Browsing by Subject "MEG"

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  • Huovilainen, Tatu (Helsingfors universitet, 2016)
    Background and aims. Most of the knowledge about neurocognitive processes of reading is based on artificial reading paradigms, such as serial presentation of isolated words or linguistic violation paradigms. The main aim of this thesis was to develop a novel approach to study the neural processes of reading. Specifically, a naturalistic reading task was employed due to concerns for ecological validity, that have been raised about the effects of task on the reading processes. A combination of methods was used to overcome difficulties introduced by this unconstrained reading approach. The second aim was to apply this novel paradigm to test if early differences in the neurocognitive processing of words from different word classes can be found during naturalistic reading. Early processing differences between word classes have been observed before, but they might be task-specific or due to processing related to linguistic violations. Methods. Magnetoencephalography (MEG) and eye movements were recorded simultaneously while participants (8, 4 males) silently read a biographical novel presented on a computer screen. The eye movement recording was used to relate the MEG recording to specific word fixation events during reading. Independent component analysis (ICA) was used to remove eye movement artifacts from the MEG recording and to extract activations of individual cortical areas. An automatic parser was used to extract word class information for all the words in the reading material. Event-related fields (ERFs) evoked by fixations on nouns and verbs were compared using nonparametric cluster-based permutation tests in time window of 0–250 ms after the fixation onset. Results and conclusions. The novel combination of methods used in this study proved to be a promising approach to examine neural processes of reading. In comparison to mainstream methodology of cognitive neuroscience of reading, the present approach has several theoretical and practical advantages. Statistically significant differences between nouns and verbs were found in the sensors above the left temporal cortex, in the 138–164 ms and 184–206 ms time windows after the fixation onset. The results confirm some of the earlier findings that were based on non-naturalistic reading settings and suggests that syntactic and/or semantic information is accessed remarkably early in the course of normal reading.
  • Wilenius, Juha; Lehtinen, Henri; Paetau, Ritva; Salmelin, Riitta; Kirveskari, Erika (2018)
    Objective The intracarotid amobarbital procedure (IAP) is the current "gold standard" in the preoperative assessment of language lateralization in epilepsy surgery candidates. It is, however, invasive and has several limitations. Here we tested a simple noninvasive language lateralization test performed with magnetoencephalography (MEG). Methods We recorded auditory MEG responses to pairs of vowels and pure tones in 16 epilepsy surgery candidates who had undergone IAP. For each individual, we selected the pair of planar gradiometer sensors with the strongest N100m response to vowels in each hemisphere and -from the vector sum of signals of this gradiometer pair-calculated the vowel/tone amplitude ratio in the left (L) and right (R) hemisphere and, subsequently, the laterality index: LI = (L-R)/(L+R). In addition to the analysis using a single sensor pair, an alternative analysis was performed using averaged responses over 18 temporal sensor pairs in both hemispheres. Results The laterality index did not correlate significantly with the lateralization data obtained from the IAP. However, an MEG pattern of stronger responses to vowels than tones in the left hemisphere and stronger responses to tones than vowels in the right hemisphere was associated with left-hemispheric language dominance in the IAP in all the six patients who showed this pattern. This results in a specificity of 100% and a sensitivity of 67% of this MEG pattern in predicting left-hemispheric language dominance (p = 0.01, Fisher's exact test). In the analysis using averaged responses over temporal channels, one additional patient who was left-dominant in IAP showed this particular MEG pattern, increasing the sensitivity to 78% (p = 0.003). Significance This simple MEG paradigm shows promise in feasibly and noninvasively confirming left-hemispheric language dominance in epilepsy surgery candidates. It may aid in reducing the need for the IAP, if the results are confirmed in larger patient samples.
