core/image

Insert an image to make a visual statement.

Image

Patient in ‘vegetative state’ not just aware, but paying attention

0071: Patient in ‘vegetative state’ not just aware, but paying attention

core/embed

<figure class="wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio"><div class="wp-block-embed__wrapper">
https://www.youtube.com/watch?v=oNhcpOIQCNs
</div></figure>

Add a block that displays content pulled from other sites, like Twitter, Instagram or YouTube.

Embed

The Waterfall Motion Aftereffect Illusion

0069: The Waterfall Motion Aftereffect Illusion

<figure class="wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-4-3 wp-has-aspect-ratio"><div class="wp-block-embed__wrapper">
https://www.youtube.com/watch?v=hb7tjqhfDus
</div></figure>

Neurons from a fetal animal growing in tissue culture

0063: Neurons from a fetal animal growing in tissue culture

<figure class="wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio"><div class="wp-block-embed__wrapper">
https://www.youtube.com/watch?v=1qhqZ9ECm70
</div></figure>

core/paragraph

<p>See how a small team of artists were able to blur the line between real and rendered in NVIDIA’s <a href="https://www.youtube.com/hashtag/gtc21">#GTC21</a> keynote in this behind-the-scenes documentary.</p>

See how a small team of artists were able to blur the line between real and rendered in NVIDIA’s <a href="https://www.youtube.com/hashtag/gtc21">#GTC21</a> keynote in this behind-the-scenes documentary.

Start with the building block of all narrative.

Paragraph

NVIDA - Connecting in the Metaverse: The Making of the GTC Keynote 

0054: NVIDA – Connecting in the Metaverse: The Making of the GTC Keynote

<figure class="wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio"><div class="wp-block-embed__wrapper">
https://www.youtube.com/watch?v=KHMwq9pv7mg
</div></figure>

From Motor Control to Team Play in Simulated Humanoid Football

0027: From Motor Control to Team Play in Simulated Humanoid Football

The eHMI: How Autonomous Cars Will Communicate With the Outside World

0026: Humans in Car Seat Costumes Simulating Fully Autonomous Vehicles

<figure class="wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio"><div class="wp-block-embed__wrapper">
https://www.youtube.com/watch?v=0qPuFbEhRhw&amp;t=15s
</div></figure>

Las Vegas filmed at midnight with Night Vision color camera x27

0045: Seven Magic Mountains Las Vegas filmed at midnight with Night Vision color camera x27

core/gallery

<p>Since its introduction in 1957, the Mooney test has continued to see active use in studies of visual perception, in studies using brain imaging, and in clinical research. Mooney’s original version is of limited length, however, and was designed to be administered by time-consuming personal interview. We have developed a new, extended version of the Mooney test that is suitable for online testing and for use in a test–retest paradigm. The Mooney–Verhallen Test (MVT) comprises 144 trials, takes on average less than 10&nbsp;min to complete, and has a Spearman–Brown-corrected test–retest reliability of&nbsp;<em>ρ</em>&nbsp;= .89. We outline our methods for developing the stimuli and for selecting the final stimulus set, and we present the results from two rounds of testing on two independent samples of 374 participants and 505 participants, respectively. The test is freely available for scientific use.</p>

Display multiple images in a rich gallery.

Gallery

Since its introduction in 1957, the Mooney test has continued to see active use in studies of visual perception, in studies using brain imaging, and in clinical research. Mooney’s original version is of limited length, however, and was designed to be administered by time-consuming personal interview. We have developed a new, extended version of the Mooney test that is suitable for online testing and for use in a test–retest paradigm. The Mooney–Verhallen Test (MVT) comprises 144 trials, takes on average less than 10&nbsp;min to complete, and has a Spearman–Brown-corrected test–retest reliability of&nbsp;<em>ρ</em>&nbsp;= .89. We outline our methods for developing the stimuli and for selecting the final stimulus set, and we present the results from two rounds of testing on two independent samples of 374 participants and 505 participants, respectively. The test is freely available for scientific use.

