To decode and to modulate the emotional aspect of pain
- Institution
- Massachusetts Institute of Technology, MA
- Principal investigator
- Fan Wang
- Funding
- $591K
- Duration
- 2025–2029
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Still being scored
Abstract
To decode and to modulate the emotional aspect of pain Abstract It is well known that pain contains both a sensory-discriminative and an emotional component. While the sensory-discriminative aspects of pain are easily quantifiable, quantitative measures of “emotions” are generally lacking, particularly in preclinical animal models where subjects cannot verbally relay their emotional state. Notably, emotions are all intimately associated with bodily autonomic responses. In preliminary studies in mice, we have measured heart rate responses in acute pain models and discovered that formalin pain dramatically reduces heart rate variability (HRV) while moderately affects heart rate (HR). In aim 1, we will systematically characterize several autonomic responses to identify key autonomic signatures for different mouse pain models. Furthermore, we previously identified general anesthesia activated central amygdala (CeA) neurons (CeAGA) as potent pain-suppressing neurons. Exciting preliminary data revealed that activating CeAGA neurons reduced HR and significantly increased HRV, suggesting that the pain-suppression effect of these neurons is in part due to reversing pain-elicited autonomic responses. In aim 2, we will perform in vivo imaging and functional manipulations of two populations of CeA neurons (CeAGA and CeASst) with concurrent measurements of autonomic responses and behavior in acute and chronic pain models to determine how their activity is causally linked to different patterns of autonomic and behavioral responses. Finally, it is known that past pain experience leads to hypervigilant and anticipatory responses to similar sensory stimuli. Human studies suggest that receiving information about upcoming pain can preemptively elicit autonomic responses. We have established a new pain anticipation paradigm in mice where we can clearly observe the nocebo effect. We also identified pain anticipatory neural signals in the midline thalamic nuclei (MT). In aim 3, we will dissect the role of specific populations of MT neurons in driving anticipatory autonomic and behavioral responses when mice expect upcoming pain and the consequent nocebo responses using in vivo imaging and functional manipulations. We expect that the proposed research will break new ground in our understanding of the emotional aspects of pain. Ultimately, this knowledge can be used to develop non-addictive, non-surgical chronic pain treatments that remove the negative affective component of pain.
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