Brain State-Dependent Brain Stimulation

A little goes a long way: Neurobiological effects of low intensity rTMS and implications for mechanisms of rTMS

Repetitive transcranial magnetic stimulation (rTMS) is a widespread technique in neuroscience and medicine, however its mechanisms are not well known. In this review, we consider intensity as a key therapeutic parameter of rTMS, and review the studies that have examined the biological effects of rTMS using magnetic fields that are orders of magnitude lower that those currently used in the clinic. We discuss how extensive characterisation of "low intensity" rTMS has set the stage for translation of new rTMS parameters from a mechanistic evidence base, with potential for innovative and effective therapeutic applications. Low-intensity rTMS demonstrates neurobiological effects across healthy and disease models, which include depression, injury and regeneration, abnormal circuit organisation, tinnitus etc. Various short and long-term changes to metabolism, neurotransmitter release, functional connectivity, genetic changes, cell survival and behaviour have been investigated and we summarise these key changes and the possible mechanisms behind them. Mechanisms at genetic, molecular, cellular and system levels have been identified with evidence that low-intensity rTMS and potentially rTMS in general acts through several key pathways to induce changes in the brain with modulation of internal calcium signalling identified as a major mechanism. We discuss the role that preclinical models can play to inform current clinical research as well as uncover new pathways for investigation.

P300 Modulation via Transcranial Alternating Current Stimulation in Adult Attention-Deficit/Hyperactivity Disorder: A Crossover Study

OBJECTIVE

A repeated finding regarding event-related potentials (ERPs) is that patients with ADHD show a reduced P300 amplitude. This raises the question of whether the attention of ADHD patients can be increased by stabilizing the P300. Assuming that the P300 is generated by event-related oscillations (EROs) in the low frequency range (0-8 Hz), one approach to increase the P300 could be to stimulate the patient's P300 underlying ERO by means of transcranial alternating current stimulation (tACS). The aim of this follow-up study was to investigate this hypothesized mechanism of action in adult ADHD patients.

MATERIALS AND METHODS

Undergoing a crossover design, 20 adult ADHD patients (10 female) received an actual stimulation via tACS on one day and a sham stimulation on another day. Before and after each intervention, EEG characteristics (P300 amplitudes, low frequency power) and attention performances (d2 attention test, visual oddball task (VOT)) were recorded.

RESULTS

Electrophysiological analyses revealed no evidence for an enhanced P300 amplitude or low frequency power increase after actual stimulation compared to sham stimulation. Instead, a significant effect was found for a stronger N700 amplitude increase after actual stimulation compared to sham stimulation. Consistent with the P300 null results, none of the examined neuropsychological performance measures indicated a tACS-induced improvement in attentional ability.

CONCLUSION

Contrary to a previous study using tACS to modulate the P300 in adult ADHD patients, the current study yields no evidence that tACS can increase the P300 amplitude in adult ADHD patients and that such P300 enhancement can directly improve neuropsychological parameters of attention.

Spontaneous Fluctuations in Oscillatory Brain State Cause Differences in Transcranial Magnetic Stimulation Effects Within and Between Individuals

Transcranial magnetic stimulation (TMS) can cause measurable effects on neural activity and behavioral performance in healthy volunteers. In addition, TMS is increasingly used in clinical practice for treating various neuropsychiatric disorders. Unfortunately, TMS-induced effects show large intra- and inter-subject variability, hindering its reliability, and efficacy. One possible source of this variability may be the spontaneous fluctuations of neuronal oscillations. We present recent studies using multimodal TMS including TMS-EMG (electromyography), TMS-tACS (transcranial alternating current stimulation), and concurrent TMS-EEG-fMRI (electroencephalography, functional magnetic resonance imaging), to evaluate how individual oscillatory brain state affects TMS signal propagation within targeted networks. We demonstrate how the spontaneous oscillatory state at the time of TMS influences both immediate and longer-lasting TMS effects. These findings indicate that at least part of the variability in TMS efficacy may be attributable to the current practice of ignoring (spontaneous) oscillatory fluctuations during TMS. Ignoring this state-dependent spread of activity may cause great individual variability which so far is poorly understood and has proven impossible to control. We therefore also compare two technical solutions to directly account for oscillatory state during TMS, namely, to use (a) tACS to externally control these oscillatory states and then apply TMS at the optimal (controlled) brain state, or (b) oscillatory state-triggered TMS (closed-loop TMS). The described multimodal TMS approaches are paramount for establishing more robust TMS effects, and to allow enhanced control over the individual outcome of TMS interventions aimed at modulating information flow in the brain to achieve desirable changes in cognition, mood, and behavior.

Abnormal Dynamic Functional Network Connectivity Estimated from Default Mode Network Predicts Symptom Severity in Major Depressive Disorder

