Modeling Infant i's Look on Trial t: Race-Face Preference Depends on i's Looking Style.
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ABSTRACT:
SUBMITTER: Thomas H
PROVIDER: S-EPMC5481384 | biostudies-other | 2017
REPOSITORIES: biostudies-other
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Project description:Denitrification plays a critical role in regulating ecosystem nutrient availability and anthropogenic reactive nitrogen (N) production. Its importance has inspired an increasing number of studies, yet it remains the most poorly constrained term in terrestrial ecosystem N budgets. We censused the peer-reviewed soil denitrification literature (1975-2015) to identify opportunities for future studies to advance our understanding despite the inherent challenges in studying the process. We found that only one-third of studies reported estimates of both nitrous oxide (N2 O) and dinitrogen (N2 ) production fluxes, often the dominant end products of denitrification, while the majority of studies reported only net N2 O fluxes or denitrification potential. Of the 236 studies that measured complete denitrification to N2 , 49% used the acetylene inhibition method, 84% were conducted in the laboratory, 81% were performed on surface soils (0-20 cm depth), 75% were located in North America and Europe, and 78% performed treatment manipulations, mostly of N, carbon, or water. To improve understanding of soil denitrification, we recommend broadening access to technologies for new methodologies to measure soil N2 production rates, conducting more studies in the tropics and on subsoils, performing standardized experiments on unmanipulated soils, and using more precise terminology to refer to measured process rates (e.g., net N2 O flux or denitrification potential). To overcome the greater challenges in studying soil denitrification, we envision coordinated research efforts based on standard reporting of metadata for all soil denitrification studies, standard protocols for studies contributing to a Global Denitrification Research Network, and a global consortium of denitrification researchers to facilitate sharing ideas, resources, and to provide mentorship for researchers new to the field.
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Project description:BackgroundGame-based learning is a successful strategy for teaching various concepts to students, from general orientations to more in-depth material. Pharmacy students in a first-year lab course were introduced to library and drug information resources through a lecture-style class in their first week of school, which was ineffective in terms of engagement. To combat this issue, the pharmacy liaison librarian advocated for moving this class session later in the semester and proposed a game-based activity to replace the lecture.Case presentation"The Amazing Race: Drug Information Edition" was inspired by a well-known TV competition that involves completing several stages (called "legs") of challenges to finish the race. The librarian developed questions designed to make students use various parts of the library website as well as two drug information databases. Students competed in teams, and the first three teams to complete the race were awarded small prizes. The race was first implemented in 2018, and modifications were made to the 2019 iteration based on student feedback.ConclusionsDespite several challenges, the race was well received by both the students and the course instructors and increased engagement with introductory library and drug information material. The activity has enhanced the librarian's relationship and collaboration with the course faculty and made a positive impression on the students.
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Project description:Principles of a dynamic, dyadic systems view of mother-infant face-to-face communication, which considers self- and interactive processes in relation to one another, were tested. The process of interaction across time in a large low-risk community sample at infant age 4 months was examined. Split-screen videotape was coded on a 1-s time base for communication modalities of attention, affect, orientation, touch, and composite facial-visual engagement. Time-series approaches generated self- and interactive contingency estimates in each modality. Evidence supporting the following principles was obtained: (a) Significant moment-to-moment predictability within each partner (self-contingency) and between the partners (interactive contingency) characterizes mother-infant communication. (b) Interactive contingency is organized by a bidirectional, but asymmetrical, process: Maternal contingent coordination with infant is higher than infant contingent coordination with mother. (c) Self-contingency organizes communication to a far greater extent than interactive contingency. (d) Self- and interactive contingency processes are not separate; each affects the other in communication modalities of facial affect, facial-visual engagement, and orientation. Each person's self-organization exists in a dynamic, homoeostatic (negative feedback) balance with the degree to which the person coordinates with the partner. For example, those individuals who are less facially stable are likely to coordinate more strongly with the partner's facial affect and vice versa. Our findings support the concept that the dyad is a fundamental unit of analysis in the investigation of early interaction. Moreover, an individual's self-contingency is influenced by the way the individual coordinates with the partner. Our results imply that it is not appropriate to conceptualize interactive processes without simultaneously accounting for dynamically interrelated self-organizing processes.
