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Previously, schizophrenia is found to be related to the variability of the functional magnetic resonance imaging (fMRI) signal in the white matter. However, evidence about the relationship between genetic vulnerabilities and physiological fluctuation in the brain is lacking. We investigated whether familial risk for psychosis (FR) and polygenic risk score for schizophrenia (PRS) are linked with physiological fluctuation in fMRI data. We used data from the Oulu Brain and Mind study (n = 140−149, aged 20−24 years) that is a substudy of the Northern Finland Birth Cohort 1986. The participants underwent a resting-state fMRI scan. Coefficient of variation (CV) of blood oxygen level dependent (BOLD) signal (CVBOLD) was used as a proxy of physiological fluctuation in the brain. Familial risk was defined to be present if at least one parent had been diagnosed with psychosis previously. PRS was computed based on the results of the prior GWAS by the Schizophrenia Working Group. FR or PRS were not associated with CVBOLD in cerebrospinal fluid, white matter, or grey matter. The findings did not provide evidence for the previous suggestions that genetic vulnerabilities for schizophrenia become apparent in alterations of the variation of the BOLD signal in the brain.

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.

Narcolepsy is a chronic neurological disease characterized by dysfunction of the hypocretin system in brain causing disruption in the wake-promoting system. In addition to sleep attacks and cataplexy, patients with narcolepsy commonly report cognitive symptoms while objective deficits in sustained attention and executive function have been observed. Prior resting-state functional magnetic resonance imaging (fMRI) studies in narcolepsy have reported decreased inter/intranetwork connectivity regarding the default mode network (DMN). Recently developed fast fMRI data acquisition allows more precise detection of brain signal propagation with a novel dynamic lag analysis. In this study, we used fast fMRI data to analyze dynamics of inter resting-state network (RSN) information signaling between narcolepsy type 1 patients (NT1, n = 23) and age- and sex-matched healthy controls (HC, n = 23). We investigated dynamic connectivity properties between positive and negative peaks and, furthermore, their anticorrelative (pos-neg) counterparts. The lag distributions were significantly (P < 0.005, familywise error rate corrected) altered in 24 RSN pairs in NT1. The DMN was involved in 83% of the altered RSN pairs. We conclude that narcolepsy type 1 is characterized with delayed and monotonic inter-RSN information flow especially involving anticorrelations, which are known to be characteristic behavior of the DMN regarding neurocognition.

Background: Physiological brain pulsations have been shown to play a critical role in maintaining interstitial homeostasis in the glymphatic brain clearance mechanism. We investigated whether psychotic symptomatology is related to the physiological variation of the human brain using fMRI. Methods: The participants (N = 277) were from the Northern Finland Birth Cohort 1986. Psychotic symptoms were evaluated with the Positive Symptoms Scale of the Structured Interview for Prodromal Syndromes (SIPS). We used the coefficient of variation of BOLD signal (CVBOLD) as a proxy for physiological brain pulsatility. The CVBOLD-analyses were controlled for motion, age, sex, and educational level. The results were also compared with fMRI and voxel-based morphometry (VBM) meta-analyses of schizophrenia patients (data from the Brainmap database). Results: At the global level, participants with psychotic-like symptoms had higher CVBOLD in cerebrospinal fluid (CSF) and white matter (WM), when compared to participants with no psychotic symptoms. Voxel-wise analyses revealed that CVBOLD was increased, especially in periventricular white matter, basal ganglia, cerebellum and parts of the cortical structures. Those brain regions, which included alterations of physiological fluctuation in symptomatic psychosis risk, overlapped <6% with the regions that were found to be affected in the meta-analyses of previous fMRI and VBM studies in schizophrenia patients. Motion did not vary as a function of SIPS. Conclusions: Psychotic-like symptoms were associated with elevated CVBOLD in a variety of brain regions. The CVBOLD findings may produce new information about cerebral physiological fluctuations that have been out of reach in previous fMRI and VBM studies.

Objective: We conducted a multimodal coordinate-based meta-analysis (CBMA) to investigate structural and functional brain alterations in first-degree relatives of schizophrenia patients (FRs). Methods: We conducted a systematic literature search from electronic databases to find studies that examined differences between FRs and healthy controls using whole-brain functional magnetic resonance imaging (fMRI) or voxel-based morphometry (VBM). A CBMA of 30 fMRI (754 FRs; 959 controls) and 11 VBM (885 FRs; 775 controls) datasets were conducted using the anisotropic effect-size version of signed differential mapping. Further, we conducted separate meta-analyses about functional alterations in different cognitive tasks: social cognition, executive functioning, working memory, and inhibitory control. Results: FRs showed higher fMRI activation in the right frontal gyrus during cognitive tasks than healthy controls. In VBM studies, there were no differences in gray matter density between FRs and healthy controls. Furthermore, multi-modal meta-analysis obtained no differences between FRs and healthy controls. By utilizing the BrainMap database, we showed that the brain region which showed functional alterations in FRs (i) overlapped only slightly with the brain regions that were affected in the meta-analysis of schizophrenia patients and (ii) correlated positively with the brain regions that exhibited increased activity during cognitive tasks in healthy individuals. Conclusions: Based on this meta-analysis, FRs may exhibit only minor functional alterations in the brain during cognitive tasks, and the alterations are much more restricted and only slightly overlapping with the regions that are affected in schizophrenia patients. The familial risk did not relate to structural alterations in the gray matter.

The amount of functional MRI (fMRI) data processed in research is growing, yet no practice or protocol to store them in a lossy format exists. Many researchers are struggling with limited storage space, and speed of common processing tools are often bound by storage speed. In this work, we present a lossy compression framework for fMRI data with user adjustable trade-off between compression ratio and root mean squared error (RMSE). Our goal is to demonstrate the usability of on-the-fly lossy compression for fMRI data. On one hand, the storage footprint and processing speeds both benefit from higher data compression rates achieved with lossy compression. On the other hand, data quality for functional analysis remains effectively the same. With this short demonstration we encourage the research community to develop a lossy data standard for fMRI data.

