Applied human neuroscience: Fostering and designing inclusive environments with the 3E-Cognition perspective.

The conventional medical paradigm often focuses on deficits and impairments, failing to capture the rich tapestry of experiences and abilities inherent in neurodiversity conditions. In this article, we introduce the 3E-Cognition perspective, offering a paradigm shift by emphasizing the dynamic interplay between the brain, body, and environment in shaping cognitive processes. The perspective fosters a more inclusive and supportive understanding of neurodiversity, with potential applications across various domains such as education, workplace, and healthcare. We begin by introducing the 3E-Cognition principles: embodied, environmentally scaffolded, and enactive. Then, we explore how the 3E-Cognition perspective can be applied to create inclusive environments and experiences for neurodiverse individuals. We provide examples in the realms of education, workplace, and healthcare. In all of these domains, spaces, methodologies, epistemologies, and roles that cater to diverse needs and strengths can be designed using the 3E principles. Finally, we discuss the challenges and benefits of implementing the 3E-Cognition perspective. We focus on the need for technological advancements and research in complex real-world scenarios; we suggest mobile brain/body imaging is a possible solution. We furthermore highlight the importance of recognizing and valuing the diverse manners of experiencing and interacting with the world, the promotion of diverse well-being, and the facilitation of innovation and creativity. Thus, we conclude that the 3E-Cognition perspective offers a groundbreaking approach to understanding and supporting neurodiversity: by embracing the inherent interconnectedness of the brain, body, and environment, we can create a more inclusive and supportive world.

Frequency-dependent modulation of neural oscillations across the gait cycle.

Balance and walking are fundamental to support common daily activities. Relatively accurate characterizations of normal and impaired gait features were attained at the kinematic and muscular levels. Conversely, the neural processes underlying gait dynamics still need to be elucidated. To shed light on gait-related modulations of neural activity, we collected high-density electroencephalography (hdEEG) signals and ankle acceleration data in young healthy participants during treadmill walking. We used the ankle acceleration data to segment each gait cycle in four phases: initial double support, right leg swing, final double support, left leg swing. Then, we processed hdEEG signals to extract neural oscillations in alpha, beta, and gamma bands, and examined event-related desynchronization/synchronization (ERD/ERS) across gait phases. Our results showed that ERD/ERS modulations for alpha, beta, and gamma bands were strongest in the primary sensorimotor cortex (M1), but were also found in premotor cortex, thalamus and cerebellum. We observed a modulation of neural oscillations across gait phases in M1 and cerebellum, and an interaction between frequency band and gait phase in premotor cortex and thalamus. Furthermore, an ERD/ERS lateralization effect was present in M1 for the alpha and beta bands, and in the cerebellum for the beta and gamma bands. Overall, our findings demonstrate that an electrophysiological source imaging approach based on hdEEG can be used to investigate dynamic neural processes of gait control. Future work on the development of mobile hdEEG-based brain-body imaging platforms may enable overground walking investigations, with potential applications in the study of gait disorders.

Sensorimotor brain dynamics reflect architectural affordances.

Anticipating meaningful actions in the environment is an essential function of the brain. Such predictive mechanisms originate from the motor system and allow for inferring actions from environmental affordances, and the potential to act within a specific environment. Using architecture, we provide a unique perspective on the ongoing debate in cognitive neuroscience and philosophy on whether cognition depends on movement or is decoupled from our physical structure. To investigate cognitive processes associated with architectural affordances, we used a mobile brain/body imaging approach recording brain activity synchronized to head-mounted displays. Participants perceived and acted on virtual transitions ranging from nonpassable to easily passable. We found that early sensory brain activity, on revealing the environment and before actual movement, differed as a function of affordances. In addition, movement through transitions was preceded by a motor-related negative component that also depended on affordances. Our results suggest that potential actions afforded by an environment influence perception.

Correcting whole-body motion capture data using rigid body transformation.

