Anish Mitra

All Publications

• Targeted neurostimulation reverses a spatiotemporal biomarker of treatment-resistant depression. Proceedings of the National Academy of Sciences of the United States of America Mitra, A., Raichle, M. E., Geoly, A. D., Kratter, I. H., Williams, N. R. 2023; 120 (21): e2218958120

  Abstract

  Major depressive disorder (MDD) is widely hypothesized to result from disordered communication across brain-wide networks. Yet, prior resting-state-functional MRI (rs-fMRI) studies of MDD have studied zero-lag temporal synchrony (functional connectivity) in brain activity absent directional information. We utilize the recent discovery of stereotyped brain-wide directed signaling patterns in humans to investigate the relationship between directed rs-fMRI activity, MDD, and treatment response to FDA-approved neurostimulation paradigm termed Stanford neuromodulation therapy (SNT). We find that SNT over the left dorsolateral prefrontal cortex (DLPFC) induces directed signaling shifts in the left DLPFC and bilateral anterior cingulate cortex (ACC). Directional signaling shifts in the ACC, but not the DLPFC, predict improvement in depression symptoms, and moreover, pretreatment ACC signaling predicts both depression severity and the likelihood of SNT treatment response. Taken together, our findings suggest that ACC-based directed signaling patterns in rs-fMRI are a potential biomarker of MDD.

  View details for DOI 10.1073/pnas.2218958120

  View details for PubMedID 37186863

• Spontaneous Infra-slow Brain Activity Has Unique Spatiotemporal Dynamics and Laminar Structure NEURON Mitra, A., Kraft, A., Wright, P., Acland, B., Snyder, A. Z., Rosenthal, Z., Czerniewski, L., Bauer, A., Snyder, L., Culver, J., Lee, J., Raichle, M. E. 2018; 98 (2): 297-+

  Abstract

  Systems-level organization in spontaneous infra-slow (<0.1Hz) brain activity, measured using blood oxygen signals in fMRI and optical imaging, has become a major theme in the study of neural function in both humans and animal models. Yet the neurophysiological basis of infra-slow activity (ISA) remains unresolved. In particular, is ISA a distinct physiological process, or is it a low-frequency analog of faster neural activity? Here, using whole-cortex calcium/hemoglobin imaging in mice, we show that ISA in each of these modalities travels through the cortex along stereotypical spatiotemporal trajectories that are state dependent (wake versus anesthesia) and distinct from trajectories in delta (1-4 Hz) activity. Moreover, mouse laminar electrophysiology reveals that ISA travels through specific cortical layers and is organized into unique cross-laminar temporal dynamics that are different from higher frequency local field potential activity. These findings suggest that ISA is a distinct neurophysiological process that is reflected in fMRI blood oxygen signals.

  View details for DOI 10.1016/j.neuron.2018.03.015

  View details for Web of Science ID 000430440900010

  View details for PubMedID 29606579

  View details for PubMedCentralID PMC5910292

• Lag threads organize the brain's intrinsic activity (vol 112, pg e2235, 2015) PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA Mitra, A., Snyder, A. Z., Blazey, T., Raichle, M. E. 2015; 112 (52): E7307

  View details for DOI 10.1073/pnas.1523893113

  View details for Web of Science ID 000367234700025

• Propagated infra-slow intrinsic brain activity reorganizes across wake and slow wave sleep ELIFE Mitra, A., Snyder, A. Z., Tagliazucchi, E., Laufs, H., Raichle, M. E. 2015; 4

  Abstract

  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.

  View details for DOI 10.7554/eLife.10781

  View details for Web of Science ID 000373846800001

  View details for PubMedID 26551562

  View details for PubMedCentralID PMC4737658

• A comparison of machine learning classifiers for pediatric epilepsy using resting-state functional MRI latency data BIOMEDICAL REPORTS Nguyen, R. D., Smyth, M. D., Zhu, L., Pao, L. P., Swisher, S. K., Kennady, E. H., Mitra, A., Patel, R. P., Lankford, J. E., Von Allmen, G., Watkins, M. W., Funke, M. E., Shah, M. N. 2021; 15 (3)

  View details for DOI 10.3892/br.2021.1453

  View details for Web of Science ID 000680890300001

• Global waves synchronize the brain's functional systems with fluctuating arousal. Science advances Raut, R. V., Snyder, A. Z., Mitra, A., Yellin, D., Fujii, N., Malach, R., Raichle, M. E. 2021; 7 (30)

  Abstract

  We propose and empirically support a parsimonious account of intrinsic, brain-wide spatiotemporal organization arising from traveling waves linked to arousal. We hypothesize that these waves are the predominant physiological process reflected in spontaneous functional magnetic resonance imaging (fMRI) signal fluctuations. The correlation structure ("functional connectivity") of these fluctuations recapitulates the large-scale functional organization of the brain. However, a unifying physiological account of this structure has so far been lacking. Here, using fMRI in humans, we show that ongoing arousal fluctuations are associated with global waves of activity that slowly propagate in parallel throughout the neocortex, thalamus, striatum, and cerebellum. We show that these waves can parsimoniously account for many features of spontaneous fMRI signal fluctuations, including topographically organized functional connectivity. Last, we demonstrate similar, cortex-wide propagation of neural activity measured with electrocorticography in macaques. These findings suggest that traveling waves spatiotemporally pattern brain-wide excitability in relation to arousal.