Alterations induced by prenatal exposure to nicotine have been observed in experimental (rodent) studies. While numerous developmental outcomes have been associated with prenatal exposure to maternal cigarette smoking (PEMCS) in humans, the possible relation with brain structure is less clear. Here we sought to elucidate the relation between PEMCS and structural properties of human corpus callosum in adolescence and early adulthood in a total of 1,747 youth. We deployed three community-based cohorts of 446 (age 25–27 years, 46% exposed), 934 (age 12–18 years, 47% exposed) and 367 individuals (age 18–21 years, 9% exposed). A mega-analysis revealed lower mean diffusivity in the callosal segments of exposed males. We speculate that prenatal exposure to maternal cigarette smoking disrupts the early programming of callosal structure and increases the relative portion of small-diameter fibres.

Objective: Epilepsy causes measurable irregularity over a range of brain signal frequencies, as well as autonomic nervous system functions that modulate heart and respiratory rate variability. Imaging dynamic neuronal signals utilizing simultaneously acquired ultra-fast 10 Hz magnetic resonance encephalography (MREG), direct current electroencephalography (DC-EEG), and near-infrared spectroscopy (NIRS) can provide a more comprehensive picture of human brain function. Spectral entropy (SE) is a nonlinear method to summarize signal power irregularity over measured frequencies. SE was used as a joint measure to study whether spectral signal irregularity over a range of brain signal frequencies based on synchronous multimodal brain signals could provide new insights in the neural underpinnings of epileptiform activity. Methods: Ten patients with focal drug-resistant epilepsy (DRE) and ten healthy controls (HC) were scanned with 10 Hz MREG sequence in combination with EEG, NIRS (measuring oxygenated, deoxygenated, and total hemoglobin: HbO, Hb, and HbT, respectively), and cardiorespiratory signals. After pre-processing, voxelwise SEMREG was estimated from MREG data. Different neurophysiological and physiological subfrequency band signals were further estimated from MREG, DC-EEG, and NIRS: fullband (0–5 Hz, FB), near FB (0.08–5 Hz, NFB), brain pulsations in very-low (0.009–0.08 Hz, VLFP), respiratory (0.12–0.4 Hz, RFP), and cardiac (0.7–1.6 Hz, CFP) frequency bands. Global dynamic fluctuations in MREG and NIRS were analyzed in windows of 2 min with 50% overlap. Results: Right thalamus, cingulate gyrus, inferior frontal gyrus, and frontal pole showed significantly higher SEMREG in DRE patients compared to HC. In DRE patients, SE of cortical Hb was significantly reduced in FB (p = .045), NFB (p = .017), and CFP (p = .038), while both HbO and HbT were significantly reduced in RFP (p = .038, p = .045, respectively). Dynamic SE of HbT was reduced in DRE patients in RF

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 co

The brain is cleaned from waste by glymphatic clearance serving a similar purpose as the lymphatic system in the rest of the body. Impairment of the glymphatic brain clearance precedes protein accumulation and reduced cognitive function in Alzheimer’s disease (AD). Cardiovascular pulsations are a primary driving force of the glymphatic brain clearance. We developed a method to quantify cardiovascular pulse propagation in the human brain with magnetic resonance encephalography (MREG). We extended a standard optical flow estimation method to three spatial dimensions, with a multi-resolution processing scheme. We added application-specific criteria for discarding inaccurate results. With the proposed method, it is now possible to estimate the propagation of cardiovascular pulse wavefronts from the whole brain MREG data sampled at 10 Hz. The results show that on average the cardiovascular pulse propagates from major arteries via cerebral spinal fluid spaces into all tissue compartments in the brain. We present an example, that cardiovascular pulsations are significantly altered in AD: coefficient of variation and sample entropy of the pulse propagation speed in the lateral ventricles change in AD. These changes are in line with the theory of glymphatic clearance impairment in AD. The proposed non-invasive method can assess a performance indicator related to the glymphatic clearance in the human brain.

Resting-state functional magnetic resonance imaging (rsfMRI) is a translational imaging method with great potential in several neurobiologic applications. Most preclinical rsfMRI studies are performed in anesthetized animals, but the confounding effects of anesthesia on the measured functional connectivity (FC) are poorly understood. Therefore, we measured FC under six commonly used anesthesia protocols and compared the findings with data obtained from awake rats. The results demonstrated that each anesthesia protocol uniquely modulated FC. Connectivity patterns obtained under propofol and urethane anesthesia were most similar to that observed in awake rats. FC patterns in the α-chloralose and isoflurane-medetomidine combination groups had moderate to good correspondence with that in the awake group. The FC patterns in the isoflurane and medetomidine groups differed most from that in the awake rats. These results can be directly exploited in rsfMRI study designs to improve the data quality, comparability, and interpretation.

