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El Manira, Abdeljabbar, and Peter Wallén. "Mechanisms of Modulation of a Neural Network." Physiology 15, no. 4 (August 2000): 186–91. http://dx.doi.org/10.1152/physiologyonline.2000.15.4.186.
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Neural networks form the basis for the generation and control of various patterns of behavior. Such networks are subjected to modulatory systems that influence their operation and, thereby, the behavior. In the lamprey locomotor network, analysis on the ion channel, synaptic, and cellular levels has given new insights into the organization of such modulatory systems.
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Beranek, Ladislav, and Radim Remes. "Distribution of Node Characteristics in Evolving Tripartite Network." Entropy 22, no. 3 (February 25, 2020): 263. http://dx.doi.org/10.3390/e22030263.
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Many real-world networks have a natural tripartite structure. Investigating the structure and the behavior of actors in these networks is useful to gain a deeper understanding of their behavior and dynamics. In our paper, we describe an evolving tripartite network using a network model with preferential growth mechanisms and different rules for changing the strength of nodes and the weights of edges. We analyze the characteristics of the strength distribution and behavior of selected nodes and selected actors in this tripartite network. The distributions of these analyzed characteristics follow the power-law under different modeled conditions. Performed simulations have confirmed all these results. Despite its simplicity, the model expresses well the basic properties of the modeled network. It can provide further insights into the behavior of systems with more complex behaviors, such as the multi-actor e-commerce system that we have used as a real basis for the validation of our model.
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BADHAM, JENNIFER, FRANK KEE, and RUTH F. HUNTER. "Simulating network intervention strategies: Implications for adoption of behaviour." Network Science 6, no. 2 (May 16, 2018): 265–80. http://dx.doi.org/10.1017/nws.2018.4.
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AbstractThis study uses simulation over real and artificial networks to compare the eventual adoption outcomes of network interventions, operationalized as idealized contagion processes with different sets of seeds. While the performance depends on the details of both the network and behaviour adoption mechanisms, interventions with seeds that are central to the network are more effective than random selection in the majority of simulations, with faster or more complete adoption throughout the network. These results provide additional theoretical justification for utilizing relevant network information in the design of public health behavior interventions.
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Jayashree, Devasagayam, V. Uma Rani, and K. Soma Sundaram. "Trust Based Misbehavior Detection in Wireless Sensor Networks." Applied Mechanics and Materials 622 (August 2014): 191–98. http://dx.doi.org/10.4028/www.scientific.net/amm.622.191.
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Due to emerging technology Wireless Sensor Network (WSN), it is necessary to monitor the behavior of sensor nodes and establish the secure communication in network. Security is a challenging task in wireless environment. Several encryption mechanisms are available to prevent outsider attacks, but no mechanism available for insider attacks. A trust model is a collection of rules used to establish co-operation or collaboration among nodes as well as monitoring misbehavior of wireless sensor networks. Trust model is necessary to enhance secure localization, communication or routing, aggregation, collaboration among nodes. In this paper, proposed a behavior based distributed trust model for wireless sensor network to effectively deal with self-ish or malicious nodes. Here, take multidimensional trust attributes derived from communications and networks to evaluate the overall trust of sensor nodes. It monitors the behavior of nodes and establishes secure communication among networks.
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Papan, Jozef, Pavel Segec, Oleksandra Yeremenko, Ivana Bridova, and Michal Hodon. "Enhanced Multicast Repair Fast Reroute Mechanism for Smart Sensors IoT and Network Infrastructure." Sensors 20, no. 12 (June 17, 2020): 3428. http://dx.doi.org/10.3390/s20123428.
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The sprawling nature of Internet of Things (IoT) sensors require the comprehensive management and reliability of the entire network. Modern Internet Protocol (IP) networks demand specific qualitative and quantitative parameters that need to be met. One of these requirements is the minimal packet loss in the network. After a node or link failure within the network, the process of network convergence will begin. This process may take an unpredictable time, mostly depending on the size and the structure of the affected network segment and the routing protocol used within the network. The categories of proposed solutions for these problems are known as Fast ReRoute (FRR) mechanisms. The majority of current Fast ReRoute mechanisms use precomputation of alternative backup paths in advance. This paper presents an Enhanced Multicast Repair (EM-REP) FRR mechanism that uses multicast technology to create an alternate backup path and does not require pre-calculation. This principle creates a unique reactive behavior in the Fast ReRoute area. The enhanced M-REP FRR mechanism can find an alternative path in the event of multiple links or nodes failing at different times and places in the network. This unique behavior can be applied in the IoT sensors area, especially in network architecture that guarantees reliability of data transfer.
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Trojanowski, Nicholas F., Olivia Padovan-Merhar, David M. Raizen, and Christopher Fang-Yen. "Neural and genetic degeneracy underlies Caenorhabditis elegans feeding behavior." Journal of Neurophysiology 112, no. 4 (August 15, 2014): 951–61. http://dx.doi.org/10.1152/jn.00150.2014.
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Degenerate networks, in which structurally distinct elements can perform the same function or yield the same output, are ubiquitous in biology. Degeneracy contributes to the robustness and adaptability of networks in varied environmental and evolutionary contexts. However, how degenerate neural networks regulate behavior in vivo is poorly understood, especially at the genetic level. Here, we identify degenerate neural and genetic mechanisms that underlie excitation of the pharynx (feeding organ) in the nematode Caenorhabditis elegans using cell-specific optogenetic excitation and inhibition. We show that the pharyngeal neurons MC, M2, M4, and I1 form multiple direct and indirect excitatory pathways in a robust network for control of pharyngeal pumping. I1 excites pumping via MC and M2 in a state-dependent manner. We identify nicotinic and muscarinic receptors through which the pharyngeal network regulates feeding rate. These results identify two different mechanisms by which degeneracy is manifest in a neural circuit in vivo.
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Jones, Jeff. "Characteristics of Pattern Formation and Evolution in Approximations of Physarum Transport Networks." Artificial Life 16, no. 2 (April 2010): 127–53. http://dx.doi.org/10.1162/artl.2010.16.2.16202.
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Most studies of pattern formation place particular emphasis on its role in the development of complex multicellular body plans. In simpler organisms, however, pattern formation is intrinsic to growth and behavior. Inspired by one such organism, the true slime mold Physarum polycephalum, we present examples of complex emergent pattern formation and evolution formed by a population of simple particle-like agents. Using simple local behaviors based on chemotaxis, the mobile agent population spontaneously forms complex and dynamic transport networks. By adjusting simple model parameters, maps of characteristic patterning are obtained. Certain areas of the parameter mapping yield particularly complex long term behaviors, including the circular contraction of network lacunae and bifurcation of network paths to maintain network connectivity. We demonstrate the formation of irregular spots and labyrinthine and reticulated patterns by chemoattraction. Other Turing-like patterning schemes were obtained by using chemorepulsion behaviors, including the self-organization of regular periodic arrays of spots, and striped patterns. We show that complex pattern types can be produced without resorting to the hierarchical coupling of reaction-diffusion mechanisms. We also present network behaviors arising from simple pre-patterning cues, giving simple examples of how the emergent pattern formation processes evolve into networks with functional and quasi-physical properties including tensionlike effects, network minimization behavior, and repair to network damage. The results are interpreted in relation to classical theories of biological pattern formation in natural systems, and we suggest mechanisms by which emergent pattern formation processes may be used as a method for spatially represented unconventional computation.
