IEEE Organizations related to Synaptogenesis

Back to Top

No organizations are currently tagged "Synaptogenesis"



Conferences related to Synaptogenesis

Back to Top

2018 International Joint Conference on Neural Networks (IJCNN)

IJCNN is the flagship conference of the International Neural Network Society and the IEEE ComputationalIntelligence Society. It covers a wide range of topics in the field of neural networks, from biological neuralnetwork modeling to artificial neural computation.


2017 NASA/ESA Conference on Adaptive Hardware and Systems (AHS)

The purpose of the conference is to bring together leading researchers from the adaptive hardware and systems community to exchange experiences and share new ideas in the field. While the focus of this conference is on communications and space applications, we welcomeoriginal contributions in other application areas such as consumer, medical, defense and security, as the techniques employed in these areas can be disseminated across the board.

  • 2015 NASA/ESA Conference on Adaptive Hardware and Systems (AHS)

    The purpose of the conference is to bring together leading researchers from the adaptive hardware and systems community to exchange experiences and share new ideas in the field. While the focus of this conference is on communications and space applications, we welcome original contributions in other application areas such as consumer, medical, defence and security, as the techniques employed in these areas can be disseminated across the board. Adaptation reflects the capability of a system to maintain or improve its performance in the context of internal or external changes, such as uncertainty and variation during fabrication, faults and degradation in the field, changes in the operational environment, incidental or intentional interference, different users and preferences, modifications of standards and requirements, or trade-off.

  • 2014 NASA/ESA Conference on Adaptive Hardware and Systems (AHS)

    The purpose of the conference is to bring together leading researchers from the adaptive hardware and systems community to exchange experiences and share new ideas in the field. We welcome original contributions in the areas of hardware and software adaptation at different system levels, including, but not limited to, tools and algorithms for adaptive system design, novel applications of adaptive hardware and systems, and enabling technologies for such systems. We also welcome novel contributions in the areas of adaptive transmission for telecommunications, data compression techniques, software/hardware architectures for unmanned autonomous vehicles, etc.While the focus of this conference is on communications and space applications, we welcome original contributions in other application areas such as consumer, medical, defence and security, as the techniques employed can be disseminated across the board. We also welcome papers describing significant applications of adaptive hardware

  • 2013 NASA/ESA Conference on Adaptive Hardware and Systems (AHS)

    We welcome original contributions in the areas of hardware and software adaptation at different system levels, including, but not limited to, tools and algorithms for adaptive system design (e.g. adaptation-aware compilers), novel applications of adaptive hardware and systems (e.g. intelligent agent machines), and enabling technologies for such systems (e.g. instrumentation platforms, reconfigurable and multi-core architectures). We also welcome novel contributions in the areas of adaptive transmission for telecommunications (e.g. aware of power limitations, changing environment, and interferences), data compression techniques (e.g. new image compression techniques for space applications), software/hardware architectures for unmanned autonomous vehicles (e.g. adapting to extreme environments and mission unknowns), etc.

  • 2012 NASA/ESA Conference on Adaptive Hardware and Systems (AHS)

    The conference scope covers the areas of hardware and software adaptation at different system levels, including novel tools and algorithms for adaptive system design (e.g. adaptation-aware compilers), novel applications of adaptive hardware and systems (e.g. intelligent agent machines), and novel enabling hardware technologies for such systems (e.g. instrumentation platforms, novel reconfigurable and multi-core architectures). We also welcome novel contributions in the areas of adaptive data transmission.

  • 2011 NASA/ESA Conference on Adaptive Hardware and Systems (AHS)

    The conference scope covers the areas of hardware and software adaptation at different system levels, including novel tools and algorithms for adaptive system design (e.g. adaptation-aware compilers), novel applications of adaptive hardware and systems (e.g. intelligent agent machines), and novel enabling hardware technologies for such systems (e.g. instrumentation platforms, novel reconfigurable and multi-core architectures). We also welcome novel contributions in the areas of adaptive data transmission

  • 2010 NASA/ESA Conference on Adaptive Hardware and Systems (AHS)

    The purpose of the conference is to bring together leading researchers from the adaptive hardware and systems community to exchange experiences and share new ideas in the field. Adaptation reflects the capability of a system to maintain or improve its performance in the context of internal or external changes, such as uncertainties and variations during fabrication, faults and degradations, modifications in the operational environment, incidental or intentional interference, different users and preferences,

  • 2009 NASA/ESA Conference on Adaptive Hardware and Systems (AHS)

