scholarly journals Modulation of voltage-dependent K+ conductances in photoreceptors trades off investment in contrast gain for bandwidth

2018 ◽  
Author(s):  
Francisco JH Heras ◽  
Mikko Vähäsöyrinki ◽  
Jeremy E Niven
Keyword(s):  
Information Processing ◽  
Energy Consumption ◽  
Computational Models ◽  
Membrane Resistance ◽  
Functional Requirements ◽  
Low Frequencies ◽  
Contrast Gain ◽  
Shift Performance ◽  
Voltage Dependent ◽  
The Impact

AbstractModulation is essential for adjusting neurons to prevailing conditions and differing demands. Yet understanding how modulators adjust neuronal properties to alter information processing remains unclear, as is the impact of neuromodulation on energy consumption. Here we combine two computational models, one Hodgkin-Huxley type and the other analytic, to investigate the effects of neuromodulation upon Drosophila melanogaster photoreceptors. Voltage-dependent K+ conductances: (i) activate upon depolarisation to reduce membrane resistance and adjust bandwidth to functional requirements; (ii) produce negative feedback to increase bandwidth in an energy efficient way; (iii) produce shunt-peaking thereby increasing the membrane gain bandwidth product; and (iv) inactivate to amplify low frequencies. Through their effects on the voltage-dependent K+ conductances, three modulators, serotonin, calmodulin and PIP2, trade-off contrast gain against membrane bandwidth. Serotonin shifts the photoreceptor performance towards higher contrast gains and lower membrane bandwidths, whereas PIP2 and calmodulin shift performance towards lower contrast gains and higher membrane bandwidths. These neuromodulators have little effect upon the overall energy consumed by photoreceptors, instead they redistribute the energy invested in gain versus bandwidth. This demonstrates how modulators can shift neuronal information processing within the limitations of biophysics and energy consumption.

scholarly journals Voltage-dependent K+ Channels Improve the Energy Efficiency of Signalling in Blowfly Photoreceptors

2016 ◽  
Author(s):  
Francisco J. H. Heras ◽  
John Anderson ◽  
Simon B. Laughlin ◽  
Jeremy E. Niven
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Negative Feedback ◽  
Light Adaptation ◽  
Bright Light ◽  
Spiking Neurons ◽  
Delayed Rectifier ◽  
Voltage Response ◽  
Functional Requirements ◽  
Voltage Dependent

AbstractVoltage-dependent conductances in many spiking neurons are tuned to reduce action potential energy consumption, so improving the energy efficiency of spike coding. However, the contribution of voltage-dependent conductances to the energy efficiency of analogue coding, by graded potentials in dendrites and non-spiking neurons, remains unclear. We investigate the contribution of voltage-dependent conductances to the energy efficiency of analogue coding by modelling blowfly R1-6 photoreceptor membrane. Two voltage-dependent delayed rectifier K+ conductances (DRs) shape the membrane's voltage response and contribute to light adaptation. They make two types of energy saving. By reducing membrane resistance upon depolarisation they convert the cheap, low bandwidth membrane needed in dim light to the expensive high bandwidth membrane needed in bright light. This investment of energy in bandwidth according to functional requirements can halve daily energy consumption. Second, DRs produce negative feedback that reduces membrane impedance and increases bandwidth. This negative feedback allows an active membrane with DRs to consume at least 30% less energy than a passive membrane with the same capacitance and bandwidth. Voltage gated conductances in other non-spiking neurons, and in dendrites, might be organized to make similar savings.

A Simulation Study Investigating the Impact of Dendritic Morphology and Synaptic Topology on Neuronal Firing Patterns

2010 ◽  
Vol 22 (4) ◽  
pp. 1086-1111 ◽  
Author(s):  
Jen-Yung Chen
Keyword(s):  
Information Processing ◽  
Computational Models ◽  
Dendritic Morphology ◽  
Neuronal Firing ◽  
Membrane Properties ◽  
Neuron Models ◽  
Spatial And Temporal Scales ◽  
Brain Functions ◽  
Scaling Analyses ◽  
The Impact

