Chicks, like children, spontaneously reorient by three-dimensional environmental geometry, not by image matching

Spatial reorientation by layout geometry occurs in numerous species, but its underlying mechanisms are debated. While some argue that navigating animals' sense of place is based on geometric computations over three-dimensional representations, others claim it depends on panoramic image-matching processes. Because children reorient by subtle three-dimensional perturbations of the terrain and not by salient two-dimensional brightness contours on surfaces or freestanding columns, children's sense of place cannot be explained by image matching. To test image-matching theories in a different species, the present experiment investigates the reorientation performance of domestic chicks (Gallus gallus) in environments similar to those used with children. Chicks, like children, spontaneously reoriented by geometric relationships of subtle three-dimensional terrains, and not by salient two-dimensional brightness contours on surfaces or columns. These findings add to the evidence for homologous navigation systems in humans and other vertebrates, and they cast doubt on image-matching theories of reorientation in these species.     

Spatial reorientation by geometry in bumblebees

Human and non-human animals are capable of using basic geometric information to reorient in an environment. Geometric information includes metric properties associated with spatial surfaces (e.g., short vs. long wall) and left-right directionality or 'sense' (e.g. a long wall to the left of a short wall). However, it remains unclear whether geometric information is encoded by explicitly computing the layout of surface geometry or by matching images of the environment. View-based spatial encoding is generally thought to hold for insect navigation and, very recently, evidence for navigation by geometry has been reported in ants but only in a condition which does not allow the animals to use features located far from the goal. In this study we tested the spatial reorientation abilities of bumblebees (Bombus terrestris). After spatial disorientation, by passive rotation both clockwise and anticlockwise, bumblebees had to find one of the four exit holes located in the corners of a rectangular enclosure. Bumblebees systematically confused geometrically equivalent exit corners (i.e. corners with the same geometric arrangement of metric properties and sense, for example a short wall to the left of a long wall). However, when one wall of the enclosure was a different colour, bumblebees appeared to combine this featural information (either near or far from the goal) with geometric information to find the correct exit corner. Our results show that bumblebees are able to use both geometric and featural information to reorient themselves, even when features are located far from the goal.     

Size-Sensitive Perceptual Representations Underlie Visual and Haptic Object Recognition

A variety of similarities between visual and haptic object recognition suggests that the two modalities may share common representations. However, it is unclear whether such common representations preserve low-level perceptual features or whether transfer between vision and haptics is mediated by high-level, abstract representations. Two experiments used a sequential shape-matching task to examine the effects of size changes on unimodal and crossmodal visual and haptic object recognition. Participants felt or saw 3D plastic models of familiar objects. The two objects presented on a trial were either the same size or different sizes and were the same shape or different but similar shapes. Participants were told to ignore size changes and to match on shape alone. In Experiment 1, size changes on same-shape trials impaired performance similarly for both visual-to-visual and haptic-to-haptic shape matching. In Experiment 2, size changes impaired performance on both visual-to-haptic and haptic-to-visual shape matching and there was no interaction between the cost of size changes and direction of transfer. Together the unimodal and crossmodal matching results suggest that the same, size-specific perceptual representations underlie both visual and haptic object recognition, and indicate that crossmodal memory for objects must be at least partly based on common perceptual representations.     

FitEM2EM--tools for low resolution study of macromolecular assembly and dynamics

Studies of the structure and dynamics of macromolecular assemblies often involve comparison of low resolution models obtained using different techniques such as electron microscopy or atomic force microscopy. We present new computational tools for comparing (matching) and docking of low resolution structures, based on shape complementarity. The matched or docked objects are represented by three dimensional grids where the value of each grid point depends on its position with regard to the interior, surface or exterior of the object. The grids are correlated using fast Fourier transformations producing either matches of related objects or docking models depending on the details of the grid representations. The procedures incorporate thickening and smoothing of the surfaces of the objects which effectively compensates for differences in the resolution of the matched/docked objects, circumventing the need for resolution modification. The presented matching tool FitEM2EMin successfully fitted electron microscopy structures obtained at different resolutions, different conformers of the same structure and partial structures, ranking correct matches at the top in every case. The differences between the grid representations of the matched objects can be used to study conformation differences or to characterize the size and shape of substructures. The presented low-to-low docking tool FitEM2EMout ranked the expected models at the top.     

