Using the freedom of design that metamaterials provide, we show how electromagnetic fields can be redirected at will and propose a design strategy. The conserved fields-electric displacement field D, magnetic induction field B, and Poynting vector B-are all displaced in a consistent manner. A simple illustration is given of the cloaking of a proscribed volume of space to exclude completely all electromagnetic fields. Our work has relevance to exotic lens design and to the cloaking of objects from electromagnetic fields.

/pdf/controlling-electromagnetic-fields-3ryxkryf1t.pdf

Controlling Electromagnetic Fields

We describe a model of visual processing in which feedback connections from a higher- to a lower- order visual cortical area carry predictions of lower-level neural activities, whereas the feedforward connections carry the residual errors between the predictions and the actual lower-level activities. When exposed to natural images, a hierarchical network of model neurons implementing such a model developed simple-cell-like receptive fields. A subset of neurons responsible for carrying the residual errors showed endstopping and other extra-classical receptive-field effects. These results suggest that rather than being exclusively feedforward phenomena, nonclassical surround effects in the visual cortex may also result from cortico-cortical feedback as a consequence of the visual system using an efficient hierarchical strategy for encoding natural images.

Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects.

Recently, artificially constructed metamaterials have become of considerable interest, because these materials can exhibit electromagnetic characteristics unlike those of any conventional materials. Artificial magnetism and negative refractive index are two specific types of behavior that have been demonstrated over the past few years, illustrating the new physics and new applications possible when we expand our view as to what constitutes a material. In this review, we describe recent advances in metamaterials research and discuss the potential that these materials may hold for realizing new and seemingly exotic electromagnetic phenomena.

/pdf/metamaterials-and-negative-refractive-index-5ehczes1hu.pdf

Metamaterials and negative refractive index.

Brains, it has recently been argued, are essentially prediction machines. They are bundles of cells that support perception and action by constantly attempting to match incoming sensory inputs with top-down expectations or predictions. This is achieved using a hierarchical generative model that aims to minimize prediction error within a bidirectional cascade of cortical processing. Such accounts offer a unifying model of perception and action, illuminate the functional role of attention, and may neatly capture the special contribution of cortical processing to adaptive success. This target article critically examines this "hierarchical prediction machine" approach, concluding that it offers the best clue yet to the shape of a unified science of mind and action. Sections 1 and 2 lay out the key elements and implications of the approach. Section 3 explores a variety of pitfalls and challenges, spanning the evidential, the methodological, and the more properly conceptual. The paper ends (sections 4 and 5) by asking how such approaches might impact our more general vision of mind, experience, and agency.

/pdf/whatever-next-predictive-brains-situated-agents-and-the-epj56cs868.pdf

Whatever next? Predictive brains, situated agents, and the future of cognitive science

From the Publisher: 
The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

Interneurons exhibiting centre--surround antagonism within their receptive fields are commonly found in peripheral visual pathways. We propose that this organization enables the visual system to encode spatial detail in a manner that minimizes the deleterious effects of intrinsic noise, by exploiting the spatial correlation that exists within natural scenes. The antagonistic surround takes a weighted mean of the signals in neighbouring receptors to generate a statistical prediction of the signal at the centre. The predicted value is subtracted from the actual centre signal, thus minimizing the range of outputs transmitted by the centre. In this way the entire dynamic range of the interneuron can be devoted to encoding a small range of intensities, thus rendering fine detail detectable against intrinsic noise injected at later stages in processing. This predictive encoding scheme also reduces spatial redundancy, thereby enabling the array of interneurons to transmit a larger number of distinguishable images, taking into account the expected structure of the visual world. The profile of the required inhibitory field is derived from statistical estimation theory. This profile depends strongly upon the signal: noise ratio and weakly upon the extent of lateral spatial correlation. The receptive fields that are quantitatively predicted by the theory resemble those of X-type retinal ganglion cells and show that the inhibitory surround should become weaker and more diffuse at low intensities. The latter property is unequivocally demonstrated in the first-order interneurons of the fly's compound eye. The theory is extended to the time domain to account for the phasic responses of fly interneurons. These comparisons suggest that, in the early stages of processing, the visual system is concerned primarily with coding the visual image to protect against subsequent intrinsic noise, rather than with reconstructing the scene or extracting specific features from it. The treatment emphasizes that a neuron's dynamic range should be matched to both its receptive field and the statistical properties of the visual pattern expected within this field. Finally, the analysis is synthetic because it is an extension of the background suppression hypothesis (Barlow & Levick 1976), satisfies the redundancy reduction hypothesis (Barlow 1961 a, b) and is equivalent to deblurring under certain conditions (Ratliff 1965).

Predictive Coding: A Fresh View of Inhibition in the Retina

Recent research has uncovered a number of different ways in which bees use cues derived from optic flow for navigational purposes. The distance flown to a food source is gauged by integrating the apparent motion of the visual world that is experienced en route. In other words, bees possess a visually driven 'odometer' that is robust to variations in wind load and energy expenditure. Bees flying through a tunnel maintain equidistance to the flanking walls by balancing the apparent speeds of the images of the walls. This strategy enables them to negotiate narrow passages or to fly between obstacles. The speed of flight in a tunnel is controlled by holding constant the average image velocity as seen by the two eyes. This avoids potential collisions by ensuring that the bee slows down when flying through narrow passages. Bees landing on a horizontal surface hold constant the image velocity of the surface as they approach it. This automatically ensures that flight speed decreases with altitude and is close to zero at touchdown. The movement-sensitive mechanisms underlying these various behaviours seem to be different, qualitatively as well as quantitatively, from those mediating the well-investigated optomotor response.