Schizophrenia and other psychotic disorders are severe and disabling mental disorders that break out during early adulthood, often when a person is in his/her early 20s. Furthermore, functional decline in many cognitive areas, including the ability to communicate in social interactions and impaired facial expression recognition, is typical to patients with schizophrenia. Understanding the risk factors of psychosis is essential as these disorders may be more amenable to treatment in their early stages. However, recognition of those at the highest risk of psychosis is challenging as no definitive biomarkers are available. Functional MRI is a promising tool that can potentially identify neural signals relating to the individual’s risk of psychosis onset. Psychotic disorders are etiologically heterogeneous disorders — both environmental and genetic factors have been linked to the onset of psychotic disorders. The most influential risk factor for a psychotic disorder is familial risk with genetic loading. The present study examines whether familial risk of psychosis (FR), the polygenic risk score for schizophrenia (PRS) and early adversity associate with brain response to faces. We used fMRI to measure blood oxygen level dependent (BOLD) response to faces. Our study showed that FR associated with deviant prefrontal cortex BOLD responses. In addition, we detected that interregional BOLD signal and grey matter volume varied as a function of PRS; the lowest functional and structural covariance was detected in individuals with high PRS. We also detected that early adversities associated with brain response to faces and that this association varied as a function of glucocorticoid receptor gene expression. Our findings indicate that the above risk factors of psychosis associate with brain response to faces., Tiivistelmä Skitsofrenia ja muut psykoosisairaudet ovat vakavia mielenterveyden häiriöitä, jotka puhkeavat usein nuorella aikuisiällä. Eräs tyypillinen piirre psykoosisairauksille on vaikeus tunnistaa muiden ihmisten kasvonilmeitä. Psykoosisairauksien riskitekijöiden ymmärtäminen on tärkeää, sillä hoito tehoaa parhaiten sairastumisen alkuvaiheessa. Suurimmassa psykoosivaarassa olevien henkilöiden tunnistaminen on kuitenkin haastavaa, sillä luotettavia tautiin liittyviä biomarkkereita ei ole saatavilla. Toiminnallinen magneettikuvaus (fMRI) on lupaava työkalu, jolla saattaa olla tulevaisuudessa käyttöarvoa psykoosivaaraan liittyvien aivomuutosten tunnistamisessa. Etiologialtaan psyykoosisairaudet ovat heterogeenisiä: sekä ympäristö että perinnölliset tekijät vaikuttavat yksilön sairastumisriskiin. Voimakkain riskitekijä on suvullinen psykoosialttius. Tässä osajulkaisuväitöskirjassa tutkitaan suvullisen psykoosialttiuden, skitsofrenian polygeenisen riskipisteen (PRS) sekä varhaisten vastoinkäymisten yhteyttä aivojen kasvonilmeitä tulkitsevaan järjestelmään. Tutkimuksessa on hyödynnetty fMRI-kuvausta kasvonilmestimuluksen aikana. Tutkimuksessamme suvullinen psykoosialttius oli yhteydessä etuotsalohkon fMRI-signaalimuutoksiin. Tämän lisäksi havaitsimme, että kasvonilmejärjestelmän fMRI-signaalin ja harmaan aineen kovarianssi oli yhteydessä PRS:ään: matalin aivoalueiden välinen korrelaatio havaittiin henkilöillä, joiden PRS oli korkea. Havaitsimme myös, että varhaiset vastoinkäymiset ovat yhteydessä kasvonilmeiden aikaansaamiin aivovasteisiin. Tämä assosiaatio oli myös yhteydessä glukokortikoidireseptorin geenin ilmentymiseen. Väitöskirjan löydökset viittaavat siihen, että edellä mainitut psykoosin riskitekijät ovat yhteydessä kasvonilmeitä tulkitsevaan järjestelmään.

Chemotherapy aided by opening of the blood-brain barrier with intra-arterial infusion of hyperosmolar mannitol improves the outcome in primary central nervous system lymphoma. Proper opening of the blood-brain barrier is crucial for the treatment, yet there are no means available for its real-time monitoring. The intact blood-brain barrier maintains a mV-level electrical potential difference between blood and brain tissue, giving rise to a measurable electrical signal at the scalp. Therefore, we used direct-current electroencephalography (DC-EEG) to characterize the spatiotemporal behavior of scalp-recorded slow electrical signals during blood-brain barrier opening. Nine anesthetized patients receiving chemotherapy were monitored continuously during 47 blood-brain barrier openings induced by carotid or vertebral artery mannitol infusion. Left or right carotid artery mannitol infusion generated a strongly lateralized DC-EEG response that began with a 2 min negative shift of up to 2000 μV followed by a positive shift lasting up to 20 min above the infused carotid artery territory, whereas contralateral responses were of opposite polarity. Vertebral artery mannitol infusion gave rise to a minimally lateralized and more uniformly distributed slow negative response with a posterior-frontal gradient. Simultaneously performed near-infrared spectroscopy detected a multiphasic response beginning with mannitol-bolus induced dilution of blood and ending in a prolonged increase in the oxy/deoxyhemoglobin ratio. The pronounced DC-EEG shifts are readily accounted for by opening and sealing of the blood-brain barrier. These data show that DC-EEG is a promising real-time monitoring tool for blood-brain barrier disruption augmented drug delivery.

In brain studies, the function of the cerebrospinal fluid (CSF) awakes growing interest, particularly related to studies of the glymphatic system in the brain, which is connected with the complex system of lymphatic vessels responsible for cleaning the tissues. The CSF is a clear, colourless liquid including water (H2O) approximately with a concentration of 99 %. In addition, it contains electrolytes, amino acids, glucose, and other small molecules found in plasma. The CSF acts as a cushion behind the skull, providing basic mechanical as well as immunological protection to the brain. Disturbances of the CSF circulation have been linked to several brain related medical disorders, such as dementia. Our goal is to develop an in vivo method for the non-invasive measurement of cerebral blood flow and CSF circulation by exploiting optical and capacitive sensing techniques simultaneously. We introduce a prototype of a wearable probe that is aimed to be used for long-term brain monitoring purposes, especially focusing on studies of the glymphatic system. In this method, changes in cerebral blood flow, particularly oxy- and deoxyhaemoglobin, are measured simultaneously and analysed with the response gathered by the capacitive sensor in order to distinct the dynamics of the CSF circulation behind the skull. Presented prototype probe is tested by measuring liquid flows inside phantoms mimicking the CSF circulation.

