Multiple Levels Of Information Processing Research Articles

An Evaluation of Internet of Things and Cyber-Physical System Integration

In order to make physical systems run more efficiently and effectively at multiple levels of information processing, Cyber-Physical Systems (CPS) combine physical processes, Computing, Communication, and Control (the 3Cs) into a single system. There are many factors that make solving the problem of packet transmission in CPS difficult, including unforeseeable node mobility, low number of nodes, lack of global data, and intermittent network access. Currently, there is no good answer to this problem in the literature. The impact of the CPS on engineered systems is much greater in the present and future. Cyber-physical system integration often presents unique challenges in the fields of design, implementation, and application. One of the goals of this research is to better understand the various definitions of an integrated CPS, as well as the growth of new research areas in this field. The application of CPSs faces a number of difficulties, including those related to efficiency, reliability, controllability, and security. We are moving forward in technological innovation with the development of CPSs and the Internet of Things (IoT). It is possible for engineers to gain a better understanding of engineering systems and management modules by utilizing the CPS-IoT models.

Global shape perception contributes to crossmodal correspondences.

The Bouba/Kiki effect constitutes a classic sound-shape correspondence, with the meaningless sounds "Bouba" and "Kiki" being mapped onto smooth and spiky patterns, respectively. While it is commonly believed that the Bouba/Kiki effect is driven by the local rounded and angular features of a pattern, here we investigated the importance of an alternative level of visual processing-namely the global contours. We adopted compound radial frequency (RF) patterns and segmented them into convexities (outward curves) or concavities (inward curves). Note that convexities are more informative in terms of inferring the global contour than concavities. When the perceptual grouping of segments was facilitated by increasing their length, the grouping of convexities was more efficient than that of concavities as manifested by the closer matching judgments to the compound RF patterns. When we interfered with the perceptual grouping of segments by rotating each segment by 180°, the matching consensus of convexities was higher when they were presented in the original than in the reversed orientation. Hence, the Bouba/Kiki effect was susceptible to the factors modulating the perceptual grouping process going from segments to the global contour, suggesting that the Bouba/Kiki effect may occur at the global level of shape perception. Sound-shape correspondences would therefore seem to be expressed at multiple levels of information processing, furthering our understanding of the development, underpinning neural mechanisms, and applications of crossmodal correspondences. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Subtyping cognitive profiles in Autism Spectrum Disorder using a Functional Random Forest algorithm

DSM-5 Autism Spectrum Disorder (ASD) comprises a set of neurodevelopmental disorders characterized by deficits in social communication and interaction and repetitive behaviors or restricted interests, and may both affect and be affected by multiple cognitive mechanisms. This study attempts to identify and characterize cognitive subtypes within the ASD population using our Functional Random Forest (FRF) machine learning classification model. This model trained a traditional random forest model on measures from seven tasks that reflect multiple levels of information processing. 47 ASD diagnosed and 58 typically developing (TD) children between the ages of 9 and 13 participated in this study. Our RF model was 72.7% accurate, with 80.7% specificity and 63.1% sensitivity. Using the random forest model, the FRF then measures the proximity of each subject to every other subject, generating a distance matrix between participants. This matrix is then used in a community detection algorithm to identify subgroups within the ASD and TD groups, and revealed 3 ASD and 4 TD putative subgroups with unique behavioral profiles. We then examined differences in functional brain systems between diagnostic groups and putative subgroups using resting-state functional connectivity magnetic resonance imaging (rsfcMRI). Chi-square tests revealed a significantly greater number of between group differences (p < .05) within the cingulo-opercular, visual, and default systems as well as differences in inter-system connections in the somato-motor, dorsal attention, and subcortical systems. Many of these differences were primarily driven by specific subgroups suggesting that our method could potentially parse the variation in brain mechanisms affected by ASD.

Neuronal Correlates of Functional Coupling between Reach- and Grasp-Related Components of Muscle Activity.

