Dynamic imaging of coherent sources reveals different network connectivity underlying the generation and perpetuation of epileptic seizures

The concept of focal epilepsies includes a seizure origin in brain regions with hyper synchronous activity (epileptogenic zone and seizure onset zone) and a complex epileptic network of different brain areas involved in the generation, propagation, and modulation of seizures. The purpose of this work was to study functional and effective connectivity between regions involved in networks of epileptic seizures. The beginning and middle part of focal seizures from ictal surface EEG data were analyzed using dynamic imaging of coherent sources (DICS), an inverse solution in the frequency domain which describes neuronal networks and coherences of oscillatory brain activities. The information flow (effective connectivity) between coherent sources was investigated using the renormalized partial directed coherence (RPDC) method. In 8/11 patients, the first and second source of epileptic activity as found by DICS were concordant with the operative resection site; these patients became seizure free after epilepsy surgery. In the remaining 3 patients, the results of DICS / RPDC calculations and the resection site were discordant; these patients had a poorer post-operative outcome. The first sources as found by DICS were located predominantly in cortical structures; subsequent sources included some subcortical structures: thalamus, Nucl. Subthalamicus and cerebellum. DICS seems to be a powerful tool to define the seizure onset zone and the epileptic networks involved. Seizure generation seems to be related to the propagation of epileptic activity from the primary source in the seizure onset zone, and maintenance of seizures is attributed to the perpetuation of epileptic activity between nodes in the epileptic network. Despite of these promising results, this proof of principle study needs further confirmation prior to the use of the described methods in the clinical praxis

Multimodal alterations of directed connectivity profiles in patients with attention-deficit/hyperactivity disorders

Functional and effective connectivity measures for tracking brain region interactions that have been investigated using both electroencephalography (EEG) and magnetoencephalography (MEG) bringing up new insights into clinical research. However, the differences between these connectivity methods, especially at the source level, have not yet been systematically studied. The dynamic characterization of coherent sources and temporal partial directed coherence, as measures of functional and effective connectivity, were applied to multimodal resting EEG and MEG data obtained from 11 young patients (mean age 13.2 ± 1.5 years) with attention-deficit/hyperactivity disorder (ADHD) and age-matched healthy subjects. Additionally, machine-learning algorithms were applied to the extracted connectivity features to identify biomarkers differentiating the two groups. An altered thalamo-cortical connectivity profile was attested in patients with ADHD who showed solely information outflow from cortical regions in comparison to healthy controls who exhibited bidirectional interregional connectivity in alpha, beta, and gamma frequency bands. We achieved an accuracy of 98% by combining features from all five studied frequency bands. Our findings suggest that both types of connectivity as extracted from EEG or MEG are sensitive methods to investigate neuronal network features in neuropsychiatric disorders. The connectivity features investigated here can be further tested as biomarkers of ADHD

Frequency-specific network activity predicts bradykinesia severity in Parkinson's disease

Objective Bradykinesia has been associated with beta and gamma band interactions in the basal ganglia-thalamo-cortical circuit in Parkinson’s disease. In this present cross-sectional study, we aimed to search for neural networks with electroencephalography whose frequency-specific actions may predict bradykinesia. Methods Twenty Parkinsonian patients treated with bilateral subthalamic stimulation were first prescreened while we selected four levels of contralateral stimulation (0: OFF, 1–3: decreasing symptoms to ON state) individually, based on kinematics. In the screening period, we performed 64-channel electroencephalography measurements simultaneously with electromyography and motion detection during a resting state, finger tapping, hand grasping tasks, and pronation-supination of the arm, with the four levels of contralateral stimulation. We analyzed spectral power at the low (13–20 Hz) and high (21–30 Hz) beta frequency bands and low (31–60 Hz) and high (61–100 Hz) gamma frequency bands using the dynamic imaging of coherent sources. Structural equation modelling estimated causal relationships between the slope of changes in network beta and gamma activities and the slope of changes in bradykinesia measures. Results Activity in different subnetworks, including predominantly the primary motor and premotor cortex, the subthalamic nucleus predicted the slopes in amplitude and speed while switching between stimulation levels. These subnetwork dynamics on their preferred frequencies predicted distinct types and parameters of the movement only on the contralateral side. Discussion Concurrent subnetworks affected in bradykinesia and their activity changes in the different frequency bands are specific to the type and parameters of the movement; and the primary motor and premotor cortex are common nodes

The impact of MEG source reconstruction method on source-space connectivity estimation: A comparison between minimum-norm solution and beamforming.

