Songbirds
yield insight into speech production
With the help of a little singing bird, Penn State physicists are
gaining insight into how the human brain functions, which may lead to a
better understanding of complex vocal behaviour, human speech production
and ultimately, speech disorders and related diseases.
Dezhe Jin, assistant professor of physics, is looking at how
songbirds transmit impulses through nerve cells in the brain to produce
a complex behaviour, such as singing.
Songbirds are particularly well suited for studying speech production
and syntax - the rules of syllable or word sequence - because there are
more similarities between birdsong and human speech than one may
initially think.
"We are not only interested in birds," Jin told attendees on March 18
at the American Physical Society's March meeting in Portland, Ore.
"We are ultimately interested in studying how the human brain works
and better understanding ourselves." While many animals communicate
vocally, songbirds are among the few that learn their communication
sounds in a manner similar to humans. Although human and bird brains are
different, researchers believe that both the speech and song learning
processes involve similar neural mechanisms.
"It is very hard to do human experiments," said Jin. "So, to conduct
these experiments, we use the songbird.
"Songbirds are much simpler than humans, and have fewer neurons."
Alexay Kozhevnikov, assistant professor of physics, works with Jin to
conduct recordings of brain activity that occurs in songbirds during
singing. In this way, the songbird's brain acts as a laboratory for
understanding neural networking.
Because the major brain components involved in song production are
well documented, Jin uses them as a framework for designing
computational models. He can test these models against the neural
recordings, and eventually determine how the interconnection of these
networks leads to syllable production and syntax.
As in human language, birdsong is composed of syllables. However,
rather than a random string of syllables, the order follows a complex
and variable pattern, which is determined by restriction and
flexibility. Restriction states that a certain syllable can only be
followed by a specific set of other syllables. However, the syllable
that comes next is selected randomly from the possible set, creating the
flexibility.
The underlying mechanism for stringing together multiple song
syllables is similar to putting words together to form a sentence.
Flexibility allows the researchers to focus on how this mechanism
determines syllable syntax.
"The similarity between the restriction and flexibility is very
solid," said Jin. "You have to be cautious though because people will be
tempted to take it too far and assume that the birds are talking." Jin
shows that a particular syllable is encoded in a branching chain network
of neurons in the high vocal centre (HVC), or "control centre" for song
production in the brain. The HVC transmits precisely timed impulses, or
spikes, to downstream neurons that drive syllable production.
His model of impulse transmission in the brain predicts the syllable
sequence statistically will follow a partially observable Markov model.
This means that the decision at the branch point is random, and the
branch that propagates the signal is chosen independent of events
leading up to that point.
A key feature of Jin's model is the winner-take-all mechanism - when
an impulse reaches a branch point within the chain network, the signal
will continue on through one branch, while abandoning other potential
branches.
The syntax of birdsong syllable sequence is governed by the
connectivity of the neural networks.
"When the signal is passed on at a branch point, it is an
all-or-nothing transmission, in that both branches may sense the signal,
but the one that may receive a slightly stronger signal will win out and
the impulse will progress down that chain," says Jin.
The similarity between the neural networks in songbirds and humans
makes them important for understanding the brain circuitry that
underlies speech and language production. The knowledge obtained from
analysing the neural pathways in birdsong can function as a bridge to
address and treat speech and language disorders.
The National Science Foundation supported this work.
ScienceDaily
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