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Palenciano, Ana F., Carlos González-García, Juan E. Arco, and María Ruz. "Transient and Sustained Control Mechanisms Supporting Novel Instructed Behavior." Cerebral Cortex 29, no. 9 (October 25, 2018): 3948–60. http://dx.doi.org/10.1093/cercor/bhy273.
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Abstract The success of humans in novel environments is partially supported by our ability to implement new task procedures via instructions. This complex skill has been associated with the activity of control-related brain areas. Current models link fronto-parietal and cingulo-opercular networks with transient and sustained modes of cognitive control, based on observations during repetitive task settings or rest. The current study extends this dual model to novel instructed tasks. We employed a mixed design and an instruction-following task to extract phasic and tonic brain signals associated with the encoding and implementation of novel verbal rules. We also performed a representation similarity analysis to capture consistency in task-set encoding within trial epochs. Our findings show that both networks are involved while following novel instructions: transiently, during the implementation of the instruction, and in a sustained fashion, across novel trials blocks. Moreover, the multivariate results showed that task representations in the cingulo-opercular network were more stable than in the fronto-parietal one. Our data extend the dual model of cognitive control to novel demanding situations, highlighting the high flexibility of control-related regions in adopting different temporal profiles.
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Bechtel, William. "Resituating cognitive mechanisms within heterarchical networks controlling physiology and behavior." Theory & Psychology 29, no. 5 (October 2019): 620–39. http://dx.doi.org/10.1177/0959354319873725.
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Cognitive science has traditionally focused on mechanisms involved in high-level reasoning and problem-solving processes. Such mechanisms are often treated as autonomous from but controlling underlying physiological processes. I offer a different perspective on cognition which starts with the basic production mechanisms through which organisms construct and repair themselves and navigate their environments and then I develop a framework for conceptualizing how cognitive control mechanisms form a heterarchical network that regulates production mechanisms. Many of these control mechanisms perform cognitive tasks such as evaluating circumstances and making decisions. Cognitive control mechanisms are present in individual cells, but in metazoans, intracellular control is supplemented by a nervous system in which a multitude of neural control mechanisms are organized heterarchically. On this perspective, high-level cognitive mechanisms are not autonomous, but are elements in larger heterarchical networks. This has implications for future directions in cognitive science research.
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Wiedemann, Urs Achim, and Anita Lüthi. "Timing of Network Synchronization By Refractory Mechanisms." Journal of Neurophysiology 90, no. 6 (December 2003): 3902–11. http://dx.doi.org/10.1152/jn.00284.2003.
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Even without active pacemaker mechanisms, temporally patterned synchronization of neural network activity can emerge spontaneously and is involved in neural development and information processing. Generation of spontaneous synchronization is thought to arise as an alternating sequence between a state of elevated excitation followed by a period of quiescence associated with neuronal and/or synaptic refractoriness. However, the cellular factors controlling recruitment and timing of synchronized events have remained difficult to specify, although the specific temporal pattern of spontaneous rhythmogenesis determines its impact on developmental processes. We studied spontaneous synchronization in a model of 600–1,000 integrate-and-fire neurons interconnected with a probability of 5–30%. One-third of neurons generated spontaneous discharges and provided a background of intrinsic activity to the network. The heterogeneity and random coupling of these neurons maintained this background activity asynchronous. Refractoriness was modeled either by use-dependent synaptic depression or by cellular afterhyperpolarization. In both cases, the recruitment of neurons into spontaneous synchronized discharges was determined by the interplay of refractory mechanisms with stochastic fluctuations in background activity. Subgroups of easily recruitable neurons served as amplifiers of these fluctuations, thereby initiating a cascade-like recruitment of neurons (“avalanche effect”). In contrast, timing depended on the precise implementation of neuronal refractoriness and synaptic connectivity. With synaptic depression, neuronal synchronization always occurred stochastically, whereas with cellular afterhyperpolarization, stochastic turned into periodic behavior with increasing synaptic strength. These results associate the type of refractory mechanism with the temporal statistics and the mechanism of synchronization, thereby providing a framework for differentiating between cellular mechanisms of spontaneous rhythmogenesis.
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Northmore, David P. M. "A network of spiking neurons develops sensorimotor mechanisms while guiding behavior." Neurocomputing 58-60 (June 2004): 1057–63. http://dx.doi.org/10.1016/j.neucom.2004.01.166.
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Schreurs, Bieke, Antoine Van den Beemt, Nienke Moolenaar, and Maarten De Laat. "Networked individualism and learning in organizations." Journal of Workplace Learning 31, no. 2 (April 3, 2019): 95–115. http://dx.doi.org/10.1108/jwl-05-2018-0070.
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Purpose This paper aims to investigate the extent professionals from the vocational sector are networked individuals. The authors explore how professionals use their personal networks to engage in a wide variety of learning activities and examine what social mechanisms influence professionals’ agency to form personal informal learning networks. Design/methodology/approach This study applied a mixed-method approach to data collection. Social network data were gathered among school professionals working in the vocational sector. Ego-network analysis was performed. A total of 24 in-depth, semi-structured, qualitative interviews were analyzed. Findings This study found that networked individualism is not represented to its full potential in the vocational sector. However, it is important to form informal learning ties with different stakeholders because all types of informal learning ties serve different learning purposes. The extent to which social mechanisms (i.e. proximity, trust, level of expertise and homophily) influence professionals’ agency to form informal learning ties differs depending on the stakeholder with whom the informal learning ties are formed. Research limitations/implications This study excludes the investigation of social mechanisms that shape learning through more impersonal virtual learning resources, such as social media or expert forums. Moreover, the authors only included individual- and dyadic-level social mechanisms. Practical implications By investigating the social mechanisms that shape informal learning ties, this study provides insights how professionals can be stimulated to build rich personal learning networks in the vocational sector. Originality/value The authors extend earlier research with in-depth information on the different types of learning activities professionals engage in in their personal learning networks with different stakeholders. The ego-network perspective reveals how different social mechanisms influence professionals’ agency to shape informal learning networks with different stakeholders.
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Xu, Yingying, Liangqun Qi, Xichen Lyu, and Xinyu Zang. "An Evolution Analysis of Collaborative Innovation Network considering Government Subsidies and Supervision." Mathematical Problems in Engineering 2019 (July 29, 2019): 1–12. http://dx.doi.org/10.1155/2019/2906908.
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Collaborative innovation networks have the basic attributes of complex networks. The interaction of innovation network members has promoted the development of collaborative innovation networks. Using the game-based theory in the B-A scale-free network context, this paper builds an evolutionary game model of network members and explores the emergence mechanism from collaborative innovation behavior to the macroevolution of networks. The results show that revenue distribution, compensation of the betrayer, government subsidies, and supervision have positively contributed to the continued stability of collaborative innovation networks. However, the effect mechanisms are dissimilar for networks of different scales. In small networks, the rationality of the revenue distribution among members that have similar strengths should receive more attention, and the government should implement medium-intensity supervision measures. In large networks, however, compensation of the betrayer should be attached greater importance to, and financial support from the government can promote stable evolution more effectively.
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Grandori, Anna, and Giuseppe Soda. "Inter-firm Networks: Antecedents, Mechanisms and Forms." Organization Studies 16, no. 2 (March 1995): 183–214. http://dx.doi.org/10.1177/017084069501600201.
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This paper is an effort to review and organize the now vast literature on inter firm networks, with the aim of assessing the important current forms of net work, the organizational mechanisms supporting them, and the main variables that have been shown to influence network emergence and shape. These results are achieved through a literature review encompassing a number of approaches across the social sciences. The paper can therefore be used as a typological state-of-art on inter-firm networks, and as a basis for developing hypotheses of relationship between network antecedents and forms.
