Unusual links between inherent and apparent optical properties in shallow lakes,the case of Taihu Lake

The spectral distribution of downwelling solar irradiance is an important factor in the radiative balance, primary productivity and biogeochemistry in most lakes. In the present study, we show the relative importance of different inherent and apparent optical properties in controlling the spectral attenuation of diffuse downwelling irradiance in a large shallow lake in eastern China. Most importantly, we show how elevated concentrations of suspended matter not only increase attenuation, but are linked to a “spectral shift” in major attenuation peaks, with important consequences on biogeochemical processes and remote sensing. The analysis of the lake optical properties in relation to the geographical distribution of submerged macrophytes indicates how heterogenic optical conditions play a role in controlling benthic primary production.     

A role of synchronicity of neural activity based on dynamic plasticity of synapses in encoding spatiotemporal features of electrosensory stimuli

It is quite important for investigation of sensory mechanism to understand how dynamical property of neurons is used for encoding the feature of spatiotemporally varying stimuli. To consider concretely the problem, we focus our study on electrosensory system of a weakly electric fish. Weakly electric fish generate electric field around their body using electric organ discharge (EOD) and accurately detect the location of an object through the modulation of electric field induced by the object. We made a neural network model of electrosensory lateral-line lobe (ELL). Here we show that the features of EOD modulation depending specifically distance and size of an object are encoded into the timing of burst firing of ELL neurons. These features can be represented by the spatial area of synchronous burst firing and the interburst interval in the ELL network. We show that short-term changes of excitatory and inhibitory synapses, induced by efferent signals, regulate the ELL activity so as to effectively encode the features of EOD modulation.     

Burnout: From Popular Culture to Psychiatric Diagnosis in Sweden

This article aims to understand how burn-out became an object of thought, through the study of certain processes of legitimization. It traces the genealogy of the burn-out concept from the initial article from 1974, via its confirmation as a “disease” in the 1980s, to its appearance as a legitimate diagnosis in Sweden in 1997. The theoretical framework is that of applied metaphysics, which means a study on how a specific phenomenon came into being. Consequently, I take departure from ontology in motion with an approach that concerns the legitimization processes. The conclusion will show the underlying processes of legitimization in relation to the making of a psychiatric object of thought in Swedish society.     

Lipari–Szabo mapping: A graphical approach to Lipari–Szabo analysis of NMR relaxation data using reduced spectral density mapping

In this paper, we explore connections between the Lipari–Szabo formalism and reduced spectral density mapping, and show how spectral density estimates can be associated with Lipari–Szabo parameters via a simple geometric construction which we call Lipari–Szabo mapping. This relationship can be used to estimate Lipari–Szabo parameters from spectral density estimates without the need for nonlinear optimization, and to perform `model selection' in a graphical manner. The Lipari–Szabo map also provides insight into the Lipari–Szabo model, and allows us to determine when a given set of experimental spectral densities are inconsistent with the Lipari–Szabo formalism. Practical applications of Lipari–Szabo mapping in conjunction with more traditional analysis methods are discussed.     

From Sensory Signals to Modality-Independent Conceptual Representations: A Probabilistic Language of Thought Approach

People learn modality-independent, conceptual representations from modality-specific sensory signals. Here, we hypothesize that any system that accomplishes this feat will include three components: a representational language for characterizing modality-independent representations, a set of sensory-specific forward models for mapping from modality-independent representations to sensory signals, and an inference algorithm for inverting forward models—that is, an algorithm for using sensory signals to infer modality-independent representations. To evaluate this hypothesis, we instantiate it in the form of a computational model that learns object shape representations from visual and/or haptic signals. The model uses a probabilistic grammar to characterize modality-independent representations of object shape, uses a computer graphics toolkit and a human hand simulator to map from object representations to visual and haptic features, respectively, and uses a Bayesian inference algorithm to infer modality-independent object representations from visual and/or haptic signals. Simulation results show that the model infers identical object representations when an object is viewed, grasped, or both. That is, the model’s percepts are modality invariant. We also report the results of an experiment in which different subjects rated the similarity of pairs of objects in different sensory conditions, and show that the model provides a very accurate account of subjects’ ratings. Conceptually, this research significantly contributes to our understanding of modality invariance, an important type of perceptual constancy, by demonstrating how modality-independent representations can be acquired and used. Methodologically, it provides an important contribution to cognitive modeling, particularly an emerging probabilistic language-of-thought approach, by showing how symbolic and statistical approaches can be combined in order to understand aspects of human perception.     

