A new study has discovered why learning tasks can be easier said than done.
Neural engineers from the Center for the Neural Basis of Cognition (CNBC), a joint program between the University of Pittsburgh and Carnegie Mellon University, have discovered a fundamental constraint in the brain that may explain why this happens.
They have found for the first time that there were constraints on how adaptable the brain was during learning and that the constraints were key determinant for whether a new skill would be easy or difficult to learn. Understanding the ways in which the brain's activity can be 'flexed' during learning could eventually be used to develop better treatments for stroke and other brain injuries.
For the study, the research team trained animals to use a brain-computer interface (BCI), similar to ones that have shown recent promise in clinical trials for assisting tetraplegics and amputees.
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The researchers recorded neural activity in the motor cortex and directed the recordings into a computer, which translated the activity into movement of a cursor on the computer screen. The subjects' goal was to move the cursor to targets on the screen, which required them to generate the patterns of neural activity that the experimenters had requested. If the subjects could move the cursor well, that meant that they had learned to generate the neural activity pattern that the researchers had specified.
The researchers found that their subjects learned to generate some neural activity patterns more easily than others, since they only sometimes achieved accurate cursor movements. The harder-to-learn patterns were different from any of the pre-existing patterns, whereas the easier-to-learn patterns were combinations of pre-existing brain patterns. Because the existing brain patterns likely reflected how the neurons were interconnected, the results suggest that the connectivity among neurons shapes learning.
The study is published in Nature.