Terrence J. Sejnowski

NOTE Communicated by David Willshaw The Variance of Covariance Rules for Associative Matrix Memories and Reinforcement Learning (2009)

Massively-parallel connectionist networks have traditionally been applied to constraint-satisfaction in early visual processing (Ballard, Hinton & Sejnowski, 1983), but are now being applied to...

Text pages: (2009)

Scott Makeig, Klaus Gramann, Tzyy-ping Jung, Terrence J. Sejnowski, Howard Poizner, Scott Makeig

2008) for a special issue invited by the International Organization of Psychophysiology in conjunction with the keynote address by Dr. Makeig for their meeting in

Peter Dayan, Terrence J. Sejnowski

(Kohonen 1987; Hinton and Anderson 1981) and are also biologically

� REVIEW Gain Modulation in the Central Nervous System: Where Behavior, Neurophysiology, and Computation Meet (2008)

Emilio Salinas, Terrence J. Sejnowski

Gain modulation is a nonlinear way in which neurons combine information from two (or more) sources, which may be of sensory, motor, or cognitive origin. Gain modulation is revealed when one input,...

Dopaminergic Modulation of Local Network Activity in Rat Prefrontal Cortex (2008)

Daniel Durstewitz, Jeremy K. Seamans, Terrence J. Sejnowski, J Neurophysiol, H. Trantham-davidson, S. Kroner, ...

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Neurobiology of Disease Pathological Effect of Homeostatic Synaptic Scaling on Network Dynamics in Diseases of the Cortex (2008)

Flavio Fröhlich, Maxim Bazhenov, Terrence J. Sejnowski

Slow periodic EEG discharges are common in CNS disorders. The pathophysiology of this aberrant rhythmic activity is poorly understood. We used a computational model of a neocortical network with a...

Where Behavior, Neurophysiology, and Computation Meet (2008)

Emilio Salinas, Terrence J. Sejnowski, Emilio Salinas, Terrence J. Sejnowski

Gain modulation is a nonlinear way in which neurons combine information from two (or more) sources, which may be of sensory, motor, or cognitive origin. Gain modulation is revealed when one input,...

LETTER Communicated by Laurence Abbott Spike-Timing-Dependent Hebbian Plasticity as Temporal Difference Learning (2008)

Spike count distributions, factorizability, and contextual effects in area V1 (2008)

A spike-timing-dependent Hebbian mechanism governs the plasticity of recurrent excitatory synapses in the neocortex: synapses that are activated a few milliseconds before a postsynaptic spike are...

Odelia Schwartz, Javier R. Movellan, Thomas Wachtler, Thomas D. Albright, Terrence J. Sejnowski

Neural models of contextual integration typically incorporate a mean firing rate representation. We examine representation of the full spike count distribution, and its usefulness in explaining...

Mini-Review Network Oscillations: Emerging Computational Principles (2008)

Terrence J. Sejnowski, Ole Paulsen

Despite extensive work on the behavioral and physiological correlates of brain rhythms, it is still unresolved whether they have any important function in the mammalian cerebral cortex. In...

LETTER Communicated by Michael Lewicki Soft Mixer Assignment in a Hierarchical Generative Model of Natural Scene Statistics (2008)

Odelia Schwartz, Terrence J. Sejnowski, Peter Dayan

Gaussian scale mixture models offer a top-down description of signal generation that captures key bottom-up statistical characteristics of filter responses to images. However, the pattern of...

Active dendritic conductances enhance processing of plastic synaptic stimuli (2008)

Volman, Vladislav, Levine, Herbert, Sejnowski, Terrence J

No abstract available.

Cellular/Molecular Nonlinear Interaction between Shunting and Adaptation Controls a Switch between Integration and Coincidence Detection in Pyramidal Neurons (2008)

Steven A. Prescott, Stéphanie Ratté, Yves De Koninck, Terrence J. Sejnowski

The membrane conductance of a pyramidal neuron in vivo is substantially increased by background synaptic input. Increased membrane conductance, or shunting, does not simply reduce neuronal...

Corresponding author: (2008)

Susanne Schreiber, Jean-marc Fellous, Paul Tiesinga, Terrence J. Sejnowski, J. Sejnowski

of ionic conductances on spike timing reliability of cortical

Relevance Vector Machine and Support Vector Machine Classifier Analysis of Scanning Laser Polarimetry Retinal Nerve Fiber Layer Measurements (2008)

Christopher Bowd, Felipe A. Medeiros, Zuohua Zhang, Linda M. Zangwill, Jiucang Hao, Te-won Lee, ...

PURPOSE. To classify healthy and glaucomatous eyes using relevance vector machine (RVM) and support vector machine (SVM) learning classifiers trained on retinal nerve fiber layer (RNFL) thickness...

Automated Medical Diagnosis based on Decision Theory and Learning from Cases (2008)

Towards Automatic Recognition of Spontaneous Facial Actions (2008)

terry @ salk.edu

Marian Stewart Bartlett, Javier R. Movellan, Gwen Littlewort, Bjorn Braathen, Mark G. Frank, Terrence J. Sejnowski

Charles Darwin (1872/1998) was the first to fully recognize that facial expression is one of the most powerful and immediate means for human beings to communicate their emotions, intentions, and...

London, England 2 A Critique of Pure Vision' (2008)

Edited Christof Koch, Joel L. Davis, A Bradford Book, Patricia S. Churchl, V. S. Ramach, Terrence J. Sejnowski

Any domain of scientific research has its sustaining orthodoxy. That is, research on a problem, whether in astronomy, physics, or biology, is con-ducted against a backdrop of broadly shared...

ARTICLE Coni~nunicated by John Platt and Simon Haykin An Information-Maximization Approach to Blind Separation and Blind Deconvolution (2008)

Odelia Schwartz, Terrence J. Sejnowski, Peter Dayan

We derive a new self-organizing learning algorithm that maximizes the information transferred in a network of nonlinear units. The al-gorithm does not assume any knowledge of the input distributions,...

Abstract (2008)

In the analysis of natural images, Gaussian scale mixtures (GSM) have been used to account for the statistics of filter responses, and to inspire hierarchical cortical representational learning...

Correlation Coding in Stochastic Neural Networks (2008)

Wulfram Gerstner, Alain Germond, Raphael Ritz, Terrence J. Sejnowski

Abstract. Stimulus4ependent changes have been observed in the cor-relations between the spike trains of simultaneously-recorded pairs of neurons from the auditory cortex of marmosets even when there...

NOTE A Perceptron Reveals the Face of Sex (2008)

Communicated Garrison Cottrell, Michael S. Gray, David T. Lawrence, Beatrice A. Golomb, Terrence J. Sejnowski

Recognizing the sex of conspecifics is important. Humans rely primar-ily on visual pattern recognition for this task. A wide variety of linear and nonlinear models have been developed to understand...

I999 6th Joint Sy~nposiurn orz Neural Computation Proceedings ICA mixture models for image processing (2008)

Te-won Lee, Michael S. Lewicki, Terrence J. Sejnowski

We apply a probabilistic method for learning efficient image codes to the problem of unsupervised classification, segmentation and de-noising of images. The method is based on the Independent...

LETTER Communicated by Hagai Attias Dictionary Learning Algorithms for Sparse Representation (2008)

Kenneth Kreutz-delgado, Joseph F. Murray, Bhaskar D. Rao, Kjersti Engan, Te-won Lee, Terrence J. Sejnowski, ...

Algorithms for data-driven learning of domain-specific overcomplete dictionaries are developed to obtain maximum likelihood and maximum a posteriori dictionary estimates based on the use of Bayesian...

marni0salk.edu cabalQinca.dei.unipd.it movellanQcogsci.ucsd.edu (2008)

Marian Stewart, Bartlett Gianluca, Donato Javier, R. Movellan, Joseph C. Hager, Paul Ekman, ...

jchagerQibm.com terry0salk.edu The Facial Action Coding System (FACS) (10) is an objective method for quantify-ing facial movement in terms of component actions. This system is widely used in...

Towards Automatic Recognition of Spontaneous Facial Actions (2008)

Marian Stewart Bartlett, Javier R. Movellan, Gwen Littlewort, Bjorn Braathen, Mark G. Frank, Terrence J. Sejnowski

Charles Darwin (1872/1998) was the first to fully recognize that facial expression is one of the most powerful and immediate means for human beings to communicate their emotions, intentions, and...

David Marr: A Pioneer in Computational Neuroscience (2008)

David Man, Jack D. Cowan, W. Eric, L. Grirnson, Norberto M. Grzywacz, Ellen C. Hildreth, ...

David Man advocated and exemplified an approach to brain modeling that is based on computational sophistication together with a thorough knowledge of the biological facts. The pioneering papers in...

Book Review Unsupervised Learning- Foundations of Neural Computation (2008)

Edited Geoffrey Hinton, Terrence J. Sejnowski, Deliang Wang

The resurgence of the field of neural networks in the 1980's was primarily fueled by supervised learning, exemplified by the backpropagation algorithm. In supervised learning, a desired output...

response properties of parietal neurones (2008)

Re Pouget, Terrence J. Sejnowski

new view of hemineglect based on the

Repeated decompositions reveal the stability of infomax decomposition of fMRI data (2008)

Jeng-ren Duann, Tzyy-ping Jung, Terrence J. Sejnowski, Scott Makeig

Abstract – In this study, we decomposed 12 fMRI data sets from six subjects each 101 times using the infomax algorithm. The first decomposition was taken as a reference decomposition; the others...

after (2008)

David M Eaglemanô, Terrence J Sejnowski

The line-motion illusion can be reversed by motion signals

127 THE COMPUTATIONAL NEUROETHOLOGY OF SLEEP (2008)

Terrence J. Sejnowski, N. Elsner, R. Wehner (eds

On average, a third of our lives pass by in an apparently dormant state. Although body movements are suppressed during sleep, resulting in reduced external behavior, the internal activity of the...