Animal colour vision--behavioural tests and physiological concepts

Over a century ago workers such as J. Lubbock and K. von Frisch developed behavioural criteria for establishing that non‐human animals see colour. Many animals in most phyla have since then been shown to have colour vision. Colour is used for specific behaviours, such as phototaxis and object recognition, while other behaviours such as motion detection are colour blind. Having established the existence of colour vision, research focussed on the question of how many spectral types of photoreceptors are involved. Recently, data on photoreceptor spectral sensitivities have been combined with behavioural experiments and physiological models to study systematically the next logical question: ‘what neural interactions underlie colour vision ?‘This review gives an overview of the methods used to study animal colour vision, and discusses how quantitative modelling can suggest how photoreceptor signals are combined and compared to allow for the discrimination of biologically relevant stimuli.     

The Psychology of Art

Eisenstein begins his article with the basic problem of all forms of art: how is theme or content changed from an object of reality into an object of art and what is the secret of the method of art? The rest of his presentation gives examples of different art forms to show how reality is transformed into art. Cinema has a special status among arts because best films “are larger than life.”     

Visual perception of rigidity of solid shape

Summary Organisms react to objective properties of bodies in their visual field instead of to the perpetually changing retinal images of those bodies. We show how such a faculty can be mechanized. The organism synthesizes an internal model of the external object, that is a bundle of expectations of how the visual input will transform in response to the organism's exploratory movements. We deduce the necessary structure of the internal model and we show how the organism can extract this structure from the invariant features of the sensory input transformations. With this internal model it is possible to predict the subsequent aspects (contours) of the visual object as the spatial relations of organism and object change.     

Electromechanical model for object roughness perception during finger sliding

Touch allows us to gather abundant information in the world around us. However, how sensory cells embedded in the fingers convey texture information into their firing patterns is still poorly understood. Here, we develop an electromechanical model for roughness perception by incorporating main ingredients such as voltage-gated ion channels, active ion pumps, mechanosensitive channels, and cell deformation. The model reveals that sensory cells can convey texture wavelengths into the period of their firing patterns as the finger slides across object surfaces, but they can only convey a limited range of texture wavelengths. We also show that an increase in sliding speed broadens the decoding wavelength range at the cost of reduction of lower perception limits. Thus, a smaller sliding speed and a bigger contact force may be needed to successfully discern a smooth surface, consistent with previous psychophysical observations. Moreover, we show that cells with slowly adapting mechanosensitive channels can still fire action potentials under static loadings, indicating that slowly adapting mechanosensitive channels may contribute to the perception of coarse textures under static touch. Our work thus provides a new theoretical framework to study roughness perception and may have important implications for the design of electronic skin, artificial touch, and haptic interfaces.     

On the spectral formulation of Granger causality

Spectral measures of causality are used to explore the role of different rhythms in the causal connectivity between brain regions. We study several spectral measures related to Granger causality, comprising the bivariate and conditional Geweke measures, the directed transfer function, and the partial directed coherence. We derive the formulation of dependence and causality in the spectral domain from the more general formulation in the information-theory framework. We argue that the transfer entropy, the most general measure derived from the concept of Granger causality, lacks a spectral representation in terms of only the processes associated with the recorded signals. For all the spectral measures we show how they are related to mutual information rates when explicitly considering the parametric autoregressive representation of the processes. In this way we express the conditional Geweke spectral measure in terms of a multiple coherence involving innovation variables inherent to the autoregressive representation. We also link partial directed coherence with Sims' criterion of causality. Given our results, we discuss the causal interpretation of the spectral measures related to Granger causality and stress the necessity to explicitly consider their specific formulation based on modeling the signals as linear Gaussian stationary autoregressive processes.     

