Anish Mitra

Methods to detect, characterize, and remove motion artifact in resting state fMRI

Head motion systematically alters correlations in resting state functional connectivity fMRI (RSFC). In this report we examine impact of motion on signal intensity and RSFC correlations. We find that motion-induced signal changes (1) are often complex and variable waveforms, (2) are often shared across nearly all brain voxels, and (3) often persist more than 10s after motion ceases. These signal changes, both during and after motion, increase observed RSFC correlations in a distance-dependent manner. Motion-related signal changes are not removed by a variety of motion-based regressors, but are effectively reduced by global signal regression. We link several measures of data quality to motion, changes in signal intensity, and changes in RSFC correlations. We demonstrate that improvements in data quality measures during processing may represent cosmetic improvements rather than true correction of the data. We demonstrate a within-subject, censoring-based artifact removal strategy based on volume censoring that reduces group differences due to motion to chance levels. We note conditions under which group-level regressions do and do not correct motion-related effects.

Lag structure in resting-state fMRI

The discovery that spontaneous fluctuations in blood oxygen level-dependent (BOLD) signals contain information about the functional organization of the brain has caused a paradigm shift in neuroimaging. It is now well established that intrinsic brain activity is organized into spatially segregated resting-state networks (RSNs). Less is known regarding how spatially segregated networks are integrated by the propagation of intrinsic activity over time. To explore this question, we examined the latency structure of spontaneous fluctuations in the fMRI BOLD signal. Our data reveal that intrinsic activity propagates through and across networks on a timescale of ∼1 s. Variations in the latency structure of this activity resulting from sensory state manipulation (eyes open vs. closed), antecedent motor task (button press) performance, and time of day (morning vs. evening) suggest that BOLD signal lags reflect neuronal processes rather than hemodynamic delay. Our results emphasize the importance of the temporal structure of the brains spontaneous activity.

Lag threads organize the brain’s intrinsic activity

Significance It is well known that slow intrinsic activity, as measured by resting-state fMRI in a variety of animals including humans, is organized into temporally synchronous networks. The question of whether intrinsic activity contains reproducible temporal sequences has received far less attention. We have previously shown that human resting-state fMRI contains a highly reproducible lag structure. Here, we demonstrate that this lag structure is of high dimensionality and consists of multiple highly reproducible temporal sequences, which we term “lag threads.” Moreover, we demonstrate that the well-known zero-lag temporal correlation structure of intrinsic activity emerges as a consequence of lag structure. Thus, lag threads may represent a fundamental and previously unsuspected level of organization in resting-state activity. It has been widely reported that intrinsic brain activity, in a variety of animals including humans, is spatiotemporally structured. Specifically, propagated slow activity has been repeatedly demonstrated in animals. In human resting-state fMRI, spontaneous activity has been understood predominantly in terms of zero-lag temporal synchrony within widely distributed functional systems (resting-state networks). Here, we use resting-state fMRI from 1,376 normal, young adults to demonstrate that multiple, highly reproducible, temporal sequences of propagated activity, which we term “lag threads,” are present in the brain. Moreover, this propagated activity is largely unidirectional within conventionally understood resting-state networks. Modeling experiments show that resting-state networks naturally emerge as a consequence of shared patterns of propagation. An implication of these results is that common physiologic mechanisms may underlie spontaneous activity as imaged with fMRI in humans and slowly propagated activity as studied in animals.

Resting-State Network Complexity and Magnitude Are Reduced in Prematurely Born Infants

Premature birth is associated with high rates of motor and cognitive disability. Investigations have described resting-state functional magnetic resonance imaging (rs-fMRI) correlates of prematurity in older children, but comparable data in the neonatal period remain scarce. We studied 25 term-born control infants within the first week of life and 25 very preterm infants (born at gestational ages ranging from 23 to 29 weeks) without evident structural injury at term equivalent postmenstrual age. Conventional resting-state network (RSN) mapping revealed only modest differences between the term and prematurely born infants, in accordance with previous work. However, clear group differences were observed in quantitative analyses based on correlation and covariance matrices representing the functional MRI time series extracted from 31 regions of interest in 7 RSNs. In addition, the maximum likelihood dimensionality estimates of the group-averaged covariance matrices in the term and preterm infants were 5 and 3, respectively, indicating that prematurity leads to a reduction in the complexity of rs-fMRI covariance structure. These findings highlight the importance of quantitative analyses of rs-fMRI data and suggest a more sensitive method for delineating the effects of preterm birth in infants without evident structural injury.

