Our work in print

Principles of gamma synchrony predict figure–ground perception in texture stimuli

Karimian, M., Roberts, M. J., De Weerd, P., Senden, M.

eLife, 14, RP105482

doi:10.7554/eLife.105482Preprint

Probabilistic prediction of neural dynamics via autoregressive flow matching

Rogalla, N., Qin, Y., Senden, M., El-Gazzar, A., van Gerven, M.

arXiv, 2604.11178

doi:10.48550/arXiv.2604.11178

The evolving landscape of neuroscience

Senden, M.

Aperture Neuro, 6(SI 2)

doi:10.52294/001c.156380Preprint

Functional whole-brain models: A new framework for unifying brain structure and cognitive function

Senden, M., Dalla Porta, L., Fousek, J., Mejias, J. F., Zamora-López, G.

arXiv, 2605.18118

doi:10.48550/arXiv.2605.18118

Layered structure of cortex explains reversal dynamics in bistable perception

Evers, K. S., Peters, J. C., Goebel, R., Senden, M.

Scientific Reports, 15, 36878

doi:10.1038/s41598-025-20811-2Preprint

PrediRep: Modeling hierarchical predictive coding with an unsupervised deep learning network

Hashim, I. C., Senden, M., Goebel, R.

Neural Networks, 185, 107246

doi:10.1016/j.neunet.2025.107246Preprint

The global communication pathways of the human brain transcend the cortical-subcortical-cerebellar division

Schulte, J., Senden, M., Deco, G., Kobeleva, X., Zamora-López, G.

arXiv, 2505.22893

doi:10.48550/arXiv.2505.22893

Encoding and decoding models

Senden, M., Kroner, A.

Encyclopedia of the Human Brain (Second Edition), 680–698

doi:10.1016/b978-0-12-820480-1.00176-5

Convolutional neural networks develop major organizational principles of early visual cortex when enhanced with retinal sampling

da Costa, D., Kornemann, L., Goebel, R., Senden, M.

Scientific Reports, 14, 8980

doi:10.1038/s41598-024-59376-xPreprint

Multi-scale spiking network model of human cerebral cortex

Pronold, J., van Meegen, A., Shimoura, R. O., Vollenbröker, H., Senden, M., Hilgetag, C. C., Bakker, R., van Albada, S. J.

Cerebral Cortex, 34(10), bhae409

doi:10.1093/cercor/bhae409Preprint

Modular-integrative modeling: a new framework for building brain models that blend biological realism and functional performance

Senden, M., van Albada, S. J., Pezzulo, G., Falotico, E., Hashim, I., Kroner, A., Kurth, A. C., Lanillos, P., Narayanan, V., Pennartz, C., Petrovici, M. A., Steffen, L., Weidler, T., Goebel, R.

National Science Review, 11(5), nwad318

doi:10.1093/nsr/nwad318

Neural correlates of high-level visual saliency models

Kroner, A., Senden, M., Goebel, R.

bioRxiv

doi:10.1101/2023.07.29.551075

Editorial: The embodied brain: computational mechanisms of integrated sensorimotor interactions with a dynamic environment, volume II

Röhrbein, F., Senden, M.

Frontiers in Computational Neuroscience, 17, 1203717

doi:10.3389/fncom.2023.1203717

AngoraPy: A Python toolkit for modeling anthropomorphic goal-driven sensorimotor systems

Weidler, T., Goebel, R., Senden, M.

Frontiers in Neuroinformatics, 17, 1223687

doi:10.3389/fninf.2023.1223687Preprint

Editorial: Focus feature on biomarkers in network neuroscience

Douw, L., Senden, M., van den Heuvel, M. P.

Network Neuroscience, 6(2), 298–300

doi:10.1162/netn_e_00249

Reading imagined letter shapes from the mind’s eye using real-time 7 Tesla fMRI

Goebel, R., van Hoof, R., Bhat, S., Lührs, M., Senden, M.

2022 10th International Winter Conference on Brain-Computer Interface (BCI), 1–3

doi:10.1109/BCI53720.2022.9735031

Extremely fast pRF mapping for real-time applications

Bhat, S., Lührs, M., Goebel, R., Senden, M.

NeuroImage, 245, 118671

doi:10.1016/j.neuroimage.2021.118671Preprint

Cortical synchrony as a mechanism of collinear facilitation and suppression in early visual cortex

Evers, K., Peters, J., Senden, M.

Frontiers in Systems Neuroscience, 15, 670702

doi:10.3389/fnsys.2021.670702

Biologically inspired semantic lateral connectivity for convolutional neural networks

Weidler, T., Lehnen, J., Denman, Q., Sebők, D., Weiss, G., Driessens, K., Senden, M.

arXiv, 2105.09830

doi:10.48550/arXiv.2105.09830

Model-based whole-brain effective connectivity to study distributed cognition in health and disease

Gilson, M., Zamora-López, G., Pallarés, V., Adhikari, M. H., Senden, M., Tauste Campo, A., Mantini, D., Corbetta, M., Deco, G., Insabato, A.

