Light not only allows us to see but is also fundamental to our health and well-being. Several parameters of light exposure, such as wavelengths, intensity, and timing of exposure, all play an important role on its effects on psychophysiological functions. The way in which studies have previously quantified light (based on intensity), has been found to be inadequate since it does not consider the spectrum of light which influences non-visual effects. Among these non-visual effects, light has been found to have antidepressant effects, however, these effects remain inconsistent for non-seasonal depression and their underlying mechanisms remain elusive. The three research studies in this thesis investigated the effects of light on mood. The first study focused on the direct pathway between light and mood, aiming to predict mood outcomes based on the amount of intrinsically photosensitive retinal ganglion cells (ipRGC) stimulation from polychromatic light in healthy individuals. The second and third studies focused on the indirect pathways, exploring predictors and underlying mechanisms of mood improvements by means of sleep and circadian re-alignment in the context of non-seasonal depression. These studies explored the antidepressant mechanisms of monochromatic light therapy and predictive models of mood improvement. The results from study I (systematic review) suggest that ipRGCs may not be as involved in the mood improvement associated with polychromatic light. Drawing strong conclusions from these results are, however, cautioned. Mood metrics used across the studies were inconsistent and the light sources were not designed to maximally stimulate ipRGCs. The results from study II (open-label trial) support the notion that light therapy does have antidepressant effects in people with non-seasonal depression. The underlying mechanisms for these antidepressant effects may involve improvements in sleep initiation and daytime functioning. Individuals with difficulties with fallings asleep and waking-up may be those that respond most prominently to light therapy. The results from study III (randomized controlled trial) indicate that depression symptoms improved slightly more in the active light therapy condition as opposed to a placebo condition. Although this effect was modest across the overall group, there were considerable inter-individual variations in treatment response. The degree of improvement in mood was associated with improvement in pre-sleep thoughts and the circadian rhythmicity of skin temperature. Short REM latency and worst global subjective sleep were predictive of greater response to light therapy. Overall, further research is required to disentangle the involvement of the different photoreceptors in the mood response to polychromatic light in healthy individuals. Monochromatic light therapy for non-seasonal depression yields overall modest antidepressant effects. Clinical applications of light therapy may benefit from further research investigating differential effects in sub-groups of depression and underlying mechanisms in larger studies.

This thesis examined the borderline personality disorder symptom profiles of teenage girls who were referred to a tertiary child and youth psychiatry clinic. Self-injury and unstable mood are key features of Borderline Personality Disorder (BPD) but are also associated with other disorders such as depression and anxiety disorders. The aim of the larger study was to determine whether BPD can be differentiated from other disorders in a highly comorbid adolescent sample who self-injure. To answer this question, individuals in our sample were grouped based on the pattern of BPD symptom endorsement using a latent class analysis. The subgroups that emerged from our sample were then compared to each other across other clinical measures. Four latent classes were identified. The most impaired class had a high prevalence of BPD (70%). An intermediate class had a significantly higher prevalence of PTSD (41.7%). Another intermediate group had a higher prevalence of anxiety disorders (62%) (Social Phobia and Generalized Anxiety Disorder). The largest class had a low prevalence of all psychiatric disorders. The results indicated that only a small subset of teenage girls who presented with self-injury and unstable mood met criteria for BPD. These girls represented a distinct and severely impaired group with high comorbidity. The subgroups that emerged from our sample provide guidance to clinicians regarding the likelihood of a personality disorder diagnosis in this population and the pattern of emotional difficulties of youth who self-injure. / Thesis / Master of Science (MSc)

Mood disorders (MD) are among the most common mental disorders worldwide. Low treatment adherence and treatment resistance are two of the most substantial challenges facing clinicians who treat persons with MD. This thesis examined: (1) a pilot study investigating whether a one-on-one personalized medication training program, called PIMM/SAM, improves medication adherence in persons with MD; and (2) a systematic review and meta-analysis on the effects of electroconvulsive therapy (ECT) on cognitive functioning in persons with depression. To evaluate the impact of PIMM/SAM on medication adherence, a randomized controlled trial was launched in a mood disorders inpatient unit to compare PIMM/SAM (partnership in medication management/self-administered medication) program to standard prescribing practice (SPP). Over follow-up in the feasibility portion of the trial, participants in the PIMM/SAM group (n = 7) held fewer negative beliefs about medications and had lower depersonalization scores compared to participants in the SPP group (n = 5). Between-group differences on the Medication Adherence Rating Scale favoured the PIMM/SAM group, but were not statistically significant. To examine the effects of bilateral versus unilateral ECT on cognitive performance in persons with TRD, 18 studies across 10 different cognitive domains were meta-analyzed. In the 8- to 30-day timeframe post-ECT, persons who received bilateral versus unilateral ECT had over double the odds of worse cognitive performance in global cognition, non-verbal memory delayed recall, verbal memory immediate and delayed recall, subjective memory, and verbal memory immediate recall. A personalized medication training program in a mood disorders clinic may have positive implications for medication adherence. The trial to evaluate PIMM/SAM versus SPP is ongoing and further evidence about the training program is expected within the next 12 months. The systematic review and meta-analysis showed that cognitive performance was worse in persons who received bilateral versus unilateral ECT in some cognitive domains at 8 to 30 days post-treatment. / Thesis / Doctor of Philosophy (PhD) / Mood disorders (MD), including major depressive disorder (MDD) and bipolar disorder, are among the most common mental disorders worldwide. Treating MD is a challenge because of long treatments, the presence of other illnesses, treatment side effects, problems with memory, attention, and decision-making, a lack of understanding about medications, or incorrect beliefs about medication (BAM). Persons with MD who do not respond to drug treatment are often given electroconvulsive therapy (ECT). This thesis explored the challenges of treating persons with MD through: (1) a pilot study examining whether a one-on-one personalized medication training program, called PIMM/SAM, would help persons with MD take their medications as prescribed; and (2) a study of the effects of ECT on cognitive functioning in depression. Results: (1) participants randomized to PIMM/SAM group held fewer negative BAM than participants receiving standard care; (2) evidence showed worse cognitive functioning in persons who received more intense forms of ECT.

