Interactive simulation and rendering of fluids on graphics hardware

Computational uid dynamics can be used to reproduce the complex motion of fluids for use in computer graphics, but the simulation and rendering are both highly computationally intensive. In the past performing these tasks on the CPU could take many minutes per frame, especially for large scale scenes at high levels of detail, which limited their usage to offline applications such as in film and media. However, using the massive parallelism of GPUs, it is nowadays possible to produce uid visual effects in real time for interactive applications such as games. We present such an interactive simulation using the CUDA GPU computing environment and OpenGL graphics API. Smoothed Particle Hydrodynamics (SPH) is a popular particle-based fluid simulation technique that has been shown to be well suited to acceleration on the GPU. Our work extends an existing GPU-based SPH implementation by incorporating rigid body interaction and rendering. Solid objects are represented using particles to accumulate hydrodynamic forces from surrounding fluid, while motion and collision handling are handled by the Bullet Physics library on the CPU. Our system demonstrates two-way coupling with multiple objects floating, displacing fluid and colliding with each other. For rendering we compare the performance and memory consumption of two approaches, splatting and raycasting, we also describe the visual characteristics of each. In our evaluation we consider a target of between 24 and 30 fps to be sufficient for smooth interaction and aim to determine the performance impact of our new features. We begin by establishing a performance baseline and find that the original system runs smoothly up to 216,000 fluid particles but after introducing rendering this drops to 27,000 particles with the rendering taking up the majority of the frame time in both techniques. We find that the most significant limiting factor to splatting performance to be the onscreen area occupied by fluid while the raycasting performance is primarily determined by the resolution of the 3D texture used for sampling. Finally we find that performing solid interaction on the CPU is a viable approach that does not introduce significant overhead unless solid particles vastly outnumber fluid ones

Did you see it? A Python tool for psychophysical assessment of the human blind spot

The blind spot is a region in the temporal monocular visual field in humans, which corresponds to a physiological scotoma within the nasal hemi-retina. This region has no photoreceptors, so is insensitive to visual stimulation. There is no corresponding perceptual scotoma because the visual stimulation is “filled-in” by the visual system. Investigations of visual perception in and around the blind spot allow us to investigate this filling-in process. However, because the location and size of the blind spot are individually variable, experimenters must first map the blind spot in every observer. We present an open-source tool, which runs in Psychopy software, to estimate the location and size of the blind spot psychophysically. The tool will ideally be used with an Eyelink eye-tracker (SR Research), but it can also run in standalone mode. Here, we explain the rationale for the tool and demonstrate its validity in normally-sighted observers. We develop a detailed map of the blind spot in one observer. Then, in a group of 12 observers, we propose a more efficient, pragmatic method to define a “safe zone” within the blind spot, for which the experimenter can be fully confident that visual stimuli will not be seen. Links are provided to this open-source tool and a user manual

Visuospatial coding as ubiquitous scaffolding for human cognition

For more than 100 years we have known that the visual field is mapped onto the surface of visual cortex, imposing an inherently spatial reference frame on visual information processing. Recent studies highlight visuospatial coding not only throughout visual cortex, but also brain areas not typically considered visual. Such widespread access to visuospatial coding raises important questions about its role in wider cognitive functioning. Here, we synthesise these recent developments and propose that visuospatial coding scaffolds human cognition by providing a reference frame through which neural computations interface with environmental statistics and task demands via perception–action loops

Direct comparison of contralateral bias and face/scene selectivity in human occipitotemporal cortex

