Resting-state Functional Connectivity MRI Research Articles

Resting-State Functional Connectivity of the Subthalamic Nucleus to Limbic, Associative, and Motor Networks.

The subthalamic nucleus (STN) is a small structure situated deep in the midbrain that exhibits wide-ranging functionality. In addition to its role in motor control, the STN is considered a hub for synchronizing aspects of emotion and cognition including attention, inhibitory control, motivation, and working memory. Evidence from neuroanatomical tracer studies suggests that the medial, ventromedial, and dorsolateral parts of the STN correspond to limbic, associative, and motor subdivisions, respectively. Although the extent of STN functional anatomical overlap remains unclear, blood oxygenation level dependent imaging of the STN may provide complementary information about the diverse functions of this structure. Methodological limitations in spatial and temporal resolutions, however, have prevented a comprehensive exploration of temporal correlations from the STN to the whole brain. In this study, we optimize spatial (2 mm isotropic) and temporal (TR = 1 s) resolutions to take full advantage of the time series signal-to-noise ratio capabilities of multichannel array coils and simultaneous multislice imaging. We interrogated STN seed-to-voxel resting-state functional MRI connectivity in a group of 30 healthy participants that included the whole brain at high-temporal and spatial resolutions. This analysis revealed STN functional connectivity to limbic, associative, and motor networks. Our findings contribute to the understanding of STN functional neuroanatomy in humans and are clinically relevant for ongoing research in deep brain stimulation.

Separate neural representations of depression, anxiety and apathy in Parkinson\u2019s disease

Depression, anxiety and apathy are distinct neuropsychiatric symptoms that highly overlap in Parkinson’s disease (PD). It remains unknown whether each symptom is uniquely associated with a functional network dysfunction. Here, we examined whether individual differences in each neuropsychiatric symptom predict functional connectivity patterns in PD patients while controlling for all other symptoms and motor function. Resting-state functional connectivity MRI were acquired from 27 PD patients and 29 healthy controls. Widespread reduced functional connectivity was identified in PD patients and explained by either the neuropsychiatric or motor symptoms. Depression in PD predicted increased functional connectivity between the orbitofrontal, hippocampal complex, cingulate, caudate and thalamus. Apathy in PD predicted decreased caudate-thalamus and orbitofrontal-parahippocampal connectivity. Anxiety in PD predicted three distinct types of functional connectivity not described before: (i) increased limbic-orbitofrontal cortex; (ii) decreased limbic-dorsolateral prefrontal cortex and orbitofrontal-dorsolateral prefrontal cortices and (iii) decreased sensorimotor-orbitofrontal cortices. The first two types of functional connectivity suggest less voluntary and more automatic emotion regulation. The last type is argued to be specific to PD and reflect an impaired ability of the orbitofrontal cortex to guide goal-directed motor actions in anxious PD patients.

Cognitive control networks in OCD: A resting-state connectivity study in unmedicated patients with obsessive-compulsive disorder and their unaffected relatives

Objectives: Executive network deficits are putative neurocognitive endophenotypes for obsessive-compulsive disorder (OCD). Yet, unlike alterations in fronto-striatal and limbic connectivity, connectivity in the fronto-parietal (FPN) and cingulo-opercular (CON) networks involved in cognitive control has received little attention.Methods: The coherence of FPN, CON and fronto-limbic networks was investigated in 39 unmedicated OCD patients, 16 of their unaffected siblings and 36 healthy controls using resting-state functional-connectivity MRI and a seed-based analysis approach.Results: FPN and CON connectivity was similar for patients and controls. Siblings showed higher connectivity than patients within the CON, and between the CON and FPN compared to patients and controls (trend level). In OCD patients, but not in siblings, fronto-limbic hyperconnectivity was present compared to controls. In contrast to our expectations, no group differences in resting-state connectivity of the cognitive control networks were observed between OCD patients and controls.Conclusions: The increased within- and between-network connectivity in siblings, but not in patients, could indicate a mechanism of increased cognitive control that may act as a protective mechanism. None of the observed network alterations can be considered an endophenotype for OCD since differences were present in either patients or siblings, but not in both groups.

