Can We Nudge Our Brain Activity to Make Healthier Choices?

Summary: New research suggests our brain activity could be influenced to make healthier choices.

Source: UC Berkeley.

UC Berkeley scientists capture the moment-to-moment dynamics of decision-making.

Netflix binge-watching versus a hike in the woods. A cheeseburger versus kale salad. Fentanyl versus Tylenol. New UC research from the University California, Berkeley, suggests our brain activity could be influenced to make the healthier choice.

In recording moment-by-moment deliberations by macaque monkeys over which option is likely to yield the most fruit juice, UC Berkeley scientists have captured the dynamics of decision-making down to millisecond changes in neurons in the brain’s orbitofrontal cortex.

The findings, reported this week in the journal Nature Neuroscience, shed new light on internal decision-making processes — particularly with regard to habitual behaviors — and help target the brain circuitry for implants to treat such neuropsychiatric disorders as anxiety, depression and addiction.

“If we can measure a decision in real time, we can potentially also manipulate it,” said study senior author Jonathan Wallis, a UC Berkeley neuroscientist and professor of psychology. “For example, a device could be created that detects when an addict is about to choose a drug and instead bias their brain activity towards a healthier choice.”

Located behind the eyes, the orbitofrontal cortex plays a key role in decision-making and, when damaged, can lead to poor choices and impulsivity.

While previous studies have linked activity in the orbitofrontal cortex to making final decisions, this is the first to track the neural changes that occur during deliberations between different options.

“We can now see a decision unfold in real time and make predictions about choices,” Wallis said.

Measuring the signals from electrodes implanted in the monkeys’ brains, Wallis and fellow researchers tracked the primates’ neural activity as they weighed the pros and cons of images that delivered different amounts of juice.

A computational algorithm tracked the monkeys’ orbitofrontal activity as they looked from one image to another, determining which picture would yield the greater reward. The shifting brain patterns enabled researchers to predict which image the monkey would settle on.

For the experiment, they presented a monkey with a series of four different images of abstract shapes, each of which delivered to the monkey a different amount of juice. They used a pattern-recognition algorithm known as linear discriminant analysis to identify, from the pattern of neural activity, which picture the monkey was looking at.

Image shows a woman thinking about an apple or burger. The food images are drawn in thought bubbles.

Our brain activity could be nudged in the direction of making more healthy choices. NeuroscienceNews.com image is adapted from the UC Berkeley press release.

Next, they presented the monkey with two of those same images, and watched the neural patterns switch back and forth to the point where the researchers could predict which image the monkey would choose based on the length of time that the monkey stared at the picture.

“Effectively we could now see the decision unfold and make predictions about the animal’s choice,” Wallis said.

The more the monkey needed to think about the options, particularly when there was not much difference between the amounts of juice offered, the more the neural patterns would switch back and forth.

“Now that we can see when the brain is considering a particular choice, we could potentially use that signal to electrically stimulate the neural circuits involved in the decision and change the final choice,” Wallis said.

About this neuroscience research article

Erin Rich, a researcher at the Helen Wills Neuroscience Institute at UC Berkeley, is lead author of the study.

Funding: The research was funded by grants from the National Institute on Drug Abuse and the National Institute of Mental Health.

Source: Yasmin Anwar – UC Berkeley
Image Source: This NeuroscienceNews.com image is adapted from the UC Berkeley press release.
Original Research: Abstract for “Decoding subjective decisions from orbitofrontal cortex” by Erin L Rich and Jonathan D Wallis in Nature Neuroscience. Published online June 6 2016 doi:10.1038/nn.4320

Cite This NeuroscienceNews.com Article
UC Berkeley. “Can We Nudge Our Brain Activity to Make Healthier Choices?.” NeuroscienceNews. NeuroscienceNews, 9 June 2016.
<http://neurosciencenews.com/healthy-choices-brain-activity-4422/>.
UC Berkeley. (2016, June 9). Can We Nudge Our Brain Activity to Make Healthier Choices?. NeuroscienceNews. Retrieved June 9, 2016 from http://neurosciencenews.com/healthy-choices-brain-activity-4422/
UC Berkeley. “Can We Nudge Our Brain Activity to Make Healthier Choices?.” http://neurosciencenews.com/healthy-choices-brain-activity-4422/ (accessed June 9, 2016).

Abstract

Decoding subjective decisions from orbitofrontal cortex

When making a subjective choice, the brain must compute a value for each option and compare those values to make a decision. The orbitofrontal cortex (OFC) is critically involved in this process, but the neural mechanisms remain obscure, in part due to limitations in our ability to measure and control the internal deliberations that can alter the dynamics of the decision process. Here we tracked these dynamics by recovering temporally precise neural states from multidimensional data in OFC. During individual choices, OFC alternated between states associated with the value of two available options, with dynamics that predicted whether a subject would decide quickly or vacillate between the two alternatives. Ensembles of value-encoding neurons contributed to these states, with individual neurons shifting activity patterns as the network evaluated each option. Thus, the mechanism of subjective decision-making involves the dynamic activation of OFC states associated with each choice alternative.

“Decoding subjective decisions from orbitofrontal cortex” by Erin L Rich and Jonathan D Wallis in Nature Neuroscience. Published online June 6 2016 doi:10.1038/nn.4320

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