Biology subjects

Bruining, H.

Publications and source records attributed to Bruining, H..

4 recordsLinked to original sources

bioRxiv2026

Age-specific pediatric templates improve EEG source-reconstructed biomarkers in children

EEG source reconstruction requires an anatomical head model, ideally constructed from individual magnetic resonance imaging (MRI) scans. In developmental studies of children and adolescents, however, MRIs are rarely available. Researchers therefore routinely rely on adult templates, such as the FreeSurfer average (fsaverage), despite substantial anatomical changes throughout development. How much this reliance on adult models biases downstream EEG biomarkers remains unclear. Here, we investigated whether age-specific pediatric templates offer a better alternative to fsaverage for EEG-derived biomarkers in children and adolescents, using individual MRI-based reconstruction as the reference. We analyzed eyes-closed resting-state EEGs from 384 Healthy Brain Network participants aged 5.5 to 17.5 years. For each participant, we tested three anatomical models: their individual MRI, an age-specific pediatric template from a series spanning ages 6-17 at one-year intervals, and the adult fsaverage template. We compared four EEG biomarkers in childhood and adolescence: absolute power, relative power, long-range temporal correlations quantified with detrended fluctuation analysis (DFA), and functional excitation-inhibition (fE/I) ratio. Pediatric templates agreed more closely with individual MRI-based biomarkers in both developmental groups and had fewer parcels with significantly different biomarker values than the adult template, except for absolute power in older adolescents. We conclude that when individual MRI is not available, age-specific pediatric templates match individual MRI-based EEG biomarker values more closely than the adult template across all four biomarkers up to approximately 12 years of age and should be the preferred choice at least up to this age.

neuroscience↗

bioRxiv2025

E/I ratio and net E+I strength are differentially affected across brain disorders

Neuronal oscillations wax and wane near criticality, switching between high- and low-power states. However, the link between this bistability and excitation-inhibition balance is not well understood. Using a computational model, we demonstrate that bistability is influenced by two key factors: the excitatory-inhibitory (E/I) ratio and the combined strength of excitatory and inhibitory activity (E+I). We developed algorithms to infer both metrics from electrophysiological data and validated them in vivo. In intracranial recordings from epilepsy patients, both E/I and E+I increased during seizures, while interictally, E+I remained elevated in seizure zones as E/I decreased--consistent with compensatory inhibition. Extending the framework to scalp EEG from eight disorders, we found that Alzheimers disease is better classified by E/I changes, whereas autism spectrum disorder and ADHD are distinguished by E+I alterations. Our findings highlight the importance of bistability in understanding EI regulation and offer handles for diagnostic and treatment decision support.

neuroscience↗

bioRxiv2024

Qualitative EEG abnormalities signal a shift towards inhibition-dominated brain networks. Results from the EU-AIMS LEAP studies

Qualitative EEG abnormalities are common in Autism Spectrum Disorder (ASD) and hypothesized to reflect disrupted excitation/inhibition balance. To test this, we recently introduced a functional measure of network-level E/I ratio (fE/I). Here, we applied fE/I and other EEG measures to alpha oscillations from source-reconstructed data in the EU-AIMS dataset (267 ASD, 209 controls). We analyzed these measures alongside qualitative EEG abnormalities ranging from slowing of activity to epileptiform patterns, aiming to replicate the findings from the SPACE-BAMBI study. EEG abnormalities were rare in adults and could not be statistically assessed. ASD children-adolescents with EEG abnormalities exhibited lower relative alpha power and fE/I compared to those without. However, EEG-abnormality scoring did not stratify the behavioral heterogeneity of ASD using clinical measures. Surprisingly, several controls also exhibited qualitative EEG abnormalities with a strikingly similar anatomical distribution of reduced fE/I, suggesting a shift towards inhibition-dominated network dynamics in sensory processing regions. The robustness of this association between EEG abnormalities and reduced fE/I was further supported by re-analysis of the SPACE-BAMBI study in source space. Stratification by the presence of EEG abnormalities and their effects on network activity may help understand neurodevelopmental physiological heterogeneity and the difficulties in implementing E/I targeting treatments in unselected cohorts.

neuroscience↗

bioRxiv2021

EEG-based visual deviance detection in freely behaving mice

The mouse is widely used as an experimental model to study visual processing. To probe how the visual system detects changes in the environment, functional paradigms in freely behaving mice are strongly needed. We developed and validated the first EEG-based method to investigate visual deviance detection in freely behaving mice. Mice with EEG implants were exposed to a visual deviant detection paradigm that involved changes in light intensity as standard and deviant stimuli. By subtracting the standard from the deviant evoked waveform, deviant detection was evident as bi-phasic negativity (starting around 70 ms) in the difference waveform. Additionally, deviance-associated evoked (beta/gamma) and induced (gamma) oscillatory responses were found. We showed that the results were stimulus-independent by applying a "flip-flop" design and the results showed good repeatability in an independent measurement. Together, we put forward a validated, easy-to-use paradigm to measure visual deviance processing in freely behaving mice.

neuroscience↗