I’m curious where you got the highly specific “ranging from 0 to 1,000” bit, but moreover it’s misleading to mention rate coding as the be-all end all of neural coding, especially as it is largely out of date. Neural coding has been found to be more complex.
I don’t think “rate coding” can be called “out of date” when we don’t even have a ballbark estimate of how computation works in the brain. Research hot topics (namely, temporal coding) are not always indicative of progress.
Maybe you don’t understand what rate coding is. Population codes are still rates. The fundamental debate is over whether a population response r(t) contains all the relevant information needed to understand computations performed, or whether the statistical characteristics of the spike patterns themselves carry “extra” information. Here, r(t) is obtained by spike filtering, which removes the finer inter-spike-interval information.
Rate coding has not been completely discredited, it certainly plays a role, but computational efficiency considerations rule it out as the main coding method.
No one in theoretical neuroscience has ever said anything like this.
I don’t think “rate coding” can be called “out of date” when we don’t even have a ballbark estimate of how computation works in the brain. Research hot topics (namely, temporal coding) are not always indicative of progress.
Maybe you don’t understand what rate coding is. Population codes are still rates. The fundamental debate is over whether a population response r(t) contains all the relevant information needed to understand computations performed, or whether the statistical characteristics of the spike patterns themselves carry “extra” information. Here, r(t) is obtained by spike filtering, which removes the finer inter-spike-interval information.
No one in theoretical neuroscience has ever said anything like this.