  • Karadeniz, Sami (Helsingin yliopisto, 2019)
    Aims of the present study: Attention-deficit/hyperactivity disorder (ADHD), beginning in childhood and often continuing into adulthood, is a neurodevelopmental condition that impairs an individual’s functioning in everyday life. The disorder is characterized by impairments in attention regulation or impulse control, or both. Many of the symptoms are related to disturbances in attention, the ability to select behaviorally relevant stimuli and to filter out irrelevant information among the overwhelming amount of sensory data. Neural mechanisms of attention have been linked to oscillations in electophysiological brain activity at alpha frequencies (8–13 Hz), but information on alpha oscillations in adult ADHD has remained scarce. The aim of the present study was to examine differences in attention and distractibility related alpha oscillations between adult ADHD patients and neurotypical controls. Methods: Participants were instructed to attend moving spherical objects and to report color changes in the objects. Number of attended objects varied from one (in right or left visual hemifield) to two (one in both hemifields). In addition to the attended objects, participants were at times presented with distractors which they were instructed to ignore. Brain activity during task performance was measured with magnetoencephalography (MEG). Results and discussion: Behavioral performance was similar between the groups. However, alpha oscillations related to distractor processing differed in a statistically significant manner between ADHD patients and controls. Main differences were related to inter-hemispheric interactions, suggesting that attentional deficits in ADHD might be related to abnormalities between inter-hemispheric communication.
  • Trusbak Haumann, Niels; Hansen, Brian; Huotilainen, Minna; Vuust, Peter; Brattico, Elvira (2020)
    Background The accuracy of electroencephalography (EEG) and magnetoencephalography (MEG) in measuring neural evoked responses (ERs) is challenged by overlapping neural sources. This lack of accuracy is a severe limitation to the application of ERs to clinical diagnostics. New method We here introduce a theory of stochastic neuronal spike timing probability densities for describing the large-scale spiking activity in neural assemblies, and a spike density component analysis (SCA) method for isolating specific neural sources. The method is tested in three empirical studies with 564 cases of ERs to auditory stimuli from 94 humans, each measured with 60 EEG electrodes and 306 MEG sensors, and a simulation study with 12,300 ERs. Results The first study showed that neural sources (but not non-encephalic artifacts) in individual averaged MEG/EEG waveforms are modelled accurately with temporal Gaussian probability density functions (median 99.7 %–99.9 % variance explained). The following studies confirmed that SCA can isolate an ER, namely the mismatch negativity (MMN), and that SCA reveals inter-individual variation in MMN amplitude. Finally, SCA reduced errors by suppressing interfering sources in simulated cases. Comparison with existing methods We found that gamma and sine functions fail to adequately describe individual MEG/EEG waveforms. Also, we observed that principal component analysis (PCA) and independent component analysis (ICA) does not consistently suppress interference from overlapping brain activity in neither empirical nor simulated cases. Conclusions These findings suggest that the overlapping neural sources in single-subject or patient data can be more accurately separated by applying SCA in comparison to PCA and ICA.
  • Koskinen, Miika; Kurimo, Mikko; Gross, Joachim; Hyvärinen, Aapo; Hari, Riitta (2020)
    Natural speech builds on contextual relations that can prompt predictions of upcoming utterances. To study the neural underpinnings of such predictive processing we asked 10 healthy adults to listen to a 1-h-long audiobook while their magnetoencephalographic (MEG) brain activity was recorded. We correlated the MEG signals with acoustic speech envelope, as well as with estimates of Bayesian word probability with and without the contextual word sequence (N-gram and Unigram, respectively), with a focus on time-lags. The MEG signals of auditory and sensorimotor cortices were strongly coupled to the speech envelope at the rates of syllables (4-8 Hz) and of prosody and intonation (0.5-2 Hz). The probability structure of word sequences, independently of the acoustical features, affected the
  • Haumann, Niels Trusbak; Parkkonen, Lauri; Kliuchko, Marina; Vuust, Peter; Brattico, Elvira (2016)
    We here compared results achieved by applying popular methods for reducing artifacts in magnetoencephalography (MEG) and electroencephalography (EEG) recordings of the auditory evoked Mismatch Negativity (MMN) responses in healthy adult subjects. We compared the Signal Space Separation (SSS) and temporal SSS (tSSS) methods for reducing noise from external and nearby sources. Our results showed that tSSS reduces the interference level more reliably than plain SSS, particularly for MEG gradiometers, also for healthy subjects not wearing strongly interfering magnetic material. Therefore, tSSS is recommended over SSS. Furthermore, we found that better artifact correction is achieved by applying Independent Component Analysis (ICA) in comparison to Signal Space Projection (SSP). Although SSP reduces the baseline noise level more than ICA, SSP also significantly reduces the signal-slightly more than it reduces the artifacts interfering with the signal. However, ICA also adds noise, or correction errors, to the wave form when the signal-to-noise ratio (SNR) in the original data is relatively low-in particular to EEG and to MEG magnetometer data. In conclusion, ICA is recommended over SSP, but one should be careful when applying ICA to reduce artifacts on neurophysiological data with relatively low SNR.
