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Mäntylä VM, Lehtonen AJ, Korhonen V, Srbova L, Pokki J. Quantifying the Influence of X-Ray Irradiation on Cell-Size-Scale Viscoelasticity of Collagen Type 1. J Biomech Eng 2024; 146:044501. [PMID: 38183220 DOI: 10.1115/1.4064404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 12/27/2023] [Indexed: 01/07/2024]
Abstract
X-rays are widely used in mammography and radiotherapy of breast cancer. The research has focused on the effects of X-rays on cells in breast tissues, instead of the tissues' nonliving material, extracellular matrix. It is unclear what the influence of X-ray irradiation is on the matrix's mechanical cues, known to regulate malignant cancer-cell behaviors. Here, we developed a technique based on magnetic microrheology that can quantify the influence of X-ray irradiation on matrix viscoelasticity--or (solid-like) elastic and (liquid-like) viscous characteristics--at cell-size scales. To model breast-tissue extracellular matrix, we used the primary component of the tissue matrix, collagen type 1, as it is for control, and as irradiated by X-rays (tube voltage 50 kV). We used a magnetic microrheometer to measure collagen matrices using 10-μm-diameter magnetic probes. In each matrix, the probes were nanomanipulated using controlled magnetic forces by the microrheometer while the probes' displacements were detected to measure the viscoelasticity. The collagen-matrix data involve with a typical spatial variation in viscoelasticity. We find that higher irradiation doses (320 Gy) locally reduce stiffness (soften) collagen matrices and increase their loss tangent, indicating an elevated liquid-like nature. For lower, clinically relevant irradiation doses (54 Gy), we find insignificant matrix-viscoelasticity changes. We provide this irradiation-related technique for detection, and modification, of matrix viscoelastic cues at cell-size scales. The technique enables enhanced characterization of irradiated tissue constituents in a variety of breast-cancer radiotherapy types.
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Affiliation(s)
- Väinö Mikael Mäntylä
- Department of Electrical Engineering and Automation, Aalto University, Espoo FI-02150, Finland
| | - Arttu Juhani Lehtonen
- Department of Electrical Engineering and Automation, Aalto University, Espoo FI-02150, Finland
| | - Vesa Korhonen
- Department of Electrical Engineering and Automation, Aalto University, Espoo FI-02150, Finland
| | - Linda Srbova
- Department of Electrical Engineering and Automation, Aalto University, Espoo FI-02150, Finland
| | - Juho Pokki
- ASME Professional Mem. Department of Electrical Engineering and Automation, Aalto University, Espoo FI-02150, Finland
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Ebrahimi SM, Tuunanen J, Saarela V, Honkamo M, Huotari N, Raitamaa L, Korhonen V, Helakari H, Järvelä M, Kaakinen M, Eklund L, Kiviniemi V. Synchronous functional magnetic resonance eye imaging, video ophthalmoscopy, and eye surface imaging reveal the human brain and eye pulsation mechanisms. Sci Rep 2024; 14:2250. [PMID: 38278832 PMCID: PMC10817967 DOI: 10.1038/s41598-023-51069-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 12/30/2023] [Indexed: 01/28/2024] Open
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.
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Affiliation(s)
- Seyed-Mohsen Ebrahimi
- Oulu Functional NeuroImaging (OFNI), Diagnostic Imaging, Medical Research Center (MRC), Finland Oulu University Hospital, 90029, Oulu, Finland.
- Research Unit of Health Sciences and Technology (HST), Faculty of Medicine, University of Oulu, 90220, Oulu, Finland.
| | - Johanna Tuunanen
- Oulu Functional NeuroImaging (OFNI), Diagnostic Imaging, Medical Research Center (MRC), Finland Oulu University Hospital, 90029, Oulu, Finland
- Research Unit of Health Sciences and Technology (HST), Faculty of Medicine, University of Oulu, 90220, Oulu, Finland
| | - Ville Saarela
- Department of Ophthalmology and Medical Research Center, Oulu University Hospital and Research Unit of Clinical Medicine, University of Oulu, Oulu, Finland
| | - Marja Honkamo
- Department of Ophthalmology and Medical Research Center, Oulu University Hospital and Research Unit of Clinical Medicine, University of Oulu, Oulu, Finland
| | - Niko Huotari
- Oulu Functional NeuroImaging (OFNI), Diagnostic Imaging, Medical Research Center (MRC), Finland Oulu University Hospital, 90029, Oulu, Finland
- Research Unit of Health Sciences and Technology (HST), Faculty of Medicine, University of Oulu, 90220, Oulu, Finland
| | - Lauri Raitamaa
- Oulu Functional NeuroImaging (OFNI), Diagnostic Imaging, Medical Research Center (MRC), Finland Oulu University Hospital, 90029, Oulu, Finland
- Research Unit of Health Sciences and Technology (HST), Faculty of Medicine, University of Oulu, 90220, Oulu, Finland
| | - Vesa Korhonen
- Oulu Functional NeuroImaging (OFNI), Diagnostic Imaging, Medical Research Center (MRC), Finland Oulu University Hospital, 90029, Oulu, Finland
- Research Unit of Health Sciences and Technology (HST), Faculty of Medicine, University of Oulu, 90220, Oulu, Finland
| | - Heta Helakari
- Oulu Functional NeuroImaging (OFNI), Diagnostic Imaging, Medical Research Center (MRC), Finland Oulu University Hospital, 90029, Oulu, Finland
- Research Unit of Health Sciences and Technology (HST), Faculty of Medicine, University of Oulu, 90220, Oulu, Finland
| | - Matti Järvelä
- Oulu Functional NeuroImaging (OFNI), Diagnostic Imaging, Medical Research Center (MRC), Finland Oulu University Hospital, 90029, Oulu, Finland
- Research Unit of Health Sciences and Technology (HST), Faculty of Medicine, University of Oulu, 90220, Oulu, Finland
| | - Mika Kaakinen
- Oulu Center for Cell-Matrix Research, Faculty of Biochemistry and Molecular Medicine, Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Lauri Eklund
- Oulu Center for Cell-Matrix Research, Faculty of Biochemistry and Molecular Medicine, Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Vesa Kiviniemi
- Oulu Functional NeuroImaging (OFNI), Diagnostic Imaging, Medical Research Center (MRC), Finland Oulu University Hospital, 90029, Oulu, Finland.
- Research Unit of Health Sciences and Technology (HST), Faculty of Medicine, University of Oulu, 90220, Oulu, Finland.
- Oulu Center for Cell-Matrix Research, Faculty of Biochemistry and Molecular Medicine, Biocenter Oulu, University of Oulu, Oulu, Finland.
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Ferdinando H, Moradi S, Korhonen V, Kiviniemi V, Myllylä T. Altered cerebrovascular-CSF coupling in Alzheimer's Disease measured by functional near-infrared spectroscopy. Sci Rep 2023; 13:22364. [PMID: 38102188 PMCID: PMC10724150 DOI: 10.1038/s41598-023-48965-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Accepted: 12/01/2023] [Indexed: 12/17/2023] Open
Abstract
In-vivo microscopical studies indicate that brain cerebrospinal fluid (CSF) transport driven by blood vessel pulsations is reduced in the early stages of Alzheimer's disease (AD). We hypothesized that the coupling pattern between cerebrovascular pulsations and CSF is altered in AD, and this can be measured using multi-wavelength functional near-infrared spectroscopy (fNIRS). To study this, we quantified simultaneously cerebral hemo- and CSF hydrodynamics in early AD patients and age-matched healthy controls. Physiological pulsations were analysed in the vasomotor very low frequency (VLF 0.008-0.1 Hz), respiratory (Resp. 0.1-0.6 Hz), and cardiac (Card. 0.6-5 Hz) bands. A sliding time window cross-correlation approach was used to estimate the temporal stability of the cerebrovascular-CSF coupling. We investigated how the lag time series variation of the coupling differs between AD patients and control. The couplings involving deoxyhemoglobin (HbR) and CSF water, along with their first derivative, in the cardiac band demonstrated significant difference between AD patients and controls. Furthermore, the lag time series variation of HbR-CSF in the cardiac band provided a significant relationship, p-value = 0.04 and r2 = 0.16, with the mini-mental state exam (MMSE) score. In conclusion, the coupling pattern between hemodynamics and CSF is reduced in AD and it correlates with MMSE score.
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Affiliation(s)
- Hany Ferdinando
- Research Unit of Health Science and Technology, University of Oulu, Oulu, Finland.
| | - Sadegh Moradi
- Opto-Electronics and Measurement Technique Research Unit, University of Oulu, Oulu, Finland
| | - Vesa Korhonen
- Research Unit of Health Science and Technology, University of Oulu, Oulu, Finland
- Department of Radiology, Oulu University Hospital, Oulu, Finland
| | - Vesa Kiviniemi
- Research Unit of Health Science and Technology, University of Oulu, Oulu, Finland
- Department of Radiology, Oulu University Hospital, Oulu, Finland
| | - Teemu Myllylä
- Research Unit of Health Science and Technology, University of Oulu, Oulu, Finland
- Opto-Electronics and Measurement Technique Research Unit, University of Oulu, Oulu, Finland
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Helakari H, Järvelä M, Väyrynen T, Tuunanen J, Piispala J, Kallio M, Ebrahimi SM, Poltojainen V, Kananen J, Elabasy A, Huotari N, Raitamaa L, Tuovinen T, Korhonen V, Nedergaard M, Kiviniemi V. Effect of sleep deprivation and NREM sleep stage on physiological brain pulsations. Front Neurosci 2023; 17:1275184. [PMID: 38105924 PMCID: PMC10722275 DOI: 10.3389/fnins.2023.1275184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Accepted: 11/02/2023] [Indexed: 12/19/2023] Open
Abstract
Introduction Sleep increases brain fluid transport and the power of pulsations driving the fluids. We investigated how sleep deprivation or electrophysiologically different stages of non-rapid-eye-movement (NREM) sleep affect the human brain pulsations. Methods Fast functional magnetic resonance imaging (fMRI) was performed in healthy subjects (n = 23) with synchronous electroencephalography (EEG), that was used to verify arousal states (awake, N1 and N2 sleep). Cardiorespiratory rates were verified with physiological monitoring. Spectral power analysis assessed the strength, and spectral entropy assessed the stability of the pulsations. Results In N1 sleep, the power of vasomotor (VLF < 0.1 Hz), but not cardiorespiratory pulsations, intensified after sleep deprived vs. non-sleep deprived subjects. The power of all three pulsations increased as a function of arousal state (N2 > N1 > awake) encompassing brain tissue in both sleep stages, but extra-axial CSF spaces only in N2 sleep. Spectral entropy of full band and respiratory pulsations decreased most in N2 sleep stage, while cardiac spectral entropy increased in ventricles. Discussion In summary, the sleep deprivation and sleep depth, both increase the power and harmonize the spectral content of human brain pulsations.
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Affiliation(s)
- Heta Helakari
- Oulu Functional Neuroimaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Matti Järvelä
- Oulu Functional Neuroimaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Tommi Väyrynen
- Oulu Functional Neuroimaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Johanna Tuunanen
- Oulu Functional Neuroimaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Johanna Piispala
- Clinical Neurophysiology, Oulu University Hospital, Oulu, Finland
| | - Mika Kallio
- Clinical Neurophysiology, Oulu University Hospital, Oulu, Finland
| | - Seyed Mohsen Ebrahimi
- Oulu Functional Neuroimaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Valter Poltojainen
- Oulu Functional Neuroimaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Janne Kananen
- Oulu Functional Neuroimaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland
- Clinical Neurophysiology, Oulu University Hospital, Oulu, Finland
| | - Ahmed Elabasy
- Oulu Functional Neuroimaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Niko Huotari
- Oulu Functional Neuroimaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Lauri Raitamaa
- Oulu Functional Neuroimaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Timo Tuovinen
- Oulu Functional Neuroimaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Vesa Korhonen
- Oulu Functional Neuroimaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Maiken Nedergaard
- Center of Translational Neuromedicine, University of Copenhagen, Copenhagen, Denmark
- Center of Translational Neuromedicine, University of Rochester, Rochester, NY, United States
| | - Vesa Kiviniemi
- Oulu Functional Neuroimaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland
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Väyrynen T, Helakari H, Korhonen V, Tuunanen J, Huotari N, Piispala J, Kallio M, Raitamaa L, Kananen J, Järvelä M, Matias Palva J, Kiviniemi V. Infra-slow fluctuations in cortical potentials and respiration drive fast cortical EEG rhythms in sleeping and waking states. Clin Neurophysiol 2023; 156:207-219. [PMID: 37972532 DOI: 10.1016/j.clinph.2023.10.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 08/09/2023] [Accepted: 10/23/2023] [Indexed: 11/19/2023]
Abstract
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.
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Affiliation(s)
- Tommi Väyrynen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland; MIPT group to: Research Unit of Health Sciences and Technology (HST), Faculty of Medicine, University of Oulu, Oulu 90220, Finland; Medical Research Center (MRC), Oulu 90220, Finland.
| | - Heta Helakari
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland; MIPT group to: Research Unit of Health Sciences and Technology (HST), Faculty of Medicine, University of Oulu, Oulu 90220, Finland; Medical Research Center (MRC), Oulu 90220, Finland
| | - Vesa Korhonen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland; MIPT group to: Research Unit of Health Sciences and Technology (HST), Faculty of Medicine, University of Oulu, Oulu 90220, Finland; Medical Research Center (MRC), Oulu 90220, Finland
| | - Johanna Tuunanen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland; MIPT group to: Research Unit of Health Sciences and Technology (HST), Faculty of Medicine, University of Oulu, Oulu 90220, Finland; Medical Research Center (MRC), Oulu 90220, Finland
| | - Niko Huotari
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland; MIPT group to: Research Unit of Health Sciences and Technology (HST), Faculty of Medicine, University of Oulu, Oulu 90220, Finland; Medical Research Center (MRC), Oulu 90220, Finland
| | - Johanna Piispala
- MIPT group to: Research Unit of Health Sciences and Technology (HST), Faculty of Medicine, University of Oulu, Oulu 90220, Finland; Medical Research Center (MRC), Oulu 90220, Finland; Clinical Neurophysiology, Oulu University Hospital, Oulu 90220, Finland
| | - Mika Kallio
- MIPT group to: Research Unit of Health Sciences and Technology (HST), Faculty of Medicine, University of Oulu, Oulu 90220, Finland; Medical Research Center (MRC), Oulu 90220, Finland; Clinical Neurophysiology, Oulu University Hospital, Oulu 90220, Finland
| | - Lauri Raitamaa
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland; MIPT group to: Research Unit of Health Sciences and Technology (HST), Faculty of Medicine, University of Oulu, Oulu 90220, Finland; Medical Research Center (MRC), Oulu 90220, Finland
| | - Janne Kananen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland; MIPT group to: Research Unit of Health Sciences and Technology (HST), Faculty of Medicine, University of Oulu, Oulu 90220, Finland; Medical Research Center (MRC), Oulu 90220, Finland; Clinical Neurophysiology, Oulu University Hospital, Oulu 90220, Finland
| | - Matti Järvelä
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland; MIPT group to: Research Unit of Health Sciences and Technology (HST), Faculty of Medicine, University of Oulu, Oulu 90220, Finland; Medical Research Center (MRC), Oulu 90220, Finland
| | - J Matias Palva
- Department of Neuroscience and Biomedical Engineering, Aalto University, 02150 Espoo, Finland; Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Finland; Centre for Cognitive Neuroimaging, University of Glasgow, United Kingdom
| | - Vesa Kiviniemi
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland; MIPT group to: Research Unit of Health Sciences and Technology (HST), Faculty of Medicine, University of Oulu, Oulu 90220, Finland; Medical Research Center (MRC), Oulu 90220, Finland; Biocenter Oulu, Faculty of Biochemistry and Molecular Medicine, University of Oulu, Oulu 90220, Finland
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Elabasy A, Suhonen M, Rajna Z, Hosni Y, Kananen J, Annunen J, Ansakorpi H, Korhonen V, Seppänen T, Kiviniemi V. Author Correction: Respiratory brain impulse propagation in focal epilepsy. Sci Rep 2023; 13:7515. [PMID: 37160935 PMCID: PMC10169774 DOI: 10.1038/s41598-023-34268-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/11/2023] Open
Affiliation(s)
- Ahmed Elabasy
- Center for Machine Vision and Signal Analysis, University of Oulu, 90014, Oulu, Finland.
- Oulu Functional NeuroImaging, Research Unit of Health Science and Technology, University of Oulu, 90029, Oulu, Finland.
| | - Mia Suhonen
- Diagnostics, Medical Research Center, Oulu University Hospital, 90029, Oulu, Finland.
