Lucas C. Parra

According to our database, Lucas C. Parra authored at least 71 papers between 1995 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Real-time estimation of overt attention from dynamic features of the face using deep-learning.

Aimar Silvan Ortubay, Lucas C. Parra, Jens Madsen

CoRR, 2024

The Role of Fibration Symmetries in Geometric Deep Learning.

Osvaldo Matías Velarde, Lucas C. Parra, Paolo Boldi, Hernán A. Makse

CoRR, 2024

2023

Architecture of the brain's visual system enhances network stability and performance through layers, delays, and feedback.

Osvaldo Matías Velarde, Hernán A. Makse, Lucas C. Parra

PLoS Comput. Biol., November, 2023

2022

Deep Learning Achieves Neuroradiologist-Level Performance in Detecting Hydrocephalus Requiring Treatment.

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

J. Digit. Imaging, 2022

2020

Functional connectivity of EEG is subject-specific, associated with phenotype, and different from fMRI.

Maximilian Nentwich, Lei Ai, Jens Madsen, Qawi K. Telesford, Stefan Haufe, Michael P. Milham, Lucas C. Parra

NeuroImage, 2020

Deep learning achieves radiologist-level performance of tumor segmentation in breast MRI.

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

CoRR, 2020

2019

Inherent physiological artifacts in EEG during tDCS.

Nigel Gebodh, Zeinab Esmaeilpour, Devin Adair, Kenneth Chelette, Jacek Dmochowski, Adam J. Woods, Emily S. Kappenman, Lucas C. Parra, Marom Bikson

NeuroImage, 2019

Multiway canonical correlation analysis of brain data.

Alain de Cheveigné, Giovanni M. Di Liberto, Dorothée Arzounian, Daniel D. E. Wong, Jens Hjortkjær, Søren Asp Fuglsang, Lucas C. Parra

NeuroImage, 2019

Tissue segmentation with deep 3D networks and spatial priors.

Lukas Hirsch, Yu Huang, Lucas C. Parra

CoRR, 2019

2018

Elucidating relations between fMRI, ECoG, and EEG through a common natural stimulus.

Stefan Haufe, Paul DeGuzman, Simon Henin, Michael Arcaro, Christopher J. Honey, Uri Hasson, Lucas C. Parra

NeuroImage, 2018

Extracting multidimensional stimulus-response correlations using hybrid encoding-decoding of neural activity.

Jacek P. Dmochowski, Jason J. Ki, Paul DeGuzman, Paul Sajda, Lucas C. Parra

NeuroImage, 2018

Correlated Components Analysis - Extracting Reliable Dimensions in Multivariate Data.

Lucas C. Parra, Stefan Haufe, Jacek P. Dmochowski

CoRR, 2018

Optimized tDCS for Targeting Multiple Brain Regions: An Integrated Implementation.

Yu Huang, Chris Thomas, Abhishek Datta, Lucas C. Parra

Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2018

ROAST: An Open-Source, Fully-Automated, Realistic Volumetric-Approach-Based Simulator For TES.

Yu Huang, Abhishek Datta, Marom Bikson, Lucas C. Parra

Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2018

2017

Optimal use of EEG recordings to target active brain areas with transcranial electrical stimulation.

Jacek P. Dmochowski, Laurent Koessler, Anthony M. Norcia, Marom Bikson, Lucas C. Parra

NeuroImage, 2017

2016

The New York Head - A precise standardized volume conductor model for EEG source localization and tES targeting.

Yu Huang, Lucas C. Parra, Stefan Haufe

NeuroImage, 2016

Measuring engagement in a classroom: Synchronised neural recordings during a video presentation.

Andreas Trier Poulsen, Simon Kamronn, Jacek Dmochowski, Lucas C. Parra, Lars Kai Hansen

CoRR, 2016

2015

Neural Correlates of Perceived Confidence in a Partial Report Paradigm.

Martín Graziano, Lucas C. Parra, Mariano Sigman

J. Cogn. Neurosci., 2015

2014

Joint decorrelation, a versatile tool for multichannel data analysis.

Alain de Cheveigné, Lucas C. Parra

NeuroImage, 2014

Imaging artifacts induced by electrical stimulation during conventional fMRI of the brain.

Andrea Antal, Marom Bikson, Abhishek Datta, Belen Lafon, Peter Dechent, Lucas C. Parra, Walter Paulus

NeuroImage, 2014

Evoked Neural Responses to Events in Video.

Daniel Rosenthal, Paul DeGuzman, Lucas C. Parra, Paul Sajda

IEEE J. Sel. Top. Signal Process., 2014

Bayesian correlated component analysis for inference of joint EEG activation.

Andreas Trier Poulsen, Simon Kamronn, Lucas C. Parra, Lars Kai Hansen

Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2014

2013

Transcranial Electrical Stimulation Accelerates Human Sleep Homeostasis.

Davide Reato, Fernando Gasca, Abhishek Datta, Marom Bikson, Lisa Marshall, Lucas C. Parra

PLoS Comput. Biol., 2013

Subject position affects EEG magnitudes.

