Dynamic correlations in ongoing neuronal oscillations in humans - perspectives on brain function and its disorders

This Thesis is involved with neuronal oscillations in the human brain and their coordination across time, space and frequency. The aim of the Thesis was to quantify correlations in neuronal oscillations over these dimensions, and to elucidate their significance in cognitive processing and brain disorders. Magnetoencephalographic (MEG) recordings of major depression patients revealed that long-range temporal correlations (LRTC) were decreased, compared to control subjects, in the 5 Hz oscillations in a manner that was dependent on the degree of the disorder. While studying epileptic patients, on the other hand, it was found that the LRTC in neuronal oscillations recorded intracranially with electroencephalography (EEG) were strengthened in the seizure initiation region. A novel approach to map spatial correlations between cortical regions was developed. The method is based on parcellating the cortex to patches and estimating phase synchrony between all patches. Mapping synchrony from inverse-modelled MEG / EEG data revealed wide-spread phase synchronization during a visual working memory task. Furthermore, the network architectures of task-related synchrony were found to be segregated over frequency. Cross-frequency interactions were investigated with analyses of nested brain activity in data recorded with full-bandwidth EEG during a somatosensory detection task. According to these data, the phase of ongoing infra-slow fluctuations (ISF), which were discovered in the frequency band of 0.01-0.1 Hz, was correlated with the amplitude of faster > 1 Hz neuronal oscillations. Strikingly, the behavioral detection performance displayed similar dependency on the ISFs as the > 1 Hz neuronal oscillations. The studies composing this Thesis showed that correlations in neuronal oscillations are functionally related to brain disorders and cognitive processing. Such correlations are suggested to reveal the coordination of neuronal oscillations across time, space and frequency. The results contribute to system-level understanding of brain function

Dynamic large-scale network synchronization from perception to action

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.Peer reviewe

Ghost interactions in MEG/EEG source space : A note of caution on inter-areal coupling measures

When combined with source modeling, magneto- (MEG) and electroencephalography (EEG) can be used to study long-range interactions among cortical processes non-invasively. Estimation of such inter-areal connectivity is nevertheless hindered by instantaneous field spread and volume conduction, which artificially introduce linear correlations and impair source separability in cortical current estimates. To overcome the inflating effects of linear source mixing inherent to standard interaction measures, alternative phase- and amplitude-correlation based connectivity measures, such as imaginary coherence and orthogonalized amplitude correlation have been proposed. Being by definition insensitive to zero-lag correlations, these techniques have become increasingly popular in the identification of correlations that cannot be attributed to field spread or volume conduction. We show here, however, that while these measures are immune to the direct effects of linear mixing, they may still reveal large numbers of spurious false positive connections through field spread in the vicinity of true interactions. This fundamental problem affects both region-of-interest-based analyses and all-to-all connectome mappings. Most importantly, beyond defining and illustrating the problem of spurious, or "ghost" interactions, we provide a rigorous quantification of this effect through extensive simulations. Additionally, we further show that signal mixing also significantly limits the separability of neuronal phase and amplitude correlations. We conclude that spurious correlations must be carefully considered in connectivity analyses in MEG/EEG source space even when using measures that are immune to zero-lag correlations.Peer reviewe

