Global excitability and network structure in the human brain

We utilize a model of Wilson-Cowan oscillators to investigate structure-function relationships in the human brain by means of simulations of the spontaneous dynamics of brain networks generated through human connectome data. This allows us to establish relationships between the global excitability of such networks and global structural network quantities for connectomes of two different sizes for a number of individual subjects. We compare the qualitative behavior of such correlations between biological networks and shuffled networks, the latter generated by shuffling the pairwise connectivities of the former while preserving their distribution. Our results point towards a remarkable propensity of the brain's to achieve a trade-off between low network wiring cost and strong functionality, and highlight the unique capacity of brain network topologies to exhibit a strong transition from an inactive state to a globally excited one.Comment: 12 pages, 10 figure

Network analysis of the human structural connectome including the brainstem: a new perspective on consciousness

The underlying anatomical structure is fundamental to the study of brain networks and is likely to play a key role in the generation of conscious experience. We conduct a computational and graph-theoretical study of the human structural connectome incorporating a variety of subcortical structures including the brainstem, which is typically not considered in similar studies. Our computational scheme involves the use of Python DIPY and Nibabel libraries to develop an averaged structural connectome comprised of 100 healthy adult subjects. We then compute degree, eigenvector, and betweenness centralities to identify several highly connected structures and find that the brainstem ranks highest across all examined metrics. Our results highlight the importance of including the brainstem in structural network analyses. We suggest that structural network-based methods can inform theories of consciousness, such as global workspace theory (GWT), integrated information theory (IIT), and the thalamocortical loop theory.Comment: 23 pages, 5 figure

Network analysis of the human structural connectome including the brainstem

The underlying anatomical structure is fundamental to the study of brain networks, but the role of brainstem from a structural perspective is not very well understood. We conduct a computational and graph-theoretical study of the human structural connectome incorporating a variety of subcortical structures including the brainstem. Our computational scheme involves the use of Python DIPY and Nibabel libraries to develop structural connectomes using 100 healthy adult subjects. We then compute degree, eigenvector, and betweenness centralities to identify several highly connected structures and find that the brainstem ranks highest across all examined metrics, a result that holds even when the connectivity matrix is normalized by volume. We also investigated some global topological features in the connectomes, such as the balance of integration and segregation, and found that the domination of the brainstem generally causes networks to become less integrated and segregated. Our results highlight the importance of including the brainstem in structural network analyses

The antagonist SPECT tracer 123I-iododexetimide binds preferentially to the muscarinic M1 receptor in-vivo, but is it also a potential tool to assess the occupancy of muscarinic M1 receptors by agonists?

Cognitive deterioration in neuropsychiatric disorders is associated with high attrition rates giving an urgent need to develop better pharmaceutical therapies. The underlying mechanisms of cognitive impairments are unclear but research has shown that the muscarinic receptor subtype 1 (M1 receptor) plays a critical role. Blocking the M1 receptor gives rise to profound cognitive deficits, while the administration of M1 agonist drugs improves cognitive functioning. In this research highlight we will outline supporting data that the radiotracer 123I-iododexetimide preferentially binds to the M1 receptor in-vivo and can be used to assess changes in M1 receptor expression in-vivo associated with cognitive decline. These findings come from a previously published paper extensively examining binding characteristics of 123/127I-iododexetimide to muscarinic receptors. Results of biodistribution studies also has shown that acute administration of the M1/4 receptor agonist xanomeline could inhibit 127I-iododexetimide binding in M1-rich brain areas in rats, suggesting that 123I-iododexetimide may also be used to evaluate the occupancy of M1 receptors by M1 agonists in-vivo. This may be of clinical relevance considering the efficacy of M1 agonist drugs in the treatment of cognitive deficits. Here we show the results from new biodistribution experiments in rats conducted to test the hypothesis that 123I-iododexetimide may be a useful radiotracer to evaluate the M1 receptor occupancy by M1 agonists in-vivo. Contrary to our expectations, no significant change in 123I-iododexetimide ex-vivo binding was observed after acute administration of xanomeline in M1 receptor-rich brain areas, whereas significantly decreased 123I-iododexetimide binding was found after chronic treatment with xanomeline. 123I-iododexetimide single photon emission computed tomography (SPECT) may therefore be a useful imaging tool to further evaluate M1 receptor changes in neuropsychiatric disorders, as a potential stratifying biomarker, to assess the occupancy of M1 receptors after M1 antagonist treatment, or after chronic treatment with M1 agonists, although it may be less suited to evaluate the M1 receptor occupancy after acute treatment with M1 agonists. Future studies should concentrate efforts towards finding also an M1 agonist radiotracer for positron emission tomography (PET) or SPECT to assess the working mechanism of M1 agonists