Who's driving? The default mode network in healthy elderly individuals at risk of cognitive decline

González-López, Mauricio; González-Moreira, Eduardo; Areces-González, Ariosky; Paz-Linares, Deirel; Fernández, Thalı́a

doi:10.3389/fneur.2022.1009574

Cited by 4 publications

(2 citation statements)

References 108 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The processing done with our HCP-compatible pipeline and the source spectra with the BC-VARETA Toolbox of EEG data from the CHBM dataset (Valdes-Sosa et al, 2021) The forward model and source spectra obtained by our structural HCP-compatible pipeline and BC-VARETA Toolbox, respectively, from the EEG of 70 subjects from the Cuban Human Brain Mapping project and the MEG of 70 subjects from the Human Connectome Project were used to perform a statistical comparison between the sources of EEG and MEG rhythms (Riaz et al, 2020) Our BC-VARETA Toolbox was used to analyze the EEG source activity and functional connectivity to explore the feasibility of functional connectivity under aggravating conditions for the spatial resolution of EEG source analysis commonly found in clinical settings. This study (González-López et al, 2022) uses EEGs with a limited number of channels (19 channels) to obtain the inverse problem solution. This proves that BC-VARETA Toolbox is feasible and can be used in clinical settings since it involves significantly lower costs than other neuroimaging tools and can be employed using standard 19-leads EEG to assess brain connectivity.…”

Section: Discussionmentioning

confidence: 99%

Multimodal pipeline for HCP-compatible processing and registration of legacy datasets (MRI, MEG, and EEG)

Gonzalez¹,

Paz-Linares²,

Riaz³

et al. 2023

Preprint

View full text Add to dashboard Cite

<p>Extracting cortical features, which are the most relevant at characterizing structure and function for normal or abnormal brain conditions, would greatly benefit from multimodal neuroimage processing following the surface-based style. This style recognizes the natural definition space for such features due to the layered (surface-based) Cortex structural and functional organization. It may therefore be more sensitive and specific than the former volume-based style. The Human Connectome Project (HCP) multimodal pipelines render high-quality surface-based processing for some of the most consistently acquired neuroimaging modalities, with the quality too reliant on their precise acquisition requirements. Relevant international brain initiatives are espoused to develop an HCP-compatible neuroinformatic facility for the quality-ensured processing of international neuroimaging datasets, which may not follow the specific HCP acquisition requirements, also coined as legacy datasets. We appointed some initiatives to introduce multimodal pipelines in two HCP-compatible processing branches. a) Structural: forward- modeling with geometry (sources and head) and Lead Fields defined for legacy MEG, or EEG, in the HCP individual cortical space (Cifti) obtained from legacy MRI. Our pipeline (Ciftify-MEEG) leverages a more diverse neuroinformatic repository than the HCP structural or MEG pipelines. Ciftify-MEEG produces substantial processing illustrated here with EEG examples, incorporating alternative processing paths and corrections based on a quality control loop and upon qualitative and quantitative indicators. b) Functional: identifying spectral topographies and connectomes for the cortical oscillatory activity observed in the MEG or EEG frequency bands. We leverage a novel repository of Bayesian sparse inverse methods that target identifying the topographies and connectomes with actual statistical guarantees, the brain connectivity Variable Resolution Electromagnetic Tomographic Analysis (BC-VARETA). Our pipeline design for BC-VARETA, which we denominate Ciftify-bcVARETA, is integrated into the Ciftify- MEEG outputs and with Bayesian sparse priors structured upon Cifti space information. Ciftify-bcVARETA identification is less biased to forward models and more biased to the observations than the HCP pipeline illustrated here with topographies obtained for MEG and EEG legacy databases.</p>

show abstract

Section: Discussionmentioning

confidence: 99%

Multimodal pipeline for HCP-compatible processing and registration of legacy datasets (MRI, MEG, and EEG)

Gonzalez¹,

Paz-Linares²,

Riaz³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Another CiftiStorm application was the study of spectral source connectivity measures derived from the SSSBL method applied to individuals at risk of cognitive decline (González-López et al, 2022). This study reported meaningful and statistically significant source connectivity changes even when SSSBL was used to obtain inverse solutions from a 10-20 EEG system (19 sensors) commonly found in clinical settings.…”

Section: Comparing Eeg/meg Inverse Solutionsmentioning

confidence: 97%

CiftiStorm pipeline: facilitating reproducible EEG/MEG source connectomics

Areces-Gonzalez,

Paz-Linares,

Riaz

et al. 2024

Front. Neurosci.