Principles of goal-directed spatial robot navigation in biomimetic models

Mobile robots and animals alike must effectively navigate their environments in order to achieve their goals. For animals goal-directed navigation facilitates finding food, seeking shelter or migration; similarly robots perform goal-directed navigation to find a charging station, get out of the rain or guide a person to a destination. This similarity in tasks extends to the environment as well; increasingly, mobile robots are operating in the same underwater, ground and aerial environments that animals do. Yet despite these similarities, goal-directed navigation research in robotics and biology has proceeded largely in parallel, linked only by a small amount of interdisciplinary research spanning both areas. Most state-of-the-art robotic navigation systems employ a range of sensors, world representations and navigation algorithms that seem far removed from what we know of how animals navigate; their navigation systems are shaped by key principles of navigation in ‘real-world’ environments including dealing with uncertainty in sensing, landmark observation and world modelling. By contrast, biomimetic animal navigation models produce plausible animal navigation behaviour in a range of laboratory experimental navigation paradigms, typically without addressing many of these robotic navigation principles. In this paper, we attempt to link robotics and biology by reviewing the current state of the art in conventional and biomimetic goal-directed navigation models, focusing on the key principles of goal-oriented robotic navigation and the extent to which these principles have been adapted by biomimetic navigation models and why.     

Learning and Exposure Affect Environmental Perception Less than Evolutionary Navigation Costs

Most behaviors are conditional upon successful navigation of the environment, which depends upon distance perception learned over repeated trials. Unfortunately, we understand little about how learning affects distance perception–especially in the most common human navigational scenario, that of adult navigation in familiar environments. Further, dominant theories predict mutually exclusive effects of learning on distance perception, especially when the risks or costs of navigation differ. We tested these competing predictions in four experiments in which we also presented evolutionarily relevant navigation costs. Methods included within- and between-subjects comparisons and longitudinal designs in laboratory and real-world settings. Data suggested that adult distance estimation rapidly reflects evolutionarily relevant navigation costs and repeated exposure does little to change this. Human distance perception may have evolved to reflect navigation costs quickly and reliably in order to provide a stable signal to other behaviors and with little regard for objective accuracy.     

Evolutionary foundations of number: spontaneous representation of numerical magnitudes by cotton-top tamarins

Although animals of many species have been shown to discriminate between visual-spatial arrays or auditory-temporal sequences based on numerosity, most of the evidence for numerosity discrimination derives from experiments involving extensive laboratory training. Under these conditions, animals' discrimination of two numerosities depends on their ratio and is independent of their absolute value. It is an open question whether any untrained non-human animal spontaneously represents number in this way, as do human children and adults. We present the results of familiarization-discrimination experiments on cotton-top tamarin monkeys (Saguinus oedipus) that provide evidence for numerosity discrimination in the absence of training. Presented with auditory stimuli (speech syllables) controlled for the continuous variables of sequence duration, item duration, inter-stimulus interval and overall energy, tamarins readily discriminated sequences of 4 versus 8, 4 versus 6, and 8 versus 12 syllables. By contrast, tamarins failed to discriminate sequences of 4 versus 5 and 8 versus 10 syllables, providing evidence that their numerosity discrimination is approximate and shows the ratio signature of numerosity discrimination in humans and trained non-human animals. These results provide strong support for the hypothesis that representations of large, approximate numerosity are evolutionarily ancient and spontaneously available to non-human animals.     

