PicPsy: A new bank of 106 photographs and line drawings with written naming norms for Spanish-speaking children and adults.

The use of pictures as experimental stimuli is a frequent practice in psychological and educational research. In addition, picture-naming task allows the study of different cognitive processes such as perception, attention, memory and language. Line drawings have been widely used in research to date but it has begun to be highlighted the need for more ecological stimuli such as photographs. However, normative data of a photographic set has not been published yet for use with children. We present PicPsy, a new standardized bank of photographs and matched line drawing. We collected written picture-naming norms for name agreement, unknown responses, alternative names, familiarity and visual complexity. A total of 118 native Spanish-speaking children in grades 3-4 participated in the study. For comparison purposes, 89 adults were also included in the study. Child and adult performance was highly correlated, but we found significant age group differences in all variables examined except for visual complexity. Researchers and teachers could benefit from using the new standardized bank reported here which is published under public domain license. The data and materials for this research are available at the Open Science Framework, https://osf.io/nyf3t/.

Age, education and intellectual quotient influences: structural equation modeling on the study of Benton Visual Retention Test (BVRT)

This study searched for sociodemographic influences on visual memory and visuoconstructive ability in healthy and clinical samples evaluated with Benton Visual Retention Test (BVRT) in two studies. In Study 1, we searched for changes related to age in children, adolescents, adults and elderly on the performance of the BVRT. In Study 2, we investigated the relations among age, years of education and intellectual quotient (IQ) on the performance of the BVRT using Structural Equation Modeling (SEM). Participants were 624 individuals aged between six and 89 years old (M = 25.40; SD = 22.34) from the normatization and evidence validity studies at Brazil. We used a sociodemographic questionnaire, BVRT and IQ measure was estimated. Study 1 has shown a performance similar to the developmental graphics with a U-inverted pattern in relation to age: An increase of the visual memory ability in the children and adolescent groups as age increases, a tendency of a decrease in the performance in the adult group that intensifies in the elderly group. Study 2 found that the model for the BVRT performance tested by SEM denoted satisfactory goodness-of-fit indexes, χ2/gl = 2.67, p < .001; CFI = .92; TLI = .93; RMSEA = .004, 90% CI = [.03, .05];WLSMV = 1.79, and corroborated the theoretical assumption. The SEM model confirmed in this study highlight the strong role of years of education in the prediction of BVRT scores

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Cross-platform and cross-interaction study of user personality based on images on Twitter and Flickr.

Assessing the predictive value of different social media platforms is important to understand the variation in how users reveal themselves across multiple platforms. Most social media platforms allow users to interact in multiple ways: by posting content to the platform, liking others' posts, or building a user profile. While prior studies offer insights into how language use differs across platforms, differences in image usage is less well understood. In this study, we analyzed variation in image content with user personality across three interaction types (posts, likes and profile images) and two platforms, using a unique data set of users who are active on both Twitter and Flickr. Usage patterns on these two social media platforms revealed different aspects of users' personality. Cross-platform data fusion is thus shown to improve personality prediction performance.

Accelerated low-rank representation for subspace clustering and semi-supervised classification on large-scale data.

The scalability of low-rank representation (LRR) to large-scale data is still a major research issue, because it is extremely time-consuming to solve singular value decomposition (SVD) in each optimization iteration especially for large matrices. Several methods were proposed to speed up LRR, but they are still computationally heavy, and the overall representation results were also found degenerated. In this paper, a novel method, called accelerated LRR (ALRR) is proposed for large-scale data. The proposed accelerated method integrates matrix factorization with nuclear-norm minimization to find a low-rank representation. In our proposed method, the large square matrix of representation coefficients is transformed into a significantly smaller square matrix, on which SVD can be efficiently implemented. The size of the transformed matrix is not related to the number of data points and the optimization of ALRR is linear with the number of data points. The proposed ALRR is convex, accurate, robust, and efficient for large-scale data. In this paper, ALRR is compared with state-of-the-art in subspace clustering and semi-supervised classification on real image datasets. The obtained results verify the effectiveness and superiority of the proposed ALRR method.