  View details for DOI 10.1126/sciadv.abf2709

  View details for PubMedID 34290088

• Convolutional Neural Networks for Pediatric Refractory Epilepsy Classification Using Resting-State fMRI. World neurosurgery Nguyen, R. D., Kennady, E. H., Smyth, M. D., Zhu, L. n., Pao, L. P., Swisher, S. K., Rosas, A. n., Mitra, A. n., Patel, R. P., Lankford, J. n., Von Allmen, G. n., Watkins, M. W., Funke, M. E., Shah, M. N. 2021

  Abstract

  This study aims to evaluate the performance of convolutional neural networks (CNN) trained with resting-state functional MRI (rfMRI) latency data in the classification of patients with pediatric epilepsy from healthy controls.Preoperative rfMRI and anatomical MRI scans were obtained from 63 pediatric patients with refractory epilepsy and 259 pediatric healthy controls. Latency maps of the temporal difference between rfMRI and the global mean signal were calculated using voxel-wise cross-covariance. Healthy control and epilepsy latency z-score maps were pseudorandomized and partitioned into training data (60%), validation data (20%) and test data (20%). Healthy control and epilepsy patients were labeled as negative and positive, respectively. CNN models were then trained with the designated training data. Model hyperparameters were evaluated with a grid-search method. The model with the highest sensitivity was evaluated using unseen test data. Accuracy, sensitivity, specificity, F1-score and AUC were used to evaluate the model's ability to classify epilepsy in the test data set.The model with the highest validation sensitivity, correctly classified 74% of unseen test patients with 85% sensitivity, 71% specificity, F1-score of 0.56 and an AUC of 0.86.Using rfMRI latency data, we trained a CNN model to classify pediatric epilepsy patients from healthy controls with good performance. CNN could serve as an adjunct in the diagnosis of pediatric epilepsy. Identification of pediatric epilepsy earlier in the disease course could decrease time to referral to specialized epilepsy centers, and thus improve prognosis in this population.

  View details for DOI 10.1016/j.wneu.2020.12.131

  View details for PubMedID 33418117

• Probabilistic Flow in Brain-wide Activity. NeuroImage Mitra, A., Snyder, A. Z., Raichle, M. E. 2020: 117321

  Abstract

  Patterns of low frequency brain-wide activity have drawn attention across multiple disciplines in neuroscience. Brain-wide activity patterns are often described through correlations, which capture concurrent increases and decreases in neural activity. More recently, several groups have described reproducible temporal sequences across the brain, illustrating precise long-distance control over the timing of low frequency activity. Features of correlation and temporal organization both point to a systems-level structure of brain activity consisting of large-scale networks and their mutual interactions. Yet a unified view for understanding large networks and their interactions remains elusive. Here, we propose a framework for computing probabilistic flow in brain-wide activity. We demonstrate how flow probabilities are modulated across rest and task states and show that the probabilistic perspective captures both intra- and inter-network dynamics. Finally, we suggest that a probabilistic framework may prove fruitful in characterizing low frequency brain-wide activity in health and disease.

  View details for DOI 10.1016/j.neuroimage.2020.117321

  View details for PubMedID 32882378

• Plasticity and Spontaneous Activity Pulses in Disused Human Brain Circuits. Neuron Newbold, D. J., Laumann, T. O., Hoyt, C. R., Hampton, J. M., Montez, D. F., Raut, R. V., Ortega, M., Mitra, A., Nielsen, A. N., Miller, D. B., Adeyemo, B., Nguyen, A. L., Scheidter, K. M., Tanenbaum, A. B., Van, A. N., Marek, S., Schlaggar, B. L., Carter, A. R., Greene, D. J., Gordon, E. M., Raichle, M. E., Petersen, S. E., Snyder, A. Z., Dosenbach, N. U. 2020; 107 (3): 580

  Abstract

  To induce brain plasticity in humans, we casted the dominant upper extremity for 2weeks and tracked changes in functional connectivity using daily 30-min scans of resting-state functional MRI (rs-fMRI). Casting caused cortical and cerebellar regions controlling the disused extremity to functionally disconnect from the rest of the somatomotor system, while internal connectivity within the disused sub-circuit was maintained. Functional disconnection was evident within 48 h, progressed throughout the cast period, and reversed after cast removal. During the cast period, large, spontaneous pulses of activity propagated through the disused somatomotor sub-circuit. The adult brain seems to rely on regular use to maintain its functional architecture. Disuse-driven spontaneous activity pulses may help preserve functionally disconnected sub-circuits.

