PT  - JOURNAL ARTICLE
AU  - Alexandre Delaux
AU  - Jean-Baptiste de Saint Aubert
AU  - Stephen Ramanoël
AU  - Marcia Bécu
AU  - Lukas Gehrke
AU  - Marius Klug
AU  - Ricardo Chavarriaga
AU  - José-Alain Sahel
AU  - Klaus Gramann
AU  - Angelo Arleo
TI  - Mobile brain/body imaging of landmark-based navigation with high-density EEG
AID  - 10.1101/2021.01.13.426330
DP  - 2021 Jan 01
TA  - bioRxiv
PG  - 2021.01.13.426330
4099  - http://biorxiv.org/content/early/2021/01/17/2021.01.13.426330.short
4100  - http://biorxiv.org/content/early/2021/01/17/2021.01.13.426330.full
AB  - Coupling behavioral and brain imaging in naturalistic, ecological conditions is key to comprehend the neural bases of spatial navigation. This highly-integrative function encompasses sensorimotor, cognitive, and executive processes that jointly mediate active exploration and spatial learning. However, most neuroimaging approaches in humans do not account for all these processes, in particular multisensory integration, since they are based on static, motion constrained paradigms. Here, we bring together the technology and data analysis tools to conduct simultaneous brain/body imaging during navigation in mobile conditions. Following the Mobile Brain/Body Imaging approach, we focus on landmark-based navigation in actively behaving young adults solving a virtual reality Y-maze task. The presented EEG analysis identifies exploitable neural signals from a specific network of brain regions that matches the state-of-the-art imaging literature of landmark-based navigation, revealing the concurrent activation of brain areas engaged in active, natural spatial navigation. In particular, we focus on the role of the retrosplenial cortex in visuo-spatial processing and coding. In line with previous evidence, we find behavioral modulations of neural processes during navigation, like attentional demand, as reflected in the alpha/gamma range and memory workload in the delta/theta range. Finally, our results show how the fine temporal resolution of mobile EEG recordings captures the time course of neuro-behavioral correlations, as participants actively interact with their environment. We confirm that combining mobile high-density EEG and biometric measures can help unravel the brain network and neural modulations subtending ecological landmark-based navigation.Competing Interest StatementThe authors have declared no competing interest.AbbreviationsAMICAAdaptative Mixture Independent Component AnalysisANOVAAnalysis of VarianceBABrodmann AreaECDEquivalent Current DipoleEEGElectroencephalogramERPEvent-Related PotentialsERSPEvent-Related Spectral PerturbationsfMRIfunctional Magnetic Resonance ImagingICIndependent ComponentICAIndependent Component AnalysisMNIMontreal Neurological InstituteMoBIMobile Brain/Body ImagingROIRegion of InterestRSCRetrosplenial CortexVRVirtual Reality