- Oulu Functional NeuroImaging, Research Unit of Health Science and Technology, University of Oulu, 90029, Oulu, Finland.
| | - Zalan Rajna
- Center for Machine Vision and Signal Analysis, University of Oulu, 90014, Oulu, Finland
- Oulu Functional NeuroImaging, Research Unit of Health Science and Technology, University of Oulu, 90029, Oulu, Finland
| | - Youssef Hosni
- Center for Machine Vision and Signal Analysis, University of Oulu, 90014, Oulu, Finland
- Oulu Functional NeuroImaging, Research Unit of Health Science and Technology, University of Oulu, 90029, Oulu, Finland
| | - Janne Kananen
- Diagnostics, Medical Research Center, Oulu University Hospital, 90029, Oulu, Finland
- Oulu Functional NeuroImaging, Research Unit of Health Science and Technology, University of Oulu, 90029, Oulu, Finland
- Clinical Neurophysiology, Research Unit of Health Science and Technology, University of Oulu, 90029, Oulu, Finland
| | - Johanna Annunen
- Research Unit of Clinical Neuroscience, Neurology, University of Oulu, 90029, Oulu, Finland
- Neurocenter (Member of ERN EpiCARE), Medical Research Center, Oulu University Hospital, 90029, Oulu, Finland
| | - Hanna Ansakorpi
- Research Unit of Clinical Neuroscience, Neurology, University of Oulu, 90029, Oulu, Finland
| | - Vesa Korhonen
- Diagnostics, Medical Research Center, Oulu University Hospital, 90029, Oulu, Finland
- Oulu Functional NeuroImaging, Research Unit of Health Science and Technology, University of Oulu, 90029, Oulu, Finland
| | - Tapio Seppänen
- Center for Machine Vision and Signal Analysis, University of Oulu, 90014, Oulu, Finland
| | - Vesa Kiviniemi
- Diagnostics, Medical Research Center, Oulu University Hospital, 90029, Oulu, Finland.
- Oulu Functional NeuroImaging, Research Unit of Health Science and Technology, University of Oulu, 90029, Oulu, Finland.
- Biocenter Oulu, University of Oulu, 90014, Oulu, Finland.
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Elabasy A, Suhonen M, Rajna Z, Hosni Y, Kananen J, Annunen J, Ansakorpi H, Korhonen V, Seppänen T, Kiviniemi V. Respiratory brain impulse propagation in focal epilepsy. Sci Rep 2023; 13:5222. [PMID: 36997658 PMCID: PMC10063583 DOI: 10.1038/s41598-023-32271-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Accepted: 03/24/2023] [Indexed: 04/03/2023] Open
Abstract
Respiratory brain pulsations pertaining to intra-axial hydrodynamic solute transport are markedly altered in focal epilepsy. We used optical flow analysis of ultra-fast functional magnetic resonance imaging (fMRI) data to investigate the velocity characteristics of respiratory brain impulse propagation in patients with focal epilepsy treated with antiseizure medication (ASM) (medicated patients with focal epilepsy; ME, n = 23), drug-naïve patients with at least one seizure (DN, n = 19) and matched healthy control subjects (HC, n = 75). We detected in the two patient groups (ME and DN) several significant alterations in the respiratory brain pulsation propagation velocity, which showed a bidirectional change dominated by a reduction in speed. Furthermore, the respiratory impulses moved more in reversed or incoherent directions in both patient groups vs. the HC group. The speed reductions and directionality changes occurred in specific phases of the respiratory cycle. In conclusion, irrespective of medication status, both patient groups showed incoherent and slower respiratory brain impulses, which may contribute to epileptic brain pathology by hindering brain hydrodynamics.
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Affiliation(s)
- Ahmed Elabasy
- Center for Machine Vision and Signal Analysis, University of Oulu, 90014, Oulu, Finland.
- Oulu Functional NeuroImaging, Diagnostic Radiology, Medical Research Center/HTS, Oulu University Hospital, 90029, Oulu, Finland.
| | - Mia Suhonen
- Medical Imaging, Physics and Technology, University of Oulu, 90029, Oulu, Finland.
- Oulu Functional NeuroImaging, Diagnostic Radiology, Medical Research Center/HTS, Oulu University Hospital, 90029, Oulu, Finland.
| | - Zalan Rajna
- Center for Machine Vision and Signal Analysis, University of Oulu, 90014, Oulu, Finland
| | - Youssef Hosni
- Center for Machine Vision and Signal Analysis, University of Oulu, 90014, Oulu, Finland
- Oulu Functional NeuroImaging, Diagnostic Radiology, Medical Research Center/HTS, Oulu University Hospital, 90029, Oulu, Finland
| | - Janne Kananen
- Medical Imaging, Physics and Technology, University of Oulu, 90029, Oulu, Finland
- Oulu Functional NeuroImaging, Diagnostic Radiology, Medical Research Center/HTS, Oulu University Hospital, 90029, Oulu, Finland
- Clinical Neurophysiology, Oulu University Hospital, 90029 OYS, Oulu, Finland
| | - Johanna Annunen
- Research Unit of Clinical Neuroscience, Neurology, University of Oulu, 90029, Oulu, Finland
- Neurocenter, Neurology, Oulu University Hospital, Member of ERN EpiCARE, 90029, Oulu, Finland
- MRC, Oulu University Hospital, 90029, Oulu, Finland
| | - Hanna Ansakorpi
- Research Unit of Clinical Neuroscience, Neurology, University of Oulu, 90029, Oulu, Finland
| | - Vesa Korhonen
- Medical Imaging, Physics and Technology, University of Oulu, 90029, Oulu, Finland
- Oulu Functional NeuroImaging, Diagnostic Radiology, Medical Research Center/HTS, Oulu University Hospital, 90029, Oulu, Finland
| | - Tapio Seppänen
- Center for Machine Vision and Signal Analysis, University of Oulu, 90014, Oulu, Finland
| | - Vesa Kiviniemi
- Medical Imaging, Physics and Technology, University of Oulu, 90029, Oulu, Finland.
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Myllylä T, Korhonen V, Karthikeyan P, Honka U, Lohela J, Inget K, Ferdinando H, Karhula SS, Nikkinen J. Cerebral tissue oxygenation response to brain irradiation measured during clinical radiotherapy. J Biomed Opt 2023; 28:015002. [PMID: 36742351 PMCID: PMC9887167 DOI: 10.1117/1.jbo.28.1.015002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 12/01/2022] [Indexed: 06/18/2023]
Abstract
SIGNIFICANCE Cancer therapy treatments produce extensive changes in the physiological and morphological properties of tissues, which are also individual dependent. Currently, a key challenge involves developing more tailored cancer therapy, and consequently, individual biological response measurement during therapy, such as tumor hypoxia, is of high interest. This is the first time human cerebral haemodynamics and cerebral tissue oxygenation index (TOI) changes were measured during the irradiation in clinical radiotherapy and functional near-infrared spectroscopy (fNIRS) technique was demonstrated as a feasible technique for clinical use in radiotherapy, based on 34 online patient measurements. AIM Our aim is to develop predictive biomarkers and noninvasive real-time methods to establish the effect of radiotherapy during treatment as well as to optimize radiotherapy dose planning for individual patients. In particular, fNIRS-based technique could offer an effective and clinically feasible online technique for continuous monitoring of brain tissue hypoxia and responses to chemo- and radiotherapy, which involves modulating tumor oxygenation to increase or decrease tumor hypoxia. We aim to show that fNIRS is feasible for repeatability measuring in patient radiotherapy, the temporal alterations of tissue oxygenation induced by radiation. APPROACH Fiber optics setup using multiwavelength fNIRS was built and combined with a medical linear accelerator to measure cerebral tissue oxygenation changes during the whole-brain radiotherapy treatment, where the radiation dose is given in whole brain area only preventing dosage to eyes. Correlation of temporal alterations in cerebral haemodynamics and TOI response to brain irradiation was quantified. RESULTS Online fNIRS patient measurement of cerebral haemodynamics during clinical brain radiotherapy is feasible in clinical environment, and results based on 34 patient measurements show strong temporal alterations in cerebral haemodynamics and decrease in TOI during brain irradiation and confirmed the repeatability. Our proof-of-concept study shows evidently that irradiation causes characteristic immediate changes in brain tissue oxygenation. CONCLUSIONS In particular, TOI seems to be a sensitive parameter to observe the tissue effects of radiotherapy. Monitoring the real-time interactions between the subjected radiation dose and corresponding haemodynamic effects may provide important tool for the researchers and clinicians in the field of radiotherapy. Eventually, presented fNIRS technique could be used for improving dose planning and safety control for individual patients.
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Affiliation(s)
- Teemu Myllylä
- University of Oulu, Research Unit of Health Sciences and Technology, Oulu, Finland
- University of Oulu, Optoelectronics and Measurement Techniques Unit, Oulu, Finland
| | - Vesa Korhonen
- University of Oulu, Research Unit of Health Sciences and Technology, Oulu, Finland
- Oulu University Hospital, Department of Diagnostic Radiology, Oulu, Finland
- Medical Research Center, Oulu, Finland
| | - Priya Karthikeyan
- University of Oulu, Research Unit of Health Sciences and Technology, Oulu, Finland
| | - Ulriika Honka
- University of Oulu, Research Unit of Health Sciences and Technology, Oulu, Finland
| | - Jesse Lohela
- University of Oulu, Research Unit of Health Sciences and Technology, Oulu, Finland
- Oulu University Hospital, Department of Oncology and Radiotherapy, Oulu, Finland
| | - Kalle Inget
- University of Oulu, Research Unit of Health Sciences and Technology, Oulu, Finland
- Medical Research Center, Oulu, Finland
| | - Hany Ferdinando
- University of Oulu, Research Unit of Health Sciences and Technology, Oulu, Finland
| | - Sakari S. Karhula
- University of Oulu, Research Unit of Health Sciences and Technology, Oulu, Finland
- Medical Research Center, Oulu, Finland
- Oulu University Hospital, Department of Oncology and Radiotherapy, Oulu, Finland
| | - Juha Nikkinen
- University of Oulu, Research Unit of Health Sciences and Technology, Oulu, Finland
- Medical Research Center, Oulu, Finland
- Oulu University Hospital, Department of Oncology and Radiotherapy, Oulu, Finland
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9
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Helakari H, Tuunanen J, Korhonen V, Piispala J, Kallio M, Väyrynen T, Kivipää A, Huotari N, Raitamaa L, Syväoja S, Kiviniemi V. Brain respiratory pulsatility of fast fMRI stabilizes during NREM Stage 2 sleep. Sleep Med 2022. [DOI: 10.1016/j.sleep.2022.05.050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
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10
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Kananen J, Järvelä M, Korhonen V, Tuovinen T, Huotari N, Raitamaa L, Helakari H, Väyrynen T, Raatikainen V, Nedergaard M, Ansakorpi H, Jacobs J, LeVan P, Kiviniemi V. Increased interictal synchronicity of respiratory related brain pulsations in epilepsy. J Cereb Blood Flow Metab 2022; 42:1840-1853. [PMID: 35570730 PMCID: PMC9536129 DOI: 10.1177/0271678x221099703] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Respiratory brain pulsations have recently been shown to drive electrophysiological brain activity in patients with epilepsy. Furthermore, functional neuroimaging indicates that respiratory brain pulsations have increased variability and amplitude in patients with epilepsy compared to healthy individuals. To determine whether the respiratory drive is altered in epilepsy, we compared respiratory brain pulsation synchronicity between healthy controls and patients. Whole brain fast functional magnetic resonance imaging was performed on 40 medicated patients with focal epilepsy, 20 drug-naïve patients and 102 healthy controls. Cerebrospinal fluid associated respiratory pulsations were used to generate individual whole brain respiratory synchronization maps, which were compared between groups. Finally, we analyzed the seizure frequency effect and diagnostic accuracy of the respiratory synchronization defect in epilepsy. Respiratory brain pulsations related to the verified fourth ventricle pulsations were significantly more synchronous in patients in frontal, periventricular and mid-temporal regions, while the seizure frequency correlated positively with synchronicity. The respiratory brain synchronicity had a good diagnostic accuracy (ROCAUC = 0.75) in discriminating controls from medicated patients. The elevated respiratory brain synchronicity in focal epilepsy suggests altered physiological effect of cerebrospinal fluid pulsations possibly linked to regional brain water dynamics involved with interictal brain physiology.
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Affiliation(s)
- Janne Kananen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu, Finland.,Medical Research Center (MRC), Oulu, Finland
| | - Matti Järvelä
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu, Finland.,Medical Research Center (MRC), Oulu, Finland
| | - Vesa Korhonen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu, Finland.,Medical Research Center (MRC), Oulu, Finland
| | - Timo Tuovinen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu, Finland.,Medical Research Center (MRC), Oulu, Finland
| | - Niko Huotari
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu, Finland.,Medical Research Center (MRC), Oulu, Finland
| | - Lauri Raitamaa
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu, Finland.,Medical Research Center (MRC), Oulu, Finland
| | - Heta Helakari
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu, Finland.,Medical Research Center (MRC), Oulu, Finland
| | - Tommi Väyrynen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu, Finland.,Medical Research Center (MRC), Oulu, Finland
| | - Ville Raatikainen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu, Finland.,Medical Research Center (MRC), Oulu, Finland
| | - Maiken Nedergaard
- Center for Translational Neuromedicine, Department of Neurosurgery, University of Rochester Medical Center, Rochester, NY, USA.,Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Hanna Ansakorpi
- Medical Research Center (MRC), Oulu, Finland.,Research Unit of Neuroscience, Neurology, University of Oulu, Oulu, Finland.,Department of Neurology, Oulu University Hospital, Oulu, Finland
| | - Julia Jacobs
- Department of Pediatric Neurology and Muscular Disease, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,Department of Paediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Department of Neuroscience, Cumming School of Medicine, University of Calgary, Calgary, Canada.,Hotchkiss Brain Institute and Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada
| | - Pierre LeVan
- Department of Paediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Department of Neuroscience, Cumming School of Medicine, University of Calgary, Calgary, Canada.,Hotchkiss Brain Institute and Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada.,Department of Radiology, Medical Physics, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Vesa Kiviniemi
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu, Finland.,Medical Research Center (MRC), Oulu, Finland
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11
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Poltojainen V, Kemppainen J, Keinänen N, Bode M, Isokangas JM, Kuitunen H, Nikkinen J, Sonkajärvi E, Korhonen V, Tuovinen T, Järvelä M, Huotari N, Raitamaa L, Kananen J, Korhonen T, Tetri S, Kuittinen O, Kiviniemi V. Physiological instability is linked to mortality in primary central nervous system lymphoma: A case-control fMRI study. Hum Brain Mapp 2022; 43:4030-4044. [PMID: 35543292 PMCID: PMC9374894 DOI: 10.1002/hbm.25901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 04/07/2022] [Accepted: 04/26/2022] [Indexed: 11/07/2022] Open
Abstract
Primary central nervous system lymphoma (PCNSL) is an aggressive brain disease where lymphocytes invade along perivascular spaces of arteries and veins. The invasion markedly changes (peri)vascular structures but its effect on physiological brain pulsations has not been previously studied. Using physiological magnetic resonance encephalography (MREGBOLD ) scanning, this study aims to quantify the extent to which (peri)vascular PCNSL involvement alters the stability of physiological brain pulsations mediated by cerebral vasculature. Clinical implications and relevance were explored. In this study, 21 PCNSL patients (median 67y; 38% females) and 30 healthy age-matched controls (median 63y; 73% females) were scanned for MREGBOLD signal during 2018-2021. Motion effects were removed. Voxel-by-voxel Coefficient of Variation (CV) maps of MREGBOLD signal was calculated to examine the stability of physiological brain pulsations. Group-level differences in CV were examined using nonparametric covariate-adjusted tests. Subject-level CV alterations were examined against control population Z-score maps wherein clusters of increased CV values were detected. Spatial distributions of clusters and findings from routine clinical neuroimaging were compared [contrast-enhanced, diffusion-weighted, fluid-attenuated inversion recovery (FLAIR) data]. Whole-brain mean CV was linked to short-term mortality with 100% sensitivity and 100% specificity, as all deceased patients revealed higher values (n = 5, median 0.055) than surviving patients (n = 16, median 0.028) (p < .0001). After adjusting for medication, head motion, and age, patients revealed higher CV values (group median 0.035) than healthy controls (group median 0.024) around arterial territories (p ≤ .001). Abnormal clusters (median 1.10 × 105 mm3 ) extended spatially beyond FLAIR lesions (median 0.62 × 105 mm3 ) with differences in volumes (p = .0055).
