Subject head motion during the acquisition of diffusion-weighted imaging (DWI) of the brain induces artifacts and affects image quality. Information about the frequency and extent of motion could reveal which aspects of motion correction are most necessary. Therefore, we investigate the extent of translation and rotation among participants, and how the motion changes during the scan acquisition. We analyze 5,380 DWI scans from 1,034 participants. We measure the rotations and translations in the sagittal, coronal and transverse planes needed to align the volumes to the first and previous volumes, as well as the displacement. The different types of motion are compared with each other and compared over time. The largest rotation (per minute) is around the right - left axis (median 0.378 °/min, range 0.000 - 11.466°) and the largest translation (per minute) is along the anterior - posterior axis (median 1.867 mm/min, range 0.000 - 10.944 mm). We additionally observe that spikes in movement occur at the beginning of the scan, particularly in anterior - posterior translation. The results show that all scans are affected by subtle head motion, which may impact subsequent image analysis.

OBJECTIVE: To provide a navigator-based run-time motion and first-order field correction for three-dimensional human brain imaging with high precision, minimal calibration and acquisition, and fast processing.
METHODS: A complex-valued linear perturbation model with feedback control is extended to estimate and correct for gradient shim fields using orbital navigators (2.3 ms). Two approaches for sensitizing the model to gradient fields are presented, one based on finite differences with three additional navigators, and another projection-based approximation requiring no additional navigators. A mechanism for noise decorrelation of the matrix and the data is proposed and evaluated to reduce unwanted parameter biases.
RESULTS: The rigid motion and first-order field control achieves robust motion and gradient shim corrections improving image quality in a series of phantom and in vivo experiments with varying field conditions. In phantom scans, magnet drifts, forced gradient field perturbations and field distortions from shifts of a second bottle phantom are successfully corrected. Field estimates of the magnet drifts are in good agreement with concurrent field probe measurements. For in vivo scans, the proposed method mitigates field variations from torso motions while being robust to head motion. In vivo gradient field precisions were 30   nT / m $$ 30\\;\\mathrm{nT}/\\mathrm{m} $$ along with single-digit micrometer and millidegree rigid precisions.
CONCLUSIONS: The navigator-based method achieves accurate, high-precision run-time motion and field corrections with low sequence impact and calibration requirements.

Deep learning can be used effectively to predict participants\' age from brain magnetic resonance imaging (MRI) data, and a growing body of evidence suggests that the difference between predicted and chronological age-referred to as brain-predicted age difference (brain-PAD)-is related to various neurological and neuropsychiatric disease states. A crucial aspect of the applicability of brain-PAD as a biomarker of individual brain health is whether and how brain-predicted age is affected by MR image artifacts commonly encountered in clinical settings. To investigate this issue, we trained and validated two different 3D convolutional neural network architectures (CNNs) from scratch and tested the models on a separate dataset consisting of motion-free and motion-corrupted T1-weighted MRI scans from the same participants, the quality of which were rated by neuroradiologists from a clinical diagnostic point of view. Our results revealed a systematic increase in brain-PAD with worsening image quality for both models. This effect was also observed for images that were deemed usable from a clinical perspective, with brains appearing older in medium than in good quality images. These findings were also supported by significant associations found between the brain-PAD and standard image quality metrics indicating larger brain-PAD for lower-quality images. Our results demonstrate a spurious effect of advanced brain aging as a result of head motion and underline the importance of controlling for image quality when using brain-predicted age based on structural neuroimaging data as a proxy measure for brain health.

BACKGROUND: Asymmetry in involuntary trunk motion during voluntary movements of the lower extremities is a risk factor for musculoskeletal injuries and may be related to core stability. Core stability plays a pivotal role in maintaining postural stability during distal segment movements. Because mediolateral head motion partially represents trunk motion during rhythmic movements, controlling it can help ensure symmetric trunk motion. This study aimed to investigate the relationship between core stability and asymmetric trunk motion during rhythmic movements, and to evaluate the effects of feedback music on mediolateral head motion.
METHODS: We developed a system that uses a wireless earbud and a high-resolution inertial measurement unit sensor to measure head angle and provide feedback music. When the head angle exceeds a predefined threshold, the music is muted in the earbud on the side of the head tilt. In our lab-based study, we measured head angles during cycling at 70% of maximum speed using this self-developed system, and compared them between individuals with good (Sahrmann core stability test: 2-5 level) and poor core stability (0-1 level). The amplitude of mediolateral head motion was represented by the difference between the left and right peak angles, and the symmetry in mediolateral head motion was represented by the average of left and right peak angles.
RESULTS: Individuals with poor core stability demonstrated significantly greater amplitude of, and less symmetry in, mediolateral head motion than those with good core stability. Additionally, feedback music significantly reduced the amplitude of mediolateral head motion in both the good- and poor-core-stability groups.
CONCLUSIONS: Our findings indicate that core stability is crucial for maintaining symmetric head motion during rhythmic movements like cycling. Feedback music could serve as an effective tool for promoting symmetry in head motion and thus preventing musculoskeletal injuries.

Oxytocin is a neuropeptide associated with prosocial behaviors, such as parent-child bonding, eye contact, and sexual activity. Intranasally-administered oxytocin has been widely used to study its effects on the brain using functional magnetic resonance imaging. Head motion is a significant confounding variable which was assessed as part of a double blind, placebo-controlled crossover study. Twenty-four mothers with drug addiction problems were initially recruited, along with 22 healthy control mothers, to test whether intranasal oxytocin enhances functional brain responses to images of their own versus unknown infant faces. Significant differences in head motion between oxytocin/placebo conditions and addiction/control groups were discovered. Administration of intranasal oxytocin was associated with more frequent counts of head motion exceeding 3 mm of framewise displacement, independent of group status (z=2.89, p=0.004). This effect was seen more strongly in the control group (z=2.30, p=0.02) than the addiction group (z=1.77, p=0.08). The addiction group was more likely to show increased head motion, independent of oxytocin or placebo condition (z=2.21, p=0.03). When examining the mean head motion across all time points, as opposed to the count of large movements, oxytocin\'s effect was limited to the addiction group (z=2.58, p=0.01), with a significant group by condition interaction effect observed. Intranasally-administered oxytocin may therefore have a confounding effect on functional MRI scanning results via its independent effect on head motion. These findings should be examined and replicated in other clinical populations.

UNASSIGNED: Chronic neck pain (CNP) can lead to altered gait which is worse when combined with head movement. Gait parameters for indicating speed and symmetry have not been thoroughly investigated in older adults with CNP. This study aimed to compare gait performance in term of speed and symmetry in older adults with and without CNP during walking with head movement.
UNASSIGNED: Fifty young older adults, consisting of 36 healthy controls without neck pain (OLDs) and 14 older adults with CNP, participated in the study. Participants completed the Neck Disability Index and Activities-specific Balance Confidence Scale. The 10-Meter Walk Test (10MWT) was used to assess gait performance. Participants were instructed to walk at preferred speed under three different head movement patterns: no head movement (NM), horizontal head movement (HM), and vertical head movement (VM). The Inertial Measurement Unit was used to capture gait performance, and its software was used to analyze gait variables; gait speed, Locomotor Rehabilitation Index (LRI), gait asymmetry index, Phase Coordination Index (PCI).
UNASSIGNED: The CNP group reported moderate neck pain with mild disability in activities of daily living, and less balance confidence than the OLD group (p < 0.05). The CNP group showed significantly slower gait speed and lower LRI during walking with both the HM and VM (p < 0.05), which corresponded to lower stride length and cadence. The gait asymmetry index in the CNP group was significantly higher than the OLD group during walking with VM (p < 0.05), whereas the PCI was significantly higher than the OLD group during walking with both HM and VM (p < 0.05).
UNASSIGNED: Chronic neck pain affects both speed and symmetry when walking with head movement. Gait parameters in this study could be implemented to identify changes in speed and symmetry of gait in older adults with CNP who have mild disability and high physical functioning.

Head motion correction is particularly challenging in diffusion-weighted MRI (dMRI) scans due to the dramatic changes in image contrast at different gradient strengths and directions. Head motion correction is typically performed using a Gaussian Process model implemented in FSL\'s Eddy. Recently, the 3dSHORE-based SHORELine method was introduced that does not require shell-based acquisitions, but it has not been previously benchmarked. Here we perform a comprehensive evaluation of both methods on realistic simulations of a software fiber phantom that provides known ground-truth head motion. We demonstrate that both methods perform remarkably well, but that performance can be impacted by sampling scheme and the extent of head motion and the denoising strategy applied before head motion correction. Furthermore, we find Eddy benefits from denoising the data first with MP-PCA. In sum, we provide the most extensive known benchmarking of dMRI head motion correction, together with extensive simulation data and a reproducible workflow. PRACTITIONER POINTS: Both Eddy and SHORELine head motion correction methods performed quite well on a large variety of simulated data. Denoising with MP-PCA can improve head motion correction performance when Eddy is used. SHORELine effectively corrects motion in non-shelled diffusion spectrum imaging data.

