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Parada FJ, Grasso-Cladera A, Rossi A, Soto-Icaza P, Arenas-Pérez M, Errázuriz MC. Applied human neuroscience: Fostering and designing inclusive environments with the 3E-Cognition perspective. Eur J Neurosci 2024; 60:4148-4168. [PMID: 39001625 DOI: 10.1111/ejn.16463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Revised: 06/17/2024] [Accepted: 06/26/2024] [Indexed: 08/07/2024]
Abstract
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.
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Affiliation(s)
- Francisco J Parada
- Centro de Estudios en Neurociencia Humana y Neuropsicología (CENHN), Facultad de Psicología, Universidad Diego Portales, Santiago, Chile
- Escuela de Diseño, Facultad de Arquitectura, Arte y Diseño, Universidad Diego Portales, Santiago, Chile, Salvador Sanfuentes 2221, Santiago, Metropolitan, Chile
| | | | - Alejandra Rossi
- Centro de Estudios en Neurociencia Humana y Neuropsicología (CENHN), Facultad de Psicología, Universidad Diego Portales, Santiago, Chile
| | - Patricia Soto-Icaza
- Laboratorio de Neurociencia Social y Neuromodulación, Centro de Investigación en Complejidad Social (neuroCICS), Facultad de Gobierno, Universidad del Desarrollo, Santiago, Chile
| | - Maritza Arenas-Pérez
- Centro de Estudios en Neurociencia Humana y Neuropsicología (CENHN), Facultad de Psicología, Universidad Diego Portales, Santiago, Chile
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Callan DE, Torre–Tresols JJ, Laguerta J, Ishii S. Shredding artifacts: extracting brain activity in EEG from extreme artifacts during skateboarding using ASR and ICA. FRONTIERS IN NEUROERGONOMICS 2024; 5:1358660. [PMID: 38989056 PMCID: PMC11233536 DOI: 10.3389/fnrgo.2024.1358660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Accepted: 05/30/2024] [Indexed: 07/12/2024]
Abstract
Introduction To understand brain function in natural real-world settings, it is crucial to acquire brain activity data in noisy environments with diverse artifacts. Electroencephalography (EEG), while susceptible to environmental and physiological artifacts, can be cleaned using advanced signal processing techniques like Artifact Subspace Reconstruction (ASR) and Independent Component Analysis (ICA). This study aims to demonstrate that ASR and ICA can effectively extract brain activity from the substantial artifacts occurring while skateboarding on a half-pipe ramp. Methods A dual-task paradigm was used, where subjects were presented with auditory stimuli during skateboarding and rest conditions. The effectiveness of ASR and ICA in cleaning artifacts was evaluated using a support vector machine to classify the presence or absence of a sound stimulus in single-trial EEG data. The study evaluated the effectiveness of ASR and ICA in artifact cleaning using five different pipelines: (1) Minimal cleaning (bandpass filtering), (2) ASR only, (3) ICA only, (4) ICA followed by ASR (ICAASR), and (5) ASR preceding ICA (ASRICA). Three skateboarders participated in the experiment. Results Results showed that all ICA-containing pipelines, especially ASRICA (69%, 68%, 63%), outperformed minimal cleaning (55%, 52%, 50%) in single-trial classification during skateboarding. The ASRICA pipeline performed significantly better than other pipelines containing ICA for two of the three subjects, with no other pipeline performing better than ASRICA. The superior performance of ASRICA likely results from ASR removing non-stationary artifacts, enhancing ICA decomposition. Evidenced by ASRICA identifying more brain components via ICLabel than ICA alone or ICAASR for all subjects. For the rest condition, with fewer artifacts, the ASRICA pipeline (71%, 82%, 75%) showed slight improvement over minimal cleaning (73%, 70%, 72%), performing significantly better for two subjects. Discussion This study demonstrates that ASRICA can effectively clean artifacts to extract single-trial brain activity during skateboarding. These findings affirm the feasibility of recording brain activity during physically demanding tasks involving substantial body movement, laying the groundwork for future research into the neural processes governing complex and coordinated body movements.
