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Plotting gridness scores as a function of bump probability indicated that bump formation was necessary, although not sufficient for grid formation, while plotting the first autocorrelation peak as a function of bump probability supported our conclusion that grid computation and gamma activity are not closely related.
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We present a methodology for building such auto-tuned DSELs, as well as a software infrastructure and example DSELs using the infrastructure, including a DSEL for structured grid computations and two DSELs for graph algorithms.
The distinct control of rate coded grid computations and gamma oscillations by noise, gE and gI was independent of the detailed implementation of the E-I models we considered and was maintained in more complex models incorporating I-I and E-E coupling.
We show that moderate intrinsic noise massively increases the range of synaptic strengths supporting gamma oscillations and grid computation.
They found that noise can increase the range of synaptic strengths with which gamma activity and grid computations are produced, and that synaptic gamma frequency and amplitude can be modulated independently from the grid firing.
The advantage in opting for grid computation is so high that the concept in itself has given rise to challenges that motivate technological advancements in other areas be it web services, patterns (analysis, design or architectural), grid markup language, semantic grid or at the programming level.
The schematic diagram of ( i^{text{th}} ) independent distribution grid computation is shown as Fig. 3.
Open image in new window Fig. 3 Illustration of the i th independent distribution grid computation model.
Grid computation to test model assumptions is also developed for these two types of models.
Since the presence of bump attractors is necessary for grid computation, we tested whether networks with only structured E-E connections can generate activity bumps.
The relationship between noise intensity and gamma differed from that for grid computations.
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