  • Jaiswal, Amit; Nenonen, Jukka; Stenroos, Matti; Gramfort, Alexandre; Dalal, Sarang S.; Westner, Britta U.; Litvak, Vladimir; Mosher, John C.; Schoffelen, Jan-Mathijs; Witton, Caroline; Oostenveld, Robert; Parkkonen, Lauri (2020)
    Beamformers are applied for estimating spatiotemporal characteristics of neuronal sources underlying measured MEG/EEG signals. Several MEG analysis toolboxes include an implementation of a linearly constrained minimum-variance (LCMV) beamformer. However, differences in implementations and in their results complicate the selection and application of beamformers and may hinder their wider adoption in research and clinical use. Additionally, combinations of different MEG sensor types (such as magnetometers and planar gradiometers) and application of preprocessing methods for interference suppression, such as signal space separation (SSS), can affect the results in different ways for different implementations. So far, a systematic evaluation of the different implementations has not been performed. Here, we compared the localization performance of the LCMV beamformer pipelines in four widely used open-source toolboxes (MNE-Python, FieldTrip, DAiSS (SPM12), and Brainstorm) using datasets both with and without SSS interference suppression. We analyzed MEG data that were i) simulated, ii) recorded from a static and moving phantom, and iii) recorded from a healthy volunteer receiving auditory, visual, and somatosensory stimulation. We also investigated the effects of SSS and the combination of the magnetometer and gradiometer signals. We quantified how localization error and point-spread volume vary with the signal-to-noise ratio (SNR) in all four toolboxes. When applied carefully to MEG data with a typical SNR (3-15 dB), all four toolboxes localized the sources reliably; however, they differed in their sensitivity to preprocessing parameters. As expected, localizations were highly unreliable at very low SNR, but we found high localization error also at very high SNRs for the first three toolboxes while Brainstorm showed greater robustness but with lower spatial resolution. We also found that the SNR improvement offered by SSS led to more accurate localization.
  • Smeds, Eero; Vanhatalo, Sampsa; Piitulainen, Harri; Bourguignon, Mathieu; Jousmaki, Veikko; Hari, Riitta (2017)
    Objective: Somatosensory evoked potentials have high prognostic value in neonatal intensive care, but their recording from infants is challenging. Here, we studied the possibility to elicit cortical responses in newborns by simple passive hand movements. Methods: We examined 13 newborns (postnatal age 1-46 days) during clinically indicated 19-channel electroencephalography (EEG) recordings in the neonatal intensive care unit; EEG indications included birth asphyxia and suspected epileptic seizures. The experimenter moved the infant's wrist or fingers at 1 or 2 Hz for 5-10 min, separately on both sides. We measured movement kinematics with an accelerometer attached to the infant's hand and computed coherence between the EEG and acceleration signals (corticokinematic coherence, CKC). Results: Statistically significant CKC (amplitude 0.020-0.511) with characteristic scalp topography was observed in all infants at twice the movement frequency. CKC was contralaterally dominant on the central scalp (median laterality index 0.48 for right-hand and -0.63 for left-hand movements). Conclusions: Passive movements elicit cortical responses that can be readily observed in clinical EEG recordings from newborns in the intensive-care environment. (C) 2017 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd.
