Advance information about an impending stimulus facilitates its subsequent identification and ensuing behavioral responses. This facilitation is thought to be mediated by top-down control signals from frontal and parietal cortex that modulate sensory cortical activity. Here we show, using Granger causality measures on blood oxygen level-dependent time series, that frontal eye field (FEF) and intraparietal sulcus (IPS) activity predicts visual occipital activity before an expected visual stimulus. Top-down levels of Granger causality from FEF and IPS to visual occipital cortex were significantly greater than both bottom-up and mean cortex-wide levels in all individual subjects and the group. In the group and most individual subjects, Granger causality was significantly greater from FEF to IPS than from IPS to FEF, and significantly greater from both FEF and IPS to intermediate-tier than lower-tier ventral visual areas. Moreover, top-down Granger causality from right IPS to intermediate-tier areas was predictive of correct behavioral performance. These results suggest that FEF and IPS modulate visual occipital cortex, and FEF modulates IPS, in relation to visual attention. The current approach may prove advantageous for the investigation of interregional directed influences in other human brain functions.

We investigated afferent inputs from all areas in the frontal cortex (FC) to different subregions in the rostral anterior cingulate cortex (rACC). Using retrograde tracing in macaque monkeys, we quantified projection strength by counting retrogradely labeled cells in each FC area. The projection from different FC regions varied across injection sites in strength, following different spatial patterns. Importantly, a site at the rostral end of the cingulate sulcus stood out as having strong inputs from many areas in diverse FC regions. Moreover, it was at the integrative conjunction of three projection trends across sites. This site marks a connectional hub inside the rACC that integrates FC inputs across functional modalities. Tractography with monkey diffusion magnetic resonance imaging (dMRI) located a similar hub region comparable to the tracing result. Applying the same tractography method to human dMRI data, we demonstrated that a similar hub can be located in the human rACC.

Summary Overdispersion and structural zeros are two major manifestations of departure from the Poisson assumption when modeling count responses using Poisson loglinear regression. As noted in a large body of literature, ignoring such departures could yield bias and lead to wrong conclusions. Different approaches have been developed to tackle these two major problems. In this paper, we review available methods for dealing with overdispersion and structural zeros within a longitudinal data setting and propose a distribution-free modeling approach to address the limitations of these methods by utilizing a new class of functional response models (FRM). We illustrate our approach with both simulated and real study data.

Young lesbian, gay, and bisexual (young LGB) individuals report higher rates of suicide ideation and attempts from their late teens through early twenties. Their high rate of Internet use suggests that online social networks offer a novel opportunity to reach them. This study explores online social networks as a venue for prevention research targeting young LGB. An automated data collection program was used to map the social connections between LGB self-identified individuals between 16 and 24 years old participating in an online social network. We then completed a descriptive analysis of the structural characteristics known to affect diffusion within such networks. Finally, we conducted Monte Carlo simulations of peer-driven diffusion of a hypothetical preventive intervention within the observed network under varying starting conditions. We mapped a network of 100,014 young LGB. The mean age was 20.4 years. The mean nodal degree was 137.5, representing an exponential degree distribution ranging from 1 through 4,309. Monte Carlo simulations revealed that a peer-driven preventive intervention ultimately reached final sample sizes of up to 18,409 individuals. The network's structure is consistent with other social networks in terms of the underlying degree distribution. Such networks are typically formed dynamically through a process of preferential attachment. This implies that some individuals could be more important to target to facilitate the diffusion of interventions. However, in terms of determining the success of an intervention targeting this population, our simulation results suggest that varying the number of peers that can be recruited is more important than increasing the number of randomly-selected starting individuals. This has implications for intervention design. Given the potential to access this