Relative Power of Intrinsic Matched EEG Bands in Rat Brains

BACKGROUND

This study sought to determine whether (1) evidence is available of interactions between anodal tDCS and oscillated tDCS stimulation patterns to increase the power of endogenous brain oscillations and (2) the frequency matching the applied anodal otDCS's frequency and the brain's dominant intrinsic frequency influence power shifting during stimulation pattern sessions by both anodal DCS and anodal oscillated DCS.

METHOD

Rats received different anodal tDCS and otDCS stimulation patterns using 8.5 Hz and 13 Hz state-related dominant intrinsic frequencies of anodal otDCS. The rats were divided into groups with specific stimulation patterns: group A: tDCS-otDCS (8.5 Hz)-otDCS (13 Hz); group B: otDCS (8.5 Hz)-tDCS-otDCS (13 Hz); group C: otDCS (13 Hz)-tDCS-otDCS (8.5 Hz). Acute relative power changes (i.e., following 10 min stimulation sessions) in six frequency bands-delta (1.5-4 Hz), theta (4-7 Hz), alpha-1 (7-10 Hz), alpha-2 (10-12 Hz), beta-1 (12-15 Hz) and beta-2 (15-20 Hz)-were compared using three factors and repeated ANOVA measurement.

RESULTS

For each stimulation, tDCS increased theta power band and, above bands alpha and beta, a drop in delta power was observed. Anodal otDCS had a mild increasing power effect in both matched intrinsic and delta bands. In group pattern stimulations, increased power of endogenous frequencies matched exogenous otDCS frequencies-8.5 Hz or 13 Hz-with more potent effects in upper bands. The power was markedly more potent with the otDCS-tDCS stimulation pattern than the tDCS-otDCS pattern.

SIGNIFICANCE

The findings suggest that the otDCS-tDCS pattern stimulation increased the power in matched intrinsic oscillations and, significantly, in the above bands in an ascending order. We provide evidence for the successful corporation between otDCS (as frequency-matched guidance) and tDCS (as a power generator) rather than tDCS alone when stimulating a desired brain intrinsic band (herein, tES specificity).

Alpha transcranial alternating current stimulation reduces depressive symptoms in people with schizophrenia and auditory hallucinations: a double-blind, randomized pilot clinical trial

People with schizophrenia exhibit reduced alpha oscillations and frontotemporal coordination of brain activity. Alpha oscillations are associated with top-down inhibition. Reduced alpha oscillations may fail to censor spurious endogenous activity, leading to auditory hallucinations. Transcranial alternating current stimulation (tACS) at the alpha frequency was shown to enhance alpha oscillations in people with schizophrenia and may thus be a network-based treatment for auditory hallucinations. We conducted a double-blind, randomized, placebo-controlled pilot clinical trial to examine the efficacy of 10-Hz tACS in treating auditory hallucinations in people with schizophrenia. 10-Hz tACS was administered in phase at the dorsolateral prefrontal cortex and the temporoparietal junction with a return current at Cz. Patients were randomized to receive tACS or sham for five consecutive days during the treatment week (40 min/day), followed by a maintenance period, during which participants received weekly tACS (40 min/visit) or sham. tACS treatment reduced general psychopathology (p < 0.05, Cohen's d = -0.690), especially depression (p < 0.005, Cohen's d = -0.806), but not auditory hallucinations. tACS treatment increased alpha power in the target region (p < 0.05), increased the frequency of peak global functional connectivity towards 10 Hz (p < 0.05), and reduced left-right frontal functional connectivity (p < 0.005). Importantly, changes in brain functional connectivity significantly correlated with symptom improvement (p < 0.05). Daily 10 Hz-tACS increased alpha power and altered alpha-band functional connectivity. Successful target engagement reduced depression and other general psychopathology symptoms, but not auditory hallucinations. Considering existing research of 10Hz tACS as a treatment for major depressive disorder, our study demonstrates its transdiagnostic potential for treating depression.

A personalizable autonomous neural mass model of epileptic seizures

Work in the last two decades has shown that neural mass models (NMM) can realistically reproduce and explain epileptic seizure transitions as recorded by electrophysiological methods (EEG, SEEG). In previous work, advances were achieved by increasing excitation and heuristically varying network inhibitory coupling parameters in the models. Based on these early studies, we provide a laminar NMM capable of realistically reproducing the electrical activity recorded by SEEG in the epileptogenic zone during interictal to ictal states. With the exception of the external noise input into the pyramidal cell population, the model dynamics are autonomous. By setting the system at a point close to bifurcation, seizure-like transitions are generated, including pre-ictal spikes, low voltage fast activity, and ictal rhythmic activity. A novel element in the model is a physiologically motivated algorithm for chloride dynamics: the gain of GABAergic post-synaptic potentials is modulated by the pathological accumulation of chloride in pyramidal cells due to high inhibitory input and/or dysfunctional chloride transport. In addition, in order to simulate SEEG signals for comparison with real seizure recordings, the NMM is embedded first in a layered model of the neocortex and then in a realistic physical model. We compare modeling results with data from four epilepsy patient cases. By including key pathophysiological mechanisms, the proposed framework captures succinctly the electrophysiological phenomenology observed in ictal states, paving the way for robust personalization methods based on NMMs.

