- Видео 3
- Просмотров 9 619
Felix Schneider
Великобритания
Добавлен 4 май 2017
Matlab Tutorial: How to assess (neuronal) signal quality
In this tutorial, I demonstrate how to evaluate the quality of your data. I show how to test average neuronal activity, assess signal-to-noise ratio and define significance thresholds. I also quickly go over confidence intervals and the area under the receiver operating characteristics (AUROC).
Data and code can be downloaded here: drive.google.com/drive/folders/1cfSwSGNbtVMR7NIuezrNP3UZ0MkR9L8w?usp=sharing
Data and code can be downloaded here: drive.google.com/drive/folders/1cfSwSGNbtVMR7NIuezrNP3UZ0MkR9L8w?usp=sharing
Просмотров: 283
Видео
Matlab Tutorial: Visualise cortical feature selectivity
Просмотров 1744 года назад
This video demonstrates one way to extract the best frequency and peak latency of neuronal responses. Furthermore, it shows how to visualise population responses in a 2D cortical feature-selectivity map. Data and code can be downloaded here: drive.google.com/drive/folders/1NjGNqMQLok_Ap1dLtR57UbNzHKkDih9e?usp=sharing
Matlab Tutorial: Spike data visualisation - Plot Raster | PSTH | SDF
Просмотров 9 тыс.4 года назад
This video explains how to visualise spiking data in an efficient way. I cover raster plots to demonstrate raw, trial-wise data but also show how to visualise the average spiking activity in a peristimulus time histogram (PSTH) or with a spike density function (SDF). Credit belongs to Alwin Gieselmann, PhD (Newcastle University). This video is based on his functions. Script and example data can...
Thanks a lot for this video. Two Questions: #1. Can I analyse Spiking Data in Pickle Files using MATLAB? #2. Can MATLAB handle data derived from DVS cameras?
Hello, Thanks for your great video. To use the codes written for the brain signal (EEG) or physiological signals, such as GSR in DEAP dataset what actions or changes in the codes should be applied.
Hello, awesome video it helped me a lot. Although I have a question: to convert the graph of x = #bin, y = #(spikes in that bin) to the usual PSTH where you need frquency, i.e: a graph where x = #bin and y = #frequency, you use the formula (#spikes in a fixed bin /#trails)(#bins that fit in a second), I'm losing my mind here trying to understand why you used that formula any hint???
Forget it I just realized, if you do (# spikes in a fixed bin / # trails) you have the average spikes per bin ie: (spikes / bin), but if you multiply that by the number of bins that fit in a second you get the average spikes per second (spikes / s) = Hz. Man it was easy I feel dumb I've been here for like two hours trying to understand this
How did you create the sptimes cell array?
I've extracted the spike times from the raw data file. How to do that depends on the recording system you're working with and the data processing during recording (e.g. filtering, thresholding etc).
Amazing work
Underrated video. Thank you. Please upload more
GREAT！Thank you very much！
very helpful.thx~
The background music is really annoying, anyway thanks for the great tutorial.
Coming back to this video after some time, I totally agree! What have I done 😅
Would it be possible to create more similar videos to learn how to analyse spike data?
If I want to transform the timestamps into z-score, how can I do that? Do I need the process the data in a particular way? And how do I run an anova with timestamps?
hi..did you import data from neuroexplorer? Please more detailed videos..Thank you.
Hi Elina, I have imported the data from the Neuralynx file format using functions that are freely available on their homepage. Let me know if you need more information.
@@felixschneider5040 I followed your tutorial to visualize my data but i got lost at 1:47 . Btw, how many minutes data should we take to plot PSTH/raster? Thanks :)
Hi Elina, script and example data are freely available. Check out the link in the description. Regarding your question: there is no simple answer, I‘m afraid. It all depends on your experimental paradigm. Personally, I would recommend to get as many repetitions of the same stimulus condition as you possibly can.
Best tutorial I have ever seen, Thank you, please keep uploading!
GREAT
another fantastic video! thanks felix!
Thanks, Tim :)