    Adaptation reflects the capability of a system to maintain or improve its performance in the context of internal or external changes, such as uncertainties and variations during fabrication, faults and degradations, modifications in the operational environment, incidental or intentional interference, different users and preferences, modifications of standards and requirements, trade-offs between performance and resources. Adaptation at hardware levels increases the system capabilities beyond what i

  • 2008 NASA/ESA Conference on Adaptive Hardware and Systems (AHS)

    The purpose of the conference is to bring together leading researchers from the adaptive hardware and systems community to exchange experiences and share new ideas in the field. The conference expands the topics addressed by the precursor series of NASA/DoD Conference on Evolvable Hardware, held between 1999 and 2005. With a broader scope including a variety of hardware and system adaptation methods and targeting more industry participation, started with the AHS 2006 conference held in Istanbul, Turkey, Jun


2012 Joint 6th Intl. Conference on Soft Computing and Intelligent Systems (SCIS) and 13th Intl. Symposium on Advanced Intelligent Systems (ISIS)

We strive to foster an open and lively scientific forum by bringing together researchers, engineers and practitioners with diversified backgrounds to discuss and disseminate the latest state-of-the-art achievements.


2006 International Conference on Microtechnologies in Medicine and Biology



Periodicals related to Synaptogenesis

Back to Top

No periodicals are currently tagged "Synaptogenesis"


Most published Xplore authors for Synaptogenesis

Back to Top

Xplore Articles related to Synaptogenesis

Back to Top

Adaptive synaptogenesis constructs networks which allocate network resources by category frequency

Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94), 1994

Demonstrates the effectiveness of two adaptive processes in constructing simple, feedforward networks which allocate the resources of the output layer based on the frequencies of the categories that compose the input environment. Specifically, the adaptive processes build networks which allocate more output layer resources to categories that appear more frequently in the input. In turn, less frequently appearing input categories ...


Synaptogenesis based bio-inspired NoC fault tolerant interconnects

2013 IEEE International Conference on Control System, Computing and Engineering, 2013

Network on Chip (NoC) is a communication framework for interconnection of processing element (PE's). The excessive and parallel communication requirements of heterogeneous PE's in NoC have made the communication structure very complex. The size of the devices are scaled down to support the complexity but the size of interconnects remains the same. To support the complexity of NoC many fault ...


Controlling information flow and energy use via adaptive synaptogenesis

2016 Annual Conference on Information Science and Systems (CISS), 2016

The adaptive synaptogenesis algorithm is a mathematically defined, random process that, in its present form, creates a feedforward network of excitatory synapses without supervision. The algorithm is fully local and consists of three separate modification processes: random synapse formation, modification of an existing synapse's strength (both strengthening and weakening), and shedding of very weak synapses. The algorithm is shown to ...


Adaptive spiking neural networks with Hodgkin-Huxley neurons and Hebbian learning

The 2011 International Joint Conference on Neural Networks, 2011

This paper will describe a numerical approach to simulating adaptive biologically-plausible spiking neural networks, with the primary application being simulating the early stages of mammalian vision. These are time dependent neural networks with a realistic Hodgkin-Huxley (HH) [1] model for the neurons. The HH model uses four nonlinear, coupled ordinary differential equations for each neuron. In addition, the learning used ...


Lab-on-a-chip devices for cell biology studies

2005 3rd IEEE/EMBS Special Topic Conference on Microtechnology in Medicine and Biology, 2005

Microtechnology offers the attractive possibility of modulating the microenvironment of single cells and, for the same price, obtain data at high throughput for a small cost. Microfluidic or "Lab on a Chip" devices, in particular, promise to play a key role for several reasons: 1) the dimensions of microchannels can be comparable to or smaller than a single cell; 2) ...


More Xplore Articles

Educational Resources on Synaptogenesis

Back to Top

IEEE.tv Videos

No IEEE.tv Videos are currently tagged "Synaptogenesis"

IEEE-USA E-Books

  • Adaptive synaptogenesis constructs networks which allocate network resources by category frequency

    Demonstrates the effectiveness of two adaptive processes in constructing simple, feedforward networks which allocate the resources of the output layer based on the frequencies of the categories that compose the input environment. Specifically, the adaptive processes build networks which allocate more output layer resources to categories that appear more frequently in the input. In turn, less frequently appearing input categories are allocated fewer output resources. The two adaptive processes, synaptogenesis and associative modification, build a network connectivity in initially unconnected networks. The first process, synaptogenesis, creates new synaptic connections; the second process, associative synaptic modification, modifies the strength of existing synaptic connections. Because these processes operate in a unsupervised fashion using only information available locally at the neurons and synapses, they provide a biologically plausible model for the allocation of neural resources.<<ETX>>

