The Journal of Young Investigators: An Undergraduate, Peer-Reviewed Science Journal
Volume 20, Issue 3. September 2010
“Electric” Fish Illuminate How Brain Directs Movement
Native to South America, the glass knifefish's ability to emit weak electrical signals makes it a superb subject for the study of how the brain uses sensory information to control locomotion. Image courtesy of Noah Cowan.
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16 February 2007 -
The study of a certain “electric” fish explains how animal brains are “tuned” to account for the laws of motion. The findings by Johns Hopkins University’s Eric Fortune and Noah Cowan, published in the January 31 issue of the Journal of Neuroscience, may lead to improvements in the quality of motion of prosthetic limbs and rehabilitation after serious neurological trauma and disease.
"All animals, including humans, must continually make adjustments as they walk, run, fly or swim through the environment. These adjustments are based on feedback from thousands of sense organs all over the body, providing vision, touch, hearing and so on.,” said Cowan, an assistant professor of mechanical engineering in Johns Hopkins' Whiting School of Engineering. “Understanding how the brain processes this overwhelming amount of information is crucial if we want to help people overcome pathologies" that affect locomtion.
Two properties of the fish, called glass knifefish, made them ideal for motion studies. First, the nocturnal fish “see” in the dark by emitting weak electric signals and gathering feedback through special electroreceptors in their brain cells. Second, the fish are capable of moving back and forth in a small tube, a behavior crucial to the study design.
The researcehrs used robotics to move a small plastic tube back and forth with increasing frequency. The fish, which used the tube as a hiding place, performed an electrical tracking technique to stay hidden in the tube as it moved. But the fish could only process the speed of the moving tube below a frequency of one motion per second (1Hz), a quality scientists describe as “low-pass” since receptors in brain cells only detect frequencies lower than a certain limit.
This low-pass activity, however, does not match previous predictions for the electroreceptors.
“I would say that it has been known for some time that the electroreceptors are more sensitive to frequencies above 1Hz than below 1Hz -- that is, the receptors have a ‘high-pass’ property,” Cowan said.
Cowan and Fortune realized that previous studies had not incorporated Newton’s Laws of motion into an analysis of animal locomotion. Once they used a mechanics analysis to apply these laws to their results, they developed a prediction for a high-pass filter which matched the known high-pass characteristics of the fish’s electroreceptor.
According to the researchers, fish brains, and likely human brains as well, use a high-pass filter to account for Newton’s laws in simple and unconscious acts, such as a person reaching for a coffee cup.
This research may contribute to medical advances in humans, including better prosthetic limbs and improved rehabilitative techniques for people suffering from strokes, cerebral palsy and other debilitating conditions.
"With this basic knowledge, we hope one day to be able to ‘tune' artificial systems, such as prosthetics, so that they don't have the jerky and rough movements that most robots have, which is critical for medical applications," Fortune said.
Written by Ojus Doshi
"All animals, including humans, must continually make adjustments as they walk, run, fly or swim through the environment. These adjustments are based on feedback from thousands of sense organs all over the body, providing vision, touch, hearing and so on.,” said Cowan, an assistant professor of mechanical engineering in Johns Hopkins' Whiting School of Engineering. “Understanding how the brain processes this overwhelming amount of information is crucial if we want to help people overcome pathologies" that affect locomtion.
Two properties of the fish, called glass knifefish, made them ideal for motion studies. First, the nocturnal fish “see” in the dark by emitting weak electric signals and gathering feedback through special electroreceptors in their brain cells. Second, the fish are capable of moving back and forth in a small tube, a behavior crucial to the study design.
The researcehrs used robotics to move a small plastic tube back and forth with increasing frequency. The fish, which used the tube as a hiding place, performed an electrical tracking technique to stay hidden in the tube as it moved. But the fish could only process the speed of the moving tube below a frequency of one motion per second (1Hz), a quality scientists describe as “low-pass” since receptors in brain cells only detect frequencies lower than a certain limit.
This low-pass activity, however, does not match previous predictions for the electroreceptors.
“I would say that it has been known for some time that the electroreceptors are more sensitive to frequencies above 1Hz than below 1Hz -- that is, the receptors have a ‘high-pass’ property,” Cowan said.
Cowan and Fortune realized that previous studies had not incorporated Newton’s Laws of motion into an analysis of animal locomotion. Once they used a mechanics analysis to apply these laws to their results, they developed a prediction for a high-pass filter which matched the known high-pass characteristics of the fish’s electroreceptor.
According to the researchers, fish brains, and likely human brains as well, use a high-pass filter to account for Newton’s laws in simple and unconscious acts, such as a person reaching for a coffee cup.
This research may contribute to medical advances in humans, including better prosthetic limbs and improved rehabilitative techniques for people suffering from strokes, cerebral palsy and other debilitating conditions.
"With this basic knowledge, we hope one day to be able to ‘tune' artificial systems, such as prosthetics, so that they don't have the jerky and rough movements that most robots have, which is critical for medical applications," Fortune said.
Written by Ojus Doshi
Journal of Young
Investigators. 2008. Volume 16.
Copyright © 2008 by Doshi Ojus and and JYI. All rights reserved.
Copyright © 2008 by Doshi Ojus and and JYI. All rights reserved.