[ { "id": "authors:d1nay-9yz85", "collection": "authors", "collection_id": "d1nay-9yz85", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20130107-174057868", "type": "book_section", "title": "The GENESIS Simulation System", "book_title": "The Handbook of Brain Theory and Neural Networks", "author": [ { "family_name": "Bower", "given_name": "James M.", "clpid": "Bower-J-M" }, { "family_name": "Beeman", "given_name": "David", "clpid": "Beeman-D" }, { "family_name": "Hucka", "given_name": "Michael", "orcid": "0000-0001-9105-5960", "clpid": "Hucka-M" } ], "contributor": [ { "family_name": "Arbib", "given_name": "Michael A.", "clpid": "Arbib-M-A" } ], "abstract": "GENESIS (the GEneral NEural Simulation System) was developed\nas a research tool to provide a standard and flexible means for\nconstructing structurally realistic models of biological neural systems.\n\"Structurally realistic\" simulations are computer-based implementations\nof models whose primary objective is to capture\nwhat is known of the anatomical structure and physiological characteristics\nof the neural system of interest. The GENESIS project\nis based on the belief that progress in understanding structure-function\nrelationships in the nervous system specifically, or in biology\nin general, will increasingly require the development and use\nof structurally realistic models (Bower, 1995). It is our view that\nonly through this type of modeling will general principles of neural\nor biological function emerge.", "isbn": "9780262267267", "publisher": "MIT Press", "place_of_publication": "Cambridge, MA", "publication_date": "2003", "pages": "475-478" }, { "id": "authors:9jt9j-c8b35", "collection": "authors", "collection_id": "9jt9j-c8b35", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20130107-174458859", "type": "book_section", "title": "The Modeler's Workspace: Making model-based studies of the nervous system more accessible", "book_title": "Computational Neuroanatomy: Principles and Methods", "author": [ { "family_name": "Hucka", "given_name": "Michael", "orcid": "0000-0001-9105-5960", "clpid": "Hucka-M" }, { "family_name": "Shankar", "given_name": "Kavita", "clpid": "Shankar-K" }, { "family_name": "Beeman", "given_name": "David", "clpid": "Beeman-D" }, { "family_name": "Bower", "given_name": "James M.", "clpid": "Bower-J-M" } ], "contributor": [ { "family_name": "Ascoli", "given_name": "Giorgio A.", "clpid": "Ascoli-G-A" } ], "abstract": "A realistic neuronal model represents a modeler's understanding of the structure and\nfunction of a part of the nervous system. The increasing number of such models represents a significant accumulation of knowledge about the structural and functional organization of nervous systems. However, locating appropriate models and interpreting them becomes\nincreasingly more difficult as the number of online model and experimental databases grows. The central motivation for the Modeler's Workspace project is to address these problems.\nThe Modeler's Workspace is a collection of software tools being created to enable users to interact with databases of models and data. It will provide facilities for: searching multiple remote databases for model components based on various criteria; visualizing the characteristics\nof the components retrieved; creating new components, either from scratch or derived from existing models; combining components into new models; linking models to experimental data as well as online publications; and interacting with simulation packages such as GENESIS to simulate the new constructs. It is being written in Java for portability and extensibility. It is modular in design and uses pluggable components. To increase the probability\nthat the Modeler's Workspace will be compatible with future databases and tools, we arc using the XML, the eXtensible Markup Language, as the interchange format for\ncommunicating with databases.", "isbn": "9781588290007", "publisher": "Humana Press", "place_of_publication": "Totowa, NJ", "publication_date": "2002", "pages": "83-103" }, { "id": "authors:h9h65-71q91", "collection": "authors", "collection_id": "h9h65-71q91", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20160107-162031185", "type": "book_section", "title": "Computational Efficiency: A Common Organizing Principle for Parallel Computer Maps and Brain Maps?", "book_title": "Advances in Neural Information Processing Systems 2 (NIPS 1989)", "author": [ { "family_name": "Nelson", "given_name": "Mark E.", "clpid": "Nelson-M-E" }, { "family_name": "Bower", "given_name": "James M.", "clpid": "Bower-J-M" } ], "contributor": [ { "family_name": "Touretzky", "given_name": "David S.", "clpid": "Touretzky-D-S" } ], "abstract": "It is well-known that neural responses in particular brain regions\nare spatially organized, but no general principles have been developed\nthat relate the structure of a brain map to the nature of\nthe associated computation. On parallel computers, maps of a sort\nquite similar to brain maps arise when a computation is distributed\nacross multiple processors. In this paper we will discuss the relationship\nbetween maps and computations on these computers and\nsuggest how similar considerations