TY - GEN
T1 - Bifurcations in a silicon neuron
AU - Basu, Arindam
AU - Petre, Csaba
AU - Hasler, Paul
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
PY - 2008
Y1 - 2008
N2 - In this paper, we describe the bifurcations occurring in a silicon neuron with one sodium and one potassium channel. The channels are designed to model the physics of ion flow in actual biological channels instead of modeling a particular set of equations. We show a pair of subcritical Hopf-bifurcation with increase in current stimulus which is characteristic of class 2 excitability in Hodgkin-Huxley neurons. Theoretical analysis of the bifurcations lead to conditions for designing and biasing the circuit. The circuit is very compact, comprising six transistors and three capacitors, lending itself to easy integration. The parameters are set using floating-gate transistors and can be programmed as desired. We hope to study more complicated dynamics of large networks of these neurons, a task which might be beyond a typical digital computer. ©2008 IEEE.
AB - In this paper, we describe the bifurcations occurring in a silicon neuron with one sodium and one potassium channel. The channels are designed to model the physics of ion flow in actual biological channels instead of modeling a particular set of equations. We show a pair of subcritical Hopf-bifurcation with increase in current stimulus which is characteristic of class 2 excitability in Hodgkin-Huxley neurons. Theoretical analysis of the bifurcations lead to conditions for designing and biasing the circuit. The circuit is very compact, comprising six transistors and three capacitors, lending itself to easy integration. The parameters are set using floating-gate transistors and can be programmed as desired. We hope to study more complicated dynamics of large networks of these neurons, a task which might be beyond a typical digital computer. ©2008 IEEE.
UR - https://www.scopus.com/pages/publications/51749101946
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-51749101946&origin=recordpage
U2 - 10.1109/ISCAS.2008.4541446
DO - 10.1109/ISCAS.2008.4541446
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781424416844
T3 - Proceedings - IEEE International Symposium on Circuits and Systems
SP - 428
EP - 431
BT - 2008 IEEE International Symposium on Circuits and Systems, ISCAS 2008
T2 - 2008 IEEE International Symposium on Circuits and Systems, ISCAS 2008
Y2 - 18 May 2008 through 21 May 2008
ER -