Neuroanatomical Predictors of Transcranial Direct Current Stimulation (tDCS)-Induced Modifications in Neurocognitive Task Performance in Typically Developing Individuals.

Transcranial direct current stimulation (tDCS) is a noninvasive neuromodulation technique gaining more attention in neurodevelopmental disorders (NDDs). Due to the phenotypic heterogeneity of NDDs, tDCS is unlikely to be equally effective in all individuals. The present study aimed to establish neuroanatomical markers in typically developing (TD) individuals that may be used for the prediction of individual responses to tDCS. Fifty-seven male and female children received 2 mA anodal and sham tDCS, targeting the left dorsolateral prefrontal cortex (DLPFCleft), right inferior frontal gyrus, and bilateral temporoparietal junction. Response to tDCS was assessed based on task performance differences between anodal and sham tDCS in different neurocognitive tasks (N-back, flanker, Mooney faces detection, attentional emotional recognition task). Measures of cortical thickness (CT) and surface area (SA) were derived from 3 Tesla structural MRI scans. Associations between neuroanatomy and task performance were assessed using general linear models (GLM). Machine learning (ML) algorithms were employed to predict responses to tDCS. Vertex-wise estimates of SA were more closely linked to differences in task performance than measures of CT. Across ML algorithms, highest accuracies were observed for the prediction of N-back task performance differences following stimulation of the DLPFCleft, where 65% of behavioral variance was explained by variability in SA. Lower accuracies were observed for all other tasks and stimulated regions. This suggests that it may be possible to predict individual responses to tDCS for some behavioral measures and target regions. In the future, these models might be extended to predict treatment outcome in individuals with NDDs.

Complex spatiotemporal oscillations emerge from transverse instabilities in large-scale brain networks.

Spatiotemporal oscillations underlie all cognitive brain functions. Large-scale brain models, constrained by neuroimaging data, aim to trace the principles underlying such macroscopic neural activity from the intricate and multi-scale structure of the brain. Despite substantial progress in the field, many aspects about the mechanisms behind the onset of spatiotemporal neural dynamics are still unknown. In this work we establish a simple framework for the emergence of complex brain dynamics, including high-dimensional chaos and travelling waves. The model consists of a complex network of 90 brain regions, whose structural connectivity is obtained from tractography data. The activity of each brain area is governed by a Jansen neural mass model and we normalize the total input received by each node so it amounts the same across all brain areas. This assumption allows for the existence of an homogeneous invariant manifold, i.e., a set of different stationary and oscillatory states in which all nodes behave identically. Stability analysis of these homogeneous solutions unveils a transverse instability of the synchronized state, which gives rise to different types of spatiotemporal dynamics, such as chaotic alpha activity. Additionally, we illustrate the ubiquity of this route towards complex spatiotemporal activity in a network of next generation neural mass models. Altogehter, our results unveil the bifurcation landscape that underlies the emergence of function from structure in the brain.

LSD-induced increase of Ising temperature and algorithmic complexity of brain dynamics.