Background: Major depressive disorder (MDD) is a severe mental illness marked by a continuous sense of sadness and a loss of interest. The default mode network (DMN) is a group of brain areas that are more active during rest and deactivate when engaged in task-oriented activities. The DMN of MDD has been found to have aberrant static functional network connectivity (FNC) in recent studies. In this work, we extend previous findings by evaluating dynamic functional network connectivity (dFNC) within the DMN subnodes in MDD. Methods: We analyzed resting-state functional magnetic resonance imaging data of 262 patients with MDD and 277 healthy controls (HCs). We estimated dFNCs for seven subnodes of the DMN, including the anterior cingulate cortex (ACC), posterior cingulate cortex (PCC), and precuneus (PCu), using a sliding window approach, and then clustered the dFNCs into five brain states. Classification of MDD and HC subjects based on state-specific FC was performed using a logistic regression classifier. Transition probabilities between dFNC states were used to identify relationships between symptom severity and dFNC data in MDD patients. Results: By comparing state-specific FNC between HC and MDD, a disrupted connectivity pattern was observed within the DMN. In more detail, we found that the connectivity of ACC is stronger, and the connectivity between PCu and PCC is weaker in individuals with MDD than in those of HC subjects. In addition, MDD showed a higher probability of transitioning from a state with weaker ACC connectivity to a state with stronger ACC connectivity, and this abnormality is associated with symptom severity. This is the first research to look at the dFC of the DMN in MDD with a large sample size. It provides novel evidence of abnormal time-varying DMN configuration in MDD and offers links to symptom severity in MDD subjects. Impact Statement This study is the first attempt that explored the temporal change on default mode network (DMN) connectivity in a relatively large cohort of patients with major depressive disorder (MDD). We also introduced a new hypothesis that explains the inconsistency in DMN functional network connectivity (FNC) comparison between MDD and healthy control based on static FNC in the previous literature. Additionally, our findings suggest that within anterior cingulate cortex connectivity and the connectivity between the precuneus and posterior cingulate cortex are the potential biomarkers for the future intervention of MDD.

The Brain Electrophysiological recording & STimulation (BEST) toolbox

Non-invasive brain stimulation (NIBS) experiments involve many recurring procedures that are not sufficiently standardized in the community. Given the diversity in experimental design and experience of the investigators, automated but yet flexible data collection and analysis tools are needed to increase objectivity, reliability, and reproducibility of NIBS experiments. The Brain Electrophysiological recording and STimulation (BEST) Toolbox is a MATLAB-based, open-source software with graphical user interface that allows users to design, run, and share freely configurable multi-protocol, multi-session NIBS studies, including transcranial magnetic, electric, and ultrasound stimulation (TMS, tES, TUS). Interfacing with a variety of recording and stimulation devices, the BEST toolbox analyzes EMG and EEG data, and configures stimulation parameters on-the-fly to facilitate closed-loop protocols and real-time applications. Its functionality is continuously expanded and includes e.g., TMS motor hotspot search, threshold estimation, motor evoked potential (MEP) and TMS-evoked EEG potential (TEP) measurements, dose-response curves, paired-pulse and dual-coil TMS, rTMS interventions.

Galvanic Vestibular Stimulation Effects on EEG Biomarkers of Motor Vigor in Parkinson's Disease

Background: Impaired motor vigor (MV) is a critical aspect of Parkinson's disease (PD) pathophysiology. While MV is predominantly encoded in the basal ganglia, deriving (cortical) EEG measures of MV may provide valuable targets for modulation via galvanic vestibular stimulation (GVS). Objective: To find EEG features predictive of MV and examine the effects of high-frequency GVS. Methods: Data were collected from 20 healthy control (HC) and 18 PD adults performing 30 trials total of a squeeze bulb task with sham or multi-sine (50-100 Hz "GVS1" or 100-150 Hz "GVS2") stimuli. For each trial, we determined the time to reach maximum force after a "Go" signal, defined MV as the inverse of this time, and used the EEG data 1-sec prior to this time for prediction. We utilized 53 standard EEG features, including relative spectral power, harmonic parameters, and amplitude and phase of bispectrum corresponding to standard EEG bands from each of 27 EEG channels. We then used LASSO regression to select a sparse set of features to predict MV. The regression weights were examined, and separate band-specific models were developed by including only band-specific features (Delta, Theta, Alpha-low, Alpha-high, Beta, Gamma). The correlation between MV prediction and measured MV was used to assess model performance. Results: Models utilizing broadband EEG features were capable of accurately predicting MV (controls: 75%, PD: 81% of the variance). In controls, all EEG bands performed roughly equally in predicting MV, while in the PD group, the model using only beta band features did not predict MV well compared to other bands. Despite having minimal effects on the EEG feature values themselves, both GVS stimuli had significant effects on MV and profound effects on MV predictability via the EEG. With the GVS1 stimulus, beta-band activity in PD subjects became more closely associated with MV compared to the sham condition. With GVS2 stimulus, MV could no longer be accurately predicted from the EEG. Conclusions: EEG features can be a proxy for MV. However, GVS stimuli have profound effects on the relationship between EEG and MV, possibly via direct vestibulo-basal ganglia connections not measurable by the EEG.

Causal roles of prefrontal cortex during spontaneous perceptual switching are determined by brain state dynamics

The prefrontal cortex (PFC) is thought to orchestrate cognitive dynamics. However, in tests of bistable visual perception, no direct evidence supporting such presumable causal roles of the PFC has been reported except for a recent work. Here, using a novel brain-state-dependent neural stimulation system, we identified causal effects on percept dynamics in three PFC activities—right frontal eye fields, dorsolateral PFC (DLPFC), and inferior frontal cortex (IFC). The causality is behaviourally detectable only when we track brain state dynamics and modulate the PFC activity in brain-state-/state-history-dependent manners. The behavioural effects are underpinned by transient neural changes in the brain state dynamics, and such neural effects are quantitatively explainable by structural transformations of the hypothetical energy landscapes. Moreover, these findings indicate distinct functions of the three PFC areas: in particular, the DLPFC enhances the integration of two PFC-active brain states, whereas IFC promotes the functional segregation between them. This work resolves the controversy over the PFC roles in spontaneous perceptual switching and underlines brain state dynamics in fine investigations of brain-behaviour causality.

