This paper presents a novel compressive sensing framework for recording brain dopamine levels with fast-scan cyclic voltammetry (FSCV) at a carbon-fiber microelectrode. Termed compressive FSCV (C-FSCV), this approach compressively samples the measured total current in each FSCV scan and performs basic FSCV processing steps, e.g., background current averaging and subtraction, directly with compressed measurements. The resulting background-subtracted faradaic currents, which are shown to have a block-sparse representation in the discrete cosine transform domain, are next reconstructed from their compressively sampled counterparts with the block sparse Bayesian learning algorithm. Using a previously recorded dopamine dataset, consisting of electrically evoked signals recorded in the dorsal striatum of an anesthetized rat, the C-FSCV framework is shown to be efficacious in compressing and reconstructing brain dopamine dynamics and associated voltammograms with high fidelity (correlation coefficient, ), while achieving compression ratio, CR, values as high as ~ 5. Moreover, using another set of dopamine data recorded 5 minutes after administration of amphetamine (AMPH) to an ambulatory rat, C-FSCV once again compresses (CR = 5) and reconstructs the temporal pattern of dopamine release with high fidelity ( ), leading to a true-positive rate of 96.4% in detecting AMPH-induced dopamine transients.

Attention deficit hyperactivity disorder (ADHD) is thought to be associated with dysfunction of ascending catecholamine neuronal systems, particularly dopamine (DA) and norepinephrine (NE). Dysfunction of these catecholamine neurons innervating the prefrontal cortex is hypothesized to underlie impaired executive functions. Dysfunction of the DA neurons innervating the striatum is additionally hypothesized to underlie deficits in motivation and reinforcement learning. However, mechanisms of action of therapeutic drugs used for treating ADHD have mainly focused on catecholamines in the prefrontal cortex and have not adequately addressed the role played by DA signaling in the striatum. Stimulants such as Adderall® and Ritalin® are chemically considered "amphetamines". While effective for treating ADHD, there are grave concerns about stimulant abuse with this drug class. The more recently developed Strattera®, a non-stimulant used to treat AHDH, offers a non-addictive alterative. However, how Strattera® acts pharmacologically in the brain is not completely established. Our study investigates the brain mechanisms of Strattera® and specifically examines how Strattera® acts on brain dopamine neurons, which are important for learning. The second part of the study investigates the mechanism of action of the stimulant class of drugs. Stimulants act on brain dopamine neurons by blocking a protein that removes dopamine after its release to terminal neurotransmission. This action is thought to underlie the addictive potential of stimulants. We are pursuing a novel action of stimulants: increasing the dopamine released by action potential dependent exocytosis. This action would increase brain dopamine, thereby mediating some of the pharmacological effects of stimulants. Collectively, our studies provide insight into how important drugs used clinically and often are abused act on the brain. The long-term goal is to distinguish the clinically efficacious component of these drugs from their addictive potential, which should help drive development of safer drugs for treating ADHD.