Genes influence the amplitude and timing of brain hemodynamic responses

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.

Improvement of olfactory fMRI activation and hemodynamic response function curve with respiration correction

BACKGROUND

Odor perception is highly dependent on respiration, however, the asynchronization between inspiration and odor delivery results in a decreased activation and hemodynamic response function (HRF) curve in olfactory functional MRI (fMRI). This study aimed to investigate the effect of a data post-processing method to minimize the asynchronization and consequently improve the olfactory activation and HRF curve and compare it between different TRs (3 s and 1 s).

NEW METHOD

A new data post-processing method of respiration correction based on olfactory perception was investigated.

COMPARISON WITH EXISTING METHODS

The odor stimuli of olfactory fMRI were mostly based on odor deliveries. But for the reason of respiration, the time of olfactory perception might be a little different. The actual onset time and duration of odor stimuli were modified based on the respiration data.

RESULTS

For 3 s TR data, an increased number of activated voxels and higher HRF curves response height were obtained with the respiration correction method in the primary olfactory cortex (POC) (P = 0.034 and 0.009) and insula (P = 0.024 and 0.001), compared with the uncorrected method. But the activated voxels and response height of the anterior cingulate cortex (ACC) did not differ between uncorrected and respiration correction methods (P = 0.102 and 0.200). The time to peak of the HRF curve was shorter with the respiration correction method in all ROIs (all P < 0.05), compared with the uncorrected method. Whereas there were no significant differences between the uncorrected and corrected results for 1 s TR data.

CONCLUSIONS

The post-processing method of respiration correction could effectively minimize the asynchronization between respirations and odor deliveries, and improve the activations and HRF curves for a routine 3 s TR olfactory fMRI data.

Characterization of Hemodynamic Alteration in Parkinson's Disease and Effect on Resting-State Connectivity

Functional magnetic resonance imaging (fMRI) is a convolution of latent neural activity and the hemodynamic response function (HRF). According to prior studies, the neurodegenerative process in idiopathic Parkinson's Disease (PD) interacts significantly with neuromuscular abnormalities. Although these underlying neuromuscular changes might influence the temporal characteristics of HRF and fMRI signals, relatively few studies have explored this possibility. We hypothesized that such alterations would engender changes in estimated functional connectivity (FC) in fMRI space compared to latent neural space. To test these theories, we calculated voxel-level HRFs by deconvolving resting-state fMRI data from PD patients (n = 61) and healthy controls (HC) (n = 47). Significant group differences in HRF (P < 0.05, Gaussian random field-corrected) were observed in several regions previously associated with PD. Subsequently, we focused on putamen-seed-based FC differences between the PD and HC groups using fMRI and latent neural signals. The results suggested that neglecting HRF variability may cultivate false-positive and false-negative FC group differences. Furthermore, HRF was related to dopamine receptor type 2 (DRD2) gene expression (P < 0.001, t = -7.06, false discover rate-corrected). Taken together, these findings reveal HRF variation and its possible underlying molecular mechanism in PD, and suggest that deconvolution could reduce the impact of HRF variation on FC group differences.

Reconstruction of time-shifted hemodynamic response

Regression of voxel time course onto expected response is a standard procedure in functional magnetic resonance imaging that relies on exact onset time and shape of superimposed hemodynamic response functions. Elegant capture of time deviation by time derivative regressors appears complicated by shape distortion and limited to ±1 s, and is usually not exploited for reconstructing the true time-shifted response function together with its magnitude. This analysis of the time-derivative approach provides closed-form functional relations between time shift and regression coefficients that allow for hemodynamic shifts of ±5 s and can explain shape distortion and reconstruction behavior. Reliable absolute latencies were no smaller than 0.6 s in a best-case experiment. Confusions of latency are a previously undiscussed shortcoming where current limitation strategy may eliminate correct latencies and protect incorrect ones.

Cerebral blood flow predicts multiple demand network activity and fluid intelligence across the adult lifespan

The preservation of cognitive function in old age is a public health priority. Cerebral hypoperfusion is a hallmark of dementia but its impact on maintaining cognitive ability across the lifespan is less clear. We investigated the relationship between baseline cerebral blood flow (CBF) and blood oxygenation level-dependent (BOLD) response during a fluid reasoning task in a population-based adult lifespan cohort. As age differences in CBF could lead to non-neuronal contributions to the BOLD signal, we introduced commonality analysis to neuroimaging to dissociate performance-related CBF effects from the physiological confounding effects of CBF on the BOLD response. Accounting for CBF, we confirmed that performance- and age-related differences in BOLD responses in the multiple-demand network were implicated in fluid reasoning. Age differences in CBF explained not only performance-related BOLD responses but also performance-independent BOLD responses. Our results suggest that CBF is important for maintaining cognitive function, while its non-neuronal contributions to BOLD signals reflect an age-related confound. Maintaining perfusion into old age may serve to support brain function and preserve cognitive performance.

