Publications related to Multivariate deep phenotyping reveals behavioral correlates of non-restorative sleep in 22q11.2 deletion syndrome

Related publications (6)

Multi‐Wearable Approach for Monitoring Diurnal Light Exposure and Body Rhythms in Nightshift Workers

Marilyne Andersen, Steffen Lutz Hartmeyer

AimAs our understanding of light's impact on human health grows, studies examining light exposure and related health outcomes in everyday settings are increasingly important, particularly in high‐risk groups like nightshift workers.MethodsIn this observati ...

Wiley2025

Walking on the Edge: Brain Connectivity Changes in Response to Virtual Height Challenges

Mohamed Bouri

Virtual reality (VR) environments simulating height offer a unique platform to investigate neural adaptations to emotionally salient contexts during locomotion. These simulations allow for controlled analysis of motor‐cognitive interactions under perceived ...

Wiley2025

Large-Scale Mechanistic Models of Brain Circuits with Biophysically and Morphologically Detailed Neurons

Armando Romani

Understanding the brain requires studying its multiscale interactions from molecules to networks. The increasing availability of large-scale datasets detailing brain circuit composition, connectivity, and activity is transforming neuroscience. However, int ...

SOC NEUROSCIENCE2024

Combining anatomical and functional networks for neuropathology identification: A case study on autism spectrum disorder

Ntorina Thanou

While the prevalence of Autism Spectrum Disorder (ASD) is increasing, research continues in an effort to identify common etiological and pathophysiological bases. In this regard, modern machine learning and network science pave the way for a better underst ...

ELSEVIER2021

Discrimination of Walking and Standing from Entropy of EEG Signals and Common Spatial Patterns

Silvestro Micera, Fiorenzo Artoni

Recently, the complexity analysis of brain activity has shown the possibility to provide additional information to discriminate between rest and motion in real-time. In this work, we propose a novel entropy-based machine learning method to classify between ...

IEEE2020

Connexin30 knock-out mice display less spontaneous locomotor activity, more sleep pressure and a reduced expression of metabolism-related genes

Pierre Magistretti

Wiley-Blackwell2014