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Brain vascular health worsens with age, as is made evident by resting grey matter cerebral blood flow (CBF GM ) reductions and lengthening arterial transit time (ATT GM ). Exercise training can improve aspects of brain health in older adults, yet its effects on CBF GM and ATT GM remain unclear. This randomised controlled trial assessed responses of CBF GM and ATT GM to a 26 week exercise intervention in 65 healthy older adults (control: n = 33, exercise: n = 32, aged 60-81 years), including whether changes in CBF GM or ATT GM were associated with changes in cognitive functions. Multiple-delay pseudo-continuous arterial spin labelling data were used to estimate resting global and regional CBF GM and ATT GM . Results showed no between-group differences in CBF GM or ATT GM following the intervention. However, exercise participants with the greatest cardiorespiratory gains (n = 17; ∆V̇O 2peak >2 mL/kg/min) experienced global CBF GM reductions (-4.0 [-7.3, -0.8] mL/100 g/min). Cognitive functions did not change in either group and changes were not associated with changes in CBF GM or ATT GM . Our findings indicate that exercise training in older adults may induce global CBF GM reductions when high cardiorespiratory fitness gains are induced, but this does not appear to affect cognitive functions., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Katrien Segaert reports financial support was provided by the Research Council of Norway. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

Endothelial dysfunction is considered a key element in the early pathogenesis of neurodegenerative disorders. Dysfunction of the cerebral endothelial cells can result in dysregulation of cerebral perfusion and disruption of the Blood Brain Barrier (BBB), leading to brain damage, neurodegeneration and cognitive decline. It has been shown that the presence of modifiable risk factors exacerbates endothelial dysfunction. This study primarily aimed to identify which among various perfusion MRI methodologies could be effectively utilized to non-invasively identify early pathological alterations as a result of endothelial dysfunction. We compared these perfusion MRI measurements to invasive immunohistochemistry to detect early pathological alterations in the cerebral vasculature of a rat model of multiple cardiovascular co-morbidities (the ZSF1 Obese rat) at several stages of the cerebrovascular pathology. We observed cerebral hyperperfusion, expressed by increased Cerebral Blood Flow (CBF) and increased BBB permeability in the ZSF1 Obese rats, at an early stage of disease development. The increase in CBF observed with Arterial Spin Labeling (ASL) was lost during later stages of disease progression. These findings are in line with recent clinical findings in early stages of Alzheimer's disease (AD), that also show early increases in CBF., Competing Interests: Declaration of competing interest Elizabeth A.V. Jones reports financial support was provided by Horizon Europe. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Purpose: To analyze the characteristics of cerebral blood flow changes of poor sleep quality in people with epilepsy(PWE)., Methods: 90 PWE treated in The General Hospital of Ningxia Medical University from December 2021 to September 2023 were divided into poor sleep quality group (PSQG) and good sleep quality group (GSQG) according to the Chinese version of the Pittsburgh Sleep Quality Index (CPSQI), to compare the differences in cerebral perfusion between the two groups of patients, so as to summarize the characteristics of cerebral blood flow changes of poor sleep quality in PWE., Results: The positive rate of interictal single-photon emission computed tomography/computed tomography (SPECT/CT) was 76.7 %(69/90), which showed localized cerebral hypoperfusion. There was no statistical difference between the two groups of PSQG (N=29) and GSQG (N=61) in terms of the positive rate of SPECT/CT, the number of hypoperfusion foci, and the range of hypoperfusion foci. In PSQG and GSQG, 9 patients(31.0 %) and 6 patients(9.8 %) showed hypoperfusion in the right parietal lobe, respectively, and the difference between the two groups was statistically significant (P=0.017). There was no statistical difference the rate of the interictal epileptiform discharges (IEDs) and the brain area of IEDs in electroencephalography(EEG) between the two groups., Conclusion: SPECT/CT of poor sleep quality in PWE demonstrated hypoperfusion in the right parietal lobe., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Objective: This study aimed to identify the factors associated with insomnia in MRI-negative epilepsy and uncover the underlying pathological mechanism driving insomnia within the context of epilepsy., Methods: We conducted a retrospective study of patients with MRI-negative epilepsy recruited consecutively from December 2021 to December 2022. All subjects completed the Insomnia Severity Index (ISI), Epworth Sleepiness Scale (ESS), Self-rating Anxiety Scale (SAS), and Self-rating Depression Scale (SDS). Additionally, some subjects underwent the three-dimensional pseudo continuous arterial spin labeling(3D-pCASL) imaging examination. Bilateral frontal lobe, temporal lobe, hippocampus, thalamus, amygdala, caudate nucleus and lenticular nucleus were selected as regions of interest(ROI) and cerebral blood flow(CBF) values were measured in these regions. Subjects were classified into insomnia (ISI ≥ 10) or non-insomnia (ISI < 10) groups, and univariate and stepwise logistic regression analyses were employed to identify the factors associated with insomnia. Furthermore, CBF values in each ROI were compared between the two groups to identify the brain regions potentially related to the underlying pathological mechanism of insomnia in epilepsy., Results: A total of 73 patients with MRI-negative epilepsy were recruited in this study(men, 49.3 %). Among them, 14 patients(19.2 %) had insomnia. Univariate regression revealed that nocturnal seizures, number of anti-seizure medication(ASM), anxiety, use of valproic acid(VPA), depression, and excessive daytime sleepiness(EDS) may be associated with insomnia in MRI-negative epilepsy (all p＜0.05). Stepwise regression demonstrated that nocturnal seizures, anxiety, and EDS were independently associated with insomnia in MRI-negative epilepsy (OR[95 %CI]P: 14.64[2.02-106.27]0.008,49.35[3.06-796.61]0.006, 13.28[1.25-140.66]0.032, respectively). Furthermore, CBF values in the left amygdala were significantly lower in patients with MRI- negative epilepsy who had insomnia., Conclusion: The prevalence of insomnia in MRI-negative epilepsy is 19.2%. Nocturnal seizures, anxiety, and EDS were independently associated with insomnia in MRI-negative epilepsy. The noteworthy decrease in CBF values in the left amygdala might be connected to the underlying pathological mechanism of insomnia in epilepsy., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