Justin K. Rice, Christopher Rorden, Jessica S. Little, Lucas C. Parra

NeuroImage, 2013

Targeted transcranial direct current stimulation for rehabilitation after stroke.

Jacek P. Dmochowski, Abhishek Datta, Yu Huang, Jessica D. Richardson, Marom Bikson, Julius Fridriksson, Lucas C. Parra

NeuroImage, 2013

Origins of power-law degree distribution in the heterogeneity of human activity in social networks

Lev Muchnik, Sen Pei, Lucas C. Parra, Saulo D. S. Reis, José S. Andrade Jr., Shlomo Havlin, Hernán A. Makse

CoRR, 2013

Spatial projections of neural arrays: A short guide to classic and new signal analysis techniques.

Lucas C. Parra, Jacek P. Dmochovski, Joao Dias, Alain de Cheveigné

Proceedings of the International Winter Workshop on Brain-Computer Interface, 2013

2012

Computational model of neuron-astrocyte interactions during focal seizure generation.

Davide Reato, Mario Cammarota, Lucas C. Parra, Giorgio Carmignoto

Frontiers Comput. Neurosci., 2012

Simultaneous and proportional control of 2D wrist movements with myoelectric signals.

Janne Mathias Hahne, Hubertus Rehbaum, Felix Bießmann, Frank C. Meinecke, Klaus-Robert Müller, Ning Jiang, Dario Farina, Lucas C. Parra

Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2012

An automated method for high-definition transcranial direct current stimulation modeling.

Yu Huang, Yuzhuo Su, Christopher Rorden, Jacek Dmochowski, Abhishek Datta, Lucas C. Parra

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012

On the role of electric field orientation in optimal design of transcranial current stimulation.

Jacek P. Dmochowski, Marom Bikson, Abhishek Datta, Jessica D. Richardson, Julius Fridriksson, Lucas C. Parra

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012

A pilot study on effects of 4×1 High-Definition tDCS on motor cortex excitability.

Egas M. Caparelli-Daquer, Trelawny J. Zimmermann, Eric Mooshagian, Lucas C. Parra, Justin K. Rice, Abhishek Datta, Marom Bikson, Eric M. Wassermann

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012

2010

Cortically-Coupled Computer Vision.

Paul Sajda, Eric Pohlmeyer, Jun Wang, Barbara Hanna, Lucas C. Parra, Shih-Fu Chang

Proceedings of the Brain-Computer Interfaces, 2010

In a Blink of an Eye and a Switch of a Transistor: Cortically Coupled Computer Vision.

Paul Sajda, Eric Pohlmeyer, Jun Wang, Lucas C. Parra, Christoforos Christoforou, Jacek Dmochowski, Barbara Hanna, Claus Bahlmann, Maneesh Kumar Singh, Shih-Fu Chang

Proc. IEEE, 2010

Maximum Likelihood in Cost-Sensitive Learning: Model Specification, Approximations, and Upper Bounds.

Jacek P. Dmochowski, Paul Sajda, Lucas C. Parra

J. Mach. Learn. Res., 2010

Second-Order Bilinear Discriminant Analysis.

Christoforos Christoforou, Robert M. Haralick, Paul Sajda, Lucas C. Parra

J. Mach. Learn. Res., 2010

2009

On the Maximization of Information Flow Between Spiking Neurons.

Lucas C. Parra, Jeffrey M. Beck, Anthony J. Bell

Neural Comput., 2009

2008

Spatiotemporal Linear Decoding of Brain State.

Lucas C. Parra, Christoforos Christoforou, Adam C. Gerson, Mads Dyrholm, An Luo, Mark Wagner, Marios G. Philiastides, Paul Sajda

IEEE Signal Process. Mag., 2008

Adaptive Template Matching with Shift-Invariant Semi-NMF.

Jonathan Le Roux, Alain de Cheveigné, Lucas C. Parra

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

2007

Bilinear Discriminant Component Analysis.

Mads Dyrholm, Christoforos Christoforou, Lucas C. Parra

J. Mach. Learn. Res., 2007

Second Order Bilinear Discriminant Analysis for single trial EEG analysis.

Christoforos Christoforou, Paul Sajda, Lucas C. Parra

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

2006

Varying complexity in tree-structured image distribution models.

Clay Spence, Lucas C. Parra, Paul Sajda

IEEE Trans. Image Process., 2006

Classifying Single-Trial ERPs from Visual and Frontal Cortex during Free Viewing.

Akaysha C. Tang, Matthew T. Sutherland, Christopher J. McKinney, Jingyu Liu, Yan Wang, Lucas C. Parra, Adam D. Gerson, Paul Sajda

Proceedings of the International Joint Conference on Neural Networks, 2006

Amplification of small electric fields by neurons; implications for spike timing.

Thomas Radman, Lucas C. Parra, Marom Bikson

Proceedings of the 28th International Conference of the IEEE Engineering in Medicine and Biology Society, 2006

Smooth bilinear classification of EEG.