Using motion capture data as a part of mobile brain-body imaging (MoBI) recording has been increasing. With minimal linear algebra background, this paper explains how the rigid body transformation can be a useful preprocessing step for denoising and missing marker recovery. Such a transformation can provide insight and necessary-and-sufficient solutions requiring no assumption other than the minimum number of markers present. First, a simulation test using the empirical datasets from the AudioMaze project published from this journal's same volume demonstrates theoretical accuracy. The simulation results show that the rigid-body method perfectly recovers missing markers on a rigid body if a minimum of three marker positions is available. Second, the same transformation is applied to the empirical dataset. Before preprocessing, the raw data show that 15-80% of data frames had all markers present for rigid-body defined body parts. After using the rigid-body correction, most body parts recovered full markers in 90-95% of the data frames. The result also suggests the necessity for performing across-trial corrections for within-participant (42% missing detected in one of the body parts) and across-participants (11% missing). The discussion section introduces a solution and a performance summary for non-rigid-body marker correction using a neural network. Data support that the rigid body transformation is an intuitive and powerful correction method necessary for preprocessing motion capture data for neurocognitive experiments. The supporting information section contains a URL link to Matlab code and example data.

Using mobile brain/body imaging to advance research in arts, health, and related therapeutics.

The uses of mobile brain/body imaging (MoBI) are expanding and allow for more direct study of the neurophysiological signals associated with behavior in psychotherapeutic encounters. Neuroaesthetics is concerned with the cognitive and neural basis of art appreciation, and scientific correlations are being made in the field that might help to clarify theories claimed in the creative arts therapies. Yet, most neuroaesthetics studies are confined to the laboratory and do not propose a translation for research methods and clinical applications. The creative arts therapies have a long history of clinical success with various patient populations and will benefit from increased scientific explanation to support intervention strategies. Examining the brain dynamics and motor behaviors that are associated with the higher complex processes involved in artistic expression offers MoBI as a promising instrumentation to move forward in linking ideas from neuroaesthetics to the creative arts therapies. Tracking brain dynamics in association with behavioral change allows for more objective and quantitative physiological monitors to evaluate, and together with subjective patient reports provides insight into the psychological mechanisms of change in treatment. We outline a framework that shows how MoBI can be used to study the effectiveness of creative arts therapy interventions motivated by the 4E approach to cognition with a focus on visual art therapy. The article illuminates how a new partnership among the fields of art therapy, neuroscience, and neuroaesthetics might work together within the 4E/MoBI framework in efforts to advance transdisciplinary research for clinical health populations.

Cognitive-motor interference in the wild: Assessing the effects of movement complexity on task switching using mobile EEG.

Adaptively changing between different tasks while in locomotion is a fundamental prerequisite of modern daily life. The cognitive processes underlying dual tasking have been investigated extensively using EEG. Due to technological restrictions, however, this was not possible for dual-task scenarios including locomotion. With new technological opportunities, this became possible and cognitive-motor interference can be studied, even in outside-the-lab environments. In the present study, participants carried out a cognitive-motor interference task as they responded to cued, auditory task-switch stimuli while performing locomotive tasks with increasing complexity (standing, walking, traversing an obstacle course). We observed increased subjective workload ratings as well as decreased behavioural performance for increased movement complexity and cognitive task difficulty. A higher movement load went along with a decrease of parietal P2, N2 and P3 amplitudes and frontal Theta power. A higher cognitive load, on the other hand, was reflected by decreased frontal CNV amplitudes. Additionally, a connectivity analysis using inter-site phase coherence revealed that higher movement as well as cognitive task difficulty had an impairing effect on fronto-parietal connectivity. In conclusion, subjective ratings, behavioural performance and electrophysiological results indicate that less cognitive resources were available to be deployed towards the execution of the cognitive task when in locomotion compared to standing still. Connectivity results also show a scarcity of attentional resources when switching a task during the highest movement complexity condition. Summarized, all findings indicate a central role of attentional control regarding cognitive-motor dual tasking and an inherent limitation of cognitive resources.

Cortical responses to whole-body balance perturbations index perturbation magnitude and predict reactive stepping behavior.

