The neuron model used in
Characterization of an advanced neuron model
... Figure 7 – Voltage traces of prediction and target data for a rapidly adaptive neuron are shown in the graph. Target parameters θ 0 and estimated parameters are given in the table beside, along with the percentage ...
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The Leaky Integrate-and-Fire Neuron Model
... here, we should substitute a time-varying current for the constant current used in the previous simulation. One way to do this in Brian is to use a TimedArray: lif.I = TimedArray((15 + 5*randn(1000))*mV) This ...
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Investigation of a Chaotic Spiking Neuron Model
... NDS model in stabilizing orbits. A single NDS neuron with a time-delayed self-feedback connection is used with different period lengths τ ∈ [50, ...been used, and the system then run and the ...
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Linearization of the Morris-Lecar Neuron Model
... The stability of a system centers around fixed points, which are points at which both differential equations are 0. 17 These can be either stable, unstable or lead to limit cycles. Phase plane plots are used to ...
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Memory and forgetting processes with the firing neuron model
... most used rule for such models is the spike time dependent plasticity (STDP) sometimes completed with details of intracellular calcium turnover [8, 21, ...easily used within computer simulations or ...
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Temporal integration by calcium dynamics in a model neuron
... Neurons in several brain areas show sustained spiking activity follow- ing a transient stimulus, with firing levels that vary with the stimulus parameters in a graded manner 1–4 . In some areas, the sustained firing ...
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CHAPTER I From Biological to Artificial Neuron Model
... is used as the neuron output function, and binary input values 0 and 1 are assumed, the basic Boolean functions AND, OR and NOT of two variables can be implemented by choosing appropriate weights and ...
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A Rate-Reduced Neuron Model for Complex Spiking Behavior
... rate-reduced neuron model that captures a wide range of complex, biologically plausible, and physiologically relevant spiking ...the model can mimic different neuronal filter properties. It can be ...
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An Efficient Perforation Based Neuron Model for Digital Application
... Applications of natural and of artificial neural networks:The utility of artificial neural network models lies in the fact that they can be used to infer a function from observations and also to use it. This is ...
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Evaluation of the role of an antioxidant gene in NSC-34 motor neuron-like cells as a model of a motor neuron disease
... SMA model. In order to do so, a lentivirus was used to confer stable PLS3 overexpression in NSC-34 ...primary neuron types across a broad range of species, including humans, resulting in long-term ...
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Realization of Logic Gates Using Mcculloch-Pitts Neuron Model
... It is sometimes called as XOR gate or exclusive or gate. It gives a true output when the number of true inputs is odd. If both the inputs are true and both are false then the output is false. These are used to ...
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Quantitative analysis of a neuron model and its application to directional selectivity in the retina
... was used to explore nonlinear synaptic effects in passive dendritic trees of arbitrary ...was used to show that shunting inhibition can be effective when located off the direct-path between the excitation ...
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Digital Implementation of the 2-compartmental Pinsky-Rinzel Pyramidal Neuron Model
... Pinsky-Rinzel model is a nonlinear 2-compartmental model for CA3 pyramidal cell which widely used in ...pyramidal neuron model is proposed by replacing its complex differential ...
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Deep Neural Model Inspection and Comparison via Functional Neuron Pathways
... be used to formulate ex- planations for differences in performance between models based on relevant linguistic or task knowl- edge that is identified as learned or not learned by the ...
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Purkinje neuron Ca2+ influx reduction rescues ataxia in SCA28 model
... widely used, well-tolerated antibiotic drug that rep- resents an immediately available therapy for SCA28 patients as well as for those affected by other SCAs characterized by ...
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Learning Rates in Generalized Neuron Model for Short Term Load Forecasting
... of model, better modeling result, include the feature of adaptivity, an artificial neural network (ANN) has been used for ...ANN model is the requirement of large training time which depends on size ...
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A Spiking Neuron Based Feature Model for Real Time Object Recognition
... hybrid model to perform the detection of some real time ...presented model used the spiking neuron based PCA approach to perform the real time pattern detection over the ...spiking ...
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The neurotoxicity of amyloid β-protein oligomers is reversible in a primary neuron model
... culture model in which relatively low concentrations of Aβ-O induce modest neuronal ...our model reflects the characteristic features of AD ...we used an experimental paradigm in which neurons ...
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Electricity demand forecasting using a sarimamultiplicative single neuron hybrid model
... is used to capture the linear components in the time series, artifi cial neural networks are applied to forecast the remaining nonlinearities in the shocks of the SARIMA ...forecasting model by combining the ...
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A Neuron Model with Dendritic Nonlinearity for Predicting the Influence of Overreaction in Shanghai Stock Market
... Keywords Neuron Model with Dendritic Nonlinearity, Overreaction, Prediction, Stock Market ...way used to predict the extent of stock-market weak-form efficiency is through testing for the effect of ...
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