scholarly journals A connectivity-constrained computational account of topographic organization in high-level visual cortex

2021 ◽  
Author(s):  
Nicholas M Blauch ◽  
Marlene Behrmann ◽  
David Plaut
Keyword(s):  
Visual Processing ◽  
Spatial Organization ◽  
Functional Organization ◽  
Spatial Clusters ◽  
Feature Extracting ◽  
Domain Specific ◽  
Visual Processes ◽  
Topographic Organization ◽  
High Level ◽  
Multiple Domain

Inferotemporal cortex (IT) in humans and other primates is topographically organized, with multiple domain-selective areas and other general patterns of functional organization. What factors underlie this organization, and what can this neural arrangement tell us about the mechanisms of high level vision? Here, we present an account of topographic organization involving a computational model with two components: 1) a feature-extracting encoder model of early visual processes, followed by 2) a model of high-level hierarchical visual processing in IT subject to specific biological constraints. In particular, minimizing the wiring cost on spatially organized feedforward and lateral connections within IT, combined with constraining the feedforward processing to be strictly excitatory, results in a hierarchical, topographic organization. This organization replicates a number of key properties of primate IT cortex, including the presence of domain-selective spatial clusters preferentially involved in the representation of faces, objects, and scenes, within-domain topographic organization such as animacy and indoor/outdoor distinctions, and generic spatial organization whereby the response correlation of pairs of units falls off with their distance. The model supports a view in which both domain-specific and domain-general topographic organization arise in the visual system from an optimization process that maximizes behavioral performance while minimizing wiring costs.

scholarly journals A connectivity-constrained computational account of topographic organization in primate high-level visual cortex

2022 ◽  
Vol 119 (3) ◽  
pp. e2112566119
Author(s):  
Nicholas M. Blauch ◽  
Marlene Behrmann ◽  
David C. Plaut
Keyword(s):  
Computational Models ◽  
Spatial Organization ◽  
Behavioral Performance ◽  
Spatial Clusters ◽  
Neuronal Connectivity ◽  
Cortical Organization ◽  
Domain Specific ◽  
Topographic Organization ◽  
High Level ◽  
Multiple Domains

Inferotemporal (IT) cortex in humans and other primates is topographically organized, containing multiple hierarchically organized areas selective for particular domains, such as faces and scenes. This organization is commonly viewed in terms of evolved domain-specific visual mechanisms. Here, we develop an alternative, domain-general and developmental account of IT cortical organization. The account is instantiated in interactive topographic networks (ITNs), a class of computational models in which a hierarchy of model IT areas, subject to biologically plausible connectivity-based constraints, learns high-level visual representations optimized for multiple domains. We find that minimizing a wiring cost on spatially organized feedforward and lateral connections, alongside realistic constraints on the sign of neuronal connectivity within model IT, results in a hierarchical, topographic organization. This organization replicates a number of key properties of primate IT cortex, including the presence of domain-selective spatial clusters preferentially involved in the representation of faces, objects, and scenes; columnar responses across separate excitatory and inhibitory units; and generic spatial organization whereby the response correlation of pairs of units falls off with their distance. We thus argue that topographic domain selectivity is an emergent property of a visual system optimized to maximize behavioral performance under generic connectivity-based constraints.

scholarly journals From Intermodulation Components to Perception and Cognition- a Review

2019 ◽  
Author(s):  
Noam Gordon ◽  
Jakob Hohwy ◽  
Matthew James Davidson ◽  
Jeroen van Boxtel ◽  
Naotsugu Tsuchiya
Keyword(s):  
Visual Processing ◽  
Future Directions ◽  
Complex Interactions ◽  
Visual Processes ◽  
Neural Integration ◽  
Neuroimaging Data ◽  
Neural Interactions ◽  
Integration Mechanisms ◽  
High Level ◽  
The Brain

Perception results from complex interactions among sensory and cognitive processes across hierarchical levels in the brain. Intermodulation (IM) components, used in frequency tagging neuroimaging designs, have emerged as a promising direct measure of such neural interactions. IMs have initially been used in electroencephalography (EEG) to investigate low-level visual processing. In a more recent trend, IMs in EEG and other neuroimaging methods are being used to shed light on mechanisms of mid- and high-level perceptual processes, including the involvement of cognitive functions such as attention and expectation. Here, we provide an account of various mechanisms that may give rise to IMs in neuroimaging data, and what these IMs may look like. We discuss methodologies that can be implemented for different uses of IMs and we demonstrate how IMs can provide insights into the existence, the degree and the type of neural integration mechanisms at hand. We then review a range of recent studies exploiting IMs in perception research, placing an emphasis on high-level visual processes. We conclude by suggesting future directions that can enhance the benefits of IM-methodology in perception research.

