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Wang Z, Jia J. Enhancing the understanding between exercise and brain health: A new tool of oxygen imaging. JOURNAL OF SPORT AND HEALTH SCIENCE 2024; 13:751-752. [PMID: 38768657 PMCID: PMC11336363 DOI: 10.1016/j.jshs.2024.05.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2024] [Accepted: 04/29/2024] [Indexed: 05/22/2024]
Affiliation(s)
- Zhibo Wang
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Jianping Jia
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China.
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2
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Georgopoulos AP, Christova P, Leuthold AC, James LM. Association between neurovascular coupling and neural signals in the resting state as revealed by a combined fMRI and magnetoencephalography study in humans. J Neurophysiol 2024; 132:1231-1234. [PMID: 39258772 DOI: 10.1152/jn.00360.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2024] [Revised: 08/29/2024] [Accepted: 08/30/2024] [Indexed: 09/12/2024] Open
Abstract
The blood oxygenation level-dependent (BOLD) activation reflects hemodynamic events mediated by neurovascular coupling. During task performance, the BOLD hemodynamic response in a relevant area is mainly driven by the high levels of synaptic activity (reflected in local field potentials, LFPs) but, in contrast, during a task-free, resting state, the contribution to BOLD of such neural events is small, as expected by the comparatively (to the task state) low level of neural events. Concomitant recording of BOLD and LFP at rest in animal experiments has estimated the neural contribution to BOLD to ∼10%. Such experiments have not been performed in humans. As an approximation, we recorded (in the same subject, n = 57 healthy participants) at a task-free, resting state the BOLD signal and, in a different session, the magnetoencephalographic (MEG) signal, which reflects purely neural (synaptic) events. We then calculated the turnover of these signals by computing the successive moment-to-moment difference in the BOLD and MEG time series and retaining the median of the absolute value of the differenced series (BOLD and TMEG, respectively). The correlation between normalized turnovers of BOLD (TBOLD) and turnovers of MEG (TMEG) was r = 0.336 (r2 = 0.113; P = 0.011). These results estimate that 11.3% of the variance in TBOLD can be explained by the variance in TMEG. This estimate is close to the aforementioned estimate obtained by direct recordings in animal experiments. NEW & NOTEWORTHY Here, we report on a weak positive association between turnovers of blood oxygenation level-dependent (TBOLD) and magnetoencephalographic (TMEG) signals in 57 healthy human subjects in a resting, task-free state. More specifically, we found that the purely neural TMEG accounted for 11.1% of the TBOLD, a percentage remarkably close to that found between resting-state local field potentials (LFPs) and BOLD recorded concurrently in animal experiments.
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Affiliation(s)
- Apostolos P Georgopoulos
- The Neuroimaging Research Group, Brain Sciences Center, Department of Veterans Affairs Health Care System, Minneapolis, Minnesota, United States
- Department of Neuroscience, University of Minnesota Medical School, Minneapolis, Minnesota, United States
- Department of Psychiatry, University of Minnesota Medical School, Minneapolis, Minnesota, United States
- Institute for Health Informatics, University of Minnesota Medical School, Minneapolis, Minnesota, United States
| | - Peka Christova
- The Neuroimaging Research Group, Brain Sciences Center, Department of Veterans Affairs Health Care System, Minneapolis, Minnesota, United States
- Department of Neuroscience, University of Minnesota Medical School, Minneapolis, Minnesota, United States
| | - Arthur C Leuthold
- The Neuroimaging Research Group, Brain Sciences Center, Department of Veterans Affairs Health Care System, Minneapolis, Minnesota, United States
- Department of Neuroscience, University of Minnesota Medical School, Minneapolis, Minnesota, United States
| | - Lisa M James
- The Neuroimaging Research Group, Brain Sciences Center, Department of Veterans Affairs Health Care System, Minneapolis, Minnesota, United States
- Department of Neuroscience, University of Minnesota Medical School, Minneapolis, Minnesota, United States
- Department of Psychiatry, University of Minnesota Medical School, Minneapolis, Minnesota, United States
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3
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Ruppert-Junck MC, Heinecke V, Librizzi D, Steidel K, Beckersjürgen M, Verburg FA, Schurrat T, Luster M, Müller HH, Timmermann L, Eggers C, Pedrosa D. Connectivity based on glucose dynamics reveals exaggerated sensorimotor network coupling on subject-level in Parkinson's disease. Eur J Nucl Med Mol Imaging 2024; 51:3630-3642. [PMID: 38884774 PMCID: PMC11445336 DOI: 10.1007/s00259-024-06796-6] [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: 02/08/2024] [Accepted: 06/07/2024] [Indexed: 06/18/2024]
Abstract
PURPOSE While fMRI provides information on the temporal changes in blood oxygenation, 2- [18F]fluoro-2-deoxy-D-glucose ([18F]FDG)-PET has traditionally offered a static snapshot of brain glucose consumption. As a result, studies investigating metabolic brain networks as potential biomarkers for neurodegeneration have primarily been conducted at the group level. However, recent pioneering studies introduced time-resolved [18F]FDG-PET with constant infusion, which enables metabolic connectivity studies at the individual level. METHODS In the current study, this technique was employed to explore Parkinson's disease (PD)-related alterations in individual metabolic connectivity, in comparison to inter-subject measures and hemodynamic connectivity. Fifteen PD patients and 14 healthy controls with comparable cognition underwent sequential resting-state dynamic PET with constant infusion and functional MRI. Intrinsic networks were identified by independent component analysis and interregional connectivity calculated for summed static PET images, PET time series and functional MRI. RESULTS Our findings revealed an intrinsic sensorimotor network in PD patients that has not been previously observed to this extent. In PD, a significantly higher number of connections in cortical motor areas was observed compared to elderly control subjects, as indicated by both static PET and functional MRI (pBonferroni-Holm = 0.027), as well as constant infusion PET and functional MRI connectomes (pBonferroni-Holm = 0.012). This intensified coupling was associated with disease severity (ρ = 0.56, p = 0.036). CONCLUSION Metabolic connectivity, as revealed by both static and dynamic PET, provides unique information on metabolic network activity. Subject-level metabolic connectivity based on constant infusion PET may serve as a potential marker for the metabolic network signature in neurodegeneration.
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Affiliation(s)
- Marina C Ruppert-Junck
- Neurology Department at Medical Faculty Marburg, Philipps-University Marburg, Marburg, Germany.
- Neurology Department, University Hospital of Marburg and Gießen, Baldingerstraße, 35043, Marburg, Germany.
- Center for Mind, Brain and Behavior - CMBB, Universities Marburg and Gießen, Marburg, Germany.
| | - Vanessa Heinecke
- Neurology Department at Medical Faculty Marburg, Philipps-University Marburg, Marburg, Germany
| | - Damiano Librizzi
- Nuclear Medicine Department, Philipps-University Marburg, Marburg, Germany
| | - Kenan Steidel
- Neurology Department at Medical Faculty Marburg, Philipps-University Marburg, Marburg, Germany
- Neurology Department, University Hospital of Marburg and Gießen, Baldingerstraße, 35043, Marburg, Germany
| | - Maya Beckersjürgen
- Neurology Department at Medical Faculty Marburg, Philipps-University Marburg, Marburg, Germany
| | - Frederik A Verburg
- Nuclear Medicine Department, Philipps-University Marburg, Marburg, Germany
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Tino Schurrat
- Nuclear Medicine Department, Philipps-University Marburg, Marburg, Germany
| | - Markus Luster
- Nuclear Medicine Department, Philipps-University Marburg, Marburg, Germany
| | - Hans-Helge Müller
- Institute for Medical Bioinformatics and Biostatistics, Philipps-University Marburg, Marburg, Germany
| | - Lars Timmermann
- Neurology Department at Medical Faculty Marburg, Philipps-University Marburg, Marburg, Germany
- Neurology Department, University Hospital of Marburg and Gießen, Baldingerstraße, 35043, Marburg, Germany
- Center for Mind, Brain and Behavior - CMBB, Universities Marburg and Gießen, Marburg, Germany
| | - Carsten Eggers
- Neurology Department at Medical Faculty Marburg, Philipps-University Marburg, Marburg, Germany
- Neurology Department, University Hospital of Marburg and Gießen, Baldingerstraße, 35043, Marburg, Germany
- Knappschaftskrankenhaus Bottrop GmbH, Bottrop, Germany
| | - David Pedrosa
- Neurology Department at Medical Faculty Marburg, Philipps-University Marburg, Marburg, Germany
- Neurology Department, University Hospital of Marburg and Gießen, Baldingerstraße, 35043, Marburg, Germany
- Center for Mind, Brain and Behavior - CMBB, Universities Marburg and Gießen, Marburg, Germany
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4
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Crocetta A, Liloia D, Costa T, Duca S, Cauda F, Manuello J. From gut to brain: unveiling probiotic effects through a neuroimaging perspective-A systematic review of randomized controlled trials. Front Nutr 2024; 11:1446854. [PMID: 39360283 PMCID: PMC11444994 DOI: 10.3389/fnut.2024.1446854] [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: 06/10/2024] [Accepted: 09/02/2024] [Indexed: 10/04/2024] Open
Abstract
The gut-brain axis, a bidirectional communication network between the gastrointestinal system and the brain, significantly influences mental health and behavior. Probiotics, live microorganisms conferring health benefits, have garnered attention for their potential to modulate this axis. However, their effects on brain function through gut microbiota modulation remain controversial. This systematic review examines the effects of probiotics on brain activity and functioning, focusing on randomized controlled trials using both resting-state and task-based functional magnetic resonance imaging (fMRI) methodologies. Studies investigating probiotic effects on brain activity in healthy individuals and clinical populations (i.e., major depressive disorder and irritable bowel syndrome) were identified. In healthy individuals, task-based fMRI studies indicated that probiotics modulate brain activity related to emotional regulation and cognitive processing, particularly in high-order areas such as the amygdala, precuneus, and orbitofrontal cortex. Resting-state fMRI studies revealed changes in connectivity patterns, such as increased activation in the Salience Network and reduced activity in the Default Mode Network. In clinical populations, task-based fMRI studies showed that probiotics could normalize brain function in patients with major depressive disorder and irritable bowel syndrome. Resting-state fMRI studies further suggested improved connectivity in mood-regulating networks, specifically in the subcallosal cortex, amygdala and hippocampus. Despite promising findings, methodological variability and limited sample sizes emphasize the need for rigorous, longitudinal research to clarify the beneficial effects of probiotics on the gut-brain axis and mental health.
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Affiliation(s)
- Annachiara Crocetta
- Department of Psychology, Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, University of Turin, Turin, Italy
- Department of Psychology, GCS fMRI, Koelliker Hospital, University of Turin, Turin, Italy
| | - Donato Liloia
- Department of Psychology, Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, University of Turin, Turin, Italy
- Department of Psychology, GCS fMRI, Koelliker Hospital, University of Turin, Turin, Italy
| | - Tommaso Costa
- Department of Psychology, Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, University of Turin, Turin, Italy
- Department of Psychology, GCS fMRI, Koelliker Hospital, University of Turin, Turin, Italy
- Neuroscience Institute of Turin (NIT), University of Turin, Turin, Italy
| | - Sergio Duca
- Department of Psychology, GCS fMRI, Koelliker Hospital, University of Turin, Turin, Italy
| | - Franco Cauda
- Department of Psychology, Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, University of Turin, Turin, Italy
- Department of Psychology, GCS fMRI, Koelliker Hospital, University of Turin, Turin, Italy
- Neuroscience Institute of Turin (NIT), University of Turin, Turin, Italy
| | - Jordi Manuello
- Department of Psychology, Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, University of Turin, Turin, Italy
- Department of Psychology, GCS fMRI, Koelliker Hospital, University of Turin, Turin, Italy
- Move’N’Brains Lab, Department of Psychology, University of Turin, Turin, Italy
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5
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Hsu LM, Shih YYI. Neuromodulation in Small Animal fMRI. J Magn Reson Imaging 2024. [PMID: 39279265 DOI: 10.1002/jmri.29575] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Revised: 08/01/2024] [Accepted: 08/02/2024] [Indexed: 09/18/2024] Open
Abstract
The integration of functional magnetic resonance imaging (fMRI) with advanced neuroscience technologies in experimental small animal models offers a unique path to interrogate the causal relationships between regional brain activity and brain-wide network measures-a goal challenging to accomplish in human subjects. This review traces the historical development of the neuromodulation techniques commonly used in rodents, such as electrical deep brain stimulation, optogenetics, and chemogenetics, and focuses on their application with fMRI. We discuss their advantageousness roles in uncovering the signaling architecture within the brain and the methodological considerations necessary when conducting these experiments. By presenting several rodent-based case studies, we aim to demonstrate the potential of the multimodal neuromodulation approach in shedding light on neurovascular coupling, the neural basis of brain network functions, and their connections to behaviors. Key findings highlight the cell-type and circuit-specific modulation of brain-wide activity patterns and their behavioral correlates. We also discuss several future directions and feature the use of mediation and moderation analytical models beyond the intuitive evoked response mapping, to better leverage the rich information available in fMRI data with neuromodulation. Using fMRI alongside neuromodulation techniques provide insights into the mesoscopic (relating to the intermediate scale between single neurons and large-scale brain networks) and macroscopic fMRI measures that correlate with specific neuronal events. This integration bridges the gap between different scales of neuroscience research, facilitating the exploration and testing of novel therapeutic strategies aimed at altering network-mediated behaviors. In conclusion, the combination of fMRI with neuromodulation techniques provides crucial insights into mesoscopic and macroscopic brain dynamics, advancing our understanding of brain function in health and disease. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Li-Ming Hsu
- Center for Animal Magnetic Resonance Imaging, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Biomedical Research Imaging Center, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Department of Radiology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Yen-Yu Ian Shih
- Center for Animal Magnetic Resonance Imaging, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Biomedical Research Imaging Center, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Department of Neurology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
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6
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Calabro FJ, Parr AC, Sydnor VJ, Hetherington H, Prasad KM, Ibrahim TS, Sarpal DK, Famalette A, Verma P, Luna B. Leveraging ultra-high field (7T) MRI in psychiatric research. Neuropsychopharmacology 2024:10.1038/s41386-024-01980-6. [PMID: 39251774 DOI: 10.1038/s41386-024-01980-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2024] [Revised: 06/21/2024] [Accepted: 07/23/2024] [Indexed: 09/11/2024]
Abstract
Non-invasive brain imaging has played a critical role in establishing our understanding of the neural properties that contribute to the emergence of psychiatric disorders. However, characterizing core neurobiological mechanisms of psychiatric symptomatology requires greater structural, functional, and neurochemical specificity than is typically obtainable with standard field strength MRI acquisitions (e.g., 3T). Ultra-high field (UHF) imaging at 7 Tesla (7T) provides the opportunity to identify neurobiological systems that confer risk, determine etiology, and characterize disease progression and treatment outcomes of major mental illnesses. Increases in scanner availability, regulatory approval, and sequence availability have made the application of UHF to clinical cohorts more feasible than ever before, yet the application of UHF approaches to the study of mental health remains nascent. In this technical review, we describe core neuroimaging methodologies which benefit from UHF acquisition, including high resolution structural and functional imaging, single (1H) and multi-nuclear (e.g., 31P) MR spectroscopy, and quantitative MR techniques for assessing brain tissue iron and myelin. We discuss advantages provided by 7T MRI, including higher signal- and contrast-to-noise ratio, enhanced spatial resolution, increased test-retest reliability, and molecular and neurochemical specificity, and how these have begun to uncover mechanisms of psychiatric disorders. Finally, we consider current limitations of UHF in its application to clinical cohorts, and point to ongoing work that aims to overcome technical hurdles through the continued development of UHF hardware, software, and protocols.
