Temporal derivative computation in the dorsal raphe network revealed by an experimentally-driven augmented integrate-and-fire modeling framework
- University of Ottawa, Canada
Abstract
By means of an expansive innervation, the serotonin (5-HT) neurons of the dorsal raphe nucleus (DRN) are positioned to enact coordinated modulation of circuits distributed across the entire brain in order to adaptively regulate behavior. Yet the network computations that emerge from the excitability and connectivity features of the DRN are still poorly understood. To gain insight into these computations, we began by carrying out a detailed electrophysiological characterization of genetically-identified mouse 5-HT and somatostatin (SOM) neurons. We next developed a single-neuron modeling framework that combines the realism of Hodgkin-Huxley models with the simplicity and predictive power of generalized integrate-and-fire (GIF) models. We found that feedforward inhibition of 5-HT neurons by heterogeneous SOM neurons implemented divisive inhibition, while endocannabinoid-mediated modulation of excitatory drive to the DRN increased the gain of 5-HT output. Our most striking finding was that the output of the DRN encodes a mixture of the intensity and temporal derivative of its input, and that the temporal derivative component dominates this mixture precisely when the input is increasing rapidly. This network computation primarily emerged from prominent adaptation mechanisms found in 5-HT neurons, including a previously undescribed dynamic threshold. By applying a bottom-up neural network modeling approach, our results suggest that the DRN is particularly apt to encode input changes over short timescales, reflecting one of the salient emerging computations that dominate its output to regulate behavior.
Data availability
Raw data is available on Dryad at https://doi.org/10.5061/dryad.66t1g1k2w. Code to fit models, run simulations, and reproduce figures is available at https://github.com/nauralcodinglab/raphegif.
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Patch-clamp recordings from dorsal raphe neuronsDryad Digital Repository, doi:10.5061/dryad.66t1g1k2w.
Article and author information
Author details
Léa Caya-Bissonnette
Jean-Claude Beique
Funding
Canadian Institutes of Health Research (175325)
- Richard Naud
- Jean-Claude Beique
Canadian Institutes of Health Research (175319)
- Richard Naud
- Jean-Claude Beique
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: All experiments were carried out in accordance with procedures approvedby the University of Ottawa Animal Care and Veterinary Services (protocol numbersCMM-164, CMM-176, CMM-1711, CMM-1743, and CMM-2737). At the beginning of each experiment, animals were deeply anaesthetized using isofluorane to minimize suffering before being euthanized.
Copyright
© 2023, Harkin 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.
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Temporal derivative computation in the dorsal raphe network revealed by an experimentally-driven augmented integrate-and-fire modeling framework
eLife 12:e72951.
https://doi.org/10.7554/eLife.72951
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