Multidimensional Sensorimotor Grounding of Concrete and Abstract Categories

Semantic categories, and the concepts belonging to them, have traditionally been defined by their relative concreteness; that is, their reliance on perception. However, sensorimotor grounding must be regarded as going beyond the basic five senses, and incorporate a multidimensional variety of perceptual and action experience. We present a series of exploratory analyses examining the sensorimotor grounding of participant-produced member concepts for 117 categories, spanning traditionally concrete (e.g., animal, furniture) and highly abstract (e.g., unit of time, science) categories. We found that both concrete and abstract categories are strongly grounded in multidimensional sensorimotor experience. Both domains were dominated by vision and, to a lesser extent, head movements, but concrete categories were more grounded in touch and hand/arm action, while abstract categories were more grounded in hearing and interoception. Importantly, this pattern of grounding was not uniform, and subdomains of concrete (e.g., ingestibles, animates, natural categories, artefacts) and abstract (e.g., internal, social, non-social) categories were grounded in different sensorimotor dimensions. Overall, these findings suggest that the distinction between abstract and concrete categories is not as clearcut as ontological assumptions might suggest, and that the strength and diversity of sensorimotor grounding in abstract categories must not be underestimated.

Changes in the Intelligence Levels and Structure in Russia: An ANOVA Method Based on Discretization and Grouping of Factors

In the present paper, we investigate how the general intelligence quotient (IQ) and its subtests changed for students from Russian University from 1991 to 2013. This study of the effect of such factors as gender, department, and year on the IQ response is carried out using the ANOVA model. Given the unevenness of the initial sample by years and departments, and consequently, heterogeneity of variances when divided by the original natural categories, we decided to aggregate the values of explanatory variables to build an adequate model. The paper proposes and investigates an algorithm for joint discretization and grouping, which uses the procedure of partial screening of solutions. It is an intermediate option between the greedy algorithm and exhaustive search. As a goodness function (an optimality criterion), we investigate 26 intermediate options between the AIC and BIC criteria. The BIC turned out to be the most informative and the most acceptable criterion for interpretation, which penalizes the complexity of the model, due to some decrease in accuracy. The resulting partition of the explanatory variables values into categories is used to interpret the modeling results and to arrive at the final conclusions of the data analysis. As a result, it is revealed that the observed features of the IQ dynamics are caused by changes in the education system and the socio-economic status of the family that occurred in Russia during the period of restructuring the society and intensive development of information technologies.

Rethinking Categories and Dimensions in the DSM

This paper addresses the role of categories and dimensions in the classification of psychopathology. While psychopathology does not sort itself out neatly into natural categories, we do find rough, symptom-based groupings that, through refinement, become diagnostic categories. Given that these categories suffer from comorbidity, uncertain boundaries, and excessive “unspecified disorder” diagnoses, there has been a move toward refining the diagnoses with dimensional measures. The paper traces efforts both to improve the diagnostic categories with validators that allow at least partial validity and to introduce dimensional measures into the diagnostic manual. Drawing from the philosophical pragmatism of Charles Sanders Peirce, William James, and John Dewey, which emphasizes the practical, effect-sensitive consequences of a theory along with an emphasis on empirical evidence and the progressive, probabilistic character of knowledge, the paper argues that these efforts must be guided both by scientific validity and clinical utility.

Visual Statistical Learning is Modulated by Arbitrary and Natural Categories

Visual Statistical Learning (VSL) describes the unintentional extraction of statistical regularities from visual environments across time or space, and is typically studied using novel stimuli (e.g., symbols unfamiliar to participants) and using familiarization procedures that are passive or require only basic vigilance. The natural visual world, however, is rich with a variety of complex visual stimuli, and we experience that world in the presence of goal-driven behavior including overt learning of other kinds. To examine how VSL responds to such contexts, we exposed subjects to statistical contingencies as they learned arbitrary categorical mappings of unfamiliar stimuli (fractals, experiment 1) or familiar stimuli with preexisting categorical boundaries (faces and scenes, experiment 2). In a familiarization stage, subjects learned by trial-and-error the arbitrary mappings between stimuli and one of two responses. Unbeknownst to participants, items were paired such that they always appeared together in the stream. Pairs were equally likely to be same- or different-category. In a pair recognition stage to assess VSL, subjects chose between a target pair and a foil pair. In both experiments, subjects’ VSL was shaped by arbitrary categories: same-category pairs were learned better than different-category pairs. Natural categories (Experiment 2) also played a role, with subjects learning same natural category pairs at higher rates than different-category pairs, an effect that did not interact with arbitrary mappings. We conclude that learning goals of the observer and pre-existing knowledge about the structure of the world play powerful roles in the incidental learning of novel statistical information.

