Spin-Echo Resting-State Functional Connectivity in High-Susceptibility Regions: Accuracy, Reliability, and the Impact of Physiological Noise

Auditory inputs modulate intrinsic neuronal timescales during sleep

Functional magnetic resonance imaging (fMRI) studies have demonstrated that intrinsic neuronal timescales (INT) undergo modulation by external stimulation during consciousness. It remains unclear if INT keep the ability for significant stimulus-induced modulation during primary unconscious states, such as sleep. This fMRI analysis addresses this question via a dataset that comprises an awake resting-state plus rest and stimulus states during sleep. We analyzed INT measured via temporal autocorrelation supported by median frequency (MF) in the frequency-domain. Our results were replicated using a biophysical model. There were two main findings: (1) INT prolonged while MF decreased from the awake resting-state to the N2 resting-state, and (2) INT shortened while MF increased during the auditory stimulus in sleep. The biophysical model supported these results by demonstrating prolonged INT in slowed neuronal populations that simulate the sleep resting-state compared to an awake state. Conversely, under sine wave input simulating the stimulus state during sleep, the model's regions yielded shortened INT that returned to the awake resting-state level. Our results highlight that INT preserve reactivity to stimuli in states of unconsciousness like sleep, enhancing our understanding of unconscious brain dynamics and their reactivity to stimuli.

Delineating disorder-general and disorder-specific dimensions of psychopathology from functional brain networks in a developmental clinical sample

The interplay between functional brain network maturation and psychopathology during development remains elusive. To establish the structure of psychopathology and its neurobiological mechanisms, mapping of both shared and unique functional connectivity patterns across developmental clinical populations is needed. We investigated shared associations between resting-state functional connectivity and psychopathology in children and adolescents aged 5-21 (n = 1689). Specifically, we used partial least squares (PLS) to identify latent variables (LV) between connectivity and both symptom scores and diagnostic information. We also investigated associations between connectivity and each diagnosis specifically, controlling for other diagnosis categories. PLS identified five significant LVs between connectivity and symptoms, mapping onto the psychopathology hierarchy. The first LV resembled a general psychopathology factor, followed by dimensions of internalising- externalising, neurodevelopment, somatic complaints, and thought problems. Another PLS with diagnostic data revealed one significant LV, resembling a cross-diagnostic case-control pattern. The diagnosis-specific PLS identified a unique connectivity pattern for autism spectrum disorder (ASD). All LVs were associated with distinct patterns of functional connectivity. These dimensions largely replicated in an independent sample (n = 420) from the same dataset, as well as to an independent cohort (n = 3504). This suggests that covariance in developmental functional brain networks supports transdiagnostic dimensions of psychopathology.

Advances in resting state fMRI acquisitions for functional connectomics

Resting state functional magnetic resonance imaging (rs-fMRI) is based on spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal, which occur simultaneously in different brain regions, without the subject performing an explicit task. The low-frequency oscillations of the rs-fMRI signal demonstrate an intrinsic spatiotemporal organization in the brain (brain networks) that may relate to the underlying neural activity. In this review article, we briefly describe the current acquisition techniques for rs-fMRI data, from the most common approaches for resting state acquisition strategies, to more recent investigations with dedicated hardware and ultra-high fields. Specific sequences that allow very fast acquisitions, or multiple echoes, are discussed next. We then consider how acquisition methods weighted towards specific parts of the BOLD signal, like the Cerebral Blood Flow (CBF) or Volume (CBV), can provide more spatially specific network information. These approaches are being developed alongside the commonly used BOLD-weighted acquisitions. Finally, specific applications of rs-fMRI to challenging regions such as the laminae in the neocortex, and the networks within the large areas of subcortical white matter regions are discussed. We finish the review with recommendations for acquisition strategies for a range of typical applications of resting state fMRI.

Improving the sensitivity of spin-echo fMRI at 3T by highly accelerated acquisitions

PURPOSE

Spin-echo (SE) functional MRI (fMRI) can be highly advantageous compared to gradient-echo (GE) fMRI with respect to magnetic field-inhomogeneity artifacts. However, at 3T, the majority of blood oxygenation level-dependent (BOLD) fMRI experiments are performed using T 2 ∗ -weighted GE sequences because of their superior sensitivity compared to SE-fMRI. The presented SE implementation of a highly accelerated GE pulse sequence therefore aims to improve the sensitivity of SE-fMRI while profiting from a reduction of susceptibility-induced signal dropout.

