Near-optimal combination of disparity across a log-polar scaled visual field

The human visual system is foveated: we can see fine spatial details in central vision, whereas resolution is poor in our peripheral visual field, and this loss of resolution follows an approximately logarithmic decrease. Additionally, our brain organizes visual input in polar coordinates. Therefore, the image projection occurring between retina and primary visual cortex can be mathematically described by the log-polar transform. Here, we test and model how this space-variant visual processing affects how we process binocular disparity, a key component of human depth perception. We observe that the fovea preferentially processes disparities at fine spatial scales, whereas the visual periphery is tuned for coarse spatial scales, in line with the naturally occurring distributions of depths and disparities in the real-world. We further show that the visual system integrates disparity information across the visual field, in a near-optimal fashion. We develop a foveated, log-polar model that mimics the processing of depth information in primary visual cortex and that can process disparity directly in the cortical domain representation. This model takes real images as input and recreates the observed topography of human disparity sensitivity. Our findings support the notion that our foveated, binocular visual system has been moulded by the statistics of our visual environment

Population-scale organization of cerebellar granule neuron signaling during a visuomotor behavior.

Granule cells at the input layer of the cerebellum comprise over half the neurons in the human brain and are thought to be critical for learning. However, little is known about granule neuron signaling at the population scale during behavior. We used calcium imaging in awake zebrafish during optokinetic behavior to record transgenically identified granule neurons throughout a cerebellar population. A significant fraction of the population was responsive at any given time. In contrast to core precerebellar populations, granule neuron responses were relatively heterogeneous, with variation in the degree of rectification and the balance of positive versus negative changes in activity. Functional correlations were strongest for nearby cells, with weak spatial gradients in the degree of rectification and the average sign of response. These data open a new window upon cerebellar function and suggest granule layer signals represent elementary building blocks under-represented in core sensorimotor pathways, thereby enabling the construction of novel patterns of activity for learning

Change blindness: eradication of gestalt strategies

Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task

The repeating Fast Radio Burst FRB 121102: Multi-wavelength observations and additional bursts

We report on radio and X-ray observations of the only known repeating Fast Radio Burst (FRB) source, FRB 121102. We have detected six additional radio bursts from this source: five with the Green Bank Telescope at 2 GHz, and one at 1.4 GHz at the Arecibo Observatory for a total of 17 bursts from this source. All have dispersion measures consistent with a single value ($\sim559$ pc cm$^{-3}$) that is three times the predicted maximum Galactic value. The 2-GHz bursts have highly variable spectra like those at 1.4 GHz, indicating that the frequency structure seen across the individual 1.4 and 2-GHz bandpasses is part of a wideband process. X-ray observations of the FRB 121102 field with the Swift and Chandra observatories show at least one possible counterpart; however, the probability of chance superposition is high. A radio imaging observation of the field with the Jansky Very Large Array at 1.6 GHz yields a 5$\sigma$ upper limit of 0.3 mJy on any point-source continuum emission. This upper limit, combined with archival WISE 22-$\mu$m and IPHAS H$\alpha$ surveys, rules out the presence of an intervening Galactic HII region. We update our estimate of the FRB detection rate in the PALFA survey to be 1.1$^{+3.7}_{-1.0} \times 10^4$ FRBs sky$^{-1}$ day$^{-1}$ (95% confidence) for peak flux density at 1.4 GHz above 300 mJy. We find that the intrinsic widths of the 12 FRB 121102 bursts from Arecibo are, on average, significantly longer than the intrinsic widths of the 13 single-component FRBs detected with the Parkes telescope.Comment: 18 pages, 5 figures. Accepted for publication in Ap

