Investigation into the mechanisms of depressive illness

Functional and structural brain abnormalities have been reported in many imaging studies of depressive illness. However, the mechanisms by which these abnormalities give rise to symptoms remain unknown. The work described in this thesis focuses on such mechanisms, particularly with regard to neural predictive error signals. Recently, these signals have been reported to be present in many studies on animals and healthy humans. The central hypothesis explored in this thesis is that depressive illness comprises a disorder of associative learning. Chapter 2 reviews the brain regions frequently reported as abnormal in imaging studies of depressive illness, and the normal function of these particular brain regions. It is concluded that such regions comprise the neural substrate for associative learning and emotion. However, confidence in this conclusion is limited by considerable variability in the human imaging literature. Therefore, chapter 3 describes a meta-analysis, which tests the hypothesis that, consistent with the non-imaging literature, the ventromedial prefrontal cortex is most active during emotional experience. The results of the meta-analysis were clearly consistent with this hypothesis. Chapter 4 provides an introduction to neural predictive error signals from the general perspective of homeostatic physiological regulation. Both experimental evidence supporting the error signals, and various formal mathematical theories describing the error signals, are summarised. This provides the background to chapter 5, which describes an original fMRI study which tested the hypothesis that patients with depressive illness would exhibit abnormal predictive error signals in response to unexpected motivationally significant stimuli. Evidence of such abnormality was found. Chapter 6 describes a further original study using transcranial ultrasound and diffusion tensor imaging of the brainstem, which investigated reports of a subtle structural abnormality in depressed patients. If present, it might give rise to abnormal error signals. However, no structural abnormality was found. Finally, chapter 7 discusses the significance of these findings in the context of clinical features of depressive illness and a wide range of treatments, ranging from psychotherapy through antidepressants to physical treatments. A number of potential future studies are identified, which could clarify understanding of depressive illness

Aversiveness of errors in performance monitoring and error related negativity in obsessive compulsive symptomatology

The error-related negativity is one of the most examined event-related potentials in the study of cognitive control, yet its functional significance has not been fully determined. The present dissertation had the objective to investigate the relationship between error processing and affective states manipulations in non-clinical samples and in OC symptomatology. Two studies constitute this dissertation. In study 1, we conducted a systematic review of studies investigating affective state manipulations, aversiveness of errors and the ERN. This review showed considerable evidence for ERN sensitivity to affect states experimental manipulations. In study 2, we aimed to explore the incidence of the error-related potentials at a gambling-type task (HiLo game) in a sample composed of people with high OCD symptomatology. Although the ERPs of interest were not elicited, we showed that the HiLo game is a promising paradigm to investigate the ERN in upcoming studies. In the general discussion, the results from the two studies are discussed in relation to the literature on error monitoring and affective conceptualizations

Visual mismatch negativity (vMMN): A review and meta-analysis of studies in psychiatric and neurological disorders

The visual mismatch negativity (vMMN) response is an event-related potential (ERP) component, which is automatically elicited by events that violate predictions based on prior events. VMMN experiments use visual stimulus repetition to induce predictions, and vMMN is obtained by subtracting the response to rare unpredicted stimuli from those to frequent stimuli. One increasingly popular interpretation of the mismatch response postulates that vMMN, similar to its auditory counterpart (aMMN), represents a prediction error response generated by cortical mechanisms forming probabilistic representations of sensory signals. Here we discuss the physiological and theoretical basis of vMMN and review thirty-three studies from the emerging field of its clinical applications, presenting a meta-analysis of findings in schizophrenia, mood disorders, substance abuse, neurodegenerative disorders, developmental disorders, deafness, panic disorder and hypertension. Furthermore, we include reports on aging and maturation as they bear upon many clinically relevant conditions. Surveying the literature we found that vMMN is altered in several clinical populations which is in line with aMMN findings. An important potential advantage of vMMN however is that it allows the investigation of deficits in predictive processing in cognitive domains which rely primarily on visual information; a principal sensory modality and thus of vital importance in environmental information processing and response, and a modality which arguably may be more sensitive to some pathological changes. However, due to the relative infancy of research in vMMN compared to aMMN in clinical populations its potential for clinical application is not yet fully appreciated. The aim of this review and meta-analysis therefore is to present, in a detailed systematic manner, the findings from clinically-based vMMN studies, to discuss their potential impact and application, to raise awareness of this measure and to improve our understanding of disease upon fundamental aspects of visual information processing

The Depressed Decision Maker: The Application of Decision Science to Psychopathology

Is decision making impaired in mental illness populations? Can behavioral economics provide insight into clinical psychology? The present project addresses these broad questions through three studies. In the first study, two meta-analyses were conducted of experiments that used the Iowa Gambling Task (IGT) to assess value based decision making in populations with mental illness. In the first meta-analysis (63 studies, combined N = 4,978), we compared IGT performance in healthy populations and populations with mental illness. In the second meta-analysis (40 studies, combined N = 1,813), we examined raw IGT performance scores as a function of type of mental illness. The first meta-analysis demonstrated that individuals with mental illness performed significantly worse than did healthy control individuals. The second meta-analysis demonstrated no performance differences based on type of mental illness. Impairment on the IGT, however, could indicate effects from several different decision processes. Accordingly, in the second study, using multiple decision tasks we explored different aspects of decision making in a single group that exhibited reliable effects in the meta-analysis, major depressive disorder. The second study answers three questions. First, how does decision making differ in clinically depressed individuals across a range of decision tasks? Second, where are the largest differences between clinically depressed and non-depressed individuals? And finally, how well can decision task performance discriminate depressed individuals from healthy controls? Depressed individuals\u27 decision-making was significantly different across a range of decision tasks, but impaired learning and pessimism bias showed the strongest behavioral signature of depression. Decision tasks significantly predict depression, but are far outperformed by self-report measures as diagnostic tools. Overall, results suggest decision tasks are better suited to identify specific impaired processes rather than for diagnostic prediction. This study suggested depression is associated with impaired reward and punishment processing, but what are the underlying causes behind these deficits? In the third study, we performed a detailed analysis of reward and punishment learning in clinically depressed individuals, quantifying choice behavior by fitting reinforcement learning models. The results suggest that depression is characterized by hyposensitivity to reward. The reinforcement learning models show that depressed individuals engage habit-oriented model-free learning strategies in contrast to the goal-oriented model-based strategies engaged by healthy controls. Overall the three studies demonstrate how interdisciplinary research combining decision science and clinical psychology can help to better understand mental illness

Worth the ‘EEfRT’? The Effort Expenditure for Rewards Task as an Objective Measure of Motivation and Anhedonia

Background: Of the putative psychopathological endophenotypes in major depressive disorder (MDD), the anhedonic subtype is particularly well supported. Anhedonia is generally assumed to reflect aberrant motivation and reward responsivity. However, research has been limited by a lack of objective measures of reward motivation. We present the Effort-Expenditure for Rewards Task (EEfRT or ‘‘effort’’), a novel behavioral paradigm as a means of exploring effort-based decision-making in humans. Using the EEfRT, we test the hypothesis that effort-based decision-making is related to trait anhedonia. Methods/Results: 61 undergraduate students participated in the experiment. Subjects completed self-report measures of mood and trait anhedonia, and completed the EEfRT. Across multiple analyses, we found a significant inverse relationship between anhedonia and willingness to expend effort for rewards. Conclusions: These findings suggest that anhedonia is specifically associated with decreased motivation for rewards, and provide initial validation for the EEfRT as a laboratory-based behavioral measure of reward motivation and effort-base