A topic of growing interest in computational neuroscience is the discovery of fundamental principles underlying global dynamics and the self-organization of the brain. In particular, the notion that the brain operates near criticality has gained considerable support, and recent work has shown that the dynamics of different brain states may be modeled by pairwise maximum entropy Ising models at various distances from a phase transition, i.e., from criticality. Here we aim to characterize two brain states (psychedelics-induced and placebo) as captured by functional magnetic resonance imaging (fMRI), with features derived from the Ising spin model formalism (system temperature, critical point, susceptibility) and from algorithmic complexity. We hypothesized, along the lines of the entropic brain hypothesis, that psychedelics drive brain dynamics into a more disordered state at a higher Ising temperature and increased complexity. We analyze resting state blood-oxygen-level-dependent (BOLD) fMRI data collected in an earlier study from fifteen subjects in a control condition (placebo) and during ingestion of lysergic acid diethylamide (LSD). Working with the automated anatomical labeling (AAL) brain parcellation, we first create "archetype" Ising models representative of the entire dataset (global) and of the data in each condition. Remarkably, we find that such archetypes exhibit a strong correlation with an average structural connectome template obtained from dMRI (r = 0.6). We compare the archetypes from the two conditions and find that the Ising connectivity in the LSD condition is lower than in the placebo one, especially in homotopic links (interhemispheric connectivity), reflecting a significant decrease of homotopic functional connectivity in the LSD condition. The global archetype is then personalized for each individual and condition by adjusting the system temperature. The resulting temperatures are all near but above the critical point of the model in the paramagnetic (disordered) phase. The individualized Ising temperatures are higher in the LSD condition than in the placebo condition (p = 9 × 10-5). Next, we estimate the Lempel-Ziv-Welch (LZW) complexity of the binarized BOLD data and the synthetic data generated with the individualized model using the Metropolis algorithm for each participant and condition. The LZW complexity computed from experimental data reveals a weak statistical relationship with condition (p = 0.04 one-tailed Wilcoxon test) and none with Ising temperature (r(13) = 0.13, p = 0.65), presumably because of the limited length of the BOLD time series. Similarly, we explore complexity using the block decomposition method (BDM), a more advanced method for estimating algorithmic complexity. The BDM complexity of the experimental data displays a significant correlation with Ising temperature (r(13) = 0.56, p = 0.03) and a weak but significant correlation with condition (p = 0.04, one-tailed Wilcoxon test). This study suggests that the effects of LSD increase the complexity of brain dynamics by loosening interhemispheric connectivity-especially homotopic links. In agreement with earlier work using the Ising formalism with BOLD data, we find the brain state in the placebo condition is already above the critical point, with LSD resulting in a shift further away from criticality into a more disordered state.

Optimised Multi-Channel Transcranial Direct Current Stimulation (MtDCS) Reveals Differential Involvement of the Right-Ventrolateral Prefrontal Cortex (rVLPFC) and Insular Complex in those Predisposed to Aberrant Experiences.

Research has shown a prominent role for cortical hyperexcitability underlying aberrant perceptions, hallucinations, and distortions in human conscious experience - even in neurotypical groups. The rVLPFC has been identified as an important structure in mediating cognitive affective states / feeling conscious states. The current study examined the involvement of the rVLPFC in mediating cognitive affective states in those predisposed to aberrant experiences in the neurotypical population. Participants completed two trait-based measures: (i) the Cortical Hyperexcitability Index_II (CHi_II, a proxy measure of cortical hyperexcitability) and (ii) two factors from the Cambridge Depersonalisation Scale (CDS). An optimised 7-channel MtDCS montage for stimulation conditions (Anodal, Cathodal and Sham) was created targeting the rVLPFC in a single-blind study. At the end of each stimulation session, participants completed a body-threat task (BTAB) while skin conductance responses (SCRs) and psychological responses were recorded. Participants with signs of increasing cortical hyperexcitability showed significant suppression of SCRs in the Cathodal stimulation relative to the Anodal and sSham conditions. Those high on the trait-based measures of depersonalisation-like experiences failed to show reliable effects. Collectively, the findings suggest that baseline brain states can mediate the effects of neurostimulation which would be missed via sample level averaging and without appropriate measures for stratifying individual differences.

Neural Geometrodynamics, Complexity, and Plasticity: A Psychedelics Perspective.

