Evidence that accent is a dimension of social categorization,not a byproduct of perceptual salience,familiarity, or ease-of-processing

Certain features of language, such as accent, are acquired from the local social environment during an acquisition period starting at infancy and ending roughly at puberty. If the scale of social interaction expands after puberty, humans will encounter variance in these linguistic features, and the linguistic similarity between people will indicate the degree to which they share a common early social history. There is reason to believe that such a dynamic is not a modern phenomenon, but has likely occurred throughout our species’ evolutionary history since the advent of language. Consequently, the human mind may contain systems for categorizing others according to their linguistic repertoires, including their accents. Four studies demonstrate that (i) accent differences—both native versus non-native accents and also two different non-native accents‚ are the basis of spontaneous and implicit social categorization, and (ii) this is not driven by general acoustic-differences, low level sound differences, or differences in familiarity or ease-of-processing. Results are consistent with the hypothesis that human mind contains systems for categorizing others according to their accents.     

From perceptual to language-mediated categorization

From at least two months onwards, infants can form perceptual categories. During the first year of life, object knowledge develops from the ability to represent individual object features to representing correlations between attributes and to integrate information from different sources. At the end of the first year, these representations are shaped by labels, opening the way to conceptual knowledge. Here, we review the development of object knowledge and object categorization over the first year of life. We then present an artificial neural network model that models the transition from early perceptual categorization to categories mediated by labels. The model informs a current debate on the role of labels in object categorization by suggesting that although labels do not act as object features they nevertheless affect perceived similarity of perceptually distinct objects sharing the same label. The model presents the first step of an integrated account from early perceptual categorization to language-based concept learning.     

A neural representation of categorization uncertainty in the human brain

The ability to classify visual objects into discrete categories ("friend" versus "foe"; "edible" versus "poisonous") is essential for survival and is a fundamental cognitive function. The cortical substrates that mediate this function, however, have not been identified in humans. To identify brain regions involved in stimulus categorization, we developed a task in which subjects classified stimuli according to a variable categorical boundary. Psychophysical functions were used to define a decision variable, categorization uncertainty, which was systematically manipulated. Using event-related functional MRI, we discovered that activity in a fronto-striatal-thalamic network, consisting of the medial frontal gyrus, anterior insula, ventral striatum, and dorsomedial thalamus, was modulated by categorization uncertainty. We found this network to be distinct from the frontoparietal attention network, consisting of the frontal and parietal eye fields, where activity was not correlated with categorization uncertainty.     

Looking the part: social status cues shape race perception

It is commonly believed that race is perceived through another's facial features, such as skin color. In the present research, we demonstrate that cues to social status that often surround a face systematically change the perception of its race. Participants categorized the race of faces that varied along White-Black morph continua and that were presented with high-status or low-status attire. Low-status attire increased the likelihood of categorization as Black, whereas high-status attire increased the likelihood of categorization as White; and this influence grew stronger as race became more ambiguous (Experiment 1). When faces with high-status attire were categorized as Black or faces with low-status attire were categorized as White, participants' hand movements nevertheless revealed a simultaneous attraction to select the other race-category response (stereotypically tied to the status cue) before arriving at a final categorization. Further, this attraction effect grew as race became more ambiguous (Experiment 2). Computational simulations then demonstrated that these effects may be accounted for by a neurally plausible person categorization system, in which contextual cues come to trigger stereotypes that in turn influence race perception. Together, the findings show how stereotypes interact with physical cues to shape person categorization, and suggest that social and contextual factors guide the perception of race.     

Colour categorization by domestic chicks

Spectral stimuli form a physical continuum, which humans divide into discrete non-overlapping regions or categories that are designated by colour names. Little is known about whether non-verbal animals form categories on stimulus continua, but work in psychology and artificial intelligence provides models for stimulus generalization and categorization. We compare predictions of such models to the way poultry chicks (Gallus gallus) generalize to novel stimuli following appetitive training to either one or two colours. If the two training colours are (to human eyes) red and greenish-yellow or green and blue, chicks prefer intermediates, i.e. orange rather than red or yellow and turquoise rather than green or blue. The level of preference for intermediate colours implies that the chicks interpolate between the training stimuli. However, they do not extrapolate beyond the limits set by the training stimuli, at least for red and yellow training colours. Similarly, chicks trained to red and blue generalize to purple, but they do not generalize across grey after training to the complementary colours yellow and blue. These results are consistent with a modified version of a Bayesian model of generalization from multiple examples that was proposed by Shepard and show similarities to human colour categorization.     