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Affiliation(s)
- Finnegan J Calabro
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.
| | - Ashley C Parr
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Valerie J Sydnor
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Konasale M Prasad
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, PA, USA
| | - Tamer S Ibrahim
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Deepak K Sarpal
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Alyssa Famalette
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Piya Verma
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Beatriz Luna
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
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7
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Wu YL, Christodoulou AG, Beumer JH, Rigatti LH, Fisher R, Ross M, Watkins S, Cortes DRE, Ruck C, Manzoor S, Wyman SK, Stapleton MC, Goetzman E, Bharathi S, Wipf P, Wang H, Tan T, Christner SM, Guo J, Lo CWY, Epperly MW, Greenberger JS. Mitigation of Fetal Radiation Injury from Mid-Gestation Total-body Irradiation by Maternal Administration of Mitochondrial-Targeted GS-Nitroxide JP4-039. Radiat Res 2024; 202:565-579. [PMID: 39074819 DOI: 10.1667/rade-24-00095.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Accepted: 06/11/2024] [Indexed: 07/31/2024]
Abstract
Victims of a radiation terrorist event will include pregnant women and unborn fetuses. Mitochondrial dysfunction and oxidative stress are key pathogenic factors of fetal radiation injury. The goal of this preclinical study is to investigate the efficacy of mitigating fetal radiation injury by maternal administration of the mitochondrial-targeted gramicidin S (GS)-nitroxide radiation mitigator JP4-039. Pregnant female C57BL/6NTac mice received 3 Gy total-body irradiation (TBI) at mid-gestation embryonic day 13.5 (E13.5). Using novel time-and-motion-resolved 4D in utero magnetic resonance imaging (4D-uMRI), we found TBI caused extensive injury to the fetal brain that included cerebral hemorrhage, loss of cerebral tissue, and hydrocephalus with excessive accumulation of cerebrospinal fluid (CSF). Histopathology of the fetal mouse brain showed broken cerebral vessels and elevated apoptosis. Further use of novel 4D Oxy-wavelet MRI capable of probing in vivo mitochondrial function in intact brain revealed a significant reduction of mitochondrial function in the fetal brain after 3 Gy TBI. This was validated by ex vivo Oroboros mitochondrial respirometry. One day after TBI (E14.5) maternal administration of JP4-039, which passes through the placenta, significantly reduced fetal brain radiation injury and improved fetal brain mitochondrial respiration. Treatment also preserved cerebral brain tissue integrity and reduced cerebral hemorrhage and cell death. JP4-039 administration following irradiation resulted in increased survival of pups. These findings indicate that JP4-039 can be deployed as a safe and effective mitigator of fetal radiation injury from mid-gestational in utero ionizing radiation exposure.
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Affiliation(s)
- Yijen L Wu
- Department of Pediatrics, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania 15201
- Rangos Research Center Animal Imaging Core, Children's Hospital of Pittsburgh of UPMC, Pittsburgh, Pennsylvania 15224
| | - Anthony G Christodoulou
- Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095
| | - Jan H Beumer
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania 15261
- Cancer Therapeutics Program, UPMC Hillman Cancer Center, Pittsburgh, Pennsylvania 15232
| | - Lora H Rigatti
- Division of Laboratory Animal Resources (DLAR), University of Pittsburgh, Pittsburgh, Pennsylvania 15213
| | - Renee Fisher
- Department of Radiation Oncology, School of Medicine, UPMC Hillman Cancer Center, Pittsburgh, PA 15232
| | - Mark Ross
- Department of Cell Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania 15260
| | - Simon Watkins
- Department of Cell Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania 15260
| | - Devin R E Cortes
- Department of Pediatrics, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania 15201
- Rangos Research Center Animal Imaging Core, Children's Hospital of Pittsburgh of UPMC, Pittsburgh, Pennsylvania 15224
- Department of Biomedical Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania 15261
| | - Cody Ruck
- Department of Pediatrics, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania 15201
- Rangos Research Center Animal Imaging Core, Children's Hospital of Pittsburgh of UPMC, Pittsburgh, Pennsylvania 15224
| | - Shanim Manzoor
- Department of Pediatrics, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania 15201
- Rangos Research Center Animal Imaging Core, Children's Hospital of Pittsburgh of UPMC, Pittsburgh, Pennsylvania 15224
| | - Samuel K Wyman
- Department of Pediatrics, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania 15201
- Rangos Research Center Animal Imaging Core, Children's Hospital of Pittsburgh of UPMC, Pittsburgh, Pennsylvania 15224
| | - Margaret C Stapleton
- Department of Pediatrics, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania 15201
| | - Eric Goetzman
- Department of Pediatrics, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania 15201
| | - Sivakama Bharathi
- Department of Pediatrics, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania 15201
| | - Peter Wipf
- Department of Biomedical Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania 15261
- Department of Chemistry, Kenneth P. Dietrich School of Arts & Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania 15260
| | - Hong Wang
- Department of Biostatistics, University of Pittsburgh, Pittsburgh, Pennsylvania 15260
| | - Tuantuan Tan
- Department of Pediatrics, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania 15201
| | - Susan M Christner
- Cancer Therapeutics Program, UPMC Hillman Cancer Center, Pittsburgh, Pennsylvania 15232
| | - Jianxia Guo
- Cancer Therapeutics Program, UPMC Hillman Cancer Center, Pittsburgh, Pennsylvania 15232
| | - Cecilia W Y Lo
- Department of Pediatrics, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania 15201
| | - Michael W Epperly
- Department of Radiation Oncology, School of Medicine, UPMC Hillman Cancer Center, Pittsburgh, PA 15232
| | - Joel S Greenberger
- Department of Radiation Oncology, School of Medicine, UPMC Hillman Cancer Center, Pittsburgh, PA 15232
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8
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Volpi T, Silvestri E, Aiello M, Lee JJ, Vlassenko AG, Goyal MS, Corbetta M, Bertoldo A. The brain's "dark energy" puzzle: How strongly is glucose metabolism linked to resting-state brain activity? J Cereb Blood Flow Metab 2024; 44:1433-1449. [PMID: 38443762 PMCID: PMC11342718 DOI: 10.1177/0271678x241237974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 01/05/2024] [Accepted: 02/11/2024] [Indexed: 03/07/2024]
Abstract
Brain glucose metabolism, which can be investigated at the macroscale level with [18F]FDG PET, displays significant regional variability for reasons that remain unclear. Some of the functional drivers behind this heterogeneity may be captured by resting-state functional magnetic resonance imaging (rs-fMRI). However, the full extent to which an fMRI-based description of the brain's spontaneous activity can describe local metabolism is unknown. Here, using two multimodal datasets of healthy participants, we built a multivariable multilevel model of functional-metabolic associations, assessing multiple functional features, describing the 1) rs-fMRI signal, 2) hemodynamic response, 3) static and 4) time-varying functional connectivity, as predictors of the human brain's metabolic architecture. The full model was trained on one dataset and tested on the other to assess its reproducibility. We found that functional-metabolic spatial coupling is nonlinear and heterogeneous across the brain, and that local measures of rs-fMRI activity and synchrony are more tightly coupled to local metabolism. In the testing dataset, the degree of functional-metabolic spatial coupling was also related to peripheral metabolism. Overall, although a significant proportion of regional metabolic variability can be described by measures of spontaneous activity, additional efforts are needed to explain the remaining variance in the brain's 'dark energy'.
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Affiliation(s)
- Tommaso Volpi
- Padova Neuroscience Center, University of Padova, Padova, Italy
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
| | - Erica Silvestri
- Department of Information Engineering, University of Padova, Padova, Italy
| | | | - John J Lee
- Neuroimaging Laboratories at the Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - Andrei G Vlassenko
- Neuroimaging Laboratories at the Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - Manu S Goyal
- Neuroimaging Laboratories at the Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - Maurizio Corbetta
- Padova Neuroscience Center, University of Padova, Padova, Italy
- Department of Neuroscience, University of Padova, Padova, Italy
| | - Alessandra Bertoldo
- Padova Neuroscience Center, University of Padova, Padova, Italy
- Department of Information Engineering, University of Padova, Padova, Italy
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9
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Chen H, Mirg S, Gaddale P, Agrawal S, Li M, Nguyen V, Xu T, Li Q, Liu J, Tu W, Liu X, Drew PJ, Zhang N, Gluckman BJ, Kothapalli S. Multiparametric Brain Hemodynamics Imaging Using a Combined Ultrafast Ultrasound and Photoacoustic System. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2401467. [PMID: 38884161 PMCID: PMC11336909 DOI: 10.1002/advs.202401467] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Revised: 04/25/2024] [Indexed: 06/18/2024]
Abstract
Studying brain-wide hemodynamic responses to different stimuli at high spatiotemporal resolutions can help gain new insights into the mechanisms of neuro- diseases and -disorders. Nonetheless, this task is challenging, primarily due to the complexity of neurovascular coupling, which encompasses interdependent hemodynamic parameters including cerebral blood volume (CBV), cerebral blood flow (CBF), and cerebral oxygen saturation (SO2). The current brain imaging technologies exhibit inherent limitations in resolution, sensitivity, and imaging depth, restricting their capacity to comprehensively capture the intricacies of cerebral functions. To address this, a multimodal functional ultrasound and photoacoustic (fUSPA) imaging platform is reported, which integrates ultrafast ultrasound and multispectral photoacoustic imaging methods in a compact head-mountable device, to quantitatively map individual dynamics of CBV, CBF, and SO2 as well as contrast agent enhanced brain imaging at high spatiotemporal resolutions. Following systematic characterization, the fUSPA system is applied to study brain-wide cerebrovascular reactivity (CVR) at single-vessel resolution via relative changes in CBV, CBF, and SO2 in response to hypercapnia stimulation. These results show that cortical veins and arteries exhibit differences in CVR in the stimulated state and consistent anti-correlation in CBV oscillations during the resting state, demonstrating the multiparametric fUSPA system's unique capabilities in investigating complex mechanisms of brain functions.
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Affiliation(s)
- Haoyang Chen
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Center for Neural EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Shubham Mirg
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Center for Neural EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Prameth Gaddale
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Sumit Agrawal
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Menghan Li
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Van Nguyen
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Tianbao Xu
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Qiong Li
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Jinyun Liu
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Wenyu Tu
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Xiao Liu
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Institute for Computational and Data SciencesThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Patrick J. Drew
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Center for Neural EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Department of Engineering Science and MechanicsThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Department of BiologyThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Department of NeurosurgeryThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Nanyin Zhang
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Center for Neural EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Bruce J. Gluckman
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Center for Neural EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Department of Engineering Science and MechanicsThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Department of NeurosurgeryThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Sri‐Rajasekhar Kothapalli
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Center for Neural EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Penn State Cancer InstituteThe Pennsylvania State UniversityHersheyPA17033USA
- Graduate Program in AcousticsThe Pennsylvania State UniversityUniversity ParkPA16802USA
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10
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Wright AM, Xu T, Ingram J, Koo J, Zhao Y, Tong Y, Wen Q. Robust data-driven segmentation of pulsatile cerebral vessels using functional magnetic resonance imaging. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.17.603932. [PMID: 39091755 PMCID: PMC11290998 DOI: 10.1101/2024.07.17.603932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/04/2024]
Abstract
Functional magnetic resonance imaging (fMRI) captures rich physiological and neuronal information that can offer insights into neurofluid dynamics, vascular health, and waste clearance function. The availability of cerebral vessel segmentation could facilitate fluid dynamics research in fMRI. However, without magnetic resonance angiography scans, cerebral vessel segmentation is challenging and time-consuming. This study leverages cardiac-induced pulsatile fMRI signal to develop a data-driven, automatic segmentation of large cerebral arteries and the superior sagittal sinus (SSS). The method was validated in a local dataset by comparing it to ground truth cerebral artery and SSS segmentations. Using the Human Connectome Project (HCP) aging dataset, the method's reproducibility was tested on 422 participants aged 36 to 100 years, each with four repeated fMRI scans. The method demonstrated high reproducibility, with an intraclass correlation coefficient > 0.7 in both cerebral artery and SSS segmentation volumes. This study demonstrates that the large cerebral arteries and SSS can be reproducibly and automatically segmented in fMRI datasets, facilitating the investigation of fluid dynamics in these regions.
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11
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Jiang Y, Pais‐Roldán P, Pohmann R, Yu X. High Spatiotemporal Resolution Radial Encoding Single-Vessel fMRI. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2309218. [PMID: 38689514 PMCID: PMC11234406 DOI: 10.1002/advs.202309218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 03/23/2024] [Indexed: 05/02/2024]
Abstract
High-field preclinical functional MRI (fMRI) is enabled the high spatial resolution mapping of vessel-specific hemodynamic responses, that is single-vessel fMRI. In contrast to investigating the neuronal sources of the fMRI signal, single-vessel fMRI focuses on elucidating its vascular origin, which can be readily implemented to identify vascular changes relevant to vascular dementia or cognitive impairment. However, the limited spatial and temporal resolution of fMRI is hindered hemodynamic mapping of intracortical microvessels. Here, the radial encoding MRI scheme is implemented to measure BOLD signals of individual vessels penetrating the rat somatosensory cortex. Radial encoding MRI is employed to map cortical activation with a focal field of view (FOV), allowing vessel-specific functional mapping with 50 × 50 µm2 in-plane resolution at a 1 to 2 Hz sampling rate. Besides detecting refined hemodynamic responses of intracortical micro-venules, the radial encoding-based single-vessel fMRI enables the distinction of fMRI signals from vessel and peri-vessel voxels due to the different contribution of intravascular and extravascular effects.
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Affiliation(s)
- Yuanyuan Jiang
- Athinoula A. Martinos Center for Biomedical ImagingMassachusetts General Hospital and Harvard Medical SchoolCharlestownMA02129USA
| | - Patricia Pais‐Roldán
- Institute of Neuroscience and Medicine 4Medical Imaging PhysicsForschungszentrum Jülich52425JülichGermany
| | - Rolf Pohmann
- High‐Field Magnetic ResonanceMax Planck Institute for Biological Cybernetics72076TübingenGermany
| | - Xin Yu
- Athinoula A. Martinos Center for Biomedical ImagingMassachusetts General Hospital and Harvard Medical SchoolCharlestownMA02129USA
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12
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Song B, Yoshida S. Explainability of three-dimensional convolutional neural networks for functional magnetic resonance imaging of Alzheimer's disease classification based on gradient-weighted class activation mapping. PLoS One 2024; 19:e0303278. [PMID: 38771733 PMCID: PMC11108152 DOI: 10.1371/journal.pone.0303278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 04/22/2024] [Indexed: 05/23/2024] Open
Abstract
Currently, numerous studies focus on employing fMRI-based deep neural networks to diagnose neurological disorders such as Alzheimer's Disease (AD), yet only a handful have provided results regarding explainability. We address this gap by applying several prevalent explainability methods such as gradient-weighted class activation mapping (Grad-CAM) to an fMRI-based 3D-VGG16 network for AD diagnosis to improve the model's explainability. The aim is to explore the specific Region of Interest (ROI) of brain the model primarily focuses on when making predictions, as well as whether there are differences in these ROIs between AD and normal controls (NCs). First, we utilized multiple resting-state functional activity maps including ALFF, fALFF, ReHo, and VMHC to reduce the complexity of fMRI data, which differed from many studies that utilized raw fMRI data. Compared to methods utilizing raw fMRI data, this manual feature extraction approach may potentially alleviate the model's burden. Subsequently, 3D-VGG16 were employed for AD classification, where the final fully connected layers were replaced with a Global Average Pooling (GAP) layer, aimed at mitigating overfitting while preserving spatial information within the feature maps. The model achieved a maximum of 96.4% accuracy on the test set. Finally, several 3D CAM methods were employed to interpret the models. In the explainability results of the models with relatively high accuracy, the highlighted ROIs were primarily located in the precuneus and the hippocampus for AD subjects, while the models focused on the entire brain for NC. This supports current research on ROIs involved in AD. We believe that explaining deep learning models would not only provide support for existing research on brain disorders, but also offer important referential recommendations for the study of currently unknown etiologies.
