With aging, it is natural that cognitive and motor functions decline, affecting independent living and the quality of life. For many years, many methods have been sought to slow or reverse these effects. Brain stimulation to enhance cognitive skills is one such methodology. Recent research has proved that the learning ability of a person, and not his or her age, decides how well he or she can respond to various techniques for brain stimulation.
A research team from EPFL headed by Friedhelm Hummel researched how native learning abilities can modulate the effects of anodal transcranial direct current stimulation- at DCS. This non-invasive technique applies low electrical currents to the brain via electrodes put on the head. “It became apparent that people who have less effective learning ability benefitted from brain stimulation whereas those people who already had effective strategies did not benefit, or even did worse,” said Friedhelm Hummel of EPFL.
Knowing Brain Stimulation
Non-invasive brain stimulation includes all techniques used for changing brain activity without surgical means or implants. In a range of studies, numerous techniques have been investigated. Such as DCS, which applies a constant flow of electric current through the head, thus changing neuronal activity. Whereas some studies show promising results, other research methods show that atDCS can have very variable effects: some people respond very well, whereas others do not. While researchers have considered age a determining factor, the new study places more importance on learning ability.
Study Design
The study had 40 participants divided into two age groups: 20 middle-aged adults between the ages of 50 and 65, and 20 older adults over the age of 65. Each group was further divided into those receiving active atDCS and those receiving a placebo. Participants practiced a finger-tapping task designed to measure motor learning over ten days. The goal was to replicate a numerical sequence on a keypad as quickly and accurately as possible.
The researchers, therefore, administered a machine-learning model previously trained with publicly available data to classify participants for their learning ability. Participants were classified into “optimal” versus “suboptimal” learners based on this model after initial performance. The aim was to explore who would benefit from the brain stimulation based on their ability to learn quickly in the performance of the task.
Key Findings
The study found that the participants who were initially “suboptimal” learners-that is, struggled early on in learning the task- showed a significant improvement in accuracy when receiving atDCS. Those with “optimal” learning strategies, however, did not benefit from at DCS. And, in some cases, even showed a decline in performance.
This would suggest that the benefits of brain stimulation could be different depending on the initial stages of learning. Whereas for participants performing poorly, atDCS restored motor learning. This effect was absent in participants who already showed a more efficient learning strategy and even disrupted performance by stimulation.
Future Directions
This now opens new avenues for individualized brain stimulation treatment, from broad factors like age. To the consideration of the ability of a person to learn during the design of stimulation protocols. Presumably, this might make treatments more effective, especially in the context of neurorehabilitation. Patients recovering from brain injuries, such as strokes or traumatic brain injuries. May have their recovery improved by personalization of brain stimulation treatments based on their specific learning capabilities.
ANI