tACS facilitates flickering driving by boosting steady-state visual evoked potentials

Objective.There has become of increasing interest in transcranial alternating current stimulation (tACS) since its inception nearly a decade ago. tACS in modulating brain state is an active area of research and has been demonstrated effective in various neuropsychological and clinical domains. In the visual domain, much effort has been dedicated to brain rhythms and rhythmic stimulation, i.e. tACS. However, less is known about the interplay between the rhythmic stimulation and visual stimulation.Approach.Here, we used steady-state visual evoked potential (SSVEP), induced by flickering driving as a widely used technique for frequency-tagging, to investigate the aftereffect of tACS in healthy human subjects. Seven blocks of 64-channel electroencephalogram were recorded before and after the administration of 20min 10Hz tACS, while subjects performed several blocks of SSVEP tasks. We characterized the physiological properties of tACS aftereffect by comparing and validating the temporal, spatial, spatiotemporal and signal-to-noise ratio (SNR) patterns between and within blocks in real tACS and sham tACS.Main results.Our result revealed that tACS boosted the 10Hz SSVEP significantly. Besides, the aftereffect on SSVEP was mitigated with time and lasted up to 5 min.Significance.Our results demonstrate the feasibility of facilitating the flickering driving by external rhythmic stimulation and open a new possibility to alter the brain state in a direction by noninvasive transcranial brain stimulation.

Glial cells have more important role in tDCS-induced brain activities rather than neurons

Transcranial Direct Current Stimulation (tDCS) is a non-invasive and sub-threshold method for altering the excitability of neurons to achieve target conditions. Many clinical applications of tDCS are in progress including treatment of neurological disease. Despite the therapeutic and practical potentials of tDCS, the precise mechanism of its impact is still unclear to a large extent. The initial perspective about the effect of tDCS on synaptic plasticity was that electric stimulation of the brain degrades the threshold of neural firing, thus facilitating electrical transmission and improving conductivity between neurons and ultimately leading to changes in the processing of information. However, new results of some experimental studies have changed the initial perspective. Recently, calcium imaging has shown sudden calcium fluctuations, followed by a change in cortical metaplasticity under tDCS. These pieces of evidence pinpoint the important role of astrocytes in describing the effect of tDCS. Astrocytes are glial cells that are traditionally viewed with only a supportive and nutritional role, but recent research expresses that they are active and contribute to processing and regulating synaptic information. We hypothesize that considering astrocytes as an important player in tDCS effect instead of the direct effect on voltage membrane of neurons is closer to the reality of tDCS effect mechanism. This hypothesis is examined here based on the experimental evidence published so far, which indicates astroglia involvement in tDCS-induced activities and results of our proposed computational model.

Patient-Tailored, Home-Based Non-invasive Brain Stimulation for Memory Deficits in Dementia Due to Alzheimer's Disease

Alzheimer's disease (AD) is an irreversible, progressive brain disorder that can cause dementia (Alzheimer's disease-related dementia, ADRD) with growing cognitive disability and vast physical, emotional, and financial pressures not only on the patients but also on caregivers and families. Loss of memory is an early and very debilitating symptom in AD patients and a relevant predictor of disease progression. Data from rodents, as well as human studies, suggest that dysregulation of specific brain oscillations, particularly in the hippocampus, is linked to memory deficits. Animal and human studies demonstrate that non-invasive brain stimulation (NIBS) in the form of transcranial alternating current stimulation (tACS) allows to reliably and safely interact with ongoing oscillatory patterns in the brain in specific frequencies. We developed a protocol for patient-tailored home-based tACS with an instruction program to train a caregiver to deliver daily sessions of tACS that can be remotely monitored by the study team. We provide a discussion of the neurobiological rationale to modulate oscillations and a description of the study protocol. Data of two patients with ADRD who have completed this protocol illustrate the feasibility of the approach and provide pilot evidence on the safety of the remotely-monitored, caregiver-administered, home-based tACS intervention. These findings encourage the pursuit of a large, adequately powered, randomized controlled trial of home-based tACS for memory dysfunction in ADRD.

Selective enhancement of low-gamma activity by tACS improves phonemic processing and reading accuracy in dyslexia

The phonological deficit in dyslexia is associated with altered low-gamma oscillatory function in left auditory cortex, but a causal relationship between oscillatory function and phonemic processing has never been established. After confirming a deficit at 30 Hz with electroencephalography (EEG), we applied 20 minutes of transcranial alternating current stimulation (tACS) to transiently restore this activity in adults with dyslexia. The intervention significantly improved phonological processing and reading accuracy as measured immediately after tACS. The effect occurred selectively for a 30-Hz stimulation in the dyslexia group. Importantly, we observed that the focal intervention over the left auditory cortex also decreased 30-Hz activity in the right superior temporal cortex, resulting in reinstating a left dominance for the oscillatory response. These findings establish a causal role of neural oscillations in phonological processing and offer solid neurophysiological grounds for a potential correction of low-gamma anomalies and for alleviating the phonological deficit in dyslexia.

