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Dimitrios Pantazis

Researcher at McGovern Institute for Brain Research

Publications -  135
Citations -  8448

Dimitrios Pantazis is an academic researcher from McGovern Institute for Brain Research. The author has contributed to research in topics: Magnetoencephalography & Visual cortex. The author has an hindex of 30, co-authored 119 publications receiving 6642 citations. Previous affiliations of Dimitrios Pantazis include Massachusetts Institute of Technology & University of Southern California.

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Brainstorm: a user-friendly application for MEG/EEG analysis

TL;DR: Brainstorm as discussed by the authors is a collaborative open-source application dedicated to magnetoencephalography (MEG) and EEG data visualization and processing, with an emphasis on cortical source estimation techniques and their integration with anatomical magnetic resonance imaging (MRI) data.
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Resolving human object recognition in space and time

TL;DR: This work acquired human magnetoencephalography and functional magnetic resonance imaging responses to 92 object images and identified transient and persistent neural activities during object processing with sources in V1 and IT.
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Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence

TL;DR: It was shown that the DNN captured the stages of human visual processing in both time and space from early visual areas towards the dorsal and ventral streams and provided an algorithmically informed view on the spatio-temporal dynamics of visual object recognition in the human visual brain.
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Framework for the Statistical Shape Analysis of Brain Structures using SPHARM-PDM

TL;DR: This manuscript presents a comprehensive set of tools for the computation of 3D structural statistical shape analysis, which has been applied in several studies on brain morphometry, but can potentially be employed in other 3D shape problems.
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Autism as a disorder of prediction

TL;DR: The hypothesis that some salient aspects of the autism phenotype may be manifestations of an underlying impairment in predictive abilities has the potential of providing unifying insights into multiple aspects of autism, with attendant benefits for improving diagnosis and therapy.