Weaker incoming connections to a key emotion-related brain region are linked to higher depressive symptoms in a study of 890 neurotypical young adults, with researchers applying a directional analysis to resting-state brain scans to tease apart influence between regions. The work, published in the International Journal of Neuropsychopharmacology, used Granger causality to estimate whether activity in one area tends to precede and predict activity in another, a step beyond conventional measures that simply note concurrent activity.
The subgenual anterior cingulate cortex, or sgACC, sits at the front of the brain and helps regulate emotion and bodily responses. Altered activity in this area and its connections has long been associated with depression, and it has twice been the target of brain stimulation treatments. The new study sought to distinguish which region might influence the sgACC rather than merely co-activate with it.
Led by Huey-Ting Li of Yale University School of Medicine, the researchers analysed resting-state functional MRI scans from 890 healthy adults aged 22 to 35 who took part in the Human Connectome Project. The sample comprised 459 women and 431 men, and participants completed a questionnaire measuring depression, anxiety and other emotional and behavioural symptoms.
The team investigated connections between the sgACC and 268 other brain regions, separating connections estimated to run toward the sgACC from those running away from it. They then used a clustering approach to group participants by similar connectivity patterns and compared the groups’ symptom profiles with those derived from conventional measures of regional activity.
A substantial portion of the incoming connections to the sgACC involved frontal and parietal regions implicated in planning and attention, as well as the anterior insula, temporal regions and the cerebellum. The orbitofrontal cortex showed connections in both directions. By contrast, the sgACC appeared to send signals mainly to movement-related areas, the brainstem and the cerebellum.
Clustering based on incoming connections yielded five groups. Depression scores rose from the first to the fifth group, though only the lowest-scoring group differed reliably from the three highest-scoring groups. Participants with weaker inputs from several frontal, parietal, temporal and occipital areas tended to cluster with higher depressive symptoms, with the strongest links involving the superior frontal gyrus and the temporal poles.
The researchers note that, because the participants were not a clinical sample, the absolute differences in depressive symptoms were modest. The gap between the lowest- and highest-scoring groups was small to moderate.
Beyond depression, the groups also differed in anxiety, physical complaints, attention problems, aggression and rule-breaking behaviour. The group with the greatest depressive symptoms also showed the heaviest burden of both internalising problems (such as anxiety and depression) and externalising problems (such as aggression).
Sex composition varied across the groups, and in some groups men showed higher scores on certain behavioural problems. Nevertheless, the link between group membership and depressive symptoms remained after adjusting for sex.
Using incoming connections, the team could correctly classify participants into the five groups with about 87% accuracy, rising to roughly 92% with a more stringent tuning process. However, they emphasised that the groups were defined from the same connectivity data, so these figures reflect internal separation within the dataset rather than predictive power for new individuals.
By contrast, clustering based on outgoing connections produced only two groups that did not differ in symptom levels, and conventional measures of co-activation did not yield meaningful groupings. The authors caution that this may partly reflect differences in how reliably each type of connection can be measured, rather than proving that sgACC inputs are more relevant to mood than its outputs.
The study authors concluded that the findings highlight an outsized role of sgACC inputs in distinguishing individuals’ depressive symptom severity in a neurotypical population. They stated: “highlight an outsized role of sgACC inputs in distinguishing individuals’ depressive symptom severity in a neurotypical population.”
Limitations acknowledged include the non-clinical nature of the sample, the absence of independent replication, and the cross-sectional design. The use of Granger causality with fMRI data estimates directional patterns in blood-flow signals rather than establishing that one brain region actively drives another.
The research, titled Functional inputs to the subgenual cingulate cortex differentiate levels of depressive symptom severity in neurotypical young adults: Granger causality and clustering analyses, was led by Huey-Ting Li with colleagues Yu Chen, Shefali Chaudhary, Jaime S. Ide and Chiang-Shan R. Li.
