ArticleScientific reports2019
Alternative classifications of neurons based on physiological properties and synaptic responses, a computational study.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed.
- Conserved Kir channel mechanisms governing intrinsic excitability in human and rodent parvalbumin neurons.Communications biology · 2026Article
- Neuronal identity is not static: An input-driven perspective.PLoS computational biology · 2025Article
- Regulation of input excitability in human and mouse parvalbumin interneurons by Kir potassium channels.bioRxiv : the preprint server for biology · 2025Article
- Neurons of the Central Nucleus of the Amygdala That Express Angiotensin Type 2 Receptors Couple Lowered Blood Pressure with Anxiolysis in Male Mice.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Inhibition of BK channels by GABAb receptors enhances intrinsic excitability of layer 2/3 vasoactive intestinal polypeptide-expressing interneurons in mouse neocortex.The Journal of physiology · 2025Article
- Circuit dynamics of superficial and deep CA1 pyramidal cells and inhibitory cells in freely-moving macaques.bioRxiv : the preprint server for biology · 2024Article
- A nonparametric test of group distributional differences for hierarchically clustered functional data.Biometrics · 2023Article
- Conventional measures of intrinsic excitability are poor estimators of neuronal activity under realistic synaptic inputs.PLoS computational biology · 2021Article
- Homeostatic plasticity and burst activity are mediated by hyperpolarization-activated cation currents and T-type calcium channels in neuronal cultures.Scientific reports · 2021Article
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3 authors.
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Abstract
One of the central goals of today's neuroscience is to achieve the conceivably most accurate classification of neuron types in the mammalian brain. As part of this research effort, electrophysiologists commonly utilize current clamp techniques to gain a detailed characterization of the neurons' physiological properties. While this approach has been useful, it is not well understood whether neurons that share physiological properties of a particular phenotype would also operate consistently under the action of natural synaptic inputs. We approached this problem by simulating a biophysically diverse population of model neurons based on 3 generic phenotypes. We exposed the model neurons to two types of stimulation to investigate their voltage responses under conventional current step protocols and under simulated synaptic bombardment. We extracted standard physiological parameters from the voltage responses elicited by current step stimulation and spike arrival times descriptive of the model's firing behavior under synaptic inputs. The biophysical phenotypes could be reliably identified using classification based on the 'static' physiological properties, but not the interspike interval-based parameters. However, the model neurons associated with the biophysically different phenotypes retained cell type specific features in the fine structure of their spike responses that allowed their accurate classification.
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