Flexible Information Processing Research Articles

Characterization of network switching in disorder of consciousness at multiple time scales

Objective. Recent works have shown that flexible information processing is closely related to the reconfiguration of human brain networks underlying brain functions. However, the role of network switching for consciousness is poorly explored and whether such transition can indicate the behavioral performance of patients with disorders of consciousness (DOC) remains unknown. Here, we investigate the relationship between the switching of brain networks (states) over time and the consciousness levels. Approach. By applying multilayer network methods, we calculated time-resolved functional connectivity from source-level EEG data in different frequency bands. At various time scales, we explored how the human brain changes its community structure and traverses across defined network states (integrated and segregated states) in subjects with different consciousness levels. Main results. Network switching in the human brain is decreased with increasing time scale opposite to that in random systems. Transitions of community assignment (denoted by flexibility) are negatively correlated with the consciousness levels (particularly in the alpha band) at short time scales. At long time scales, the opposite trend is found. Compared to healthy controls, patients show a new balance between dynamic segregation and integration, with decreased proportion and mean duration of segregated state (contrary to those of integrated state) at small scales. Significance. These findings may contribute to the development of EEG-based network analysis and shed new light on the pathological mechanisms of neurological disorders like DOC.

Linking Self-Construal to Creativity: The Role of Approach Motivation and Cognitive Flexibility.

While some evidence has linked the way individuals define themselves in relation to others (independent versus interdependent self-construal) to creativity, little is known about the underlying mechanism in explaining why and how self-construal influences creativity. Integrating approach-avoidance motivation theory and the dual pathway to creativity model, this research focuses on the motivational and cognitive mechanisms that transfer the effects of self-construal on creativity. Specifically, we expect that independent self-construal is a driver of creativity because it facilitates individuals’ approach motivation, which in turn increases flexible information processing. To test the three-stage mediation model, one experiment and one survey study were conducted. In Study 1, in a sample of 231 Dutch students, self-construal was manipulated by a story-writing task; approach-avoidance motivation, cognitive flexibility, and creativity were measured. In Study 2, self-construal, approach (and avoidance) motivation, cognitive flexibility, and creativity were all measured in a second sample of Dutch students (N = 146). The results of two studies supported the three-stage mediation model, showing that approach motivation and cognitive flexibility together mediated the effects of self-construal on creativity. Limitations and implications for future research are discussed.

Adaptive Engagement of Cognitive Control in Context-Dependent Decision Making.

Many decisions require a context-dependent mapping from sensory evidence to action. The capacity for flexible information processing of this sort is thought to depend on a cognitive control system in frontoparietal cortex, but the costs and limitations of control entail that its engagement should be minimized. Here, we show that humans reduce demands on control by exploiting statistical structure in their environment. Using a context-dependent perceptual discrimination task and model-based analyses of behavioral and neuroimaging data, we found that predictions about task context facilitated decision making and that a quantitative measure of context prediction error accounted for graded engagement of the frontoparietal control network. Within this network, multivariate analyses further showed that context prediction error enhanced the representation of task context. These results indicate that decision making is adaptively tuned by experience to minimize costs while maintaining flexibility.

Approach of hybrid soft computing for agricultural data classification

Soft computing is an important computational paradigm, and it provides the capability of flexible information processing to solve real world problems. Agricultural data classification is one of the important applications of computing technologies in agriculture, and it has become a hot topic because of the enormous growth of agricultural data available. Support vector machine is a powerful soft computing technique and it realizes the idea of structural risk minimization principle to find a partition hyperplane that can satisfy the class requirement. Rough set theory is another famous soft computing technique to deal with vague and uncertain data. Ensemble learning is an effective method to learn multiple learners and combine their decisions for achieving much higher prediction accuracy. In this study, the support vector machine, rough set and ensemble learning were incorporated to construct a hybrid soft computing approach to classify the agricultural data. An experimental evaluation of different methods was conducted on public agricultural datasets. The experimental results indicated that the proposed algorithm improves the performance of classification effectively. Keywords: agricultural data, soft computing, rough set, support vector machine, ensemble learning, classification DOI: 10.3965/j.ijabe.20150806.1312 Citation: Shi L, Duan Q G, Si H P, Qiao H B, Zhang J J, Ma X M. Approach of hybrid soft computing for agricultural data classification. Int J Agric & Biol Eng, 2015; 8(6): 54－61.

