Publication

Homeostasis and Learning through Spike-Timing Dependent Plasticity

Publications associées (53)

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.

Connectez-vous pour utiliser Chat avec Graph Search

, , , ,

Neuromorphic computing takes inspiration from the brain to build highly parallel, energy- and area-efficient architectures. Recently, hardware realizations of neurons and synapses using memristive devices were proposed and applied for the task of correlati ...

Ieee-Inst Electrical Electronics Engineers Inc2017

Theory of representation learning in cortical neural networks

Carlos Stein Naves de Brito

Our brain continuously self-organizes to construct and maintain an internal representation of the world based on the information arriving through sensory stimuli. Remarkably, cortical areas related to different sensory modalities appear to share the same f ...

EPFL2016

Learning spatio-temporal patterns in the presence of input noise using phase-change memristors

Stanislaw Andrzej Wozniak, Evangelos Eleftheriou, Angeliki Pantazi

Neuromorphic systems increasingly attract research interest owing to their ability to provide biologically inspired methods of computing, alternative to the classic von Neumann architecture. In these systems, computing relies on spike-based communication b ...

2016

The development of sensory receptive fields has been modeled in the past by a variety of models including normative models such as sparse coding or independent component analysis and bottom-up models such as spike-timing dependent plasticity or the Bienen- ...

Public Library of Science2016

Does computational neuroscience need new synaptic learning paradigms?

Wulfram Gerstner, Johanni Michael Brea

Computational neuroscience is dominated by a few paradigmatic models, but it remains an open question whether the existing modelling frameworks are sufficient to explain observed behavioural phenomena in terms of neural implementation. We take learning and ...

Elsevier Science Bv2016

Adaptation of short-term plasticity parameters via error-driven learning may explain the correlation between activity-dependent synaptic properties, connectivity motifs and target specificity

Michele Giugliano, Eleni Vasilaki

The anatomical connectivity among neurons has been experimentally found to be largely non-random across brain areas. This means that certain connectivity motifs occur at a higher frequency than would be expected by chance. Of particular interest, short-ter ...

Frontiers Research Foundation2015

, , ,

Bursts of activity in networks of neurons are thought to convey salient information and drive synaptic plasticity. Here we report that network bursts also exert a profound effect on Spike-Timing-Dependent Plasticity (STDP). In acute slices of juvenile rat ...

2015

Our brain has the capacity to analyze a visual scene in a split second, to learn how to play an instrument, and to remember events, faces and concepts. Neurons underlie all of these diverse functions. Neurons, cells within the brain that generate and trans ...

EPFL2014

Recent experimental data from the rodent cerebral cortex and olfactory bulb indicate that specific connectivity motifs are correlated with short-term dynamics of excitatory synaptic transmission. It was observed that neurons with short-term facilitating sy ...

Public Library of Science2014

Dynamics of self-sustained asynchronous-irregular activity in random networks of spiking neurons with strong synapses

Marc-Oliver Gewaltig

Random networks of integrate-and-fire neurons with strong current-based synapse scan, unlike previously believed, assume stable states of sustained asynchronous and irregular firing, even without external random background or pacemaker neurons. We analyze ...

Frontiers Research Foundation2014