Literature DB >> 14608010

Measuring spike coding in the rat supraoptic nucleus.

G S Bhumbra1, R E J Dyball.   

Abstract

Measuring spike coding objectively is essential to establish whether activity recorded under one set of conditions is truly different from that recorded under another set of conditions. However, there is no generally accepted method for making such comparisons. Measuring firing frequency alone only partially reflects spike patterning. In this paper, novel quantities based on the logarithmic interspike intervals are proposed as useful measures of spontaneous activity. We illustrate the methods by comparing extracellular recordings from magnocellular cells of the rat supraoptic nucleus in vivo and in vitro and between oxytocin and vasopressin cells in vivo. A bimodal Gaussian function fitted to the log interspike interval histogram accurately described the distribution profile for very different types of activity. We introduce the entropy of the log interval distribution as a novel quantity that measures the capacity of a cell to encode information other than a constant instantaneous frequency. Unlike existing entropy measures that are based on spike counts, it quantifies the variability in the interval distribution. In addition, the mutual information between adjacent log intervals is proposed as an objective measure of patterned activity. For cells recorded in vivo and in vitro, there was no significant difference in mean spike frequencies but there were differences in the log interval entropy (t = -4.97, P < 0.001) and the mutual information (z = -2.64, P < 0.01). The differences may result from the disruption of connections in the slice preparation. When a comparison was made between the spike activity of oxytocin and vasopressin cells recorded in vivo, there was a difference in mutual information (z = 5.15, P < 0.001) but not in mean spike frequency. Both comparisons highlight the potential limitations of using mean spike frequency alone as a measure of spike coding. We propose that our novel parameters based on interval analysis constitute informative measures of spontaneous activity under different physiological conditions.

Entities:  

Mesh:

Substances:

Year:  2003        PMID: 14608010      PMCID: PMC1664829          DOI: 10.1113/jphysiol.2003.053264

Source DB:  PubMed          Journal:  J Physiol        ISSN: 0022-3751            Impact factor:   5.182


  23 in total

1.  Efficiency and ambiguity in an adaptive neural code.

Authors:  A L Fairhall; G D Lewen; W Bialek; R R de Ruyter Van Steveninck
Journal:  Nature       Date:  2001-08-23       Impact factor: 49.962

2.  Responses of magnocellular neurons to osmotic stimulation involves coactivation of excitatory and inhibitory input: an experimental and theoretical analysis.

Authors:  G Leng; C H Brown; P M Bull; D Brown; S Scullion; J Currie; R E Blackburn-Munro; J Feng; T Onaka; J G Verbalis; J A Russell; M Ludwig
Journal:  J Neurosci       Date:  2001-09-01       Impact factor: 6.167

3.  RANDOM WALK MODELS FOR THE SPIKE ACTIVITY OF A SINGLE NEURON.

Authors:  G L GERSTEIN; B MANDELBROT
Journal:  Biophys J       Date:  1964-01       Impact factor: 4.033

4.  An approach to the quantitative analysis of electrophysiological data from single neurons.

Authors:  G L GERSTEIN; N Y KIANG
Journal:  Biophys J       Date:  1960-09       Impact factor: 4.033

5.  Reading a neural code.

Authors:  W Bialek; F Rieke; R R de Ruyter van Steveninck; D Warland
Journal:  Science       Date:  1991-06-28       Impact factor: 47.728

6.  Some quantitative methods for the study of spontaneous activity of single neurons.

Authors:  R W RODIECK; N Y KIANG; G L GERSTEIN
Journal:  Biophys J       Date:  1962-07       Impact factor: 4.033

7.  Neurones in the supraoptic nucleus of the rat are regulated by a projection from the suprachiasmatic nucleus.

Authors:  L N Cui; K Saeb-Parsy; R E Dyball
Journal:  J Physiol       Date:  1997-07-01       Impact factor: 5.182

8.  Neuronal spike trains and stochastic point processes. I. The single spike train.

Authors:  D H Perkel; G L Gerstein; G P Moore
Journal:  Biophys J       Date:  1967-07       Impact factor: 4.033

9.  Caesium blocks depolarizing after-potentials and phasic firing in rat supraoptic neurones.

Authors:  M Ghamari-Langroudi; C W Bourque
Journal:  J Physiol       Date:  1998-07-01       Impact factor: 5.182

10.  Neurosecretory cell: capable of conducting impulse in rats.

Authors:  K Yagi; T Azuma; K Matsuda
Journal:  Science       Date:  1966-11-11       Impact factor: 47.728

View more
  13 in total

1.  Phasic spike patterning in rat supraoptic neurones in vivo and in vitro.

Authors:  Nancy Sabatier; Colin H Brown; Mike Ludwig; Gareth Leng
Journal:  J Physiol       Date:  2004-05-14       Impact factor: 5.182

2.  Rhythmic changes in spike coding in the rat suprachiasmatic nucleus.

Authors:  G S Bhumbra; A N Inyushkin; K Saeb-Parsy; A Hon; R E J Dyball
Journal:  J Physiol       Date:  2004-12-20       Impact factor: 5.182

3.  Spike coding from the perspective of a neurone.

Authors:  G S Bhumbra; R E J Dyball
Journal:  Cogn Process       Date:  2005-08-12

4.  Age affects spontaneous activity and depolarizing afterpotentials in isolated gonadotropin-releasing hormone neurons.

Authors:  Yong Wang; Mona Garro; Heather A Dantzler; Julia A Taylor; David D Kline; M Cathleen Kuehl-Kovarik
Journal:  Endocrinology       Date:  2008-06-26       Impact factor: 4.736

5.  Spike coding during osmotic stimulation of the rat supraoptic nucleus.

Authors:  G S Bhumbra; A N Inyushkin; M Syrimi; R E J Dyball
Journal:  J Physiol       Date:  2005-09-15       Impact factor: 5.182

6.  Differences in spike train variability in rat vasopressin and oxytocin neurons and their relationship to synaptic activity.

Authors:  Chunyan Li; Pradeep K Tripathi; William E Armstrong
Journal:  J Physiol       Date:  2007-03-01       Impact factor: 5.182

7.  Quantifying neural coding of event timing.

Authors:  Demetris S Soteropoulos; Stuart N Baker
Journal:  J Neurophysiol       Date:  2008-11-19       Impact factor: 2.714

8.  Information theoretic analysis of proprioceptive encoding during finger flexion in the monkey sensorimotor system.

Authors:  Claire L Witham; Stuart N Baker
Journal:  J Neurophysiol       Date:  2014-10-08       Impact factor: 2.714

9.  Pharmacological imposition of sleep slows cognitive decline and reverses dysregulation of circadian gene expression in a transgenic mouse model of Huntington's disease.

Authors:  Patrick N Pallier; Elizabeth S Maywood; Zhiguang Zheng; Johanna E Chesham; Alexei N Inyushkin; Richard Dyball; Michael H Hastings; A Jennifer Morton
Journal:  J Neurosci       Date:  2007-07-18       Impact factor: 6.167

10.  Probabilistic identification of cerebellar cortical neurones across species.

Authors:  Gert Van Dijck; Marc M Van Hulle; Shane A Heiney; Pablo M Blazquez; Hui Meng; Dora E Angelaki; Alexander Arenz; Troy W Margrie; Abteen Mostofi; Steve Edgley; Fredrik Bengtsson; Carl-Fredrik Ekerot; Henrik Jörntell; Jeffrey W Dalley; Tahl Holtzman
Journal:  PLoS One       Date:  2013-03-04       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.