Sampling Rate Effects on Resting State fMRI Metrics

Low image sampling rates used in resting state functional magnetic resonance imaging (rs-fMRI) may cause aliasing of the cardiorespiratory pulsations over the very low frequency (VLF) BOLD signal fluctuations which reflects to functional connectivity (FC). In this study, we examine the effect of sampling rate on currently used rs-fMRI FC metrics. Ultra-fast fMRI magnetic resonance encephalography (MREG) data, sampled with TR 0.1 s, was downsampled to different subsampled repetition times (sTR, range 0.3–3 s) for comparisons. Echo planar k-space sampling (TR 2.15 s) and interleaved slice collection schemes were also compared against the 3D single shot trajectory at 2.2 s sTR. The quantified connectivity metrics included stationary spatial, time, and frequency domains, as well as dynamic analyses. Time domain methods included analyses of seed-based functional connectivity, regional homogeneity (ReHo), coefficient of variation, and spatial domain group level probabilistic independent component analysis (ICA). In frequency domain analyses, we examined fractional and amplitude of low frequency fluctuations. Aliasing effects were spatially and spectrally analyzed by comparing VLF (0.01–0.1 Hz), respiratory (0.12–0.35 Hz) and cardiac power (0.9–1.3 Hz) FFT maps at different sTRs. Quasi-periodic pattern (QPP) of VLF events were analyzed for effects on dynamic FC methods. The results in conventional time and spatial domain analyses remained virtually unchanged by the different sampling rates. In frequency domain, the aliasing occurred mainly in higher sTR (1–2 s) where cardiac power aliases over respiratory power. The VLF power maps suffered minimally from increasing sTRs. Interleaved data reconstruction induced lower ReHo compared to 3D sampling (p < 0.001). Gradient recalled echo-planar imaging (EPI BOLD) data produced both better and worse metrics. In QPP analyses, the repeatability of the VLF pulse detection becomes linearly reduced with increasing sTR. In conclusion, the conventional resting state metrics (e.g., FC, ICA) were not markedly affected by different TRs (0.1–3 s). However, cardiorespiratory signals showed strongest aliasing in central brain regions in sTR 1–2 s. Pulsatile QPP and other dynamic analyses benefit linearly from short TR scanning

Nykyisten toimittajien suorituskyvyn mittaaminen

Tämä insinöörityö tehtiin suomalaiselle teknisen kaupan erikoisliikkeelle Etra Oy:lle, joka kuuluu Etola-yhtiöihin. Työn tavoitteena oli parantaa yrityksen nykyisten toimittajien suorituskyvyn mittaamista, kehittämällä helposti ymmärrettävä mittaristo toimittajien suorituskyvyn seurantaan. Tällä hetkellä toimeksiantoyrityksellä on muutamia erillisiä raportteja toimittajien suorituskyvystä. Tämä ei kuitenkaan anna kokonaisvaltaista kuvaa toimittajien suorituskyvystä. Tavoitteen saavuttamiseksi kartoitettiin ensin yrityksen nykytila toimittajien suorituskyvyn seurannassa ja selvitettiin yrityksen tämän hetkiset vahvuudet ja heikkoudet prosessissa. Tarvittava tieto tähän saatiin yrityksen sisäisestä dokumentaatiosta, toiminnanohjausjärjestelmästä, raportointityökaluista ja haastattelemalla. Nykytilan-analyysin jälkeen perehdyttiin alan kirjallisuuteen ja teoriaan tavarantoimittajien arvioinnin parhaista käytännöistä. Näin saatiin koottua käsitekehys parhaista käytännöistä, jonka avulla aloitettiin suunnittelemaan tavarantoimittajien suorituskyvyn mittaristoa yhdessä yrityksen henkilöstön kanssa. Mittariston suunnittelu tehtiin teemahaastatteluiden avulla. Haastatteluihin osallistuivat henkilöitä, jotka ovat läheisesti tekemisissä tavarantoimittajien kanssa, sekä heillä on vankka tietämys tavarantoimittajiin liittyvistä asioista. Lopputuloksena syntyi tasapainotettu toimittajien suorituskykymittaristo ja tämän toiminta testattiin esimerkki toimittajilla. Suorituskykymittaristoa voidaan käyttää toimittajien suorituskyvyn arviointiin, sekä ongelmakohtien tunnistamiseen toimittajienhallinnassa. Sen lisäksi se helpottaa yrityksen henkilöstöä toimittajien suorituskyvyn seurannassa. Näin voidaan parantaa toimittajien seurantaa ja tilaus-toimitusten laatua yhdessä toimittajien kanssa. Tämän lisäksi kirjoitettiin vielä toimenpidesuosituksia, jotka nousivat esille insinöörityön aikana. Toimenpidesuositukset perustuivat teoriaan, haastatteluihin, sekä omiin näkemyksiin.This thesis was carried out for a Finnish technology company Etra Oy which is part of the Etola Group. The aim of this study was to improve the measurement of the case company’s existing suppliers’ performance by developing a user-friendly supplier performance measurement system for monitoring supplier performance. Currently the case company measures the supplier performance with a few separate reports. These reports, however, do not provide an overall picture of supplier performance. To achieve the aim of this study, the case company’s current state of monitoring supplier performance was examined and the current strengths and weaknesses in the process was investigated. The information needed for this, was obtained from the case company’s internal documentation, enterprise resource planning system, reporting tools and interviews. After the current state analysis, the author explored current literature and theory of best practices of supplier evaluation. This led to creating a conceptual framework of best practices which allowed starting a design process to create a supplier performance scorecard with the case company’s employees. The scorecard was designed in theme interviews with the employees who are closely involved with suppliers and have solid knowledge of these matters. The outcome of this study was a balanced supplier performance measurement system. This was tested by using sample suppliers. The performance measurement system can be used to evaluate the performance of the suppliers, as well as to identify the problems in supplier management. In addition it facilitates the case company’s employees to monitor supplier performance. This improves the monitoring of suppliers and overall quality supply chain. In addition, recommendations were given for further action. The recommendations were based on the theory, interviews and the author’s own assessments

