Abstract
Biological neurons possess elaborate dendrites that perform elaborate computations. They are however ignored in the widely used point neuron models. Here, we present a simple addition to the commonly used leaky integrate-and-fire model that introduces the concept of a dendrite. All synapses on the dendrite have a mutual relationship. The result is a form of short term plasticity in which synapse strengths are influenced by recent activity in other synapses. This improves the ability of the neuron to recognize temporal sequences.
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Acknowledgment
This research has received funding from the European Union’s Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 785907 (Human Brain Project SGA2).
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Vandesompele, A., Wyffels, F., Dambre, J. (2020). Dendritic Computation in a Point Neuron Model. In: Farkaš, I., Masulli, P., Wermter, S. (eds) Artificial Neural Networks and Machine Learning – ICANN 2020. ICANN 2020. Lecture Notes in Computer Science(), vol 12397. Springer, Cham. https://doi.org/10.1007/978-3-030-61616-8_48
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DOI: https://doi.org/10.1007/978-3-030-61616-8_48
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