Detecting Memory and Structure in Human Navigation Patterns Using Markov Chain Models of Varying Order

One of the most frequently used models for understanding human navigation on the Web is the Markov chain model, where Web pages are represented as states and hyperlinks as probabilities of navigating from one page to another. Predominantly, human navigation on the Web has been thought to satisfy the memoryless Markov property stating that the next page a user visits only depends on her current page and not on previously visited ones. This idea has found its way in numerous applications such as Google''s PageRank algorithm and others. Recently, new studies suggested that human navigation may better be modeled using higher order Markov chain models, i.e., the next page depends on a longer history of past clicks. Yet, this finding is preliminary and does not account for the higher complexity of higher order Markov chain models which is why the memoryless model is still widely used. In this work we thoroughly present a diverse array of advanced inference methods for determining the appropriate Markov chain order. We highlight strengths and weaknesses of each method and apply them for investigating memory and structure of human navigation on the Web. Our experiments reveal that the complexity of higher order models grows faster than their utility, and thus we confirm that the memoryless model represents a quite practical model for human navigation on a page level. However, when we expand our analysis to a topical level, where we abstract away from specific page transitions to transitions between topics, we find that the memoryless assumption is violated and specific regularities can be observed. We report results from experiments with two types of navigational datasets (goal-oriented vs. free form) and observe interesting structural differences that make a strong argument for more contextual studies of human navigation in future work.     

Modality-independent coding of spatial layout in the human brain

In many nonhuman species, neural computations of navigational information such as position and orientation are not tied to a specific sensory modality [1, 2]. Rather, spatial signals are integrated from multiple input sources, likely leading to abstract representations of space. In contrast, the potential for abstract spatial representations in humans is not known, because most neuroscientific experiments on human navigation have focused exclusively on visual cues. Here, we tested the modality independence hypothesis with two functional magnetic resonance imaging (fMRI) experiments that characterized computations in regions implicated in processing spatial layout [3]. According to the hypothesis, such regions should be recruited for spatial computation of 3D geometric configuration, independent of a specific sensory modality. In support of this view, sighted participants showed strong activation of the parahippocampal place area (PPA) and the retrosplenial cortex (RSC) for visual and haptic exploration of information-matched scenes but not objects. Functional connectivity analyses suggested that these effects were not related to visual recoding, which was further supported by a similar preference for haptic scenes found with blind participants. Taken together, these findings establish the PPA/RSC network as critical in modality-independent spatial computations and provide important evidence for a theory of high-level abstract spatial information processing in the human brain.     

Calculating spatial statistics for velocity jump processes with experimentally observed reorientation parameters

Mathematical modelling of the directed movement of animals, microorganisms and cells is of great relevance in the fields of biology and medicine. Simple diffusive models of movement assume a random walk in the position, while more realistic models include the direction of movement by assuming a random walk in the velocity. These velocity jump processes, although more realistic, are much harder to analyse and an equation that describes the underlying spatial distribution only exists in one dimension. In this communication we set up a realistic reorientation model in two dimensions, where the mean turning angle is dependent on the previous direction of movement and bias is implicitly introduced in the probability distribution for the direction of movement. This model, and the associated reorientation parameters, is based on data from experiments on swimming microorganisms. Assuming a transport equation to describe the motion of a population of random walkers using a velocity jump process, together with this realistic reorientation model, we use a moment closure method to derive and solve a system of equations for the spatial statistics. These asymptotic equations are a very good match to simulated random walks for realistic parameter values.     

Stable panoramic views facilitate snap-shot like memories for spatial reorientation in homing pigeons

Following spatial disorientation, animals can reorient themselves by relying on geometric cues (metric and sense) specified both by the macroscopic surface layout of an enclosed space and prominent visual landmarks in arrays. Whether spatial reorientation in arrays of landmarks is based on explicit representation of the geometric cues is a matter of debate. Here we trained homing pigeons (Columba livia) to locate a food-reward in a rectangular array of four identical or differently coloured pipes provided with four openings, only one of which allowed the birds to have access to the reward. Pigeons were trained either with a stable or a variable position of the opening on pipes, so that they could view the array either from the same or a variable perspective. Explicit mapping of configural geometry would predict successful reorientation irrespective of access condition. In contrast, we found that a stable view of the array facilitated spatial learning in homing pigeons, likely through the formation of snapshot-like memories.     

