[Comp-neuro] recent abstracts on computational neuroscience in our lab

jtorres at ugr.es jtorres at ugr.es
Tue Feb 12 16:22:42 CET 2013

Dear Colleague

Below you can find abstracts and links to two of our recent papers in the
field of computational neuroscience which can be of interest for someone
in the neuroscience community:

1) S. Johnson, J. Marro and J. J. Torres,``Robust short-term memory
without synaptic learning'', PLoS ONE 8(1) e50276 (2013)

Short-term memory in the brain cannot in general be explained the way
long-term memory can – as a gradual modification of synaptic weights –
since it takes place too quickly. Theories based on some form of cellular
bistability, however, do not seem able to account for the fact that noisy
neurons can collectively store information in a robust manner. We show how
a sufficiently clustered network of simple model neurons can be instantly
induced into metastable states capable of retaining information for a
short time (a few seconds). The mechanism is robust to different network
topologies and kinds of neural model. This could constitute a viable means
available to the brain for sensory and/or short-term memory with no need
of synaptic learning. Relevant phenomena described by neurobiology and
psychology, such as local synchronization of synaptic inputs and power-law
statistics of forgetting avalanches, emerge naturally from this mechanism,
and we suggest possible experiments to test its viability in more
biological settings.


2) G. Pinamonti, J. Marro, J. J. Torres ``Stochastic resonance crossovers
in complex networks'', PLoS ONE 7(12), e51170 (2012)

Here we numerically study the emergence of stochastic resonance as a mild
phenomenon and how this transforms into an amazing enhancement of the
signal-to-noise ratio at several levels of a disturbing ambient noise. The
setting is a cooperative, interacting complex system modelled as an
Ising-Hopfield network in which the intensity of mutual interactions or
“synapses” varies with time in such a way that it accounts for, e.g.,
a kind of fatigue reported to occur in the cortex. This induces
nonequilibrium phase transitions whose rising comes associated to various
mechanisms producing two types of resonance. The model thus clarifies the
details of the signal transmission and the causes of correlation among
noise and signal. We also describe short-time persistent memory states,
and conclude on the limited relevance of the network wiring topology. Our
results, in qualitative agreement with the observation of excellent
transmission of weak signals in the brain when competing with both
intrinsic and external noise, are expected to be of wide validity and may
have technological application. We also present here a first contact
between the model behavior and psychotechnical data.


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