Lucas C. Parra

发表

Lucas C. Parra, Stefan Haufe, Jacek Dmochowski, 2018, Neurons, Behavior, Data analysis, and Theory.

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

Yu Huang, Yuzhuo Su, Abhishek Datta, 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Neural Correlates of Perceived Confidence in a Partial Report Paradigm

Lucas C. Parra, Mariano Sigman, Martín Graziano, 2015, Journal of Cognitive Neuroscience.

Fully Automated Whole-Head Segmentation with Improved Smoothness and Continuity, with Theory Reviewed

Yu Huang, Lucas C. Parra, L. Parra, 2015, PloS one.

A ressource for assessing information processing in the developing brain using EEG and eye tracking

Lucas C. Parra, Michael P. Milham, Nicolas Langer, 2016 .

Bilinear Discriminant Component Analysis

Lucas C. Parra, Christoforos Christoforou, Mads Dyrholm, 2007, J. Mach. Learn. Res..

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

Barak A. Pearlmutter, Christopher V. Alvino, Lucas C. Parra, 2003, Neurocomputing.

Joint decorrelation, a versatile tool for multichannel data analysis

Lucas C. Parra, Alain de Cheveigné, L. Parra, 2014, NeuroImage.

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

Lucas C. Parra, Jacek Dmochowski, Lars Kai Hansen, 2016, ArXiv.

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

Lucas C. Parra, Shlomo Havlin, Lev Muchnik, 2013, Scientific Reports.

Rigor and reproducibility in research with transcranial electrical stimulation: An NIMH-sponsored workshop

Lucas C. Parra, Sarah H. Lisanby, Pejman Sehatpour, 2017, Brain Stimulation.

Hierarchical, multi-resolution models for object recognition: applications to mammographic computer-aided diagnosis

Robert M. Nishikawa, Lucas C. Parra, Paul Sajda, 2000, Proceedings 29th Applied Imagery Pattern Recognition Workshop.

Computational model of neuron-astrocyte interactions during focal seizure generation

Lucas C. Parra, Davide Reato, Mario Cammarota, 2012, Front. Comput. Neurosci..

EEG in the classroom: Synchronised neural recordings during video presentation

Lucas C. Parra, Lars Kai Hansen, Simon Kamronn, 2016, Scientific Reports.

Hierarchical image probability (HIP) models

Lucas C. Parra, Paul Sajda, Clay Spence, 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).

Adaptive Auto-Regressive Proportional Myoelectric Control

Lucas C. Parra, Janne M. Hahne, Jorge Igual, 2019, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

Geometric source separation: merging convolutive source separation with geometric beamforming

Christopher V. Alvino, Lucas C. Parra, L. Parra, 2001, Neural Networks for Signal Processing XI: Proceedings of the 2001 IEEE Signal Processing Society Workshop (IEEE Cat. No.01TH8584).

Spatial signatures of visual object recognition events learned from single-trial analysis of EEG

Lucas C. Parra, Paul Sajda, A. D. Gerson, 2003, Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439).

Using EEG to Predict Speech Intelligibility

Lucas C. Parra, Ivan Iotzov, L. Parra, 2019, 2019 Conference on Cognitive Computational Neuroscience.

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

Lucas C. Parra, Harrison H. Barrett, H. Barrett, 1998, IEEE Trans. Medical Imaging.

Statistical Independence and Novelty Detection with Information Preserving Nonlinear Maps

Lucas C. Parra, Gustavo Deco, Stefan Miesbach, 1996, Neural Computation.

Transcranial Electrical Stimulation Accelerates Human Sleep Homeostasis

Abhishek Datta, Lucas C. Parra, Marom Bikson, 2013, PLoS Comput. Biol..

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

Abhishek Datta, Lucas C. Parra, Justin K. Rice, 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

The Healthy Brain Network Serial Scanning Initiative: a resource for evaluating inter-individual differences and their reliabilities across scan conditions and sessions

Satrajit S. Ghosh, Lei Ai, Lucas C. Parra, 2016, bioRxiv.

An Adaptive Beamforming Perspective on Convolutive Blind Source Separation

Lucas C. Parra, Craig Langdale Fancourt, L. Parra, 2002, Noise Reduction in Speech Applications.

Concurrent Adaptation of Human and Machine Improves Simultaneous and Proportional Myoelectric Control

Lucas C. Parra, Klaus-Robert Muller, Janne M. Hahne, 2015, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

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

Abhishek Datta, Lucas C. Parra, Walter Paulus, 2014, NeuroImage.

