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Functional magnetic resonance imaging (fMRI) of blood oxygenation level dependent (BOLD) signals during the resting-state is widely used to study functional connectivity (FC) of slowly fluctuating ongoing brain activity (BOLD-FC) in humans with and without brain diseases. While physiological impairments, e.g. aberrant perfusion or vascular reactivity, are common in neurological and psychiatric disorders, their impact on BOLD-FC is widely unknown and ignored. The aim of our simulation study, therefore, was to investigate the influence of impaired neurovascular coupling on resting-state BOLD-FC. Simulated BOLD signals comprising intra- and extravascular contributions were derived from an adjusted balloon model, which allows for independent definitions of cerebral blood flow (CBF) and cerebral metabolic rate of oxygen (CMRO2) responses, being elicited by a synthetic oscillatory input signal with low frequency (0.05 ​Hz) amplitude modulations. BOLD-FC was then defined by correlations between physiological reference BOLD time curves (seeds of seed-based BOLD-FC) and the test BOLD time curves (targets of BOLD-FC) featuring altered physiological variables (CMRO2, CBF, cerebral blood volume (CBV)). Impact of impaired neurovascular coupling on BOLD-FC was investigated for three different scenarios with independent changes in (1) CBF and CMRO2amplitudes, (2) CBF and CMRO2delays, and (3) coupling between CBF and CBV. For scenario 1, we found ‘linear’ influences of CMRO2 and CBF amplitudes on BOLD-FC: for a given CMRO2 amplitude, BOLD-FC changes from negative to positive FC with increasing CBF amplitude, and increasing CMRO2 amplitude simply shifts this dependence linearly. For scenario 2, CMRO2 and CBF delays had a complex ‘non-linear’ effect on BOLD-FC: for small CMRO2 delays, we found that BOLD-FC changes from positive to negative BOLD-FC with increasing CBF delays, but for large CMRO2 delays positive BOLD-FC simply diminishes with increasing CBF delay. For scenario 3, changes in CBF-CBV coupling have almost no effect on BOLD-FC. All these changes were not critically influenced by both signal-to-noise-ratio and temporal resolution modulations. Our results demonstrate the importance of alterations in neurovascular coupling for aberrant resting-state BOLD-FC. Based on our data, we suggest to complement BOLD-FC studies, at least of at-risk patient populations, with perfusion and oxygenation sensitive MRI. In cases where this is not available, we recommend careful interpretation of BOLD-FC results considering previous findings about hemodynamic-metabolic changes. In the future, accurate modeling of the hemodynamic-metabolic context might improve both our understanding of the crucial interplay between vascular-hemodynamic-neuronal components of intrinsic BOLD-FC and the evaluation of aberrant BOLD-FC in brain diseases with vascular-hemodynamic impairments. •Neurovascular coupling crucially impacts on BOLD-based functional connectivity.•CMRO2, CBF, and CBV amplitudes, delays and coupling distinctly modulate BOLD-FC.•Modeling hemodynamic impairments allows to scrutinize contributions to BOLD-FC.•BOLD signal modeling might finally increase fidelity of BOLD-FC studies in patients.

•Capillary transit time heterogeneity (CTH) impacts on BOLD-FC.•Simulations indicate impact of local CBF response timing on BOLD-FC.•CTH may indicate broadened and delayed CBF responses.•Hemodynamic impairments need to be considered in BOLD-FC interpretation. Functional connectivity (FC) derived from blood oxygenation level dependent (BOLD) functional magnetic resonance imaging at rest (rs-fMRI), is commonly interpreted as indicator of neuronal connectivity. In a number of brain disorders, however, metabolic, vascular, and hemodynamic impairments can be expected to alter BOLD-FC independently from neuronal activity. By means of a neurovascular coupling (NVC) model of BOLD-FC, we recently demonstrated that aberrant timing of cerebral blood flow (CBF) responses may influence BOLD-FC. In the current work, we support and extend this finding by empirically linking BOLD-FC with capillary transit time heterogeneity (CTH), which we consider as an indicator of delayed and broadened CBF responses. We assessed 28 asymptomatic patients with unilateral high-grade internal carotid artery stenosis (ICAS) as a hemodynamic lesion model with largely preserved neurocognitive functioning and 27 age-matched healthy controls. For each participant, we obtained rs-fMRI, arterial spin labeling, and dynamic susceptibility contrast MRI to study the dependence of left-right homotopic BOLD-FC on local perfusion parameters. Additionally, we investigated the dependency of BOLD-FC on CBF response timing by detailed simulations. Homotopic BOLD-FC was negatively associated with increasing CTH differences between homotopic brain areas. This relation was more pronounced in asymptomatic ICAS patients even after controlling for baseline CBF and relative cerebral blood volume influences. These findings match simulation results that predict an influence of delayed and broadened CBF responses on BOLD-FC. Results demonstrate that increasing CTH differences between homotopic brain areas lead to BOLD-FC reductions. Simulations suggest that CTH increases correspond to broadened and delayed CBF responses to fluctuations in ongoing neuronal activity. [Display omitted] .

