Short-term EEG dynamics and neural generators evoked by navigational images

Abstract

The ecological environment offered by virtual reality is primarily supported by visual information. The different image contents and their rhythmic presentation imply specific bottom-up and top-down processing. Because these processes already occur during passive observation we studied the brain responses evoked by the presentation of specific 3D virtual tunnels with respect to 2D checkerboard. For this, we characterized electroencephalograhy dynamics (EEG), the evoked potentials and related neural generators involved in various visual paradigms. Time-frequency analysis showed modulation of alpha-beta oscillations indicating the presence of stronger prediction and after-effects of the 3D-tunnel with respect to the checkerboard. Whatever the presented image, the generators of the P100 were situated bilaterally in the occipital cortex (BA18, BA19) and in the right inferior temporal cortex (BA20). In checkerboard but not 3D-tunnel presentation, the left fusiform gyrus (BA37) was additionally recruited. P200 generators were situated in the temporal cortex (BA21) and the cerebellum (lobule VI/Crus I) specifically for the checkerboard while the right parahippocampal gyrus (BA36) and the cerebellum (lobule IV/V and IX/X) were involved only during the 3D-tunnel presentation. For both type of image, P300 generators were localized in BA37 but also in BA19, the right BA21 and the cerebellar lobule VI for only the checkerboard and the left BA20-BA21 for only the 3D-tunnel. Stronger P300 delta-theta oscillations recorded in this later situation point to a prevalence of the effect of changing direction over the proper visual content of the 3D-tunnel. The parahippocampal gyrus (BA36) implicated in navigation was also identified when the 3D-tunnel was compared to their scrambled versions, highlighting an action-oriented effect linked to navigational content.

Caudate and cerebellar involvement in altered P2 and P3 components of GO/NoGO evoked potentials in children with attention‐deficit/hyperactivity disorder

“…For the source modeling, we performed swLORETA implemented into the ASA Software ANT Neuro, the Netherlands (Cebolla et al, 2011(Cebolla et al, , 2016(Cebolla et al, , 2017Leroy et al, 2017;Palmero-Soler et al, 2007) et al, 2004), swLORETA can model spatially distinct sources of neuronal activity from EEG signals without prior knowledge about the anatomical location of the generators, even in the presence of noise and when two dipoles are simultaneously active. Details about the method are described in (Cebolla et al, 2011(Cebolla et al, , 2017.…”

Neural generators involved in visual cue processing in children with attention‐deficit/hyperactivity disorder (ADHD)

“…For the source modeling, we performed standardized weighted low-resolution electromagnetic tomography (swLORETA), implemented into ASA Software (ANT Neuro, the Netherlands) (Cebolla et al, 2011(Cebolla et al, , 2017Leroy et al, 2017;Palmero-Soler et al, 2007). As a distributed inverse solution approach, swLORETA can model spatially distinct sources of neuronal activity from EEG signals without prior knowledge about the anatomical location of the generators.…”

EEG dynamics and neural generators of psychological flow during one tightrope performance

“…electroencephalography (EEG) recordings represents a new field of interest [18][19][20] . Additionally, recent advances in the high-density EEG approach, coupled with inverse modelling methods [21][22][23][24][25] for the detection of neural cortical and subcortical generators 26 , have paved the way for electrophysiological exploration of the flow state experienced in human participants.…”