https://espace.library.uq.edu.au/view/UQ:696285/UQ696285_OA.pdf

Honeybee navigation en route to the goal: visual flight control and odometry

Insects process and learn information flexibly to adapt to their environment. The honeybee Apis mellifera constitutes a traditional model for studying learning and memory at behavioural, cellular and molecular levels. Earlier studies focused on elementary associative and non-associative forms of learning determined by either olfactory conditioning of the proboscis extension reflex or the learning of visual stimuli in an operant context. However, research has indicated that bees are capable of cognitive performances that were thought to occur only in some vertebrate species. For example, honeybees can interpolate visual information, exhibit associative recall, categorize visual information and learn contextual information. Here we show that honeybees can form 'sameness' and 'difference' concepts. They learn to solve 'delayed matching-to-sample' tasks, in which they are required to respond to a matching stimulus, and 'delayed non-matching-to-sample' tasks, in which they are required to respond to a different stimulus; they can also transfer the learned rules to new stimuli of the same or a different sensory modality. Thus, not only can bees learn specific objects and their physical parameters, but they can also master abstract inter-relationships, such as sameness and difference.

The concepts of ‘sameness’ and ‘difference’ in an insect

1.

If a homing ant (Cataglyphis bicolor,C. albicans) gets lost, it does not perform a random walk but adopts a stereotyped search strategy. During its search the ant performs a number of loops of ever-increasing size, starting and ending at the origin and pointing at different azimuthal directions. This strategy ensures that the centre area where the nest is most likely to be, is investigated most extensively.




2.

After one hour of continuous search the ant's search paths cover an area of about 104 m2. Nevertheless, the system of loops performed during this time is precisely centred around the origin. The ant's searching density does not depend on the azimuthal direction around the origin but only on the distance from the origin. It rapidly decreases with increasing distance.




3.

The ant's searching pattern can be characterized by two functions: thed/t-function correlating distance (d) with time (t), and theα/t-function correlating azimuthal direction (α) with time. If fixes of the ant's position are taken every 10 s, the vectors pointing from the origin to successive fixes change their lengthsd systematically (α/t-function) and their directionsα randomly (α/t-function). What is especially characteristic of the ant's searching pattern is the oscillatingd/t-function which clearly demonstrates that the searching ant repeatedly returns to the origin, even after it has walked, within one hour, along a search trajectory of more than 1 km (the latter number refers toC. albicans-A). The ant's walking speed does not change within a search time of 1 h.




4.

The distribution of changes in direction between successive segments of a search path,β, is usually unimodal with a mean of 0°, if complete search paths are considered. Nevertheless, within smaller periods of time, especially during the initial portions of the search the integrated angleβ may continuously change in the same direction. Such portions of the search crudely resemble a spiral which alternately expands and contracts.




5.

Although all 3 species ofCataglyphis studied in this paper adopt the same general search strategy, there are some differences in the fine structure of the search:C. albicans-A departs further from the origin than any other species, and performs the most rapid turns. The tendency towards spiralling is most pronounced inC. albicans-B.




6.

An efficient searching strategy is formulated, based on purely theoretical grounds. It is assumed that when the search begins the probability density function (PDF) for the location of the nest is Gaussian in two dimensions (a priori PDF). It is further assumed that the ant can never becompletely certain that a given area has been fully explored, so that it is only theprobability of encountering the nest within a certain region that decreases as the time spent in searching this region increases. Thus, the most promising region to search is specified by an a posteriori PDF which takes the ant's past performance into account.




7.

A computer model is presented that searches in optimum fashion, as proposed above. In the model, motion of the ant is characterized in terms of radial and tangential components, with the tangential component varying randomly and the radial component varying according to the a posteriori PDF. The model successfully describes what the ants are actually doing (e.g., compare Figs. 17 and 18 with Fig. 3, Figs. 19 and 20 with Figs. 8–10, and Fig. 21a and b with Figs. 4 and 5), indicating that the searching behaviour ofCataglyphis is geared to find the nest as quickly as possible.

Searching behaviour of desert ants, genusCataglyphis (Formicidae, Hymenoptera)

When negotiating a narrow gap, honeybees tend to fly through the middle of the gap, balancing the distances to the boundary on either side. To investigate the basis of this “centering response,” bees were trained to fly through a tunnel on their way to a feeding site and back, while their flight trajectories were filmed from above. The wall on either side carried a visual pattern. When the patterns were stationary vertical gratings, bees tended to fly through the middle of the tunnel, i.e. along its longitudinal axis. However, when one of the gratings was in motion, bees flying in the same direction as the moving grating tended to fly closer to while bees flying in the opposite direction tended to fly closer to the stationary grating. This demonstrates, directly and unequivocally, that flying bees estimate the distances of surfaces in terms of the apparent motion of their images. A series of further experiments revealed that the distance to the gratings is gauged in terms of their apparent angular speeds, and that the visual system of the bee is capable of measuring angular speed largely independently of the spatial period, intensity profile, or contrast of the grating. Thus, the motion-sensitive mechanisms mediating range perception appear to be qualitatively different from those that mediate the well-known optomotor response in insects, or those involved in motion detection and ocular tracking in man.

/pdf/range-perception-through-apparent-image-speed-in-freely-nv8t2tp94k.pdf

Mandyam V. Srinivasan

Papers

Predictive Coding: A Fresh View of Inhibition in the Retina

Honeybee navigation en route to the goal: visual flight control and odometry

The concepts of ‘sameness’ and ‘difference’ in an insect

Searching behaviour of desert ants, genusCataglyphis (Formicidae, Hymenoptera)

Range perception through apparent image speed in freely flying honeybees.