SCALING BEHAVIOR OF THE DENDRITIC BRANCHES OF THALAMIC NEURONS

Fractals ◽  
1993 ◽  
Vol 01 (02) ◽  
pp. 171-178 ◽  
Author(s):  
KLAUS-D. KNIFFKI ◽  
MATTHIAS PAWLAK ◽  
CHRISTIANE VAHLE-HINZ
Keyword(s):  
Growth Process ◽  
Scaling Law ◽  
Branching Ratio ◽  
Scaling Behavior ◽  
Neuronal Growth ◽  
Thalamic Neurons ◽  
Dendritic Trees ◽  
Ventrobasal Complex ◽  
Dendritic Branches

The morphology of Golgi-impregnated thalamic neurons was investigated quantitatively. In particular, it was sought to test whether the dendritic bifurcations can be described by the scaling law (d0)n=(d1)n+(d2)nwith a single value of the diameter exponent n. Here d0 is the diameter of the parent branch, d1 and d2 are the diameters of the two daughter branches. Neurons from two functionally distinct regions were compared: the somatosensory ventrobasal complex (VB) and its nociceptive ventral periphery (VBvp). It is shown that for the neuronal trees studied in both regions, the scaling law was fulfilled. The diameter exponent n, however, was not a constant. It increased from n=1.76 for the 1st order branches to n=3.92 for the 7th order branches of neurons from both regions. These findings suggest that more than one simple intrinsic rule is involved in the neuronal growth process, and it is assumed that the branching ratio d0/d1 is not required to be encoded genetically. Furthermore, the results support the concept of the dendritic trees having a statistically identical topology in neurons of VB and VBvp and thus may be regarded as integrative modules.

scholarly journals Any neuron can perform linearly non-separable computations

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 539
Author(s):  
Romain D. Cazé
Keyword(s):  
Granule Cells ◽  
Large Fraction ◽  
Single Layer ◽  
Dendritic Arbor ◽  
Dendritic Trees ◽  
Artificial Neuron ◽  
Integrate And Fire ◽  
Layer Neuron ◽  
Dendritic Branches ◽  
Integrate And Fire Neuron

Multiple studies have shown how dendrites enable some neurons to perform linearly non-separable computations. These works focus on cells with an extended dendritic arbor where voltage can vary independently, turning dendritic branches into local non-linear subunits. However, these studies leave a large fraction of the nervous system unexplored. Many neurons, e.g. granule cells, have modest dendritic trees and are electrically compact. It is impossible to decompose them into multiple independent subunits. Here, we upgraded the integrate and fire neuron to account for saturating dendrites. This artificial neuron has a unique membrane voltage and can be seen as a single layer. We present a class of linearly non-separable computations and how our neuron can perform them. We thus demonstrate that even a single layer neuron with dendrites has more computational capacity than without. Because any neuron has one or more layer, and all dendrites do saturate, we show that any dendrited neuron can implement linearly non-separable computations.

Responses of thalamic neurons in rats to skin cooling and hypothalamic temperature

1989 ◽  
Vol 256 (6) ◽  
pp. R1293-R1298
Author(s):  
Y. Sakata ◽  
A. Morimoto ◽  
N. Murakami
Keyword(s):  
Digital Signals ◽  
Cold Stimulation ◽  
Thalamic Neurons ◽  
Hypothalamic Temperature ◽  
Analog Signals ◽  
Ventrobasal Complex ◽  
Graded Response ◽  
Skin Cooling ◽  
Specific Localization ◽  
Marginal Region

The responses of rat thalamic neurons to skin cooling were electrophysiologically examined. The responses of cold-excited neurons were classified into two types. One is a steplike response in which the activity abruptly increases with skin cooling, and the other is a graded response in which the activity gradually increases with skin cooling. The sites of these neurons were histologically identified in the ventrobasal complex of the thalamus, ventrolateral thalamus, and posterior thalamus. Two-thirds of them were found in a marginal region of the ventrobasal complex. There is no specific localization between the sites of thalamic neurons showing the steplike response and those showing the graded response. Furthermore, the effects of hypothalamic temperature on the thalamic neurons responding to skin cooling were observed. The response of thalamic neurons to cold stimulation of the skin was markedly suppressed during the hypothalamic warming. These results show that the steplike response is related to converting thermal analog signals to digital signals and that the graded response is related to relaying analog patterns of cold signals. Thermal afferent signals are modulated by hypothalamic temperature and subsequently cold sensation is modulated.

