scholarly journals Dynamic dot displays reveal material motion network in the human brain

2020 ◽  
Author(s):  
Alexandra C. Schmid ◽  
Huseyin Boyaci ◽  
Katja Doerschner
Keyword(s):  
Three Dimensional ◽  
Brain Regions ◽  
Specific Pattern ◽  
Research Field ◽  
Neural Mechanisms ◽  
Motion Processing ◽  
Neural Basis ◽  
Cortical Regions ◽  
Motion Versus ◽  
Cortical Architecture

ABSTRACTThere is growing research interest in the neural mechanisms underlying the recognition of material categories and properties. This research field, however, is relatively more recent and limited compared to investigations of the neural mechanisms underlying object and scene category recognition. Motion is particularly important for the perception of non-rigid materials, but the neural basis of non-rigid material motion remains unexplored. Using fMRI, we investigated which brain regions respond preferentially to material motion versus other types of motion. We introduce a new database of stimuli – dynamic dot materials – that are animations of moving dots that induce vivid percepts of various materials in motion, e.g. flapping cloth, liquid waves, wobbling jelly. Control stimuli were scrambled versions of these same animations and rigid three-dimensional rotating dots. Results showed that isolating material motion properties with dynamic dots (in contrast with other kinds of motion) activates a network of cortical regions in both ventral and dorsal visual pathways, including areas normally associated with the processing of surface properties and shape, and extending to somatosensory and premotor cortices. We suggest that such a widespread preference for material motion is due to strong associations between stimulus properties. For example viewing dots moving in a specific pattern not only elicits percepts of material motion; one perceives a flexible, non-rigid shape, identifies the object as a cloth flapping in the wind, infers the object’s weight under gravity, and anticipates how it would feel to reach out and touch the material. These results are a first important step in mapping out the cortical architecture and dynamics in material-related motion processing.

Perceptual Representations and the Vividness of Stimulus-Triggered and Stimulus-Independent Experiences

2020 ◽  
Vol 15 (5) ◽  
pp. 1200-1213 ◽  
Author(s):  
Peter Fazekas ◽  
Georgina Nemeth ◽  
Morten Overgaard
Keyword(s):  
Working Memory ◽  
Mental Imagery ◽  
Information Exchange ◽  
Activity Patterns ◽  
Mind Wandering ◽  
Brain Regions ◽  
Neural Basis ◽  
Fine Grained ◽  
Common Framework ◽  
Cortical Regions

In recent years, researchers from independent subfields have begun to engage with the idea that the same cortical regions that contribute to on-line perception are recruited during and underlie off-line activities such as information maintenance in working memory, mental imagery, hallucinations, dreaming, and mind wandering. Accumulating evidence suggests that in all of these cases the activity of posterior brain regions provides the contents of experiences. This article is intended to move one step further by exploring specific links between the vividness of experiences, which is a characteristic feature of consciousness regardless of its actual content, and certain properties of the content-specific neural-activity patterns. Investigating the mechanisms that underlie mental imagery and its relation to working memory and the processes responsible for mind wandering and its similarities to dreaming form two clusters of research that are in the forefront of the recent scientific study of mental phenomena, yet communication between these two clusters has been surprisingly sparse. Here our aim is to foster such information exchange by articulating a hypothesis about the fine-grained phenomenological structure determining subjective vividness and its possible neural basis that allows us to shed new light on these mental phenomena by bringing them under a common framework.

Neural Basis of Visual Distraction

2010 ◽  
Vol 22 (8) ◽  
pp. 1794-1807 ◽  
Author(s):  
So-Yeon Kim ◽  
Joseph B. Hopfinger
Keyword(s):  
Neural Activity ◽  
Brain Regions ◽  
Neural Mechanisms ◽  
Intraparietal Sulcus ◽  
Neural Basis ◽  
Luminance Change ◽  
Visual Distraction ◽  
Distractor Processing ◽  
Level Of Activity ◽  
New Evidence