METHODS

Spin-echo MR encephalography (SE-MREG) is compared with the more conventionally used spin-echo echo-planar imaging (SE-EPI) and spin-echo simultaneous multislice (SE-SMS) at 3T in terms of capability to detect neuronal activations and resting-state functional connectivity. For activation analysis, healthy subjects underwent consecutive SE-MREG (pulse repetition time [TR] = 0.25 seconds), SE-SMS (TR = 1.3 seconds), and SE-EPI (TR = 4.4 seconds) scans in pseudorandomized order applied to a visual block design paradigm for generation of t-statistics maps. For the investigation of functional connectivity, additional resting-state data were acquired for 5 minutes and a seed-based correlation analysis using Stanford's FIND (Functional Imaging in Neuropsychiatric Disorders) atlas was performed.

RESULTS

The increased sampling rate of SE-MREG relative to SE-SMS and SE-EPI improves the sensitivity to detect BOLD activation by 33% and 54%, respectively, and increases the capability to extract resting-state networks. Compared with a brain region that is not affected by magnetic field inhomogeneities, SE-MREG shows 2.5 times higher relative signal strength than GE-MREG in mesial temporal structures.

CONCLUSION

SE-MREG offers a viable possibility for whole-brain fMRI with consideration of brain regions that are affected by strong susceptibility-induced magnetic field gradients.

Effective connectivity between bed nucleus of the stria terminalis and amygdala: Reproducibility and relation to anxiety

In a previous study, we investigated the resting‐state fMRI effective connectivity (EC) between the bed nucleus of the stria terminalis (BNST) and the laterobasal (LB), centromedial (CM), and superficial (SF) amygdala. We found strong negative EC from all amygdala nuclei to the BNST, while the BNST showed positive EC to the amygdala. However, the validity of these findings remains unclear, since a reproduction in different samples has not been done. Moreover, the association of EC with measures of anxiety offers deeper insight, due to the known role of the BNST and amygdala in fear and anxiety. Here, we aimed to reproduce our previous results in three additional samples. We used spectral Dynamic Causal Modeling to estimate the EC between the BNST, the LB, CM, and SF, and its association with two measures of self‐reported anxiety. Our results revealed consistency over samples with regard to the negative EC from the amygdala nuclei to the BNST, while the positive EC from BNST to the amygdala was also found, but weaker and more heterogenic. Moreover, we found the BNST‐BNST EC showing a positive and the CM‐BNST EC, showing a negative association with anxiety. Our study suggests a reproducible pattern of negative EC from the amygdala to the BNST along with weaker positive EC from the BNST to the amygdala. Moreover, less BNST self‐inhibition and more inhibitory influence from the CM to the BNST seems to be a pattern of EC that is related to higher anxiety.

Influence of three different anesthesia protocols on aged rat brain: a resting-state functional magnetic resonance imaging study

Background

Resting-state functional magnetic resonance imaging (rs-fMRI) is a promising method for the study of brain function. Typically, rs-fMRI is performed on anesthetized animals. Although different functional connectivity (FC) in various anesthetics on whole brain have been studied, few studies have focused on different FC in the aged brain. Here, we measured FC under three commonly used anesthesia methods and analyzed data to determine if the FC in whole brain analysis were similar among groups.

Methods

Twenty-four male aged Wistar rats were randomly divided into three groups (n = 8 in each group). Anesthesia was performed under either isoflurane (ISO), combined ISO + dexmedetomidine (DEX) or α-chloralose (AC) according to the groups. Data of rs-fMRI was analyzed by FC in a voxel-wise way. Differences in the FC maps between the groups were analyzed by one-way analysis of variance and post hoc two-sample t tests.

Results

Compared with ISO + DEX anesthesia, ISO anesthesia caused increased FC in posterior brain and decreased FC in the middle brain of the aged rat. AC anesthesia caused global suppression as no increase in FC was observed.

Conclusion

ISO could be used as a substitute for ISO + DEX in rat default mode network studies if the left temporal association cortex is not considered important.