Black-capped Chickadees (Poecile atricapillus) can identify individual females by their fee-bee songs

Individual recognition is a social behavior that occurs in many bird species. A bird’s ability to discriminate among familiar and unfamiliar conspecifics is critical to avoid wasting resources such as time and energy during social interactions. Black-capped Chickadees (Poecile atricapillus) are able to discriminate individual female and male chick-a-dee calls, potentially male and female tseet calls, and male fee-bee songs. In the current study, we used an operant discrimination go/no-go paradigm to determine whether female and male chickadees could discriminate between fee-bee songs produced by individual female chickadees as well as test which song component(s) enable this discrimination. Birds trained on natural categories—the songs of different females—learned to respond to rewarded stimuli more quickly than birds trained on random groupings of female songs and were able to transfer this learning to new songs from the same categories. Chickadees were also able to generalize their responding when exposed to the bee note of the fee-bee song of rewarded individuals; they did not generalize to fee notes. Our results provide evidence that Black-capped Chickadees can use female-produced fee-bee songs for individual recognition. However, the acoustic features underlying individual recognition require further investigation.

Immobility theory

The content of the manuscript represents a bold idea system, it is beyond the boundaries of all existing knowledge but the method of reasoning and logic is also very strict and scientific. The purpose of the manuscript is to unify the natural categories (natural philosophy, natural geometry, quantum mechanics, astronomy,…), and to open a new direction for most other sciences.The manuscript content focuses on the most basic foundations of nature, and has since drawn some great results that we rarely notice, such as:1. About Philosophy• Proved the existence of time and non-dilation.• Proved that matter is always motionless in space.• Conclusion that space is energy.• ...2. About Mathematics• Solved the squaring the circle problem(a millennium problem).• Using the equation to calculate speed of light is 471.000.000 m/s• ...3. About Physics• Explained the nature of gravity.• Explained dark energy, spin value of Nucleon• Explained matter and antimatter• ...

Hegel’s Critique of Greek Ethical Life

Hegel was attracted to the Greek ideal, but he ultimately rejected it as a model for the modern world. This article discusses four deficiencies he identified in ancient Greek ethical life: the immediate relationship between the subjective will of the individual and the ethical norms of the polis, the absence of institutions that mediated citizens’ private goals with the polis, the deficient conception of the human being which underlay slavery, and the granting of recognition on the basis of natural categories rather than politically integrative norms. These deficiencies explain not only why Hegel thought the Greek polis had to disintegrate under the onslaught of subjective particularity, but also why he rejected the Greek ideal as a model of social membership for modern ethical life. In addition, they illuminate his rejection of Fries and provide grounds for criticizing Rousseau. His account of the highly articulated modern state represents a response to the question of how the deficiencies of Greek ethical life can be overcome.

Integrating prediction errors at two time scales permits rapid recalibration of speech sound categories

Speech perception is assumed to arise from internal models of specific sensory features associated speech sounds. When these features change, the listener should recalibrate its internal model by appropriately weighing new versus old evidence in a volatility dependent manner. Models of speech recalibration have classically ignored volatility. Those that explicitly consider volatility have been designed to describe human behavior in tasks where sensory cues are associated with arbitrary experimenter-defined categories or rewards. In such settings, a model that maintains a single representation of the category but continuously adapts the learning rate works well. Using neurocomputational modelling we show that recalibration of existing “natural” categories is better described when sound categories are represented at different time scales. We illustrate our proposal by modeling the rapid recalibration of speech categories (Lüttke et al. 2016).