Realistic modeling of mesoscopic ephaptic coupling in the human brain

Several decades of research suggest that weak electric fields may influence neural processing, including those induced by neuronal activity and proposed as a substrate for a potential new cellular communication system, i.e., ephaptic transmission. Here we aim to model mesoscopic ephaptic activity in the human brain and explore its trajectory during aging by characterizing the electric field generated by cortical dipoles using realistic finite element modeling. Extrapolating from electrophysiological measurements, we first observe that modeled endogenous field magnitudes are comparable to those in measurements of weak but functionally relevant self-generated fields and to those produced by noninvasive transcranial brain stimulation, and therefore possibly able to modulate neuronal activity. Then, to evaluate the role of these fields in the human cortex in large MRI databases, we adapt an interaction approximation that considers the relative orientation of neuron and field to estimate the membrane potential perturbation in pyramidal cells. We use this approximation to define a simplified metric (EMOD1) that weights dipole coupling as a function of distance and relative orientation between emitter and receiver and evaluate it in a sample of 401 realistic human brain models from healthy subjects aged 16-83. Results reveal that ephaptic coupling, in the simplified mesoscopic modeling approach used here, significantly decreases with age, with higher involvement of sensorimotor regions and medial brain structures. This study suggests that by providing the means for fast and direct interaction between neurons, ephaptic modulation may contribute to the complexity of human function for cognition and behavior, and its modification across the lifespan and in response to pathology.

Linking Molecular Pathways and Large-Scale Computational Modeling to Assess Candidate Disease Mechanisms and Pharmacodynamics in Alzheimer's Disease

Introduction: While the prevalence of neurodegenerative diseases associated with dementia such as Alzheimer's disease (AD) increases, our knowledge on the underlying mechanisms, outcome predictors, or therapeutic targets is limited. In this work, we demonstrate how computational multi-scale brain modeling links phenomena of different scales and therefore identifies potential disease mechanisms leading the way to improved diagnostics and treatment. Methods: The Virtual Brain (TVB; thevirtualbrain.org) neuroinformatics platform allows standardized large-scale structural connectivity-based simulations of whole brain dynamics. We provide proof of concept for a novel approach that quantitatively links the effects of altered molecular pathways onto neuronal population dynamics. As a novelty, we connect chemical compounds measured with positron emission tomography (PET) with neural function in TVB addressing the phenomenon of hyperexcitability in AD related to the protein amyloid beta (Abeta). We construct personalized virtual brains based on an averaged healthy connectome and individual PET derived distributions of Abeta in patients with mild cognitive impairment (MCI, N = 8) and Alzheimer's Disease (AD, N = 10) and in age-matched healthy controls (HC, N = 15) using data from ADNI-3 data base (http://adni.loni.usc.edu). In the personalized virtual brains, individual Abeta burden modulates regional Excitation-Inhibition balance, leading to local hyperexcitation with high Abeta loads. We analyze simulated regional neural activity and electroencephalograms (EEG). Results: Known empirical alterations of EEG in patients with AD compared to HCs were reproduced by simulations. The virtual AD group showed slower frequencies in simulated local field potentials and EEG compared to MCI and HC groups. The heterogeneity of the Abeta load is crucial for the virtual EEG slowing which is absent for control models with homogeneous Abeta distributions. Slowing phenomena primarily affect the network hubs, independent of the spatial distribution of Abeta. Modeling the N-methyl-D-aspartate (NMDA) receptor antagonism of memantine in local population models, reveals potential functional reversibility of the observed large-scale alterations (reflected by EEG slowing) in virtual AD brains. Discussion: We demonstrate how TVB enables the simulation of systems effects caused by pathogenetic molecular candidate mechanisms in human virtual brains.

Dose-Dependent Effects of Closed-Loop tACS Delivered During Slow-Wave Oscillations on Memory Consolidation

Sleep is critically important to consolidate information learned throughout the day. Slow-wave sleep (SWS) serves to consolidate declarative memories, a process previously modulated with open-loop non-invasive electrical stimulation, though not always effectively. These failures to replicate could be explained by the fact that stimulation has only been performed in open-loop, as opposed to closed-loop where phase and frequency of the endogenous slow-wave oscillations (SWOs) are matched for optimal timing. The current study investigated the effects of closed-loop transcranial Alternating Current Stimulation (tACS) targeting SWOs during sleep on memory consolidation. 21 participants took part in a three-night, counterbalanced, randomized, single-blind, within-subjects study, investigating performance changes (correct rate and F1 score) on images in a target detection task over 24 h. During sleep, 1.5 mA closed-loop tACS was delivered in phase over electrodes at F3 and F4 and 180° out of phase over electrodes at bilateral mastoids at the frequency (range 0.5-1.2 Hz) and phase of ongoing SWOs for a duration of 5 cycles in each discrete event throughout the night. Data were analyzed in a repeated measures ANOVA framework, and results show that verum stimulation improved post-sleep performance specifically on generalized versions of images used in training at both morning and afternoon tests compared to sham, suggesting the facilitation of schematization of information, but not of rote, veridical recall. We also found a surprising inverted U-shaped dose effect of sleep tACS, which is interpreted in terms of tACS-induced faciliatory and subsequent refractory dynamics of SWO power in scalp EEG. This is the first study showing a selective modulation of long-term memory generalization using a novel closed-loop tACS approach, which holds great potential for both healthy and neuropsychiatric populations.

