Analytic Sensing For Multi-Layer Spherical Models With Application To EEG Source Imaging

À propos
Confidentialité
Mentions légales

Graph Chatbot

Publications associées (31)

Segmenting electroencephalography wires reduces radiofrequency shielding artifacts in simultaneous electroencephalography and functional magnetic resonance imaging at 7 T

Rolf Gruetter, João Pedro Forjaco Jorge, Thanh Phong Kevin Lê, Özlem Ipek

Purpose: Simultaneous scalp electroencephalography and functional magnetic resonance imaging (EEG-fMRI) enable noninvasive assessment of brain function with high spatial and temporal resolution. However, at ultra-high field, the data quality of both modali ...

Wiley2022

Microscopic field theory for structure formation in systems of self-propelled particles with generic torques

Ignacio Pagonabarraga Mora, Elena Sesé Sansa

We derive a dynamical field theory for self-propelled particles subjected to generic torques and forces by explicitly coarse-graining their microscopic dynamics, described by a many-body Fokker-Planck equation. The model includes both intrinsic torques ind ...

AIP Publishing2022

M2D2: Maximum-Mean-Discrepancy Decoder for Temporal Localization of Epileptic Brain Activities

David Atienza Alonso, Amir Aminifar, Alireza Amirshahi, Anthony Hitchcock Thomas

Recent years have seen growing interest in leveraging deep learning models for monitoring epilepsy patients based on electroencephalographic (EEG) signals. However, these approaches often exhibit poor generalization when applied outside of the setting in w ...

2022

Computation Complexity Reduction Technique for Accurate Seizure Detection Implants

Alexandre Schmid, Keyvan Farhang Razi

An automatic seizure detection method from high-resolution intracranial-EEG (iEEG) signals is presented to minimize the computational complexity and realize real-time accurate seizure detection for biomedical implants. Complex signal processing on a large ...

IEEE2022

Exploring the spatial resolution of TMS-EEG coupling on the sensorimotor region

Sylvain Jean-François Harquel, Estelle Emeline Raffin

The use of TMS-EEG coupling as a neuroimaging tool for the functional exploration of the human brain recently gained strong interest. If this tool directly inherits the fine temporal resolution from EEG, its spatial counterpart remains unknown. In this stu ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2022

Identifying uncertainty states during wayfinding in indoor environments: An EEG classification Study

Mahsa Shoaran, Bingzhao Zhu

The researchers used a machine-learning classification approach to better understand neurological features associated with periods of wayfinding uncertainty. The participants (n = 30) were asked to complete wayfinding tasks of varying difficulty in a virtu ...

ELSEVIER SCI LTD2022

An Efficient Sampling Algorithm for Non-smooth Composite Potentials

Nicolas Henri Bernard Flammarion

We consider the problem of sampling from a density of the form p(x) ? exp(-f (x) - g(x)), where f : Rd-+ R is a smooth function and g : R-d-+ R is a convex and Lipschitz function. We propose a new algorithm based on the Metropolis-Hastings framework. Under ...

Microtome Publishing2022

Epileptic Seizure Detection With Patient-Specific Feature and Channel Selection for Low-power Applications

Alexandre Schmid, Keyvan Farhang Razi

An accurate epileptic seizure detector using intracranial electroencephalography (iEEG) recordings, suitable for low-power wearable/implantable applications, is presented. Eleven time-domain features with low hardware complexity are employed in the feature ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Generalization Error Bounds Via Rényi-, f-Divergences and Maximal Leakage

Michael Christoph Gastpar, Ibrahim Issa, Amedeo Roberto Esposito

In this work, the probability of an event under some joint distribution is bounded by measuring it with the product of the marginals instead (which is typically easier to analyze) together with a measure of the dependence between the two random variables. ...

2021

Is there an analog of Nesterov acceleration for gradient-based MCMC?

Xiang Cheng, Nicolas Henri Bernard Flammarion

We formulate gradient-based Markov chain Monte Carlo (MCMC) sampling as optimization on the space of probability measures, with Kullback-Leibler (KL) divergence as the objective functional. We show that an under-damped form of the Langevin algorithm perfor ...

2021

Exploring MEG brain fingerprints: Evaluation, pitfalls, and interpretations

Dimitri Nestor Alice Van De Ville, Alessandra Griffa, Enrico Amico, Sélima Zahar, Ekansh Sareen

Individual characterization of subjects based on their functional connectome (FC), termed “FC fingerprinting”, has become a highly sought-after goal in contemporary neuroscience research. Recent functional magnetic resonance imaging (fMRI) studies have dem ...

2021

Page 2 sur 2