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\"This is the autobiography of Coretta Scott King--wife of Martin Luther King, Jr.; founder of the Martin Luther King, Jr. Center for Nonviolent Social Change (the King Center); architect of the MLK, Jr. legacy; and global leader in movements for civil and human rights as well as peace. Learn about how a girl born in the segregated deep south became a global leader at the forefront of the peace movement and an unforgettable champion of social change. Resilience, bravery, and joy lie at the center of this timeless story about fighting for justice against all odds.\" -- Provided by publisher.

Pain treatment services and clinical indicators of pain chronicity focus on afferent nociceptive projections and psychological markers of pain perception with little focus on motor processes. Research supports a strong role for the motor system both in terms of pain related disability and in descending pain modulation. However, there is little understanding of the neurological regions implicated in pain-motor interactions and how the motor and sensory systems interact under conditions of pain. We performed an ALE meta-analysis on two clinical cohorts with atypical sensory and motor processes under conditions of pain and no pain. Persons with sensory altered processing (SAP) and no pain presented with greater activity in the precentral and supplementary motor area relative to persons with self-reported pain. In persons with motor altered processing (MAP), there appeared to be a suppression of activity in key pain regions such as the insula, thalamus, and postcentral gyrus. As such, activation within the motor system may play a critical role in dampening pain symptoms in persons with SAP, and in suppressing activity in key pain regions of the brain in persons with MAP. Future research endeavors should focus on understanding how sensory and motor processes interact both to understand disability and discover new treatment avenues.

Clinical comparisons do not usually take laterality into account and thus may report erroneous or misleading data. The concept of laterality, well evaluated in brain and motor systems, may also apply at the level of peripheral nerves. Therefore, we sought to evaluate the extent to which we could observe an effect of laterality in MRI-collected white matter indices of the sciatic nerve and its two branches (tibial and fibular). We enrolled 17 healthy persons and performed peripheral nerve diffusion weighted imaging (DWI) and magnetization transfer imaging (MTI) of the sciatic, tibial and fibular nerve. Participants were scanned bilaterally, and findings were divided into ipsilateral and contralateral nerve fibers relative to self-reporting of hand dominance. Generalized estimating equation modeling was used to evaluate nerve fiber differences between ipsilateral and contralateral legs while controlling for confounding variables. All findings controlled for age, sex and number of scans performed. A main effect of laterality was found in radial, axial, and mean diffusivity for the tibial nerve. Axial diffusivity was found to be lateralized in the sciatic nerve. When evaluating mean MTR, a main effect of laterality was found for each nerve division. A main effect of sex was found in the tibial and fibular nerve fiber bundles. For the evaluation of nerve measures using DWI and MTI, in either healthy or disease states, consideration of underlying biological metrics of laterality in peripheral nerve fiber characteristics need to considered for data analysis. Integrating knowledge regarding biological laterality of peripheral nerve microstructure may be applied to improve how we diagnosis pain disorders, how we track patients' recovery and how we forecast pain chronification.

Converging areas of research have implicated glutamate and γ-aminobutyric acid (GABA) as key players in neuronal signalling and other central functions. Further research is needed, however, to identify microstructural and behavioral links to regional variability in levels of these neurometabolites, particularly in the presence of demyelinating disease. Thus, we sought to investigate the extent to which regional glutamate and GABA levels are related to a neuroimaging marker of microstructural damage and to motor and cognitive performance. Twenty-one healthy volunteers and 47 people with multiple sclerosis (all right-handed) participated in this study. Motor and cognitive abilities were assessed with standard tests used in the study of multiple sclerosis. Proton magnetic resonance spectroscopy data were acquired from sensorimotor and parietal regions of the brains’ left cerebral hemisphere using a MEGA-PRESS sequence. Our analysis protocol for the spectroscopy data was designed to account for confounding factors that could contaminate the measurement of neurometabolite levels due to disease, such as the macromolecule signal, partial volume effects, and relaxation effects. Glutamate levels in both regions of interest were lower in people with multiple sclerosis. In the sensorimotor (though not the parietal) region, GABA concentration was higher in the multiple sclerosis group compared to controls. Lower magnetization transfer ratio within grey and white matter regions from which spectroscopy data were acquired was linked to neurometabolite levels. When adjusting for age, normalized brain volume, MTR, total N-acetylaspartate level, and glutamate level, significant relationships were found between lower sensorimotor GABA level and worse performance on several tests, including one of upper limb motor function. This work highlights important methodological considerations relevant to analysis of spectroscopy data, particularly in the afflicted human brain. These findings support that regional neurotransmitter levels are linked to local microstructural integrity and specific behavioral abilities that can be affected in diseases such as multiple sclerosis. •Method optimized for obtaining accurate estimates of GABA levels with 1H-MRS in MS.•Neurometabolite levels are linked to regional MTR, a marker of microstructural damage.•Elevated sensorimotor GABA levels are linked to motor performance of MS participants.

