Biological signals may carry specific characteristics that reflect basic dynamics of the body. In particular, heart beat signals carry specific signatures that are related to human physiologic mechanisms. In recent years, many researchers have shown that representations which used non-linear symbolic sequences can often reveal much hidden dynamic information. This kind of symbolization proved to be useful for predicting life-threatening cardiac diseases.
This paper presents an improved method called the “Adaptive Interbeat Interval Analysis (AIIA) method”. The AIIA method uses the Simple K-Means algorithm for symbolization, which offers a new way to represent subtle variations between two interbeat intervals without human intervention. After symbolization, it uses the n-gram algorithm to generate different kinds of symbolic sequences. Each symbolic sequence stands for a variation phase. Finally, the symbolic sequences are categorized by classic classifiers.
In the experiments presented in this paper, AIIA method achieved 91% (3-gram, 26 clusters) accuracy in successfully classifying between the patients with Atrial Fibrillation (AF), Congestive Heart Failure (CHF) and healthy people. It also achieved 87% (3-gram, 26 clusters) accuracy in classifying the patients with apnea.
The two experiments presented in this paper demonstrate that AIIA method can categorize different heart diseases. Both experiments acquired the best category results when using the Bayesian Network. For future work, the concept of the AIIA method can be extended to the categorization of other physiological signals. More features can be added to improve the accuracy.
This article analyzes some analogies going from Artificial Life questions about the symbol–matter connection to Artificial Intelligence questions about symbol-grounding. It focuses on the notion of the interpretability of syntax and how the symbols are integrated in a unity ("binding problem"). Utilizing the DNA code as a model, this paper discusses how syntactic features could be defined as high-grade characteristics of the non syntactic relations in a material-dynamic structure, by using an emergentist approach. This topic furnishes the ground for a confutation of J. Searle’s statement that syntax is observer-relative, as he wrote in his book "Mind: A Brief Introduction". Moreover the evolving discussion also modifies the classic symbol-processing doctrine in the mind which Searle attacks as a strong AL argument, that life could be implemented in a computational mode. Lastly, this paper furnishes a new way of support for the autonomous systems thesis in Artificial Life and Artificial Intelligence, using, inter alia, the "adaptive resonance theory" (ART).
Analogy-making; Connectionism; Theories of syntax; Genetic code; Artificial life; Cognitive robotics & AI; Binding problem
In this paper aesthetic experience is defined as an experience qualitatively different from everyday experience and similar to other exceptional states of mind. Three crucial characteristics of aesthetic experience are discussed: fascination with an aesthetic object (high arousal and attention), appraisal of the symbolic reality of an object (high cognitive engagement), and a strong feeling of unity with the object of aesthetic fascination and aesthetic appraisal. In a proposed model, two parallel levels of aesthetic information processing are proposed. On the first level two sub-levels of narrative are processed, story (theme) and symbolism (deeper meanings). The second level includes two sub-levels, perceptual associations (implicit meanings of object's physical features) and detection of compositional regularities. Two sub-levels are defined as crucial for aesthetic experience, appraisal of symbolism and compositional regularities. These sub-levels require some specific cognitive and personality dispositions, such as expertise, creative thinking, and openness to experience. Finally, feedback of emotional processing is included in our model: appraisals of everyday emotions are specified as a matter of narrative content (eg, empathy with characters), whereas the aesthetic emotion is defined as an affective evaluation in the process of symbolism appraisal or the detection of compositional regularities.
aesthetic experience; fascination; appraisal; emotion; narrative; composition
Brain-machine interfaces are a growing field of research and application. The increasing possibilities to connect the human brain to electronic devices and computer software can be put to use in medicine, the military, and entertainment. Concrete technologies include cochlear implants, Deep Brain Stimulation, neurofeedback and neuroprosthesis. The expectations for the near and further future are high, though it is difficult to separate hope from hype. The focus in this paper is on the effects that these new technologies may have on our ‘symbolic order’—on the ways in which popular categories and concepts may change or be reinterpreted. First, the blurring distinction between man and machine and the idea of the cyborg are discussed. It is argued that the morally relevant difference is that between persons and non-persons, which does not necessarily coincide with the distinction between man and machine. The concept of the person remains useful. It may, however, become more difficult to assess the limits of the human body. Next, the distinction between body and mind is discussed. The mind is increasingly seen as a function of the brain, and thus understood in bodily and mechanical terms. This raises questions concerning concepts of free will and moral responsibility that may have far reaching consequences in the field of law, where some have argued for a revision of our criminal justice system, from retributivist to consequentialist. Even without such a (unlikely and unwarranted) revision occurring, brain-machine interactions raise many interesting questions regarding distribution and attribution of responsibility.