Graphical user interface for analyzing radiological data

Brain research is increasingly focusing on critically sampled multimodal data. Due to the complexity of the brain multiple measures are analyzed simultaneously to bring forth a more comprehensive picture of brain functions. Furthermore the data has markedly increased in size, which places new demands for analysis tools. This master’s thesis presents a MRI-compatible multimodal measurement arrangement, a Hepta-scan concept and a toolbox (Nifty) for analyzing the measurements. The concept measures brain (MREG), non-invasive blood pressure (NIBP), electroencephalography (EEG), near infrared spectroscopy (NIRS) and anesthesia data in synchrony. Nifty combines several existing and newly developed software to create a simple access point for all available tools. It includes a database which holds information of a large amount of data obtained in the multimodal measurements. This thesis presents the software and hardware parts of the Hepta-scan concept and explains the workflow in it. Finally the Nifty toolbox design is presented and the functionality of it explained.Aivotutkimus keskittyy entistä enemmän kriittisesti näytteistettyyn multimodaalisen dataan. Aivojen monimutkaisuus vaatii useiden mittareiden analysointia samanaikaisesti, jotta saadaan kattava kuva aivojen toiminnasta. Lisäksi aiempaa tarkempi kuvantaminen lisää datan määrää, mikä asettaa uusia vaatimuksia analyysityökaluille. Tämä diplomityö esittää MRI -yhteensopivan multimodaalisen mittausjärjestelmän, Hepta-scan konseptin ja työkalupaketin (Nifty) mittausten analysointiin. Konsepti mittaa aivoja (MREG), noninvasiivista verenpainetta (NIBP), aivosähkökäyrää (EEG), lähi-infrapunaspektroskopiaa (NIRS) ja anestesiadataa synkronoidusti. Nifty yhdistää useita olemassa olevia ja uusia kehitettyjä ohjelmia, jotka muodostavat yksinkertaisen käynnistyspisteen kaikille työkaluille. Se sisältää tietokantajärjestelmän, joka pitää yllä informaatiota multimodaalisista mittauksista. Tämä työ esittää ohjelmisto- ja laitteistopuolen Hepta-scan konseptista, ja selittää sen työnkulun. Lopuksi työkalupaketti, Niftyn rakenne esitetään, ja sen toiminnot selitetään

Rapid Prototyping of a Mobile SaaS Application

Rapidly developing a customizable mobile application and the related software as a service (SaaS) is challenging and rarely studied. Traditionally, SaaS solutions are mainly accessed using personal computers, but the mobile SaaS solutions are needed in the tourism sector, for example, where users are mobile. This paper presents a case study where the original need was to design a customizable mobile tourism guide service for use by several small tourism companies, and to assess its functionality in a field study. The result of applying the Vaadin 6 Java web framework and LAMP technologies was a robust mobile application SaaS prototype system that fulfilled the essential design needs in the eight field test cases. This study shows that the field testing of a mobile concept can be completed easier when using Vaadin Java web framework, as it provides support for cross-platform functionality and GUI design, and completes, for example, LAMP-based SaaS solution. However, results point it out that new digital navigation features were needed to develop or improved and mobile web approach causes some usability challenges especially in the compass based navigation and user tracking. This study provides an example of how to develop a SaaS-based mobile service prototyping environment, which is needed while field testing new B2B mobile services with various groups of stakeholders. Our case study analysis reveal that the Vaadin development environment facilitates the rapid prototyping for digital services in an affordable way. The overall contribution of this paper is predominantly for software engineers and web application developers