Coordinated reach-to-grasp movements require precise spatiotemporal synchrony between proximal forelimb muscles (shoulder, elbow) that transport the hand toward a target during reach, and distal muscles (wrist, digit) that simultaneously preshape and orient the hand for grasp. The precise mechanisms through which the redundant neuromuscular circuitry coordinates reach with grasp, however, remain unclear. Recently, Geed and Van Kan (2016) demonstrated, using exploratory factor analysis (EFA), that limited numbers of global, template-like transport/preshape- and grasp-related muscle components underlie the complexity and variability of intramuscular electromyograms (EMGs) of up to 21 distal and proximal muscles recorded while monkeys performed reach-to-grasp tasks. Importantly, transport/preshape- and grasp-related muscle components showed invariant spatiotemporal coupling, which provides a potential mechanism for coordinating forelimb muscles during reach-to-grasp movements. In the present study, we tested whether ensemble discharges of forelimb neurons in the cerebellar nucleus interpositus (NI) and its target, the magnocellular red nucleus (RNm), a source of rubrospinal fibers, function as neuronal correlates of the transport/preshape- and grasp-related muscle components we identified. EFA applied to single-unit discharges of populations of NI and RNm neurons recorded while the same monkeys that were used previously performed the same reach-to-grasp tasks, revealed neuronal components in the ensemble discharges of both NI and RNm neuronal populations with characteristics broadly similar to muscle components. Subsets of NI and RNm neuronal components were strongly and significantly crosscorrelated with subsets of muscle components, suggesting that similar functional units of reach-to-grasp behavior are expressed by NI and RNm neuronal populations and forelimb muscles. Importantly, like transport/preshape- and grasp-related muscle components, their NI and RNm neuronal correlates showed invariant spatiotemporal coupling. Clinical and lesion studies have reported disruption of coupling between reach and grasp following cerebellar damage; the present results expand on those studies by identifying a neuronal mechanism that may underlie cerebellar contributions to spatiotemporal coordination of distal and proximal limb muscles during reaching to grasp. We conclude that finding similar functional units of behavior expressed at multiple levels of information processing along interposito-rubrospinal pathways and forelimb muscles supports the hypothesis that functionally related populations of NI and RNm neurons act synergistically in the control of complex coordinated motor behaviors.

A Data Forwarding Scheme Based on Delaunay Triangulation for Cyber-Physical Systems

Cyber-physical system (CPS) cooperates with physical processes, computing, communication, and control (3C) into multiple levels of information processing and operation management to streamline and fortify the operation of physical systems. Due to the unique characteristics, such as unpredictable node mobility, low node density, lack of global information and network intermittent connectivity, an algorithm for data forwarding in CPS is a considerably difficult and challenging problem, and there is no good solution to it in existing works. In this paper, we propose a fully-fledged data forwarding algorithm tailored to the CPS environment. The proposed protocol, called data forwarding based on Delaunay triangulation (DFDT), takes into account the computational geometry based on Delaunay triangulation to form a few triangle communities according to nodes’ connectivity. Data in a community are forwarded to other nodes once a node comes into this community to increase the data delivery ratio. DFDT achieves a good performance by data gathering and sending data to other nodes with higher probability of meeting the link. An extensive simulation has been performed to validate the analytical results and to show the effectiveness of our approach compared with the three existing popular data forwarding algorithms.

Adaptive Information Processing and a Systemic Biopsychosocial Model

Shapiro’s (2001) adaptive information processing (AIP) model portrays an innate healing system hypothesized to be composed of neurophysiological mechanisms of action causally related to the resolution of disturbing life experiences. The author expands the model to include psychosocial mechanisms and suggests that a model of a biopsychosocial system can best depict causal properties related to positive outcomes of eye movement desensitization and reprocessing (EMDR). Teleofunctionalist and evolutionary perspectives are applied: the first, to explain the inclusion of the psychological and social features highlighted in the updated model; the second, to support the hypothesis that AIP is a goal of the human attachment system. It is posited that bonding, following a disturbing life experience, facilitates the access of information related to previous states, thus allowing an update of self/world models. These interactions are analogous to psychotherapeutic encounters, with multiple levels of information processing at subpersonal, personal, and interpersonal levels. Analysis of the causal properties of personal and interpersonal levels supports a broader understanding of AIP’s scope in conceptualizing psychopathology and informing treatment applications and research.

Concepts and principles in the analysis of brain networks

The brain is a large-scale network, operating at multiple levels of information processing ranging from neurons, to local circuits, to systems of brain areas. Recent advances in the mathematics of graph theory have provided tools with which to study networks. These tools can be employed to understand how the brain's behavioral repertoire is mediated by the interactions of objects of information processing. Within the graph-theoretic framework, networks are defined by independent objects (nodes) and the relationships shared between them (edges). Importantly, the accurate incorporation of graph theory into the study of brain networks mandates careful consideration of the assumptions, constraints, and principles of both the mathematics and the underlying neurobiology. This review focuses on understanding these principles and how they guide what constitutes a brain network and its elements, specifically focusing on resting-state correlations in humans. We argue that approaches that fail to take the principles of graph theory into consideration and do not reflect the underlying neurobiological properties of the brain will likely mischaracterize brain network structure and function.

Development of anxiety: the role of threat appraisal and fear learning.

Anxious individuals exhibit threat biases at multiple levels of information processing. From a developmental perspective, abnormal safety learning in childhood may establish threat-related appraisal biases early, which may contribute to chronic disorders in adulthood. This review illustrates how the interface among attention, threat appraisal, and fear learning can generate novel insights for outcome prediction. This review summarizes data on amygdala function, as it relates to learning and attention, highlights the importance of examining threat appraisal, and introduces a novel imaging paradigm to investigate the neural correlates of threat appraisal and threat-sensitivity during extinction recall. This novel paradigm can be used to investigate key questions relevant to prognosis and treatment. Depression and Anxiety, 2011.© 2010 Wiley-Liss, Inc.

Cognitive styles in the context of modern psychology: Toward an integrated framework of cognitive style.

The goals of this article are to elucidate trends and perspectives in the field of cognitive style research and to propose an integrated framework to guide future research. This is accomplished by means of a comprehensive literature review of the major advances and the theoretical and experimental problems that have accumulated over the years and by a discussion of the promising theoretical models that can be further developed, in part, with modern neuroscience techniques and with research from different psychological fields. On the basis of the research reviewed in this article, the author suggests that cognitive styles represent heuristics that individuals use to process information about their environment. These heuristics can be identified at multiple levels of information processing, from perceptual to metacognitive, and they can be grouped according to the type of regulatory function they exert on processes ranging from automatic data encoding to conscious executive allocation of cognitive resources.

Acute hypoglycemia impairs the functioning of the central but not peripheral nervous system

Acute hypoglycemia impairs functions of the central nervous system, but few controlled studies have assessed the impact of hypoglycemia on the function of the peripheral nervous system. Sixteen non-diabetic humans underwent two separate hyperinsulinemic glucose clamp procedures on different study days, in a counter-balanced fashion. On one occasion, euglycemia was maintained (blood glucose, 5.0 mmol l −1), and on the other occasion, hypoglycemia (blood glucose, 2.6 mmol l −1) was induced. During each condition, subjects performed a combined psychometric, cognitive-experimental and psychophysical test battery, and measures were made (in the dominant median and common peroneal nerves) of the motor nerve conduction velocities and the amplitudes of the motor action potentials. Hypoglycemia caused impaired performance of general cognitive and information processing tasks ( P<.05), but nerve conduction velocities and the amplitudes of motor action potentials were unaffected. Conduction velocities of the common peroneal nerve decreased from baseline within each experimental condition, perhaps due to hyperinsulinemia. Overall, these results demonstrate that multiple levels of information processing in the brain may alter while peripheral nerve function remains intact, and imply that peripheral neurons do not have the same obligate requirement for glucose as a metabolic fuel as neurons of the central nervous system.

Integrating Organizational and Individual Information Processing Perspectives on Choice

Existing information processing theories of strategic choice focus on either the organizational or individual level of analysis. This single level focus makes these theories incomplete representations of how strategic decisions are actually made in organizations. We believe an integration of these two levels is necessary for a comprehensive view of choice. This paper thus proposes a parallel process model of strategic decision making that integrates organizational and individual level information processing perspectives. The integrated, comprehensive view afforded by the proposed model enhances understanding of strategic decision making by identifying (1) multiple ways in which bias can enter into choices and (2) dual level influences on decision activities such as information gathering and alternative generation. The proposed model portrays strategic decision making as complex, multilevel information processing and choices as emergent outcomes of that processing. The model is developed as follows. First, the individual level of the model is generated by recognizing that people process information in stages. The notion of stages is used because it depicts the basic structure of information processing and is widely supported by empirical research. Second, the organizational level of the model is articulated by acknowledging organizations (1) process information in stages and (2) exhibit information processing activities analogous to those at the individual level. Third, a series of linking mechanisms connecting individual information processing stages to analogous organizational level ones is proposed. These linking mechanisms thus conceptually operationalize the integration of the two levels. Fourth, three contingency variables are presented to flesh out the model and formulate propositions. Contingency variables specifically acknowledge differences in information processing across organizations. A final section of the paper explains how key variables in the proposed model can be operationalized and outlines a test for the presence of multiple levels of information processing in a strategic choice context.