The goal of this study was to determine whether the cortical responses elicited by whole-body balance perturbations were similar to established cortical markers of action monitoring. Postural changes imposed by balance perturbations elicit a robust negative potential (N1) and a brisk increase of theta activity in the electroencephalogram recorded over midfrontal scalp areas. Because action monitoring is a cognitive function proposed to detect errors and initiate corrective adjustments, we hypothesized that the possible cortical markers of action monitoring during balance control (N1 potential and theta rhythm) scale with perturbation intensity and the eventual execution of reactive stepping responses (as opposed to feet-in-place responses). We recorded high-density electroencephalogram from eleven young individuals, who participated in an experimental balance assessment. The participants were asked to recover balance following anteroposterior translations of the support surface at various intensities, while attempting to maintain both feet in place. We estimated source-resolved cortical activity using independent component analysis. Combining time-frequency decomposition and group-level general linear modeling of single-trial responses, we found a significant relation of the interaction between perturbation intensity and stepping responses with multiple cortical features from the midfrontal cortex, including the N1 potential, and theta, alpha, and beta rhythms. Our findings suggest that the cortical responses to balance perturbations index the magnitude of a deviation from a stable postural state to predict the need for reactive stepping responses. We propose that the cortical control of balance may involve cognitive control mechanisms (i.e., action monitoring) that facilitate postural adjustments to maintain postural stability.

Identifying key factors for improving ICA-based decomposition of EEG data in mobile and stationary experiments.

Recent developments in EEG hardware and analyses approaches allow for recordings in both stationary and mobile settings. Irrespective of the experimental setting, EEG recordings are contaminated with noise that has to be removed before the data can be functionally interpreted. Independent component analysis (ICA) is a commonly used tool to remove artifacts such as eye movement, muscle activity, and external noise from the data and to analyze activity on the level of EEG effective brain sources. The effectiveness of filtering the data is one key preprocessing step to improve the decomposition that has been investigated previously. However, no study thus far compared the different requirements of mobile and stationary experiments regarding the preprocessing for ICA decomposition. We thus evaluated how movement in EEG experiments, the number of channels, and the high-pass filter cutoff during preprocessing influence the ICA decomposition. We found that for commonly used settings (stationary experiment, 64 channels, 0.5 Hz filter), the ICA results are acceptable. However, high-pass filters of up to 2 Hz cut-off frequency should be used in mobile experiments, and more channels require a higher filter to reach an optimal decomposition. Fewer brain ICs were found in mobile experiments, but cleaning the data with ICA has been proved to be important and functional even with low-density channel setups. Based on the results, we provide guidelines for different experimental settings that improve the ICA decomposition.

Single-trial regression of spatial exploration behavior indicates posterior EEG alpha modulation to reflect egocentric coding.

Learning to navigate uncharted terrain is a key cognitive ability that emerges as a deeply embodied process, with eye movements and locomotion proving most useful to sample the environment. We studied healthy human participants during active spatial learning of room-scale virtual reality (VR) mazes. In the invisible maze task, participants wearing a wireless electroencephalography (EEG) headset were free to explore their surroundings, only given the objective to build and foster a mental spatial representation of their environment. Spatial uncertainty was resolved by touching otherwise invisible walls that were briefly rendered visible inside VR, similar to finding your way in the dark. We showcase the capabilities of mobile brain/body imaging using VR, demonstrating several analysis approaches based on general linear models (GLMs) to reveal behavior-dependent brain dynamics. Confirming spatial learning via drawn sketch maps, we employed motion capture to image spatial exploration behavior describing a shift from initial exploration to subsequent exploitation of the mental representation. Using independent component analysis, the current work specifically targeted oscillations in response to wall touches reflecting isolated spatial learning events arising in deep posterior EEG sources located in the retrosplenial complex. Single-trial regression identified significant modulation of alpha oscillations by the immediate, egocentric, exploration behavior. When encountering novel walls, as well as with increasing walking distance between subsequent touches when encountering novel walls, alpha power decreased. We conclude that these oscillations play a prominent role during egocentric evidencing of allocentric spatial hypotheses.

Rhythmic neural activity is comodulated with short-term gait modifications during first-time use of a dummy prosthesis: a pilot study.

