Scientists have traditionally believed that the way our
brains process smells via neuron connections in the olfactory bulb was dictated
by the anatomy of the olfactory bulb and could only change slowly in response
A new study from researchers at the Center for the Neural Basis
of Cognition (CNBC), which is a joint project between Carnegie Mellon
University and the University of Pittsburgh, has described a mechanism called
Associate professor of biological sciences at Carnegie
Mellon Nathan Urban describes the process like this, “If you think of the brain
like a computer, then the connections between neurons are like the software
that the brain is running. Our work shows that this biological software is
changed rapidly as a function of the kind of input that the system receives.”
The researchers believe this ability to change neuronal
circuits on the fly depending on the input is the reason we are able to walk
into a room and notice a floral scent, then determine that it is certainly a
floral smell and then narrow it down to the smell of roses.
To prove that the neurons do behave as the scientists predicted;
a computer-modeling program was used to simulate the effects of stimuli on
slices of olfactory bulb from a mouse viewed under a microscope with a water
immersion objective at 20x, 40x, or 60x. The slices of mouse olfactory bulb
were excited with specific excitation wavelengths in the 480 to 520nm
range. The process was also videoed with a special camera.
The researchers then created a continuous firing rate
network model in MATLAB that represented a 25 x 25 array of simulated
non-spiking neurons representing olfactory bulb mitral cells. The simulated
cells active firing rate was represented by a continuous variable.
Using this process, Urban and other researchers on the
project were able to show that lateral inhibition is enhanced by dynamic
connectivity when a large number of neurons respond to a stimulus and filter
out the noise from other neurons. This separation of noise from other neurons
allows stimuli to be more clearly recognized and separated from other similar
quote: were able to show that lateral inhibition is enhanced by dynamic connectivity
quote: Also, can they move the test on to something other than just a mouse?