Cortical beta burst dynamics are altered in Parkinson's disease but normalized by deep brain stimulation

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.Peer reviewe

Search for the ac Josephson effect in superfluid 3He

Experiments testing for the existence of the ac Josephson effect in superfluid 3He, analogous to phenomena observed in superconducting microbridges, have been performed. Small holes were employed as the weak link between two reservoirs filled with 3He; several different orifice geometries were tried. Simple model calculations suggest that steps in the flow characteristics should be observable with our resolution when an ac pressure modulation is applied across the weak link. We found that such effects do not exist for the parameter values used in our experiments.Peer reviewe

TOTI-hankkeen loppuraportti

TOTI-hankkeessa tavoitteena oli saada tutkittua tietoa, jota voidaan käyttää optimaalisten toimistotilojen suunnittelemiseen. Monitieteellinen tutkijaryhmä kehitti toimivia kokonaisratkaisuja yhdessä rakennusalan ammattilaisten ja toimitilojen käyttäjien kanssa. Erityisesti tarkasteltiin avotilatoimistojen oloja ja siellä akustiikkaa, lämpöoloja, yksityisyyttä, sisustusta, työtehtävien vaatimuksia ja organisaation tehtäviä.1

Signal Space Separation Beamformer

We have combined Signal Space Separation and beamformers (SSS beamformer). The SSS beamformer was tested by simulation in the presence of simulated brain noise. The SSS beamformer performs at least as well as the conventional beamformer, provided that the expansion order is sufficiently high. For beamformer outputs which depend on power or power difference normalized by the projected noise, the spatial resolution of the SSS beamformer is significantly better than that of the conventional beamformers if the sources are deeper, and about the same as that of the conventional beamformer when the sources are superficial. For beamformer outputs which depend on the ratio of powers, the spatial resolutions of the SSS and conventional beamfomers are the same. The sensor noise covariance matrix in the SSS basis is non-diagonal. The SSS beamformers with diagonalized noise covariance matrix exhibit better spatial resolution than that with non-diagonal noise covariance matrix. The SSS beamformers are computationally more efficient than the conventional beamformers

Comparison of beamformer implementations for MEG source localization

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.Peer reviewe

Virtual MEG Helmet : Computer Simulation of an Approach to Neuromagnetic Field Sampling

Head movements during an MEG recording are commonly considered an obstacle. In this computer simulation study, we introduce an approach, the virtual MEG helmet (VMH), which employs the head movements for data quality improvement. With a VMH, a denser MEG helmet is constructed by adding new sensors corresponding to different head positions. Based on the Shannon's theory of communication, we calculated the total information as a figure of merit for comparing the actual 306-sensor Elekta Neuromag helmet to several types of the VMH. As source models, we used simulated randomly distributed source current (RDSC), simulated auditory and somatosensory evoked fields. Using the RDSC model with the simulation of 360 recorded events, the total information (bits/sample) was 989 for the most informative single head position and up to 1272 for the VMH (addition of 28.6%). Using simulated AEFs, the additional contribution of a VMH was 12.6% and using simulated SEF only 1.1%. For the distributed and bilateral sources, a VMH can provide a more informative sampling of the neuromagnetic field during the same recording time than measuring the MEG from one head position. VMH can, in some situations, improve source localization of the neuromagnetic fields related to the normal and pathological brain activity. This should be investigated further employing real MEG recordings.Peer reviewe

Liikennealan kansallinen kasvuohjelma 2018 - 2022

Liikennealan kansallisen kasvuohjelman 2018–2022 lähtökohtana on edistää toimialan yritysvetoista kehitystä, kasvua ja kansainvälistymistä. Liikenne toimii Suomen kansantalouden merkittävänä ajurina sisältäen n. 35 000 yritystä ja työllistäen n. 200 000 henkilöä. Samaan aikaan liikenteen markkinoilla toimivien yritysten liikevaihto on arviolta yli 60 mrd. euroa. Liikenneala on merkittävien teknologisten, taloudellisten ja yhteiskunnallisten murrosten keskellä ja sen uudistuminen pohjautuu pitkälti digitalisaation mukanaan tuomiin mahdollisuuksiin. Liikennealan globaalit markkinat tarjoavat valtavan kasvupotentiaalin, esimerkiksi MaaSin (liikenne palveluna) markkinoiden ennustetaan kasvavan yli 1 000 miljardiin dollariin vuoteen 2030 menness

SQUIDs in biomagnetism : A roadmap towards improved healthcare

This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 686865.Peer reviewedPublisher PD

Sensitivity of a 29-Channel MEG Source Montage

In this paper, we study the performance of a source montage corresponding to 29 brain regions reconstructed from whole-head magnetoencephalographic (MEG) recordings, with the aim of facilitating the review of MEG data containing epileptiform discharges. Test data were obtained by superposing simulated signals from 100-nAm dipolar sources to a resting state MEG recording from a healthy subject. Simulated sources were placed systematically to different cortical locations for defining the optimal regularization for the source montage reconstruction and for assessing the detectability of the source activity from the 29-channel MEG source montage. The signal-to-noise ratio (SNR), computed for each source from the sensor-level and source-montage signals, was used as the evaluation parameter. Without regularization, the SNR from the simulated sources was larger in the sensor-level signals than in the source montage reconstructions. Setting the regularization to 2% increased the source montage SNR to the same level as the sensor-level SNR, improving the detectability of the simulated events from the source montage reconstruction. Sources producing a SNR of at least 15 dB were visually detectable from the source-montage signals. Such sources are located closer than about 75 mm from the MEG sensors, in practice covering all areas in the grey matter. The 29-channel source montage creates more focal signals compared to the sensor space and can significantly shorten the detection time of epileptiform MEG discharges for focus localization