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1.
J Neurosci ; 44(22)2024 May 29.
Article in English | MEDLINE | ID: mdl-38548336

ABSTRACT

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.


Subject(s)
Magnetic Resonance Imaging , Transcranial Direct Current Stimulation , Humans , Male , Transcranial Direct Current Stimulation/methods , Female , Child , Adolescent , Cognition/physiology , Psychomotor Performance/physiology
2.
Trials ; 22(1): 248, 2021 Apr 06.
Article in English | MEDLINE | ID: mdl-33823927

ABSTRACT

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.


Subject(s)
Autism Spectrum Disorder , Transcranial Direct Current Stimulation , Adolescent , Autism Spectrum Disorder/diagnosis , Autism Spectrum Disorder/therapy , Brain , Child , Clinical Trials, Phase II as Topic , Double-Blind Method , Humans , Randomized Controlled Trials as Topic , Treatment Outcome
3.
Front Neurosci ; 12: 477, 2018.
Article in English | MEDLINE | ID: mdl-30061811

ABSTRACT

Deficits in the interpretation of others' intentions from gaze-direction or other social attention cues are well-recognized in ASD. Here we investigated whether an EEG brain computer interface (BCI) can be used to train social cognition skills in ASD patients. We performed a single-arm feasibility clinical trial and enrolled 15 participants (mean age 22y 2m) with high-functioning ASD (mean full-scale IQ 103). Participants were submitted to a BCI training paradigm using a virtual reality interface over seven sessions spread over 4 months. The first four sessions occurred weekly, and the remainder monthly. In each session, the subject was asked to identify objects of interest based on the gaze direction of an avatar. Attentional responses were extracted from the EEG P300 component. A final follow-up assessment was performed 6-months after the last session. To analyze responses to joint attention cues participants were assessed pre and post intervention and in the follow-up, using an ecologic "Joint-attention task." We used eye-tracking to identify the number of social attention items that a patient could accurately identify from an avatar's action cues (e.g., looking, pointing at). As secondary outcome measures we used the Autism Treatment Evaluation Checklist (ATEC) and the Vineland Adaptive Behavior Scale (VABS). Neuropsychological measures related to mood and depression were also assessed. In sum, we observed a decrease in total ATEC and rated autism symptoms (Sociability; Sensory/Cognitive Awareness; Health/Physical/Behavior); an evident improvement in Adapted Behavior Composite and in the DLS subarea from VABS; a decrease in Depression (from POMS) and in mood disturbance/depression (BDI). BCI online performance and tolerance were stable along the intervention. Average P300 amplitude and alpha power were also preserved across sessions. We have demonstrated the feasibility of BCI in this kind of intervention in ASD. Participants engage successfully and consistently in the task. Although the primary outcome (rate of automatic responses to joint attention cues) did not show changes, most secondary neuropsychological outcome measures showed improvement, yielding promise for a future efficacy trial. (clinical-trial ID: NCT02445625-clinicaltrials.gov).

4.
Physiol Meas ; 34(3): 377-90, 2013 Mar.
Article in English | MEDLINE | ID: mdl-23442889

ABSTRACT

A new type of optical probe based on laser Doppler self-mixing technology, for a truly non-contact measurement in a single location, and extraction of the temporal features of the distension wave in the arterial wall, was developed. The monitoring of temporal features allows the assessment of cardiovascular function when measurement is carried out at the carotid artery. An algorithm based on the short-time Fourier transform and empirical mode decomposition was applied to the test setup self-mixing signals for the determination of waveform features, with an accuracy of a few milliseconds and a root mean square error less than 3 ms. In vivo testing signals show great consistency in the measured pulse pressure waveform.


Subject(s)
Algorithms , Echocardiography, Doppler , Hemodynamics/physiology , Optical Devices , Signal Processing, Computer-Assisted , Carotid Arteries/physiology , Humans , Image Processing, Computer-Assisted , Spectrum Analysis , Time Factors
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