  View details for DOI 10.1016/j.neuron.2020.05.007

  View details for PubMedID 32778224

• Local Perturbations of Cortical Excitability Propagate Differentially Through Large-Scale Functional Networks. Cerebral cortex (New York, N.Y. : 1991) Rosenthal, Z. P., Raut, R. V., Yan, P., Koko, D., Kraft, A. W., Czerniewski, L., Acland, B., Mitra, A., Snyder, L. H., Bauer, A. Q., Snyder, A. Z., Culver, J. P., Raichle, M. E., Lee, J. 2020

  Abstract

  Electrophysiological recordings have established that GABAergic interneurons regulate excitability, plasticity, and computational function within local neural circuits. Importantly, GABAergic inhibition is focally disrupted around sites of brain injury. However, it remains unclear whether focal imbalances in inhibition/excitation lead to widespread changes in brain activity. Here, we test the hypothesis that focal perturbations in excitability disrupt large-scale brain network dynamics. We used viral chemogenetics in mice to reversibly manipulate parvalbumin interneuron (PV-IN) activity levels in whisker barrel somatosensory cortex. We then assessed how this imbalance affects cortical network activity in awake mice using wide-field optical neuroimaging of pyramidal neuron GCaMP dynamics as well as local field potential recordings. We report 1) that local changes in excitability can cause remote, network-wide effects, 2) that these effects propagate differentially through intra- and interhemispheric connections, and 3) that chemogenetic constructs can induce plasticity in cortical excitability and functional connectivity. These findings may help to explain how focal activity changes following injury lead to widespread network dysfunction.

  View details for DOI 10.1093/cercor/bhz314

  View details for PubMedID 32043145

• Electrically coupled inhibitory interneurons constrain long-range connectivity of cortical networks. NeuroImage Kraft, A. W., Mitra, A. n., Rosenthal, Z. P., Dosenbach, N. U., Bauer, A. Q., Snyder, A. Z., Raichle, M. E., Culver, J. P., Lee, J. M. 2020: 116810

  Abstract

  Spontaneous infra-slow brain activity (ISA) exhibits a high degree of temporal synchrony, or correlation, between distant brain regions. The spatial organization of ISA synchrony is not explained by anatomical connections alone, suggesting that active neural processes coordinate spontaneous activity. Inhibitory interneurons (IINs) form electrically coupled connections via the gap junction protein connexin 36 (Cx36) and networks of interconnected IINs are known to influence neural synchrony over short distances. However, the role of electrically coupled IIN networks in regulating spontaneous correlation over the entire brain is unknown. In this study, we performed OIS imaging on Cx36-/- mice to examine the role of this gap junction in ISA correlation across the entire cortex. We show that Cx36 deletion increased long-distance intra-hemispheric anti-correlation and inter-hemispheric correlation in spontaneous ISA. This suggests that electrically coupled IIN networks modulate ISA synchrony over long cortical distances.

  View details for DOI 10.1016/j.neuroimage.2020.116810

  View details for PubMedID 32276058

• Organization of Propagated Intrinsic Brain Activity in Individual Humans. Cerebral cortex (New York, N.Y. : 1991) Raut, R. V., Mitra, A., Marek, S., Ortega, M., Snyder, A. Z., Tanenbaum, A., Laumann, T. O., Dosenbach, N. U., Raichle, M. E. 2019

  Abstract

  Spontaneous infra-slow (<0.1Hz) fluctuations in functional magnetic resonance imaging (fMRI) signals are temporally correlated within large-scale functional brain networks, motivating their use for mapping systems-level brain organization. However, recent electrophysiological and hemodynamic evidence suggest state-dependent propagation of infra-slow fluctuations, implying a functional role for ongoing infra-slow activity. Crucially, the study of infra-slow temporal lag structure has thus far been limited to large groups, as analyzing propagation delays requires extensive data averaging to overcome sampling variability. Here, we use resting-state fMRI data from 11 extensively-sampled individuals to characterize lag structure at the individual level. In addition to stable individual-specific features, we find spatiotemporal topographies in each subject similar to the group average. Notably, we find a set of early regions that are common to all individuals, are preferentially positioned proximal to multiple functional networks, and overlap with brain regions known to respond to diverse behavioral tasks-altogether consistent with a hypothesized ability to broadly influence cortical excitability. Our findings suggest that, like correlation structure, temporal lag structure is a fundamental organizational property of resting-state infra-slow activity.

