Is there any Brain Computer Interface research in India?

where to get EEG dataset of imagined speech?

Hey Everyone,

I would like to use Google Colab to accelerate the process of calculation of my deep learning model. However, I cannot run the model directly from the .ipynb file in the Google Colaboratory, since it has several .py functions written separately and then the main program will call them together in another .py file.

One of the proposed solutions consisted of following these steps:

1. Commit the code on Github 2. Clone on collab 3. run this command: !python model_Trainer.py on Colab

I have done steps 1 and 2 successfully, however, I still cannot run the third step. And I am getting the following error: python3: can't open file 'model_trainer.py': [Errno 2] No such file or directory.

Does anyone have a solution to this problem?

I look forward to hearing from you.

I've recently started pursuing PhD in Medical Image Processing. I am struggling to find a suitable problem to carry out research.

I was initially interested in working on brain images but after doing studies and according to peers' advices lots of works have already done with brain, but still work can be done on:

1. Retinal images

2. Chest radiography

3. Estimating probability of lung cancer etc.

I would be obliged if somebody suggests me some relevant topics(related to brain or other organs) where still there are lots of scopes to work on.

Suggest some research topics in Machine Learning in the field of computer science.

For normalized auto correlation, we normalizes the sequence so that the auto-correlations  at zero lag are identically 1.0.

So, I want to know how it will be in the case of cross correlations?

Does anyone know any references for computational models on the effects of plasticity on the brain and brain mapping techniques? How does plasticity impact structure with regards to function mapping and how does it impact brain mapping? How does the model gets modified as the individual ages?

While I have found a lot on the stability plasticity dilemma, I could not find reference to any simple models that may account for plasticity. Any references to this topic either computationally oriented or biologically oriented are welcome.

I would like to implement the approximated surface Laplacian (SL) estimated using Hjorth Algorithm but I can't find an open literature on the approximation of The SL at scalp edges as suggested in "Spatial Filter Selection for EEG Based Communication" by McFarland et al.

They mention Zhou's work for edge electrodes SL approximation but I do not have access to that literature.

Does anyone have relevant literature on that?

Has anyone got any reviews and practical recommendations about portable neuroimaging equipment that can be used to record during normal everyday activities?

I got curious about the zero-padding of EEG signals, if I have two events that mark an area of interest, and I cut these specific areas of interest, they differ in their length by a few samples.

So, if I wanted to make all the epochs the same length, can I pad them with zeros or will that affect the overall results?

To be more specific, if the sampling rate is 500Hz and the area of interest is supposed to be 2 seconds long, so I expect to have 1000 samples, but I end up with 970 or 1100 samples, what would be the best approach to make them all the same length?

Thank you in advance.