Insects and mammals share similarities of neural organization underlying the perception of odors, taste, vision, sound, and gravity. We observed that insect somatosensation also corresponds to that of mammals. In , the projections of all the somatosensory neuron types to the insect's equivalent of the spinal cord segregated into modality-specific layers comparable to those in mammals. Some sensory neurons innervate the ventral brain directly to form modality-specific and topological somatosensory maps. Ascending interneurons with dendrites in matching layers of the nerve cord send axons that converge to respective brain regions. Pathways arising from leg somatosensory neurons encode distinct qualities of leg movement information and play different roles in ground detection. Establishment of the ground pattern and genetic tools for neuronal manipulation should provide the basis for elucidating the mechanisms underlying somatosensation.

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S U M M A R YThe particle motion of surface waves, in addition to phase and group velocities, can provide useful information for S-wave velocity structure in the crust and upper mantle. In this study, we applied a new method to retrieve velocity structure using the ZH ratio, the ratio between vertical and horizontal surface amplitudes of Rayleigh waves. Analysing data from the GEOSCOPE network, we measured the ZH ratios for frequencies between 0.004 and 0.05 Hz (period between 20 and 250 s) and inverted them for S-wave velocity structure beneath each station. Our analysis showed that the resolving power of the ZH ratio is limited and final solutions display dependence on starting models; in particular, the depth of the Moho in the starting model is important in order to get reliable results. Thus, initial models for the inversion need to be carefully constructed. We chose PREM and CRUST2.0 in this study as a starting model for all but one station (ECH). The eigenvalue analysis of the least-squares problem that arises for each step of the iterative process shows a few dominant eigenvalues which explains the cause of the inversion's initial-model dependence. However, the ZH ratio is unique in having high sensitivity to near-surface structure and thus provides complementary information to phase and group velocities. Application of this method to GEOSCOPE data suggest that low velocity zones may exist beneath some stations near hotspots. Our tests with different starting models show that the models with low-velocity anomalies fit better to the ZH ratio data. Such low velocity zones are seen near Hawaii (station KIP), Crozet Island (CRZF) and Djibuti (ATD) but not near Reunion Island (RER). It is also found near Echery (ECH) which is in a geothermal area. However, this method has a tendency to produce spurious low velocity zones and resolution of the low velocity zones requires further careful study. We also performed simultaneous inversions for volumetric perturbation and discontinuitydepth perturbation. While its formulation and inversion were straightforward, there seemed to be a difficult trade-off problem between volumetric perturbation and discontinuity-depth perturbation.

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[1] By applying the noise cross-correlation technique to Apollo 17 Lunar Seismic Profiling Experiment (LSPE) data, we discovered temporal changes in Rayleigh-wave group velocity within a diurnal cycle (29.53 d). Assuming that this phenomenon is caused by density and seismic parameter changes due to temperature, we formulated an inverse problem. Thermal diffusivity serves as the key parameter for this problem because it controls the depth penetration of temperature change. The results of inversion indicate that a typical number for the thermal diffusivity of terrestrial rocks (k % 10 À6 m 2 /s) is too large to fit the data. Our preferred value is about k % 10 À7 (m 2 /s), although the inversion alone cannot discriminate among the values below this number. Differences between this estimate and a lower estimate (k % 10 À8 m 2 /s) by Langseth et al. may indicate the significance of radiation for thermal transfer in the upper-most lunar crust. We also find a direct correlation between the Rayleigh-wave amplitudes and the statistics of thermal moonquakes, both of which change with the diurnal periodicity and peak at sunset. This implies that thermal moonquakes are the source of valuable seismic noise, lending strong support to an idea proposed by Larose et al. This is in contrast to the terrestrial situation where the ocean-generated noise plays a critical role in the cross-correlation approach. The noise correlation approach is potentially useful for many planets which undergo wide swings in surface temperature and thus potentially have thermal quakes.Citation: Tanimoto, T., M. Eitzel, and T. Yano (2008), The noise cross-correlation approach for Apollo 17 LSPE data: Diurnal change in seismic parameters in shallow lunar crust,

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