Deans' stroke musings: Deciphering Proprioception: How the Brain Maps Movement

Changing stroke rehab and research worldwide now.Time is Brain! trillions and trillions of neurons that DIE each day because there are NO effective hyperacute therapies besides tPA(only 12% effective). I have 523 posts on hyperacute therapy, enough for researchers to spend decades proving them out. These are my personal ideas and blog on stroke rehabilitation and stroke research. Do not attempt any of these without checking with your medical provider. Unless you join me in agitating, when you need these therapies they won't be there.

What this blog is for:

My blog is not to help survivors recover, it is to have the 10 million yearly stroke survivors light fires underneath their doctors, stroke hospitals and stroke researchers to get stroke solved. 100% recovery. The stroke medical world is completely failing at that goal, they don't even have it as a goal. Shortly after getting out of the hospital and getting NO information on the process or protocols of stroke rehabilitation and recovery I started searching on the internet and found that no other survivor received useful information. This is an attempt to cover all stroke rehabilitation information that should be readily available to survivors so they can talk with informed knowledge to their medical staff. It lays out what needs to be done to get stroke survivors closer to 100% recovery. It's quite disgusting that this information is not available from every stroke association and doctors group.

Saturday, March 23, 2024

Deciphering Proprioception: How the Brain Maps Movement

13 years, I have seen very little that is useful in proprioception recovery. What is your doctor's protocol to recover proprioception?

proprioception (67 posts to March 2011)

Deciphering Proprioception: How the Brain Maps Movement

Summary: A new study reveals the mechanisms behind proprioception, our body’s innate ability to sense limb position and movement, critical for movement without visual cues. Utilizing musculoskeletal simulations and neural network models, researchers have advanced our understanding of how the brain integrates sensory data from muscle spindles to perceive bodily position and motion.

This study suggests that the brain prioritizes limb position and velocity in processing proprioceptive input. The findings, which could revolutionize neuroprosthetics, demonstrate the importance of task-driven modeling in uncovering the computational principles underlying sensory processing.

Key Facts:

Innovative Approach to Proprioception: The study employed musculoskeletal modeling and neural network models to simulate naturalistic muscle spindle signals, offering new insights into how the brain perceives limb position and movement.
Task-Driven Neural Network Models: By training neural network models on computational tasks reflecting proprioceptive processing, researchers found that predicting limb position and velocity were key tasks that shaped “brain-like” representations.
Implications for Neuroprosthetics: Understanding proprioceptive processing at this level opens new possibilities for enhancing neuroprosthetic design, aiming for more natural and intuitive limb control.

Source: EPFL

How does your brain know the position and movement of your different body parts? The sense is known as proprioception, and it is something like a “sixth sense”, allowing us to move freely without constantly watching our limbs.

Proprioception involves a complex network of sensors embedded in our muscles that relay information about limb position and movement back to our brain. However, little is known about how the brain puts together the different signals it receives from muscles.

A new study led by Alexander Mathis at EPFL now sheds light on the question by exploring how our brains create a cohesive sense of body position and movement. Published in Cell, the study was carried out by PhD students Alessandro Marin Vargas, Axel Bisi, and Alberto Chiappa, with experimental data from Chris Versteeg and Lee Miller at Northwestern University.

“It is widely believed that sensory systems should exploit the statistics of the world and this theory could explain many properties of the visual and auditory system,” says Mathis. “To generalize this theory to proprioception, we used musculoskeletal simulators to compute the statistics of the distributed sensors.”

The researchers used this musculoskeletal modeling to generate muscle spindle signals in the upper limb to generate a collection of “large-scale, naturalistic movement repertoire”.

They then used this repertoire to train thousands of “task-driven” neural network models on sixteen computational tasks, each of which reflects a scientific hypothesis about the computations carried out by the proprioceptive pathway, which includes parts of the brainstem and somatosensory cortex.

The approach allowed the team to comprehensively analyse how different neural network architectures and computational tasks influence the development of “brain-like” representations of proprioceptive information.

They found that neural network models trained on tasks that predict limb position and velocity were most effective, suggesting that our brains prioritize integrating the distributed muscle spindle input to understand body movement and position.

The research highlights the potential of task-driven modeling in neuroscience. Unlike traditional methods that focus on predicting neural activity directly, task-driven models can offer insights into the underlying computational principles of sensory processing.

The research also paves the way for new experimental avenues in neuroscience, since a better understanding of proprioceptive processing could lead to significant advancements in neuroprosthetics, with more natural and intuitive control of artificial limbs.