I have two signals that represent the response of a neuron under two different conditions.
- Signal 1 (S1): response to Stimulus A
- Signal 2 (S2): response to Stimulus A+B
The response to stimulus A is common in both signals but I am interested in the response to stimulus B only. Because the signals are noisy, they have been acquired multiple times. S1 is acquired 60 times and S2 is acquired only 4 times.
Will averaging S1 over these 60 acquisitions and S2 over 4 (Figure 1) and then subtracting the averaged signals (S2_avg - S1_avg) give me a better representation of response to Stimulus B or should both the signals be averaged across equal acquisitions (Figure 2)?
Averaging S1 60 times really smooths the response to Stimulus A but compared to this, response to Stimulus A is not smooth in S2 as it is only averaged 4 times. So in this way, what I understand is by averaging S1 many times might actually be a disadvantage.
Additional info following answers: my underlying assumption is that the neuron behaves like an LTI system. My concern is that averaging S1 many times smoothes it as compared to response to stimulus A in S2. As such, subtracting them would not really remove the common signal in them.