Heritability of REM sleep neurophysiology in adolescence

Alterations of rapid eye movement (REM) sleep have long been observed in patients with psychiatric disorders and proposed as an endophenotype-a link between behavior and genes. Recent experimental work has shown that REM sleep plays an important role in the emotional processing of memories, emotion regulation, and is altered in the presence of stress, suggesting a mechanism by which REM sleep may impact psychiatric illness. REM sleep shows a developmental progression and increases during adolescence-a period of rapid maturation of the emotional centers of the brain. This study uses a behavioral genetics approach to understand the relative contribution of genes, shared environmental and unique environmental factors to REM sleep neurophysiology in adolescents. Eighteen monozygotic (MZ; n = 36; 18 females) and 12 dizygotic (DZ; n = 24; 12 females) same-sex twin pairs (mean age = 12.46; SD = 1.36) underwent whole-night high-density sleep EEG recordings. We find a significant genetic contribution to REM sleep EEG power across frequency bands, explaining, on average, between 75 to 88% of the variance in power, dependent on the frequency band. In the lower frequency bands between delta and sigma, however, we find an additional impact of shared environmental factors over prescribed regions. We hypothesize that these regions may reflect the contribution of familial and environmental stress shared amongst the twins. The observed strong genetic contribution to REM sleep EEG power in early adolescence establish REM sleep neurophysiology as a potentially strong endophenotype, even in adolescence-a period marked by significant brain maturation.

Characterization of Hemodynamic Alterations in Schizophrenia and Bipolar Disorder and Their Effect on Resting-State fMRI Functional Connectivity

Common and distinct neural bases of Schizophrenia (SZ) and bipolar disorder (BP) have been explored using resting-state fMRI (rs-fMRI) functional connectivity (FC). However, fMRI is an indirect measure of neural activity, which is a convolution of the hemodynamic response function (HRF) and latent neural activity. The HRF, which models neurovascular coupling, varies across the brain within and across individuals, and is altered in many psychiatric disorders. Given this background, this study had three aims: quantifying HRF aberrations in SZ and BP, measuring the impact of such HRF aberrations on FC group differences, and exploring the genetic basis of HRF aberrations. We estimated voxel-level HRFs by deconvolving rs-fMRI data obtained from SZ (N = 38), BP (N = 19), and matched healthy controls (N = 35). We identified HRF group differences (P < .05, FDR corrected) in many regions previously implicated in SZ/BP, with mediodorsal, habenular, and central lateral nuclei of the thalamus exhibiting HRF differences in all pairwise group comparisons. Thalamus seed-based FC analysis revealed that ignoring HRF variability results in false-positive and false-negative FC group differences, especially in insula, superior frontal, and lingual gyri. HRF was associated with DRD2 gene expression (P < .05, 1.62 < |Z| < 2.0), as well as with medication dose (P < .05, 1.75 < |Z| < 3.25). In this first study to report HRF aberrations in SZ and BP, we report the possible modulatory effect of dopaminergic signalling on HRF, and the impact that HRF variability can have on FC studies in clinical samples. To mitigate the impact of HRF variability on FC group differences, we suggest deconvolution during data preprocessing.

Separating vascular and neuronal effects of age on fMRI BOLD signals

Accurate identification of brain function is necessary to understand the neurobiology of cognitive ageing, and thereby promote well-being across the lifespan. A common tool used to investigate neurocognitive ageing is functional magnetic resonance imaging (fMRI). However, although fMRI data are often interpreted in terms of neuronal activity, the blood oxygenation level-dependent (BOLD) signal measured by fMRI includes contributions of both vascular and neuronal factors, which change differentially with age. While some studies investigate vascular ageing factors, the results of these studies are not well known within the field of neurocognitive ageing and therefore vascular confounds in neurocognitive fMRI studies are common. Despite over 10 000 BOLD-fMRI papers on ageing, fewer than 20 have applied techniques to correct for vascular effects. However, neurovascular ageing is not only a confound in fMRI, but an important feature in its own right, to be assessed alongside measures of neuronal ageing. We review current approaches to dissociate neuronal and vascular components of BOLD-fMRI of regional activity and functional connectivity. We highlight emerging evidence that vascular mechanisms in the brain do not simply control blood flow to support the metabolic needs of neurons, but form complex neurovascular interactions that influence neuronal function in health and disease. This article is part of the theme issue 'Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity'.

Environmental Factors Shape Sleep EEG Connectivity During Early Adolescence

Quantifying the degree to which genetic and environmental factors shape brain network connectivity is critical to furthering our understanding of the developing human brain. Sleep, a state of sensory disengagement, provides a unique opportunity to study brain network activity noninvasively by means of sleep electroencephalography (EEG) coherence. We conducted a high-density sleep EEG study in monozygotic (MZ; n = 38; mean age = 12.46; 20 females) and dizygotic (DZ; n = 24; mean age = 12.50; 12 females) twins to assess the heritability of sleep EEG coherence in early adolescence—a period of significant brain rewiring. Structural equation modeling was used to estimate three latent factors: genes, environmental factors shared between twins and environmental factors unique to each twin. We found a strong contribution of unique environmental factors (66% of the variance) and moderate genetic influence (19% of the variance) on sleep EEG coherence across frequencies and sleep states. An exception to this was sleep spindle activity, an index of the thalamocortical network, which showed on average a genetic contribution of 48% across connections. Furthermore, we observed high intraindividual stability of coherence across two consecutive nights suggesting that despite only a modest genetic contribution, sleep EEG coherence is like a trait. Our findings in adolescent humans are in line with earlier findings in animals that show the primordial cerebral map and its connections are plastic and it is through interaction with the environment that the pattern of brain network connectivity is shaped. Therefore, even in twins living together, small differences in the environment may cascade into meaningful differences in brain connectivity.

Altered Neurobiological Processing of Unintentional Social Norm Violations: A Multiplex, Multigenerational Functional Magnetic Resonance Imaging Study on Social Anxiety Endophenotypes

BACKGROUND

Patients with social anxiety disorder (SAD) fear negative evaluation in social situations. Specifically, previous work indicated that social anxiety is associated with increased medial prefrontal cortex activation in response to unintentional social norm (SN) transgressions, accompanied by increased embarrassment ratings for such SN violations. Here, we used data from the multiplex, multigenerational LFLSAD (Leiden Family Lab study on Social Anxiety Disorder), which involved two generations of families genetically enriched for SAD, and investigated whether these neurobiological and behavioral correlates of unintentional SN processing are SAD endophenotypes. Of four endophenotype criteria, we examined two: first, the cosegregation of these characteristics with social anxiety (SA) within families of SAD probands (criterion 4), and second, the heritability of the candidate endophenotypes (criterion 3).

METHODS

Participants (n = 110, age range 9.0-61.5 years, eight families) performed the revised Social Norm Processing Task; functional magnetic resonance imaging data and behavioral ratings related to this paradigm were used to examine whether brain activation in response to processing unintentional SN violations and ratings of embarrassment were associated with SA levels. Next, heritability of these measurements was estimated.

RESULTS

As expected, voxelwise functional magnetic resonance imaging analyses revealed positive associations between SA levels and brain activation in the medial prefrontal cortex and medial temporal gyrus, superior temporal gyrus, and superior temporal sulcus, and these brain activation levels displayed moderate to moderately high heritability. Furthermore, although SA levels correlated positively with behavioral ratings of embarrassment for SN transgressions, these behavioral characteristics were not heritable.

CONCLUSIONS

These results show, for the first time, that brain responses in the medial prefrontal cortex and medial temporal gyrus, superior temporal gyrus, and superior temporal sulcus, related to processing unintentional SN violations, provide a neurobiological candidate endophenotype of SAD.

The brain's hemodynamic response function rapidly changes under acute psychosocial stress in association with genetic and endocrine stress response markers

Ample evidence links dysregulation of the stress response to the risk for psychiatric disorders. However, we lack an integrated understanding of mechanisms that are adaptive during the acute stress response but potentially pathogenic when dysregulated. One mechanistic link emerging from rodent studies is the interaction between stress effectors and neurovascular coupling, a process that adjusts cerebral blood flow according to local metabolic demands. Here, using task-related fMRI, we show that acute psychosocial stress rapidly impacts the peak latency of the hemodynamic response function (HRF-PL) in temporal, insular, and prefrontal regions in two independent cohorts of healthy humans. These latency effects occurred in the absence of amplitude effects and were moderated by regulatory genetic variants of KCNJ2, a known mediator of the effect of stress on vascular responsivity. Further, hippocampal HRF-PL correlated with both cortisol response and genetic variants that influence the transcriptional response to stress hormones and are associated with risk for major depression. We conclude that acute stress modulates hemodynamic response properties as part of the physiological stress response and suggest that HRF indices could serve as endophenotype of stress-related disorders.