A single bout of exercise improves executive function (EF) and is a benefit - in part -attributed to an exercise-mediated increase in cerebral blood flow enhancing neural efficiency. Limited work has used an event-related protocol to examine postexercise changes in preparatory phase cerebral hemodynamics for an EF task. This is salient given the neural efficiency hypothesis' assertion that improved EF is related to decreased brain activity. Here, event-related transcranial Doppler ultrasound was used to measure pro- (saccade to target) and antisaccades (saccade mirror-symmetrical target) preparatory phase middle cerebral artery velocity (MCAv) prior to and immediately after 15-min of aerobic exercise. Antisaccades produced longer reaction times (RT) and an increased preparatory phase MCAv than prosaccades - a result attributed to greater EF neural activity for antisaccades. Antisaccades selectively produced a postexercise RT reduction (ps < 0.01); however, antisaccade preparatory phase MCAv did not vary from pre- to postexercise (p=0.53) and did not correlate with the antisaccade RT benefit (p = 0.31). Accordingly, results provide no evidence that improved neural efficiency indexed via functional hyperemia is linked to a postexercise EF behavioural benefit. Instead, results support an evolving view that an EF benefit represents the additive interplay between interdependent exercise-mediated neurophysiological changes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Cerebrovascular diseases continue to be one of the leading causes of morbidity and mortality in humans. Abnormalities in dynamic cerebral autoregulation (dCA) have been implicated in many of these disease conditions. Accurate models are therefore needed to better understand the complex pathophysiology behind impaired dCA. We thus present here a simple framework for modelling a vessel-driven network model of dCA in the microvasculature, as opposed to the conventional compartmental modelling approach. Network models incorporate the actual connectivity and anatomy of the vasculature, thereby allowing us to include and trace changes in the calibre and morphology of individual vessels, investigate the spatial specificity and heterogeneity of the various control mechanisms to help disentangle their contributions, and link the model parameters to the actual network physiology. The proposed control feedback mechanisms are incorporated at the level of the individual vessel, and the dynamic pressure and flow fields are solved for here within a simple vessel network. In response to an upstream pressure drop, the network is found to be able to recover cerebral blood flow (CBF) while exhibiting the characteristic autoregulatory behaviour in terms of changes in vessel calibre and the biphasic flow response. We assess the feasibility of our formulation in larger networks by comparing the simulation results to those obtained using a one-dimensional (1D) model of CBF applied to the same microvasculature network and find that our model results are in very good agreement with the 1D solution, while significantly reducing the computational cost, thus enabling more detailed models of network behaviour to be adopted in the future. Accurate and computationally feasible models of dCA that are more representative of the vasculature can help increase the translatability of haemodynamic models into the clinical environment, which would help develop more informed treatment guidelines for patients with cerebrovascular diseases., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Functional MRI using blood oxygenation level-dependent (BOLD) contrast indirectly probes neuronal activity via evoked cerebral blood volume (CBV) and oxygenation changes. Thus, its spatio-temporal characteristics are determined by vascular physiology and MRI parameters. In this paper, we focus on the spatial distribution and time course of the fMRI signal and their magnetic field strength dependence. Even though much is still unknown, the following consistent picture is emerging: a) For high spatial resolution imaging, fMRI contrast-to-noise increases supra-linearly with field strength. b) The location and spacing of penetrating arteries and ascending veins in the cortical tissue are not correlated to cortical columns, imposing limitations on achievable point-spread function (PSF) in fMRI. c) Baseline CBV distribution may vary over cortical layers biasing fMRI signal to layers with high CBV values. d) The largest CBV change is in the tissue microvasculature, less in surface arteries and even less in pial veins. e) Venous CBV changes are only relevant for longer stimuli, and oxygenation changes are largest in post-capillary blood vessels. f) The balloon effect (i.e. slow recovery of CBV to baseline) is located in the tissue, consistent with the fact that the post-stimulus undershoot has narrower spatial PSF than the positive BOLD response. g) The onset time following stimulation has been found to be shortest in middle/lower layers, both in optical imaging and high-resolution fMRI, but we argue and demonstrate with simulations that varying signal latencies can also be caused by vascular properties and, therefore, may potentially not be interpreted as neural latencies. With simulations, we illustrate the field strength dependency of fMRI signal transients, such as the adaptation during stimulation, initial dip and the post-stimulus undershoot. In sum, vascular structure and function impose limitations on the achievable PSF of fMRI and give rise to complex fMRI transients, which contain time-varying amount of excitatory and inhibitory neuronal information. Nevertheless, non-invasive fMRI at ultra-high magnetic fields not only provides high contrast-to-noise but also an unprecedented detailed view on cognitive processes in the human brain., (Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.)

In this paper, we introduce a new locally multivariate procedure to quantitatively extract voxel-wise patterns of abnormal perfusion in individual patients. This a contrario approach uses a multivariate metric from the computer vision community that is suitable to detect abnormalities even in the presence of closeby hypo- and hyper-perfusions. This method takes into account local information without applying Gaussian smoothing to the data. Furthermore, to improve on the standard a contrario approach, which assumes white noise, we introduce an updated a contrario approach that takes into account the spatial coherency of the noise in the probability estimation. Validation is undertaken on a dataset of 25 patients diagnosed with brain tumours and 61 healthy volunteers. We show how the a contrario approach outperforms the massively univariate general linear model usually employed for this type of analysis., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Establishing baseline MRI biomarkers for normal brain aging is significant and valuable for separating normal changes in the brain structure and function from different neurological diseases. In this paper for the first time we have simultaneously measured a variety of tissue specific contributions defining R2* relaxation of the gradient recalled echo (GRE) MRI signal in human brains of healthy adults (ages 22 to 74years) and related these measurements to tissue structural and functional properties. This was accomplished by separating tissue (R2t(⁎)) and extravascular BOLD contributions to the total tissue specific GRE MRI signal decay (R2(⁎)) using an advanced version of previously developed Gradient Echo Plural Contrast Imaging (GEPCI) approach and the acquisition and post-processing methods that allowed the minimization of artifacts related to macroscopic magnetic field inhomogeneities, and physiological fluctuations. Our data (20 healthy subjects) show that in most cortical regions R2t(⁎) increases with age while tissue hemodynamic parameters, i.e. relative oxygen extraction fraction (OEFrel), deoxygenated cerebral blood volume (dCBV) and tissue concentration of deoxyhemoglobin (Cdeoxy) remain practically constant. We also found the important correlations characterizing the relationships between brain structural and hemodynamic properties in different brain regions. Specifically, thicker cortical regions have lower R2t(⁎) and these regions have lower OEF. The comparison between GEPCI-derived tissue specific structural and functional metrics and literature information suggests that (a) regions in a brain characterized by higher R2t(⁎) contain higher concentration of neurons with less developed cellular processes (dendrites, spines, etc.), (b) regions in a brain characterized by lower R2t(⁎) represent regions with lower concentration of neurons but more developed cellular processes, and (c) the age-related increases in the cortical R2t(⁎) mostly reflect the age-related increases in the cellular packing density. The baseline GEPCI-based biomarkers obtain herein could serve to help distinguish age-related changes in brain cellular and hemodynamic properties from changes which occur due to the neurodegenerative diseases., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Diffuse optical tomography (DOT) has been used by several groups to assess cerebral hemodynamics of cerebral ischemia in humans and animals. In this study, we combined DOT with an indocyanine green (ICG)-tracking method to achieve interleaved images of cerebral hemodynamics and blood flow index (BFI) using two middle cerebral artery occlusion (MCAO) rat models. To achieve volumetric images with high-spatial resolution, we first integrated a depth compensation algorithm (DCA) with a volumetric mesh-based rat head model to generate three-dimensional (3D) DOT on a rat brain atlas. Then, the experimental DOT data from two rat models were collected using interleaved strategy for cerebral hemodynamics and BFI during and after ischemic stroke, with and without a thrombolytic therapy for the embolic MCAO model. The acquired animal data were further analyzed using the integrated rat-atlas-guided DOT method to form time-evolving 3D images of both cerebral hemodynamics and BFI. In particular, we were able to show and identify therapeutic outcomes of a thrombolytic treatment applied to the embolism-induced ischemic model. This paper demonstrates that volumetric DOT is capable of providing high-quality, interleaved images of cerebral hemodynamics and blood perfusion in small animals during and after ischemic stroke, with excellent 3D visualization and quantifications., (© 2013 Elsevier Inc. All rights reserved.)

In this paper, patient-specific perfusion abnormalities in Arterial Spin Labeling (ASL) were identified by comparing a single patient to a group of healthy controls using a mixed-effect hierarchical General Linear Model (GLM). Two approaches are currently in use to solve hierarchical GLMs: (1) the homoscedastic approach assumes homogeneous variances across subjects and (2) the heteroscedastic approach is theoretically more efficient in the presence of heterogeneous variances but algorithmically more demanding. In practice, in functional magnetic resonance imaging studies, the superiority of the heteroscedastic approach is still under debate. Due to the low signal-to-noise ratio of ASL sequences, within-subject variances have a significant impact on the estimated perfusion maps and the heteroscedastic model might be better suited in this context. In this paper we studied how the homoscedastic and heteroscedastic approaches behave in terms of specificity and sensitivity in the detection of patient-specific ASL perfusion abnormalities. Validation was undertaken on a dataset of 25 patients diagnosed with brain tumors and 36 healthy volunteers. We showed evidence of heterogeneous within-subject variances in ASL and pointed out an increased false positive rate of the homoscedastic model. In the detection of patient-specific brain perfusion abnormalities with ASL, modeling heterogeneous variances increases the sensitivity at the same specificity level., (Copyright © 2013 Elsevier Inc. All rights reserved.)

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., (Copyright © 2013 Elsevier Inc. All rights reserved.)

In this paper the cerebral blood flow (CBF) in resting state obtained from SPECT imaging is employed as a hemodynamics descriptor to study the concurrent changes between brain structures and to build binarized connectivity graphs. The statistical similarity in CBF between pairs of regions was measured by computing the Pearson correlation coefficient across 31 normal subjects. We demonstrated the CBF connectivity matrices follow 'small-world' attributes similar to previous studies using different modalities of neuroimaging data (MRI, fMRI, EEG, MEG). The highest concurrent fluctuations in CBF were detected between homologous cortical regions (homologous callosal connections). It was found that the existence of structural core regions or hubs positioned on a high proportion of shortest paths within the CBF network. These were anatomically distributed in frontal, limbic, occipital and parietal regions that suggest its important role in functional integration. Our findings point to a new possibility of using CBF variable to investigate the brain networks based on graph theory in normal and pathological states. Likewise, it opens a window to future studies to link covariation between morphometric descriptors, axonal connectivity and CBF processes with a potential diagnosis applications., (Copyright © 2012 Elsevier Inc. All rights reserved.)

This paper presents a state-space hemodynamic model by which any event-related hemodynamic prediction function (i.e., the basis function of the design matrix in the general linear model) is obtained as an output of the model. To model the actual event-related behavior during a task period (intra-activity dynamics) besides the contrasting behavior among the different task periods and against the rest periods (inter-activity dynamics), the modular system is investigated by parametric subspace-based state-space modeling of actual hemodynamic response to an impulse stimulus. This model provides a simple and computationally efficient way to generate the event-related basis function for an experiment by just convolving the developed hemodynamic model with the impulse approximation of the experimental stimuli. The demonstration of the stated findings is carried out by conducting finger-related experiments with slow- and fast-sampling near-infrared spectroscopy instruments to model and validate the cortical hemodynamic responses. The generated basis functions of the finger-related experiments are adapted from real data to validate the incorporation of non-delayed and real-time event-related features and to effectively demonstrate a dynamic-modeling-based online framework. The proposed method demonstrates potential in estimating event-related intra- and inter-activation dynamics and thereby outperforms the classical Gaussian approximation method., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Brain's electrical activity correlates strongly to changes in cerebral blood flow (CBF) and the cerebral metabolic rate of oxygen (CMRO(2)). Subthreshold synaptic processes correlate better than the spike rates of principal neurons to CBF, CMRO(2) and positive BOLD signals. Stimulation-induced rises in CMRO(2) are controlled by the ATP turnover, which depends on the energy used to fuel the Na,K-ATPase to reestablish ionic gradients, while stimulation-induced CBF responses to a large extent are controlled by mechanisms that depend on Ca(2+) rises in neurons and astrocytes. This dichotomy of metabolic and vascular control explains the gap between the stimulation-induced rises in CMRO(2) and CBF, and in turn the BOLD signal. Activity-dependent rises in CBF and CMRO(2) vary within and between brain regions due to differences in ATP turnover and Ca(2+)-dependent mechanisms. Nerve cells produce and release vasodilators that evoke positive BOLD signals, while the mechanisms that control negative BOLD signals by activity-dependent vasoconstriction are less well understood. Activation of both excitatory and inhibitory neurons produces rises in CBF and positive BOLD signals, while negative BOLD signals under most conditions correlate to excitation of inhibitory interneurons, but there are important exceptions to that rule as described in this paper. Thus, variations in the balance between synaptic excitation and inhibition contribute dynamically to the control of metabolic and hemodynamic responses, and in turn the amplitude and polarity of the BOLD signal. Therefore, it is not possible based on a negative or positive BOLD signal alone to decide whether the underlying activity goes on in principal or inhibitory neurons., (Copyright © 2012 Elsevier Inc. All rights reserved.)

