Neural Correlates of Human Cognition in Real-World Environments

According to embodied accounts of human cognition, the mind is at the interface of the body and the environment. For practical reasons, however, neuroscientific research on human cognition has mostly been confined to the laboratory until now. The emergence of portable brain and body imaging research methods offers an unprecedented opportunity to capture the expression of cognitive processes during active behaviours performed in real-world contexts. In the present thesis, electroencephalography (EEG) was used to investigate embodied aspects of human cognition in motion and in the real-world. This approach, however, presents new challenges in terms of signal processing because of the increased noise related to whole body movements. As the necessary signal processing tools were not well-established, the current work involved the development of new solutions to address the specific requirements of mobile EEG data before real-world brain recordings could be validly interpreted. In a series of Event Related Potential (ERP) experiments, real-world conditions were compared to traditional lab-based conditions. The neural marker of attention (P300 ERP) was recorded when participants performed an attentional task while walking through the university’s corridors versus standing in the lab. Differences in the classic P300 ERP effect show that attentional processes in the real-world are not the same as those recorded in the lab. Following up on this finding, the attenuation of the P300 effect under real-world conditions was shown to be driven by cognitive demands related to displacement through space rather than the act of walking itself. This is a demonstration, at a brain level, that when walking in the real-world, cognitive resources are reallocated to the processing of visual flow and vestibular information associated with displacement. The findings reflect the dynamic interplay between mind, body, and environment, providing innovative evidence strengthening the embodied framework of human cognition. The same dynamic interplay between body, environment and cognitive function is uniquely represented in real-world navigation. The literature on spatial navigation in humans, however, mainly involved navigating virtual reality environments often while lying on a scanner bed. Most of the evidence on the neural markers of spatial navigation comes from intracranially recorded brain oscillations in rodents. The innovation in this thesis was to investigate brain oscillations associated with cognitive function underlying real-world navigation in humans using surface electrodes. The present work demonstrates that human brain dynamics related to navigational cognitive processes can be recorded in active exploration of real-world environments. The key finding resulting from this novel approach is that real-world spatial navigation is associated with specific neural signatures underlying distinct cognitive functions. Frontal low-frequency oscillations were found to be associated with wayfinding, while parietal high-frequency oscillations were associated with spatial memory. Furthermore, these neural correlates were found to be dynamically modulated depending on the body’s contextual positioning within the environment. Therefore, these findings again provide evidence in support of the embodiment theory of cognition. The final study addressed the concern that findings might reflect walking speed variation. The existing animal literature has shown that low-frequency bands are modulated by walking speed. This study characterised the specific modulations in spectral power as a function of walking speed in humans. Critically the pattern showed no similarity to the spectral patterns found in relation to real-world spatial navigation, confirming the cognitive interpretation of this work. Taken together, these findings provide innovative real-world evidence supporting the theoretical embodiment framework. The neural correlates of attention, memory, and spatial navigation were found to be modulated by the dynamic experience of one’s environment. Beyond this work’s theoretical implications for cognitive sciences, the present findings offer new perspectives for real-world application

Understanding Minds in Real-World Environments: Toward a Mobile Cognition Approach

There is a growing body of evidence that important aspects of human cognition have been marginalized, or overlooked, by traditional cognitive science. In particular, the use of laboratory-based experiments in which stimuli are artificial, and response options are fixed, inevitably results in findings that are less ecologically valid in relation to real-world behavior. In the present review we highlight the opportunities provided by a range of new mobile technologies that allow traditionally lab-bound measurements to now be collected during natural interactions with the world. We begin by outlining the theoretical support that mobile approaches receive from the development of embodied accounts of cognition, and we review the widening evidence that illustrates the importance of examining cognitive processes in their context. As we acknowledge, in practice, the development of mobile approaches brings with it fresh challenges, and will undoubtedly require innovation in paradigm design and analysis. If successful, however, the mobile cognition approach will offer novel insights in a range of areas, including understanding the cognitive processes underlying navigation through space and the role of attention during natural behavior. We argue that the development of real-world mobile cognition offers both increased ecological validity, and the opportunity to examine the interactions between perception, cognition and action—rather than examining each in isolation

Understanding minds in real-world environments : toward a mobile cognition approach

