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Electrocatalytic activity of cobalt phthalocyanine CoPc adsorbed on a graphite electrode for the oxidation of reduced L-glutathione (GSH) and the reduction of its disulfide (GSSG) at physiological pH.
Modified electrodes coated by adsorbed cobalt phthalocyanines are known to show substantial electrocatalytic activity for the electro-oxidation of several thiols in alkaline aqueous solution. In thisExpand
  • 68
  • 1
Spike train statistics and Gibbs distributions
  • B. Cessac, R. Cofré
  • Mathematics, Computer Science
  • Journal of Physiology-Paris
  • 20 February 2013
This paper is based on a lecture given in the LACONEU summer school, Valparaiso, January 2012. We introduce Gibbs distribution in a general setting, including non stationary dynamics, and presentExpand
  • 17
  • 1
  • Open Access
Exact computation of the maximum-entropy potential of spiking neural-network models.
  • R. Cofré, B. Cessac
  • Physics, Computer Science
  • Physical review. E, Statistical, nonlinear, and…
  • 14 May 2014
Understanding how stimuli and synaptic connectivity influence the statistics of spike patterns in neural networks is a central question in computational neuroscience. The maximum-entropy approach hasExpand
  • 22
  • Open Access
Dynamics and spike trains statistics in conductance-based Integrate-and-Fire neural networks with chemical and electric synapses
Communication between neurons involves chemical synapses as well as electric synapses. On theoretical grounds, the role of gap junctions in encoding and shaping collective dynamics as well as spikeExpand
  • 12
  • Open Access
Dynamics and spike trains statistics in conductance-based integrate-and-fire neural networks with chemical and electric synapses
Abstract We investigate the effect of electric synapses (gap junctions) on collective neuronal dynamics and spike statistics in a conductance-based integrate-and-fire neural network, driven byExpand
  • 8
  • Open Access
Information Entropy Production of Maximum Entropy Markov Chains from Spike Trains
The spiking activity of neuronal networks follows laws that are not time-reversal symmetric; the notion of pre-synaptic and post-synaptic neurons, stimulus correlations and noise correlations have aExpand
  • 8
Achievement versus Aptitude in College Admissions: A Cautionary Note Based on Evidence from Chile.
Abstract In recent years there has been a debate over the alleged superiority of achievement tests over aptitude tests on the grounds that the first would be fairer for college admissions and lessExpand
  • 15
Large Deviations Properties of Maximum Entropy Markov Chains from Spike Trains
We consider the maximum entropy Markov chain inference approach to characterize the collective statistics of neuronal spike trains, focusing on the statistical properties of the inferred model. ToExpand
  • 4
  • Open Access
Estimating maximum entropy distributions from periodic orbits in spike trains
We present a method allowing to compute the shape of a Maximum Entropy potential with spatio-temporal constraints, from the periodic orbits appearing in the spike train.
  • 3
Dimensionality Reduction on Spatio-Temporal Maximum Entropy Models of Spiking Networks
Maximum entropy models (MEM) have been widely used in the last 10 years to characterize the statistics of networks of spiking neurons. A major drawback of this approach is that the number ofExpand
  • 8