Neurons, AfferentMathematicsNeural Networks (ComputerAs neuromodulation therapy has grown, so has the recognition that computational models can provide important insights into the design, operation, and clinical application of neurostimulation systems. Models of deep brain stimulation and spinal cord ...
demands through coordination of spiking activity in large populations of neurons across the brain globally7. In other words, a model bridging cognitive computational neuroscience and clinical neurology is needed. We propose that our model of neurodegeneration represents a step in that direction ...
Computational models of visual neurons specialised in the detection of periodic and aperio- dic oriented visual stimuli: bar and grating cells. Biological Cybernetics, 76:83-96, 1997.Petkov N. and Kruizinga P. (1997): Computational models of visual neurons specialised in the detection of periodic...
functionsofthebrainformsthebasisforunderstandingadvancedprocessesinthebrain. Neuronalculturesshowremarkablepropertiesofself-organizationandsynchronizationwhen allowedtogrowwithoutinterference.Clustersofneuronsareseentoformwithoutanyexternal helpintheseneuronalcultures.Theseclustersproceedtoformanetworkofinterconnectswhich allowsthe...
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.....
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 ...
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...
DNNs consist of a network of interconnected layers of artificial neurons or nodes which are simple mathematical functions (Kelleher 2019: 65). These models can be said to emerge from an intensive training—or “learning”—process, which entails the processing of a vast set of data across DNNs...
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, ...
The Journal of Computational Neuroscience focuses on understanding brain function at the level of neurons and circuits via computational and model-based approaches that are tied to biology and are experimentally testable. Publishes full-length original papers, as well as rapid communications, perspectives...