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Affiliation(s)
- Daniel E. Callan
- Brain Information Communication Research Laboratory, Advanced Telecommunications Research Institute International, Kyoto, Japan
- Institut Supérieur de l'Aéronautique et de l'Espace, University of Toulouse, Toulouse, France
| | - Juan Jesus Torre–Tresols
- Brain Information Communication Research Laboratory, Advanced Telecommunications Research Institute International, Kyoto, Japan
- Institut Supérieur de l'Aéronautique et de l'Espace, University of Toulouse, Toulouse, France
| | - Jamie Laguerta
- Brain Information Communication Research Laboratory, Advanced Telecommunications Research Institute International, Kyoto, Japan
- Department of Integrated Engineering, University of British Columbia, Vancouver, BC, Canada
| | - Shin Ishii
- Brain Information Communication Research Laboratory, Advanced Telecommunications Research Institute International, Kyoto, Japan
- Graduate School of Informatics, Kyoto University, Kyoto, Japan
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Brandt-Rauf PW, Ayaz H. Occupational Health and Neuroergonomics: The Future of Wearable Neurotechnologies at the Workplace. J Occup Environ Med 2024; 66:456-460. [PMID: 38829949 DOI: 10.1097/jom.0000000000003080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/05/2024]
Affiliation(s)
- Paul W Brandt-Rauf
- From the School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, Pennsylvania
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Feder S, Miksch J, Grimm S, Krems JF, Bendixen A. Using event-related brain potentials to evaluate motor-auditory latencies in virtual reality. FRONTIERS IN NEUROERGONOMICS 2023; 4:1196507. [PMID: 38234486 PMCID: PMC10790907 DOI: 10.3389/fnrgo.2023.1196507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 06/14/2023] [Indexed: 01/19/2024]
Abstract
Actions in the real world have immediate sensory consequences. Mimicking these in digital environments is within reach, but technical constraints usually impose a certain latency (delay) between user actions and system responses. It is important to assess the impact of this latency on the users, ideally with measurement techniques that do not interfere with their digital experience. One such unobtrusive technique is electroencephalography (EEG), which can capture the users' brain activity associated with motor responses and sensory events by extracting event-related potentials (ERPs) from the continuous EEG recording. Here we exploit the fact that the amplitude of sensory ERP components (specifically, N1 and P2) reflects the degree to which the sensory event was perceived as an expected consequence of an own action (self-generation effect). Participants (N = 24) elicit auditory events in a virtual-reality (VR) setting by entering codes on virtual keypads to open doors. In a within-participant design, the delay between user input and sound presentation is manipulated across blocks. Occasionally, the virtual keypad is operated by a simulated robot instead, yielding a control condition with externally generated sounds. Results show that N1 (but not P2) amplitude is reduced for self-generated relative to externally generated sounds, and P2 (but not N1) amplitude is modulated by delay of sound presentation in a graded manner. This dissociation between N1 and P2 effects maps back to basic research on self-generation of sounds. We suggest P2 amplitude as a candidate read-out to assess the quality and immersiveness of digital environments with respect to system latency.
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Affiliation(s)
- Sascha Feder
- Cognitive Systems Lab, Institute of Physics, Faculty of Natural Sciences, Chemnitz University of Technology, Chemnitz, Germany
| | - Jochen Miksch
- Cognitive Systems Lab, Institute of Physics, Faculty of Natural Sciences, Chemnitz University of Technology, Chemnitz, Germany
- Physics of Cognition Group, Institute of Physics, Faculty of Natural Sciences, Chemnitz University of Technology, Chemnitz, Germany
| | - Sabine Grimm
- Cognitive Systems Lab, Institute of Physics, Faculty of Natural Sciences, Chemnitz University of Technology, Chemnitz, Germany
- Physics of Cognition Group, Institute of Physics, Faculty of Natural Sciences, Chemnitz University of Technology, Chemnitz, Germany
| | - Josef F. Krems
- Research Group Cognitive and Engineering Psychology, Institute of Psychology, Faculty of Behavioural and Social Sciences, Chemnitz University of Technology, Chemnitz, Germany
| | - Alexandra Bendixen
- Cognitive Systems Lab, Institute of Physics, Faculty of Natural Sciences, Chemnitz University of Technology, Chemnitz, Germany
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Callan DE, Fukada T, Dehais F, Ishii S. The role of brain-localized gamma and alpha oscillations in inattentional deafness: implications for understanding human attention. Front Hum Neurosci 2023; 17:1168108. [PMID: 37305364 PMCID: PMC10248426 DOI: 10.3389/fnhum.2023.1168108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 04/27/2023] [Indexed: 06/13/2023] Open
Abstract
Introduction The processes involved in how the attention system selectively focuses on perceptual and motor aspects related to a specific task, while suppressing features of other tasks and/or objects in the environment, are of considerable interest for cognitive neuroscience. The goal of this experiment was to investigate neural processes involved in selective attention and performance under multi-task situations. Several studies have suggested that attention-related gamma-band activity facilitates processing in task-specific modalities, while alpha-band activity inhibits processing in non-task-related modalities. However, investigations into the phenomenon of inattentional deafness/blindness (inability to observe stimuli in non-dominant task when primary task is demanding) have yet to observe gamma-band activity. Methods This EEG experiment utilizes an engaging whole-body perceptual motor task while carrying out a secondary auditory detection task to investigate neural correlates of inattentional deafness in natural immersive high workload conditions. Differences between hits and misses on the auditory detection task in the gamma (30-50 Hz) and alpha frequency (8-12 Hz) range were carried out at the cortical source level using LORETA. Results Participant auditory task performance correlated with an increase in gamma-band activity for hits over misses pre- and post-stimulus in left auditory processing regions. Alpha-band activity was greater for misses relative to hits in right auditory processing regions pre- and post-stimulus onset. These results are consistent with the facilitatory/inhibitory role of gamma/alpha-band activity for neural processing. Additional gamma- and alpha-band activity was found in frontal and parietal brain regions which are thought to reflect various attentional monitoring, selection, and switching processes. Discussion The results of this study help to elucidate the role of gamma and alpha frequency bands in frontal and modality-specific regions involved with selective attention in multi-task immersive situations.
