Motor planning is not restricted to only one hemisphere: evidence from ERPs in individuals with hemiplegic cerebral palsy.

The evidence for the hemispheric specialization of motor planning reveals several inconsistencies between the left-lateralized hypothesis and a distributed system across the hemispheres. We compared participants with left hemiplegic cerebral palsy (HCP) to right-handed control subjects in this study's first experiment by inviting them to perform a motor planning task. Participants were required to release the start button, grasp a hexagon, and rotate it according to the instructions. In the second experiment, we compared left-HCP subjects with right-HCP subjects inviting them to perform the same task (we used the data for left-HCP subjects from the first experiment). P2 amplitude, as well as planning time, grasping time, releasing time, and initial grip selection planning patterns, were used as outcome measures in both experiments. The first experiment revealed that controls acted more quickly and chose more effective planning patterns. Also, the P2 amplitude was smaller in left-HCP subjects than in control subjects. No significant group effect was observed in the second experiment for any movement-related measure or P2. At the neural level, however, there was an interaction between 'region' and 'group,' indicating the distinction between the two groups in the right region. The results are discussed in terms of motor planning's hemispheric distribution and individual differences in the HCP group.

On-Body Placement of Wearable Safety Promotion Devices Based on Wireless Communication for Construction Workers-on-Foot: State-of-the-Art Review.

High auditory noise levels and limited visibility are often considered among the main factors that hinder seamless communication on construction sites. Many previous research studies have leveraged technology to overcome these obstacles and communicate using the hearing, sight and touch senses. However, the technological efficacy does not secure the users' perceptivity of the wireless communication devices. Statistical data regarding the number of fatal accidents on construction sites have remained steady despite regular efforts. This study analyzed prior research on wearable safety promotion devices for personnel that move around the jobsite on foot. A seven-point checklist was utilized to shortlist prior studies (2005-2021) attempting to provide safety information wirelessly to the construction workers-on-foot. The reasoning behind various on-body placements was investigated along with the information conveyed using the three communication modalities. A novel communication network is also introduced to visualize the technical details. Lastly, limitations and future recommendations have been presented to gain insights about the factors that might affect the placement of the wearable safety promotion devices.

Mood and Behaviors of Adolescents With Depression in a Longitudinal Study Before and During the COVID-19 Pandemic.

OBJECTIVE: To investigate whether, compared to pre-pandemic levels, depressive and anxiety symptoms in adolescents with depression increased during the pandemic. METHOD: We used data from National Institute of Mental Health Characterization and Treatment of Depression (NIMH CAT-D) cohort, a longitudinal case-control study that started pre-pandemic. Most of the participants are from the states of Maryland and Virginia in the United States. We compared depressive symptoms (1,820 measurements; 519 measurements pre-pandemic and 1,302 during the pandemic) and anxiety symptoms (1,800 measurements; 508 measurements pre-pandemic and 1,292 ratings during the pandemic) of 166 adolescents (109 girls, 96 adolescents with depression) before and during the pandemic. Data were collected during yearly clinical visits, interim 4-month follow-up visits, inpatient stays, and weekly outpatient sessions, with additional data collection during the pandemic. Pre-pandemic, healthy volunteers (HVs) had a median of 1 depressive and anxiety rating (range, 1-3), and adolescents with depression had a median of 2 ratings (anxiety rating range, 1-25; depressive rating range, 1-26). During the pandemic, HVs had a median of 8 anxiety ratings and 9 depressive ratings (range, 1-13), and adolescents with depression had a median of 7 anxiety and depressive ratings (range, 1-29). We also analyzed adolescent- and parent-reported behaviors in the CoRonavIruS Health Impact Survey (CRISIS), totaling 920 self-reported measures for 164 adolescents (112 girls, 92 adolescents with depression). HVs had a median of 7 surveys (range, 1-8), and adolescents with depression had a median of 5 surveys (range, 1-8). RESULTS: Pre-pandemic, adolescents with depression had a mean depressive score of 11.16 (95% CI = 10.10, 12.22) and HVs had a mean depressive score of 1.76 (95% CI = 0.40, 3.13), a difference of 9.40 points (95% CI = 7.78, 11.01). During the pandemic, this difference decreased by 22.6% (2.05 points, 95% CI = 0.71, 3.40, p = .003) due to 0.89 points decrease in severity of scores in adolescents with depression (95% CI = 0.08, 1.70, p = .032) and 1.16 points increase in HVs' depressive symptoms (95% CI = 0.10, 2.23, p = .032). Compared to their pre-pandemic levels, adolescents with depression reported overall lower anxiety symptoms during the pandemic. Parent-on-child reports also were consistent with these results. CONCLUSION: Contrary to our hypothesis, we found that both depressive and anxiety symptoms were lower for adolescents with depression during the pandemic compared to before. In contrast, the depression scores for the HVs were higher during the pandemic relative to their pre-pandemic ratings; these scores remained much lower than those of adolescents with depression. CLINICAL TRIAL REGISTRATION INFORMATION: Characterization and Treatment of Adolescent Depression; https://clinicaltrials.gov/; NCT03388606.