Despite numerous important contributions, the investigation of brain connectivity with magnetoencephalography (MEG) still faces multiple challenges. One critical aspect of source-level connectivity, largely overlooked in the literature, is the putative effect of the choice of the inverse method on the subsequent cortico-cortical coupling analysis. We set out to investigate the impact of three inverse methods on source coherence detection using simulated MEG data. To this end, thousands of randomly located pairs of sources were created. Several parameters were manipulated, including inter- and intra-source correlation strength, source size and spatial configuration. The simulated pairs of sources were then used to generate sensor-level MEG measurements at varying signal-to-noise ratios (SNR). Next, the source level power and coherence maps were calculated using three methods (a) L2-Minimum-Norm Estimate (MNE), (b) Linearly Constrained Minimum Variance (LCMV) beamforming, and (c) Dynamic Imaging of Coherent Sources (DICS) beamforming. The performances of the methods were evaluated using Receiver Operating Characteristic (ROC) curves. The results indicate that beamformers perform better than MNE for coherence reconstructions if the interacting cortical sources consist of point-like sources. On the other hand, MNE provides better connectivity estimation than beamformers, if the interacting sources are simulated as extended cortical patches, where each patch consists of dipoles with identical time series (high intra-patch coherence). However, the performance of the beamformers for interacting patches improves substantially if each patch of active cortex is simulated with only partly coherent time series (partial intra-patch coherence). These results demonstrate that the choice of the inverse method impacts the results of MEG source-space coherence analysis, and that the optimal choice of the inverse solution depends on the spatial and synchronization profile of the interacting cortical sources. The insights revealed here can guide method selection and help improve data interpretation regarding MEG connectivity estimation

Untersuchung neuronaler Netzwerke bei West Syndrom mittels Quellenanalyse und partial directed coherence

West syndrome is a severe epileptic encephalopathy of infancy with a poor developmental outcome. This syndrome is associated with the pathognomonic EEG feature of hypsarrhythmia. The aim of the study was to describe neuronal networks underlying hypsarrhythmia using the source analysis method (dynamic imaging of coherent sources or DICS) which represents an inverse solution algorithm in the frequency domain. In order to investigate the interaction within the detected network, a renormalized partial directed coherence (RPDC) method was also applied as a measure of the directionality of information flow between the source signals

BrainmappingNeuronal Networks in Children with Continuous Spikes and Waves during Slow Sleep as revealed by DICS and RPDC

CSWS is an age-related epileptic encephalopathy consisting of the triad of seizures, neuropsychological impairment and a specific EEG-pattern. This EEG-pattern is characterized by spike-and-wave-discharges emphasized during non-REM sleep. Until now, little has been known about the pathophysiologic processes. So far research approaches on the underlying neuronal network have been based on techniques with a good spatial but poor temporal resolution like fMRI and FDG-PET. In this study the search for sources participating in the neuronal network of CSWS is done by processing EEG-data with high temporal resolution. This allows not only interferences on the location of the individual sources but also on the direction of information flow between them. DICS is applied to the data to solve the inverse problem in the frequency domain. Afterwards RPDC, based on Granger causality, is implemented to reveal effective connectivity between the sources. 12 patients suffering from CSWS without any proof for macroscopic cerebral pathologies in a T1-MRI were investigated at two points of time, before and after treatment. All results are compared to other studies on the neuronal network of CSWS, to knowledge about genesis of epileptic activity in general and to knowledge about the pathogenesis of related psychiatric syndromes. During the active phase of CSWS the thalamus represents the central hub of the neuronal network, and also the cerebellum and key nodes of the DMN contribute to it. Therefore the results are concordant to the ones of former studies and to assumptions on the genesis of epileptic activity. In addition, pathogenetic parallels are found to autism, ADHD and memory-impairment. After cessation of CSWS, the network consists of exclusively cortical sources. In addition to the SWI the mean absolute source power, the mean coherence strength and the mean RPDC strength could be revealed as reliable indicators for the severity of the encephalopathy