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Affiliation(s)
- Valter Poltojainen
- Oulu Functional Neuroimaging, University of Oulu/Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland.,Department of Radiology, Oulu University Hospital, Oulu, Finland
| | - Janette Kemppainen
- Oulu Functional Neuroimaging, University of Oulu/Oulu University Hospital, Oulu, Finland.,Cancer and Translational Medicine Research Unit, University of Oulu, Oulu, Finland
| | - Nina Keinänen
- Department of Anaesthesiology, Oulu University Hospital, Oulu, Finland
| | - Michaela Bode
- Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland.,Department of Radiology, Oulu University Hospital, Oulu, Finland
| | | | - Hanne Kuitunen
- Department of Oncology and Haematology, Oulu University Hospital, Oulu, Finland
| | - Juha Nikkinen
- Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland.,Department of Oncology and Radiotherapy, Oulu University Hospital, Oulu, Finland
| | - Eila Sonkajärvi
- Department of Anaesthesiology, Oulu University Hospital, Oulu, Finland
| | - Vesa Korhonen
- Oulu Functional Neuroimaging, University of Oulu/Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland.,Department of Radiology, Oulu University Hospital, Oulu, Finland
| | - Timo Tuovinen
- Oulu Functional Neuroimaging, University of Oulu/Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland.,Department of Radiology, Oulu University Hospital, Oulu, Finland
| | - Matti Järvelä
- Oulu Functional Neuroimaging, University of Oulu/Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland.,Department of Radiology, Oulu University Hospital, Oulu, Finland
| | - Niko Huotari
- Oulu Functional Neuroimaging, University of Oulu/Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland.,Department of Radiology, Oulu University Hospital, Oulu, Finland
| | - Lauri Raitamaa
- Oulu Functional Neuroimaging, University of Oulu/Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland.,Department of Radiology, Oulu University Hospital, Oulu, Finland
| | - Janne Kananen
- Oulu Functional Neuroimaging, University of Oulu/Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland.,Department of Radiology, Oulu University Hospital, Oulu, Finland
| | - Tommi Korhonen
- Medical Research Center, University of Oulu/Oulu University Hospital, Oulu, Finland.,Department of Clinical Neuroscience, University of Oulu, Oulu, Finland
| | - Sami Tetri
- Medical Research Center, University of Oulu/Oulu University Hospital, Oulu, Finland.,Department of Clinical Neuroscience, University of Oulu, Oulu, Finland
| | - Outi Kuittinen
- Department of Oncology and Haematology, Oulu University Hospital, Oulu, Finland.,Cancer Center, Kuopio University Hospital, Kuopio, Finland.,Faculty of Health Medicine, Institute of Clinical Medicine, University of Eastern Finland, Oulu, Finland
| | - Vesa Kiviniemi
- Oulu Functional Neuroimaging, University of Oulu/Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland.,Department of Radiology, Oulu University Hospital, Oulu, Finland
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12
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Huotari N, Tuunanen J, Raitamaa L, Raatikainen V, Kananen J, Helakari H, Tuovinen T, Järvelä M, Kiviniemi V, Korhonen V. Cardiovascular Pulsatility Increases in Visual Cortex Before Blood Oxygen Level Dependent Response During Stimulus. Front Neurosci 2022; 16:836378. [PMID: 35185462 PMCID: PMC8853630 DOI: 10.3389/fnins.2022.836378] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 01/13/2022] [Indexed: 11/13/2022] Open
Abstract
The physiological pulsations that drive tissue fluid homeostasis are not well characterized during brain activation. Therefore, we used fast magnetic resonance encephalography (MREG) fMRI to measure full band (0–5 Hz) blood oxygen level-dependent (BOLDFB) signals during a dynamic visual task in 23 subjects. This revealed brain activity in the very low frequency (BOLDVLF) as well as in cardiac and respiratory bands. The cardiovascular hemodynamic envelope (CHe) signal correlated significantly with the visual BOLDVLF response, considered as an independent signal source in the V1-V2 visual cortices. The CHe preceded the canonical BOLDVLF response by an average of 1.3 (± 2.2) s. Physiologically, the observed CHe signal could mark increased regional cardiovascular pulsatility following vasodilation.
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Affiliation(s)
- Niko Huotari
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu, Finland
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland
- *Correspondence: Niko Huotari,
| | - Johanna Tuunanen
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu, Finland
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland
| | - Lauri Raitamaa
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu, Finland
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland
| | - Ville Raatikainen
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu, Finland
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland
| | - Janne Kananen
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu, Finland
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland
| | - Heta Helakari
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu, Finland
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland
| | - Timo Tuovinen
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu, Finland
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland
| | - Matti Järvelä
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu, Finland
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland
| | - Vesa Kiviniemi
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu, Finland
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland
| | - Vesa Korhonen
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu, Finland
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland
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13
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Kotila A, Tohka J, Kauppi JP, Gabbatore I, Mäkinen L, Hurtig TM, Ebeling HE, Korhonen V, Kiviniemi VJ, Loukusa S. Neural-level associations of non-verbal pragmatic comprehension in young Finnish autistic adults. Int J Circumpolar Health 2021; 80:1909333. [PMID: 34027832 PMCID: PMC8158210 DOI: 10.1080/22423982.2021.1909333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Revised: 03/12/2021] [Accepted: 03/23/2021] [Indexed: 11/18/2022] Open
Abstract
This video-based study examines the pragmatic non-verbal comprehension skills and corresponding neural-level findings in young Finnish autistic adults, and controls. Items from the Assessment Battery of Communication (ABaCo) were chosen to evaluate the comprehension of non-verbal communication. Inter-subject correlation (ISC) analysis of the functional magnetic resonance imaging data was used to reveal the synchrony of brain activation across participants during the viewing of pragmatically complex scenes of ABaCo videos. The results showed a significant difference between the ISC maps of the autistic and control groups in tasks involving the comprehension of non-verbal communication, thereby revealing several brain regions where correlation of brain activity was greater within the control group. The results suggest a possible weaker modulation of brain states in response to the pragmatic non-verbal communicative situations in autistic participants. Although there was no difference between the groups in behavioural responses to ABaCo items, there was more variability in the accuracy of the responses in the autistic group. Furthermore, mean answering and reaction times correlated with the severity of autistic traits. The results indicate that even if young autistic adults may have learned to use compensatory resources in their communicative-pragmatic comprehension, pragmatic processing in naturalistic situations still requires additional effort.
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Affiliation(s)
- Aija Kotila
- Faculty of Humanities, Research Unit of Logopedics, University of Oulu, Oulu, Finland
| | - Jussi Tohka
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Jukka-Pekka Kauppi
- Faculty of Information Technology, University of Jyväskylä, Jyväskylä, Finland
| | - Ilaria Gabbatore
- Faculty of Humanities, Research Unit of Logopedics, University of Oulu, Oulu, Finland
- Department of Psychology, University of Turin, Turin, Italy
| | - Leena Mäkinen
- Faculty of Humanities, Research Unit of Logopedics, University of Oulu, Oulu, Finland
| | - Tuula M. Hurtig
- Clinic of Child Psychiatry, Oulu University Hospital and PEDEGO Research Unit, University of Oulu, Oulu, Finland
- Research Unit of Clinical Neuroscience, Psychiatry, University of Oulu
| | - Hanna E. Ebeling
- Clinic of Child Psychiatry, Oulu University Hospital and PEDEGO Research Unit, University of Oulu, Oulu, Finland
| | - Vesa Korhonen
- Department of Diagnostic Radiology, Medical Research Center, Oulu University Hospital and Research Unit of Medical Imaging, Physics and Technology, the Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Vesa J. Kiviniemi
- Department of Diagnostic Radiology, Medical Research Center, Oulu University Hospital and Research Unit of Medical Imaging, Physics and Technology, the Faculty of Medicine, University of Oulu, Oulu, Finland
- Oulu Functional NeuroImaging-lab, Medical Research Center, Oulu University Hospital, Oulu, Finland
| | - Soile Loukusa
- Faculty of Humanities, Research Unit of Logopedics, University of Oulu, Oulu, Finland
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14
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Raitamaa L, Huotari N, Korhonen V, Helakari H, Koivula A, Kananen J, Kiviniemi V. Spectral analysis of physiological brain pulsations affecting the BOLD signal. Hum Brain Mapp 2021; 42:4298-4313. [PMID: 34037278 PMCID: PMC8356994 DOI: 10.1002/hbm.25547] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Revised: 05/18/2021] [Accepted: 05/19/2021] [Indexed: 12/17/2022] Open
Abstract
Physiological pulsations have been shown to affect the global blood oxygen level dependent (BOLD) signal in human brain. While these pulsations have previously been regarded as noise, recent studies show their potential as biomarkers of brain pathology. We used the extended 5 Hz spectral range of magnetic resonance encephalography (MREG) data to investigate spatial and frequency distributions of physiological BOLD signal sources. Amplitude spectra of the global image signals revealed cardiorespiratory envelope modulation (CREM) peaks, in addition to the previously known very low frequency (VLF) and cardiorespiratory pulsations. We then proceeded to extend the amplitude of low frequency fluctuations (ALFF) method to each of these pulsations. The respiratory pulsations were spatially dominating over most brain structures. The VLF pulsations overcame the respiratory pulsations in frontal and parietal gray matter, whereas cardiac and CREM pulsations had this effect in central cerebrospinal fluid (CSF) spaces and major blood vessels. A quasi‐periodic pattern (QPP) analysis showed that the CREM pulsations propagated as waves, with a spatiotemporal pattern differing from that of respiratory pulsations, indicating them to be distinct intracranial physiological phenomenon. In conclusion, the respiration has a dominant effect on the global BOLD signal and directly modulates cardiovascular brain pulsations.
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Affiliation(s)
- Lauri Raitamaa
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu.,Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu
| | - Niko Huotari
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu.,Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu
| | - Vesa Korhonen
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu.,Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu
| | - Heta Helakari
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu.,Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu
| | - Anssi Koivula
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu.,Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu
| | - Janne Kananen
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu.,Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu
| | - Vesa Kiviniemi
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu.,Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu
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15
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Rajna Z, Mattila H, Huotari N, Tuovinen T, Krüger J, Holst SC, Korhonen V, Remes AM, Seppänen T, Hennig J, Nedergaard M, Kiviniemi V. Cardiovascular brain impulses in Alzheimer's disease. Brain 2021; 144:2214-2226. [PMID: 33787890 PMCID: PMC8422353 DOI: 10.1093/brain/awab144] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Revised: 03/13/2021] [Accepted: 03/23/2021] [Indexed: 11/30/2022] Open
Abstract
Accumulation of amyloid-β is a key neuropathological feature in brain of
Alzheimer’s disease patients. Alterations in cerebral haemodynamics,
such as arterial impulse propagation driving the (peri)vascular CSF flux,
predict future Alzheimer’s disease progression. We now present a
non-invasive method to quantify the three-dimensional propagation of
cardiovascular impulses in human brain using ultrafast 10 Hz magnetic
resonance encephalography. This technique revealed spatio-temporal abnormalities
in impulse propagation in Alzheimer’s disease. The arrival latency and
propagation speed both differed in patients with Alzheimer’s disease.
Our mapping of arterial territories revealed Alzheimer’s
disease-specific modifications, including reversed impulse propagation around
the hippocampi and in parietal cortical areas. The findings imply that pervasive
abnormality in (peri)vascular CSF impulse propagation compromises vascular
impulse propagation and subsequently glymphatic brain clearance of
amyloid-β in Alzheimer’s disease.
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Affiliation(s)
- Zalán Rajna
- Center for Machine Vision and Signal Analysis, University of Oulu, 90570 Oulu, Finland
| | - Heli Mattila
- Oulu Functional Neuroimaging Group, Research Unit of Medical Imaging, Physics and Technology, University of Oulu, 90570 Oulu, Finland
| | - Niko Huotari
- Oulu Functional Neuroimaging Group, Research Unit of Medical Imaging, Physics and Technology, University of Oulu, 90570 Oulu, Finland
| | - Timo Tuovinen
- Oulu Functional Neuroimaging Group, Research Unit of Medical Imaging, Physics and Technology, University of Oulu, 90570 Oulu, Finland
| | - Johanna Krüger
- Research Unit of Clinical Neuroscience, Neurology, University of Oulu, 90570 Oulu, Finland
| | - Sebastian C Holst
- Neurobiology Research Unit, Copenhagen University Hospital, 2100 Copenhagen, Denmark
| | - Vesa Korhonen
- Department of Diagnostic Radiology, Medical Research Center, Oulu University Hospital, 90220 Oulu, Finland
| | - Anne M Remes
- Research Unit of Clinical Neuroscience, Neurology, University of Oulu, 90570 Oulu, Finland
| | - Tapio Seppänen
- Center for Machine Vision and Signal Analysis, University of Oulu, 90570 Oulu, Finland
| | - Jürgen Hennig
- Department of Radiology, Medical Physics, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, 79110 Freiburg, Germany
| | - Maiken Nedergaard
- Center for Translational Neuromedicine, University of Rochester Medical Center, Rochester, NY 14642, USA
| | - Vesa Kiviniemi
- Oulu Functional Neuroimaging Group, Research Unit of Medical Imaging, Physics and Technology, University of Oulu, 90570 Oulu, Finland
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16
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Kotila A, Hyvärinen A, Mäkinen L, Leinonen E, Hurtig T, Ebeling H, Korhonen V, Kiviniemi VJ, Loukusa S. Processing of pragmatic communication in ASD: a video-based brain imaging study. Sci Rep 2020; 10:21739. [PMID: 33303942 PMCID: PMC7729953 DOI: 10.1038/s41598-020-78874-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Accepted: 11/30/2020] [Indexed: 01/24/2023] Open
Abstract
Social and pragmatic difficulties in autism spectrum disorder (ASD) are widely recognized, although their underlying neural level processing is not well understood. The aim of this study was to examine the activity of the brain network components linked to social and pragmatic understanding in order to reveal whether complex socio-pragmatic events evoke differences in brain activity between the ASD and control groups. Nineteen young adults (mean age 23.6 years) with ASD and 19 controls (mean age 22.7 years) were recruited for the study. The stimulus data consisted of video clips showing complex social events that demanded processing of pragmatic communication. In the analysis, the functional magnetic resonance imaging signal responses of the selected brain network components linked to social and pragmatic information processing were compared. Although the processing of the young adults with ASD was similar to that of the control group during the majority of the social scenes, differences between the groups were found in the activity of the social brain network components when the participants were observing situations with concurrent verbal and non-verbal communication events. The results suggest that the ASD group had challenges in processing concurrent multimodal cues in complex pragmatic communication situations.
