Resting-state Connectivity Dynamics in the Human Brain using High-speed fMRI

Resting-state fMRI using seed-based connectivity analysis (SCA) typically involves regression of the confounding signals resulting from movement and physiological noise sources. This not only adds additional complexity to the analysis but may also introduce possible regression bias. We recently introduced a computationally efficient real-time SCA approach without confound regression, which employs sliding-window correlation analysis with running mean and standard deviation (meta-statistics). The present study characterizes the confound tolerance of this windowed seed-based connectivity analysis (wSCA), which combines efficient decorrelation of confounding signal events with high-pass filter characteristics that reduce sensitivity to drifts. The confound suppression and the strength of resting-state network (RSN) connectivity were characterized for a range of confounding signal profiles as a function of sliding-window width and scan duration, using simulation and in vivo data. The connectivity strength in six resting-state networks (RSNs) and artifactual connectivity in white matter were compared between wSCA and conventional regression-based SCA (cSCA). The wSCA approach demonstrated scalable confound suppression that increased with decreasing sliding-window width and increasing scan duration in both simulations and in vivo. The confound suppression for sliding-window widths ≤ 15 s was comparable to that of cSCA. Twenty-eight RSNs that were previously reported in a group-ICA study were detected in real-time at scan durations as short as 30 s and with sliding-window widths as short as 4 s. The inter- and intra- network connectivity dynamics of the 28 resting-state networks were studied in real-time and self-repeating connectivity patterns were identified. The wSCA is further investigated offline to study the strength and temporal fluctuations in connectivity using 28 single-region seeds and 28 multi-region seed clusters to measure inter-regional connectivity (IRC) in 140 functional brain regions and inter-network connectivity (INC) among the hubs of 28 RSNs. Multi-region seed IRC maps displayed smaller temporal fluctuations and stronger resting-state connectivity compared with single-region seed IRC maps. Dual thresholding of the meta-statistics maps demonstrated higher spatio-temporal IRC stability in auditory, sensorimotor, and visual cortices compared to other brain regions. The group averaged INC matrices for single-region seeds were consistent with the functional network connectivity matrices (FNCMs) presented in the aforementioned group-ICA study. Furthermore, we extended the mapping of functional connectivity to the whole-brain connectivity fingerprints. In combination with novel brain parcellation methods and advanced machine learning algorithms, wSCA can aid in studying the spatial and temporal connectivity dynamics of the resting-state connectivity. The robust confound tolerance, high temporal resolution, and compatibility with real-time high-speed fMRI, make this approach suitable for monitoring data quality, neurofeedback, and clinical research studies involving disease related changes in functional connectomics

Safety and EEG data quality of concurrent high-density EEG and high-speed fMRI at 3 Tesla

Concurrent EEG and fMRI is increasingly used to characterize the spatial-temporal dynamics of brain activity. However, most studies to date have been limited to conventional echo-planar imaging (EPI). There is considerable interest in integrating recently developed high-speed fMRI methods with high-density EEG to increase temporal resolution and sensitivity for task-based and resting state fMRI, and for detecting interictal spikes in epilepsy. In the present study using concurrent high-density EEG and recently developed high-speed fMRI methods, we investigate safety of radiofrequency (RF) related heating, the effect of EEG on cortical signal-to-noise ratio (SNR) in fMRI, and assess EEG data quality.The study compared EPI, multi-echo EPI, multi-band EPI and multi-slab echo-volumar imaging pulse sequences, using clinical 3 Tesla MR scanners from two different vendors that were equipped with 64- and 256-channel MR-compatible EEG systems, respectively, and receive only array head coils. Data were collected in 11 healthy controls (3 males, age range 18-70 years) and 13 patients with epilepsy (8 males, age range 21-67 years). Three of the healthy controls were scanned with the 256-channel EEG system, the other subjects were scanned with the 64-channel EEG system. Scalp surface temperature, SNR in occipital cortex and head movement were measured with and without the EEG cap. The degree of artifacts and the ability to identify background activity was assessed by visual analysis by a trained expert in the 64 channel EEG data (7 healthy controls, 13 patients).RF induced heating at the surface of the EEG electrodes during a 30-minute scan period with stable temperature prior to scanning did not exceed 1.0° C with either EEG system and any of the pulse sequences used in this study. There was no significant decrease in cortical SNR due to the presence of the EEG cap (p > 0.05). No significant differences in the visually analyzed EEG data quality were found between EEG recorded during high-speed fMRI and during conventional EPI (p = 0.78). Residual ballistocardiographic artifacts resulted in 58% of EEG data being rated as poor quality.This study demonstrates that high-density EEG can be safely implemented in conjunction with high-speed fMRI and that high-speed fMRI does not adversely affect EEG data quality. However, the deterioration of the EEG quality due to residual ballistocardiographic artifacts remains a significant constraint for routine clinical applications of concurrent EEG-fMRI