Neuronal networks of burst suppression EEG as revealed by source analysis and renormalized partial directed coherence

Burst-suppression (BS) is an electroencephalography (EEG) pattern consist-ing of alternative periods of slow waves of high amplitude (the burst) and periods of so called flat EEG (the suppression). It is generally associated with the reduced level of consciousness. The aim of this study was to reveal the neuronal network underlying both burst and suppression phases using a source analysis method: dynamic imaging of coherent sources (DICS) and to describe the effective connectivity between the identified sources using renormalized partial directed coherence (RPDC). DICS was applied separately to the EEG segments of 13 neonates with burst and suppression EEG pattern. Power spectrum analyses were performed to identify the predominant frequencies. The brain area with the strongest power in the analyzed frequency (1-4 Hz) range was defined as the reference region. DICS was used to compute the coher-ence between this reference region and the entire brain. RPDC was used to describe the in-formational flow between the described sources. Delta activity during burst phases was associated with sources in the thalamus and brainstem as well as bilateral sources in the cortical regions mainly frontal and parietal, whereas suppression phases were associated with coherent sources only in the cor-tical regions. Results of the RPDC analyses showed an ascending informational flow from the brainstem towards the thalamus and from the thalamus to cortical regions, which was absent during suppression phases. Especially those brain regions were affected, that are im-portant for cognitive processing. The results of this study strengthen the assumption that there is a specific periodicity of neural activity and that thalamocortical deafferentiation is an essential feature of BS. Thus a burst can be understood as short, repetitive recovery of cortical neural dynamics. The described deafferentation may play a role in the poor neuro-logical outcome in these encephalopathies