Increased very low frequency pulsations and decreased cardiorespiratory pulsations suggest altered brain clearance in narcolepsy

Abstract Background: Narcolepsy is a chronic neurological disease characterized by daytime sleep attacks, cataplexy, and fragmented sleep. The disease is hypothesized to arise from destruction or dysfunction of hypothalamic hypocretin-producing cells that innervate wake-promoting systems including the ascending arousal network (AAN), which regulates arousal via release of neurotransmitters like noradrenalin. Brain pulsations are thought to drive intracranial cerebrospinal fluid flow linked to brain metabolite transfer that sustains homeostasis. This flow increases in sleep and is suppressed by noradrenalin in the awake state. Here we tested the hypothesis that narcolepsy is associated with altered brain pulsations, and if these pulsations can differentiate narcolepsy type 1 from healthy controls. Methods: In this case-control study, 23 patients with narcolepsy type 1 (NT1) were imaged with ultrafast fMRI (MREG) along with 23 age- and sex-matched healthy controls (HC). The physiological brain pulsations were quantified as the frequency-wise signal variance. Clinical relevance of the pulsations was investigated with correlation and receiving operating characteristic analysis. Results: We find that variance and fractional variance in the very low frequency (MREGvlf) band are greater in NT1 compared to HC, while cardiac (MREGcard) and respiratory band variances are lower. Interestingly, these pulsations differences are prominent in the AAN region. We further find that fractional variance in MREGvlf shows promise as an effective bi-classification metric (AUC = 81.4%/78.5%), and that disease severity measured with narcolepsy severity score correlates with MREGcard variance (R = −0.48, p = 0.0249). Conclusions: We suggest that our novel results reflect impaired CSF dynamics that may be linked to altered glymphatic circulation in narcolepsy type 1

The variability of functional MRI brain signal increases in Alzheimer's disease at cardiorespiratory frequencies

Biomarkers sensitive to prodromal or early pathophysiological changes in Alzheimer's disease (AD) symptoms could improve disease detection and enable timely interventions. Changes in brain hemodynamics may be associated with the main clinical AD symptoms. To test this possibility, we measured the variability of blood oxygen level-dependent (BOLD) signal in individuals from three independent datasets (totaling 80 AD patients and 90 controls). We detected a replicable increase in brain BOLD signal variability in the AD populations, which constituted a robust biomarker for clearly differentiating AD cases from controls. Fast BOLD scans showed that the elevated BOLD signal variability in AD arises mainly from cardiovascular brain pulsations. Manifesting in abnormal cerebral perfusion and cerebrospinal fluid convection, present observation presents a mechanism explaining earlier observations of impaired glymphatic clearance associated with AD in humans.Peer reviewe

Infra-slow fluctuations in cortical potentials and respiration drive fast cortical EEG rhythms in sleeping and waking states

Objective: Infra-slow fluctuations (ISF, 0.008–0.1 Hz) characterize hemodynamic and electric potential signals of human brain. ISFs correlate with the amplitude dynamics of fast (>1 Hz) neuronal oscillations, and may arise from permeability fluctuations of the blood–brain barrier (BBB). It is unclear if physiological rhythms like respiration drive or track fast cortical oscillations, and the role of sleep in this coupling is unknown. Methods: We used high-density full-band electroencephalography (EEG) in healthy human volunteers (N = 21) to measure concurrently the ISFs, respiratory pulsations, and fast neuronal oscillations during periods of wakefulness and sleep, and to assess the strength and direction of their phase-amplitude coupling. Results: The phases of ISFs and respiration were both coupled with the amplitude of fast neuronal oscillations, with stronger ISF coupling being evident during sleep. Phases of ISF and respiration drove the amplitude dynamics of fast oscillations in sleeping and waking states, with different contributions. Conclusions: ISFs in slow cortical potentials and respiration together significantly determine the dynamics of fast cortical oscillations. Significance: We propose that these slow physiological phases play a significant role in coordinating cortical excitability, which is a fundamental aspect of brain function.Peer reviewe

Synchronous functional magnetic resonance eye imaging, video ophthalmoscopy, and eye surface imaging reveal the human brain and eye pulsation mechanisms

