<div dir="ltr"><div><div><div>Dear Tarik and Makato, also best wishes for the new year, and hope you had a wonderful christmas!<br><br></div>Thank you all for your suggestions! The main thing right now would be to choose several things to be included that are 'most important'. For us, this would be something visual and something auditory in any case, so we could do basic ERP analyses - just capture N/P 1/2, etc. In addition, some kind of frequency encoding (maybe different ones) would also be highly desired. <br><br></div>Some more information: the reason is that we wish to use this 'localizer' to compare different environmental conditions which are less than ideal (i.e. a very loud and noisy room, a screen which can only be seen for 1/2 of it) - with the 'perfect' laboratory condition, in order to tell us something about the quality of the EEG itself, using within-subject testing (so we would measure it always twice, and quantify EEG signal 'decay' just with paired T-test on several observables from the task such as N1 and so forth). Also, the frequency encoding would be interesting in case some (additional, location-specific) artifact corrections are required, such as with EEG/fMRI - then you can check whether the frequency is still 'in the signal' after all the corrections.<br><br></div>Kind regards,<br>Johan<br><div><br>PS. I think it would also be great if a localizer would be so standardized, that they would allow for a reliable comparison between different sites/studies - maybe even in past studies - but this is a somewhat harder problem to tackle properly than just the scenario mentioned above: instead of optimizing for just time (and not worry too much about the ERP shape as such), you now also optimize for ERP shape in terms of its comparison with the 'standard'. Regardless, I also think it would be of very high value to have some kind of standardized EEG talk - one which could be distributed free of charge (i.e. without spending too much on software like presentation and such) to anyone with a wish to do anything with EEG. I somehow doubt that a vendor-based task would be the way to go - these require payment of some kind - which is a barrier for proceeding further.<br><br><br><div><br></div><div><br></div><div><br><div><div><br><div><br><div class="gmail_quote">---------- Forwarded message ----------<br>From: <b class="gmail_sendername">Tarik S Bel-Bahar</b> <span dir="ltr"><<a href="mailto:tarikbelbahar@gmail.com">tarikbelbahar@gmail.com</a>></span><br>Date: Fri, Dec 26, 2014 at 10:22 PM<br>Subject: Re: [Eeglablist] EEG 'localizer'?<br>To: Johan <<a href="mailto:johanvandermeer@gmail.com">johanvandermeer@gmail.com</a>><br>Cc: "<a href="mailto:eeglablist@sccn.ucsd.edu">eeglablist@sccn.ucsd.edu</a>" <<a href="mailto:eeglablist@sccn.ucsd.edu">eeglablist@sccn.ucsd.edu</a>><br><br><br><div dir="ltr"><div style="color:#333399"><br></div><div class="gmail_extra"><div class="gmail_quote"><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex"><div dir="ltr"><span class=""><div style="color:rgb(51,51,153)">Hello Johan, </div><div style="color:rgb(51,51,153)">Hoping all is well and have a good new year!</div></span><div style="color:rgb(51,51,153)"><span class="">My strongest recommendation is that you do plenty of pilot testing from short & long versions of tasks, and show yourself that you can generate robust and intended metrics from the mini-tasks. </span><div style="color:rgb(51,51,153);display:inline">Some other thoughts are listed</div><span class=""> below that you might find useful to consider. </span></div><div style="color:rgb(51,51,153)"><span class="">Good luck with your efforts, it will be interesting to hear more </span><div style="color:rgb(51,51,153);display:inline">about </div>them someday.</div><div style="color:rgb(51,51,153)">Best wishes, Tarik</div><div style="color:rgb(51,51,153)"><br></div><div style="color:rgb(51,51,153)"><br></div><div style="color:rgb(51,51,153)">************************</div><div style="color:rgb(51,51,153)"><span style="color:rgb(34,34,34)"><span class=""><div style="color:rgb(51,51,153)">EEG fingerprinting and localizer tasks are of interest to the general community for multiple reasons, but I don't think there're are yet candidates for batteries of valid "EEG mini-tasks". Your question is tricky, as ERP and EEG tasks/metrics are well-established, but EEG sources and "localizer" tasks are less well established. Overall, a lot of reliability, validity, and single-trial work still needs to be done across the EEG/ERP/source-estimation field before we can have a good advanced mini-batteries of EEG tasks to deploy. This topic also connects with the search for quickly-generated neurocognitive markers for psychiatric, neurological, BCI, and operative monitoring endeavors. Exploring recent literature and reviews in that area would highlight some major candidate markers (ie, CENTRICS efforts). Some EEG companies sell standardized ERP/EEG tasks/metrics with their systems, and there is of course a broad market in non-EEG cognitive-testing batteries (e.g., NIH Toolbox, Cantab, etc.). Overall, responses to your question about whether it's safe to use a task are highly dependent on the evidence base considered appropriate by the respondent (e.g., # and quality of previous studies, consistency of patterns, constraints on metrics, psychometric properties, external validity, etc..). </div><div style="color:rgb(51,51,153)"><br></div></span><div style="color:rgb(51,51,153)"><div><span style="color:rgb(34,34,34)"><div style="color:rgb(51,51,153)"><span class="">Of some help might be the several reviews of basic guidelines for </span><div style="color:rgb(51,51,153);display:inline">major ERPs such as </div>P300, MMN, ERN, FRN, N400<div style="color:rgb(51,51,153);display:inline">, including</div><span class=""> information about minimal recommended trial count and other constraints that are essential. You can also find articles that have tried to establish minimum-trial-numbers for the ERN, FRN, and MMN, often in pediatric populations. All these can be found on Google Scholar, most within last ~7 years. You may also want to search for other terms such as EEG + fingerprinting, cognitive state monitoring, and localizer.