A Novel Genetic Programming Approach for Inferring Gene Regulatory Network

Computational intelligence (CI) techniques are well suited to many of the problems arising in biology as they have flexible information processing capabilities for handling huge volume of real life data with noise, ambiguity, missing values, and so on. To process the executed knowledge through CI approaches needs techniques from computer science & engineering, mathematics and statistics. It involves in- depth study with in the areas of genomic signals, gene regulation and homeostatic regulation. The evolutionary computing techniques like genetic programming plays vital role to effectively resolve several crucial problems related to genomics. The core objective of this work is to study and model the different regulation mechanisms involved in the living organisms and propose accurate evolutionary algorithms for inferring Gene Regulatory Networks.

Guest Editorial on Decision Making in Human and Machine Vision

Granular information processing is one of the human-inspired problem-solving aspects of natural computing, as information abstraction is inherent in human thinking and reasoning processes, and plays an essential role in human cognition. Among the different facets of natural computing fuzzy sets, rough sets and their hybridization are well accepted paradigms that are based on the construction, representation and interpretation of granules, as well as the utilization of granules for problem solving. These tools are also known as primary constituents of soft computing whose objective is to provide flexible information processing capability for handling real-life ambiguous situations. They have been successfully employed in various image processing tasks, including image segmentation, enhancement and classification, both individually or in combination with other computing techniques. The reason of such success is rooted to the fact that they provide powerful tools to describe uncertainty, naturally embedded in images, which can be exploited in various image processing tasks.

Representational Switching by Dynamical Reorganization of Attractor Structure in a Network Model of the Prefrontal Cortex

The prefrontal cortex (PFC) plays a crucial role in flexible cognitive behavior by representing task relevant information with its working memory. The working memory with sustained neural activity is described as a neural dynamical system composed of multiple attractors, each attractor of which corresponds to an active state of a cell assembly, representing a fragment of information. Recent studies have revealed that the PFC not only represents multiple sets of information but also switches multiple representations and transforms a set of information to another set depending on a given task context. This representational switching between different sets of information is possibly generated endogenously by flexible network dynamics but details of underlying mechanisms are unclear. Here we propose a dynamically reorganizable attractor network model based on certain internal changes in synaptic connectivity, or short-term plasticity. We construct a network model based on a spiking neuron model with dynamical synapses, which can qualitatively reproduce experimentally demonstrated representational switching in the PFC when a monkey was performing a goal-oriented action-planning task. The model holds multiple sets of information that are required for action planning before and after representational switching by reconfiguration of functional cell assemblies. Furthermore, we analyzed population dynamics of this model with a mean field model and show that the changes in cell assemblies' configuration correspond to those in attractor structure that can be viewed as a bifurcation process of the dynamical system. This dynamical reorganization of a neural network could be a key to uncovering the mechanism of flexible information processing in the PFC.

Failure to modulate attentional control in advanced aging linked to white matter pathology.

Advanced aging is associated with reduced attentional control and less flexible information processing. Here, the origins of these cognitive effects were explored using a functional magnetic resonance imaging task that systematically varied demands to shift attention and inhibit irrelevant information across task blocks. Prefrontal and parietal regions previously implicated in attentional control were recruited by the task and most so for the most demanding task configurations. A subset of older individuals did not modulate activity in frontal and parietal regions in response to changing task requirements. Older adults who did not dynamically modulate activity underperformed their peers and scored more poorly on neuropsychological measures of executive function and speed of processing. Examining 2 markers of preclinical pathology in older adults revealed that white matter hyperintensities (WMHs), but not high amyloid burden, were associated with failure to modulate activity in response to changing task demands. In contrast, high amyloid burden was associated with alterations in default network activity. These results suggest failure to modulate frontal and parietal activity reflects a disruptive process in advanced aging associated with specific neuropathologic processes.