A cube that seems to shift its spatial arrangement as you keep looking; the elegant silhouette of a pirouetting dancer, which starts to spin in the opposite direction the more you stare at it; an illustration that shows two profiles – or is it a vase? These optical illusions are examples of bistable visual perception. Beyond their entertaining aspect, they provide a way for scientists to explore the dynamics of human consciousness, and the neural regions involved in this process.

Some studies show that bistable visual perception is associated with the activation of the prefrontal cortex, a brain area involved in complex cognitive processes. However, it is unclear whether this region is required for the illusions to emerge. Some research has showed that even if sections of the prefrontal cortex are temporally deactivated, participants can still experience the illusions.

Instead, Takamitsu Watanabe proposes that bistable visual perception is a process tied to dynamic brain states – that is, that distinct regions of the prefontal cortex are required for this fluctuating visual awareness, depending on the state of the whole brain. Such causal link cannot be observed if brain activity is not tracked closely.

To investigate this, the brain states of 65 participants were recorded as individuals were experiencing the optical illusions; the activity of their various brain regions could therefore be mapped, and then areas of the prefrontal cortex could precisely be inhibited at the right time using transcranial magnetic stimulation. This revealed that, indeed, prefrontal cortex regions were necessary for bistable visual perception, but not in a simple way. Instead, which ones were required and when depended on activity dynamics taking place in the whole brain. Overall, these results indicate that monitoring brain states is necessary to better understand – and ultimately, control – the neural pathways underlying perception and behaviour.

Control of Transcranial Direct Current Stimulation Duration by Assessing Functional Connectivity of Near-Infrared Spectroscopy Signals

Transcranial direct current stimulation (tDCS) has been shown to create neuroplasticity in healthy and diseased populations. The control of stimulation duration by providing real-time brain state feedback using neuroimaging is a topic of great interest. This study presents the feasibility of a closed-loop modulation for the targeted functional network in the prefrontal cortex. We hypothesize that we cannot improve the brain state further after reaching a specific state during a stimulation therapy session. A high-definition tDCS of 1[Formula: see text]mA arranged in a ring configuration was applied at the targeted right prefrontal cortex of 15 healthy male subjects for 10[Formula: see text]min. Functional near-infrared spectroscopy was used to monitor hemoglobin chromophores during the stimulation period continuously. The correlation matrices obtained from filtered oxyhemoglobin were binarized to form subnetworks of short- and long-range connections. The connectivity in all subnetworks was analyzed individually using a new quantification measure of connectivity percentage based on the correlation matrix. The short-range network in the stimulated hemisphere showed increased connectivity in the initial stimulation phase. However, the increase in connection density reduced significantly after 6[Formula: see text]min of stimulation. The short-range network of the left hemisphere and the long-range network gradually increased throughout the stimulation period. The connectivity percentage measure showed a similar response with network theory parameters. The connectivity percentage and network theory metrics represent the brain state during the stimulation therapy. The results from the network theory metrics, including degree centrality, efficiency, and connection density, support our hypothesis and provide a guideline for feedback on the brain state. The proposed neuro-feedback scheme is feasible to control the stimulation duration to avoid overdosage.

Applications of optimal nonlinear control to a whole-brain network of FitzHugh-Nagumo oscillators

We apply the framework of optimal nonlinear control to steer the dynamics of a whole-brain network of FitzHugh-Nagumo oscillators. Its nodes correspond to the cortical areas of an atlas-based segmentation of the human cerebral cortex, and the internode coupling strengths are derived from diffusion tensor imaging data of the connectome of the human brain. Nodes are coupled using an additive scheme without delays and are driven by background inputs with fixed mean and additive Gaussian noise. Optimal control inputs to nodes are determined by minimizing a cost functional that penalizes the deviations from a desired network dynamic, the control energy, and spatially nonsparse control inputs. Using the strength of the background input and the overall coupling strength as order parameters, the network's state-space decomposes into regions of low- and high-activity fixed points separated by a high-amplitude limit cycle, all of which qualitatively correspond to the states of an isolated network node. Along the borders, however, additional limit cycles, asynchronous states, and multistability can be observed. Optimal control is applied to several state-switching and network synchronization tasks, and the results are compared to controllability measures from linear control theory for the same connectome. We find that intuitions from the latter about the roles of nodes in steering the network dynamics, which are solely based on connectome features, do not generally carry over to nonlinear systems, as had been previously implied. Instead, the role of nodes under optimal nonlinear control critically depends on the specified task and the system's location in state space. Our results shed new light on the controllability of brain network states and may serve as an inspiration for the design of new paradigms for noninvasive brain stimulation.