Accelerated spin-echo functional MRI using multisection excitation by simultaneous spin-echo interleaving (MESSI) with complex-encoded generalized slice dithered enhanced resolution (cgSlider) simultaneous multislice echo-planar imaging

PURPOSE

Spin-echo functional MRI (SE-fMRI) has the potential to improve spatial specificity when compared with gradient-echo fMRI. However, high spatiotemporal resolution SE-fMRI with large slice-coverage is challenging as SE-fMRI requires a long echo time to generate blood oxygenation level-dependent (BOLD) contrast, leading to long repetition times. The aim of this work is to develop an acquisition method that enhances the slice-coverage of SE-fMRI at high spatiotemporal resolution.

THEORY AND METHODS

An acquisition scheme was developed entitled multisection excitation by simultaneous spin-echo interleaving (MESSI) with complex-encoded generalized slice dithered enhanced resolution (cgSlider). MESSI uses the dead-time during the long echo time by interleaving the excitation and readout of 2 slices to enable 2× slice-acceleration, while cgSlider uses the stable temporal background phase in SE-fMRI to encode/decode 2 adjacent slices simultaneously with a "phase-constrained" reconstruction method. The proposed cgSlider-MESSI was also combined with simultaneous multislice (SMS) to achieve further slice-acceleration. This combined approach was used to achieve 1.5-mm isotropic whole-brain SE-fMRI with a temporal resolution of 1.5 s and was evaluated using sensory stimulation and breath-hold tasks at 3T.

RESULTS

Compared with conventional SE-SMS, cgSlider-MESSI-SMS provides 4-fold increase in slice-coverage for the same repetition time, with comparable temporal signal-to-noise ratio. Corresponding fMRI activation from cgSlider-MESSI-SMS for both fMRI tasks were consistent with those from conventional SE-SMS. Overall, cgSlider-MESSI-SMS achieved a 32× encoding-acceleration by combining Rinplane × MB × cgSlider × MESSI = 4 × 2 × 2 × 2.

CONCLUSION

High-quality, high-resolution whole-brain SE-fMRI was acquired at a short repetition time using cgSlider-MESSI-SMS. This method should be beneficial for high spatiotemporal resolution SE-fMRI studies requiring whole-brain coverage.

Vessel architecture imaging using multiband gradient-echo/spin-echo EPI

Objectives

To apply the MB (multiband) excitation and blipped-CAIPI (blipped-controlled aliasing in parallel imaging) techniques in a spin and gradient-echo (SAGE) EPI sequence to improve the slice coverage for vessel architecture imaging (VAI).

Materials and methods

Both MB excitation and blipped-CAIPI with in-plane parallel imaging were incorporated into a gradient-echo (GE)/spin-echo (SE) EPI sequence for simultaneous tracking of the dynamic MR signal changes in both GE and SE contrasts after the injection of contrast agent. MB and singleband (SB) excitation were compared using a 20-channel head coil at 3 Tesla, and high-resolution MB VAI could be performed in 32 glioma patients.

Results

Whole-brain covered high resolution VAI can be achieved after applying multiband excitation with a factor of 2 and in-plane parallel imaging with a factor of 3. The quality of the images resulting from MB acceleration was comparable to those from the SB method: images were reconstructed without any loss of spatial resolution or severe distortions. In addition, MB and SB signal-to-noise ratios (SNR) were similar. A relative low g-factor induced from the MB acceleration method was achieved after using a blipped-CAIPI technique (1.35 for GE and 1.33 for SE imaging). Performing quantitative VAI, we found that, among all VAI parametric maps, microvessel type indicator (MTI), distance map (I) and vascular-induced bolus peak-time shift (VIPS) were highly correlated. Likewise, VAI parametric maps of slope, slope length and short axis were highly correlated.

Conclusions

Multiband accelerated SAGE successfully doubles the number of readout slices in the same measurement time when compared to conventional readout sequences. The corresponding VAI parametric maps provide insights into the complexity and heterogeneity of vascular changes in glioma.