How do Scrabble players encode letter position during reading? / ¿Cómo codifican los jugadores de Scrabble la posición de las letras durante la lectura?

BACKGROUND: A number of experiments with skilled adult readers have shown that a transposed-letter pseudoword (e.g., CHOLOCATE) is considerably more word-like than a control replacement-letter pseudoword (e.g., CHOTONATE). For instance, in lexical decision, response times are longer and less accurate for CHOLOCATE than for CHOTONATE (i.e., a transposed-letter effect). METHOD: Here, we examined how letter position coding is attained in individuals who excel in orthographic-lexical processing: competitive Scrabble players. To this end, we conducted a lexical decision experiment with two types of pseudowords (transposedletter vs. replacement-letter pseudowords). RESULTS: Data showed that while the transposed-letter effect does occur in expert Scrabble players, the magnitude of the effect is dramatically smaller than in a control group of university students-in particular, for the accuracy data. CONCLUSIONS: The parameters responsible for the flexibility of letter position coding in models of visual word recognition must be modulated by the degree of expertise in orthographic-lexical processing

ANTECEDENTES: en experimentos con lectores adultos, las pseudopalabras creadas por transposición de letras (v.g., CHOLOCATE) se confunden frecuentemente con su palabra base. Por ejemplo, en tareas de decisión léxica ('¿es el estímulo una palabra?'), los tiempos de respuesta son mayores y con mayor porcentaje de errores para CHOLOCATE que para su control ortográfico CHOTONATE (es decir, un efecto de transposición de letras). MÉTODO: en el presente experimento examinamos los procesos de codificación de la posición de las letras en individuos particularmente expertos en el procesamiento ortográfico-léxico: jugadores de Scrabble de competición. Para ello, se realizó un experimento de decisión léxica con dos tipos de pseudopalabras (vía transposición de letras [CHOLOCATE] vs. vía sustitución de letras [CHOTONATE]). RESULTADOS: si bien los jugadores expertos de Scrabble muestran un efecto de transposición de letras, la magnitud del efecto es mucho menor que en estudiantes universitarios no entrenados a Scrabble, en particular para los datos de precisión. CONCLUSIONES: en los modelos de reconocimiento visual de palabras, la flexibilidad en la codificación de la posición de las letras en palabras debe ser modulada por la destreza en el procesamiento ortográfico-léxico

Press to grasp: how action dynamics shape object categorization.

Action and object are deeply linked to each other. Not only can viewing an object influence an ongoing action, but motor representations of action can also influence visual categorization of objects. It is tempting to assume that this influence is effector-specific. However, there is indirect evidence suggesting that this influence may be related to the action goal and not just to the effector involved in achieving it. This paper aimed, for the first time, to tackle this issue directly. Participants were asked to categorize different objects in terms of the effector (e.g. hand or foot) typically used to act upon them. The task was delivered before and after a training session in which participants were instructed either just to press a pedal with their foot or to perform the same foot action with the goal of guiding an avatar's hand to grasp a small ball. Results showed that pressing a pedal to grasp a ball influenced how participants correctly identified graspable objects as hand-related ones, making their responses more uncertain than before the training. Just pressing a pedal did not have any similar effect. This is evidence that the influence of action on object categorization can be goal-related rather than effector-specific.

Probing principles of large-scale object representation: category preference and location encoding.