Brain structural differences in children with fetal alcohol spectrum disorder and its subtypes

IntroductionThe teratogenic effects of prenatal alcohol exposure (PAE) have been examined in animal models and humans. The current study extends the prior literature by quantifying differences in brain structure for individuals with a fetal alcohol spectrum disorder (FASD) compared to typically developing controls, as well as examining FASD subtypes. We hypothesized the FASD group would reveal smaller brain volume, reduced cortical thickness, and reduced surface area compared to controls, with the partial fetal alcohol syndrome (pFAS)/fetal alcohol syndrome (FAS) subtypes showing the largest effects and the PAE/alcohol-related neurodevelopmental disorder (ARND) subtype revealing intermediate effects.MethodsThe sample consisted of 123 children and adolescents recruited from a single site including children with a diagnosis of FASD/PAE (26 males, 29 females) and controls (34 males, 34 females). Structural T1-weighted MRI scans were obtained on a 3T Trio TIM scanner and FreeSurfer v7.2 was used to quantify brain volume, cortical thickness, and surface area. Analyses examined effects by subgroup: pFAS/FAS (N = 32, Mage = 10.7 years, SEage = 0.79), PAE/ARND (N = 23, Mage = 10.8, SEage = 0.94), and controls (N = 68, Mage = 11.1, SEage = 0.54).ResultsTotal brain volume in children with an FASD was smaller relative to controls, but subtype analysis revealed only the pFAS/FAS group differed significantly from controls. Regional analyses similarly revealed reduced brain volume in frontal and temporal regions for children with pFAS/FAS, yet children diagnosed with PAE/ARND generally had similar volumes as controls. Notable differences to this pattern occurred in the cerebellum, caudate, and pallidum where children with pFAS/FAS and PAE/ARND revealed lower volume relative to controls. In the subset of participants who had neuropsychological testing, correlations between volume and IQ scores were observed. Goodness-of-Fit analysis by age revealed differences in developmental patterns (linear vs. quadratic) between groups in some cases.DiscussionThis study confirmed prior results indicating decreased brain volume in children with an FASD and extended the results by demonstrating differential effects by structure for FASD subtypes. It provides further evidence for a complex role of PAE in structural brain development that is likely related to the cognitive and behavioral effects experienced by children with an FASD

Temperature measurement during a 30-minute EPI sequence with EEG cap on, in the Phillips Achieva scanner.

<p>Temperature measurement during a 30-minute EPI sequence with EEG cap on, in the Phillips Achieva scanner.</p

Temperature measurement during a 30-minute EVI sequence with EEG cap on, in the Phillips Achieva scanner.

<p>Temperature measurement during a 30-minute EVI sequence with EEG cap on, in the Phillips Achieva scanner.</p

EEG quality using conventional versus high-speed MR sequences and dependence on head motion.

<p>EEG quality using conventional versus high-speed MR sequences and dependence on head motion.</p

Posterior dominant (alpha) rhythm in an EEG recorded in the MR scanner, during a high-speed sequence.

<p><b>Left:</b> Power Spectrum at EEG electrodes demonstrates a clear peak at 9.44 Hz, at the occipital electrodes. <b>Right:</b> power-map of alpha activity showing its 3D distribution.</p

fMRI acquisition parameters.

<p>fMRI acquisition parameters.</p

Flowchart of the scan protocol during the systematically temperature measurements.

<p>Flowchart of the scan protocol during the systematically temperature measurements.</p

Summary of temperature measurements.

<p>Summary of temperature measurements.</p