  • Synaptogenesis based bio-inspired NoC fault tolerant interconnects

    Network on Chip (NoC) is a communication framework for interconnection of processing element (PE's). The excessive and parallel communication requirements of heterogeneous PE's in NoC have made the communication structure very complex. The size of the devices are scaled down to support the complexity but the size of interconnects remains the same. To support the complexity of NoC many fault tolerant routing techniques have been proposed to cope with the faulty nodes and interconnects which occur during the communication. All the routing algorithms lack the adaptiveness, robustness and they also have the drawbacks of congestion, delayed communication and latency issues. In this paper a synaptogenesis bases bio-inspired algorithm is proposed for NoC. This algorithm is fault tolerant as it adapts the mechanism of biological brain. The results show that the bio-inspired algorithm quickly recovers from the fault and it is robust and fault tolerant. The average packet network latency was increased by 11.64%, average bandwidth was reduced by 0.07% and throughput is drop to 43.30% during the network recovery from faults. While comparing with literature technique the average throughput and accepted traffic is increased by 76.92%.

  • Controlling information flow and energy use via adaptive synaptogenesis

    The adaptive synaptogenesis algorithm is a mathematically defined, random process that, in its present form, creates a feedforward network of excitatory synapses without supervision. The algorithm is fully local and consists of three separate modification processes: random synapse formation, modification of an existing synapse's strength (both strengthening and weakening), and shedding of very weak synapses. The algorithm is shown to have desirable stability properties; further, the algorithm can be parameterized to control the synaptic energy use by a neuron and to control the net information received by a neuron. In addition to the fundamental mathematics on which the algorithm is based, the interaction of parameter settings with characterized random inputs are described. Finally, specific extensions of the algorithm are suggested.

  • Adaptive spiking neural networks with Hodgkin-Huxley neurons and Hebbian learning

    This paper will describe a numerical approach to simulating adaptive biologically-plausible spiking neural networks, with the primary application being simulating the early stages of mammalian vision. These are time dependent neural networks with a realistic Hodgkin-Huxley (HH) [1] model for the neurons. The HH model uses four nonlinear, coupled ordinary differential equations for each neuron. In addition, the learning used here is biologically plausible as well, being a Hebbian approach based on spike timing dependent plasticity (STDP) [2]. To make the approach very general and flexible, neurogenesis and synaptogenesis have been implemented, which allows the code to automatically add or remove neurons (or synapses) as required. Traditional rate-based and spiking neural networks have been shown to be very effective for some tasks, but they have problems with long term learning and “catastrophic forgetting.” Typically, once a network is trained to perform some task, it is difficult to adapt it to new applications. While adaptive rate-based NN's have been developed, our approach is one of the few that uses a biologically plausible system. To do this properly, one can mimic processes that occur in the human brain. To be effective, however, this must be accomplished while maintaining the current memories. In this paper we will describe a new computational approach that can continually learn and grow. Neurons and synapses can be automatically added and removed from the simulation while it runs. The learning algorithm [3] uses a combination of homeostasis of synapse weights, spike timing, and stochastic forgetting to achieve stable and efficient learning. The approach is not only adaptable, but it is also scalable to very large systems (billions of neurons). Also, it has the capability to remove synapses which have very low strength, thus saving memory. There are several issues when implementing neurogenesis and synaptogenesis in a spiking code. When several synapses die, it may lead to a neuron which has no synapses and thus requires its removal. Conversely, a neurons death may require updating of synaptic information of all the neurons it was connected to. More importantly, rules need to be developed which help determine when the network should be modified. These issues and efficient ways to address them will be discussed. In addition, the computer performance and memory requirements of several neuron models (integrate and fire, Izkehvich, and Hodgkin-Huxley) will be discussed [4]. The software is written in C++ and is efficient and scalable, it also requires minimal memory per neuron and synapse. A 2.4 GHz MacBook laptop ran 100 million synapses (1 million neurons) for 0.1 simulated seconds (100,000 timesteps) in 5.2 hours (a mouse has roughly 10 million neurons and 81 billion synapses [5]). This case required only 200 MBytes of memory.

