Potency of transgenic effectors for neurogenetic manipulation in Drosophila larvae

Genetic manipulations of neuronal activity are a cornerstone of studies aimed to identify the functional impact of defined neurons for animal behavior. With its small nervous system, rapid life cycle, and genetic amenability, the fruit fly Drosophila melanogaster provides an attractive model system to study neuronal circuit function. In the past two decades, a large repertoire of elegant genetic tools has been developed to manipulate and study neural circuits in the fruit fly. Current techniques allow genetic ablation, constitutive silencing, or hyperactivation of neuronal activity and also include conditional thermogenetic or optogenetic activation or inhibition. As for all genetic techniques, the choice of the proper transgenic tool is essential for behavioral studies. Potency and impact of effectors may vary in distinct neuron types or distinct types of behavior. We here systematically test genetic effectors for their potency to alter the behavior of Drosophila larvae, using two distinct behavioral paradigms: general locomotor activity and directed, visually guided navigation. Our results show largely similar but not equal effects with different effector lines in both assays. Interestingly, differences in the magnitude of induced behavioral alterations between different effector lines remain largely consistent between the two behavioral assays. The observed potencies of the effector lines in aminergic and cholinergic neurons assessed here may help researchers to choose the best-suited genetic tools to dissect neuronal networks underlying the behavior of larval fruit flies

Comparative validation of standard, picture-sort and meal-based food-frequency questionnaires adapted for an elderly population of low socio-economic status

OBJECTIVE: To compare the validity of a modified Block food-frequency questionnaire (FFQ), a picture-sort administration of the FFQ (PSFFQ) and a meal pattern-based questionnaire (MPQ) in a multi-ethnic population of low socio-economic status (SES). DESIGN: Participants completed six 24-hour dietary recalls (24HR) over six months; the FFQ, PSFFQ and MPQ were completed in random order in the subsequent month. Instruments were interviewer-administered. The PSFFQ and MPQ were developed in formative research concerning difficulties for older adults in responding to standard food-frequency instruments. SETTING: Rural North Carolina, USA. Subjects One hundred and twenty-two African American, Native American and white adults aged > or = 65 years, with approximately one-third in each ethnic group. Inclusion criteria included education < or = 12 years and income < or = 150% of national poverty level or Medicaid recipient. RESULTS: Comparing median intakes from the average of the 24HR with the three diet assessment instruments, the MPQ tended to overestimate intakes compared with the FFQ and PSFFQ. Correlations among nutrients obtained by the 24HR and the other three instruments were generally statistically significant and positive. Across nutrients, the PSFFQ was most highly correlated with the 24HR for women, while the FFQ was most highly correlated with the 24HR for men. CONCLUSIONS: Dietary assessments using 24HR and FFQ were similar to results reported elsewhere, although correlations between 24HR and FFQ were somewhat lower. Interviewer-administered dietary assessments should be used with caution to evaluate dietary intake among older adults with low SES. Gender differences and the lower correlations should be investigated more thoroughly to assist in choosing dietary assessment instruments for this population

Relating Neuronal to Behavioral Performance: Variability of Optomotor Responses in the Blowfly

Behavioral responses of an animal vary even when they are elicited by the same stimulus. This variability is due to stochastic processes within the nervous system and to the changing internal states of the animal. To what extent does the variability of neuronal responses account for the overall variability at the behavioral level? To address this question we evaluate the neuronal variability at the output stage of the blowfly's (Calliphora vicina) visual system by recording from motion-sensitive interneurons mediating head optomotor responses. By means of a simple modelling approach representing the sensory-motor transformation, we predict head movements on the basis of the recorded responses of motion-sensitive neurons and compare the variability of the predicted head movements with that of the observed ones. Large gain changes of optomotor head movements have previously been shown to go along with changes in the animals' activity state. Our modelling approach substantiates that these gain changes are imposed downstream of the motion-sensitive neurons of the visual system. Moreover, since predicted head movements are clearly more reliable than those actually observed, we conclude that substantial variability is introduced downstream of the visual system

Impact and sources of neuronal variability in the fly's motion vision pathway

Warzecha A-K, Rosner R, Grewe J. Impact and sources of neuronal variability in the fly's motion vision pathway. Journal Of Physiology-Paris. 2013;107(1-2):26-40.Nervous systems encode information about dynamically changing sensory input by changes in neuronal activity. Neuronal activity changes, however, also arise from noise sources within and outside the nervous system or from changes of the animal's behavioral state. The resulting variability of neuronal responses in representing sensory stimuli limits the reliability with which animals can respond to stimuli and may thus even affect the chances for survival in certain situations. Relevant sources of noise arising at different stages along the motion vision pathway have been investigated from the sensory input to the initiation of behavioral reactions. Here, we concentrate on the reliability of processing visual motion information in flies. Flies rely on visual motion information to guide their locomotion. They are among the best established model systems for the processing of visual motion information allowing us to bridge the gap between behavioral performance and underlying neuronal computations. It has been possible to directly assess the consequences of noise at major stages of the fly's visual motion processing system on the reliability of neuronal signals. Responses of motion sensitive neurons and their variability have been related to optomotor movements as indicators for the overall performance of visual motion computation. We address whether and how noise already inherent in the stimulus, e.g. photon noise for the visual system, influences later processing stages and to what extent variability at the output level of the sensory system limits behavioral performance. Recent advances in circuit analysis and the progress in monitoring neuronal activity in behaving animals should now be applied to understand how the animal meets the requirements of fast and reliable manoeuvres in naturalistic situations. (C) 2012 Elsevier Ltd. All rights reserved

