Deep-learning models of the ascending proprioceptive pathway are subject to illusions

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Here we provide the data to run the code provided in github.

Data required to train and test the models in data.zip ~37 GB when uncompressed. This includes: cleaned_smooth: pre-processed data from FLAG3D and PCR dataset, the elbow flexion datasets u ...

Background: Individuals with Parkinson's disease (PD) with freezing of gait (FoG) exhibit difficulty with changes in sensory input, indicating a potential sensorimotor integration deficit. Understanding how levodopa impacts balance particularly in FoG, is ...

The lumbosacral spinal cord contains neural circuits crucial for locomotion, organized into rostrocaudal levels with distinct somatosensory and motor neuron pools that project to and from the muscles of the lower limbs. However, the specific spinal levels ...

Proprioception tells the brain the state of the body based on distributed sensory neurons. Yet, the principles that govern proprioceptive processing are poorly understood. Here, we employ a task -driven modeling approach to investigate the neural code of p ...

Stochastic resonance (SR) is the phenomenon wherein the introduction of a suitable level of noise enhances the detection of subthreshold signals in non linear systems. It manifests across various physical and biological systems, including the human brain. ...

Deep-learning models of the ascending proprioceptive pathway are subject to illusions

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Data for Deep-learning models of the ascending proprioceptive pathway are subject to illusions

Effect of Medication and Freezing of Gait on Rambling and Trembling in Quiet Standing in Individuals With Parkinson's Disease

Towards personalized mapping through lumbosacral spinal cord task fMRI

Task-driven neural network models predict neural dynamics of proprioception

Behavioural stochastic resonance across the lifespan