Lucas C. Parra

76 papers B 3Journal 50Unranked 21
YearRankTypeTitle / Venue / Authors
2025 J jnl
Cross-site Validation of AI Segmentation and Harmonization in Breast MRI.
J. Imaging Inform. Medicine
Yu Huang, Nicholas J. Leotta, Lukas Hirsch, Roberto Lo Gullo, Mary Hughes, Jeffrey Reiner, Nicole B. Saphier, Kelly S. Myers, Babita Panigrahi, Emily Ambinder, Philip Di Carlo, Lars J. Grimm, Dorothy Lowell, Sora Yoon, Sujata V. Ghate, Lucas C. Parra, Elizabeth J. Sutton
2025 J jnl
Effect of explanation videos on learning: The role of attention and academic performance.
Educ. Inf. Technol.
Melanie V. Adler, Jens Madsen, James Hedberg, Richard Steinberg, Lucas C. Parra
2025 J jnl
Full-Head Segmentation of MRI with Abnormal Brain Anatomy: Model and Data Release.
CoRR
Andrew M. Birnbaum, Adam Buchwald, Peter Turkeltaub, Adam Jacks, Yu Huang, Abhishek Datta, Lucas C. Parra, Lukas Hirsch
2024 J jnl
Real-time estimation of overt attention from dynamic features of the face using deep-learning.
CoRR
Aimar Silvan Ortubay, Lucas C. Parra, Jens Madsen
2024 J jnl
Recurrent Joint Embedding Predictive Architecture with Recurrent Forward Propagation Learning.
CoRR
Osvaldo Matías Velarde, Lucas C. Parra
2024 J jnl
Robustness of Deep Networks for Mammography: Replication Across Public Datasets.
J. Imaging Inform. Medicine
Osvaldo Matías Velarde, Clarissa Lin, Sarah Eskreis-Winkler, Lucas C. Parra
2024 J jnl
The Role of Fibration Symmetries in Geometric Deep Learning.
CoRR
Osvaldo Matías Velarde, Lucas C. Parra, Paolo Boldi, Hernán A. Makse
2023 J jnl
Architecture of the brain's visual system enhances network stability and performance through layers, delays, and feedback.
PLoS Comput. Biol.
Osvaldo Matías Velarde, Hernán A. Makse, Lucas C. Parra
2022 J jnl
Deep Learning Achieves Neuroradiologist-Level Performance in Detecting Hydrocephalus Requiring Treatment.
J. Digit. Imaging
Yu Huang, Raquel Moreno, Rachna Malani, Alicia Meng, Nathaniel C. Swinburne, Andrei I. Holodny, Ye Choi, Henry Rusinek, James B. Golomb, Ajax George, Lucas C. Parra, Robert J. Young
2020 J jnl
Deep learning achieves radiologist-level performance of tumor segmentation in breast MRI.
CoRR
Lukas Hirsch, Yu Huang, Shaojun Luo, Carolina Rossi Saccarelli, Roberto Lo Gullo, Isaac Daimiel Naranjo, Almir Galvão Vieira Bitencourt, Natsuko Onishi, Eun Sook Ko, Dortis Leithner, Daly Avendano, Sarah Eskreis-Winkler, Mary Hughes, Danny F. Martinez, Katja Pinker, Krishna Juluru, Amin E. El-Rowmeim, Pierre Elnajjar, Hedvig Hricak, Elizabeth A. Morris, Hernán A. Makse, Lucas C. Parra, Elizabeth J. Sutton
2020 J jnl
Functional connectivity of EEG is subject-specific, associated with phenotype, and different from fMRI.
NeuroImage
Maximilian Nentwich, Lei Ai, Jens Madsen, Qawi K. Telesford, Stefan Haufe, Michael P. Milham, Lucas C. Parra
2019 J jnl
Inherent physiological artifacts in EEG during tDCS.
NeuroImage
Nigel Gebodh, Zeinab Esmaeilpour, Devin Adair, Kenneth Chelette, Jacek Dmochowski, Adam J. Woods, Emily S. Kappenman, Lucas C. Parra, Marom Bikson
2019 J jnl
Multiway canonical correlation analysis of brain data.
NeuroImage
Alain de Cheveigné, Giovanni M. Di Liberto, Dorothée Arzounian, Daniel D. E. Wong, Jens Hjortkjær, Søren Asp Fuglsang, Lucas C. Parra
2019 J jnl
Tissue segmentation with deep 3D networks and spatial priors.
CoRR
Lukas Hirsch, Yu Huang, Lucas C. Parra
2018 J jnl
Correlated Components Analysis - Extracting Reliable Dimensions in Multivariate Data.
CoRR
Lucas C. Parra, Stefan Haufe, Jacek P. Dmochowski
2018 J jnl
Elucidating relations between fMRI, ECoG, and EEG through a common natural stimulus.
NeuroImage
Stefan Haufe, Paul DeGuzman, Simon Henin, Michael Arcaro, Christopher J. Honey, Uri Hasson, Lucas C. Parra
2018 J jnl
Extracting multidimensional stimulus-response correlations using hybrid encoding-decoding of neural activity.
NeuroImage
Jacek P. Dmochowski, Jason J. Ki, Paul DeGuzman, Paul Sajda, Lucas C. Parra
2018 — conf
Optimized tDCS for Targeting Multiple Brain Regions: An Integrated Implementation.
EMBC
Yu Huang, Chris Thomas, Abhishek Datta, Lucas C. Parra
2018 — conf
ROAST: An Open-Source, Fully-Automated, Realistic Volumetric-Approach-Based Simulator For TES.
EMBC
Yu Huang, Abhishek Datta, Marom Bikson, Lucas C. Parra
2017 J jnl
Optimal use of EEG recordings to target active brain areas with transcranial electrical stimulation.
NeuroImage
Jacek P. Dmochowski, Laurent Koessler, Anthony M. Norcia, Marom Bikson, Lucas C. Parra
2016 J jnl
Measuring engagement in a classroom: Synchronised neural recordings during a video presentation.
CoRR
Andreas Trier Poulsen, Simon Kamronn, Jacek Dmochowski, Lucas C. Parra, Lars Kai Hansen
2016 J jnl
The New York Head - A precise standardized volume conductor model for EEG source localization and tES targeting.
NeuroImage
Yu Huang, Lucas C. Parra, Stefan Haufe
2015 J jnl
Neural Correlates of Perceived Confidence in a Partial Report Paradigm.
J. Cogn. Neurosci.
Martín Graziano, Lucas C. Parra, Mariano Sigman
2014 — conf
Bayesian correlated component analysis for inference of joint EEG activation.
PRNI
Andreas Trier Poulsen, Simon Kamronn, Lucas C. Parra, Lars Kai Hansen
2014 J jnl
Evoked Neural Responses to Events in Video.
IEEE J. Sel. Top. Signal Process.
Daniel Rosenthal, Paul DeGuzman, Lucas C. Parra, Paul Sajda
2014 J jnl
Imaging artifacts induced by electrical stimulation during conventional fMRI of the brain.
NeuroImage
Andrea Antal, Marom Bikson, Abhishek Datta, Belen Lafon, Peter Dechent, Lucas C. Parra, Walter Paulus
2014 J jnl
Joint decorrelation, a versatile tool for multichannel data analysis.
NeuroImage
Alain de Cheveigné, Lucas C. Parra
2013 J jnl
Origins of power-law degree distribution in the heterogeneity of human activity in social networks
CoRR
Lev Muchnik, Sen Pei, Lucas C. Parra, Saulo D. S. Reis, José S. Andrade Jr., Shlomo Havlin, Hernán A. Makse
2013 — conf
Spatial projections of neural arrays: A short guide to classic and new signal analysis techniques.
BCI
Lucas C. Parra, Jacek P. Dmochovski, Joao Dias, Alain de Cheveigné
2013 J jnl
Subject position affects EEG magnitudes.
NeuroImage
Justin K. Rice, Christopher Rorden, Jessica S. Little, Lucas C. Parra
2013 J jnl
Targeted transcranial direct current stimulation for rehabilitation after stroke.
NeuroImage
Jacek P. Dmochowski, Abhishek Datta, Yu Huang, Jessica D. Richardson, Marom Bikson, Julius Fridriksson, Lucas C. Parra
2013 J jnl
Transcranial Electrical Stimulation Accelerates Human Sleep Homeostasis.
PLoS Comput. Biol.
Davide Reato, Fernando Gasca, Abhishek Datta, Marom Bikson, Lisa Marshall, Lucas C. Parra
2012 — conf
A pilot study on effects of 4×1 High-Definition tDCS on motor cortex excitability.