Speech Fluency Improvement in Developmental Stuttering Using Non-invasive Brain Stimulation: Insights From Available Evidence

Developmental stuttering (DS) is a disturbance of the normal rhythm of speech that may be interpreted as very debilitating in the most affected cases. Interventions for DS are historically based on the behavioral modifications of speech patterns (e.g., through speech therapy), which are useful to regain a better speech fluency. However, a great variability in intervention outcomes is normally observed, and no definitive evidence is currently available to resolve stuttering, especially in the case of its persistence in adulthood. In the last few decades, DS has been increasingly considered as a functional disturbance, affecting the correct programming of complex motor sequences such as speech. Compatibly, understanding of the neurophysiological bases of DS has dramatically improved, thanks to neuroimaging, and techniques able to interact with neural tissue functioning [e.g., non-invasive brain stimulation (NIBS)]. In this context, the dysfunctional activity of the cortico-basal-thalamo-cortical networks, as well as the defective patterns of connectivity, seems to play a key role, especially in sensorimotor networks. As a consequence, a direct action on the functionality of "defective" or "impaired" brain circuits may help people who stutter to manage dysfluencies in a better way. This may also "potentiate" available interventions, thus favoring more stable outcomes of speech fluency. Attempts aiming at modulating (and improving) brain functioning of people who stutter, realized by using NIBS, are quickly increasing. Here, we will review these recent advancements being applied to the treatment of DS. Insights will be useful not only to assess whether the speech fluency of people who stutter may be ameliorated by acting directly on brain functioning but also will provide further suggestions about the complex and dynamic pathophysiology of DS, where causal effects and "adaptive''/''maladaptive" compensation mechanisms may be strongly overlapped. In conclusion, this review focuses future research toward more specific, targeted, and effective interventions for DS, based on neuromodulation of brain functioning.

Increased cortical excitability but stable effective connectivity index during attentional lapses

Modern lifestyle curtails sleep and increases nighttime work and leisure activities. This has a deleterious impact on vigilance and attention, exacerbating chances of committing attentional lapses, with potential dramatic outcomes. Here, we investigated the brain signature of attentional lapses and assessed whether cortical excitability and brain response propagation were modified during lapses and whether these modifications changed with aging. We compared electroencephalogram (EEG) responses to transcranial magnetic stimulation (TMS) during lapse and no-lapse periods while performing a continuous attentional/vigilance task at night, after usual bedtime. Data were collected in healthy younger (N = 12; 18-30 years) and older individuals (N = 12; 50-70 years) of both sexes. The amplitude and slope of the first component of the TMS-evoked potential were larger during lapses. In contrast, TMS response scattering over the cortical surface, as well as EEG response complexity, did not significantly vary between lapse and no-lapse periods. Importantly, despite qualitative differences, age did not significantly affect any of the TMS-EEG measures. These results demonstrate that attentional lapses are associated with a transient increase of cortical excitability. This initial change is not associated with detectable changes in subsequent effective connectivity-as indexed by response propagation-and are not markedly different between younger and older adults. These findings could contribute to develop models aimed to predicting and preventing lapses in real-life situations.

Transcranial Auricular Vagus Nerve Stimulation (taVNS) and Ear-EEG: Potential for Closed-Loop Portable Non-invasive Brain Stimulation

No matter how hard we concentrate, our attention fluctuates – a fact that greatly affects our success in completing a current task. Here, we review work from two methods that, in a closed-loop manner, have the potential to ameliorate these fluctuations. Ear-EEG can measure electric brain activity from areas in or around the ear, using small and thus portable hardware. It has been shown to capture the state of attention with high temporal resolution. Transcutaneous auricular vagus nerve stimulation (taVNS) comes with the same advantages (small and light) and critically current research suggests that it is possible to influence ongoing brain activity that has been linked to attention. Following the review of current work on ear-EEG and taVNS we suggest that a combination of the two methods in a closed-loop system could serve as a potential application to modulate attention.

Effect of Transcranial Direct Current Stimulation on Professional Female Soccer Players' Recovery Following Official Matches

This study investigated the effect of transcranial direct current stimulation (tDCS) combined with a recovery training session on the well-being and self-perceived recovery of professional female soccer players after official matches. Data from 13 world-class players were analyzed after participating in four official soccer matches of the first division of the Brazilian Women's Soccer Championship (7-, 10-, and 13-day intervals). We applied anodal tDCS (a-tDCS) over the left dorsolateral prefrontal cortex with 2 mA for 20 minutes (+F3/-F4 montage) the day after each match. Participants underwent two randomly ordered sessions of a-tDCS or sham. Players completed the Well-Being Questionnaire (WBQ) and the Total Quality Recovery (TQR) scale before each experimental condition and again the following morning. A two-way repeated-measures ANOVA showed a significant time x condition interaction on the WBQ (F_(1,11)=5.21; p=0.043; η_p²=0.32), but not on the TQR (F_(1,12) = 0.552; p = 0.47; η_p² = 0.044). There was a large effect size (ES) for a-tDCS for the WBQ score (ES = 1.02; 95%CI = 0.17;1.88), and there was a moderate WBQ score increase (ES = 0.53; 95%CI = -0.29;1.34) for the sham condition. We found similar increases in the TQR score for a-tDCS (ES = 1.50; 95%CI = 0.63-2.37) and the sham condition (ES = 1.36; 95%CI = 0.51-2.22). These results suggest that a-tDCS (+F3/-F4 montage) combined with a recovery training session may slightly improve perceived well-being beyond the level of improvement after only the recovery training session among world-class female soccer players. Prior to widely adopting this recovery approach, further study is needed with larger and more diverse samples, including for female teams of different performance levels.

