Tracking the Development of Functional Connectomes for Face Processing.

Face processing capacities become more specialized and advanced during development, but neural underpinnings of these processes are not fully understood. The present study applied graph theory-based network analysis to task-negative (resting blocks) and task-positive (viewing faces) functional magnetic resonance imaging data in children (5-17 years) and adults (18-42 years) to test the hypothesis that the development of a specialized network for face processing is driven by task-positive processing (face viewing) more than by task-negative processing (visual fixation) and by both progressive and regressive changes in network properties. Predictive modeling was used to predict age from node-based network properties derived from task-positive and task-negative states in a whole-brain network (WBN) and a canonical face network (FN). The best-fitting model indicated that FN maturation was marked by both progressive and regressive changes in information diffusion (eigenvector centrality) in the task-positive state, with regressive changes outweighing progressive changes. Hence, FN maturation was characterized by reductions in information diffusion potentially reflecting the development of more specialized modules. In contrast, WBN maturation was marked by a balance of progressive and regressive changes in hub-connectivity (betweenness centrality) in the task-negative state. These findings suggest that the development of specialized networks like the FN depends on dynamic developmental changes associated with domain-specific information (e.g., face processing), but maturation of the brain as a whole can be predicted from task-free states.

The changing landscape of functional brain networks for face processing in typical development.

Greater expertise for faces in adults than in children may be achieved by a dynamic interplay of functional segregation and integration of brain regions throughout development. The present study examined developmental changes in face network functional connectivity in children (5-12 years) and adults (18-43 years) during face-viewing using a graph-theory approach. A face-specific developmental change involved connectivity of the right occipital face area. During childhood, this node increased in strength and within-module clustering based on positive connectivity. These changes reflect an important role of the ROFA in segregation of function during childhood. In addition, strength and diversity of connections within a module that included primary visual areas (left and right calcarine) and limbic regions (left hippocampus and right inferior orbitofrontal cortex) increased from childhood to adulthood, reflecting increased visuo-limbic integration. This integration was pronounced for faces but also emerged for natural objects. Taken together, the primary face-specific developmental changes involved segregation of a posterior visual module during childhood, possibly implicated in early stage perceptual face processing, and greater integration of visuo-limbic connections from childhood to adulthood, which may reflect processing related to development of perceptual expertise for individuation of faces and other visually homogenous categories.

Influence of estradiol on functional brain organization for working memory.

Working memory is a cognitive function that is affected by aging and disease. To better understand the neural substrates for working memory, the present study examined the influence of estradiol on working memory using functional magnetic resonance imaging. Pre-menopausal women were tested on a verbal n-back task during the early (EF) and late follicular (LF) phases of the menstrual cycle. Although brain activation patterns were similar across the two phases, the most striking pattern that emerged was that estradiol had different associations with the two hemispheres. Increased activation in left frontal circuitry in the LF phase was associated with increased estradiol levels and decrements in working memory performance. In contrast, increased activation in right hemisphere regions in the LF phase was associated with improved task performance. The present study showed that better performance in the LF than the EF phase was associated with a pattern of reduced recruitment of the left-hemisphere and increased recruitment of the right-hemisphere in the LF compared to EF phase. We speculate that estradiol interferes with left-hemisphere working-memory processing in the LF phase, but that recruitment of the right hemisphere can compensate for left-hemisphere interference. This may be related to the proposal that estradiol can reduce cerebral asymmetries by modulating transcallosal communication (Hausmann, 2005).

The pattern of responding in the peak-interval procedure with gaps: an individual-trials analysis.

Humans and lower animals time as if using a stopwatch that can be "stopped" or "reset" on command. This view is challenged by data from the peak-interval procedure with gaps: Unexpected retention intervals (gaps) delay the response function in a seemingly continuous fashion, from stop to reset. We evaluated whether these results are an artifact of averaging over trials, or whether subjects use discrete alternatives or a continuum of alternatives in individual-trials: A Probability-of-Reset hypothesis proposes that in individual gap trials subjects stochastically use discrete alternatives (stop/reset), such that when averaged over trials, the response distribution in gap trials falls in between "stop" and "reset." Alternatively, a Resource Allocation hypothesis proposes that during individual gap trials working memory for the pregap duration decays, such that the response function in individual gap trials is shifted rightward in a continuous fashion. Both hypotheses provided very good fits with the observed individual-trial distributions, although the Resource Allocation hypothesis generated reliably better fits. Results provide support for the usefulness of individual-trial analyses in dissociating theoretical alternatives in interval timing tasks.

Interval timing accuracy and scalar timing in C57BL/6 mice.

In many species, interval timing behavior is accurate-appropriate estimated durations-and scalar-errors vary linearly with estimated durations. Whereas accuracy has been previously examined, scalar timing has not been clearly demonstrated in house mice (Mus musculus), raising concerns about mouse models of human disease. The authors estimated timing accuracy and precision in C57BL/6 mice, the most used background strain for genetic models of human disease, in a peak-interval procedure with multiple intervals. Both when timing 2 intervals (Experiment 1) or 3 intervals (Experiment 2), C57BL/6 mice demonstrated varying degrees of timing accuracy. An important finding was that, both at the individual and group levels, their precision varied linearly with the subjective estimated duration. Further evidence for scalar timing was obtained using an intraclass correlation statistic. This is the first report of consistent, reliable scalar timing in a sizable sample of house mice, thus validating the peak-interval procedure as a valuable technique, the intraclass correlation statistic as a powerful test of the scalar property, and the C57BL/6 strain as a suitable background for behavioral investigations of genetically engineered mice modeling disorders of interval timing.