A model of visual recognition and categorization.

To recognize a previously seen object, the visual system must overcome the variability in the object''s appearance caused by factors such as illumination and pose. Developments in computer vision suggest that it may be possible to counter the influence of these factors, by learning to interpolate between stored views of the target object, taken under representative combinations of viewing conditions. Daily life situations, however, typically require categorization, rather than recognition, of objects. Due to the open-ended character of both natural and artificial categories, categorization cannot rely on interpolation between stored examples. Nonetheless, knowledge of several representative members, or prototypes, of each of the categories of interest can still provide the necessary computational substrate for the categorization of new instances. The resulting representational scheme based on similarities to prototypes appears to be computationally viable, and is readily mapped onto the mechanisms of biological vision revealed by recent psychophysical and physiological studies.     

Ultra-rapid categorization of fourier-spectrum equalized natural images: macaques and humans perform similarly

Background

Comparative studies of cognitive processes find similarities between humans and apes but also monkeys. Even high-level processes, like the ability to categorize classes of object from any natural scene under ultra-rapid time constraints, seem to be present in rhesus macaque monkeys (despite a smaller brain and the lack of language and a cultural background). An interesting and still open question concerns the degree to which the same images are treated with the same efficacy by humans and monkeys when a low level cue, the spatial frequency content, is controlled.

Methodology/Principal Findings

We used a set of natural images equalized in Fourier spectrum and asked whether it is still possible to categorize them as containing an animal and at what speed. One rhesus macaque monkey performed a forced-choice saccadic task with a good accuracy (67.5% and 76% for new and familiar images respectively) although performance was lower than with non-equalized images. Importantly, the minimum reaction time was still very fast (100 ms). We compared the performances of human subjects with the same setup and the same set of (new) images. Overall mean performance of humans was also lower than with original images (64% correct) but the minimum reaction time was still short (140 ms).

Conclusion

Performances on individual images (% correct but not reaction times) for both humans and the monkey were significantly correlated suggesting that both species use similar features to perform the task. A similar advantage for full-face images was seen for both species. The results also suggest that local low spatial frequency information could be important, a finding that fits the theory that fast categorization relies on a rapid feedforward magnocellular signal.     

A hierarchical probabilistic model for rapid object categorization in natural scenes

Humans can categorize objects in complex natural scenes within 100-150 ms. This amazing ability of rapid categorization has motivated many computational models. Most of these models require extensive training to obtain a decision boundary in a very high dimensional (e.g., ～6,000 in a leading model) feature space and often categorize objects in natural scenes by categorizing the context that co-occurs with objects when objects do not occupy large portions of the scenes. It is thus unclear how humans achieve rapid scene categorization.To address this issue, we developed a hierarchical probabilistic model for rapid object categorization in natural scenes. In this model, a natural object category is represented by a coarse hierarchical probability distribution (PD), which includes PDs of object geometry and spatial configuration of object parts. Object parts are encoded by PDs of a set of natural object structures, each of which is a concatenation of local object features. Rapid categorization is performed as statistical inference. Since the model uses a very small number (～100) of structures for even complex object categories such as animals and cars, it requires little training and is robust in the presence of large variations within object categories and in their occurrences in natural scenes. Remarkably, we found that the model categorized animals in natural scenes and cars in street scenes with a near human-level performance. We also found that the model located animals and cars in natural scenes, thus overcoming a flaw in many other models which is to categorize objects in natural context by categorizing contextual features. These results suggest that coarse PDs of object categories based on natural object structures and statistical operations on these PDs may underlie the human ability to rapidly categorize scenes.     

Methods for mapping and categorization of DNA sequence reads from allopolyploid organisms

Genome read categorization determines the genome of origin for sequence reads from an allopolyploid organism. Different techniques have been used to perform read categorization, mostly based on homoeo-SNPs identified between extant diploid relatives of allopolyploids. We present a novel technique for read categorization implemented by the software PolyDog. We demonstrate its accuracy and improved categorization relative to other methods. We discuss the situations in which one method or another might be most appropriate.     

