"Leaping" methods show great promise for significantly accelerating stochastic simulations of complex biochemical reaction networks. However, few practical applications of leaping have appeared in the literature to date. Here, we address this issue using the "partitioned leaping algorithm" (PLA) [L. A. Harris and P. Clancy, J. Chem. Phys. 125, 144107 (2006)], a recently introduced multiscale leaping approach. We use the PLA to investigate stochastic effects in two model biochemical reaction networks. The networks that we consider are simple enough so as to be accessible to our intuition but sufficiently complex so as to be generally representative of real biological systems. We demonstrate how the PLA allows us to quantify subtle effects of stochasticity in these systems that would be difficult to ascertain otherwise as well as not-so-subtle behaviors that would strain commonly used "exact" stochastic methods. We also illustrate bottlenecks that can hinder the approach and exemplify and discuss possible strategies for overcoming them. Overall, our aim is to aid and motivate future applications of leaping by providing stark illustrations of the benefits of the method while at the same time elucidating obstacles that are often encountered in practice.

Improvements in vehicle safety require understanding of the neural systems that support the complex, dynamic task of real-world driving. We used functional near infrared spectroscopy (fNIRS) and pupilometry to quantify cortical and physiological responses during a realistic, simulated driving task in which vehicle dynamics were manipulated. Our results elucidate compensatory changes in driver behavior in response to changes in vehicle handling. We also describe associated neural and physiological responses under different levels of mental workload. The increased cortical activation we observed during the late phase of the experiment may indicate motor learning in prefrontal-parietal networks. Finally, relationships among cortical activation, steering control, and individual personality traits suggest that individual brain states and traits may be useful in predicting a driver's response to changes in vehicle dynamics. Results such as these will be useful for informing the design of automated safety systems that facilitate safe and supportive driver-car communication.

Here, we investigated processing by receptive fields, a fundamental property of neurons in the visual system, using fMRI and population receptive field (pRF) mapping in 20 human females with monosomic Turner syndrome (TS) (mean age, 10.3 Ϯ 2.0 years) versus 22 ageand sex-matched controls (mean age, 10.4 Ϯ 1.9 years). TS, caused by X-chromosome haploinsufficiency in females, is associated with well-recognized effects on visuospatial processing, parieto-occipital cortical anatomy, and parietal lobe function. However, it is unknown whether these effects are related to altered brain structure and function in early visual areas (V1-V3) versus downstream parietal cortical regions. Results show that girls with TS have the following: (1) smaller volume of V1-V3, (2) lower average pRF eccentricity in early visual areas, and (3) sparser pRF coverage in the periphery of the visual field. Further, we examined whether the lower volume of early visual areas, defined using retinotopic mapping, in TS is due to smaller surface area or thinner cortex. Results show that girls with TS had a general reduction in surface area relative to controls in bilateral V1 and V2. Our data suggest the possibility that the smaller cortical surface area of early visual areas in girls with TS may be associated with a lower number of neurons, which in turn, leads to lesser coverage of the peripheral visual field compared to controls. These results indicate that X-chromosome haploinsufficiency associated with TS affects the functional neuroanatomy of early visual areas, and suggest that investigating pRFs in TS may shed insights into their atypical visuospatial processing.

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Smartphones and other modern technologies have introduced multiple new forms of distraction that color the modern driving experience. While many smartphone functions aim to improve driving by providing the driver with real-time navigation and traffic updates, others, such as texting, are not compatible with driving and are often the cause of accidents. Because both functions elicit driver attention, an outstanding question is the degree to which drivers’ naturalistic interactions with navigation and texting applications differ in regard to brain and behavioral indices of distracted driving. Here, we employed functional near-infrared spectroscopy to examine the cortical activity that occurs under parametrically increasing levels of smartphone distraction during naturalistic driving. Our results highlight a significant increase in bilateral prefrontal and parietal cortical activity that occurs in response to increasingly greater levels of smartphone distraction that, in turn, predicts changes in common indices of vehicle control.