might also apply to maps in the\nbrain.", "isbn": "1-55860-100-7", "publisher": "Morgan Kaufmann", "place_of_publication": "San Mateo, CA", "publication_date": "1990", "pages": "60-67" }, { "id": "authors:1z0at-3vj04", "collection": "authors", "collection_id": "1z0at-3vj04", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20160107-161336333", "type": "book_section", "title": "A Computer Modeling Approach to Understanding the Inferior Olive and Its Relationships to the Cerebellar Cortex in Rats", "book_title": "Advances in Neural Information Processing Systems 2 (NIPS 1989)", "author": [ { "family_name": "Lee", "given_name": "Maurice", "clpid": "Lee-Maurice" }, { "family_name": "Bower", "given_name": "James M.", "clpid": "Bower-J-M" } ], "contributor": [ { "family_name": "Touretzky", "given_name": "David S.", "clpid": "Touretzky-D-S" } ], "abstract": "This paper presents the results of a simulation of the spatial relationship\nbetween the inferior olivary nucleus and folium crus IIA of the lateral\nhemisphere of the rat cerebellum. The principal objective of this\nmodeling effort was to resolve an apparent conflict between a proposed\nzonal organization of olivary projections to cerebellar cortex suggested\nby anatomical tract-tracing experiments (Brodal & Kawamura 1980;\nCampbell & Armstrong 1983) and a more patchy organization apparent\nwith physiological mapping (Robertson 1987). The results suggest that\nseveral unique features of the olivocerebellar circuit may contribute to\nthe appearance of zonal organization using anatomical techniques, but\nthat the detailed patterns of patchy tactile projections seen with\nphysiological techniques are a more accurate representation of the\nafferent organization of this region of cortex.", "isbn": "1-55860-100-7", "publisher": "Morgan Kaufmann", "place_of_publication": "San Mateo, CA", "publication_date": "1990", "pages": "117-124" }, { "id": "authors:wdt70-jf744", "collection": "authors", "collection_id": "wdt70-jf744", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20160107-162410256", "type": "book_section", "title": "Computer Simulation of Oscillatory Behavior in Cerebral Cortical Networks", "book_title": "Advances in Neural Information Processing Systems 2 (NIPS 1989)", "author": [ { "family_name": "Wilson", "given_name": "Matthew A.", "clpid": "Wilson-M-A" }, { "family_name": "Bower", "given_name": "James M.", "clpid": "Bower-J-M" } ], "contributor": [ { "family_name": "Touretzky", "given_name": "David S.", "clpid": "Touretzky-D-S" } ], "abstract": "It has been known for many years that specific regions of the working\ncerebral cortex display periodic variations in correlated cellular\nactivity. While the olfactory system has been the focus of much of\nthis work, similar behavior has recently been observed in primary\nvisual cortex. We have developed models of both the olfactory\nand visual cortex which replicate the observed oscillatory properties\nof these networks. Using these models we have examined the\ndependence of oscillatory behavior on single cell properties and network\narchitectures. We discuss the idea that the oscillatory events\nrecorded from cerebral cortex may be intrinsic to the architecture\nof cerebral cortex as a whole, and that these rhythmic patterns\nmay be important in coordinating neuronal activity during sensory\nprocessing.", "isbn": "1-55860-100-7", "publisher": "Morgan Kaufmann", "place_of_publication": "San Mateo, CA", "publication_date": "1990", "pages": "84-91" }, { "id": "authors:jqrbb-m6e44", "collection": "authors", "collection_id": "jqrbb-m6e44", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20141212-145236780", "type": "book_section", "title": "Modeling Small Oscillating Biological Networks in Analog VLSI", "book_title": "Advances in Neural Information Processing Systems", "author": [ { "family_name": "Ryckebusch", "given_name": "Sylvie", "clpid": "Ryckebusch-S" }, { "family_name": "Bower", "given_name": "James M.", "clpid": "Bower-J-M" }, { "family_name": "Mead", "given_name": "Carver", "orcid": "0000-0003-4051-0462", "clpid": "Mead-C-A" } ], "contributor": [ { "family_name": "Touretzky", "given_name": "D. S.", "clpid": "Touretzky-D-S" } ], "abstract": "We have used analog VLSI technology to model a class of small oscillating\nbiological neural circuits known as central pattern generators\n(CPG). These circuits generate rhythmic patterns of activity\nwhich drive locomotor behaviour in the animal. We have designed,\nfabricated, and tested a model neuron circuit which relies on many\nof the same mechanisms as a biological central pattern generator\nneuron, such as delays and internal feedback. We show that this\nneuron can be used to build several small circuits based on known\nbiological CPG circuits, and that these circuits produce patterns of\noutput which are very similar to the observed biological patterns.", "isbn": "1558600159", "publisher": "Morgan Kaufmann Publishers", "place_of_publication": "San Mateo, CA", "publication_date": "1989", "pages": "384-393" }, { "id": "authors:ddw6a-3ta29", "collection": "authors", "collection_id": "ddw6a-3ta29", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20160107-160453795", "type": "book_section", "title": "Neural