Brain-machine interaction; Brain-computer interfaces; Converging technologies; Cyborg; Deep brain stimulation; Moral responsibility; Neuroethics
Using a naturalistic video database, we examined whether gestures scaffold the symbolic development of a language-enculturated chimpanzee, a language-enculturated bonobo, and a human child during the second year of life. These three species constitute a complete clade: species possessing a common immediate ancestor. A basic finding was the functional and formal similarity of many gestures between chimpanzee, bonobo, and human child. The child’s symbols were spoken words; the apes’ symbols were lexigrams – non-iconic visual signifiers. A developmental pattern in which gestural representation of a referent preceded symbolic representation of the same referent appeared in all three species (but was statistically significant only for the child). Nonetheless, across species, the ratio of symbol to gesture increased significantly with age. But even though their symbol production increased, the apes continued to communicate more frequently by gesture than by symbol. In contrast, by 15–18 months of age, the child used symbols more frequently than gestures. This ontogenetic sequence from gesture to symbol, present across the clade but more pronounced in child than ape, provides support for the role of gesture in language evolution. In all three species, the overwhelming majority of gestures were communicative (i.e., paired with eye contact, vocalization, and/or persistence). However, vocalization was rare for the apes, but accompanied the majority of the child’s communicative gestures. This species difference suggests the co-evolution of speech and gesture after the evolutionary divergence of the hominid line. Multimodal expressions of communicative intent (e.g., vocalization plus persistence) were normative for the child, but less common for the apes. This species difference suggests that multimodal expression of communicative intent was also strengthened after hominids diverged from apes.
gestural theory of language evolution; language-enculturated apes; symbolic development; cross-species comparisons; gesture; communication development; language development
Automatic speech recognition (ASR) systems rely almost exclusively on short-term segment-level features (MFCCs), while ignoring higher level suprasegmental cues that are characteristic of human speech. However, recent experiments have shown that categorical representations of prosody, such as those based on the Tones and Break Indices (ToBI) annotation standard, can be used to enhance speech recognizers. However, categorical prosody models are severely limited in scope and coverage due to the lack of large corpora annotated with the relevant prosodic symbols (such as pitch accent, word prominence, and boundary tone labels). In this paper, we first present an architecture for augmenting a standard ASR with symbolic prosody. We then discuss two novel, un-supervised adaptation techniques for improving, respectively, the quality of the linguistic and acoustic components of our categorical prosody models. Finally, we implement the augmented ASR by enriching ASR lattices with the adapted categorical prosody models. Our experiments show that the proposed unsupervised adaptation techniques significantly improve the quality of the prosody models; the adapted prosodic language and acoustic models reduce binary pitch accent (presence versus absence) classification error rate by 13.8% and 4.3%, respectively (relative to the seed models) on the Boston University Radio News Corpus, while the prosody-enriched ASR exhibits a 3.1% relative reduction in word error rate (WER) over the baseline system.
Categorical prosody models; lattice enrichment; speech recognition; unsupervised adaptation
When the body is ailing the mind is soon impaired. Good health practices contribute to longer and better life. A balanced life of work-rest-play is necessary to human health.
Psychosocial stresses at any period of life may impair morale and productivity and increase the likelihood of physical or mental disease. Bereavement, separation, divorce, loss of friendship, retirement, loss of self-esteem and symbolic losses contribute significantly to mental and physical ill health. Social and psychological support systems are vital to mental health maintenance.
Mature persons evolve principles, values, moral and ethical tenets, philosophic and religious ideals and special codes of conduct to give meaning to their lives. The basic needs of survival and procreation must be integrated with moral precepts relating to interindividual behavior so as to give a person a feeling of self-worth, which is an indispensable element in mental health.