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

Lucas C. Parra, Gustavo Deco, L. Parra, 1997, Neural Networks.

A Resource for Assessing Information Processing in the Developing Brain Using EEG and Eye Tracking

Lucas C. Parra, Michael P. Milham, Nicolas Langer, 2016 .

Unmixing Hyperspectral Data

Andreas Ziehe, Lucas C. Parra, Klaus-Robert Müller, 1999, NIPS.

Targeted transcranial direct current stimulation for rehabilitation after stroke

Yu Huang, Abhishek Datta, Lucas C. Parra, 2013, NeuroImage.

The bilinear brain: towards subject-invariant analysis

Robert M. Haralick, Lucas C. Parra, Paul Sajda, 2010, 2010 4th International Symposium on Communications, Control and Signal Processing (ISCCSP).

Recovering Audio Sources in a Multi-Path Environment

Lucas C. Parra, Paul Sajda, 1999 .

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

Lucas C. Parra, Jacek Dmochowski, Paul Sajda, 2017, NeuroImage.

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

Claus Bahlmann, Shih-Fu Chang, Lucas C. Parra, 2010, Proceedings of the IEEE.

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

Yan Wang, Lucas C. Parra, Paul Sajda, 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

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

Lucas C. Parra, Paul Sajda, Adam D. Gerson, 2005, NeuroImage.

Adaptive Template Matching with Shift-Invariant Semi-NMF

Jonathan Le Roux, Lucas C. Parra, Alain de Cheveigné, 2008, NIPS.

Convolutive Blind Source Separation Methods

Lucas C. Parra, Jan Larsen, Michael Syskind Pedersen, 2008 .

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

Lucas C. Parra, Paul Sajda, Clay Spence, 2002, Proceedings IEEE International Symposium on Biomedical Imaging.

Cortically-Coupled Computer Vision

Shih-Fu Chang, Lucas C. Parra, Paul Sajda, 2010, Brain-Computer Interfaces.

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

Lucas C. Parra, Paul Sajda, Clay Spence, 2000, NIPS.

On the Maximization of Information Flow Between Spiking Neurons

Lucas C. Parra, Jeffrey M. Beck, Anthony J. Bell, 2009, Neural Computation.

Telluride Decoding Toolbox

Lucas C. Parra, Alain de Cheveigné, Nima Mesgarani, 2015 .

Targeted electrical stimulation of active brain sources using reciprocity

Lucas C. Parra, Anthony M. Norcia, Jacek Dmochowski, 2016 .

A stochastic network with rotor neurons

Lucas C. Parra, Gustavo Deco, 1993, Proceedings of 1993 International Conference on Neural Networks (IJCNN-93-Nagoya, Japan).

Subject position affects EEG magnitudes

Lucas C. Parra, Chris Rorden, Justin K. Rice, 2013, NeuroImage.

On-line Blind Source Separation of Non-Stationary Signals

Lucas C. Parra, Clay D. Spence, L. Parra, 2001 .

UNSUPERVISED LEARNING FOR BOLTZMANN MACHINES

Lucas C. Parra, Gustavo Deco, L. Parra, 1995 .

Inherent physiological artifacts in EEG during tDCS

Lucas C. Parra, Jacek Dmochowski, Adam J. Woods, 2019, NeuroImage.

Temporal visual cues aid speech recognition

Lucas C. Parra, John J. Foxe, Xiang Zhou, 2006 .

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

Lucas C. Parra, Yu Huang, Krishna Juluru, 2020, ArXiv.

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

Lucas C. Parra, Stefan Haufe, Christopher J. Honey, 2018, NeuroImage.

Self-organization in stochastic neural networks

Lucas C. Parra, Gustavo Deco, 1993, Proceedings of 1993 International Conference on Neural Networks (IJCNN-93-Nagoya, Japan).

Single-trial analysis of EEG during rapid visual discrimination: enabling cortically-coupled computer vision

Lucas C. Parra, Paul Sajda, A. D. Gerson, 2007 .

Maximising Sensitivity in a Spiking Network

Lucas C. Parra, Anthony J. Bell, A. J. Bell, 2004, NIPS.

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

Dario Farina, Lucas C. Parra, Klaus-Robert Müller, 2012, 2012 IEEE International Workshop on Machine Learning for Signal Processing.

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

Lucas C. Parra, Clay Spence, L. Parra, 2000, J. VLSI Signal Process..

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

Lucas C. Parra, Paul Sajda, Truman R. Brown, 2004, IEEE Transactions on Medical Imaging.

