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Ahmadi, K., Pouretemad, H. R., Esfandiari, J., Yoonessi, A., & Yoonessi, A. (2015). Psychophysical evidence for impaired Magno, Parvo, and Konio-cellular pathways in dyslexic childrenJournal of ophthalmic & vision research10(4), 433.

Ahmadi, K., Fracasso, A., van Dijk, J.A., Kruijt, C., van Genderen, M., Dumoulin, S.O., & Hoffmann, M.N. (2017). Altered organization of the visual cortex in FHONDA syndrome. NeuroImage, 1-8.

de Best, P.B., Raz, N., Dumoulin, S.O., & Levin, N. (2018). How ocular dominance and binocularity are reflected by the population receptive field properties. IOVS, 56, 5301-531

de Best, P. B., Raz, N., Guy, N., Ben-Hur, T., Dumoulin, S. O., Pertzov, Y., & Levin, N. (2019). Role of population receptive field size in complex visual dysfunctions: a posterior cortical atrophy modelJama Neurology76(11), 1391-1396.

de Best, P. B., Abulafia, R., McKyton, A., & Levin, N. (2020). Convergence Along the Visual Hierarchy Is Altered in Posterior Cortical AtrophyInvestigative Ophthalmology & Visual Science61(11), 8.

Bhat, A., Cicchini, G.M., & Burr, D.C. Inhibitory surrounds of motion mechanisms revealed by continuous tracking. (2018). Journal of Vision, 18, 1-10

Binda, P., Kurzawski, J.W., Lunghi, C., Biagi, L., Tosetti, M, Morrone, M.C. (2018). Response to short-term deprivation of the human adult visual cortex measured with 7T BOLDeLife.40014

Binda, P., Kurzawski, J.W., Lunghi, C., Biagi, L., Tosetti, M, Morrone, M.C. (2020). Short-term plasticity of the human adult visual cortex measured with 7T BOLD. bioRxiv preprint doi:;

Carvalho J, Invernizzi A, Ahmadi K, Hoffmann MB, Renken RJ, Cornelissen FW (2020). Micro-probing enables fine-grained mapping of neuronal populations using fMRI. Neuroimage 209, 116423.

Carvalho J, Renken, R and Cornelissen, FW (2019) Predictive masking is associated with a system-wide reconfiguration of neural populations in the human visual cortex. bioRxiv 758094

Carvalho J, Martins J, Invernizzi A, Jansonious N, Renken RJ, Cornelissen FW (2020) Visual field reconstruction using fMRI-based techniques. TVST. (In press)

Carvalho J, Renken RJ, Cornelissen FW (2019) Studying Cortical Plasticity in Ophthalmic and Neurological Disorders: From Stimulus-Driven to Cortical Circuitry Modeling Approaches. Neural Plasticity, 2724101.

van Dijk, J. A., de Haas, B., Moutsiana, C., & Schwarzkopf, D. S. (2016). Intersession reliability of population receptive field estimates. NeuroImage, 143, 293-303.

van Dijk, J. A., Fracasso, A., Petridou, N., & Dumoulin, S. O. (2020). Linear systems analysis for laminar fMRi: evaluating BoLD amplitude scaling for luminance contrast manipulationsScientific reports10(1), 1-15.

van Dijk, J. A., Fracasso, A., Petridou, N., & Dumoulin, S. O. (2020). Validating Linear Systems Analysis for Laminar fMRI: Temporal Additivity for Stimulus Duration ManipulationsBrain Topography, 1-14.

Grillini, A., Ombelet, D., Soans, R.S., & Cornelissen, F.W. (2018). Toward using the spatio-temporal properties of eye movements to classify visual field defects. ETRA ’18 Proceedings, 38

Grillini, A., Renken, R.J., & Cornelissen, F.W. (2019) Attention modulation of visual spatial integration: psychophysical evidence supported by population coding modelingJournal of Cognitive Neuroscience, 1-14

Grillini, A., Renken, R. J, Vrijling, A. C. L., Heutink, J., Cornelissen, F. W. (2020) Eye movement evaluation in Multiple Sclerosis and Parkinson’s Disease using a Standardized Oculomotor and Neuro-ophthalmic Disorder Assessment (SONDA). Frontiers in Neurology. doi: 10.3389/fneur.2020.00971

Gestefeld, B., Grillini, A., Marsman, J. B., Cornelissen, F. W. (2020) Using natural viewing behavior to screen for and reconstruct visual field defects. Journal of Vision 20(9):11. doi:

Himmelberg, M.M., Segala, F.G., Maloney, R.T., Harris, J.M. & Wade, A.R (2020). Decoding neural responses to motion-in-depth using EEG. Frontiers in Neuroscience, DOI: 10.3389/fnins.2020.581706

Himmelberg, M.M. & Wade, A.R. (2019). Eccentricity-dependent temporal contrast tuning in human visual cortex measured with fMRI, NeuroImage, 194, 462-472. DOI:10.1016/j.neuroimage.2018.09.049

Himmelberg, M.M., West, R.J.H., Elliot, C.J.H., & Wade, A.R. (2018). Abnormal visual gain control and excitotoxicity in early-onset Parkinson’s disease Drosophila modelsJournal of Neurophysiology, 119, 957-970

