ABSTRACT
Background: Transcranial direct current stimulation (tDCS) is a promising treatment for Alzheimer's Disease (AD). However, identifying objective biomarkers that can predict brain stimulation efficacy, remains a challenge. The primary aim of this investigation is to delineate the cerebral regions implicated in AD, taking into account the existing lacuna in comprehension of these regions. In pursuit of this objective, we have employed a supervised machine learning algorithm to prognosticate the neurophysiological outcomes resultant from the confluence of tDCS therapy plus cognitive intervention within both the cohort of responders and non-responders to antecedent tDCS treatment, stratified on the basis of antecedent cognitive outcomes. Methods: The data were obtained through an interventional trial. The study recorded high-resolution electroencephalography (EEG) in 70 AD patients and analyzed spectral power density during a 6 min resting period with eyes open focusing on a fixed point. The cognitive response was assessed using the AD Assessment Scale-Cognitive Subscale. The training process was carried out through a Random Forest classifier, and the dataset was partitioned into K equally-partitioned subsamples. The model was iterated k times using K-1 subsamples as the training bench and the remaining subsample as validation data for testing the model. Results: A clinical discriminating EEG biomarkers (features) was found. The ML model identified four brain regions that best predict the response to tDCS associated with cognitive intervention in AD patients. These regions included the channels: FC1, F8, CP5, Oz, and F7. Conclusion: These findings suggest that resting-state EEG features can provide valuable information on the likelihood of cognitive response to tDCS plus cognitive intervention in AD patients. The identified brain regions may serve as potential biomarkers for predicting treatment response and maybe guide a patient-centered strategy. Clinical Trial Registration: https://classic.clinicaltrials.gov/ct2/show/NCT02772185?term=NCT02772185&draw=2&rank=1, identifier ID: NCT02772185.
ABSTRACT
Chronic migraine is a difficult disease to diagnose, and its pathophysiology remains undefined. Its symptoms affect the quality of life and daily living tasks of the affected person, leading to momentary disability. This is a pilot, randomized, controlled, double-blind clinical trial study with female patients between 18 and 65 years old with chronic migraine. The patients underwent twelve mindfulness sessions paired with anodal transcranial direct-current stimulation (tDCS) over the left dorsolateral prefrontal cortex (DLPFC), with current intensity of 2 mA applied for 20 min, three times a week for 4 weeks. In addition, 20 min of mindfulness home practices were performed by guided meditation audio files. A total of 30 participants were evaluated after the treatment, and these were subdivided into two groups-active tDCS and sham tDCS, both set to mindfulness practice. The FFMQ-BR (Five Facet of Mindfulness Questionnaire), MIDAS (Migraine Disability Assessment), and HIT-6 (Headache Impact Test) questionnaires were used to evaluate the outcomes. After the treatment, the active mindfulness and tDCS group showed better results in all outcomes. The sham group also showed improvements, but with smaller effect sizes compared to the active group. The only significant difference in the intergroup analysis was the outcome evaluated by HIT-6 in the post treatment result. Our results provide the first therapeutic evidence of mindfulness practices associated with left DLPFC anodal tDCS with a consequent increase in the level of full attention and analgesic benefits in the clinical symptoms of patients with chronic migraine.
ABSTRACT
Congenital Zika Syndrome (CZS) is characterized by changes in cranial morphology associated with heterogeneous neurological manifestations and cognitive and behavioral impairments. In this syndrome, longitudinal neuroimaging could help clinicians to predict developmental trajectories of children and tailor treatment plans accordingly. However, regularly acquiring magnetic resonance imaging (MRI) has several shortcomings besides cost, particularly those associated with childrens' clinical presentation as sensitivity to environmental stimuli. The indirect monitoring of local neural activity by non-invasive functional near-infrared spectroscopy (fNIRS) technique can be a useful alternative for longitudinally accessing the brain function in children with CZS. In order to provide a common framework for advancing longitudinal neuroimaging assessment, we propose a principled guideline for fNIRS acquisition and analyses in children with neurodevelopmental disorders. Based on our experience on collecting fNIRS data in children with CZS we emphasize the methodological challenges, such as clinical characteristics of the sample, desensitization, movement artifacts and environment control, as well as suggestions for tackling such challenges. Finally, metrics based on fNIRS can be associated with established clinical metrics, thereby opening possibilities for exploring this tool as a long-term predictor when assessing the effectiveness of treatments aimed at children with severe neurodevelopmental disorders.