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Steijvers, Lisanne C. J., Stephanie Brinkhues, Christian J. P. A. Hoebe, Theo G. van Tilburg, Vivian Claessen, Noortje Bouwmeester-Vincken, Femke Hamers, Petra Vranken, and Nicole H. T. M. Dukers-Muijrers. "Social networks and infectious diseases prevention behavior: A cross-sectional study in people aged 40 years and older." PLOS ONE 16, no. 5 (May 19, 2021): e0251862. http://dx.doi.org/10.1371/journal.pone.0251862.
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Background Social networks, i.e., our in-person and online social relations, are key to lifestyle behavior and health, via mechanisms of influence and support from our relations. We assessed associations between various social network aspects and practicing behavior to prevent respiratory infectious diseases. Methods We analyzed baseline-data (2019) from the SaNAE-cohort on social networks and health, collected by an online questionnaire in Dutch community-dwelling people aged 40–99 years. Outcome was the number of preventive behaviors in past two months [range 0–4]. Associations between network aspects were tested using ordinal regression analyses, adjusting for confounders. Results Of 5,128 participants (mean age 63; 54% male), 94% regularly washed hands with water and soap, 55% used only paper (not cloth) handkerchiefs/tissues; 19% touched their face as little as possible; 39% kept distance from people with respiratory infectious disease symptoms; median score of behaviors was 2. Mean network size was 11 (46% family; 27% friends); six network members were contacted exclusively in-person and two exclusively via phone/internet. Participants received informational, emotional, and practical support from four, six, and two network members, respectively. Independently associated with more preventive behaviors were: ‘strong relationships’, i.e., large share of friends and aspects related to so called ‘weak relationships’, a larger share of distant living network members, higher number of members with whom there was exclusively phone/internet contact, and more network members providing informational support. Club membership and a larger share of same-aged network members were inversely associated. Conclusion Friends (‘strong’ relationships) may play an important role in the adoption of infection-preventive behaviors. So may ‘weak relationships’, e.g. geographically more distant network members, who may provide informational support as via non-physical modes of contact. Further steps are to explore employment of these types of relationships when designing infectious diseases control programs aiming to promote infection-preventive behavior in middle aged-and older individuals.
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Srinivasan, Karthik K., and Hani S. Mahmassani. "Modeling Inertia and Compliance Mechanisms in Route Choice Behavior Under Real-Time Information." Transportation Research Record: Journal of the Transportation Research Board 1725, no. 1 (January 2000): 45–53. http://dx.doi.org/10.3141/1725-07.
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This research examines route choice, in the presence of real-time information, as a consequence of two underlying behavioral mechanisms: compliance and inertia. The compliance mechanism reflects the propensity of a user to comply with the information supplied by advanced traveler information systems (ATIS). The inertial mechanism represents the tendency of users to continue on their current paths. These two mechanisms in route choice are neither mutually exclusive nor collectively exhaustive. A framework is proposed to model these mechanisms explicitly. The proposed framework decomposes the route choice into two states by exploiting the user’s path choice structure (resulting from the current choice prior to the decision of interest) and the information supplied by ATIS. In each state, the mechanisms are incorporated by associating their utilities with those that reflect the specific attributes of the alternative paths. The resulting nested choice structure is implemented using the multinomial probit model. This framework is illustrated using route choice data obtained from dynamic interactive simulator experiments. The empirical results strongly support the simultaneous presence of both the compliance and inertia mechanisms in route choice behavior. The results also indicate that information quality, network loading and day-to-day evolution, level-of-service measures, and trip-makers’ prior experience are significant determinants of route choice through the inertial and compliance mechanisms. These findings have important implications in travel behavior forecasting, ATIS design and evaluation, demand management, and network state prediction.
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Liu, Jiaqi, Nan Zhong, Deng Li, and Hui Liu. "BMCGM: A Behavior Economics-Based Message Transmission Cooperation Guarantee Mechanism in Vehicular Ad-hoc NETworks." Sensors 18, no. 10 (October 3, 2018): 3316. http://dx.doi.org/10.3390/s18103316.
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Vehicular Ad-hoc NETwork (VANET) is a special mobile ad hoc network that composed of facilities such as vehicle nodes and roadside units. Message transfer among vehicle nodes has been a great challenge due to the network’s highly variable topology and the selfish nature of vehicle nodes. Thus, it is very necessary to propose a mechanism to improve the cooperation among vehicle nodes to guarantee the effective message transmission. Currently, incentive-based cooperation mechanisms are commonly used to encourage nodes to participate in message transmission. Those mechanisms are based on traditional economics and generally assume that the decision-making behavior of nodes is completely independent. Also, the cooperation of nodes depends on whether the cooperation behavior can obtain the higher utility. But researches in behavioral economics have shown that due to the existence of altruistic reciprocity, the behavior of nodes is affected by not only their utility but also the behavioral motives of other nodes, so as to obtain different results from traditional incentive-based mechanisms. Therefore, the paper introduces the reciprocal altruistic from behavioral economics and proposes the reciprocal altruistic factor to reconstruct the utility function of nodes. The reconstructed utility function reflects the interaction of behavioral motives among nodes, which promotes the node’s cooperative behavior. Also, since the Network Formation Game (NFG) is a common mathematical model for studying the interaction and communication links formation among network nodes, hence the paper regards NFG in traditional economics as the research object. A Behavior Economics-based Message Transmission Cooperation Guarantee Mechanism named BMCGM is proposed, which motivates nodes to participate in the message transmission to reduce the transmission delay ratio. The simulation results show that the BMCGM reduces message transmission delay by at least 30.3% compared with the recent representative cooperation transmission mechanism.
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Phan, Tuan Q., and Edoardo M. Airoldi. "A natural experiment of social network formation and dynamics." Proceedings of the National Academy of Sciences 112, no. 21 (May 11, 2015): 6595–600. http://dx.doi.org/10.1073/pnas.1404770112.
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Social networks affect many aspects of life, including the spread of diseases, the diffusion of information, the workers' productivity, and consumers' behavior. Little is known, however, about how these networks form and change. Estimating causal effects and mechanisms that drive social network formation and dynamics is challenging because of the complexity of engineering social relations in a controlled environment, endogeneity between network structure and individual characteristics, and the lack of time-resolved data about individuals' behavior. We leverage data from a sample of 1.5 million college students on Facebook, who wrote more than 630 million messages and 590 million posts over 4 years, to design a long-term natural experiment of friendship formation and social dynamics in the aftermath of a natural disaster. The analysis shows that affected individuals are more likely to strengthen interactions, while maintaining the same number of friends as unaffected individuals. Our findings suggest that the formation of social relationships may serve as a coping mechanism to deal with high-stress situations and build resilience in communities.
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Nargeot, Romuald, Morgane Le Bon-Jego, and John Simmers. "Cellular and Network Mechanisms of Operant Learning-Induced Compulsive Behavior in Aplysia." Current Biology 19, no. 12 (June 2009): 975–84. http://dx.doi.org/10.1016/j.cub.2009.05.030.
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Bellot-Saez, Alba, Rebecca Stevenson, Orsolya Kékesi, Evgeniia Samokhina, Yuval Ben-Abu, John W. Morley, and Yossi Buskila. "Neuromodulation of Astrocytic K+ Clearance." International Journal of Molecular Sciences 22, no. 5 (March 3, 2021): 2520. http://dx.doi.org/10.3390/ijms22052520.
