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1
Dynamic functional brain network connectivity during pseudoword processing relates to children’s reading skill
Panda, Erin J.
;
Valiante, Taufik A.
;
Pang, Elizabeth W.
. - : Elsevier, 2022
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2
Computational Models in Electroencephalography.
Glomb, Katharina
;
Cabral, Joana
;
Cattani, Anna
...
In: Brain topography, vol 35, iss 1 (2022)
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3
Functional Brain Networks and Verbal Fluency in Healthy Ageing ...
Oosterhuis, Elise
. - : Open Science Framework, 2022
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4
Unified Coding of Spectral and Temporal Phonetic Cues: Electrophysiological Evidence for Abstract Phonological Features ...
Monahan, Philip
. - : Open Science Framework, 2022
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5
A Preliminary Report of Network Electroencephalographic Measures in Primary Progressive Apraxia of Speech and Aphasia
Rene L. Utianski; Hugo Botha; John N. Caviness; Gregory A. Worrell; Joseph R. Duffy; Heather M. Clark; Jennifer L. Whitwell; Keith A. Josephs
In: Brain Sciences; Volume 12; Issue 3; Pages: 378 (2022)
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6
Spectral Entropy Monitoring Accelerates the Emergence from Sevoflurane Anesthesia in Thoracic Surgery: A Randomized Controlled Trial
Jui-Tai Chen; Yu-Ming Wu; Tung-Yu Tiong; Juan P. Cata; Kuang-Tai Kuo; Chun-Cheng Li; Hsin-Yi Liu; Yih-Giun Cherng; Hsiang-Ling Wu; Ying-Hsuan Tai
In: Journal of Clinical Medicine; Volume 11; Issue 6; Pages: 1631 (2022)
Abstract:
The clinical efficacy of spectral entropy monitoring in improving postoperative recovery remains unclear. This trial aimed to investigate the impact of M-Entropy (GE Healthcare, Helsinki, Finland) guidance on emergence from anesthesia and postoperative delirium in thoracic surgery. Adult patients undergoing video-assisted thoracoscopic surgery for lung resection at a medical center were randomly allocated into the M-Entropy guidance group (n = 39) and the control group (n = 37). In the M-Entropy guidance group, sevoflurane anesthesia was titrated to maintain response and state entropy values between 40 and 60 intraoperatively. In the control group, the dosing of sevoflurane was adjusted based on clinical judgment and vital signs. The primary outcome was time to spontaneous eye opening. M-Entropy guidance significantly reduced the time proportion of deep anesthesia (entropy value <40) during surgery, mean difference: −21.5% (95% confidence interval (CI): −32.7 to −10.3) for response entropy and −24.2% (−36.3 to −12.2) for state entropy. M-Entropy guidance significantly shortened time to spontaneous eye opening compared to clinical signs, mean difference: −154 s (95% CI: −259 to −49). In addition, patients of the M-Entropy group had a lower rate of emergence agitation (absolute risk reduction: 0.166, 95% CI: 0.005–0.328) and delirium (0.245, 0.093–0.396) at the postanesthesia care unit. M-Entropy-guided anesthesia hastened awakening and potentially prevented emergence agitation and delirium after thoracic surgery. These results may provide an implication for facilitating postoperative recovery and reducing the complications associated with delayed emergence and delirium.
Keyword:
chest surgery
;
delirium
;
depth of anesthesia
;
electroencephalography
;
emergence agitation
URL:
https://doi.org/10.3390/jcm11061631
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7
Simultaneous Classification of Both Mental Workload and Stress Level Suitable for an Online Passive Brain–Computer Interface
Mahsa Bagheri; Sarah D. Power
In: Sensors; Volume 22; Issue 2; Pages: 535 (2022)
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8
Rethinking the Methods and Algorithms for Inner Speech Decoding and Making Them Reproducible
Foteini Simistira Liwicki; Vibha Gupta; Rajkumar Saini; Kanjar De; Marcus Liwicki
In: NeuroSci; Volume 3; Issue 2; Pages: 226-244 (2022)
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9
Unified Coding of Spectral and Temporal Phonetic Cues: Electrophysiological Evidence for Abstract Phonological Features
Monahan, Philip J.
;
Schertz, Jessamyn
;
Fu, Zhanao
. - : University of Toronto, 2022
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10
A dimension reduction technique applied to regression on high dimension, low sample size neurophysiological data sets
Santana, Adrielle,
;
Barbosa, Adriano,
;
Yehia, Hani,
...
In: ISSN: 1471-2202 ; EISSN: 1471-2202 ; BMC Neuroscience ; https://hal.univ-grenoble-alpes.fr/hal-03374818 ; BMC Neuroscience, BioMed Central, 2021, 22 (1), ⟨10.1186/s12868-020-00605-0⟩ (2021)
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11
Somatosensory contribution to audio-visual speech processing
Ito, Takayuki
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Ohashi, Hiroki
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Gracco, Vincent
In: ISSN: 0010-9452 ; Cortex ; https://hal.archives-ouvertes.fr/hal-03320604 ; Cortex, Elsevier, 2021, 143, pp.195-204. ⟨10.1016/j.cortex.2021.07.013⟩ ; https://doi.org/10.1016/j.cortex.2021.07.013 (2021)
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12
An ERP index of real-time error correction within a noisy-channel framework of human communication.
Ryskin, Rachel
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Stearns, Laura
;
Bergen, Leon
. - : eScholarship, University of California, 2021
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13
Good Scientific Practice in MEEG Research: Progress and Perspectives
Niso, Guiomar
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Krol, Laurens
;
Combrisson, Etienne
...
In: https://hal.archives-ouvertes.fr/hal-03494100 ; 2021 (2021)
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14
Modality switch effects emerge early and increase throughout conceptual processing: Evidence from ERPs ...
Bernabeu, Pablo
. - : Open Science Framework, 2021
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15
Human processing of transmitted speech varying in perceived quality ... : Menschliche Verarbeitung von technisch übertragener Sprache in unterschiedlich wahrgenommener Qualität ...
Uhrig, Stefan Josef
. - : Technische Universität Berlin, 2021
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16
Sustained neural rhythms reveal endogenous oscillations supporting speech perception. ...
Van Bree, Sander
;
Sohoglu, Ediz
;
Davis, Matt
. - : Apollo - University of Cambridge Repository, 2021
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17
Application of Machine Learning to Electroencephalography for the Diagnosis of Primary Progressive Aphasia: A Pilot Study
Lucía Fernández-Romero
;
Adela Fraile-Pereda
;
Paloma Balugo
...
In: Brain Sciences ; Volume 11 ; Issue 10 (2021)
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18
Testing Low-Frequency Neural Activity in Sentence Understanding ...
Lo, Chia-Wen
. - : My University, 2021
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19
ВОЗДЕЙСТВИЕ ТЕХНОЛОГИЙ ВИРТУАЛЬНОЙ РЕАЛЬНОСТИ НА ПСИХОЭМОЦИОНАЛЬНОЕ СОСТОЯНИЕ ПАЦИЕНТОВ С АФАЗИЯМИ ... : The impact of virtual reality on the emotional state of patients with aphasia ...
Карпов, О.Э.
;
Даминов, В.Д.
;
Новак, Э.В.
. - : Фонд развития современных и цифровых технологий, 2021
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20
Testing Low-Frequency Neural Activity in Sentence Understanding
Lo, Chia-Wen
. - 2021
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