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Affiliation(s)
- Daniel E. Callan
- Brain Information Communication Research Laboratory, Advanced Telecommunications Research Institute International, Kyoto, Japan
- Institut Supérieur de l'Aéronautique et de l'Espace, University of Toulouse, Toulouse, France
| | - Takashi Fukada
- Brain Information Communication Research Laboratory, Advanced Telecommunications Research Institute International, Kyoto, Japan
- Graduate School of Informatics, Kyoto University, Kyoto, Japan
| | - Frédéric Dehais
- Institut Supérieur de l'Aéronautique et de l'Espace, University of Toulouse, Toulouse, France
| | - Shin Ishii
- Brain Information Communication Research Laboratory, Advanced Telecommunications Research Institute International, Kyoto, Japan
- Graduate School of Informatics, Kyoto University, Kyoto, Japan
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Rosenkranz M, Cetin T, Uslar VN, Bleichner MG. Investigating the attentional focus to workplace-related soundscapes in a complex audio-visual-motor task using EEG. FRONTIERS IN NEUROERGONOMICS 2023; 3:1062227. [PMID: 38235454 PMCID: PMC10790850 DOI: 10.3389/fnrgo.2022.1062227] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 12/16/2022] [Indexed: 01/19/2024]
Abstract
Introduction In demanding work situations (e.g., during a surgery), the processing of complex soundscapes varies over time and can be a burden for medical personnel. Here we study, using mobile electroencephalography (EEG), how humans process workplace-related soundscapes while performing a complex audio-visual-motor task (3D Tetris). Specifically, we wanted to know how the attentional focus changes the processing of the soundscape as a whole. Method Participants played a game of 3D Tetris in which they had to use both hands to control falling blocks. At the same time, participants listened to a complex soundscape, similar to what is found in an operating room (i.e., the sound of machinery, people talking in the background, alarm sounds, and instructions). In this within-subject design, participants had to react to instructions (e.g., "place the next block in the upper left corner") and to sounds depending on the experimental condition, either to a specific alarm sound originating from a fixed location or to a beep sound that originated from varying locations. Attention to the alarm reflected a narrow attentional focus, as it was easy to detect and most of the soundscape could be ignored. Attention to the beep reflected a wide attentional focus, as it required the participants to monitor multiple different sound streams. Results and discussion Results show the robustness of the N1 and P3 event related potential response during this dynamic task with a complex auditory soundscape. Furthermore, we used temporal response functions to study auditory processing to the whole soundscape. This work is a step toward studying workplace-related sound processing in the operating room using mobile EEG.