Formal specification of an immune based agent architecture

The natural immune system is a subject of great research interests because it provides powerful and flexible information processing capability as a decentralized intelligent system. The immune system constitutes an excellent model of adaptive cooperation at the local level and of emergent behaviour at the global level. These concepts can be applied in the Multi-Agent Systems field where autonomous agents interact in order to solve a common goal. There exists several theories to explain immunological phenomena and software models to simulate various components in the immune system. This paper presents a formal specification of the idiotypic network theory viewed as an agent architecture. The specification gives a precise and non ambiguous description of this architecture which is validated through the automatic generation of traces and interesting properties are proven. This specification constitutes a starting point for understanding, reuse and implementations of this architecture. The approach is illustrated with the robot soccer simulation example.

Soft computing in medicine

Soft computing (SC) is not a new term; we have gotten used to reading and hearing about it daily. Nowadays, the term is used often in computer science and information technology. It is possible to define SC in different ways. Nonetheless, SC is a consortium of methodologies which works synergistically and provides, in one form or another, flexible information processing capability for handling real life ambiguous situations. Its aim is to exploit the tolerance for imprecision, uncertainty, approximate reasoning and partial truth in order to achieve tractability, robustness and low-cost solutions. SC includes fuzzy logic (FL), neural networks (NNs), and genetic algorithm (GA) methodologies. SC combines these methodologies as FL and NN (FL–NN), NN and GA (NN–GA) and FL and GA (FL–GA). Recent years have witnessed the phenomenal growth of bio-informatics and medical informatics by using computational techniques for interpretation and analysis of biological and medical data. Among the large number of computational techniques used, SC, which incorporates neural networks, evolutionary computation, and fuzzy systems, provides unmatched utility because of its demonstrated strength in handling imprecise information and providing novel solutions to hard problems. The aim of this paper is to introduce briefly the various SC methodologies and to present various applications in medicine between the years 2000 and 2008. The scope is to demonstrate the possibilities of applying SC to medicine-related problems. The recent published knowledge about use of SC in medicine is researched in MEDLINE. This study detects which methodology or methodologies of SC are used frequently together to solve the special problems of medicine. According to MEDLINE database searches, the rates of preference of SC methodologies in medicine were found as 68% of FL–NN, 27% of NN–GA and 5% of FL–GA. So far, FL–NN methodology was significantly used in medicine. The rates of using FL–NN in clinical science, diagnostic science and basic science were found as %83, %71 and %48, respectively. On the other hand NN–GA and FL–GA methodologies were mostly preferred by basic science of medicine. Another message emerging from this survey is that the number of papers which used NN–GA methodology has continuously risen until today. Also search results put the case clearly that FL–GA methodology has not applied well enough to medicine yet. Undeniable interest in studying SC methodologies in genetics, physiology, radiology, cardiology, and neurology disciplines proves that studying SC is very fruitful in these disciplines and it is expected that future researches in medicine will use SC more than it is used today to solve more complex problems.

Memory influences on hippocampal and striatal neural codes: Effects of a shift between task rules

Interactions with neocortical memory systems may facilitate flexible information processing by hippocampus. We sought direct evidence for such memory influences by recording hippocampal neural responses to a change in cognitive strategy. Well-trained rats switched (within a single recording session) between the use of place and response strategies to solve a plus maze task. Maze and extramaze environments were constant throughout testing. Place fields demonstrated (in-field) firing rate and location-based reorganization [Leutgeb, S., Leutgeb, J. K., Barnes, C. A., Moser, E. I., McNaughton, B. L., & Moser, M. B. (2005). Independent codes for spatial and episodic memory in hippocampal neuronal ensembles. Science, 309, 619–623] after a task switch, suggesting that hippocampus encoded each phase of testing as a different context, or episode. The task switch also resulted in qualitative and quantitative changes to discharge that were correlated with an animal’s velocity or acceleration of movement. Thus, the effects of a strategy switch extended beyond the spatial domain, and the movement correlates were not passive reflections of the current behavioral state. To determine whether hippocampal neural responses were unique, striatal place and movement-correlated neurons were simultaneously recorded with hippocampal neurons. Striatal place and movement cells exhibited a response profile that was similar, but not identical, to that observed for hippocampus after a strategy switch. Thus, retrieval of a different memory led both neural systems to represent a different context. However, hippocampus may play a special (though not exclusive) role in flexible spatial processing since correlated firing amongst cell pairs was highest when rats successfully switched between two spatial tasks. Correlated firing by striatal cell pairs increased following any strategy switch, supporting the view that striatum codes change in reinforcement contingencies.