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Potassium homeostasis is fundamental for brain function. Therefore, effective removal of excessive K+ from the synaptic cleft during neuronal activity is paramount. Astrocytes play a key role in K+ clearance from the extracellular milieu using various mechanisms, including uptake via Kir channels and the Na+-K+ ATPase, and spatial buffering through the astrocytic gap-junction coupled network. Recently we showed that alterations in the concentrations of extracellular potassium ([K+]o) or impairments of the astrocytic clearance mechanism affect the resonance and oscillatory behavior of both the individual and networks of neurons. These results indicate that astrocytes have the potential to modulate neuronal network activity, however, the cellular effectors that may affect the astrocytic K+ clearance process are still unknown. In this study, we have investigated the impact of neuromodulators, which are known to mediate changes in network oscillatory behavior, on the astrocytic clearance process. Our results suggest that while some neuromodulators (5-HT; NA) might affect astrocytic spatial buffering via gap-junctions, others (DA; Histamine) primarily affect the uptake mechanism via Kir channels. These results suggest that neuromodulators can affect network oscillatory activity through parallel activation of both neurons and astrocytes, establishing a synergistic mechanism to maximize the synchronous network activity.
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Carollo, Alessandro, Jan Paolo Macapinlac Balagtas, Michelle Jin-Yee Neoh, and Gianluca Esposito. "A Scientometric Approach to Review the Role of the Medial Preoptic Area (MPOA) in Parental Behavior." Brain Sciences 11, no. 3 (March 20, 2021): 393. http://dx.doi.org/10.3390/brainsci11030393.
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Research investigating the neural substrates underpinning parental behaviour has recently gained momentum. Particularly, the hypothalamic medial preoptic area (MPOA) has been identified as a crucial region for parenting. The current study conducted a scientometric analysis of publications from 1 January 1972 to 19 January 2021 using CiteSpace software to determine trends in the scientific literature exploring the relationship between MPOA and parental behaviour. In total, 677 scientific papers were analysed, producing a network of 1509 nodes and 5498 links. Four major clusters were identified: “C-Fos Expression”, “Lactating Rat”, “Medial Preoptic Area Interaction” and “Parental Behavior”. Their content suggests an initial trend in which the properties of the MPOA in response to parental behavior were studied, followed by a growing attention towards the presence of a brain network, including the reward circuits, regulating such behavior. Furthermore, while attention was initially directed uniquely to maternal behavior, it has recently been extended to the understanding of paternal behaviors as well. Finally, although the majority of the studies were conducted on rodents, recent publications broaden the implications of previous documents to human parental behavior, giving insight into the mechanisms underlying postpartum depression. Potential directions in future works were also discussed.
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Mohan, T. R. Krishna. "Bifurcations and Chaos in a Model Biochemical Reaction Pathway." International Journal of Bifurcation and Chaos 08, no. 02 (February 1998): 381–94. http://dx.doi.org/10.1142/s0218127498000231.
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Control mechanisms in the form of positive and negative feedback loops are responsible for the sensitivity and stability in the coherent behavior of the spatio-temporal organization in living cells. Models of these networks involving such feedback mechanisms have been shown to exhibit a rich spectrum of dynamical behaviors. A network involving both positive and negative feedbacks was earlier investigated by Sinha and Ramaswamy [1987]. We obtain a phase diagram of the possible dynamical behaviors for this model. Further, we investigate the origin and properties of the complex oscillations in the model. A simpler system is derived and shown to possess similar dynamical behaviors. Avenues for further investigation of the system with respect to relevant variations in some of the parameter values are suggested.
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Glavaški, Mila, and Lazar Velicki. "Shared Molecular Mechanisms of Hypertrophic Cardiomyopathy and Its Clinical Presentations: Automated Molecular Mechanisms Extraction Approach." Life 11, no. 8 (August 3, 2021): 785. http://dx.doi.org/10.3390/life11080785.
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Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiovascular disease with a prevalence of 1 in 500 people and varying clinical presentations. Although there is much research on HCM, underlying molecular mechanisms are poorly understood, and research on the molecular mechanisms of its specific clinical presentations is scarce. Our aim was to explore the molecular mechanisms shared by HCM and its clinical presentations through the automated extraction of molecular mechanisms. Molecular mechanisms were congregated by a query of the INDRA database, which aggregates knowledge from pathway databases and combines it with molecular mechanisms extracted from abstracts and open-access full articles by multiple machine-reading systems. The molecular mechanisms were extracted from 230,072 articles on HCM and 19 HCM clinical presentations, and their intersections were found. Shared molecular mechanisms of HCM and its clinical presentations were represented as networks; the most important elements in the intersections’ networks were found, centrality scores for each element of each network calculated, networks with reduced level of noise generated, and cooperatively working elements detected in each intersection network. The identified shared molecular mechanisms represent possible mechanisms underlying different HCM clinical presentations. Applied methodology produced results consistent with the information in the scientific literature.
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Li, Xuelong, Marko Jusup, Zhen Wang, Huijia Li, Lei Shi, Boris Podobnik, H. Eugene Stanley, Shlomo Havlin, and Stefano Boccaletti. "Punishment diminishes the benefits of network reciprocity in social dilemma experiments." Proceedings of the National Academy of Sciences 115, no. 1 (December 19, 2017): 30–35. http://dx.doi.org/10.1073/pnas.1707505115.
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Network reciprocity has been widely advertised in theoretical studies as one of the basic cooperation-promoting mechanisms, but experimental evidence favoring this type of reciprocity was published only recently. When organized in an unchanging network of social contacts, human subjects cooperate provided the following strict condition is satisfied: The benefit of cooperation must outweigh the total cost of cooperating with all neighbors. In an attempt to relax this condition, we perform social dilemma experiments wherein network reciprocity is aided with another theoretically hypothesized cooperation-promoting mechanism—costly punishment. The results reveal how networks promote and stabilize cooperation. This stabilizing effect is stronger in a smaller-size neighborhood, as expected from theory and experiments. Contrary to expectations, punishment diminishes the benefits of network reciprocity by lowering assortment, payoff per round, and award for cooperative behavior. This diminishing effect is stronger in a larger-size neighborhood. An immediate implication is that the psychological effects of enduring punishment override the rational response anticipated in quantitative models of cooperation in networks.
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Tong, Xing, and Xiaomeng Han. "Knowledge network capability and organizational innovation: Network position transition and ambidextrous innovative behaviors as mediators." Social Behavior and Personality: an international journal 49, no. 9 (September 1, 2021): 1–16. http://dx.doi.org/10.2224/sbp.10246.
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In this study we examined the influence of knowledge network capability on organizational innovation. Drawing on organizational network theory and taking a knowledge-based view, we proposed ambidextrous innovation behavior and network position transition as mediators to clarify the underlying mechanisms of the effect of knowledge network capability on organizational innovation. Furthermore, we proposed knowledge base as a boundary variable to understand its interplay with knowledge network capability in regard to organizational innovation. Participants were 265 senior managers of recently established high-tech enterprises in China. Consistent with our predictions, the results show there was a positive relationship between knowledge network capability and ambidextrous innovation behavior, and network position transition mediated this relationship. In addition, the results suggest that knowledge base can strengthen the direct effect of knowledge network capability on organizational innovation. Our findings enrich the literature on knowledge networks and innovation, and provide important implications for enterprises to innovate by employing knowledge network capability.
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Siegel, Alexandra A., Jonathan Nagler, Richard Bonneau, and Joshua A. Tucker. "Tweeting Beyond Tahrir." World Politics 73, no. 2 (March 26, 2021): 243–74. http://dx.doi.org/10.1017/s0043887120000295.
