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Mapping the dominant direction of the structural network of the macaque prefrontal cortex reveals its hierarchical structure

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Fens poster - PFC hierarchy.pdf
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Citation

Goulas, A., Uylings, H. B. M., & Stiers, P. (2012). Mapping the dominant direction of the structural network of the macaque prefrontal cortex reveals its hierarchical structure. Poster presented at 8th Forum of Neuroscience (FENS), Barcelona, Spain.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0014-67A6-C
Abstract
The prefrontal cortex is associated with flexible and goal directed behaviour, integrating information from various modalities and bridging the cognitive, emotional, and motivational domain. Several models have been proposed in order to describe its organization including ones that advocate the presence of a hierarchical gradient along the anterior-posterior axis. However, there are several limitations of such models including the absence of a formal quantification of the underlying organization principles. We analyze the structural network of the macaque prefrontal cortex in order to unveil its hierarchical structure by mapping its dominant direction. We use a formal approach employing an algorithm from network science which allows us to quantify the organization principles put forth in hierarchical models. We demonstrate that the prefrontal cortex is not wired in a way to “optimally” comply with a hierarchical structure. Within this “non-optimal” hierarchical organization, while a strict anterior-posterior gradient does not hold, the relations of a subset of prefrontal regions comply with predictions of hierarchical models. Regions in high levels of the traced hierarchy can function as regulators, analogous to regulator structures in large scale biological systems. Additionally, these highly influential regions are dispersed throughout the orbital, medial and lateral surfaces of the prefrontal cortex and can be further differentiated with respect to their role in the cognitive/motivational domain. The findings elucidate the underlying structural organization of the prefrontal cortex and can be used for the enrichment and modification of dominant models.