Mads Dyrholm, Lucas C. Parra

Proceedings of the 28th International Conference of the IEEE Engineering in Medicine and Biology Society, 2006

2005

Recipes for the linear analysis of EEG.

Lucas C. Parra, Clay D. Spence, Adam D. Gerson, Paul Sajda

NeuroImage, 2005

Cortical origins of response time variability during rapid discrimination of visual objects.

Adam D. Gerson, Lucas C. Parra, Paul Sajda

NeuroImage, 2005

2004

Nonnegative matrix factorization for rapid recovery of constituent spectra in magnetic resonance chemical shift imaging of the brain.

Paul Sajda, Shuyan Du, Truman R. Brown, Radka Stoyanova, Dikoma C. Shungu, Xiangling Mao, Lucas C. Parra

IEEE Trans. Medical Imaging, 2004

Maximising Sensitivity in a Spiking Network.

Anthony J. Bell, Lucas C. Parra

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

2003

A multi-scale probabilistic network model for detection, synthesis and compression in mammographic image analysis.

Paul Sajda, Clay Spence, Lucas C. Parra

Medical Image Anal., 2003

Blind Source Separation via Generalized Eigenvalue Decomposition.

Lucas C. Parra, Paul Sajda

J. Mach. Learn. Res., 2003

Single-trial detection in EEG and MEG: Keeping it linear.

Lucas C. Parra, Christopher V. Alvino, Akaysha C. Tang, Barak A. Pearlmutter, Nick Yeung, Allen Osman, Paul Sajda

Neurocomputing, 2003

2002

Geometric source separation: merging convolutive source separation with geometric beamforming.

Lucas C. Parra, Christopher V. Alvino

IEEE Trans. Speech Audio Process., 2002

Linear Spatial Integration for Single-Trial Detection in Encephalography.

Lucas C. Parra, Christopher V. Alvino, Akaysha C. Tang, Barak A. Pearlmutter, Nick Yeung, Allen Osman, Paul Sajda

NeuroImage, 2002

Capturing contextual dependencies in medical imagery using hierarchical multi-scale models.

Paul Sajda, Clay Spence, Lucas C. Parra

Proceedings of the 2002 IEEE International Symposium on Biomedical Imaging, 2002

2000

On-line Convolutive Blind Source Separation of Non-Stationary Signals.

Lucas C. Parra, Clay Spence

J. VLSI Signal Process., 2000

Convolutive blind separation of non-stationary sources.

Lucas C. Parra, Clay Spence

IEEE Trans. Speech Audio Process., 2000

Higher-Order Statistical Properties Arising from the Non-Stationarity of Natural Signals.

Lucas C. Parra, Clay Spence, Paul Sajda

Proceedings of the Advances in Neural Information Processing Systems 13, 2000

Mammographic mass detection with a hierarchical image probability (HIP) model.

Clay D. Spence, Lucas C. Parra, Paul Sajda

Proceedings of the Medical Imaging 2000: Image Processing, 2000

Hierarchical Image Probability (HIP) Models.

Clay Spence, Lucas C. Parra, Paul Sajda

Proceedings of the 2000 International Conference on Image Processing, 2000

Hierarchical, Multi-resolution Models for Object Recognition: Applications to Mammographic Computer-aided Diagnosis.

Paul Sajda, Clay Spence, Lucas C. Parra, Robert M. Nishikawa

Proceedings of the 29th Applied Image Pattern Recognition Workshop (AIPR 2000), 2000

1999

Hierarchical Image Probability (H1P) Models.

Clay Spence, Lucas C. Parra

Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

Unmixing Hyperspectral Data.

Lucas C. Parra, Clay Spence, Paul Sajda, Andreas Ziehe, Klaus-Robert Müller

Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

1998

List-Mode Likelihood EM Algorithm and Noise Estimation Demonstrated on 2D-PET.

Lucas C. Parra, Harrison H. Barrett

IEEE Trans. Medical Imaging, 1998

1997

Non-linear Feature Extraction by Redundancy Reduction in an Unsupervised Stochastic Neural Network.

Gustavo Deco, Lucas C. Parra

Neural Networks, 1997

Temporal Models in Blind Source Separation.

Lucas C. Parra

Proceedings of the Adaptive Processing of Sequences and Data Structures, 1997

1996

Statistical Independence and Novelty Detection with Information Preserving Nonlinear Maps.

Lucas C. Parra, Gustavo Deco, Stefan Miesbach

Neural Comput., 1996

Maximum Likelihood Blind Source Separation: A Context-Sensitive Generalization of ICA.

Barak A. Pearlmutter, Lucas C. Parra

Proceedings of the Advances in Neural Information Processing Systems 9, 1996

1995

Unüberwachtes Lernen mit informationstheoretischen Kriterien in konnektionistischen Modellen.

Lucas C. Parra

PhD thesis, 1995

Continuous Boltzmann machine with rotor neurons.

Lucas C. Parra, Gustavo Deco

Neural Networks, 1995

Symplectic Nonlinear Component Analysis.

Lucas C. Parra

Proceedings of the Advances in Neural Information Processing Systems 8, 1995