  • Auno, Sami; Lauronen, Leena; Wilenius, Juha; Peltola, Maria; Vanhatalo, Sampsa; Palva, J. Matias (2021)
    Objective: To examine the usability of long-range temporal correlations (LRTCs) in non-invasive localization of the epileptogenic zone (EZ) in refractory parietal lobe epilepsy (RPLE) patients. Methods: We analyzed 10 RPLE patients who had presurgical MEG and underwent epilepsy surgery. We quantified LRTCs with detrended fluctuation analysis (DFA) at four frequency bands for 200 cortical regions estimated using individual source models. We correlated individually the DFA maps to the distance from the resection area and from cortical locations of interictal epileptiform discharges (IEDs). Additionally, three clinical experts inspected the DFA maps to visually assess the most likely EZ locations. Results: The DFA maps correlated with the distance to resection area in patients with type II focal cortical dysplasia (FCD) (p < 0:05), but not in other etiologies. Similarly, the DFA maps correlated with the IED locations only in the FCD II patients. Visual analysis of the DFA maps showed high interobserver agreement and accuracy in FCD patients in assigning the affected hemisphere and lobe. Conclusions: Aberrant LRTCs correlate with the resection areas and IED locations. Significance: This methodological pilot study demonstrates the feasibility of approximating cortical LRTCs from MEG that may aid in the EZ localization and provide new non-invasive insight into the presurgical evaluation of epilepsy. (c) 2021 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. This is an open access article under the CC BY license (
  • Hirvonen, Jonni Santeri; Monto, Simo Petteri; Wang, Sheng Hua; Palva, Jaakko Matias; Palva, Satu Orvokki (2018)
    Sensory-guided actions entail the processing of sensory information, generation of perceptual decisions, and the generation of appropriate actions. Neuronal activity underlying these processes is distributed into sensory, fronto-parietal, and motor brain areas, respectively. How the neuronal processing is coordinated across these brain areas to support functions from perception to action remains unknown. We investigated whether phase synchronization in large-scale networks coordinate these processes. We recorded human cortical activity with magnetoencephalography (MEG) during a task in which weak somatosensory stimuli remained unperceived or were perceived. We then assessed dynamic evolution of phase synchronization in large-scale networks from source-reconstructed MEG data by using advanced analysis approaches combined with graph theory. Here we show that perceiving and reporting of weak somatosensory stimuli is correlated with sustained strengthening of large-scale synchrony concurrently in delta/theta (3-7 Hz) and gamma (40-60 Hz) frequency bands. In a data-driven network localization, we found this synchronization to dynamically connect the task-relevant, that is, the fronto-parietal, sensory, and motor systems. The strength and temporal pattern of interareal synchronization were also correlated with the response times. These data thus show that key brain areas underlying perception, decision-making, and actions are transiently connected by large-scale dynamic phase synchronization in the delta/theta and gamma bands.
  • He, Bin; Astolfi, Laura; Valdes-Sosa, Pedro Antonio; Marinazzo, Daniele; Palva, Satu O.; Benar, Christian-George; Michel, Christoph M.; Koenig, Thomas (2019)
    We review the theory and algorithms of electrophysiological brain connectivity analysis. This tutorial is aimed at providing an introduction to brain functional connectivity from electrophysiological signals, including electroencephalography, magnetoencephalography, electrocorticography, and stereoelectroencephalography. Various connectivity estimators are discussed, and algorithms introduced. Important issues for estimating and mapping brain functional connectivity with electrophysiology are discussed.
  • Haumann, Niels T.; Lumaca, Massimo; Kliuchko, Marina; Santacruz, Jose L.; Vuust, Peter; Brattico, Elvira (2021)
    Evoked cortical responses (ERs) have mainly been studied in controlled experiments using simplified stimuli. Though, an outstanding question is how the human cortex responds to the complex stimuli encountered in realistic situations. Few electroencephalography (EEG) studies have used Music Information Retrieval (MIR) tools to extract cortical P1/N1/P2 to acoustical changes in real music. However, less than ten events per music piece could be detected leading to ERs due to limitations in automatic detection of sound onsets. Also, the factors influencing a successful extraction of the ERs have not been identified. Finally, previous studies did not localize the sources of the cortical generators. This study is based on an EEG/MEG dataset from 48 healthy normal hearing participants listening to three real music pieces. Acoustic features were computed from the audio signal of the music with the MIR Toolbox. To overcome limits in automatic methods, sound onsets were also manually detected. The chance of obtaining detectable ERs based on ten randomly picked onset points was less than 1:10,000. For the first time, we show that naturalistic P1/N1/P2 ERs can be reliably measured across 100 manually identified sound onsets, substantially improving the signal-to-noise level compared to 2.5 Hz). Furthermore, during monophonic sections of the music only P1/P2 were measurable, and during polyphonic sections only N1. Finally, MEG source analysis revealed that naturalistic P2 is located in core areas of the auditory cortex.