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Affiliation(s)
- Boyue Song
- Graduate School of Engineering, Kochi University of Technology, Kami City, Kochi Prefecture, Japan
| | - Shinichi Yoshida
- School of Information, Kochi University of Technology, Kami City, Kochi Prefecture, Japan
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13
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DiNuzzo M, Dienel GA, Behar KL, Petroff OA, Benveniste H, Hyder F, Giove F, Michaeli S, Mangia S, Herculano-Houzel S, Rothman DL. Neurovascular coupling is optimized to compensate for the increase in proton production from nonoxidative glycolysis and glycogenolysis during brain activation and maintain homeostasis of pH, pCO 2, and pO 2. J Neurochem 2024; 168:632-662. [PMID: 37150946 PMCID: PMC10628336 DOI: 10.1111/jnc.15839] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 04/22/2023] [Accepted: 05/02/2023] [Indexed: 05/09/2023]
Abstract
During transient brain activation cerebral blood flow (CBF) increases substantially more than cerebral metabolic rate of oxygen consumption (CMRO2) resulting in blood hyperoxygenation, the basis of BOLD-fMRI contrast. Explanations for the high CBF versus CMRO2 slope, termed neurovascular coupling (NVC) constant, focused on maintenance of tissue oxygenation to support mitochondrial ATP production. However, paradoxically the brain has a 3-fold lower oxygen extraction fraction (OEF) than other organs with high energy requirements, like heart and muscle during exercise. Here, we hypothesize that the NVC constant and the capillary oxygen mass transfer coefficient (which in combination determine OEF) are co-regulated during activation to maintain simultaneous homeostasis of pH and partial pressure of CO2 and O2 (pCO2 and pO2). To test our hypothesis, we developed an arteriovenous flux balance model for calculating blood and brain pH, pCO2, and pO2 as a function of baseline OEF (OEF0), CBF, CMRO2, and proton production by nonoxidative metabolism coupled to ATP hydrolysis. Our model was validated against published brain arteriovenous difference studies and then used to calculate pH, pCO2, and pO2 in activated human cortex from published calibrated fMRI and PET measurements. In agreement with our hypothesis, calculated pH, pCO2, and pO2 remained close to constant independently of CMRO2 in correspondence to experimental measurements of NVC and OEF0. We also found that the optimum values of the NVC constant and OEF0 that ensure simultaneous homeostasis of pH, pCO2, and pO2 were remarkably similar to their experimental values. Thus, the high NVC constant is overall determined by proton removal by CBF due to increases in nonoxidative glycolysis and glycogenolysis. These findings resolve the paradox of the brain's high CBF yet low OEF during activation, and may contribute to explaining the vulnerability of brain function to reductions in blood flow and capillary density with aging and neurovascular disease.
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Affiliation(s)
| | - Gerald A Dienel
- Department of Neurology, University of Arkansas for Medical Sciences, Little Rock, AR, 72205 USA
- Department of Cell Biology and Physiology, University of New Mexico School of Medicine, Albuquerque, NM, 87131 USA
| | - Kevin L Behar
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, 06511 USA
| | - Ognen A Petroff
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, 06511 USA
| | - Helene Benveniste
- Department of Anesthesiology, Yale University, New Haven, CT, 06520 USA
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520 USA
| | - Fahmeed Hyder
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520 USA
- Department of Radiology, Magnetic Resonance Research Center (MRRC), Yale University, New Haven, CT, 06520 USA
| | - Federico Giove
- Centro Ricerche Enrico Fermi, Rome, RM, 00184 Italy
- Fondazione Santa Lucia IRCCS, Rome, RM, 00179 Italy
| | - Shalom Michaeli
- Department of Radiology, Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN, 55455 USA
| | - Silvia Mangia
- Department of Radiology, Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN, 55455 USA
| | - Suzana Herculano-Houzel
- Department of Psychology, Vanderbilt University, Nashville, TN
- Department of Biological Sciences, Vanderbilt University, Nashville, TN
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN
| | - Douglas L Rothman
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520 USA
- Department of Radiology, Magnetic Resonance Research Center (MRRC), Yale University, New Haven, CT, 06520 USA
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14
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Rué‐Queralt J, Fluhr H, Tourbier S, Aleman‐Gómez Y, Pascucci D, Yerly J, Glomb K, Plomp G, Hagmann P. Connectome spectrum electromagnetic tomography: A method to reconstruct electrical brain source networks at high-spatial resolution. Hum Brain Mapp 2024; 45:e26638. [PMID: 38520365 PMCID: PMC10960556 DOI: 10.1002/hbm.26638] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 02/01/2024] [Accepted: 02/13/2024] [Indexed: 03/25/2024] Open
Abstract
Connectome spectrum electromagnetic tomography (CSET) combines diffusion MRI-derived structural connectivity data with well-established graph signal processing tools to solve the M/EEG inverse problem. Using simulated EEG signals from fMRI responses, and two EEG datasets on visual-evoked potentials, we provide evidence supporting that (i) CSET captures realistic neurophysiological patterns with better accuracy than state-of-the-art methods, (ii) CSET can reconstruct brain responses more accurately and with more robustness to intrinsic noise in the EEG signal. These results demonstrate that CSET offers high spatio-temporal accuracy, enabling neuroscientists to extend their research beyond the current limitations of low sampling frequency in functional MRI and the poor spatial resolution of M/EEG.
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Affiliation(s)
- Joan Rué‐Queralt
- Department of RadiologyLausanne University Hospital and University of Lausanne (CHUV‐UNIL)LausanneSwitzerland
- Department of PsychologyUniversity of FribourgFribourgSwitzerland
- Center for ImagingEPFLLausanneSwitzerland
| | - Hugo Fluhr
- Department of RadiologyLausanne University Hospital and University of Lausanne (CHUV‐UNIL)LausanneSwitzerland
| | - Sebastien Tourbier
- Department of RadiologyLausanne University Hospital and University of Lausanne (CHUV‐UNIL)LausanneSwitzerland
| | - Yasser Aleman‐Gómez
- Department of RadiologyLausanne University Hospital and University of Lausanne (CHUV‐UNIL)LausanneSwitzerland
- Department of PsychiatryLausanne University HospitalLausanneSwitzerland
| | | | - Jérôme Yerly
- Department of Diagnostic and Interventional RadiologyLausanne University HospitalLausanneSwitzerland
- Center for Biomedical ImagingEPFLLausanneSwitzerland
| | - Katharina Glomb
- Department of NeurologyCharité University Medicine Berlin and Berlin Institute of HealthBerlinGermany
| | - Gijs Plomp
- Department of PsychologyUniversity of FribourgFribourgSwitzerland
| | - Patric Hagmann
- Department of RadiologyLausanne University Hospital and University of Lausanne (CHUV‐UNIL)LausanneSwitzerland
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15
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Amemiya S, Takao H, Abe O. Resting-State fMRI: Emerging Concepts for Future Clinical Application. J Magn Reson Imaging 2024; 59:1135-1148. [PMID: 37424140 DOI: 10.1002/jmri.28894] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 06/22/2023] [Accepted: 06/22/2023] [Indexed: 07/11/2023] Open
Abstract
Resting-state functional magnetic resonance imaging (rsfMRI) has been developed as a method of investigating spontaneous neural activity. Based on its low-frequency signal synchronization, rsfMRI has made it possible to identify multiple macroscopic structures termed resting-state networks (RSNs) on a single scan of less than 10 minutes. It is easy to implement even in clinical practice, in which assigning tasks to patients can be challenging. These advantages have accelerated the adoption and growth of rsfMRI. Recently, studies on the global rsfMRI signal have attracted increasing attention. Because it primarily arises from physiological events, less attention has hitherto been paid to the global signal than to the local network (i.e., RSN) component. However, the global signal is not a mere nuisance or a subsidiary component. On the contrary, it is quantitatively the dominant component that accounts for most of the variance in the rsfMRI signal throughout the brain and provides rich information on local hemodynamics that can serve as an individual-level diagnostic biomarker. Moreover, spatiotemporal analyses of the global signal have revealed that it is closely and fundamentally associated with the organization of RSNs, thus challenging the basic assumptions made in conventional rsfMRI analyses and views on RSNs. This review introduces new concepts emerging from rsfMRI spatiotemporal analyses focusing on the global signal and discusses how they may contribute to future clinical medicine. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Shiori Amemiya
- Department of Radiology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Hidemasa Takao
- Department of Radiology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Osamu Abe
- Department of Radiology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
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16
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Kung YC, Li CW, Hsu AL, Liu CY, Wu CW, Chang WC, Lin CP. Neurovascular coupling in eye-open-eye-close task and resting state: Spectral correspondence between concurrent EEG and fMRI. Neuroimage 2024; 289:120535. [PMID: 38342188 DOI: 10.1016/j.neuroimage.2024.120535] [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: 09/09/2023] [Revised: 01/23/2024] [Accepted: 02/08/2024] [Indexed: 02/13/2024] Open
Abstract
Neurovascular coupling serves as an essential neurophysiological mechanism in functional neuroimaging, which is generally presumed to be robust and invariant across different physiological states, encompassing both task engagement and resting state. Nevertheless, emerging evidence suggests that neurovascular coupling may exhibit state dependency, even in normal human participants. To investigate this premise, we analyzed the cross-frequency spectral correspondence between concurrently recorded electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data, utilizing them as proxies for neurovascular coupling during the two conditions: an eye-open-eye-close (EOEC) task and a resting state. We hypothesized that given the state dependency of neurovascular coupling, EEG-fMRI spectral correspondences would change between the two conditions in the visual system. During the EOEC task, we observed a negative phase-amplitude-coupling (PAC) between EEG alpha-band and fMRI visual activity. Conversely, in the resting state, a pronounced amplitude-amplitude-coupling (AAC) emerged between EEG and fMRI signals, as evidenced by the spectral correspondence between the EEG gamma-band of the midline occipital channel (Oz) and the high-frequency fMRI signals (0.15-0.25 Hz) in the visual network. This study reveals distinct scenarios of EEG-fMRI spectral correspondence in healthy participants, corroborating the state-dependent nature of neurovascular coupling.
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Affiliation(s)
- Yi-Chia Kung
- Department of Radiology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Chia-Wei Li
- Department of Radiology, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan
| | - Ai-Ling Hsu
- Bachelor Program in Artificial Intelligence, Chang Gung University, Taoyuan, Taiwan; Department of Psychiatry, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Chi-Yun Liu
- Graduate Institute of Mind, Brain and Consciousness, Taipei Medical University, Taipei, Taiwan
| | - Changwei W Wu
- Graduate Institute of Mind, Brain and Consciousness, Taipei Medical University, Taipei, Taiwan; Research Center of Sleep Medicine, Taipei Medical University Hospital, Taipei, Taiwan.
| | - Wei-Chou Chang
- Department of Radiology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Ching-Po Lin
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Hsinchu, Taiwan; Department of Education and Research, Taipei City Hospital, Taipei, Taiwan
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17
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Beinlich FR, Asiminas A, Untiet V, Bojarowska Z, Plá V, Sigurdsson B, Timmel V, Gehrig L, Graber MH, Hirase H, Nedergaard M. Oxygen imaging of hypoxic pockets in the mouse cerebral cortex. Science 2024; 383:1471-1478. [PMID: 38547288 PMCID: PMC11251491 DOI: 10.1126/science.adn1011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 02/23/2024] [Indexed: 04/02/2024]
Abstract
Consciousness is lost within seconds upon cessation of cerebral blood flow. The brain cannot store oxygen, and interruption of oxidative phosphorylation is fatal within minutes. Yet only rudimentary knowledge exists regarding cortical partial oxygen tension (Po2) dynamics under physiological conditions. Here we introduce Green enhanced Nano-lantern (GeNL), a genetically encoded bioluminescent oxygen indicator for Po2 imaging. In awake behaving mice, we uncover the existence of spontaneous, spatially defined "hypoxic pockets" and demonstrate their linkage to the abrogation of local capillary flow. Exercise reduced the burden of hypoxic pockets by 52% compared with rest. The study provides insight into cortical oxygen dynamics in awake behaving animals and concurrently establishes a tool to delineate the importance of oxygen tension in physiological processes and neurological diseases.
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Affiliation(s)
- Felix R.M. Beinlich
- Division of Glial Disease and Therapeutics, Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of Copenhagen; 2200 Copenhagen, Denmark
| | - Antonios Asiminas
- Division of Glial Disease and Therapeutics, Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of Copenhagen; 2200 Copenhagen, Denmark
| | - Verena Untiet
- Division of Glial Disease and Therapeutics, Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of Copenhagen; 2200 Copenhagen, Denmark
| | - Zuzanna Bojarowska
- Division of Glial Disease and Therapeutics, Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of Copenhagen; 2200 Copenhagen, Denmark
| | - Virginia Plá
- Division of Glial Disease and Therapeutics, Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of Copenhagen; 2200 Copenhagen, Denmark
| | - Björn Sigurdsson
- Division of Glial Disease and Therapeutics, Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of Copenhagen; 2200 Copenhagen, Denmark
| | - Vincenzo Timmel
- School of Engineering, FHNW University of Applied Sciences and Arts Northwestern Switzerland; 5210 Windisch, Switzerland
| | - Lukas Gehrig
- School of Engineering, FHNW University of Applied Sciences and Arts Northwestern Switzerland; 5210 Windisch, Switzerland
| | - Michael H. Graber
- School of Engineering, FHNW University of Applied Sciences and Arts Northwestern Switzerland; 5210 Windisch, Switzerland
| | - Hajime Hirase
- Division of Glial Disease and Therapeutics, Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of Copenhagen; 2200 Copenhagen, Denmark
- Division of Glial Disease and Therapeutics, Center for Translational Neuromedicine, University of Rochester Medical Center; Rochester, NY 14642, USA
| | - Maiken Nedergaard
- Division of Glial Disease and Therapeutics, Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of Copenhagen; 2200 Copenhagen, Denmark
- Division of Glial Disease and Therapeutics, Center for Translational Neuromedicine, University of Rochester Medical Center; Rochester, NY 14642, USA
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18
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Choi SH, Im GH, Choi S, Yu X, Bandettini PA, Menon RS, Kim SG. No replication of direct neuronal activity-related (DIANA) fMRI in anesthetized mice. SCIENCE ADVANCES 2024; 10:eadl0999. [PMID: 38536912 PMCID: PMC10971415 DOI: 10.1126/sciadv.adl0999] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Accepted: 01/18/2024] [Indexed: 04/04/2024]
Abstract
Direct imaging of neuronal activity (DIANA) by functional magnetic resonance imaging (fMRI) could be a revolutionary approach for advancing systems neuroscience research. To independently replicate this observation, we performed fMRI experiments in anesthetized mice. The blood oxygenation level-dependent (BOLD) response to whisker stimulation was reliably detected in the primary barrel cortex before and after DIANA experiments; however, no DIANA-like fMRI peak was observed in individual animals' data with the 50 to 300 trials. Extensively averaged data involving 1050 trials in six mice showed a flat baseline and no detectable neuronal activity-like fMRI peak. However, spurious, nonreplicable peaks were found when using a small number of trials, and artifactual peaks were detected when some outlier-like trials were excluded. Further, no detectable DIANA peak was observed in the BOLD-responding thalamus from the selected trials with the neuronal activity-like reference function in the barrel cortex. Thus, we were unable to replicate the previously reported results without data preselection.