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abstractDo online social networks affect political tolerance in the highly polarized climate of postcoup Egypt? Taking advantage of the real-time networked structure of Twitter data, the authors find that not only is greater network diversity associated with lower levels of intolerance, but also that longer exposure to a diverse network is linked to less expression of intolerance over time. The authors find that this relationship persists in both elite and non-elite diverse networks. Exploring the mechanisms by which network diversity might affect tolerance, the authors offer suggestive evidence that social norms in online networks may shape individuals’ propensity to publicly express intolerant attitudes. The findings contribute to the political tolerance literature and enrich the ongoing debate over the relationship between online echo chambers and political attitudes and behavior by providing new insights from a repressive authoritarian context.
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Gelenbe, Erol, and Stelios Timotheou. "Random Neural Networks with Synchronized Interactions." Neural Computation 20, no. 9 (September 2008): 2308–24. http://dx.doi.org/10.1162/neco.2008.04-07-509.
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Large-scale distributed systems, such as natural neuronal and artificial systems, have many local interconnections, but they often also have the ability to propagate information very fast over relatively large distances. Mechanisms that enable such behavior include very long physical signaling paths and possibly saccades of synchronous behavior that may propagate across a network. This letter studies the modeling of such behaviors in neuronal networks and develops a related learning algorithm. This is done in the context of the random neural network (RNN), a probabilistic model with a well-developed mathematical theory, which was inspired by the apparently stochastic spiking behavior of certain natural neuronal systems. Thus, we develop an extension of the RNN to the case when synchronous interactions can occur, leading to synchronous firing by large ensembles of cells. We also present an O(N3) gradient descent learning algorithm for an N-cell recurrent network having both conventional excitatory-inhibitory interactions and synchronous interactions. Finally, the model and its learning algorithm are applied to a resource allocation problem that is NP-hard and requires fast approximate decisions.
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Mühlbauer, Ricardo, and João Kleinschmidt. "Bring Your Own Reputation: A Feasible Trust System for Vehicular Ad Hoc Networks." Journal of Sensor and Actuator Networks 7, no. 3 (September 1, 2018): 37. http://dx.doi.org/10.3390/jsan7030037.
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The establishment of trust in vehicular ad hoc networks (VANETs) will require the application of non-conventional measures of information security, such as reputation of the participants. The system proposed in this paper uses the concept of certified reputation, in which vehicles communicate providing digital certificates that include their own reputation level. The vehicles periodically come in contact with certification and traffic control authorities to update their reputation levels, which are determined by the validation of their behavior on the network. Decision-making mechanisms in the receiver vehicles are responsible for evaluating whether the messages are true or false, based on the reputation of the communication nodes. The quantitative analysis of simulated scenarios showed the combination of the central reputation scheme with an appropriate vehicular decision mechanism achieved a total of correct decisions superior than without reputation systems. Considering the constraints of a high mobile network, the proposed system is a feasible way to reduce the risk of anomalous or malicious behavior in a vehicular network.
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Ghazizadeh, Elham, and ShiNung Ching. "Slow manifolds within network dynamics encode working memory efficiently and robustly." PLOS Computational Biology 17, no. 9 (September 15, 2021): e1009366. http://dx.doi.org/10.1371/journal.pcbi.1009366.
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Working memory is a cognitive function involving the storage and manipulation of latent information over brief intervals of time, thus making it crucial for context-dependent computation. Here, we use a top-down modeling approach to examine network-level mechanisms of working memory, an enigmatic issue and central topic of study in neuroscience. We optimize thousands of recurrent rate-based neural networks on a working memory task and then perform dynamical systems analysis on the ensuing optimized networks, wherein we find that four distinct dynamical mechanisms can emerge. In particular, we show the prevalence of a mechanism in which memories are encoded along slow stable manifolds in the network state space, leading to a phasic neuronal activation profile during memory periods. In contrast to mechanisms in which memories are directly encoded at stable attractors, these networks naturally forget stimuli over time. Despite this seeming functional disadvantage, they are more efficient in terms of how they leverage their attractor landscape and paradoxically, are considerably more robust to noise. Our results provide new hypotheses regarding how working memory function may be encoded within the dynamics of neural circuits.
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Muratbekova-Touron, Maral, and Tolganay Umbetalijeva. "Human Resource Management Patterns of (Anti) Corruption Mechanisms within Informal Networks." Business and Professional Ethics Journal 38, no. 2 (2019): 177–93. http://dx.doi.org/10.5840/bpej201961880.
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In this article, we propose to comprehend the corruption mechanisms of tender bidding processes in terms of Human Resource Management (HRM) practices within informal networks. Taking the context of Kazakhstan, we analyze the behavior of individual actors as members of informal networks. Our analysis shows that both corruption and anti-corruption mechanisms can be explained in terms of HRM practices such as (camouflaged) recruitment (e.g., of powerful government officials via network ties), compensation (e.g., kickbacks for corruption; social recognition or shame for anti-corruption) and performance management (e.g., demonstrative punishment for corruption; extreme formalization, peer pressure or social sanctions for anti-corruption).
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Marsh, Donald J., Dmitry D. Postnov, Olga V. Sosnovtseva, and Niels-Henrik Holstein-Rathlou. "The nephron-arterial network and its interactions." American Journal of Physiology-Renal Physiology 316, no. 5 (May 1, 2019): F769—F784. http://dx.doi.org/10.1152/ajprenal.00484.2018.
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Tubuloglomerular feedback and the myogenic mechanism form an ensemble in renal afferent arterioles that regulate single-nephron blood flow and glomerular filtration. Each mechanism generates a self-sustained oscillation, the mechanisms interact, and the oscillations synchronize. The synchronization generates a bimodal electrical signal in the arteriolar wall that propagates retrograde to a vascular node, where it meets similar electrical signals from other nephrons. Each signal carries information about the time-dependent behavior of the regulatory ensemble. The converging signals support synchronization of the nephrons participating in the information exchange, and the synchronization can lead to formation of nephron clusters. We review the experimental evidence and the theoretical implications of these interactions and consider additional interactions that can limit the size of nephron clusters. The architecture of the arterial tree figures prominently in these interactions.
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Chevalier, Marc, Rafaël De Sa, Laura Cardoit, and Muriel Thoby-Brisson. "Mechanisms Underlying Adaptation of Respiratory Network Activity to Modulatory Stimuli in the Mouse Embryo." Neural Plasticity 2016 (2016): 1–10. http://dx.doi.org/10.1155/2016/3905257.
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Breathing is a rhythmic behavior that requires organized contractions of respiratory effector muscles. This behavior must adapt to constantly changing conditions in order to ensure homeostasis, proper body oxygenation, and CO2/pH regulation. Respiratory rhythmogenesis is controlled by neural networks located in the brainstem. One area considered to be essential for generating the inspiratory phase of the respiratory rhythm is the preBötzinger complex (preBötC). Rhythmogenesis emerges from this network through the interplay between the activation of intrinsic cellular properties (pacemaker properties) and intercellular synaptic connections. Respiratory activity continuously changes under the impact of numerous modulatory substances depending on organismal needs and environmental conditions. The preBötC network has been shown to become active during the last third of gestation. But only little is known regarding the modulation of inspiratory rhythmicity at embryonic stages and even less on a possible role of pacemaker neurons in this functional flexibility during the prenatal period. By combining electrophysiology and calcium imaging performed on embryonic brainstem slice preparations, we provide evidence showing that embryonic inspiratory pacemaker neurons are already intrinsically sensitive to neuromodulation and external conditions (i.e., temperature) affecting respiratory network activity, suggesting a potential role of pacemaker neurons in mediating rhythm adaptation to modulatory stimuli in the embryo.
