Cell and circuit origins of fast network oscillations in the mammalian main olfactory bulb

Neural synchrony generates fast network oscillations throughout the brain, including the main olfactory bulb (MOB), the first processing station of the olfactory system. Identifying the mechanisms synchronizing neurons in the MOB will be key to understanding how network oscillations support the coding of a high-dimensional sensory space. Here, using paired recordings and optogenetic activation of glomerular sensory inputs in MOB slices, we uncovered profound differences in principal mitral cell (MC) vs. tufted cell (TC) spike-time synchrony: TCs robustly synchronized across fast- and slow-gamma frequencies, while MC synchrony was weaker and concentrated in slow-gamma frequencies. Synchrony among both cell types was enhanced by shared glomerular input but was independent of intraglomerular lateral excitation. Cell-type differences in synchrony could also not be traced to any difference in the synchronization of synaptic inhibition. Instead, greater TC than MC synchrony paralleled the more periodic firing among resonant TCs than MCs and emerged in patterns consistent with densely synchronous network oscillations. Collectively, our results thus reveal a mechanism for parallel processing of sensory information in the MOB via differential TC vs. MC synchrony, and further contrast mechanisms driving fast network oscillations in the MOB from those driving the sparse synchronization of irregularly-firing principal cells throughout cortex.

Cell and circuit origins of fast network oscillations in the mammalian main olfactory bulb

Neural synchrony generates fast network oscillations throughout the brain, including the main olfactory bulb (MOB), the first processing station of the olfactory system. Identifying the mechanisms synchronizing neurons in the MOB will be key to understanding how network oscillations support the coding of a high-dimensional sensory space. Here, using paired recordings and optogenetic activation of glomerular sensory inputs in MOB slices, we uncovered profound differences in principal mitral cell (MC) vs. tufted cell (TC) spike-time synchrony: TCs robustly synchronized across fast- and slow-gamma frequencies, while MC synchrony was weaker and concentrated in slow-gamma frequencies. Synchrony among both cell types was enhanced by shared glomerular input but was independent of intraglomerular lateral excitation. Cell-type differences in synchrony could also not be traced to any difference in the synchronization of synaptic inhibition. Instead, greater TC than MC synchrony paralleled the more periodic firing among resonant TCs than MCs and emerged in patterns consistent with densely synchronous network oscillations. Collectively, our results thus reveal a mechanism for parallel processing of sensory information in the MOB via differential TC vs. MC synchrony, and further contrast mechanisms driving fast network oscillations in the MOB from those driving the sparse synchronization of irregularly-firing principal cells throughout cortex.

FAST NETWORK CODING SIMULATION WITH PARALLELIZATION OF PROCESSES IN THE DTSMS SYSTEM

Изложены принципы быстрого имитационного моделирования процедур сетевого кодирования с распараллеливанием процессов в многоядерных ЭВМ на основе разработанной системы моделирования DTSMS. Представлены способы и схемы взаимодействия элементов модели с реализацией модели сети в соответствии с общепринятой в сетевом кодировании архитектурой «бабочка» для последовательного и асинхронного режимов работы. Выполнена оценка объема выделяемой памяти и времени моделирования для DTSMS в сравнении с реализацией на открытой системе компьютерной алгебры GNU/Octave. The principles of fast network coding simulation with parallelization of processes in multicore computers based on the developed DTSMS simulation system are stated. Methods and schemes of the sequential and asynchronous model elements interaction within the framework of the "butterfly" network model architecture generally accepted in network coding are presented. The allocated memory amount and simulation time for DTSMS are estimated in comparison with the open computer algebra system GNU/Octave.

Geocast Routing Protocols for Ad-Hoc Networks

Geocasting is a subset of conventional multicasting problem. Geocasting means to deliver a message or data to a specific geographical area. Routing refers to the activities necessary to route a message in its travel from source to the destination node. The routing of a message is very important and relatively difficult problems in the context of Ad-hoc Networks because nodes are moving very fast, network load or traffic patterns, and topology of the network is dynamical changes with time. In this chapter, different geocast routing mechanisms used in both Mobile Ad-hoc Networks and Vehicular Ad-hoc Networks. The authors have shown a strong and in-depth analysis of the strengths and weaknesses of each protocol. For delivering geocast message, both the source and destination nodes use location information. The nodes determine their locations by using the Global Positioning System (GPS). They have presented a comprehensive comparative analysis of existing geocast routing protocols and proposed future direction in designing a new routing protocol addressing the problem.

Personality, Resilience, and Psychopathology: A Model for the Interaction between Slow and Fast Network Processes in the Context of Mental Health

Network theories have been put forward for psychopathology (in which mental disorders originate from causal relations between symptoms) and for personality (in which personality factors originate from coupled equilibria of cognitions, affect states, behaviours, and environments). Here, we connect these theoretical strands in an overarching personality–resilience–psychopathology model. In this model, factors in personality networks control the shape of the dynamical landscape in which symptom networks evolve; for example, the neuroticism item ‘I often feel blue’ measures a general tendency to experience negative affect, which is hypothesized to influence the threshold parameter of the symptom ‘depressed mood’ in the psychopathology network. Conversely, events at the level of the fast–evolving psychopathology network (e.g. a depressive episode) can influence the slow–evolving personality variables (e.g. by increasing feelings of worthlessness). We apply the theory to neuroticism and major depressive disorder. Through simulations, we show that the model can accommodate important phenomena, such as the strong relation between neuroticism and depression and individual differences in the change of neuroticism levels and development of depression over time. The results of the simulation are implemented in an online, interactive simulation tool. Implications for research into the relationship between personality and psychopathology are discussed. © 2020 The Authors. European Journal of Personality published by John Wiley & Sons Ltd on behalf of European Association of Personality Psychology

ARCFIRE: Experimentation with the Recursive InterNetwork Architecture

European funded research into the Recursive Inter-Network Architecture (RINA) started with IRATI, which developed an initial prototype implementation for OS/Linux. IRATI was quickly succeeded by the PRISTINE project, which developed different policies, each tailored to specific use cases. Both projects were development-driven, where most experimentation was limited to unit testing and smaller scale integration testing. In order to assess the viability of RINA as an alternative to current network technologies, larger scale experimental deployments are needed. The opportunity arose for a project that shifted focus from development towards experimentation, leveraging Europe’s investment in Future Internet Research and Experimentation (FIRE+) infrastructures. The ARCFIRE project took this next step, developing a user-friendly framework for automating RINA experiments. This paper reports and discusses the implications of the experimental results achieved by the ARCFIRE project, using open source RINA implementations deployed on FIRE+ Testbeds. Experiments analyze the properties of RINA relevant to fast network recovery, network renumbering, Quality of Service, distributed mobility management, and network management. Results highlight RINA properties that can greatly simplify the deployment and management of real-world networks; hence, the next steps should be focused on addressing very specific use cases with complete network RINA-based networking solutions that can be transferred to the market.