Spontaneous and stimulated firing in cultured rat suprachiasmatic neurons

Walsh, I.B.; Berg, R.J. van den; Marani, Enrico; Rietveld, W.J.

doi:10.1016/0006-8993(92)91351-e

Cited by 31 publications

(14 citation statements)

References 44 publications

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“…lLN v spontaneous activity is somewhat variable, with 33% of cells silent in the light phase and 38% in the dark in LD. That, overall, 35% of lLN v s are silent in LD is slightly higher but still comparable with mammalian clock neurons in the suprachiasmatic nucleus (SCN) (Walsh et al, 1992;Kim and Dudek, 1993). Despite the 35% of silent lLN v s, the average AP firing frequency and the percentage of lLN v s that fire APs show a circadian temporal pattern similar to that in mammalian SCN, which is consistent with linear regression analysis of the scatter plot of individual cells (Fig.…”

Section: Discussionsupporting

confidence: 81%

Circadian Control of Membrane Excitability in Drosophila melanogaster Lateral Ventral Clock Neurons

Cao¹,

Nitabach²

2008

Journal of Neuroscience

147

182

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Section: Discussionsupporting

confidence: 81%

Circadian Control of Membrane Excitability in Drosophila melanogaster Lateral Ventral Clock Neurons

Cao¹,

Nitabach²

2008

Journal of Neuroscience

147

182

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“…Figure 6 shows the variation of the mean CTS-output frequency along with 24 h, where one can observe that the CTS-output frequency varies from 0 Hz to a maximal value oscillator 3.5 Hz within the time interval of 6-12 h (midday), falling then to 0 Hz at 18 h. These results are in agreement with experimental data found in literature for suprachiasmatic neurons, presenting spontaneous activity, in experiments in vivo and in vitro. Most of these studies have been done in rodents, and the registered firing frequencies range from 0.5 to 14 Hz (Aujard et al 2001;Walsh et al 1992;Schaap et al 1999;Pennartz et al 1998;Kononenko and Dudek 2004;Glotzbach et al 1987;Zlomanczuk et al 1991). Such interval appears to be compatible with the firing frequency of neurons able to signalize the circadian cycle and hormone releasing (Fig.…”

Section: Numerical Results and Discussionmentioning

confidence: 83%

“…It is a method that adopt the statistical analysis of the phases of oscillators ( ) to study the average behavior of oscillators and cluster formation. In this method, σ is given by Resting potential (V R ) −65 mV Walsh et al (1992) Reverse Potential (V 0 ) −70 mV Kudela et al (1997) and Barrett et al (1980) Time constant of excitatory effect (τ E ) 7.3 ms Kim and Dudek (1993) Time constant of inhibitory effect (τ I ) 13 ms Kim and Dudek (1992) Decay time constant for the refractory 1.2 ms Carp (1992) …”

Section: Description Of the Modelmentioning

confidence: 99%

Computational modeling of synchronization process of the circadian timing system of mammals

et al. 2009

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This paper presents a model for the circadian temporization system of mammals which associates the synchronization dynamics of coupling oscillators to a set of equations able to reproduce the synaptic characteristics of somatodendritic membrane of neurons. The circadian timing system is organized in a way to receive information from the external and internal environments, and its function is the timing organization of physiological and behavioral processes in a circadian pattern. Circadian timing system in mammals is constituted by a group of structures which includes the suprachiasmatic nucleus, the intergeniculate leaflet and the pineal gland. In suprachiasmatic nucleus are found neuron groups working as a biological pacemaker-the so-called biological master clock. By means of numerical simulations using the Kuramoto model, we simulated the dynamics behavior of the biological pacemaker. For this we used a set of 1,000 coupled oscillators with long-range coupling, which were distributed on a 10 x 10 x 10 spherical lattice, and a new method to estimate the order parameter, which characterizes the degree of synchronization of oscillator system. Our model has been able to produce frequency responses in accordance with physiological patterns, and to reproduce two fundamental characteristics of biological rhythms: the endogenous generation and synchronization to the light-dark cycle.

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“…After 12:00 h, the output frequency of CTS falls until it reaches 0 Hz at 18:00 h. These results agree with experimental data reported in the literature. Suprachiasmatic neurons presenting spontaneous activity have been found by several investigators in vivo and in vitro experiments, and firing frequencies recorded in some of these experiments in rodents have varied from 1.8 to 5.4 Hz (13,18,24). Discharges of about 5.4 Hz and two troughs of about 1.8 and 2.4 Hz were recorded by Zlomanczuk et al (24) from SCN neurons of hamsters, which exhibited a split in overt behavior.…”

Section: Resultsmentioning

confidence: 99%

“…Numerical values of parameters found in the literature were applied to these programs (Table 1; Refs. [18][19][20][21][22]. Some of these values were obtained from experimental studies.…”

Section: Model Adoptedmentioning

confidence: 99%

A simple model for circadian timing by mammals

Cardoso

Cruz

Silva

et al. 2009

Braz J Med Biol Res

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Circadian timing is structured in such a way as to receive information from the external and internal environments, and its function is the timing organization of the physiological and behavioral processes in a circadian pattern. In mammals, the circadian timing system consists of a group of structures, which includes the suprachiasmatic nucleus (SCN), the intergeniculate leaflet and the pineal gland. Neuron groups working as a biological pacemaker are found in the SCN, forming a biological master clock. We present here a simple model for the circadian timing system of mammals, which is able to reproduce two fundamental characteristics of biological rhythms: the endogenous generation of pulses and synchronization with the light-dark cycle. In this model, the biological pacemaker of the SCN was modeled as a set of 1000 homogeneously distributed coupled oscillators with long-range coupling forming a spherical lattice. The characteristics of the oscillator set were defined taking into account the Kuramoto's oscillator dynamics, but we used a new method for estimating the equilibrium order parameter. Simultaneous activities of the excitatory and inhibitory synapses on the elements of the circadian timing circuit at each instant were modeled by specific equations for synaptic events. All simulation programs were written in Fortran 77, compiled and run on PC DOS computers. Our model exhibited responses in agreement with physiological patterns. The values of output frequency of the oscillator system (maximal value of 3.9 Hz) were of the order of magnitude of the firing frequencies recorded in suprachiasmatic neurons of rodents in vivo and in vitro (from 1.8 to 5.4 Hz).

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Spontaneous and stimulated firing in cultured rat suprachiasmatic neurons

Cited by 31 publications

References 44 publications

Circadian Control of Membrane Excitability in Drosophila melanogaster Lateral Ventral Clock Neurons

Circadian Control of Membrane Excitability in Drosophila melanogaster Lateral Ventral Clock Neurons

Computational modeling of synchronization process of the circadian timing system of mammals

A simple model for circadian timing by mammals

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