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Scarciglia A, Catrambone V, Bianco M, Bonanno C, Toschi N, Valenza G. Stochastic brain dynamics exhibits differential regional distribution and maturation-related changes. Neuroimage 2024; 290:120562. [PMID: 38484917 DOI: 10.1016/j.neuroimage.2024.120562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Revised: 02/29/2024] [Accepted: 03/01/2024] [Indexed: 03/18/2024] Open
Abstract
Functional magnetic resonance imaging (fMRI) is a powerful non-invasive method for studying brain function by analyzing blood oxygenation level-dependent (BOLD) signals. These signals arise from intricate interplays of deterministic and stochastic biological elements. Quantifying the stochastic part is challenging due to its reliance on assumptions about the deterministic segment. We present a methodological framework to estimate intrinsic stochastic brain dynamics in fMRI data without assuming deterministic dynamics. Our approach utilizes Approximate Entropy and its behavior in noisy series to identify and characterize dynamical noise in unobservable fMRI dynamics. Applied to extensive fMRI datasets (645 Cam-CAN, 1086 Human Connectome Project subjects), we explore lifelong maturation of intrinsic brain noise. Findings indicate 10% to 60% of fMRI signal power is due to intrinsic stochastic brain elements, varying by age. These components demonstrate a physiological role of neural noise which shows a distinct distributions across brain regions and increase linearly during maturation.
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Affiliation(s)
- Andrea Scarciglia
- Department of Information Engineering, School of Engineering, University of Pisa, Italy; Bioengineering and Robotics Research Center E.Piaggio, School of Engineering, University of Pisa, Italy.
| | - Vincenzo Catrambone
- Department of Information Engineering, School of Engineering, University of Pisa, Italy; Bioengineering and Robotics Research Center E.Piaggio, School of Engineering, University of Pisa, Italy
| | - Martina Bianco
- Department of Information Engineering, School of Engineering, University of Pisa, Italy; Department of Mathematics, University of Pisa, Italy
| | | | - Nicola Toschi
- Department of Biomedicine and Prevention, University of Rome "Tor Vergata", Rome, Italy; A.A. Martinos Center for Biomedical Imaging, MGH and Harvard Medical School, Boston, MA, USA
| | - Gaetano Valenza
- Department of Information Engineering, School of Engineering, University of Pisa, Italy; Bioengineering and Robotics Research Center E.Piaggio, School of Engineering, University of Pisa, Italy
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Golestani AM, Chen JJ. Comparing data-driven physiological denoising approaches for resting-state fMRI: implications for the study of aging. Front Neurosci 2024; 18:1223230. [PMID: 38379761 PMCID: PMC10876882 DOI: 10.3389/fnins.2024.1223230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 01/17/2024] [Indexed: 02/22/2024] Open
Abstract
Introduction Physiological nuisance contributions by cardiac and respiratory signals have a significant impact on resting-state fMRI data quality. As these physiological signals are often not recorded, data-driven denoising methods are commonly used to estimate and remove physiological noise from fMRI data. To investigate the efficacy of these denoising methods, one of the first steps is to accurately capture the cardiac and respiratory signals, which requires acquiring fMRI data with high temporal resolution. Methods In this study, we used such high-temporal resolution fMRI data to evaluate the effectiveness of several data-driven denoising methods, including global-signal regression (GSR), white matter and cerebrospinal fluid regression (WM-CSF), anatomical (aCompCor) and temporal CompCor (tCompCor), ICA-AROMA. Our analysis focused on the consequence of changes in low-frequency, cardiac and respiratory signal power, as well as age-related differences in terms of functional connectivity (fcMRI). Results Our results confirm that the ICA-AROMA and GSR removed the most physiological noise but also more low-frequency signals. These methods are also associated with substantially lower age-related fcMRI differences. On the other hand, aCompCor and tCompCor appear to be better at removing high-frequency physiological signals but not low-frequency signal power. These methods are also associated with relatively higher age-related fcMRI differences, whether driven by neuronal signal or residual artifact. These results were reproduced in data downsampled to represent conventional fMRI sampling frequency. Lastly, methods differ in performance depending on the age group. Discussion While this study cautions direct comparisons of fcMRI results based on different denoising methods in the study of aging, it also enhances the understanding of different denoising methods in broader fcMRI applications.