BACKGROUND: After transfemoral amputation, many hours of practice are needed to re-learn walking with a prosthesis. The long adaptation process that consolidates a novel gait pattern seems to depend on cerebellar function for reinforcement of specific gait modifications, but the precise, step-by-step gait modifications (e.g., foot placement) most likely rely on top-down commands from the brainstem and cerebral cortex. The aim of this study was to identify, in able-bodied individuals, the specific modulations of cortical rhythms that accompany short-term gait modifications during first-time use of a dummy prosthesis. METHODS: Fourteen naïve participants walked on a treadmill without (one block, 4 min) and with a dummy prosthesis (three blocks, 3 × 4 min), while ground reaction forces and 32-channel EEG were recorded. Gait cycle duration, stance phase duration, step width, maximal ground reaction force and, ground reaction force trace over time were measured to identify gait modifications. Independent component analysis of EEG data isolated brain-related activity from distinct anatomical sources. The source-level data were segmented into gait cycles and analyzed in the time-frequency domain to reveal relative enhancement or suppression of intrinsic cortical oscillations. Differences between walking conditions were evaluated with one-way ANOVA and post-hoc testing (α = 0.05). RESULTS: Immediate modifications occurred in the gait parameters when participants were introduced to the dummy prosthesis. Except for gait cycle duration, these modifications remained throughout the duration of the experimental session. Power modulations of the theta, mu, beta, and gamma rhythms, of sources presumably from the fronto-central and the parietal cortices, were found across the experimental session. Significant power modulations of the theta, beta, and gamma rhythms within the gait cycle were predominately found around the heel strike of both feet and the swing phase of the right (prosthetic) leg. CONCLUSIONS: The modulations of cortical activity could be related to whole-body coordination, including the swing phase and placing of the prosthesis, and the bodyweight transfer between legs and arms. Reduced power modulation of the gamma rhythm within the experimental session may indicate initial motor memories being formed. Better understanding of the sensorimotor processes behind gait modifications may inform the development of neurofeedback strategies to assist gait rehabilitation.

Cortical dynamics during preparation and execution of reactive balance responses with distinct postural demands.

The contributions of the cerebral cortex to human balance control are clearly demonstrated by the profound impact of cortical lesions on the ability to maintain standing balance. The cerebral cortex is thought to regulate subcortical postural centers to maintain upright balance and posture under varying environmental conditions and task demands. However, the cortical mechanisms that support standing balance remain elusive. Here, we present an EEG-based analysis of cortical oscillatory dynamics during the preparation and execution of balance responses with distinct postural demands. In our experiment, participants responded to backward movements of the support surface either with one forward step or by keeping their feet in place. To challenge the postural control system, we applied participant-specific high accelerations of the support surface such that the postural demand was low for stepping responses and high for feet-in-place responses. We expected that postural demand modulated the power of intrinsic cortical oscillations. Independent component analysis and time-frequency domain statistics revealed stronger suppression of alpha (9-13 Hz) and low-gamma (31-34 Hz) rhythms in the supplementary motor area (SMA) when preparing for feet-in-place responses (i.e., high postural demand). Irrespective of the response condition, support-surface movements elicited broadband (3-17 Hz) power increase in the SMA and enhancement of the theta (3-7 Hz) rhythm in the anterior prefrontal cortex (PFC), anterior cingulate cortex (ACC), and bilateral sensorimotor cortices (M1/S1). Although the execution of reactive responses resulted in largely similar cortical dynamics, comparison between the bilateral M1/S1 showed that stepping responses corresponded with stronger suppression of the beta (13-17 Hz) rhythm in the M1/S1 contralateral to the support leg. Comparison between response conditions showed that feet-in-place responses corresponded with stronger enhancement of the theta (3-7 Hz) rhythm in the PFC. Our results provide novel insights into the cortical dynamics of SMA, PFC, and M1/S1 during the control of human balance.

Cognitive load reduces the effects of optic flow on gait and electrocortical dynamics during treadmill walking.

During navigation of complex environments, the brain must continuously adapt to both external demands, such as fluctuating sensory inputs, and internal demands, such as engagement in a cognitively demanding task. Previous studies have demonstrated changes in behavior and gait with increased sensory and cognitive load, but the underlying cortical mechanisms remain largely unknown. In the present study, in a mobile brain/body imaging (MoBI) approach, 16 young adults walked on a treadmill with high-density EEG while 3-dimensional (3D) motion capture tracked kinematics of the head and feet. Visual load was manipulated with the presentation of optic flow with and without continuous mediolateral perturbations. The effects of cognitive load were assessed by the performance of a go/no-go task on half of the blocks. During increased sensory load, participants walked with shorter and wider strides, which may indicate a more restrained pattern of gait. Interestingly, cognitive task engagement attenuated these effects of sensory load on gait. Using an independent component analysis and dipole-fitting approach, we found that cautious gait was accompanied by neuro-oscillatory modulations localized to frontal (supplementary motor area, anterior cingulate cortex) and parietal (inferior parietal lobule, precuneus) areas. Our results show suppression in alpha/mu (8-12 Hz) and beta (13-30 Hz) rhythms, suggesting enhanced activation of these regions with unreliable sensory inputs. These findings provide insight into the neural correlates of gait adaptation and may be particularly relevant to older adults who are less able to adjust to ongoing cognitive and sensory demands while walking. NEW & NOTEWORTHY The neural underpinnings of gait adaptation in humans are poorly understood. To this end, we recorded high-density EEG combined with three-dimensional body motion tracking as participants walked on a treadmill while exposed to full-field optic flow stimulation. Perturbed visual input led to a more cautious gait pattern with neuro-oscillatory modulations localized to premotor and parietal regions. Our findings show a possible brain-behavior link that might further our understanding of gait and mobility impairments.

