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The Enigmatic Canal-Associated Neurons Regulate Caenorhabditis elegans Larval Development Through a cAMP Signaling Pathway.
Caenorhabditis elegans larval development requires the function of the two Canal-Associated Neurons (CANs): killing the CANs by laser microsurgery or disrupting their development by mutating the gene ceh-10 results in early larval arrest. How these cells promote larval development, however, remains a mystery. In screens for mutations that bypass CAN function, we identified the gene kin-29, which encodes a member of the Salt-Inducible Kinase (SIK) family and a component of a conserved pathway that regulates various C. elegans phenotypes. Like kin-29 loss, gain-of-function mutations in genes that may act upstream of kin-29 or growth in cyclic-AMP analogs bypassed ceh-10 larval arrest, suggesting that a conserved adenylyl cyclase/PKA pathway inhibits KIN-29 to promote larval development, and that loss of CAN function results in dysregulation of KIN-29 and larval arrest. The adenylyl cyclase ACY-2 mediates CAN-dependent larval development: acy-2 mutant larvae arrested development with a similar phenotype to ceh-10 mutants, and the arrest phenotype was suppressed by mutations in kin-29 ACY-2 is expressed predominantly in the CANs, and we provide evidence that the acy-2 functions in the CANs to promote larval development. By contrast, cell-specific expression experiments suggest that kin-29 acts in both the hypodermis and neurons, but not in the CANs. Based on our findings, we propose two models for how ACY-2 activity in the CANs regulates KIN-29 in target cells
Pinwheel stabilization by ocular dominance segregation
We present an analytical approach for studying the coupled development of
ocular dominance and orientation preference columns. Using this approach we
demonstrate that ocular dominance segregation can induce the stabilization and
even the production of pinwheels by their crystallization in two types of
periodic lattices. Pinwheel crystallization depends on the overall dominance of
one eye over the other, a condition that is fulfilled during early cortical
development. Increasing the strength of inter-map coupling induces a transition
from pinwheel-free stripe solutions to intermediate and high pinwheel density
states.Comment: 10 pages, 4 figure
Topological Speed Limits to Network Synchronization
We study collective synchronization of pulse-coupled oscillators interacting
on asymmetric random networks. We demonstrate that random matrix theory can be
used to accurately predict the speed of synchronization in such networks in
dependence on the dynamical and network parameters. Furthermore, we show that
the speed of synchronization is limited by the network connectivity and stays
finite, even if the coupling strength becomes infinite. In addition, our
results indicate that synchrony is robust under structural perturbations of the
network dynamics.Comment: 5 pages, 3 figure
Breaking Synchrony by Heterogeneity in Complex Networks
For networks of pulse-coupled oscillators with complex connectivity, we
demonstrate that in the presence of coupling heterogeneity precisely timed
periodic firing patterns replace the state of global synchrony that exists in
homogenous networks only. With increasing disorder, these patterns persist
until they reach a critical temporal extent that is of the order of the
interaction delay. For stronger disorder these patterns cease to exist and only
asynchronous, aperiodic states are observed. We derive self-consistency
equations to predict the precise temporal structure of a pattern from the
network heterogeneity. Moreover, we show how to design heterogenous coupling
architectures to create an arbitrary prescribed pattern.Comment: 4 pages, 3 figure
Two Different Forms of Arousal in Drosophila Are Oppositely Regulated by the Dopamine D1 Receptor Ortholog DopR via Distinct Neural Circuits
Arousal is fundamental to many behaviors, but whether it is unitary or whether there are different types of behavior-specific arousal has not been clear. In Drosophila, dopamine promotes sleep-wake arousal. However, there is conflicting evidence regarding its influence on environmentally stimulated arousal. Here we show that loss-of-function mutations in the D1 dopamine receptor DopR enhance repetitive startle-induced arousal while decreasing sleep-wake arousal (i.e., increasing sleep). These two types of arousal are also inversely influenced by cocaine, whose effects in each case are opposite to, and abrogated by, the DopR mutation. Selective restoration of DopR function in the central complex rescues the enhanced stimulated arousal but not the increased sleep phenotype of DopR mutants. These data provide evidence for at least two different forms of arousal, which are independently regulated by dopamine in opposite directions, via distinct neural circuits
A Pair of Dopamine Neurons Target the D1-Like Dopamine Receptor DopR in the Central Complex to Promote Ethanol-Stimulated Locomotion in Drosophila
Dopamine is a mediator of the stimulant properties of drugs of abuse, including ethanol, in mammals and in the fruit fly Drosophila. The neural substrates for the stimulant actions of ethanol in flies are not known. We show that a subset of dopamine neurons and their targets, through the action of the D1-like dopamine receptor DopR, promote locomotor activation in response to acute ethanol exposure. A bilateral pair of dopaminergic neurons in the fly brain mediates the enhanced locomotor activity induced by ethanol exposure, and promotes locomotion when directly activated. These neurons project to the central complex ellipsoid body, a structure implicated in regulating motor behaviors. Ellipsoid body neurons are required for ethanol-induced locomotor activity and they express DopR. Elimination of DopR blunts the locomotor activating effects of ethanol, and this behavior can be restored by selective expression of DopR in the ellipsoid body. These data tie the activity of defined dopamine neurons to D1-like DopR-expressing neurons to form a neural circuit that governs acute responding to ethanol
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
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
Self-organization and the selection of pinwheel density in visual cortical development
Self-organization of neural circuitry is an appealing framework for
understanding cortical development, yet its applicability remains unconfirmed.
Models for the self-organization of neural circuits have been proposed, but
experimentally testable predictions of these models have been less clear. The
visual cortex contains a large number of topological point defects, called
pinwheels, which are detectable in experiments and therefore in principle well
suited for testing predictions of self-organization empirically. Here, we
analytically calculate the density of pinwheels predicted by a pattern
formation model of visual cortical development. An important factor controlling
the density of pinwheels in this model appears to be the presence of non-local
long-range interactions, a property which distinguishes cortical circuits from
many nonliving systems in which self-organization has been studied. We show
that in the limit where the range of these interactions is infinite, the
average pinwheel density converges to . Moreover, an average pinwheel
density close to this value is robustly selected even for intermediate
interaction ranges, a regime arguably covering interaction-ranges in a wide
range of different species. In conclusion, our paper provides the first direct
theoretical demonstration and analysis of pinwheel density selection in models
of cortical self-organization and suggests to quantitatively probe this type of
prediction in future high-precision experiments.Comment: 22 pages, 3 figure
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