Concurrent TMS-fMRI for causal network perturbation and proof of target engagement

The experimental manipulation of neural activity by neurostimulation techniques overcomes the inherent limitations of correlative recordings, enabling the researcher to investigate causal brain-behavior relationships. But only when stimulation and recordings are combined, the direct impact of the stimulation on neural activity can be evaluated. In humans, this can be achieved non-invasively through the concurrent combination of transcranial magnetic stimulation (TMS) with functional magnetic resonance imaging (fMRI). Concurrent TMS-fMRI allows the assessment of the neurovascular responses evoked by TMS with excellent spatial resolution and full-brain coverage. This enables the functional mapping of both local and remote network effects of TMS in cortical as well as deep subcortical structures, offering unique opportunities for basic research and clinical applications. The purpose of this review is to introduce the reader to this powerful tool. We will introduce the technical challenges and state-of-the art solutions and provide a comprehensive overview of the existing literature and the available experimental approaches. We will highlight the unique insights that can be gained from concurrent TMS-fMRI, including the state-dependent assessment of neural responsiveness and inter-regional effective connectivity, the demonstration of functional target engagement, and the systematic evaluation of stimulation parameters. We will also discuss how concurrent TMS-fMRI during a behavioral task can help to link behavioral TMS effects to changes in neural network activity and to identify peripheral co-stimulation confounds. Finally, we will review the use of concurrent TMS-fMRI for developing TMS treatments of psychiatric and neurological disorders and suggest future improvements for further advancing the application of concurrent TMS-fMRI.

The intervention, the patient and the illness - Personalizing non-invasive brain stimulation in psychiatry

Current hypotheses on the therapeutic action of non-invasive brain stimulation (NIBS) in psychiatric disorders build on the abundant data from neuroimaging studies. This makes NIBS a very promising tool for developing personalized interventions within a precision medicine framework. NIBS methods fundamentally vary in their neurophysiological properties. They comprise repetitive transcranial magnetic stimulation (rTMS) and its variants (e.g. theta burst stimulation - TBS) as well as different types of transcranial electrical stimulation (tES), with the largest body of evidence for transcranial direct current stimulation (tDCS). In the last two decades, significant conceptual progress has been made in terms of NIBS targets, i.e. from single brain regions to neural circuits and to functional connectivity as well as their states, recently leading to brain state modulating closed-loop approaches. Regarding structural and functional brain anatomy, NIBS meets an individually unique constellation, which varies across normal and pathophysiological states. Thus, individual constitutions and signatures of disorders may be indistinguishable at a given time point, but can theoretically be parsed along course- and treatment-related trajectories. We address precision interventions on three levels: 1) the NIBS intervention, 2) the constitutional factors of a single patient, and 3) the phenotypes and pathophysiology of illness. With examples from research on depressive disorders, we propose solutions and discuss future perspectives, e.g. individual MRI-based electrical field strength as a proxy for NIBS dosage, and also symptoms, their clusters, or biotypes instead of disorder focused NIBS. In conclusion, we propose interleaved research on these three levels along a general track of reverse and forward translation including both clinically directed research in preclinical model systems, and biomarker guided controlled clinical trials. Besides driving the development of safe and efficacious interventions, this framework could also deepen our understanding of psychiatric disorders at their neurophysiological underpinnings.

Closed-loop neurostimulation for affective symptoms and disorders: An overview

Affective and anxiety disorders are the most prevalent and incident psychiatric disorders worldwide. Therapeutic approaches to these disorders using non-invasive brain stimulation (NIBS) and analogous techniques have been extensively investigated. In this paper, we discuss the combination of NIBS and neurofeedback in closed-loop setups and its application for affective symptoms and disorders. For this, we first provide a rationale for this combination by presenting some of the main original findings of NIBS, with a primary focus on transcranial magnetic stimulation (TMS), and neurofeedback, including protocols based on electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). Then, we provide a scope review of studies combining real-time neurofeedback with NIBS protocols in the so-called closed-loop brain state-dependent neuromodulation (BSDS). Finally, we discuss the concomitant use of TMS and real-time functional near-infrared spectroscopy (fNIRS) as a possible solution to the current limitations of BSDS-based protocols for affective and anxiety disorders.

Advancing clinical response characterization to frontotemporal transcranial direct current stimulation with electric field distribution in patients with schizophrenia and auditory hallucinations: a pilot study

Transcranial direct current stimulation (tDCS) has been proposed as a therapeutic option for treatment-resistant auditory verbal hallucinations (AVH) in schizophrenia. In such cases, repeated sessions of tDCS are delivered with the anode over the left prefrontal cortex and the cathode over the left temporoparietal junction. Despite promising findings, the clinical response to tDCS is highly heterogeneous among patients. Here, we explored baseline differences between responders and nonresponders to frontotemporal tDCS using electric field modeling. We hypothesized that responders would display different tDCS-induced electric field strength in the brain areas involved in AVH compared to nonresponders.Using baseline structural MRI scans of 17 patients with schizophrenia and daily AVH who received 10 sessions of active frontotemporal tDCS, we constructed individual realistic whole brain models estimating electric field strength. Electric field maps were compared between responders (n = 6) and nonresponders to tDCS (n = 11) using an independent two-sample t test. Clinical response was defined as at least a 50% decrease of AVH 1 month after the last tDCS session.Results from the electric field map comparison showed that responders to tDCS displayed higher electric field strength in the left transverse temporal gyrus at baseline compared to nonresponders (T = 2.37; p = 0.016; 32 voxels).These preliminary findings suggested that the strength of the tDCS-induced electric field reaching the left transverse temporal gyrus could play an important role in the response to frontotemporal tDCS. In addition, this work suggests the interest of using electric field modeling to individualize tDCS and increase response rate.

