Simultaneous fMRI Research Articles

Preservation of EEG spectral power features during simultaneous EEG-fMRI.

Electroencephalographic (EEG) data quality is severely compromised when recorded inside the magnetic resonance (MR) environment. Here we characterized the impact of the ballistocardiographic (BCG) artifact on resting-state EEG spectral properties and compared the effectiveness of seven common BCG correction methods to preserve EEG spectral features. We also assessed if these methods retained posterior alpha power reactivity to an eyes closure-opening (EC-EO) task and compared the results from EEG-informed fMRI analysis using different BCG correction approaches. Electroencephalographic data from 20 healthy young adults were recorded outside the MR environment and during simultaneous fMRI acquisition. The gradient artifact was effectively removed from EEG-fMRI acquisitions using Average Artifact Subtraction (AAS). The BCG artifact was corrected with seven methods: AAS, Optimal Basis Set (OBS), Independent Component Analysis (ICA), OBS followed by ICA, AAS followed by ICA, PROJIC-AAS and PROJIC-OBS. EEG signal preservation was assessed by comparing the spectral power of traditional frequency bands from the corrected rs-EEG-fMRI data with the data recorded outside the scanner. We then assessed the preservation of posterior alpha functional reactivity by computing the ratio between the EC and EO conditions during the EC-EO task. EEG-informed fMRI analysis of the EC-EO task was performed using alpha power-derived BOLD signal predictors obtained from the EEG signals corrected with different methods. The BCG artifact caused significant distortions (increased absolute power, altered relative power) across all frequency bands. Artifact residuals/signal losses were present after applying all correction methods. The EEG reactivity to the EC-EO task was better preserved with ICA-based correction approaches, particularly when using ICA feature extraction to isolate alpha power fluctuations, which allowed to accurately predict hemodynamic signal fluctuations during the EEG-informed fMRI analysis. Current software solutions for the BCG artifact problem offer limited efficiency to preserve the EEG spectral power properties using this particular EEG setup. The state-of-the-art approaches tested here can be further refined and should be combined with hardware implementations to better preserve EEG signal properties during simultaneous EEG-fMRI. Existing and novel BCG artifact correction methods should be validated by evaluating signal preservation of both ERPs and spontaneous EEG spectral power.

Working memory biases early object discrimination and parietal activity during attentional selection.

The contents of working memory (WM) guide visual attention, but the neural mechanisms underlying WM biases remains unclear. Here, we used simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) approaches to characterize the timing and location of the neural response underlying WM guidance during a visual search task. Behaviorally, we observed faster search performance when the WM contents matching targets (valid) compared to when WM contents did not reappear (neutral). The EEG data showed similar benefit effects of posterior N1 component, in which targets induced larger N1 amplitudes in the valid condition than in the neutral condition. Interestingly, the fMRI activation in left supramarginal gyrus (SMG)/inferior parietal lobule (IPL) and bilateral occipital cortex was lower in the valid compared to neutral conditions. Importantly, the magnitude of the increased N1 activity and the decreased fMRI activity in the left SMG/IPL predicted the extent of search improvement at an individual subject level. These results suggest that information held in WM enhances early object discrimination during attentional selection, and the left SMG/IPL may be a critical region in mediating goal-directed processing under WM biases in human visual attention.

Simultaneous Functional Magnetic Resonance and Optoacoustic Imaging of Brain-Wide Sensory Responses in Mice.

Functional magnetic resonance imaging (fMRI) has massively contributed to the understanding of mammalian brain function. However, the origin and interpretation of the blood oxygen level-dependent (BOLD) signals retrieved by fMRI remain highly disputed. This article reports on the development of a fully hybridized system enabling concurrent functional magnetic resonance optoacoustic tomography (MROT) measurements of stimulus-evoked brain-wide sensory responses in mice. The highly complementary angiographic and soft tissue contrasts of both modalities along with simultaneous multi-parametric readings of stimulus-evoked hemodynamic responses are leveraged in order to establish unequivocal links between the various counteracting physiological and metabolic processes in the brain. The results indicate that the BOLD signals are highly correlated, both spatially and temporally, with the total hemoglobin readings resolved with volumetric multi-spectral optoacoustic tomography. Furthermore, the differential oxygenated and deoxygenated hemoglobin optoacoustic readings exhibit superior sensitivity as compared to the BOLD signals when detecting stimulus-evoked hemodynamic responses. The fully hybridized MROT approach greatly expands the neuroimaging toolset to comprehensively study neurovascular and neurometabolic coupling mechanisms and related diseases.