Knowing when seizures occur may help patients and can also provide insight into epileptogenesis mechanisms. We recorded seizures over periods of several days in the Genetic Absence Epileptic Rat from Strasbourg (GAERS) model of absence epilepsy, while we monitored behavioral activity with a combined head accelerometer (ACCEL), neck electromyogram (EMG), and electrooculogram (EOG). The three markers consistently discriminated between states of behavioral activity and rest. Both GAERS and control Wistar rats spent more time in rest (55-66%) than in activity (34-45%), yet GAERS showed prolonged continuous episodes of activity (23 vs. 18 min) and rest (34 vs. 30 min). On average, seizures lasted 13 s and were separated by 3.2 min. Isolated seizures were associated with a decrease in the power of the activity markers from steep for ACCEL to moderate for EMG and weak for EOG, with ACCEL and EMG power changes starting before seizure onset. Seizures tended to occur in bursts, with the probability of seizing significantly increasing around a seizure in a window of ±4 min. Furthermore, the seizure rate was strongly increased for several minutes when transitioning from activity to rest. These results point to mechanisms that control behavioral states as determining factors of seizure occurrence.

OBJECTIVE: Navigator-based correction of rigid-body motion reconciling high precision with minimal acquisition, minimal calibration and simple, fast processing.
METHODS: A short orbital navigator (2.3 ms) is inserted in a three-dimensional (3D) gradient echo sequence for human head imaging. Head rotation and translation are determined by linear regression based on a complex-valued model built either from three reference navigators or in a reference-less fashion, from the first actual navigator. Optionally, the model is expanded by global phase and field offset. Run-time scan correction on this basis establishes servo control that maintains validity of the linear picture by keeping its expansion point stable in the head frame of reference. The technique is assessed in a phantom and demonstrated by motion-corrected imaging in vivo.
RESULTS: The proposed approach is found to establish stable motion control both with and without reference acquisition. In a phantom, it is shown to accurately detect motion mimicked by rotation of scan geometry as well as change in global B0 . It is demonstrated to converge to accurate motion estimates after perturbation well beyond the linear signal range. In vivo, servo navigation achieved motion detection with precision in the single-digit range of micrometers and millidegrees. Involuntary and intentional motion in the range of several millimeters were successfully corrected, achieving excellent image quality.
CONCLUSIONS: The combination of linear regression and feedback control enables prospective motion correction for head imaging with high precision and accuracy, short navigator readouts, fast run-time computation, and minimal demand for reference data.

Objective.Head motion correction (MC) is an essential process in brain positron emission tomography (PET) imaging. We have used the Polaris Vicra, an optical hardware-based motion tracking (HMT) device, for PET head MC. However, this requires attachment of a marker to the subject\'s head. Markerless HMT (MLMT) methods are more convenient for clinical translation than HMT with external markers. In this study, we validated the United Imaging Healthcare motion tracking (UMT) MLMT system using phantom and human point source studies, and tested its effectiveness on eight18F-FPEB and four11C-LSN3172176 human studies, with frame-based region of interest (ROI) analysis. We also proposed an evaluation metric, registration quality (RQ), and compared it to a data-driven evaluation method, motion-corrected centroid-of-distribution (MCCOD).Approach.UMT utilized a stereovision camera with infrared structured light to capture the subject\'s real-time 3D facial surface. Each point cloud, acquired at up to 30 Hz, was registered to the reference cloud using a rigid-body iterative closest point registration algorithm.Main results.In the phantom point source study, UMT exhibited superior reconstruction results than the Vicra with higher spatial resolution (0.35 ± 0.27 mm) and smaller residual displacements (0.12 ± 0.10 mm). In the human point source study, UMT achieved comparable performance as Vicra on spatial resolution with lower noise. Moreover, UMT achieved comparable ROI values as Vicra for all the human studies, with negligible mean standard uptake value differences, while no MC results showed significant negative bias. TheRQevaluation metric demonstrated the effectiveness of UMT and yielded comparable results to MCCOD.Significance.We performed an initial validation of a commercial MLMT system against the Vicra. Generally, UMT achieved comparable motion-tracking results in all studies and the effectiveness of UMT-based MC was demonstrated.