scholarly journals A locomotor neural circuit persists and functions similarly in larvae and adult Drosophila

2021 ◽  
Author(s):  
Kristen M. Lee ◽  
Chris Q. Doe
Keyword(s):  
Molecular Markers ◽  
Structural Changes ◽  
Neural Circuit ◽  
Structural Plasticity ◽  
Locomotor Behavior ◽  
Input Output ◽  
Neuronal Remodeling ◽  
Forward Locomotion ◽  
Output Neurons ◽  
Adult Drosophila

AbstractIndividual neurons can undergo drastic structural changes, known as neuronal remodeling or structural plasticity. One example of this is in response to hormones, such as during puberty in mammals or metamorphosis in insects. However, in each of these examples it remains unclear whether the remodeled neuron resumes prior patterns of connectivity, and if so, whether the persistent circuits drive similar behaviors. Here, we utilize a well-characterized neural circuit in the Drosophila larva: the Moonwalking Descending Neuron (MDN) circuit. We previously showed that larval MDN induces backward crawling, and synapses onto the Pair1 interneuron to inhibit forward crawling (Carreira-Rosario et al., 2018). MDN is remodeled during metamorphosis and regulates backward walking in the adult fly. We investigated whether Pair1 is remodeled during metamorphosis and functions within the MDN circuit during adulthood. We assayed morphology and molecular markers to demonstrate that Pair1 is remodeled during metamorphosis and persists in the adult fly. In the adult, optogenetic activation of Pair1 resulted in arrest of forward locomotion, similar to what is observed in larvae. MDN and Pair1 are also synaptic partners in the adult, showing that the MDN-Pair1 interneuron circuit is retained in the adult following hormone-driven pupal remodeling. Thus, the MDN-Pair1 neurons are an interneuronal circuit – i.e. a pair of synaptically connected interneurons – that persists through metamorphosis, taking on new input/output neurons, yet generating similar locomotor behavior at both stages.

scholarly journals A locomotor neural circuit persists and functions similarly in larvae and adult Drosophila

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Kristen Lee ◽  
Chris Q Doe
Keyword(s):  
Molecular Markers ◽  
Structural Changes ◽  
Neural Circuit ◽  
Structural Plasticity ◽  
Locomotor Behavior ◽  
Backward Walking ◽  
Neuronal Remodeling ◽  
Forward Locomotion ◽  
Adult Drosophila

Individual neurons can undergo drastic structural changes, known as neuronal remodeling or structural plasticity. One example of this is in response to hormones, such as during puberty in mammals or metamorphosis in insects. However, in each of these examples it remains unclear whether the remodeled neuron resumes prior patterns of connectivity, and if so, whether the persistent circuits drive similar behaviors. Here, we utilize a well-characterized neural circuit in the Drosophila larva: the Moonwalking Descending Neuron (MDN) circuit. We previously showed that larval MDN induces backward crawling, and synapses onto the Pair1 interneuron to inhibit forward crawling (Carreira-Rosario et al., 2018). MDN is remodeled during metamorphosis and regulates backward walking in the adult fly. We investigated whether Pair1 is remodeled during metamorphosis and functions within the MDN circuit during adulthood. We assayed morphology and molecular markers to demonstrate that Pair1 is remodeled during metamorphosis and persists in the adult fly. MDN-Pair1 connectivity is lost during early pupal stages, when both neurons are severely pruned back, but connectivity is re-established at mid-pupal stages and persist into the adult. In the adult, optogenetic activation of Pair1 resulted in arrest of forward locomotion, similar to what is observed in larvae. Thus, the MDN-Pair1 neurons are an interneuronal circuit - a pair of synaptically connected interneurons – that is re-established during metamorphosis, yet generates similar locomotor behavior at both larval and adult stages.

scholarly journals A neural circuit basis for context-modulation of individual locomotor behavior

2019 ◽  
Author(s):  
Kyobi Skutt-Kakaria ◽  
Pablo Reimers ◽  
Timothy A. Currier ◽  
Zach Werkhoven ◽  
Benjamin L. de Bivort
Keyword(s):  
Neural Circuit ◽  
Locomotor Behavior ◽  
Context Dependence ◽  
Central Complex ◽  
Ambient Illumination ◽  
Behavioral Characteristic ◽  
Illumination Changes ◽  
Output Neurons ◽  
Context Specific ◽  
Innate Behaviors

AbstractDefying the cliche that biological variation arises from differences in nature or nurture, genetically identical animals reared in the same environment exhibit striking differences in their behaviors. Innate behaviors can be surprisingly flexible, for example by exhibiting context-dependence. The intersection of behavioral individuality and context-dependence is largely unexplored, particularly at the neural circuit level. Here, we show that individual flies’ tendencies to turn left or right (locomotor handedness) changes when ambient illumination changes. This change is itself a stable individual behavioral characteristic. Silencing output neurons of the central complex (a premotor area that mediates goal-directed navigation) blocks this change. These neurons respond to light with idiosyncratic changes to their baseline calcium levels, and idiosyncratic morphological variation in their presynaptic arbors correlates with idiosyncratic sensory-context-specific turn biases. These findings provide a circuit mechanism by which individual locomotor biases arise and are modulated by sensory context.

