[Multidimensional and computational theory of mood]

What is mood? Despite its crucial place in psychiatric nosography and cognitive science, it is still difficult to delimit its conceptual ground. The distinction between emotion and mood is ambiguous: mood is often presented as an affective state that is more prolonged and less intense than emotion, or as an affective polarity distinguishing high and low mood swinging around a baseline. However, these definitions do not match the clinical reality of mood disorders such as unipolar depression and bipolar disorder, and do not allow us to understand the effect of mood on behaviour, perception and cognition. In this paper, we propose a multidimensional and computational theory of mood inspired by contemporary hypotheses in theoretical neuroscience and philosophy of emotion. After suggesting an operational distinction between emotion and mood, we show how a succession of emotions can cumulatively generate congruent mood over time, making mood an emerging state from emotion. We then present how mood determines mental and behavioral states when interacting with the environment, constituting a dispositional state of emotion, perception, belief, and action. Using this theoretical framework, we propose a computational representation of the emerging and dispositional dimensions of mood by formalizing mood as a layer of third-order Bayesian beliefs encoding the precision of emotion, and regulated by prediction errors associated with interoceptive predictions. Finally, we show how this theoretical framework sheds light on the processes involved in mood disorders, the emergence of mood congruent beliefs, or the mechanisms of antidepressant treatments in clinical psychiatry.

The evaluation of depression in multiple sclerosis using the newly proposed Multiple Sclerosis Depression Rating Scale

Fatigue and depression are frequent symptoms in multiple sclerosis (MS). Both are overlapping and shadowing each other and may impair the quality of life. For detection of depression symptoms in MS, the Multiple Sclerosis Depression Rating Scale (MSDRS) has been proposed recently. Here, we compare the performance of MSDRS in MS patients with and without fatigue to that of established rating scales, i.e. Hospital Anxiety and Depression Scale and Beck Depression Inventory. Twenty-nine MS patients were screened for fatigue and depression symptoms. Patients with fatigue showed significantly higher depression scores compared to patients without fatigue, whereas the number of depressed patients did not differ between the two groups. MSDRS seems to have higher sensitivity to detect severe depression than established rating scales. However, one should keep in mind that such a finding might be due to an increase in false positive cases when using MSDRS. Implementing this scale in future studies might be of help to enhance the understanding of its potential utility.