  View details for DOI 10.1093/cercor/bhz198

  View details for PubMedID 31504262

• On time delay estimation and sampling error in resting-state fMRI NEUROIMAGE Raut, R. V., Mitra, A., Snyder, A. Z., Raichle, M. E. 2019; 194: 211–27

  Abstract

  Accumulating evidence indicates that resting-state functional magnetic resonance imaging (rsfMRI) signals correspond to propagating electrophysiological infra-slow activity (<0.1 Hz). Thus, pairwise correlations (zero-lag functional connectivity (FC)) and temporal delays among regional rsfMRI signals provide useful, complementary descriptions of spatiotemporal structure in infra-slow activity. However, the slow nature of fMRI signals implies that practical scan durations cannot provide sufficient independent temporal samples to stabilize either of these measures. Here, we examine factors affecting sampling variability in both time delay estimation (TDE) and FC. Although both TDE and FC accuracy are highly sensitive to data quantity, we use surrogate fMRI time series to study how the former is additionally related to the magnitude of a given pairwise correlation and, to a lesser extent, the temporal sampling rate. These contingencies are further explored in real data comprising 30-min rsfMRI scans, where sampling error (i.e., limited accuracy owing to insufficient data quantity) emerges as a significant but underappreciated challenge to FC and, even more so, to TDE. Exclusion of high-motion epochs exacerbates sampling error; thus, both sides of the bias-variance (or data quality-quantity) tradeoff associated with data exclusion should be considered when analyzing rsfMRI data. Finally, we present strategies for TDE in motion-corrupted data, for characterizing sampling error in TDE and FC, and for mitigating the influence of sampling error on lag-based analyses.

  View details for DOI 10.1016/j.neuroimage.2019.03.020

  View details for Web of Science ID 000468742800018

  View details for PubMedID 30902641

  View details for PubMedCentralID PMC6559238

• Role of resting state MRI temporal latency in refractory pediatric extratemporal epilepsy lateralization. Journal of magnetic resonance imaging : JMRI Shah, M. N., Nguyen, R. D., Pao, L. P., Zhu, L., CreveCoeur, T. S., Mitra, A., Smyth, M. D. 2019; 49 (5): 1347–55

  Abstract

  BACKGROUND: Pediatric epilepsy affects 0.5-1% of children, with 10-30% of these children refractory to medical anticonvulsant therapy and potentially requiring surgical intervention. Analysis of resting state functional MRI (rsMRI) signal temporal differences (latency) has been proposed to study the pathological cognitive processes.PURPOSE/HYPOTHESIS: To quantitatively and qualitatively analyze the correlation of rsMRI signal latency to pediatric refractory extratemporal epilepsy seizure foci lateralization.STUDY TYPE: Retrospective review.POPULATION: With Institutional Review Board approval, rsMRI and anatomical MRI scans were obtained from 38 registered pediatric epilepsy surgery patients from Washington University and 259 healthy control patients from the ADHD-200 dataset.FIELD STRENGTH/SEQUENCE: 3 T echo planar imaging (EPI) blood oxygenation level-dependent (BOLD) sequence.ASSESSMENT: The images were transformed to pediatric atlases in Talairach space. Preoperative voxelwise latency maps were generated with parabolic interpolation of the rsMRI signal lateness or earliness when compared with the global mean signal (GMS) using cross-covariance analysis.STATISTICAL TESTS: Latency z-score maps were created for each epilepsy patient by voxelwise calculation using healthy control mean and standard deviation maps. Voxelwise hypothesis testing was performed via multiple comparisons corrected (false discovery and familywise error rate) and uncorrected methods to determine significantly late and early voxels. Significantly late and/or early voxels were counted for the right and left hemisphere separately. The hemisphere with the greater proportion of significantly late and/or early voxels was hypothesized to contain the seizure focus. Preoperative rsMRI latency analysis hypotheses were compared with postoperative seizure foci lateralization determined by resection images.RESULTS: Preoperative rsMRI latency analysis correctly identified seizure foci lateralization of 64-85% of postoperative epilepsy resections with the proposed methods. RsMRI latency lateralization analysis was 77-100% sensitive and 58-79% specific. In some patients, qualitative analysis yielded preoperative rsMRI latency patterns specific to procedure performed.DATA CONCLUSION: Preoperative rsMRI signal latency of pediatric epilepsy patients was correlated with seizure foci lateralization. J. Magn. Reson. Imaging 2019;49:1347-1355.

  View details for DOI 10.1002/jmri.26320

  View details for PubMedID 30350326

• Brain Networks How Many Types Are There? NEOCORTEX Raichle, M. E., Raut, R. V., Mitra, A., Singer, W., Sejnowski, T. J., Rakic, P. 2019: 97–108

  View details for Web of Science ID 000546253000007

• Resting state signal latency predicts laterality in pediatric medically refractory temporal lobe epilepsy CHILDS NERVOUS SYSTEM Shah, M. N., Mitra, A., Goyal, M. S., Snyder, A. Z., Zhang, J., Shimony, J. S., Limbrick, D. D., Raichle, M. E., Smyth, M. D. 2018; 34 (5): 901–10

