Keyword search (4,164 papers available)

"Neuroimage" Category Publications:

Title Authors PubMed ID
1 Arcuate fasciculus architecture is associated with individual differences in pre-attentive detection of unpredicted music changes Vaquero L; Ramos-Escobar N; Cucurell D; François C; Putkinen V; Segura E; Huotilainen M; Penhune V; Rodríguez-Fornells A; 33454403
MLNP
2 Cortical gradients of functional connectivity are robust to state-dependent changes following sleep deprivation. Cross N; Paquola C; Pomares FB; Perrault AA; Jegou A; Nguyen A; Aydin U; Bernhardt BC; Grova C; Dang-Vu TT; 33186718
PERFORM
3 The sensation of groove engages motor and reward networks. Matthews TE, Witek MAG, Lund T, Vuust P, Penhune VB 32217163
PSYCHOLOGY
4 What you learn & when you learn it: Impact of early bilingual & music experience on the structural characteristics of auditory-motor pathways Vaquero L; Rousseau PN; Vozian D; Klein D; Penhune V; 32119984
PSYCHOLOGY
5 Investigating microstructural variation in the human hippocampus using non-negative matrix factorization. Patel R, Steele CJ, Chen A, Patel S, Devenyi GA, Germann J, Tardif CL, Chakravarty MM 31715254
PSYCHOLOGY
6 BOLD signal physiology: Models and applications. Gauthier CJ, Fan AP 29544818
IMAGING
7 ERP evidence of adaptive changes in error processing and attentional control during rhythm synchronization learning Padrão G; Penhune V; de Diego-Balaguer R; Marco-Pallares J; Rodriguez-Fornells A; 24956067
PSYCHOLOGY
8 White-matter structural connectivity predicts short-term melody and rhythm learning in non-musicians Vaquero L; Ramos-Escobar N; François C; Penhune V; Rodríguez-Fornells A; 29929006
MLNP
9 Regional cerebellar volumes are related to early musical training and finger tapping performance. Baer LH, Park MT, Bailey JA, Chakravarty MM, Li KZ, Penhune VB 25583606
PSYCHOLOGY
10 Advanced MRI techniques to improve our understanding of experience-induced neuroplasticity. Tardif CL, Gauthier CJ, Steele CJ, Bazin PL, Schäfer A, Schaefer A, Turner R, Villringer A 26318050
PERFORM
11 SPARK: Sparsity-based analysis of reliable k-hubness and overlapping network structure in brain functional connectivity. Lee K, Lina JM, Gotman J, Grova C 27046111
PERFORM
12 L-DOPA reduces model-free control of behavior by attenuating the transfer of value to action. Kroemer NB, Lee Y, Pooseh S, Eppinger B, Goschke T, Smolka MN 30381245
PSYCHOLOGY
13 Tracking the microstructural properties of the main white matter pathways underlying speech processing in simultaneous interpreters Elmer S; Hänggi J; Vaquero L; Cadena GO; François C; Rodríguez-Fornells A; 30831314
PSYCHOLOGY
14 Cortical reactivations during sleep spindles following declarative learning. Jegou A, Schabus M, Gosseries O, Dahmen B, Albouy G, Desseilles M, Sterpenich V, Phillips C, Maquet P, Grova C, Dang-Vu TT 30928690
PERFORM
15 Complex patterns of spatially extended generators of epileptic activity: Comparison of source localization methods cMEM and 4-ExSo-MUSIC on high resolution EEG and MEG data. Chowdhury RA, Merlet I, Birot G, Kobayashi E, Nica A, Biraben A, Wendling F, Lina JM, Albera L, Grova C 27561712
PERFORM
16 Investigation of the confounding effects of vasculature and metabolism on computational anatomy studies. Tardif CL, Steele CJ, Lampe L, Bazin PL, Ragert P, Villringer A, Gauthier CJ 28159689
PERFORM
17 Comparison of the spatial resolution of source imaging techniques in high-density EEG and MEG. Hedrich T, Pellegrino G, Kobayashi E, Lina JM, Grova C 28619655
PERFORM

 