Spatial reorientation by geometry with freestanding objects and extended surfaces: a unifying view

The macroscopic, three-dimensional surface layout geometry of an enclosure apparently provides a different contribution for spatial reorientation than the geometric cues associated with freestanding objects arranged in arrays with similar geometric shape. Here, we showed that a unitary spatial representation can account for the capability of animals to reorient both by extended surfaces and discrete objects in a small-scale spatial task. We trained domestic chicks to locate a food-reward from an opening on isolated cylinders arranged either in a geometrically uninformative (square-shaped) or informative (rectangular-shaped) arrays. The arrays were located centrally within a rectangular-shaped enclosure. Chicks trained to access the reward from a fixed position of openings proved able to reorient according to the geometric cues specified by the shape of the enclosure in all conditions. Chicks trained in a fixed position of opening with geometric cues provided both by the arena and the array proved able to reorient according to each shape separately. However, chicks trained to access the reward from a variable position of openings failed to reorient. The results suggest that the physical constrains associated with the presence of obstacles in a scene, rather than their apparent visual extension, are crucial for spatial reorientation.     

Vision as temporal trace

Most current models of human and animal vision assume that the processes of vision involve 2D (or even 3D) internal representations of the external world--an iconic representation. Within these models, recognition involves some form of lineal, areal or volumetric comparison of these internal representations (either learned or innate) with current sensory inputs. However, this view has recently come under criticism. In this paper, a neural model of vision is explored in which this iconic world view is replaced by a temporally ordered trace of (essentially) local features. The model employs hierarchical, recurrently linked, self-organizing topological maps.     

Molecular interactions in bacterial cellulose composites studied by 1D FT-IR and dynamic 2D FT-IR spectroscopy

Specific strain-induced orientation and interactions in three Acetobacter cellulose composites: cellulose (C), cellulose/pectin (CP) and cellulose/xyloglucan (CXG) were characterized by FT-IR and dynamic 2D FT-IR spectroscopies. On the molecular level, the reorientation of the cellulose fibrils occurred in the direction of the applied mechanical strain. The cellulose-network reorientation depends on the composition of the matrix, including the water content, which lubricates the motion of macromolecules in the network. At the submolecular level, dynamic 2D FT-IR data suggested that there was no interaction between cellulose and pectin in CP and that they responded independently to a small amplitude strain, while in CXG, cellulose and xyloglucan were uniformly strained along the sample length.     

Transitive inference in non-human animals: an empirical and theoretical analysis

Transitive inference has long been considered one of the hallmarks of human deductive reasoning. Recent reports of transitive-like behaviors in non-human animals have prompted a flourishing empirical and theoretical search for the mechanism(s) that may mediate this ability in non-humans. In this paper, I begin by describing the transitive inference tasks customarily used with non-human animals and then review the empirical findings. Transitive inference has been demonstrated in a wide variety of species, and the signature effects that usually accompany transitive inference in humans (the serial position effect and the symbolic distance effect) have also been found in non-humans. I then critically analyze the most prominent models of this ability in non-human animals. Some models are cognitive, proposing for instance that animals use the rules of formal logic or form mental representations of the premises to solve the task, others are based on associative mechanisms such as value transfer and reinforcement and non-reinforcement. Overall, I argue that the reinforcement-based models are in a much better empirical and theoretical position. Hence, transitive inference in non-human animals should be considered a property of reinforcement history rather than of inferential processes. I finalize by shedding some light on some promising lines of research.     

