Complex Information Processing Research Articles

The nature of interpretive phenomenological reflective practice for junior doctors

ABSTRACTThe role of reflective practice in clinical professional development has been demonstrated in the extant literature to be relevant and important. As a cognitive strategy, reflection allows clinicians to inform their ability to collect and process complex information; make sound clinical judgements; deliver patient-centred care and learn from medical mistakes. Therefore, learning from reflection is necessary for lifelong and continual professional development. The imperative to derive meaning from clinical practice makes reflection an important aspect of clinical training. Indeed, reflection compels the practitioner to question one’s already held professional values and attitudes during the mental capture of clinical experience. Interpretive phenomenology is a useful approach for enhancing the understanding of lived experiences. This paradigm has been much under-utilised in medical education. Understanding reflective practice for clinicians from an interpretive phenomenological perspective serves to create the potential for linking theory and practice within the context of professionalism and clinical responsibility. This article attempts to demonstrate the efficacy of interpretive phenomenological perspective to reflective practice within the context of clinical training, medical education, and on becoming effective reflective practitioners.

Multisensory feature integration in (and out) of the focus of spatial attention.

Anne Treisman transformed the way in which we think about visual feature integration. However, that does not mean that she was necessarily right, nor that she looked much beyond vision when considering how features might be bound together into perceptual objects. While such a narrow focus undoubtedly makes sense, given the complexity of human multisensory information processing, it is nevertheless somewhat surprising to find that Treisman herself never extended her feature integration theory outside of the visual modality. After all, she first cut her 'attentional teeth' thinking about problems of auditory and audiovisual selective attention. In this article, we review the literature concerning feature integration beyond the visual modality, concentrating, in particular, on the integration of features from different sensory modalities. We highlight a number of the challenges, as far as any straightforward attempt to extend feature integration to the non-visual (i.e. auditory and tactile) and cross-modal (or multisensory) cases, is concerned. These challenges include the problem of how basic features should be defined, the question of whether it even makes sense to talk of objects of perception in the auditory and olfactory modalities, the possibility of integration outside of the focus of spatial attention, and the integration of features from different sensory modalities in the control of action. Nevertheless, despite such limitations, Treisman's feature integration theory still stands as the standard approach against which alternatives are assessed, be it in the visual case or, increasingly, beyond.

Cognitive Dysfunctions and Assessments in Multiple Sclerosis.

Cognitive impairment has been reported at all phases and all subtypes of multiple sclerosis. It remains a major cause of neurological disability in young and middle-aged adults suffering from the disease. The severity and type of cognitive impairment varies considerably among individuals and can be observed both in early and in later stages. The areas which have commonly shown more deficits are: information processing speed, complex attention, memory, and executive function. Even though an alteration in both the white matter and in the gray matter has been found in patients with multiple sclerosis and cognitive impairment, the underlying process still remains unknown. Standardized neurological examinations fail to detect emerging cognitive deficits and self-reported cognitive complaints by the patients can be confounded by other subjective symptoms. This review is a comprehensive and short update of the literature on cognitive dysfunctions, the possible confounders and the impact of quality of life in patients with multiple sclerosis.

How Does the Regulatory Genome Work?

The regulatory genome controls genome activity throughout the life of an organism. This requires that complex information processing functions are encoded in, and operated by, the regulatory genome. Although much remains to be learned about how the regulatory genome works, we here discuss two cases where regulatory functions have been experimentally dissected in great detail and at the systems level, and formalized by computational logic models. Both examples derive from the sea urchin embryo, but assess two distinct organizational levels of genomic information processing. The first example shows how the regulatory system of a single gene, endo16, executes logic operations through individual transcription factor binding sites and cis-regulatory modules that control the expression of this gene. The second example shows information processing at the gene regulatory network (GRN) level. The GRN controlling development of the sea urchin endomesoderm has been experimentally explored at an almost complete level. A Boolean logic model of this GRN suggests that the modular logic functions encoded at the single-gene level show compositionality and suffice to account for integrated function at the network level. We discuss these examples both from a biological-experimental point of view and from a computer science-informational point of view, as both illuminate principles of how the regulatory genome works.

Stereotypes of Older Adults: Development and Evaluation of an Updated Stereotype Content and Strength Survey.

Stereotypes are beliefs about a particular group often adopted to bypass complex information processing. Like racism and other forms of discrimination, ageism affects individuals and society as a whole. The purpose of the study was to analyze the Stereotype Content and Strength Survey (SCSS) designed to update assessment tools commonly used to measure stereotypes of older adults. An updated survey was developed including aging-related descriptive items from previously published studies. Students enrolled at two Midwestern universities (n = 491) were directed to think about their perceptions of "older adults" and select the proportion they believed could be described by the items used in the tool. Response categories for each descriptive item were dichotomized and operationalized to be a strong stereotype if the collapsed response percentage was significantly ≥80%. A Principal Axis Factor analysis and Direct Oblim rotation was computed on 117 descriptive items representing positive, negative, and physical characteristics, resulting in a 3-factor model with acceptable psychometric properties. Cronbach alpha analyses revealed reliable scales for negative (α = .92), positive (α = .88), and physical (α = .81) stereotypes. Of 117 descriptive items, 33 emerged as strong stereotypes including 30 positive, 2 physical, and 1 negative item. This updated assessment has the potential to contribute to an understanding of the existence of age-related stereotypes as well as the strength, or the proportion of older adults who could be described by each of the items used in the SCSS.

Improvement of hyponatremia in cirrhosis is associated with improved complex information processing.

Hyponatremia, a cause of brain dysfunction and risk factor for hepatic encephalopathy, is frequent in patients with advanced cirrhosis and ascites. The interdependence of liver failure and hyponatremia makes it difficult to separate the effects of each on cognitive function. The objective was to assess whether an increase in plasma sodium in patients with cirrhosis and ascites leads to an improvement in cognitive function. This is a post-hoc analysis of 250 cirrhosis patients without overt hepatic encephalopathy randomized to receive either placebo or satavaptan, a vasopressin V2 antagonist. The exposure was plasma sodium, and the outcome was the trail-making test (TMT) parts A and B, which assesses speed of information processing, performed before the study starts and after 14days. The results were analyzed by initial and change to final sodium concentration. At entry, the patients with normonatremia exhibited better results on both the TMT-A (median 56 vs 77.5s for patients with sodium ≤130mmol/L [P=0.0059]) and the TMT-B (median 127 vs 170s for patients with sodium ≤130mmol/L [P=0.0066]), unrelated to age. Improvement of hyponatremia was more common in patients who received satavaptan (59.7%) than placebo (18.5%). Correction of hyponatremia did not shorten the simple TMT-A but markedly improved the complex TMT-B by an average of 20s compared with 6.5s in those with continuing hyponatremia (P=0.02). Liver status measures remained stable during the period reported. These data suggest that improvement of hyponatremia in patients with cirrhosis leads to an increase in the speed of complex information processing.

Archaeal Histone Contributions to the Origin of Eukaryotes.

The eukaryotic lineage arose from bacterial and archaeal cells that underwent a symbiotic merger. At the origin of the eukaryote lineage, the bacterial partner contributed genes, metabolic energy, and the building blocks of the endomembrane system. What did the archaeal partner donate that made the eukaryotic experiment a success? The archaeal partner provided the potential for complex information processing. Archaeal histones were crucial in that regard by providing the basic functional unit with which eukaryotes organize DNA into nucleosomes, exert epigenetic control of gene expression, transcribe genes with CCAAT-box promoters, and a manifest cell cycle with condensed chromosomes. While mitochondrial energy lifted energetic constraints on eukaryotic protein production, histone-based chromatin organization paved the path to eukaryotic genome complexity, a critical hurdle en route to the evolution of complex cells.

Introduction of Fractal Based Information Processing and Recognition

Fractal characteristic, one typical nonlinear characteristic, is applied as a key characteristic in complex information processing and used in many research domains [...]

