1,207 research outputs found
The evolutionary ecology of decorating behaviour
Many animals decorate themselves through the accumulation of environmental material on their exterior. Decoration has been studied across a range of different taxa, but there are substantial limits to current understanding. Decoration in non-humans appears to function predominantly in defence against predators and parasites, although an adaptive function is often assumed rather than comprehensively demonstrated. It seems predominantly an aquatic phenomenon-presumably because buoyancy helps reduce energetic costs associated with carrying the decorative material. In terrestrial examples, decorating is relatively common in the larval stages of insects. Insects are small and thus able to generate the power to carry a greater mass of material relative to their own body weight. In adult forms, the need to be lightweight for flight probably rules out decoration. We emphasize that both benefits and costs to decoration are rarely quantified, and that costs should include those associated with collecting as well as carrying the material.PostprintPeer reviewe
Nonconservative Lagrangian mechanics II: purely causal equations of motion
This work builds on the Volterra series formalism presented in [D. W.
Dreisigmeyer and P. M. Young, J. Phys. A \textbf{36}, 8297, (2003)] to model
nonconservative systems. Here we treat Lagrangians and actions as `time
dependent' Volterra series. We present a new family of kernels to be used in
these Volterra series that allow us to derive a single retarded equation of
motion using a variational principle
Signal Propagation in Feedforward Neuronal Networks with Unreliable Synapses
In this paper, we systematically investigate both the synfire propagation and
firing rate propagation in feedforward neuronal network coupled in an
all-to-all fashion. In contrast to most earlier work, where only reliable
synaptic connections are considered, we mainly examine the effects of
unreliable synapses on both types of neural activity propagation in this work.
We first study networks composed of purely excitatory neurons. Our results show
that both the successful transmission probability and excitatory synaptic
strength largely influence the propagation of these two types of neural
activities, and better tuning of these synaptic parameters makes the considered
network support stable signal propagation. It is also found that noise has
significant but different impacts on these two types of propagation. The
additive Gaussian white noise has the tendency to reduce the precision of the
synfire activity, whereas noise with appropriate intensity can enhance the
performance of firing rate propagation. Further simulations indicate that the
propagation dynamics of the considered neuronal network is not simply
determined by the average amount of received neurotransmitter for each neuron
in a time instant, but also largely influenced by the stochastic effect of
neurotransmitter release. Second, we compare our results with those obtained in
corresponding feedforward neuronal networks connected with reliable synapses
but in a random coupling fashion. We confirm that some differences can be
observed in these two different feedforward neuronal network models. Finally,
we study the signal propagation in feedforward neuronal networks consisting of
both excitatory and inhibitory neurons, and demonstrate that inhibition also
plays an important role in signal propagation in the considered networks.Comment: 33pages, 16 figures; Journal of Computational Neuroscience
(published
Internal and external cooling methods and their effect on body temperature, thermal perception and dexterity
© 2018 The Authors. Published by PLOS. This is an open access article available under a Creative Commons licence.
The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1371/journal.pone.0191416© 2018 Maley et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Objective The present study aimed to compare a range of cooling methods possibly utilised by occupational workers, focusing on their effect on body temperature, perception and manual dexterity. Methods Ten male participants completed eight trials involving 30 min of seated rest followed by 30 min of cooling or control of no cooling (CON) (34C, 58% relative humidity). The cooling methods utilised were: ice cooling vest (CV0), phase change cooling vest melting at 14C (CV14), evaporative cooling vest (CVEV), arm immersion in 10C water (AI), portable water-perfused suit (WPS), heliox inhalation (HE) and ice slushy ingestion (SL). Immediately before and after cooling, participants were assessed for fine (Purdue pegboard task) and gross (grip and pinch strength) manual dexterity. Rectal and skin temperature, as well as thermal sensation and comfort, were monitored throughout. Results Compared with CON, SL was the only method to reduce rectal temperature (P = 0.012). All externally applied cooling methods reduced skin temperature (P0.05). Conclusion The present study observed that ice ingestion or ice applied to the skin produced the greatest effect on rectal and skin temperature, respectively. AI should not be utilised if workers require subsequent fine manual dexterity. These results will help inform future studies investigating appropriate pre-cooling methods for the occupational worker.This project is financially supported by the US Government through the Technical Support Working Group within the Combating Terrorism Technical Support Office.Published versio
Coordinated optimization of visual cortical maps (I) Symmetry-based analysis
In the primary visual cortex of primates and carnivores, functional
architecture can be characterized by maps of various stimulus features such as
orientation preference (OP), ocular dominance (OD), and spatial frequency. It
is a long-standing question in theoretical neuroscience whether the observed
maps should be interpreted as optima of a specific energy functional that
summarizes the design principles of cortical functional architecture. A
rigorous evaluation of this optimization hypothesis is particularly demanded by
recent evidence that the functional architecture of OP columns precisely
follows species invariant quantitative laws. Because it would be desirable to
infer the form of such an optimization principle from the biological data, the
optimization approach to explain cortical functional architecture raises the
following questions: i) What are the genuine ground states of candidate energy
functionals and how can they be calculated with precision and rigor? ii) How do
differences in candidate optimization principles impact on the predicted map
structure and conversely what can be learned about an hypothetical underlying
optimization principle from observations on map structure? iii) Is there a way
to analyze the coordinated organization of cortical maps predicted by
optimization principles in general? To answer these questions we developed a
general dynamical systems approach to the combined optimization of visual
cortical maps of OP and another scalar feature such as OD or spatial frequency
preference.Comment: 90 pages, 16 figure
Central synapses release a resource-efficient amount of glutamate.
