Resting state network estimation in individual subjects

Hacker, Carl D.; Laumann, Timothy O.; Szrama, Nicholas; Baldassarre, Antonello; Snyder, Abraham Z.; Leuthardt, Eric C.; Corbetta, Maurizio

doi:10.1016/j.neuroimage.2013.05.108

Cited by 240 publications

(296 citation statements)

References 90 publications

Supporting

Mentioning

281

Contrasting

Unclassified

Order By: Relevance

“…1) involved the temporo-parietal junction (caudal superior temporal gyrus, supramarginal and angular gyri) and the posterior portion of the inferior frontal gyrus. These results are similar to those described as in previously task-related fMRI studies (Corbetta and Shulman 2002;Shulman et al 2010) and rs-fMRI connectivity studies (Fox et al 2006;Shulman et al 2009;Hacker et al 2013) Repeated measures ANOVA revealed a significant interaction between the group and the CPRS scores (F (3,308) =206.25; p < 0.001). Post-hoc independent-sample t-test are summarized in table 3 and revealed significant differences between the CPRS scores for the three groups (see Fig.…”

supporting

confidence: 90%

Double-dissociation between the mechanism leading to impulsivity and inattention in Attention Deficit Hyperactivity Disorder: A resting-state functional connectivity study

Sanefuji

Craig

Parlatini

et al. 2017

Cortex

View full text Add to dashboard Cite

Two core symptoms characterize Attention Deficit Hyperactivity Disorder (ADHD) subtypes: inattentiveness and hyperactivity-impulsivity. While previous brain imaging research investigated ADHD as if it was a homogenous condition, its two core symptoms may originate from different brain mechanisms. We, therefore, hypothesized that the functional connectivity of cortico-striatal and attentional networks would be different between ADHD subtypes. We studied 165 children (mean age 10.93 years; age range, 7-17 year old) diagnosed as having ADHD based on their revised Conner's rating scale score and 170 typical developing individuals (mean age 11.46 years; age range, 7-17 year old) using resting state functional fMRI. Groups were matched for age, IQ and head motion during the MRI acquisition. We fractionated the ADHD group into predominantly inattentive, hyperactive-impulsive and combined subtypes based on their revised Conner's rating scale score. We then analyzed differences in resting state functional connectivity of the cortico-striatal and attentional networks between these subtypes. We found a double dissociation of functional connectivity in the cortico-striatal and ventral attentional networks, reflecting the subtypes of the ADHD participants. Particularly, the hyperactive-impulsive subtype was associated with increased connectivity in cortico-striatal network, whereas the inattentive subtype was associated with increased connectivity in the right ventral attention network. Our study demonstrated for the first time a right lateralized, double dissociation between specific networks associated with hyperactivity-impulsivity and inattentiveness in ADHD children, providing a biological M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT 2 basis for exploring symptom dimensions and revealing potential targets for more personalized treatments.

show abstract

supporting

confidence: 90%

Double-dissociation between the mechanism leading to impulsivity and inattention in Attention Deficit Hyperactivity Disorder: A resting-state functional connectivity study

Sanefuji

Craig

Parlatini

et al. 2017

Cortex

View full text Add to dashboard Cite

show abstract

“…BA44 is located immediately anterior to the ventralmost aspects of the motor homunculus. It is frequently classified as part of Broca's area, which is most closely associated with language generation (50-52) and the brain's language networks (53). However, this region is not exclusively recruited by language tasks.…”

Section: Discussionmentioning

confidence: 99%

Brain aerobic glycolysis and motor adaptation learning

Shannon

Vaishnavi

Vlassenko

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

View full text Add to dashboard Cite

Ten percent to 15% of glucose used by the brain is metabolized nonoxidatively despite adequate tissue oxygenation, a process termed aerobic glycolysis (AG). Because of the known role of glycolysis in biosynthesis, we tested whether learning-induced synaptic plasticity would lead to regionally appropriate, learningdependent changes in AG. Functional MRI (fMRI) before, during, and after performance of a visual-motor adaptation task demonstrated that left Brodmann area 44 (BA44) played a key role in adaptation, with learning-related changes to activity during the task and altered resting-state, functional connectivity after the task. PET scans before and after task performance indicated a sustained increase in AG in left BA 44 accompanied by decreased oxygen consumption. Intersubject variability in behavioral adaptation rate correlated strongly with changes in AG in this region, as well as functional connectivity, which is consistent with a role for AG in synaptic plasticity.T he resting brain's energy needs are supported almost entirely by the metabolism of glucose to carbon dioxide and water (1). The first step of this process, glycolysis, requires no oxygen whereas the second step, oxidative phosphorylation, does. In the normal adult human brain, 10-15% of the glucose never reaches the second step-it is shunted away from oxidative phosphorylation despite the presence of adequate oxygen (2-5). This process is commonly referred to as aerobic glycolysis (AG).Several roles for AG have been identified, including biosynthesis (for recent reviews, see refs. 6-8), the regulation of cellular redox states (9, 10), the regulation of apoptosis (11), the provision of ATP for membrane pumps (12)(13)(14), and the regulation of cell excitability (15, 16). More recently, similar functions of AG have been observed in the posttranscriptional control of T-cell effector function (17, 18), an observation now extended to the microglia (19), where it is associated with an activated state related to inflammation as well as synaptic pruning.In the developing human brain, at a time when synaptic growth rates are highest (approximately age 10), total glucose consumption is twice that of the adult, and 30% of that glucose consumption is AG (a recent summary of this early literature is contained in ref. 20), suggesting an important role in brain development. Another remarkable feature of AG in the adult human brain is that it varies regionally (21): nearly 25% of resting glucose consumption in the medial prefrontal cortex is AG whereas AG constitutes as little as 2% glucose consumption in the cerebellum and medial temporal lobes. Correlation of these regional data with regional gene expression in the adult human brain revealed increased gene expression typical of infancy (i.e., neotony) that is related to synapse formation and growth (20).Further supporting the link between AG and plasticity are findings demonstrating that lactate, released by astrocytes and taken up by neurons, is critical for memory formation. Neuronal uptake of lactate ch...

show abstract

“…2. Critically, the ROIs have been ordered first by RSN membership (Hacker et al 2013) (see Fig. 7) and, within RSN, by temporal order using latency projections by RSN block.…”

Section: Restingmentioning

confidence: 99%

Lag structure in resting-state fMRI

Mitra

Snyder

Hacker

et al. 2014

Journal of Neurophysiology

173

362

View full text Add to dashboard Cite

Mitra A, Snyder AZ, Hacker CD, Raichle ME. Lag structure in resting-state fMRI. J Neurophysiol 111: 2374 -2391, 2014. First published March 5, 2014 doi:10.1152/jn.00804.2013.-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 ϳ1 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.

show abstract

Resting state network estimation in individual subjects

Cited by 240 publications

References 90 publications

Double-dissociation between the mechanism leading to impulsivity and inattention in Attention Deficit Hyperactivity Disorder: A resting-state functional connectivity study

Double-dissociation between the mechanism leading to impulsivity and inattention in Attention Deficit Hyperactivity Disorder: A resting-state functional connectivity study

Brain aerobic glycolysis and motor adaptation learning

Lag structure in resting-state fMRI

Contact Info

Product

Resources

About