The orientation of the neuronal growth process can be directed via magnetic nanoparticles under an applied magnetic field

2014 ◽  
Vol 10 (7) ◽  
pp. 1549-1558 ◽  
Author(s):  
Cristina Riggio ◽  
M. Pilar Calatayud ◽  
Martina Giannaccini ◽  
Beatriz Sanz ◽  
Teobaldo E. Torres ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Magnetic Nanoparticles ◽  
Applied Magnetic Field ◽  
Growth Process ◽  
Neuronal Growth

scholarly journals Locally sequential synaptic reactivation during hippocampal ripples

2020 ◽  
Vol 6 (7) ◽  
pp. eaay1492 ◽  
Author(s):  
Tomoe Ishikawa ◽  
Yuji Ikegaya
Keyword(s):  
Cognitive Processing ◽  
Calcium Imaging ◽  
Pyramidal Neurons ◽  
Ex Vivo ◽  
Dendritic Trees ◽  
Neuronal Ensembles ◽  
Hippocampal Networks ◽  
Dendritic Branches ◽  
Multiple Sequences ◽  
Complex Manner

The sequential reactivation of memory-relevant neuronal ensembles during hippocampal sharp-wave (SW) ripple oscillations reflects cognitive processing. However, how a downstream neuron decodes this spatiotemporally organized activity remains unexplored. Using subcellular calcium imaging from CA1 pyramidal neurons in ex vivo hippocampal networks, we discovered that neighboring spines are activated serially along dendrites toward or away from cell bodies. Sequential spine activity was engaged repeatedly in different SWs in a complex manner. In a single SW event, multiple sequences appeared discretely in dendritic trees, but overall, sequences occurred preferentially in some dendritic branches. Thus, sequential replays of multineuronal spikes are distributed across several compartmentalized dendritic foci of a postsynaptic neuron, with their spatiotemporal features preserved.

The Cycle of Learning, Memorizing, and Forgetting

2020 ◽  
Author(s):  
Spring Library
Keyword(s):  
Growth Process ◽  
Neuronal Growth ◽  
Neurite Retraction ◽  
Identity Learning ◽  
Crucial Part

Memories are a crucial part of our identity. Learning enhances neuronal growth process that establishes new connections, or neurite retraction to remove existing connections.

scholarly journals Any neuron can perform linearly non-separable computations

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 539
Author(s):  
Romain D. Cazé
Keyword(s):  
Granule Cells ◽  
Large Fraction ◽  
Single Layer ◽  
Dendritic Arbor ◽  
Dendritic Trees ◽  
Artificial Neuron ◽  
Integrate And Fire ◽  
Layer Neuron ◽  
Dendritic Branches ◽  
Integrate And Fire Neuron

Multiple studies have shown how dendrites enable some neurons to perform linearly non-separable computations. These works focus on cells with an extended dendritic arbor where voltage can vary independently, turning dendritic branches into local non-linear subunits. However, these studies leave a large fraction of the nervous system unexplored. Many neurons, e.g. granule cells, have modest dendritic trees and are electrically compact. It is impossible to decompose them into multiple independent subunits. Here, we upgraded the integrate and fire neuron to account for saturating dendrites. This artificial neuron has a unique membrane voltage and can be seen as a single layer. We present a class of linearly non-separable computations and how our neuron can perform them. We thus demonstrate that even a single layer neuron with dendrites has more computational capacity than without. Because any neuron has one or more layer, and all dendrites do saturate, we show that any dendrited neuron can implement linearly non-separable computations.