Patterns of brain oscillations across different electrode montages in transcranial pulsed current stimulation

Transcranial pulsed current stimulation (tPCS) is a neuromodulatory technique that has been studied in the last decade. Several parameters have been assessed independently to optimize the effects. Our aim was to explore the effects of tPCS using different montages on cortical brain oscillations indexed by power spectrum and interhemispheric coherence in different electroencephalography frequency bands. Twenty healthy individuals were randomized to receive either active tPCS or sham intervention using the following bilateral montages: ear clip (conventional), ear hook, or mastoid placement. Electroencephalography was recorded before and after the electroencephalography intervention to assess tPCS-induced after effects. Our results showed that active tPCS with bimastoid montage increased significantly alpha absolute power (P=0.0166) and low alpha (P=0.0014) in the frontal region, as well as in the low alpha power spectrum in the central (P=0.0001) and parieto-occipital regions (P=0.0068) compared with the other montages. For interhemispheric coherence analysis, the Kruskal-Wallis test showed a significant main effect of group for theta (P=0.0012) in the frontal region, mainly for ear-clip montage. Our findings evidenced that tPCS delivered through different electrode montages exert different effects on cortical brain oscillations and thus have a different neural signature. We discuss the implications of these findings as well as potential clinical explorations of this technique.

A model of individualized canonical microcircuits supporting cognitive operations

Major cognitive functions such as language, memory, and decision-making are thought to rely on distributed networks of a large number of basic elements, called canonical microcircuits. In this theoretical study we propose a novel canonical microcircuit model and find that it supports two basic computational operations: a gating mechanism and working memory. By means of bifurcation analysis we systematically investigate the dynamical behavior of the canonical microcircuit with respect to parameters that govern the local network balance, that is, the relationship between excitation and inhibition, and key intrinsic feedback architectures of canonical microcircuits. We relate the local behavior of the canonical microcircuit to cognitive processing and demonstrate how a network of interacting canonical microcircuits enables the establishment of spatiotemporal sequences in the context of syntax parsing during sentence comprehension. This study provides a framework for using individualized canonical microcircuits for the construction of biologically realistic networks supporting cognitive operations.

Low frequency transcranial electrical stimulation does not entrain sleep rhythms measured by human intracranial recordings

Transcranial electrical stimulation has widespread clinical and research applications, yet its effect on ongoing neural activity in humans is not well established. Previous reports argue that transcranial alternating current stimulation (tACS) can entrain and enhance neural rhythms related to memory, but the evidence from non-invasive recordings has remained inconclusive. Here, we measure endogenous spindle and theta activity intracranially in humans during low-frequency tACS and find no stable entrainment of spindle power during non-REM sleep, nor of theta power during resting wakefulness. As positive controls, we find robust entrainment of spindle activity to endogenous slow-wave activity in 66% of electrodes as well as entrainment to rhythmic noise-burst acoustic stimulation in 14% of electrodes. We conclude that low-frequency tACS at common stimulation intensities neither acutely modulates spindle activity during sleep nor theta activity during waking rest, likely because of the attenuated electrical fields reaching the cortical surface.

Modulation of Somatosensory Alpha Rhythm by Transcranial Alternating Current Stimulation at Mu-Frequency

Introduction: Transcranial alternating current stimulation (tACS) is emerging as an interventional tool to modulate different functions of the brain, potentially by interacting with intrinsic ongoing neuronal oscillations. Functionally different intrinsic alpha oscillations are found throughout the cortex. Yet it remains unclear whether tACS is capable of specifically modulating the somatosensory mu-rhythm in amplitude. Objectives: We used tACS to modulate mu-alpha oscillations in amplitude. When compared to sham stimulation we expected a modulation of mu-alpha oscillations but not visual alpha oscillations by tACS. Methods: Individual mu-alpha frequencies were determined in 25 participants. Subsequently, blocks of tACS with individual mu-alpha frequency and sham stimulation were applied over primary somatosensory cortex (SI). Electroencephalogram (EEG) was recorded before and after either stimulation or sham. Modulations of mu-alpha and, for control, visual alpha amplitudes were then compared between tACS and sham. Results: Somatosensory mu-alpha oscillations decreased in amplitude after tACS was applied at participants' individual mu-alpha frequency. No changes in amplitude were observed for sham stimulation. Furthermore, visual alpha oscillations were not affected by tACS or sham, respectively. Conclusion: Our results demonstrate the capability of tACS to specifically modulate the targeted somatosensory mu-rhythm when the tACS frequency is tuned to the individual endogenous rhythm and applied over somatosensory areas. Our results are in contrast to previously reported amplitude increases of visual alpha oscillations induced by tACS applied over visual cortex. Our results may point to a specific interaction between our stimulation protocol and the functional architecture of the somatosensory system.