In: Sommer & Wichert, Eds., Exploratory analysis and data modeling in functional neuroimaging,The MIT Press, 2002. Having your voxels and timing them too? (2008)

Scott Makeig, Tzyy-ping Jung, Terrence J. Sejnowski

The two major noninvasive functional human brain imaging modalities developed during the last part of the twentieth century, high-density scalp EEG (electroencephalogram) and fMRI (functional...

Toward Petascale Simulation of Cellular (2008)

Scott B. Baden, Terrence J. Sejnowski, Thomas M. Bartol, Joel Stiles

Abstract—MCell is a Monte Carlo simulator of cell microphysiology, and the scalable variant can be used to study challenging problems of interest to the biological community. MCell can currently...

Scotland (2008)

Te-won Lee, Mark Girolami, Terrence J. Sejnowski

An extension of the infomax algorithm of Bell and Sejnowski (1995) is presented that is able blindly to separate mixed signals with sub- and supergaussian source distributions. This was achieved by...

Kinetic Models of Synaptic Currents (2008)

Alain Destexhe, Zachary F. Mainen, Terrence J. Sejnowski

Synaptic interactions are essential to neural network models of all levels of complexity. Synaptic interactions in \realistic " network models pose a particular challenge, since the aim is...

Abstract (2008)

Odelia Schwartz, Terrence J. Sejnowski, Peter Dayan

The misjudgement of tilt in images lies at the heart of entertaining visual illusions and rigorous perceptual psychophysics. A wealth of findings has attracted many mechanistic models, but few clear...

Objective Functions for Topography: A Comparison of Optimal Maps (2008)

Geoffrey J. Goodhill, Terrence J. Sejnowski

This paper addresses this question for a very simple problem: the mapping of 10 \Theta 10 points in a square array to 1 \Theta 100 points in a linear array (see figure 1). Our approach is to...

Recognition: From Theory to Applications, NATO ASI Series F. Springer-Verlag. Learning Viewpoint Invariant Face Representations from Visual Experience by Temporal Association (2008)

Mixture of Trajectory Models for Neural Decoding of Goal-Directed Movements (2008)

In natural visual experience, different views of an object or face tend to appear in close temporal proximity. A set of simulations is presented which demonstrate how viewpoint invariant...

Kechen Zhang, Iris Ginzburg, Bruce L. Mcnaughton, Terrence J. Sejnowski, J Neurophysiol, A. Thiel, ...

You might find this additional information useful... This article cites 71 articles, 34 of which you can access free at:

Jolla, CA 92093. Independent components of face images: A (2007)

Marian Stewart Bartlett, H. Martin Lades, Terrence J. Sejnowski

representation for face recognition

c (2007)

In a task such as face recognition, much of the important information may be contained in the high-order relationships among the image pixels. A number of face recognition algorithms employ principal...

Wachtler et al. Vol. 18, No. 1/January 2001/J. Opt. Soc. Am. A 65 Chromatic structure of natural scenes (2007)

Thomas Wachtler, Te-won Lee, Terrence J. Sejnowski

We applied independent component analysis (ICA) to hyperspectral images in order to learn an efficient representation of color in natural scenes. In the spectra of single pixels, the algorithm found...

z (2007)

Receptive Fields, Marwan Jabri, Soo-young Lee, Terrence J. Sejnowski

We describe in this paper the properties of independent components of optical ow of moving objects. Video sequences of objects seen by an observer moving at various angles, directions and distances...

1 (2007)

Tzyy-ping Jung, Colin Humphries, Te-won Lee, Scott Makeig, Martin J. Mckeown, Vicente Iragui, ...

Pervasive electroencephalographic (EEG) artifacts associated with blinks, eye-movements, muscle noise, cardiac signals, and line noise poses a major challenge for EEG interpretation and analysis....

z (2007)

Marwan A. Jabri, Soo-young Lee, Terrence J. Sejnowski

In this paper we describe the properties of independent components of optical flow of moving objects. Video sequences of objects seen by an observer moving at various angles, directions and distances...

Selective Integration: A Model for Disparity Estimation (2007)

Michael Gray, Re Pouget, Richard S. Zemel, Steven J. Nowlan, Terrence J. Sejnowski

Local disparity information is often sparse and noisy, which creates two conflicting demands when estimating disparity in an image region: the need to spatially average to get an accurate estimate,...

Biologically Plausible Learning Rules for the Vestibulo-Ocular Reex (VOR) (2007)

Olivier Coenen, Terrence J. Sejnowski, Stephen G. Lisberger

Our previous dynamical models of the VOR and smooth pursuit have focused on performance and have not addressed the nature of the error signals or the local learning rules that are responsible for the...

Foraging Through Prediction (2007)

Peter Dayan, P Read Montague, Terrence J Sejnowski, P Read, Montague Terrence, J Sejnowski

To survive, an animal must use sensory events to predict the presence of mates, food, danger, and various other stimuli that are important for its survival and procreation. Although reliable...

Reference Material (2007)

Hinton Geoffrey, Geoffrey E, Terrence J. Sejnowski, David H. Ackley, Boltzmann Machines

d effect transistors of size 1,2,4,8,16. Each transistor can be activated by a digital charge on the gate. The digital charges are stored in RAM cells. -- the learning procedure uses digital counters...

Selective Integration: A Model for Disparity Estimation (2007)

Michael S. Gray, Alexandre Pouget, Re Pouget, Richard S. Zemel, Steven J. Nowlan, Terrence J. Sejnowski

Local disparity information is often sparse and noisy, which creates two conflicting demands when estimating disparity in an image region: the need to spatially average to get an accurate estimate,...

G-Protein Activation Kinetics And Spill-Over Of Gaba May Account For Differences Between Inhibitory Responses In The Hippocampus And Thalamus (2007)

Gabaa Gabab, Alain Destexhe, Terrence J. Sejnowski, Tc Thalamocortical

We have developed a model of GABAergic synaptic transmission mediated by GABAA and GABAB receptors, including cooperativity in the G-protein cascade mediating the activation of K + channels by GABAB...

y (2007)

Olivier Coenen, Terrence J. Sejnowski, Stephen G. Lisberger

zy

Biology and (2007)

Olivier J. M, D. Coenen, Terrence J. Sejnowski

Learning to make predictions in the cerebellum may explain the anticipatory modulation of the vestibulo-ocular reflex (VOR) gain with vergence

and (2007)

Michael S. Gray, Re Pouget, Richard S. Zemel, Steven J. Nowlan, Terrence J. Sejnowski

Local disparity information is often sparse and noisy, which creates two conflicting demands when estimating disparity in an image region: the need to spatially average to get an accurate estimate,...

and Biology (2007)

Michael S. Gray, Javier R. Movellan, Terrence J. Sejnowski

A systematic comparison

Book Review Unsupervised Learning- Foundations of Neural Computation (2007)

Edited Geoffrey Hinton, Terrence J. Sejnowski, Deliang Wang

The resurgence of the field of neural networks in the 1980's was primarily fueled by supervised learning, exemplified by the backpropagation algorithm. In supervised learning, a desired output...

NOTE Communicated by Geoffrey Hinton Optimal Smoothing in Visual Motion Perception (2007)

David M. Eagleman, Terrence J. Sejnowski

When a �ash is aligned with a moving object, subjects perceive the �ash to lag behind the moving object. Two different models have been proposed to explain this “�ash-lag ” effect. In the...

Summary (2007)

Maxim Bazhenov, Mark Stopfer, Mikhail Rabinovich, Terrence J. Sejnowski

Locust antennal lobe (AL) projection neurons (PNs) respond to olfactory stimuli with sequences of depolarizing and hyperpolarizing epochs, each lasting hun-dreds of milliseconds. A computer...

LETTER Communicated by Laurence Abbott Spike-Timing-Dependent Hebbian Plasticity as Temporal Difference Learning (2007)

NOTE Communicated by Geoffrey Hinton Optimal Smoothing in Visual Motion Perception (2007)

A spike-timing-dependent Hebbian mechanism governs the plasticity of recurrent excitatory synapses in the neocortex: synapses that are activated a few milliseconds before a postsynaptic spike are...

David M. Eagleman, Terrence J. Sejnowski

When a �ash is aligned with a moving object, subjects perceive the �ash to lag behind the moving object. Two different models have been proposed to explain this “�ash-lag ” effect. In the...

Cerebellar glomeruli: Does limited extracellular calcium implement a sparse encoding strategy? (2007)

David M. Eagleman, Olivier J-m, D. Coenen, Vladimir Mitsner, Thomas M. Bartol, Anthony J. Bell, ...

A class of synaptic learning models – in which presynaptic terminals have access to a weighted sum of the postsynaptic activity – has traditionally been dismissed as biologically unfeasible. This...

1 (2007)

Te-won Lee, Terrence J. Sejnowski

September. We apply independent component analysis (ICA) for learning an efficient color image representation of natural scenes. In the spectra of single pixels, the algorithm was able to find basis...