Knowledge about the principles that govern large-scale neural representations of objects is central to a systematic understanding of object recognition. We used functional magnetic resonance imaging (fMRI) and multivariate pattern classification to investigate two such candidate principles: category preference and location encoding. The former designates the preferential activation of distinct cortical regions by a specific category of objects. The latter refers to information about where in the visual field a particular object is located. Participants viewed exemplars of three object categories (faces, bodies, and scenes) that were presented left or right of fixation. The analysis of fMRI activation patterns revealed the following. Category-selective regions retained their preference to the same categories in a manner tolerant to changes in object location. However, category preference was not absolute: category-selective regions also contained location-tolerant information about nonpreferred categories. Furthermore, location information was present throughout high-level ventral visual cortex and was distributed systematically across the cortical surface. We found more location information in lateral-occipital cortex than in ventral-temporal cortex. Our results provide a systematic account of the extent to which the principles of category preference and location encoding determine the representation of objects in the high-level ventral visual cortex.

Methods for comparing scanpaths and saliency maps: strengths and weaknesses.

In this article, we are interested in the computational modeling of visual attention. We report methods commonly used to assess the performance of these kinds of models. We survey the strengths and weaknesses of common assessment methods based on diachronic eye-tracking data. We then illustrate the use of some methods to benchmark computational models of visual attention.

How a hobby can shape cognition: visual word recognition in competitive Scrabble players.

Competitive Scrabble is an activity that involves extraordinary word recognition experience. We investigated whether that experience is associated with exceptional behavior in the laboratory in a classic visual word recognition paradigm: the lexical decision task (LDT). We used a version of the LDT that involved horizontal and vertical presentation and a concreteness manipulation. In Experiment 1, we presented this task to a group of undergraduates, as these participants are the typical sample in word recognition studies. In Experiment 2, we compared the performance of a group of competitive Scrabble players with a group of age-matched nonexpert control participants. The results of a series of cognitive assessments showed that the Scrabble players and control participants differed only in Scrabble-specific skills (e.g., anagramming). Scrabble expertise was associated with two specific effects (as compared to controls): vertical fluency (relatively less difficulty judging lexicality for words presented in the vertical orientation) and semantic deemphasis (smaller concreteness effects for word responses). These results suggest that visual word recognition is shaped by experience, and that with experience there are efficiencies to be had even in the adult word recognition system.

Adaptive object recognition model using incremental feature representation and hierarchical classification.

This paper presents an adaptive object recognition model based on incremental feature representation and a hierarchical feature classifier that offers plasticity to accommodate additional input data and reduces the problem of forgetting previously learned information. The incremental feature representation method applies adaptive prototype generation with a cortex-like mechanism to conventional feature representation to enable an incremental reflection of various object characteristics, such as feature dimensions in the learning process. A feature classifier based on using a hierarchical generative model recognizes various objects with variant feature dimensions during the learning process. Experimental results show that the adaptive object recognition model successfully recognizes single and multiple-object classes with enhanced stability and flexibility.

Effects of spatial frequency content on classification of face gender and expression.

The role of different spatial frequency bands on face gender and expression categorization was studied in three experiments. Accuracy and reaction time were measured for unfiltered, low-pass (cut-off frequency of 1 cycle/deg) and high-pass (cutoff frequency of 3 cycles/deg) filtered faces. Filtered and unfiltered faces were equated in root-mean-squared contrast. For low-pass filtered faces reaction times were higher than unfiltered and high-pass filtered faces in both categorization tasks. In the expression task, these results were obtained with expressive faces presented in isolation (Experiment 1) and also with neutral-expressive dynamic sequences where each expressive face was preceded by a briefly presented neutral version of the same face (Experiment 2). For high-pass filtered faces different effects were observed on gender and expression categorization. While both speed and accuracy of gender categorization were reduced comparing to unfiltered faces, the efficiency of expression classification remained similar. Finally, we found no differences between expressive and non expressive faces in the effects of spatial frequency filtering on gender categorization (Experiment 3). These results show a common role of information from the high spatial frequency band in the categorization of face gender and expression.

Monkeys quickly learn and generalize visual categories without lateral prefrontal cortex.

Categorization is a basic mental process that helps individuals distinguish among groups of negative and positive objects, e.g., poisons and nutrients, or predators and prey. Monkey experiments have suggested that lateral prefrontal cortex (LPFC) participates in learning and processing visual categories. However, in humans category specific visual agnosia follows inferior temporal cortex but not LPFC damage. Here, we use a new behavioral approach to show that both normal monkeys and those with bilateral removal of LPFC learn and generalize perceptual categories of related visual stimuli rapidly without explicit instruction. These results strongly indicate that visual categorization occurs at some earlier stage of feed-forward processing, presumably in temporal cortex, without top-down information from LPFC.

Effects of memory load on visual search

No está claro el efecto que la carga de memoria tiene sobre la atención en la Búsqueda Visual (BV): se ha encontrado tanto ausencia como efectos negativos y positivos de la carga de memoria en BV. El principal objetivo del presente trabajo fue explorar si la carga de memoria puede modular una tarea de BV por medio de la influencia del «estado o set atencional» de los participantes, generado a través del orden (aleatorio versus bloqueado) y el tiempo (largo versus corto) de presentación de los ensayos. En el experimento 1 se aleatorizó el orden de presentación (5, 10 y 15 estímulos), mientras que para los experimentos 2A y 2B permaneció constante (10 estímulos). En estos últimos cambiamos el tiempo de presentación (3000 versus 1300, respectivamente). Los resultados mostraron ausencia de efectos de la carga de memoria en los experimentos 1 y 2A, mientras que sí se encontraron en el experimento 2B: los TRs en la tarea de BV fueron significativamente mayores con carga alta de memoria; apoyando nuestra hipótesis sobre el «set atencional». Se discuten también otras posibles implicaciones teóricas para comprender mejor cómo la carga de memoria puede modular los procesos atencionales involucrados en BV (AU)

It remains unclear how memory load affects attentional processes in visual search (VS). No effects, as well as beneficial and detrimental effects of memory load, have been found in this type of task. The main goal of the present research was to explore whether memory load has a modulating effect on VS by means of a different attentional set induced by the order of trials (mixed vs. blocked) and by the time presentation of visual display (long vs. short). In Experiment 1, we randomized the order of type of trial (5, 10 and 15 items presented in the display) while it remained constant (10 items) in Experiments 2A and 2B. In the later experiments, we also changed time presentation of visual display (3000 vs. 1300 ms, respectively). Results showed no differential effects of memory load in Experiments 1 and 2A, but they showed up in Experiment 2B: RTs were longer in the attentional task for trials under high memory load conditions. Although our hypothesis of the attentional set is supported by the results, other theoretical implications are also worth discussing in order to better understand how memory load may modulate attentional processes in VS (AU)

Feature integration in natural language concepts.

Two experiments measured the joint influence of three key sets of semantic features on the frequency with which artifacts (Experiment 1) or plants and creatures (Experiment 2) were categorized in familiar categories. For artifacts, current function outweighed both originally intended function and current appearance. For biological kinds, appearance and behavior, an inner biological function, and appearance and behavior of offspring all had similarly strong effects on categorization. The data were analyzed to determine whether an independent cue model or an interactive model best accounted for how the effects of the three feature sets combined. Feature integration was found to be additive for artifacts but interactive for biological kinds. In keeping with this, membership in contrasting artifact categories tended to be superadditive, indicating overlapping categories, whereas for biological kinds, it was subadditive, indicating conceptual gaps between categories. It is argued that the results underline a key domain difference between artifact and biological concepts.

Development of a FACS-verified set of basic and self-conscious emotion expressions.

In 2 studies, the authors developed and validated of a new set of standardized emotion expressions, which they referred to as the University of California, Davis, Set of Emotion Expressions (UCDSEE). The precise components of each expression were verified using the Facial Action Coding System (FACS). The UCDSEE is the first FACS-verified set to include the three "self-conscious" emotions known to have recognizable expressions (embarrassment, pride, and shame), as well as the 6 previously established "basic" emotions (anger, disgust, fear, happiness, sadness, and surprise), all posed by the same 4 expressers (African and White males and females). This new set has numerous potential applications in future research on emotion and related topics.

