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Wang S, Djebbara Z, Sanches de Oliveira G, Gramann K. Human brain dynamics dissociate early perceptual and late motor-related stages of affordance processing. Eur J Neurosci 2024; 60:4639-4660. [PMID: 39034404 DOI: 10.1111/ejn.16461] [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: 09/13/2023] [Revised: 04/24/2024] [Accepted: 06/21/2024] [Indexed: 07/23/2024]
Abstract
Affordances, the opportunities for action offered by the environment to an agent, are vital for meaningful behaviour and exist in every interaction with the environment. There is an ongoing debate in the field about whether the perception of affordances is an automated process. Some studies suggest that affordance perception is an automated process that is independent from the visual context and bodily interaction with the environment, whereas others argue that it is modulated by the visual and motor context in which affordances are perceived. The present paper aims to resolve this debate by examining affordance automaticity from the perspective of sensorimotor time windows. To investigate the impact of different forms of bodily interactions with an environment, that is, the movement context (physical vs. joystick movement), we replicated a previous study on affordance perception in which participants actively moved through differently wide doors in an immersive 3D virtual environment. In the present study, we displayed the same environment on a 2D screen with participants moving through doors of different widths using the keys on a standard keyboard. We compared components of the event-related potential (ERP) from the continuously recorded electroencephalogram (EEG) that were previously reported to be related to affordance perception of architectural transitions (passable and impassable doors). Comparing early sensory and later motor-related ERPs, our study replicated ERPs reflecting early affordance perception but found differences in later motor-related components. These results indicate a shift from automated perception of affordances during early sensorimotor time windows to movement context dependence of affordance perception at later stages, suggesting that affordance perception is a dynamic and flexible process that changes over sensorimotor stages.
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Affiliation(s)
- Sheng Wang
- Biological Psychology and Neuroergonomics, Technische Universität Berlin, Berlin, Germany
| | - Zakaria Djebbara
- Biological Psychology and Neuroergonomics, Technische Universität Berlin, Berlin, Germany
- Department of Architecture, Design and Media Technology, Aalborg University, Aalborg, Denmark
| | | | - Klaus Gramann
- Biological Psychology and Neuroergonomics, Technische Universität Berlin, Berlin, Germany
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2
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Randau M, Bach B, Reinholt N, Pernet C, Oranje B, Rasmussen BS, Arnfred S. Transdiagnostic psychopathology in the light of robust single-trial event-related potentials. Psychophysiology 2024; 61:e14562. [PMID: 38459627 DOI: 10.1111/psyp.14562] [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: 09/25/2023] [Revised: 01/25/2024] [Accepted: 02/24/2024] [Indexed: 03/10/2024]
Abstract
Recent evidence indicates that event-related potentials (ERPs) as measured on the electroencephalogram (EEG) are more closely related to transdiagnostic, dimensional measures of psychopathology (TDP) than to diagnostic categories. A comprehensive examination of correlations between well-studied ERPs and measures of TDP is called for. In this study, we recruited 50 patients with emotional disorders undergoing 14 weeks of transdiagnostic group psychotherapy as well as 37 healthy comparison subjects (HC) matched in age and sex. HCs were assessed once and patients three times throughout treatment (N = 172 data sets) with a battery of well-studied ERPs and psychopathology measures consistent with the TDP framework The Hierarchical Taxonomy of Psychopathology (HiTOP). ERPs were quantified using robust single-trial analysis (RSTA) methods and TDP correlations with linear regression models as implemented in the EEGLAB toolbox LIMO EEG. We found correlations at several levels of the HiTOP hierarchy. Among these, a reduced P3b was associated with the general p-factor. A reduced error-related negativity correlated strongly with worse symptomatology across the Internalizing spectrum. Increases in the correct-related negativity correlated with symptoms loading unto the Distress subfactor in the HiTOP. The Flanker N2 was related to specific symptoms of Intrusive Cognitions and Traumatic Re-experiencing and the mismatch negativity to maladaptive personality traits at the lowest levels of the HiTOP hierarchy. Our study highlights the advantages of RSTA methods and of using validated TDP constructs within a consistent framework. Future studies could utilize machine learning methods to predict TDP from a set of ERP features at the subject level.
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Affiliation(s)
- Martin Randau
- Research Unit for Psychotherapy & Psychopathology, Mental Health Service West, Copenhagen University Hospital - Psychiatry Region Zealand, Slagelse, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Bo Bach
- Psychiatric Research Unit, Copenhagen University Hospital - Psychiatry Region Zealand, Slagelse, Denmark
| | - Nina Reinholt
- Psychiatric Research Unit, Copenhagen University Hospital - Psychiatry Region Zealand, Slagelse, Denmark
| | - Cyril Pernet
- Neurobiology Research Unit, Copenhagen University Hospital, Copenhagen, Denmark
| | - Bob Oranje
- Center for Neuropsychiatric Schizophrenia Research (CNSR), Copenhagen University Hospital, Copenhagen, Denmark
| | - Belinda S Rasmussen
- Psychiatric Research Unit, Copenhagen University Hospital - Psychiatry Region Zealand, Slagelse, Denmark
| | - Sidse Arnfred
- Research Unit for Psychotherapy & Psychopathology, Mental Health Service West, Copenhagen University Hospital - Psychiatry Region Zealand, Slagelse, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Psychiatric Research Unit, Copenhagen University Hospital - Psychiatry Region Zealand, Slagelse, Denmark
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Klug M, Berg T, Gramann K. Optimizing EEG ICA decomposition with data cleaning in stationary and mobile experiments. Sci Rep 2024; 14:14119. [PMID: 38898069 PMCID: PMC11187149 DOI: 10.1038/s41598-024-64919-3] [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: 12/08/2023] [Accepted: 06/14/2024] [Indexed: 06/21/2024] Open
Abstract
Electroencephalography (EEG) studies increasingly utilize more mobile experimental protocols, leading to more and stronger artifacts in the recorded data. Independent Component Analysis (ICA) is commonly used to remove these artifacts. It is standard practice to remove artifactual samples before ICA to improve the decomposition, for example using automatic tools such as the sample rejection option of the AMICA algorithm. However, the effects of movement intensity and the strength of automatic sample rejection on ICA decomposition have not been systematically evaluated. We conducted AMICA decompositions on eight open-access datasets with varying degrees of motion intensity using varying sample rejection criteria. We evaluated decomposition quality using mutual information of the components, the proportion of brain, muscle, and 'other' components, residual variance, and an exemplary signal-to-noise ratio. Within individual studies, increased movement significantly decreased decomposition quality, though this effect was not found across different studies. Cleaning strength significantly improved the decomposition, but the effect was smaller than expected. Our results suggest that the AMICA algorithm is robust even with limited data cleaning. Moderate cleaning, such as 5 to 10 iterations of the AMICA sample rejection, is likely to improve the decomposition of most datasets, regardless of motion intensity.