  Abstract

  Temporal lobe epilepsy (TLE) affects resting state brain networks in adults. This study aims to correlate resting state functional MRI (rsMRI) signal latency in pediatric TLE patients with their laterality.From 2006 to 2016, 26 surgical TLE patients (12 left, 14 right) with a mean age of 10.7 years (range 0.9-18) were prospectively studied. Preoperative rsMRI was obtained in patients with concordant lateralizing structural MRI, EEG, and PET studies. Standard preprocessing techniques and seed-based rsMRI analyses were performed. Additionally, the latency in rsMRI signal between each 6 mm voxel sampled was examined, compared to the global mean signal, and projected onto standard atlas space for individuals and the cohort.All but one of the 26 patients improved seizure frequency postoperatively with a mean follow-up of 2.9 years (range 0-7.7), with 21 patients seizure-free. When grouped for epileptogenic laterality, the latency map qualitatively demonstrated that the right TLE patients had a relatively early signal pattern, whereas the left TLE patients had a relatively late signal pattern compared to the global mean signal in the right temporal lobe. Quantitatively, the two groups had significantly different signal latency clusters in the bilateral temporal lobes (p < 0.001).There are functional MR signal latency changes in medical refractory pediatric TLE patients. Qualitatively, signal latency in the right temporal lobe precedes the mean signal in right TLE patients and is delayed in left TLE patients. With larger confirmatory studies, preoperative rsMRI latency analysis may offer an inexpensive, noninvasive adjunct modality to lateralize pediatric TLE.

  View details for DOI 10.1007/s00381-018-3770-5

  View details for Web of Science ID 000429793400015

  View details for PubMedID 29511809

  View details for PubMedCentralID PMC5897166

• Principles of cross-network communication in human resting state fMRI SCANDINAVIAN JOURNAL OF PSYCHOLOGY Mitra, A., Raichle, M. E. 2018; 59 (1): 83–90

  Abstract

  Directed signaling among and within the large-scale networks of the human brain is functionally critical. Recent advances in our understanding of spontaneous fluctuations of the fMRI BOLD signal have provided strategies to study the spatial-temporal properties of directed signaling at infra-slow frequencies. Herein we explore the relationship between two canonical systems of the human brain, the default mode network (DMN) and the dorsal attention network (DAN) whose anti-correlated relationship is well known but poorly understood. We find that within the DMN, activity moves from retrosplenial to prefrontal cortex whereas in the DAN activity moves from the frontal eye fields to the parietal cortex. Bi-directional communication between the two networks occurs via their earliest elements (i.e., from the retrosplenial cortex of the DMN to the frontal eye fields of the DAN). This framework for network communication appears to generalize across all networks providing an expanded basis for understanding human brain function.

  View details for DOI 10.1111/sjop.12422

  View details for Web of Science ID 000426038300011

  View details for PubMedID 29356003

  View details for PubMedCentralID PMC5783194

• On the role of the corpus callosum in interhemispheric functional connectivity in humans PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA Roland, J. L., Snyder, A. Z., Hacker, C. D., Mitra, A., Shimony, J. S., Limbrick, D. D., Raichle, M. E., Smyth, M. D., Leuthardt, E. C. 2017; 114 (50): 13278–83

  Abstract

  Resting state functional connectivity is defined in terms of temporal correlations between physiologic signals, most commonly studied using functional magnetic resonance imaging. Major features of functional connectivity correspond to structural (axonal) connectivity. However, this relation is not one-to-one. Interhemispheric functional connectivity in relation to the corpus callosum presents a case in point. Specifically, several reports have documented nearly intact interhemispheric functional connectivity in individuals in whom the corpus callosum (the major commissure between the hemispheres) never develops. To investigate this question, we assessed functional connectivity before and after surgical section of the corpus callosum in 22 patients with medically refractory epilepsy. Section of the corpus callosum markedly reduced interhemispheric functional connectivity. This effect was more profound in multimodal associative areas in the frontal and parietal lobe than primary regions of sensorimotor and visual function. Moreover, no evidence of recovery was observed in a limited sample in which multiyear, longitudinal follow-up was obtained. Comparison of partial vs. complete callosotomy revealed several effects implying the existence of polysynaptic functional connectivity between remote brain regions. Thus, our results demonstrate that callosal as well as extracallosal anatomical connections play a role in the maintenance of interhemispheric functional connectivity.

  View details for DOI 10.1073/pnas.1707050114

  View details for Web of Science ID 000417806200074

  View details for PubMedID 29183973

  View details for PubMedCentralID PMC5740665

• Resting-state fMRI in sleeping infants more closely resembles adult sleep than adult wakefulness PLOS ONE Mitra, A., Snyder, A. Z., Tagliazucchi, E., Laufs, H., Elison, J., Emerson, R. W., Shen, M. D., Wolff, J. J., Botteron, K. N., Dager, S., Estes, A. M., Evans, A., Gerig, G., Hazlett, H. C., Paterson, S. J., Schultz, R. T., Styner, M. A., Zwaigenbaum, L., Schlaggar, B. L., Piven, J., Pruett, J. R., Raichle, M., IBIS Network 2017; 12 (11): e0188122

  Abstract

  Resting state functional magnetic resonance imaging (rs-fMRI) in infants enables important studies of functional brain organization early in human development. However, rs-fMRI in infants has universally been obtained during sleep to reduce participant motion artifact, raising the question of whether differences in functional organization between awake adults and sleeping infants that are commonly attributed to development may instead derive, at least in part, from sleep. This question is especially important as rs-fMRI differences in adult wake vs. sleep are well documented. To investigate this question, we compared functional connectivity and BOLD signal propagation patterns in 6, 12, and 24 month old sleeping infants with patterns in adult wakefulness and non-REM sleep. We find that important functional connectivity features seen during infant sleep closely resemble those seen during adult sleep, including reduced default mode network functional connectivity. However, we also find differences between infant and adult sleep, especially in thalamic BOLD signal propagation patterns. These findings highlight the importance of considering sleep state when drawing developmental inferences in infant rs-fMRI.

