BOLD fMRI and hemodynamic responses to somatosensory stimulation in anesthetized mice: spontaneous breathing vs. mechanical ventilation

Mouse functional MRI (fMRI) has been of great interest due to the abundance of transgenic models. Due to a mouse's small size, spontaneous breathing has often been used. Because the vascular physiology affecting fMRI might not be controlled normally, its effects on functional responses were investigated with optical intrinsic signal (OIS) imaging and 9.4 T BOLD fMRI. Three conditions were tested in C57BL/6 mice: spontaneous breathing under ketamine and xylazine anesthesia (KX), mechanical ventilation under KX, and mechanical ventilation under isoflurane. Spontaneous breathing under KX induced an average pCO₂ of 83 mmHg, whereas a mechanical ventilation condition achieved a pCO₂ of 37-41 mmHg within a physiological range. The baseline diameter of arterial and venous vessels was only 7%-9% larger with spontaneous breathing than with mechanical ventilation under KX, but it was much smaller than that in normocapnic isoflurane-anesthetized mice. Three major functional studies were performed. First, CBV-weighted OIS and arterial dilations to 4-second forepaw stimulation were rapid and larger at normocapnia than hypercapnia under KX, but very small under isoflurane. Second, CBV-weighted OIS and arterial dilations by vasodilator acetazolamide were measured for investigating vascular reactivity and were larger in the normocapnic condition than in the hypercapnic condition under KX. Third, evoked OIS and BOLD fMRI responses in the contralateral mouse somatosensory cortex to 20-second forepaw stimulation were faster and larger in the mechanical ventilation than spontaneous breathing. BOLD fMRI peaked at the end of the 20-second stimulation under hypercapnic spontaneous breathing, and at ~9 seconds under mechanical ventilation. The peak amplitude of BOLD fMRI was 2.2% at hypercapnia and ~3.4% at normocapnia. Overall, spontaneous breathing induces sluggish reduced hemodynamic and fMRI responses, but it is still viable for KX anesthesia due to its simplicity, noninvasiveness, and well-localized BOLD activity in the somatosensory cortex.

Resting State BOLD Variability of the Posterior Medial Temporal Lobe Correlates with Cognitive Performance in Older Adults with and without Risk for Cognitive Decline

Local brain signal variability [SD of the BOLD signal (SDBOLD]] correlates with age and cognitive performance, and recently differentiated Alzheimer's disease (AD) patients from healthy controls. However, it is unknown whether changes to SDBOLD precede diagnosis of AD or mild cognitive impairment. We compared ostensibly healthy older adult humans who scored below the recommended threshold on the Montreal cognitive assessment (MoCA) and who showed reduced medial temporal lobe (MTL) volume in a previous study ("at-risk" group, n = 20), with healthy older adults who scored within the normal range on the MoCA ("control" group, n = 20). Using multivariate partial least-squares analysis we assessed the correlations between SDBOLD and age, MoCA score, global fractional anisotropy, global mean diffusivity, and four cognitive factors. Greater SDBOLD in the MTL and occipital cortex positively correlated with performance on cognitive control/speed tasks but negatively correlated with memory scores in the control group. These relations were weaker in the at-risk group. A post hoc analysis assessed associations between MTL volumes and SDBOLD in both groups. This revealed a negative correlation, most robust in the at-risk group, between MTL SDBOLD and MTL subregion volumetry, particularly the entorhinal and parahippocampal regions. Together, these results suggest that the association between SDBOLD and cognition differs between the at-risk and control groups, which may be because of lower MTL volumes in the at-risk group. Our data indicate relations between MTL SDBOLD and cognition may be helpful in understanding brain differences in individuals who may be at risk for further cognitive decline.

Scale-free functional brain dynamics during recovery from sport-related concussion

Studies using blood‐oxygenation‐level‐dependent functional magnetic resonance imaging (BOLD fMRI) have characterized how the resting brain is affected by concussion. The literature to date, however, has largely focused on measuring changes in the spatial organization of functional brain networks. In the present study, changes in the temporal dynamics of BOLD signals are examined throughout concussion recovery using scaling (or fractal) analysis. Imaging data were collected for 228 university‐level athletes, 61 with concussion and 167 athletic controls. Concussed athletes were scanned at the acute phase of injury (1–7 days postinjury), the subacute phase (8–14 days postinjury), medical clearance to return to sport (RTS), 1 month post‐RTS and 1 year post‐RTS. The wavelet leader multifractal approach was used to assess scaling (c₁) and multifractal (c₂) behavior. Significant longitudinal changes were identified for c₁, which was lowest at acute injury, became significantly elevated at RTS, and returned near control levels by 1 year post‐RTS. No longitudinal changes were identified for c₂. Secondary analyses showed that clinical measures of acute symptom severity and time to RTP were related to longitudinal changes in c₁. Athletes with both higher symptoms and prolonged recovery had elevated c₁ values at RTS, while athletes with higher symptoms but rapid recovery had reduced c₁ at acute injury. This study provides the first evidence for long‐term recovery of BOLD scale‐free brain dynamics after a concussion.

Neurometabolites and sport-related concussion: From acute injury to one year after medical clearance

Sport-related concussion is associated with acute disturbances in neurometabolic function, with effects that may last weeks to months after injury. However, is presently unknown whether these disturbances resolve at medical clearance to return to play (RTP) or continue to evolve over longer time intervals. Moreover, little is known about how these neurometabolic changes correlate with other measures of brain physiology. In this study, these gaps were addressed by evaluating ninety-nine (99) university-level athletes, including 33 with sport-related concussion and 66 without recent injury, using multi-parameter magnetic resonance imaging (MRI), which included single-voxel spectroscopy (SVS), diffusion tensor imaging (DTI) and resting-state functional MRI (fMRI). The concussed athletes were scanned at the acute phase of injury (27/33 imaged), medical clearance to RTP (25/33 imaged), one month post-RTP (25/33 imaged) and one year post-RTP (13/33 imaged). We measured longitudinal changes in N-acetyl aspartate (NAA) and myo-inositol (Ins), over the course of concussion recovery. Concussed athletes showed no significant abnormalities or longitudinal change in NAA values, whereas Ins was significantly elevated at RTP and one month later. Interestingly, Ins response was attenuated by a prior history of concussion. Subsequent analyses identified significant associations between Ins values, DTI measures of white matter microstructure and fMRI measures of functional connectivity. These associations varied over the course of concussion recovery, suggesting that elevated Ins values at RTP and beyond reflect distinct changes in brain physiology, compared to acute injury. These findings provide novel information about neurometabolic recovery after a sport-related concussion, with evidence of disturbances that persist beyond medical clearance to RTP.

Concurrent Imaging of Markers of Current Flow and Neurophysiological Changes During tDCS

Despite being a popular neuromodulation technique, clinical translation of transcranial direct current stimulation (tDCS) is hampered by variable responses observed within treatment cohorts. Addressing this challenge has been difficult due to the lack of an effective means of mapping the neuromodulatory electromagnetic fields together with the brain's response. In this study, we present a novel imaging technique that provides the capability of concurrently mapping markers of tDCS currents, as well as the brain's response to tDCS. A dual-echo echo-planar imaging (DE-EPI) sequence is used, wherein the phase of the acquired MRI-signal encodes the tDCS current induced magnetic field, while the magnitude encodes the blood oxygenation level dependent (BOLD) contrast. The proposed technique was first validated in a custom designed phantom. Subsequent test-retest experiments in human participants showed that tDCS-induced magnetic fields can be detected reliably in vivo. The concurrently acquired BOLD data revealed large-scale networks characteristic of a brain in resting-state as well as a 'cathodal' and an 'anodal' resting-state component under each electrode. Moreover, 'cathodal's BOLD-signal was observed to significantly decrease with the applied current at the group level in all datasets. With its ability to image markers of electromagnetic cause as well as neurophysiological changes, the proposed technique may provide an effective means to visualize neural engagement in tDCS at the group level. Our technique also contributes to addressing confounding factors in applying BOLD fMRI concurrently with tDCS.

Frequency-dependent electrical stimulation of fimbria-fornix preferentially affects the mesolimbic dopamine system or prefrontal cortex

BACKGROUND

The fimbria/fornix fiber system is an essential part of the hippocampal-VTA loop, and therefore activities that are propagated through this fiber system control the activity of the mesolimbic dopamine system.

OBJECTIVES/HYPOTHESIS

We hypothesized that stimulation of the fimbria/fornix with an increasing number of electrical pulses would cause increasing activity of the mesolimbic dopamine system, which coincides with concurrent changes in neuronal activities in target regions of the mesolimbic dopaminergic system.

METHODS

Right fimbria/fornix fibers were electrically stimulated with different pulse protocols. Stimulus-induced changes in neuronal activities were visualized with BOLD-fMRI, whereas stimulus-induced release of dopamine, as measured for the activity of the mesolimbic dopamine system, was determined in the nucleus accumbens with in vivo fast-scan cyclic voltammetry.

RESULTS

Dependent on the protocol, electrical fimbria/fornix stimulation caused BOLD responses in various targets of the mesolimbic dopamine system. Stimulation in the low theta frequency range (5 Hz) triggered significant BOLD responses mainly in the hippocampal formation, infralimbic cortex, and septum. Stimulation in the beta frequency range (20 Hz) caused additional activation in the medial prefrontal cortex (mPFC), nucleus accumbens, striatum, and VTA. Stimulation in the high-gamma frequency range (100 Hz) caused further activation in the hippocampus proper and mPFC. The strong activation in the mPFC during 100 Hz stimulations depended not only on the number of pulses but also on the frequency. Thus, short bursts of 5 or 20 high-frequency pulses caused stronger activation in the mPFC than continuous 5 or 20 Hz pulses. In contrast, high-frequency burst fimbria/fornix stimulation did not further activate the mesolimbic dopamine system when compared to continuous 5 or 20 Hz pulse stimulation.