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Affiliation(s)
- Ali M. Golestani
- Department of Physics and Astronomy, University of Calgary, Calgary, AB, Canada
- Department of Oncology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - J. Jean Chen
- Rotman Research Institute at Baycrest, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Department of Biomedical Engineering, University of Toronto, Toronto, ON, Canada
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Hougaard A, Gaist D, Garde E, Iversen P, Madsen CG, Kyvik KO, Ashina M, Siebner HR, Madsen KH. Lack of reproducibility of resting-state functional MRI findings in migraine with aura. Cephalalgia 2023; 43:3331024231212574. [PMID: 37950678 DOI: 10.1177/03331024231212574] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2023]
Abstract
BACKGROUND Several studies have applied resting-state functional MRI to examine whether functional brain connectivity is altered in migraine with aura patients. These studies had multiple limitations, including small sample sizes, and reported conflicting results. Here, we performed a large, cross-sectional brain imaging study to reproduce previous findings. METHODS We recruited women aged 30-60 years from the nationwide Danish Twin Registry. Resting-state functional MRI of women with migraine with aura, their co-twins, and unrelated migraine-free twins was performed at a single centre. We carried out an extensive series of brain connectivity data analyses. Patients were compared to migraine-free controls and to co-twins. RESULTS Comparisons were based on data from 160 patients, 30 co-twins, and 136 controls. Patients were similar to controls with regard to age, and several lifestyle characteristics. We replicated clear effects of age on resting-state networks. In contrast, we failed to detect any differences, and to replicate previously reported differences, in functional connectivity between migraine patients with aura and non-migraine controls or their co-twins in any of the analyses. CONCLUSION Given the large sample size and the unbiased population-based design of our study, we conclude that women with migraine with aura have normal resting-state brain connectivity outside of migraine attacks.
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Affiliation(s)
- Anders Hougaard
- Danish Headache Center, Department of Neurology, Copenhagen University Hospital - Rigshospitalet Glostrup, Glostrup, Denmark
- Department of Neurology, Copenhagen University Hospital - Herlev and Gentofte, Herlev, Denmark
- Department of Clinical Medicine, Faculty of Medical and Health Sciences, University of Copenhagen, Copenhagen, Denmark
| | - David Gaist
- Research Unit for Neurology, Odense University Hospital, Odense, Denmark; University of Southern Denmark, Odense, Denmark
| | - Ellen Garde
- Department of Public Health, Section of Environmental Health, University of Copenhagen, Copenhagen, Denmark
- Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital - Amager and Hvidovre, Hvidovre, Denmark
| | - Pernille Iversen
- Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital - Amager and Hvidovre, Hvidovre, Denmark
| | - Camilla G Madsen
- Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital - Amager and Hvidovre, Hvidovre, Denmark
- Department of Radiology, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Hvidovre, Denmark
| | - Kirsten O Kyvik
- Department of Public Health, Section of Environmental Health, University of Copenhagen, Copenhagen, Denmark
- The Danish Twin Registry, Epidemiology, Biostatistics and Biodemography, Institute of Public Health, University of Southern Denmark, Odense, Denmark
- Odense Patient data Explorative Network (OPEN), Odense University Hospital, Odense, Denmark
| | - Messoud Ashina
- Danish Headache Center, Department of Neurology, Copenhagen University Hospital - Rigshospitalet Glostrup, Glostrup, Denmark
- Department of Clinical Medicine, Faculty of Medical and Health Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Hartwig R Siebner
- Department of Clinical Medicine, Faculty of Medical and Health Sciences, University of Copenhagen, Copenhagen, Denmark
- Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital - Amager and Hvidovre, Hvidovre, Denmark
- Department of Neurology, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark
| | - Kristoffer H Madsen
- Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital - Amager and Hvidovre, Hvidovre, Denmark
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kgs. Lyngby, Denmark
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Deery HA, Di Paolo R, Moran C, Egan GF, Jamadar SD. The older adult brain is less modular, more integrated, and less efficient at rest: A systematic review of large-scale resting-state functional brain networks in aging. Psychophysiology 2023; 60:e14159. [PMID: 36106762 PMCID: PMC10909558 DOI: 10.1111/psyp.14159] [Citation(s) in RCA: 32] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 07/22/2022] [Accepted: 07/25/2022] [Indexed: 12/23/2022]
Abstract
The literature on large-scale resting-state functional brain networks across the adult lifespan was systematically reviewed. Studies published between 1986 and July 2021 were retrieved from PubMed. After reviewing 2938 records, 144 studies were included. Results on 11 network measures were summarized and assessed for certainty of the evidence using a modified GRADE method. The evidence provides high certainty that older adults display reduced within-network and increased between-network functional connectivity. Older adults also show lower segregation, modularity, efficiency and hub function, and decreased lateralization and a posterior to anterior shift at rest. Higher-order functional networks reliably showed age differences, whereas primary sensory and motor networks showed more variable results. The inflection point for network changes is often the third or fourth decade of life. Age effects were found with moderate certainty for within- and between-network altered patterns and speed of dynamic connectivity. Research on within-subject bold variability and connectivity using glucose uptake provides low certainty of age differences but warrants further study. Taken together, these age-related changes may contribute to the cognitive decline often seen in older adults.