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Affiliation(s)
- Marc Rosenkranz
- Neurophysiology of Everyday Life Group, Department of Psychology, University of Oldenburg, Oldenburg, Germany
| | - Timur Cetin
- Pius-Hospital Oldenburg, University Hospital for Visceral Surgery, University of Oldenburg, Oldenburg, Germany
| | - Verena N. Uslar
- Pius-Hospital Oldenburg, University Hospital for Visceral Surgery, University of Oldenburg, Oldenburg, Germany
| | - Martin G. Bleichner
- Neurophysiology of Everyday Life Group, Department of Psychology, University of Oldenburg, Oldenburg, Germany
- Research Center for Neurosensory Science, University of Oldenburg, Oldenburg, Germany
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Barresi G, Nam CS, Esfahani ET, Balconi M. Editorial: Neuroergonomics in Human-Robot Interaction. Front Neurorobot 2022; 16:1006103. [PMID: 36148002 PMCID: PMC9486395 DOI: 10.3389/fnbot.2022.1006103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Accepted: 08/04/2022] [Indexed: 11/13/2022] Open
Affiliation(s)
- Giacinto Barresi
- Rehab Technologies, Istituto Italiano di Tecnologia, Genoa, Italy
| | - Chang S. Nam
- Edward P. Fitts Department of Industrial & Systems Engineering, North Carolina State University, Raleigh, NC, United States
| | - Ehsan T. Esfahani
- Human in the Loop Systems Laboratory, Department of Mechanical and Aerospace Engineering, University at Buffalo, Buffalo, NY, United States
| | - Michela Balconi
- International Research Center for Cognitive Applied Neuroscience (IrcCAN), Catholic University of the Sacred Heart, Milan, Italy
- Research Unit in Affective and Social Neuroscience, Department of Psychology, Catholic University of the Sacred Heart, Milan, Italy
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Stevens R, Galloway TL. Exploring how healthcare teams balance the neurodynamics of autonomous and collaborative behaviors: a proof of concept. Front Hum Neurosci 2022; 16:932468. [PMID: 35966993 PMCID: PMC9365959 DOI: 10.3389/fnhum.2022.932468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 07/04/2022] [Indexed: 11/13/2022] Open
Abstract
Team members co-regulate their activities and move together at the collective level of behavior while coordinating their actions toward shared goals. In parallel with team processes, team members need to resolve uncertainties arising from the changing task and environment. In this exploratory study we have measured the differential neurodynamics of seven two-person healthcare teams across time and brain regions during autonomous (taskwork) and collaborative (teamwork) segments of simulation training. The questions posed were: (1) whether these abstract and mostly integrated constructs could be separated neurodynamically; and, (2) what could be learned about taskwork and teamwork by trying to do so? The taskwork and teamwork frameworks used were Neurodynamic Information (NI), an electroencephalography (EEG) derived measure shown to be a neurodynamic proxy for the pauses and hesitations associated with individual uncertainty, and inter-brain EEG coherence (IBC) which is a required component of social interactions. No interdependency was observed between NI and IBC, and second-by-second dynamic comparisons suggested mutual exclusivity. These studies show that proxies for fundamental properties of teamwork and taskwork can be separated neurodynamically during team performances of ecologically valid tasks. The persistent expression of NI and IBC were not simultaneous suggesting that it may be difficult for team members to maintain inter-brain coherence while simultaneously reducing their individual uncertainties. Lastly, these separate dynamics occur over time frames of 15–30 s providing time for real-time detection and mitigation of individual and collaborative complications during training or live patient encounters.
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Affiliation(s)
- Ronald Stevens
- UCLA School of Medicine, Brain Research Institute, Los Angeles, CA, United States
- The Learning Chameleon, Inc., Culver City, CA, United States
- *Correspondence: Ronald Stevens
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Wang S, Sanches de Oliveira G, Djebbara Z, Gramann K. The Embodiment of Architectural Experience: A Methodological Perspective on Neuro-Architecture. Front Hum Neurosci 2022; 16:833528. [PMID: 35615743 PMCID: PMC9124889 DOI: 10.3389/fnhum.2022.833528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2021] [Accepted: 03/30/2022] [Indexed: 11/21/2022] Open
Abstract
People spend a large portion of their time inside built environments. Research in neuro-architecture-the neural basis of human perception of and interaction with the surrounding architecture-promises to advance our understanding of the cognitive processes underlying this common human experience and also to inspire evidence-based architectural design principles. This article examines the current state of the field and offers a path for moving closer to fulfilling this promise. The paper is structured in three sections, beginning with an introduction to neuro-architecture, outlining its main objectives and giving an overview of experimental research in the field. Afterward, two methodological limitations attending current brain-imaging architectural research are discussed: the first concerns the limited focus of the research, which is often restricted to the aesthetic dimension of architectural experience; the second concerns practical limitations imposed by the typical experimental tools and methods, which often require participants to remain stationary and prevent naturalistic interaction with architectural surroundings. Next, we propose that the theoretical basis of ecological psychology provides a framework for addressing these limitations and motivates emphasizing the role of embodied exploration in architectural experience, which encompasses but is not limited to aesthetic contemplation. In this section, some basic concepts within ecological psychology and their convergences with architecture are described. Lastly, we introduce Mobile Brain/Body Imaging (MoBI) as one emerging brain imaging approach with the potential to improve the ecological validity of neuro-architecture research. Accordingly, we suggest that combining theoretical and conceptual resources from ecological psychology with state-of-the-art neuroscience methods (Mobile Brain/Body Imaging) is a promising way to bring neuro-architecture closer to accomplishing its scientific and practical goals.
