Brain-Training Software Shows Promise for Elderly Patients with Depression

August 11, 2014

Elderly patients suffering from treatment-resistant depression could find relief in the form of specially designed computer games, according to a recent study in Nature Communications. The study, which brought together researchers from Yale University and Weill Cornell Medical College, introduced brain-training software to 11 older, treatment-resistant adults (60 to 89 years old) who were not responding to antidepressants. The computerized cognitive training programs improved symptoms to the same degree as the gold standard drug treatment, escitalopram, but three times as fast (four weeks instead of 12 weeks). Moreover, 8 of 10  patients who failed to show improvement with conventional antidepressants recovered when the computer exercises were added to their treatment.

“We’ve never seen such good results,” says Bruce Wexler, Professor Emeritus of and Senior Research Scientist in Psychiatry at Yale and the cofounder of C8 Sciences, which develops and markets brain-training software for improving learning. He added: “We’ve also never had such clear neural targets.”

Wexler worked with researchers at Cornell, including neuropsychologist Sarah Shizuko Morimoto, to develop a game that would target the frontal executive regulatory system. Cornell researchers had discovered that this part of the brain is damaged by the aging process in elderly patients suffering from depression, and also found that deficits in executive functioning are associated with poor and slow response to antidepressant treatment.

This discovery was the result of prior research predicting remission using a cognitive test battery known as the Mattis Dementia Rating Scale. When broken down into discreet cognitive functions, “Only one function predicted remission,” Morimoto says. “Verbal fluency.” Verbal fluency refers to one’s ability to name a series of items, such as products in a grocery store. Those patients who used strategies like grouping items from the same category together were more likely to respond well to antidepressants. Other studies with similar outcomes followed.

Then, Morimoto says, “We started to think about how to change that function and, if that could improve outcomes in patients with depression—how to optimize the underlying circuitry.” She and Cornell colleagues Willie Hu, Joanna Seirup and George Alexopoulos began collaborating with Wexler, who is an expert in designing neurobiological-based computer interventions, and his Yale colleague Jiacheng Liu.

In one computer program, elderly patients tracked a moving ball on the screen and clicked a button whenever the ball changed from red to yellow. If they got it right, the game moved faster. Then a new color was introduced, but they couldn’t click on it. Or they had to remember which colors to click in which order. What these games were ultimately testing—and strengthening—was sustained attention, response inhibition, cognitive flexibility, working memory and use of categories. “They all draw on a similar neural system that regulates emotion,” Wexler says. Another game focused on developing semantic strategy.

While the findings are early, patients still show significant improvement in their depressive symptoms and sustained cognitive improvements three months after the study. Morimoto is in the midst of a full pilot study that she says will allow researchers to determine how much of the improvement they are seeing in patients is due solely to the computer programs. “We are also doing pre- and post- EEGs and neuroimaging hoping to find a neurobiological signature,” she adds.

Researchers hope that further clinical testing will reveal this to be a true alternative treatment for geriatric depression, whether on its own or to improve patient response to antidepressants.

CONTACT: Brita Belli, Communications Officer, Yale Office of Cooperative Research, (203)436-4933, brita.belli@yale.edu.