Contributions of Dorsal/Ventral Hippocampus and Dorsolateral/Dorsomedial Striatum to Interval Timing

Humans and animals have remarkable capabilities in keeping time and using time as a guide to orient their learning and decision making. Psychophysical models of timing and time perception have been proposed for decades and have received behavioral, anatomical and pharmacological data support. However, despite numerous studies that aimed at delineating the neural underpinnings of interval timing, a complete picture of the neurobiological network of timing in the seconds-to-minutes range remains elusive. Based on classical interval timing protocols and proposing a Timing, Immersive Memory and Emotional Regulation (TIMER) test battery, the author investigates the contributions of the dorsal and ventral hippocampus as well as the dorsolateral and the dorsomedial striatum to interval timing by comparing timing performances in mice after they received cytotoxic lesions in the corresponding brain regions. On the other hand, a timing-based theoretical framework for the emergence of conscious experience that is closely related to the function of the claustrum is proposed so as to serve both biological guidance and the research and evolution of “strong” artificial intelligence. Finally, a new “Double Saturation Model of Interval Timing” that integrates the direct- and indirect- pathways of striatum is proposed to explain the set of empirical findings.

Data-Driven Motion Detection and Characterization in PET Brain Scans Using List Mode

Head motion during a Positron Emission Tomography (PET) brain scan can considerably degrade image quality. External motion-tracking devices have proven successful in minimizing this effect, but the associated time, maintenance, and workflow changes inhibit their widespread clinical use. List-mode PET acquisition allows for the retroactive analysis of coincidence events on any time scale throughout a scan, and therefore potentially offers a data-driven motion detection and characterization technique. An algorithm was developed to parse list-mode data, divide the full acquisition into short scan intervals, and calculate the line-of-response (LOR) midpoint average for each interval. These LOR midpoint averages, known as “radioactivity centroids,” were presumed to represent the center of the radioactivity distribution in the scanner, and it was thought that changes in this metric over time would correspond to intra-scan motion.

Several scans were taken of the 3D Hoffman brain phantom on a GE Discovery IQ PET/CT scanner to test the ability of the radioactivity to indicate intra-scan motion. Each scan incrementally surveyed motion in a different degree of freedom (2 translational and 2 rotational). The radioactivity centroids calculated from these scans correlated linearly to phantom positions/orientations. Centroid measurements over 1-second intervals performed on scans with ~1mCi of activity in the center of the field of view had standard deviations of 0.026 cm in the x- and y-dimensions and 0.020 cm in the z-dimension, which demonstrates high precision and repeatability in this metric. Radioactivity centroids are thus shown to successfully represent discrete motions on the submillimeter scale. It is also shown that while the radioactivity centroid can precisely indicate the amount of motion during an acquisition, it fails to distinguish what type of motion occurred.