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

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Abstract

Significance Understanding how stress predisposes for psychopathology requires the identification of physiological stress-regulatory mechanisms with pathogenic potential. Here, we applied fMRI to investigate the interaction between acute psychosocial stress and the brain’s hemodynamic response function (HRF). The HRF models how local neural activity elicits cerebral blood flow changes, spanning several biophysical processes including neurovascular coupling (NVC). Stress replicably shifted the HRF peak in temporal, insular, and prefrontal brain regions, moderated by functional variants of KCNJ2 , a protein involved in NVC. Hippocampal HRF markers correlated with the cortisol response and genetic variants that reflect transcriptional responses to glucocorticoids and the risk for depression. We suggest that acute psychosocial stress modulates hemodynamic response properties which could lead to previously undescribed endophenotypes of stress-related disorders.

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... Paralleling the literature in non-human animals, intrinsically evoked (from spontaneous, ongoing activity) and extrinsically evoked (from an external stimulus) activity may yield different vascular and metabolic responses (7)(8)(9)(10). This basic work extends evidence for noncanonical neurovascular coupling in the DMN, including carbon dioxide challenge paradigms (11), reduced cerebrovascular reactivity in aging (12), hypoxia (13,14) and under stress (15). ...
... Although participants were not explicitly stressed by our experimental paradigm, a subset of participants completed self-report measures of stress from the perceived stress scale during a separate study conducted within our research group. We restricted our analysis to those regions that also show stress specificity from Elbau et al. (15), including the right hippocampus, bilateral anterior cingulate cortex, and medial orbitofrontal cortex. We find that self-reported stress is associated with ACA in the pregenual region of the anterior cingulate cortex across all participants (left: r=0.43, p=0.008; right: r=0.34, p=0.040). ...
... In addition to prior evidence for variability in EEG-BOLD coupling, our study was motivated by findings of increased latency of hemodynamic responses during stress in otherwise psychiatrically unaffected participants (15). Although our participants were not explicitly stressed via our resting-state paradigm, we found that the magnitude of the delay in alpha-BOLD coupling in the subgenual region of the ACC was correlated with self-reported measures of stress. ...
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Neuroimaging methods rely on models of neurovascular coupling that assume hemodynamic responses evolve seconds after changes in neural activity. However, emerging evidence reveals noncanonical BOLD (blood oxygen level dependent) responses that are delayed under stress and aberrant in neuropsychiatric conditions. To investigate BOLD coupling to resting-state fluctuations in neural activity, we simultaneously recorded EEG and fMRI in people with schizophrenia and psychiatrically unaffected participants. We focus on alpha band power to examine voxelwise, time-lagged BOLD correlations. Principally, we find diversity in the temporal profile of alpha-BOLD coupling within regions of the default mode network (DMN). This includes early coupling (0-2 seconds BOLD lag) for more posterior regions, thalamus and brainstem. Anterior regions of the DMN show coupling at canonical lags (4-6 seconds), with greater lag scores associated with self-reported measures of stress and greater lag scores in participants with schizophrenia. Overall, noncanonical alpha-BOLD coupling is widespread across the DMN and other non-cortical regions, and is delayed in people with schizophrenia. These findings are consistent with a hemo-neural hypothesis, that blood flow and/or metabolism can regulate ongoing neural activity, and further, that the hemo-neural lag may be associated with subjective arousal or stress. Our work highlights the need for more studies of neurovascular coupling in psychiatric conditions.
... Even though these meta-analytic studies provide a useful summary of stress-related brain responses across different stress tasks and appear to converge towards insular activity associated with stressors, the pattern of activation or deactivation of the amygdala and the hippocampus is more ambiguous. A plausible reason for the somewhat low consistency in the limbic regions may lie in the fastchanging dynamics of the stress response in general ( Elbau et al., 2018) and individual differences in stressrelated brain activity ( Chung et al., 2016;Henckens et al., 2016). As described before, most studies used repetitive mental calculation blocks and negative social feedback as stressors ( Dedovic, D'Aguiar, & Pruessner, 2009;Dedovic, Rexroth, et al., 2009). ...
... Such temporal fluctuations of the fMRI correlate of the stress response can, indeed, be detected with temporally fine-grained models applied to functional connectivity ( Kühnel et al., 2022) or hemodynamic response functional markers ( Elbau et al, 2018). Another option is to directly embed peripheral stress indices into the statistical fMRI models of the imaging stress task, such as the widely available HR measured with pulse photoplethysmography (PPG) or electrocardiography (ECG). ...
... Participants performed a stress task based on the MIST ( Dedovic et al., 2005), which was adapted by splitting the 'control' condition into two phases (PreStress and Post-Stress phases without negative social feedback) and by further subdividing each task phase into five interleaved blocks of active task performance and rest blocks ( Elbau et al., 2018;Kühnel et al., 2020Kühnel et al., , 2022. The task has been validated for its effectiveness in eliciting a cardiovascular, endocrine, and behavioral stress response ( Elbau et al., 2018). ...
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Abnormalities in the neural mechanisms of the stress response have the potential to serve as a transdiagnostic marker for stress-related disorders. This potential is rooted in the highly individual and dynamic stress response, which poses a challenge to classical experimentally informed models that focus on specific phases, conditions, or stimuli during a stress task. Here, we integrate individual heart rates (HR) as an immanent index of the stress-response and combine these with functional magnetic resonance imaging (fMRI) data. In this study, 83 healthy participants completed a multimodal psychosocial imaging stress task comprising three different task phases (PreStress, Stress, and PostStress), with each phase consisting of five 60 s blocks of active task interleaved with 40 s of rest, and simultaneous recordings of pulse plethysmography. Participants were asked to solve mental calculations and were exposed to negative social feedback during the Stress phase. We estimated a general linear model (GLM) with individual heart rates averaged per active block as a single parametric modulator of the task regressor across all 15 active blocks irrespective of the task phase. Results revealed a negative correlation between HR and activation in the bilateral amygdala and anterior hippocampus as well as deactivation in the default mode network. Positive correlations with HR were detected in the bilateral insular cortex, bilateral angular gyrus, and parts of the inferior and superior parietal lobes. In summary, our findings emphasize the utility of integrating the commonly assessed cardiovascular stress response (here: HR) as an immediate index of the participant’s stress status. We conclude that by such integration, brain regions involved in regulating the acute stress response, such as the anterior hippocampus and amygdala, are detected more sensitively by tracking the individual’s “stress wave” rather than treating every experimental block uniformly. Our approach may serve as a complementary analysis to the task-regressor based model.
... Perhaps the brain errs on the side of excess blood flow, given the potentially devastating consequences of hypoxia. However, the overshoot effect suggests that the brain may have some flexibility to reallocate blood flow during stress (Elbau et al., 2018) as a compensatory mechanism in dementia (Becker et al., 1996) or in neuropsychiatric disorders such as schizophrenia (Tan et al., 2006). These examples raise the intriguing possibility that the overshoot may relate to the needs of "baseline" metabolic maintenance and intrinsic processes that are distinct from the extrinsic stimulus and evoked responses (Devor et al., 2011). ...
... Few studies have followed-up this intriguing result, and could be confirmed by reanalysis of existing EEG-fMRI datasets using lagged-correlation relationships, rather than conventional hemodynamic modeling. These findings are consistent with a growing literature that identifies variability in the shape or latency of the canonical hemodynamic response function (HRF; Rangaprakash et al., 2017;Elbau et al., 2018;Ekstrom, 2021). In fact, simultaneous EEG-fMRI has been proposed as an ideal method to help disentangle this variability in the hemodynamic response (Prokopiou et al., 2020) since the canonical hemodynamic response function was initially developed and has largely been studied in the context of eventrelated paradigms rather than during the resting-state. ...
... Changes in the regional distribution of blood flow by arousal may, in turn, alter background activity patterns which will make the background activity in those regions more or less responsive to extrinsic input. This model is an extension of the explanation proposed by Elbau et al. (2018) to explain stress induced delays in metabolic coupling. In order to assay these subcortical and brainstem mechanisms, high field strength MRI is needed (Priovoulos et al., 2018). ...
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The brain is a living organ with distinct metabolic constraints. However, these constraints are typically considered as secondary or supportive of information processing which is primarily performed by neurons. The default operational definition of neural information processing is that (1) it is ultimately encoded as a change in individual neuronal firing rate as this correlates with the presentation of a peripheral stimulus, motor action or cognitive task. Two additional assumptions are associated with this default interpretation: (2) that the incessant background firing activity against which changes in activity are measured plays no role in assigning significance to the extrinsically evoked change in neural firing, and (3) that the metabolic energy that sustains this background activity and which correlates with differences in neuronal firing rate is merely a response to an evoked change in neuronal activity. These assumptions underlie the design, implementation, and interpretation of neuroimaging studies, particularly fMRI, which relies on changes in blood oxygen as an indirect measure of neural activity. In this article we reconsider all three of these assumptions in light of recent evidence. We suggest that by combining EEG with fMRI, new experimental work can reconcile emerging controversies in neurovascular coupling and the significance of ongoing, background activity during resting-state paradigms. A new conceptual framework for neuroimaging paradigms is developed to investigate how ongoing neural activity is “entangled” with metabolism. That is, in addition to being recruited to support locally evoked neuronal activity (the traditional hemodynamic response), changes in metabolic support may be independently “invoked” by non-local brain regions, yielding flexible neurovascular coupling dynamics that inform the cognitive context. This framework demonstrates how multimodal neuroimaging is necessary to probe the neurometabolic foundations of cognition, with implications for the study of neuropsychiatric disorders.
... We used a psycho-social stress paradigm that was adapted from the Montreal imaging stress task (Pruessner et al., 2008). In this task, participants have to perform arithmetic tasks under time pressure and with negative performance feedback (Brückl et al., 2020;Elbau et al., 2018;Kühnel et al., 2020) that is given after each trial and additionally verbally between task blocks. These tasks typically correspond to mild laboratory stressors with 47%-65% cortisol responders (Noack et al., 2019). ...
... To assess the subjective stress response, we calculated the change in positive (activity, wakefulness, self-certainty, focus, and relaxed state of mind) and negative (internal and external agitation, anxiety, sadness, anger, dysphoria, sensitivity as well as three items assessing somatic changes) sum scores form the respective items directly after the task (T6) and after the 30-minute rest interval (T8) (Elbau et al., 2018;Kühnel et al., 2020). ...