  View details for DOI 10.1371/journal.pone.0188122

  View details for Web of Science ID 000415646100025

  View details for PubMedID 29149191

  View details for PubMedCentralID PMC5693436

• Visual experience sculpts whole-cortex spontaneous infraslow activity patterns through an Arc-dependent mechanism PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA Kraft, A. W., Mitra, A., Bauer, A. Q., Snyder, A. Z., Raichle, M. E., Culver, J. P., Lee, J. 2017; 114 (46): E9952–E9961

  Abstract

  Decades of work in experimental animals has established the importance of visual experience during critical periods for the development of normal sensory-evoked responses in the visual cortex. However, much less is known concerning the impact of early visual experience on the systems-level organization of spontaneous activity. Human resting-state fMRI has revealed that infraslow fluctuations in spontaneous activity are organized into stereotyped spatiotemporal patterns across the entire brain. Furthermore, the organization of spontaneous infraslow activity (ISA) is plastic in that it can be modulated by learning and experience, suggesting heightened sensitivity to change during critical periods. Here we used wide-field optical intrinsic signal imaging in mice to examine whole-cortex spontaneous ISA patterns. Using monocular or binocular visual deprivation, we examined the effects of critical period visual experience on the development of ISA correlation and latency patterns within and across cortical resting-state networks. Visual modification with monocular lid suturing reduced correlation between left and right cortices (homotopic correlation) within the visual network, but had little effect on internetwork correlation. In contrast, visual deprivation with binocular lid suturing resulted in increased visual homotopic correlation and increased anti-correlation between the visual network and several extravisual networks, suggesting cross-modal plasticity. These network-level changes were markedly attenuated in mice with genetic deletion of Arc, a gene known to be critical for activity-dependent synaptic plasticity. Taken together, our results suggest that critical period visual experience induces global changes in spontaneous ISA relationships, both within the visual network and across networks, through an Arc-dependent mechanism.

  View details for DOI 10.1073/pnas.1711789114

  View details for Web of Science ID 000415173300029

  View details for PubMedID 29087327

  View details for PubMedCentralID PMC5699067

• On the Stability of BOLD fMRI Correlations CEREBRAL CORTEX Laumann, T. O., Snyder, A. Z., Mitra, A., Gordon, E. M., Gratton, C., Adeyemo, B., Gilmore, A. W., Nelson, S. M., Berg, J. J., Greene, D. J., McCarthy, J. E., Tagliazucchi, E., Laufs, H., Schlaggar, B. L., Dosenbach, N. F., Petersen, S. E. 2017; 27 (10): 4719–32

  Abstract

  Measurement of correlations between brain regions (functional connectivity) using blood oxygen level dependent (BOLD) fMRI has proven to be a powerful tool for studying the functional organization of the brain. Recently, dynamic functional connectivity has emerged as a major topic in the resting-state BOLD fMRI literature. Here, using simulations and multiple sets of empirical observations, we confirm that imposed task states can alter the correlation structure of BOLD activity. However, we find that observations of "dynamic" BOLD correlations during the resting state are largely explained by sampling variability. Beyond sampling variability, the largest part of observed "dynamics" during rest is attributable to head motion. An additional component of dynamic variability during rest is attributable to fluctuating sleep state. Thus, aside from the preceding explanatory factors, a single correlation structure-as opposed to a sequence of distinct correlation structures-may adequately describe the resting state as measured by BOLD fMRI. These results suggest that resting-state BOLD correlations do not primarily reflect moment-to-moment changes in cognitive content. Rather, resting-state BOLD correlations may predominantly reflect processes concerned with the maintenance of the long-term stability of the brain's functional organization.

  View details for DOI 10.1093/cercor/bhw265

  View details for Web of Science ID 000410394400004

  View details for PubMedID 27591147

  View details for PubMedCentralID PMC6248456

• Data Quality Influences Observed Links Between Functional Connectivity and Behavior CEREBRAL CORTEX Siegel, J. S., Mitra, A., Laumann, T. O., Seitzman, B. A., Raichle, M., Corbetta, M., Snyder, A. Z. 2017; 27 (9): 4492–4502

  View details for DOI 10.1093/cercor/bhw253

  View details for Web of Science ID 000407847800016

• Data Quality Influences Observed Links Between Functional Connectivity and Behavior. Cerebral cortex (New York, N.Y. : 1991) Siegel, J. S., Mitra, A., Laumann, T. O., Seitzman, B. A., Raichle, M., Corbetta, M., Snyder, A. Z. 2017; 27 (9): 4492-4502

