This article introduces an extremely simple and local learning rule for to pographic map formatio... more This article introduces an extremely simple and local learning rule for to pographic map formation. The rule, called the maximum entropy learning rule (MER), maximizes the unconditional entropy of the map's output for any type of input distribution. The aim of this article is to show that MER is a viable strategy for building topographic maps that maximize the average
Chaos an Interdisciplinary Journal of Nonlinear Science, Sep 1, 2008
We apply an information-theoretic measure for phase synchrony to local field potentials (LFPs) [c... more We apply an information-theoretic measure for phase synchrony to local field potentials (LFPs) [corrected] recorded with a multi-electrode array implanted in area V4 of the monkey visual cortex. We show for the first time statistically significant stimulus-dependent synchrony of the visual cortical LFPs and this during different, short time intervals of the response. Furthermore, we could compute waves of synchronous activity over the array and correlate their timing with the stimulus-dependent difference in synchrony [corrected]
Every year about 1.2 million people die in auto accidents. Approximately every min-ute one person... more Every year about 1.2 million people die in auto accidents. Approximately every min-ute one person dies in car crash. More than 80% of accidents are collisions between moving objects. This sad statistics reveals why developing on-board drive assistance system became an ...
Recently developed CMOS-based microprobes contain hundreds of electrodes on a single shaft with i... more Recently developed CMOS-based microprobes contain hundreds of electrodes on a single shaft with inter-electrode distances as small as 30 μm. So far, neuroscientists needed to select electrodes manually from hundreds of electrodes. Here we present an electronic depth control algorithm that allows to select electrodes automatically, hereby allowing to reduce the amount of data and locating those electrodes that are close to neurons. The electrodes are selected according to a new penalized signal-to-noise ratio (PSNR) criterion that demotes electrodes from becoming selected if their signals are redundant with previously selected electrodes. It is shown that, using the PSNR, interneurons generating smaller spikes are also selected. We developed a model that aims to evaluate algorithms for electronic depth control, but also generates benchmark data for testing spike sorting and spike detection algorithms. The model comprises a realistic tufted pyramidal cell, non-tufted pyramidal cells and inhibitory interneurons. All neurons are synaptically activated by hundreds of fibers. This arrangement allows the algorithms to be tested in more realistic conditions, including backgrounds of synaptic potentials, varying spike rates with bursting and spike amplitude attenuation.
The paper is an overview of the most frequently used neural network algo- rithms for implementing... more The paper is an overview of the most frequently used neural network algo- rithms for implementing Independent Component Analysis (ICA). The performance of six structurally different algorithms was ranked in blind separation of independent artifi- cially generated signals using the stationary linear ICA model. Ranking of the estimated components was also carried out and compared among different ICA approaches. All
Although EEG experiments over the past decades have shown numerous applications for brain-compute... more Although EEG experiments over the past decades have shown numerous applications for brain-computer interfacing (BCI), there is a need for user-friendly BCI devices that can be used in real-world situations. 3D anthropometry and statistical shape modeling have been shown to improve the fit of devices such as helmets and respirators, and thus they might also be suitable to design BCI headgear that better fits the size and shape variation of the human head. In this paper, a new design method for BCI devices is proposed and evaluated. A one-size-fits-all BCI headset frame is designed on the basis of three digital mannequins derived from a shape model of the human head. To verify the design, the geometric fit, stability and repeatability of the prototype were compared to an EEG cap and a commercial BCI headset in a preliminary experiment. Most design specifications were met, and all the results were found to be similar to those of the commercial headset. Therefore, the suggested design method is a feasible alternative to traditional anthropometric design for BCI headsets and similar headgear.
The local mean decomposition (LMD) has been recently developed for the analysis of time series wh... more The local mean decomposition (LMD) has been recently developed for the analysis of time series which have nonlinearity and nonstationarity. The smoothed local mean of the LMD surpasses the cubic spline method used by the empirical mode decomposition (EMD) to ...
We develop the general, multivariate case of the Edgeworth approximation of differential entropy ... more We develop the general, multivariate case of the Edgeworth approximation of differential entropy and show that it can be more accurate than the nearest-neighbor method in the multivariate case and that it scales better with sample size. Furthermore, we introduce mutual information estimation as an application.
