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Medeiros J, Simões M, Castelhano J, Abreu R, Couceiro R, Henriques J, Castelo-Branco M, Madeira H, Teixeira C, de Carvalho P. EEG as a potential ground truth for the assessment of cognitive state in software development activities: A multimodal imaging study. PLoS One 2024; 19:e0299108. [PMID: 38452019 PMCID: PMC10919648 DOI: 10.1371/journal.pone.0299108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 02/06/2024] [Indexed: 03/09/2024] Open
Abstract
Cognitive human error and recent cognitive taxonomy on human error causes of software defects support the intuitive idea that, for instance, mental overload, attention slips, and working memory overload are important human causes for software bugs. In this paper, we approach the EEG as a reliable surrogate to MRI-based reference of the programmer's cognitive state to be used in situations where heavy imaging techniques are infeasible. The idea is to use EEG biomarkers to validate other less intrusive physiological measures, that can be easily recorded by wearable devices and useful in the assessment of the developer's cognitive state during software development tasks. Herein, our EEG study, with the support of fMRI, presents an extensive and systematic analysis by inspecting metrics and extracting relevant information about the most robust features, best EEG channels and the best hemodynamic time delay in the context of software development tasks. From the EEG-fMRI similarity analysis performed, we found significant correlations between a subset of EEG features and the Insula region of the brain, which has been reported as a region highly related to high cognitive tasks, such as software development tasks. We concluded that despite a clear inter-subject variability of the best EEG features and hemodynamic time delay used, the most robust and predominant EEG features, across all the subjects, are related to the Hjorth parameter Activity and Total Power features, from the EEG channels F4, FC4 and C4, and considering in most of the cases a hemodynamic time delay of 4 seconds used on the hemodynamic response function. These findings should be taken into account in future EEG-fMRI studies in the context of software debugging.
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Affiliation(s)
- Júlio Medeiros
- Department of Informatics Engineering, CISUC-Centre for Informatics and Systems of the University of Coimbra, University of Coimbra, Coimbra, Portugal
| | - Marco Simões
- Department of Informatics Engineering, CISUC-Centre for Informatics and Systems of the University of Coimbra, University of Coimbra, Coimbra, Portugal
| | - João Castelhano
- ICNAS-Institute of Nuclear Sciences Applied to Health, University of Coimbra, Coimbra, Portugal
| | - Rodolfo Abreu
- ICNAS-Institute of Nuclear Sciences Applied to Health, University of Coimbra, Coimbra, Portugal
| | - Ricardo Couceiro
- Department of Informatics Engineering, CISUC-Centre for Informatics and Systems of the University of Coimbra, University of Coimbra, Coimbra, Portugal
| | - Jorge Henriques
- Department of Informatics Engineering, CISUC-Centre for Informatics and Systems of the University of Coimbra, University of Coimbra, Coimbra, Portugal
| | - Miguel Castelo-Branco
- ICNAS-Institute of Nuclear Sciences Applied to Health, University of Coimbra, Coimbra, Portugal
| | - Henrique Madeira
- Department of Informatics Engineering, CISUC-Centre for Informatics and Systems of the University of Coimbra, University of Coimbra, Coimbra, Portugal
| | - César Teixeira
- Department of Informatics Engineering, CISUC-Centre for Informatics and Systems of the University of Coimbra, University of Coimbra, Coimbra, Portugal
| | - Paulo de Carvalho
- Department of Informatics Engineering, CISUC-Centre for Informatics and Systems of the University of Coimbra, University of Coimbra, Coimbra, Portugal
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Nozari E, Bertolero MA, Stiso J, Caciagli L, Cornblath EJ, He X, Mahadevan AS, Pappas GJ, Bassett DS. Macroscopic resting-state brain dynamics are best described by linear models. Nat Biomed Eng 2024; 8:68-84. [PMID: 38082179 DOI: 10.1038/s41551-023-01117-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 09/26/2023] [Indexed: 12/22/2023]
Abstract
It is typically assumed that large networks of neurons exhibit a large repertoire of nonlinear behaviours. Here we challenge this assumption by leveraging mathematical models derived from measurements of local field potentials via intracranial electroencephalography and of whole-brain blood-oxygen-level-dependent brain activity via functional magnetic resonance imaging. We used state-of-the-art linear and nonlinear families of models to describe spontaneous resting-state activity of 700 participants in the Human Connectome Project and 122 participants in the Restoring Active Memory project. We found that linear autoregressive models provide the best fit across both data types and three performance metrics: predictive power, computational complexity and the extent of the residual dynamics unexplained by the model. To explain this observation, we show that microscopic nonlinear dynamics can be counteracted or masked by four factors associated with macroscopic dynamics: averaging over space and over time, which are inherent to aggregated macroscopic brain activity, and observation noise and limited data samples, which stem from technological limitations. We therefore argue that easier-to-interpret linear models can faithfully describe macroscopic brain dynamics during resting-state conditions.
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Affiliation(s)
- Erfan Nozari
- Department of Mechanical Engineering, University of California, Riverside, CA, USA
- Department of Electrical and Computer Engineering, University of California, Riverside, CA, USA
- Department of Bioengineering, University of California, Riverside, CA, USA
| | - Maxwell A Bertolero
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Jennifer Stiso
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA
| | - Lorenzo Caciagli
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Eli J Cornblath
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA
| | - Xiaosong He
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Arun S Mahadevan
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - George J Pappas
- Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Dani S Bassett
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
- Santa Fe Institute, Santa Fe, NM, USA.
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Rangaprakash D, David O, Barry RL, Deshpande G. Comparison of hemodynamic response functions obtained from resting-state functional MRI and invasive electrophysiological recordings in rats. bioRxiv 2023:2023.02.27.530359. [PMID: 37961471 PMCID: PMC10634675 DOI: 10.1101/2023.02.27.530359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Resting-state functional MRI (rs-fMRI) is a popular technology that has enriched our understanding of brain and spinal cord functioning, including how different regions communicate (connectivity). But fMRI is an indirect measure of neural activity capturing blood hemodynamics. The hemodynamic response function (HRF) interfaces between the unmeasured neural activity and measured fMRI time series. The HRF is variable across brain regions and individuals, and is modulated by non-neural factors. Ignoring this HRF variability causes errors in FC estimates. Hence, it is crucial to reliably estimate the HRF from rs-fMRI data. Robust techniques have emerged to estimate the HRF from fMRI time series. Although such techniques have been validated non-invasively using simulated and empirical fMRI data, thorough invasive validation using simultaneous electrophysiological recordings, the gold standard, has been elusive. This report addresses this gap in the literature by comparing HRFs derived from invasive intracranial electroencephalogram recordings with HRFs estimated from simultaneously acquired fMRI data in six epileptic rats. We found that the HRF shape parameters (HRF amplitude, latency and width) were not significantly different (p>0.05) between ground truth and estimated HRFs. In the single pathological region, the HRF width was marginally significantly different (p=0.03). Our study provides preliminary invasive validation for the efficacy of the HRF estimation technique in reliably estimating the HRF non-invasively from rs-fMRI data directly. This has a notable impact on rs-fMRI connectivity studies, and we recommend that HRF deconvolution be performed to minimize HRF variability and improve connectivity estimates.
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Affiliation(s)
- D Rangaprakash
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, USA
| | - Olivier David
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institute of Neuroscience, F-38000, Grenoble, France
- Aix-Marseille Université, Institut National de la Santé et de la Recherche Médicale, Institut de Neurosciences des Systèmes (INS) UMR1106, Marseille 13005, France
| | - Robert L Barry
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, USA
- Harvard-Massachusetts Institute of Technology Division of Health Sciences & Technology, Cambridge, Massachusetts, USA
| | - Gopikrishna Deshpande
- AU MRI Research Center, Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, USA
- Department of Psychological Sciences, Auburn University, Auburn, AL, USA
- Center for Neuroscience, Auburn University, Auburn, AL, USA
- Alabama Advanced Imaging Consortium, Birmingham, AL, USA
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Schilling KG, Li M, Rheault F, Gao Y, Cai L, Zhao Y, Xu L, Ding Z, Anderson AW, Landman BA, Gore JC. Whole-brain, gray, and white matter time-locked functional signal changes with simple tasks and model-free analysis. Proc Natl Acad Sci U S A 2023; 120:e2219666120. [PMID: 37824529 PMCID: PMC10589709 DOI: 10.1073/pnas.2219666120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Accepted: 08/11/2023] [Indexed: 10/14/2023] Open
Abstract
Recent studies have revealed the production of time-locked blood oxygenation level-dependent (BOLD) functional MRI (fMRI) signals throughout the entire brain in response to tasks, challenging the existence of sparse and localized brain functions and highlighting the pervasiveness of potential false negative fMRI findings. "Whole-brain" actually refers to gray matter, the only tissue traditionally studied with fMRI. However, several reports have demonstrated reliable detection of BOLD signals in white matter, which have previously been largely ignored. Using simple tasks and analyses, we demonstrate BOLD signal changes across the whole brain, in both white and gray matters, in similar manner to previous reports of whole brain studies. We investigated whether white matter displays time-locked BOLD signals across multiple structural pathways in response to a stimulus in a similar manner to the cortex. We find that both white and gray matter show time-locked activations across the whole brain, with a majority of both tissue types showing statistically significant signal changes for all task stimuli investigated. We observed a wide range of signal responses to tasks, with different regions showing different BOLD signal changes to the same task. Moreover, we find that each region may display different BOLD responses to different stimuli. Overall, we present compelling evidence that, just like all gray matter, essentially all white matter in the brain shows time-locked BOLD signal changes in response to multiple stimuli, challenging the idea of sparse functional localization and the prevailing wisdom of treating white matter BOLD signals as artifacts to be removed.
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Affiliation(s)
- Kurt G. Schilling
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN37232
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN37232
| | - Muwei Li
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN37232
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN37232
| | - Francois Rheault
- Department of Electrical Engineering and Computer Engineering, Vanderbilt University, Nashville, TN37235
| | - Yurui Gao
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN37232
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN37235
| | - Leon Cai
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN37235
| | - Yu Zhao
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN37232
| | - Lyuan Xu
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN37232
| | - Zhaohua Ding
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN37232
| | - Adam W. Anderson
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN37232
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN37232
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN37235
| | - Bennett A. Landman
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN37232
- Department of Electrical Engineering and Computer Engineering, Vanderbilt University, Nashville, TN37235
| | - John C. Gore
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN37232
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN37232
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN37235
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Chabert S, Salas R, Cantor E, Veloz A, Cancino A, González M, Torres F, Bennett C. Hemodynamic response function description in patients with glioma. J Neuroradiol 2023:S0150-9861(23)00247-X. [PMID: 37805126 DOI: 10.1016/j.neurad.2023.10.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 10/04/2023] [Accepted: 10/05/2023] [Indexed: 10/09/2023]
Abstract
INTRODUCTION Functional magnetic resonance imaging is a powerful tool that has provided many insights into cognitive sciences. Yet, as its analysis is mostly based on the knowledge of an a priori canonical hemodynamic response function (HRF), its reliability in patients' applications has been questioned. There have been reports of neurovascular uncoupling in patients with glioma, but no specific description of the Hemodynamic Response Function (HRF) in glioma has been reported so far. The aim of this work is to describe the HRF in patients with glioma. METHODS Forty patients were included. MR images were acquired on a 1.5T scanner. Activated clusters were identified using a fuzzy general linear model; HRFs were adjusted with a double-gamma function. Analyses were undertaken considering the tumor grade, age, sex, tumor location, and activated location. RESULTS Differences are found in the occipital, limbic, insular, and sub-lobar areas, but not in the frontal, temporal, and parietal lobes. The presence of a glioma slows the time-to-peak and onset times by 5.2 and 3.8 % respectively; high-grade gliomas present 8.1 % smaller HRF widths than low-grade gliomas. DISCUSSION AND CONCLUSION There is significant HRF variation due to the presence of glioma, but the magnitudes of the observed differences are small. Most processing pipelines should be robust enough for this magnitude of variation and little if any impact should be visible on functional maps. The differences that have been observed in the literature between functional mapping obtained with magnetic resonance vs. that obtained with direct electrostimulation during awake surgery are more probably due to the intrinsic difference in the mapping process: fMRI mapping detects all recruited areas while intra-surgical mapping indicates only the areas indispensable for the realization of a certain task. Surgical mapping might not be the gold standard to use when trying to validate the fMRI mapping process.
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Affiliation(s)
- Stéren Chabert
- School of Biomedical Engineering, Universidad de Valparaiso, General Cruz 222, Valparaiso, Chile; Millennium Science Initiative Intelligent Healthcare Engineering, Santiago, Chile.
| | - Rodrigo Salas
- School of Biomedical Engineering, Universidad de Valparaiso, General Cruz 222, Valparaiso, Chile; Millennium Science Initiative Intelligent Healthcare Engineering, Santiago, Chile
| | - Erika Cantor
- Institute of Statistics, Universidad de Valparaíso, Valparaíso, Chile
| | - Alejandro Veloz
- School of Biomedical Engineering, Universidad de Valparaiso, General Cruz 222, Valparaiso, Chile
| | - Astrid Cancino
- Millennium Science Initiative Intelligent Healthcare Engineering, Santiago, Chile; Doctorado en Ciencias e Ingeniería para la Salud, Universidad de Valparaiso, Valparaiso, Chile
| | - Matías González
- Neurosurgery Department, Hospital Carlos van Buren, Valparaiso, Chile
| | - Francisco Torres
- Millennium Science Initiative Intelligent Healthcare Engineering, Santiago, Chile; Radiology Department, Hospital Carlos van Buren, Valparaiso, Chile
| | - Carlos Bennett
- Neurosurgery Department, Hospital Carlos van Buren, Valparaiso, Chile
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Fesharaki NJ, Taylor A, Mosby K, Kim JH, Ress D. Global effects of aging on the hemodynamic response function in the human brain. Res Sq 2023:rs.3.rs-3299293. [PMID: 37720046 PMCID: PMC10503846 DOI: 10.21203/rs.3.rs-3299293/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/19/2023]
Abstract
In functional magnetic resonance imaging, the hemodynamic response function (HRF) is a transient, stereotypical response to local changes in cerebral hemodynamics and oxygen metabolism due to briefly (< 4 s) evoked neural activity. Accordingly, the HRF is often used as an impulse response with the assumption of linearity in data analysis. In cognitive aging studies, it has been very common to interpret differences in brain activation as age-related changes in neural activity. Contrary to this assumption, however, evidence has accrued that normal aging may also significantly affect the vasculature, thereby affecting cerebral hemodynamics and metabolism, confounding interpretation of fMRI aging studies. In this study, use was made of a multisensory stimulus to evoke the HRF in ~ 87% of cerebral cortex in cognitively intact adults with ages ranging from 22-75 years. The stimulus evokes both positive and negative HRFs, which were characterized using model-free parameters in native-space coordinates. Results showed significant age trends in HRF parameter distributions in terms of both amplitudes (e.g., peak amplitude and CNR) and temporal dynamics (e.g., full-width-at-half-maximum). This work sets the stage for using HRF methods as a biomarker for age-related pathology.
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Chen G, Taylor PA, Reynolds RC, Leibenluft E, Pine DS, Brotman MA, Pagliaccio D, Haller SP. BOLD Response is more than just magnitude: Improving detection sensitivity through capturing hemodynamic profiles. Neuroimage 2023; 277:120224. [PMID: 37327955 PMCID: PMC10527035 DOI: 10.1016/j.neuroimage.2023.120224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 05/21/2023] [Accepted: 06/11/2023] [Indexed: 06/18/2023] Open
Abstract
Typical fMRI analyses often assume a canonical hemodynamic response function (HRF) that primarily focuses on the peak height of the overshoot, neglecting other morphological aspects. Consequently, reported analyses often reduce the overall response curve to a single scalar value. In this study, we take a data-driven approach to HRF estimation at the whole-brain voxel level, without assuming a response profile at the individual level. We then employ a roughness penalty at the population level to estimate the response curve, aiming to enhance predictive accuracy, inferential efficiency, and cross-study reproducibility. By examining a fast event-related FMRI dataset, we demonstrate the shortcomings and information loss associated with adopting the canonical approach. Furthermore, we address the following key questions: 1) To what extent does the HRF shape vary across different regions, conditions, and participant groups? 2) Does the data-driven approach improve detection sensitivity compared to the canonical approach? 3) Can analyzing the HRF shape help validate the presence of an effect in conjunction with statistical evidence? 4) Does analyzing the HRF shape offer evidence for whole-brain response during a simple task?
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Affiliation(s)
- Gang Chen
- Scientific and Statistical Computing Core, National Institute of Mental Health, USA.
| | - Paul A Taylor
- Scientific and Statistical Computing Core, National Institute of Mental Health, USA
| | - Richard C Reynolds
- Scientific and Statistical Computing Core, National Institute of Mental Health, USA
| | - Ellen Leibenluft
- Neuroscience and Novel Therapeutics Unit, Emotion and Development Branch, National Institute of Mental Health, USA
| | - Daniel S Pine
- Neuroscience and Novel Therapeutics Unit, Emotion and Development Branch, National Institute of Mental Health, USA
| | - Melissa A Brotman
- Neuroscience and Novel Therapeutics Unit, Emotion and Development Branch, National Institute of Mental Health, USA
| | | | - Simone P Haller
- Neuroscience and Novel Therapeutics Unit, Emotion and Development Branch, National Institute of Mental Health, USA
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Bailes SM, Gomez DEP, Setzer B, Lewis LD. Resting-state fMRI signals contain spectral signatures of local hemodynamic response timing. eLife 2023; 12:e86453. [PMID: 37565644 PMCID: PMC10506795 DOI: 10.7554/elife.86453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Accepted: 08/10/2023] [Indexed: 08/12/2023] Open
Abstract
Functional magnetic resonance imaging (fMRI) has proven to be a powerful tool for noninvasively measuring human brain activity; yet, thus far, fMRI has been relatively limited in its temporal resolution. A key challenge is understanding the relationship between neural activity and the blood-oxygenation-level-dependent (BOLD) signal obtained from fMRI, generally modeled by the hemodynamic response function (HRF). The timing of the HRF varies across the brain and individuals, confounding our ability to make inferences about the timing of the underlying neural processes. Here, we show that resting-state fMRI signals contain information about HRF temporal dynamics that can be leveraged to understand and characterize variations in HRF timing across both cortical and subcortical regions. We found that the frequency spectrum of resting-state fMRI signals significantly differs between voxels with fast versus slow HRFs in human visual cortex. These spectral differences extended to subcortex as well, revealing significantly faster hemodynamic timing in the lateral geniculate nucleus of the thalamus. Ultimately, our results demonstrate that the temporal properties of the HRF impact the spectral content of resting-state fMRI signals and enable voxel-wise characterization of relative hemodynamic response timing. Furthermore, our results show that caution should be used in studies of resting-state fMRI spectral properties, because differences in fMRI frequency content can arise from purely vascular origins. This finding provides new insight into the temporal properties of fMRI signals across voxels, which is crucial for accurate fMRI analyses, and enhances the ability of fast fMRI to identify and track fast neural dynamics.
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Affiliation(s)
- Sydney M Bailes
- Department of Biomedical Engineering, Boston UniversityBostonUnited States
| | - Daniel EP Gomez
- Department of Biomedical Engineering, Boston UniversityBostonUnited States
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General HospitalCharlestownUnited States
- Department of Radiology, Harvard Medical SchoolBostonUnited States
| | - Beverly Setzer
- Department of Biomedical Engineering, Boston UniversityBostonUnited States
- Graduate Program for Neuroscience, Boston UniversityBostonUnited States
| | - Laura D Lewis
- Department of Biomedical Engineering, Boston UniversityBostonUnited States
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General HospitalCharlestownUnited States
- Institute for Medical Engineering and Science, Massachusetts Institute of TechnologyCambridgeUnited States
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of TechnologyCambridgeUnited States
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Rangaprakash D, Barry RL, Deshpande G. The confound of hemodynamic response function variability in human resting-state functional MRI studies. Front Neurosci 2023; 17:934138. [PMID: 37521709 PMCID: PMC10375034 DOI: 10.3389/fnins.2023.934138] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Accepted: 04/07/2023] [Indexed: 08/01/2023] Open
Abstract
Functional magnetic resonance imaging (fMRI) is an indirect measure of neural activity with the hemodynamic response function (HRF) coupling it with unmeasured neural activity. The HRF, modulated by several non-neural factors, is variable across brain regions, individuals and populations. Yet, a majority of human resting-state fMRI connectivity studies continue to assume a non-variable HRF. In this article, with supportive prior evidence, we argue that HRF variability cannot be ignored as it substantially confounds within-subject connectivity estimates and between-subjects connectivity group differences. We also discuss its clinical relevance with connectivity impairments confounded by HRF aberrations in several disorders. We present limited data on HRF differences between women and men, which resulted in a 15.4% median error in functional connectivity estimates in a group-level comparison. We also discuss the implications of HRF variability for fMRI studies in the spinal cord. There is a need for more dialogue within the community on the HRF confound, and we hope that our article is a catalyst in the process.
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Affiliation(s)
- D. Rangaprakash
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
| | - Robert L. Barry
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Harvard-Massachusetts Institute of Technology Division of Health Sciences and Technology, Cambridge, MA, United States
| | - 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
- Center for Neuroscience, Auburn University, Auburn, AL, United States
- Alabama Advanced Imaging Consortium, Birmingham, AL, United States
- Key Laboratory for Learning and Cognition, School of Psychology, 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
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Sapey-Triomphe LA, Pattyn L, Weilnhammer V, Sterzer P, Wagemans J. Neural correlates of hierarchical predictive processes in autistic adults. Nat Commun 2023; 14:3640. [PMID: 37336874 DOI: 10.1038/s41467-023-38580-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 05/08/2023] [Indexed: 06/21/2023] Open
Abstract
Bayesian theories of autism spectrum disorders (ASD) suggest that atypical predictive mechanisms could underlie the autistic symptomatology, but little is known about their neural correlates. Twenty-six neurotypical (NT) and 26 autistic adults participated in an fMRI study where they performed an associative learning task in a volatile environment. By inverting a model of perceptual inference, we characterized the neural correlates of hierarchically structured predictions and prediction errors in ASD. Behaviorally, the predictive abilities of autistic adults were intact. Neurally, predictions were encoded hierarchically in both NT and ASD participants and biased their percepts. High-level predictions were following activity levels in a set of regions more closely in ASD than NT. Prediction errors yielded activation in shared regions in NT and ASD, but group differences were found in the anterior cingulate cortex and putamen. This study sheds light on the neural specificities of ASD that might underlie atypical predictive processing.
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Affiliation(s)
- Laurie-Anne Sapey-Triomphe
- Department of Brain and Cognition, Leuven Brain Institute, KU Leuven, 3000, Leuven, Belgium.
- Leuven Autism Research (LAuRes), KU Leuven, 3000, Leuven, Belgium.
| | - Lauren Pattyn
- Department of Brain and Cognition, Leuven Brain Institute, KU Leuven, 3000, Leuven, Belgium
| | - Veith Weilnhammer
- Department of Psychiatry, Charité-Universitätsmedizin Berlin, 10117, Berlin, Germany
- Berlin Institute of Health, Charité-Universitätsmedizin Berlin, 10178, Berlin, Germany
| | - Philipp Sterzer
- Department of Psychiatry, Charité-Universitätsmedizin Berlin, 10117, Berlin, Germany
- Berlin Institute of Health, Charité-Universitätsmedizin Berlin, 10178, Berlin, Germany
| | - Johan Wagemans
- Department of Brain and Cognition, Leuven Brain Institute, KU Leuven, 3000, Leuven, Belgium
- Leuven Autism Research (LAuRes), KU Leuven, 3000, Leuven, Belgium
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Dowdle LT, Vizioli L, Moeller S, Akçakaya M, Olman C, Ghose G, Yacoub E, Uğurbil K. Evaluating increases in sensitivity from NORDIC for diverse fMRI acquisition strategies. Neuroimage 2023; 270:119949. [PMID: 36804422 DOI: 10.1016/j.neuroimage.2023.119949] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Revised: 01/27/2023] [Accepted: 02/15/2023] [Indexed: 02/19/2023] Open
Abstract
As the neuroimaging field moves towards detecting smaller effects at higher spatial resolutions, and faster sampling rates, there is increased attention given to the deleterious contribution of unstructured, thermal noise. Here, we critically evaluate the performance of a recently developed reconstruction method, termed NORDIC, for suppressing thermal noise using datasets acquired with various field strengths, voxel sizes, sampling rates, and task designs. Following minimal preprocessing, statistical activation (t-values) of NORDIC processed data was compared to the results obtained with alternative denoising methods. Additionally, we examined the consistency of the estimates of task responses at the single-voxel, single run level, using a finite impulse response (FIR) model. To examine the potential impact on effective image resolution, the overall smoothness of the data processed with different methods was estimated. Finally, to determine if NORDIC alters or removes temporal information important for modeling responses, we employed an exhaustive leave-p-out cross validation approach, using FIR task responses to predict held out timeseries, quantified using R2. After NORDIC, the t-values are increased, an improvement comparable to what could be achieved by 1.5 voxels smoothing, and task events are clearly visible and have less cross-run error. These advantages are achieved with smoothness estimates increasing by less than 4%, while 1.5 voxel smoothing is associated with increases of over 140%. Cross-validated R2s based on the FIR models show that NORDIC is not measurably distorting the temporal structure of the data under this approach and is the best predictor of non-denoised time courses. The results demonstrate that analyzing 1 run of data after NORDIC produces results equivalent to using 2 to 3 original runs and that NORDIC performs equally well across a diverse array of functional imaging protocols. Significance Statement: For functional neuroimaging, the increasing availability of higher field strengths and ever higher spatiotemporal resolutions has led to concomitant increase in concerns about the deleterious effects of thermal noise. Historically this noise source was suppressed using methods that reduce spatial precision such as image blurring or averaging over a large number of trials or sessions, which necessitates large data collection efforts. Here, we critically evaluate the performance of a recently developed reconstruction method, termed NORDIC, which suppresses thermal noise. Across datasets varying in field strength, voxel sizes, sampling rates, and task designs, NORDIC produces substantial gains in data quality. Both conventional t-statistics derived from general linear models and coefficients of determination for predicting unseen data are improved. These gains match or even exceed those associated with 1 voxel Full Width Half Max image smoothing, however, even such small amounts of smoothing are associated with a 52% reduction in estimates of spatial precision, whereas the measurable difference in spatial precision is less than 4% following NORDIC.
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Affiliation(s)
- Logan T Dowdle
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, 2021 6th Street SE, MN 55455, United States; Department of Neuroscience, University of Minnesota, Minneapolis, MN, United States.
| | - Luca Vizioli
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, 2021 6th Street SE, MN 55455, United States
| | - Steen Moeller
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, 2021 6th Street SE, MN 55455, United States
| | - Mehmet Akçakaya
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, 2021 6th Street SE, MN 55455, United States; Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, United States
| | - Cheryl Olman
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, 2021 6th Street SE, MN 55455, United States; Department of Psychology, University of Minnesota, Minneapolis, MN, United States
| | - Geoffrey Ghose
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, 2021 6th Street SE, MN 55455, United States; Department of Neuroscience, University of Minnesota, Minneapolis, MN, United States; Department of Psychology, University of Minnesota, Minneapolis, MN, United States
| | - Essa Yacoub
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, 2021 6th Street SE, MN 55455, United States
| | - Kâmil Uğurbil
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, 2021 6th Street SE, MN 55455, United States
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12
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Cowdrick KR, Urner T, Sathialingam E, Fang Z, Quadri A, Turrentine K, Yup Lee S, Buckley EM. Agreement in cerebrovascular reactivity assessed with diffuse correlation spectroscopy across experimental paradigms improves with short separation regression. Neurophotonics 2023; 10:025002. [PMID: 37034012 PMCID: PMC10079775 DOI: 10.1117/1.nph.10.2.025002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 03/07/2023] [Indexed: 06/19/2023]
Abstract
Significance Cerebrovascular reactivity (CVR), i.e., the ability of cerebral vasculature to dilate or constrict in response to vasoactive stimuli, is a biomarker of vascular health. Exogenous administration of inhaled carbon dioxide, i.e., hypercapnia (HC), remains the "gold-standard" intervention to assess CVR. More tolerable paradigms that enable CVR quantification when HC is difficult/contraindicated have been proposed. However, because these paradigms feature mechanistic differences in action, an assessment of agreement of these more tolerable paradigms to HC is needed. Aim We aim to determine the agreement of CVR assessed during HC, breath-hold (BH), and resting state (RS) paradigms. Approach Healthy adults were subject to HC, BH, and RS paradigms. End tidal carbon dioxide (EtCO2) and cerebral blood flow (CBF, assessed with diffuse correlation spectroscopy) were monitored continuously. CVR (%/mmHg) was quantified via linear regression of CBF versus EtCO2 or via a general linear model (GLM) that was used to minimize the influence of systemic and extracerebral signal contributions. Results Strong agreement ( CCC ≥ 0.69 ; R ≥ 0.76 ) among CVR paradigms was demonstrated when utilizing a GLM to regress out systemic/extracerebral signal contributions. Linear regression alone showed poor agreement across paradigms ( CCC ≤ 0.35 ; R ≤ 0.45 ). Conclusions More tolerable experimental paradigms coupled with regression of systemic/extracerebral signal contributions may offer a viable alternative to HC for assessing CVR.
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Affiliation(s)
- Kyle R. Cowdrick
- Georgia Institute of Technology and Emory University, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
| | - Tara Urner
- Georgia Institute of Technology and Emory University, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
| | - Eashani Sathialingam
- Georgia Institute of Technology and Emory University, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
| | - Zhou Fang
- Georgia Institute of Technology and Emory University, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
| | - Ayesha Quadri
- Children’s Healthcare of Atlanta and Emory University School of Medicine, Department of Pediatrics, Atlanta, Georgia, United States
- Morehouse School of Medicine, Atlanta, Georgia, United States
| | - Katherine Turrentine
- Children’s Healthcare of Atlanta and Emory University School of Medicine, Department of Pediatrics, Atlanta, Georgia, United States
| | - Seung Yup Lee
- Georgia Institute of Technology and Emory University, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
- Kennesaw State University, Department of Electrical and Computer Engineering, Marietta, Georgia, United States
| | - Erin M. Buckley
- Georgia Institute of Technology and Emory University, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
- Children’s Healthcare of Atlanta and Emory University School of Medicine, Department of Pediatrics, Atlanta, Georgia, United States
- Children’s Healthcare of Atlanta, Children’s Research Scholar, Atlanta, Georgia, United States
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13
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Schilling KG, Li M, Rheault F, Gao Y, Cai L, Zhao Y, Xu L, Ding Z, Anderson AW, Landman BA, Gore JC. Whole-brain, gray and white matter time-locked functional signal changes with simple tasks and model-free analysis. bioRxiv 2023:2023.02.14.528557. [PMID: 36824784 PMCID: PMC9948951 DOI: 10.1101/2023.02.14.528557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/17/2023]
Abstract
Recent studies have revealed the production of time-locked blood oxygenation-level dependent (BOLD) functional MRI (fMRI) signals throughout the entire brain in response to a task, challenging the idea of sparse and localized brain functions, and highlighting the pervasiveness of potential false negative fMRI findings. In these studies, 'whole-brain' refers to gray matter regions only, which is the only tissue traditionally studied with fMRI. However, recent reports have also demonstrated reliable detection and analyses of BOLD signals in white matter which have been largely ignored in previous reports. Here, using model-free analysis and simple tasks, we investigate BOLD signal changes in both white and gray matters. We aimed to evaluate whether white matter also displays time-locked BOLD signals across all structural pathways in response to a stimulus. We find that both white and gray matter show time-locked activations across the whole-brain, with a majority of both tissue types showing statistically significant signal changes for all task stimuli investigated. We observed a wide range of signal responses to tasks, with different regions showing very different BOLD signal changes to the same task. Moreover, we find that each region may display different BOLD responses to different stimuli. Overall, we present compelling evidence that the whole brain, including both white and gray matter, show time-locked activation to multiple stimuli, not only challenging the idea of sparse functional localization, but also the prevailing wisdom of treating white matter BOLD signals as artefacts to be removed.
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Affiliation(s)
- Kurt G Schilling
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Muwei Li
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Francois Rheault
- Department of Electrical Engineering and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Yurui Gao
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States
| | - Leon Cai
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States
| | - Yu Zhao
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Lyuan Xu
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Zhaohua Ding
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Adam W Anderson
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States
| | - Bennett A Landman
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Electrical Engineering and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - John C Gore
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States
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14
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Chuang KH, Li Z, Huang HH, Khorasani Gerdekoohi S, Athwal D. Hemodynamic transient and functional connectivity follow structural connectivity and cell type over the brain hierarchy. Proc Natl Acad Sci U S A 2023; 120:e2202435120. [PMID: 36693103 DOI: 10.1073/pnas.2202435120] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Abstract
The neural circuit of the brain is organized as a hierarchy of functional units with wide-ranging connections that support information flow and functional connectivity. Studies using MRI indicate a moderate coupling between structural and functional connectivity at the system level. However, how do connections of different directions (feedforward and feedback) and regions with different excitatory and inhibitory (E/I) neurons shape the hemodynamic activity and functional connectivity over the hierarchy are unknown. Here, we used functional MRI to detect optogenetic-evoked and resting-state activities over a somatosensory pathway in the mouse brain in relation to axonal projection and E/I distribution. Using a highly sensitive ultrafast imaging, we identified extensive activation in regions up to the third order of axonal projections following optogenetic excitation of the ventral posteriomedial nucleus of the thalamus. The evoked response and functional connectivity correlated with feedforward projections more than feedback projections and weakened with the hierarchy. The hemodynamic response exhibited regional and hierarchical differences, with slower and more variable responses in high-order areas and bipolar response predominantly in the contralateral cortex. Electrophysiological recordings suggest that these reflect differences in neural activity rather than neurovascular coupling. Importantly, the positive and negative parts of the hemodynamic response correlated with E/I neuronal densities, respectively. Furthermore, resting-state functional connectivity was more associated with E/I distribution, whereas stimulus-evoked effective connectivity followed structural wiring. These findings indicate that the structure-function relationship is projection-, cell-type- and hierarchy-dependent. Hemodynamic transients could reflect E/I activity and the increased complexity of hierarchical processing.
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15
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Zhang D, Fu Q, Xue C, Xiao C, Sun Y, Liu W, Hu X. Characterization of Hemodynamic Alteration in Parkinson's Disease and Effect on Resting-State Connectivity. Neuroscience 2023:S0306-4522(23)00006-4. [PMID: 36642395 DOI: 10.1016/j.neuroscience.2023.01.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 12/30/2022] [Accepted: 01/03/2023] [Indexed: 01/14/2023]
Abstract
Functional magnetic resonance imaging (fMRI) is a convolution of latent neural activity and the hemodynamic response function (HRF). According to prior studies, the neurodegenerative process in idiopathic Parkinson's Disease (PD) interacts significantly with neuromuscular abnormalities. Although these underlying neuromuscular changes might influence the temporal characteristics of HRF and fMRI signals, relatively few studies have explored this possibility. We hypothesized that such alterations would engender changes in estimated functional connectivity (FC) in fMRI space compared to latent neural space. To test these theories, we calculated voxel-level HRFs by deconvolving resting-state fMRI data from PD patients (n = 61) and healthy controls (HC) (n = 47). Significant group differences in HRF (P < 0.05, Gaussian random field-corrected) were observed in several regions previously associated with PD. Subsequently, we focused on putamen-seed-based FC differences between the PD and HC groups using fMRI and latent neural signals. The results suggested that neglecting HRF variability may cultivate false-positive and false-negative FC group differences. Furthermore, HRF was related to dopamine receptor type 2 (DRD2) gene expression (P < 0.001, t = -7.06, false discover rate-corrected). Taken together, these findings reveal HRF variation and its possible underlying molecular mechanism in PD, and suggest that deconvolution could reduce the impact of HRF variation on FC group differences.
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Affiliation(s)
- Da Zhang
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Qianyi Fu
- International Laboratory for Children's Medical Imaging Research, School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, Jiangsu, China
| | - Chen Xue
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Chaoyong Xiao
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China; Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yu Sun
- International Laboratory for Children's Medical Imaging Research, School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, Jiangsu, China; Research Centre for University of Birmingham and Southeast University, Southeast University, Nanjing, Jiangsu, China
| | - Weiguo Liu
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
| | - Xiao Hu
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China; Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, Jiangsu, China.
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16
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Duarte JV, Guerra C, Moreno C, Gomes L, Castelo-Branco M. Changes in hemodynamic response function components reveal specific changes in neurovascular coupling in type 2 diabetes. Front Physiol 2023; 13:1101470. [PMID: 36703928 PMCID: PMC9872943 DOI: 10.3389/fphys.2022.1101470] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Accepted: 12/12/2022] [Indexed: 01/11/2023] Open
Abstract
Type 2 Diabetes Mellitus (T2DM) is a metabolic disease that leads to multiple vascular complications with concomitant changes in human neurophysiology, which may lead to long-term cognitive impairment, and dementia. Early impairments of neurovascular coupling can be studied using event-related functional magnetic resonance imaging (fMRI) designs. Here, we aimed to characterize the changes in the hemodynamic response function (HRF) in T2DM to probe components from the initial dip to late undershoot. We investigated whether the HRF morphology is altered throughout the brain in T2DM, by extracting several parameters of the fMRI response profiles in 141 participants (64 patients with T2DM and 77 healthy controls) performing a visual motion discrimination task. Overall, the patients revealed significantly different HRFs, which extended to all brain regions, suggesting that this is a general phenomenon. The HRF in T2DM was found to be more sluggish, with a higher peak latency and lower peak amplitude, relative slope to peak, and area under the curve. It also showed a pronounced initial dip, suggesting that the initial avidity for oxygen is not compensated for, and an absent or less prominent but longer undershoot. Most HRF parameters showed a higher dispersion and variability in T2DM. In sum, we provide a definite demonstration of an impaired hemodynamic response function in the early stages of T2DM, following a previous suggestion of impaired neurovascular coupling. The quantitative demonstration of a significantly altered HRF morphology in separate response phases suggests an alteration of distinct physiological mechanisms related to neurovascular coupling, which should be considered in the future to potentially halt the deterioration of the brain function in T2DM.
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Affiliation(s)
- João Valente Duarte
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Institute for Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal,Faculty of Medicine, University of Coimbra, Coimbra, Portugal,Intelligent Systems Associate Laboratory (LASI), Coimbra, Portugal
| | - Catarina Guerra
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Institute for Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal
| | - Carolina Moreno
- Service of Endocrinology, Diabetes and Metabolism, Coimbra University Hospital, Coimbra, Portugal
| | - Leonor Gomes
- Service of Endocrinology, Diabetes and Metabolism, Coimbra University Hospital, Coimbra, Portugal
| | - Miguel Castelo-Branco
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Institute for Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal,Faculty of Medicine, University of Coimbra, Coimbra, Portugal,Intelligent Systems Associate Laboratory (LASI), Coimbra, Portugal,*Correspondence: Miguel Castelo-Branco,
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17
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Laurence A, Toffa DH, Peng K, Robert M, Bouthillier A, Nguyen DK, Leblond F. Multispectral intraoperative imaging for the detection of the hemodynamic response to interictal epileptiform discharges. Biomed Opt Express 2022; 13:6245-6257. [PMID: 36589558 PMCID: PMC9774841 DOI: 10.1364/boe.465699] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 10/03/2022] [Accepted: 10/27/2022] [Indexed: 06/17/2023]
Abstract
Interictal epileptiform discharges (IEDs) are brief neuronal discharges occurring between seizures in patients with epilepsy. The characterization of the hemodynamic response function (HRF) specific to IEDs could increase the accuracy of other functional imaging techniques to localize epileptiform activity, including functional near-infrared spectroscopy and functional magnetic resonance imaging. This study evaluated the possibility of using an intraoperative multispectral imaging system combined with electrocorticography (ECoG) to measure the average HRF associated with IEDs in eight patients. Inter-patient variability of the HRF is illustrated in terms of oxygenated hemoglobin peak latency, oxygenated hemoglobin increase/decrease following IEDs, and signal-to-noise ratio. A sub-region was identified using an unsupervised clustering algorithm in three patients that corresponded to the most active area identified by ECoG.
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Affiliation(s)
- Audrey Laurence
- Polytechnique Montreal, Department of Engineering Physics, Montréal, Canada
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal, Montréal, Canada
| | - Dènahin H. Toffa
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal, Montréal, Canada
- Centre Hospitalier de l’Université de Montréal, Division of Neurology, Montréal, Canada
| | - Ke Peng
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal, Montréal, Canada
| | - Manon Robert
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal, Montréal, Canada
| | - Alain Bouthillier
- Centre Hospitalier de l’Université de Montréal, Division of Neurosurgery, Montréal, Canada
| | - Dang K. Nguyen
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal, Montréal, Canada
- Centre Hospitalier de l’Université de Montréal, Division of Neurology, Montréal, Canada
| | - Frederic Leblond
- Polytechnique Montreal, Department of Engineering Physics, Montréal, Canada
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal, Montréal, Canada
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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] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 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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Kim SG. On the encoding of natural music in computational models and human brains. Front Neurosci 2022; 16:928841. [PMID: 36203808 PMCID: PMC9531138 DOI: 10.3389/fnins.2022.928841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 08/15/2022] [Indexed: 11/13/2022] Open
Abstract
This article discusses recent developments and advances in the neuroscience of music to understand the nature of musical emotion. In particular, it highlights how system identification techniques and computational models of music have advanced our understanding of how the human brain processes the textures and structures of music and how the processed information evokes emotions. Musical models relate physical properties of stimuli to internal representations called features, and predictive models relate features to neural or behavioral responses and test their predictions against independent unseen data. The new frameworks do not require orthogonalized stimuli in controlled experiments to establish reproducible knowledge, which has opened up a new wave of naturalistic neuroscience. The current review focuses on how this trend has transformed the domain of the neuroscience of music.
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Mann‐Krzisnik D, Mitsis GD. Extracting electrophysiological correlates of functional magnetic resonance imaging data using the canonical polyadic decomposition. Hum Brain Mapp 2022; 43:4045-4073. [PMID: 35567768 PMCID: PMC9374895 DOI: 10.1002/hbm.25902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Revised: 04/25/2022] [Accepted: 04/27/2022] [Indexed: 11/11/2022] Open
Abstract
The relation between electrophysiology and BOLD-fMRI requires further elucidation. One approach for studying this relation is to find time-frequency features from electrophysiology that explain the variance of BOLD time-series. Convolution of these features with a canonical hemodynamic response function (HRF) is often required to model neurovascular coupling mechanisms and thus account for time shifts between electrophysiological and BOLD-fMRI data. We propose a framework for extracting the spatial distribution of these time-frequency features while also estimating more flexible, region-specific HRFs. The core component of this method is the decomposition of a tensor containing impulse response functions using the Canonical Polyadic Decomposition. The outputs of this decomposition provide insight into the relation between electrophysiology and BOLD-fMRI and can be used to construct estimates of BOLD time-series. We demonstrated the performance of this method on simulated data while also examining the effects of simulated measurement noise and physiological confounds. Afterwards, we validated our method on publicly available task-based and resting-state EEG-fMRI data. We adjusted our method to accommodate the multisubject nature of these datasets, enabling the investigation of inter-subject variability with regards to EEG-to-BOLD neurovascular coupling mechanisms. We thus also demonstrate how EEG features for modelling the BOLD signal differ across subjects.
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Affiliation(s)
- Dylan Mann‐Krzisnik
- Graduate Program in Biological and Biomedical EngineeringMcGill UniversityMontréalQuebecCanada
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21
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Schilling KG, Li M, Rheault F, Ding Z, Anderson AW, Kang H, Landman BA, Gore JC. Anomalous and heterogeneous characteristics of the BOLD hemodynamic response function in white matter. Cereb Cortex Commun 2022; 3:tgac035. [PMID: 36196360 PMCID: PMC9519945 DOI: 10.1093/texcom/tgac035] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Revised: 08/09/2022] [Accepted: 08/12/2022] [Indexed: 01/12/2023] Open
Abstract
Detailed knowledge of the BOLD hemodynamic response function (HRF) is crucial for accurate analyses and interpretation of functional MRI data. Considerable efforts have been made to characterize the HRF in gray matter (GM), but much less attention has been paid to BOLD effects in white matter (WM). However, several recent reports have demonstrated reliable detection and analyses of WM BOLD signals both after stimulation and in a resting state. WM and GM differ in composition, energy requirements, and blood flow, so their neurovascular couplings also may well be different. We aimed to derive a comprehensive characterization of the HRF in WM across a population, including accurate measurements of its shape and its variation along and between WM pathways, using resting-state fMRI acquisitions. Our results show that the HRF is significantly different between WM and GM. Features of the HRF, such as a prominent initial dip, show strong relationships with features of the tissue microstructure derived from diffusion imaging, and these relationships differ between WM and GM, consistent with BOLD signal fluctuations reflecting different energy demands and neurovascular couplings in tissues of different composition and function. We also show that the HRF varies in shape significantly along WM pathways and is different between different WM pathways, suggesting the temporal evolution of BOLD signals after an event vary in different parts of the WM. These features of the HRF in WM are especially relevant for interpretation of the biophysical basis of BOLD effects in WM.
