Periods of rest in fMRI contain individual spontaneous events which are related to slowly fluctuating spontaneous activity

fMRI studies of brain activity at rest study slow (<0.1 Hz) intrinsic fluctuations in the blood‐oxygenation‐level‐dependent (BOLD) signal that are observed in a temporal scale of several minutes. The origin of these fluctuations is not clear but has previously been associated with slow changes in rhythmic neuronal activity resulting from changes in cortical excitability or neuronal synchronization. In this work, we show that individual spontaneous BOLD events occur during rest, in addition to slow fluctuations. Individual spontaneous BOLD events were identified by deconvolving the hemodynamic impulse response function for each time point in the fMRI time series, thus requiring no information on timing or a‐priori spatial information of events. The patterns of activation detected were related to the motor, visual, default‐mode, and dorsal attention networks. The correspondence between spontaneous events and slow fluctuations in these networks was assessed using a sliding window, seed‐correlation analysis, where seed regions were selected based on the individual spontaneous event BOLD activity maps. We showed that the correlation varied considerably over time, peaking at the time of spontaneous events in these networks. By regressing spontaneous events out of the fMRI signal, we showed that both the correlation strength and the power in spectral frequencies <0.1 Hz decreased, indicating that spontaneous activation events contribute to low‐frequency fluctuations observed in resting state networks with fMRI. This work provides new insights into the origin of signals detected in fMRI studies of functional connectivity. Hum Brain Mapp, 2013. © 2012 Wiley Periodicals, Inc.     

Spatial heterogeneity of the relation between resting‐state connectivity and blood flow: An important consideration for pharmacological studies

Resting state fMRI (RSfMRI) and arterial spin labeling (ASL) provide the field of pharmacological Neuroimaging tool for investigating states of brain activity in terms of functional connectivity or cerebral blood flow (CBF). Functional connectivity reflects the degree of synchrony or correlation of spontaneous fluctuations—mostly in the blood oxygen level dependent (BOLD) signal—across brain networks; but CBF reflects mean delivery of arterial blood to the brain tissue over time. The BOLD and CBF signals are linked to common neurovascular and hemodynamic mechanisms that necessitate increased oxygen transportation to the site of neuronal activation; however, the scale and the sources of variation in static CBF and spatiotemporal BOLD correlations are likely different. We tested this hypothesis by examining the relation between CBF and resting‐state‐network consistency (RSNC)—representing average intranetwork connectivity, determined from dual regression analysis with eight standard networks of interest (NOIs)—in a crossover placebo‐controlled study of morphine and alcohol. Overall, we observed spatially heterogeneous relations between RSNC and CBF, and between the experimental factors (drug‐by‐time, time, drug and physiological rates) and each of these metrics. The drug‐by‐time effects on CBF were significant in all networks, but significant RSNC changes were limited to the sensorimotor, the executive/salience and the working memory networks. The post‐hoc voxel‐wise statistics revealed similar dissociations, perhaps suggesting differential sensitivity of RSNC and CBF to neuronal and vascular endpoints of drug actions. The spatial heterogeneity of RSNC/CBF relations encourages further investigation into the role of neuroreceptor distribution and cerebrovascular anatomy in predicting spontaneous fluctuations under drugs. Hum Brain Mapp 35:929–942, 2014. © 2012 Wiley Periodicals, Inc.     

Localized reductions in resting‐state functional connectivity in children with prenatal alcohol exposure

Fetal alcohol spectrum disorders (FASD) are characterized by impairment in cognitive function that may or may not be accompanied by craniofacial anomalies, microcephaly, and/or growth retardation. Resting‐state functional MRI (rs‐fMRI), which examines the low‐frequency component of the blood oxygen level dependent (BOLD) signal in the absence of an explicit task, provides an efficient and powerful mechanism for studying functional brain networks even in low‐functioning and young subjects. Studies using independent component analysis (ICA) have identified a set of resting‐state networks (RSNs) that have been linked to distinct domains of cognitive and perceptual function, which are believed to reflect the intrinsic functional architecture of the brain. This study is the first to examine resting‐state functional connectivity within these RSNs in FASD. Rs‐fMRI scans were performed on 38 children with FASD (19 with either full fetal alcohol syndrome (FAS) or partial FAS (PFAS), 19 nonsyndromal heavily exposed (HE)), and 19 controls, mean age 11.3 ± 0.9 years, from the Cape Town Longitudinal Cohort. Nine resting‐state networks were generated by ICA. Voxelwise group comparison between a combined FAS/PFAS group and controls revealed localized dose‐dependent functional connectivity reductions in five regions in separate networks: anterior default mode, salience, ventral and dorsal attention, and R executive control. The former three also showed lower connectivity in the HE group. Gray matter connectivity deficits in four of the five networks appear to be related to deficits in white matter tracts that provide intra‐RSN connections. Hum Brain Mapp 38:5217–5233, 2017. © 2017 Wiley Periodicals, Inc.     

