Steele, John Douglas

2018-05-22T12:48:30Z

2018-05-22T12:48:30Z

2005

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.

http://hdl.handle.net/1842/30787

The University of Edinburgh

Annexe Thesis Digitisation Project 2018 Block 19

Already catalogued

Investigation into the mechanisms of depressive illness

Thesis or Dissertation

Doctoral

MD Doctor of Medicine