Himmelberg, M.M, West, R.J.H., West, Wade, A.R.W., & Elliot, C.J.H. (2018). A perspective plus in Parkinson’s diseaseMovement Disorders, 33, 248

Himmelberg, M.M., & Wade, A.R. (2019) Eccentricity-dependent temporal contrast tuning in human visual cortex measured with fMRINeuroImage, 184, 462-474

Hernández-García, A., & König, P. (2018). Do deep nets really need weight decay and dropout? arXiv preprint arXiv:1802.07042

Hernández-García, A. (2017). Perceived emotion from images through deep neural networks. Seventh International Conference on Affective Computing and Intelligent Interaction (conference proceedings), 566-570

Hernández-García, A., & König, P. (2018). Further advantages of data augmentation on convolution neural networks. Artificial Neural Networks and Machine Learning (conference proceedings), 95-103

Hernández-García, A., Gameiro, R.R., Grillini, A., & König, P. (2020). Global visual salience of competing stimuli. Journal of Vision, 20(27).

Hernández-García, A., König, P., & Kietzmann, T.C. (2020). Learning robust visual representations using data augmentation invariance. arXiv:1906.04547

Hernández-García, A., Mehrer, J., Kriegeskorte, N., König, P., & Kietzmann, T.C. (2018). Deep neural networks trained with heavier data augmentation learn features closer to representations in hIT.  Cognitive Computational Neuroscience (CCN) (conference proceedings)

Hoffmann, M. B., & Dumoulin, S. O. (2015). Congenital visual pathway abnormalities: a window onto cortical stability and plasticityTrends in neurosciences38(1), 55-65.

Hoffmann, M., Thieme, H., & Ahmadi, K. (2017). Potenzial von fMRT für die Funktionsüberprüfung des pathologischen SehsystemsKlinische Monatsblatter Fur Augenheilkunde, 234, 303-310.

Klein, B.P., Fracasso, A., van Dijk, J.A., Paffen, C.L.E., te Pas, S.F., & Dumoulin, S.O. Cortical depth dependent population receptive field attraction by spatial attention in human V1. (2018). NeuroImage, 176, 301-312

Kurzawski JW, Cencini M, Peretti L, Gómez PA, Schulte RF, Donatelli G, Cosottini M, Cecchi P, Costagli M, Retico A, Tosetti M, Buonincontri G. Retrospective rigid motion correction of three-dimensional magnetic resonance fingerprinting of the human brain. Magn Reson Med. 2020 Nov;84(5):2606-2615. doi: 10.1002/mrm.28301. Epub 2020 May 5. PMID: 32368835.

Kupers, E.R., Edadan, A., Benson, N.C., Zuiderbaan, W., de Jonge, M.C., Dumoulin, S.O., Winawer, J. (2020). A Population Receptive Field Model of the Magnetoencephalography Response. bioRxiv preprint doi:

Mikellidou, K., Kurzawski, J.W., Frijia, F., Montanaro, D., Greco, V., Burr, D.C., & Morrone, M.C. (2017). Area Prostriata in the Human BrainCurrent Biology, 19, 3056-306

Moutsiana, C., de Haas, B., Papageorgiou, A., van Dijk, J. A., Balraj, A., Greenwood, J. A., & Schwarzkopf, D. S. (2016). Cortical idiosyncrasies predict the perception of object size. Nature Communications, 7, 12110.

Østergaard, F.G., Himmelberg, M.M., Laursen, B. et al. (2020) Classification of α-synuclein-induced changes in the AAV α-synuclein rat model of Parkinson’s disease using electrophysiological measurements of visual processingSci Rep 10, 11869.

Østergaard, F. G., Wade, A. R., Siebner, H.R., Christensen, K.V., & Laursen, B. Progressive Effects of Sildenafil on Visual Processing in RatsNeuroscience44, 131-141

Prabhakaran G, Carvalho J, Invernizzi A, Kanowski M, Renken RJ, Cornelissen FW, Hoffmann MB (2020) Foveal pRF properties in the visual cortex depend on the extent of stimulated visual field. Neuroimage 222: 117250.

Puzniak, R.J., Ahmadi, K., Kaufmannb, J., Gouws, A., Morland, A.B., Pestilli, F., Hoffmanna, M.B. (2019) Quantifying nerve decussation abnormalities in the optic chiasmNeuroimage Clinical, 24

Raz, N., & Levin, N. (2016). Neuro-visual rehabilitationJournal of Neurology, 1-8.

Semeniuta, S., Severyn, A., & Barth, E. (2017). A hybrid variational autoencoder for text generation. Conference on Emperical Methods in Natural Language Processing (proceedings), 627-637

Semeniuta, S., Severyn, A., & Gelly, S. (2018). On accurate evaluation of GAN for language generation. arXiv preprint arXiv:1806.04936v2

Semeniuta, S., Severyn, A., & Barth, E. (2016). Recurrent dropout without memory lossarXiv preprint arXiv:1603.05118.

Semeniuta, S. & Barth, E. (2016). Image Classification with Recurrent Attention Models. IEEE SSCI 16

Yildrim, F., Carvalho, J., Cornelissen, & F.W. (2018). A second-order orientation-contrast stimulus for population-receptive-field-based retinotopic mappingNeuroImage, 164, 183-193