Studies with magnetoencephalography (MEG) are still quite rarely combined simultaneously with methods that can provide a metabolic dimension to MEG investigations. In addition, continuous blood pressure measurements which comply with MEG compatibility requirements are lacking. For instance, by combining methods reflecting neurovascular status one could obtain more information on low frequency fluctuations that have recently gained increasing interest as a mediator of functional connectivity within brain networks. This paper presents a multimodal brain imaging setup, capable to non-invasively and continuously measure cerebral hemodynamic, cardiorespiratory and blood pressure oscillations simultaneously with MEG. In the setup, all methods apart from MEG rely on the use of fibre optics. In particular, we present a method for measuring of blood pressure and cardiorespiratory oscillations continuously with MEG. The potential of this type of multimodal setup for brain research is demonstrated by our preliminary studies on human, showing effects of mild hypercapnia, gathered simultaneously with the presented modalities.

Resting-state fMRI results in neurodegenerative diseases have been somewhat conflicting. This may be due to complex partial volume effects of CSF in BOLD signal in patients with brain atrophy. To encounter this problem, we used a coefficient of variation (CV) map to highlight artifacts in the data, followed by analysis of gray matter voxels in order to minimize brain volume effects between groups. The effects of these measures were compared to whole brain ICA dual regression results in Alzheimer’s disease (AD) and behavioral variant frontotemporal dementia (bvFTD). 23 AD patients, 21 bvFTD patients and 25 healthy controls were included. The quality of the data was controlled by CV mapping. For detecting functional connectivity (FC) differences whole brain ICA (wbICA) and also segmented gray matter ICA (gmICA) followed by dual regression were conducted, both of which were performed both before and after data quality control. Decreased FC was detected in posterior DMN in the AD group and in the Salience network in the bvFTD group after combining CV quality control with gmICA. Before CV quality control, the decreased connectivity finding was not detectable in gmICA in neither of the groups. Same finding recurred when exclusion was based on randomization. The subjects excluded due to artifacts noticed in the CV maps had significantly lower temporal signal-to-noise ratio than the included subjects. Data quality measure CV is an effective tool in detecting artifacts from resting state analysis. CV reflects temporal dispersion of the BOLD signal stability and may thus be most helpful for spatial ICA, which has a blind spot in spatially correlating widespread artifacts. CV mapping in conjunction with gmICA yields results suiting previous findings both in AD and bvFTD.

Brain disorders such as epilepsy, dementia and other mental illnesses induce increasing costs on health care systems with aging populations. The most effective treatment of these disorders would be either prevention or intervention of the disorder before irreversible damage develops. However, despite the increased interest in different brain diseases, many of them are still detected too late. One reason for this is the lack of appropriate functional imaging modality that can critically sample the targeted physiological phenomenon. Furthermore, it has been shown that one imaging modality is not enough to cover brain functionality properly; a multimodal approach is required. The main goal of this thesis was to validate near-infrared spectroscopy (NIRS) for brain measurement and to integrate it into a multimodal neuroimaging setup that can critically sample basic human physiological phenomena. A novel key element was the combined use of NIRS with ultra-fast magnetic resonance encephalography (MREG), electroencephalography (EEG), continuous non-invasive blood pressure and anesthesia monitoring as a synchronous system. This unique multimodal neuroimaging set-up with a new functional magnetic resonance imaging sequence, MREG, can sample human brain physiology at 10 Hz sampling rate without cardiorespiratory aliasing. The implemented setup was successfully used in scanning multiple patient and control populations. With the help of critical sampling rate, non-stationarity between the measured signals reflecting brain pulsations could be detected. Combined NIRS and EEG showed the capability to monitor therapeutic opening of the blood-brain barrier during treatment of central nervous system lymphoma for the first time in humans. Furthermore, our multimodal neuroimaging setup enabled the mapping of the recently described brain avalanches and glymphatic pulsation mechanisms of the brain. In conclusion, the ultra-fast multimodal laboratory with integrated NIRS offers no, Tiivistelmä Aivosairaudet kuten epilepsia, dementia ja muut mielenterveyden häiriöt aiheuttavat kasvavissa määrin kuluja ikääntyvien ihmisten terveydenhuollossa. Näiden tautien tehokkain hoitokeino olisi joko ennaltaehkäisy tai varhainen havaitseminen ennen peruuttamattomien kudosvaurioiden kehittymistä. Lisääntyneestä kiinnostuksesta huolimatta monet aivosairaudet havaitaan edelleen liian myöhään. Osasyy tähän on sopivan toiminnallisen kuvausmenetelmän puuttuminen, jolla voitaisiin kuvata haluttu fysiologinen ilmiö riittävän nopeasti. Onkin osoitettu, ettei yksittäinen kuvausmenetelmä riitä aivojen toiminnan riittävän tarkkaan ymmärtämiseen, vaan siihen tarvitaan eri menetelmien yhdistämistä. Tämän väitöskirjatutkimuksen päätarkoituksena oli arvioida lähi-infrapunaspektroskopian (NIRS) soveltuvuutta aivojen toiminnan mittaamisessa sekä integroida se osaksi multimodaalista neurokuvantamisjärjestelmää. Uutena elementtinä NIRS:iä käytettiin yhdessä ultranopean magneettiresonanssienkefalogrammin (MREG), aivosähkökäyrän (EEG), jatkuva-aikaisen kajoamattoman verenpaineen mittauksen ja anestesiamonitoroinnin kanssa samanaikaisesti, ajallisesti synkronoituna. Yhdessä uuden toiminnallisen magneettikuvaussekvenssin, MREG:n, kanssa tällä ainutlaatuisella multimodaalisella neurokuvantamisjärjestelmällä voidaan kuvata ihmisen aivojen perusfysiologiaa 10 Hz näytteistysnopeudella ilman sydämen sykkeen ja hengityksen laskostumista. Toteutetulla multimodaalisella mittausjärjestelmällä tehtiin useita onnistuneita kuvauksia eri potilasryhmillä ja terveillä koehenkilöillä. Kriittisen näytteistämisen ansiosta voitiin havaita epästationaarisuutta aivojen pulsaatioita heijastelevien signaalien välillä. NIRS:n ja EEG:n samanaikainen mittaaminen mahdollisti ensimmäistä kertaa ihmisen veriaivoesteen aukeamisen monitoroinnin keskushermostolymfoomapotilaiden hoidossa. Lisäksi multimodaalinen neurokuvantamisjärjestelmä mahdollisti hiljattain havaittujen aivojen vyöryjen (engl. avalanches) ja g

