View-tolerant face recognition and Hebbian learning imply mirror-symmetric neural tuning to head orientation

The primate brain contains a hierarchy of visual areas, dubbed the ventral stream, which rapidly computes object representations that are both specific for object identity and relatively robust against identity-preserving transformations like depth-rotations. Current computational models of object recognition, including recent deep learning networks, generate these properties through a hierarchy of alternating selectivity-increasing filtering and tolerance-increasing pooling operations, similar to simple-complex cells operations. While simulations of these models recapitulate the ventral stream's progression from early view-specific to late view-tolerant representations, they fail to generate the most salient property of the intermediate representation for faces found in the brain: mirror-symmetric tuning of the neural population to head orientation. Here we prove that a class of hierarchical architectures and a broad set of biologically plausible learning rules can provide approximate invariance at the top level of the network. While most of the learning rules do not yield mirror-symmetry in the mid-level representations, we characterize a specific biologically-plausible Hebb-type learning rule that is guaranteed to generate mirror-symmetric tuning to faces tuning at intermediate levels of the architecture

Defining the essence of innovation how important terms in promoting of transformation processes in Ukraine

Feature hierarchies are essential to many visual object recognition systems and are well motivated by observations in biological systems. The present paper proposes an algorithm to incrementally compute feature hierarchies. The features are represented as estimated densities, using a variant of local soft histograms. The kernel functions used for this estimation in conjunction with their unitary extension establish a tight frame and results from framelet theory apply. Traversing the feature hierarchy requires resampling of the spatial and the feature bins. For the resampling, we derive a multi-resolution scheme for quadratic spline kernels and we derive an optimization algorithm for the upsampling. We complement the theoretic results by some illustrative experiments, consideration of convergence rate and computational efficiency.DIPLECSGARNICSELLII

Natural images from the birthplace of the human eye

Here we introduce a database of calibrated natural images publicly available through an easy-to-use web interface. Using a Nikon D70 digital SLR camera, we acquired about 5000 six-megapixel images of Okavango Delta of Botswana, a tropical savanna habitat similar to where the human eye is thought to have evolved. Some sequences of images were captured unsystematically while following a baboon troop, while others were designed to vary a single parameter such as aperture, object distance, time of day or position on the horizon. Images are available in the raw RGB format and in grayscale. Images are also available in units relevant to the physiology of human cone photoreceptors, where pixel values represent the expected number of photoisomerizations per second for cones sensitive to long (L), medium (M) and short (S) wavelengths. This database is distributed under a Creative Commons Attribution-Noncommercial Unported license to facilitate research in computer vision, psychophysics of perception, and visual neuroscience.Comment: Submitted to PLoS ON

Integrated information increases with fitness in the evolution of animats

One of the hallmarks of biological organisms is their ability to integrate disparate information sources to optimize their behavior in complex environments. How this capability can be quantified and related to the functional complexity of an organism remains a challenging problem, in particular since organismal functional complexity is not well-defined. We present here several candidate measures that quantify information and integration, and study their dependence on fitness as an artificial agent ("animat") evolves over thousands of generations to solve a navigation task in a simple, simulated environment. We compare the ability of these measures to predict high fitness with more conventional information-theoretic processing measures. As the animat adapts by increasing its "fit" to the world, information integration and processing increase commensurately along the evolutionary line of descent. We suggest that the correlation of fitness with information integration and with processing measures implies that high fitness requires both information processing as well as integration, but that information integration may be a better measure when the task requires memory. A correlation of measures of information integration (but also information processing) and fitness strongly suggests that these measures reflect the functional complexity of the animat, and that such measures can be used to quantify functional complexity even in the absence of fitness data.Comment: 27 pages, 8 figures, one supplementary figure. Three supplementary video files available on request. Version commensurate with published text in PLoS Comput. Bio

Patch-Based Experiments with Object Classification in Video Surveillance

We present a patch-based algorithm for the purpose of object classification in video surveillance. Within detected regions-of-interest (ROIs) of moving objects in the scene, a feature vector is calculated based on template matching of a large set of image patches. Instead of matching direct image pixels, we use Gabor-filtered versions of the input image at several scales. This approach has been adopted from recent experiments in generic object-recognition tasks. We present results for a new typical video surveillance dataset containing over 9,000 object images. Furthermore, we compare our system performance with another existing smaller surveillance dataset. We have found that with 50 training samples or higher, our detection rate is on the average above 95%. Because of the inherent scalability of the algorithm, an embedded system implementation is well within reach