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Affiliation(s)
- Aija Kotila
- Research Unit of Logopedics, Faculty of Humanities, University of Oulu, Oulu, Finland.
| | - Aapo Hyvärinen
- Department of Computer Science, University of Helsinki, Helsinki, Finland
| | - Leena Mäkinen
- Research Unit of Logopedics, Faculty of Humanities, University of Oulu, Oulu, Finland
| | - Eeva Leinonen
- Office of the Vice Chancellor, Murdoch University, Murdoch, WA, Australia
| | - Tuula Hurtig
- Research Unit of Clinical Neuroscience, Psychiatry, University of Oulu, Oulu, Finland
- PEDEGO Research Unit, The Faculty of Medicine, University of Oulu, Oulu, Finland
- Department of Child Psychiatry, Faculty of Medicine, Institute of Clinical Medicine, Oulu University Hospital, Oulu, Finland
| | - Hanna Ebeling
- PEDEGO Research Unit, The Faculty of Medicine, University of Oulu, Oulu, Finland
- Department of Child Psychiatry, Faculty of Medicine, Institute of Clinical Medicine, Oulu University Hospital, Oulu, Finland
| | - Vesa Korhonen
- Department of Diagnostic Radiology, Medical Research Center (MRC), University and University Hospital of Oulu, Oulu, Finland
- Research Unit of Medical Imaging, Physics and Technology, The Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Vesa J Kiviniemi
- Department of Diagnostic Radiology, Medical Research Center (MRC), University and University Hospital of Oulu, Oulu, Finland
- Research Unit of Medical Imaging, Physics and Technology, The Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Soile Loukusa
- Research Unit of Logopedics, Faculty of Humanities, University of Oulu, Oulu, Finland
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17
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Kotila A, Järvelä M, Korhonen V, Loukusa S, Hurtig T, Ebeling H, Kiviniemi V, Raatikainen V. Atypical Inter-Network Deactivation Associated With the Posterior Default-Mode Network in Autism Spectrum Disorder. Autism Res 2020; 14:248-264. [PMID: 33206471 DOI: 10.1002/aur.2433] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 10/27/2020] [Accepted: 10/28/2020] [Indexed: 12/13/2022]
Abstract
Previous studies have suggested that atypical deactivation of functional brain networks contributes to the complex cognitive and behavioral profile associated with autism spectrum disorder (ASD). However, these studies have not considered the temporal dynamics of deactivation mechanisms between the networks. In this study, we examined (a) mutual deactivation and (b) mutual activation-deactivation (i.e., anticorrelated) time-lag patterns between resting-state networks (RSNs) in young adults with ASD (n = 20) and controls (n = 20) by applying the recently defined dynamic lag analysis (DLA) method, which measures time-lag variations peak-by-peak between the networks. In order to achieve temporally accurate lag patterns, the brain imaging data was acquired with a fast functional magnetic resonance imaging (fMRI) sequence (TR = 100 ms). Group-level independent component analysis was used to identify 16 RSNs for the DLA. We found altered mutual deactivation timings in ASD in (a) three of the deactivated and (b) two of the transiently anticorrelated (activated-deactivated) RSN pairs, which survived the strict threshold for significance of surrogate data. Of the significant RSN pairs, 80% included the posterior default-mode network (DMN). We propose that temporally altered deactivation mechanisms, including timings and directionality, between the posterior DMN and RSNs mediating processing of socially relevant information may contribute to the ASD phenotype. LAY SUMMARY: To understand autistic traits on a neural level, we examined temporal fluctuations in information flow between brain regions in young adults with autism spectrum disorder (ASD) and controls. We used a fast neuroimaging procedure to investigate deactivation mechanisms between brain regions. We found that timings and directionality of communication between certain brain regions were temporally altered in ASD, suggesting atypical deactivation mechanisms associated with the posterior default-mode network.
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Affiliation(s)
- Aija Kotila
- Research Unit of Logopedics, the Faculty of Humanities, University of Oulu, Oulu, Finland
| | - Matti Järvelä
- Research Unit of Medical Imaging, Physics and Technology, the Faculty of Medicine, University of Oulu, Oulu, Finland.,Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland
| | - Vesa Korhonen
- Research Unit of Medical Imaging, Physics and Technology, the Faculty of Medicine, University of Oulu, Oulu, Finland.,Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland
| | - Soile Loukusa
- Research Unit of Logopedics, the Faculty of Humanities, University of Oulu, Oulu, Finland
| | - Tuula Hurtig
- Research Unit of Clinical Neuroscience, Psychiatry, University of Oulu, Oulu, Finland.,Clinic of Child Psychiatry, Oulu University Hospital and PEDEGO Research Unit, University of Oulu, Oulu, Finland
| | - Hanna Ebeling
- Clinic of Child Psychiatry, Oulu University Hospital and PEDEGO Research Unit, University of Oulu, Oulu, Finland
| | - Vesa Kiviniemi
- Research Unit of Medical Imaging, Physics and Technology, the Faculty of Medicine, University of Oulu, Oulu, Finland.,Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland
| | - Ville Raatikainen
- Research Unit of Medical Imaging, Physics and Technology, the Faculty of Medicine, University of Oulu, Oulu, Finland.,Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland
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18
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Järvelä M, Raatikainen V, Kotila A, Kananen J, Korhonen V, Uddin LQ, Ansakorpi H, Kiviniemi V. Lag Analysis of Fast fMRI Reveals Delayed Information Flow Between the Default Mode and Other Networks in Narcolepsy. Cereb Cortex Commun 2020; 1:tgaa073. [PMID: 34296133 PMCID: PMC8153076 DOI: 10.1093/texcom/tgaa073] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Revised: 09/29/2020] [Accepted: 09/29/2020] [Indexed: 11/12/2022] Open
Abstract
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.
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Affiliation(s)
- M Järvelä
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, 90220 Oulu, Finland
| | - V Raatikainen
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, 90220 Oulu, Finland
| | - A Kotila
- Research Unit of Logopedics, University of Oulu, 90014 Oulu, Finland
| | - J Kananen
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, 90220 Oulu, Finland
| | - V Korhonen
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, 90220 Oulu, Finland
| | - L Q Uddin
- Department of Psychology, University of Miami, Coral Gables, 33124 FL, USA
| | - H Ansakorpi
- Research Unit of Clinical Neuroscience, Neurology, University of Oulu, 90014 Oulu, Finland
| | - V Kiviniemi
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, 90220 Oulu, Finland
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19
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Kananen J, Helakari H, Korhonen V, Huotari N, Järvelä M, Raitamaa L, Raatikainen V, Rajna Z, Tuovinen T, Nedergaard M, Jacobs J, LeVan P, Ansakorpi H, Kiviniemi V. Respiratory-related brain pulsations are increased in epilepsy-a two-centre functional MRI study. Brain Commun 2020; 2:fcaa076. [PMID: 32954328 PMCID: PMC7472909 DOI: 10.1093/braincomms/fcaa076] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Revised: 04/29/2020] [Accepted: 05/05/2020] [Indexed: 01/03/2023] Open
Abstract
Resting-state functional MRI has shown potential for detecting changes in cerebral blood oxygen level-dependent signal in patients with epilepsy, even in the absence of epileptiform activity. Furthermore, it has been suggested that coefficient of variation mapping of fast functional MRI signal may provide a powerful tool for the identification of intrinsic brain pulsations in neurological diseases such as dementia, stroke and epilepsy. In this study, we used fast functional MRI sequence (magnetic resonance encephalography) to acquire ten whole-brain images per second. We used the functional MRI data to compare physiological brain pulsations between healthy controls (n = 102) and patients with epilepsy (n = 33) and furthermore to drug-naive seizure patients (n = 9). Analyses were performed by calculating coefficient of variation and spectral power in full band and filtered sub-bands. Brain pulsations in the respiratory-related frequency sub-band (0.11-0.51 Hz) were significantly (P < 0.05) increased in patients with epilepsy, with an increase in both signal variance and power. At the individual level, over 80% of medicated and drug-naive seizure patients exhibited areas of abnormal brain signal power that correlated well with the known clinical diagnosis, while none of the controls showed signs of abnormality with the same threshold. The differences were most apparent in the basal brain structures, respiratory centres of brain stem, midbrain and temporal lobes. Notably, full-band, very low frequency (0.01-0.1 Hz) and cardiovascular (0.8-1.76 Hz) brain pulses showed no differences between groups. This study extends and confirms our previous results of abnormal fast functional MRI signal variance in epilepsy patients. Only respiratory-related brain pulsations were clearly increased with no changes in either physiological cardiorespiratory rates or head motion between the subjects. The regional alterations in brain pulsations suggest that mechanisms driving the cerebrospinal fluid homeostasis may be altered in epilepsy. Magnetic resonance encephalography has both increased sensitivity and high specificity for detecting the increased brain pulsations, particularly in times when other tools for locating epileptogenic areas remain inconclusive.
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Affiliation(s)
- Janne Kananen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| | - Heta Helakari
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| | - Vesa Korhonen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| | - Niko Huotari
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| | - Matti Järvelä
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| | - Lauri Raitamaa
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| | - Ville Raatikainen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| | - Zalan Rajna
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Center for Machine Vision and Signal Analysis (CMVS), University of Oulu, Oulu 90014, Finland
| | - Timo Tuovinen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
| | - Maiken Nedergaard
- Center for Translational Neuromedicine, Department of Neurosurgery, University of Rochester Medical Center, Rochester, NY 14642, USA
- Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Julia Jacobs
- Department of Pediatric Neurology and Muscular Disease, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg 79110, Germany
- Department of Paediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
- Department of Neuroscience, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
- Hotchkiss Brain Institute and Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, AB T2N 4N1, Canada
| | - Pierre LeVan
- Department of Paediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
- Department of Neuroscience, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
- Hotchkiss Brain Institute and Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, AB T2N 4N1, Canada
- Department of Radiology, Medical Physics, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg 79110, Germany
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
| | - Hanna Ansakorpi
- Medical Research Center (MRC), Oulu 90220, Finland
- Research Unit of Neuroscience, Neurology, University of Oulu, Oulu 90220, Finland
- Department of Neurology, Oulu University Hospital, Oulu 90029, Finland
| | - Vesa Kiviniemi
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland
- Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu 90220, Finland
- Medical Research Center (MRC), Oulu 90220, Finland
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20
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Raitamaa L, Korhonen V, Huotari N, Raatikainen V, Hautaniemi T, Kananen J, Rasila A, Helakari H, Zienkiewicz A, Myllylä T, Borchardt V, Kiviniemi V. Breath hold effect on cardiovascular brain pulsations - A multimodal magnetic resonance encephalography study. J Cereb Blood Flow Metab 2019; 39:2471-2485. [PMID: 30204040 PMCID: PMC6893986 DOI: 10.1177/0271678x18798441] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Ultra-fast functional magnetic resonance encephalography (MREG) enables separate assessment of cardiovascular, respiratory, and vasomotor waves from brain pulsations without temporal aliasing. We examined effects of breath hold- (BH) related changes on cardiovascular brain pulsations using MREG to study the physiological nature of cerebrovascular reactivity. We used alternating 32 s BH and 88 s resting normoventilation (NV) to change brain pulsations during MREG combined with simultaneously measured respiration, continuous non-invasive blood pressure, and cortical near-infrared spectroscopy (NIRS) in healthy volunteers. Changes in classical resting-state network BOLD-like signal and cortical blood oxygenation were reproduced based on MREG and NIRS signals. Cardiovascular pulsation amplitudes of MREG signal from anterior cerebral artery, oxygenated hemoglobin concentration in frontal cortex, and blood pressure decreased after BH. MREG cardiovascular pulse amplitudes in cortical areas and sagittal sinus increased, while cerebrospinal fluid and white matter remained unchanged. Respiratory centers in the brainstem - hypothalamus - thalamus - amygdala network showed strongest increases in cardiovascular pulsation amplitude. The spatial propagation of averaged cardiovascular impulses altered as a function of successive BH runs. The spread of cardiovascular pulse cycles exhibited a decreasing spatial similarity over time. MREG portrayed spatiotemporally accurate respiratory network activity and cardiovascular pulsation dynamics related to BH challenges at an unpreceded high temporal resolution.
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Affiliation(s)
- Lauri Raitamaa
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu, Finland
| | - Vesa Korhonen
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu, Finland.,Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland
| | - Niko Huotari
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu, Finland
| | - Ville Raatikainen
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu, Finland
| | - Taneli Hautaniemi
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu, Finland
| | - Janne Kananen
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu, Finland
| | - Aleksi Rasila
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu, Finland
| | - Heta Helakari
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu, Finland
| | - Aleksandra Zienkiewicz
- Biomedical Sensors and Measurement Systems Group, Optoelectronics and Measurement Techniques Unit, University of Oulu, Oulu, Finland
| | - Teemu Myllylä
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu, Finland.,Biomedical Sensors and Measurement Systems Group, Optoelectronics and Measurement Techniques Unit, University of Oulu, Oulu, Finland
| | - Viola Borchardt
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu, Finland
| | - Vesa Kiviniemi
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu, Finland.,Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland
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21
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Raatikainen V, Korhonen V, Borchardt V, Huotari N, Helakari H, Kananen J, Raitamaa L, Joskitt L, Loukusa S, Hurtig T, Ebeling H, Uddin LQ, Kiviniemi V. Dynamic lag analysis reveals atypical brain information flow in autism spectrum disorder. Autism Res 2019; 13:244-258. [PMID: 31637863 PMCID: PMC7027814 DOI: 10.1002/aur.2218] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Revised: 08/28/2019] [Accepted: 09/16/2019] [Indexed: 02/06/2023]
Abstract
This study investigated whole‐brain dynamic lag pattern variations between neurotypical (NT) individuals and individuals with autism spectrum disorder (ASD) by applying a novel technique called dynamic lag analysis (DLA). The use of 3D magnetic resonance encephalography data with repetition time = 100 msec enables highly accurate analysis of the spread of activity between brain networks. Sixteen resting‐state networks (RSNs) with the highest spatial correlation between NT individuals (n = 20) and individuals with ASD (n = 20) were analyzed. The dynamic lag pattern variation between each RSN pair was investigated using DLA, which measures time lag variation between each RSN pair combination and statistically defines how these lag patterns are altered between ASD and NT groups. DLA analyses indicated that 10.8% of the 120 RSN pairs had statistically significant (P‐value <0.003) dynamic lag pattern differences that survived correction with surrogate data thresholding. Alterations in lag patterns were concentrated in salience, executive, visual, and default‐mode networks, supporting earlier findings of impaired brain connectivity in these regions in ASD. 92.3% and 84.6% of the significant RSN pairs revealed shorter mean and median temporal lags in ASD versus NT, respectively. Taken together, these results suggest that altered lag patterns indicating atypical spread of activity between large‐scale functional brain networks may contribute to the ASD phenotype. Autism Res 2020, 13: 244–258. © 2019 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals, Inc. Lay Summary Autism spectrum disorder (ASD) is characterized by atypical neurodevelopment. Using an ultra‐fast neuroimaging procedure, we investigated communication across brain regions in adults with ASD compared with neurotypical (NT) individuals. We found that ASD individuals had altered information flow patterns across brain regions. Atypical patterns were concentrated in salience, executive, visual, and default‐mode network areas of the brain that have previously been implicated in the pathophysiology of the disorder.
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Affiliation(s)
- Ville Raatikainen
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland.,Research Unit of Medical Imaging, Physics, and Technology, The Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Vesa Korhonen
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland.,Research Unit of Medical Imaging, Physics, and Technology, The Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Viola Borchardt
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland.,Research Unit of Medical Imaging, Physics, and Technology, The Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Niko Huotari
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland.,Research Unit of Medical Imaging, Physics, and Technology, The Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Heta Helakari
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland.,Research Unit of Medical Imaging, Physics, and Technology, The Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Janne Kananen
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland.,Research Unit of Medical Imaging, Physics, and Technology, The Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Lauri Raitamaa
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland.,Research Unit of Medical Imaging, Physics, and Technology, The Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Leena Joskitt
- Clinic of Child Psychiatry, Oulu University Hospital, Oulu, Finland
| | - Soile Loukusa
- Research Unit of Logopedics, Faculty of Humanities, University of Oulu, Oulu, Finland
| | - Tuula Hurtig
- Clinic of Child Psychiatry, Oulu University Hospital, Oulu, Finland
| | - Hanna Ebeling
- Clinic of Child Psychiatry, Oulu University Hospital, Oulu, Finland
| | - Lucina Q Uddin
- Department of Psychology, University of Miami, Coral Gables, Florida
| | - Vesa Kiviniemi
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland.,Research Unit of Medical Imaging, Physics, and Technology, The Faculty of Medicine, University of Oulu, Oulu, Finland
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22
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Korhonen V, Mattsson M, Inkinen M, Toom A. Understanding the Multidimensional Nature of Student Engagement During the First Year of Higher Education. Front Psychol 2019; 10:1056. [PMID: 31133948 PMCID: PMC6524002 DOI: 10.3389/fpsyg.2019.01056] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2019] [Accepted: 04/24/2019] [Indexed: 12/18/2022] Open
Abstract
In the description of the complex relationship between individual students and their education context, as well as understanding of questions related to progression, retention or dropouts in higher education, student engagement is considered the primary construct. In particular, the significance of the first year of higher education in terms of engagement is decisive. We aim at developing a multidimensional conceptualization of engagement and utilized network analysis. Data were collected as part of the annual Student Barometer survey in Finland during the 2012-2013 academic year, and we gathered a nationally representative sample (n = 2422) of first-year students in different disciplines at 13 Finnish universities. Network analysis confirmed the multidimensional process model of engagement and its six dimensions. The central dimensions of engagement are identity and sense of belonging, which develop in the interplay between individual and collective dimensions as a long-term process. Additional network analyses with covariates identified positive and negative factors that affect engagement. The study adds new perspectives to existing knowledge of engagement. It is important to understand the process-like nature of engagement and make visible factors affecting the process. Based on these findings, we provide novel practical recommendations for interventions for university students who struggle with engagement during their first year.
