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Abstract: The westernmost Nankai Trough, southwest Japan, exhibits a rapid along-strike reduction in plate coupling in the proximity to the subducting Kyushu-Palau ridge. Yet how and to what extent the ridge subduction impacts physical properties at the megathrust have not been investigated. Here we present high-resolution seismic P-wave velocity models along the forearc wedge in the western Nankai Trough derived from full-waveform inversion analyses of seismic refraction data. The velocity models show that where the plate coupling is weak and the plate boundary presumably hosts slow earthquakes, the upper plate exhibits lower seismic velocities indicating higher degree of fracturing over a ~ 100 km length along trough. Intriguingly, the extent of the upper-plate low-velocity features is significantly larger than the surficial width of the Kyushu-Palau ridge, and this low-velocity zone is underthrust by the slab with increased crustal thickness by 2–4 km. Seismic reflection images consistently reveal that the thicker slab crust has appreciable basement roughness extending ~ 60 km from the eastern margin of the Kyushu-Palau ridge beneath the western Shikoku basin. We suggest that such a thicker and rugged slab crust, together with the main body of the Kyushu-Palau ridge, can cause significant fracture zones in the overriding plate, decrease the interplate coupling and produce preferable conditions for shallow slow earthquakes to occur when subducted. The results may also provide structural constraints on the western limit of future megathrust earthquakes in the Nankai Trough. Graphical Abstract

Author(s): Dan Bassett (corresponding author) [1]; David T. Sandwell [1]; Yuri Fialko [1]; Anthony B. Watts [2] The March 2011 Tohoku-oki earthquake was only the second giant (moment magnitude M [...]

We present a high‐resolution three‐dimensional (3‐D) anisotropic P wave velocity (Vp) model in the northern Hikurangi margin offshore Gisborne, New Zealand, constructed by tomographic inversion of over 430,000 first arrivals recorded by a dense grid of ocean bottom seismometers. Since the study area covers a region where shallow slow slip events (SSEs) occur repeatedly and the subduction of a seamount is proposed, it offers an ideal location to link our understanding of structural and hydrogeologic properties at megathrust faults to slip behavior. The Vp model reveals an ~30‐km‐wide, low‐velocity accretionary wedge at the toe of the overriding plate, where previous seismic reflection studies show a series of active thrust faults branching from the plate interface. We find some locations with significant Vp azimuthal anisotropy >5% near the branching faults and the deformation front. This finding suggests that the anisotropy is not ubiquitous and homogeneous within the overriding plate, but more localized in the vicinity of active thrust faults. The fast axes of Vp within the accretionary wedge are mostly oriented to the plate convergence direction, which is interpreted as preferentially oriented cracks in a compressional stress regime associated with plate subduction. We find that the magnitudes of anisotropy are roughly equivalent to values found at oceanic spreading centers, where the extensional stress regime is dominant and the crack density is expected to be higher than subduction zones. This consideration may indicate that additional effects such as fault foliation and clay mineral alignment also contribute to upper plate anisotropy along subduction margins. Plain Language Summary: We use man‐made sound waves (controlled‐source seismic data) to reveal in three dimensions the speed of sound within rocks and sediments that make up the northern Hikurangi margin off the east coast of North Island, New Zealand. We find that the sediments lying on top of subducting plate (accretionary wedge) have low velocities and host several branching faults. We also find that the speed of sound is faster when measured in the direction that the plates are colliding and slower when measured parallel to the faults (this phenomenon is called seismic anisotropy). This difference in speed suggests that the faults contain cracks that are aligned parallel to the direction of the plate subduction. Key Points: We present a three‐dimensional anisotropic P wave velocity model in northern Hikurangi from traveltime tomography using NZ3D OBS dataWe find evidence for fault‐bound anisotropy that azimuthal anisotropy is larger in the vicinity of the splay faults and deformation frontAnisotropy magnitude >5% may indicate preferentially oriented cracks and along‐fault clay‐rich layers contribute to upper plate anisotropy [ABSTRACT FROM AUTHOR]

The brain is a complex, multiscale dynamical system composed of many interacting regions. Knowledge of the spatiotemporal organization of these interactions is critical for establishing a solid understanding of the brain’s functional architecture and the relationship between neural dynamics and cognition in health and disease. The possibility of studying these dynamics through careful analysis of neuroimaging data has catalyzed substantial interest in methods that estimate time-resolved fluctuations in functional connectivity (often referred to as “dynamic” or time-varying functional connectivity; TVFC). At the same time, debates have emerged regarding the application of TVFC analyses to resting fMRI data, and about the statistical validity, physiological origins, and cognitive and behavioral relevance of resting TVFC. These and other unresolved issues complicate interpretation of resting TVFC findings and limit the insights that can be gained from this promising new research area. This article brings together scientists with a variety of perspectives on resting TVFC to review the current literature in light of these issues. We introduce core concepts, define key terms, summarize controversies and open questions, and present a forward-looking perspective on how resting TVFC analyses can be rigorously and productively applied to investigate a wide range of questions in cognitive and systems neuroscience.

Network neuroscience applied to epilepsy holds promise to map pathological networks, localize seizure generators, and inform targeted interventions to control seizures. However, incomplete sampling of the epileptic brain because of sparse placement of intracranial electrodes may affect model results. In this study, we evaluate the sensitivity of several published network measures to incomplete spatial sampling and propose an algorithm using network subsampling to determine confidence in model results. We retrospectively evaluated intracranial EEG data from 28 patients implanted with grid, strip, and depth electrodes during evaluation for epilepsy surgery. We recalculated global and local network metrics after randomly and systematically removing subsets of intracranial EEG electrode contacts. We found that sensitivity to incomplete sampling varied significantly across network metrics. This sensitivity was largely independent of whether seizure onset zone contacts were targeted or spared from removal. We present an algorithm using random subsampling to compute patient-specific confidence intervals for network localizations. Our findings highlight the difference in robustness between commonly used network metrics and provide tools to assess confidence in intracranial network localization. We present these techniques as an important step toward translating personalized network models of seizures into rigorous, quantitative approaches to invasive therapy.