The Evolution of Chunks in Sequence Learning

Published on April 12, 2022

Learning complex sequences is like arranging puzzle pieces into cohesive patterns. In a study with Guinea baboons, researchers investigated the process of chunking in sequence learning. Chunking refers to how we break down long sequences into smaller, more manageable parts. The baboons were trained to perform a specific sequence of movements on a touch screen, and the researchers found that over time, the chunks of the sequence changed. Some chunks became longer, while others merged together. These findings challenge current theories of how we learn and organize sequences. By understanding how chunking evolves, we can gain insights into how our brains process and optimize complex tasks. To dive deeper into this fascinating research, check out the full article!

Abstract
Chunking mechanisms are central to several cognitive processes and notably to the acquisition of visuo-motor sequences. Individuals segment sequences into chunks of items to perform visuo-motor tasks more fluidly, rapidly, and accurately. However, the exact dynamics of chunking processes in the case of extended practice remain unclear. Using an operant conditioning device, 18 Guinea baboons (Papio papio) produced a fixed sequence of nine movements during 1000 trials by pointing to a moving target on a touch screen. Response times analyses revealed a specific chunking pattern of the sequence for each baboon. More importantly, we found that these patterns evolved during the course of the experiment, with chunks becoming progressively fewer and longer. We identified two chunk reorganization mechanisms: the recombination of preexisting chunks and the concatenation of two distinct chunks into a single one. These results provide new evidence on chunking mechanisms in sequence learning and challenge current models of associative and statistical learning.

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