Vaihesynkronia epilepsiapotilaiden aivokuoren sähköisissä mittauksissa

The recording of electric potentials produced by neuronal activity is a central tool in studies of brain function. Continuous multi-channel measurements allow the elucidation of time course and loci of neuronal activity. However, the spatial resolution provided by traditional electroencephalography, the non-invasive measurement of electric potentials on the scalp, is insufficient for the examination of small-scale phenomena. This is a considerable problem not only in basic brain research, but also in clinical localization of epileptogenic zones in patients. Hence, in pre-surgical evaluation of epileptic patients, recordings using electrodes placed into the subdural space between the cortex and the skull must be used to locate pathological brain regions. These recordings reveal neuronal potentials with high accuracy, but they have so far been rarely utilized in brain research. Quantification of phase synchrony is a relatively novel method for identifying interactions between two dynamical systems. It is based on the estimation of phases of two systems and on the subsequent evaluation of their mutual dependencies. As phase relations appear to be a central element of the neuronal code, the functional connectivity in neuronal networks can be probed with this method. The phase-locking index, together with its statistical significance, is typically calculated for narrow frequency bands. This restriction can be seen as both an advantage and a drawback; neuronal oscillations have gained widespread interest, but their functional significance to brain operation is still under hot debate. There is, nevertheless, a growing body of evidence of linking narrow-band network oscillations to information processing in the brain. In this thesis, I have studied intracranial, subdural-electrode measurements of three epileptic patients. The aim of this work was twofold: first, the eligibility of the phase synchrony method for analysis of subdural recorded activity had to be determined. The second aim was to estimate the usability of the method for studying network-level mechanisms of epilepsy and their modulation under anti-epileptic medication. This report begins with an introduction to the structure and operation of the human brain at different scales and with a brief note on epilepsy. Next I describe the physical basis for the phase synchronization phenomenon and its relation to measurements of brain function. The methods used and developed in the course of this work follow, with an emphasis on wavelet analysis, image processing and the recording procedures. The result section begins with the co-localization of computerized tomography and magnetic resonance images that was used to obtain the electrode locations in relation to anatomic landmarks. The localization data are, in turn, needed in the determination of volume conduction artefacts in phase synchrony estimates as a function of inter-electrode separation. In this thesis, I show that this artefact is restricted to a distance of20-30 mm, and even at short distances (10 mm), its effects are minor. I evaluate also the effects of an anti-epileptic and anxiolytic drug, benzodiazepine, on the amplitude of cortical oscillations and their phase synchrony. Benzodiazepine was found to enhance amplitude and suppress phase synchrony. In addition, largest changes were observed near the clinically identified epileptogenic regions. This finding may lead to more sophisticated methods for the localization of the epileptic focus. Taken together, these promising results indicate the need for clinical studies utilizing the methods described in this thesis. The work was conducted in the Biomag-laboratory of the Helsinki University Central Hospital. The laboratory is a part of the Helsinki Brain Research Center, a center of excellence of the Academy of Finland.Aivojen hermoverkkotason toiminnan tutkimuksessa hermosolujen tuottamat sähköiset potentiaalit ovat tärkeä työkalu. Mittaamalla potentiaaleja usealla kanavalla voidaan päätellä missä ja milloin aivot aktivoituvat. Päänahan pinnalta mitattavan tavanomaisen elektroenkefalografian paikkaresoluutio ei kuitenkaan riitä, jos halutaan tarkastella mittakaavaltaan alle senttimetrin luokkaa olevia ilmiöitä. Paitsi perustutkimuksessa, tämä rajoitus on ongelmallinen myös epilepsiapotilaiden kohtaukset alullepanevan eli epileptogeenisen aivoalueen paikantamisessa. Käytännössä tämä ongelma ratkaistaan asettamalla potilaille elektrodeja kallon ja aivokuoren väliseen subduraalitilaan. Toimenpide tehdään erikoistuneissa yksiköissä epilepsian kirurgista hoitoa edeltävän tarkkailujakson aikana. Suoraan aivokuoren pinnalta mitattavia potentiaaleja on harvoin hyödynnetty perustutkimuksessa, eikä niiden käyttö kliinisessä tutkimuksessa ole tuonut juurikaan lisävalaistusta epilepsian syihin tai sen huonosti tunnettuihin mekanismeihin. Vaihesynkronian arvioiminen on uudehko menetelmä kahden dynaamisen systeemin välisen vuorovaikutuksen havaitsemiseksi niiden korreloituneiden vaiheiden avulla. Menetelmää käyttäen voidaan myös aivoperäisistä sähköisistä ja magneettisista signaaleista etsiä mitattujen alueiden välisiä toiminnallisia yhteyksiä. Analyysissä, joka tehdään erikseen kaikille kiinnostaville taajuuskaistoille, lasketaan kahden kapeakaistaisen signaalin vaihe-erojakaumasta vaihelukituskerroin ja tilastolliset merkittävyydet. Aivojen tiihiin asti tunnetun toiminnan kannalta analyysin rajoittuminen kapeille taajuuskaistoille on sekä etu että haitta: hermostolliset oskillaatiot ovat viime aikoina nousseet kiinnostuksen kohteeksi monissa yhteyksissä, mutta niiden yleisestä merkityksestä solutason mekanismeille tai korkeammille aivotoiminnoille ei olla yksimielisiä. On kuitenkin olemassa näyttöä siitä, että oskillaatioiden väliset vaihesuhteet ovat yksi aivokuoren käyttämä informaation esitystapa. Tässä diplomityössä olen tarkastellut kolmelle epilepsiapotilaalle tehtyjä kallonsisäisiä mittauksia. Tavoitteena on ollut ensin varmistaa pintamittauksia varten kehitetyn vaihesynkroniamenetelmiin toimivuus luonteeltaan erilaisissa mittauksissa, ja toiseksi arvioida sen soveltuvuutta epilepsiaan liittyvien hermoverkkotason ilmiöiden tutkimiseen. Epilepsiatutkimuksessa apuna käytetään mittauksia, joiden aikana potilas on epileptisiä kohtauksia hillitsevän lääkityksen alaisena. Raportti alkaa yleistasoisella ihmisaivojen rakenteen ja toiminnan esittelyllä, sisältäen työn ymmärtämisen kannalta oleelliset tiedot epilepsiasta. Sen jälkeen esitellään vaihesynkronian fysikaalinen tausta ja liitetään aivoista mitattavat signaalit siihen. Tämän jälkeen käydään läpi työn teossa käytetyt menetelmät; mittaukset, kuvankäsittely ja aallokesuodatus. Elektrodien paikannustulokset määritettiin yhdellä potilaalla yhdistämällä tietokonetomografialla saadut röntgenkuvat anatomisiin magneettiresonanssikuviin. Paikannustietojen avulla laskettuja elektrodien etäisyyksiä käytettiin hyväksi arvioitaessa tilavuusjohtumisen vaihesynkroniaan aiheuttamaa virhettä, jonka todettiin rajoittuvan muutaman senttimetrin etäisyydelle. Epileptisiä kohtauksia hillitseviin lääkkeen, bentsodiatsepiinin, todettiin nostavan oskillaatioiden amplitudia ja laskevan niiden välistä synkroniaa. Yleisen synkroniaa laskevan vaikutuksen lisäksi havaittiin suurimpien muutosten keskittyvän lähelle alueita, joiden kliinisissä tutkimuksissa oli todettu liittyvän epileptisten kohtausten syntyyn. Saatujen tulosten perusteella kliiniset jatkotutkimukset tässä työssä käytettyjä menetelmiä soveltaen ovat tarpeellisia. Tämä diplomityö on tehty Helsingin Yliopistollisen Keskussairaalan Biomag-laboratoriossa, joka on osa Suomen Akatemian nimeämää Helsingin aivotutkimuskeskus -huippuyksikköä