Title:Comparison of the spatial resolution of source imaging techniques in high-density EEG and MEG.
Authors:Hedrich TPellegrino GKobayashi ELina JMGrova C
Link:https://www.ncbi.nlm.nih.gov/pubmed/28619655?dopt=Abstract
DOI:10.1016/j.neuroimage.2017.06.022
Publication:NeuroImage
Keywords:EEGMEGResolution matrixSomatosensorySource imagingSpatial resolution
PMID:28619655 Category:Neuroimage Date Added:2019-04-15
Dept Affiliation: PERFORM
1 Multimodal Functional Imaging Lab, Biomedical Engineering Dpt., McGill University, Montreal, Canada. Electronic address: tanguy.hedrich@mail.mcgill.ca.
2 Multimodal Functional Imaging Lab, Biomedical Engineering Dpt., McGill University, Montreal, Canada; Neurology and Neurosurgery Department, Montreal Neurological Institute (MNI), McGill University, Montreal, Canada; San Camillo Hospital IRCCS, Venice, Italy.
3 Neurology and Neurosurgery Department, Montreal Neurological Institute (MNI), McGill University, Montreal, Canada.
4 Département de Génie Électrique, École de Technologie Supérieure, Canada; Centre de recherches mathémathiques, Université de Montréal, Montreal, Canada; Center for Advanced Research on Sleep Medecine (CEAMS), hôpital du Sacré-Coeur, Montreal, Canada.
5 Multimodal Functional Imaging Lab, Biomedical Engineering Dpt., McGill University, Montreal, Canada; Neurology and Neurosurgery Department, Montreal Neurological Institute (MNI), McGill University, Montreal, Canada; Physics Dpt., PERFORM Centre, Concordia University, Canada; Centre de recherches mathémathiques, Université de Montréal, Montreal, Canada.

Description:

Comparison of the spatial resolution of source imaging techniques in high-density EEG and MEG.

Neuroimage. 2017 08 15;157:531-544

Authors: Hedrich T, Pellegrino G, Kobayashi E, Lina JM, Grova C

Abstract

BACKGROUND: The present study aims at evaluating and comparing electrical and magnetic distributed source imaging methods applied to high-density Electroencephalography (hdEEG) and Magnetoencephalography (MEG) data. We used resolution matrices to characterize spatial resolution properties of Minimum Norm Estimate (MNE), dynamic Statistical Parametric Mapping (dSPM), standardized Low-Resolution Electromagnetic Tomography (sLORETA) and coherent Maximum Entropy on the Mean (cMEM, an entropy-based technique). The resolution matrix provides information of the Point Spread Functions (PSF) and of the Crosstalk functions (CT), this latter being also called source leakage, as it reflects the influence of a source on its neighbors.

METHODS: The spatial resolution of the inverse operators was first evaluated theoretically and then with real data acquired using electrical median nerve stimulation on five healthy participants. We evaluated the Dipole Localization Error (DLE) and the Spatial Dispersion (SD) of each PSF and CT map.

RESULTS: cMEM showed the smallest spatial spread (SD) for both PSF and CT maps, whereas localization errors (DLE) were similar for all methods. Whereas cMEM SD values were lower in MEG compared to hdEEG, the other methods slightly favored hdEEG over MEG. In real data, cMEM provided similar localization error and significantly less spatial spread than other methods for both MEG and hdEEG. Whereas both MEG and hdEEG provided very accurate localizations, all the source imaging methods actually performed better in MEG compared to hdEEG according to all evaluation metrics, probably due to the higher signal-to-noise ratio of the data in MEG.

CONCLUSION: Our overall results show that all investigated methods provide similar localization errors, suggesting very accurate localization for both MEG and hdEEG when similar number of sensors are considered for both modalities. Intrinsic properties of source imaging methods as well as their behavior for well-controlled tasks, suggest an overall better performance of cMEM in regards to spatial resolution and spatial leakage for both hdEEG and MEG. This indicates that cMEM would be a good candidate for studying source localization of focal and extended generators as well as functional connectivity studies.

PMID: 28619655 [PubMed - indexed for MEDLINE]





BookR developed by Sriram Narayanan
for the Concordia University School of Health
Copyright © 2011-2026
Cookie settings
Concordia University