The effects of methylphenidate on whole brain intrinsic functional connectivity

Methylphenidate (MPH) is an indirect dopaminergic and noradrenergic agonist that is used to treat attention deficit hyperactivity disorder and that has shown therapeutic potential in neuropsychiatric diseases such as depression, dementia, and Parkinson's disease. While effects of MPH on task‐induced brain activation have been investigated, little is known about how MPH influences the resting brain. To investigate the effects of 40 mg of oral MPH on intrinsic functional connectivity, we used resting state fMRI in 54 healthy male subjects in a double‐blind, randomized, placebo‐controlled study. Functional connectivity analysis employing ICA revealed seven resting state networks (RSN) of interest. Connectivity strength between the dorsal attention network and the thalamus was increased after MPH intake. Other RSN located in association cortex areas, such as the left and right frontoparietal networks and the executive control network, showed MPH‐induced connectivity increase to sensory‐motor and visual cortex regions and connectivity decrease to cortical and subcortical components of cortico‐striato‐thalamo‐cortical circuits (CST). RSN located in sensory‐motor cortex areas showed the opposite pattern with MPH‐induced connectivity increase to CST components and connectivity decrease to sensory‐motor and visual cortex regions. Our results provide evidence that MPH does not only alter intrinsic connectivity between brain areas involved in sustained attention, but that it also induces significant changes in the cortico‐cortical and cortico‐subcortical connectivity of many other cognitive and sensory‐motor RSN. Hum Brain Mapp 35:5379–5388, 2014. © 2014 Wiley Periodicals, Inc.     

Brain dynamics of post‐task resting state are influenced by expertise: Insights from baseball players

Post‐task resting state dynamics can be viewed as a task‐driven state where behavioral performance is improved through endogenous, non‐explicit learning. Tasks that have intrinsic value for individuals are hypothesized to produce post‐task resting state dynamics that promote learning. We measured simultaneous fMRI/EEG and DTI in Division‐1 collegiate baseball players and compared to a group of controls, examining differences in both functional and structural connectivity. Participants performed a surrogate baseball pitch Go/No‐Go task before a resting state scan, and we compared post‐task resting state connectivity using a seed‐based analysis from the supplementary motor area (SMA), an area whose activity discriminated players and controls in our previous results using this task. Although both groups were equally trained on the task, the experts showed differential activity in their post‐task resting state consistent with motor learning. Specifically, we found (1) differences in bilateral SMA–L Insula functional connectivity between experts and controls that may reflect group differences in motor learning, (2) differences in BOLD‐alpha oscillation correlations between groups suggests variability in modulatory attention in the post‐task state, and (3) group differences between BOLD‐beta oscillations that may indicate cognitive processing of motor inhibition. Structural connectivity analysis identified group differences in portions of the functionally derived network, suggesting that functional differences may also partially arise from variability in the underlying white matter pathways. Generally, we find that brain dynamics in the post‐task resting state differ as a function of subject expertise and potentially result from differences in both functional and structural connectivity. Hum Brain Mapp 37:4454–4471, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.     

