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Zhou X, Ghorbani F, Roessner V, Hommel B, Prochnow A, Beste C. The metacontrol of event segmentation-A neurophysiological and behavioral perspective. Hum Brain Mapp 2024; 45:e26727. [PMID: 39081074 PMCID: PMC11289429 DOI: 10.1002/hbm.26727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Revised: 03/27/2024] [Accepted: 05/06/2024] [Indexed: 08/03/2024] Open
Abstract
During our everyday life, the constant flow of information is divided into discrete events, a process conceptualized in Event Segmentation Theory (EST). How people perform event segmentation and the resulting granularity of encapsulated segments likely depends on their metacontrol style. Yet, the underlying neural mechanisms remain undetermined. The current study examines how the metacontrol style affects event segmentation through the analysis of EEG data using multivariate pattern analysis (MVPA) and source localization analysis. We instructed two groups of healthy participants to either segment a movie as fine-grained as possible (fine-grain group) or provided no such instruction (free-segmentation group). The fine-grain group showed more segments and a higher likelihood to set event boundaries upon scene changes, which supports the notion that cognitive control influences segmentation granularity. On a neural level, representational dynamics were decodable 400 ms prior to the decision to close a segment and open a new one, and especially fronto-polar regions (BA10) were associated with this representational dynamic. Groups differed in their use of this representational dynamics to guide behavior and there was a higher sensitivity to incoming information in the Fine-grain group. Moreover, a higher likelihood to set event boundaries was reflected by activity increases in the insular cortex suggesting an increased monitoring of potentially relevant upcoming events. The study connects the EST with the metacontrol framework and relates these to overarching neural concepts of prefrontal cortex function.
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Affiliation(s)
- Xianzhen Zhou
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU DresdenDresdenGermany
| | - Foroogh Ghorbani
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU DresdenDresdenGermany
| | - Veit Roessner
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU DresdenDresdenGermany
| | | | - Astrid Prochnow
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU DresdenDresdenGermany
| | - Christian Beste
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU DresdenDresdenGermany
- School of PsychologyShandong Normal UniversityJinanChina
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2
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Bailey KM, Sami S, Smith FW. Decoding familiar visual object categories in the mu rhythm oscillatory response. Neuropsychologia 2024; 199:108900. [PMID: 38697558 DOI: 10.1016/j.neuropsychologia.2024.108900] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 04/22/2024] [Accepted: 04/29/2024] [Indexed: 05/05/2024]
Abstract
Whilst previous research has linked attenuation of the mu rhythm to the observation of specific visual categories, and even to a potential role in action observation via a putative mirror neuron system, much of this work has not considered what specific type of information might be coded in this oscillatory response when triggered via vision. Here, we sought to determine whether the mu rhythm contains content-specific information about the identity of familiar (and also unfamiliar) graspable objects. In the present study, right-handed participants (N = 27) viewed images of both familiar (apple, wine glass) and unfamiliar (cubie, smoothie) graspable objects, whilst performing an orthogonal task at fixation. Multivariate pattern analysis (MVPA) revealed significant decoding of familiar, but not unfamiliar, visual object categories in the mu rhythm response. Thus, simply viewing familiar graspable objects may automatically trigger activation of associated tactile and/or motor properties in sensorimotor areas, reflected in the mu rhythm. In addition, we report significant attenuation in the central beta band for both familiar and unfamiliar visual objects, but not in the mu rhythm. Our findings highlight how analysing two different aspects of the oscillatory response - either attenuation or the representation of information content - provide complementary views on the role of the mu rhythm in response to viewing graspable object categories.
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Affiliation(s)
| | - Saber Sami
- Norwich Medical School, University of East Anglia, UK
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Kukkar KK, Rao N, Huynh D, Shah S, Contreras-Vidal JL, Parikh PJ. Context-dependent reduction in corticomuscular coupling for balance control in chronic stroke survivors. Exp Brain Res 2024:10.1007/s00221-024-06884-x. [PMID: 38963559 DOI: 10.1007/s00221-024-06884-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 06/26/2024] [Indexed: 07/05/2024]
Abstract
Balance control is an important indicator of mobility and independence in activities of daily living. How the functional coupling between the cortex and the muscle for balance control is affected following stroke remains to be known. We investigated the changes in coupling between the cortex and leg muscles during a challenging balance task over multiple frequency bands in chronic stroke survivors. Fourteen participants with stroke and ten healthy controls performed a challenging balance task. They stood on a computerized support surface that was either fixed (low difficulty condition) or sway-referenced with varying gain (medium and high difficulty conditions). We computed corticomuscular coherence between electrodes placed over the sensorimotor area (electroencephalography) and leg muscles (electromyography) and assessed balance performance using clinical and laboratory-based tests. We found significantly lower delta frequency band coherence in stroke participants when compared with healthy controls under medium difficulty condition, but not during low and high difficulty conditions. These differences were found for most of the distal but not for proximal leg muscle groups. No differences were found at other frequency bands. Participants with stroke showed poor balance clinical scores when compared with healthy controls, but no differences were found for laboratory-based tests. The observation of effects at distal but not at proximal muscle groups suggests differences in the (re)organization of the descending connections across two muscle groups for balance control. We argue that the observed group difference in delta band coherence indicates balance context-dependent alteration in mechanisms for the detection of somatosensory modulation resulting from sway-referencing of the support surface for balance maintenance following stroke.
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Affiliation(s)
- Komal K Kukkar
- Center for Neuromotor and Biomechanics Research, Department of Health and Human Performance, University of Houston, 3875 Holman Street, suite 104R GAR, Houston, TX, 77204, USA
| | - Nishant Rao
- Yale Child Study Center, Yale University, New Haven, Connecticut, USA
| | - Diana Huynh
- Center for Neuromotor and Biomechanics Research, Department of Health and Human Performance, University of Houston, 3875 Holman Street, suite 104R GAR, Houston, TX, 77204, USA
| | - Sheel Shah
- Center for Neuromotor and Biomechanics Research, Department of Health and Human Performance, University of Houston, 3875 Holman Street, suite 104R GAR, Houston, TX, 77204, USA
| | - Jose L Contreras-Vidal
- Laboratory for Noninvasive Brain-Machine Interface Systems, Department of Electrical and Computer Engineering, University of Houston, Houston, TX, USA
| | - Pranav J Parikh
- Center for Neuromotor and Biomechanics Research, Department of Health and Human Performance, University of Houston, 3875 Holman Street, suite 104R GAR, Houston, TX, 77204, USA.
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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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Song BG, Kang N. Removal of movement artifacts and assessment of mental stress analyzing electroencephalogram of non-driving passengers under whole-body vibration. Front Neurosci 2024; 18:1328704. [PMID: 38726034 PMCID: PMC11079143 DOI: 10.3389/fnins.2024.1328704] [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: 10/27/2023] [Accepted: 04/12/2024] [Indexed: 05/12/2024] Open
Abstract
The discomfort caused by whole-body vibration (WBV) has long been assessed using subjective surveys or objective measurements of body acceleration. However, surveys have the disadvantage that some of participants often express their feelings in a capricious manner, and acceleration data cannot take into account individual preferences and experiences of their emotions. In this study, we investigated vibration-induced mental stress using the electroencephalogram (EEG) of 22 seated occupants excited by random vibrations. Between the acceleration and the EEG signal, which contains electrical noise due to the head shaking caused by random vibrations, we found that there was a strong correlation, which acts as an artifact in the EEG, and therefore we removed it using an adaptive filter. After removing the artifact, we analyzed the characteristics of the brainwaves using topographic maps and observed that the activities detected in the frontal electrodes showed significant differences between the static and vibration conditions. Further, frontal alpha asymmetry (FAA) and relative band power indices in the frontal electrodes were analyzed statistically to assess mental stress under WBV. As the vibration level increased, EEG analysis in the frontal electrodes showed a decrease in FAA and alpha power but an increase in gamma power. These results are in good agreement with the literature in the sense that FAA and alpha band power decreases with increasing stress, thus demonstrating that WBV causes mental stress and that the stress increases with the vibration level. EEG assessment of stress during WBV is expected to be used in the evaluation of ride comfort alongside existing self-report and acceleration methods.
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Affiliation(s)
- Byoung-Gyu Song
- Department of Mechanical Engineering, Kyungpook National University, Daegu, Republic of Korea
| | - Namcheol Kang
- School of Mechanical Engineering, Kyungpook National University, Daegu, Republic of Korea
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Zhu HY, Chen HT, Lin CT. Understanding the effects of stress on the P300 response during naturalistic simulation of heights exposure. PLoS One 2024; 19:e0301052. [PMID: 38630669 PMCID: PMC11023450 DOI: 10.1371/journal.pone.0301052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 03/10/2024] [Indexed: 04/19/2024] Open
Abstract
Stress is a prevalent bodily response universally experienced and significantly affects a person's mental and cognitive state. The P300 response is a commonly observed brain behaviour that provides insight into a person's cognitive state. Previous works have documented the effects of stress on the P300 behaviour; however, only a few have explored the performance in a mobile and naturalistic experimental setup. Our study examined the effects of stress on the human brain's P300 behaviour through a height exposure experiment that incorporates complex visual, vestibular, and proprioceptive stimuli. A more complex sensory environment could produce translatable findings toward real-world behaviour and benefit emerging technologies such as brain-computer interfaces. Seventeen participants experienced our experiment that elicited the stress response through physical and virtual height exposure. We found two unique groups within our participants that exhibited contrasting behavioural performance and P300 target reaction response when exposed to stressors (from walking at heights). One group performed worse when exposed to heights and exhibited a significant decrease in parietal P300 peak amplitude and increased beta and gamma power. On the other hand, the group less affected by stress exhibited a change in their N170 peak amplitude and alpha/mu rhythm desynchronisation. The findings of our study suggest that a more individualised approach to assessing a person's behaviour performance under stress can aid in understanding P300 performance when experiencing stress.
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Affiliation(s)
- Howe Yuan Zhu
- Australian AI Institute, GrapheneX-UTS Human-centric AI Centre, University of Technology Sydney, Sydney, New South Wales, Australia
| | - Hsiang-Ting Chen
- School of Computer Science, University of Adelaide, Adelaide, South Australia, Australia
| | - Chin-Teng Lin
- Australian AI Institute, GrapheneX-UTS Human-centric AI Centre, University of Technology Sydney, Sydney, New South Wales, Australia
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Ghin F, Eggert E, Gholamipourbarogh N, Talebi N, Beste C. Response stopping under conflict: The integrative role of representational dynamics associated with the insular cortex. Hum Brain Mapp 2024; 45:e26643. [PMID: 38664992 PMCID: PMC11046082 DOI: 10.1002/hbm.26643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 02/02/2024] [Accepted: 02/18/2024] [Indexed: 04/29/2024] Open
Abstract
Coping with distracting inputs during goal-directed behavior is a common challenge, especially when stopping ongoing responses. The neural basis for this remains debated. Our study explores this using a conflict-modulation Stop Signal task, integrating group independent component analysis (group-ICA), multivariate pattern analysis (MVPA), and EEG source localization analysis. Consistent with previous findings, we show that stopping performance is better in congruent (nonconflicting) trials than in incongruent (conflicting) trials. Conflict effects in incongruent trials compromise stopping more due to the need for the reconfiguration of stimulus-response (S-R) mappings. These cognitive dynamics are reflected by four independent neural activity patterns (ICA), each coding representational content (MVPA). It is shown that each component was equally important in predicting behavioral outcomes. The data support an emerging idea that perception-action integration in action-stopping involves multiple independent neural activity patterns. One pattern relates to the precuneus (BA 7) and is involved in attention and early S-R processes. Of note, three other independent neural activity patterns were associated with the insular cortex (BA13) in distinct time windows. These patterns reflect a role in early attentional selection but also show the reiterated processing of representational content relevant for stopping in different S-R mapping contexts. Moreover, the insular cortex's role in automatic versus complex response selection in relation to stopping processes is shown. Overall, the insular cortex is depicted as a brain hub, crucial for response selection and cancellation across both straightforward (automatic) and complex (conditional) S-R mappings, providing a neural basis for general cognitive accounts on action control.
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Affiliation(s)
- Filippo Ghin
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of MedicineTU DresdenDresdenGermany
| | - Elena Eggert
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of MedicineTU DresdenDresdenGermany
| | - Negin Gholamipourbarogh
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of MedicineTU DresdenDresdenGermany
| | - Nasibeh Talebi
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of MedicineTU DresdenDresdenGermany
| | - Christian Beste
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of MedicineTU DresdenDresdenGermany
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Behboodi A, Kline J, Gravunder A, Phillips C, Parker SM, Damiano DL. Development and evaluation of a BCI-neurofeedback system with real-time EEG detection and electrical stimulation assistance during motor attempt for neurorehabilitation of children with cerebral palsy. Front Hum Neurosci 2024; 18:1346050. [PMID: 38633751 PMCID: PMC11021665 DOI: 10.3389/fnhum.2024.1346050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 03/22/2024] [Indexed: 04/19/2024] Open
Abstract
In the realm of motor rehabilitation, Brain-Computer Interface Neurofeedback Training (BCI-NFT) emerges as a promising strategy. This aims to utilize an individual's brain activity to stimulate or assist movement, thereby strengthening sensorimotor pathways and promoting motor recovery. Employing various methodologies, BCI-NFT has been shown to be effective for enhancing motor function primarily of the upper limb in stroke, with very few studies reported in cerebral palsy (CP). Our main objective was to develop an electroencephalography (EEG)-based BCI-NFT system, employing an associative learning paradigm, to improve selective control of ankle dorsiflexion in CP and potentially other neurological populations. First, in a cohort of eight healthy volunteers, we successfully implemented a BCI-NFT system based on detection of slow movement-related cortical potentials (MRCP) from EEG generated by attempted dorsiflexion to simultaneously activate Neuromuscular Electrical Stimulation which assisted movement and served to enhance sensory feedback to the sensorimotor cortex. Participants also viewed a computer display that provided real-time visual feedback of ankle range of motion with an individualized target region displayed to encourage maximal effort. After evaluating several potential strategies, we employed a Long short-term memory (LSTM) neural network, a deep learning algorithm, to detect the motor intent prior to movement onset. We then evaluated the system in a 10-session ankle dorsiflexion training protocol on a child with CP. By employing transfer learning across sessions, we could significantly reduce the number of calibration trials from 50 to 20 without compromising detection accuracy, which was 80.8% on average. The participant was able to complete the required calibration trials and the 100 training trials per session for all 10 sessions and post-training demonstrated increased ankle dorsiflexion velocity, walking speed and step length. Based on exceptional system performance, feasibility and preliminary effectiveness in a child with CP, we are now pursuing a clinical trial in a larger cohort of children with CP.
