Neural correlates of context-dependent feature conjunction learning in visual search tasks

CoBeL-RL: A neuroscience-oriented simulation framework for complex behavior and learning

Reinforcement learning (RL) has become a popular paradigm for modeling animal behavior, analyzing neuronal representations, and studying their emergence during learning. This development has been fueled by advances in understanding the role of RL in both the brain and artificial intelligence. However, while in machine learning a set of tools and standardized benchmarks facilitate the development of new methods and their comparison to existing ones, in neuroscience, the software infrastructure is much more fragmented. Even if sharing theoretical principles, computational studies rarely share software frameworks, thereby impeding the integration or comparison of different results. Machine learning tools are also difficult to port to computational neuroscience since the experimental requirements are usually not well aligned. To address these challenges we introduce CoBeL-RL, a closed-loop simulator of complex behavior and learning based on RL and deep neural networks. It provides a neuroscience-oriented framework for efficiently setting up and running simulations. CoBeL-RL offers a set of virtual environments, e.g., T-maze and Morris water maze, which can be simulated at different levels of abstraction, e.g., a simple gridworld or a 3D environment with complex visual stimuli, and set up using intuitive GUI tools. A range of RL algorithms, e.g., Dyna-Q and deep Q-network algorithms, is provided and can be easily extended. CoBeL-RL provides tools for monitoring and analyzing behavior and unit activity, and allows for fine-grained control of the simulation via interfaces to relevant points in its closed-loop. In summary, CoBeL-RL fills an important gap in the software toolbox of computational neuroscience.

Visual search training benefits from the integrative effect of enhanced covert attention and optimized overt eye movements

Training serves as an effective approach to improve visual search performance when the target does not automatically pop out from the distractors. In the present study, we trained participants on a conjunction visual search task and examined the training effects in behavior and eye movement. The results of Experiments 1 to 4 showed that training improved behavioral performance and reduced the number of saccades and overall scanning time. Training also increased the search initiation time before the first saccade and the proportion of trials in which the participants correctly identified the target without any saccade, but these effects were modulated by stimulus’ parameters. In Experiment 5, we simultaneously recorded eye movements and electroencephalography signals and the results revealed significant N2 posterior contralateral (N2pc) components after the stimulus onset (i.e., stimulus-locked) and before the first saccade (i.e., saccade-locked) when the search target was the trained one. These N2pc components can be considered as the neural signatures for the enhanced covert attention to the trained target. Together with the training-induced increase in functional visual field, these mechanisms could support the beneficial effects of increased search initiation time and reduced number of saccades. These findings suggest that visual search training enhanced covert attention to target and optimized overt eye movements to facilitate search performance.

Multidimensional Reasoning Can Promote 3-Year-Old Children's Performance on the Dimensional Change Card Sort Task

An important aspect of executive functioning is the ability to flexibly switch between behavioral rules. This study explored how considering the multidimensionality of objects affects behavioral rule switching in 3-year-old children. In Study 1 (N = 40), children who participated in a brief game separating and aggregating an object's dimensions (i.e., color and shape) showed improved performance on the Dimensional Change Card Sort (DCCS), a measure of behavioral rule switching, relative to controls. In Study 2 (N = 80) DCCS performance improved even when the initial practice involved a different dimension (pattern and shape). Thus, practice thinking about multidimensionality can affect 3-year-olds' DCCS performance and therefore may play an important role in the development of flexible thinking.

Pop-out for illusory rather than veridical trajectories with double-drift stimuli

If a patch of texture drifts in one direction while its internal texture drifts in the orthogonal direction, the perceived direction of this double-drift stimulus (also known as the infinite regress and curveball illusions) deviates strongly from its physical direction. Here, we use double-drift stimuli to construct two types of search arrays: The first had an oddball target in terms of the physical trajectories, but no oddball for the perceived trajectory, whereas the second had a perceptual oddball, but no physical oddball. We used these two arrays to determine whether pop-out operates over physical or perceived trajectories. Participants reported the location of the odd double-drift stimulus that had either a unique physical or perceived trajectory in a set of four or eight items. When the distractors all shared one perceived trajectory, but the target had an odd perceived trajectory, it popped out even though the physical trajectories of the stimuli were mixed: Accuracy rates were at ceiling, and response times decreased with increasing set size. In contrast, participants were significantly less accurate and slower at finding the physical oddball when all the paths had a common perceived trajectory. Moreover, responses became less accurate and slower with increasing set size. Our findings suggest that, at least for this type of stimulus, perceptual features can be processed rapidly, whereas the search for physical features is very inefficient.