In the brain, complex information interactions among neurons span several spatial and temporal scales, making it extremely difficult to identify the principles governing neural information processing. In this study, we used computational models to investigate the impact of dendritic morphology and synaptic topology on patterns of neuronal firing. We first constructed Hodgkin-Huxley-type neuron models that possessed dendrites with different morphological features. We then simulated the responses of these neurons to a number of spatiotemporal input patterns. The similarity between neuronal responses to different patterned inputs was effectively evaluated by a novel combination of metric space analysis and multidimensional scaling analyses. The results showed that neurons with different morphological or anatomical features exhibit differences in stimulus-specific temporal encoding and firing reliability. These findings support the idea that in addition to biophysical membrane properties, the dendritic morphology and the synaptic topology of a neuron can play a significant role in neuronal information processing and may directly contribute to various brain functions.

scholarly journals On the impact of sampling frequency on software energy measurements

2015 ◽  
Author(s):  
Rubén Saborido ◽  
Venera Arnaoudova ◽  
Giovanni Beltrame ◽  
Foutse Khomh ◽  
Giuliano Antoniol
Keyword(s):  
Energy Consumption ◽  
Mobile Applications ◽  
High Frequency ◽  
Sampling Frequency ◽  
Low Frequencies ◽  
Median Error ◽  
Android Applications ◽  
Reduce Energy Consumption ◽  
The Impact ◽  
Closed Source

Energy consumption is a major concern when developing and evolving mobile applications and researchers are investigating ways to reduce energy consumption. We conjecture that these studies are at the border between hardware and software and we must be careful on how the energy consumption is measured. To the best of our knowledge, no previous work investigates how much energy and power consumption is due to high frequency events missed when sampling at low frequencies such as 10 kHz and verified the error at the precision of method level. In this paper, we propose an approach for accurate measurements of the energy consumption of mobile applications. We apply the proposed approach to assess the energy consumption of 21 mobile, closed source, applications and four open source Android applications. We show that by sampling at 10 kHz one may expect a median error of 8%, however, such error may be as high as 50%.

Voltage-modulated membrane resistance in coupled leech neurons

1979 ◽  
Vol 42 (2) ◽  
pp. 465-475 ◽  
Author(s):  
B. Zipser
Keyword(s):  
Membrane Resistance ◽  
Resting Potential ◽  
Reverse Direction ◽  
Time Constants ◽  
Voltage Dependent ◽  
Current Threshold ◽  
Coupling Factors ◽  
The Impact ◽  
Junctional Resistance ◽  
Lateral Neurons

1. Resistive interactions have been studied between two pairs of large identifiable neurons in ganglion 6 of the leech CNS, called the lateral and rostral cells. Both are motor neurons causing penile eversion. 2. Lateral and rostral neurons have different membrane resistance properties. Input resistances of lateral neurons are virtually constant. By contrast, membrane resistances of rostral neurons are highly voltage dependent. When depolarized from resting potential to firing level, a rostral neuron's input resistance can increase 10-fold, from 30 to 300 Momega. 3. Voltage-dependent membrane characteristics of rostral neurons cause resistive interactions with lateral neurons to be nonlinear. DC potentials evoked in lateral cells are transmitted to rostral cells with an efficiency varying over a 10-fold range. Hyperpolarizing coupling is weak, with coupling factors of about 0.03. Depolarizing coupling factors increase progressively with increasing lateral neuron depolarization, reaching values of up to 0.3. 4. Membrane resistance changes in rostral neurons accompany lateral to rostral cell interactions. Input resistances increase during depolarizing and decrease during hyperpolarizing coupling potentials. The lateral to rostral cell junctional resistance is high and invariant, as evidenced by uniformly weak coupling in the reverse direction, from rostral to lateral neurons. 5. In conclusion, asymmetries in lateral to rostral cell interaction are based on postsynaptic rather than junctional resistance changes. The impact of the lateral onto the rostral cell's excitability contains a nonlinear component besides the usual linear additive one. As in conventional resistive coupling, depolarizing coupling potentials raise the rostral neuron closer to its voltage threshold. But more significantly, depolarizing coupling potentials lower the rostral neuron's current threshold because increases in resistance proportionately reduce the amount of excitatory current needed to reach firing level. Thus, the resistance change acts to amplify the input signal efficiency. In addition to the static changes in current threshold, the reostral neuron also changes dynamically. Membrane resistance increases lead to increases in space constant shrinking the neuron's electrical lenght. 6. Other properties of the network have been analyzed. The pair of lateral neurons is strongly coupled, whereas the pair of rostral neurons is weakly coupled, the coupling factors are 0.3 and 0.05, respectively. Hyperpolarizing membrane time constants for the lateral and rostral neurons are estimated to be between 100 and 200 ms. Time constants of depolarized rostral neurons are significantly larger.

