‘Silence’ helps the brain encode information
Neuroscientists at NeuRA and UNSW Sydney have shown that the brain may ignore input known as ‘chatter’ and instead use periods of silence to register information about its environment. The scientists have challenged the conventional wisdom that neural activity is the main driver of human perception.
Dr Ingvars Birznieks and Dr Richard Vickery have developed a novel method of controlling the neural information presented to the brain using brief mechanical taps delivered to the fingertips.
Each tap generated only one nerve impulse in each activated neuron. By varying the frequency of taps, they were able to control the pattern of nerve impulses generated in a subject’s brain. The researchers were able to test several ideas that describe how nerve impulses encode information about the environment.
The sense of touch relies on vibrations as the ridges on fingertips scan over surfaces. How these vibrations are decoded by the brain is not well understood. Previous theories have suggested that the number of nerve impulses is counted as an index of vibration frequency, or that somehow a periodic regularity in the impulse patterns are detected. However, this latest research conclusively ruled out these theories.
Birznieks and Vickery generated bursts of nerve impulses to mimic successive skin ridge contact. Subjects rated the frequency independent of the number of impulses in the burst. The period between successive bursts did not correlate with the reported frequency.
“Instead, it was the silent period between bursts that best explained the subjects’ experiences,” said Dr Birznieks.
“We were hoping to disprove one of the two competing theories, but showing they were both incorrect and finding a completely new coding strategy totally surprised us.”
Dr Vickery says both researchers were excited but sceptical after the initial discovery and spent several years trying to disprove the findings before having full confidence to present their work to the scientific community.
These findings are interesting not just because that they represent a new way of understanding how the brain deciphers the barrage of neural impulses, but also because it offers a better understanding of these coding strategies that will ultimately help researchers build better brain-machine interfaces.
This next-generation of interfaces will provide a more sophisticated method of control for a range of devices and applications including telesurgery and prosthetics.
Find out more
- Link to full paper: https://doi.org/10.1016/j.cub.2017.04.011