Learning and disrupting invariance in visual recognition

Learning by temporal association rules such as Foldiak's trace rule is an attractive hypothesis that explains the development of invariance in visual recognition. Consistent with these rules, several recent experiments have shown that invariance can be broken by appropriately altering the visual environment but found puzzling differences in the effects at the psychophysical versus single cell level. We show a) that associative learning provides appropriate invariance in models of object recognition inspired by Hubel and Wiesel b) that we can replicate the "invariance disruption" experiments using these models with a temporal association learning rule to develop and maintain invariance, and c) that we can thereby explain the apparent discrepancies between psychophysics and singe cells effects. We argue that these models account for the stability of perceptual invariance despite the underlying plasticity of the system, the variability of the visual world and expected noise in the biological mechanisms

A hierarchical model of peripheral vision

We present a peripheral vision model inspired by the cortical architecture discovered by Hubel and Wiesel. As with existing cortical models, this model contains alternating layers of simple cells, which employ tuning functions to increase specificity, and complex cells, which pool over simple cells to increase invariance. To extend the traditional cortical model, we introduce the option of eccentricity-dependent pooling and tuning parameters within a given model layer. This peripheral vision system can be used to model physiological data where receptive field sizes change as a function of eccentricity. This gives the user flexibility to test different theories about filtering and pooling ranges in the periphery. In a specific instantiation of the model, pooling and tuning parameters can increase linearly with eccentricity to model physiological data found in different layers of the visual cortex. Additionally, it can be used to introduce pre-cortical model layers such as retina and LGN. We have tested the model s response with different parameters on several natural images to demonstrate its effectiveness as a research tool. The peripheral vision model presents a useful tool to test theories about crowding, attention, visual search, and other phenomena of peripheral vision.This work was supported by the following grants: NSF-0640097, NSF-0827427, NSF-0645960, DARPA-DSO, AFSOR FA8650-50-C-7262, AFSOR FA9550-09-1-0606

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

Preliminary MEG decoding results

Decoding analysis has been applied to electrophysiology and fMRI data to study the visual system, however, this method has only been applied to MEG visual data in a few instances. Here we use the Neural Decoding Toolbox for Matlab to show that it is possible to decode visual stimuli based on MEG data

Decolorization and partial mineralization of a polyazo dye by Bacillus firmus immobilized within tubular polymeric gel

The degradation of C.I. Direct red 80, a polyazo dye, was investigated using Bacillus firmus immobilized by entrapment in tubular polymeric gel. This bacterial strain was able to completely decolorize 50 mg/L of C.I. Direct red 80 under anoxic conditions within 12 h and also degrade the reaction intermediates (aromatic amines) during the subsequent 12 h under aerobic conditions. The tubular gel harboring the immobilized cells consisted of anoxic and aerobic regions integrated in a single unit which was ideal for azo dye degradation studies. Results obtained show that effective dye decolorization (97.8%), chemical oxygen demand (COD) reduction (91.7%) and total aromatic amines removal were obtained in 15 h with the immobilized bacterial cell system whereas for the free cells, a hydraulic residence time of 24 h was required for an equivalent performance in a sequential anoxic and aerobic process. Repeated-batch experiments indicate the immobilized cells could decolorize C.I. Direct red 80 and reduce medium COD in five successive batch runs with enhanced activity obtained after each consecutive run, thus suggesting its stability and potential for repeated use in wastewater treatment. UV–visible spectrophotometry and HPLC analysis were used to confirm the partial mineralization of the dye. Data from this study could be used as a reference for the development of effective industrial scale biotechnological process for the removal of dyes and their metabolites in textile wastewater

The diagnostic and prognostic value of red cell distribution width in cardiovascular disease, current status and prospective

The red blood cell distribution width (RDW) is an index of the heterogeneity of circulating red blood cell size, which along with other standard complete blood count (CBC) parameters are used to identify hematological system diseases. Besides hematological disorders, several clinical studies have shown that an increased in the RDW may be associated with other diseases including acute pancreatitis, chronic kidney disease, gastrointestinal disorders, cancer, and of special interest in this review, cardiovascular disease (CVD). The diagnostic and prognostic value of RDW in different CVD (acute coronary syndrome, ischemic cerebrovascular disease, peripheral artery disease, atrial fibrillation, heart failure, and acute ischemic stroke) has been reviewed in this article, to provide an understanding how its measurement may be applied to improve the management of these conditions.Keywords: RDW, Biomarker, Cardiovascular disease