Can individually targeted and optimized multi-channel tDCS outperform standard bipolar tDCS in stimulating the primary somatosensory cortex?

Addressing the sources of inter-subject variability in E-field parameters in anodal tDCS stimulation over motor cortical network

Objetive: .Although transcranial direct current stimulation constitutes a non-invasive neuromodulation technique with promising results in a great variety of applications, its clinical implementation is compromised by the high inter-subject variability reported. This study aims to analyze the inter-subject variability in electric fields (E-fields) over regions of the cortical motor network under two electrode montages: the classical C3Fp2 and an alternative P3F3, which confines more the E-field over this region.Approach.Computational models of the head of 98 healthy subjects were developed to simulate the E-field under both montages. E-field parameters such as magnitude, focality and orientation were calculated over three regions of interest (ROI): M1S1, supplementary motor area (SMA) and preSMA. The role of anatomical characteristics as a source of inter-subject variability on E-field parameters and individualized stimulation intensity were addressed using linear mixed-effect models.Main results.P3F3 showed a more confined E-field distribution over M1S1 than C3Fp2; the latter elicited higher E-fields over supplementary motor areas. Both montages showed high inter-subject variability, especially for the normal component over C3Fp2. Skin, bone and CSF ROI volumes showed a negative association with E-field magnitude irrespective of montage. Grey matter volume and montage were the main sources of variability for focality. The curvature of gyri was found to be significantly associated with the variability of normal E-fields.Significance.Computational modeling proves useful in the assessment of E-field variability. Our simulations predict significant differences in E-field magnitude and focality for C3Fp2 and P3F3. However, anatomical characteristics were also found to be significant sources of E-field variability irrespective of electrode montage. The normal E-field component better captured the individual variability and low rate of responder subjects observed in experimental studies.

Exciting the social butterfly: Anodal cerebellar transcranial direct current stimulation modulates neural activation during predictive social mentalizing

Transcranial Direct Current Stimulation (tDCS) has emerged as a promising tool for enhancing social cognition. The posterior cerebellum, which is part of the mentalizing network, has been implicated in social processes. In our combined tDCS-fMRI study, we investigated the effects of offline anodal cerebellar tDCS on activation in the cerebellum during social action prediction. Forty-one participants were randomly assigned to receive either anodal (2 mA) or sham (0 mA) stimulation over the midline of the posterior cerebellum for 20 min. Twenty minutes post stimulation, participants underwent a functional MRI scan to complete a social action prediction task, during which they had to correctly order randomly presented sentences that described either actions of social agents (based on their personality traits) or events of objects (based on their characteristics). As hypothesized, our results revealed that participants who received anodal cerebellar tDCS exhibited increased activation in the posterior cerebellar Crus 2 and lobule IX, and in key cerebral mentalizing areas, including the medial prefrontal cortex, temporo-parietal junction, and precuneus. Contrary to our hypotheses, participants who received anodal stimulation demonstrated faster responses to non-social objects compared to social agents, while sham participants showed no significant differences. We did not find a significant relationship between electric field magnitude, neural activation and behavioral outcomes. These findings suggest that tDCS targeting the posterior cerebellum selectively enhances activation in social mentalizing areas, while only facilitating behavioral performance of non-social material, perhaps because of a ceiling effect due to familiarity with social processing.

Comparing the performance of beamformer algorithms in estimating orientations of neural sources

The efficacy of transcranial electric stimulation (tES) to effectively modulate neuronal activity depends critically on the spatial orientation of the targeted neuronal population. Therefore, precise estimation of target orientation is of utmost importance. Different beamforming algorithms provide orientation estimates; however, a systematic analysis of their performance is still lacking. For fixed brain locations, EEG and MEG data from sources with randomized orientations were simulated. The orientation was then estimated (1) with an EEG and (2) with a combined EEG-MEG approach. Three commonly used beamformer algorithms were evaluated with respect to their abilities to estimate the correct orientation: Unit-Gain (UG), Unit-Noise-Gain (UNG), and Array-Gain (AG) beamformer. Performance depends on the signal-to-noise ratios for the modalities and on the chosen beamformer. Overall, the UNG and AG beamformers appear as the most reliable. With increasing noise, the UG estimate converges to a vector determined by the leadfield, thus leading to insufficient orientation estimates.

Normative tDCS over V5 and FEF reveals practice-induced modulation of extraretinal smooth pursuit mechanisms, but no specific stimulation effect

The neural networks subserving smooth pursuit eye movements (SPEM) provide an ideal model for investigating the interaction of sensory processing and motor control during ongoing movements. To better understand core plasticity aspects of sensorimotor processing for SPEM, normative sham, anodal or cathodal transcranial direct current stimulation (tDCS) was applied over visual area V5 and frontal eye fields (FEF) in sixty healthy participants. The identical within-subject paradigm was used to assess SPEM modulations by practice. While no specific tDCS effects were revealed, within- and between-session practice effects indicate plasticity of top-down extraretinal mechanisms that mainly affect SPEM in the absence of visual input and during SPEM initiation. To explore the potential of tDCS effects, individual electric field simulations were computed based on calibrated finite element head models and individual functional localization of V5 and FEF location (using functional MRI) and orientation (using combined EEG/MEG) was conducted. Simulations revealed only limited electric field target intensities induced by the applied normative tDCS montages but indicate the potential efficacy of personalized tDCS for the modulation of SPEM. In sum, results indicate the potential susceptibility of extraretinal SPEM control to targeted external neuromodulation (e.g., personalized tDCS) and intrinsic learning protocols.