The Staff Views About Assessing Voices Questionnaire: Piloting a Novel Socratic Method of Evaluating and Training Multidisciplinary Staff's Cognitive Assessment of Patients' Distressing Voices

Cognitive features of auditory hallucinations (voices) have important clinical significance and their assessment is vital for cognitive behavior therapy to be more widely deployed by multidisciplinary staff. Using a new Socratic instrument-The Staff Views About Assessing Voices Questionnaire (SVAVQ)-we surveyed a community inpatient rehabilitation multidisciplinary workforce's (N = 50) assessment and attitude toward asking cognitive questions about patients' voices. We found that there were many clinically important gaps in what staff asked about in relation to cognitive features of voices. We identified a range of beliefs the staff hold that may prevent assessment of voice cognitive features. However, after attending the Socratic SVAVQ interview, 84% of staff said they planned to ask patients more questions about cognitive features of patients' voices. Research could now test if other psychosis services neglect the assessment of important cognitive features of patients' voices and if staff Socratic questioning improves their cognitive assessments.

Failure to modulate reward prediction errors in declarative learning with theta (6 Hz) frequency transcranial alternating current stimulation

Recent evidence suggests that reward prediction errors (RPEs) play an important role in declarative learning, but its neurophysiological mechanism remains unclear. Here, we tested the hypothesis that RPEs modulate declarative learning via theta-frequency oscillations, which have been related to memory encoding in prior work. For that purpose, we examined the interaction between RPE and transcranial Alternating Current Stimulation (tACS) in declarative learning. Using a between-subject (real versus sham stimulation group), single-blind stimulation design, 76 participants learned 60 Dutch-Swahili word pairs, while theta-frequency (6 Hz) tACS was administered over the medial frontal cortex (MFC). Previous studies have implicated MFC in memory encoding. We replicated our previous finding of signed RPEs (SRPEs) boosting declarative learning; with larger and more positive RPEs enhancing memory performance. However, tACS failed to modulate the SRPE effect in declarative learning and did not affect memory performance. Bayesian statistics supported evidence for an absence of effect. Our study confirms a role of RPE in declarative learning, but also calls for standardized procedures in transcranial electrical stimulation.

The Effects of Non-invasive Brain Stimulation on Impulsivity in People with Mental Disorders: a Systematic Review and Explanatory Meta-Analysis

Impulsivity is a multi-faceted construct that underpins various mental health disorders. Impulsive behavior exacts a substantial health and economic burden, hence the importance of developing specific interventions to target impulsivity. Two forms of non-invasive brain stimulation, namely transcranial direct current stimulation (tDCS) and repetitive transcranial magnetic stimulation (rTMS), have been used to modulate impulsivity. To date, no reviews have systematically examined their effects on modulating impulsivity in people with mental health disorders. We conducted a systematic review and meta-analysis of the literature from AMED, Embase, Medline and PsycINFO databases on the use of rTMS and tDCS to modulate impulsivity in people with mental health disorders. Results from 11 tDCS and 18 rTMS studies indicate that tDCS has a significant, albeit small, effect on modulating impulsivity (g = 0.29; 95% CI, 0.09 to 0.48; p = .004) whereas rTMS has no significant effect on impulsivity (g = -0.08; 95% Cl, -0.35 to 0.19; p = .550). Subgroup analyses identified the key parameters required to enhance the effects of tDCS and rTMS on impulsivity. Gender and stimulation intensity acted as significant moderators for effects of rTMS on impulsivity. There is insufficient evidence to support the use of tDCS or rTMS in clinical practice to reduce impulsivity in people with mental health disorders. The use of standardized non-invasive brain stimulation protocols and outcome measures in patients with the same diagnosis is advised to minimize methodological heterogeneity.

Relations between large-scale brain connectivity and effects of regional stimulation depend on collective dynamical state

At the macroscale, the brain operates as a network of interconnected neuronal populations, which display coordinated rhythmic dynamics that support interareal communication. Understanding how stimulation of different brain areas impacts such activity is important for gaining basic insights into brain function and for further developing therapeutic neurmodulation. However, the complexity of brain structure and dynamics hinders predictions regarding the downstream effects of focal stimulation. More specifically, little is known about how the collective oscillatory regime of brain network activity—in concert with network structure—affects the outcomes of perturbations. Here, we combine human connectome data and biophysical modeling to begin filling these gaps. By tuning parameters that control collective system dynamics, we identify distinct states of simulated brain activity and investigate how the distributed effects of stimulation manifest at different dynamical working points. When baseline oscillations are weak, the stimulated area exhibits enhanced power and frequency, and due to network interactions, activity in this excited frequency band propagates to nearby regions. Notably, beyond these linear effects, we further find that focal stimulation causes more distributed modifications to interareal coherence in a band containing regions’ baseline oscillation frequencies. Importantly, depending on the dynamical state of the system, these broadband effects can be better predicted by functional rather than structural connectivity, emphasizing a complex interplay between anatomical organization, dynamics, and response to perturbation. In contrast, when the network operates in a regime of strong regional oscillations, stimulation causes only slight shifts in power and frequency, and structural connectivity becomes most predictive of stimulation-induced changes in network activity patterns. In sum, this work builds upon and extends previous computational studies investigating the impacts of stimulation, and underscores the fact that both the stimulation site, and, crucially, the regime of brain network dynamics, can influence the network-wide responses to local perturbations.