... After establishing an association between BMI and stress-induced negative affect, we investigated whether the brain response to stress was also affected in participants with high BMI. As previously shown (Elbau et al., 2018;Kühnel et al., 2022Kühnel et al., , 2020 Figure 3B). However, the interaction of sex and BMI did not reach significance (posterior insula R: p = .071, ...
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Background Stress is associated with elevated risk for overweight and obesity, especially in women. Since body mass index (BMI) is correlated with increased inflammation and reduced baseline cortisol, obesity may lead to altered stress responses. However, it is not well understood whether stress-induced changes in brain function scale with BMI and if peripheral inflammation contributes to this. Methods We investigated the subjective, autonomous, endocrine, and neural stress response in a transdiagnostic sample (N=192, 120 women, M BMI =23.7±4.0 kg/m ² ; N=148, 89 women, with cytokines). First, we used regression models to examine effects of BMI on stress reactivity. Second, we predicted BMI based on stress-induced changes in activation and connectivity using cross-validated elastic-nets. Third, to link stress responses with inflammation, we quantified the association of BMI-related cytokines with model predictions. Results BMI was associated with higher negative affect after stress and an increased response to stress in the substantia nigra and the bilateral posterior insula ( p FWE <.05). Moreover, stress-induced changes in activation of the hippocampus, dACC, and posterior insula predicted BMI in women ( p perm <.001), but not in men. BMI was associated with higher baseline cortisol while cytokines were not associated with predicted BMI scores. Conclusions Stress-induced changes in the hippocampus and posterior insula predicted BMI in women, indicating that acute brain responses to stress might be more strongly related to a higher BMI in women compared to men. Altered stress-induced changes were associated with baseline cortisol but independent of cytokines, suggesting that the endocrine system and not inflammation contributes to stress-related changes in BMI.
... After an emotional face-matching task (w12 min) and a baseline resting-state measurement, participants rated their current affective state using the BSKE (Befindensskalierung nach Kategorien und Eigenschaftsworten) scales (57) (Supplement). The psychosocial stress paradigm was adapted from the Montreal Imaging Stress Task (58), where stress is induced by performing arithmetic tasks with time pressure and negative feedback (59,60) corresponding to a mild laboratory stressor with 47% to 65% cortisol responders (61). The task lasted approximately 25 minutes and included a prestress phase without negative feedback or time pressure, followed by a stress phase with psychosocial stress induction, and a poststress phase (analogous to prestress). ...
... Regions were defined using an FC-based atlas (73), except for the hypothalamus (Harvard-Oxford atlas) because the resolution of the Shen atlas was too coarse. Time series were detrended (linear), despiked (winsorized at 64 standard deviations), and residualized with the same covariates as previously reported (59), including the six movement parameters, their derivative, and five components from white matter and cerebrospinal fluid, respectively (74) (Supplement). To estimate changes relative to the restingstate baseline before the task, we concatenated time series by matching their raw blood oxygen level-dependent image intensity (Supplement). ...
... While previous studies highlighted characteristic changes in activations (48,58,59,116,117), most case-control studies are relatively small and cannot resolve dimensional aspects of psychological stress susceptibility. This may add to the limited convergence of findings (71,(118)(119)(120). ...
Article
Background Maladaptive stress responses are important risk factors in the etiology of mood and anxiety disorders, but exact pathomechanisms remain to be understood. Mapping individual differences of acute stress-induced neurophysiological changes, especially on the level of neural activation and functional connectivity (FC), could provide important insights in how variation in the individual stress response is linked to disease risk. Methods Using an established psycho-social stress task flanked by two resting-states, we measured subjective, physiological, and brain responses to acute stress and recovery in 217 participants with and without mood and anxiety disorders. To estimate block-wise changes in stress-induced activation and FC, we used hierarchical mixed-effects models based on denoised timeseries within predefined stress-related regions. We predicted inter- and intra-individual differences in stress phases (anticipation vs. stress vs. recovery) and transdiagnostic dimensions of stress reactivity using elastic net and support vector machines. Results We identified four subnetworks showing distinct changes in FC over time. FC but not activation trajectories predicted the stress phase (accuracy: 70%, pperm<.001) and increases in heart rate (R²=.075, pperm<.001). Critically, individual spatio-temporal trajectories of changes across networks also predicted negative affectivity (ΔR²=.075, pperm=.030), but not the presence or absence of a mood and anxiety disorder. Conclusions Spatio-temporal dynamics of brain network reconfiguration induced by stress reflect individual differences in the psychopathology dimension negative affectivity. These results support the idea that vulnerability for mood and anxiety disorders can be conceptualized best at the level of network dynamics, which may pave the way for improved prediction of individual risk.
... Furthermore, NVC research is vital in understanding and assessing brain health (Chang et al., 2013;Wu et al., 2019), in addition to brain-related pathologies (Csipo et al., 2019;Huneau et al., 2015b), such as ischemic stroke, cerebral small vessel disease, and heart disease. Recent research has indicated that NVC may vary in response to hormonal conditions, suggesting that hemodynamic response function indices may serve as an endophenotype for stress-related disorders (Elbau et al., 2018). However, the effects of mental stress on FC and NVC during the interaction of physical environmental and psychosocial stressors have not been explored. ...
... The FC analysis of the HbO data revealed abnormal hemodynamic responses and weak connectivity in the PFC in the SNE group (Fig. 10), supporting the concept that neural activity contributes to stress response and is linked to abnormal neurovascular response. NVC plays a major role in matching the metabolic supply with regional neural activity and adjusting the cerebral blood flow in accordance with regional metabolic needs (Elbau et al., 2018;MacVicar and Newman, 2015). The findings related to the HbO data in this study are consistent with prior studies (Chou et al., 2016;Rosenbaum et al., 2018), which found weakened connectivity in the PFC in stressed subjects. ...
... The findings related to the HbO data in this study are consistent with prior studies (Chou et al., 2016;Rosenbaum et al., 2018), which found weakened connectivity in the PFC in stressed subjects. These observations may be attributed to genetic variations, such as in KCNJ2 (potassium inwardly rectifying channel, subfamily J), which influence NVC under stress (Elbau et al., 2018;Longden et al., 2014). Future studies using advanced neuroimaging techniques, such as fMRI, may further confirm the use of neurovascular data in stress diagnosis. ...
Article
This study aims to evaluate the effect of workstation type on the neural and vascular networks of the prefrontal cortex (PFC) underlying the cognitive activity involved during mental stress. Workstation design has been reported to affect the physical and mental health of employees. However, while the functional effects of ergonomic workstations have been documented, there is little research on the influence of workstation design on the executive function of the brain. In this study, 23 healthy volunteers in ergonomic and non-ergonomic workstations completed the Montreal imaging stress task, while their brain activity was recorded using the synchronized measurement of electroencephalography and functional near-infrared spectroscopy. The results revealed desynchronization in alpha rhythms and oxygenated hemoglobin, as well as decreased functional connectivity in the PFC networks at the non-ergonomic workstations. Additionally, a significant increase in salivary alpha-amylase activity was observed in all participants at the non-ergonomic workstations, confirming the presence of induced stress. These findings suggest that workstation design can significantly impact cognitive functioning and human capabilities at work. Therefore, the use of functional neuroimaging in workplace design can provide critical information on the causes of workplace-related stress.
... standardized stress tests (Foley & Kirschbaum, 2010), such as the Trier Social Stress Task (TSST) (Kirschbaum, Pirke, & Hellhammer, 1993) and adaptations suitable for exploration through functional imaging (fMRI) (Elbau et al., 2018;Noack, Nolte, Nieratschker, Habel, & Derntl, 2019). Whereas stress is an integral part of everyday life, responding to repeated stressful experiences can unveil interindividual differences that have been linked to psychopathology before (Grillon, Southwick, & Charney, 1996;McEwen, 1998;McLaughlin, Conron, Koenen, & Gilman, 2010). ...
... The fMRI session started with a T2-weighted high-resolution image for spatial normalization, followed by an emotional face matching task and a pre-stress resting state. Immediately before the stress paradigm, participants rated their current affective state using the previously used (Elbau et al., 2018) Befindensskalierung nach Kategorien und Eigenschaftsworten (BSKE, for details see Supporting Information). Approximately 60 min (64.6 min ± 8.7) after IVP, the stress task started. ...
... Psychosocial stress was induced by an imaging stress task previously reported by Elbau et al. (2018), with minor changes regarding the aversiveness of the feedback and the number of task blocks. As in F I G U R E 1 Schematic summary of the procedure and task. ...
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Acute and chronic stress are important factors in the development of mental disorders. Reliable measurement of stress reactivity is therefore pivotal. Critically, experimental induction of stress often involves multiple “hits” and it is an open question whether individual differences in responses to an earlier stressor lead to habituation, sensitization, or simple additive effects on following events. Here, we investigated the effect of the individual cortisol response to intravenous catheter placement (IVP) on subsequent neural, psychological, endocrine, and autonomous stress reactivity. We used an established psychosocial stress paradigm to measure the acute stress response (Stress ) and recovery (PostStress ) in 65 participants. Higher IVP‐induced cortisol responses were associated with lower pulse rate increases during stress recovery (b = −4.8 bpm, p = .0008) and lower increases in negative affect after the task (b = −4.2, p = .040). While the cortisol response to IVP was not associated with subsequent specific stress‐induced neural activation patterns, the similarity of brain responses Pre‐ and PostStress was higher IVP‐cortisol responders (t [64] = 2.35, p = .022) indicating faster recovery. In conclusion, preparatory stress induced by IVP reduced reactivity in a subsequent stress task by modulating the latency of stress recovery. Thus, an individually stronger preceding release of cortisol may attenuate a second physiological response and perceived stress suggesting that relative changes, not absolute levels are crucial for stress attribution. Our study highlights that considering the entire trajectory of stress induction during an experiment is important to develop reliable individual biomarkers.
... In the conventional EEG-correlated fMRI studies, the EEG features are usually convolved with the canonical hemodynamic response function (HRF), considering a fixed hemodynamic time delay of 5 seconds [44,45]. However, given the existence of intra-and inter-variability regarding the hemodynamic delay, as it is reported in the literature [46,47], we also tackle this concern of the hemodynamic time delay to be considered in the HRF, by considering slight variations of the hemodynamic time delay in the HRF to be convolved with the EEG features. ...
