C. Lainscsek

发表

Non-Linear Dynamical Analysis of EEG Time Series Distinguishes Patients with Parkinson’s Disease from Healthy Individuals

T. Sejnowski, T. Sejnowski, H. Poizner, 2013, Front. Neurol..

Muscle artifacts in single trial EEG data distinguish patients with Parkinson's disease from healthy individuals

Terrence J. Sejnowski, Howard Poizner, Claudia Lainscsek, 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Electrocardiogram classification using delay differential equations.

T. Sejnowski, C. Lainscsek, 2013, Chaos.

Finger tapping movements of Parkinson's disease patients automatically rated using nonlinear delay differential equations.

H Poizner, Luis F. Schettino, P. Rowat, 2012, Chaos.

A class of Lorenz-like systems.

Claudia Lainscsek, C. Lainscsek, 2012, Chaos.

Automatic Recognition of Spontaneous Facial Actions

Ian R. Fasel, J. Movellan, M. Bartlett, 2006 .

Global modeling of the Rössler system from the /z-variable

Christophe Letellier, Claudia Lainscsek, I. F. Gorodnitsky, 2003 .

Reconstructing Dynamical Systems from Amplitude Measures of Spiky Time-Series

I. Gorodnitsky, C. Lainscsek, Christophe Letellier Coria, 2001 .

Discovering independent parameters in complex dynamical systems.

T. Sejnowski, C. Letellier, C. Lainscsek, 2015, Chaos, solitons, and fractals.

Cortical chimera states predict epileptic seizures.

T. Sejnowski, S. Cash, C. Lainscsek, 2019, Chaos.

Equivariance identification using delay differential equations

C. Letellier, C. Lainscsek, G. Gouesbet, 2000 .

A nine-dimensional Lorenz system to study high-dimensional chaos

Christophe Letellier, Peter Reiterer, Ferdinand Schürrer, 1998 .

Brain network dynamics codify heterogeneity in seizure evolution

T. Sejnowski, S. Cash, C. Lainscsek, 2022, Brain communications.

An open-access EEG dataset for speech decoding: Exploring the role of articulation and coarticulation

T. Sejnowski, C. Lainscsek, Lindy Comstock, 2022, bioRxiv.

Identification of Nonlinear Oscillator Models for Speech Analysis and Synthesis

Gernot Kubin, Erhard Rank, Claudia Lainscsek, 2004, Summer School on Neural Networks.

Multimodal classification of Parkinson’s disease using delay differential analysis

Terrence J. Sejnowski, Howard Poizner, Claudia Lainscsek, 2020, 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Delay differential analysis for dynamical sleep spindle detection

Terrence J. Sejnowski, Christopher E. Gonzalez, István Ulbert, 2019, Journal of Neuroscience Methods.

Non-Linear Dynamical Classification of Short Time Series of the Rössler System in High Noise Regimes

Terrence J. Sejnowski, Howard Poizner, Claudia Lainscsek, 2013, Front. Neurol..

Recognizing facial expression: machine learning and application to spontaneous behavior

Gwen Littlewort, Marian Stewart Bartlett, Ian R. Fasel, 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

Automatic Recognition of Facial Actions in Spontaneous Expressions

Gwen Littlewort, Marian Stewart Bartlett, Ian R. Fasel, 2006, J. Multim..

Delay Differential Analysis of Time Series

Terrence J. Sejnowski, Claudia Lainscsek, T. Sejnowski, 2015, Neural Computation.

Interpretation of the Precision Matrix and Its Application in Estimating Sparse Brain Connectivity during Sleep Spindles from Human Electrocorticography Recordings

Terrence J. Sejnowski, John Doyle, Sydney S. Cash, 2017, Neural Computation.

Automatic Sleep Scoring from a Single Electrode Using Delay Differential Equations

Terrence J. Sejnowski, Christophe Letellier, Jean-François Muir, 2014 .

Analytical Derivation of Nonlinear Spectral Effects and 1/f Scaling Artifact in Signal Processing of Real-World Data

Terrence J. Sejnowski, Aaron L. Sampson, Claudia Lainscsek, 2017, Neural Computation.

Assessing observability of chaotic systems using Delay Differential Analysis.

T. Sejnowski, C. Letellier, C. Lainscsek, 2020, Chaos.

Delay Differential Analysis of Seizures in Multichannel Electrocorticography Data

Terrence J. Sejnowski, Sydney S. Cash, Claudia Lainscsek, 2017, Neural Computation.

Causality detection in cortical seizure dynamics using cross-dynamical delay differential analysis.

Sydney S Cash, Claudia Lainscsek, Terrence J Sejnowski, 2019, Chaos.

Dynamical ergodicity DDA reveals causal structure in time series.

T. Sejnowski, S. Cash, C. Lainscsek, 2021, Chaos.

Nonuniqueness of global modeling and time scaling.

Claudia Lainscsek, C. Lainscsek, 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.

Delay Differential Analysis of Electroencephalographic Data

Terrence J. Sejnowski, Howard Poizner, Claudia Lainscsek, 2015, Neural Computation.

Multivariate spectral analysis of electroencephalography data

Terrence J. Sejnowski, Howard Poizner, Claudia Lainscsek, 2013, 2013 6th International IEEE/EMBS Conference on Neural Engineering (NER).

Brain network dynamics codify heterogeneity in seizure propagation

T. Sejnowski, S. Cash, C. Lainscsek, 2021, bioRxiv.

Characterizing Brain Connectivity From Human Electrocorticography Recordings With Unobserved Inputs During Epileptic Seizures

Terrence J. Sejnowski, Anup Das, Sydney S. Cash, 2019, Neural Computation.

A General Form for Global Dynamical Data Models for Three-Dimensional Systems

C. Lainscsek, F. Schürrer, J. Kadtke, 1998 .

Nonlinear dynamics underlying sensory processing dysfunction in schizophrenia

Terrence J. Sejnowski, Michael L. Thomas, Aaron L. Sampson, 2019, Proceedings of the National Academy of Sciences.

Fully Automatic Facial Action Recognition in Spontaneous Behavior

Gwen Littlewort, Marian Stewart Bartlett, Javier R. Movellan, 2006, 7th International Conference on Automatic Face and Gesture Recognition (FGR06).

Machine learning methods for fully automatic recognition of facial expressions and facial actions

Gwen Littlewort, Marian Stewart Bartlett, Ian R. Fasel, 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

Nonlinear DDE Analysis of Repetitive Hand Movements in Parkinson’s Disease

Howard Poizner, Peter F. Rowat, Claudia Lainscsek, 2009 .

Exploratory methods for high-performance EEG speech decoding

T. Sejnowski, C. Lainscsek, Lindy Comstock, 2021, bioRxiv.

Presentation Title: Non-linear Dynamical Analysis of Eeg Time Series Distinguishes Patients with Parkinson's Disease from Healthy Individuals

T. Sejnowski, C. Lainscsek, J. Weyhenmeyer, 2022 .

Characterizing Brain Connectivity From Human Electrocorticography Recordings With Unobserved Inputs During Epileptic Seizures

T. Sejnowski, S. Cash, C. Lainscsek, 2019, Neural Computation.

Transformations that preserve the uniqueness of the differential form for Lorenz-like systems.

T. Sejnowski, C. Lainscsek, Eduardo M. A. M. Mendes, 2023, Chaos.

Delay Differential Equation Models of Normal and Diseased Electrocardiograms

T. Sejnowski, C. Lainscsek, 2014 .