Enhancement of multitasking performance and neural oscillations by transcranial alternating current stimulation

Multitasking is associated with the generation of stimulus-locked theta (4–7 Hz) oscillations arising from prefrontal cortex (PFC). Transcranial alternating current stimulation (tACS) is a non-invasive brain stimulation technique that influences endogenous brain oscillations. Here, we investigate whether applying alternating current stimulation within the theta frequency band would affect multitasking performance, and explore tACS effects on neurophysiological measures. Brief runs of bilateral PFC theta-tACS were applied while participants were engaged in a multitasking paradigm accompanied by electroencephalography (EEG) data collection. Unlike an active control group, a tACS stimulation group showed enhancement of multitasking performance after a 90-minute session (F_1,35 = 6.63, p = 0.01, ηp² = 0.16; effect size = 0.96), coupled with significant modulation of posterior beta (13–30 Hz) activities (F_1,32 = 7.66, p = 0.009, ηp² = 0.19; effect size = 0.96). Across participant regression analyses indicated that those participants with greater increases in frontal theta, alpha and beta oscillations exhibited greater multitasking performance improvements. These results indicate frontal theta-tACS generates benefits on multitasking performance accompanied by widespread neuronal oscillatory changes, and suggests that future tACS studies with extended treatments are worth exploring as promising tools for cognitive enhancement.

Transcranial Electric Stimulation for Precision Medicine: A Spatiomechanistic Framework

During recent years, non-invasive brain stimulation, including transcranial electrical stimulation (tES) in general, and transcranial direct current stimulation (tDCS) in particular, have created new hopes for treatment of neurological and psychiatric diseases. Despite promising primary results in some brain disorders, a more widespread application of tES is hindered by the unsolved question of determining optimum stimulation protocols to receive meaningful therapeutic effects. tES has a large parameter space including various montages and stimulation parameters. Moreover, inter- and intra-individual differences in responding to stimulation protocols have to be taken into account. These factors contribute to the complexity of selecting potentially effective protocols for each disorder, different clusters of each disorder, and even each single patient. Expanding knowledge in different dimensions of basic and clinical neuroscience could help researchers and clinicians to select potentially effective protocols based on tES modulatory mechanisms for future clinical studies. In this article, we propose a heuristic spatiomechanistic framework which contains nine levels to address tES effects on brain functions. Three levels refer to the spatial resolution (local, small-scale networks and large-scale networks) and three levels of tES modulatory effects based on its mechanisms of action (neurochemical, neuroelectrical and oscillatory modulations). At the group level, this framework could be helpful to enable an informed and systematic exploration of various possible protocols for targeting a brain disorder or its neuroscience-based clusters. Considering recent advances in exploration of neurodiversity at the individual level with different brain mapping technologies, the proposed framework might also be used in combination with personal data to design individualized protocols for tES in the context of precision medicine in the future.

Phase Dependency of the Human Primary Motor Cortex and Cholinergic Inhibition Cancelation During Beta tACS

The human motor cortex has a tendency to resonant activity at about 20 Hz so stimulation should more readily entrain neuronal populations at this frequency. We investigated whether and how different interneuronal circuits contribute to such resonance by using transcranial magnetic stimulation (TMS) during transcranial alternating current stimulation (tACS) at motor (20 Hz) and a nonmotor resonance frequency (7 Hz). We tested different TMS interneuronal protocols and triggered TMS pulses at different tACS phases. The effect of cholinergic short-latency afferent inhibition (SAI) was abolished by 20 Hz tACS, linking cortical beta activity to sensorimotor integration. However, this effect occurred regardless of the tACS phase. In contrast, 20 Hz tACS selectively modulated MEP size according to the phase of tACS during single pulse, GABAAergic short-interval intracortical inhibition (SICI) and glutamatergic intracortical facilitation (ICF). For SICI this phase effect was more marked during 20 Hz stimulation. Phase modulation of SICI also depended on whether or not spontaneous beta activity occurred at ~20 Hz, supporting an interaction effect between tACS and underlying circuit resonances. The present study provides in vivo evidence linking cortical beta activity to sensorimotor integration, and for beta oscillations in motor cortex being promoted by resonance in GABAAergic interneuronal circuits.

Alternating Current Stimulation for Vision Restoration after Optic Nerve Damage: A Randomized Clinical Trial

BACKGROUND

Vision loss after optic neuropathy is considered irreversible. Here, repetitive transorbital alternating current stimulation (rtACS) was applied in partially blind patients with the goal of activating their residual vision.