A comparative study of cortical computations in the mammalian visual cortex

textA common feature of all mammals is the cerebral cortex, which is essential for higher-order functions and processing information to generate motor actions. While cortical circuits exhibit a striking uniformity in anatomical organization, it is unknown whether these circuits preform similar computations across mammalian species. In this dissertation I compare the emergence of two computations in the primary visual cortex (V1) of carnivores and rodents. A cortical computation is a transformation in neural representation, such that the spiking output of a cortical neuron exhibits a selectivity not present in the inputs from upstream neurons. Here I explore two computations: orientation selectivity, the preference of neurons for oriented edges in the visual world, and binocularity, the integration of signals from the two eyes. In the first section, I compare the emergence of orientation selectivity in the early visual pathway of mouse and cat. Recordings from thalamic relay cells and V1 neurons in both species reveal orientation selectivity in mouse V1 is not emergent, and could be inherited subcortically. In a second set of experiments, I measure orientation selectivity and the organization of V1 orientation preference in a grasshopper mouse with predatory behavior, compared to the scavenger lab mouse. Here I find the same functional properties. In the second section, I focus on the integration of ocular inputs in V1 of mouse and cat. I first compare disparity selectivity in cats, where convergence of ocular inputs has long been established, with mice, where ocular integration had not previously been investigated. Similar to cats, mouse V1 neurons were sensitive to binocular disparity, albeit to a lesser degree, and could be described by a linear feed-forward model. I next explore the disruption of binocular disparity tuning in both animals. In cats, strabismus induced during development causes increased monocularity in V1 and a loss of disparity selectivity. In mice, monocular deprivation causes increased ocular input, which also manifests as decreased disparity selectivity. Finally, I explore how excitatory and inhibitory neurons in mouse V1 integrate binocular signals. Paravalbumin-expressing inhibitory interneurons are more binocular but less disparity tuned than surrounding cortical neurons, providing a canonical mechanism explaining loss of disparity selectivity in both carnivores and rodents.Neuroscienc

Two-photon imaging and analysis of neural network dynamics

The glow of a starry night sky, the smell of a freshly brewed cup of coffee or the sound of ocean waves breaking on the beach are representations of the physical world that have been created by the dynamic interactions of thousands of neurons in our brains. How the brain mediates perceptions, creates thoughts, stores memories and initiates actions remains one of the most profound puzzles in biology, if not all of science. A key to a mechanistic understanding of how the nervous system works is the ability to analyze the dynamics of neuronal networks in the living organism in the context of sensory stimulation and behaviour. Dynamic brain properties have been fairly well characterized on the microscopic level of individual neurons and on the macroscopic level of whole brain areas largely with the help of various electrophysiological techniques. However, our understanding of the mesoscopic level comprising local populations of hundreds to thousands of neurons (so called 'microcircuits') remains comparably poor. In large parts, this has been due to the technical difficulties involved in recording from large networks of neurons with single-cell spatial resolution and near- millisecond temporal resolution in the brain of living animals. In recent years, two-photon microscopy has emerged as a technique which meets many of these requirements and thus has become the method of choice for the interrogation of local neural circuits. Here, we review the state-of-research in the field of two-photon imaging of neuronal populations, covering the topics of microscope technology, suitable fluorescent indicator dyes, staining techniques, and in particular analysis techniques for extracting relevant information from the fluorescence data. We expect that functional analysis of neural networks using two-photon imaging will help to decipher fundamental operational principles of neural microcircuits.Comment: 36 pages, 4 figures, accepted for publication in Reports on Progress in Physic

Engineering data compendium. Human perception and performance. User's guide

The concept underlying the Engineering Data Compendium was the product of a research and development program (Integrated Perceptual Information for Designers project) aimed at facilitating the application of basic research findings in human performance to the design and military crew systems. The principal objective was to develop a workable strategy for: (1) identifying and distilling information of potential value to system design from the existing research literature, and (2) presenting this technical information in a way that would aid its accessibility, interpretability, and applicability by systems designers. The present four volumes of the Engineering Data Compendium represent the first implementation of this strategy. This is the first volume, the User's Guide, containing a description of the program and instructions for its use