Nonspatial attentional capture by previously rewarded scene semantics

Recent research has shown that reward influences visual perception and cognition in a way that is distinct from the well-documented goal-directed mechanisms. In the current study we explored how task-irrelevant stimulus-reward associations affect processing of stimuli when attention is constrained and reward no longer delivered. During a training phase, participants performed a choice game, exposing them to different reward schedules for different semantic categories of natural scene pictures. In a separate test session in which no additional reward was provided, the differentially rewarded scene categories were used as task-irrelevant non-targets in a rapid serial visual presentation (RSVP) task. Participants performed a detection task on a previously non-rewarded target category. Results show that participants' sensitivity index (d′) for target detection decreased as a function of whether the reward was coupled to the distractor category during training. The semantic category of natural scenes associated with high reward caused more interference in target detection than the semantic category associated with a low reward. The same was found when new, unseen distractor pictures of the same semantic categories were used. The present findings suggest that reward can be selectively associated with high level scene semantics. We argue that learned stimulus-reward associations persistently bias perceptual processing independently of spatial shifts in attention and the immediate prospect of reward.     

From domain-generality to domain-sensitivity: 4-Month-olds learn an abstract repetition rule in music that 7-month-olds do not

Learning must be constrained for it to lead to productive generalizations. Although biology is undoubtedly an important source of constraints, prior experience may be another, leading learners to represent input in ways that are more conducive to some generalizations than others, and/or to up- and down-weight features when entertaining generalizations. In two experiments, 4-month-old and 7-month-old infants were familiarized with sequences of musical chords or tones adhering either to an AAB pattern or an ABA pattern. In both cases, the 4-month-olds learned the generalization, but the 7-month-olds did not. The success of the 4-month-olds appears to contradict an account that this type of pattern learning is the provenance of a language-specific rule-learning module. It is not yet clear what drives the age-related change, but plausible candidates include differential experience with language and music, as well as interactions between general cognitive development and stimulus complexity.     

A QBF-based formalization of abstract argumentation semantics

We introduce a unified logical theory, based on signed theories and Quantified Boolean Formulas (QBFs) that can serve as the basis for representing and computing various argumentation-based decision problems. It is shown that within our framework we are able to model, in a simple and modular way, a wide range of semantics for abstract argumentation theory. This includes complete, grounded, preferred, stable, semi-stable, stage, ideal and eager semantics. Furthermore, our approach is purely logical, making for instance decision problems like skeptical and credulous acceptance of arguments simply a matter of entailment and satisfiability checking. The latter may be verified by off-the-shelf QBF-solvers.     

Evidence for the activation of sensorimotor information during visual word recognition: the body-object interaction effect

We examined the effects of sensorimotor experience in two visual word recognition tasks. Body-object interaction (BOI) ratings were collected for a large set of words. These ratings assess perceptions of the ease with which a human body can physically interact with a word's referent. A set of high BOI words (e.g., mask) and a set of low BOI words (e.g., ship) were created, matched on imageability and concreteness. Facilitatory BOI effects were observed in lexical decision and phonological lexical decision tasks: responses were faster for high BOI words than for low BOI words. We discuss how our findings may be accounted for by (a) semantic feedback within the visual word recognition system, and (b) an embodied view of cognition (e.g., Barsalou's perceptual symbol systems theory), which proposes that semantic knowledge is grounded in sensorimotor interactions with the environment.     

Action selection as a guide for visual attention

We plan our actions in order to fulfil certain sensory goals. It is generally believed, therefore, that anticipation of sensory action-outcomes plays an essential role in action selection. In this study, we examined the role of action selection, prior to action execution, in the guidance of visual attention. The experiments began with an initial acquisition phase, in which participants learned to associate two actions (left/right keypress) with two visual outcomes (red/green colour). Next, participants performed in a test phase, in which they continued to select and perform the same actions while their attentional bias was measured for items that resembled the anticipated action-outcome. The findings indicate that learned action-outcome association contributes to the guidance of attention. This guidance, furthermore, was short-lived and disappeared with larger delays between action selection and execution. The findings help situate processes of visual attention in a context that includes action selection and action-outcome associative learning.     