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Affiliation(s)
- M Klug
- Young Investigator Group Intuitive XR, Neuroadaptive Human-Computer Interaction, Institute of Medical Technology, BTU Cottbus-Senftenberg, Cottbus, Germany.
- Biopsychology and Neuroergonomics, Institute of Psychology and Ergonomics, TU Berlin, Berlin, Germany.
| | - T Berg
- Biopsychology and Neuroergonomics, Institute of Psychology and Ergonomics, TU Berlin, Berlin, Germany
| | - K Gramann
- Biopsychology and Neuroergonomics, Institute of Psychology and Ergonomics, TU Berlin, Berlin, Germany
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Lo CW, Meyer L. Chunk boundaries disrupt dependency processing in an AG: Reconciling incremental processing and discrete sampling. PLoS One 2024; 19:e0305333. [PMID: 38889141 PMCID: PMC11185458 DOI: 10.1371/journal.pone.0305333] [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: 03/18/2024] [Accepted: 05/29/2024] [Indexed: 06/20/2024] Open
Abstract
Language is rooted in our ability to compose: We link words together, fusing their meanings. Links are not limited to neighboring words but often span intervening words. The ability to process these non-adjacent dependencies (NADs) conflicts with the brain's sampling of speech: We consume speech in chunks that are limited in time, containing only a limited number of words. It is unknown how we link words together that belong to separate chunks. Here, we report that we cannot-at least not so well. In our electroencephalography (EEG) study, 37 human listeners learned chunks and dependencies from an artificial grammar (AG) composed of syllables. Multi-syllable chunks to be learned were equal-sized, allowing us to employ a frequency-tagging approach. On top of chunks, syllable streams contained NADs that were either confined to a single chunk or crossed a chunk boundary. Frequency analyses of the EEG revealed a spectral peak at the chunk rate, showing that participants learned the chunks. NADs that cross boundaries were associated with smaller electrophysiological responses than within-chunk NADs. This shows that NADs are processed readily when they are confined to the same chunk, but not as well when crossing a chunk boundary. Our findings help to reconcile the classical notion that language is processed incrementally with recent evidence for discrete perceptual sampling of speech. This has implications for language acquisition and processing as well as for the general view of syntax in human language.
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Affiliation(s)
- Chia-Wen Lo
- Research Group Language Cycles, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Lars Meyer
- Research Group Language Cycles, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- University Clinic Münster, Münster, Germany
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Hu X, Meng Z, He Q. Choice overload interferes with early processing and necessitates late compensation: Evidence from electroencephalogram. Eur J Neurosci 2024; 59:2995-3008. [PMID: 38575329 DOI: 10.1111/ejn.16322] [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: 12/18/2023] [Revised: 02/28/2024] [Accepted: 03/07/2024] [Indexed: 04/06/2024]
Abstract
Having a multitude of choices can be advantageous, yet an abundance of options can be detrimental to the decision-making process. Based on existing research, the present study combined electroencephalogram and self-reported methodologies to investigate the neural mechanisms underlying the phenomenon of choice overload. Behavioural data suggested that an increase in the number of options led to negative evaluations and avoidance of choice tendencies, even in the absence of time pressure. Event-related potential results indicated that the large choice set interfered with the early visual process, as evidenced by the small P1 amplitude, and failed to attract more attentional resources in the early stage, as evidenced by the small amplitude of P2 and N2. However, the LPC amplitude was increased in the late stage, suggesting greater investment of attentional resources and higher emotional arousal. Multivariate pattern analysis revealed that the difference between small and large choice set began at around 120 ms, and the early and late stages were characterised by opposite activation patterns. This suggested that too many options interfered with early processing and necessitate continued processing at a later stage. In summary, both behavioural and event-related potential (ERP) results confirm the choice overload effect, and it was observed that individuals tend to subjectively exaggerate the choice overload effect.
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Affiliation(s)
- Xinye Hu
- Faculty of Psychology, MOE Key Laboratory of Cognition and Personality, Southwest University, Chongqing, China
| | - Zong Meng
- Faculty of Psychology, Beijing Normal University, Beijing, China
| | - Qinghua He
- Faculty of Psychology, MOE Key Laboratory of Cognition and Personality, Southwest University, Chongqing, China
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Southwest University Branch, Collaborative Innovation Center of Assessment toward Basic Education Quality, Beijing Normal University, Chongqing, China
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6
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Randau M, Reinholt N, Pernet C, Oranje B, Rasmussen BS, Arnfred S. Robust single-trial event-related potentials differentiate between distress and fear disorders. Psychophysiology 2024; 61:e14500. [PMID: 38073133 DOI: 10.1111/psyp.14500] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 10/24/2023] [Accepted: 11/21/2023] [Indexed: 04/17/2024]
Abstract
Recent evidence indicates that measures of brain functioning as indexed by event-related potentials (ERPs) on the electroencephalogram align more closely to transdiagnostic measures of psychopathology than to categorical taxonomies. The Hierarchical Taxonomy of Psychopathology (HiTOP) is a transdiagnostic, dimensional framework aiming to solve issues of comorbidity, symptom heterogeneity, and arbitrary diagnostic boundaries. Based on shared features, the emotional disorders are allocated into subfactors Distress and Fear. Evidence indicates that disorders that are close in the HiTOP hierarchy share etiology, symptom profiles, and treatment outcomes. However, further studies testing the biological underpinnings of the HiTOP are called for. In this study, we assessed differences between Distress and Fear in a range of well-studied ERP components. In total, 50 patients with emotional disorders were divided into two groups (Distress, N = 25; Fear, N = 25) according to HiTOP criteria and compared against 37 healthy comparison (HC) subjects. Addressing issues in traditional ERP preprocessing and analysis methods, we applied robust single-trial analysis as implemented in the EEGLAB toolbox LIMO EEG. Several ERP components were found to differ between the groups. Surprisingly, we found no difference between Fear and HC for any of the ERPs. This suggests that some well-established results from the literature, e.g., increased error-related negativity in OCD, are not a shared neurobiological correlate of the Fear subfactor. Conversely, for Distress, we found reductions compared to Fear and HC in several ERP components across paradigms. Future studies could utilize HiTOP-validated psychopathology measures to more precisely define subfactor groups.
