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This model is the Integrate-and-Fire (IF) model that was mentioned in Section 2.3. Closely related to IF model is a model called Spike Response Model (SRM) (Gerstner, W. (1995) [15] Pages 738-758) that is dependent on impulse function response convoluted with the input stimulus signal. This forms a base for a large number of models developed ...
Convolution has applications that include probability, statistics, acoustics, spectroscopy, signal processing and image processing, geophysics, engineering, physics, computer vision and differential equations. [1] The convolution can be defined for functions on Euclidean space and other groups (as algebraic structures).
The degree of convolution is generally greater in species with more complex behavior, which benefits from the increased surface area. The cerebellum, or "little brain," is behind the brainstem and below the occipital lobe of the cerebrum in humans. Its purposes include the coordination of fine sensorimotor tasks, and it may be involved in some ...
A gyrification index (GI) is a measure of the magnitude of cortical convolutions on the surface of the mammalian brain. [ 6 ] [ 35 ] Reptile's and bird's brains do not show gyrification. Mammals with a high GI are generally larger than those with a low GI; for example the pilot whale and bottlenose dolphin show the highest GI values.
Given the complex structure of the human brain, measures that can represent the small-world properties of the brain network are of great importance since it simplifies the systems and becomes decipherable. Graph theoretical approaches have set up a mathematical framework to model the pairwise communications between elements of a network. [13]
Cortical convolution has increased the folding of the brain’s surface over the course of human evolution. It has been hypothesized that the high degree of cortical convolution may be a neurological substrate that supports some of the human brain's most distinctive cognitive abilities.
The FitzHugh–Nagumo model is a simplication of the Hodgkin–Huxley model. The Hindmarsh–Rose model is an extension which describes neuronal spike bursts. The Morris–Lecar model is a modification which does not generate spikes, but describes slow-wave propagation, which is implicated in the inhibitory synaptic mechanisms of central ...
In artificial neural networks, a convolutional layer is a type of network layer that applies a convolution operation to the input. Convolutional layers are some of the primary building blocks of convolutional neural networks (CNNs), a class of neural network most commonly applied to images, video, audio, and other data that have the property of uniform translational symmetry.