Abstract
The basal ganglia and thalamus play an important role in cognition, procedural learning, eye movements, control of voluntary motor movements, emotional control, habit development, and are structures that are severely impacted by neurological disorders such as Alzheimer’s disease, Parkinson’s disease, or Tourette syndrome. To understand the structural connectivity of cortical and subcortical circuits in the healthy human brain could thus be of pivotal importance for detecting changes in this circuitry and to start early intervention, to assess the progress of movement rehabilitation, or the effectiveness of therapeutic approaches in neuropsychiatry. While conventional magnetic resonance imaging (MRI), positron emission tomography, or magnetoencephalography are able to provide detailed information about connectivity at the macro level, the sensitivity and specificity these imaging techniques put limits on the amount of detail one can obtain when measuring in vivo connectivity of human basal ganglia and thalamus. In contrast, the multiband diffusion echo planar imaging MRI sequence, which acquires multiple slices of the brain simultaneously, enables high resolution imaging of these brain structures with only short acquisition times at 3-Tesla field strength. Here, we introduce a novel protocol that allows us to generate comprehensive in vivo participant-specific probabilistic patterns and visualizations of the structural connections that exist within basal ganglia and thalamic nuclei. Moreover, we are able to map specific parcellations of these nuclei into sub-territories based on their connectivity with primary motor-, and somatosensory cortex. The detailed subcortical structural connectivity mapping introduced in this work could benefit early intervention and therapy methods for human movement rehabilitation and for treating neuropsychiatric disorders.
Footnotes
Email: Irtiza A. Gilani (irtizagilani{at}yahoo.com), Kader K. Oguz (karlioguz{at}yahoo.com), Huseyin Boyaci (hboyaci{at}bilkent.edu.tr), Katja Doerschner (katja{at}bilkent.edu.tr)
Sponsor: TÜBİTAK (Scientific and Technological Research Council of Turkey) 1001 Grant 112K069.