CONCLUSIONS

There exists a frequency-dependent dissociation between BOLD responses and activation of the dopaminergic system. Low frequencies were more efficient to activate the mesolimbic dopamine system, whereas high frequencies were more efficient to trigger BOLD responses in target regions of the mesolimbic dopamine system, particularly the mPFC.

Key Aspects of Neurovascular Control Mediated by Specific Populations of Inhibitory Cortical Interneurons

Inhibitory interneurons can evoke vasodilation and vasoconstriction, making them potential cellular drivers of neurovascular coupling. However, the specific regulatory roles played by particular interneuron subpopulations remain unclear. Our purpose was therefore to adopt a cell-specific optogenetic approach to investigate how somatostatin (SST) and neuronal nitric oxide synthase (nNOS)-expressing interneurons might influence the neurovascular relationship. In mice, specific activation of SST- or nNOS-interneurons was sufficient to evoke hemodynamic changes. In the case of nNOS-interneurons, robust hemodynamic changes occurred with minimal changes in neural activity, suggesting that the ability of blood oxygen level dependent functional magnetic resonance imaging (BOLD fMRI) to reliably reflect changes in neuronal activity may be dependent on type of neuron recruited. Conversely, activation of SST-interneurons produced robust changes in evoked neural activity with shallow cortical excitation and pronounced deep layer cortical inhibition. Prolonged activation of SST-interneurons often resulted in an increase in blood volume in the centrally activated area with an accompanying decrease in blood volume in the surrounding brain regions, analogous to the negative BOLD signal. These results demonstrate the role of specific populations of cortical interneurons in the active control of neurovascular function.

EEG microstates are correlated with brain functional networks during slow-wave sleep

Electroencephalography (EEG) microstates have been extensively studied in wakefulness and have been described as the "atoms of thought". Previous studies of EEG have found four microstates, i.e., microstates A, B, C and D, that are consistent among participants across the lifespan during the resting state. Studies using simultaneous EEG and functional magnetic resonance imaging (fMRI) have provided evidence for correlations between EEG microstates and fMRI networks during the resting state. Microstates have also been found during non-rapid eye movement (NREM) sleep. Slow-wave sleep (SWS) is considered the most restorative sleep stage and has been associated with the maintenance of sleep. However, the relationship between EEG microstates and brain functional networks during SWS has not yet been investigated. In this study, simultaneous EEG-fMRI data were collected during SWS to test the correspondence between EEG microstates and fMRI networks. EEG microstate-informed fMRI analysis revealed that three out of the four microstates showed significant correlations with fMRI data: 1) fMRI fluctuations in the insula and posterior temporal gyrus positively correlated with microstate B, 2) fMRI signals in the middle temporal gyrus and fusiform gyrus negatively correlated with microstate C, and 3) fMRI fluctuations in the occipital lobe negatively correlated with microstate D, while fMRI signals in the anterior cingulate and cingulate gyrus positively correlated with this microstate. Functional brain networks were then assessed using group independent component analysis based on the fMRI data. The group-level spatial correlation analysis showed that the fMRI auditory network overlapped the fMRI activation map of microstate B, the executive control network overlapped the fMRI deactivation of microstate C, and the visual and salience networks overlapped the fMRI deactivation and activation maps of microstate D. In addition, the subject-level spatial correlations between the general linear model (GLM) beta map of each microstate and the individual maps of each component yielded by dual regression also showed that EEG microstates were closely associated with brain functional networks measured using fMRI during SWS. Overall, the results showed that EEG microstates were closely related to brain functional networks during SWS, which suggested that EEG microstates provide an important electrophysiological basis underlying brain functional networks.

Reduced hippocampal recruitment during response conflict resolution in mesial temporal lobe epilepsy

Recent evidence suggests that the human hippocampus (HC) is not only involved in the processing of motivationally relevant approach-avoidance conflicts but is also engaged in the resolution of more general response conflicts as measured in the Stroop paradigm. Here we investigated whether neural activity in the HC is necessary for successful response conflict resolution. We compared hippocampal recruitment during an auditory Stroop paradigm in 20 patients with mesial temporal lobe epilepsy (MTLE) due to hippocampal sclerosis and 20 age-matched healthy controls using functional magnetic resonance imaging (fMRI). We analyzed hippocampal activation and behavioral performance in conflict trials relative to non-conflict trials. Moreover, functional connectivity (FC) analyses with left and right HCs as seeds were performed. Subjects' regional gray matter volumes were analyzed based on high-resolution T2-weighted MRI scans. The current study replicated previous results showing increased activation in left HC during the processing of conflict trials in healthy subjects. By contrast, MTLE patients showed higher behavioral costs of response conflict resolution and reduced conflict-related HC activation. In patients with left MTLE, left HC activation was predictive of faster conflict-related response times (RTs). By contrast, right HC activation was related to RT slowing, suggestive of a maladaptive compensation attempt in MTLE patients. Our results provide evidence that left hippocampal activation is required for the successful resolution of response conflicts.

Neural cue reactivity during acute abstinence predicts short-term smoking relapse

In smokers, neural responses to smoking cues can be sensitive to acute abstinence, but the degree to which abstinence-related cue reactivity contributes to relapse is not fully understood. This study addressed this question in a sample of 75 smokers who were motivated to quit smoking. Participants underwent blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) during presentation of visual smoking cues and neutral stimuli on two occasions: once during smoking satiety and once following 24-hour abstinence (order counterbalanced). Following the imaging sessions, participants received brief smoking cessation counseling prior to a short-term (7-day) quit attempt. The primary smoking cessation outcome was biochemically confirmed 7-day relapse. The secondary smoking cessation outcome measure was total number of self-reported days of abstinence. During abstinence (vs satiety), smoking cue reactivity was significantly increased only in the anterior cingulate cortex (ACC); other regions showing a cue (vs neutral) response did not exhibit an abstinence effect in the stringent whole-brain analysis. Participants who showed greater smoking cue reactivity in the ACC during acute abstinence (compared with smoking satiety) were more likely to relapse (OR = 2.10 per standard deviation increase in percent signal change [abstinence minus smoking satiety], 95% CI: 1.05 to 4.20, P = 0.036). Greater abstinence-induced change in ACC activation also predicted fewer total days abstinent (β = -0.63, 95% CI = 0.43 to 0.66, P < 0.0001). This study provides the first evidence that changes in smoking cue reactivity in the ACC during acute abstinence predict smoking relapse, thereby improving our understanding of the neurobiology of smoking cessation.

A cortical rat hemodynamic response function for improved detection of BOLD activation under common experimental conditions

For a reliable estimation of neuronal activation based on BOLD fMRI measurements an accurate model of the hemodynamic response is essential. Since a large part of basic neuroscience research is based on small animal data, it is necessary to characterize a hemodynamic response function (HRF) which is optimized for small animals. Therefore, we have determined and investigated the HRFs of rats obtained under a variety of experimental conditions in the primary somatosensory cortex. Measurements were performed on animals of different sex and strain, under different anesthetics, with and without ventilation and using different stimulation modalities. All modalities of stimulation used in this study induced neuronal activity in the primary somatosensory cortex or in subcortical regions. Since the HRFs of the BOLD responses in the primary somatosensory cortex showed a close concordance for the different conditions, we were able to determine a cortical rat HRF. This HRF is based on 143 BOLD measurements of 76 rats and can be used for statistical parametric mapping. It showed substantially faster progression than the human HRF, with a maximum after 2.8 ± 0.8 s, and a following undershoot after 6.1 ± 3.7 s. If the rat HRF was used statistical analysis of rat data showed a significantly improved detection performance in the somatosensory cortex in comparison to the commonly used HRF based on measurements in humans.

Metastable Resting State Brain Dynamics

Metastability refers to the fact that the state of a dynamical system spends a large amount of time in a restricted region of its available phase space before a transition takes place, bringing the system into another state from where it might recur into the previous one. beim Graben and Hutt (2013) suggested to use the recurrence plot (RP) technique introduced by Eckmann et al. (1987) for the segmentation of system's trajectories into metastable states using recurrence grammars. Here, we apply this recurrence structure analysis (RSA) for the first time to resting-state brain dynamics obtained from functional magnetic resonance imaging (fMRI). Brain regions are defined according to the brain hierarchical atlas (BHA) developed by Diez et al. (2015), and as a consequence, regions present high-connectivity in both structure (obtained from diffusion tensor imaging) and function (from the blood-level dependent-oxygenation-BOLD-signal). Remarkably, regions observed by Diez et al. were completely time-invariant. Here, in order to compare this static picture with the metastable systems dynamics obtained from the RSA segmentation, we determine the number of metastable states as a measure of complexity for all subjects and for region numbers varying from 3 to 100. We find RSA convergence toward an optimal segmentation of 40 metastable states for normalized BOLD signals, averaged over BHA modules. Next, we build a bistable dynamics at population level by pooling 30 subjects after Hausdorff clustering. In link with this finding, we reflect on the different modeling frameworks that can allow for such scenarios: heteroclinic dynamics, dynamics with riddled basins of attraction, multiple-timescale dynamics. Finally, we characterize the metastable states both functionally and structurally, using templates for resting state networks (RSNs) and the automated anatomical labeling (AAL) atlas, respectively.

