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There is a lack of multi-session P300 datasets for Brain-Computer Interfaces (BCI). Publicly available datasets are usually limited by small number of participants with few BCI sessions. In this sense, the lack of large, comprehensive datasets with various individuals and multiple sessions has limited advances in the development of more effective data processing and analysis methods for BCI systems. This is particularly evident to explore the feasibility of deep learning methods that require large datasets. Here we present the BCIAUT-P300 dataset, containing 15 autism spectrum disorder individuals undergoing 7 sessions of P300-based BCI joint-attention training, for a total of 105 sessions. The dataset was used for the 2019 IFMBE Scientific Challenge organized during MEDICON 2019 where, in two phases, teams from all over the world tried to achieve the best possible object-detection accuracy based on the P300 signals. This paper presents the characteristics of the dataset and the approaches followed by the 9 finalist teams during the competition. The winner obtained an average accuracy of 92.3% with a convolutional neural network based on EEGNet. The dataset is now publicly released and stands as a benchmark for future P300-based BCI algorithms based on multiple session data.

We conducted a systematic analysis of the temporal and spatial patterns of Cenozoic deformation of the northeastern (NE) and southwestern (SW) parts of the Qaidam Basin, the largest and thickest Cenozoic sedimentary basin within the Tibetan Plateau, by constructing balanced cross-sections traversing the whole basin using high-resolution seismicreflection data. We found that that these two parts deformed synchronously with similar temporal patterns involving nearly constant NE-SW contraction before c. 2.5 Ma and much more intense shortening, possibly enhanced by fierce wind erosion, since then. However, the spatial deformation patterns of these two areas differ markedly: an eastward weakening trend in the SW part is not observed in the NE part. We believe that this difference is due to their different boundary conditions. This result places new constraints on the formation mechanisms of the northern Tibetan Plateau.

There has been a growing interest in computational electroencephalogram (EEG) signal processing in a diverse set of domains, such as cortical excitability analysis, event-related synchronization, or desynchronization analysis. In recent years, several inconsistencies were found across different EEG studies, which authors often attributed to methodological differences. However, the assessment of such discrepancies is deeply underexplored. It is currently unknown if methodological differences can fully explain emerging differences and the nature of these differences. This study aims to contrast widely used methodological approaches in EEG processing and compare their effects on the outcome variables. To this end, two publicly available datasets were collected, each having unique traits so as to validate the results in two different EEG territories. The first dataset included signals with event-related potentials (visual stimulation) from 45 subjects. The second dataset included resting state EEG signals from 16 subjects. Five EEG processing steps, involved in the computation of power and phase quantities of EEG frequency bands, were explored in this study: artifact removal choices (with and without artifact removal), EEG signal transformation choices (raw EEG channels, Hjorth transformed channels, and averaged channels across primary motor cortex), filtering algorithms (Butterworth filter and Blackman–Harris window), EEG time window choices (−750 ms to 0 ms and −250 ms to 0 ms), and power spectral density (PSD) estimation algorithms (Welch’s method, Fast Fourier Transform, and Burg’s method). Powers and phases estimated by carrying out variations of these five methods were analyzed statistically for all subjects. The results indicated that the choices in EEG transformation and time-window can strongly affect the PSD quantities in a variety of ways. Additionally, EEG transformation and filter choices can influence phase quantities significantly. These results raise the need for a consistent and standard EEG processing pipeline for computational EEG studies. Consistency of signal processing methods cannot only help produce comparable results and reproducible research, but also pave the way for federated machine learning methods, e.g., where model parameters rather than data are shared.

The Altyn Tagh fault (ATF) plays a significant role in the northward growth of the Tibetan Plateau, but its Cenozoic kinematics and related structural response in adjacent basins remain debated. In this study, we identified a transition zone between the ATF and the Qaidam Basin interior and termed it the Altyn Slope, based on a dense network of two-and three-dimensional seismic reflection profiles and isopach maps. Tilted by a series of E-W-trending transpressional faults that constitute the positive flower structure of the ATF, the present Altyn Slope is characterized by a southeast-dipping slope with its undulating southeastern boundary with peaks coincidentally located at the major anticlinal belts in the basin. We propose a method for restoring the Ceno zoic tilting history of the Altyn Slope during different time periods by identifying growth-strata geometry from the recent isopach maps. The results show that the Altyn Slope began to form in the late Eocene (ca. 40 Ma) and continued to expand until the mid-Miocene (ca. 15 Ma) albeit with a temporally developing shape. However, the Altyn Slope shrank toward the ATF and underwent significant NE-SW-directed folding since the mid-Miocene (ca. 15 Ma), resulting in formation of undulations of its southeastern boundary. We thus infer that the left-slip motion on the ATF is divided into two distinct stages: during the first stage, ca. 40-15 Ma, the ATF was activated with slow slip rate, and most transpressional stress was converted to vertical strain, raising the Altyn Slope instead of producing strike-slip motion. During the second stage, since ca. 15 Ma, faster sinistral strike-slip motion on the ATF took place, releasing the stress beneath the Altyn Slope and inducing intense NE-SW-directed shortening within the Northern Tibetan Plateau.