</span></div><div><br></div></span></div></div></span><span style="color:rgb(34,34,34)"><div style="color:rgb(51,51,153)"><br></div><div style="color:rgb(51,51,153)"><span class="">There are some trade-offs that require consideration here in terms of fidelity (more trials, less tasks) vs. bandwidth (less trials, more tasks), in terms of the EEG metrics/constructs to be derived (established ERP/EEG metrics vs. simple "localizers" or "fingerprints"), and in terms of how you expect to use the resulting EEG-derived metrics (eg., diagnostics, exploratory analyses, tracking ICs from the min-battery in other conditions). If you want to connect with known ERPs, you will need some minimim number of valid trials for each ERP metrics to be able to compare to previous findings. The more you deviate from previous protocols, the more likely that the resultant metrics will be tentative/exploratory. See Luck's MONSTER method as an interesting approach in the ERP area. In your search for an EEG-localizer battery, a good rule of thumb cutoff is around 50 trials per each kind of tasks (50 face trials, 50 sound trials, 50 finger-tap trials) - or 50 trials per condition within each task. You might cut things to 30 trials if you have few artifacts and can denoise the data accurately. If you're not looking for any particular well-established ERP, you could essentially just present stimuli in different modalities for ~50 trials, mostly or all with passive presentation requiring no response, or a simple response to maintain attention to the stimuli. If you'd like involvement of executive processes, then you could vary the stimuli to include oddballs or responses. For a very brief task generating a</span><div style="color:rgb(51,51,153);display:inline">n ERN or FRN</div>,<div style="color:rgb(51,51,153);display:inline"> consider </div>experimenting <div style="color:rgb(51,51,153);display:inline">with </div><div style="color:rgb(51,51,153);display:inline">protocols which require</div> a speeded-response-period<div style="color:rgb(51,51,153);display:inline"> and/or false negative feedback</div>, so as to maximize<div style="color:rgb(51,51,153);display:inline"> the number of trials generating fronto-medial negativities.</div></div></span></div><div style="color:rgb(51,51,153)"><br></div><div style="color:rgb(51,51,153)">If you want to get ICA maps of visual, auditory, or other networks, then you might be able to simply show a visual stimulus such as a check board or faces, for example, to get good visual Independent Components (though the latter stimuli would activate higher-order visual regions). Same for auditory and sensori-motor networks. There are a good number of tasks that give reliable activation within and/or across specific neuropsychological systems. Further, many research groups have decomposed brief periods of resting data, and derived Independent components associated with known intrinsic brain networks. This suggests rest tasks can also work to get "localizers<div style="color:rgb(51,51,153);display:inline">"</div> or <div style="color:rgb(51,51,153);display:inline">"</div>fingerprints"<div style="color:rgb(51,51,153);display:inline">.</div></div></div></blockquote><span class=""><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex"><div dir="ltr"><div style="color:rgb(51,51,153)"><br></div><div style="color:rgb(51,51,153)">********************</div><div style="color:rgb(51,51,153)"><br></div><div style="color:rgb(51,51,153)"><br></div><div style="color:rgb(51,51,153)"><br></div><div style="color:rgb(51,51,153)"><br></div><div style="color:rgb(51,51,153)"><br></div><div style="color:rgb(51,51,153)"><br></div><div style="color:rgb(51,51,153)"><br></div><div style="color:rgb(51,51,153)"><br></div><div style="color:rgb(51,51,153)"><br></div><div style="color:rgb(51,51,153)"><br></div><div style="color:rgb(51,51,153)"><br></div><div style="color:rgb(51,51,153)"><br></div><div style="color:rgb(51,51,153)"><br></div><div style="color:rgb(51,51,153)"><br></div><div style="color:rgb(51,51,153)"><br></div><div class="gmail_extra"><br><div class="gmail_quote"><div><div>On Tue, Dec 23, 2014 at 10:53 AM, Johan <span dir="ltr"><<a href="mailto:johanvandermeer@gmail.com" target="_blank">johanvandermeer@gmail.com</a>></span> wrote:<br></div></div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div><div><div dir="ltr"><div><div><div><div><div><div><div><div><div>Dear all,<br><br></div>I am searching for a single task, which can (well.. ideally..) be performed in under about 5-10 minutes (no longer), and which can get me (ideally!) an ERP of:<br><br></div>visual<br></div>auditory<br></div>motor<br></div>go-nogo (response inhibition)<br><br></div>... and, if possible, also the possibility to impart specific frequencies in the EEG signal that can be extracted later on - sort of like the case when you have a flickering checkerboard with pattern reversals every 0.2 seconds for a 5 Hz 'base' signal in the EEG.<br><br></div>The objective is to compress as much information as possible into a single EEG task - so that you can compare the outcome (within subject analysis) between 2 different situations... without (1) totally confusing the subject, and (2) still have the time to do a larger experiment. <br><br>So - it's sort of like an EEG 'localizer' task.<br><br></div>Does anyone ever try this before, or has seen anywhere something like this being attempted? Or rather you think this is just impossible and not worth the effort? :-)<br><br></div>Thank you very much for your time and kind regards,<br>Johan van der Meer<br></div>
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