Filtering Techniques to Improve Trace-Cache Efficiency

The trace cache is becoming an important building block of modern, wide-issue, processors. So far, trace cache related research has been focused on increasing fetch bandwidth. Trace-caches have been shown to effectively increase the number of “useful ” instructions that can be fetched into the machine, thus enabling more instructions to be executed each cycle. However, trace cache has another important benefit that got less attention in recent research: especially for variable length ISA, such as Intel’s IA-32 architecture (X86), reducing instruction decoding power is particularly attractive. Keeping the instruction traces in decoded format, implies the decoding power is only paid upon the build of a trace, thus reducing the overall power consumption of th

Selecting long atomic traces for high coverage

This paper performs a comprehensive investigation of dynamic selection for long atomic traces. It introduces a classification of trace selection methods and discusses existing and novel dynamic selection approaches – including loop unrolling, procedure inlining and incremental merging of traces based on dynamic bias. The paper empirically analyzes a number of selection schemes in an idealized framework. Observations based on the SPEC-CPU2000 benchmarks show that: (a) selection based on dynamic bias is necessary to achieve the best performance across all benchmarks, (b) the best selection scheme is benchmark and maximum trace-length specific, (c) simple selection, based on program structure information only, is sufficient to achieve the best performance for several benchmarks. Consequently, two alternatives for the trace selection mechanism are established: (a) a “best performance ” approach relying on complex dynamic criteria; (b) a “value ” approach that provides the best performance (and potentially the best power consumption) based on simpler static criteria. Another emerging alternative advocates adaptive based mechanisms to adjust selection criteria

Head pitch movements predicted from neuronal responses to downward motion.

<p>A first-order low-pass filter (τ = 150 ms) was applied to neuronal responses of a VS2/3-cell recorded in close temporal succession during the presence (red) or absence (blue) of haltere oscillations.</p

Signal-to-noise ratios for simulated and actually observed head optomotor pitch movements.

<p>Signal-to-noise ratios (SNRs) are means across flies (predictions: N = 7, behavior: N = 6) and plotted as functions of time after stimulus motion onset. In order to predict head pitch in the elevated (reduced) motor activity state a first-order (second-order) low-pass filter was used. The SNR of actually observed head movements at the end of the trials in both motor activity states is considerably smaller than predicted for the respective state. At the end of the open-loop interval (grey shaded box and inset), the SNR of the predicted high activity state responses already outreaches the SNR of the head movements recorded in that state (see text for details). Note that the seeming state difference in SNRs of actually observed responses is at least in part the consequence of spontaneous head pitch superimposing on the visually induced response (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0026886#pone.0026886-Rosner1" target="_blank">[16]</a>).</p

Comparison of predicted and actually observed head pitch responses to downward motion.

<p>The same neuronal responses were used for the predictions in (A) and (B). The gain factor was adjusted to fit the mean response amplitude of the behavioral responses. (A) Behavioral responses (red) were recorded while the fly was in a state of elevated motor activity. A first-order low-pass filter (τ = 100 ms) was used to predict head pitch from neuronal responses. Predictions (dark gray) are much less variable than the actually observed responses. All pitch responses recorded in the elevated activity state of one fly are shown. (B) Neuronal and behavioral (blue) responses were recorded while the fly was in a state of reduced motor activity. A second-order low-pass filter (τ₁ = 100 ms, τ₂ = 100 ms) better approximates head pitch in the reduced motor activity state than a first-order filter. Again, predictions (dark gray) are less variable than the actually observed responses. Only a subset of the recorded traces is shown for illustration of response shape and variability. Note the different scales in (A) and (B).</p

Apparent Motion Perception in the Praying Mantis: Psychophysics and Modelling

Apparent motion is the perception of motion created by rapidly presenting still frames in which objects are displaced in space. Observers can reliably discriminate the direction of apparent motion when inter-frame object displacement is below a certain limit, Dmax . Earlier studies of motion perception in humans found that Dmax is lower-bounded at around 15 arcmin, and thereafter scales with the size of the spatial elements in the images. Here, we run corresponding experiments in the praying mantis Sphodromantis lineola to investigate how Dmax scales with the element size. We use random moving chequerboard patterns of varying element and displacement step sizes to elicit the optomotor response, a postural stabilization mechanism that causes mantids to lean in the direction of large-field motion. Subsequently, we calculate Dmax as the displacement step size corresponding to a 50% probability of detecting an optomotor response in the same direction as the stimulus. Our main findings are that the mantis Dmax scales roughly as a square-root of element size and that, in contrast to humans, it is not lower-bounded. We present two models to explain these observations: a simple high-level model based on motion energy in the Fourier domain and a more-detailed one based on the Reichardt Detector. The models present complementary intuitive and physiologically-realistic accounts of how Dmax scales with the element size in insects. We conclude that insect motion perception is limited by only a single stage of spatial filtering, reflecting the optics of the compound eye. In contrast, human motion perception reflects a second stage of spatial filtering, at coarser scales than imposed by human optics, likely corresponding to the magnocellular pathway. After this spatial filtering, mantis and human motion perception and Dmax are qualitatively very similar