Modulating attentional load affects numerosity estimation: evidence against a pre-attentive subitizing mechanism

Traditionally, the visual enumeration of a small number of items (1 to about 4), referred to as subitizing, has been thought of as a parallel and pre-attentive process and functionally different from the serial attentive enumeration of larger numerosities. We tested this hypothesis by employing a dual task paradigm that systematically manipulated the attentional resources available to an enumeration task. Enumeration accuracy for small numerosities was severely decreased as more attentional resources were taken away from the numerical task, challenging the traditionally held notion of subitizing as a pre-attentive, capacity-independent process. Judgement of larger numerosities was also affected by dual task conditions and attentional load. These results challenge the proposal that small numerosities are enumerated by a mechanism separate from large numerosities and support the idea of a single, attention-demanding enumeration mechanism

Multiscale Convolutional Neural Networks for Vision–Based Classification of Cells

International audienceWe present a Multiscale Convolutional Neural Network (MCNN) approach for vision-based classification of cells. Based on several deep Convolutional Neural Networks (CNN) acting at different resolutions, the proposed architecture avoid the classical handcrafted features extraction step, by processing features extraction and classification as a whole. The proposed approach gives better classification rates than classical state-of-the-art methods allowing a safer Computer-Aided Diagnosis of pleural cancer

Age and distraction are determinants of performance on a novel visual search task in aged Beagle dogs

Aging has been shown to disrupt performance on tasks that require intact visual search and discrimination abilities in human studies. The goal of the present study was to determine if canines show age-related decline in their ability to perform a novel simultaneous visual search task. Three groups of canines were included: a young group (N = 10; 3 to 4.5 years), an old group (N = 10; 8 to 9.5 years), and a senior group (N = 8; 11 to 15.3 years). Subjects were first tested for their ability to learn a simple two-choice discrimination task, followed by the visual search task. Attentional demands in the task were manipulated by varying the number of distracter items; dogs received an equal number of trials with either zero, one, two, or three distracters. Performance on the two-choice discrimination task varied with age, with senior canines making significantly more errors than the young. Performance accuracy on the visual search task also varied with age; senior animals were significantly impaired compared to both the young and old, and old canines were intermediate in performance between young and senior. Accuracy decreased significantly with added distracters in all age groups. These results suggest that aging impairs the ability of canines to discriminate between task-relevant and -irrelevant stimuli. This is likely to be derived from impairments in cognitive domains such as visual memory and learning and selective attention

Spatial Stereoresolution for Depth Corrugations May Be Set in Primary Visual Cortex

Stereo “3D” depth perception requires the visual system to extract binocular disparities between the two eyes' images. Several current models of this process, based on the known physiology of primary visual cortex (V1), do this by computing a piecewise-frontoparallel local cross-correlation between the left and right eye's images. The size of the “window” within which detectors examine the local cross-correlation corresponds to the receptive field size of V1 neurons. This basic model has successfully captured many aspects of human depth perception. In particular, it accounts for the low human stereoresolution for sinusoidal depth corrugations, suggesting that the limit on stereoresolution may be set in primary visual cortex. An important feature of the model, reflecting a key property of V1 neurons, is that the initial disparity encoding is performed by detectors tuned to locally uniform patches of disparity. Such detectors respond better to square-wave depth corrugations, since these are locally flat, than to sinusoidal corrugations which are slanted almost everywhere. Consequently, for any given window size, current models predict better performance for square-wave disparity corrugations than for sine-wave corrugations at high amplitudes. We have recently shown that this prediction is not borne out: humans perform no better with square-wave than with sine-wave corrugations, even at high amplitudes. The failure of this prediction raised the question of whether stereoresolution may actually be set at later stages of cortical processing, perhaps involving neurons tuned to disparity slant or curvature. Here we extend the local cross-correlation model to include existing physiological and psychophysical evidence indicating that larger disparities are detected by neurons with larger receptive fields (a size/disparity correlation). We show that this simple modification succeeds in reconciling the model with human results, confirming that stereoresolution for disparity gratings may indeed be limited by the size of receptive fields in primary visual cortex

On the Inverse Problem of Binocular 3D Motion Perception

It is shown that existing processing schemes of 3D motion perception such as interocular velocity difference, changing disparity over time, as well as joint encoding of motion and disparity, do not offer a general solution to the inverse optics problem of local binocular 3D motion. Instead we suggest that local velocity constraints in combination with binocular disparity and other depth cues provide a more flexible framework for the solution of the inverse problem. In the context of the aperture problem we derive predictions from two plausible default strategies: (1) the vector normal prefers slow motion in 3D whereas (2) the cyclopean average is based on slow motion in 2D. Predicting perceived motion directions for ambiguous line motion provides an opportunity to distinguish between these strategies of 3D motion processing. Our theoretical results suggest that velocity constraints and disparity from feature tracking are needed to solve the inverse problem of 3D motion perception. It seems plausible that motion and disparity input is processed in parallel and integrated late in the visual processing hierarchy