Realistic models of apparent dynamic changes in resting‐state connectivity in somatosensory cortex

Variations over time in resting‐state correlations in blood oxygenation level‐dependent (BOLD) signals from different cortical areas may indicate changes in brain functional connectivity. However, apparent variations over time may also arise from stationary signals when the sample duration is finite. Recently, a vector autoregressive (VAR) null model has been proposed to simulate real functional magnetic resonance imaging (fMRI) data, which provides a robust stationary model for identifying possible temporal dynamic changes in functional connectivity. In this work, we propose a simpler model that uses a filtered stationary dataset. The filtered stationary model generates statistically stationary time series from random data with a single prescribed correlation coefficient that is calculated as the average over the entire time series. In addition, we propose a dynamic model, which is better able to replicate real fMRI connectivity, estimated from monkey brain studies, than the two stationary models. We compare simulated results using these three models with the behavior of primary somatosensory cortex (S1) networks in anesthetized squirrel monkeys at high field (9.4 T), using a sliding window correlation analysis. We found that at short window sizes, both stationary models reproduced the distribution of correlations of real signals well, but at longer window sizes, a dynamic model reproduced the distribution of correlations of real signals better than the stationary models. While stationary models replicate several features of real data, a close representation of the behavior of resting‐state data acquired from somatosensory cortex of non‐human primates is obtained only when a dynamic correlation is introduced, suggesting dynamic variations in connectivity are real. Hum Brain Mapp 37:3897–3910, 2016. © 2016 Wiley Periodicals, Inc .     

Altered amygdalar resting‐state connectivity in depression is explained by both genes and environment

Recent findings indicate that alterations of the amygdalar resting‐state fMRI connectivity play an important role in the etiology of depression. While both depression and resting‐state brain activity are shaped by genes and environment, the relative contribution of genetic and environmental factors mediating the relationship between amygdalar resting‐state connectivity and depression remain largely unexplored. Likewise, novel neuroimaging research indicates that different mathematical representations of resting‐state fMRI activity patterns are able to embed distinct information relevant to brain health and disease. The present study analyzed the influence of genes and environment on amygdalar resting‐state fMRI connectivity, in relation to depression risk. High‐resolution resting‐state fMRI scans were analyzed to estimate functional connectivity patterns in a sample of 48 twins (24 monozygotic pairs) informative for depressive psychopathology (6 concordant, 8 discordant and 10 healthy control pairs). A graph‐theoretical framework was employed to construct brain networks using two methods: (i) the conventional approach of filtered BOLD fMRI time‐series and (ii) analytic components of this fMRI activity. Results using both methods indicate that depression risk is increased by environmental factors altering amygdalar connectivity. When analyzing the analytic components of the BOLD fMRI time‐series, genetic factors altering the amygdala neural activity at rest show an important contribution to depression risk. Overall, these findings show that both genes and environment modify different patterns the amygdala resting‐state connectivity to increase depression risk. The genetic relationship between amygdalar connectivity and depression may be better elicited by examining analytic components of the brain resting‐state BOLD fMRI signals. Hum Brain Mapp 36:3761–3776, 2015. © 2015 Wiley Periodicals, Inc.     

Altered resting‐state connectivity in Huntington's Disease

Huntington's disease (HD) is an autosomal dominantly inherited neurodegenerative disorder characterized by motor, cognitive, and psychiatric symptoms. Using resting‐state fMRI (rs‐fMRI) we investigated the functional integrity of resting‐state networks (RSN) in HD. 17 HD and 19 matched control participants were examined at a 3 Tesla MR scanner. After controlling for structural degeneration by means of voxel‐based morphometry, task‐free rs‐fMRI data were analyzed using Independent Component Analysis (ICA) and a dual‐regression approach in the context of genetic and clinical parameters. Further, we evaluated HD‐related differences in interregional connectivity between networks. RSN analysis showed a significant increase in intrinsic functional connectivity in the HD sample compared with controls, including the thalamus, striatum, prefrontal, premotor, and parietal maps. A subset of the Default Mode Network (DMN) was also affected. In the HD cohort, motor impairment correlated with higher network connectivity in mainly motor and parietal cortices. Deteriorating total functional capacity was additionally associated with higher connectivity in the striatum, thalamus, insular and frontal areas. This pattern of increased activity in intrinsic functional networks might suggest a reduced ability of intra‐network differentiation with clinical disease progression in HD. Finally, results showed reduced long‐range connectivity between parietal ICA components in HD compared to controls, indicating impaired functional coupling between interregional networks in HD. Our data demonstrates that functional connectivity is profoundly altered in HD, both within and between RSN. Rs‐fMRI analysis may provide additional valuable insights into neuronal dysfunctions beyond HD‐related structural degeneration and disruptions of functional circuits in HD. Hum Brain Mapp 35:2582–2593, 2014. © 2013 Wiley Periodicals, Inc .     

