PMID- 23966844
OWN - NLM
STAT- MEDLINE
DCOM- 20140227
LR  - 20211021
IS  - 1553-7358 (Electronic)
IS  - 1553-734X (Print)
IS  - 1553-734X (Linking)
VI  - 9
IP  - 8
DP  - 2013
TI  - Characteristic effects of stochastic oscillatory forcing on neural firing: 
      analytical theory and comparison to paddlefish electroreceptor data.
PG  - e1003170
LID - 10.1371/journal.pcbi.1003170 [doi]
LID - e1003170
AB  - Stochastic signals with pronounced oscillatory components are frequently 
      encountered in neural systems. Input currents to a neuron in the form of 
      stochastic oscillations could be of exogenous origin, e.g. sensory input or 
      synaptic input from a network rhythm. They shape spike firing statistics in a 
      characteristic way, which we explore theoretically in this report. We consider a 
      perfect integrate-and-fire neuron that is stimulated by a constant base current 
      (to drive regular spontaneous firing), along with Gaussian narrow-band noise (a 
      simple example of stochastic oscillations), and a broadband noise. We derive 
      expressions for the nth-order interval distribution, its variance, and the serial 
      correlation coefficients of the interspike intervals (ISIs) and confirm these 
      analytical results by computer simulations. The theory is then applied to 
      experimental data from electroreceptors of paddlefish, which have two distinct 
      types of internal noisy oscillators, one forcing the other. The theory provides 
      an analytical description of their afferent spiking statistics during spontaneous 
      firing, and replicates a pronounced dependence of ISI serial correlation 
      coefficients on the relative frequency of the driving oscillations, and 
      furthermore allows extraction of certain parameters of the intrinsic oscillators 
      embedded in these electroreceptors.
FAU - Bauermeister, Christoph
AU  - Bauermeister C
AD  - Max-Planck-Institute for the Physics of Complex Systems, Dresden, Germany.
FAU - Schwalger, Tilo
AU  - Schwalger T
FAU - Russell, David F
AU  - Russell DF
FAU - Neiman, Alexander B
AU  - Neiman AB
FAU - Lindner, Benjamin
AU  - Lindner B
LA  - eng
GR  - R01 DC004922/DC/NIDCD NIH HHS/United States
GR  - R01DC04922/DC/NIDCD NIH HHS/United States
PT  - Journal Article
PT  - Research Support, N.I.H., Extramural
PT  - Research Support, Non-U.S. Gov't
DEP - 20130815
PL  - United States
TA  - PLoS Comput Biol
JT  - PLoS computational biology
JID - 101238922
SB  - IM
MH  - Action Potentials/physiology
MH  - Animals
MH  - Computational Biology
MH  - Computer Simulation
MH  - Fishes/*physiology
MH  - *Models, Neurological
MH  - Models, Statistical
MH  - Sensory Receptor Cells/*physiology
PMC - PMC3744407
COIS- The authors have declared that no competing interests exist.
EDAT- 2013/08/24 06:00
MHDA- 2014/02/28 06:00
PMCR- 2013/08/01
CRDT- 2013/08/23 06:00
PHST- 2012/12/13 00:00 [received]
PHST- 2013/06/21 00:00 [accepted]
PHST- 2013/08/23 06:00 [entrez]
PHST- 2013/08/24 06:00 [pubmed]
PHST- 2014/02/28 06:00 [medline]
PHST- 2013/08/01 00:00 [pmc-release]
AID - PCOMPBIOL-D-12-01957 [pii]
AID - 10.1371/journal.pcbi.1003170 [doi]
PST - ppublish
SO  - PLoS Comput Biol. 2013;9(8):e1003170. doi: 10.1371/journal.pcbi.1003170. Epub 
      2013 Aug 15.