Motor data scaling by respiration frequencies in rest

Functional Magnetic Resonance Imaging (fMRI) is widely used as a tool to see activations in the different brain regions. Motor data acquired from fMRI scan is accompanied with signal due to hemodynamic changes taking place during the scan. This hemodynamic signal is dominated by parameter alteration in the large vessels of brain. Scaling of task induced BOLD signal with hypercapnic or breathold data is one of the effective methods to minimize the signal due to large vessels. Patient discomfort and compliance has been a major issue with these methods hence in this study we used respiration frequencies in rest data to scale task induced data and compared results with breathold scaling. The correlation between respiration frequencies and breathold signal was very good indicating presence of hemodynamic component in respiration. Scaling was done in both time and frequency domain. Standard deviation was used in time domain and frequency fluctuation amplitude was used in frequency. Results of scaling with respiration frequencies and with breathold signal; were comparable and active areas during performance of motor task reduced after scaling, minimizing the effect of large vessels. These outcomes showed that respiration frequencies can be efficiently used for scaling data.

Name thesis:degree_name

Master of Science in Biomedical Engineering - (M.S.)

Discipline thesis:degree_discipline

Biomedical Engineering

Year

2010

Author dc:creator

• Kamble, Amit Madhukar

Contributors dc:contributor

• Bharat Biswal
• Tara L. Alvarez
• Sergei Adamovich

• Functional magnetic resonance imaging
• Motor data
• Respiration frequencies
• Scaling data
• Biomedical Engineering and Bioengineering

Repository record dc:identifier

https://digitalcommons.njit.edu/theses/76

OAI identifier oai:identifier

oai:digitalcommons.njit.edu:theses-1075