The study investigates the encoding of internal states and their rate-of-change in the mesoaccumbal dopamine (DA) pathways of mice. Using optogenetics and Neuropixels probes, the researchers found that DA neurons in the medial ventral tegmental area (mVTA) and lateral ventral tegmental area (lVTA) exhibit distinct activity patterns during reward-seeking behavior. mVTA DA neurons showed sustained activity, while lVTA DA neurons exhibited transient responses. These neural activity patterns matched the patterns of DA release in the nucleus accumbens (NAc), with sustained and transient DA release in the NAcMed and NAcLat, respectively. The study proposes a model where the brain uses two parallel lines for proportional-differential encoding of a state variable and its temporal dynamics. This model suggests that mVTA DA neurons encode the state, while lVTA DA neurons encode the rate-of-change of the state. The findings provide insights into how the brain processes and responds to changes in reward expectation and prediction errors.The study investigates the encoding of internal states and their rate-of-change in the mesoaccumbal dopamine (DA) pathways of mice. Using optogenetics and Neuropixels probes, the researchers found that DA neurons in the medial ventral tegmental area (mVTA) and lateral ventral tegmental area (lVTA) exhibit distinct activity patterns during reward-seeking behavior. mVTA DA neurons showed sustained activity, while lVTA DA neurons exhibited transient responses. These neural activity patterns matched the patterns of DA release in the nucleus accumbens (NAc), with sustained and transient DA release in the NAcMed and NAcLat, respectively. The study proposes a model where the brain uses two parallel lines for proportional-differential encoding of a state variable and its temporal dynamics. This model suggests that mVTA DA neurons encode the state, while lVTA DA neurons encode the rate-of-change of the state. The findings provide insights into how the brain processes and responds to changes in reward expectation and prediction errors.