Interhemispheric Resting-State Functional Connectivity Predicts Severity of Idiopathic Normal Pressure Hydrocephalus.

Idiopathic normal pressure hydrocephalus (iNPH) is characterized by a clinical triad (gait disturbance, dementia, and urinary incontinence), and by radiological findings of enlarged ventricles reflecting disturbance of central spinal fluid circulation. A diagnosis of iNPH is sometimes challenging, and the pathophysiological mechanisms underlying the clinical symptoms of iNPH remain largely unknown. Here, we used an emerging MRI technique, resting-state functional connectivity MRI (rsfcMRI), to develop a subsidiary diagnostic technique and to explore the underlying pathophysiological mechanisms of iNPH. rsfcMRI data were obtained from 11 patients with iNPH and 11 age-matched healthy volunteers, yielding rsfcMRI-derived functional connectivity (FC) from both groups. A linear support vector machine classifier was trained to distinguish the patterns of FCs of the patients with iNPH from those of the healthy volunteers. After dimensional reduction, the support vector machine successfully classified the two groups with an accuracy of 80%. Moreover, we found that rsfcMRI-derived FC carried information to predict the severity of the triad in iNPH. FCs relevant to the classification of severity were mainly based on interhemispheric connectivity, suggesting that disruption of the corpus callosum fibers due to ventricular enlargement may explain the triad of iNPH. The present results support the usefulness of rsfcMRI as a tool to understand pathophysiology of iNPH, and also to help with its clinical diagnosis.

Resting-State Functional Connectivity in the Human Connectome Project: Current Status and Relevance to Understanding Psychopathology.

A key tenet of modern psychiatry is that psychiatric disorders arise from abnormalities in brain circuits that support human behavior. Our ability to examine hypotheses around circuit-level abnormalities in psychiatric disorders has been made possible by advances in human neuroimaging technologies. These advances have provided the basis for recent efforts to develop a more complex understanding of the function of brain circuits in health and of their relationship to behavior-providing, in turn, a foundation for our understanding of how disruptions in such circuits contribute to the development of psychiatric disorders. This review focuses on the use of resting-state functional connectivity MRI to assess brain circuits, on the advances generated by the Human Connectome Project, and on how these advances potentially contribute to understanding neural circuit dysfunction in psychopathology. The review gives particular attention to the methods developed by the Human Connectome Project that may be especially relevant to studies of psychopathology; it outlines some of the key findings about what constitutes a brain region; and it highlights new information about the nature and stability of brain circuits. Some of the Human Connectome Project's new findings particularly relevant to psychopathology-about neural circuits and their relationships to behavior-are also presented. The review ends by discussing the extension of Human Connectome Project methods across the lifespan and into manifest illness. Potential treatment implications are also considered.

Low-frequency hippocampal–cortical activity drives brain-wide resting-state functional MRI connectivity

The hippocampus, including the dorsal dentate gyrus (dDG), and cortex engage in bidirectional communication. We propose that low-frequency activity in hippocampal-cortical pathways contributes to brain-wide resting-state connectivity to integrate sensory information. Using optogenetic stimulation and brain-wide fMRI and resting-state fMRI (rsfMRI), we determined the large-scale effects of spatiotemporal-specific downstream propagation of hippocampal activity. Low-frequency (1 Hz), but not high-frequency (40 Hz), stimulation of dDG excitatory neurons evoked robust cortical and subcortical brain-wide fMRI responses. More importantly, it enhanced interhemispheric rsfMRI connectivity in various cortices and hippocampus. Subsequent local field potential recordings revealed an increase in slow oscillations in dorsal hippocampus and visual cortex, interhemispheric visual cortical connectivity, and hippocampal-cortical connectivity. Meanwhile, pharmacological inactivation of dDG neurons decreased interhemispheric rsfMRI connectivity. Functionally, visually evoked fMRI responses in visual regions also increased during and after low-frequency dDG stimulation. Together, our results indicate that low-frequency activity robustly propagates in the dorsal hippocampal-cortical pathway, drives interhemispheric cortical rsfMRI connectivity, and mediates visual processing.