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Joseph, Meera, and Akinlabi Olaniyi Akindeji. "Optimizing Signal Behavior of Femtocells for Improved Network." Transactions on Environment and Electrical Engineering 1, no. 3 (October 16, 2016): 100. http://dx.doi.org/10.22149/teee.v1i3.51.
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The high demand for network coverage in an indoor setting brought about the acceptance of femtocell technology as a solution using the backhaul connectivity in the existing network. The quality of signal, voice calling, Internet, security and data are improved through the use femtocell at the indoor environment. Here the service provider attempts to reduce their operation cost by presenting self-organizing mechanisms for optimization of the network. The remarkable part is that, femtocells improves coverage, enhances the data rate at the indoor environment. Therefore, the challenges of the femtocell also known as interference deteriorates the capacity and quality performance of the whole cellular network. In this paper we simulate the bit error rate against signal behaviour at the indoor environment and we also simulate the transmitting power over signal for both macrocells and femtocells. We focus on the transmitting power that might cause interference within the cellular network.
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Ramirez, Jan-Marino, and Nathan A. Baertsch. "The Dynamic Basis of Respiratory Rhythm Generation: One Breath at a Time." Annual Review of Neuroscience 41, no. 1 (July 8, 2018): 475–99. http://dx.doi.org/10.1146/annurev-neuro-080317-061756.
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Rhythmicity is a universal timing mechanism in the brain, and the rhythmogenic mechanisms are generally dynamic. This is illustrated for the neuronal control of breathing, a behavior that occurs as a one-, two-, or three-phase rhythm. Each breath is assembled stochastically, and increasing evidence suggests that each phase can be generated independently by a dedicated excitatory microcircuit. Within each microcircuit, rhythmicity emerges through three entangled mechanisms: ( a) glutamatergic transmission, which is amplified by ( b) intrinsic bursting and opposed by ( c) concurrent inhibition. This rhythmogenic triangle is dynamically tuned by neuromodulators and other network interactions. The ability of coupled oscillators to reconfigure and recombine may allow breathing to remain robust yet plastic enough to conform to nonventilatory behaviors such as vocalization, swallowing, and coughing. Lessons learned from the respiratory network may translate to other highly dynamic and integrated rhythmic systems, if approached one breath at a time.
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Dumas, G., Q. Moreau, E. Tognoli, and J. A. S. Kelso. "The Human Dynamic Clamp Reveals the Fronto-Parietal Network Linking Real-Time Social Coordination and Cognition." Cerebral Cortex 30, no. 5 (December 20, 2019): 3271–85. http://dx.doi.org/10.1093/cercor/bhz308.
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Abstract How does the brain allow us to interact with others? Social neuroscience has already provided some answers to these questions but has tended to treat high-level, cognitive interpretations of social behavior separately from the sensorimotor mechanisms upon which they rely. The goal here is to identify the underlying neural processes and mechanisms linking sensorimotor coordination and intention attribution. We combine the human dynamic clamp, a novel paradigm for studyingrealistic social behavior, with high-resolution electroencephalography. The collection of humanness and intention attribution reports, kinematics, and neural data affords an opportunity to relate brain activity to the ongoing social behavior. Behavioral results demonstrate that sensorimotor coordination influences the judgments of cooperativeness and humanness. Analysis of brain dynamics reveals two distinct networks related to the integration of visuo-motor information from self and other which overlap over the right parietal region. Furthermore, judgment of humanness and cooperation of others modulate the functional connectivity between this right parietal hub and the prefrontal cortex. These results reveal how distributed neural dynamics integrates information from “low-level” sensorimotor mechanisms and “high-level” social cognition to support the realistic social behaviors that play out in real time during interactive scenarios.
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Parvin, Sazia, Amjad Gawanmeh, Sitalakshmi Venkatraman, Ali Alwadi, Jamal N. Al-Karaki, and Paul D. Yoo. "A trust-based authentication framework for security of WPAN using network slicing." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 2 (April 1, 2021): 1375. http://dx.doi.org/10.11591/ijece.v11i2.pp1375-1387.
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New technologies bring along many challenges including security and privacy. Wireless personal area networks (WPANs) are characterized by limited energy resources and computing power that calls for lightweight security mechanisms in these networks as a mandatory requirement. In this paper, a lightweight trust-based framework for node authentication in WPAN is proposed. Our main objective is to minimise the effort in distinguishing valid requests of trustworthy nodes from invalid requests of malicious nodes that can result in network compromises. We achieve this through network slicing which divides the network into virtually primary and secondary networks. The proposed framework has three-fold benefits. First, it authenticates nodes’ requests based on a novel method of trust value calculation. Second, the framework maintains energy efficiency while authenticating nodes’ requests to access WPAN resources. Finally, the framework provides a solution for biasing problem that can arise due to unexpected behaviour of malicious users in WPANs. The framework efficacy is illustrated on a case study to shown how it can accurately capture trust relations among nodes while preventing malicious behavior.
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DITTRICH, PETER, and LARS WINTER. "CHEMICAL ORGANIZATIONS IN A TOY MODEL OF THE POLITICAL SYSTEM." Advances in Complex Systems 11, no. 04 (August 2008): 609–27. http://dx.doi.org/10.1142/s0219525908001878.
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Because sociology is seeking mechanisms for explaining social phenomena, we discuss in this paper whether and how the metaphor of a chemical reaction network can be employed as a formal mechanism to describe social and political systems. A reaction network is a quite general concept that allows one to model a variety of dynamical systems. Furthermore, a set of powerful tools can infer potential dynamical properties from the network structure. Using a toy model of the political system inspired by Luhmann, we demonstrate how chemical organization theory can be applied and can give insight into the structure and dynamics of the resulting model. We show how chemical organization theory allows one to identify an overlapping hierarchy of important subsystems in these networks. Simulations reveal how this hierarchy constrains the potential dynamical behavior of the model.
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Norekian, Tigran P., and Aleksey Y. Malyshev. "Neural Mechanisms Underlying Co-Activation of Functionally Antagonistic Motoneurons During a Clione Feeding Behavior." Journal of Neurophysiology 95, no. 4 (April 2006): 2560–69. http://dx.doi.org/10.1152/jn.01174.2005.
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The ability of some neural networks to produce multiple motor patterns required during different behaviors is a well-documented phenomenon. We describe here a dramatic transition from coordinated inhibition between two functionally antagonistic groups of motoneurons to their co-activation in the feeding neural network of the predatory mollusk Clione limacina. To seize its prey, Clione uses specialized oral appendages, called buccal cones, which are controlled by two groups of motoneurons: cerebral A (Cr-A) neurons controlling buccal cone protraction and cerebral B (Cr-B) neurons controlling buccal cone retraction. When Cr-A neurons are active, Cr-B neurons usually receive strong inhibitory inputs that terminate their firing, which leads to the full protraction and elongation of the buccal cones. We have found, however, that the Cr-A and Cr-B motoneurons sometimes burst simultaneously without any traces of inhibition in the Cr-B motoneurons. This transformation of the neural network activity from inhibitory interactions to co-activation presumably occurs during the late “extraction” period of the feeding behavior when buccal cones become partially retracted and rhythmically active. The transition from the inhibitory interaction to co-activation is controlled by the activity of a single pair of cerebral interneurons (Cr-Aint interneurons), which are electrically coupled to the Cr-A neurons and monosynaptically inhibit Cr-B neurons. Normally, the Cr-Aint interneurons are active along with Cr-A motoneurons and inhibit Cr-B motoneurons. During a period of co-activation, however, these interneurons do not produce spikes, thus allowing Cr-A motoneuron activation without inhibition of the Cr-B motoneurons.
