Population-Based Tract-To-Region Connectome of the Human Brain and Its Hierarchical Topology

Connectome maps region-to-region connectivities but does not inform which white matter pathways form the connections. Here we constructed the first population-based tract-to-region connectome to fill this information gap. The constructed connectome quantifies the population probability of a white matter tract innervating a cortical region. The results show that ~85% of the tract-to-region connectome entries are consistent across individuals, whereas the remaining (~15%) have substantial individual differences requiring individualized mapping. Further hierarchical clustering on cortical regions revealed their parcellations into dorsal, ventral, and limbic networks based on the tract-to-region connective patterns. The clustering results on white matter bundles revealed the connectome-based categorization of fiber bundle systems in the association pathways. This new tract-to-region connectome provides insights into the connective topology between cortical regions and white matter bundles. The derived hierarchical relation further offers a connectome-based categorization of gray matter and white matter structures.

Panel experiments and dynamic causal effects: A finite population perspective

In panel experiments, we randomly assign units to different interventions, measuring their outcomes, and repeating the procedure in several periods. Using the potential outcomes framework, we define finite population dynamic causal effects that capture the relative effectiveness of alternative treatment paths. For a rich class of dynamic causal effects, we provide a nonparametric estimator that is unbiased over the randomization distribution and derive its finite population limiting distribution as either the sample size or the duration of the experiment increases. We develop two methods for inference: a conservative test for weak null hypotheses and an exact randomization test for sharp null hypotheses. We further analyze the finite population probability limit of linear fixed effects estimators. These commonly‐used estimators do not recover a causally interpretable estimand if there are dynamic causal effects and serial correlation in the assignments, highlighting the value of our proposed estimator.

DYNAMIC PROPERTIES OF THE LARGE-DETUNING CAVITY QED SYSTEM IN THE PRESENCE OF CAVITY DECAY

We consider a physical process of two Λ-type three-level atoms interacting with a bimodal cavity including the influence of the cavity decay. We analyze the influence of cavity decay on several physical quantities of the process, such as atomic population probability, residual entanglement, concurrence of two atoms, average population inversion, average photon number, the fidelity for quantum phase gate, and the fidelity of generating atomic EPR state. It is found that all of these physical quantities decrease with the increase of cavity decay when the other relevant parameters are fixed.

Population versus Clinical Perspectives on Smoking Behaviour

Effective mass-reach smoking-cessation interventions are required in order to accelerate the decline in the prevalence of smoking in Australia and other industrialised countries. Such large-scale interventions still rely, to a major extent, on theoretical principles derived from research with clinical or other opportunistic samples. Schachter (1982) argues that this type of research provides information which is unrepresentative of smokers in the general population. We compared a population-probability sample with a sample of smokers enrolling in a smoking-cessation program offered by a community health centre. The health centre sample was composed of predominantly female, older smokers who had higher smoking rates, had made more previous attempts to stop smoking, and tended to attribute their last relapse to irritability. We discuss some potential implications for research relevant to population-wide smoking control strategies.