The question of whether symbolically mediated behavior is exclusive to modern humans or shared with anatomically archaic populations such as the Neandertals is hotly debated. At the Grotte du Renne, Arcy-sur-Cure, France, the Châtelperronian levels contain Neandertal remains and large numbers of personal ornaments, decorated bone tools and colorants, but it has been suggested that this association reflects intrusion of the symbolic artifacts from the overlying Protoaurignacian and/or of the Neandertal remains from the underlying Mousterian.
We tested these hypotheses against the horizontal and vertical distributions of the various categories of diagnostic finds and statistically assessed the probability that the Châtelperronian levels are of mixed composition. Our results reject that the associations result from large or small scale, localized or generalized post-depositional displacement, and they imply that incomplete sample decontamination is the parsimonious explanation for the stratigraphic anomalies seen in the radiocarbon dating of the sequence.
The symbolic artifacts in the Châtelperronian of the Grotte du Renne are indeed Neandertal material culture.
The immortal HeLa cells case is an intriguing example of bio-objectification processes with great scientific, social, and symbolic impacts. These cells generate questions about representation, significance, and value of the exceptional, variety, individuality, and property. Of frightening (a lethal cancer) and emarginated (a black, poor woman) origins, with their ability to “contaminate” cultures and to “spread” into spaces for becoming of extraordinary value for human knowledge, well-being, and economy advancements, HeLa cells have represented humanity, and emphasized the importance of individual as a core concept of the personalized medicine. Starting from the process leading from HeLa “cells” to HeLa “bio-objects,” we focus on their importance as high quality bio-specimen. We discuss the tension between phenomenological characteristic of fundamental biological research and the variety of material and methodologies in epidemiology and personalized medicine. The emerging methodologies and societal changes reflect present EU policies and lead toward a new paradigm of science.
Communication about feelings is a core element of human interaction. Aided augmentative and alternative communication systems must therefore include symbols representing these concepts. The symbols must be readily distinguishable in order for users to communicate effectively. However, emotions are represented within most systems by schematic faces in which subtle distinctions are difficult to represent. We examined whether background color cuing and spatial arrangement might help children identify symbols for different emotions.
Thirty nondisabled children searched for symbols representing emotions within an 8-choice array. On some trials, a color cue signaled the valence of the emotion (positive vs. negative). Additionally, symbols were either organized with the negatively-valenced symbols at the top and the positive symbols on the bottom of the display, or the symbols were distributed randomly throughout. Dependent variables were accuracy and speed of responses.
The speed with which children could locate a target was significantly faster for displays in which symbols were clustered by valence, but only when the symbols had white backgrounds. Addition of a background color cue did not facilitate responses.
Rapid search was facilitated by a spatial organization cue, but not by the addition of background color. Further examination of the situations in which color cues may be useful is warranted.
Aided AAC; Color Cuing; Display Construction
Classification is one of the data mining problems receiving enormous attention in the database community. Although artificial neural networks (ANNs) have been successfully applied in a wide range of machine learning applications, they are however often regarded as black boxes, i.e., their predictions cannot be explained. To enhance the explanation of ANNs, a novel algorithm to extract symbolic rules from ANNs has been proposed in this paper. ANN methods have not been effectively utilized for data mining tasks because how the classifications were made is not explicitly stated as symbolic rules that are suitable for verification or interpretation by human experts. With the proposed approach, concise symbolic rules with high accuracy, that are easily explainable, can be extracted from the trained ANNs. Extracted rules are comparable with other methods in terms of number of rules, average number of conditions for a rule, and the accuracy. The effectiveness of the proposed approach is clearly demonstrated by the experimental results on a set of benchmark data mining classification problems.
data mining; neural networks; symbolic rules; weight freezing; constructive algorithm; pruning; clustering; rule extraction; symbolic rules
The names of genes are central in describing their function and relationship. However, gene symbols are often a subject of controversy. In addition, the discovery of mammalian genes is now so rapid that a proper use of gene symbol nomenclature rules tends to be overlooked. This is currently the situation in the rat and there is a need for a cohesive and unifying overview of all rat gene symbols in use. Based on the experiences in rat gene symbol curation that we have gained from running the "Ratmap" rat genome database, we have now developed a database that unifies different rat gene naming attempts with the accepted rat gene symbol nomenclature rules.
