Human cortical dynamics during full-body heading changes

The retrosplenial complex (RSC) plays a crucial role in spatial orientation by computing heading direction and translating between distinct spatial reference frames based on multi-sensory information. While invasive studies allow investigating heading computation in moving animals, established non-invasive analyses of human brain dynamics are restricted to stationary setups. To investigate the role of the RSC in heading computation of actively moving humans, we used a Mobile Brain/Body Imaging approach synchronizing electroencephalography with motion capture and virtual reality. Data from physically rotating participants were contrasted with rotations based only on visual flow. During physical rotation, varying rotation velocities were accompanied by pronounced wide frequency band synchronization in RSC, the parietal and occipital cortices. In contrast, the visual flow rotation condition was associated with pronounced alpha band desynchronization, replicating previous findings in desktop navigation studies, and notably absent during physical rotation. These results suggest an involvement of the human RSC in heading computation based on visual, vestibular, and proprioceptive input and implicate revisiting traditional findings of alpha desynchronization in areas of the navigation network during spatial orientation in movement-restricted participants.

LIDAR Scanning as an Advanced Technology in Physical Hydraulic Modelling: The Stilling Basin Example

In hydraulic engineering, stilling basin design is traditionally carried out using physical models, conducting visual flow observations as well as point-source measurements of pressure, flow depth, and velocity at locations of design relevance. Point measurements often fail to capture the strongly varying three-dimensionality of the flows within the stilling basin that are important for the best possible design of the structure. This study introduced fixed scanning 2D LIDAR technology for laboratory-scale physical hydraulic modelling of stilling basins. The free-surface motions were successfully captured along both longitudinal and transverse directions, providing a detailed free-surface map. LIDAR-derived free-surface elevations were compared with typical point-source measurements using air–water conductivity probes, showing that the elevations measured with LIDAR consistently corresponded to locations of strongest air–water flow interactions at local void fractions of approximately 50%. The comparison of LIDAR-derived free-surface elevations with static and dynamic pressure sensors confirmed differences between the two measurement devices in the most energetic parts of the jump roller. The present study demonstrates that LIDAR technology can play an important role in physical hydraulic modelling, enabling design improvement through detailed free-surface characterization of complex air–water flow motions beyond the current practice of point measurements and visual flow observations.

The usability of a visual, flow-based programming environment for non-programmers

Living with “Big Data” gives us the advantage of being able to exploit this wealth of data sources and derive useful insights to make better decisions, enhance productivity, and optimize resources. However, this advantage is limited to a small group of professionals, with the rest of the population unable to access this data. Lack of support for non-professionals creates the need for data manipulation tools to support all sectors of society without acquiring complex technical skills. “Kit” is a visual flow-based programming environment that aims to facilitate manipulation and visualization for all citizens, particularly non-programmers, enabling them to have hands on data in an easy manner. This study evaluates Kit’s usability by having non-programmers involved in various evaluation activities to assess their ability to solve data-related problems using a prototype of the environment. The results provided useful insights to improve the design of data manipulation tools aiming to support non-programmers

The usability of a visual, flow-based programming environment for non-programmers

Living with “Big Data” gives us the advantage of being able to exploit this wealth of data sources and derive useful insights to make better decisions, enhance productivity, and optimize resources. However, this advantage is limited to a small group of professionals, with the rest of the population unable to access this data. Lack of support for non-professionals creates the need for data manipulation tools to support all sectors of society without acquiring complex technical skills. “Kit” is a visual flow-based programming environment that aims to facilitate manipulation and visualization for all citizens, particularly non-programmers, enabling them to have hands on data in an easy manner. This study evaluates Kit’s usability by having non-programmers involved in various evaluation activities to assess their ability to solve data-related problems using a prototype of the environment. The results provided useful insights to improve the design of data manipulation tools aiming to support non-programmers

Directional effects of whole-body spinning and visual flow in virtual reality on vagal neuromodulation

