Using fMRI Techniques for Assessing 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.