We explore the intersection of neural dynamics and the effects of psychedelics in light of distinct timescales in a framework integrating concepts from dynamics, complexity, and plasticity. We call this framework neural geometrodynamics for its parallels with general relativity's description of the interplay of spacetime and matter. The geometry of trajectories within the dynamical landscape of "fast time" dynamics are shaped by the structure of a differential equation and its connectivity parameters, which themselves evolve over "slow time" driven by state-dependent and state-independent plasticity mechanisms. Finally, the adjustment of plasticity processes (metaplasticity) takes place in an "ultraslow" time scale. Psychedelics flatten the neural landscape, leading to heightened entropy and complexity of neural dynamics, as observed in neuroimaging and modeling studies linking increases in complexity with a disruption of functional integration. We highlight the relationship between criticality, the complexity of fast neural dynamics, and synaptic plasticity. Pathological, rigid, or "canalized" neural dynamics result in an ultrastable confined repertoire, allowing slower plastic changes to consolidate them further. However, under the influence of psychedelics, the destabilizing emergence of complex dynamics leads to a more fluid and adaptable neural state in a process that is amplified by the plasticity-enhancing effects of psychedelics. This shift manifests as an acute systemic increase of disorder and a possibly longer-lasting increase in complexity affecting both short-term dynamics and long-term plastic processes. Our framework offers a holistic perspective on the acute effects of these substances and their potential long-term impacts on neural structure and function.

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.

Targeted tDCS Mitigates Dual-Task Costs to Gait and Balance in Older Adults.

OBJECTIVE: Among older adults, the ability to stand or walk while performing cognitive tasks (ie, dual-tasking) requires coordinated activation of several brain networks. In this multicenter, double-blinded, randomized, and sham-controlled study, we examined the effects of modulating the excitability of the left dorsolateral prefrontal cortex (L-DLPFC) and the primary sensorimotor cortex (SM1) on dual-task performance "costs" to standing and walking. METHODS: Fifty-seven older adults without overt illness or disease completed 4 separate study visits during which they received 20 minutes of transcranial direct current stimulation (tDCS) optimized to facilitate the excitability of the L-DLPFC and SM1 simultaneously, or each region separately, or neither region (sham). Before and immediately after stimulation, participants completed a dual-task paradigm in which they were asked to stand and walk with and without concurrent performance of a serial-subtraction task. RESULTS: tDCS simultaneously targeting the L-DLPFC and SM1, as well as tDCS targeting the L-DLPFC alone, mitigated dual-task costs to standing and walking to a greater extent than tDCS targeting SM1 alone or sham (p < 0.02). Blinding efficacy was excellent and participant subjective belief in the type of stimulation received (real or sham) did not contribute to the observed functional benefits of tDCS. INTERPRETATION: These results demonstrate that in older adults, dual-task decrements may be amenable to change and implicate L-DPFC excitability as a modifiable component of the control system that enables dual-task standing and walking. tDCS may be used to improve resilience and the ability of older results to walk and stand under challenging conditions, potentially enhancing everyday functioning and reducing fall risks. ANN NEUROL 2021;90:428-439.

Local and Distributed fMRI Changes Induced by 40 Hz Gamma tACS of the Bilateral Dorsolateral Prefrontal Cortex: A Pilot Study.

Over the past few years, the possibility of modulating fast brain oscillatory activity in the gamma (γ) band through transcranial alternating current stimulation (tACS) has been discussed in the context of both cognitive enhancement and therapeutic scenarios. However, the effects of tACS targeting regions outside the motor cortex, as well as its spatial specificity, are still unclear. Here, we present a concurrent tACS-fMRI block design study to characterize the impact of 40 Hz tACS applied over the left and right dorsolateral prefrontal cortex (DLPFC) in healthy subjects. Results suggest an increase in blood oxygenation level-dependent (BOLD) activity in the targeted bilateral DLPFCs, as well as in surrounding brain areas affected by stimulation according to biophysical modeling, i.e., the premotor cortex and anterior cingulate cortex (ACC). However, off-target effects were also observed, primarily involving the visual cortices, with further effects on the supplementary motor areas (SMA), left subgenual cingulate, and right superior temporal gyrus. The specificity of 40 Hz tACS over bilateral DLPFC and the possibility for network-level effects should be considered in future studies, especially in the context of recently promoted gamma-induction therapeutic protocols for neurodegenerative disorders.

