Выбор оптимального количества бинов для расчета взаимной информации между сигналами ЭЭГ и кардиоритмограммы

В роботі розглянуто метод визначення взаємної інформації для оцінки взаємозв’язку між сигналами ЕЕГ та кардіоритмограми. У розробленому методі кількість бінів вибирається базуючись на значеннях взаємної інформації, які розраховані на проміжку значень бінів. При застосуванні методу до сигналів ЕЕГ та КРГ було знайдено, що метод може бути застосований при аналізі взаємозв’язку між сигналами ЕЕГ в каналах, що розташовані поряд або симетрично, згідно з системою 10-20. Для взаємної інформації між сигналами ЕЕГ та КРГ, що пов’язані у значно меншій мірі, метод не може бути застосований для малого обсягу вибірки.In the present work the problem of optimal bin number selection for equidistant Mutual Information (MI) estimator between electroencephalogram (EEG) and cardiorhythmogram (CRG) is addressed. In the previously developed method the bin number selected based on the finding an optimal bin number on the MI values on the range of bin numbers. With application to the real raw EEG and CRG signals it was found that for closely placed or symmetrical channels of EEG data the method can be applied, and the true value of MI value can be found with proposed method. In application to MI calculation between raw EEG and CRG signals that are not significantly coupled, true MI value cannot be estimated with proposed method for small sample size.В работе рассмотрен метод определения взаимной информации для оценки взаимосвязи между сигналами ЭЭГ и кардиоритмограммы. В разработанном методе количество бинов выбирается на промежутке значений бинов. При применении метода к сигналам ЭЭГ и КРГ было найдено, что метод может быть применим при анализе взаимосвязи между сигналами ЭЭГ в каналах, что расположены рядом или симметрично, в соответствии с системой 10-20. Для взаимной информации между сигналами ЭЭГ и КРГ, что связаны в значительно меньшей мере, метод не может применяться для малого значения выборки

A framework for quantitative analysis of user-generated spatial data

This paper proposes a new framework for automated analysis of game-play metrics for aiding game designers in finding out the critical aspects of the game caused by factors like design modications, change in playing style, etc. The core of the algorithm measures similarity between spatial distribution of user generated in-game events and automatically ranks them in order of importance. The feasibility of the method is demonstrated on a data set collected from a modern, multiplayer First Person Shooter, together with application examples of its use. The proposed framework can be used to accompany traditional testing tools and make the game design process more efficient

Bursting activity spreading through asymmetric interactions

People communicate with those who have the same background or share a common interest by using a social networking service (SNS). News or messages propagate through inhomogeneous connections in an SNS by sharing or facilitating additional comments. Such human activity is known to lead to endogenous bursting in the rate of message occurrences. We analyze a multi-dimensional self-exciting process to reveal dependence of the bursting activity on the topology of connections and the distribution of interaction strength on the connections. We determine the critical conditions for the cases where interaction strength is regulated at either the point of input or output for each person. In the input regulation condition, the network may exhibit bursting with infinitesimal interaction strength, if the dispersion of the degrees diverges as in the scale-free networks. In contrast, in the output regulation condition, the critical value of interaction strength, represented by the average number of events added by a single event, is a constant $1-1/\sqrt{2} \approx 0.3$, independent of the degree dispersion. Thus, the stability in human activity crucially depends on not only the topology of connections but also the manner in which interactions are distributed among the connections.Comment: 8 pages, 8 figure

Temporal structure in spiking patterns of ganglion cells defines perceptual thresholds in rodents with subretinal prosthesis.

Subretinal prostheses are designed to restore sight in patients blinded by retinal degeneration using electrical stimulation of the inner retinal neurons. To relate retinal output to perception, we studied behavioral thresholds in blind rats with photovoltaic subretinal prostheses stimulated by full-field pulsed illumination at 20 Hz, and measured retinal ganglion cell (RGC) responses to similar stimuli ex-vivo. Behaviorally, rats exhibited startling response to changes in brightness, with an average contrast threshold of 12%, which could not be explained by changes in the average RGC spiking rate. However, RGCs exhibited millisecond-scale variations in spike timing, even when the average rate did not change significantly. At 12% temporal contrast, changes in firing patterns of prosthetic response were as significant as with 2.3% contrast steps in visible light stimulation of healthy retinas. This suggests that millisecond-scale changes in spiking patterns define perceptual thresholds of prosthetic vision. Response to the last pulse in the stimulation burst lasted longer than the steady-state response during the burst. This may be interpreted as an excitatory OFF response to prosthetic stimulation, and can explain behavioral response to decrease in illumination. Contrast enhancement of images prior to delivery to subretinal prosthesis can partially compensate for reduced contrast sensitivity of prosthetic vision