Spiking Sensory Neurons for Analyzing Electrophysiological Data
نویسندگان
چکیده
منابع مشابه
Toward Data Representation with Formal Spiking Neurons
Notable advances in the understanding of neural processing have been made when sensory systems were investigated from the viewpoint of adaptation to the statistical structure of its input space. For this purpose, mathematical methods for data representation were used. Here, we point out that emphasis on the input structure has happened at cost of the biological plausibility of the corresponding...
متن کاملAnalyzing large-scale spiking neural data with HRLAnalysis™
The additional capabilities provided by high-performance neural simulation environments and modern computing hardware has allowed for the modeling of increasingly larger spiking neural networks. This is important for exploring more anatomically detailed networks but the corresponding accumulation in data can make analyzing the results of these simulations difficult. This is further compounded b...
متن کاملNetworks of Spiking Neurons :
The computational power of formal models for networks of spiking neurons is compared with that of other neural network models based on McCulloch Pitts neurons (i.e. threshold gates) respectively sigmoidal gates. In particular it is shown that networks of spiking neurons are computationally more powerful than these other neural network models. A concrete biologically relevant function is exhibit...
متن کاملSpiking Neurons on GPUs
Simulating large networks of spiking neurons is a very common task in the areas of Neuroinformatics and Computational Neurosciences. These simulations are time-consuming but also often intrinsically parallel. The recent advent of powerful and programmable graphic cards seems to be a pertinent solution to the problem: they offer a cheap but efficient possibility to serve as very fast co-processo...
متن کاملFractionally Predictive Spiking Neurons
Recent experimental work has suggested that the neural firing rate can be interpreted as a fractional derivative, at least when signal variation induces neural adaptation. Here, we show that the actual neural spike-train itself can be considered as the fractional derivative, provided that the neural signal is approximated by a sum of power-law kernels. A simple standard thresholding spiking neu...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: ECS Journal of Solid State Science and Technology
سال: 2020
ISSN: 2162-8777
DOI: 10.1149/2162-8777/ab9e9f