Dementia ConnEEGtome: Towards multicentric harmonization of EEG connectivity in neurodegeneration

Prado, Pável; Birba, Agustina; Cruzat, Josephine; Santamaría-García, Hernando; Parra, Mario A.; Moguilner, Sebastián; Tagliazucchi, Enzo; Ibáñez, Agustín

doi:10.1016/j.ijpsycho.2021.12.008

Cited by 30 publications

(29 citation statements)

References 157 publications

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“…The pipeline is not without its limitations. First, there is currently no correction for the presence of potentially confounding demographic covariates such as age, sex, or years of formal education (Parra et al, 2022). Second, the source-space analysis of functional connectivity is limited, as it does not include directed connectivity metrics (Cassani et al, 2018).…”

Section: Potential Pitfallsmentioning

confidence: 99%

“…Additional sources of variability arise from differing conceptual frameworks (e.g., dissimilar connectivity metrics and methodological procedures) for the quantification of EEG connectivity. These sources of variability are reflected in the fact that different functional connectivity metrics yield different results, even when applied to the same EEG scalp distribution (Prado et al, 2022). The outcome of any analysis is impacted by the choice of artifact removal, filtering, and averaging methods (Alam et al, 2020;Prado-Gutierrez et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…The outcome of any analysis is impacted by the choice of artifact removal, filtering, and averaging methods (Alam et al, 2020;Prado-Gutierrez et al, 2019). Likewise, choice-related methodological biases are reflected in the effect of EEG spatial transformations on functional connectivity analyses at both sensor (Cohen, 2015) and source spaces (Prado et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

“…To help overcome methodological issues in multicentric studies on neurodegeneration, our team developed a pipeline for the harmonization of EEG datasets and the classification of dementia based on hd-EEG connectivity (Prado et al, 2022). The pipeline was purposefully built with several main goals in mind: namely data security and organization, code availability and automatism and flexibility.…”

Section: Introductionmentioning

confidence: 99%

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A pipeline for large-scale assessments of dementia EEG connectivity across multicentric settings

Ballesteros¹,

Prado²,

Ibáñez³

et al. 2023

Preprint

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Multicentric initiatives based on high-density electroencephalography (hd-EEG) are urgently needed for classification and characterization of diseases subtypes in diverse and low-resource settings. These initiatives are, however, not without challenges, with sources of variability arising from differing data acquisition and harmonization methods, multiple preprocessing pipelines, and different theoretical modes and methods to compute source space/scalp functional connectivity. Our team developed a novel pipeline aimed at the harmonization of hd-EEG datasets and dementia classification. This pipeline handles data from recording to machine learning classification based on multi-metric measures of source space connectivity. A user interface is provided for those with limited background in MATLAB. Here, we present our pipeline and detail a comprehensive step-by-step example for prospective analysts reviewing the five main stages of the pipeline: data pre-processing; normalization; source transformation; connectivity metrics and dementia classification. This detailed step-by-step pipeline may improve the assessment of heterogenous, multicentric, and multi-methods approaches to functional connectivity in aging and dementia.

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Section: Potential Pitfallsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A pipeline for large-scale assessments of dementia EEG connectivity across multicentric settings

Ballesteros¹,

Prado²,

Ibáñez³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…A key difference is that for reproducibility efforts, every lab on its own needs to be able to perform the experiment independently and asynchronously. A similar role in the research landscape is played by multicentre studies (e.g., [38]), which also focus on the harmonization of experiment protocols, but with the goal of creating a uniform data set. An alternative approach, which considers real-time interaction between robots and EEG setups at different sites, is teleoperation.…”

Section: State Of the Artmentioning

confidence: 99%

EEG Correlates of Distractions and Hesitations in Human–Robot Interaction: A LabLinking Pilot Study

Richter

Putze

Ivucic

et al. 2023

MTI

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In this paper, we investigate the effect of distractions and hesitations as a scaffolding strategy. Recent research points to the potential beneficial effects of a speaker’s hesitations on the listeners’ comprehension of utterances, although results from studies on this issue indicate that humans do not make strategic use of them. The role of hesitations and their communicative function in human-human interaction is a much-discussed topic in current research. To better understand the underlying cognitive processes, we developed a human–robot interaction (HRI) setup that allows the measurement of the electroencephalogram (EEG) signals of a human participant while interacting with a robot. We thereby address the research question of whether we find effects on single-trial EEG based on the distraction and the corresponding robot’s hesitation scaffolding strategy. To carry out the experiments, we leverage our LabLinking method, which enables interdisciplinary joint research between remote labs. This study could not have been conducted without LabLinking, as the two involved labs needed to combine their individual expertise and equipment to achieve the goal together. The results of our study indicate that the EEG correlates in the distracted condition are different from the baseline condition without distractions. Furthermore, we could differentiate the EEG correlates of distraction with and without a hesitation scaffolding strategy. This proof-of-concept study shows that LabLinking makes it possible to conduct collaborative HRI studies in remote laboratories and lays the first foundation for more in-depth research into robotic scaffolding strategies.

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Multivariate word properties in fluency tasks reveal markers of Alzheimer's dementia

Ferrante,

Migeot,

Birba

et al. 2023

Alzheimer's & Dementia

Self Cite

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INTRODUCTIONVerbal fluency tasks are common in Alzheimer's disease (AD) assessments. Yet, standard valid response counts fail to reveal disease‐specific semantic memory patterns. Here, we leveraged automated word‐property analysis to capture neurocognitive markers of AD vis‐à‐vis behavioral variant frontotemporal dementia (bvFTD).METHODSPatients and healthy controls completed two fluency tasks. We counted valid responses and computed each word's frequency, granularity, neighborhood, length, familiarity, and imageability. These features were used for group‐level discrimination, patient‐level identification, and correlations with executive and neural (magnetic resonanance imaging [MRI], functional MRI [fMRI], electroencephalography [EEG]) patterns.RESULTSValid responses revealed deficits in both disorders. Conversely, frequency, granularity, and neighborhood yielded robust group‐ and subject‐level discrimination only in AD, also predicting executive outcomes. Disease‐specific cortical thickness patterns were predicted by frequency in both disorders. Default‐mode and salience network hypoconnectivity, and EEG beta hypoconnectivity, were predicted by frequency and granularity only in AD.DISCUSSIONWord‐property analysis of fluency can boost AD characterization and diagnosis.Highlights We report novel word‐property analyses of verbal fluency in AD and bvFTD. Standard valid response counts captured deficits and brain patterns in both groups. Specific word properties (e.g., frequency, granularity) were altered only in AD. Such properties predicted cognitive and neural (MRI, fMRI, EEG) patterns in AD. Word‐property analysis of fluency can boost AD characterization and diagnosis.

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Dementia ConnEEGtome: Towards multicentric harmonization of EEG connectivity in neurodegeneration

Cited by 30 publications

References 157 publications

A pipeline for large-scale assessments of dementia EEG connectivity across multicentric settings

A pipeline for large-scale assessments of dementia EEG connectivity across multicentric settings

EEG Correlates of Distractions and Hesitations in Human–Robot Interaction: A LabLinking Pilot Study

Multivariate word properties in fluency tasks reveal markers of Alzheimer's dementia

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