Eye movement‐related brain potentials during assisted navigation in real‐world environments

Wunderlich, Anna; Gramann, Klaus

doi:10.1111/ejn.15095

Cited by 34 publications

(35 citation statements)

References 61 publications

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“…Then, data segments containing artifacts (e.g., motion or EEG instrumental artifacts) were automatically rejected by using the automatic continuous rejection (i.e., pop_rejcont()) function of EEGLAB. Parameters used for pop_rejcont() function included: the channel range [1:64]; epochs length of 0.5 s; epoch overlap of 0.25 s; frequency limits to consider for thresholding Hz ; four contiguous epochs necessary to label a region as artifactual with high-frequency data (spectrum over 10 dB); the spectrum was computed within the function; Hamming was used as taper before fast Fourier Transformation (FFT) [71], [75], [76]. The selected segments containing artifacts were rejected from the data and produced a clean signal u.…”

Section: ) Eeg Data Filtering and Artifact Removalmentioning

confidence: 99%

Improving Outcome Prediction for Traumatic Brain Injury From Imbalanced Datasets Using RUSBoosted Trees on Electroencephalography Spectral Power

Noor¹,

Ibrahim²,

Lah³

et al. 2021

IEEE Access

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Reliable prediction of traumatic brain injury (TBI) outcomes based on machine learning (ML) that is derived from quantitative electroencephalography (EEG) features has renewed interest in recent years. Nevertheless, the approach has suffered from imbalanced datasets. Hence, to get a reliable predictive model for predicting outcomes, specifically in a high proportion of moderate TBI with good outcomes, could be challenging. This work proposes an improved outcome predictive model that combines the absolute power spectral density (PSD) as input features for training random under-sampling boosting decision trees (RUSBoosted Trees) as a classifier. Resting-state, eyes-closed EEG data were obtained from 27 moderate TBI patients with follow-up visits. Patient outcome at 4-10 weeks to 12-month was dichotomized based on the Glasgow Outcome Scale as poor (GOS score ≤ 4) and good outcomes (GOS score = 5). The predictive values of absolute PSD from five frequency bands: δ (0.5-4Hz), θ (4-7Hz), α (7-13Hz), β (13-30Hz) and γ (30-100Hz) were evaluated to identify the most informative predictors for reliable prediction outcomes. RUSBoosted Trees performed best at discriminating patients into two outcomes categories (G-Mean = 92.95%, TP rate =100%, TN rate = 86.4%) of absolute PSD in δ and γ bands, which was excellent compared to the other state-of-the-art methods. The highest area under the curve (AUC) of absolute PSD in δ (AUC δ = 0.97) and γ (AUC γ = 0.95) revealed their predictive values as robust prognostic markers for prediction outcomes. The RUSBoosted Trees presents a promising result in prognosis prediction of highly imbalanced data, making it an accessible prediction tool for clinical decision-making, unlike the black-box approaches.

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Section: ) Eeg Data Filtering and Artifact Removalmentioning

confidence: 99%

Improving Outcome Prediction for Traumatic Brain Injury From Imbalanced Datasets Using RUSBoosted Trees on Electroencephalography Spectral Power

Noor¹,

Ibrahim²,

Lah³

et al. 2021

IEEE Access

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“…This has already been proven possible in golfing and shooting studies (Kerick et al, 2004; Reinecke et al, 2011) and can likely be applied to adaptive sport studies that require minimal environmental set‐up such as table tennis. In this regard, advantages in device mobility and data processing tools seem to increase degrees of freedom without reducing the quality of assessed data (Wunderlich & Gramann, 2020). The concept of ‘affordances’ further suggests that the inherent ‘meaning’ of things perceived by an individual may shape the possibilities for potential actions and experiences (Gibson, 1979).…”

Section: Discussionmentioning

confidence: 99%

“…As such, it is important to consider whether our attempts to measure cortical activity accurately and precisely has driven us towards a greater abstraction, isolation and focusing of measurements, inevitably contributing to an unintended reduction in EV (Ladouce et al, 2017). In addition to their beneficial effects in detecting movement-related artefacts, an implementation of additional information sources like motion sensors (Mustile et al, 2021) or eye tracking technology (Wunderlich & Gramann, 2020) in EEG research in sports and exercise may also allow for investigations of movement-associated brain activity in less restricted and therefore more variable and ecologically valid environments. The element of 'stimulus' received the second highest average rating.…”