Default‐mode network functional connectivity is closely related to metabolic activity

Over the last decade, the brain's default‐mode network (DMN) and its function has attracted a lot of attention in the field of neuroscience. However, the exact underlying mechanisms of DMN functional connectivity, or more specifically, the blood‐oxygen level‐dependent (BOLD) signal, are still incompletely understood. In the present study, we combined 2‐deoxy‐2‐[¹⁸F]fluoroglucose positron emission tomography (FDG‐PET), proton magnetic resonance spectroscopy (¹H‐MRS), and resting‐state functional magnetic resonance imaging (rs‐fMRI) to investigate more directly the association between local glucose consumption, local glutamatergic neurotransmission and DMN functional connectivity during rest. The results of the correlation analyzes using the dorsal posterior cingulate cortex (dPCC) as seed region showed spatial similarities between fluctuations in FDG‐uptake and fluctuations in BOLD signal. More specifically, in both modalities the same DMN areas in the inferior parietal lobe, angular gyrus, precuneus, middle, and medial frontal gyrus were positively correlated with the dPCC. Furthermore, we could demonstrate that local glucose consumption in the medial frontal gyrus, PCC and left angular gyrus was associated with functional connectivity within the DMN. We did not, however, find a relationship between glutamatergic neurotransmission and functional connectivity. In line with very recent findings, our results lend further support for a close association between local metabolic activity and functional connectivity and provide further insights towards a better understanding of the underlying mechanism of the BOLD signal. Hum Brain Mapp 36:2027–2038, 2015. © 2015 Wiley Periodicals, Inc.     

Oscillations,networks, and their development: MEG connectivity changes with age

Magnetoencephalographic (MEG) investigations of inter‐regional amplitude correlations have yielded new insights into the organization and neurophysiology of resting‐state networks (RSNs) first identified using fMRI. Inter‐regional MEG amplitude correlations in adult RSNs have been shown to be most prominent in alpha and beta frequency ranges and to express strong congruence with RSN topologies found using fMRI. Despite such advances, little is known about how oscillatory connectivity in RSNs develops throughout childhood and adolescence. This study used a novel fMRI‐guided MEG approach to investigate the maturation of resting‐state amplitude correlations in physiologically relevant frequency ranges within and among six RSNs in 59 participants, aged 6–34 years. We report age‐related increases in inter‐regional amplitude correlations that were largest in alpha and beta frequency bands. In contrast to fMRI reports, these changes were observed both within and between the various RSNs analyzed. Our results provide the first evidence of developmental changes in spontaneous neurophysiological connectivity in source‐resolved RSNs, which indicate increasing integration within and among intrinsic functional brain networks throughout childhood, adolescence, and early adulthood. Hum Brain Mapp 35:5249–5261, 2014. © 2014 Wiley Periodicals, Inc .     

Functional segmentation of the brain cortex using high model order group PICA

Baseline activity of resting state brain networks (RSN) in a resting subject has become one of the fastest growing research topics in neuroimaging. It has been shown that up to 12 RSNs can be differentiated using an independent component analysis (ICA) of the blood oxygen level dependent (BOLD) resting state data. In this study, we investigate how many RSN signal sources can be separated from the entire brain cortex using high dimension ICA analysis from a group dataset. Group data from 55 subjects was analyzed using temporal concatenation and a probabilistic independent component analysis algorithm. ICA repeatability testing verified that 60 of the 70 computed components were robustly detectable. Forty‐two independent signal sources were identifiable as RSN, and 28 were related to artifacts or other noninterest sources (non‐RSN). The depicted RSNs bore a closer match to functional neuroanatomy than the previously reported RSN components. The non‐RSN sources have significantly lower temporal intersource connectivity than the RSN (P < 0.0003). We conclude that the high model order ICA of the group BOLD data enables functional segmentation of the brain cortex. The method enables new approaches to causality and connectivity analysis with more specific anatomical details. Hum Brain Mapp, 2009. © 2009 Wiley‐Liss, Inc.     