Soft approaches to information retrieval and information access on the Web: An introduction to the special topic section

AbstractThe World Wide Web is a popular and interactive medium used to collect, disseminate, and access an increasingly huge amount of information, which constitutes the mainstay of the so‐called information and knowledge society. Because of its spectacular growth, related to both Web resources (pages, sites, and services) and number of users, the Web is nowadays the main information repository and provides some automatic systems for locating, accessing, and retrieving information. However, an open and crucial question remains: how to provide fast and effective retrieval of the information relevant to specific users' needs. This is a very hard and complex task, since it is pervaded with subjectivity, vagueness, and uncertainty. The expression soft computing refers to techniques and methodologies that work synergistically with the aim of providing flexible information processing tolerant of imprecision, vagueness, partial truth, and approximation. So, soft computing represents a good candidate to design effective systems for information access and retrieval on the Web. One of the most representative tools of soft computing is fuzzy set theory. This special topic section collects research articles witnessing some recent advances in improving the processes of information access and retrieval on the Web by using soft computing tools, and in particular, by using fuzzy sets and/or integrating them with other soft computing tools. In this introductory article, we first review the problem of Web retrieval and the concept of soft computing technology. We then briefly introduce the articles in this section and conclude by highlighting some future research directions that could benefit from the use of soft computing technologies.

Special Issue on Motion Control and its Applications in Robot Technology (RT)

Robot Technology (RT) now surpasses information technology (IT) in strategic importance. With robot applications leading to expansion beyond manufacturing into the bioindustrial, medical/welfare, and lifesciences fields, conversion from an industrial to a solutions business is critical. This requires that we define new robot concepts that push the envelope beyond conventional consideration into intellectualization that functions throughout the real world through robotic technologies. This further emphasizes the importance of motion control as a major robotic innovation. Advances in high-function hardware, flexible information processing, and real-time image processing are expected to launch new trends in addition to the above. This special issue presents papers and technical reports featuring a wide academic and industrial repertoire. Topics cover aspects of motion viewed through RT. We thank Prof. Kazuhiro Kosuge of Tohoku University, the contributors, and the reviewers who made this special issue possible. Thanks also go the editor-in-chief of the Journal of Robotics and Mechatronics, Prof. Makoto Kaneko of Hiroshima University, who provided the opportunity for editing this special issue.

Musical development of elderly people.

Creating and listening to music typically depends on hearing, flexibility of the voice, motor skills, and cognitive processing. Declines in these factors are not generally apparent prior to the sixth decade due to compensation by flexible information processing. Musical activities of elderly people (with a focus on Germany) are described, beginning with choir attendance, singing, and instrumental training. The survey indicates a great interest among elderly persons to initiate opportunities for making music by themselves; this suggests a new niche for professional music educators. Changes in the lives of professional musicians at the age of retirement are described. Music listening and music preferences are discussed, not only for normally aging people but also for aged persons in clinics and caregiving homes. The significance of psychological research about musical development for music therapy with elderly people is stressed. Research into the development of musical ability has been an important theme in the psychology of music. Within the last decade, however, there has been a turn to research on the development of ability in music in adults and aged people. For a long time the opinion prevailed that musical ability develops mainly in infancy and childhood. It is still conjectured that You can't teach an old dog new tricks. This paper addresses these issues within the context of practice and research, primarily in Germany. Although lifelong development has been a central concept in developmental psychology for decades (Baltes & Schaie, 1973), in Germany it became a primary research focus with respect to the psychology of music in 1993 (Gembris, 1993). The present article concentrates on the developmental aspects of musical ability in elderly adults. The first part deals with age related changes in basic abilities. The second part concerns musical activities of elderly people. The last part concerns the motivation for playing and listening to music. Basic Abilities A survey of the literature on changes in musical ability in adults and aged is fraught with the difficulties that arise equally in research into the musical ability in the early years of life. Musical performance differs from individual to individual to a considerable degree (Gembris, 1998, p. 373). These differences grow with age. Most research results, therefore, must be interpreted with caution. They are mostly derived from cross-sectional statistical designs. Differences between persons in different age cohorts are interpreted as developmental gain. Real understanding can only stem from longitudinal studies that have not yet been conducted. Yet another problem in research, especially concerning people in older age groups, derives from the flexibility of human capacities. The slow decay of musical ability over many years may remain unnoticed because deficits in perception and performance are compensated by enhanced attention and control (Maier, Ambuehl, & Schandry, 1994, p. 167). Hearing Figure 1 shows decay in the perception of sound intensity of age groups from 18 - 24 to 65 - 70 years. Within the youngest group already there exists a considerable difference between males and females. But not until the age of 50 years does it appear that men are harder of hearing than women of the same age. At this age the median difference is 20 dB, particularly in the high frequencies which are especially important in the perception of consonants in speech and high tones played by certain orchestral instruments such as the flute. This means high sounds have to be four times as intense in order to achieve the same loudness levels as low sounds. The decay in the perception of intensity can often be compensated by suitable technical aids. But nevertheless, problems arise. Older people develop their individual taste for a frequency spectrum. Correcting the hearing deficits using a hearing aid changes spectral and temporal characteristics of the sound and alters its original perceptual characteristics. …

Knowledge-Based Leak Monitoring for Pipelines

This paper presents a hybrid knowledge-based approach for leak monitoring in pipes and pipelines used for the transport of fluids (liquids, LPG, gases). The hybrid leak detection and localization scheme combines Real Time Transient Model (RTTM) based methods with Artificial Neural Networks (ANN). This enables to combine analytical knowledge available prior to system operation with knowledge by example, presented In form of measured process signals. Knowledge by example can be presented before and during system operation, enabling a flexible information processing scheme. A real application for a pipeline transporting petrochemical liquids demonstrates the performance of the approach.

２１世紀に向けた結晶学の新たな挑戦 ６． 新物質を求めて 原子レベルで機能調和した人工格子

Toward advanced information the oriented society, the creation of novel functional sensors and devices which can detect many kinds of information such as electric field, magnet field and light will become important to realize flexible information and transfer processes in human bodies. The transition metal oxides possess numerous functional properties, including ferroelectric-piezo-electric, photoactive, ferromagnetic, spin glass, and superconductive properties. By integrating these characteristics in function harmonized artificial lattices at atomic or molecular level, it is possible to create highly sensitive sensor materials for external field (super-five senses) and flexible information processing devices (brain type memory) . In this article, we describe how to create novel functional oxide superlattices and heterostructures as sensitive and multi-functional devices.

Excitotoxic Septal Lesions Result in Spatial Memory Deficits and Altered Flexibility of Hippocampal Single-Unit Representations

The septal nuclei are reciprocally connected with the hippocampal formation and contribute importantly to spatial and memory processing. Using excitotoxic lesions of the septal area, we investigated whether neurodegeneration in subcortical projections to hippocampus can compromise flexible information processing by hippocampal single units. In agreement with the mild effects of excitotoxic septal lesions on hippocampal physiology compared with fimbria-fornix lesions and septal inactivation, we observed limited lesion effects on single-unit activity. The location specificity of hippocampal complex spike cells remained unchanged, but a less reliable location-dependent discharge was observed in experimental animals with a pronounced postoperative working memory deficit. Testing in the absence of ambient illumination and in a new environment revealed that the spatial correlates of complex spike cells in lesioned animals may rely on a more limited set of sensory cues. Altered sensory cues resulted in a significantly different response pattern between the control and lesion group in the new environment, a situation that normally results in place field reorganization. Such a group difference was not observed during dark testing, a condition in which place field reorganization is less prominent. A contribution of hippocampal interneurons to the observed alterations in the spatial properties of the principal cells was suggested by decreased theta modulation in the lesioned group. Because excitotoxic lesions result in memory deficits that resemble age-related memory problems in the absence of age-related degenerative processes, we suggest that septal neurodegeneration could directly contribute to those behavioral changes with advanced age that correlate with functional alterations in the hippocampal formation.

Activity-dependent potentiation of synaptic transmission from L30 inhibitory interneurons of aplysia depends on residual presynaptic Ca2+ but not on postsynaptic Ca2+.