Estimated hemodynamic response function parameters obtained from resting state BOLD fMRI signals in subjects with autism spectrum disorder and matched healthy subjects

In Functional magnetic resonance imaging (fMRI), the blood oxygen level dependent (BOLD) signal is modeled as a convolution of the hemodynamic response function (HRF) and the unmeasured latent neural signal. Although most cortical and subcortical brain regions share the canonical shape of the HRF, the temporal structure of HRFs are variable across brain regions and subjects. This variability is induced by both neural and non-neural factors. The variability between subjects can be examined by three parameters that characterize the HRF: response height (RH), time-to-peak (TTP) and full-width at half-max (FWHM). This data provides three HRF parameters at every voxel, obtained from Autism Spectrum Disorder (ASD) patients (N = 531), and matched healthy controls (N = 571). Since ongoing studies suggest that non-standard populations have important differences in their HRFs when compared with healthy control, this data set is valuable in studying variability of HRF in ASD group and inferring the underlying pathology that also affects the HRF. It also has implications for fMRI analyses like resting-sate connectivity analysis.

Aberrant hemodynamic responses in autism: Implications for resting state fMRI functional connectivity studies

Functional MRI (fMRI) is modeled as a convolution of the hemodynamic response function (HRF) and an unmeasured latent neural signal. However, HRF itself is variable across brain regions and subjects. This variability is induced by both neural and non-neural factors. Aberrations in underlying neurochemical mechanisms, which control HRF shape, have been reported in autism spectrum disorders (ASD). Therefore, we hypothesized that this will lead to voxel-specific, yet systematic differences in HRF shape between ASD and healthy controls. As a corollary, we also hypothesized that such alterations will lead to differences in estimated functional connectivity in fMRI space compared to latent neural space. To test these hypotheses, we performed blind deconvolution of resting-state fMRI time series acquired from large number of ASD and control subjects obtained from the Autism Brain Imaging Data Exchange (ABIDE) database (N = 1102). Many brain regions previously implicated in autism showed systematic differences in HRF shape in ASD. Specifically, we found that precuneus had aberrations in all HRF parameters. Consequently, we obtained precuneus-seed-based functional connectivity differences between ASD and controls using fMRI as well as using latent neural signals. We found that non-deconvolved fMRI data failed to detect group differences in connectivity between precuneus and certain brain regions that were instead observed in deconvolved data. Our results are relevant for the understanding of hemodynamic and neurochemical aberrations in ASD, as well as have methodological implications for resting-state functional connectivity studies in Autism, and more generally in disorders that are accompanied by neurochemical alterations that may impact HRF shape.

Age differences in arterial and venous extra-cerebral blood flow in healthy adults: contributions of vascular risk factors and genetic variants

Sufficient cerebral blood flow (CBF) and venous drainage are critical for normal brain function, and their alterations can affect brain aging. However, to date, most studies focused on arterial CBF (inflow) with little attention paid to the age differences in venous outflow. We measured extra-cerebral arterial and venous blood flow rates with phase-contrast MRI and assessed the influence of vascular risk factors and genetic polymorphisms (ACE insertion/deletion, COMT val158met, and APOEε4) in 73 adults (age 18-74 years). Advanced age, elevated vascular risk, ACE Deletion, and COMT met alleles were linked to lower in- and outflow, with no effects of APOE ε4 noted. Lower age-related CBF rate was unrelated to brain volume and was observed only in val homozygotes of COMTval158met. Thus, in a disease-free population, age differences in CBF may be notable only in persons with high vascular risk and carriers of genetic variants associated with vasoconstriction and lower dopamine availability. It remains to be established if treatments targeting alleviation of the mutable factors can improve the course of cerebrovascular aging in spite of the immutable genetic influence.

Building a Science of Individual Differences from fMRI

To date, fMRI research has been concerned primarily with evincing generic principles of brain function through averaging data from multiple subjects. Given rapid developments in both hardware and analysis tools, the field is now poised to study fMRI-derived measures in individual subjects, and to relate these to psychological traits or genetic variations. We discuss issues of validity, reliability and statistical assessment that arise when the focus shifts to individual subjects and that are applicable also to other imaging modalities. We emphasize that individual assessment of neural function with fMRI presents specific challenges and necessitates careful consideration of anatomical and vascular between-subject variability as well as sources of within-subject variability.