Spin-echo (SE) BOLD fMRI has high microvascular specificity, and thus provides a more reliable means to localize neural activity compared to conventional gradient-echo BOLD fMRI. However, the most common SE BOLD acquisition method, SE-EPI, is known to suffer from T2′ contrast contamination with undesirable draining vein bias. To address this, in this study, we extended a recently developed distortion/blurring-free multi-shot EPI technique, Echo-Planar Time-resolved Imaging (EPTI), to cortical-depth dependent SE-fMRI at 7T to test whether it could provide purer SE BOLD contrast with minimal T2′ contamination for improved neuronal specificity. From the same acquisition, the time-resolved feature of EPTI also provides a series of asymmetric SE (ASE) images with varying T2′ weightings, and enables extraction of data equivalent to conventional SE EPI with different echo train lengths (ETLs). This allows us to systematically examine how T2′-contribution affects different SE acquisition strategies using a single dataset. A low-rank spatiotemporal subspace reconstruction was implemented for the SE-EPTI acquisition, which incorporates corrections for both shot-to-shot phase variations and dynamic B0 drifts. SE-EPTI was used in a visual task fMRI experiment to demonstrate that i) the pure SE image provided by EPTI results in the highest microvascular specificity; ii) the ASE EPTI series, with a graded introduction of T2′ weightings at time points farther away from the pure SE, show a gradual sensitivity increase along with increasing draining vein bias; iii) the longer ETL seen in conventional SE EPI acquisitions will induce more draining vein bias. Consistent results were observed across multiple subjects, demonstrating the robustness of the proposed technique for SE-BOLD fMRI with high specificity.

Resting state functional magnetic resonance (rs-fMRI) imaging offers insights into how different brain regions are connected into functional networks. It was recently shown that networks that are almost identical to the ones created from conventional correlation analysis can be obtained from a subset of high-amplitude data, suggesting that the functional networks may be driven by instantaneous co-activations of multiple brain regions rather than ongoing oscillatory processes. The rs-fMRI studies, however, rely on the blood oxygen level dependent (BOLD) signal, which is only indirectly sensitive to neural activity through neurovascular coupling. To provide more direct evidence that the neuronal co-activation events produce the time-varying network patterns seen in rs-fMRI studies, we examined the simultaneous rs-fMRI and local field potential (LFP) recordings in rats performed in our lab over the past several years. We developed complementary analysis methods that focus on either the temporal or spatial domain, and found evidence that the interaction between LFP and BOLD may be driven by instantaneous co-activation events as well. BOLD maps triggered on high-amplitude LFP events resemble co-activation patterns created from rs-fMRI data alone, though the co-activation time points are defined differently in the two cases. Moreover, only LFP events that fall into the highest or lowest thirds of the amplitude distribution result in a BOLD signal that can be distinguished from noise. These findings provide evidence of an electrophysiological basis for the time-varying co-activation patterns observed in previous studies. •The relationship between LFP and BOLD is dominated by the high-amplitude events.•FMRI frames that co-occur with high LFP events can resemble LFP-BOLD correlation map.•Such fMRI frames can be divided into a few groups showing distinct spatial patterns.•Multimodal methods might provide insights into dynamic functional connectivity.

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. •Numerous techniques are available for denoising the BOLD fMRI signal.•Motion-related artifacts and physiological noise fluctuations are the main targets.•Phase-based and multi-echo fMRI can help to improve the performance of denoising.•There exist multiple equally-efficient alternatives to global signal regression.•There is no “best” method for preprocessing, but there are incorrect methods.