Neural predictors of gait stability when walking freely in the real-world.

BACKGROUND: Gait impairments during real-world locomotion are common in neurological diseases. However, very little is currently known about the neural correlates of walking in the real world and on which regions of the brain are involved in regulating gait stability and performance. As a first step to understanding how neural control of gait may be impaired in neurological conditions such as Parkinson's disease, we investigated how regional brain activation might predict walking performance in the urban environment and whilst engaging with secondary tasks in healthy subjects. METHODS: We recorded gait characteristics including trunk acceleration and brain activation in 14 healthy young subjects whilst they walked around the university campus freely (single task), while conversing with the experimenter and while texting with their smartphone. Neural spectral power density (PSD) was evaluated in three brain regions of interest, namely the pre-frontal cortex (PFC) and bilateral posterior parietal cortex (right/left PPC). We hypothesized that specific regional neural activation would predict trunk acceleration data obtained during the different walking conditions. RESULTS: Vertical trunk acceleration was predicted by gait velocity and left PPC theta (4-7 Hz) band PSD in single-task walking (R-squared = 0.725, p = 0.001) and by gait velocity and left PPC alpha (8-12 Hz) band PSD in walking while conversing (R-squared = 0.727, p = 0.001). Medio-lateral trunk acceleration was predicted by left PPC beta (15-25 Hz) band PSD when walking while texting (R-squared = 0.434, p = 0.010). CONCLUSIONS: We suggest that the left PPC may be involved in the processes of sensorimotor integration and gait control during walking in real-world conditions. Frequency-specific coding was operative in different dual tasks and may be developed as biomarkers of gait deficits in neurological conditions during performance of these types of, now commonly undertaken, dual tasks.

The aging brain shows less flexible reallocation of cognitive resources during dual-task walking: A mobile brain/body imaging (MoBI) study.

Aging is associated with reduced abilities to selectively allocate attention across multiple domains. This may be particularly problematic during everyday multitasking situations when cognitively demanding tasks are performed while walking. Due to previous limitations in neuroimaging technology, much remains unknown about the cortical mechanisms underlying resource allocation during locomotion. Here, we utilized an EEG-based mobile brain/body imaging (MoBI) technique that integrates high-density event-related potential (ERP) recordings with simultaneously acquired foot-force sensor data to monitor gait patterns and brain activity concurrently. To assess effects of motor load on cognition we evaluated young (N=17; mean age=27.2) and older adults (N=16; mean age=63.9) and compared behavioral and ERP measures associated with performing a Go/No-Go response inhibition task as participants sat stationary or walked on a treadmill. Stride time and variability were also measured during task performance and compared to stride parameters obtained without task performance, thereby assessing effects of cognitive load on gait. Results showed that older, but not young adults' accuracy dropped significantly when performing the inhibitory task while walking. Young adults revealed ERP modulations at relatively early (N2 amplitude reduction) and later (earlier P3 latency) stages within the processing stream as motor load increased while walking. In contrast, older adults' ERP modulations were limited to later processing stages (increased P3 amplitude) of the inhibitory network. The relative delay and attenuation of ERP modulations accompanied by behavioral costs in older participants might indicate an age-associated loss in flexible resource allocation across multiple tasks. Better understanding of the neural underpinnings of these age-related changes may lead to improved strategies to reduce fall risk and enhance mobility in aging.

Recalibration of inhibitory control systems during walking-related dual-task interference: a mobile brain-body imaging (MOBI) study.

