Dataset Information

Mechanical Conflict-Avoidance Assay to Measure Pain Behavior in Mice.

ABSTRACT: Pain comprises of both sensory (nociceptive) and affective (unpleasant) dimensions. In preclinical models, pain has traditionally been assessed using reflexive tests that allow inferences regarding pain's nociceptive component but provide little information about the affective or motivational component of pain. Developing tests that capture these components of pain are therefore translationally important. Hence, researchers need to use non-reflexive behavioral assays to study pain perception at that level. Mechanical conflict-avoidance (MCA) is an established voluntary non-reflexive behavior assay, for studying motivational responses to a noxious mechanical stimulus in a 3 chamber paradigm. A change in a mouse's location preference, when faced with competing noxious stimuli, is used to infer the perceived unpleasantness of bright light versus tactile stimulation of the paws. This protocol outlines a modified version of the MCA assay which pain researchers can use to understand affective-motivational responses in a variety of mouse pain models. Though not specifically described here, our example MCA data use the intraplantar complete Freund's adjuvant (CFA), spared nerve injury (SNI), and a fracture/casting model as pain models to illustrate the MCA procedure.

SUBMITTER: Gaffney CM

PROVIDER: S-EPMC9058981 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

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Mechanical Conflict-Avoidance Assay to Measure Pain Behavior in Mice.

Gaffney Caitlyn M CM Muwanga Gabriella G Shen Huaishuang H Tawfik Vivianne L VL Shepherd Andrew J AJ

Journal of visualized experiments : JoVE 20220218 180

Pain comprises of both sensory (nociceptive) and affective (unpleasant) dimensions. In preclinical models, pain has traditionally been assessed using reflexive tests that allow inferences regarding pain's nociceptive component but provide little information about the affective or motivational component of pain. Developing tests that capture these components of pain are therefore translationally important. Hence, researchers need to use non-reflexive behavioral assays to study pain perception at ...[more]

PMID: 35253785

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Project description:Decisions under threat are crucial to survival and require integration of distinct situational features, such as threat probability and magnitude. Recent evidence from human lesion and neuroimaging studies implicated anterior hippocampus (aHC) and amygdala in approach-avoidance decisions under threat, and linked their integrity to cautious behavior. Here we sought to elucidate how threat dimensions and behavior are represented in these structures. Twenty human participants (11 female) completed an approach-avoidance conflict task during high-resolution fMRI. Participants could gather tokens under threat of capture by a virtual predator, which would lead to token loss. Threat probability (predator wake-up rate) and magnitude (amount of token loss) varied on each trial. To disentangle effects of threat features, and ensuing behavior, we performed a multifold parametric analysis. We found that high threat probability and magnitude related to BOLD signal in left aHC/entorhinal cortex. However, BOLD signal in this region was better explained by avoidance behavior than by these threat features. A priori ROI analysis confirmed the relation of aHC BOLD response with avoidance. Exploratory subfield analysis revealed that this relation was specific to anterior CA2/3 but not CA1. Left lateral amygdala responded to low and high, but not intermediate, threat probability. Our results suggest that aHC BOLD signal is better explained by avoidance behavior than by threat features in approach-avoidance conflict. Rather than representing threat features in a monotonic manner, it appears that aHC may compute approach-avoidance decisions based on integration of situational threat features represented in other neural structures.SIGNIFICANCE STATEMENT An effective threat anticipation system is crucial to survival across species. Natural threats, however, are diverse and have distinct features. To be able to adapt to different modes of danger, the brain needs to recognize these features, integrate them, and use them to modify behavior. Our results disclose the human anterior hippocampus as a likely arbiter of approach-avoidance decisions harnessing compound environmental information while partially replicating previous findings and blending into recent efforts to illuminate the neural basis of approach-avoidance conflict in humans.

Dataset Information

Mechanical Conflict-Avoidance Assay to Measure Pain Behavior in Mice.

Publications

Mechanical Conflict-Avoidance Assay to Measure Pain Behavior in Mice.

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