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Affiliation(s)
- Sheng Wang
- Biological Psychology and Neuroergonomics, Technische Universität Berlin, Berlin, Germany
| | | | - Zakaria Djebbara
- Biological Psychology and Neuroergonomics, Technische Universität Berlin, Berlin, Germany
- Department of Architecture, Design and Media Technology, Aalborg University, Aalborg, Denmark
| | - Klaus Gramann
- Biological Psychology and Neuroergonomics, Technische Universität Berlin, Berlin, Germany
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Dehais F, Ladouce S, Darmet L, Nong TV, Ferraro G, Torre Tresols J, Velut S, Labedan P. Dual Passive Reactive Brain-Computer Interface: A Novel Approach to Human-Machine Symbiosis. FRONTIERS IN NEUROERGONOMICS 2022; 3:824780. [PMID: 38235478 PMCID: PMC10790872 DOI: 10.3389/fnrgo.2022.824780] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 03/02/2022] [Indexed: 01/19/2024]
Abstract
The present study proposes a novel concept of neuroadaptive technology, namely a dual passive-reactive Brain-Computer Interface (BCI), that enables bi-directional interaction between humans and machines. We have implemented such a system in a realistic flight simulator using the NextMind classification algorithms and framework to decode pilots' intention (reactive BCI) and to infer their level of attention (passive BCI). Twelve pilots used the reactive BCI to perform checklists along with an anti-collision radar monitoring task that was supervised by the passive BCI. The latter simulated an automatic avoidance maneuver when it detected that pilots missed an incoming collision. The reactive BCI reached 100% classification accuracy with a mean reaction time of 1.6 s when exclusively performing the checklist task. Accuracy was up to 98.5% with a mean reaction time of 2.5 s when pilots also had to fly the aircraft and monitor the anti-collision radar. The passive BCI achieved a F1-score of 0.94. This first demonstration shows the potential of a dual BCI to improve human-machine teaming which could be applied to a variety of applications.
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Affiliation(s)
- Frédéric Dehais
- Artificial and Natural Intelligence Toulouse Institute, Université de Toulouse, Toulouse, France
- Department for Aerospace Vehicles Design and Control, ISAE-SUPAERO, Université de Toulouse, Toulouse, France
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, United States
| | - Simon Ladouce
- Department for Aerospace Vehicles Design and Control, ISAE-SUPAERO, Université de Toulouse, Toulouse, France
| | - Ludovic Darmet
- Department for Aerospace Vehicles Design and Control, ISAE-SUPAERO, Université de Toulouse, Toulouse, France
| | - Tran-Vu Nong
- Department for Aerospace Vehicles Design and Control, ISAE-SUPAERO, Université de Toulouse, Toulouse, France
| | - Giuseppe Ferraro
- Department for Aerospace Vehicles Design and Control, ISAE-SUPAERO, Université de Toulouse, Toulouse, France
| | - Juan Torre Tresols
- Department for Aerospace Vehicles Design and Control, ISAE-SUPAERO, Université de Toulouse, Toulouse, France
| | - Sébastien Velut
- Department for Aerospace Vehicles Design and Control, ISAE-SUPAERO, Université de Toulouse, Toulouse, France
| | - Patrice Labedan
- Department for Aerospace Vehicles Design and Control, ISAE-SUPAERO, Université de Toulouse, Toulouse, France
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Chang M, Büchel D, Reinecke K, Lehmann T, Baumeister J. Ecological validity in exercise neuroscience research: A systematic investigation. Eur J Neurosci 2022; 55:487-509. [PMID: 34997653 DOI: 10.1111/ejn.15595] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Revised: 12/27/2021] [Accepted: 01/03/2022] [Indexed: 11/28/2022]
Abstract
The contribution of cortical processes to adaptive motor behaviour is of great interest in the field of exercise neuroscience. Next to established criteria of objectivity, reliability and validity, ecological validity refers to the concerns of whether measurements and behaviour in research settings are representative of the real world. Because exercise neuroscience investigations using mobile electroencephalography are oftentimes conducted in laboratory settings under controlled environments, methodological approaches may interfere with the idea of ecological validity. This review utilizes an original ecological validity tool to assess the degree of ecological validity in current exercise neuroscience research. A systematic literature search was conducted to identify articles investigating cortical dynamics during goal-directed sports movement. To assess ecological validity, five elements (environment, stimulus, response, body and mind) were assessed on a continuum of artificiality-naturality and simplicity-complexity. Forty-seven studies were included in the present review. Results indicate lowest average ratings for the element of environment. The elements stimulus, body and mind had mediocre ratings, and the element of response had the highest overall ratings. In terms of the type of sport, studies that assessed closed-skill indoor sports had the highest ratings, whereas closed-skill outdoor sports had the lowest overall rating. Our findings identify specific elements that are lacking in ecological validity and areas of improvement in current exercise neuroscience literature. Future studies may potentially increase ecological validity by moving from reductionist, artificial environments towards complex, natural environments and incorporating real-world sport elements such as adaptive responses and competition.