Brain activity fluctuations occur in multiple spatial and temporal scales. Functional magnetic resonance imaging (fMRI) has shown that infra slow fluctuations (ISF) of blood oxygen level-dependent signal (BOLD) are organized into well-defined areas called resting state networks (RSN). ISFs have also been detected in full-band EEG (fbEEG) data and in recent years, many have combined these two modalities to enable more accurate measurements of brain fluctuations. In simultaneous EEG-fMRI measurements the ISFs of BOLD signal have been found to be correlated with amplitude envelopes of faster electrophysiological data, suggesting the same underlying neuronal dynamics. Also direct correlations have been found in task related studies but not previously in resting state studies. Understanding the relation between EEG and BOLD signal in resting state might prove beneficial in the research of baseline activity fluctuations of the brain. Functional connectivity (FC) of the RSNs has been found to vary in different tasks and in some diseases, but also in resting state in healthy people. Despite numerous studies, no clear cause for these variations has yet been found. To research these open questions we performed simultaneous fbEEG-fMRI studies. The measurements from both modalities were analyzed with independent component analysis to improve the comparability of these results. Correlation analysis revealed that the EEG ISFs correlate with BOLD signal both temporally and spatially. These correlations showed spatiotemporal variability that was related to the strength of RSN functional connectivity. These results indicate that the ISFs of EEG and BOLD reflect a common source of fluctuations. The understanding of the correlations between ISFs in EEG and fMRI BOLD signals gives basic information of brain dynamics and of the variables that affect it. A better understanding of the background of brain activity helps in the development of more effective treatments for various n, Tiivistelmä Aivojen toiminta vaihtelee monissa avaruudellisissa ja ajallisissa mittakaavoissa. Toiminnallisissa magneettikuvauksissa (TMK) on havaittu, että veren happipitoisuudesta riippuvan (engl. BOLD) signaalin erittäin hitaat vaihtelut ovat järjestäytyneet hyvin määriteltyihin alueisiin, joita kutsutaan lepotilahermoverkostoiksi. Erittäin hitaita vaihteluita on havaittu myös täysikaistaisesta aivosähkökäyrästä (fbEEG). Viime vuosina nämä kaksi menetelmää on usein yhdistetty tarkemman mittaustuloksen aikaansaamiseksi. Samanaikaisissa EEG-TMK-mittauksissa BOLD signaalin erittäin hitaiden vaihteluiden on huomattu korreloivan nopeampien elektrofysiologisten värähtelyjen amplitudien verhokäyrien kanssa, mikä viittaa samaan perustana olevaan neuraaliseen dynamiikkaan. Myös suoria korrelaatioita on löydetty tehtäviin liittyvissä tutkimuksissa, mutta ei aiemmin lepotilatutkimuksissa. Lepotilan EEG:n ja BOLD-signaalin suhteen ymmärrys voi osoittautua hyödylliseksi aivojen perustilan aktiivisuuden vaihteluiden tutkimisessa. Hermoverkostojen toiminnallisen liittyvyyden on todettu huojuvan tietyissä tehtävissä ja joissain sairauksissa, mutta myös lepotilassa terveillä henkilöillä. Runsaasta tutkimuksesta huolimatta ei liittyvyyden huojunnalle ole vielä löytynyt selkeää aiheuttajaa. Näiden avoimien kysymysten tutkimiseksi suoritimme yhdenaikaisia fbEEG-TMK-mittauksia. Kummankin modaliteetin mittaustuloksia analysoitiin itsenäisten komponenttien analyysillä tulosten vertailtavuuden parantamiseksi. Korrelaatioanalyysit osoittivat, että EEG:n erittäin hitaat vaihtelut korreloivat ajallisesti ja avaruudellisesti TMK:n BOLD-signaalin kanssa. Näissä korrelaatioissa esiintyi sekä paikkaan että aikaan liittyvää huojuntaa, joka oli yhteydessä lepotilahermoverkostojen toiminnallisen liittyvyyden vahvuuteen. Nämä tulokset viittaavat siihen, että samat tekijät tuottavat EEG:n ja TMK:n BOLD-signaalien hitaat vaihtelut. EEG:n ja TMK:n signaalien erittäin hitaiden vaihteluiden välisen kor

