Browsing by Author "Koskinen, M."

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Functional Magnetic Resonance Imaging Blood Oxygenation Level-Dependent Signal and Magnetoencephalography Evoked Responses Yield Different Neural Functionality in Reading
(2011) Vartiainen, J.; Liljestrom, M.; Koskinen, M.; Renvall, H.; Salmelin, Riitta
School of Science | A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
It is often implicitly assumed that the neural activation patterns revealed by hemodynamic methods, such as functional magnetic resonance imaging (fMRI), and electrophysiological methods, such as magnetoencephalography (MEG) and electroencephalography (EEG), are comparable. In early sensory processing that seems to be the case, but the assumption may not be correct in high-level cognitive tasks. For example, MEG and fMRI literature of single-word reading suggests differences in cortical activation, but direct comparisons are lacking. Here, while the same human participants performed the same reading task, analysis of MEG evoked responses and fMRI blood oxygenation level-dependent (BOLD) signals revealed marked functional and spatial differences in several cortical areas outside the visual cortex. Divergent patterns of activation were observed in the frontal and temporal cortex, in accordance with previous separate MEG and fMRI studies of reading. Furthermore, opposite stimulus effects in the MEG and fMRI measures were detected in the left occipitotemporal cortex: MEG evoked responses were stronger to letter than symbol strings, whereas the fMRI BOLD signal was stronger to symbol than letter strings. The EEG recorded simultaneously during MEG and fMRI did not indicate neurophysiological differences that could explain the observed functional discrepancies between the MEG and fMRI results. Acknowledgment of the complementary nature of hemodynamic and electrophysiological measures, as reported here in a cognitive task using evoked response analysis in MEG and BOLD signal analysis in fMRI, represents an essential step toward an informed use of multimodal imaging that reaches beyond mere combination of location and timing of neural activation
Intersubject consistency of cortical MEG signals during movie viewing
(2014) Lankinen, K.; Saari, Jukka; Hari, R.; Koskinen, M.
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
According to recent functional magnetic resonance imaging (fMRI) studies, spectators of a movie may share similar spatiotemporal patterns of brain activity. We aimed to extend these findings of intersubject correlation to temporally accurate single-trial magnetoencephalography (MEG). A silent 15-min black-and-white movie was shown to eight subjects twice. We adopted a spatial filtering model and estimated its parameter values by using multi-set canonical correlation analysis (M-CCA) so that the intersubject correlation was maximized. The procedure resulted in multiple (mutually uncorrelated) time-courses with statistically significant intersubject correlations at frequencies below 10 Hz; the maximum correlation was 0.28 ± 0.075 in the ≤ 1 Hz band. Moreover, the 24-Hz frame rate elicited steady-state responses with statistically significant intersubject correlations up to 0.29 ± 0.12. To assess the brain origin of the across-subjects correlated signals, the time-courses were correlated with minimum-norm source current estimates (MNEs) projected to the cortex. The time series implied across-subjects synchronous activity in the early visual, posterior and inferior parietal, lateral temporo-occipital, and motor cortices, and in the superior temporal sulcus (STS) bilaterally. These findings demonstrate the capability of the proposed methodology to uncover cortical MEG signatures from single-trial signals that are consistent across spectators of a movie.
Uncovering cortical MEG responses to listened audiobook stories
(2014) Koskinen, M.; Seppä, M.
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Naturalistic stimuli, such as normal speech and narratives, are opening up intriguing prospects in neuroscience, especially when merging neuroimaging with machine learning methodology. Here we propose a task-optimized spatial filtering strategy for uncovering individual magnetoencephalographic (MEG) responses to audiobook stories. Ten subjects listened to 1-h-long recording once, as well as to 48 repetitions of a 1-min-long speech passage. Employing response replicability as statistical validity and utilizing unsupervised learning methods, we trained spatial filters that were able to generalize over datasets of an individual. For this blind-signal-separation (BSS) task, we derived a version of multi-set similarity-constrained canonical correlation analysis (SimCCA) that theoretically provides maximal signal-to-noise ratio (SNR) in this setting. Irrespective of significant noise in unaveraged MEG traces, the method successfully uncovered feasible time courses up to ~ 120 Hz, with the most prominent signals below 20 Hz. Individual trial-to-trial correlations of such time courses reached the level of 0.55 (median 0.33 in the group) at ~ 0.5 Hz, with considerable variation between subjects. By this filtering, the SNR increased up to 20 times. In comparison, independent component analysis (ICA) or principal component analysis (PCA) did not improve SNR notably. The validity of the extracted brain signals was further assessed by inspecting their associations with the stimulus, as well as by mapping the contributing cortical signal sources. The results indicate that the proposed methodology effectively reduces noise in MEG recordings to that extent that brain responses can be seen to nonrecurring audiobook stories. The study paves the way for applications aiming at accurately modeling the stimulus–response-relationship by tackling the response variability, as well as for real-time monitoring of brain signals of individuals in naturalistic experimental conditions.