  • Partanen, Eino J.; Leminen, Alina; Cook, Clare; Shtyrov, Yury (2018)
    To master linguistic communication, humans must acquire large vocabularies quickly and effortlessly. Efficient word learning might be facilitated by the ability to rapidly acquire novel word forms even outside the focus of attention, occurring within minutes of repetitive exposure and suggesting fast and automatic lexicon acquisition. However, this phenomenon has been studied in the auditory modality only, and it is unknown whether similar mechanisms also exist in the visual domain. We tested this by presenting participants with novel written word forms while the focus of their attention was on a non-linguistic dual colour-detection task. Matched familiar word forms served as a control. Using magnetoencephalography (MEG), we scrutinised changes in neuromagnetic responses to familiar and to novel word forms over approximately 15 minutes of exposure. We found, for the first time, a visual analogue of automatic rapid build-up of neural memory circuits for unattended novel lexical items, seen as a rapid enhancement of early (similar to 100 ms post-onset) activation in the left anterior-superior temporal lobe. Our results suggest that the brain quickly forms cortical representations for new written forms, and indicate that the automatic neural mechanisms subserving rapid online acquisition of novel linguistic information might be shared by both auditory and visual modalities.
  • Moisseinen, Nella (Helsingin yliopisto, 2018)
    Aivoverenkiertohäiriö (AVH) on maailmanlaajuisesti merkittävimpiä kielen ja auditiivisen havaitsemisen vaikeuksien aiheuttajia. Viime vuosikymmeninä musiikin ja kielen harjoittamisen on havaittu edistävän aivoissa paitsi modaliteetin sisäistä (kieli–kieli, musiikki–musiikki) havaitsemista myös siirtymävaikutusta erityisesti musiikista kielen havaitsemiseen. Tämä Pro Gradu -tutkielma selvitti äänikirjojen ja musiikin kuuntelun vaikutuksia varhaiseen puheen ja musiikin havaitsemiseen ensimmäisestä aivohalvauksesta toipuvissa aivoissa. Kontrolloituun tutkimusasetelmaan kuului kaksi interventioryhmää, joista toinen kuunteli päivittäin äänikirjoja ja toinen musiikkia ensimmäisten kahden kuukauden aikana aivohalvaukseen sairastumisesta; kontrolliryhmä ei saanut kuunneltavaa materiaalia. Potilaiden (N = 55) varhaista puheen ja musiikin havaitsemista aivoissa mitattiin äänisarjassa poikkeavan tavun (puhe) ja soinnun (musiikki) magneettisella poikkeavuusnegativisuusvasteella (magnetic mismatch negativity, MMNm) akuuttivaiheessa sekä seurantamittauksissa kolme ja kuusi kuukautta aivohalvaukseen sairastumisesta. Magnetoenkefalografisten (MEG) vasteiden lähteet aivoissa paikannettiin erotuskäyrien miniminormiestimaateilla (MNE) potilaiden yksilöllisissä, rakenteellisiin magneettiresonanssikuviin (MRI) perustuvissa aivomalleissa. Vasteiden lähteet rajoitettiin kuuteen puheen ja musiikin havaitsemisen kannalta keskeiseen alueeseen (keskimmäinen ja alempi otsalohkopoimu, ylempi ja keskimmäinen ohimolohkopoimu sekä supramarginaalinen ja kulmapoimu). Ryhmä- ja leesion hemisfäärin interaktiot analysoitiin tilastollisesti toistomittausten varianssianalyysillä näillä alueilla. Lisäksi interaktiotulokset korreloitiin (Pearson) neuropsykologiseen kuntoutumiseen verbaalisen muistin, työmuistin, kielen ja musiikin havaitsemisen osa-alueilla aivovasteiden laajemman osallisuuden selvittämiseksi auditiivisessa tiedonkäsittelyssä. Tutkimuksessa havaittiin, että äänikirjojen kuuntelu tehosti varhaista kielen havaitsemista vasemmanpuoleisilla otsalohkon alueilla kontrolliryhmään verrattuna; MMNm:n lateralisoituminen vasemmalle ilmeni kolme kuukautta aivohalvaukseen sairastumisesta ja oli lisäksi yhteydessä verbaalisen muistin paranemiseen äänikirjaryhmällä. Musiikin havaitseminen puolestaan herätti MMNm- ja P3a-komponentin yhdistelmän, jonka amplitudi vasemmalla alemmalla otsalohkopoimulla korreloi negatiivisesti työmuistin ja verbaalisen muistin paranemiseen kuusi kuukautta aivohalvaukseen sairastumisesta. Musiikin kuuntelu paransi suoriutumista, kun äänikirjojen kuuntelu oli yhteydessä kasvavaan amplitudiin ja heikkenevään työ- ja verbaaliseen muistiin; ilmiö todennäköisesti liittyy musiikin aikaansaamaan aktivaation levittäytymiseen aivoissa. Yhdessä tulokset viittaavat siihen, että äänikirjojen kuuntelu voi kehittää varhaista auditiivista havaitsemista kielimodaliteetin sisällä, joskaan se ei suoraan tue myöhempää, tarkkaavuuteen ja/tai musiikkimodaliteettiin liittyvää havaitsemista. Musiikin kuuntelu sen sijaan ei tue varhaista puheen havaitsemista suoraan, mutta voi edistää aivohalvauksen jälkeisiä plastisia muutoksia havaitsemisen ja verbaalisen muistin kannalta edullisemmalla tavalla.
