160 research outputs found
Fly Photoreceptors Demonstrate Energy-Information Trade-Offs in Neural Coding
Trade-offs between energy consumption and neuronal performance must shape the design and evolution of nervous systems, but we lack empirical data showing how neuronal energy costs vary according to performance. Using intracellular recordings from the intact retinas of four flies, Drosophila melanogaster, D. virilis, Calliphora vicina, and Sarcophaga carnaria, we measured the rates at which homologous R1–6 photoreceptors of these species transmit information from the same stimuli and estimated the energy they consumed. In all species, both information rate and energy consumption increase with light intensity. Energy consumption rises from a baseline, the energy required to maintain the dark resting potential. This substantial fixed cost, ∼20% of a photoreceptor's maximum consumption, causes the unit cost of information (ATP molecules hydrolysed per bit) to fall as information rate increases. The highest information rates, achieved at bright daylight levels, differed according to species, from ∼200 bits s(−1) in D. melanogaster to ∼1,000 bits s(−1) in S. carnaria. Comparing species, the fixed cost, the total cost of signalling, and the unit cost (cost per bit) all increase with a photoreceptor's highest information rate to make information more expensive in higher performance cells. This law of diminishing returns promotes the evolution of economical structures by severely penalising overcapacity. Similar relationships could influence the function and design of many neurons because they are subject to similar biophysical constraints on information throughput
Network adaptation improves temporal representation of naturalistic stimuli in drosophila eye: II Mechanisms
Retinal networks must adapt constantly to best present the ever changing visual world to the brain. Here we test the hypothesis that adaptation is a result of different mechanisms at several synaptic connections within the network. In a companion paper (Part I), we showed that adaptation in the photoreceptors (R1-R6) and large monopolar cells (LMC) of the Drosophila eye improves sensitivity to under-represented signals in seconds by enhancing both the amplitude and frequency distribution of LMCs' voltage responses to repeated naturalistic contrast series. In this paper, we show that such adaptation needs both the light-mediated conductance and feedback-mediated synaptic conductance. A faulty feedforward pathway in histamine receptor mutant flies speeds up the LMC output, mimicking extreme light adaptation. A faulty feedback pathway from L2 LMCs to photoreceptors slows down the LMC output, mimicking dark adaptation. These results underline the importance of network adaptation for efficient coding, and as a mechanism for selectively regulating the size and speed of signals in neurons. We suggest that concert action of many different mechanisms and neural connections are responsible for adaptation to visual stimuli. Further, our results demonstrate the need for detailed circuit reconstructions like that of the Drosophila lamina, to understand how networks process information
Visual Coding in Locust Photoreceptors
Information capture by photoreceptors ultimately limits the quality of visual processing in the brain. Using conventional sharp microelectrodes, we studied how locust photoreceptors encode random (white-noise, WN) and naturalistic (1/f stimuli, NS) light patterns in vivo and how this coding changes with mean illumination and ambient temperature. We also examined the role of their plasma membrane in shaping voltage responses. We found that brightening or warming increase and accelerate voltage responses, but reduce noise, enabling photoreceptors to encode more information. For WN stimuli, this was accompanied by broadening of the linear frequency range. On the contrary, with NS the signaling took place within a constant bandwidth, possibly revealing a ‘preference’ for inputs with 1/f statistics. The faster signaling was caused by acceleration of the elementary phototransduction current - leading to bumps - and their distribution. The membrane linearly translated phototransduction currents into voltage responses without limiting the throughput of these messages. As the bumps reflected fast changes in membrane resistance, the data suggest that their shape is predominantly driven by fast changes in the light-gated conductance. On the other hand, the slower bump latency distribution is likely to represent slower enzymatic intracellular reactions. Furthermore, the Q10s of bump duration and latency distribution depended on light intensity. Altogether, this study suggests that biochemical constraints imposed upon signaling change continuously as locust photoreceptors adapt to environmental light and temperature conditions
Responses of Auditory Nerve and Anteroventral Cochlear Nucleus Fibers to Broadband and Narrowband Noise: Implications for the Sensitivity to Interaural Delays
The quality of temporal coding of sound waveforms in the monaural afferents that converge on binaural neurons in the brainstem limits the sensitivity to temporal differences at the two ears. The anteroventral cochlear nucleus (AVCN) houses the cells that project to the binaural nuclei, which are known to have enhanced temporal coding of low-frequency sounds relative to auditory nerve (AN) fibers. We applied a coincidence analysis within the framework of detection theory to investigate the extent to which AVCN processing affects interaural time delay (ITD) sensitivity. Using monaural spike trains to a 1-s broadband or narrowband noise token, we emulated the binaural task of ITD discrimination and calculated just noticeable differences (jnds). The ITD jnds derived from AVCN neurons were lower than those derived from AN fibers, showing that the enhanced temporal coding in the AVCN improves binaural sensitivity to ITDs. AVCN processing also increased the dynamic range of ITD sensitivity and changed the shape of the frequency dependence of ITD sensitivity. Bandwidth dependence of ITD jnds from AN as well as AVCN fibers agreed with psychophysical data. These findings demonstrate that monaural preprocessing in the AVCN improves the temporal code in a way that is beneficial for binaural processing and may be crucial in achieving the exquisite sensitivity to ITDs observed in binaural pathways