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Affiliation(s)
- Sang-Han Choi
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea
| | - Geun Ho Im
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea
| | - Sangcheon Choi
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA, USA
| | - Xin Yu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA, USA
| | - Peter A. Bandettini
- Section on Functional Imaging Methods and Functional MRI Facility, NIMH, NIH, Bethesda, MD, USA
| | - Ravi S. Menon
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, Western University, London, Ontario N6A 5B7, Canada
| | - Seong-Gi Kim
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea
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19
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Dinh TNA, Moon HS, Kim SG. Separation of bimodal fMRI responses in mouse somatosensory areas into V1 and non-V1 contributions. Sci Rep 2024; 14:6302. [PMID: 38491035 PMCID: PMC10943206 DOI: 10.1038/s41598-024-56305-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 03/05/2024] [Indexed: 03/18/2024] Open
Abstract
Multisensory integration is necessary for the animal to survive in the real world. While conventional methods have been extensively used to investigate the multisensory integration process in various brain areas, its long-range interactions remain less explored. In this study, our goal was to investigate interactions between visual and somatosensory networks on a whole-brain scale using 15.2-T BOLD fMRI. We compared unimodal to bimodal BOLD fMRI responses and dissected potential cross-modal pathways with silencing of primary visual cortex (V1) by optogenetic stimulation of local GABAergic neurons. Our data showed that the influence of visual stimulus on whisker activity is higher than the influence of whisker stimulus on visual activity. Optogenetic silencing of V1 revealed that visual information is conveyed to whisker processing via both V1 and non-V1 pathways. The first-order ventral posteromedial thalamic nucleus (VPM) was functionally affected by non-V1 sources, while the higher-order posterior medial thalamic nucleus (POm) was predominantly modulated by V1 but not non-V1 inputs. The primary somatosensory barrel field (S1BF) was influenced by both V1 and non-V1 inputs. These observations provide valuable insights for into the integration of whisker and visual sensory information.
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Affiliation(s)
- Thi Ngoc Anh Dinh
- Center for Neuroscience Imaging Research (CNIR), Institute for Basic Science (IBS), Suwon, 16419, South Korea
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, 16419, South Korea
| | - Hyun Seok Moon
- Center for Neuroscience Imaging Research (CNIR), Institute for Basic Science (IBS), Suwon, 16419, South Korea
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, 16419, South Korea
| | - Seong-Gi Kim
- Center for Neuroscience Imaging Research (CNIR), Institute for Basic Science (IBS), Suwon, 16419, South Korea.
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, 16419, South Korea.
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, 16419, South Korea.
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20
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Le TT, Im GH, Lee CH, Choi SH, Kim SG. Mapping cerebral perfusion in mice under various anesthesia levels using highly sensitive BOLD MRI with transient hypoxia. SCIENCE ADVANCES 2024; 10:eadm7605. [PMID: 38416820 PMCID: PMC10901365 DOI: 10.1126/sciadv.adm7605] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Accepted: 01/24/2024] [Indexed: 03/01/2024]
Abstract
Cerebral perfusion is critical for the early detection of neurological diseases and for effectively monitoring disease progression and treatment responses. Mouse models are widely used in brain research, often under anesthesia, which can affect vascular physiology. However, the impact of anesthesia on regional cerebral blood volume and flow in mice has not been thoroughly investigated. In this study, we have developed a whole-brain perfusion MRI approach by using a 5-second nitrogen gas stimulus under inhalational anesthetics to induce transient BOLD dynamic susceptibility contrast (DSC). This method proved to be highly sensitive, repeatable within each imaging session, and across four weekly sessions. Relative cerebral blood volumes measured by BOLD DSC agree well with those by contrast agents. Quantitative cerebral blood volume and flow metrics were successfully measured in mice under dexmedetomidine and various isoflurane doses using both total vasculature-sensitive gradient-echo and microvasculature-sensitive spin-echo BOLD MRI. Dexmedetomidine reduces cerebral perfusion, while isoflurane increases cerebral perfusion in a dose-dependent manner.
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Affiliation(s)
- Thuy Thi Le
- Center for Neuroscience Imaging Research (CNIR), Institute for Basic Science (IBS), Suwon, Republic of Korea
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Republic of Korea
| | - Geun Ho Im
- Center for Neuroscience Imaging Research (CNIR), Institute for Basic Science (IBS), Suwon, Republic of Korea
| | - Chan Hee Lee
- Center for Neuroscience Imaging Research (CNIR), Institute for Basic Science (IBS), Suwon, Republic of Korea
| | - Sang Han Choi
- Center for Neuroscience Imaging Research (CNIR), Institute for Basic Science (IBS), Suwon, Republic of Korea
| | - Seong-Gi Kim
- Center for Neuroscience Imaging Research (CNIR), Institute for Basic Science (IBS), Suwon, Republic of Korea
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Republic of Korea
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21
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Cerri DH, Albaugh DL, Walton LR, Katz B, Wang TW, Chao THH, Zhang W, Nonneman RJ, Jiang J, Lee SH, Etkin A, Hall CN, Stuber GD, Shih YYI. Distinct neurochemical influences on fMRI response polarity in the striatum. Nat Commun 2024; 15:1916. [PMID: 38429266 PMCID: PMC10907631 DOI: 10.1038/s41467-024-46088-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Accepted: 02/13/2024] [Indexed: 03/03/2024] Open
Abstract
The striatum, known as the input nucleus of the basal ganglia, is extensively studied for its diverse behavioral roles. However, the relationship between its neuronal and vascular activity, vital for interpreting functional magnetic resonance imaging (fMRI) signals, has not received comprehensive examination within the striatum. Here, we demonstrate that optogenetic stimulation of dorsal striatal neurons or their afferents from various cortical and subcortical regions induces negative striatal fMRI responses in rats, manifesting as vasoconstriction. These responses occur even with heightened striatal neuronal activity, confirmed by electrophysiology and fiber-photometry. In parallel, midbrain dopaminergic neuron optogenetic modulation, coupled with electrochemical measurements, establishes a link between striatal vasodilation and dopamine release. Intriguingly, in vivo intra-striatal pharmacological manipulations during optogenetic stimulation highlight a critical role of opioidergic signaling in generating striatal vasoconstriction. This observation is substantiated by detecting striatal vasoconstriction in brain slices after synthetic opioid application. In humans, manipulations aimed at increasing striatal neuronal activity likewise elicit negative striatal fMRI responses. Our results emphasize the necessity of considering vasoactive neurotransmission alongside neuronal activity when interpreting fMRI signal.
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Affiliation(s)
- Domenic H Cerri
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Daniel L Albaugh
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Lindsay R Walton
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Brittany Katz
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Tzu-Wen Wang
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Tzu-Hao Harry Chao
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Weiting Zhang
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Randal J Nonneman
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jing Jiang
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Department of Pediatrics, University of Iowa Carver College of Medicine, Iowa City, IA, USA
- Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, IA, USA
- Iowa Neuroscience Institute, University of Iowa Carver College of Medicine, Iowa City, IA, USA
| | - Sung-Ho Lee
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Amit Etkin
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Alto Neuroscience, Los Altos, CA, USA
| | - Catherine N Hall
- Sussex Neuroscience, University of Sussex, Falmer, United Kingdom
- School of Psychology, University of Sussex, Falmer, United Kingdom
| | - Garret D Stuber
- Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA, USA
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, USA
- Department of Pharmacology, University of Washington, Seattle, WA, USA
| | - Yen-Yu Ian Shih
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
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22
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Nakamura NH, Oku Y, Fukunaga M. "Brain-breath" interactions: respiration-timing-dependent impact on functional brain networks and beyond. Rev Neurosci 2024; 35:165-182. [PMID: 37651646 DOI: 10.1515/revneuro-2023-0062] [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: 06/05/2023] [Accepted: 08/06/2023] [Indexed: 09/02/2023]
Abstract
Breathing is a natural daily action that one cannot do without, and it sensitively and intensely changes under various situations. What if this essential act of breathing can impact our overall well-being? Recent studies have demonstrated that breathing oscillations couple with higher brain functions, i.e., perception, motor actions, and cognition. Moreover, the timing of breathing, a phase transition from exhalation to inhalation, modulates specific cortical activity and accuracy in cognitive tasks. To determine possible respiratory roles in attentional and memory processes and functional neural networks, we discussed how breathing interacts with the brain that are measured by electrophysiology and functional neuroimaging: (i) respiration-dependent modulation of mental health and cognition; (ii) respiratory rhythm generation and respiratory pontomedullary networks in the brainstem; (iii) respiration-dependent effects on specific brainstem regions and functional neural networks (e.g., glutamatergic PreBötzinger complex neurons, GABAergic parafacial neurons, adrenergic C1 neurons, parabrachial nucleus, locus coeruleus, temporoparietal junction, default-mode network, ventral attention network, and cingulo-opercular salience network); and (iv) a potential application of breathing manipulation in mental health care. These outlines and considerations of "brain-breath" interactions lead to a better understanding of the interoceptive and cognitive mechanisms that underlie brain-body interactions in health conditions and in stress-related and neuropsychiatric disorders.
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Affiliation(s)
- Nozomu H Nakamura
- Division of Physiome, Department of Physiology, Hyogo Medical University, 1-1, Mukogawa cho, Nishinomiya, Hyogo 663-8501, Japan
| | - Yoshitaka Oku
- Division of Physiome, Department of Physiology, Hyogo Medical University, 1-1, Mukogawa cho, Nishinomiya, Hyogo 663-8501, Japan
| | - Masaki Fukunaga
- Section of Brain Function Information, National Institute of Physiological Sciences, 38 Nishigonaka Myodaiji, Okazaki, Aichi 444-8585, Japan
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23
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Wu YL, Christodoulou AG, Beumer JH, Rigatti LH, Fisher R, Ross M, Watkins S, Cortes DRE, Ruck C, Manzoor S, Wyman SK, Stapleton MC, Goetzman E, Bharathi S, Wipf P, Tan T, Eiseman JL, Christner SM, Guo J, Lo CWY, Epperly MW, Greenberger JS. Mitigation of Fetal Irradiation Injury from Mid-Gestation Total Body Radiation with Mitochondrial-Targeted GS-Nitroxide JP4-039. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.13.580105. [PMID: 38405696 PMCID: PMC10888932 DOI: 10.1101/2024.02.13.580105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Victims of a radiation terrorist event will include pregnant women and unborn fetuses. Mitochondrial dysfunction and oxidative stress are key pathogenic factors of fetal irradiation injury. The goal of this preclinical study is to investigate the efficacy of mitigating fetal irradiation injury by maternal administration of the mitochondrial-targeted gramicidin S (GS)- nitroxide radiation mitigator, JP4-039. Pregnant female C57BL/6NTac mice received 3 Gy total body ionizing irradiation (TBI) at mid-gestation embryonic day 13.5 (E13.5). Using novel time- and-motion-resolved 4D in utero magnetic resonance imaging (4D-uMRI), we found TBI caused extensive injury to the fetal brain that included cerebral hemorrhage, loss of cerebral tissue, and hydrocephalus with excessive accumulation of cerebrospinal fluid (CSF). Histopathology of the fetal mouse brain showed broken cerebral vessels and elevated apoptosis. Further use of novel 4D Oxy-wavelet MRI capable of probing in vivo mitochondrial function in intact brain revealed significant reduction of mitochondrial function in the fetal brain after 3Gy TBI. This was validated by ex vivo Oroboros mitochondrial respirometry. Maternal administration JP4-039 one day after TBI (E14.5), which can pass through the placental barrier, significantly reduced fetal brain radiation injury and improved fetal brain mitochondrial respiration. This also preserved cerebral brain tissue integrity and reduced cerebral hemorrhage and cell death. As JP4-039 administration did not change litter sizes or fetus viability, together these findings indicate JP4-039 can be deployed as a safe and effective mitigator of fetal radiation injury from mid-gestational in utero ionizing radiation exposure. One Sentence Summary Mitochondrial-targeted gramicidin S (GS)-nitroxide JP4-039 is safe and effective radiation mitigator for mid-gestational fetal irradiation injury.
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24
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Yakovlev A, Gritskova A, Manzhurtsev A, Ublinskiy M, Menshchikov P, Vanin A, Kupriyanov D, Akhadov T, Semenova N. Dynamics of γ-aminobutyric acid concentration in the human brain in response to short visual stimulation. MAGMA (NEW YORK, N.Y.) 2024; 37:39-51. [PMID: 37715877 DOI: 10.1007/s10334-023-01118-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 08/30/2023] [Accepted: 08/31/2023] [Indexed: 09/18/2023]
Abstract
OBJECTIVE To find a possible quantitative relation between activation-induced fast (< 10 s) changes in the γ-aminobutyric acid (GABA) level and the amplitude of a blood oxygen level-dependent contrast (BOLD) response (according to magnetic resonance spectroscopy [MRS] and functional magnetic resonance imaging [fMRI]). MATERIALS AND METHODS fMRI data and MEGA-PRESS magnetic resonance spectra [echo time (TE)/repetition time (TR) = 68 ms/1500 ms] of an activated area in the visual cortex of 33 subjects were acquired using a 3 T MR scanner. Stimulation was performed by presenting an image of a flickering checkerboard for 3 s, repeated with an interval of 13.5 s. The time course of GABA and creatine (Cr) concentrations and the width and height of resonance lines were obtained with a nominal time resolution of 1.5 s. Changes in the linewidth and height of n-acetylaspartate (NAA) and Cr signals were used to determine the BOLD effect. RESULTS In response to the activation, the BOLD-corrected GABA + /Cr ratio increased by 5.0% (q = 0.027) and 3.8% (q = 0.048) at 1.6 and 3.1 s, respectively, after the start of the stimulus. Time courses of Cr and NAA signal width and height reached a maximum change at the 6th second (~ 1.2-1.5%, q < 0.05). CONCLUSION The quick response of the observed GABA concentration to the short stimulus is most likely due to a release of GABA from vesicles followed by its packaging back into vesicles.
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Affiliation(s)
- Alexey Yakovlev
- Clinical and Research Institute of Emergency Paediatric Surgery and Traumatology, Bol'shaya Polyanka St. 22, Moscow, 119180, Russian Federation.
- N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, Kosygina St. 4, Moscow, 119334, Russian Federation.
- Emanuel Institute of Biochemical Physics, Russian Academy of Sciences, Kosygina St. 4, Moscow, 119334, Russian Federation.
| | - Alexandra Gritskova
- Moscow State University, Leninskie Gory Str. 1, Moscow, 119991, Russian Federation
| | - Andrei Manzhurtsev
- Clinical and Research Institute of Emergency Paediatric Surgery and Traumatology, Bol'shaya Polyanka St. 22, Moscow, 119180, Russian Federation
- Emanuel Institute of Biochemical Physics, Russian Academy of Sciences, Kosygina St. 4, Moscow, 119334, Russian Federation
- Moscow State University, Leninskie Gory Str. 1, Moscow, 119991, Russian Federation
| | - Maxim Ublinskiy
- Clinical and Research Institute of Emergency Paediatric Surgery and Traumatology, Bol'shaya Polyanka St. 22, Moscow, 119180, Russian Federation
- Emanuel Institute of Biochemical Physics, Russian Academy of Sciences, Kosygina St. 4, Moscow, 119334, Russian Federation
- Moscow State University, Leninskie Gory Str. 1, Moscow, 119991, Russian Federation
| | - Petr Menshchikov
- Emanuel Institute of Biochemical Physics, Russian Academy of Sciences, Kosygina St. 4, Moscow, 119334, Russian Federation
- LLC Philips Healthcare, 13 Sergeya Makeeva Str., Moscow, 123022, Russian Federation
| | - Anatoly Vanin
- N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, Kosygina St. 4, Moscow, 119334, Russian Federation
| | - Dmitriy Kupriyanov
- LLC Philips Healthcare, 13 Sergeya Makeeva Str., Moscow, 123022, Russian Federation
| | - Tolib Akhadov
- Clinical and Research Institute of Emergency Paediatric Surgery and Traumatology, Bol'shaya Polyanka St. 22, Moscow, 119180, Russian Federation
- Moscow State University, Leninskie Gory Str. 1, Moscow, 119991, Russian Federation
| | - Natalia Semenova
- Clinical and Research Institute of Emergency Paediatric Surgery and Traumatology, Bol'shaya Polyanka St. 22, Moscow, 119180, Russian Federation
- N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, Kosygina St. 4, Moscow, 119334, Russian Federation
- Emanuel Institute of Biochemical Physics, Russian Academy of Sciences, Kosygina St. 4, Moscow, 119334, Russian Federation
- Moscow State University, Leninskie Gory Str. 1, Moscow, 119991, Russian Federation
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25
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Etekochay MO, Amaravadhi AR, González GV, Atanasov AG, Matin M, Mofatteh M, Steinbusch HW, Tesfaye T, Praticò D. Unveiling New Strategies Facilitating the Implementation of Artificial Intelligence in Neuroimaging for the Early Detection of Alzheimer's Disease. J Alzheimers Dis 2024; 99:1-20. [PMID: 38640152 DOI: 10.3233/jad-231135] [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] [Indexed: 04/21/2024]
Abstract
Alzheimer's disease (AD) is a chronic neurodegenerative disorder with a global impact. The past few decades have witnessed significant strides in comprehending the underlying pathophysiological mechanisms and developing diagnostic methodologies for AD, such as neuroimaging approaches. Neuroimaging techniques, including positron emission tomography and magnetic resonance imaging, have revolutionized the field by providing valuable insights into the structural and functional alterations in the brains of individuals with AD. These imaging modalities enable the detection of early biomarkers such as amyloid-β plaques and tau protein tangles, facilitating early and precise diagnosis. Furthermore, the emerging technologies encompassing blood-based biomarkers and neurochemical profiling exhibit promising results in the identification of specific molecular signatures for AD. The integration of machine learning algorithms and artificial intelligence has enhanced the predictive capacity of these diagnostic tools when analyzing complex datasets. In this review article, we will highlight not only some of the most used diagnostic imaging approaches in neurodegeneration research but focus much more on new tools like artificial intelligence, emphasizing their application in the realm of AD. These advancements hold immense potential for early detection and intervention, thereby paving the way for personalized therapeutic strategies and ultimately augmenting the quality of life for individuals affected by AD.