Online learning of objects in a biologically motivated visual architecture.

We present a biologically motivated architecture for object recognition that is capable of online learning of several objects based on interaction with a human teacher. The system combines biological principles such as appearance-based representation in topographical feature detection hierarchies and context-driven transfer between different levels of object memory. Training can be performed in an unconstrained environment by presenting objects in front of a stereo camera system and labeling them by speech input. The learning is fully online and thus avoids an artificial separation of the interaction into training and test phases. We demonstrate the performance on a challenging ensemble of 50 objects.

Enhanced category tuning revealed by intracranial electroencephalograms in high-order human visual areas.

The functional organization of human sensory cortex was studied by comparing intracranial EEG (iEEG) recordings of local field potentials in neurosurgical patients with functional magnetic resonance imaging (fMRI) obtained in healthy subjects. Using naturalistic movie stimuli, we found a tight correlation between these two measures throughout the human sensory cortex. Importantly, the correlation between the iEEG and fMRI signals was site-specific, exhibiting neuroanatomically specific coupling. In several cortical sites the iEEG activity was confined strictly to one object category. This site selectivity was not limited to faces but included other object categories such as houses and tools. The selectivity of the iEEG signals to images of different object categories was remarkably higher when compared with the selectivity of the corresponding fMRI signals. A plausible interpretation of the fMRI and iEEG results concerns cortical organization in which object categories are organized in a mosaic of narrowly tuned object-selective clusters.

The impact of temporal compression and space selection on SVM analysis of single-subject and multi-subject fMRI data.

In the present study, we compared the effects of temporal compression (averaging across multiple scans) and space selection (i.e. selection of "regions of interest" from the whole brain) on single-subject and multi-subject classification of fMRI data using the support vector machine (SVM). Our aim was to investigate various data transformations that could be applied before training the SVM to retain task discriminatory variance while suppressing irrelevant components of variance. The data were acquired during a blocked experiment design: viewing unpleasant (Class 1), neutral (Class 2) and pleasant pictures (Class 3). In the multi-subject level analysis, we used a "leave-one-subject-out" approach, i.e. in each iteration, we trained the SVM using data from all but one subject and tested its performance in predicting the class label of the this last subject's data. In the single-subject level analysis, we used a "leave-one-block-out" approach, i.e. for each subject, we selected randomly one block per condition to be the test block and trained the SVM using data from the remaining blocks. Our results showed that in a single-subject level both temporal compression and space selection improved the SVM accuracy. However, in a multi-subject level, the temporal compression improved the performance of the SVM, but the space selection had no effect on the classification accuracy.

Neural timing of visual implicit categorization.

Most of the neuroimaging studies that have shown visual category-specific activations or categorization effects have been based on a subtractive approach. In the present study, we investigated, by means of EEG, not only the net result of the categorization but also the dynamics of the process. Subjects had to perform a target detection task throughout an image set of distractors belonging to six categories: letters, geometrical figures, faces, tools, structured textures and Asiatic characters. Multivariate analyses were performed on the responses to the non-target stimuli according to their category. Categorical neural responses were only obtained on P2 latencies and N2 amplitudes. This result suggests that there are no differences in the first stage of the implicit categorization of the distractors (visual analysis and proximal stimulus representation elaboration from 100 to 220 ms) and that differences appear between 220 and 280 ms (matching to structural representations). Over-learned stimuli (e.g. letters) elicited the shortest P2 latency, contrasting with unknown categories (e.g. Asiatic characters) that revealed the longest P2 latencies and flattened N2 waves. Categorical differences indicate that the more a subject knows about an object, the less cognitive resources are used. In conclusion, our results suggest that a reduction in neural activity could reflect an improved accuracy in cognitive and cortical processing.