Deciphering a neural code for vision

Contrast adaptation in the Limulus lateral eye

Luminance and contrast adaptation are neuronal mechanisms employed by the visual system to adjust our sensitivity to light. They are mediated by an assortment of cellular and network processes distributed across the retina and visual cortex. Both have been demonstrated in the eyes of many vertebrates, but only luminance adaptation has been shown in invertebrate eyes to date. Since the computational benefits of contrast adaptation should apply to all visual systems, we investigated whether this mechanism operates in horseshoe crab eyes, one of the best-understood neural networks in the animal kingdom. The spike trains of optic nerve fibers were recorded in response to light stimuli modulated randomly in time and delivered to single ommatidia or the whole eye. We found that the retina adapts to both the mean luminance and contrast of a white-noise stimulus, that luminance- and contrast-adaptive processes are largely independent, and that they originate within an ommatidium. Network interactions are not involved. A published computer model that simulates existing knowledge of the horseshoe crab eye did not show contrast adaptation, suggesting that a heretofore unknown mechanism may underlie the phenomenon. This mechanism does not appear to reside in photoreceptors because white-noise analysis of electroretinogram recordings did not show contrast adaptation. The likely site of origin is therefore the spike discharge mechanism of optic nerve fibers. The finding of contrast adaption in a retinal network as simple as the horseshoe crab eye underscores the broader importance of this image processing strategy to vision.

A fast and flexible panoramic virtual reality system for behavioural and electrophysiological experiments

Ideally, neuronal functions would be studied by performing experiments with unconstrained animals whilst they behave in their natural environment. Although this is not feasible currently for most animal models, one can mimic the natural environment in the laboratory by using a virtual reality (VR) environment. Here we present a novel VR system based upon a spherical projection of computer generated images using a modified commercial data projector with an add-on fish-eye lens. This system provides equidistant visual stimulation with extensive coverage of the visual field, high spatio-temporal resolution and flexible stimulus generation using a standard computer. It also includes a track-ball system for closed-loop behavioural experiments with walking animals. We present a detailed description of the system and characterize it thoroughly. Finally, we demonstrate the VR system’s performance whilst operating in closed-loop conditions by showing the movement trajectories of the cockroaches during exploratory behaviour in a VR forest.

A new 'view' of ecology and conservation through animal-borne video systems

Over the past three decades, technological advances for monitoring wild animals have expanded the ability of ecologists to study animal behavior and space use. Currently, researchers are deploying animal-borne video and environmental data collection systems (AVEDs), which enable researchers to see what the animal sees in the field. AVEDs record fine-scale movements as well as features of the surrounding environment and thus provide essential context for understanding animal decisions and interactions with other individuals. These fine-scale data are often crucial for understanding potential conservation threats to species of concern. Here, we discuss the development and research potential offered by AVEDs. The benefits of AVEDs are greatest in hypothesis-driven studies that require a fine-scale perspective that other technologies cannot offer.

Are sparse-coding simple cell receptive field models physiologically plausible?

Olshausen and Field (1996) developed a simple cell receptive field model for natural scene processing in V1, based on unsupervised learning and non-orthogonal basis function optimization of an overcomplete representation of visual space. The model was originally tested with an ensemble of whitened natural scenes, simulating pre-cortical filtering in the retinal ganglia and lateral geniculate nucleus, and the basis functions qualitatively resembled the orientation-specific responses of V1 simple cells in the spatial domain. In this study, the quantitative tuning responses of the basis functions in the spectral domain are estimated using a Gaussian model, to determine their goodness-of-fit to the known bandwidths of simple cells in primate V1. Five simulation experiments which examined key features of the model are reported: changing the size of the basis functions; using a complete versus over-complete representation; changing the sparseness factor; using a variable learning rate; and mapping the basis functions with a whitening spatial function. The key finding of this study is that across all image themes, basis function sizes, number of basis functions, sparseness factors and learning rates, the spatial-frequency tuning did not closely resemble that of primate area 17 -- the model results more closely resembled the unclassified cat neurones of area 19 with a single exception, and not area 17 as predicted.

The visual ecology of fiddler crabs

With their eyes on long vertical stalks, their panoramic visual field and their pronounced equatorial acute zone for vertical resolving power, the visual system of fiddler crabs is exquisitely tuned to the geometry of vision in the flat world of inter-tidal mudflats. The crabs live as burrow-centred grazers in dense, mixed-sex, mixed-age and mixed-species colonies, with the active space of an individual rarely exceeding 1 m(2). The full behavioural repertoire of fiddler crabs can thus be monitored over extended periods of time on a moment to moment basis together with the visual information they have available to guide their actions. These attributes make the crabs superb subjects for analysing visual tasks and the design of visual processing mechanisms under natural conditions, a prerequisite for understanding the evolution of visual systems. In this review we show, on the one hand, how deeply embedded fiddler crab vision is in the behavioural and the physical ecology of these animals and, on the other hand, how their behavioural options are constrained by their perceptual limitations. Studying vision in fiddler crabs reminds us that vision has a topography, that it is context-dependent and pragmatic and that there are perceptual limits to what animals can know and therefore care about.