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Affiliation(s)
| | - Amoolya Rao Amaravadhi
- Internal Medicine, Malla Reddy Institute of Medical Sciences, Jeedimetla, Hyderabad, India
| | - Gabriel Villarrubia González
- Expert Systems and Applications Laboratory (ESALAB), Faculty of Science, University of Salamanca, Salamanca, Spain
| | - Atanas G Atanasov
- Department of Biotechnology and Nutrigenomics, Institute of Genetics and Animal Biotechnology of the Polish Academy of Sciences, Jastrzebiec, Poland
- Ludwig Boltzmann Institute Digital Health and Patient Safety, Medical University of Vienna, Vienna, Austria
| | - Maima Matin
- Ludwig Boltzmann Institute Digital Health and Patient Safety, Medical University of Vienna, Vienna, Austria
| | - Mohammad Mofatteh
- School of Medicine, Dentistry, and Biomedical Sciences, Queen's University Belfast, Belfast, UK
| | - Harry Wilhelm Steinbusch
- Department of Cellular and Translational Neuroscience, School for Mental Health and Neuroscience, Faculty of Health Medicine and Life Sciences, Maastricht University, Netherlands
| | - Tadele Tesfaye
- CareHealth Medical Practice, Jimma Road, Addis Ababa, Ethiopia
| | - Domenico Praticò
- Alzheimer's Center at Temple, Lewis Katz School of Medicine, Temple University, Philadelphia, PA, USA
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26
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Voets NL, Bartsch AJ, Plaha P. Functional MRI applications for intra-axial brain tumours: uses and nuances in surgical practise. Br J Neurosurg 2023; 37:1544-1559. [PMID: 36148501 DOI: 10.1080/02688697.2022.2123893] [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: 03/18/2022] [Accepted: 09/07/2022] [Indexed: 11/02/2022]
Abstract
PURPOSE Functional MRI (fMRI) has well-established uses to inform risks and plan maximally safe approaches in neurosurgery. In the field of brain tumour surgery, however, fMRI is currently in a state of clinical equipoise due to debate around both its sensitivity and specificity. MATERIALS AND METHODS In this review, we summarise the role and our experience of fMRI in neurosurgery for gliomas and metastases. We discuss nuances in the conduct and interpretation of fMRI that, based on our practise, most directly impact fMRI's usefulness in the neurosurgical setting. RESULTS Illustrated examples in which fMRI in our hands directly influences the neurosurgical treatment of brain tumours include evaluating the probability and nature of functional risks, especially for language functions. These presurgical risk assessments, in turn, help to predict the resectability of tumours, select or deselect patients for awake surgery, indicate the need for neurophysiological monitoring and guide the optimal use of intra-operative stimulation mapping. A further emerging application of fMRI is in measuring functional adaptation of functional networks after (partial) surgery, of potential use in the timing of further surgery. CONCLUSIONS In appropriately selected patients with a clearly defined surgical question, fMRI offers a valuable complementary tool in the pre-surgical evaluation of brain tumours. However, there is a great need for standards in the administration and analysis of fMRI as much as in the techniques that it is commonly evaluated against. Surprisingly little data exists that evaluates the accuracy of fMRI not just against complementary methods, but in terms of its ultimate clinical aim of minimising post-surgical morbidity.
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Affiliation(s)
- Natalie L Voets
- Department of Neurosurgery, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- GenesisCare Ltd, Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Andreas J Bartsch
- Department of Neuroradiology, University of Heidelberg, Heidelberg, Germany
| | - Puneet Plaha
- Department of Neurosurgery, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- Nuffield Department of Neurosurgery, University of Oxford, Oxford, UK
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27
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Báez-Yáñez MG, Siero JCW, Petridou N. A mechanistic computational framework to investigate the hemodynamic fingerprint of the blood oxygenation level-dependent signal. NMR IN BIOMEDICINE 2023; 36:e5026. [PMID: 37643645 DOI: 10.1002/nbm.5026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 07/18/2023] [Accepted: 07/28/2023] [Indexed: 08/31/2023]
Abstract
Blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) is one of the most used imaging techniques to map brain activity or to obtain clinical information about human cortical vasculature, in both healthy and disease conditions. Nevertheless, BOLD fMRI is an indirect measurement of brain functioning triggered by neurovascular coupling. The origin of the BOLD signal is quite complex, and the signal formation thus depends, among other factors, on the topology of the cortical vasculature and the associated hemodynamic changes. To understand the hemodynamic evolution of the BOLD signal response in humans, it is beneficial to have a computational framework available that virtually resembles the human cortical vasculature, and simulates hemodynamic changes and corresponding MRI signal changes via interactions of intrinsic biophysical and magnetic properties of the tissues. To this end, we have developed a mechanistic computational framework that simulates the hemodynamic fingerprint of the BOLD signal based on a statistically defined, three-dimensional, vascular model that approaches the human cortical vascular architecture. The microvasculature is approximated through a Voronoi tessellation method and the macrovasculature is adapted from two-photon microscopy mice data. Using this computational framework, we simulated hemodynamic changes-cerebral blood flow, cerebral blood volume, and blood oxygen saturation-induced by virtual arterial dilation. Then we computed local magnetic field disturbances generated by the vascular topology and the corresponding blood oxygen saturation changes. This mechanistic computational framework also considers the intrinsic biophysical and magnetic properties of nearby tissue, such as water diffusion and relaxation properties, resulting in a dynamic BOLD signal response. The proposed mechanistic computational framework provides an integrated biophysical model that can offer better insights regarding the spatial and temporal properties of the BOLD signal changes.
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Affiliation(s)
- Mario Gilberto Báez-Yáñez
- Department of Radiology, Centre for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Jeroen C W Siero
- Department of Radiology, Centre for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
- Spinoza Centre for Neuroimaging Amsterdam, Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands
| | - Natalia Petridou
- Department of Radiology, Centre for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
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28
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Chen H, Mirg S, Gaddale P, Agrawal S, Li M, Nguyen V, Xu T, Li Q, Liu J, Tu W, Liu X, Drew PJ, Zhang N, Gluckman BJ, Kothapalli SR. Dissecting Multiparametric Cerebral Hemodynamics using Integrated Ultrafast Ultrasound and Multispectral Photoacoustic Imaging. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.07.566048. [PMID: 37986863 PMCID: PMC10659547 DOI: 10.1101/2023.11.07.566048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Understanding brain-wide hemodynamic responses to different stimuli at high spatiotemporal resolutions can help study neuro-disorders and brain functions. However, the existing brain imaging technologies have limited resolution, sensitivity, imaging depth and provide information about only one or two hemodynamic parameters. To address this, we propose a multimodal functional ultrasound and photoacoustic (fUSPA) imaging platform, which integrates ultrafast ultrasound and multispectral photoacoustic imaging methods in a compact head-mountable device, to quantitatively map cerebral blood volume (CBV), cerebral blood flow (CBF), oxygen saturation (SO2) dynamics as well as contrast agent enhanced brain imaging with high spatiotemporal resolutions. After systematic characterization, the fUSPA system was applied to quantitatively study the changes in brain hemodynamics and vascular reactivity at single vessel resolution in response to hypercapnia stimulation. Our results show an overall increase in brain-wide CBV, CBF, and SO2, but regional differences in singular cortical veins and arteries and a reproducible anti-correlation pattern between venous and cortical hemodynamics, demonstrating the capabilities of the fUSPA system for providing multiparametric cerebrovascular information at high-resolution and sensitivity, that can bring insights into the complex mechanisms of neurodiseases.
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Affiliation(s)
- Haoyang Chen
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
- Center for Neural Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Shubham Mirg
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
- Center for Neural Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Prameth Gaddale
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Sumit Agrawal
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Menghan Li
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Van Nguyen
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Tianbao Xu
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Qiong Li
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Jinyun Liu
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Wenyu Tu
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Xiao Liu
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
- Institute for Computational and Data Sciences, The Pennsylvania State University, University Park, PA 16802, USA
| | - Patrick J. Drew
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
- Center for Neural Engineering, The Pennsylvania State University, University Park, PA 16802, USA
- Department of Engineering Science and Mechanics, The Pennsylvania State University, University Park, PA 16802, USA
- Department of Biology, The Pennsylvania State University, University Park, PA 16802, USA
- Department of Neurosurgery, The Pennsylvania State University, University Park, PA 16802, USA
| | - Nanyin Zhang
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
- Center for Neural Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Bruce J. Gluckman
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
- Center for Neural Engineering, The Pennsylvania State University, University Park, PA 16802, USA
- Department of Engineering Science and Mechanics, The Pennsylvania State University, University Park, PA 16802, USA
- Department of Neurosurgery, The Pennsylvania State University, University Park, PA 16802, USA
| | - Sri-Rajasekhar Kothapalli
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
- Center for Neural Engineering, The Pennsylvania State University, University Park, PA 16802, USA
- Penn State Cancer Institute, The Pennsylvania State University, Hershey, PA 17033, USA
- Graduate Program in Acoustics, The Pennsylvania State University, University Park, PA 16802, USA
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29
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Chang WT, Lin W, Giovanello KS. Enabling brain-wide mapping of directed functional connectivity at 3T via layer-dependent fMRI with draining-vein suppression. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.24.563835. [PMID: 37961360 PMCID: PMC10634801 DOI: 10.1101/2023.10.24.563835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Layer-dependent functional magnetic resonance imaging (fMRI) offers a compelling avenue for investigating directed functional connectivity (FC). To construct a comprehensive map of brain-wide directed FC, several technical criteria must be met, including sub-mm spatial resolution, adequate temporal resolution, functional sensitivity, global brain coverage, and high spatial specificity. Although gradient echo (GE)-based echo planar imaging (EPI) is commonly used for rapid fMRI acquisition, it faces significant challenges due to the draining-vein effect, particularly when utilizing blood oxygen level-dependent (BOLD) contrast. In this study, we mitigated this effect by incorporating velocity-nulling (VN) gradients into a GE-BOLD fMRI sequence, opting for a 3T magnetic field strength over 7T. We also integrated several advanced techniques, such as simultaneous multi-slice (SMS) acceleration and NORDIC denoising, to enhance temporal resolution, spatial coverage, and signal sensitivity. Collectively, the VN fMRI method exhibited notable spatial specificity, as evidenced by the identification of double-peak activation patterns within the primary motor cortex (M1) during a finger-tapping task. Additionally, the technique demonstrated BOLD sensitivity in the lateral geniculate nucleus (LGN). Furthermore, our VN fMRI technique displayed superior robustness when compared to conventional fMRI approaches across participants. Our findings of directed FC elucidate several layer-specific functional relationships between different brain regions and align closely with existing literature. Given the widespread availability of 3T scanners, this technical advancement has the potential for significant impact across multiple domains of neuroscience research.
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Affiliation(s)
- Wei-Tang Chang
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, NC, USA
- Department of Radiology, University of North Carolina at Chapel Hill, NC, USA
- Department of Biomedical Engineering, University of North Carolina at Chapel Hill, NC, USA
| | - Weili Lin
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, NC, USA
- Department of Radiology, University of North Carolina at Chapel Hill, NC, USA
| | - Kelly S. Giovanello
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, NC, USA
- Department of Psychology & Neuroscience, University of North Carolina at Chapel Hill, NC, USA
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Theriault JE, Shaffer C, Dienel GA, Sander CY, Hooker JM, Dickerson BC, Barrett LF, Quigley KS. A functional account of stimulation-based aerobic glycolysis and its role in interpreting BOLD signal intensity increases in neuroimaging experiments. Neurosci Biobehav Rev 2023; 153:105373. [PMID: 37634556 PMCID: PMC10591873 DOI: 10.1016/j.neubiorev.2023.105373] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 07/28/2023] [Accepted: 08/23/2023] [Indexed: 08/29/2023]
Abstract
In aerobic glycolysis, oxygen is abundant, and yet cells metabolize glucose without using it, decreasing their ATP per glucose yield by 15-fold. During task-based stimulation, aerobic glycolysis occurs in localized brain regions, presenting a puzzle: why produce ATP inefficiently when, all else being equal, evolution should favor the efficient use of metabolic resources? The answer is that all else is not equal. We propose that a tradeoff exists between efficient ATP production and the efficiency with which ATP is spent to transmit information. Aerobic glycolysis, despite yielding little ATP per glucose, may support neuronal signaling in thin (< 0.5 µm), information-efficient axons. We call this the efficiency tradeoff hypothesis. This tradeoff has potential implications for interpretations of task-related BOLD "activation" observed in fMRI. We hypothesize that BOLD "activation" may index local increases in aerobic glycolysis, which support signaling in thin axons carrying "bottom-up" information, or "prediction error"-i.e., the BIAPEM (BOLD increases approximate prediction error metabolism) hypothesis. Finally, we explore implications of our hypotheses for human brain evolution, social behavior, and mental disorders.
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Affiliation(s)
- Jordan E Theriault
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA.
| | - Clare Shaffer
- Northeastern University, Department of Psychology, Boston, MA, USA
| | - Gerald A Dienel
- Department of Neurology, University of Arkansas for Medical Sciences, Little Rock, AR, USA; Department of Cell Biology and Physiology, University of New Mexico, Albuquerque, NM, USA
| | - Christin Y Sander
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Jacob M Hooker
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Bradford C Dickerson
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA; Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Lisa Feldman Barrett
- Northeastern University, Department of Psychology, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Karen S Quigley
- Northeastern University, Department of Psychology, Boston, MA, USA; VA Bedford Healthcare System, Bedford, MA, USA
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31
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Miri Ashtiani SN, Daliri MR. Identification of cognitive load-dependent activation patterns using working memory task-based fMRI at various levels of difficulty. Sci Rep 2023; 13:16476. [PMID: 37777667 PMCID: PMC10543376 DOI: 10.1038/s41598-023-43837-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 09/28/2023] [Indexed: 10/02/2023] Open
Abstract
Working memory, which is regarded as the foundation of cognitive processes, is a system that stores, processes, and manipulates information in short intervals of time that are actually needed for daily functioning. This study aimed to assess the brain activity of healthy controls (HC) while performing the N-back task, which is one of the most popularly used tests for evaluating working memory along with functional magnetic resonance imaging (fMRI). In this regard, we collected fMRI data from right-handed individuals in a 3.0 T scanner during the Persian version of the visual variant N-back task performance with three levels of complexity varied throughout the experiment (1, 2, and 3-back conditions) to increase the cognitive demands. The statistical parametric mapping (SPM12) software was used to analyze fMRI data for the identification of cognitive load-dependent activation patterns based on contrast images obtained from different levels of task difficulty. Our findings showed that as cognitive complexity increased, the number of significant activation clusters and cluster extent increased in several areas distributed in the cerebellum, frontoparietal lobes, insula, SMA, and lenticular nucleus, the majority of which are recognized for their role in working memory. Furthermore, deactivation patterns during 1-, 2-, and 3-back vs. 0-back contrasts revealed significant clusters in brain regions that are mostly described as being part of the default mode network (DMN). Based on previous research, our results supported the recognized involvement of the mentioned cortical and subcortical areas in various types or levels of N-back tasks. This study found that altering activation patterns by increasing task difficulty could aid in evaluating the various stages of cognitive dysfunction in many brain diseases such as multiple sclerosis (MS) and Alzheimer's disease by comparing controls in future studies to apply early appropriate treatment strategies.
