The preprocessing of diffusion magnetic resonance imaging (dMRI) data involve numerous steps, including the corrections for head motion, susceptibility distortion, low signal‐to‐noise ratio, and ...signal drifting. Researchers or clinical practitioners often need to configure different preprocessing steps depending on disparate image acquisition schemes, which increases the technical threshold for dMRI analysis for nonexpert users. This could cause disparities in data processing approaches and thus hinder the comparability between studies. To make the dMRI data processing steps transparent and adapt to various dMRI acquisition schemes for researchers, we propose a semi‐automated pipeline tool for dMRI named integrated diffusion image operator or iDIO. This pipeline integrates features from a wide range of advanced dMRI software tools and targets at providing a one‐click solution for dMRI data analysis, via adaptive configuration for a set of suggested processing steps based on the image header of the input data. Additionally, the pipeline provides options for post‐processing, such as estimation of diffusion tensor metrics and whole‐brain tractography‐based connectomes reconstruction using common brain atlases. The iDIO pipeline also outputs an easy‐to‐interpret quality control report to facilitate users to assess the data quality. To keep the transparency of data processing, the execution log and all the intermediate images produced in the iDIO's workflow are accessible. The goal of iDIO is to reduce the barriers for clinical or nonspecialist users to adopt the state‐of‐art dMRI processing steps.
To make the dMRI data processing steps transparent and adapt to various dMRI acquisition schemes for researchers, we propose a semi‐automated pipeline tool for dMRI named integrated diffusion image operator or iDIO. This pipeline integrates features from a wide range of advanced dMRI software tools and targets at providing a one‐click solution for dMRI data analysis, via adaptive configuration for a set of suggested processing steps based on the image header of the input data.
The corpus callosum serves as a crucial organization for understanding the information integration between the two hemispheres. Our previous study explored the functional connectivity between the ...corpus callosum and white-matter functional networks (WM-FNs), but the corresponding physical connectivity remains unknown. The current study uses the resting-state fMRI of Human Connectome Project data to identify ten WM-FNs in 108 healthy subjects, and then independently maps the structural and functional connectivity between the corpus callosum and above WM-FNs using the diffusion tensor images (DTI) tractography and resting-state functional connectivity (RSFC). Our results demonstrated that the structural and functional connectivity between the human corpus callosum and WM-FNs have the following high overall correspondence: orbitofrontal WM-FN, DTI map = 89% and RSFC map = 92%; sensorimotor middle WM-FN, DTI map = 47% and RSFC map = 77%; deep WM-FN, DTI map = 50% and RSFC map = 79%; posterior corona radiata WM-FN, DTI map = 82% and RSFC map = 73%. These findings reinforce the notion that the corpus callosum has unique spatial distribution patterns connecting to distinct WM-FNs. However, important differences between the structural and functional connectivity mapping results were also observed, which demonstrated a synergy between DTI tractography and RSFC toward better understanding the information integration of primary and higher-order functional systems in the human brain.
Nonrapid eye movement (NREM) sleep is associated with fading consciousness in humans. Recent neuroimaging studies have demonstrated the spatiotemporal alterations of the brain functional connectivity ...(FC) in NREM sleep, suggesting the changes of information integration in the sleeping brain. However, the common stationarity assumption in FC does not satisfactorily explain the dynamic process of information integration during sleep. The dynamic FC (dFC) across brain networks is speculated to better reflect the time‐varying information propagation during sleep. Accordingly, we conducted simultaneous EEG‐fMRI recordings involving 12 healthy men during sleep and observed dFC across sleep stages using the sliding‐window approach. We divided dFC into two aspects: mean dFC (dFCmean) and variance dFC (dFCvar). A high dFCmean indicates stable brain network integrity, whereas a high dFCvar indicates instability of information transfer within and between functional networks. For the network‐based dFC, the dFCvar were negatively correlated with the dFCmean across the waking and three NREM sleep stages. As sleep deepened, the dFCmean decreased (N0~N1 > N2 > N3), whereas the dFCvar peaked during the N2 stage (N0~N1 < N3 < N2). The highest dFCvar during the N2 stage indicated the unstable synchronizations across the entire brain. In the N3 stage, the overall disrupted network integration was observed through the lowest dFCmean and elevated dFCvar, compared with N0 and N1. Conclusively, when the network specificity (dFCmean) breaks down, the consciousness dissipates with increasing variability of information exchange (dFCvar).
