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  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Biological cybernetics 16 (1974), S. 53-64 
    ISSN: 1432-0770
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Computer Science , Physics
    Notes: Abstract This paper describes a model for the generation of repetitive firing patterns in single neurons to be used as a module in large-scale network simulation studies. The model is based on the combination of extended versions of Hill's model for accomodation and of Kernell's model for adaptation. Both digital computer and electronic circuit realizations of the model are presented. The model is shown to produce strength-duration curves for accomodation which are compatible with available data from real neurons. Both “high ceiling” and “low ceiling” cell types can be matched by adjusting parameters in the model. An equation relating steady-state firing rate to amplitude of applied steady current is presented which includes the accumulation of potassium conductance changes with repetitive firing. The occurence of phasic and tonic responses to step stimulation is mapped in the parameter space of the model. Several representative response patterns to irregular inputs are presented.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Biological cybernetics 16 (1974), S. 79-86 
    ISSN: 1432-0770
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Computer Science , Physics
    Notes: Abstract This paper describes computer simulation of 100 artificial neurons interconnected in mutually exciting random pools. The individual neuromimes include accommodation according to an extended version of Hill's model and adaptation according to an extended version of Kernell's model. The main finding is that the constituent cells of the pools tend to fire in coordinated bursts and that these bursts recur rhythmically. The rate of burst recurrence depends primarily on the time constant of recovery of the after-hyperpolarization conductance change although it may be slightly altered by the average level of random background activity. It does not seem possible to attribute the salient slow rhythm observed in the rat mesencephalic reticular formation to this mechanism, as matching the data requires absurdly large values of the conductance change recovery time constant.
    Type of Medium: Electronic Resource
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  • 3
    ISSN: 1432-0770
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Computer Science , Physics
    Notes: Abstract.  This paper presents a dynamic-similarity-based system for mathematically characterizing the functional connectivity and information flow of neural junctions. This approach allows for quantitative comparison of operations of neural junctions across systems, and an interpretation of their connectivity parameters in terms of the flow of multiunit firing patterns. The paper further uses this characterization to show how to rationally construct reduced operational models of neural junctions. Both uniformly proportional scaling and partial fragmentary representations are developed. The uniformly scaled models are better adapted to overall capacities and broader theoretical conceptualizations; the partial representations are better adapted to direct comparison with microelectrode experimentation. The characterization of information flow is based on coordinated multiunit patterns such as synfire chains or sequential configurations. The system can be applied to component parts of large composite networks including junctions with topographical patchiness and other irregularities. The characterization should be of use to anatomists, physiologists, modelers, and theorists. The theory predicts that the necessity for cooperative confluence of synaptic potentials in sending and receiving sequential configurations across topographically constrained projection fields requires the existence of functional ‘pattern modules’ within the topographical synaptology of the junction.
    Type of Medium: Electronic Resource
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  • 4
    ISSN: 1432-0770
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Computer Science , Physics
    Notes: Abstract.  This paper applies a general mathematical system for characterizing and scaling functional connectivity and information flow across the diffuse (EC) and discrete (DG) input junctions to the CA3 hippocampus. Both gross connectivity and coordinated multiunit informational firing patterns are quantitatively characterized in terms of 32 defining parameters interrelated by 17 equations, and then scaled down according to rules for uniformly proportional scaling and for partial representation. The diffuse EC-CA3 junction is shown to be uniformly scalable with realistic representation of both essential spatiotemporal cooperativity and coordinated firing patterns down to populations of a few hundred neurons. Scaling of the discrete DG-CA3 junction can be effected with a two-step process, which necessarily deviates from uniform proportionality but nonetheless produces a valuable and readily interpretable reduced model, also utilizing a few hundred neurons in the receiving population. Partial representation produces a reduced model of only a portion of the full network where each model neuron corresponds directly to a biological neuron. The mathematical analysis illustrated here shows that although omissions and distortions are inescapable in such an application, satisfactorily complete and accurate models the size of pattern modules are possible. Finally, the mathematical characterization of these junctions generates a theory which sees the DG as a definer of the fine structure of embedded traces in the hippocampus and entire coordinated patterns of sequences of 14-cell links in CA3 as triggered by the firing of sequences of individual neurons in DG.