The Salk Institute, (2007)

Alain Destexhe, Zachary F. Mainen, Terrence J. Sejnowski, Computational Neurobiology Laboratory

corresponding author

y (2007)

NOTE Communicated by Laurence Abbott Neuronal Tuning: To Sharpen or Broaden? (2007)

Diagnosis is the process of identifying the disorders of a machine or a patient by considering its history, symptoms and other signs. Starting from possible initial information, new information is...

Kechen Zhang, Terrence J. Sejnowski

Sensory and motor variables are typically represented by a population of broadly tuned neurons. A coarser representation with broader tuning can often improve coding accuracy, but sometimes the...

LETTER Communicated by Erkki Oja Variational Bayesian Learning of ICA with Missing Data (2007)

Kwokleung Chan, Te-won Lee, Terrence J. Sejnowski

Missing data are common in real-world data sets and are a problem for many estimation techniques. We have developed a variational Bayesian method to perform independent component analysis (ICA) on...

A Comparison of Local Versus Global Image (2007)

Decompositions For Visual, Michael S. Gray, Javier R. Movellan, Terrence J. Sejnowski

What is the appropriate spatial scale for image representation? In the primate visual system, receptive fields are small at early stages of processing (area V1), and larger at late stages of...

Electroencephalographic Brain Dynamics Following Visual Targets (2007)

Requiring Manual Responses, Scott Makeig, Arnaud Delorme, Marissa Westerfield, Tzyy-ping Jung, Jeanne Townsend, ...

Background: Scalp-recorded electroencephalographic (EEG) signals produced by partial synchronization of cortical field activity mix locally synchronous electrical activities of many cortical areas....

Spike count distributions, factorizability, and contextual effects in area V1 (2007)

Odelia Schwartz, Javier R. Movellan, Thomas Wachtler, Thomas D. Albright, Terrence J. Sejnowski

Neural models of contextual integration typically incorporate a mean firing rate representation. We examine representation of the full spike count distribution, and its usefulness in explaining...

Towards Automatic Recognition of Spontaneous Facial Actions (2007)

Marian Stewart Bartlett, Javier R. Movellan, Gwen Littlewort, Bjorn Braathen, Mark G. Frank, Terrence J. Sejnowski

Charles Darwin (1872/1998) was the first to fully recognize that facial expression is one of the most powerful and immediate means for human beings to communicate their emotions, intentions, and...

Structural factors leading to changes in persistent activity following focal-trauma and neurodegeneration (2007)

Ohayon, Elan, Bazhenov, Maxim, Sejnowski, Terrence J, Kwan, Hon C, Burnham, W McIntyre

Analysis of fMRI Data by Blind Separation into Independent Spatial Components (2007)

McKeown, Martin J., Makeig, Scott, Brown, Greg G., Jung, Tzyy-Ping, Kindermann, Sandra S., Bell, Anthony J., ...

Current analytical techniques applied to functional magnetic resonance imaging (fMRI) data require a priori knowledge or specific assumptions about the time courses of processes contributing to the...

Dendritic Tree- Artificial Dendritic Development – Synaptic Integration- Genetic Algorithm- Structure to Function Mapping Acknowledgements This research was supported by the Deutsche Forschungsgemeinschaft (K.M.S.) and the (2007)

Klaus M. Stiefel, Terrence J. Sejnowski, Ted Carnevale

and Dr. Diego Raskin-Gutman for discussions and Dr. Melanie Mitchell for introducing

Selective attention through phase relationship of excitatory and inhibitory input synchrony in a model cortical neuron (2006)

Mishra, Jyoti, Fellous, Jean-Marc, Sejnowski, Terrence J

Neurons in area V2 and V4 exhibit stimulus specific tuning to single stimuli, and respond at intermediate firing rates when presented with two differentially preferred stimuli ('pair response')....

Reduction of anion reversal potential subverts the inhibitory control of firing rate in spinal lamina I neurons: towards a biophysical basis for neuropathic pain (2006)

Prescott, Steven A, Sejnowski, Terrence J, De Koninck, Yves

Abstract Background Reduction of the transmembrane chloride gradient in spinal lamina I neurons contributes to the cellular hyperexcitability producing allodynia and hyperalgesia after peripheral...

Functionally Independent Components of the Late Positive Event-Related Potential During Visual Spatial Attention (2006)

Makeig, Scott, Westeifleld, Marissa, Jung, Tzyy-Ping, Covington, James, Townsend, Jeanne, Sejnowski, Terrence J., ...

Human event-related potentials (ERPs) were recorded from 10 subjects presented with visual target and nontarget stimuli at five screen locations and responding to targets presented at one of the...

Blind Separation of Auditory Event-Related Brain Responses into Independent Components (2006)

Makeig, Scott, Jung, Tzyy-Ping, Bell, Anothny J., Ghahremandi, Dara, Sejnowski, Terrence J.

Average event-related potential (ERP) data recorded from the human scalp reveal electro-encephalo- graphic EEG) activity that is reliable time-locked and phase-locked to experimental events. We...

Removing Electroencephalographic Artifacts by Blind Source Separation (2006)

Jung, Tzyy-Ping, Maeig, Scott, Humphries, Colin, Lee, Te-Won, McKeown, Marin J., Iragui, Vicente, ...

Eye movements, eye blinks, cardiac signals, muscle noise, and line noise present serious problems for electroencephalographic ~EEG! interpretation and analysis when rejecting contaminated EEG...

Spatio-temporal dynamics in fMRI recordings revealed with complex independent component analysis (2006)

Jörn Anemüller, Jeng-Ren Duann, Terrence J. Sejnowski, Scott Makeig

Independent component analysis (ICA) of functional magnetic resonance imaging (fMRI) data is commonly carried out under the assumption that each source may be represented as a spatially fixed pattern...

Inhibitory synchrony as a mechanism for attentional gain modulation (2005)

Tiesinga, Paul H. E., Fellous, Jean-Marc, Salinas, Emilio, Jose, Jorge V., Sejnowski, Terrence J.

Recordings from area V4 of monkeys have revealed that when the focus of attention is on a visual stimulus within the receptive field of a cortical neuron, two distinct changes can occur: The firing...

Spatio-temporal dynamics in fMRI recordings (2005)

Revealed With Complex, Jörn Anemüller, Jeng-ren Duann, Terrence J. Sejnowski, Scott Makeig

Independent component analysis (ICA) of functional magnetic resonance imaging (fMRI) data is commonly carried out under the assumption that each source may be represented as a spatially fixed pattern...

Homeostatic Synaptic Plasticity Can Explain Post-traumatic Epileptogenesis in Chronically Isolated Neocortex (2005)

Houweling, Arthur R., Bazhenov, Maxim, Timofeev, Igor, Steriade, Mircea, Sejnowski, Terrence J.

Chronically isolated neocortex develops chronic hyperexcitability and focal epileptogenesis in a period of days to weeks. The mechanisms operating in this model of post-traumatic epileptogenesis are...

Electroencephalographic Brain Dynamics Following Manually Responded Visual Targets (2004)

Scott Makeig, Arnaud Delorme, Marissa Westerfield, Tzyy-Ping Jung, Jeanne Townsend, Eric Courchesne, ...

A new analysis considers EEG signals, not as average responses, but as individual event-related perturbations in ongoing dynamical brain processes.

Electroencephalographic Brain Dynamics Following Manually Responded Visual Targets (2004)

Scott Makeig, Arnaud Delorme, Marissa Westerfield, Tzyy-Ping Jung, Jeanne Townsend, Eric Courchesne, ...

Scalp-recorded electroencephalographic (EEG) signals produced by partial synchronization of cortical field activity mix locally synchronous electrical activities of many cortical areas. Analysis of...

Influence of Ionic Conductances on Spike Timing Reliability of Cortical (2004)

Neurons For Suprathreshold, Susanne Schreiber, Jean-marc Fellous, Paul Tiesinga, Terrence J. Sejnowski

this paper, see RESULTS (Influence of conductances on the frequency preference)

Discovering Spike Patterns in Neuronal Responses (2004)

Jean-marc Fellous, Peter J. Thomas, Terrence J. Sejnowski

Introduction Repeated injection of a fluctuating current into the soma of a cortical neuron in vitro yields similar spike patterns, precise to within a few milliseconds (Mainen and Sejnowski, 1995)....

Unraveling Spatio-Temporal Dynamics in fMRI Recordings Using Complex ICA (2004)

Jörn Anemüller, Jeng-Ren Duann, Terrence J. Sejnowski, Scott Makeig

Independent component analysis (ICA) of functional magnetic resonance imaging (fMRI) data is commonly carried out under the assumption that each source may be represented as a spatially fixed pattern...

Reliable Measurement of Cortical Flow Patterns Using Complex Independent Component Analysis of Electroencephalographic Signals (2004)

Jörn Anemüller, Terrence J. Sejnowski, Scott Makeig

Complex independent component analysis (ICA) of frequency-domain electroencephalographic (EEG) data [1] is a generalization of real time-domain ICA to the frequency-domain. Complex ICA aims to model...

Homeostatic Synaptic Plasticity Can Explain Post-traumatic Epileptogenesis in Chronically Isolated Neocortex (2004)

Houweling, Arthur R., Bazhenov, Maxim, Timofeev, Igor, Steriade, Mircea, Sejnowski, Terrence J.

Chronically isolated neocortex develops chronic hyperexcitability and focal epileptogenesis in a period of days to weeks. The mechanisms operating in this model of post-traumatic epileptogenesis are...