Drug-Responsive Inhomogeneous Cortical Modulation by Direct Current Stimulation.

OBJECTIVE: Cathodal direct current stimulation (cDCS) induces long-term depression (LTD)-like reduction of cortical excitability (DCS-LTD), which has been tested in the treatment of epilepsy with modest effects. In part, this may be due to variable cortical neuron orientation relative to the electric field. We tested, in vivo and in vitro, whether DCS-LTD occurs throughout the cortical thickness, and if not, then whether drug-DCS pairing can enhance the uniformity of the cortical response and the cDCS antiepileptic effect. METHODS: cDCS-mediated changes in cortical excitability were measured in vitro in mouse motor cortex (M1) and in human postoperative neocortex, in vivo in mouse somatosensory cortex (S1), and in a mouse kainic acid (KA)-seizure model. Contributions of N-methyl-D-aspartate-type glutamate receptors (NMDARs) to cDCS-mediated plasticity were tested with application of NMDAR blockers (memantine/D-AP5). RESULTS: cDCS reliably induced DCS-LTD in superficial cortical layers, and a long-term potentiation (LTP)-like enhancement (DCS-LTP) was recorded in deep cortical layers. Immunostaining confirmed layer-specific increase of phospho-S6 ribosomal protein in mouse M1. Similar nonuniform cDCS aftereffects on cortical excitability were also found in human neocortex in vitro and in S1 of alert mice in vivo. Application of memantine/D-AP5 either produced a more uniform DCS-LTD throughout the cortical thickness or at least abolished DCS-LTP. Moreover, a combination of memantine and cDCS suppressed KA-induced seizures. INTERPRETATION: cDCS aftereffects are not uniform throughout cortical layers, which may explain the incomplete cDCS clinical efficacy. NMDAR antagonists may augment cDCS efficacy in epilepsy and other disorders where regional depression of cortical excitability is desirable. ANN NEUROL 2020;88:489-502.

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.

Impact of network-targeted multichannel transcranial direct current stimulation on intrinsic and network-to-network functional connectivity.

Dynamics within and between functional resting-state networks have a crucial role in determining both healthy and pathological brain functioning in humans. The possibility to noninvasively interact and selectively modulate the activity of networks would open to relevant applications in neuroscience. Here we tested a novel approach for multichannel, network-targeted transcranial direct current stimulation (net-tDCS), optimized to increase excitability of the sensorimotor network (SMN) while inducing cathodal inhibitory modulation over prefrontal and parietal brain regions negatively correlated with the SMN. Using an MRI-compatible multichannel transcranial electrical stimulation (tES) device, 20 healthy participants underwent real and sham tDCS while at rest in the MRI scanner. Changes in functional connectivity (FC) during and after stimulation were evaluated, looking at the intrinsic FC of the SMN and the strength of the negative connectivity between SMN and the rest of the brain. Standard, bifocal tDCS targeting left motor cortex (electrode ~C3) and right frontopolar (~Fp2) regions was tested as a control condition in a separate sample of healthy subjects to investigate network specificity of multichannel stimulation effects. Net-tDCS induced greater FC increase over the SMN compared to bifocal tDCS, during and after stimulation. Moreover, exploratory analysis of the impact of net-tDCS on negatively correlated networks showed an increase in the negative connectivity between SMN and prefrontal/parietal areas targeted by cathodal stimulation both during and after real net-tDCS. Results suggest preliminary evidence of the possibility of manipulating distributed network connectivity patterns through net-tDCS, with potential relevance for the development of cognitive enhancement and therapeutic tES solutions.

Intermittent tACS during a visual task impacts neural oscillations and LZW complexity.