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Affiliation(s)
- Hamish A. Deery
- Turner Institute for Brain and Mental HealthMonash UniversityMelbourneVictoriaAustralia
- Monash Biomedical ImagingMonash UniversityMelbourneVictoriaAustralia
| | - Robert Di Paolo
- Turner Institute for Brain and Mental HealthMonash UniversityMelbourneVictoriaAustralia
- Monash Biomedical ImagingMonash UniversityMelbourneVictoriaAustralia
| | - Chris Moran
- Peninsula Clinical School, Central Clinical SchoolMonash UniversityFrankstonVictoriaAustralia
- Department of Geriatric MedicinePeninsula HealthFrankstonVictoriaAustralia
| | - Gary F. Egan
- Turner Institute for Brain and Mental HealthMonash UniversityMelbourneVictoriaAustralia
- Monash Biomedical ImagingMonash UniversityMelbourneVictoriaAustralia
- Australian Research Council Centre of Excellence for Integrative Brain FunctionMelbourneVictoriaAustralia
| | - Sharna D. Jamadar
- Turner Institute for Brain and Mental HealthMonash UniversityMelbourneVictoriaAustralia
- Monash Biomedical ImagingMonash UniversityMelbourneVictoriaAustralia
- Australian Research Council Centre of Excellence for Integrative Brain FunctionMelbourneVictoriaAustralia
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Tzeng WY, Figarella K, Garaschuk O. Olfactory impairment in men and mice related to aging and amyloid-induced pathology. Pflugers Arch 2021; 473:805-821. [PMID: 33608800 PMCID: PMC7895745 DOI: 10.1007/s00424-021-02527-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Revised: 01/07/2021] [Accepted: 01/28/2021] [Indexed: 12/31/2022]
Abstract
Olfaction, or the sense of smell, is one of the most ancient senses in men and mice, important for a large variety of innate and acquired behaviors. Clinical data reveal an early impairment of olfaction during normal aging and in the course of neurodegenerative diseases, but the underlying cellular/molecular mechanisms remain obscure. In the current review, we compare different aspects of the aging- and Alzheimer's disease related impairment of olfaction in men and mice, aiming at the identification of common morbidities and biomarkers, which can be analyzed in detail in the appropriate mouse models. We also identify common, often interdependent (patho)physiological pathways, including but not limited to extracellular amyloid depositions, neuroinflammation, ɛ4 allele of the apolipoprotein E, CNS insulin resistance, and the impairment of adult neurogenesis, to be targeted by basic and clinical research.
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Affiliation(s)
- Wen-Yu Tzeng
- Institute of Physiology, Department of Neurophysiology, Eberhard Karls University of Tübingen, Keplerstr. 15, 72074, Tübingen, Germany
| | - Katherine Figarella
- Institute of Physiology, Department of Neurophysiology, Eberhard Karls University of Tübingen, Keplerstr. 15, 72074, Tübingen, Germany
| | - Olga Garaschuk
- Institute of Physiology, Department of Neurophysiology, Eberhard Karls University of Tübingen, Keplerstr. 15, 72074, Tübingen, Germany.
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