The role of ongoing neuronal activity for baseline and stimulus-induced BOLD signals in the rat hippocampus

To understand how ongoing neuronal activity affects baseline BOLD signals, neuronal and resultant fMRI responses were simultaneously recorded in the right hippocampus of male rats during continuous low-frequency (2 or 4 Hz) pulse stimulation of the right perforant pathway. Despite continuously increased neuronal activity, BOLD signals only transiently increased in the hippocampus and subsequently returned to either the initial level (2 Hz) or even to a consistently lower level (4 Hz). Whereas the initially transient increase in BOLD signals coincided with an increased spiking of granule cells, the subsequent reduction of BOLD signals was independent of granule cell spiking activity but coincided with persistent inhibition of granule cell excitability, i.e., with reduced postsynaptic activity and prolonged population spike latency. The decline in BOLD signals occurred in the presence of an elevated local cerebral blood volume (CBV), thus the reduction of granule cell excitability is attended by high oxygen consumption. When previous or current stimulations lessen baseline BOLD signals, subsequent short stimulation periods only elicited attenuated BOLD responses, even when actual spiking activity of granule cells was similar. Thus, the quality of stimulus-induced BOLD responses critically depends on the current existing inhibitory activity, which closely relates to baseline BOLD signals. Thus, a meaningful interpretation of stimulus-induced BOLD responses should consider slowly developing variations in baseline BOLD signals; therefore, baseline correction tools should be cautiously used for fMRI data analysis.

APOE gene-dependent BOLD responses to a breath-hold across the adult lifespan

Age and apolipoprotein E (APOE) e4 genotype are two of the strongest known risk factors for sporadic Alzheimer's disease (AD). Neuroimaging has shown hemodynamic response changes with age, in asymptomatic carriers of the APOE e4 allele, and in AD. In this study, we aimed to characterize and differentiate age- and APOE gene-specific hemodynamic changes to breath-hold and visual stimulation. A further aim was to study whether these responses were modulated by 3-day intake of nitrate, a nitric oxide (NO) source. The study was designed as a randomized, double-blinded, placebo-controlled crossover study, and the study cohort comprised 41 APOE e4 carriers (e3/e4 or e4/e4 genotype) and 40 non-carriers (e3/e3 genotype) aged 30-70 years at enrollment. The participants underwent two scanning sessions, each preceded by ingestion of sodium nitrate or sodium chloride (control). During functional magnetic resonance imaging (fMRI) sessions, participants performed two concurrent tasks; a breath-hold task to probe cerebrovascular reactivity and a visual stimulation task to evoke functional hyperemia, respectively. We found that the blood oxygenation level dependent (BOLD) hemodynamic response to breath-hold was altered in APOE e4 carriers relative to non-carriers. Mid-aged (50-60 years of age) e4 carriers exhibited a significantly increased peak time relative to mid-aged e3 carriers, and peak time for younger (30-40 years of age) e4 carriers was significantly shorter than that of mid-aged e4 carriers. The response width was significantly increased for e4 carriers. The response peak magnitude significantly decreased with age. For the visual stimulation task, we found age-related changes, with reduced response magnitude with age but no significant effect of APOE allele type. We found no effect of nitrate ingestion on BOLD responses evoked by the breath-hold and visual stimulation tasks. The APOE gene-dependent response to breath-hold may reflect NO-independent differences in vascular function.

A deconvolution algorithm for multi-echo functional MRI: Multi-echo Sparse Paradigm Free Mapping

This work introduces a novel algorithm for deconvolution of the BOLD signal in multi-echo fMRI data: Multi-echo Sparse Paradigm Free Mapping (ME-SPFM). Assuming a linear dependence of the BOLD percent signal change on the echo time (TE) and using sparsity-promoting regularized least squares estimation, ME-SPFM yields voxelwise time-varying estimates of the changes in the apparent transverse relaxation (ΔR₂^⁎) without prior knowledge of the timings of individual BOLD events. Our results in multi-echo fMRI data collected during a multi-task event-related paradigm at 3 Tesla demonstrate that the maps of R₂^⁎ changes obtained with ME-SPFM at the times of the stimulus trials show high spatial and temporal concordance with the activation maps and BOLD signals obtained with standard model-based analysis. This method yields estimates of ΔR₂^⁎ having physiologically plausible values. Owing to its ability to blindly detect events, ME-SPFM also enables us to map ΔR₂^⁎ associated with spontaneous, transient BOLD responses occurring between trials. This framework is a step towards deciphering the dynamic nature of brain activity in naturalistic paradigms, resting-state or experimental paradigms with unknown timing of the BOLD events.

Colouring perception: Package colour cues affect neural responses to sweet dairy drinks in reward and inhibition related regions

Extrinsic product cues such as package colour may change product perception and perceived reward value during product evaluation. Healthier foods (i.e., 'light', sugar- or fat-reduced) often have different packages than regular products, e.g., they may be less vibrantly coloured. People vary in their degree of health-interest and self-control ability and may be affected differently by package colour. This study assesses the extent to which package colour and participant characteristics interact and influence product perception and brain responses. Thirty-four healthy females performed a functional MRI task in which they viewed four differently coloured packages (regular vs. healthier; differing in brightness and saturation levels) with or without simultaneously tasting a either a regular or a healthier calorie-reduced drink. Results indicate main effects of package and taste and a package*taste interaction effect. Compared to healthier packages viewing regular packages enhanced activation in region implicated in inhibitory control (inferior frontal gyrus) and a reward-related region (striatum), the latter even more so as participants' health interest increased (r = 0.43, p = 0.01). Incongruent package-taste combinations decreased activation in the orbitofrontal cortex (OFC, a region implicated in reward representation) compared to congruent combinations. Tasting the healthier compared to regular product enhanced activation in the middle and superior frontal gyrus, which are implicated in inhibitory control, as well as the striatum and OFC, suggesting a cognitively driven preference for the healthier product. In conclusion, this paper provides evidence for the conditions under which package colour and taste properties modulate neural correlates related to reward and inhibition. Individual differences in health-interest and impulsivity influence package- and taste-related neural correlates and thus underscore the importance of taking participant characteristics into account in food research.

A multivoxel pattern analysis framework with mutual connectivity analysis investigating changes in resting state connectivity in patients with HIV associated neurocognitve disorder

Functional MRI (fMRI) quantifies brain activity non-invasively by measuring the blood oxygen level dependent (BOLD) response to neuronal activity. It was recently demonstrated, on realistic fMRI simulations, that nonlinear connectivity approaches, such as Mutual Connectivity Analysis with Local Models (MCA-LM), are better suited for extracting connectivity measures than conventional techniques of cross-correlating time-series pairs. In this work, we investigate the application of MCA-LM in extracting meaningful connectivity measures aiding in distinguishing healthy controls from individuals presenting with symptoms of HIV Associated Neurocognitive Disorder (HAND), which occurs as a result of HIV infection of the central nervous system. The pairwise connectivity measures provide a high-dimensional representation of connectivity profiles for subjects and are used as features for classification. We adopt feature selection (FS) techniques reducing the number of redundant and noisy features, while also controlling the complexity of the classifiers. We investigate three FS techniques: 1) Kendall's τ, 2) Information Gain Attribute selection 3) ReliefF and two classifiers:1) AdaBoost and 2) Random Forests. Our results demonstrate that MCA-LM consistently outperforms correlation in terms of Area under the Receiver Operating Characteristic Curve and accuracy. Improved performance with MCA-LM suggests that such a nonlinear approach is better at capturing meaningful connectivity relationships between brain regions. This demonstrates potential for developing novel neuroimaging-derived biomarkers for HAND. Furthermore, FS helps identify connections between anatomical regions that are affected by HAND. In this work, we show that the regions of the basal ganglia and frontal cortex, which are known to be affected by HAND according to current literature, are identified as most discriminative.

Effect of cervical manipulation on vertebral artery and cerebral haemodynamics in patients with chronic neck pain: a crossover randomised controlled trial

OBJECTIVE

It is hypothesised that cervical manipulation may increase the risk of cerebrovascular accidents. We aimed to determine whether cervical spine manipulation is associated with changes in vertebral artery and cerebrovascular haemodynamics measured with MRI compared with neutral neck position and maximum neck rotation in patients with chronic neck pain.

SETTING

The Imaging Research Centre at St. Joseph's Hospital in Hamilton, Ontario, Canada.

PARTICIPANTS

Twenty patients were included. The mean age was 32 years (SD ±12.5), mean neck pain duration was 5.3 years (SD ±5.7) and mean neck disability index score was 13/50 (SD ±6.4).

INTERVENTIONS

Following baseline measurement of cerebrovascular haemodynamics, we randomised participants to: (1) maximal neck rotation followed by cervical manipulation or (2) cervical manipulation followed by maximal neck rotation. The primary outcome, vertebral arteries and cerebral haemodynamics, was measured after each intervention and was obtained by measuring three-dimensional T1-weighted high-resolution anatomical images, arterial spin labelling and phase-contrast flow encoded MRI. Our secondary outcome was functional connectivity within the default mode network measured with resting state functional MRI.

RESULTS

Compared with neutral neck position, we found a significant change in contralateral blood flow following maximal neck rotation. There was also a significant change in contralateral vertebral artery blood velocity following maximal neck rotation and cervical manipulation. We found no significant changes within the cerebral haemodynamics following cervical manipulation or maximal neck rotation. However, we observed significant increases in functional connectivity in the posterior cerebrum and cerebellum (resting state MRI) after manipulation and maximum rotation.

CONCLUSION

Our results are in accordance with previous work, which has shown a decrease in blood flow and velocity in the contralateral vertebral artery with head rotation. This may explain why we also observed a decrease in blood velocity with manipulation because it involves neck rotation. Our work is the first to show that cervical manipulation does not result in brain perfusion changes compared with a neutral neck position or maximal neck rotation. The changes observed were found to not be clinically meaningful and suggests that cervical manipulation may not increase the risk of cerebrovascular events through a haemodynamic mechanism.

TRIAL REGISTRATION NUMBER

NCT02667821.

Electrical Stimulation of the Lateral Entorhinal Cortex Causes a Frequency-Specific BOLD Response Pattern in the Rat Brain

Although deep brain stimulation of the entorhinal cortex has recently shown promise in the treatment of early forms of cognitive decline, the underlying neurophysiological processes remain elusive. Therefore, the lateral entorhinal cortex (LEC) was stimulated with trains of continuous 5 Hz and 20 Hz pulses or with bursts of 100 Hz pulses to visualize activated neuronal networks, i.e., neuronal responses in the dentate gyrus and BOLD responses in the entire brain were simultaneously recorded. Electrical stimulation of the LEC caused a wide spread pattern of BOLD responses. Dependent on the stimulation frequency, BOLD responses were only triggered in the amygdala, infralimbic, prelimbic, and dorsal peduncular cortex (5 Hz), or in the nucleus accumbens, piriform cortex, dorsal medial prefrontal cortex, hippocampus (20 Hz), and contralateral entorhinal cortex (100 Hz). In general, LEC stimulation caused stronger BOLD responses in frontal cortex regions than in the hippocampus. Identical stimulation of the perforant pathway, a fiber bundle projecting from the entorhinal cortex to the dentate gyrus, hippocampus proper, and subiculum, mainly elicited significant BOLD responses in the hippocampus but rarely in frontal cortex regions. Consequently, BOLD responses in frontal cortex regions are mediated by direct projections from the LEC rather than via signal propagation through the hippocampus. Thus, the beneficial effects of deep brain stimulation of the entorhinal cortex on cognitive skills might depend more on an altered prefrontal cortex than hippocampal function.

Non-invasive Motor Cortex Neuromodulation Reduces Secondary Hyperalgesia and Enhances Activation of the Descending Pain Modulatory Network

Central sensitization is a driving mechanism in many chronic pain patients, and manifests as hyperalgesia and allodynia beyond any apparent injury. Recent studies have demonstrated analgesic effects of motor cortex (M1) stimulation in several chronic pain disorders, yet its neural mechanisms remain uncertain. We evaluated whether anodal M1 transcranial direct current stimulation (tDCS) would mitigate central sensitization as measured by indices of secondary hyperalgesia. We used a capsaicin-heat pain model to elicit secondary mechanical hyperalgesia in 27 healthy subjects. In an assessor and subject-blind randomized, sham-controlled, crossover trial, anodal M1 tDCS decreased the intensity of pinprick hyperalgesia more than cathodal or sham tDCS. To elucidate the mechanism driving analgesia, subjects underwent fMRI of painful mechanical stimuli prior to and following induction of the pain model, after receiving M1 tDCS. We hypothesized that anodal M1 tDCS would enhance engagement of a descending pain modulatory (DPM) network in response to mechanical stimuli. Anodal tDCS normalized the effects of central sensitization on neurophysiological responses to mechanical pain in the medial prefrontal cortex, pregenual anterior cingulate cortex, and periaqueductal gray, important regions in the DPM network. Taken together, these results provide support for the hypothesis that anodal M1-tDCS reduces central sensitization-induced hyperalgesia through the DPM network in humans.

Functional MRI Task Comparison for Language Mapping in Neurosurgical Patients

BACKGROUND AND PURPOSE

Language task-based functional MRI (fMRI) is increasingly used for presurgical planning in patients with brain lesions. Different paradigms elicit activations of different components of the language network. The aim of this study is to optimize fMRI clinical usage by comparing the effectiveness of three language tasks for language lateralization and localization in a large group of patients with brain lesions.

METHODS

We analyzed fMRI data from a sequential retrospective cohort of 51 patients with brain lesions who underwent presurgical fMRI language mapping. We compared the effectiveness of three language tasks (Antonym Generation, Sentence Completion (SC), and Auditory Naming) for lateralizing language function and for activating cortex within patient-specific regions-of-interest representing eloquent language areas, and assessed the degree of spatial overlap of the areas of activation elicited by each task.

RESULTS

The tasks were similarly effective for lateralizing language within the anterior language areas. The SC task produced higher laterality indices within the posterior language areas and had a significantly higher agreement with the clinical report. Dice coefficients between the task pairs were in the range of .351-.458, confirming substantial variation in the components of the language network activated by each task.

CONCLUSIONS

SC task consistently produced large activations within the dominant hemisphere and was more effective for lateralizing language within the posterior language areas. The low degree of spatial overlap among the tasks strongly supports the practice of using a battery of tasks to help the surgeon to avoid eloquent language areas.

Moderating Effect of Cortical Thickness on BOLD Signal Variability Age-Related Changes

The time course of neuroanatomical structural and functional measures across the lifespan is commonly reported in association with aging. Blood oxygen-level dependent signal variability, estimated using the standard deviation of the signal, or "BOLDSD," is an emerging metric of variability in neural processing, and has been shown to be positively correlated with cognitive flexibility. Generally, BOLDSD is reported to decrease with aging, and is thought to reflect age-related cognitive decline. Additionally, it is well established that normative aging is associated with structural changes in brain regions, and that these predict functional decline in various cognitive domains. Nevertheless, the interaction between alterations in cortical morphology and BOLDSD changes has not been modeled quantitatively. The objective of the current study was to investigate the influence of cortical morphology metrics [i.e., cortical thickness (CT), gray matter (GM) volume, and cortical area (CA)] on age-related BOLDSD changes by treating these cortical morphology metrics as possible physiological confounds using linear mixed models. We studied these metrics in 28 healthy older subjects scanned twice at approximately 2.5 years interval. Results show that BOLDSD is confounded by cortical morphology metrics. Respectively, changes in CT but not GM volume nor CA, show a significant interaction with BOLDSD alterations. Our study highlights that CT changes should be considered when evaluating BOLDSD alternations in the lifespan.

Phase fMRI informs whole-brain function connectivity balance across lifespan with connection-specific aging effects during the resting state

A functional magnetic resonance imaging (fMRI) experiment produces complex-valued images consisting of pairwise magnitude and phase images. As different perspective on the same magnetic source, fMRI magnitude and phase data are complementary for brain function analysis. We collected 600-subject fMRI data during rest, decomposed via group-level independent component analysis (ICA) (mICA and pICA for magnitude and phase respectively), and calculated brain functional network connectivity matrices (mFC and pFC). The pFC matrix shows a fewer of significant connections balanced across positive and negative relationships. In comparison, the mFC matrix contains a positively-biased pattern with more significant connections. Our experiment data analyses also show that human brain maintains a whole-brain connection balance in resting state across an age span from 10 to 76 years, however, phase and magnitude data analyses reveal different connection-specific age effects on significant positive and negative subnetwork couplings.

Sensorimotor network hypersynchrony as an endophenotype in families with genetic generalized epilepsy: A resting-state functional magnetic resonance imaging study

Recent evidence suggests that three specific brain networks show state-dependent levels of synchronization before, during, and after episodes of generalized spike-wave discharges (GSW) in patients with genetic generalized epilepsy (GGE). Here, we investigate whether synchronization in these networks differs between patients with GGE (n = 13), their unaffected first-degree relatives (n = 17), and healthy controls (n = 18). All subjects underwent two 10-minute simultaneous electroencephalographic-functional magnetic resonance imaging (fMRI) recordings without GSW. Whole-brain data were divided into 90 regions, and blood oxygen level-dependent (BOLD) phase synchrony in a 0.04-0.07-Hz band was estimated between all pairs of regions. Three networks were defined: (1) the network with highest synchrony during GSW events, (2) a sensorimotor network, and (3) an occipital network. Average synchrony (mean node degree) was inferred across each network over time. Notably, synchrony was significantly higher in the sensorimotor network in patients and in unaffected relatives, compared to controls. There was a trend toward higher synchrony in the GSW network in patients and in unaffected relatives. There was no difference between groups for the occipital network. Our findings provide evidence that elevated fMRI BOLD synchrony in a sensorimotor network is a state-independent endophenotype of GGE, present in patients in the absence of GSW, and present in unaffected relatives.

Dependence of the MR signal on the magnetic susceptibility of blood studied with models based on real microvascular networks

PURPOSE

The primary goal of this study was to estimate the value of β , the exponent in the power law relating changes of the transverse relaxation rate and intra-extravascular local magnetic susceptibility differences as Δ R 2 ∗ ∝ ( Δ χ ) β . The secondary objective was to evaluate any differences that might exist in the value of β obtained using a deoxyhemoglobin-weighted Δ χ distribution versus a constant Δ χ distribution assumed in earlier computations. The third objective was to estimate the value of β that is relevant for methods based on susceptibility contrast agents with a concentration of Δ χ higher than that used for BOLD fMRI calculations.

METHODS

Our recently developed model of real microvascular anatomical networks is used to extend the original simplified Monte-Carlo simulations to compute β from the first principles.