Nested synchrony - a novel cross-scale interaction among neuronal oscillations

Neuronal interactions form the basis for our brain function, and oscillations and synchrony are the principal candidates for mediating them in the cortical networks. Phase synchrony, where oscillatory neuronal ensembles directly synchronize their phases, enables precise integration between separated brain regions. However, it is unclear how neuronal interactions are dynamically coordinated in space and over time. Cross-scale effects have been proposed to be responsible for linking levels of processing hierarchy and to regulate neuronal dynamics. Most notably, nested oscillations, where the phase of a neuronal oscillation modulates the amplitude of a faster one, may locally integrate neuronal activities in distinct frequency bands. Yet, hierarchical control of inter-areal synchrony could provide a more comprehensive view to the dynamical structure of oscillatory interdependencies in the human brain. In this study, the notion of nested oscillations is extended to a cross-frequency and inter-areal model of oscillatory interactions. In this model, the phase of a slower oscillation modulates inter-areal synchrony in a higher frequency band. This would allow cross-scale integration of global interactions and, thus, offers a mechanism for binding distributed neuronal activities. We show that inter-areal phase synchrony can be modulated by the phase of a slower neuronal oscillation using magnetoencephalography (MEG). This effect is the most pronounced at frequencies below 35 Hz. Importantly, changes in oscillation amplitudes did not explain the findings. We expect that the novel cross-frequency interaction could offer new ways to understand the flexible but accurate dynamic organization of ongoing neuronal oscillations and synchrony.Peer reviewe

Graph properties of synchronized cortical networks during visual working memory maintenance

Oscillatory synchronization facilitates communication in neuronal networks and is intimately associated with human cognition. Neuronal activity in the human brain can be non-invasively imaged with magneto- (MEG) and electroencephalography (EEG), but the large-scale structure of synchronized cortical networks supporting cognitive processing has remained uncharacterized. We combined simultaneous MEG and EEG (MEEG) recordings with minimum-norm-estimate-based inverse modeling to investigate the structure of oscillatory phase synchronized networks that were active during visual working memory (VWM) maintenance. Inter-areal phase-synchrony was quantified as a function of time and frequency by single-trial phase-difference estimates of cortical patches covering the entire cortical surfaces. The resulting networks were characterized with a number of network metrics that were then compared between delta/theta- (3–6 Hz), alpha- (7–13 Hz), beta- (16–25 Hz), and gamma- (30–80 Hz) frequency bands. We found several salient differences between frequency bands. Alpha- and beta-band networks were more clustered and small-world like but had smaller global efficiency than the networks in the delta/theta and gamma bands. Alpha- and beta-band networks also had truncated-power-law degree distributions and high k-core numbers. The data converge on showing that during the VWM-retention period, human cortical alpha- and beta-band networks have a memory-load dependent, scale-free small-world structure with densely connected core-like structures. These data further show that synchronized dynamic networks underlying a specific cognitive state can exhibit distinct frequency-dependent network structures that could support distinct functional roles

Brain Responses to Letters and Speech Sounds and Their Correlations with Cognitive Skills Related to Reading in Children