scholarly journals On the impact of sampling frequency on software energy measurements

2015 ◽  
Author(s):  
Rubén Saborido ◽  
Venera Venera Arnaoudova ◽  
Giovanni Beltrame ◽  
Foutse Khomh ◽  
Giuliano Antoniol
Keyword(s):  
Energy Consumption ◽  
Mobile Applications ◽  
Low Frequency ◽  
Battery Life ◽  
Low Frequencies ◽  
Fine Grain ◽  
Rough Approximation ◽  
Median Error ◽  
Real Picture ◽  
The Impact

Energy consumption is a major concern when developing and evolving mobile applications. The user wishes to access fast and powerful mobile applications, which is usually in contrast to optimized battery life and heat generation. The software engineering community have acknowledged the relevance of the problem and researchers are investigating ways to reduce energy consumption, for example by examining which library, device configuration, and applications parameters should be used to promote long battery life. We conjecture that these studies are at the border between hardware and software and we must be careful on how the energy consumption is measured and how the energy consumption is attributed to methods and libraries.To the best of our knowledge, no previous work investigates how much energy and power consumption is due to high frequency events missed when sampling at low frequencies such as 10 kHz and verified the error at the precision of method level. Low frequency sampling is a rough approximation that hinders the understanding of fine grain details: the real picture of energy consumption as well as the root causes are missed. This has profound implications on the choice of methods to evolve or components to replace.In this paper, we propose an approach for accurate measurements of the energy consumption of mobile applications. We apply the proposed approach to assess the energy consumption of 21 mobile, closed source, applications and four open source Android applications.We show that by sampling at 10 kHz one may expect a median error of 8%, however, such error may be as high as 50% for short fast executing methods. Finally, we revisit a previous approach that estimates the energy consumption of methods based on execution time and found that it can miss as much as 84% of the energy, with a median of 30%.

scholarly journals On the impact of sampling frequency on software energy measurements

2015 ◽  
Author(s):  
Rubén Saborido ◽  
Venera Venera Arnaoudova ◽  
Giovanni Beltrame ◽  
Foutse Khomh ◽  
Giuliano Antoniol
Keyword(s):  
Energy Consumption ◽  
Mobile Applications ◽  
Low Frequency ◽  
Battery Life ◽  
Low Frequencies ◽  
Fine Grain ◽  
Rough Approximation ◽  
Median Error ◽  
Real Picture ◽  
The Impact

Energy consumption is a major concern when developing and evolving mobile applications. The user wishes to access fast and powerful mobile applications, which is usually in contrast to optimized battery life and heat generation. The software engineering community have acknowledged the relevance of the problem and researchers are investigating ways to reduce energy consumption, for example by examining which library, device configuration, and applications parameters should be used to promote long battery life. We conjecture that these studies are at the border between hardware and software and we must be careful on how the energy consumption is measured and how the energy consumption is attributed to methods and libraries.To the best of our knowledge, no previous work investigates how much energy and power consumption is due to high frequency events missed when sampling at low frequencies such as 10 kHz and verified the error at the precision of method level. Low frequency sampling is a rough approximation that hinders the understanding of fine grain details: the real picture of energy consumption as well as the root causes are missed. This has profound implications on the choice of methods to evolve or components to replace.In this paper, we propose an approach for accurate measurements of the energy consumption of mobile applications. We apply the proposed approach to assess the energy consumption of 21 mobile, closed source, applications and four open source Android applications.We show that by sampling at 10 kHz one may expect a median error of 8%, however, such error may be as high as 50% for short fast executing methods. Finally, we revisit a previous approach that estimates the energy consumption of methods based on execution time and found that it can miss as much as 84% of the energy, with a median of 30%.

scholarly journals Voltage-dependent K + channels improve the energy efficiency of signalling in blowfly photoreceptors

2017 ◽  
Vol 14 (129) ◽  
pp. 20160938 ◽  
Author(s):  
Francisco J. H. Heras ◽  
John Anderson ◽  
Simon B. Laughlin ◽  
Jeremy E. Niven
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Negative Feedback ◽  
Light Adaptation ◽  
Bright Light ◽  
Spiking Neurons ◽  
Delayed Rectifier ◽  
Voltage Response ◽  
Functional Requirements ◽  
Voltage Dependent

