Pedaling-related brain activation in people post-stroke: an fMRI study

This study aimed to enhance our understanding of supraspinal control of locomotion in stroke survivors and its relationship to locomotor impairment. We focused mainly on the locomotor component of walking, which involves rhythmic, reciprocal, flexion and extension movements of multiple joints in both legs. Functional magnetic resonance imaging (fMRI) was used to record human brain activity while pedaling was used as a model of locomotion. First, we examined the spatiotemporal characteristics of hemodynamic responses recorded with fMRI and found that they were different in stroke survivors and control subjects. However, these differences were not substantial enough to require altering the normal canonical hemodynamic response function to obtain valid measurements of pedaling-related brain activity. During pedaling, stroke survivors and control subjects showed activity in the sensorimotor cortex and cerebellum. Stroke survivors had reduced volume of activation in those regions, however the signal intensity was similar between the groups. In stroke survivors, sensorimotor cortex activity was symmetrically distributed across the damaged and undamaged hemispheres; while cerebellum activity was lateralized to the damaged hemisphere. These brain activation patterns were different from those observed during non-locomotor movements, where volume of activation was unchanged but signal intensity was reduced in stroke survivors. We conclude that neural adaptations for producing locomotor and non-locomotor movements post-stroke are not the same and that the spinal cord and cerebellum might have a compensatory role in producing hemiparetic locomotion. Finally, we examined the relationship between locomotor performance and pedaling-related brain activity measured with fMRI. We found no relationship between the brain activation symmetry and locomotor symmetry, suggesting that the brain activation from each hemisphere was not directly responsible for control of the contralateral leg. However, our stroke survivors demonstrated poor locomotor performance and decreased volume of activation measured during pedaling, suggesting that impaired locomotion was associated with reduced volume of activation. Signal intensity of brain activity was associated with rate of pedaling in stroke survivors, suggesting that increased signal intensity in the active brain areas may compensate for reduced volume of activation in the production of hemiparetic locomotion

Changes in Hemodynamic Responses in Chronic Stroke Survivors Do Not Affect fMRI Signal Detection in a Block Experimental Design

The use of canonical functions to model BOLD-fMRI data in people post-stroke may lead to inaccurate descriptions of task-related brain activity. The purpose of this study was to determine whether the spatiotemporal profile of hemodynamic responses (HDRs) obtained from stroke survivors during an event-related experiment could be used to develop individualized HDR functions that would enhance BOLD-fMRI signal detection in block experiments. Our long term goal was to use this information to develop individualized HDR functions for stroke survivors that could be used to analyze brain activity associated with locomotor-like movements. We also aimed to examine the reproducibility of HDRs obtained across two scan sessions in order to determine whether data from a single event-related session could be used to analyze block data obtained in subsequent sessions. Results indicate that the spatiotemporal profile of HDRs measured with BOLD-fMRI in stroke survivors was not the same as that observed in individuals without stroke. We observed small between-group differences in the rates of rise and decline of HDRs that were more apparent in individuals with cortical as compared to subcortical stroke. There were no differences in the peak or time to peak of HDRs in people with and without stroke. Of interest, differences in HDRs were not as substantial as expected from previous reports and were not large enough to necessitate the use of individualized HDR functions to obtain valid measures of movement-related brain activity. We conclude that all strokes do not affect the spatiotemporal characteristics of HDRs in such a way as to produce inaccurate representations of brain activity as measured by BOLD-fMRI. However, care should be taken to identify individuals whose BOLD-fMRI data may not provide an accurate representation of underlying brain activation when canonical models are used. Examination of HDRs need not be done for each scan session, as our data suggest that the characteristics of HDRs in stroke survivors are reproducible across days

A Novel fMRI Paradigm Suggests that Pedaling-related Brain Activation is Altered after Stroke

