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Risto J. Ilmoniemi
Researcher at Aalto University
Publications - 399
Citations - 30687
Risto J. Ilmoniemi is an academic researcher from Aalto University. The author has contributed to research in topics: Transcranial magnetic stimulation & Magnetoencephalography. The author has an hindex of 79, co-authored 376 publications receiving 27731 citations. Previous affiliations of Risto J. Ilmoniemi include Helsinki University Central Hospital & University of Helsinki.
Papers
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Magnetoencephalography—theory, instrumentation, and applications to noninvasive studies of the working human brain
TL;DR: The mathematical theory of the method is explained in detail, followed by a thorough description of MEG instrumentation, data analysis, and practical construction of multi-SQUID devices.
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Interpreting magnetic fields of the brain: minimum norm estimates
TL;DR: In this procedure, essentially nothing is assumed about the source currents, except that they are spatially restricted to a certain region, and the results can describe the structure of the current flow fairly well.
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Language-specific phoneme representations revealed by electric and magnetic brain responses
Risto Näätänen,Anne Lehtokoski,Mietta Lennes,Marie Cheour,Minna Huotilainen,Minna Huotilainen,Antti Iivonen,Martti Vainio,Paavo Alku,Paavo Alku,Risto J. Ilmoniemi,Aavo Luuk,Jüri Allik,Janne Sinkkonen,Janne Sinkkonen,Kimmo Alho +15 more
TL;DR: It is found that the brain's automatic change-detection response, reflected electrically as the mismatch negativity (MMN) was enhanced when the infrequent, deviant stimulus was a prototype relative to when it was a non-prototype (the Estonian /õ/).
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Long-Range Temporal Correlations and Scaling Behavior in Human Brain Oscillations
TL;DR: It is argued that critical-state dynamics of spontaneous oscillations may lend neural networks capable of quick reorganization during processing demands, and the demonstrated scaling laws pose novel quantitative constraints on computational models of network oscillations.
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Signal-space projection method for separating MEG or EEG into components.
TL;DR: In this work, the signal-space projection (SSP) method, the signals measured by d sensors are considered to form a time-varying vector in a d-dimensional signal space, which is a measure of similarity of the equivalence classes in signal space and a way to characterise the separability of sources.