The analyses performed for this dissertation have several novel components that add to the field study cigarette dependence. The prior DTI literature investigating cigarette
smokers has reported inconsistent results. One reason for these inconsistencies may be the analysis methods used which make it impossible to have localized, tract specific results. In hopes of providing clarity, this study is the first in the cigarette smoking field of research to use an along the tract tractography based DTI analysis. This style of analysis makes it possible for the first time in the smoking literature to analyze diffusion at each millimeter along a singular fiber bundle. This study is also the first to use our along the tract UNC−Utah NA−MIC DTI Fiber Analysis Framework in an adult study sample. While this framework existed prior to my completion of 2 of this dissertation, it was present in separate scripts available for use only in command line format. Now, there are graphical user interfaces for each step of the process, allowing for a smooth analysis of diffusion data for any non−technical user. Further, prior to this study, all of previous application of the tools in our framework were in neonate and infant brain development studies. This study demonstrates that this workflow can be used for the study of adult data, and the framework is now freely available to the entire neuroscience field.
As along the tract analysis of DTI data is a new technique, we are also the first in the cigarette dependence field to pair this DTI analysis style with sMRI analysis. Combining imaging modalities is a powerful technique that enables a more clear per- spective as to the biology being observed in the brain, by collecting information on both the white and gray matter. While the DTI and sMRI analysis provide different kinds of information on brain structure, looking at the two information types together helps in determining the full picture. Through multimodal analysis, we were able to uncover a new interesting story that may provide structural evidence for known behav- ioral differences between smokers and non−smokers, and among those who are cigarette dependent.
fornix, and thus our findings in this tract adds breadth to the literature and provides a new region of the brain worthy of further investigation in cigarette dependence. Lastly, this is the first study to our knowledge to correlate white and grey matter structural findings with the Cigarette Dependence Scale as a measurement of cigarette addiction severity. Most prior studies rely upon the FTND to measure addiction severity, so these analyses provide support for the use of the CDS in future studies.
5.8 Limitations
The limitations to this dissertation are many. The first and largest limitation being the small sample size for analysis that limits the generalizability of the results, and requires replication. While our sample size is similar to other studies published in the literature, we acknowledge that there are many factors involved in cigarette dependence that were not investigated directly, or controlled for in this study due to limited power. Ideally we would like to have considered family history of cigarette dependence, common polymorphisms in important enzyme genes that regulate dopamine levels such as DAT and COMT, as well as nAChR SNPs that could contribute to addiction disorders. We did not collect information on the use of other legal and illegal substances, which is an important detail to consider in cigarette smokers as alcohol consumption and the use of other drugs is often comorbid with cigarette dependence. Other studies also often look at how age of onset affects cigarette addiction severity, and have found those who start smoking at an earlier age to be more impaired on measures of working memory [? ]. While we did not look at age of onset in our study, we did control for participant age, which positively correlated with age of onset for the DTI study, but not the sMRI analysis. Age of onset did however negatively correlate with craving prior to the scan, which highlights yet another facet of addiction (craving) that we would like to further investigate. Due to these limitations, our results are preliminary and will form the basis
for future scientific inquiry within the lab.
Further, the data analyzed here were collected within a study thats main focus was fMRI analysis, thus the DTI and sMRI acquisition sequences, and field of views were not optimal for these methods of analysis. For example, there were several regions of the brain that could not be analyzed in the structural analysis with FreeSurfer as the signal intensity was too low in regions of the temporal pole and superior frontal and parietal cortices. This limited our analysis of the circuitry involved in episodic prospection and decision−making as we could not interrogate the temporal lobe cortical regions for effect of group or cigarette consumption and dependence. While this limited the analysis in this dissertation, it did allow us to recognize the situation, and to adjust our DTI and sMRI protocols for other studies in the lab where data acquisition was ongoing or still in the planning stages. So through this dissertation, our lab will now have better DTI and sMRI acquisition sequences going forward, and frameworks with which to analyze the data.