Section: Key Finding 1: Potential To Conduct Experiments In Real-worl...mentioning

confidence: 99%

Ecological validity in exercise neuroscience research: A systematic investigation

Chang

Büchel

Reinecke

et al. 2022

Eur J of Neuroscience

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The contribution of cortical processes to adaptive motor behaviour is of great interest in the field of exercise neuroscience. Next to established criteria of objectivity, reliability and validity, ecological validity refers to the concerns of whether measurements and behaviour in research settings are representative of the real world. Because exercise neuroscience investigations using mobile electroencephalography are oftentimes conducted in laboratory settings under controlled environments, methodological approaches may interfere with the idea of ecological validity. This review utilizes an original ecological validity tool to assess the degree of ecological validity in current exercise neuroscience research. A systematic literature search was conducted to identify articles investigating cortical dynamics during goal-directed sports movement. To assess ecological validity, five elements (environment, stimulus, response, body and mind) were assessed on a continuum of artificiality-naturality and simplicity-complexity. Forty-seven studies were included in the present review. Results indicate lowest average ratings for the element of environment. The elements stimulus, body and mind had mediocre ratings, and the element of response had the highest overall ratings. In terms of the type of sport, studies that assessed closed-skill indoor sports had the highest ratings, whereas closed-skill outdoor sports had the lowest overall rating. Our findings identify specific elements that are lacking in ecological validity and areas of improvement in current exercise neuroscience literature. Future studies may potentially increase ecological validity by moving from reductionist, artificial environments towards complex, natural environments and incorporating realworld sport elements such as adaptive responses and competition.

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“…Creating a distributedyet integrated and contextualized-neurosomatic system capable of ensuring internal dynamical regularities in response to the ever changing internal and external environments. Importantly, recent work focusing on cardiovascular and respiratory systems (Chen et al, 2020;Kandasamy et al, 2016;Mai et al, 2018;Park et al, 2018;Richter & Tallon-Baudry, 2016;Varga & Heck, 2017), as well as mobile brain/body imaging (MoBI) (Djebbara et al, 2019;Shamay-Tsoory & Mendelsohn, 2019;Wunderlich & Gramann, 2020), has provided relevant evidence supporting the 4E perspective (Parada & Rossi, 2020). Yet, the holobiont and its microbial dynamics have not been understood from the 4E perspective (Palacios-Garcia & Parada, 2019).…”

Section: The Holobiont Mindmentioning

confidence: 99%

The holobiont mind: A bridge between 4E-cognition and the microbiome

Palacios-García¹,

Fj²

2021

Preprint

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All life on earth is intrinsically linked. At the very foundation of everyevolutionary interaction are microorganisms; integral components in thecomposition of both organisms and ecosystems. This perspectivechallenges the traditional conception of monogenetic biologicalindividuals, suggesting living beings are actually composite multi-speciescomplexes; holobionts. In the present article, we introduce the conceptof the holobiont mind; a biogenic conception of cognition. Wefurthermore expand on the idea of the mind as the emerging product ofmulti-genomic morphology of a composite agent, in ever changinginteraction with its ecological niche. We briefly review recent evidence onthe Brain-Gut-Microbiome axis and the Microbiome of the BuiltEnvironment in order to provide a bridge between the Holobiont Mindand the 4E approach to Cognition, two complementary lines of evidencethat have not been linked before, opening novel venues for research withdirect impact on health and disease.

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Eye movement‐related brain potentials during assisted navigation in real‐world environments

Abstract: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 34 publications

References 61 publications

Improving Outcome Prediction for Traumatic Brain Injury From Imbalanced Datasets Using RUSBoosted Trees on Electroencephalography Spectral Power

Improving Outcome Prediction for Traumatic Brain Injury From Imbalanced Datasets Using RUSBoosted Trees on Electroencephalography Spectral Power

Ecological validity in exercise neuroscience research: A systematic investigation

The holobiont mind: A bridge between 4E-cognition and the microbiome

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