Abstract Introduction Correlated low‐frequency fluctuations of resting‐state functional magnetic resonance imaging (rsf MRI ) signals have been widely used for inferring intrinsic brain functional connectivity ( FC ). In animal studies, accurate estimate of anesthetic effects on rsf MRI signals is demanded for reliable interpretations of FC changes. We have previously shown that inter‐regional FC can reliably delineate local millimeter‐scale circuits within digit representations of primary somatosensory cortex (S1) subregions (areas 3a, 3b, and 1) in monkeys under isoflurane anesthesia. The goals of this study are to determine (1) the general effects of isoflurane on rsf MRI signals in the S1 circuit and (2) whether the effects are functional‐ and regional‐ dependent, by quantifying the relationships between isoflurane levels, power and inter‐regional correlation coefficients in digit and face regions of distinct S1 subregions. Methods Functional MRI data were collected from male adult squirrel monkeys at three different isoflurane levels (1.25%, 0.875%, and 0.5%). All scans were acquired on a 9.4T magnet with a 3‐cm‐diameter surface transmit‐receive coil centered over the S1 cortex. Power and seed‐based inter‐regional functional connectivity analyses were subsequently performed. Results As anesthesia level increased, we observed (1) diminishing amplitudes of signal fluctuations, (2) reduced power of fluctuations in the low‐frequency band used for connectivity measurements, (3) decreased inter‐voxel connectivity around seed regions, and (4) weakened inter‐regional FC across all pairs of regions of interest (digit‐to‐digit). The low‐frequency power measures derived from rsf MRI signals from control muscle regions, however, did not exhibit any isoflurane level‐related changes. Within the isoflurane dosage range we tested, the inter‐regional functional connectivity differences were still detectable, and the effects of isoflurane did not differ across region‐of‐interest ( ROI ) pairs. Conclusion Our data demonstrate that isoflurane induced similar dose‐dependent suppressive effects on the power of rsf MRI signals and local fine‐scale FC across functionally related but distinct S1 subregions.
MRI guided transcranial focused ultrasound (MRgFUS) is a neuromodulation tool that can excite or inhibit neural activity with high spatial precision and real-time functional feedback. Our goal is to develop a MRgFUS device for human pain therapy. Here, we studied suppressive effects of FUS on a key hub in the thalamus for transmitting peripheral inputs to cortex for pain perception, and mapped changes in effective functional connectivity of thalamic networks using hierarchical clustering. We show that concurrently delivered FUS of moderate intensity suppressed painful heat responses at the thalamus target and induced reorganization of effective connectivity networks.
Patients with multiple sclerosis present with focal lesions throughout the spinal cord. There is a clinical need for non-invasive measurements of spinal cord activity and functional organization in multiple sclerosis, given the cord's critical role in the disease. Recent reports of spontaneous blood oxygenation level-dependent fluctuations in the spinal cord using functional MRI suggest that, like the brain, cord activity at rest is organized into distinct, synchronized functional networks among grey matter regions, likely related to motor and sensory systems. Previous studies looking at stimulus-evoked activity in the spinal cord of patients with multiple sclerosis have demonstrated increased levels of activation as well as a more bilateral distribution of activity compared to controls. Functional connectivity studies of brain networks in multiple sclerosis have revealed widespread alterations, which may take on a dynamic trajectory over the course of the disease, with compensatory increases in connectivity followed by decreases associated with structural damage. We build upon this literature by examining functional connectivity in the spinal cord of patients with multiple sclerosis. Using ultra-high field 7 T imaging along with processing strategies for robust spinal cord functional MRI and lesion identification, the present study assessed functional connectivity within cervical cord grey matter of patients with relapsing-remitting multiple sclerosis (n = 22) compared to a large sample of healthy controls (n = 56). Patient anatomical images were rated for lesions by three independent raters, with consensus ratings revealing 19 of 22 patients presented with lesions somewhere in the imaged volume. Linear mixed models were used to assess effects of lesion location on functional connectivity. Analysis in control subjects demonstrated a robust pattern of connectivity among ventral grey matter regions as well as a distinct network among dorsal regions. A gender effect was also observed in controls whereby females demonstrated higher ventral network connectivity. Wilcoxon rank-sum tests detected no differences in average connectivity or power of low frequency fluctuations in patients compared to controls. The presence of lesions was, however, associated with local alterations in connectivity with differential effects depending on columnar location. The patient results suggest that spinal cord functional networks are generally intact in relapsing-remitting multiple sclerosis but that lesions are associated with focal abnormalities in intrinsic connectivity. These findings are discussed in light of the current literature on spinal cord functional MRI and the potential neurological underpinnings.