Frontotemporal lobar degeneration (FTLD) is the second most common neurodegenerative disease leading to early-onset dementia with an estimated worldwide prevalence of 10 to 30 cases per 100000 individuals in the age group of 46 to 65 years. Behavioral variant frontotemporal dementia (bvFTD) is the most common FTLD subtype. It is characterized by a progressive deterioration of behavior and personality as well as executive dysfunction. In Finland, almost 50 % of familial FTLD cases are attributable to the C9ORF72 mutation. bvFTD is associated with a characteristic pattern of brain atrophy detectable in structural MRI. However, these changes are typically not visible in the early stages of the disease. Resting-state functional MRI (RS-fMRI) is being increasingly used to evaluate changes in functional connectivity within neuronal networks in the brain but only a few RS-fMRI investigations of bvFTD patients have been published with inconsistent results. The object of this thesis was to investigate functional connectivity changes detected in the salience (SLN) and default mode networks (DMN) in bvFTD. Another aim was to clarify the role of other cognitive resting-state networks in this disease. A cohort of 26 bvFTD patients was studied, with 8 of these patients carrying the C9ORF72 expansion. Connectivity changes were detected in multiple clinically relevant cognitive networks. Decreased functional connectivity was observed in the SLN, which is associated with guiding of behavior. Increased activity was present in the DMN and the dorsal attention network (DAN). In C9ORF72 associated bvFTD, there was an abnormal linkage detected between the DMN and the thalamus. Currently, fMRI is generally used as a research tool and in a group setting. Different study methods have been used in the literature and also in the studies of this thesis, the analysis procedures differed to some extent. The variety of analysis methods may explain the heterogeneity in fMRI findings in bv, Tiivistelmä Otsa-ohimolohkorappeuma (Frontotemporal lobar degeneration, FTLD) on toiseksi yleisin etenevä dementiaan johtava sairaus, joka ilmaantuu usein jo työikäisenä. Otsalohkodementia on otsa-ohimolohkorappeuman yleisin alamuoto, jonka oireisto painottuu persoonan ja käyttäytymisen muutoksiin sekä toiminnan ohjauksen ongelmiin. Suomessa C9ORF72-toistojaksomutaatio selittää lähes 50 % perinnöllisistä otsa-ohimolohkorappeumista. Aivojen rakenteellisella magneettikuvauksella (MK) voidaan havaita rakenteellisia muutoksia, jotka ilmaantuvat kuitenkin vasta taudin edettyä vaikeampaan vaiheeseen. Aivojen lepotilan toiminnallinen magneettikuvaus (TMK) mahdollistaa aivojen hermoverkkojen toiminnan eli konnektiviteetin kartoituksen. Aiemmin TMK:a on tutkittu esim. Alzheimerin taudissa. Otsalohkodementiassa TMK:sta on julkaistu ainoastaan yksittäisiä tutkimuksia ja tulokset ovat olleet osin ristiriitaisia. Väitöskirjatutkimuksen tarkoituksena on ollut selvittää valve-lepotilan hermoverkossa ja olennaisen tunnistavassa hermoverkossa tapahtuvia muutoksia otsalohkodementiaa sairastavilla potilailla. Toisena tavoitteena on ollut tutkia muissa kognitiivisissa hermoverkoissa tapahtuvia muutoksia. Otsalohkodementiaa sairastaville potilaille (n= 26) sekä ikä- ja sukupuolivakioiduille kontrolleille on tehty kliininen tutkimus ja rakenteellinen sekä toiminnallinen aivojen magneettikuvaus. Kahdeksalla potilaalla todettiin C9ORF72-toistojaksomutaatio. Useiden kognitiivisten hermoverkkojen toiminnassa havaittiin muutoksia, jotka korreloivat potilaiden kliinisiin oireisiin. Alentunutta konnektiviteettia todettiin olennaisen tunnistavassa hermoverkossa, joka osallistuu käyttäytymisen säätelyyn. Lisääntynyttä konnektiviteettia esiintyi valve-lepotilan hermoverkossa ja tarkkaavaisuus hermoverkossa. Potilailla, joilla on C9ORF72-mutaatio, havaittiin epänormaali yhteys valve-lepotilan hermoverkon ja talamuksen välillä. TMK:ta käytetään tällä hetkellä lähinnä tutkimustyökaluna. Analyysityöka

Neuropsychiatric illnesses usually become overtly manifest in adolescence and early adulthood. A critical long-term aim is to be able to prevent the development of such illnesses, which requires instruments to identify subjects at high risk of illness and to offer them effective interventions. There is an indisputable need for more sophisticated methods to enable more precise detection of adolescents and young adults who are at high risk of developing psychosis. Abnormal function in brain networks has been reported in people with schizophrenia and other psychotic disorders. Similar abnormalities have been found also in people at risk for developing psychosis, but it is not known whether this applies also to spontaneous resting state activity in young people with a familial risk for psychosis. We conducted resting-state functional MRI (R-fMRI) in 72 (29 male) young adults with a history of psychosis in one or both parents (FR) but without psychosis themselves, and 72 (29 male) similarly healthy control subjects without familial risk for psychosis. Both groups in the Oulu Brain and Mind study were drawn from the Northern Finland Birth Cohort 1986. All volunteers were 20–25 years old. Parental psychosis was established using the Care Register for Health Care. R-fMRI data was pre-processed using independent component analysis (ICA). A dual regression technique was used to detect between-group differences with p < 0.05 threshold corrected for multiple comparisons at voxel level. FR subjects demonstrated significantly decreased activity compared to control subjects in the default mode network and in the central executive network and increased activity in the cerebellum. The findings clarify previously controversial literature on the subject. The finding suggests that abnormal activity in these brain networks in rest may be associated with increased vulnerability to psychosis. The findings maybe helpful in developing more precise methods for detecting young peo, Tiivistelmä Psykoottisiin häiriöihin sairastutaan yleensä nuoruudessa tai varhaisaikuisuudessa. Psykoositutkimuksen tavoitteena on löytää uusia menetelmiä, joiden avulla kyettäisiin tunnistamaan suurimmassa psykoosiriskissä olevat nuoret, jotta heille voitaisiin tarjota sairautta ennaltaehkäiseviä hoitokeinoja. Skitsofreniaan ja muihin psykoottisiin häiriöihin sairastuneilla on havaittu aivotoiminnan poikkeavuuksia. Samankaltaisia aivotoiminnan poikkeavuuksia on havaittu myös nuorilla, jotka ovat vaarassa sairastua psykoosiin. Toistaiseksi on ollut epäselvää, onko psykoosiin sairastuneiden henkilöiden lapsilla aivohermoverkkojen toiminnan poikkeavuuksia lepotilassa. Suoritimme aivojen lepotilan MRI-tutkimuksen (R-fMRI) 72:lle (29 miestä) nuorelle aikuiselle, joiden jompikumpi vanhempi oli sairastunut psykoosin sekä 72:lle (29 miestä) nuorelle aikuiselle, joiden vanhemmat eivät olleet sairastaneet psykoosia. Molemmat tutkimusryhmät tässä Oulu Brain and Mind -tutkimuksessa olivat Pohjois-Suomen 1986 syntymäkohortin jäseniä. Tutkittavat olivat 20–25 vuoden iässä. Lepotilan toiminnallinen magneettikuvaus suoritettiin 1.5 Teslan Siemensin magneettikuvantamislaitteella. Tutkimuskohteiksi valittiin lepotilan toiminnallinen aivohermoverkko, toiminnan ohjauksesta vastaava aivohermoverkko ja pikkuaivot. Kuvantamisdataan sovellettiin itsenäisten komponenttien analyysia aivohermoverkkojen määrittämistä varten. Ryhmien välisen eron havaitsemiseen käytettiin ei-parametristä permutaatiotestiä, joka kynnystettiin tilastollisesti merkitsevään tasoon (p < 0.05). Lepotilan oletushermoverkossa ja toiminnanohjauksesta vastaavassa aivohermoverkoissa havaittiin vähäisempää aktiivisuutta ja pikkuaivoissa kohonnutta aktiivisuutta perinnöllisessä psykoosiriskissä olevilla nuorilla aikuisilla verrattuna verrokkeihin. Tutkimustulokset selkeyttivät aiempaa ristiriitaista kirjallisuutta tutkimusaiheesta. Tutkimuksessa havaittujen aivoalueiden poikkeava toiminta lepotilassa voi liittyä kohonne