Activity-induced short-term synaptic enhancement (STE) is a common property of neurons, one that can endow neural circuits with the capacity for rapid and flexible information processing. Evidence from a variety of systems indicates that the expression of STE depends largely on the action of residual Ca2+, which enters the presynaptic terminal during activity. We have shown previously that a Ca2+-dependent STE in the inhibitory synapse between interneurons L30 and L29 in the abdominal ganglion of Aplysia californica has a functional role in regulating the gain of the siphon withdrawal circuit through facilitated recurrent inhibition onto the L29s. In the present paper, we further explore the role of Ca2+ in L30 STE by examining two basic issues: 1) What is the role of residual presynaptic Ca2+ in the maintenance of L30 STE? We examine this question by first inducing STE in the L30s then rapidly buffering presynaptic free calcium through the use of the photoactivated Ca2+ chelator diazo-4, which was preloaded into the L30 neurons. Three forms of STE in the L30s were examined: frequency facilitation (FF), augmentation (AUG), and posttetanic potentiation (PTP). In each case, the activation-induced enhancement of the L30 to L29 synapse was reduced to preactivation levels at the first test pulse following photolysis of diazo-4. 2) What is the role of postsynaptic Ca2+ in the induction of L30 STE? We examine whether there is a postsynaptic requirement of elevated Ca2+ for the induction of L30 STE by first injecting the calcium chelator bis-(o-aminophenoxy)-N,N,N',N'-tetraacetic acid (BAPTA) into the postsynaptic cell L29 (at levels sufficient to block transmitter release from the L29s), to prevent any increase in postsynaptic intracellular Ca2+ that may occur during L30 (presynaptic) activation. We found that BAPTA injection did not effect either the induction or the time course of FF, AUG, or PTP in the L30s. Taken collectively, our data indicate that all forms of STE in the L30s depend on presynaptic free cytosolic Ca2+ for their maintenance but do not require the elevation of postsynaptic Ca2+ for their induction.

Development and Future for Construction Management System at Field

In the recent years, the construction industry is facing more competition due to the introduction ofreformed bid system and other changes in the market.Although the industry is working harder to become more competitive, negative factors such as aging work force and inefficient structure of multiple layers of contracts are preventing improvement of productivity to reduce the cost.On the other hand, performance and prices of computers and other information processing equipment are drastically improving these days. I think the construction industry is suited for adopting computer systems since it is the nature of the industry to produce one of a kind taylor made products sites at the field and each job requires flexible information processing system to handle different tasks in real time bases.Therefore, the future of construction management system at the field should take more steps toward office automation using computers. However, it will not be efficient if each individual job sites decided to develop their own system and not sharing with others.In this monograph, I would like to examine the past history of office automation at the field and it's future.

A self-organizing model of walking patterns of insects

Insects generate walking patterns which depend upon external conditions. For example, when an insect is exposed to an additional load parallel to the direction in which it is walking, the walking pattern changes according to the magnitude of the load. Furthermore, even after some of its legs have been amputated, an insect will produce walking patterns with its remaining legs. These adaptations in insect walking could not previously be explained by a mathematical model, since the mathematical models were based upon the hypothesis that the relationship between walking velocity and walking patterns is fixed under all conditions. We have produced a mathematical model which describes self-organizing insect walking patterns in real-time by using feedback information regarding muscle load (Kimura et al. 1993). As part of this model, we introduced a new rule to coordinate leg movement, in which the information is circulated to optimize the efficiency of the energy transduction of each effector organ. We describe this mechanism as `the least dissatisfaction for the greatest number of elements'. In this paper, we introduce the following aspects of this model, which reflect adaptability to changing circumstances: (1) after one leg is exposed to a transient perturbation, the walking pattern recovers swiftly; (2) when the external load parallel to the walking direction is continuously increased or decreased, the pattern transition point is shifted according to the magnitude of the load increment or decrement. This model generates a walking pattern which optimizes energy consumption at a given walking velocity even under these conditions; and (3) when some of the legs are amputated, the model generates walking patterns which are consistent with experimental results. We also discuss the ability of a hierarchical self-organizing model to describe a swift and flexible information processing system.