To monitor the spontaneous recovery of cervical spinal cord injury (SCI) using longitudinal multiparametric MRI methods.Quantitative MRI imaging including diffusion tensor imaging, magnetization transfer (MT), and chemical exchange saturation transfer (CEST) were conducted in anesthetized squirrel monkeys at 9.4T. The structural, cellular, and molecular features of the spinal cord were examined before and at different time points after a dorsal column lesion in each monkey.Images with MT contrast enhanced visualization of the gray and white matter boundaries and the lesion and permitted differentiation of core and rim compartments within an abnormal volume (AV). In the early weeks after SCI, both core and rim exhibited low cellular density and low protein content, with high levels of exchanging hydroxyl, amine, and amide protons, as evidenced by increased apparent diffusion coefficient, decreased fractional anisotropy, decreased MT ratio, decreased nuclear Overhauser effect, and large CEST effects. Over time, cellular density and fiber density increased, whereas amide, amine, and hydroxyl levels dropped significantly, but at differing rates. Histology confirmed the nature of the AV to be a cyst.Multiparametric MRI offers a novel method to quantify the spontaneous changes in structure and cellular and molecular compositions of SC during spontaneous recovery from injury.
Evaluating the symptomatic progression of mild cognitive impairment (MCI) caused by Alzheimer disease (AD) is practically accomplished by tracking performance on cognitive tasks, such as the Alzheimer Disease Assessment Scale’s cognitive subscale (ADAS_cog), the Mini-Mental Status Examination (MMSE), and the Functional Activities Questionnaire (FAQ). The longitudinal relationships between cognitive decline and metabolic function as assessed using 18F-FDG PET are needed to address both the cognitive and the biologic progression of disease state in individual subjects. We conducted an exploratory investigation to evaluate longitudinal changes in brain glucose metabolism of individual subjects and their relationship to the subject’s changes of cognitive status. Methods: We describe a method to determine correlations in 18F-FDG spatial distribution over time. This parameter is termed the regional 18F-FDG time correlation coefficient (rFTC). By using linear mixed-effects models, we determined the difference in the rFTC decline rate between controls and subjects at high risk of developing AD, such as individuals with MCI or the presence of apolipoprotein E (APOE)–ε4 allele. The association between each subject’s rFTC and performance on cognitive tests (ADAS_cog, MMSE, and FAQ) was determined with 2 different correlation methods. All subject data were downloaded from the Alzheimer Disease Neuroimaging Initiative. Results: The rFTC values of controls remained fairly constant over time (−0.003 annual change; 95% confidence interval, −0.010–0.004). In MCI patients, the rFTC declined faster than in controls by an additional annual change of −0.02 (95% confidence interval, −0.030 to −0.010). In MCI patients, the decline in rFTC was associated with cognitive decline (ADAS_cog, P = 0.011; FAQ, P = 0.0016; MMSE, P = 0.004). After a linear effect of time was accounted for, visit-to-visit changes in rFTC correlated with visit-to-visit changes in all 3 cognitive tests. Conclusion: Longitudinal changes in rFTC detect subtle metabolic changes in individuals associated with variations in their cognition. This analytic tool may be useful for a patient-based monitoring of cognitive decline.
BackgroundMRI-guided transcranial focused ultrasound (MRgFUS) as a next-generation neuromodulation tool can precisely target and stimulate deep brain regions with high spatial selectivity. Combined with MR-ARFI (acoustic radiation force imaging) and using fMRI BOLD signal as functional readouts, our previous studies have shown that low-intensity FUS can excite or suppress neural activity in the somatosensory cortex.ObjectiveTo investigate whether low-intensity FUS can suppress nociceptive heat stimulation-induced responses in thalamic nuclei during hand stimulation, and to determine how this suppression influences the information processing flow within nociception networks.FindingsBOLD fMRI activations evoked by 47.5 °C heat stimulation of hand were detected in 24 cortical regions, which belong to sensory, affective, and cognitive nociceptive networks. Concurrent delivery of low-intensity FUS pulses (520 kHz, 425 kPa) to the predefined heat nociceptive stimulus-responsive thalamic centromedial_parafascicular (CM_para), mediodorsal (MD), ventral_lateral (VL_ and ventral_lateral_posteroventral (VLpv) nuclei suppressed their heat responses. Off-target cortical areas exhibited reduced, enhanced, or no significant fMRI signal changes, depending on the specific areas. Differentiable thalamocortical information flow during the processing of nociceptive heat input was observed, as indicated by the time to reach 10% or 30% of the heat-evoked BOLD signal peak. Suppression of thalamic heat responses significantly altered nociceptive processing flow and direction between the thalamus and cortical areas. Modulation of contralateral versus ipsilateral areas by unilateral thalamic activity differed. Signals detected in high-order cortical areas, such as dorsal frontal (DFC) and ventrolateral prefrontal (vlPFC) cortices, exhibited faster response latencies than sensory areas.ConclusionsThe concurrent delivery of FUS suppressed nociceptive heat response in thalamic nuclei and disrupted the nociceptive network. This study offers new insights into the functional causal connections within the thalamocortical networks and demonstrates the modulatory effects of low-intensity FUS on nociceptive information processing.
