New York, Sep 30 (IANS) Researchers have developed a brain prosthesis that can replace or support a damaged part of the brain and help people with memory loss problems form memories as efficiently as any other person.
The prosthesis, which includes a small array of electrodes implanted into the brain, has performed well in laboratory testing in animals and is currently being evaluated in human patients.
The device that relies on a new algorithm was designed originally at University of Southern California and tested at Wake Forest Baptist Medical Centre in North Carolina.
The researchers explained that when your brain receives the sensory input, it creates a memory in the form of a complex electrical signal that travels through multiple regions of the hippocampus, the memory centre of the brain.
At each region, the signal is re-encoded until it reaches the final region as a wholly different signal that is sent off for long-term storage.
If there is damage at any region that prevents this translation, then there is the possibility that long-term memory will not be formed.
That is why an individual with hippocampal damage (for example, due to Alzheimer’s disease) can recall events from a long time ago – things that were already translated into long-term memories before the brain damage occurred – but have difficulty forming new long-term memories.
Song and Berger found a way to accurately mimic how a memory is translated from short-term memory into long-term memory, using data obtained first from animals, and then from humans.
The prosthesis is designed to bypass a damaged hippocampal section and provide the next region with the correctly translated memory.
That is despite the fact that there is currently no way of “reading” a memory just by looking at its electrical signal.
“It is like being able to translate from Spanish to French without being able to understand either language,” said Ted Berger from USC Viterbi School of Engineering.
In hundreds of trials conducted with nine patients, the new algorithm accurately predicted how the signals would be translated with about 90 percent accuracy.
The research was presented at the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society in Milan, Italy.