Homeostatic Synaptic Plasticity Can Explain Post-traumatic Epileptogenesis in Chronically Isolated Neocortex (2004)

Houweling, Arthur R., Bazhenov, Maxim, Timofeev, Igor, Steriade, Mircea, Sejnowski, Terrence J.

Chronically isolated neocortex develops chronic hyperexcitability and focal epileptogenesis in a period of days to weeks. The mechanisms operating in this model of post-traumatic epileptogenesis are...

Complex Independent Component Analysis of Frequency-Domain Electroencephalographic Data (2003)

Anemuller, Jorn, Sejnowski, Terrence J., Makeig, Scott

Independent component analysis (ICA) has proven useful for modeling brain and electroencephalographic (EEG) data. Here, we present a new, generalized method to better capture the dynamics of brain...

Consistency of infomax ICA decomposition of functional brain imaging data (2003)

Jeng-ren Duann, Tzyy-ping Jung, Scott Makeig, Terrence J. Sejnowski

Ten spatial infomax ICA decompositions were performed on two fMRI data sets collected from the same subject. The maximally-independent spatial components were then tested across decompositions for...

Complex Spectral-Domain Independent Component Analysis of Electroencephalographic Data (2003)

Jörn Anemüller, Terrence J. Sejnowski, Scott Makeig

Independent component analysis (ICA) has proved to be a highly useful tool for modeling brain data and in particular electroencephalographic (EEG) data. In this paper, a new method is presented that...

Complex Independent Component Analysis of Frequency-Domain Electroencephalographic Data (2003)

Jörn Anemüller, Terrence J. Sejnowski, Scott Makeig

Independent component analysis (ICA) has proven useful for modeling brain and electroencephalographic (EEG) data. Here, we present a new, generalized method to better capture the dynamics of brain...

The Diffusion Mediated Biochemical Signal (2003)

Relay Channel Peter, Peter J. Thomas, Donald J. Spencer, Terrence J. Sejnowski

Biochemical signal-transduction networks are the biological information-processing systems by which individual cells, from neurons to amoebae, perceive and respond to their chemical environments. We...

Complex Independent Component Analysis Of Frequency-Domain Electroencephalographic Data (2003)

Jörn Anemüller, Terrence J. Sejnowski, Scott Makeig

Independentcomponent analysis(ICA)hasprovenuseful for modelingbrainandelectroencephalographic (EEG)data.Here,wepresent a new,generalizedmethodtobettercapturethe dynamicsofbrainsignals thanprevious...

Regulation of Persistent Activity by Background Inhibition in an In Vitro Model of a Cortical Microcircuit (2003)

Fellous, Jean-Marc, Sejnowski, Terrence J.

We combined in vitro intracellular recording from prefrontal cortical neurons with simulated synaptic activity of a layer 5 prefrontal microcircuit using a dynamic clamp. During simulated in vivo...

Comparison of machine learning and traditional classifiers in glaucoma diagnosis (2002)

Kwokleung Chan, Te-won Lee, Associate Member, Michael H. Goldbaum, Robert N. Weinreb, Terrence J. Sejnowski

Abstract—Glaucoma is a progressive optic neuropathy with characteristic structural changes in the optic nerve head reflected in the visual field. The visual-field sensitivity test is commonly used...

Model of Thalamocortical Slow-Wave Sleep Oscillations and Transitions to Activated States (2002)

Maxim Bazhenov, Igor Timofeev, Mircea Steriade, Terrence J. Sejnowski

During natural slow-wave sleep (SWS) in nonanesthetized cats, silent (down) states alternate with active (up) states; the down states are absent during rapid-eye-movement sleep and waking....

A Monte Carlo model reveals independent signaling at central glutamatergic synapses (2002)

Kevin M. Franks, Thomas M. Bartol, Terrence J. Sejnowski

ABSTRACT We have developed a biophysically realistic model of receptor activation at an idealized central glutamatergic synapse that uses Monte Carlo techniques to simulate the stochastic nature of...

Comparison of machine learning and traditional classifiers in glaucoma diagnosis (2002)

Kwokleung Chan, Te-won Lee, Robert N. Weinreb, Terrence J. Sejnowski

Abstract. Glaucoma is a progressive optic neuropathy with characteristic structural changes in the optic nerve head reflected in the visual field. Visual field sensitivity test is hence commonly used...

Face recognition by independent component analysis (2002)

Marian Stewart Bartlett, Javier R. Movellan, Terrence J. Sejnowski

Abstract—A number of current face recognition algorithms use face representations found by unsupervised statistical methods. Typically these methods find a set of basis images and represent faces...

Face Recognition by Independent Component Analysis (2002)

Marian Stewart Bartlett, Javier R. Movellan, Terrence J. Sejnowski

A number of current face recognition algorithms use face representations found by unsupervised statistical methods. Typically these methods find a set of basis images and represent faces as a linear...

Single-Trial Variability in Event-Related BOLD Signals (2002)

Scott Makeig, Jen-chuen Hsieh, Terrence J. Sejnowski

This paper demonstrates that ICA, applied to event-related fMRI paradigms, can reveal BOLD processes having novel and highly variable HRs, even in simple sensory response paradigms, allowing detailed...

Face recognition by independent component analysis (2002)

Marian Stewart Bartlett, Javier R. Movellan, Terrence J. Sejnowski

Abstract—A number of current face recognition algorithms use face representations found by unsupervised statistical methods. Typically these methods find a set of basis images and represent faces...

Attractor Reliability Reveals Deterministic Structure in Neuronal Spike Trains (2002)

Variational learning of clusters of undercomplete nonsymmetric independent components (2001)

This article consists of two parts. First, a test is given to determinewhether a spike train forms a temporally modulated renewal process. Second, we quantify the extra---non-Poisson---structure...

Kwokleung Chan, Te-won Lee, Terrence J. Sejnowski

We apply a variational method to automatically determine the number of mixtures of independent components in high-dimensional datasets, in which the sources may be nonsymmetrically distributed. The...

Simulating a lesion in a basis function model of spatial representations: comparison with hemineglect (2001)

Alexandre Pouget, Terrence J. Sejnowski

The basis function theory of spatial representations explains how neurons i n the parietal cortex can perform nonlinear transformations from sensory to motor coordinates. The authors present computer...

Analysis and visualization of single-trial event-related potentials (2001)

Tzyy-ping Jung, Scott Makeig, Marissa Westerfield, Jeanne Townsend, Eric Courchesne, Terrence J. Sejnowski

Abstract: In this study, alinear decomposition technique, independent component analysis (ICA), is applied to single-trial multichannel EEG data from event-related potential (ERP) experiments....

Computational model of carbachol-induced delta, theta, and gamma oscillations in the hippocampus (2001)

Jean-marc Fellous, Jorge V. José, Terrence J. Sejnowski

ABSTRACT: Field potential recordings from the rat hippocampus in vivo contain distinct frequency bands of activity, including � (0.5–2 Hz), � (4–12 Hz), and � (30–80 Hz), that are...

Nonlocal interactions in color perception: nonlinear processing of chromatic signals from remote inducers (2001)

Thomas Wachtler, Thomas D. Albright, Terrence J. Sejnowski

The perceived color of an object depends on the chromaticity of its immediate background. But color appearance is also influenced by remote chromaticities. To quantify these influences, the effects...

Nonlocal interactions in color perception: nonlinear processing of chromatic signals from remote inducers (2001)

Thomas Wachtler, Thomas D. Albright, Terrence J. Sejnowski

The perceived color of an object depends on the chromaticity of its immediate background. But color appearance is also influenced by remote chromaticities. To quantify these influences, the effects...

The Chromatic Structure of Natural Scenes (2001)

Thomas Wachtler, Te-won Lee, Terrence J. Sejnowski

We applied Independent Component Analysis (ICA) to hyperspectral images in order to learn an ecient representation of color in natural scenes. In the spectra of single pixels, the algorithm found...

Face Recognition by Independent Component Analysis (2001)

Marian Stewart Bartlett, Javier R. Movellan, Terrence J. Sejnowski

A number of current face recognition algorithms use face representations found by unsupervised statistical methods. Typically these methods find a set of basis images and represent faces as a linear...

Variational learning of clusters of undercomplete nonsymmetric independent components (2001)

Kwokleung Chan, Te-won Lee, Terrence J. Sejnowski

We apply a variational method to automatically determine the number of mixtures of independent components in high-dimensional datasets, in which the sources may be nonsymmetrically distributed. The...

Imaging Brain Dynamics Using Independent Component Analysis (2001)

Tzyy-Ping Jung, Scott Makeig, Martin J. Mckeown, Anthony J. Bell, Te-won Lee, Terrence J. Sejnowski, ...

The analysis of electroence... In this paper, we outline the assumptions underlying ICA and demonstrate its application to a variety of electrical and hemodynamic recordings from the human brain.

Learning To Evaluate Go Positions Via Temporal Difference Methods (2000)

Nicol N. Schraudolph, Peter Dayan, Terrence J. Sejnowski

The game of Go has a high branching factor that defeats the tree search approach used in computer chess, and long-range spatiotemporal interactions that make position evaluation extremely difficult....

Moving-window ICA decomposition of EEG data reveals event-related changes in oscillatory brain activity (2000)

Scott Makeig, Sigurd Enghoff, Tzyy-ping Jung, Terrence J. Sejnowski

Abstract. Decomposition of temporally overlapping subepochs from 3-s electroencephalographic (EEG) epochs time locked to the presentation of visual target stimuli in a selective attention task...