Featural and Configural Processing of Faces and Houses in Matched Dyslexic and Typical Readers

2020 ◽  
Author(s):  
Bahareh Jozranjbar ◽  
Arni Kristjansson ◽  
Heida Maria Sigurdardottir
Keyword(s):  
Object Recognition ◽  
Visual Processing ◽  
Reading Ability ◽  
Visual Recognition ◽  
Reading Deficits ◽  
Domain Specific ◽  
Configural Information ◽  
Lower House ◽  
Single Process ◽  
Processing Mechanisms

While dyslexia is typically described as a phonological deficit, recent evidence suggests that ventral stream regions, important for visual categorization and object recognition, are hypoactive in dyslexic readers who might accordingly show visual recognition deficits. By manipulating featural and configural information of faces and houses, we investigated whether dyslexic readers are disadvantaged at recognizing certain object classes or utilizing particular visual processing mechanisms. Dyslexic readers found it harder to recognize objects (houses), suggesting that visual problems in dyslexia are not completely domain-specific. Mean accuracy for faces was equivalent in the two groups, compatible with domain-specificity in face processing. While face recognition abilities correlated with reading ability, lower house accuracy was nonetheless related to reading difficulties even when accuracy for faces was kept constant, suggesting a specific relationship between visual word recognition and the recognition of non-face objects. Representational similarity analyses (RSA) revealed that featural and configural processes were clearly separable in typical readers, while dyslexic readers appeared to rely on a single process. This occurred for both faces and houses and was not restricted to particular visual categories. We speculate that reading deficits in some dyslexic readers reflect their reliance on a single process for object recognition.

scholarly journals Distributed Simulation Platforms and Data Passing Tools for Natural Hazards Engineering: Reviews, Limitations, and Recommendations

2021 ◽  
Author(s):  
Lichao Xu ◽  
Szu-Yun Lin ◽  
Andrew W. Hlynka ◽  
Hao Lu ◽  
Vineet R. Kamat ◽  
...  
Keyword(s):  
Natural Hazards ◽  
Data Exchange ◽  
Distributed Simulation ◽  
Distributed Data ◽  
Interactive Simulation ◽  
Integrated Simulation ◽  
Domain Specific ◽  
Advantages And Disadvantages ◽  
High Level ◽  
Data Passing

AbstractThere has been a strong need for simulation environments that are capable of modeling deep interdependencies between complex systems encountered during natural hazards, such as the interactions and coupled effects between civil infrastructure systems response, human behavior, and social policies, for improved community resilience. Coupling such complex components with an integrated simulation requires continuous data exchange between different simulators simulating separate models during the entire simulation process. This can be implemented by means of distributed simulation platforms or data passing tools. In order to provide a systematic reference for simulation tool choice and facilitating the development of compatible distributed simulators for deep interdependent study in the context of natural hazards, this article focuses on generic tools suitable for integration of simulators from different fields but not the platforms that are mainly used in some specific fields. With this aim, the article provides a comprehensive review of the most commonly used generic distributed simulation platforms (Distributed Interactive Simulation (DIS), High Level Architecture (HLA), Test and Training Enabling Architecture (TENA), and Distributed Data Services (DDS)) and data passing tools (Robot Operation System (ROS) and Lightweight Communication and Marshalling (LCM)) and compares their advantages and disadvantages. Three specific limitations in existing platforms are identified from the perspective of natural hazard simulation. For mitigating the identified limitations, two platform design recommendations are provided, namely message exchange wrappers and hybrid communication, to help improve data passing capabilities in existing solutions and provide some guidance for the design of a new domain-specific distributed simulation framework.

scholarly journals Temporal Processing Capacity in High-Level Visual Cortex Is Domain Specific

2015 ◽  
Vol 35 (36) ◽  
pp. 12412-12424 ◽  
Author(s):  
A. Stigliani ◽  
K. S. Weiner ◽  
K. Grill-Spector
Keyword(s):  
Visual Cortex ◽  
Temporal Processing ◽  
Processing Capacity ◽  
Domain Specific ◽  
High Level

scholarly journals The role of prefrontal cortex in working memory: examining the contents of consciousness

1998 ◽  
Vol 353 (1377) ◽  
pp. 1819-1828 ◽  
Author(s):  
◽  
S. M. Courtney ◽  
L. Petit ◽  
J. V. Haxby ◽  
L. G. Ungerleider
Keyword(s):  
Working Memory ◽  
Prefrontal Cortex ◽  
Visual Processing ◽  
Right Hemisphere ◽  
Functional Organization ◽  
Spatial Working Memory ◽  
Domain Specificity ◽  
Long Term Memory ◽  
Present Evidence ◽  
The Right

Working memory enables us to hold in our ‘mind's eye’ the contents of our conscious awareness, even in the absence of sensory input, by maintaining an active representation of information for a brief period of time. In this review we consider the functional organization of the prefrontal cortex and its role in this cognitive process. First, we present evidence from brain–imaging studies that prefrontal cortex shows sustained activity during the delay period of visual working memory tasks, indicating that this cortex maintains on–line representations of stimuli after they are removed from view. We then present evidence for domain specificity within frontal cortex based on the type of information, with object working memory mediated by more ventral frontal regions and spatial working memory mediated by more dorsal frontal regions. We also propose that a second dimension for domain specificity within prefrontal cortex might exist for object working memory on the basis of the type of representation, with analytic representations maintained preferentially in the left hemisphere and image–based representations maintained preferentially in the right hemisphere. Furthermore, we discuss the possibility that there are prefrontal areas brought into play during the monitoring and manipulation of information in working memory in addition to those engaged during the maintenance of this information. Finally, we consider the relationship of prefrontal areas important for working memory, both to posterior visual processing areas and to prefrontal areas associated with long–term memory.

