Chunking as a function of sequence length.

Chunking mechanisms are central to several cognitive processes. During the acquisition of visuo-motor sequences, it is commonly reported that these sequences are segmented into chunks leading to more fluid, rapid, and accurate performances. The question of a chunk's storage capacity has been often investigated but little is known about the dynamics of chunk size evolution relative to sequence length. In two experiments, we studied the dynamics and the evolution of a sequence's chunking pattern as a function of sequence length in a non-human primate species (Guinea baboons, Papio papio). Using an operant conditioning device, baboons had to point on a touch screen to a moving target. In Experiment 1, they had to produce repeatedly the same sequence of 4 movements during 2000 trials. In Experiment 2, the sequence was composed of 5 movements and was repeated 4000 times. For both lengths, baboons initially produced small chunks that became fewer and longer with practice. Moreover, the dynamics and the evolution of the chunking pattern varied as a function of sequence length. Finally, with extended practice (i.e., more than 2000 trials), we observed that the mean chunk size reached a plateau indicating that there are fundamental limits to chunking processes that also depend on sequence length. These data therefore provide new empirical evidence for understanding the general properties of chunking mechanisms in sequence learning.

Simple questions on simple associations: regularity extraction in non-human primates.

When human and non-human animals learn sequences, they manage to implicitly extract statistical regularities through associative learning mechanisms. In two experiments conducted with a non-human primate species (Guinea baboons, Papio papio), we addressed simple questions on the learning of simple AB associations appearing in longer noisy sequences. Using a serial reaction time task, we manipulated the position of AB within the sequence, such that it could be either fixed (by appearing always at the beginning, middle, or end of a four-element sequence; Experiment 1) or variable (Experiment 2). We also tested the effect of sequence length in Experiment 2 by comparing the performance on AB when it was presented at a variable position within a sequence of four or five elements. The slope of RTs from A to B was taken for each condition as a measurement of learning rate. While all conditions differed significantly from a no-regularity baseline, we found strong evidence that the learning rate did not differ between the conditions. These results indicate that regularity extraction is not impacted by the position of the regularity within a sequence and by the length of the sequence. These data provide novel general empirical constraints for modeling associative mechanisms in sequence learning.

The dynamics of chunking in humans (Homo sapiens) and Guinea baboons (Papio papio).

Chunking is an important cognitive process allowing the compression of information in short-term memory. The aim of this study is to compare the dynamics of chunking during the learning of a visuomotor sequence in humans (Homo sapiens) and Guinea baboons (Papio papio). We duplicated in humans an experimental paradigm that has been used previously in baboons. On each trial, human participants had to point to a moving target on a touch screen. The experiment involved the repetition of the same sequence of nine items over a 1,000 trials. To reproduce as much as possible the conditions under which baboons performed the task, human participants were tested at their own pace. Results revealed that baboons and humans shared similar chunking dynamics: In both species, the sequence was initially parsed into small chunks that became longer and fewer with practice through two reorganization mechanisms (recombinations and concatenations). Differences were also observed regarding the global decrease in response times that was faster and more pronounced in humans compared with baboons. Analyses of these similarities and differences provide new empirical evidence for understanding the general properties of chunking mechanisms in sequence learning and its evolution across species. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Detecting non-adjacent dependencies is the exception rather than the rule.

Statistical learning refers to our sensitivity to the distributional properties of our environment. Humans have been shown to readily detect the dependency relationship of events that occur adjacently in a stream of stimuli but processing non-adjacent dependencies (NADs) appears more challenging. In the present study, we tested the ability of human participants to detect NADs in a new Hebb-naming task that has been proposed recently to study regularity detection in a noisy environment. In three experiments, we found that most participants did not manage to extract NADs. These results suggest that the ability to learn NADs in noise is the exception rather than the rule. They provide new information about the limits of statistical learning mechanisms.

The Evolution of Chunks in Sequence Learning.

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.

Learning Higher-Order Transitional Probabilities in Nonhuman Primates.

The extraction of cooccurrences between two events, A and B, is a central learning mechanism shared by all species capable of associative learning. Formally, the cooccurrence of events A and B appearing in a sequence is measured by the transitional probability (TP) between these events, and it corresponds to the probability of the second stimulus given the first (i.e., p(B|A)). In the present study, nonhuman primates (Guinea baboons, Papio papio) were exposed to a serial version of the XOR (i.e., exclusive-OR), in which they had to process sequences of three stimuli: A, B, and C. In this manipulation, first-order TPs (i.e., AB and BC) were uninformative due to their transitional probabilities being equal to .5 (i.e., p(B|A) = p(C|B) = .5), while second-order TPs were fully predictive of the upcoming stimulus (i.e., p(C|AB) = 1). In Experiment 1, we found that baboons were able to learn second-order TPs, while no learning occurred on first-order TPs. In Experiment 2, this pattern of results was replicated, and a final test ruled out an alternative interpretation in terms of proximity to the reward. These results indicate that a nonhuman primate species can learn a nonlinearly separable problem such as the XOR. They also provide fine-grained empirical data to test models of statistical learning on the interaction between the learning of different orders of TPs. Recent bioinspired models of associative learning are also introduced as promising alternatives to the modeling of statistical learning mechanisms.

Detection of regularities in a random environment.

Regularity detection, or statistical learning, is regarded as a fundamental component of our cognitive system. To test the ability of human participants to detect regularity in a more ecological situation (i.e., mixed with random information), we used a simple letter-naming paradigm in which participants were instructed to name single letters presented one at a time on a computer screen. The regularity consisted of a triplet of letters that were systematically presented in that order. Participants were not told about the presence of this regularity. A variable number of random letters were presented between two repetitions of the regular triplet, making this paradigm similar to a Hebb repetition task. Hence, in this Hebb-naming task, we predicted that if any learning of the triplet occurred, naming times for the predictable letters in the triplet would decrease as the number of triplet repetitions increased. Surprisingly, across four experiments, detection of the regularity only occurred under very specific experimental conditions and was far from a trivial task. Our study provides new evidence regarding the limits of statistical learning and the critical role of contextual information in the detection (or not) of repeated patterns.