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Affiliation(s)
- Melissa Chang
- Exercise Science & Neuroscience Unit, Department of Exercise & Health, Paderborn University, Paderborn, Germany
| | - Daniel Büchel
- Exercise Science & Neuroscience Unit, Department of Exercise & Health, Paderborn University, Paderborn, Germany
| | - Kirsten Reinecke
- Institute of Sports Medicine, Department of Exercise & Health, Paderborn University, Paderborn, Germany
| | - Tim Lehmann
- Exercise Science & Neuroscience Unit, Department of Exercise & Health, Paderborn University, Paderborn, Germany
| | - Jochen Baumeister
- Exercise Science & Neuroscience Unit, Department of Exercise & Health, Paderborn University, Paderborn, Germany
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Somon B, Giebeler Y, Darmet L, Dehais F. Benchmarking cEEGrid and Solid Gel-Based Electrodes to Classify Inattentional Deafness in a Flight Simulator. FRONTIERS IN NEUROERGONOMICS 2022; 2:802486. [PMID: 38235232 PMCID: PMC10790867 DOI: 10.3389/fnrgo.2021.802486] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 12/06/2021] [Indexed: 01/19/2024]
Abstract
Transfer from experiments in the laboratory to real-life tasks is challenging due notably to the inability to reproduce the complexity of multitasking dynamic everyday life situations in a standardized lab condition and to the bulkiness and invasiveness of recording systems preventing participants from moving freely and disturbing the environment. In this study, we used a motion flight simulator to induce inattentional deafness to auditory alarms, a cognitive difficulty arising in complex environments. In addition, we assessed the possibility of two low-density EEG systems a solid gel-based electrode Enobio (Neuroelectrics, Barcelona, Spain) and a gel-based cEEGrid (TMSi, Oldenzaal, Netherlands) to record and classify brain activity associated with inattentional deafness (misses vs. hits to odd sounds) with a small pool of expert participants. In addition to inducing inattentional deafness (missing auditory alarms) at much higher rates than with usual lab tasks (34.7% compared to the usual 5%), we observed typical inattentional deafness-related activity in the time domain but also in the frequency and time-frequency domains with both systems. Finally, a classifier based on Riemannian Geometry principles allowed us to obtain more than 70% of single-trial classification accuracy for both mobile EEG, and up to 71.5% for the cEEGrid (TMSi, Oldenzaal, Netherlands). These results open promising avenues toward detecting cognitive failures in real-life situations, such as real flight.
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Affiliation(s)
- Bertille Somon
- Artificial and Natural Intelligence Toulouse Institute, Université de Toulouse, Toulouse, France
- Department for Aerospace Vehicles Design and Control, ISAE-SUPAERO, Université de Toulouse, Toulouse, France
| | - Yasmina Giebeler
- Department for Aerospace Vehicles Design and Control, ISAE-SUPAERO, Université de Toulouse, Toulouse, France
- Department of Psychology and Ergonomics, Technische Universität Berlin, Berlin, Germany
| | - Ludovic Darmet
- Department for Aerospace Vehicles Design and Control, ISAE-SUPAERO, Université de Toulouse, Toulouse, France
| | - Frédéric Dehais
- Artificial and Natural Intelligence Toulouse Institute, Université de Toulouse, Toulouse, France
- Department for Aerospace Vehicles Design and Control, ISAE-SUPAERO, Université de Toulouse, Toulouse, France
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, United States
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Ascari L, Marchenkova A, Bellotti A, Lai S, Moro L, Koshmak K, Mantoan A, Barsotti M, Brondi R, Avveduto G, Sechi D, Compagno A, Avanzini P, Ambeck-Madsen J, Vecchiato G. Validation of a Novel Wearable Multistream Data Acquisition and Analysis System for Ergonomic Studies. SENSORS (BASEL, SWITZERLAND) 2021; 21:8167. [PMID: 34960261 PMCID: PMC8707223 DOI: 10.3390/s21248167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 11/30/2021] [Accepted: 12/03/2021] [Indexed: 12/02/2022]
Abstract
Nowadays, the growing interest in gathering physiological data and human behavior in everyday life scenarios is paralleled by an increase in wireless devices recording brain and body signals. However, the technical issues that characterize these solutions often limit the full brain-related assessments in real-life scenarios. Here we introduce the Biohub platform, a hardware/software (HW/SW) integrated wearable system for multistream synchronized acquisitions. This system consists of off-the-shelf hardware and state-of-art open-source software components, which are highly integrated into a high-tech low-cost solution, complete, yet easy to use outside conventional labs. It flexibly cooperates with several devices, regardless of the manufacturer, and overcomes the possibly limited resources of recording devices. The Biohub was validated through the characterization of the quality of (i) multistream synchronization, (ii) in-lab electroencephalographic (EEG) recordings compared with a medical-grade high-density device, and (iii) a Brain-Computer-Interface (BCI) in a real driving condition. Results show that this system can reliably acquire multiple data streams with high time accuracy and record standard quality EEG signals, becoming a valid device to be used for advanced ergonomics studies such as driving, telerehabilitation, and occupational safety.
