Claudia Lainscsek

Claudia Lainscsek
Salk Institute for Biological Studies · Computational Neurobiology Laboratory

Dipl.Ing. Dr. techn.

About

51
Publications
15,290
Reads
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1,906
Citations
Citations since 2016
16 Research Items
866 Citations
2016201720182019202020212022020406080100120140
2016201720182019202020212022020406080100120140
2016201720182019202020212022020406080100120140
2016201720182019202020212022020406080100120140
Additional affiliations
August 2010 - present
Salk Institute for Biological Studies
Position
  • Salk Institute for Biological Studies
January 2001 - December 2012
University of California, San Diego

Publications

Publications (51)
Article
High density electrocorticogram (ECoG) electrodes are capable of recording neurophysiological data with high temporal resolution with wide spatial coverage. These recordings are a window to understanding how the human brain processes information and subsequently behaves in healthy and pathologic states. Here, we describe and implement delay differe...
Article
Significance One of the fundamental challenges of neuroscience is to understand the seamless orchestration of many interconnected brain regions, which is needed to produce the integrated experience of cognition. This paper describes a method based on dynamical systems theory to identify important nonlinear features underlying brain signals. We show...
Article
Most natural systems, including the brain, are highly nonlinear and complex, and determining information flow among the components that make up these dynamic systems is challenging. One such example is identifying abnormal causal interactions among different brain areas that give rise to epileptic activities. Here, we introduce cross-dynamical dela...
Article
A chimera state is a spatiotemporal pattern of broken symmetry, where synchrony (coherent state) and asynchrony (incoherent state) coexist. Here, we report chimera states in electrocorticography recordings preceding, by several hours, each of seven seizures in one patient with epilepsy. Before the seizures, the onset channels are not synchronized,...
Article
In estimating the frequency spectrum of real-world time series data, we must violate the assumption of infinite-length, orthogonal components in the Fourier basis. While it is widely known that care must be taken with discretely sampled data to avoid aliasing of high frequencies, less attention is given to the influence of low frequencies with peri...
Article
Full-text available
Dynamic functional brain connectivity facilitates adaptive cognition and behavior. Abnormal alterations within such connectivity could result in disrupted functions observed across various neurological conditions. As one of the most common neurological disorders, epilepsy is defined by the seemingly random occurrence of spontaneous seizures. A cent...
Preprint
Full-text available
State-of-the-art technologies in neural speech decoding utilize data collected from microwires or microarrays implanted directly into the cerebral cortex. Yet as a tool accessible only to individuals with implanted electrodes, speech decoding from devices of this nature is severely limited in its implementation, and cannot be considered a viable so...
Article
Determining synchronization, causality, and dynamical similarity in highly complex nonlinear systems like brains is challenging. Although distinct, these measures are related by the unknown deterministic structure of the underlying dynamical system. For two systems that are not independent on each other, either because they result from a common pro...
Article
In 1994, Sprott [Phys. Rev. E 50, 647–650 (1994)] proposed a set of 19 different simple dynamical systems producing chaotic attractors. Among them, 14 systems have a single nonlinear term. To the best of our knowledge, their diffeomorphical equivalence and the topological equivalence of their chaotic attractors were never systematically investigate...
Preprint
Full-text available
Dynamic functional brain connectivity facilitates adaptive cognition and behavior. Abnormal alterations within such connectivity could result in disrupted functions observed across various neurological conditions. As one of the most common neurological disorders, epilepsy is defined by the seemingly random occurrence of spontaneous seizures. A cent...
Article
Observability can determine which recorded variables of a given system are optimal for discriminating its different states. Quantifying observability requires knowledge of the equations governing the dynamics. These equations are often unknown when experimental data are considered. Consequently, we propose an approach for numerically assessing obse...
Preprint
Observability can determine which recorded variables of a given system are optimal for discriminating its different states. Quantifying observability requires knowledge of the equations governing the dynamics. These equations are often unknown when experimental data are considered. Consequently, we propose an approach for numerically assessing obse...
Article
Full-text available
Epilepsy is a neurological disorder characterized by the sudden occurrence of unprovoked seizures. There is extensive evidence of significantly altered brain connectivity during seizure periods in the human brain. Research on analyzing human brain functional connectivity during epileptic seizures has been limited predominantly to the use of the cor...
Article
Full-text available
Background Sleep spindles are involved in memory consolidation and other cognitive functions. Numerous automated methods for detection of spindles have been proposed; most of these rely on spectral analysis in some form. However, none of these approaches are ideal, and novel approaches to the problem could provide additional insights. New method H...
Article
Full-text available
