Development of an MRI-Compatible Nasal Drug Delivery Method for Probing Nicotine Addiction Dynamics

Substance abuse is a fundamentally dynamic disease, characterized by repeated oscillation between craving, drug self-administration, reward, and satiety. To model nicotine addiction as a control system, a magnetic resonance imaging (MRI)-compatible nicotine delivery system is needed to elicit cyclical cravings. Using a concentric nebulizer, inserted into one nostril, we delivered each dose equivalent to a single cigarette puff by a syringe pump. A control mechanism permits dual modes: one delivers puffs on a fixed interval programmed by researchers; with the other, subjects press a button to self-administer each nicotine dose. We tested the viability of this delivery method for studying the brain’s response to nicotine addiction in three steps. First, we established the pharmacokinetics of nicotine delivery, using a dosing scheme designed to gradually achieve saturation. Second, we lengthened the time between microdoses to elicit craving cycles, using both fixed-interval and subject-driven behavior. Finally, we demonstrate a potential application of our device by showing that a fixed-interval protocol can reliably identify neuromodulatory targets for pharmacotherapy or brain stimulation. Our MRI-compatible nasal delivery method enables the measurement of neural circuit responses to drug doses on a single-subject level, allowing the development of data-driven predictive models to quantify individual dysregulations of the reward control circuit causing addiction.

Abandoned Object Detection

In the current fast paced life, security has become an important aspect which cannot be ignored. One of the usually neglected but important division of security in public areas involves the unattended objects. Bombs and other harmful objects that are incendiary cause great harm. And in most of the cases such objects are left unattended for some time before causing harm. As such, unattended objects should be given importance and must be checked to ensure safety. This paper shows a method to identify unattended objects in public areas. This is done by comparing a fixed/initial background frame with frames after a fixed interval. If there is a change in the frames, then that refers to an attended object. No change observed, proves an unattended object which is highlighted by a box. This is done with the help of blob analysis. This paper does this with the help of MATLAB. MATLAB being a software accessible to wide range of people provides an easy process with moderate results. It uses a wide range of predefined functions and toolboxes to do this.