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Infants are experts at playing, with an amazing ability to generate novel structured behaviors in unstructured environments that lack clear extrinsic reward signals. We seek to replicate some of these abilities with a neural network that…

Machine Learning · Computer Science 2018-02-22 Nick Haber , Damian Mrowca , Li Fei-Fei , Daniel L. K. Yamins

The adaptive learning capabilities seen in biological neural networks are largely a product of the self-modifying behavior emerging from online plastic changes in synaptic connectivity. Current methods in Reinforcement Learning (RL) only…

Neural and Evolutionary Computing · Computer Science 2020-06-16 Samuel Schmidgall

Social behavior across animal species ranges from simple pairwise interactions to thousands of individuals coordinating goal-directed movements. Regardless of the scale, these interactions are governed by the interplay between multimodal…

Neurons and Cognition · Quantitative Biology 2024-08-06 Sarah Josephine Stednitz , Andrew Lesak , Adeline L Fecker , Peregrine Painter , Phil Washbourne , Luca Mazzucato , Ethan K Scott

With the increasing acquisition of large-scale neural recordings comes the challenge of inferring the computations they perform and understanding how these give rise to behavior. Here, we review emerging conceptual and technological…

Neurons and Cognition · Quantitative Biology 2019-06-25 Simon Musall , Anne Urai , David Sussillo , Anne Churchland

Humans and animals have a rich and flexible understanding of the physical world, which enables them to infer the underlying dynamical trajectories of objects and events, plausible future states, and use that to plan and anticipate the…

Artificial Intelligence · Computer Science 2023-10-26 Aran Nayebi , Rishi Rajalingham , Mehrdad Jazayeri , Guangyu Robert Yang

Neurofeedback is a form of brain training in which subjects are fed back information about some measure of their brain activity which they are instructed to modify in a way thought to be functionally advantageous. Over the last twenty…

Neurons and Cognition · Quantitative Biology 2018-05-15 David Papo

Recurrent neural network-based reinforcement learning systems are capable of complex motor control tasks such as locomotion and manipulation, however, much of their underlying mechanisms still remain difficult to interpret. Our aim is to…

Robotics · Computer Science 2023-06-29 Eugene R. Rush , Christoffer Heckman , Kaushik Jayaram , J. Sean Humbert

Humans sometimes have an insight that leads to a sudden and drastic performance improvement on the task they are working on. Sudden strategy adaptations are often linked to insights, considered to be a unique aspect of human cognition tied…

Artificial Intelligence · Computer Science 2024-03-04 Anika T. Löwe , Léo Touzo , Paul S. Muhle-Karbe , Andrew M. Saxe , Christopher Summerfield , Nicolas W. Schuck

Settlement of marine larvae on a substrate is a fundamental problem of marine life. The probability of settlement is one of the quantitative characteristic of the settlement process. The probability of larval contact with a substrate is the…

Biological Physics · Physics 2015-11-11 Gregory Zilman , Julia Novak , Alex Liberzon , Shimrit Perkol-Finkel , Yehuda Benayahu

Behavioral changes in animals and humans, as a consequence of an error or a verbal instruction, can be extremely rapid. Improvement in behavioral performances are usually associated in machine learning and reinforcement learning to synaptic…

Neurons and Cognition · Quantitative Biology 2025-03-12 Cristiano Capone , Luca Falorsi

In nature, active matter, such as worms or dogs, tend to spontaneously form a stable rotational cluster when they flock to the same food source on an unregulated and unconfined surface. {In this paper we present an $n$-node flexible active…

Soft Condensed Matter · Physics 2023-08-21 Gaoxiao Jiang , Zhihong You , Rui Ma , Chen-Xu Wu

Adaptive behavior is mainly the result of adaptive brains. We go a step beyond and claim that the brain does not only adapt to its surrounding reality but rather, it builds itself up to constructs its own reality. That is, rather than just…

Neural and Evolutionary Computing · Computer Science 2016-08-09 Fernando Corbacho

Cognitive control is a suite of processes that helps individuals pursue goals despite resistance or uncertainty about what to do. Although cognitive control has been extensively studied as a dynamic feedback loop of perception, valuation,…

We hypothesize that curiosity is a mechanism found by evolution that encourages meaningful exploration early in an agent's life in order to expose it to experiences that enable it to obtain high rewards over the course of its lifetime. We…

Machine Learning · Computer Science 2020-03-12 Ferran Alet , Martin F. Schneider , Tomas Lozano-Perez , Leslie Pack Kaelbling

Place cells in the rat hippocampus play a key role in creating the animal's internal representation of the world. During active navigation, these cells spike only in discrete locations, together encoding a map of the environment.…

Neurons and Cognition · Quantitative Biology 2016-03-22 Yuri Dabaghian

We study in this paper the effect of an unique initial stimulation on random recurrent networks of leaky integrate and fire neurons. Indeed given a stochastic connectivity this so-called spontaneous mode exhibits various non trivial…

Neural and Evolutionary Computing · Computer Science 2007-05-23 H. Soula , G. Beslon , O. Mazet

Latest insights from biology show that intelligence not only emerges from the connections between neurons but that individual neurons shoulder more computational responsibility than previously anticipated. This perspective should be…

Machine Learning · Computer Science 2024-03-19 Quentin Delfosse , Patrick Schramowski , Martin Mundt , Alejandro Molina , Kristian Kersting

Reading is a pervasive and cognitively demanding activity that underpins modern human culture. It is a prime instance of a class of tasks where eye movements are coordinated for the purpose of comprehension. Existing theories explain either…

Human-Computer Interaction · Computer Science 2026-03-09 Yunpeng Bai , Xiaofu Jin , Shengdong Zhao , Antti Oulasvirta

Recurrent neural networks are powerful tools for understanding and modeling computation and representation by populations of neurons. Continuous-variable or "rate" model networks have been analyzed and applied extensively for these…

Neurons and Cognition · Quantitative Biology 2016-01-29 Brian DePasquale , Mark M. Churchland , L. F. Abbott

The emergence of vision catalysed a pivotal evolutionary advancement, enabling organisms not only to perceive but also to interact intelligently with their environment. This transformation is mirrored by the evolution of robotic systems,…

Robotics · Computer Science 2025-03-06 Yuhang Hu , Jiong Lin , Hod Lipson
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