Modelling unsupervised online-learning of artificial grammars: Linking implicit and statistical learning

Humans rapidly learn complex structures in various domains. Findings of above-chance performance of some untrained control groups in artificial grammar learning studies raise questions about the extent to which learning can occur in an untrained, unsupervised testing situation with both correct and incorrect structures. The plausibility of unsupervised online-learning effects was modelled with n-gram, chunking and simple recurrent network models. A novel evaluation framework was applied, which alternates forced binary grammaticality judgments and subsequent learning of the same stimulus. Our results indicate a strong online learning effect for n-gram and chunking models and a weaker effect for simple recurrent network models. Such findings suggest that online learning is a plausible effect of statistical chunk learning that is possible when ungrammatical sequences contain a large proportion of grammatical chunks. Such common effects of continuous statistical learning may underlie statistical and implicit learning paradigms and raise implications for study design and testing methodologies.     

Implicit learning for probable changes in a visual change detection task

Previous research demonstrates that implicitly learned probability information can guide visual attention. We examined whether the probability of an object changing can be implicitly learned and then used to improve change detection performance. In a series of six experiments, participants completed 120–130 training change detection trials. In four of the experiments the object that changed color was the same shape (trained shape) on every trial. Participants were not explicitly aware of this change probability manipulation and change detection performance was not improved for the trained shape versus untrained shapes. In two of the experiments, the object that changed color was always in the same general location (trained location). Although participants were not explicitly aware of the change probability, implicit knowledge of it did improve change detection performance in the trained location. These results indicate that improved change detection performance through implicitly learned change probability occurs for location but not shape.     

Syntactic structure and artificial grammar learning: the learnability of embedded hierarchical structures

Embedded hierarchical structures, such as "the rat the cat ate was brown", constitute a core generative property of a natural language theory. Several recent studies have reported learning of hierarchical embeddings in artificial grammar learning (AGL) tasks, and described the functional specificity of Broca's area for processing such structures. In two experiments, we investigated whether alternative strategies can explain the learning success in these studies. We trained participants on hierarchical sequences, and found no evidence for the learning of hierarchical embeddings in test situations identical to those from other studies in the literature. Instead, participants appeared to solve the task by exploiting surface distinctions between legal and illegal sequences, and applying strategies such as counting or repetition detection. We suggest alternative interpretations for the observed activation of Broca's area, in terms of the application of calculation rules or of a differential role of working memory. We claim that the learnability of hierarchical embeddings in AGL tasks remains to be demonstrated.     

Memory modulated saliency: A computational model of the incremental learning of target locations in visual search

The top-down guidance of visual attention is one of the main factors allowing humans to effectively process vast amounts of incoming visual information. Nevertheless we still lack a full understanding of the visual, semantic, and memory processes governing visual attention. In this paper, we present a computational model of visual search capable of predicting the most likely positions of target objects. The model does not require a separate training phase, but learns likely target positions in an incremental fashion based on a memory of previous fixations. We evaluate the model on two search tasks and show that it outperforms saliency alone and comes close to the maximal performance of the Contextual Guidance Model (CGM; Torralba, Oliva, Castelhano, & Henderson, 2006; Ehinger, Hidalgo-Sotelo, Torralba, & Oliva, 2009), even though our model does not perform scene recognition or compute global image statistics. The search performance of our model can be further improved by combining it with the CGM.     

Testing for effects of racial attitudes and visual contrast on the speed of a driver’s response to a pedestrian

Although ethnic minorities are overrepresented in pedestrian-vehicle collisions, previous driving studies did not examine racial attitudes in such collisions. Our objective was to determine whether the speed of a driver’s response to a pedestrian was affected by the driver’s racial attitudes and the contrast between the pedestrian’s skin colour and background. Participants viewed simulated driving scenes of a pedestrian on a road and pressed a button as soon as they saw an obstacle. Visual information, but not racial attitudes, affected the time it took observers to respond to pedestrian and non-pedestrian stimuli in driving scenes. Results indicated that contrast affected response time even when the stimulus was subliminal. We believe this is the first demonstration of contrast effects with subliminal stimuli in a driving context. Results have implications for traffic safety and for methodology used to study racial attitudes.     