Resting-state Functional Magnetic Resonance Imaging Correlates of Sevoflurane-induced Unconsciousness

Background:Blood oxygen level–dependent (BOLD) functional magnetic resonance imaging (fMRI) has been used to study the effects of anesthetic agents on correlated intrinsic neural activity. Previous studies have focused primarily on intravenous agents. The authors studied the effects of sevoflurane, an inhaled anesthetic. Methods:Resting-state BOLD fMRI was acquired from 10 subjects before sedation and from 9 subjects rendered unresponsive by 1.2% sevoflurane. The fMRI data were analyzed taking particular care to minimize the impact of artifact generated by head motion. Results:BOLD correlations were specifically weaker within the default mode network and ventral attention network during sevoflurane-induced unconsciousness, especially between anterior and posterior midline regions. Reduced functional connectivity between these same networks and the thalamus was also spatially localized to the midline frontal regions. The amplitude of BOLD signal fluctuations was substantially reduced across all brain regions. The importance of censoring epochs contaminated by head motion was demonstrated by comparative analyses. Conclusions:Sevoflurane-induced unconsciousness is associated with both globally reduced BOLD signal amplitudes and selectively reduced functional connectivity within cortical networks associated with consciousness (default mode network) and orienting to salient external stimuli (ventral attention network). Scrupulous attention to minimizing the impact of head motion artifact is critical in fMRI studies using anesthetic agents.

On the existence of a generalized non-specific task-dependent network

In this paper we suggest the existence of a generalized task-related cortical network that is up-regulated whenever the task to be performed requires the allocation of generalized non-specific cognitive resources, independent of the specifics of the task to be performed. We have labeled this general purpose network, the extrinsic mode network (EMN) as complementary to the default mode network (DMN), such that the EMN is down-regulated during periods of task-absence, when the DMN is up-regulated, and vice versa. We conceptualize the EMN as a cortical network for extrinsic neuronal activity, similar to the DMN as being a cortical network for intrinsic neuronal activity. The EMN has essentially a fronto-temporo-parietal spatial distribution, including the inferior and middle frontal gyri, inferior parietal lobule, supplementary motor area, inferior temporal gyrus. We hypothesize that this network is always active regardless of the cognitive task being performed. We further suggest that failure of network up- and down-regulation dynamics may provide neuronal underpinnings for cognitive impairments seen in many mental disorders, such as, e.g., schizophrenia. We start by describing a common observation in functional imaging, the close overlap in fronto-parietal activations in healthy individuals to tasks that denote very different cognitive processes. We now suggest that this is because the brain utilizes the EMN network as a generalized response to tasks that exceeds a cognitive demand threshold and/or requires the processing of novel information. We further discuss how the EMN is related to the DMN, and how a network for extrinsic activity is related to a network for intrinsic activity. Finally, we discuss whether the EMN and DMN networks interact in a common single brain system, rather than being two separate and independent brain systems.

Unmasking Language Lateralization in Human Brain Intrinsic Activity

Lateralization of function is a fundamental feature of the human brain as exemplified by the left hemisphere dominance of language. Despite the prominence of lateralization in the lesion, split-brain and task-based fMRI literature, surprisingly little asymmetry has been revealed in the increasingly popular functional imaging studies of spontaneous fluctuations in the fMRI BOLD signal (so-called resting-state fMRI). Here, we show the global signal, an often discarded component of the BOLD signal in resting-state studies, reveals a leftward asymmetry that maps onto regions preferential for semantic processing in left frontal and temporal cortex and the right cerebellum and a rightward asymmetry that maps onto putative attention-related regions in right frontal, temporoparietal, and parietal cortex. Hemispheric asymmetries in the global signal resulted from amplitude modulation of the spontaneous fluctuations. To confirm these findings obtained from normal, healthy, right-handed subjects in the resting-state, we had them perform 2 semantic processing tasks: synonym and numerical magnitude judgment and sentence comprehension. In addition to establishing a new technique for studying lateralization through functional imaging of the resting-state, our findings shed new light on the physiology of the global brain signal.

Propagated infra-slow intrinsic brain activity reorganizes across wake and slow wave sleep.

Propagation of slow intrinsic brain activity has been widely observed in electrophysiogical studies of slow wave sleep (SWS). However, in human resting state fMRI (rs-fMRI), intrinsic activity has been understood predominantly in terms of zero-lag temporal synchrony (functional connectivity) within systems known as resting state networks (RSNs). Prior rs-fMRI studies have found that RSNs are generally preserved across wake and sleep. Here, we use a recently developed analysis technique to study propagation of infra-slow intrinsic blood oxygen level dependent (BOLD) signals in normal adults during wake and SWS. This analysis reveals marked changes in propagation patterns in SWS vs. wake. Broadly, ordered propagation is preserved within traditionally defined RSNs but lost between RSNs. Additionally, propagation between cerebral cortex and subcortical structures reverses directions, and intra-cortical propagation becomes reorganized, especially in visual and sensorimotor cortices. These findings show that propagated rs-fMRI activity informs theoretical accounts of the neural functions of sleep. DOI: http://dx.doi.org/10.7554/eLife.10781.001

Human cortical–hippocampal dialogue in wake and slow-wave sleep

Significance Reciprocal cortical–hippocampal signaling is widely believed to underlie consolidation of declarative memories. By investigating human fMRI and electrocorticography during both wake and slow-wave sleep (SWS), we find, first, that δ-band activity and infraslow activity propagate in opposite directions between the hippocampus and cortex. Second, both δ activity and infraslow activity reverse propagation directions between the hippocampus and the cortex across wake and SWS. These results highlight reciprocal communication between frequencies, and constitute direct evidence for the reversal of the human cortical–hippocampal dialogue across wake and SWS. Declarative memory consolidation is hypothesized to require a two-stage, reciprocal cortical–hippocampal dialogue. According to this model, higher frequency signals convey information from the cortex to hippocampus during wakefulness, but in the reverse direction during slow-wave sleep (SWS). Conversely, lower-frequency activity propagates from the information “receiver” to the “sender” to coordinate the timing of information transfer. Reversal of sender/receiver roles across wake and SWS implies that higher- and lower-frequency signaling should reverse direction between the cortex and hippocampus. However, direct evidence of such a reversal has been lacking in humans. Here, we use human resting-state fMRI and electrocorticography to demonstrate that δ-band activity and infraslow activity propagate in opposite directions between the hippocampus and cerebral cortex. Moreover, both δ activity and infraslow activity reverse propagation directions between the hippocampus and cerebral cortex across wake and SWS. These findings provide direct evidence for state-dependent reversals in human cortical–hippocampal communication.

How networks communicate: propagation patterns in spontaneous brain activity

Initially regarded as ‘noise’, spontaneous (intrinsic) activity accounts for a large portion of the brains metabolic cost. Moreover, it is now widely known that infra-slow (less than 0.1 Hz) spontaneous activity, measured using resting state functional magnetic resonance imaging of the blood oxygen level-dependent (BOLD) signal, is correlated within functionally defined resting state networks (RSNs). However, despite these advances, the temporal organization of spontaneous BOLD fluctuations has remained elusive. By studying temporal lags in the resting state BOLD signal, we have recently shown that spontaneous BOLD fluctuations consist of remarkably reproducible patterns of whole brain propagation. Embedded in these propagation patterns are unidirectional ‘motifs’ which, in turn, give rise to RSNs. Additionally, propagation patterns are markedly altered as a function of state, whether physiological or pathological. Understanding such propagation patterns will likely yield deeper insights into the role of spontaneous activity in brain function in health and disease. This article is part of the themed issue ‘Interpreting blood oxygen level-dependent: a dialogue between cognitive and cellular neuroscience’.