Computational models for improved diagnosis and prognosis of stroke using robot-based biomarkers

Stroke is a leading cause of death and permanent disability worldwide, affecting millions of individuals. Traditional clinical scores for assessment of stroke-related impairments are inherently subjective and limited by inter-rater and intra-rater reliability, as well as floor and ceiling effects. In contrast, robotic technologies provide objective, highly repeatable tools for quantification of neurological impairments following stroke. KINARM is an exoskeleton robotic device that provides objective, reliable tools for assessment of sensorimotor, proprioceptive and cognitive brain function by means of a battery of behavioral tasks. As such, KINARM is particularly useful for assessment of neurological impairments following stroke. This thesis introduces a computational framework for assessment of neurological impairments using the data provided by KINARM. This is done by achieving two main objectives. First, to investigate how robotic measurements can be used to estimate current and future abilities to perform daily activities for subjects with stroke. We are able to predict clinical scores related to activities of daily living at present and future time points using a set of robotic biomarkers. The findings of this analysis provide a proof of principle that robotic evaluation can be an effective tool for clinical decision support and target-based rehabilitation therapy. The second main objective of this thesis is to address the emerging problem of long assessment time, which can potentially lead to fatigue when assessing subjects with stroke. To address this issue, we examine two time reduction strategies. The first strategy focuses on task selection, whereby KINARM tasks are arranged in a hierarchical structure so that an earlier task in the assessment procedure can be used to decide whether or not subsequent tasks should be performed. The second strategy focuses on time reduction on the longest two individual KINARM tasks. Both reduction strategies are shown to provide significant time savings, ranging from 30% to 90% using task selection and 50% using individual task reductions, thereby establishing a framework for reduction of assessment time on a broader set of KINARM tasks. All in all, findings of this thesis establish an improved platform for diagnosis and prognosis of stroke using robot-based biomarkers.

The Function of Intestinal Afferent Neurons in Regulating Satiety During Health and Obesity

Background and aim: Within the gastrointestinal tract, vagal afferents regulate satiety and food intake via chemical and mechanical mechanisms. Cysteinyl Leukotrienes (CysLTs) are lipid mediators that are believed to regulate food intake and body weight. However, the involvement of vagal afferents in this effect remains to be established. Conversely, Glucagon like peptide-1 (GLP-1) is a satiety and incretin peptide hormone. The effect of obesity on GLP-1 mediated gut-brain signaling has yet to be investigated. Since intestinal vagal afferents’ activity is reduced during obesity, it is intriguing to investigate their responses to GLP-1 in such conditions. Methods: Extracellular recordings were performed on intestinal afferents from normal C57Bl6, low fat fed (LFF), and high fat fed (HFF) mice. To examine the effect on neuronal calcium signaling, calcium-imaging experiments were performed on isolated nodose ganglion neurons. Food intake experiments were conducted using LFF and HFF mice. Oral glucose tolerance tests (OGTT) were carried out. Whole cell patch clamp recordings were performed on nodose ganglion neurons from A) normal C57Bl mice to test the effect of CysLTs on membrane excitability, B) LFF and HFF mice to examine GLP-1 effect on membrane excitability during obesity. c-Fos immunohistochemical techniques were performed to measure the level of neuronal activation in the brainstem of both LFF and HFF mice in response to Ex-4. Results: CysLTs increased intestinal afferent firing rate and mechanosensitivity. In single nodose neuron experiments, CysLTs increased excitability. The GLP-1 agonist Ex-4 significantly decreased food intake in LFF but not HFF mice. However, Ex-4 markedly attenuated the rise in blood glucose in both LFF and HFF mice. The observed increase in nerve firing and mechanosensitivity following the application of GLP-1 and Ex-4 was abolished in HFF mice. Cell membrane excitability was significantly increased by Ex-4 in nodose from LFF but not HFF mice. Ex-4 significantly increased the number of activated neurons in the NTS area of LFF mice but not in their HFF counterparts. Conclusion: The previous observations indicate that the role CysLTs play in regulating satiety is likely to be vagally mediated. Also that satiety, but not incretin, effects of GLP-1 are impaired during obesity.