Voltage-dependent conductances in many spiking neurons are tuned to reduce action potential energy consumption, so improving the energy efficiency of spike coding. However, the contribution of voltage-dependent conductances to the energy efficiency of analogue coding, by graded potentials in dendrites and non-spiking neurons, remains unclear. We investigate the contribution of voltage-dependent conductances to the energy efficiency of analogue coding by modelling blowfly R1-6 photoreceptor membrane. Two voltage-dependent delayed rectifier K + conductances (DRs) shape the membrane's voltage response and contribute to light adaptation. They make two types of energy saving. By reducing membrane resistance upon depolarization they convert the cheap, low bandwidth membrane needed in dim light to the expensive high bandwidth membrane needed in bright light. This investment of energy in bandwidth according to functional requirements can halve daily energy consumption. Second, DRs produce negative feedback that reduces membrane impedance and increases bandwidth. This negative feedback allows an active membrane with DRs to consume at least 30% less energy than a passive membrane with the same capacitance and bandwidth. Voltage-dependent conductances in other non-spiking neurons, and in dendrites, might be organized to make similar savings.

Strategy Study on China E-Business Service in Big Data Era

2013 ◽  
Vol 798-799 ◽  
pp. 983-986 ◽  
Author(s):  
Wen Jin Xu
Keyword(s):  
Big Data ◽  
Information Processing ◽  
Energy Consumption ◽  
Point Of View ◽  
Business Service ◽  
Strategy Study ◽  
Massive Growth ◽  
Rational Mode ◽  
Real Time Computing ◽  
The Impact

The era of big data means that the data grows in explosive way,but this massive growth of the data does not mean lots of information. In this article, we show that such big data cannot be used in the same way as before; otherwise from the point of view of energy consumption, the computer system cannot afford it. At the same time, the information collected at this stage is also unable to meet the impact of the arrival of such a big data. The big data is taken from the application. To complete specific, we should often choose the rational mode of information processing or the algorithm. In business computing, offline computing and real time computing are the two ways to process big data.

Impact of roof shading on building energy performance in warm & humid climatic places of India

2020 ◽  
pp. 50-64
Author(s):  
Kuladeep Kumar Sadevi ◽  
Avlokita Agrawal
Keyword(s):  
Energy Consumption ◽  
Energy Conservation ◽  
Energy Performance ◽  
General Assumption ◽  
Climatic Conditions ◽  
Building Envelope ◽  
Passive Cooling ◽  
Base Case ◽  
U Value ◽  
The Impact

With the rise in awareness of energy efficient buildings and adoption of mandatory energy conservation codes across the globe, significant change is being observed in the way the buildings are designed. With the launch of Energy Conservation Building Code (ECBC) in India, climate responsive designs and passive cooling techniques are being explored increasingly in building designs. Of all the building envelope components, roof surface has been identified as the most significant with respect to the heat gain due to the incident solar radiation on buildings, especially in tropical climatic conditions. Since ECBC specifies stringent U-Values for roof assembly, use of insulating materials is becoming popular. Along with insulation, the shading of the roof is also observed to be an important strategy for improving thermal performance of the building, especially in Warm and humid climatic conditions. This study intends to assess the impact of roof shading on building’s energy performance in comparison to that of exposed roof with insulation. A typical office building with specific geometry and schedules has been identified as base case model for this study. This building is simulated using energy modelling software ‘Design Builder’ with base case parameters as prescribed in ECBC. Further, the same building has been simulated parametrically adjusting the amount of roof insulation and roof shading simultaneously. The overall energy consumption and the envelope performance of the top floor are extracted for analysis. The results indicate that the roof shading is an effective passive cooling strategy for both naturally ventilated and air conditioned buildings in Warm and humid climates of India. It is also observed that a fully shaded roof outperforms the insulated roof as per ECBC prescription. Provision of shading over roof reduces the annual energy consumption of building in case of both insulated and uninsulated roofs. However, the impact is higher for uninsulated roofs (U-Value of 3.933 W/m2K), being 4.18% as compared to 0.59% for insulated roofs (U-Value of 0.33 W/m2K).While the general assumption is that roof insulation helps in reducing the energy consumption in tropical buildings, it is observed to be the other way when insulation is provided with roof shading. It is due to restricted heat loss during night.

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