Resting-State Functional Connectivity-Based Biomarkers and Functional MRI-Based Neurofeedback for Psychiatric Disorders: A Challenge for Developing Theranostic Biomarkers

Psychiatric research has been hampered by an explanatory gap between psychiatric symptoms and their neural underpinnings, which has resulted in poor treatment outcomes. This situation has prompted us to shift from symptom-based diagnosis to data-driven diagnosis, aiming to redefine psychiatric disorders as disorders of neural circuitry. Promising candidates for data-driven diagnosis include resting-state functional connectivity MRI (rs-fcMRI)-based biomarkers. Although biomarkers have been developed with the aim of diagnosing patients and predicting the efficacy of therapy, the focus has shifted to the identification of biomarkers that represent therapeutic targets, which would allow for more personalized treatment approaches. This type of biomarker (i.e., “theranostic biomarker”) is expected to elucidate the disease mechanism of psychiatric conditions and to offer an individualized neural circuit-based therapeutic target based on the neural cause of a condition. To this end, researchers have developed rs-fcMRI-based biomarkers and investigated a causal relationship between potential biomarkers and disease-specific behavior using functional MRI (fMRI)-based neurofeedback on functional connectivity. In this review, we introduce a recent approach for creating a theranostic biomarker, which consists mainly of 2 parts: (1) developing an rs-fcMRI-based biomarker that can predict diagnosis and/or symptoms with high accuracy, and (2) the introduction of a proof-of-concept study investigating the relationship between normalizing the biomarker and symptom changes using fMRI-based neurofeedback. In parallel with the introduction of recent studies, we review rs-fcMRI-based biomarker and fMRI-based neurofeedback, focusing on the technological improvements and limitations associated with clinical use.

Functional network integrity presages cognitive decline in preclinical Alzheimer disease.

To examine the utility of resting-state functional connectivity MRI (rs-fcMRI) measurements of network integrity as a predictor of future cognitive decline in preclinical Alzheimer disease (AD). A total of 237 clinically normal older adults (aged 63-90 years, Clinical Dementia Rating 0) underwent baseline β-amyloid (Aβ) imaging with Pittsburgh compound B PET and structural and rs-fcMRI. We identified 7 networks for analysis, including 4 cognitive networks (default, salience, dorsal attention, and frontoparietal control) and 3 noncognitive networks (primary visual, extrastriate visual, motor). Using linear and curvilinear mixed models, we used baseline connectivity in these networks to predict longitudinal changes in preclinical Alzheimer cognitive composite (PACC) performance, both alone and interacting with Aβ burden. Median neuropsychological follow-up was 3 years. Baseline connectivity in the default, salience, and control networks predicted longitudinal PACC decline, unlike connectivity in the dorsal attention and all noncognitive networks. Default, salience, and control network connectivity was also synergistic with Aβ burden in predicting decline, with combined higher Aβ and lower connectivity predicting the steepest curvilinear decline in PACC performance. In clinically normal older adults, lower functional connectivity predicted more rapid decline in PACC scores over time, particularly when coupled with increased Aβ burden. Among examined networks, default, salience, and control networks were the strongest predictors of rate of change in PACC scores, with the inflection point of greatest decline beyond the fourth year of follow-up. These results suggest that rs-fcMRI may be a useful predictor of early, AD-related cognitive decline in clinical research settings.

Multifocal tDCS targeting the resting state motor network increases cortical excitability beyond traditional tDCS targeting unilateral motor cortex

Scientists and clinicians have traditionally targeted single brain regions with stimulation to modulate brain function and disease. However, brain regions do not operate in isolation, but interact with other regions through networks. As such, stimulation of one region may impact and be impacted by other regions in its network. Here we test whether the effects of brain stimulation can be enhanced by simultaneously targeting a region and its network, identified with resting state functional connectivity MRI. Fifteen healthy participants received two types of transcranial direct current stimulation (tDCS): a traditional two-electrode montage targeting a single brain region (left primary motor cortex [M1]) and a novel eight-electrode montage targeting this region and its associated resting state network. As a control, 8 participants also received multifocal tDCS mismatched to this network. Network-targeted tDCS more than doubled the increase in left M1 excitability over time compared to traditional tDCS and the multifocal control. Modeling studies suggest these results are unlikely to be due to tDCS effects on left M1 itself, however it is impossible to completely exclude this possibility. It also remains unclear whether multifocal tDCS targeting a network selectively modulates this network and which regions within the network are most responsible for observed effects. Despite these limitations, network-targeted tDCS appears to be a promising approach for enhancing tDCS effects beyond traditional stimulation targeting a single brain region. Future work is needed to test whether these results extend to other resting state networks and enhance behavioral or therapeutic effects.

Test-retest reliability of prefrontal transcranial Direct Current Stimulation (tDCS) effects on functional MRI connectivity in healthy subjects

Transcranial Direct Current Stimulation (tDCS) of the prefrontal cortex (PFC) can be used for probing functional brain connectivity and meets general interest as novel therapeutic intervention in psychiatric and neurological disorders. Along with a more extensive use, it is important to understand the interplay between neural systems and stimulation protocols requiring basic methodological work. Here, we examined the test-retest (TRT) characteristics of tDCS-induced modulations in resting-state functional-connectivity MRI (RS fcMRI). Twenty healthy subjects received 20minutes of either active or sham tDCS of the dorsolateral PFC (2mA, anode over F3 and cathode over F4, international 10–20 system), preceded and ensued by a RS fcMRI (10minutes each). All subject underwent three tDCS sessions with one-week intervals in between. Effects of tDCS on RS fcMRI were determined at an individual as well as at a group level using both ROI-based and independent-component analyses (ICA). To evaluate the TRT reliability of individual active-tDCS and sham effects on RS fcMRI, voxel-wise intra-class correlation coefficients (ICC) of post-tDCS maps between testing sessions were calculated. For both approaches, results revealed low reliability of RS fcMRI after active tDCS (ICC(2,1) = −0.09 – 0.16). Reliability of RS fcMRI (baselines only) was low to moderate for ROI-derived (ICC(2,1) = 0.13 – 0.50) and low for ICA-derived connectivity (ICC(2,1) = 0.19 – 0.34). Thus, for ROI-based analyses, the distribution of voxel-wise ICC was shifted to lower TRT reliability after active, but not after sham tDCS, for which the distribution was similar to baseline. The intra-individual variation observed here resembles variability of tDCS effects in motor regions and may be one reason why in this study robust tDCS effects at a group level were missing. The data can be used for appropriately designing large scale studies investigating methodological issues such as sources of variability and localisation of tDCS effects.

Multimodal MR-imaging reveals large-scale structural and functional connectivity changes in profound early blindness.

In the setting of profound ocular blindness, numerous lines of evidence demonstrate the existence of dramatic anatomical and functional changes within the brain. However, previous studies based on a variety of distinct measures have often provided inconsistent findings. To help reconcile this issue, we used a multimodal magnetic resonance (MR)-based imaging approach to provide complementary structural and functional information regarding this neuroplastic reorganization. This included gray matter structural morphometry, high angular resolution diffusion imaging (HARDI) of white matter connectivity and integrity, and resting state functional connectivity MRI (rsfcMRI) analysis. When comparing the brains of early blind individuals to sighted controls, we found evidence of co-occurring decreases in cortical volume and cortical thickness within visual processing areas of the occipital and temporal cortices respectively. Increases in cortical volume in the early blind were evident within regions of parietal cortex. Investigating white matter connections using HARDI revealed patterns of increased and decreased connectivity when comparing both groups. In the blind, increased white matter connectivity (indexed by increased fiber number) was predominantly left-lateralized, including between frontal and temporal areas implicated with language processing. Decreases in structural connectivity were evident involving frontal and somatosensory regions as well as between occipital and cingulate cortices. Differences in white matter integrity (as indexed by quantitative anisotropy, or QA) were also in general agreement with observed pattern changes in the number of white matter fibers. Analysis of resting state sequences showed evidence of both increased and decreased functional connectivity in the blind compared to sighted controls. Specifically, increased connectivity was evident between temporal and inferior frontal areas. Decreases in functional connectivity were observed between occipital and frontal and somatosensory-motor areas and between temporal (mainly fusiform and parahippocampus) and parietal, frontal, and other temporal areas. Correlations in white matter connectivity and functional connectivity observed between early blind and sighted controls showed an overall high degree of association. However, comparing the relative changes in white matter and functional connectivity between early blind and sighted controls did not show a significant correlation. In summary, these findings provide complimentary evidence, as well as highlight potential contradictions, regarding the nature of regional and large scale neuroplastic reorganization resulting from early onset blindness.