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Affiliation(s)
- Seyedeh Naghmeh Miri Ashtiani
- Biomedical Engineering Department, School of Electrical Engineering, Iran University of Science and Technology (IUST), Tehran, Iran
| | - Mohammad Reza Daliri
- Biomedical Engineering Department, School of Electrical Engineering, Iran University of Science and Technology (IUST), Tehran, Iran.
- School of Cognitive Sciences (SCS), Institute for Research in Fundamental Sciences (IPM), Tehran, Iran.
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32
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Amemiya S, Takao H, Hanaoka S, Abe O. Resting-state networks representation of the global phenomena. Front Neurosci 2023; 17:1220848. [PMID: 37662100 PMCID: PMC10469869 DOI: 10.3389/fnins.2023.1220848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 08/07/2023] [Indexed: 09/05/2023] Open
Abstract
Resting-state functional magnetic resonance imaging (rsfMRI) has been widely applied to investigate spontaneous neural activity, often based on its macroscopic organization that is termed resting-state networks (RSNs). Although the neurophysiological mechanisms underlying the RSN organization remain largely unknown, accumulating evidence points to a substantial contribution from the global signals to their structured synchronization. This study further explored the phenomenon by taking advantage of the inter- and intra-subject variations of the time delay and correlation coefficient of the signal timeseries in each region using the global mean signal as the reference signal. Consistent with the hypothesis based on the empirical and theoretical findings, the time lag and correlation, which have consistently been proven to represent local hemodynamic status, were shown to organize networks equivalent to RSNs. The results not only provide further evidence that the local hemodynamic status could be the direct source of the RSNs' spatial patterns but also explain how the regional variations in the hemodynamics, combined with the changes in the global events' power spectrum, lead to the observations. While the findings pose challenges to interpretations of rsfMRI studies, they further support the view that rsfMRI can offer detailed information related to global neurophysiological phenomena as well as local hemodynamics that would have great potential as biomarkers.
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Affiliation(s)
- Shiori Amemiya
- Department of Radiology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
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Clark A, Flouri D, Mufti N, James J, Clements E, Aughwane R, Aertsen M, David A, Melbourne A. Developments in functional imaging of the placenta. Br J Radiol 2023; 96:20211010. [PMID: 35234516 PMCID: PMC10321248 DOI: 10.1259/bjr.20211010] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 01/26/2022] [Accepted: 02/22/2022] [Indexed: 12/21/2022] Open
Abstract
The placenta is both the literal and metaphorical black box of pregnancy. Measurement of the function of the placenta has the potential to enhance our understanding of this enigmatic organ and serve to support obstetric decision making. Advanced imaging techniques are key to support these measurements. This review summarises emerging imaging technology being used to measure the function of the placenta and new developments in the computational analysis of these data. We address three important examples where functional imaging is supporting our understanding of these conditions: fetal growth restriction, placenta accreta, and twin-twin transfusion syndrome.
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Affiliation(s)
- Alys Clark
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | | | | | - Joanna James
- Department of Obstetrics and Gynaecology, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Eleanor Clements
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, UK
| | - Rosalind Aughwane
- Elizabeth Garrett Anderson Institute for Women’s Health, University College London, London, UK
| | - Michael Aertsen
- Department of Radiology, University Hospitals KU Leuven, Leuven, Belgium
| | - Anna David
- Elizabeth Garrett Anderson Institute for Women’s Health, University College London, London, UK
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34
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Yeung MK. The prefrontal cortex is differentially involved in implicit and explicit facial emotion processing: An fNIRS study. Biol Psychol 2023; 181:108619. [PMID: 37336356 DOI: 10.1016/j.biopsycho.2023.108619] [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: 03/19/2023] [Revised: 06/14/2023] [Accepted: 06/15/2023] [Indexed: 06/21/2023]
Abstract
Despite extensive research, the differential roles of the prefrontal cortex (PFC) in implicit and explicit facial emotion processing remain elusive. Functional near-infrared spectroscopy (fNIRS) is a neuroimaging technique that can measure changes in both oxyhemoglobin (HbO) and deoxyhemoglobin (HbR) concentrations. Currently, how HbO and HbR change during facial emotion processing remains unclear. Here, fNIRS was used to examine and compare PFC activation during implicit and explicit facial emotion processing. Forty young adults performed a facial-matching task that required either emotion discrimination (explicit task) or age discrimination (implicit task), and the activation of their PFCs was measured by fNIRS. Participants attempted the task on two occasions to determine whether their activation patterns were maintained over time. The PFC displayed increases in HbO and/or decreases in HbR during the implicit and explicit facial emotion tasks. Importantly, there were significantly greater changes in PFC HbO during the explicit task, whereas no significant difference in HbR changes between conditions was found. Between sessions, HbO changes were reduced across tasks, but the difference in HbO changes between the implicit and explicit tasks remained unchanged. The test-retest reliability of the behavioral measures was excellent, whereas that of fNIRS measures was mostly poor to fair. Thus, the PFC plays a specific role in recognizing facial expressions, and its differential involvement in implicit and explicit facial emotion processing can be consistently captured at the group level by changes in HbO. This study demonstrates the potential of fNIRS for elucidating the neural mechanisms underlying facial emotion recognition.
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Affiliation(s)
- Michael K Yeung
- Department of Psychology, The Education University of Hong Kong, Hong Kong, China; University Research Facility in Behavioral and Systems Neuroscience, The Hong Kong Polytechnic University, Hong Kong, China.
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Wu T, Liu C, Thamizhchelvan AM, Fleischer C, Peng X, Liu G, Mao H. Label-Free Chemically and Molecularly Selective Magnetic Resonance Imaging. CHEMICAL & BIOMEDICAL IMAGING 2023; 1:121-139. [PMID: 37235188 PMCID: PMC10207347 DOI: 10.1021/cbmi.3c00019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/29/2023] [Revised: 03/20/2023] [Accepted: 04/01/2023] [Indexed: 05/28/2023]
Abstract
Biomedical imaging, especially molecular imaging, has been a driving force in scientific discovery, technological innovation, and precision medicine in the past two decades. While substantial advances and discoveries in chemical biology have been made to develop molecular imaging probes and tracers, translating these exogenous agents to clinical application in precision medicine is a major challenge. Among the clinically accepted imaging modalities, magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) exemplify the most effective and robust biomedical imaging tools. Both MRI and MRS enable a broad range of chemical, biological and clinical applications from determining molecular structures in biochemical analysis to imaging diagnosis and characterization of many diseases and image-guided interventions. Using chemical, biological, and nuclear magnetic resonance properties of specific endogenous metabolites and native MRI contrast-enhancing biomolecules, label-free molecular and cellular imaging with MRI can be achieved in biomedical research and clinical management of patients with various diseases. This review article outlines the chemical and biological bases of several label-free chemically and molecularly selective MRI and MRS methods that have been applied in imaging biomarker discovery, preclinical investigation, and image-guided clinical management. Examples are provided to demonstrate strategies for using endogenous probes to report the molecular, metabolic, physiological, and functional events and processes in living systems, including patients. Future perspectives on label-free molecular MRI and its challenges as well as potential solutions, including the use of rational design and engineered approaches to develop chemical and biological imaging probes to facilitate or combine with label-free molecular MRI, are discussed.
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Affiliation(s)
- Tianhe Wu
- Department
of Radiology and Imaging Sciences, Emory
University School of Medicine, Atlanta, Georgia 30322, United States
| | - Claire Liu
- F.M.
Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland 21205, United States
| | - Anbu Mozhi Thamizhchelvan
- Department
of Radiology and Imaging Sciences, Emory
University School of Medicine, Atlanta, Georgia 30322, United States
| | - Candace Fleischer
- Department
of Radiology and Imaging Sciences, Emory
University School of Medicine, Atlanta, Georgia 30322, United States
| | - Xingui Peng
- Jiangsu
Key Laboratory of Molecular and Functional Imaging, Department of
Radiology, Zhongda Hospital, Medical School
of Southeast University, Nanjing, Jiangsu 210009, China
| | - Guanshu Liu
- F.M.
Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland 21205, United States
- Russell
H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, United States
| | - Hui Mao
- Department
of Radiology and Imaging Sciences, Emory
University School of Medicine, Atlanta, Georgia 30322, United States
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36
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Williams RJ, Specht JL, Mazerolle EL, Lebel RM, MacDonald ME, Pike GB. Correspondence between BOLD fMRI task response and cerebrovascular reactivity across the cerebral cortex. Front Physiol 2023; 14:1167148. [PMID: 37228813 PMCID: PMC10203231 DOI: 10.3389/fphys.2023.1167148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Accepted: 04/24/2023] [Indexed: 05/27/2023] Open
Abstract
BOLD sensitivity to baseline perfusion and blood volume is a well-acknowledged fMRI confound. Vascular correction techniques based on cerebrovascular reactivity (CVR) might reduce variance due to baseline cerebral blood volume, however this is predicated on an invariant linear relationship between CVR and BOLD signal magnitude. Cognitive paradigms have relatively low signal, high variance and involve spatially heterogenous cortical regions; it is therefore unclear whether the BOLD response magnitude to complex paradigms can be predicted by CVR. The feasibility of predicting BOLD signal magnitude from CVR was explored in the present work across two experiments using different CVR approaches. The first utilized a large database containing breath-hold BOLD responses and 3 different cognitive tasks. The second experiment, in an independent sample, calculated CVR using the delivery of a fixed concentration of carbon dioxide and a different cognitive task. An atlas-based regression approach was implemented for both experiments to evaluate the shared variance between task-invoked BOLD responses and CVR across the cerebral cortex. Both experiments found significant relationships between CVR and task-based BOLD magnitude, with activation in the right cuneus (R 2 = 0.64) and paracentral gyrus (R 2 = 0.71), and the left pars opercularis (R 2 = 0.67), superior frontal gyrus (R 2 = 0.62) and inferior parietal cortex (R 2 = 0.63) strongly predicted by CVR. The parietal regions bilaterally were highly consistent, with linear regressions significant in these regions for all four tasks. Group analyses showed that CVR correction increased BOLD sensitivity. Overall, this work suggests that BOLD signal response magnitudes to cognitive tasks are predicted by CVR across different regions of the cerebral cortex, providing support for the use of correction based on baseline vascular physiology.
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Affiliation(s)
- Rebecca J. Williams
- Faculty of Health, School of Human Services, Charles Darwin University, Darwin, NT, Australia
| | - Jacinta L. Specht
- Department of Clinical Neuroscience, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Erin L. Mazerolle
- Departments of Psychology and Computer Science, St. Francis Xavier University, Antigonish, NS, Canada
| | - R. Marc Lebel
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- GE HealthCare, Calgary, AB, Canada
| | - M. Ethan MacDonald
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Department of Biomedical Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB, Canada
- Department of Electrical and Software Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB, Canada
| | - G. Bruce Pike
- Department of Clinical Neuroscience, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
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Berenbaum JG, Nadkarni PA, Marvel CL. An fMRI analysis of verbal and non-verbal working memory in people with a past history of opioid dependence. Front Neurosci 2023; 17:1053500. [PMID: 37090800 PMCID: PMC10113507 DOI: 10.3389/fnins.2023.1053500] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2022] [Accepted: 03/20/2023] [Indexed: 04/07/2023] Open
Abstract
Introduction Working memory describes the ability to maintain and manipulate information held in mind, and it is a fundamental aspect of executive function. Within drug addiction, impairments of executive control over behavior are thought to lead to poor decision making and risky behaviors. Previous research has demonstrated working memory (WM) and executive function difficulties in opioid-dependent individuals, but the neural underpinnings of such impairments in this population are not well understood. Methods This study used functional magnetic resonance imaging to examine the neural mechanisms involved in WM in 13 opioid-dependent, methadone-maintained participants (OP) and 13 matched, healthy controls (HC). A Sternberg item-recognition task was administered with three conditions: (1) a "verbal" condition in which participants determined whether any six visually presented target letters matched a probe item that was presented 4-6 s later, (2) a "non-verbal" condition in which participants were presented with a Chinese character and, following a 4-6 s delay, determined whether the character matched the probe item, and (3) a "control" condition in which participants were presented with three horizontal lines and following the same delay, determined whether the lines matched a probe item (always the same three lines). Functional magnetic resonance imaging (fMRI) contrasts focused on the delay (or "maintenance") phase for verbal and non-verbal conditions relative to the control condition. Results Accuracy on the WM task did not differ between groups, but the OP group was significantly slower to respond. The fMRI imaging results indicated differences in brain activity between the OP and HC groups. fMRI-guided regions of interest correlated with age of first alcohol and THC use, suggesting that early substance use, in addition to years of opioid-abuse, may have played a role in the OP group's WM performance. Discussion A deeper understanding of these neural differences between opioid-dependent individuals and their healthy control counterparts helps shed light on fundamental ways in which substance use impacts the brain and cognition, potentially opening up novel avenues for therapeutic targets to treat substance use disorder.
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Affiliation(s)
| | | | - Cherie L. Marvel
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
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Sala A, Lizarraga A, Caminiti SP, Calhoun VD, Eickhoff SB, Habeck C, Jamadar SD, Perani D, Pereira JB, Veronese M, Yakushev I. Brain connectomics: time for a molecular imaging perspective? Trends Cogn Sci 2023; 27:353-366. [PMID: 36621368 PMCID: PMC10432882 DOI: 10.1016/j.tics.2022.11.015] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 11/19/2022] [Accepted: 11/30/2022] [Indexed: 01/09/2023]
Abstract
In the past two decades brain connectomics has evolved into a major concept in neuroscience. However, the current perspective on brain connectivity and how it underpins brain function relies mainly on the hemodynamic signal of functional magnetic resonance imaging (MRI). Molecular imaging provides unique information inaccessible to MRI-based and electrophysiological techniques. Thus, positron emission tomography (PET) has been successfully applied to measure neural activity, neurotransmission, and proteinopathies in normal and pathological cognition. Here, we position molecular imaging within the brain connectivity framework from the perspective of timeliness, validity, reproducibility, and resolution. We encourage the neuroscientific community to take an integrative approach whereby MRI-based, electrophysiological techniques, and molecular imaging contribute to our understanding of the brain connectome.
