Thursday, April 25, 2024
4/25/2024
Abstract The brain assesses the environment, makes decisions, and turns decisions into behavior. Behavior, or the total outward movement displayed by an organism, is constructed by stitching together small, stereotyped bits of movement, or ‘syllables’ of action. The complexity of innate animal behavior is in part derived from the fact that the dozens or hundreds of syllables that an animal can perform can be flexibly concatenated into a nearly infinite variety of syllable sequences. Some sequences are deterministic — with syllable B always following syllable A in time — while others are constructed more probabilistically. Escape behaviors, for example, are typically more determined, while foraging is composed in a more probabilistic manner. In the mammalian brain, the dorsolateral striatum (DLS) is responsible for concatenating syllables into sequences of behavior, but it is unclear is how the DLS strings actions together into either variable or stereotyped sequences. One hypothesis is that the release of the neurotransmitter dopamine in DLS is capable of carrying information about – and perhaps regulates – how the DLS chooses to construct behavioral sequences. However, testing this hypothesis requires developing a quantitative description of how continuous behavior is segmented into discrete syllable movements. Recent work in our lab has developed an algorithm called Motion Sequencing, or ‘MoSeq’ for short, which objectively and automatically segments mouse behavior into its component syllables. Since MoSeq affords us fine-timescale information regarding the identity of each syllable and the temporal boundaries between one syllable and the next, we can now explore how dopamine activity in the DLS relates to the sequence structure of ongoing mouse behavior. Here, I propose to combine the MoSeq’s segmentation pipeline with neural imaging and manipulation approaches to investigate the relationship between striatal dopamine and behavioral sequence variability. Based upon preliminary data, I hypothesize that high levels of dopamine release both predicts the expression of variable sequences, and causally influences sequence variability during spontaneous behavior. In Aim 1, I will simultaneously perform recordings of dopamine release in DLS and MoSeq behavioral recordings; I will investigate how syllable-associated dopamine relates to the variability of the behavioral sequence in which a syllable is embedded. In Aim 2, I will leverage a real-time variant of the MoSeq platform, in which a syllable can be detected as an animal is performing it. I will stimulate DLS-projecting dopaminergic axons during the expression of specific target syllables and examine changes in the variability of syllables that follow the target. These experiments will reveal fast-timescale relationships between striatal dopamine and behavioral sequences and will advance our understanding of how animals are able to flexibly construct sequences of syllables on a moment-to-moment basis.
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