Browsing by Author "Kujala, Jan"

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Analysis of functional connectivity and oscillatory power using DICS: From raw MEG data to group-level statistics in Python
(2018-08-11) van Vliet, Marijn; Liljeström, Mia; Aro, Susanna; Salmelin, Riitta; Kujala, Jan
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Communication between brain regions is thought to be facilitated by the synchronization of oscillatory activity. Hence, large-scale functional networks within the brain may be estimated by measuring synchronicity between regions. Neurophysiological recordings, such as magnetoencephalography (MEG) and electroencephalography (EEG), provide a direct measure of oscillatory neural activity with millisecond temporal resolution. In this paper, we describe a full data analysis pipeline for functional connectivity analysis based on dynamic imaging of coherent sources (DICS) of MEG data. DICS is a beamforming technique in the frequency-domain that allows the study of the cortical sources of oscillatory activity and synchronization between brain regions. All the analysis steps, starting from the raw MEG data up to publication-ready group-level statistics and visualization, are discussed in depth, including methodological considerations, rules of thumb and tradeoffs. We start by computing cross-spectral density (CSD) matrices using a wavelet approach in several frequency bands (alpha, theta, beta, gamma). We then provide a way to create comparable source spaces across subjects and discuss the cortical mapping of spectral power. For connectivity analysis, we present a canonical computation of coherence that facilitates a stable estimation of all-to-all connectivity. Finally, we use group-level statistics to limit the network to cortical regions for which significant differences between experimental conditions are detected and produce vertex- and parcel-level visualizations of the different brain networks. Code examples using the MNE-Python package are provided at each step, guiding the reader through a complete analysis of the freely available openfMRI ds000117 "familiar vs. unfamiliar vs. scrambled faces" dataset. The goal is to educate both novice and experienced data analysts with the "tricks of the trade" necessary to successfully perform this type of analysis on their own data.
Beta- and gamma-band cortico-cortical interactions support naturalistic reading of continuous text
(2024-01) Kujala, Jan; Mäkelä, Sasu; Ojala, Pauliina; Hyönä, Jukka; Salmelin, Riitta
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Large-scale integration of information across cortical structures, building on neural connectivity, has been proposed to be a key element in supporting human cognitive processing. In electrophysiological neuroimaging studies of reading, quantification of neural interactions has been limited to the level of isolated words or sentences due to artefacts induced by eye movements. Here, we combined magnetoencephalography recording with advanced artefact rejection tools to investigate both cortico-cortical coherence and directed neural interactions during naturalistic reading of full-page texts. Our results show that reading versus visual scanning of text was associated with wide-spread increases of cortico-cortical coherence in the beta and gamma bands. We further show that the reading task was linked to increased directed neural interactions compared to the scanning task across a sparse set of connections within a wide range of frequencies. Together, the results demonstrate that neural connectivity flexibly builds on different frequency bands to support continuous natural reading.
Cortical beta burst dynamics are altered in Parkinson's disease but normalized by deep brain stimulation
(2022-08-15) Pauls, K.  Amande M; Korsun, Olesia; Nenonen, Jukka; Nurminen, Jussi; Liljeström, Mia; Kujala, Jan; Pekkonen, Eero; Renvall, Hanna
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Exaggerated subthalamic beta oscillatory activity and increased beta range cortico-subthalamic synchrony have crystallized as the electrophysiological hallmarks of Parkinson's disease. Beta oscillatory activity is not tonic but occurs in ‘bursts’ of transient amplitude increases. In Parkinson's disease, the characteristics of these bursts are altered especially in the basal ganglia. However, beta oscillatory dynamics at the cortical level and how they compare with healthy brain activity is less well studied. We used magnetoencephalography (MEG) to study sensorimotor cortical beta bursting and its modulation by subthalamic deep brain stimulation in Parkinson's disease patients and age-matched healthy controls. We show that the changes in beta bursting amplitude and duration typical of Parkinson's disease can also be observed in the sensorimotor cortex, and that they are modulated by chronic subthalamic deep brain stimulation, which, in turn, is reflected in improved motor function at the behavioural level. In addition to the changes in individual beta bursts, their timing relative to each other was altered in patients compared to controls: bursts were more clustered in untreated Parkinson's disease, occurring in ‘bursts of bursts’, and re-burst probability was higher for longer compared to shorter bursts. During active deep brain stimulation, the beta bursting in patients resembled healthy controls’ data. In summary, both individual bursts’ characteristics and burst patterning are affected in Parkinson's disease, and subthalamic deep brain stimulation normalizes some of these changes to resemble healthy controls’ beta bursting activity, suggesting a non-invasive biomarker for patient and treatment follow-up.