A Battery of Tests for the Dominant Eye

Gastropod shells were covered with artificial materials to determine whether the octopus can bore through these compounds which are resistant to chemical attack. The octopus penetrated acrylic, epoxy, and polyester coatings, which are harder than shell, and thus mechanical action by radular teeth is sufficient to bore the hole, and chemical involvement is not necessary.     

Mental body distance comparison: A tool for assessing clinical disturbances in visual body image

Despite numerous body size estimation studies, it cannot be concluded that the disturbance of body image in anorexia nervosa (AN) is specifically one of the visual body images.We adopted a visual imagery method, the Distance Comparison task, to enable across-population testing of differences in visual body image with respect to shape. Participants were asked to mentally scan across two body widths (e.g. hips and shoulders) and to decide as quickly as possible which one was longer or shorter. If the mental representation accessed to make such comparisons is visual, an inverse relation would be expected between RT and distance difference on the body to be judged (i.e. actual difference in size between the two body widths), with accuracy increasing with increasing distance difference. Females with high body shape concern (scoring high on the Body Shape Questionnaire: BSQ, n = 23) were compared to females with low body shape concern (scoring low on the BSQ, n = 19).RT and distance differences on the body demonstrated standard distance differences effects: RT increased and accuracy decreased with decreasing distance differences on the body. Groups differed with respect to accuracy, in that females high on body shape concern were significantly less accurate than females low on body shape concern when making evaluations involving small (?9 cm) differences, which implies a less appropriate visual image of the own body in the former group. With respect to the relation between RT and body distance difference, on the other hand, there were no differences between groups. We concluded that evaluations of own body size employ visual imagery and that the distance comparison task holds promise for the assessment of visual disturbances in body image in clinical populations.     

Contextual learning of multiple target locations in visual search

In visual search, detection of a target is faster when a layout of nontarget items is repeatedly encountered, suggesting that contextual invariances can guide attention. Moreover, contextual cueing can also adapt to environmental changes. For instance, when the target undergoes a predictable (i.e., learnable) location change, then contextual cueing remains effective even after the change, suggesting that a learned context is “remapped” and adjusted to novel requirements. Here, we explored the stability of contextual remapping: Four experiments demonstrated that target location changes are only effectively remapped when both the initial and the future target positions remain predictable across the entire experiment. Otherwise, contextual remapping fails. In sum, this pattern of results suggests that multiple, predictable target locations can be associated with a given repeated context, allowing the flexible adaptation of previously learned contingencies to novel task demands.     

An Eye‐Tracking Study of Exploitations of Spatial Constraints in Diagrammatic Reasoning

Semantic studies on diagrammatic notations (Barwise & Etchemendy, 1990 ; Shimojima, 1995 ; Stenning & Lemon, 2001 ) have revealed that the “non‐deductive,” “emergent,” or “perceptual” effects of diagrams (Chandrasekaran, Kurup, Banerjee, Josephson, & Winkler, 2004 ; Kulpa, 2003 ; Larkin & Simon, 1987 ; Lindsay, 1988 ) are all rooted in the exploitation of spatial constraints on graphical structures. Thus, theoretically, this process is a key factor in inference with diagrams, explaining the frequently observed reduction of inferential load. The purpose of this study was to examine the empirical basis for this theoretical suggestion, focusing on the reality of the constraint‐exploitation strategy in actual practices of diagrammatic reasoning. Eye movements were recorded while participants used simple position diagrams to solve three‐ or four‐term transitive inference problems. Our experiments revealed that the participants could exploit spatial constraints on graphical structures even when (a) they were not in the position of actually manipulating diagrams, (b) the semantic rule for the provided diagrams did not match their preferences, and (c) the constraint‐exploitation strategy invited a partly adverse effect. These findings indicate that the hypothesized process is in fact robust, with the potential to broadly account for the inferential advantage of diagrams.     

Constraint on the semantic flexibility in visual statistical learning

We examined whether the expression of visual statistical learning (VSL) is flexible at the superordinate-categorical level. In the familiarization phase, participants viewed a sequence of line drawings. In the test phase, participants observed two test sequences (statistically related triplets versus unrelated foils) that consisted of the same objects as those presented during the familiarization phase (the same condition) or different objects that shared the same categorical information with drawings during the familiarization (the different condition). They then decided whether the first or the second sequence was more familiar. The results of Experiment 1 showed greater familiarity above chance levels for statistically related triplets only in the same condition. In Experiment 2, even where the word stimuli representing each superordinate-level category were included in the test phase (the categorical condition), the results showed VSL only in the same condition. Our findings suggest that the semantic flexibility of VSL is limited to the basic-level category.     