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Project description:Damage to the right fusiform face area can disrupt the ability to recognize faces, a classic example of how damage to a specialized brain region can disrupt a specialized brain function. However, similar symptoms can arise from damage to other brain regions, and face recognition is now thought to depend on a distributed brain network. The extent of this network and which regions are critical for facial recognition remains unclear. Here, we derive this network empirically based on lesion locations causing clinically significant impairments in facial recognition. Cases of acquired prosopagnosia were identified through a systematic literature search and lesion locations were mapped to a common brain atlas. The network of brain regions connected to each lesion location was identified using resting state functional connectivity from healthy participants (n = 1000), a technique termed lesion network mapping. Lesion networks were overlapped to identify connections common to lesions causing prosopagnosia. Reproducibility was assessed using split-half replication. Specificity was assessed through comparison with non-specific control lesions (n = 135) and with control lesions associated with symptoms other than prosopagnosia (n = 155). Finally, we tested whether our facial recognition network derived from clinically evident cases of prosopagnosia could predict subclinical facial agnosia in an independent lesion cohort (n = 31). Our systematic literature search identified 44 lesions causing prosopagnosia, only 29 of which intersected the right fusiform face area. However, all 44 lesion locations fell within a single brain network defined by connectivity to the right fusiform face area. Less consistent connectivity was found to other face-selective regions. Surprisingly, all 44 lesion locations were also functionally connected, through negative correlation, with regions in the left frontal cortex. This connectivity pattern was highly reproducible and specific to lesions causing prosopagnosia. Positive connectivity to the right fusiform face area and negative connectivity to left frontal regions were independent predictors of prosopagnosia and predicted subclinical facial agnosia in an independent lesion cohort. We conclude that lesions causing prosopagnosia localize to a single functionally connected brain network defined by connectivity to the right fusiform face area and to left frontal regions. Implications of these findings for models of facial recognition deficits are discussed.
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Project description:Additive and multiplicative regression models of habituation were compared regarding the fit to looking times from a habituation experiment with infants aged between 3 and 11 months. In contrast to earlier studies, the current study considered multiple probability distributions, namely Weibull, gamma, lognormal and normal distribution. In the habituation experiment the type of contrast between the habituation and the test trial was varied (luminance, color or orientation contrast), crossed with the number of habituation trials (1, 3, 5, or 7 habituation trials) and crossed with three age cohorts (4, 7, 10 months). The initial mean LT to dark stimuli (around 3.7 s) was considerably shorter than the mean LT to green and gray stimuli (around 5 s). Infants showed the strongest dishabituation to changes from dark to bright (luminance contrast) and weak-to-no dishabituation to a 90-degrees rotation of the gray stimuli (orientation contrast). The dishabituation was stronger after five and seven habituation trials, but the result was not statistically robust. The gamma distribution showed the best fit in terms of log-likelihood and mean absolute error and the best predictive performance. Furthermore, the gamma distribution showed small correlations between parameters relative to other models. The normal additive model showed an inferior fit and medium correlations between the parameters. In particular, the positive correlation between the initial looking time (LT) and the habituation rate was likely responsible for a different interpretation relative to the multiplicative models of the main effect of age on the habituation rate. Otherwise, the additive and multiplicative models provided similar statistical conclusions. The performance of the model versions without pooling and with partial pooling across participants (also called random-effects, multi-level or hierarchical models) were compared. The latter type of models showed worse data fit but more precise predictions and reduced correlations between the parameters. The performance of model variants with auto-regressive time structures were explored but showed considerably worse fit. The performance of quadratic models that allowed non-monotonic changes in LTs were investigated as well. However, when fitted with LT data, these models did not produce non-monotonic change in LTs. The study underscores the utility of partial-pooling models in terms of providing more accurate predictions. Further, it agrees with previous research in that a multiplicative LT model is preferable. Nevertheless, the current results suggest that the impact of the choice of an additive model on the statistical inference is less dramatic then previously assumed.
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