A survey of energy drink consumption patterns among college students

<p>Abstract</p> <p>Background</p> <p>Energy drink consumption has continued to gain in popularity since the 1997 debut of Red Bull, the current leader in the energy drink market. Although energy drinks are targeted to young adult consumers, there has been little research regarding energy drink consumption patterns among college students in the United States. The purpose of this study was to determine energy drink consumption patterns among college students, prevalence and frequency of energy drink use for six situations, namely for insufficient sleep, to increase energy (in general), while studying, driving long periods of time, drinking with alcohol while partying, and to treat a hangover, and prevalence of adverse side effects and energy drink use dose effects among college energy drink users.</p> <p>Methods</p> <p>Based on the responses from a 32 member college student focus group and a field test, a 19 item survey was used to assess energy drink consumption patterns of 496 randomly surveyed college students attending a state university in the Central Atlantic region of the United States.</p> <p>Results</p> <p>Fifty one percent of participants (<it>n </it>= 253) reported consuming greater than one energy drink each month in an average month for the current semester (defined as energy drink user). The majority of users consumed energy drinks for insufficient sleep (67%), to increase energy (65%), and to drink with alcohol while partying (54%). The majority of users consumed one energy drink to treat most situations although using three or more was a common practice to drink with alcohol while partying (49%). Weekly jolt and crash episodes were experienced by 29% of users, 22% reported ever having headaches, and 19% heart palpitations from consuming energy drinks. There was a significant dose effect only for jolt and crash episodes.</p> <p>Conclusion</p> <p>Using energy drinks is a popular practice among college students for a variety of situations. Although for the majority of situations assessed, users consumed one energy drink with a reported frequency of 1 – 4 days per month, many users consumed three or more when combining with alcohol while partying. Further, side effects from consuming energy drinks are fairly common, and a significant dose effect was found with jolt and crash episodes. Future research should identify if college students recognize the amounts of caffeine that are present in the wide variety of caffeine-containing products that they are consuming, the amounts of caffeine that they are consuming in various situations, and the physical side effects associated with caffeine consumption.</p

Cross-Modal Object Recognition Is Viewpoint-Independent

BACKGROUND: Previous research suggests that visual and haptic object recognition are viewpoint-dependent both within- and cross-modally. However, this conclusion may not be generally valid as it was reached using objects oriented along their extended y-axis, resulting in differential surface processing in vision and touch. In the present study, we removed this differential by presenting objects along the z-axis, thus making all object surfaces more equally available to vision and touch. METHODOLOGY/PRINCIPAL FINDINGS: Participants studied previously unfamiliar objects, in groups of four, using either vision or touch. Subsequently, they performed a four-alternative forced-choice object identification task with the studied objects presented in both unrotated and rotated (180 degrees about the x-, y-, and z-axes) orientations. Rotation impaired within-modal recognition accuracy in both vision and touch, but not cross-modal recognition accuracy. Within-modally, visual recognition accuracy was reduced by rotation about the x- and y-axes more than the z-axis, whilst haptic recognition was equally affected by rotation about all three axes. Cross-modal (but not within-modal) accuracy correlated with spatial (but not object) imagery scores. CONCLUSIONS/SIGNIFICANCE: The viewpoint-independence of cross-modal object identification points to its mediation by a high-level abstract representation. The correlation between spatial imagery scores and cross-modal performance suggest that construction of this high-level representation is linked to the ability to perform spatial transformations. Within-modal viewpoint-dependence appears to have a different basis in vision than in touch, possibly due to surface occlusion being important in vision but not touch

Representing Where along with What Information in a Model of a Cortical Patch

Behaving in the real world requires flexibly combining and maintaining information about both continuous and discrete variables. In the visual domain, several lines of evidence show that neurons in some cortical networks can simultaneously represent information about the position and identity of objects, and maintain this combined representation when the object is no longer present. The underlying network mechanism for this combined representation is, however, unknown. In this paper, we approach this issue through a theoretical analysis of recurrent networks. We present a model of a cortical network that can retrieve information about the identity of objects from incomplete transient cues, while simultaneously representing their spatial position. Our results show that two factors are important in making this possible: A) a metric organisation of the recurrent connections, and B) a spatially localised change in the linear gain of neurons. Metric connectivity enables a localised retrieval of information about object identity, while gain modulation ensures localisation in the correct position. Importantly, we find that the amount of information that the network can retrieve and retain about identity is strongly affected by the amount of information it maintains about position. This balance can be controlled by global signals that change the neuronal gain. These results show that anatomical and physiological properties, which have long been known to characterise cortical networks, naturally endow them with the ability to maintain a conjunctive representation of the identity and location of objects

Transient Increase in Zn2+ in Hippocampal CA1 Pyramidal Neurons Causes Reversible Memory Deficit

The translocation of synaptic Zn2+ to the cytosolic compartment has been studied to understand Zn2+ neurotoxicity in neurological diseases. However, it is unknown whether the moderate increase in Zn2+ in the cytosolic compartment affects memory processing in the hippocampus. In the present study, the moderate increase in cytosolic Zn2+ in the hippocampus was induced with clioquinol (CQ), a zinc ionophore. Zn2+ delivery by Zn-CQ transiently attenuated CA1 long-term potentiation (LTP) in hippocampal slices prepared 2 h after i.p. injection of Zn-CQ into rats, when intracellular Zn2+ levels was transiently increased in the CA1 pyramidal cell layer, followed by object recognition memory deficit. Object recognition memory was transiently impaired 30 min after injection of ZnCl2 into the CA1, but not after injection into the dentate gyrus that did not significantly increase intracellular Zn2+ in the granule cell layer of the dentate gyrus. Object recognition memory deficit may be linked to the preferential increase in Zn2+ and/or the preferential vulnerability to Zn2+ in CA1 pyramidal neurons. In the case of the cytosolic increase in endogenous Zn2+ in the CA1 induced by 100 mM KCl, furthermore, object recognition memory was also transiently impaired, while ameliorated by co-injection of CaEDTA to block the increase in cytosolic Zn2+. The present study indicates that the transient increase in cytosolic Zn2+ in CA1 pyramidal neurons reversibly impairs object recognition memory