Cortical entrainment: what we can learn from studying naturalistic speech perception
(2020-07-02) Alexandrou, Anna Maria; Saarinen, Timo; Kujala, Jan; Salmelin, Riitta
A2 Katsausartikkeli tieteellisessä aikakauslehdessä
The popular framework of cortical entrainment postulates that speech comprehension crucially depends on the continuous alignment of low-frequency cortical oscillatory activity with the amplitude envelope of perceived acoustic speech signals. The evidence for cortical entrainment mostly stems from tightly controlled experimental paradigms focusing on repeated perception of isolated sentences that feature a very constant speaking rate. However, these kinds of decontextualised and extremely regular stimuli do not reflect natural speech as we encounter it in real life. We thus advance the view that naturalistic experimental paradigms, utilising spontaneously produced speech as stimuli and suitable frequency-domain methodological tools, should be used to address an important question that remains open: whether cortical entrainment is observed during speech perception and comprehension in real-life communicative situations. In addition, we discuss how the phenomenon currently labelled as cortical entrainment might be confounded by a regular repetition of evoked responses.
Cortical tracking of global and local variations of speech rhythm during connected natural speech perception
(2018-01-01) Alexandrou, Anna Maria; Saarinen, Timo; Kujala, Jan; Salmelin, Riitta
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
During natural speech perception, listeners must track the global speaking rate, that is, the overall rate of incoming linguistic information, as well as transient, local speaking rate variations occurring within the global speaking rate. Here, we address the hypothesis that this tracking mechanism is achieved through coupling of cortical signals to the amplitude envelope of the perceived acoustic speech signals. Cortical signals were recorded with magnetoencephalography (MEG) while participants perceived spontaneously produced speech stimuli at three global speaking rates (slow, normal/ habitual, and fast). Inherently to spontaneously produced speech, these stimuli also featured local variations in speaking rate. The coupling between cortical and acoustic speech signals was evaluated using audio–MEG coherence. Modulations in audio–MEG coherence spatially dif- ferentiated between tracking of global speaking rate, highlighting the temporal cortex bilaterally and the right parietal cortex, and sensitivity to local speaking rate variations, emphasizing the left parietal cortex. Cortical tuning to the temporal structure of natural connected speech thus seems to require the joint contribution of both auditory and parietal regions. These findings suggest that cortical tuning to speech rhythm operates on two functionally distinct levels: one encoding the global rhythmic structure of speech and the other associated with online, rapidly evolving temporal predictions. Thus, it may be proposed that speech perception is shaped by evolutionary tuning, a preference for certain speaking rates, and predictive tuning, associated with cortical tracking of the constantly changing-rate of linguistic information in a speech stream.
Detection of cortical gamma-band activity with magnetoencephalography
(2010) Hiltunen, Tuukka
Informaatio- ja luonnontieteiden tiedekunta | Bachelor's thesis
Dog Experts' Brains Distinguish Socially Relevant Body Postures Similarly in Dogs and Humans
(2012) Kujala, Miiamaaria V.; Kujala, Jan; Carlson, Synnöve; Hari, Riitta
School of Science | A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
We read conspecifics' social cues effortlessly, but little is known about our abilities to understand social gestures of other species. To investigate the neural underpinnings of such skills, we used functional magnetic resonance imaging to study the brain activity of experts and non-experts of dog behavior while they observed humans or dogs either interacting with, or facing away from a conspecific. The posterior superior temporal sulcus (pSTS) of both subject groups dissociated humans facing toward each other from humans facing away, and in dog experts, a distinction also occurred for dogs facing toward vs. away in a bilateral area extending from the pSTS to the inferior temporo-occipital cortex: the dissociation of dog behavior was significantly stronger in expert than control group. Furthermore, the control group had stronger pSTS responses to humans than dogs facing toward a conspecific, whereas in dog experts, the responses were of similar magnitude. These findings suggest that dog experts' brains distinguish socially relevant body postures similarly in dogs and humans.