This paper provides a brief overview of how we got involved in fMRI work and of our efforts to elucidate the mechanisms underlying BOLD signal changes. The phenomenon discussed here in particular is the post-stimulus undershoot (PSU), the interpretation of which has captivated many fMRI scientists and is still under debate to date. This controversy is caused both by the convoluted physiological origin of the BOLD effect, which allows many possible explanations, and the lack of comprehensive data in the early years. BOLD effects reflect changes in cerebral blood flow (CBF), volume (CBV), metabolic rate of oxygen (CMRO(2)), and hematocrit fraction (Hct). However, the size of such effects is modulated by vascular origin such as intravascular, extravascular, macro and microvascular, venular and capillary, the relative contributions of which depend not only on the spatial resolution of the measurements, but also on stimulus duration, on magnetic field strength and on whether spin echo (SE) or gradient echo (GRE) detection is used. The two most dominant explanations of the PSU have been delayed vascular compliance (first venular, later arteriolar, and recently capillary) and sustained increases in CMRO(2), while post-activation reduction in CBF is a distant third. MRI has the capability to independently measure CBF and arteriolar, venous, and total CBV contributions in humans and animals, which has been of great assistance in improving the understanding of BOLD phenomena. Using currently available MRI and optical data, we conclude that the predominant PSU origin is a sustained increase in CMRO(2). However, some contributions from delayed vascular compliance are likely, and small CBF undershoot contributions that are difficult to detect with current arterial spin labeling technology can also not be excluded. The relative contribution of these different processes, which are not mutually exclusive and can act together, is likely to vary with stimulus duration and type., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Acetylcholinesterase inhibitors (AChEIs), such as donepezil, have been shown to improve cognition in mild to moderate Alzheimer's disease (AD) patients. In this paper, our goal is to determine the relationship between altered cerebral blood flow (CBF) and intrinsic functional network connectivity changes in mild AD patients before and after 12-week donepezil treatment. An integrative neuroimaging approach was employed by combining pseudocontinuous arterial spin labeling (pCASL) MRI and resting-state functional MRI (R-fMRI) methods to determine the changes in CBF and functional connectivity (FC) in the cholinergic pathway. Linear regression analyses determined the correlations of the regional CBF alterations and functional connectivity changes with cognitive responses. These were measured with the Mini-Mental Status Examination (MMSE) scores and Alzheimer's disease Assessment Scale-Cognitive subscale (ADAS-cog) scores. Our results show that the regional CBF in mild AD subjects after donepezil treatment was significantly increased in the middle cingulate cortex (MCC) and posterior cingulate cortex (PCC), which are the neural substrates of the medial cholinergic pathway. In both brain regions, the baseline CBF and its changes after treatment were significantly correlated with the behavioral changes in ADAS-cog scores. The intrinsic FC was significantly enhanced in the medial cholinergic pathway network in the brain areas of the parahippocampal, temporal, parietal and prefrontal cortices. Finally, the FC changes in the medial prefrontal areas demonstrated an association with the CBF level in the MCC and the PCC, and also were correlated with ADAS-cog score changes. These findings indicate that regional CBF and FC network changes in the medial cholinergic pathway were associated with cognitive performance. It also is suggested that the combined pCASL-MRI and R-fMRI methods could be used to detect regional CBF and FC changes when using drug treatments in mild AD subjects., (Copyright © 2012 Elsevier Inc. All rights reserved.)

In a companion paper (Lorthois et al., Neuroimage, in press), we perform the first simulations of blood flow in an anatomically accurate large human intra-cortical vascular network (~10000 segments), using a 1D non-linear model taking into account the complex rheological properties of blood flow in microcirculation. This model predicts blood pressure, blood flow and hematocrit distributions, volumes of functional vascular territories, regional flow at voxel and network scales, etc. Using the same approach, we study flow reorganizations induced by global arteriolar vasodilations (an isometabolic global increase in cerebral blood flow). For small to moderate global vasodilations, the relationship between changes in volume and changes in flow is in close agreement with Grubb's law, providing a quantitative tool for studying the variations of its exponent with underlying vascular architecture. A significant correlation between blood flow and vascular structure at the voxel scale, practically unchanged with respect to baseline, is demonstrated. Furthermore, the effects of localized arteriolar vasodilations, representative of a local increase in metabolic demand, are analyzed. In particular, localized vasodilations induce flow changes, including vascular steal, in the neighboring arteriolar trunks at small distances (<300 μm), while their influence in the neighboring veins is much larger (about 1 mm), which provides an estimate of the vascular point spread function. More generally, for the first time, the hemodynamic component of various functional neuroimaging techniques has been isolated from metabolic and neuronal components, and a direct relationship with several known characteristics of the BOLD signal has been demonstrated., (Copyright © 2010 Elsevier Inc. All rights reserved.)

Despite the fact that emotions involve multiple time-varying components, little is known about the underlying neural basis of these temporal dynamics. In this paper, we assess these temporal dynamics by using time-varying hemodynamic response functions (HRF) to model BOLD responses to emotional stimuli. We show that these time-varying HRFs lead to a better fit to the BOLD data and yield larger areas of significant activation than do conventional gamma-based canonical HRFs. We also report for the first time that intensity of emotional experience is associated with both magnitude and duration of brain activation. Specifically, greater negative emotional intensity was associated with greater magnitude of activation in the occipital cortex and with longer duration of activation in regions along the cortical midline associated with self-referent processing: the anterior medial prefrontal cortex and the posterior cingulate cortex. These data significantly advance our understanding of how the brain processes emotion and suggest that the intensity of a negative emotional experience is due in part to elaborative self-referent processing that is captured by the duration of neural activity in cortical midline structures. These data also underscore the importance of using modeling techniques that will help elucidate the chronometry of both normal and psychopathological emotional processes.

The difference between the rate of change of cerebral blood volume (CBV) and cerebral blood flow (CBF) following stimulation is thought to be due to circumferential stress relaxation in veins (Mandeville, J.B., Marota, J.J.A., Ayata, C., Zaharchuk, G., Moskowitz, M.A., Rosen, B.R., Weisskoff, R.M., 1999. Evidence of a cerebrovascular postarteriole windkessel with delayed compliance. J. Cereb. Blood Flow Metab. 19, 679-689). In this paper we explore the visco-elastic properties of blood vessels, and present a dynamic model relating changes in CBF to changes in CBV. We refer to this model as the visco-elastic windkessel (VW) model. A novel feature of this model is that the parameter characterising the pressure-volume relationship of blood vessels is treated as a state variable dependent on the rate of change of CBV, producing hysteresis in the pressure-volume space during vessel dilation and contraction. The VW model is nonlinear time-invariant, and is able to predict the observed differences between the time series of CBV and that of CBF measurements following changes in neural activity. Like the windkessel model derived by Mandeville, J.B., Marota, J.J.A., Ayata, C., Zaharchuk, G., Moskowitz, M.A., Rosen, B.R., Weisskoff, R.M., 1999. Evidence of a cerebrovascular postarteriole windkessel with delayed compliance. J. Cereb. Blood Flow Metab. 19, 679-689, the VW model is primarily a model of haemodynamic changes in the venous compartment. The VW model is demonstrated to have the following characteristics typical of visco-elastic materials: (1) hysteresis, (2) creep, and (3) stress relaxation, hence it provides a unified model of the visco-elastic properties of the vasculature. The model will not only contribute to the interpretation of the Blood Oxygen Level Dependent (BOLD) signals from functional Magnetic Resonance Imaging (fMRI) experiments, but also find applications in the study and modelling of the brain vasculature and the haemodynamics of circulatory and cardiovascular systems.

Signal variations in functional Magnetic Resonance Imaging experiments essentially reflect the vascular system response to increased demand for oxygen caused by neuronal activity, termed the blood oxygenation level dependent (BOLD) effect. The most comprehensive model to date of the BOLD signal is formulated as a mixed continuous-discrete-time system of nonlinear stochastic differential equations. Previous approaches to the analysis of this system have been based on linearised approximations of the dynamics, which are limited in their ability to capture the inherent nonlinearities in the physiological system. In this paper we present a nonlinear filtering method for simultaneous estimation of the hidden physiological states and the system parameters, based on an iterative coordinate descent framework. State estimates of the cerebral blood flow, cerebral blood volume and deoxyhaemoglobin content are determined using a particle filter, demonstrated via simulation to be accurate, robust and efficient in comparison to linearisation-based techniques. The adaptive state and parameter estimation algorithm generates physiologically reasonable parameter estimates for experimental fMRI data. It is anticipated that signal processing techniques for modelling and estimation will become increasingly important in fMRI analyses as limitations of linear and linearised modelling are reached.

Like cerebral blood flow (CBF), cerebral blood volume (CBV) is an important physiological parameter closely associated with brain activity and thus, noninvasive quantification of CBV during brain activation provides another opportunity to investigate the relationship between neuronal activity and hemodynamic changes. In this paper, a new method is presented that is able to quantify CBV at rest and during activation. Specifically, using an inversion recovery pulse sequence, a set of brain images was collected at various inversion times (TIs). At each TI, functional images were acquired with a block-design visual stimulation paradigm. A biophysical model comprised of multiple tissue components was developed and was utilized for the determination of CBV using the visual stimulation data. MRI experiments on five healthy volunteers showed that CBV was 5.0 +/- 1.5 ml blood/100 ml brain during rest and increased to 6.6 +/- 1.8 ml blood/100 ml brain following visual stimulation. Furthermore, experiments with visual stimulation at two frequencies (2 and 8 Hz) showed that the increases in CBV correlated with the strength of stimulation. This technique, with its ability to measure quantitative CBV values noninvasively, provides a valuable tool for quantifying hemodynamic signals associated with brain activation.

