5,285 research outputs found
Developmental time windows for axon growth influence neuronal network topology
Early brain connectivity development consists of multiple stages: birth of
neurons, their migration and the subsequent growth of axons and dendrites. Each
stage occurs within a certain period of time depending on types of neurons and
cortical layers. Forming synapses between neurons either by growing axons
starting at similar times for all neurons (much-overlapped time windows) or at
different time points (less-overlapped) may affect the topological and spatial
properties of neuronal networks. Here, we explore the extreme cases of axon
formation especially concerning short-distance connectivity during early
development, either starting at the same time for all neurons (parallel, i.e.
maximally-overlapped time windows) or occurring for each neuron separately one
neuron after another (serial, i.e. no overlaps in time windows). For both
cases, the number of potential and established synapses remained comparable.
Topological and spatial properties, however, differed: neurons that started
axon growth early on in serial growth achieved higher out-degrees, higher local
efficiency, and longer axon lengths while neurons demonstrated more homogeneous
connectivity patterns for parallel growth. Second, connection probability
decreased more rapidly with distance between neurons for parallel growth than
for serial growth. Third, bidirectional connections were more numerous for
parallel growth. Finally, we tested our predictions with C. elegans data.
Together, this indicates that time windows for axon growth influence the
topological and spatial properties of neuronal networks opening the possibility
to a posteriori estimate developmental mechanisms based on network properties
of a developed network.Comment: Biol Cybern. 2015 Jan 30. [Epub ahead of print
Development and Evolution of Neural Networks in an Artificial Chemistry
We present a model of decentralized growth for Artificial Neural Networks
(ANNs) inspired by the development and the physiology of real nervous systems.
In this model, each individual artificial neuron is an autonomous unit whose
behavior is determined only by the genetic information it harbors and local
concentrations of substrates modeled by a simple artificial chemistry. Gene
expression is manifested as axon and dendrite growth, cell division and
differentiation, substrate production and cell stimulation. We demonstrate the
model's power with a hand-written genome that leads to the growth of a simple
network which performs classical conditioning. To evolve more complex
structures, we implemented a platform-independent, asynchronous, distributed
Genetic Algorithm (GA) that allows users to participate in evolutionary
experiments via the World Wide Web.Comment: 8 pages LaTeX, style file included, 8 embedded postscript figures. To
be published in Proc. of 3rd German Workshop on Artificial Life (GWAL
Neuroelectronic interfacing with cultured multielectrode arrays toward a cultured probe
Efficient and selective electrical stimulation and recording of neural activity in peripheral, spinal, or central pathways requires multielectrode arrays at micrometer scale. ¿Cultured probe¿ devices are being developed, i.e., cell-cultured planar multielectrode arrays (MEAs). They may enhance efficiency and selectivity because neural cells have been grown over and around each electrode site as electrode-specific local networks. If, after implantation, collateral sprouts branch from a motor fiber (ventral horn area) and if they can be guided and contacted to each ¿host¿ network, a very selective and efficient interface will result. Four basic aspects of the design and development of a cultured probe, coated with rat cortical or dorsal root ganglion neurons, are described. First, the importance of optimization of the cell-electrode contact is presented. It turns out that impedance spectroscopy, and detailed modeling of the electrode-cell interface, is a very helpful technique, which shows whether a cell is covering an electrode and how strong the sealing is. Second, the dielectrophoretic trapping method directs cells efficiently to desired spots on the substrate, and cells remain viable after the treatment. The number of cells trapped is dependent on the electric field parameters and the occurrence of a secondary force, a fluid flow (as a result of field-induced heating). It was found that the viability of trapped cortical cells was not influenced by the electric field. Third, cells must adhere to the surface of the substrate and form networks, which are locally confined, to one electrode site. For that, chemical modification of the substrate and electrode areas with various coatings, such as polyethyleneimine (PEI) and fluorocarbon monolayers promotes or inhibits adhesion of cells. Finally, it is shown how PEI patterning, by a stamping technique, successfully guides outgrowth of collaterals from a neonatal rat lumbar spinal cord explant, after six days in cultur
