Sparsened neuronal activity in an optogenetically activated olfactory glomerulus

© The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Scientific Reports 8 (2018): 14955, doi:10.1038/s41598-018-33021-w.Glomeruli are the functional units of olfactory information processing but little remains known about their individual unit function. This is due to their widespread activation by odor stimuli. We expressed channelrhodopsin-2 in a single olfactory sensory neuron type, and used laser stimulation and simultaneous in vivo calcium imaging to study the responses of a single glomerulus to optogenetic stimulation. Calcium signals in the neuropil of this glomerulus were representative of the sensory input and nearly identical if evoked by intensity-matched odor and laser stimuli. However, significantly fewer glomerular layer interneurons and olfactory bulb output neurons (mitral cells) responded to optogenetic versus odor stimuli, resulting in a small and spatially compact optogenetic glomerular unit response. Temporal features of laser stimuli were represented with high fidelity in the neuropil of the glomerulus and the mitral cells, but not in interneurons. Increases in laser stimulus intensity were encoded by larger signal amplitudes in all compartments of the glomerulus, and by the recruitment of additional interneurons and mitral cells. No spatial expansion of the glomerular unit response was observed in response to stronger input stimuli. Our data are among the first descriptions of input-output transformations in a selectively activated olfactory glomerulus.Funded by the World Class Institute/National Research Foundation of Korea (KRF: WCI 2009-003) and NIH: DC005259 and NS099691 grants

Action representation in the mouse parieto-frontal network

The posterior parietal cortex (PPC) and frontal motor areas comprise a cortical network supporting goal-directed behaviour, with functions including sensorimotor transformations and decision making. In primates, this network links performed and observed actions via mirror neurons, which fire both when individuals perform an action and when they observe the same action performed by a conspecific. Mirror neurons are believed to be important for social learning, but it is not known whether mirror-like neurons occur in similar networks in other social species, such as rodents, or if they can be measured in such models using paradigms where observers passively view a demonstrator. Therefore, we imaged Ca2+ responses in PPC and secondary motor cortex (M2) while mice performed and observed pellet-reaching and wheel-running tasks, and found that cell populations in both areas robustly encoded several naturalistic behaviours. However, neural responses to the same set of observed actions were absent, although we verified that observer mice were attentive to performers and that PPC neurons responded reliably to visual cues. Statistical modelling also indicated that executed actions outperformed observed actions in predicting neural responses. These results raise the possibility that sensorimotor action recognition in rodents could take place outside of the parieto-frontal circuit, and underscore that detecting socially-driven neural coding depends critically on the species and behavioural paradigm used

Efficient and accurate extraction of in vivo calcium signals from microendoscopic video data

In vivo calcium imaging through microendoscopic lenses enables imaging of previously inaccessible neuronal populations deep within the brains of freely moving animals. However, it is computationally challenging to extract single-neuronal activity from microendoscopic data, because of the very large background fluctuations and high spatial overlaps intrinsic to this recording modality. Here, we describe a new constrained matrix factorization approach to accurately separate the background and then demix and denoise the neuronal signals of interest. We compared the proposed method against previous independent components analysis and constrained nonnegative matrix factorization approaches. On both simulated and experimental data recorded from mice, our method substantially improved the quality of extracted cellular signals and detected more well-isolated neural signals, especially in noisy data regimes. These advances can in turn significantly enhance the statistical power of downstream analyses, and ultimately improve scientific conclusions derived from microendoscopic data

