Dear Vladimir,
Thanks for your response.
I’m looking to remove eyeblinks from my data. What sort of threshold would you suggest to remove eyeblinks using the ‘Peak to Peak amplitude’ method?
Thanks,
Emily
From: Vladimir Litvak [mailto:[log in to unmask]]
Sent: 09 June 2016 16:01
To: Emily Hird
Cc: [log in to unmask]
Subject: Re: [SPM] Bad channel threshold ERP data
Dear Emily,
It might be a better idea instead of 'Threshold channels' method use the 'Peak to Peak amplitude' method which is not sensitive to the absolute value of your data but just do differences within a trial. It all depends on what kind of artefacts you actually have so you might want to also look at your data first.
Best,
Vladimir
On Thu, Jun 9, 2016 at 3:24 PM, Emily Hird <[log in to unmask]> wrote:
Dear SPM users,
I am preprocessing ERPs to look for a slow-wave anticipatory potential, so I have removed the highpass filter from my pipeline to ensure this slow-wave activity isn’t cleaned out of the data.
However, this leads to more channels being marked as ‘bad’ during artefact rejection with a threshold of 0.2 (this threshold is suggested in the manual). Is it advisable to change the ‘bad channel’ threshold from 0.2 to a higher value, so fewer channels are marked as bad when looking at data which hasn’t been highpass filtered?
Many thanks in advance.
Emily Hird
PhD student
School of Psychological Sciences
Zochonis Building, Brunswick Street, Manchester M13 9PT