Spikes with and without concurrent high-frequency oscillations: Topographic relationship and neural correlates using EEG-fMRI

ObjectiveEpilepsy surgery is the best therapeutic option for patients with drug-resistant focal epilepsy. During presurgical investigation, interictal spikes can provide important information on eligibility, lateralisation and localisation of the surgical target. However, their relationship to epileptogenic tissue is variable. Interictal spikes with concurrent high-frequency oscillations (HFOs) have been postulated to reflect epileptogenic tissue more reliably. Here, we studied the voltage distribution of scalp-recorded spikes with and without concurrent HFO and identified their respective haemodynamic correlates using simultaneous electroencephalography and functional Magnetic Resonance Imaging (EEG-fMRI). MethodsThe scalp topography of spikes with and without concurrent HFOs were assessed in 31 consecutive patients with focal drug-resistant epilepsy who showed interictal spikes during presurgical evaluation. Simultaneous EEG-fMRI was then used in 17 patients with spikes and concurrent HFOs. Haemodynamic changes were obtained from the spatial correlation between the patient-specific voltage map of each spike population and the intra-scanner EEG. The haemodynamic response of spikes with and without HFOs were compared in terms of their spatial similarity, strength, the distance between activation peaks and concordance with interictal localisation. ResultsTwenty-five patients showed spikes with and without concurrent HFOs. Among patients with both types of spikes, most spikes were not associated with HFOs (p < 0.0001, Mann-Whitney test). Twenty of the 25 patients showed an average of 8 ± 6 (standard deviation) electrodes with significant voltage differences (p = 0.025, permutation test corrected for multiple comparisons) on scalp electrodes within and distant to the spike field.Comparing the haemodynamic response between both spike populations, we found no significant differences in the peak strength (p = 0.71, Mann-Whitney test), spatial distribution (p = 0.113, One-sample Wilcoxon test) and distance between activation peaks (p = 0.5, One-sample Wilcoxon test), with all peaks being co-localised in the same lobe. SignificanceOur data showed that spikes with and without HFOs have different scalp voltage distributions. However, when assessing the haemodynamic changes of each spike type, we found that both elicit similar haemodynamic changes and share high spatial similarity suggesting that the epileptic networks of spikes with and without HFOs have the same underlying neural substrate.

Low frequency repetitive transcranial magnetic stimulation to the right dorsolateral prefrontal cortex engages thalamus, striatum, and the default mode network.

The positive treatment outcomes of low frequency (LF) repetitive transcranial magnetic stimulation (rTMS) when applied over the right dorsolateral prefrontal cortex (DLPFC) in treatment-refractory depression has been verified. However, the mechanism of action behind these results have not been well-explored. In this work we used simultaneous functional magnetic resonance imaging (fMRI) during TMS to explore the effect of LF rTMS on brain activity when applied to the right [RDLPFC1 (MNI: 50, 30, 36)] and left DLPFC sites [LDLPFC1 (MNI: -50, 30, 36), LDLPFC2 (MNI: -41, 16, 54)]. Seventeen healthy adult volunteers participated in this study. To identify brain areas affected by rTMS, an independent component analysis and a general linear model were used. Our results showed an important laterality effect when contrasting rTMS over the left and right sites. Specifically, LF rTMS increased brain activity at the striatum, thalamus, and areas of the default mode network when applied to the right, but not to the contralateral left DLPFC. In contrast, no site differences were observed when evaluating the effect of LF rTMS over the two left sites. These findings demonstrate that LF rTMS to the right DLPFC was able to stimulate the cortico-striato-thalamo-cortical pathway, which is dysregulated in patients with major depressive disorder; therefore, possibly providing some neurobiological justification for the successful outcomes found thus far for LF rTMS in the treatment of depression.