Learning To Evaluate Go Positions Via Temporal Difference Methods (2000)

Nicol N. Schraudolph, Peter Dayan, Terrence J. Sejnowski

The game of Go has a high branching factor that defeats the tree search approach used in computer chess, and long-range spatiotemporal interactions that make position evaluation extremely difficult....

Independent component analysis of biomedical signals (2000)

Tzyy-ping Jung, Scott Makeig, Te-won Lee, Martin J. Mckeown, Glen Brown, Anthony J. Bell, ...

A color version of this article can be downloaded from

Learning To Evaluate Go Positions Via Temporal Difference Methods (2000)

Nicol N. Schraudolph, Peter Dayan, Terrence J. Sejnowski

Introduction 1.1 The Game of Go Go was developed four millennia ago in China; it is one of the oldest and most popular board games in the world. Like chess, it is a deterministic, perfect...

Image Representations for Facial Expression Coding (2000)

Marian Stewart Bartlett, Javier R. Movellan, Paul Ekman, Gianluca Donato, Joseph C. Hager, Terrence J. Sejnowski

The Facial Action Coding System (FACS) (9) is an objective method for quantifying facial movement in terms of component actions. This system is widely used in behavioral investigations of emotion,...

Removing Electroencephalographic Artifacts by Blind Source Separation (2000)

Tzyy-Ping Jung, Scott Makeig, Colin Humphries, Te-Won Lee, Martin J. Mckeown, Vicente Iragui, ...

Eye movements, eye blinks, cardiac signals, muscle noise, and line noise present serious problems for electroencephalographic ~EEG! interpretation and analysis when rejecting contaminated EEG...

Cholinergic Induction of Oscillations in the Hippocampal Slice in the Slow (0.5-2 Hz), Theta (5-12 Hz), and Gamma (35-70 Hz) Bands (2000)

Jean-marc Fellous, Terrence J. Sejnowski

: Carbachol, a muscarinic receptor agonist, produced three distinct spontaneous oscillations in the CA3 region of rat hippocampal slices. Carbachol concentrations in the 4--13 #M range produced...

ICA Mixture Models for Unsupervised Classification of Non-Gaussian Classes and Automatic Context Switching in Blind Signal Separation (2000)

Te-won Lee, Michael S. Lewicki, Terrence J. Sejnowski

An unsupervised classification algorithm is derived by modeling observed data as a mixture of several mutually exclusive classes that are each described by linear combinations of independent,...

Awareness during Drowsiness: Dynamics and Electrophysiological Correlates (2000)

Scott Makeig, Scott Makeig, Tzyy-Ping Jung, Terrence J. Sejnowski

this article are those of the authors and do not reflect the official policy or position of the Department of the Navy, Department of Defense, or the U.S. Government

The Spectral Independent Components Of Natural Scenes (2000)

Te-won Lee, Thomas Wachtler, Terrence J. Sejnowski

We apply independent component analysis (ICA) for learning an efficient color image representation of natural scenes. In the spectra of single pixels, the algorithm was able to find basis functions...

Integrated human brain science: Theory, Method, Application (Music), chapter Independent Component Analysis of Simulated ERP Data (2000)

Scott Makeig, Tzyy-ping Jung, Dara Ghahremani, Terrence J. Sejnowski

Research, Department of the Navy under work unit ONR.Reimb-6429. The views expressed in this article are those of

Independent component analysis of biomedical signals (2000)

Tzyy-ping Jung, Scott Makeig, Te-won Lee, Martin J. Mckeown, Glen Brown, Anthony J. Bell, ...

Biomedical signals from many sources including hearts, brains and endocrine systems pose a challenge to researchers who may have to separate weak signals arriving from multiple sources contaminated...

Moving-window ICA decomposition of EEG data reveals event-related changes in oscillatory brain activity (2000)

Scott Makeig, Sigurd Enghoff, Tzyy-ping Jung, Terrence J. Sejnowski

Abstract. Decomposition of temporally overlapping subepochs from 3-s electroencephalographic (EEG) epochs time locked to the presentation of visual target stimuli in a selective attention task...

Independent Component Analysis for Mixed Sub-Gaussian and Super-Gaussian Sources (1999)

Te-won Lee, Terrence J. Sejnowski

An extension of the infomax algorithm of Bell & Sejnowski (1995) is presented that is able to separate the mixed sub- and super-Gaussian source distributions. The same learning rule has been...

A Theory of Geometric Constraints on Neural Activity for Natural Three-Dimensional Movement (1999)

Kechen Zhang, Terrence J Sejnowski

This paper presents a theoretical analysis of how neuronal activity correlated with natural movements might be constrained by geometry. The basic theory, although essentially linear, can account for...

Measuring Facial Expressions by Computer Image Analysis (1999)

Marian Stewart Bartlett, Joseph C. Hager, Paul Ekman, Terrence J. Sejnowski

Facial expressions provide an important behavioral measure for the study of emotion, cognitive processes, and social interaction. The Facial Action Coding System, (Ekman

Face Image Analysis for Expression Measurement and Detection of Deceit (1999)

Marian Stewart Bartlett, Gianluca Donato, Javier R. Movellan, Joseph C. Hager, Paul Ekman, Terrence J. Sejnowski

The Facial Action Coding System (FACS) (10) is an objective method for quantifying facial movement in terms of component actions. This system is widely used in behavioral investigations of emotion,...

Analyzing and Visualizing Single-Trial Event-Related Potentials (1999)

Jeanne Townsend, Eric Courchesne, Terrence J. Sejnowski

Event-related potentials (ERPs), are portions of electroencephalographic (EEG) recordings that are both time- and phase-locked to experimental events. ERPs are usually averaged to increase their...

A Unifying Information-theoretic Framework for Independent Component Analysis (1999)

Te-won Lee, Mark Girolami, Anthony J. Bell, Terrence J. Sejnowski

We show that different theories recently proposed for Independent Component Analysis (ICA) lead to the same iterative learning algorithm for blind separation of mixed independent sources. We review...

Lesioning a Basis Function Model of Spatial Representations in the Parietal Cortex: Comparison with Hemineglect (1999)

Re Pougety, Terrence J Sejnowski, Alexandre Pouget

In a recently developed theory of spatial representations, the position of an object is encoded not in a particular frame of reference, as in previous models, but rather a population of neurons that...

Classifying Facial Action (1999)

Marian Stewart, Marian Stewart Bartlett, Paul A. Viola, Terrence J. Sejnowski, Beatrice A. Golomb, Joseph C. Hager, ...

The Facial Action Coding System, (FACS), devised by Ekman and Friesen (1978), provides an objective means for measuring the facial muscle contractions involved in a facial expression. In this paper,...

Neuronal Tuning: To Sharpen or Broaden (1999)

K. Zhang, T. J. Sejnowski, Kechen Zhang, Terrence J. Sejnowski

Sensory and motor variables are typically represented by a population of broadly tuned neurons. A coarser representation with broader tuning can often improve coding accuracy, but sometimes the...

A Theory of Geometric Constraints on Neural Activity for Natural Three-Dimensional Movement (1999)

Kechen Zhang, Terrence J. Sejnowski

Although the orientation of an arm in space or the static view of an object may be represented by a population of neurons in complex ways, how these variables change with movement often follows...

Makeig et al., Philosophical Transactions of the Royal Society: Biological Sciences 354:1135-44, 1999. (1999)

June Functionally Independent, Scott Makeig, Marissa Westerfield, Jeanne Townsend, Tzyy-ping Jung, Eric Courchesne, ...

This report was supported by the Office of Naval Research, Department of the Navy (ONR.reimb.6429, S. Makeig), the Howard Hughes Medical Institute (T. Sejnowski), the National Institutes of Health...

Blind source separation of more sources than mixtures using overcomplete representations (1999)

Te-won Lee, Michael S. Lewicki, Mark Girolami, Terrence J. Sejnowski, Senior Member

Abstract—Empirical results were obtained for the blind source separation of more sources than mixtures using a recently proposed framework for learning overcomplete representations. This technique...

Classifying Facial Actions (1999)

Gianluca Donato Marian, Marian Stewart Bartlett, Joseph C. Hager, Paul Ekman, Terrence J. Sejnowski

This paper explores and compares techniques for automatically recognizing facial actions in sequences of images. These techniques include analysis of facial motion through estimation of optical flow;...

Sejnowski: ”Neural codes and distributed representations: foundations of neural computation (1999)

Edited L. Abbott, T. Sejnowski, Laurence F. Abbott, Terrence J. Sejnowski

Massively-Parallel Architectures for Automatic Recognition of Visual Speech Signals. (1998)

Sejnowski, Terrence J.

During the last year significant progress has been made in the primary objective of estimating the acoustic characteristics fo speech from the visual speech signals. Neural networks have been trained...

Massively Parallel Network Architectures for Automatic Recognition of Visual Speech Signals. (1998)

Sejnowski, Terrence J., Goldstein, Moise

This research sought to produce a massively-parallel network architecture that could interpret speech signals from video recordings of human talkers. This report summarizes the project's results: (1)...

Connectionist Models: Proceedings of the Summer School Held in San Diego, California on 1990, (1998)

Touretzky, David S., Elman, Jeffrey L., SeJnowski, Terrence J., Hinton, Geoffrey E.

