Assaf Harel

Wright State University | WSU · Department of Psychology

The integration of artificial intelligence transparency in time-critical decision support is complex and requires consideration of the impact on human-machine teaming. The relationships between transparency, trust, workload, and situational awareness are key to understanding this impact on performance. We detail the development of a novel design fr...

Scene perception and spatial navigation are interdependent cognitive functions, and there is increasing evidence that cortical areas that process perceptual scene properties also carry information about the potential for navigation in the environment (navigational affordances). However, the temporal stages by which visual information is transformed...

Throughout evolution, the human visual system has adapted to efficiently encode several environmental constants to deal with the huge complexity involved in representing large-scale spatial environments. Being terrestrial animals, these constants reflect a specific ground-based viewpoint. For example, people show a strong affinity for detecting a p...

Visual analysis of complex real-world scenes (e.g. overhead imagery) is a skill essential to many professional domains. However, little is currently known about how this skill is formed and develops with experience. The present work adopts a neuroergonomic approach to uncover the underlying mechanisms associated with the acquisition of scene expert...

People are often considered cognitive misers. When given a free choice between two tasks, people tend to choose tasks requiring less cognitive effort. Such demand avoidance (DA) is associated with cognitive control, but it is still not clear to what extent individual differences in cognitive control can account for variations in DA. We sought to el...

Recent studies show that pre-stimulus band-specific power and phase in the electroencephalogram (EEG) can predict accuracy on tasks involving the detection of near-threshold stimuli. However, results in the auditory modality have been mixed, and few works have examined pre-stimulus features when more complex decisions are made (e.g. identifying sup...

Over the last decade, the efforts toward unraveling the complex interplay between the brain, body, and environment have set a promising line of research that utilizes neuroscience to study human performance in natural work contexts such as aviation. Thus, a relatively new discipline called neuroergonomics is holding the promise of studying the neur...

A great challenge for cognitive neuroscience is studying human behavior in its complexity as it manifests in the real world. The field of aviation provides a unique opportunity to investigate how perception, action and cognition interact in complex yet controlled ecologically valid environments. We suggest a novel cross-domain approach that combine...

A key question in the field of scene perception is what information people use when making decisions about images of scenes. A significant body of evidence has indicated the importance of global properties of a scene image. Ideally, well-controlled, real-world images would be used to examine the influence of these properties on perception. Unfortun...

Recent work studying the temporal dynamics of visual scene processing (Harel et al., 2016) has found that global scene properties (GSPs) modulate the amplitude of early Event-Related Potentials (ERPs). It is still not clear, however, to what extent the processing of these GSPs is influenced by their behavioral relevance, determined by the goals of...

Despite the importance of an observer's goals in determining how a visual object is categorized, surprisingly little is known about how humans process the task context in which objects occur and how it may interact with the processing of objects. Using magnetoencephalography (MEG), functional magnetic resonance imaging (fMRI) and multivariate techn...

Per subject matrices of temporal cross-classification analysis of task.

Per subject time courses of mean classification accuracy for task separated by task type and cross-classification accuracy between task types.

Per subject time courses of mean classification accuracy for task and object.

Matlab scripts including helper functions to produce Figures 3–6 based on available source data.

Despite the importance of an observer’s goals in determining how a visual object is categorized, surprisingly little is known about how humans process the task context in which objects occur and how it may interact with the processing of objects. Using magnetoencephalography (MEG), functional magnetic resonance imaging (fMRI) and multivariate techn...

The perception of a visual stimulus is dependent not only upon local features, but also on the arrangement of those features. When stimulus features are perceptually well organized (e.g., symmetric or parallel), a global configuration with a high degree of salience emerges from the interactions between these features, often referred to as emergent...

Our remarkable ability to process complex visual scenes is supported by a network of scene-selective cortical regions. Despite growing knowledge about the scene representation in these regions, much less is known about the temporal dynamics with which these representations emerge. We conducted two experiments aimed at identifying and characterizing...

How can we enhance the ability of observers to pickup visual information? One approach to this question has been to investigate people who naturally develop an exceptional skill, or expertise, in visual object recognition (e.g. bird watchers, car buffs), and determine how expert processing and the neural substrates supporting it differ from those i...

