# What is the difference between spike-triggered averaging and reverse correlation?

I'm interested in the difference between spike-triggered averaging and reverse correlation.

In some papers (i.e., Schwartz, Odelia, et al) I see the term 'Spike Triggered Averaging'. In others, (ie Ringach et al 2004) I see the term 'Reverse Correlation'. According to wikipedia, they are the same:

Spike-triggered averaging is also commonly referred to as “reverse correlation″ or “white-noise analysis”

I was wondering though: Is there a subtle difference between spike-triggered averaging and reverse correlation?

### References

• Schwartz, Odelia, et al (2006). "Spike-triggered neural characterization." Journal of Vision 6.4
• Ringach, Dario, and Robert Shapley. "Reverse correlation in neurophysiology." Cognitive Science 28.2 (2004): 147-166
-

There's the naïve version of spike triggered averaging, and the sophisticated version. Both of them are consistent estimators for a linear-nonlinear system under certain conditions (Paninski, 2003). If your stimulus is $x_i$ and your spike count in a small bin is $y_i$, naïve version is $$\mathrm{STA} = \frac{1}{N} \sum_i x_i y_i$$ The sophisticated version is equivalent to linear regression where a (pseudo-)inverse of the stimulus covariance is premultiplied to the naïve version. The naïve version converges slower in general.