Pilot Study of Prism EFP NeuroFeedback in Adult ADHD.

OBJECTIVE: A pilot study to preliminarily examine the effects of Prism EFP NeuroFeedback (NF) in adult ADHD. METHOD: Prism EFP NF is a form of NF specifically designed to target emotional dysregulation (ED) through down regulation of amygdala activity. Prism EFP NF has been shown to improve other disorders with significant ED. Nine participants with adult ADHD received an open trial of Prism EFP NF consisting of fifteen sessions over 8 weeks; all completed at least 5 weeks of treatment with seven completing all 8 weeks. Outcomes were assessed by change in ADHD symptoms from baseline to End of Treatment. RESULTS: About two-third reduction was seen in total DSM ADHD symptom scores (primary outcome measure) with improvement observed in all other clinical measures. No significant adverse events were seen. CONCLUSION: This preliminary trial found substantial effects of Prism EFP NF on ADHD/ED symptoms and global impairment.

Prospective longitudinal investigation shows correlation of event-related potential to mild traumatic brain injury in adolescents.

STUDY DESIGN: Prospective longitudinal cohort study. BACKGROUND: Adolescent athletes may be more susceptible to the long-term effects of mild traumatic brain injury (mTBI). A diagnostic and prognostic neuromarker may optimize management and return-to-activity decision-making in athletes who experience mTBI. OBJECTIVE: Measure an event-related potential (ERP) component captured with electroencephalography (EEG), called processing negativity (PN), at baseline and post-injury in adolescents who suffered mTBI and determine their longitudinal response relative to healthy controls. METHODS: Thirty adolescents had EEG recorded during an auditory oddball task at a pre-mTBI baseline session and subsequent post-mTBI sessions. Longitudinal EEG data from patients and healthy controls (n= 77) were obtained from up to four sessions in total and processed using Brain Network Analysis algorithms. RESULTS: The average PN amplitude in healthy controls significantly decreased over sessions 2 and 3; however, it remained steady in the mTBI group's 2nd (post-mTBI) session and decreased only in sessions 3 and 4. Pre- to post-mTBI amplitude changes correlated with the time interval between sessions. CONCLUSION: These results demonstrate that PN amplitude changes may be associated with mTBI exposure and subsequent recovery in adolescent athletes. Further study of PN may lead to it becoming a neuromarker for mTBI prognosis and return-to-activity decision-making in adolescents.

Improved Back-Projection Cortical Potential Imaging by Multi-resolution Optimization Technique.

Electroencephalogram (EEG) has evolved to be a well-established tool for imaging brain activity. This progress is mainly due to the development of high-resolution (HR) EEG methods. One class of HR-EEG is the cortical potential imaging (CPI), which aims to estimate the potential distribution on the cortical surface, which is much more informative than EEG. Even though these methods exhibit good performance, most of them have inherent inaccuracies that originate from their operating principles that constrain the solution or require a complex calculation process. The back-projection CPI (BP-CPI) method is relatively new and has the advantage of being constraint-free and computation inexpensive. The method has shown relatively good accuracy, which is necessary to become a clinical tool. However, better performance must be achieved. In the present study, two improvements are proposed. Both are embedded as adjacent stages to the BP-CPI and are based on the multi-resolution optimization approach (MR-CPI). A series of Monte-Carlo simulations were performed to examine the characteristics of the proposed improvements. Additional tests were done, including different EEG noise levels and variation in electrode-numbers. The results showed highly accurate cortical potential estimations, with a reduction in estimation error by a factor of 3.75 relative to the simple BP-CPI estimation error. We also validated these results with true EEG data. Analyzing these EEGs, we have demonstrated the MR-CPI competence to correctly localize cortical activations in a real environment. The MR-CPI methods were shown to be reliable for estimating cortical potentials, enabling researchers to obtain fast and robust high-resolution EEGs.

Brain Network Activation Analysis Utilizing Spatiotemporal Features for Event Related Potentials Classification.

The purpose of this study was to introduce an improved tool for automated classification of event-related potentials (ERPs) using spatiotemporally parcellated events incorporated into a functional brain network activation (BNA) analysis. The auditory oddball ERP paradigm was selected to demonstrate and evaluate the improved tool. Methods: The ERPs of each subject were decomposed into major dynamic spatiotemporal events. Then, a set of spatiotemporal events representing the group was generated by aligning and clustering the spatiotemporal events of all individual subjects. The temporal relationship between the common group events generated a network, which is the spatiotemporal reference BNA model. Scores were derived by comparing each subject's spatiotemporal events to the reference BNA model and were then entered into a support vector machine classifier to classify subjects into relevant subgroups. The reliability of the BNA scores (test-retest repeatability using intraclass correlation) and their utility as a classification tool were examined in the context of Target-Novel classification. Results: BNA intraclass correlation values of repeatability ranged between 0.51 and 0.82 for the known ERP components N100, P200, and P300. Classification accuracy was high when the trained data were validated on the same subjects for different visits (AUCs 0.93 and 0.95). The classification accuracy remained high for a test group recorded at a different clinical center with a different recording system (AUCs 0.81, 0.85 for 2 visits). Conclusion: The improved spatiotemporal BNA analysis demonstrates high classification accuracy. The BNA analysis method holds promise as a tool for diagnosis, follow-up and drug development associated with different neurological conditions.

Brain Network Activation (BNA) reveals scopolamine-induced impairment of visual working memory.

The overarching goal of this event-related potential (ERP) study was to examine the effects of scopolamine on the dynamics of brain network activation using a novel ERP network analysis method known as Brain Network Activation (BNA). BNA was used for extracting group-common stimulus-activated network patterns elicited to matching probe stimuli in the context of a delayed matching-to-sample task following placebo and scopolamine treatments administered to healthy participants. The BNA extracted networks revealed the existence of two pathophysiological mechanisms following scopolamine, disconnection, and compensation. Specifically, weaker frontal theta and parietal alpha coupling was accompanied with enhanced fronto-centro-parietal theta activation relative to placebo. In addition, using the characteristic BNA network of each treatment as well as corresponding literature-guided selective subnetworks as combined biomarkers managed to differentiate between individual responses to each of the treatments. Behavioral effects associated with scopolamine included delayed response time and impaired response accuracy. These results indicate that the BNA method is sensitive to the effects of scopolamine on working memory and that it may potentially enable diagnosis and treatment assessment of dysfunctions associated with cholinergic deficiency.

Source localization of temporal lobe epilepsy using PCA-LORETA analysis on ictal EEG recordings.

Localizing the source of an epileptic seizure using noninvasive EEG suffers from inaccuracies produced by other generators not related to the epileptic source. The authors isolated the ictal epileptic activity, and applied a source localization algorithm to identify its estimated location. Ten ictal EEG scalp recordings from five different patients were analyzed. The patients were known to have temporal lobe epilepsy with a single epileptic focus that had a concordant MRI lesion. The patients had become seizure-free following partial temporal lobectomy. A midinterval (approximately 5 seconds) period of ictal activity was used for Principal Component Analysis starting at ictal onset. The level of epileptic activity at each electrode (i.e., the eigenvector of the component that manifest epileptic characteristic), was used as an input for low-resolution tomography analysis for EEG inverse solution (Zilberstain et al., 2004). The algorithm accurately and robustly identified the epileptic focus in these patients. Principal component analysis and source localization methods can be used in the future to monitor the progression of an epileptic seizure and its expansion to other areas.