The correlation method from brain imaging has been used to estimate functional connectivity in the human brain. However, brain regions might show very high correlation even when the two regions are not directly connected due to the strong interaction of the two regions with common input from a third region. One previously proposed solution to this...
Chapter
Time series analysis with nonlinear delay differential equations (DDEs) is a powerful tool since it reveals spectral as well as nonlinear properties of the underlying dynamical system. Here global DDE models are used to analyze electrocardiography recordings (ECGs) in order to capture distinguishing features for different heart conditions such as n...
Article
Full-text available
We propose a time-domain approach to detect frequencies, frequency couplings, and phases using nonlinear correlation functions. For frequency analysis, this approach is a multivariate extension of discrete Fourier transform, and for higher-order spectra, it is a linear and multivariate alternative to multidimensional fast Fourier transform of multi...
Article
Full-text available
Parkinson's disease (PD) is known to lead to marked alterations in cortical-basal ganglia activity that may be amenable to serve as a biomarker for PD diagnosis. Using non-linear delay differential equations (DDE) for classification of PD patients on and off dopaminergic therapy (PD-on, PD-off, respectively) from healthy age-matched controls (CO),...
Article
Full-text available
Non-linear dynamical system analysis based on embedding theory has been used for modeling and prediction but it also has applications to signal detection and classification of time series. An embedding creates a multidi-mensional geometrical object from a single time series. Traditionally either delay or derivative embeddings have been used. The de...
Article
Sleep scoring is commonly performed from electroencephalogram (EEG), electrooculogram (EOG), and electromyogram (EMG) to produce a socalled hypnogram. A neurologist thus visually encodes each epoch of 30 s into one of the sleep stages (wake, REM sleep, S1, S2, S3, S4). To avoid such a long process (about 3–4 hours) a technique for automatic sleep s...
Article
Full-text available
The pathophysiology of Parkinson’s disease (PD) is known to involve altered patterns of neuronal firing and synchronization in cortical-basal ganglia circuits. We used delay differential equations (DDE) as non-linear time-domain classification tools to analyze electroencephalographic (EEG) recordings from PD patients on and off dopaminergic therapy...
Article
Full-text available
Time series analysis with delay differential equations (DDEs) reveals non-linear properties of the underlying dynamical system and can serve as a non-linear time-domain classification tool. Here global DDE models were used to analyze short segments of simulated time series from a known dynamical system, the Rössler system, in high noise regimes. In...
Conference Paper
Full-text available
We propose a time-domain approach to detect cross-trial frequencies based on nonlinear correlation functions. This method is a multivariate extension of discrete Fourier transform (DFT) and can be applied to short and/or sparse time series. Cross-trial and/or cross-channel spectra (CTS) can be obtained for electroencephalography (EEG) data where mu...
Article
Full-text available
Time series analysis with nonlinear delay differential equations (DDEs) reveals nonlinear as well as spectral properties of the underlying dynamical system. Here, global DDE models were used to analyze 5 min data segments of electrocardiographic (ECG) recordings in order to capture distinguishing features for different heart conditions such as norm...
Article
Full-text available
Parkinson's disease is a degenerative condition whose severity is assessed by clinical observations of motor behaviors. These are performed by a neurological specialist through subjective ratings of a variety of movements including 10-s bouts of repetitive finger-tapping movements. We present here an algorithmic rating of these movements which may...
Article
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The transformation of a three-dimensional dynamical system to its differential model can be used to identify different nonlinear dynamical systems that share the same time series of one of its variables. This transformation then can be used to find classes of nonlinear dynamical systems with similar dynamical behavior.
Article
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Starting from an observed single time series, it is shown how to reconstruct a global model in the original phase space by using the ansatz library approach. This model is then compared to the underlying dynamical system that describes the initial time series, and the nonuniqueness of the reconstructed model is discussed. This framework is extended...
Chapter
Full-text available
Time series analysis with nonlinear delay differential equations (DDEs) is a very powerful tool since it reveals spectral as well as topological properties of the underlying dynamical system and is robust against noise. Here we apply nonlinear DDEs to examine the nature of the spatiotemporal distortions in repetitive finger tapping movements of mil...
Article
Full-text available
Spontaneous facial expressions differ from posed expressions in both which muscles are moved, and in the dynamics of the movement. Advances in the field of automatic facial expression measurement will require development and assessment on spontaneous behavior. Here we present preliminary results on a task of facial action detection in spontaneous f...
Conference Paper
Full-text available
We present results on a user independent fully automatic system for real time recognition of facial actions from the Facial Action Coding System (FACS). The system automatically detects frontal faces in the video stream and codes each frame with respect to 20 Action units. We present preliminary results on a task of facial action detection in spont...
Article
Full-text available
