This next post builds upon last week’s about the Brain Computer Interface, that was used with Rhesus Monkeys, so that's why we have our image for this week of MONKEY, who's thinking!
The researchers hypothesized that new learning leads to new connections within brains, and that’s exactly what they proved! They monitored 90 neural units within those monkey’s brains, while the monkeys were moving a computer cursor – yes, monkeys can do that!
So, they were able to map the connections between those neural circuits during this activity – this was their pretest, or baseline, recording the existing neural connections. Next, the scientists provided several sessions of practice along with coaching, so a lot like what happens in classrooms with practice and guidance on feedback of student performance…
Notice, this was SEVERAL sessions of practice, not just a one-off lesson – several sessions. This was followed by a week of practice, so deliberate independent practice by the monkeys on this newly learned task.
After the learning sessions, and week of practice, the scientists again took measures of the neuronal connections in those same 90 neural units. Comparing these new mappings with their baseline maps, they found new patterns. Their conclusion is that these new neuronal patterns were enabling the monkeys to continually improve their skills, so their accuracy and speed with the computer cursor!
One of the scientists, Aaron Batista said “These findings suggest that the process for humans to master a new skill might also involve the generation of new neural activity patterns.”
This is likely one of the first scientific experiments to show this connection between neuronal patterns and learned behaviours.
Another researcher in this study, Steven Chase, stated that “if we can look directly at the brain during motor learning, we believe we can design neurofeedback strategies that facilitate the process that leads to the formation of new neural activity patterns."
This opens the door to supporting learning in many different ways, some of them quite challenging if this is to be used with humans? Who knows where this will lead? Maybe one day, this will support people to learn to read – until then, we are left with using explicit instruction in both decoding and comprehension, and we are more confident that we are actually changing our students’ brain connections in these learning processes.
Emily R. Oby, Matthew D. Golub, Jay A. Hennig, Alan D. Degenhart, Elizabeth C. Tyler-Kabara, Byron M. Yu, Steven M. Chase, Aaron P. Batista. New neural activity patterns emerge with long-term learning. Proceedings of the National Academy of Sciences, 2019; 201820296 DOI: 10.1073/pnas.1820296116