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Affiliation(s)
- Vesa Korhonen
- Faculty of Education and Culture, Tampere University, Tampere, Finland
| | - Markus Mattsson
- Centre for University Teaching and Learning, Faculty of Educational Sciences, University of Helsinki, Helsinki, Finland
| | - Mikko Inkinen
- Centre for University Teaching and Learning, Faculty of Educational Sciences, University of Helsinki, Helsinki, Finland
| | - Auli Toom
- Centre for University Teaching and Learning, Faculty of Educational Sciences, University of Helsinki, Helsinki, Finland
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23
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Kananen J, Tuovinen T, Ansakorpi H, Rytky S, Helakari H, Huotari N, Raitamaa L, Raatikainen V, Rasila A, Borchardt V, Korhonen V, LeVan P, Nedergaard M, Kiviniemi V. Altered physiological brain variation in drug-resistant epilepsy. Brain Behav 2018; 8:e01090. [PMID: 30112813 PMCID: PMC6160661 DOI: 10.1002/brb3.1090] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2018] [Revised: 07/04/2018] [Accepted: 07/08/2018] [Indexed: 12/26/2022] Open
Abstract
INTRODUCTION Functional magnetic resonance imaging (fMRI) combined with simultaneous electroencephalography (EEG-fMRI) has become a major tool in mapping epilepsy sources. In the absence of detectable epileptiform activity, the resting state fMRI may still detect changes in the blood oxygen level-dependent signal, suggesting intrinsic alterations in the underlying brain physiology. METHODS In this study, we used coefficient of variation (CV) of critically sampled 10 Hz ultra-fast fMRI (magnetoencephalography, MREG) signal to compare physiological variance between healthy controls (n = 10) and patients (n = 10) with drug-resistant epilepsy (DRE). RESULTS We showed highly significant voxel-level (p < 0.01, TFCE-corrected) increase in the physiological variance in DRE patients. At individual level, the elevations range over three standard deviations (σ) above the control mean (μ) CVMREG values solely in DRE patients, enabling patient-specific mapping of elevated physiological variance. The most apparent differences in group-level analysis are found on white matter, brainstem, and cerebellum. Respiratory (0.12-0.4 Hz) and very-low-frequency (VLF = 0.009-0.1 Hz) signal variances were most affected. CONCLUSIONS The CVMREG increase was not explained by head motion or physiological cardiorespiratory activity, that is, it seems to be linked to intrinsic physiological pulsations. We suggest that intrinsic brain pulsations play a role in DRE and that critically sampled fMRI may provide a powerful tool for their identification.
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Affiliation(s)
- Janne Kananen
- Department of Diagnostic Radiology, Medical Research Center, Oulu University Hospital, Oulu, Finland.,Oulu Functional NeuroImaging-Group, Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland
| | - Timo Tuovinen
- Department of Diagnostic Radiology, Medical Research Center, Oulu University Hospital, Oulu, Finland.,Oulu Functional NeuroImaging-Group, Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland
| | - Hanna Ansakorpi
- Research Unit of Neuroscience, Neurology, University of Oulu, Oulu, Finland.,Department of Neurology and Medical Research Center Oulu, Oulu University Hospital, Oulu, Finland
| | - Seppo Rytky
- Department of Clinical Neurophysiology, Medical Research Center Oulu, Oulu University Hospital, Oulu, Finland
| | - Heta Helakari
- Department of Diagnostic Radiology, Medical Research Center, Oulu University Hospital, Oulu, Finland.,Oulu Functional NeuroImaging-Group, Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland
| | - Niko Huotari
- Department of Diagnostic Radiology, Medical Research Center, Oulu University Hospital, Oulu, Finland.,Oulu Functional NeuroImaging-Group, Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland
| | - Lauri Raitamaa
- Department of Diagnostic Radiology, Medical Research Center, Oulu University Hospital, Oulu, Finland.,Oulu Functional NeuroImaging-Group, Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland
| | - Ville Raatikainen
- Department of Diagnostic Radiology, Medical Research Center, Oulu University Hospital, Oulu, Finland.,Oulu Functional NeuroImaging-Group, Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland
| | - Aleksi Rasila
- Department of Diagnostic Radiology, Medical Research Center, Oulu University Hospital, Oulu, Finland.,Oulu Functional NeuroImaging-Group, Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland
| | - Viola Borchardt
- Department of Diagnostic Radiology, Medical Research Center, Oulu University Hospital, Oulu, Finland.,Oulu Functional NeuroImaging-Group, Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland
| | - Vesa Korhonen
- Department of Diagnostic Radiology, Medical Research Center, Oulu University Hospital, Oulu, Finland.,Oulu Functional NeuroImaging-Group, Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland
| | - Pierre LeVan
- Faculty of Medicine, Department of Radiology - Medical Physics, University Medical Center Freiburg, University of Freiburg, Freiburg, Germany
| | - Maiken Nedergaard
- Center for Translational Neuromedicine, Department of Neurosurgery, University of Rochester, Rochester, New York.,Faculty of Health and Medical Sciences, Center for Basic and Translational Neuroscience, University of Copenhagen, Copenhagen, Denmark
| | - Vesa Kiviniemi
- Department of Diagnostic Radiology, Medical Research Center, Oulu University Hospital, Oulu, Finland.,Oulu Functional NeuroImaging-Group, Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland
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24
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Myllylä T, Harju M, Korhonen V, Bykov A, Kiviniemi V, Meglinski I. Assessment of the dynamics of human glymphatic system by near-infrared spectroscopy. J Biophotonics 2018; 11:e201700123. [PMID: 28802090 DOI: 10.1002/jbio.201700123] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/14/2017] [Revised: 07/25/2017] [Accepted: 08/10/2017] [Indexed: 06/07/2023]
Abstract
Fluctuations in brain water content has attracted increasing interest, particularly as regards studies of the glymphatic system, which is connected with the complex organization of dural lymphatic vessels, responsible for cleaning tissue. Disturbances of glymphatic circulation are associated with several brain disorders, including dementia. This article introduces an approach to noninvasive measurement of water dynamics in the human brain utilizing near-infrared spectroscopy (NIRS). We demonstrate the possibility to sense dynamic variations of water content between the skull and grey matter, for instance, in the subarachnoid space. Measured fluctuations in water content, especially in the cerebrospinal fluid (CSF), are assumed to be correlated with the dynamics of glymphatic circulation. The sampling volume for the NIRS optode was estimated by Monte Carlo modelling for the wavelengths of 660, 740, 830 and 980 nm. In addition, using combinations of these wavelengths, this article presents the calculation models for quantifying water and haemodynamics. The presented NIRS technique allows long-term functional brain monitoring, including sleeping time. Furthermore, it is used in combination with different magnetic neuroimaging techniques, particularly magnetic resonance encephalography. Using the combined setup, we report the preliminary results on the interaction between CSF and blood oxygen level-dependent fluctuations.
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Affiliation(s)
- Teemu Myllylä
- Optoelectronics and Measurement Techniques Unit, University of Oulu, Oulu, Finland
- Oulu Functional Neuroimaging Group, Research Unit of Medical Imaging, Physics and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Markus Harju
- Inverse Problems Group, Department of Mathematical Sciences, University of Oulu, Oulu, Finland
| | - Vesa Korhonen
- Oulu Functional Neuroimaging Group, Research Unit of Medical Imaging, Physics and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland
| | - Alexander Bykov
- Optoelectronics and Measurement Techniques Unit, University of Oulu, Oulu, Finland
- Department of Photonics and Optical Information Technology, ITMO University, St Petersburg, Russia
| | - Vesa Kiviniemi
- Oulu Functional Neuroimaging Group, Research Unit of Medical Imaging, Physics and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland
| | - Igor Meglinski
- Optoelectronics and Measurement Techniques Unit, University of Oulu, Oulu, Finland
- Department of Photonics and Optical Information Technology, ITMO University, St Petersburg, Russia
- Institute of Biology, Irkutsk State University, Irkutsk, Russia
- Institute of Engineering Physics for Biomedicine, National Research Nuclear University MEPhI (Moscow Engineering Physics Institute), Moscow, Russia
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25
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Keinänen T, Rytky S, Korhonen V, Huotari N, Nikkinen J, Tervonen O, Palva JM, Kiviniemi V. Fluctuations of the EEG-fMRI correlation reflect intrinsic strength of functional connectivity in default mode network. J Neurosci Res 2018; 96:1689-1698. [PMID: 29761531 DOI: 10.1002/jnr.24257] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2018] [Revised: 04/20/2018] [Accepted: 04/23/2018] [Indexed: 01/14/2023]
Abstract
Both functional magnetic resonance imaging (fMRI) and electrophysiological recordings have revealed that resting-state functional connectivity is temporally variable in human brain. Combined full-band electroencephalography-fMRI (fbEEG-fMRI) studies have shown that infraslow (<.1 Hz) fluctuations in EEG scalp potential are correlated with the blood-oxygen-level-dependent (BOLD) fMRI signals and that also this correlation appears variable over time. Here, we used simultaneous fbEEG-fMRI to test the hypothesis that correlation dynamics between BOLD and fbEEG signals could be explained by fluctuations in the activation properties of resting-state networks (RSNs) such as the extent or strength of their activation. We used ultrafast magnetic resonance encephalography (MREG) fMRI to enable temporally accurate and statistically robust short-time-window comparisons of infra-slow fbEEG and BOLD signals. We found that the temporal fluctuations in the fbEEG-BOLD correlation were dependent on RSN connectivity strength, but not on the mean signal level or magnitude of RSN activation or motion during scanning. Moreover, the EEG-fMRI correlations were strongest when the intrinsic RSN connectivity was strong and close to the pial surface. Conversely, weak fbEEG-BOLD correlations were attributable to periods of less coherent or spatially more scattered intrinsic RSN connectivity, or RSN activation in deeper cerebral structures. The results thus show that the on-average low correlations between infra-slow EEG and BOLD signals are, in fact, governed by the momentary coherence and depth of the underlying RSN activation, and may reach systematically high values with appropriate source activities. These findings further consolidate the notion of slow scalp potentials being directly coupled to hemodynamic fluctuations.
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Affiliation(s)
- Tuija Keinänen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.,Department of Clinical Neurophysiology, Oulu University Hospital, Oulu, Finland
| | - Seppo Rytky
- Department of Clinical Neurophysiology, Oulu University Hospital, Oulu, Finland
| | - Vesa Korhonen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
| | - Niko Huotari
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
| | - Juha Nikkinen
- Department of Oncology and Radiotherapy, Oulu University Hospital, Oulu, Finland
| | - Osmo Tervonen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
| | - J Matias Palva
- Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Vesa Kiviniemi
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
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26
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Adam A, Robison J, Lu J, Jose R, Badran N, Vivas-Buitrago T, Rigamonti D, Sattar A, Omoush O, Hammad M, Dawood M, Maghaslah M, Belcher T, Carson K, Hoffberger J, Jusué Torres I, Foley S, Yasar S, Thai QA, Wemmer J, Klinge P, Al-Mutawa L, Al-Ghamdi H, Carson KA, Asgari M, de Zélicourt D, Kurtcuoglu V, Garnotel S, Salmon S, Balédent O, Lokossou A, Page G, Balardy L, Czosnyka Z, Payoux P, Schmidt EA, Zitoun M, Sevestre MA, Alperin N, Baudracco I, Craven C, Matloob S, Thompson S, Haylock Vize P, Thorne L, Watkins LD, Toma AK, Bechter K, Pong AC, Jugé L, Bilston LE, Cheng S, Bradley W, Hakim F, Ramón JF, Cárdenas MF, Davidson JS, García C, González D, Bermúdez S, Useche N, Mejía JA, Mayorga P, Cruz F, Martinez C, Matiz MC, Vallejo M, Ghotme K, Soto HA, Riveros D, Buitrago A, Mora M, Murcia L, Bermudez S, Cohen D, Dasgupta D, Curtis C, Domínguez L, Remolina AJ, Grijalba MA, Whitehouse KJ, Edwards RJ, Eleftheriou A, Lundin F, Fountas KN, Kapsalaki EZ, Smisson HF, Robinson JS, Fritsch MJ, Arouk W, Garzon M, Kang M, Sandhu K, Baghawatti D, Aquilina K, James G, Thompson D, Gehlen M, Schmid Daners M, Eklund A, Malm J, Gomez D, Guerra M, Jara M, Flores M, Vío K, Moreno I, Rodríguez S, Ortega E, Rodríguez EM, McAllister JP, Guerra MM, Morales DM, Sival D, Jimenez A, Limbrick DD, Ishikawa M, Yamada S, Yamamoto K, Junkkari A, Häyrinen A, Rauramaa T, Sintonen H, Nerg O, Koivisto AM, Roine RP, Viinamäki H, Soininen H, Luikku A, Jääskeläinen JE, Leinonen V, Kehler U, Lilja-Lund O, Kockum K, Larsson EM, Riklund K, Söderström L, Hellström P, Laurell K, Kojoukhova M, Sutela A, Vanninen R, Vanha KI, Timonen M, Rummukainen J, Korhonen V, Helisalmi S, Solje E, Remes AM, Huovinen J, Paananen J, Hiltunen M, Kurki M, Martin B, Loth F, Luciano M, Luikku AJ, Hall A, Herukka SK, Mattila J, Lötjönen J, Alafuzoff I, Jurjević I, Miyajima M, Nakajima M, Murai H, Shin T, Kawaguchi D, Akiba C, Ogino I, Karagiozov K, Arai H, Reis RC, Teixeira MJ, Valêncio CG, da Vigua D, Almeida-Lopes L, Mancini MW, Pinto FCG, Maykot RH, Calia G, Tornai J, Silvestre SSS, Mendes G, Sousa V, Bezerra B, Dutra P, Modesto P, Oliveira MF, Petitto CE, Pulhorn H, Chandran A, McMahon C, Rao AS, Jumaly M, Solomon D, Moghekar A, Relkin N, Hamilton M, Katzen H, Williams M, Bach T, Zuspan S, Holubkov R, Rigamonti A, Clemens G, Sharkey P, Sanyal A, Sankey E, Rigamonti K, Naqvi S, Hung A, Schmidt E, Ory-Magne F, Gantet P, Guenego A, Januel AC, Tall P, Fabre N, Mahieu L, Cognard C, Gray L, Buttner-Ennever JA, Takagi K, Onouchi K, Thompson SD, Thorne LD, Tully HM, Wenger TL, Kukull WA, Doherty D, Dobyns WB, Moran D, Vakili S, Patel MA, Elder B, Goodwin CR, Crawford JA, Pletnikov MV, Xu J, Blitz A, Herzka DA, Guerrero-Cazares H, Quiñones-Hinojosa A, Mori S, Saavedra P, Treviño H, Maitani K, Ziai WC, Eslami V, Nekoovaght-Tak S, Dlugash R, Yenokyan G, McBee N, Hanley DF. Abstracts from Hydrocephalus 2016. Fluids Barriers CNS 2017; 14:15. [PMID: 28929972 PMCID: PMC5471936 DOI: 10.1186/s12987-017-0054-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Affiliation(s)
- A Adam
- Johns Hopkins University, Baltimore, MD, USA.,Department of Neurosurgery, Johns Hopkins University, Baltimore, MD, USA.,Johns Hopkins Biostatistics Center, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.,Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - J Robison
- Johns Hopkins University, Baltimore, MD, USA.,Department of Neurosurgery, Johns Hopkins University, Baltimore, MD, USA.,Department of Neurosurgery, Johns Hopkins University, School of Medicine, Baltimore, MD, USA
| | - J Lu
- Johns Hopkins University, Baltimore, MD, USA.,Department of Neurosurgery, Johns Hopkins University, Baltimore, MD, USA.,Department of Neurosurgery, Johns Hopkins University, School of Medicine, Baltimore, MD, USA
| | - R Jose
- Johns Hopkins Aramco Healthcare, Dhahran, Saudi Arabia
| | - N Badran
- Johns Hopkins Aramco Healthcare, Dhahran, Saudi Arabia
| | - T Vivas-Buitrago
- Johns Hopkins University, Baltimore, MD, USA.,Department of Neurosurgery, Johns Hopkins University, Baltimore, MD, USA.,Department of Neurosurgery, Johns Hopkins University, School of Medicine, Baltimore, MD, USA
| | - D Rigamonti
