Low-Frequency Seismic Noise Properties in the Japanese Islands.

The records of seismic noise in Japan for the period of 1997-2020, which includes the Tohoku seismic catastrophe on 11 March 2011, are considered. The following properties of noise are analyzed: The wavelet-based Donoho-Johnston index, the singularity spectrum support width, and the entropy of the wavelet coefficients. The question of whether precursors of strong earthquakes can be formulated on their basis is investigated. Attention is paid to the time interval after the Tohoku mega-earthquake to the trends in the mean properties of low-frequency seismic noise, which reflect the constant simplification of the statistical structure of seismic vibrations. Estimates of two-dimensional probability densities of extreme values are presented, which highlight the places in which extreme values of seismic noise properties are most often realized. The estimates of the probability densities of extreme values coincide with each other and have a maximum in the region: 30° N ≤ Lat ≤ 34° N, 136° E ≤ Lon≤ 140° E. The main conclusions of the conducted studies are that the preparation of a strong earthquake is accompanied by a simplification of the structure of seismic noise. It is shown that bursts of coherence between the time series of the day length and the noise properties within annual time window precede bursts of released seismic energy. The value of the lag in the release of seismic energy relative to bursts of coherence is about 1.5 years, which can be used to declare a time interval of high seismic hazard after reaching the peak of coherence.

Properties of GPS noise at Japan islands before and after Tohoku mega-earthquake.

The field of 3-components GPS signals is analyzed for the network of 1203 stations at the Japanese islands from January 30 up to March 26, 2011. This time interval includes just over 40 days of observation before the Tohoku mega-earthquake on March 11, 2011 (M = 9.0) and nearly 16 days of observation following this event. The signals from each station are three-component time series with time step 30 minutes. We study the statistical properties of the random fluctuations of GPS signals before and after the seismic catastrophe after transition to increments. The values of wavelet-based spectral index for GPS noise components for each station were estimated separately for pieces of records before and after seismic event. The maps of the noise spectral index are constructed as the values for grid size of 50 × 50 nodes covering the region under study, based on information from 10 stations closest to each node. These maps clearly extract the region of future seismic catastrophe by relatively high noise spectral index. The using of principal components method distinguished this spatial anomaly more explicitly. These results support the hypothesis that statistical properties of random fluctuations of geophysical fields carry important information about earthquake preparation.

Toward a probabilistic definition of seizures.

This writing (1) draws attention to the intricacies inherent to the pursuit of a universal seizure definition even when powerful, well-understood signal analysis methods are used to this end; (2) identifies this aim as a multi-objective optimization problem and discusses the advantages and disadvantages of adopting or rejecting a unitary seizure definition; and (3) introduces a probabilistic measure of seizure activity to manage this thorny issue. The challenges posed by the attempt to define seizures unitarily may be partly related to their fractal properties and understood through a simplistic analogy to the so-called "Richardson effect." A revision of the time-honored conceptualization of seizures may be warranted to further advance epileptology. This article is part of a Supplemental Special Issue entitled The Future of Automated Seizure Detection and Prediction.

Automated seizure detection: unrecognized challenges, unexpected insights.

One of epileptology's fundamental aims is the formulation of a universal, internally consistent seizure definition. To assess this aim's feasibility three signal analysis methods were applied to a seizure time series and performance comparisons were undertaken among them and with respect to a validated algorithm. One of the methods uses a Fisher's matrix weighted measure of the rate of parameters change of a 2nd order auto-regressive model, another is based on the Wavelet Transform Maximum Modulus for quantification of changes in the logarithm of the standard deviation of ECoG power and yet another employs the ratio of short-to-long term averages computed from cortical signals. The central finding, fluctuating concordance among all methods' output as a function of seizure duration, uncovers unexpected hurdles in the path to a universal definition, while furnishing relevant knowledge in the dynamical (spectral non-stationarity/varying ictal signal complexity) and clinical (potential un-attainability of consensus) domains. This article is part of a Supplemental Special Issue entitled The Future of Automated Seizure Detection and Prediction.

Challenges for emerging neurostimulation-based therapies for real-time seizure control.

In step with the worthwhile aim of this special issue, two junior investigators impart their insights on the therapeutic challenges imposed by pharmacoresistant epilepsies and offer viable approaches to improvement of treatment outcomes. Sunderam's comprehensive perspective addresses issues of critical importance for the design of efficacious therapies. Talathi delves into the thorny roles of so-called "interictal" spikes in ictio- and epileptogenesis, roles that are central to understanding the dynamics of these phenomena and implicitly of how to prevent them or abort them. First, however, Osorio and co-workers illustrate the complex behavior of the epileptogenic network and point to the importance of real-time intraindividual adaptation and optimization of therapies for seizures originating from the same epileptogenic network.