In the recent years, a number of studies using functional MRI (fMRI) have shown substantial differences between the activation pattern of older subjects (>50 years of age) and younger subjects (21-40 years) while performing a number of different sensorimotor and cognitive tasks. It has been concluded that the contrast observed is due to differences in neuronal activity in the older subjects. However, early hypothesis that normal aging involves widespread loss of neurons have been revised in light of accumulating evidence that in most regions of the brain, the number of neurons is stable throughout adulthood and senescence. In addition to direct effects on neuronal function, factors contributing to cerebrovascular reactivity is known to be altered in older people that could give rise to altered hemodynamic responses. Since the signal observed using fMRI could be modulated both by hemodynamics and oxygenation changes resulting from neuronal changes, these two factors must be separated to gain a better understanding about age related changes in the activation pattern obtained using fMRI. The present project proposed intends to combine basic science, engineering, and computational issues to specifically elucidate mechanisms (neuronal vs vascular) that results in older subjects having altered brain activation in comparison to young subjects. Results obtained from the noninvasive technique (fMRI) would provide ways to measure a number of relevant physiological factors and characterize them biophysically to understand human brain function with aging. Methods and techniques developed can also be used to study between two or more different groups.
The present project will help determine biophysical aspects of aging using non-invasive functional Magnetic Resonance Imaging (fMRI). As longitudinal studies are very important to follow individuals through different stages of their life span, fMRI techniques would become crucial in obtaining valuable biomarkers in studies of aging. FMRI presents many caveats in determining the actual physiological indicators that influence signal response in young and old subjects. This project is designed to address certain caveats by effectively testing and quantifying the neural and hemodynamic components that may modulate signal response in young and old subjects. This study will significantly gain information regarding the underlying nature and necessary corrections in fMRI signals. Such a correction is necessary to accurately determine the progression and determinants of change across all segments of the life span that affect cognitive effects and brain function.
|Di, Xin; Huang, Jia; Biswal, Bharat B (2017) Task modulated brain connectivity of the amygdala: a meta-analysis of psychophysiological interactions. Brain Struct Funct 222:619-634|
|Di, Xin; Azeez, Azeezat; Li, Xiaobo et al. (2017) Disrupted focal white matter integrity in autism spectrum disorder: A voxel-based meta-analysis of diffusion tensor imaging studies. Prog Neuropsychopharmacol Biol Psychiatry :|
|Di, Xin; Biswal, Bharat B (2017) Psychophysiological Interactions in a Visual Checkerboard Task: Reproducibility, Reliability, and the Effects of Deconvolution. Front Neurosci 11:573|
|Yuan, Rui; Di, Xin; Taylor, Paul A et al. (2016) Functional topography of the thalamocortical system in human. Brain Struct Funct 221:1971-84|
|Gohel, Suril R; Biswal, Bharat B (2015) Functional integration between brain regions at rest occurs in multiple-frequency bands. Brain Connect 5:23-34|
|Di, Xin; Biswal, Bharat B (2015) Characterizations of resting-state modulatory interactions in the human brain. J Neurophysiol 114:2785-96|
|Carlozzi, Noelle E; Tulsky, David S; Chiaravalloti, Nancy D et al. (2014) NIH Toolbox Cognitive Battery (NIHTB-CB): the NIHTB Pattern Comparison Processing Speed Test. J Int Neuropsychol Soc 20:630-41|
|Di, Xin; Rypma, Bart; Biswal, Bharat B (2014) Correspondence of executive function related functional and anatomical alterations in aging brain. Prog Neuropsychopharmacol Biol Psychiatry 48:41-50|
|Di, Xin; Kim, Eun H; Chen, Peii et al. (2014) Lateralized resting-state functional connectivity in the task-positive and task-negative networks. Brain Connect 4:641-8|
|Di, Xin; Biswal, Bharat B (2014) Identifying the default mode network structure using dynamic causal modeling on resting-state functional magnetic resonance imaging. Neuroimage 86:53-9|
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