A natural approach to studying vision

An ultimate goal of systems neuroscience is to understand how sensory stimuli encountered in the natural environment are processed by neural circuits. Achieving this goal requires knowledge of both the characteristics of natural stimuli and the response properties of sensory neurons under natural stimulation. Most of our current notions of sensory processing have come from experiments using simple, parametric stimulus sets. However, a growing number of researchers have begun to question whether this approach alone is sufficient for understanding the real-life sensory tasks performed by the organism. Here, focusing on the early visual pathway, we argue that the use of natural stimuli is vital for advancing our understanding of sensory processing.

Movement-induced motion signal distributions in outdoor scenes

The movement of an observer generates a characteristic field of velocity vectors on the retina (Gibson 1950). Because such optic flow-fields are useful for navigation, many theoretical, psychophysical and physiological studies have addressed the question how ego-motion parameters such as direction of heading can be estimated from optic flow. Little is known, however, about the structure of optic flow under natural conditions. To address this issue, we recorded sequences of panoramic images along accurately defined paths in a variety of outdoor locations and used these sequences as input to a two-dimensional array of correlation-based motion detectors (2DMD). We find that (a) motion signal distributions are sparse and noisy with respect to local motion directions; (b) motion signal distributions contain patches (motion streaks) which are systematically oriented along the principal flow-field directions; (c) motion signal distributions show a distinct, dorso-ventral topography, reflecting the distance anisotropy of terrestrial environments; (d) the spatiotemporal tuning of the local motion detector we used has little influence on the structure of motion signal distributions, at least for the range of conditions we tested; and (e) environmental motion is locally noisy throughout the visual field, with little spatial or temporal correlation; it can therefore be removed by temporal averaging and is largely over-ridden by image motion caused by observer movement. Our results suggest that spatial or temporal integration is important to retrieve reliable information on the local direction and size of motion vectors, because the structure of optic flow is clearly detectable in the temporal average of motion signal distributions. Ego-motion parameters can be reliably retrieved from such averaged distributions under a range of environmental conditions. These observations raise a number of questions about the role of specific environmental and computational constraints in the processing of natural optic flow.

Responses of blowfly motion-sensitive neurons to reconstructed optic flow along outdoor flight paths

The retinal image flow a blowfly experiences in its daily life on the wing is determined by both the structure of the environment and the animal's own movements. To understand the design of visual processing mechanisms, there is thus a need to analyse the performance of neurons under natural operating conditions. To this end, we recorded flight paths of flies outdoors and reconstructed what they had seen, by moving a panoramic camera along exactly the same paths. The reconstructed image sequences were later replayed on a fast, panoramic flight simulator to identified, motion sensitive neurons of the so-called horizontal system (HS) in the lobula plate of the blowfly, which are assumed to extract self-motion parameters from optic flow. We show that under real life conditions HS-cells not only encode information about self-rotation, but are also sensitive to translational optic flow and, thus, indirectly signal information about the depth structure of the environment. These properties do not require an elaboration of the known model of these neurons, because the natural optic flow sequences generate--at least qualitatively--the same depth-related response properties when used as input to a computational HS-cell model and to real neurons.

PSTH-based classification of sensory stimuli using ensembles of single neurons

The problem of understanding how ensembles of neurons code for somatosensory information has been defined as a classification problem: given the response of a population of neurons to a set of stimuli, which stimulus generated the response on a single-trial basis? Multivariate statistical techniques such as linear discriminant analysis (LDA) and artificial neural networks (ANNs), and different types of preprocessing stages, such as principal and independent component analysis, have been used to solve this classification problem, with surprisingly small performance differences. Therefore, the goal of this project was to design a new method to maximize computational efficiency rather than classification performance. We developed a peri-stimulus time histogram (PSTH)-based method, which consists of creating a set of templates based on the average neural responses to stimuli and classifying each single trial by assigning it to the stimulus with the 'closest' template in the Euclidean distance sense. The PSTH-based method is computationally more efficient than methods as simple as linear discriminant analysis, performs significantly better than discriminant analyses (linear, quadratic or Mahalanobis) when small binsizes are used (1 ms) and as well as LDA with any other binsize, is optimal among other minimum-distance classifiers and can be optimally applied on raw neural data without a previous stage of dimension reduction. We conclude that the PSTH-based method is an efficient alternative to more sophisticated methods such as LDA and ANNs to study how ensemble of neurons code for discrete sensory stimuli, especially when datasets with many variables are used and when the time resolution of the neural code is one of the factors of interest.

