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In the quest for deciphering the neural code, theoretical advances were made which allow for the determination of the information rate inherent in the spike trains of nerve cells. However, up to now, the dependence of the information rate on stimulus parameters has not been studied in any neuron in a systematic way. Here, I investigate the information carried by the spike trains of H1, a motion-sensitive visual interneuron of the blowfly (Calliphora vicina) using a moving grating as a stimulus. Stimulus parameters fall in two classes: those that have only a minor effect on the information rate like increasing the frequency bandwidth or the maximum amplitude of the stimulus velocity, and those which dramatically affect the neural information rate, like varying the spatial size or the contrast of the visual pattern being moved. It appears that, for a broad range of complex stimuli, the neuron covers the stimulus with its whole response repertoire regardless of the stimulus entropy, with the information rate being limited by the noise of the stimulus and the neural hardware.

We investigated the effect of mean firing on the information rate of a spiking motion-sensitive neuron in the fly (H1-cell). In the control condition, the cell was stimulated repeatedly by identical zero-symmetrical white-noise motion. The mean firing rate was manipulated by adding a constant velocity offset either in the same area of the receptive field where the dynamic stimulus was displayed or in a separate one. We determined the information rate in the resulting spike trains in the time domain as the difference between the total and the noise entropy rate and found that the information rate increases with increasing mean firing under both stimulus conditions.

In this last paper in a series (Borst and Haag, 1996; Haag et al., 1997) about the lobula plate tangential cells of the fly visual system (CH, HS, and VS cells), the visual response properties were examined using intracellular recordings and computer simulations. In response to visual motion stimuli, all cells responded mainly by a graded shift of their axonal membrane potential. While ipsilateral motion resulted in a graded membrane potential shift, contralateral motion led to distinct EPSPs. For HS cells, simultaneous extracellular recorded action potentials of a spiking interneuron, presumably the H2 cell, corresponded to the EPSPs in the HS cell in a one-to-one fashion. When HS cells were hyperpolarized during ipsilateral motion, they mainly produced action potentials, but when they were hyperpolarized during contralateral motion only a slight increase of EPSP amplitude, could be observed. Intracellular application of the sodium channel blocker QX 314 abolished action potentials of HS cells while having little effect on the graded membrane response to ipsilateral motion. HS and CH cells were also studied with respect to their spatial integration properties. For both cell types, their graded membrane response was found to increase less than linearly with the size of the ipsilateral motion pattern. However, while for HS cells various amounts of hyperpolarizing current injected during motion stimulation led to different saturation levels, this was not the case for CH cells. In response to a sinusoidal velocity modulation, CH cells followed pattern motion only up to 10 Hz modulation frequency, but HS cells still revealed significant membrane depolarizations up to about 40 Hz. In the computer simulations, the compartmental models of tangential cells, as derived in the previous papers, were linked to an array of local motion detectors. The model cells revealed the same basic response features as their natural counterparts. They showed a response saturation as a function of stimulus size. In CH-models, however, the saturation was less pronounced than in real CH-cells, indicating spatially nonuniform membrane resistances with higher values in the dendrite. As in the experiments, HS models responded to high-frequency velocity modulation with a higher amplitude than did CH models.