Correction: Ntakolia et al. An Explainable Machine Learning Approach for COVID-19's Impact on Mood States of Children and Adolescents during the First Lockdown in Greece. Healthcare 2022, 10, 149.

Argyris Stringaris was initially included as an author in the original publication [...].

An Explainable Machine Learning Approach for COVID-19's Impact on Mood States of Children and Adolescents during the First Lockdown in Greece.

The global spread of COVID-19 led the World Health Organization to declare a pandemic on 11 March 2020. To decelerate this spread, countries have taken strict measures that have affected the lifestyles and economies. Various studies have focused on the identification of COVID-19's impact on the mental health of children and adolescents via traditional statistical approaches. However, a machine learning methodology must be developed to explain the main factors that contribute to the changes in the mood state of children and adolescents during the first lockdown. Therefore, in this study an explainable machine learning pipeline is presented focusing on children and adolescents in Greece, where a strict lockdown was imposed. The target group consists of children and adolescents, recruited from children and adolescent mental health services, who present mental health problems diagnosed before the pandemic. The proposed methodology imposes: (i) data collection via questionnaires; (ii) a clustering process to identify the groups of subjects with amelioration, deterioration and stability to their mood state; (iii) a feature selection process to identify the most informative features that contribute to mood state prediction; (iv) a decision-making process based on an experimental evaluation among classifiers; (v) calibration of the best-performing model; and (vi) a post hoc interpretation of the features' impact on the best-performing model. The results showed that a blend of heterogeneous features from almost all feature categories is necessary to increase our understanding regarding the effect of the COVID-19 pandemic on the mood state of children and adolescents.

Clinical utility of family history of depression for prognosis of adolescent depression severity and duration assessed with predictive modeling.

BACKGROUND: Family history of depression (FHD) is a known risk factor for the new onset of depression. However, it is unclear if FHD is clinically useful for prognosis in adolescents with current, ongoing, or past depression. This preregistered study uses a longitudinal, multi-informant design to examine whether a child's FHD adds information about future depressive episodes and depression severity applying state-of-the-art predictive out-of-sample methodology. METHODS: We examined data in adolescents with current or past depression (age 11-17 years) from the National Institute of Mental Health Characterization and Treatment of Adolescent Depression (CAT-D) study. We asked whether a history of depression in a first-degree relative was predictive of depressive episode duration (72 participants) and future depressive symptom severity in probands (129 participants, 1,439 total assessments). RESULTS: Family history of depression, while statistically associated with time spent depressed, did not improve predictions of time spent depressed, nor did it improve models of change in depression severity measured by self- or parent-report. CONCLUSIONS: Family history of depression does not improve the prediction of the course of depression in adolescents already diagnosed with depression. The difference between statistical association and predictive models highlights the importance of assessing predictive performance when evaluating questions of clinical utility.

