ArticleJournal of neurophysiology2012
Biophysical basis of the phase response curve of subthalamic neurons with generalization to other cell types.
Article in Journal of neurophysiology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Model-based design of subthalamic nucleus neurons using hybrid optimization.Journal of neurophysiology · 2026Article
- Neuronal and network resonance in the external globus pallidus.Journal of neurophysiology · 2025Article
- The voltage and spiking responses of subthreshold resonant neurons to structured and fluctuating inputs: persistence and loss of resonance and variability.Biological cybernetics · 2022Review
- Broadband Entrainment of Striatal Low-Threshold Spike Interneurons.Frontiers in neural circuits · 2020Article
- How to correctly quantify neuronal phase-response curves from noisy recordings.Journal of computational neuroscience · 2019Article
- Phase-Dependent Suppression of Beta Oscillations in Parkinson's Disease Patients.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2019Article
- Predicting responses to inhibitory synaptic input in substantia nigra pars reticulata neurons.Journal of neurophysiology · 2018Article
- Predicting the response of striatal spiny neurons to sinusoidal input.Journal of neurophysiology · 2017Article
- Neurons as oscillators.Journal of neurophysiology · 2016Review
- Phase-resetting as a tool of information transmission.Current opinion in neurobiology · 2015Review
- On the firing rate dependency of the phase response curve of rat Purkinje neurons in vitro.PLoS computational biology · 2015Article
- Predicting the responses of repetitively firing neurons to current noise.PLoS computational biology · 2014Article
- Spectral reconstruction of phase response curves reveals the synchronization properties of mouse globus pallidus neurons.Journal of neurophysiology · 2013Article
- Active decorrelation in the basal ganglia.Neuroscience · 2013Review
- Effect of sharp jumps at the edges of phase response curves on synchronization of electrically coupled neuronal oscillators.PloS one · 2013Article
- Optimal number of stimulation contacts for coordinated reset neuromodulation.Frontiers in neuroengineering · 2013Article
- Desynchronization boost by non-uniform coordinated reset stimulation in ensembles of pulse-coupled neurons.Frontiers in computational neuroscience · 2013Article
- Phase response curves of subthalamic neurons measured with synaptic input and current injection.Journal of neurophysiology · 2012Article
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2 authors.
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Abstract
Experimental evidence indicates that the response of subthalamic neurons to excitatory postsynaptic potentials (EPSPs) is well described by their infinitesimal phase response curves (iPRC). However, the factors controlling the shape of that iPRC, and hence controlling the way subthalamic neurons respond to synaptic input, are unclear. We developed a biophysical model of subthalamic neurons to aid in the understanding of their iPRCs; this model exhibited an iPRC type common to many subthalamic cells. We devised a method for deriving its iPRC from its biophysical properties that clarifies how these different properties interact to shape the iPRC. This method revealed why the response of subthalamic neurons is well approximated by their iPRCs and how that approximation becomes less accurate under strong fluctuating input currents. It also connected iPRC structure to aspects of cellular physiology that could be estimated in simple current-clamp experiments. This allowed us to directly compare the iPRC predicted by our theory with the iPRC estimated from the response to EPSPs or current pulses in individual cells. We found that theoretically predicted iPRCs agreed well with estimates derived from synaptic stimuli, but not with those estimated from the response to somatic current injection. The difference between synaptic currents and those applied experimentally at the soma may arise from differences in the dynamics of charge redistribution on the dendrites and axon. Ultimately, our approach allowed us to identify novel ways in which voltage-dependent conductances interact with AHP conductances to influence synaptic integration that will apply to a wide range of cell types.
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