The chunking dynamics of long sequence learning in human and non-human primates

Les primates humains et non-humains sont exposés dans leur environnement à un flux continu d’informations séquentielles. Afin de structurer ce flux, le système cognitif est capable de repérer les patterns d’événements invariants et d’organiser en conséquence des séquences d’actions planifiées. L’apprentissage statistique désigne la capacité de nos systèmes cognitifs à extraire les régularités de l’environnement et repose sur des mécanismes associatifs Hebbien, communs aux primates humains et non-humains. Par ailleurs, en raison de la capacité limitée de la mémoire de travail, lorsque les régularités prennent la forme d’une longue séquence d’informations, celle-ci doit être segmentée en des paquets d’informations, appelés chunks, pour être compressée et exécutée plus rapidement et efficacement. Le présent travail s’intéresse aux dynamiques de l’apprentissage de séquences et du chunking. Nous nous sommes intéressés à la formation des chunks durant l’apprentissage de séquences visuo-motrices, à leurs évolutions lors d’une pratique intensive, et à l’impact de la taille de ces séquences sur le chunking. Par ailleurs, nous avons cherché à comprendre le rôle de l’apprentissage associatif, commun aux primates non-humains et aux humains, et le rôle d’habiletés spécifiques aux humains, comme le langage, dans l’apprentissage de ces séquences. Nous avons donc contrasté les résultats obtenus chez des primates non-humains, babouins de Guinée (Papio papio), à ceux de primates humains (Homo sapiens). Ces résultats nous informent sur les mécanismes de chunking dans l'apprentissage de séquences et remettent en question les modèles computationnels actuels d'apprentissage statistique.Human and non-human primates are exposed in their environment to a continuous stream of sequential information. To structure this flow, the cognitive system is able to identify patterns of invariant events and organize sequences of planned actions accordingly. Statistical learning refers to the ability of our cognitive systems to extract regularities from the environment and is based on Hebbian associative mechanisms, common to human and non-human primates. Furthermore, due to the limited capacity of working memory, when the regularities take the form of a long sequence of information, this sequence must be segmented into packets of information, called chunks, to be compressed and executed more quickly and efficiently.This work focuses on the dynamics of sequence learning and chunking. We were interested in the formation of chunks during the learning of visuo-motor sequences, in their evolution during intensive practice, and in the impact of the size of these sequences on chunking. In addition, we sought to understand the role of associative learning, common to non-human primates and humans, and the role of human-specific skills, such as language, in the learning of these sequences. We therefore contrasted the results obtained in non-human primates, Guinea baboons (Papio papio), with those of human primates (Homo sapiens). These results inform us about chunking mechanisms in sequence learning and challenge current computational models of statistical learning

Sequence Learning and Chunk Stability in Guinea Baboons (Papio papio) Apprentissage de séquence et stabilité des chunks chez les babouins de Guinée (Papio papio)

International audienceChunking mechanisms, the processes of grouping several items together into a single processing unit, are central to several cognitive processes in human and non-human primates and notably to the acquisition of visuomotor sequences. Individuals segment sequences into chunks to perform visuomotor tasks more fluidly, rapidly, and accurately. Using an operant conditioning device, we previously studied the precise mechanisms by which chunks are formed and reorganized during sequence learning. Eighteen Guinea baboons (Papio papio) repeatedly produced the same fixed sequence of nine movements during 1,000 trials by pointing to a moving target on a touch screen. We found that chunking patterns are reorganized during the course of learning, with chunks becoming progressively fewer and longer. We also identified two forms of reorganization of the chunking pattern: the recombination of preexisting chunks and the concatenation of two distinct chunks into a single one. To understand the conditions under which these reorganizations occur, we study here how the stability of a chunk and the stability of chunk boundaries are related to these reorganizations. Our analyses showed that less stable chunks and less stable boundaries are more likely to produce reorganizations. These results provide new evidence about the fine- grained dynamics of chunking mechanisms during sequence learning.Les mécanismes de chunking, processus par lesquels plusieurs items sont regroupés pour former une unité fonctionnelle, sont centraux dans de nombreux processus cognitifs chez les primates humains et non-humains, et particulièrement lors de l’acquisition de séquences visuomotrices. Les individus segmentent les séquences en chunks pour réaliser les tâches visuomotrices plus fluidement, rapidement et précisément. L’utilisation d‘un système de conditionnement automatique nous a précédemment permis d’étudier les mécanismes précis par lesquels ces chunks sont formés et réorganisés durant l’apprentissage de séquences. Dix-huit babouins de Guinée (Papio papio) ont répété la même séquence fixe de neuf mouvements durant 1000 essais lors d’une tâche de pointage d’une cible mouvante sur écran tactile. Nous avons constaté que les patterns de chunking sont réorganisés au cours de l'apprentissage, les chunks devenant progressivement moins nombreux et plus longs. Nous avons également identifié deux formes de réorganisation du pattern de chunking : la recombinaison de chunks préexistants et la concaténation de deux chunks distincts en un seul. Pour comprendre les conditions dans lesquelles ces réorganisations se produisent, nous étudions ici comment la stabilité d'un chunk et la stabilité des frontières entre chunks sont liées à ces réorganisations. Nos analyses montrent que les chunks et les frontières moins stables sont les plus susceptibles de produire des réorganisations. Ces résultats apportent de nouvelles informations sur la dynamique fine des mécanismes de chunking au cours de l'apprentissage de séquences

The Dynamics of Chunking in Humans (Homo sapiens) and Guinea baboons (Papio papio)

International audienceChunking 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 visuo-motor 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 9-items over a thousand 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 to 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

The Dynamics of Chunking in Humans (Homo sapiens) and Guinea baboons (Papio papio)

International audienceChunking 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 visuo-motor 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 9-items over a thousand 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 to 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

The Evolution of Chunks in Sequence Learning

International audienceChunking 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, eighteen Guinea baboons (Papio papio) produced a fixed sequence of nine movements during 1,000 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

Chunking as a function of sequence length

International audienceChunking 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

CHUNKING AND ASSOCIATIVE LEARNING IN NON-HUMAN PRIMATES

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

International audienceStatistical 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

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

International audienceWhen 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