Comparison of Resting-State Brain Activation Detected by BOLD, Blood Volume and Blood Flow

Resting-state brain activity has been widely investigated using blood oxygenation level dependent (BOLD) contrast techniques. However, BOLD signal changes reflect a combination of the effects of cerebral blood flow (CBF), cerebral blood volume (CBV), as well as the cerebral metabolic rate of oxygen (CMRO₂). In this study, resting-state brain activation was detected and compared using the following techniques: (a) BOLD, using a gradient-echo echo planar imaging (GE-EPI) sequence; (b) CBV-weighted signal, acquired using gradient and spin echo (GRASE) based vascular space occupancy (VASO); and (c) CBF, using pseudo-continuous arterial spin labeling (pCASL). Reliable brain networks were detected using VASO and ASL, including sensorimotor, auditory, primary visual, higher visual, default mode, salience and left/right executive control networks. Differences between the resting-state activation detected with ASL, VASO and BOLD could potentially be due to the different temporal signal-to-noise ratio (tSNR) and the short post-labeling delay (PLD) in ASL, along with differences in the spin-echo readout of VASO. It is also possible that the dynamics of spontaneous fluctuations in BOLD, CBV and CBF could differ due to biological reasons, according to their location within the brain.

Clinical application of advanced MR methods in children: points to consider

The application of both functional MRI and diffusion MR tractography prior to a neurosurgical operation is well established in adults, but less so in children, for several reasons. For this review, we have identified several aspects (task design, subject preparation, actual scanning session, data processing, interpretation of results, and decision-making) where pediatric peculiarities should be taken into account. Further, we not only systematically identify common issues, but also provide solutions, based on our experience as well as a review of the pertinent literature. The aim is to provide the clinician as well as the imaging scientist with information that helps to plan, conduct, and interpret such a clinically-indicated exam in a way that maximizes benefit for, and minimizes the burden on the individual child.

Functional connectomics from a "big data" perspective

In the last decade, explosive growth regarding functional connectome studies has been observed. Accumulating knowledge has significantly contributed to our understanding of the brain's functional network architectures in health and disease. With the development of innovative neuroimaging techniques, the establishment of large brain datasets and the increasing accumulation of published findings, functional connectomic research has begun to move into the era of "big data", which generates unprecedented opportunities for discovery in brain science and simultaneously encounters various challenging issues, such as data acquisition, management and analyses. Big data on the functional connectome exhibits several critical features: high spatial and/or temporal precision, large sample sizes, long-term recording of brain activity, multidimensional biological variables (e.g., imaging, genetic, demographic, cognitive and clinic) and/or vast quantities of existing findings. We review studies regarding functional connectomics from a big data perspective, with a focus on recent methodological advances in state-of-the-art image acquisition (e.g., multiband imaging), analysis approaches and statistical strategies (e.g., graph theoretical analysis, dynamic network analysis, independent component analysis, multivariate pattern analysis and machine learning), as well as reliability and reproducibility validations. We highlight the novel findings in the application of functional connectomic big data to the exploration of the biological mechanisms of cognitive functions, normal development and aging and of neurological and psychiatric disorders. We advocate the urgent need to expand efforts directed at the methodological challenges and discuss the direction of applications in this field.

The Organization of Mouse and Human Cortico-Hippocampal Networks Estimated by Intrinsic Functional Connectivity

While the hippocampal memory system has been relatively conserved across mammals, the cerebral cortex has undergone massive expansion. A central question in brain evolution is how cortical development affected the nature of cortical inputs to the hippocampus. To address this question, we compared cortico-hippocampal connectivity using intrinsic functional connectivity MRI (fcMRI) in awake mice and humans. We found that fcMRI recapitulates anatomical connectivity, demonstrating sensory mapping within the mouse parahippocampal region. Moreover, we identified a similar topographical modality-specific organization along the longitudinal axis of the mouse hippocampus, indicating that sensory information arriving at the hippocampus is only partly integrated. Finally, comparing cortico-hippocampal connectivity across species, we discovered preferential hippocampal connectivity of sensory cortical networks in mice compared with preferential connectivity of association cortical networks in humans. Supporting this observation in humans but not in mice, sensory and association cortical networks are connected to spatially distinct subregions within the parahippocampal region. Collectively, these findings indicate that sensory cortical networks are coupled to the mouse but not the human hippocampal memory system, suggesting that the emergence of expanded and new association areas in humans resulted in the rerouting of cortical information flow and dissociation of primary sensory cortices from the hippocampus.