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UC Merced Proceedings of the Annual Meeting of the Cognitive Science Society Title A General Purpose Architecture for Building Spiking Neuron Models of Biological Cognition Permalink

Chris Eliasmith, Terrence Stewart
2013 Proceedings of the Annual Meeting of the Cognitive Science Society   unpublished
This system is a general-purpose, biologically constrained, and neurally plausible cognitive architecture implemented using spiking neurons, and is the core foundation of our large-scale brain simulation  ...  By combining these models with a general method for cognitive control (the cortex-basal ganglia-thalamus loop), we have created the beginnings of a novel biologically realistic cognitive architecture.  ... 

Artificial Cognitive Systems: From VLSI Networks of Spiking Neurons to Neuromorphic Cognition

Giacomo Indiveri, Elisabetta Chicca, Rodney J. Douglas
2009 Cognitive Computation  
Specifically, we show how VLSI networks of spiking neurons with spike-based plasticity mechanisms and soft winner-take-all architectures represent important building blocks useful for implementing artificial  ...  Neuromorphic engineering (NE) is an emerging research field that has been attempting to identify neural types of computational principles, by implementing biophysically realistic models of neural systems  ...  Acknowledgments This work was supported by the DAISY (FP6-2005-015803) EU Grant, by the Swiss National Science Foundation under Grant PMPD2-110298/1, and by the Swiss Federal Institute of Technology Zurich  ... 
doi:10.1007/s12559-008-9003-6 fatcat:gzrod52nxzgqzdifiedgqffwoi

Neuromorphic Cognition [chapter]

Giacomo Indiveri, Rodney Douglas
2015 Encyclopedia of Computational Neuroscience  
Detailed Description Digital computers provide prodigious computational power and memory for the simulation of models of cognition.  ...  and architectural constraints are based on those of the biological nervous systems  ...  cognition engineering workshop ( for fruitful discussions on neuromorphic cognition.  ... 
doi:10.1007/978-1-4614-6675-8_113 fatcat:rxxwd7jwyvb3nge53e5lkcrifu

Neuromorphic Cognition [chapter]

Giacomo Indiveri, Dr. Rodney Douglas
2014 Encyclopedia of Computational Neuroscience  
Detailed Description Digital computers provide prodigious computational power and memory for the simulation of models of cognition.  ...  and architectural constraints are based on those of the biological nervous systems  ...  cognition engineering workshop ( for fruitful discussions on neuromorphic cognition.  ... 
doi:10.1007/978-1-4614-7320-6_113-1 fatcat:iifw447nnjcjxbnk74lszqmtgu

BrainCog: A Spiking Neural Network based Brain-inspired Cognitive Intelligence Engine for Brain-inspired AI and Brain Simulation [article]

Yi Zeng, Dongcheng Zhao, Feifei Zhao, Guobin Shen, Yiting Dong, Enmeng Lu, Qian Zhang, Yinqian Sun, Qian Liang, Yuxuan Zhao, Zhuoya Zhao, Hongjian Fang (+7 others)
2022 arXiv   pre-print
BrainCog incorporates different types of spiking neuron models, learning rules, brain areas, etc., as essential modules provided by the platform.  ...  In this paper, we present the Brain-inspired Cognitive Intelligence Engine (BrainCog) for creating brain-inspired AI and brain simulation models.  ...  to build true and general purpose AI for human and ecology good.  ... 
arXiv:2207.08533v1 fatcat:pb2ah43qlra7zmvhr4no27ovcu

Large-Scale Synthesis of Functional Spiking Neural Circuits

Terrence C. Stewart, Chris Eliasmith
2014 Proceedings of the IEEE  
This paper reviews a system capable of performing multiple cognitive functions using a combination of biologically plausible spiking neurons, and an architecture that mimics the organization, function,  ...  The resulting NEF/SPA/Nengo combination is a general tool set for both evaluating hypotheses about how the brain works, and for building systems that compute particular functions using neuron-like components  ...  The NEF thus provides a generic framework for implementing a very large class of functions in networks of biologically plausible spiking neurons.  ... 
doi:10.1109/jproc.2014.2306061 fatcat:bclajcxbmzgp5bqeageaek5leu

Cognitive computing building block: A versatile and efficient digital neuron model for neurosynaptic cores

Andrew S. Cassidy, Paul Merolla, John V. Arthur, Steve K. Esser, Bryan Jackson, Rodrigo Alvarez-Icaza, Pallab Datta, Jun Sawada, Theodore M. Wong, Vitaly Feldman, Arnon Amir, Daniel Ben-Dayan Rubin (+4 others)
2013 The 2013 International Joint Conference on Neural Networks (IJCNN)  
Although designed with cognitive algorithms and applications in mind, serendipitously, the neuron model can qualitatively replicate the 20 biologically-relevant behaviors of a dynamical neuron model.  ...  The model supports a wide variety of computational functions and neural codes. We capture 50+ neuron behaviors in a library for hierarchical composition of complex computations and behaviors.  ...  We would like to thank David Peyton for his expert assistance revising this manuscript.  ... 
doi:10.1109/ijcnn.2013.6707077 dblp:conf/ijcnn/CassidyMAEJADSWFARAMRM13 fatcat:3q3cp665rjgz7mupmlkenxdtzi

Why build a virtual brain? Large-scale neural simulations as jump start for cognitive computing