METHODS

We conducted a multicenter, prospective, randomized, double-blind, sham-controlled trial in an ambulatory setting with daily application of rtACS (n = 45) or sham-stimulation (n = 37) for 50 min for a duration of 10 week days. A volunteer sample of patients with optic nerve damage (mean age 59.1 yrs) was recruited. The primary outcome measure for efficacy was super-threshold visual fields with 48 hrs after the last treatment day and at 2-months follow-up. Secondary outcome measures were near-threshold visual fields, reaction time, visual acuity, and resting-state EEGs to assess changes in brain physiology.

RESULTS

The rtACS-treated group had a mean improvement in visual field of 24.0% which was significantly greater than after sham-stimulation (2.5%). This improvement persisted for at least 2 months in terms of both within- and between-group comparisons. Secondary analyses revealed improvements of near-threshold visual fields in the central 5° and increased thresholds in static perimetry after rtACS and improved reaction times, but visual acuity did not change compared to shams. Visual field improvement induced by rtACS was associated with EEG power-spectra and coherence alterations in visual cortical networks which are interpreted as signs of neuromodulation. Current flow simulation indicates current in the frontal cortex, eye, and optic nerve and in the subcortical but not in the cortical regions.

CONCLUSION

rtACS treatment is a safe and effective means to partially restore vision after optic nerve damage probably by modulating brain plasticity. This class 1 evidence suggests that visual fields can be improved in a clinically meaningful way.

TRIAL REGISTRATION

ClinicalTrials.gov NCT01280877.

Analysis and Enhancements of a Prolific Macroscopic Model of Epilepsy

Macroscopic models of epilepsy can deliver surprisingly realistic EEG simulations. In the present study, a prolific series of models is evaluated with regard to theoretical and computational concerns, and enhancements are developed. Specifically, we analyze three aspects of the models: (1) Using dynamical systems analysis, we demonstrate and explain the presence of direct current potentials in the simulated EEG that were previously undocumented. (2) We explain how the system was not ideally formulated for numerical integration of stochastic differential equations. A reformulated system is developed to support proper methodology. (3) We explain an unreported contradiction in the published model specification regarding the use of a mathematical reduction method. We then use the method to reduce the number of equations and further improve the computational efficiency. The intent of our critique is to enhance the evolution of macroscopic modeling of epilepsy and assist others who wish to explore this exciting class of models further.

Entrainment of Human Alpha Oscillations Selectively Enhances Visual Conjunction Search

The functional role of the alpha-rhythm which dominates the human electroencephalogram (EEG) is unclear. It has been related to visual processing, attentional selection and object coherence, respectively. Here we tested the interaction of alpha oscillations of the human brain with visual search tasks that differed in their attentional demands (pre-attentive vs. attentive) and also in the necessity to establish object coherence (conjunction vs. single feature). Between pre- and post-assessment elderly subjects received 20 min/d of repetitive transcranial alternating current stimulation (tACS) over the occipital cortex adjusted to their individual alpha frequency over five consecutive days. Compared to sham the entrained alpha oscillations led to a selective, set size independent improvement in the conjunction search task performance but not in the easy or in the hard feature search task. These findings suggest that cortical alpha oscillations play a specific role in establishing object coherence through suppression of distracting objects.

Transcranial alternating current stimulation affects the BOLD signal in a frequency and task-dependent manner

Transcranial alternating current stimulation (tACS) has emerged as a promising tool for manipulating ongoing brain oscillations. While previous studies demonstrated frequency‐specific effects of tACS on diverse cognitive functions, its effect on neural activity remains poorly understood. Here we asked how tACS modulates regional fMRI blood oxygenation level dependent (BOLD) signal as a function of frequency, current strength, and task condition. TACS was applied over the posterior cortex of healthy human subjects while the BOLD signal was measured during rest or task conditions (visual perception, passive video viewing and motor task). TACS was applied in a blockwise manner at different frequencies (10, 16, 60 and 80 Hz). The strongest tACS effects on BOLD activity were observed with stimulation at alpha (10 Hz) and beta (16 Hz) frequency bands, while effects of tACS at the gamma range were rather modest. Specifically, we found that tACS at 16 Hz induced BOLD activity increase in fronto‐parietal areas. Overall, tACS effects varied as a function of frequency and task, and were predominantly seen in regions that were not activated by the task. Also, the modulated regions were poorly predicted by current density modeling studies. Taken together, our results suggest that tACS does not necessarily exert its strongest effects in regions below the electrodes and that region specificity might be achieved with tACS due to varying susceptibility of brain regions to entrain to a given frequency. Hum Brain Mapp 37:94–121, 2016. © 2015 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc

Investigating the cortical regions involved in MEP modulation in tDCS

Transcranial magnetic stimulation (TMS) is used in several studies to evaluate cortical excitability changes induced by transcranial direct current stimulation (tDCS) of the primary motor cortex. Interpretation of these results, however, is hindered by the very different spatial distribution of the electric field (E-field) induced by the two techniques and by the different target neurons that they might act upon. In this study we used the finite element method to calculate the E-field distribution induced by TMS and tDCS in a realistically shaped model of a human head. A model of a commercially available figure-8 coil was placed over a position above the identified hand knob (HK) region. We also modeled two configurations of bipolar tDCS montages with one of the electrodes placed over the HK and a return electrode over the contralateral orbital region. The electrodes over the HK were either rectangular in shape, with an area of 35 cm² or cylindrical with an area of π cm² (1 cm radius). To compare the E-field distribution in TMS and the two tDCS models, average values of the E-field's magnitude as well as the polar and azimuthal angle were investigated in the HK region and premotor areas. The results show that both techniques induce fields with different magnitudes and directions in the HK: the field in tDCS is predominantly perpendicular to the cortical surface, contrary to what happens in TMS where the field is mostly parallel to it. In the premotor areas, the magnitude of the E-field induced in TMS was well below the accepted threshold for MEP generation, 100 V/m. In tDCS, the magnitude of the field in these areas was comparable to that induced at the HK with a significant component perpendicular to the cortical surface. These results indicate that tDCS and TMS target preferentially different neuronal structures at the HK. Besides, they show that premotor areas may play a role in the tDCS-induced after effects on motor cortex excitability.

Modeling sequence and quasi-uniform assumption in computational neurostimulation

Computational neurostimulation aims to develop mathematical constructs that link the application of neuromodulation with changes in behavior and cognition. This process is critical but daunting for technical challenges and scientific unknowns. The overarching goal of this review is to address how this complex task can be made tractable. We describe a framework of sequential modeling steps to achieve this: (1) current flow models, (2) cell polarization models, (3) network and information processing models, and (4) models of the neuroscientific correlates of behavior. Each step is explained with a specific emphasis on the assumptions underpinning underlying sequential implementation. We explain the further implementation of the quasi-uniform assumption to overcome technical limitations and unknowns. We specifically focus on examples in electrical stimulation, such as transcranial direct current stimulation. Our approach and conclusions are broadly applied to immediate and ongoing efforts to deploy computational neurostimulation.

Experiments and models of cortical oscillations as a target for noninvasive brain stimulation

Noninvasive brain stimulation is attracting substantial attention due to its potential for safe and effective modulation of brain network dynamics. Promising applications include cognitive enhancement and treatment of disorders of the central nervous system. Recently, targeting of cortical oscillations by brain stimulation with periodic electromagnetic waveforms has emerged as a particularly appealing approach for understanding the causal role of cortical oscillations in human cognition and behavior. Two main approaches exist: repetitive transcranial magnetic stimulation (rTMS) and transcranial alternating current stimulation (tACS); rTMS is more widely used as a research and clinical tool but only recently has it been suggested to selectively engage frequency-matched cortical oscillations. In contrast, tACS is an offspring of transcranial direct current stimulation and has been introduced with the specific aim of engaging cortical oscillations. One of the main lessons that the field of noninvasive brain stimulation has learned over the last few years is that without a mechanistic understanding of how stimulation engages neuronal circuits, little progress can be made toward the rational design of individualized, adaptive stimulation treatments. Computer simulations of cellular and network models from the field of computational neuroscience are a key tool to gain such a mechanistic understanding. However, the insights gained from such modeling strategies can only be fully leveraged when used in tight conjunction with experimental approaches in both human and animal model studies. Here, I provide an in-depth review of the pioneering experimental and computational studies that together provide the basis for understanding how periodic noninvasive brain stimulation targets cortical oscillations to enable the rational design of brain stimulation treatments for disorders associated with specific deficits in cortical oscillations.

Computational modeling of neurostimulation in brain diseases

Neurostimulation as a therapeutic tool has been developed and used for a range of different diseases such as Parkinson's disease, epilepsy, and migraine. However, it is not known why the efficacy of the stimulation varies dramatically across patients or why some patients suffer from severe side effects. This is largely due to the lack of mechanistic understanding of neurostimulation. Hence, theoretical computational approaches to address this issue are in demand. This chapter provides a review of mechanistic computational modeling of brain stimulation. In particular, we will focus on brain diseases, where mechanistic models (e.g., neural population models or detailed neuronal models) have been used to bridge the gap between cellular-level processes of affected neural circuits and the symptomatic expression of disease dynamics. We show how such models have been, and can be, used to investigate the effects of neurostimulation in the diseased brain. We argue that these models are crucial for the mechanistic understanding of the effect of stimulation, allowing for a rational design of stimulation protocols. Based on mechanistic models, we argue that the development of closed-loop stimulation is essential in order to avoid inference with healthy ongoing brain activity. Furthermore, patient-specific data, such as neuroanatomic information and connectivity profiles obtainable from neuroimaging, can be readily incorporated to address the clinical issue of variability in efficacy between subjects. We conclude that mechanistic computational models can and should play a key role in the rational design of effective, fully integrated, patient-specific therapeutic brain stimulation.

