Name
Title | ||
|---|---|---|
Basic Difference Between Brain and Computer: Integration of Asynchronous Processes Implemented as Hardware Model of the Retina |
Abstract | ||
|---|---|---|
There exists a common view that the brain acts like a Turing machine: The machine reads information from an infinite tape (sensory data) and, on the basis of the machine's state and information from the tape, an action (decision) is made. The main problem with this model lies in how to synchronize a large number of tapes in an adaptive way so that the machine is able to accomplish tasks such as object classification. We propose that such mechanisms exist already in the eye. A popular view is that the retina, typically associated with high gain and adaptation for light processing, is actually performing local preprocessing by means of its center-surround receptive field. We would like to show another property of the retina: The ability to integrate many independent processes. We believe that this integration is implemented by synchronization of neuronal oscillations. In this paper, we present a model of the retina consisting of a series of coupled oscillators which can synchronize on several scales. Synchronization is an analog process which is converted into a digital spike train in the output of the retina. We have developed a hardware implementation of this model, which enables us to carry out rapid simulation of multineuron oscillatory dynamics. We show that the properties of the spike trains in our model are similar to those found in vivo in the cat retina. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/TNN.2006.882814 | IEEE transactions on neural networks / a publication of the IEEE Neural Networks Council |
Keywords | Field | DocType |
analog process,center-surround receptive field,asynchronous processes,index terms—brain computation,brain act,synchronization,basic difference,universal turing machine,infinite tape,visual system.,quasi-periodic oscillations,digital spike train,turing machine,spike train,common view,popular view,hardware model,cat retina,modeling,in vivo,cerebro,central nervous system,classification,synchronisation,neural network,turing machines,neural nets,visual system,indexing terms,oscillations,receptive field | Receptive field,Asynchronous communication,Synchronization,Spike train,Universal Turing machine,Computer science,Turing machine,Preprocessor,Artificial intelligence,Computer hardware,Artificial neural network,Machine learning | Journal |
Volume | Issue | ISSN |
18 | 1 | 1045-9227 |
Citations | PageRank | References |
11 | 1.36 | 10 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andrzej W Przybyszewski | 1 | 11 | 1.36 |
| Paul S Linsay | 2 | 11 | 1.36 |
| P. Gaudiano | 3 | 12 | 1.71 |
| Christopher M Wilson | 4 | 11 | 1.36 |