Several authors have suggested allowing for unknown latency of the hemodynamic response by incorporation of hemodynamic derivative terms into the linear model for the statistical analysis of fMRI data. In this paper, we show how to use random field theory to provide a P value for local maxima of two test statistics that have been recently proposed for detecting activation based on this analysis.

Near infrared spectroscopy (NIRS) can detect vascular changes in cerebral cortical tissue elicited by functional stimulation. For some 10 years, another optical signal has been reported to be accessible by NIRS. This signal has been reported to correlate to the electrophysiological response rendering NIRS an exquisite non-invasive approach to investigate neurovascular coupling in the human adult. Due to their typical latency of up to hundreds of milliseconds, these signals have been termed "fast" optical signals and have been postulated to stem from scatter changes in neuronal tissue, as a fingerprint of the electrophysiological response. Here, we utter a less optimistic view on the non-invasive detectability of these changes in the human, motivated by an upper limit signal size estimation, predicting a signal size by orders of magnitude smaller than those previously reported. Also, we discuss the influence of small stimulus correlated movement artifacts potentially mimicking a fast optical signal. Based on invasive studies, we perform an upper limit estimation for changes in intensity and mean time of flight, which can be expected assuming a scatter change in the cerebral cortex while measuring on the surface of the head of an adult subject. Since the resulting numbers are far below those previously reported, we constructed a simple system, which minimizes technical noise. The system allows us to detect rather small intensity changes (2 x 10(-3)%) when averaging over approximately 3000 stimuli. Despite this outstandingly low noise level of the system, we find a reliable change in response to a sub-motor-threshold steady state median nerve stimulation in just one single subject (8 subjects examined, 4 subjects twice). Exceeding the motor threshold leads to large stimulus related artifacts, on a similar time scale and with comparable amplitude as previously reported signals. To check for potential modality specific problems, we next performed a visual stimulation study, avoiding potential motor artifacts. For the steady state visually evoked response, no subject yielded a reliable result (11 subjects examined, 4 subjects twice). The paper discusses these findings by a review of the literature on fast optical signals and their being accessible in the adult human.

Visual assessment, with significant inter- or intraobserver variability, is still the norm for the evaluation of Single Photon Emission Computerized Tomography (SPECT) cerebral perfusion studies. We present in this paper an automated method for screening SPECT studies to detect diffuse disseminated abnormalities based on a computerized atlas of normal regional cerebral blood flow (rCBF). To generate the atlas, a set of normal brain SPECT studies are registered together. The atlas contains the intensity mean, the nonlinear displacement mean, and the variance of the activity pattern. A patient is then evaluated by registering his or her SPECT volume to the atlas and computing the nonlinear 3-D displacement of each voxel needed for the best shape fit to it. A voxel is counted as "abnormal" if the intensity difference between the atlas and the registered patient (or if the 3-D motion necessary to move the voxel to its registered position) is superior to 3 SD of normal mean. The number of abnormal voxels is used to classify studies. We validated this approach on 24 SPECT perfusion studies selected visually for having clear diffuse anomalies and 21 normal studies. A Markovian segmentation algorithm is also used to identify the white and gray matters for regional analysis. Based on the number of abnormal voxels, two supervised classifiers were tested: (1) minimum distance-to-mean and (2) Bayesian. The analysis of the intensity and displacement "abnormal" voxels allow one to achieve an 80% correct classification rate for the whole brain and a 93% rate if we consider only voxels in the segmented gray matter region.

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 (CMRO(2)) 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.

Local signals obtained from BOLD fMRI are generally confounded by global effects. In this paper, we make an essential distinction between global effects and the global signal. Global effects have a similar influence on local signals from a large proportion of cerebral voxels. They may reflect diffuse physiological processes or variations in scanner sensitivity and are difficult to measure directly. Global effects are often estimated from the global signal, which is the spatial average of local signals from all cerebral voxels. If the global signal is strongly correlated with experimental manipulations, meaningfully different results may be obtained whether or not global effects are modeled (G. K. Aguirre et al., 1998, NeuroImage, 8, 302-306). In particular, if local BOLD signals make a significant contribution to the global signal, analyses using ANCOVAor proportional scaling models may yield artifactual deactivations. In this paper, we present a modification to the proportional scaling model that accounts for the contribution of local BOLD signals to the global signal. An event-related oddball stimulus paradigm and a block design working memory task were used to illustrate the efficacy of our model., (Copyright 2001 Academic Press.)

