Reliability of resting brain networks using FMRI

Resting state FMRI studies on human subjects are primarily focused on elaborating effects of resting state brain networks on task induced paradigm and to check consistency of these networks between different groups of populations. Recent studies have shown consistency of RSFC networks within same subjects with intra-site and intra-session variation. The primary objective of this study was to check consistency of resting state networks between sites and between different groups of people in spite of change in scanning parameters and population. A total of 437 subjects resting state FMRI data from six different sites were collected varying in age group from 21 to 40 years, with scanning parameters varying from site to site. All the data was pre-processed in exactly similar fashion to reduce effects of site variation and to make group comparison feasible. It was hypothesized that in spite of variation in scanning parameters and population differences, cross-correlation values of time series between 97 ROIs chosen in the brain, should be consistent. To compare resting state connectivity measures, scatter plots of cross-correlation co-efficient between ROIs across sites were used. The investigation demonstrated a strong correlation between cross correlation values for pair of ROIS between sites. These findings suggest reliability and consistency of resting state brain networks between sites

Graph Theoretical Analysis of Functional Brain Networks: Test-Retest Evaluation on Short- and Long-Term Resting-State Functional MRI Data

Graph-based computational network analysis has proven a powerful tool to quantitatively characterize functional architectures of the brain. However, the test-retest (TRT) reliability of graph metrics of functional networks has not been systematically examined. Here, we investigated TRT reliability of topological metrics of functional brain networks derived from resting-state functional magnetic resonance imaging data. Specifically, we evaluated both short-term (<1 hour apart) and long-term (>5 months apart) TRT reliability for 12 global and 6 local nodal network metrics. We found that reliability of global network metrics was overall low, threshold-sensitive and dependent on several factors of scanning time interval (TI, long-term>short-term), network membership (NM, networks excluding negative correlations>networks including negative correlations) and network type (NT, binarized networks>weighted networks). The dependence was modulated by another factor of node definition (ND) strategy. The local nodal reliability exhibited large variability across nodal metrics and a spatially heterogeneous distribution. Nodal degree was the most reliable metric and varied the least across the factors above. Hub regions in association and limbic/paralimbic cortices showed moderate TRT reliability. Importantly, nodal reliability was robust to above-mentioned four factors. Simulation analysis revealed that global network metrics were extremely sensitive (but varying degrees) to noise in functional connectivity and weighted networks generated numerically more reliable results in compared with binarized networks. For nodal network metrics, they showed high resistance to noise in functional connectivity and no NT related differences were found in the resistance. These findings provide important implications on how to choose reliable analytical schemes and network metrics of interest

A Single Session of rTMS Enhances Small-Worldness in Writer’s Cramp: Evidence from Simultaneous EEG-fMRI Multi-Modal Brain Graph

peer reviewedBackground and Purpose: Repetitive transcranial magnetic stimulation (rTMS) induces widespread changes in brain connectivity. As the network topology differences induced by a single session of rTMS are less known we undertook this study to ascertain whether the network alterations had a small-world morphology using multi-modal graph theory analysis of simultaneous EEG-fMRI. Method: Simultaneous EEG-fMRI was acquired in duplicate before (R1) and after (R2) a single session of rTMS in 14 patients with Writer's Cramp (WC). Whole brain neuronal and hemodynamic network connectivity were explored using the graph theory measures and clustering coefficient, path length and small-world index were calculated for EEG and resting state fMRI (rsfMRI). Multi-modal graph theory analysis was used to evaluate the correlation of EEG and fMRI clustering coefficients. Result: A single session of rTMS was found to increase the clustering coefficient and small-worldness significantly in both EEG and fMRI (p < 0.05). Multi-modal graph theory analysis revealed significant modulations in the fronto-parietal regions immediately after rTMS. The rsfMRI revealed additional modulations in several deep brain regions including cerebellum, insula and medial frontal lobe. Conclusion: Multi-modal graph theory analysis of simultaneous EEG-fMRI can supplement motor physiology methods in understanding the neurobiology of rTMS in vivo. Coinciding evidence from EEG and rsfMRI reports small-world morphology for the acute phase network hyper-connectivity indicating changes ensuing low-frequency rTMS is probably not "noise"

Neuroimaging and Neurocognitive Outcomes in Older Patients with Multiple Myeloma Treated with Chemotherapy and Autologous Stem Cell Transplantation

There is a paucity of research on treatment-related neurotoxicity in older adults with multiple myeloma (MM) treated with high-dose chemotherapy (HDC) and autologous SCT (HDC/ASCT), despite the increasing use of this regimen. We examined resting state functional connectivity (RSFC), gray matter (GM) volume, neurocognitive function (NF), and proinflammatory cytokines (PCy) in older patients with MM pre- and post-HDC/ASCT. Eighteen patients underwent MRI, NF tests, and serum PCy measurements prior to HDC/ASCT, and fifteen patients completed a follow up five-months post-HDC/ASCT. There were significant decreases in RSFC post-HDC/ASCT in (1) the central executive network (CEN) involving the left dorsolateral prefrontal cortex and right posterior parietal cortex (p = 0.022) and (2) the CEN involving the right posterior parietal cortex and the salience network involving the right dorsal anterior cingulate cortex (p = 0.029). There were no significant changes in GM or NF, except for improvements in attention (Digit Span Backward, p = 0.03). There were significant increases in several PCy post-HDC/ASCT (p ≤ 0.05). In conclusion, RSFC decreased in frontal, parietal, and cingulate cortices post-HDC/ASCT, NF was relatively stable, and several PCy increased. These findings are congruent with other studies in cancer patients and provide supporting evidence for the vulnerability of frontoparietal regions to chemotherapy’s adverse effects