The purpose of this study was to examine the feasibility of using functional magnetic resonance imaging (fMRI) to measure pedaling-related brain activation in individuals with stroke and age-matched controls. We also sought to identify stroke-related changes in brain activation associated with pedaling. Fourteen stroke and 12 control subjects were asked to pedal a custom, MRI-compatible device during fMRI. Subjects also performed lower limb tapping to localize brain regions involved in lower limb movement. All stroke and control subjects were able to pedal while positioned for fMRI. Two control subjects were withdrawn due to claustrophobia, and one control data set was excluded from analysis due to an incidental finding. In the stroke group, one subject was unable to enter the gantry due to excess adiposity, and one stroke data set was excluded from analysis due to excessive head motion. Consequently, 81% of subjects (12/14 stroke, 9/12 control) completed all procedures and provided valid pedaling-related fMRI data. In these subjects, head motion was ≤3 mm. In both groups, brain activation localized to the medial aspect of M1, S1, and Brodmann’s area 6 (BA6) and to the cerebellum (vermis, lobules IV, V, VIII). The location of brain activation was consistent with leg areas. Pedaling-related brain activation was apparent on both sides of the brain, with values for laterality index (LI) of –0.06 (0.20) in the stroke cortex, 0.05 (±0.06) in the control cortex, 0.29 (0.33) in the stroke cerebellum, and 0.04 (0.15) in the control cerebellum. In the stroke group, activation in the cerebellum – but not cortex – was significantly lateralized toward the damaged side of the brain (p = 0.01). The volume of pedaling-related brain activation was smaller in stroke as compared to control subjects. Differences reached statistical significance when all active regions were examined together [p = 0.03; 27,694 (9,608) μL stroke; 37,819 (9,169) μL control]. When individual regions were examined separately, reduced brain activation volume reached statistical significance in BA6 [p = 0.04; 4,350 (2,347) μL stroke; 6,938 (3,134) μL control] and cerebellum [p = 0.001; 4,591 (1,757) μL stroke; 8,381 (2,835) μL control]. Regardless of whether activated regions were examined together or separately, there were no significant between-group differences in brain activation intensity [p = 0.17; 1.30 (0.25)% stroke; 1.16 (0.20)% control]. Reduced volume in the stroke group was not observed during lower limb tapping and could not be fully attributed to differences in head motion or movement rate. There was a tendency for pedaling-related brain activation volume to increase with increasing work performed by the paretic limb during pedaling (p = 0.08, r = 0.525). Hence, the results of this study provide two original and important contributions. First, we demonstrated that pedaling can be used with fMRI to examine brain activation associated with lower limb movement in people with stroke. Unlike previous lower limb movements examined with fMRI, pedaling involves continuous, reciprocal, multijoint movement of both limbs. In this respect, pedaling has many characteristics of functional lower limb movements, such as walking. Thus, the importance of our contribution lies in the establishment of a novel paradigm that can be used to understand how the brain adapts to stroke to produce functional lower limb movements. Second, preliminary observations suggest that brain activation volume is reduced during pedaling post-stroke. Reduced brain activation volume may be due to anatomic, physiology, and/or behavioral differences between groups, but methodological issues cannot be excluded. Importantly, brain action volume post-stroke was both task-dependent and mutable, which suggests that it could be modified through rehabilitation. Future work will explore these possibilities

P3‐164: Less daily computer use is related to smaller hippocampal volumes in dementia‐free elderly

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/152632/1/alzjjalz2015061535.pd

Post-Acquisition Processing Confounds in Brain Volumetric Quantification of White Matter Hyperintensities

BACKGROUND: Disparate research sites using identical or near-identical magnetic resonance imaging (MRI) acquisition techniques often produce results that demonstrate significant variability regarding volumetric quantification of white matter hyperintensities (WMH) in the aging population. The sources of such variability have not previously been fully explored. NEW METHOD: 3D FLAIR sequences from a group of randomly selected aged subjects were analyzed to identify sources-of-variability in post-acquisition processing that can be problematic when comparing WMH volumetric data across disparate sites. The methods developed focused on standardizing post-acquisition protocol processing methods to develop a protocol with less than 0.5% inter-rater variance. RESULTS: A series of experiments using standard MRI acquisition sequences explored post-acquisition sources-of-variability in the quantification of WMH volumetric data. Sources-of-variability included: the choice of image center, software suite and version, thresholding selection, and manual editing procedures (when used). Controlling for the identified sources-of-variability led to a protocol with less than 0.5% variability between independent raters in post-acquisition WMH volumetric quantification. COMPARISON WITH EXISTING METHOD(S): Post-acquisition processing techniques can introduce an average variance approaching 15% in WMH volume quantification despite identical scan acquisitions. Understanding and controlling for such sources-of-variability can reduce post-acquisition quantitative image processing variance to less than 0.5%. DISCUSSION: Considerations of potential sources-of-variability in MRI volume quantification techniques and reduction in such variability is imperative to allow for reliable cross-site and cross-study comparisons

IC‐P‐076: Less daily computer use is related to smaller hippocampal volumes in dementia‐free elderly

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153184/1/alzjjalz201506097.pd

IC‐P‐112: Risk Factors Associated With Decreased Cortical Thickness in Dementia Free Okinawan Elderly

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153189/1/alzjjalz201606142.pd

IC‐P‐135: Baseline Normal Appearing White Matter Structural Integrity and Cerebral Blood Flow Can Predict White Matter Hyperintensity Expansion Over Time: A Voxel‐Wise Analysis

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/152693/1/alzjjalz201606165.pd

O2‐03‐04: Baseline Normal Appearing White Matter Structural Integrity and Cerebral Blood Flow Can Predict White Matter Hyperintensity Expansion Over Time: a Voxel‐Wise Analysis

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153012/1/alzjjalz201606408.pd