The simplicity and locality of the contrastive Hebb synapse (CHS) used in Boltzmann machine learning makes it an attractive model for real biological synapses. The slow learning exhibited by the...

Woods Hole Workshop on Computational Neuroscience (1998)

Sejnowski, Terrence J.

The Woods Hole Workshop on Computational Neuroscience was held at the Marine Biological Laboratory on August 26 to August 31, 1996. Twenty-two investigators attended the workshop on the computational...

Submicrosecond pacemaker precision is behaviorally modulated: The gymnotiform electromotor pathway (1998)

Moortgat, Katherine T., Keller, Clifford H., Bullock, Theodore H., Sejnowski, Terrence J.

What are the limits and modulators of neural precision? We address this question in the most regular biological oscillator known, the electric organ command in the brainstem of wave-type electric...

Submicrosecond pacemaker precision is behaviorally modulated: The gymnotiform electromotor pathway (1998)

Moortgat, Katherine T., Keller, Clifford H., Bullock, Theodore H., Sejnowski, Terrence J.

What are the limits and modulators of neural precision? We address this question in the most regular biological oscillator known, the electric organ command in the brainstem of wave-type electric...

Submicrosecond pacemaker precision is behaviorally modulated: The gymnotiform electromotor pathway (1998)

Moortgat, Katherine T., Keller, Clifford H., Bullock, Theodore H., Sejnowski, Terrence J.

What are the limits and modulators of neural precision? We address this question in the most regular biological oscillator known, the electric organ command in the brainstem of wave-type electric...

A computational model of how the basal ganglia produce sequences (1998)

Gregory S. Berns, Terrence J. Sejnowski

We propose a systems-level computational model of the basal ganglia based closely on known anatomy and physiology. First, we assume that the thalamic targets, which relay ascending information to...

Removing Electroencephalographic Artifacts: Comparison between ICA and PCA (1998)

Tzyy-Ping Jung, Colin Humphries, Te-won Lee, Scott Makeig, Martin J. Mckeown, Vicente Iragui, ...

Pervasive electroencephalographic (EEG) artifacts associated with blinks, eye-movements, muscle noise, cardiac signals, and line noise poses a major challenge for EEG interpretation and analysis....

Learning nonlinear overcomplete representations for efficient coding (1998)

Michael S. Lewicki, Terrence J. Sejnowski, Howard Hughes

We derive a learning algorithm for inferring an overcomplete basis by viewing it as probabilistic model of the observed data. Overcomplete bases allow for better approximation of the underlying...

Computational models of thalamocortical augmenting responses (1998)

Maxim Bazhenov, Igor Timofeev, Mircea Steriade, Terrence J. Sejnowski

Repetitive stimulation of the dorsal thalamus at 7–14 Hz produces an increasing number of spikes at an increasing frequency in neocortical neurons during the first few stimuli. Possible mechanisms...

A model for encoding multiple object motions and self-motion in area MST of primate visual cortex (1998)

Richard S. Zemel, Terrence J. Sejnowski

Many cells in the dorsal part of the medial superior temporal (MST) region of visual cortex respond selectively to specific combinations of expansion/contraction, translation, and rotation motions....

Analysis of fMRI data by blind separation into independent spatial components (1998)

Martin J. Mckeown, Scott Makeig, Greg G. Brown, Tzyy-ping Jung, Ra S. Kindermann, Anthony J. Bell, ...

Abstract: Current analytical techniques applied to functional magnetic resonance imaging (fMRI) data require a priori knowledge or specific assumptions about the time courses of processes...

Interpreting Neuronal Population Activity by Reconstruction: Unified Framework With Application to Hippocampal Place Cells (1998)

Kechen Zhang, Iris Ginzburg, Bruce L. Mcnaughton, Terrence J. Sejnowski

this paper, various reconstruction methods that are the reconstruction problem, different methods were applied to multi- theoretically optimal under different frameworks are consid- electrode spike...

Blind Source Separation of More Sources Than Mixtures Using Overcomplete Representations (1998)

Te-won Lee, Michael S. Lewicki, Mark Girolami, Terrence J. Sejnowski

Empirical results were obtained for the blind source separation of more sources than mixtures using a recently proposed framework for learning overcomplete representations. This technique assumes a...

Learning Overcomplete Representations (1998)

Michael S. Lewicki, Terrence J. Sejnowski, Howard Hughes

In an overcomplete basis, the number of basis vectors is greater than the dimensionality of the input, and the representation of an input is not a unique combination of basis vectors. Overcomplete...

Learning Viewpoint Invariant Face Representations From Visual Experience in an Attractor Network (1998)

Interpreting neuronal population activity by reconstruction: A unified framework with application to hippocampal place cells (1998)

In natural visual experience, different views of an object or face tend to appear in close temporal proximity as an animal manipulates the object or navigates around it, or as a face changes...

Kechen Zhang, Iris Ginzburg, Bruce L. McNaughton, Terrence J. Sejnowski

Physical variables such as the orientation of a line in the visual field or the location of the body in space are coded as activity levels in populations of neurons. Reconstruction or decoding is an...

Independent Component Representations for Face Recognition (1998)

Marian Stewart Bartlett, H. Martin Lades, Terrence J. Sejnowski

In a task such as face recognition, much of the important information may be contained in the high-order relationships among the image pixels. A number of face recognition algorithms employ principal...

A Model for Encoding Multiple Object Motions and Self-Motion in Area MST of Primate Visual Cortex (1998)

Richard S. Zemel, Terrence J. Sejnowski

this paper, we describe a computational model based on the hypothesis that neurons in MST signal those aspects of the flow that arise from a common underlying cause. We designed the model to match...

Coding Time-Varying Signals Using Sparse, Shift-Invariant Representations (1998)

Michael S. Lewicki, Terrence J. Sejnowski

A common way to represent a time series is to divide it into shortduration blocks, each of which is then represented by a set of basis functions. A limitation of this approach, however, is that the...

A Unifying Information-theoretic Framework for Independent Component Analysis (1998)

Te-won Lee, Mark Girolami, Anthony J. Bell, Terrence J. Sejnowski

We show that different theories recently proposed for Independent Component Analysis (ICA) lead to the same iterative learning algorithm for blind separation of mixed independent sources. We review...

Independent component analysis for mixed subgaussian and super-gaussian sources (1998)

Te-won Lee, Terrence J. Sejnowski

An extension of the infomax algorithm of Bell & Sejnowski (1995) is presented that is able to separate the mixed sub- and super-Gaussian source distributions. The same learning rule has been...

Paradoxical Effects of External Modulation of Inhibitory Interneurons (1997)

Misha V. Tsodyks, William E. Skaggs, Terrence J. Sejnowski, Bruce L. Mcnaughton

The neocortex, hippocampus, and several other brain regions contain populations of excitatory principal cells with recurrent connections and strong interactions with local inhibitory interneurons. To...

The neural basis of cognitive development: A constructivist manifesto (1997)

Steven R. Quartz, Terrence J. Sejnowski, Howard Hughes

Quartz, S. & Sejnowski, T.J. (1997). The neural basis of cognitive development: A constructivist manifesto.

Independent Component Analysis Using an Extended Infomax Algorithm for Mixed Sub-Gaussian and Super-Gaussian Sources (1997)

Te-won Lee, Mark Girolami, Terrence J. Sejnowski, Howard Hughes

An extension of the infomax algorithm of Bell and Sejnowski (1995) is presented that is able to blindly separate mixed signals with sub- and super-Gaussian source distributions. This was achieved by...

Extended ICA Removes Artifacts from Electroencephalographic Recordings (1997)

Tzyy-Ping Jung, Colin Humphries, Te-won Lee, Scott Makeig, Martin J. Mckeown, Vicente Iragui, ...

Severe contamination of electroencephalographic (EEG) activity by eye movements, blinks, muscle, heart and line noise is a serious problem for EEG interpretation and analysis. Rejecting contaminated...

Extended ICA Removes Artifacts from Electroencephalographic Recordings (1997)

Colin Humphries, Te-won Lee, Scott Makeig, Martin J. Mckeown, Vicente Iragui, ...

Severe contamination of electroencephalographic (EEG) activity by eye movements, blinks, muscle, heart and line noise is a serious problem for EEG interpretation and analysis. Rejecting contaminated...

Extended ICA Removes Artifacts from Electroencephalographic Recordings (1997)

Tzyy-Ping Jung, Colin Humphries, Te-won Lee, Scott Makeig, Martin J. Mckeown, Vicente Iragui, ...

Severe contamination of electroencephalographic (EEG) activity by eye movements, blinks, and muscle, heart and line noise presents a serious problem for EEG interpretation and analysis. Rejecting...

The Neural Basis of Cognitive Development: A Constructivist Manifesto (1997)

A Constructivist Manifesto, Steven R. Quartz, Terrence J. Sejnowski, Submitted To Behavioral, Brain Sciences

The neural structures and mechanisms underlying development undergo major changes during the acquisition of cognitive skills. How can these changes be characterized, and to what extent do they alter...

Estimating Alertness from the EEG Power Spectrum (1997)

Tzyy-Ping Jung, Scott Makeig, Magnus Stensmo, Terrence J. Sejnowski

In tasks requiring sustained attention, human alertness varies on a minute time scale. This can have serious consequences in occupations ranging from air traffic control to monitoring of nuclear...

