The long and the short of behavioral statistics: A link to
depression?
You just move like a mouse, or do so abnormally like a mutant mouse
The brain is no longer a mysterious black box. Elucidation of the
human genome
is having a profound impact on the understanding of brain function in
health and
disease. However, genes cannot be systematically manipulated in
humans, and this
is why animal models of human functions are being developed.
Now that the human and mice genome sequences are known, unprecedented
opportunities arise for the advancement of psychology and psychiatry.
But there
are some fundamental limitations: while much of psychology and
psychiatry relies
on the evaluation of questionnaires and self-reports, mice are
notoriously
non-compliant with these.
Therefore, the only alternative is to resort to objective tests.
Indeed mice
models of behaviour have been proposed, yet such models are generally
considered
to be a seriously inadequate representation of human-specific
disorders.
A new holistic approach to assess model behaviour has been proposed
and
evaluated by researchers at the University of Tokyo (Yoshiharu
Yamamoto, Toru
Nakamura and Zbigniew Struzik) and Osaka Bioscience Institute (Toru
Takumi). The
lifestyle of the mouse has been monitored in a way comparable with
that of
monitoring humans. Every move of the animal is recorded by pressure
sensors
under the cage, and this information is collected for more than 24
hours. The
findings are published in the journal PLoS ONE.
This information is next processed to reflect how many small and how
many large
movements the mouse undertakes and, very importantly, how long they
last. These
durations of small and large movements are then processed to provide a
mathematical representation of how probable it is that the mouse will
make small
or large moves of a certain duration.
Similarly, the team at the University of Tokyo evaluated the lifestyle
of
healthy humans by monitoring their wrist activity for more than 24
hours and
plotting similar graphs of probabilities of large and small moves. The
surprising discovery came when the team compared the probabilities of
durations
between mice and humans and realised that there is no difference in
behaviour
statistics.
In fact, the observed probabilistic laws expressed as graphs for the
durations
of both resting periods and active periods collapsed when rescaled by
the
well-known allometric factor, capturing the difference in average
resting and
activity durations between mice and humans.
No less stunning was the realisation that mice with an artificially
eliminated
gene regulating the circadian rhythm ---so-called Period2 gene "knock
out"
mice--- showed a distortion in the resting duration probabilistic law
analogous
to that previously observed by the team in humans suffering from major
depressive disorder.
This discovery is not only expected to help in the practical diagnosis
and
evaluation of depressive disorder, but even in the development of a
new drug
targeting the "depression genome".
The observation that healthy mice show behaviour statistics during
rest and
activity indistinguishable from humans may have a fundamental impact
on the
understanding of the higher brain functions. This intriguing
hypothesis has been
suggested by the team, who point out that similar statistics are shown
in
activity avalanches between neuronal cells grown in vitro in a Petri
dish.
The statistics of such an artificially raised neuronal "society" are
also known
to change when information exchange is pharmacologically suppressed.
The
statistics of such neurons unable to contact their neighbours come
close to
those observed in "depressed" mice and humans ---could the analogy run
as deep
as this" The current finding indicates that perhaps, yes indeed.
Citation: Nakamura T, Takumi T, Takano A, Aoyagi N, Yoshiuchi K, et
al. (2008)
Of Mice and Men - Universality and Breakdown of Behavioral
Organization. PLoS
ONE 3(4): e2050. doi:10.1371/journal.pone.0002050
Source: Public Library of Science
http://www.physorg.com/news128750650.html
date: Mon, 5 May 2008 05:44:19 -0700 (PDT)
author: Lance
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