- Johns Hopkins University, Baltimore, MD, USA.,Johns Hopkins Aramco Healthcare, Dhahran, Saudi Arabia.,Department of Neurosurgery, Johns Hopkins University, Baltimore, MD, USA.,Department of Neurosurgery, Johns Hopkins University, School of Medicine, Baltimore, MD, USA.,Johns Hopkins Hopkins Aramco Healthcare, Dhahran, Saudi Arabia
| | - A Sattar
- Johns Hopkins Aramco Healthcare, Ras Tanura, Saudi Arabia.,Primary Care, Johns Hopkins Aramco Healthcare, Ras Tanura, Saudi Arabia
| | - O Omoush
- Johns Hopkins Aramco Healthcare, Ras Tanura, Saudi Arabia.,Primary Care, Johns Hopkins Aramco Healthcare, Ras Tanura, Saudi Arabia
| | - M Hammad
- Johns Hopkins Aramco Healthcare, Ras Tanura, Saudi Arabia
| | - M Dawood
- Johns Hopkins Aramco Healthcare, Ras Tanura, Saudi Arabia
| | - M Maghaslah
- Johns Hopkins Aramco Healthcare, Ras Tanura, Saudi Arabia
| | - T Belcher
- Johns Hopkins Aramco Healthcare, Ras Tanura, Saudi Arabia
| | - K Carson
- Department of Neurosurgery, Johns Hopkins University, Baltimore, MD, USA.,Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - J Hoffberger
- Department of Neurosurgery, Johns Hopkins University, Baltimore, MD, USA
| | - I Jusué Torres
- Department of Neurosurgery, Johns Hopkins University, Baltimore, MD, USA.,Department of Neurosurgery, Johns Hopkins University, School of Medicine, Baltimore, MD, USA
| | - S Foley
- Department of Neurosurgery, Rhode Island Hospital, Providence, RI, USA
| | - S Yasar
- Department of Neurosurgery, Johns Hopkins University, Baltimore, MD, USA
| | - Q A Thai
- Department of Neurosurgery, Johns Hopkins University, Baltimore, MD, USA
| | - J Wemmer
- Department of Neurosurgery, Johns Hopkins University, Baltimore, MD, USA
| | - P Klinge
- Department of Neurosurgery, Johns Hopkins University, Baltimore, MD, USA
| | - L Al-Mutawa
- Department of Neurosurgery, Johns Hopkins University, Baltimore, MD, USA
| | - H Al-Ghamdi
- Department of Neurosurgery, Rhode Island Hospital, Providence, RI, USA
| | - K A Carson
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - M Asgari
- The Interface Group, Institute of PhysiologyUniversity of Zurich, Zurich, Switzerland
| | - D de Zélicourt
- The Interface Group, Institute of PhysiologyUniversity of Zurich, Zurich, Switzerland
| | - V Kurtcuoglu
- The Interface Group, Institute of PhysiologyUniversity of Zurich, Zurich, Switzerland.,Institute of Physiology, University of Zurich, Zurich, Switzerland.,Neuroscience Center Zurich and the Zurich Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland
| | - S Garnotel
- BioFlowImage Laboratory, University of Picardie Jules Verne, Amiens, France.,Reims Mathematics Laboratory, University of Reims Champagne-Ardenne, Reims, France.,Image Processing Laboratory, University Hospital of Amiens-Picardie, Amiens, France.,BioFlowImage Laboratory, Department of Medical Image Processing, University Hospital of Picardie Jules Verne, Amiens, France
| | - S Salmon
- Reims Mathematics Laboratory, University of Reims Champagne-Ardenne, Reims, France
| | - O Balédent
- BioFlowImage Laboratory, University of Picardie Jules Verne, Amiens, France.,Image Processing Laboratory, University Hospital of Amiens-Picardie, Amiens, France.,BioFlowImage Laboratory, Department of Medical Image Processing, University Hospital of Picardie Jules Verne, Amiens, France
| | - A Lokossou
- BioFlowImage Laboratory, Department of Medical Image Processing, University Hospital of Picardie Jules Verne, Amiens, France
| | - G Page
- BioFlowImage Laboratory, Department of Medical Image Processing, University Hospital of Picardie Jules Verne, Amiens, France
| | - L Balardy
- Department of Geriatric, University Hospital of Toulouse, Toulouse, France.,Departments of Geriatric, University Hospital of Toulouse, Toulouse, France.,Department of Geriatry, University Hospital Toulouse, Toulouse, France
| | - Z Czosnyka
- Neurosciences department, University of Cambridge, Cambridge, UK.,Brain Physics Lab, Academic Neurosurgery, University of Cambridge, Cambridge, UK
| | - P Payoux
- Department of Nuclear Medicine, University Hospital of Toulouse, Toulouse, France.,Department of Nuclear Medicine, University Hospital Toulouse, Toulouse, France.,INSER TONIC 1014, Toulouse Neuroimaging Center, Toulouse, France
| | - E A Schmidt
- UMR 1214-INSERM/UPS-TONIC Toulouse Neuro-Imaging Center, Toulouse, France.,Department of Neurosurgery, University Hospital of Toulouse, Toulouse, France.,Department of Neurosurgery, University Hospital Toulouse, Toulouse, France
| | - M Zitoun
- BioFlowImage, University Hospital of Picardie Jules Verne, Amiens, France
| | - M A Sevestre
- BioFlowImage, University Hospital of Picardie Jules Verne, Amiens, France
| | - N Alperin
- University of Miami Health System, Miami, FL, USA
| | - I Baudracco
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - C Craven
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - S Matloob
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - S Thompson
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - P Haylock Vize
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - L Thorne
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - L D Watkins
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK.,The National Hospital for Neurology and Neurosurgery, Queen Square, London, UK
| | - A K Toma
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK.,The National Hospital for Neurology and Neurosurgery, Queen Square, London, UK
| | - Karl Bechter
- Department Psychiatry II/Bezirkskliniken, Ulm University, Günzburg, Germany
| | - A C Pong
- Neuroscience Research Australia, Randwick, Australia.,School of Medical Sciences, University of New South Wales, Kensington, Australia
| | - L Jugé
- Neuroscience Research Australia, Randwick, Australia.,School of Medical Sciences, University of New South Wales, Kensington, Australia
| | - L E Bilston
- Neuroscience Research Australia, Randwick, Australia.,Prince of Wales Clinical School, University of New South Wales, Kensington, Australia
| | - S Cheng
- Neuroscience Research Australia, Randwick, Australia.,Department of Engineering, Faculty of Science and Engineering, Macquarie University, Sydney, Australia
| | - W Bradley
- Department of Radiology, University of California San Diego Health System, San Diego, CA, USA
| | - F Hakim
- Department of Surgery, Section of Neurosurgery, Fundación Santa Fe de Bogotá, Bogotá, Colombia.,Neurosurgery Department, Hospital Universitario, Fundación Santafe de Bogota, Bogota, Colombia
| | - J F Ramón
- Department of Surgery, Section of Neurosurgery, Fundación Santa Fe de Bogotá, Bogotá, Colombia.,Grupo de Hidrocefalia con Presión Normal, Hospital Universitario Fundación Santa Fe de Bogotá, Bogotá, Colombia.,Neurosurgery Department, Hospital Universitario, Fundación Santafe de Bogota, Bogota, Colombia
| | - M F Cárdenas
- Department of Surgery, Section of Neurosurgery, Fundación Santa Fe de Bogotá, Bogotá, Colombia
| | - J S Davidson
- Department of Surgery, Section of Neurosurgery, Fundación Santa Fe de Bogotá, Bogotá, Colombia
| | - C García
- Department of Surgery, Section of Neurosurgery, Fundación Santa Fe de Bogotá, Bogotá, Colombia
| | - D González
- Department of Surgery, Section of Neurosurgery, Fundación Santa Fe de Bogotá, Bogotá, Colombia
| | - S Bermúdez
- Department of Diagnostic Imaging, Section of Neuroradiology, Fundación Santa Fe de Bogotá, Bogotá, Colombia
| | - N Useche
- Department of Diagnostic Imaging, Section of Neuroradiology, Fundación Santa Fe de Bogotá, Bogotá, Colombia
| | - J A Mejía
- Grupo de Hidrocefalia con Presión Normal, Hospital Universitario Fundación Santa Fe de Bogotá, Bogotá, Colombia
| | - P Mayorga
- Grupo de Hidrocefalia con Presión Normal, Hospital Universitario Fundación Santa Fe de Bogotá, Bogotá, Colombia
| | - F Cruz
- Grupo de Hidrocefalia con Presión Normal, Hospital Universitario Fundación Santa Fe de Bogotá, Bogotá, Colombia
| | - C Martinez
- Grupo de Hidrocefalia con Presión Normal, Hospital Universitario Fundación Santa Fe de Bogotá, Bogotá, Colombia
| | - M C Matiz
- Grupo de Hidrocefalia con Presión Normal, Hospital Universitario Fundación Santa Fe de Bogotá, Bogotá, Colombia
| | - M Vallejo
- Grupo de Hidrocefalia con Presión Normal, Hospital Universitario Fundación Santa Fe de Bogotá, Bogotá, Colombia
| | - K Ghotme
- Grupo de Hidrocefalia con Presión Normal, Hospital Universitario Fundación Santa Fe de Bogotá, Bogotá, Colombia
| | - H A Soto
- Grupo de Hidrocefalia con Presión Normal, Hospital Universitario Fundación Santa Fe de Bogotá, Bogotá, Colombia
| | - D Riveros
- Grupo de Hidrocefalia con Presión Normal, Hospital Universitario Fundación Santa Fe de Bogotá, Bogotá, Colombia
| | - A Buitrago
- Grupo de Hidrocefalia con Presión Normal, Hospital Universitario Fundación Santa Fe de Bogotá, Bogotá, Colombia
| | - M Mora
- Grupo de Hidrocefalia con Presión Normal, Hospital Universitario Fundación Santa Fe de Bogotá, Bogotá, Colombia
| | - L Murcia
- Grupo de Hidrocefalia con Presión Normal, Hospital Universitario Fundación Santa Fe de Bogotá, Bogotá, Colombia
| | - S Bermudez
- Grupo de Hidrocefalia con Presión Normal, Hospital Universitario Fundación Santa Fe de Bogotá, Bogotá, Colombia
| | - D Cohen
- Grupo de Hidrocefalia con Presión Normal, Hospital Universitario Fundación Santa Fe de Bogotá, Bogotá, Colombia
| | - D Dasgupta
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK
| | - C Curtis
- Department of Microbiology, University College London Hospital NHS Foundation Trust, London, UK
| | - L Domínguez
- Neurosurgery Department, Cartagena University, Cartagena de Indias, Colombia
| | - A J Remolina
- Neurosurgery Department, Cartagena University, Cartagena de Indias, Colombia
| | - M A Grijalba
- Neurosurgery Department, Cartagena University, Cartagena de Indias, Colombia
| | - K J Whitehouse
- Department of Paediatric Neurosurgery, Bristol Royal Hospital for Children, Bristol, UK
| | - R J Edwards
- Department of Paediatric Neurosurgery, Bristol Royal Hospital for Children, Bristol, UK
| | - A Eleftheriou
- Department of Neurology, University Hospital, Linköping, Sweden
| | - F Lundin
- Division of Neuroscience, Department of Clinical and Experimental Medicine (IKE), Linköping University, Linköping, Sweden
| | - K N Fountas
- Department of Neurosurgery, School of Medicine, University of Thessaly, Larisa, Greece
| | - E Z Kapsalaki
- Department of Diagnostic Radiology, School of Medicine, University of Thessaly, Larisa, Greece
| | - H F Smisson
- Department of Neurosurgery, Georgia Neurosurgical Institute, Macon, GA, USA
| | - J S Robinson
- Department of Neurosurgery, Georgia Neurosurgical Institute, Macon, GA, USA
| | - M J Fritsch
- Klinik für Neurochirurgie, Dietrich-Bonhoeffer-Klinikum, Neubrandenburg, Germany
| | - W Arouk
- Klinik für Neurochirurgie, Dietrich-Bonhoeffer-Klinikum, Neubrandenburg, Germany
| | - M Garzon
- Great Ormond Street Hospital, London, UK
| | - M Kang
- Great Ormond Street Hospital, London, UK
| | - K Sandhu
- Great Ormond Street Hospital, London, UK
| | | | - K Aquilina
- Great Ormond Street Hospital, London, UK
| | - G James
- Great Ormond Street Hospital, London, UK
| | - D Thompson
- Great Ormond Street Hospital, London, UK
| | - M Gehlen
- Department of Mechanical and Process Engineering, ETH Zurich, Zurich, Switzerland.,Institute of Physiology, University of Zurich, Zurich, Switzerland
| | - M Schmid Daners
- Department of Mechanical and Process Engineering, ETH Zurich, Zurich, Switzerland
| | - A Eklund
- Department of Radiation Sciences, Umeå University, Umeå, Sweden
| | - J Malm
- Department of Pharmacology and Clinical Neuroscience, Umeå University, Umeå, Sweden
| | - D Gomez
- Neurosurgery Department, Hospital Universitario, Fundación Santafe de Bogota, Bogota, Colombia
| | - M Guerra
- Instituto de Anatomía, Histología y Patología, Facultad de Medicina, UACh, Valdivia, Chile
| | - M Jara
- Instituto de Anatomía, Histología y Patología, Facultad de Medicina, UACh, Valdivia, Chile
| | - M Flores
- Laboratorio de Polímeros, Facultad de Ciencias, UACh, Valdivia, Chile
| | - K Vío
- Instituto de Anatomía, Histología y Patología, Facultad de Medicina, UACh, Valdivia, Chile
| | - I Moreno
- Laboratorio de Polímeros, Facultad de Ciencias, UACh, Valdivia, Chile
| | - S Rodríguez
- Instituto de Anatomía, Histología y Patología, Facultad de Medicina, UACh, Valdivia, Chile
| | - E Ortega
- Instituto de Neurociencias Clínicas, Facultad de Medicina, UACh, Valdivia, Chile
| | - E M Rodríguez
- Instituto de Anatomía, Histología y Patología, Facultad de Medicina, UACh, Valdivia, Chile.,Instituto de Histologia y Patologia, Facultad de Medicina, Universidad Austral de Chile, Valdivia, Chile
| | - J P McAllister
- Department of Neurosurgery, St. Louis Children's Hospital, St. Louis, MO, USA
| | - M M Guerra
- Instituto de Histologia y Patologia, Facultad de Medicina, Universidad Austral de Chile, Valdivia, Chile
| | - D M Morales
- Department of Neurosurgery, St. Louis Children's Hospital, St. Louis, MO, USA
| | - D Sival
- Department of Pediatrics Pathology and Medical Biology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - A Jimenez
- Departamento de Biología Celular, Genética y Fisiología Facultad de Ciencias, Universidad de Malaga, Malaga, Spain
| | - D D Limbrick
- Department of Neurosurgery, St. Louis Children's Hospital, St. Louis, MO, USA.,Department of Pediatrics, St. Louis Children's Hospital, St. Louis, MO, USA
| | - M Ishikawa
- Rakuwa Villa Ilios, Kyoto, Japan.,Normal Pressure Hydrocephalus Center, Otowa Hospital, Kyoto, Japan
| | - S Yamada
- Normal Pressure Hydrocephalus Center, Otowa Hospital, Kyoto, Japan.,Department of Neurosurgery, Otowa Hospital, Kyoto, Japan
| | - K Yamamoto
- Department of Neurosurgery, Otowa Hospital, Kyoto, Japan
| | - A Junkkari
- Neurosurgery of NeuroCenter, Kuopio University Hospital and University of Eastern Finland, Kuopio, Finland.,Neurosurgery of NeuroCenter, Kuopio University Hospital, Kuopio, Finland
| | - A Häyrinen
- Neurosurgery of NeuroCenter, Kuopio University Hospital and University of Eastern Finland, Kuopio, Finland
| | - T Rauramaa
- Department of Pathology, Kuopio University Hospital and University of Eastern Finland, Kuopio, Finland.,Department of Pathology, Kuopio University Hospital, Kuopio, Finland.,Institute of Clinical Medicine-Pathology, University of Eastern Finland, Kuopio, Finland
| | - H Sintonen
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - O Nerg
- Neurology of NeuroCenter, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland.,Neurology of NeuroCenter, Kuopio University Hospital, Kuopio, Finland.,Institute of Clinical Medicine-Neurology, University of Eastern Finland, Kuopio, Finland
| | - A M Koivisto
- Neurology of NeuroCenter, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland.,Unit of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland.,Neurology of NeuroCenter, Kuopio University Hospital, Kuopio, Finland.,Institute of Clinical Medicine-Neurology, University of Eastern Finland, Kuopio, Finland.,Department of Neurology, Kuopio University Hospital, Kuopio, Finland
| | - R P Roine
- University of Eastern Finland, Kuopio Finland and Helsinki and Uusimaa Hospital DistrictGroup Administration, Helsinki, Finland
| | - H Viinamäki
- Department of Psychiatry, Kuopio University Hospital and University of Eastern Finland, Kuopio, Finland
| | - H Soininen
- Department of Neurology, University of Eastern Finland, Kuopio, Finland.,Unit of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland.,Neurology of NeuroCenter, Kuopio University Hospital, Kuopio, Finland.,Institute of Clinical Medicine-Neurology, University of Eastern Finland, Kuopio, Finland.,Department of Neurology, Kuopio University Hospital, Kuopio, Finland
| | - A Luikku
- Neurology of NeuroCenter, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - J E Jääskeläinen
- Neurosurgery of NeuroCenter, Kuopio University Hospital and University of Eastern Finland, Kuopio, Finland.,Department of Neurosurgery, Kuopio University Hospital, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland.,Neurosurgery of NeuroCenter, Kuopio University Hospital, Kuopio, Finland
| | - V Leinonen
- Neurosurgery of NeuroCenter, Kuopio University Hospital and University of Eastern Finland, Kuopio, Finland.,Department of Neurosurgery, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland.,Department of Neurosurgery, Kuopio University Hospital, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland.,Neurosurgery of NeuroCenter, Kuopio University Hospital, Kuopio, Finland
