Dynamic brain networks explored by structure-revealing methods

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The upcoming Square Kilometre Array Observatory will produce images of neutral hydrogen distribution during the epoch of reionization by observing the corresponding 21-cm signal. However, the 21-cm signal will be subject to instrumental limitations such as ...

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Proprioception tells the brain the state of the body based on distributed sensors in the body. However, the principles that govern proprioceptive processing from those distributed sensors are poorly understood. Here, we employ a task-driven neural network ...

Background Disrupted sense of agency (SoA)-the sense of being the agent of one's own actions-has been demonstrated in patients with functional neurological disorder (FND), and a key area of the corresponding neuronal network is the right temporoparietal ju ...

Neural decoding of the visual system is a subject of research interest, both to understand how the visual system works and to be able to use this knowledge in areas, such as computer vision or brain-computer interfaces. Spike-based decoding is often used, ...

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While humans are known to have several premotor cortical areas, secondary motor cortex (M2) is often considered to be the only higher -order motor area of the mouse brain and is thought to combine properties of various human premotor cortices. Here, we sho ...

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 ...

In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...

This article summarizes the recent advancements in the design, fabrication, and control of microrobotic devices for the diagnosis and treatment of brain disorders. With a focus on diverse actuation methods, we discuss how advancements in materials science ...

Fluorescence lifetime imaging (FLI) has been receiving increased attention in recent years as a powerful diagnostic technique in biological and medical research. However, existing FLI systems often suffer from a tradeoff between processing speed, accuracy, ...

Dynamic brain networks explored by structure-revealing methods

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Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Integrated Wireless Power, Data Communication, and Thermal Sensing System for Autonomous Multisite Brain Implants

Task-driven neural network models predict neural dynamics of proprioception: Neural network model weights

Non-invasive neuromodulation of the right temporoparietal junction using theta-burst stimulation in functional neurological disorder

Predicting Visual Stimuli From Cortical Response Recorded With Wide-Field Imaging in a Mouse

Improving Lipschitz-Constrained Neural Networks by Learning Activation Functions

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Aggregating Spatial and Photometric Context for Photometric Stereo

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The mouse motor system contains multiple premotor areas and partially follows human

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

Random matrix methods for high-dimensional machine learning models

Small-scale robotic devices for medical interventions in the brain

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging