From Habitat Use to Social Behavior Natural History of a Voiceless Poison Frog, Dendrobates tinctorius, bioRxiv, 2019-01-09

Descriptive studies of natural history have always been a source of knowledge on which experimental work and scientific progress rely. Poison frogs are a well-studied group of small Neotropical frogs with diverse parental behaviors, distinct calls, and bright colors that warn predators about their toxicity; and a showcase of advances in fundamental biology through natural history observations. The dyeing poison frog, Dendrobates tinctorius, is emblematic of the Guianas region, widespread in the pet-trade, and increasingly popular in research. This species shows several unusual behaviors, such as the lack of advertisement calls and the aggregation around tree-fall gaps, which remain poorly described and understood. Here, we summarize our observations from a natural population of D. tinctorius in French Guiana collected over various field trips between 2009 and 2017; our aim is to provide groundwork for future fundamental and applied research spanning parental care, animal dispersal, disease spread, habitat use in relation to color patterns, and intra specific communication, to name a few. We report sex differences in habitat use and the striking invasion of tree-fall gaps; describe their courtship and aggressive behaviors; document egg development and tadpole transport; and discuss how the knowledge generated by this study could set the grounds for further research on the behavior, ecology, and conservation of this species.

biorxiv animal-behavior-and-cognition 0-100-users 2019

Associations between vascular risk factors and brain MRI indices in UK Biobank Supplementary Material, bioRxiv, 2019-01-04

Aims Several factors are known to increase risk for cerebrovascular disease and dementia, but there is limited evidence on associations between multiple vascular risk factors (VRFs) and detailed aspects of brain macro- and microstructure in large community-dwelling populations across middle- and older age. Methods and Results Associations between VRFs (smoking, hypertension, pulse pressure, diabetes, hypercholersterolaemia, BMI, and waist-hip ratio) and both global and regional brain structural and diffusion MRI markers were examined in UK Biobank (N = 9722, age range 44-77 years). A larger number of VRFs was associated with greater brain atrophy, lower grey matter volume, and poorer white matter health. Effect sizes were small (brain structural R2 ≤ 1.8%). Higher aggregate vascular risk was related to multiple regional MRI hallmarks associated with dementia risk lower frontal and temporal cortical volumes, lower subcortical volumes, higher white matter hyperintensity volumes, and poorer white matter microstructure in association and thalamic pathways. Smoking pack years, hypertension and diabetes showed the most consistent associations across all brain measures. Hypercholesterolaemia was not uniquely associated with any MRI marker. Conclusion Higher levels of VRFs were associated with poorer brain health across grey and white matter macro- and microstructure. Effects are mainly additive, converging upon frontal and temporal cortex, subcortical structures, and specific classes of white matter fibres. Though effect sizes were small, these results emphasise the vulnerability of brain health to vascular factors even in relatively healthy middle and older age, and the potential to partly ameliorate cognitive decline by addressing these malleable risk factors.

biorxiv neuroscience 0-100-users 2019

Fundamental bounds on learning performance in neural circuits, bioRxiv, 2019-01-01

How does the size of a neural circuit influence its learning performance? Intuitively, we expect the learning capacity of a neural circuit to grow with the number of neurons and synapses. Larger brains tend to be found in species with higher cognitive function and learning ability. Similarly, adding connections and units to artificial neural networks can allow them to solve more complex tasks. However, we show that in a biologically relevant setting where synapses introduce an unavoidable amount of noise, there is an optimal size of network for a given task. Beneath this optimal size, our analysis shows how adding apparently redundant neurons and connections can make tasks more learnable. Therefore large neural circuits can either devote connectivity to generating complex behaviors, or exploit this connectivity to achieve faster and more precise learning of simpler behaviors. Above the optimal network size, the addition of neurons and synaptic connections starts to impede learning performance. This suggests that overall brain size may be constrained by the need to learn efficiently with unreliable synapses, and may explain why some neurological learning deficits are associated with hyperconnectivity. Our analysis is independent of specific learning rules and uncovers fundamental relationships between learning rate, task performance, network size and intrinsic noise in neural circuits.

biorxiv neuroscience 0-100-users 2019

 

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