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Non-invasive neuroimaging serves as a valuable tool for investigating the mechanisms within the central nervous system (CNS) related to somatosensory and motor processing, emotions, memory, cognition, and other functions. Despite the extensive use of brain imaging, spinal cord imaging has received relatively less attention, regardless of its potential to study peripheral communications with the brain and the descending corticospinal systems. To comprehensively understand the neural mechanisms underlying human sensory and motor functions, particularly in pathological conditions, simultaneous examination of neuronal activity in both the brain and spinal cord becomes imperative. Although technically demanding in terms of data acquisition and analysis, a growing but limited number of studies have successfully utilized specialized acquisition protocols for corticospinal imaging. These studies have effectively assessed sensorimotor, autonomic, and interneuronal signaling within the spinal cord, revealing interactions with cortical processes in the brain. In this mini-review, we aim to examine the expanding body of literature that employs cutting-edge corticospinal imaging to investigate the flow of sensorimotor information between the brain and spinal cord. Additionally, we will provide a concise overview of recent advancements in functional magnetic resonance imaging (fMRI) techniques. Furthermore, we will discuss potential future perspectives aimed at enhancing our comprehension of large-scale neuronal networks in the CNS and their disruptions in clinical disorders. This collective knowledge will aid in refining combined corticospinal fMRI methodologies, leading to the development of clinically relevant biomarkers for conditions affecting sensorimotor processing in the CNS.

Abstract Neuromodulation of deep brain structures via transcranial ultrasound stimulation (TUS) is a promising, but still elusive approach to non-invasive treatment of brain disorders. The purpose of this study was to confirm that MR-guided TUS of the lateral geniculate nucleus (LGN) can modulate visual evoked potentials (VEPs) in the intact large animal; and to study the impact on cortical brain oscillations. The LGN on one side was identified with T2-weighted MRI in sheep (all male, n = 9). MR acoustic radiation force imaging (MR-ARFI) was used to confirm localization of the targeted area in the brain. Electroencephalographic (EEG) signals were recorded, and the visual evoked potential (VEP) peak-to-peak amplitude (N70 and P100) was calculated for each trial. Time–frequency spectral analysis was performed to elucidate the effect of TUS on cortical brain dynamics. The VEP peak-to-peak amplitude was reversibly suppressed relative to baseline during TUS. Dynamic spectral analysis demonstrated a change in cortical oscillations when TUS is paired with visual sensory input. Sonication-associated microscopic displacements, as measured by MR-ARFI, correlated with the TUS-mediated suppression of visual evoked activity. TUS non-invasively delivered to LGN can neuromodulate visual activity and oscillatory dynamics in large mammalian brains.

IntroductiontDCS is a non-invasive neuromodulation technique that has been widely studied both as a therapy for neuropsychiatric diseases and for cognitive enhancement. However, recent meta-analyses have reported significant inconsistencies amongst tDCS studies. Enhancing empirical understanding of current flow in the brain may help elucidate some of these inconsistencies.MethodsWe investigated tDCS-induced current distribution by injecting a low frequency current waveform in a phantom and in vivo. MR phase images were collected during the stimulation and a time-series analysis was used to reconstruct the magnetic field. A current distribution map was derived from the field map using Ampere's law.ResultsThe current distribution map in the phantom showed a clear path of current flow between the two electrodes, with more than 75% of the injected current accounted for. However, in brain, the results did evidence a current path between the two target electrodes but only some portion ( 25%) of injected current reached the cortex demonstrating that a significant fraction of the current is bypassing the brain and traveling from one electrode to the other external to the brain, probably due to conductivity differences in brain tissue types. Substantial inter-subject and intra-subject (across consecutive scans) variability in current distribution maps were also observed in human but not in phantom scans.DiscussionsAn in-vivo current mapping technique proposed in this study demonstrated that much of the injected current in tDCS was not accounted for in human brain and deviated to the edge of the brain. These findings would have ramifications in the use of tDCS as a neuromodulator and may help explain some of the inconsistencies reported in other studies.

