Signal propagation in complex networks drives epidemics, is responsible for information going viral, promotes trust and facilitates moral behavior in social groups, enables the development of ...misinformation detection algorithms, and it is the main pillar supporting the fascinating cognitive abilities of the brain, to name just some examples. The geometry of signal propagation is determined as much by the network topology as it is by the diverse forms of nonlinear interactions that may take place between the nodes. Advances are therefore often system dependent and have limited translational potential across domains. Given over two decades worth of research on the subject, the time is thus certainly ripe, indeed the need is urgent, for a comprehensive review of signal propagation in complex networks. We here first survey different models that determine the nature of interactions between the nodes, including epidemic models, Kuramoto models, diffusion models, cascading failure models, and models describing neuronal dynamics. Secondly, we cover different types of complex networks and their topologies, including temporal networks, multilayer networks, and neural networks. Next, we cover network time series analysis techniques that make use of signal propagation, including network correlation analysis, information transfer and nonlinear correlation tools, network reconstruction, source localization and link prediction, as well as approaches based on artificial intelligence. Lastly, we review applications in epidemiology, social dynamics, neuroscience, engineering, and robotics. Taken together, we thus provide the reader with an up-to-date review of the complexities associated with the network’s role in propagating signals in the hope of better harnessing this to devise innovative applications across engineering, the social and natural sciences as well as to inspire future research.
Mitochondria are a major target in hypoxic/ischemic injury. Mitochondrial impairment increases with age leading to dysregulation of molecular pathways linked to mitochondria. The perturbation of ...mitochondrial homeostasis and cellular energetics worsens outcome following hypoxic-ischemic insults in elderly individuals. In response to acute injury conditions, cellular machinery relies on rapid adaptations by modulating posttranslational modifications. Therefore, post-translational regulation of molecular mediators such as hypoxia-inducible factor 1α (HIF-1α), peroxisome proliferator-activated receptor γ coactivator α (PGC-1α), c-MYC, SIRT1 and AMPK play a critical role in the control of the glycolytic-mitochondrial energy axis in response to hypoxic-ischemic conditions. The deficiency of oxygen and nutrients leads to decreased energetic reliance on mitochondria, promoting glycolysis. The combination of pseudohypoxia, declining autophagy, and dysregulation of stress responses with aging adds to impaired host response to hypoxic-ischemic injury. Furthermore, intermitochondrial signal propagation and tissue wide oscillations in mitochondrial metabolism in response to oxidative stress are emerging as vital to cellular energetics. Recently reported intercellular transport of mitochondria through tunneling nanotubes also play a role in the response to and treatments for ischemic injury. In this review we attempt to provide an overview of some of the molecular mechanisms and potential therapies involved in the alteration of cellular energetics with aging and injury with a neurobiological perspective.
The brain can efficiently receive and process weak signals, and reproducing signal amplification is an important task. We investigate weak signal propagation in a coupled feedforward network composed ...of bistable neurons, where the neuron connections include intra-layer and inter-layer couplings. We find that both intra- and inter-layer couplings both determine whether the weak signal propagation is enhanced or attenuated. Both the numerical and analytical results indicate that weak signal enhancement is dependent on two conditions: I. the intra-layer coupling strength is less than the critical value at which neurons in the first layer are fully synchronized; II. the inter-layer coupling strength is greater than the critical value at which neurons in the second layer exhibit a Hopf bifurcation. It has been revealed that the most significant signal enhancement occurs when the intra-layer coupling is less than a critical value and the inter-layer coupling reaches a critical value. Additionally, we have examined the impact of the weak signal frequency on signal propagation. Our qualitative analysis of the Hopf bifurcation provides a theoretical basis for the study of weak signal propagation in multilayer networks.
•The weak signal enhancement is most obvious when the inter-layer coupling strength reaches the critical value of the Hopf bifurcation.
Active topolectrical circuits Kotwal, Tejas; Moseley, Fischer; Stegmaier, Alexander ...
