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:Sound degradation type differentially affects neural indicators of cognitive workload and speech tracking
Authors:Gagné NGreenlaw KMCoffey EBJ
Link:https://pubmed.ncbi.nlm.nih.gov/40412301/
DOI:10.1016/j.heares.2025.109303
Publication:Hearing research
Keywords:Alpha bandCognitive workloadElectroencephalographyHearing-in-noiseNeural speech trackingSpeech perceptionTheta band
PMID:40412301 Category: Date Added:2025-05-25
Dept Affiliation: PSYCHOLOGY
1 Department of Psychology, Concordia University, Montréal, Canada; International Laboratory for Brain, Music and Sound Research (BRAMS); The Centre for Research on Brain, Language and Music (CRBLM). Electronic address: nathan.gagne@mail.concordia.ca.
2 Department of Psychology, Concordia University, Montréal, Canada; International Laboratory for Brain, Music and Sound Research (BRAMS); The Centre for Research on Brain, Language and Music (CRBLM).

Description:

Hearing-in-noise (HIN) is a challenging task that is essential to human functioning in social, vocational, and educational contexts. Successful speech perception in noisy settings is thought to rely in part on the brain's ability to enhance neural representations of attended speech. In everyday HIN situations, important features of speech (i.e., pitch, rhythm) may be degraded in addition to being embedded in noise. The impact of these differences in sound quality on experiences of workload and neural representations of speech will be important for informing our knowledge on the cognitive demands imposed by every-day difficult listening situations. We investigated HIN perception in 20 healthy adults using continuous speech that was either clean, spectrally degraded, or temporally degraded. Each sound condition was presented both with and without pink noise. Participants engaged in a selective listening task, in which a short-story was presented with varying sound quality, while EEG data were recorded. Neural correlates of cognitive workload were obtained using power levels of two frequency bands sensitive to task difficulty manipulations: alpha (8 - 12 Hz) and theta (4 - 8 Hz). Acoustic and linguistic features (speech envelope, word onsets, word surprisal) were decoded to reveal the degree to which speech was successfully encoded. Overall, alpha-theta power increased significantly when noise was added across sound conditions, while prediction accuracy of speech tracking decreased, suggesting that more effort was required to listen, and that the speech was not as successfully encoded. The temporal degradation also resulted in greater EEG power, possibly as a function of a compensatory mechanism to restore the important temporal information required for speech comprehension. Our findings suggest that measures related to cognitive workload and successful speech encoding are differentially affected by noise and sound degradations, which may help to inform future interventions that aim to mitigate these every-day challenges.





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