Multiband multi-echo imaging of simultaneous oxygenation and flow timeseries for resting state connectivity.

A novel sequence has been introduced that combines multiband imaging with a multi-echo acquisition for simultaneous high spatial resolution pseudo-continuous arterial spin labeling (ASL) and blood-oxygenation-level dependent (BOLD) echo-planar imaging (MBME ASL/BOLD). Resting-state connectivity in healthy adult subjects was assessed using this sequence. Four echoes were acquired with a multiband acceleration of four, in order to increase spatial resolution, shorten repetition time, and reduce slice-timing effects on the ASL signal. In addition, by acquiring four echoes, advanced multi-echo independent component analysis (ME-ICA) denoising could be employed to increase the signal-to-noise ratio (SNR) and BOLD sensitivity. Seed-based and dual-regression approaches were utilized to analyze functional connectivity. Cerebral blood flow (CBF) and BOLD coupling was also evaluated by correlating the perfusion-weighted timeseries with the BOLD timeseries. These metrics were compared between single echo (E2), multi-echo combined (MEC), multi-echo combined and denoised (MECDN), and perfusion-weighted (PW) timeseries. Temporal SNR increased for the MECDN data compared to the MEC and E2 data. Connectivity also increased, in terms of correlation strength and network size, for the MECDN compared to the MEC and E2 datasets. CBF and BOLD coupling was increased in major resting-state networks, and that correlation was strongest for the MECDN datasets. These results indicate our novel MBME ASL/BOLD sequence, which collects simultaneous high-resolution ASL/BOLD data, could be a powerful tool for detecting functional connectivity and dynamic neurovascular coupling during the resting state. The collection of more than two echoes facilitates the use of ME-ICA denoising to greatly improve the quality of resting state functional connectivity MRI.

Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature

The development of human cognition results from the emergence of coordinated activity between distant brain areas. Network science, combined with non-invasive functional imaging, has generated unprecedented insights regarding the adult brain's functional organization, and promises to help elucidate the development of functional architectures supporting complex behavior. Here we review what is known about functional network development from birth until adulthood, particularly as understood through the use of resting-state functional connectivity MRI (rs-fcMRI). We attempt to synthesize rs-fcMRI findings with other functional imaging techniques, with macro-scale structural connectivity, and with knowledge regarding the development of micro-scale structure. We highlight a number of outstanding conceptual and technical barriers that need to be addressed, as well as previous developmental findings that may need to be revisited. Finally, we discuss key areas ripe for future research in order to (1) better characterize normative developmental trajectories, (2) link these trajectories to biologic mechanistic events, as well as component behaviors and (3) better understand the clinical implications and pathophysiological basis of aberrant network development.

