Symbolic Processing Techniques in Connectionist Networks and Their Application to High-Level Cognitive Tasks

Author(s):  
Michael G. Dyer
Author(s):  
Mark Reybrouck

Musical sense-making relies on two distinctive strategies: tracking the moment-to-moment history of the actual unfolding and recollecting actual and previous sounding events in a kind of synoptic overview. Both positions are not opposed but complement each other. The aim of this contribution, therefore, is to provide a comprehensive framework that provides both conceptual and operational tools for coping with the sounds. Five major possibilities are proposed in this regard: (i) the concepts of perspective and resolution, which refer to the distance the listener takes with respect to the sounding music and the fine-grainedness of his/her discriminative abilities; (ii) the continuous/discrete dichotomy which conceives of the music as one continuous flow as against a division in separate and distinct elements; (iii) the in time/outside-of-time distinction, with the former proceeding in real time and the latter proceeding outside of the time of unfolding; (iv) the deictic approach to musical sense-making, which conceives of an act of mental pointing to the music, and (v) the levels of processing, which span a continuum between primitive sensory reactivity to actual sounding stimuli and high-level symbolic processing.


2019 ◽  
Author(s):  
Cody W. Whoolery ◽  
Sanghee Yun ◽  
Ryan P. Reynolds ◽  
Melanie J. Lucero ◽  
Ivan Soler ◽  
...  

ABSTRACTAstronauts on interplanetary space missions - such as to Mars - will be exposed to space radiation, a spectrum of highly-charged, fast-moving particles that includes 56Fe and 28Si. Earth-based preclinical studies with mature, “astronaut-aged” rodents show space radiation decreases performance in low- and some high-level cognitive tasks. Given the prevalence of touchscreens in astronaut training and in-mission assessment, and the ability of rodent touchscreen tasks to assess the functional integrity of brain circuits and multiple cognitive domains in a non-aversive way, it is surprising the effect of space radiation on rodent touchscreen performance is unknown. To fill this knowledge gap, 6-month-old C57BL/6J male mice were exposed to whole-body space radiation and assessed on a touchscreen battery starting 1-month later. Relative to Sham, 56Fe irradiation did not overtly change performance on tasks of visual discrimination, reversal learning, rule-based, or object-spatial paired associates learning, suggesting preserved functional integrity of supporting brain circuits. Surprisingly, 56Fe irradiation led to better performance on a dentate gyrus-reliant task of pattern separation ability. Irradiated mice discriminated similar visual cues in ∼40% fewer days and ∼40% more accurately than control mice. Improved pattern separation was not touchscreen-, radiation-particle, or neurogenesis-dependent, as both 56Fe and 28Si irradiation led to faster context discrimination (e.g. Sham Block 5 vs. 56Fe Block 2) in a non-touchscreen task and 56Fe led to fewer new dentate gyrus neurons relative to Sham. These data urge revisitation of the broadly-held view that space radiation is detrimental to cognition.SIGNIFICANCE STATEMENTAstronauts on an interplanetary mission - such as to Mars - will be unavoidably exposed to galactic cosmic radiation, a spectrum of highly-charged, fast-moving particles. Rodent studies suggest space radiation is detrimental to cognition. However, here we show this is not universally true. Mature mice that received whole body exposure to Mars-relevant space radiation perform similarly to control mice on high-level cognitive tasks, reflecting the functional integrity of key neural circuits. Even more surprisingly, irradiated mice perform better than controls in both appetitive and aversive tests of pattern separation, a mission-critical task reliant on dentate gyrus integrity. Notably, improved pattern separation was not touchscreen-, radiation-particle-, or neurogenesis-dependent. Our work urges revisitation of the generally-accepted conclusion that space radiation is detrimental to cognition.


Author(s):  
V. Santhi ◽  
B. K. Tripathy

The image quality enhancement process is considered as one of the basic requirement for high-level image processing techniques that demand good quality in images. High-level image processing techniques include feature extraction, morphological processing, pattern recognition, automation engineering, and many more. Many classical enhancement methods are available for enhancing the quality of images and they can be carried out either in spatial domain or in frequency domain. But in real time applications, the quality enhancement process carried out by classical approaches may not serve the purpose. It is required to combine the concept of computational intelligence with the classical approaches to meet the requirements of real-time applications. In recent days, Particle Swarm Optimization (PSO) technique is considered one of the new approaches in optimization techniques and it is used extensively in image processing and pattern recognition applications. In this chapter, image enhancement is considered an optimization problem, and different methods to solve it through PSO are discussed in detail.