... In the conventional EEG-correlated fMRI studies, the EEG features are usually convolved with the canonical HRF (that supposedly reflects the BOLD signal response) considering a fixed hemodynamic time delay of 5 seconds (see Fig 2, second block marked as blue) [44,45]. Nevertheless, given the evidence of intra-and inter-variability regarding the hemodynamic delay, as it is reported in the literature [46,47], we performed, in our study, slight variations on the HRF to be used [44], and considered four different hemodynamic time delays (4, 5, 6 and 7 seconds), instead of focusing only on a 5 seconds delay canonical HRF as used in the conventional studies [45]. After this step, the convolved EEG features are synchronized and ready to be compared to the BOLD signals of regions of interest (Insula) found in the fMRI study [43]. ...
Article
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Cognitive human error and recent cognitive taxonomy on human error causes of software defects support the intuitive idea that, for instance, mental overload, attention slips, and working memory overload are important human causes for software bugs. In this paper, we approach the EEG as a reliable surrogate to MRI-based reference of the programmer’s cognitive state to be used in situations where heavy imaging techniques are infeasible. The idea is to use EEG biomarkers to validate other less intrusive physiological measures, that can be easily recorded by wearable devices and useful in the assessment of the developer’s cognitive state during software development tasks. Herein, our EEG study, with the support of fMRI, presents an extensive and systematic analysis by inspecting metrics and extracting relevant information about the most robust features, best EEG channels and the best hemodynamic time delay in the context of software development tasks. From the EEG-fMRI similarity analysis performed, we found significant correlations between a subset of EEG features and the Insula region of the brain, which has been reported as a region highly related to high cognitive tasks, such as software development tasks. We concluded that despite a clear inter-subject variability of the best EEG features and hemodynamic time delay used, the most robust and predominant EEG features, across all the subjects, are related to the Hjorth parameter Activity and Total Power features, from the EEG channels F4, FC4 and C4, and considering in most of the cases a hemodynamic time delay of 4 seconds used on the hemodynamic response function. These findings should be taken into account in future EEG-fMRI studies in the context of software debugging.
... Using massively parallel reporter assays in cell lines and stimulated expression quantitative trait locus (eQTL) analyses in peripheral blood, we have previously reported that genetic variants can alter effects of GCs at gene regulatory elements (8). These variants are linked to a spectrum of outcomes, including altered risk for psychiatric disorders, variation in amygdala reactivity to threat, startle response, and cortisol response to a psychological stressor (8)(9)(10) stressrelated changes in brain physiology, such as the peak latency of the hemodynamic response function in limbic brain regions (11). In addition to genetic variation, the activity of glucocorticoid response elements (GREs) is also influenced by the local epigenetic landscape, including at the level of DNA methylation (DNAm) (12,13). ...
... (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The GR expression quantitative trait methylation (eQTM) analysis encompassed 11,944 transcripts and 740,357 CpG sites, utilising standardised changes in expression and methylation across a 2Mb window. Data analysis was carried out using MatrixEQTL, with covariate adjustment similar to the differential DNAm analysis and meQTL analyses, incorporating SV1-3 from the gene expression data. ...
Preprint
Background: Glucocorticoids play a crucial role as mediators of negative health effects associated with chronic stress, including increased risk for psychiatric disorders as well as cardiovascular and metabolic diseases. This study investigates the impact of genetic variants and glucocorticoid receptor (GR)-activation on gene expression and DNA methylation in peripheral blood and the relationship of these variants with disease risk. Methods: We conducted a comprehensive molecular quantitative trait locus (QTL) analysis, mapping GR-methylation (me)QTLs, GR-expression (e)QTLs, and GR-expression quantitative trait methylation (eQTM) in a cohort of 199 individuals, with DNA methylation and RNA expression data collected before and after GR-activation with dexamethasone. A multi-level network analysis was employed to map the complex relationships between the transcriptome, epigenome, and genetic variation. Results: We identified 3,772 GR-meQTL CpGs corresponding to 114,134 local GR-meQTLs. eQTM and eQTL analyses revealed distinct genetic influences on RNA expression and DNA methylation. Multi-level network analysis uncovered GR-network trio QTLs, characterised by SNP-CpG-transcript combinations where meQTLs act as both eQTLs and eQTMs. These trios' genes demonstrated enrichment in immune response and cell activation pathways and showed a significant overlap with transcripts altered by GR-activation in the mouse brain. GR-trio variants were enriched in GWAS for bipolar disorder, schizophrenia, autoimmune and cardiovascular diseases and traits, cytokines levels and BMI. Conclusions: Genetic variants modulating the molecular effects of glucocorticoids are associated with psychiatric as well as medical diseases. Our findings support stress as a shared risk factor for transdiagnostic negative health outcomes and may lead to innovative interventions targeting shared underlying molecular mechanisms.
... The components of the NVC may present intraindividual, inter-region, and inter-condition variability (Elbau et al., 2018). Its characterization to understand how the hemodynamic response is altered in T2DM, is therefore quite relevant. ...
... Finally, as a limitation of the study, we should mention that despite the strong statistical power of these results, besides T2DM, there are several other sources of NVC changes, which, in turn, can introduce variability. For instance, the BOLD signal, which measures indirectly the NVC, is also sensitive to other hemodynamic processes, even from non-pathological sources (e.g., atypical brain physiology) (Rossini et al., 2004;Elbau et al., 2018). Thus, when the NVC is investigated, its interpretation and comparison between groups become more complicated by additional factors (Whittaker et al., 2016). ...
Article
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Type 2 Diabetes Mellitus (T2DM) is a metabolic disease that leads to multiple vascular complications with concomitant changes in human neurophysiology, which may lead to long-term cognitive impairment, and dementia. Early impairments of neurovascular coupling can be studied using event-related functional magnetic resonance imaging (fMRI) designs. Here, we aimed to characterize the changes in the hemodynamic response function (HRF) in T2DM to probe components from the initial dip to late undershoot. We investigated whether the HRF morphology is altered throughout the brain in T2DM, by extracting several parameters of the fMRI response profiles in 141 participants (64 patients with T2DM and 77 healthy controls) performing a visual motion discrimination task. Overall, the patients revealed significantly different HRFs, which extended to all brain regions, suggesting that this is a general phenomenon. The HRF in T2DM was found to be more sluggish, with a higher peak latency and lower peak amplitude, relative slope to peak, and area under the curve. It also showed a pronounced initial dip, suggesting that the initial avidity for oxygen is not compensated for, and an absent or less prominent but longer undershoot. Most HRF parameters showed a higher dispersion and variability in T2DM. In sum, we provide a definite demonstration of an impaired hemodynamic response function in the early stages of T2DM, following a previous suggestion of impaired neurovascular coupling. The quantitative demonstration of a significantly altered HRF morphology in separate response phases suggests an alteration of distinct physiological mechanisms related to neurovascular coupling, which should be considered in the future to potentially halt the deterioration of the brain function in T2DM.
... An accurate estimation of the HRF is crucial to correctly interpret both the hemodynamic activity itself and the underlying source signals. Furthermore, the HRF has shown potential as a biomarker for healthy aging (West et al., 2019) or pathological brain functioning; examples of which include obsessive-compulsive disorder (Rangaprakash et al., 2021), mild traumatic brain injury (Mayer et al., 2014), Alzheimer's disease (Asemani et al., 2017), epilepsy (Van Eyndhoven et al., 2021) and severe psychosocial stress (Elbau et al., 2018). While HRFs can as well be defined in nonlinear and dynamic frameworks with the help of Volterra kernels (Friston, 2002), linear models have particularly gained popularity due to the combination of their remarkable performance and simplicity. ...
... SVD is a method for calculating the pseudo-inverse of a rank-deficient matrix, which is the case for many signal processing applications on real data, such as for extraction of signals from noisy environments (Demmel, 1997). Stabilization of the pseudo-inverse in presence of noise can be achieved by choosing the optimal number of singular values of ̂ r to be discarded, which can be viewed as a regularization problem (Sano, 1993). ...
Article
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Functional ultrasound (fUS) indirectly measures brain activity by detecting changes in cerebral blood volume following neural activation. Conventional approaches model such functional neuroimaging data as the convolution between an impulse response, known as the hemodynamic response function (HRF), and a binarized representation of the input signal based on the stimulus onsets, the so-called experimental paradigm (EP). However, the EP may not characterize the whole complexity of the activity-inducing signals that evoke the hemodynamic changes. Furthermore, the HRF is known to vary across brain areas and stimuli. To achieve an adaptable framework that can capture such dynamics of the brain function, we model the multivariate fUS time-series as convolutive mixtures and apply block-term decomposition on a set of lagged fUS autocorrelation matrices, revealing both the region-specific HRFs and the source signals that induce the hemodynamic responses. We test our approach on two mouse-based fUS experiments. In the first experiment, we present a single type of visual stimulus to the mouse, and deconvolve the fUS signal measured within the mouse brain’s lateral geniculate nucleus, superior colliculus and visual cortex. We show that the proposed method is able to recover back the time instants at which the stimulus was displayed, and we validate the estimated region-specific HRFs based on prior studies. In the second experiment, we alter the location of the visual stimulus displayed to the mouse, and aim at differentiating the various stimulus locations over time by identifying them as separate sources.
... For true BOLD response magnitude to appear in the regression coefficient, and apart from HRF shape variants [10][11][12][13][14] , such procedure must take into account unknown shifts in time that may come from region-specific neurovascular coupling, different stimulus quality or familiarity 15,16 , reaction time, genetics 17 , age and disease 18 , stress 19 , unknown internally triggered processes, or specification failure of onset time. ...
... Calibrations of ratio-latency transfer on regressors of usual experimental designs may have no part in common with the calibration from single HRF which then would return wrong latency. Regressor correlation as one source of deviation 15 can be minimized by outsourcing correlated regressors to a preceding regression and working on residuals 19 , at a potential cost of destroying measured HRFs. ...
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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.
... Cortisol was sampled 4 times: Arrival (s1), right after the end of the main test (s2), 20 min after the end of the main test (s3) and after a recovery period, 40 min after the end of the main test (s4). To account for cortisol changes through time, circadian influence in cortisol was corrected similarly to (Elbau et al., 2018) by subtracting, for each subject, the line between s1 and s4 from each cortisol sample. The AUC i formula (Pruessner et al., 2003) was applied to the two corrected cortisol values after the stress task (s2 and s3) to estimate the total cortisol released between these two samples. ...