Proceedings of the National Academy of Sciences - PNAS,
08/2021, Letnik:
118, Številka:
32
Journal Article
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The transfer of topological concepts from the quantum world to classical mechanical and electronic systems has opened fundamentally different approaches to protected information transmission and wave ...guidance. A particularly promising emergent technology is based on recently discovered topolectrical circuits that achieve robust electric signal transduction by mimicking edge currents in quantum Hall systems. In parallel, modern active matter research has shown how autonomous units driven by internal energy reservoirs can spontaneously self-organize into collective coherent dynamics. Here, we unify key ideas from these two previously disparate fields to develop design principles for active topolectrical circuits (ATCs) that can self-excite topologically protected global signal patterns. Realizing autonomous active units through nonlinear Chua diode circuits, we theoretically predict and experimentally confirm the emergence of self-organized protected edge oscillations in one- and two-dimensional ATCs. The close agreement between theory, simulations, and experiments implies that nonlinear ATCs provide a robust and versatile platform for developing high-dimensional autonomous electrical circuits with topologically protected functionalities.
The propagation and detection of weak signals play a vital role in the central nervous system's information processing. In this paper, a biophysical two-compartment model is adopted to investigate ...how the neuronal morphology and network properties modulate signal propagation in a multi-layer feedforward network (FFN). The numerical simulation results show that neurons with larger dendrites have higher firing rates and better responses to weak signals. Similarly, the output layer of FFN constructed by larger-dendrite neurons also exhibits better responses. A suitable chaotic current is necessary for the propagation of weak signals. Excessively strong or weak chaotic current leads to propagation failure. Sparse connection and weak synaptic strength optimize the responses of the output layer, which is consistent with real biological networks observed in the brain. It is found that weak signal propagation in FFN is highly correlated with the regulation of firing rate. Our results may provide novel insights into the modeling of complex networks and network function implementation.
•Larger dendritic feedforward networks (FFN) exhibit better responses to weak signals in the output layer.•Chaotic currents drive the propagation of weak signals by adjusting the firing rate of neurons.•Sparse connection and weak synaptic strength are necessary conditions for weak signal propagation.•The responses of the output layer in FFN are related to the level of firing rate.
Wave phase difference is a fundamental property that characterises the relative behaviour of transmitted signals. It has significant roles in signal wave analysis and in interpreting various ...propagation phenomena, which are crucial when designing wireless links and various applications in signal processing techniques, optics, and acoustics. This study investigated the concept of phase difference significance based on high frequencies (i.e., 1.0, 2.4, 10.0, and 20.0 GHz). Several phase difference models and their shortcomings were reviewed to emphasise the need for greater accuracy and precision in quantifying phase differences. The outcomes revealed that 1 GHz contributed to the lowest phase difference among the other frequencies. A constructive signal may be deployed to provide a better link build-up. Overall, determining the importance of phase difference in GHz and identifying the signal attitude substantially contribute to the advancement of wave analysis, while simultaneously encouraging further exploration in this domain.
Gathering information and giving feedback on it happen all the time for the human and animals. Soft materials such as hydrogels are often chosen as sensors due to their portability and wearability. ...However, these materials previously reported have various defects, such as poor underwater adhesion, underwater swelling, unstable underwater conductivity. Herein, a hydrophobic ionogel is prepared by ion-dipole and ion-ion interactions between fluorine-rich poly (ionic liquid) and ionic liquid, and covalent cross-linking. The conductive ionogel shows adjustable mechanical property (fracture strength: 0.24–0.52 MPa, break strain: 210% to 360%), underwater adhesion (693 KPa to plastic), optical transparency (81%, 2 mm), temperature tolerance and suitable conductivity (10−5-10−4 S/cm). Thus, the ionogel is used as s multimodal sensor no matter in the air or in aquatic environment. Based on the mechanism of electron transport path change, the ionogel sensor can recognize different objects entering water, and even different objects touching ice, such as hands, tweezers and aluminum foil, and send messages out of the water by Morse code. Even more, the standing posture and touching between two persons can be recorded by ionogel sensor. And the ionogels can be served as temperature sensor, containing wide operating temperature window (0–80 °C) and high detecting accuracy (0.2 °C). Therefore, the ionogel has vital important applications in non-contact signal propagation and wearable devices.