Traditional Visual Search vs. X-Ray Image Inspection in Students and Professionals: Are the Same Visual-Cognitive Abilities Needed?

The act of looking for targets amongst an array of distractors is a cognitive task that has been studied extensively over many decades and has many real-world applications. Research shows that specific visual-cognitive abilities are needed to efficiently and effectively locate a target among distractors. It is, however, not always clear whether the results from traditional, simplified visual search tasks conducted by students will extrapolate to an applied inspection tasks in which professionals search for targets that are more complex, ambiguous, and less salient. More concretely, there are several potential challenges when interpreting traditional visual search results in terms of their implications for the X-ray image inspection task. In this study, we tested whether a theoretical intelligence model with known facets of visual-cognitive abilities (visual processing Gv, short-term memory Gsm, and processing speed Gs) can predict performance in both a traditional visual search task and an X-ray image inspection task in both students and professionals. Results showed that visual search ability as measured with a traditional visual search task is not comparable to an applied X-ray image inspection task. Even though both tasks require aspects of the same visual-cognitive abilities, the overlap between the tasks was small. We concluded that different aspects of visual-cognitive abilities predict performance on the measured tasks. Furthermore, although our tested populations were comparable in terms of performance predictors based on visual-cognitive abilities, professionals outperformed students on an applied X-ray image inspection task. Hence, inferences from our research questions have to be treated with caution, because the comparability of the two populations depends on the task.

Self-reference in action: Arm-movement responses are enhanced in perceptual matching

Considerable evidence now shows that making a reference to the self in a task modulates attention, perception, memory, and decision-making. Furthermore, the self-reference effect (SRE) cannot be reduced to domain-general factors (e.g., reward value) and is supported by distinct neural circuitry. However, it remains unknown whether self-associations modulate response execution as well. This was tested in the present study. Participants carried out a perceptual-matching task, and movement time (MT) was measured separately from reaction-time (RT; drawing on methodology from the literature on intelligence). A response box recorded 'home'-button-releases (measuring RT from stimulus onset); and a target-key positioned 14 cm from the response box recorded MT (from 'home'-button-release to target-key depression). MTs of responses to self- as compared with other-person-associated stimuli were faster (with a higher proportion correct for self-related responses). We present a novel demonstration that the SRE can modulate the execution of rapid-aiming arm-movement responses. Implications of the findings are discussed, along with suggestions to guide and inspire future work in investigating how the SRE influences action.

Learning efficient visual search for stimuli containing diagnostic spatial configurations and color-shape conjunctions

Visual search is often slow and difficult for complex stimuli such as feature conjunctions. Search efficiency, however, can improve with training. Search for stimuli that can be identified by the spatial configuration of two elements (e.g., the relative position of two colored shapes) improves dramatically within a few hundred trials of practice. Several recent imaging studies have identified neural correlates of this learning, but it remains unclear what stimulus properties participants learn to use to search efficiently. Influential models, such as reverse hierarchy theory, propose two major possibilities: learning to use information contained in low-level image statistics (e.g., single features at particular retinotopic locations) or in high-level characteristics (e.g., feature conjunctions) of the task-relevant stimuli. In a series of experiments, we tested these two hypotheses, which make different predictions about the effect of various stimulus manipulations after training. We find relatively small effects of manipulating low-level properties of the stimuli (e.g., changing their retinotopic location) and some conjunctive properties (e.g., color-position), whereas the effects of manipulating other conjunctive properties (e.g., color-shape) are larger. Overall, the findings suggest conjunction learning involving such stimuli might be an emergent phenomenon that reflects multiple different learning processes, each of which capitalizes on different types of information contained in the stimuli. We also show that both targets and distractors are learned, and that reversing learned target and distractor identities impairs performance. This suggests that participants do not merely learn to discriminate target and distractor stimuli, they also learn stimulus identity mappings that contribute to performance improvements.