The purpose of this work is to design a neuronal fiber tracking algorithm, which will be more suitable for reconstruction of fibers associated with functionally important regions in the human brain. The functional activations in the brain normally occur in the gray matter regions. Hence the fibers bordering these regions are weakly myelinated, resulting in poor performance of conventional tractography methods to trace the fiber links between them. A lower fractional anisotropy in this region makes it even difficult to track the fibers in the presence of noise. In this work, the authors focused on a stochastic approach to reconstruct these fiber pathways based on a Bayesian regularization framework.To estimate the true fiber direction (propagation vector), the a priori and conditional probability density functions are calculated in advance and are modeled as multivariate normal. The variance of the estimated tensor element vector is associated with the uncertainty due to noise and partial volume averaging (PVA). An adaptive and multiple sampling of the estimated tensor element vector, which is a function of the pre-estimated variance, overcomes the effect of noise and PVA in this work.The algorithm has been rigorously tested using a variety of synthetic data sets. The quantitative comparison of the results to standard algorithms motivated the authors to implement it for in vivo DTI data analysis. The algorithm has been implemented to delineate fibers in two major language pathways (Broca's to SMA and Broca's to Wernicke's) across 12 healthy subjects. Though the mean of standard deviation was marginally bigger than conventional (Euler's) approach [P. J. Basser et al., "In vivo fiber tractography using DT-MRI data," Magn. Reson. Med. 44(4), 625-632 (2000)], the number of extracted fibers in this approach was significantly higher. The authors also compared the performance of the proposed method to Lu's method [Y. Lu et al., "Improved fiber tractography with Bayesian tensor regularization," Neuroimage 31(3), 1061-1074 (2006)] and Friman's stochastic approach [O. Friman et al., "A Bayesian approach for stochastic white matter tractography," IEEE Trans. Med. Imaging 25(8), 965-978 (2006)]. Overall performance of the approach is found to be superior to above two methods, particularly when the signal-to-noise ratio was low.The authors observed that an adaptive sampling of the tensor element vectors, estimated as a function of the variance in a Bayesian framework, can effectively delineate neuronal fibers to analyze the structure-function relationship in human brain. The simulated and in vivo results are in good agreement with the theoretical aspects of the algorithm.
Spontaneous fluctuations of Blood Oxygenation-Level Dependent (BOLD) MRI signal in a resting state have previously been detected and analyzed to describe intrinsic functional networks in the spinal cord of rodents, non-human primates and human subjects. In this study we combined high resolution imaging at high field with data-driven Independent Component Analysis (ICA) to i) delineate fine-scale functional networks within and between segments of the cervical spinal cord of monkeys, and also to ii) characterize the longitudinal effects of a unilateral dorsal column injury on these networks. Seven distinct functional hubs were revealed within each spinal segment, with new hubs detected at bilateral intermediate and gray commissure regions in addition to the bilateral dorsal and ventral horns previously reported. Pair-wise correlations revealed significantly stronger connections between hubs on the dominant hand side. Unilateral dorsal-column injuries disrupted predominantly inter-segmental rather than intra-segmental functional connectivities as revealed by correlation strengths and graph-theory based community structures. The effects of injury on inter-segmental connectivity were evident along the length of the cord both below and above the lesion region. Connectivity strengths recovered over time and there was revival of inter-segmental communities as animals recovered function. BOLD signals of frequency 0.01-0.033 Hz were found to be most affected by injury. The results in this study provide new insights into the intrinsic functional architecture of spinal cord and underscore the potential of functional connectivity measures to characterize changes in networks after an injury and during recovery.