ArticleFrontiers in neuroinformatics2021
Comparing the Electrophysiology and Morphology of Human and Mouse Layer 2/3 Pyramidal Neurons With Bayesian Networks.
Article in Frontiers in neuroinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed, 17 citations in OpenAlex.
- A framework for comparative analysis of human and mouse cortical neuron dendrites in corresponding brain regions.Nature neuroscience · 2026Article
- Dendritic morphology and synaptic nonlinearities enhance functional complexity in human cortical neurons.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Mechanistic explanation of neuroplasticity using equivalent circuits.Frontiers in computational neuroscience · 2026Article
- Adaptations of the axon initial segment in fast-spiking interneurons of the human neocortex support low action potential thresholds.PLoS biology · 2025Article
- Auditory sensory processing induces cortical and thalamic event-related desynchronization in the mouse.PloS one · 2025Article
- What makes human cortical pyramidal neurons functionally complex.bioRxiv : the preprint server for biology · 2024Article
- Classifying Neuronal Cell Types Based on Shared Electrophysiological Information from Humans and Mice.Neuroinformatics · 2024Article
- A biologically inspired repair mechanism for neuronal reconstructions with a focus on human dendrites.PLoS computational biology · 2024Article
- Morphological screens using aged primary adult neuronal, microglial, and astrocytic cultures to find novel neurotherapeutics.Frontiers in cellular neuroscience · 2023Article
- Reduced expression of the psychiatric risk gene DLG2 (PSD93) impairs hippocampal synaptic integration and plasticity.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2022Article
- Comparing the Electrophysiology and Morphology of Human and Mouse Layer 2/3 Pyramidal Neurons With Bayesian Networks.Frontiers in neuroinformatics · 2021Article
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3 authors at 1 institution in 1 country.
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Abstract
Pyramidal neurons are the most common neurons in the cerebral cortex. Understanding how they differ between species is a key challenge in neuroscience. We compared human temporal cortex and mouse visual cortex pyramidal neurons from the Allen Cell Types Database in terms of their electrophysiology and dendritic morphology. We found that, among other differences, human pyramidal neurons had a higher action potential threshold voltage, a lower input resistance, and larger dendritic arbors. We learned Gaussian Bayesian networks from the data in order to identify correlations and conditional independencies between the variables and compare them between the species. We found strong correlations between electrophysiological and morphological variables in both species. In human cells, electrophysiological variables were correlated even with morphological variables that are not directly related to dendritic arbor size or diameter, such as mean bifurcation angle and mean branch tortuosity. Cortical depth was correlated with both electrophysiological and morphological variables in both species, and its effect on electrophysiology could not be explained in terms of the morphological variables. For some variables, the effect of cortical depth was opposite in the two species. Overall, the correlations among the variables differed strikingly between human and mouse neurons. Besides identifying correlations and conditional independencies, the learned Bayesian networks might be useful for probabilistic reasoning regarding the morphology and electrophysiology of pyramidal neurons.
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