This article introduces an extremely simple and local learning rule for to pographic map formatio... more This article introduces an extremely simple and local learning rule for to pographic map formation. The rule, called the maximum entropy learning rule (MER), maximizes the unconditional entropy of the map's output for any type of input distribution. The aim of this article is to show that MER is a viable strategy for building topographic maps that maximize the average
Chaos an Interdisciplinary Journal of Nonlinear Science, Sep 1, 2008
We apply an information-theoretic measure for phase synchrony to local field potentials (LFPs) [c... more We apply an information-theoretic measure for phase synchrony to local field potentials (LFPs) [corrected] recorded with a multi-electrode array implanted in area V4 of the monkey visual cortex. We show for the first time statistically significant stimulus-dependent synchrony of the visual cortical LFPs and this during different, short time intervals of the response. Furthermore, we could compute waves of synchronous activity over the array and correlate their timing with the stimulus-dependent difference in synchrony [corrected]
Every year about 1.2 million people die in auto accidents. Approximately every min-ute one person... more Every year about 1.2 million people die in auto accidents. Approximately every min-ute one person dies in car crash. More than 80% of accidents are collisions between moving objects. This sad statistics reveals why developing on-board drive assistance system became an ...
Recently developed CMOS-based microprobes contain hundreds of electrodes on a single shaft with i... more Recently developed CMOS-based microprobes contain hundreds of electrodes on a single shaft with inter-electrode distances as small as 30 μm. So far, neuroscientists needed to select electrodes manually from hundreds of electrodes. Here we present an electronic depth control algorithm that allows to select electrodes automatically, hereby allowing to reduce the amount of data and locating those electrodes that are close to neurons. The electrodes are selected according to a new penalized signal-to-noise ratio (PSNR) criterion that demotes electrodes from becoming selected if their signals are redundant with previously selected electrodes. It is shown that, using the PSNR, interneurons generating smaller spikes are also selected. We developed a model that aims to evaluate algorithms for electronic depth control, but also generates benchmark data for testing spike sorting and spike detection algorithms. The model comprises a realistic tufted pyramidal cell, non-tufted pyramidal cells and inhibitory interneurons. All neurons are synaptically activated by hundreds of fibers. This arrangement allows the algorithms to be tested in more realistic conditions, including backgrounds of synaptic potentials, varying spike rates with bursting and spike amplitude attenuation.
The paper is an overview of the most frequently used neural network algo- rithms for implementing... more The paper is an overview of the most frequently used neural network algo- rithms for implementing Independent Component Analysis (ICA). The performance of six structurally different algorithms was ranked in blind separation of independent artifi- cially generated signals using the stationary linear ICA model. Ranking of the estimated components was also carried out and compared among different ICA approaches. All
Although EEG experiments over the past decades have shown numerous applications for brain-compute... more Although EEG experiments over the past decades have shown numerous applications for brain-computer interfacing (BCI), there is a need for user-friendly BCI devices that can be used in real-world situations. 3D anthropometry and statistical shape modeling have been shown to improve the fit of devices such as helmets and respirators, and thus they might also be suitable to design BCI headgear that better fits the size and shape variation of the human head. In this paper, a new design method for BCI devices is proposed and evaluated. A one-size-fits-all BCI headset frame is designed on the basis of three digital mannequins derived from a shape model of the human head. To verify the design, the geometric fit, stability and repeatability of the prototype were compared to an EEG cap and a commercial BCI headset in a preliminary experiment. Most design specifications were met, and all the results were found to be similar to those of the commercial headset. Therefore, the suggested design method is a feasible alternative to traditional anthropometric design for BCI headsets and similar headgear.
The local mean decomposition (LMD) has been recently developed for the analysis of time series wh... more The local mean decomposition (LMD) has been recently developed for the analysis of time series which have nonlinearity and nonstationarity. The smoothed local mean of the LMD surpasses the cubic spline method used by the empirical mode decomposition (EMD) to ...
We develop the general, multivariate case of the Edgeworth approximation of differential entropy ... more We develop the general, multivariate case of the Edgeworth approximation of differential entropy and show that it can be more accurate than the nearest-neighbor method in the multivariate case and that it scales better with sample size. Furthermore, we introduce mutual information estimation as an application.
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