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Affiliation(s)
- Martin Randau
- Research Unit for Psychotherapy & Psychopathology, Mental Health Service West, Copenhagen University Hospital - Psychiatry Region Zealand, Slagelse, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Nina Reinholt
- Psychiatric Research Unit, Copenhagen University Hospital - Psychiatry Region Zealand, Slagelse, Denmark
| | - Cyril Pernet
- Neurobiology Research Unit, Copenhagen University Hospital, Copenhagen, Denmark
| | - Bob Oranje
- Center for Neuropsychiatric Schizophrenia Research (CNSR), Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS), Copenhagen University Hospital, Copenhagen, Denmark
| | - Belinda S Rasmussen
- Psychiatric Research Unit, Copenhagen University Hospital - Psychiatry Region Zealand, Slagelse, Denmark
| | - Sidse Arnfred
- Research Unit for Psychotherapy & Psychopathology, Mental Health Service West, Copenhagen University Hospital - Psychiatry Region Zealand, Slagelse, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Psychiatric Research Unit, Copenhagen University Hospital - Psychiatry Region Zealand, Slagelse, Denmark
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Mirdamadi JL, Ting LH, Borich MR. Distinct Cortical Correlates of Perception and Motor Function in Balance Control. J Neurosci 2024; 44:e1520232024. [PMID: 38413231 PMCID: PMC11007305 DOI: 10.1523/jneurosci.1520-23.2024] [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: 08/08/2023] [Revised: 02/07/2024] [Accepted: 02/14/2024] [Indexed: 02/29/2024] Open
Abstract
Fluctuations in brain activity alter how we perceive our body and generate movements but have not been investigated in functional whole-body behaviors. During reactive balance, we recently showed that evoked brain activity is associated with the balance ability in young individuals. Furthermore, in PD, impaired whole-body motion perception in reactive balance is associated with impaired balance. Here, we investigated the brain activity during the whole-body motion perception in reactive balance in young adults (9 female, 10 male). We hypothesized that both ongoing and evoked cortical activity influences the efficiency of information processing for successful perception and movement during whole-body behaviors. We characterized two cortical signals using electroencephalography localized to the SMA: (1) the "N1," a perturbation-evoked potential that decreases in amplitude with expectancy and is larger in individuals with lower balance function, and (2) preperturbation β power, a transient rhythm that favors maintenance of the current sensorimotor state and is inversely associated with tactile perception. In a two-alternative forced choice task, participants judged whether pairs of backward support surface perturbations during standing were in the "same" or "different" direction. As expected, lower whole-body perception was associated with lower balance ability. Within a perturbation pair, N1 attenuation was larger on correctly perceived trials and associated with better balance, but not perception. In contrast, preperturbation β power was higher on incorrectly perceived trials and associated with poorer perception, but not balance. Together, ongoing and evoked cortical activity have unique roles in information processing that give rise to distinct associations with perceptual and balance ability.
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Affiliation(s)
- Jasmine L Mirdamadi
- Division of Physical Therapy, Department of Rehabilitation Medicine, Emory University School of Medicine, Atlanta, Georgia 30322
| | - Lena H Ting
- Division of Physical Therapy, Department of Rehabilitation Medicine, Emory University School of Medicine, Atlanta, Georgia 30322
- The Wallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, Georgia 30322
| | - Michael R Borich
- Division of Physical Therapy, Department of Rehabilitation Medicine, Emory University School of Medicine, Atlanta, Georgia 30322
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Boebinger S, Payne A, Martino G, Kerr K, Mirdamadi J, McKay JL, Borich M, Ting L. Precise cortical contributions to sensorimotor feedback control during reactive balance. PLoS Comput Biol 2024; 20:e1011562. [PMID: 38630803 PMCID: PMC11057980 DOI: 10.1371/journal.pcbi.1011562] [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: 10/02/2023] [Revised: 04/29/2024] [Accepted: 03/25/2024] [Indexed: 04/19/2024] Open
Abstract
The role of the cortex in shaping automatic whole-body motor behaviors such as walking and balance is poorly understood. Gait and balance are typically mediated through subcortical circuits, with the cortex becoming engaged as needed on an individual basis by task difficulty and complexity. However, we lack a mechanistic understanding of how increased cortical contribution to whole-body movements shapes motor output. Here we use reactive balance recovery as a paradigm to identify relationships between hierarchical control mechanisms and their engagement across balance tasks of increasing difficulty in young adults. We hypothesize that parallel sensorimotor feedback loops engaging subcortical and cortical circuits contribute to balance-correcting muscle activity, and that the involvement of cortical circuits increases with balance challenge. We decomposed balance-correcting muscle activity based on hypothesized subcortically- and cortically-mediated feedback components driven by similar sensory information, but with different loop delays. The initial balance-correcting muscle activity was engaged at all levels of balance difficulty. Its onset latency was consistent with subcortical sensorimotor loops observed in the lower limb. An even later, presumed, cortically-mediated burst of muscle activity became additionally engaged as balance task difficulty increased, at latencies consistent with longer transcortical sensorimotor loops. We further demonstrate that evoked cortical activity in central midline areas measured using electroencephalography (EEG) can be explained by a similar sensory transformation as muscle activity but at a delay consistent with its role in a transcortical loop driving later cortical contributions to balance-correcting muscle activity. These results demonstrate that a neuromechanical model of muscle activity can be used to infer cortical contributions to muscle activity without recording brain activity. Our model may provide a useful framework for evaluating changes in cortical contributions to balance that are associated with falls in older adults and in neurological disorders such as Parkinson's disease.