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Affiliation(s)
| | - Muwei Li
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, USA,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Francois Rheault
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37232, USA
| | - Zhaohua Ding
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, USA,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA,Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37232, USA
| | - Adam W Anderson
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, USA,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA,Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37232, USA
| | - Hakmook Kang
- Department of Biostatistics, Vanderbilt University, Nashville, TN 37232, USA
| | - Bennett A Landman
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, USA,Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37232, USA
| | - John C Gore
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, USA,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA,Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37232, USA
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22
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Taylor AJ, Kim JH, Ress D. Temporal stability of the hemodynamic response function across the majority of human cerebral cortex. Hum Brain Mapp 2022; 43:4924-4942. [PMID: 35965416 PMCID: PMC9582369 DOI: 10.1002/hbm.26047] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2021] [Revised: 07/13/2022] [Accepted: 07/25/2022] [Indexed: 12/23/2022] Open
Abstract
The hemodynamic response function (HRF) measured with functional magnetic resonance imaging is generated by vascular and metabolic responses evoked by brief (<4 s) stimuli. It is known that the human HRF varies across cortex, between subjects, with stimulus paradigms, and even between different measurements in the same cortical location. However, our results demonstrate that strong HRFs are remarkably repeatable across sessions separated by time intervals up to 3 months. In this study, a multisensory stimulus was used to activate and measure the HRF across the majority of cortex (>70%, with lesser reliability observed in some areas of prefrontal cortex). HRFs were measured with high spatial resolution (2‐mm voxels) in central gray matter to minimize variations caused by partial‐volume effects. HRF amplitudes and temporal dynamics were highly repeatable across four sessions in 20 subjects. Positive and negative HRFs were consistently observed across sessions and subjects. Negative HRFs were generally weaker and, thus, more variable than positive HRFs. Statistical measurements showed that across‐session variability is highly correlated to the variability across events within a session; these measurements also indicated a normal distribution of variability across cortex. The overall repeatability of the HRFs over long time scales generally supports the long‐term use of event‐related functional magnetic resonance imaging protocols.
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Affiliation(s)
- Amanda J Taylor
- Department of Neuroscience, Baylor College of Medicine, Houston, Texas, USA
| | - Jung Hwan Kim
- Department of Neuroscience, Baylor College of Medicine, Houston, Texas, USA
| | - David Ress
- Department of Neuroscience, Baylor College of Medicine, Houston, Texas, USA
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23
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Zhang WT, Chao THH, Yang Y, Wang TW, Lee SH, Oyarzabal EA, Zhou J, Nonneman R, Pegard NC, Zhu H, Cui G, Shih YYI. Spectral fiber photometry derives hemoglobin concentration changes for accurate measurement of fluorescent sensor activity. Cell Rep Methods 2022; 2:100243. [PMID: 35880016 PMCID: PMC9308135 DOI: 10.1016/j.crmeth.2022.100243] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 04/08/2022] [Accepted: 06/08/2022] [Indexed: 12/22/2022]
Abstract
Fiber photometry is an emerging technique for recording fluorescent sensor activity in the brain. However, significant hemoglobin absorption artifacts in fiber photometry data may be misinterpreted as sensor activity changes. Because hemoglobin exists widely in the brain, and its concentration varies temporally, such artifacts could impede the accuracy of photometry recordings. Here we present use of spectral photometry and computational methods to quantify photon absorption effects by using activity-independent fluorescence signals, which can be used to derive oxy- and deoxy-hemoglobin concentration changes. Although these changes are often temporally delayed compared with the fast-responding fluorescence spikes, we found that erroneous interpretation may occur when examining pharmacology-induced sustained changes and that sometimes hemoglobin absorption could flip the GCaMP signal polarity. We provide hemoglobin-based correction methods to restore fluorescence signals and compare our results with other commonly used approaches. We also demonstrated the utility of spectral fiber photometry for delineating regional differences in hemodynamic response functions.
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Affiliation(s)
- Wei-Ting Zhang
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Tzu-Hao Harry Chao
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Yue Yang
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Tzu-Wen Wang
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Sung-Ho Lee
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Esteban A. Oyarzabal
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jingheng Zhou
- In Vivo Neurobiology Group, Neurobiology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC 27709, USA
| | - Randy Nonneman
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Nicolas C. Pegard
- Department of Applied Physical Sciences, UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Hongtu Zhu
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Guohong Cui
- In Vivo Neurobiology Group, Neurobiology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC 27709, USA
| | - Yen-Yu Ian Shih
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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24
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Andrea B, Atiqah A, Gianluca E. Reproducible Inter-Personal Brain Coupling Measurements in Hyperscanning Settings With functional Near Infra-Red Spectroscopy. Neuroinformatics 2022; 20:665-675. [PMID: 34716564 DOI: 10.1007/s12021-021-09551-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/21/2021] [Indexed: 12/31/2022]
Abstract
Despite a huge advancement in neuroimaging techniques and growing importance of inter-personal brain research, few studies assess the most appropriate computational methods to measure brain-brain coupling. Here, we focus on the signal processing methods to detect brain-coupling in dyads. From a public dataset of functional Near Infra-Red Spectroscopy signals (N=24 dyads), we derived a synthetic control condition by randomization, we investigated the effectiveness of four most used signal similarity metrics: Cross Correlation, Mutual Information, Wavelet Coherence and Dynamic Time Warping. We also accounted for temporal variations between signals by allowing for misalignments up to a maximum lag. Starting from the observed effect sizes, computed in terms of Cohen's d, the power analysis indicated that a high sample size ([Formula: see text]) would be required to detect significant brain-coupling. We therefore discuss the need for specialized statistical approaches and propose bootstrap as an alternative method to avoid over-penalizing the results. In our settings, and based on bootstrap analyses, Cross Correlation and Dynamic Time Warping outperform Mutual Information and Wavelet Coherence for all considered maximum lags, with reproducible results. These results highlight the need to set specific guidelines as the high degree of customization of the signal processing procedures prevents the comparability between studies, their reproducibility and, ultimately, undermines the possibility of extracting new knowledge.
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Affiliation(s)
- Bizzego Andrea
- Department of Psychology and Cognitive Science, University of Trento, Trento, Italy
| | - Azhari Atiqah
- Psychology Program, School of Social Sciences, Nanyang Technological University, Singapore, Singapore
| | - Esposito Gianluca
- Department of Psychology and Cognitive Science, University of Trento, Trento, Italy. .,Psychology Program, School of Social Sciences, Nanyang Technological University, Singapore, Singapore. .,Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.
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25
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Wu GR, Colenbier N, Van Den Bossche S, Clauw K, Johri A, Tandon M, Marinazzo D. rsHRF: A toolbox for resting-state HRF estimation and deconvolution. Neuroimage 2021; 244:118591. [PMID: 34560269 DOI: 10.1016/j.neuroimage.2021.118591] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Revised: 06/25/2021] [Accepted: 09/16/2021] [Indexed: 10/20/2022] Open
Abstract
The hemodynamic response function (HRF) greatly influences the intra- and inter-subject variability of brain activation and connectivity, and might confound the estimation of temporal precedence in connectivity analyses, making its estimation necessary for a correct interpretation of neuroimaging studies. Additionally, the HRF shape itself is a useful local measure. However, most algorithms for HRF estimation are specific for task-related fMRI data, and only a few can be directly applied to resting-state protocols. Here we introduce rsHRF, a Matlab and Python toolbox that implements HRF estimation and deconvolution from the resting-state BOLD signal. We first provide an overview of the main algorithm, practical implementations, and then demonstrate the feasibility and usefulness of rsHRF by validation experiments with a publicly available resting-state fMRI dataset. We also provide tools for statistical analyses and visualization. We believe that this toolbox may significantly contribute to a better analysis and understanding of the components and variability of BOLD signals.
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Affiliation(s)
- Guo-Rong Wu
- Key Laboratory of Cognition and Personality, Faculty of Psychology, Southwest University, Chongqing 400715, China; Department of Data Analysis, Faculty of Psychology and Educational Sciences, Ghent University, Ghent 9000, Belgium.
| | - Nigel Colenbier
- Department of Data Analysis, Faculty of Psychology and Educational Sciences, Ghent University, Ghent 9000, Belgium; Research Center for Motor Control and Neuroplasticity, KU Leuven, Leuven 3001, Belgium; Brain Imaging and Neural Dynamics Research Group, IRCCS San Camillo Hospital, Venice 30126, Italy
| | - Sofie Van Den Bossche
- Department of Data Analysis, Faculty of Psychology and Educational Sciences, Ghent University, Ghent 9000, Belgium
| | - Kenzo Clauw
- Department of Data Analysis, Faculty of Psychology and Educational Sciences, Ghent University, Ghent 9000, Belgium
| | - Amogh Johri
- International Institute of Information Technology, Bangalore 560100, India
| | - Madhur Tandon
- Indraprastha Institute of Information Technology, Delhi 110020, India
| | - Daniele Marinazzo
- Department of Data Analysis, Faculty of Psychology and Educational Sciences, Ghent University, Ghent 9000, Belgium; Brain Imaging and Neural Dynamics Research Group, IRCCS San Camillo Hospital, Venice 30126, Italy
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26
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Chen JE, Glover GH, Fultz NE, Rosen BR, Polimeni JR, Lewis LD. Investigating mechanisms of fast BOLD responses: The effects of stimulus intensity and of spatial heterogeneity of hemodynamics. Neuroimage 2021; 245:118658. [PMID: 34656783 DOI: 10.1016/j.neuroimage.2021.118658] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2021] [Revised: 09/18/2021] [Accepted: 10/12/2021] [Indexed: 12/17/2022] Open
Abstract
Recent studies have demonstrated that fast fMRI can track neural activity well above the temporal limit predicted by the canonical hemodynamic response model. While these findings are promising, the biophysical mechanisms underlying these fast fMRI phenomena remain underexplored. In this study, we discuss two aspects of the hemodynamic response, complementary to several existing hypotheses, that can accommodate faster fMRI dynamics beyond those predicted by the canonical model. First, we demonstrate, using both visual and somatosensory paradigms, that the timing and shape of hemodynamic response functions (HRFs) vary across graded levels of stimulus intensity-with lower-intensity stimulation eliciting faster and narrower HRFs. Second, we show that as the spatial resolution of fMRI increases, voxel-wise HRFs begin to deviate from the canonical model, with a considerable portion of voxels exhibiting faster temporal dynamics than predicted by the canonical HRF. Collectively, both stimulus/task intensity and image resolution can affect the sensitivity of fMRI to fast brain activity, which may partly explain recent observations of fast fMRI signals. It is further noteworthy that, while the present investigations focus on fast neural responses, our findings suggest that a revised hemodynamic model may benefit the many fMRI studies using paradigms with wide ranges of contrast levels (e.g., resting or naturalistic conditions) or with modern, high-resolution MR acquisitions.
