Unlock the brain code for depression

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The treatment of depression is complicated by the high heterogeneity and remarkable complexity of the disease. Medications to treat depression are available, but one-third of patients do not respond to these first-line drug treatments. Other treatments such as deep brain stimulation (DBS) can provide patients with significant relief, but previous results have been inconsistent. The development of more personalized treatments and improved outcomes requires a better understanding of the neurophysiological mechanisms of depression.

Led by Sameer Sheth, MD, PhD, at Baylor College of Medicine, along with Wayne Goodman, MD, and Nader Pouratian, MD, PhD, the researchers collected electrophysiological recordings from prefrontal cortical areas in three subjects, all of whom had undergone severe treatment. underwent. resistant depression.

The prefrontal cortex plays an important role in psychiatric and cognitive disorders, affecting a person’s ability to set goals and form habits. These highly evolved brain regions are particularly difficult to study in non-human models, so data collected on human brain activity is particularly valuable.

The researchers made electrophysiological recordings of neural activity from the surface of the brain using implanted intracranial electrodes, and they measured the severity of each participant’s depression over nine days. The patients underwent brain surgery as part of a feasibility study for treatment with DBS.

The researchers found that lower depression severity correlated with decreased low-frequency neural activity and increased high-frequency activity. They also found that changes in the anterior cingulate cortex (ACC) served as the best predictive area of ​​depression severity. In addition to the ACC, and consistent with the diverse nature of the pathways and symptoms of depression, they also identified individual-specific sets of traits that successfully predicted severity.

“Ideally, to use neuromodulation techniques to treat complex psychiatric or neurological conditions, we need to understand their underlying neurophysiology,” said Dr. Sheth. “We are thrilled to have made the first advances in understanding how mood is encoded in human prefrontal circuits. As more such data becomes available, we will hopefully be able to identify which patterns are common among individuals and which are specific. This information will be critical in designing and customizing next-generation therapies for depression, such as DBS.”

John Krystal, MD, editor of Biological psychiatrysaid of the work: “We now have a growing collection of approaches that can be applied to mapping the circuitry and characterizing the neural codes underlying depression. This knowledge will guide and inform the next generation of brain stimulation treatments about the way we understand and treat depression, broadly.”

Reference: Xiao J, Provenza NR, Asfouri J, et al. Decoding the severity of depression from intracranial neural activity. Biol Psychiatry. 2023;0(0). doi: 10.1016/j.biopsych.2023.01.020

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