Associative vocabulary learning: development and testing of two paradigms for the (re-) acquisition of action- and object-related words
Graph Chatbot
Chattez avec Graph Search
Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.
AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.
How do animals learn to repeat behaviors that lead to the obtention of food or other “rewarding” objects? As a biologically plausible paradigm for learning in spiking neural networks, spike-timing dependent plasticity (STDP) has been shown to perform well ...
This paper describes the design of a robot agent and associated learning algorithms to help children in handwriting acquisition. The main issue lies in how to program a robot to obtain human-like handwriting and then exploit it to teach children. We propos ...
In healthy young subjects, the brain derived neurotropic factor (BDNF) val(66)met polymorphism negatively affects behavioural outcome in short-term motor cortex or hippocampus-based learning paradigms. In repetitive training paradigms over several days thi ...
The complexity of processes occurring in the brain is an intriguing issue not just for scientists and medical doctors, but the humanity in general. The cortex ability to perceive and analyze an enormous amount of information in an instance of time, the par ...
Computational models have played a central role in the debate over language learnability. This article discusses how they have been used in different stances, from generative views to more recently introduced explanatory frameworks based on embodiment, cog ...
We investigate generic models for cortical microcircuits, i.e., recurrent circuits of integrate-and-fire neurons with dynamic synapses. These complex dynamic systems subserve the amazing information processing capabilities of the cortex, but are at the pre ...
Current theoretical positions assume that action-related word meanings are established by functional connections between perisylvian language areas and the motor cortex (MC) according to Hebb's associative learning principle. To test this assumption, we pr ...
memory in biological neural networks. Similarly, artificial neural networks could benefit from modulatory dynamics when facing certain types of learning problem. Here we test this hypothesis by introducing modulatory neurons to enhance or dampen neural pla ...
Reinforcement learning in neural networks requires a mechanism for exploring new network states in response to a single, nonspecific reward signal. Existing models have introduced synaptic or neuronal noise to drive this exploration. However, those types o ...
Artificial neural networks are applied to many real-world problems, ranging from pattern classification to robot control. In order to design a neural network for a particular task, the choice of an architecture (including the choice of a neuron model), and ...
