Ensemble deep clustering analysis for time window determination of event-related potentials

Data availability: Data will be made available on request.Copyright © 2023 The Authors. Objective: Cluster analysis of spatio-temporal event-related potential (ERP) data is a promising tool for exploring the measurement time window of ERPs. However, even after preprocessing, the remaining noise can result in uncertain cluster maps followed by unreliable time windows while clustering via conventional clustering methods. Methods: We designed an ensemble deep clustering pipeline to determine a reliable time window for the ERP of interest from temporal concatenated grand average ERP data. The proposed pipeline includes semi-supervised deep clustering methods initialized by consensus clustering and unsupervised deep clustering methods with end-to-end architectures. Ensemble clustering from those deep clusterings was used by the designed adaptive time window determination to estimate the time window. Results: After applying simulated and real ERP data, our method successfully obtained the time window for identifying the P3 components (as the interest of both ERP studies) while additional noise (e.g., adding 20 dB to −5 dB white Gaussian noise) was added to the prepared data. Conclusion: Compared to the state-of-the-art clustering methods, a superior clustering performance was yielded from both ERP data. Furthermore, more stable and precise time windows were elicited as the noise increased. Significance: Our study provides a complementary understanding of identifying the cognitive process using deep clustering analysis to the existing studies. Our finding suggests that deep clustering can be used to identify the ERP of interest when the data is imperfect after preprocessing

Brain Evoked Response Qualification Using Multi-Set Consensus Clustering: Toward Single-Trial EEG Analysis

Data availability: This study does not include data collection from individual participants, and public data has been used.Electronic Supplementary Material: Below is the link to the electronic supplementary material. Supplementary Material 1: https://static-content.springer.com/esm/art%3A10.1007%2Fs10548-024-01074-y/MediaObjects/10548_2024_1074_MOESM1_ESM.docx .In event-related potential (ERP) analysis, it is commonly assumed that individual trials from a subject share similar properties and originate from comparable neural sources, allowing reliable interpretation of group-averages. Nevertheless, traditional group-level ERP analysis methods, including cluster analysis, often overlook critical information about individual subjects’ neural processes due to using fixed measurement intervals derived from averaging. We developed a multi-set consensus clustering pipeline to examine cognitive processes at the individual subject level. Initially, consensus clustering from diverse methods was applied to single-trial EEG epochs of individual subjects. Subsequently, a second level of consensus clustering was performed across the trials of each subject. A newly modified time window determination method was then employed to identify individual subjects’ ERP(s) of interest. We validated our method with simulated data for ERP components N2 and P3, and real data from a visual oddball task to confirm the P3 component. Our findings revealed that estimated time windows for individual subjects provide precise ERP identification compared to fixed time windows across all subjects. Additionally, Monte Carlo simulations with synthetic single-trial data demonstrated stable scores for the N2 and P3 components, confirming the reliability of our method. The proposed method enhances the examination of brain-evoked responses at the individual subject level by considering single-trial EEG data, thereby extracting mutual information relevant to the neural process. This approach offers a significant improvement over conventional ERP analysis, which relies on the averaging mechanism and fixed measurement interval.The authors have no relevant financial or non-financial interests to disclose. The authors have no funding for this study. Open Access funding provided by University of Jyväskylä (JYU)

Estimation of the ductility of web-bonded FRP beams for assessment of strengthened RC exterior joints

Beam-column joints in Reinforced Concrete (RC) moment resisting frame (MRF) subjected to lateral loads can be critical regions. They must therefore be designed adequately in order to dissipate large amounts of energy without a significant loss of strength and ductility. When the joint are inadequately designed or damaged under unanticipated loads, web-bonded FRP is one of the possible strengthening methods that can be used. In this paper, a computer model is presented in order to estimate the ductility of strengthened beams and a range of possible design charts is produced to select the type and amount of FRP required for upgrading exterior beam-column joints. Finally, displacement ductility of a subassembly is assessed using these design charts and the result is compared with experiment. The comparison proves the model is acceptable

Web-bonded FRPs for relocation of plastic hinges away from the column face in exterior RC joints

In an RC building subjected to lateral loads, the beam-column joints constitute one of the critical regions. In existing frames, which were not adequately designed, a practical way of controlling plastic hinging and implement the strong-column weak-beam concept is through the use of a web-bonded FRP retrofitting system. This paper presents the results of an experimental and numerical study carried out in order to evaluate the ability of CFRP sheets in preventing the plastic hinge formation at the face of the column in exterior RC joints. Seven scaled-down RC exterior joints of a typical Ordinary Moment Resisting Frame are tested under moderately monotonic/cyclic loads. Two specimens are used as control while the other five are CFRP-strengthened/repaired of different lengths and thicknesses. The results show that carbon fibre sheets can effectively relocate the plastic hinge away from the face of the column. Non-linear numerical results using ANSYS are also presented and discussed

Strength and ductility of FRP web-bonded RC beams for the assessment of retrofitted beam-column joints

It is generally accepted that beam-column joints are critical elements of reinforced concrete (RC) buildings subjected to lateral loads, and that they may require specific design treatment following the accepted design philosophy of the strong-column-weak-beam. In earthquake-prone regions, the joints must be designed to allow the dissipation of large amounts of energy into the neighbouring elements without a significant loss of strength and ductility. The frames are often designed carefully based on the strong-column-weak-beam concept and their joints detailed accordingly. Sometimes, though, the detailing is inadequate (example, RC joints designed to earlier codes have insufficient lateral resistance). Web-bonded FRP (fibre reinforced plastic) is one of the few possible strengthening methods that can be used when an inadequately detailed joint is damaged causing severe degradation of the joint's structural strength. In this paper, the results of some tests on FRP strengthened specimens are presented. The results show that the method is effective and capable of restoring or even upgrading the strength of the system. In addition, using the basic principles of equilibrium and compatibility, an analytical model is presented that simplifies the analysis and design of this strengthening scheme. Based on the model, a range of design graphs are presented for selection of the type and the amount of FRP required upgrading an existing joint to a specified moment capacity and curvature ductility