TRY plant trait database - enhanced coverage and open access
Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives
Expression in Antennae and Reproductive Organs Suggests a Dual Role of an Odorant-Binding Protein in Two Sibling Helicoverpa Species
Odorant-binding proteins (OBPs) mediate both perception and release of semiochemicals in insects. These proteins are the ideal targets for understanding the olfactory code of insects as well as for interfering with their communication system in order to control pest species. The two sibling Lepidopteran species Helicoverpa armigera and H. assulta are two major agricultural pests. As part of our aim to characterize the OBP repertoire of these two species, here we focus our attention on a member of this family, OBP10, particularly interesting for its expression pattern. The protein is specifically expressed in the antennae of both sexes, being absent from other sensory organs. However, it is highly abundant in seminal fluid, is transferred to females during mating and is eventually found on the surface of fertilised eggs. Among the several different volatile compounds present in reproductive organs, OBP10 binds 1-dodecene, a compound reported as an insect repellent. These results have been verified in both H. armigera and H. assulta with no apparent differences between the two species. The recombinant OBP10 binds, besides 1-dodecene, some linear alcohols and several aromatic compounds. The structural similarity of OBP10 with OBP1 of the mosquito Culex quinquefasciatus, a protein reported to bind an oviposition pheromone, and its affinity with 1-dodecene suggest that OBP10 could be a carrier for oviposition deterrents, favouring spreading of the eggs in these species where cannibalism is active among larvae
Robust Models for Optic Flow Coding in Natural Scenes Inspired by Insect Biology
The extraction of accurate self-motion information from the visual world is a difficult problem that has been solved very efficiently by biological organisms utilizing non-linear processing. Previous bio-inspired models for motion detection based on a correlation mechanism have been dogged by issues that arise from their sensitivity to undesired properties of the image, such as contrast, which vary widely between images. Here we present a model with multiple levels of non-linear dynamic adaptive components based directly on the known or suspected responses of neurons within the visual motion pathway of the fly brain. By testing the model under realistic high-dynamic range conditions we show that the addition of these elements makes the motion detection model robust across a large variety of images, velocities and accelerations. Furthermore the performance of the entire system is more than the incremental improvements offered by the individual components, indicating beneficial non-linear interactions between processing stages. The algorithms underlying the model can be implemented in either digital or analog hardware, including neuromorphic analog VLSI, but defy an analytical solution due to their dynamic non-linear operation. The successful application of this algorithm has applications in the development of miniature autonomous systems in defense and civilian roles, including robotics, miniature unmanned aerial vehicles and collision avoidance sensors
Naturally occurring and stress induced tubular structures from mammalian cells, a survival mechanism
Skeletal muscle and performance adaptations to high-intensity training in elite male soccer players: speed endurance runs versus small-sided game training.
PURPOSE: To examine the skeletal muscle and performance responses across two different exercise training modalities which are highly applied in soccer training. METHODS: Using an RCT design, 39 well-trained male soccer players were randomized into either a speed endurance training (SET; n = 21) or a small-sided game group (SSG; n = 18). Over 4 weeks, thrice weekly, SET performed 6-10 × 30-s all-out runs with 3-min recovery, while SSG completed 2 × 7-9-min small-sided games with 2-min recovery. Muscle biopsies were obtained from m. vastus lateralis pre and post intervention and were subsequently analysed for metabolic enzyme activity and muscle protein expression. Moreover, the Yo-Yo Intermittent Recovery level 2 test (Yo-Yo IR2) was performed. RESULTS: Muscle CS maximal activity increased (P < 0.05) by 18% in SET only, demonstrating larger (P < 0.05) improvement than SSG, while HAD activity increased (P < 0.05) by 24% in both groups. Na(+)-K(+) ATPase α1 subunit protein expression increased (P < 0.05) in SET and SSG (19 and 37%, respectively), while MCT4 protein expression rose (P < 0.05) by 30 and 61% in SET and SSG, respectively. SOD2 protein expression increased (P < 0.05) by 28 and 37% in SET and SSG, respectively, while GLUT-4 protein expression increased (P < 0.05) by 40% in SSG only. Finally, SET displayed 39% greater improvement (P < 0.05) in Yo-Yo IR2 performance than SSG. CONCLUSION: Speed endurance training improved muscle oxidative capacity and exercise performance more pronouncedly than small-sided game training, but comparable responses were in muscle ion transporters and antioxidative capacity in well-trained male soccer players
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