Stimulation can be used to alter brain activity and is a therapeutic option for certain neurological conditions. However, predicting the distributed effects of local perturbations is difficult. Previous studies show that responses to stimulation depend on anatomical (or structural) coupling. In addition to structure, here we consider how stimulation effects also depend on the brain’s collective dynamical (or functional) state, arising from the coordination of rhythmic activity across large-scale networks. In a whole-brain computational model, we show that global responses to regional stimulation can indeed be contingent upon and differ across various dynamical working points. Notably, depending on the network’s oscillatory regime, stimulation can accelerate the activity of the stimulated site, and lead to widespread effects at both the new, excited frequency, as well as in a much broader frequency range including areas’ baseline frequencies. While structural connectivity is a good predictor of “excited band” changes, in some states “baseline band” effects can be better predicted by functional connectivity, which depends upon the system’s oscillatory regime. By integrating and extending past efforts, our results thus indicate that dynamical—in additional to structural—brain organization plays a role in governing how focal stimulation modulates interactions between distributed network elements.

Transcranial electric stimulation as a neural interface to gain insight on human brain functions: current knowledge and future perspective

The use of brain-stimulation approaches in social and affective science has greatly increased over the last two decades. The interest in social factors has grown along with technological advances in brain research. Transcranial electric stimulation (tES) is a research tool that allows scientists to establish contributory causality between brain functioning and social behaviour, therefore deepening our understanding of the social mind. Preliminary evidence is also starting to demonstrate that tES, either alone or in combination with pharmacological or behavioural interventions, can alleviate the symptomatology of individuals with affective or social cognition disorders. This review offers an overview of the application of tES in the field of social and affective neuroscience. We discuss issues and challenges related to this application and suggest avenue for future basic and translational research.

Non-invasive Brain Stimulation of the Posterior Parietal Cortex Alters Postural Adaptation

Effective central sensory integration of visual, vestibular, and proprioceptive information is required to promote adaptability in response to changes in the environment during postural control. Patients with a lesion in the posterior parietal cortex (PPC) have an impaired ability to form an internal representation of body position, an important factor for postural control and adaptation. Suppression of PPC excitability has also been shown to decrease postural stability in some contexts. As of yet, it is unknown whether stimulation of the PPC may influence postural adaptation. This investigation aimed to identify whether transcranial direct current stimulation (tDCS) of the bilateral PPC could modulate postural adaptation in response to a bipedal incline postural adaptation task. Using young, healthy subjects, we delivered tDCS over bilateral PPC followed by bouts of inclined stance (incline-interventions). Analysis of postural after-effects identified differences between stimulation conditions for maximum lean after-effect (LAE; p = 0.005) as well as a significant interaction between condition and measurement period for the average position (p = 0.03). We identified impaired postural adaptability following both active stimulation conditions. Results reinforce the notion that the PPC is involved in motor adaptation and extend this line of research to the realm of standing posture. The results further highlight the role of the bilateral PPC in utilizing sensory feedback to update one's internal representation of verticality and demonstrates the diffuse regions of the brain that are involved in postural control and adaptation. This information improves our understanding of the role of the cortex in postural control, highlighting the potential for the PPC as a target for sensorimotor rehabilitation.

The visual system as target of non-invasive brain stimulation for migraine treatment: Current insights and future challenges

The visual network is crucially implicated in the pathophysiology of migraine. Several lines of evidence indicate that migraine is characterized by an altered visual cortex excitability both during and between attacks. Visual symptoms, the most common clinical manifestation of migraine aura, are likely the result of cortical spreading depression originating from the extrastriate area V3A. Photophobia, a clinical hallmark of migraine, is linked to an abnormal sensory processing of the thalamus which is converged with the non-image forming visual pathway. Finally, visual snow is an increasingly recognized persistent visual phenomenon in migraine, possibly caused by increased perception of subthreshold visual stimuli. Emerging research in non-invasive brain stimulation (NIBS) has vastly developed into a diversity of areas with promising potential. One of its clinical applications is the single-pulse transcranial magnetic stimulation (sTMS) applied over the occipital cortex which has been approved for treating migraine with aura, albeit limited evidence. Studies have also investigated other NIBS techniques, such as repetitive TMS (rTMS) and transcranial direct current stimulation (tDCS), for migraine prophylaxis but with conflicting results. As a dynamic brain disorder with widespread pathophysiology, targeting migraine with NIBS is challenging. Furthermore, unlike the motor cortex, evidence suggests that the visual cortex may be less plastic. Controversy exists as to whether the same fundamental principles of NIBS, based mainly on findings in the motor cortex, can be applied to the visual cortex. This review aims to explore existing literature surrounding NIBS studies on the visual system of migraine. We will first provide an overview highlighting the direct implication of the visual network in migraine. Next, we will focus on the rationale behind using NIBS for migraine treatment, including its effects on the visual cortex, and the shortcomings of currently available evidence. Finally, we propose a broader perspective of how novel approaches, the concept of brain networks and the integration of multimodal imaging with computational modeling, can help refine current NIBS methods, with the ultimate goal of optimizing a more individualized treatment for migraine.

