**Author details**

prenatal alcohol exposure on functional activity. The advantages reported for this method included increased adaptability, more systematic in detecting diverse brain networks, and better able to identify commonalities and differences across subjects and groups [141].

fMRI data can also be analyzed to show how components of a neural system are working together when performing a specific task. The identification of associations between anatom‐ ically distinct time series is referred to as "functional connectivity" [140]. The ability to identify consistent, reproducible, and accurate regions of interest is the key to developing connectivi‐ ty maps [142]. Using a new strategy to develop cortical landmarks (dense individualized and common connectivity-based cortical landmarks, DICCOLs), Li et al. [143] used functional connectomics signatures to identify 10 brain regions with structurally disrupted landmarks that could be used to distinctly identify prenatal cocaine exposed brains from that of controls.

Finally, a novel application of machine learning has been used to test whether brain images can be used to correctly identify prenatal cocaine-exposed young adults from socioeconomi‐ cally matched controls [144]. Regional features were extracted from both structural and functional MR images, and the power of each to discriminate between prenatal cocaine exposed and control brains was accomplished through machine learning methods. The method accurately identified 91.8% of prenatally cocaine-exposed brains. The use of both structural and functional images was critical to improving the accuracy of the classification

Prenatal drug exposure is a risk factor for increased vulnerability to difficulties in both behavior and cognition. Continued research to identify the structural and functional targets of prenatal drug-related neurotoxicity is important. Identifying biomarkers of prenatal drugrelated changes in brain development and relating those changes to behavior, or in the case of alcohol to physical features, has the potential to inform diagnostic and treatment strategies. MRI, fMRI, and DTI neuroimaging methods provide powerful tools for visualizing the brain and, because they are noninvasive, are especially suited for research in young children. The impact of prenatal drug exposure on brain structure and function is subtle and often ac‐ count for a small amount of variance that contributes to deficits in behavior regulation and cognition. These subtle effects can be explained by the complex interactions of the pattern of prenatal drug exposure both in terms of the timing and dose as well as the combination of multiple drugs, genetic, and environmental factors. Changes in brain structure and function in children and adolescents with prenatal drug exposure can be difficult to assess for a number of other reasons. To date, a neuropsychological profile for prenatal drug-related deficits in cognitive function has not been identified and there are diffuse individual differences in the expression of the impact of prenatal drug exposure on the brain and behavior. Furthermore, limitations in statistical approaches to the analysis of neuroimaging data can often lead to difficulty in detecting these subtle effects. Future studies will require large sample sizes and longitudinal research designs, and increasingly sophisticated neuroimaging and statistical

system compared to either type of image alone.

206 Recent Advances in Drug Addiction Research and Clinical Applications

**5. Conclusions**

Jennifer Willford1\*, Conner Smith1 , Tyler Kuhn1 , Brady Weber1 and Gale Richardson2

\*Address all correspondence to: Jennifer.Willford@sru.edu

1 Slippery Rock University, Slippery Rock, PA, USA

2 University of Pittsburgh, Pittsburgh PA, USA