The ability to maintain focus and avoid distraction by goal-irrelevant stimuli is critical for performing many tasks and may be a key deficit in attention-related problems. Recent studies have demonstrated that irrelevant stimuli that are consciously perceived may be filtered out on a neural level and not cause the distraction triggered by subliminal stimuli. However, in everyday situations, suprathreshold stimuli often do capture attention, but the neural mechanisms by which some stimuli rapidly and automatically trigger distraction remain unknown. Here, we investigated the neural basis of distraction by utilizing a particularly strong form of distractor: the abrupt appearance of a new object. Our results revealed a competitive relation between brain regions coding the locations of the target and the distractor, with distractor processing increasing and target processing decreasing, but only when the distractor was a new object; an equivalent luminance change to an existing object neither generated distraction nor affected target processing. Results also revealed changes in neural activity in intraparietal sulcus (IPS) and temporo-parietal junction (TPJ) that were unique to the new object distractor condition. The strongest relations between behavioral distraction and neural activity were observed in these parietal regions. Furthermore, participants who were less susceptible to distraction showed a more consistent, albeit more moderate, level of activity in IPS and TPJ. The present results thus provide new evidence regarding the neural mechanisms underlying distraction and resistance to it.

scholarly journals Unraveling Representations in Scene-selective Brain Regions Using Scene-Parsing Deep Neural Networks

2020 ◽  
pp. 1-12 ◽  
Author(s):  
Kshitij Dwivedi ◽  
Radoslaw Martin Cichy ◽  
Gemma Roig
Keyword(s):  
Scene Perception ◽  
Research Question ◽  
Brain Regions ◽  
Computational Approach ◽  
Differential Sensitivity ◽  
Neural Basis ◽  
Cortical Regions ◽  
Differential Contribution ◽  
Parahippocampal Place Area ◽  
Variance Explained

Visual scene perception is mediated by a set of cortical regions that respond preferentially to images of scenes, including the occipital place area (OPA) and parahippocampal place area (PPA). However, the differential contribution of OPA and PPA to scene perception remains an open research question. In this study, we take a deep neural network (DNN)-based computational approach to investigate the differences in OPA and PPA function. In a first step, we search for a computational model that predicts fMRI responses to scenes in OPA and PPA well. We find that DNNs trained to predict scene components (e.g., wall, ceiling, floor) explain higher variance uniquely in OPA and PPA than a DNN trained to predict scene category (e.g., bathroom, kitchen, office). This result is robust across several DNN architectures. On this basis, we then determine whether particular scene components predicted by DNNs differentially account for unique variance in OPA and PPA. We find that variance in OPA responses uniquely explained by the navigation-related floor component is higher compared to the variance explained by the wall and ceiling components. In contrast, PPA responses are better explained by the combination of wall and floor, that is, scene components that together contain the structure and texture of the scene. This differential sensitivity to scene components suggests differential functions of OPA and PPA in scene processing. Moreover, our results further highlight the potential of the proposed computational approach as a general tool in the investigation of the neural basis of human scene perception.

scholarly journals Unravelling Representations in Scene-selective Brain Regions Using Scene Parsing Deep Neural Networks

2020 ◽  
Author(s):  
Kshitij Dwivedi ◽  
Radoslaw Martin Cichy ◽  
Gemma Roig
Keyword(s):  
Scene Perception ◽  
Research Question ◽  
Brain Regions ◽  
Computational Approach ◽  
Differential Sensitivity ◽  
Neural Basis ◽  
Cortical Regions ◽  
Differential Contribution ◽  
Parahippocampal Place Area ◽  
Variance Explained

Visual scene perception is mediated by a set of cortical regions that respond preferentially to images of scenes, including the occipital place area (OPA) and parahippocampal place area (PPA). However, the differential contribution of OPA and PPA to scene perception remains an open research question. In this study, we take a deep neural network (DNN)-based computational approach to investigate the differences in OPA and PPA function. In a first step we search for a computational model that predicts fMRI responses to scenes in OPA and PPA well. We find that DNNs trained to predict scene components (e.g., wall, ceiling, floor) explain higher variance uniquely in OPA and PPA than a DNN trained to predict scene category (e.g., bathroom, kitchen, office). This result is robust across several DNN architectures. On this basis, we then determine whether particular scene components predicted by DNNs differentially account for unique variance in OPA and PPA. We find that variance in OPA responses uniquely explained by the navigation-related floor component is higher compared to the variance explained by the wall and ceiling components. In contrast, PPA responses are better explained by the combination of wall and floor, that is scene components that together contain the structure and texture of the scene. This differential sensitivity to scene components suggests differential functions of OPA and PPA in scene processing. Moreover, our results further highlight the potential of the proposed computational approach as a general tool in the investigation of the neural basis of human scene perception.