  • Siebenhühner, Felix; Wang, Sheng H.; Arnulfo, Gabriele; Lampinen, Anna; Nobili, Lino; Palva, J. Matias; Palva, Satu (2020)
    Phase synchronization of neuronal oscillations in specific frequency bands coordinates anatomically distributed neuronal processing and communication. Typically, oscillations and synchronization take place concurrently in many distinct frequencies, which serve separate computational roles in cognitive functions. While within-frequency phase synchronization has been studied extensively, less is known about the mechanisms that govern neuronal processing distributed across frequencies and brain regions. Such integration of processing between frequencies could be achieved via cross-frequency coupling (CFC), either by phase-amplitude coupling (PAC) or by n:m-cross-frequency phase synchrony (CFS). So far, studies have mostly focused on local CFC in individual brain regions, whereas the presence and functional organization of CFC between brain areas have remained largely unknown. We posit that interareal CFC may be essential for large-scale coordination of neuronal activity and investigate here whether genuine CFC networks are present in human resting-state (RS) brain activity. To assess the functional organization of CFC networks, we identified brain-wide CFC networks at mesoscale resolution from stereoelectroencephalography (SEEG) and at macroscale resolution from source-reconstructed magnetoencephalography (MEG) data. We developed a novel, to our knowledge, graph-theoretical method to distinguish genuine CFC from spurious CFC that may arise from nonsinusoidal signals ubiquitous in neuronal activity. We show that genuine interareal CFC is present in human RS activity in both SEEG and MEG data. Both CFS and PAC networks coupled theta and alpha oscillations with higher frequencies in large-scale networks connecting anterior and posterior brain regions. CFS and PAC networks had distinct spectral patterns and opposing distribution of low- and high-frequency network hubs, implying that they constitute distinct CFC mechanisms. The strength of CFS networks was also predictive of cognitive performance in a separate neuropsychological assessment. In conclusion, these results provide evidence for interareal CFS and PAC being 2 distinct mechanisms for coupling oscillations across frequencies in large-scale brain networks.
  • Hirvonen, Jonni (Helsingfors universitet, 2013)
    Tässä pro gradu -tutkielmassa on tarkasteltu aivosähkö- ja aivomagneettikäyrien amplitudien vaihteluiden vastaavuussuhteita koehenkilön suoriutumiseen audiovisuaalisten ärsykkeiden tarkkaavaisuustehtävissä. Aikaisemmista tutkimuksista tiedetään, että koehenkilön osumatarkkuus ei pysy vakiona koko tehtävän ajan, vaan on monesti jaksottunut valppauden ja herpaantumisen jaksoihin. Lisäksi osumatarkkuus koko kokeen ajalta on alhaisempi kuin lyhyen kalibraatiojakson ajalta mitattuna. Tämän intuitiiviseltä tuntuvan keskittymiskyvyn järkkymisen taustalla on esitetty olevan henkilön introspektiiviset ja mielenvaelteluun liittyvät kognitiiviset toiminnot. Ennen tätä tutkimusta on jäänyt kuitenkin osoittamatta osumatarkkuuden ailahtelun yhteys aivokuoren hermostollisen aktiivisuuden pitkällä ajalla autokorreloiviin muutoksiin lähdemallintamisella. Tämän pro gradun tutkimustulokset osoittavat, että näiden kahden lajin välillä on olemassa merkittävä korrelaatioyhteys. Lisäksi lepovaiheen aivotoiminnasta modaliteettispesifeillä tarkkaavaisuus- ja oletustilan verkoston alueilla voidaan ennustaa psykofyysisen suoriutumisen vaihteluja jatkuvan audiovisuaalisen ärsykekynnyksen tarkkaavaisuustehtävän aikana. Keskittymiskyvyn vaihtelun muutoksia hermostollisella tasolla ja näitä mahdollisesti ilmentäviä käyttäytymisen ailahteluja psykofyysisinä parametreinä, kuten osumatarkkuutena ja reaktionopeutena, voidaan