What makes the prefrontal cortex so appealing in the era of brain imaging? A network analytical perspective

Abstract

It is thought that the prefrontal cortex (PFC) subserves cognitive control processes by coordinating the flow of information in the cerebral cortex. In the network of cortical areas the central position of the PFC makes difficult to dissociate processing and the cognitive function mapped to this region, especially when using whole brain imaging techniques, which can detect frequently activated regions. Accordingly, the present study showed particularly high rate of increase of published studies citing the PFC and imaging as compared to other fields of the neurosciences on the PubMed. Network measures used to characterize the role of the areas in signal flow indicated specialization of the different regions of the PFC in cortical processing. Notably, areas of the dorsolateral PFC and the anterior cingulate cortex, which received the highest number of citations, were identified as global convergence points in the network. These prefrontal regions also had central position in the dominant cluster consisted exclusively by the associational areas of the cortex. We also present findings relevant to models suggesting that control processes of the PFC are depended on serial processing, which results in bottleneck effects. The findings suggest that PFC is best understood via its role in cortical information processing.

Efficiency of weak brain connections support general cognitive functioning

“…This finding may be interpreted within the framework of the parietofrontal integration theory of intelligence [Jung and Haier, 2007], which received large experimental support using a number of imaging techniques, such as structural MRI [Narr et al, 2007], diffusion weighted MRI [Chiang et al, 2009] and task-fMRI [Choi et al, 2008;Yuan et al, 2012]. In this respect, our finding of an involvement of the prefrontal lobes bilaterally may suggest that an increase of information transfer between these regions and the rest of the brain plays a crucial role in higher-order cognition [Negyessy et al, 2012]. In this respect, our finding of an involvement of the prefrontal lobes bilaterally may suggest that an increase of information transfer between these regions and the rest of the brain plays a crucial role in higher-order cognition [Negyessy et al, 2012].…”

“…In particular, the anterior cingulate cortex has been associated with intellectual functioning because of the positive correlation between its fractional anisotropy and intelligence [Chiang et al, 2009], and for structurally interconnecting the medial frontal lobes [van den Heuvel et al, 2008]. In this respect, our finding of an involvement of the prefrontal lobes bilaterally may suggest that an increase of information transfer between these regions and the rest of the brain plays a crucial role in higher-order cognition [Negyessy et al, 2012]. Moreover, consistent with previous research [Gour et al, 2011;Maguire et al, 2000], the involvement of the hippocampus and temporal pole may be expression of their central role in memory, and an increase in their seed-to-brain information transfer may represent a preparatory process for evoked activity.…”

Network Path Convergence Shapes Low-Level Processing in the Visual Cortex

“…Up to now convergence degree has been computed only in binary networks (Négyessy et al, 2008 , 2012 ; Bányai et al, 2011b ). Our findings show that the CD can also be computed for weighted networks (denoted CDw), increasing the power of this index zin network analysis.…”

“…In the cerebral cortex, CD revealed the mostly complementary divergent and convergent nature of reciprocal links and that this complementarity resulted in the formation of nearly symmetrical forward and backward subnetworks. Furthermore, the sum of the inward and outward convergence degrees of a node provided the node-centric representation of convergence/divergence, which is a useful measure of the coordinative function of cortical areas (Négyessy et al, 2008(Négyessy et al, , 2012. Specifically, low-level areas including primary sensory cortices, serve as sources of information via their mostly divergent outputs and convergent inputs.…”

“…Large-scale hierarchical network dynamics were simulated by a bilaminar Wilson–Cowan model, suitable for studying the oscillatory characteristics of feedforward and feedback interactions (Mejias et al, 2016 ). First of all, we aimed to extend the use of CD to weighted networks, as this index has been defined and applied only for binary graphs before (Négyessy et al, 2008 , 2012 ; Bányai et al, 2011b ). To this end, a refined combination of existing methods was developed for finding shortest paths in weighted graphs, which favors robustness at the expense of a winner-take-all approach (Newman, 2001 , 2005 ; Opsahl et al, 2010 ; Avena-Koenigsberger et al, 2018 ).…”