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Affiliation(s)
- Ahad Behboodi
- Department of Biomechanics, University of Nebraska Omaha, Omaha, NE, United States
- Neurorehabilitation and Biomechanics Research Section, Rehabilitation Medicine Department, Clinical Center, National Institutes of Health, Bethesda, MD, United States
| | - Julia Kline
- Neurorehabilitation and Biomechanics Research Section, Rehabilitation Medicine Department, Clinical Center, National Institutes of Health, Bethesda, MD, United States
| | - Andrew Gravunder
- Neurorehabilitation and Biomechanics Research Section, Rehabilitation Medicine Department, Clinical Center, National Institutes of Health, Bethesda, MD, United States
| | - Connor Phillips
- Neurorehabilitation and Biomechanics Research Section, Rehabilitation Medicine Department, Clinical Center, National Institutes of Health, Bethesda, MD, United States
| | - Sheridan M. Parker
- Neurorehabilitation and Biomechanics Research Section, Rehabilitation Medicine Department, Clinical Center, National Institutes of Health, Bethesda, MD, United States
| | - Diane L. Damiano
- Neurorehabilitation and Biomechanics Research Section, Rehabilitation Medicine Department, Clinical Center, National Institutes of Health, Bethesda, MD, United States
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Labonte-LeMoyne E, Cameron AF, Sénécal S, Fredette M, Faubert J, Lepore F, Léger PM. What's that on Your Phone? Effects of Mobile Device Task Type on Pedestrian Performance. HUMAN FACTORS 2024; 66:1068-1080. [PMID: 36426775 PMCID: PMC10900866 DOI: 10.1177/00187208221141175] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
BACKGROUND The number of accidents due to distracted pedestrian is on the rise and many governments and institutions are enacting public policies which restrict texting while walking. However, pedestrians do more than just texting when they use their mobile devices on the go. OBJECTIVE Exploring pedestrian multitasking, this paper aims to examine the effects of mobile device task type on pedestrian performance outcomes. METHOD We performed two studies in lab simulations where 78 participants were asked to perform different tasks on a mobile device (playing a game, reading, writing an email, texting one person, group texting) while performing a pedestrian visual discrimination task while either standing or walking on a treadmill. Behavioral performance as well as neurophysiological data are collected. RESULTS Results show that compared to a no-phone control, multitasking with any of the tasks on a mobile device leads to poor performance on a pedestrian visual discrimination task. Playing a game is the most cognitively demanding task and leads to the greatest performance degradation. CONCLUSION Our studies show that multitasking with a mobile device has the potential to negatively impact pedestrian safety, regardless of task type. However, the impacts of different mobile device tasks are not all equivalent. More research is needed to tease out the different effects of these various tasks and to design mobile applications which effectively and safely capture pedestrians' attention. APPLICATION Public policy, infrastructure, and smart technologies can be used to mitigate the negative effects of mobile multitasking. A more thorough understanding of mobile device task-specific factors at play can help tailor these counter-measures to better aid distracted pedestrians.
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Mohammadi Y, Østergaard J, Graversen C, Andersen OK, Biurrun Manresa J. Validity and reliability of self-reported and neural measures of listening effort. Eur J Neurosci 2023; 58:4357-4370. [PMID: 37984406 DOI: 10.1111/ejn.16187] [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: 03/10/2023] [Revised: 10/17/2023] [Accepted: 10/23/2023] [Indexed: 11/22/2023]
Abstract
Listening effort can be defined as a measure of cognitive resources used by listeners to perform a listening task. Various methods have been proposed to measure this effort, yet their reliability remains unestablished, a crucial step before their application in research or clinical settings. This study encompassed 32 participants undertaking speech-in-noise tasks across two sessions, approximately a week apart. They listened to sentences and word lists at varying signal-to-noise ratios (SNRs) (-9, -6, -3 and 0 dB), then retaining them for roughly 3 s. We evaluated the test-retest reliability of self-reported effort ratings, theta (4-7 Hz) and alpha (8-13 Hz) oscillatory power, suggested previously as neural markers of listening effort. Additionally, we examined the reliability of correct word percentages. Both relative and absolute reliability were assessed using intraclass correlation coefficients (ICC) and Bland-Altman analysis. We also computed the standard error of measurement (SEM) and smallest detectable change (SDC). Our findings indicated heightened frontal midline theta power for word lists compared to sentences during the retention phase under high SNRs (0 dB, -3 dB), likely indicating a greater memory load for word lists. We observed SNR's impact on alpha power in the right central region during the listening phase and frontal theta power during the retention phase in sentences. Overall, the reliability analysis demonstrated satisfactory between-session variability for correct words and effort ratings. However, neural measures (frontal midline theta power and right central alpha power) displayed substantial variability, even though group-level outcomes appeared consistent across sessions.
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Affiliation(s)
- Yousef Mohammadi
- Integrative Neuroscience, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - Jan Østergaard
- Department of Electronic Systems, Aalborg University, Aalborg, Denmark
| | - Carina Graversen
- Integrative Neuroscience, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
- Center for Neuroplasticity and Pain (CNAP), Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - Ole Kaeseler Andersen
- Integrative Neuroscience, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
- Center for Neuroplasticity and Pain (CNAP), Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - José Biurrun Manresa
- Center for Neuroplasticity and Pain (CNAP), Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
- Institute for Research and Development in Bioengineering and Bioinformatics (IBB), CONICET-UNER, Oro Verde, Argentina
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11
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Kiani MM, Heidari Beni MH, Aghajan H. Aberrations in temporal dynamics of cognitive processing induced by Parkinson's disease and Levodopa. Sci Rep 2023; 13:20195. [PMID: 37980451 PMCID: PMC10657430 DOI: 10.1038/s41598-023-47410-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 11/10/2023] [Indexed: 11/20/2023] Open
Abstract
The motor symptoms of Parkinson's disease (PD) have been shown to significantly improve by Levodopa. However, despite the widespread adoption of Levodopa as a standard pharmaceutical drug for the treatment of PD, cognitive impairments linked to PD do not show visible improvement with Levodopa treatment. Furthermore, the neuronal and network mechanisms behind the PD-induced cognitive impairments are not clearly understood. In this work, we aim to explain these cognitive impairments, as well as the ones exacerbated by Levodopa, through examining the differential dynamic patterns of the phase-amplitude coupling (PAC) during cognitive functions. EEG data recorded in an auditory oddball task performed by a cohort consisting of controls and a group of PD patients during both on and off periods of Levodopa treatment were analyzed to derive the temporal dynamics of the PAC across the brain. We observed distinguishing patterns in the PAC dynamics, as an indicator of information binding, which can explain the slower cognitive processing associated with PD in the form of a latency in the PAC peak time. Thus, considering the high-level connections between the hippocampus, the posterior and prefrontal cortices established through the dorsal and ventral striatum acting as a modulatory system, we posit that the primary issue with cognitive impairments of PD, as well as Levodopa's cognitive deficit side effects, can be attributed to the changes in temporal dynamics of dopamine release influencing the modulatory function of the striatum.
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Affiliation(s)
- Mohammad Mahdi Kiani
- Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran
| | | | - Hamid Aghajan
- Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran.
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Symeonidou ER, Ferris DP. Visual Occlusions Result in Phase Synchrony Within Multiple Brain Regions Involved in Sensory Processing and Balance Control. IEEE Trans Neural Syst Rehabil Eng 2023; 31:3772-3780. [PMID: 37725737 PMCID: PMC10616968 DOI: 10.1109/tnsre.2023.3317055] [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] [Indexed: 09/21/2023]
Abstract
There is a need to develop appropriate balance training interventions to minimize the risk of falls. Recently, we found that intermittent visual occlusions can substantially improve the effectiveness and retention of balance beam walking practice (Symeonidou & Ferris, 2022). We sought to determine how the intermittent visual occlusions affect electrocortical activity during beam walking. We hypothesized that areas involved in sensorimotor processing and balance control would demonstrate spectral power changes and inter-trial coherence modulations after loss and restoration of vision. Ten healthy young adults practiced walking on a treadmill-mounted balance beam while wearing high-density EEG and experiencing reoccurring visual occlusions. Results revealed spectral power fluctuations and inter-trial coherence changes in the visual, occipital, temporal, and sensorimotor cortex as well as the posterior parietal cortex and the anterior cingulate. We observed a prolonged alpha increase in the occipital, temporal, sensorimotor, and posterior parietal cortex after the occlusion onset. In contrast, the anterior cingulate showed a strong alpha and theta increase after the occlusion offset. We observed transient phase synchrony in the alpha, theta, and beta bands within the sensory, posterior parietal, and anterior cingulate cortices immediately after occlusion onset and offset. Intermittent visual occlusions induced electrocortical spectral power and inter-trial coherence changes in a wide range of frequencies within cortical areas relevant for multisensory integration and processing as well as balance control. Our training intervention could be implemented in senior and rehabilitation centers, improving the quality of life of elderly and neurologically impaired individuals.
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Alessa FM, Alhaag MH, Al-harkan IM, Ramadan MZ, Alqahtani FM. A Neurophysiological Evaluation of Cognitive Load during Augmented Reality Interactions in Various Industrial Maintenance and Assembly Tasks. SENSORS (BASEL, SWITZERLAND) 2023; 23:7698. [PMID: 37765755 PMCID: PMC10536580 DOI: 10.3390/s23187698] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 09/03/2023] [Accepted: 09/04/2023] [Indexed: 09/29/2023]
Abstract
Augmented reality (AR) has been shown to improve productivity in industry, but its adverse effects (e.g., headaches, eye strain, nausea, and mental workload) on users warrant further investigation. The objective of this study is to investigate the effects of different instruction methods (i.e., HoloLens AR-based and paper-based instructions) and task complexity (low and high-demanding tasks) on cognitive workloads and performance. Twenty-eight healthy males with a mean age of 32.12 (SD 2.45) years were recruited in this study and were randomly divided into two groups. The first group performed the experiment using AR-based instruction, and the second group used paper-based instruction. Performance was measured using total task time (TTT). The cognitive workload was measured using the power of electroencephalograph (EEG) features and the NASA task load index (NASA TLX). The results showed that using AR instructions resulted in a reduction in maintenance times and an increase in mental workload compared to paper instructions, particularly for the more demanding tasks. With AR instruction, 0.45% and 14.94% less time was spent on low- and high-demand tasks, respectively, as compared to paper instructions. According to the EEG features, employing AR to guide employees during highly demanding maintenance tasks increased information processing, which could be linked with an increased germane cognitive load. Increased germane cognitive load means participants can better facilitate long-term knowledge and skill acquisition. These results suggested that AR is superior and recommended for highly demanding maintenance tasks since it speeds up maintenance times and increases the possibility that information is stored in long-term memory and encrypted for recalls.
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Affiliation(s)
- Faisal M. Alessa
- Department of Industrial Engineering, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia
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14
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Callara AL, Fontanelli L, Belcari I, Rho G, Greco A, Zelič Ž, Sebastiani L, Santarcangelo EL. Modulation of the heartbeat evoked cortical potential by hypnotizability and hypnosis. Psychophysiology 2023; 60:e14309. [PMID: 37070749 DOI: 10.1111/psyp.14309] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 03/07/2023] [Accepted: 03/22/2023] [Indexed: 04/19/2023]
Abstract
Hypnotizability is a psychophysiological trait measured by scales and associated with several differences, including interoceptive accuracy and the morpho-functional characteristics of interoception-related brain regions. The aim of the study was to assess whether the amplitude of the heartbeat evoked cortical potential (HEP), a correlate of interoceptive accuracy, differs in participants with low (lows) and high (highs) hypnotizability scores (assessed by the Stanford Hypnotic Susceptibility Scale, Form A) before and after the induction of hypnosis. ECG and EEG were monitored in 16 highs and 15 lows during an experimental session, including open eyes baseline (B), closed eyes relaxation (R), hypnotic induction (IND), neutral hypnosis (NH), and post session baseline (Post). No significant difference was observed between groups and conditions in autonomic variables. The HEP amplitude was lower in highs than in lows at the right parietal site, likely due to hypnotizability related differences in the functional connection between the right insula and parietal cortex. It increased in highs and decreased in lows across the session, possibly due to the highs' preeminently internally directed attention and to the lows' possible disengagement from the task. Since interoception is involved in several cognitive-emotional functions, its hypnotizability related differences may contribute to the variability of experience and behavior in daily life.