Dynamic imaging of coherent sources: Development of a method and software
(2001) Kujala, Jan
Helsinki University of Technology | Master's thesis
Uusia analyysimenetelmiä tarvitaan synkronisen aktiivisuuden tutkimiseksi aivoissa. Magnetoenkefalografiassa (MEG) ja elektroenkefalografiassa eri sensoreilla ja elektrodeilla mitattujen signaalien välillä on havaittu tehtäväsidonnaisia vuorovaikutuksia kognitiivisissa ja motorisissa tehtävissä. MEG:n ja EEG:n aikaresoluutio on riittävän hyvä neuronaalisten liityntöjen luonnehtimiseksi, toisin kuin esim. fMRI:ssa. Tässä työssä tarkoitus oli kehittää dynaaminen koherenssinkuvantamismenetelmä (DICS), joka mahdollistaa kortiko-kortikaalisten ja kortiko-lihas vuorovaikutusten tutkimisen arvioimalla tehoa ja koherenssia aivoissa. DICS:n perusajatus on käyttää avaruudellista suodinta, joka datan lineaarikombinaatioiden avulla optimoi halutun ominaisuuden, erityisesti koherenssin, näennäisillä kanavilla eli sijainneissa aivoissa. Projektissa saimme luotua toimivan ohjelmistopaketin, jota voidaan käyttää MEG datan analysointiin sekä kortiko-kortikaalisten että kortiko-lihas koherenssien havaitsemiseksi. Ohjelmisto mahdollistaa myös tulosten havainnoillisen visualisoinnin yhdistämällä funktionaalisen ja anatomisen tiedon yhdeksi esitykseksi. Tehdyt simulaatiot osoittivat, että DICS:lla pystytään erottamaan koherenttia aktiivisuutta tapauksissa, joissa aktiivisuus on heikkoa tai joissa lähdealueet ovat lähellä toisiaan. Menetelmä on myös tarkka sekä koherenttien alueiden paikantamisessa että koherenssiarvojen laskemisessa. Oikean mitta-aineiston analysoinnissa pystyimme käyttämään menetelmää koherenttien aktiivisten alueiden havaitsemiseen tilanteissa, missä se ei aiemmin ole onnistunut. Menetelmän kehitys jatkuu olemassaolevien työvälineiden ja lähestymistapojen kehityksellä, mutta myös uusia asioita ollaan liittämässä ohjelmistopakettiin. Erityisesti vaihelukittuvuusanalyysiä ollaan kehittämässä, jotta DICS:ta saataisiin täydellinen aika-avaruudellinen työväline vuorovaikutusten kuvantamiseksi aivoissa.
Empathy enhances decoding accuracy of human neurophysiological responses to emotional facial expressions of humans and dogs
(2024-11-25) Kujala, Miiamaaria V.; Parkkonen, Lauri; Kujala, Jan
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Despite the growing interest in the nonhuman animal emotionality, we currently know little about the human brain processing of nonconspecific emotional expressions. Here, we characterized the millisecond-scale temporal dynamics of human brain responses to conspecific human and nonconspecific canine emotional facial expressions. Our results revealed generally similar cortical responses to human and dog facial expressions in the occipital cortex during the first 500 ms, temporal cortex at 100-500 ms and parietal cortex at 150-350 ms from the stimulus onset. Responses to dog faces were pronounced at the latencies in temporal cortices corresponding to the time windows of early posterior negativity and late posterior positivity, suggesting attentional engagement to emotionally salient stimuli. We also utilized support vector machine-based classifiers to discriminate between the brain responses to different images. The subject trait-level empathy correlated with the accuracy of classifying the brain responses of aggressive from happy dog faces and happy from neutral human faces. This result likely reflects the attentional enhancement provoked by the subjective ecological salience of the stimuli.