Statistical Approaches to Structural Change in Regional Interindustry Models

1986 ◽  
Vol 18 (9) ◽  
pp. 1189-1207
Author(s):  
B Ó Huallacháin
Keyword(s):  
Structural Change ◽  
Structural Changes ◽  
Washington State ◽  
Multivariate Statistical Analyses ◽  
Input Output ◽  
Multivariate Statistical ◽  
State Data ◽  
System A ◽  
Statistical Approaches ◽  
The Impact

The conventional approach to assessing structural change in regional input – output tables is to measure the impact of coefficient change on the estimation of outputs and multipliers. The methods developed and tested in this paper focus exclusively on the coefficients. Univariate and multivariate statistical analyses can be used to identify and measure various types of changes ranging from coefficient instability to changes in interindustry relationships as a system. A distinction is made between structural changes in input relationships and those in output relationships. The methods are tested by using Washington State data for the years 1963 and 1967. The results are compared with previous analyses of change in these data.

A Dynamic Interindustry Model for the Economic Analysis of Pollution Abatement

1974 ◽  
Vol 6 (3) ◽  
pp. 321-338 ◽  
Author(s):  
A Rose
Keyword(s):  
Linear Programming ◽  
Structural Changes ◽  
Environmental Control ◽  
Pollution Abatement ◽  
Primary Component ◽  
Component Model ◽  
Input Output ◽  
Two Component ◽  
Output System ◽  
Policy And Planning

A two-component model is presented for the analysis of the economic impact of pollution abatement. The primary component is a dynamic input-output system in which the structure of the economy is related to the level of environmental control as well as to time. A submodel, which consists of the various abatement activities within each industry, is used to explore the underlying nature of structural changes which take place as a result of changes in environmental regulations. The usefulness of the overall model for policy and planning purposes is illustrated by an example in which the submodel is transformed into a linear-programming format.

Driving forces and structural changes of China as a market provider for Korea

2018 ◽  
Vol 22 (3) ◽  
pp. 194-211 ◽  
Author(s):  
Yongqi Feng ◽  
Tianshu Zhang
Keyword(s):  
Steady State ◽  
Driving Force ◽  
Design Methodology ◽  
Structural Changes ◽  
Driving Forces ◽  
Consumption Expenditure ◽  
Input Output ◽  
Content Type ◽  
Fixed Capital Formation ◽  
The Impact

Purpose The purpose of this paper is to provide a better understanding of the driving forces and structural changes of China as a market provider for Korea. This paper gives the answers for the following questions: How do China’s final demands trigger the growth of its imports from Korea? And what’s the impact of China’s final demands on the import in different industries? Design/methodology/approach Based on the Multi-Regional Input-Output model and World Input-Output Table database, this paper constructs the non-competitive imports input-output (IO) table of China to Korea. According to this table, we can calculate the induced imports coefficient and comprehensive induced import coefficients of China’s four final demands for imports from Korea in the 56 industries in China. Findings Among the four driving forces, the strongest one is changes in inventories and valuables. The impact of final consumption expenditure and fixed capital formation is much lower than that of changes in inventories and valuables, but they have a broader impact for the 56 industries. This paper finds out the China’s import induction of the final demands to Korea peaked in 2005 and 2010 and decreased greatly in 2014, so the position of China as market provider for Korea will no longer rise substantially, contrarily it will be in a steady state. Originality/value First, this paper constructs the non-competitive IO table to analyze the market provider issues between two countries and provides practical ways and methods for studies on the issues of imports and market provider. Second, this paper investigates the different roles of four final demands on driving force of China as market provider for Korea and the structural changes of China as a market provider for Korea among 56 industries from 2000 to 2014.

scholarly journals Non-ionotropic NMDA receptor signaling gates bidirectional structural plasticity of dendritic spines

2020 ◽  
Author(s):  
Ivar S. Stein ◽  
Deborah K. Park ◽  
Nicole Claiborne ◽  
Karen Zito
Keyword(s):  
Dendritic Spines ◽  
Structural Changes ◽  
Brain Plasticity ◽  
Structural Plasticity ◽  
Ion Flow ◽  
Neuronal Connections ◽  
Vital Component ◽  
Brain Circuit ◽  
Signaling Components

