PMID- 36244004
OWN - NLM
STAT- MEDLINE
DCOM- 20221128
LR  - 20221212
IS  - 1432-0770 (Electronic)
IS  - 0340-1200 (Print)
IS  - 0340-1200 (Linking)
VI  - 116
IP  - 5-6
DP  - 2022 Dec
TI  - A dynamic spike threshold with correlated noise predicts observed patterns of 
      negative interval correlations in neuronal spike trains.
PG  - 611-633
LID - 10.1007/s00422-022-00946-5 [doi]
AB  - Negative correlations in the sequential evolution of interspike intervals (ISIs) 
      are a signature of memory in neuronal spike-trains. They provide coding benefits 
      including firing-rate stabilization, improved detectability of weak sensory 
      signals, and enhanced transmission of information by improving signal-to-noise 
      ratio. Primary electrosensory afferent spike-trains in weakly electric fish fall 
      into two categories based on the pattern of ISI correlations: non-bursting units 
      have negative correlations which remain negative but decay to zero with 
      increasing lags (Type I ISI correlations), and bursting units have oscillatory 
      (alternating sign) correlation which damp to zero with increasing lags (Type II 
      ISI correlations). Here, we predict and match observed ISI correlations in these 
      afferents using a stochastic dynamic threshold model. We determine the ISI 
      correlation function as a function of an arbitrary discrete noise correlation 
      function [Formula: see text], where k is a multiple of the mean ISI. The function 
      permits forward and inverse calculations of the correlation function. Both types 
      of correlation functions can be generated by adding colored noise to the spike 
      threshold with Type I correlations generated with slow noise and Type II 
      correlations generated with fast noise. A first-order autoregressive (AR) process 
      with a single parameter is sufficient to predict and accurately match both types 
      of afferent ISI correlation functions, with the type being determined by the sign 
      of the AR parameter. The predicted and experimentally observed correlations are 
      in geometric progression. The theory predicts that the limiting sum of ISI 
      correlations is [Formula: see text] yielding a perfect DC-block in the power 
      spectrum of the spike train. Observed ISI correlations from afferents have a 
      limiting sum that is slightly larger at [Formula: see text] ([Formula: see 
      text]). We conclude that the underlying process for generating ISIs may be a 
      simple combination of low-order AR and moving average processes and discuss the 
      results from the perspective of optimal coding.
CI  - (c) 2022. The Author(s).
FAU - Sidhu, Robin S
AU  - Sidhu RS
AD  - Department of Electrical and Computer Engineering, University of Illinois at 
      Urbana-Champaign, Urbana, IL, USA.
FAU - Johnson, Erik C
AU  - Johnson EC
AD  - The Johns Hopkins University Applied Physics Laboratory, Laurel, MD, USA.
FAU - Jones, Douglas L
AU  - Jones DL
AD  - Department of Electrical and Computer Engineering, University of Illinois at 
      Urbana-Champaign, Urbana, IL, USA.
FAU - Ratnam, Rama
AU  - Ratnam R
AUID- ORCID: 0000-0002-9931-7846
AD  - Division of Biological and Life Sciences, School of Arts and Sciences, Ahmedabad 
      University, Ahmedabad, Gujarat, India. rama.ratnam@ahduni.edu.in.
LA  - eng
GR  - EFRI-BSBA-0938007/National Science Foundation/
GR  - IGERT 0903622/National Science Foundation/
PT  - Journal Article
PT  - Research Support, N.I.H., Extramural
PT  - Research Support, Non-U.S. Gov't
PT  - Research Support, U.S. Gov't, Non-P.H.S.
DEP - 20221016
PL  - Germany
TA  - Biol Cybern
JT  - Biological cybernetics
JID - 7502533
SB  - IM
MH  - Animals
MH  - Action Potentials/physiology
MH  - *Electric Fish/physiology
MH  - Neurons/physiology
MH  - Noise
MH  - Models, Neurological
PMC - PMC9691502
OTO - NOTNLM
OT  - Adaptation
OT  - Dynamic threshold
OT  - Negative interspike interval correlations
OT  - Noisy threshold
OT  - Optimal neural coding
OT  - P-type electrosensory afferents
OT  - Serial correlation coefficients
OT  - Weakly electric fish
EDAT- 2022/10/17 06:00
MHDA- 2022/11/29 06:00
PMCR- 2022/10/16
CRDT- 2022/10/16 13:59
PHST- 2021/12/10 00:00 [received]
PHST- 2022/09/26 00:00 [accepted]
PHST- 2022/10/17 06:00 [pubmed]
PHST- 2022/11/29 06:00 [medline]
PHST- 2022/10/16 13:59 [entrez]
PHST- 2022/10/16 00:00 [pmc-release]
AID - 10.1007/s00422-022-00946-5 [pii]
AID - 946 [pii]
AID - 10.1007/s00422-022-00946-5 [doi]
PST - ppublish
SO  - Biol Cybern. 2022 Dec;116(5-6):611-633. doi: 10.1007/s00422-022-00946-5. Epub 
      2022 Oct 16.