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Affiliation(s)
- Alejandro Luis Callara
- Department of Information Engineering, University of Pisa, Pisa, Italy
- Research Center "E. Piaggio", University of Pisa, Pisa, Italy
| | - Lorenzo Fontanelli
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Iacopo Belcari
- Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
| | - Gianluca Rho
- Department of Information Engineering, University of Pisa, Pisa, Italy
| | - Alberto Greco
- Department of Information Engineering, University of Pisa, Pisa, Italy
- Research Center "E. Piaggio", University of Pisa, Pisa, Italy
| | - Žan Zelič
- Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
| | - Laura Sebastiani
- Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
| | - Enrica L Santarcangelo
- Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
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Mohammadi Y, Graversen C, Østergaard J, Andersen OK, Reichenbach T. Phase-locking of Neural Activity to the Envelope of Speech in the Delta Frequency Band Reflects Differences between Word Lists and Sentences. J Cogn Neurosci 2023; 35:1301-1311. [PMID: 37379482 DOI: 10.1162/jocn_a_02016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/30/2023]
Abstract
The envelope of a speech signal is tracked by neural activity in the cerebral cortex. The cortical tracking occurs mainly in two frequency bands, theta (4-8 Hz) and delta (1-4 Hz). Tracking in the faster theta band has been mostly associated with lower-level acoustic processing, such as the parsing of syllables, whereas the slower tracking in the delta band relates to higher-level linguistic information of words and word sequences. However, much regarding the more specific association between cortical tracking and acoustic as well as linguistic processing remains to be uncovered. Here, we recorded EEG responses to both meaningful sentences and random word lists in different levels of signal-to-noise ratios (SNRs) that lead to different levels of speech comprehension as well as listening effort. We then related the neural signals to the acoustic stimuli by computing the phase-locking value (PLV) between the EEG recordings and the speech envelope. We found that the PLV in the delta band increases with increasing SNR for sentences but not for the random word lists, showing that the PLV in this frequency band reflects linguistic information. When attempting to disentangle the effects of SNR, speech comprehension, and listening effort, we observed a trend that the PLV in the delta band might reflect listening effort rather than the other two variables, although the effect was not statistically significant. In summary, our study shows that the PLV in the delta band reflects linguistic information and might be related to listening effort.
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16
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He C, Chen YY, Phang CR, Stevenson C, Chen IP, Jung TP, Ko LW. Diversity and Suitability of the State-of-the-Art Wearable and Wireless EEG Systems Review. IEEE J Biomed Health Inform 2023; 27:3830-3843. [PMID: 37022001 DOI: 10.1109/jbhi.2023.3239053] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
Wireless electroencephalography (EEG) systems have been attracting increasing attention in recent times. Both the number of articles discussing wireless EEG and their proportion relative to general EEG publications have increased over years. These trends indicate that wireless EEG systems could be more accessible to researchers and the research community has recognized the potential of wireless EEG systems. To explore the development and diverse applications of wireless EEG systems, this review highlights the trends in wearable and wireless EEG systems over the past decade and compares the specifications and research applications of the major wireless systems marketed by 16 companies. For each product, five parameters (number of channels, sampling rate, cost, battery life, and resolution) were assessed for comparison. Currently, these wearable and portable wireless EEG systems have three main application areas: consumer, clinical, and research. To address this multitude of options, the article also discussed the thought process to find a suitable device that meets personalization and use cases specificities. These investigations suggest that low-price and convenience are key factors for consumer applications, wireless EEG systems with FDA or CE-certification may be more suitable for clinical settings, and devices that provide raw EEG data with high-density channels are important for laboratory research. This article presents an overview of the current state of the wireless EEG systems specifications and possible applications and serves as a guide point as it is expected that more influential and novel research will cyclically promote the development of such EEG systems.
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17
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Kukkar KK, Rao N, Huynh D, Shah S, Contreras-Vidal JL, Parikh PJ. Task-dependent Alteration in Delta Band Corticomuscular Coherence during Standing in Chronic Stroke Survivors. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.07.17.23292472. [PMID: 37503096 PMCID: PMC10371181 DOI: 10.1101/2023.07.17.23292472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Balance control is an important indicator of mobility and independence in activities of daily living. How the changes in functional integrity of corticospinal tract due to stroke affects the maintenance of upright stance remains to be known. We investigated the changes in functional coupling between the cortex and lower limb muscles during a challenging balance task over multiple frequency bands in chronic stroke survivors. Eleven stroke patients and nine healthy controls performed a challenging balance task. They stood on a computerized platform with/without somatosensory input distortion created by sway-referencing the support surface, thereby varying the difficulty levels of the task. We computed corticomuscular coherence between Cz (electroencephalography) and leg muscles and assessed balance performance using Berg Balance scale (BBS), Timed-up and go (TUG) and center of pressure (COP) measures. We found lower delta frequency band coherence in stroke patients when compared with healthy controls under medium difficulty condition for distal but not proximal leg muscles. For both groups, we found similar coherence at other frequency bands. On BBS and TUG, stroke patients showed poor balance. However, similar group differences were not consistently observed across COP measures. The presence of distal versus proximal effect suggests differences in the (re)organization of the corticospinal connections across the two muscles groups for balance control. We argue that the observed group difference in the delta coherence might be due to altered mechanisms for the detection of somatosensory modulation resulting from sway-referencing of the support platform for balance control.
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Affiliation(s)
- Komal K Kukkar
- Center for Neuromotor and Biomechanics Research, Department of Health and Human Performance, University of Houston, Houston, Texas
| | - Nishant Rao
- Haskins Laboratories, Yale University, New Haven, Connecticut
| | - Diana Huynh
- Center for Neuromotor and Biomechanics Research, Department of Health and Human Performance, University of Houston, Houston, Texas
| | - Sheel Shah
- Center for Neuromotor and Biomechanics Research, Department of Health and Human Performance, University of Houston, Houston, Texas
| | - Jose L Contreras-Vidal
- Laboratory for Noninvasive Brain-Machine Interface Systems, Department of Electrical and Computer Engineering, University of Houston, Houston, Texas
| | - Pranav J Parikh
- Center for Neuromotor and Biomechanics Research, Department of Health and Human Performance, University of Houston, Houston, Texas
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18
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Koyun AH, Stock AK, Beste C. Neurophysiological mechanisms underlying the differential effect of reward prospect on response selection and inhibition. Sci Rep 2023; 13:10903. [PMID: 37407656 DOI: 10.1038/s41598-023-37524-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 06/22/2023] [Indexed: 07/07/2023] Open
Abstract
Reward and cognitive control play crucial roles in shaping goal-directed behavior. Yet, the behavioral and neural underpinnings of interactive effects of both processes in driving our actions towards a particular goal have remained rather unclear. Given the importance of inhibitory control, we investigated the effect of reward prospect on the modulatory influence of automatic versus controlled processes during response inhibition. For this, a performance-contingent monetary reward for both correct response selection and response inhibition was added to a Simon NoGo task, which manipulates the relationship of automatic and controlled processes in Go and NoGo trials. A neurophysiological approach was used by combining EEG temporal signal decomposition and source localization methods. Compared to a non-rewarded control group, rewarded participants showed faster response execution, as well as overall lower response selection and inhibition accuracy (shifted speed-accuracy tradeoff). Interestingly, the reward group displayed a larger interference of the interactive effects of automatic versus controlled processes during response inhibition (i.e., a larger Simon NoGo effect), but not during response selection. The reward-specific behavioral effect was mirrored by the P3 amplitude, underlining the importance of stimulus-response association processes in explaining variability in response inhibition performance. The selective reward-induced neurophysiological modulation was associated with lower activation differences in relevant structures spanning the inferior frontal and parietal cortex, as well as higher activation differences in the somatosensory cortex. Taken together, this study highlights relevant neuroanatomical structures underlying selective reward effects on response inhibition and extends previous reports on the possible detrimental effect of reward-triggered performance trade-offs on cognitive control processes.
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Affiliation(s)
- Anna Helin Koyun
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Schubertstrasse 42, 01309, Dresden, Germany
- Faculty of Medicine, University Neuropsychology Center, TU Dresden, Dresden, Germany
| | - Ann-Kathrin Stock
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Schubertstrasse 42, 01309, Dresden, Germany.
- Faculty of Medicine, University Neuropsychology Center, TU Dresden, Dresden, Germany.
- Biopsychology, Faculty of Psychology, School of Science, TU Dresden, Dresden, Germany.
| | - Christian Beste
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Schubertstrasse 42, 01309, Dresden, Germany
- Faculty of Medicine, University Neuropsychology Center, TU Dresden, Dresden, Germany
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19
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Rahman M, Karwowski W, Sapkota N, Ismail L, Alhujailli A, Sumano RF, Hancock PA. Isometric Arm Forces Exerted by Females at Different Levels of Physical Comfort and Their EEG Signatures. Brain Sci 2023; 13:1027. [PMID: 37508959 PMCID: PMC10377375 DOI: 10.3390/brainsci13071027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 06/26/2023] [Accepted: 06/29/2023] [Indexed: 07/30/2023] Open
Abstract
A variety of subjective measures have traditionally been used to assess the perception of physical exertion at work and related body responses. However, the current understanding of physical comfort experienced at work is very limited. The main objective of this study was first to investigate the magnitude of isometric arm forces exerted by females at different levels of physical comfort measured on a new comfort scale and, second, to assess their corresponding neural signatures expressed in terms of power spectral density (PSD). The study assessed PSDs of four major electroencephalography (EEG) frequency bands, focusing on the brain regions controlling motor and perceptual processing. The results showed statistically significant differences in exerted arm forces and the rate of perceived exertion at the various levels of comfort. Significant differences in power spectrum density at different physical comfort levels were found for the beta EEG band. Such knowledge can be useful in incorporating female users' force requirements in the design of consumer products, including tablets, laptops, and other hand-held information technology devices, as well as various industrial processes and work systems.
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Affiliation(s)
- Mahjabeen Rahman
- Computational Neuroergonomics Laboratory, Department of Industrial Engineering and Management Systems, University of Central Florida, Orlando, FL 32816, USA
| | - Waldemar Karwowski
- Computational Neuroergonomics Laboratory, Department of Industrial Engineering and Management Systems, University of Central Florida, Orlando, FL 32816, USA
| | - Nabin Sapkota
- Department of Engineering Technology, Northwestern State University of Louisiana, Natchitoches, LA 71497, USA
| | - Lina Ismail
- Department of Industrial and Management Engineering, Arab Academy for Science, Technology, and Maritime Transport, Alexandria 2913, Egypt
| | - Ashraf Alhujailli
- Department of Management Science, Yanbu Industrial College, Yanbu 46452, Saudi Arabia
| | - Raul Fernandez Sumano
- Industrial Engineering Technology, Dunwoody College of Technology, Minneapolis, MN 55403, USA
| | - P A Hancock
- Department of Psychology, University of Central Florida, Orlando, FL 32816, USA
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20
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Bollini A, Vitali H, Crepaldi M, Parmiggiani A, Campus C, Lorini C, Gori M. Dr-MUSIC: An Effective Device for Investigating Multisensory Mechanisms during Development with EEG recordings . ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-5. [PMID: 38082766 DOI: 10.1109/embc40787.2023.10340915] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
From birth, we are continuously exposed to multisensory stimuli that we learn to select and integrate during development to perceive a coherent world. To date, there are no optimal solutions to investigate how auditory, visual and tactile signals are integrated during EEG recording in infants and children. The present work aims to introduce Dr-MUSIC, a novel multisensory device with EEG-compatible timing and an attractive design for children. It is composed of audio, visual, and tactile stimulators arranged in the form of a couple of chubby dragons that can simultaneously provide selectable uni-, bi-, or tri-modal information. We first validated the system's EEG compatibility in 8 adults by implementing an audio-tactile oddball task during a high-density EEG recording. Then, we replicated the same task in a couple of toddlers to validate the device's usability for young children. The results suggest that the system can be effectively used for setting new experimental protocols to understand the neural basis of multisensory integration in the first years of life.Clinical Relevance- The amusing design and the possibility of changing the stimulation's characteristics (i.e., light, sound, and vibrotactile features) make it attractive in children with and without sensory impairments. Therefore, Dr-MUSIC could be used to investigate multisensory development and related neural correlates in typical and atypical children to design new early rehabilitation protocols.
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21
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Konjusha A, Yu S, Mückschel M, Colzato L, Ziemssen T, Beste C. Auricular Transcutaneous Vagus Nerve Stimulation Specifically Enhances Working Memory Gate Closing Mechanism: A System Neurophysiological Study. J Neurosci 2023; 43:4709-4724. [PMID: 37221097 PMCID: PMC10286950 DOI: 10.1523/jneurosci.2004-22.2023] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 04/24/2023] [Accepted: 04/30/2023] [Indexed: 05/25/2023] Open
Abstract
Everyday tasks and goal-directed behavior involve the maintenance and continuous updating of information in working memory (WM). WM gating reflects switches between these two core states. Neurobiological considerations suggest that the catecholaminergic and the GABAergic are likely involved in these dynamics. Both of these neurotransmitter systems likely underlie the effects to auricular transcutaneous vagus nerve stimulation (atVNS). We examine the effects of atVNS on WM gating dynamics and their underlying neurophysiological and neurobiological processes in a randomized crossover study design in healthy humans of both sexes. We show that atVNS specifically modulates WM gate closing and thus specifically modulates neural mechanisms enabling the maintenance of information in WM. WM gate opening processes were not affected. atVNS modulates WM gate closing processes through the modulation of EEG alpha band activity. This was the case for clusters of activity in the EEG signal referring to stimulus information, motor response information, and fractions of information carrying stimulus-response mapping rules during WM gate closing. EEG-beamforming shows that modulations of activity in fronto-polar, orbital, and inferior parietal regions are associated with these effects. The data suggest that these effects are not because of modulations of the catecholaminergic (noradrenaline) system as indicated by lack of modulatory effects in pupil diameter dynamics, in the inter-relation of EEG and pupil diameter dynamics and saliva markers of noradrenaline activity. Considering other findings, it appears that a central effect of atVNS during cognitive processing refers to the stabilization of information in neural circuits, putatively mediated via the GABAergic system.SIGNIFICANCE STATEMENT Goal-directed behavior depends on how well information in short-term memory can be flexibly updated but also on how well it can be shielded from distraction. These two functions were guarded by a working memory gate. We show how an increasingly popular brain stimulation techniques specifically enhances the ability to close the working memory gate to shield information from distraction. We show what physiological and anatomic aspects underlie these effects.
