adults
Research Papers
Electrophysiological signatures of brain aging in autism spectrum disorder
Recent evidence suggests that structural and functional brain aging is atypical in adults with autism spectrum disorder (ASD). However, it remains unclear if oscillatory slowing, a key marker of neurophysiological aging, follows an atypical trajectory in this population. This study examines patterns of age-related oscillatory slowing in adults with ASD, captured by reductions in the brain's peak alpha frequency (PAF). Resting-state electroencephalography (EEG) data from adults (18-70 years) with ASD (N = 93) and non-ASD controls (N = 87) were pooled from three independent datasets. A robust curve-fitting procedure quantified the peak frequency of alpha oscillations (7-13 Hz) across all brain regions. Associations between PAF and age were assessed and compared between groups. Consistent with characteristic patterns of oscillatory slowing, PAF was negatively associated with age across the entire sample (p < .0001). A significant group-by-age interaction revealed that this relationship was more pronounced in adults with ASD (p < .01). These findings invite further longitudinal investigations of PAF in adults with ASD to confirm if age-related oscillatory slowing is accelerated.
View Full Paper →EEG spectral power, but not theta/beta ratio, is a neuromarker for adult ADHD
Adults with attention-deficit/hyperactivity disorder (ADHD) have been described as having altered resting-state electroencephalographic (EEG) spectral power and theta/beta ratio (TBR). However, a recent review (Pulini et al. 2018) identified methodological errors in neuroimaging, including EEG, ADHD classification studies. Therefore, the specific EEG neuromarkers of adult ADHD remain to be identified, as do the EEG characteristics that mediate between genes and behaviour (mediational endophenotypes). Resting-state eyes-open and eyes-closed EEG was measured from 38 adults with ADHD, 45 first-degree relatives of people with ADHD and 51 unrelated controls. A machine learning classification analysis using penalized logistic regression (Elastic Net) examined if EEG spectral power (1-45 Hz) and TBR could classify participants into ADHD, first-degree relatives and/or control groups. Random-label permutation was used to quantify any bias in the analysis. Eyes-open absolute and relative EEG power distinguished ADHD from control participants (area under receiver operating characteristic = 0.71-0.77). The best predictors of ADHD status were increased power in delta, theta and low-alpha over centro-parietal regions, and in frontal low-beta and parietal mid-beta. TBR did not successfully classify ADHD status. Elevated eyes-open power in delta, theta, low-alpha and low-beta distinguished first-degree relatives from controls (area under receiver operating characteristic = 0.68-0.72), suggesting that these features may be a mediational endophenotype for adult ADHD. Resting-state EEG spectral power may be a neuromarker and mediational endophenotype of adult ADHD. These results did not support TBR as a diagnostic neuromarker for ADHD. It is possible that TBR is a characteristic of childhood ADHD.
View Full Paper →Neurofeedback as a nonpharmacological treatment for adults with attention-deficit/hyperactivity disorder (ADHD): study protocol for a randomized controlled trial
Background: Neurofeedback has been applied effectively in various areas, especially in the treatment of children with attention-deficit/hyperactivity disorder (ADHD). This study protocol is designed to investigate the effect of slow cortical potential (SCP) feedback and a new form of neurofeedback using near-infrared spectroscopy (NIRS) on symptomatology and neurophysiological parameters in an adult ADHD population. A comparison of SCP and NIRS feedback therapy methods has not been previously conducted and may yield valuable findings about alternative treatments for adult ADHD. Methods/Design: The outcome of both neurofeedback techniques will be assessed over 30 treatment sessions and after a 6-month follow-up period, and then will be compared to a nonspecific biofeedback treatment. Furthermore, to investigate if treatment effects in this proof-of-principle study can be predicted by specific neurophysiological baseline parameters, regression models will be applied. Finally, a comparison with healthy controls will be conducted to evaluate deviant pretraining neurophysiological parameters, stability of assessment measures, and treatment outcome. Discussion: To date, an investigation and comparison of SCP and NIRS feedback training to an active control has not been conducted; therefore, we hope to gain valuable insights in effects and differences of these types of treatment for ADHD in adults. Trial registration: This study is registered with the German Registry of Clinical Trials:DRKS00006767, date of registration: 8 October 2014. © 2015 Mayer et al.; licensee BioMed Central.
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