A model of fasciculation and sorting in mixed populations of axons
We extend a recently proposed model (Chaudhuri et al., EPL 87, 20003 (2009))
aiming to describe the formation of fascicles of axons during neural
development. The growing axons are represented as paths of interacting directed
random walkers in two spatial dimensions. To mimic turnover of axons, whole
paths are removed and new walkers are injected with specified rates. In the
simplest version of the model, we use strongly adhesive short-range inter-axon
interactions that are identical for all pairs of axons. We generalize the model
to adhesive interactions of finite strengths and to multiple types of axons
with type-specific interactions. The dynamic steady state is characterized by
the position-dependent distribution of fascicle sizes. With distance in the
direction of axon growth, the mean fascicle size and emergent time scales grow
monotonically, while the degree of sorting of fascicles by axon type has a
maximum at a finite distance. To understand the emergence of slow time scales,
we develop an analytical framework to analyze the interaction between
neighboring fascicles.Comment: 19 pages, 13 figures; version accepted for publication in Phys Rev
The dendritic density field of a cortical pyramidal cell
Much is known about the computation in individual neurons in the cortical column. Also, the selective connectivity between many cortical neuron types has been studied in great detail. However, due to the complexity of this microcircuitry its functional role within the cortical column remains a mystery. Some of the wiring behavior between neurons can be interpreted directly from their particular dendritic and axonal shapes. Here, I describe the dendritic density field (DDF) as one key element that remains to be better understood. I sketch an approach to relate DDFs in general to their underlying potential connectivity schemes. As an example, I show how the characteristic shape of a cortical pyramidal cell appears as a direct consequence of connecting inputs arranged in two separate parallel layers
Spatial and Temporal Sensing Limits of Microtubule Polarization in Neuronal Growth Cones by Intracellular Gradients and Forces
Neuronal growth cones are the most sensitive amongst eukaryotic cells in
responding to directional chemical cues. Although a dynamic microtubule
cytoskeleton has been shown to be essential for growth cone turning, the
precise nature of coupling of the spatial cue with microtubule polarization is
less understood. Here we present a computational model of microtubule
polarization in a turning neuronal growth cone (GC). We explore the limits of
directional cues in modifying the spatial polarization of microtubules by
testing the role of microtubule dynamics, gradients of regulators and
retrograde forces along filopodia. We analyze the steady state and transition
behavior of microtubules on being presented with a directional stimulus. The
model makes novel predictions about the minimal angular spread of the chemical
signal at the growth cone and the fastest polarization times. A regulatory
reaction-diffusion network based on the cyclic
phosphorylation-dephosphorylation of a regulator predicts that the receptor
signal magnitude can generate the maximal polarization of microtubules and not
feedback loops or amplifications in the network. Using both the
phenomenological and network models we have demonstrated some of the physical
limits within which the MT polarization system works in turning neuron.Comment: 7 figures and supplementary materia
Electrical Interactions via the Extracellular Potential Near Cell Bodies
Ephaptic interactions between a neuron and axons or dendrites passing by its cell body can be, in principle, more significant than ephaptic interactions among axons in a fiber tract. Extracellular action potentials outside axons are small in amplitude and spatially spread out, while they are larger in amplitude and much more spatially confined near cell bodies. We estimated the extracellular potentials associated with an action potential in a cortical pyramidal cell using standard one-dimensional cable theory and volume conductor theory. Their spatial and temporal pattern reveal much about the location and timing of currents in the cell, especially in combination with a known morphology, and simple experiments could resolve questions about spike initiation. From the extracellular potential we compute the ephaptically induced polarization in a nearby passive cable. The magnitude of this induced voltage can be several mV, does not spread electrotonically, and depends only weakly on the passive properties of the cable. We discuss their possible functional relevance
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