Evidence for genetic regulation of the human parieto-occipital 10-Hz rhythmic activity
(2016-07-04) Salmela, Elina; Renvall, Hanna; Kujala, Jan; Hakosalo, Osmo; Illman, Mia; Vihla, Minna; Leinonen, Eira; Salmelin, Riitta; Kere, Juha
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Several functional and morphological brain measures are partly under genetic control. The identification of direct links between neuroimaging signals and corresponding genetic factors can reveal cellular-level mechanisms behind the measured macroscopic signals and contribute to the use of imaging signals as probes of genetic function. To uncover possible genetic determinants of the most prominent brain signal oscillation, the parieto-occipital 10-Hz alpha rhythm, we measured spontaneous brain activity with magnetoencephalography in 210 healthy siblings while the subjects were resting, with eyes closed and open. The reactivity of the alpha rhythm was quantified from the difference spectra between the two conditions. We focused on three measures: peak frequency, peak amplitude and the width of the main spectral peak. In accordance with earlier electroencephalography studies, spectral peak amplitude was highly heritable (h2 > 0.75). Variance component-based analysis of 28 000 single-nucleotide polymorphism markers revealed linkage for both the width and the amplitude of the spectral peak. The strongest linkage was detected for the width of the spectral peak over the left parieto-occipital cortex on chromosome 10 (LOD = 2.814, nominal P <0.03). This genomic region contains several functionally plausible genes, including GRID1 and ATAD1 that regulate glutamate receptor channels mediating synaptic transmission, NRG3 with functions in brain development and HRT7 involved in the serotonergic system and circadian rhythm. Our data suggest that the alpha oscillation is in part genetically regulated, and that it may be possible to identify its regulators by genetic analyses on a realistically modest number of samples.
Gamma oscillations in V1 are correlated with GABAA receptor density: A multi-modal MEG and Flumazenil-PET study
(2015) Kujala, Jan; Jung, Julien; Bouvard, Sandrine; Lecaignard, Francoise; Lothe, Amélie; Bouet, Romain; Ciumas, Carolina; RYvlin, Philippe; Jerbi, Karim
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
High-frequency oscillations in the gamma-band reflect rhythmic synchronization of spike timing in active neural networks. The modulation of gamma oscillations is a widely established mechanism in a variety of neurobiological processes, yet its neurochemical basis is not fully understood. Modeling, in-vitro and in-vivo animal studies suggest that gamma oscillation properties depend on GABAergic inhibition. In humans, search for evidence linking total GABA concentration to gamma oscillations has led to promising -but also to partly diverging- observations. Here, we provide the first evidence of a direct relationship between the density of GABAA receptors and gamma oscillatory gamma responses in human primary visual cortex (V1). By combining Flumazenil-PET (to measure resting-levels of GABAA receptor density) and MEG (to measure visually-induced gamma oscillations), we found that GABAA receptor densities correlated positively with the frequency and negatively with amplitude of visually-induced gamma oscillations in V1. Our findings demonstrate that gamma-band response profiles of primary visual cortex across healthy individuals are shaped by GABAA-receptor-mediated inhibitory neurotransmission. These results bridge the gap with in-vitro and animal studies and may have future clinical implications given that altered GABAergic function, including dysregulation of GABAA receptors, has been related to psychiatric disorders including schizophrenia and depression.
