Researchers Move Closer to Objectively Quantifying Pain

A preliminary study suggests fMRI can be used to determine pain response

1 min read
Researchers Move Closer to Objectively Quantifying Pain

Pain management is one of the most difficult areas of medicine. Clinicians have little to go on beyond patients' self-reports, which can be highly variable. If doctors underestimate a patient's pain, they risk causing unnecessary suffering, but if they employ a better-safe-than-sorry approach, they risk over-medicating with drugs that are increasingly associated with abuse.

There have been various attempts to quantify pain as a physiological phenomenon, but none have proved effective enough to replace self-reporting. Now researchers at Stanford University have published a study of a promising fMRI-based solution.

The researchers used a machine-learning algorithm to recognize specific patterns in the fMRI data. They then found an association between certain patterns and pain in both self-reporting and non-reporting patients, implying a high degree of similarity across subjects. Although specific brain areas, such as the secondary somatosensory cortex, were implicated in the study, the researchers found that a whole-brain approach was more accurate at predicting pain than any individual brain region on its own (86.6 percent, compared to 71.9 percent for the secondary somatosensory cortex and 64.3 percent for a region called the mid-insular cortex).

The next step is to try to make the model robust enough to distinguish between different types of pain--for example, thermal versus mechanical--and to localize where on the body the pain is being experienced. Physicians will probably always have to rely on patient descriptions of pain to some degree, but experiments such as these offer hope that they will soon be able to bolster those qualitative ratings with more objective measurements, which should improve treatment outcomes.

Photo, the National Library of Medicine

The Conversation (0)

Are You Ready for Workplace Brain Scanning?

Extracting and using brain data will make workers happier and more productive, backers say

11 min read
Vertical
A photo collage showing a man wearing a eeg headset while looking at a computer screen.
Nadia Radic
DarkGray

Get ready: Neurotechnology is coming to the workplace. Neural sensors are now reliable and affordable enough to support commercial pilot projects that extract productivity-enhancing data from workers’ brains. These projects aren’t confined to specialized workplaces; they’re also happening in offices, factories, farms, and airports. The companies and people behind these neurotech devices are certain that they will improve our lives. But there are serious questions about whether work should be organized around certain functions of the brain, rather than the person as a whole.

To be clear, the kind of neurotech that’s currently available is nowhere close to reading minds. Sensors detect electrical activity across different areas of the brain, and the patterns in that activity can be broadly correlated with different feelings or physiological responses, such as stress, focus, or a reaction to external stimuli. These data can be exploited to make workers more efficient—and, proponents of the technology say, to make them happier. Two of the most interesting innovators in this field are the Israel-based startup InnerEye, which aims to give workers superhuman abilities, and Emotiv, a Silicon Valley neurotech company that’s bringing a brain-tracking wearable to office workers, including those working remotely.

Keep Reading ↓Show less
{"imageShortcodeIds":[]}