... The cortisol response was sampled from saliva at four time points during the experimental procedure (s1-s4; see Fig. 2a) and corrected for the circadian influence (Elbau et al., 2018) (see Materials and Methods for details). As expected, the cortisol response is larger in the stress group [ Fig. 2b; repeated measures ANOVA (rmANOVA) group vs. timepoints (s2 and s3), group effect: F 1,116 = 5.25, p = 0.024, ƞ p 2 = 0.043]. ...
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Laboratory stressors are essential tools to study the human stress response. However, despite considerable progress in the development of stress induction procedures in recent years, the field is still missing standardization and the methods employed frequently require considerable personnel resources. Virtual reality (VR) offers flexible solutions to these problems, but available VR stress-induction tests still contain important sources of variation that challenge data interpretation. One of the major drawbacks is that tasks based on motivated performance do not adapt to individual abilities. Here, we provide open access to, and present, a novel and standardized immersive multimodal virtual environment stress test (IMVEST) in which participants are simultaneously exposed to mental -arithmetic calculations- and environmental challenges, along with intense visual and auditory stimulation. It contains critical elements of stress elicitation – perceived threat to physical self, social-evaluative threat and negative feedback, uncontrollability and unpredictability – and adjusts mathematical challenge to individual's ongoing performance. It is accompanied by a control VR scenario offering a comparable but not stressful situation. We validate and characterize the stress response to IMVEST in one-hundred-and-eighteen participants. Both cortisol and a wide range of autonomic nervous system (ANS) markers – extracted from the electrocardiogram, electrodermal activity and respiration – are significantly affected. We also show that ANS features can be used to train a stress prediction machine learning model that strongly discriminates between stress and control conditions, and indicates which aspects of IMVEST affect specific ANS components.
... Relative to the other paradigms, changes in activity in the amygdala and insula were less prevalent in the MIST (Dedovic et al., 2009;Kogler et al. (2015a); Lederbogen et al., 2011;Soliman et al., 2011;Wheelock et al., 2016;Zschucke et al., 2015). Activation patterns in frontal regions encompassed increases (Chung et al., 2016;Dedovic et al., 2009;Goodman et al., 2018;Kogler et al., 2017;Soliman et al., 2011;Wheelock et al., 2016;Zschucke et al., 2015) as well as decreases (Dedovic et al., 2009;Elbau et al., 2018;Goodman et al., 2018;Kogler et al., 2017;Soliman et al., 2011;Zschucke et al., 2015). These patterns were especially pronounced in the medial and inferior frontal gyrus as well as the lateral prefrontal cortex. ...
... Moreover, some studies showed activation in subcortical regions like the thalamus and basal ganglia (Dedovic et al., 2005;Lederbogen et al., 2011;Wheelock et al., 2016) while others showed divergent activation patterns (Dedovic et al., 2009;Soliman et al., 2011;Zschucke et al., 2015). Lastly, activation in motor related areas like the precentral gyrus and cerebellum have been detected (Dedovic et al., 2005;Elbau et al., 2018;Kogler et al., 2017;Wheelock et al., 2016). ...
Article
Psychosocial stress is an omnipresent phenomenon whose neural correlates in humans are still poorly understood. Several paradigms have been developed to induce acute stress in fMRI settings, but it is unclear whether there is a global brain activation pattern related to psychosocial stress. To integrate the different neuronal activation patterns, we conducted an activation likelihood estimation analysis on 31 studies totaling 1279 participants. Studies used the ScanSTRESS, Montreal Imaging Stress Test, aversive viewing paradigm (AVP), Social-Evaluative Threat or Cyberball. The analysis revealed bilateral activation clusters comprising the claustrum, insula and inferior frontal gyrus. This indicates that exposure to psychosocial stress leads to activations in brain areas involved in affective processing and the endocrine stress response. Furthermore, in a systematic review, Cyberball and AVP presented themselves as outliers due to increased activation in motor areas and lack of induction of stress related activity changes, respectively. As different paradigms emphasize different dimensions of psychosocial stress such as social evaluation or performance pressure, future research is needed to identify differences between the paradigms.
... The right PFC has previously been investigated to be strongly related to psychosocial stress [26,55] and the findings are consistent with other studies that documented the impact of physical stressor processing on HPA-axis activation and autonomic stress responses [56,57]. Furthermore, Elbau, et al. [58] observed a rapid impact under psychosocial stress on the peak latency of hemodynamic responses to PFC. ...
... The EEG-fNIRS fusion approach here was built on the assumption that homeostasis of the brain microenvironment is preserved by components of the NVC unit (astrocytes, neurons, and blood vessels, and excitation-inhibition balance) in a PFC microcircuit [61,62]. NVC plays a major role in matching the metabolic supply with regional neural activity and adjusting the cerebral blood flow in accordance with regional metabolic needs [58,63]. In which, our results (Fig. 8) demonstrated an inverse relationship between alpha cortical activity (direct relationship in the case of alpha power) and the hemodynamic signal (HbO) as well as a maximum peak in correlation at a time delay of 5 seconds. ...
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This research seeks to examine the impact of workstation types on the coupling of neural and vascular activities of the prefrontal cortex (PFC). The design of the workstations was found to impair the performance, physical and mental health of employees. However, the mechanism underlying cognitive activity involved during workstation design-related stress effects in the PFC has not been fully understood. We used electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) to simultaneously measure electrical activity and hemoglobin concentration changes in the PFC. The multimodal signal was collected from 23 healthy adult volunteers who completed the Montreal imaging stress task in ergonomic and non-ergonomic workstations. A supervised machine learning method based on temporally embedded canonical correlation analysis (tCCA) was utilized to obtain the association between neural activity and local changes in hemoglobin concentrations to enhance localization and accuracy. The results showed deactivation in alpha power rhythms and oxygenated hemoglobin, as well as declined activation pattern of the fused data in the right PFC at the non-ergonomic workstation. Additionally, all participants at the non-ergonomic workstation experienced a substantial rise in salivary alpha-amylase activity in comparison with the ergonomic workstation, indicating the existence of high-stress levels. The proposed tCCA approach obtains excellent results in discriminating workstation types achieving accuracies of 98.8% and a significant improvement of 8.0% ( p<0.0001p < 0.0001 ) and 9.4% ( p<0.0001p < 0.0001 ) over EEG-only and fNIRS-only, respectively. Our study suggests the use of functional neuroimaging in designing the workplace as it provides critical information on the causes of workplace-related stress.
... Previous work in rodents raised the intriguing possibility that acute psychosocial stress may be sufficient to alter neurovascular coupling (20), but it has been challenging to test this directly in the human brain due to technical limitations on interrogating neurovascular coupling mechanisms noninvasively. Instead, Elbau et al. (9) were able to test for changes in neurovascular coupling indirectly, by quantifying temporal shifts in the canonical hemodynamic response function (HRF) evoked during a mental arithmetic task under stress and control conditions. In the stress condition, the task difficulty was adjusted to yield a high failure rate, and subjects received frequent performance assessments and negative verbal feedback to elicit psychosocial stress. ...
... Also of clinical relevance, Elbau et al. (9) report substantial interindividual variability in the prestress hippocampal hemodynamic lag. This measure mediated the relationship between the endocrine response evoked by stress during the task and genetic variants that influence depression risk. ...
... Longer TTP is also linked to reduced intelligence (Anderson et al., 2020). Aberrant HRFs have been observed in stress (Elbau et al., 2018), mild traumatic brain injury (Mayer et al., 2014), aging (West et al., 2019;Yabluchanskiy et al., 2020;Tsvetanov et al., 2021), isolated cervical dystonia (Berman et al., 2020), and levels of consciousness (Gemma et al., 2009;Wu et al., 2019). Such HRF changes are concerning because they are at least partly driven by non-neural factors and can confound FC group differences. ...
Article
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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.
... Previous work on HRF estimation has explored data-driven approaches. Some mnethods adopted a smoothness constraint using, for example, a Gaussian process prior ( Goutte et al., 2000;Ciuciu et al., 2003;Eickenberg et al., 2017 ), cubic smoothing splines ( Zhang et al., 2007 ), B-splines ( Degras and Lindquist, 2014 ), a canonical HRF combined with its temporal derivative ( Elbau et al., 2018 ), wavelet bases ( Van De Ville et al., 2004;Khalidov et al., 2011 ), a biophysically informed HRF ( Rosa et al., 2015 ), Tikhonov regularization ( Zhang et al., 2007;Casanova et al., 2008;Casanova et al. 2009;Zhang et al. 2012 ), spatial regularization ( Badillo et al., 2013;Chaari et al., 2013;Zhang et al., 2018 ), cross validation ( Zhang et al., 2013 ), and nonlinear optimization ( Pedregosa et al., 2015 ). Some of these methods were applied to individual-level modeling for task-based experiments ( Goutte et al., 2000;Ciuciu et al., 2003;Zhang et al., 2007;Chaari et al., 2013;Pedregosa et al., 2015 ) and for resting state data ( Wu et al., 2021 ); Cherkaoui et al., 2021 ). ...
Article
Typical fMRI analyses often assume a canonical hemodynamic response function (HRF) that primarily focuses on the peak height of the overshoot, neglecting other morphological aspects. Consequently, reported analyses often reduce the overall response curve to a single scalar value. In this study, we take a data-driven approach to HRF estimation at the whole-brain voxel level, without assuming a response profile at the individual level. We then employ a roughness penalty at the population level to estimate the response curve, aiming to enhance predictive accuracy, inferential efficiency, and cross-study reproducibility. By examining a fast event-related FMRI dataset, we demonstrate the shortcomings and information loss associated with adopting the canonical approach. Furthermore, we address the following key questions: 1. To what extent does the HRF shape vary across different regions, conditions, and participant groups? 2. Does the data-driven approach improve detection sensitivity compared to the canonical approach? 3. Can analyzing the HRF shape help validate the presence of an effect in conjunction with statistical evidence? 4. Does analyzing the HRF shape offer evidence for whole-brain response during a simple task?
... One study presented a link between stress and neurovascular coupling, a physiological process that drives changes in blood flow to specific brain regions. The hemodynamic response function showed an increased signal in several brain regions, including in the temporal and prefrontal cortex, indicating changes in blood flow regulation in response to stress as well as the cortisol secretion and the adrenocorticotropic hormone (ACTH) response [72]. The ACTH is a hormone made by the pituitary gland, a small gland located at the bottom of the brain. ...
Article
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Purpose. Study the effects of 13-cis-retinoic acid (13-RA), a synthetic analogue of a vitamin A used for the treatment of severe acne, on the blood flow in the rat brain using technetium-99m hexamethyl propylene amine oxime (99mTc-HMPAO) imaging. Methods. A total of 30 adult male Wistar rats were divided into the control (C), low-dose (L), and high-dose (H) groups. The L and H rats were exposed subcutaneously to 0.3 and 0.5 mg, respectively, of 13-RA per kg of body weight for seven days. Brain blood flow imaging was performed using a gamma camera. Then, a region of interest (ROI) around the brain (target, T), a whole-body region (WB), and a background region (BG) was selected and delimited. The net 99mTc-HMPAO brain counts were calculated as the net target counts, NTC = T − BG / WB − BG in all groups. At the end of the 99mTc-HMPAO brain blood flow imaging, the brain, heart, kidney, lung, and liver were rapidly removed, and their uptake was determined. Brain histopathological analysis was performed using hematoxylin and eosin stains. In addition, the plasma fatty acids were studied using gas chromatography/mass spectrometry. Results. There were highly significant differences between L and H in comparison to C and across the groups. The 99mTc-HMPAO radioactivity in the brain showed increased uptake in a dose-dependent manner. There were also significant changes in the brain tissues and decreased free fatty acids among the groups compared to C. Conclusion. 13-RA increases 99mTcHMPAO brain perfusion, uptake, and function and reduces fatty acids.
... If changing context influences the hemodynamic response function (HRF), then this would in turn influence activity estimates, producing apparent context-sensitivity even if the underlying neural representation is fully invariant. Factors known to influence the HRF include stimulus duration [51], separate scans [52], inter-trial interval [53], stress level [54], and levels of some neurotransmitters [55][56][57]. Exploring which changes in the HRF could influence the results of tests against invariance is beyond the scope of this work, but researchers should design their studies so that factors known to influence the HRF do not co-vary with changes in context. ...
Article
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Many research questions in sensory neuroscience involve determining whether the neural representation of a stimulus property is invariant or specific to a particular stimulus context (e.g., Is object representation invariant to translation? Is the representation of a face feature specific to the context of other face features?). Between these two extremes, representations may also be context-tolerant or context-sensitive. Most neuroimaging studies have used operational tests in which a target property is inferred from a significant test against the null hypothesis of the opposite property. For example, the popular cross-classification test concludes that representations are invariant or tolerant when the null hypothesis of specificity is rejected. A recently developed neurocomputational theory suggests two insights regarding such tests. First, tests against the null of context-specificity, and for the alternative of context-invariance, are prone to false positives due to the way in which the underlying neural representations are transformed into indirect measurements in neuroimaging studies. Second, jointly performing tests against the nulls of invariance and specificity allows one to reach more precise and valid conclusions about the underlying representations, particularly when the null of invariance is tested using the fine-grained information from classifier decision variables rather than only accuracies (i.e., using the decoding separability test). Here, we provide empirical and computational evidence supporting both of these theoretical insights. In our empirical study, we use encoding of orientation and spatial position in primary visual cortex as a case study, as previous research has established that these properties are encoded in a context-sensitive way. Using fMRI decoding, we show that the cross-classification test produces false-positive conclusions of invariance, but that more valid conclusions can be reached by jointly performing tests against the null of invariance. The results of two simulations further support both of these conclusions. We conclude that more valid inferences about invariance or specificity of neural representations can be reached by jointly testing against both hypotheses, and using neurocomputational theory to guide the interpretation of results.
... Chronic disruptions of neurovascular couplingtypically manifesting as decreases in arterial dilation amplitude and resulting flow changes, along with delayed onset of responses [3,4] have adverse health effects on the brain. Stress affects neurovascular coupling [4,5], and many neurodegenerative diseases are marked by vascular dysfunction [6]. There is evidence suggesting that neurovascular dysfunction plays a role in autism [7] and other neurodevelopmental and mental disorders [7][8][9]. ...
Article
In the brain, increases in neural activity drive changes in local blood flow via neurovascular coupling. The common explanation for increased blood flow (known as functional hyperemia) is that it supplies the metabolic needs of active neurons. However, there is a large body of evidence that is inconsistent with this idea. Baseline blood flow is adequate to supply oxygen needs even with elevated neural activity. Neurovascular coupling is irregular, absent, or inverted in many brain regions, behavioral states, and conditions. Increases in respiration can increase brain oxygenation without flow changes. Simulations show that given the architecture of the brain vasculature, areas of low blood flow are inescapable and cannot be removed by functional hyperemia. As discussed in this article, potential alternative functions of neurovascular coupling include supplying oxygen for neuromodulator synthesis, brain temperature regulation, signaling to neurons, stabilizing and optimizing the cerebral vascular structure, accommodating the non-Newtonian nature of blood, and driving the production and circulation of cerebrospinal fluid (CSF).
... Within a subject, the HRFs may vary in magnitude and timing across trials, sessions, seasons, brain regions, and tasks (Aguirre et al., 1998;Cohen et al., 2002;Gonzalez-Castillo et al., 2015;Handwerker et al., 2004;Meyer et al., 2016;Neumann et al., 2003;Puckett et al., 2014;Taylor et al., 2018;Truccolo et al., 2002). Comparison between HRFs across subjects and brain conditions can show even larger variability (Bonakdarpour et al., 2007;D'Esposito et al., 2003;Elbau et al., 2018;Handwerker et al., 2004). Some of the variability in many early experiments could be attributed to the use of coarse spatial resolution (3-5 mm anisotropic voxels), which creates partial volume effects that mix gray matter, white matter, and superficial vascular signals from draining veins (Kim & Ress, 2017;Turner, 2002). ...
Article
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The hemodynamic response function (HRF) measured with functional magnetic resonance imaging is generated by vascular and metabolic responses evoked by brief (<4 s) stimuli. It is known that the human HRF varies across cortex, between subjects, with stimulus paradigms, and even between different measurements in the same cortical location. However, our results demonstrate that strong HRFs are remarkably repeatable across sessions separated by time intervals up to 3 months. In this study, a multisensory stimulus was used to activate and measure the HRF across the majority of cortex (>70%, with lesser reliability observed in some areas of prefrontal cortex). HRFs were measured with high spatial resolution (2‐mm voxels) in central gray matter to minimize variations caused by partial‐volume effects. HRF amplitudes and temporal dynamics were highly repeatable across four sessions in 20 subjects. Positive and negative HRFs were consistently observed across sessions and subjects. Negative HRFs were generally weaker and, thus, more variable than positive HRFs. Statistical measurements showed that across‐session variability is highly correlated to the variability across events within a session; these measurements also indicated a normal distribution of variability across cortex. The overall repeatability of the HRFs over long time scales generally supports the long‐term use of event‐related functional magnetic resonance imaging protocols. We measured and characterized the hemodynamic response function (HRF) across multiple time intervals (3‐hour, 3‐day, and 3‐month) to examine its longitudinal stability within cerebral cortex. Results quantify both amplitude and temporal stability of the HRF across brain regions and subjects. The work continues characterization of a simple but effective event‐related multisensory stimulus protocol that successfully evokes strong HRFs across the majority of human cerebral cortex in a single scanning session.
... Neurovascular coupling is essential for brain integrity (Longden et al., 2016). It has been shown to be modified by psychological stress in humans (Elbau et al., 2018) and suggested to be diminished upon stress in rodents (Han et al., 2019;Lee et al., 2015;Longden et al., 2014). The present study questions whether changes in neurovascular signaling are associated with variable stress susceptibility. ...
Article
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Neurovascular coupling ensures rapid and precise delivery of O2 and nutrients to active brain regions. Chronic stress is known to disturb neurovascular signaling with grave effects on brain integrity. We hypothesized that stress-induced neurovascular disturbances depend on stress susceptibility. Wistar male rats were exposed to 8 weeks of chronic mild stress. Stressed rats with anhedonia-like behavior and with preserved hedonic state were identified from voluntary sucrose consumption. In brain slices from nonstressed, anhedonic, and hedonic rats, neurons and astrocytes showed similar intracellular Ca²⁺ responses to neuronal excitation. Parenchymal arterioles in brain slices from nonstressed, anhedonic, and hedonic rats showed vasodilation in response to neuronal excitation. This vasodilation was dependent on inward rectifying K⁺ channel (Kir2) activation. In hedonic rats, this vasodilation was transient and followed by vasoconstriction insensitive to Kir2 channel inhibition with 100 µM BaCl2. Isolated arteries from hedonic rats showed increased contractility. Elevation of bath K⁺ relaxed isolated middle cerebral arteries in a concentration-dependent and Kir2-dependent manner. The vasorelaxation to 20–24 mM K⁺ was reduced in arteries from hedonic rats. The expression of voltage-gated K⁺ channels, Kv7.4, was reduced in the cerebral arteries from hedonic rats, whereas the expression of arterial inward-rectifying K⁺ channels, Kir2.1 was similar to that of nonstressed and anhedonic rats. We propose that preserved hedonic state is associated with increased arterial contractility caused by reduced hyperpolarizing contribution of Kv7.4 channels leading to biphasic cerebrovascular responses to neuronal excitation. These findings reveal a novel potential coping mechanism associated with altered neurovascular signaling.
... 78 However, it should be noted that the aforementioned studies utilized altered physiological states or external stimulations to characterize the regional neurovascular relationships, and these relationships may be different under resting-state conditions. In support, altered vascular responses have been observed in several disease states, 77,79,80 and in response to stress, 81 pain, 8 or anesthesia, 82 and many studies have also shown non-linear coupling between sensory stimulation frequencies and hemodynamic responses. 5,69,[83][84][85][86][87] Furthermore, there are known interactions between neurophysiological conditions and neuronal responses to sensory stimulations. ...