Network Neuroscience, 4(2), 338–373

doi:10.1162/netn_a_00117Preprint

Contextual encoder–decoder network for visual saliency prediction

Kroner, A., Senden, M., Driessens, K., Goebel, R.

Neural Networks, 129, 261–270

doi:10.1016/j.neunet.2020.05.004Preprint

Investigating the reliability of population receptive field size estimates using fMRI

Lage-Castellanos, A., Valente, G., Senden, M., De Martino, F.

Frontiers in Neuroscience, 14, 825

doi:10.3389/fnins.2020.00825

Interfering with a memory without erasing its trace

Lange, G., Senden, M., Radermacher, A., De Weerd, P.

Neural Networks, 121, 339–355

doi:10.1016/j.neunet.2019.09.027Preprint

Editorial: The embodied brain: computational mechanisms of integrated sensorimotor interactions with a dynamic environment

Senden, M., Peters, J., Röhrbein, F., Deco, G., Goebel, R.

Frontiers in Computational Neuroscience, 14, 53

doi:10.3389/fncom.2020.00053

Running large-scale simulations on the Neurorobotics Platform to understand vision – the case of visual crowding

Bornet, A., Kaiser, J., Kroner, A., Falotico, E., Ambrosano, A., Cantero, K., Herzog, M. H., Francis, G.

Frontiers in Neurorobotics, 13, 33

doi:10.3389/fnbot.2019.00033

The road ahead in clinical network neuroscience

Douw, L., van Dellen, E., Gouw, A. A., Griffa, A., de Haan, W., van den Heuvel, M. P., Hillebrand, A., Van Mieghem, P., Nissen, I. A., Otte, W. M., Reijmer, Y. D., Schoonheim, M. M., Senden, M., van Straaten, E. C. W., Tijms, B. M., Tewarie, P., Stam, C. J.

Network Neuroscience, 3(4), 969–993

doi:10.1162/netn_a_00103

Effects of synaptic and myelin plasticity on learning in a network of Kuramoto phase oscillators

Karimian, M., Dibenedetto, D., Moerel, M., Burwick, T., Westra, R. L., De Weerd, P., Senden, M.

Chaos: An Interdisciplinary Journal of Nonlinear Science, 29(8), 083122

doi:10.1063/1.5092786Preprint

Reconstructing imagined letters from early visual cortex reveals tight topographic correspondence between visual mental imagery and perception

Senden, M., Emmerling, T. C., van Hoof, R., Frost, M. A., Goebel, R.

Brain Structure and Function, 224(3), 1167–1183

doi:10.1007/s00429-019-01828-6Preprint

Configural properties underlie the perceived faceness of a stimulus

Gnolo, C., Senden, M., Grillini, A., Cornelissen, F. W., Goebel, R.

bioRxiv

doi:10.1101/509026

[Re] A neural model of the saccade generator in the reticular formation

Senden, M., Schuecker, J., Hahne, J., Diesmann, M., Goebel, R.

ReScience, 4(1), 3

doi:10.5281/zenodo.1241004

Task-related effective connectivity reveals that the cortical rich club gates cortex-wide communication

Senden, M., Reuter, N., van den Heuvel, M. P., Goebel, R., Deco, G., Gilson, M.

Human Brain Mapping, 39(3), 1246–1262

doi:10.1002/hbm.23913Preprint

Comparing task-relevant information across different methods of extracting functional connectivity

Stulz, S. B., Insabato, A., Deco, G., Gilson, M., Senden, M.

bioRxiv

doi:10.1101/509059

Cortical rich club regions can organize state-dependent functional network formation by engaging in oscillatory behavior

Senden, M., Reuter, N., van den Heuvel, M. P., Goebel, R., Deco, G.

NeuroImage, 146, 561–574

doi:10.1016/j.neuroimage.2016.10.044

Evaluating population receptive field estimation frameworks in terms of robustness and reproducibility

Senden, M., Reithler, J., Gijsen, S., Goebel, R.

PLoS ONE, 9(12), e114054

doi:10.1371/journal.pone.0114054

Rich club organization supports a diverse set of functional network configurations

Senden, M., Deco, G., de Reus, M. A., Goebel, R., van den Heuvel, M. P.

NeuroImage, 96, 174–182

doi:10.1016/j.neuroimage.2014.03.066

How anatomy shapes dynamics: a semi-analytical study of the brain at rest by a simple spin model

Deco, G., Senden, M., Jirsa, V.

Frontiers in Computational Neuroscience, 6, 68

doi:10.3389/fncom.2012.00068

Structural connectivity allows for multi-threading during rest: The structure of the cortex leads to efficient alternation between resting state exploratory behavior and default mode processing

Senden, M., Goebel, R., Deco, G.

NeuroImage, 60(4), 2274–2284

doi:10.1016/j.neuroimage.2012.02.061