This paper presents a newly developed database known as RGST (Rat Gene Symbol Tracker). The database contains rat gene symbols from three major sources: the Rat Genome Database (RGD), Ensembl, and NCBI-Gene. All rat symbols are compared with official symbols from orthologous human genes as specified by the Human Gene Nomenclature Committee (HGNC). Based on the outcome of the comparisons, a rat gene symbol may be selected. Rat symbols that do not match a human ortholog undergo a strict procedure of comparisons between the different rat gene sources as well as with the Mouse Genome Database (MGD). For each rat gene this procedure results in an unambiguous gene designation. The designation is presented as a status level that accompanies every rat gene symbol suggested in the database. The status level describes both how a rat symbol was selected, and its validity.
This database fulfils the important need of unifying rat gene symbols into an automatic and cohesive nomenclature system. The RGST database is available directly from the RatMap home page: .
Neural network models of attention can provide a unifying approach to the study of human cognitive and emotional development (Posner & Rothbart, 2007). This paper we argue that a neural networks approach to the infant development of joint attention can inform our understanding of the nature of human social learning, symbolic thought process and social cognition. At its most basic, joint attention involves the capacity to coordinate one’s own visual attention with that of another person. We propose that joint attention development involves increments in the capacity to engage in simultaneous or parallel processing of information about one’s own attention and the attention of other people. Infant practice with joint attention is both a consequence and organizer of the development of a distributed and integrated brain network involving frontal and parietal cortical systems. This executive distributed network first serves to regulate the capacity of infants to respond to and direct the overt behavior of other people in order to share experience with others through the social coordination of visual attention. In this paper we describe this parallel and distributed neural network model of joint attention development and discuss two hypotheses that stem from this model. One is that activation of this distributed network during coordinated attention enhances to depth of information processing and encoding beginning in the first year of life. We also propose that with development joint attention becomes internalized as the capacity to socially coordinate mental attention to internal representations. As this occurs the executive joint attention network makes vital contributions to the development of human symbolic thinking and social cognition.
The effect of regular exercise on cognitive functioning and personality was investigated in 32 subjects representing 4 discrete groups based on sex and age. Before and after a 10 week exercise programme of jogging, calisthenics, and recreational activities, a test battery was administered to assess functioning in a number of domains: intelligence (WAIS Digit Symbol and Block Design); brain function (Trail-Making); speed of performance (Crossing-Off); memory and learning (WMS Visual Reproduction and Associate Learning); morale and life satisfaction (Life Satisfaction and Control Ratings); anxiety (MAACL); and depression (MAACL). Improvement was observed on several physiological parameters. ANOVA revealed significant sex and age differences on Digit Symbol and Block Design and age differences on Trail-Making, Crossing-Off, Associate Learning, and anxiety. Regardless of sex and age, significant improvement in performance was observed from pre to post-test on Digit Symbol, Block Design, Trail-Making, Crossing-Off, and on Associate Learning. In addition, an increase on health status rating (p less than .01) and decrease in anxiety were observed from pre to post-test. These data illustrate beneficial effects of exercise on certain measures of cognitive functioning and personality.
Analysis of signals by means of symbolic methods consists in calculating a measure of signal complexity, for example informational entropy or Lempel-Ziv algorithmic complexity. For construction of these entropic measures one uses distributions of symbols representing the analyzed signal.
We introduce a new signal characteristic named sequential spectrum that is suitable for analysis of the wide group of signals, including biosignals.
The paper contains a brief review of analyses of artificial signals showing features similar to those of biosignals. An example of using sequential spectrum for analyzing EEG signals registered during different stages of sleep is also presented.
Sequential spectrum is an effective tool for general description of nonstationary signals and it its advantage over Fourier spectrum. Sequential spectrum enables assessment of pathological changes in EEG-signals recorded in persons with epilepsy.
Uncontrolled high blood pressure leads clinicians to wonder about adherence degree among hypertensive patients. In this context, our study aims to describe and analyze patients' experience of antihypertensive drugs in order to shed light on the multiple social and symbolic logics, forming part of the cultural factors shaping personal medication practices.
The medical inductive and comprehensive anthropological approach implemented is based on an ethnographic survey (observations of consultations and interviews). Semi-structured interviews were conducted with 68 hypertensive patients (39 women and 29 men, between the ages of 40 and 95, of whom 52 were over 60) who had been receiving treatment for over a year.
