Mobile Brain/Body Imaging (MoBI) is a rapidly emerging technology to study how brain activity supports naturalistic human interactions with complex, real-world environments. Major advances in our understanding of the neural correlates of human behavior and cognition have been made using well-designed experimental tasks paired with neuroimaging. However, due to technological constraints, these approaches have been largely confined to a relatively small repertoire of tasks performed in highly controlled, laboratory environments that do not reflect the dynamic and complex nature of real-world contexts where human behavior normally takes place.
Recent technological advancements in portable biomedical recording devices and computational approaches have increased the accessibility of MoBI-relevant recording systems, creating opportunities to increase the use of this promising approach to study naturalistic human cognition and behavior in ecologically valid contexts. These developments, especially the capability of wearable sensors to simultaneously record brain activity with a multitude of behavioral variables enabled a paradigm shift in experimental designs where behavior is precisely captured instead of constrained. Therefore, MoBI approaches grant detailed investigations of naturalistic human behavior that in turn, is well-suited to inform analyses of brain activities supporting these behaviors.
In fact, MoBI has recently been referred to “as a new frontier in the field of human cognitive neuroscience” due to a growing literature showing both the feasibility and broad application of this technology to study human behavior in naturalistic settings. By focusing on the core principles of MoBI paired with a diverse array of exemplar applications, this interactive symposium will provide the audience with knowledge of the basic concepts and opportunities that hold promise for unraveling the neural mechanisms supporting human cognition across a wide breadth of behaviors performed in real-world environments.
By the end of the session, attendees will be able to:
1. Understand the history, goals, and core principles of the MoBI research framework
2. Summarize and compare diverse basic, real-world, and clinical research applications of the MoBI concept to observe and understand brain dynamics in the context of naturalistic behaviors and environments
3. Identify at least one future direction of MoBI research specific to their research interests
The topic should be of both general and specific interest to OHBM attendees, thus, the symposium is targeting attendees at any career stage that are interested in simultaneous measurements of brain activity and human behavior during human-environment interactions. The level of content will be balanced between introducing core principles of the MoBI concept and more advanced examples of novel applications that span the disciplines of neuroscience, psychology, and rehabilitation.
Walking can be an essential motor skill for independent living. However, even daily walking may compete with other concurrent activities, such as navigating routes, for limited shared resources. Age-related changes in cognitive or motor skills, as well as potential dependencies between tasks, can lead to performance declines in one or both tasks (e.g. Fraser & Bherer, 2013).
Despite the application of various behavioral, kinematic, and neurophysiological measures, a comprehensive understanding of cognitive motor interference in dual-task walking has not yet been achieved. Behavioral studies in realistic movement conditions lack sufficient information about the sources and timing of sub-processes that drive observable behavior. Neuroimaging studies, on the other hand, are often conducted in restricted and artificially induced movement scenarios due to the technical constraints of several imaging modalities. For a deeper understanding of performance in dual-task scenarios, it is essential to combine different types of data recorded in scenarios that allow for natural behavior.
In this presentation, I will outline our recent Mobile Brain/Body Imaging (MoBI, Makeig et al., 2009; Gramann et al., 2011; 2014) research on age-related performance changes during dual-task walking. We conducted two studies to examine the behavioral and EEG data from younger (< 35 years) and older participants (>65 years) as they completed simple visual tasks while sitting, standing, and walking on level ground. We observed that dual-task walking had a greater impact on older participants as compared to younger participants. This was characterized by a decrease in walking speed, diminished visual task accuracy and reduced amplitudes and prolonged latencies of the event-related potential P1. While walking, delayed responses in the visual task were linked to prolonged P1 latencies, and reduced P1 amplitudes were associated with an increased number of missed visual targets in both groups (Protzak, Wiczorek & Gramann, 2021). Time-frequency data analysis revealed that power modulations within motor cortex areas between button presses performed while sitting and walking were reduced in older participants, and less pronounced changes in the beta and alpha band were associated with a greater reduction in walking speed in both groups (Protzak, Wiczorek & Gramann, 2021). Our current analysis indicates that modulations in the periodic component of the power spectrum of motor cortex areas are linked to changes in walking speed when shifting from single-task to dual-task walking.
Our results contribute to the understanding of cognitive-motor interference during dual-task walking in younger and older adults. We observed changes in early attentional-perceptual processing and motor resource allocation that were related to the task and the age group, even in simple dual-task paradigms.
The hippocampus is commonly associated with processing of allocentric spatial information tested in stationary setups, yet its interaction with physical locomotion in humans requires further investigation.