•High-resolution 7T SE-BOLD fMRI was employed to observe fine-scale structures in M1.•SE-BOLD fMRI showed higher spatial specificity compared to GE-BOLD fMRI, providing non-invasive evidence of fine-grained organizational patterns.•An MR-compatible data glove was used to record hand motion in real-time during fMRI acquisition. The human primary motor cortex (M1) follows a well-established somatotopic organization, yet finer-scale representations, such as mirrored finger maps, have remained difficult to resolve non-invasively. To investigate movement representations in an action-based framework rather than a strictly somatotopic layout, we conducted both conventional gradient-echo (GE) and highly specific spin-echo (SE) BOLD fMRI at 7 T with 1 mm isotropic resolution. Subjects performed 1-Hz visually-instructed thumb–index finger or thumb–ring finger opposition tasks, and their finger movements were recorded using an MR-compatible data glove to verify proper task performance. In each subject, the activated M1 region spanning multiple slices was subdivided into ten columns along a medial-to-lateral axis. Finger dominance (index vs. ring) was determined within each column. In GE-BOLD fMRI, two distinct tasks exhibited similar activation patterns across columns, reflecting its limited ability to resolve columnar activation differences due to contamination from draining vein effects. In contrast, SE-BOLD fMRI revealed alternating task dominance across columns, demonstrating higher spatial specificity compared to GE-BOLD. By integrating SE-BOLD fMRI, but not GE-BOLD, with behavioral data, we present a more accurate mesoscopic mapping of motor activity in individual subjects. These findings provide non-invasive evidence of fine-grained motor organization, demonstrating the utility of SE-BOLD contrast for mapping mesoscopic representations.

Among agents of selection that shape phenotypic traits in animals, humans can cause more rapid changes than many natural factors. Studies have focused on human selection of morphological traits, but little is known about human selection of behavioural traits. By monitoring elk (Cervus elaphus) with satellite telemetry, we tested whether individuals harvested by hunters adopted less favourable behaviours than elk that survived the hunting season. Among 45 2-year-old males, harvested elk showed bolder behaviour, including higher movement rate and increased use of open areas, compared with surviving elk that showed less conspicuous behaviour. Personality clearly drove this pattern, given that inter-individual differences in movement rate were present before the onset of the hunting season. Elk that were harvested further increased their movement rate when the probability of encountering hunters was high (close to roads, flatter terrain, during the weekend), while elk that survived decreased movements and showed avoidance of open areas. Among 77 females (2–19 y.o.), personality traits were less evident and likely confounded by learning because females decreased their movement rate with increasing age. As with males, hunters typically harvested females with bold behavioural traits. Among less-experienced elk (2–9 y.o.), females that moved faster were harvested, while elk that moved slower and avoided open areas survived. Interestingly, movement rate decreased as age increased in those females that survived, but not in those that were eventually harvested. The latter clearly showed lower plasticity and adaptability to the local environment. All females older than 9 y.o. moved more slowly, avoided open areas and survived. Selection on behavioural traits is an important but often-ignored consequence of human exploitation of wild animals. Human hunting could evoke exploitation-induced evolutionary change, which, in turn, might oppose adaptive responses to natural and sexual selection.

Monte Carlo simulations have been used to analyze oxygenation-related signal changes in pass-band balanced steady state free precession (bSSFP) as well as in gradient echo (GE) and spin echo (SE) sequences. Signal changes were calculated for artificial cylinders and neurovascular networks acquired from the mouse parietal cortex by two-photon laser scanning microscopy at 1 μm isotropic resolution. Signal changes as a function of vessel size, blood volume, vessel orientation to the main magnetic field B0 as well as relations of intra- and extravascular and of micro- and macrovascular contributions have been analyzed. The results show that bSSFP is highly sensitive to extravascular and microvascular components. Furthermore, GE and bSSFP, and to a lesser extent SE, exhibit a strong dependence of their signal change on the orientation of the vessel network to B0. •The contribution from capillaries is highest for SE, followed by bSSFP and is much lower for GE.•The intravascular contribution of bSSFP and SE is in the range of 5–10%, and negligible for GE at 9.4T.•BOLD signal change of GE, SE and bSSFP depend on orientation of cortex to B0.

