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

constructing stable spatial maps of the word

To interact rapidly and effectively with our environment, our brain needs access to a neural representation—or map—of the spatial layout of the external world. However, the construction of such a map poses major challenges to the visual system, given that the images on our retinae depend on where the eyes are looking, and shift each time we move our eyes, head, and body to explore the world. Much research has been devoted to how the stability is achieved, with the debate often polarized between the utility of spatiotopic maps (that remain solid in external coordinates), as opposed to transiently updated retinotopic maps. Our research suggests that the visual system uses both strategies to maintain stability. f MRI, motion-adaptation, and saccade-adaptation studies demonstrate and characterize spatiotopic neural maps within the dorsal visual stream that remain solid in external rather than retinal coordinates. However, the construction of these maps takes time (up to 500 ms) and attentional resources. To s..

Progress toward an understanding of cortical computation

The additional data, perspectives, questions, and criticisms contributed by the commentaries strengthen our view that local cortical processors coordinate their activity with the context in which it occurs using contextual fields and synchronized population codes. We therefore predict that whereas the specialization of function has been the keynote of this century the coordination of function will be the keynote of the next

Efficient spiking neural network model of pattern motion selectivity in visual cortex

Simulating large-scale models of biological motion perception is challenging, due to the required memory to store the network structure and the computational power needed to quickly solve the neuronal dynamics. A low-cost yet high-performance approach to simulating large-scale neural network models in real-time is to leverage the parallel processing capability of graphics processing units (GPUs). Based on this approach, we present a two-stage model of visual area MT that we believe to be the first large-scale spiking network to demonstrate pattern direction selectivity. In this model, component-direction- selective (CDS) cells in MT linearly combine inputs from V1 cells that have spatiotemporal receptive fields according to the motion energy model of Simoncelli and Heeger. Pattern-direction-selective (PDS) cells in MT are constructed by pooling over MT CDS cells with a wide range of preferred directions. Responses of our model neurons are comparable to electrophysiological results for grating and plaid stimuli as well as speed tuning. The behavioral response of the network in a motion discrimination task is in agreement with psychophysical data. Moreover, our implementation outperforms a previous implementation of the motion energy model by orders of magnitude in terms of computational speed and memory usage. The full network, which comprises 153,216 neurons and approximately 40 million synapses, processes 20 frames per second of a 40∈×∈40 input video in real-time using a single off-the-shelf GPU. To promote the use of this algorithm among neuroscientists and computer vision researchers, the source code for the simulator, the network, and analysis scripts are publicly available. © 2014 Springer Science+Business Media New York

Space Takes Time: Concentration Dependent Output Codes from Primary Olfactory Networks Rapidly Provide Additional Information at Defined Discrimination Thresholds

As odor concentration increases, primary olfactory network representations expand in spatial distribution, temporal complexity and duration. However, the direct relationship between concentration dependent odor representations and the psychophysical thresholds of detection and discrimination is poorly understood. This relationship is absolutely critical as thresholds signify transition points whereby representations become meaningful to the organism. Here, we matched stimulus protocols for psychophysical assays and intracellular recordings of antennal lobe (AL) projection neurons (PNs) in the moth Manduca sexta to directly compare psychophysical thresholds and the output representations they elicit. We first behaviorally identified odor detection and discrimination thresholds across an odor dilution series for a panel of structurally similar odors. We then characterized spatiotemporal spiking patterns across a population of individually filled and identified AL PNs in response to those odors at concentrations below, at, and above identified thresholds. Using spatial and spatiotemporal based analyses we observed that each stimulus produced unique representations, even at sub-threshold concentrations. Mean response latency did not decrease and the percent glomerular activation did not increase with concentration until undiluted odor. Furthermore, correlations between spatial patterns for odor decreased, but only significantly with undiluted odor. Using time-integrated Euclidean distance (ED) measures, we determined that added spatiotemporal information was present at the discrimination but not detection threshold. This added information was evidenced by an increase in integrated distance between the sub-detection and discrimination threshold concentrations (of the same odor) that was not present in comparison of the sub-detection and detection threshold. After consideration of delays for information to reach the AL we find that it takes ∼120–140 ms for the AL to output identity information. Overall, these results demonstrate that as odor concentration increases, added information about odor identity is embedded in the spatiotemporal representation at the discrimination threshold

Dynamic and Integrative Properties of the Primary Visual Cortex

The ability to derive meaning from complex, ambiguous sensory input requires the integration of information over both space and time, as well as cognitive mechanisms to dynamically shape that integration. We have studied these processes in the primary visual cortex (V1), where neurons have been proposed to integrate visual inputs along a geometric pattern known as the association field (AF). We first used cortical reorganization as a model to investigate the role that a specific network of V1 connections, the long-range horizontal connections, might play in temporal and spatial integration across the AF. When retinal lesions ablate sensory information from portions of the visual field, V1 undergoes a process of reorganization mediated by compensatory changes in the network of horizontal collaterals. The reorganization accompanies the brain’s amazing ability to perceptually “fill-inâ€, or “seeâ€, the lost visual input. We developed a computational model to simulate cortical reorganization and perceptual fill-in mediated by a plexus of horizontal connections that encode the AF. The model reproduces the major features of the perceptual fill-in reported by human subjects with retinal lesions, and it suggests that V1 neurons, empowered by their horizontal connections, underlie both perceptual fill-in and normal integrative mechanisms that are crucial to our visual perception. These results motivated the second prong of our work, which was to experimentally study the normal integration of information in V1. Since psychophysical and physiological studies suggest that spatial interactions in V1 may be under cognitive control, we investigated the integrative properties of V1 neurons under different cognitive states. We performed extracellular recordings from single V1 neurons in macaques that were trained to perform a delayed-match-to-sample contour detection task. We found that the ability of V1 neurons to summate visual inputs from beyond the classical receptive field (cRF) imbues them with selectivity for complex contour shapes, and that neuronal shape selectivity in V1 changed dynamically according to the shapes monkeys were cued to detect. Over the population, V1 encoded subsets of the AF, predicted by the computational model, that shifted as a function of the monkeys’ expectations. These results support the major conclusions of the theoretical work; even more, they reveal a sophisticated mode of form processing, whereby the selectivity of the whole network in V1 is reshaped by cognitive state