Inferotemporal cortex subserves three-dimensional structure categorization

We perceive real-world objects as three-dimensional (3D), yet it is unknown which brain area underlies our ability to perceive objects in this way. The macaque inferotemporal (IT) cortex contains neurons that respond selectively to 3D structures defined by binocular disparity. To examine the causal role of IT in the categorization of 3D structures, we electrically stimulated clusters of IT neurons with a similar 3D-structure preference while monkeys performed a 3D-structure categorization task. Microstimulation of 3D-structure-selective IT clusters caused monkeys to choose the preferred structure of the 3D-structure-selective neurons considerably more often. Microstimulation in IT also accelerated the monkeys' choice for the preferred structure, while delaying choices corresponding to the nonpreferred structure of a given site. These findings reveal that 3D-structure-selective neurons in IT contribute to the categorization of 3D objects.     

研究: 异族面孔分类中情绪的调节作用

人们对异族面孔的分类绩效比本族面孔更好,这称作异族分类优势.但面孔异族分类优势是否也和面孔异族效应一样受到情绪的调节作用,尚未可知.本文通过两个实验考察情绪对于面孔种族分类任务的影响.实验一要求40名大学生被试对不同表情面孔(中性,负性,正性)完成种族判断任务,结果发现,正性和负性情绪使年轻人对异族面孔分类变得更慢,削弱了面孔异族分类优势,而且正性情绪对异族分类效应影响更大.实验二以不同情绪加工特点的老年人为被试,发现老年人对负性异族面孔的分类绩效明显更差,负性情绪对异族分类优势的影响更大.这些结果为异族分类优势理论中,异族面孔分类和个体身份加工过程相互制约的潜在假设提供了进一步的支持.     

Population heterogeneity and color stimulus heterogeneity in agent-based color categorization

Investigating the interactions between universal and culturally specific influences on color categorization across individuals and cultures has proven to be a challenge for human color categorization and naming research. The present article simulates the evolution of color lexicons to evaluate the role of two realistic constraints found in the human phenomenon: (i) heterogeneous observer populations and (ii) heterogeneous color stimuli. Such constraints, idealized and implemented as agent categorization and communication games, produce interesting and unexpected consequences for stable categorization solutions evolved and shared by agent populations. We find that the presence of a small fraction of color deficient agents in a population, or the presence of a “region of increased salience” in the color stimulus space, break rotational symmetry in population categorization solutions, and confine color category boundaries to a subset of available locations. Further, these heterogeneities, each in a different, predictable, way, might lead to a change of category number and size. In addition, the concurrent presence of both types of heterogeneity gives rise to novel constrained solutions which optimize the success rate of categorization and communication games. Implications of these agent-based results for psychological theories of color categorization and the evolution of color naming systems in human societies are discussed.     

Uniform categorization of biocommunication in bacteria, fungi and plants

This article describes a coherent biocommunication categorization for the kingdoms of bacteria, fungi and plants. The investigation further shows that, besides biotic sign use in trans-, inter- and intraorganismic communication processes, a common trait is interpretation of abiotic influences as indicators to generate an appropriate adaptive behaviour. Far from being mechanistic interactions, communication processes within organisms and between organisms are sign-mediated interactions. Sign-mediated interactions are the precondition for every cooperation and coordination between at least two biological agents such as cells, tissues, organs and organisms. Signs of biocommunicative processes are chemical molecules in most cases. The signs that are used in a great variety of signaling processes follow syntactic (combinatorial), pragmatic (context-dependent) and semantic (content-specific) rules. These three levels of semiotic rules are helpful tools to investigate communication processes throughout all organismic kingdoms. It is not the aim to present the latest empirical data concerning communication in these three kingdoms but to present a unifying perspective that is able to interconnect transdisciplinary research on bacteria, fungi and plants.     

Effects of stimulus manipulations on visual categorization in pigeons

Four pigeons were previously trained [Lazareva, O.F., Freiburger, K.L., Wasserman, E.A., 2004. Pigeons concurrently categorize photographs at both basic and superordinate levels. Psychon. Bull. Rev. 11, 1111-1117] to classify color photographs into either their proper basic-level category (cars, chairs, flowers, or people) or a superordinate-level category (nominally natural or artificial). In Experiment 1, the same pigeons were shown either reflected or inverted versions of the training stimuli. Reflection had no effect on pigeons' classification behavior, whereas inversion impaired discrimination of all stimulus categories, except flowers, on the basic-level and superordinate-level tasks. Pixel matching analysis revealed that pattern matching played at most a minor role in the birds' categorization behavior. In Experiment 2, the pigeons were shown test stimuli that were either blurred or quartered and scrambled. Blurring impaired discrimination of cars, but had no effect on discrimination of people and flowers; scrambling impaired discrimination of people and flowers leaving discrimination of cars and chairs unaffected. These results suggest that categorization of flowers and people may be controlled primarily by the overall shape of the object rather than by local features, whereas categorization of cars and chairs may rely primarily on local features rather than the overall shape of the object.     