A New Mooney Test R. J. Verhallen & J. D. Mollon  Behavior Research Methods (October 2015)

0033: A New Mooney Test (2015)

core/quote

<blockquote class="wp-block-quote"><p><strong>Figure 5. Demonstration of the Influence of Associative Pictorial Recall (Top-Down Signaling) on the Interpretation of a Retinal Stimulus (Bottom-Up Signaling)</strong></p><p><br>To most observers, this figure initially appears as a random pattern with no clear figural interpretation. The perceptual experience elicited by this stimulus is radically (and perhaps permanently) different after viewing the pattern shown in&nbsp;Figure 8.</p></blockquote>

<blockquote class="wp-block-quote"><p><strong>Figure 8. Demonstration of the Influence of Associative Pictorial Recall (Top-Down Signaling) on the Interpretation of a Retinal Stimulus (Bottom-Up Signaling)</strong></p><p><br>Most observers will experience a clear meaningful percept upon viewing this pattern. After achieving this percept, refer back to&nbsp;Figure 5. The perceptual interpretation of the pattern should now be markedly different, with a figural interpretation that is driven largely by imaginal influences drawn from memory.</p></blockquote>

Give quoted text visual emphasis. "In quoting others, we cite ourselves." — Julio Cortázar

Quote

On the Perception of Probable Things: Neural Substrates of Associative Memory, Imagery, and Perception (Neuron, 2012) - Thomas D. Albright

0042: On the Perception of Probable Things

core/freeform

Classic Block

0025: Turner’s Perspective Lectures Diagrams

Hubel and Wiesel and the discovery of orientation selectivity in the receptive fields of V1

0005: Hubel and Wiesel

Depth Invariance In Object Recognition

0004: Depth Invariance In Object Recognition

<p><strong>Orientation Variability</strong></p>

<p>Objects can be more readily identified from some orientations compared with others (Palmer, Rosch, &amp; Chase, 1981). According to the RBC hypothesis [<strong>Recognition-by-Components</strong>], difficult views will be those in which the components extracted from the image are not the components (and their relations) in the representation of the object. Often such mismatches will arise from an "<em>accident</em>" of viewpoint where an image property is not correlated with the property in the three-dimensional world. For example, when the viewpoint in the image is along the axis of the major components of the object, the resultant foreshortening converts one or some of the components into surface components, such as disks and rectangles in Figure 27, which are not included in the com- potential description of the object. In addition, as illustrated in Figure 27, the surfaces may occlude otherwise diagnostic components. Consequently, the components extracted from the image will not readily match the mental representation of the object and identification will be much more difficult compared to an orientation, such as that shown in Figure 28, which does convey the components.</p>

Objects can be more readily identified from some orientations compared with others (Palmer, Rosch, &amp; Chase, 1981). According to the RBC hypothesis [<strong>Recognition-by-Components</strong>], difficult views will be those in which the components extracted from the image are not the components (and their relations) in the representation of the object. Often such mismatches will arise from an "<em>accident</em>" of viewpoint where an image property is not correlated with the property in the three-dimensional world. For example, when the viewpoint in the image is along the axis of the major components of the object, the resultant foreshortening converts one or some of the components into surface components, such as disks and rectangles in Figure 27, which are not included in the com- potential description of the object. In addition, as illustrated in Figure 27, the surfaces may occlude otherwise diagnostic components. Consequently, the components extracted from the image will not readily match the mental representation of the object and identification will be much more difficult compared to an orientation, such as that shown in Figure 28, which does convey the components.

Recognition-by-Components: A Theory of Human Image Understanding, Irving Biederman (Pyschological Review 1987, Vol. M , No. 2, 115-147)

0003: Recognition-by-Components: A Theory of Human Image Understanding (Extract)

<figure class="wp-block-embed alignwide is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-4-3 wp-has-aspect-ratio"><div class="wp-block-embed__wrapper">
https://www.youtube.com/watch?v=CNZA6yGGOYc
</div></figure>