ArticleProceedings of the National Academy of Sciences of the United States of America2025
Synaptic integration and competition in the substantia nigra pars reticulata-An experimental and in silico analysis.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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1 citing paper in PubMed.
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Authors and funding
7 authors.
Funding
Abstract
The substantia nigra pars reticulata (SNr) is a primary output for basal ganglia signaling. It plays an important role in the control of movement, integrating inputs from upstream structures in the basal ganglia, before sending organized projections to a range of targets in the midbrain, brainstem, and thalamus. Here, we present a detailed in silico model of the mouse SNr, including its major afferent inputs. The electrophysiological and morphological properties of SNr neurons are characterized in acute brain slices via whole cell patch-clamp recordings and morphological reconstruction. Using reconstructed morphologies, multicompartmental models of single neurons are instantiated within the NEURON simulation environment and populated with relevant modeled ion channels. Model parameters are optimized via an evolutionary algorithm, such that simulated neurons faithfully reproduce recorded electrophysiological behavior. Using the simulation infrastructure software
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