Performance tests in working memory samples.

<p>Performance tests in working memory samples.</p

Language task vs adjusted volume index correlations.

<p>Language task vs adjusted volume index correlations.</p

When the FAT goes wide: Right extended Frontal Aslant Tract volume predicts performance on working memory tasks in healthy humans

<div><p>The Frontal Aslant Tract (FAT) is a tract recently described as having implications on language function. The originally proposed anatomical FAT definition characterizes a connection between Broca’s territory and anterior supplementary and pre-supplementary motor areas in the Superior Frontal Gyrus (SFG). Here we propose an extended definition of the FAT (the exFAT) that propagates more anteriorly into the SFG. A sample of 834 subjects from the WU-Minn HCP 900 subjects data release (S900) was selected. The bilateral exFATs were reconstructed for the whole sample using an automated pipeline and thresholded adjusted tract volumes were calculated. A laterality test was performed on the whole sample. The frontal cortex has known implications on superior cognitive functions, so here we evaluate the implications of exFAT volume on performance in a language task and on a set of working memory tasks. Two sub-samples of 70 subjects each were drawn from the S900 sample by selecting the 35 top-performers and 35 bottom-performers for both language and working memory tasks. Additional laterality tests were performed on each subsample. We did not find the exFAT to be lateralized in any of the samples. We found statistically significant differences in left adjusted exFAT volume between top-performers and bottom-performers in the language task. We also found statistically significant differences in right adjusted exFAT volume between top-performers and bottom-performers for 2-back working memory tasks. To check for the predictive power of the exFAT volumes as correlates for performance, we ran a repeated random sub-sampling cross-validation procedure based on a Support Vector Machine (SVM) classifier that was capable of correctly classifying holdout subjects to their corresponding group (top-performer vs bottom-performer) with an average accuracy of 74.5% for language task performance based on left exFAT volume and an accuracy of 64.2% for Working Memory performance based on right exFAT volume.</p></div

Performance tests in language samples.

<p>Performance tests in language samples.</p

Lateralization tests for language samples.

<p>Lateralization tests for language samples.</p

Working memory vs adjusted volume index correlations.

<p>Working memory vs adjusted volume index correlations.</p

Bilateral exFAT probability map.

<p>Probability map showing average fiber density along the bilateral exFAT trajectory. Values are only shown in voxels present in >10% of subjects.</p

Relationships of Osteoporosis Health Beliefs to Practiced Exercise Behaviors of Women

The purpose of this study was to examine the relationship of health beliefs contained in the Health Belief Model to practiced exercise behavior of women. A descriptive correlation design was used with a convenience sample of 201 women. The revised version of the Osteoporosis Health Belief Exercise Scale developed by Kim, Horan, Gendler and Patel (1991b) was used to measure health beliefs related to osteoporosis. The ARIC/Baecke questionnaire of Habitual Physical Activity was used to measure life style physical activity. Health motivation and exercise benefits were found to be positively correlated to exercise behavior. However, susceptibility and exercise barriers were inversely correlated to exercise behavior. Perceived exercise barriers and health motivation explained the greatest variance in exercise behaviors. The Health Belief Model can be used as a guide by nurses to promote health behaviors consistent with research findings

Tractography reconstruction framework of the optic radiations.

<p>(1) Standard preprocessing of the DWIs including Echo Planar Imaging distortion correction, eddy current distortion correction and head motion correction. (2) Distortion correction of the DWI. (3) Quantitative diffusion fractional anisotropy (FA) mapping. (4-5) Subcortical segmentation and cortical parcellation from FS of the 3D-structural image. (6) Registration of the structural images to the corresponding DWI sequence. (7) Seed and target masks. (8) Probabilistic streamline fiber tracking by high order integration over fiber orientation distributions (iFOD2) derived from constrained spherical deconvolution (CSD) with a maximum harmonic order of 8 and use of ACT during tracking. (9) Conversion of the tract file into a track density image. (10) Exclusion mask comprising CSF, whole contralateral hemisphere and ipsilateral GM regions. (11) Final optic radiation reconstruction in track density image and 3D tract file.</p

Improved Framework for Tractography Reconstruction of the Optic Radiation - Fig 4

<p>Streamlines of the reconstructed OR in five patients with multiple sclerosis: (a) Lesion masks is shown in red. (b) Probabilistic streamlines fiber tracking by iFOD2. (c) Probabilistic streamlines fiber tracking by high order integration over fiber orientation distributions (iFOD2) adding the anatomical exclusion criteria (AEC).</p