Enhanced mirror neuron network activity and effective connectivity during live interaction among female subjects

Facial expressions are indispensable in daily human communication. Previous neuroimaging studies investigating facial expression processing have presented pre-recorded stimuli and lacked live face-to-face interaction. Our paradigm alternated between presentations of real-time model performance and pre-recorded videos of dynamic facial expressions to participants. Simultaneous functional magnetic resonance imaging (fMRI) and facial electromyography activity recordings, as well as post-scan valence and arousal ratings were acquired from 44 female participants. Live facial expressions enhanced the subjective valence and arousal ratings as well as facial muscular responses. Live performances showed greater engagement of the right posterior superior temporal sulcus (pSTS), right inferior frontal gyrus (IFG), right amygdala and right fusiform gyrus, and modulated the effective connectivity within the right mirror neuron system (IFG, pSTS, and right inferior parietal lobule). A support vector machine algorithm could classify multivoxel activation patterns in brain regions involved in dynamic facial expression processing in the mentalizing networks (anterior and posterior cingulate cortex). These results indicate that live social interaction modulates the activity and connectivity of the right mirror neuron system and enhances spontaneous mimicry, further facilitating emotional contagion.

Detection of laser-associated heating in the brain during simultaneous fMRI and optogenetic stimulation.

To calculate temperatures from T2 *-weighted images collected during optogenetic fMRI based on proton resonance frequency (PRF) shift thermometry, to monitor confounding heating effects and determine appropriate light parameters for optogenetic stimulation. fMRI is mainly based on long-TE gradient-recalled echo acquisitions that are also suitable for measuring small temperature changes via the PRF shift. A motion- and respiration-robust processing pipeline was developed to calculate temperature changes based on the PRF shift directly from the T2 *-weighted images collected for fMRI with a two-shot 2D gradient-recalled echo-EPI sequence at 9.4T. Optogenetic fMRI protocols which differed in stimulation durations (3, 6 and 9s) within a total block duration of 30 s were applied in a squirrel monkey to validate the methods with blue and green light (20 Hz, 30 mW) delivery interleaved between periods. General linear modeling was performed on the resulting time series temperature maps to verify if light delivery with each protocol resulted in significant heating in the brain around the optical fiber. The temperature SD was 0.05°C with the proposed imaging protocol and processing. Statistical analysis showed that the optogenetic stimulation protocol with a 3s stimulation duration did not result in significant temperature rises. Significant temperature rises up to 0.13°C (p< 0. 05) were observed with 6 and 9s stimulation durations for blue and green light. The proposed processing pipeline can be useful for the design of optogenetic stimulation protocols and for monitoring confounding heating effects.

Dynamic functional connectivity estimation for neurofeedback emotion regulation paradigm with simultaneous EEG-fMRI analysis.

Joint Analysis of EEG and fMRI datasets can bring new insight into brain mechanisms. In this paper, we employed the recently introduced Correlated Coupled Tensor Matrix Factorization (CCMTF) method for analysis of the emotion regulation paradigm based on EEG frontal asymmetry neurofeedback in the alpha frequency band with simultaneous fMRI. CCMTF method assumes that the co-variations of the common dimension (temporal dimension) between EEG and fMRI are correlated and not necessarily identical. The results of the CCMTF method suggested that EEG and fMRI had similar covariations during the transition of brain activities from resting states to task (view and upregulation) states and these covariations followed an increasing trend. The fMRI shared spatial component showed activations in the limbic system, DLPFC, OFC, and VLPC regions, which were consistent with the previous studies and were linked to EEG frequency patterns in the range of 1–15 Hz with a correlation value close to 0.75. The estimated regions from the CCMTF method were then used as the candidate nodes for dynamic functional connectivity (dFC) analysis, in which the changes in connectivity from view to upregulation states were examined. The results of the dFC analysis were compared with a Normalized Mutual information (NMI) based approach in two different frequency ranges (1–15 and 15–40 Hz) as the NMI method was applied to the vectors of dFC nodes of EEG and fMRI data. The results of the two methods illustrated that the relation between EEG and fMRI datasets was mostly in the frequency range of 1–15 Hz. These relations were both in the brain activations and the dFCs between the two modalities. This paper suggests that the CCMTF method is a capable approach for extracting the shared information between EEG and fMRI data and can reveal new information about brain functions and their connectivity without solving the EEG inverse problem or analyzing different frequency bands.

Basal ganglia-cortical connectivity underlies self-regulation of brain oscillations in humans

Brain-computer interfaces provide an artificial link by which the brain can directly interact with the environment. To achieve fine brain-computer interface control, participants must modulate the patterns of the cortical oscillations generated from the motor and somatosensory cortices. However, it remains unclear how humans regulate cortical oscillations, the controllability of which substantially varies across individuals. Here, we performed simultaneous electroencephalography (to assess brain-computer interface control) and functional magnetic resonance imaging (to measure brain activity) in healthy participants. Self-regulation of cortical oscillations induced activity in the basal ganglia-cortical network and the neurofeedback control network. Successful self-regulation correlated with striatal activity in the basal ganglia-cortical network, through which patterns of cortical oscillations were likely modulated. Moreover, basal ganglia-cortical network and neurofeedback control network connectivity correlated with strong and weak self-regulation, respectively. The findings indicate that the basal ganglia-cortical network is important for self-regulation, the understanding of which should help advance brain-computer interface technology.

A computational model based on corticospinal functional MRI revealed asymmetrically organized motor corticospinal networks in humans

Evolution of the direct, monosynaptic connection from the primary motor cortex to the spinal cord parallels acquisition of hand dexterity and lateralization of hand preference. In non-human mammals, the indirect, multi-synaptic connections between the bilateral primary motor cortices and the spinal cord also participates in controlling dexterous hand movement. However, it remains unknown how the direct and indirect corticospinal pathways work in concert to control unilateral hand movement with lateralized preference in humans. Here we demonstrated the asymmetric functional organization of the two corticospinal networks, by combining network modelling and simultaneous functional magnetic resonance imaging techniques of the brain and the spinal cord. Moreover, we also found that the degree of the involvement of the two corticospinal networks paralleled lateralization of hand preference. The present results pointed to the functionally lateralized motor nervous system that underlies the behavioral asymmetry of handedness in humans.

Toward Completely Sampled Extracellular Neural Recording During fMRI.

This work aims to estimate severe fMRI scanning artifacts in extracellular neural recordings made at ultrahigh magnetic field strengths in order to remove the artifact interferences and uncover the complete neural electrophysiology signal. We build on previous work that used PCA to denoise EEG recorded during fMRI, adapting it to cover the much larger frequency range (1-6000 Hz) of the extracellular field potentials (EFPs) observed by extracellular neural recordings. We examine the singular value decomposition (SVD)-PCA singular value shrinkage (SVS) and compare two shrinkage rules and a sliding template subtraction approach. Additionally, we present a new technique for estimating the singular value upper bounds in spontaneous neural activity recorded in the isoflurane anesthetized rat that uses the temporal first difference of the neural signal. The approaches are tested on artificial datasets to examine their efficacy in detecting extracellular action potentials (EAPs: 300-6000 Hz) recorded during fMRI gradient interferences. Our results indicate that it is possible to uncover the EAPs recorded during gradient interferences. The methods are then tested on natural (non-artificial) datasets recorded from the cortex of isoflurane anesthetized rats, where both local field potential (LFP: 1-300 Hz) and EAP signals are analyzed. The SVS methods are shown to be advantageous compared to sliding template subtraction, especially in the high frequency range corresponding to EAPs. Our novel approach moves us towards simultaneous fMRI and completely sampled neural recording (1-6000Hz with no temporal gaps), providing the opportunity for further study of spontaneous brain function and neurovascular coupling at ultrahigh field in the isoflurane anesthetized rat.

Evaluating the Safety of Simultaneous Intracranial Electroencephalography and Functional Magnetic Resonance Imaging Acquisition Using a 3 Tesla Magnetic Resonance Imaging Scanner.

BackgroundThe unsurpassed sensitivity of intracranial electroencephalography (icEEG) and the growing interest in understanding human brain networks and ongoing activities in health and disease have make the simultaneous icEEG and functional magnetic resonance imaging acquisition (icEEG-fMRI) an attractive investigation tool. However, safety remains a crucial consideration, particularly due to the impact of the specific characteristics of icEEG and MRI technologies that were safe when used separately but may risk health when combined. Using a clinical 3-T scanner with body transmit and head-receive coils, we assessed the safety and feasibility of our icEEG-fMRI protocol.MethodsUsing platinum and platinum-iridium grid and depth electrodes implanted in a custom-made acrylic-gel phantom, we assessed safety by focusing on three factors. First, we measured radio frequency (RF)-induced heating of the electrodes during fast spin echo (FSE, as a control) and the three sequences in our icEEG-fMRI protocol. Heating was evaluated with electrodes placed orthogonal or parallel to the static magnetic field. Using the configuration with the greatest heating observed, we then measured the total heating induced in our protocol, which is a continuous 70-min icEEG-fMRI session comprising localizer, echo-planar imaging (EPI), and magnetization-prepared rapid gradient-echo sequences. Second, we measured the gradient switching-induced voltage using configurations mimicking electrode implantation in the frontal and temporal lobes. Third, we assessed the gradient switching-induced electrode movement by direct visual detection and image analyses.ResultsOn average, RF-induced local heating on the icEEG electrode contacts tested were greater in the orthogonal than parallel configuration, with a maximum increase of 0.2°C during EPI and 1.9°C during FSE. The total local heating was below the 1°C safety limit across all contacts tested during the 70-min icEEG-fMRI session. The induced voltage was within the 100-mV safety limit regardless of the configuration. No gradient switching-induced electrode displacement was observed.ConclusionWe provide evidence that the additional health risks associated with heating, neuronal stimulation, or device movement are low when acquiring fMRI at 3 T in the presence of clinical icEEG electrodes under the conditions reported in this study. High specific absorption ratio sequences such as FSE should be avoided to prevent potential inadvertent tissue heating.

Diffuse noxious inhibitory controls and conditioned pain modulation: a shared neurobiology within the descending pain inhibitory system?

Diffuse noxious inhibitory controls and conditioned pain modulation: a shared neurobiology within the descending pain inhibitory system?

Changes in white matter functional networks during wakefulness and sleep.

Blood oxygenation level‐dependent (BOLD) signals in the white matter (WM) have been demonstrated to encode neural activities by showing structure‐specific temporal correlations during resting‐state and task‐specific imaging of fiber pathways with various degrees of correlations in strength and time delay. Previous neuroimaging studies have shown state‐dependent functional connectivity and regional amplitude of signal fluctuations in brain gray matter across wakefulness and nonrapid eye movement (NREM) sleep cycles. However, the functional characteristics of WM during sleep remain unknown. Using simultaneous electroencephalography and functional magnetic resonance imaging data during wakefulness and NREM sleep collected from 66 healthy participants, we constructed 10 stable WM functional networks using clustering analysis. Functional connectivity between these WM functional networks and regional amplitude of WM signal fluctuations across multiple low‐frequency bands were evaluated. In general, decreased WM functional connectivity between superficial and middle layer WM functional networks was observed from wakefulness to sleep. In addition, functional connectivity between the deep and cerebellar networks was higher during light sleep and lower during both wakefulness and deep sleep. The regional fluctuation amplitude was always higher during light sleep and lower during deep sleep. Importantly, slow‐wave activity during deep sleep negatively correlated with functional connectivity between WM functional networks but positively correlated with fluctuation strength in the WM. These observations provide direct physiological evidence that neural activities in the WM are modulated by the sleep–wake cycle. This study provided the initial mapping of functional changes in WM during sleep.

Segmenting electroencephalography wires reduces radiofrequency shielding artifacts in simultaneous electroencephalography and functional magnetic resonance imaging at 7 T.

PurposeSimultaneous scalp electroencephalography and functional magnetic resonance imaging (EEG‐fMRI) enable noninvasive assessment of brain function with high spatial and temporal resolution. However, at ultra‐high field, the data quality of both modalities is degraded by mutual interactions. Here, we thoroughly investigated the radiofrequency (RF) shielding artifact of a state‐of‐the‐art EEG‐fMRI setup, at 7 T, and design a practical solution to limit this issue.MethodsElectromagnetic field simulations and MR measurements assessed the shielding effect of the EEG setup, more specifically the EEG wiring. The effectiveness of segmenting the wiring with resistors to reduce the transmit field disruption was evaluated on a wire‐only EEG model and a simulation model of the EEG cap.ResultsThe EEG wiring was found to exert a dominant effect on the disruption of the transmit field, whose intensity varied periodically as a function of the wire length. Breaking the electrical continuity of the EEG wires into segments shorter than one quarter RF wavelength in air (25 cm at 7 T) reduced significantly the RF shielding artifacts. Simulations of the EEG cap with segmented wires indicated similar improvements for a moderate increase of the power deposition.ConclusionWe demonstrated that segmenting the EEG wiring into shorter lengths using commercially available nonmagnetic resistors is effective at reducing RF shielding artifacts in simultaneous EEG‐fMRI. This prevents the formation of RF‐induced standing waves, without substantial specific absorption rate (SAR) penalties, and thereby enables benefiting from the functional sensitivity boosts achievable at ultra‐high field.

High-Density Electroencephalography-Informed Multiband Functional Magnetic Resonance Imaging Reveals Rhythm-Specific Activations Within the Trigeminal Nociceptive Network.

The interest in exploring trigeminal pain processing has grown in recent years, mainly due to various pathologies (such as migraine) related to this system. However, research efforts have mainly focused on understanding molecular mechanisms or studying pathological states. On the contrary, non-invasive imaging studies are limited by either spatial or temporal resolution depending on the modality used. This can be overcome by using multimodal imaging techniques such as simultaneous functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). Although this technique has already been applied to neuroscientific research areas and consequently gained insights into diverse sensory systems and pathologies, only a few studies have applied EEG-fMRI in the field of pain processing and none in the trigeminal system. Focusing on trigeminal nociception, we used a trigeminal pain paradigm, which has been well-studied in either modality. For validation, we first acquired stand-alone measures with each imaging modality before fusing them in a simultaneous session. Furthermore, we introduced a new, yet simple, non-parametric correlation technique, which exploits trial-to-trial variance of both measurement techniques with Spearman’s correlations, to consolidate the results gained by the two modalities. This new technique does not presume a linear relationship and needs a few repetitions per subject. We also showed cross-validation by analyzing visual stimulations. Using these techniques, we showed that EEG power changes in the theta-band induced by trigeminal pain correlate with fMRI activation within the brainstem, whereas those of gamma-band oscillations correlate with BOLD signals in higher cortical areas.

Insomnia disorder diagnosed by resting-state fMRI-based SVM classifier

BackgroundThe main classification systems of sleep disorders are based on the subjective self-reported criteria. Objective measures are essential to characterize the nocturnal sleep disturbance, identify daytime impairment, and determine the course of these symptoms. The aim of this study was to establish a resting-state fMRI-based support vector machine (SVM) classifier to diagnose insomnia disorder. MethodsWe enrolled 20 patients with insomnia disorder and 21 healthy controls, and obtained their simultaneous polysomnographic electroencephalography and functional magnetic resonance imaging (EEG-fMRI) recordings. The SVM classifiers were trained to capture insomnia. Classifier performance was quantified by a 5-fold cross validation and on independent test dataset. ResultsThe fMRI-based SVM classifier was able to diagnose insomnia with an accuracy of 89.3% (sensitivity of 90.9%, specificity of 87.7%). The robustness of SVM classifier was encouraging. ConclusionsWe established an encouraging resting-state fMRI-based SVM classifier to automatically diagnose insomnia disorder. As an objective measure for assessing insomnia disorder, it would be of additional value to the current self-reported subjective criteria.

High-Frequency Transcranial Magnetic Stimulation Combined With Functional Magnetic Resonance Imaging Reveals Distinct Activation Patterns Associated With Different Dorsolateral Prefrontal Cortex Stimulation Sites

ObjectivesTranscranial magnetic stimulation (TMS) has been extensively used for the treatment of depression, obsessive-compulsive disorder, and certain neurologic disorders. Despite having promising treatment efficacy, the fundamental neural mechanisms of TMS remain understudied. Materials and MethodsIn this study, 15 healthy adult participants received simultaneous TMS and functional magnetic resonance imaging to map the modulatory effect of TMS when it was applied over three different sites in the dorsolateral prefrontal cortex. Independent component analysis (ICA) was used to identify the networks affected by TMS when applied over the different sites. The standard general linear model (GLM) analysis was used for comparison. ResultsICA showed that TMS affected the stimulation sites as well as remote brain areas, some areas/networks common across all TMS sites, and other areas/networks specific to each TMS site. In particular, TMS site and laterality differences were observed at the left executive control network. In addition, laterality differences also were observed at the dorsal anterior cingulate cortex and dorsolateral/dorsomedial prefrontal cortex. In contrast with the ICA findings, the GLM-based results mainly showed activation of auditory cortices regardless of the TMS sites. ConclusionsOur findings support the notion that TMS could act through a top-down mechanism, indirectly modulating deep subcortical nodes by directly stimulating cortical regions. Clinical Trial RegistrationThe Clinicaltrials.gov registration number for the study is NCT03394066.

Brain Response to a Knee Proprioception Task Among Persons With Anterior Cruciate Ligament Reconstruction and Controls.

Knee proprioception deficits and neuroplasticity have been indicated following injury to the anterior cruciate ligament (ACL). Evidence is, however, scarce regarding brain response to knee proprioception tasks and the impact of ACL injury. This study aimed to identify brain regions associated with the proprioceptive sense of joint position at the knee and whether the related brain response of individuals with ACL reconstruction differed from that of asymptomatic controls. Twenty-one persons with unilateral ACL reconstruction (mean 23 months post-surgery) of either the right (n = 10) or left (n = 11) knee, as well as 19 controls (CTRL) matched for sex, age, height, weight and current activity level, performed a knee joint position sense (JPS) test during simultaneous functional magnetic resonance imaging (fMRI). Integrated motion capture provided real-time knee kinematics to activate test instructions, as well as accurate knee angles for JPS outcomes. Recruited brain regions during knee angle reproduction included somatosensory cortices, prefrontal cortex and insula. Neither brain response nor JPS errors differed between groups, but across groups significant correlations revealed that greater errors were associated with greater ipsilateral response in the anterior cingulate (r = 0.476, P = 0.009), supramarginal gyrus (r = 0.395, P = 0.034) and insula (r = 0.474, P = 0.008). This is the first study to capture brain response using fMRI in relation to quantifiable knee JPS. Activated brain regions have previously been associated with sensorimotor processes, body schema and interoception. Our innovative paradigm can help to guide future research investigating brain response to lower limb proprioception.

Integrated Positron Emission Tomography/Magnetic Resonance Imaging for Resting-State Functional and Metabolic Imaging in Human Brain: What Is Correlated and What Is Impacted.

Integrated positron emission tomography (PET)/magnetic resonance imaging (MRI) could simultaneously obtain both functional MRI (fMRI) and 18F-fluorodeoxyglucose (FDG) PET and thus provide multiparametric information for the analysis of brain metabolism. In this study, we aimed to, for the first time, investigate the interplay of simultaneous fMRI and FDG PET scan using a randomized self-control protocol. In total, 24 healthy volunteers underwent PET/MRI scan for 30–40 min after the injection of FDG. A 22-min brain scan was separated into MRI-off mode (without fMRI pulsing) and MRI-on mode (with fMRI pulsing), with each one lasting for 11 min. We calculated the voxel-wise fMRI metrics (regional homogeneity, amplitude of low-frequency fluctuations, fractional amplitude of low-frequency fluctuations, and degree centrality), resting networks, relative standardized uptake value ratios (SUVr), SUVr slope, and regional cerebral metabolic rate of glucose (rCMRGlu) maps. Paired two-sample t-tests were applied to assess the statistical differences between SUVr, SUVr slope, correlation coefficients of fMRI metrics, and rCMRGlu between MRI-off and MRI-on modes, respectively. The voxel-wise whole-brain SUVr revealed no statistical difference (P > 0.05), while the SUVr slope was significantly elevated in sensorimotor, dorsal attention, ventral attention, control, default, and auditory networks (P < 0.05) during fMRI scan. The task-based group independent-component analysis revealed that the most active network components derived from the combined MRI-off and MRI-on static PET images were frontal pole, superior frontal gyrus, middle temporal gyrus, and occipital pole. High correlation coefficients were found among fMRI metrics with rCMRGlu in both MRI-off and MRI-on mode (P < 0.05). Our results systematically evaluated the impact of simultaneous fMRI scan on the quantification of human brain metabolism from an integrated PET/MRI system.