Self-influencing synaptic plasticity: Recurrent changes of synaptic weights can lead to specific functional properties |
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Authors: | Minija Tamosiunaite Bernd Porr Florentin Wörgötter |
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Institution: | Department of Psychology, University of Stirling, Stirling, FK9 4LA, Scotland. minija_tamosiunaite@fc.vdu.lt |
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Abstract: | Recent experimental results suggest that dendritic and back-propagating spikes can influence synaptic plasticity in different
ways (Holthoff, 2004; Holthoff et al., 2005). In this study we investigate how these signals could interact at dendrites in
space and time leading to changing plasticity properties at local synapse clusters. Similar to a previous study (Saudargiene
et al., 2004) we employ a differential Hebbian learning rule to emulate spike-timing dependent plasticity and investigate
how the interaction of dendritic and back-propagating spikes, as the post-synaptic signals, could influence plasticity. Specifically,
we will show that local synaptic plasticity driven by spatially confined dendritic spikes can lead to the emergence of synaptic
clusters with different properties. If one of these clusters can drive the neuron into spiking, plasticity may change and
the now arising global influence of a back-propagating spike can lead to a further segregation of the clusters and possibly
the dying-off of some of them leading to more functional specificity. These results suggest that through plasticity being
a spatial and temporal local process, the computational properties of dendrites or complete neurons can be substantially augmented.
Action Editor: Wulfram Gerstner |
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Keywords: | Spike-timing-dependent plasticity Dendritic spike Back-propagating spike Local learning |
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