BACKGROUND: Neural circuits allow whole-body yaw rotation to modulate vagal parasympathetic activity, which alters beat-to-beat variation in heart rate. The overall output of spinning direction, as well as vestibular-visual interactions on vagal activity still needs to be investigated. OBJECTIVE: This study investigated direction-dependent effects of visual and natural vestibular stimulation on two autonomic responses: heart rate variability (HRV) and pupil diameter. METHODS: Healthy human male subjects (n = 27) underwent constant whole-body yaw rotation with eyes open and closed in the clockwise (CW) and anticlockwise (ACW) directions, at 90°/s for two minutes. Subjects also viewed the same spinning environments on video in a VR headset. RESULTS: CW spinning significantly decreased parasympathetic vagal activity in all conditions (CW open p = 0.0048, CW closed p = 0.0151, CW VR p = 0.0019,), but not ACW spinning (ACW open p = 0.2068, ACW closed p = 0.7755, ACW VR p = 0.1775,) as indicated by an HRV metric, the root mean square of successive RR interval differences (RMSSD). There were no direction-dependent effects of constant spinning on sympathetic activity inferred through the HRV metrics, stress index (SI), sympathetic nervous system index (SNS index) and pupil diameter. Neuroplasticity in the CW eyes closed and CW VR conditions post stimulation was observed. CONCLUSIONS: Only one direction of yaw spinning, and visual flow caused vagal nerve neuromodulation and neuroplasticity, resulting in an inhibition of parasympathetic activity on the heart, to the same extent in either vestibular or visual stimulation. These results indicate that visual flow in VR can be used as a non-electrical method for vagus nerve inhibition without the need for body motion in the treatment of disorders with vagal overactivity. The findings are also important for VR and spinning chair based autonomic nervous system modulation protocols, and the effects of motion integrated VR.

Feature selectivity explains mismatch signals in mouse visual cortex

Sensory experience is often dependent on one’s own actions, including self-motion. Theories of predictive coding postulate that actions are regulated by calculating prediction error, which is the difference between sensory experience and expectation based on self-generated actions. Signals consistent with prediction error have been reported in mouse visual cortex (V1) when visual flow coupled to running is unexpectedly perturbed. Here, we show that such signals can be elicited by visual stimuli uncoupled with the animal’s running. We recorded the activity of mouse V1 neurons while presenting drifting gratings that unexpectedly stopped. We found strong responses to visual perturbations, which were enhanced during running. If these perturbation responses are signals about sensorimotor mismatch, they should be largest for front-to-back visual flow expected from the animals’ running. Responses, however, did not show a bias for front-to-back visual flow. Instead, perturbation responses were strongest in the preferred orientation of individual neurons and perturbation responsive neurons were more likely to prefer slow visual speeds. Our results therefore indicate that prediction error signals can be explained by the convergence of known motor and sensory signals in visual cortex, providing a purely sensory and motor explanation for purported mismatch signals.

Effects of Visual Flow Alterations on Psychophysiological Responses to Virtual Reality Exercise

Virtual reality (VR) technology combined with exercise, called VR exercise, is believed to have beneficial effects on mood; but VR factors contributing to improved mood remain ambiguous. The purpose of this study was to examine the effect of visual flow speed on psychophysiological responses (i.e., physiological responses, ratings of perceived exertion or RPE, and mood) to immersive VR exercise in a simulated natural environment. Eighteen male participants ( Mage =23.1, SD = 1.9 years) cycled an ergometer at 80 watts for 5 minutes on three separate occasions while watching a first-person VR movie through VR goggles at three different speeds of visual flow, corresponding to 7.5 km.h−1, 15 km.h−1, and 22.5 km.h−1. The order of the three speeds was randomized in a counterbalanced design. We measured heart rate, oxygen uptake, minute ventilation, respiratory rate, and cadence during the exercise, and we recorded ratings of perceived exertion (RPE) and mood immediately after the exercise. We evaluated mood states with the Two-Dimensional Mood Scale. One-way repeated measures analysis of variance or the Friedman test revealed no significant effects on any physiological variables, RPE or cadence as a result of altered visual flow speed during VR exercise ( p > .05). However, speed of visual flow significantly influenced participant ratings of Vitality ( p = 0.01) and Pleasure ( p = 0.02), with the faster speed resulting in a more positive mood state. As these findings showed that VR exercise with faster visual flow induced positive mood states, we recommend faster visual flow to induce better mood states in VR exercise.