Discovering Implied Serial Order Through Model-Free and Model-Based Learning

Jensen, Greg; Terrace, H. S.; Ferrera, Vincent P.

doi:10.3389/fnins.2019.00878

Cited by 21 publications

(49 citation statements)

References 65 publications

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“…Monkeys were able to demonstrate a SDE during learning of 5-item lists using TI, and using the simultaneous chaining paradigm (D'Amato and Colombo, 1990;Jensen et al, 2013). SDEs emerge as an automatic consequence of TI when learning lists that are specified as a one-dimensional spatial continuum and on which feedback is represented by a fuzzy distribution (Jensen et al, 2019). These results suggest that if humans treat the Category TI similarly to monkeys, then human performance in the Category TI condition should resemble that seen in the Standard TI condition.…”

Section: Discussionmentioning

confidence: 99%

Category learning in a transitive inference paradigm

et al. 2021

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The implied order of a ranked set of visual images can be learned by transitive inference, without reliance on stimulus features that explicitly signal their order. Such learning is difficult to explain by associative mechanisms but can be accounted for by cognitive representations and processes such as transitive inference. Our study seeks to determine if those representations may be applied to categories of images without explicit verbal instruction. Specifically, we asked whether participants can (a) infer that images being presented belonged to familiar categories, even when every image presented during every trial is unique, and (b) perform transitive inferences about the ordering of those categories. To address these questions, we compared the performance of humans during a standard TI task, which used the same set of images throughout the session, to performance in a category TI tasks, which drew images from a set of categories. Each of the images used in the category TI task was only presented once, limiting the extent to which stimulus-outcome associations could be learned. Participants were able to learn the order of the categories based on transitive inference. However, participants in the category TI condition did not produce a symbolic distance effect. These findings collectively suggest that differing cognitive processes may underpin serial learning when learning about specific stimuli versus stimulus categories.

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Section: Discussionmentioning

confidence: 99%

Category learning in a transitive inference paradigm

et al. 2021

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“…A related unknown is whether mice can use transitive reasoning to infer dimensional, explicitly transitive relationships (e.g., size) without extended training. Humans and non-human primates can employ similar cognitive mechanisms in feedback-trained transitive inference tasks to those used to evaluate explicitly transitive relationships [2, 12, 53, 99]. An ethologically relevant example for mice is social dominance, where mice form consistent linear dominance hierarchies that exhibit triangle transitivity [107].…”

Section: Discussionmentioning

confidence: 99%

Mutations in neuroligin-3 in male mice impact behavioral flexibility but not relational memory in a touchscreen test of visual transitive inference

et al. 2019

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Cognitive dysfunction including disrupted behavioral flexibility is central to neurodevelopmental disorders such as Autism Spectrum Disorder (ASD). A cognitive measure that assesses relational memory, and the ability to flexibly assimilate and transfer learned information is transitive inference. Transitive inference is highly conserved across vertebrates and disrupted in cognitive disorders. Here, we examined how mutations in the synaptic cell-adhesion molecule neuroligin-3 (Nlgn3) that have been documented in ASD impact relational memory and behavioral flexibility. We first refined a rodent touchscreen assay to measure visual transitive inference, then assessed two mouse models of Nlgn3 dysfunction (Nlgn3−/y and Nlgn3R451C). Deep analysis of touchscreen behavioral data at a trial level established we could measure trajectories in flexible responding and changes in processing speed as cognitive load increased. We show that gene mutations in Nlgn3 do not disrupt relational memory, but significantly impact flexible responding. Our study presents the first analysis of reaction times in a rodent transitive inference test, highlighting response latencies from the touchscreen system are useful indicators of processing demands or decision-making processes. These findings expand our understanding of how dysfunction of key components of synaptic signaling complexes impact distinct cognitive processes disrupted in neurodevelopmental disorders, and advance our approaches for dissecting rodent behavioral assays to provide greater insights into clinically relevant cognitive symptoms.

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“…d, same as c, for neighbouring item pairs. The winner/loser asymmetries described so far might be explained by alternative learning biases, such as asymmetric learning weights for chosen vs. unchosen items 37 . Given abovechance performance, the chosen item will statistically be more likely to be the winning item.…”

Section: Partial Feedbackmentioning

confidence: 97%

Asymmetric learning facilitates human inference of transitive relations

Ciranka

Linde-Domingo

Padezhki

et al. 2021

Preprint

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Humans and other animals are capable of inferring never-experienced relations (e.g., A>C) from other relational observations (e.g., A>B and B>C). The processes behind such transitive inference are subject to intense research. Here, we demonstrate a new aspect of relational learning, building on previous evidence that transitive inference can be accomplished through simple reinforcement learning mechanisms. We show in simulations that inference of novel relations benefits from an asymmetric learning policy, where observers update only their belief about the winner (or loser) in a pair. Across 4 experiments (n=145), we find substantial empirical support for such asymmetries in inferential learning. The learning policy favoured by our simulations and experiments gives rise to a compression of values which is routinely observed in psychophysics and behavioural economics. In other words, a seemingly biased learning strategy that yields well-known cognitive distortions can be beneficial for transitive inferential judgments.

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Discovering Implied Serial Order Through Model-Free and Model-Based Learning

Cited by 21 publications

References 65 publications

Category learning in a transitive inference paradigm

Category learning in a transitive inference paradigm

Mutations in neuroligin-3 in male mice impact behavioral flexibility but not relational memory in a touchscreen test of visual transitive inference

Asymmetric learning facilitates human inference of transitive relations

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