Human visual cortex is organised broadly according to two major principles: retinotopy (the spatial mapping of the retina in cortex) and category-selectivity (preferential responses to specific categories of stimuli). Historically, these principles were considered anatomically separate, with retinotopy restricted to the occipital cortex and category-selectivity emerging in the lateral-occipital and ventral-temporal cortex. However, recent studies show that category-selective regions exhibit systematic retinotopic biases, for example exhibiting stronger activation for stimuli presented in the contra- compared to the ipsilateral visual field. It is unclear, however, whether responses within category-selective regions are more strongly driven by retinotopic location or by category preference, and if there are systematic differences between category-selective regions in the relative strengths of these preferences. Here, we directly compare contralateral and category preferences by measuring fMRI responses to scene and face stimuli presented in the left or right visual field and computing two bias indices: a contralateral bias (response to the contralateral minus ipsilateral visual field) and a face/scene bias (preferred response to scenes compared to faces, or vice versa). We compare these biases within and between scene- and face-selective regions and across the lateral and ventral surfaces of the visual cortex more broadly. We find an interaction between surface and bias: lateral surface regions show a stronger contralateral than face/scene bias, whilst ventral surface regions show the opposite. These effects are robust across and within subjects, and appear to reflect large-scale, smoothly varying gradients. Together, these findings support distinct functional roles for the lateral and ventral visual cortex in terms of the relative importance of the spatial location of stimuli during visual information processing. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00429-021-02411-8

Representation of contralateral visual space in the human hippocampus

The initial encoding of visual information primarily from the contralateral visual field is a fundamental organizing principle of the primate visual system. Recently, the presence of such retinotopic sensitivity has been shown to extend well beyond early visual cortex to regions not historically considered retinotopically sensitive. In particular, human scene-selective regions in parahippocampal and medial parietal cortex exhibit prominent biases for the contralateral visual field. Here we used fMRI to test the hypothesis that the human hippocampus, which is thought to be anatomically connected with these scene-selective regions, would also exhibit a biased representation of contralateral visual space. First, population receptive field mapping with scene stimuli revealed strong biases for the contralateral visual field in bilateral hippocampus. Second, the distribution of retinotopic sensitivity suggested a more prominent representation in anterior medial portions of the hippocampus. Finally, the contralateral bias was confirmed in independent data taken from the Human Connectome Project initiative. The presence of contralateral biases in the hippocampus - a structure considered by many as the apex of the visual hierarchy - highlights the truly pervasive influence of retinotopy. Moreover, this finding has important implications for understanding how this information relates to the allocentric global spatial representations known to be encoded therein.SIGNIFICANCE STATEMENT:Retinotopic encoding of visual information is an organizing principle of visual cortex. Recent work demonstrates this sensitivity in structures far beyond early visual cortex, including those anatomically connected to the hippocampus. Here, using population receptive field modelling in two independent sets of data we demonstrate a consistent bias for the contralateral visual field in bilateral hippocampus. Such a bias highlights the truly pervasive influence of retinotopy, with important implications for understanding how the presence of retinotopy relates to more allocentric spatial representations

Direct comparison of contralateral bias and face/scene selectivity in human occipitotemporal cortex

Human visual cortex is organised broadly according to two major principles: retinotopy (the spatial mapping of the retina in cortex) and category-selectivity (preferential responses to specific categories of stimuli). Historically, these principles were considered anatomically separate, with retinotopy restricted to the occipital cortex and category-selectivity emerging in the lateral-occipital and ventral-temporal cortex. However, recent studies show that category-selective regions exhibit systematic retinotopic biases, for example exhibiting stronger activation for stimuli presented in the contra- compared to the ipsilateral visual field. It is unclear, however, whether responses within category-selective regions are more strongly driven by retinotopic location or by category preference, and if there are systematic differences between category-selective regions in the relative strengths of these preferences. Here, we directly compare contralateral and category preferences by measuring fMRI responses to scene and face stimuli presented in the left or right visual field and computing two bias indices: a contralateral bias (response to the contralateral minus ipsilateral visual field) and a face/scene bias (preferred response to scenes compared to faces, or vice versa). We compare these biases within and between scene- and face-selective regions and across the lateral and ventral surfaces of the visual cortex more broadly. We find an interaction between surface and bias: lateral surface regions show a stronger contralateral than face/scene bias, whilst ventral surface regions show the opposite. These effects are robust across and within subjects, and appear to reflect large-scale, smoothly varying gradients. Together, these findings support distinct functional roles for the lateral and ventral visual cortex in terms of the relative importance of the spatial location of stimuli during visual information processing. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00429-021-02411-8