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Affiliation(s)
- Arianna Sala
- Department of Nuclear Medicine, Klinikum Rechts der Isar, Technical University of Munich, School of Medicine, 81675 Munich, Germany; Coma Science Group, GIGA-Consciousness, University of Liege, 4000 Liege, Belgium; Centre du Cerveau(2), University Hospital of Liege, 4000 Liege, Belgium
| | - Aldana Lizarraga
- Department of Nuclear Medicine, Klinikum Rechts der Isar, Technical University of Munich, School of Medicine, 81675 Munich, Germany
| | - Silvia Paola Caminiti
- Vita-Salute San Raffaele University, 20132 Milan, Italy; In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Raffaele Scientific Institute, 20132 Milan, Italy
| | - Vince D Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA 30303, USA
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine, Brain, and Behaviour (INM-7), Research Centre Jülich, 52428 Jülich, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine-University Düsseldorf, 40225 Düsseldorf, Germany
| | - Christian Habeck
- Cognitive Neuroscience Division, Department of Neurology, Columbia University, New York, NY 10032, USA
| | - Sharna D Jamadar
- Turner Institute for Brain and Mental Health, Monash University, 3800 Melbourne, Australia; Monash Biomedical Imaging, Monash University, 3800 Melbourne, Australia
| | - Daniela Perani
- Vita-Salute San Raffaele University, 20132 Milan, Italy; In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Raffaele Scientific Institute, 20132 Milan, Italy; Nuclear Medicine Unit, San Raffaele Hospital, 20132 Milan, Italy
| | - Joana B Pereira
- Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 14152 Stockholm, Sweden; Memory Research Unit, Department of Clinical Sciences, Malmö Lund University, 20502 Lund, Sweden
| | - Mattia Veronese
- Department of Neuroimaging, King's College London, London SE5 8AF, UK; Department of Information Engineering, University of Padua, 35131 Padua, Italy
| | - Igor Yakushev
- Department of Nuclear Medicine, Klinikum Rechts der Isar, Technical University of Munich, School of Medicine, 81675 Munich, Germany.
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Zaretskaya N, Fink E, Arsenovic A, Ischebeck A. Fast and functionally specific cortical thickness changes induced by visual stimulation. Cereb Cortex 2023; 33:2823-2837. [PMID: 35780393 DOI: 10.1093/cercor/bhac244] [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: 02/25/2022] [Revised: 05/23/2022] [Accepted: 05/24/2022] [Indexed: 11/13/2022] Open
Abstract
Structural characteristics of the human brain serve as important markers of brain development, aging, disease progression, and neural plasticity. They are considered stable properties, changing slowly over time. Multiple recent studies reported that structural brain changes measured with magnetic resonance imaging (MRI) may occur much faster than previously thought, within hours or even minutes. The mechanisms behind such fast changes remain unclear, with hemodynamics as one possible explanation. Here we investigated the functional specificity of cortical thickness changes induced by a flickering checkerboard and compared them to blood oxygenation level-dependent (BOLD) functional MRI activity. We found that checkerboard stimulation led to a significant thickness increase, which was driven by an expansion at the gray-white matter boundary, functionally specific to V1, confined to the retinotopic representation of the checkerboard stimulus, and amounted to 1.3% or 0.022 mm. Although functional specificity and the effect size of these changes were comparable to those of the BOLD signal in V1, thickness effects were substantially weaker in V3. Furthermore, a comparison of predicted and measured thickness changes for different stimulus timings suggested a slow increase of thickness over time, speaking against a hemodynamic explanation. Altogether, our findings suggest that visual stimulation can induce structural gray matter enlargement measurable with MRI.
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Affiliation(s)
- Natalia Zaretskaya
- Department of Cognitive Psychology and Neuroscience, Institute of Psychology, University of Graz, Universitaetsplatz 2, 8010 Graz, Austria
- BioTechMed-Graz, Mozartgasse 12, 8010 Graz, Austria
| | - Erik Fink
- Department of Cognitive Psychology and Neuroscience, Institute of Psychology, University of Graz, Universitaetsplatz 2, 8010 Graz, Austria
| | - Ana Arsenovic
- Department of Cognitive Psychology and Neuroscience, Institute of Psychology, University of Graz, Universitaetsplatz 2, 8010 Graz, Austria
- BioTechMed-Graz, Mozartgasse 12, 8010 Graz, Austria
| | - Anja Ischebeck
- Department of Cognitive Psychology and Neuroscience, Institute of Psychology, University of Graz, Universitaetsplatz 2, 8010 Graz, Austria
- BioTechMed-Graz, Mozartgasse 12, 8010 Graz, Austria
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Schellekens W, Bhogal AA, Roefs ECA, Báez-Yáñez MG, Siero JCW, Petridou N. The many layers of BOLD. The effect of hypercapnic and hyperoxic stimuli on macro- and micro-vascular compartments quantified by CVR, M, and CBV across cortical depth. J Cereb Blood Flow Metab 2023; 43:419-432. [PMID: 36262088 PMCID: PMC9941862 DOI: 10.1177/0271678x221133972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 09/01/2022] [Accepted: 09/05/2022] [Indexed: 11/16/2022]
Abstract
Ultra-high field functional magnetic resonance imaging (fMRI) offers the spatial resolution to measure neuronal activity at the scale of cortical layers. However, cortical depth dependent vascularization differences, such as a higher prevalence of macro-vascular compartments near the pial surface, have a confounding effect on depth-resolved blood-oxygen-level dependent (BOLD) fMRI signals. In the current study, we use hypercapnic and hyperoxic breathing conditions to quantify the influence of all venous vascular and micro-vascular compartments on laminar BOLD fMRI, as measured with gradient-echo (GE) and spin-echo (SE) scan sequences, respectively. We find that all venous vascular and micro-vascular compartments are capable of comparable theoretical maximum signal intensities, as represented by the M-value parameter. However, the capacity for vessel dilation, as reflected by the cerebrovascular reactivity (CVR), is approximately two and a half times larger for all venous vascular compartments combined compared to the micro-vasculature at superficial layers. Finally, there is roughly a 35% difference in estimates of CBV changes between all venous vascular and micro-vascular compartments, although this relative difference was approximately uniform across cortical depth. Thus, our results suggest that fMRI BOLD signal differences across cortical depth are likely caused by differences in dilation properties between macro- and micro-vascular compartments.
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Affiliation(s)
- Wouter Schellekens
- Radiology Department, Center for Image Sciences, UMC Utrecht,
Netherlands
| | - Alex A Bhogal
- Radiology Department, Center for Image Sciences, UMC Utrecht,
Netherlands
| | - Emiel CA Roefs
- Radiology Department, Center for Image Sciences, UMC Utrecht,
Netherlands
| | - Mario G Báez-Yáñez
- Radiology Department, Center for Image Sciences, UMC Utrecht,
Netherlands
| | - Jeroen CW Siero
- Radiology Department, Center for Image Sciences, UMC Utrecht,
Netherlands
- Spinoza Centre for Neuroimaging, Amsterdam, The
Netherlands
| | - Natalia Petridou
- Radiology Department, Center for Image Sciences, UMC Utrecht,
Netherlands
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Baadsgaard K, Hansen DN, Peters DA, Frøkjær JB, Sinding M, Sørensen A. T2* weighted fetal MRI and the correlation with placental dysfunction. Placenta 2023; 131:90-97. [PMID: 36565490 DOI: 10.1016/j.placenta.2022.12.002] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Revised: 11/29/2022] [Accepted: 12/12/2022] [Indexed: 12/23/2022]
Abstract
INTRODUCTION Transverse relaxation time (T2*) is related to tissue oxygenation and morphology. We aimed to describe T2* weighted MRI in selected fetal organs in normal pregnancies, and to investigate the correlation between fetal organ T2* and placental T2*, birthweight (BW) deviation, and redistribution of fetal blood flow. METHODS T2*-weighted MRI was performed in 126 singleton pregnancies between 23+6- and 41+3-weeks' gestation. The T2* value was obtained from the placenta and fetal organs (brain, lungs, heart, liver, kidneys, and spleen). In normal BW pregnancies (BW > 10th centile), the correlation between the T2* value and gestational age (GA) at MRI was estimated by linear regression. The correlation between fetal organ Z-score and BW group was demonstrated by boxplots and investigated by analysis of variance (ANOVA) for each organ. RESULTS In normal BW pregnancies fetal organ T2* was negatively correlated with GA. We found a significant correlation between BW group and fetal organ T2* z-score in the fetal heart, kidney, lung and spleen. A positive linear correlation was demonstrated between fetal organ T2* and outcomes related to placental function such as BW deviation and placenta T2* in all investigated fetal organs except for the fetal liver. In the fetal heart, kidneys, and spleen the T2* value showed a significant correlation with fetal redistribution of blood flow (Middle cerebral artery Pulsatility Index) before delivery. DISCUSSION Fetal T2* is correlated with BW, placental function, and redistribution of fetal blood flow, suggesting that fetal organ T2* reflects fetal oxygenation and morphological changes related to placental dysfunction.
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Affiliation(s)
- Kirstine Baadsgaard
- Department of Clinical Medicine Aalborg University, Søndre Skovvej 15, 9000, Aalborg, Denmark; Department of Obstetrics and Gynecology, Aalborg University Hospital, Reberbansgade 15, 9000, Aalborg, Denmark.
| | - Ditte N Hansen
- Department of Clinical Medicine Aalborg University, Søndre Skovvej 15, 9000, Aalborg, Denmark; Department of Obstetrics and Gynecology, Aalborg University Hospital, Reberbansgade 15, 9000, Aalborg, Denmark
| | - David A Peters
- Department of Clinical Engineering, Central Denmark Region, Universitetsbyen 25, 8000, Aarhus C, Denmark
| | - Jens B Frøkjær
- Department of Clinical Medicine Aalborg University, Søndre Skovvej 15, 9000, Aalborg, Denmark; Department of Radiology, Aalborg University Hospital, Reberbansgade 15, 9000, Aalborg, Denmark
| | - Marianne Sinding
- Department of Clinical Medicine Aalborg University, Søndre Skovvej 15, 9000, Aalborg, Denmark; Department of Obstetrics and Gynecology, Aalborg University Hospital, Reberbansgade 15, 9000, Aalborg, Denmark
| | - Anne Sørensen
- Department of Clinical Medicine Aalborg University, Søndre Skovvej 15, 9000, Aalborg, Denmark; Department of Obstetrics and Gynecology, Aalborg University Hospital, Reberbansgade 15, 9000, Aalborg, Denmark
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de Oliveira ÍAF, Siero JCW, Dumoulin SO, van der Zwaag W. Improved Selectivity in 7 T Digit Mapping Using VASO-CBV. Brain Topogr 2023; 36:23-31. [PMID: 36517699 PMCID: PMC9834127 DOI: 10.1007/s10548-022-00932-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 11/28/2022] [Indexed: 12/15/2022]
Abstract
Functional magnetic resonance imaging (fMRI) at Ultra-high field (UHF, ≥ 7 T) benefits from significant gains in the BOLD contrast-to-noise ratio (CNR) and temporal signal-to-noise ratio (tSNR) compared to conventional field strengths (3 T). Although these improvements enabled researchers to study the human brain to unprecedented spatial resolution, the blood pooling effect reduces the spatial specificity of the widely-used gradient-echo BOLD acquisitions. In this context, vascular space occupancy (VASO-CBV) imaging may be advantageous since it is proposed to have a higher spatial specificity than BOLD. We hypothesized that the assumed higher specificity of VASO-CBV imaging would translate to reduced overlap in fine-scale digit representation maps compared to BOLD-based digit maps. We used sub-millimeter resolution VASO fMRI at 7 T to map VASO-CBV and BOLD responses simultaneously in the motor and somatosensory cortices during individual finger movement tasks. We assessed the cortical overlap in different ways, first by calculating similarity coefficient metrics (DICE and Jaccard) and second by calculating selectivity measures. In addition, we demonstrate a consistent topographical organization of the targeted digit representations (thumb-index-little finger) in the motor areas. We show that the VASO-CBV responses yielded less overlap between the digit clusters than BOLD, and other selectivity measures were higher for VASO-CBV too. In summary, these results were consistent across metrics and participants, confirming the higher spatial specificity of VASO-CBV compared to BOLD.
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Affiliation(s)
- Ícaro A. F. de Oliveira
- grid.458380.20000 0004 0368 8664Spinoza Centre for Neuroimaging, Meibergdreef 75, 1105 BK Amsterdam, The Netherlands ,grid.12380.380000 0004 1754 9227Experimental and Applied Psychology, VU University, Amsterdam, The Netherlands ,grid.419918.c0000 0001 2171 8263Computational Cognitive Neuroscience and Neuroimaging, Netherlands Institute for Neuroscience, Amsterdam, The Netherlands
| | - Jeroen C. W. Siero
- grid.458380.20000 0004 0368 8664Spinoza Centre for Neuroimaging, Meibergdreef 75, 1105 BK Amsterdam, The Netherlands ,grid.7692.a0000000090126352Radiology, Utrecht Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Serge O. Dumoulin
- grid.458380.20000 0004 0368 8664Spinoza Centre for Neuroimaging, Meibergdreef 75, 1105 BK Amsterdam, The Netherlands ,grid.12380.380000 0004 1754 9227Experimental and Applied Psychology, VU University, Amsterdam, The Netherlands ,grid.419918.c0000 0001 2171 8263Computational Cognitive Neuroscience and Neuroimaging, Netherlands Institute for Neuroscience, Amsterdam, The Netherlands ,grid.5477.10000000120346234Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, The Netherlands
| | - Wietske van der Zwaag
- grid.458380.20000 0004 0368 8664Spinoza Centre for Neuroimaging, Meibergdreef 75, 1105 BK Amsterdam, The Netherlands ,grid.419918.c0000 0001 2171 8263Computational Cognitive Neuroscience and Neuroimaging, Netherlands Institute for Neuroscience, Amsterdam, The Netherlands
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Uhlig M, Reinelt JD, Lauckner ME, Kumral D, Schaare HL, Mildner T, Babayan A, Möller HE, Engert V, Villringer A, Gaebler M. Rapid volumetric brain changes after acute psychosocial stress. Neuroimage 2023; 265:119760. [PMID: 36427754 DOI: 10.1016/j.neuroimage.2022.119760] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 11/14/2022] [Accepted: 11/21/2022] [Indexed: 11/25/2022] Open
Abstract
Stress is an important trigger for brain plasticity: Acute stress can rapidly affect brain activity and functional connectivity, and chronic or pathological stress has been associated with structural brain changes. Measures of structural magnetic resonance imaging (MRI) can be modified by short-term motor learning or visual stimulation, suggesting that they also capture rapid brain changes. Here, we investigated volumetric brain changes (together with changes in T1 relaxation rate and cerebral blood flow) after acute stress in humans as well as their relation to psychophysiological stress measures. Sixty-seven healthy men (25.8±2.7 years) completed a standardized psychosocial laboratory stressor (Trier Social Stress Test) or a control version while blood, saliva, heart rate, and psychometrics were sampled. Structural MRI (T1 mapping / MP2RAGE sequence) at 3T was acquired 45 min before and 90 min after intervention onset. Grey matter volume (GMV) changes were analysed using voxel-based morphometry. Associations with endocrine, autonomic, and subjective stress measures were tested with linear models. We found significant group-by-time interactions in several brain clusters including anterior/mid-cingulate cortices and bilateral insula: GMV was increased in the stress group relative to the control group, in which several clusters showed a GMV decrease. We found a significant group-by-time interaction for cerebral blood flow, and a main effect of time for T1 values (longitudinal relaxation time). In addition, GMV changes were significantly associated with state anxiety and heart rate variability changes. Such rapid GMV changes assessed with VBM may be induced by local tissue adaptations to changes in energy demand following neural activity. Our findings suggest that endogenous brain changes are counteracted by acute psychosocial stress, which emphasizes the importance of considering homeodynamic processes and generally highlights the influence of stress on the brain.