  Abstract

  A growing field of research explores links between behavioral measures and functional connectivity (FC) assessed using resting-state functional magnetic resonance imaging. Recent studies suggest that measurement of these relationships may be corrupted by head motion artifact. Using data from the Human Connectome Project (HCP), we find that a surprising number of behavioral, demographic, and physiological measures (23 of 122), including fluid intelligence, reading ability, weight, and psychiatric diagnostic scales, correlate with head motion. We demonstrate that "trait" (across-subject) and "state" (across-day, within-subject) effects of motion on FC are remarkably similar in HCP data, suggesting that state effects of motion could potentially mimic trait correlates of behavior. Thus, head motion is a likely source of systematic errors (bias) in the measurement of FC:behavior relationships. Next, we show that data cleaning strategies reduce the influence of head motion and substantially alter previously reported FC:behavior relationship. Our results suggest that spurious relationships mediated by head motion may be widespread in studies linking FC to behavior.

  View details for DOI 10.1093/cercor/bhw253

  View details for PubMedID 27550863

  View details for PubMedCentralID PMC6410500

• Mapping visual dominance in human sleep NEUROIMAGE McAvoy, M., Mitra, A., Tagliazucchi, E., Laufs, H., Raichle, M. E. 2017; 150: 250–61

  Abstract

  Sleep is a universal behavior, essential for humans and animals alike to survive. Its importance to a person's physical and mental health cannot be overstated. Although lateralization of function is well established in the lesion, split-brain and task based neuroimaging literature, and more recently in functional imaging studies of spontaneous fluctuations of the fMRI BOLD signal during wakeful rest, it is unknown if these asymmetries are present during sleep. We investigated hemispheric asymmetries in the global brain signal during non-REM sleep. Here we show that increasing sleep depth is accompanied by an increasing rightward asymmetry of regions in visual cortex including primary bilaterally and in the right hemisphere along the lingual gyrus and middle temporal cortex. In addition, left hemisphere language regions largely maintained their leftward asymmetry during sleep. Right hemisphere attention related regions expressed a more complicated relation with some regions maintaining a rightward asymmetry while this was lost in others. These results suggest that asymmetries in the human brain are state dependent.

  View details for DOI 10.1016/j.neuroimage.2017.02.053

  View details for Web of Science ID 000399855800021

  View details for PubMedID 28232191

• The Lag Structure of Intrinsic Activity is Focally Altered in High Functioning Adults with Autism CEREBRAL CORTEX Mitra, A., Snyder, A. Z., Constantino, J. N., Raichle, M. E. 2017; 27 (2): 1083–93

  Abstract

  The behaviors that define autism spectrum disorders (ASDs) have been hypothesized to result from disordered communication within brain networks. Several groups have investigated this question using resting-state functional magnetic resonance imaging (RS-fMRI). However, the published findings to date have been inconsistent across laboratories. Prior RS-fMRI studies of ASD have employed conventional analysis techniques based on the assumption that intrinsic brain activity is exactly synchronous over widely separated parts of the brain. By relaxing the assumption of synchronicity and focusing, instead, on lags between time series, we have recently demonstrated highly reproducible patterns of temporally lagged activity in normal human adults. We refer to this analysis technique as resting-state lag analysis (RS-LA). Here, we report RS-LA as well as conventional analyses of RS-fMRI in adults with ASD and demographically matched controls. RS-LA analyses demonstrated significant group differences in rs-fMRI lag structure in frontopolar cortex, occipital cortex, and putamen. Moreover, the degree of abnormality in individuals was highly correlated with behavioral measures relevant to the diagnosis of ASD. In this sample, no significant group differences were observed using conventional RS-fMRI analysis techniques. Our results suggest that altered propagation of intrinsic activity may contribute to abnormal brain function in ASD.

  View details for DOI 10.1093/cercor/bhv294

  View details for Web of Science ID 000397257600015

  View details for PubMedID 26656726

  View details for PubMedCentralID PMC6375249

• Human cortical-hippocampal dialogue in wake and slow-wave sleep PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA Mitra, A., Snyder, A. Z., Hacker, C. D., Pahwa, M., Tagliazucchi, E., Laufs, H., Leuthardt, E. C., Raichle, M. E. 2016; 113 (44): E6868–E6876

  Abstract

  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.

  View details for DOI 10.1073/pnas.1607289113

  View details for Web of Science ID 000386608200020

  View details for PubMedID 27791089

  View details for PubMedCentralID PMC5098641

• How networks communicate: propagation patterns in spontaneous brain activity PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES Mitra, A., Raichle, M. E. 2016; 371 (1705)

  Abstract

  Initially regarded as 'noise', spontaneous (intrinsic) activity accounts for a large portion of the brain's 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'.