Moving to higher ground: The dynamic field theory and the dynamics of visual cognition

In the present report, we describe a new dynamic field theory that captures the dynamics of visuo-spatial cognition. This theory grew out of the dynamic systems approach to motor control and development, and is grounded in neural principles. The initial application of dynamic field theory to issues in visuo-spatial cognition extended concepts of the motor approach to decision making in a sensori-motor context, and, more recently, to the dynamics of spatial cognition. Here we extend these concepts still further to address topics in visual cognition, including visual working memory for non-spatial object properties, the processes that underlie change detection, and the ‘binding problem’ in vision. In each case, we demonstrate that the general principles of the dynamic field approach can unify findings in the literature and generate novel predictions. We contend that the application of these concepts to visual cognition avoids the pitfalls of reductionist approaches in cognitive science, and points toward a formal integration of brains, bodies, and behavior.     

The interplay between perceptual organization and categorization in the representation of complex visual patterns by young infants

The relation between perceptual organization and categorization processes in 3- and 4-month-olds was explored. The question was whether an invariant part abstracted during category learning could interfere with Gestalt organizational processes. A 2003 study by Quinn and Schyns had reported that an initial category familiarization experience in which infants were presented with visual patterns consisting of a pacman shape and a complex polygon could interfere with infants' subsequent good continuation-based parsing of a circle from visual patterns consisting of a circle and a complex polygon. However, an alternative noninterference explanation for the results was possible because the pacman had been presented with greater frequency and duration than had the circle. The current study repeated Quinn and Schyns's procedure but provided an equivalent number of familiarization trials and duration of study time for the infants to process the pacman during initial familiarization and the circle during subsequent familiarization. The results replicated the previous findings of Quinn and Schyns. The data are consistent with the interference account and suggest that a cognitive system of adaptable feature creation can take precedence over organizational principles with which a perceptual system comes pre-equipped.     

Using an AI creativity system to explore how aesthetic experiences are processed along the brain’s perceptual neural pathways

With the increased sophistication of AI techniques, the application of these systems has been expanding to ever newer fields. Increasingly, these systems are being used in modeling of human aesthetics and creativity, e.g. how humans create artworks and design products. Our lab has developed one such AI creativity deep learning system that can be used to create artworks in the form of images and videos. In this paper, we describe this system and its use in studying the human visual system and the formation of aesthetic experiences. Specifically, we show how time-based AI created media can be used to explore the nature of the dual-pathway neuro-architecture of the human visual system and how this relates to higher cognitive judgments such as aesthetic experiences that rely on these divergent information streams. We propose a theoretical framework for how the movement within percepts such as video clips, causes the engagement of reflexive attention and a subsequent focus on visual information that are primarily processed via the dorsal stream, thereby modulating aesthetic experiences that rely on information relayed via the ventral stream. We outline our recent study in support of our proposed framework, which serves as the first study that investigates the relationship between the two visual streams and aesthetic experiences.     

Exploring explicit learning strategies: A dissociative framework for research

To explain learning, comparative researchers invoke an associative construct by which immediate reinforcement strengthens animal's adaptive responses. In contrast, cognitive researchers freely acknowledge humans' explicit-learning capability to test and confirm hypotheses even lacking direct reinforcement. We describe a new dissociative framework that may stretch animals' learning toward the explicit pole of cognition. We discuss the neuroscience of reinforcement-based learning and suggest the possibility of disabling a dominant form of reinforcement-based discrimination learning. In that vacuum, researchers may have an opportunity to observe animals' explicit learning strategies (i.e., hypotheses, rules, task self-construals). We review initial research using this framework showing explicit learning by humans and perhaps by monkeys. Finally, we consider why complementary explicit and reinforcement-based learning systems might promote evolutionary and ecological fitness. Illuminating the evolution of parallel learning systems may also tell part of the story of the emergence of humans' extraordinary capacity for explicit-declarative cognition.