RESULTS

Our results show that β = 1 for most BOLD fMRI measurements of real vascular networks, as opposed to earlier predictions of β = 1 .5 using uniform Δ χ distributions. For perfusion or fMRI methods based on contrast agents, which generate larger values for Δ χ , β = 1 for B 0 ≤ 9.4 T, whereas at 14 T β can drop below 1 and the variation across subjects is large, indicating that a lower concentration of contrast agent with a lower value of Δ χ is desired for experiments at high B₀ .

CONCLUSION

These results improve our understanding of the relationship between R₂ ^* and the underlying microvascular properties. The findings will help to infer the cerebral metabolic rate of oxygen and cerebral blood volume from BOLD and perfusion MRI, respectively.

Glycolysis Paradigm Shift Dictates a Reevaluation of Glucose and Oxygen Metabolic Rates of Activated Neural Tissue

In 1988 two seminal studies were published, both instigating controversy. One concluded that “the energy needs of activated neural tissue are minimal, being fulfilled via the glycolytic pathway alone,” a conclusion based on the observation that neural activation increased glucose consumption, which was not accompanied by a corresponding increase in oxygen consumption (Fox et al., 1988). The second demonstrated that neural tissue function can be supported exclusively by lactate as the energy substrate (Schurr et al., 1988). While both studies continue to have their supporters and detractors, the present review attempts to clarify the issues responsible for the persistence of the controversies they have provoked and offer a possible rationalization. The concept that lactate rather than pyruvate, is the glycolytic end-product, both aerobically and anaerobically, and thus the real mitochondrial oxidative substrate, has gained a greater acceptance over the years. The idea of glycolysis as the sole ATP supplier for neural activation (glucose → lactate + 2ATP) continues to be controversial. Lactate oxidative utilization by activated neural tissue could explain the mismatch between glucose and oxygen consumption and resolve the existing disagreements among users of imaging methods to measure the metabolic rates of the two energy metabolic substrates. The postulate that the energy necessary for active neural tissue is supplied by glycolysis alone stems from the original aerobic glycolysis paradigm. Accordingly, glucose consumption is accompanied by oxygen consumption at 1–6 ratio. Since Fox et al. (1988) observed only a minimal if non-existent oxygen consumption compared to glucose consumption, their conclusion make sense. Nevertheless, considering (a) the shift in the paradigm of glycolysis (glucose → lactate; lactate + O₂ + mitochondria → pyruvate → TCA cycle → CO₂ + H₂O + 17ATP); (b) that one mole of lactate oxidation requires only 50% of the amount of oxygen necessary for the oxidation of one mole of glucose; and (c) that lactate, as a mitochondrial substrate, is over eight times more efficient at ATP production than glucose as a glycolytic substrate, suggest that future studies of cerebral metabolic rates of activated neural tissue should include along with the measurements of CMR_O2 and CMR_glucose the measurement of CMR_lactate.

A circular echo planar sequence for fast volumetric fMRI

PURPOSE

To demonstrate a circular EPI (CEPI) sequence as well as a generalized EPI reconstruction for fast fMRI with parallel imaging acceleration.

METHODS

The CEPI acquisition was constructed using variable readout lengths and maximum ramp sampling as well as blipped-CAIPI z-gradient encoding for simultaneous multislice (SMS) and 3D volumetric imaging. A signal equation model with constant and linear phase terms was used to iteratively reconstruct images with low ghosting. Simulation, phantom, and human imaging experiments including audio/visual fMRI were performed at 3T using a 52-channel coil.

RESULTS

Application of CEPI gradients with duration of 27 ms covering a 22-cm FOV at a 64 × 64 pixel resolution in SMS and 3D acquisitions resulted in images with comparable quality to those of standard Cartesian EPI. With parallel imaging techniques robust detection of BOLD fMRI activation with temporal sampling down to 275 ms was possible. The high temporal resolution enabled higher activation statistics at a penalty in increased noise and residual aliasing. The un-accelerated 3D acquisition showed large temporal instability compared with a standard 2D acquisition.

CONCLUSION

Nonuniform sampling and generalized image reconstructions can be applied to EPI acquisitions including those with blipped-CAIPI z gradients. The same gradients can be used for either SMS or 3D acquisitions providing identical coverage.

Resting State Functional Connectivity Signature of Treatment Effects of Repetitive Transcranial Magnetic Stimulation in Mal de Debarquement Syndrome

Repetitive transcranial magnetic stimulation (rTMS) has been used in experimental protocols to treat mal de debarquement syndrome (MdDS), a neurological condition that represents a maladaptive brain state resulting from entrainment to external oscillating motion. Medical treatments and biomarkers for MdDS remain limited but neuromodulation with rTMS has shown evidence for therapeutic effects. This study took a neuroimaging approach to examine the neuromodulatory effect of rTMS on MdDS. Twenty individuals with MdDS underwent five daily treatments of rTMS over bilateral dorsolateral prefrontal cortex (DLPFC). Participants received 1 Hz over right DLPFC (1200 pulses) followed by 10 Hz over left DLPFC (2000 pulses). Resting state functional magnetic resonance imaging was acquired before and after treatments to determine functional connectivity changes associated with a positive treatment effect. A single-subject-based analysis protocol was developed to capture the degree of resting state functional connectivity (RSFC) between the rTMS target and the entorhinal cortex (EC), an area previously shown to be hypermetabolic in MdDS. Our results showed that rocking motion perception in subjects was modulated by rTMS over the DLPFC. Improvements in symptoms correlated most strongly with a post-rTMS reduction in functional connectivity between the left EC and the precuneus, right inferior parietal lobule, and the contralateral EC, which are part of the posterior default mode network. Positive response to rTMS correlated with higher baseline RSFC between the DLPFC and the EC. Our findings suggest that baseline prefrontal-limbic functional connectivity may serve as a predictor of treatment response to prefrontal stimulation in MdDS and that RSFC may serve as a dynamic biomarker of symptom status.

GLMdenoise improves multivariate pattern analysis of fMRI data

GLMdenoise is a denoising technique for task-based fMRI. In GLMdenoise, estimates of spatially correlated noise (which may be physiological, instrumental, motion-related, or neural in origin) are derived from the data and incorporated as nuisance regressors in a general linear model (GLM) analysis. We previously showed that GLMdenoise outperforms a variety of other denoising techniques in terms of cross-validation accuracy of GLM estimates (Kay et al., 2013a). However, the practical impact of denoising for experimental studies remains unclear. Here we examine whether and to what extent GLMdenoise improves sensitivity in the context of multivariate pattern analysis of fMRI data. On a large number of participants (31 participants across 4 experiments; 3 T, gradient-echo, spatial resolution 2-3.75 mm, temporal resolution 1.3-2 s, number of conditions 32-75), we perform representational similarity analysis (Kriegeskorte et al., 2008a) as well as pattern classification (Haxby et al., 2001). We find that GLMdenoise substantially improves replicability of representational dissimilarity matrices (RDMs) across independent splits of each participant's dataset (average RDM replicability increases from r = 0.46 to r = 0.61). Additionally, we find that GLMdenoise substantially improves pairwise classification accuracy (average classification accuracy increases from 79% correct to 84% correct). We show that GLMdenoise often improves and never degrades performance for individual participants and that GLMdenoise also improves across-participant consistency. We conclude that GLMdenoise is a useful tool that can be routinely used to maximize the amount of information extracted from fMRI activity patterns.

Physiological and Pathological Brain Activation in the Anesthetized Rat Produces Hemodynamic-Dependent Cortical Temperature Increases That Can Confound the BOLD fMRI Signal

Anesthetized rodent models are ubiquitous in pre-clinical neuroimaging studies. However, because the associated cerebral morphology and experimental methodology results in a profound negative brain-core temperature differential, cerebral temperature changes during functional activation are likely to be principally driven by local inflow of fresh, core-temperature, blood. This presents a confound to the interpretation of blood-oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) data acquired from such models, since this signal is also critically temperature-dependent. Nevertheless, previous investigation on the subject is surprisingly sparse. Here, we address this issue through use of a novel multi-modal methodology in the urethane anesthetized rat. We reveal that sensory stimulation, hypercapnia and recurrent acute seizures induce significant increases in cortical temperature that are preferentially correlated to changes in total hemoglobin concentration (Hbt), relative to cerebral blood flow and oxidative metabolism. Furthermore, using a phantom-based evaluation of the effect of such temperature changes on the BOLD fMRI signal, we demonstrate a robust inverse relationship between both variables. These findings suggest that temperature increases, due to functional hyperemia, should be accounted for to ensure accurate interpretation of BOLD fMRI signals in pre-clinical neuroimaging studies.

Adolescent Hippocampal and Prefrontal Brain Activation During Performance of the Virtual Morris Water Task

The frontal cortex undergoes substantial structural and functional changes during adolescence and significant developmental changes also occur in the hippocampus. Both of these regions are notably vulnerable to alcohol and other substance use, which is typically initiated during adolescence. Identifying measures of brain function during adolescence, particularly before initiation of drug or alcohol use, is critical to understanding how such behaviors may affect brain development, especially in these vulnerable brain regions. While there is a substantial developmental literature on adolescent working memory, less is known about spatial memory. Thus, a virtual Morris water task (vMWT) was applied to probe function of the adolescent hippocampus. Multiband blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) data were acquired at 3T during task performance. Participants included 32 healthy, alcohol- and drug-naïve adolescents, 13–14 years old, examined at baseline of a 3-year longitudinal MRI study. Significantly greater BOLD activation was observed in the hippocampus and surrounding areas, and in prefrontal regions involved in executive function, during retrieval relative to motor performance. In contrast, significantly greater BOLD activation was observed in components of the default mode network, including frontal medial cortex, during the motor condition (when task demands were minimal) relative to the retrieval condition. Worse performance (longer path length) during retrieval was associated with greater activation of angular gyrus/supramarginal gyrus, whereas worse performance (longer path length/latency) during motor control was associated with less activation of frontal pole. Furthermore, while latency (time to complete task) was greater in females than in males, there were no sex differences in path length (accuracy), suggesting that females required more time to navigate the virtual environment, but did so as effectively as males. These findings demonstrate that performance of the vMWT elicits hippocampal and prefrontal activation patterns in early adolescence, similar to activation observed during spatial memory retrieval in adults. Given that this task is sensitive to hippocampal function, and that the adolescent hippocampus is notably vulnerable to the effects of alcohol and other substances, data acquired using this task during healthy adolescent development may provide a framework for understanding neurobiological impact of later initiation of use.

On the Stability of BOLD fMRI Correlations

Measurement of correlations between brain regions (functional connectivity) using blood oxygen level dependent (BOLD) fMRI has proven to be a powerful tool for studying the functional organization of the brain. Recently, dynamic functional connectivity has emerged as a major topic in the resting-state BOLD fMRI literature. Here, using simulations and multiple sets of empirical observations, we confirm that imposed task states can alter the correlation structure of BOLD activity. However, we find that observations of "dynamic" BOLD correlations during the resting state are largely explained by sampling variability. Beyond sampling variability, the largest part of observed "dynamics" during rest is attributable to head motion. An additional component of dynamic variability during rest is attributable to fluctuating sleep state. Thus, aside from the preceding explanatory factors, a single correlation structure-as opposed to a sequence of distinct correlation structures-may adequately describe the resting state as measured by BOLD fMRI. These results suggest that resting-state BOLD correlations do not primarily reflect moment-to-moment changes in cognitive content. Rather, resting-state BOLD correlations may predominantly reflect processes concerned with the maintenance of the long-term stability of the brain's functional organization.

Neurophysiological Basis of Multi-Scale Entropy of Brain Complexity and Its Relationship With Functional Connectivity

Recently, non-linear statistical measures such as multi-scale entropy (MSE) have been introduced as indices of the complexity of electrophysiology and fMRI time-series across multiple time scales. In this work, we investigated the neurophysiological underpinnings of complexity (MSE) of electrophysiology and fMRI signals and their relations to functional connectivity (FC). MSE and FC analyses were performed on simulated data using neural mass model based brain network model with the Brain Dynamics Toolbox, on animal models with concurrent recording of fMRI and electrophysiology in conjunction with pharmacological manipulations, and on resting-state fMRI data from the Human Connectome Project. Our results show that the complexity of regional electrophysiology and fMRI signals is positively correlated with network FC. The associations between MSE and FC are dependent on the temporal scales or frequencies, with higher associations between MSE and FC at lower temporal frequencies. Our results from theoretical modeling, animal experiment and human fMRI indicate that (1) Regional neural complexity and network FC may be two related aspects of brain's information processing: the more complex regional neural activity, the higher FC this region has with other brain regions; (2) MSE at high and low frequencies may represent local and distributed information processing across brain regions. Based on literature and our data, we propose that the complexity of regional neural signals may serve as an index of the brain's capacity of information processing—increased complexity may indicate greater transition or exploration between different states of brain networks, thereby a greater propensity for information processing.

Mutual connectivity analysis of resting-state functional MRI data with local models

Functional connectivity analysis of functional MRI (fMRI) can represent brain networks and reveal insights into interactions amongst different brain regions. However, most connectivity analysis approaches adopted in practice are linear and non-directional. In this paper, we demonstrate the advantage of a data-driven, directed connectivity analysis approach called Mutual Connectivity Analysis using Local Models (MCA-LM) that approximates connectivity by modeling nonlinear dependencies of signal interaction, over more conventionally used approaches, such as Pearson's and partial correlation, Patel's conditional dependence measures, etcetera. We demonstrate on realistic simulations of fMRI data that, at long sampling intervals, i.e. high repetition time (TR) of fMRI signals, MCA-LM performs better than or comparable to correlation-based methods and Patel's measures. However, at fast image acquisition rates corresponding to low TR, MCA-LM significantly outperforms these methods. This insight is particularly useful in the light of recent advances in fast fMRI acquisition techniques. Methods that can capture the complex dynamics of brain activity, such as MCA-LM, should be adopted to extract as much information as possible from the improved representation. Furthermore, MCA-LM works very well for simulations generated at weak neuronal interaction strengths, and simulations modeling inhibitory and excitatory connections as it disentangles the two opposing effects between pairs of regions/voxels. Additionally, we demonstrate that MCA-LM is capable of capturing meaningful directed connectivity on experimental fMRI data. Such results suggest that it introduces sufficient complexity into modeling fMRI time-series interactions that simple, linear approaches cannot, while being data-driven, computationally practical and easy to use. In conclusion, MCA-LM can provide valuable insights towards better understanding brain activity.

Converging Evidence From Electrocorticography and BOLD fMRI for a Sharp Functional Boundary in Superior Temporal Gyrus Related to Multisensory Speech Processing

Although humans can understand speech using the auditory modality alone, in noisy environments visual speech information from the talker’s mouth can rescue otherwise unintelligible auditory speech. To investigate the neural substrates of multisensory speech perception, we compared neural activity from the human superior temporal gyrus (STG) in two datasets. One dataset consisted of direct neural recordings (electrocorticography, ECoG) from surface electrodes implanted in epilepsy patients (this dataset has been previously published). The second dataset consisted of indirect measures of neural activity using blood oxygen level dependent functional magnetic resonance imaging (BOLD fMRI). Both ECoG and fMRI participants viewed the same clear and noisy audiovisual speech stimuli and performed the same speech recognition task. Both techniques demonstrated a sharp functional boundary in the STG, spatially coincident with an anatomical boundary defined by the posterior edge of Heschl’s gyrus. Cortex on the anterior side of the boundary responded more strongly to clear audiovisual speech than to noisy audiovisual speech while cortex on the posterior side of the boundary did not. For both ECoG and fMRI measurements, the transition between the functionally distinct regions happened within 10 mm of anterior-to-posterior distance along the STG. We relate this boundary to the multisensory neural code underlying speech perception and propose that it represents an important functional division within the human speech perception network.

Pulse sequences and parallel imaging for high spatiotemporal resolution MRI at ultra-high field

The SNR and CNR benefits of ultra-high field (UHF) have helped push the envelope of achievable spatial resolution in MRI. For applications based on susceptibility contrast where there is a large CNR gain, high quality sub-millimeter resolution imaging is now being routinely performed, particularly in fMRI and phase imaging/QSM. This has enabled the study of structure and function of very fine-scale structures in the brain. UHF has also helped push the spatial resolution of many other MRI applications as will be outlined in this review. However, this push in resolution comes at a cost of a large encoding burden leading to very lengthy scans. Developments in parallel imaging with controlled aliasing and the move away from 2D slice-by-slice imaging to much more SNR-efficient simultaneous multi-slice (SMS) and 3D acquisitions have helped address this issue. In particular, these developments have revolutionized the efficiency of UHF MRI to enable high spatiotemporal resolution imaging at an order of magnitude faster acquisition. In addition to describing the main approaches to these techniques, this review will also outline important key practical considerations in using these methods in practice. Furthermore, new RF pulse design to tackle the B1+ and SAR issues of UHF and the increased SAR and power requirement of SMS RF pulses will also be touched upon. Finally, an outlook into new developments of smart encoding in more dimensions, particularly through using better temporal/across-contrast encoding and reconstruction will be described. Just as controlled aliasing fully exploits spatial encoding in parallel imaging to provide large multiplicative gains in accelerations, the complimentary use of these new approaches in temporal and across-contrast encoding are expected to provide exciting opportunities for further large gains in efficiency to further push the spatiotemporal resolution of MRI.

Resting State BOLD Variability in Alzheimer's Disease: A Marker of Cognitive Decline or Cerebrovascular Status?

Background: Alzheimer's disease (AD) is a neurodegenerative disorder that may benefit from early diagnosis and intervention. Therefore, there is a need to identify early biomarkers of AD using non-invasive techniques such as functional magnetic resonance imaging (fMRI). Recently, novel approaches to the analysis of resting-state fMRI data have been developed that focus on the moment-to-moment variability in the blood oxygen level dependent (BOLD) signal. The objective of the current study was to investigate BOLD variability as a novel early biomarker of AD and its associated psychophysiological correlates. Method: Data were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) 2 database from 19 participants with AD and 19 similarly aged controls. For each participant, a map of BOLD signal variability (SDBOLD) was computed as the standard deviation of the BOLD timeseries at each voxel. Group comparisons were performed to examine global differences in resting state SDBOLD in AD versus healthy controls. Correlations were then examined between participant SDBOLD maps and (1) ADNI-derived composite scores of memory and executive function and (2) neuroimaging markers of cerebrovascular status. Results: Between-group comparisons revealed significant (p < 0.05) increases in SDBOLD in patients with AD relative to healthy controls in right-lateralized frontal regions. Lower memory scores and higher WMH burden were associated with greater SDBOLD in the healthy control group (p < 0.1), but not individuals with AD. Conclusion: The current study provides proof of concept of a novel resting state fMRI analysis technique that is non-invasive, easily accessible, and clinically compatible. To further explore the potential of SDBOLD as a biomarker of AD, additional studies in larger, longitudinal samples are needed to better understand the changes in SDBOLD that characterize earlier stages of disease progression and their underlying psychophysiological correlates.