Little is known about how transcranial alternating current stimulation (tACS) interacts with brain activity. Here, we investigate the effects of tACS using an intermittent tACS-EEG protocol and use, in addition to classical metrics, Lempel-Ziv-Welch complexity (LZW) to characterize the interactions between task, endogenous and exogenous oscillations. In a cross-over study, EEG was recorded from thirty participants engaged in a change-of-speed detection task while receiving multichannel tACS over the visual cortex at 10 Hz, 70 Hz and a control condition. In each session, tACS was applied intermittently during 5 s events interleaved with EEG recordings over multiple trials. We found that, with respect to control, stimulation at 10 Hz ([Formula: see text]) enhanced both [Formula: see text] and [Formula: see text] power, [Formula: see text]-LZW complexity and [Formula: see text] but not [Formula: see text] phase locking value with respect to tACS onset ([Formula: see text]-PLV, [Formula: see text]-PLV), and increased reaction time (RT). [Formula: see text] increased RT with little impact on other metrics. As trials associated with larger [Formula: see text]-power (and lower [Formula: see text]-LZW) predicted shorter RT, we argue that [Formula: see text] produces a disruption of functionally relevant fast oscillations through an increase in [Formula: see text]-band power, slowing behavioural responses and increasing the complexity of gamma oscillations. Our study highlights the complex interaction between tACS and endogenous brain dynamics, and suggests the use of algorithmic complexity inspired metrics to characterize cortical dynamics in a behaviorally relevant timescale.

Multitarget transcranial direct current stimulation for freezing of gait in Parkinson's disease.

BACKGROUND: Recent findings suggest that transcranial direct current stimulation of the primary motor cortex may ameliorate freezing of gait. However, the effects of multitarget simultaneous stimulation of motor and cognitive networks are mostly unknown. The objective of this study was to evaluate the effects of multitarget transcranial direct current stimulation of the primary motor cortex and left dorsolateral prefrontal cortex on freezing of gait and related outcomes. METHODS: Twenty patients with Parkinson's disease and freezing of gait received 20 minutes of transcranial direct current stimulation on 3 separate visits. Transcranial direct current stimulation targeted the primary motor cortex and left dorsolateral prefrontal cortex simultaneously, primary motor cortex only, or sham stimulation (order randomized and double-blinded assessments). Participants completed a freezing of gait-provoking test, the Timed Up and Go, and the Stroop test before and after each transcranial direct current stimulation session. RESULTS: Performance on the freezing of gait-provoking test (P = 0.010), Timed Up and Go (P = 0.006), and the Stroop test (P = 0.016) improved after simultaneous stimulation of the primary motor cortex and left dorsolateral prefrontal cortex, but not after primary motor cortex only or sham stimulation. CONCLUSIONS: Transcranial direct current stimulation designed to simultaneously target motor and cognitive regions apparently induces immediate aftereffects in the brain that translate into reduced freezing of gait and improvements in executive function and mobility. © 2018 International Parkinson and Movement Disorder Society.

Intensity dependent effects of transcranial direct current stimulation on corticospinal excitability in chronic spinal cord injury.

OBJECTIVE: To investigate the effects of anodal transcranial direct current stimulation (a-tDCS) intensity on corticospinal excitability and affected muscle activation in individuals with chronic spinal cord injury (SCI). DESIGN: Single-blind, randomized, sham-controlled, crossover study. SETTING: Medical research institute and rehabilitation hospital. PARTICIPANTS: Volunteers (N = 9) with chronic SCI and motor dysfunction in wrist extensor muscles. INTERVENTIONS: Three single session exposures to 20 minutes of a-tDCS (anode over the extensor carpi radialis [ECR] muscle representation on the left primary motor cortex, cathode over the right supraorbital area) using 1 mA, 2 mA, or sham stimulation, delivered at rest, with at least 1 week between sessions. MAIN OUTCOME MEASURES: Corticospinal excitability was assessed with motor-evoked potentials (MEPs) from the ECR muscle using surface electromyography after transcranial magnetic stimulation. Changes in spinal excitability, sensory threshold, and muscle strength were also investigated. RESULTS: Mean MEP amplitude significantly increased by approximately 40% immediately after 2mA a-tDCS (pre: 0.36 ± 0.1 mV; post: 0.47 ± 0.11 mV; P = .001), but not with 1 mA or sham. Maximal voluntary contraction measures remained unaltered across all conditions. Sensory threshold significantly decreased over time after 1mA (P = .002) and 2mA (P = .039) a-tDCS and did not change with sham. F-wave persistence showed a nonsignificant trend for increase (pre: 32% ± 12%; post: 41% ± 10%; follow-up: 46% ± 12%) after 2 mA stimulation. No adverse effects were reported with any of the experimental conditions. CONCLUSIONS: The a-tDCS can transiently raise corticospinal excitability to affected muscles in patients with chronic SCI after 2 mA stimulation. Sensory perception can improve with both 1 and 2 mA stimulation. This study gives support to the safe and effective use of a-tDCS using small electrodes in patients with SCI and highlights the importance of stimulation intensity.

