Advances in deciphering the brain code for depression
New study advances fundamental understanding of neural circuitry in depression
A new study published in the journal Biological Psychiatry on 16 March 2023 expands our basic understanding of how neural circuits work in depression in the Human Brain. The study shows that changes in brain activity in the anterior cingulate cortex may be the most telling indicator of the severity of depression.
Clinical depression is one of the most common psychiatric disorders and can have devastating effects. The great heterogeneity and complexity of the illness complicate the treatment of depression. Disorders of mood and cognition are common, debilitating and notoriously difficult to treat.
To advance the treatment of depression, it is necessary to address the significant gaps in our understanding of the neurophysiological basis. Although there are drugs to treat depression, about one third of patients do not respond to these first-line drug therapies.
Technical-physical therapies such as deep brain stimulation (THS) aim to provide significant relief to patients. However, previous results have been mixed. A deeper understanding of the neurophysiological mechanisms of depression is needed to develop personalised treatments and achieve better therapeutic outcomes.
The prefrontal cortex occupies a significant role in psychiatric and cognitive disorders and influences a person’s ability to set goals and develop habits. Studying these highly developed brain regions is particularly difficult in non-human models. Therefore, data obtained from human brain activity is of particular value.
Electrophysiological recordings from prefrontal cortical regions offer valuable insight.
At Baylor College of Medicine in Houston, Texas, USA, researchers led by Sameer Sheth, MD, PhD, along with Wayne Goodman, MD, and Nader Pouratian, MD, PhD,performed electrophysiological recordings from prefrontal cortical regions in three human subjects. All three suffered from treatment-resistant depression.
The researchers performed electrophysiological recordings of neuronal activity from the brain surface using implanted intracranial electrodes and recorded the severity of depression in each participant over nine days. The patients underwent brain surgery as part of a Deep Brain Stimulation (DBS) treatment feasibility study.
The researchers found that lower depression severity correlated with reduced low-frequency neural activity and increased high-frequency activity. They also discovered that changes in the anterior cingulate cortex (ACC) were the best predictor of depression severity.
In addition to the ACC, and in line with the diverse nature of signalling pathways and symptoms of depression, the researchers* also identified individually specific features that successfully predicted the severity of the illness.
The prefrontal cortex plays a significant role in psychiatric and cognitive disorders and influences a person’s ability to set goals and form habits.
New findings relevant to future use of brain stimulation techniques
“To apply neuromodulation techniques to treat complex psychiatric or neurological disorders, it is ideally necessary to understand the underlying neurophysiology,” Dr Sheth explains about the study. He continues: “We are pleased to have made initial progress in understanding how moods are encoded in human prefrontal circuits. As more such data becomes available, we hope to be able to identify general and individually specific patterns in affected individuals. This information will be critical in the development and personalisation of next-generation treatment approaches for depression, such as DBS.”
John Krystal, MD, editor of the journal Biological Psychiatry, published by Elsevier, commented on the study as follows: “We now have a growing collection of approaches that can be used to map neural circuits and characterise the underlying neural codes of depression. This knowledge will support next-generation brain stimulation techniques and influence the way we understand and treat depression in general.”
Results of the study:
The researchers found that in all prefrontal regions, reduced depression severity was associated with reduced low-frequency neuronal activity and increased high-frequency activity. When restricting the model to single-region decoding, the anterior cingulate cortex proved to be the best predictor of depression severity in all three subjects. Removing this limitation led to the identification of unique, individually specific combinations of spatial-spectral features that predicted symptom severity and reflected the heterogeneous nature of depression.
The ability to decipher the severity of depression from neural activity extends our basic understanding of the manifestation of depression in the Human Brain. This provides a neural target signature for personalised neuromodulation therapies and contributes to the advancement of treatment approaches.
Original research: Open Access