Differences in behavioral and cortical indices in pianists and non-musicians during a non-musical motor planning task: An event-related potential study.

Psychological studies have shown that music has an impact on human cognitive function. We aimed to compare the performance and neural activity of pianists and non-musicians during a non-musical motor-planning task. In addition, we investigated the effect of task complexity on the characteristics of the behavioral and neural responses. The participants had to grasp a hexagonal knob with their right hand and rotate it 60° or 180° clockwise (CW) or counterclockwise (CCW). We examined the groups in terms of the amplitude of the P2 component in the event-related potential (at the neural level) and the planning time, grasping time, releasing time, and planning pattern for initial grip selection (at the behavioral level). At the behavioral level, we observed no significant difference between groups, while at the neural level; we found an interaction between direction and group indicating that pianists showed lower P2 amplitude in the CW directions. However, there was no significant difference between groups in the CCW direction. A significant main effect of rotation was revealed at both the neural and behavioral levels; increasing the rotation angle led to an increase in the planning time and the P2 amplitude, indicating a complexity effect. In conclusion, we observed that pianists had lower P2 amplitude in lateral movements than non-musicians; however, due to the lack of behavioral group differences, further research is warranted to support the far-transfer theory in this field.

Motor control times and strategies in left- and right-handed participants: Behavioral evidence for the hemispheric distribution of motor planning.

Background: There is conflicting evidence in favor of the hemispheric distribution of motor planning. Some studies supported the left-hemisphere-dominance hypothesis for motor planning and claimed that the left-hemisphere has a crucial function in motor control even in left-handers. The present study aimed to compare the right- and left-handed participants on motor planning ability and to investigate the performance of their dominant hands in a specific action selection task. Also, the effect of task complexity was assessed. Methods: Twenty right-handers and 20 left-handers performed an action selection task. The participants had to grasp a hexagonal knob with their dominant hand and consequently rotated it 60° or 180 ° clockwise or counterclockwise. Depending on our objects, we used mixed factorial ANOVA and the groups were examined in terms of the planning time, grasping time, releasing time and planning pattern for initial grip selection. The SPSS 19 was used for analyzing the data and p≤0.05 was considered as the significant level. Results: No significant differences were observed between the two groups. The movement-related measures revealed a main effect of rotation (p˂0.001). However, a significant interaction between direction × planning pattern × group (p˂0.001) indicated a preferential bias for rotatory movements in the medial direction which is consistent with the "medial over lateral advantage". Conclusion: Both left- and right-handed participants had a similar motor planning ability while performing a planning task with their dominant hands. Because our study was behavioral, it only provided a test of the left-hemisphere hypothesis of motor planning.

Improved reproducibility of diffusion MRI of the human brain with a four-way blip-up and down phase-encoding acquisition approach.

PURPOSE: To assess the effects of blip-up and -down echo planar imaging (EPI) acquisition designs, with different choices of phase-encoding directions (PEDs) on the reproducibility of diffusion MRI (dMRI)-derived metrics in the human brain. METHODS: Diffusion MRI data in seven subjects were acquired five times, each with five different protocols. The base design included 64 diffusion directions acquired with anterior-posterior (AP) PED, the first and second protocols added reverse phase-encoded b=0s/mm2 posterior-anterior (PA) PED images. The third one included 32 directions all with PED acquisitions with opposite polarity (AP and PA). The fourth protocol, also with 32 unique directions used four PEDs (AP, PA, right-left (RL), and left-right (LR)). The scan time was virtually identical for all protocols. The variability of diffusion MRI metrics for each subject and each protocol was computed across the different sessions. RESULTS: The highest reproducibility for all dMRI metrics was obtained with protocol four (AP/PA-RL/LR, ie, four-way PED). Protocols that used only b=0s/mm2 for distortion correction, which are the most widely used designs, had the lowest reproducibility. CONCLUSIONS: An acquisition design with four PEDs, including all DWIs in addition to b=0s/mm2 images should be used to achieve high reproducibility in diffusion MRI studies.

