Filter neurons for specific optic flow patterns in the fly's visual systems

The control of locomotion in a given environment requires information about instantaneous self-motion. Visually oriented animals, including man, may gain such information by analyzing the momentary optic flow pattern generated over both eyes during relative movement between animal and environment. Optic flow patterns can be described by vector fields where each single vector indicates the direction and velocity of the local relative movement at a certain position within the visual field. An optic flow pattern depends upon a set of motion parameters, namely (i) the direction of gaze and (ii) the rotatory and (iii) translatory components of self-motion. The translatory flow vectors also depend an the distance between visual objects and the eyes. Therefore, optic flow fields contain valuable information about the 3D-layout of the surroundings and instantaneous self-motion (Koenderink and van Doorn, 1987). About 50 motion-sensitive, wide-field interneurons which are assumed to be' involved in locomotor control are located in the third visual neuropil (lobula plate) of the blowfly's (Calliphora erythrocephala) visual system (Hausen, 1993). The output of many direction-specific movement detectors (EMDS) with small receptive fields are spatially integrated in a retinotopic manner an the dendrites of these interneurons. Are such interneurons adapted to sense specific aspects of the momentary optic flow field? To address this question, we investigated the receptive field organization of 10 identifiable interneurons of the so called vertical-system (VS; Hengstenberg, 1982) in great detail. We recorded intracellularly from the VS-neurons to determine the spatial distribution of local preferred directions and motion sensitivities at 52 positions spaced equally over the ipsilateral visual hemisphere (for method see: Menzel and Hengstenberg, 1991; Krapp and Hengstenberg 1992). The resulting response fields of the VS-neurons (about 90 recordings) show striking similarities to optic flow fields generated by specific motions in space (Krapp and Hengstenberg, 1994). By applying an iterative least square formalism (Koenderink and van Doorn, 1987) to the response fields we calculated the optimal self-motion parameters (translatory and rotatory component) for each VS-neuron. These parameters describe an optic flow field that best fits the respective measured response field. To find out whether the VS-neurons are functionally tuned more to the translatory or to the rotatory component of self-motion we systematically varied the optimal motion parameters. The error between the measured response field and the calculated optic flow field increases if both the translatory and the rotatory component deviate from the optimal motion parameters. The increase in the error is almost the same if only the rotatory component is varied. In contrast, if the translatory component is varied and the rotatory component is kept optimal the increase in the error is considerably smaller. The analysis of the response fields of the VS-neurons leads to the following conclusion: the VS-neurons are functionally tuned to sense rotations around different horizontally aligned body axes. The neurons VS1-VS3 are optimized to sense optic flow fields generated during nose-up pitch. VS4-VS7 are filter neurons for counterclockwise roll and VS8-VS10 are adapted to rotations around an axis that lies between the pitch and roll axes. Thus, the signals of the VS-neurons could contribute directly to visual flight control and gaze stabilization

Modeling visual-based pitch, lift and speed control strategies in hoverflies

<div><p>To avoid crashing onto the floor, a free falling fly needs to trigger its wingbeats quickly and control the orientation of its thrust accurately and swiftly to stabilize its pitch and hence its speed. Behavioural data have suggested that the vertical optic flow produced by the fall and crossing the visual field plays a key role in this anti-crash response. Free fall behavior analyses have also suggested that flying insect may not rely on graviception to stabilize their flight. Based on these two assumptions, we have developed a model which accounts for hoverflies´ position and pitch orientation recorded in 3D with a fast stereo camera during experimental free falls. Our dynamic model shows that optic flow-based control combined with closed-loop control of the pitch suffice to stabilize the flight properly. In addition, our model sheds a new light on the visual-based feedback control of fly´s pitch, lift and thrust. Since graviceptive cues are possibly not used by flying insects, the use of a vertical reference to control the pitch is discussed, based on the results obtained on a complete dynamic model of a virtual fly falling in a textured corridor. This model would provide a useful tool for understanding more clearly how insects may or not estimate their absolute attitude.</p></div

Angular sensitivity of blowfly photoreceptors: intracellular measurements and wave-optical predictions

The angular sensitivity of blowfly photoreceptors was measured in detail at wavelengths λ = 355, 494 and 588 nm. The measured curves often showed numerous sidebands, indicating the importance of diffraction by the facet lens. The shape of the angular sensitivity profile is dependent on wavelength. The main peak of the angular sensitivities at the shorter wavelengths was flattened. This phenomenon as well as the overall shape of the main peak can be quantitatively described by a wave-optical theory using realistic values for the optical parameters of the lens-photoreceptor system. At a constant response level of 6 mV (almost dark adapted), the visual acuity of the peripheral cells R1-6 is at longer wavelengths mainly diffraction limited, while at shorter wavelengths the visual acuity is limited by the waveguide properties of the rhabdomere. Closure of the pupil narrows the angular sensitivity profile at the shorter wavelengths. This effect can be fully described by assuming that the intracellular pupil progressively absorbs light from the higher order modes. In light-adapted cells R1-6 the visual acuity is mainly diffraction limited at all wavelengths.

Circulating brain‐derived neurotrophic factor concentrations and the risk of cardiovascular disease in the community

BACKGROUND: Brain‐derived neurotrophic factor (BDNF) is a pleiotropic peptide involved in maintaining endothelial integrity. It is unknown if circulating BDNF levels are associated with risk of cardiovascular disease (CVD). METHODS AND RESULTS: We prospectively investigated the association of circulating BDNF levels with cardiovascular events and mortality in 3687 participants (mean age 65 years, 2068 women) from the Framingham Heart Study (FHS). Using a common nonsynonomous single nucleotide polymorphism (SNP) in the BDNF gene (rs6265), we then performed a Mendelian randomization experiment in the CARDIoGRAM (Coronary ARtery DIsease Genome‐Wide Replication And Meta‐Analysis) consortium (>22 000 coronary artery disease [CAD] cases, >60 000 controls) to investigate whether SNP rs6265 was associated with CAD in CARDIoGRAM and, if so, whether the effect estimate differed from that predicted based on FHS data. On follow‐up (median 8.9 years), 467 individuals (261 women) in FHS experienced a CVD event, and 835 (430 women) died. In multivariable‐adjusted Cox regression, serum BDNF was associated inversely with CVD risk (hazard ratio [HR] per 1‐SD increase 0.88, 95% CI 0.80 to 0.97, P=0.01) and with mortality (HR 0.87, 95% CI 0.80 to 0.93, P=0.0002). SNP rs6265 was associated with BDNF concentrations (0.772 ng/mL increase per minor allele copy) in FHS. In CARDIoGRAM, SNP rs6265 was associated with CAD (odds ratio 0.957, 95% CI 0.923 to 0.992), a magnitude consistent with the predicted effect (HR per minor allele copy 0.99, 95% CI 0.98 to 1.0; P=0.06 for difference between predicted and observed effect). CONCLUSION: Higher serum BDNF is associated with a decreased risk of CVD and mortality. Mendelian randomization suggests a causal protective role of BDNF in the pathogenesis of CVD