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Affiliation(s)
- Luca Ascari
- Henesis s.r.l., 43123 Parma, Italy; (A.B.); (S.L.); (A.M.); (M.B.); (G.A.); (D.S.); (A.C.)
- Camlin Italy s.r.l., 43123 Parma, Italy; (L.M.); (K.K.); (R.B.)
| | - Anna Marchenkova
- Institute of Neuroscience, National Research Council of Italy, 43125 Parma, Italy; (A.M.); (P.A.)
| | - Andrea Bellotti
- Henesis s.r.l., 43123 Parma, Italy; (A.B.); (S.L.); (A.M.); (M.B.); (G.A.); (D.S.); (A.C.)
| | - Stefano Lai
- Henesis s.r.l., 43123 Parma, Italy; (A.B.); (S.L.); (A.M.); (M.B.); (G.A.); (D.S.); (A.C.)
| | - Lucia Moro
- Camlin Italy s.r.l., 43123 Parma, Italy; (L.M.); (K.K.); (R.B.)
| | | | - Alice Mantoan
- Henesis s.r.l., 43123 Parma, Italy; (A.B.); (S.L.); (A.M.); (M.B.); (G.A.); (D.S.); (A.C.)
| | - Michele Barsotti
- Henesis s.r.l., 43123 Parma, Italy; (A.B.); (S.L.); (A.M.); (M.B.); (G.A.); (D.S.); (A.C.)
| | | | - Giovanni Avveduto
- Henesis s.r.l., 43123 Parma, Italy; (A.B.); (S.L.); (A.M.); (M.B.); (G.A.); (D.S.); (A.C.)
| | - Davide Sechi
- Henesis s.r.l., 43123 Parma, Italy; (A.B.); (S.L.); (A.M.); (M.B.); (G.A.); (D.S.); (A.C.)
| | - Alberto Compagno
- Henesis s.r.l., 43123 Parma, Italy; (A.B.); (S.L.); (A.M.); (M.B.); (G.A.); (D.S.); (A.C.)
| | - Pietro Avanzini
- Institute of Neuroscience, National Research Council of Italy, 43125 Parma, Italy; (A.M.); (P.A.)
| | | | - Giovanni Vecchiato
- Institute of Neuroscience, National Research Council of Italy, 43125 Parma, Italy; (A.M.); (P.A.)
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14
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De Sanctis P, Solis-Escalante T, Seeber M, Wagner J, Ferris DP, Gramann K. Time to move: Brain dynamics underlying natural action and cognition. Eur J Neurosci 2021; 54:8075-8080. [PMID: 34904290 PMCID: PMC10454984 DOI: 10.1111/ejn.15562] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 12/08/2021] [Accepted: 12/08/2021] [Indexed: 12/14/2022]
Abstract
Advances in Mobile Brain/Body Imaging (MoBI) technology allows for real-time measurements of human brain dynamics during every day, natural, real-life situations. This special issue Time to Move brings together a collection of experimental papers, targeted reviews and opinion articles that lay out the latest MoBI findings. A wide range of topics across different fields are covered including art, athletics, virtual reality, and mobility. What unites these diverse topics is the common goal to enhance and restore human abilities by reaching a better understanding on how cognition is implemented by the brain-body relationship. The breadth and novelty of paradigms and findings reported here positions MoBI as a new frontier in the field of human cognitive neuroscience.
