The accessory olfactory system controls social and sexual behavior. However, key aspects of sensory signaling along the accessory olfactory pathway remain largely unknown. Here, we investigate patterns of spontaneous neuronal activity in mouse accessory olfactory bulb mitral cells, the direct neural link between vomeronasal sensory input and limbic output. Both in vitro and in vivo, we identify a subpopulation of mitral cells that exhibit slow stereotypical rhythmic discharge. In intrinsically rhythmogenic neurons, these periodic activity patterns are maintained in absence of fast synaptic drive. The physiological mechanism underlying mitral cell autorhythmicity involves cyclic activation of three interdependent ionic conductances: subthreshold persistent Na ϩ current, R-type Ca 2ϩ current, and Ca 2ϩ -activated big conductance K ϩ current. Together, the interplay of these distinct conductances triggers infraslow intrinsic oscillations with remarkable periodicity, a default output state likely to affect sensory processing in limbic circuits.
Various spectrum sensing approaches have been shown to suffer from a so-called signal-to-noise ratio (SNR)-wall, an SNR value below which a detector cannot perform robustly no matter how many observations are used. Up to now, the eigenvalue-based maximum-minimum-eigenvalue (MME) detector has been a notable exception. For instance, the model uncertainty of imperfect knowledge of the receiver noise power, which is known to be responsible for the energy detector's fundamental limits, does not adversely affect the maximum-minimum-eigenvalue (MME) detector's performance. While additive white Gaussian noise (AWGN) is a standard assumption in wireless communications, it is not a reasonable one for the maximum-minimum-eigenvalue (MME) detector. In fact, in this work, we prove that uncertainty in the amount of noise coloring does lead to an SNR wall for the maximum-minimum-eigenvalue (MME) detector. We derive a lower bound on this SNR wall and evaluate it for example scenarios. The findings are supported by numerical simulations.
Magnetic induction measurements enable contactless monitoring of breathing and heart activity. Since this technique is in the scope of many research groups, there are several research devices available. Most of these devices are suitable for tomography approaches, e.g. edema detection or for monitoring technical processes, such as fluid in tubes or metal blocks. However, these devices are less useable for vital parameter monitoring. In this article, we present an new modular magnetic induction measurement system called MONTOS (Monitoring System) for this scenario. Since the implementation is fully digital, each module can easily be applied to several measurement conditions in vital parameter monitoring, i.e. Multi-Frequency measurement modes, Single-Excitation and Multiple-Measurements or Multiple-Excitation and Single-Measurement. Data output is realized via local area networks (LAN), thereby streaming the data to a monitoring computer. Finally, it will be demonstrated that impedance changes due to breathing of a human adult can be detected.
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