A Unifying Measure for Neighbourhood Preservation in Topographic Mappings (1997)

Geoffrey Goodhill, Steven Finch, Terrence J. Sejnowski

In this paper, the abstract computational principles underlying topographic maps are discussed. We give a definition of a "perfectly neighbourhood preserving" map, which we call a...

Paradoxical Effects of External Modulation of Inhibitory Interneurons (1997)

Misha V. Tsodyks, William E. Skaggs, Terrence J. Sejnowski, Bruce L. McNaughton

. The neocortex, hippocampus, and several other brain regions contain populations of excitatory principal cells with recurrent connections and strong interactions with local inhibitory interneurons....

The `Independent Components' of Natural Scenes are Edge Filters. (1997)

Michael S. Lewicki, Terrence J. Sejnowski, Howard Hughes

Field (1994) has suggested that neurons with line and edge selectivities found in primary visual cortex of cats and monkeys form a sparse, distributed representaton of natural scenes, and Barlow...

The Salk (1997)

Multilayer architectures such as those used in Bayesian belief networks and Helmholtz ma-chines provide a framework for representing and learning higher order statistical relations among inputs....

Varieties of attention: a model of visual search (1996)

Giedrius T. Buracas, Thomas D. Albright, Terrence J. Sejnowski

We have trained monkeys to perform a feature conjunction search task for color and motion and have recorded from neurons in area MT during the performance of this task. In order to put the...

Tempering backpropagation networks: Not all weights are created equal (1996)

Exploration bonuses and dual control (1996)

Backpropagation learning algorithms typically collapse the network's structure into a single vector of weight parameters to be optimized. We suggest that their performance may be improved by...

Peter Dayan, Terrence J Sejnowski

certainty equivalence Finding the Bayesian balance between exploration and exploitation in adaptive optimal control is in general intractable. This paper shows how to compute suboptimal estimates...

Empirical Entropy Manipulation for Real-World Problems (1996)

Paul Viola, Nicol N. Schraudolph, Terrence J. Sejnowski

No finite sample is sufficient to determine the density, and therefore the entropy, of a signal directly. Some assumption about either the functional form of the density or about its smoothness is...

Independent Component Analysis of Electroencephalographic Data (1996)

Scott Makeig, Anthony J. Bell, Tzyy-ping Jung, Terrence J. Sejnowski

Because of the distance between the skull and brain and their different resistivities, electroencephalographic (EEG) data collected from any point on the human scalp includes activity generated...

Using Feedforward Neural Networks to Monitor Alertness from Changes in EEG Correlation and Coherence (1996)

Scott Makeig, Tzyy-ping Jung, Terrence J. Sejnowski

We report here that changes in the normalized electroencephalographic (EEG) cross-spectrum can be used in conjunction with feedforward neural networks to monitor changes in alertness of operators...

Classifying Facial Action (1996)

Marian Stewart Bartlett, Paul A. Viola, Terrence J. Sejnowski, Beatrice A. Golomb, Joseph C. Hager, Paul Ekman

The Facial Action Coding System, (FACS), devised by Ekman and Friesen (1978), provides an objective means for measuring the facial muscle contractions involved in a facial expression. In this paper,...

Dynamics of Rule Induction by Making Queries: Transition Between Strategies (1996)

Iris Ginzburg, Terrence J. Sejnowski

The induction of rules by making queries is a dynamical process based on seeking information. Experimenters typically look for one dominant strategy that is used by subjects, which may or may not...

Quantifying Neighbourhood Preservation in Topographic Mappings (1996)

Geoffrey J. Goodhill, Terrence J. Sejnowski

Mappings that preserve neighbourhood relationships are important in many contexts, from neurobiology to multivariate data analysis. It is important to be clear about precisely what is meant by...

Edges are the `Independent Components' of Natural Scenes. (1996)

Optimizing Cortical Mappings (1996)

Field (1994) has suggested that neurons with line and edge selectivities found in primary visual cortex of cats and monkeys form a sparse, distributed representation of natural scenes, and Barlow...

Geoffrey J. Goodhill, Steven Finch, Terrence J. Sejnowski

"Topographic" mappings occur frequently in the brain. A popular approach to understanding the structure of such mappings is to map points representing input features in a space of a few...

Independent Component Analysis of Simulated EEG Using a Three-Shell Spherical Head Model (1996)

Dara Ghahremani, Scott Makeig, Tzyy-Ping Jung, Anthony J. Bell, Terrence J. Sejnowski

The Independent Component Analysis (ICA) algorithm 1 is a new information-theoretic approach to the problem of separating multichannel electroencephalographic (EEG) data into independent sources 2 ....

Bayesian Unsupervised Learning of Higher Order Structure (1996)

Michael Lewicki, Terrence J. Sejnowski

Multilayer architectures such as those used in Bayesian belief networks and Helmholtz machines provide a powerful framework for representing and learning higher order statistical relations among...

Tempering Backpropagation Networks: Not All Weights are Created Equal (1996)

Ionic Mechanisms Underlying Synchronized Oscillations And Propagating Waves In A Model Of Ferret Thalamic Slices (1996)

Backpropagation learning algorithms typically collapse the network's structure into a single vector of weight parameters to be optimized. We suggest that their performance may be improved by...

Alain Destexhe, Thierry Bal, David A. Mccormick, Terrence J. Sejnowski

this paper, we investigated model networks of TC and RE cells, endowed with intrinsic properties and topographic connectivity specific to the thalamus. The model reproduced the propagating properties...

Empirical Entropy Manipulation for Real-World Problems (1996)

Paul Viola, Nicol N. Schraudolph, Terrence J. Sejnowski

No finite sample is sufficient to determine the density, and therefore the entropy, of a signal directly. Some assumption about either the functional form of the density or about its smoothness is...

Learning Viewpoint Invariant Representations of Faces in an Attractor Network (1996)

Learning the Higher-Order Structure of a Natural Sound. (1996)

In natural visual experience, different views of an object tend to appear in close temporal proximity as an animal manipulates the object or navigates around it. We investigated the ability of an...

Anthony J. Bell, Terrence J. Sejnowski, Computational Neurobiology Laboratory

. Unsupervised learning algorithms paying attention only to second-order statistics ignore the phase structure (higher-order statistics) of signals, which contains all the informative temporal and...

A Dynamical Model of Context Dependencies for the Vestibulo-Ocular Reflex (1996)

Unsupervised Learning Of Invariant Representations Of Faces Through Temporal Association (1996)

The vestibulo-ocular reflex (VOR) stabilizes images on the retina during rapid head motions. The gain of the VOR (the ratio of eye to head rotation velocity) is typically around-1 when the eyes are...

A Dynamical Model of Context Dependencies for the Vestibulo-Ocular Reflex (1996)

The appearance of an object or a face changes continuously as the observer moves through the environment or as a face changes expression or pose. Recognizing an object or a face despite these image...

Terrence J. Sejnowski, Coenen Terrence, J. Sejnowski

The vestibulo-ocular reflex (VOR) stabilizes images on the retina during rapid head motions. The gain of the VOR, i.e. the ratio of eye to head rotation velocity, measured with the eyes focused at a...

Independent component analysis of electroencephalographic data (1996)

Scott Makeig, Anthony J. Bell, Tzyy-ping Jung, Terrence J. Sejnowski

Because of the distance between the skull and brain and their different resistivities, electroencephalographic (EEG) data collected from any point on the human scalp includes activity generated...

Using feedforward neural networks to monitor alertness from changes in EEG correlation and coherence (1996)

Scott Makeig, Tzyy-ping Jung, Terrence J. Sejnowski, S. Makeig

We report here that changes in the normalized electroencephalographic (EEG) cross-spectrum can be used in conjunction with feedforward neural networks to monitor changes in alertness of operators...

A Predictive Perspective on the Cerebellum (1996)

Empirical entropy manipulation for real-world problems (1996)

ved phenomena. We propose that the prediction of sensorimotor neural signals can be used to establish appropriate timing information and can play an important role to construct motor control...

Paul Viola, Nicol N. Schraudolph, Terrence J. Sejnowski

violaQsalk.edu No finite sample is sufficient to determine the density, and therefore the entropy, of a signal directly. Some assumption about either the functional form of the density or about its...

Tempering backpropagation networks: Not all weights are created equal (1996)

Nicol N. Schraudolph, Terrence J. Sejnowski, Evotec Biosystems Gmbh

Backpropagation learning algorithms typically collapse the network's structure into a single vector of weight parameters to be optimized. We suggest that their performance may be improved by...

An information-maximization approach to blind separation and blind deconvolution (1995)

A non-linear information maximisation algorithm that performs blind separation (1995)

and blind deconvolution

Plasticity-mediated competitive learning (1995)

Abstract A new learning algorithm is derived which performs online stochastic gradient ascent in the mutual information between outputs and inputs of a network. In the absence of a priori knowledge...

Using temporal-difference reinforcement learning to improve decision-theoretic utilities for diagnosis (1995)

Differentiation between the nodes of a competitive learning network is conventionally achieved through competition on the basis of neural activity. Simple inhibitory mechanisms are limited to sparse...

A mixture model system for medical and machine diagnosis (1995)

Probability theory represents and manipulates uncertainties, but cannot tell us how to behave. For that we need utility theory which assigns values to the usefulness of different states, and decision...

An Information-Maximization Approach to Blind Separation and Blind Deconvolution (1995)

Diagnosis of human disease or machine fault is a missing data problem since many variables are initially unknown. Additional information needs to be obtained. The joint probability distributionof the...

