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15 results for “Gestalt”
Figure 11. Cognitive architecture of the process of social signals perception-Gestalt Processing in Human-Robot Interaction: A Novel Account for Autism Research
<p>A possible cognitive architecture and formalization of the process of learning via<br> multisensory integration is presented in figure 11. The formal description of the proposed cognitive<br> architecture, capable of interpreting social-communication signals, signs and symbols, is based on<br> multisensory integration at the level of perception, parallel processing at the level of interpretation<br> and decision making followed by verbalization, as well as performing an action (eye contact,<br> gesture, mimicking) at the level of behaviour.</p>
Figure 9. The impossible figure (right) is not noticeable as such at first glance-Gestalt Processing in Human-Robot Interaction: A Novel Account for Autism Research
<p>In the lexical domain a similar effect of holistic word processing is described in (Anstis,<br> 2005b). The viewers were presented with pairs of three-letter words in quick succession and asked<br> to report if the upper halves of the successively presented words were identical. Surprisingly, even<br> when the upper halves of the words were orthographically identical, the error rate was reliably<br> higher than expected and in comparison with matching identical successive words. As the author of<br> the study Stuart Anstis points out: “students were processing the words not as separable parts, but<br> holistically as perceptual units that could not be perceptually split apart. These results show that in<br> normal circumstances, the visual system cannot, or does not, divide words into upper and lower<br> halves” (Anstis, 2005b, p. 239).The author relates the results of his study to studies of visual<br> perception of faces as evidence that the mechanism of holistic processing in the visual and the<br> lexical domains is essentially the same.</p>
Figure 8. Machine faces, perceived as more figure-like(left) and less figure-like (right)-Gestalt Processing in Human-Robot Interaction: A Novel Account for Autism Research
<p>In an experimental study on visual perception, addressing directly Gestalt phenomena, a new<br> Gestalt cue for figure-ground assignment was introduced (Vechera et al., 2002). The foreground<br> versus the background organization is a strong determinant for decisions on objects seen among<br> image elements. A well-known set of perceptual cues that are often called Gestalt cues are the size<br> or area, the symmetry and the convexity vs. concavity judgments. It is generally assumed that<br> figures are ‘small, symmetrical and convex’. The authors asked the question whether these cues are<br> all that are necessary for a region of the image to be judged as a figure. The main result of this study<br> is that regions in the lower portion of a stimulus array appear more figure-like than regions in the<br> upper portion of the display.</p>
Figure 6. Noticeable subjective response to the distorted face to the right-Gestalt Processing in Human-Robot Interaction: A Novel Account for Autism Research
<p>Quite surprisingly, if the distortion is viewed in the normal upward position, it evokes strong<br> emotional response to the distorted face to the right in figure 6.</p>
Figure 5. The distortion is barely noticeable if the faces are viewed in the reversed position-Gestalt Processing in Human-Robot Interaction: A Novel Account for Autism Research
<p>According to the feature-based processing theories of human faces the main elements,<br> noticed and remembered in a face, are the eyes, the nose and the mouth (Thompson, 1980; Anstis,<br> 2005a). If, however, we distort some of the elements of a face, these should influence perception,regardless of the position of the image – upright or reversed – from the observer viewpoint. Figure 5<br> presents the reversed image of the face on the left and the reversed distorted face on the right. The<br> distortion was achieved by rotating the eyes of the image in the vertical direction.<br> Figure</p>
Figure 4. Main elements of a face, according to the feature-based processing theories-Gestalt Processing in Human-Robot Interaction: A Novel Account for Autism Research
<p>In 1980 Peter Thompson proposed a new experimental paradigm for investigation of<br> perception, called “face thatcherization” (also named “Thomson illusion”) (Thompson, 1980).<br> Imagine that the following face, depicted in figure 4, is a photo of the then UK Prime Minister<br> Margaret Thatcher.</p>