Self Cite

View full text Add to dashboard Cite

We present CiftiStorm, an electrophysiological source imaging (ESI) pipeline incorporating recently developed methods to improve forward and inverse solutions. The CiftiStorm pipeline produces Human Connectome Project (HCP) and megconnectome-compliant outputs from dataset inputs with varying degrees of spatial resolution. The input data can range from low-sensor-density electroencephalogram (EEG) or magnetoencephalogram (MEG) recordings without structural magnetic resonance imaging (sMRI) to high-density EEG/MEG recordings with an HCP multimodal sMRI compliant protocol. CiftiStorm introduces a numerical quality control of the lead field and geometrical corrections to the head and source models for forward modeling. For the inverse modeling, we present a Bayesian estimation of the cross-spectrum of sources based on multiple priors. We facilitate ESI in the T1w/FSAverage32k high-resolution space obtained from individual sMRI. We validate this feature by comparing CiftiStorm outputs for EEG and MRI data from the Cuban Human Brain Mapping Project (CHBMP) acquired with technologies a decade before the HCP MEG and MRI standardized dataset.

show abstract

Theta Current Sources Density Changes in Cardiac Surgery Patients Cognitive After Multitasking Training

Tarasova,

Kupriyanova,

Syrova

et al. 2023

Kompleks. probl. serdečno-sosud. zabol.

View full text Add to dashboard Cite

HighlightsWe estimated theta current sources density changes in patients who received cognitive multitasking training in the early postoperative period of cardiac surgery.Patients with cognitive multitasking training had a significantly lower theta current source density (t<–3.89; p<0.002) before surgery compared to baseline. The strongest differences were localized in Brodmann areas 7, 19 and 31 which related to the structures of the parieto-occipital lobes of the brain, cuneus and precuneus. AbstractAim. The effect of cognitive recovery techniques on brain activity remains a significant issue in modern health care. The aim of this study was to estimate theta current sources density changes using standardized low resolution electromagnetic tomography – sLORETA – (standardized low resolution brain electromagnetic tomography) in patients who have received cognitive multitasking training (CMT) in the postoperative period of coronary artery bypass grafting (CABG).Methods. The study included 30 patients aged between 45 and 75 years who underwent routine CABG. Clinical and neurophysiological examinations were carried out 2–3 days before surgery and 11–12 days after CABG. The cognitive training started 3–4 days after CABG and lasted until discharge and consisted of a motor task - a keypress in response to an object appearing on the screen and three consecutive cognitive tasks (counting backwards, verbal fluency and unusual use of an ordinary object).Results. Patients with CMT had lower theta current source density (t<–3.89; p<0.002) before CABG as compared to postoperative data, the most significant differences were noted in parieto-occipital lobes of the brain, cuneus and precuneus (Brodmann areas 7, 19 and 31).Conclusion. The results of our research contribute to a better understanding of the pathogenetic mechanisms underlying postoperative cognitive impairments in cardiac surgery patients.

show abstract

Who's driving? The default mode network in healthy elderly individuals at risk of cognitive decline

Cited by 4 publications

References 108 publications

Multimodal pipeline for HCP-compatible processing and registration of legacy datasets (MRI, MEG, and EEG)

Multimodal pipeline for HCP-compatible processing and registration of legacy datasets (MRI, MEG, and EEG)

CiftiStorm pipeline: facilitating reproducible EEG/MEG source connectomics

Theta Current Sources Density Changes in Cardiac Surgery Patients Cognitive After Multitasking Training

Contact Info

Product

Resources

About