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

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.

Pathological effects of cortical architecture on working memory in schizophrenia

Neural connectivity of the prefrontal cortex is essential to working memory. Reduction of prefrontal connectivity and abnormal prefrontal dopamine modulation are common characteristics associated with schizophrenia. Two experiments separately modeled the effects of exaggerated pruning and of synaptic depression to imitate schizophrenic performance in a prefrontal neural network. In the first model, effects of cortical pruning were simulated with a set of scale-free networks of neurons and compared with empirical results from the Sternberg working memory task. The second set of simulations were based on the synaptic theory of working memory. Simulations of this model measured memory duration in relation to synaptic facilitation and depression constants and in relation to the level of neural connectivity. In the first set of simulations, modulating levels of cortical pruning resulted in a gain or loss in accuracy and speed of memory recollection. In the second set of simulations, increased facilitation time constants and decreased inhibitory time constants resulting in longer memory durations, and overly connected networks resulted in very low memory durations. In the first model, the decline in memory performance can be attributed to the emergence of pathological memory behavior brought about by the warping of the basins of attraction. Collectively, the simulations demonstrate that a reduction of prefrontal cortical hubs can lead to schizophrenia like performance in neural networks, and may account for pathological working memory in the disorder.