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Affiliation(s)
- Scott Boebinger
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, Georgia, United States of America
| | - Aiden Payne
- Department of Psychology, Florida State University, Tallahassee, Florida, United States of America
| | - Giovanni Martino
- Department of Biomedical Sciences, University of Padova, Padua, Italy
| | - Kennedy Kerr
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, Georgia, United States of America
| | - Jasmine Mirdamadi
- Division of Physical Therapy, Department of Rehabilitation Medicine, Emory University, Atlanta, Georgia, United States of America
| | - J. Lucas McKay
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, Georgia, United States of America
- Departments of Biomedical Informatics and Neurology, Emory University, Atlanta, Georgia, United States of America
| | - Michael Borich
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, Georgia, United States of America
- Division of Physical Therapy, Department of Rehabilitation Medicine, Emory University, Atlanta, Georgia, United States of America
| | - Lena Ting
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, Georgia, United States of America
- Division of Physical Therapy, Department of Rehabilitation Medicine, Emory University, Atlanta, Georgia, United States of America
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Hilton C, Kapaj A, Fabrikant SI. Fixation-related potentials during mobile map assisted navigation in the real world: The effect of landmark visualization style. Atten Percept Psychophys 2024:10.3758/s13414-024-02864-z. [PMID: 38468023 DOI: 10.3758/s13414-024-02864-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/13/2024] [Indexed: 03/13/2024]
Abstract
An often-proposed enhancement for mobile maps to aid assisted navigation is the presentation of landmark information, yet understanding of the manner in which they should be displayed is limited. In this study, we investigated whether the visualization of landmarks as 3D map symbols with either an abstract or realistic style influenced the subsequent processing of those landmarks during route navigation. We utilized a real-world mobile electroencephalography approach to this question by combining several tools developed to overcome the challenges typically encountered in real-world neuroscience research. We coregistered eye-movement and EEG recordings from 45 participants as they navigated through a real-world environment using a mobile map. Analyses of fixation event-related potentials revealed that the amplitude of the parietal P200 component was enhanced when participants fixated landmarks in the real world that were visualized on the mobile map in a realistic style, and that frontal P200 latencies were prolonged for landmarks depicted in either a realistic or abstract style compared with features of the environment that were not presented on the map, but only for the male participants. In contrast, we did not observe any significant effects of landmark visualization style on visual P1-N1 peaks or the parietal late positive component. Overall, the findings indicate that the cognitive matching process between landmarks seen in the environment and those previously seen on a map is facilitated by more realistic map display, while low-level perceptual processing of landmarks and recall of associated information are unaffected by map visualization style.
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Affiliation(s)
- Christopher Hilton
- Geographic Information Visualization & Analysis (GIVA), Department of Geography, University of Zurich- Irchel, Winterthurerstr. 190, CH-8057, Zurich, Switzerland.
- Institute of Psychology and Ergonomics, Technische Universität Berlin, Berlin, Germany.
| | - Armand Kapaj
- Geographic Information Visualization & Analysis (GIVA), Department of Geography, University of Zurich- Irchel, Winterthurerstr. 190, CH-8057, Zurich, Switzerland
| | - Sara Irina Fabrikant
- Geographic Information Visualization & Analysis (GIVA), Department of Geography, University of Zurich- Irchel, Winterthurerstr. 190, CH-8057, Zurich, Switzerland
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Yun S, Jo SH, Jeon HJ, Choo B, Seok JH, Shin H, Kim IY, Choi SW, Koo BH. Neurophysiological insights into impaired mentalization in borderline personality disorder an electroencephalography study. Front Psychiatry 2024; 14:1293347. [PMID: 38268560 PMCID: PMC10806161 DOI: 10.3389/fpsyt.2023.1293347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 12/22/2023] [Indexed: 01/26/2024] Open
Abstract
Introduction Borderline personality disorder (BPD) is characterized by interpersonal and emotional instabilities, recurring suicidal tendencies, and feelings of emptiness. Childhood adverse event is reported in 70%-80% of cases involving BPD. Furthermore, the deficiency in mentalization capacity plays a significant role in emotion dysregulation and social interaction problems within individuals with BPD. This study explored the relationship among childhood adverse experiences, mentalization capacity, and neurophysiological activity in patients with BPD. Methods Resting-state electroencephalography was used to identify the neural correlates associated with childhood adversity and mentalization deficits. The participants included 45 patients with BPD and 15 healthy controls. Results The BPD group exhibited reduced alpha activity during eyes-closed rest, indicating heightened arousal even during relaxation. Correlations were found between the power spectral density (PSD) and mentalization capacity in the delta and theta ranges, suggesting an association between PSD and emotional awareness and expression. Gamma activity negatively correlated with psychic equivalence, implying a blurring of the boundaries between internal mental experiences and the external world. Conclusion These findings offer insights into the pathophysiology of BPD, provide potential diagnostic markers, and suggest personalized treatment approaches based on mentalization traits.