Transcranial direct-current stimulation modulates synaptic mechanisms involved in associative learning in behaving rabbits.

Transcranial direct-current stimulation (tDCS) is a noninvasive brain stimulation technique that has been successfully applied for modulation of cortical excitability. tDCS is capable of inducing changes in neuronal membrane potentials in a polarity-dependent manner. When tDCS is of sufficient length, synaptically driven after-effects are induced. The mechanisms underlying these after-effects are largely unknown, and there is a compelling need for animal models to test the immediate effects and after-effects induced by tDCS in different cortical areas and evaluate the implications in complex cerebral processes. Here we show in behaving rabbits that tDCS applied over the somatosensory cortex modulates cortical processes consequent to localized stimulation of the whisker pad or of the corresponding area of the ventroposterior medial (VPM) thalamic nucleus. With longer stimulation periods, poststimulation effects were observed in the somatosensory cortex only after cathodal tDCS. Consistent with the polarity-specific effects, the acquisition of classical eyeblink conditioning was potentiated or depressed by the simultaneous application of anodal or cathodal tDCS, respectively, when stimulation of the whisker pad was used as conditioned stimulus, suggesting that tDCS modulates the sensory perception process necessary for associative learning. We also studied the putative mechanisms underlying immediate effects and after-effects of tDCS observed in the somatosensory cortex. Results when pairs of pulses applied to the thalamic VPM nucleus (mediating sensory input) during anodal and cathodal tDCS suggest that tDCS modifies thalamocortical synapses at presynaptic sites. Finally, we show that blocking the activation of adenosine A1 receptors prevents the long-term depression (LTD) evoked in the somatosensory cortex after cathodal tDCS.

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).

Multiscale neuro-inspired models for interpretation of EEG signals in patients with epilepsy.

OBJECTIVE: The aim is to gain insight into the pathophysiological mechanisms underlying interictal epileptiform discharges observed in electroencephalographic (EEG) and stereo-EEG (SEEG, depth electrodes) recordings performed during pre-surgical evaluation of patients with drug-resistant epilepsy. METHODS: We developed novel neuro-inspired computational models of the human cerebral cortex at three different levels of description: i) microscale (detailed neuron models), ii) mesoscale (neuronal mass models) and iii) macroscale (whole brain models). Although conceptually different, micro- and mesoscale models share some similar features, such as the typology of neurons (pyramidal cells and three types of interneurons), their spatial arrangement in cortical layers, and their synaptic connectivity (excitatory and inhibitory). The whole brain model consists of a large-scale network of interconnected neuronal masses, with connectivity based on the human connectome. RESULTS: For these three levels of description, the fine-tuning of free parameters and the quantitative comparison with real data allowed us to reproduce interictal epileptiform discharges with a high degree of fidelity and to formulate hypotheses about the cell- and network-related mechanisms underlying the generation of fast ripples and SEEG-recorded epileptic spikes and spike-waves. CONCLUSIONS: The proposed models provide valuable insights into the pathophysiological mechanisms underlying the generation of epileptic events. The knowledge gained from these models effectively complements the clinical analysis of SEEG data collected during the evaluation of patients with epilepsy. SIGNIFICANCE: These models are likely to play a key role in the mechanistic interpretation of epileptiform activity.