Spatial Representations in the Parietal Cortex May Use Basis Functions (1995)

We derive a new self-organising learning algorithm which maximises the information transferred in a network of non-linear units. The algorithm does not assume any knowledge of the input...

Alexandre Pouget, Terrence J. Sejnowski, Howard Hughes

The parietal cortex is thought to represent the egocentric positions of objects in particular coordinate systems. We propose an alternative approach to spatial perception of objects in the parietal...

Dynamic Remapping (1995)

Alexandre Pouget, Terrence J. Sejnowski, Howard Hughes

Introduction The term dynamic remapping has been used in many different ways but one of the clearest formulations of this concept comes from the mental rotation studies by Georgopoulos et al. (1989)....

A Novel Reinforcement Model of Birdsong Vocalization Learning (1995)

Kenji Doya, Terrence J. Sejnowski

Songbirds learn to imitate a tutor song through auditory and motor learning. We have developed a theoretical framework for song learning that accounts for response properties of neurons that have...

Quantifying Neighbourhood Preservation in Topographic Mappings (1995)

Geoffrey J. Goodhill, Steven Finch, Terrence J. Sejnowski

Mappings that preserve neighbourhood relationships are relevant in both practical and biological contexts. It is important to be clear about precisely what preserving neighbourhoods could mean. We...

A Non-linear Information Maximisation Algorithm that Performs Blind Separation. (1995)

An Information-Maximisation Approach to Blind Separation and Blind Deconvolution (1995)

A new learning algorithm is derived which performs online stochastic gradient ascent in the mutual information between outputs and inputs of a network. In the absence of a priori knowledge about the...

Fast Kinetic Models For Simulating Ampa, Nmda, Gaba_a And Gaba_b Receptors (1995)

We derive a new self-organising learning algorithm which maximises the information transferred in a network of non-linear units. The algorithm does not assume any knowledge of the input...

Alain Destexhe, Zachary F. Mainen, Terrence J. Sejnowski

Since the introduction of the alpha function by Rall in 1967 [12], there has been significant progress in our understanding of the molecular events underlying synaptic transmission. Particular...

Fast Blind Separation Based on Information Theory. (1995)

Blind Separation And Blind Deconvolution: An Information-Theoretic Approach (1995)

Blind separation is an information theoretic problem, and we have proposed an information theoretic `sigmoid-based' solution [2]. Here we elaborate on several aspects of that solution. Firstly,...

An Information-Maximisation Approachto Blind Separation and Blind Deconvolution (1995)

Blind separation and blind deconvolution are related problems in unsupervised learning. In blind separation [7], illustrated in Fig.1a, a set of sources, s 1 (t); : : : ; s N (t), (different people...

Anthony Bell And, Anthony J. Bell, Terrence J. Sejnowski

Wederive a new self-organising learning algorithm which maximises the information transferred in a network of non-linear units. The algorithm does not assume any knowledge of the input distributions,...

Plasticity-mediated competitive learning (1995)

A perceptron reveals the face of sex (1995)

Differentiation between the nodes of a competitive learning network is conventionally achieved through competition on the basis of neural activity. Simple inhibitory mechanisms are limited to sparse...

Michael S. Gray, Michael S. Gray, David T. Lawrence, David T. Lawrence, Beatrice A. Golomb, Beatrice A. Golomb, ...

Recognizing the sex of conspecifics is important. Humans rely primarily on visual pattern recdgnition for this task. In this note we show that a perceptron using normalized grey levels as input can...

Reliability of spike timing (1995)

Terrence J. Sejnowski, In C Blshop, W Maass (eds

Neurons use action potentials to signal over long distances, as summarized in Chapter 1 by Gerstner. The all-or-none nature of the action potential means that it codes information by its presence or...

UCSD School of Medicine independent study project : 1994, nos. 9-16. (1994)

Mishra, Dev K., Fithian, Donald C., Balen, Paul F., Daniel, Dale M., Rosen, Peter., Clark, Richard., ...

Thesis (M.D.)--University of California, San Diego, 1994.

Temporal difference learning of position evaluation in the game of Go (1994)

Nicol N. Schraudolph, Peter Dayan, Terrence J. Sejnowski

The game of Go has a high branching factor that defeats the tree search approach used in computer chess, and long-range spatiotemporal interactions that make position evaluation extremely difficult....

TD(λ) converges with probability 1 (1994)

Peter Dayan, Terrence J Sejnowski

The methods of temporal differences (Samuel, 1959; Sutton 1984, 1988) allow agents to learn accurate predictions about stationary stochastic future outcomes. The learning is effectively stochastic...

TD(λ) Converges with Probability 1 (1994)

Peter Dayan, Terrence J Sejnowski

The methods of temporal differences (Samuel, 1959; Sutton 1984, 1988) allow agents to learn accurate predictions about stationary stochastic future outcomes. The learning is effectively stochastic...

A Neural Model of the Cortical Representation of Egocentric Distance (1994)

Alexandre Pouget, Terrence J. Sejnowski

Neurons in the visual cortex of monkeys respond selectively to the disparity between the images in the two eyes. Recent recordings have shown that some of the disparity-selective neurons in the...

Temporal Difference Learning of Position Evaluation in the Game of Go (1994)

Nicol N. Schraudolph, Peter Dayan, Terrence J. Sejnowski

The game of Go has a high branching factor that defeats the tree search approach used in computer chess, and long-range spatiotemporal interactions that make position evaluation extremely difficult....

Associative EPSP-Spike Potentiation Induced by Pairing Orthodromic and Antidromic Stimulation in Rat Hippocampal Slices (1994)

Jennifer M. Jester, Lee W. Campbell, Terrence J. Sejnowski, Terry J. Sejnowski

ter washing out the AP5, the same stimulation resulted in population spike increases. This suggests that activation of the N-methyl-D-aspartate (NMDA) subtype of glutamate receptor is necessary for...

Modeling the Control of Reticular Thalamic Oscillations by Neuromodulators (1994)

Alain Destexhe, Diego Contreras, Terrence J. Sejnowski, Mircea Steriade

Compartmental models of thalamic reticular (RE) neurons were investigated based on current-clamp and voltage-clamp data. Spontaneous oscillations in the model arise from the interaction between...

Unsupervised discrimination of clustered data via optimization of binary information gain (1993)

Filter Selection Model for Generating Visual Motion Signals (1993)

We present the information-theoretic derivation of a learning algorithm that clusters unlabelled data with linear discriminants. In contrast to methods that try to preserve information about the...

Steven J. Nowlan, Terrence J. Sejnowski

Neurons in area MT of primate visual cortex encode the velocity of moving objects. We present a model of how MT cells aggregate responses from V1 to form such a velocity representation. Two different...

Egocentric Spatial Representation in Early Vision (1993)

Re Pouget, Steven A. Fisher, Terrence J. Sejnowski, Howard Hughes, Alexandre Pouget

Neurons encoding simple visual features in area V1 such as orientation, direction of motion and color are organized in retinotopic maps. However, recent physiological experiments have shown that the...

Biologically Plausible Local Learning Rules for the Adaptation of the Vestibulo-Ocular Reflex (1993)

Olivier Coenen, Terrence J. Sejnowski, Stephen G. Lisberger

The vestibulo-ocular reflex (VOR) is a compensatory eye movement that stabilizes images on the retina during head turns. Its magnitude, or gain, can be modified by visual experience during head...

Vision Research 42 (2002) 2095-2103 (1993)

Color Opponency Is, Te-won Lee, Thomas Wachtler, Terrence J. Sejnowski

The human visual system encodes the chromatic signals conveyed by the three types of retinal cone photoreceptors in an opponent fashion. This opponency is thought to reduce redundant information by...

Predicting responses of nonlinear neurons in monkey striate cortex to complex patterns (1992)

Sidney R. Lehky, Terrence J. Sejnowski, Robert Desimone

The overwhelming majority of neurons in primate visual cor-tex are nonlinear. For those ceils, the techniques of linear system analysis, used with some success to model retinal ganglion cells and...

Competitive Anti-Hebbian Learning of Invariants (1992)

Competitive anti-Hebbian learning of invariants (1992)

Although the detection of invariant structure in a given set of input patterns is vital to many recognition tasks, connectionist learning rules tend to focus on directions of high variance (principal...

Neural model of stereoacuity and depth interpolation based on a distributed representation of stereo disparity (1990)

Although the detection of invariant structure in a given set of input patterns is vital to many recognition tasks, connectionist learning rules tend to focus on directions of high variance (principal...

Sidney R. Lehky, Terrence J. Sejnowski

We have developed a model for the representation of stereo disparity by a population of neurons that is based on tuning curves similar in shape to those measured physiologically (Poggio and Fischer,...

ORIGINAL CONTRIBUTION Analysis of Hidden Units in a Layered Network Trained to Classify Sonar Targets (1987)

R. Paul Gorman, Terrence J. Sejnowski

Abstract--A neural network learning procedure has been applied to the classification ~/sonar returns [kom two undersea targets, a metal cylinder and a similarly shaped rock. Networks with an...

A learning algorithm for Boltzmann machines (1985)

David H. Ackley, Geoffrey E. Hinton, Terrence J. Sejnowski

The computotionol power of massively parallel networks of simple processing elements resides in the communication bandwidth provided by the hardware connections between elements. These connections...

Learning machines (1965)

Nils J. Nilsson, Terrence J. Sejnowski, Terrence J. Sejnowski, Halbert White, Halbert White

lntroduction by

Mark Liberman