The Role of Competitive Inhibition and Top-Down Feedback in Binding during Object Recognition

TiDEC: A Two-Layered Integrated Decision Cycle for Population Evolution

Agent-based simulation is a useful approach for the analysis of dynamic population evolution. In this field, the existing models mostly treat the migration behavior as a result of utility maximization, which partially ignores the endogenous mechanisms of human decision making. To simulate such a process, this article proposes a new cognitive architecture called the two-layered integrated decision cycle (TiDEC) which characterizes the individual's decision-making process. Different from the previous ones, the new hybrid architecture incorporates deep neural networks for its perception and implicit knowledge learning. The proposed model is applied in China and U.S. population evolution. To the best of our knowledge, this is the first time that the cognitive computation is used in such a field. Computational experiments using the actual census data indicate that the cognitive model, compared with the traditional utility maximization methods, cannot only reconstruct the historical demographic features but also achieve better prediction of future evolutionary dynamics.

Explicit Categorization Goals Affect Attention-Related Processing of Race and Gender During Person Construal

Faces are categorized by gender and race very quickly, seemingly without regard to perceivers' goals or motivations, suggesting an automaticity to these judgments that has downstream consequences for evaluations, stereotypes, and social interactions. The current study investigated the extent to which early neurocognitive processes involved in the categorization of faces vary when participants' tasks goals were to categorize faces by race or by gender. In contrast to previous findings, task-related differences were found, such that differentiation in the P2 event-related potential (ERP) according to perceived gender was facilitated by having an explicit task goal of categorizing faces by gender; however, the P2 was sensitive to race regardless of task goals. Use of principal components analysis (PCA) revealed two underlying components that comprised the P2 and that were differentially sensitive to the gender and race of the faces, depending on participants' top-down task goals. Results suggest that top-down task demands facilitate discrimination of faces along the attended dimension within less than 200 ms, but that the effect of top-down task demands may not be evident when examining early ERP components that reflect more than one distinct underlying process.

Replicability of the Curvature Effect as a Function of Presentation Time and Response Measure in Japanese Observers

Although objects with curved contours are generally preferred over those with sharp-angled contours, the strength of this preference varies according to several factors. In the present study, non-Western Japanese observers viewed and rated their preferences (e.g., liking or attractiveness) for real and meaningless objects with curved or sharp-angled contours. We varied the presentation time (90 ms vs. until a response was received) and the response measure (like/dislike vs. 1-100 rating scale). When using like/dislike ratings, a preference for curved objects was found only when images of real objects were presented briefly (90 ms), whereas this effect was reversed (i.e., increased preference for sharp-angled contours) when using the 1 to 100 scale under the until-response condition. In addition, the curvature effect was not observed for real objects when the like/dislike rating and the until-response condition were employed or when the 1 to 100 scale and 90 ms presentation time were used. The curvature effect for meaningless objects remained unstable regardless of presentation time or response measure. Similar to the preference for real objects, a preference for sharp-angled objects was observed when preference was measured using a 1 to 100 rating scale. Taken together, the present findings indicate that the preferences for curved objects were situation-dependent in Japanese observers.

GABAergic-astrocyte signaling: A refinement of inhibitory brain networks

Interneurons play a critical role in precise control of network operation. Indeed, higher brain capabilities such as working memory, cognitive flexibility, attention, or social interaction rely on the action of GABAergic interneurons. Evidence from excitatory neurons and synapses has revealed astrocytes as integral elements of synaptic transmission. However, GABAergic interneurons can also engage astrocyte signaling; therefore, it is tempting to speculate about different scenarios where, based on particular interneuron cell type, GABAergic‐astrocyte interplay would be involved in diverse outcomes of brain function. In this review, we will highlight current data supporting the existence of dynamic GABAergic‐astrocyte communication and its impact on the inhibitory‐regulated brain responses, bringing new perspectives on the ways astrocytes might contribute to efficient neuronal coding.

Neuroimaging Findings on Amodal Completion: A Review

Amodal completion is the phenomenon of perceiving completed objects even though physically they are partially occluded. In this review, we provide an extensive overview of the results obtained from a variety of neuroimaging studies on the neural correlates of amodal completion. We discuss whether low-level and high-level cortical areas are implicated in amodal completion; provide an overview of how amodal completion unfolds over time while dissociating feedforward, recurrent, and feedback processes; and discuss how amodal completion is represented at the neuronal level. The involvement of low-level visual areas such as V1 and V2 is not yet clear, while several high-level structures such as the lateral occipital complex and fusiform face area seem invariant to occlusion of objects and faces, respectively, and several motor areas seem to code for object permanence. The variety of results on the timing of amodal completion hints to a mixture of feedforward, recurrent, and feedback processes. We discuss whether the invisible parts of the occluded object are represented as if they were visible, contrary to a high-level representation. While plenty of questions on amodal completion remain, this review presents an overview of the neuroimaging findings reported to date, summarizes several insights from computational models, and connects research of other perceptual completion processes such as modal completion. In all, it is suggested that amodal completion is the solution to deal with various types of incomplete retinal information, and highly depends on stimulus complexity and saliency, and therefore also give rise to a variety of observed neural patterns.