SUMMARYExperience-dependent refinement of neuronal connections is critically important for brain development and learning. Here we show that ion flow-independent NMDAR signaling is required for the long-term dendritic spine growth that is a vital component of brain circuit plasticity. We found that inhibition of p38 MAPK, shown to be downstream of non-ionotropic NMDAR signaling in LTD and spine shrinkage, blocked LTP-induced spine growth but not LTP. We hypothesized that non-ionotropic NMDAR signaling drives the cytoskeletal changes that support bidirectional spine structural plasticity. Indeed, we found that key signaling components downstream of non-ionotropic NMDAR function in LTD-induced spine shrinkage also are necessary for LTP-induced spine growth. Furthermore, NMDAR conformational signaling with coincident Ca2+ influx is sufficient to drive CaMKII-dependent long-term spine growth, even when Ca2+ is artificially driven through voltage-gated Ca2+ channels. Our results support a model in which non-ionotropic NMDAR signaling gates the bidirectional spine structural changes vital for brain plasticity.

scholarly journals AN ALTERNATIVE APPROACH OF INPUT-OUTPUT TABLES TO DYNAMIC STRUCTURE CHANGES IN KOREAN IT INDUSTRIES

2013 ◽  
Vol 19 (2) ◽  
pp. 257-271 ◽  
Author(s):  
Byung-Sun Cho ◽  
Sang Sup Cho ◽  
Jungmann Lee
Keyword(s):  
Structural Changes ◽  
Impact Analysis ◽  
Consumer Preferences ◽  
New Technology ◽  
Dynamic Structure ◽  
Input Output ◽  
It Industry ◽  
Current Time ◽  
Structure Changes ◽  
Industry Policy

The structure of the IT industry has always evolved in line with technological progresses and changes in consumer preferences, as well as with regulatory trends. This is why, when assessing the effect that a new technology or industry policy may have on the national economy, companies and policy-makers need to consider dynamic structural changes affecting the IT industry. One of the most popular existing methods for economic impact analysis is based on a traditional input-output table, and is conducted over a period between the current time and a given time in the future. In this study, we compare the accuracy of RAS and Cross Entropy (CE), the two most widely employed methods for updating input-output (IO) tables, by applying them to Korean IT industries. The main results of this study are the following. In terms of the accuracy of input coefficient estimates, we have found that both the RAS and CE methods have a tendency to overestimate or underestimate them. When the Korean industry was first divided into fourteen sectors, and the RAS and CE methods were applied to each of the fourteen industries, it was difficult to discern a consistent trend for the two methods concerning their accuracy in estimation of input coefficients. Secondly, when used to update an IO table in which the IT industry is subdivided into IT equipment and services, neither the CE nor RAS method proved distinctly superior to the other. Third, in light of the above two findings, we concluded that updating IO tables is best done through a hybrid method combining the CE and RAS methods. This paper proposes a procedure consisting of two steps: IO tables are first updated using the two methods, which are once again updated by employing the OLS average approach through the use of optimal weights.

Structural Changes in Less Developed Areas: An Input- Output Framework

2004 ◽  
Vol 38 (6) ◽  
pp. 603-614 ◽  
Author(s):  
Claudia Ciobanu ◽  
Konstadinos Mattas ◽  
Dimitris Psaltopoulos
Keyword(s):  
Structural Changes ◽  
Input Output

scholarly journals Chronic Social Defeat Stress Modulates Dendritic Spines Structural Plasticity in Adult Mouse Frontal Association Cortex

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Yu Shu ◽  
Tonghui Xu
Keyword(s):  
Prefrontal Cortex ◽  
Chronic Stress ◽  
Neural Circuits ◽  
Neural Circuit ◽  
Structural Plasticity ◽  
Social Defeat ◽  
Social Defeat Stress ◽  
Chronic Social Defeat Stress ◽  
Stress Experience ◽  
Spine Dynamics

Chronic stress is associated with occurrence of many mental disorders. Previous studies have shown that dendrites and spines of pyramidal neurons of the prefrontal cortex undergo drastic reorganization following chronic stress experience. So the prefrontal cortex is believed to play a key role in response of neural system to chronic stress. However, how stress induces dynamic structural changes in neural circuit of prefrontal cortex remains unknown. In the present study, we examined the effects of chronic social defeat stress on dendritic spine structural plasticity in the mouse frontal association (FrA) cortexin vivousing two-photon microscopy. We found that chronic stress altered spine dynamics in FrA and increased the connectivity in FrA neural circuits. We also found that the changes in spine dynamics in FrA are correlated with the deficit of sucrose preference in defeated mice. Our findings suggest that chronic stress experience leads to adaptive change in neural circuits that may be important for encoding stress experience related memory and anhedonia.

Sign in / Sign up

Export Citation Format

Share Document