We implemented human scale virtual Morris Water Maze in desktop and mobile VR and analysed the EEG dynamics in individuals with right medial temporal lesions. Behaviourally (Iggena et al., 2023), the lesioned group showed greater improvement in navigation performance than controls when they had access to multisensory input from physical movement. The EEG power dynamics corroborates our interpretation of the behavioural findings that patients’ strategy relies on continuous integration of body-based information and its absence in desktop VR leads to exertion of greater cognitive effort in the group. Their strategy was reflected in the motion capture data indicating that patients preferred to replicate the previously walked trajectories and higher theta activity in the middle of stationary trials. On the other hand, the relationship between the oscillatory EEG dynamics and performance in controls implies that their performance in mobile VR depends on landmark-based planning at the beginning of a trial. Analysis of motion and EEG data revealed an increase in head angular velocity and the EEG theta power in the control group at the onset of mobile trials.
In summary, the mobile EEG data support our previous findings that patients compensate for attenuated hippocampal input using body-based instead of landmark-based navigation strategy. The results highlight the strength of MoBI in providing the full picture of brain-behavioral dynamics underlying naturalistic navigation which is not as readily accessible using stationary neuroimaging setups alone.
, Technical University Berlin Berlin
Recent neurotechnological developments have enabled the study of real-world navigation in humans. Previous research in freely-moving rodents proposed a central role of the medial temporal lobe’s (MTL) involvement in spatial navigation and the formation of novel memory. Whether navigation and memory paradigms elicit functional similarities in the human MTL, which might generalize to more abstract cognitive domains such as imagination, remains unknown.
Here, we examined motion capture and intracranial electroencephalography (iEEG) from participants who had undergone chronic implantation of the responsive neurostimulation device, RNS System (NeuroPace, Inc.) for the treatment of epilepsy. We instructed participants to navigate two routes, including four turns each, in the real-world and imagine navigating the very same routes. Participants learned to perform this real-world spatial navigation task in an indoor room (14.6 × 13.5 m2) fully equipped with motion capture. Feedback on their performance was derived from motion capture and displayed on a tablet screen to refine their walking routes after each run by overlaying their actual movement trajectories recorded with motion capture on the ideal, instructed routes. After each actual walk, participants walked on a treadmill while imagining these walking routes in their minds.
Mobile iEEG was recorded from electrodes located in the deep brain within the MTL. In agreement with previous reports, transient theta oscillations were evident in each participant at spectral peaks in the 3-10 Hz frequency range. Short-lasting theta bouts frequently occurred at upcoming turns and formed temporal dynamics resembling the maze structure consistently across trials (30-35, left/right walks each). Similarly, we found that theta bouts occurred at specific time points during imagined navigation but not during sole treadmill walking, which we used as a control condition. These theta dynamics encoded the routes’ geometry comparably during real-world and imagined navigation. In both types of navigation, temporally structured theta bouts were present at the same anatomical locations, suggesting the involvement of similar functional networks supporting real-world and imagined navigation. Visual flow was absent during imagined navigation and bodily cues were identical to sole treadmill walking. Therefore, these findings demonstrate the capability of the MTL to internally generate theta dynamics relevant for memory retrieval and spontaneous imagination in the absence of environmental cues.
Altogether, our results open up novel avenues to study real-world spatial navigation, episodic memory, imagination, and possible future behaviors. The non-continuous but structured nature of human theta oscillations we report enables the opportunity to compare the timing and structure of these transient oscillations across cognitive tasks and behaviors. In studies including human participants, imaginations can be instructed and verbally reported, allowing the investigation of the neural mechanisms of abstract, hypothetical, or unprecedented future scenarios parallel to real-world behaviors.
Martin Seeber, PhD
, University of California - Los Angeles Los Angeles, CA
Our brains have evolved to optimize the outcomes of our behavior. Fifteen years ago, based on our research on EEG source imaging, I and my colleagues proposed that it was time that human cognitive neuroscience broke out of its confining box in which participant heads are held rigidly still during experiments designed to record only very low-dimensional behavior (e.g., sparse, minimal button press actions). As our ICA decomposition technique can separate activity recorded in scalp EEG from eye movements, muscle activity, and cortical activity, it was now possible to collect and analyze high-density EEG data from participants who were performing naturally motivated actions in 3D environments, thereby offering a first opportunity to study the natural cognition of humans. I believed this to be the natural progression from 19th century psychophysics through 20th century psychophysiology to a new (21st century) era of what I called mobile brain/body imaging or MoBI, recording What the brain does (using EEG), What the brain experiences (using scene and event recording), and What the brain controls (using high-definition body and eye movement recording) during a wide range of possible tasks and scenarios. The intervening decade and a half have confirmed the importance and widespread interest in experiments involving multimodal recording to advance cognitive and medical neuroscience understanding. Continuing progress in microelectronics have made mobile recording ever more convenient and less expensive to perform. There has been perhaps less progress in developing mathematical tools marrying kinetics and biomechanics models to models of brain activity - an important task for the future whose potential value is dramatized by the recent successes of deep learning approaches.
Scott Makeig, PhD
, University of California - San Diego
Institute for Neural Computation