Smart search: Investigations into human visual search in structured environments

To us, visual search for objects in the environment feels effortless as compared to other tasks such as multiplying large numbers. However, our efforts at building artificial systems have revealed that the former is computationally more challenging than the latter. That makes us wonder how our brain efficiently carries out visual searches. Decades of research indicate that the efficiency of human visual search relies on a plethora of processes, primary of which are: one, processing the hierarchical construction of the visual world (simple features such as orientations of lines constituting complex features such as shapes), two, selectively processing information relevant to the search task (e.g., suppress processing from parts of the image that contain non-target features), and three, learning the relationships between the constituent elements of the world that can guide the information selection process (e.g., knowing where an object occurs in a scene helps us constrain the search to those locations). Furthering our understanding of the processes underlying efficient search, I present new evidence using artificial neural networks, neuroimaging experiments (fMRI and EEG), and large-scale behavioral experiments. The main contributions are as follows: one, the search for body shapes can occur parallelly across our field of view; two, where selective attention needs to be deployed in a hierarchical visual system depends on the representational capacity of that visual system; three, the knowledge about the co-occurrences amongst the distractors can be learned and utilized to increase our search efficiency. I conclude the thesis by discussing the questions raised through our investigations and the research directions aimed at furthering our understanding of our seemingly effortless, but smart, visual search capabilities

Body shape as a visual feature: Evidence from spatially-global attentional modulation in human visual cortex

Raw fMRI data accompanying the NeuroImage 2022 paper. Information about the structure of data acquisition (run types, etc.) can be found in the paper. Processed data (to produce the figures in the paper and any further analysis) can be found on OSF: https://doi.org/10.17605/OSF.IO/HJ5VCFeature-based attention modulates visual processing beyond the focus of spatial attention. Previous work has reported such spatially-global effects for low-level features such as color and orientation, as well as for faces. Here, using fMRI, we provide evidence for spatially-global attentional modulation for human bodies. Participants were cued to search for one of six object categories in two vertically-aligned images. Two additional, horizontally-aligned, images were simultaneously presented but were never task-relevant across three experimental sessions. Analyses time-locked to the objects presented in these task-irrelevant images revealed that responses evoked by body silhouettes were modulated by the participants’ top-down attentional set, becoming more body-selective when participants searched for bodies in the task-relevant images. These effects were observed both in univariate analyses of the body-selective cortex and in multivariate analyses of the object-selective visual cortex. Additional analyses showed that this modulation reflected response gain rather than a bias induced by the cues, and that it reflected enhancement of body responses rather than suppression of non-body responses. These findings provide evidence for a spatially-global attention mechanism for body shapes, supporting the rapid and parallel detection of conspecifics in our environment

Body shape as a visual feature: Evidence from spatially-global attentional modulation in human visual cortex

Feature-based attention modulates visual processing beyond the focus of spatial attention. Previous work has reported such spatially-global effects for low-level features such as color and orientation, as well as for faces. Here, using fMRI, we provide evidence for spatially-global attentional modulation for human bodies. Participants were cued to search for one of six object categories in two vertically-aligned images. Two additional, horizontally-aligned, images were simultaneously presented but were never task-relevant across three experimental sessions. Analyses time-locked to the objects presented in these task-irrelevant images revealed that responses evoked by body silhouettes were modulated by the participants’ top-down attentional set, becoming more body-selective when participants searched for bodies in the task-relevant images. These effects were observed both in univariate analyses of the body-selective cortex and in multivariate analyses of the object-selective visual cortex. Additional analyses showed that this modulation reflected response gain rather than a bias induced by the cues, and that it reflected enhancement of body responses rather than suppression of non-body responses. These findings provide evidence for a spatially-global attention mechanism for body shapes, supporting the rapid and parallel detection of conspecifics in our environment

Statistical learning of distractor co-occurrences facilitates visual search

Visual search is facilitated by knowledge of the relationship between the target and the distractors, including both where the target is likely to be among the distractors and how it differs from the distractors. Whether the statistical structure among distractors themselves, unrelated to target properties, facilitates search is less well understood. Here, we assessed the benefit of distractor structure using novel shapes whose relationship to each other was learned implicitly during visual search. Participants searched for target items in arrays of shapes that comprised either four pairs of co-occurring distractor shapes (structured scenes) or eight distractor shapes randomly partitioned into four pairs on each trial (unstructured scenes). Across five online experiments (N = 1,140), we found that after a period of search training, participants were more efficient when searching for targets in structured than unstructured scenes. This structure benefit emerged independently of whether the position of the shapes within each pair was fixed or variable and despite participants having no explicit knowledge of the structured pairs they had seen. These results show that implicitly learned co-occurrence statistics between distractor shapes increases search efficiency. Increased efficiency in the rejection of regularly co-occurring distractors may contribute to the efficiency of visual search in natural scenes, where such regularities are abundant