Muscle weakness is common in many neurological, neuromuscular, and musculoskeletal conditions. Muscle size only partially explains muscle strength as adaptions within the nervous system also contribute to strength. Brain-based biomarkers of neuromuscular function could provide diagnostic, prognostic, and predictive value in treating these disorders. Therefore, we sought to characterize and quantify the brain's contribution to strength by developing multimodal MRI pipelines to predict grip strength. However, the prediction of strength was not straightforward, and we present a case of sex being a clear confound in brain decoding analyses. While each MRI modality—structural MRI (i.e., gray matter morphometry), diffusion MRI (i.e., white matter fractional anisotropy), resting state functional MRI (i.e., functional connectivity), and task-evoked functional MRI (i.e., left or right hand motor task activation)—and a multimodal prediction pipeline demonstrated significant predictive power for strength (R2 = 0.108–0.536, p ≤ 0.001), after correcting for sex, the predictive power was substantially reduced (R2 = −0.038–0.075). Next, we flipped the analysis and demonstrated that each MRI modality and a multimodal prediction pipeline could significantly predict sex (accuracy = 68.0%−93.3%, AUC = 0.780–0.982, p < 0.001). However, correcting the brain features for strength reduced the accuracy for predicting sex (accuracy = 57.3%−69.3%, AUC = 0.615–0.780). Here we demonstrate the effects of sex-correlated confounds in brain-based predictive models across multiple brain MRI modalities for both regression and classification models. We discuss implications of confounds in predictive modeling and the development of brain-based MRI biomarkers, as well as possible strategies to overcome these barriers.

Background: Neuromodulation by transcranial focused ultrasound (FUS) offers the potential to non-invasively treat specific brain regions, with treatment location verified by magnetic resonance acoustic radiation force imaging (MR-ARFI). Objective: To investigate the safety of these methods prior to widespread clinical use, we report histologic findings in two large animal models following FUS neuromodulation and MR-ARFI. Methods: Two rhesus macaques and thirteen Dorset sheep were studied. FUS neuromodulation was targeted to the primary visual cortex in rhesus macaques and to subcortical locations, verified by MR-ARFI, in eleven sheep. Both rhesus macaques and five sheep received a single FUS session, whereas six sheep received repeated sessions three to six days apart. The remaining two control sheep did not receive ultrasound but otherwise underwent the same anesthetic and MRI procedures as the eleven experimental sheep. Hematoxylin and eosin-stained sections of brain tissue (harvested zero to eleven days following FUS) were evaluated for tissue damage at FUS and control locations as well as tissue within the path of the FUS beam. TUNEL staining was used to evaluate for the presence of apoptosis in sheep receiving high dose FUS. Results: No FUS-related pre-mortem histologic findings were observed in the rhesus macaques or in any of the examined sheep. Extravascular red blood cells (RBCs) were present within the meninges of all sheep, regardless of treatment group. Similarly, small aggregates of perivascular RBCs were rarely noted in non-target regions of neural parenchyma of FUS-treated (8/11) and untreated (2/2) sheep. However, no concurrent histologic abnormalities were observed, consistent with RBC extravasation occurring as post-mortem artifact following brain extraction. Sheep within the high dose FUS group were TUNEL-negative at the targeted site of FUS. Conclusions: The absence of FUS-related histologic findings suggests that the neuromodulation and MR-ARFI protocols evaluated do not cause tissue damage.

Recent studies have demonstrated that fast fMRI can track neural activity well above the temporal limit predicted by the canonical hemodynamic response model. While these findings are promising, the biophysical mechanisms underlying these fast fMRI phenomena remain underexplored. In this study, we discuss two aspects of the hemodynamic response, complementary to several existing hypotheses, that can accommodate faster fMRI dynamics beyond those predicted by the canonical model. First, we demonstrate, using both visual and somatosensory paradigms, that the timing and shape of hemodynamic response functions (HRFs) vary across graded levels of stimulus intensity—with lower-intensity stimulation eliciting faster and narrower HRFs. Second, we show that as the spatial resolution of fMRI increases, voxel-wise HRFs begin to deviate from the canonical model, with a considerable portion of voxels exhibiting faster temporal dynamics than predicted by the canonical HRF. Collectively, both stimulus/task intensity and image resolution can affect the sensitivity of fMRI to fast brain activity, which may partly explain recent observations of fast fMRI signals. It is further noteworthy that, while the present investigations focus on fast neural responses, our findings suggest that a revised hemodynamic model may benefit the many fMRI studies using paradigms with wide ranges of contrast levels (e.g., resting or naturalistic conditions) or with modern, high-resolution MR acquisitions.

International spread of the coronavirus SARS-CoV-2 has prompted many MRI scanning facilities to require scan subjects to wear a facial covering (“mask”) during scanning as a precaution against transmission of the virus. Because wearing a mask mixes expired air with the subject's inspired air stream, the concentration of inspired carbon dioxide [CO2] is elevated, resulting in mild hypercapnia. Changes in the inspired gas mixture have been demonstrated to alter R2*-weighted Blood Oxygen Dependent (BOLD) contrast. In this study, we investigate a potential for face masking to alter BOLD contrast during a sensory-motor task designed to activate visual, auditory, and sensorimotor cortices in 8 subjects. We utilize a nasal cannula to supply air to the subject wearing a surgical mask in on-off blocks of 90s to displace expired CO2, while the subject performs the sensory-motor task. While only a small fraction (2.5%) of the sensory-motor task activation is related to nasal air modulation, a 30.0% change in gray matter BOLD signal baseline is found due to air modulation. Repeating the scan with mask removed produces a small subject-specific bias in BOLD baseline signal from nasal air supply, which may be due to cognitive influence of airflow or cannula-induced hypoxia. Measurements with capnography demonstrate wearing a mask induces an average increase in ETCO2 of 7.4%. Altogether, these results demonstrate that wearing a face mask during gradient-echo fMRI can alter BOLD baseline signal but minimally affects task activation.

Magnetic resonance elastography (MRE) is emerging as a new tool for studying viscoelastic changes in the brain resulting from functional processes. Here, we demonstrate a novel time series method to generate robust functional magnetic resonance elastography (fMRE) activation maps in response to a visual task with a flashing checkerboard stimulus. Using a single-shot spin-echo (SS-SE) pulse sequence, the underlying raw images inherently contain blood-oxygen-level dependent (BOLD) contrast, allowing simultaneous generation of functional magnetic resonance imaging (fMRI) activation maps from the magnitude and functional magnetic resonance elastography (fMRE) maps from the phase. This allows an accurate comparison of the spatially localized stiffness (fMRE) and BOLD (fMRI) changes within a single scan, eliminating confounds inherent in separately acquired scans. Results indicate that tissue stiffness within the visual cortex increases 6–11% with visual stimuli, whereas the BOLD signal change was 1–2%. Furthermore, the fMRE and fMRI activation maps have strong spatial overlap within the visual cortex, providing convincing evidence that fMRE is possible in the brain. However, the fMRE temporal SNR (tSNRfMRE) maps are heterogeneous across the brain. Using a dictionary matching approach to characterize the time series, the viscoelastic changes are consistent with a viscoelastic response function (VRF) time constant of 12.1 ​s ± 3.0 ​s for a first-order exponential decay, or a shape parameter of 8.1 ​s ± 1.4 ​s for a gamma-variate.

The Multidisciplinary Approach to the Study of Chronic Pelvic Pain (MAPP) Research Network is an ongoing multi-center collaborative research group established to conduct integrated studies in participants with urologic chronic pelvic pain syndrome (UCPPS). The goal of these investigations is to provide new insights into the etiology, natural history, clinical, demographic and behavioral characteristics, search for new and evaluate candidate biomarkers, systematically test for contributions of infectious agents to symptoms, and conduct animal studies to understand underlying mechanisms for UCPPS. Study participants were enrolled in a one-year observational study and evaluated through a multisite, collaborative neuroimaging study to evaluate the association between UCPPS and brain structure and function. 3D T1-weighted structural images, resting-state fMRI, and high angular resolution diffusion MRI were acquired in five participating MAPP Network sites using 8 separate MRI hardware and software configurations. We describe the neuroimaging methods and procedures used to scan participants, the challenges encountered in obtaining data from multiple sites with different equipment/software, and our efforts to minimize site-to-site variation.