Human Sensorimotor Beta Event Characteristics and Aperiodic Signal Are Highly Heritable
(2024-01-31) Amande, K.; Salmela, Elina; Korsun, Olesia; Kujala, Jan; Salmelin, Riitta; Renvall, Hanna
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Individuals’ phenotypes, including the brain's structure and function, are largely determined by genes and their interplay. The resting brain generates salient rhythmic patterns that can be characterized noninvasively using functional neuroimaging such as magnetoencephalography (MEG). One of these rhythms, the somatomotor (rolandic) beta rhythm, shows intermittent high amplitude “events” that predict behavior across tasks and species. Beta rhythm is altered in neurological disease. The aperiodic (1/f) signal present in electrophysiological recordings is also modulated by some neurological conditions and aging. Both sensorimotor beta and aperiodic signal could thus serve as biomarkers of sensorimotor function. Knowledge about the extent to which these brain functional measures are heritable could shed light on the mechanisms underlying their generation. We investigated the heritability and variability of human spontaneous sensorimotor beta rhythm events and aperiodic activity in 210 healthy male and female adult siblings’ spontaneous MEG activity. The most heritable trait was the aperiodic 1/f signal, with a heritability of 0.87 in the right hemisphere. Time-resolved beta event amplitude parameters were also highly heritable, whereas the heritabilities for overall beta power, peak frequency, and measures of event duration remained nonsignificant. Human sensorimotor neural activity can thus be dissected into different components with variable heritability. We postulate that these differences partially reflect different underlying signal-generating mechanisms. The 1/f signal and beta event amplitude measures may depend more on fixed, anatomical parameters, whereas beta event duration and its modulation reflect dynamic characteristics, guiding their use as potential disease biomarkers.
Human sensorimotor resting state beta events and aperiodic activity show good test–retest reliability
(2024-07) Pauls, K. Amande M.; Nurmi, Pietari; Ala-Salomäki, Heidi; Renvall, Hanna; Kujala, Jan; Liljeström, Mia
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Objective: Diseases affecting sensorimotor function impair physical independence. Reliable functional clinical biomarkers allowing early diagnosis or targeting treatment and rehabilitation could reduce this burden. Magnetoencephalography (MEG) non-invasively measures brain rhythms such as the somatomotor ‘rolandic’ rhythm which shows intermittent high-amplitude beta (14–30 Hz) ‘events’ that predict behavior across tasks and species and are altered by sensorimotor neurological diseases. Methods: We assessed test–retest stability, a prerequisite for biomarkers, of spontaneous sensorimotor aperiodic (1/f) signal and beta events in 50 healthy human controls across two MEG sessions using the intraclass correlation coefficient (ICC). Beta events were determined using an amplitude-thresholding approach on a narrow-band filtered amplitude envelope obtained using Morlet wavelet decomposition. Results: Resting sensorimotor characteristics showed good to excellent test–retest stability. Aperiodic component (ICC 0.77–0.88) and beta event amplitude (ICC 0.74–0.82) were very stable, whereas beta event duration was more variable (ICC 0.55–0.7). 2–3 minute recordings were sufficient to obtain stable results. Analysis automatization was successful in 86%. Conclusions: Sensorimotor beta phenotype is a stable feature of an individual's resting brain activity even for short recordings easily measured in patients. Significance: Spontaneous sensorimotor beta phenotype has potential as a clinical biomarker of sensorimotor system integrity.
Korkeataajuisen MEG-signaalin signaali-kohinasuhteen parantaminen OTP-algoritmin avulla
(2018-09-07) Haakana, Joonas
Sähkötekniikan korkeakoulu | Bachelor's thesis
Large-scale functional networks connect differently for processing words and symbol strings
(2018-05-01) Liljeström, Mia; Vartiainen, Johanna; Kujala, Jan; Salmelin, Riitta
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Reconfigurations of synchronized large-scale networks are thought to be central neural mechanisms that support cognition and behavior in the human brain. Magnetoencephalog-raphy (MEG) recordings together with recent advances in network analysis now allow for sub-second snapshots of such networks. In the present study, we compared frequency-resolved functional connectivity patterns underlying reading of single words and visual recognition of symbol strings. Word reading emphasized coherence in a left-lateralized network with nodes in classical perisylvian language regions, whereas symbol processing recruited a bilateral network, including connections between frontal and parietal regions previously associated with spatial attention and visual working memory. Our results illustrate the flexible nature of functional networks, whereby processing of different form categories, written words vs. symbol strings, leads to the formation of large-scale functional networks that operate at distinct oscillatory frequencies and incorporate task-relevant regions. These results suggest that category-specific processing should be viewed not so much as a local process but as a distributed neural process implemented in signature networks. For words, increased coherence was detected particularly in the alpha (8–13 Hz) and high gamma (60–90 Hz) frequency bands, whereas increased coherence for symbol strings was observed in the high beta (21–29 Hz) and low gamma (30–45 Hz) frequency range. These findings attest to the role of coherence in specific frequency bands as a general mechanism for integrating stimulus-dependent information across brain regions.
