Inferring and validating mechanistic models of neural microcircuits based on spike-train data
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In this paper we present a method for automatic detection of motor intention from in vivo neuronal recordings in monkeys. The analysis relies on a data base of spike trains collected in a series of experiments aiming to study the hand-eye coordination mech ...
We present a framework for efficient, accurate approximate Bayesian inference in generalized linear models (GLMs), based on the expectation propagation (EP) technique. The parameters can be endowed with a factorizing prior distribution, encoding properties ...
How the visual brain integrates temporally dispersed information is an open question. Often, it is assumed that the visual system simply sums light over a certain period of time (e.g. Bloch's law). However, in feature fusion, information presented later do ...
Neurons generate spikes reliably with millisecond precision if driven by a fluctuating current—is it then possible to predict the spike timing knowing the input? We determined parameters of an adapting threshold model using data recorded in vitro from 24 l ...
A neuron that is stimulated repeatedly by the same time-dependent stimulus exhibits slightly different spike timing at each trial. We compared the exact solution of the time-dependent firing rate for a stochastically spiking neuron model with refractorines ...
PhotoMEA is a biosensor useful for the analysis of an in vitro neuronal network, fully based on optical methods. Its function is based on the stimulation of neurons with caged glutamate and the recording of neuronal activity by Voltage-Sensitive fluorescen ...
In the present paper we propose a novel method for the identification and modeling of neural networks using extracellular spike recordings. We create a deterministic model of the effective network, whose dynamic behavior fits experimental data. The network ...
We describe evolution of spiking neural architectures to control navigation of autonomous mobile robots. Experimental results with simple fitness functions indicate that evolution can rapidly generate spiking circuits capable of navigating in textured envi ...
This work investigates the capacity of Integrate-and-Fire-type (I&F-type) models to quantitatively predict spike trains of real neurons in various laboratory and in vivo-like settings. A step-by-step methodology is developed to build an equivalent effectiv ...
We introduce a two-dimensional integrate-and-fire model that combines an exponential spike mechanism with an adaptation equation, based on recent theoretical findings. We describe a systematic method to estimate its parameters with simple electrophysiologi ...