Impact of noise on retinal coding of visual signals

Neural noise introduces uncertainty about the signals encoded in neural spike trains. Because of the uncertainty neurons can reliably transmit a limited amount of information. This amount is difficult to quantify for neurons that combine signals and noise in a complex manner, as many trials would be needed to estimate the joint probability distribution of stimulus and neural response accurately. The task is experimentally tractable, however, for neurons that combine signals with additive Gaussian noise. For such neurons, the joint probability distribution is well defined and information transmission rates can be computed from estimates of signal-to-noise ratio. Here we use power spectral analysis to specify the contributions of signal and noise to retinal coding of visual information. We show that in the spike trains of cat ganglion cells noise power is minimal and constant at temporal frequencies from 0.3 to 20 Hz and that it increases at higher frequencies to a plateau level that generally depends on stimulus contrast. We also show that trial-to-trial fluctuations in noise amplitude at different frequencies are uncorrelated and normally distributed. Although the contrast dependence indicates that noise at high temporal frequencies contributes nonlinearly to ganglion cell spike trains, cells in the primary visual cortex are not known to respond to stimulus modulations >20 Hz. Hence, noise in the retinal output would appear additive, white, and Gaussian from their perspective. This greatly simplifies analysis of information transmission from the eye to the primary visual cortex and perhaps other regions of the brain.

FliMax, a novel stimulus device for panoramic and highspeed presentation of behaviourally generated optic flow

A high-speed panoramic visual stimulation device is introduced which is suitable to analyse visual interneurons during stimulation with rapid image displacements as experienced by fast moving animals. The responses of an identified motion sensitive neuron in the visual system of the blowfly to behaviourally generated image sequences are very complex and hard to predict from the established input circuitry of the neuron. This finding suggests that the computational significance of visual interneurons can only be assessed if they are characterised not only by conventional stimuli as are often used for systems analysis, but also by behaviourally relevant input.

Processing of natural temporal stimuli by macaque retinal ganglion cells

This study quantifies the performance of primate retinal ganglion cells in response to natural stimuli. Stimuli were confined to the temporal and chromatic domains and were derived from two contrasting environments, one typically northern European and the other a flower show. The performance of the cells was evaluated by investigating variability of cell responses to repeated stimulus presentations and by comparing measured to model responses. Both analyses yielded a quantity called the coherence rate (in bits per second), which is related to the information rate. Magnocellular (MC) cells yielded coherence rates of up to 100 bits/sec, rates of parvocellular (PC) cells were much lower, and short wavelength (S)-cone-driven ganglion cells yielded intermediate rates. The modeling approach showed that for MC cells, coherence rates were generated almost exclusively by the luminance content of the stimulus. Coherence rates of PC cells were also dominated by achromatic content. This is a consequence of the stimulus structure; luminance varied much more in the natural environment than chromaticity. Only approximately one-sixth of the coherence rate of the PC cells derived from chromatic content, and it was dominated by frequencies below 10 Hz. S-cone-driven ganglion cells also yielded coherence rates dominated by low frequencies. Below 2-3 Hz, PC cell signals contained more power than those of MC cells. Response variation between individual ganglion cells of a particular class was analyzed by constructing generic cells, the properties of which may be relevant for performance higher in the visual system. The approach used here helps define retinal modules useful for studies of higher visual processing of natural stimuli.

Processing of natural temporal stimuli by macaque retinal ganglion cells

This study quantifies the performance of primate retinal ganglion cells in response to natural stimuli. Stimuli were confined to the temporal and chromatic domains and were derived from two contrasting environments, one typically northern European and the other a flower show. The performance of the cells was evaluated by investigating variability of cell responses to repeated stimulus presentations and by comparing measured to model responses. Both analyses yielded a quantity called the coherence rate (in bits per second), which is related to the information rate. Magnocellular (MC) cells yielded coherence rates of up to 100 bits/sec, rates of parvocellular (PC) cells were much lower, and short wavelength (S)-cone-driven ganglion cells yielded intermediate rates. The modeling approach showed that for MC cells, coherence rates were generated almost exclusively by the luminance content of the stimulus. Coherence rates of PC cells were also dominated by achromatic content. This is a consequence of the stimulus structure; luminance varied much more in the natural environment than chromaticity. Only approximately one-sixth of the coherence rate of the PC cells derived from chromatic content, and it was dominated by frequencies below 10 Hz. S-cone-driven ganglion cells also yielded coherence rates dominated by low frequencies. Below 2-3 Hz, PC cell signals contained more power than those of MC cells. Response variation between individual ganglion cells of a particular class was analyzed by constructing generic cells, the properties of which may be relevant for performance higher in the visual system. The approach used here helps define retinal modules useful for studies of higher visual processing of natural stimuli.

