For the paper:

Rossant C, Leijon S, Magnusson AK, Brette R (2011) Sensitivity of
noisy neurons to coincident inputs. J Neurosci 31:17193-206

Abstract:

How do neurons compute? Two main theories compete: neurons could
temporally integrate noisy inputs (rate-based theories) or they could
detect coincident input spikes (spike timing-based
theories). Correlations at fine timescales have been observed in many
areas of the nervous system, but they might have a minor impact. To
address this issue, we used a probabilistic approach to quantify the
impact of coincidences on neuronal response in the presence of
fluctuating synaptic activity. We found that when excitation and
inhibition are balanced, as in the sensory cortex in vivo, synchrony
in a very small proportion of inputs results in dramatic increases in
output firing rate. Our theory was experimentally validated with in
vitro recordings of cortical neurons of mice. We conclude that not
only are noisy neurons well equipped to detect coincidences, but they
are so sensitive to fine correlations that a rate-based description of
neural computation is unlikely to be accurate in general.

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http://briansimulator.org/docs/examples-frompapers_Rossant_et_al_2011.html

The simulation generates images similar to Fig. 4A,B in the paper:



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