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27
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Arora Y, Walia P, Hayashibe M, Muthalib M, Chowdhury SR, Perrey S, Dutta A. Grey-box modeling and hypothesis testing of functional near-infrared spectroscopy-based cerebrovascular reactivity to anodal high-definition tDCS in healthy humans. PLoS Comput Biol 2021; 17:e1009386. [PMID: 34613970 DOI: 10.1371/journal.pcbi.1009386] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Accepted: 08/28/2021] [Indexed: 12/12/2022] Open
Abstract
Transcranial direct current stimulation (tDCS) has been shown to evoke hemodynamics response; however, the mechanisms have not been investigated systematically using systems biology approaches. Our study presents a grey-box linear model that was developed from a physiologically detailed multi-compartmental neurovascular unit model consisting of the vascular smooth muscle, perivascular space, synaptic space, and astrocyte glial cell. Then, model linearization was performed on the physiologically detailed nonlinear model to find appropriate complexity (Akaike information criterion) to fit functional near-infrared spectroscopy (fNIRS) based measure of blood volume changes, called cerebrovascular reactivity (CVR), to high-definition (HD) tDCS. The grey-box linear model was applied on the fNIRS-based CVR during the first 150 seconds of anodal HD-tDCS in eleven healthy humans. The grey-box linear models for each of the four nested pathways starting from tDCS scalp current density that perturbed synaptic potassium released from active neurons for Pathway 1, astrocytic transmembrane current for Pathway 2, perivascular potassium concentration for Pathway 3, and voltage-gated ion channel current on the smooth muscle cell for Pathway 4 were fitted to the total hemoglobin concentration (tHb) changes from optodes in the vicinity of 4x1 HD-tDCS electrodes as well as on the contralateral sensorimotor cortex. We found that the tDCS perturbation Pathway 3 presented the least mean square error (MSE, median <2.5%) and the lowest Akaike information criterion (AIC, median -1.726) from the individual grey-box linear model fitting at the targeted-region. Then, minimal realization transfer function with reduced-order approximations of the grey-box model pathways was fitted to the ensemble average tHb time series. Again, Pathway 3 with nine poles and two zeros (all free parameters), provided the best Goodness of Fit of 0.0078 for Chi-Square difference test of nested pathways. Therefore, our study provided a systems biology approach to investigate the initial transient hemodynamic response to tDCS based on fNIRS tHb data. Future studies need to investigate the steady-state responses, including steady-state oscillations found to be driven by calcium dynamics, where transcranial alternating current stimulation may provide frequency-dependent physiological entrainment for system identification. We postulate that such a mechanistic understanding from system identification of the hemodynamics response to transcranial electrical stimulation can facilitate adequate delivery of the current density to the neurovascular tissue under simultaneous portable imaging in various cerebrovascular diseases.
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28
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Dowdle LT, Ghose G, Chen CCC, Ugurbil K, Yacoub E, Vizioli L. Statistical power or more precise insights into neuro-temporal dynamics? Assessing the benefits of rapid temporal sampling in fMRI. Prog Neurobiol 2021; 207:102171. [PMID: 34492308 DOI: 10.1016/j.pneurobio.2021.102171] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Revised: 08/09/2021] [Accepted: 09/02/2021] [Indexed: 01/25/2023]
Abstract
Functional magnetic resonance imaging (fMRI), a non-invasive and widely used human neuroimaging method, is most known for its spatial precision. However, there is a growing interest in its temporal sensitivity. This is despite the temporal blurring of neuronal events by the blood oxygen level dependent (BOLD) signal, the peak of which lags neuronal firing by 4-6 seconds. Given this, the goal of this review is to answer a seemingly simple question - "What are the benefits of increased temporal sampling for fMRI?". To answer this, we have combined fMRI data collected at multiple temporal scales, from 323 to 1000 milliseconds, with a review of both historical and contemporary temporal literature. After a brief discussion of technological developments that have rekindled interest in temporal research, we next consider the potential statistical and methodological benefits. Most importantly, we explore how fast fMRI can uncover previously unobserved neuro-temporal dynamics - effects that are entirely missed when sampling at conventional 1 to 2 second rates. With the intrinsic link between space and time in fMRI, this temporal renaissance also delivers improvements in spatial precision. Far from producing only statistical gains, the array of benefits suggest that the continued temporal work is worth the effort.
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Affiliation(s)
- Logan T Dowdle
- Center for Magnetic Resonance Research, University of Minnesota, 2021 6th St SE, Minneapolis, MN, 55455, United States; Department of Neurosurgery, University of Minnesota, 500 SE Harvard St, Minneapolis, MN, 55455, United States; Department of Neuroscience, University of Minnesota, 321 Church St SE, Minneapolis, MN, 55455, United States.
| | - Geoffrey Ghose
- Center for Magnetic Resonance Research, University of Minnesota, 2021 6th St SE, Minneapolis, MN, 55455, United States; Department of Neuroscience, University of Minnesota, 321 Church St SE, Minneapolis, MN, 55455, United States
| | - Clark C C Chen
- Department of Neurosurgery, University of Minnesota, 500 SE Harvard St, Minneapolis, MN, 55455, United States
| | - Kamil Ugurbil
- Center for Magnetic Resonance Research, University of Minnesota, 2021 6th St SE, Minneapolis, MN, 55455, United States
| | - Essa Yacoub
- Center for Magnetic Resonance Research, University of Minnesota, 2021 6th St SE, Minneapolis, MN, 55455, United States
| | - Luca Vizioli
- Center for Magnetic Resonance Research, University of Minnesota, 2021 6th St SE, Minneapolis, MN, 55455, United States; Department of Neurosurgery, University of Minnesota, 500 SE Harvard St, Minneapolis, MN, 55455, United States.
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29
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Rangaprakash D, Tadayonnejad R, Deshpande G, O'Neill J, Feusner JD. FMRI hemodynamic response function (HRF) as a novel marker of brain function: applications for understanding obsessive-compulsive disorder pathology and treatment response. Brain Imaging Behav 2021; 15:1622-1640. [PMID: 32761566 DOI: 10.1007/s11682-020-00358-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The hemodynamic response function (HRF) represents the transfer function linking neural activity with the functional MRI (fMRI) signal, modeling neurovascular coupling. Since HRF is influenced by non-neural factors, to date it has largely been considered as a confound or has been ignored in many analyses. However, underlying biophysics suggests that the HRF may contain meaningful correlates of neural activity, which might be unavailable through conventional fMRI metrics. Here, we estimated the HRF by performing deconvolution on resting-state fMRI data from a longitudinal sample of 25 healthy controls scanned twice and 44 adults with obsessive-compulsive disorder (OCD) before and after 4-weeks of intensive cognitive-behavioral therapy (CBT). HRF response height, time-to-peak and full-width at half-maximum (FWHM) in OCD were abnormal before treatment and normalized after treatment in regions including the caudate. Pre-treatment HRF predicted treatment outcome (OCD symptom reduction) with 86.4% accuracy, using machine learning. Pre-treatment HRF response height in the caudate head and time-to-peak in the caudate tail were top-predictors of treatment response. Time-to-peak in the caudate tail, a region not typically identified in OCD studies using conventional fMRI activation or connectivity measures, may carry novel importance. Additionally, pre-treatment response height in caudate head predicted post-treatment OCD severity (R = -0.48, P = 0.001), and was associated with treatment-related OCD severity changes (R = -0.44, P = 0.0028), underscoring its relevance. With HRF being a reliable marker sensitive to brain function, OCD pathology, and intervention-related changes, these results could guide future studies towards novel discoveries not possible through conventional fMRI approaches like standard BOLD activation or connectivity.
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Affiliation(s)
- D Rangaprakash
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, 90095, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School and Harvard-MIT Health Sciences and Technology, Cambridge, MA, 02129, USA
| | - Reza Tadayonnejad
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, 90095, USA.,Division of the Humanities and Social Sciences, California Institute of Technology, Pasadena, CA, 91125, USA
| | - Gopikrishna Deshpande
- AU MRI Research Center, Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, 36849, USA.,Department of Psychological Sciences, Auburn University, Auburn, AL, 36849, USA.,Alabama Advanced Imaging Consortium, Auburn University and University of Alabama Birmingham, Auburn, AL, USA.,Center for Health Ecology and Equity Research, Auburn University, Auburn, AL, USA.,Center for Neuroscience, Auburn University, Auburn, AL, USA.,School of Psychology, Capital Normal University, Beijing, China.,Key Laboratory for Learning and Cognition, Capital Normal University, Beijing, China.,Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Joseph O'Neill
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Jamie D Feusner
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, 90095, USA.
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30
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de la Rosa N, Ress D, Taylor AJ, Kim JH. Retinotopic variations of the negative blood-oxygen-level dependent hemodynamic response function in human primary visual cortex. J Neurophysiol 2021; 125:1045-1057. [PMID: 33625949 DOI: 10.1152/jn.00676.2020] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Functional magnetic resonance imaging (fMRI) measures blood-oxygen-level-dependent (BOLD) contrast that is generally assumed to be linearly related to excitatory neural activity. The positive hemodynamic response function (pHRF) is the positive BOLD response (PBR) evoked by a brief neural stimulation; the pHRF is often used as the impulse response for linear analysis of neural excitation. Many fMRI studies have observed a negative BOLD response (NBR) that is often associated with neural suppression. However, the temporal dynamics of the NBR evoked by a brief stimulus, the negative HRF (nHRF), remains unclear. Here, a unilateral visual stimulus was presented in a slow event-related design to elicit both pHRFs in the stimulus representation (SR), and nHRFs elsewhere. The observed nHRFs were not inverted versions of the pHRF previously reported. They were characterized by a stronger initial negative response followed by a significantly later positive peak. In contralateral primary visual cortex (V1), these differences varied with eccentricity from the SR. Similar nHRFs were observed in ipsilateral V1 with less eccentricity variation. Experiments with the blocked version of the same stimulus confirmed that brain regions presenting the unexpected nHRF dynamics correspond to those presenting a strong NBR. These data demonstrated that shift-invariant temporal linearity did not hold for the NBR while confirming that the PBR maintained rough linearity. Modeling indicated that the observed nHRFs can be created by suppression of both blood flow and oxygen metabolism. Critically, the nHRF can be misinterpreted as a pHRF due to their similarity, which could confound linear analysis for event-related fMRI experiments.NEW & NOTEWORTHY We investigate dynamics of the negative hemodynamic response function (nHRF), the negative blood-oxygen-level-dependent (BOLD) response (NBR) evoked by a brief stimulus, in human early visual cortex. Here, we show that the nHRFs are not inverted versions of the corresponding pHRFs. The nHRF has complex dynamics that varied significantly with eccentricity. The results also show shift-invariant temporal linearity does not hold for the NBR.
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31
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Dowdle LT, Ghose G, Ugurbil K, Yacoub E, Vizioli L. Clarifying the role of higher-level cortices in resolving perceptual ambiguity using ultra high field fMRI. Neuroimage 2021; 227:117654. [PMID: 33333319 PMCID: PMC10614695 DOI: 10.1016/j.neuroimage.2020.117654] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Revised: 11/17/2020] [Accepted: 12/05/2020] [Indexed: 12/17/2022] Open
Abstract
The brain is organized into distinct, flexible networks. Within these networks, cognitive variables such as attention can modulate sensory representations in accordance with moment-to-moment behavioral requirements. These modulations can be studied by varying task demands; however, the tasks employed are often incongruent with the postulated functions of a sensory system, limiting the characterization of the system in relation to natural behaviors. Here we combine domain-specific task manipulations and ultra-high field fMRI to study the nature of top-down modulations. We exploited faces, a visual category underpinned by a complex cortical network, and instructed participants to perform either a stimulus-relevant/domain-specific or a stimulus-irrelevant task in the scanner. We found that 1. perceptual ambiguity (i.e. difficulty of achieving a stable percept) is encoded in top-down modulations from higher-level cortices; 2. the right inferior-temporal lobe is active under challenging conditions and uniquely encodes trial-by-trial variability in face perception.