Parkinson’s disease (PD) is a neurodegenerative disorder associated with motor disturbance and non-motor symptoms (NMS). Although NMS such as sleep and circadian disruption, cognitive impairment, and mood disturbance are prevalent and debilitating, treatments are limited, owing to lack of knowledge about their etiologies and interactions. This project comprised two studies of NMS in mild to moderate idiopathic PD without dementia. The hypothesis of Study 1 was that disruption of rest-activity circadian rhythm contributes to cognitive impairment in PD independently of sleep disruption. Thirty-five participants underwent 7-10 days of actigraphy monitoring, which provided estimates of sleep and circadian functioning, and then neuropsychological testing. Hierarchical regression showed that circadian interdaily stability predicted executive function, visuospatial function, and psychomotor speed, though not memory, independently of sleep. Sleep efficiency independently predicted executive but not other cognitive function. Study 2 examined daily temporal associations between sleep, subjective cognition, and mood (anxiety, positive affect) in PD. Twenty participants used a smartphone app to engage in 14 days of ecological momentary assessment (EMA) of daytime symptoms and subjective sleep quantity and quality. They wore actigraphs for objective sleep assessment. The hypothesis was that sleep quality would predict cognition and mood. Multilevel modeling indicated that subjective sleep quality was bidirectionally associated with mood on a day-to-day basis (i.e., last night’s perceived sleep affected today’s mood, which in turn will affect tonight’s sleep). There was also a trend for subjective sleep quality to predict the next day’s subjective cognitive function. Objective sleep was not associated with any daytime symptoms. Study 1 provided the first evidence that circadian rhythm contributes to cognition in PD independently of sleep. Study 2 indicated that, on a daily timescale, subjective sleep is relevant to mood and possibly cognition in PD, whereas objective sleep is either insufficiently sensitive or not relevant. Together these findings support the use of EMA to investigate small-timescale interactions among NMS, and present circadian rhythms and sleep perception as intervention targets for improving cognition and mood, and ultimately for enhancing quality of life in PD. / 2020-02-15T00:00:00Z

As the world is quickly aging, the prevalence of Alzheimer’s Disease (AD) and other dementias is also rapidly growing. AD is a neurodegenerative disease that gradually destroys one’s ability to learn, reason, and carry out daily activities. Memory impairment is the most prominent cognitive symptom of AD and can influence individuals' ability to live independently from the early stages of the disease. Compounding this, despite many promising advances made in the pharmacological treatment of AD, there is yet no treatment that can halt the disease. Non-pharmacological interventions are powerful solutions to help manage cognitive and functional symptoms of AD. However, there are still many challenges to the development of effective strategies. Firstly, little is known about the influence of distinct types of memory symptoms, such as false memories, on the daily life function of AD patients. Secondly, easy-to-use in-vivo biomarkers to detect AD and map disease progression patterns are still lacking making it challenging to implement strategies early on and target the stage of disease and pattern of cognitive impairment. In this dissertation, I will explore current advances made in AD research and outline some of the work done on the influence of false memories on the daily life of patients with AD. I will also investigate the use of Event-Related Potentials (ERPs) to help the diagnosis and characterization of AD. I will examine the feasibility and effectiveness of two behavioral interventions to sustain memory and cognition in AD patients: remote social interactions and a digital home-based cognitive training program. The results of this dissertation will shed light on how behavioral interventions can help sustain daily life function in AD patients, and they will bring forth novel research approaches that can be used to maximize the effectiveness of behavioral strategies. / 2026-02-20T00:00:00Z

Introduction: Through large neuroimaging consortia, researchers have identified a series of neuroanatomical alterations in mood and psychotics disorders, such as major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SCZ). However, the mechanism behind these alterations is not well understood. One of the existing hypotheses suggests that the observed brain changes are related to a process of accelerated brain ageing. Studies investigating this hypothesis use a measure called the brain age gap (i.e., the difference between machine learning model predictions of brain age and chronological age). Thus far, there is limited understanding on how mood and psychotic disorders affect model predictions, how can predictions be clinically useful, and what is the biological meaning behind the brain age gap. In this thesis, we investigated accelerated brain ageing in mood and psychotic disorders. We sought to estimate the effect of the brain age gap and propose new ways of modeling brain age. We also explored the clinical utility and meaning of the brain age gap. Results: We confirmed the presence of a brain age gap in MDD, BD, and SCZ through a systematic review and meta-analysis. SCZ presented the highest levels of brain age gap, followed by BD and MDD. We analyzed the clinical utility of brain age for antidepressant treatment response and concluded that the brain age gap is not a predictor of antidepressant treatment response in weeks 8 and 16. We proposed a new method for brain age prediction that is more interpretable than previous approaches while preserving good predictive performance. We have also used model explanation strategies and identified that the brain age gap is largely associated with total gray matter volume reduction and ventricle enlargement in SCZ. Conclusion: The results of this thesis suggest that the brain age gap is present across mood and psychotic disorders. The results have also helped to clarify the meaning behind the brain age gap, a largely used but still poorly understood measure in neuroimaging research. So far, there is no indication that the brain age gap can be a useful tool for treatment response prediction in MDD. / Thesis / Doctor of Philosophy (PhD)

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