Profile of life-long learning of prospective teacher in learning biology

Instead of constructing knowledge, learning also debriefs the student’s skills to be survive in life. Especially in biology learning which has a conceptual structure about life, it is relevant to address the program toward life-long learning orientation. Therefore, debriefing life-long learning is important. As preliminary study, the focus of this article is to investigate the profile of student life-long learning in biology instruction. A number of 22 students in Plant Physiology course from Biology education department in one teacher college in Central Java was involved as participants. Data were collected by using questionnaire with 30 statements representing five standard life-long learning (complex thinking, information processing, effective communication, collaboration, and habits of mind standards). Research result shows that overall, the average score of life-long learning student profile is 2.91 from a maximum score of 4.00. From each standard, the average scores of complex thinking standard (3.14), information processing standard (2.77), effective communication standard (2.89), collaboration standard (3.08), and habits of mind standard (2.69). Based on the data collected, life-long learning profile of students is still quite low especially for habits of mind, information processing, and effective communication. Thus, it is very urgent to develop a program of debriefing life-long learning for next biology courses (Plant Biodiversity and horticulture) for them in near future.

Who needs a brain? Slime moulds, behavioural ecology and minimal cognition

Although human decision making seems complex, there is evidence that many decisions are grounded in simple heuristics. Such heuristic models of decision making are widespread in nature. To understand how and why different forms of information processing evolve, it is insightful to study the minimal requirements for cognition. Here, we explore the minimally cognitive behaviour of the acellular slime mould, Physarum polycephalum, in order to discuss the ecological pressures that lead to the development of information processing mechanisms. We discuss evidence for memory, basic forms of learning and economically irrational choice in P. polycephalum. We compare P. polycephalum’s behaviour with a number of other non-neuronal organisms in order to question the evolutionary need for complex nervous systems to develop cognitive traits. By highlighting a few examples of common mechanisms, we conclude that all organisms contain the building blocks for more complex information processing. Returning the debate about cognition to the biological basics demystifies some of the confusion around the term ‘cognition’.

On Overcoming the Identified Limitations of a Usable PIN Entry Method

In the domain of password security, research has made significant progress in handling different kinds of threats which require human intelligence factor to fix the vulnerabilities. In spite of having strong theoretical establishments, most of these defense mechanisms cannot be used in practice as humans have limitations in processing complex information. The little bit of good news is that very few research proposals in this field have shown the promises to be deployable in practice. This paper focuses on such one method - proposed by Roth et al. back in 2004, which provides adequate user-friendliness to enter Personal Identification Number (PIN) securely in the presence of human shoulder surfers. Surprisingly, the background algorithm of this method for validating users’ responses runs in linear time on a search space of cardinality 5 and hence, the validation process does not put much load on the authenticating device. Therefore, such human identification protocol can also be integrated into the IoT infrastructure for conducting a more secured login from the client-side. Having such advantages, though remained secure for almost ten years after its release in 2004, recently, few proposals revealed some serious vulnerable aspects of the Roth et al. ’s proposal. In this paper, we have taken an attempt to save this user-friendly form of authentication. Firstly, we have made a critical discussion on the importance of the targeted PIN entry method in the domain of usable security and then given a brief overview of the identified limitations of this protocol. Followed by this, a few initiatives have been taken to fix the identified vulnerabilities of Roth et al. ’s proposal by revising its working principle, while the login procedure and the usability standard of this method stay unaffected.

Determinant factors of using data and knowledge in bridge engineering

Complexity and heterogeneity of information and decision processes in bridge construction necessitates the use of heterogeneous and complex information resources. However, for data collection and processing in this area, transactional database systems are mainly employed. They allow only the processing of detailed precise data as well as static ones. Other categories of data used in this area, including, for instance, fuzzy, temporal or active data, make it necessary to use additional specialized database systems. A similar remark can be made in relation to the various categories of acquired and processed knowledge in bridge construction projects (e.g. complete or incomplete knowledge in the reasoning process). Numerous independent and autonomous software applications used for this purpose do not offer comprehensive support for complex and multi-stage problems. It appears then that rational IT solutions in this area should be sought within the integrated systems of intelligent databases, supplemented with data fuzzing mechanisms and active data support, and, additionally, enabling the exchange of data with heuristic reasoning systems, in particular with expert systems that use the rule-based organization of knowledge, cooperating with case-based reasoning systems.