Predicting the electric field distribution in the brain for the treatment of glioblastoma

The use of alternating electric fields has been recently proposed for the treatment of recurrent glioblastoma. In order to predict the electric field distribution in the brain during the application of such tumor treating fields (TTF), we constructed a realistic head model from MRI data and placed transducer arrays on the scalp to mimic an FDA-approved medical device. Values for the tissue dielectric properties were taken from the literature; values for the device parameters were obtained from the manufacturer. The finite element method was used to calculate the electric field distribution in the brain. We also included a 'virtual lesion' in the model to simulate the presence of an idealized tumor. The calculated electric field in the brain varied mostly between 0.5 and 2.0 V cm( - 1) and exceeded 1.0 V cm( - 1) in 60% of the total brain volume. Regions of local field enhancement occurred near interfaces between tissues with different conductivities wherever the electric field was perpendicular to those interfaces. These increases were strongest near the ventricles but were also present outside the tumor's necrotic core and in some parts of the gray matter-white matter interface. The electric field values predicted in this model brain are in reasonably good agreement with those that have been shown to reduce cancer cell proliferation in vitro. The electric field distribution is highly non-uniform and depends on tissue geometry and dielectric properties. This could explain some of the variability in treatment outcomes. The proposed modeling framework could be used to better understand the physical basis of TTF efficacy through retrospective analysis and to improve TTF treatment planning.

The effects of theta transcranial alternating current stimulation (tACS) on fluid intelligence

The objective of the study was to explore the influence of transcranial alternating current stimulation (tACS) on resting brain activity and on measures of fluid intelligence. Theta tACS was applied to the left parietal and left frontal brain areas of healthy participants after which resting electroencephalogram (EEG) data was recorded. Following sham/active stimulation, the participants solved two tests of fluid intelligence while their EEG was recorded. The results showed that active theta tACS affected spectral power in theta and alpha frequency bands. In addition, active theta tACS improved performance on tests of fluid intelligence. This influence was more pronounced in the group of participants that received stimulation to the left parietal area than in the group of participants that received stimulation to the left frontal area. Left parietal tACS increased performance on the difficult test items of both tests (RAPM and PF&C) whereas left frontal tACS increased performance only on the easy test items of one test (RAPM). The observed behavioral tACS influences were also accompanied by changes in neuroelectric activity. The behavioral and neuroelectric data tentatively support the P-FIT neurobiological model of intelligence.

Optimization of multifocal transcranial current stimulation for weighted cortical pattern targeting from realistic modeling of electric fields

Recently, multifocal transcranial current stimulation (tCS) devices using several relatively small electrodes have been used to achieve more focal stimulation of specific cortical targets. However, it is becoming increasingly recognized that many behavioral manifestations of neurological and psychiatric disease are not solely the result of abnormality in one isolated brain region but represent alterations in brain networks. In this paper we describe a method for optimizing the configuration of multifocal tCS for stimulation of brain networks, represented by spatially extended cortical targets. We show how, based on fMRI, PET, EEG or other data specifying a target map on the cortical surface for excitatory, inhibitory or neutral stimulation and a constraint on the maximal number of electrodes, a solution can be produced with the optimal currents and locations of the electrodes. The method described here relies on a fast calculation of multifocal tCS electric fields (including components normal and tangential to the cortical boundaries) using a five layer finite element model of a realistic head. Based on the hypothesis that the effects of current stimulation are to first order due to the interaction of electric fields with populations of elongated cortical neurons, it is argued that the optimization problem for tCS stimulation can be defined in terms of the component of the electric field normal to the cortical surface. Solutions are found using constrained least squares to optimize current intensities, while electrode number and their locations are selected using a genetic algorithm. For direct current tCS (tDCS) applications, we provide some examples of this technique using an available tCS system providing 8 small Ag/AgCl stimulation electrodes. We demonstrate the approach both for localized and spatially extended targets defined using rs-fcMRI and PET data, with clinical applications in stroke and depression. Finally, we extend these ideas to more general stimulation protocols, such as alternating current tCS (tACS).

Transcranial slow oscillation stimulation during sleep enhances memory consolidation in rats

BACKGROUND

The importance of slow-wave sleep (SWS), hallmarked by the occurrence of sleep slow oscillations (SO), for the consolidation of hippocampus-dependent memories has been shown in numerous studies. Previously, the application of transcranial direct current stimulation, oscillating at the frequency of endogenous slow oscillations, during SWS enhanced memory consolidation for a hippocampus dependent task in humans suggesting a causal role of slowly oscillating electric fields for sleep dependent memory consolidation.

OBJECTIVE

Here, we aimed to replicate and extend these findings to a rodent model.

METHODS

Slow oscillatory direct transcranial current stimulation (SO-tDCS) was applied over the frontal cortex of rats during non-rapid eye movement (NREM) sleep and its effects on memory consolidation in the one-trial object-place recognition task were examined. A retention interval of 24 h was used to investigate the effects of SO-tDCS on long-term memory.

RESULTS

Animals' preference for the displaced object was significantly greater than chance only when animals received SO-tDCS. EEG spectral power indicated a trend toward a transient enhancement of endogenous SO activity in the SO-tDCS condition.

CONCLUSIONS

These results support the hypothesis that slowly oscillating electric fields causal affect sleep dependent memory consolidation, and demonstrate that oscillatory tDCS can be a valuable tool to investigate the function of endogenous cortical network activity.