Brain phenotyping in Moebius syndrome and other congenital facial weakness disorders by diffusion MRI morphometry.

In this study, we used a novel imaging technique, DTI (diffusion tensor imaging)-driven tensor-based morphometry, to investigate brain anatomy in subjects diagnosed with Moebius syndrome (n = 21), other congenital facial weakness disorders (n = 9) and healthy controls (n = 15). First, we selected a subgroup of subjects who satisfied the minimum diagnostic criteria for Moebius syndrome with only mild additional neurological findings. Compared to controls, in this cohort, we found a small region of highly significant volumetric reduction in the paramedian pontine reticular formation and the medial longitudinal fasciculus, important structures for the initiation and coordination of conjugate horizontal gaze. Subsequently, we tested if volume measurements from this region could help differentiate individual subjects of the different cohorts that were included in our study. We found that this region allowed discriminating Moebius syndrome subjects from congenital facial weakness disorders and healthy controls with high sensitivity (94%) and specificity (89%). Interestingly, this region was normal in congenital facial weakness subjects with oculomotor deficits of myopathic origin, who would have been classified as Moebius on the basis of purely clinical diagnostic criteria, indicating a potential role for diffusion MRI morphometry for differential diagnosis in this condition. When the entire Moebius syndrome cohort was compared to healthy controls, in addition to this 'landmark' region, other areas of significantly reduced volume in the brainstem emerged, including the location of the nuclei and fibres of cranial nerve VI (abducens nerve), and fibres of cranial nerve VII (facial nerve), and a more rostral portion of the medial longitudinal fasciculus. The high sensitivity and specificity of DTI-driven tensor-based morphometry in reliably detecting very small areas of volumetric abnormality found in this study suggest broader applications of this analysis in personalized medicine to detect hypoplasia or atrophy of small pathways and/or brainstem nuclei in other neurological disorders.

Hypoplasia of cerebellar afferent networks in Down syndrome revealed by DTI-driven tensor based morphometry.

Quantitative magnetic resonance imaging (MRI) investigations of brain anatomy in children and young adults with Down syndrome (DS) are limited, with no diffusion tensor imaging (DTI) studies covering that age range. We used DTI-driven tensor based morphometry (DTBM), a novel technique that extracts morphometric information from diffusion data, to investigate brain anatomy in 15 participants with DS and 15 age- and sex-matched typically developing (TD) controls, ages 6-24 years (mean age ~17 years). DTBM revealed marked hypoplasia of cerebellar afferent systems in DS, including fronto-pontine (middle cerebellar peduncle) and olivo-cerebellar (inferior cerebellar peduncle) connections. Prominent gray matter hypoplasia was observed in medial frontal regions, the inferior olives, and the cerebellum. Very few abnormalities were detected by classical diffusion MRI metrics, such as fractional anisotropy and mean diffusivity. Our results highlight the potential importance of cerebro-cerebellar networks in the clinical manifestations of DS and suggest a role for DTBM in the investigation of other brain disorders involving white matter hypoplasia or atrophy.

Detection and Distinction of Mild Brain Injury Effects in a Ferret Model Using Diffusion Tensor MRI (DTI) and DTI-Driven Tensor-Based Morphometry (D-TBM).

