Recent developments and future avenues for human corticospinal neuroimaging.

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.

Transcranial ultrasound neuromodulation of the thalamic visual pathway in a large animal model and the dose-response relationship with MR-ARFI.

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.

Morphological Component Analysis of Functional MRI Brain Networks.

OBJECTIVE: Sparse representations have been utilized to identify functional connectivity (FC) of networks, while ICA employs the assumption of independence among the network sources to demonstrate FC. Here, we investigate a sparse decomposition method based on Morphological Component Analysis and K-SVD dictionary learning - MCA-KSVD - and contrast the effect of the sparsity constraint vs. the independency constraint on FC and denoising. METHODS: Using a K-SVD algorithm, fMRI signals are decomposed into morphological components which have sparse spatial overlap. We present simulations when the independency assumption of ICA fails and MCA-KSVD recovers more accurate spatial-temporal structures. Denoising performance of both methods is investigated at various noise levels. A comprehensive experimental study was conducted on resting-state and task fMRI. RESULTS: Validations show that ICA is advantageous when network components are well-separated and sparse. In such cases, the MCA-KSVD method has modest value over ICA in terms of network delineation but is significantly more effective in reducing spatial and temporal noise. Results demonstrate that the sparsity constraint yields sparser networks with higher spatial resolution while suppressing weak signals. Temporally, this localization effect yields higher contrast-to-noise ratios (CNRs) of time series. CONCLUSION: While marginally improving the spatial decomposition, MCA-KSVD denoises fMRI data much more effectively than ICA, preserving network structures and improving CNR, especially for weak networks. SIGNIFICANCE: A sparsity-based decomposition approach may be useful for investigating functional connectivity in noisy cases. It may serve as an efficient decomposition method for reduced acquisition time and may prove useful for detecting weak network activations.

Ruminative reflection is associated with anticorrelations between the orbitofrontal cortex and the default mode network in depression: implications for repetitive transcranial magnetic stimulation.

Patients with depression who ruminate repeatedly focus on depressive thoughts; however, there are two cognitive subtypes of rumination, reflection and brooding, each associated with different prognoses. Reflection involves problem-solving and is associated with positive outcomes, whereas brooding involves passive, negative, comparison with other people and is associated with poor outcomes. Rumination has also been related to atypical functional hyperconnectivity between the default mode network and subgenual prefrontal cortex. Repetitive pulse transcranial magnetic stimulation of the prefrontal cortex has been shown to alter functional connectivity, suggesting that the abnormal connectivity associated with rumination could potentially be altered. This study examined potential repetitive pulse transcranial magnetic stimulation prefrontal cortical targets that could modulate one or both of these rumination subtypes. Forty-three patients who took part in a trial of repetitive pulse transcranial magnetic stimulation completed the Rumination Response Scale questionnaire and resting-state functional magnetic resonance imaging. Seed to voxel functional connectivity analyses identified an anticorrelation between the left lateral orbitofrontal cortex (-44, 26, -8; k = 172) with the default mode network-subgenual region in relation to higher levels of reflection. Parallel analyses were not significant for brooding or the RRS total score. These findings extend previous studies of rumination and identify a potential mechanistic model for symptom-based neuromodulation of rumination.

Inconsistencies in mapping current distribution in transcranial direct current stimulation.

Introduction: tDCS 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. Methods: We 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. Results: The 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. Discussions: An 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.

Confounds in neuroimaging: A clear case of sex as a confound in brain-based prediction.

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 (R 2 = 0.108-0.536, p ≤ 0.001), after correcting for sex, the predictive power was substantially reduced (R 2 = -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.

Investigating mechanisms of fast BOLD responses: The effects of stimulus intensity and of spatial heterogeneity of hemodynamics.

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.

Effect of wearing a face mask on fMRI BOLD contrast.

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.

Finding the neural correlates of collaboration using a three-person fMRI hyperscanning paradigm.

