Localizing Movement-Related Primary Sensorimotor Cortices with Multi-Band EEG Frequency Changes and Functional MRI

Kuo, Chia‐Hua; Luu, Phan; Morgan, Kyle; Dow, Mark W.; Davey, Colin; Song, Jasmine; Malony, Allen D.; Tucker, Don M.

doi:10.1371/journal.pone.0112103

Cited by 24 publications

(20 citation statements)

References 62 publications

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“…In human cortex, Kuo et al ( 2014 ) showed that beta-band (14–30 Hz) ERD (power decreases) was significant during finger movement, expressed in all participants and consistently localized to the primary motor cortex (hand region) and in well-accordance with fMRI localizations. As described for the mu rhythm, beta ERD also occur during both movement execution (Ofori et al, 2015 ) and observation (Zarka et al, 2014 ; Cevallos et al, 2015 ; Babiloni et al, 2016 ).…”

Section: Beta Oscillationmentioning

confidence: 75%

Brain Oscillations in Sport: Toward EEG Biomarkers of Performance

et al. 2016

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Brain dynamics is at the basis of top performance accomplishment in sports. The search for neural biomarkers of performance remains a challenge in movement science and sport psychology. The non-invasive nature of high-density electroencephalography (EEG) recording has made it a most promising avenue for providing quantitative feedback to practitioners and coaches. Here, we review the current relevance of the main types of EEG oscillations in order to trace a perspective for future practical applications of EEG and event-related potentials (ERP) in sport. In this context, the hypotheses of unified brain rhythms and continuity between wake and sleep states should provide a functional template for EEG biomarkers in sport. The oscillations in the thalamo-cortical and hippocampal circuitry including the physiology of the place cells and the grid cells provide a frame of reference for the analysis of delta, theta, beta, alpha (incl.mu), and gamma oscillations recorded in the space field of human performance. Based on recent neuronal models facilitating the distinction between the different dynamic regimes (selective gating and binding) in these different oscillations we suggest an integrated approach articulating together the classical biomechanical factors (3D movements and EMG) and the high-density EEG and ERP signals to allow finer mathematical analysis to optimize sport performance, such as microstates, coherency/directionality analysis and neural generators.

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Section: Beta Oscillationmentioning

confidence: 75%

Brain Oscillations in Sport: Toward EEG Biomarkers of Performance

et al. 2016

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“…Individual head models were obtained from each participant using the photogrammetry system and solved using GeoSource 3.0 software. The dense array of Geodesic sensor locations obtained from each participant enables high-resolution finite difference method (FDM) conformal MRI atlas head models (Li, Papademetris, & Tucker, 2016), and demonstrably high source localization accuracy (Kuo et al, 2014;Song et al, 2015). Here, the inverse problem was solved using the inverse mapping constraint LORETA with a regularization α = 3.…”

Section: Eeg Recording and Processingmentioning

confidence: 99%

Disentangling the Independent Contributions of Visual and Conceptual Features to the Spatiotemporal Dynamics of Scene Categorization

Greene

Hansen

2020

Preprint

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Human scene categorization is characterized by its remarkable speed. While many visual and conceptual features have been linked to this ability, significant correlations exist between feature spaces, impeding our ability to determine their relative contributions to scene categorization. Here, we employed a whitening transformation to decorrelate a variety of visual and conceptual features and assess the time course of their unique contributions to scene categorization. Participants (both sexes) viewed 2,250 full-color scene images drawn from 30 different scene categories while having their brain activity measured through 256-channel EEG. We examined the variance explained at each electrode and time point of visual event-related potential (vERP) data from nine different whitened encoding models. These ranged from low-level features obtained from filter outputs to high-level conceptual features requiring human annotation. The amount of category information in the vERPs was assessed through multivariate decoding methods. Behavioral similarity measures were obtained in separate crowdsourced experiments. We found that all nine models together contributed 78% of the variance of human scene similarity assessments and was within the noise ceiling of the vERP data. Low-level models explained earlier vERP variability (88 ms post-image onset), while high-level models explained later variance (169 ms). Critically, only high-level models shared vERP variability with behavior. Taken together, these results suggest that scene categorization is primarily a high-level process, but reliant on previously extracted low-level features. Significance StatementIn a single fixation, we glean enough information to describe a general scene category. Many types of features are associated with scene categories, ranging from low-level properties such as colors and contours, to high-level properties such as objects and attributes. Because these properties are correlated, it is difficult to understand each property's unique contributions to scene categorization. This work uses a whitening transformation to remove the correlations between features and examines the extent to which each feature contributes to visual eventrelated potentials (vERPs) over time. We found that low-level visual features contributed first, but were not correlated with categorization behavior. High-level features followed 80 ms later, providing key insights into how the brain makes sense of a complex visual world.

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“…Additionally, advances in EEG source localization (Michel et al, 2004) and in paired fMRI-EEG localization studies (Cottereau, Ales, & Norcia, 2014; Kuo et al, 2014) will be helpful in supplying converging evidence with the more spatially-specific fMRI literature. Lastly, to reconcile the findings presented here, as well as to account for the discrepancies found in the current fMRI and EEG literature, and overcome under specific predictions, an updated internal attention model is needed.…”

Section: Discussionmentioning

confidence: 99%

Intraparietal regions play a material general role in working memory: Evidence supporting an internal attentional role

2015

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Determining the role of intraparietal sulcus (IPS) regions in working memory (WM) remains a topic of considerable interest and lack of clarity. One group of hypotheses, the internal attention view, proposes that the IPS plays a material general role in maintaining information in WM. An alternative viewpoint, the pure storage account, proposes that the IPS in each hemisphere maintains material specific (e.g., left – phonological; right – visuospatial) information. Yet, adjudication between competing theoretical perspectives is complicated by divergent findings from different methodologies and their use of different paradigms, perhaps most notably between functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). For example, fMRI studies typically use full field stimulus presentations and report bilateral IPS activation, whereas EEG studies direct attention to a single hemifield and report a contralateral bias in both hemispheres. Here, we addressed this question by applying a regions-of-interest fMRI approach to elucidate IPS contributions to WM. Importantly, we manipulated stimulus type (verbal, visuospatial) and the cued hemifield to assess the degree to which IPS activations reflect stimulus specific or stimulus general processing consistent with the pure storage or internal attention hypotheses. These data revealed significant contralateral bias along regions IPS0-5 regardless of stimulus type. Also present was a weaker stimulus-based bias apparent in stronger left lateralized activations for verbal stimuli and stronger right lateralized activations for visuospatial stimuli. However, there was no consistent stimulus-based lateralization of activity. Thus, despite the observation of stimulus-based modulation of spatial lateralization this pattern was bilateral. As such, although it is quantitatively underspecified, our results are overall more consistent with an internal attention view that the IPS plays a material general role in refreshing the contents of WM.

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Localizing Movement-Related Primary Sensorimotor Cortices with Multi-Band EEG Frequency Changes and Functional MRI

Cited by 24 publications

References 62 publications

Brain Oscillations in Sport: Toward EEG Biomarkers of Performance

Brain Oscillations in Sport: Toward EEG Biomarkers of Performance

Disentangling the Independent Contributions of Visual and Conceptual Features to the Spatiotemporal Dynamics of Scene Categorization

Intraparietal regions play a material general role in working memory: Evidence supporting an internal attentional role

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