Scientists use AI to Identify Brain Patterns Affecting Antidepressants

With the help of artificial intelligence, scientists were able to identify the brain patterns that make people less responsive to antidepressants.

Scientists have finally identified the brain patterns that influence the efficacy of antidepressants.

Researchers have long sought to understand why antidepressants help with some patient’s recovery when it doesn’t work for others. Is a patient’s recovery due to a placebo effect, or does the individual’s biology influence the outcome?

Researchers at the University of Texas Southwestern decided to explore this issue in two separate studies. In one of the studies, the team used AI to identify the brain patterns that make people less responsive to certain antidepressants.

Simply put, imaging and artificial intelligence can now help determine if a medication is likely to be effective.

In a statement, one of the researchers, who is also the founding director of UT Southwestern’s Center for Depression Research and Clinical Care, Dr. Madhukar Trivedi, said:

“We need to end the guessing game and find objective measures for prescribing interventions that will work. People with depression already suffer from hopelessness, and the problem can become worse if they take ineffective medication.”

The team conducted two studies to identify the brain activities that influence antidepressants.

Imaging Provides a Glimpse of How Depression Manifests

The researchers used imaging to examined the brain patterns of over 300 participants in a resting state and while processing emotions. For the two studies, the participants were divided into a healthy control group, and people with depression who either received antidepressants or placebos.

In the group that received the medication, the researchers noted a link between brain activity and whether a patient became less depressed within two weeks of treatment.

According to Dr. Trivedi, these brain patterns are essential for understanding how depression manifests in individual patients.

For some people, the brain’s resting state could provide the required insight. In others, emotional processing is key to predicting whether an antidepressant will work.

One of the studies, published in Nature Human Behavior, took the investigation even further.

Using Artificial Intelligence to Identify the Brain Patterns

In the second, the researchers examined the brain activities of participants while they were presented with a conflict. The UT Southwestern team showed a quick succession of photos with conflicting messages – for example, an angry face with the word “happy” – to the volunteers undergoing brain imaging,

Then, they asked the participants to read the word on the paragraph before clicking to the next image.

This time, the researchers did not focus on the neural regions that are supposedly vital for predicting the efficacy of antidepressants. Instead, they also used machine learning to analyze the entire brain patterns.

AI identified the specific parts of the brain that are essential for predicting the efficacy of SSRI treatment. The lateral prefrontal cortices is an example of such a region.

Also, findings from the analysis suggested that participants with abnormal neural responses during emotional conflicts were likely to improve within eight weeks of treatment.

Dr. Trivedi concluded: