ArticlePLoS computational biology2015
On the firing rate dependency of the phase response curve of rat Purkinje neurons in vitro.
Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
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- Modulation of neuronal dynamics by sustained and activity-dependent continuous-wave near-infrared laser stimulation.Neurophotonics · 2024Article
- Basket to Purkinje Cell Inhibitory Ephaptic Coupling Is Abolished in Episodic Ataxia Type 1.Cells · 2023Article
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- Open-source software for automated rodent behavioral analysis.Frontiers in neuroscience · 2023Review
- Transcranial direct current stimulation of cerebellum alters spiking precision in cerebellar cortex: A modeling study of cellular responses.PLoS computational biology · 2021Article
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- Automatic Adaptation of Model Neurons and Connections to Build Hybrid Circuits with Living Networks.Neuroinformatics · 2020Article
- Homogeneous and Narrow Bandwidth of Spike Initiation in Rat L1 Cortical Interneurons.Frontiers in cellular neuroscience · 2020Article
- Inverse Stochastic Resonance in Cerebellar Purkinje Cells.PLoS computational biology · 2016Article
- Time-invariant feed-forward inhibition of Purkinje cells in the cerebellar cortex in vivo.The Journal of physiology · 2016Article
- Enhanced Sensitivity to Rapid Input Fluctuations by Nonlinear Threshold Dynamics in Neocortical Pyramidal Neurons.PLoS computational biology · 2016Article
- Intrinsic Cellular Properties and Connectivity Density Determine Variable Clustering Patterns in Randomly Connected Inhibitory Neural Networks.Frontiers in neural circuits · 2016Article
- The 40-year history of modeling active dendrites in cerebellar Purkinje cells: emergence of the first single cell "community model".Frontiers in computational neuroscience · 2015Review
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4 authors.
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Abstract
Synchronous spiking during cerebellar tasks has been observed across Purkinje cells: however, little is known about the intrinsic cellular mechanisms responsible for its initiation, cessation and stability. The Phase Response Curve (PRC), a simple input-output characterization of single cells, can provide insights into individual and collective properties of neurons and networks, by quantifying the impact of an infinitesimal depolarizing current pulse on the time of occurrence of subsequent action potentials, while a neuron is firing tonically. Recently, the PRC theory applied to cerebellar Purkinje cells revealed that these behave as phase-independent integrators at low firing rates, and switch to a phase-dependent mode at high rates. Given the implications for computation and information processing in the cerebellum and the possible role of synchrony in the communication with its post-synaptic targets, we further explored the firing rate dependency of the PRC in Purkinje cells. We isolated key factors for the experimental estimation of the PRC and developed a closed-loop approach to reliably compute the PRC across diverse firing rates in the same cell. Our results show unambiguously that the PRC of individual Purkinje cells is firing rate dependent and that it smoothly transitions from phase independent integrator to a phase dependent mode. Using computational models we show that neither channel noise nor a realistic cell morphology are responsible for the rate dependent shift in the phase response curve.
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