2009 ◽  
Vol 66 (6) ◽  
pp. 1023-1028 ◽  
Author(s):  
James H. Churnside ◽  
Eirik Tenningen ◽  
James J. Wilson

Abstract Churnside, J. H., Tenningen, E., and Wilson, J. J. 2009. Comparison of data-processing algorithms for the lidar detection of mackerel in the Norwegian Sea. – ICES Journal of Marine Science, 66: 1023–1028. A broad-scale lidar survey was conducted in the Norwegian Sea in summer 2002. Since then, various data-processing techniques have been developed, including manual identification of fish schools, multiscale median filtering, and curve fitting of the lidar profiles. In the automated techniques, applying a threshold to the data, as carrried out already to eliminate plankton scattering, has been demonstrated previously to improve the correlation between lidar and acoustic data. We applied these techniques to the lidar data of the 2002 survey and compared the results with those of a mackerel (Scomber scombrus) survey done by FV “Endre Dyrøy” and FV “Trønderbas” during the same period. Despite a high level of variability in both lidar and trawl data, the broad-scale distribution of fish inferred from the lidar agreed with that of mackerel caught by the FV “Endre Dyrøy”. This agreement was obtained using both manual and automated processing of the lidar data. This work is the first comparison of concurrent lidar and trawl surveys, and it demonstrates the utility of airborne lidar for mackerel studies.


Author(s):  
Mohammed Al-Momin ◽  
Ammar Almomin

<span lang="EN-US">The conventional method for detecting blood abnormality is time consuming and lacks the high level of accuracy. In this paper a MATLAB based solution has been suggested to tackle the problem of time consumption and accuracy. Three types of blood abnormality have been covered here, namely, anemia which is characterized by low count of red blood cells (RBCs), Leukemia which is depicted by increasing the number of white blood cells (WBCs), and sickle cell blood disorder which is caused by a deformation in the shape of red cells. The algorithm has been tested on different images of blood smears and noticed to give an acceptable level of accuracy. Image processing techniques has been used here to detect the different types of blood constituents. Unlike many other researches, this research includes the blood sickling disorder which is epidemic in certain regions of the world, and offers a more accuracy than other algorithms through the use of detaching overlapped cells strategy.</span>


2021 ◽  
Author(s):  
Fumeng Yang

We present exploratory research of virtual reality techniques and mnemonic devices to assist in retrieving knowledge from scholarly articles. We used abstracts of scientific publications to represent knowledge in scholarly articles; participants were asked to read, remember, and retrieve knowledge from a set of abstracts. We conducted an experiment to compare participants’ recall and recognition performance in three different conditions: a control condition without a pre-specified strategy to test baseline individual memory ability, a condition using an image-based variant of a mnemonic called a “memory palace,” and a condition using a virtual reality-based variant of a memory palace. Our analyses show that using a virtual reality-based memory palace variant greatly increased the amount of knowledge retrieved and retained over the baseline, and it shows a moderate improvement over the other image-based memory palace variant. Anecdotal feedback from participants suggested that personalizing a memory palace variant would be appreciated. Our results support the value of virtual reality for some high-level cognitive tasks and help improve future applications of virtual reality and visualization.


2019 ◽  
Vol 20 (20) ◽  
pp. 5158 ◽  
Author(s):  
Meng Liang ◽  
Yuhang Fu ◽  
Ruibo Gao ◽  
Qiaoqiao Wang ◽  
Junlan Nie

Molecular visualization is often challenged with rendering of large molecular structures in real time. The key to LOD (level-of-detail), a classical technology, lies in designing a series of hierarchical abstractions of protein. In the paper, we improved the smoothness of transition for these abstractions by constructing a complete binary tree of a protein. In order to reduce the degree of expansion of the geometric model corresponding to the high level of abstraction, we introduced minimum ellipsoidal enveloping and some post-processing techniques. At the same time, a simple, ellipsoid drawing method based on graphics processing unit (GPU) is used that can guarantee that the drawing speed is not lower than the existing sphere-drawing method. Finally, we evaluated the rendering performance and effect on series of molecules with different scales. The post-processing techniques applied, diffuse shading and contours, further conceal the expansion problem and highlight the surface details.


2015 ◽  
pp. 860-878
Author(s):  
V. Santhi ◽  
B. K. Tripathy

The image quality enhancement process is considered as one of the basic requirement for high-level image processing techniques that demand good quality in images. High-level image processing techniques include feature extraction, morphological processing, pattern recognition, automation engineering, and many more. Many classical enhancement methods are available for enhancing the quality of images and they can be carried out either in spatial domain or in frequency domain. But in real time applications, the quality enhancement process carried out by classical approaches may not serve the purpose. It is required to combine the concept of computational intelligence with the classical approaches to meet the requirements of real-time applications. In recent days, Particle Swarm Optimization (PSO) technique is considered one of the new approaches in optimization techniques and it is used extensively in image processing and pattern recognition applications. In this chapter, image enhancement is considered an optimization problem, and different methods to solve it through PSO are discussed in detail.


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