A Neural Mechanism of Social Categorization

Humans readily sort one another into multiple social categories from mere facial features. However, the facial features used to do so are not always clear-cut because they can be associated with opponent categories (e.g., feminine male face). Recently, computational models and behavioral studies have provided indirect evidence that categorizing such faces is accomplished through dynamic competition between parallel, coactivated social categories that resolve into a stable categorical percept. Using a novel paradigm combining fMRI with real-time hand tracking, the present study examined how the brain translates diverse social cues into categorical percepts. Participants (male and female) categorized faces varying in gender and racial typicality. When categorizing atypical faces, participants' hand movements were simultaneously attracted toward the unselected category response, indexing the degree to which such faces activated the opposite category in parallel. Multivoxel pattern analyses (MVPAs) provided evidence that such social category coactivation manifested in neural patterns of the right fusiform cortex. The extent to which the hand was simultaneously attracted to the opposite gender or race category response option corresponded to increased neural pattern similarity with the average pattern associated with that category, which in turn associated with stronger engagement of the dorsal anterior cingulate cortex. The findings point to a model of social categorization in which occasionally conflicting facial features are resolved through competition between coactivated ventral-temporal cortical representations with the assistance of conflict-monitoring regions. More broadly, the results offer a promising multimodal paradigm to investigate the neural basis of "hidden", temporarily active representations in the service of a broad range of cognitive processes.SIGNIFICANCE STATEMENT Individuals readily sort one another into social categories (e.g., sex, race), which have important consequences for a variety of interpersonal behaviors. However, individuals routinely encounter faces that contain diverse features associated with multiple categories (e.g., feminine male face). Using a novel paradigm combining neuroimaging with hand tracking, the present research sought to address how the brain comes to arrive at stable social categorizations from multiple social cues. The results provide evidence that opponent social categories coactivate in face-processing regions, which compete and may resolve into an eventual stable categorization with the assistance of conflict-monitoring regions. Therefore, the findings provide a neural mechanism through which the brain may translate inherently diverse social cues into coherent categorizations of other people.

The Time-Course of Ultrarapid Categorization: The Influence of Scene Congruency and Top-Down Processing

Although categorization can take place at different levels of abstraction, classic studies on semantic labeling identified the basic level, for example, dog, as entry point for categorization. Ultrarapid categorization tasks have contradicted these findings, indicating that participants are faster at detecting superordinate-level information, for example, animal, in a complex visual image. We argue that both seemingly contradictive findings can be reconciled within the framework of parallel distributed processing and its successor Leabra (Local, Error-driven and Associative, Biologically Realistic Algorithm). The current study aimed at verifying this prediction in an ultrarapid categorization task with a dynamically changing presentation time (PT) for each briefly presented object, followed by a perceptual mask. Furthermore, we manipulated two defining task variables: level of categorization (basic vs. superordinate categorization) and object presentation mode (object-in-isolation vs. object-in-context). In contradiction with previous ultrarapid categorization research, focusing on reaction time, we used accuracy as our main dependent variable. Results indicated a consistent superordinate processing advantage, coinciding with an overall improvement in performance with longer PT and a significantly more accurate detection of objects in isolation, compared with objects in context, at lower stimulus PT. This contextual disadvantage disappeared when PT increased, indicating that figure-ground separation with recurrent processing is vital for meaningful contextual processing to occur.

Opposing effects of glutamatergic and GABAergic pharmacological manipulations on a visual perception task with relevance to schizophrenia

RATIONALE

Numerous psychiatric disorders and neurodegenerative diseases have been associated with differences in visual perception, and it has been proposed that the treatment of these differences may represent a novel means to treat disorders like schizophrenia. Unfortunately, few methods exist to study visual perception in pre-clinical species.

OBJECTIVE

The purpose of the present study was to adapt a task of visual integration by proximity with relevance to schizophrenia to a rodent touchscreen environment to determine the effects of glutamatergic and GABAergic compounds. In this way, we could evaluate the effects of common models of cognitive impairment, as well as the effects of net excitation versus inhibition, on a task of visual integration.