Aivovamman vaikutus aivokuoren rytmiseen toimintaan

Mild traumatic brain injuries (mTBI) are common, and while most patients recover well, there is a minority of patients suffering from prolonged symptoms lasting over three months. Pathological processes provoke low-frequency (0.5 - 7 Hz) oscillatory brain activity, measurable with electroencephalography (EEG) and magnetoencephalography (MEG). After mTBI, low frequency activity (LFA) is hypothesized to arise from cortical neurons suffering from de-afferentation after traumatic axonal injury. The natural evolution and prognostic value of low-frequency activity (LFA) measured with MEG, however, is not yet firmly established and reliable biomarkers for cognitive complaints after mTBI are lacking. The aim of this thesis was to examine the occurrence and natural evolution of low frequency activity (LFA) after mild traumatic brain injury (mTBI), and to assess its prognostic value in predicting those with prolonged symptoms. Additionally, we wanted to examine the effect of mTBI to brain oscillatory activity during cognitive tasks and find indicators for altered processing. The existence of LFA in healthy subjects might, however, hamper its’ diagnostic value. Therefore, in Study I we created a reference database of resting-state oscillatory brain activity and observed LFA in only 1,4% of healthy subjects’ MEG recordings. The Study II assessed the occurrence and evolution of LFA in resting-state MEG recordings of mTBI patients. At a single-subject level, 7/26 patients presented aberrant 4–7 Hz (theta) band activity; 3/7 patients with abnormal theta activity were without any detectable lesions in MRI. Of the twelve patients with follow-up measurements, five showed abnormal theta activity in the first recording, but only two in the second measurement, implying the importance of early measurements in clinical settings. The presence of LFA was not, however, correlated with the prevalence of self-reported symptoms. The Study III concentrated on the modulation of oscillatory activity during cognitive tasks, Paced Auditory Serial Addition Test (PASAT) and a vigilance test. Attenuation of cortical activity at alpha band (8 – 14 Hz) during PASAT compared with rest was stronger in patients than in controls (p≤0.05, corrected). Furthermore, the patients presented significant attenuation of oscillatory activity also in the left superior frontal gyrus and right prefrontal cortices which was not detected in controls. Spectral peak amplitudes of areal mean oscillatory activity at the alpha band were negatively correlated with the patients’ neuropsychological performance (p<0.01, uncorrected). Areal alpha frequency modulation during PASAT compared with rest was altered in patients: While the alpha peak frequency increased occipitally and remained stable parietally in controls, it was stable occipitally and decreased parietally in mTBI patients (p=0.012). According to our studies, LFA, especially theta-band oscillatory activity can provide an early objective sign of brain dysfunction after mTBI, and cortical oscillatory activity during a demanding cognitive task (PASAT) is altered after mTBI. Our observations suggest that both aberrant theta-band activity and the altered alpha activity during cognitive tasks may offer clinically relevant indicators of changes in neural processing after mTBI.Aivovamma on aivojen rakenteellinen tai toiminnallinen vaurio, joka syntyy kun päähän kohdistuu voimakas ulkoinen energia, tai äkillinen kiihtyvyys-hidastuvuusvoima (kuten äkkipysäyksissä). Aivovamma aiheuttaa tajunnanhäiriön tai muun neurologisen oireiston, joka voi olla ohimenevä tai pysyvä. Lievät aivovammat ovat yleisiä, ja vaikka suurin osa loukkaantuneista toipuu hyvin, kärsii pieni vähemmistö pitkäaikaisista jälkioireista. Lievä aivovamma ei aina aiheuta todennettavia diagnostisia muutoksia, eikä siitä toipumista ennustavia tekijöitä juuri tunneta. Aivosairaudet, myös aivovammat, muuttavat aivojen sähköistä toimintaa ja aiheuttavat matalataajuista rytmistä toimintaa (0.5 – 7 Hz), joka voidaan tunnistaa aivosähkökäyrän (EEG) tai magnetoenkefalografian (MEG) avulla. Aivovamman jälkeisen hidasaaltotoiminnan ajatellaan johtuvan hermosolujen viejähaarakkeiden vaurion aiheuttamasta hermosolujen poikkeavasta sähköisestä toiminnasta. Koska lievän- keskivaikean aivovamman todentaminen voi olla vaikeaa, tutkimme MEG:n mahdollisuuksia diagnostiikan apuvälineenä. Hidasaaltotoiminnan esiintyminen terveillä henkilöillä voisi vähentää löydöksen diagnostista merkitystä vamman jälkeen. Sen vuoksi selvitimme poikkeavan hidasaaltotoiminnan esiintyvyyttä 139:llä terveellä koehenkilöllä ja havaitsimme poikkeavia hidasaaltoja vain kahdella (1.4%). Lievän aivovamman saaneista 26:sta potilaasta hidasaaltotoimintaa (4-7 Hz) esiintyi 7:llä (27%). Kolmella heistä ei pystytty havaitsemaan poikkeavia muutoksia aivojen rakenteellisessa magneettikuvauksessa. Seurantamittaus kuuden kuukauden kuluttua saatiin tehtyä 12 potilaalle. Heistä viidellä (42%) havaittiin hidasaaltotoimintaa ensimmäisessä mittauksessa, mutta seurantamittauksessa vain kahdella. Aikainen mittausajankohta vamman jälkeen vaikuttaa siten parantavan tutkimuksen herkkyyttä. Alkuvaiheen hidasaaltotoiminta ei vaikuttanut ennustavan mahdollisen jälkioireiston kehittymistä, mutta pieni otoskoko vaikeuttaa löydöksen arvioimista. Tarkkaavaisuuden ja muistin häiriöt ovat tavallisimpia oireita aivovamman jälkeen. Tästä syystä tarkastelimme myös muisti- ja tarkkaavaisuustehtävien vaikutusta potilaiden aivojen rytmiseen toimintaan ja mahdollisten muutosten yhteyttä havaittuihin oireisiin. Havaitsimme haastavan muistitehtävän aikana potilaiden rytmisen toiminnan vaimentuvan lepotilanteeseen verrattuna voimakkaammin ja useammilla alueilla ns. alfa-taajuuskaistalla (8-14 Hz) kuin kontrollihenkilöiden. Rytmisen toiminnan voimakkaampi vaimentuminen potilailla oli yhteydessä parempaan neuropsykologiseen testisuoriutumiseen. Myös alueelliset huipputaajuudet käyttäytyivät eri tavoin kontrollihenkilöillä ja potilailla. Kontrollihenkilöillä tehtävän aikana takaraivolohkon alfa-taajuus nousi päälakilohkon taajuuden pysyessä vakaana verrattuna lepotilaan. Potilailla tehtävän aikana alfataajuus käyttäytyi päinvastoin; takaraivolohkon alfa-taajuus säilyi ennallaan, mutta päälakilohkon huipputaajuus laski verrattuna lepotilaan. Tutkimuksemme perusteella pian vamman jälkeen todettava hidasaaltotoiminta voi osoittaa objektiivisesti aivotoiminnan häiriön. Potilailla aivojen rytminen toiminta vaativan kognitiivisen tehtävän aikana erosi kontrolleista. Havaintojemme perusteella sekä hidasaaltotoiminnan esiintyminen, että rytmisen toiminnan muuntuminen kognitiivisten tehtävien aikana voivat jatkossa tarjota kliinisesti merkityksellisiä välineitä arvioitaessa tiedonkäsittelyn tehottomuutta lievän aivovamman jälkeen. Lisätutkimukset laajemmalla aineistolla havaintojemme vahvistamiseksi ovat tarpeellisia aivovamman diagnostiikan kehittämiseksi

