Summation of visual motion across eye movements reflects a nonspatial decision mechanism

Human vision remains perceptually stable even though retinal inputs change rapidly with each eye movement. Although the neural basis of visual stability remains unknown, a recent psychophysical study pointed to the existence of visual feature-representations anchored in environmental rather than retinal coordinates (e.g., "spatiotopic" receptive fields; Melcher and Morrone, 2003). In that study, sensitivity to a moving stimulus presented after a saccadic eye movement was enhanced when preceded by another moving stimulus at the same spatial location before the saccade. The finding is consistent with spatiotopic sensory integration, but it could also have arisen from a probabilistic improvement in performance due to the presence of more than one motion signal for the perceptual decision. Here we show that this statistical advantage accounts completely for summation effects in this task. We first demonstrate that measurements of summation are confounded by noise related to an observer's uncertainty about motion onset times. When this uncertainty is minimized, comparable summation is observed regardless of whether two motion signals occupy the same or different locations in space, and whether they contain the same or opposite directions of motion. These results are incompatible with the tuning properties of motion-sensitive sensory neurons and provide no evidence for a spatiotopic representation of visual motion. Instead, summation in this context reflects a decision mechanism that uses abstract representations of sensory events to optimize choice behavior. Copyright © 2010 the authors

Cortical Contributions to Saccadic Suppression

The stability of visual perception is partly maintained by saccadic suppression: the selective reduction of visual sensitivity that accompanies rapid eye movements. The neural mechanisms responsible for this reduced perisaccadic visibility remain unknown, but the Lateral Geniculate Nucleus (LGN) has been proposed as a likely site. Our data show, however, that the saccadic suppression of a target flashed in the right visual hemifield increased with an increase in background luminance in the left visual hemifield. Because each LGN only receives retinal input from a single hemifield, this hemifield interaction cannot be explained solely on the basis of neural mechanisms operating in the LGN. Instead, this suggests that saccadic suppression must involve processing in higher level cortical areas that have access to a considerable part of the ipsilateral hemifield

Relationship between Structure, Entropy and Diffusivity in Water and Water-like Liquids

Anomalous behaviour of the excess entropy ($S_e$) and the associated scaling relationship with diffusivity are compared in liquids with very different underlying interactions but similar water-like anomalies: water (SPC/E and TIP3P models), tetrahedral ionic melts (SiO$_2$ and BeF$_2$) and a fluid with core-softened, two-scale ramp (2SRP) interactions. We demonstrate the presence of an excess entropy anomaly in the two water models. Using length and energy scales appropriate for onset of anomalous behaviour, the density range of the excess entropy anomaly is shown to be much narrower in water than in ionic melts or the 2SRP fluid. While the reduced diffusivities ($D^*$) conform to the excess entropy scaling relation, $D^* =A\exp (\alpha S_e)$ for all the systems (Y. Rosenfeld, Phys. Rev. A {\bf 1977}, {\it 15}, 2545), the exponential scaling parameter, $\alpha$, shows a small isochore-dependence in the case of water. Replacing $S_e$ by pair correlation-based approximants accentuates the isochore-dependence of the diffusivity scaling. Isochores with similar diffusivity scaling parameters are shown to have the temperature dependence of the corresponding entropic contribution. The relationship between diffusivity, excess entropy and pair correlation approximants to the excess entropy are very similar in all the tetrahedral liquids.Comment: 24 pages, 4 figures, to be published in Journal of Physical Chemistry

Optimal measurement of visual motion across spatial and temporal scales

Sensory systems use limited resources to mediate the perception of a great variety of objects and events. Here a normative framework is presented for exploring how the problem of efficient allocation of resources can be solved in visual perception. Starting with a basic property of every measurement, captured by Gabor's uncertainty relation about the location and frequency content of signals, prescriptions are developed for optimal allocation of sensors for reliable perception of visual motion. This study reveals that a large-scale characteristic of human vision (the spatiotemporal contrast sensitivity function) is similar to the optimal prescription, and it suggests that some previously puzzling phenomena of visual sensitivity, adaptation, and perceptual organization have simple principled explanations.Comment: 28 pages, 10 figures, 2 appendices; in press in Favorskaya MN and Jain LC (Eds), Computer Vision in Advanced Control Systems using Conventional and Intelligent Paradigms, Intelligent Systems Reference Library, Springer-Verlag, Berli

Knowledge transfer for scene-specific motion prediction

When given a single frame of the video, humans can not only interpret the content of the scene, but also they are able to forecast the near future. This ability is mostly driven by their rich prior knowledge about the visual world, both in terms of (i) the dynamics of moving agents, as well as (ii) the semantic of the scene. In this work we exploit the interplay between these two key elements to predict scene-specific motion patterns. First, we extract patch descriptors encoding the probability of moving to the adjacent patches, and the probability of being in that particular patch or changing behavior. Then, we introduce a Dynamic Bayesian Network which exploits this scene specific knowledge for trajectory prediction. Experimental results demonstrate that our method is able to accurately predict trajectories and transfer predictions to a novel scene characterized by similar elements

Visual Cells Remember Earlier Applied Target: Plasticity of Orientation Selectivity