Evidence for use of chemical cues by male horseshoe crabs when locating nesting females (Limulus polyphemus)

Horseshoe crabs come ashore in attached pairs during spring high tides to mate and nest on beaches of the Atlantic and Gulf coasts. Unattached males also come ashore and crowd around the nesting pairs as satellites and engage in sperm competition with the attached male. Females with no satellites and females with large numbers of satellites nest next to one another on the same tide. When females are removed and replaced by a cement model, satellite males continue to be attracted to the same location. Models over sites where females with many satellites had nested are more attractive to males than sites from which a female with no satellites had been removed or a site where no crab had been nesting recently. A second experiment demonstrated that males are responding to chemical cues. A sponge filled with seawater taken from below a female with many satellites and placed under a model female was more attractive to males than a sponge filled with seawater. This is the first demonstration that horseshoe crabs use chemical cues, in addition to visual cues, to locate mates.

Cell-based model of the Limulus lateral eye

We present a cell-based model of the Limulus lateral eye that computes the eye's input to the brain in response to any specified scene. Based on the results of extensive physiological studies, the model simulates the optical sampling of visual space by the array of retinal receptors (ommatidia), the transduction of light into receptor potentials, the integration of excitatory and inhibitory signals into generator potentials, and the conversion of generator potentials into trains of optic nerve impulses. By simulating these processes at the cellular level, model ommatidia can reproduce response variability resulting from noise inherent in the stimulus and the eye itself, and they can adapt to changes in light intensity over a wide operating range. Programmed with these realistic properties, the model eye computes the simultaneous activity of its ensemble of optic nerve fibers, allowing us to explore the retinal code that mediates the visually guided behavior of the animal in its natural habitat. We assess the accuracy of model predictions by comparing the response recorded from a single optic nerve fiber to that computed by the model for the corresponding receptor. Correlation coefficients between recorded and computed responses were typically >95% under laboratory conditions. Parametric analyses of the model together with optic nerve recordings show that animal-to-animal variation in the optical and neural properties of the eye do not alter significantly its response to objects having the size and speed of horseshoe crabs. The eye appears robustly designed for encoding behaviorally important visual stimuli. Simulations with the cell-based model provide insights about the design of the Limulus eye and its encoding of the animal's visual world.

Circadian rhythms of rod-cone dominance in the Japanese quail retina

When the Japanese quail is held in constant darkness, retinal responses (ERG b-waves) increase during the animal's subjective night and decrease during its subjective day. Rod photoreceptors dominate the b-wave responses (lambdamax = 506 nm) to all stimulus intensities at night but only to those intensities below the cone threshold during the day. Above the cone threshold, cones dominate b-wave responses (lambdamax, approximately 550-600 nm) during the day regardless of the state of retinal adaptation. Apparently a circadian oscillator enables cone signals to block rod signals during the day but not at night. The ERG b-wave reflects the activity of bipolar cells that are postsynaptic to rods and cones. The ERG a-wave reflects the activity of both rods and cones. The amplitude of the isolated a-wave (PIII) changes with time of day, as does that of the b-wave, but its spectral sensitivity does not. The PIII responses are maximal at approximately 520 nm both day and night and may reflect multiple receptor mechanisms. The shift in rod-cone dominance detected with the ERG b-wave resembles the Purkinje shift of human vision but, unlike the Purkinje shift, does not require a change in ambient light intensity. The shift occurs in constant darkness, with a period of approximately 24 hr indicative of a circadian rhythm in the functional organization of the retina.

Circadian rhythms of rod-cone dominance in the Japanese quail retina

When the Japanese quail is held in constant darkness, retinal responses (ERG b-waves) increase during the animal's subjective night and decrease during its subjective day. Rod photoreceptors dominate the b-wave responses (lambdamax = 506 nm) to all stimulus intensities at night but only to those intensities below the cone threshold during the day. Above the cone threshold, cones dominate b-wave responses (lambdamax, approximately 550-600 nm) during the day regardless of the state of retinal adaptation. Apparently a circadian oscillator enables cone signals to block rod signals during the day but not at night. The ERG b-wave reflects the activity of bipolar cells that are postsynaptic to rods and cones. The ERG a-wave reflects the activity of both rods and cones. The amplitude of the isolated a-wave (PIII) changes with time of day, as does that of the b-wave, but its spectral sensitivity does not. The PIII responses are maximal at approximately 520 nm both day and night and may reflect multiple receptor mechanisms. The shift in rod-cone dominance detected with the ERG b-wave resembles the Purkinje shift of human vision but, unlike the Purkinje shift, does not require a change in ambient light intensity. The shift occurs in constant darkness, with a period of approximately 24 hr indicative of a circadian rhythm in the functional organization of the retina.