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pro vyhledávání: '"Quoy, Mathias"'
In the last three decades it has become clear that cortical regions, interconnected via white-matter fibers, form a modular and hierarchical network. This organization, which has also been seen at the microscopic level in the form of interconnected n
Externí odkaz:
http://arxiv.org/abs/2405.18587
In a large variety of systems (biological, physical, social etc.), synchronization occurs when different oscillating objects tune their rhythm when they interact with each other. The different underlying network defining the connectivity properties a
Externí odkaz:
http://arxiv.org/abs/2303.03099
In this article, we propose a variational inference formulation of auto-associative memories, allowing us to combine perceptual inference and memory retrieval into the same mathematical framework. In this formulation, the prior probability distributi
Externí odkaz:
http://arxiv.org/abs/2210.08013
As a phenomenon in dynamical systems allowing autonomous switching between stable behaviors, chaotic itinerancy has gained interest in neurorobotics research. In this study, we draw a connection between this phenomenon and the predictive coding theor
Externí odkaz:
http://arxiv.org/abs/2106.08937
In this work, we build upon the Active Inference (AIF) and Predictive Coding (PC) frameworks to propose a neural architecture comprising a generative model for sensory prediction, and a distinct generative model for motor trajectories. We highlight h
Externí odkaz:
http://arxiv.org/abs/2104.09163
Autor:
Pitti, Alexandre, Quoy, Mathias, Lavandier, Catherine, Boucenna, Sofiane, Swaileh, Wassim, Weidmann, Claudio
In order to keep trace of information and grow up, the infant brain has to resolve the problem about where old information is located and how to index new ones. We propose that the immature prefrontal cortex (PFC) use its primary functionality of det
Externí odkaz:
http://arxiv.org/abs/2005.11203
In this article, we apply the Free-Energy Principle to the question of motor primitives learning. An echo-state network is used to generate motor trajectories. We combine this network with a perception module and a controller that can influence its d
Externí odkaz:
http://arxiv.org/abs/2005.05151
Akademický článek
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Publikováno v:
In Neural Networks January 2020 121:242-258
The aim of the present paper is to study the effects of Hebbian learning in random recurrent neural networks with biological connectivity, i.e. sparse connections and separate populations of excitatory and inhibitory neurons. We furthermore consider
Externí odkaz:
http://arxiv.org/abs/0706.2602