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Affiliation(s)
- Seokho Yun
- Department of Psychiatry, Yeungnam University Hospital, Yeungnam University College of Medicine, Daegu, Republic of Korea
| | - So-Hye Jo
- Department of Psychiatry, Yeungnam University Hospital, Yeungnam University College of Medicine, Daegu, Republic of Korea
| | - Hye-Jin Jeon
- Department of Psychiatry, Yeungnam University Hospital, Yeungnam University College of Medicine, Daegu, Republic of Korea
| | - Bokyung Choo
- Industry-Academic Cooperations, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Jeong-Ho Seok
- Institute of Behavioral Science in Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Hyunkyung Shin
- Institute of Behavioral Science in Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - In-Young Kim
- Institute of Behavioral Science in Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Sun-Woo Choi
- Institute of Behavioral Science in Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Bon-Hoon Koo
- Department of Psychiatry, Yeungnam University Hospital, Yeungnam University College of Medicine, Daegu, Republic of Korea
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Steele AG, Faraji AH, Contreras-Vidal JL. Electrospinography for non-invasively recording spinal sensorimotor networks in humans. J Neural Eng 2024; 20:066043. [PMID: 38118169 DOI: 10.1088/1741-2552/ad1782] [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: 06/12/2023] [Accepted: 12/20/2023] [Indexed: 12/22/2023]
Abstract
Objective. Currently, few non-invasive measures exist for directly measuring spinal sensorimotor networks. Electrospinography (ESG) is one non-invasive method but is primarily used to measure evoked responses or for monitoring the spinal cord during surgery. Our objectives were to evaluate the feasibility of ESG to measure spinal sensorimotor networks by determining spatiotemporal and functional connectivity changes during single-joint movements at the spinal and cortical levels.Approach. We synchronously recorded electroencephalography (EEG), electromyography, and ESG in ten neurologically intact adults while performing one of three lower-limb tasks (no movement, plantar-flexion and knee flexion) in the prone position. A multi-pronged approach was applied for removing artifacts usingH∞filtering, artifact subspace reconstruction and independent component (IC) analysis. Next, data were segmented by task and ICs of EEG were clustered across participants. Within-participant analysis of ICs and ESG data was conducted, and ESG was characterized in the time and frequency domains. Generalized partial directed coherence analysis was performed within ICs and between ICs and ESG data by participant and task.Results.K-means clustering resulted in five clusters of ICs at Brodmann areas (BAs) 9, BA 8, BA 39, BA 4, and BA 22. Areas associated with motor planning, working memory, visual processing, movement, and attention, respectively. Time-frequency analysis of ESG data found localized changes during movement execution when compared to no movement. Lastly, we found bi-directional changes in functional connectivity (p < 0.05, adjusted for multiple comparisons) within IC's and between IC's and ESG sensors during movement when compared to the no movement condition.Significance. To our knowledge this is the first report using high density ESG for characterizing single joint lower limb movements. Our findings provide support that ESG contains information about efferent and afferent signaling in neurologically intact adults and suggests that we can utilize ESG to directly study the spinal cord.
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Affiliation(s)
- Alexander G Steele
- Laboratory for Noninvasive Brain-Machine Interfaces, IUCRC BRAIN, University of Houston, N308 Engineering Building I, Houston, TX 77204, United States of America
- Center for Neuroregeneration, Department of Neurosurgery, Houston Methodist Research Institute, Houston, TX 77030, United States of America
| | - Amir H Faraji
- Center for Neuroregeneration, Department of Neurosurgery, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- Center for Translational Neural Prosthetics and Interfaces, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- Clinical Innovations Laboratory, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- Department of Neurological Surgery, Houston Methodist Hospital, Houston, TX 77030, United States of America
| | - Jose L Contreras-Vidal
- Laboratory for Noninvasive Brain-Machine Interfaces, IUCRC BRAIN, University of Houston, N308 Engineering Building I, Houston, TX 77204, United States of America
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Zhang G, Garrett DR, Luck SJ. Optimal Filters for ERP Research I: A General Approach for Selecting Filter Settings. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.25.542359. [PMID: 37292873 PMCID: PMC10245912 DOI: 10.1101/2023.05.25.542359] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Filtering plays an essential role in event-related potential (ERP) research, but filter settings are usually chosen on the basis of historical precedent, lab lore, or informal analyses. This reflects, in part, the lack of a well-reasoned, easily implemented method for identifying the optimal filter settings for a given type of ERP data. To fill this gap, we developed an approach that involves finding the filter settings that maximize the signal-to-noise ratio for a specific amplitude score (or minimizes the noise for a latency score) while minimizing waveform distortion. The signal is estimated by obtaining the amplitude score from the grand average ERP waveform (usually a difference waveform). The noise is estimated using the standardized measurement error of the single-subject scores. Waveform distortion is estimated by passing noise-free simulated data through the filters. This approach allows researchers to determine the most appropriate filter settings for their specific scoring methods, experimental designs, subject populations, recording setups, and scientific questions. We have provided a set of tools in ERPLAB Toolbox to make it easy for researchers to implement this approach with their own data.
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Affiliation(s)
- Guanghui Zhang
- Center for Mind & Brain, University of California-Davis, Davis, CA, USA
| | - David R Garrett
- Center for Mind & Brain, University of California-Davis, Davis, CA, USA
| | - Steven J Luck
- Center for Mind & Brain, University of California-Davis, Davis, CA, USA
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13
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Ody E, Kircher T, Straube B, He Y. Pre-movement event-related potentials and multivariate pattern of EEG encode action outcome prediction. Hum Brain Mapp 2023; 44:6198-6213. [PMID: 37792296 PMCID: PMC10619393 DOI: 10.1002/hbm.26506] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 09/04/2023] [Accepted: 09/17/2023] [Indexed: 10/05/2023] Open
Abstract
Self-initiated movements are accompanied by an efference copy, a motor command sent from motor regions to the sensory cortices, containing a prediction of the movement's sensory outcome. Previous studies have proposed pre-motor event-related potentials (ERPs), including the readiness potential (RP) and its lateralized sub-component (LRP), as potential neural markers of action feedback prediction. However, it is not known how specific these neural markers are for voluntary (active) movements as compared to involuntary (passive) movements, which produce much of the same sensory feedback (tactile, proprioceptive) but are not accompanied by an efference copy. The goal of the current study was to investigate how active and passive movements are distinguishable from premotor electroencephalography (EEG), and to examine if this change of neural activity differs when participants engage in tasks that differ in their expectation of sensory outcomes. Participants made active (self-initiated) or passive (finger moved by device) finger movements that led to either visual or auditory stimuli (100 ms delay), or to no immediate contingency effects (control). We investigated the time window before the movement onset by measuring pre-movement ERPs time-locked to the button press. For RP, we observed an interaction between task and movement. This was driven by movement differences in the visual and auditory but not the control conditions. LRP conversely only showed a main effect of movement. We then used multivariate pattern analysis to decode movements (active vs. passive). The results revealed ramping decoding for all tasks from around -800 ms onwards up to an accuracy of approximately 85% at the movement. Importantly, similar to RP, we observed lower decoding accuracies for the control condition than the visual and auditory conditions, but only shortly (from -200 ms) before the button press. We also decoded visual vs. auditory conditions. Here, task is decodable for both active and passive conditions, but the active condition showed increased decoding shortly before the button press. Taken together, our results provide robust evidence that pre-movement EEG activity may represent action-feedback prediction in which information about the subsequent sensory outcome is encoded.