Letter-speech sound (LSS) integration is crucial for initial stages of reading acquisition. However, the relationship between cortical organization for supporting LSS integration, including unimodal and multimodal processes, and reading skills in early readers remains unclear. In the present study, we measured brain responses to Finnish letters and speech sounds from 29 typically developing Finnish children in a child-friendly audiovisual integration experiment using magnetoencephalography. Brain source activations in response to auditory, visual and audiovisual stimuli as well as audiovisual integration response were correlated with reading skills and cognitive skills predictive of reading development after controlling for the effect of age. Regression analysis showed that from the brain measures, the auditory late response around 400 ms showed the largest association with phonological processing and rapid automatized naming abilities. In addition, audiovisual integration effect was most pronounced in the left and right temporoparietal regions and the activities in several of these temporoparietal regions correlated with reading and writing skills. Our findings indicated the important role of temporoparietal regions in the early phase of learning to read and their unique contribution to reading skills.peerReviewe

Very slow EEG fluctuations predict the dynamics of stimulus detection and oscillation amplitudes in humans

Our ability to perceive weak signals is correlated among consecutive trials and fluctuates slowly over time. Although this “streaking effect” has been known for decades, the underlying neural network phenomena have remained largely unidentified. We examined the dynamics of human behavioral performance and its correlation with infraslow (0.01–0.1 Hz) fluctuations in ongoing brain activity. Full-band electroencephalography revealed prominent infraslow fluctuations during the execution of a somatosensory detection task. Similar fluctuations were predominant also in the dynamics of behavioral performance. The subjects' ability to detect the sensory stimuli was strongly correlated with the phase, but not with the amplitude of the infraslow EEG fluctuations. These data thus reveal a direct electrophysiological correlate for the slow fluctuations in human psychophysical performance. We then examined the correlation between the phase of infraslow EEG fluctuations and the amplitude of 1–40 Hz neuronal oscillations in six frequency bands. Like the behavioral performance, the amplitudes in these frequency bands were robustly correlated with the phase of the infraslow fluctuations. These data hence suggest that the infraslow fluctuations reflect the excitability dynamics of cortical networks. We conclude that ongoing 0.01–0.1 Hz EEG fluctuations are prominent and functionally significant during execution of cognitive tasks

Neuronal synchrony reveals working memory networks and predicts individual memory capacity

Visual working memory (VWM) is used to maintain sensory information for cognitive operations, and its deficits are associated with several neuropsychological disorders. VWM is based on sustained neuronal activity in a complex cortical network of frontal, parietal, occipital, and temporal areas. The neuronal mechanisms that coordinate this distributed processing to sustain coherent mental images and the mechanisms that set the behavioral capacity limit have remained unknown. We mapped the anatomical and dynamic structures of network synchrony supporting VWM by using a neuro informatics approach and combined magnetoencephalography and electroencephalography. Interareal phase synchrony was sustained and stable during the VWM retention period among frontoparietal and visual areas in α- (10–13 Hz), β- (18–24 Hz), and γ- (30–40 Hz) frequency bands. Furthermore, synchrony was strengthened with increasing memory load among the frontoparietal regions known to underlie executive and attentional functions during memory maintenance. On the other hand, the subjects’ individual behavioral VWM capacity was predicted by synchrony in a network in which the intraparietal sulcus was the most central hub. These data suggest that interareal phase synchrony in the α-, β-, and γ-frequency bands among frontoparietal and visual regions could be a systems level mechanism for coordinating and regulating the maintenance of neuronal object representations in VWM

Epileptogenic neocortical networks are revealed by abnormal temporal dynamics in seizure-free subdural EEG

Long-term video electroencephalographic (EEG) recording is currently a routine procedure in the presurgical evaluation of localization-related epilepsies. Cortical epileptogenic zone is usually localized from ictal recordings with intracranial electrodes, causing a significant burden to patients and health care. Growing literature suggests that epileptogenic networks exhibit aberrant dynamics also during seizure-free periods. We examined if neocortical epileptogenic regions can be circumscribed by quantifying local long-range temporal (auto-)correlations (LRTC) with detrended fluctuation analysis of seizure-free ongoing subdural EEG activity in 4 frequency bands in 5 patients. We show here with subdural EEG recordings that the LRTC are abnormally strong near the seizure onset area. This effect was most salient in neocortical oscillations in the beta frequency band (14–30 Hz). Moreover, lorazepam, a widely used antiepileptic drug, exerted contrasting effects on LRTC (n = 2): lorazepam attenuated beta-band LRTC near the epileptic focus, whereas it strengthened LRTC in other cortical areas. Our findings demonstrate that interictal neuronal network activity near the focus of seizure onset has pathologically strong intrinsic temporal correlations. The observed effect by lorazepam on beta-band activity suggests that the antiepileptic mechanism of benzodiazepines may be related to the normalization of LRTC within the epileptic focus. We propose that this method may become a promising candidate for routine invasive and noninvasive presurgical localization of epileptic foci