Dopamine neurons (DNs) are key regulators of motivated behaviors, and defects in dopamine signaling may underlie some psychiatric disorders including addiction, depression, and schizophrenia, as well as neurological disorders such as Parkinson's. Much of the work in this area has been based on the dogma that DNs encode reward prediction errors (RPE) and that they do so in a uniform manner. However, work from several groups, including ours, indicates that DNs projecting to different targets exhibit distinct properties and serve distinct functions. In this proposal, we aim to link the diversity of DNs defined by their connectivity and activity with their functions. One recent example, drawn from our work, is that DNs projecting to the posterior `tail' of the striatum (TS) differ in many ways from DNs projecting to the ventral striatum (VS) and other regions. VS- projecting DNs, which signal `canonical' RPEs, are activated by reward and inhibited by negative events. By contrast, TS-projecting DNs are activated by novel stimuli and a subset of negative events. Here, based on our initial results, we will compare VS- and TS-projecting DNs with regard to their (1) activity, (2) function during behaviors, and (3) mechanism underlying the generation of the activities. We will test the main hypothesis that TS-projecting DNs integrate a unique set of inputs, signal threat prediction errors, and positively reinforces threat predictions or avoidance behaviors.
Specific Aim 1 will characterize the activity of projection-specific DNs during behavior.
Specific Aim 2 will demonstrate the causal link between the function and the activity patterns of projection-specific DNs.
Specific Aim 3 will aim to understanding neural circuit mechanisms that generate distinct response patterns of DNs in a projection-specific manner. If our main hypothesis holds true, the results will demonstrate that dopamine in VS and TS operates in a similar manner at the algorithmic level: in both systems, an increase in dopamine results in facilitation of certain behaviors (approach or avoidance) or stimulus-based predictions (of outcome value or a threat). The methods and results of the proposed study will pave the way for looking at other DN populations in the future. This will further the goal of elucidating a unifying theory regarding the computational algorithm by which multiple DN populations function. We expect these results to provide insights into dopaminergic defects and even dopamine-directed therapeutic interventions in brain disorders.
Malfunction of the midbrain dopamine system is associated with a variety of pathological conditions including depression, anhedomia, apathy, schizophrenia, addiction, eating disorders and Parkinson's disease. In particular, aberrant dopamine responses to salient events have been implicated in addiction, schizophrenia and other mental disorders. This study will allow us to better understand how dopamine responses are suppressed when they should not respond, that is, when reward expectation is high in time and in space. Understanding dopamine signaling in the healthy brain is essential to understanding states of aberrant dopamine signaling.