GABAergic effect on resting-state functional connectivity: Dynamics under pharmacological antagonism

Resting state functional connectivity MRI measures synchronous activity among brain regions although the mechanisms governing the temporally coherent BOLD signals remain unclear. Recent studies suggest that γ-amino butyric acid (GABA) levels are correlated with functional connectivity. To understand whether changes in GABA transmission alter functional connectivity, we modulated the GABAergic activity by a GABAA receptor antagonist, bicuculline. Resting and evoked electrophysiology and BOLD signals were measured in isoflurane-anesthetized rats under infusion of low-dose bicuculline or vehicle individually. Both somatosensory BOLD activations and evoked potentials induced by forepaw stimulation were increased significantly under bicuculline compared to vehicle, indicating increased excitability. Gradually elevated resting BOLD correlation within and between the somatosensory and visual cortices, as well as between somatosensory and caudate putamen but not within subcortical areas were found with the infusion of bicuculline. Increased cerebral blood flow was observed throughout the cortical and subcortical areas where the receptor density is high, but it didn’t correlate with BOLD connectivity except in the primary somatosensory cortex. Furthermore, resting EEG coherence in the alpha and beta bands exhibited consistent change with the BOLD correlation. The increased cortico-cortical and cortico-striatal connectivity without dependence on the receptor distribution indicate that the functional connectivity may be mediated by long-range projection via the cortical and striatal GABAergic inter-neurons. Our results indicate an important role of the GABAergic system on neural and hemodynamic oscillations, which further supports the neuronal basis of functional connectivity MRI and its correlation with neurotransmission.

Multicenter stability of resting state fMRI in the detection of Alzheimer's disease and amnestic MCI

BackgroundIn monocentric studies, patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD) dementia exhibited alterations of functional cortical connectivity in resting-state functional MRI (rs-fMRI) analyses. Multicenter studies provide access to large sample sizes, but rs-fMRI may be particularly sensitive to multiscanner effects.MethodsWe used data from five centers of the “German resting-state initiative for diagnostic biomarkers” (psymri.org), comprising 367 cases, including AD patients, MCI patients and healthy older controls, to assess the influence of the distributed acquisition on the group effects. We calculated accuracy of group discrimination based on whole brain functional connectivity of the posterior cingulate cortex (PCC) using pooled samples as well as second-level analyses across site-specific group contrast maps.ResultsWe found decreased functional connectivity in AD patients vs. controls, including clusters in the precuneus, inferior parietal cortex, lateral temporal cortex and medial prefrontal cortex. MCI subjects showed spatially similar, but less pronounced, differences in PCC connectivity when compared to controls. Group discrimination accuracy for AD vs. controls (MCI vs. controls) in the test data was below 76% (72%) based on the pooled analysis, and even lower based on the second level analysis stratified according to scanner. Only a subset of quality measures was useful to detect relevant scanner effects.ConclusionsMulticenter rs-fMRI analysis needs to employ strict quality measures, including visual inspection of all the data, to avoid seriously confounded group effects. While pending further confirmation in biomarker stratified samples, these findings suggest that multicenter acquisition limits the use of rs-fMRI in AD and MCI diagnosis.

Diagnostic classification of unipolar depression based on resting-state functional connectivity MRI: effects of generalization to a diverse sample.

In small, selected samples, an approach combining resting-state functional connectivity MRI and multivariate pattern analysis has been able to successfully classify patients diagnosed with unipolar depression. Purposes of this investigation were to assess the generalizability of this approach to a large clinically more realistic sample and secondarily to assess the replicability of previously reported methodological feasibility in a more homogeneous subgroup with pronounced depressive symptoms. Two independent subsets were drawn from the depression and control cohorts of the BiDirect study, each with 180 patients with and 180 controls without depression. Functional connectivity either among regions covering the gray matter or selected regions with known alterations in depression was assessed by resting-state fMRI. Support vector machines with and without automated feature selection were used to train classifiers differentiating between individual patients and controls in the entire first subset as well as in the subgroup. Model parameters were explored systematically. The second independent subset was used for validation of successful models. Classification accuracies in the large, heterogeneous sample ranged from 45.0 to 56.1% (chance level 50.0%). In the subgroup with higher depression severity, three out of 90 models performed significantly above chance (60.8-61.7% at independent validation). In conclusion, common classification methods previously successful in small homogenous depression samples do not immediately translate to a more realistic population. Future research to develop diagnostic classification approaches in depression should focus on more specific clinical questions and consider heterogeneity, including symptom severity as an important factor.