Abstract The eye possesses a paravascular solute transport pathway that is driven by physiological pulsations, resembling the brain glymphatic pathway. We developed synchronous multimodal imaging tools aimed at measuring the driving pulsations of the human eye, using an eye-tracking functional eye camera (FEC) compatible with magnetic resonance imaging (MRI) for measuring eye surface pulsations. Special optics enabled integration of the FEC with MRI-compatible video ophthalmoscopy (MRcVO) for simultaneous retinal imaging along with functional eye MRI imaging (fMREye) of the BOLD (blood oxygen level dependent) contrast. Upon optimizing the fMREye parameters, we measured the power of the physiological (vasomotor, respiratory, and cardiac) eye and brain pulsations by fast Fourier transform (FFT) power analysis. The human eye pulsated in all three physiological pulse bands, most prominently in the respiratory band. The FFT power means of physiological pulsation for two adjacent slices was significantly higher than in one-slice scans (RESP1 vs. RESP2; df = 5, p = 0.045). FEC and MRcVO confirmed the respiratory pulsations at the eye surface and retina. We conclude that in addition to the known cardiovascular pulsation, the human eye also has respiratory and vasomotor pulsation mechanisms, which are now amenable to study using non-invasive multimodal imaging of eye fluidics

Continuous blood pressure recordings simultaneously with functional brain imaging:studies of the glymphatic system

Abstract The lymph system is responsible for cleaning the tissues of metabolic waste products, soluble proteins and other harmful fluids etc. Lymph flow in the body is driven by body movements and muscle contractions. Moreover, it is indirectly dependent on the cardiovascular system, where the heart beat and blood pressure maintain force of pressure in lymphatic channels. Over the last few years, studies revealed that the brain contains the so-called glymphatic system, which is the counterpart of the systemic lymphatic system in the brain. Similarly, the flow in the glymphatic system is assumed to be mostly driven by physiological pulsations such as cardiovascular pulses. Thus, continuous measurement of blood pressure and heart function simultaneously with functional brain imaging is of great interest, particularly in studies of the glymphatic system. We present our MRI compatible optics based sensing system for continuous blood pressure measurement and show our current results on the effects of blood pressure variations on cerebral brain dynamics, with a focus on the glymphatic system. Blood pressure was measured simultaneously with near-infrared spectroscopy (NIRS) combined with an ultrafast functional brain imaging (fMRI) sequence magnetic resonance encephalography (MREG, 3D brain 10 Hz sampling rate)

Combined spatiotemporal ICA (stICA) for continuous and dynamic lag structure analysis of MREG data

Abstract This study investigated lag structure in the resting-state fMRI by applying a novel independent component (ICA) method to magnetic resonance encephalography (MREG) data. Briefly, the spatial ICA (sICA) was used for defining the frontal and back nodes of the default mode network (DMN), and the temporal ICA (tICA), which is enabled by the high temporal resolution of MREG (TR=100ms), was used to separate both neuronal and physiological components of these two spatial map regions. Subsequently, lag structure was investigated between the frontal (DMNvmpf) and posterior (DMNpcc) DMN nodes using both conventional method with all-time points and a sliding-window approach. A rigorous noise exclusion criterion was applied for tICs to remove physiological pulsations, motion and system artefacts. All the de-noised tICs were used to calculate the null-distributions both for expected lag variability over time and over subjects. Lag analysis was done for the three highest correlating denoised tICA pairs. Mean time lag of 0.6 s (± 0.5 std) and mean absolute correlation of 0.69 (± 0.08) between the highest correlating tICA pairs of DMN nodes was observed throughout the whole analyzed period. In dynamic 2 min window analysis, there was large variability over subjects as ranging between 1–10 sec. Directionality varied between these highly correlating sources an average 28.8% of the possible number of direction changes. The null models show highly consistent correlation and lag structure between DMN nodes both in continuous and dynamic analysis. The mean time lag of a null-model over time between all denoised DMN nodes was 0.0 s and, thus the probability of having either DMNpcc or DMNvmpf as a preceding component is near equal. All the lag values of highest correlating tICA pairs over subjects lie within the standard deviation range of a null-model in whole time window analysis, supporting the earlier findings that there is a consistent temporal lag structure across groups of individuals. However, in dynamic analysis, there are lag values exceeding the threshold of significance of a null-model meaning that there might be biologically meaningful variation in this measure. Taken together the variability in lag and the presence of high activity peaks during strong connectivity indicate that individual avalanches may play an important role in defining dynamic independence in resting state connectivity within networks