The 5-HT2C receptor agonist meta-chlorophenylpiperazine (mCPP) reduces palatable food consumption and BOLD fMRI responses to food images in healthy female volunteers

RATIONALE

Brain 5-HT_2C receptors form part of a neural network that controls eating behaviour. 5-HT_2C receptor agonists decrease food intake by activating proopiomelanocortin (POMC) neurons in the arcuate nucleus of the hypothalamus, but recent research in rodents has suggested that 5-HT_2C receptor agonists may also act via dopaminergic circuitry to reduce the rewarding value of food and other reinforcers. No mechanistic studies on the effects of 5-HT_2C agonists on food intake in humans have been conducted to date.

OBJECTIVES

The present study examined the effects of the 5-HT_2C receptor agonist meta-chlorophenylpiperazine (mCPP) on food consumption, eating microstructure and blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) responses to food pictures in healthy female volunteers.

METHODS

In a double-blind, placebo-controlled, crossover design, participants were randomized immediately after screening to receive oral mCPP (30mg) in a single morning dose, or placebo, in a counterbalanced order. Test foods were served from a Universal Eating Monitor (UEM) that measured eating rate and fMRI BOLD signals to the sight of food and non-food images were recorded.

RESULTS

mCPP decreased rated appetite and intake of a palatable snack eaten in the absence of hunger but had no significant effect on the consumption of a pasta lunch (although pasta eating rate was reduced). mCPP also decreased BOLD fMRI responses to the sight of food pictures in areas of reward-associated circuitry. A post hoc analysis identified individual variability in the response to mCPP (exploratory responder-non-responder analysis). Some participants did not reduce their cookie intake after treatment with mCPP and this lack of response was associated with enhanced ratings of cookie pleasantness and enhanced baseline BOLD responses to food images in key reward and appetite circuitry.

CONCLUSIONS

These results suggest that 5-HT_2C receptor activation in humans inhibits food reward-related responding and that further investigation of stratification of responding to mCPP and other 5-HT_2C receptor agonists is warranted.

[Evaluation of vascular reactivity to overcome limitations of neurovascular uncoupling in BOLD fMRI of malignant brain tumors]

The sensitivity of fMRI in identification of eloquent cortical centers in the case of large infiltrative growing tumors and pronounced peritumoral edema may be reduced or significantly limited in some cases. The main cause is an attenuated Blood-Oxygen-Level-Dependent response (BOLD) caused by pathological vascular reactivity and subsequent neurovascular uncoupling of fMRI. In our study, we attempted to overcome these limitations and increase the sensitivity of this technique in identification of eloquent cortical areas adjacent to brain tumors by using vasoreactivity features of a breath-holding test and including these data in the BOLD analysis. Local vasoreactivity using a breath-holding paradigm with the same block design of both motor and speech tests was determined in 5 healthy volunteers and 3 patients in the preoperative period (two patients with high grade gliomas and one patient with single metastasis). A coherence-based model was developed for analysis of BOLD fMRI, which took into account altered hemodynamics in peritumoral zones. Obtained coherence maps demonstrated clinically more significant activation zones that were not seen with standard methods of fMRI processing. Thus, neurovascular uncoupling that is known to affect the accuracy of the BOLD fMRI response adjacent to brain tumors may be partially overcome by including an independent measurement of vasoreactivity using a breath-holding test in the BOLD analysis.

The roadmap for estimation of cell-type-specific neuronal activity from non-invasive measurements

The computational properties of the human brain arise from an intricate interplay between billions of neurons connected in complex networks. However, our ability to study these networks in healthy human brain is limited by the necessity to use non-invasive technologies. This is in contrast to animal models where a rich, detailed view of cellular-level brain function with cell-type-specific molecular identity has become available due to recent advances in microscopic optical imaging and genetics. Thus, a central challenge facing neuroscience today is leveraging these mechanistic insights from animal studies to accurately draw physiological inferences from non-invasive signals in humans. On the essential path towards this goal is the development of a detailed 'bottom-up' forward model bridging neuronal activity at the level of cell-type-specific populations to non-invasive imaging signals. The general idea is that specific neuronal cell types have identifiable signatures in the way they drive changes in cerebral blood flow, cerebral metabolic rate of O2 (measurable with quantitative functional Magnetic Resonance Imaging), and electrical currents/potentials (measurable with magneto/electroencephalography). This forward model would then provide the 'ground truth' for the development of new tools for tackling the inverse problem-estimation of neuronal activity from multimodal non-invasive imaging data.This article is part of the themed issue 'Interpreting BOLD: a dialogue between cognitive and cellular neuroscience'.

Cortex-wide BOLD fMRI activity reflects locally-recorded slow oscillation-associated calcium waves

Spontaneous slow oscillation-associated slow wave activity represents an internally generated state which is characterized by alternations of network quiescence and stereotypical episodes of neuronal activity - slow wave events. However, it remains unclear which macroscopic signal is related to these active periods of the slow wave rhythm. We used optic fiber-based calcium recordings of local neural populations in cortex and thalamus to detect neurophysiologically defined slow calcium waves in isoflurane anesthetized rats. The individual slow wave events were used for an event-related analysis of simultaneously acquired whole-brain BOLD fMRI. We identified BOLD responses directly related to onsets of slow calcium waves, revealing a cortex-wide BOLD correlate: the entire cortex was engaged in this specific type of slow wave activity. These findings demonstrate a direct relation of defined neurophysiological events to a specific BOLD activity pattern and were confirmed for ongoing slow wave activity by independent component and seed-based analyses.

When a person is in a deep non-dreaming sleep, neurons in their brain alternate slowly between periods of silence and periods of activity. This gives rise to low-frequency brain rhythms called slow waves, which are thought to help stabilize memories. Slow wave activity can be detected on multiple scales, from the pattern of electrical impulses sent by an individual neuron to the collective activity of the brain’s entire outer layer, the cortex. But does slow wave activity in an individual group of neurons in the cortex affect the activity of the rest of the brain?

To find out, Schwalm, Schmid, Wachsmuth et al. took advantage of the fact that slow waves also occur under general anesthesia, and placed anesthetized rats inside miniature whole-brain scanners. A small region of cortex in each rat had been injected with a dye that fluoresces whenever the neurons in that region are active. An optical fiber was lowered into the rat’s brain to transmit the fluorescence signals to a computer. Monitoring these signals while the animals lay inside the scanner revealed that slow-wave activity in any one group of cortical neurons was accompanied by slow-wave activity across the cortex as a whole. This relationship was seen only for slow waves, and not for other brain rhythms.

Slow waves seem to occur in all species of animal with a backbone, and in both healthy and diseased brains. While it is not possible to inject fluorescent dyes into the human brain, it is possible to monitor neuronal activity using electrodes. Comparing local electrode recordings with measures of whole-brain activity from scanners could thus allow similar experiments to be performed in people. There is growing evidence – from animal models and from studies of patients – that slow waves may be altered in Alzheimer’s disease. Further work is required to determine whether detecting these changes could help diagnose disease at earlier stages, and whether reversing them may have therapeutic potential.

Methods for cleaning the BOLD fMRI signal

Blood oxygen-level-dependent functional magnetic resonance imaging (BOLD fMRI) has rapidly become a popular technique for the investigation of brain function in healthy individuals, patients as well as in animal studies. However, the BOLD signal arises from a complex mixture of neuronal, metabolic and vascular processes, being therefore an indirect measure of neuronal activity, which is further severely corrupted by multiple non-neuronal fluctuations of instrumental, physiological or subject-specific origin. This review aims to provide a comprehensive summary of existing methods for cleaning the BOLD fMRI signal. The description is given from a methodological point of view, focusing on the operation of the different techniques in addition to pointing out the advantages and limitations in their application. Since motion-related and physiological noise fluctuations are two of the main noise components of the signal, techniques targeting their removal are primarily addressed, including both data-driven approaches and using external recordings. Data-driven approaches, which are less specific in the assumed model and can simultaneously reduce multiple noise fluctuations, are mainly based on data decomposition techniques such as principal and independent component analysis. Importantly, the usefulness of strategies that benefit from the information available in the phase component of the signal, or in multiple signal echoes is also highlighted. The use of global signal regression for denoising is also addressed. Finally, practical recommendations regarding the optimization of the preprocessing pipeline for the purpose of denoising and future venues of research are indicated. Through the review, we summarize the importance of signal denoising as an essential step in the analysis pipeline of task-based and resting state fMRI studies.

The Serotonin Receptor 6 Antagonist Idalopirdine and Acetylcholinesterase Inhibitor Donepezil Have Synergistic Effects on Brain Activity-A Functional MRI Study in the Awake Rat

The 5-HT₆ receptor is a promising target for cognitive disorders, in particular for Alzheimer's disease (AD) and other CNS disorders. The high-affinity and selective 5-HT₆ receptor antagonist idalopirdine (Lu AE58054) is currently in development for mild-moderate AD as adjunct therapy to acetylcholinesterase inhibitors (AChEIs). We studied the effects of idalopirdine alone and in combination with the AChEI donepezil on brain activity using BOLD (Blood Oxygen Level Dependent) functional magnetic resonance imaging (fMRI) in the awake rat. Idalopirdine (2 mg/kg, i.v.) alone had a modest effect on brain activity, resulting in activation of eight brain regions at the peak response. Of these, the cholinergic diagonal band of Broca, the infralimbic cortex, the ventral pallidum, the nucleus accumbens shell, and the magnocellular preoptic area were shared with the effects of donepezil (0.3 mg/kg, i.v.). Donepezil alone activated 19 brain regions at the peak response, including several cortical regions, areas of the septo-hippocampal system and the serotonergic raphe nucleus. When idalopirdine and donepezil were combined, there was a robust stimulation pattern with activation of 36 brain regions spread across the extended-amygdala-, striato-pallidal, and septo-hippocampal networks as well as the cholinergic system. These findings indicate that, whilst idalopirdine and donepezil recruit a number of overlapping regions including one of the forebrain cholinergic nuclei, the synergistic effect of both compounds extends beyond the cholinergic system and the effects of donepezil alone toward recruitment of multiple neural circuits and neurotransmitter systems. These data provide new insight into the mechanisms via which idalopirdine might improve cognition in donepezil-treated AD patients.

