A computer algorithm for spatio-temporal patterns in interactive neuron populations
β Scribed by S.M. Ahn
- Publisher
- Elsevier Science
- Year
- 1975
- Weight
- 238 KB
- Volume
- 4
- Category
- Article
- ISSN
- 0010-468X
No coin nor oath required. For personal study only.
β¦ Synopsis
A computer algorithm has been developed which enables numerical computations to be performed for interactive neuron populations whose spatio-temporal behaviors are represented by a set of certain integro-differential equations. The computation is based on the fact that the eigenfunctions of a symmetric Hilbert-Schmidt operator form a set of complete orthonormal functions in L2 space. This algorithm differs from the ones which computes the value of the solution at each (x, t) point in that it computes the coefficients corresponding to the eigenfunctions. Therefore it is shown that the error' in the coefficient of one eigenfunction does not propagate to that of another eigenfunction from one sampling time to the next one. This enables us to analyze the temporal behavior of one spatial frequency which is not affected by that of the other spatial frequencies.
Neuron populations
Spatio-temporal behaviors Integro-differential equations
π SIMILAR VOLUMES
## Abstract This study examined the sea surface temperature (SST) patterns in the Gulf of Guinea (GOG) and discussed their implications for the spatioβtemporal variability of precipitation in West Africa. The SST data spanning over 49 years (1950β1998) at 2Β° Γ 2Β° resolutions were sourced from the a
It is shown that real-time computations on spike patterns and temporal integration of information in neural microcircuit models are compatible with potentially descruptive additional inputs such as oscillations. A minor change in the connection statistics of such circuits (making synaptic connection