This work is supported by a scholarship from the University of Stirling and a research grant from SINAPSE (Scottish Imaging Network: A Platform for Scientific Excellence).There is a growing body of evidence that important aspects of human cognition have been marginalized, or overlooked, by traditional cognitive science. In particular, the use of laboratory-based experiments in which stimuli are artificial, and response options are fixed, inevitably results in findings that are less ecologically valid in relation to real-world behavior. In the present review we highlight the opportunities provided by a range of new mobile technologies that allow traditionally lab-bound measurements to now be collected during natural interactions with the world. We begin by outlining the theoretical support that mobile approaches receive from the development of embodied accounts of cognition, and we review the widening evidence that illustrates the importance of examining cognitive processes in their context. As we acknowledge, in practice, the development of mobile approaches brings with it fresh challenges, and will undoubtedly require innovation in paradigm design and analysis. If successful, however, the mobile cognition approach will offer novel insights in a range of areas, including understanding the cognitive processes underlying navigation through space and the role of attention during natural behavior. We argue that the development of real-world mobile cognition offers both increased ecological validity, and the opportunity to examine the interactions between perception, cognition and action—rather than examining each in isolation.Publisher PDFPeer reviewe

Mobile EEG identifies the re-allocation of attention during real-world activity

S.L., M.I. and D.I.D. are members of the SINAPSE collaboration (www.sinapse.ac.uk), a pooling initiative funded by the Scottish Funding Council and the Chief Scientific Office of the Scottish Executive.The distribution of attention between competing processing demands can have dramatic real-world consequences, however little is known about how limited attentional resources are distributed during real-world behaviour. Here we employ mobile EEG to characterise the allocation of attention across multiple sensory-cognitive processing demands during naturalistic movement. We used a neural marker of attention, the Event-Related Potential (ERP) P300 effect, to show that attention to targets is reduced when human participants walk compared to when they stand still. In a second experiment, we show that this reduction in attention is not caused by the act of walking per se. A third experiment identified the independent processing demands driving reduced attention to target stimuli during motion. ERP data reveals that the reduction in attention seen during walking reflects the linear and additive sum of the processing demands produced by visual and inertial stimulation. The mobile cognition approach used here shows how limited resources are precisely re-allocated according to the sensory processing demands that occur during real-world behaviour.Publisher PDFPeer reviewe

Mobile EEG reveals functionally dissociable dynamic processes supporting real-world ambulatory obstacle avoidance : evidence for early proactive control

This work is supported by a scholarship from the University of Stirling and a reseach grant from SINAPSE (Scottish Imaging Network: A Platform for Scientific excellence). GL is supported by the Wellcome Trust [209209/Z/17/Z].The ability to safely negotiate the world on foot takes humans years to develop, reflecting the huge cognitive demands associated with real‐time planning and control of walking. Despite the importance of walking, methodological limitations mean that surprisingly little is known about the neural and cognitive processes that support ambulatory motor control. Here, we report mobile EEG data recorded from thirty‐two healthy young adults during real‐world ambulatory obstacle avoidance. Participants walked along a path while stepping over expected and unexpected obstacles projected on the floor, allowing us to capture the dynamic oscillatory response to changes in environmental demands. Compared to obstacle‐free walking, time‐frequency analysis of the EEG data revealed clear frontal theta and centro‐parietal beta power neural markers of proactive and reactive forms of movement control (occurring before and after crossing an obstacle). Critically, the temporal profile of changes in frontal theta allowed us to arbitrate between early selection and late adaptation mechanisms of proactive control. Our data show that motor plans are updated as soon as an upcoming obstacle appears, rather than when the obstacle is reached. In addition, regardless of whether motor plans required updating, a clear beta rebound was present after obstacles were crossed, reflecting the resetting of the motor system. Overall, mobile EEG recorded during real‐world walking provides novel insight into the cognitive and neural basis of dynamic motor control in humans, suggesting new routes to the monitoring and rehabilitation of motor disorders such as dyspraxia and Parkinson’s disease.Publisher PDFPeer reviewe

Retrospective on the First Passive Brain-Computer Interface Competition on Cross-Session Workload Estimation

International audienceAs is the case in several research domains, data sharing is still scarce in the field of Brain-Computer Interfaces (BCI), and particularly in that of passive BCIs— i.e ., systems that enable implicit interaction or task adaptation based on a user's mental state(s) estimated from brain measures. Moreover, research in this field is currently hindered by a major challenge, which is tackling brain signal variability such as cross-session variability. Hence, with a view to develop good research practices in this field and to enable the whole community to join forces in working on cross-session estimation, we created the first passive brain-computer interface competition on cross-session workload estimation. This competition was part of the 3rd International Neuroergonomics conference. The data were electroencephalographic recordings acquired from 15 volunteers (6 females; average 25 y.o.) who performed 3 sessions—separated by 7 days—of the Multi-Attribute Task Battery-II (MATB-II) with 3 levels of difficulty per session (pseudo-randomized order). The data -training and testing sets—were made publicly available on Zenodo along with Matlab and Python toy code ( https://doi.org/10.5281/zenodo.5055046 ). To this day, the database was downloaded more than 900 times (unique downloads of all version on the 10th of December 2021: 911). Eleven teams from 3 continents (31 participants) submitted their work. The best achieving processing pipelines included a Riemannian geometry-based method. Although better than the adjusted chance level (38% with an α at 0.05 for a 3-class classification problem), the results still remained under 60% of accuracy. These results clearly underline the real challenge that is cross-session estimation. Moreover, they confirmed once more the robustness and effectiveness of Riemannian methods for BCI. On the contrary, chance level results were obtained by one third of the methods—4 teams- based on Deep Learning. These methods have not demonstrated superior results in this contest compared to traditional methods, which may be due to severe overfitting. Yet this competition is the first step toward a joint effort to tackle BCI variability and to promote good research practices including reproducibility

