Norepinephrine tunes prefrontal-thalamic circuitry to modulate avoidance behavior

NIH RePORTER · NIH · R21 · $223,737 · view on reporter.nih.gov ↗

Abstract

Norepinephrine tunes prefrontal-thalamic circuitry to modulate avoidance behavior Abstract Anxiety disorders are the most common mental illness in the U.S., affecting ~18% of the population. However, the underlying mechanisms associated with anxiety remain elusive. Recent evidence has identified the medial prefrontal cortex (mPFC) as a crucial regulator of anxiety and disruption of mPFC-mediated executive functions in anxiety disorders. On the other hand, norepinephrine (NE) has long been associated with stress and anxiety. A morphological study showed a higher density of dopamine beta-hydroxylase (DBH) varicosities in the PFC than in other cortices. However, how the mPFC executes top-down control over other brain regions to regulate anxiety-related approach-avoidance behavior and whether and how this is modulated by norepinephrine (NE) remain unclear. This project will test the innovative concept that mPFC – paraventricular thalamus (mPFC-PVT) circuit is an important previously overlooked target for anxiety and decision-making. Our pilot study suggests that chemogenetically inhibiting mPFC-PVT pathway with DREADD viral victor significantly increased the time spent in the open arm of the elevated plus-maze, indicating a reduction in anxiety-related avoidance behavior. We thus hypothesize that mPFC-pPVT neurons are active during the exploration of aversive environments, which drives avoidance behavior and elicits anxiety-dependent behaviors. We will explore the extent that prefrontal NE signaling modulates this effect. We will investigate the communication between these two regions by using calcium imaging, a detailed DeepLabCut analysis of animal’s behavior (Aim 1) combined with a G- protein-coupled receptor (GPCR) Activation-Based Norepinephrine (GRAB-NE) sensor (Aim 2) for anxiety-like behavior. The GRAB-NE will allow us to monitor prefrontal NE dynamics in real-time in free-behaving animals. The DeepLabCut™ will provide a detailed analysis of an animal’s posture with a sub-millisecond temporal resolution that could be used to determine an animal’s emotional state change. In summary, we address these conceptually innovative questions using state-of-the-art methods, which allow for precise, causal interrogation into the role of this circuit both in vivo and ex vivo in a projection-specific manner.

Key facts

NIH application ID
10451927
Project number
1R21MH129989-01
Recipient
DREXEL UNIVERSITY
Principal Investigator
Wen-Jun Gao
Activity code
R21
Funding institute
NIH
Fiscal year
2022
Award amount
$223,737
Award type
1
Project period
2022-03-07 → 2024-02-29