Spatiotemporal burst coding for extracting features of spatiotemporally varying stimuli

Encoding features of spatiotemporally varying stimuli is quite important for understanding the neural mechanisms of various sensory coding. Temporal coding can encode features of time-varying stimulus, and population coding with temporal coding is adequate for encoding spatiotemporal correlation of stimulus features into spatiotemporal activity of neurons. However, little is known about how spatiotemporal features of stimulus are encoded by spatiotemporal property of neural activity. To address this issue, we propose here a population coding with burst spikes, called here spatiotemporal burst (STB) coding. In STB coding, the temporal variation of stimuli is encoded by the precise onset timing of burst spike, and the spatiotemporal correlation of stimuli is emphasized by one specific aspect of burst firing, or spike packet followed by silent interval. To show concretely the role of STB coding, we study the electrosensory system of a weakly electric fish. Weakly electric fish must perceive the information about an object nearby by analyzing spatiotemporal modulations of electric field around it. On the basis of well-characterized circuitry, we constructed a neural network model of the electrosensory system. Here we show that STB coding encodes well the information of object distance and size by extracting the spatiotemporal correlation of the distorted electric field. The burst activity of electrosensory neurons is also affected by feedback signals through synaptic plasticity. We show that the control of burst activity caused by the synaptic plasticity leads to extracting the stimulus features depending on the stimulus context. Our results suggest that sensory systems use burst spikes as a unit of sensory coding in order to extract spatiotemporal features of stimuli from spatially distributed stimuli.     

Flexible representations of dynamics are used in object manipulation

To manipulate an object skillfully, the brain must learn its dynamics, specifying the mapping between applied force and motion. A fundamental issue in sensorimotor control is whether such dynamics are represented in an extrinsic frame of reference tied to the object or an intrinsic frame of reference linked to the arm. Although previous studies have suggested that objects are represented in arm-centered coordinates [1-6], all of these studies have used objects with unusual and complex dynamics. Thus, it is not known how objects with natural dynamics are represented. Here we show that objects with simple (or familiar) dynamics and those with complex (or unfamiliar) dynamics are represented in object- and arm-centered coordinates, respectively. We also show that objects with simple dynamics are represented with an intermediate coordinate frame when vision of the object is removed. These results indicate that object dynamics can be flexibly represented in different coordinate frames by the brain. We suggest that with experience, the representation of the dynamics of a manipulated object may shift from a coordinate frame tied to the arm toward one that is linked to the object. The additional complexity required to represent dynamics in object-centered coordinates would be economical for familiar objects because such a representation allows object use regardless of the orientation of the object in hand.     

Using hardware models to quantify sensory data acquisition across the rat vibrissal array

Our laboratory investigates how animals acquire sensory data to understand the neural computations that permit complex sensorimotor behaviors. We use the rat whisker system as a model to study active tactile sensing; our aim is to quantitatively describe the spatiotemporal structure of incoming sensory information to place constraints on subsequent neural encoding and processing. In the first part of this paper we describe the steps in the development of a hardware model (a 'sensobot') of the rat whisker array that can perform object feature extraction. We show how this model provides insights into the neurophysiology and behavior of the real animal. In the second part of this paper, we suggest that sensory data acquisition across the whisker array can be quantified using the complete derivative. We use the example of wall-following behavior to illustrate that computing the appropriate spatial gradients across a sensor array would enable an animal or mobile robot to predict the sensory data that will be acquired at the next time step.     

Depth perception in disparity-defined objects: finding the balance between averaging and segregation

Deciding what constitutes an object, and what background, is an essential task for the visual system. This presents a conundrum: averaging over the visual scene is required to obtain a precise signal for object segregation, but segregation is required to define the region over which averaging should take place. Depth, obtained via binocular disparity (the differences between two eyes’ views), could help with segregation by enabling identification of object and background via differences in depth. Here, we explore depth perception in disparity-defined objects. We show that a simple object segregation rule, followed by averaging over that segregated area, can account for depth estimation errors. To do this, we compared objects with smoothly varying depth edges to those with sharp depth edges, and found that perceived peak depth was reduced for the former. A computational model used a rule based on object shape to segregate and average over a central portion of the object, and was able to emulate the reduction in perceived depth. We also demonstrated that the segregated area is not predefined but is dependent on the object shape. We discuss how this segregation strategy could be employed by animals seeking to deter binocular predators.This article is part of the themed issue ‘Vision in our three-dimensional world’.     