Development of a new diagnosis test for simultanagnosia

Simultanagnosia is a neurological disorder caused by bilateral lesions to the occipitoparietal brain regions. The disorder causes an inability to attend to more than one object or one feature at once. The ambition of this project was to create an ecological diagnosis tool to investigate patterns of visual exploration in normal perceivers and patients with simultanagnosia while looking at everyday scenes. The scenes were manipulated by having a neutral or busy background, having 2 or 3 actors present in the scene, and by having the actors interacting with each other or not. We administrated homemade videos to 40 control participants (24 women, mean age: 21.4). The principal aim of the study was to create norms from which to investigate a patient with simultanagnosia. The participants were asked to simply look at the videos, so that they could describe what they saw at the end of each scene. Presentation order of the scenes was randomized. Participants' eye movements were recorded using an Eyelink 1000 eye-tracking device. The eye tracking analyses consisted of measuring the proportion of total fixation time to regions of interest within each scene. We defined these regions in accordance to the relevant elements of the scene (e.g., the position of the actors, and the area of interaction). The results showed that participants’ attention to the scene was moderated by the number of actors, and by their interactivity. However, there was no significant effect of the background manipulation. The results are discussed in terms of the creation of a new diagnosis test for patients with simultanagnosia.Mémoire de master [120] en sciences psychologiques, Université catholique de Louvain, 201

Predikce navigačních rozhodnutí v reálném světě: Rozhraní mozek-počítač založené na vizuálních evokovaných potenciálech P300

Navzdory široké dostupnosti přenosných EEG systémů se současné aplikace rozhraní mozek-počítač (BCI) do značné míry omezují na laboratorní a klinické prostředí. V této studii bylo paradigma vizuální P300 použito k vyvolání mozkových odpovědí odrážejících navigační rozhodování v reálném světě. Účastníci (n = 8) byli během experimentu vybaveni tabletem a mobilním systémem EEG, a následně vyzvání k navigaci po univerzitních chodbách. Po dosažení křižovatky byly účastníkům prezentovány šipky vlevo a vpravo blikající na tabletu (a další nesměrové podněty typu distraktor). Spolu s navigačními rozhodnutími účastníka byly zaznamenány neurální reakce vyvolané prezentací těchto stimulů (evokované potenciály). Účastníci absolvovali dvě samostatná sezení, abychom získali data pro trénování i testování off-line BCI systému zaměřeného na předpovídání jejich navigačních rozhodnutí na základě extrakce příznaků evokovaných potenciálů. Spolehlivost single-trial klasifikace dosáhla 59,6 % (až 72,3 % při klasifikaci průměrů šesti epoch). Výsledky klasifikace byly porovnány se statistickou analýzou evokovaných potenciálů. Diskuze výsledků rozebírá důsledky pro návrh BCI systémů v reálném světě a navrhuje několik doporučení k jejich zlepšení.Despite the widespread availability of portable neuroimaging systems, current applications of brain-computer interfaces (BCI) have largely remained confined to laboratory and clinical settings. In the present study, a visual P300 paradigm was used to elicit neural responses reflective of decision making within the frame of real-world navigation. Participants (n = 8) were equipped with a tablet and a mobile EEG system while navigating through university corridors. Upon reaching an intersection, participants were presented with left and right arrows flashing on the tablet (and additional non-directional stimuli in the distractor condition). Neural responses elicited by the presentation of such stimuli (Event-Related Potentials) were recorded along with the participant's navigational decisions. The participants completed two separate sessions to collect data for both the training and testing of an offline BCI system aimed at predicting their navigational decisions based on the extraction of event-related potentials features. Single-trial classification accuracy reached 59.6 % (up to 72.3 % when classifying group averages of six trials). Individual classification results were contrasted with single-trial analysis. Results are discussed in terms of their implications for the design of real-world BCI applications, and several recommendations to improve experimental protocols are proposed