On the Design of Energy Efficient Wireless Access Networks

Wireless access networks today consume 0.5 percent of the global energy. Rapidly growing demand for new services and ubiqutious connectivity, will further increase the energy consumption. This situation imposes a big challenge for mobile operators not only due to soaring cost of energy, but also increasing concern for global warming and sustainable development. This thesis focuses on the energy efficiency issue at the system level and studies how to incorporate energy-awareness into the design of future wireless access networks. The main contributions have been given in the areas of energy efficiency assessment, architectural and operational solutions, and total cost of investment analysis. The precise evaluation of energy efficiency is the first essential step to determine optimized solutions where metrics and models constitute the two key elements.We show that maximizing energy efficiency is not always equivalent to minimizing energy consumption which is one of the main reasons behind the presented contradictory and disputable conclusions in the literature. Further we indicate that in order to avoid the debatable directions, energy efficient network design problems should be formulated with well defined coverage and capacity requirements. Moreover, we propose novel backhaul power consumption models considering various technology and architectural options relevant for urban and rural environments and show that backhaul will potentially become a bottleneck in future ultra-high capacity wireless access networks. Second, we focus on clean-slate network deployment solutions satisfying different quality of service requirements in a more energy efficient manner. We identify that the ratio between idle- and transmit power dependent power consumption of a base station as well as the network capacity requirement are the two key parameters that affect the energy-optimum design.While results show that macro cellular systems are the most energy efficient solution for moderate average traffic density, Hetnet solutions prevail homogeneous deployment due to their ability to increase the capacity with a relatively lower energy consumption and thus enable significant energy savings in medium and high capacity demand regions. Moreover, we investigate the energy saving potential of short-term energy aware management approach, i.e., cell DTX, taking advantage of low resource utilization in the current networks arising from strict QoS requirements. With the help of developed novel quantitative method, we show that Cell DTX brings striking reduction in energy consumption and further savings are achievable if the networks are designed taking into account the fact that network deployment and operation are closely related. Finally, we develop a general framework for investigating the main cost elements and for evaluating the viability of energy efficient solutions.We first reveal the strong positive impact of spectrum on both energy and infrastructure cost and further indicate that applying sustainable solutions might also bring total cost reduction, but the viability highly depends on unit cost values as well as the indirect cost benefits of energy efficiency. Results obtained in this dissertation might provide guidelines for the network designers to achieve future high-capacity and sustainable wireless access networks.QC 20140505</p

Towards Green Wireless Access Networks : Main Tradeoffs, Deployment Strategies and Measurement Methodologies

Wireless access networks today consume 0.5 percent of the global energy. Rapidly growing demand for capacity will further increase the energy consumption. Thus, improving energy efficiency has a great importance not only for environmental awareness but also to lower the operational cost of network operators. However, current networks which are optimized based on non-energy related objectives introduce challenges towards green wireless access networks. In this thesis we investigate the solutions at the deployment level and handle energy efficiency assessment issues in wireless access networks. The precise characterization of the power consumption of the whole network has a crucial importance in order to obtain consistent conclusions from any proposed solution at the network level. For this purpose, we propose a novel power consumption model  considering  the impact of backhaul for two established technologies, i.e., fiber and microwave, which is often ignored in the literature. We show that there is a tradeoff between the power saved by using low power base stations and the excess power that has to be spent for backhauling their traffic which therefore needs to carefully be included into energy efficiency analysis. Furthermore, among the solutions that are analyzed, fiber-based backhaul solution is identified to outperform microwave regardless of the considered topology. The proposed model is then used to gain a general insight regarding the important design parameters and their possible impact on energy- and cost oriented network design. To this end, we present a  high-level framework to see the main tradeoffs between energy, infrastructure cost, spectrum and show that future high-capacity systems are increasingly limited by infrastructure and energy costs where spectrum has a strong positive impact on both. We then investigate different network deployment strategies to improve the energy efficiency where we focus on the impact of various base station types, cell size, power consumption parameters and the capacity demand. We propose a refined power consumption model where the parameters are determined in accordance with cell size. We show that network densification can only be justified when capacity expansion is anticipated and over-provisioning of the network is not plausible for greener network. The improvement through heterogeneous networks is indicated to be highly related to the traffic demand where up to 30% improvement is feasible for high area throughput targets. Furthermore, we consider the problem of energy efficiency assessment at the network level in order to allow operators to know their current status and quantify the potential energy savings of different solutions to establish future strategies. We propose elaborate metric forms that can characterize the efficiency and a methodology that indicate how to perform a reliable and accurate measurement considering the complexity of wireless networks. We show the weakness of the current metrics reporting the "effectiveness" and how these might indicate disputable improvement directions unless they are properly revised. This illustrates the need for a standardized network level energy efficiency evaluation methodology towards green wireless access.QC 20121109Energy-efficient wireless networking (eWIN

