<p>If I understand your question correctly, yes, since ERP involves averaging over similar events, very accurate time-locking to stimulus onset is critical.  The idea of an ERP is that activity relevant to the stimulus will happen at a similar timepoint after similar stimuli--if you don't have an accurate time stamp (usually to the level of single milliseconds if not better), then the activity will be "smeared" across the time course.  For a good overview of ERPs, see the article <a href="http://dx.doi.org/10.4103%2F0972-6748.57865" rel="nofollow">Event-related Potentials: An Overview</a></p>

CC BY-SA 3.0
2014-10-24T03:57:41.580Z
then we cannot know if  a part of EEG signal is a P300 stimulus without knowing  the stimulus onset , which means that we know that part is a P300 signal from the time line , not from it's features , for example if the stimulus onset at t=1 s , them at t=1.3 s we expect a P300 signal , is this right ?
Learner
CC BY-SA 3.0
2014-10-24T09:11:23.170Z
Basically yes, although the P3 best correlates with response timing, not stimulus timing, and there exist algorithms for identifying P3s based on the data, although not very well.
jona
CC BY-SA 3.0
2014-10-23T17:13:29.557Z
2014-10-23T17:13:29.557Z
Krysta
<p>When I'm reading the documentation of importing events in EEGLAB from a file <a href="http://sccn.ucsd.edu/wiki/A02:_Importing_Event_Epoch_Info" rel="nofollow noreferrer">here</a> I have noticed that when we used a stimulus , we must know which time  we will apply it , since in the dataset file , you have to identify  of what times stimulus happen . <br> I don't know if my understanding is right or not , since i didn't  deal with EEG data practically (but in 2 weeks I will), but I was  reading a theoretical topics and papers on that.
<br> thanks in advance.</p>

CC BY-SA 3.0
2014-10-23T15:22:57.157Z
I'm unclear what this question means; it sounds to me like you're asking for theoretical papers on why you have to imported events have to have a timestamp, is that right?
Krysta
CC BY-SA 3.0
2014-10-23T15:45:16.720Z
@Krysta, my question is : when we do an ERP experiment do we need to know what times or period of times  that  stimulus  begin ?(i hope that's clear)
Learner
<eeg><signal-detection>
reading an EEG dataset using EEGLAB
Learner
# reading an EEG dataset using EEGLAB

(Asked by: username_0 on 2014-10-23)

When I'm reading the documentation of importing events in EEGLAB from a file [here](http://sccn.ucsd.edu/wiki/A02:_Importing_Event_Epoch_Info) I have noticed that when we used a stimulus , we must know which time we will apply it , since in the dataset file , you have to identify of what times stimulus happen .   
 I don't know if my understanding is right or not , since i didn't deal with EEG data practically (but in 2 weeks I will), but I was reading a theoretical topics and papers on that.
  
 thanks in advance.

**Tags:** eeg, signal-detection

> **Comments:**
> **username_1**: I'm unclear what this question means; it sounds to me like you're asking for theoretical papers on why you have to imported events have to have a timestamp, is that right?  
> **username_0**: @username_1, my question is : when we do an ERP experiment do we need to know what times or period of times  that  stimulus  begin ?(i hope that's clear)  

---

## 1 answers

### Answer by username_1 on 2014-10-23. Score: 4 | Accepted answer

If I understand your question correctly, yes, since ERP involves averaging over similar events, very accurate time-locking to stimulus onset is critical. The idea of an ERP is that activity relevant to the stimulus will happen at a similar timepoint after similar stimuli--if you don't have an accurate time stamp (usually to the level of single milliseconds if not better), then the activity will be "smeared" across the time course. For a good overview of ERPs, see the article [Event-related Potentials: An Overview](http://dx.doi.org/10.4103%2F0972-6748.57865)

> **Comments:**
> **username_0**: then we cannot know if  a part of EEG signal is a P300 stimulus without knowing  the stimulus onset , which means that we know that part is a P300 signal from the time line , not from it's features , for example if the stimulus onset at t=1 s , them at t=1.3 s we expect a P300 signal , is this right ?  
> **username_2**: Basically yes, although the P3 best correlates with response timing, not stimulus timing, and there exist algorithms for identifying P3s based on the data, although not very well.  

---