scholarly journals Comparison of Intensity- and Polarization-based Contrast in Amyloid-beta Plaques as Observed by Optical Coherence Tomography

2019 ◽  
Vol 9 (10) ◽  
pp. 2100 ◽  
Author(s):  
Johanna Gesperger ◽  
Antonia Lichtenegger ◽  
Thomas Roetzer ◽  
Marco Augustin ◽  
Danielle J. Harper ◽  
...  
Keyword(s):  
Optical Coherence Tomography ◽  
Amyloid Beta ◽  
Cross Sections ◽  
Imaging Modality ◽  
Three Dimensional ◽  
Brain Regions ◽  
Optical Coherence ◽  
Amyloid Beta Protein ◽  
Tissue Sections ◽  
Cortical Regions

One key hallmark of Alzheimer’s disease (AD) is the accumulation of extracellular amyloid-beta protein in cortical regions of the brain. For a definitive diagnosis of AD, post-mortem histological analysis, including sectioning and staining of different brain regions, is required. Here, we present optical coherence tomography (OCT) as a tissue-preserving imaging modality for the visualization of amyloid-beta plaques and compare their contrast in intensity- and polarization-sensitive (PS) OCT. Human brain samples of eleven patients diagnosed with AD were imaged. Three-dimensional PS-OCT datasets were acquired and plaques were manually segmented in 500 intensity and retardation cross-sections per patient using the freely available ITK-SNAP software. The image contrast of plaques was quantified. Histological staining of tissue sections from the same specimens was performed to compare OCT findings against the gold standard. Furthermore, the distribution of plaques was evaluated for intensity-based OCT, PS-OCT and the corresponding histological amyloid-beta staining. Only 5% of plaques were visible in both intensity and retardation segmentations, suggesting that different types of plaques may be visualized by the two OCT contrast channels. Our results indicate that multicontrast OCT imaging might be a promising approach for a tissue-preserving visualization of amyloid-beta plaques in AD.

Neural Mechanisms of Motion Processing in the Mammalian Retina

2018 ◽  
Vol 4 (1) ◽  
pp. 165-192 ◽  
Author(s):  
Wei Wei
Keyword(s):  
Visual Motion ◽  
Ganglion Cells ◽  
Direction Selectivity ◽  
Neural Mechanisms ◽  
Motion Processing ◽  
Retinal Ganglion ◽  
Multiple Streams ◽  
Neural Basis ◽  
Population Activity ◽  
Motion Features

Visual motion on the retina activates a cohort of retinal ganglion cells (RGCs). This population activity encodes multiple streams of information extracted by parallel retinal circuits. Motion processing in the retina is best studied in the direction-selective circuit. The main focus of this review is the neural basis of direction selectivity, which has been investigated in unprecedented detail using state-of-the-art functional, connectomic, and modeling methods. Mechanisms underlying the encoding of other motion features by broader RGC populations are also discussed. Recent discoveries at both single-cell and population levels highlight the dynamic and stimulus-dependent engagement of multiple mechanisms that collectively implement robust motion detection under diverse visual conditions.