    Type of Medium: Electronic Resource
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  • 5
    Electronic Resource
    Electronic Resource
    Springer
    Biological cybernetics 65 (1991), S. 351-355 
    ISSN: 1432-0770
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Computer Science , Physics
    Notes: Abstract The present paper presents a theory for the mechanics of cross-talk among constituent neurons in networks in which multiple memory traces have been embedded, and develops criteria for memory capacity based on the disruptive influences of this cross-talk. The theory is based on interconnection patterns defined by the sequential configuration model of dynamic firing patterns. The theory accurately predicts the memory capacities observed in computer simulated nets, and predicts that cortical-like modules should be able to store up to about 300–900 selectively retrievable memory traces before disruption by cross-talk is likely. It also predicts that the cortex may has designed itself for modules of 30,000 neurons to at least in part to optimize memory capacity.
    Type of Medium: Electronic Resource
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  • 6
    Electronic Resource
    Electronic Resource
    Springer
    Biological cybernetics 65 (1991), S. 339-349 
    ISSN: 1432-0770
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Computer Science , Physics
    Notes: Abstract This paper presents a sequential configuration model to represent the coordinated firing patterns of memory traces in groups of neurons in local networks. Computer simulations are used to study the dynamic properties of memory traces selectively retrieved from networks in which multiple memory traces have been embedded according to the sequential configuration model. Distinct memory traces which utilize the same neurons, but differ only in temporal sequencing are selectively retrievable. Firing patterns of constituent neurons of retrieved memory traces exhibit the main properties of neurons observed in multi microelectrode recordings. The paper shows how to adjust relative synaptic weightings so as to control the disruptive influences of cross-talk in multipy-embedded networks. The theoretical distinction between (primarily anatomical) beds and (primarily physiological) realizations underlines the fundamentally stochastic nature of network firing patterns, and allows the definition of 4 degrees of clarity of retrieved memory traces.
    Type of Medium: Electronic Resource
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  • 7
    Electronic Resource
    Electronic Resource
    Springer
    Biological cybernetics 28 (1978), S. 121-127 
    ISSN: 1432-0770
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Computer Science , Physics
    Notes: Abstract This paper describes computer simulations of diffusely-connected neuronal populations. Main findings are that diffuse monosynaptic linkages between populations are selectively sensitive to synchronized clusters of action potentials in the pre-synaptic population; that diffusely-connected excitatory recurrent collaterals tend to produce rhythmic series of synchronized clusters; and that diffusely-connected inhibition (both recurrent and afferent) tend to reduce the number of cells participating in a given synchronized cluster and thereby the overall transfer rate. However, recurrent inhibition tends to increase the rate at which synchronized clusters are produced by recurrent excitation. These results suggest the speculation that diffusely connected neuronal populations are particularly prone to deal with synchronized clusters of action potentials.
    Type of Medium: Electronic Resource
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  • 8
    Electronic Resource
    Electronic Resource
    Amsterdam : Elsevier
    International Journal of Radiation Applications & Instrumentation. Part 39 (1988), S. 559 
    ISSN: 0883-2889
    Source: Elsevier Journal Backfiles on ScienceDirect 1907 - 2002
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Type of Medium: Electronic Resource
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  • 9
    ISSN: 1520-4804
    Source: ACS Legacy Archives
    Topics: Chemistry and Pharmacology
    Type of Medium: Electronic Resource
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  • 10
    Electronic Resource
    Electronic Resource
    s.l. : American Chemical Society
    The @journal of organic chemistry 47 (1982), S. 2489-2491 
    ISSN: 1520-6904
    Source: ACS Legacy Archives
    Topics: Chemistry and Pharmacology
    Type of Medium: Electronic Resource
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