[Eeglablist] Re-referencing before or after creating bi-polar HEOG and VEOG channel

[Makoto Miyakoshi]

Dear Melissa,

Re-referencing is one of the things I'm getting less and less confident.

If you say you will analyze EEG signal with ICA to the end (i.e.,
group-level statistics), referencing is not a serious problem, as long as
you properly remove bad channels before average referencing. That's all I
know. So my personal recommendation is, perform average reference and use
ICA (do not forget to discard one channel or reduce data dimension by one
before ICA after average referencing; see
http://sccn.ucsd.edu/wiki/Makoto's_preprocessing_pipeline).

Otherwise, you should read these papers carefully and decide what to do.

Dien J. 1998. Issues in the application of the average reference: Review,
critiques, and recommendations.*Behavior Research Methods, Instruments, and
Computers* 30: 34-43.

DeZhong Yao's REST: http://www.neuro.uestc.edu.cn/rest/

Nima Bigdely-Shamlo's PREP pipeline:
http://journal.frontiersin.org/article/10.3389/fninf.2015.00016/abstract

FYI, Joseph concluded that one should use average reference if good number
of channels are available. Nima told me that DeZong Yao's REST is a smart
solution. One of the conclusions from Nima's paper is that you should
choose clean channels to perform average referencing.

Makoto

On Mon, Jul 27, 2015 at 7:47 PM, melissa scott <melissascott6 at gmail.com>
wrote:

> Dear Colleagues,
>
> My advisor's lab recently started collecting ERP data. We decided to
> reference the electrodes to the left earlobe during data acquisition and
> plan to re-reference to the average of the left and right earlobes offline.
> We think we should also re-reference the electrodes above and below the
> eyes before we create our bipolar channel (VEOG) that we will subsequently
> use for blink detection and correction. Does this seem appropriate? We
> appreciate your thoughts and suggestions.
>
> thanks, Melissa
>
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-- 
Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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