I wrote about Threshold-Free-Cluster-Enhancement (TFCE) before, this time I stumbled upon a weirdly looking H0 diagram. Let me explain: If you simulate data without any effect, you expect that the P(data|H0) distribution is uniform, that is, all p-values are equally likely. Here, I define the p-value as the minimal p-value over time that I get from one whole simulation (1000 permutations per simulated dataset) – I simulated only cluster in time not space (find the notebook here, raw-jl here). When I did this for 100 repetitions, each applying permutation TFCE and calculating the min-p, I got the following histogram of…

Here is a fun trick (I think) invented by Martin Rolfs and Casimir Ludwig. You are in a train and would like to know the speed of the train – but no phone, GPS or speedometer – here is how you do it. Here is how to do it: Stretch out both arms, thumbs up. Make eye-movements from one thumb to the other, focus on the eye movements going in direction of the train Slowly increase/decrease the distance of the thumbs, effectively changing (in a controlled manner) how large your eye movements are. Notice the rail sleepers of the nearby…

Purkinjes Blue Arc is a cool and not well known visual effect. It consists of illusionary blue arcs, emanating from a (typically) red stimulus. It has been rediscovered at least half a dozen times in the last 200 years and goes back to Purkinje. The exact physiological reason for the Blue Arcs is still not now. A detailed write-up of the demonstration with more tipps can be found in Moreland 1967. Modern screen technology make it much easier for you, to experience this effect. Just follow these simple instructions! Purkinjes Blue Arc Recipe You need an OLED screen – ~50%…

I just started dabbling with Pluto.jl and very quickly it allows to give very insightful notebooks. For example, take this signal: Clearly, the simulated event-responses (the event-related potentials) overlap in time (e.g. at ~sample 350). We could do a “naive” regression on all timepoints relative to the event-onset, ignoring any overlap – or we could use linear deconvolution aka. overlap-correction to correct for the overlap (as the name says ;). What follows is the beauty of Pluto.jl – simple reactive/interactive notebooks. As shown in the following gif, it is very easy to show the dependency of deconvolution-success on window-size and…

For my new EEG course in Stuttgart I spend some time to make this gif – I couldn’t find a version online. It shows a simple fact: If you calculate the mean, the breakdown point of 0%. That is, every datapoint counts whether it is an outlier or not.Trimmed or winsorized means instead calculate the mean based on the inner X % (e.g. inner 80% for trimmed mean of 20%, removing the top and bottom 10% of datapoints) – or in case of winsorizing the mean with the 20% extreme values not removed, but changed to the now new remaining…

I will be starting a new lab on Computational Cognitive Science, next month at University of Stuttgart. I will be working on the connection of EEG and Eye-Tracking, Statistics and methods development. The group is attached to the SimTech and the VIS Stuttgart

I recently asked on twitter whether people can recommend recording chambers to seat the subject in psychological experiments. I had a tough time googling it, terms that could be helpful in case you are in search for the same thing: Testing chamber, subject booth, audiology. I got a lot of answers and for the sake of “google-ability” will summarize them here: Steve Luck recommends a separated chamber, but highlights importance of air-conditioning due to sweating artefacts Aina Puce recommends no chamber, but to sit 2-3m behind the subject and use white noise generators Regarding actual chambers several commercial vendors were…

PS: For this project I moved from EEG to fMRI, and in this post I will sometimes explain terms that might be very basic to fMRI people, but maybe not for EEG people. I want to investigate cortical area V1. But I don’t want to spend time on retinotopy during my recording session. Thus I looked a bit into automatic methods to estimate it from segmented (segment = split up in WhiteMatter/GrayMatter+extract 3D-surfaces from voxel-MRI and also inflate them) brains. I used the freesurfer/label/lh.V1 labels and the neurophythy/Benson et al tools [zotpressInText item=”{4784278:P2Y9DRY4}”]. The manual retinotopy was performed by Sam…

22.10.2019 Edit: Thanks Matt Craddock, I understand the source of the problem better. He mentioned that this should not occur if the amplifiers record the triggers as trigger channels (before converting it to events). And mentions that this could happen through downsampling. Indeed after checking in the dataset I used it was downsampled from 1024 to 512Hz. This made many eventlatencies ~ X.50001, which will be uprounded with round and floored with floor. This gives some context to the problem.Full discussion on twitter TLDR; EEGlab allows for non-integer event latencies (in units of samples). Eeglab chose floor(latency), while others e.g….