High spatial correspondence at a columnar level between activation and resting state fMRI signals and local field potentials

Although blood oxygenation level-dependent (BOLD) fMRI has been widely used to map brain responses to external stimuli and to delineate functional circuits at rest, the extent to which BOLD signals correlate spatially with underlying neuronal activity, the spatial relationships between stimulus-evoked BOLD activations and local correlations of BOLD signals in a resting state, and whether these spatial relationships vary across functionally distinct cortical areas are not known. To address these critical questions, we directly compared the spatial extents of stimulated activations and the local profiles of intervoxel resting state correlations for both high-resolution BOLD at 9.4 T and local field potentials (LFPs), using 98-channel microelectrode arrays, in functionally distinct primary somatosensory areas 3b and 1 in nonhuman primates. Anatomic images of LFP and BOLD were coregistered within 0.10 mm accuracy. We found that the point spread functions (PSFs) of BOLD and LFP responses were comparable in the stimulus condition, and both estimates of activations were slightly more spatially constrained than local correlations at rest. The magnitudes of stimulus responses in area 3b were stronger than those in area 1 and extended in a medial to lateral direction. In addition, the reproducibility and stability of stimulus-evoked activation locations within and across both modalities were robust. Our work suggests that the intrinsic resolution of BOLD is not a limiting feature in practice and approaches the intrinsic precision achievable by multielectrode electrophysiology.

Combined fMRI-MRS acquires simultaneous glutamate and BOLD-fMRI signals in the human brain

Combined fMRI-MRS is a novel method to non-invasively investigate functional activation in the human brain using simultaneous acquisition of hemodynamic and neurochemical measures. The aim of the current study was to quantify neural activity using combined fMRI-MRS at 7 T. BOLD-fMRI and semi-LASER localization MRS data were acquired from the visual cortex of 13 participants during short blocks (64 s) of flickering checkerboards. We demonstrate a correlation between glutamate and BOLD-fMRI time courses (R=0.381, p=0.031). In addition, we show increases in BOLD-fMRI (1.43±0.17%) and glutamate concentrations (0.15±0.05 I.U., ~2%) during visual stimulation. In contrast, we observed no change in glutamate concentrations in resting state MRS data during sham stimulation periods. Spectral line width changes generated by the BOLD-response were corrected using line broadening. In summary, our results establish the feasibility of concurrent measurements of BOLD-fMRI and neurochemicals using a novel combined fMRI-MRS sequence. Our findings strengthen the link between glutamate and functional activity in the human brain by demonstrating a significant correlation of BOLD-fMRI and glutamate over time, and by showing ~2% glutamate increases during 64 s of visual stimulation. Our tool may become useful for studies characterizing functional dynamics between neurochemicals and hemodynamics in health and disease.

•

Novel MRI sequence measures hemodynamics and neurochemistry in same TR.

•

Stimulation block duration relevant for functional experiments (64s).

•

BOLD-fMRI and glutamate time courses correlate during functional stimulation.

•

Visual stimulation increases glutamate concentrations.

•

Useful to study fundamental relationship between hemodynamics and neurochemistry.

A method for independent component graph analysis of resting-state fMRI

INTRODUCTION

Independent component analysis (ICA) has been extensively used for reducing task-free BOLD fMRI recordings into spatial maps and their associated time-courses. The spatially identified independent components can be considered as intrinsic connectivity networks (ICNs) of non-contiguous regions. To date, the spatial patterns of the networks have been analyzed with techniques developed for volumetric data.

OBJECTIVE

Here, we detail a graph building technique that allows these ICNs to be analyzed with graph theory.

METHODS

First, ICA was performed at the single-subject level in 15 healthy volunteers using a 3T MRI scanner. The identification of nine networks was performed by a multiple-template matching procedure and a subsequent component classification based on the network "neuronal" properties. Second, for each of the identified networks, the nodes were defined as 1,015 anatomically parcellated regions. Third, between-node functional connectivity was established by building edge weights for each networks. Group-level graph analysis was finally performed for each network and compared to the classical network.

RESULTS

Network graph comparison between the classically constructed network and the nine networks showed significant differences in the auditory and visual medial networks with regard to the average degree and the number of edges, while the visual lateral network showed a significant difference in the small-worldness.

CONCLUSIONS

This novel approach permits us to take advantage of the well-recognized power of ICA in BOLD signal decomposition and, at the same time, to make use of well-established graph measures to evaluate connectivity differences. Moreover, by providing a graph for each separate network, it can offer the possibility to extract graph measures in a specific way for each network. This increased specificity could be relevant for studying pathological brain activity or altered states of consciousness as induced by anesthesia or sleep, where specific networks are known to be altered in different strength.

How do antidepressants influence the BOLD signal in the developing brain?

Depression is a highly prevalent life-threatening disorder, with its first onset commonly occurring during adolescence. Adolescent depression is increasingly being treated with antidepressants, such as fluoxetine. The use of medication during this sensitive period of physiological and cognitive brain development produces neurobiological changes, some of which may outlast the course of treatment. In this review, we look at how antidepressant treatment in adolescence is likely to alter neurovascular coupling and brain energy use and how these changes, in turn, affect our ability to identify neuronal activity changes between participant groups. BOLD (blood oxygen level dependent) fMRI (functional magnetic resonance imaging), the method most commonly used to record brain activity in humans, is an indirect measure of neuronal activity. This means that between-group comparisons – adolescent versus adult, depressed versus healthy, medicated versus non-medicated – rely upon a stable relationship existing between neuronal activity and the BOLD response across these groups. We use data from animal studies to detail the ways in which fluoxetine may alter this relationship, and explore how these alterations may influence the interpretation of BOLD signal differences between groups that have been treated with fluoxetine and those that have not.

Fronto-limbic effective connectivity as possible predictor of antidepressant response to SSRI administration

The timely selection of the optimal treatment for depressed patients is critical to improve remission rates. The detection of pre-treatment variables able to predict differential treatment response may provide novel approaches for treatment selection. Selective serotonin reuptake inhibitors (SSRIs) modulate the fronto-limbic functional response and connectivity, an effect preceding the overt clinical antidepressant effects. Here we investigated whether the cortico-limbic connectivity associated with emotional bias measured before SSRI administration predicts the efficacy of antidepressant treatment in MDD patients. fMRI and Dynamic Causal Modeling (DCM) were combined to study if effective connectivity might differentiate healthy controls (HC) and patients affected by major depression who later responded (RMDD, n=21), or failed to respond (nRMDD, n=12), to 6 weeks of escitalopram administration. Sixteen DCMs exploring connectivity between anterior cingulate cortex (ACC), ventrolateral prefrontal cortex (VLPFC), Amygdala (Amy), and fusiform gyrus (FG) were constructed. Analyses revealed that nRMDD had reduced endogenous connectivity from Amy to VLPFC and to ACC, with an increased connectivity and modulation of the ACC to Amy connectivity when processing of fearful emotional stimuli compared to HC. RMDD and HC did not significantly differ among themselves. Pre-treatment effective connectivity in fronto-limbic circuitry could be an important factor affecting antidepressant response, and highlight the mechanisms which may be involved in recovery from depression. These results suggest that fronto-limbic connectivity might provide a neural biomarker to predict the clinical outcome to SSRIs administration in major depression.

Physiological basis of vascular autocalibration (VasA): Comparison to hypercapnia calibration methods

Purpose

The statistical power of functional MRI (fMRI) group studies is significantly hampered by high intersubject spatial and magnitude variance. We recently presented a vascular autocalibration method (VasA) to account for vascularization differences between subjects and hence improve the sensitivity in group studies. Here, we validate the novel calibration method by means of direct comparisons of VasA with more established measures of baseline venous blood volume (and indirectly vascular reactivity), the M‐value.

Methods

Seven healthy volunteers participated in two 7 T (T) fMRI experiments to compare M‐values with VasA estimates: (i) a hypercapnia experiment to estimate voxelwise M‐value maps, and (ii) an fMRI experiment using visual stimulation to estimate voxelwise VasA maps.

Results

We show that VasA and M‐value calibration maps show the same spatial profile, providing strong evidence that VasA is driven by local variations in vascular reactivity as reflected in the M‐value.

Conclusion

The agreement of vascular reactivity maps obtained with VasA when compared with M‐value maps confirms empirically the hypothesis that the VasA method is an adequate tool to account for variations in fMRI response amplitudes caused by vascular reactivity differences in healthy volunteers. VasA can therefore directly account for them and increase the statistical power of group studies. The VasA toolbox is available as a statistical parametric mapping (SPM) toolbox, facilitating its general application. Magn Reson Med 78:1168–1173, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.