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Affiliation(s)
- Anyla Konjusha
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Dresden 01307, Germany
| | - Shijing Yu
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Dresden 01307, Germany
| | - Moritz Mückschel
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Dresden 01307, Germany
| | - Lorenza Colzato
- Faculty of Psychology, Shandong Normal University, Jinan 250014, China
| | - Tjalf Ziemssen
- Department of Neurology, Faculty of Medicine, MS Centre, TU Dresden, Dresden 01307, Germany
| | - Christian Beste
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Dresden 01307, Germany
- Faculty of Psychology, Shandong Normal University, Jinan 250014, China
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22
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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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23
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Park S, Ha J, Ahn W, Kim L. Measurement of craving among gamers with internet gaming disorder using repeated presentations of game videos: a resting-state electroencephalography study. BMC Public Health 2023; 23:816. [PMID: 37143023 PMCID: PMC10158347 DOI: 10.1186/s12889-023-15750-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 04/25/2023] [Indexed: 05/06/2023] Open
Abstract
BACKGROUND Internet gaming disorder (IGD) is receiving increasing attention owing to its effects on daily living and psychological function. METHODS In this study, electroencephalography was used to compare neural activity triggered by repeated presentation of a stimulus in healthy controls (HCs) and those with IGD. A total of 42 adult men were categorized into two groups (IGD, n = 21) based on Y-IAT-K scores. Participants were required to watch repeated presentations of video games while wearing a head-mounted display, and the delta (D), theta (T), alpha (A), beta (B), and gamma (G) activities in the prefrontal (PF), central (C), and parieto-occipital (PO) regions were analyzed. RESULTS The IGD group exhibited higher absolute powers of DC, DPO, TC, TPO, BC, and BPO than HCs. Among the IGD classification models, a neural network achieves the highest average accuracy of 93% (5-fold cross validation) and 84% (test). CONCLUSIONS These findings may significantly contribute to a more comprehensive understanding of the neurological features associated with IGD and provide potential neurological markers that can be used to distinguish between individuals with IGD and HCs.
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Affiliation(s)
- Sangin Park
- Industry-Academy Cooperation Team, Hanyang University, 222, Wangsimni-ro, Seongdong-gu, Seoul, 04763, South Korea
| | - Jihyeon Ha
- Center for Bionics, Korea Institute of Science and Technology, 5, Hwarang-ro 14-gil Seongbuk-gu, Seoul, 02792, South Korea
| | - Wonbin Ahn
- Applied AI Research Lab, LG AI Research, 128, Yeoui-daero, Yeongdeungpo-gu, Seoul, 07796, South Korea
| | - Laehyun Kim
- Center for Bionics, Korea Institute of Science and Technology, 5, Hwarang-ro 14-gil Seongbuk-gu, Seoul, 02792, South Korea.
- Department of HY-KIST Bio-convergence, Hanyang University, 222, Wangsimni-ro, Seongdong-gu, Seoul, 04763, South Korea.
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24
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Nakuci J, Wasylyshyn N, Cieslak M, Elliott JC, Bansal K, Giesbrecht B, Grafton ST, Vettel JM, Garcia JO, Muldoon SF. Within-subject reproducibility varies in multi-modal, longitudinal brain networks. Sci Rep 2023; 13:6699. [PMID: 37095180 PMCID: PMC10126005 DOI: 10.1038/s41598-023-33441-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 04/12/2023] [Indexed: 04/26/2023] Open
Abstract
Network neuroscience provides important insights into brain function by analyzing complex networks constructed from diffusion Magnetic Resonance Imaging (dMRI), functional MRI (fMRI) and Electro/Magnetoencephalography (E/MEG) data. However, in order to ensure that results are reproducible, we need a better understanding of within- and between-subject variability over long periods of time. Here, we analyze a longitudinal, 8 session, multi-modal (dMRI, and simultaneous EEG-fMRI), and multiple task imaging data set. We first confirm that across all modalities, within-subject reproducibility is higher than between-subject reproducibility. We see high variability in the reproducibility of individual connections, but observe that in EEG-derived networks, during both rest and task, alpha-band connectivity is consistently more reproducible than connectivity in other frequency bands. Structural networks show a higher reliability than functional networks across network statistics, but synchronizability and eigenvector centrality are consistently less reliable than other network measures across all modalities. Finally, we find that structural dMRI networks outperform functional networks in their ability to identify individuals using a fingerprinting analysis. Our results highlight that functional networks likely reflect state-dependent variability not present in structural networks, and that the type of analysis should depend on whether or not one wants to take into account state-dependent fluctuations in connectivity.
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Affiliation(s)
- Johan Nakuci
- Neuroscience Program, University at Buffalo, SUNY, Buffalo, NY, 14260, USA.
- School of Psychology, Georgia Institute of Technology, Atlanta, GA, 14260, USA.
| | - Nick Wasylyshyn
- U.S. CCDC Army Research Laboratory, Aberdeen Proving Ground, Aberdeen, MD, 21005, USA
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Matthew Cieslak
- Department of Psychological and Brain Sciences, University of California, Santa Barbara, CA, 93106, USA
| | - James C Elliott
- Department of Psychological and Brain Sciences, University of California, Santa Barbara, CA, 93106, USA
| | - Kanika Bansal
- U.S. CCDC Army Research Laboratory, Aberdeen Proving Ground, Aberdeen, MD, 21005, USA
- Department of Biomedical Engineering, Columbia University, New York, NY, 10027, USA
| | - Barry Giesbrecht
- Department of Psychological and Brain Sciences, University of California, Santa Barbara, CA, 93106, USA
- Institute for Collaborative Biotechnologies, University of California, Santa Barbara, CA, 93106, USA
| | - Scott T Grafton
- Department of Psychological and Brain Sciences, University of California, Santa Barbara, CA, 93106, USA
- Institute for Collaborative Biotechnologies, University of California, Santa Barbara, CA, 93106, USA
| | - Jean M Vettel
- U.S. CCDC Army Research Laboratory, Aberdeen Proving Ground, Aberdeen, MD, 21005, USA
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychological and Brain Sciences, University of California, Santa Barbara, CA, 93106, USA
| | - Javier O Garcia
- U.S. CCDC Army Research Laboratory, Aberdeen Proving Ground, Aberdeen, MD, 21005, USA
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Sarah F Muldoon
- Neuroscience Program, University at Buffalo, SUNY, Buffalo, NY, 14260, USA.
- Department of Mathematics and CDSE Program, University at Buffalo, SUNY, Buffalo, NY, 14260, USA.
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25
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Wendiggensen P, Beste C. How Intermittent Brain States Modulate Neurophysiological Processes in Cognitive Flexibility. J Cogn Neurosci 2023; 35:749-764. [PMID: 36724399 DOI: 10.1162/jocn_a_01970] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Cognitive flexibility is an essential facet of everyday life, for example, when switching between different tasks. Neurophysiological accounts on cognitive flexibility have often focused on the task switch itself, disregarding preceding processes and the possible impact of "brain states" before engaging in cognitive flexibility. In a combined working memory/task-switching paradigm, we examined how neuronal processes during cognitive flexibility are interrelated to preceding neuronal processes across time and brain regions in a sample of n = 42 healthy adults. The interrelation of alpha- and theta-band-related processes over brain states ahead and during response selection was investigated on a functional neuroanatomical level using EEG-beamforming. The results showed that response selection processes (reflected by theta-band activity) seem to be strongly connected to "idling" and preparatory brain activity states (in both the theta- and alpha-band). Notably, the superior parietal cortex seems to play a crucial role by assembling alpha-band-related inhibitory processes from the rule- and goal-based actions during "idling" brain states, namely, short-term maintenance of rules (temporal cortex), task-set reconfiguration (superior frontal/precentral regions), and perceptual control (occipital cortex). This information is further relayed to response selection processes associated with theta-band activity. Notably, when the task has to be switched, theta-band activity in the superior frontal gyrus indicates a need for cognitive control in the "idling" brain state, which also seems to be relayed by BA7. The results indicate the importance of brain activity states ahead of response selection processes for cognitive flexibility.
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26
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Zhao L, Zhang Y, Yu X, Wu H, Wang L, Li F, Duan M, Lai Y, Liu T, Dong L, Yao D. Quantitative signal quality assessment for large-scale continuous scalp electroencephalography from a big data perspective. Physiol Meas 2023; 44. [PMID: 35952665 DOI: 10.1088/1361-6579/ac890d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 08/11/2022] [Indexed: 11/12/2022]
Abstract
Objective. Despite electroencephalography (EEG) being a widely used neuroimaging technique with an excellent temporal resolution, in practice, the signals are heavily contaminated by artifacts masking responses of interest in an experiment. It is thus essential to guarantee a prompt and effective detection of artifacts that provides quantitative quality assessment (QA) on raw EEG data. This type of pipeline is crucial for large-scale EEG studies. However, current EEG QA studies are still limited.Approach. In this study, combined from a big data perspective, we therefore describe a quantitative signal quality assessment pipeline, a stable and general threshold-based QA pipeline that automatically integrates artifact detection and new QA measures to assess continuous resting-state raw EEG data. One simulation dataset and two resting-state EEG datasets from 42 healthy subjects and 983 clinical patients were utilized to calibrate the QA pipeline.Main Results. The results demonstrate that (1) the QA indices selected are sensitive: they almost strictly and linearly decrease as the noise level increases; (2) stable, replicable QA thresholds are valid for other experimental and clinical EEG datasets; and (3) use of the QA pipeline on these datasets reveals that high-frequency noises are the most common noises in EEG practice. The QA pipeline is also deployed in the WeBrain cloud platform (https://webrain.uestc.edu.cn/, the Chinese EEG Brain Consortium portal).Significance. These findings suggest that the proposed QA pipeline may be a stable and promising approach for quantitative EEG signal quality assessment in large-scale EEG studies.
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Affiliation(s)
- Lingling Zhao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, People's Republic of China.,School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
| | - Yufan Zhang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, People's Republic of China.,School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
| | - Xue Yu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, People's Republic of China.,School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
| | - Hanxi Wu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
| | - Lei Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
| | - Fali Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, People's Republic of China.,School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, People's Republic of China.,Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, People's Republic of China
| | - Mingjun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, People's Republic of China.,Sichuan Institute for Brain Science and Brain-Inspired Intelligence, Chengdu 611731, People's Republic of China
| | - Yongxiu Lai
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, People's Republic of China.,School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, People's Republic of China.,Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, People's Republic of China
| | - Tiejun Liu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, People's Republic of China.,School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, People's Republic of China.,Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, People's Republic of China.,Sichuan Institute for Brain Science and Brain-Inspired Intelligence, Chengdu 611731, People's Republic of China
| | - Li Dong
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, People's Republic of China.,School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, People's Republic of China.,Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, People's Republic of China.,Sichuan Institute for Brain Science and Brain-Inspired Intelligence, Chengdu 611731, People's Republic of China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, People's Republic of China.,School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, People's Republic of China.,Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, People's Republic of China.,Sichuan Institute for Brain Science and Brain-Inspired Intelligence, Chengdu 611731, People's Republic of China
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Mastropietro A, Pirovano I, Marciano A, Porcelli S, Rizzo G. Reliability of Mental Workload Index Assessed by EEG with Different Electrode Configurations and Signal Pre-Processing Pipelines. SENSORS (BASEL, SWITZERLAND) 2023; 23:1367. [PMID: 36772409 PMCID: PMC9920504 DOI: 10.3390/s23031367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 01/18/2023] [Accepted: 01/21/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND AND OBJECTIVE Mental workload (MWL) is a relevant construct involved in all cognitively demanding activities, and its assessment is an important goal in many research fields. This paper aims at evaluating the reproducibility and sensitivity of MWL assessment from EEG signals considering the effects of different electrode configurations and pre-processing pipelines (PPPs). METHODS Thirteen young healthy adults were enrolled and were asked to perform 45 min of Simon's task to elicit a cognitive demand. EEG data were collected using a 32-channel system with different electrode configurations (fronto-parietal; Fz and Pz; Cz) and analyzed using different PPPs, from the simplest bandpass filtering to the combination of filtering, Artifact Subspace Reconstruction (ASR) and Independent Component Analysis (ICA). The reproducibility of MWL indexes estimation and the sensitivity of their changes were assessed using Intraclass Correlation Coefficient and statistical analysis. RESULTS MWL assessed with different PPPs showed reliability ranging from good to very good in most of the electrode configurations (average consistency > 0.87 and average absolute agreement > 0.92). Larger fronto-parietal electrode configurations, albeit being more affected by the choice of PPPs, provide better sensitivity in the detection of MWL changes if compared to a single-electrode configuration (18 vs. 10 statistically significant differences detected, respectively). CONCLUSIONS The most complex PPPs have been proven to ensure good reliability (>0.90) and sensitivity in all experimental conditions. In conclusion, we propose to use at least a two-electrode configuration (Fz and Pz) and complex PPPs including at least the ICA algorithm (even better including ASR) to mitigate artifacts and obtain reliable and sensitive MWL assessment during cognitive tasks.