A Single Session of rTMS Enhances Small-Worldness in Writer's Cramp: Evidence from Simultaneous EEG-fMRI Multi-Modal Brain Graph.

peer reviewedBackground and Purpose: Repetitive transcranial magnetic stimulation (rTMS) induces widespread changes in brain connectivity. As the network topology differences induced by a single session of rTMS are less known we undertook this study to ascertain whether the network alterations had a small-world morphology using multi-modal graph theory analysis of simultaneous EEG-fMRI. Method: Simultaneous EEG-fMRI was acquired in duplicate before (R1) and after (R2) a single session of rTMS in 14 patients with Writer's Cramp (WC). Whole brain neuronal and hemodynamic network connectivity were explored using the graph theory measures and clustering coefficient, path length and small-world index were calculated for EEG and resting state fMRI (rsfMRI). Multi-modal graph theory analysis was used to evaluate the correlation of EEG and fMRI clustering coefficients. Result: A single session of rTMS was found to increase the clustering coefficient and small-worldness significantly in both EEG and fMRI (p < 0.05). Multi-modal graph theory analysis revealed significant modulations in the fronto-parietal regions immediately after rTMS. The rsfMRI revealed additional modulations in several deep brain regions including cerebellum, insula and medial frontal lobe. Conclusion: Multi-modal graph theory analysis of simultaneous EEG-fMRI can supplement motor physiology methods in understanding the neurobiology of rTMS in vivo. Coinciding evidence from EEG and rsfMRI reports small-world morphology for the acute phase network hyper-connectivity indicating changes ensuing low-frequency rTMS is probably not "noise"

Recovery of resting brain connectivity ensuing mild traumatic brain injury.

peer reviewedBrains reveal amplified plasticity as they recover from an injury. We aimed to define time dependent plasticity changes in patients recovering from mild traumatic brain injury (mTBI). Twenty-five subjects with mild head injury were longitudinally evaluated within 36 h, 3 and 6 months using resting state functional connectivity (RSFC). Region of interest (ROI) based connectivity differences over time within the patient group and in comparison with a healthy control group were analyzed at p < 0.005. We found 33 distinct ROI pairs that revealed significant changes in their connectivity strength with time. Within 3 months, the majority of the ROI pairs had decreased connectivity in mTBI population, which increased and became comparable to healthy controls at 6 months. Within this diffuse decreased connectivity in the first 3 months, there were also few regions with increased connections. This hyper connectivity involved the salience network and default mode network within 36 h, and lingual, inferior frontal and fronto-parietal networks at 3 months. Our findings in a fairly homogenous group of patients with mTBI evaluated during the 6 month window of recovery defines time varying brain connectivity changes as the brain recovers from an injury. A majority of these changes were seen in the frontal and parietal lobes between 3 and 6 months after injury. Hyper connectivity of several networks supported normal recovery in the first 6 months and it remains to be seen in future studies whether this can predict an early and efficient recovery of brain function

Functional Connectivity Alterations between Networks and Associations with Infant Immune Health within Networks in HIV Infected Children on Early Treatment: A Study at 7 Years

Although HIV has been shown to impact brain connectivity in adults and youth, it is not yet known to what extent long-term early antiretroviral therapy (ART) may alter these effects, especially during rapid brain development in early childhood. Using both independent component analysis (ICA) and seed-based correlation analysis (SCA), we examine the effects of HIV infection in conjunction with early ART on resting state functional connectivity (FC) in 7 year old children. HIV infected (HIV+) children were from the Children with HIV Early Antiretroviral Therapy (CHER) trial and all initiated ART before 18 months; uninfected children were recruited from an interlinking vaccine trial. To better understand the effects of current and early immune health on the developing brain, we also investigated among HIV+ children the association of FC at 7 years with CD4 count and CD4%, both in infancy (6–8 weeks) and at scan. Although we found no differences within any ICA-generated resting state networks (RSNs) between HIV+ and uninfected children (27 HIV+, 18 uninfected), whole brain connectivity to seeds located at RSN connectivity peaks revealed several loci of FC differences, predominantly from seeds in midline regions (posterior cingulate cortex, paracentral lobule, cuneus, and anterior cingulate). Reduced long-range connectivity and increased short-range connectivity suggest developmental delay. Within the HIV+ children, clinical measures at age 7 years were not associated with FC values in any of the RSNs; however, poor immune health during infancy was associated with localized FC increases in the somatosensory, salience and basal ganglia networks. Together these findings suggest that HIV may affect brain development from its earliest stages and persist into childhood, despite early ART