Prefrontal cortex contribution in transitive inference task through the interplay of beta and gamma oscillations DOI Creative Commons
Fabio Di Bello,

Valentina Mione,

Pierpaolo Pani

и другие.

Communications Biology, Год журнала: 2024, Номер 7(1)

Опубликована: Дек. 31, 2024

Transitive inference allows people to infer new relations between previously experienced premises. It has been hypothesized that this logical thinking relies on a mental schema spatially organizes elements, facilitating inferential insights. However, recent evidence challenges the need for these complex cognitive processes. To dig into neural substrate driving TI processes, we examine role of beta and gamma local field potential bands in prefrontal cortex 2 monkeys. During problem-solving period, discover tight link modulation complexity. This correlation diminishes its strength before initiating motor response, indicating chosen item. Notably, while band maintains constant relationship with performance throughout trial, shows flexible relationship. research highlights interplay computations when solving problems.

Язык: Английский

A mathematical theory of relational generalization in transitive inference DOI Creative Commons
Samuel Lippl, Kenneth Kay, Greg Jensen

и другие.

Proceedings of the National Academy of Sciences, Год журнала: 2024, Номер 121(28)

Опубликована: Июль 5, 2024

Humans and animals routinely infer relations between different items or events generalize these to novel combinations of items. This allows them respond appropriately radically circumstances is fundamental advanced cognition. However, how learning systems (including the brain) can implement necessary inductive biases has been unclear. We investigated transitive inference (TI), a classic relational task paradigm in which subjects must learn relation ( A > B C ) it new ). Through mathematical analysis, we found that broad range biologically relevant models (e.g. gradient flow ridge regression) perform TI successfully recapitulate signature behavioral patterns long observed living subjects. First, with item-wise additive representations automatically encode relations. Second, for more general representations, single scalar “conjunctivity factor” determines model behavior on and, further, principle norm minimization (a standard statistical bias) enables fixed, partly conjunctive transitively. Finally, neural networks “rich regime,” representation improves generalization many tasks, unexpectedly show poor anomalous TI. find such form (over hidden weights) yields local encoding mechanism lacking transitivity. Our findings minimal principles give rise classical bias (transitivity), explain empirically behaviors, establish formal approach understanding basis abstraction.

Язык: Английский

Процитировано

5

Neural mechanisms of relational learning and fast knowledge reassembly in plastic neural networks DOI
Thomas Miconi, Kenneth Kay

Nature Neuroscience, Год журнала: 2025, Номер unknown

Опубликована: Янв. 15, 2025

Язык: Английский

Процитировано

0

An active neural mechanism for relational learning and fast knowledge reassembly DOI Creative Commons
Thomas Miconi, Kenneth Kay

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2023, Номер unknown

Опубликована: Июль 28, 2023

How do we gain general insights from limited novel experiences? Humans and animals have a striking ability to learn relationships between experienced items, enabling efficient generalization rapid assimilation of new information. One fundamental instance such relational learning is transitive inference (learn

Язык: Английский

Процитировано

2

Neural dynamics of robust legged robots DOI Creative Commons
Eugene R. Rush, Christoffer Heckman, Kaushik Jayaram

и другие.

Frontiers in Robotics and AI, Год журнала: 2024, Номер 11

Опубликована: Апрель 18, 2024

Legged robot control has improved in recent years with the rise of deep reinforcement learning, however, much underlying neural mechanisms remain difficult to interpret. Our aim is leverage bio-inspired methods from computational neuroscience better understand activity robust locomotion controllers. Similar past work, we observe that terrain-based curriculum learning improves agent stability. We study biomechanical responses and within our network controller by simultaneously pairing physical disturbances targeted ablations. identify an agile hip reflex enables regain its balance recover lateral perturbations. Model gradients are employed quantify relative degree various sensory feedback channels drive this reflexive behavior. also find recurrent dynamics implicated behavior, utilize sampling-based ablation these key neurons. framework combines model-based for drawing causal relationships between embodied

Язык: Английский

Процитировано

0

Transitive inference as probabilistic preference learning DOI
Francesco Mannella, Giovanni Pezzulo

Psychonomic Bulletin & Review, Год журнала: 2024, Номер unknown

Опубликована: Окт. 22, 2024

Язык: Английский

Процитировано

0

Learning to infer transitively: serial ordering on a mental line in premotor cortex DOI Creative Commons
Sofia Raglio, Gabriele Di Antonio, Emiliano Brunamonti

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Окт. 29, 2024

ABSTRACT Transitive inference (TI) is a form of deductive reasoning that allows to infer unknown relationships among premises. It hypothesized this cognitive task accomplished by mapping stimuli onto linear workspace, referred as the ‘mental line,’ based on their arbitrarily assigned ranks. However, open questions remain: does mental line have neural correlate, and if so, where how it represented learned in brain? In study, we investigate role monkeys’ dorsal premotor cortex (PMd) encoding during acquisition item relationships. Our findings provide evidence TI can be solved through transformation representations ranked items. We show PMd multi-unit activity organizes along theoretically informed direction, implementing geometrical solution effectively explains animal behavior. results suggest plays crucial integrating into ‘geometric symbolic distance (i.e., rank difference) between items influences related motor decisions. Furthermore, observe an ongoing learning process characterized rotation line, which aligns manifold plan unfolds. This elucidates cortical optimization strategy statistical structure task.

Язык: Английский

Процитировано

0

Prefrontal cortex contribution in transitive inference task through the interplay of beta and gamma oscillations DOI Creative Commons
Fabio Di Bello,

Valentina Mione,

Pierpaolo Pani

и другие.

Communications Biology, Год журнала: 2024, Номер 7(1)

Опубликована: Дек. 31, 2024

Transitive inference allows people to infer new relations between previously experienced premises. It has been hypothesized that this logical thinking relies on a mental schema spatially organizes elements, facilitating inferential insights. However, recent evidence challenges the need for these complex cognitive processes. To dig into neural substrate driving TI processes, we examine role of beta and gamma local field potential bands in prefrontal cortex 2 monkeys. During problem-solving period, discover tight link modulation complexity. This correlation diminishes its strength before initiating motor response, indicating chosen item. Notably, while band maintains constant relationship with performance throughout trial, shows flexible relationship. research highlights interplay computations when solving problems.

Язык: Английский

Процитировано

0