METHOD

Rats were trained to perform a visual discrimination where the stimuli were composed of rows of dots differing only in there horizontal and vertical proximity. Once stable performance had been achieved, animals were tested under the influence of glutamatergic or GABAergic drugs (ketamine, MK-801, PCP, memantine, chlordiazepoxide, or diazepam) while attempting to perform a visual discrimination with altered stimuli.

RESULTS

Ketamine appeared to impair perceptual grouping in this paradigm, while the GABA agonist chlordiazepoxide enhanced grouping even in the presence of non-selective effects.

CONCLUSIONS

In general, these findings support the theory that NMDA antagonists may disrupt visual grouping by proximity and highlight a potential beneficial effect of enhanced GABA activity in perception. However, additional research will be required to confirm the stimulus selectivity of this effect, and the clinical significance of this approach.

A conceptual framework of computations in mid-level vision

If a picture is worth a thousand words, as an English idiom goes, what should those words-or, rather, descriptors-capture? What format of image representation would be sufficiently rich if we were to reconstruct the essence of images from their descriptors? In this paper, we set out to develop a conceptual framework that would be: (i) biologically plausible in order to provide a better mechanistic understanding of our visual system; (ii) sufficiently robust to apply in practice on realistic images; and (iii) able to tap into underlying structure of our visual world. We bring forward three key ideas. First, we argue that surface-based representations are constructed based on feature inference from the input in the intermediate processing layers of the visual system. Such representations are computed in a largely pre-semantic (prior to categorization) and pre-attentive manner using multiple cues (orientation, color, polarity, variation in orientation, and so on), and explicitly retain configural relations between features. The constructed surfaces may be partially overlapping to compensate for occlusions and are ordered in depth (figure-ground organization). Second, we propose that such intermediate representations could be formed by a hierarchical computation of similarity between features in local image patches and pooling of highly-similar units, and reestimated via recurrent loops according to the task demands. Finally, we suggest to use datasets composed of realistically rendered artificial objects and surfaces in order to better understand a model's behavior and its limitations.

Early recurrent feedback facilitates visual object recognition under challenging conditions

Standard models of the visual object recognition pathway hold that a largely feedforward process from the retina through inferotemporal cortex leads to object identification. A subsequent feedback process originating in frontoparietal areas through reciprocal connections to striate cortex provides attentional support to salient or behaviorally-relevant features. Here, we review mounting evidence that feedback signals also originate within extrastriate regions and begin during the initial feedforward process. This feedback process is temporally dissociable from attention and provides important functions such as grouping, associational reinforcement, and filling-in of features. Local feedback signals operating concurrently with feedforward processing are important for object identification in noisy real-world situations, particularly when objects are partially occluded, unclear, or otherwise ambiguous. Altogether, the dissociation of early and late feedback processes presented here expands on current models of object identification, and suggests a dual role for descending feedback projections.

Cognitive unbinding: a neuroscientific paradigm of general anesthesia and related states of unconsciousness

"Cognitive unbinding" refers to the impaired synthesis of specialized cognitive activities in the brain and has been proposed as a mechanistic paradigm of unconsciousness. This article draws on recent neuroscientific data to revisit the tenets and predictions of cognitive unbinding, using general anesthesia as a representative state of unconsciousness. Current evidence from neuroimaging and neurophysiology supports the proposition that cognitive unbinding is a parsimonious explanation for the direct mechanism (or "proximate cause") of anesthetic-induced unconsciousness across multiple drug classes. The relevance of cognitive unbinding to sleep, disorders of consciousness, and psychological processes is also explored. It is concluded that cognitive unbinding is a viable neuroscientific framework for unconscious processes across the fields of anesthesiology, sleep neurobiology, neurology and psychoanalysis.

Recurrent Processing during Object Recognition

How does the brain learn to recognize objects visually, and perform this difficult feat robustly in the face of many sources of ambiguity and variability? We present a computational model based on the biology of the relevant visual pathways that learns to reliably recognize 100 different object categories in the face of naturally occurring variability in location, rotation, size, and lighting. The model exhibits robustness to highly ambiguous, partially occluded inputs. Both the unified, biologically plausible learning mechanism and the robustness to occlusion derive from the role that recurrent connectivity and recurrent processing mechanisms play in the model. Furthermore, this interaction of recurrent connectivity and learning predicts that high-level visual representations should be shaped by error signals from nearby, associated brain areas over the course of visual learning. Consistent with this prediction, we show how semantic knowledge about object categories changes the nature of their learned visual representations, as well as how this representational shift supports the mapping between perceptual and conceptual knowledge. Altogether, these findings support the potential importance of ongoing recurrent processing throughout the brain's visual system and suggest ways in which object recognition can be understood in terms of interactions within and between processes over time.