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Brain can be trained to process sound in alternate way, study shows UCSF
scientists have found that the brains of rats can be trained to learn an
alternate way of processing changes in the loudness of sound. The
discovery, they say, has potential for the treatment of hearing loss,
autism, and other sensory disabilities in humans. It also gives clues,
they say, about the process of learning and the way we perceive the world.
"We addressed a very fundamental question," says Daniel B. Polley, PhD,
lead author of the study. "When we notice a sound getting louder, what
happens in our brain so that we know it's getting louder?"
Polley is a postdoctoral research fellow in the laboratory of senior
author Michael M. Merzenich, PhD, co-director of the Coleman Memorial
Laboratory in the UCSF Keck Center for Integrative Neuroscience and UCSF
professor of otolaryngology.
The study was published recently in Proceedings of the National Academy of
Sciences (November 16, 2004).
"This is a very old idea," Polley notes. "How to relate the bigness of a
stimulus to the bigness of its internal representation in the brain." Over
the centuries, philosophers and scientists have put together a picture of
how our brains model the world through the mechanism of our senses.
Physical stimuli such as light, sound, and touch are converted by our
sensory organs -- eyes, ears, and skin -- into electrical signals, which
are processed by neurons in different areas of the brain. As those neurons
fire, we see, hear, and feel. When the light or sound changes in
intensity, our neurons fire faster or slower in direct ratio to the
change. That ratio varies depending on the sense involved, but is constant
for each sense: the louder a sound, the faster the neurons in the auditory
cortex fire.
But now that picture has changed. Polley trained two groups of rats to
become " experts" at discriminating between very small differences in
loudness -- an ability that untrained rats do not have. He then looked at
how the expert rats processed changes in loudness compared to two groups
of untrained rats, and found that the auditory cortex in the expert rats
contained groups of neurons that had become selective for specific volume
levels -- they fired only at those levels and were quiet otherwise. This
physiological change in the brain, called "plasticity," has been widely
observed in humans and animals who have learned new skills.
Then came the breakthrough discovery: the expert rats were processing
volume changes in a new and different way. In the brains of the untrained
rats, the overall neural response rate increased as the sound got louder
and louder, as the classical model would predict. In the expert rats,
however, the overall response rate of the selective neurons increased
until the sound reached a loudness threshold of 40 decibels -- and then
leveled off while the loudness increased 100-fold, from 40 to 80 decibels.
"At first glance, this was not good," observes Polley: If their neurons
were not increasing their firing rate, how were the expert rats
registering the increase in volume? David T. Blake, PhD, UCSF assistant
research physiologist and a co-author of the study, cracked the puzzle.
Instead of looking for a simple increase in firing rate, Blake measured
the rate at which the firing changed, either up or down. This rate turned
out to be in exact proportion to the increase in volume -- and at the same
ratio as the firing rate increase. Tests confirmed that the untrained
rats' brains were not registering volume increases in this new way; it had
been learned by the expert rats as they became better at discriminating
changes in volume.
Polley concludes, "There is still proportionality between response
strength in the brain and the stimulus. But now neurons are much more
selective, and can represent sound intensity with decreasing firing rates
as well as increasing firing rates." This system is "optimal" for
representing subtle changes in loudness, reasons Polley, because "it gives
you two directions to change through," making it many times more
responsive than a simple firing rate increase. "And it becomes optimized
through learning."
The discovery has several implications. From a practical viewpoint, "I
think it has quite a bit to offer," says Christoph E. Schreiner, UCSF
professor of otolaryngology and a co-author of the study. In particular,
it might present a technique for retraining people with partial hearing
loss, who often cannot hear very soft sounds but have normal hearing at
higher volume levels.
"There's a very steep volume curve that goes from soft to very loud right
away, and people have a hard time with that," Schreiner explains,
"especially for hearing-aid users." However, they -- or their auditory
cortexes -- might be trained to be more sensitive to minor volume changes
at the lower threshold of hearing, "so this steep transition doesn't
bother them anymore." Similarly, such training might be of value to
profoundly hearing-impaired people with cochlear implants, which replace
the function of the inner ear but are not as sensitive to small volume
changes.
Another group that might be helped is children with sensory-modulation
disorders, including children with autism. These children are
"overwhelmingly sensitive" to changes in their environment, explains
Polley. "So when presented with a moderate stimulus -- a sound, a touch, a
flash of light -- they respond as if their entire sensory systems have
become overwhelmed. What might be needed in their brains is greater
selectivity." Potentially, they could be trained to distinguish smaller
degrees of change in their environments. Being perceived as gradual, these
changes would be less overwhelming.
From a psychological viewpoint, the study says something about how we
acquire and refine new skills. When we speak of training a musician's ear
or a painter' s eye, speculates Polley, we may be referring to the
alternate sensory processing system employed by the expert rats. "This is
implicit learning," he says. "How do we learn the skills that distinguish
one tradesman from another tradesman? These processes are undoubtedly
operating in these types of learning behaviors, and they most likely are
responsible for expertise. We are looking at the neural substrate for
these lifelong learning processes."
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