Figure 3. Robotic faces, similar to smiley emoticons-Gestalt Processing in Human-Robot Interaction: A Novel Account for Autism Research
<p>The smiley Gestalt is the result from a dynamic (evolved in time) cognitive process, it is<br> immediately given in cognition, memorable, emotionally rich and socially relevant and reflects the<br> special kind of Gestalt complexity as defined by Edwin Rausch (1988). Conventional representations<br> of holistic entities like smileys or novel robotic faces come to life because they capture essential<br> Gestalt qualities of the perceived image. For example, in figure 3 the robotic faces resemble the<br> smileys in terms of the evoked internal/emotional reactions.</p>
Figure 2. Taxonomy of the educational technologies for children with ASC-Gestalt Processing in Human-Robot Interaction: A Novel Account for Autism Research
<p>learner (Perlin, 1997).<br> MOSOCO is an emergent technology implemented in a smartphone called “Mobile Social<br> Compass” (Escobedo et al., 2012). Six basic social skills are being encouraged by prompting the<br> user to initiate social contact. The menu displays symbols for the basic social skills – eye contact,<br> space and proximity, start an interaction, asking questions, sharing interests and finish an<br> interaction. The MOSOCO application has turned out to be an extremely useful tool as an online<br> prompt in starting, maintaining and finishing social interaction for both typical and autistic students,<br> as well as to anyone that feels need for improving their social competence.</p>
Multiple Fingers – One Gestalt
<p>The Gestalt theory of perception offered principles by which distributed visual sensations are combined into a structured experience (“Gestalt”). We demonstrate conditions whereby haptic sensations at two fingertips are integrated in the perception of a single object. When virtual bumps were presented simultaneously to the right hand’s thumb and index finger during lateral arm movements, participants reported perceiving a single bump. A discrimination task measured the bump’s perceived location and perceptual reliability (assessed by differential thresholds) for four finger configurations, which varied in their adherence to the Gestalt principles of proximity (small vs. large finger separation) and synchrony (virtual spring to link movements of the two fingers vs. no spring). According to models of integration, reliability should increase with the degree to which multi-finger cues integrate into a unified percept. Differential thresholds were smaller in the virtual-spring condition (synchrony) than when fingers were unlinked. Additionally, in the condition with reduced synchrony, greater proximity led to lower differential thresholds. Thus, with greater adherence to Gestalt principles, thresholds approached values predicted for optimal integration. We conclude that the Gestalt principles of synchrony and proximity apply to haptic perception of surface properties and that these principles can interact to promote multi-finger integration.</p> <p><strong>Lezkan</strong>, A. Manuel, S.G. Colgate, J.E., Klatzky, R.L,. Peshkin, M.A. & <strong>Drewing</strong>, K. (2016). Multiple Fingers – One Gestalt. <em>IEEE Transactions on Haptics,</em> <em>9</em>(2), 255-266.</p> <p>The Zip file contains all data relative to the publication.</p> <p>A description of the variables is contained in the file VARIABLE_CODES.txt</p>
THE ROLE OF GESTALT IN THE REALIZATION OF CONCEPTS THROUGH SIMILARITIES
Open the record for dataset details and reuse information.
A Study to Determine the Role of Physician Gestalt in Predicting COVID-19 in Patients
ClinicalTrials.gov study NCT04974177. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Genetic and Epigenetic Signatures of Translational Aging Laboratory Testing (GESTALT)
ClinicalTrials.gov study NCT02339012. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Variants in ZFX Cause an X-linked Neurodevelopmental Disorder with Recurrent Facial Gestalt
GEO Series GSE218688. Homo sapiens. 18 samples. Type: Expression profiling by high throughput sequencing.
Variants in ZFX Cause an X-linked Neurodevelopmental Disorder with Recurrent Facial Gestalt
GEO Series GSE218689. Homo sapiens. 8 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Variants in ZFX Cause an X-linked Neurodevelopmental Disorder with Recurrent Facial Gestalt
GEO Series GSE218691. Homo sapiens. 26 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.