Fernando Montani
National University of La Plata
44 Papers
119 Citations
Fernando Montani is an academic researcher from National University of La Plata. The author has contributed to research in topics: Computer science & Population. The author has an hindex of 14, co-authored 36 publications. Previous affiliations of Fernando Montani include Imperial College London & Istituto Italiano di Tecnologia.
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Papers
The impact of high-order interactions on the rate of synchronous discharge and information transmission in somatosensory cortex
Fernando Montani,Robin A. A. Ince,Riccardo Senatore,Ehsan Arabzadeh,Mathew E. Diamond,Stefano Panzeri,Stefano Panzeri +6 more
TL;DR: The rate of synchronous discharge of a local population of neurons is considered, a macroscopic index of the activation of the neural network that can be measured experimentally and it is found that correlations of higher order progressively decrease the information available through the neural population.
Automatic online spike sorting with singular value decomposition and fuzzy C-mean clustering
Andriy Oliynyk,Andriy Oliynyk,Claudio Bonifazzi,Fernando Montani,Luciano Fadiga,Luciano Fadiga +5 more
TL;DR: This new software provides neuroscience laboratories with a new tool for fast and robust online classification of single neuron activity, and could become crucial in situations when online spike detection from multiple electrodes is paramount, such as in human clinical recordings or in brain-computer interfaces.
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Entropy-Complexity Characterization of Brain Development in Chickens
TL;DR: Electroencephalography (EEG)ects the electrical activity of the brain, which can be considered chaotic and ruled by a nonlinear dynamics, and identifies the dynamic of the developing chicken brain within the zone of a chaotic dissipative behavior in the plane H C.
36
Efficiency characterization of a large neuronal network: A causal information approach
TL;DR: A simple network of cortical spiking neurons with axonal conduction delays and spike timing dependent plasticity, representative of a cortical column or hypercolumn with a large proportion of inhibitory neurons is considered, inferring the emergent dynamical properties of the system.
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Causal information quantification of prominent dynamical features of biological neurons.
TL;DR: This paper presents a novel methodology to characterize the dynamics of this system, which takes into account the fine temporal ‘structures’ of the complex neuronal signals and accurately distinguish the most fundamental properties of neurophysiological neurons.