Somatic multicellularity as a satisficing solution to the prediction-error minimization problem

ABSTRACTAdaptive success in the biosphere requires the dynamic ability to adjust physiological, transcriptional, and behavioral responses to environmental conditions. From chemical networks to organisms to whole communities, biological entities at all levels of organization seek to optimize their predictive power. Here, we argue that this fundamental drive provides a novel perspective on the origin of multicellularity. One way for unicellular organisms to minimize surprise with respect to external inputs is to be surrounded by reproductively-disabled, i.e. somatic copies of themselves – highly predictable agents which in effect reduce uncertainty in their microenvironments. We show that the transition to multicellularity can be modeled as a phase transition driven by environmental threats. We present modeling results showing how multicellular bodies can arise if non-reproductive somatic cells protect their reproductive parents from environmental lethality. We discuss how a somatic body can be interpreted as a Markov blanket around one or more reproductive cells, and how the transition to somatic multicellularity can be represented as a transition from exposure of reproductive cells to a high-uncertainty environment to their protection from environmental uncertainty by this Markov blanket. This is, effectively, a transition by the Markov blanket from transparency to opacity for the variational free energy of the environment. We suggest that the ability to arrest the cell cycle of daughter cells and redirect their resource utilization from division to environmental threat amelioration is the key innovation of obligate multicellular eukaryotes, that the nervous system evolved to exercise this control over long distances, and that cancer is an escape by somatic cells from the control of reproductive cells. Our quantitative model illustrates the evolutionary dynamics of this system, provides a novel hypothesis for the origin of multicellular animal bodies, and suggests a fundamental link between the architectures of complex organisms and information processing in proto-cognitive cellular agents.

AI Research and Its Methodology from the Viewpoint of Complex Information Processing

AI Research and Its Methodology from the Viewpoint of Complex Information Processing

Factors That Hinder and Facilitate Cancer Patients' Knowledge About Pain Management—A Qualitative Study

ContextPain management education may improve pain control for some patients, whereas individual differences exist. ObjectivesTo evaluate possible critical components, facilitators, and hindrances for improved knowledge about pain management, in not hospitalized adult oncology patients with pain from bone metastasis participating in a pain management intervention. MethodsThis substudy is a qualitative evaluation of the PRO-SELF Pain Control Program, tested in a randomized controlled trial. During six weeks, 87 participants in the intervention group received tailored coaching encounters by a trained oncology nurse. Three encounters for each patient were audio recorded. The encounter between patient's with the largest (n = 12) and lowest (n = 8) change in knowledge about pain management from before to after the intervention was transcribed verbatim and analyzed with qualitative content analysis. ResultsThe critical components of the intervention were repetition of information, struggling with resistance, use of peer experiences, and keeping track of variations. Facilitators of improvement were patients' trust and preparedness to try new procedures, the patient's self-awareness and body awareness, and taking active role in own care. Difficulties in processing complex information, culturally conditioned behaviors, fear, and lack of knowledge were the most important barriers to the success of the intervention. ConclusionEducation in pain management in cancer patients requires repeated information, allowing time for overcoming resistance related to dysfunctional beliefs and fear. To facilitate the patient's involvement in their pain management, tailored and person-centered education is needed.

Deficit of corpus callosum axons, reduced axon diameter and decreased area are markers of abnormal development of interhemispheric connections in autistic subjects

IntroductionIn autism spectrum disorder, lack of coherence and of complex information processing, and narrowly focused interests and repetitive behaviors are considered a sign of long-range underconnectivity and short-range overconnectivity. The goal of this morphometric study of five anatomically and functionally different segments of the corpus callosum (CC) was to establish patterns of differences between long-range interhemispheric connections in nine neurotypical and nine autistic subjects.ResultsElectron microscopy revealed a significant reduction in average axon diameter and axon cross-sectional area in autistic subjects, and reduction in CC segment–specific diversification of connections of functionally different cortical regions. The study shows an increase in the percentage of small diameter axons (< 0.651 μm) and a decrease in the percentage of axons with large diameter (> 1.051 μm). The total number of small-diameter axons is reduced in segment I and III by 43% on average. The number of medium- and large-diameter axons is reduced in all five CC segments by an average of 49 and 72%, respectively.ConclusionsThe detected pattern of pathology suggests a failure of mechanisms controlling guidance of axons during development leading to axonal deficit, and failure of mechanisms controlling axon structure. A reduction in axon diameter may affect the velocity and volume of signal transmission, and distort functional specialization of CC segments. Significant deficits in axon number and reduction in axon size in all five CC segments appear to be substantial components of brain connectome integrity distortion which may contribute to the autism phenotype.