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RADDE, NICOLE. "THE EFFECT OF TIME SCALE DIFFERENCES AND TIME DELAYS ON THE STRUCTURAL STABILITY OF OSCILLATIONS IN A TWO-GENE NETWORK." Advances in Complex Systems 11, no. 03 (June 2008): 471–83. http://dx.doi.org/10.1142/s0219525908001751.
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Biological networks are often modeled by systems of ordinary differential equations. In chemical reaction kinetics, for instance, sigmoid functions represent the regulation of gene expression via transcription factors. Solutions of these models tend to converge to a unique steady state, and feedback control mechanisms are required for a more complex dynamic behavior. This paper focuses on periodic behavior in two-component regulatory networks. Here, a key issue is that oscillations in chemical reaction systems are usually not robust with respect to parameter variations. Small variations lead to bifurcations that change the system's overall qualitative dynamic behavior. This concerns the mechanisms stabilizing periodic behavior in living cells. Using a small sample network, we demonstrate that oscillations can efficiently be stabilized by large time scale differences that correspond to reactions with different velocities. Furthermore, the inclusion of a time delay, reflecting transport and diffusion processes, has a similar effect. This suggests that processes of this kind potentially play a crucial role in biological oscillators.
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Skinner, F. K., L. Zhang, J. L. Perez Velazquez, and P. L. Carlen. "Bursting in Inhibitory Interneuronal Networks: A Role for Gap-Junctional Coupling." Journal of Neurophysiology 81, no. 3 (March 1, 1999): 1274–83. http://dx.doi.org/10.1152/jn.1999.81.3.1274.
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Bursting in inhibitory interneuronal networks: a role for gap-junctional coupling. Much work now emphasizes the concept that interneuronal networks play critical roles in generating synchronized, oscillatory behavior. Experimental work has shown that functional inhibitory networks alone can produce synchronized activity, and theoretical work has demonstrated how synchrony could occur in mutually inhibitory networks. Even though gap junctions are known to exist between interneurons, their role is far from clear. We present a mechanism by which synchronized bursting can be produced in a minimal network of mutually inhibitory and gap-junctionally coupled neurons. The bursting relies on the presence of persistent sodium and slowly inactivating potassium currents in the individual neurons. Both GABAA inhibitory currents and gap-junctional coupling are required for stable bursting behavior to be obtained. Typically, the role of gap-junctional coupling is focused on synchronization mechanisms. However, these results suggest that a possible role of gap-junctional coupling may lie in the generation and stabilization of bursting oscillatory behavior.
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Zhang, Guo, Ke Yu, Tao Wang, Ting-Ting Chen, Wang-Ding Yuan, Fan Yang, Zi-Wei Le, et al. "Synaptic mechanisms for motor variability in a feedforward network." Science Advances 6, no. 25 (June 2020): eaba4856. http://dx.doi.org/10.1126/sciadv.aba4856.
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Behavioral variability often arises from variable activity in the behavior-generating neural network. The synaptic mechanisms underlying this variability are poorly understood. We show that synaptic noise, in conjunction with weak feedforward excitation, generates variable motor output in the Aplysia feeding system. A command-like neuron (CBI-10) triggers rhythmic motor programs more variable than programs triggered by CBI-2. CBI-10 weakly excites a pivotal pattern-generating interneuron (B34) strongly activated by CBI-2. The activation properties of B34 substantially account for the degree of program variability. CBI-10– and CBI-2–induced EPSPs in B34 vary in amplitude across trials, suggesting that there is synaptic noise. Computational studies show that synaptic noise is required for program variability. Further, at network state transition points when synaptic conductance is low, maximum program variability is promoted by moderate noise levels. Thus, synaptic strength and noise act together in a nonlinear manner to determine the degree of variability within a feedforward network.
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Horn, D., and E. Ruppin. "Compensatory Mechanisms in an Attractor Neural Network Model of Schizophrenia." Neural Computation 7, no. 1 (January 1995): 182–205. http://dx.doi.org/10.1162/neco.1995.7.1.182.
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We investigate the effect of synaptic compensation on the dynamic behavior of an attractor neural network receiving its input stimuli as external fields projecting on the network. It is shown how, in the face of weakened inputs, memory performance may be preserved by strengthening internal synaptic connections and increasing the noise level. Yet, these compensatory changes necessarily have adverse side effects, leading to spontaneous, stimulus-independent retrieval of stored patterns. These results can support Stevens' recent hypothesis that the onset of schizophrenia is associated with frontal synaptic regeneration, occurring subsequent to the degeneration of temporal neurons projecting on these areas.
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Behn, Cecilia G. Diniz, Emery N. Brown, Thomas E. Scammell, and Nancy J. Kopell. "Mathematical Model of Network Dynamics Governing Mouse Sleep–Wake Behavior." Journal of Neurophysiology 97, no. 6 (June 2007): 3828–40. http://dx.doi.org/10.1152/jn.01184.2006.
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Recent work in experimental neurophysiology has identified distinct neuronal populations in the rodent brain stem and hypothalamus that selectively promote wake and sleep. Mutual inhibition between these cell groups has suggested the conceptual model of a sleep–wake switch that controls transitions between wake and sleep while minimizing time spent in intermediate states. By combining wake- and sleep-active populations with populations governing transitions between different stages of sleep, a “sleep–wake network” of neuronal populations may be defined. To better understand the dynamics inherent in this network, we created a model sleep–wake network composed of coupled relaxation oscillation equations. Mathematical analysis of the deterministic model provides insight into the dynamics underlying state transitions and predicts mechanisms for each transition type. With the addition of noise, the simulated sleep–wake behavior generated by the model reproduces many qualitative and quantitative features of mouse sleep–wake behavior. In particular, the existence of simulated brief awakenings is a unique feature of the model. In addition to capturing the experimentally observed qualitative difference between brief and sustained wake bouts, the model suggests distinct network mechanisms for the two types of wakefulness. Because circadian and other factors alter the fine architecture of sleep–wake behavior, this model provides a novel framework to explore dynamical principles that may underlie normal and pathologic sleep–wake physiology.
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Chou, Kenny F., and Kamal Sen. "AIM: A network model of attention in auditory cortex." PLOS Computational Biology 17, no. 8 (August 27, 2021): e1009356. http://dx.doi.org/10.1371/journal.pcbi.1009356.
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Attentional modulation of cortical networks is critical for the cognitive flexibility required to process complex scenes. Current theoretical frameworks for attention are based almost exclusively on studies in visual cortex, where attentional effects are typically modest and excitatory. In contrast, attentional effects in auditory cortex can be large and suppressive. A theoretical framework for explaining attentional effects in auditory cortex is lacking, preventing a broader understanding of cortical mechanisms underlying attention. Here, we present a cortical network model of attention in primary auditory cortex (A1). A key mechanism in our network is attentional inhibitory modulation (AIM) of cortical inhibitory neurons. In this mechanism, top-down inhibitory neurons disinhibit bottom-up cortical circuits, a prominent circuit motif observed in sensory cortex. Our results reveal that the same underlying mechanisms in the AIM network can explain diverse attentional effects on both spatial and frequency tuning in A1. We find that a dominant effect of disinhibition on cortical tuning is suppressive, consistent with experimental observations. Functionally, the AIM network may play a key role in solving the cocktail party problem. We demonstrate how attention can guide the AIM network to monitor an acoustic scene, select a specific target, or switch to a different target, providing flexible outputs for solving the cocktail party problem.
