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Sterling, M.

Publications and source records attributed to Sterling, M..

2 recordsLinked to original sources

Rodent ultrasonic vocal interaction resolved with millimeter precision using hybrid beamforming

Ultrasonic vocalizations (USVs) fulfill an important role in communication and navigation in many species. Because of their social and affective significance, rodent USVs are increasingly used as a behavioral measure in neurodevelopmental and neurolinguistic research. Reliably attributing USVs to their emitter during close interactions has emerged as a difficult, key challenge. If addressed, all subsequent analyses gain substantial confidence. We present a hybrid ultrasonic tracking system, HyVL, that synergistically integrates a high-resolution acoustic camera with high-quality ultrasonic microphones. HyVL is the first to achieve millimeter precision (~3.4-4.8mm, 91% assigned) in localizing USVs, ~3x better than other systems, approaching the physical limits (mouse snout ~ 10mm). We analyze mouse courtship interactions and demonstrate that males and females vocalize in starkly different relative spatial positions, and that the fraction of female vocalizations has likely been overestimated previously due to imprecise localization. Further, we find that male mice vocalize more intensely when interacting with two mice, an effect mostly driven by the dominant male. HyVL substantially improves the precision with which social communication between rodents can be studied. It is also affordable, open-source, easy to set up, can be integrated with existing setups, and reduces the required number of experiments and animals. Data & Code AvailabilityDuring the review process, reviewers can access all Data and Code via the link below: https://data.donders.ru.nl/loqin/reviewer-208072048/iJ4c-oRNlPIp3vArKiYQ0lAW9FipiHL8foxSzwt1FDAUpon acceptance, these materials will be made available to the public.

animal behavior and cognition↗

Genetic, lifestyle and environmental risk factors for chronic pain revealed through GWAS

Chronic pain (CP) is a leading cause of disability worldwide with complex aetiologies that remain elusive. Here we addressed this issue by performing a GWAS on a large UK Biobank sample (N=188,352 cases & N=69,627 controls) which identified two independent loci associated with CP near ADAMTS6 and LEMD2. Gene-based tests revealed additional CP-associated genes (DCAKD, NMT1, MLN, IP6K3). Across 1328 complex traits, 548 (41%) were genetically correlated with CP, of which 175 (13%) showed genetic causal relationships using the latent causal variable approach and Mendelian randomization. In particular, major depressive disorder, anxiety, smoking, body fat & BMI were found to increase the risk of CP, whereas diet, walking for pleasure & higher educational attainment were associated with a reduced risk (i.e., protective effect). This data-driven hypothesis-free approach has uncovered several specific risk factors that warrant further examination in longitudinal trials to help deliver effective early screening & management strategies for CP.

genetics↗