Inferring Causality from Noninvasive Brain Stimulation in Cognitive Neuroscience

Noninvasive brain stimulation (NIBS) techniques, such as transcranial magnetic stimulation or transcranial direct and alternating current stimulation, are advocated as measures to enable causal inference in cognitive neuroscience experiments. Transcending the limitations of purely correlative neuroimaging measures and experimental sensory stimulation, they allow to experimentally manipulate brain activity and study its consequences for perception, cognition, and eventually, behavior. Although this is true in principle, particular caution is advised when interpreting brain stimulation experiments in a causal manner. Research hypotheses are often oversimplified, disregarding the underlying (implicitly assumed) complex chain of causation, namely, that the stimulation technique has to generate an electric field in the brain tissue, which then evokes or modulates neuronal activity both locally in the target region and in connected remote sites of the network, which in consequence affects the cognitive function of interest and eventually results in a change of the behavioral measure. Importantly, every link in this causal chain of effects can be confounded by several factors that have to be experimentally eliminated or controlled to attribute the observed results to their assumed cause. This is complicated by the fact that many of the mediating and confounding variables are not directly observable and dose-response relationships are often nonlinear. We will walk the reader through the chain of causation for a generic cognitive neuroscience NIBS study, discuss possible confounds, and advise appropriate control conditions. If crucial assumptions are explicitly tested (where possible) and confounds are experimentally well controlled, NIBS can indeed reveal cause-effect relationships in cognitive neuroscience studies.

Cortical excitability controls the strength of mental imagery

Mental imagery provides an essential simulation tool for remembering the past and planning the future, with its strength affecting both cognition and mental health. Research suggests that neural activity spanning prefrontal, parietal, temporal, and visual areas supports the generation of mental images. Exactly how this network controls the strength of visual imagery remains unknown. Here, brain imaging and transcranial magnetic phosphene data show that lower resting activity and excitability levels in early visual cortex (V1-V3) predict stronger sensory imagery. Further, electrically decreasing visual cortex excitability using tDCS increases imagery strength, demonstrating a causative role of visual cortex excitability in controlling visual imagery. Together, these data suggest a neurophysiological mechanism of cortical excitability involved in controlling the strength of mental images.

Beyond the target area: an integrative view of tDCS-induced motor cortex modulation in patients and athletes

Transcranial Direct Current Stimulation (tDCS) is a non-invasive technique used to modulate neural tissue. Neuromodulation apparently improves cognitive functions in several neurologic diseases treatment and sports performance. In this study, we present a comprehensive, integrative review of tDCS for motor rehabilitation and motor learning in healthy individuals, athletes and multiple neurologic and neuropsychiatric conditions. We also report on neuromodulation mechanisms, main applications, current knowledge including areas such as language, embodied cognition, functional and social aspects, and future directions. We present the use and perspectives of new developments in tDCS technology, namely high-definition tDCS (HD-tDCS) which promises to overcome one of the main tDCS limitation (i.e., low focality) and its application for neurological disease, pain relief, and motor learning/rehabilitation. Finally, we provided information regarding the Transcutaneous Spinal Direct Current Stimulation (tsDCS) in clinical applications, Cerebellar tDCS (ctDCS) and its influence on motor learning, and TMS combined with electroencephalography (EEG) as a tool to evaluate tDCS effects on brain function.

Intracortical Dynamics Underlying Repetitive Stimulation Predicts Changes in Network Connectivity

Targeted stimulation can be used to modulate the activity of brain networks. Previously we demonstrated that direct electrical stimulation produces predictable poststimulation changes in brain excitability. However, understanding the neural dynamics during stimulation and its relationship to poststimulation effects is limited but critical for treatment optimization. Here, we applied 10 Hz direct electrical stimulation across several cortical regions in 14 human subjects (6 males) implanted with intracranial electrodes for seizure monitoring. The stimulation train was characterized by a consistent increase in high gamma (70-170 Hz) power. Immediately post-train, low-frequency (1-8 Hz) power increased, resulting in an evoked response that was highly correlated with the neural response during stimulation. Using two measures of network connectivity, corticocortical evoked potentials (indexing effective connectivity), and theta coherence (indexing functional connectivity), we found a stronger response to stimulation in regions that were highly connected to the stimulation site. In these regions, repeated cycles of stimulation trains and rest progressively altered the stimulation response. Finally, after just 2 min (∼10%) of repetitive stimulation, we were able to predict poststimulation connectivity changes with high discriminability. Together, this work reveals a relationship between stimulation dynamics and poststimulation connectivity changes in humans. Thus, measuring neural activity during stimulation can inform future plasticity-inducing protocols.SIGNIFICANCE STATEMENT Brain stimulation tools have the potential to revolutionize the treatment of neuropsychiatric disorders. Despite the widespread use of brain stimulation techniques such as transcranial magnetic stimulation, the therapeutic efficacy of these technologies remains suboptimal. This is in part because of a lack of understanding of the dynamic neural changes that occur during stimulation. In this study, we provide the first detailed characterization of neural activity during plasticity induction through intracranial electrode stimulation and recording in 14 medication-resistant epilepsy patients. These results fill a missing gap in our understanding of stimulation-induced plasticity in humans. In the longer-term, these data will also guide our translational efforts toward non-invasive, personalized, closed-loop neuromodulation therapy for neurological and psychiatric disorders in humans.

State-Dependent Changes in Brain Glycogen Metabolism

A fundamental understanding of glycogen structure, concentration, polydispersity and turnover is critical to qualify the role of glycogen in the brain. These molecular and metabolic features are under the control of neuronal activity through the interdependent action of neuromodulatory tone, ionic homeostasis and availability of metabolic substrates, all variables that concur to define the state of the system. In this chapter, we briefly describe how glycogen responds to selected behavioral, nutritional, environmental, hormonal, developmental and pathological conditions. We argue that interpreting glycogen metabolism through the lens of brain state is an effective approach to establish the relevance of energetics in connecting molecular and cellular neurophysiology to behavior.