Publication

Characterization of reliability of spike timing in spinal interneurons during oscillating inputs

Publications associées (34)

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

Taming neuronal noise with large networks

Valentin Marc Schmutz

How does reliable computation emerge from networks of noisy neurons? While individual neurons are intrinsically noisy, the collective dynamics of populations of neurons taken as a whole can be almost deterministic, supporting the hypothesis that, in the br ...

EPFL2022

RMSSD Is More Sensitive to Artifacts Than Frequency-Domain Parameters: Implication in Athletes? Monitoring

Jean-Marc Vesin, Grégoire Millet, Sasan Yazdani

Easy-to-use and accurate heart rate variability (HRV) assessments are essential in athletes??? follow-up, but artifacts may lead to erroneous analysis. Artifact detection and correction are the purpose of extensive literature and implemented in dedicated a ...

JOURNAL SPORTS SCIENCE & MEDICINE2022

Clustering and control for adaptation uncovers time-warped spike time patterns in cortical networks in vivo

James Bryden Isbister

How information in the nervous system is encoded by patterns of action potentials (i.e. spikes) remains an open question. Multi-neuron patterns of single spikes are a prime candidate for spike time encoding but their temporal variability requires further c ...

2021

, ,

While most models of randomly connected neural networks assume single-neuron models with simple dynamics, neurons in the brain exhibit complex intrinsic dynamics over multiple timescales. We analyze how the dynamical properties of single neurons and recurr ...

2019

Understanding ultrasound neuromodulation using a computationally efficient and interpretable model of intramembrane cavitation

Silvestro Micera, Esra Neufeld, Théo Lemaire

Objective. Low-intensity focused ultrasound stimulation (LIFUS) emerges as an attracting technology for noninvasive modulation of neural circuits, yet the underlying action mechanisms remain unclear. The neuronal intramembrane cavitation excitation (NICE) ...

2019

Inferring and validating mechanistic models of neural microcircuits based on spike-train data

Olivier Richard Hagens

The interpretation of neuronal spike train recordings often relies on abstract statistical models that allow for principled parameter estimation and model selection but provide only limited insights into underlying microcircuits. In contrast, mechanistic m ...

2019

Visual masking in Schizophrenia: an endophenotype and its neural correlates

Michael Herzog, Maya Roinishvili, Ophélie Gladys Favrod

Objective: In visual backward masking, a target is followed by a mask, which deteriorates performance on the target. Masking is a very sensitive endophenotype for schizophrenia. Patients and their siblings (to a lesser extent) show strong performance defic ...

2019

, ,

Neural population equations such as neural mass or field models are widely used to study brain activity on a large scale. However, the relation of these models to the properties of single neurons is unclear. Here we derive an equation for several interacti ...

Public Library of Science2017

, ,

Various time- and frequency-based approaches have been proposed to measure baroreflex sensitivity. All these methods are block-based ones. This study proposes a novel instantaneous measure of baroreflex sensitivity that enables the investigation of frequen ...

2017

Cognitive neuroscience has seen rapid growth in the size and complexity of data recorded from the human brain as well as in the computational tools available to analyze this data. This data explosion has resulted in an increased use of multivariate, model- ...

Frontiers Media Sa2017