New research from CiNet: Multiple threat-detection systems in the human brain

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Images of the cerebellum as it learns which arm we should move when expecting pain, from the new NICT CiNet brain scanner.

When encountering danger, the brain rapidly signals to the body to enter defence mode. Learning to produce appropriate responses to pending dangers is critical for our survival and adaptation. However, there are a great variety of defensive responses – ranging from facial expression to communicate danger to others, autonomic responses such as sweating and a racing heart, and ‘motor’ defence such as retracting our limbs. But how exactly do we learn these diverse reactions? To be more precise, do we acquire these reactions through a single system, or a network of multiple learning systems?

In a new article, CiNet researchers addressed this question by using pain as an example of danger. They studied human volunteers whilst they learned to associate visual pictures with impending painful heat pulses. Physiological results from the body revealed two different patterns of response: a ‘non-specific’ pattern that does not care where on the body the threat is, which included facial fear responses, sweating, and increased heart rate. And a ‘specific’ pattern that needs to know where the threat is, such as which arm we should withdraw to try to avoid pain.

The researchers then studied the brain activity whilst subjects did the task, using the new state-of-the-art imaging facilities at CiNet. These results clearly showed two different learning systems in the brain, with the non-specific system correlating with responses from the classic fear learning circuit (the amygdala and striatum), and the ‘specific’ system correlating with responses in the cerebellum. The research shows the human pain and defence system is built on a brain network of different learning sub-systems, not a single pathway as previously thought.

“Dissociable Learning Processes Underlie Human Pain Conditioning.”
Zhang, Suyi, Hiroaki Mano, Gowrishankar Ganesh, Trevor Robbins, and Ben Seymour.
Current Biology. Accessed December 17, 2015. doi:10.1016/j.cub.2015.10.066.