Sleep modulates the neural substrates of both spatial and contextual memory consolidation

It is known that sleep reshapes the neural representations that subtend the memories acquired while navigating in a virtual environment. However, navigation is not process-pure, as manifold learning components contribute to performance, notably the spatial and contextual memory constituents. In this context, it remains unclear whether post-training sleep globally promotes consolidation of all of the memory components embedded in virtual navigation, or rather favors the development of specific representations. Here, we investigated the effect of post-training sleep on the neural substrates of the consolidation of spatial and contextual memories acquired while navigating in a complex 3D, naturalistic virtual town. Using fMRI, we mapped regional cerebral activity during various tasks designed to tap either the spatial or the contextual memory component, or both, 72 h after encoding with or without sleep deprivation during the first post-training night. Behavioral performance was not dependent upon post-training sleep deprivation, neither in a natural setting that engages both spatial and contextual memory processes nor when looking more specifically at each of these memory representations. At the neuronal level however, analyses that focused on contextual memory revealed distinct correlations between performance and neuronal activity in frontal areas associated with recollection processes after post-training sleep, and in the parahippocampal gyrus associated with familiarity processes in sleep-deprived participants. Likewise, efficient spatial memory was associated with posterior cortical activity after sleep whereas it correlated with parahippocampal/medial temporal activity after sleep deprivation. Finally, variations in place-finding efficiency in a natural setting encompassing spatial and contextual elements were associated with caudate activity after post-training sleep, suggesting the automation of navigation. These data indicate that post-training sleep modulates the neural substrates of the consolidation of both the spatial and contextual memories acquired during virtual navigation.     

Fast projection matching for cryo-electron microscopy image reconstruction

A new FFT-accelerated projection matching method is presented and tested. The electron microscopy images are represented by their Fourier-Bessel transforms and the 3D model by its expansion in spherical harmonics, or more specifically in terms of symmetry-adapted functions. The rotational and translational properties of these representations are used to quickly access all the possible 2D projections of the 3D model, which allow an exhaustive inspection of the whole five-dimensional domain of parameters associated to each particle.     

The effect of Hamming distances in a computational model of selection by consequences

McDowell (2004) instantiated the Darwinian principles of selection, recombination, and mutation in a computational model of selection by consequences. The model has been tested under a variety of conditions and the outcome is quantitatively indistinguishable from that displayed by live organisms. The computational model animates a virtual organism with a repertoire of 100 behaviors, selected from the integers from 0 to 1023, where the corresponding binary representations constitute the behavior's genotypes. Using strings of binary digits raises the specific problem of Hamming distances: the number of bits that must be changed from 1 to 0 or from 0 to 1 in order to obtain another string of equal length. McDowell hypothesized that the Hamming distance may be computationally equivalent to the changeover delay used in experiments with live organisms. The results of the present experiments confirmed this hypothesis and revealed a robust rule about the effects of Hamming distances within the model, namely, in order to obtain good matching, the difference between the Hamming distance that separates the target classes and the largest Hamming distance comprised within a class must be equal to or larger than three.     

Distance and shape: perception of the 3-dimensional world by weakly electric fish.

Weakly electric fish orient at night in complete darkness by employing their active electrolocation system. They emit short electric signals and perceive the consequences of these emissions with epidermal electroreceptors. Objects are detected by analyzing the electric images which they project onto the animal's electroreceptive skin surface. This process corresponds to similar processes during vision, where visual images are cast onto the retinas of eyes. Behavioral experiments have shown that electric fish can measure the distance of objects during active electrolocation, thus possessing three-dimensional depth perception of their surroundings. The fundamental mechanism for distance determination differs from stereopsis used during vision by two-eyed animals, but resembles some supplementary mechanisms for distance deduction in humans. Weakly electric fish can also perceive the three-dimensional shape of objects. The fish can learn to identify certain objects and discriminate them from all other objects. In addition, they spontaneously categorize objects according to their shapes and not according to object size or material properties. There is good evidence that some fundamental types of perceptional invariances during visual object recognition in humans are also found in electric fish during active electrolocation. These include size invariance (maybe including size constancy), rotational invariance, and translational invariance. The mechanisms of shape detection during electrolocation are still unknown, and their discoveries require additional experiments.