The nature of the animacy organization in human ventral temporal cortex

Contains fulltext : 213574.pdf (Publisher’s version ) (Open Access)The principles underlying the animacy organization of the ventral temporal cortex (VTC) remain hotly debated, with recent evidence pointing to an animacy continuum rather than a dichotomy. What drives this continuum? According to the visual categorization hypothesis, the continuum reflects the degree to which animals contain animate-diagnostic features. By contrast, the agency hypothesis posits that the continuum reflects the degree to which animals are perceived as social agents. Here, we tested both hypotheses with a stimulus set in which visual categorizability and agency were dissociated based on representations in convolutional neural networks and behavioral experiments. Using fMRI, we found that visual categorizability and agency explained independent components of the animacy continuum in VTC. Modeled together, they fully explained the animacy continuum. Further analyses revealed that the clusters explained by visual categorizability were localized posterior to the clusters explained by agency. These results provide evidence for multiple animacy continua in VTC that follow different organizational principles.Conference on Cognitive Computational Neuroscience (Berlin, Germany, 13-16 September 2019

The functional role of cue-driven feature-based feedback in object recognition

Contains fulltext : 198424pub.pdf (publisher's version ) (Open Access)Visual object recognition is not a trivial task, especially when the objects are degraded or surrounded by clutter or presented briefly. External cues (such as verbal cues or visual context) can boost recognition performance in such conditions. In this work, we build an artificial neural network to model the interaction between the object processing stream (OPS) and the cue. We study the effects of varying neural and representational capacities of the OPS on the performance boost provided by cue-driven feature- based feedback in the OPS. We observe that the feedback provides performance boosts only if the category-specific features about the objects cannot be fully represented in the OPS. This representational limit is more dependent on task demands than neural capacity. We also observe that the feedback scheme trained to maximise recognition performance boost is not the same as tuning-based feedback, and actually performs better than tuning-based feedback.2018 Conference on Cognitive Computational Neuroscience, 5-8 September 2018, Philadelphia, Pennsylvani

Modulation of early visual processing alleviates capacity limits in solving multiple tasks

Item does not contain fulltextIn daily life situations, we have to perform multiple tasks given a visual stimulus, which requires task-relevant information to be transmitted through our visual system. When it is not possible to transmit all the possibly relevant information to higher layers, due to a bottleneck, task-based modulation of early visual processing might be necessary. In this work, we report how the effectiveness of modulating the early processing stage of an artificial neural network depends on the information bottleneck faced by the network. The bottleneck is quantified by the number of tasks the network has to perform and the neural capacity of the later stage of the network. The effectiveness is gauged by the performance on multiple object detection tasks, where the network is trained with a recent multi-task optimization scheme. By associating neural modulations with task-based \textit{switching} of the state of the network and characterizing when such switching is helpful in early processing, our results provide a functional perspective towards understanding why task-based modulation of early neural processes might be observed in the primate visual cortex.Conference on Cognitive Computational Neuroscience (Berlin, Germany, 13-16 September 2019

Desert Friendly Animal - The Camel

[Vet World 2009; 2(6.000): 240-241

Розмірно-залежні фізичні властивості металевих плівок: аналіз теплових і механічних характеристик у нанорозмірному режимі

Металеві плівки - тонкі шари металу, нанесені на поверхні, мають широкий спектр використання в багатьох секторах. Металеві плівки, як правило, виготовляються шляхом напилення або хімічного осадження з парової фази і відіграють важливу роль в електроніці, оптиці та покриттях. Їх фундаментальна провідність, відбивна здатність і здатність до адаптації є важливими для розробки інноваційних матеріалів і систем. Проведено дослідження жорсткості, оптичної відбивної здатності, температуропровідності та енергетичної рухливості металевих плівок. На вищевказані властивості впливає товщина шару, склад і процеси осадження. Розуміння складності цих фізичних особливостей має вирішальне значення для модифікації металевих плівок для конкретних застосувань, що стимулює технологічні та матеріалознавчі інновації. У цьому дослідженні були оцінені фізичні характеристики металевих плівок, товщина яких 20-200 нм. Запропоновано методи визначення температурно-залежних коефіцієнтів опору, теплопровідності, теплопровідності та теплопровідності плівок Cu, Al. Швидке нагрівання, яке спостерігається за короткий проміжок часу, дозволяє першочергово оцінити теплові характеристики металевого шару без впливу на підкладку.Metallic films, which are thin layers of metal deposited on surfaces, have a wide range of uses in many sectors. Metallic films are usually produced by sputtering or chemical vapor deposition and serve an important role in electronics, optics and coatings. Their fundamental conductivity, reflective qualities and adaptability makes important for the development of innovative materials and systems. Investigations are conducted on the rigidity, optical reflecting power, temperature conductivity and power mobility of metallic films. These attributes are affected by layer thickness, composition and deposition processes. Understanding the complexities of these physical features is critical for modifying metallic films to particular applications, which drives technological and material science innovation. In this research, the physical characteristics of metallic films, which are thinner than 20 – 200 nm were evaluated. The suggested methods for determining the Cu, and Al films temperature-dependent coefficients of resistance, thermal conductivity properties, particular heat and thermal diffusivity. The rapid amount of heating that is observed in a brief period allows the thermal characteristics of the metallic layer to be primarily evaluated without impacting the substrate