Search Results for author: Dimitrios Pantazis

Found 7 papers, 1 papers with code

An F-ratio-Based Method for Estimating the Number of Active Sources in MEG

1 code implementation9 Jun 2023 Amita Giri, John C. Mosher, Amir Adler, Dimitrios Pantazis

Overall, when tuned for optimal selection of thresholds, our method offers researchers a precise tool to estimate the true number of active brain sources and accurately model brain function.

Anatomy

The dual-path hypothesis for the emergence of anosognosia in Alzheimer's disease

no code implementations11 Feb 2023 Katia Andrade, Thomas Guiyesse, Takfarinas Medani, Etienne Koechlin, Dimitrios Pantazis, Bruno Dubois

Proceeding from the notion of anosognosia as a dimensional syndrome, ranging from the lack of concern about one's own deficits (i. e., anosodiaphoria) to the complete lack of awareness of deficits, our hypothesis states that (i) unawareness of deficits would result from a failure in the error-monitoring system, whereas (ii) anosodiaphoria would more likely result from an imbalance between emotional processing and error-monitoring systems.

Brain Source Localization by Alternating Projection

no code implementations2 Feb 2022 Amir Adler, Mati Wax, Dimitrios Pantazis

We present a novel solution to the problem of localizing magnetoencephalography (MEG) and electroencephalography (EEG) brain signals.

EEG Electroencephalogram (EEG)

MEG Source Localization via Deep Learning

no code implementations1 Dec 2020 Dimitrios Pantazis, Amir Adler

We present a deep learning solution to the problem of localization of magnetoencephalography (MEG) brain signals.

A Graph Gaussian Embedding Method for Predicting Alzheimer's Disease Progression with MEG Brain Networks

no code implementations8 May 2020 Mengjia Xu, David Lopez Sanz, Pilar Garces, Fernando Maestu, Quanzheng Li, Dimitrios Pantazis

Characterizing the subtle changes of functional brain networks associated with the pathological cascade of Alzheimer's disease (AD) is important for early diagnosis and prediction of disease progression prior to clinical symptoms.

Deep Neural Networks predict Hierarchical Spatio-temporal Cortical Dynamics of Human Visual Object Recognition

no code implementations12 Jan 2016 Radoslaw M. Cichy, Aditya Khosla, Dimitrios Pantazis, Antonio Torralba, Aude Oliva

The complex multi-stage architecture of cortical visual pathways provides the neural basis for efficient visual object recognition in humans.

Object Recognition

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