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Affiliation(s)
- Edward Ody
- Department of Psychiatry and PsychotherapyUniversity of MarburgMarburgGermany
| | - Tilo Kircher
- Department of Psychiatry and PsychotherapyUniversity of MarburgMarburgGermany
| | - Benjamin Straube
- Department of Psychiatry and PsychotherapyUniversity of MarburgMarburgGermany
| | - Yifei He
- Department of Psychiatry and PsychotherapyUniversity of MarburgMarburgGermany
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14
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Wang P, Limanowski J. Phasic modulation of beta power at movement-related frequencies during visuomotor conflict. J Neurophysiol 2023; 130:1367-1372. [PMID: 37877188 DOI: 10.1152/jn.00338.2023] [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: 09/06/2023] [Revised: 10/02/2023] [Accepted: 10/17/2023] [Indexed: 10/26/2023] Open
Abstract
Rhythmic cortical activity is thought to underlie many cognitive functions including the flexible weighting of sensory information depending on the current behavioral context. Here, we tested for potential oscillatory alignment and power modulation at behaviorally relevant frequencies in magnetoencephalography (MEG) data acquired during a virtual reality-based, rhythmic hand-target phase matching task. The task contained conditions differing in terms of visuomotor incongruence and whether or not behavior (grasping movements) had to be adapted to keep vision aligned with the target. We tested for potential oscillatory alignment with movement frequencies and cross-frequency coupling with oscillations in the alpha, beta, and gamma bands. Our results revealed local peaks at 1 Hz power, corresponding to the frequency at which hand movements alternated between open and close; thus, potentially indicating an "entrainment" of neural oscillations at key movement frequencies. We found 1 Hz power was selectively enhanced when participants needed to align incongruent vision with the target. Moreover, the phase of the "movement-entrained" 1 Hz oscillations coupled significantly with the momentary amplitude of beta band oscillations-again, this coupling was selectively enhanced when incongruent vision was task relevant. We propose that this reflected a top-down mechanism, most likely related to selective attention and rhythmic sensory sampling. Thus, phasic low-frequency (beta) power suppression likely indicated a variable (attentional) sampling of visual movement feedback; i.e., related to increased sensitivity for visually matching alternating hand movements to a phasic target at ecologically important time points, rather than continually during the grasping cycle.NEW & NOTEWORTHY Our results reveal an increased spectral power at movement frequencies in a rhythmic hand-target phase matching task under visuomotor conflict; this effect was strongest when incongruent visual movement feedback was required to guide action. Moreover, the phase of these slow frequencies coupled with the momentary power beta oscillations; again, this coupling was selectively strengthened when incongruent vision was task relevant.
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Affiliation(s)
- Peng Wang
- Institute of Psychology, University of Greifswald, Greifswald, Germany
| | - Jakub Limanowski
- Institute of Psychology, University of Greifswald, Greifswald, Germany
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15
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Windolf C, Yu H, Paulk AC, Meszéna D, Muñoz W, Boussard J, Hardstone R, Caprara I, Jamali M, Kfir Y, Xu D, Chung JE, Sellers KK, Ye Z, Shaker J, Lebedeva A, Raghavan M, Trautmann E, Melin M, Couto J, Garcia S, Coughlin B, Horváth C, Fiáth R, Ulbert I, Movshon JA, Shadlen MN, Churchland MM, Churchland AK, Steinmetz NA, Chang EF, Schweitzer JS, Williams ZM, Cash SS, Paninski L, Varol E. DREDge: robust motion correction for high-density extracellular recordings across species. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.24.563768. [PMID: 37961359 PMCID: PMC10634799 DOI: 10.1101/2023.10.24.563768] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
High-density microelectrode arrays (MEAs) have opened new possibilities for systems neuroscience in human and non-human animals, but brain tissue motion relative to the array poses a challenge for downstream analyses, particularly in human recordings. We introduce DREDge (Decentralized Registration of Electrophysiology Data), a robust algorithm which is well suited for the registration of noisy, nonstationary extracellular electrophysiology recordings. In addition to estimating motion from spikes in the action potential (AP) frequency band, DREDge enables automated tracking of motion at high temporal resolution in the local field potential (LFP) frequency band. In human intraoperative recordings, which often feature fast (period <1s) motion, DREDge correction in the LFP band enabled reliable recovery of evoked potentials, and significantly reduced single-unit spike shape variability and spike sorting error. Applying DREDge to recordings made during deep probe insertions in nonhuman primates demonstrated the possibility of tracking probe motion of centimeters across several brain regions while simultaneously mapping single unit electrophysiological features. DREDge reliably delivered improved motion correction in acute mouse recordings, especially in those made with an recent ultra-high density probe. We also implemented a procedure for applying DREDge to recordings made across tens of days in chronic implantations in mice, reliably yielding stable motion tracking despite changes in neural activity across experimental sessions. Together, these advances enable automated, scalable registration of electrophysiological data across multiple species, probe types, and drift cases, providing a stable foundation for downstream scientific analyses of these rich datasets.