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Affiliation(s)
- Marie Uhlig
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; International Max Planck Research School NeuroCom, Leipzig, Germany.
| | - Janis D Reinelt
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Mark E Lauckner
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Independent Research Group "Adaptive Memory", Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Medical Faculty of Leipzig University, Leipzig, Germany
| | - Deniz Kumral
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Institute of Psychology, Neuropsychology, University of Freiburg, Freiburg im Breisgau, Germany
| | - H Lina Schaare
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Otto Hahn Group "Cognitive Neurogenetics", Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Germany
| | - Toralf Mildner
- NMR Methods & Development Group, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Anahit Babayan
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; MindBrainBody Institute at the Berlin School of Mind and Brain, Faculty of Philosophy, Humboldt-Universität zu Berlin, Berlin, German
| | - Harald E Möller
- NMR Methods & Development Group, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Veronika Engert
- Institute of Psychosocial Medicine, Psychotherapy and Psychooncology, Jena University Hospital, Friedrich-Schiller University, Jena, Germany; Independent Research Group "Social Stress and Family Health", Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Arno Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; MindBrainBody Institute at the Berlin School of Mind and Brain, Faculty of Philosophy, Humboldt-Universität zu Berlin, Berlin, German
| | - Michael Gaebler
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; MindBrainBody Institute at the Berlin School of Mind and Brain, Faculty of Philosophy, Humboldt-Universität zu Berlin, Berlin, German
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44
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Lee D, Le TT, Im GH, Kim SG. Whole-brain perfusion mapping in mice by dynamic BOLD MRI with transient hypoxia. J Cereb Blood Flow Metab 2022; 42:2270-2286. [PMID: 35903000 PMCID: PMC9670005 DOI: 10.1177/0271678x221117008] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Non-invasive mapping of cerebral perfusion is critical for understanding neurovascular and neurodegenerative diseases. However, perfusion MRI methods cannot be easily implemented for whole-brain studies in mice because of their small size. To overcome this issue, a transient hypoxia stimulus was applied to induce a bolus of deoxyhemoglobins as an endogenous paramagnetic contrast in blood oxygenation level-dependent (BOLD) MRI. Based on stimulus-duration-dependent studies, 5 s anoxic stimulus was chosen, which induced a decrease in arterial oxygenation to 59%. Dynamic susceptibility changes were acquired with whole-brain BOLD MRI using both all-vessel-sensitive gradient-echo and microvascular-sensitive spin-echo readouts. Cerebral blood flow (CBF) and cerebral blood volume (CBV) were quantified by modeling BOLD dynamics using a partial-volume-corrected arterial input function. In the mouse under ketamine/xylazine anesthesia, total CBF and CBV were 112.0 ± 15.0 ml/100 g/min and 3.39 ± 0.59 ml/100 g (n = 15 mice), respectively, whereas microvascular CBF and CBV were 85.8 ± 6.9 ml/100 g/min and 2.23 ± 0.27 ml/100 g (n = 7 mice), respectively. Regional total vs. microvascular perfusion metrics were highly correlated but a slight mismatch was observed in the large-vessel areas and cortical depth profiles. Overall, this non-invasive, repeatable, simple hypoxia BOLD-MRI approach is viable for perfusion mapping of rodents.
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Affiliation(s)
- DongKyu Lee
- Center for Neuroscience Imaging Research (CNIR), Institute for Basic Science (IBS), Suwon, Republic of Korea
| | - Thuy Thi Le
- Center for Neuroscience Imaging Research (CNIR), Institute for Basic Science (IBS), Suwon, Republic of Korea.,Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea.,Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Republic of Korea
| | - Geun Ho Im
- Center for Neuroscience Imaging Research (CNIR), Institute for Basic Science (IBS), Suwon, Republic of Korea
| | - Seong-Gi Kim
- Center for Neuroscience Imaging Research (CNIR), Institute for Basic Science (IBS), Suwon, Republic of Korea.,Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea.,Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Republic of Korea
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45
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González Méndez PP, Rodino Climent J, Stanley JA, Sitaram R. Real-Time fMRI Neurofeedback Training as a Neurorehabilitation Approach on Depressive Disorders: A Systematic Review of Randomized Control Trials. J Clin Med 2022; 11:jcm11236909. [PMID: 36498484 PMCID: PMC9737316 DOI: 10.3390/jcm11236909] [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: 10/17/2022] [Revised: 11/02/2022] [Accepted: 11/10/2022] [Indexed: 11/25/2022] Open
Abstract
Real-time functional magnetic resonance imaging neurofeedback (rt-fMRI-nf) training is an emerging intervention for neurorehabilitation. However, its translation into clinical use on participants with clinical depression is unclear, the effect estimates from randomized control trials and the certainty of the supporting evidence on the effect estimates are unknown. As the number of studies on neurofeedback increases every year, and better quality evidence becomes available, we evaluate the evidence of all randomized control trials available on the clinical application of rt-fMRI-nf training on participants with clinical depression. We performed electronic searches in Pubmed, Embase, CENTRAL, rtFIN database, Epistemonikos, trial registers, reference lists, other systematic reviews, conference abstracts, and cross-citation in Google Scholar. Reviewers independently selected studies, extracted data and evaluated the risk of bias. The certainty of the evidence was judged using the GRADE framework. This review complies with PRISMA guidelines and was submitted to PROSPERO registration. We found 435 results. After the selection process, we included 11 reports corresponding to four RCTs. The effect of rt-fMRI-nf on improving the severity of clinical depression scores demonstrated a tendency to favor the intervention; however, the general effect was not significant. At end of treatment, SMD (standardized mean difference): -0.32 (95% CI -0.73 to 0.10). At follow-up, SMD: -0.33 (95% CI -0.91, 1.25). All the studies showed changes in BOLD fMRI activation after training; however, only one study confirmed regulation success during a transfer run. Whole-brain analyses suggests that rt-fMRI nf may alter activity patterns in brain networks. More studies are needed to evaluate quality of life, acceptability, adverse effects, cognitive tasks, and physiology measures. We conclude that the current evidence on the effect of rt-fMRI-nf training for decision-making outcomes in patients with clinical depression is still based on low certainty of the evidence.
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Affiliation(s)
- Pamela P. González Méndez
- Department of Psychiatry, School of Medicine, Pontificia Universidad Católica de Chile, Santiago 8331150, Chile
- Correspondence: (P.P.G.M.); (R.S.)
| | - Julio Rodino Climent
- Brain Dynamics Laboratory, School of Biomedical Engineering, Universidad de Valparaíso, Valparaíso 2362905, Chile
| | - Jeffrey A. Stanley
- Department of Psychiatry and Behavioral Neurosciences, School of Medicine, Wayne State University, Detroit, MI 48202, USA
| | - Ranganatha Sitaram
- Diagnostic Imaging Department, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Correspondence: (P.P.G.M.); (R.S.)
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Wang Y, LeDue JM, Murphy TH. Multiscale imaging informs translational mouse modeling of neurological disease. Neuron 2022; 110:3688-3710. [PMID: 36198319 DOI: 10.1016/j.neuron.2022.09.006] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 05/26/2022] [Accepted: 09/06/2022] [Indexed: 11/05/2022]
Abstract
Multiscale neurophysiology reveals that simple motor actions are associated with changes in neuronal firing in virtually every brain region studied. Accordingly, the assessment of focal pathology such as stroke or progressive neurodegenerative diseases must also extend widely across brain areas. To derive mechanistic information through imaging, multiple resolution scales and multimodal factors must be included, such as the structure and function of specific neurons and glial cells and the dynamics of specific neurotransmitters. Emerging multiscale methods in preclinical animal studies that span micro- to macroscale examinations fill this gap, allowing a circuit-based understanding of pathophysiological mechanisms. Combined with high-performance computation and open-source data repositories, these emerging multiscale and large field-of-view techniques include live functional ultrasound, multi- and single-photon wide-scale light microscopy, video-based miniscopes, and tissue-penetrating fiber photometry, as well as variants of post-mortem expansion microscopy. We present these technologies and outline use cases and data pipelines to uncover new knowledge within animal models of stroke, Alzheimer's disease, and movement disorders.
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Affiliation(s)
- Yundi Wang
- University of British Columbia, Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Detwiller Pavilion, 2255 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada; Djavad Mowafaghian Centre for Brain Health, University of British Columbia, 2215 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada
| | - Jeffrey M LeDue
- University of British Columbia, Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Detwiller Pavilion, 2255 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada; Djavad Mowafaghian Centre for Brain Health, University of British Columbia, 2215 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada
| | - Timothy H Murphy
- University of British Columbia, Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Detwiller Pavilion, 2255 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada; Djavad Mowafaghian Centre for Brain Health, University of British Columbia, 2215 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada.
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47
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Drew PJ. Neurovascular coupling: motive unknown. Trends Neurosci 2022; 45:809-819. [PMID: 35995628 PMCID: PMC9768528 DOI: 10.1016/j.tins.2022.08.004] [Citation(s) in RCA: 44] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 08/01/2022] [Accepted: 08/05/2022] [Indexed: 12/13/2022]
Abstract
In the brain, increases in neural activity drive changes in local blood flow via neurovascular coupling. The common explanation for increased blood flow (known as functional hyperemia) is that it supplies the metabolic needs of active neurons. However, there is a large body of evidence that is inconsistent with this idea. Baseline blood flow is adequate to supply oxygen needs even with elevated neural activity. Neurovascular coupling is irregular, absent, or inverted in many brain regions, behavioral states, and conditions. Increases in respiration can increase brain oxygenation without flow changes. Simulations show that given the architecture of the brain vasculature, areas of low blood flow are inescapable and cannot be removed by functional hyperemia. As discussed in this article, potential alternative functions of neurovascular coupling include supplying oxygen for neuromodulator synthesis, brain temperature regulation, signaling to neurons, stabilizing and optimizing the cerebral vascular structure, accommodating the non-Newtonian nature of blood, and driving the production and circulation of cerebrospinal fluid (CSF).
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Affiliation(s)
- Patrick J Drew
- Center for Neural Engineering, Departments of Engineering Science and Mechanics, Neurosurgery, Biology, and Biomedical Engineering, The Pennsylvania State University, W-317 Millennium Science Complex, University Park, PA 16802, USA.
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48
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Lee JY, You T, Woo CW, Kim SG. Optogenetic fMRI for Brain-Wide Circuit Analysis of Sensory Processing. Int J Mol Sci 2022; 23:ijms232012268. [PMID: 36293125 PMCID: PMC9602603 DOI: 10.3390/ijms232012268] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 10/12/2022] [Accepted: 10/12/2022] [Indexed: 11/20/2022] Open
Abstract
Sensory processing is a complex neurological process that receives, integrates, and responds to information from one's own body and environment, which is closely related to survival as well as neurological disorders. Brain-wide networks of sensory processing are difficult to investigate due to their dynamic regulation by multiple brain circuits. Optogenetics, a neuromodulation technique that uses light-sensitive proteins, can be combined with functional magnetic resonance imaging (ofMRI) to measure whole-brain activity. Since ofMRI has increasingly been used for investigating brain circuits underlying sensory processing for over a decade, we systematically reviewed recent ofMRI studies of sensory circuits and discussed the challenges of optogenetic fMRI in rodents.
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Affiliation(s)
- Jeong-Yun Lee
- Center for Neuroscience Imaging Research (CNIR), Institute for Basic Science (IBS), Suwon 16419, Korea
| | - Taeyi You
- Center for Neuroscience Imaging Research (CNIR), Institute for Basic Science (IBS), Suwon 16419, Korea
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon 16419, Korea
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon 16419, Korea
| | - Choong-Wan Woo
- Center for Neuroscience Imaging Research (CNIR), Institute for Basic Science (IBS), Suwon 16419, Korea
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon 16419, Korea
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon 16419, Korea
| | - Seong-Gi Kim
- Center for Neuroscience Imaging Research (CNIR), Institute for Basic Science (IBS), Suwon 16419, Korea
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon 16419, Korea
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon 16419, Korea
- Correspondence: ; Tel.: +82-31-299-4350; Fax: +82-31-299-4506
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Kim JH, Taylor AJ, Himmelbach M, Hagberg GE, Scheffler K, Ress D. Characterization of the blood oxygen level dependent hemodynamic response function in human subcortical regions with high spatiotemporal resolution. Front Neurosci 2022; 16:1009295. [PMID: 36303946 PMCID: PMC9592726 DOI: 10.3389/fnins.2022.1009295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 08/31/2022] [Indexed: 11/30/2022] Open
Abstract
Subcortical brain regions are absolutely essential for normal human function. These phylogenetically early brain regions play critical roles in human behaviors such as the orientation of attention, arousal, and the modulation of sensory signals to cerebral cortex. Despite the critical health importance of subcortical brain regions, there has been a dearth of research on their neurovascular responses. Blood oxygen level dependent (BOLD) functional MRI (fMRI) experiments can help fill this gap in our understanding. The BOLD hemodynamic response function (HRF) evoked by brief (<4 s) neural activation is crucial for the interpretation of fMRI results because linear analysis between neural activity and the BOLD response relies on the HRF. Moreover, the HRF is a consequence of underlying local blood flow and oxygen metabolism, so characterization of the HRF enables understanding of neurovascular and neurometabolic coupling. We measured the subcortical HRF at 9.4T and 3T with high spatiotemporal resolution using protocols that enabled reliable delineation of HRFs in individual subjects. These results were compared with the HRF in visual cortex. The HRF was faster in subcortical regions than cortical regions at both field strengths. There was no significant undershoot in subcortical areas while there was a significant post-stimulus undershoot that was tightly coupled with its peak amplitude in cortex. The different BOLD temporal dynamics indicate different vascular dynamics and neurometabolic responses between cortex and subcortical nuclei.
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Affiliation(s)
- Jung Hwan Kim
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, United States
| | - Amanda J. Taylor
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, United States
| | - Marc Himmelbach
- Division of Neuropsychology, Center of Neurology, Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Gisela E. Hagberg
- High Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
- Department of Biomedical Magnetic Resonance, Eberhard Karl’s University of Tübingen and University Hospital, Tübingen, Germany
| | - Klaus Scheffler
- High Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
- Department of Biomedical Magnetic Resonance, Eberhard Karl’s University of Tübingen and University Hospital, Tübingen, Germany
| | - David Ress
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, United States
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Demirayak P, Deshpande G, Visscher K. Laminar functional magnetic resonance imaging in vision research. Front Neurosci 2022; 16:910443. [PMID: 36267240 PMCID: PMC9577024 DOI: 10.3389/fnins.2022.910443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 08/23/2022] [Indexed: 11/13/2022] Open
Abstract
Magnetic resonance imaging (MRI) scanners at ultra-high magnetic fields have become available to use in humans, thus enabling researchers to investigate the human brain in detail. By increasing the spatial resolution, ultra-high field MR allows both structural and functional characterization of cortical layers. Techniques that can differentiate cortical layers, such as histological studies and electrode-based measurements have made critical contributions to the understanding of brain function, but these techniques are invasive and thus mainly available in animal models. There are likely to be differences in the organization of circuits between humans and even our closest evolutionary neighbors. Thus research on the human brain is essential. Ultra-high field MRI can observe differences between cortical layers, but is non-invasive and can be used in humans. Extensive previous literature has shown that neuronal connections between brain areas that transmit feedback and feedforward information terminate in different layers of the cortex. Layer-specific functional MRI (fMRI) allows the identification of layer-specific hemodynamic responses, distinguishing feedback and feedforward pathways. This capability has been particularly important for understanding visual processing, as it has allowed researchers to test hypotheses concerning feedback and feedforward information in visual cortical areas. In this review, we provide a general overview of successful ultra-high field MRI applications in vision research as examples of future research.
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Affiliation(s)
- Pinar Demirayak
- Civitan International Research Center, University of Alabama at Birmingham, Birmingham, AL, United States
- Department of Neurobiology, University of Alabama at Birmingham, Birmingham, AL, United States
- *Correspondence: Pinar Demirayak,
| | - Gopikrishna Deshpande
- Department of Electrical and Computer Engineering, AU MRI Research Center, Auburn University, Auburn, AL, United States
- Department of Psychological Sciences, Auburn University, Auburn, AL, United States
- Alabama Advanced Imaging Consortium, Birmingham, AL, United States
- Center for Neuroscience, Auburn University, Auburn, AL, United States
- School of Psychology, Capital Normal University, Beijing, China
- Key Laboratory of Learning and Cognition, Capital Normal University, Beijing, China
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
- Centre for Brain Research, Indian Institute of Science, Bangalore, India
| | - Kristina Visscher
- Civitan International Research Center, University of Alabama at Birmingham, Birmingham, AL, United States
- Department of Neurobiology, University of Alabama at Birmingham, Birmingham, AL, United States
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