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Affiliation(s)
- Alfonso Mastropietro
- Institute of Biomedical Technologies, National Research Council, Via Fratelli Cervi 93, 20054 Segrate, Italy
| | - Ileana Pirovano
- Institute of Biomedical Technologies, National Research Council, Via Fratelli Cervi 93, 20054 Segrate, Italy
| | - Alessio Marciano
- Department of Molecular Medicine, University of Pavia, Via Forlanini 6, 27100 Pavia, Italy
| | - Simone Porcelli
- Department of Molecular Medicine, University of Pavia, Via Forlanini 6, 27100 Pavia, Italy
| | - Giovanna Rizzo
- Institute of Biomedical Technologies, National Research Council, Via Fratelli Cervi 93, 20054 Segrate, Italy
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28
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Gonsisko CB, Ferris DP, Downey RJ. iCanClean Improves Independent Component Analysis of Mobile Brain Imaging with EEG. SENSORS (BASEL, SWITZERLAND) 2023; 23:928. [PMID: 36679726 PMCID: PMC9863946 DOI: 10.3390/s23020928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 01/06/2023] [Accepted: 01/11/2023] [Indexed: 06/17/2023]
Abstract
Motion artifacts hinder source-level analysis of mobile electroencephalography (EEG) data using independent component analysis (ICA). iCanClean is a novel cleaning algorithm that uses reference noise recordings to remove noisy EEG subspaces, but it has not been formally tested in a parameter sweep. The goal of this study was to test iCanClean’s ability to improve the ICA decomposition of EEG data corrupted by walking motion artifacts. Our primary objective was to determine optimal settings and performance in a parameter sweep (varying the window length and r2 cleaning aggressiveness). High-density EEG was recorded with 120 + 120 (dual-layer) EEG electrodes in young adults, high-functioning older adults, and low-functioning older adults. EEG data were decomposed by ICA after basic preprocessing and iCanClean. Components well-localized as dipoles (residual variance < 15%) and with high brain probability (ICLabel > 50%) were marked as ‘good’. We determined iCanClean’s optimal window length and cleaning aggressiveness to be 4-s and r2 = 0.65 for our data. At these settings, iCanClean improved the average number of good components from 8.4 to 13.2 (+57%). Good performance could be maintained with reduced sets of noise channels (12.7, 12.2, and 12.0 good components for 64, 32, and 16 noise channels, respectively). Overall, iCanClean shows promise as an effective method to clean mobile EEG data.
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29
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Hilditch CJ, Bansal K, Chachad R, Wong LR, Bathurst NG, Feick NH, Santamaria A, Shattuck NL, Garcia JO, Flynn-Evans EE. Reconfigurations in brain networks upon awakening from slow wave sleep: Interventions and implications in neural communication. Netw Neurosci 2023; 7:102-121. [PMID: 37334002 PMCID: PMC10270716 DOI: 10.1162/netn_a_00272] [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: 04/11/2022] [Accepted: 08/05/2022] [Indexed: 04/04/2024] Open
Abstract
Sleep inertia is the brief period of impaired alertness and performance experienced immediately after waking. Little is known about the neural mechanisms underlying this phenomenon. A better understanding of the neural processes during sleep inertia may offer insight into the awakening process. We observed brain activity every 15 min for 1 hr following abrupt awakening from slow wave sleep during the biological night. Using 32-channel electroencephalography, a network science approach, and a within-subject design, we evaluated power, clustering coefficient, and path length across frequency bands under both a control and a polychromatic short-wavelength-enriched light intervention condition. We found that under control conditions, the awakening brain is typified by an immediate reduction in global theta, alpha, and beta power. Simultaneously, we observed a decrease in the clustering coefficient and an increase in path length within the delta band. Exposure to light immediately after awakening ameliorated changes in clustering. Our results suggest that long-range network communication within the brain is crucial to the awakening process and that the brain may prioritize these long-range connections during this transitional state. Our study highlights a novel neurophysiological signature of the awakening brain and provides a potential mechanism by which light improves performance after waking.
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Affiliation(s)
- Cassie J. Hilditch
- Fatigue Countermeasures Laboratory, Department of Psychology, San José State University, San José, CA, USA
| | - Kanika Bansal
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
- US DEVCOM Army Research Laboratory, Humans in Complex Systems Division, Aberdeen Proving Ground, MD, USA
| | - Ravi Chachad
- Fatigue Countermeasures Laboratory, Department of Psychology, San José State University, San José, CA, USA
| | - Lily R. Wong
- Fatigue Countermeasures Laboratory, Department of Psychology, San José State University, San José, CA, USA
| | - Nicholas G. Bathurst
- Fatigue Countermeasures Laboratory, Human Systems Integration Division, NASA Ames Research Center, Moffett Field, CA, USA
| | - Nathan H. Feick
- Fatigue Countermeasures Laboratory, Department of Psychology, San José State University, San José, CA, USA
| | - Amanda Santamaria
- Cognitive and Systems Neuroscience Research Hub, University of South Australia, Adelaide, SA, Australia
| | - Nita L. Shattuck
- Operations Research Department, Naval Postgraduate School, Monterey, CA, USA
| | - Javier O. Garcia
- US DEVCOM Army Research Laboratory, Humans in Complex Systems Division, Aberdeen Proving Ground, MD, USA
| | - Erin E. Flynn-Evans
- Fatigue Countermeasures Laboratory, Human Systems Integration Division, NASA Ames Research Center, Moffett Field, CA, USA
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30
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Szewczyk M, Augustynowicz P, Szubielska M. Implicit spatial sequential learning facilitates attentional selection in covert visual search. An event-related potentials study. Front Hum Neurosci 2022; 16:974791. [DOI: 10.3389/fnhum.2022.974791] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Accepted: 11/16/2022] [Indexed: 12/04/2022] Open
Abstract
IntroductionWhile most studies on implicit sequential learning focus on object learning, the hidden structure of target location and onset time can also be a subject of implicitly gathered knowledge. In our study, we wanted to investigate the effect of implicitly learned spatial and temporal sequential predictability on performance in a localization task in a paradigm in which covert selective attention is engaged. We were also interested in the neural mechanism of the facilitating effect of the predictable spatio-temporal context on visual search processes. Specifically, with the use of an event-related potential technique, we wanted to verify whether perceptual, attentional, and motor processes can be enhanced by the predictive spatio-temporal context of visual stimuli.MethodsWe analyzed data from 15 young, healthy adults who took part in an experimental electroencephalographic (EEG) study and performed a visual search localization task. Predictable sequences of four target locations and/or target onset times were presented in separate blocks of trials that formed the Space, Space- Time, and Time conditions. One block of trials with randomly presented stimuli served as a control condition.ResultsThe behavioral results revealed that participants successfully learned only the spatial dimension of target predictability. Although spatial predictability was a response-relevant dimension, we found that attentional selection–instead of motor preparation–was the facilitation mechanism in this type of visual search task. This was manifested by a shorter latency and more negative amplitude of the N2pc component and the lack of an effect on the sLRP component. We observed no effect of predictability on perceptual processing (P1 component).DiscussionWe discuss these results with reference to the current knowledge on sequential learning. Our findings also contribute to the current debate on the predictive coding theory.
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31
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Ismail L, Karwowski W, Farahani FV, Rahman M, Alhujailli A, Fernandez-Sumano R, Hancock PA. Modeling Brain Functional Connectivity Patterns during an Isometric Arm Force Exertion Task at Different Levels of Perceived Exertion: A Graph Theoretical Approach. Brain Sci 2022; 12:1575. [PMID: 36421899 PMCID: PMC9688629 DOI: 10.3390/brainsci12111575] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 11/09/2022] [Accepted: 11/13/2022] [Indexed: 09/29/2023] Open
Abstract
The perception of physical exertion is the cognitive sensation of work demands associated with voluntary muscular actions. Measurements of exerted force are crucial for avoiding the risk of overexertion and understanding human physical capability. For this purpose, various physiological measures have been used; however, the state-of-the-art in-force exertion evaluation lacks assessments of underlying neurophysiological signals. The current study applied a graph theoretical approach to investigate the topological changes in the functional brain network induced by predefined force exertion levels for twelve female participants during an isometric arm task and rated their perceived physical comfort levels. The functional connectivity under predefined force exertion levels was assessed using the coherence method for 84 anatomical brain regions of interest at the electroencephalogram (EEG) source level. Then, graph measures were calculated to quantify the network topology for two frequency bands. The results showed that high-level force exertions are associated with brain networks characterized by more significant clustering coefficients (6%), greater modularity (5%), higher global efficiency (9%), and less distance synchronization (25%) under alpha coherence. This study on the neurophysiological basis of physical exertions with various force levels suggests that brain regions communicate and cooperate higher when muscle force exertions increase to meet the demands of physically challenging tasks.
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Affiliation(s)
- Lina Ismail
- Department of Industrial and Management Engineering, Arab Academy for Science Technology & Maritime Transport, Alexandria 2913, Egypt
| | - Waldemar Karwowski
- Department of Industrial Engineering and Management Systems, University of Central Florida, Orlando, FL 32816, USA
| | - Farzad V. Farahani
- Department of Biostatistics, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Mahjabeen Rahman
- Department of Industrial Engineering and Management Systems, University of Central Florida, Orlando, FL 32816, USA
| | - Ashraf Alhujailli
- Department of Management Science, Yanbu Industrial College, Yanbu 46452, Saudi Arabia
| | - Raul Fernandez-Sumano
- Department of Industrial Engineering and Management Systems, University of Central Florida, Orlando, FL 32816, USA
| | - P. A. Hancock
- Department of Psychology, University of Central Florida, Orlando, FL 32816, USA
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Gori M, Amadeo MB, Pavani F, Valzolgher C, Campus C. Temporal visual representation elicits early auditory-like responses in hearing but not in deaf individuals. Sci Rep 2022; 12:19036. [PMID: 36351944 PMCID: PMC9646881 DOI: 10.1038/s41598-022-22224-x] [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: 01/03/2022] [Accepted: 10/11/2022] [Indexed: 11/10/2022] Open
Abstract
It is evident that the brain is capable of large-scale reorganization following sensory deprivation, but the extent of such reorganization is to date, not clear. The auditory modality is the most accurate to represent temporal information, and deafness is an ideal clinical condition to study the reorganization of temporal representation when the audio signal is not available. Here we show that hearing, but not deaf individuals, show a strong ERP response to visual stimuli in temporal areas during a time-bisection task. This ERP response appears 50-90 ms after the flash and recalls some aspects of the N1 ERP component usually elicited by auditory stimuli. The same ERP is not evident for a visual space-bisection task, suggesting that the early recruitment of temporal cortex is specific for building a highly resolved temporal representation within the visual modality. These findings provide evidence that the lack of auditory input can interfere with typical development of complex visual temporal representations.
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Affiliation(s)
- Monica Gori
- grid.25786.3e0000 0004 1764 2907Unit for Visually Impaired People, Fondazione Istituto Italiano di Tecnologia, Via Enrico Melen 83, 16152 Genoa, Italy
| | - Maria Bianca Amadeo
- grid.25786.3e0000 0004 1764 2907Unit for Visually Impaired People, Fondazione Istituto Italiano di Tecnologia, Via Enrico Melen 83, 16152 Genoa, Italy
| | - Francesco Pavani
- grid.11696.390000 0004 1937 0351Center for Mind/Brain Sciences (CIMeC), University of Trento, Trento, Italy ,grid.11696.390000 0004 1937 0351Centro Interateneo di Ricerca Cognizione, Linguaggio e Sordità (CIRCLeS), University of Trento, Trento, Italy ,grid.461862.f0000 0004 0614 7222Integrative, Multisensory, Perception, Action and Cognition Team (IMPACT), Centre de Recherche en Neuroscience de Lyon (CRNL), Bron, France
| | - Chiara Valzolgher
- grid.11696.390000 0004 1937 0351Center for Mind/Brain Sciences (CIMeC), University of Trento, Trento, Italy ,grid.461862.f0000 0004 0614 7222Integrative, Multisensory, Perception, Action and Cognition Team (IMPACT), Centre de Recherche en Neuroscience de Lyon (CRNL), Bron, France
| | - Claudio Campus
- grid.25786.3e0000 0004 1764 2907Unit for Visually Impaired People, Fondazione Istituto Italiano di Tecnologia, Via Enrico Melen 83, 16152 Genoa, Italy
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Chuang CH, Chang KY, Huang CS, Jung TP. IC-U-Net: A U-Net-based Denoising Autoencoder Using Mixtures of Independent Components for Automatic EEG Artifact Removal. Neuroimage 2022; 263:119586. [PMID: 36031182 DOI: 10.1016/j.neuroimage.2022.119586] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 07/27/2022] [Accepted: 08/22/2022] [Indexed: 10/31/2022] Open
Abstract
Electroencephalography (EEG) signals are often contaminated with artifacts. It is imperative to develop a practical and reliable artifact removal method to prevent the misinterpretation of neural signals and the underperformance of brain-computer interfaces. Based on the U-Net architecture, we developed a new artifact removal model, IC-U-Net, for removing pervasive EEG artifacts and reconstructing brain signals. IC-U-Net was trained using mixtures of brain and non-brain components decomposed by independent component analysis. It uses an ensemble of loss functions to model complex signal fluctuations in EEG recordings. The effectiveness of the proposed method in recovering brain activities and removing various artifacts (e.g., eye blinks/movements, muscle activities, and line/channel noise) was demonstrated in a simulation study and four real-world EEG experiments. IC-U-Net can reconstruct a multi-channel EEG signal and is applicable to most artifact types, offering a promising end-to-end solution for automatically removing artifacts from EEG recordings. It also meets the increasing need to image natural brain dynamics in a mobile setting. The code and pre-trained IC-U-Net model are available at https://github.com/roseDwayane/AIEEG.
