Abstract
Synchronized neural bursts are one of the most noticeable dynamic features of neural networks, being essential for various phenomena in neuroscience, yet their complex dynamics are not well understood. With extrinsic electrical and optical manipulations on cultured neural networks, we demonstrate that the regularity (or randomness) of burst sequences is in many cases determined by a (few) low-dimensional attractor(s) working under strong neural noise. Moreover, there is an optimal level of noise strength at which the regularity of the interburst interval sequence becomes maximal - a phenomenon of coherence resonance. The experimental observations are successfully reproduced through computer simulations on a well-established neural network model, suggesting that the same phenomena may occur in many in vivo as well as in vitro neural networks.
| Original language | English |
|---|---|
| Article number | 042701 |
| Journal | Physical Review E - Statistical, Nonlinear, and Soft Matter Physics |
| Volume | 92 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2015 Oct 1 |
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ASJC Scopus subject areas
- Condensed Matter Physics
- Statistical and Nonlinear Physics
- Statistics and Probability
Cite this
Coherence resonance in bursting neural networks. / Kim, June Hoan; Lee, Ho Jun; Min, Cheol Hong; Lee, Kyoung Jin.
In: Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, Vol. 92, No. 4, 042701, 01.10.2015.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Coherence resonance in bursting neural networks
AU - Kim, June Hoan
AU - Lee, Ho Jun
AU - Min, Cheol Hong
AU - Lee, Kyoung Jin
PY - 2015/10/1
Y1 - 2015/10/1
N2 - Synchronized neural bursts are one of the most noticeable dynamic features of neural networks, being essential for various phenomena in neuroscience, yet their complex dynamics are not well understood. With extrinsic electrical and optical manipulations on cultured neural networks, we demonstrate that the regularity (or randomness) of burst sequences is in many cases determined by a (few) low-dimensional attractor(s) working under strong neural noise. Moreover, there is an optimal level of noise strength at which the regularity of the interburst interval sequence becomes maximal - a phenomenon of coherence resonance. The experimental observations are successfully reproduced through computer simulations on a well-established neural network model, suggesting that the same phenomena may occur in many in vivo as well as in vitro neural networks.
AB - Synchronized neural bursts are one of the most noticeable dynamic features of neural networks, being essential for various phenomena in neuroscience, yet their complex dynamics are not well understood. With extrinsic electrical and optical manipulations on cultured neural networks, we demonstrate that the regularity (or randomness) of burst sequences is in many cases determined by a (few) low-dimensional attractor(s) working under strong neural noise. Moreover, there is an optimal level of noise strength at which the regularity of the interburst interval sequence becomes maximal - a phenomenon of coherence resonance. The experimental observations are successfully reproduced through computer simulations on a well-established neural network model, suggesting that the same phenomena may occur in many in vivo as well as in vitro neural networks.
UR - http://www.scopus.com/inward/record.url?scp=84945189229&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84945189229&partnerID=8YFLogxK
U2 - 10.1103/PhysRevE.92.042701
DO - 10.1103/PhysRevE.92.042701
M3 - Article
C2 - 26565266
AN - SCOPUS:84945189229
VL - 92
JO - Physical Review E
JF - Physical Review E
SN - 2470-0045
IS - 4
M1 - 042701
ER -