I am setting up a classical conditioning paradigm with monetary rewards (three possible outcomes: reward, punishment, no monetary change). I aim at finding relative differences in SCR among these three types of events and I plan to use PsPM for my analysis. Since I am completely new to SCR recordings, I would like to ask advice regarding how to set some recording parameters.
I use BIOPAC Student Lab with the MP36 data acquisition unit, SS57LA lead for disposable setup and EL507 EDA Isotonic Gel Snap Electrodes.
Given this equipment, the BIOPAC software suggests using three sequential, biquadratic (second order) digital Infinite Impulse Response (IIR) filters as follows:
Low Pass IIR Filter
a. IIR Frequency: 65.5
b. IIR Quality Factor: 0.5
Low Pass IIR Filter
a. IIR Frequency: 38.5
b. IIR Quality Factor: 1
Band Stop IIR Filter
a. IIR Frequency: 50
b. IIR Quality Factor: 1
I would like to know if these parameters sound reasonable or if I should collect data without any filters during data acquisition. I worry to lose precious information by setting filters online, during data acquisition. What would you recommend?
I should add that I also plan to set the following parameters:
High Pass Filter: 0.05Hz (hardware filter implemented using resistors and capacitors in the front end circuitry of the data acquisition unit)
EDA channel sample rate = 2000Hz
Acquisition sampling rate = 2000Hz
Gain = x2000
Looking forward to hearing from you.
Many thanks and best,
Ambra
Last edit: Ambra Ferrari 2018-01-09
If you would like to refer to this comment somewhere else in this project, copy and paste the following link:
Dear Ambra
I would recommend not using any filters during acquisition, only an anti-alias low-pass filter at half the sample rate. Any other filtering (including the 0.05 Hz high-pass filter) can be done off-line. PsPM expects non-filtered data by default.
Dominik
If you would like to refer to this comment somewhere else in this project, copy and paste the following link:
Great thanks!
I have a further question, regarding experiment design this time. Does PsPM need baseline periods (i.e. rest periods with no stimulations at all), similar to what I would use for MRI designs?
Best, Ambra
If you would like to refer to this comment somewhere else in this project, copy and paste the following link:
this is an important question, not only for PsPM. For most psychophysiologial measures, the dynamic range is limited, so when stimulations come too close in succession, the mapping from stimulation to physiological measure becomes non-linear, which is a problem for most analysis approaches, PsPM and otherwise (e.g. computing averages over trial-by-trial peak amplitudes).
For SCR, we have specifically shown with intraneural stimulation that this mapping is linear up to about 1 stimulus every 1 seconds (Gerster et al. 2017), but I'd generally recommend to have longer inter-trial-intervals. For DCM specifically, I'd recommend having at least 5-10 s between trials, to improve estimability; for GLM shorter intervals will do. For other psychophysiological measures, I'd go by rules of thumb. Pupil size responses are rather fast, such that ITIs are not such an issue.
Hope this helps
Dominik
If you would like to refer to this comment somewhere else in this project, copy and paste the following link:
going back to my initial question about filters: in the end we did use filters during data acquisition. Probably due to my lack of experience with the system, the default filters (see my first post) were the only way I found to see a nice signal during data acquisition. However, I did decrease the gain as you suggested (x100). My question is: do I need to change any settings in PsPM, since I feed filtered data to it?
Many thanks and best,
Ambra
If you would like to refer to this comment somewhere else in this project, copy and paste the following link:
I suggest you leave all the settings on default. Since PsPM downsamples SCR to 10 Hz, the lowpass filter is essential. The software's highpass filter, though rendered redundant by your hardware filter, shouldn't harm either.
Best,
Samuel
Last edit: Samuel Gerster 2018-04-11
If you would like to refer to this comment somewhere else in this project, copy and paste the following link:
Hello,
I am setting up a classical conditioning paradigm with monetary rewards (three possible outcomes: reward, punishment, no monetary change). I aim at finding relative differences in SCR among these three types of events and I plan to use PsPM for my analysis. Since I am completely new to SCR recordings, I would like to ask advice regarding how to set some recording parameters.
I use BIOPAC Student Lab with the MP36 data acquisition unit, SS57LA lead for disposable setup and EL507 EDA Isotonic Gel Snap Electrodes.
Given this equipment, the BIOPAC software suggests using three sequential, biquadratic (second order) digital Infinite Impulse Response (IIR) filters as follows:
a. IIR Frequency: 65.5
b. IIR Quality Factor: 0.5
a. IIR Frequency: 38.5
b. IIR Quality Factor: 1
a. IIR Frequency: 50
b. IIR Quality Factor: 1
I would like to know if these parameters sound reasonable or if I should collect data without any filters during data acquisition. I worry to lose precious information by setting filters online, during data acquisition. What would you recommend?
I should add that I also plan to set the following parameters:
High Pass Filter: 0.05Hz (hardware filter implemented using resistors and capacitors in the front end circuitry of the data acquisition unit)
EDA channel sample rate = 2000Hz
Acquisition sampling rate = 2000Hz
Gain = x2000
Looking forward to hearing from you.
Many thanks and best,
Ambra
Last edit: Ambra Ferrari 2018-01-09
Dear Ambra
I would recommend not using any filters during acquisition, only an anti-alias low-pass filter at half the sample rate. Any other filtering (including the 0.05 Hz high-pass filter) can be done off-line. PsPM expects non-filtered data by default.
Dominik
Hi Dominik,
thanks for your help.
Would you use a FIR or IIR low pass filter?
Thanks and best
Ambra
Hi Ambra
for the anti-alias filter, only a hardware filter makes sense. It will probably be IIR then.
If there is no hardware low-pass filter, do not filter and oversample generously - 2k will suffice.
No hardware high-pass filter is needed but make sure the signal does not exceed the converter's dynamic range with the gain you're using.
Dominik
Great thanks!
I have a further question, regarding experiment design this time. Does PsPM need baseline periods (i.e. rest periods with no stimulations at all), similar to what I would use for MRI designs?
Best, Ambra
Dear Ambra
this is an important question, not only for PsPM. For most psychophysiologial measures, the dynamic range is limited, so when stimulations come too close in succession, the mapping from stimulation to physiological measure becomes non-linear, which is a problem for most analysis approaches, PsPM and otherwise (e.g. computing averages over trial-by-trial peak amplitudes).
For SCR, we have specifically shown with intraneural stimulation that this mapping is linear up to about 1 stimulus every 1 seconds (Gerster et al. 2017), but I'd generally recommend to have longer inter-trial-intervals. For DCM specifically, I'd recommend having at least 5-10 s between trials, to improve estimability; for GLM shorter intervals will do. For other psychophysiological measures, I'd go by rules of thumb. Pupil size responses are rather fast, such that ITIs are not such an issue.
Hope this helps
Dominik
Hello Dominik,
going back to my initial question about filters: in the end we did use filters during data acquisition. Probably due to my lack of experience with the system, the default filters (see my first post) were the only way I found to see a nice signal during data acquisition. However, I did decrease the gain as you suggested (x100). My question is: do I need to change any settings in PsPM, since I feed filtered data to it?
Many thanks and best,
Ambra
Dear Ambra,
I suggest you leave all the settings on default. Since PsPM downsamples SCR to 10 Hz, the lowpass filter is essential. The software's highpass filter, though rendered redundant by your hardware filter, shouldn't harm either.
Best,
Samuel
Last edit: Samuel Gerster 2018-04-11