Matteo Colombo
2016 Journal of experimental and theoretical artificial intelligence (Print)  
I am also grateful to lasha Abzianidze, luigi Acerbi, one anonymous referee and to the editor of Jetai, Eric Dietrich, for their constructive criticisms and helpful suggestions.  ...  Acknowledgement This was work supported by the Deutsche Forschungsgemeinschaft (DFG) as part of the priority program ''New Frameworks of Rationality'' ([SPP 1516]).  ...  For many integrate-and-fire neurons models, the model fits nicely with an event-driven simulation, whereby all operations in the simulation are driven by neural spike events, which is generally well suited  ... 
doi:10.1080/0952813x.2016.1148076 fatcat:rvycy7bbrfea5m6db5uugprl2e

NeuCube EvoSpike Architecture for Spatio-temporal Modelling and Pattern Recognition of Brain Signals [chapter]

Nikola Kasabov
2012 Lecture Notes in Computer Science  
This paper proposes a new evolving spiking model called NeuCube as part of the EvoSpike project, especially for modeling brain data.  ...  Yet, there are no computational models to integrate all these different types of data into a single model to help understand brain processes and for a better brain signal pattern recognition.  ...  to build a NeuCube model in the following way: Training of a NeuCube Architecture 1.  ... 
doi:10.1007/978-3-642-33212-8_21 fatcat:bvz7ic36wrb5ncikqae3k653qu

Frontiers in Neuromorphic Engineering

Giacomo Indiveri, Timothy K. Horiuchi
2011 Frontiers in Neuroscience  
These systems typically comprise one or more neuromorphic sensors, interfaced to general-purpose neural network chips using spiking silicon neurons and dynamic synapses.  ...  By providing real-time spiking implementations of core neural circuits, neuromorphic engineering will play an important role in the development and fielding of biologically relevant working models of cognition  ... 
doi:10.3389/fnins.2011.00118 pmid:22013408 pmcid:PMC3189639 fatcat:jb5tzvih6zg23ehiek2xabfdbu

Memory and Information Processing in Neuromorphic Systems

Giacomo Indiveri, Shih-Chii Liu
2015 Proceedings of the IEEE  
more biological-like models of neurons and synapses together with a suite of adaptation and learning mechanisms analogous to the ones found in biological nervous systems.  ...  In this paper we present a survey of brain-inspired processor architectures that support models of cortical networks and deep neural networks.  ...  and general purpose.  ... 
doi:10.1109/jproc.2015.2444094 fatcat:enmuv4qr6bdktlh7t3rfwfj27i

Large-scale cognitive model design using the Nengo neural simulator

Sugandha Sharma, Sean Aubin, Chris Eliasmith
2016 Biologically Inspired Cognitive Architectures  
Nengo has recently been used to build Spaun, a stateof-the-art, large-scale neural model that performs motor, perceptual, and cognitive functions with spiking neurons .  ...  The purpose of this tutorial is to simultaneously introduce the reader to the SPA and its implementation in Nengo.  ...  We have recently suggested a general architecture that aids in structuring such models in a biologically constrained manner (Eliasmith, 2013) .  ... 
doi:10.1016/j.bica.2016.05.001 fatcat:nrhliu4ow5fzhff6lunmbrub3e

The use and abuse of large-scale brain models

Chris Eliasmith, Oliver Trujillo
2014 Current Opinion in Neurobiology  
In addition to discussing challenges involved with building large neural models, we identify several expected benefits of pursuing such a research program.  ...  The second is that models, and more importantly their underlying methods, should provide mechanisms for varying the level of simulated detail.  ...  But, is making such a connection really the purpose of such models? And, if so, what does that mean for the role of biological realism? Why build large-scale brain models?  ... 
doi:10.1016/j.conb.2013.09.009 pmid:24709593 fatcat:uuth5tbxqbej3jljfz6j7cej2e

Toward Reflective Spiking Neural Networks Exploiting Memristive Devices

Valeri A. Makarov, Sergey A. Lobov, Sergey Shchanikov, Alexey Mikhaylov, Viktor B. Kazantsev
2022 Frontiers in Computational Neuroscience  
The design of modern convolutional artificial neural networks (ANNs) composed of formal neurons copies the architecture of the visual cortex.  ...  Then, memristive SNNs can diverge from the development of ANNs and build their niche, cognitive, or reflective computations.  ...  Single High-Dimensional Neurons in Deep Spiking Neural Network Layers May Provide Cognition Remarkably, a simple generic model offers a clear-cut mathematical explanation of a wealth of empirical evidence  ... 
doi:10.3389/fncom.2022.859874 pmid:35782090 pmcid:PMC9243340 fatcat:ulpwch56gfhejbvz6etjbw2csi

A cognitive architecture for the implementation of emotions in computing systems

Jordi Vallverdú, Max Talanov, Salvatore Distefano, Manuel Mazzara, Alexander Tchitchigin, Ildar Nurgaliev
2016 Biologically Inspired Cognitive Architectures  
In this paper we present a new neurobiologically-inspired affective cognitive architecture: NEUCOGAR (NEUromodulating COGnitive ARchitecture).  ...  As basis of the modeling we use and extend the L\"ovheim Cube of Emotion with parameters of the Von Neumann architecture.  ...  Acknowledgments Partial support for this research was received by the Spanish Government's DGICYT research project: FFI2011-23238, "Innovation in scientific practice: cognitive approaches and their philosophical  ... 
doi:10.1016/j.bica.2015.11.002 fatcat:7s332cessrf7rfuofl6csnsoi4
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