Clinical research is no longer a monopolistic environment wherein patients and participants are the sole voice of information. The introduction and acceleration of AI-based methods in healthcare is creating a complex environment where human-derived data is no longer the sole mechanism through which researchers and clinicians explore and test their hypotheses. The concept of self-agency is intimately tied into this, as generative data does not encompass the same person-lived experiences as human-derived data. The lack of accountability and transparency in recognizing data sources supporting medical and research decisions has the potential to immediately and negatively impact patient care. This commentary considers how self-agency is being confronted by the introduction and proliferation of generative AI, and discusses future directions to improve, rather than undermine AI-fueled healthcare progress.

Physical insult from a mild Traumatic Brain Injury (mTBI) leads to changes in blood flow in the brain and measurable changes in white matter, suggesting a physiological basis for chronic symptom presentation. Post-traumatic headache (PTH) is frequently reported by persons after an mTBI that may persist beyond the acute period (>3 months). It remains unclear whether ongoing inflammation may contribute to the clinical trajectory of PTH. We recruited a cohort of pediatric subjects with PTH who had an acute or a persistent clinical trajectory, each around the 3-month post-injury time point, as well as a group of age and sex-matched healthy controls. We collected salivary markers of mRNA expression as well as brain imaging and psychological testing. The persistent PTH group showed the highest levels of psychological burden and pain symptom reporting. Our data suggest that the acute and persistent PTH cohort had elevated levels of complement factors relative to healthy controls. The greatest change in mRNA expression was found in the acute-PTH cohort wherein the complement cascade and markers of vascular health showed a prominent role for C1Q in PTH pathophysiology. These findings (1) underscore a prolonged engagement of what is normally a healthy response and (2) show that a persistent PTH symptom trajectory may parallel a poorly regulated inflammatory response.

A structural or functional pattern of neuroplasticity that could systematically discriminate between people with impaired and preserved motor performance could help us to understand the brain networks contributing to preservation or compensation of behavior in multiple sclerosis (MS). This study aimed to (1) investigate whether a machine learning-based technique could accurately classify MS participants into groups defined by upper extremity function (i.e. motor function preserved (MP) vs. motor function impaired (MI)) based on their regional grey matter measures (GMM, cortical thickness and deep grey matter volume) and inter-regional functional connection (FC), (2) investigate which features (GMM, FC, or GMM + FC) could classify groups more accurately, and (3) identify the multivariate patterns of GMM and FCs that are most discriminative between MP and MI participants, and between each of these groups and the healthy controls (HCs). With 26 MP, 25 MI, and 21 HCs (age and sex matched) underwent T1-weighted and resting-state functional MRI at 3 T, we applied support vector machine (SVM) based classification to learn discriminant functions indicating regions in which GMM or between which FCs were most discriminative between groups. This study demonstrates that there exist structural and FC patterns sufficient for correct classification of upper limb motor ability of people with MS. The classifier with GMM + FC features yielded the highest accuracy of 85.61 % ( p  < 0.001) to distinguish between the MS groups using leave-one-out cross-validation. It suggests that a machine-learning approach combining structural and functional features is useful for identifying the specific neural substrates that are necessary and sufficient to preserve motor function among people with MS.