Study of cortical rhythmic activity and connectivity with magnetoencephalography

Intracranial recordings in animals and neuroimaging studies on humans have indicated that oscillatory activity and its modulations may play a fundamental role in large-scale neural information processing. Furthermore, rhythmic interactions between cortical areas have been detected across a variety of tasks with electroencephalography (EEG) and magnetoencephalography (MEG). This kind of coupling has been proposed to be a key mechanism through which information is integrated across segregated areas. So far, rhythmic interactions have been analyzed primarily at the EEG/MEG sensor level, without explicit knowledge of cortical areas involved. In this thesis work we developed new methods that can be used to image oscillatory activity and coherence at the cortical level with MEG. Dynamic Imaging of Coherent Sources (DICS) enables localization of interacting areas both using external reference signals and directly from the MEG data. When the interacting areas have been determined it is possible to use additional measures beyond coherence to further quantify interactions within the networks. DICS was originally designed for study of continuous data; its further development into event-related DICS (erDICS) adds the possibility to image modulations of rhythmic activity that are locked to stimulus or movement timing. Furthermore, permutation testing incorporated into erDICS allows the evaluation of the statistical significance of the results. Analysis of simulated and real data showed that DICS and erDICS yield accurate localization and quantification of oscillatory activity and coherence. Comparison of DICS to other methods of localizing oscillatory activity revealed that it is equally accurate and that it can better separate the activity originating from two nearby areas. We applied DICS to two datasets, recorded from groups of subjects while they performed slow finger movements and when they were reading continuously. In both cases, we were able to systematically identify interacting cortico-cortical networks and, using phase coupling and causality measures, to quantify the manner in which the nodes within these networks influenced each other. Furthermore, we compared the identified reading network to results reported in neurophysiological and hemodynamic activation studies. In addition to areas typically detected in activation studies of reading the network included areas that are normally found in language production rather than perception tasks, indicating more extensive networking of neural systems than usually observed in activation studies

Social perception and cognition : processing of gestures, postures and facial expressions in the human brain

