Synaptic input sequence discrimination on behavioral time-scales mediated by reaction-diffusion chemistry in dendrites
Abstract
Sequences of events are ubiquitous in sensory, motor, and cognitive function. Key computational operations, including pattern recognition, event prediction, and plasticity, involve neural discrimination of spatio-temporal sequences. Here we show that synaptically-driven reaction-diffusion pathways on dendrites can perform sequence discrimination on behaviorally relevant time-scales. We used abstract signaling models to show that selectivity arises when inputs at successive locations are aligned with, and amplified by, propagating chemical waves triggered by previous inputs. We incorporated biological detail using sequential synaptic input onto spines in morphologically, electrically, and chemically detailed pyramidal neuronal models based on rat data. Again, sequences were recognized, and local channel modulation downstream of putative sequence-triggered signaling could elicit changes in neuronal firing. We predict that dendritic sequence-recognition zones occupy 5 to 30 microns and recognize time-intervals of 0.2 to 5s. We suggest that this mechanism provides highly parallel and selective neural computation in a functionally important time range.
Data availability
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NeuroMorpho.orgPublicly available at NeuroMorpho.org (accession no: NMO_09573).
Article and author information
Author details
Funding
National Centre for Biological Sciences (Plan 4142)
- Upinder Singh Bhalla
Department of Science and Technology, Ministry of Science and Technology (SR/CSI/66/2013)
- Upinder Singh Bhalla
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Frances K Skinner, University Health Network, Canada
Version history
- Received: February 7, 2017
- Accepted: April 17, 2017
- Accepted Manuscript published: April 19, 2017 (version 1)
- Accepted Manuscript updated: April 27, 2017 (version 2)
- Version of Record published: May 11, 2017 (version 3)
Copyright
© 2017, Bhalla
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.
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Further reading
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- Neuroscience
Probing memory of a complex visual image within a few hundred milliseconds after its disappearance reveals significantly greater fidelity of recall than if the probe is delayed by as little as a second. Classically interpreted, the former taps into a detailed but rapidly decaying visual sensory or ‘iconic’ memory (IM), while the latter relies on capacity-limited but comparatively stable visual working memory (VWM). While iconic decay and VWM capacity have been extensively studied independently, currently no single framework quantitatively accounts for the dynamics of memory fidelity over these time scales. Here, we extend a stationary neural population model of VWM with a temporal dimension, incorporating rapid sensory-driven accumulation of activity encoding each visual feature in memory, and a slower accumulation of internal error that causes memorized features to randomly drift over time. Instead of facilitating read-out from an independent sensory store, an early cue benefits recall by lifting the effective limit on VWM signal strength imposed when multiple items compete for representation, allowing memory for the cued item to be supplemented with information from the decaying sensory trace. Empirical measurements of human recall dynamics validate these predictions while excluding alternative model architectures. A key conclusion is that differences in capacity classically thought to distinguish IM and VWM are in fact contingent upon a single resource-limited WM store.
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- Neuroscience
Our ability to recall details from a remembered image depends on a single mechanism that is engaged from the very moment the image disappears from view.