•The state dependency of the neurovascular coupling was reflected by distinctive patterns of the EEG-fMRI spectra correspondence between task and resting conditions.•In the eye-open-eye-close (EOEC) ...task, a phase-amplitude coupling (PAC) was found between EEG alpha-band oscillations and the low-frequency fMRI signals in the visual area.•In the resting state, an amplitude-amplitude coupling (AAC) was demonstrated between gamma-band of EEG-Oz and the high-frequency fMRI signals (0.15–0.25 Hz) in the visual network.•Based on the hilbert-huang transform (HHT), the EEG-fMRI coupling was carried out for both PAC and AAC, exhibiting different sensitivity features between PAC/AAC spectral correspondence maps.
Neurovascular coupling serves as an essential neurophysiological mechanism in functional neuroimaging, which is generally presumed to be robust and invariant across different physiological states, encompassing both task engagement and resting state. Nevertheless, emerging evidence suggests that neurovascular coupling may exhibit state dependency, even in normal human participants. To investigate this premise, we analyzed the cross-frequency spectral correspondence between concurrently recorded electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data, utilizing them as proxies for neurovascular coupling during the two conditions: an eye-open-eye-close (EOEC) task and a resting state. We hypothesized that given the state dependency of neurovascular coupling, EEG-fMRI spectral correspondences would change between the two conditions in the visual system. During the EOEC task, we observed a negative phase-amplitude-coupling (PAC) between EEG alpha-band and fMRI visual activity. Conversely, in the resting state, a pronounced amplitude-amplitude-coupling (AAC) emerged between EEG and fMRI signals, as evidenced by the spectral correspondence between the EEG gamma-band of the midline occipital channel (Oz) and the high-frequency fMRI signals (0.15–0.25 Hz) in the visual network. This study reveals distinct scenarios of EEG-fMRI spectral correspondence in healthy participants, corroborating the state-dependent nature of neurovascular coupling.
We explored the macro-scale neurovascular coupling via the spectral correspondence of concurrent EEG-fMRI signals in a resting-state condition and a eye-open-eye-close (EOEC) task. By decomposing time-frequency maps for both signals, we revealed the EEG-fMRI spectral coupling through the temporal correlations at different frequency bands in the resting state, as compared with those in the EOEC task. Display omitted
Even when brain scans fail to detect a striate lesion, functional evidence for blindsight can be adduced. In the aftermath of an automobile accident, JK became blind. Results of ophthalmic exams ...indicated that the blindness must be cortical. Nevertheless, multiple MRI scans failed to detect structural damage to the striate cortex. Prior to the accident JK had been an athlete; after the accident he retained some athletic abilities, arousing suspicions that he might be engaged in fraud. His residual athletic abilities-e.g., hitting a handball or baseball, or catching a Frisbee-coupled with his experienced blindness, suggested blindsight. But due to the apparent absence of striate lesions, we designed a series of tasks for temporal and spatial dimensions in an attempt to detect
evidence of his disability. Indeed, test results revealed compelling neural evidence that comport with his subjective reports. This spatiotemporal task-related method that includes contrasts with healthy controls, and detailed understanding of the patient's conscious experience, can be generalized for clinical, scientific and forensic investigations of blindsight.
Background
Subjective cognitive decline (SCD) appears in the preclinical stage of the Alzheimer's disease continuum. In this stage, dynamic features are more sensitive than static features to reflect ...early subtle changes in functional brain connectivity. Therefore, we studied local and extended dynamic connectivity of the resting brain of people with SCD to determine their intrinsic brain changes.
Methods
We enrolled cognitively normal older adults from the communities and divided them into SCD and normal control (NC) groups. We used mean dynamic amplitude of low-frequency fluctuation (mdALFF) to evaluate region of interest (ROI)-wise local dynamic connectivity of resting-state functional MRI. The dynamic functional connectivity (dFC) between ROIs was tested by whole-brain-based statistics.
Results
When comparing SCD (
N
= 40) with NC (
N
= 45), mdALFF
mean
decreased at right inferior parietal lobule (IPL) of the frontoparietal network (FPN). Still, it increased at the right middle temporal gyrus (MTG) of the ventral attention network (VAN) and right calcarine of the visual network (VIS). Also, the mdALFF
var
(variance) increased at the left superior temporal gyrus of AUD, right MTG of VAN, right globus pallidum of the cingulo-opercular network (CON), and right lingual gyrus of VIS. Furthermore, mdALFF
mean
at right IPL of FPN are correlated negatively with subjective complaints and positively with objective cognitive performance. In the dFC seeded from the ROIs with local mdALFF group differences, SCD showed a generally lower dFC
mean
and higher dFC
var
(variance) to other regions of the brain. These weakened and unstable functional connectivity appeared among FPN, CON, the default mode network, and the salience network, the large-scale networks of the triple network model for organizing neural resource allocations.
Conclusion
The local dynamic connectivity of SCD decreased in brain regions of cognitive executive control. Meanwhile, compensatory visual efforts and bottom-up attention rose. Mixed decrease and compensatory increase of dynamics of intrinsic brain activity suggest the transitional nature of SCD. The FPN local dynamics balance subjective and objective cognition and maintain cognitive preservation in preclinical dementia. Aberrant triple network model features the dFC alternations of SCD. Finally, the right lateralization phenomenon emerged early in the dementia continuum and affected local dynamic connectivity.
Subjective cognitive decline (SCD) is an early stage of dementia linked to Alzheimer's disease pathology. White matter changes were found in SCD using diffusion tensor imaging, but there are known ...limitations in voxel-wise tensor-based methods. Fixel-based analysis (FBA) can help understand changes in white matter fibers and how they relate to neurodegenerative proteins and multidomain behavior data in individuals with SCD.
Healthy adults with normal cognition were recruited in the Northeastern Taiwan Community Medicine Research Cohort in 2018-2022 and divided into SCD and normal control (NC). Participants underwent evaluations to assess cognitive abilities, mental states, physical activity levels, and susceptibility to fatigue. Neurodegenerative proteins were measured using an immunomagnetic reduction technique. Multi-shell diffusion MRI data were collected and analyzed using whole-brain FBA, comparing results between groups and correlating them with multidomain assessments.
The final enrollment included 33 SCD and 46 NC participants, with no significant differences in age, sex, or education between the groups. SCD had a greater fiber-bundle cross-section than NC (pFWE < 0.05) at bilateral frontal superior longitudinal fasciculus II (SLFII). These white matter changes correlate negatively with plasma Aβ42 level (r = -0.38, p = 0.01) and positively with the AD8 score for subjective cognitive complaints (r = 0.42, p = 0.004) and the Hamilton Anxiety Rating Scale score for the degree of anxiety (Ham-A, r = 0.35, p = 0.019). The dimensional analysis of FBA metrics and blood biomarkers found positive correlations of plasma neurofilament light chain with fiber density at the splenium of corpus callosum (pFWE < 0.05) and with fiber-bundle cross-section at the right thalamus (pFWE < 0.05). Further examination of how SCD grouping interacts between the correlations of FBA metrics and multidomain assessments showed interactions between the fiber density at the corpus callosum with letter-number sequencing cognitive score (pFWE < 0.01) and with fatigue to leisure activities (pFWE < 0.05).
Based on FBA, our investigation suggests white matter structural alterations in SCD. The enlargement of SLFII's fiber cross-section is linked to plasma Aβ42 and neuropsychiatric symptoms, which suggests potential early axonal dystrophy associated with Alzheimer's pathology in SCD. The splenium of the corpus callosum is also a critical region of axonal degeneration and cognitive alteration for SCD.
Sleep inertia (SI) is a time period during the transition from sleep to wakefulness wherein individuals perceive low vigilance with cognitive impairments; SI is generally identified by longer ...reaction times (RTs) in attention tasks immediately after awakening followed by a gradual RT reduction along with waking time. The sluggish recovery of vigilance in SI involves a dynamic process of brain functions, as evidenced in recent functional magnetic resonance imaging (fMRI) studies in within-network and between-network connectivity. However, these fMRI findings were generally based on the presumption of unchanged neurovascular coupling (NVC) before and after sleep, which remains an uncertain factor to be investigated. Therefore, we recruited 12 young participants to perform a psychomotor vigilance task (PVT) and a breath-hold task of cerebrovascular reactivity (CVR) before sleep and thrice after awakening (A1, A2, and A3, with 20 min intervals in between) using simultaneous electroencephalography (EEG)-fMRI recordings. If the NVC were to hold in SI, we hypothesized that time-varying consistencies could be found between the fMRI response and EEG beta power, but not in neuron-irrelevant CVR. Results showed that the reduced accuracy and increased RT in the PVT upon awakening was consistent with the temporal patterns of the PVT-induced fMRI responses (thalamus, insula, and primary motor cortex) and the EEG beta power (Pz and CP1). The neuron-irrelevant CVR did not show the same time-varying pattern among the brain regions associated with PVT. Our findings imply that the temporal dynamics of fMRI indices upon awakening are dominated by neural activities. This is the first study to explore the temporal consistencies of neurovascular components on awakening, and the discovery provides a neurophysiological basis for further neuroimaging studies regarding SI.
Diffusion Tensor Imaging (DTI) tractography has been widely used in brain tumor surgery to ensure thorough resection and minimize functional damage. However, due to enhanced anisotropic uncertainty ...in the area with peritumoral edema, diffusion tractography is generally not practicable leading to high false-negative results in neural tracking. In this study, we evaluated the usefulness of the neurite orientation dispersion and density imaging (NODDI) derived tractography for investigating structural heterogeneity of the brain in patients with brain tumor. A total of 24 patients with brain tumors, characterized by peritumoral edema, and 10 healthy counterparts were recruited from 2014 to 2021. All participants underwent magnetic resonance imaging. Moreover, we used the images obtained from the healthy participants for calibrating the orientation dispersion threshold for NODDI-derived corticospinal tract (CST) reconstruction. Compared to DTI, NODDI-derived tractography has a great potential to improve the reconstruction of fiber tracking through regions of vasogenic edema. The regions with edematous CST in NODDI-derived tractography demonstrated a significant decrease in the intracellular volume fraction (VF
ic
,
p
< 0.000) and an increase in the isotropic volume fraction (VF
iso
,
p
< 0.014). Notably, the percentage of the involved volume of the concealed CST and lesion-to-tract distance could reflect the motor function of the patients. After the tumor resection, four patients with 1–5 years follow-up were showed subsidence of the vasogenic edema and normal CST on DTI tractography. NODDI-derived tractography revealed tracts within the edematous area and could assist neurosurgeons to locate the neural tracts that are otherwise not visualized by conventional DTI tractography.
Objective
The objective of this article is to investigate the neurological substrates associated with medication overuse (MO) in patients with chronic migraine (CM).
Methods
We recruited age- and ...sex-matched CM patients with MO (CMwMO), CM patients without MO (CMwoMO), and healthy controls (HCs). Magnetic resonance T1-weighted images were processed by voxel-based morphometry, and the findings were correlated with clinical variables and treatment responses.
Results
A total of 66 patients with CM (half with MO) and 33 HCs completed the study. Patients with CMwMO compared to the patients with CMwoMO showed gray matter volume (GMV) decrease in the orbitofrontal cortex and left middle occipital gyrus as well as GMV increase in the left temporal pole/parahippocampus. The GMV changes explained 31.1% variance of the analgesics use frequency. The patients who responded to treatment had greater GMV in the orbitofrontal cortex (p = 0.028). Patients with CM (with and without MO), compared with HCs, had decreased GMV at multiple brain areas including the frontal, temporal and occipital lobes, precuneus and cerebellum.
Conclusions
Our study showed GMV changes in CMwMO patients compared to the CMwoMO patients. These three cerebral regions accounted for significant variance in analgesics use frequency. Moreover, the GMV of the orbitofrontal cortex was predictive of the response to MO treatments.
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