Walking while simultaneously performing cognitively demanding tasks such as talking or texting are typical complex behaviors in our daily routines. Little is known about neural mechanisms underlying cortical resource allocation during such mobile actions, largely due to portability limitations of conventional neuroimaging technologies. We applied an EEG-based Mobile Brain-Body Imaging (MOBI) system that integrates high-density event-related potential (ERP) recordings with simultaneously acquired foot-force sensor data to monitor gait patterns and brain activity. We compared behavioral and ERP measures associated with performing a Go/NoGo response-inhibition task under conditions where participants (N=18) sat in a stationary way, walked deliberately or walked briskly. This allowed for assessment of effects of increasing dual-task load (i.e. walking speed) on neural indices of inhibitory control. Stride time and variability were also measured during inhibitory task performance and compared to stride parameters without task performance, thereby assessing reciprocal dual-task effects on gait parameters. There were no task performance differences between sitting and either walking condition, indicating that participants could perform both tasks simultaneously without suffering dual-task costs. However, participants took longer strides under dual-task load, likely indicating an adaptive mechanism to reduce inter-task competition for cortical resources. We found robust differences in amplitude, latency and topography of ERP components (N2 and P3) associated with inhibitory control between the sitting and walking conditions. Considering that participants showed no dual-task performance costs, we suggest that observed neural alterations under increasing task-load represent adaptive recalibration of the inhibitory network towards a more controlled and effortful processing mode, thereby optimizing performance under dual-task situations.

Dual-layer electroencephalography data during real-world table tennis.

Real-world settings are necessary to improve the ecological validity of neuroscience research, and electroencephalography (EEG) facilitates mobile electrocortical recordings because of its easy portability and high temporal resolution. Table tennis is a whole-body, goal-directed sport that requires constant visuomotor feedback, anticipation, strategic decision-making, object interception, and performance monitoring - making it an interesting testbed for a variety of neuroscience studies. Although traditionally plagued by artifact contamination, recent advances in signal processing and hardware approaches, such as the dual-layer approach, have allowed high fidelity EEG recordings during whole-body maneuvers. Here, we present a dual-layer EEG dataset from 25 healthy human participants playing table tennis with a human opponent and a ball machine. Our dataset includes synchronized, multivariate time series recordings from 120 scalp electrodes, 120 noise electrodes, 8 neck electromyography electrodes, and inertial measurement units on the participant, paddles, and ball machine to record hit events. We also include de-identified T1 anatomical MR images and digitized electrode locations to create subject-specific head models for source localization. In addition, we provide anonymized video recordings and Adobe Premiere project files with hit events labeled (originally used to mark successful/missed hits). Researchers could use the videos to mark their own events of interest. We formatted our dataset in the Brain Imaging Data Structure (BIDS) format to facilitate data reuse and to adhere to the scientific community's new organization standard.

Parieto-Occipital Electrocortical Dynamics during Real-World Table Tennis.

Traditional human electroencephalography (EEG) experiments that study visuomotor processing use controlled laboratory conditions with limited ecological validity. In the real world, the brain integrates complex, dynamic, multimodal visuomotor cues to guide the execution of movement. The parietal and occipital cortices are especially important in the online control of goal-directed actions. Table tennis is a whole-body, responsive activity requiring rapid visuomotor integration that presents a myriad of unanswered neurocognitive questions about brain function during real-world movement. The aim of this study was to quantify the electrocortical dynamics of the parieto-occipital cortices while playing a sport with high-density electroencephalography. We included analysis of power spectral densities (PSDs), event-related spectral perturbations, intertrial phase coherences (ITPCs), event-related potentials (ERPs), and event-related phase coherences of parieto-occipital source-localized clusters while participants played table tennis with a ball machine and a human. We found significant spectral power fluctuations in the parieto-occipital cortices tied to hit events. Ball machine trials exhibited more fluctuations in θ power around hit events, an increase in intertrial phase coherence and deflection in the event-related potential, and higher event-related phase coherence between parieto-occipital clusters as compared with trials with a human. Our results suggest that sport training with a machine elicits fundamentally different brain dynamics than training with a human.

Virtual Reality for Spatial Navigation.

