Abstract

Mood disorders are classically regarded as a major disturbance of mood in addition to other key symptoms according to Diagnostic and Statistical Manual of Mental Disorders (DSM) criteria and are commonly classified according to polarity (unipolar, bipolar), course of the illness (e.g. single and recurrent episodes), severity (mild/moderate/severe) or are based on symptom combinations to form subtypes such as melancholic and atypical depression. Reliable neurobiological underpinnings of any of these clinical classifiers have not yet emerged, leaving a noticeable lack of neurobiologically informed treatment options in depression. In fact, neurobiology underpinnings are at best a second thought as an attempt to explain what has been observed clinically. Integration of clinical and neurobiological models rarely occurs in Psychiatry and even less so is the approach to utilise neurobiological information to inform clinically meaningful symptoms and dimensions. For example, cognitive function has been strongly linked to genes in recent large genome-wide association studies pointing towards cognitive function as an neurobiologically informed symptom dimension with possible relevance to depression (Davies et al., 2016). Interestingly, cognitive dysfunction observed commonly in acute and remitted depression may present as such a neurobiologically informed treatment target (Beblo et al., 2011).
In their perspective paper, Porter et al. (2017) raise the important clinical issue of cognitive impairments in mood disorders in both acute states of the illness as well as during remitted and chronic stages of the condition suggesting that cognitive symptoms may not only be regarded as a state but also as a possible trait marker of mood disorders. Assuming that most of the mood and cognitive symptoms (and several other symptoms) observed in depression are part of complex processes of interacting emotion and cognitive as well as social cognitive processes (Weightman et al., 2014), it can be argued that cognitive symptoms form complex symptom dimensions in depression.
Extending from conceptual consideration into clinical translation, an emphasis on cognitive and emotional aspects of mood disorders as taken by Porter et al. (2017) for the treatment of mood disorders is a logical consequence of a dimensional approach taken in mood disorders. The relative paucity of effective pharmacological and psychotherapeutic treatments addressing cognitive and affective symptoms in mood disorders underscores the so often heard complaint of the mismatch between neurobiologically informed disease concepts and efficacious treatments in mood disorders. Here, the authors step in with a suggestion of criteria for already existing and for a yet to be developed cognitive training programme that they call Cognitive and Affective Remediation Training (CART). While the idea of a composition and clinical translation of such a program may be in part inspired by similar approaches in schizophrenia, applying specifics to mood disorders is still outstanding. Porter et al. point to some of the most important requirements for CART.
First and foremost, it should be expected that a cognitive and affective remediation intervention is required to target brain networks that underlie cognitive and emotional processing dimensions in mood disorders and that show sensitivity to change following a targeted intervention. Without doubt, patients should feel and do better following any type of treatment, but without a measurable change in underlying brain networks (or other key biological measures), how can it be assumed that impaired cognitive and affective processing have a chance of restoration and recovery followed by symptom recovery of the patient? Therefore, neurocircuitry based target selection of CART is key for its efficacious clinical application. However, further research needs to be conducted to elucidate which targets should be engaged beyond the dorsolateral prefrontal cortex (DLPFC). And vice versa, applying CART programmes will explore further how cognitive training interventions related to underlying neurocircuitry.
A second key requirement for an efficacious application of CART is its relevance to generalised function. While Porter et al. rightly suggest that targeting multiple cognitive and affective domains may improve more broadly general psychosocial function – an argument that finds support from evidence showing that improving cognitive function more broadly increases general day-to-day function (Jaeger et al., 2006) – it can also be argued that targeting specific cognitive domains such as executive function through a remediation program may improve psychosocial function specifically. The jury is still out to determine whether cognitive training (and which cognitive domains should be targeted?) leads to changes in either generalised or specific domains of psychosocial function.
Interestingly, it can be argued that the anticipated psychosocial and functional effects of a cognitive training program that includes both cognitive and affective components may be mediated by improvements in social cognitive function. Social cognition – the ability to identify, perceive, and interpret socially relevant information – is an important skill that plays a significant role in successful interpersonal functioning. The difficulties with social interaction observed in major depressive disorder may, at least in part, be due to an altered ability to correctly interpret emotional stimuli and mental states (Weightman et al., 2014). These features seem to persist even in remission – particularly a bias towards negative emotions persists – although some patients may respond to intervention. Enhancing the ability of accurate facial recognition, prosody and prosody pair matching that are important social cognition measures may carry an underestimated potential for improving functional and psychosocial outcomes in mood disorders. Naming social cognitive function as an important target that needs to be addressed effectively by CART programmes, may help conceptually and clinically to decide which types of exercises should be selected. Social cognitive training would need to include various components aiming to disengage from excessive attendance to negative stimuli, increase attention to positive stimuli, and to reduce tendencies towards negative thinking styles and to enhance emotional reactivity to both negative and positive stimuli.
Importantly, we have learned from research that cognitive functions such as executive function and emotional processing are closely intertwined. Hence, it can be expected that improving cognitive performance in relevant domains will assist in gaining more control and flexibility over the so often troubled emotion processing in depression. While we like to believe that such insight may help us guide towards a rational target selection of which cognitive domain relates to corresponding neural networks, research has shown tremendous difficulties linking specific cognitive function to underlying neural networks. However, promising are findings that show an activation of the DLPFC through cognitive training and vice versa, electrical stimulation of the DLPFC may also improve related cognitive functions. Of note is that some of this research indicates that improvement of cognitive function may help improve emotional symptoms as well.
Taken together, the approach suggested by Porter et al. (2017) in relation to targeting cognitive and affective dimensions of depression can be regarded as an important attempt to integrate clinical and neurobiological information as a foundation for interventions in mood disorders and to develop biologically informed treatments of clinical relevance. Taking a dimensional approach to understanding mood disorders may lead to urgently needed more effective and longer lasting treatment effects. While this remains to be seen through convincing evidence-based clinical research, the authors should feel encouraged to engage following this path.
Footnotes
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.
Funding
The author(s) received no financial support for the research, authorship and/or publication of this article.