MEG connectivity and power detections with minimum norm estimates require different regularization parameters
(2016) Hincapié, Ana Sofía; Kujala, Jan; Mattout, Jérémie; Daligault, Sebastien; Delpuech, Claude; Mery, Domingo; Cosmelli, Diego; Jerbi, Karim
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Minimum Norm Estimation (MNE) is an inverse solution method widely used to reconstruct the source time series that underlie magnetoencephalography (MEG) data. MNE addresses the ill-posed nature of MEG source estimation through regularization (e.g., Tikhonov regularization). Selecting the best regularization parameter is a critical step. Generally, once set, it is common practice to keep the same coefficient throughout a study. However, it is yet to be known whether the optimal lambda for spectral power analysis of MEG source data coincides with the optimal regularization for source-level oscillatory coupling analysis. We addressed this question via extensive Monte-Carlo simulations of MEG data, where we generated 21,600 configurations of pairs of coupled sources with varying sizes, signal-to-noise ratio (SNR), and coupling strengths. Then, we searched for the Tikhonov regularization coefficients (lambda) that maximize detection performance for (a) power and (b) coherence. For coherence, the optimal lambda was two orders of magnitude smaller than the best lambda for power. Moreover, we found that the spatial extent of the interacting sources and SNR, but not the extent of coupling, were the main parameters affecting the best choice for lambda. Our findings suggest using less regularization when measuring oscillatory coupling compared to power estimation.
A multimodal spectral approach to characterize rhythm in natural speech
(2016) Alexandrou, Anna; Saarinen, Timo; Kujala, Jan; Salmelin, Riitta
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Human utterances demonstrate temporal patterning, also referred to as rhythm. While simple oromotor behaviors (e.g., chewing) feature a salient periodical structure, conversational speech displays a time-varying quasi-rhythmic pattern. Quantification of periodicity in speech is challenging. Unimodal spectral approaches have highlighted rhythmic aspects of speech. However, speech is a complex multimodal phenomenon that arises from the interplay of articulatory, respiratory, and vocal systems. The present study addressed the question of whether a multimodal spectral approach, in the form of coherence analysis between electromyographic (EMG) and acoustic signals, would allow one to characterize rhythm in natural speech more efficiently than a unimodal analysis. The main experimental task consisted of speech production at three speaking rates; a simple oromotor task served as control. The EMG-acoustic coherence emerged as a sensitive means of tracking speech rhythm, whereas spectral analysis of either EMG or acoustic amplitude envelope alone was less informative. Coherence metrics seem to distinguish and highlight rhythmic structure in natural speech.
Naturalistic reading of multi-page texts elicits spatially extended modulation of oscillatory activity in the right hemisphere
(2024-12) Mäkelä, Sasu; Kujala, Jan; Ojala, Pauliina; Hyönä, Jukka; Salmelin, Riitta
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
The study of the cortical basis of reading has greatly benefited from the use of naturalistic paradigms that permit eye movements. However, due to the short stimulus lengths used in most naturalistic reading studies, it remains unclear how reading of texts comprising more than isolated sentences modulates cortical processing. To address this question, we used magnetoencephalography to study the spatiospectral distribution of oscillatory activity during naturalistic reading of multi-page texts. In contrast to previous results, we found abundant activity in the right hemisphere in several frequency bands, whereas reading-related modulation of neural activity in the left hemisphere was quite limited. Our results show that the role of the right hemisphere may be importantly emphasized as the reading process extends beyond single sentences.