Immersive virtual reality (VR) allows its users to experience physical space in a non-physical world. It has developed into a powerful research tool to investigate the neural basis of human spatial navigation as an embodied experience. The task of wayfinding can be carried out by using a wide range of strategies, leading to the recruitment of various sensory modalities and brain areas in real-life scenarios. While traditional desktop-based VR setups primarily focus on vision-based navigation, immersive VR setups, especially mobile variants, can efficiently account for motor processes that constitute locomotion in the physical world, such as head-turning and walking. When used in combination with mobile neuroimaging methods, immersive VR affords a natural mode of locomotion and high immersion in experimental settings, designing an embodied spatial experience. This in turn facilitates ecologically valid investigation of the neural underpinnings of spatial navigation.

Stroop in motion: Neurodynamic modulation underlying interference control while sitting, standing, and walking.

There is conflicting evidence about how interference control in healthy adults is affected by walking as compared to standing or sitting. Although the Stroop paradigm is one of the best-studied paradigms to investigate interference control, the neurodynamics associated with the Stroop task during walking have never been studied. We investigated three Stroop tasks using variants with increasing interference levels - word-reading, ink-naming, and the switching of the two tasks, combined in a systematic dual-tasking fashion with three motor conditions - sitting, standing, and treadmill walking. Neurodynamics underlying interference control were recorded using the electroencephalogram. Worsened performance was observed for the incongruent compared to congruent trials and for the switching Stroop compared to the other two variants. The early frontocentral event-related potentials (ERPs) associated with executive functions (P2, N2) differentially signaled posture-related workloads, while the later stages of information processing indexed faster interference suppression and response selection in walking compared to static conditions. The early P2 and N2 components as well as frontocentral Theta and parietal Alpha power were sensitive to increasing workloads on the motor and cognitive systems. The distinction between the type of load (motor and cognitive) became evident only in the later posterior ERP components in which the amplitude non-uniformly reflected the relative attentional demand of a task. Our data suggest that walking might facilitate selective attention and interference control in healthy adults. Existing interpretations of ERP components recorded in stationary settings should be considered with care as they might not be directly transferable to mobile settings.

The effects of blurred visual inputs with different levels on the cerebral activity during free level walking.

Objective: The aim of this study was to evaluate the effects of blurred vision on electrocortical activities at different levels during walking. Materials and methods: A total of 22 healthy volunteers (all men; mean age: 24.4 ± 3.9 years) underwent an electroencephalography (EEG) test synchronous with free level walking. Visual status was simulated by goggles covered by the occlusion foil targeted at a Snellen visual acuity of 20/60 (V0.3), 20/200 (V0.1), and light perception (V0). At each of these conditions, the participants completed barefoot walking for five blocks of 10 m. The EEG signals were recorded by a wireless EEG system with electrodes of interest, namely, Cz, Pz, Oz, O1, and O2. The gait performances were assessed by the Vicon system. Results: During walking with normal vision (V1.0), there were cerebral activities related to visual processing, characterized as higher spectral power of delta (Oz and O2 vs. Cz, Pz, and O1, p ≤ 0.033) and theta (Oz vs. Cz and O1, p = 0.044) bands in occipital regions. Moderately blurred vision (V0.3) would attenuate the predominance of delta- and theta-band activities at Oz and O2, respectively. At the statuses of V0.1 and V0, the higher power of delta (at V0.1 and V0, Oz, and O2 vs. Cz, Pz, and O1, p ≤ 0.047) and theta bands (at V0.1, Oz vs. Cz, p = 0.010; at V0, Oz vs. Cz, Pz, and O1, p ≤ 0.016) emerged again. The cautious gait pattern, characterized by a decrease in gait speed (p < 0.001), a greater amplitude of deviation from the right ahead (p < 0.001), a prolonged stance time (p = 0.001), a restricted range of motion in the hip on the right side (p ≤ 0.010), and an increased knee flexion during stance on the left side (p = 0.014), was only detected at the status of V0. The power of the alpha band at the status of V0 was higher than that at V1.0, V0.3, and V0.1 (p ≤ 0.011). Conclusion: Mildly blurred visual inputs would elicit generalization of low-frequency band activity during walking. In circumstance to no effective visual input, locomotor navigation would rely on cerebral activity related to visual working memory. The threshold to trigger the shift might be the visual status that is as blurred as the level of Snellen visual acuity of 20/200.