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Affiliation(s)
- Chun-Hsiang Chuang
- Research Center for Education and Mind Sciences, College of Education, National Tsing Hua University, Hsinchu, Taiwan; Institute of Information Systems and Applications, College of Electrical Engineering and Computer Science, National Tsing Hua University, Hsinchu, Taiwan; Department of Education and Learning Technology, National Tsing Hua University, Hsinchu, Taiwan.
| | - Kong-Yi Chang
- Research Center for Education and Mind Sciences, College of Education, National Tsing Hua University, Hsinchu, Taiwan; Institute of Information Systems and Applications, College of Electrical Engineering and Computer Science, National Tsing Hua University, Hsinchu, Taiwan; Department of Computer Science and Engineering, National Taiwan Ocean University, Keelung, Taiwan
| | - Chih-Sheng Huang
- Department of Artificial Intelligence Research and Development, Elan Microelectronics Corporation, Hsinchu, Taiwan; College of Artificial Intelligence and Green Energy, National Yang Ming Chiao Tung University, Hsinchu, Taiwan; College of Electrical Engineering and Computer Science, National Taipei University of Technology, Taipei, Taiwan
| | - Tzyy-Ping Jung
- Institute of Engineering in Medicine and Institute for Neural Computation, University of California San Diego, La Jolla, USA
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Studnicki A, Downey RJ, Ferris DP. Characterizing and Removing Artifacts Using Dual-Layer EEG during Table Tennis. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22155867. [PMID: 35957423 PMCID: PMC9371038 DOI: 10.3390/s22155867] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 07/28/2022] [Accepted: 08/02/2022] [Indexed: 05/27/2023]
Abstract
Researchers can improve the ecological validity of brain research by studying humans moving in real-world settings. Recent work shows that dual-layer EEG can improve the fidelity of electrocortical recordings during gait, but it is unclear whether these positive results extrapolate to non-locomotor paradigms. For our study, we recorded brain activity with dual-layer EEG while participants played table tennis, a whole-body, responsive sport that could help investigate visuomotor feedback, object interception, and performance monitoring. We characterized artifacts with time-frequency analyses and correlated scalp and reference noise data to determine how well different sensors captured artifacts. As expected, individual scalp channels correlated more with noise-matched channel time series than with head and body acceleration. We then compared artifact removal methods with and without the use of the dual-layer noise electrodes. Independent Component Analysis separated channels into components, and we counted the number of high-quality brain components based on the fit of a dipole model and using an automated labeling algorithm. We found that using noise electrodes for data processing provided cleaner brain components. These results advance technological approaches for recording high fidelity brain dynamics in human behaviors requiring whole body movement, which will be useful for brain science research.
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Sarailoo R, Latifzadeh K, Amiri SH, Bosaghzadeh A, Ebrahimpour R. Assessment of instantaneous cognitive load imposed by educational multimedia using electroencephalography signals. Front Neurosci 2022; 16:744737. [PMID: 35979334 PMCID: PMC9377376 DOI: 10.3389/fnins.2022.744737] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 07/14/2022] [Indexed: 11/13/2022] Open
Abstract
The use of multimedia learning is increasing in modern education. On the other hand, it is crucial to design multimedia contents that impose an optimal amount of cognitive load, which leads to efficient learning. Objective assessment of instantaneous cognitive load plays a critical role in educational design quality evaluation. Electroencephalography (EEG) has been considered a potential candidate for cognitive load assessment among neurophysiological methods. In this study, we experiment to collect EEG signals during a multimedia learning task and then build a model for instantaneous cognitive load measurement. In the experiment, we designed four educational multimedia in two categories to impose different levels of cognitive load by intentionally applying/violating Mayer's multimedia design principles. Thirty university students with homogenous English language proficiency participated in our experiment. We divided them randomly into two groups, and each watched a version of the multimedia followed by a recall test task and filling out a NASA-TLX questionnaire. EEG signals are collected during these tasks. To construct the load assessment model, at first, power spectral density (PSD) based features are extracted from EEG signals. Using the minimum redundancy - maximum relevance (MRMR) feature selection approach, the best features are selected. In this way, the selected features consist of only about 12% of the total number of features. In the next step, we propose a scoring model using a support vector machine (SVM) for instantaneous cognitive load assessment in 3s segments of multimedia. Our experiments indicate that the selected feature set can classify the instantaneous cognitive load with an accuracy of 84.5 ± 2.1%. The findings of this study indicate that EEG signals can be used as an appropriate tool for measuring the cognitive load introduced by educational videos. This can be help instructional designers to develop more effective content.
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Affiliation(s)
- Reza Sarailoo
- Artificial Intelligence Group, Faculty of Computer Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran
| | - Kayhan Latifzadeh
- Artificial Intelligence Group, Faculty of Computer Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran
| | - S. Hamid Amiri
- Artificial Intelligence Group, Faculty of Computer Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran
| | - Alireza Bosaghzadeh
- Artificial Intelligence Group, Faculty of Computer Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran
| | - Reza Ebrahimpour
- Artificial Intelligence Group, Faculty of Computer Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran
- School of Cognitive Sciences, Institute for Research in Fundamental Sciences, Tehran, Iran
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36
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Pérez A, Davis MH, Ince RAA, Zhang H, Fu Z, Lamarca M, Lambon Ralph MA, Monahan PJ. Timing of brain entrainment to the speech envelope during speaking, listening and self-listening. Cognition 2022; 224:105051. [PMID: 35219954 PMCID: PMC9112165 DOI: 10.1016/j.cognition.2022.105051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Revised: 01/24/2022] [Accepted: 01/26/2022] [Indexed: 11/17/2022]
Abstract
This study investigates the dynamics of speech envelope tracking during speech production, listening and self-listening. We use a paradigm in which participants listen to natural speech (Listening), produce natural speech (Speech Production), and listen to the playback of their own speech (Self-Listening), all while their neural activity is recorded with EEG. After time-locking EEG data collection and auditory recording and playback, we used a Gaussian copula mutual information measure to estimate the relationship between information content in the EEG and auditory signals. In the 2-10 Hz frequency range, we identified different latencies for maximal speech envelope tracking during speech production and speech perception. Maximal speech tracking takes place approximately 110 ms after auditory presentation during perception and 25 ms before vocalisation during speech production. These results describe a specific timeline for speech tracking in speakers and listeners in line with the idea of a speech chain and hence, delays in communication.
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Affiliation(s)
- Alejandro Pérez
- MRC Cognition and Brain Sciences Unit, University of Cambridge, UK; Department of Language Studies, University of Toronto Scarborough, Canada; Department of Psychology, University of Toronto Scarborough, Canada.
| | - Matthew H Davis
- MRC Cognition and Brain Sciences Unit, University of Cambridge, UK
| | - Robin A A Ince
- School of Psychology and Neuroscience, University of Glasgow, UK
| | - Hanna Zhang
- Department of Language Studies, University of Toronto Scarborough, Canada; Department of Linguistics, University of Toronto, Canada
| | - Zhanao Fu
- Department of Language Studies, University of Toronto Scarborough, Canada; Department of Linguistics, University of Toronto, Canada
| | - Melanie Lamarca
- Department of Language Studies, University of Toronto Scarborough, Canada
| | | | - Philip J Monahan
- Department of Language Studies, University of Toronto Scarborough, Canada; Department of Psychology, University of Toronto Scarborough, Canada
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37
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Jin RN, Inada H, Négyesi J, Ito D, Nagatomi R. Carbon dioxide effects on daytime sleepiness and EEG signal: A combinational approach using classical frequentist and Bayesian analyses. INDOOR AIR 2022; 32:e13055. [PMID: 35762237 PMCID: PMC9327715 DOI: 10.1111/ina.13055] [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: 10/31/2021] [Revised: 04/29/2022] [Accepted: 05/10/2022] [Indexed: 06/15/2023]
Abstract
Environmental carbon dioxide (CO2 ) could affect various mental and physiological activities in humans, but its effect on daytime sleepiness is still controversial. In a randomized and counterbalanced crossover study with twelve healthy volunteers, we applied a combinational approach using classical frequentist and Bayesian statistics to analyze the CO2 exposure effect on daytime sleepiness and electroencephalogram (EEG) signals. Subjective sleepiness was measured by the Japanese Karolinska Sleepiness Scale (KSS-J) by recording EEG during CO2 exposure at different concentrations: Normal (C), 4000 ppm (Moderately High: MH), and 40 000 ppm (high: H). The daytime sleepiness was significantly affected by the exposure time but not the CO2 condition in the classical statistics. On the other hand, the Bayesian paired t-test revealed that the CO2 exposure at the MH condition might induce daytime sleepiness at the 40-min point compared with the C condition. By contrast, EEG was significantly affected by a short exposure to the H condition but not exposure time. The Bayesian analysis of EEG was primarily consistent with results by the classical statistics but showed different credible levels in the Bayes' factor. Our result suggested that the EEG may not be suitable to detect objective sleepiness induced by CO2 exposure because the EEG signal was highly sensitive to environmental CO2 concentration. Our study would be helpful for researchers to revisit whether EEG is applicable as a judgment indicator of objective sleepiness.
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Affiliation(s)
- Rui Nian Jin
- Division of Biomedical Engineering for Health & WelfareTohoku University Graduate School of Biomedical EngineeringSendaiMiyagiJapan
| | - Hitoshi Inada
- Division of Biomedical Engineering for Health & WelfareTohoku University Graduate School of Biomedical EngineeringSendaiMiyagiJapan
| | - János Négyesi
- Division of Biomedical Engineering for Health & WelfareTohoku University Graduate School of Biomedical EngineeringSendaiMiyagiJapan
| | - Daisuke Ito
- Division of Biomedical Engineering for Health & WelfareTohoku University Graduate School of Biomedical EngineeringSendaiMiyagiJapan
| | - Ryoichi Nagatomi
- Division of Biomedical Engineering for Health & WelfareTohoku University Graduate School of Biomedical EngineeringSendaiMiyagiJapan
- Department of Medicine and Science in Sports and ExerciseTohoku University Graduate School of MedicineSendaiMiyagiJapan
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38
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Riddle J, Alexander ML, Schiller CE, Rubinow DR, Frohlich F. Reward-Based Decision-Making Engages Distinct Modes of Cross-Frequency Coupling. Cereb Cortex 2022; 32:2079-2094. [PMID: 34622271 PMCID: PMC9113280 DOI: 10.1093/cercor/bhab336] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 08/18/2021] [Accepted: 08/22/2021] [Indexed: 11/13/2022] Open
Abstract
Prefrontal cortex exerts control over sensory and motor systems via cross-frequency coupling. However, it is unknown whether these signals play a role in reward-based decision-making and whether such dynamic network configuration is altered in a major depressive episode. We recruited men and women with and without depression to perform a streamlined version of the Expenditure of Effort for Reward Task during recording of electroencephalography. Goal-directed behavior was quantified as willingness to exert physical effort to obtain reward, and reward-evaluation was the degree to which the decision to exert effort was modulated by incentive level. We found that the amplitude of frontal-midline theta oscillations was greatest in participants with the greatest reward-evaluation. Furthermore, coupling between frontal theta phase and parieto-occipital gamma amplitude was positively correlated with reward-evaluation. In addition, goal-directed behavior was positively correlated with coupling between frontal delta phase to motor beta amplitude. Finally, we performed a factor analysis to derive 2 symptom dimensions and found that mood symptoms positively tracked with reward-evaluation and motivation symptoms negatively tracked with goal-directed behavior. Altogether, these results provide evidence that 2 aspects of reward-based decision-making are instantiated by different modes of prefrontal top-down control and are modulated in different symptom dimensions of depression.
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Affiliation(s)
- Justin Riddle
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Carolina Center for Neurostimulation, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Morgan L Alexander
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Carolina Center for Neurostimulation, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Crystal Edler Schiller
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - David R Rubinow
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Flavio Frohlich
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Carolina Center for Neurostimulation, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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39
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Jalilpour S, Müller-Putz G. Toward passive BCI: asynchronous decoding of neural responses to direction- and angle-specific perturbations during a simulated cockpit scenario. Sci Rep 2022; 12:6802. [PMID: 35473959 PMCID: PMC9042920 DOI: 10.1038/s41598-022-10906-5] [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: 11/10/2021] [Accepted: 04/01/2022] [Indexed: 11/09/2022] Open
Abstract
Neuroimaging studies have provided proof that loss of balance evokes specific neural transient wave complexes in electroencephalography (EEG), called perturbation evoked potentials (PEPs). Online decoding of balance perturbations from ongoing EEG signals can establish the possibility of implementing passive brain-computer interfaces (pBCIs) as a part of aviation/driving assistant systems. In this study, we investigated the feasibility of identifying the existence and expression of perturbations in four different conditions by using EEG signals. Fifteen healthy participants experienced four various postural changes while they sat in a glider cockpit. Sudden perturbations were exposed by a robot connected to a glider and moved to the right and left directions with tilting angles of 5 and 10 degrees. Perturbations occurred in an oddball paradigm in which participants were not aware of the time and expression of the perturbations. We employed a hierarchical approach to separate the perturbation and rest, and then discriminate the expression of perturbations. The performance of the BCI system was evaluated by using classification accuracy and F1 score. Asynchronously, we achieved average accuracies of 89.83 and 73.64% and average F1 scores of 0.93 and 0.60 for binary and multiclass classification, respectively. These results manifest the practicality of pBCI for the detection of balance disturbances in a realistic situation.
