65 research outputs found
Holographic Calculations of Renyi Entropy
We extend the approach of Casini, Huerta and Myers to a new calculation of
the Renyi entropy of a general CFT in d dimensions with a spherical entangling
surface, in terms of certain thermal partition functions. We apply this
approach to calculate the Renyi entropy in various holographic models. Our
results indicate that in general, the Renyi entropy will be a complicated
nonlinear function of the central charges and other parameters which
characterize the CFT. We also exhibit the relation between this new thermal
calculation and a conventional calculation of the Renyi entropy where a twist
operator is inserted on the spherical entangling surface. The latter insight
also allows us to calculate the scaling dimension of the twist operators in the
holographic models.Comment: 71 pages, 6 figure
25th annual computational neuroscience meeting: CNS-2016
The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong
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