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Affiliation(s)
- Logan T Dowdle
- Center for Magnetic Resonance Research, University of Minnesota 2021 6th St SE, Minneapolis, MN 55455, United States; Department of Neuroscience, University of Minnesota, 321 Church St SE, Minneapolis, MN 55455.
| | - Geoffrey Ghose
- Center for Magnetic Resonance Research, University of Minnesota 2021 6th St SE, Minneapolis, MN 55455, United States; Department of Neuroscience, University of Minnesota, 321 Church St SE, Minneapolis, MN 55455
| | - Kamil Ugurbil
- Center for Magnetic Resonance Research, University of Minnesota 2021 6th St SE, Minneapolis, MN 55455, United States
| | - Essa Yacoub
- Center for Magnetic Resonance Research, University of Minnesota 2021 6th St SE, Minneapolis, MN 55455, United States
| | - Luca Vizioli
- Center for Magnetic Resonance Research, University of Minnesota 2021 6th St SE, Minneapolis, MN 55455, United States; Department of Neurosurgery, University of Minnesota, 500 SE Harvard St, Minneapolis, MN 55455.
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32
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Abstract
Accurate identification of brain function is necessary to understand the neurobiology of cognitive ageing, and thereby promote well-being across the lifespan. A common tool used to investigate neurocognitive ageing is functional magnetic resonance imaging (fMRI). However, although fMRI data are often interpreted in terms of neuronal activity, the blood oxygenation level-dependent (BOLD) signal measured by fMRI includes contributions of both vascular and neuronal factors, which change differentially with age. While some studies investigate vascular ageing factors, the results of these studies are not well known within the field of neurocognitive ageing and therefore vascular confounds in neurocognitive fMRI studies are common. Despite over 10 000 BOLD-fMRI papers on ageing, fewer than 20 have applied techniques to correct for vascular effects. However, neurovascular ageing is not only a confound in fMRI, but an important feature in its own right, to be assessed alongside measures of neuronal ageing. We review current approaches to dissociate neuronal and vascular components of BOLD-fMRI of regional activity and functional connectivity. We highlight emerging evidence that vascular mechanisms in the brain do not simply control blood flow to support the metabolic needs of neurons, but form complex neurovascular interactions that influence neuronal function in health and disease. This article is part of the theme issue 'Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity'.
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Affiliation(s)
- Kamen A. Tsvetanov
- Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0SZ, UK
- Department of Psychology, University of Cambridge, Cambridge CB2 3EB, UK
| | - Richard N. A. Henson
- Department of Psychiatry, University of Cambridge, Cambridge CB2 0SP, UK
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, UK
| | - James B. Rowe
- Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0SZ, UK
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, UK
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33
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Abstract
The global mean signal of resting-state fMRI (rs-fMRI) shows a characteristic spatiotemporal pattern that is closely related to the pattern of vascular perfusion. Although being increasingly adopted in the mapping of the flow of neural activity, the mechanism that gives rise to the BOLD signal time lag remains controversial. In the present study, we compared the time lag of the global mean signal with those of the local network components obtained by applying temporal independent component analysis to the resting-state fMRI data, as well as by using simultaneous wide-field visual stimulation, and demonstrated that the time lag patterns are highly similar across all types of data. These results suggest that the time lag of the rs-fMRI signal reflects the local variance of the hemodynamic responses rather than the arrival or transit time of the stimulus, whether the trigger is neuronal or non-neuronal in origin as long as it is mediated by local hemodynamic responses. Examinations of the internal carotid artery signal further confirmed that the arterial signal is tightly inversely coupled with the global mean signal in accordance with previous studies, presumably reflecting the blood flow or blood pressure changes that are occurring almost simultaneously in the internal carotid artery and the cerebral pial/capillary arteries, within the low-frequency component in human rs-fMRI.
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Affiliation(s)
- Shiori Amemiya
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Hidemasa Takao
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Osamu Abe
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
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34
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Wang L, Li C, Chen D, Lv X, Go R, Wu J, Yan T. Hemodynamic response varies across tactile stimuli with different temporal structures. Hum Brain Mapp 2020; 42:587-597. [PMID: 33169898 PMCID: PMC7814760 DOI: 10.1002/hbm.25243] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Revised: 10/01/2020] [Accepted: 10/03/2020] [Indexed: 11/23/2022] Open
Abstract
Tactile stimuli can be distinguished based on their temporal features (e.g., duration, local frequency, and number of pulses), which are fundamental for vibrotactile frequency perception. Characterizing how the hemodynamic response changes in shape across experimental conditions is important for designing and interpreting fMRI studies on tactile information processing. In this study, we focused on periodic tactile stimuli with different temporal structures and explored the hemodynamic response function (HRF) induced by these stimuli. We found that HRFs were stimulus‐dependent in tactile‐related brain areas. Continuous stimuli induced a greater area of activation and a stronger and narrower hemodynamic response than intermittent stimuli with the same duration. The magnitude of the HRF increased with increasing stimulus duration. By normalizing the characteristics into topographic matrix, nonlinearity was obvious. These results suggested that stimulation patterns and duration within a cycle may be key characters for distinguishing different stimuli. We conclude that different temporal structures of tactile stimuli induced different HRFs, which are essential for vibrotactile perception and should be considered in fMRI experimental designs and analyses.
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Affiliation(s)
- Luyao Wang
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China.,Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing, China
| | - Chunlin Li
- School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Duanduan Chen
- School of Life Science, Beijing Institute of Technology, Beijing, China
| | - Xiaoyu Lv
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China.,Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing, China
| | - Ritsu Go
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China.,Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing, China
| | - Jinglong Wu
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China.,Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing, China.,Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, Okayama, Japan
| | - Tianyi Yan
- School of Life Science, Beijing Institute of Technology, Beijing, China.,Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing, China
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35
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Sekeres MJ, Moscovitch M, Winocur G, Pishdadian S, Nichol D, Grady CL. Reminders activate the prefrontal-medial temporal cortex and attenuate forgetting of event memory. Hippocampus 2020; 31:28-45. [PMID: 32965760 DOI: 10.1002/hipo.23260] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Revised: 08/06/2020] [Accepted: 08/21/2020] [Indexed: 01/03/2023]
Abstract
Replicas of an aspect of an experienced event can serve as effective reminders, yet little is known about the neural basis of such reminding effects. Here we examined the neural activity underlying the memory-enhancing effect of reminders 1 week after encoding of naturalistic film clip events. We used fMRI to determine differences in network activity associated with recently reactivated memories relative to comparably aged, non-reactivated memories. Reminders were effective in facilitating overall retrieval of memory for film clips, in an all-or-none fashion. Prefrontal cortex and hippocampus were activated during both reminders and retrieval. Peak activation in ventro-lateral prefrontal cortex (vPFC) preceded peak activation in the right hippocampus during the reminders. For film clips that were successfully retrieved after 7 days, pre-retrieval reminders did not enhance the quality of the retrieved memory or the number of details retrieved, nor did they more strongly engage regions of the recollection network than did successful retrieval of a non-reminded film clip. These results suggest that reminders prior to retrieval are an effective means of boosting retrieval of otherwise inaccessible episodic events, and that the inability to recall certain events after a delay of a week largely reflects a retrieval deficit, rather than a storage deficit for this information. The results extend other evidence that vPFC drives activation of the hippocampus to facilitate memory retrieval and scene construction, and show that this facilitation also occurs when reminder cues precede successful retrieval attempts. The time course of vPFC-hippocampal activity during the reminder suggests that reminders may first engage schematic information meditated by vPFC followed by a recollection process mediated by the hippocampus.
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Affiliation(s)
- Melanie J Sekeres
- School of Psychology, University of Ottawa, Ottawa, Ontario, Canada.,Rotman Research Institute, Baycrest, Toronto, Ontario, Canada
| | - Morris Moscovitch
- Rotman Research Institute, Baycrest, Toronto, Ontario, Canada.,Department of Psychology, Baycrest, Toronto, Ontario, Canada.,Department of Psychology, University of Toronto, Toronto, Ontario, Canada
| | - Gordon Winocur
- Rotman Research Institute, Baycrest, Toronto, Ontario, Canada.,Department of Psychology, University of Toronto, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.,Department of Psychology, Trent University, Peterborough, Ontario, Canada
| | - Sara Pishdadian
- Rotman Research Institute, Baycrest, Toronto, Ontario, Canada.,Department of Psychology, York University, Toronto, Ontario, Canada
| | - Dan Nichol
- Rotman Research Institute, Baycrest, Toronto, Ontario, Canada
| | - Cheryl L Grady
- Rotman Research Institute, Baycrest, Toronto, Ontario, Canada.,Department of Psychology, University of Toronto, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
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36
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Kay K, Jamison KW, Zhang RY, Uğurbil K. A temporal decomposition method for identifying venous effects in task-based fMRI. Nat Methods 2020; 17:1033-1039. [PMID: 32895538 DOI: 10.1038/s41592-020-0941-6] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2019] [Accepted: 08/03/2020] [Indexed: 11/09/2022]
Abstract
The spatial resolution of functional magnetic resonance imaging (fMRI) is fundamentally limited by effects from large draining veins. Here we describe an analysis method that provides data-driven estimates of these effects in task-based fMRI. The method involves fitting a one-dimensional manifold that characterizes variation in response timecourses observed in a given dataset, and then using identified early and late timecourses as basis functions for decomposing responses into components related to the microvasculature (capillaries and small venules) and the macrovasculature (large veins), respectively. We show the removal of late components substantially reduces the superficial cortical depth bias of fMRI responses and helps eliminate artifacts in cortical activity maps. This method provides insight into the origins of the fMRI signal and can be used to improve the spatial accuracy of fMRI.
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Affiliation(s)
- Kendrick Kay
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA.
| | - Keith W Jamison
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA.,Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Ru-Yuan Zhang
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA.,Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Institute of Psychology and Behavioral Science, Shanghai Jiao Tong University, Shanghai, China
| | - Kamil Uğurbil
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
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37
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Abstract
The blood oxygen-level dependent (BOLD) functional magnetic resonance imaging (fMRI) signal depends on an interplay of cerebral blood flow (CBF), oxygen metabolism, and cerebral blood volume. Despite wide usage of BOLD fMRI, it is not clear how these physiological components create the BOLD signal. Here, baseline CBF and its dynamics evoked by a brief stimulus (2 s) in human visual cortex were measured at 3T. We found a stereotypical CBF response: immediate increase, rising to a peak a few second after the stimulus, followed by a significant undershoot. The BOLD hemodynamic response function (HRF) was also measured in the same session. Strong correlations between HRF and CBF peak responses indicate that the flow responses evoked by neural activation in nearby gray matter drive the early HRF. Remarkably, peak CBF and HRF were also strongly modulated by baseline perfusion. The CBF undershoot was reliable and significantly correlated with the HRF undershoot. However, late-time dynamics of the HRF and CBF suggest that oxygen metabolism can also contribute to the HRF undershoot. Combined measurement of the CBF and HRF for brief neural activation is a useful tool to understand the temporal dynamics of neurovascular and neurometabolic coupling.