Evoked Neural Responses to Events in Video

Lucas C. Parra, Paul Sajda, Daniel Rosenthal, 2014, IEEE Journal of Selected Topics in Signal Processing.

Second-Order Bilinear Discriminant Analysis

Robert M. Haralick, Lucas C. Parra, Paul Sajda, 2010, J. Mach. Learn. Res..

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

Barak A. Pearlmutter, Lucas C. Parra, L. Parra, 1996, NIPS.

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

Lucas C. Parra, Paul Sajda, Clay Spence, 2003, Medical Image Anal..

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

Lucas C. Parra, Alain de Cheveigne, Jacek P. Dmochovski, 2013, 2013 International Winter Workshop on Brain-Computer Interface (BCI).

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

Yu Huang, Lucas C. Parra, Stefan Haufe, 2015, NeuroImage.

Second Order Bilinear Discriminant Analysis for single trial EEG analysis

Lucas C. Parra, Paul Sajda, Christoforos Christoforou, 2007, NIPS.

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

Lucas C. Parra, Jacek Dmochowski, Anthony M. Norcia, 2016, NeuroImage.

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

Lucas C. Parra, Jacek Dmochowski, Paul Sajda, 2010, J. Mach. Learn. Res..

Lucas C. Parra, Lars Kai Hansen, Simon Kamronn, 2014, 2014 International Workshop on Pattern Recognition in Neuroimaging.

Optimized tDCS for Targeting Multiple Brain Regions: An Integrated Implementation

Yu Huang, Abhishek Datta, Lucas C. Parra, 2018, 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

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

Lucas C. Parra, Paul Sajda, Clay D. Spence, 2000, Medical Imaging: Image Processing.

A SURVEY OF CONVOLUTIVE BLIND SOURCE SEPARATION METHODS

Lucas C. Parra, Jan Larsen, Michael Syskind Pedersen, 2007 .

Realistic volumetric-approach to simulate transcranial electric stimulation—ROAST—a fully automated open-source pipeline

Lucas C. Parra, Yu Huang, Marom Bikson, 2017, bioRxiv.

Recipes for the linear analysis of EEG

Lucas C. Parra, Paul Sajda, Clay D. Spence, 2005, NeuroImage.

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

Lei Ai, Lucas C. Parra, Qawi K. Telesford, 2020, NeuroImage.

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

Yu Huang, Abhishek Datta, Lucas C. Parra, 2018, 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Temporal Models in Blind Source Separation

Lucas C. Parra, L. Parra, 1997, Summer School on Neural Networks.

Data Descriptor: A resource for assessing information processing in the developing brain using EEG and eye tracking

Lucas C. Parra, Michael P. Milham, Nicolas Langer, 2017 .

Unüberwachtes Lernen mit informationstheoretischen Kriterien in konnektionistischen Modellen

Lucas C. Parra, Lucas C. Parra, 1995 .

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

Abhishek Datta, Lucas C. Parra, Jacek Dmochowski, 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Continuous Boltzmann machine with rotor neurons

Lucas C. Parra, Gustavo Deco, 1995, Neural Networks.

Multiway canonical correlation analysis of brain data

Lucas C. Parra, Alain de Cheveigné, Jens Hjortkjær, 2019, NeuroImage.

High-throughput image search via single-trial event detection in a rapid serial visual presentation task

Lucas C. Parra, Paul Sajda, A. D. Gerson, 2003, First International IEEE EMBS Conference on Neural Engineering, 2003. Conference Proceedings..

The generalized sidelobe decorrelator

Lucas C. Parra, Craig Langdale Fancourt, 2001, Proceedings of the 2001 IEEE Workshop on the Applications of Signal Processing to Audio and Acoustics (Cat. No.01TH8575).

Varying complexity in tree-structured image distribution models

Lucas C. Parra, Paul Sajda, Clay Spence, 2006, IEEE Transactions on Image Processing.

Convolutive Source Separation and Signal Modeling with ML

Lucas C. Parra, Bert de Vries, Clay D. Spence, 2007 .

Convolutive blind separation of non-stationary sources

Lucas C. Parra, Clay Spence, L. Parra, 2000, IEEE Trans. Speech Audio Process..

Symplectic Nonlinear Component Analysis

Lucas C. Parra, L. Parra, 1995, NIPS.

Blind Source Separation via Generalized Eigenvalue Decomposition

Lucas C. Parra, Paul Sajda, L. Parra, 2003, J. Mach. Learn. Res..