Control of Sensory Acquisition: The Vestibulo-Ocular Reflex", "book_title": "Advances in Neural Information Processing Systems 1 (NIPS 1988)", "author": [ { "family_name": "Paulini", "given_name": "Michael G.", "clpid": "Paulini-M-G" }, { "family_name": "Nelson", "given_name": "Mark E.", "clpid": "Nelson-M-E" }, { "family_name": "Bower", "given_name": "James M.", "clpid": "Bower-J-M" } ], "contributor": [ { "family_name": "Touretzky", "given_name": "David S.", "clpid": "Touretzky-D-S" } ], "abstract": "We present a new hypothesis that the cerebellum plays a key role in actively\ncontrolling the acquisition of sensory infonnation by the nervous\nsystem. In this paper we explore this idea by examining the function of\na simple cerebellar-related behavior, the vestibula-ocular reflex or\nVOR, in which eye movements are generated to minimize image slip\non the retina during rapid head movements. Considering this system\nfrom the point of view of statistical estimation theory, our results suggest\nthat the transfer function of the VOR, often regarded as a static or\nslowly modifiable feature of the system, should actually be continuously\nand rapidly changed during head movements. We further suggest\nthat these changes are under the direct control of the cerebellar cortex\nand propose experiments to test this hypothesis.", "isbn": "1-558-60015-9", "publisher": "Morgan Kaufmann", "place_of_publication": "San Mateo, CA", "publication_date": "1989", "pages": "410-418" }, { "id": "authors:bnc6e-xkz53", "collection": "authors", "collection_id": "bnc6e-xkz53", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20160810-142009904", "type": "book_section", "title": "Piriform (Olfactory) cortex model on the hypercube", "book_title": "C3P Proceedings of the third conference on Hypercube concurrent computers and applications", "author": [ { "family_name": "Bower", "given_name": "J. M.", "clpid": "Bower-J-M" }, { "family_name": "Nelson", "given_name": "M. E.", "clpid": "Nelson-M-E" }, { "family_name": "Wilson", "given_name": "M. A.", "clpid": "Wilson-M-A" }, { "family_name": "Fox", "given_name": "G. C.", "clpid": "Fox-G-C" }, { "family_name": "Furmanski", "given_name": "W.", "clpid": "Furmanski-W" } ], "abstract": "We present a concurrent hypercube implementation of a neurophysiological model for the piriform (olfactory) cortex. \n\nThe project was undertaken as the first step towards constructing a general neural network simulator on the hypercube, suitable both for applied and biological nets. \n\nThe method presented here is expected to be useful for a class of complex and computationally expensive network models with long range connectivity and non-homogeneous activity patterns. The hypercube communication for the fully interconnected case is efficiently realized by the fold algorithm, constructed previously for problems in concurrent matrix algebra whereas the patchy activity is successfully load balanced by the scattered decomposition. We discuss also briefly other communication strategies, relevant for sparse and variable connectivities. \n\nSample numerical results presented here were derived on the NCUBE hypercube at CaItech.", "doi": "10.1145/63047.63052", "isbn": "0-89791-278-0", "publisher": "ACM", "place_of_publication": "New York, NY", "publication_date": "1988-01" }, { "id": "authors:38n8s-s2x94", "collection": "authors", "collection_id": "38n8s-s2x94", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20160107-153403517", "type": "book_section", "title": "Optimal Neural Spike Classification", "book_title": "Neural Information Processing Systems", "author": [ { "family_name": "Atiya", "given_name": "Amir F.", "clpid": "Atiya-A-F" }, { "family_name": "Bower", "given_name": "James M.", "clpid": "Bower-J-M" } ], "contributor": [ { "family_name": "Anderson", "given_name": "Dana Z.", "clpid": "Anderson-D-Z" } ], "abstract": "Being able to record the electrical activities of a number of neurons simultaneously is likely\nto be important in the study of the functional organization of networks of real neurons. Using\none extracellular microelectrode to record from several neurons is one approach to studying\nthe response properties of sets of adjacent and therefore likely related neurons. However, to\ndo this, it is necessary to correctly classify the signals generated by these different neurons.\nThis paper considers this problem of classifying the signals in such an extracellular recording,\nbased upon their shapes, and specifically considers the classification of signals in the case when\nspikes overlap temporally.", "isbn": "0883185695", "publisher": "American Institute of Physics", "place_of_publication": "New York, NY", "publication_date": "1988", "pages": "95-102" }, { "id": "authors:jq038-cga36", "collection": "authors", "collection_id": "jq038-cga36", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20160107-154754000", "type": "book_section", "title": "Neural Networks for Template Matching: Application to Real-Time Classification of the Action Potentials of Real Neurons", "book_title": "Neural Information Processing Systems", "author": [ { "family_name": "Wong", "given_name": "Yiu-fai", "clpid": "Wong-Y-F" }, { "family_name": "Banik", "given_name": "Jashojiban", "clpid": "Banik-Jashojiban" }, { "family_name": "Bower", "given_name": "James M.", "clpid": "Bower-J-M" } ], "contributor": [ { "family_name": "Anderson", "given_name": "Dana Z.", "clpid": "Anderson-D-Z" } ], "abstract": "Much experimental study of real neural networks relies on the proper classification of\nextracellulary sampled neural signals (i .e. action potentials) recorded from the brains of experimental\nanimals. In most neurophysiology laboratories this classification task is simplified\nby limiting investigations to single, electrically well-isolated neurons recorded one at a time.