A hierarchical memory network-based approach to uncertain streaming data

Various interferences can cause uncertainties such as missing data, outliers, noise, and redundancies that are persistent either in stationary or streaming data. In such case, preprocessing methods are widely accepted, of which PCA (Principal Component Analysis), filter, and Bayesian are most popular. As batch learning schemes, they work well particularly in the stationary environment through making correction and revision for bad samples. However, for the streaming data an in-time response for the unusual is needed, where an online learning scheme is even more suitable. As we have known, human brain is a highly complex and intelligent information processing organ, in which memory serves as a crucial role. The more repeated information will be remembered more deeply, and the less repeated will be forgot soon. Considering the mechanisms of memory such as remembering, forgetting, and recalling, a human memory-inspired approach is proposed in this paper. Differ from any mathematic methods, it is an instance-replaced approach by retrieving superior historical instances in memory library to replace the abnormal ones. Through modeling these mechanisms and adding different priorities for each instance on storing and retrieving, a hierarchical memory network (HMN) is constructed, which contains three levels, namely, perpetual, long-term, and short-term. In HMN, data instances migrate dynamically to change their hierarchies to adapt changing circumstances. The perpetual level stores data with the deepest memory and never forgets them again. The long-term level interacts with other two levels through migrating instances with deeper memory into perpetual memory and forgetting shallower ones back to the short-term level. Likewise, data in short-term level will be migrated into long-term memory once up to a predefined threshold, meanwhile some instances under the lowest index will be forever discarded. Benchmark and real-world industrial datasets are utilized to build and test HMN, and simulation results verify its effectiveness.

Neural Reconstruction Integrity: A Metric for Assessing the Connectivity Accuracy of Reconstructed Neural Networks.

Neuroscientists are actively pursuing high-precision maps, or graphs consisting of networks of neurons and connecting synapses in mammalian and non-mammalian brains. Such graphs, when coupled with physiological and behavioral data, are likely to facilitate greater understanding of how circuits in these networks give rise to complex information processing capabilities. Given that the automated or semi-automated methods required to achieve the acquisition of these graphs are still evolving, we developed a metric for measuring the performance of such methods by comparing their output with those generated by human annotators (“ground truth” data). Whereas classic metrics for comparing annotated neural tissue reconstructions generally do so at the voxel level, the metric proposed here measures the “integrity” of neurons based on the degree to which a collection of synaptic terminals belonging to a single neuron of the reconstruction can be matched to those of a single neuron in the ground truth data. The metric is largely insensitive to small errors in segmentation and more directly measures accuracy of the generated brain graph. It is our hope that use of the metric will facilitate the broader community's efforts to improve upon existing methods for acquiring brain graphs. Herein we describe the metric in detail, provide demonstrative examples of the intuitive scores it generates, and apply it to a synthesized neural network with simulated reconstruction errors. Demonstration code is available.

Neuronal types of the human cortical amygdaloid nucleus.

The human cortical amygdaloid nucleus (CoA) receives exteroceptive sensory stimuli, modulates the functions coded by the intrinsic amygdaloid circuit, and constitutes the beginning of the limbic lobe continuum with direct and indirect connections toward subcortical, allocortical, and higher order neocortical areas. To provide basic data on the human CoA, we characterized and classified the neurons using the thionin and the "single-section" Golgi method adapted for postmortem brain tissue and light microscopy. We found 10 different types of neurons named according to the morphological features of the cell body, dendritic branches, and spine distribution. Most cells are multipolar spiny neurons with two or more primary dendrites, including pyramidal-like ones. Three-dimensional reconstructions evidenced the types and diversity of the dendritic spines in each neuron. The unlike density of spines along dendritic branches, from proximal to distal ones, indicate that the synaptic processing and plasticity can be different in each CoA neuron. Our study provides novel data on the neuronal composition of the human CoA indicating that the variety of cells in this region can have phylogenetic, ontogenetic, morphological, and likely functional implications for the integrated human brain function. This can reflect both a more complex subcortical synaptic processing of sensory and emotional information and an adaptation for species-specific social behavior display.

Correction: LKB1 Regulates Mitochondria-Dependent Presynaptic Calcium Clearance and Neurotransmitter Release Properties at Excitatory Synapses along Cortical Axons.

[This corrects the article DOI: 10.1371/journal.pbio.1002516.].