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Affiliation(s)
- Jung Hwan Kim
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - Amanda J Taylor
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - Danny JJ Wang
- Laboratory of FMRI Technology (LOFT), Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Xiaowei Zou
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - David Ress
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
- David Ress, Baylor College of Medicine, 1 Baylor Plaza T115E, Houston, TX 77030, USA.
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38
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Diachek E, Blank I, Siegelman M, Affourtit J, Fedorenko E. The Domain-General Multiple Demand (MD) Network Does Not Support Core Aspects of Language Comprehension: A Large-Scale fMRI Investigation. J Neurosci 2020; 40:4536-4550. [PMID: 32317387 PMCID: PMC7275862 DOI: 10.1523/jneurosci.2036-19.2020] [Citation(s) in RCA: 63] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Revised: 03/02/2020] [Accepted: 04/05/2020] [Indexed: 11/21/2022] Open
Abstract
Aside from the language-selective left-lateralized frontotemporal network, language comprehension sometimes recruits a domain-general bilateral frontoparietal network implicated in executive functions: the multiple demand (MD) network. However, the nature of the MD network's contributions to language comprehension remains debated. To illuminate the role of this network in language processing in humans, we conducted a large-scale fMRI investigation using data from 30 diverse word and sentence comprehension experiments (481 unique participants [female and male], 678 scanning sessions). In line with prior findings, the MD network was active during many language tasks. Moreover, similar to the language-selective network, which is robustly lateralized to the left hemisphere, these responses were stronger in the left-hemisphere MD regions. However, in contrast with the language-selective network, the MD network responded more strongly (1) to lists of unconnected words than to sentences, and (2) in paradigms with an explicit task compared with passive comprehension paradigms. Indeed, many passive comprehension tasks failed to elicit a response above the fixation baseline in the MD network, in contrast to strong responses in the language-selective network. Together, these results argue against a role for the MD network in core aspects of sentence comprehension, such as inhibiting irrelevant meanings or parses, keeping intermediate representations active in working memory, or predicting upcoming words or structures. These results align with recent evidence of relatively poor tracking of the linguistic signal by the MD regions during naturalistic comprehension, and instead suggest that the MD network's engagement during language processing reflects effort associated with extraneous task demands.SIGNIFICANCE STATEMENT Domain-general executive processes, such as working memory and cognitive control, have long been implicated in language comprehension, including in neuroimaging studies that have reported activation in domain-general multiple demand (MD) regions for linguistic manipulations. However, much prior evidence has come from paradigms where language interpretation is accompanied by extraneous tasks. Using a large fMRI dataset (30 experiments/481 participants/678 sessions), we demonstrate that MD regions are engaged during language comprehension in the presence of task demands, but not during passive reading/listening, conditions that strongly activate the frontotemporal language network. These results present a fundamental challenge to proposals whereby linguistic computations, such as inhibiting irrelevant meanings, keeping representations active in working memory, or predicting upcoming elements, draw on domain-general executive resources.
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Affiliation(s)
- Evgeniia Diachek
- Department of Psychology, Vanderbilt University, Nashville, Tennessee 37203
| | - Idan Blank
- Department of Psychology, University of California at Los Angeles, Los Angeles, California 90095
| | - Matthew Siegelman
- Department of Psychology, Columbia University, New York, New York 10027
| | - Josef Affourtit
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
| | - Evelina Fedorenko
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, Massachusetts 02129
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39
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Lambers H, Segeroth M, Albers F, Wachsmuth L, van Alst TM, Faber C. A cortical rat hemodynamic response function for improved detection of BOLD activation under common experimental conditions. Neuroimage 2019; 208:116446. [PMID: 31846759 DOI: 10.1016/j.neuroimage.2019.116446] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 11/13/2019] [Accepted: 12/05/2019] [Indexed: 01/23/2023] Open
Abstract
For a reliable estimation of neuronal activation based on BOLD fMRI measurements an accurate model of the hemodynamic response is essential. Since a large part of basic neuroscience research is based on small animal data, it is necessary to characterize a hemodynamic response function (HRF) which is optimized for small animals. Therefore, we have determined and investigated the HRFs of rats obtained under a variety of experimental conditions in the primary somatosensory cortex. Measurements were performed on animals of different sex and strain, under different anesthetics, with and without ventilation and using different stimulation modalities. All modalities of stimulation used in this study induced neuronal activity in the primary somatosensory cortex or in subcortical regions. Since the HRFs of the BOLD responses in the primary somatosensory cortex showed a close concordance for the different conditions, we were able to determine a cortical rat HRF. This HRF is based on 143 BOLD measurements of 76 rats and can be used for statistical parametric mapping. It showed substantially faster progression than the human HRF, with a maximum after 2.8 ± 0.8 s, and a following undershoot after 6.1 ± 3.7 s. If the rat HRF was used statistical analysis of rat data showed a significantly improved detection performance in the somatosensory cortex in comparison to the commonly used HRF based on measurements in humans.
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Affiliation(s)
- Henriette Lambers
- Translational Research Imaging Center (TRIC), Department of Clinical Radiology, University Hospital Münster, Albert-Schweitzer-Campus 1, Münster, D-48149, Germany
| | - Martin Segeroth
- Translational Research Imaging Center (TRIC), Department of Clinical Radiology, University Hospital Münster, Albert-Schweitzer-Campus 1, Münster, D-48149, Germany
| | - Franziska Albers
- Translational Research Imaging Center (TRIC), Department of Clinical Radiology, University Hospital Münster, Albert-Schweitzer-Campus 1, Münster, D-48149, Germany
| | - Lydia Wachsmuth
- Translational Research Imaging Center (TRIC), Department of Clinical Radiology, University Hospital Münster, Albert-Schweitzer-Campus 1, Münster, D-48149, Germany
| | - Timo Mauritz van Alst
- Translational Research Imaging Center (TRIC), Department of Clinical Radiology, University Hospital Münster, Albert-Schweitzer-Campus 1, Münster, D-48149, Germany
| | - Cornelius Faber
- Translational Research Imaging Center (TRIC), Department of Clinical Radiology, University Hospital Münster, Albert-Schweitzer-Campus 1, Münster, D-48149, Germany.
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40
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Oh H, Kim JH, Yau JM. EPI distortion correction for concurrent human brain stimulation and imaging at 3T. J Neurosci Methods 2019; 327:108400. [PMID: 31434000 DOI: 10.1016/j.jneumeth.2019.108400] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Revised: 08/15/2019] [Accepted: 08/17/2019] [Indexed: 01/21/2023]
Abstract
BACKGROUND Transcranial magnetic stimulation (TMS) can be paired with functional magnetic resonance imaging (fMRI) in concurrent TMS-fMRI experiments. These multimodal experiments enable causal probing of network architecture in the human brain which can complement alternative network mapping approaches. Critically, merely introducing the TMS coil into the scanner environment can sometimes produce substantial magnetic field inhomogeneities and spatial distortions which limit the utility of concurrent TMS-fMRI. METHOD AND RESULTS We assessed the efficacy of point spread function corrected echo planar imaging (PSF-EPI) in correcting for the field inhomogeneities associated with a TMS coil at 3 T. In phantom and brain scans, we quantitatively compared the coil-induced distortion artifacts measured in EPI scans with and without PSF correction. We found that the application of PSF corrections to the EPI data significantly improved signal-to-noise and reduced distortions. In phantom scans with the PSF-EPI sequence, we also characterized the temporal profile of dynamic artifacts associated with TMS delivery and found that image quality remained high as long as the TMS pulse preceded the RF excitation pulses by at least 50 ms. Lastly, we validated the PSF-EPI sequence in human brain scans involving TMS and motor behavior as well as resting state fMRI scans. CONCLUSIONS Our collective results demonstrate the potential benefits of PSF-EPI for concurrent TMS-fMRI when coil-related artifacts are a concern. The ability to collect high quality resting state fMRI data in the same session as the concurrent TMS-fMRI experiment offers a unique opportunity to interrogate network architecture in the human brain.
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41
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Taylor AJ, Kim JH, Singh V, Halfen EJ, Pfeuffer J, Ress D. More than BOLD: Dual-spin populations create functional contrast. Magn Reson Med 2019; 83:681-694. [PMID: 31423634 DOI: 10.1002/mrm.27941] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2018] [Revised: 07/16/2019] [Accepted: 07/21/2019] [Indexed: 11/06/2022]
Abstract
PURPOSE Functional MRI contrast has generally been associated with changes in transverse relaxivity caused by blood oxygen concentration, the so-called blood oxygen level dependent contrast. However, this interpretation of fMRI contrast has been called into question by several recent experiments at high spatial resolution. Experiments were conducted to examine contrast dependencies that cannot be explained only by differences in relaxivity in a single-spin population. METHODS Measurements of functional signal and contrast were obtained in human early visual cortex during a high-contrast visual stimulation over a large range of TEs and for several flip angles. Small voxels (1.5 mm) were used to restrict the measurements to cortical gray matter in early visual areas identified using retinotopic mapping procedures. RESULTS Measurements were consistent with models that include 2 spin populations. The dominant population has a relatively short transverse lifetime that is strongly modulated by activation. However, functional contrast is also affected by volume changes between this short-lived population and the longer-lived population. CONCLUSION Some of the previously observed "nonclassical" behaviors of functional contrast can be explained by these interacting dual-spin populations.
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Affiliation(s)
- Amanda J Taylor
- Department of Neuroscience, Baylor College of Medicine, Houston, Texas
| | - Jung H Kim
- Department of Neuroscience, Baylor College of Medicine, Houston, Texas
| | | | | | - Josef Pfeuffer
- Siemens Healthcare, Application Development, Erlangen, Germany
| | - David Ress
- Department of Neuroscience, Baylor College of Medicine, Houston, Texas
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42
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Abstract
Neural activity in the brain is usually coupled to increases in local cerebral blood flow, leading to the increase in oxygenation that generates the BOLD fMRI signal. Recent work has begun to elucidate the vascular and neural mechanisms underlying the BOLD signal. The dilatory response is distributed throughout the vascular network. Arteries actively dilate within a second following neural activity increases, while venous distensions are passive and have a time course that last tens of seconds. Vasodilation, and thus local blood flow, is controlled by the activity of both neurons and astrocytes via multiple different pathways. The relationship between sensory-driven neural activity and the vascular dynamics in sensory areas are well-captured with a linear convolution model. However, depending on the behavioral state or brain region, the coupling between neural activity and hemodynamic signals can be weak or even inverted.
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Affiliation(s)
- Patrick J Drew
- Departments of Engineering Science and Mechanics, Biomedical Engineering and Neurosurgery, Pennsylvania State University, University Park, PA 16802, United States.
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43
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Boillat Y, Zwaag W. Whole brain measurements of the positive BOLD response variability during a finger tapping task at 7 T show regional differences in its profiles. Magn Reson Med 2018; 81:2720-2727. [DOI: 10.1002/mrm.27566] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2018] [Revised: 09/18/2018] [Accepted: 09/21/2018] [Indexed: 11/08/2022]
Affiliation(s)
- Yohan Boillat
- Laboratory for Functional and Metabolic Imaging Ecole Polytechnique Fédérale de Lausanne Lausanne Switzerland
| | - Wietske Zwaag
- Biomedical Imaging Research Center Ecole Polytechnique Fédérale de Lausanne Lausanne Switzerland
- Spinoza Centre for Neuroimaging Amsterdam Netherlands
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