Neural Modeling

Large Ca2+signals essential for cerebellar long-term depression (LTD) at parallel fiber (PF)-Purkinje cell synapses are known to be induced when PF activation precedes climbing fiber (CF) activation by 50-200 ms, consistent with cerebellar learning theories. However, large Ca2+signals and/or LTD can also be induced by massive PF stimulation alone or by photolysis of caged Ca2+or inositol 1,4,5-trisphosphate (IP3). To understand the spike-timing detection mechanisms in cerebellar LTD, we developed a kinetic model of Ca2+dynamics within a Purkinje dendritic spine. In our kinetic simulation, IP3was first produced via the metabotropic pathway of PF inputs, and the Ca2+influx in response to the CF input triggered regenerative Ca2+-induced Ca2+release from the internal stores via the IP3receptors activated by the increased IP3. The delay in IP3increase caused by the PF metabotropic pathway generated the optimal PF-CF interval. The Ca2+dynamics revealed a threshold for large Ca2+release that decreased as IP3increased, and it coherently explained the different forms of LTD. At 2.5 μmIP3, CF activation after PF activation was essential to reach the threshold for the regenerative Ca2+release. At 10 μmIP3, the same as achieved experimentally by strong IP3photolysis, the threshold was lower, and thus large Ca2+release was generated even without CF stimulation. In contrast, the basal 0.1 μmIP3level resulted in an extremely high Ca2+threshold for regenerative Ca2+release. Thus, the results demonstrated that Ca2+dynamics can detect spike timing under physiological conditions, which supports cerebellar learning theories.

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“…The exponential Euler method (MacGregor, 1987) with a time step of 1 s was used to solve the differential equations.…”

Section: Simulator and Numerical Integrationmentioning

confidence: 99%

Inositol 1,4,5-Trisphosphate-Dependent Ca²⁺Threshold Dynamics Detect Spike Timing in Cerebellar Purkinje Cells

Doi

Kuroda²,

Michikawa³

et al. 2005

J. Neurosci.

111

160

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“…On the other hand, more focused approaches have been adopted by research groups interested in answering specific questions in spinal cord investigation, which meant developing their own simulators, without a goal of general usage (Capaday and Stein 1987;Maltenfort et al 1998;Nussbaumer et al 2002;Ivashko et al 2003;Lowery and Erim 2005;Subramanian et al 2005;Stienen et al 2007;Uchiyama and Windhorst 2007). Bashor's (1998) spinal network simulator was based on MacGregor's implementations in Fortran of neuronal, synaptic and network models (MacGregor 1987). Its focus was on the interactions between the neuronal networks associated with two antagonistic muscles, with parameter values based on cat data from the literature.…”

Section: Introductionmentioning

confidence: 99%

Simulation system of spinal cord motor nuclei and associated nerves and muscles, in a Web-based architecture

2008

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“…5) is based on the MacGregor neuromime model, 10 which is a parallel circuit model containing the membrane capacitance, leakage conductance, a potassium channel branch and the excitatory/inhibitory connection branches. Each excitatory or inhibitory input will add a branch, with the variable conductance controlled by the parameters, step σ and time constant τ .…”

Section: Neuron Modelmentioning

confidence: 99%

A Modeling Study of Notch Noise Responses of Type III Units in the Gerbil Dorsal Cochlear Nucleus

Zheng

Voigt

2006

Ann Biomed Eng

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Abstract-A computational model of the neural circuitry of the gerbil dorsal cochlear nucleus (DCN), based on the MacGregor's neuromime model, was used to simulate type III unit (P-cell) responses to notch noise stimuli. The DCN patch model is based on a previous computational model of the cat DCN [Hancock, K. E., and H. F. Voigt. Ann. Biomed. Eng. 27:73-87, 1999]. According to the experimental study of Parsons et al. [Ann. Biomed. Eng. 29:887-896, 2001], the responses of gerbil DCN type III units to notch noise stimuli are similar to those of cat DCN type IV units, which are thought to be spectral notch detectors. This suggests that type III units in the gerbil DCN may serve as spectral notch detectors. In this modeling study, a simplified notch noise response plot-spike discharge rate vs. notch cutoff frequency plot-was used to compare model responses to the experimental results. Parameter estimation and sensitivity analysis of three connection parameters within the DCN patch have been studied and shows the model is robust, providing reasonable fits to the experimental data from 14 of 15 type III units examined [work supported by a grant from NIDCD, Boston University's Biomedical Engineering department and Hearing Research Center].

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Neural Modeling

Cited by 68 publications

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Inositol 1,4,5-Trisphosphate-Dependent Ca²⁺Threshold Dynamics Detect Spike Timing in Cerebellar Purkinje Cells

Inositol 1,4,5-Trisphosphate-Dependent Ca²⁺Threshold Dynamics Detect Spike Timing in Cerebellar Purkinje Cells

Simulation system of spinal cord motor nuclei and associated nerves and muscles, in a Web-based architecture

A Modeling Study of Notch Noise Responses of Type III Units in the Gerbil Dorsal Cochlear Nucleus

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Neural Modeling

Cited by 68 publications

References 0 publications

Inositol 1,4,5-Trisphosphate-Dependent Ca2+Threshold Dynamics Detect Spike Timing in Cerebellar Purkinje Cells

Inositol 1,4,5-Trisphosphate-Dependent Ca2+Threshold Dynamics Detect Spike Timing in Cerebellar Purkinje Cells

Simulation system of spinal cord motor nuclei and associated nerves and muscles, in a Web-based architecture

A Modeling Study of Notch Noise Responses of Type III Units in the Gerbil Dorsal Cochlear Nucleus

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Product

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Inositol 1,4,5-Trisphosphate-Dependent Ca²⁺Threshold Dynamics Detect Spike Timing in Cerebellar Purkinje Cells

Inositol 1,4,5-Trisphosphate-Dependent Ca²⁺Threshold Dynamics Detect Spike Timing in Cerebellar Purkinje Cells