EMBC
Egas M. Caparelli-Daquer, Trelawny J. Zimmermann, Eric Mooshagian, Lucas C. Parra, Justin K. Rice, Abhishek Datta, Marom Bikson, Eric M. Wassermann
2012 — conf
An automated method for high-definition transcranial direct current stimulation modeling.
EMBC
Yu Huang, Yuzhuo Su, Christopher Rorden, Jacek Dmochowski, Abhishek Datta, Lucas C. Parra
2012 J jnl
Computational model of neuron-astrocyte interactions during focal seizure generation.
Frontiers Comput. Neurosci.
Davide Reato, Mario Cammarota, Lucas C. Parra, Giorgio Carmignoto
2012 — conf
On the role of electric field orientation in optimal design of transcranial current stimulation.
EMBC
Jacek P. Dmochowski, Marom Bikson, Abhishek Datta, Jessica D. Richardson, Julius Fridriksson, Lucas C. Parra
2012 — conf
Simultaneous and proportional control of 2D wrist movements with myoelectric signals.
MLSP
Janne Mathias Hahne, Hubertus Rehbaum, Felix Bießmann, Frank C. Meinecke, Klaus-Robert Müller, Ning Jiang, Dario Farina, Lucas C. Parra
2010 — ch.
Cortically-Coupled Computer Vision.
Brain-Computer Interfaces
Paul Sajda, Eric Pohlmeyer, Jun Wang, Barbara Hanna, Lucas C. Parra, Shih-Fu Chang
2010 J jnl
In a Blink of an Eye and a Switch of a Transistor: Cortically Coupled Computer Vision.
Proc. IEEE
Paul Sajda, Eric Pohlmeyer, Jun Wang, Lucas C. Parra, Christoforos Christoforou, Jacek Dmochowski, Barbara Hanna, Claus Bahlmann, Maneesh Kumar Singh, Shih-Fu Chang
2010 J jnl
Maximum Likelihood in Cost-Sensitive Learning: Model Specification, Approximations, and Upper Bounds.
J. Mach. Learn. Res.
Jacek P. Dmochowski, Paul Sajda, Lucas C. Parra
2010 J jnl
Second-Order Bilinear Discriminant Analysis.
J. Mach. Learn. Res.
Christoforos Christoforou, Robert M. Haralick, Paul Sajda, Lucas C. Parra
2009 J jnl
On the Maximization of Information Flow Between Spiking Neurons.
Neural Comput.
Lucas C. Parra, Jeffrey M. Beck, Anthony J. Bell
2008 — conf
Adaptive Template Matching with Shift-Invariant Semi-NMF.
NIPS
Jonathan Le Roux, Alain de Cheveigné, Lucas C. Parra
2008 J jnl
Spatiotemporal Linear Decoding of Brain State.
IEEE Signal Process. Mag.
Lucas C. Parra, Christoforos Christoforou, Adam C. Gerson, Mads Dyrholm, An Luo, Mark Wagner, Marios G. Philiastides, Paul Sajda
2007 J jnl
Bilinear Discriminant Component Analysis.
J. Mach. Learn. Res.
Mads Dyrholm, Christoforos Christoforou, Lucas C. Parra
2007 — conf
Second Order Bilinear Discriminant Analysis for single trial EEG analysis.
NIPS
Christoforos Christoforou, Paul Sajda, Lucas C. Parra
2006 — conf
Amplification of small electric fields by neurons; implications for spike timing.
EMBC
Thomas Radman, Lucas C. Parra, Marom Bikson
2006 B conf
Classifying Single-Trial ERPs from Visual and Frontal Cortex during Free Viewing.
IJCNN
Akaysha C. Tang, Matthew T. Sutherland, Christopher J. McKinney, Jingyu Liu, Yan Wang, Lucas C. Parra, Adam D. Gerson, Paul Sajda
2006 — conf
Smooth bilinear classification of EEG.
EMBC
Mads Dyrholm, Lucas C. Parra
2006 J jnl
Varying complexity in tree-structured image distribution models.
IEEE Trans. Image Process.
Clay Spence, Lucas C. Parra, Paul Sajda
2005 J jnl
Cortical origins of response time variability during rapid discrimination of visual objects.
NeuroImage
Adam D. Gerson, Lucas C. Parra, Paul Sajda
2005 J jnl
Recipes for the linear analysis of EEG.
NeuroImage
Lucas C. Parra, Clay D. Spence, Adam D. Gerson, Paul Sajda
2004 — conf
Maximising Sensitivity in a Spiking Network.