The concept of resting state functional magnetic resonance imaging (fMRI) is built onto an original finding in 1995 that brain hemispheres present synchronous signal fluctuations with distinct patterns. fMRI measurements rely on blood oxygenation changes that indirectly mirror neural activity. Therefore, the origin of functional connectivity patterns, resting state networks (RSNs), has been a widely debated research question and numerous contributing factors have been identified. According to current understanding the fluctuations reflect maintenance of the system integrity in addition to spontaneous thought and action processes in the resting state. A popular method to study the functional connectivity in resting state fMRI is spatial independent component analysis (ICA) that decomposes signal sources into statistically independent components. The dichotomy of functional specialization versus functional integration has a correspondence in fMRI studies where RSNs play the integrative viewpoint of brain function. Although canonical large-scale RSNs are broadly distributed they also express modularity that can be accomplished by ICA with a high number of estimated components. The characteristics of high ICA dimensionality are broadly investigated in the thesis. An enduring issue in resting state research has been the confounding noise sources like motion and cardiorespiratory processes which may hamper the analysis. In this thesis the ability of ICA to separate these noise sources from the default mode network, a major RSN, is studied. Additionally, the suitability of ICA for full frequency spectrum analysis, a relatively rare setting in biosignal analysis, is investigated. The results of the thesis support the viewpoint of ICA as a robust analysis method for functional connectivity analysis. Cardiorespiratory and motion induced noise did not confound the functional connectivity analyses with ICA. High dimensional ICA provided better signal source separation, Tiivistelmä Konsepti lepotilan tutkimisesta toiminnallisella magneettikuvauksella (engl. functional magnetic resonance imaging, fMRI) on rakentunut vuonna 1995 tehdylle löydökselle aivopuoliskojen välillä synkronisesta signaalivaihtelusta. Mittaukset perustuvat veren hapetuksen muutoksiin, jotka epäsuorasti heijastelevat hermostollista toimintaa. Tämän takia toiminnallisen kytkennällisyyden muodot, lepotilaverkostot, ovat olleet laajasti väitelty tutkimusaihe ja monia verkostoihin vaikuttavia tekijöitä onkin tunnistettu. Nykykäsityksen mukaan signaalivaihtelut lepotilassa heijastelevat järjestelmän yhtenäisyyden ylläpitoa spontaanin ajattelun ja toiminnan lisäksi. Suosittu menetelmä toiminnallisen kytkennällisyyden tutkimiseen lepotilan fMRI:ssä on spatiaalinen itsenäisten komponenttien analyysi (engl. independent component analysis, ICA), joka hajottaa signaalilähteet tilastollisesti itsenäisiin komponentteihin. Aivotoiminnan mallintamisessa kahtiajaolla toiminnalliseen erikoistumiseen ja toiminnalliseen integraatioon on vastaavuus fMRI-tutkimukseen, jossa lepotilaverkostot vastaavat toiminnallisen integraation näkökulmasta. Vaikka kanoniset lepotilaverkostot ovat laaja-alaisia, ne ovat toisaalta modulaarisia, jota voidaan tutkia tutkimalla korkean komponenttimäärän ICA-hajotelmaa. Korkea- dimensioisen ICA-hajotelman ominaisuuksia tutkitaan laajasti tässä väitöskirjassa. Kestoaihe lepotilatutkimuksessa on ollut analyysiä hankaloittavien kohinalähteiden kuten liikkeen ja kardiorespiratoristen prosessien vaikutus. Väitöskirjassa tutkitaan ICA:n kykyä erotella kohinalähteitä ’default mode’ -verkostosta, joka on merkittävin lepotilaverkosto. Lisäksi tutkitaan ICA:n soveltuvuutta täyden taajuuskaistan analysointiin, joka on verrattain harvinaista biosignaalien analyysissä. Väitöskirjan tulokset tukevat näkemystä ICA:n suorituskyvystä toiminnallisen kytkennällisyyden analyysissä. Kardiorespiratorinen ja liikkeestä lähtöisin oleva kohina ei häirinnyt merkittävästi ICA-tul