Mild traumatic brain injury (mTBI) is highly prevalent but lacks both research tools with adequate sensitivity to detect cellular alterations that accompany mild injury and pre-clinical models that are able to robustly mimic hallmark features of human TBI. To address these related challenges, high-resolution diffusion tensor MRI (DTI) analysis was performed in a model of mild TBI in the ferret - a species that, unlike rodents, share with humans a gyrencephalic cortex and high white matter (WM) volume. A set of DTI image analysis tools were optimized and implemented to explore key features of DTI alterations in ex vivo adult male ferret brains (n = 26), evaluated 1 day to 16 weeks after mild controlled cortical impact (CCI). Using template-based ROI analysis, lesion overlay mapping and DTI-driven tensor-based morphometry (D-TBM) significant differences in DTI and morphometric values were found and their dependence on time after injury evaluated. These observations were also qualitatively compared with immunohistochemistry staining of neurons, astrocytes, and microglia in the same tissue. Focal DTI abnormalities including reduced cortical diffusivity were apparent in 12/13 injured brains with greatest lesion extent found acutely following CCI by ROI overlay maps and reduced WM FA in the chronic period was observed near to the CCI site (ANOVA for FA in focal WM: time after CCI p = 0.046, brain hemisphere p = 0.0012) often in regions without other prominent MRI abnormalities. Global abnormalities were also detected, especially for WM regions, which demonstrated reduced diffusivity (ANOVA for Trace: time after CCI p = 0.007) and atrophy that appeared to become more extensive and bilateral with longer time after injury (ANOVA for D-TBM Log of the Jacobian values: time after CCI p = 0.007). The findings of this study extend earlier work in rodent models especially by evaluation of focal WM abnormalities that are not influenced by partial volume effects in the ferret. There is also substantial overlap between DTI and morphometric findings in this model and those from human studies of mTBI implying that the combination of DTI tools with a human-similar model system can provide an advantageous and informative approach for mTBI research.

Tensor-based morphometry using scalar and directional information of diffusion tensor MRI data (DTBM): Application to hereditary spastic paraplegia.

Tensor-based morphometry (TBM) performed using T1-weighted images (T1WIs) is a well-established method for analyzing local morphological changes occurring in the brain due to normal aging and disease. However, in white matter regions that appear homogeneous on T1WIs, T1W-TBM may be inadequate for detecting changes that affect specific pathways. In these regions, diffusion tensor MRI (DTI) can identify white matter pathways on the basis of their different anisotropy and orientation. In this study, we propose performing TBM using deformation fields constructed using all scalar and directional information provided by the diffusion tensor (DTBM) with the goal of increasing sensitivity in detecting morphological abnormalities of specific white matter pathways. Previously, mostly fractional anisotropy (FA) has been used to drive registration in diffusion MRI-based TBM (FA-TBM). However, FA does not have the directional information that the tensors contain, therefore, the registration based on tensors provides better alignment of brain structures and better localization of volume change. We compare our DTBM method to both T1W-TBM and FA-TBM in investigating differences in brain morphology between patients with complicated hereditary spastic paraplegia of type 11 (SPG11) and a group of healthy controls. Effect size maps of T1W-TBM of SPG11 patients showed diffuse atrophy of white matter. However, DTBM indicated that atrophy was more localized, predominantly affecting several long-range pathways. The results of our study suggest that DTBM could be a powerful tool for detecting morphological changes of specific white matter pathways in normal brain development and aging, as well as in degenerative disorders.

Impact of time-of-day on diffusivity measures of brain tissue derived from diffusion tensor imaging.

Diurnal fluctuations in MRI measures of structural and functional properties of the brain have been reported recently. These fluctuations may have a physiological origin, since they have been detected using different MRI modalities, and cannot be explained by factors that are typically known to confound MRI measures. While preliminary evidence suggests that measures of structural properties of the brain based on diffusion tensor imaging (DTI) fluctuate as a function of time-of-day (TOD), the underlying mechanism has not been investigated. Here, we used a longitudinal within-subjects design to investigate the impact of time-of-day on DTI measures. In addition to using the conventional monoexponential tensor model to assess TOD-related fluctuations, we used a dual compartment tensor model that allowed us to directly assess if any change in DTI measures is due to an increase in CSF/free-water volume fraction or due to an increase in water diffusivity within the parenchyma. Our results show that Trace or mean diffusivity, as measured using the conventional monoexponential tensor model tends to increase systematically from morning to afternoon scans at the interface of grey matter/CSF, most prominently in the major fissures and the sulci of the brain. Interestingly, in a recent study of the glymphatic system, these same regions were found to show late enhancement after intrathecal injection of a CSF contrast agent. The increase in Trace also impacts DTI measures of diffusivity such as radial and axial diffusivity, but does not affect fractional anisotropy. The dual compartment analysis revealed that the increase in diffusivity measures from PM to AM was driven by an increase in the volume fraction of CSF-like free-water. Taken together, our findings provide important insight into the likely physiological origins of diurnal fluctuations in MRI measurements of structural properties of the brain.