\nHowever, for those interested in sampling the activities of many single neurons simultaneously,\nwaveform classification becomes a serious concern. In this paper we describe and constrast\nthree approaches to this problem each designed not only to recognize isolated neural events,\nbut also to separately classify temporally overlapping events in real time. First we present two\nformulations of waveform classification using a neural network template matching approach.\nThese two formulations are then compared to a simple template matching implementation.\nAnalysis with real neural signals reveals that simple template matching is a better solution to\nthis problem than either neural network approach.", "isbn": "0883185695", "publisher": "American Institute of Physics", "place_of_publication": "New York, NY", "publication_date": "1988", "pages": "103-113" }, { "id": "authors:rkac2-91e81", "collection": "authors", "collection_id": "rkac2-91e81", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20160107-161054400", "type": "book_section", "title": "GENESIS: A System for Simulating Neural Networks", "book_title": "Advances in Neural Information Processing Systems 1 (NIPS 1988)", "author": [ { "family_name": "Wilson", "given_name": "Matthew A.", "clpid": "Wilson-M-A" }, { "family_name": "Bhalla", "given_name": "Upinder S.", "clpid": "Bhalla-U-S" }, { "family_name": "Uhley", "given_name": "John D.", "clpid": "Uhley-J-D" }, { "family_name": "Bower", "given_name": "James M.", "clpid": "Bower-J-M" } ], "contributor": [ { "family_name": "Touretzky", "given_name": "David S.", "clpid": "Touretzky-D-S" } ], "abstract": "We have developed a graphically oriented, general purpose simulation system to facilitate the modeling of neural networks.\nThe simulator is implemented under UNIX and X-windows and is\ndesigned to support simulations at many levels of detail.\nSpecifically, it is intended for use in both applied network\nmodeling and in the simulation of detailed, realistic, biologically-based\nmodels. Examples of current models developed under this\nsystem include mammalian olfactory bulb and cortex, invertebrate\ncentral pattern generators, as well as more abstract connectionist\nsimulations.", "isbn": "1-558-60015-9", "publisher": "Morgan Kaufmann", "place_of_publication": "San Mateo, CA", "publication_date": "1988", "pages": "485-492" }, { "id": "authors:7ss3f-6qa12", "collection": "authors", "collection_id": "7ss3f-6qa12", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20160107-154534268", "type": "book_section", "title": "A Computer Simulation of Olfactory Cortex with Functional Implications for Storage and Retrieval of Olfactory Information", "book_title": "Neural Information Processing Systems", "author": [ { "family_name": "Wilson", "given_name": "Matthew A.", "clpid": "Wilson-M-A" }, { "family_name": "Bower", "given_name": "James M.", "clpid": "Bower-J-M" } ], "contributor": [ { "family_name": "Anderson", "given_name": "Dana Z.", "clpid": "Anderson-D-Z" } ], "abstract": "Based on anatomical and physiological data, we have developed a computer simulation of piriform\n(olfactory) cortex which is capable of reproducing spatial and temporal patterns of actual\ncortical activity under a variety of conditions. Using a simple Hebb-type learning rule in conjunction\nwith the cortical dynamics which emerge from the anatomical and physiological organization\nof the model, the simulations are capable of establishing cortical representations for different\ninput patterns. The basis of these representations lies in the interaction of sparsely distributed,\nhighly divergent/convergent interconnections between modeled neurons. We have shown that\ndifferent representations can be stored with minimal interference. and that following learning\nthese representations are resistant to input degradation, allowing reconstruction of a representation\nfollowing only a partial presentation of an original training stimulus. Further, we have\ndemonstrated that the degree of overlap of cortical representations for different stimuli can\nalso be modulated. For instance similar input patterns can be induced to generate distinct cortical\nrepresentations (discrimination). while dissimilar inputs can be induced to generate overlapping\nrepresentations (accommodation). Both features are presumably important in classifying olfactory\nstimuli.", "isbn": "0883185695", "publisher": "American Institute of Physics", "place_of_publication": "New York, NY", "publication_date": "1988", "pages": "114-126" } ]