The \"just noticeable difference\" (JND) represents the minimum amount by which a stimulus must change to produce a noticeable variation in one's perceptual experience (i.e., Weber's law). Recent work has shown that within-participant standard deviations of grip aperture (i.e., JNDs) increase linearly with increasing object size during the early, but not the late, stages of goal-directed grasping. A visually based explanation for this finding is that the early and late stages of grasping are respectively mediated by relative and absolute visual information and therefore render a time-dependent adherence to Weber's law. Alternatively, a motor-based explanation contends that the larger aperture shaping impulses required for larger objects gives rise to a stochastic increase in the variability of motor output (i.e., impulse-variability hypothesis). To test the second explanation, we had participants grasp differently sized objects in grasping time criteria of 400 and 800 ms. Thus, the 400 ms condition required larger aperture shaping impulses than the 800 ms condition. In line with previous work, JNDs during early aperture shaping (i.e., at the time of peak aperture acceleration and peak aperture velocity) for both the 400 and 800 ms conditions scaled linearly with object size, whereas JNDs later in the response (i.e., at the time of peak grip aperture) did not. Moreover, the 400 and 800 ms conditions produced comparable slopes relating JNDs to object size. In other words, larger aperture shaping impulses did not give rise to a stochastic increase in aperture variability at each object size. As such, the theoretical tenets of the impulse-variability hypothesis do not provide a viable framework for the time-dependent scaling of JNDs to object size. Instead, we propose that a dynamic interplay between relative and absolute visual information gives rise to grasp trajectories that exhibit an early adherence and late violation to Weber's law.

Endometriosis, affecting approximately 176 million adults and adolescents worldwide, is a debilitating condition in which uterine tissue grows outside the uterus. The condition costs the US economy approximately $78 billion annually in pain-related disability. By understanding the neural underpinnings of endometriosis-associated pain (EAP) and risk factors for chronification, translational research methods could lessen diagnostic delays and maximize successful pain remediation. This can be accomplished by the novel use of a known method, offset analgesia (OA), to better elucidate the neural mechanisms that may contribute to and maintain EAP. This commentary will provide justification and rationale for the use of OA in the study of EAP. Utilizing an OA paradigm in patients with endometriosis, especially adolescents, may (1) provide insight into neural mechanisms contributing to pain maintenance, which could capture those at-risk for the transition to chronic pelvic pain, (2) provide a metric for the development of future centrally mediated treatment options for this population, and (3) elucidate the brain changes that result in resistance to treatment and pain chronification.

Multiple sclerosis (MS) is a neuroinflammatory disease of the central nervous system (CNS) that involves a targeted destruction of myelin and degeneration of neurons. The pathological changes sustained during MS can lead to substantial disability in motor and cognitive performance, as well as dysfunction in activities of daily living. Despite progress, we still do not fully understand the factors that intervene between brain injury and clinical outcomes. Modern research suggests that these factors include the brains' innate plasticity and its ability to functionally compensate for MS-related neuropathology. Considerable evidence points to atypical brain activity in persons with MS, however without understanding the process through which such activity is produced, our understanding of adaptive- or maladaptive – changes in brain activity is limited.The aim of this dissertation was to evaluate a brain mechanism that integrated performance-related cues for adaptation with the use of atypical brain region during task performance. The theoretical tenets of Botvinick and colleagues theory of conflict monitoring and cognitive control model were applied to evaluate how brain regions implicated in responding to the need for adaptation (anterior cingulate cortex; ACC) and implementing adaptive resources (dorsolateral prefrontal cortex; DLPFC) relate to cognitive performance in persons with MS. Regression models evaluating structural integrity using Magnetization Transfer Ratio imaging from the ACC and DLPFC were significant predictors of cognitive performance. However, only the model in the healthy control group remained significant after correcting for nuisance variables. No additional value of accounting for MTR within the ACC and DLPFC was found when considering whole-brain neuropathology. Functional connectivity between the ACC and DLPFC was positively related with cognitive performance. Accounting for functional connectivity improved on existing methods of evaluating cognitive performance only in the MS group. This was a robust finding, using multiple neuroimaging measures of MS-related neuropathology and of behavioral performance.Together, findings suggest that MS-related neuropathology does not modulate the functional connectivity between the ACC and DLPFC and is not responsible for observed correlations with cognitive performance. Rather, the presence of neuropathology may create the conditions for impaired cognitive performance under which the importance of inherent brain mechanisms for adaptation are highlighted. Evidence is put forward in support of considering the functional connectivity between these conflict-defined regions when attempting to determine the impact of disease-related neuropathology on a patients' level of cognitive performance. Implications for future research and clinical care of persons with MS are discussed.