Two Kinds of fMRI Repetition Suppression? Evidence for Dissociable Neural Mechanisms

2008 ◽  
Vol 99 (6) ◽  
pp. 2877-2886 ◽  
Author(s):  
Russell A. Epstein ◽  
Whitney E. Parker ◽  
Alana M. Feiler
Keyword(s):  
Short Interval ◽  
Brain Regions ◽  
Neural Mechanisms ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Repetition Suppression ◽  
Underlying Mechanisms ◽  
Cortical Regions ◽  
Formal Requirements ◽  
Parahippocampal Place Area

Repetition suppression (RS) is a reduction of neural response that is often observed when stimuli are presented more than once. Many functional magnetic resonance imaging (fMRI) studies have exploited RS to probe the sensitivity of cortical regions to variations in different stimulus dimensions; however, the neural mechanisms underlying fMRI-RS are not fully understood. Here we test the hypothesis that long-interval (between-trial) and short-interval (within-trial) RS effects are caused by distinct and independent neural mechanisms. Subjects were scanned while viewing visual scenes that were repeated over both long and short intervals. Within the parahippocampal place area (PPA) and other brain regions, suppression effects relating to both long- and short-interval repetition were observed. Critically, two sources of evidence indicated that these effects were engendered by different underlying mechanisms. First, long- and short-interval RS effects were entirely noninteractive even although they were measured within the same set of trials during which subjects performed a constant behavioral task, thus fulfilling the formal requirements for a process dissociation. Second, long- and short-interval RS were differentially sensitive to viewpoint: short-interval RS was only significant when scenes were repeated from the same viewpoint while long-interval RS less viewpoint-dependent. Taken together, these results indicate that long- and short-interval fMRI-RS are mediated by different neural mechanisms that independently modulate the overall fMRI signal. These findings have important implications for understanding the results of studies that use fMRI-RS to explore representational spaces.

scholarly journals The neural basis of depth perception from motion parallax

2016 ◽  
Vol 371 (1697) ◽  
pp. 20150256 ◽  
Author(s):  
HyunGoo R. Kim ◽  
Dora E. Angelaki ◽  
Gregory C. DeAngelis
Keyword(s):  
Relative Motion ◽  
Depth Perception ◽  
Motion Parallax ◽  
Three Dimensional ◽  
Neural Mechanisms ◽  
Neural Basis ◽  
Middle Temporal ◽  
Scene Structure ◽  
Neural Substrate ◽  
The Brain

In addition to depth cues afforded by binocular vision, the brain processes relative motion signals to perceive depth. When an observer translates relative to their visual environment, the relative motion of objects at different distances (motion parallax) provides a powerful cue to three-dimensional scene structure. Although perception of depth based on motion parallax has been studied extensively in humans, relatively little is known regarding the neural basis of this visual capability. We review recent advances in elucidating the neural mechanisms for representing depth-sign (near versus far) from motion parallax. We examine a potential neural substrate in the middle temporal visual area for depth perception based on motion parallax, and we explore the nature of the signals that provide critical inputs for disambiguating depth-sign. This article is part of the themed issue ‘Vision in our three-dimensional world’.

scholarly journals Homogeneous 2D and 3D alignment of cardiomyocyte in dilated cardiomyopathy revealed by intravital heart imaging

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kiyoshi Masuyama ◽  
Tomoaki Higo ◽  
Jong-Kook Lee ◽  
Ryohei Matsuura ◽  
Ian Jones ◽  
...  
Keyword(s):  
Heart Failure ◽  
Dilated Cardiomyopathy ◽  
Cardiac Dysfunction ◽  
Three Dimensional ◽  
Single Layer ◽  
Specific Pattern ◽  
Two Dimensional ◽  
Heart Imaging ◽  
Novel Method ◽  
2D And 3D

AbstractIn contrast to hypertrophic cardiomyopathy, there has been reported no specific pattern of cardiomyocyte array in dilated cardiomyopathy (DCM), partially because lack of alignment assessment in a three-dimensional (3D) manner. Here we have established a novel method to evaluate cardiomyocyte alignment in 3D using intravital heart imaging and demonstrated homogeneous alignment in DCM mice. Whilst cardiomyocytes of control mice changed their alignment by every layer in 3D and position twistedly even in a single layer, termed myocyte twist, cardiomyocytes of DCM mice aligned homogeneously both in two-dimensional (2D) and in 3D and lost myocyte twist. Manipulation of cultured cardiomyocyte toward homogeneously aligned increased their contractility, suggesting that homogeneous alignment in DCM mice is due to a sort of alignment remodelling as a way to compensate cardiac dysfunction. Our findings provide the first intravital evidence of cardiomyocyte alignment and will bring new insights into understanding the mechanism of heart failure.

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