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1
Dynamic functional brain network connectivity during pseudoword processing relates to children’s reading skill
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2
Development of a standard of care for patients with valosin-containing protein associated multisystem proteinopathy.
In: Orphanet journal of rare diseases, vol 17, iss 1 (2022)
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3
Family history of FXTAS is associated with age-related cognitive-linguistic decline among mothers with the FMR1 premutation.
In: Journal of neurodevelopmental disorders, vol 14, iss 1 (2022)
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4
Cortical microstructure in primary progressive aphasia: a multicenter study.
In: Alzheimer's research & therapy, vol 14, iss 1 (2022)
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5
Providing a parent-administered outcome measure in a bilingual family of a father and a mother of two adolescents with ASD: brief report.
In: Developmental neurorehabilitation, vol 25, iss 2 (2022)
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6
Open access dataset of task-free hemodynamic activity in 4-month-old infants during sleep using fNIRS. ...
Blanco, Borja; Molnar, Monika; Carreiras, Manuel. - : Apollo - University of Cambridge Repository, 2022
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7
Entwicklung einer neuronalen Leitstruktur für die biomimetische Freisetzung von Wachstumsfaktoren im Rahmen der cochleären Regeneration ...
Wille, Inga. - : Hannover : Institutionelles Repositorium der Leibniz Universität Hannover, 2022
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8
A Hermeneutic Phenomenological Study of Teacher Perceptions of the Effects Movement Strategies Have On Student Learning
In: Doctoral Dissertations and Projects (2022)
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9
Anosognosia in Dementia: Evaluation of Perfusion Correlates Using 99mTc-HMPAO SPECT and Automated Brodmann Areas Analysis
In: Diagnostics; Volume 12; Issue 5; Pages: 1136 (2022)
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10
Cerebral Polymorphisms for Lateralisation: Modelling the Genetic and Phenotypic Architectures of Multiple Functional Modules
In: Symmetry; Volume 14; Issue 4; Pages: 814 (2022)
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11
Benefits from Repetitive Transcranial Magnetic Stimulation in Post-Stroke Rehabilitation
In: Journal of Clinical Medicine; Volume 11; Issue 8; Pages: 2149 (2022)
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12
Should Neurosurgeons Try to Preserve Non-Traditional Brain Networks? A Systematic Review of the Neuroscientific Evidence
In: Journal of Personalized Medicine; Volume 12; Issue 4; Pages: 587 (2022)
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13
Emergent Neuroimaging Findings for Written Expression in Children: A Scoping Review
In: Brain Sciences; Volume 12; Issue 3; Pages: 406 (2022)
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14
Advancements in Oncology with Artificial Intelligence—A Review Article
In: Cancers; Volume 14; Issue 5; Pages: 1349 (2022)
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15
Simultaneous Classification of Both Mental Workload and Stress Level Suitable for an Online Passive Brain–Computer Interface
In: Sensors; Volume 22; Issue 2; Pages: 535 (2022)
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16
Expanding the Phenotype of B3GALNT2-Related Disorders
In: Genes; Volume 13; Issue 4; Pages: 694 (2022)
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17
The Neurobiological Correlates of Gaze Perception in Healthy Individuals and Neurologic Patients
In: Biomedicines; Volume 10; Issue 3; Pages: 627 (2022)
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18
Rethinking the Methods and Algorithms for Inner Speech Decoding and Making Them Reproducible
In: NeuroSci; Volume 3; Issue 2; Pages: 226-244 (2022)
Abstract: This study focuses on the automatic decoding of inner speech using noninvasive methods, such as Electroencephalography (EEG). While inner speech has been a research topic in philosophy and psychology for half a century, recent attempts have been made to decode nonvoiced spoken words by using various brain–computer interfaces. The main shortcomings of existing work are reproducibility and the availability of data and code. In this work, we investigate various methods (using Convolutional Neural Network (CNN), Gated Recurrent Unit (GRU), Long Short-Term Memory Networks (LSTM)) for the detection task of five vowels and six words on a publicly available EEG dataset. The main contributions of this work are (1) subject dependent vs. subject-independent approaches, (2) the effect of different preprocessing steps (Independent Component Analysis (ICA), down-sampling and filtering), and (3) word classification (where we achieve state-of-the-art performance on a publicly available dataset). Overall we achieve a performance accuracy of 35.20% and 29.21% when classifying five vowels and six words, respectively, in a publicly available dataset, using our tuned iSpeech-CNN architecture. All of our code and processed data are publicly available to ensure reproducibility. As such, this work contributes to a deeper understanding and reproducibility of experiments in the area of inner speech detection.
Keyword: brain–computer interface (BCI); Convolutional Neural Network (CNN); deep learning; electroencephalography (EEG); independent component analysis; inner speech; supervised learning
URL: https://doi.org/10.3390/neurosci3020017
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19
CEREBRAL ABSCESS AND MYCOTIC ANEURYSM AS A CONSEQUENCE OF INFECTIVE ENDOCARDITIS: A CASE REPORT ...
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20
CEREBRAL ABSCESS AND MYCOTIC ANEURYSM AS A CONSEQUENCE OF INFECTIVE ENDOCARDITIS: A CASE REPORT ...
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