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.

Thursday, April 7, 2016

Motor learning tied to intelligent control of sensory neurons in muscles

This seems to be a slightly different way of stating that better sensation leads to better motor recovery as written by Margaret Yekutiel in the book, Sensory Re-Education of the Hand After Stroke in 2001.
So why the fuck don't we have a stroke protocol on this? 15 years and NOTHING has been publicly put out there for survivors to find and use. 
http://www.alphagalileo.org/ViewItem.aspx?ItemId=162606&CultureCode=en 
31 March 2016 Umeå universitet
Sensory neurons in human muscles provide important information used for the perception and control of movement. Learning to move in a novel context also relies on the brain’s independent control of these sensors, not just of muscles, according to a new study published in the journal Current Biology.
Each muscle can have tens or hundreds of encapsulated sensory receptors, and these “sensors” are called muscle spindles. Spindles differ from other sensory receptors as they also receive nerve fibers from the central nervous system itself, which acts to control spindle output.
There are more nerve fibers travelling to and from spindles than to the actual muscle tissues generating force and powering movement. Despite more than a hundred years of research on this class of sensory receptors, however, it has been unclear how, why and when the nervous system chooses to independently control spindles.
“The findings strongly point to independent control of these sensors during motor learning,” says Dr. Michael Dimitriou, who conducted the study and is a researcher at the Department of Integrative Medical Biology at Umeå University in Sweden.
In this study, Dr. Dimitriou monitored spindle signals in humans while they learned to control the position of a visual cursor by moving their hand (much like using a computer mouse). Depending on what stage in the learning process, the spindles sent very different signals in response to virtually identical movements.
The research shows that the sensory capability of spindle neurons was adjusted according to the ongoing requirements of the task being learned. In other words, muscle spindle signal patterns were changed during the learning process to become selectively informative about different aspects of movement.
“It is well-known that effective extraction of information is a major component in good learning performance, and this is true in motor adaptation as well. Richer and more relevant sensory information from spindles allows for efficient update of the computational circuits in our brain that guide movement. Differing levels of skill in controlling muscle sensors is probably a factor defining individual differences in motor learning performance,” says Dr. Dimitriou.
Beyond increased understanding of how human motor learning works, the current findings may also have more practical implications, such as in prosthetic limb and robotics control, argues Michael Dimitriou:
“To use a common example, computer algorithms can easily defeat a human in a game of chess. However, even the most sophisticated robot cannot match the skill and dexterity of a child in moving pieces on the chessboard. Better understanding of human sensory control is a way forward.”
http://dx.doi.org/10.1016/j.cub.2016.02.030

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