Functional communication between brain regions is likely to play a key role in complex cognitive processes that require continuous integration of information across different regions of the brain. This makes the studying of functional connectivity in the human brain of high importance. It also provides new insights into the hierarchical organization of the human brain regions. Resting-state networks (RSNs) can be reliably and reproducibly detected using independent component analysis (ICA) at both individual subject and group levels. A growing number of ICA studies have reported altered functional connectivity in clinical populations. In the current work, it was hypothesized that ICA model order selection influences characteristics of RSNs as well as their functional connectivity. In addition, it was suggested that high ICA model order could be a useful tool to provide more detailed functional connectivity results. RSNs’ characteristics, i.e. spatial features, volume and repeatability of RSNs, were evaluated, and also differences in functional connectivity were investigated across different ICA model orders. ICA model order estimation had a significant impact on the spatial characteristics of the RSNs as well as their parcellation into sub-networks. Notably, at low model orders neuroanatomically and functionally different units tend to aggregate into large singular RSN components, while at higher model orders these units become separate RSN components. Disease-related differences in functional connectivity also seem to alter as a function of ICA model order. The volume of between-group differences reached maximum at high model orders. These findings demonstrate that fine-grained RSNs can provide detailed, disease-specific functional connectivity alterations. Finally, in order to overcome the multiple comparisons problem encountered at high ICA model orders, a new framework for group-ICA analysis was introduced. The framework involved concatenation of IC map, Tiivistelmä Toiminnallisten aivoalueiden välinen viestintä on todennäköisesti avainasemassa kognitiivisissa prosesseissa, jotka edellyttävät jatkuvaa tiedon integraatiota aivojen eri alueiden välillä. Tämä tekee ihmisaivojen toiminnallisen kytkennällisyyden tutkimuksesta erittäin tärkeätä. Kytkennälllisyyden tutkiminen antaa myös uutta tietoa ihmisaivojen osa-alueiden välisestä hierarkiasta. Aivojen hermoverkot voidaan luotettavasti ja toistettavasti havaita lepotilan toiminnasta yksilö- ja ryhmätasolla käyttämällä itsenäisten komponenttien analyysia (engl. Independent component analysis, ICA). Yhä useammat ICA-tutkimukset ovat raportoineet poikkeuksellisia toiminnallisen konnektiviteetin muutoksia kliinisissä populaatioissa. Tässä tutkimuksessa hypotetisoitiin, että ICA:lla laskettaujen komponenttien lukumäärä (l. asteluku) vaikuttaa tuloksena saatujen hermoverkkojen ominaisuuksiin kuten tilavuuteen ja kytkennällisyyteen. Lisäksi oletettiin, että korkea ICA-asteluku voisi olla herkempit tuottamaan yksityiskohtaisia toiminnallisen jaottelun tuloksia. Aivojen lepotilan hermoverkkojen ominaisuudet, kuten anatominen jakautuminen, volyymi ja lepohermoverkkojen havainnoinnin toistettavuus evaluoitin. Myös toiminnallisen kytkennällisyyden erot tutkitaan eri ICA-asteluvuilla. Havaittiin että asteluvulla on huomattava vaikutus aivojen lepotilan hermoverkkojen tilaominaisuuksiin sekä niiden jakautumiseen alaverkoiksi. Pienillä asteluvuilla hermoverkojen neuroanatomisesti erilliset yksiköt pyrkivät keräytymään laajoiksi yksittäisiksi komponenteiksi, kun taas korkeammilla asteluvuilla ne havaitaan erillisinä. Sairauksien aiheuttamat muutokset toiminnallisessa kytkennällisyydessä näyttävät muuttuvan myös ICA asteluvun mukaan saavuttaen maksiminsa korkeilla asteluvuilla. Korkeilla asteluvuilla voidaan havaita yksityiskohtaisia, sairaudelle ominaisia toiminnallisen konnektiviteetin muutoksia. Korkeisiin ICA asteluvun liittyvän tilastollisen monivertailuongelman ratkaisemiseksi ke

FMRI was performed with the dynamic facial expressions fear and happiness. This was done to detect differences in valence processing between 25 subjects with autism spectrum disorders (ASDs) and 27 typically developing controls. Valence scaling was abnormal in ASDs. Positive valence induces lower deactivation and abnormally strong activity in ASD in multiple regions. Negative valence increased deactivation in visual areas in subjects with ASDs. The most marked differences between valences focus on fronto-insular and temporal regions. This supports the idea that subjects with ASDs may have difficulty in passive processing of the salience and mirroring of expressions. When the valence scaling of brain activity fails, in contrast to controls, these areas activate and/or deactivate inappropriately during facial stimuli presented dynamically.

Udgivelsesdato: 2009-Jul, Laboratory rats are commonly fed ad libitum (AL). Moderate dietary restriction (DR) decreases mortality and morbidity when compared with AL feeding, but there are several obstacles to the implementation of DR. Traditional methods of restricted feeding disrupt normal diurnal eating rhythms and are not compatible with group housing. We have designed a novel method, the diet board, to restrict the feeding of group-housed rats. Animals fed from the diet board had 15% lower body weight than the AL-fed animals at the age of 17 weeks. The welfare effects of diet board feeding were assessed by comparing the stress physiology of diet board fed animals with that of AL-fed animals. Diet board feeding was associated with higher serum corticosterone levels and lower faecal secretion of IgA, suggesting the diet board causes a stress reaction. However, the AL-fed group had larger adrenal glands with higher adrenaline and noradrenaline content than the diet board animals. No gastric ulcers were found in any of the animals at necropsy. The diet board thus appears to cause a stress reaction when compared with AL-fed rats, but no apparent pathology was associated with this reaction. The diet board could help to solve the health problems associated with AL feeding, while allowing the rats to be group-housed and to maintain their normal diurnal eating rhythms. The diet board can also be seen as a functional cage furniture item, dividing the cage into compartments and thus increasing the structural complexity of the environment. In conclusion, the diet board appears to possess refinement potential compared with traditional methods of DR.