Using fMRI Techniques for Assessing Sub-types of Depression

By Paola Tine,

Master in Applied Neuroscience student.

A Burden of Disease

As one of the most common mental issues in Europe, China, and the United States (Zhuo et al., 2019), depression is one of the world’s greatest burdens of disease and a primary cause of death by suicide, affecting more than 264 million people around the globe (WHO 2020). While many studies have been conducted in recent years trying to analyse its biological basis, there is no consensus on its origin. This is unsurprising due to the high variability of the illness in both perceived symptoms and biological causes, such as cortisol alterations, increased cortical thickness, altered brain connectivity, elevated amygdala activity and hippocampus variations (Harvard Health Publishing, 2020), and due to the absence of an objective test that can assess the illness. In fact, patients self-reporting symptoms is still the main source of data for practitioners to assess the presence of the illness in order to address and treat it. Currently, when an individual shows five of the nine symptoms reported in the Diagnostic & Statistical Manual of Mental Disorders (DSM-5) they can be diagnosed with depression (APA, 2020). Unfortunately, the uncertainty in this method of assessment often leads to incorrect diagnoses and treatments. Several studies have shown that there is very high variability in patients’ responses to treatments, with some preferring medications rather than psychotherapy and vice versa (Corey-Lisle et al., 2004). It is therefore imperative that additional studies be conducted to further understand both the neurological basis of depression and provide more specific diagnosis methods and treatments addressing more detailed conditions of the patients. These neurological studies should be conducted in strict collaboration with social and psychological studies.

fMRI to Assess Sub-types of Depression

Experimental research using neuroimaging techniques with the goal of expanding the knowledge of neurological factors related to depression have consistently increased in recent years (Scott et al., 1983). One of the primary research goals in investigating depression has been the identification of potentially different sub-types of the condition through the exploration of brain connectivity (Gong & He, 2015). The main brain imaging techniques used in this scope are electroencephalography (EEG), positron emission tomography (PET), and functional magnetic resonance imaging (fMRI). These diverse techniques produce a varied range of results, in accordance with their technical potential. For example, fMRI techniques have been proven to be effective in exploring brain connectivity between the forebrain and the striatum, which is of fundamental importance in understanding the brain’s response to the messages coming from the amygdala. Hyper-connectivity between these areas has been found to be at the base of many depressive symptoms, including chronic anhedonia (Gorwood, 2008).

 

fMRI studies are useful in determining which areas of the brain function in specific contexts. For example, researchers have determined which areas of the brain are implicated in self-relation including the anterior cingulate cortex, the medial prefrontal cortex, the posterior cingulate cortex, the dorsomedial thalamus and the precuneus (Greicius et al., 2003, Raichle et al., 2001). This kind of information can be useful in better understanding how depression changes brain function. However, caution should always be used when drawing conclusions as areas of the brain are rarely activated solely for one purpose. In one review of neuroimaging correlates of depression using PET, MRI, MRS and fMRI, it appeared that depression could affect the default-mode network, the affective network, the cognitive control network, and the amygdala, and that all of these areas also respond to medication and antidepressants (Castanheira et al., 2019). Furthermore, while the structural differences in the brain were varied amongst test subjects, there did appear to be changes in grey matter volume in cortical and subcortical regions that may be linked to depressive states.

 

One of the main studies trying to determine the presence of depression sub-types, published in Nature Medicine claims that there could be four types of depression, and that ‘distinct patterns of abnormal functional connectivity differentiated the four biotypes and were associated with specific clinical-symptom profiles’ (Drysdale et al., 2016). For instance, depressed people belonging to the biotypes 1 and 4 (whose primary feature is increased anxiety) when compared to control, presented reduced connectivity in the networks of the fronto-amygdala area, an important area of the brain for regulating fear and negative emotions. Differently, in biotypes 3 and 4 (whose primary features are increased anhedonia and psychomotor retardation) they found increased connectivity in the networks of the thalamic and fronto-striatal areas that regulate motor initiation and control. Finally, biotypes 1 and 2 (whose common features are anergia and fatigue) presented lowered connectivity in the anterior cingulate and orbitofrontal areas, which are the areas supporting motivation. In a similar vein, studies have been investigating potential lateralisation of depression. For example, a resting-state fMRI study from 2018, found that the neural basis of depression might be related to a dominant right hemisphere (Li, Xu and Lu, 2018). However, while research directed towards the identification of neurobiological markers of depression continues to progress fast, it should be noted that many of the studies considered had small sample numbers making it difficult to draw significant conclusions.

Potential Pitfalls

While there are currently a wide range of methods and techniques used to research depression, including the examination of treatment responses and how symptoms are self-reported, there is still a great deal of uncertainty over what the causes of depression could be. Here the problem of reconciliating an understanding of brain and mind is presenting itself in all its glory. Most of the issues come from the fact that there does not appear to be a neurobiological pattern to depression, which makes many scientists sceptical about translating neuroscientific knowledge in clinical settings. In fact, as noted by the same scientists that defined the four sub-types of depression, ‘biomarkers have transformed modern medicine but remain largely elusive in psychiatry, partly because there is a weak correspondence between diagnostic labels and their neurobiological substrates’ (Drysdale et al., 2016). As this study concludes, depression is indeed a multiform syndrome, whose aetiology and symptoms should be addressed as pieces of a complex puzzle. As such, there are various ‘faces’ of depression, and depressed people might present completely different symptomatology on a psychological level, even if some connectivity issues might be shared.

 

The problematic nature of translating neurological findings into psychological concepts lies in the methodology of psychological and behavioral inference. Specifically, the reverse inference fallacy, which aims at discovering the connections between cognitive events and some specific neurobiological structures and disorders is an important limit to the clinical translation of neurological findings (Zhuo et al., 2019). This is due to the multifaceted nature of brain functions, which makes the aetiology of observed biological phenomenon difficult to entangle, and as such makes the connection between biomarkers and psychiatric disorders very problematic.

Conclusion: Towards New Directions of Research

The efficacy of using fMRI techniques for investigating brain connectivity and identifying subtypes of depression can help to improve diagnosis and treatment. Thanks to neuroimaging techniques, recent studies have been able to detect biological problems at the brain level, notably improving our knowledge of ‘depressed brains’. However, neuroimaging in the study of depression presents several potential pitfalls too. The fallacy of reverse inference commonly misrepresents psychological phenomena and the lack of interdisciplinary research further muddies the waters. Observations made using fMRI technique may be incredibly useful; however, they do not exist in isolation and a further range of factors and contexts should also be considered when researching the phenomenon. Additionally, these studies often lead to a variety of outcomes and theories, some of which are incompatible with each other. For example, according to Leanne Williams, a Stanford clinical neuroscientist, there are six subtypes, not the usually accepted four, and she also suggests that the real issue is looking at ‘where the crisis is’, in order to be able to prevent depression rather than simply treat it (cited in Underwood, 2019). In this sense, social scientists, psychologists and medical anthropologists are increasingly exploring depression as a ‘social disease’, trying to tackle the socio-cultural roots and causes of the illness (Bader, 2018). Nevertheless, while there has been an increase in recent years of interdisciplinary studies researching the causes rather than the social reception of depression, with a large focus on adolescent mental health (Patalay and Gage, 2019), these studies are still in their preliminary stages. Future studies could be strengthened by collaboration between disciplines, directed more specifically to the factors causing the insurgence of this widespread problem at its roots.

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