Keyword search (4,163 papers available)

"Electroencephalography" Keyword-tagged Publications:

Title Authors PubMed ID
1 Sound degradation type differentially affects neural indicators of cognitive workload and speech tracking Gagné N; Greenlaw KM; Coffey EBJ; 40412301
PSYCHOLOGY
2 Phase-Amplitude Coupling of NREM Sleep Oscillations Shows Between-Night Stability and is Related to Overnight Memory Gains Cross N; O' Byrne J; Weiner OM; Giraud J; Perrault AA; Dang-Vu TT; 40214027
PERFORM
3 PreVISE: an efficient virtual reality system for SEEG surgical planning Spiegler P; Abdelsalam H; Hellum O; Hadjinicolaou A; Weil AG; Xiao Y; 39735694
ENCS
4 Metrics for evaluation of automatic epileptogenic zone localization in intracranial electrophysiology Hrtonova V; Nejedly P; Travnicek V; Cimbalnik J; Matouskova B; Pail M; Peter-Derex L; Grova C; Gotman J; Halamek J; Jurak P; Brazdil M; Klimes P; Frauscher B; 39608298
SOH
5 A protocol for trustworthy EEG decoding with neural networks Borra D; Magosso E; Ravanelli M; 39549492
ENCS
6 SpeechBrain-MOABB: An open-source Python library for benchmarking deep neural networks applied to EEG signals Borra D; Paissan F; Ravanelli M; 39265481
ENCS
7 The neurophysiology of closed-loop auditory stimulation in sleep: A magnetoencephalography study Jourde HR; Merlo R; Brooks M; Rowe M; Coffey EBJ; 37675803
CONCORDIA
8 Dynamic networks differentiate the language ability of children with cochlear implants Koirala N; Deroche MLD; Wolfe J; Neumann S; Bien AG; Doan D; Goldbeck M; Muthuraman M; Gracco VL; 37409105
PSYCHOLOGY
9 Class imbalance should not throw you off balance: Choosing the right classifiers and performance metrics for brain decoding with imbalanced data Thölke P; Mantilla-Ramos YJ; Abdelhedi H; Maschke C; Dehgan A; Harel Y; Kemtur A; Mekki Berrada L; Sahraoui M; Young T; Bellemare Pépin A; El Khantour C; Landry M; Pascarella A; Hadid V; Combrisson E; O' Byrne J; Jerbi K; 37385392
IMAGING
10 Neurophysiology, Neuropsychology, and Epilepsy, in 2022: Hills We Have Climbed and Hills Ahead. Neurophysiology in epilepsy Frauscher B; Bénar CG; Engel JJ; Grova C; Jacobs J; Kahane P; Wiebe S; Zjilmans M; Dubeau F; 37119580
PERFORM
11 Electroencephalographic characteristics of children and adolescents with chronic musculoskeletal pain Ocay DD; Teel EF; Luo OD; Savignac C; Mahdid Y; Blain-Moraes S; Ferland CE; 36601627
HKAP
12 Alpha and beta neural oscillations differentially reflect age-related differences in bilateral coordination Shih PC; Steele CJ; Nikulin VV; Gundlach C; Kruse J; Villringer A; Sehm B; 33979705
PSYCHOLOGY
13 Fast oscillations >40 Hz localize the epileptogenic zone: An electrical source imaging study using high-density electroencephalography. Avigdor T, Abdallah C, von Ellenrieder N, Hedrich T, Rubino A, Lo Russo G, Bernhardt B, Nobili L, Grova C, Frauscher B 33450578
PERFORM
14 PASS: A Multimodal Database of Physical Activity and Stress for Mobile Passive Body/ Brain-Computer Interface Research Parent M; Albuquerque I; Tiwari A; Cassani R; Gagnon JF; Lafond D; Tremblay S; Falk TH; 33363449
PERFORM
15 Source imaging of deep-brain activity using the regional spatiotemporal Kalman filter Hamid L; Habboush N; Stern P; Japaridze N; Aydin Ü; Wolters CH; Claussen JC; Heute U; Stephani U; Galka A; Siniatchkin M; 33250282
PERFORM
16 Localization Accuracy of Distributed Inverse Solutions for Electric and Magnetic Source Imaging of Interictal Epileptic Discharges in Patients with Focal Epilepsy. Heers M, Chowdhury RA, Hedrich T, Dubeau F, Hall JA, Lina JM, Grova C, Kobayashi E 25609211
PERFORM
17 Sleep spindles may predict response to cognitive-behavioral therapy for chronic insomnia Dang-Vu TT; Hatch B; Salimi A; Mograss M; Boucetta S; O' Byrne J; Brandewinder M; Berthomier C; Gouin JP; 29157588
PERFORM

 

Title:Dynamic networks differentiate the language ability of children with cochlear implants
Authors:Koirala NDeroche MLDWolfe JNeumann SBien AGDoan DGoldbeck MMuthuraman MGracco VL
Link:https://pubmed.ncbi.nlm.nih.gov/37409105/
DOI:10.3389/fnins.2023.1141886
Publication:Frontiers in neuroscience
Keywords:age of interventioncochlear implantelectrical source imaging (ESI)electroencephalography (EEG)language and reading
PMID:37409105 Category: Date Added:2023-07-06
Dept Affiliation: PSYCHOLOGY

Description:

Background: Cochlear implantation (CI) in prelingually deafened children has been shown to be an effective intervention for developing language and reading skill. However, there is a substantial proportion of the children receiving CI who struggle with language and reading. The current study-one of the first to implement electrical source imaging in CI population was designed to identify the neural underpinnings in two groups of CI children with good and poor language and reading skill.

Methods: Data using high density electroencephalography (EEG) under a resting state condition was obtained from 75 children, 50 with CIs having good (HL) or poor language skills (LL) and 25 normal hearing (NH) children. We identified coherent sources using dynamic imaging of coherent sources (DICS) and their effective connectivity computing time-frequency causality estimation based on temporal partial directed coherence (TPDC) in the two CI groups compared to a cohort of age and gender matched NH children.

Findings: Sources with higher coherence amplitude were observed in three frequency bands (alpha, beta and gamma) for the CI groups when compared to normal hearing children. The two groups of CI children with good (HL) and poor (LL) language ability exhibited not only different cortical and subcortical source profiles but also distinct effective connectivity between them. Additionally, a support vector machine (SVM) algorithm using these sources and their connectivity patterns for each CI group across the three frequency bands was able to predict the language and reading scores with high accuracy.

Interpretation: Increased coherence in the CI groups suggest overall that the oscillatory activity in some brain areas become more strongly coupled compared to the NH group. Moreover, the different sources and their connectivity patterns and their association to language and reading skill in both groups, suggest a compensatory adaptation that either facilitated or impeded language and reading development. The neural differences in the two groups of CI children may reflect potential biomarkers for predicting outcome success in CI children.





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