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Looking to the Future 

Looking to the Future
Looking to the Future

Riitta Hari

, and Aina Puce

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date: 05 March 2021

This chapter looks to the future of MEG and EEG. Advances are expected both in instrumentation and in data-analysis tools suitable for experiments carried out in naturalistic settings. Moreover, the person’s behavior should be analyzed in much more finer detail than is done at present. Machine-learning approaches allow decoding of different brain states and distinctions between some patient and control groups; they also have implications for the development of brain–machine interfaces and brain-controlled prosthetic devices. Data governance will gain more emphasis when big brain-imaging datasets will be more widely available to the research community. At the same time, new challenges emerge for ensuring data quality, replicability, statistical analysis, documentation, and visualization. The main contribution of MEG and EEG to neuroscience continue to be in the accurate temporal information they provide.

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