BACKGROUND: A canonical proposition states that, in mature brain, neurons responsive to sensory stimuli are tuned to specific properties installed shortly after birth. It is amply demonstrated that that neurons in adult visual cortex of cats are orientation-selective that is they respond with the highest firing rates to preferred oriented stimuli. METHODOLOGY/PRINCIPAL FINDINGS: In anesthetized cats, prepared in a conventional fashion for single cell recordings, the present investigation shows that presenting a stimulus uninterruptedly at a non-preferred orientation for twelve minutes induces changes in orientation preference. Across all conditions orientation tuning curves were investigated using a trial by trial method. Contrary to what has been previously reported with shorter adaptation duration, twelve minutes of adaptation induces mostly attractive shifts, i.e. toward the adapter. After a recovery period allowing neurons to restore their original orientation tuning curves, we carried out a second adaptation which produced three major results: (1) more frequent attractive shifts, (2) an increase of their magnitude, and (3) an additional enhancement of responses at the new or acquired preferred orientation. Additionally, we also show that the direction of shifts depends on the duration of the adaptation: shorter adaptation in most cases produces repulsive shifts, whereas adaptation exceeding nine minutes results in attractive shifts, in the same unit. Consequently, shifts in preferred orientation depend on the duration of adaptation. CONCLUSION/SIGNIFICANCE: The supplementary response improvements indicate that neurons in area 17 keep a memory trace of the previous stimulus properties, thereby upgrading cellular performance. It also highlights the dynamic nature of basic neuronal properties in adult cortex since repeated adaptations modified both the orientation tuning selectivity and the response strength to the preferred orientation. These enhanced neuronal responses suggest that the range of neuronal plasticity available to the visual system is broader than anticipated

Integration across time determines path deviation discrimination for moving objects.

YesBackground: Human vision is vital in determining our interaction with the outside world. In this study we characterize our ability to judge changes in the direction of motion of objects-a common task which can allow us either to intercept moving objects, or else avoid them if they pose a threat. Methodology/Principal Findings: Observers were presented with objects which moved across a computer monitor on a linear path until the midline, at which point they changed their direction of motion, and observers were required to judge the direction of change. In keeping with the variety of objects we encounter in the real world, we varied characteristics of the moving stimuli such as velocity, extent of motion path and the object size. Furthermore, we compared performance for moving objects with the ability of observers to detect a deviation in a line which formed the static trace of the motion path, since it has been suggested that a form of static memory trace may form the basis for these types of judgment. The static line judgments were well described by a 'scale invariant' model in which any two stimuli which possess the same two-dimensional geometry (length/width) result in the same level of performance. Performance for the moving objects was entirely different. Irrespective of the path length, object size or velocity of motion, path deviation thresholds depended simply upon the duration of the motion path in seconds. Conclusions/Significance: Human vision has long been known to integrate information across space in order to solve spatial tasks such as judgment of orientation or position. Here we demonstrate an intriguing mechanism which integrates direction information across time in order to optimize the judgment of path deviation for moving objects.Wellcome Trust, Leverhulme Trust, NI

Representations of time in human frontoparietal cortex

Precise time estimation is crucial in perception, action and social interaction. Previous neuroimaging studies in humans indicate that perceptual timing tasks involve multiple brain regions; however, whether the representation of time is localized or distributed in the brain remains elusive. Using ultra-high-field functional magnetic resonance imaging combined with multivariate pattern analyses, we show that duration information is decoded in multiple brain areas, including the bilateral parietal cortex, right inferior frontal gyrus and, albeit less clearly, the medial frontal cortex. Individual differences in the duration judgment accuracy were positively correlated with the decoding accuracy of duration in the right parietal cortex, suggesting that individuals with a better timing performance represent duration information in a more distinctive manner. Our study demonstrates that although time representation is widely distributed across frontoparietal regions, neural populations in the right parietal cortex play a crucial role in time estimation

Temporal Integration of Movement: The Time-Course of Motion Streaks Revealed by Masking

Temporal integration in the visual system causes fast-moving objects to leave oriented ‘motion streaks’ in their wake, which could be used to facilitate motion direction perception. Temporal integration is thought to occur over 100 ms in early cortex, although this has never been tested for motion streaks. Here we compare the ability of fast-moving (‘streaky’) and slow-moving fields of dots to mask briefly flashed gratings either parallel or orthogonal to the motion trajectory. Gratings were presented at various asynchronies relative to motion onset (from to ms) to sample the time-course of the accumulating streaks. Predictions were that masking would be strongest for the fast parallel condition, and would be weak at early asynchronies and strengthen over time as integration rendered the translating dots more streaky and grating-like. The asynchrony where the masking function reached a plateau would correspond to the temporal integration period. As expected, fast-moving dots caused greater masking of parallel gratings than orthogonal gratings, and slow motion produced only modest masking of either grating orientation. Masking strength in the fast, parallel condition increased with time and reached a plateau after 77 ms, providing an estimate of the temporal integration period for mechanisms encoding motion streaks. Interestingly, the greater masking by fast motion of parallel compared with orthogonal gratings first reached significance at 48 ms before motion onset, indicating an effect of backward masking by motion streaks