Fractal dimension (FD) is a quantitative parameter that can characterizes the complexity of human brain tissue. Extensive grey matter (GM) pathology has been previously identified in Frontotemporal dementia (FTD) and its variants. The aim of the present study was to investigate the GM morphometric abnormalities in the behavioral variant FTD (bvFTD) and primary progressive aphasia (PPA) using FD analysis. Twenty-seven bvFTD, 12 PPA and 20 controls were studied. SPM8 was used to segment the brain into GM tissue. Then the FD values were estimated for the GM skeleton, surface and general structure in patients and controls using our previously published algorithm. We found that patients with bvFTD had significant reduction in FD values of skeleton and general structure when compared to controls. In PPA, more significant decrease in FD was noted in the whole brain and left hemisphere skeleton along with left hemisphere general structure. Only the right hemisphere skeleton had a significant correlation with total score of Frontal Systems Behavior Scale (FrSBe). The results showed that the variants of FTD are associated with disease specific morphometric complexity patterns. These results indicate that FD can be used as a biomarker for the structural changes associated with neurodegenerative diseases.

In this article, we first review some aspects of functional magnetic resonance imaging (fMRI) paradigm designing for major cognitive functions by using stimulus delivery systems like Cogent, E-Prime, Presentation, etc., along with their technical aspects. We also review the stimulus presentation possibilities (block, event-related) for visual or auditory paradigms and their advantage in both clinical and research setting. The second part mainly focus on various fMRI data post-processing tools such as Statistical Parametric Mapping (SPM) and Brain Voyager, and discuss the particulars of various preprocessing steps involved (realignment, co-registration, normalization, smoothing) in these software and also the statistical analysis principles of General Linear Modeling for final interpretation of a functional activation result.

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