Learning to Program “Recycles” Preexisting Frontoparietal Population Codes of Logical Algorithms

Computer programming is a cornerstone of modern society, yet little is known about how the human brain enables this recently invented cultural skill. According to the neural recycling hypothesis, cultural skills (e.g., reading, math) repurpose preexisting neural "information maps." Alternatively, such maps could emerge de novo during learning, as they do in artificial neural networks. Representing and manipulating logical algorithms, such as "for" loops and "if" conditionals, is key to programming. Are representations of these algorithms acquired when people learn to program? Alternatively, do they predate instruction and get "recycled"? College students (<i>n</i> = 22, 11 females and 11 males) participated in a functional magnetic resonance imaging study before and after their first programming course (Python) and completed a battery of behavioral tasks. After a one-semester Python course, reading Python functions (relative to working memory control) activated an independently localized left-lateralized frontoparietal reasoning network. This same network was already engaged by pseudocode, plain English descriptions of Python, even before the course. Critically, multivariate population codes in this frontoparietal network distinguished "for" loops and "if" conditional algorithms, both before and after. Representational similarity analysis revealed shared information in the frontoparietal network before and after instruction. Programming recycles preexisting representations of logical algorithms in frontoparietal cortices, supporting the recycling framework of cultural skill acquisition.