Article
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Significance Although emerging evidence suggests that the hemodynamic response function (HRF) can vary by brain region and species, a single, canonical, human-based HRF is widely used in animal studies. Therefore, the development of flexible, accessible, brain-region specific HRF calculation approaches is paramount as hemodynamic animal studies become increasingly popular. Aim To establish an fMRI-compatible, spectral, fiber-photometry platform for HRF calculation and validation in any rat brain region. Approach We used our platform to simultaneously measure (a) neuronal activity via genetically encoded calcium indicators (GCaMP6f), (b) local cerebral blood volume (CBV) from intravenous Rhodamine B dye, and (c) whole brain CBV via fMRI with the Feraheme contrast agent. Empirical HRFs were calculated with GCaMP6f and Rhodamine B recordings from rat brain regions during resting-state and task-based paradigms. Results We calculated empirical HRFs for the rat primary somatosensory, anterior cingulate, prelimbic, retrosplenial, and anterior insular cortical areas. Each HRF was faster and narrower than the canonical HRF and no significant difference was observed between these cortical regions. When used in general linear model analyses of corresponding fMRI data, the empirical HRFs showed better detection performance than the canonical HRF. Conclusions Our findings demonstrate the viability and utility of fiber-photometry-based HRF calculations. This platform is readily scalable to multiple simultaneous recording sites, and adaptable to study transfer functions between stimulation events, neuronal activity, neurotransmitter release, and hemodynamic responses.
... Individuals with certain mutations in KCNJ2 have been reported to also exhibit psychiatric symptoms resembling major depressive disorder ( Chan et al., 2010 ). KCNJ2 expression in smooth muscle cells is downregulated by the glucocorticoid receptor under the 7-day heterotypic stress paradigm, indicating its potential important role in neurovascular coupling ( Elbau et al., 2018 ;Longden et al., 2014 ). The potential role of stress and neurovascular coupling in suicide is also supported by our observation of enrichment of pericyte genes, though further studies are needed to explain why this enrichment was found in OFC and not in PFC/DLPFC. ...
Article
Suicide claims over 800,000 deaths worldwide, making it a serious public health problem. The etiopathophysiology of suicide remains unclear and is highly complex, and postmortem gene expression studies can offer insights into the molecular biological mechanism underlying suicide. In the current study, we conducted a meta-analysis of postmortem brain gene expression in relation to suicide. We identified five gene expression datasets for postmortem orbitofrontal, prefrontal, or dorsolateral prefrontal cortical brain regions from the Gene Expression Omnibus repository. After quality control, the total sample size was 380 (141 suicide deaths and 239 deaths from other causes). We performed the analyses using two meta-analytic approaches. We further performed pathway and cell-set enrichment analyses. We found reduced expression of the KCNJ2 (Potassium Inwardly Rectifying Channel Subfamily J Member 2), A2M (Alpha-2-Macroglobulin), AGT (Angiotensinogen), PMP2 (Peripheral Myelin Protein 2), and VEZF1 (Vascular Endothelial Zinc Finger 1) genes (FDR p<0.05). Our findings support the involvement of astrocytes, stress response, immune system, and microglia in suicide. These findings will require further validation in additional large datasets.
... By quantifying gene expression in peripheral blood at baseline and three hours post dexamethasone administration, we reported eQTLs which modulate the transcriptome response to GR-activation in men. The eQTL SNPs (eSNPs) were shown to be enriched among genetic variants associated with schizophrenia as well as MDD and to predict amygdala reactivity to threat [33] as well as neurovascular-coupling related features of the neural stress response [34]. The transcripts regulated by these variants form tight co-expression networks. ...
Article
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Substantial sex differences have been reported in the physiological response to stress at multiple levels, including the release of the stress hormone, cortisol. Here, we explore the genomic variants in 93 females and 196 males regulating the initial transcriptional response to cortisol via glucocorticoid receptor (GR) activation. Gene expression levels in peripheral blood were obtained before and after GR-stimulation with the selective GR agonist dexamethasone to identify differential expression following GR-activation. Sex stratified analyses revealed that while the transcripts responsive to GR-stimulation were mostly overlapping between males and females, the quantitative trait loci (eQTLs) regulation differential transcription to GR-stimulation was distinct. Sex-stratified eQTL SNPs (eSNPs) were located in different functional genomic elements and sex-stratified transcripts were enriched within postmortem brain transcriptional profiles associated with Major Depressive Disorder (MDD) specifically in males and females in the cingulate cortex. Female eSNPs were enriched among SNPs linked to MDD in genome-wide association studies. Finally, transcriptional sensitive genetic profile scores derived from sex-stratified eSNPS regulating differential transcription to GR-stimulation were predictive of depression status and depressive symptoms in a sex-concordant manner in a child and adolescent cohort ( n = 584). These results suggest the potential of eQTLs regulating differential transcription to GR-stimulation as biomarkers of sex-specific biological risk for stress-related psychiatric disorders.
... Microglial activation in response to stress in depression has been implicated in a dysfunctional hypothalamus-pituitary-adrenal (HPA) axis and higher cortisol levels [85]. The disparity of inflammation in the CNS promotes the release of cytokines and upsets the functional coupling and structural changes, leading to impaired neurovascular responsivity and reduced cerebral blood flow following neural stimulation [86]. In addition to attenuated brain activity, structural deficits support the findings from functional imaging that there are volumetric reductions in grey matter [87], hypometabolism during the resting state [88], increased vulnerability to cellular apoptosis [89], and altered connectivity [90] in the OFC; Tsujii et al. proposed that the OFC is a potential area that could be used to discern between MDD and bipolar disorder, two disorders with similar symptoms [91]. ...
Article
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Background: Major depressive disorder (MDD) is a debilitating condition with a high disease burden and medical comorbidities. There are currently few to no validated biomarkers to guide the diagnosis and treatment of MDD. In the present study, we evaluated the differences between MDD patients and healthy controls (HCs) in terms of cortical haemodynamic responses during a verbal fluency test (VFT) using functional near-infrared spectroscopy (fNIRS) and serum amino acid profiles, and ascertained if these parameters were correlated with clinical characteristics. Methods: Twenty-five (25) patients with MDD and 25 age-, gender-, and ethnicity-matched HCs were recruited for the study. Real-time monitoring of the haemodynamic response during completion of a VFT was quantified using a 52-channel NIRS system. Serum samples were analysed and quantified by liquid chromatography-mass spectrometry for amino acid profiling. Receiver-operating characteristic (ROC) curves were used to classify potential candidate biomarkers. Results: The MDD patients had lower prefrontal and temporal activation during completion of the VFT than HCs. The MDD patients had lower mean concentrations of oxy-Hb in the left orbitofrontal cortex (OFC), and lower serum histidine levels. When the oxy-haemoglobin response was combined with the histidine concentration, the sensitivity and specificity of results improved significantly from 66.7% to 73.3% and from 65.0% to 90.0% respectively, as compared to results based only on the NIRS response. Conclusions: These findings demonstrate the use of combination biomarkers to aid in the diagnosis of MDD. This technique could be a useful approach to detect MDD with greater precision, but additional studies are required to validate the methodology.
... The rationale would be that one can think of the HRF as a fixed transfer function between neural activity and hemodynamics, and in this sense it should be constant across tasks. Yet increasing evidence points to a variability of the HRF across tasks and conditions (Handwerker, Gonzalez-Castillo et al. 2012, Elbau, Brucklmeier et al. 2018, Taylor, Kim et al. 2018, Cardoso, Lima et al. 2019. In this sense we would certainly encourage (and engage ourselves in) more research along these lines, using hierarchical and clustering approaches to find one or more ...
Article
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The hemodynamic response function (HRF) greatly influences the intra- and inter-subject variability of brain activation and connectivity, and might confound the estimation of temporal precedence in connectivity analyses, making its estimation necessary for a correct interpretation of neuroimaging studies. Additionally, the HRF shape itself is a useful local measure. However, most algorithms for HRF estimation are specific for task-related fMRI data, and only a few can be directly applied to resting-state protocols. Here we introduce rsHRF, a Matlab and Python toolbox that implements HRF estimation and deconvolution from the resting-state BOLD signal. We first provide an overview of the main algorithm, practical implementations, and then demonstrate the feasibility and usefulness of rsHRF by validation experiments with a publicly available resting-state fMRI dataset. We also provide tools for statistical analyses and visualization. We believe that this toolbox may significantly contribute to a better analysis and understanding of the components and variability of BOLD signals.
... The short version is also referred to as BSKE (short for German "Befindlichkeitsskalierung nach Kategorien und Eigenschaftswörtern"). This questionnaire has been validated and used in several stress-related experimental studies (Bach and Erdmann, 2007;Elbau et al., 2018;Höhne et al., 2014;Ising et al., 2008) and in pharmacological drug trials (Gerlach et al., 2002;Uhlig et al., 2000). The BSKE presents several terms and asks the participant to indicate on a scale from 0 "not at all" to 5 "very strongly" how much a certain term represents their current affective state. ...
Article
Negative interpersonal experiences are a key contributor to psychiatric disorders. While previous research has shown that negative interpersonal experiences influence social cognition, less is known about the effects on participation in social interactions and the underlying neurobiology. To address this, we developed a new naturalistic version of a gaze-contingent paradigm using real video sequences of gaze behaviour that respond to the participants' gaze in real-time in order to create a believable and continuous interactive social situation. Additionally, participants listened to two autobiographical audio-scripts that guided them to imagine a recent stressful and a relaxing situation and performed the gaze-based social interaction task before and after the presentation of either the stressful or the relaxing audio-script. Our results demonstrate that the social interaction task robustly recruits brain areas with known involvement in social cognition, namely the medial prefrontal cortex, bilateral temporoparietal junction, superior temporal sulcus as well as the precuneus. Imagery of negative interpersonal experiences compared to relaxing imagery led to a prolonged change in affective state and to increased brain responses during the subsequent social interaction paradigm in the temporoparietal junction, medial prefrontal cortex, anterior cingulate cortex, precuneus and inferior frontal gyrus. Taken together this study presents a new naturalistic social interaction paradigm suitable to study the neural mechanisms of social interaction and the results demonstrate that the imagery of negative interpersonal experiences affects social interaction on neural levels.
... In many papers on EEGcorrelated fMRI, a canonical hemodynamic response function (HRF) based on two gamma density functions is used to translate IED-related temporal dynamics to BOLD fluctuations (Friston et al., 1998). However, there is insur-55 mountable evidence that the HRF is not fixed, but varies substantially over subjects (Aguirre et al., 1998), over brain regions (Handwerker et al., 2004), with age (Jacobs et al., 2008), or even with stress level (Elbau et al., 2018). For the diseased brain, this issue may be even greater: i.e., 60 additional variation, e.g. in brain areas involved in the epileptic network, has been observed compared to healthy controls (van Houdt et al., 2013;Bénar et al., 2002;Jacobs et al., 2009;Lemieux et al., 2008;Grouiller et al., 2010). ...