Characterizing Variability of Modular Brain Connectivity with Constrained Principal Component Analysis.

Characterizing the variability of resting-state functional brain connectivity across subjects and/or over time has recently attracted much attention. Principal component analysis (PCA) serves as a fundamental statistical technique for such analyses. However, performing PCA on high-dimensional connectivity matrices yields complicated “eigenconnectivity” patterns, for which systematic interpretation is a challenging issue. Here, we overcome this issue with a novel constrained PCA method for connectivity matrices by extending the idea of the previously proposed orthogonal connectivity factorization method. Our new method, modular connectivity factorization (MCF), explicitly introduces the modularity of brain networks as a parametric constraint on eigenconnectivity matrices. In particular, MCF analyzes the variability in both intra- and inter-module connectivities, simultaneously finding network modules in a principled, data-driven manner. The parametric constraint provides a compact module-based visualization scheme with which the result can be intuitively interpreted. We develop an optimization algorithm to solve the constrained PCA problem and validate our method in simulation studies and with a resting-state functional connectivity MRI dataset of 986 subjects. The results show that the proposed MCF method successfully reveals the underlying modular eigenconnectivity patterns in more general situations and is a promising alternative to existing methods.

Suppression of the Hemodynamic Response Function Demonstrates Altered Cerebral Vasoreactivity in Sickle Cell Disease

Introduction: Children with sickle cell disease (SCD) face progressive cognitive decline compared to their unaffected siblings, even prior to the occurrence of stroke, suggesting damage to the underlying functional brain organization. Hence, functional MRI (fMRI) studies are needed to help characterize the pathophysiological basis of cognitive decline in SCD.Functional MRI techniques measure the blood oxygenation level dependent (BOLD) signal, which is sensitive to changes in the ratio of oxy- to deoxy-hemoglobin driven by local changes in neural activity. Regional brain activity raises local oxygen consumption that is overly compensated for by increases in local blood flow, bringing an excess of oxygenated blood and elevating the ratio of oxy- to deoxy-hemoglobin in the active brain regions. This stereotyped neurovascular coupling sequence unfolds over 20 seconds and gives rise to the canonical hemodynamic response function (HRF). Given the severe chronic anemia with attendant hypoxia, alterations in oxygen binding, increased cerebral blood flow (CBF), and prevalence of vasculopathy associated with SCD, careful comparison of the HRF between children with SCD and controls must occur prior to pursuing fMRI analyses.Children with SCD have increased CBF and oxygen extraction fraction at baseline when compared to controls, suggesting that they require these compensatory mechanisms to meet the brain's metabolic demands at rest, which could affect their ability to further increase blood flow in response to local neural activity. Thus, we hypothesized that children with SCD would have a blunted HRF with lower peak amplitudes when compared to sibling controls. To test our hypothesis, we conducted the gold-standard visual task-driven fMRI paradigm for measuring HRF in children with SCD and their siblings.Methods: Children with HbSS or HbS beta thalassemia null disease and healthy, sibling controls between the ages of 5 and 21 years were recruited from St. Louis Children's Hospital. Participants were excluded for history of overt stroke, vasculopathy, stem cell transplant or chronic exchange transfusion therapy. Participants completed a fMRI task that required them to press a button with their right index fingers at the onset of a 30 Hz counterphase-flickering checkerboard and to press a button with their left index finger at its offset. Nine time points (TR = 2.2 s) were included in the general linear model used to describe the HRF in response to each stimulus. No assumptions were made regarding the shape of the HRF. A peak-finding algorithm extracted regions of interest (ROI) from the group fMRI activation map. Activations were averaged across all voxels within each ROI to generate region-wise time courses for each participant. Results are reported as median [interquartile range], and comparisons are made using a Mann Whitney U test or Pearson chi-square test.Results: Fourteen children with SCD and 13 healthy sibling controls were included in the analysis. There was not a statistically significant difference in age (10.0 [9.8-15.5] years vs. 13.0 years [11.0-14.5]; p = 0.66) or gender (p = 0.31) between the SCD and control cohorts. Eighty-six percent of SCD participants were treated with hydroxyurea at a dose of 30.3 [28.6-33.1] mg/kg/day. The baseline hemoglobin of the SCD cohort was 8.8 [8.3-10.1] g/dL. Two children with SCD had a history of silent cerebral infarcts.The peak amplitude of the HRF in the primary visual cortex (V1) was significantly reduced in children with SCD (right: 0.29 [0.23-0.50]% and left: 0.29 [0.20-0.53]%) when compared to sibling controls (right: 0.56 [0.53-0.95]%, p < 0.001 and left: 0.52 [0.38-0.90]%, p = 0.01). While the HRF amplitude was reduced by almost 50%, there was no difference in the timing of the BOLD response (i.e. lag) between groups, both demonstrating a time-to-peak of 8.8 seconds (Figure).Conclusion: The striking decrease in HRF amplitude suggests that patients with SCD have altered cerebral vasoreactivity to neural stimuli. Further investigation into the pathophysiology behind and clinical implications of the blunted hemodynamic response in SCD is warranted. We are currently investigating the relationship between HRF suppression, cognitive outcomes and stroke risk in SCD, and the effects of HRF suppression on functional connectivity networks using resting-state functional connectivity MRI collected simultaneously in the same cohorts. [Display omitted] DisclosuresFields:NeuroPhage Pharmaceuticals: Equity Ownership, Membership on an entity's Board of Directors or advisory committees. King:NIH - BMTCTN: Research Funding; NIH - NHLBI: Research Funding; HRSA: Research Funding. Dosenbach:NeuroPhage Pharmaceuticals: Equity Ownership, Membership on an entity's Board of Directors or advisory committees.