Humans are a social species with the internal capability to process social information from other humans. To understand others behavior and to react accordingly, it is necessary to infer their internal states, emotions and aims, which are conveyed by subtle nonverbal bodily cues such as postures, gestures, and facial expressions. This thesis investigates the brain functions underlying the processing of such social information. Studies I and II of this thesis explore the neural basis of perceiving pain from another person s facial expressions by means of functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG). In Study I, observing another s facial expression of pain activated the affective pain system (previously associated with self-experienced pain) in accordance with the intensity of the observed expression. The strength of the response in anterior insula was also linked to the observer s empathic abilities. The cortical processing of facial pain expressions advanced from the visual to temporal-lobe areas at similar latencies (around 300 500 ms) to those previously shown for emotional expressions such as fear or disgust. Study III shows that perceiving a yawning face is associated with middle and posterior STS activity, and the contagiousness of a yawn correlates negatively with amygdalar activity. Study IV explored the brain correlates of interpreting social interaction between two members of the same species, in this case human and canine. Observing interaction engaged brain activity in very similar manner for both species. Moreover, the body and object sensitive brain areas of dog experts differentiated interaction from noninteraction in both humans and dogs whereas in the control subjects, similar differentiation occurred only for humans. Finally, Study V shows the engagement of the brain area associated with biological motion when exposed to the sounds produced by a single human being walking. However, more complex pattern of activation, with the walking sounds of several persons, suggests that as the social situation becomes more complex so does the brain response. Taken together, these studies demonstrate the roles of distinct cortical and subcortical brain regions in the perception and sharing of others internal states via facial and bodily gestures, and the connection of brain responses to behavioral attributes.Ihminen on sosiaalinen laji, ja meillä on myös kanssaihmistemme välittämän sosiaalisen informaation käsittelyyn erikoistuneita aivomekanismeja. Ymmärtääksemme muiden käyttäytymistä ja vastataksemme siihen tarkoituksenmukaisesti, meidän täytyy ymmärtää muiden ihmisten hienovaraisen kehonkielen kuten eleiden tai kasvonilmeiden välittämiä tunnetiloja ja päämääriä. Tässä väitöskirjatyössä tutkittiin tällaisen sosiaalisen informaation käsittelyä aivoissa. Väitöskirja tarkastelee aivotoimintaa toisten ihmisten tunnetilojen havainnoinnissa kasvojen ja kehon eleiden kautta sekä näiden aivovasteiden yhteyttä käyttäytymiseen. Osatöissä I ja II tarkasteltiin toisen ihmisen kipukokemuksen havaitsemista kasvonilmeistä toiminnallisen magneettikuvauksen (fMRI) ja magnetoenkefalografian (MEG) avulla. Tutkimuksissa selvisi, että toisen ihmisen kivun kasvonilmettä katsottaessa ne aivoalueet, jotka osallistuvat myös itse koettuun kipuun, aktivoituivat sitä voimakkaammin, mitä voimakkaampaa kipua kasvonilmeen arveltiin välittävän. Aivoaktivaatio oli myös yhteydessä katselijan empatiakykyihin. Kipuilmeiden käsittely eteni näköaivokuorelta ohimolohkon alueille samassa ajassa kuin on aikaisemmin osoitettu pelon ja inhon ilmeille (noin 300 500 ms). Osatyössä III osoitettiin, että myös haukottelevien kasvojen havaitseminen aktivoi ohimolohkon alueita. Tulokset osoittivat myös, että mitä heikompaa mantelitumakkeen aktivaatio oli havainnon aikana, sitä enemmän koehenkilö tunsi tarvetta haukotella itse katsellessaan haukottelevia kasvoja. Osatyössä IV tutkittiin vuorovaikutuksen havaitsemista kahden ihmisen tai kahden koiran sosiaalisista eleistä. Kummankin lajin vuorovaikutuseleiden katselu aktivoi aivoja samankaltaisesti, mutta koirien elekieleen perehtyneiden asiantuntijoiden aivovasteet kehon ja muiden havaintokohteiden käsittelyyn erikoistuneilla alueilla erottelivat koirien vuorovaikutustilanteet ei-vuorovaikutteisista tilanteista samaan tapaan kuin ihmisten väliset vastaavat tilanteet. Sen sijaan kontrollikoehenkilöiden aivovasteet erottelivat samalla tavalla vain ihmisten vuorovaikutuksen. Osatyössä V osoitettiin, että biologisen liikkeen havaitsemiseen erikoistunut aivoalue aktivoituu yhden ihmisen kävelyääniä kuunnellessa, mutta aktivaatiokuvio leviää kuunneltaessa usean ihmisen kävelyääniä, mikä viittaa aivovasteiden monimutkaistumiseen riippuen sosiaalisesta ympäristöstä