Why synapses release a certain amount of neurotransmitter is poorly understood. We combined patch-clamp electrophysiology with computer simulations to estimate how much glutamate is discharged at two distinct central synapses of the rat. We found that, regardless of some uncertainty over synaptic microenvironment, synapses generate the maximal current per released glutamate molecule while maximizing signal information content. Our result suggests that synapses operate on a principle of resource optimization
Coordinated optimization of visual cortical maps (II) Numerical studies
It is an attractive hypothesis that the spatial structure of visual cortical
architecture can be explained by the coordinated optimization of multiple
visual cortical maps representing orientation preference (OP), ocular dominance
(OD), spatial frequency, or direction preference. In part (I) of this study we
defined a class of analytically tractable coordinated optimization models and
solved representative examples in which a spatially complex organization of the
orientation preference map is induced by inter-map interactions. We found that
attractor solutions near symmetry breaking threshold predict a highly ordered
map layout and require a substantial OD bias for OP pinwheel stabilization.
Here we examine in numerical simulations whether such models exhibit
biologically more realistic spatially irregular solutions at a finite distance
from threshold and when transients towards attractor states are considered. We
also examine whether model behavior qualitatively changes when the spatial
periodicities of the two maps are detuned and when considering more than 2
feature dimensions. Our numerical results support the view that neither minimal
energy states nor intermediate transient states of our coordinated optimization
models successfully explain the spatially irregular architecture of the visual
cortex. We discuss several alternative scenarios and additional factors that
may improve the agreement between model solutions and biological observations.Comment: 55 pages, 11 figures. arXiv admin note: substantial text overlap with
arXiv:1102.335
The role of input noise in transcriptional regulation
Even under constant external conditions, the expression levels of genes
fluctuate. Much emphasis has been placed on the components of this noise that
are due to randomness in transcription and translation; here we analyze the
role of noise associated with the inputs to transcriptional regulation, the
random arrival and binding of transcription factors to their target sites along
the genome. This noise sets a fundamental physical limit to the reliability of
genetic control, and has clear signatures, but we show that these are easily
obscured by experimental limitations and even by conventional methods for
plotting the variance vs. mean expression level. We argue that simple, global
models of noise dominated by transcription and translation are inconsistent
with the embedding of gene expression in a network of regulatory interactions.
Analysis of recent experiments on transcriptional control in the early
Drosophila embryo shows that these results are quantitatively consistent with
the predicted signatures of input noise, and we discuss the experiments needed
to test the importance of input noise more generally.Comment: 11 pages, 5 figures minor correction
Autism as a disorder of neural information processing: directions for research and targets for therapy
The broad variation in phenotypes and severities within autism spectrum disorders suggests the involvement of multiple predisposing factors, interacting in complex ways with normal developmental courses and gradients. Identification of these factors, and the common developmental path into which theyfeed, is hampered bythe large degrees of convergence from causal factors to altered brain development, and divergence from abnormal brain development into altered cognition and behaviour. Genetic, neurochemical, neuroimaging and behavioural findings on autism, as well as studies of normal development and of genetic syndromes that share symptoms with autism, offer hypotheses as to the nature of causal factors and their possible effects on the structure and dynamics of neural systems. Such alterations in neural properties may in turn perturb activity-dependent development, giving rise to a complex behavioural syndrome many steps removed from the root causes. Animal models based on genetic, neurochemical, neurophysiological, and behavioural manipulations offer the possibility of exploring these developmental processes in detail, as do human studies addressing endophenotypes beyond the diagnosis itself
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