Forward- and backpropagation in a silicon dendrite

Author

Rasche, C. ; Douglas, R.J.

Author_Institution

Inst. of Neuroinformatics, Zurich, Switzerland

Volume

12

Issue

2

fYear

2001

fDate

3/1/2001 12:00:00 AM

Firstpage

386

Lastpage

393

Abstract

We have developed an analog very-large-scale integrated (aVLSI) electronic circuit that emulates a compartmental model of a neuronal dendrite. The horizontal conductances of the compartmental model are implemented as a switched capacitor network. The transmembrane conductances are implemented as transconductance amplifiers. The electrotonic properties of our silicon cable are qualitatively similar to those of the ideal passive cable that is commonly used to model mathematically the electrotonic behavior of neurons. In particular the propagation of excitatory postsynaptic potentials is realistic, and we are easily able to emulate such classical synaptic integration models as direction selectivity. We are also able to emulate the backpropagation into the dendrite of single somatic spikes and bursts of spikes. Thus, this silicon dendrite is suitable for incorporation in detailed silicon neurons operating in real-time; in particular for the emulation of forward- and backpropagating electrical activities found in real neurons

Keywords

VLSI; analogue integrated circuits; analogue processing circuits; backpropagation; bioelectric potentials; biomembrane transport; neural chips; real-time systems; somatosensory phenomena; switched capacitor networks; aVLSI electronic circuit; analog VLSI electronic circuit; backpropagation; direction selectivity; electrotonic properties; excitatory postsynaptic potential propagation; forward propagation; horizontal conductances; neural nets; neuronal dendrite; real-time operation; silicon cable; silicon dendrite; silicon neurons; single somatic spikes; spike bursts; switched capacitor network; synaptic integration models; transconductance amplifiers; transmembrane conductances; Adaptive signal processing; Backpropagation; Biomedical signal processing; Computational modeling; Distributed computing; Electronic circuits; Emulation; Intelligent networks; Neurons; Silicon;

fLanguage

English

Journal_Title

Neural Networks, IEEE Transactions on

Publisher

ieee

ISSN

1045-9227

Type

jour

DOI

10.1109/72.914532

Filename

914532