Mechanisms and functional roles of glutamatergic synapse diversity in a cerebellar circuit.
Abstract
Synaptic currents display a large degree of heterogeneity of their temporal characteristics,
but the functional role of such heterogeneities remains unknown. We investigated in
rat cerebellar slices synaptic currents in Unipolar Brush Cells (UBCs), which generate
intrinsic mossy fibers relaying vestibular inputs to the cerebellar cortex. We show
that UBCs respond to sinusoidal modulations of their sensory input with heterogeneous
amplitudes and phase shifts. Experiments and modeling indicate that this variability
results both from the kinetics of synaptic glutamate transients and from the diversity
of postsynaptic receptors. While phase inversion is produced by an mGluR2-activated
outward conductance in OFF-UBCs, the phase delay of ON UBCs is caused by a late rebound
current resulting from AMPAR recovery from desensitization. Granular layer network
modeling indicates that phase dispersion of UBC responses generates diverse phase
coding in the granule cell population, allowing climbing-fiber-driven Purkinje cell
learning at arbitrary phases of the vestibular input.
Type
Journal articleSubject
AMPA receptorcerebellum
computational model
desensitization
metabotropic receptor
neuroscience
rat
sensory processing
Permalink
https://hdl.handle.net/10161/15104Published Version (Please cite this version)
10.7554/eLife.15872Publication Info
Zampini, Valeria; Liu, Jian K; Diana, Marco A; Maldonado, Paloma P; Brunel, Nicolas;
& Dieudonné, Stéphane (2016). Mechanisms and functional roles of glutamatergic synapse diversity in a cerebellar
circuit. Elife, 5. 10.7554/eLife.15872. Retrieved from https://hdl.handle.net/10161/15104.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
Collections
More Info
Show full item recordScholars@Duke
Nicolas Brunel
Professor of Neurobiology
We use theoretical models of brain systems to investigate how they process and learn
information from their inputs. Our current work focuses on the mechanisms of learning
and memory, from the synapse to the network level, in collaboration with various experimental
groups. Using methods fromstatistical physics, we have shown recently that the synapticconnectivity
of a network that maximizes storage capacity reproducestwo key experimentally observed
features: low connection proba

Articles written by Duke faculty are made available through the campus open access policy. For more information see: Duke Open Access Policy
Rights for Collection: Scholarly Articles
Works are deposited here by their authors, and represent their research and opinions, not that of Duke University. Some materials and descriptions may include offensive content. More info