NIPS
Anthony J. Bell, Lucas C. Parra
2004 J jnl
Nonnegative matrix factorization for rapid recovery of constituent spectra in magnetic resonance chemical shift imaging of the brain.
IEEE Trans. Medical Imaging
Paul Sajda, Shuyan Du, Truman R. Brown, Radka Stoyanova, Dikoma C. Shungu, Xiangling Mao, Lucas C. Parra
2003 J jnl
A multi-scale probabilistic network model for detection, synthesis and compression in mammographic image analysis.
Medical Image Anal.
Paul Sajda, Clay Spence, Lucas C. Parra
2003 J jnl
Blind Source Separation via Generalized Eigenvalue Decomposition.
J. Mach. Learn. Res.
Lucas C. Parra, Paul Sajda
2003 J jnl
Single-trial detection in EEG and MEG: Keeping it linear.
Neurocomputing
Lucas C. Parra, Christopher V. Alvino, Akaysha C. Tang, Barak A. Pearlmutter, Nick Yeung, Allen Osman, Paul Sajda
2002 — conf
Capturing contextual dependencies in medical imagery using hierarchical multi-scale models.
ISBI
Paul Sajda, Clay Spence, Lucas C. Parra
2002 J jnl
Geometric source separation: merging convolutive source separation with geometric beamforming.
IEEE Trans. Speech Audio Process.
Lucas C. Parra, Christopher V. Alvino
2002 J jnl
Linear Spatial Integration for Single-Trial Detection in Encephalography.
NeuroImage
Lucas C. Parra, Christopher V. Alvino, Akaysha C. Tang, Barak A. Pearlmutter, Nick Yeung, Allen Osman, Paul Sajda
2000 J jnl
Convolutive blind separation of non-stationary sources.
IEEE Trans. Speech Audio Process.
Lucas C. Parra, Clay Spence
2000 B conf
Hierarchical Image Probability (HIP) Models.
ICIP
Clay Spence, Lucas C. Parra, Paul Sajda
2000 — conf
Hierarchical, Multi-resolution Models for Object Recognition: Applications to Mammographic Computer-aided Diagnosis.
AIPR
Paul Sajda, Clay Spence, Lucas C. Parra, Robert M. Nishikawa
2000 — conf
Higher-Order Statistical Properties Arising from the Non-Stationarity of Natural Signals.
NIPS
Lucas C. Parra, Clay Spence, Paul Sajda
2000 B conf
Mammographic mass detection with a hierarchical image probability (HIP) model.
Image Processing
Clay D. Spence, Lucas C. Parra, Paul Sajda
2000 J jnl
On-line Convolutive Blind Source Separation of Non-Stationary Signals.
J. VLSI Signal Process.
Lucas C. Parra, Clay Spence
1999 — conf
Hierarchical Image Probability (H1P) Models.
NIPS
Clay Spence, Lucas C. Parra
1999 — conf
Unmixing Hyperspectral Data.
NIPS
Lucas C. Parra, Clay Spence, Paul Sajda, Andreas Ziehe, Klaus-Robert Müller
1998 J jnl
List-Mode Likelihood EM Algorithm and Noise Estimation Demonstrated on 2D-PET.
IEEE Trans. Medical Imaging
Lucas C. Parra, Harrison H. Barrett
1997 J jnl
Non-linear Feature Extraction by Redundancy Reduction in an Unsupervised Stochastic Neural Network.
Neural Networks
Gustavo Deco, Lucas C. Parra
1997 — conf
Temporal Models in Blind Source Separation.
Summer School on Neural Networks
Lucas C. Parra
1996 — conf
Maximum Likelihood Blind Source Separation: A Context-Sensitive Generalization of ICA.
NIPS
Barak A. Pearlmutter, Lucas C. Parra
1996 J jnl
Statistical Independence and Novelty Detection with Information Preserving Nonlinear Maps.
Neural Comput.
Lucas C. Parra, Gustavo Deco, Stefan Miesbach
1995 J jnl
Continuous Boltzmann machine with rotor neurons.
Neural Networks
Lucas C. Parra, Gustavo Deco
1995 — conf
Symplectic Nonlinear Component Analysis.
NIPS
Lucas C. Parra
1995 — —
Unüberwachtes Lernen mit informationstheoretischen Kriterien in konnektionistischen Modellen.
Lucas C. Parra