Humans have an extraordinary ability to interact and cooperate with others. Despite the social and evolutionary significance of collaboration, research on finding its neural correlates has been limited partly due to restrictions on the simultaneous neuroimaging of more than one participant (also known as hyperscanning). Several studies have used dyadic fMRI hyperscanning to examine the interaction between two participants. However, to our knowledge, no study to date has aimed at revealing the neural correlates of social interactions using a three-person (or triadic) fMRI hyperscanning paradigm. Here, we simultaneously measured the blood-oxygenation level-dependent signal from 12 triads (n = 36 participants), while they engaged in a collaborative drawing task based on the social game of Pictionary General linear model analysis revealed increased activation in the brain regions previously linked with the theory of mind during the collaborative phase compared to the independent phase of the task. Furthermore, using intersubject correlation analysis, we revealed increased synchronization of the right temporo-parietal junction (R TPJ) during the collaborative phase. The increased synchrony in the R TPJ was observed to be positively associated with the overall team performance on the task. In sum, our paradigm revealed a vital role of the R TPJ among other theory-of-mind regions during a triadic collaborative drawing task.

Histologic safety of transcranial focused ultrasound neuromodulation and magnetic resonance acoustic radiation force imaging in rhesus macaques and sheep.

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.

Imaging brain function with simultaneous BOLD and viscoelasticity contrast: fMRI/fMRE.

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 â€‹s ± 3.0 â€‹s for a first-order exponential decay, or a shape parameter of 8.1 â€‹s ± 1.4 â€‹s for a gamma-variate.

On the analysis of rapidly sampled fMRI data.

Recent advances in parallel imaging and simultaneous multi-slice techniques have permitted whole-brain fMRI acquisitions at sub-second sampling intervals, without significantly sacrificing the spatial coverage and resolution. Apart from probing brain function at finer temporal scales, faster sampling rates may potentially lead to enhanced functional sensitivity, owing possibly to both cleaner neural representations (due to less aliased physiological noise) and additional statistical benefits (due to more degrees of freedom for a fixed scan duration). Accompanying these intriguing aspects of fast acquisitions, however, confusion has also arisen regarding (1) how to preprocess/analyze these fast fMRI data, and (2) what exactly is the extent of benefits with fast acquisitions, i.e., how fast is fast enough for a specific research aim? The first question is motivated by the altered spectral distribution and noise characteristics at short sampling intervals, while the second question seeks to reconcile the complicated trade-offs between the functional contrast-to-noise ratio and the effective degrees of freedom. Although there have been recent efforts to empirically approach different aspects of these two questions, in this work we discuss, from a theoretical perspective accompanied by some illustrative, proof-of-concept experimental in vivo human fMRI data, a few considerations that are rarely mentioned, yet are important for both preprocessing and optimizing statistical inferences for studies that employ acquisitions with sub-second sampling intervals. Several summary recommendations include concerns regarding advisability of relying on low-pass filtering to de-noise physiological contributions, employment of statistical models with sufficient complexity to account for the substantially increased serial correlation, and cautions regarding using rapid sampling to enhance functional sensitivity given that different analysis models may associate with distinct trade-offs between contrast-to-noise ratios and the effective degrees of freedom. As an example, we demonstrate that as TR shortens, the intrinsic differences in how noise is accommodated in general linear models and Pearson correlation analyses (assuming Gaussian distributed stochastic signals and noise) can result in quite different outcomes, either gaining or losing statistical power.

Dynamic per slice shimming for simultaneous brain and spinal cord fMRI.

PURPOSE: Simultaneous brain and spinal cord functional MRI is emerging as a new tool to study the central nervous system but is challenging. Poor B0 homogeneity and small size of the spinal cord are principal obstacles to this nascent technology. Here we extend a dynamic shimming approach, first posed by Finsterbusch, by shimming per slice for both the brain and spinal cord. METHODS: We shim dynamically by a simple and fast optimization of linear field gradients and frequency offset separately for each slice in order to minimize off-resonance for both the brain and spinal cord. Simultaneous acquisition of brain and spinal cord fMRI is achieved with high spatial resolution in the spinal cord by means of an echo-planar RF pulse for reduced FOV. Brain slice acquisition is full FOV. RESULTS: T2*-weighted images of brain and spinal cord are acquired with high clarity and minimal observable image artifacts. Fist-clenching fMRI experiments reveal task-consistent activation in motor cortices, cerebellum, and C6-T1 spinal segments. CONCLUSIONS: High quality functional results are obtained for a sensory-motor task. Consistent activation in both the brain and spinal cord is observed at individual levels, not only at group level. Because reduced FOV excitation is applicable to any spinal cord section, future continuation of these methods holds great potential.

Striatal dopamine deficits predict reductions in striatal functional connectivity in major depression: a concurrent 11C-raclopride positron emission tomography and functional magnetic resonance imaging investigation.

Major depressive disorder (MDD) is characterized by the altered integration of reward histories and reduced responding of the striatum. We have posited that this reduced striatal activation in MDD is due to tonically decreased stimulation of striatal dopamine synapses which results in decremented propagation of information along the cortico-striatal-pallido-thalamic (CSPT) spiral. In the present investigation, we tested predictions of this formulation by conducting concurrent functional magnetic resonance imaging (fMRI) and 11C-raclopride positron emission tomography (PET) in depressed and control (CTL) participants. We scanned 16 depressed and 14 CTL participants with simultaneous fMRI and 11C-raclopride PET. We estimated raclopride binding potential (BPND), voxel-wise, and compared MDD and CTL samples with respect to BPND in the striatum. Using striatal regions that showed significant between-group BPND differences as seeds, we conducted whole-brain functional connectivity analysis using the fMRI data and identified brain regions in each group in which connectivity with striatal seed regions scaled linearly with BPND from these regions. We observed increased BPND in the ventral striatum, bilaterally, and in the right dorsal striatum in the depressed participants. Further, we found that as BPND increased in both the left ventral striatum and right dorsal striatum in MDD, connectivity with the cortical targets of these regions (default-mode network and salience network, respectively) decreased. Deficits in stimulation of striatal dopamine receptors in MDD could account in part for the failure of transfer of information up the CSPT circuit in the pathophysiology of this disorder.

MR-Compatible Haptic Display of Membrane Puncture in Robot-Assisted Needle Procedures.

Multilayer electroactive polymer films actuate a small hand-held device that can display tool tip forces during MR-guided interventions. The display produces localized skin stretch at the thumb and index fingertips. Tests confirm that the device does not significantly affect MR imaging and produces detectable stimuli in response to forces measured by a biopsy needle instrumented with optical fibers. Tests with human subjects explored robotic and teleoperated paradigms to detect when the needle contacted a membrane embedded at variable depth in a tissue phantom that approximated the properties of porcine liver. In the first case, naive users detected membranes with a 98.9% success rate as the needle was driven at fixed speed. In the second case, users with experience in needle-based procedures controlled the needle insertion and detected membranes embedded in tissue phantoms with a 98% success rate. In the second experiment, some users detected membranes with very light contact forces, but there was greater subject-to-subject variation.

MR Performance in the Presence of a Radio Frequency-Penetrable Positron Emission Tomography (PET) Insert for Simultaneous PET/MRI.

Despite the great promise of integrated positron emission tomography (PET)/magnetic resonance (MR) imaging to add molecular information to anatomical and functional MR, its potential impact in medicine is diminished by a very high cost, limiting its dissemination. An RF-penetrable PET ring that can be inserted into any existing MR system has been developed to address this issue. Employing optical signal transmission along with battery power enables the PET ring insert to electrically float with respect to the MR system. Then, inter-modular gaps of the PET ring allow the RF transmit field from the standard built-in body coil to penetrate into the PET fields-of-view (FOV) with some attenuation that can be compensated for. MR performance, including RF noise, magnetic susceptibility, RF penetrability through and $B_{1}$ uniformity within the PET insert, and MR image quality, were analyzed with and without the PET ring present. The simulated and experimentally measured RF field attenuation factors with the PET ring present were -2.7 and -3.2 dB, respectively. The magnetic susceptibility effect (0.063 ppm) and noise emitted from the PET ring in the MR receive channel were insignificant. $B_{1}$ homogeneity of a spherical agar phantom within the PET ring FOV dropped by 8.4% and MR image SNR was reduced by 3.5 and 4.3 dB with the PET present for gradient-recalled echo and fast-spin echo, respectively. This paper demonstrates, for the first time, an RF-penetrable PET insert comprising a full ring of operating detectors that achieves simultaneous PET/MR using the standard built-in body coil as the RF transmitter.

PET Imaging Stability Measurements During Simultaneous Pulsing of Aggressive MR Sequences on the SIGNA PET/MR System.

The recent introduction of simultaneous whole-body PET/MR scanners has enabled new research taking advantage of the complementary information obtainable with PET and MRI. One such application is kinetic modeling, which requires high levels of PET quantitative stability. To accomplish the required PET stability levels, the PET subsystem must be sufficiently isolated from the effects of MR activity. Performance measurements have previously been published, demonstrating sufficient PET stability in the presence of MR pulsing for typical clinical use; however, PET stability during radiofrequency (RF)-intensive and gradient-intensive sequences has not previously been evaluated for a clinical whole-body scanner. In this work, PET stability of the GE SIGNA PET/MR was examined during simultaneous scanning of aggressive MR pulse sequences. Methods: PET performance tests were acquired with MR idle and during simultaneous MR pulsing. Recent system improvements mitigating RF interference and gain variation were used. A fast recovery fast spin echo MR sequence was selected for high RF power, and an echo planar imaging sequence was selected for its high heat-inducing gradients. Measurements were performed to determine PET stability under varying MR conditions using the following metrics: sensitivity, scatter fraction, contrast recovery, uniformity, count rate performance, and image quantitation. A final PET quantitative stability assessment for simultaneous PET scanning during functional MRI studies was performed with a spiral in-and-out gradient echo sequence. Results: Quantitation stability of a 68Ge flood phantom was demonstrated within 0.34%. Normalized sensitivity was stable during simultaneous scanning within 0.3%. Scatter fraction measured with a 68Ge line source in the scatter phantom was stable within the range of 40.4%-40.6%. Contrast recovery and uniformity were comparable for PET images acquired simultaneously with multiple MR conditions. Peak noise equivalent count rate was 224 kcps at an effective activity concentration of 18.6 kBq/mL, and the count rate curves and scatter fraction curve were consistent for the alternating MR pulsing states. A final test demonstrated quantitative stability during a spiral functional MRI sequence. Conclusion: PET stability metrics demonstrated that PET quantitation was not affected during simultaneous aggressive MRI. This stability enables demanding applications such as kinetic modeling.

Dissociated patterns of anti-correlations with dorsal and ventral default-mode networks at rest.

Previous studies of resting state functional connectivity have demonstrated that the default-mode network (DMN) is negatively correlated with a set of brain regions commonly activated during goal-directed tasks. However, the location and extent of anti-correlations are inconsistent across different studies, which has been posited to result largely from differences in whether or not global signal regression (GSR) was applied as a pre-processing step. Notably, coordinates of seed regions-of-interest defined within the posterior cingulate cortex (PCC)/precuneus, an area often employed to study functional connectivity of the DMN, have been inconsistent across studies. Taken together with recent observations that the DMN contains functionally heterogeneous subdivisions, it is presently unclear whether these seeds map to different DMN subnetworks, whose patterns of anti-correlation may differ. If so, then seed location may be a non-negligible factor that, in addition to differences in preprocessing steps, contributes to the inconsistencies reported among published studies regarding DMN correlations/anti-correlations. In this study, they examined anti-correlations of different subnetworks within the DMN during rest using both seed-based and point process analyses, and discovered that: (1) the ventral branch of the DMN (vDMN) yielded significantly weaker anti-correlations than that associated with the dorsal branch of the DMN (dDMN); (2) vDMN anti-correlations introduced by GSR were distinct from dDMN anti-correlations; (3) PCC/precuneus seeds employed by earlier studies mapped to different DMN subnetworks, which may explain some of the inconsistency (in addition to preprocessing steps) in the reported DMN anti-correlations. Hum Brain Mapp 38:2454-2465, 2017. © 2017 Wiley Periodicals, Inc.

Nuisance Regression of High-Frequency Functional Magnetic Resonance Imaging Data: Denoising Can Be Noisy.

Recently, emerging studies have demonstrated the existence of brain resting-state spontaneous activity at frequencies higher than the conventional 0.1 Hz. A few groups utilizing accelerated acquisitions have reported persisting signals beyond 1 Hz, which seems too high to be accommodated by the sluggish hemodynamic process underpinning blood oxygen level-dependent contrasts (the upper limit of the canonical model is ∼0.3 Hz). It is thus questionable whether the observed high-frequency (HF) functional connectivity originates from alternative mechanisms (e.g., inflow effects, proton density changes in or near activated neural tissue) or rather is artificially introduced by improper preprocessing operations. In this study, we examined the influence of a common preprocessing step-whole-band linear nuisance regression (WB-LNR)-on resting-state functional connectivity (RSFC) and demonstrated through both simulation and analysis of real dataset that WB-LNR can introduce spurious network structures into the HF bands of functional magnetic resonance imaging (fMRI) signals. Findings of present study call into question whether published observations on HF-RSFC are partly attributable to improper data preprocessing instead of actual neural activities.