Recovery of constituent spectra using non-negative matrix factorization

Lucas C. Parra, Paul Sajda, Shuyan Du, 2003, SPIE Optics + Photonics.

Segmentation of MRI head anatomy using deep volumetric networks and multiple spatial priors

Lucas C. Parra, Lukas Hirsch, Yu Huang, 2019, Journal of medical imaging.

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

Lucas C. Parra, Marom Bikson, Thomas Radman, 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.

Direct Current Stimulation Alters Neuronal Input/Output Function

Lucas C. Parra, Marom Bikson, Belen Lafon, 2017, Brain Stimulation.

Reliability and correlation of fMRI, ECoG and EEG during natural stimulus processing

Lucas C. Parra, Stefan Haufe, Christopher J. Honey, 2018 .

Heterogeneity of Human Activity Levels Gives Rise to Power-Law Distribution in Online Social Networks

Lucas C. Parra, Shlomo Havlin, Lev Muchnik, 2013 .

Collective Behaviour in Video Viewing: A Thermodynamic Analysis of Gaze Position

Lucas C. Parra, Paul DeGuzman, Hernán A. Makse, 2017, PloS one.

Transcranial Slow Oscillation Stimulation During Sleep Enhances Memory Consolidation in Rats

Lucas C. Parra, Jan Born, Fernando Gasca, 2014, Brain Stimulation.

Measurements and models of electric fields in the in vivo human brain during transcranial electric stimulation

Lucas C. Parra, Michael Dayan, Orrin Devinsky, 2017, Brain Stimulation.

Inter-Individual Variation during Transcranial Direct Current Simulation and Normaliziation of Dose Using MRI-Derived Computational Models

Abhishek Datta, Lucas C. Parra, Dennis Q. Truong, 2014, Brain Stimulation.

Divergent neural responses to narrative speech in disorders of consciousness

Lucas C. Parra, Mary M. Conte, Ivan Iotzov, 2017, Annals of clinical and translational neurology.

Approximate Kalman filtering for the harmonic plus noise model

Lucas C. Parra, L. Parra, U. Jain, 2001, Proceedings of the 2001 IEEE Workshop on the Applications of Signal Processing to Audio and Acoustics (Cat. No.01TH8575).

Age and sex affect intersubject correlation of EEG throughout development

Lucas C. Parra, Michael P. Milham, Tamara Vanderwal, 2016 .

Action enhances perception: Visually evoked neural responses are enhanced when engaging in a motor task

Lucas C. Parra, Jacek Dmochowski, Jason J. Ki, 2019 .

Direct current stimulation modulates LTP and LTD: activity dependence and dendritic effects

Lucas C. Parra, Marom Bikson, Greg Kronberg, 2017, Brain Stimulation.

No EEG evidence for subconscious detection during Rapid Serial Visual Presentation

Lucas C. Parra, L. Parra, Joao Dias, 2011, 2011 IEEE Signal Processing in Medicine and Biology Symposium (SPMB).

The Variability of Neural Responses to Naturalistic Videos Change with Age and Sex

Lei Ai, Lucas C. Parra, Michael P. Milham, 2018, eNeuro.

Realistic application of acoustic blind source separation

Lucas C. Parra, 2000 .

Geometric source separation: merging convolutive source separation with geometric beamforming

Christopher V. Alvino, Lucas C. Parra, 2001, Neural Networks for Signal Processing XI: Proceedings of the 2001 IEEE Signal Processing Society Workshop (IEEE Cat. No.01TH8584).

Direct Current Stimulation Modulates LTP and LTD: Activity Dependence and Dendritic Effects

Lucas C. Parra, Marom Bikson, Greg Kronberg, 2017, Brain Stimulation.

Lip-Reading Aids Word Recognition Most in Moderate Noise: A Bayesian Explanation Using High-Dimensional Feature Space

Wei Ji Ma, Xiang Zhou, Lucas C. Parra, 2009, PloS one.

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

Lucas C. Parra, Stefan Haufe, Christopher J. Honey, 2017, bioRxiv.

Spike Timing Amplifies the Effect of Electric Fields on Neurons: Implications for Endogenous Field Effects

Yuzhuo Su, Lucas C. Parra, Je Hi An, 2007, The Journal of Neuroscience.

1 Separation of non-stationary natural signals

Lucas C. Parra, L. Parra, 2001 .

Steerable frequency-invariant beamforming for arbitrary arrays

Lucas C. Parra, L. Parra, 2006 .