PurposeMotor function and recovery after stroke likely rely directly on the residual anatomical connections in the brain and its resting-state functional connectivity. Both structural and functional properties of cortical networks after stroke are revealed using multimodal magnetic resonance imaging (MRI). Specifically, functional connectivity MRI (fcMRI) can extract functional networks of the brain at rest, while structural connectivity can be estimated from white matter fiber orientations measured with high angular-resolution diffusion imaging (HARDI). A model that marries these two techniques may be the key to understanding functional recovery after stroke. In this study, a novel set of voxel-level measures of structurofunctional correlations (SFC) was developed and tested in a group of chronic stroke subjects.MethodsA fully automated method is presented for modeling the structure-function relationship of brain connectivity in individuals with stroke. Brains from ten chronic stroke subjects and nine age-matched controls were imaged with a structural T1-weighted scan, resting-state fMRI, and HARDI. Each subject's T1-weighted image was nonlinearly registered to a T1-weighted 152-brain MNI template using a local histogram-matching technique that alleviates distortions caused by brain lesions. Fractional anisotropy maps and mean BOLD images of each subject were separately registered to the individual's T1-weighted image using affine transformations. White matter fiber orientations within each voxel were estimated with the q-ball model, which approximates the orientation distribution function (ODF) from the diffusion-weighted measurements. Deterministic q-ball tractography was performed in order to obtain a set of fiber trajectories. The new structurofunctional correlation method assigns each voxel a new BOLD time course based on a summation of its structural connections with a common fiber length interval. Then, the voxel's original time-course was correlated with this fiber-distance BOLD signal to derive a novel structurofunctional correlation coefficient. These steps were repeated for eight fiber distance intervals, and the maximum of these correlations was used to define an intrinsic structurofunctional correlation (iSFC) index. A network-based SFC map (nSFC) was also developed in order to enhance resting-state functional networks derived from conventional functional connectivity analyses. iSFC and nSFC maps were individually compared between stroke subjects and controls using a voxel-based two-tailed Student's t-test (alpha = 0.01). A linear regression was also performed between the SFC metrics and the Box and Blocks Score, a clinical measure of arm motor function.ResultsSignificant decreases (p < 0.01) in iSFC were found in stroke subjects within functional hubs of the brain, including the precuneus, prefrontal cortex, posterior parietal cortex, and cingulate gyrus. Many of these differences were significantly correlated with the Box and Blocks Score. The nSFC maps of prefrontal networks in control subjects r...
Understanding anatomy is vital to occupational therapy (OT) for clinical success. Anatomy requires comprehending three-dimensional (3D) human structure relationships and student age and learning style differences may affect this understanding. This study examined how 3D anatomy software influenced online OT students' grades among different ages and learning styles. The intervention group had 17 students (mean age 33 ± 8 years) and the control group had 18 students (mean age 32 ± 6 years). Students were categorized above or below the age of 30 and completed a learning style questionnaire at the beginning of the course. To determine the usefulness of the software, the intervention group completed a custom-survey. Independent sample t-tests were used to compare grades between the intervention and control groups. Non-parametric tests were used to compare grades of different ages and learning style groups. The intervention group had higher overall final course grades when compared to the control group, although not statistically significant (p>0.05). Additionally, lecture and laboratory grades were not higher (p>0.05). Most students (82%) reported the use of the anatomy software to be helpful in understanding course concepts. No statistically significant course grade differences were found among the different learning styles or two age groups (p>0.05). In conclusion, intervention group final course grades were higher and the software benefitted all learning styles and both age groups. Thus, OT programs should consider using 3D anatomy software programs to aid in foundational anatomy education.
Background and Purpose: Despite the implications of optimizing strength training post-stroke, little is known about the differences in fatigability between men and women with chronic stroke. The purpose of this study was to determine the sex differences in knee extensor muscle fatigability and potential mechanisms in individuals with stroke. Methods: Eighteen participants (10 men, eight women) with chronic stroke (≥6 months) and 23 (12 men, 11 women) nonstroke controls participated in the study. Participants performed an intermittent isometric contraction task (6 s contraction, 3 s rest) at 30% of maximal voluntary contraction (MVC) torque until failure to maintain the target torque. Electromyography was used to determine muscle activation and contractile properties were assessed with electrical stimulation of the quadriceps muscles. Results: Individuals with stroke had a briefer task duration (greater fatigability) than nonstroke individuals (24.1 ± 17 min vs. 34.9 ± 16 min). Men were more fatigable than women for both nonstroke controls and individuals with stroke (17.9 ± 9 min vs. 41.6 ± 15 min). Individuals with stroke had less fatigue-related changes in muscle contractile properties and women with stroke differed in their muscle activation strategy during the fatiguing contractions. Conclusions: Men and women fatigue differently post-stroke and this may be due to the way they neurally activate muscle groups.
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