I have seen some work on this topic, but that was not significant. May be this area has less potential?? I am bit confuse about the scope of integrating both area i-e big data and neuroscience.
Conference Paper Parallel Processing of Massive EEG Data with MapReduce
Conference Paper Parallel Real Time Seizure Detection in Large EEG Data
People have already looked at parallel processing of EEG data.
The EEG parallelization problem is not hard, as data can be processed in parallel without the need to synchronize on algorithmic writes, making the algorithm data-parallel.
Unless there is a new neuroscience algorithm that requires parallelization, this area has less research potential in my opinion.
On the other hand, ASIC or FPGA based EEG processing implementations may have some potential for research. However, this is mainly an engineering effort and a lot of work has already been done in this area in my opinion.
https://ieeexplore.ieee.org/abstract/document/6865607
https://ieeexplore.ieee.org/document/6271152
I think so, If the predictive analysis is performed. parallel processing is the best solution
Philippe Fournier Viger thanks sir, i got a good point of "time series" from your comment
Munish Bhatia i am thinking to do feature extraction and classification using map reduce / apache spark, and i want to check how much efficient it can be. I have mentioned a paper that used hadoop, but apache spark claims to be 100 time faster than hadoop
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