luonnehtia skaalauslakianalyysilla. Ilmiön skaalaton käyttäytyminen heijastelee monimutkaisen järjestelmän taipumusta luoda sisäisiä vastaavuussuhteita eli autokorrelaatioita, jotka heikkenevät hitaammin ja ulottuvat kauemmaksi ajassa ja/tai paikassa kuin mitä alla piilevistä mekanismeista voidaan suoraan ennustaa. On havaittu, että osumatarkkuuden jaksottuminen ja spontaani aivotoiminta noudattavat potenssilain skaalauskäyttäytymistä ajan suhteen. Psykofyysisen ja hermostollisen skaalauslain mukaisen käyttäytymisen kvantifioimiseksi tässä opinnäytetyössä on käytetty vaihtelun ikkunallista autokorrelaatioanalyysiä, DFA:ta. DFA paljastaa ilmiön sisällä olevien peräkkäisten tapahtumien autokorrelaatioiden kestävyyden tarkasteluvälin kasvaessa. Skaalausluvut eli DFA-eksponentit on johdettu tässä kokeessa jatkuvan audiovisuaalisen ärsykekynnyksen tarkkaavaisuustehtävän ja levon aikana rekisteröidyistä aivosähkö- ja aivomagneettikäyräsignaalien verhokäyrästä sekä psykofyysisen osuma/huti -binäärisekvenssistä rakennetusta keinotekoisesta satunnaiskulun kaltaisesta käyrästä. Jatkuvat ärsykekynnystehtävät soveltuvat hyvin tarkkaavaisuuden top-down mekanismien tutkimiseen, koska heikoista, vain juuri ja juuri havaintokyvyn säteellä olevista ärsykkeistä seuraa verraten heikko bottom-up hermostovaste. Näin keskittymiskykyyn vaikuttavat top-down säätelymekanismit kuten motivaatio, päämäärät tai mielenvaeltelu eli spontaanilta vaikuttava aivotoiminta edustuu selkeämmin aivosähkö- ja -magneettikäyrissä. Aivokuoren kokonaisvaltaisen skaalautumisen lisäksi ollaan kiinnostuneita psykofyysisten ja hermostollisten vastaavuussuhteiden jakaumamallista tietyille aivoalueille. Mitattujen hermostollisten signaalien paikantaminen tarkalleen tietyille aivokuoren alueille aiheuttaa käänteisen ongelman, joka on ratkaistu tässä MNE -lähdemallintamisella. Lähdemallintamisen algoritmit tuottavat todennäköisimmän mallin aivokuoren alueista, joiden aktiivisuudella voidaan selittää mitatut MEEG signaalit. Mallintaminen on työn kriittinen vaihe, koska sillä yhdistetään neuroanatominen tieto fysiologisen ja psykofyysisen tiedon kanssa. Yksilötason data on käsitelty lopuksi ryhmätasolla tilastollisin menetelmin korrelaatiotulosten merkittävyyksien arvioimiseksi.
  • Lobier, Muriel; Palva, J. Matias; Palva, Satu (2018)
    Visuospatial attention prioritizes processing of attended visual stimuli. It is characterized by lateralized alpha-band (8-14 Hz) amplitude suppression in visual cortex and increased neuronal activity in a network of frontal and parietal areas. It has remained unknown what mechanisms coordinate neuronal processing among frontoparietal network and visual cortices and implement the attention-related modulations of alpha-band amplitudes and behavior. We investigated whether large-scale network synchronization could be such a mechanism. We recorded human cortical activity with magnetoencephalography (MEG) during a visuospatial attention task. We then identified the frequencies and anatomical networks of inter-areal phase synchronization from source localized MEG data. We found that visuospatial attention is associated with robust and sustained long-range synchronization of cortical oscillations exclusively in the high-alpha (10-14 Hz) frequency band. This synchronization connected frontal, parietal and visual regions and was observed concurrently with amplitude suppression of low-alpha (6-9 Hz) band oscillations in visual cortex. Furthermore, stronger high-alpha phase synchronization was associated with decreased reaction times to attended stimuli and larger suppression of alpha-band amplitudes. These results thus show that high-alpha band phase synchronization is functionally significant and could coordinate the neuronal communication underlying the implementation of visuospatial attention.