Spontaneous categorization along competence in partner and leader evaluations

Successful cooperation requires a partner both willing and capable of contributing to a joint endeavour. Accordingly, partner choice psychology should include mechanisms to distinguish between people with good and bad intentions, and between people who are competent and incompetent. While it is well established that intentions influence partner choice, the literature offers mixed evidence concerning people's ability to gauge competence in social interactions. Theoretical accounts in leadership-followership psychology and food-sharing imply that partner competence can influence the estimated future benefits from cooperation. The available empirical evidence, however, is limited to leadership evaluations in the political science literature. This paper thus investigates if people have dedicated cognitive mechanisms, which have evolved to categorize potential social partners on competence. It looks at competence both in regular social partnerships and leader-follower relations. In a series of four experiments relying on the memory confusion protocol, it demonstrates that people spontaneously distinguish between competent and incompetent social partners. This mental categorization is present equally in partner and leader evaluations. These results have interesting implications for partner choice literature and evolutionary leadership theories.     

Rethinking ethnicity: Identity,categorization and power

This article argues that ethnic identity is to be understood and theorized as an example of social identity in general and that externally‐located processes of social categorization are enormously influential in the production and reproduction of social identities. However, much research concerned with ethnicity, particularly social anthropological research, inspired, whether directly or indirectly, by Barth's Ethnic Groups and Boundaries, has concentrated upon internal process of group identification, at the expense of categorization. To acknowledge the necessary role of categorization in the social construction of ethnic identity is also to recognize (a) the importance of power and authority relations (domination) in that process, and (b) a distinction, which is developed in this article, between the nominal and the virtual dimensions of ethnic and other social identities. Finally, the article offers an outline of a substantive research agenda concerned with contexts of social categorization.     

Whistle discrimination and categorization by the Atlantic bottlenose dolphin (Tursiops truncatus): a review of the signature whistle framework and a perceptual test

Dolphin whistles vary by frequency contour, changes in frequency over time. Individual dolphins may broadcast their identities via uniquely contoured whistles, "signature whistles." A recent debate concerning categorization of these whistles has highlighted the on-going need for perceptual studies of whistles by dolphins. This article reviews research on dolphin whistles as well as presenting a study in which a captive, female, adult bottlenose dolphin performed a conditional matching task in which whistles produced by six wild dolphins in Sarasota Bay were each paired with surrogate producers, specific objects/places. The dolphin subject also categorized unfamiliar exemplars produced by the whistlers represented by the original stimuli. The dolphin successfully discriminated among the group of whistles, associated them with surrogate producers, grouped new exemplars of the same dolphin's whistle together when the contour was intact, and discriminated among same-contour whistles produced by the same dolphin. Whistle sequences that included partial contours were not categorized with the original whistlers. Categorization appeared to be based on contour rather than specific acoustic parameters or voice cues. These findings are consistent with the perceptual tenets associated with the signature whistle framework which suggests that dolphins use individualized whistle contours for identification of known conspecifics.     

Color categorization and color constancy in a neural network model of V4

We develop a neural network model that instantiates color constancy and color categorization in a single unified framework. Previous models achieve similar effects but ignore important biological constraints. Color constancy in this model is achieved by a new application of the double opponent cells found in the blobs of the visual cortex. Color categorization emerges naturally, as a consequence of processing chromatic stimuli as vectors in a four-dimensional color space. A computer simulation of this model is subjected to the classic psychophysical tests that first uncovered these phenomena, and its response matches psychophysical results very closely.     

A complete categorization of multiscale models of infectious disease systems

Modelling of infectious disease systems has entered a new era in which disease modellers are increasingly turning to multiscale modelling to extend traditional modelling frameworks into new application areas and to achieve higher levels of detail and accuracy in characterizing infectious disease systems. In this paper we present a categorization framework for categorizing multiscale models of infectious disease systems. The categorization framework consists of five integration frameworks and five criteria. We use the categorization framework to give a complete categorization of host-level immuno-epidemiological models (HL-IEMs). This categorization framework is also shown to be applicable in categorizing other types of multiscale models of infectious diseases beyond HL-IEMs through modifying the initial categorization framework presented in this study. Categorization of multiscale models of infectious disease systems in this way is useful in bringing some order to the discussion on the structure of these multiscale models.