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Affiliation(s)
- Shayan Jalilpour
- Institute of Neural Engineering, Graz University of Technology, Stremayrgasse 16/4, 8010, Graz, Austria
| | - Gernot Müller-Putz
- Institute of Neural Engineering, Graz University of Technology, Stremayrgasse 16/4, 8010, Graz, Austria. .,BioTechMed, Graz, Austria.
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40
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Goel R, Nakagome S, Paloski WH, Contreras-Vidal JL, Parikh PJ. Assessment of Biomechanical Predictors of Occurrence of Low-Amplitude N1 Potentials Evoked by Naturally Occurring Postural Instabilities. IEEE Trans Neural Syst Rehabil Eng 2022; 30:476-485. [PMID: 35201989 PMCID: PMC11047164 DOI: 10.1109/tnsre.2022.3154707] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Naturally occurring postural instabilities that occur while standing and walking elicit specific cortical responses in the fronto-central regions (N1 potentials) followed by corrective balance responses to prevent falling. However, no framework could simultaneously track different biomechanical parameters preceding N1s, predict N1s, and assess their predictive power. Here, we propose a framework and show its utility by examining cortical activity (through electroencephalography [EEG]), ground reaction forces, and head acceleration in the anterior-posterior (AP) direction. Ten healthy young adults carried out a balance task of standing on a support surface with or without sway referencing in the AP direction, amplifying, or dampening natural body sway. Using independent components from the fronto-central cortical region obtained from subject-specific head models, we first robustly validated a prior approach on identifying low-amplitude N1 potentials before early signs of balance corrections. Then, a machine learning algorithm was used to evaluate different biomechanical parameters obtained before N1 potentials, to predict the occurrence of N1s. When different biomechanical parameters were directly compared, the time to boundary (TTB) was found to be the best predictor of the occurrence of upcoming low-amplitude N1 potentials during a balance task. Based on these findings, we confirm that the spatio-temporal characteristics of the center of pressure (COP) might serve as an essential parameter that can facilitate the early detection of postural instability in a balance task. Extending our framework to identify such biomarkers in dynamic situations like walking might improve the implementation of corrective balance responses through brain-machine-interfaces to reduce falls in the elderly.
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41
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Darfler M, Cruz-Garza JG, Kalantari S. An EEG-Based Investigation of the Effect of Perceived Observation on Visual Memory in Virtual Environments. Brain Sci 2022; 12:brainsci12020269. [PMID: 35204033 PMCID: PMC8870655 DOI: 10.3390/brainsci12020269] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 02/01/2022] [Accepted: 02/08/2022] [Indexed: 11/16/2022] Open
Abstract
The presence of external observers has been shown to affect performance on cognitive tasks, but the parameters of this impact for different types of tasks and the underlying neural dynamics are less understood. The current study examined the behavioral and brain activity effects of perceived observation on participants’ visual working memory (VWM) in a virtual reality (VR) classroom setting, using the task format as a moderating variable. Participants (n = 21) were equipped with a 57-channel EEG cap, and neural data were collected as they completed two VWM tasks under two observation conditions (observed and not observed) in a within-subjects experimental design. The “observation” condition was operationalized through the addition of a static human avatar in the VR classroom. The avatar’s presence was associated with a significant effect on extending the task response time, but no effect was found on task accuracy. This outcome may have been due to a ceiling effect, as the mean participant task scores were quite high. EEG data analysis supported the behavioral findings by showing consistent differences between the no-observation and observation conditions for one of the VWM tasks only. These neural differences were identified in the dorsolateral prefrontal cortex (dlPFC) and the occipital cortex (OC) regions, with higher theta-band activity occurring in the dlPFC during stimulus encoding and in the OC during response selection when the “observing” avatar was present. These findings provide evidence that perceived observation can inhibit performance during visual tasks by altering attentional focus, even in virtual contexts.
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42
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Arake M, Ohta H, Tsuruhara A, Kobayashi Y, Shinomiya N, Masaki H, Morimoto Y. Measuring Task-Related Brain Activity With Event-Related Potentials in Dynamic Task Scenario With Immersive Virtual Reality Environment. Front Behav Neurosci 2022; 16:779926. [PMID: 35185487 PMCID: PMC8847391 DOI: 10.3389/fnbeh.2022.779926] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Accepted: 01/10/2022] [Indexed: 11/27/2022] Open
Abstract
Measurement of event-related potentials (ERPs) in simulated and real environments is advantageous for understanding cognition and behavior during practice of goal-directed activities. Recently, instead of using task-irrelevant “probe stimuli” to elicit ERPs, extraction of ERPs directly from events that occur in simulated and real environments has drawn increased attention. Among the previous ERP studies using immersive virtual reality, only a few cases elicited ERPs from task-related events in dynamic task settings. Furthermore, as far as we surveyed, there were no studies that examined the source of ERPs or correlation between ERPs and behavioral performance in 360-degree immersive virtual reality using head-mounted display. In this study, EEG signals were recorded from 16 participants while they were playing the first-person shooter game with immersive virtual reality environment. Error related negativity (ERN) and correct-(response)-related negativity (CRN) elicited by shooting-related events were successfully extracted. We found the ERN amplitudes to be correlated with the individual shooting performance. Interestingly, the main source of the ERN was the rostral anterior cingulate cortex (ACC), which is different from previous studies where the signal source was often estimated to be the more caudal part of ACC. The obtained results are expected to contribute to the evaluation of cognitive functions and behavioral performance by ERPs in a simulated environment.
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Affiliation(s)
- Masashi Arake
- Department of Physiology, National Defense Medical College, Tokorozawa, Japan
- Aeromedical Laboratory, Japan Air Self-Defense Force, Sayama, Japan
| | - Hiroyuki Ohta
- Department of Pharmacology, National Defense Medical College, Tokorozawa, Japan
| | - Aki Tsuruhara
- Aeromedical Laboratory, Japan Air Self-Defense Force, Sayama, Japan
| | - Yasushi Kobayashi
- Department of Anatomy and Neurobiology, National Defense Medical College, Tokorozawa, Japan
| | - Nariyoshi Shinomiya
- Department of Integrative Physiology and Bio-Nano Medicine, National Defense Medical College, Tokorozawa, Japan
| | - Hiroaki Masaki
- Faculty of Sport Sciences, Waseda University, Tokorozawa, Japan
| | - Yuji Morimoto
- Department of Physiology, National Defense Medical College, Tokorozawa, Japan
- *Correspondence: Yuji Morimoto,
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43
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Monahan PJ, Schertz J, Fu Z, Pérez A. Unified Coding of Spectral and Temporal Phonetic Cues: Electrophysiological Evidence for Abstract Phonological Features. J Cogn Neurosci 2022; 34:618-638. [DOI: 10.1162/jocn_a_01817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Abstract
Spoken word recognition models and phonological theory propose that abstract features play a central role in speech processing. It remains unknown, however, whether auditory cortex encodes linguistic features in a manner beyond the phonetic properties of the speech sounds themselves. We took advantage of the fact that English phonology functionally codes stops and fricatives as voiced or voiceless with two distinct phonetic cues: Fricatives use a spectral cue, whereas stops use a temporal cue. Evidence that these cues can be grouped together would indicate the disjunctive coding of distinct phonetic cues into a functionally defined abstract phonological feature. In English, the voicing feature, which distinguishes the consonants [s] and [t] from [z] and [d], respectively, is hypothesized to be specified only for voiceless consonants (e.g., [s t]). Here, participants listened to syllables in a many-to-one oddball design, while their EEG was recorded. In one block, both voiceless stops and fricatives were the standards. In the other block, both voiced stops and fricatives were the standards. A critical design element was the presence of intercategory variation within the standards. Therefore, a many-to-one relationship, which is necessary to elicit an MMN, existed only if the stop and fricative standards were grouped together. In addition to the ERPs, event-related spectral power was also analyzed. Results showed an MMN effect in the voiceless standards block—an asymmetric MMN—in a time window consistent with processing in auditory cortex, as well as increased prestimulus beta-band oscillatory power to voiceless standards. These findings suggest that (i) there is an auditory memory trace of the standards based on the shared (voiceless) feature, which is only functionally defined; (ii) voiced consonants are underspecified; and (iii) features can serve as a basis for predictive processing. Taken together, these results point toward auditory cortex's ability to functionally code distinct phonetic cues together and suggest that abstract features can be used to parse the continuous acoustic signal.
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Affiliation(s)
| | | | - Zhanao Fu
- Cambridge University, United Kingdom
| | - Alejandro Pérez
- University of Toronto Scarborough, Ontario, Canada
- Cambridge University, United Kingdom
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44
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Galindo SE, Toharia P, Robles OD, Pastor L. SynCoPa: Visualizing Connectivity Paths and Synapses Over Detailed Morphologies. Front Neuroinform 2022; 15:753997. [PMID: 35027889 PMCID: PMC8751653 DOI: 10.3389/fninf.2021.753997] [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: 08/05/2021] [Accepted: 11/22/2021] [Indexed: 12/02/2022] Open
Abstract
Brain complexity has traditionally fomented the division of neuroscience into somehow separated compartments; the coexistence of the anatomical, physiological, and connectomics points of view is just a paradigmatic example of this situation. However, there are times when it is important to combine some of these standpoints for getting a global picture, like for fully analyzing the morphological and topological features of a specific neuronal circuit. Within this framework, this article presents SynCoPa, a tool designed for bridging gaps among representations by providing techniques that allow combining detailed morphological neuron representations with the visualization of neuron interconnections at the synapse level. SynCoPa has been conceived for the interactive exploration and analysis of the connectivity elements and paths of simple to medium complexity neuronal circuits at the connectome level. This has been done by providing visual metaphors for synapses and interconnection paths, in combination with the representation of detailed neuron morphologies. SynCoPa could be helpful, for example, for establishing or confirming a hypothesis about the spatial distributions of synapses, or for answering questions about the way neurons establish connections or the relationships between connectivity and morphological features. Last, SynCoPa is easily extendable to include functional data provided, for example, by any of the morphologically-detailed simulators available nowadays, such as Neuron and Arbor, for providing a deep insight into the circuits features prior to simulating it, in particular any analysis where it is important to combine morphology, network topology, and physiology.
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Affiliation(s)
- Sergio E Galindo
- Ciencias de la Computación, Arquitectura de Computado, Lenguajes y Sistemas Informáticos y Estadística e Investigación Operativa, Esc. Tec. Sup. de Ingeniería Informática, Rey Juan Carlos University, Madrid, Spain
| | - Pablo Toharia
- DATSI, ETSIINF, Universidad Politécnica de Madrid, Madrid, Spain.,Center for Computational Simulation, Universidad Politécnica de Madrid, Madrid, Spain
| | - Oscar D Robles
- Ciencias de la Computación, Arquitectura de Computado, Lenguajes y Sistemas Informáticos y Estadística e Investigación Operativa, Esc. Tec. Sup. de Ingeniería Informática, Rey Juan Carlos University, Madrid, Spain.,Center for Computational Simulation, Universidad Politécnica de Madrid, Madrid, Spain
| | - Luis Pastor
- Ciencias de la Computación, Arquitectura de Computado, Lenguajes y Sistemas Informáticos y Estadística e Investigación Operativa, Esc. Tec. Sup. de Ingeniería Informática, Rey Juan Carlos University, Madrid, Spain.,Center for Computational Simulation, Universidad Politécnica de Madrid, Madrid, Spain
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45
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Liu H, Li B, Zhang M, Dai C, Xi P, Liu Y, Huang Q, He J, Lang Y, Tang R. Unexpected Terrain Induced Changes in Cortical Activity in Bipedal-Walking Rats. BIOLOGY 2021; 11:biology11010036. [PMID: 35053035 PMCID: PMC8773320 DOI: 10.3390/biology11010036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 12/25/2021] [Accepted: 12/26/2021] [Indexed: 11/23/2022]
Abstract
Simple Summary Most studies on cortical dynamics during walking require subjects to walk stably on specific terrain. In fact, humans or other animals are often disturbed by an abrupt change in terrains during walking. To study the impact of unexpected terrain on cortical activity, we analyzed the kinematics and electroencephalography (EEG) dynamics of bipedal-walking rats after encountering unexpected terrain. We found that the gait of rats after encountering the unexpected terrain were significantly different from normal walking. Furthermore, the activities of the left and right primary motor areas (M1), the left and right primary somatosensory areas (S1), and the retrosplenial area (RSP) are coupled to gait cycle phase and varied with the terrain conditions. These findings suggest that unexpected terrains induced changes in gait and cortical activity, and provide novel insights into cortical dynamics during walking. Abstract Humans and other animals can quickly respond to unexpected terrains during walking, but little is known about the cortical dynamics in this process. To study the impact of unexpected terrains on brain activity, we allowed rats with blocked vision to walk on a treadmill in a bipedal posture and then walk on an uneven area at a random position on the treadmill belt. Whole brain EEG signals and hind limb kinematics of bipedal-walking rats were recorded. After encountering unexpected terrain, the θ band power of the bilateral M1, the γ band power of the left S1, and the θ to γ band power of the RSP significantly decreased compared with normal walking. Furthermore, when the rats left uneven terrain, the β band power of the bilateral M1 and the α band power of the right M1 decreased, while the γ band power of the left M1 significantly increased compared with normal walking. Compared with the flat terrain, the θ to low β (3–20 Hz) band power of the bilateral S1 increased after the rats contacted the uneven terrain and then decreased in the single- or double- support phase. These results support the hypothesis that unexpected terrains induced changes in cortical activity.
