Learning outside the box

Learning a new skill, whether it is riding a bicycle or playing chess, usually requires at least several days of practice if not much more. Due to experimental limitations, however, most neuroscience studies that attempt to unveil the neural representations of skill learning explore tasks that can be learned within much shorter time scales, a few hours at most. Therefore, the neural substrates of long-term learning remain poorly understood. An intriguing important question is why some tasks can be learned within hours, whereas other tasks require longer-term practice. Oby et al. (1) tackle this challenge by using a brain−computer interface (BCI) approach combined with chronic neural recordings. Although, originally, BCI was used to demonstrate the feasibility of designing neural prostheses (2, 3), a clever exploitation of this technique can help to discover properties of the neural code and how it changes during learning. In this study, they show that new patterns of neural activity emerge with long-term learning—patterns that were not previously observed in the neural population they measured. Some of these new patterns enable the longer-term learning.A common paradigm to study motor control is the arm reaching paradigm in which primates move a manipulandum to control the location of a cursor on the screen, while neurons are recorded in motor regions of the brain. Although this paradigm has led to many successful discoveries about how neurons represent directional movements and new motor skills (4, 5), it remains unclear why some skills can be acquired within minutes or hours, whereas other skills require a much lengthier learning process that lasts days or weeks. A BCI paradigm, as used here, is one that directly links the changes in the monkey brain, namely the patterns of neural activity, with the desired outcome—the moving of a cursor to a desired … [↵][1]1To whom correspondence may be addressed. Email: rony.paz{at}weizmann.ac.il. [1]: #xref-corresp-1-1