What do we do?
We work with diffusion-weighted magnetic resonance imaging (DW-MRI), a type of in-vivo magnetic resonance sequence from which diffusion measures in brain tissue can be calculated (Stejskal & Tanner, 1965). From these measures, diffusion models can be estimated. Diffusion tensor imaging is one of these models, and it allows making inferences about structural connectivity, since it informs about the microstructural properties of the white matter (Basser, Mattiello, & LeBihan, 1994). Fractional anisotropy is a measure of the directionality of diffusion, often associated with microstructural integrity (Horsfield & Jones, 2002). From this connectivity measure, white matter tracts can be reconstructed and segmented, by means of a procedure known as tractography (Basser, Pajevic, Pierpaoli, Duda, & Aldroubi, 2000). Numerous studies have demonstrated associations between tracts’ connectivity measures and neuropsychological capacities. Given the artifact-prone nature of diffusion data and tractography, rigorous processing control is required, for which we are working in collaboration with the PROVIDI Lab (UMC Utrecht, the Netherlands).
We currently have two projects involving these techniques, which we think exemplify the compatibility of neuropsychological tractography and genetic research. In association with centers from Spain (Centro de Atención Infantil Temprana – Universidad de Córdoba) and Iceland (University of Iceland), we are going to look at how cerebellar genetic malformations affect fine motor skills, specially due to weak connectivity in the cerebellar peduncles. The ultimate goal is to design an effective intervention program. The other project is based in Argentina and ongoing; we are applying tractography along with behavioral assessments in clinical neuropsychological patients. Recently, we had a case of a nonverbal 4 years old boy, who had underdeveloped arcuate fasciculi (key for speech, see figure below). We contacted researchers from USA who had been working with this pathology (Jeong, Sundaram, Behen, & Chugani, 2016) and came to the conclusion that the case is likely a mutation in the MID1 gene.
Basser, P. J., Mattiello, J., & LeBihan, D. (1994). MR diffusion tensor spectroscopy and imaging. Biophysical Journal, 66(1), 259–267.https://doi.org/10.1016/S0006-3495(94)80775-1
Basser, P. J., Pajevic, S., Pierpaoli, C., Duda, J., & Aldroubi, A. (2000). In Vivo Fiber Tractography Using DT-MRI Data. Magnenetic Resonance in Medicine, 44, 625–632. https://doi.org/10.1002/1522-2594(200010)44
Horsfield, M. A., & Jones, D. K. (2002). Applications of diffusion-weighted and diffusion tensor MRI to white matter diseases – a review. NMR in Biomedicine,15(7–8), 570–577. https://doi.org/10.1002/nbm.787
Jeong, J. W., Sundaram, S., Behen, M. E., & Chugani, H. T. (2016). Relationship between genotype and arcuate fasciculus morphology in six young children with global developmental delay: Preliminary DTI stuy. Journal of Magnetic Resonance Imaging, 44(6), 1504–1512. https://doi.org/10.1002/jmri.25306
Stejskal, E. O., & Tanner, J. E. (1965). Spin diffusion measurements: spin echoes in the presence of a time‐dependent field gradient. The Journal of Chemical Physics, 42(1), 288–292.
Neurocognitive tractographic assessment
Neurocognitive tractographic assessment (NTA) is an emerging field that aims at enhancing research and clinical practice based on the integration of neuropsychology, neuroimaging, bioinformatics, biophysics, and biomedicine. NTA combines different levels, including genetics, neurochemistry (hormones, neurotransmitters), cognitive microstructure (i.e. the study of neural networks by tractography), brain morphometry, cognitive ontologies (behavioral and mental concepts), and social scaffolding.
‘All Life Is Problem Solving’