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Affiliation(s)
- Honghao Liu
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China; (H.L.); (B.L.); (M.Z.); (C.D.); (P.X.); (Y.L.); (Q.H.); (J.H.)
| | - Bo Li
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China; (H.L.); (B.L.); (M.Z.); (C.D.); (P.X.); (Y.L.); (Q.H.); (J.H.)
| | - Minjian Zhang
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China; (H.L.); (B.L.); (M.Z.); (C.D.); (P.X.); (Y.L.); (Q.H.); (J.H.)
| | - Chuankai Dai
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China; (H.L.); (B.L.); (M.Z.); (C.D.); (P.X.); (Y.L.); (Q.H.); (J.H.)
| | - Pengcheng Xi
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China; (H.L.); (B.L.); (M.Z.); (C.D.); (P.X.); (Y.L.); (Q.H.); (J.H.)
| | - Yafei Liu
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China; (H.L.); (B.L.); (M.Z.); (C.D.); (P.X.); (Y.L.); (Q.H.); (J.H.)
| | - Qiang Huang
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China; (H.L.); (B.L.); (M.Z.); (C.D.); (P.X.); (Y.L.); (Q.H.); (J.H.)
- Beijing Innovation Centre for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing 100081, China
| | - Jiping He
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China; (H.L.); (B.L.); (M.Z.); (C.D.); (P.X.); (Y.L.); (Q.H.); (J.H.)
- Beijing Innovation Centre for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing 100081, China
| | - Yiran Lang
- Beijing Innovation Centre for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing 100081, China
- Correspondence: (Y.L.); (R.T.)
| | - Rongyu Tang
- Beijing Innovation Centre for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing 100081, China
- Correspondence: (Y.L.); (R.T.)
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46
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Park W, Kim SP, Eid M. Neural Coding of Vibration Intensity. Front Neurosci 2021; 15:682113. [PMID: 34858124 PMCID: PMC8631937 DOI: 10.3389/fnins.2021.682113] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Accepted: 10/04/2021] [Indexed: 11/13/2022] Open
Abstract
Vibrotactile feedback technology has become widely used in human-computer interaction due to its low cost, wearability, and expressiveness. Although neuroimaging studies have investigated neural processes associated with different types of vibrotactile feedback, encoding vibration intensity in the brain remains largely unknown. The aim of this study is to investigate neural processes associated with vibration intensity using electroencephalography. Twenty-nine healthy participants (aged 18-40 years, nine females) experienced vibrotactile feedback at the distal phalanx of the left index finger with three vibration intensity conditions: no vibration, low-intensity vibration (1.56 g), and high-intensity vibration (2.26 g). The alpha and beta band event-related desynchronization (ERD) as well as P2 and P3 event-related potential components for each of the three vibration intensity conditions are obtained. Results demonstrate that the ERD in the alpha band in the contralateral somatosensory and motor cortex areas is significantly associated with the vibration intensity. The average power spectral density (PSD) of the peak period of the ERD (400-600 ms) is significantly stronger for the high- and low-vibration intensity conditions compared to the no vibration condition. Furthermore, the average PSD of the ERD rebound (700-2,000 ms) is significantly maintained for the high-vibration intensity compared to low-intensity and no vibration conditions. Beta ERD signals the presence of vibration. These findings inform the development of quantitative measurements for vibration intensities based on neural signals.
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Affiliation(s)
- Wanjoo Park
- Engineering Division, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
| | - Sung-Phil Kim
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
| | - Mohamad Eid
- Engineering Division, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
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47
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Aloui N, Planat-Chretien A, Bonnet S. Artefact subspace reconstruction for both EEG and fNIRS co-registred signals. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021; 2021:208-211. [PMID: 34891273 DOI: 10.1109/embc46164.2021.9629641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Combining electroencephalography (EEG) to functional near-infrared spectroscopy (fNIRS) is a promising technique that has gained momentum thanks to their complementarity. While EEG measures the electrical activity of the brain, fNIRS records the variations in cerebral blood flow and related hemoglobin concentrations. However, both modalities are typically contaminated with artefacts. Muscle and eye artefacts, affect the EEG signals, while hemodynamic and oxygenation changes in the extracerebral compartment due to systemic changes (superficial layer) corrupt the fNIRS signals. Moreover, both signals are sensitive to sensor motion artefacts characterized by large amplitude. There are several well-established methods for removing artefacts for both modalities. The objective of this paper is to apply a common approach to denoise both EEG and fNIRS signals. Indeed Artifact Subspace Reconstruction (ASR) method, which is an automatic, online-capable and efficient method for deleting transient or large-amplitude EEG artefacts, can be a good alternative to also denoise fNIRS signals. In this paper, we first propose, a new more comprehensive formulation of ASR. Then, we study the effectiveness of the method in denoising both the EEG and fNIRS signals.
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48
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Ha J, Park S, Im CH, Kim L. Classification of Gamers Using Multiple Physiological Signals: Distinguishing Features of Internet Gaming Disorder. Front Psychol 2021; 12:714333. [PMID: 34630223 PMCID: PMC8498337 DOI: 10.3389/fpsyg.2021.714333] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 08/26/2021] [Indexed: 11/13/2022] Open
Abstract
The proliferating and excessive use of internet games has caused various comorbid diseases, such as game addiction, which is now a major social problem. Recently, the American Psychiatry Association classified “Internet gaming disorder (IGD)” as an addiction/mental disorder. Although many studies have been conducted on the diagnosis, treatment, and prevention of IGD, screening studies for IGD are still scarce. In this study, we classified gamers using multiple physiological signals to contribute to the treatment and prevention of IGD. Participating gamers were divided into three groups based on Young’s Internet Addiction Test score and average game time as follows: Group A, those who rarely play games; Group B, those who enjoy and play games regularly; and Group C, those classified as having IGD. In our game-related cue-based experiment, we obtained self-reported craving scores and multiple physiological data such as electrooculogram (EOG), photoplethysmogram (PPG), and electroencephalogram (EEG) from the users while they watched neutral (natural scenery) or stimulating (gameplay) videos. By analysis of covariance (ANCOVA), 13 physiological features (vertical saccadic movement from EOG, standard deviation of N-N intervals, and PNN50 from PPG, and many EEG spectral power indicators) were determined to be significant to classify the three groups. The classification was performed using a 2-layers feedforward neural network. The fusion of three physiological signals showed the best result compared to other cases (combination of EOG and PPG or EEG only). The accuracy was 0.90 and F-1 scores were 0.93 (Group A), 0.89 (Group B), and 0.88 (Group C). However, the subjective self-reported scores did not show a significant difference among the three groups by ANCOVA analysis. The results indicate that the fusion of physiological signals can be an effective method to objectively classify gamers.
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Affiliation(s)
- Jihyeon Ha
- Center for Bionics, Korea Institute of Science and Technology, Seoul, South Korea.,Department of Biomedical Engineering, Hanyang University, Seoul, South Korea
| | - Sangin Park
- Center for Bionics, Korea Institute of Science and Technology, Seoul, South Korea
| | - Chang-Hwan Im
- Department of Biomedical Engineering, Hanyang University, Seoul, South Korea
| | - Laehyun Kim
- Center for Bionics, Korea Institute of Science and Technology, Seoul, South Korea.,Department of HY-KIST Bio-Convergence, Hanyang University, Seoul, South Korea
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49
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McFerren A, Riddle J, Walker C, Buse JB, Frohlich F. Causal role of frontal-midline theta in cognitive effort: a pilot study. J Neurophysiol 2021; 126:1221-1233. [PMID: 34469696 PMCID: PMC8560423 DOI: 10.1152/jn.00068.2021] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 08/25/2021] [Accepted: 08/25/2021] [Indexed: 11/22/2022] Open
Abstract
Frontal-midline theta (FMT) oscillations are increased in amplitude during cognitive control tasks. Since these tasks often conflate cognitive control and cognitive effort, it remains unknown if FMT amplitude maps onto cognitive control or effort. To address this gap, we utilized the glucose facilitation effect to manipulate cognitive effort without changing cognitive control demands. We performed a single-blind, crossover human study in which we provided participants with a glucose drink (control session: volume-matched water) to reduce cognitive effort and improve performance on a visuospatial working memory task. Following glucose consumption, participants performed the working memory task at multiple time points of a 3-h window to sample across the rise and fall of blood glucose. Using high-density electroencephalography (EEG), we calculated FMT amplitude during the delay period of the working memory task. Source localization analysis revealed that FMT oscillations originated from bilateral prefrontal cortex. We found that glucose increased working memory accuracy during the high working memory load condition but decreased FMT amplitude. The decrease in FMT amplitude coincided with both peak blood glucose elevation and peak performance enhancement for glucose relative to water. Therefore, the positive association between glucose consumption and task performance provided causal evidence that the amplitude of FMT oscillations may correspond to cognitive effort, rather than cognitive control. Due to the COVID-19 pandemic, data collection was terminated prematurely; the preliminary nature of these findings due to small sample size should be contextualized by rigorous experimental design and use of a novel causal perturbation to dissociate cognitive effort and cognitive control.NEW & NOTEWORTHY We investigated whether frontal-midline theta (FMT) oscillations tracked with cognitive control or cognitive effort by simultaneous manipulation of cognitive control demands in a working memory task and causal perturbation of cognitive effort using glucose consumption. Facilitation of performance from glucose consumption corresponded with decreased FMT amplitude, which provided preliminary causal evidence for a relationship between FMT amplitude with cognitive effort.
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Affiliation(s)
- Amber McFerren
- Department of Psychiatry, University of North Carolina, Chapel Hill, North Carolina
- Carolina Center for Neurostimulation, University of North Carolina, Chapel Hill, North Carolina
| | - Justin Riddle
- Department of Psychiatry, University of North Carolina, Chapel Hill, North Carolina
- Carolina Center for Neurostimulation, University of North Carolina, Chapel Hill, North Carolina
| | - Christopher Walker
- Department of Psychiatry, University of North Carolina, Chapel Hill, North Carolina
- Carolina Center for Neurostimulation, University of North Carolina, Chapel Hill, North Carolina
| | - John B Buse
- Division of Endocrinology and Metabolism, University of North Carolina School of Medicine, Chapel Hill, North Carolina
| | - Flavio Frohlich
- Department of Psychiatry, University of North Carolina, Chapel Hill, North Carolina
- Carolina Center for Neurostimulation, University of North Carolina, Chapel Hill, North Carolina
- Department of Neurology, University of North Carolina, Chapel Hill, North Carolina
- Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, North Carolina
- Department of Biomedical Engineering, University of North Carolina, Chapel Hill, North Carolina
- Neuroscience Center, University of North Carolina, Chapel Hill, North Carolina
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50
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Koller-Schlaud K, Querbach J, Behr J, Ströhle A, Rentzsch J. Test-Retest Reliability of Frontal and Parietal Alpha Asymmetry during Presentation of Emotional Face Stimuli in Healthy Subjects. Neuropsychobiology 2021; 79:428-436. [PMID: 32182618 DOI: 10.1159/000505783] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2019] [Accepted: 01/05/2020] [Indexed: 11/19/2022]
Abstract
Resting-state and event-related frontal alpha asymmetry have been suggested as potential neurobiological biomarkers for depression and other psychiatric conditions. To be used as such, sufficient test-retest reliability needs to be demonstrated. However, test-retest reliability is underinvestigated for event-related alpha asymmetry. The objective of this study was to examine both short-term within-session and long-term between-session reliability of stimulus-related medial and lateral frontal as well as parietal alpha EEG asymmetry in healthy subjects during a simple emotional face processing task. Twenty-three healthy adults participated in two sessions with a test-retest interval of about 1 week. Reliability was estimated with Pearson's correlation coefficient and paired t test. Results revealed moderate to high within-session reliability of stimulus-related alpha asymmetry for all electrode sites and both conditions. Alpha asymmetry mean values did not change significantly within sessions. Between-session reliability was fair for frontomedial and moderate for frontolateral stimulus-related asymmetry. Exploratory exclusion of subjects with unstable between-session self-rating scores of emotional state and empathy toward stimuli resulted in some higher reliability values. Our results indicate that stimulus-related alpha asymmetry may serve as a useful electrophysiological tool given its adequate within-session reliability. However, long-term stability of stimulus-related frontal alpha asymmetry over 1 week was comparatively low and varied depending on electrode position. Influencing state factors during EEG recording, such as current mood or stimulus engagement, should be considered in future study designs and analyses. Further, we recommend to analyze alpha asymmetry from both frontomedial and frontolateral sites.
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Affiliation(s)
- Kristin Koller-Schlaud
- Department of Psychiatry and Psychotherapy Campus Mitte, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.,Department of Psychiatry, Psychotherapy, and Psychosomatics, Brandenburg Medical School Theodor Fontane, Neuruppin, Germany
| | - Julia Querbach
- Department of Psychiatry and Psychotherapy Campus Mitte, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Joachim Behr
- Department of Psychiatry and Psychotherapy Campus Mitte, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.,Department of Psychiatry, Psychotherapy, and Psychosomatics, Brandenburg Medical School Theodor Fontane, Neuruppin, Germany.,Faculty of Health Science Brandenburg, Joint Faculty of the University of Potsdam, Brandenburg University of Technology Cottbus-Senftenberg and Brandenburg Medical School Theodor Fontane, Potsdam, Germany
| | - Andreas Ströhle
- Department of Psychiatry and Psychotherapy Campus Mitte, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Johannes Rentzsch
- Department of Psychiatry and Psychotherapy Campus Mitte, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany, .,Department of Psychiatry, Psychotherapy, and Psychosomatics, Brandenburg Medical School Theodor Fontane, Neuruppin, Germany,
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