A Flight Sensory-Motor to Olfactory Histamine Circuit Mediates Olfactory Processing of Ecologically and Behaviorally Natural Stimuli

Environmental pressures have conferred species specific behavioral and morphological traits to optimize reproductive success. To optimally interact with their environment, nervous systems have evolved motor-to-sensory circuits that mediate the processing of its own reafference. Moth flight behavioral patterns to odor sources are stereotyped, presumably to optimize the likelihood of interacting with the odor source. In the moth Manduca sexta wing beating causes oscillatory flow of air over the antenna; because of this, odorant-antennal interactions are oscillatory in nature. Electroantennogram recordings on antennae show that the biophysical properties of their spiking activity can effectively track odors presented at the wing beat frequency. Psychophysical experiments using Manduca show that when odors are pulsed, as opposed to presented as a continuous stream, detection and discrimination thresholds are lowered. In this study, we characterized histamine immunoreactivity in the thoracic ganglia and brain of Manduca. We generated antibodies for and characterized the distribution of the histamine B receptor, the first known antibody for this receptor protein. Our results show an elaborate pair of neurons projecting from the mesothoracic ganglion to the brain, including axon innervation of the antennal lobe and antennal mechanosensory and motor centers. Additionally, histamine B receptor labeling overlapped with a subset of GABAergic and peptidergic local interneurons. Next, we characterized the response properties of these cells within the context of fictive flight behavior and found a tonic increase in activity. Furthermore, disrupting this circuit, with surgical ablation and pharmacology, disrupts antennal lobe projection neurons from entraining to odors presented at a natural 20 Hz frequency, as well as behavioral measures of detection and discrimination thresholds. Finally, we characterized the relationship between motor patterns/behaviors, and circuit structure of this pair of histamine immunoreactive neurons. Specifically, presence of MDHn axon collaterals entering the antennal lobe is correlated with olfactory-guided target approach behaviors in crepuscular and nocturnal moths who require stereotyped zigzagging and wing beating behaviors for locating an olfactory target have axonal ramifications in the antennal lobe. This study is the first characterization of a motor to olfactory corollary discharge circuit in invertebrates and may represent the first characterization of a higher order corollary discharge circuit in an invertebrate model

Grid Multi-Butterfly Memristive Neural Network With Three Memristive Systems: Modeling, Dynamic Analysis, and Application in Police IoT

© 2024, IEEE. This is an open access accepted manuscript distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/Nowadays, the Internet of Things (IoT) technology has been widely applied in the police security system. However, with more and more image data that concerns crime scenes being transmitted through the police IoT, there are some new security and privacy issues. Therefore, how to design a safe and efficient secret image sharing solution suitable for police IoT has become a very urgent task. In this work, a grid multi-butterfly memristive Hopfield neural network (HNN) with three memristive systems is constructed and its complex dynamics are deeply analyzed. Among them, the first memristive system is modeled by emulating a self connection synapse, the second memristive system is modeled by coupling two neurons, and the third memristive system is modeled by describing external electromagnetic radiation. Dynamic analyses show that the proposed memristive HNN can not only generate two kinds of 1-directional (1D) multi-butterfly chaotic attractors but also produce complex grid (2D) multi-butterfly chaotic attractors. More importantly, by switching the initial states of the second and third memristive systems, the grid multi-butterfly memristive HNN exhibits initial-boosted plane coexisting multi-butterfly attractors. Moreover, the number of butterflies contained in a multi-butterfly attractor and coexisting attractors can be easily adjusted by changing memristive parameters. Based on these complex dynamics, an image security solution is designed to show the application of the newly constructed grid multi-butterfly memristive HNN to police IoT security. Security performances indicate the designed scheme can resist various attacks and has high robustness. Finally, the test results are further demonstrated through RPI-based hardware experimentsPeer reviewe

Design and implementation of a fast Fourier transform architecture using twiddle factor based decomposition algorithm

With the advent of signal processing and wireless communication mobile platform devices, the necessity for data transformation from one form to another becomes an unavoidable aspect. One such mathematical tool that is widely used for transforming time and frequency domain signals is Fourier Transform. Fast Fourier Transform (FFT) is perhaps the fastest way to achieve transformation. Many algorithms and architectures have been designed over the years in an attempt to make FFT algorithms more efficient and to target many applications; The main objective of our work is to design, simulate and implement an architecture based on the Twiddle-Factor-Based decomposition FFT algorithm. The significant feature of the algorithm is its effective memory access reduction that accounts to be as much as 30% lesser than in any other conventional FFT algorithms. As a result of this memory reduction, this algorithm is said to be more power efficient and is said to compute in much lesser number of clock cycles than other algorithms developed; The real focus of the design is to build architecture to map this efficient algorithm on to hardware retaining the maximum efficiency of the algorithm. The complete design, simulation and testing is done using Active-HDL tool which is a VHDL package designed. The architecture designed is found to retain the memory savings capability of the algorithm thus enabling power efficiency

Quantum Chaos = Volume-Law Spatiotemporal Entanglement

Chaotic systems are highly sensitive to a small perturbation, be they biological, chemical, classical, ecological, political, or quantum. Taking this as the underlying principle, we construct an operational notion for quantum chaos. Namely, we demand that the whole future state of a large, isolated quantum system is highly sensitive to past multitime operations on a small subpart of that system. This immediately leads to a direct link between quantum chaos and volume-law spatiotemporal entanglement. Remarkably, our operational criterion already contains the routine notions, as well as the well-known diagnostics for quantum chaos. This includes the Peres-Loschmidt Echo, Dynamical Entropy, and Out-of-Time-Order Correlators. Our principle therefore unifies these existing diagnostics within a single structure. Within this framework, we also go on to quantify how several mechanisms lead to quantum chaos, such as unitary designs. Our work paves the way to systematically study exotic many-body dynamical phenomena like Many-Body Localisation, many-body scars, measurement-induced phase transitions, and Floquet dynamics. We anticipate that our work may lead to a clear link between the Eigenstate Thermalization Hypothesis and quantum chaos.Comment: 20 + 6 pages, 5 figure

Progress in the use of genetic methods to study insect behavior outside Drosophila

In the span of a decade we have seen a rapid progress in the application of genetic tools and genome editing approaches in ‘non-model’ insects. It is now possible to target sensory receptor genes and neurons, explore their functional roles and manipulate behavioral responses in these insects. In this review, we focus on the latest examples from Diptera, Lepidoptera and Hymenoptera of how applications of genetic tools advanced our understanding of diverse behavioral phenomena. We further discuss genetic methods that could be applied to study insect behavior in the future

Density-matrix simulation of small surface codes under current and projected experimental noise

We present a full density-matrix simulation of the quantum memory and computing performance of the distance-3 logical qubit Surface-17, following a recently proposed quantum circuit and using experimental error parameters for transmon qubits in a planar circuit QED architecture. We use this simulation to optimize components of the QEC scheme (e.g., trading off stabilizer measurement infidelity for reduced cycle time) and to investigate the benefits of feedback harnessing the fundamental asymmetry of relaxation-dominated error in the constituent transmons. A lower-order approximate calculation extends these predictions to the distance-$5$ Surface-49. These results clearly indicate error rates below the fault-tolerance threshold of surface code, and the potential for Surface-17 to perform beyond the break-even point of quantum memory. At state-of-the-art qubit relaxation times and readout speeds, Surface-49 could surpass the break-even point of computation.Comment: 10 pages + 8 pages appendix, 12 figure