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Affiliation(s)
- Charlie Windolf
- Department of Statistics, Columbia University
- Zuckerman Institute, Columbia University
| | - Han Yu
- Zuckerman Institute, Columbia University
- Department of Electrical Engineering, Columbia University
| | - Angelique C Paulk
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School
| | - Domokos Meszéna
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
| | - William Muñoz
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School
| | - Julien Boussard
- Department of Statistics, Columbia University
- Zuckerman Institute, Columbia University
| | - Richard Hardstone
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School
| | - Irene Caprara
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School
| | - Mohsen Jamali
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School
| | - Yoav Kfir
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School
| | - Duo Xu
- Weill Institute for Neurosciences, University of California San Francisco
- Department of Neurological Surgery, University of California San Francisco
| | - Jason E Chung
- Department of Neurological Surgery, University of California San Francisco
| | - Kristin K Sellers
- Weill Institute for Neurosciences, University of California San Francisco
- Department of Neurological Surgery, University of California San Francisco
| | - Zhiwen Ye
- Department of Biological Structure, University of Washington
| | - Jordan Shaker
- Department of Biological Structure, University of Washington
| | | | | | - Eric Trautmann
- Department of Neuroscience, Columbia University Medical Center
- Zuckerman Institute, Columbia University
- Grossman Center for the Statistics of Mind, Columbia University
| | - Max Melin
- David Geffen School of Medicine, University of California Los Angeles
| | - João Couto
- David Geffen School of Medicine, University of California Los Angeles
| | - Samuel Garcia
- Centre National de la Recherche Scientifique, Centre de Recherche en Neurosciences de Lyon
| | - Brian Coughlin
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School
| | - Csaba Horváth
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
| | - Richárd Fiáth
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
| | - István Ulbert
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
| | | | - Michael N Shadlen
- Zuckerman Institute, Columbia University
- Howard Hughes Medical Institute
| | | | - Anne K Churchland
- David Geffen School of Medicine, University of California Los Angeles
| | | | - Edward F Chang
- Weill Institute for Neurosciences, University of California San Francisco
- Department of Neurological Surgery, University of California San Francisco
| | - Jeffrey S Schweitzer
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School
| | - Ziv M Williams
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School
| | - Sydney S Cash
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School
| | - Liam Paninski
- Department of Statistics, Columbia University
- Zuckerman Institute, Columbia University
- Department of Neuroscience, Columbia University Medical Center
- Grossman Center for the Statistics of Mind, Columbia University
| | - Erdem Varol
- Department of Statistics, Columbia University
- Zuckerman Institute, Columbia University
- Department of Computer Science & Engineering, New York University
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16
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Cheng B, Lin E, Wunderlich A, Gramann K, Fabrikant SI. Using spontaneous eye blink-related brain activity to investigate cognitive load during mobile map-assisted navigation. Front Neurosci 2023; 17:1024583. [PMID: 36866330 PMCID: PMC9971562 DOI: 10.3389/fnins.2023.1024583] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2022] [Accepted: 01/26/2023] [Indexed: 02/16/2023] Open
Abstract
The continuous assessment of pedestrians' cognitive load during a naturalistic mobile map-assisted navigation task is challenging because of limited experimental control over stimulus presentation, human-map-interactions, and other participant responses. To overcome this challenge, the present study takes advantage of navigators' spontaneous eye blinks during navigation to serve as event markers in continuously recorded electroencephalography (EEG) data to assess cognitive load in a mobile map-assisted navigation task. We examined if and how displaying different numbers of landmarks (3 vs. 5 vs. 7) on mobile maps along a given route would influence navigators' cognitive load during navigation in virtual urban environments. Cognitive load was assessed by the peak amplitudes of the blink-related fronto-central N2 and parieto-occipital P3. Our results show increased parieto-occipital P3 amplitude indicating higher cognitive load in the 7-landmark condition, compared to showing 3 or 5 landmarks. Our prior research already demonstrated that participants acquire more spatial knowledge in the 5- and 7-landmark conditions compared to the 3-landmark condition. Together with the current study, we find that showing 5 landmarks, compared to 3 or 7 landmarks, improved spatial learning without overtaxing cognitive load during navigation in different urban environments. Our findings also indicate a possible cognitive load spillover effect during map-assisted wayfinding whereby cognitive load during map viewing might have affected cognitive load during goal-directed locomotion in the environment or vice versa. Our research demonstrates that users' cognitive load and spatial learning should be considered together when designing the display of future navigation aids and that navigators' eye blinks can serve as useful event makers to parse continuous human brain dynamics reflecting cognitive load in naturalistic settings.
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Affiliation(s)
- Bingjie Cheng
- Department of Geography and Digital Society Initiative, University of Zurich, Zurich, Switzerland,*Correspondence: Bingjie Cheng,
| | - Enru Lin
- Department of Geography and Digital Society Initiative, University of Zurich, Zurich, Switzerland
| | - Anna Wunderlich
- Department of Biopsychology and Neuroergonomics, Technical University of Berlin, Berlin, Germany
| | - Klaus Gramann
- Department of Biopsychology and Neuroergonomics, Technical University of Berlin, Berlin, Germany
| | - Sara I. Fabrikant
- Department of Geography and Digital Society Initiative, University of Zurich, Zurich, Switzerland
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17
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Abstract
Automated preprocessing methods are critically needed to process the large publicly-available EEG databases, but the optimal approach remains unknown because we lack data quality metrics to compare them. Here, we designed a simple yet robust EEG data quality metric assessing the percentage of significant channels between two experimental conditions within a 100 ms post-stimulus time range. Because of volume conduction in EEG, given no noise, most brain-evoked related potentials (ERP) should be visible on every single channel. Using three publicly available collections of EEG data, we showed that, with the exceptions of high-pass filtering and bad channel interpolation, automated data corrections had no effect on or significantly decreased the percentage of significant channels. Referencing and advanced baseline removal methods were significantly detrimental to performance. Rejecting bad data segments or trials could not compensate for the loss in statistical power. Automated Independent Component Analysis rejection of eyes and muscles failed to increase performance reliably. We compared optimized pipelines for preprocessing EEG data maximizing ERP significance using the leading open-source EEG software: EEGLAB, FieldTrip, MNE, and Brainstorm. Only one pipeline performed significantly better than high-pass filtering the data.
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Affiliation(s)
- Arnaud Delorme
- SCCN, INC, UCSD, La Jolla, CA, USA.
- CerCo CNRS, Paul Sabatier University, Toulouse, France.
