Raul Cristian Muresan

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We present a method that estimates the strength of neuronal oscillations at the cellular level, relying on autocorrelation histograms computed on spike trains. The method delivers a number, termed oscillation score, that estimates the degree to which a neuron is oscillating in a given frequency band. Moreover, it can also reliably identify the oscillation(More)
A novel method for pattern recognition using Discrete Fourier Transforms on the global pulse signal of a pulse-coupled neural network (PCNN) is presented in this paper. We describe the mathematical model of the PCNN and an original way of analyzing the pulse of the network in order to achieve scaleand translation-independent recognition for isolated(More)
We investigated spontaneous activity and excitability in large networks of artificial spiking neurons. We compared three different spiking neuron models: integrate-and-fire (IF), regular-spiking (RS), and resonator (RES). First, we show that different models have different frequency-dependent response properties, yielding large differences in excitability.(More)
RetinotopicNET is an efficient simulator for neural architectures with retinotopic-like receptive fields. The system has two main characteristics: it is event-driven and it takes advantage of the retinotopic arrangement in the receptive fields. The dynamics of the simulator are driven by the spike events of the simple integrate-and-fire neurons. By using an(More)
When computing a cross-correlation histogram, slower signal components can hinder the detection of faster components, which are often in the research focus. For example, precise neuronal synchronization often co-occurs with slow co-variation in neuronal rate responses. Here we present a method - dubbed scaled correlation analysis - that enables the(More)
Neuronal mechanisms underlying beta/gamma oscillations (20-80 Hz) are not completely understood. Here, we show that in vivo beta/gamma oscillations in the cat visual cortex sometimes exhibit remarkably stable frequency even when inputs fluctuate dramatically. Enhanced frequency stability is associated with stronger oscillations measured in individual units(More)
We present a novel viewpoint on the complexity of neural mechanisms, addressing some aspects of cortical processing, like memory, context modulation and coherence. Our simulation studies show how relatively small, recurrent microcircuits can interact with populations of neurons, achieving spontaneous memory / recall effects. Here, context modulation can(More)
Elaborated data-mining techniques are widely available today. Nevertheless, many non-linear relations among variables remain undiscovered in multi-dimensional datasets. To address this issue we propose a method based on the concept of fractal dimension that explores the structure of multivariate data and apply the method to simulated data, as well as to(More)
Mechanisms of explicit object recognition are often difficult to investigate and require stimuli with controlled features whose expression can be manipulated in a precise quantitative fashion. Here, we developed a novel method (called "Dots"), for generating visual stimuli, which is based on the progressive deformation of a regular lattice of dots, driven(More)