Extraction of prefronto-amygdalar pathways by combining probability maps

Tobias Bracht, Oliver Tüscher, Susanne Schnell, Björn Kreher, Nicolas Rüsch, Volkmar Glauche, Klaus Lieb, Dieter Ebert, Kamil A. Il'yasov, Jürgen Hennig, Cornelius Weiller, Ludger Tebartz van Elst*, Dorothee Saur

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

41 Scopus citations

Abstract

Many recent studies reported altered functional connectivity within the frontolimbic circuitry in a wide range of neuropsychiatric disorders. However, functional connectivity must rely on structural connections. In this study we applied a novel probabilistic fiber tracking method to assess the structural connectivity between the amygdala and different prefrontal brain regions in vivo. Twenty healthy subjects were investigated with diffusion tensor imaging. Probabilistic fiber tracking was started from the amygdala and different prefrontal brain regions. Resulting probability maps were combined using an extended multiplication of probabilistic maps to identify the most probable anatomical pathways connecting these structures. We found one ventral pathway through the uncinate fascicle, connecting the amygdala and the medial and lateral orbitofrontal cortices. In addition to this ventral pathway, we depicted distinct dorsal pathways (medial and lateral), which connect the amygdala with the anterior cingulate cortex and the dorsolateral prefrontal cortex. The dorso-medial pathway proceeds through the inferior thalamic peduncle, while the dorsolateral pathway travels through the external capsule. We believe that our approach provides a promising tool to assess the integrity of specific structural connections in patients with neuropsychiatric disorders.

Original languageEnglish (US)
Pages (from-to)217-222
Number of pages6
JournalPsychiatry Research - Neuroimaging
Volume174
Issue number3
DOIs
StatePublished - Dec 30 2009

Keywords

  • Amygdala
  • DTI
  • Prefrontal cortex
  • Probabilistic tracking

ASJC Scopus subject areas

  • Neuroscience (miscellaneous)
  • Radiology Nuclear Medicine and imaging
  • Psychiatry and Mental health

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