  View details for DOI 10.1098/rstb.2015.0546

  View details for Web of Science ID 000383505900014

  View details for PubMedID 27574315

  View details for PubMedCentralID PMC5003863

• Unmasking Language Lateralization in Human Brain Intrinsic Activity CEREBRAL CORTEX McAvoy, M., Mitra, A., Coalson, R. S., d'Avossa, G., Keidel, J. L., Petersen, S. E., Raichle, M. E. 2016; 26 (4): 1733–46

  Abstract

  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.

  View details for DOI 10.1093/cercor/bhv007

  View details for Web of Science ID 000374246700031

  View details for PubMedID 25636911

  View details for PubMedCentralID PMC4785953

• Resting-State Network Complexity and Magnitude Are Reduced in Prematurely Born Infants CEREBRAL CORTEX Smyser, C. D., Snyder, A. Z., Shimony, J. S., Mitra, A., Inder, T. E., Neil, J. J. 2016; 26 (1): 322–33

  Abstract

  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.

  View details for DOI 10.1093/cercor/bhu251

  View details for Web of Science ID 000370972500030

  View details for PubMedID 25331596

  View details for PubMedCentralID PMC4677980

• Partial covariance based functional connectivity computation using Ledoit-Wolf covariance regularization NEUROIMAGE Brier, M. R., Mitra, A., McCarthy, J. E., Ances, B. M., Snyder, A. Z. 2015; 121: 29–38

  Abstract

  Functional connectivity refers to shared signals among brain regions and is typically assessed in a task free state. Functional connectivity commonly is quantified between signal pairs using Pearson correlation. However, resting-state fMRI is a multivariate process exhibiting a complicated covariance structure. Partial covariance assesses the unique variance shared between two brain regions excluding any widely shared variance, hence is appropriate for the analysis of multivariate fMRI datasets. However, calculation of partial covariance requires inversion of the covariance matrix, which, in most functional connectivity studies, is not invertible owing to rank deficiency. Here we apply Ledoit-Wolf shrinkage (L2 regularization) to invert the high dimensional BOLD covariance matrix. We investigate the network organization and brain-state dependence of partial covariance-based functional connectivity. Although RSNs are conventionally defined in terms of shared variance, removal of widely shared variance, surprisingly, improved the separation of RSNs in a spring embedded graphical model. This result suggests that pair-wise unique shared variance plays a heretofore unrecognized role in RSN covariance organization. In addition, application of partial correlation to fMRI data acquired in the eyes open vs. eyes closed states revealed focal changes in uniquely shared variance between the thalamus and visual cortices. This result suggests that partial correlation of resting state BOLD time series reflect functional processes in addition to structural connectivity.

  View details for DOI 10.1016/j.neuroimage.2015.07.039

  View details for Web of Science ID 000363122000004

  View details for PubMedID 26208872

  View details for PubMedCentralID PMC4604032

• On the existence of a generalized non-specific task-dependent network FRONTIERS IN HUMAN NEUROSCIENCE Hugdahl, K., Raichle, M. E., Mitra, A., Specht, K. 2015; 9: 430

  Abstract

  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.

  View details for DOI 10.3389/fnhum.2015.00430

  View details for Web of Science ID 000360267400001

  View details for PubMedID 26300757

  View details for PubMedCentralID PMC4526816

• Resting-state Functional Magnetic Resonance Imaging Correlates of Sevoflurane-induced Unconsciousness ANESTHESIOLOGY Palanca, B. A., Mitra, A., Larson-Prior, L., Snyder, A. Z., Avidan, M. S., Raichle, M. E. 2015; 123 (2): 346–56

  Abstract

  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.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.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.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.

  View details for DOI 10.1097/ALN.0000000000000731

  View details for Web of Science ID 000363537300013

  View details for PubMedID 26057259

  View details for PubMedCentralID PMC4509973

• Lag threads organize the brain's intrinsic activity PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA Mitra, A., Snyder, A. Z., Blazey, T., Raichle, M. E. 2015; 112 (17): E2235–E2244

  Abstract

  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.

  View details for DOI 10.1073/pnas.1503960112

  View details for Web of Science ID 000353554000018

  View details for PubMedID 25825720

  View details for PubMedCentralID PMC4418865

• Lag structure in resting-state fMRI JOURNAL OF NEUROPHYSIOLOGY Mitra, A., Snyder, A. Z., Hacker, C. D., Raichle, M. E. 2014; 111 (11): 2374–91

  Abstract

  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 brain's spontaneous activity.

  View details for DOI 10.1152/jn.00804.2013

  View details for Web of Science ID 000339171000019

  View details for PubMedID 24598530

  View details for PubMedCentralID PMC4097876

• Methods to detect, characterize, and remove motion artifact in resting state fMRI NEUROIMAGE Power, J. D., Mitra, A., Laumann, T. O., Snyder, A. Z., Schlaggar, B. L., Petersen, S. E. 2014; 84: 320–41

  Abstract

  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.

  View details for DOI 10.1016/j.neuroimage.2013.08.048

  View details for Web of Science ID 000328868600030

  View details for PubMedID 23994314

  View details for PubMedCentralID PMC3849338