The resting‐state neurovascular coupling relationship: rapid changes in spontaneous neural activity in the somatosensory cortex are associated with haemodynamic fluctuations that resemble stimulus‐evoked haemodynamics

Although promise exists for patterns of resting‐state blood oxygen level‐dependent (BOLD) functional magnetic resonance imaging (fMRI) brain connectivity to be used as biomarkers of early brain pathology, a full understanding of the nature of the relationship between neural activity and spontaneous fMRI BOLD fluctuations is required before such data can be correctly interpreted. To investigate this issue, we combined electrophysiological recordings of rapid changes in multi‐laminar local field potentials from the somatosensory cortex of anaesthetized rats with concurrent two‐dimensional optical imaging spectroscopy measurements of resting‐state haemodynamics that underlie fluctuations in the BOLD fMRI signal. After neural ‘events’ were identified, their time points served to indicate the start of an epoch in the accompanying haemodynamic fluctuations. Multiple epochs for both neural ‘events’ and the accompanying haemodynamic fluctuations were averaged. We found that the averaged epochs of resting‐state haemodynamic fluctuations taken after neural ‘events’ closely resembled the temporal profile of stimulus‐evoked cortical haemodynamics. Furthermore, we were able to demonstrate that averaged epochs of resting‐state haemodynamic fluctuations resembling the temporal profile of stimulus‐evoked haemodynamics could also be found after peaks in neural activity filtered into specific electroencephalographic frequency bands (theta, alpha, beta, and gamma). This technique allows investigation of resting‐state neurovascular coupling using methodologies that are directly comparable to that developed for investigating stimulus‐evoked neurovascular responses.     

Dual‐echo ASL contributes to decrypting the link between functional connectivity and cerebral blow flow

Arterial spin labeling (ASL) MRI with a dual‐echo readout module (DE‐ASL) enables noninvasive simultaneous acquisition of cerebral blood flow (CBF)‐weighted images and blood oxygenation level dependent (BOLD) contrast. Up to date, resting‐state functional connectivity (FC) studies based on CBF fluctuations have been very limited, while the BOLD is still the method most frequently used. The purposes of this technical report were (i) to assess the potentiality of the DE‐ASL sequence for the quantification of resting‐state FC and brain organization, with respect to the conventional BOLD (cvBOLD) and (ii) to investigate the relationship between a series of complex network measures and the CBF information. Thirteen volunteers were scanned on a 3 T scanner acquiring a pseudocontinuous multislice DE‐ASL sequence, from which the concomitant BOLD (ccBOLD) simultaneously to the ASL can be extracted. In the proposed comparison, the brain FC and graph‐theoretical analysis were used for quantifying the connectivity strength between pairs of regions and for assessing the network model properties in all the sequences. The main finding was that the ccBOLD part of the DE‐ASL sequence provided highly comparable connectivity results compared to cvBOLD. As expected, because of its different nature, ASL sequence showed different patterns of brain connectivity and graph indices compared to BOLD sequences. To conclude, the resting‐state FC can be reliably detected using DE‐ASL, simultaneously to CBF quantifications, whereas a single fMRI experiment precludes the quantitative measurement of BOLD signal changes. Hum Brain Mapp 38:5831–5844, 2017. © 2017 Wiley Periodicals, Inc.     

Loss of frontal regulator of vigilance during sleep inertia: A simultaneous EEG‐fMRI study

Sleep inertia refers to a distinct physiological state of waking up from sleep accompanied by performance impairments and sleepiness. The neural substrates of sleep inertia are unknown, but growing evidence suggests that this inertia state maintains certain sleep features. To investigate the neurophysiological mechanisms of sleep inertia, a comparison of pre‐sleep and post‐sleep wakefulness with eyes‐open resting‐state was performed using simultaneous EEG‐fMRI, which has the potential to reveal the dynamic details of neuroelectric and hemodynamic responses with high temporal resolution. Our data suggested sleep‐like features of slow EEG power and decreased BOLD activity were persistent during sleep inertia. In the pre‐sleep phase, participants with stronger EEG vigilance showed stronger activity in the fronto‐parietal network (FPN), but this phenomenon disappeared during sleep inertia. A time course analysis confirmed a decreased correlation between EEG vigilance and the FPN activity during sleep inertia. This simultaneous EEG‐fMRI study advanced our understanding of sleep inertia and revealed the importance of the FPN in maintaining awareness. This is the first study to reveal the dynamic brain network changes from multi‐modalities perspective during sleep inertia.     

Neuronal correlates of spontaneous fluctuations in fMRI signals in monkey visual cortex: Implications for functional connectivity at rest

Recent studies have demonstrated large amplitude spontaneous fluctuations in functional-MRI (fMRI) signals in humans in the resting state. Importantly, these spontaneous fluctuations in blood-oxygenation-level-dependent (BOLD) signal are often synchronized over distant parts of the brain, a phenomenon termed functional-connectivity. Functional-connectivity is widely assumed to reflect interregional coherence of fluctuations in activity of the underlying neuronal networks. Despite the large body of human imaging literature on spontaneous activity and functional-connectivity in the resting state, the link to underlying neural activity remains tenuous. Through simultaneous fMRI and intracortical neurophysiological recording, we demonstrate correlation between slow fluctuations in BOLD signals and concurrent fluctuations in the underlying locally measured neuronal activity. This correlation varied with time-lag of BOLD relative to neuronal activity, resembling a traditional hemodynamic response function with peaks at approximately 6 s lag of BOLD signal. The correlations were reliably detected when the neuronal signal consisted of either the spiking rate of a small group of neurons, or relative power changes in the multi-unit activity band, and particularly in the local field potential gamma band. Analysis of correlation between the voxel-by-voxel fMRI time-series and the neuronal activity measured within one cortical site showed patterns of correlation that slowly traversed cortex. BOLD fluctuations in widespread areas in visual cortex of both hemispheres were significantly correlated with neuronal activity from a single recording site in V1. To the extent that our V1 findings can be generalized to other cortical areas, fMRI-based functional-connectivity between remote regions in the resting state can be linked to synchronization of slow fluctuations in the underlying neuronal signals.     

The association between resting‐state functional magnetic resonance imaging and aortic pulse‐wave velocity in healthy adults

Resting‐state functional magnetic resonance imaging (rs‐fMRI) is frequently used to study brain function; but, it is unclear whether BOLD‐signal fluctuation amplitude and functional connectivity are associated with vascular factors, and how vascular‐health factors are reflected in rs‐fMRI metrics in the healthy population. As arterial stiffening is a known age‐related cardiovascular risk factor, we investigated the associations between aortic stiffening (as measured using pulse‐wave velocity [PWV]) and rs‐fMRI metrics. We used cardiac MRI to measure aortic PWV (an established indicator of whole‐body vascular stiffness), as well as dual‐echo pseudo‐continuous arterial‐spin labeling to measure BOLD and CBF dynamics simultaneously in a group of generally healthy adults. We found that: (1) higher aortic PWV is associated with lower variance in the resting‐state BOLD signal; (2) higher PWV is also associated with lower BOLD‐based resting‐state functional connectivity; (3) regions showing lower connectivity do not fully overlap with those showing lower BOLD variance with higher PWV; (4) CBF signal variance is a significant mediator of the above findings, only when averaged across regions‐of‐interest. Furthermore, we found no significant association between BOLD signal variance and systolic blood pressure, which is also a known predictor of vascular stiffness. Age‐related vascular stiffness, as measured by PWV, provides a unique scenario to demonstrate the extent of vascular bias in rs‐fMRI signal fluctuations and functional connectivity. These findings suggest that a substantial portion of age‐related rs‐fMRI differences may be driven by vascular effects rather than directly by brain function.     

Resting‐state functional connectivity and motor imagery brain activation

Motor imagery (MI) relies on the mental simulation of an action without any overt motor execution (ME), and can facilitate motor learning and enhance the effect of rehabilitation in patients with neurological conditions. While functional magnetic resonance imaging (fMRI) during MI and ME reveals shared cortical representations, the role and functional relevance of the resting‐state functional connectivity (RSFC) of brain regions involved in MI is yet unknown. Here, we performed resting‐state fMRI followed by fMRI during ME and MI with the dominant hand. We used a behavioral chronometry test to measure ME and MI movement duration and compute an index of performance (IP). Then, we analyzed the voxel‐matched correlation between the individual MI parameter estimates and seed‐based RSFC maps in the MI network to measure the correspondence between RSFC and MI fMRI activation. We found that inter‐individual differences in intrinsic connectivity in the MI network predicted several clusters of activation. Taken together, present findings provide first evidence that RSFC within the MI network is predictive of the activation of MI brain regions, including those associated with behavioral performance, thus suggesting a role for RSFC in obtaining a deeper understanding of neural substrates of MI and of MI ability. Hum Brain Mapp 37:3847–3857, 2016. © 2016 Wiley Periodicals, Inc.     