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Perez, Phoebe Nicole G., Paul Albert L. Sino, Marvin U. Herrera, and Alvin Karlo Garcia Tapia. "Conducting Properties of Polyaniline Emeraldine Salt on Paper in the Low-Frequency Region." Materials Science Forum 923 (May 2018): 72–76. http://dx.doi.org/10.4028/www.scientific.net/msf.923.72.
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Polyaniline emeraldine salt (PAni-ES) was successfully deposited on paper through layer-by-layer technique. In this method, a paper was alternately dipped in aniline monomer and an oxidizing agent for different dipping cycles. This process produced green PAni-ES on paper. The morphology of the samples showed polymeric networks with pores, fiber-like structures and aggregates. There is a transition from frequency-independent to frequency-dependent conductivities of the samples. The conductivity increased with increasing number of dipping cycles. The frequency-dependent conductivities follow the power-law behavior reflecting conducting network and hopping mechanisms. Lastly, the conductivities with frequency followed a scaling behavior reflecting a common physical mechanism in PAni-ES on paper.
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Barreto, Luís. "XCP-Winf and RCP-Winf: Improving Explicit Wireless Congestion Control." Journal of Computer Networks and Communications 2015 (2015): 1–18. http://dx.doi.org/10.1155/2015/925207.
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Congestion control in wireless networks is strongly dependent on the dynamics and instability of wireless links. Therefore, it is very difficult to accurately evaluate the characteristics of the wireless links. It is known that TCP experiences serious performance degradation problems in wireless networks. Moreover, congestion control mechanisms that rely on network interaction and network parameters, such as XCP and RCP, do not evaluate accurately the capacity and available link bandwidth in wireless networks. In this paper we propose new explicit flow control protocols for wireless mesh networks, based on XCP and RCP. We name these protocols XCP-Winf and RCP-Winf. They rely on the MAC layer information gathered by a new method to accurately estimate the available bandwidth and the path capacity over a wireless network path. The estimation is performed in real time and without the need to intrusively inject packets in the network. These new congestion control mechanisms are evaluated in different scenarios in wireless mesh and ad hoc networks and compared against several new approaches for wireless congestion control. It is shown that both XCP-Winf and RCP-Winf outperform the evaluated approaches, showing its stable behavior and better channel utilization.
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Mura, Ivan. "On the impact of hidden modeling assumptions on living systems- predictive dynamics." Revista Ontare 2, no. 1 (September 17, 2015): 85. http://dx.doi.org/10.21158/23823399.v2.n1.2014.1236.
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ONTARE. REVISTA DE INVESTIGACIÓN DE LA FACULTAD DE INGENIERÍAThis paper aims at showing the predictive modeling of living systems, particularly some commonly structured modeling assumptions which simplify the behavior of living systems. It also takes into account the stochastic modeling of basic gene expression mechanisms, such as transcription and translation, reaffirming the effect that simplifications have on the predictive behavior of living systems. These mechanisms rely on the basis of most gene expressions, signaling pathways and protein- protein interaction network models. This paper states that the usage of naïve modeling abstractions may result in predictive behaviors that are quite far from reality.
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Tan, Haowen, Yuanzhao Song, Shichang Xuan, Sungbum Pan, and Ilyong Chung. "Secure D2D Group Authentication Employing Smartphone Sensor Behavior Analysis." Symmetry 11, no. 8 (August 1, 2019): 969. http://dx.doi.org/10.3390/sym11080969.
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Nowadays, with rapid advancement of both the upcoming 5G architecture construction and emerging Internet of Things (IoT) scenarios, Device-to-Device (D2D) communication provides a novel paradigm for mobile networking. By facilitating continuous and high data rate services between physically proximate devices without interconnection with access points (AP) or service network (SN), spectral efficiency of the 5G network can be drastically increased. However, due to its inherent open wireless communicating features, security issues and privacy risks in D2D communication remain unsolved in spite of its benefits and prosperous future. Hence, proper D2D authentication mechanisms among the D2D entities are of great significance. Moreover, the increasing proliferation of smartphones enables seamlessly biometric sensor data collecting and processing, which highly correspond to the user’s unique behavioral characteristics. For the above consideration, we present a secure certificateless D2D authenticating mechanism intended for extreme scenarios in this paper. In the assumption, the key updating mechanism only requires a small modification in the SN side, while the decryption information of user equipment (UEs) remains constant as soon as the UEs are validated. Note that a symmetric key mechanism is adopted for the further data transmission. Additionally, the user activities data from smartphone sensors are analyzed for continuous authentication, which is periodically conducted after the initial validation. Note that in the assumed scenario, most of the UEs are out of the effective range of cellular networks. In this case, the UEs are capable of conducting data exchange without cellular connection. Security analysis demonstrates that the proposed scheme can provide adequate security properties as well as resistance to various attacks. Furthermore, performance analysis proves that the proposed scheme is efficient compared with state-of-the-art D2D authentication schemes.
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Eggebrecht, Adam T., Jed T. Elison, Eric Feczko, Alexandre Todorov, Jason J. Wolff, Sridhar Kandala, Chloe M. Adams, et al. "Joint Attention and Brain Functional Connectivity in Infants and Toddlers." Cerebral Cortex 27, no. 3 (January 7, 2017): 1709–20. http://dx.doi.org/10.1093/cercor/bhw403.
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Abstract Initiating joint attention (IJA), the behavioral instigation of coordinated focus of 2 people on an object, emerges over the first 2 years of life and supports social-communicative functioning related to the healthy development of aspects of language, empathy, and theory of mind. Deficits in IJA provide strong early indicators for autism spectrum disorder, and therapies targeting joint attention have shown tremendous promise. However, the brain systems underlying IJA in early childhood are poorly understood, due in part to significant methodological challenges in imaging localized brain function that supports social behaviors during the first 2 years of life. Herein, we show that the functional organization of the brain is intimately related to the emergence of IJA using functional connectivity magnetic resonance imaging and dimensional behavioral assessments in a large semilongitudinal cohort of infants and toddlers. In particular, though functional connections spanning the brain are involved in IJA, the strongest brain-behavior associations cluster within connections between a small subset of functional brain networks; namely between the visual network and dorsal attention network and between the visual network and posterior cingulate aspects of the default mode network. These observations mark the earliest known description of how functional brain systems underlie a burgeoning fundamental social behavior, may help improve the design of targeted therapies for neurodevelopmental disorders, and, more generally, elucidate physiological mechanisms essential to healthy social behavior development.
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SOLODOVNIKOV, S. "NETWORK MECHANISMS OF ECONOMIC MANAGEMENT AS NEW FORMS OF SOCIAL AND FUNCTIONAL TECHNOLOGIES." Экономическая наука сегодня, no. 9 (June 27, 2019): 84–92. http://dx.doi.org/10.21122/2309-6667-2019-9-84-92.
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The article aims to eliminate the gap in the study of network mechanisms of economic management as new forms of social and functional technologies. As a result of the study, the concept of network mechanisms of economic management is defined as fundamentally new forms of social and functional technologies, characterized by a significant acceleration of management processes, receiving and exchanging information through the use of the latest Internet technologies, which leads to changes in the behavior logic of the network economy subjects and ideological competition. The influence of network mechanisms of economic management on the emergence of fundamentally new mechanisms of economic and political economic competition has been investigated.