Towards a consensus regarding global signal regression for resting state functional connectivity MRI

The number of resting state functional connectivity MRI studies continues to expand at a rapid rate along with the options for data processing. Of the processing options, few have generated as much controversy as global signal regression and the subsequent observation of negative correlations (anti-correlations). This debate has motivated new processing strategies and advancement in the field, but has also generated significant confusion and contradictory guidelines. In this article, we work towards a consensus regarding global signal regression. We highlight several points of agreement including the fact that there is not a single “right” way to process resting state data that reveals the “true” nature of the brain. Although further work is needed, different processing approaches likely reveal complementary insights about the brain's functional organisation.

A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy.

Resting-state functional connectivity MRI (rs-fcMRI) is a technique that identifies connectivity between different brain regions based on correlations over time in the blood-oxygenation level dependent signal. rs-fcMRI has been applied extensively to identify abnormalities in brain connectivity in different neurologic and psychiatric diseases. However, the relationship among rs-fcMRI connectivity abnormalities, brain electrophysiology and disease state is unknown, in part because the causal significance of alterations in functional connectivity in disease pathophysiology has not been established. Transcranial Magnetic Stimulation (TMS) is a technique that uses electromagnetic induction to noninvasively produce focal changes in cortical activity. When combined with electroencephalography (EEG), TMS can be used to assess the brain's response to external perturbations. Here we provide a protocol for combining rs-fcMRI, TMS and EEG to assess the physiologic significance of alterations in functional connectivity in patients with neuropsychiatric disease. We provide representative results from a previously published study in which rs-fcMRI was used to identify regions with abnormal connectivity in patients with epilepsy due to a malformation of cortical development, periventricular nodular heterotopia (PNH). Stimulation in patients with epilepsy resulted in abnormal TMS-evoked EEG activity relative to stimulation of the same sites in matched healthy control patients, with an abnormal increase in the late component of the TMS-evoked potential, consistent with cortical hyperexcitability. This abnormality was specific to regions with abnormal resting-state functional connectivity. Electrical source analysis in a subject with previously recorded seizures demonstrated that the origin of the abnormal TMS-evoked activity co-localized with the seizure-onset zone, suggesting the presence of an epileptogenic circuit. These results demonstrate how rs-fcMRI, TMS and EEG can be utilized together to identify and understand the physiological significance of abnormal brain connectivity in human diseases.