scholarly journals The Rapid Extraction of Gist—Early Neural Correlates of High-level Visual Processing

2012 ◽  
Vol 24 (2) ◽  
pp. 521-529 ◽  
Author(s):  
Frank Oppermann ◽  
Uwe Hassler ◽  
Jörg D. Jescheniak ◽  
Thomas Gruber
Keyword(s):  
Visual Processing ◽  
Time Course ◽  
Occipital Cortex ◽  
Stimulus Onset ◽  
Gamma Band ◽  
Oscillatory Activity ◽  
Rapid Extraction ◽  
The Right ◽  
High Level ◽  
Individual Objects

The human cognitive system is highly efficient in extracting information from our visual environment. This efficiency is based on acquired knowledge that guides our attention toward relevant events and promotes the recognition of individual objects as they appear in visual scenes. The experience-based representation of such knowledge contains not only information about the individual objects but also about relations between them, such as the typical context in which individual objects co-occur. The present EEG study aimed at exploring the availability of such relational knowledge in the time course of visual scene processing, using oscillatory evoked gamma-band responses as a neural correlate for a currently activated cortical stimulus representation. Participants decided whether two simultaneously presented objects were conceptually coherent (e.g., mouse–cheese) or not (e.g., crown–mushroom). We obtained increased evoked gamma-band responses for coherent scenes compared with incoherent scenes beginning as early as 70 msec after stimulus onset within a distributed cortical network, including the right temporal, the right frontal, and the bilateral occipital cortex. This finding provides empirical evidence for the functional importance of evoked oscillatory activity in high-level vision beyond the visual cortex and, thus, gives new insights into the functional relevance of neuronal interactions. It also indicates the very early availability of experience-based knowledge that might be regarded as a fundamental mechanism for the rapid extraction of the gist of a scene.

Similarity of Computations Across Domains Does Not Imply Shared Implementation: The Case of Language Comprehension

2021 ◽  
Vol 30 (6) ◽  
pp. 526-534
Author(s):  
Evelina Fedorenko ◽  
Cory Shain
Keyword(s):  
Language Processing ◽  
Language Comprehension ◽  
Fluid Intelligence ◽  
Linguistic Knowledge ◽  
Domain Specific ◽  
Cognitive Operations ◽  
High Level ◽  
General Circuits ◽  
The Mind ◽  
Language Network

Understanding language requires applying cognitive operations (e.g., memory retrieval, prediction, structure building) that are relevant across many cognitive domains to specialized knowledge structures (e.g., a particular language’s lexicon and syntax). Are these computations carried out by domain-general circuits or by circuits that store domain-specific representations? Recent work has characterized the roles in language comprehension of the language network, which is selective for high-level language processing, and the multiple-demand (MD) network, which has been implicated in executive functions and linked to fluid intelligence and thus is a prime candidate for implementing computations that support information processing across domains. The language network responds robustly to diverse aspects of comprehension, but the MD network shows no sensitivity to linguistic variables. We therefore argue that the MD network does not play a core role in language comprehension and that past findings suggesting the contrary are likely due to methodological artifacts. Although future studies may reveal some aspects of language comprehension that require the MD network, evidence to date suggests that those will not be related to core linguistic processes such as lexical access or composition. The finding that the circuits that store linguistic knowledge carry out computations on those representations aligns with general arguments against the separation of memory and computation in the mind and brain.

scholarly journals Driving and visual deficits in stroke patients

2018 ◽  
Vol 76 (2) ◽  
pp. 85-88 ◽  
Author(s):  
Marina Marcondes Braga ◽  
Renato Nickel ◽  
Marcos Lange ◽  
Élcio Juliato Piovesan
Keyword(s):  
High Risk ◽  
Visual Attention ◽  
Visual Processing ◽  
Moderate Risk ◽  
Interference Factor ◽  
Visual Deficits ◽  
Useful Field Of View ◽  
High Level ◽  
Safe Performance ◽  
Intention Group

ABSTRACT Objective: The aim of the present study was to conduct an exploratory assessment of visual impairment following stroke, and to discuss the possibilities of reintroducing patients to the activity of driving. Methods: The Useful Field of View test was used to assess visual processing and visual attention. Results: A total of 18 patients were included in the study, and were assigned to either the drive group (n = 9) or the intention group (n = 9). In the drive group, one patient was categorized as moderate-to-high risk; whereas, in the intention group, one patient was categorized as low-to-moderate risk. Additionally, two patients in the intention group were categorized as high risk. The patients did not perceive their visual deficits as a limitation. Conclusion: Visual attention is an interference factor in terms of the safe performance of driving after a stroke. All patients showed a high level of interest for the independence provided through being able to drive.

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