Article
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EEG-correlated fMRI analysis is widely used to detect regional BOLD fluctuations that are synchronized to interictal epileptic discharges, which can provide evidence for localizing the ictal onset zone. However, the typical, asymmetrical and mass-univariate approach cannot capture the inherent, higher order structure in the EEG data, nor multivariate relations in the fMRI data, and it is nontrivial to accurately handle varying neurovascular coupling over patients and brain regions. We aim to overcome these drawbacks in a data-driven manner by means of a novel structured matrix-tensor factorization: the single-subject EEG data (represented as a third-order spectrogram tensor) and fMRI data (represented as a spatiotemporal BOLD signal matrix) are jointly decomposed into a superposition of several sources, characterized by space-time-frequency profiles. In the shared temporal mode, Toeplitz-structured factors account for a spatially specific, neurovascular ‘bridge’ between the EEG and fMRI temporal fluctuations, capturing the hemodynamic response’s variability over brain regions. By analyzing interictal data from twelve patients, we show that the extracted source signatures provide a sensitive localization of the ictal onset zone (10/12). Moreover, complementary parts of the IOZ can be uncovered by inspecting those regions with the most deviant neurovascular coupling, as quantified by two entropy-like metrics of the hemodynamic response function waveforms (9/12). Hence, this multivariate, multimodal factorization provides two useful sets of EEG-fMRI biomarkers, which can assist the presurgical evaluation of epilepsy. We make all code required to perform the computations available at https://github.com/svaneynd/structured-cmtf.
... Arguably, translating these findings to clinical applications would require a broad generalization of the results or the prediction algorithm to psychosocial stress. Here, we assessed the predictive performance of Goldfarb et al's 1 algorithm for subjective stress in an independent sample using an MR adaption of the TSST 6,7 . In line with Goldfarb et al. 1 , we observed robust stress-induced changes in hippocampal connectivity. ...
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Stress is an everyday experience and maladaptive responses play a crucial role in the etiology of affective disorders. Despite its ubiquity, the neural underpinnings of subjective stress experiences have not yet been elucidated, particularly at an individual level. In an important advance, Goldfarb et al. ¹ showed recently that subjective stress and arousal levels in response to threatening stimuli were successfully predicted based on changes in hippocampal connectivity during the task using a machine learning approach. Crucially, stress responses were predicted by interpretable hippocampal connectivity networks, shedding new light on the role of the hippocampus in regulating stress reactivity ² . However, the authors induced stress by displaying aversive pictures, while stress research often relies on the extensively validated Trier social stress task (TSST) ³ . The TSST incorporates crucial factors such as unpredictability of success and the social-evaluative threat of the stressor thereby eliciting cortisol responses more robustly compared to threatening images ⁴ . Towards generalization, cross validation within a sample as conducted by Goldfarb et al. ¹ or independent replications are important steps, but the generalizability to different stressors allows to draw broader conclusions about the potential use of hippocampal connectivity to predict subjective stress ⁵ . Arguably, translating these findings to clinical applications would require a broad generalization of the results or the prediction algorithm to psychosocial stress. Here, we assessed the predictive performance of Goldfarb et al’s ¹ algorithm for subjective stress in an independent sample using an MR adaption of the TSST 6,7 . In line with Goldfarb et al. ¹ , we observed robust stress-induced changes in hippocampal connectivity. However, the spatial correlation of the changes in connectivity was low indicating little convergence across alleged stress paradigms. Critically, stress-induced changes of hippocampal connectivity were not robustly predictive of subjective stress across a multiverse of analyses based on connectivity changes. Collectively, this indicates that the generalizability of the reported stress connectivity fingerprint to other stressors is limited at best, suggesting that specific tasks might require tailored algorithms to robustly predict stress above chance levels.
... One notable finding comes from Cohen and colleagues [53], who demonstrated that varying levels of CBF (induced by hypercapnia, normocapnia and hypocapnia) mediated the onset time, time-to-peak and amplitude of the HRF under the same visual stimulation. The HRF has also been shown to change with genetic, hormonal and other systemic fluctuations [270][271][272]. Regional variability in the HRF is partly dictated by the size of surrounding blood vessels, e.g. ...
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... In addition to math performance measures, participant autonomic responses to MIST are commonly used to validate and index stress reactivity to the task (Allendorfer et al., 2014Wheelock et al., 2016;Elbau et al., 2018;Goodman et al., 2018Goodman et al., , 2019Gossett et al., 2018;Orem et al., 2019). In the present study, we sought to assess whether these measures indicated stress reactivity and whether this reactivity varied across repeated MRI visits. ...
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FMRI Montreal Imaging Stress Tasks (MIST) have been shown to activate endocrine and autonomic stress responses that are mediated by a prefrontal cortex (PFC)-hippocampus-amygdala circuit. However, the stability of the neurobehavioral responses over time and the ability to monitor response to clinical interventions has yet to be validated. The objective of this study was to compare the fMRI and physiologic responses to acute psychosocial stress in healthy volunteers during initial and follow-up visits approximately 13 weeks later, simulating a typical duration of clinical intervention. We hypothesized that responses to stress would remain highly conserved across the 2 visits in the absence of an intervention. 15 healthy volunteers completed a variant of control math task (CMT) and stress math task (SMT) conditions based on MIST. Neural responses were modeled using an event-related design with estimates for math performance and auditory feedback for each task condition. For each visit, measures of stress reactivity included differential fMRI and heart rate (SMT-CMT), as well as salivary alpha-amylase before and after scanning sessions. The results revealed that differential fMRI, as well as increased heart rate and salivary alpha-amylase from before and after scanning remained similar between visits. Intraclass correlation coefficient (ICC) values revealed areas of reliable task-dependent BOLD fMRI signal response across visits for peaks of clusters for the main effect of condition (SMT vs CMT) within dorsal anterior cingulate cortex (ACC), insula, and hippocampus regions during math performance and within subgenual ACC, posterior cingulate cortex, dorsolateral PFC regions during auditory feedback. Given that the neurobehavioral response to acute stress remained highly conserved across visits in the absence of an intervention, this study confirms the utility for MIST for assessing longitudinal changes in controlled trials that can identify underlying neurobiological mechanisms involved in mediating the efficacy of stress-reduction interventions.
... It has been shown to be especially effective in bird species due to their specific bone structure 63 and lack of mastication muscles 64 . However, to avoid stress-related artifacts on the BOLD signal 27 and any unanticipated movements that could induce artifacts or would lead in worst case to the detachment of the pedestal, pigeons need to be accustomed to all experimental procedures. Thus, it is mandatory for both scientific and for animal welfare reasons, to implement a habituation protocol and to ensure its effectiveness. ...
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... Glucocorticoids and HPA axis involvement have been extensively described under acute stress, but their functioning throughout chronic stress and particularly in the workplace still requires clarification (Elbau et al., 2018;Rohleder, 2018;Sunwoo et al., 2019). ...
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... In many papers on EEGcorrelated fMRI, a canonical hemodynamic response function (HRF) based on two gamma density functions is used to translate IED-related temporal dynamics to BOLD fluc-55 tuations (Friston et al., 1998). However, there is insurmountable evidence that the HRF is not fixed, but varies substantially over subjects (Aguirre et al., 1998), over brain regions (Handwerker et al., 2004), with age (Jacobs et al., 2008), or even with stress level (Elbau et al., 2018). 60 For the diseased brain, this issue may be even greater: i.e., additional variation, e.g. in brain areas involved in the epileptic network, has been observed compared to healthy controls (van Houdt et al., 2013;Bénar et al., 2002;Jacobs et al., 2009;Lemieux et al., 2008;Grouiller et al., 2010). ...
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EEG-correlated fMRI analysis is widely used to detect regional blood oxygen level dependent fluctuations that are significantly synchronized to interictal epileptic discharges, which can provide evidence for localizing the ictal onset zone. However, such an asymmetrical, mass-univariate approach cannot capture the inherent, higher order structure in the EEG data, nor multivariate relations in the fMRI data, and it is nontrivial to accurately handle varying neurovascular coupling over patients and brain regions. We aim to overcome these drawbacks in a data-driven manner by means of a novel structured matrix-tensor factorization: the single-subject EEG data (represented as a third-order spectrogram tensor) and fMRI data (represented as a spatiotemporal BOLD signal matrix) are jointly decomposed into a superposition of several sources, characterized by space-time-frequency profiles. In the shared temporal mode, Toeplitz-structured factors account for a spatially specific, neurovascular `bridge' between the EEG and fMRI temporal fluctuations, capturing the hemodynamic response's variability over brain regions. We show that the extracted source signatures provide a sensitive localization of the ictal onset zone, and, moreover, that complementary localizing information can be derived from the spatial variation of the hemodynamic response. Hence, this multivariate, multimodal factorization provides two useful sets of EEG-fMRI biomarkers, which can inform the presurgical evaluation of epilepsy. We make all code required to perform the computations available.
... However, the BOLD signal is a noisy, indirect measure of underlying neural activity, and the sluggish hemodynamic response places a fundamental limit on the temporal resolution of TVFC estimated from fMRI data. It is well established that the shape of the hemodynamic response function varies across brain areas (Handwerker, Ollinger, & D'Esposito, 2004) and individuals (Aguirre, Zarahn, & D'Esposito, 1998), and emerging work suggests that neurovascular coupling may also vary across behavioral and bodily states (Elbau et al., 2018;Lecrux & Hamel, 2016;Winder, Echagarruga, Zhang, & Drew, 2017). While these and other factors can complicate the neurophysiological interpretation of fMRI findings, we do not believe they preclude the use of BOLD fMRI for studies of time-varying neural interactions. ...
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The brain is a complex, multiscale dynamical system composed of many interacting regions. Knowledge of the spatiotemporal organization of these interactions is critical for establishing a solid understanding of the brain’s functional architecture and the relationship between neural dynamics and cognition in health and disease. The possibility of studying these dynamics through careful analysis of neuroimaging data has catalyzed substantial interest in methods that estimate time-resolved fluctuations in functional connectivity (often referred to as “dynamic” or time-varying functional connectivity; TVFC). At the same time, debates have emerged regarding the application of TVFC analyses to resting fMRI data, and about the statistical validity, physiological origins, and cognitive and behavioral relevance of resting TVFC. These and other unresolved issues complicate interpretation of resting TVFC findings and limit the insights that can be gained from this promising new research area. This article brings together scientists with a variety of perspectives on resting TVFC to review the current literature in light of these issues. We introduce core concepts, define key terms, summarize controversies and open questions, and present a forward-looking perspective on how resting TVFC analyses can be rigorously and productively applied to investigate a wide range of questions in cognitive and systems neuroscience.
