Glutamate is required for depression but not potentiation of long-term presynaptic function
Abstract
Hebbian plasticity is thought to require glutamate signalling. We show this is not the case for hippocampal presynaptic long-term potentiation (LTPpre), which is expressed as an increase in transmitter release probability (Pr). We find that LTPpre can be induced by pairing pre- and postsynaptic spiking in the absence of glutamate signalling. LTPpre induction involves a non-canonical mechanism of retrograde nitric oxide signalling, which is triggered by Ca2+ influx from L-type voltage-gated Ca2+ channels, not postsynaptic NMDA receptors (NMDARs), and does not require glutamate release. When glutamate release occurs, it decreases Pr by activating presynaptic NMDARs, and promotes presynaptic long-term depression. Net changes in Pr, therefore, depend on two opposing factors: 1) Hebbian activity, which increases Pr, and 2) glutamate release, which decreases Pr. Accordingly, release failures during Hebbian activity promote LTPpre induction. Our findings reveal a novel framework of presynaptic plasticity that radically differs from traditional models of postsynaptic plasticity.
Article and author information
Author details
Funding
Medical Research Council
- Nigel Emptage
Biotechnology and Biological Sciences Research Council
- Nigel Emptage
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2017, Padamsey et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 5,694
- views
-
- 731
- downloads
-
- 32
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Further reading
-
- Computational and Systems Biology
- Neuroscience
Accumulating evidence to make decisions is a core cognitive function. Previous studies have tended to estimate accumulation using either neural or behavioral data alone. Here, we develop a unified framework for modeling stimulus-driven behavior and multi-neuron activity simultaneously. We applied our method to choices and neural recordings from three rat brain regions—the posterior parietal cortex (PPC), the frontal orienting fields (FOF), and the anterior-dorsal striatum (ADS)—while subjects performed a pulse-based accumulation task. Each region was best described by a distinct accumulation model, which all differed from the model that best described the animal’s choices. FOF activity was consistent with an accumulator where early evidence was favored while the ADS reflected near perfect accumulation. Neural responses within an accumulation framework unveiled a distinct association between each brain region and choice. Choices were better predicted from all regions using a comprehensive, accumulation-based framework and different brain regions were found to differentially reflect choice-related accumulation signals: FOF and ADS both reflected choice but ADS showed more instances of decision vacillation. Previous studies relating neural data to behaviorally inferred accumulation dynamics have implicitly assumed that individual brain regions reflect the whole-animal level accumulator. Our results suggest that different brain regions represent accumulated evidence in dramatically different ways and that accumulation at the whole-animal level may be constructed from a variety of neural-level accumulators.
-
- Neuroscience
Moment-to-moment neural variability has been shown to scale positively with the complexity of stimulus input. However, the mechanisms underlying the ability to align variability to input complexity are unknown. Using a combination of behavioral methods, computational modeling, fMRI, MR spectroscopy, and pharmacological intervention, we investigated the role of aging and GABA in neural variability during visual processing. We replicated previous findings that participants expressed higher variability when viewing more complex visual stimuli. Additionally, we found that such variability modulation was associated with higher baseline visual GABA levels and was reduced in older adults. When pharmacologically increasing GABA activity, we found that participants with lower baseline GABA levels showed a drug-related increase in variability modulation while participants with higher baseline GABA showed no change or even a reduction, consistent with an inverted-U account. Finally, higher baseline GABA and variability modulation were jointly associated with better visual-discrimination performance. These results suggest that GABA plays an important role in how humans utilize neural variability to adapt to the complexity of the visual world.