On the Design of Energy Efficient Wireless Access Networks

Wireless access networks today consume 0.5 percent of the global energy. Rapidly growing demand for new services and ubiqutious connectivity, will further increase the energy consumption. This situation imposes a big challenge for mobile operators not only due to soaring cost of energy, but also increasing concern for global warming and sustainable development. This thesis focuses on the energy efficiency issue at the system level and studies how to incorporate energy-awareness into the design of future wireless access networks. The main contributions have been given in the areas of energy efficiency assessment, architectural and operational solutions, and total cost of investment analysis. The precise evaluation of energy efficiency is the first essential step to determine optimized solutions where metrics and models constitute the two key elements.We show that maximizing energy efficiency is not always equivalent to minimizing energy consumption which is one of the main reasons behind the presented contradictory and disputable conclusions in the literature. Further we indicate that in order to avoid the debatable directions, energy efficient network design problems should be formulated with well defined coverage and capacity requirements. Moreover, we propose novel backhaul power consumption models considering various technology and architectural options relevant for urban and rural environments and show that backhaul will potentially become a bottleneck in future ultra-high capacity wireless access networks. Second, we focus on clean-slate network deployment solutions satisfying different quality of service requirements in a more energy efficient manner. We identify that the ratio between idle- and transmit power dependent power consumption of a base station as well as the network capacity requirement are the two key parameters that affect the energy-optimum design.While results show that macro cellular systems are the most energy efficient solution for moderate average traffic density, Hetnet solutions prevail homogeneous deployment due to their ability to increase the capacity with a relatively lower energy consumption and thus enable significant energy savings in medium and high capacity demand regions. Moreover, we investigate the energy saving potential of short-term energy aware management approach, i.e., cell DTX, taking advantage of low resource utilization in the current networks arising from strict QoS requirements. With the help of developed novel quantitative method, we show that Cell DTX brings striking reduction in energy consumption and further savings are achievable if the networks are designed taking into account the fact that network deployment and operation are closely related. Finally, we develop a general framework for investigating the main cost elements and for evaluating the viability of energy efficient solutions.We first reveal the strong positive impact of spectrum on both energy and infrastructure cost and further indicate that applying sustainable solutions might also bring total cost reduction, but the viability highly depends on unit cost values as well as the indirect cost benefits of energy efficiency. Results obtained in this dissertation might provide guidelines for the network designers to achieve future high-capacity and sustainable wireless access networks.QC 20140505</p

Energy Efficiency Assessment of Wireless AccessNetworks Utilizing Indoor Base Stations

Energy efficiency in mobile radio networks has recently gained great interest due to escalating energy cost and environmental concerns. Rapidly growing demand for capacity will require denser and denser networks which further increase the energy consumption. In this regard, the deployment of small cells under macro-cellular umbrella coverage appears a promising solution to cope with the explosive demand in an energy efficient manner. In this paper, we investigate the impact of joint macro-and femtocell deployment on energy efficiency of wireless access networks, based on varying area throughput requirements. We take into account the the co-channel interference, fraction of indoor users, femto base station density and backhaul power consumption. It is shown that utilizing indoor base stations provide significant energy savings compared to traditional macro only network in urban areas with medium and high user demand where the gain increases up to 75 percent as more data traffic is offloaded to femtocells.QC 20131218Energy-efficient wireless networking (eWIN