Keyword search (3,676 papers available)


Arcuate fasciculus architecture is associated with individual differences in pre-attentive detection of unpredicted music changes

Author(s): Vaquero L; Ramos-Escobar N; Cucurell D; François C; Putkinen V; Segura E; Huotilainen M; Penhune V; Rodríguez-Fornells A;...

The mismatch negativity (MMN) is an event related brain potential (ERP) elicited by unpredicted sounds presented in a sequence of repeated auditory stimuli. The neural sources of the MMN have been ...

Article GUID: 33454403

Cortical gradients of functional connectivity are robust to state-dependent changes following sleep deprivation.

Author(s): Cross N; Paquola C; Pomares FB; Perrault AA; Jegou A; Nguyen A; Aydin U; Bernhardt BC; Grova C; Dang-Vu TT;...

Sleep deprivation leads to significant impairments in cognitive performance and changes to the interactions between large scale cortical networks, yet the hierarchical organisation of cortical acti...

Article GUID: 33186718

The sensation of groove engages motor and reward networks.

Author(s): Matthews TE, Witek MAG, Lund T, Vuust P, Penhune VB

Neuroimage. 2020 Mar 23;:116768 Authors: Matthews TE, Witek MAG, Lund T, Vuust P, Penhune VB

Article GUID: 32217163

What you learn & when you learn it: Impact of early bilingual & music experience on the structural characteristics of auditory-motor pathways

Author(s): Vaquero L; Rousseau PN; Vozian D; Klein D; Penhune V;

Music and language engage the dorsal auditory pathway, linked by the arcuate fasciculus (AF). Sustained practice in these activities can modify brain structure, depending on length of experience but also age of onset (AoO). To study the impact of early expe...

Article GUID: 32119984

Investigating microstructural variation in the human hippocampus using non-negative matrix factorization.

Author(s): Patel R, Steele CJ, Chen A, Patel S, Devenyi GA, Germann J, Tardif CL, Chakravarty MM

Neuroimage. 2019 Nov 09;:116348 Authors: Patel R, Steele CJ, Chen A, Patel S, Devenyi GA, Germann J, Tardif CL, Chakravarty MM

Article GUID: 31715254

BOLD signal physiology: Models and applications.

Author(s): Gauthier CJ, Fan AP

Neuroimage. 2019 02 15;187:116-127 Authors: Gauthier CJ, Fan AP

Article GUID: 29544818

ERP evidence of adaptive changes in error processing and attentional control during rhythm synchronization learning

Author(s): Padrão G; Penhune V; de Diego-Balaguer R; Marco-Pallares J; Rodriguez-Fornells A;

The ability to detect and use information from errors is essential during the acquisition of new skills. There is now a wealth of evidence about the brain mechanisms involved in error processing. However, the extent to which those mechanisms are engaged dur...

Article GUID: 24956067

White-matter structural connectivity predicts short-term melody and rhythm learning in non-musicians

Author(s): Vaquero L; Ramos-Escobar N; François C; Penhune V; Rodríguez-Fornells A;

Music learning has received increasing attention in the last decades due to the variety of functions and brain plasticity effects involved during its practice. Most previous reports interpreted the differences between music experts and laymen as the result ...

Article GUID: 29929006

Regional cerebellar volumes are related to early musical training and finger tapping performance.

Author(s): Baer LH, Park MT, Bailey JA, Chakravarty MM, Li KZ, Penhune VB

Neuroimage. 2015 Apr 01;109:130-9 Authors: Baer LH, Park MT, Bailey JA, Chakravarty MM, Li KZ, Penhune VB

Article GUID: 25583606

Advanced MRI techniques to improve our understanding of experience-induced neuroplasticity.

Author(s): Tardif CL, Gauthier CJ, Steele CJ, Bazin PL, Schäfer A, Schaefer A, Turner R, Villringer A

Neuroimage. 2016 05 01;131:55-72 Authors: Tardif CL, Gauthier CJ, Steele CJ, Bazin PL, Schäfer A, Schaefer A, Turner R, Villringer A

Article GUID: 26318050

SPARK: Sparsity-based analysis of reliable k-hubness and overlapping network structure in brain functional connectivity.

Author(s): Lee K, Lina JM, Gotman J, Grova C

Neuroimage. 2016 07 01;134:434-449 Authors: Lee K, Lina JM, Gotman J, Grova C

Article GUID: 27046111

L-DOPA reduces model-free control of behavior by attenuating the transfer of value to action.

Author(s): Kroemer NB, Lee Y, Pooseh S, Eppinger B, Goschke T, Smolka MN

Neuroimage. 2019 02 01;186:113-125 Authors: Kroemer NB, Lee Y, Pooseh S, Eppinger B, Goschke T, Smolka MN

Article GUID: 30381245

Tracking the microstructural properties of the main white matter pathways underlying speech processing in simultaneous interpreters

Author(s): Elmer S; Hänggi J; Vaquero L; Cadena GO; François C; Rodríguez-Fornells A;

Due to the high linguistic and cognitive demands placed on real-time language translation, professional simultaneous interpreters (SIs) have previously been proposed to serve as a reasonable model for evaluating experience-dependent brain properties. Howeve...

Article GUID: 30831314

Cortical reactivations during sleep spindles following declarative learning.

Author(s): Jegou A, Schabus M, Gosseries O, Dahmen B, Albouy G, Desseilles M, Sterpenich V, Phillips C, Maquet P, Grova C, Dang-Vu TT

Neuroimage. 2019 Jul 15;195:104-112 Authors: Jegou A, Schabus M, Gosseries O, Dahmen B, Albouy G, Desseilles M, Sterpenich V, Phillips C, Maquet P, Grova C, Dang-Vu TT

Article GUID: 30928690

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.

Author(s): Chowdhury RA, Merlet I, Birot G, Kobayashi E, Nica A, Biraben A, Wendling F, Lina JM, Albera L, Grova C...

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.
Neuroimage. 2016 De...

Article GUID: 27561712

Investigation of the confounding effects of vasculature and metabolism on computational anatomy studies.

Author(s): Tardif CL, Steele CJ, Lampe L, Bazin PL, Ragert P, Villringer A, Gauthier CJ

Neuroimage. 2017 04 01;149:233-243 Authors: Tardif CL, Steele CJ, Lampe L, Bazin PL, Ragert P, Villringer A, Gauthier CJ

Article GUID: 28159689

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

Author(s): Hedrich T, Pellegrino G, Kobayashi E, Lina JM, Grova C

Neuroimage. 2017 08 15;157:531-544 Authors: Hedrich T, Pellegrino G, Kobayashi E, Lina JM, Grova C

Article GUID: 28619655


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
Category:Neuroimage
PMID:28619655
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]