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Affiliation(s)
- Pierfilippo De Sanctis
- The Cognitive Neurophysiology Laboratory, Department of Pediatrics, Albert Einstein College of Medicine, New York City, New York, USA
- Department of Neurology, Division of Cognitive & Motor Aging, Albert Einstein College of Medicine, New York City, New York, USA
| | - Teodoro Solis-Escalante
- Department of Rehabilitation, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, Netherlands
| | - Martin Seeber
- Functional Brain Mapping Laboratory, Department of Fundamental Neurosciences, Campus Biotech, University of Geneva, Geneva, Switzerland
| | - Johanna Wagner
- Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, La Jolla, California, USA
| | - Daniel P Ferris
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, Florida, USA
| | - Klaus Gramann
- Department of Psychology and Ergonomics, Biological Psychology and Neuroergonomics, Institute of Psychology and Ergonomics, Berlin Institute of Technology, Berlin, Germany
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Vecchiato G. Hybrid Systems to Boost EEG-Based Real-Time Action Decoding in Car Driving Scenarios. FRONTIERS IN NEUROERGONOMICS 2021; 2:784827. [PMID: 38235223 PMCID: PMC10790909 DOI: 10.3389/fnrgo.2021.784827] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 11/08/2021] [Indexed: 01/19/2024]
Abstract
The complexity of concurrent cerebral processes underlying driving makes such human behavior one of the most studied real-world activities in neuroergonomics. Several attempts have been made to decode, both offline and online, cerebral activity during car driving with the ultimate goal to develop brain-based systems for assistive devices. Electroencephalography (EEG) is the cornerstone of these studies providing the highest temporal resolution to track those cerebral processes underlying overt behavior. Particularly when investigating real-world scenarios as driving, EEG is constrained by factors such as robustness, comfortability, and high data variability affecting the decoding performance. Hence, additional peripheral signals can be combined with EEG for increasing replicability and the overall performance of the brain-based action decoder. In this regard, hybrid systems have been proposed for the detection of braking and steering actions in driving scenarios to improve the predictive power of the single neurophysiological measurement. These recent results represent a proof of concept of the level of technological maturity. They may pave the way for increasing the predictive power of peripheral signals, such as electroculogram (EOG) and electromyography (EMG), collected in real-world scenarios when informed by EEG measurements, even if collected only offline in standard laboratory settings. The promising usability of such hybrid systems should be further investigated in other domains of neuroergonomics.
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Affiliation(s)
- Giovanni Vecchiato
- Institute of Neuroscience, National Research Council of Italy, Parma, Italy
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Abujelala M, Karthikeyan R, Tyagi O, Du J, Mehta RK. Brain Activity-Based Metrics for Assessing Learning States in VR under Stress among Firefighters: An Explorative Machine Learning Approach in Neuroergonomics. Brain Sci 2021; 11:885. [PMID: 34209388 PMCID: PMC8304323 DOI: 10.3390/brainsci11070885] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 06/26/2021] [Accepted: 06/28/2021] [Indexed: 12/02/2022] Open
Abstract
The nature of firefighters` duties requires them to work for long periods under unfavorable conditions. To perform their jobs effectively, they are required to endure long hours of extensive, stressful training. Creating such training environments is very expensive and it is difficult to guarantee trainees' safety. In this study, firefighters are trained in a virtual environment that includes virtual perturbations such as fires, alarms, and smoke. The objective of this paper is to use machine learning methods to discern encoding and retrieval states in firefighters during a visuospatial episodic memory task and explore which regions of the brain provide suitable signals to solve this classification problem. Our results show that the Random Forest algorithm could be used to distinguish between information encoding and retrieval using features extracted from fNIRS data. Our algorithm achieved an F-1 score of 0.844 and an accuracy of 79.10% if the training and testing data are obtained at similar environmental conditions. However, the algorithm's performance dropped to an F-1 score of 0.723 and accuracy of 60.61% when evaluated on data collected under different environmental conditions than the training data. We also found that if the training and evaluation data were recorded under the same environmental conditions, the RPM, LDLPFC, RDLPFC were the most relevant brain regions under non-stressful, stressful, and a mix of stressful and non-stressful conditions, respectively.
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Affiliation(s)
- Maher Abujelala
- Department of Industrial & Systems Engineering, Texas A & M University, College Station, TX 77843, USA;
| | - Rohith Karthikeyan
- Department of Mechanical Engineering, Texas A & M University, College Station, TX 77843, USA;
| | - Oshin Tyagi
- Department of Industrial & Systems Engineering, Texas A & M University, College Station, TX 77843, USA;
| | - Jing Du
- Department of Civil and Coastal Engineering, Engineering School of Sustainable Infrastructure and Environment (ESSIE), Herbert Wertheim College of Engineering, University of Florida, Gainesville, FL 32611, USA;
| | - Ranjana K. Mehta
- Department of Industrial & Systems Engineering, Texas A & M University, College Station, TX 77843, USA;
- Department of Mechanical Engineering, Texas A & M University, College Station, TX 77843, USA;
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