The confound of hemodynamic response function variability in human resting-state functional MRI studies

Functional magnetic resonance imaging (fMRI) is an indirect measure of neural activity with the hemodynamic response function (HRF) coupling it with unmeasured neural activity. The HRF, modulated by several non-neural factors, is variable across brain regions, individuals and populations. Yet, a majority of human resting-state fMRI connectivity studies continue to assume a non-variable HRF. In this article, with supportive prior evidence, we argue that HRF variability cannot be ignored as it substantially confounds within-subject connectivity estimates and between-subjects connectivity group differences. We also discuss its clinical relevance with connectivity impairments confounded by HRF aberrations in several disorders. We present limited data on HRF differences between women and men, which resulted in a 15.4% median error in functional connectivity estimates in a group-level comparison. We also discuss the implications of HRF variability for fMRI studies in the spinal cord. There is a need for more dialogue within the community on the HRF confound, and we hope that our article is a catalyst in the process

Disambiguating the role of blood flow and global signal with partial information decomposition

Global signal (GS) is an ubiquitous construct in resting state functional magnetic resonance imaging (rs-fMRI), associated to nuisance, but containing by definition most of the neuronal signal. Global signal regression (GSR) effectively removes the impact of physiological noise and other artifacts, but at the same time it alters correlational patterns in unpredicted ways. Performing GSR taking into account the underlying physiology (mainly the blood arrival time) has been proven to be beneficial. From these observations we aimed to: 1) characterize the effect of GSR on network-level functional connectivity in a large dataset; 2) assess the complementary role of global signal and vessels; and 3) use the framework of partial information decomposition to further look into the joint dynamics of the global signal and vessels, and their respective influence on the dynamics of cortical areas. We observe that GSR affects intrinsic connectivity networks in the connectome in a non-uniform way. Furthermore, by estimating the predictive information of blood flow and the global signal using partial information decomposition, we observe that both signals are present in different amounts across intrinsic connectivity networks. Simulations showed that differences in blood arrival time can largely explain this phenomenon, while using hemodynamic and calcium mouse recordings we were able to confirm the presence of vascular effects, as calcium recordings lack hemodynamic information. With these results we confirm network-specific effects of GSR and the importance of taking blood flow into account for improving de-noising methods. Additionally, and beyond the mere issue of data denoising, we quantify the diverse and complementary effect of global and vessel BOLD signals on the dynamics of cortical areas

Statistical approaches for resting state fMRI data analysis

This doctoral dissertation investigates the methodology to explore brain dynamics from resting state fMRI data. A standard resting state fMRI study gives rise to massive amounts of noisy data with a complicated spatio-temporal correlation structure. There are two main objectives in the analysis of these noisy data: establishing the link between neural activity and the measured signal, and determining distributed brain networks that correspond to brain function. These measures can then be used as indicators of psychological, cognitive or pathological states. Two main issues will be addressed: retrieving and interpreting the hemodynamic response function (HRF) at rest, and dealing with the redundancy inherent to fMRI data. Novel approaches are introduced, discussed and validated on simulated data and on real datasets, in health and disease, in order to track modulation of brain dynamics and HRF across different pathophysiological conditions

Early Experience And The Development Of Dopaminergic Circuitry

The developing brain is highly malleable, meaning that children are acutely sensitive to their early experiences, for better or for worse. Early adversity significantly increases the risk for psychopathology and learning challenges. Recent work in animal models powerfully suggests that the ventral tegmental area (VTA), a major source of dopaminergic projections to the rest of the brain, is a key mediator for how early stressful experiences can become biologically embedded: in mice, absent or disrupted caregiving results in latent vulnerability of the dopaminergic system to stress well into adulthood. Thus, it may be that early adversity causes a shift in the developmental trajectory of the VTA, with cascading effects on later motivational and socioemotional processes. However, little is known about whether similar disruptions in VTA circuitry are detectable in children. Thus, I leveraged fMRI methods in 4- to 10-year-old children, to examine the functional integrity of dopaminergic circuitry early in development. In Chapter 2, I tested whether stress exposure relates to VTA resting-state functional connectivity. I found an age x stress exposure interaction, such that only children with lower stress exposure showed a positive relationship between age and VTA-mPFC connectivity, consistent with an interpretation that high stress exposure is related to blunted VTA maturation. Chapter 3 examined children’s neural responses to naturalistic emotional content using movie fMRI, and linked to parenting behaviors observed in the lab. I found that children who experienced more negative parenting showed reduced VTA activity during positive emotion scenes. Finally, Chapter 4 examined curiosity, a behavior that is supported by dopaminergic circuitry, and that encourages greater learning by engaging positive interest and intrinsic motivation. I tested whether individual differences in curiosity are reflected in resting-state connectivity patterns, and can be predicted by environmental experiences. Together, this work suggests that early experiences play a critical role in tuning dopaminergic neurocircuitry in children, with potentially enduring consequences for reward and socioemotional processing. This has implications both for education and for policy: how can we protect children in negative environments, and provide positive support that will allow them to best thrive as learners

The Correlation between Astrocytic Calcium and fMRI Signals is Related to the Thalamic Regulation of Cortical States

BOLD fMRI has been wildly used for mapping brain activity, but the cellular contribution of BOLD signals is still controversial. In this study, we investigated the correlation between neuronal/astrocytic calcium and the BOLD signal using simultaneous GCaMP-mediated calcium and BOLD signal recording, in the event-related state and in resting state, in anesthetized and in free-moving rats. To our knowledge, the results provide the first demonstration that evoked and intrinsic astrocytic calcium signals could occur concurrently accompanied by opposite BOLD signals which are associated with vasodilation and vasoconstriction. We show that the intrinsic astrocytic calcium is involved in brain state changes and is related to the activation of central thalamus. First, by simultaneous LFP and fiber optic calcium recording, the results show that the coupling between LFP and calcium indicates that neuronal activity is the basis of the calcium signal in both neurons and astrocytes. Second, we found that evoked neuronal and astrocytic calcium signals are always positively correlated with BOLD responses. However, intrinsic astrocytic calcium signals are accompanied by the activation of the central thalamus followed by a striking negative BOLD signal in cortex, which suggests that central thalamus may be involved in the initiation of the intrinsic astrocytic calcium signal. Third, we confirmed that the intrinsic astrocytic calcium signal is preserved in free moving rats. Moreover, the occurrences of intrinsic astrocytic calcium spikes are coincident with the transition between different sleep stages, which suggests intrinsic astrocytic calcium spikes reflect brain state transitions. These results demonstrate that the correlation between astrocytic calcium and fMRI signals is related to the thalamic regulation of cortical states. On the other hand, by studying the relationship between vessel–specific BOLD signals and spontaneous calcium activity from adjacent neurons, we show that low frequency spontaneous neuronal activity is the cellular mechanism of the BOLD signal during resting state

Metabolic and Blood Flow Properties of Functional Brain Networks Using Human Multimodal Neuroimaging

The brain has a high energetic cost to support neuronal activity, requiring both oxygen and glucose supply from the cerebral vascular system. Additionally, the brain functions through complex patterns of interconnectivity between neuronal assemblies giving rise to functional network architectures that can be investigated across multiple spatial scales. Different brain regions have different roles and importance within these network architectures, with some regions exhibiting more global importance by being involved in cross-network communication while other being predominantly involved in local connections. There are indications that regions exhibiting a more global role in inter networks connectivity are characterized by a higher and more efficient metabolic profile, leading to differences in metabolic properties when compared to more locally connected regions. Understanding the link between oxygen/glucose metabolism and functional features of brain network architectures, across different spatial scales, is of primary importance. This thesis consists of three original studies combining human brain resting-state multimodal neuroimaging and transcriptional data to investigate the glucose/oxygen metabolic costs of brain functional connectivity. We quantified glucose metabolism from positron emission tomography, and oxygen metabolism and functional connectivity from magnetic resonance imaging. In the first study, we highlight how the oxygen/glucose metabolism of brain regions can non-linearly relate to their functional hubness, within the resting-state networks of the brain across a nested hierarchy. We found that an increase in oxygen/glucose metabolism is associated with a non-linear increase in functional hubness where increase rates are both network- and scale-dependent. In the second study, we show specific transcriptional signatures that characterize the oxygen/glucose metabolic costs of regions involved in network global versus local centrality. This study highlights the different metabolic profiles of local and global regions, with gene expression related to oxidative metabolism and synaptic pathways being enriched in association with spatial patterns in common with resting blood flow and metabolism (oxygen and glucose) and globally-connected regions. In the third study, we demonstrate that there are oxygen/glucose metabolic costs to the functional integration and segregation of resting-state networks. We highlight that the metabolic costs of functional integration could reflect the hierarchical organization of the brain from unimodal to transmodal regions