  • Lab-on-a-chip devices for cell biology studies

    Microtechnology offers the attractive possibility of modulating the microenvironment of single cells and, for the same price, obtain data at high throughput for a small cost. Microfluidic or "Lab on a Chip" devices, in particular, promise to play a key role for several reasons: 1) the dimensions of microchannels can be comparable to or smaller than a single cell; 2) the unique physicochemical behavior of liquids confined to microenvironments enables new strategies for delivering compounds to cells on a subcellular level; 3) the devices consume small quantities of precious/hazardous reagents (thus reducing cost of operation/disposal); and 4) the can be mass-produced in low-cost, portable units. Not surprisingly, in recent years there has been an eruption of microfluidic implementations of a variety of traditional bioanalysis techniques. I will review the latest efforts of our laboratory in the development of cell-based microdevices for cell biology studies, such as neuromuscular synaptogenesis, axon guidance, and chemotaxis.

  • An adaptive spiking neural network with Hebbian learning

    This paper will describe a numerical approach to simulating biologically- plausible spiking neural networks. These are time dependent neural networks with realistic models for the neurons (Hodgkin-Huxley). In addition the learning is biologically plausible as well, being a Hebbian approach based on spike timing dependent plasticity (STDP). To make the approach very general and flexible, neurogenesis and synaptogenesis have been implemented, which allows the code to automatically add or remove neurons (or synapses) as required.

  • Functional connections between avian and mammalian neurons

    The genetical controls are critical for constructing specific circuit in a brain, however, also a distant relationship likes a mammal and a bird, the fundamental structure and functions of neurons are preserved. Using Ca2+imaging of a mixed culture of rat and chick neurons, we elucidated whether the functional connections are formed between neurons from relatively distant species in this study. Periodic and synchronized Ca2+transients were often observed. Some synchronizations were not strict, suggesting that the bursting activity was loosely transmitted each other. A coculture of rat and chick neuronal cells was possible and some of neurons from distinct species made functional connections, which can be utilized to complementation of damaged neuronal circuit. The mixed circuit of cultured neurons from distinct species is the interesting testing platform for elucidating conditions required for a synaptogenesis and activity of a circuit of neurons from mixed species.

  • Long-term multielectrode registration of neuronal firing activity from rat cerebral cortex tissue in-vitro

    Activity-dependent processes are involved in neurite outgrowth and synaptogenesis. The authors expect that during neural network formation neuronal morphogenesis and synaptic connectivity are reciprocally dependent on the emerging bioelectric activity in the network. The authors want to study whether and how bioelectric activity is involved in the formation of network structure. A multielectrode recording facility has been constructed for the long-term registration of action potentials of individual neurons during network development in both organotypic and dissociated rat cerebral cortex tissue cultures. Long-term recordings of action potentials with good signal- to-noise ratios have been obtained. Experiments to correlate these activity levels with quantitative data on neuronal morphological development are in progress. Uncorrelated periodic fluctuations at a time scale of about ten minutes have been observed.

  • Bio-inspired NoC fault tolerant techniques

    The incorporation of processing elements which include processor cores, memories, configurable components and DSP cores on Network on Chip (NoC) have made the communication structure of NoC very complex. To support the complexity of NoC, the physical device sizes are scaled down. However, the interconnects are not scaled at the same rate as the device. Interconnects have contributed to faults, system delay and high power consumptions. Interconnects of NoC are more vulnerable to faults. Many fault tolerant routing techniques have been proposed but they still have the energy, power, congestion problems and they lack the adaptiveness and robustness. In this work, two novel bio-inspired NoC techniques are analyzed. The bio-inspired mechanism of “synaptogenesis” and “sprouting” is adopted in the NoC algorithm and architecture. With the help of this the algorithm is robust and NoC is fault tolerant. In sprouting algorithm, the average throughput and average packet latency was increased by 8.56% and 4.65% respectively while average bandwidth was efficiently utilized by 0.23% as compared to synaptogenesis algorithm. The bio-inspired algorithms improved the average throughput and accepted traffic by 72.12% as compared to the literature technique.

  • Dynamic Routing on the Ubichip: Toward Synaptogenetic Neural Networks

    The ubichip is a bio-inspired reconfigurable circuit developed in the framework of the European project Perplexus. The <i>ubichip</i> offers special reconfigurability capabilities, being the dynamic routing one of them. This paper describes how to exploit the dynamic routing capabilities of the <i>ubichip</i> in order to implement synaptogenetic neural networks. We present two techniques for dynamically generating the network topology, we describe their implementation in the <i>ubichip</i>, and we analyse the resulting topology. This work constitutes a first step toward neural circuits exhibiting more realistic neural plasticity features.



Standards related to Synaptogenesis

Back to Top

No standards are currently tagged "Synaptogenesis"


Jobs related to Synaptogenesis

Back to Top