Fragment-based learning of visual object categories

When we perceive a visual object, we implicitly or explicitly associate it with a category we know. It is known that the visual system can use local, informative image fragments of a given object, rather than the whole object, to classify it into a familiar category. How we acquire informative fragments has remained unclear. Here, we show that human observers acquire informative fragments during the initial learning of categories. We created new, but naturalistic, classes of visual objects by using a novel "virtual phylogenesis" (VP) algorithm that simulates key aspects of how biological categories evolve. Subjects were trained to distinguish two of these classes by using whole exemplar objects, not fragments. We hypothesized that if the visual system learns informative object fragments during category learning, then subjects must be able to perform the newly learned categorization by using only the fragments as opposed to whole objects. We found that subjects were able to successfully perform the classification task by using each of the informative fragments by itself, but not by using any of the comparable, but uninformative, fragments. Our results not only reveal that novel categories can be learned by discovering informative fragments but also introduce and illustrate the use of VP as a versatile tool for category-learning research.     

Atomic structure of a single large biomolecule from diffraction patterns of random orientations

The short and intense pulses of the new X-ray free electron lasers, now operational or under construction, may make possible diffraction experiments on single molecule-sized objects with high resolution, before radiation damage destroys the sample. In a single molecule imaging (SMI) experiment thousands of diffraction patterns of single molecules with random orientations are recorded. One of the most challenging problems of SMI is how to assemble these noisy patterns of unknown orientations into a consistent single set of diffraction data. Here we present a new method which can solve the orientation problem of SMI efficiently even for large biological molecules and in the presence of noise. We show on simulated diffraction patterns of a large protein molecule, how the orientations of the patterns can be found and the structure to atomic resolution can be solved. The concept of our algorithm could be also applied to experiments where images of an object are recorded in unknown orientations and/or positions like in cryoEM or tomography.     

Motor control of downward object-transport movements with precision grip by object weight

In the present study, we investigated the kinematics of object-transport movement in a downward direction using a precision grip, to elucidate how the central nervous system (CNS) takes into account object weight when making the movement, even when participants are unable to recognize the weight until they grasp the object. We found that the kinematics during transport movement were significantly changed by the object weight, even when the weight was unrecognized visually, suggesting that the CNS controls object-transport movement in a downward direction according to object weight, regardless of the visual recognizability of the weight.     

Location-specific Responsiveness to Environmental Perturbations in Wedge-capped Capuchins (Cebus olivaceus)

We recorded the responses of the members of a captive group of wedge-capped capuchins to novel and familiar objects placed in different parts of their cage in a study of the spatial dependency of activity with objects. We focused on behavioral pattern variability across subjects and across object location. Results show that, according to the location of the object, a great deal of within-subject response variability exists. The dominant male was slow to interact physically with objects and presented social-like behaviors—essentially grooming—towards objects in only one site. Implicit to the ethological approach is the assumption that consistent spatial location is irrelevant or, at best, of little importance to the definition of stimuli. Nevertheless, stimuli would be best considered as perturbations insofar as the significance of an object or event depends on where and when it is encountered. In order to evaluate how monkey cognition operates, it seems essential to investigate the role of the primate's own spatial structure. As a working hypothesis, we introduce the processes of spatial facilitation and inhibition and suggest that they affect how an individual interacts with objects and events.     

Principal component analysis of dynamic relative displacement fields estimated from MR images

Non-destructive measurement of acceleration-induced displacement fields within a closed object is a fundamental challenge. Inferences of how the brain deforms following skull impact have thus relied largely on indirect estimates and course-resolution cadaver studies. We developed a magnetic resonance technique to quantitatively identify the modes of displacement of an accelerating soft object relative to an object enclosing it, and applied it to study acceleration-induced brain deformation in human volunteers. We show that, contrary to the prevailing hypotheses of the field, the dominant mode of interaction between the brain and skull in mild head acceleration is one of sliding arrested by meninges.