| | - U Kehler
- Neurosurgical Department, Asklepios Klinik Hamburg Altona, Hamburg, Germany
| | - O Lilja-Lund
- Department of Pharmacology and Clinical Neuroscience, Unit of Neurology, Östersund, Umeå University, Umeå, Sweden
| | - K Kockum
- Department of Pharmacology and Clinical Neuroscience, Unit of Neurology, Östersund, Umeå University, Umeå, Sweden
| | - E M Larsson
- Department of Radiology, Uppsala University, Uppsala, Sweden
| | - K Riklund
- Department of Radiation Sciences, Umeå University, Umeå, Sweden
| | - L Söderström
- Department of Pharmacology and Clinical Neuroscience, Unit of Neurology, Östersund, Umeå University, Umeå, Sweden
| | - P Hellström
- Hydrocephalus Research Unit, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - K Laurell
- Department of Pharmacology and Clinical Neuroscience, Unit of Neurology, Östersund, Umeå University, Umeå, Sweden
| | - M Kojoukhova
- Neurosurgery of NeuroCenter, Kuopio University Hospital and University of Eastern Finland, Kuopio, Finland.,Neurosurgery of NeuroCenter, Kuopio University Hospital, Kuopio, Finland.,Department of Radiology, Kuopio University Hospital, Kuopio, Finland
| | - A Sutela
- Department of Radiology, Kuopio University Hospital and University of Eastern Finland, Kuopio, Finland.,Department of Radiology, Kuopio University Hospital, Kuopio, Finland
| | - R Vanninen
- Department of Radiology, Kuopio University Hospital and University of Eastern Finland, Kuopio, Finland
| | - K I Vanha
- Neurosurgery of NeuroCenter, Kuopio University Hospital and University of Eastern Finland, Kuopio, Finland
| | - M Timonen
- Neurosurgery of NeuroCenter, Kuopio University Hospital and University of Eastern Finland, Kuopio, Finland
| | - J Rummukainen
- Department of Pathology, Kuopio University Hospital, Kuopio, Finland
| | - V Korhonen
- Department of Neurosurgery, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - S Helisalmi
- Unit of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland.,Institute of Clinical Medicine-Neurology, University of Eastern Finland, Kuopio, Finland.,Department of Neurology, Kuopio University Hospital, Kuopio, Finland
| | - E Solje
- Institute of Clinical Medicine-Neurology, University of Eastern Finland, Kuopio, Finland.,Department of Neurology, Kuopio University Hospital, Kuopio, Finland
| | - A M Remes
- Unit of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland.,Neurology of NeuroCenter, Kuopio University Hospital, Kuopio, Finland.,Institute of Clinical Medicine-Neurology, University of Eastern Finland, Kuopio, Finland.,Department of Neurology, Kuopio University Hospital, Kuopio, Finland
| | - J Huovinen
- Department of Neurosurgery, Kuopio University Hospital, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - J Paananen
- Unit of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland.,Department of Neurology, Kuopio University Hospital, Kuopio, Finland.,Institute of Biomedicine, University of Eastern Finland, Kuopio, Finland
| | - M Hiltunen
- Unit of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland.,Neurology of NeuroCenter, Kuopio University Hospital, Kuopio, Finland.,Institute of Clinical Medicine-Neurology, University of Eastern Finland, Kuopio, Finland.,Department of Neurology, Kuopio University Hospital, Kuopio, Finland.,Institute of Biomedicine, University of Eastern Finland, Kuopio, Finland
| | - M Kurki
- Department of Neurosurgery, Kuopio University Hospital, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland.,Analytical and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute for Harvard and MIT, Cambridge, MA, USA
| | - B Martin
- Biological Engineering, University of Idaho, Moscow, ID, USA
| | - F Loth
- Mechanical Engineering, University of Akron, Akron, Ohio, USA
| | - M Luciano
- Neurosurgery, Johns Hopkins University, Baltimore, MA, USA.,Department of Neurosurgery, Johns Hopkins Hospital, Baltimore, MD, USA
| | - A J Luikku
- Institute of Clinical Medicine-Neurology, University of Eastern Finland, Kuopio, Finland.,Neurosurgery of NeuroCenter, Kuopio University Hospital, Kuopio, Finland
| | - A Hall
- Institute of Clinical Medicine-Neurology, University of Eastern Finland, Kuopio, Finland
| | - S K Herukka
- Neurology of NeuroCenter, Kuopio University Hospital, Kuopio, Finland.,Institute of Clinical Medicine-Neurology, University of Eastern Finland, Kuopio, Finland
| | - J Mattila
- VTT Technical Research Centre of Finland, Tampere, Finland.,Combinostics Ltd, Tampere, Finland
| | - J Lötjönen
- VTT Technical Research Centre of Finland, Tampere, Finland.,Combinostics Ltd, Tampere, Finland
| | - I Alafuzoff
- Institute of Clinical Medicine-Neurology, University of Eastern Finland, Kuopio, Finland.,Rudbeck Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.,Department of Pathology and Cytology, Uppsala University Hospital, Uppsala, Sweden
| | - I Jurjević
- Department of Neurosurgery, Graduate School of Medicine, Juntendo University, Tokyo, Japan.,Department of Pharmacology and Department of Neurology, University of Zagreb School of Medicine, Zagreb, Croatia
| | - M Miyajima
- Department of Neurosurgery, Graduate School of Medicine, Juntendo University, Tokyo, Japan.,Department of Neurosurgery, Juntendo University School of Medicine, Tokyo, Japan
| | - M Nakajima
- Department of Neurosurgery, Graduate School of Medicine, Juntendo University, Tokyo, Japan.,Department of Neurosurgery, Juntendo University School of Medicine, Tokyo, Japan
| | - H Murai
- Department of Neurosurgery, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - T Shin
- Department of Neurosurgery, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - D Kawaguchi
- Department of Neurosurgery, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - C Akiba
- Department of Neurosurgery, Juntendo University School of Medicine, Tokyo, Japan
| | - I Ogino
- Department of Neurosurgery, Juntendo University School of Medicine, Tokyo, Japan
| | - K Karagiozov
- Department of Neurosurgery, Juntendo University School of Medicine, Tokyo, Japan
| | - H Arai
- Department of Neurosurgery, Juntendo University School of Medicine, Tokyo, Japan
| | - R C Reis
- Group of Cerebral Hydrodynamics, Division of Functional Neurosurgery, Institute of Psychiatry, Hospital das Clínicas, University of São Paulo, São Paulo, Brazil
| | - M J Teixeira
- Group of Cerebral Hydrodynamics, Division of Functional Neurosurgery, Institute of Psychiatry, Hospital das Clínicas, University of São Paulo, São Paulo, Brazil
| | - C G Valêncio
- Group of Cerebral Hydrodynamics, Division of Functional Neurosurgery, Institute of Psychiatry, Hospital das Clínicas, University of São Paulo, São Paulo, Brazil
| | - D da Vigua
- Group of Cerebral Hydrodynamics, Division of Functional Neurosurgery, Institute of Psychiatry, Hospital das Clínicas, University of São Paulo, São Paulo, Brazil
| | - L Almeida-Lopes
- Núcleo de Pesquisa e Ensino de Fototerapia nas Ciências da Saúde (NUPEN), São Carlos, Brazil
| | - M W Mancini
- Núcleo de Pesquisa e Ensino de Fototerapia nas Ciências da Saúde (NUPEN), São Carlos, Brazil
| | - F C G Pinto
- Group of Cerebral Hydrodynamics, Division of Functional Neurosurgery, Institute of Psychiatry, Hospital das Clínicas, University of São Paulo, São Paulo, Brazil
| | - R H Maykot
- Group of Cerebral Hydrodynamics, Division of Functional Neurosurgery, Institute of Psychiatry, Hospital das Clínicas, University of São Paulo, São Paulo, Brazil
| | - G Calia
- Group of Cerebral Hydrodynamics, Division of Functional Neurosurgery, Institute of Psychiatry, Hospital das Clínicas, University of São Paulo, São Paulo, Brazil
| | - J Tornai
- Group of Cerebral Hydrodynamics, Division of Functional Neurosurgery, Institute of Psychiatry, Hospital das Clínicas, University of São Paulo, São Paulo, Brazil
| | - S S S Silvestre
- Group of Cerebral Hydrodynamics, Division of Functional Neurosurgery, Institute of Psychiatry, Hospital das Clínicas, University of São Paulo, São Paulo, Brazil
| | - G Mendes
- Group of Cerebral Hydrodynamics, Division of Functional Neurosurgery, Institute of Psychiatry, Hospital das Clínicas, University of São Paulo, São Paulo, Brazil
| | - V Sousa
- Group of Cerebral Hydrodynamics, Division of Functional Neurosurgery, Institute of Psychiatry, Hospital das Clínicas, University of São Paulo, São Paulo, Brazil
| | - B Bezerra
- Group of Cerebral Hydrodynamics, Division of Functional Neurosurgery, Institute of Psychiatry, Hospital das Clínicas, University of São Paulo, São Paulo, Brazil
| | - P Dutra
- Group of Cerebral Hydrodynamics, Division of Functional Neurosurgery, Institute of Psychiatry, Hospital das Clínicas, University of São Paulo, São Paulo, Brazil
| | - P Modesto
- Group of Cerebral Hydrodynamics, Division of Functional Neurosurgery, Institute of Psychiatry, Hospital das Clínicas, University of São Paulo, São Paulo, Brazil
| | - M F Oliveira
- Group of Cerebral Hydrodynamics, Division of Functional Neurosurgery, Institute of Psychiatry, Hospital das Clínicas, University of São Paulo, São Paulo, Brazil
| | - C E Petitto
- Group of Cerebral Hydrodynamics, Division of Functional Neurosurgery, Institute of Psychiatry, Hospital das Clínicas, University of São Paulo, São Paulo, Brazil
| | - H Pulhorn
- Department of Neurosurgery, The Walton Centre, Liverpool, UK
| | - A Chandran
- Department of Neuroradiology, The Walton Centre, Liverpool, UK
| | - C McMahon
- Department of Neurosurgery, The Walton Centre, Liverpool, UK
| | - A S Rao
- The Johns Hopkins Hospital, Baltimore, MD, USA
| | - M Jumaly
- The Johns Hopkins Hospital, Baltimore, MD, USA
| | - D Solomon
- The Johns Hopkins Hospital, Baltimore, MD, USA.,Neurology, Johns Hopkins Hospital, Baltimore, MD, USA.,Department of Neurology, Johns Hopkins Bayview Medical Center, Baltimore, MD, USA
| | - A Moghekar
- The Johns Hopkins Hospital, Baltimore, MD, USA
| | - N Relkin
- Department of Neurology, Weill Cornell Medical College, New York, NY, USA
| | - M Hamilton
- Department of Neurosurgery, University of Calgary, Alberta, Canada
| | - H Katzen
- Department of Neurology, University of Miami, Miami, FL, USA
| | - M Williams
- Department of Neurosurgery, Washington University, Seattle, WA, USA
| | - T Bach
- Utah Data Collection Center (DCC), University of Utah, Salt Lake City, UT, USA
| | - S Zuspan
- Utah Data Collection Center (DCC), University of Utah, Salt Lake City, UT, USA
| | - R Holubkov
- Utah Data Collection Center (DCC), University of Utah, Salt Lake City, UT, USA
| | | | - G Clemens
- Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - P Sharkey
- School of Business, Loyola University Maryland, Baltimore, MD, USA
| | - A Sanyal
- Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - E Sankey
- Department of Neurosurgery, Johns Hopkins University, Baltimore, MD, USA.,Department of Neurosurgery, Johns Hopkins University, School of Medicine, Baltimore, MD, USA
| | - K Rigamonti
- Department of Neurosurgery, Johns Hopkins University, Baltimore, MD, USA
| | - S Naqvi
- Primary Care, Johns Hopkins Aramco Healthcare, Abqaiq, Saudi Arabia
| | - A Hung
- Department of Neurosurgery, Johns Hopkins University, Baltimore, MD, USA.,Department of Neurosurgery, Johns Hopkins University, School of Medicine, Baltimore, MD, USA
| | - E Schmidt
- Department of Neurosurgery, University Hospital Toulouse, Toulouse, France
| | - F Ory-Magne
- Department of Neurology, University Hospital Toulouse, Toulouse, France.,INSER TONIC 1014, Toulouse Neuroimaging Center, Toulouse, France
| | - P Gantet
- Department of Nuclear Medicine, University Hospital Toulouse, Toulouse, France
| | - A Guenego
- Department of Neurosurgery, University Hospital Toulouse, Toulouse, France.,Department of Neuroradiology, University Hospital Toulouse, Toulouse, France
| | - A C Januel
- Department of Neuroradiology, University Hospital Toulouse, Toulouse, France
| | - P Tall
- Department of Neuroradiology, University Hospital Toulouse, Toulouse, France
| | - N Fabre
- Department of Neurology, University Hospital Toulouse, Toulouse, France
| | - L Mahieu
- Department of Ophtalmology, University Hospital Toulouse, Toulouse, France
| | - C Cognard
- Department of Neuroradiology, University Hospital Toulouse, Toulouse, France
| | - L Gray
- Department of Physiology, Johns Hopkins University, School of Medicine, Baltimore, MD, USA
| | | | - K Takagi
- Normal Pressure Hydrocephalus Center, Kashiwa-Tanaka Hospital, Kashiwa, Japan
| | - K Onouchi
- Department of Neurology, Kashiwa-Tanaka Hospital, Kashiwa, Japan
| | - S D Thompson
- The National Hospital for Neurology and Neurosurgery, Queen Square, London, UK
| | - L D Thorne
- The National Hospital for Neurology and Neurosurgery, Queen Square, London, UK
| | - H M Tully
- Department of Neurology, University of Washington, Seattle, WA, USA
| | - T L Wenger
- Department of Pediatrics, University of Washington, Seattle, WA, USA
| | - W A Kukull
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - D Doherty
- Department of Pediatrics, University of Washington, Seattle, WA, USA
| | - W B Dobyns
- Department of Pediatrics, University of Washington, Seattle, WA, USA
| | - D Moran
- Department of Neurosurgery, Johns Hopkins University, School of Medicine, Baltimore, MD, USA
| | - S Vakili
- Department of Neurosurgery, Johns Hopkins University, School of Medicine, Baltimore, MD, USA
| | - M A Patel
- Department of Neurosurgery, Johns Hopkins University, School of Medicine, Baltimore, MD, USA
| | - B Elder
- Department of Neurosurgery, Johns Hopkins University, School of Medicine, Baltimore, MD, USA
| | - C R Goodwin
- Department of Neurosurgery, Johns Hopkins University, School of Medicine, Baltimore, MD, USA
| | - J A Crawford
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, School of Medicine, Baltimore, MD, USA
| | - M V Pletnikov
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, School of Medicine, Baltimore, MD, USA
| | - J Xu
- F. M. Kirby Research Center for Functional Brain Imaging at the Kennedy Krieger Institute, Johns Hopkins University, School of Medicine, Baltimore, MD, USA
| | - A Blitz
- Department of Radiology and Radiological Science, Johns Hopkins University, School of Medicine, Baltimore, MD, USA
| | - D A Herzka
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - H Guerrero-Cazares
- Department of Neurosurgery, Johns Hopkins University, School of Medicine, Baltimore, MD, USA
| | - A Quiñones-Hinojosa
- Department of Neurosurgery, Johns Hopkins University, School of Medicine, Baltimore, MD, USA.,Department of Oncology, Johns Hopkins University, School of Medicine, Baltimore, MD, USA
| | - S Mori
- Department of Radiology-Magnetic Resonance Research, Johns Hopkins University, School of Medicine, Baltimore, MD, USA
| | - P Saavedra
- Department of Neurosurgery, Johns Hopkins University, School of Medicine, Baltimore, MD, USA
| | - H Treviño
- Department of Neurosurgery, Johns Hopkins University, School of Medicine, Baltimore, MD, USA
| | - K Maitani
- Department of Neurosurgery, Johns Hopkins University, School of Medicine, Baltimore, MD, USA.,Tohoku University School of Medicine, Sendai, Japan
| | - W C Ziai
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - V Eslami
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - S Nekoovaght-Tak
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - R Dlugash
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - G Yenokyan
- Department of Biostatistics, The Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - N McBee
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - D F Hanley
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
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27
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Myllylä T, Zacharias N, Korhonen V, Zienkiewicz A, Hinrichs H, Kiviniemi V, Walter M. Multimodal brain imaging with magnetoencephalography: A method for measuring blood pressure and cardiorespiratory oscillations. Sci Rep 2017; 7:172. [PMID: 28282963 PMCID: PMC5412650 DOI: 10.1038/s41598-017-00293-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2016] [Accepted: 02/17/2017] [Indexed: 11/25/2022] Open
Abstract
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.
