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Thomas T. Liu

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YNIMG Journal 2022 Journal Article

A geometric view of signal sensitivity metrics in multi-echo fMRI

  • Thomas T. Liu
  • Bochao Li
  • Brice Fernandez
  • Suchandrima Banerjee

In multi-echo fMRI (ME-fMRI), two metrics have been widely used to measure the performance of various acquisition and analysis approaches. These are temporal SNR (tSNR) and differential contrast-to-noise ratio (dCNR). A key step in ME-fMRI is the weighted combination of the data from multiple echoes, and prior work has examined the dependence of tSNR and dCNR on the choice of weights. However, most studies have focused on only one of these two metrics, and the relationship between the two metrics has not been examined. In this work, we present a geometric view that offers greater insight into the relation between the two metrics and their weight dependence. We identify three major regimes: (1) a tSNR robust regime in which tSNR is robust to the weight selection with most weight variants achieving close to optimal performance, whereas dCNR shows a pronounced dependence on the weights with most variants achieving suboptimal performance; (2) a dCNR robust regime in which dCNR is robust to the weight selection with most weight variants achieving close to optimal performance, while tSNR exhibits a strong dependence on the weights with most variants achieving significantly lower than optimal performance; and (3) a within-type robust regime in which both tSNR and dCNR achieve nearly optimal performance when the form of the weights are variants of their respective optimal weights and exhibit a moderate decrease in performance for other weight variants. Insight into the behavior observed in the different regimes is gained by considering spherical representations of the weight dependence of the components used to form each metric. For multi-echo acquisitions, dCNR is shown to be more directly related than tSNR to measures of CNR and signal-to-noise ratio (SNR) for task-based and resting-state fMRI scans, respectively.

YNIMG Journal 2019 Journal Article

APOE modifies the interaction of entorhinal cerebral blood flow and cortical thickness on memory function in cognitively normal older adults

  • Chelsea C. Hays
  • Zvinka Z. Zlatar
  • M.J. Meloy
  • Mark W. Bondi
  • Paul E. Gilbert
  • Thomas T. Liu
  • Jonathan L. Helm
  • Christina E. Wierenga

Objective The ε4 allele of the apolipoprotein E (APOE) gene increases risk for cognitive decline in normal and pathologic aging. However, precisely how APOE ε4 exerts its negative impact on cognition is poorly understood. The present study aimed to determine whether APOE genotype (ε4+ vs. ε4-) modifies the interaction of medial temporal lobe (MTL) resting cerebral blood flow (CBF) and brain structure (cortical thickness [CT], volume [Vo]) on verbal memory performance. Methods Multiple linear regression models were employed to investigate relationships between APOE genotype, arterial spin labeling MRI-measured CBF and FreeSurfer-based CT and Vo in four MTL regions of interest (left and right entorhinal cortex and hippocampus), and verbal memory performance among a sample of 117 cognitively normal older adults (41 ε4+, 76 ε4-) between the ages of 64 and 89 (mean age ​= ​73). Results Results indicated that APOE genotype modified the interaction of CBF and CT on memory in the left entorhinal cortex, such that the relationship between entorhinal CBF and memory was negative (lower CBF was associated with better memory) in non-carriers with higher entorhinal CT, positive (higher CBF was associated with better memory) in non-carriers with lower entorhinal CT, and negative (higher CBF was associated with worse memory) in ε4 carriers with lower entorhinal CT. Conclusions Findings suggest that older adult APOE ε4 carriers may experience vascular dysregulation and concomitant morphological alterations in the MTL that interact to negatively affect memory even in the absence overt clinical symptoms, providing potential insight into the mechanistic link between APOE ε4 and detriments in cognition. Moreover, findings suggest a distinct multimodal neural signature in ε4 carriers (higher CBF and lower CT in the entorhinal cortex) that could aid in the identification of candidates for future clinical trials aimed at preventing or slowing cognitive decline. Differential findings with respect to ε4 carriers and non-carriers are discussed in the context of neurovascular compensation.

YNIMG Journal 2019 Journal Article

Nuisance effects and the limitations of nuisance regression in dynamic functional connectivity fMRI

  • Alican Nalci
  • Bhaskar D. Rao
  • Thomas T. Liu

In resting-state fMRI, dynamic functional connectivity (DFC) measures are used to characterize temporal changes in the brain's intrinsic functional connectivity. A widely used approach for DFC estimation is the computation of the sliding window correlation between blood oxygenation level dependent (BOLD) signals from different brain regions. Although the source of temporal fluctuations in DFC estimates remains largely unknown, there is growing evidence that they may reflect dynamic shifts between functional brain networks. At the same time, recent findings suggest that DFC estimates might be prone to the influence of nuisance factors such as the physiological modulation of the BOLD signal. Therefore, nuisance regression is used in many DFC studies to regress out the effects of nuisance terms prior to the computation of DFC estimates. In this work we examined the relationship between seed-specific sliding window correlation-based DFC estimates and nuisance factors. We found that DFC estimates were significantly correlated with temporal fluctuations in the magnitude (norm) of various nuisance regressors. Strong correlations between the DFC estimates and nuisance regressor norms were found even when the underlying correlations between the nuisance and fMRI time courses were relatively small. We then show that nuisance regression does not necessarily eliminate the relationship between DFC estimates and nuisance norms, with significant correlations observed between the DFC estimates and nuisance norms even after nuisance regression. We present theoretical bounds on the difference between DFC estimates obtained before and after nuisance regression and relate these bounds to limitations in the efficacy of nuisance regression with regards to DFC estimates.

YNIMG Journal 2019 Journal Article

Nuisance effects in inter-scan functional connectivity estimates before and after nuisance regression

  • Alican Nalci
  • Wenjing Luo
  • Thomas T. Liu

In resting-state functional MRI, the correlation between blood-oxygenation-level-dependent (BOLD) signals across brain regions is used to estimate the functional connectivity (FC) of the brain. FC estimates are prone to the influence of nuisance factors including scanner-related artifacts and physiological modulations of the BOLD signal. Nuisance regression is widely performed to reduce the effect of nuisance factors on FC estimates on a per-scan basis. However, a dedicated analysis of nuisance effects on the variability of FC metrics across a collection of scans has been lacking. This work investigates the effects of nuisance factors on the variability of FC estimates across a collection of scans both before and after nuisance regression. Inter-scan variations in FC estimates are shown to be significantly correlated with the geometric norms of various nuisance terms, including head motion measurements, signals derived from white-matter and cerebrospinal regions, and the whole-brain global signal (GS) both before and after nuisance regression. In addition, it is shown that GS regression (GSR) can introduce GS norm-related fluctuations that are negatively correlated with inter-scan FC estimates. The empirical results are shown to be largely consistent with the predictions of a theoretical framework previously developed for the characterization of dynamic FC measures. This work shows that caution must be exercised when interpreting inter-scan FC measures across scans both before and after nuisance regression.

YNICL Journal 2018 Journal Article

Effects of HIV Infection, methamphetamine dependence and age on cortical thickness, area and volume

  • Katherine E. MacDuffie
  • Gregory G. Brown
  • Benjamin S. McKenna
  • Thomas T. Liu
  • M.J. Meloy
  • Brianna Tawa
  • Sarah Archibald
  • Christine Fennema-Notestine

OBJECTIVE: This study examined the effects of HIV infection, methamphetamine dependence and their interaction on cortical thickness, area and volume, as well as the potential interactive effects on cortical morphometry of HIV and methamphetamine with age. METHOD: T1-weighted structural images were obtained on a 3.0T General Electric MR750 scanner. Freesurfer v5.3.0 was used to derive cortical thickness, area and volume measures in thirty-four regions based on Desikan-Killiany atlas labels. RESULTS: Following correction for multiple statistical tests, HIV diagnosis was not significantly related to cortical thickness or area in any ROI, although smaller global cortical area and volume were seen in those with lower nadir CD4 count. HIV diagnosis, nevertheless, was associated with smaller mean cortical volumes in rostral middle frontal gyrus and in the inferior and superior parietal lobes. Methamphetamine dependence was significantly associated with thinner cortex especially in posterior cingulate gyrus, but was not associated with cortical area or volume following correction for multiple statistical tests. We found little evidence that methamphetamine dependence moderated differences in cortical area, volume or thickness for any ROI in the HIV seropositive group. Interactions with age revealed that HIV diagnosis attenuated the degree of age-related cortical thinning seen in non-infected individuals; intercepts indicated that young HIV seropositive individuals had thinner cortex than non-infected peers. CONCLUSIONS: Methamphetamine dependence does not appear to potentiate a reduction of cortical area, volume or thickness in HIV seropositive individuals. The finding of thinner cortex in young HIV seropositive individuals and the association between CD4 nadir and global cortical area and volume argue for prioritizing early antiretroviral treatment.

YNIMG Journal 2018 Journal Article

Template-based prediction of vigilance fluctuations in resting-state fMRI

  • Maryam Falahpour
  • Catie Chang
  • Chi Wah Wong
  • Thomas T. Liu

Changes in vigilance or alertness during a typical resting state fMRI scan are inevitable and have been found to affect measures of functional brain connectivity. Since it is not often feasible to monitor vigilance with EEG during fMRI scans, it would be of great value to have methods for estimating vigilance levels from fMRI data alone. A recent study, conducted in macaque monkeys, proposed a template-based approach for fMRI-based estimation of vigilance fluctuations. Here, we use simultaneously acquired EEG/fMRI data to investigate whether the same template-based approach can be employed to estimate vigilance fluctuations of awake humans across different resting-state conditions. We first demonstrate that the spatial pattern of correlations between EEG-defined vigilance and fMRI in our data is consistent with the previous literature. Notably, however, we observed a significant difference between the eyes-closed (EC) and eyes-open (EO) conditions, finding stronger negative correlations with vigilance in regions forming the default mode network and higher positive correlations in thalamus and insula in the EC condition when compared to the EO condition. Taking these correlation maps as “templates” for vigilance estimation, we found that the template-based approach produced fMRI-based vigilance estimates that were significantly correlated with EEG-based vigilance measures, indicating its generalizability from macaques to humans. We also demonstrate that the performance of this method was related to the overall amount of variability in a subject's vigilance state, and that the template-based approach outperformed the use of the global signal as a vigilance estimator. In addition, we show that the template-based approach can be used to estimate the variability across scans in the amplitude of the vigilance fluctuations. We discuss the benefits and tradeoffs of using the template-based approach in future fMRI studies.

YNICL Journal 2017 Journal Article

Dynamic association between perfusion and white matter integrity across time since injury in Veterans with history of TBI

  • Alexandra L. Clark
  • Katherine J. Bangen
  • Scott F. Sorg
  • Dawn M. Schiehser
  • Nicole D. Evangelista
  • Benjamin McKenna
  • Thomas T. Liu
  • Lisa Delano-Wood

OBJECTIVE: Cerebral blood flow (CBF) plays a critical role in the maintenance of neuronal integrity, and CBF alterations have been linked to deleterious white matter changes. Although both CBF and white matter microstructural alterations have been observed within the context of traumatic brain injury (TBI), the degree to which these pathological changes relate to one another and whether this association is altered by time since injury have not been examined. The current study therefore sought to clarify associations between resting CBF and white matter microstructure post-TBI. METHODS: 37 veterans with history of mild or moderate TBI (mmTBI) underwent neuroimaging and completed health and psychiatric symptom questionnaires. Resting CBF was measured with multiphase pseudocontinuous arterial spin labeling (MPPCASL), and white matter microstructural integrity was measured with diffusion tensor imaging (DTI). The cingulate cortex and cingulum bundle were selected as a priori regions of interest for the ASL and DTI data, respectively, given the known vulnerability of these regions to TBI. RESULTS: < 0.005). Decreased CBF was significantly associated with reduced cingulum fractional anisotropy (FA) in the chronic phase; however, no such association was observed for participants with less remote TBI. CONCLUSIONS: Our results showed that reduced CBF was associated with poorer white matter integrity in those who were further removed from their brain injury. Findings provide preliminary evidence of a possible dynamic association between CBF and white matter microstructure that warrants additional consideration within the context of the negative long-term clinical outcomes frequently observed in those with history of TBI. Additional cross-disciplinary studies integrating multiple imaging modalities (e.g., DTI, ASL) and refined neuropsychiatric assessment are needed to better understand the nature, temporal course, and dynamic association between brain changes and clinical outcomes post-injury.

YNIMG Journal 2017 Journal Article

Global signal regression acts as a temporal downweighting process in resting-state fMRI

  • Alican Nalci
  • Bhaskar D. Rao
  • Thomas T. Liu

In resting-state functional MRI (rsfMRI), the correlation between blood oxygenation level dependent (BOLD) signals across different brain regions is used to estimate the functional connectivity of the brain. This approach has led to the identification of a number of resting-state networks, including the default mode network (DMN) and the task positive network (TPN). Global signal regression (GSR) is a widely used pre-processing step in rsfMRI that has been shown to improve the spatial specificity of the estimated resting-state networks. In GSR, a whole brain average time series, known as the global signal (GS), is regressed out of each voxel time series prior to the computation of the correlations. However, the use of GSR is controversial because it can introduce artifactual negative correlations. For example, it has been argued that anticorrelations observed between the DMN and TPN are primarily an artifact of GSR. Despite the concerns about GSR, there is currently no consensus regarding its use. In this paper, we introduce a new framework for understanding the effects of GSR. In particular, we show that the main effects of GSR can be well approximated as a temporal downweighting process in which the data from time points with relatively large GS magnitudes are greatly attenuated while data from time points with relatively small GS magnitudes are largely unaffected. Furthermore, we show that a limiting case of this downweighting process in which data from time points with large GS magnitudes are censored can also approximate the effects of GSR. In other words, the correlation maps obtained after GSR show a high degree of spatial similarity (including the presence of anticorrelations between the DMN and TPN) with maps obtained using only the uncensored (i. e. retained) time points. Since the data from these retained time points are unaffected by the censoring process, this finding suggests that the observed anticorrelations inherently exist in the data from time points with small GS magnitudes and are not simply an artifact of GSR.

YNIMG Journal 2017 Journal Article

Reprint of ‘Noise contributions to the fMRI signal: An Overview'

  • Thomas T. Liu

The ability to discriminate signal from noise plays a key role in the analysis and interpretation of functional magnetic resonance imaging (fMRI) measures of brain activity. Over the past two decades, a number of major sources of noise have been identified, including system-related instabilities, subject motion, and physiological fluctuations. This article reviews the characteristics of the various noise sources as well as the mechanisms through which they affect the fMRI signal. Approaches for distinguishing signal from noise and the associated challenges are also reviewed. These challenges reflect the fact that some noise sources, such as respiratory activity, are generated by the same underlying brain networks that give rise to functional signals that are of interest.

YNIMG Journal 2017 Journal Article

The global signal in fMRI: Nuisance or Information?

  • Thomas T. Liu
  • Alican Nalci
  • Maryam Falahpour

The global signal is widely used as a regressor or normalization factor for removing the effects of global variations in the analysis of functional magnetic resonance imaging (fMRI) studies. However, there is considerable controversy over its use because of the potential bias that can be introduced when it is applied to the analysis of both task-related and resting-state fMRI studies. In this paper we take a closer look at the global signal, examining in detail the various sources that can contribute to the signal. For the most part, the global signal has been treated as a nuisance term, but there is growing evidence that it may also contain valuable information. We also examine the various ways that the global signal has been used in the analysis of fMRI data, including global signal regression, global signal subtraction, and global signal normalization. Furthermore, we describe new ways for understanding the effects of global signal regression and its relation to the other approaches.

YNIMG Journal 2016 Journal Article

Differences in the resting-state fMRI global signal amplitude between the eyes open and eyes closed states are related to changes in EEG vigilance

  • Chi Wah Wong
  • Pamela N. DeYoung
  • Thomas T. Liu

In resting-state functional connectivity magnetic resonance imaging (fcMRI) studies, measures of functional connectivity are often calculated after the removal of a global mean signal component. While the application of the global signal regression approach has been shown to reduce the influence of physiological artifacts and enhance the detection of functional networks, there is considerable controversy regarding its use as the method can lead to significant bias in the resultant connectivity measures. In addition, evidence from recent studies suggests that the global signal is linked to neural activity and may carry clinically relevant information. For instance, in a prior study we found that the amplitude of the global signal was negatively correlated with EEG measures of vigilance across subjects and experimental runs. Furthermore, caffeine-related decreases in global signal amplitude were associated with increases in EEG vigilance. In this study, we extend the prior work by examining measures of global signal amplitude and EEG vigilance under eyes-closed (EC) and eyes-open (EO) resting-state conditions. We show that changes (EO minus EC) in the global signal amplitude are negatively correlated with the associated changes in EEG vigilance. The slope of this EO–EC relation is comparable with the slope of the previously reported relation between caffeine-related changes in the global signal amplitude and EEG vigilance. Our findings provide further support for a basic relationship between global signal amplitude and EEG vigilance.

YNIMG Journal 2016 Journal Article

Noise contributions to the fMRI signal: An overview

  • Thomas T. Liu

The ability to discriminate signal from noise plays a key role in the analysis and interpretation of functional magnetic resonance imaging (fMRI) measures of brain activity. Over the past two decades, a number of major sources of noise have been identified, including system-related instabilities, subject motion, and physiological fluctuations. This article reviews the characteristics of the various noise sources as well as the mechanisms through which they affect the fMRI signal. Approaches for distinguishing signal from noise and the associated challenges are also reviewed. These challenges reflect the fact that some noise sources, such as respiratory activity, are generated by the same underlying brain networks that give rise to functional signals that are of interest.

YNIMG Journal 2016 Journal Article

The Cerebral Blood Flow Biomedical Informatics Research Network (CBFBIRN) data repository

  • David D. Shin
  • I. Burak Ozyurt
  • Gregory G. Brown
  • Christine Fennema-Notestine
  • Thomas T. Liu

Arterial spin labeling (ASL) MRI provides an accurate and reliable measure of cerebral blood flow (CBF). A rapidly growing number of CBF measures are being collected both in clinical and research settings around the world, resulting in a large volume of data across a wide spectrum of study populations and health conditions. Here, we describe a central CBF data repository with integrated processing workflows, referred to as the Cerebral Blood Flow Biomedical Informatics Research Network (CBFBIRN). The CBFBIRN provides an integrated framework for the analysis and comparison of CBF measures across studies and sites. In this work, we introduce the main capabilities of the CBFBIRN (data storage, processing, and sharing), describe what types of data are available, explain how users can contribute to the data repository and access existing data from it, and discuss our long-term plans for the CBFBIRN.

YNIMG Journal 2016 Journal Article

The Function Biomedical Informatics Research Network Data Repository

  • David B. Keator
  • Theo G.M. van Erp
  • Jessica A. Turner
  • Gary H. Glover
  • Bryon A. Mueller
  • Thomas T. Liu
  • James T. Voyvodic
  • Jerod Rasmussen

The Function Biomedical Informatics Research Network (FBIRN) developed methods and tools for conducting multi-scanner functional magnetic resonance imaging (fMRI) studies. Method and tool development were based on two major goals: 1) to assess the major sources of variation in fMRI studies conducted across scanners, including instrumentation, acquisition protocols, challenge tasks, and analysis methods, and 2) to provide a distributed network infrastructure and an associated federated database to host and query large, multi-site, fMRI and clinical data sets. In the process of achieving these goals the FBIRN test bed generated several multi-scanner brain imaging data sets to be shared with the wider scientific community via the BIRN Data Repository (BDR). The FBIRN Phase 1 data set consists of a traveling subject study of 5 healthy subjects, each scanned on 10 different 1. 5 to 4T scanners. The FBIRN Phase 2 and Phase 3 data sets consist of subjects with schizophrenia or schizoaffective disorder along with healthy comparison subjects scanned at multiple sites. In this paper, we provide concise descriptions of FBIRN's multi-scanner brain imaging data sets and details about the BIRN Data Repository instance of the Human Imaging Database (HID) used to publicly share the data.

YNIMG Journal 2015 Journal Article

Enhanced identification of BOLD-like components with multi-echo simultaneous multi-slice (MESMS) fMRI and multi-echo ICA

  • Valur Olafsson
  • Prantik Kundu
  • Eric C. Wong
  • Peter A. Bandettini
  • Thomas T. Liu

The recent introduction of simultaneous multi-slice (SMS) acquisitions has enabled the acquisition of blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) data with significantly higher temporal sampling rates. In a parallel development, the use of multi-echo fMRI acquisitions in conjunction with a multi-echo independent component analysis (ME-ICA) approach has been introduced as a means to automatically distinguish functionally-related BOLD signal components from signal artifacts, with significant gains in sensitivity, statistical power, and specificity. In this work, we examine the gains that can be achieved with a combined approach in which data obtained with a multi-echo simultaneous multi-slice (MESMS) acquisition are analyzed with ME-ICA. We find that ME-ICA identifies significantly more BOLD-like components in the MESMS data as compared to data acquired with a conventional multi-echo single-slice acquisition. We demonstrate that the improved performance of MESMS derives from both an increase in the number of temporal samples and the enhanced ability to filter out high-frequency artifacts.

YNIMG Journal 2014 Journal Article

MEG source imaging method using fast L1 minimum-norm and its applications to signals with brain noise and human resting-state source amplitude images

  • Ming-Xiong Huang
  • Charles W. Huang
  • Ashley Robb
  • Annemarie Angeles
  • Sharon L. Nichols
  • Dewleen G. Baker
  • Tao Song
  • Deborah L. Harrington

The present study developed a fast MEG source imaging technique based on Fast Vector-based Spatio-Temporal Analysis using a L1-minimum-norm (Fast-VESTAL) and then used the method to obtain the source amplitude images of resting-state magnetoencephalography (MEG) signals for different frequency bands. The Fast-VESTAL technique consists of two steps. First, L1-minimum-norm MEG source images were obtained for the dominant spatial modes of sensor-waveform covariance matrix. Next, accurate source time-courses with millisecond temporal resolution were obtained using an inverse operator constructed from the spatial source images of Step 1. Using simulations, Fast-VESTAL's performance was assessed for its 1) ability to localize multiple correlated sources; 2) ability to faithfully recover source time-courses; 3) robustness to different SNR conditions including SNR with negative dB levels; 4) capability to handle correlated brain noise; and 5) statistical maps of MEG source images. An objective pre-whitening method was also developed and integrated with Fast-VESTAL to remove correlated brain noise. Fast-VESTAL's performance was then examined in the analysis of human median-nerve MEG responses. The results demonstrated that this method easily distinguished sources in the entire somatosensory network. Next, Fast-VESTAL was applied to obtain the first whole-head MEG source-amplitude images from resting-state signals in 41 healthy control subjects, for all standard frequency bands. Comparisons between resting-state MEG sources images and known neurophysiology were provided. Additionally, in simulations and cases with MEG human responses, the results obtained from using conventional beamformer technique were compared with those from Fast-VESTAL, which highlighted the beamformer's problems of signal leaking and distorted source time-courses.

YNIMG Journal 2013 Journal Article

Neurovascular factors in resting-state functional MRI

  • Thomas T. Liu

There has been growing interest in the use of resting-state functional magnetic resonance imaging (rsfMRI) for the assessment of disease and treatment, and a number of studies have reported significant disease-related changes in resting-state blood oxygenation level dependent (BOLD) signal amplitude and functional connectivity. rsfMRI is particularly suitable for clinical applications because the approach does not require the patient to perform a task and scans can be obtained in a relatively short amount of time. However, the mechanisms underlying resting-state BOLD activity are not well understood and thus the interpretation of changes in resting state activity is not always straightforward. The BOLD signal represents the hemodynamic response to neural activity, and changes in resting-state activity can reflect a complex combination of neural, vascular, and metabolic factors. This paper examines the role of neurovascular factors in rsfMRI and reviews approaches for the interpretation and analysis of resting state measures in the presence of confounding factors.

YNIMG Journal 2013 Journal Article

The amplitude of the resting-state fMRI global signal is related to EEG vigilance measures

  • Chi Wah Wong
  • Valur Olafsson
  • Omer Tal
  • Thomas T. Liu

In resting-state functional magnetic resonance imaging (fMRI), functional connectivity measures can be influenced by the presence of a strong global component. A widely used pre-processing method for reducing the contribution of this component is global signal regression, in which a global mean time series signal is projected out of the fMRI time series data prior to the computation of connectivity measures. However, the use of global signal regression is controversial because the method can bias the correlation values to have an approximately zero mean and may in some instances create artifactual negative correlations. In addition, while many studies treat the global signal as a non-neural confound that needs to be removed, evidence from electrophysiological and fMRI measures in primates suggests that the global signal may contain significant neural correlates. In this study, we used simultaneously acquired fMRI and electroencephalographic (EEG) measures of resting-state activity to assess the relation between the fMRI global signal and EEG measures of vigilance in humans. We found that the amplitude of the global signal (defined as the standard deviation of the global signal) exhibited a significant negative correlation with EEG vigilance across subjects studied in the eyes-closed condition. In addition, increases in EEG vigilance due to the ingestion of caffeine were significantly associated with both a decrease in global signal amplitude and an increase in the average level of anti-correlation between the default mode network and the task-positive network.

YNIMG Journal 2012 Journal Article

A geometric view of global signal confounds in resting-state functional MRI

  • Hongjian He
  • Thomas T. Liu

Resting-state functional magnetic resonance imaging (fMRI) is proving to be an effective tool for mapping the long-range functional connections of the brain in both health and disease. One of the primary measures of connectivity is the correlation between the blood oxygenation level dependent (BOLD) time series observed in different brain regions. The computation of the correlation is often dominated by the presence of a strong global component that can introduce significant variability across functional connectivity maps acquired from different experimental scans or subjects. To address this issue, a variety of global signal correction methods have been proposed, but there is currently a lack of a clear consensus on the best approach to use. Furthermore, there has been concern that some global signal correction methods, such as global signal regression, may produce significant negative bias in the correlation values. In this paper we introduce a framework for visualizing the signal structure of resting-state fMRI data and characterizing the properties of the global signal. Using this framework, we demonstrate that a portion of the global signal can be viewed as an additive confound that increases with the mean BOLD amplitude. An approach for minimizing the contribution of this additive confound is presented, and an initial comparison with existing global signal correction methods is provided.

YNIMG Journal 2012 Journal Article

An automatic MEG low-frequency source imaging approach for detecting injuries in mild and moderate TBI patients with blast and non-blast causes

  • Ming-Xiong Huang
  • Sharon Nichols
  • Ashley Robb
  • Annemarie Angeles
  • Angela Drake
  • Martin Holland
  • Sarah Asmussen
  • John D'Andrea

Traumatic brain injury (TBI) is a leading cause of sustained impairment in military and civilian populations. However, mild (and some moderate) TBI can be difficult to diagnose because the injuries are often not detectable on conventional MRI or CT. Injured brain tissues in TBI patients generate abnormal low-frequency magnetic activity (ALFMA, peaked at 1–4Hz) that can be measured and localized by magnetoencephalography (MEG). We developed a new automated MEG low-frequency source imaging method and applied this method in 45 mild TBI (23 from combat-related blasts, and 22 from non-blast causes) and 10 moderate TBI patients (non-blast causes). Seventeen of the patients with mild TBI from blasts had tertiary injuries resulting from the blast. The results show our method detected abnormalities at the rates of 87% for the mild TBI group (blast-induced plus non-blast causes) and 100% for the moderate group. Among the mild TBI patients, the rates of abnormalities were 96% and 77% for the blast and non-blast TBI groups, respectively. The spatial characteristics of abnormal slow-wave generation measured by Z scores in the mild blast TBI group significantly correlated with those in non-blast mild TBI group. Among 96 cortical regions, the likelihood of abnormal slow-wave generation was less in the mild TBI patients with blast than in the mild non-blast TBI patients, suggesting possible protective effects due to the military helmet and armor. Finally, the number of cortical regions that generated abnormal slow-waves correlated significantly with the total post-concussive symptom scores in TBI patients. This study provides a foundation for using MEG low-frequency source imaging to support the clinical diagnosis of TBI.

YNIMG Journal 2012 Journal Article

Anti-correlated networks, global signal regression, and the effects of caffeine in resting-state functional MRI

  • Chi Wah Wong
  • Valur Olafsson
  • Omer Tal
  • Thomas T. Liu

Resting-state functional connectivity magnetic resonance imaging is proving to be an essential tool for the characterization of functional networks in the brain. Two of the major networks that have been identified are the default mode network (DMN) and the task positive network (TPN). Although prior work indicates that these two networks are anti-correlated, the findings are controversial because the anti-correlations are often found only after the application of a pre-processing step, known as global signal regression, that can produce artifactual anti-correlations. In this paper, we show that, for subjects studied in an eyes-closed rest state, caffeine can significantly enhance the detection of anti-correlations between the DMN and TPN without the need for global signal regression. In line with these findings, we find that caffeine also leads to widespread decreases in connectivity and global signal amplitude. Using a recently introduced geometric model of global signal effects, we demonstrate that these decreases are consistent with the removal of an additive global signal confound. In contrast to the effects observed in the eyes-closed rest state, caffeine did not lead to significant changes in global functional connectivity in the eyes-open rest state.

YNIMG Journal 2012 Journal Article

Caffeine increases the temporal variability of resting-state BOLD connectivity in the motor cortex

  • Anna Leigh Rack-Gomer
  • Thomas T. Liu

Correlations between spontaneous fluctuations in the blood oxygenation level dependent (BOLD) signal measured with functional MRI are finding increasing use as measures of functional connectivity in the brain, where differences can potentially predict cognitive performance and diagnose disease. Caffeine, which is a widely consumed neural stimulant and vasoactive agent, has been found to decrease the amplitude and correlation of resting-state BOLD fluctuations, and hence is an important factor to consider in functional connectivity studies. However, because the BOLD signal is sensitive to neural and vascular factors, the physiological mechanisms by which caffeine alters spontaneous BOLD fluctuations remain unclear. Resting-state functional connectivity has traditionally been assessed using stationary measures, such as the correlation coefficient between BOLD signals measured across the length of a scan. However, recent work has shown that the correlation of resting-state networks can vary considerably over time, with periods as short as 10s. In this study, we used a sliding window correlation analysis to assess temporal variations in resting-state functional connectivity of the motor cortex before and after caffeine ingestion. We found that the temporal variability of BOLD correlation was significantly higher following a caffeine dose, with transient periods of strong correlation alternating with periods of low or negative correlation. This phenomenon was primarily due to increased variability in the phase difference between BOLD time courses in the left and right motor cortices. These results indicate that caffeine may cause underlying spontaneous neural fluctuations to go in and out of coherence more frequently, and emphasizes the need to consider non-stationary measures when studying changes in functional connectivity.

YNIMG Journal 2012 Journal Article

The development of event-related fMRI designs

  • Thomas T. Liu

The diversity of experimental designs that can be used with functional magnetic resonance imaging (fMRI) has played a key role in its widespread application to studies of human cognition. This flexibility is possible because the fMRI response to external stimuli is remarkably well approximated as the response of a linear time variant system. The experimental demonstration of this property provided the foundation for the development of event-related designs, in which the fMRI response is modeled as the linear summation of the hemodynamic response to discrete events. Building upon prior work from the fields of engineering, neuroscience, and statistics, researchers in the field have created a rich collection of event-related designs and developed a rigorous theoretical framework for characterizing and optimizing the performance of designs. Ongoing challenges include the optimization of designs in the presence of experimental constraints and the development of more time-efficient optimization algorithms.

YNIMG Journal 2011 Journal Article

Accurate reconstruction of temporal correlation for neuronal sources using the enhanced dual-core MEG beamformer

  • Mithun Diwakar
  • Omer Tal
  • Thomas T. Liu
  • Deborah L. Harrington
  • Ramesh Srinivasan
  • Laura Muzzatti
  • Tao Song
  • Rebecca J. Theilmann

Beamformer spatial filters are commonly used to explore the active neuronal sources underlying magnetoencephalography (MEG) recordings at low signal-to-noise ratio (SNR). Conventional beamformer techniques are successful in localizing uncorrelated neuronal sources under poor SNR conditions. However, the spatial and temporal features from conventional beamformer reconstructions suffer when sources are correlated, which is a common and important property of real neuronal networks. Dual-beamformer techniques, originally developed by Brookes et al. to deal with this limitation, successfully localize highly-correlated sources and determine their orientations and weightings, but their performance degrades at low correlations. They also lack the capability to produce individual time courses and therefore cannot quantify source correlation. In this paper, we present an enhanced formulation of our earlier dual-core beamformer (DCBF) approach that reconstructs individual source time courses and their correlations. Through computer simulations, we show that the enhanced DCBF (eDCBF) consistently and accurately models dual-source activity regardless of the correlation strength. Simulations also show that a multi-core extension of eDCBF effectively handles the presence of additional correlated sources. In a human auditory task, we further demonstrate that eDCBF accurately reconstructs left and right auditory temporal responses and their correlations. Spatial resolution and source localization strategies corresponding to different measures within the eDCBF framework are also discussed. In summary, eDCBF accurately reconstructs source spatio-temporal behavior, providing a means for characterizing complex neuronal networks and their communication.

YNIMG Journal 2010 Journal Article

An arterial spin labeling investigation of cerebral blood flow deficits in chronic stroke survivors

  • Kathleen P. Brumm
  • Joanna E. Perthen
  • Thomas T. Liu
  • Frank Haist
  • Liat Ayalon
  • Tracy Love

Although the acute stroke literature indicates that cerebral blood flow (CBF) may commonly be disordered in stroke survivors, limited research has investigated whether CBF remains aberrant in the chronic phase of stroke. A directed study of CBF in stroke is needed because reduced CBF (hypoperfusion) may occur in neural regions that appear anatomically intact and may impact cognitive functioning in stroke survivors. Hypoperfusion in neurologically-involved individuals may also affect BOLD signal in FMRI studies, complicating its interpretation with this population. The current study measured CBF in three chronic stroke survivors with ischemic infarcts (greater than 1year post-stroke) to localize regions of hypoperfusion, and most critically, examine the CBF inflow curve using a methodology that has never, to our knowledge, been reported in the chronic stroke literature. CBF data acquired with a Pulsed Arterial Spin Labeling (PASL) flow-sensitive alternating inversion recovery (FAIR) technique indicated both delayed CBF inflow curve and hypoperfusion in the stroke survivors as compared to younger and elderly control participants. Among the stroke survivors, we observed regional hypoperfusion in apparently anatomically intact neural regions that are involved in cognitive functioning. These results may have profound implications for the study of behavioral deficits in chronic stroke, and particularly for studies using neuroimaging methods that rely on CBF to draw conclusions about underlying neural activity.

YNIMG Journal 2010 Journal Article

Caffeine increases the linearity of the visual BOLD response

  • Thomas T. Liu
  • Joy Liau

Although the blood oxygenation level dependent (BOLD) signal used in most functional magnetic resonance imaging (fMRI) studies has been shown to exhibit nonlinear characteristics, most analyses assume that the BOLD signal responds in a linear fashion to stimulus. This assumption of linearity can lead to errors in the estimation of the BOLD response, especially for rapid event-related fMRI studies. In this study, we used a rapid event-related design and Volterra kernel analysis to assess the effect of a 200 mg oral dose of caffeine on the linearity of the visual BOLD response. The caffeine dose significantly (p <0. 02) increased the linearity of the BOLD response in a sample of 11 healthy volunteers studied on a 3 T MRI system. In addition, the agreement between nonlinear and linear estimates of the hemodynamic response function was significantly increased (p =0. 013) with the caffeine dose. These findings indicate that differences in caffeine usage should be considered as a potential source of bias in the analysis of rapid event-related fMRI studies.

YNIMG Journal 2009 Journal Article

Caffeine reduces resting-state BOLD functional connectivity in the motor cortex

  • Anna Leigh Rack-Gomer
  • Joy Liau
  • Thomas T. Liu

In resting-state functional magnetic resonance imaging (fMRI), correlations between spontaneous low-frequency fluctuations in the blood oxygenation level dependent (BOLD) signal are used to assess functional connectivity between different brain regions. Changes in resting-state BOLD connectivity measures are typically interpreted as changes in coherent neural activity across spatially distinct brain regions. However, this interpretation can be complicated by the complex dependence of the BOLD signal on both neural and vascular factors. For example, prior studies have shown that vasoactive agents that alter baseline cerebral blood flow, such as caffeine and carbon dioxide, can significantly alter the amplitude and dynamics of the task-related BOLD response. In this study, we examined the effect of caffeine (200 mg dose) on resting-state BOLD connectivity in the motor cortex across a sample of healthy young subjects (N =9). We found that caffeine significantly (p <0. 05) reduced measures of resting-state BOLD connectivity in the motor cortex. Baseline cerebral blood flow and spectral energy in the low-frequency BOLD fluctuations were also significantly decreased by caffeine. These results suggest that caffeine usage should be carefully considered in the design and interpretation of resting-state BOLD fMRI studies.

YNIMG Journal 2009 Journal Article

Inter-subject variability in hypercapnic normalization of the BOLD fMRI response

  • Joy Liau
  • Thomas T. Liu

In the application of hypercapnic normalization to functional magnetic resonance imaging (fMRI) studies, the blood oxygenation level dependent (BOLD) response to a functional stimulus is typically divided by the BOLD response to a hypercapnic challenge. While some prior studies have shown that hypercapnic normalization can reduce inter-subject BOLD variability, other studies have found an increase in inter-subject variability. In this study we used measures of baseline cerebral blood flow (CBF) and the functional BOLD and CBF responses to both visual stimuli and hypercapnia to assess the effect of hypercapnic normalization on inter-subject variability. We found that the functional and hypercapnic BOLD and CBF responses all exhibited a significant inverse dependence on baseline CBF. In contrast, the maximum BOLD response was independent of baseline CBF and was not a major source of inter-subject BOLD variability. Division of the functional BOLD response by the hypercapnic BOLD response increased inter-subject variability in the normalized responses as compared to the original responses, reflecting the presence of a systematic bias term that was inversely dependent on the hypercapnic BOLD response. This systematic bias resulted from a positive intercept term in the linear relationship between the functional and hypercapnic BOLD responses. This positive intercept term reflected a steeper inverse dependence of the hypercapnic CBF response on baseline CBF, as compared to the functional CBF response. In contrast to the results obtained with normalization based on division, normalized responses obtained by using the hypercapnic BOLD response as a covariate were unaffected by the systematic bias and exhibited reduced inter-subject variability. The findings of this study indicate that the positive intercept in the linear relationship between functional and hypercapnic BOLD responses should be carefully considered in the hypercapnic normalization of BOLD fMRI data.

YNIMG Journal 2008 Journal Article

Caffeine reduces the activation extent and contrast-to-noise ratio of the functional cerebral blood flow response but not the BOLD response

  • Joy Liau
  • Joanna E. Perthen
  • Thomas T. Liu

Measures of the spatial extent of functional activation are important for a number of functional magnetic resonance imaging (fMRI) applications, such as pre-surgical planning and longitudinal tracking of changes in brain activation with disease progression and drug treatment. The interpretation of the data from these applications can be complicated by inter-subject or inter-session variability in the measured fMRI signals. Prior studies have shown that modulation of baseline cerebral blood flow (CBF) can directly alter the functional CBF and blood oxygenation level dependent (BOLD) responses, suggesting that the spatial extents of functional activation maps based on these signals may also depend on baseline CBF. In this study, we used a caffeine dose (200 mg) to decrease baseline CBF and found significant (p <0. 05) reductions in both the CBF activation extent and contrast-to-noise ratio (CNR) but no significant changes in the BOLD activation extent and CNR. In contrast, caffeine significantly changed the temporal dynamics of the BOLD response but not the CBF response. The decreases in the CBF activation extent and CNR were consistent with a significant caffeine-induced decrease in the absolute CBF change accompanied by no significant change in the residual noise. Measures of baseline CBF also accounted for a significant portion of the inter-subject variability in the CBF activation map area and CNR. Factors that can modulate baseline CBF, such as age, medication, and disease, should therefore be carefully considered in the interpretation of studies that use functional CBF activation maps.

YNIMG Journal 2008 Journal Article

Caffeine-induced uncoupling of cerebral blood flow and oxygen metabolism: A calibrated BOLD fMRI study

  • Joanna E. Perthen
  • Amy E. Lansing
  • Joy Liau
  • Thomas T. Liu
  • Richard B. Buxton

Although functional MRI (fMRI) based on blood oxygenation level-dependent (BOLD) signal changes is a sensitive tool for mapping brain activation, quantitative studies of the physiological effects of pharmacological agents using fMRI alone are difficult to interpret due to the complexities inherent in the BOLD response. Hypercapnia-calibrated BOLD methodology is potentially a more powerful physiological probe of brain function, providing measures of the changes in cerebral blood flow (CBF) and the cerebral metabolic rate of oxygen (CMRO2). In this study, we implemented a quantitative R 2* approach for assessing the BOLD response to improve the stability of repeated measurements, in combination with the calibrated BOLD method, to examine the CBF and CMRO2 responses to caffeine ingestion. Ten regular caffeine consumers were imaged before and after a 200-mg caffeine dose. A dual-echo arterial spin labeling technique was used to measure CBF and BOLD responses to visual stimulation, caffeine consumption and mild hypercapnia. For a region of interest defined by CBF activation to the visual stimulus, the results were: hypercapnia increased CBF (+46. 6%, ±11. 3, mean and standard error), visual stimulation increased both CBF (+47. 9%, ±2. 9) and CMRO2 (+20. 7%, ±1. 4), and caffeine decreased CBF (−34. 5%, ±2. 6) with a non-significant change in CMRO2 (+5. 2%, ±6. 4). The coupling between CBF and CMRO2 was significantly different in response to visual stimulation compared to caffeine consumption. A calibrated BOLD methodology using R 2∗ is a promising approach for evaluating CBF and CMRO2 changes in response to pharmacological interventions.

YNIMG Journal 2008 Journal Article

Calibrated fMRI in the medial temporal lobe during a memory-encoding task

  • Khaled Restom
  • Joanna E. Perthen
  • Thomas T. Liu

Prior measures of the blood oxygenation level-dependent (BOLD) and cerebral blood flow (CBF) responses to a memory-encoding task within the medial temporal lobe have suggested that the coupling between functional changes in CBF and changes in the cerebral metabolic rate of oxygen (CMRO2) may be tighter in the medial temporal lobe as compared to the primary sensory areas. In this study, we used a calibrated functional magnetic resonance imaging (fMRI) approach to directly estimate memory-encoding-related changes in CMRO2 and to assess the coupling between CBF and CMRO2 in the medial temporal lobe. The CBF–CMRO2 coupling ratio was estimated using a linear fit to the flow and metabolism changes observed across subjects. In addition, we examined the effect of region-of-interest (ROI) selection on the estimates. In response to the memory-encoding task, CMRO2 increased by 23. 1±8. 8% to 25. 3±5. 7% (depending upon ROI), with an estimated CBF–CMRO2 coupling ratio of 1. 66±0. 07 to 1. 75±0. 16. There was not a significant effect of ROI selection on either the CMRO2 or coupling ratio estimates. The observed coupling ratios were significantly lower than the values (2 to 4. 5) that have been reported in previous calibrated fMRI studies of the visual and motor cortices. In addition, the estimated coupling ratio was found to be less sensitive to the calibration procedure for functional responses in the medial temporal lobe as compared to the primary sensory areas.

YNIMG Journal 2007 Journal Article

A component based noise correction method (CompCor) for BOLD and perfusion based fMRI

  • Yashar Behzadi
  • Khaled Restom
  • Joy Liau
  • Thomas T. Liu

A component based method (CompCor) for the reduction of noise in both blood oxygenation level-dependent (BOLD) and perfusion-based functional magnetic resonance imaging (fMRI) data is presented. In the proposed method, significant principal components are derived from noise regions-of-interest (ROI) in which the time series data are unlikely to be modulated by neural activity. These components are then included as nuisance parameters within general linear models for BOLD and perfusion-based fMRI time series data. Two approaches for the determination of the noise ROI are considered. The first method uses high-resolution anatomical data to define a region of interest composed primarily of white matter and cerebrospinal fluid, while the second method defines a region based upon the temporal standard deviation of the time series data. With the application of CompCor, the temporal standard deviation of resting-state perfusion and BOLD data in gray matter regions was significantly reduced as compared to either no correction or the application of a previously described retrospective image based correction scheme (RETROICOR). For both functional perfusion and BOLD data, the application of CompCor significantly increased the number of activated voxels as compared to no correction. In addition, for functional BOLD data, there were significantly more activated voxels detected with CompCor as compared to RETROICOR. In comparison to RETROICOR, CompCor has the advantage of not requiring external monitoring of physiological fluctuations.

YNIMG Journal 2007 Journal Article

Cerebral blood flow and BOLD responses to a memory encoding task: A comparison between healthy young and elderly adults

  • Khaled Restom
  • Katherine J. Bangen
  • Mark W. Bondi
  • Joanna E. Perthen
  • Thomas T. Liu

Functional magnetic resonance imaging (fMRI) studies of the medial temporal lobe have primarily made use of the blood oxygenation level dependent (BOLD) response to neural activity. The interpretation of the BOLD signal as a measure of medial temporal lobe function can be complicated, however, by changes in the cerebrovascular system that can occur with both normal aging and age-related diseases, such as Alzheimer's disease. Quantitative measures of the functional cerebral blood flow (CBF) response offer a useful complement to BOLD measures and have been shown to aid in the interpretation of fMRI studies. Despite these potential advantages, the application of ASL to fMRI studies of cognitive tasks and at-risk populations has been limited. In this study, we demonstrate the application of ASL fMRI to obtain measures of the CBF and BOLD responses to the encoding of natural scenes in healthy young (mean 25 years) and elderly (mean 74 years) adults. The percent CBF increase in the medial temporal lobe was significantly higher in the older adults, whereas the CBF levels during baseline and task conditions and during a separate resting-state scan were significantly lower in the older group. The older adults also showed slightly higher values for the BOLD response amplitude and the absolute change in CBF, but the age group differences were not significant. The percent CBF and BOLD responses are consistent with an age-related increase in the cerebral metabolic rate of oxygen metabolism (CMRO2) response to memory encoding.

YNIMG Journal 2006 Journal Article

Caffeine reduces the initial dip in the visual BOLD response at 3 T

  • Yashar Behzadi
  • Thomas T. Liu

Localized changes in oxygen consumption related to increased neural activity can result in a small and transient “initial dip” of the blood oxygenation level-dependent (BOLD) signal used in functional magnetic resonance imaging (fMRI). The initial dip has been of great interest to the fMRI community because it may provide a more accurate and localized measure of neural activity than the conventional BOLD signal increase. Although potentially useful as a technique for human brain mapping, the initial dip is not always detected and has been a source of some controversy. In this study, the BOLD response to a 4-s long visual stimulus was measured with a 3-T MRI system in 5 healthy volunteers both before and immediately after a 200-mg oral caffeine dose. The caffeine dose significantly (P < 0. 001) reduced or eliminated the initial dip in all subjects. These findings suggest that caffeine usage may be a key factor in the detection of the initial dip in human fMRI studies.

YNIMG Journal 2006 Journal Article

Physiological noise reduction for arterial spin labeling functional MRI

  • Khaled Restom
  • Yashar Behzadi
  • Thomas T. Liu

Three methods for the reduction of physiological noise in arterial spin labeling (ASL) functional magnetic resonance imaging (fMRI) are presented and compared. The methods are based upon a general linear model of the ASL measurement process and on a previously described retrospective image-based method (RETROICOR) for physiological noise reduction in blood oxygenation level dependent fMRI. In the first method, the contribution of physiological noise to the interleaved control and tag images that comprise the ASL time series are assumed to be equal, while in the second method this assumption is not made. For the third method, it is assumed that physiological noise primarily impacts the perfusion time series obtained from the filtered subtraction of the control and tag images. The methods were evaluated using studies of functional activity in the visual cortex and the hippocampal region. The first and second methods significantly improved statistical performance in both brain regions, whereas the third method did not provide a significant gain. The second method provided significantly better performance than the first method in the hippocampal region, whereas the differences between methods were less pronounced in visual cortex. The improved performance of the second method in the hippocampal region appears to reflect the relatively greater effect of cardiac fluctuations in this brain region. The proposed methods should be particularly useful for ASL studies of cognitive processes where the intrinsic signal to noise ratio is typically lower than for studies of primary sensory regions.

YNIMG Journal 2005 Journal Article

A signal processing model for arterial spin labeling functional MRI

  • Thomas T. Liu
  • Eric C. Wong

A model of the signal path in arterial spin labeling (ASL)-based functional magnetic resonance imaging (fMRI) is presented. Three subtraction-based methods for forming a perfusion estimate are considered and shown to be specific cases of a generalized estimate consisting of a modulator followed by a low pass filter. The performance of the methods is evaluated using the signal model. Contamination of the perfusion estimate by blood oxygenation level dependent contrast (BOLD) is minimized by using either sinc subtraction or surround subtraction for block design experiments and by using pair-wise subtraction for randomized event-related experiments. The subtraction methods all tend to decorrelate the 1/f type low frequency noise often observed in fMRI experiments. Sinc subtraction provides the flattest noise power spectrum at low frequencies, while pair-wise subtraction yields the narrowest autocorrelation function. The formation of BOLD estimates from the ASL data is also considered and perfusion weighting of the estimates is examined using the signal model.

YNIMG Journal 2005 Journal Article

An arteriolar compliance model of the cerebral blood flow response to neural stimulus

  • Yashar Behzadi
  • Thomas T. Liu

Although functional magnetic resonance imaging (fMRI) is a widely used and powerful tool for studying brain function, the quantitative interpretation of fMRI measurements for basic neuroscience and clinical studies can be complicated by inter-subject and inter-session variability arising from modulation of the baseline vascular state by disease, aging, diet, and pharmacological agents. In particular, recent studies have shown that the temporal dynamics of the cerebral blood flow (CBF) and the blood oxygenation level dependent (BOLD) responses to stimulus are modulated by changes in baseline CBF induced by various vasoactive agents and by decreases in vascular compliance associated with aging. These effects are not readily explained using current models of the CBF and BOLD responses. We present here a second-order nonlinear feedback model of the evoked CBF response in which neural activity modulates the compliance of arteriolar smooth muscle. Within this model framework, the baseline vascular state affects the dynamic response by changing the relative contributions of an active smooth muscle component and a passive connective tissue component to the overall vessel compliance. Baseline dependencies of the BOLD signal are studied by coupling the arteriolar compliance model with a previously described balloon model of the venous compartment. Numerical simulations show that the proposed model describes to first order the observed dependence of CBF and BOLD responses on the baseline vascular state.

YNIMG Journal 2004 Journal Article

Caffeine alters the temporal dynamics of the visual BOLD response

  • Thomas T. Liu
  • Yashar Behzadi
  • Khaled Restom
  • Kamil Uludag
  • Kun Lu
  • Giedrius T. Buracas
  • David J. Dubowitz
  • Richard B. Buxton

The blood oxygenation level-dependent (BOLD) responses to visual stimuli, using both a 1-s long single trial stimulus and a 20-s long block stimulus, were measured in a 4-T magnetic field both before and immediately after a 200-mg caffeine dose. In addition, resting levels of cerebral blood flow (CBF) were measured using arterial spin labeling. For the single trial stimulus, the caffeine dose significantly (p < 0. 05) reduced the time to peak (TTP), the time after the peak at which the response returned to 50% of the peak amplitude (TA50), and the amplitude of the poststimulus undershoot in all subjects (N = 5). Other parameters, such as the full-width half-maximum (FWHM) and the peak amplitude, also showed significant changes in the majority of subjects. For the block stimulus, the TTP, TA50, and the time for the response to reach 50% of the peak amplitude (T50) were significantly reduced. In some subjects, oscillations were observed in the poststimulus portion of the response with median peak periods of 9. 1 and 9. 5 s for the single trial and block responses, respectively. Resting CBF was reduced by an average of 24%. The reproducibility of the results was verified in one subject who was scanned on 3 different days. The dynamic changes are similar to those previously reported for baseline CBF reductions induced by hypocapnia and hyperoxia.

YNIMG Journal 2004 Journal Article

Coupling of cerebral blood flow and oxygen consumption during physiological activation and deactivation measured with fMRI

  • Kâmil Uludağ
  • David J. Dubowitz
  • Elizabeth J. Yoder
  • Khaled Restom
  • Thomas T. Liu
  • Richard B. Buxton

The physiological basis of the blood oxygenation level dependent (BOLD) signal and its dependence on baseline cerebral blood flow (CBF) were investigated by comparing responses to a visual stimulus after physiological changes of the baseline. Eight human subjects were imaged with 3 and 4 T MRI scanners, and both BOLD signal and CBF were simultaneously measured. Subjects viewed a flickering radial checkerboard in a block design experiment, alternating between eyes open or closed during the off periods. Compared to a baseline state with eyes open in a darkened room, substantial deactivation (average change: 2. 9 ± 0. 3% BOLD, 22 ± 2. 1% CBF) in the occipital cortex was observed when the eyes were closed. The absolute response during stimulation (average change: 4. 4 ± 0. 4% BOLD, 36. 3 ± 3. 1% CBF) was independent of the preceding resting condition. We estimated the fractional change in CBF to be approximately 2. 2 ± 0. 15 times greater than the fractional change in metabolic rate of oxygen (CMRO2). The changes in CBF and CMRO2 were consistently linearly coupled during activation and deactivation with CBF changes being between approximately 60% and 150% compared to baseline with eyes open. Relative to an assumed baseline oxygen extraction fraction (OEF) of 40%, the estimated OEF decreased to 33 ± 1. 4% during activation and increased to 46 ± 1. 2% during rest with eyes closed. In conclusion, we found that simply closing the eyes creates a large physiological deactivation in the visual cortex, and provides a robust paradigm for studying baseline effects in fMRI. In addition, we propose a feed-forward model for neurovascular coupling which accounts for the changes in OEF seen following baseline changes, including both the current physiological perturbations as well as previously reported pharmacologically induced changes.