Almost all methods of detecting brain activation in fMRI data depend on prior knowledge of mental event timing. For example, the investigator may be required to stipulate the short time intervals during which mental activity occurs. In addition, the hemodynamic response to mental activity is often assumed to be linearly additive, and the shape of that response is frequently estimated or modeled. Analysis methods that do not make these assumptions still require prior knowledge of characteristics of the spatial distribution of neural activity. This paper describes a new method of analyzing fMRI data that does not rely on any of these assumptions. Instead, our approach is based on the following simple premise: the time course of signal in activated voxels will not vary significantly when an entire task protocol is repeated by the same individual. The model-independence of this approach makes it suitable for "screening" fMRI data for brain activation that may have unanticipated timing. Retrospective examination of the time course of the detected signals may be used to understand the nature of the activity. We demonstrate the method by using it to detect brain activation in two subjects who performed hand sensorimotor tasks according to block and single-trial designs., (Copyright 2001 Academic Press.)

Statistical parametric mapping (SPM) is currently the most widely used method for analysis of functional activation images. This paper reports a quantitative evaluation of the sensitivity and accuracy of SPM, using a realistic simulator of PET image formation, which accounted for the main physical processes involved in PET, including attenuation, scatter, randoms, Poisson noise, and limited detector resolution. Activation foci of the brain were simulated by placing spheres of specified activities in particular locations. Using these data, the sensitivity and accuracy of SPM in detecting activation foci was measured for different versions of the SPM spatial normalization method and for an elastic warping method referred to as STAR (spatial transformation algorithm for registration). The STAR method resulted in relatively better registration and hence better detection of the activation foci. A secondary goal of the paper was to evaluate the improvement in detection sensitivity obtained by applying an atlas-based adaptive smoothing method instead of the usual Gaussian filtering method. The results indicate some limitations of statistical parametric mapping, assist in the correct interpretation of the SPM maps, and point to future research directions in functional image analysis., (Copyright 2001 Academic Press.)

There is a growing appreciation of the importance of nonlinearities in evoked responses in fMRI, particularly with the advent of event-related fMRI. These nonlinearities are commonly expressed as interactions among stimuli that can lead to the suppression and increased latency of responses to a stimulus that are incurred by a preceding stimulus. We have presented previously a model-free characterization of these effects using generic techniques from nonlinear system identification, namely a Volterra series formulation. At the same time Buxton et al. (1998) described a plausible and compelling dynamical model of hemodynamic signal transduction in fMRI. Subsequent work by Mandeville et al. (1999) provided important theoretical and empirical constraints on the form of the dynamic relationship between blood flow and volume that underpins the evolution of the fMRI signal. In this paper we combine these system identification and model-based approaches and ask whether the Balloon model is sufficient to account for the nonlinear behaviors observed in real time series. We conclude that it can, and furthermore the model parameters that ensue are biologically plausible. This conclusion is based on the observation that the Balloon model can produce Volterra kernels that emulate empirical kernels. To enable this evaluation we had to embed the Balloon model in a hemodynamic input-state-output model that included the dynamics of perfusion changes that are contingent on underlying synaptic activation. This paper presents (i) the full hemodynamic model (ii), how its associated Volterra kernels can be derived, and (iii) addresses the model's validity in relation to empirical nonlinear characterizations of evoked responses in fMRI and other neurophysiological constraints., (Copyright 2000 Academic Press.)

Low-frequency (4-12 cpm) spontaneous oscillations in cerebral blood flow are well known and their augmentation after nitric oxide synthase inhibition has recently been described. However, the presence of these oscillations in blood flow velocity in the capillary network of the brain has not been demonstrated. In this paper, low-frequency oscillations in red blood cell flow velocity in cortical capillaries using intravital video microscopy were studied before and after infusion of the nitric oxide synthase inhibitor N omega-nitro-L-arginine methyl ester (L-NAME). Fluorescein isothiocyanate-labeled red blood cells were injected intravenously and served as markers of capillary flow. Red cell velocity was measured by off-line image tracking. After infusion of L-NAME (30 mg/kg), red cell velocity decreased from an average of 1.0 +/- 0.1 mm/sec to 0.53 +/- 0.1 mm/sec. Simultaneously, low-frequency oscillations in velocity emerged as indicated by an 81 +/- 17% increase in standard deviation of the 4- to 8-cpm frequency components. There was a significant temporal correlation (r = 0.58, P < 0.01) in red cell velocity between neighboring capillaries after L-NAME. Principal component analysis suggested that the high temporal correlation was a consequence of low-frequency oscillations rather than phase. These results are consistent with a model in which low-frequency spontaneous oscillations in flow velocity are brought about by precapillary vasomotion. This study provides for the first time direct evidence for low-frequency synchronous oscillations of red cell flow velocity in the cerebral capillary network.