The output of neural networks underlies behaviours in all higher animals. Mathematical equations can be used to describe the electrical activity of neurons and neural networks and the underlying biophysical properties. These equations give rise to computational models of neurons and networks that can be...
A complete model of this type of selective degeneration requires a framework for physiology that allows static brain structure to support dynamic reconfiguring of functional operations in response to current high-level demands through coordination of spiking activity in large populations of neurons across ...
Biologically Plausible Computational Neurogenetic Models: Modeling the Interaction Between Genes, Neurons and Neural Networks The paper presents a theory and a new generic computational model of a biologically plausible artificial neuron and artificial neural network (ANN) that ca... N Kasabov,L Benusko...
Explicit neuron firing models are investigated for use in computational modeling of auditory processing. Models for primary auditory neurons are driven by the receptor signal from a hair cell model, which is driven in turn by a filtering model of basilar membrane motion. The output of the primary...
Over the past two decades, substantial progress has been made in deciphering the cellular and molecular mechanisms underlying adult neurogenesis and in understanding the role played by new neurons in brain function in animal models of health and disease. By contrast, knowledge regarding the extent.....
Due to the introduction of dendritic spikes into computational models of neurons, the complexity of a single neuron has become very similar to a convolutional net with two convolutional layers. As we see later the LNP model also uses non-linearities very similar to a rectified linear function, ...
As detailed above, we used linear mapping methods to make predictive models of neurons using features extracted from different layers in each embedding model. We used two linear mapping methods to predict neural measurements from ANN activations. Each of the mapping methods are explained below. Choic...
data analysis and modelling, structural and functional models of neurons, learning and other plasticity phenomena, complex systems dynamics, cognitive processes and artificial intelligence, methodologies for net design, bio-inspired systems and engineering, and applications in a broad variety of fields. ...
COMPUTATIONAL MODELS FOR THE CONTRAST-POLARITY SENSITIVEEDGE-DETECTING NEURONS反差极性敏感型运动边缘检测神经元的计算模型自组织时空感受野反差极性在栖类,在和哺乳类某些运动的视觉系统中发现 对刺激反差极性(变亮或变暗)敏感的运动边缘检测神经元.为揭示这类神经元的信息加工原理,以Wimbbauer等人提出了捍延insker...
of individual neurons, but are mediated by population dynamics in mesoscopic neural ensembles. Understanding this multiscale mapping is an important but nontrivial issue. Here, we bridge these different levels of description by showing how computational models parametrically map classic neuromodulatory ...