Transient networks of spatio-temporal connectivity map communication pathways in brain functional systems

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Here we provide the neural data, activation and predictions for the best models and result dataframes of our article "Task-driven neural network models predict neural dynamics of proprioception". It contains the behavioral and neural experimental data (cu ...

Aim: Adolescents born very preterm (VPT;

Cell fate progression of pluripotent progenitors is strictly regulated, resulting in high human cell diversity. Epigenetic modifications also orchestrate cell fate restriction. Unveiling the epigenetic mechanisms underlying human cell diversity has been di ...

Objective. Selective neuromodulation of deep brain regions has for a long time only been possible through invasive approaches, because of the steep depth-focality trade-off of conventional non-invasive brain stimulation (NIBS) techniques. Approach. An appr ...

Electrical stimulation of the nervous system has emerged as a promising assistive technology in case of many injuries and illnesses across various parts of the nervous system. In particular, the invasive neuromodulation of the peripheral nervous system see ...

The rise of robotic body augmentation brings forth new developments that will transform robotics, human-machine interaction, and wearable electronics. Extra robotic limbs, although building upon restorative technologies, bring their own set of challenges i ...

Despite the widespread empirical success of ResNet, the generalization properties of deep ResNet are rarely explored beyond the lazy training regime. In this work, we investigate scaled ResNet in the limit of infinitely deep and wide neural networks, of wh ...

Animals, including humans, exhibit a remarkable variety of complex behaviours. How the nervous system controls all these behaviours ranging from simple, stereotyped movements to flexible, adaptive actions is a central questions of neuroscience. One of the ...

In this PhD manuscript, we explore optimisation phenomena which occur in complex neural networks through the lens of

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-layer diagonal linear networks. This rudimentary architecture, which consists of a two layer feedforward linear network with a diagonal ...

We study the random binary symmetric perceptron problem, focusing on the behavior of rare high-margin solutions. While most solutions are isolated, we demonstrate that these rare solutions are part of clusters of extensive entropy, heuristically correspond ...

Visuo-motor integration shapes our daily experience and underpins the sense of feeling in control over our actions. The last decade has seen a surge in robotically and virtually mediated interactions, whereby bodily actions ultimately result in an artifici ...

Transient networks of spatio-temporal connectivity map communication pathways in brain functional systems

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Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

Impact of a mindfulness-based intervention on neurobehavioral functioning and its association with large-scale brain networks in preterm young adolescents

Single-cell epigenomic reconstruction of developmental trajectories from pluripotency in human neural organoid systems

Safety, tolerability and blinding efficiency of non-invasive deep transcranial temporal interference stimulation: first experience from more than 250 sessions

Biophysically accurate and machine learning-based surrogate models to optimize neuroprosthesis design and operation

Investigating neural resource allocation in the sensorimotor control of extra limbs

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Uncovering interactions between Descending Neurons as a functional principle of behavioural control

Deep Learning Theory Through the Lens of Diagonal Linear Networks

On the atypical solutions of the symmetric binary perceptron

Neural signatures of visuo-motor integration during human-robot interactions