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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 (DLPFC left ), 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 DLPFC left , 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., Competing Interests: The authors declare no competing financial interests., (Copyright © 2024 the authors.)

Transcranial Direct Current Stimulation (tDCS) is a non-invasive neuromodulation technique with a wide variety of clinical and research applications. As increasingly acknowledged, its effectiveness is subject dependent, which may lead to time consuming and cost ineffective treatment development phases. We propose the combination of electroencephalography (EEG) and unsupervised learning for the stratification and prediction of individual responses to tDCS. A randomized, sham-controlled, double-blind crossover study design was conducted within a clinical trial for the development of pediatric treatments based on tDCS. The tDCS stimulation (sham and active) was applied either in the left dorsolateral prefrontal cortex or in the right inferior frontal gyrus. Following the stimulation session, participants performed 3 cognitive tasks to assess the response to the intervention: the Flanker Task, N-Back Task and Continuous Performance Test (CPT). We used data from 56 healthy children and adolescents to implement an unsupervised clustering approach that stratify participants based on their resting-state EEG spectral features before the tDCS intervention. We then applied a correlational analysis to characterize the clusters of EEG profiles in terms of participant's difference in the behavioral outcome (accuracy and response time) of the cognitive tasks when performed after a tDCS-sham or a tDCS-active session. Better behavioral performance following the active tDCS session compared to the sham tDCS session is considered a positive intervention response, whilst the reverse is considered a negative one. Optimal results in terms of validity measures was obtained for 4 clusters. These results show that specific EEG-based digital phenotypes can be associated to particular responses. While one cluster presents neurotypical EEG activity, the remaining clusters present non-typical EEG characteristics, which seem to be associated with a positive response. Findings suggest that unsupervised machine learning can be successfully used to stratify and eventually predict responses of individuals to a tDCS treatment., (© 2023. The Author(s).)

Methodological studies investigating transcranial direct current stimulation (tDCS) over the left dorsolateral prefrontal cortex (lDLPFC) in paediatric populations are limited. Therefore, we investigated in a paediatric population whether stimulation success of multichannel tDCS over the lDLPFC depends on concurrent task performance and individual head anatomy. In a randomised, sham-controlled, double-blind crossover study 22 healthy participants (10-17 years) received 2 mA multichannel anodal tDCS (atDCS) over the lDLPFC with and without a 2-back working memory (WM) task. After stimulation, the 2-back task and a Flanker task were performed. Resting state and task-related EEG were recorded. In 16 participants we calculated the individual electric field (E-field) distribution. Performance and neurophysiological activity in the 2-back task were not affected by atDCS. atDCS reduced reaction times in the Flanker task, independent of whether atDCS had been combined with the 2-back task. Flanker task related beta oscillation increased following stimulation without 2-back task performance. atDCS effects were not correlated with the E-field. We found no effect of multichannel atDCS over the lDLPFC on WM in children/adolescents but a transfer effect on interference control. While this effect on behaviour was independent of concurrent task performance, neurophysiological activity might be more sensitive to cognitive activation during stimulation. However, our results are limited by the small sample size, the lack of an active control group and variations in WM performance., (© 2021. The Author(s).)

Background: Autism spectrum disorder (ASD) is characterized by impaired social communication and interaction, and stereotyped, repetitive behaviour and sensory interests. To date, there is no effective medication that can improve social communication and interaction in ASD, and effect sizes of behaviour-based psychotherapy remain in the low to medium range. Consequently, there is a clear need for new treatment options. ASD is associated with altered activation and connectivity patterns in brain areas which process social information. Transcranial direct current stimulation (tDCS) is a technique that applies a weak electrical current to the brain in order to modulate neural excitability and alter connectivity. Combined with specific cognitive tasks, it allows to facilitate and consolidate the respective training effects. Therefore, application of tDCS in brain areas relevant to social cognition in combination with a specific cognitive training is a promising treatment approach for ASD., Methods: A phase-IIa pilot randomized, double-blind, sham-controlled, parallel-group clinical study is presented, which aims at investigating if 10 days of 20-min multi-channel tDCS stimulation of the bilateral tempo-parietal junction (TPJ) at 2.0 mA in combination with a computer-based cognitive training on perspective taking, intention and emotion understanding, can improve social cognitive abilities in children and adolescents with ASD. The main objectives are to describe the change in parent-rated social responsiveness from baseline (within 1 week before first stimulation) to post-intervention (within 7 days after last stimulation) and to monitor safety and tolerability of the intervention. Secondary objectives include the evaluation of change in parent-rated social responsiveness at follow-up (4 weeks after end of intervention), change in other ASD core symptoms and psychopathology, social cognitive abilities and neural functioning post-intervention and at follow-up in order to explore underlying neural and cognitive mechanisms., Discussion: If shown, positive results regarding change in parent-rated social cognition and favourable safety and tolerability of the intervention will confirm tDCS as a promising treatment for ASD core-symptoms. This may be a first step in establishing a new and cost-efficient intervention for individuals with ASD., Trial Registration: The trial is registered with the German Clinical Trials Register (DRKS), DRKS00014732 . Registered on 15 August 2018., Protocol Version: This study protocol refers to protocol version 1.2 from 24 May 2019.