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•A novel ionogel was prepared by hydrophobic poly (ionic liquid) and ionic liquid.•The resulting ionogel showed strong adhesion and stable conductivity in water.•The ionogel sensor detected human motion and barrier-free communication in water.•Changing electron transfer pathway was proved for contactless sensing mechanism.
Nerve impulse generation and propagation are often thought of as solely electrical events. The prevalence of this view is the result of long and intense study of nerve impulses in electrophysiology ...culminating in the introduction of the Hodgkin-Huxley model of the action potential in the 1950s. To this day, this model forms the physiological foundation for a broad area of neuroscientific research. However, the Hodgkin-Huxley model cannot account for non-electrical phenomena that accompany nerve impulse propagation, for which there is nevertheless ample evidence. This raises the question whether the Hodgkin-Huxley model is a complete model of the nerve impulse. Several alternative models have been proposed that do take into account non-electrical aspects of the nerve impulse and emphasize their importance in gaining a more complete understanding of the nature of the nerve impulse. In our opinion, these models deserve more attention in neuroscientific research, since, together with the Hodgkin-Huxley model, they will help in addressing and solving a number of questions in basic and applied neuroscience which thus far have remained outside our grasp. Here we provide a historico-scientific overview of the developments that have led to the current conception of the action potential as an electrical phenomenon, discuss some major objections against this conception, and suggest a number of scientific factors which have likely contributed to the enduring success of the Hodgkin-Huxley model and should be taken into consideration whilst contemplating the formulation of a more extensive and complete conception of the nerve impulse.
Understanding reliable signal transmission represents a notable challenge for cortical systems, which display a wide range of weights of feedforward and feedback connections among heterogeneous ...areas. We re-examine the question of signal transmission across the cortex in a network model based on mesoscopic directed and weighted inter-areal connectivity data of the macaque cortex. Our findings reveal that, in contrast to purely feedforward propagation models, the presence of long-range excitatory feedback projections could compromise stable signal propagation. Using population rate models as well as a spiking network model, we find that effective signal propagation can be accomplished by balanced amplification across cortical areas while ensuring dynamical stability. Moreover, the activation of prefrontal cortex in our model requires the input strength to exceed a threshold, which is consistent with the ignition model of conscious processing. These findings demonstrate our model as an anatomically realistic platform for investigations of global primate cortex dynamics.
•Long-range excitatory loops destabilize the system, complicating propagation•Balanced amplification facilitates robust signal transmission in large-scale models•Stable transmission in synchronous and asynchronous modes in spiking network models•Prefrontal activity beyond threshold supports ignition model of conscious processing
Joglekar et al. propose a basic circuit motif that allows for stable signal transmission in large-scale cortical-circuit models. The motif contains strong long-range recurrent excitation stabilized by local feedback inhibition, extending the balanced amplification mechanism.
Full Waveform LiDAR for Adverse Weather Conditions Wallace, Andrew M.; Halimi, Abderrahim; Buller, Gerald S.
IEEE transactions on vehicular technology,
07/2020, Letnik:
69, Številka:
7
Journal Article
Recenzirano
Odprti dostop
We present and discuss the case for full waveform pixel and image acquisition and processing to enable LiDAR sensors to penetrate and reconstruct 3D surface maps through obscuring media. To that end, ...we review work on signal propagation, on scanning and arrayed sensors, on signal processing strategies for independent pixels and employing spatial context, on reducing complexity and accelerating processing by sensor design, algorithmic changes, compressed sensing, and parallel processing. We report several experimental studies on LiDAR imaging through complex media, and how these can inform the automotive LiDAR scenario. We conclude with a discussion of future development and potential for full waveform LiDAR (FWL).
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