Antihypertensive drugs are reinterpreted when filtered through the cultural model of physiopathology (the body as an engine). This symbolic dimension facilitates acceptance of therapy but leads to a hierarchization of other prescribed drugs and of certain therapeutic classes (diuretics). Prescription compliance does not solely depend on the patient's perception of cardiovascular risk, but also on how the patient fully accepts the treatment and integrates it into his or her daily life; this requires identification with the product, building commitment and self-regulation of the treatment (experience, managing treatment and control of side effects, intake and treatment continuity). Following the prescription requires a relationship based on trust between the doctor and patient, which we have identified in three forms: reasoned trust, emotional trust and conceded trust.
Consideration and understanding of these pragmatic and symbolic issues by the treating physician should aid practitioners in carrying out their role as medical educators in the management of hypertension.
This paper was originally published in French, in the journal Pratiques et organisation des soins 39(1): 3-12.
Children take years to learn symbolic arithmetic. Nevertheless, non-human animals, human adults with no formal education, and human infants represent approximate number in arrays of objects and sequences of events, and they use these capacities to perform approximate addition and subtraction. Do children harness these abilities when they begin to learn school mathematics? In 2 experiments in different schools, kindergarten children from diverse backgrounds were tested on their non-symbolic arithmetic abilities during the school year, as well as on their mastery of number words and symbols. Performance of non-symbolic arithmetic predicted children’s mathematics achievement at the end of the school year, independent of achievement in reading or general intelligence. Non-symbolic arithmetic performance was also related to children’s mastery of number words and symbols, which figured prominently in the assessments of mathematics achievement in both schools. Thus, non-symbolic and symbolic numerical abilities are specifically related, in children of diverse socio-economic backgrounds, near the start of mathematics instruction.
Massive text mining of the biological literature holds great promise of relating disparate information and discovering new knowledge. However, disambiguation of gene symbols is a major bottleneck.
We developed a simple thesaurus-based disambiguation algorithm that can operate with very little training data. The thesaurus comprises the information from five human genetic databases and MeSH. The extent of the homonym problem for human gene symbols is shown to be substantial (33% of the genes in our combined thesaurus had one or more ambiguous symbols), not only because one symbol can refer to multiple genes, but also because a gene symbol can have many non-gene meanings. A test set of 52,529 Medline abstracts, containing 690 ambiguous human gene symbols taken from OMIM, was automatically generated. Overall accuracy of the disambiguation algorithm was up to 92.7% on the test set.
The ambiguity of human gene symbols is substantial, not only because one symbol may denote multiple genes but particularly because many symbols have other, non-gene meanings. The proposed disambiguation approach resolves most ambiguities in our test set with high accuracy, including the important gene/not a gene decisions. The algorithm is fast and scalable, enabling gene-symbol disambiguation in massive text mining applications.
Humans share with nonhuman animals an approximate number system (ANS) that permits estimation and rough calculation of number without symbols. Recent studies show a correlation between the acuity of the ANS and symbolic math performance throughout development and into adulthood, suggesting that the ANS may serve as a cognitive foundation for the uniquely human capacity for symbolic mathematics. Such a proposition leads to the untested prediction that training aimed at improving ANS performance will transfer to improvement in symbolic mathematics. Here, in two experiments, we show that ANS training on approximate addition and subtraction of arrays of dots, selectively improves symbolic addition and subtraction. This finding strongly supports the hypothesis that complex math skills are fundamentally linked to rudimentary preverbal quantitative abilities, provides the first direct evidence that ANS and symbolic math may be causally related, and raises the possibility that interventions aimed at the ANS could benefit children and adults who struggle with math.
Number comprehension; mathematical ability
OBJECTIVE: To provide a clinical review of issues surrounding reduced fluid intake in palliative care patients and a practical approach to care for these patients. DATA SOURCES: Medline was searched from 1980 to 1995 for articles concerning dehydration in dying patients. In addition, the law databases QUICKLAW, WESTLAW, and MEDMAL were searched. STUDY SELECTION: Key papers were included for discussion in relation to the clinical evidence to treat or withhold treatment and to a representative sample of the social, ethical, and legal issues. SYNTHESIS: There is little clinical evidence to guide patients, families, or clinicians in treating with reduced fluid intake during the terminal phase of life. Assisting patients to take fluids as a social or symbolic act is recognized, as is the ethical and legal stance that assisting fluid intake should be thought of as a medical therapy. CONCLUSION: Without sound evidence upon which to base clinical decisions, patients, families, and clinicians are left to balance potential benefits and burdens against the goals of care.