  • Wang, Sheng H.; Lobier, Muriel; Siebenhuhner, Felix; Puoliväli, Tuomas; Palva, Satu; Palva, J. Matias (2018)
    Inter-areal functional connectivity (FC), neuronal synchronization in particular, is thought to constitute a key systems-level mechanism for coordination of neuronal processing and communication between brain regions. Evidence to support this hypothesis has been gained largely using invasive electrophysiological approaches. In humans, neuronal activity can be non-invasively recorded only with magneto-and electroencephalography (MEG/EEG), which have been used to assess FC networks with high temporal resolution and whole-scalp coverage. However, even in source-reconstructed MEG/EEG data, signal mixing, or "source leakage", is a significant confounder for FC analyses and network localization. Signal mixing leads to two distinct kinds of false-positive observations: artificial interactions (AI) caused directly by mixing and spurious interactions (SI) arising indirectly from the spread of signals from true interacting sources to nearby false loci. To date, several interaction metrics have been developed to solve the AI problem, but the SI problem has remained largely intractable in MEG/EEG all-to-all source connectivity studies. Here, we advance a novel approach for correcting SIs in FC analyses using source-reconstructed MEG/EEG data. Our approach is to bundle observed FC connections into hyperedges by their adjacency in signal mixing. Using realistic simulations, we show here that bundling yields hyperedges with good separability of true positives and little loss in the true positive rate. Hyperedge bundling thus significantly decreases graph noise by minimizing the false-positive to true-positive ratio. Finally, we demonstrate the advantage of edge bundling in the visualization of large-scale cortical networks with real MEG data. We propose that hypergraphs yielded by bundling represent well the set of true cortical interactions that are detectable and dissociable in MEG/EEG connectivity analysis.
  • Hakala, Tero; Hulten, Annika; Lehtonen, Minna; Lagus, Krista; Salmelin, Riitta (2018)
    Neuroimaging studies of the reading process point to functionally distinct stages in word recognition. Yet, current understanding of the operations linked to those various stages is mainly descriptive in nature. Approaches developed in the field of computational linguistics may offer a more quantitative approach for understanding brain dynamics. Our aim was to evaluate whether a statistical model of morphology, with well-defined computational principles, can capture the neural dynamics of reading, using the concept of surprisal from information theory as the common measure. The Morfessor model, created for unsupervised discovery of morphemes, is based on the minimum description length principle and attempts to find optimal units of representation for complex words. In a word recognition task, we correlated brain responses to word surprisal values derived from Morfessor and from other psycholinguistic variables that have been linked with various levels of linguistic abstraction. The magnetoencephalography data analysis focused on spatially, temporally and functionally distinct components of cortical activation observed in reading tasks. The early occipital and occipito-temporal responses were correlated with parameters relating to visual complexity and orthographic properties, whereas the later bilateral superior temporal activation was correlated with whole-word based and morphological models. The results show that the word processing costs estimated by the statistical Morfessor model are relevant for brain dynamics of reading during late processing stages.
  • Tokariev, Anton; Roberts, James A.; Zalesky, Andrew; Zhao, Xuelong; Vanhatalo, Sampsa; Breakspear, Michael; Cocchi, Luca (2019)
    Sleep architecture carries vital information about brain health across the lifespan. In particular, the ability to express distinct vigilance states is a key physiological marker of neurological wellbeing in the newborn infant although systems-level mechanisms remain elusive. Here, we demonstrate that the transition from quiet to active sleep in newborn infants is marked by a substantial reorganization of large-scale cortical activity and functional brain networks. This reorganization is attenuated in preterm infants and predicts visual performance at two years. We find a striking match between these empirical effects and a computational model of large-scale brain states which uncovers fundamental biophysical mechanisms not evident from inspection of the data. Active sleep is defined by reduced energy in a uniform mode of neural activity and increased energy in two more complex anteroposterior modes. Preterm-born infants show a deficit in this sleep-related reorganization of modal energy that carries novel prognostic information.