Multichannel tDCS with Advanced Targeting for Major Depressive Disorder: A Tele-Supervised At-Home Pilot Study.

Introduction: Proof-of-principle human studies suggest that transcranial direct current stimulation (tDCS) over the dorsolateral prefrontal cortex (DLPFC) may improve depression severity. This open-label multicenter study tested remotely supervised multichannel tDCS delivered at home in patients (N=35) with major depressive disorder (MDD). The primary aim was to assess the feasibility and safety of our protocol. As an exploratory aim, we evaluated therapeutic efficacy: the primary efficacy measure was the median percent change from baseline to the end of the 4-week post-treatment follow-up period in the observer-rated Montgomery-Asberg Depression Mood Rating Scale (MADRS). Methods: Participants received 37 at-home stimulation sessions (30 minutes each) of specifically designed multichannel tDCS targeting the left DLPFC administered over eight weeks (4 weeks of daily treatments plus 4 weeks of taper), with a follow-up period of 4 weeks following the final stimulation session. The stimulation montage (electrode positions and currents) was optimized by employing computational models of the electric field generated by multichannel tDCS using available structural data from a similar population (group optimization). Conducted entirely remotely, the study employed the MADRS for assessment at baseline, at weeks 4 and 8 during treatment, and at 4-week follow-up visits. Results: 34 patients (85.3% women) with a mean age of 59 years, a diagnosis of MDD according to DSM-5 criteria, and a MADRS score ≥20 at the time of study enrolment completed all study visits. At baseline, the mean time since MDD diagnosis was 24.0 (SD 19.1) months. Concerning compliance, 85% of the participants (n=29) completed the complete course of 37 stimulation sessions at home, while 97% completed at least 36 sessions. No detrimental effects were observed, including suicidal ideation and/or behavior. The study observed a median MADRS score reduction of 64.5% (48.6, 72.4) 4 weeks post-treatment (Hedge's g = -3.1). We observed a response rate (≥ 50% improvement in MADRS scores) of 72.7% (n=24) from baseline to the last visit 4 weeks post-treatment. Secondary measures reflected similar improvements. Conclusions: These results suggest that remotely supervised and supported multichannel home-based tDCS is safe and feasible, and antidepressant efficacy motivates further appropriately controlled clinical studies.

Network-targeted transcranial direct current stimulation of the hypothalamus appetite-control network: a feasibility study.

The hypothalamus is the key regulator for energy homeostasis and is functionally connected to striatal and cortical regions vital for the inhibitory control of appetite. Hence, the ability to non-invasively modulate the hypothalamus network could open new ways for the treatment of metabolic diseases. Here, we tested a novel method for network-targeted transcranial direct current stimulation (net-tDCS) to influence the excitability of brain regions involved in the control of appetite. Based on the resting-state functional connectivity map of the hypothalamus, a 12-channel net-tDCS protocol was generated (Neuroelectrics Starstim system), which included anodal, cathodal and sham stimulation. Ten participants with overweight or obesity were enrolled in a sham-controlled, crossover study. During stimulation or sham control, participants completed a stop-signal task to measure inhibitory control. Overall, stimulation was well tolerated. Anodal net-tDCS resulted in faster stop signal reaction time (SSRT) compared to sham (p = 0.039) and cathodal net-tDCS (p = 0.042). Baseline functional connectivity of the target network correlated with SSRT after anodal compared to sham stimulation (p = 0.016). These preliminary data indicate that modulating hypothalamus functional network connectivity via net-tDCS may result in improved inhibitory control. Further studies need to evaluate the effects on eating behavior and metabolism.