On 21 Dec 1995, Jan Vorbrueggen wrote:
> In article <4b536l$baq at eis.wfunet.wfu.edu> laubach at biogfx.neuro.wfu.edu (Mark
> Laubach) writes:
>> When are you going to distinguish the stimuli? After looking at all the
> trials on average?
>> No, potentially during/immediately after the stimulus.
>> My point was that we need trial-by-trial predictors for analyzing neuron
> activity.
>> I understood that.
>> A cross-correlation is nothing more than a correlational measure between
> time-series and a correlational measure is not a predictor for
> trial-by-trial classification.
>> Ah. You seem to be thinking of using the cross-correlation of one cell's
> activity during different trials - that's not what I meant. I was talking of
> the cross-correlation of two cells simultaneously active, which you (or
> another cell) can compute on-the-fly, as it were. This _does_ enable you (or
> that other cell) to distinguish the two stimuli as they are occuring.
>> Jan
correlations computed on-the-fly sounds interesting. But to do this
it seems that a time measure should be specified in advance. At this
time I suspect that theta may be the underlying basic frequency or
reference wave. It is likely to be different for different functions.
So if a spike recording can be observed during one half of a cycle it
would be considered to be on for the area being observed. Correlations
from such research may lead to success. Ron Blue
