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State-dependent activity dynamics of hypothalamic stress effector neurons.

Authors :
Ichiyama A
Mestern S
Benigno GB
Scott KE
Allman BL
Muller L
Inoue W
Source :
ELife [Elife] 2022 Jun 30; Vol. 11. Date of Electronic Publication: 2022 Jun 30.
Publication Year :
2022

Abstract

The stress response necessitates an immediate boost in vital physiological functions from their homeostatic operation to an elevated emergency response. However, the neural mechanisms underlying this state-dependent change remain largely unknown. Using a combination of in vivo and ex vivo electrophysiology with computational modeling, we report that corticotropin releasing hormone (CRH) neurons in the paraventricular nucleus of the hypothalamus (PVN), the effector neurons of hormonal stress response, rapidly transition between distinct activity states through recurrent inhibition. Specifically, in vivo optrode recording shows that under non-stress conditions, CRH <subscript>PVN</subscript> neurons often fire with rhythmic brief bursts (RB), which, somewhat counterintuitively, constrains firing rate due to long (~2 s) interburst intervals. Stressful stimuli rapidly switch RB to continuous single spiking (SS), permitting a large increase in firing rate. A spiking network model shows that recurrent inhibition can control this activity-state switch, and more broadly the gain of spiking responses to excitatory inputs. In biological CRH <subscript>PVN</subscript> neurons ex vivo, the injection of whole-cell currents derived from our computational model recreates the in vivo-like switch between RB and SS, providing direct evidence that physiologically relevant network inputs enable state-dependent computation in single neurons. Together, we present a novel mechanism for state-dependent activity dynamics in CRH <subscript>PVN</subscript> neurons.<br />Competing Interests: AI, SM, GB, KS, BA, LM, WI No competing interests declared<br /> (© 2022, Ichiyama et al.)

Details

Language :
English
ISSN :
2050-084X
Volume :
11
Database :
MEDLINE
Journal :
ELife
Publication Type :
Academic Journal
Accession number :
35770968
Full Text :
https://doi.org/10.7554/eLife.76832