Yury Koush, PhD
Yury Koush, PhD
Verified email at yale.edu
Cited by
Cited by
Connectivity-based neurofeedback: dynamic causal modeling for real-time fMRI
Y Koush, MJ Rosa, F Robineau, K Heinen, SW Rieger, N Weiskopf, ...
Neuroimage 81, 422-430, 2013
Learning control over emotion networks through connectivity-based neurofeedback
Y Koush, DE Meskaldji, S Pichon, G Rey, SW Rieger, DEJ Linden, ...
Cerebral cortex 27 (2), 1193-1202, 2017
Consensus on the reporting and experimental design of clinical and cognitive-behavioural neurofeedback studies (CRED-nf checklist)
T Ros, S Enriquez-Geppert, V Zotev, KD Young, G Wood, ...
Brain 143 (6), 1674-1685, 2020
Signal quality and Bayesian signal processing in neurofeedback based on real-time fMRI
Y Koush, M Zvyagintsev, M Dyck, KA Mathiak, K Mathiak
NeuroImage 59 (1), 478-489, 2012
Auditory mismatch impairments are characterized by core neural dysfunctions in schizophrenia
AJ Gaebler, K Mathiak, JW Koten Jr, AA König, Y Koush, D Weyer, ...
Brain 138 (5), 1410-1423, 2015
Self-regulation of inter-hemispheric visual cortex balance through real-time fMRI neurofeedback training
F Robineau, SW Rieger, C Mermoud, S Pichon, Y Koush, D Van De Ville, ...
NeuroImage 100, 1-14, 2014
Social reinforcement can regulate localized brain activity
KA Mathiak, Y Koush, M Dyck, TJ Gaber, E Alawi, FD Zepf, M Zvyagintsev, ...
European Archives of Psychiatry and Clinical Neuroscience 260 (2), 132-136, 2010
Continuous vs. intermittent neurofeedback to regulate auditory cortex activity of tinnitus patients using real-time fMRI-A pilot study
K Emmert, R Kopel, Y Koush, R Maire, P Senn, D Van De Ville, S Haller
NeuroImage: Clinical 14, 97-104, 2017
OpenNFT: An open-source Python/Matlab framework for real-time fMRI neurofeedback training based on activity, connectivity and multivariate pattern analysis
Y Koush, J Ashburner, E Prilepin, R Sladky, P Zeidman, S Bibikov, ...
NeuroImage 156, 489-503, 2017
Targeting treatment-resistant auditory verbal hallucinations in schizophrenia with fMRI-based neurofeedback–exploring different cases of schizophrenia
MS Dyck, KA Mathiak, S Bergert, P Sarkheil, Y Koush, EM Alawi, ...
Frontiers in psychiatry 7, 37, 2016
Social reward improves the voluntary control over localized brain activity in fMRI-based neurofeedback training
KA Mathiak, EM Alawi, Y Koush, M Dyck, JS Cordes, TJ Gaber, FD Zepf, ...
Frontiers in behavioral neuroscience 9, 136, 2015
Upregulation of the rostral anterior cingulate cortex can alter the perception of emotions: fMRI-based neurofeedback at 3 and 7 T
M Gröne, M Dyck, Y Koush, S Bergert, KA Mathiak, EM Alawi, M Elliott, ...
Brain Topography 28 (2), 197-207, 2015
Maintenance of voluntary self-regulation learned through real-time fMRI neurofeedback
F Robineau, DE Meskaldji, Y Koush, SW Rieger, C Mermoud, ...
Frontiers in Human Neuroscience 11, 131, 2017
Single voxel proton spectroscopy for neurofeedback at 7 Tesla
Y Koush, MA Elliott, K Mathiak
Materials 4 (9), 1548-1563, 2011
Brain networks for engaging oneself in positive-social emotion regulation
Y Koush, S Pichon, SB Eickhoff, D Van De Ville, P Vuilleumier, ...
NeuroImage 189, 106-115, 2019
Real-time automated spectral assessment of the BOLD response for neurofeedback at 3 and 7 T
Y Koush, MA Elliott, F Scharnowski, K Mathiak
Journal of neuroscience methods 218 (2), 148-160, 2013
Towards tailoring non-invasive brain stimulation using real-time fMRI and Bayesian optimization
R Lorenz, RP Monti, A Hampshire, Y Koush, C Anagnostopoulos, ...
2016 International Workshop on Pattern Recognition in Neuroimaging (PRNI), 1-4, 2016
Real-time fMRI data for testing OpenNFT functionality
Y Koush, J Ashburner, E Prilepin, R Sladky, P Zeidman, S Bibikov, ...
Data in brief 14, 344-347, 2017
Can we predict real-time fMRI neurofeedback learning success from pre-training brain activity?
A Haugg, R Sladky, S Skouras, A McDonald, C Craddock, M Kirschner, ...
Human Brain Mapping 41 (14), 3839-3854, 2020
Functional MRS with J-edited lactate in human motor cortex at 4 T
Y Koush, RA de Graaf, L Jiang, DL Rothman, F Hyder
Neuroimage 184, 101-108, 2019
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