Abstract BACKGROUND Use of conventional blood oxygen level-dependent functional magnetic resonance imaging (conventional-BOLD-fMRI) presents challenges in accurately identifying the hand-motor cortex when a glioma involves the ipsilateral hand-knob. Zoomed imaging technique with parallel transmission (ZOOMit)-BOLD is a novel sequence allowing high spatial resolution with a relatively small field of view that may solve this problem. OBJECTIVE To compare the accuracy of ZOOMit-BOLD and conventional-BOLD in hand-motor cortex identification. METHODS A total of 20 patients with gliomas involving the sensorimotor cortex were recruited to identify the hand-motor cortex by both ZOOMit-BOLD and conventional-BOLD. Based on whether the entire or partial glioma directly invaded (was located within) the hand-knob or indirectly affected it by proximity, patients were placed into the involved or uninvolved groups, respectively. Direct cortical stimulation was applied intraoperatively to verify the location of the hand-motor cortex. Overlap indices were used to evaluate the accuracy of the hand-motor cortex identification. An overlap index equal to 0, indicating lack of overlap, was classified as inaccurate classification. RESULTS The accuracy of motor-cortex identification with ZOOMit-BOLD was 100% compared to only 65% with conventional-BOLD. The average overlap index yielded by ZOOMit-BOLD was higher than that of conventional-BOLD, regardless of whether gliomas directly invaded the hand-knob (P = .008) or not (P = .004). The overlap index in the involved group was significantly lower than that in the uninvolved group with both ZOOMit-BOLD (P = .002) and conventional-BOLD (P < .001). CONCLUSION ZOOMit-BOLD may potentially replace conventional-BOLD to identify the hand-motor cortex, particularly in cases in which gliomas directly invade the hand-knob.

•From rest to task, GSCORR reduces in sensory but increases in associative areas.•Reallocation of functional resources from sensory to associative regions at task.•Two distinct clusters of areas are recruited during GO and STOP trials.•GSCORR correlates with deactivation rather than activation.•GSCORR, activation and deactivation reflect distinct neurofunctional processes. The dynamics of global, state-dependent reconfigurations in brain connectivity are yet unclear. We aimed at assessing reconfigurations of the global signal correlation coefficient (GSCORR), a measure of the connectivity between each voxel timeseries and the global signal, from resting-state to a stop-signal task. The secondary aim was to assess the relationship between GSCORR and blood-oxygen-level-dependent (BOLD) activations or deactivation across three different trial-conditions (GO, STOP-correct, and STOP-incorrect). As primary analysis we computed whole-brain, voxel-wise GSCORR during resting-state (GSCORR-rest) and stop-signal task (GSCORR-task) in 107 healthy subjects aged 21–50, deriving GSCORR-shift as GSCORR-task minus GSCORR-rest. GSCORR-tr and trGSCORR-shift were also computed on the task residual time series to quantify the impact of the task-related activity during the trials. To test the secondary aim, brain regions were firstly divided in one cluster showing significant task-related activation and one showing significant deactivation across the three trial conditions. Then, correlations between GSCORR-rest/task/shift and activation/deactivation in the two clusters were computed. As sensitivity analysis, GSCORR-shift was computed on the same sample after performing a global signal regression and GSCORR-rest/task/shift were correlated with the task performance. Sensory and temporo-parietal regions exhibited a negative GSCORR-shift. Conversely, associative regions (ie. left lingual gyrus, bilateral dorsal posterior cingulate gyrus, cerebellum areas, thalamus, posterolateral parietal cortex) displayed a positive GSCORR-shift (FDR-corrected p < 0.05). GSCORR-shift showed similar patterns to trGSCORR-shift (magnitude increased) and after global signal regression (magnitude decreased). Concerning BOLD changes, Brodmann area 6 and inferior parietal lobule showed activation, while posterior parietal lobule, cuneus, precuneus, middle frontal gyrus showed deactivation (FDR-corrected p < 0.05). No correlations were found between GSCORR-rest/task/shift and beta-coefficients in the activation cluster, although negative correlations were observed between GSCORR-task and GO/STOP-correct deactivation (Pearson rho=-0.299/-0.273; Bonferroni-p < 0.05). Weak associations between GSCORR and task performance were observed (uncorrected p < 0.05). GSCORR state-dependent reconfiguration indicates a reallocation of functional resources to associative areas during stop-signal task. GSCORR, activation and deactivation may represent distinct proxies of brain states with specific neurofunctional relevance.