We present a systematic comparison of machine learning methods applied to the problem of fully automatic recognition of facial expressions. We report results on a series of experiments comparing recognition engines, including AdaBoost, support vector machines, linear discriminant analysis. We also explored feature selection techniques, including th...
Article
We present a systematic comparison of machine learning methods applied to the problem of fully automatic recognition of facial expressions. We explored recognition of facial actions from the Facial Action Coding System (FACS), as well as recognition of full facial expressions. Each video-frame is first scanned in real-time to detect approximately u...
Article
We present a systematic comparison of machine learning methods applied to the problem of fully automatic recognition of facial expressions. We explored recognition of facial actions from the Facial Action Coding System (FACS), as well as recognition of full facial expressions. Each videoframe is first scanned in real-time to detect approximately up...
Conference Paper
Full-text available
We present a systematic comparison of machine learning methods applied to the problem of fully automatic recognition of facial expressions. We explored recognition of facial actions from the facial action coding system (FACS), as well as recognition of fall facial expressions. Each video-frame is first scanned in real-time to detect approximately u...
Conference Paper
Full-text available
More than ten years ago the first successful application of a nonlinear oscillator model to high-quality speech signal processing was reported (Kubin and Kleijn, 1994). Since then, numerous developments have been initiated to turn nonlinear oscillators into a standard tool for speech technology. The present contribution will review and compare sev...
Conference Paper
Full-text available
An algorithm to map temporal signals into sequences of tinting patterns is introduced and applied to the analysis of dolphin sonar data collected during a target discrimination task. A parallel can be drawn between this algorithm and the biological auditory system which encodes sensory information in the timing patterns of neural spike trains. The...
Article
Obtaining a global model from the z-variable of the Rössler system is considered to be difficult because of its spiky structure. In this Letter, a 3D global model from the z-variable is derived in a space spanned by the state variable of the time-series itself and generic functions of the other two state variables. We term this space the Ansatz Spa...
Article
In 1899 Max Planck introduced natural units, also known as Planck quantities [1]. He described these units as intrinsic to the physical world, existing outside our immediate context: `These necessarily retain their meaning for all times and for all civilizations, even extraterrestrial and non-human ones, and can therefore be designated as ``natural...
Article
Full-text available
The information contained in a scalar time series and its time derivatives is used to obtain a global model for the underlying dynamics. This model provides a description of the time evolution of the system studied in a space spanned by the time series and its successive time derivatives which is expected to be equivalent to the original phase spac...
Article
The information contained in a scalar time series and its time derivatives is used to obtain a global model for the underlying dynamics. This model provides a description of the time evolution of the system studied in a space spanned by the time series and its successive time derivatives which is expected to be equivalent to the original phase spac...
Article
The construction of delay differential equations (DDE) from recorded data has been shown to be relevant to time series analysis. In particular, it allows one to detect the presence of a deterministic component in the signal. Also, it provides an opportunity to generate classification schemes in which a given signal may be mapped onto an equivalence...
Article
Full-text available
We examine the dynamics of three-dimensional cells with square planform in dissipative Rayleigh-Bénard convection. By applying a triple Fourier series ansatz up to second order, we obtain a system of nine nonlinear ordinary differential equations from the governing hydrodynamic equations. Depending on two control parameters, namely the Rayleigh num...
Article
The information contained in a scalar time series and its numerical derivatives is used to construct a global model for the underlying dynamical system, using a model transformation presented previously. Here, however, we analytically determine the most general form for the transformed model in the case of a three-dimensional model ansatz. We then...
Article
The analysis of Rayleigh-B{acute e}nard convection in a thin layer of an incompressible fluid caused by heating from below, is based on the Navier-Stokes equations. In planar geometry the Navier-Stokes equations in Bousinesq-approximation reduce to two nonlinear coupled partial differential equations for the velocity flux function and the temperatu...
Article
Full-text available
Intelligent human-computer interfaces, medical diag-nostics, and design of consumer products are just a few of the many applications that can benefit considerably from machine abilities to recognize and adapt to the user emo-tional state. The paper considers the problem of auto-matic affect recognition from continuous speech. It de-scribes a new te...

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Project (1)
Project
Our goal is to reproduce and update earlier results found using the. Ansatz library. We will concentrate on the 3D degree systems with quadratic nonlinearities. With the powerful computers we have these days, the search for category of models within the library is much easier. Maple and Mathematica have been used to find the models. Claudia Lainscsek from Salk Institute for Biological Studies · Computational Neurobiology Laboratory, Christophe Letellier from teh University of Rouen, France and I equally contribute in this project