Our poster will facilitate discussion of cognition driven primarily by physiology, emotions, sociality, and reason, i.e., therational and beyond rational. First, we take cognition to be the origin of all observable behavior. There is a growingliterature on emotional and social determinants of behavior. Physiological contributions to behavior (e.g., hunger, thirst,arousal/fatigue) are also being incorporated into recent cognitive models. We offer an approach to integrate these types ofcognition that can explain behavior over a much wider range of situations than current approaches. Their integration rangesfrom a recognition that one of the four is the overwhelming driver in extreme conditions, but otherwise their integrationis more nuanced with evidence of a general ordering. We will present and discuss approaches for their integration basedon their relative severity leading to a cognitive architecture that can represent the full spectrum of behavior, i.e., behavioroutside the laboratory.

Simulations of many people’s decisions are used in public health and safety as well as to support policymaking.These simulations rely on creditable models of individual decision-making. An obvious approach is to develop a list of plausibleactions and to then evaluate the benefits of each in the current situation to make the decision. However, such evaluations canbe implausible, e.g., zero-intelligence traders in economics, or impracticable because the approach is computationally intensivefor large-scale simulations. As a result, a commonly used approach is to select randomly from the plausible actions. Withoutdata on how people would actually chose, a random number from a uniform distribution over the plausible options is often usedto represent the unknown cognition. However, we claim that substituting a uniform random distribution for how people makedecisions is making very strong claims about the process and we will present data demonstrating it is simply wrong.

Background and objective

Vascular ectasia in port wine stain birthmarks (PWS) might result from reduced innervation with loss of autonomic stimulation. We investigated this theory and evaluated nerve and blood vessel density, and mean blood vessel size in untreated and treated PWS skin.

Methods

Skin biopsy specimens were obtained from uninvolved skin, untreated PWS, PWS with a good response to laser treatment and PWS with a poor response to laser treatment. Confocal microscopy was performed to determine nerve and blood vessel density, and mean blood vessel size.

Results

Nerve density was significantly decreased in all PWS sites compared to uninvolved skin. Mean blood vessel diameter was larger in untreated compared to treated PWS. PWS with a good response to treatment had decreased nerve density but blood vessel density and mean diameter was relatively normal. PWS with a poor response to treatment had decreased nerve density but increased blood vessel density and mean blood vessel diameter compared to normal skin.

Conclusion

Nerve density was decreased in all evaluated PWS sites and this may be a factor in lesion pathogenesis. PWS blood vessel size correlated with pulsed dye laser response and may prove to be a useful prognostic indicator of therapeutic outcome.

The Muller F element (4.2 Mb, ~80 protein-coding genes) is an unusual autosome of Drosophila melanogaster; it is mostly heterochromatic with a low recombination rate. To investigate how these properties impact the evolution of repeats and genes, we manually improved the sequence and annotated the genes on the D. erecta, D. mojavensis, and D. grimshawi F elements and euchromatic domains from the Muller D element. We find that F elements have greater transposon density (25-50%) than euchromatic reference regions (3-11%). Among the F elements, D. grimshawi has the lowest transposon density (particularly DINE-1: 2% vs. 11-27%). F element genes have larger coding spans, more coding exons, larger introns, and lower codon bias. Comparison of the Effective Number of Codons with the Codon Adaptation Index shows that, in contrast to the other species, codon bias in D. grimshawi F element genes can be attributed primarily to selection instead of mutational biases, suggesting that density and types of transposons affect the degree of local heterochromatin formation. F element genes have lower estimated DNA melting temperatures than D element genes, potentially facilitating transcription through heterochromatin. Most F element genes (~90%) have remained on that element, but the F element has smaller syntenic blocks than genome averages (3.4-3.6 vs. 8.4-8.8 genes per block), indicating greater rates of inversion despite lower rates of recombination. Overall, the F element has maintained characteristics that are distinct from other autosomes in the Drosophila lineage, illuminating the constraints imposed by a heterochromatic milieu.