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Affiliation(s)
- Teemu Myllylä
- University of Oulu, Optoelectronics and Measurement Techniques Research Unit, Health & Wellness Measurements Group, Oulu, Finland.
| | - Norman Zacharias
- Leibniz Institute for Neurobiology, Magdeburg, Germany.,Charité - Universitätsmedizin Berlin, Department of Anesthesiology, Neuroimaging Research Group, Berlin, Germany
| | - Vesa Korhonen
- Oulu University Hospital, Department of Diagnostic Radiology, Oulu, Finland.,University of Oulu, Research Unit of Medical Imaging, Physics and Technology, Oulu Functional NeuroImaging Group, Oulu, Finland
| | - Aleksandra Zienkiewicz
- University of Oulu, Optoelectronics and Measurement Techniques Research Unit, Health & Wellness Measurements Group, Oulu, Finland
| | - Hermann Hinrichs
- Leibniz Institute for Neurobiology, Magdeburg, Germany.,University Hospital Magdeburg, Clinic for Neurology, Magdeburg, Germany
| | - Vesa Kiviniemi
- Oulu University Hospital, Department of Diagnostic Radiology, Oulu, Finland.,University of Oulu, Research Unit of Medical Imaging, Physics and Technology, Oulu Functional NeuroImaging Group, Oulu, Finland
| | - Martin Walter
- Leibniz Institute for Neurobiology, Magdeburg, Germany.,University of Tübingen, Department of Psychiatry, Tübingen, Germany
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28
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Raatikainen V, Huotari N, Korhonen V, Rasila A, Kananen J, Raitamaa L, Keinänen T, Kantola J, Tervonen O, Kiviniemi V. Combined spatiotemporal ICA (stICA) for continuous and dynamic lag structure analysis of MREG data. Neuroimage 2017; 148:352-363. [PMID: 28088482 DOI: 10.1016/j.neuroimage.2017.01.024] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2016] [Revised: 01/10/2017] [Accepted: 01/11/2017] [Indexed: 01/30/2023] Open
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 0.6s (± 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 2min window analysis, there was large variability over subjects as ranging between 1-10sec. 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 0.0s 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.
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Affiliation(s)
- Ville Raatikainen
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland; Research unit of Medical Imaging, Physics and Technology, the Faculty of Medicine, University of Oulu, Oulu, Finland.
| | - Niko Huotari
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland; Research unit of Medical Imaging, Physics and Technology, the Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Vesa Korhonen
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland; Research unit of Medical Imaging, Physics and Technology, the Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Aleksi Rasila
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland
| | - Janne Kananen
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland; Research unit of Medical Imaging, Physics and Technology, the Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Lauri Raitamaa
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland; Research unit of Medical Imaging, Physics and Technology, the Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Tuija Keinänen
- Research unit of Medical Imaging, Physics and Technology, the Faculty of Medicine, University of Oulu, Oulu, Finland; Department of Clinical Neurophysiology, Oulu University Hospital, Oulu, Finland
| | - Jussi Kantola
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland
| | - Osmo Tervonen
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland; Research unit of Medical Imaging, Physics and Technology, the Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Vesa Kiviniemi
- Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu, Finland; Research unit of Medical Imaging, Physics and Technology, the Faculty of Medicine, University of Oulu, Oulu, Finland
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Kiviniemi V, Wang X, Korhonen V, Keinänen T, Tuovinen T, Autio J, LeVan P, Keilholz S, Zang YF, Hennig J, Nedergaard M. Ultra-fast magnetic resonance encephalography of physiological brain activity - Glymphatic pulsation mechanisms? J Cereb Blood Flow Metab 2016; 36:1033-45. [PMID: 26690495 PMCID: PMC4908626 DOI: 10.1177/0271678x15622047] [Citation(s) in RCA: 220] [Impact Index Per Article: 27.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2015] [Accepted: 11/06/2015] [Indexed: 11/16/2022]
Abstract
The theory on the glymphatic convection mechanism of cerebrospinal fluid holds that cardiac pulsations in part pump cerebrospinal fluid from the peri-arterial spaces through the extracellular tissue into the peri-venous spaces facilitated by aquaporin water channels. Since cardiac pulses cannot be the sole mechanism of glymphatic propulsion, we searched for additional cerebrospinal fluid pulsations in the human brain with ultra-fast magnetic resonance encephalography. We detected three types of physiological mechanisms affecting cerebral cerebrospinal fluid pulsations: cardiac, respiratory, and very low frequency pulsations. The cardiac pulsations induce a negative magnetic resonance encephalography signal change in peri-arterial regions that extends centrifugally and covers the brain in ≈1 Hz cycles. The respiratory ≈0.3 Hz pulsations are centripetal periodical pulses that occur dominantly in peri-venous areas. The third type of pulsation was very low frequency (VLF 0.001-0.023 Hz) and low frequency (LF 0.023-0.73 Hz) waves that both propagate with unique spatiotemporal patterns. Our findings using critically sampled magnetic resonance encephalography open a new view into cerebral fluid dynamics. Since glymphatic system failure may precede protein accumulations in diseases such as Alzheimer's dementia, this methodological advance offers a novel approach to image brain fluid dynamics that potentially can enable early detection and intervention in neurodegenerative diseases.
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Affiliation(s)
- Vesa Kiviniemi
- Oulu Functional NeuroImaging, Department of Diagnostic Radiology, MRC, Oulu University Hospital, Oulu, Finland Medical Imaging, Physics and Technology, the Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Xindi Wang
- Oulu Functional NeuroImaging, Department of Diagnostic Radiology, MRC, Oulu University Hospital, Oulu, Finland Medical Imaging, Physics and Technology, the Faculty of Medicine, University of Oulu, Oulu, Finland State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Vesa Korhonen
- Oulu Functional NeuroImaging, Department of Diagnostic Radiology, MRC, Oulu University Hospital, Oulu, Finland Medical Imaging, Physics and Technology, the Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Tuija Keinänen
- Oulu Functional NeuroImaging, Department of Diagnostic Radiology, MRC, Oulu University Hospital, Oulu, Finland Medical Imaging, Physics and Technology, the Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Timo Tuovinen
- Oulu Functional NeuroImaging, Department of Diagnostic Radiology, MRC, Oulu University Hospital, Oulu, Finland Medical Imaging, Physics and Technology, the Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Joonas Autio
- Oulu Functional NeuroImaging, Department of Diagnostic Radiology, MRC, Oulu University Hospital, Oulu, Finland Functional Architecture Team, Center for Life Science Technologies, RIKEN, Japan
| | - Pierre LeVan
- Medical Physics, Department of Radiology, University Medical Center Freiburg, Freiburg, Germany
| | - Shella Keilholz
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University School of Medicine, Atlanta, GA, USA
| | - Yu-Feng Zang
- Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, China
| | - Jürgen Hennig
- Medical Physics, Department of Radiology, University Medical Center Freiburg, Freiburg, Germany
| | - Maiken Nedergaard
- School of Medicine and Dentistry, University of Rochester Medical Center, Rochester, NY, USA
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Abstract
Individuals with autism spectrum disorder have a preference for attending to non-speech stimuli over speech stimuli. We are interested in whether non-speech preference is only a feature of diagnosed individuals, and whether we can we test implicit preference experimentally. In typically developed individuals, serial recall is disrupted more by speech stimuli than by non-speech stimuli. Since behaviour of individuals with autistic traits resembles that of individuals with autism, we have used serial recall to test whether autistic traits influence task performance during irrelevant speech sounds. The errors made on the serial recall task during speech or non-speech sounds were counted as a measure of speech or non-speech preference in relation to no sound condition. We replicated the serial order effect and found the speech to be more disruptive than the non-speech sounds, but were unable to find any associations between the autism quotient scores and the non-speech sounds. Our results may indicate a learnt behavioural response to speech sounds.
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Affiliation(s)
- Vesa Korhonen
- a School of Educational Science and Psychology , University of Eastern Finland , Joensuu , Finland
| | - Stefan Werner
- b Philosophical Faculty, School of Humanities , Linguistics, University of Eastern Finland , Joensuu , Finland
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31
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Korhonen V, Smit PW, Haanperä M, Casali N, Ruutu P, Vasankari T, Soini H. Whole genome analysis of Mycobacterium tuberculosis isolates from recurrent episodes of tuberculosis, Finland, 1995-2013. Clin Microbiol Infect 2016; 22:549-54. [PMID: 27021423 DOI: 10.1016/j.cmi.2016.03.014] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2015] [Revised: 02/10/2016] [Accepted: 03/13/2016] [Indexed: 11/18/2022]
Abstract
Recurrent tuberculosis (TB) is caused by an endogenous re-activation of the same strain of Mycobacterium tuberculosis (relapse) or exogenous infection with a new strain (re-infection). Recurrence of TB in Finland was analysed in a population-based, 19-year study, and genotyping was used to define relapse and re-infection. The M. tuberculosis isolates from patients with suspected relapse were further analysed by whole genome sequencing (WGS) to determine the number and type of mutations occurring in the bacterial genome between the first and second disease episodes. In addition, publicly available tools (PhyResSE and SpolPred) were used to predict drug resistance and spoligotype profile from the WGS data. Of the 8299 notified TB cases, 48 (0.6%) patients had episodes classified as recurrent. Forty-two patients had more than one culture-confirmed TB episode, and isolates from two episodes in 21 patients were available for genotyping. In 18 patients, the M. tuberculosis isolates obtained from the first and second TB episodes had identical spoligotypes. The WGS analysis of the 36 M. tuberculosis isolates from the 18 suspected relapse patients (average time between isolates 2.8 years) revealed 0 to 38 single nucleotide polymorphisms (median 1, mean 3.78) between the first and second isolate. There seemed to be no direct relation between the number of years between the two isolates, or treatment outcome, and the number of single nucleotide polymorphisms. The results suggest that the mutation rate may depend on multiple host-, strain- and treatment-related factors.
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Affiliation(s)
- V Korhonen
- National Institute for Health and Welfare, Department of Infectious Diseases, Helsinki and Turku, Finland; Tampere University Hospital, Department of Pulmonary Diseases, Tampere, Finland
| | - P W Smit
- National Institute for Health and Welfare, Department of Infectious Diseases, Helsinki and Turku, Finland
| | - M Haanperä
- National Institute for Health and Welfare, Department of Infectious Diseases, Helsinki and Turku, Finland
| | - N Casali
- Department of Infectious Diseases and Immunity, Imperial College London, UK; Centre for Immunology and Infectious Disease, Blizard Institute, Queen Mary University of London, UK
| | - P Ruutu
- National Institute for Health and Welfare, Department of Infectious Diseases, Helsinki and Turku, Finland
| | - T Vasankari
- Finnish Lung Health Association (Filha), Helsinki, Finland
| | - H Soini
- National Institute for Health and Welfare, Department of Infectious Diseases, Helsinki and Turku, Finland.
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Korhonen V, Hiltunen T, Myllylä T, Wang X, Kantola J, Nikkinen J, Zang YF, LeVan P, Kiviniemi V. Synchronous multiscale neuroimaging environment for critically sampled physiological analysis of brain function: hepta-scan concept. Brain Connect 2014; 4:677-89. [PMID: 25131996 DOI: 10.1089/brain.2014.0258] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Functional connectivity of the resting-state networks of the brain is thought to be mediated by very-low-frequency fluctuations (VLFFs <0.1 Hz) in neuronal activity. However, vasomotor waves and cardiorespiratory pulsations influence indirect measures of brain function, such as the functional magnetic resonance imaging blood-oxygen-level-dependent (BOLD) signal. How strongly physiological oscillations correlate with spontaneous BOLD signals is not known, partially due to differences in the data-sampling rates of different methods. Recent ultrafast inverse imaging sequences, including magnetic resonance encephalography (MREG), enable critical sampling of these signals. In this study, we describe a multimodal concept, referred to as Hepta-scan, which incorporates synchronous MREG with scalp electroencephalography, near-infrared spectroscopy, noninvasive blood pressure, and anesthesia monitoring. Our preliminary results support the idea that, in the absence of aliased cardiorespiratory signals, VLFFs in the BOLD signal are affected by vasomotor and electrophysiological sources. Further, MREG signals showed a high correlation coefficient between the ventromedial default mode network (DMNvmpf) and electrophysiological signals, especially in the VLF range. Also, oxy- and deoxyhemoglobin and vasomotor waves were found to correlate with DMNvmpf. Intriguingly, usage of shorter time windows in these correlation measurements produced significantly (p<0.05) higher positive and negative correlation coefficients, suggesting temporal nonstationary behavior between the measurements. Focus on the VLF range strongly increased correlation strength.
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Affiliation(s)
- Vesa Korhonen
- 1 Department of Diagnostic Radiology, Institute of Diagnostics , Medical Research Center of Oulu, Oulu, Finland
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Korhonen V, Kärnä E, Räty H. Autism spectrum disorder and impaired joint attention: A review of joint attention research from the past decade. Nordic Psychology 2014. [DOI: 10.1080/19012276.2014.921577] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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Korhonen V, Paavilainen E. Learning teams and networks: using information technology as a means of managing work process development in healthcare organizations. J Nurses Staff Dev 2002; 18:267-73. [PMID: 12394576 DOI: 10.1097/00124645-200209000-00008] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
This article focuses on the introduction of team learning and shared knowledge creation using computer-based learning environments and teams as networks in the development of healthcare organizations. Using computer technology, care units can be considered learning teams and the hospital a network of those learning teams. Team learning requires that the healthcare workers' intellectual capital and personal competence be viewed as an important resource in developing the quality of action of the entire healthcare organization.
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Laukkanen E, Korhonen V, Peiponen S, Nuutinen M, Viinamäki H. A pessimistic attitude towards the future and low psychosocial functioning predict psychiatric diagnosis among treatment-seeking adolescents. Aust N Z J Psychiatry 2001; 35:160-5. [PMID: 11284896 DOI: 10.1046/j.1440-1614.2001.00875.x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
OBJECTIVE The objective was to study factors associated with psychiatric diagnosis among adolescents (n = 164) seeking psychiatric care for mental symptoms. METHOD Psychiatric diagnosis was confirmed by a structured diagnostic interview. Psychosocial functioning was assessed with the Global Assessment of Functioning Scale, and the Beck Depression Inventory and Offer Self-Image Questionnaire were also used. Background data were gathered. RESULTS A majority (76%) of the adolescents met DSM-III-R criteria for psychiatric diagnosis. The self-image was more negative and the Beck score was higher among these adolescents than the others. All who had attempted suicide had a psychiatric disorder. Those diagnosed as having a psychiatric disorder consumed alcohol in order to get drunk more often than others. Continual conflicts with parents and smoking were not associated with the existence of a psychiatric disorder. In logistic regression analysis, low psychosocial functioning (OR = 3.9) and an uncertain or pessimistic attitude towards the future (OR = 9.1) proved to be independent risk factors for psychiatric disorders. CONCLUSIONS Health service staff should be aware of factors associated with psychiatric disorders in adolescents so that they can identify those at high risk.
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Affiliation(s)
- E Laukkanen
- Department of Psychiatry (3703), Kuopio University Hospital, PO Box 1777, FIN-70211, Kuopio, Finland.
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