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  • learning rule  (2)
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  • 1
    Electronic Resource
    Electronic Resource
    Computational Consequences of Temporally Asymmetric Learning Rules: I. Differential Hebbian Learning (1999)
    Springer
    Journal of computational neuroscience 7 (1999), S. 235-246 
    Details
    ISSN: 1573-6873
    Keywords: synaptic plasticity ; learning rule ; classical conditioning ; instability
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Medicine , Physics
    Notes: Abstract Temporally asymetric learning rules governing plastic changes in synaptic efficacy have recently been identified in physiological studies. In these rules, the exact timing of pre- and postsynaptic spikes is critical to the induced change of synaptic efficacy. The temporal learning rules treated in this article are approximately antisymmetric; the synaptic efficacy is enhanced if the postsynaptic spike follows the presynaptic spike by a few milliseconds, but the efficacy is depressed if the postsynaptic spike precedes the presynaptic spike. The learning dynamics of this rule are studied using a stochastic model neuron receiving a set of serially delayed inputs. The average change of synaptic efficacy due to the temporally antisymmetric learning rule is shown to yield differential Hebbian learning. These results are demonstrated with both mathematical analyses and computer simulations, and connections with theories of classical conditioning are discussed.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008910918445
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  • 2
    Electronic Resource
    Electronic Resource
    Computational Consequences of Temporally Asymmetric Learning Rules: II. Sensory Image Cancellation (2000)
    Springer
    Journal of computational neuroscience 9 (2000), S. 67-83 
    Details
    ISSN: 1573-6873
    Keywords: synaptic plasticity ; learning rule ; electric fish ; instability
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Medicine , Physics
    Notes: Abstract The electrosensory lateral line lobe (ELL) of mormyrid electric fish is a cerebellum-like structure that receives primary afferent input from electroreceptors in the skin. Purkinje-like cells in ELL store and retrieve a temporally precise negative image of prior sensory input. The stored image is derived from the association of centrally originating predictive signals with peripherally originating sensory input. The predictive signals are probably conveyed by parallel fibers. Recent in vitro experiments have demonstrated that pairing parallel fiber-evoked excitatory postsynaptic potentials (epsps) with postsynaptic spikes in Purkinje-like cells depresses the strength of these synapses. The depression has a tight dependence on the temporal order of pre- and postsynaptic events. The postsynaptic spike must follow the onset of the epsp within a window of about 60 msec for the depression to occur and pairings at other delays yield a nonassociative enhancement of the epsp. Mathematical analyses and computer simulations are used here to test the hypothesis that synaptic plasticity of the type established in vitro could be responsible for the storage of temporal patterns that is observed in vivo. This hypothesis is confirmed. The temporally asymmetric learning rule established in vitro results in the storage of activity patterns as observed in vivo and does so with significantly greater fidelity than other types of learning rules. The results demonstrate the importance of precise timing in pre- and postsynaptic activity for accurate storage of temporal information.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008938428112
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    Paper (German National Licenses)
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