Thanks Joe. Just to clarify, by 'the latency analysis using windowed or spatial PCA data' you mean that we can do only a spatial PCA on our ERP waveform and identify a N200-like frontal negativity and record the latency of that factor for each subject?


On Wed, Apr 9, 2014 at 12:01 PM, Joseph Dien <> wrote:
As you say, it’s not possible to get latency effects from a temporospatial factor.  Now that you’ve isolated the ERP component, you could use the information about peak channel and latency to perform a latency analysis using windowed or spatial PCA data is one possibility.  You could also use the factor as a template for performing a Woody filter analysis (not a feature of the EP Toolkit at this point), although that has a number of caveats.  What would work best depends on the features of your data.



On Apr 9, 2014, at 11:32 AM, Muhammad Adeel Parvaz <> wrote:

Dear Joe and other EPtoolkiters,

We are using EPtoolkit to identify frontal N200 and P300 components and we analyze the amplitudes both between and within groups.
However, a reviewer is now asking why we don't analyze latencies when many previous studies have shown latency differences. Since we have isolated temporospatial components, we don't have individual subjects' latencies. What would be the most effective way to address the reviewers' comment?



Joseph Dien,
Senior Research Scientist
Maryland Neuroimaging Center
University of Maryland