YNIMG Journal 2004 Journal Article

Discrepancies between BOLD and flow dynamics in primary and supplementary motor areas: application of the balloon model to the interpretation of BOLD transients

  • Takayuki Obata
  • Thomas T. Liu
  • Karla L. Miller
  • Wen-Ming Luh
  • Eric C. Wong
  • Lawrence R. Frank
  • Richard B. Buxton

The blood-oxygen-level-dependent (BOLD) signal measured in the brain with functional magnetic resonance imaging (fMRI) during an activation experiment often exhibits pronounced transients at the beginning and end of the stimulus. Such transients could be a reflection of transients in the underlying neural activity, or they could result from transients in cerebral blood flow (CBF), cerebral metabolic rate of oxygen (CMRO2), or cerebral blood volume (CBV). These transients were investigated using an arterial spin labeling (ASL) method that allows simultaneous measurements of BOLD and CBF responses. Responses to a finger-tapping task (40-s stimulus, 80-s rest) were measured in primary motor area (M1) and supplementary motor area (SMA) in five healthy volunteers. In SMA, the average BOLD response was pronounced near the beginning and end of the stimulus, while in M1, the BOLD response was nearly flat. However, CBF responses in the two regions were rather similar, and did not exhibit the same transient features as the BOLD response in SMA. Because this suggests a hemodynamic rather than a neural origin for the transients of the BOLD response in SMA, we used a generalization of the balloon model to test the degree of hemodynamic transients required to produce the measured curves. Both data sets could be approximated with modest differences in the shapes of the CMRO2 and CBV responses. This study illustrates the utility and the limitations of using theoretical models combined with ASL techniques to understand the dynamics of the BOLD response.

YNIMG Journal 2004 Journal Article

Efficiency, power, and entropy in event-related fMRI with multiple trial types

  • Thomas T. Liu

The performance of an experimental design for functional magnetic resonance imaging (fMRI) can be characterized by its estimation efficiency, which is the ability to make an estimate of the hemodynamic response, its detection power, which is the ability to detect an activation, and its conditional entropy, which is a measure of the randomness of the design. In Liu and Frank [Neuroimage 21 (2004) 387–400], it is shown that there is a fundamental theoretical trade-off between estimation efficiency and detection power for experiments with multiple trial types and that there is an empirical relation between estimation efficiency and conditional entropy. This paper provides an intuitive interpretation of the theoretical results and examines the practical implications of these results for the optimal design of fMRI experiments with multiple trial types. The properties of block designs, permuted block designs, m-sequence designs, clustered m-sequence designs, and mixed designs are explored. It is shown that these designs nearly achieve the theoretically predicted performance and can be used in practice to obtain advantageous trade-offs among efficiency, power, and entropy.

YNIMG Journal 2004 Journal Article

Efficiency, power, and entropy in event-related FMRI with multiple trial types

  • Thomas T. Liu
  • Lawrence R. Frank

Experimental designs for functional magnetic resonance imaging (fMRI) experiments can be characterized by their estimation efficiency, which is a measure of the variance in the estimate of the hemodynamic response function (HRF), and their detection power, which is a measure of the variance in the estimate of the amplitude of functional activity. Previous studies have shown that there exists a fundamental trade-off between efficiency and power for experiments with a single trial type of interest. This paper extends the prior work by presenting a theoretical model for the relation between detection power and estimation efficiency in experiments with multiple trial types. It is shown that the trade-off between efficiency and power present in multiple-trial-type experiments is identical in form to that observed for single-trial-type experiments. Departures from the predicted trade-off due to the inclusion of basis function expansions and the assumption of correlated noise are examined. Finally, conditional entropy is introduced as measure for the randomness of a design, and an empirical relation between entropy and estimation efficiency is presented.

YNIMG Journal 2004 Journal Article

Modeling the hemodynamic response to brain activation

  • Richard B. Buxton
  • Kâmil Uludağ
  • David J. Dubowitz
  • Thomas T. Liu

Neural activity in the brain is accompanied by changes in cerebral blood flow (CBF) and blood oxygenation that are detectable with functional magnetic resonance imaging (fMRI) techniques. In this paper, recent mathematical models of this hemodynamic response are reviewed and integrated. Models are described for: (1) the blood oxygenation level dependent (BOLD) signal as a function of changes in cerebral oxygen extraction fraction (E) and cerebral blood volume (CBV); (2) the balloon model, proposed to describe the transient dynamics of CBV and deoxy-hemoglobin (Hb) and how they affect the BOLD signal; (3) neurovascular coupling, relating the responses in CBF and cerebral metabolic rate of oxygen (CMRO2) to the neural activity response; and (4) a simple model for the temporal nonlinearity of the neural response itself. These models are integrated into a mathematical framework describing the steps linking a stimulus to the measured BOLD and CBF responses. Experimental results examining transient features of the BOLD response (post-stimulus undershoot and initial dip), nonlinearities of the hemodynamic response, and the role of the physiologic baseline state in altering the BOLD signal are discussed in the context of the proposed models. Quantitative modeling of the hemodynamic response, when combined with experimental data measuring both the BOLD and CBF responses, makes possible a more specific and quantitative assessment of brain physiology than is possible with standard BOLD imaging alone. This approach has the potential to enhance numerous studies of brain function in development, health, and disease.

YNIMG Journal 2002 Journal Article

Analysis and Design of Perfusion-Based Event-Related fMRI Experiments

  • Thomas T. Liu
  • Eric C. Wong
  • Lawrence R. Frank
  • Richard B. Buxton

Perfusion-based functional magnetic resonance imaging (fMRI) using arterial spin labeling (ASL) methods has the potential to provide better localization of the functional signal to the sites of neural activity compared to blood oxygenation level-dependent (BOLD) contrast fMRI. At present, experiments using ASL have been limited to simple block and periodic single-trial designs. We present here an adaptation of the general linear model to perfusion-based fMRI that enables the design and analysis of more complicated designs, such as random and semirandom event-related designs. Formulas for the least-squares estimate of the perfusion response and the F statistic for the detection of a response are derived. Exact expressions and useful approximations for detection power and estimation efficiency are presented, and it is shown that the trade-off between power and efficiency for perfusion experiments is similar to that previously observed for BOLD experiments. The least-squares estimate is compared with an estimate formed from the running subtraction of tag and control images. The running subtraction estimate is shown to be approximately equal to a temporally low-pass-filtered version of the least-squares estimate. Numerical simulations and results from ASL experiments are used to support the theoretical findings.

YNIMG Journal 2001 Journal Article

Detection Power, Estimation Efficiency, and Predictability in Event-Related fMRI

  • Thomas T. Liu
  • Lawrence R. Frank
  • Eric C. Wong
  • Richard B. Buxton

Experimental designs for event-related functional magnetic resonance imaging can be characterized by both their detection power, a measure of the ability to detect an activation, and their estimation efficiency, a measure of the ability to estimate the shape of the hemodynamic response. Randomized designs offer maximum estimation efficiency but poor detection power, while block designs offer good detection power at the cost of minimum estimation efficiency. Periodic single-trial designs are poor by both criteria. We present here a theoretical model of the relation between estimation efficiency and detection power and show that the observed trade-off between efficiency and power is fundamental. Using the model, we explore the properties of semirandom designs that offer intermediate trade-offs between efficiency and power. These designs can simultaneously achieve the estimation efficiency of randomized designs and the detection power of block designs at the cost of increasing the length of an experiment by less than a factor of 2. Experimental designs can also be characterized by their predictability, a measure of the ability to circumvent confounds such as habituation and anticipation. We examine the relation between detection power, estimation efficiency, and predictability and show that small increases in predictability can offer significant gains in detection power with only a minor decrease in estimation efficiency.

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