Measurement of excitation-inhibition ratio in autism spectrum disorder using critical brain dynamics

cited By 0Balance between excitation (E) and inhibition (I) is a key principle for neuronal network organization and information processing. Consistent with this notion, excitation-inhibition imbalances are considered a pathophysiological mechanism in many brain disorders including autism spectrum disorder (ASD). However, methods to measure E/I ratios in human brain networks are lacking. Here, we present a method to quantify a functional E/I ratio (fE/I) from neuronal oscillations, and validate it in healthy subjects and children with ASD. We define structural E/I ratio in an in silico neuronal network, investigate how it relates to power and long-range temporal correlations (LRTC) of the network's activity, and use these relationships to design the fE/I algorithm. Application of this algorithm to the EEGs of healthy adults showed that fE/I is balanced at the population level and is decreased through GABAergic enforcement. In children with ASD, we observed larger fE/I variability and stronger LRTC compared to typically developing children (TDC). Interestingly, visual grading for EEG abnormalities that are thought to reflect E/I imbalances revealed elevated fE/I and LRTC in ASD children with normal EEG compared to TDC or ASD with abnormal EEG. We speculate that our approach will help understand physiological heterogeneity also in other brain disorders.Peer reviewe

The role of stakeholders in creating societal value from coastal and ocean observations

The importance of stakeholder engagement in ocean observation and in particular the realization of economic and societal benefits is discussed, introducing a number of overarching principles such as the convergence on common goals, effective communication, co-production of information and knowledge and the need for innovation. A series of case studies examine the role of coordinating frameworks such as the United States’ Interagency Ocean Observing System (IOOS®), and the European Ocean Observing System (EOOS), public–private partnerships such as Project Azul and the Coastal Data Information Program (CDIP) and finally the role of the “third” or voluntary sector. The paper explores the value that stakeholder engagement can bring as well as making recommendations for the future

Prediction of Behavioral Improvement Through Resting-State Electroencephalography and Clinical Severity in a Randomized Controlled Trial Testing Bumetanide in Autism Spectrum Disorder

Background: Mechanism-based treatments such as bumetanide are being repurposed for autism spectrum disorder. We recently reported beneficial effects on repetitive behavioral symptoms that might be related to regulating excitation-inhibition (E/I) balance in the brain. Here, we tested the neurophysiological effects of bumetanide and the relationship to clinical outcome variability and investigated the potential for machine learning–based predictions of meaningful clinical improvement. Methods: Using modified linear mixed models applied to intention-to-treat population, we analyzed E/I-sensitive electroencephalography (EEG) measures before and after 91 days of treatment in the double-blind, randomized, placebo-controlled Bumetanide in Autism Medication and Biomarker study. Resting-state EEG of 82 subjects out of 92 participants (7–15 years) were available. Alpha frequency band absolute and relative power, central frequency, long-range temporal correlations, and functional E/I ratio treatment effects were related to the Repetitive Behavior Scale-Revised (RBS-R) and the Social Responsiveness Scale 2 as clinical outcomes. Results: We observed superior bumetanide effects on EEG, reflected in increased absolute and relative alpha power and functional E/I ratio and in decreased central frequency. Associations between EEG and clinical outcome change were restricted to subgroups with medium to high RBS-R improvement. Using machine learning, medium and high RBS-R improvement could be predicted by baseline RBS-R score and EEG measures with 80% and 92% accuracy, respectively. Conclusions: Bumetanide exerts neurophysiological effects related to clinical changes in more responsive subsets, in whom prediction of improvement was feasible through EEG and clinical measures

Tech united Eindhoven middle size league winner 2018

The Tech United Eindhoven Middle Size League (MSL) team achieved a first place at RoboCup 2018. This paper presents a short evaluation of the tournament and describes the most notable developments made in preparation of the tournament. One development in the robot’s hardware is presented: the realization of our eight-wheeled soccer player. The following developments in software will be presented: a new approach to ball state estimation and the human-alike dribble. Additionally, research towards the application of artificial intelligence in opponent action prediction and opponent recognition will be presented