What's so funny? An evaluation of the relations among humour use, mirth, and depressive symptomatology

Humour production and showing mirth (i.e., smiling and laughing) confer prosocial advantages. However, there is a paucity of literature evaluating how humour manifests in psychopathology. Humour and mirth may be especially relevant in depression, wherein profound impairments are evident in emotional and social functioning. Chapters 2 and 3 present correlational and predictive relations of depressive, social anxiety, and social anhedonia symptoms with humour styles, and consider the role of motivational systems and expressivity of positive affect as they relate to humour. As expected, symptoms and avoidance-based motivation were positively related to maladaptive humour styles and negatively related to adaptive humour styles. Interestingly, the pattern of relations shifted when considered among individuals in a depressive episode; acutely depressed individuals generally shy away from any humour style rather than gravitating toward specific styles. In a mediation model, the inverse relation between depressive symptoms and affiliative humour was fully mediated by approach-based motivation and expressivity of positive emotions. Chapters 4 and 5 examined subjective and observed mirth responses (facial affect and laughter) demonstrated by depressed and healthy comparison groups. Relative to non-depressed individuals, depressed persons reported less enjoyment, lower ratings of funniness, and fewer instances and shorter durations of positive facial affect and laughter when viewing humourous videos. There was no significant change in retrospective ratings of enjoyment and funniness at a one-week follow-up. The pattern of responsivity by depressed persons shifted when they viewed humourous videos while hearing others laughing. Both groups demonstrated more mirth when hearing others laugh; there were no differences between groups on mirthful behaviours. The one exception was that the total duration of laugher produced by depressed individuals was shorter than that produced by individuals in the healthy comparison group. This research project demonstrates that facets of depressive symptomatology are differentially associated with humour use and depressed individuals show blunted emotional responsivity to humourous stimuli. However, the pattern of reduced affective responsivity is context specific in that it fluctuates in response to hearing others’ laughter. These findings have important implications for the conceptualization of depression and the subsequent avenues for the treatment of individuals with depression.

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.