Picture naming yields highly consistent cortical activation patterns: Test–retest reliability of magnetoencephalography recordings
(2021-02-15) Ala-Salomäki, Heidi; Kujala, Jan; Liljeström, Mia; Salmelin, Riitta
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Reliable paradigms and imaging measures of individual-level brain activity are paramount when reaching from group-level research studies to clinical assessment of individual patients. Magnetoencephalography (MEG) provides a direct, non-invasive measure of cortical processing with high spatiotemporal accuracy, and is thus well suited for assessment of functional brain damage in patients with language difficulties. This MEG study aimed to identify, in a delayed picture naming paradigm, source-localized evoked activity and modulations of cortical oscillations that show high test–retest reliability across measurement days in healthy individuals, demonstrating their applicability in clinical settings. For patients with a language disorder picture naming can be a challenging task. Therefore, we also determined whether a semantic judgment task (‘Is this item living?’) with a spoken response (“yes”/“no”) would suffice to induce comparably consistent activity within brain regions related to language production. The MEG data was collected from 19 healthy participants on two separate days. In picture naming, evoked activity was consistent across measurement days (intraclass correlation coefficient (ICC)>0.4) in the left frontal (400–800 ms after image onset), sensorimotor (200–800 ms), parietal (200–600 ms), temporal (200–800 ms), occipital (400–800 ms) and cingulate (600–800 ms) regions, as well as the right temporal (600–800 ms) region. In the semantic judgment task, consistent evoked activity was spatially more limited, occurring in the left temporal (200–800 ms), sensorimotor (400–800 ms), occipital (400–600 ms) and subparietal (600–800 ms) regions, and the right supramarginal cortex (600–800 ms). The delayed naming task showed typical beta oscillatory suppression in premotor and sensorimotor regions (800–1200 ms) but other consistent modulations of oscillatory activity were mostly observed in posterior cortical regions that have not typically been associated with language processing. The high test–retest consistency of MEG evoked activity in the picture naming task testifies to its applicability in clinical evaluations of language function, as well as in longitudinal MEG studies of language production in clinical and healthy populations.
Relationship between electrophysiological and hemodynamic markers of neural activity in cognitive neuroimaging
(2012) Hirvonen, Tuomas Antero
School of Science | Master's thesis
Both magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) provide an opportunity to study human brain function nonivasively. MEG measures directly the electrical activity of the cells in the cerebral cortex. fMRI, instead, is an indirect method: it measures changes in cerebral blood flow and hemoglobin concentration which are believed to be driven by the increased energy demand of active neural populations. However, the relationship between fMRI signals and electric activity of nerve cells, commonly referred to as neurovascular coupling, is far from simple. The purpose of this study was to examine spatiospectral heterogeneity of correlations between fMRI and MEG measurements; in particular, the goal was to investigate neurovascular coupling patterns during cognitive tasks. We wanted to identify regions that show significant correlation between electric and hemodynamic signals, and to examine what kind of correlation patterns can be found between the fMRI and the frequency-decomposed MEG signals in these regions. As previous studies have mostly used simple tasks and concentrated on primary sensory cortices, a central goal was to find out if the previously detected patterns also hold for other brain areas and in more complicated cognitive tasks. The investigations were possible, as MEG allows the measurement of electric activity of the entire cerebral cortex simultaneously, and as we used experimental setups involving higher cortical processing (picture-naming, auditory discrimination and reading). The analysis was conducted with the Partial Least Squares Correlation (PLSC) method. In the approach General Linear Model (GLM) and event-related Dynamic Imaging of Coherent Sources (erDICS) were used to compute brain activity patterns from fMRI and MEG measurements before the examination of neurovascular coupling via PLSC analysis. After PLSC voxels showing similar correlation pattern were clustered together. We also tested how well the fMRI values could be predicted from MEG data by using the identified coupling patterns. The obtained frequency patterns were mostly in line with previous studies. However, correlation patterns were more variable than reported earlier in higher cortical regions, and more whole-brain-studies with cognitive tasks would be required to validate our results.