Functional connectivity in the default network during resting state is preserved in a vegetative but not in a brain dead patient

Recent studies on spontaneous fluctuations in the functional MRI blood oxygen level‐dependent (BOLD) signal in awake healthy subjects showed the presence of coherent fluctuations among functionally defined neuroanatomical networks. However, the functional significance of these spontaneous BOLD fluctuations remains poorly understood. By means of 3 T functional MRI, we demonstrate absent cortico‐thalamic BOLD functional connectivity (i.e. between posterior cingulate/precuneal cortex and medial thalamus), but preserved cortico‐cortical connectivity within the default network in a case of vegetative state (VS) studied 2.5 years following cardio‐respiratory arrest, as documented by extensive behavioral and paraclinical assessments. In the VS patient, as in age‐matched controls, anticorrelations could also be observed between posterior cingulate/precuneus and a previously identified task‐positive cortical network. Both correlations and anticorrelations were significantly reduced in VS as compared to controls. A similar approach in a brain dead patient did not show any such long‐distance functional connectivity. We conclude that some slow coherent BOLD fluctuations previously identified in healthy awake human brain can be found in alive but unaware patients, and are thus unlikely to be uniquely due to ongoing modifications of conscious thoughts. Future studies are needed to give a full characterization of default network connectivity in the VS patients population. Hum Brain Mapp, 2009. © 2009 Wiley‐Liss, Inc.     

Comparison of continuously acquired resting state and extracted analogues from active tasks

Functional connectivity analysis of brain networks has become an important tool for investigation of human brain function. Although functional connectivity computations are usually based on resting‐state data, the application to task‐specific fMRI has received growing attention. Three major methods for extraction of resting‐state data from task‐related signal have been proposed (1) usage of unmanipulated task data for functional connectivity; (2) regression against task effects, subsequently using the residuals; and (3) concatenation of baseline blocks located in‐between task blocks. Despite widespread application in current research, consensus on which method best resembles resting‐state seems to be missing. We, therefore, evaluated these techniques in a sample of 26 healthy controls measured at 7 Tesla. In addition to continuous resting‐state, two different task paradigms were assessed (emotion discrimination and right finger‐tapping) and five well‐described networks were analyzed (default mode, thalamus, cuneus, sensorimotor, and auditory). Investigating the similarity to continuous resting‐state (Dice, Intraclass correlation coefficient (ICC), R²) showed that regression against task effects yields functional connectivity networks most alike to resting‐state. However, all methods exhibited significant differences when compared to continuous resting‐state and similarity metrics were lower than test‐retest of two resting‐state scans. Omitting global signal regression did not change these findings. Visually, the networks are highly similar, but through further investigation marked differences can be found. Therefore, our data does not support referring to resting‐state when extracting signals from task designs, although functional connectivity computed from task‐specific data may indeed yield interesting information. Hum Brain Mapp 36:4053–4063, 2015. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.     

Altered functional connectivity in early Alzheimer's disease: a resting-state fMRI study

Previous studies have led to the proposal that patients with Alzheimer's disease (AD) may have disturbed functional connectivity between different brain regions. Furthermore, recent resting-state functional magnetic resonance imaging (fMRI) studies have also shown that low-frequency (<0.08 Hz) fluctuations (LFF) of the blood oxygenation level-dependent signals were abnormal in several brain areas of AD patients. However, few studies have investigated disturbed LFF connectivity in AD patients. By using resting-state fMRI, this study sought to investigate the abnormal functional connectivities throughout the entire brain of early AD patients, and analyze the global distribution of these abnormalities. For this purpose, the authors divided the whole brain into 116 regions and identified abnormal connectivities by comparing the correlation coefficients of each pair. Compared with healthy controls, AD patients had decreased positive correlations between the prefrontal and parietal lobes, but increased positive correlations within the prefrontal lobe, parietal lobe, and occipital lobe. The AD patients also had decreased negative correlations (closer to zero) between two intrinsically anti-correlated networks that had previously been found in the resting brain. By using resting-state fMRI, our results supported previous studies that have reported an anterior-posterior disconnection phenomenon and increased within-lobe functional connectivity in AD patients. In addition, the results also suggest that AD may disturb the correlation/anti-correlation effect in the two intrinsically anti-correlated networks.