Ever since Diamond and Carey's (1986) seminal work, object expertise has often been viewed through the prism of face perception (for a thorough discussion, see Tanaka and Gauthier, 1997; Sheinberg and Tarr, 2010). According to Wong and Wong (2014, W&W), however, this emphasis has simply been a response to the question of modularity of face percepti...

We engage the world through our senses. During perception, physical signals (e.g., sound waves) are converted into electrical signals in specialized receptors and conveyed to the brain where they are processed and synthesized. In this chapter, we describe how MRI can provide critical insights into this process at both cortical and subcortical level...

Significance Visual recognition is often thought to depend on neural representations that primarily reflect the physical properties of the environment. However, in this study we demonstrate that the intent of the observer fundamentally perturbs cortical representations of visual objects. Using functional MRI we measured the patterns of response to...

Real-world expertise provides a valuable opportunity to understand how experience shapes human behavior and neural function. In the visual domain, the study of expert object recognition, such as in car enthusiasts or bird watchers, has produced a large, growing, and often-controversial literature. Here, we synthesize this literature, focusing prima...

Expertise in face recognition is characterized by high proficiency in distinguishing between individual faces. However, faces also enjoy an advantage at the early stage of basic-level detection, as demonstrated by efficient visual search for faces among nonface objects. In the present study, we asked (1) whether the face advantage in detection is a...

A much-debated question in object recognition is whether expertise for faces and expertise for non-face objects utilize common perceptual information. We investigated this issue by assessing the diagnostic information required for different types of expertise. Specifically, we asked whether face categorization and expert car categorization at the s...

One of the longest-standing questions in object recognition is how malleable object representations are to top-down cognitive factors. While behavioral studies suggest that knowledge, experience and expectations modulate the representation of objects, less is known about how the neural object responses are modulated by such top-down factors. Here,...

Expertise in non-visual domains such as musical performance is associated with differences in gray matter volume of particular regions of the human brain. Whether this is also the case for expertise in visual object recognition is unknown. Here we tested whether individual variability in the ability to recognize car models, from novice performance...

Real-world visual scenes are complex cluttered, and heterogeneous stimuli engaging scene- and object-selective cortical regions including parahippocampal place area (PPA), retrosplenial complex (RSC), and lateral occipital complex (LOC). To understand the unique contribution of each region to distributed scene representations, we generated predicti...

Neuroimaging studies have identified a network of scene-selective cortical regions: Parahippocampal Place Area (PPA), Retrosplenial Complex (RSC) and Transverse Occipital Sulcus (TOS). However, the different contributions of these areas to scene recognition are unclear. Further, while PPA shows a stronger response to scenes than objects it also con...

Visual expertise is usually defined as the superior ability to distinguish between exemplars of a homogeneous category. Here, we ask how real-world expertise manifests at basic-level categorization and assess the contribution of stimulus-driven and top-down knowledge-based factors to this manifestation. Car experts and novices categorized computer-...

A recent computational model (Ullman, Vidal-Naquet, & Sali, 2002) proposes that viewpoint-dependent features of intermediate complexity (IC) are more informative about an object's category than either highly complex or very simple features of the object. Consequently, such IC features should be optimal for object categorization. We tested the psych...

A widely held notion is that face and object expertise utilize the same sources of perceptual information. Although much is known about face expertise, the nature of the diagnostic information for object expertise and the stage in the visual processing hierarchy at which it is utilized are still unknown. To address this question, we compared perfor...

The type of visual information needed for categorizing faces and nonface objects was investigated by manipulating spatial frequency scales available in the image during a category verification task addressing basic and subordinate levels. Spatial filtering had opposite effects on faces and airplanes that were modulated by categorization level. The...

We compared early stages of face processing in young and older participants as indexed by ERPs elicited by faces and non-face stimuli presented in upright and inverted orientations. The P1 and N170 components were larger in older than in young participants. However, the early distinction between stimulus categories as reflected by N170 face was sim...

Computational models suggest that features of intermediate complexity (IC) play a central role in object categorization [Ullman, S., Vidal-Naquet, M., & Sali, E. (2002). Visual features of intermediate complexity and their use in classification. Nature Neuroscience, 5, 682-687.]. The critical aspect of these features is the amount of mutual informa...