scholarly journals Four weeks lithium treatment alters neuronal dendrites in the rat hippocampus

2013 ◽  
Vol 16 (6) ◽  
pp. 1373-1382 ◽  
Author(s):  
Seong S. Shim ◽  
Michael D. Hammonds ◽  
Ronald F. Mervis
Keyword(s):  
Synaptic Plasticity ◽  
Lithium Treatment ◽  
Neuronal Morphology ◽  
Total Density ◽  
Dendritic Trees ◽  
Distal Half ◽  
Proximal Half ◽  
Area Ca1 ◽  
Dendritic Branching ◽  
Dendritic Branches

AbstractA large body of evidence from molecular, cellular and human studies suggests that lithium may enhance synaptic plasticity, which may be associated with its therapeutic efficacy. However, only a small number of studies have directly assessed this. To determine whether lithium treatment alters structural synaptic plasticity, this study examined the effect of 4 wk lithium treatment on the amount and distribution of dendrites in the dentate gyrus (DG) and hippocampal area CA1 of young adult rats. Following 4 wk lithium or control chow feeding, animals were decapitated, the hippocampi were prepared and stained using a rapid Golgi staining technique and the amount and distribution of the dendritic branching was evaluated using Sholl analyses (method of concentric circles). In the DG, lithium treatment increased the amount and distribution of dendritic branches in the proximal half of dendritic trees of the granule cells and reduced branching in the distal half. In area CA1, the same treatment also increased the number of dendritic branches in the proximal half of apical dendritic trees of CA1 pyramidal cells and reduced branching in the distal half of apical dendritic trees but had no effect on basilar dendritic trees. The lithium treatment altered the total density of dendritic trees in neither the DG nor area CA1. These findings suggest that, in the DG and apical CA1, chronic lithium treatment rearranges neuronal morphology to increase dendritic branching and distribution to where major afferent input is received.

scholarly journals Scaling law in nucleation-growth process.

1984 ◽  
Vol 26 (1) ◽  
pp. 37-43
Author(s):  
Yasusada YAMADA
Keyword(s):  
Growth Process ◽  
Scaling Law ◽  
Nucleation Growth

scholarly journals World’s Greatest Observed Point Rainfalls: Jennings (1950) Scaling Law

2013 ◽  
Vol 14 (6) ◽  
pp. 1952-1957 ◽  
Author(s):  
Huan Zhang ◽  
Klaus Fraedrich ◽  
Xiuhua Zhu ◽  
Richard Blender ◽  
Ling Zhang
Keyword(s):  
Scaling Law ◽  
Moisture Flux ◽  
Autoregressive Process ◽  
Scaling Behavior ◽  
First Order ◽  
Wide Range ◽  
Single Station ◽  
Moisture Fluxes ◽  
Rainfall Model ◽  
Scaling Coefficient

Abstract The observed relation of worldwide precipitation maxima P versus duration d follows the Jennings scaling law, P ≈ db, with scaling coefficient b ≈ 0.5. This scaling is demonstrated to hold for single-station rainfall extending over three decades. A conceptual stochastic rainfall model that reveals similar scaling behavior is introduced as a first-order autoregressive process [AR(1)] to represent the lower tropospheric vertical moisture fluxes, whose upward components balance the rainfall while the downward components are truncated and defined as no rain. Estimates of 40-yr ECMWF Re-Analysis (ERA-40) vertical moisture flux autocorrelations (at grids near the rainfall stations) provide estimates for the truncated AR(1). Subjected to maximum depth-duration analysis, the scaling coefficient b ≈ 0.5 is obtained extending for about two orders of magnitude, which is associated with a wide range of vertical moisture flux autocorrelations 0.1 < a < 0.7.

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