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Detailed knowledge of the BOLD hemodynamic response function (HRF) is crucial for accurate analyses and interpretation of functional MRI data. Considerable efforts have been made to characterize the HRF in gray matter (GM) but much less attention has been paid to BOLD effects in white matter (WM). However, several recent reports have demonstrated reliable detection and analyses of WM BOLD signals both after stimulation and in a resting state. WM and GM differ in composition, energy requirements and blood flow, so their neurovascular couplings also may well be different. We aimed to derive a comprehensive characterization of the HRF in WM across a population, including accurate measurements of its shape and its variation along and between WM pathways, using resting-state fMRI acquisitions. Our results show that the HRF is significantly different between WM and GM. Features of the HRF, such as a prominent initial dip, show strong relationships with features of the tissue microstructure derived from diffusion imaging, and these relationships differ between WM and GM, consistent with BOLD signal fluctuations reflecting different energy demands and neurovascular couplings in tissues of different composition and function. We also show that the HRF varies in shape significantly along WM pathways, and is different between different WM pathways, suggesting the temporal evolution of BOLD signals after an event vary in different parts of the WM. These features of the HRF in WM are especially relevant for interpretation of the biophysical basis of BOLD effects in WM.
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Emotions depend upon the integrated activity of neural networks that modulate arousal, autonomic function, motor control, and somatosensation. Brainstem nodes play critical roles in each of these networks, but prior studies of the neuroanatomic basis of emotion, particularly in the human neuropsychological literature, have mostly focused on the contributions of cortical rather than subcortical structures. Given the size and complexity of brainstem circuits, elucidating their structural and functional properties involves technical challenges. However, recent advances in neuroimaging have begun to accelerate research into the brainstem’s role in emotion. In this review, we provide a conceptual framework for neuroscience, psychology and behavioral science researchers to study brainstem involvement in human emotions. The “emotional brainstem” is comprised of three major networks – Ascending, Descending and Modulatory. The Ascending network is composed chiefly of the spinothalamic tracts and their projections to brainstem nuclei, which transmit sensory information from the body to rostral structures. The Descending motor network is subdivided into medial projections from the reticular formation that modulate the gain of inputs impacting emotional salience, and lateral projections from the periaqueductal gray, hypothalamus and amygdala that activate characteristic emotional behaviors. Finally, the brainstem is home to a group of modulatory neurotransmitter pathways, such as those arising from the raphe nuclei (serotonergic), ventral tegmental area (dopaminergic) and locus coeruleus (noradrenergic), which form a Modulatory network that coordinates interactions between the Ascending and Descending networks. Integration of signaling within these three networks occurs at all levels of the brainstem, with progressively more complex forms of integration occurring in the hypothalamus and thalamus. These intermediary structures, in turn, provide input for the most complex integrations, which occur in the frontal, insular, cingulate and other regions of the cerebral cortex. Phylogenetically older brainstem networks inform the functioning of evolutionarily newer rostral regions, which in turn regulate and modulate the older structures. Via these bidirectional interactions, the human brainstem contributes to the evaluation of sensory information and triggers fixed-action pattern responses that together constitute the finely differentiated spectrum of possible emotions.
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Brain imaging techniques that use vascular signals to map changes in neuronal activity rely on the coupling between electrophysiology and hemodynamics, a phenomenon referred to “neurovascular coupling” (NVC). It is unknown whether this relationship remains reliable under altered brain states associated to acetylcholine (ACh) levels, such as attention and arousal, and in pathological conditions like Alzheimer's disease. We therefore assessed the effects of varying ACh tone on whisker evoked-NVC responses in rat barrel cortex, measured by cerebral blood flow (CBF) and neurophysiological recordings (local field potentials, LFPs). We found that acutely enhanced ACh tone significantly potentiated whisker-evoked CBF responses through muscarinic ACh receptors, and concurrently facilitated neuronal responses illustrated by increases in the amplitude and power in high frequencies of the evoked LFPs. However, the cellular identity of the activated neuronal network within the responsive barrel was unchanged, as characterized by c-Fos upregulation in pyramidal cells and GABA interneurons co-expressing vasoactive intestinal polypeptide. In contrast, chronic ACh deprivation hindered whisker-evoked CBF responses, and the amplitude and power in most frequency bands of the evoked LFPs, and reduced the rostro-caudal extent and area of the activated barrel without altering its identity. Correlations between LFP power and CBF, used to estimate NVC, were enhanced under high ACh tone and significantly disturbed by ACh depletion. We conclude that ACh is not only a facilitator, but also a prerequisite for the full expression of sensory-evoked NVC responses, indicating that ACh may alter the fidelity of hemodynamic signals in assessing changes in evoked neuronal activity.
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Brain imaging techniques that use vascular signals to map changes in neuronal activity, such as blood oxygenation level-dependent functional magnetic resonance imaging, rely on the spatial and temporal coupling between changes in neurophysiology and haemodynamics, known as ‘neurovascular coupling (NVC)’. Accordingly, NVC responses, mapped by changes in brain haemodynamics, have been validated for different stimuli under physiological conditions. In the cerebral cortex, the networks of excitatory pyramidal cells and inhibitory interneurons generating the changes in neural activity and the key mediators that signal to the vascular unit have been identified for some incoming afferent pathways. The neural circuits recruited by whisker glutamatergic-, basal forebrain cholinergic- or locus coeruleus noradrenergic pathway stimulation were found to be highly specific and discriminative, particularly when comparing the two modulatory systems to the sensory response. However, it is largely unknown whether or not NVC is still reliable when brain states are altered or in disease conditions. This lack of knowledge is surprising since brain imaging is broadly used in humans and, ultimately, in conditions that deviate from baseline brain function. Using the whisker-to-barrel pathway as a model of NVC, we can interrogate the reliability of NVC under enhanced cholinergic or noradrenergic modulation of cortical circuits that alters brain states. http://rstb.royalsocietypublishing.org/cgi/content/abstract/rstb.2015.0350
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Some efforts were done to investigate the disruption of brain causal connectivity networks involved in major depressive disorder (MDD) using Granger causality (GC) analysis. However, the homogenous hemodynamic response function (HRF) assumption over the brain may disturb the inference of temporal precedence. Here we applied a blind deconvolution approach to examine the altered HRF shape in first-episode, drug-naïve MDD patients. The regions with abnormal HRF shape in patients were chosen as seeds to detect the GC alterations in MDD. The results demonstrated significantly decreased magnitude of spontaneous hemodynamic response of the orbital frontal cortex (OFC) and the caudate nucleus (CAU) in MDD comparing to healthy controls, suggesting MDD patients likely had alterations in neurovascular coupling and cerebrovascular physiology in these two regions. GC mapping showed increased/decreased GC in OFC-/CAU centered networks in MDD. The outgoing GC values from OFC to anterior cingulate cortex and occipital regions were positively correlated with Hamilton Depression Scale (HAMD) scores, while the incoming GC from insula, middle and superior temporal gyrus to CAU were negatively correlated with HAMD scores of MDD. The abnormalities of directional connections in the cortico-subcortico-cerebellar network may lead to unbalanced integrating the emotional-related information for MDD, and further exacerbating depressive symptoms.
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In functional magnetic resonance imaging (fMRI), the hemodynamic response function (HRF) reflects regulation of regional cerebral blood flow in response to neuronal activation. The HRF varies significantly between individuals. This study investigated the genetic contribution to individual variation in HRF using fMRI data from 125 monozygotic (MZ) and 149 dizygotic (DZ) twin pairs. The resemblance in amplitude, latency, and duration of the HRF in six regions in the frontal and parietal lobes was compared between MZ and DZ twin pairs. Heritability was estimated using an ACE (Additive genetic, Common environmental, and unique Environmental factors) model. The genetic influence on the temporal profile and amplitude of HRF was moderate to strong (24%-51%). The HRF may be used in the genetic analysis of diseases with a cerebrovascular etiology.
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Cerebral hemodynamic responses to brief periods of neural activity are delayed and dispersed in time. The specific shape of these responses is of some importance to the design and analysis of blood oxygenation level-dependent (BOLD), functional magnetic resonance imaging (fMRI) experiments. Using fMRI scanning, we examine here the characteristics and variability of hemodynamic responses from the central sulcus in human subjects during an event-related, simple reaction time task. Specifically, we determine the contribution of subject, day, and scanning session (within a day) to variability in the shape of evoked hemodynamic response. We find that while there is significant and substantial variability in the shape of responses collected across subjects, responses collected during multiple scans within a single subject are less variable. The results are discussed in terms of the impact of response variability upon sensitivity and specificity of analyses of event-related fMRI designs.
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Objective: Cognitive deficits are a common feature of psychiatric disorders. The authors investigated the nature of disruptions in neural circuitry underlying cognitive control capacities across psychiatric disorders through a transdiagnostic neuroimaging meta-analysis. Method: A PubMed search was conducted for whole-brain functional neuroimaging articles published through June 2015 that compared activation in patients with axis I disorders and matched healthy control participants during cognitive control tasks. Tasks that probed performance or conflict monitoring, response inhibition or selection, set shifting, verbal fluency, and recognition or working memory were included. Activation likelihood estimation meta-analyses were conducted on peak voxel coordinates. Results: The 283 experiments submitted to meta-analysis included 5,728 control participants and 5,493 patients with various disorders (schizophrenia, bipolar or unipolar depression, anxiety disorders, and substance use disorders). Transdiagnostically abnormal activation was evident in the left prefrontal cortex as well as the anterior insula, the right ventrolateral prefrontal cortex, the right intraparietal sulcus, and the midcingulate/presupplementary motor area. Disruption was also observed in a more anterior cluster in the dorsal cingulate cortex, which overlapped with a network of structural perturbation that the authors previously reported in a transdiagnostic meta-analysis of gray matter volume. Conclusions: These findings demonstrate a common pattern of disruption across major psychiatric disorders that parallels the "multiple-demand network" observed in intact cognition. This network interfaces with the anterior-cingulo-insular or "salience network" demonstrated to be transdiagnostically vulnerable to gray matter reduction. Thus, networks intrinsic to adaptive, flexible cognition are vulnerable to broad-spectrum psychopathology. Dysfunction in these networks may reflect an intermediate transdiagnostic phenotype, which could be leveraged to advance therapeutics.