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18
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Jacobsen NSJ, Blum S, Scanlon JEM, Witt K, Debener S. Mobile electroencephalography captures differences of walking over even and uneven terrain but not of single and dual-task gait. Front Sports Act Living 2022; 4:945341. [PMID: 36275441 PMCID: PMC9582531 DOI: 10.3389/fspor.2022.945341] [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: 05/16/2022] [Accepted: 09/13/2022] [Indexed: 11/09/2022] Open
Abstract
Walking on natural terrain while performing a dual-task, such as typing on a smartphone is a common behavior. Since dual-tasking and terrain change gait characteristics, it is of interest to understand how altered gait is reflected by changes in gait-associated neural signatures. A study was performed with 64-channel electroencephalography (EEG) of healthy volunteers, which was recorded while they walked over uneven and even terrain outdoors with and without performing a concurrent task (self-paced button pressing with both thumbs). Data from n = 19 participants (M = 24 years, 13 females) were analyzed regarding gait-phase related power modulations (GPM) and gait performance (stride time and stride time-variability). GPMs changed significantly with terrain, but not with the task. Descriptively, a greater beta power decrease following right-heel strikes was observed on uneven compared to even terrain. No evidence of an interaction was observed. Beta band power reduction following the initial contact of the right foot was more pronounced on uneven than on even terrain. Stride times were longer on uneven compared to even terrain and during dual- compared to single-task gait, but no significant interaction was observed. Stride time variability increased on uneven terrain compared to even terrain but not during single- compared to dual-tasking. The results reflect that as the terrain difficulty increases, the strides become slower and more irregular, whereas a secondary task slows stride duration only. Mobile EEG captures GPM differences linked to terrain changes, suggesting that the altered gait control demands and associated cortical processes can be identified. This and further studies may help to lay the foundation for protocols assessing the cognitive demand of natural gait on the motor system.
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Affiliation(s)
- Nadine Svenja Josée Jacobsen
- Neuropsychology Lab, Department of Psychology, School of Medicine and Health Sciences, University of Oldenburg, Oldenburg, Germany,*Correspondence: Nadine Svenja Josée Jacobsen
| | - Sarah Blum
- Neuropsychology Lab, Department of Psychology, School of Medicine and Health Sciences, University of Oldenburg, Oldenburg, Germany,Hörzentrum Oldenburg GmbH, Oldenburg, Germany,Cluster of Excellence Hearing4all, Oldenburg, Germany
| | - Joanna Elizabeth Mary Scanlon
- Neuropsychology Lab, Department of Psychology, School of Medicine and Health Sciences, University of Oldenburg, Oldenburg, Germany,Branch for Hearing, Speech and Audio Technology HSA, Fraunhofer Institute for Digital Media Technology IDMT, Oldenburg, Germany
| | - Karsten Witt
- Department of Neurology and Research Center Neurosensory Science, School of Medicine and Health Sciences, University of Oldenburg, Oldenburg, Germany
| | - Stefan Debener
- Neuropsychology Lab, Department of Psychology, School of Medicine and Health Sciences, University of Oldenburg, Oldenburg, Germany,Cluster of Excellence Hearing4all, Oldenburg, Germany
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19
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Gomez-Pilar J, Martínez-Cagigal V, García-Azorín D, Gómez C, Guerrero Á, Hornero R. Headache-related circuits and high frequencies evaluated by EEG, MRI, PET as potential biomarkers to differentiate chronic and episodic migraine: Evidence from a systematic review. J Headache Pain 2022; 23:95. [PMID: 35927625 PMCID: PMC9354370 DOI: 10.1186/s10194-022-01465-1] [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: 06/29/2022] [Accepted: 07/21/2022] [Indexed: 11/25/2022] Open
Abstract
Background The diagnosis of migraine is mainly clinical and self-reported, which makes additional examinations unnecessary in most cases. Migraine can be subtyped into chronic (CM) and episodic (EM). Despite the very high prevalence of migraine, there are no evidence-based guidelines for differentiating between these subtypes other than the number of days of migraine headache per month. Thus, we consider it timely to perform a systematic review to search for physiological evidence from functional activity (as opposed to anatomical structure) for the differentiation between CM and EM, as well as potential functional biomarkers. For this purpose, Web of Science (WoS), Scopus, and PubMed databases were screened. Findings Among the 24 studies included in this review, most of them (22) reported statistically significant differences between the groups of CM and EM. This finding is consistent regardless of brain activity acquisition modality, ictal stage, and recording condition for a wide variety of analyses. That speaks for a supramodal and domain-general differences between CM and EM that goes beyond a differentiation based on the days of migraine per month. Together, the reviewed studies demonstrates that electro- and magneto-physiological brain activity (M/EEG), as well as neurovascular and metabolic recordings from functional magnetic resonance imaging (fMRI) and positron emission tomography (PET), show characteristic patterns that allow to differentiate between CM and EM groups. Conclusions Although a clear brain activity-based biomarker has not yet been identified to distinguish these subtypes of migraine, research is approaching headache specialists to a migraine diagnosis based not only on symptoms and signs reported by patients. Future studies based on M/EEG should pay special attention to the brain activity in medium and fast frequency bands, mainly the beta band. On the other hand, fMRI and PET studies should focus on neural circuits and regions related to pain and emotional processing.
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Affiliation(s)
- Javier Gomez-Pilar
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales Y Nanomedicina (CIBER-BBN), Valladolid, Spain
| | - Víctor Martínez-Cagigal
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales Y Nanomedicina (CIBER-BBN), Valladolid, Spain
| | - David García-Azorín
- Headache Unit, Neurology Department, Hospital Clínico Universitario de Valladolid, Ramón y Cajal 3, 47003, Valladolid, Spain.
| | - Carlos Gómez
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales Y Nanomedicina (CIBER-BBN), Valladolid, Spain
| | - Ángel Guerrero
- Headache Unit, Neurology Department, Hospital Clínico Universitario de Valladolid, Ramón y Cajal 3, 47003, Valladolid, Spain.,Department of Medicine, University of Valladolid, Valladolid, Spain
| | - Roberto Hornero
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales Y Nanomedicina (CIBER-BBN), Valladolid, Spain
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