Biomedical subjects

Luduan Zhang

Publications and source records attributed to Luduan Zhang.

5 recordsLinked to original sources

PubMed2006

Quantifying degeneration of white matter in normal aging using fractal dimension.

Although degeneration of brain white matter (WM) in aging is a well-recognized problem, its quantification has mainly relied on volumetric measurements, which lack detail in describing the degenerative adaptation. In this study, WM structural complexity was evaluated in healthy old and young adults by analyzing the three-dimensional fractal dimension (FD) of WM segmented from magnetic resonance images of brain. FDs detected in the old were significantly smaller than in the young subjects. Specifically, WM interior structure complexity degenerated in the left hemisphere in old men but in the right hemisphere in old women. Men showed more complex WM patterns than women. An asymmetrical (right-greater-than-left-hemisphere) complexity pattern was observed in the interior and general structures of WM, yet the surface complexity was symmetrical across WM structures of the two hemispheres. WM volumes were also measured, but no significant decline was found with aging. These results suggest that the deterioration of WM complexity is not uniformly distributed between the genders and across brain hemispheres.

Adolescent↗

PubMed2005

A three-dimensional fractal analysis method for quantifying white matter structure in human brain.

Fractal dimension (FD) is increasingly used to quantify complexity of brain structures. Previous research that analyzed FD of human brain mainly focused on two-dimensional measurements. In this study, we developed a three-dimensional (3D) box-counting method to measure FD of human brain white matter (WM) interior structure, WM surface and WM general structure simultaneously. This method, which firstly incorporates a shape descriptor (3D skeleton) representing interior structure and combines the three features, provides a more comprehensive characterization of WM structure. WM FD of different brain segments was computed to test robustness of the method. FDs of fractal phantoms were computed to test the accuracy of the method. The consistency of the computed and theoretical FD values suggests that our method is accurate in measuring FDs of fractals. Statistical analysis was performed to examine sensitivity of the method in detecting WM structure differences in a number of young and old subjects. FD values of the WM skeleton and surface were significantly greater in young than old individuals, indicating more complex WM structures in young people. These results suggest that our method is accurate in quantifying three-dimensional brain WM structures and sensitive in detecting age-related degeneration of the structures.

Age Factors↗

PubMed2005

Fatigue induced by intermittent maximal voluntary contractions is associated with significant losses in muscle output but limited reductions in functional MRI-measured brain activation level.

The main purpose of this study was to characterize brain activation patterns during a fatigue task involving repetitive maximal voluntary contractions (MVC) of finger flexor muscles. Fourteen young, healthy human participants performed approximately 100 handgrip MVCs (each 2-s contraction was followed by a 1-s rest) while their brain was imaged by functional MRI (fMRI). The handgrip force and electromyograms (EMG) of the finger flexors declined progressively to about 40% of the initial values at the end of the fatigue task, suggesting that significant muscle fatigue had occurred. In contrast, the level of the fMRI signal in the primary (sensorimotor), secondary (supplementary motor), and association (prefrontal and cingulate) motor-function cortices did not change significantly throughout the fatigue task (although the signal of the primary sensorimotor cortex showed a clear trend of decline). The fMRI data from the task of intermittent handgrip MVCs differed dramatically from those obtained in a 2-min sustained handgrip MVC published in a recent report, in which the overall fMRI-measured brain activation level was substantially lower and followed an increase-then-decrease pattern compared to the linear decreases in force and EMG. These results support the notion that the motor cortical centers control the tasks of repetitive and continuous muscle contractions differently and that there is a decoupling in the signal changes of the brain and muscles during muscle fatigue processes induced by maximal voluntary contractions.

Electromyography↗

PubMed2004

Reproducibility of fMRI at 1.5 T in a strictly controlled motor task.

Reproducibility of functional MRI (fMRI) data has been controversial. This issue was examined in this study by evaluating a strictly controlled voluntary force-matching handgrip task. Handgrip force, electromyogram (EMG), and fMRI data of brain activity were simultaneously recorded during the task performance. The task was repeated three times in each of the two experimental sessions. While force remained unchanged and EMG showed little variation across trials and sessions, the results revealed that fMRI-measured brain signals varied significantly among individual trials. However, the averaged fMRI signals over the three trials did not show significant difference between the two sessions. Our data suggest that fMRI is better at defining brain activation qualitatively than quantitatively, i.e., the locations of the activation areas could be reproduced quite reliably while their sizes fluctuated substantially.

Adult↗

PubMed2002

Accessory hardware for neuromuscular measurements during functional MRI experiments.

Functional magnetic resonance imaging (fMRI) is increasingly being used for human sensorimotor function research. Few studies, however, have been able to acquire peripheral neuromuscular data (e.g. joint force and electromyograms [EMG]) online with fMRI measurements. The lack of muscle output information hinders interpretation of fMRI data and prevents investigators from designing more sophisticated experiments. We developed a data-acquisition system that can record force and EMG data simultaneously with fMRI signals. This system included three major components: a hydraulic, pressure transducer-based force measurement device, a well-shielded EMG-recording apparatus, and a visual feedback setup. The three components were integrated with a laptop computer equipped with data acquisition hardware and software. System evaluation experiments demonstrated that no significant mutual interference occurred between the MRI environment and the force-EMG data-acquisition system, i.e. the system can record relatively noise-free force and EMG signals while maintaining the quality of fMRI data. The system has enabled us to study human motor control function involving motor tasks such as handgrip and finger pinch that require precision control of force and EMG. This accessory equipment can facilitate fMRI investigations of human sensorimotor function.

Brain↗