The passive membrane properties of the tangential cells in the fly lobula plate (CH, HS, and VS cells, Fig. 1) were determined by combining compartmental modeling and current injection experiments. As a prerequisite, we built a digital base of the cells by 3D-reconstructing individual tangential cells from cobalt-stained material including both CH cells (VCH and DCH cells), all three HS cells (HSN, HSE, and HSS cells) and most members of the VS cell family (Figs. 2, 3). In a first series of experiments, hyperpolarizing and depolarizing currents were injected to determine steady-state I-V curves (Fig. 4). At potentials more negative than resting, a linear relationship holds, whereas at potentials more positive than resting, an outward rectification is observed. Therefore, in all subsequent experiments, when a sinusoidal current of variable frequency was injected, a negative DC current was superimposed to keep the neurons in a hyperpolarized state. The resulting amplitude and phase spectra revealed an average steady-state input resistance of 4 to 5 M omega and a cut-off frequency between 40 and 80 Hz (Fig. 5). To determine the passive membrane parameters Rm (specific membrane resistance), Ri (specific internal resistivity), and Cm (specific membrane capacitance), the experiments were repeated in computer simulations on compartmental models of the cells (Fig. 6). Good fits between experimental and simulation data were obtained for the following values: Rm = 2.5 k omega cm2, Ri = 60 omega cm, and Cm = 1.5 microF/cm2 for CH cells; Rm = 2.0 k omega cm2, Ri = 40 omega cm, and Cm = 0.9 microF/cm2 for HS cells; Rm = 2.0 k omega cm2, Ri = 40 omega cm, and Cm = 0.8 microF/cm2 for VS cells. An error analysis of the fitting procedure revealed an area of confidence in the Rm-Ri plane within which the Rm-Ri value pairs are still compatible with the experimental data given the statistical fluctuations inherent in the experiments (Figs. 7, 8). We also investigated whether there exist characteristic differences between different members of the same cell class and how much the exact placement of the electrode (within +/-100 microns along the axon) influences the result of the simulation (Fig. 9). The membrane parameters were further examined by injection of a hyperpolarizing current pulse (Fig. 10). The resulting compartmental models (Fig. 11) based on the passive membrane parameters determined in this way form the basis of forthcoming studies on dendritic integration and signal propagation in the fly tangential cells (Haag et al., 1997; Haag and Borst, 1997).

The extraction of the direction of motion from the time varying retinal images is one of the most basic tasks any visual system is confronted with. However, retinal images are severely corrupted by photon noise, in particular at low light levels, thus limiting the performance of motion detection mechanisms of what sort so ever. Here, we study how photon noise propagates through an array of Reichardt-type motion detectors that are commonly believed to underlie fly motion vision. We provide closed-form analytical expressions of the signal and noise spectra at the output of such a motion detector array. We find that Reichardt detectors reveal favorable noise suppression in the frequency range where most of the signal power resides. Most notably, due to inherent adaptive properties, the transmitted information about stimulus velocity remains nearly constant over a large range of velocity entropies.

In the quest for deciphering the neural code, theoretical advances were made which allow for the determination of the information rate inherent in the spike trains of nerve cells. However, up to now, the dependence of the information rate on stimulus parameters has not been studied in any neuron in a systematic way. Here, I investigate the information carried by the spike trains of H1, a motion-sensitive visual interneuron of the blowfly (Calliphora vicina) using a moving grating as a stimulus. Stimulus parameters fall in two classes: those that have only a minor effect on the information rate like increasing the frequency bandwidth or the maximum amplitude of the stimulus velocity, and those which dramatically affect the neural information rate, like varying the spatial size or the contrast of the visual pattern being moved. It appears that, for a broad range of complex stimuli, the neuron covers the stimulus with its whole response repertoire regardless of the stimulus entropy, with the information rate being limited by the noise of the stimulus and the neural hardware.

In inactive stick insects, sensory information from the femoral chordotonal organ (fCO) about position and movement of the femur-tibia joint is transferred via local nonspiking interneurons onto extensor and flexor tibiae motoneurons. Information is processed by the interaction of antagonistic parallel pathways at two levels: (1) at the input side of the nonspiking interneurons and (2) at the input side of the motoneurons. We tested by a combination of physiological experiments and computer simulation whether the known network topology and the properties of its elements are sufficient to explain the generation of the motor output in response to passive joint movements, that is resistance reflexes. In reinvestigating the quantitative characteristics of interneuronal pathways we identified 10 distinct types of nonspiking interneurons. Synaptic inputs from fCO afferents onto these interneurons are direct excitatory and indirect inhibitory. These connections were investigated with respect to position and velocity signals from the fCO. The results were introduced in the network simulation. The motor output of the simulation has the same characteristics as the real system, even when particular types of interneurons were removed in the simulation and the real system.