The movements we make with our hands both reflect our mental processes and help to shape them. Our actions and gestures can affect our mental representations of actions and objects. In this paper, we explore the relationship between action, gesture and thought in both humans and non-human primates and discuss its role in the evolution of language. Human gesture (specifically representational gesture) may provide a unique link between action and mental representation. It is kinaesthetically close to action and is, at the same time, symbolic. Non-human primates use gesture frequently to communicate, and do so flexibly. However, their gestures mainly resemble incomplete actions and lack the representational elements that characterize much of human gesture. Differences in the mirror neuron system provide a potential explanation for non-human primates' lack of representational gestures; the monkey mirror system does not respond to representational gestures, while the human system does. In humans, gesture grounds mental representation in action, but there is no evidence for this link in other primates. We argue that gesture played an important role in the transition to symbolic thought and language in human evolution, following a cognitive leap that allowed gesture to incorporate representational elements.
gesture; mental representation; evolution of language; embodied cognition; primates; mirror neurons
This paper describes HYCONES, a tightly-coupled Hybrid Connectionist Expert System that integrates neural networks with a symbolic approach (frames). The symbolic paradigm provides rich and flexible constructs to describe the domain knowledge, while the connectionist one provides the system with learning capabilities. The paper describes the architecture of the system, focusing on the hybrid aspects of the knowledge base and on its automatic knowledge acquisition technique from a case database. The first validation of the system is presented. At the end, a comparison with related research efforts and future developments are discussed.
In this article we briefly summarize how converging technologies challenge elements of the existing symbolic order, as shown in the contributions to this special issue. We then identify the vision of ‘life as a do it yourself kit’ as a common denominator in the various forms of convergence and proceed to show how this vision provokes unrest and debate about existing moral frameworks and taboos. We conclude that, just as the problems of the industrial revolution sparked off the now broadly established ideal of sustainability the converging technologies should be governed by the ideal of ‘human sustainability’. The essence of this ideal is formed by the ongoing discussion about the extent to which we may, or should want to, ‘make’ our environment and ourselves, and when it is better to simply accept what is given and what happens to us.
Converging technologies; Ethics; Sustainability
This paper discusses the design goals and the first developments of
Proto-Plasm, a novel computational environment to produce libraries of
executable, combinable and customizable computer models of natural and synthetic
biosystems, aiming to provide a supporting framework for predictive understanding of
structure and behaviour through multiscale geometric modelling and multiphysics
simulations. Admittedly, the Proto-Plasm platform is still in its infancy.
Its computational framework—language, model library, integrated development
environment and parallel engine—intends to provide patient-specific
computational modelling and simulation of organs and biosystem, exploiting novel
functionalities resulting from the symbolic combination of parametrized models of
parts at various scales. Proto-Plasm may define the model equations, but it
is currently focused on the symbolic description of model geometry and on the
parallel support of simulations. Conversely, CellML and SBML could be viewed as
defining the behavioural functions (the model equations) to be used within a
Proto-Plasm program. Here we exemplify the basic functionalities of
Proto-Plasm, by constructing a schematic heart model. We also discuss
multiscale issues with reference to the geometric and physical modelling of
computational biology; geometric and physical modelling; multilevel and multiphysics simulation; high-performance computing
Sleep deprivation is known to have detrimental effects on attentional resources and cognitive functions.
The aim of this study is to assess the changes in performance, due to 24 h of sleep deprivation, in medical students
Materials and Methods:
The performance was assessed using simple paper–pencil tasks, such as digit symbol substitution test, digit vigilance test, and letter cancellation tasks.
The results revealed an increase in the number of errors in letter cancellation tasks and digit vigilance test, with a significant decrease in the number of correct responses on the letter cancellation task. The time taken to complete the tests increased with lack of sleep, with the digit symbol substitution test being affected the most.
This study infers that sleep deprivation for 24 h affected the judgment ability more than the response speed.
Sleep deprivation might lead to compromised performance of medical students in examinations.
Digit symbol substitution test; digit vigilance test; letter cancellation task; sleep deprivation