Sham-controlled randomized multicentre trial of transcranial direct current stimulation for prolonged disorders of consciousness

BACKGROUND AND PURPOSE

Transcranial direct current stimulation (tDCS) has been shown to improve signs of consciousness in a subset of patients with disorders of consciousness (DoC). However, no multicentre study confirmed its efficacy when applied during rehabilitation. In this randomized controlled double-blind study, the effects of tDCS whilst patients were in rehabilitation were tested at the group level and according to their diagnosis and aetiology to better target DoC patients who might repond to tDCS.

METHODS

Patients received 2 mA tDCS or sham applied over the left prefrontal cortex for 4 weeks. Behavioural assessments were performed weekly and up to 3 months' follow-up. Analyses were conducted at the group and subgroup levels based on the diagnosis (minimally conscious state [MCS] and unresponsive wakefulness syndrome) and the aetiology (traumatic or non-traumatic). Interim analyses were planned to continue or stop the trial.

RESULTS

The trial was stopped for futility when 62 patients from 10 centres were enrolled (44 ± 14 years, 37 ± 24.5 weeks post-injury, 18 women, 32 MCS, 39 non-traumatic). Whilst, at the group level, no treatment effect was found, the subgroup analyses at 3 months' follow-up revealed a significant improvement for patients in MCS and with traumatic aetiology.

CONCLUSIONS

Transcranial direct current stimulation during rehabilitation does not seem to enhance patients' recovery. However, diagnosis and aetiology appear to be important factors leading to a response to the treatment. These findings bring novel insights into possible cortical plasticity changes in DoC patients given these differential results according to the subgroups of patients.

Personalized alpha-tACS targeting left posterior parietal cortex modulates visuo-spatial attention and posterior evoked EEG activity

BACKGROUND

Covert visuo-spatial attention is marked by the anticipatory lateralization of neuronal alpha activity in the posterior parietal cortex. Previous applications of transcranial alternating current stimulation (tACS) at the alpha frequency, however, were inconclusive regarding the causal contribution of oscillatory activity during visuo-spatial attention.

OBJECTIVE

Attentional shifts of behavior and electroencephalography (EEG) after-effects were assessed in a cued visuo-spatial attention paradigm. We hypothesized that parietal alpha-tACS shifts attention relative to the ipsilateral visual hemifield. Furthermore, we assumed that modulations of behavior and neurophysiology are related to individual electric field simulations.

METHODS

We applied personalized tACS at alpha and gamma frequencies to elucidate the role of oscillatory neuronal activity for visuo-spatial attention. Personalized tACS montages were algorithmically optimized to target individual left and right parietal regions that were defined by an EEG localizer.

RESULTS

Behavioral performance in the left hemifield was specifically increased by alpha-tACS compared to gamma-tACS targeting the left parietal cortex. This hemisphere-specific effect was observed despite the symmetry of simulated electric fields. In addition, visual event-related potential (ERP) amplitudes showed a reduced lateralization over posterior sites induced by left alpha-tACS. Neuronal sources of this effect were localized in the left premotor cortex. Interestingly, accuracy modulations induced by left parietal alpha-tACS were directly related to electric field magnitudes in the left premotor cortex.

CONCLUSION

Overall, results corroborate the notion that alpha lateralization plays a causal role in covert visuo-spatial attention and indicate an increased susceptibility of parietal and premotor brain regions of the left dorsal attention network to subtle tACS-neuromodulation.

Machine-learning defined precision tDCS for improving cognitive function

BACKGROUND

Transcranial direct current stimulation (tDCS) paired with cognitive training (CT) is widely investigated as a therapeutic tool to enhance cognitive function in older adults with and without neurodegenerative disease. Prior research demonstrates that the level of benefit from tDCS paired with CT varies from person to person, likely due to individual differences in neuroanatomical structure.

OBJECTIVE

The current study aims to develop a method to objectively optimize and personalize current dosage to maximize the functional gains of non-invasive brain stimulation.

METHODS

A support vector machine (SVM) model was trained to predict treatment response based on computational models of current density in a sample dataset (n = 14). Feature weights of the deployed SVM were used in a weighted Gaussian Mixture Model (GMM) to maximize the likelihood of converting tDCS non-responders to responders by finding the most optimum electrode montage and applied current intensity (optimized models).

RESULTS

Current distributions optimized by the proposed SVM-GMM model demonstrated 93% voxel-wise coherence within target brain regions between the originally non-responders and responders. The optimized current distribution in original non-responders was 3.38 standard deviations closer to the current dose of responders compared to the pre-optimized models. Optimized models also achieved an average treatment response likelihood and normalized mutual information of 99.993% and 91.21%, respectively. Following tDCS dose optimization, the SVM model successfully predicted all tDCS non-responders with optimized doses as responders.

CONCLUSIONS

The results of this study serve as a foundation for a custom dose optimization strategy towards precision medicine in tDCS to improve outcomes in cognitive decline remediation for older adults.