Twin-singleton developmental study of brain white matter anatomy.

Twin studies provide valuable insights into the analysis of genetic and environmental factors influencing human brain development. However, these findings may not generalize to singletons due to differences in pre- and postnatal environments. One would expect the effect of these differences to be greater during the early years of life. To address this concern, we compare longitudinal diffusion data of white matter regions for 26 singletons and 76 twins (monozygotic and dizygotic) from birth to 2 years of age. We use nonlinear mixed effect modeling where the temporal changes in the diffusion parameters are described by the Gompertz function. The Gompertz function describes growth trajectory in terms of intuitive parameters: asymptote, delay, and speed. We analyzed fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD) for 21 regions of interest (ROIs). These ROIs included areas in the association, projection, and commissural fiber tracts. We did not find any differences in the diffusion parameters between monozygotic and dizygotic twins. In addition, FA and RD showed no developmental differences between singletons and twins for the regions analyzed. However, the delay parameter of the Gompertz function of AD for the anterior limb of the internal capsule and anterior corona radiata was significantly different between singletons and twins. Further analysis indicated that the differences are small, and twins "catch up" by the first few months of life. These results suggest that the effects of differences of pre- and postnatal environments between twins and singletons are minimal on white matter development and disappear early in life. Hum Brain Mapp 38:1009-1024, 2017. © 2016 Wiley Periodicals, Inc.

Longitudinal modeling of appearance and shape and its potential for clinical use.

Clinical assessment routinely uses terms such as development, growth trajectory, degeneration, disease progression, recovery or prediction. This terminology inherently carries the aspect of dynamic processes, suggesting that single measurements in time and cross-sectional comparison may not sufficiently describe spatiotemporal changes. In view of medical imaging, such tasks encourage subject-specific longitudinal imaging. Whereas follow-up, monitoring and prediction are natural tasks in clinical diagnosis of disease progression and of assessment of therapeutic intervention, translation of methodologies for calculation of temporal profiles from longitudinal data to clinical routine still requires significant research and development efforts. Rapid advances in image acquisition technology with significantly reduced acquisition times and with increase of patient comfort favor repeated imaging over the observation period. In view of serial imaging ranging over multiple years, image acquisition faces the challenging issue of scanner standardization and calibration which is crucial for successful spatiotemporal analysis. Longitudinal 3D data, represented as 4D images, capture time-varying anatomy and function. Such data benefits from dedicated analysis methods and tools that make use of the inherent correlation and causality of repeated acquisitions of the same subject. Availability of such data spawned progress in the development of advanced 4D image analysis methodologies that carry the notion of linear and nonlinear regression, now applied to complex, high-dimensional data such as images, image-derived shapes and structures, or a combination thereof. This paper provides examples of recently developed analysis methodologies for 4D image data, primarily focusing on progress in areas of core expertise of the authors. These include spatiotemporal shape modeling and growth trajectories of white matter fiber tracts demonstrated with examples from ongoing longitudinal clinical neuroimaging studies such as analysis of early brain growth in subjects at risk for mental illness and neurodegeneration in Huntington's disease (HD). We will discuss broader aspects of current limitations and need for future research in view of data consistency and analysis methodologies.