首页|Researchers at Air Force Research Laboratory Zero in on Brain-Based Devices (Transitioning from global to local computational strategies during brain-machine in terface learning)
Researchers at Air Force Research Laboratory Zero in on Brain-Based Devices (Transitioning from global to local computational strategies during brain-machine in terface learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Investigators discuss new findings in brain-based devices. According to news originatingfrom Dayton, Ohio, by NewsRx correspondents, research stated, “When learning to use a brain-machineinterface (BMI), the brain modulates neuronal activity patterns, exploring and exploiting the state spacedefined by their neural manifold.”Financial supporters for this research include National Institutes of Health.The news correspondents obtained a quote from the research from Air Force Resear ch Laboratory:“Neurons directly involved in BMI control (i.e., direct neurons) can display marked changes in their firingpatterns during BMI learning. However , the extent of firing pattern changes in neurons not directlyinvolved in BMI c ontrol (i.e., indirect neurons) remains unclear. To clarify this issue, we local ized directand indirect neurons to separate hemispheres in a task designed to b ilaterally engage these hemisphereswhile animals learned to control the positio n of a platform with their neural signals. Animals that learnedto control the p latform and improve their performance in the task shifted from a global strategy , whereboth direct and indirect neurons modified their firing patterns, to a lo cal strategy, where only directneurons modified their firing rate, as animals b ecame expert in the task. Animals that did not learn theBMI task did not shift from utilizing a global to a local strategy.”
Air Force Research LaboratoryDaytonOhioUnited StatesNorth and Central AmericaBrain-machine InterfaceEmerging TechnologiesMachine Learning
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