ArticleeLife2019
Thalamocortical synapses in the cat visual system in vivo are weak and unreliable.
Article in eLife, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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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Who cites it
6 citing papers in PubMed, 7 citations in OpenAlex.
- A geniculocortical circuit model predicts functional organization underlying efficient spatial frequency coding in the mouse visual system.bioRxiv : the preprint server for biology · 2026Article
- Compressive sensing of functional connectivity maps from patterned optogenetic stimulation of neuronal ensembles.Patterns (New York, N.Y.) · 2023Article
- Mapping thalamic innervation to individual L2/3 pyramidal neurons and modeling their 'readout' of visual input.Nature neuroscience · 2023Article
- Sparsely Distributed, Pre-synaptic Kv3 KFrontiers in cellular neuroscience · 2021Article
- Article
- Model-Based Inference of Synaptic Transmission.Frontiers in synaptic neuroscience · 2019Review
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
The thalamocortical synapse of the visual system has been central to our understanding of sensory computations in the cortex. Although we have a fair understanding of the functional properties of the pre and post-synaptic populations, little is known about their synaptic properties, particularly in vivo. We used simultaneous recordings in LGN and V1 in cat in vivo to characterize the dynamic properties of thalamocortical synaptic transmission in monosynaptically connected LGN-V1 neurons. We found that thalamocortical synapses in vivo are unreliable, highly variable and exhibit short-term plasticity. Using biologically constrained models, we found that variable and unreliable synapses serve to increase cortical firing by means of increasing membrane fluctuations, similar to high conductance states. Thus, synaptic variability and unreliability, rather than acting as system noise, do serve a computational function. Our characterization of LGN-V1 synaptic properties constrains existing mathematical models, and mechanistic hypotheses, of a fundamental circuit in computational neuroscience.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.