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Information Integrator is an extension to IBM's relational database DB2, which uses data federation to provide benefits to molecular biology researchers through two unique capabilities: increased flexibility in combining data from disparate sources, and SQL access to non-SQL data, easing the task of automating data analysis.
BACKGROUND: To understand the functioning of distributed networks such as the brain, it is important to characterize their ability to integrate information. The paper considers a measure based on effective information, a quantity capturing all causal interactions that can occur between two parts of a system. RESULTS: The capacity to integrate information, or Phi, is given by the minimum amount of effective information that can be exchanged between two complementary parts of a subset. It is shown that this measure can be used to identify the subsets of a system that can integrate information, or complexes. The analysis is applied to idealized neural systems that differ in the organization of their connections. The results indicate that Phi is maximized by having each element develop a different connection pattern with the rest of the complex (functional specialization) while ensuring that a large amount of information can be exchanged across any bipartition of the network (functional integration). CONCLUSION: Based on this analysis, the connectional organization of certain neural architectures, such as the thalamocortical system, are well suited to information integration, while that of others, such as the cerebellum, are not, with significant functional consequences. The proposed analysis of information integration should be applicable to other systems and networks.
Integrating information in the molecular biosciences involves more than the cross-referencing of sequences or structures. Experimental protocols, results of computational analyses, annotations and links to relevant literature form integral parts of this information, and impart meaning to sequence or structure. In this review, we examine some existing approaches to integrating information in the molecular biosciences. We consider not only technical issues concerning the integration of heterogeneous data sources and the corresponding semantic implications, but also the integration of analytical results. Within the broad range of strategies for integration of data and information, we distinguish between platforms and developments. We discuss two current platforms and six current developments, and identify what we believe to be their strengths and limitations. We identify key unsolved problems in integrating information in the molecular biosciences, and discuss possible strategies for addressing them including semantic integration using ontologies, XML as a data model, and graphical user interfaces as integrative environments.
Three experiments tested the ability to integrate information about object-object relationships in 2 chimpanzees. In Experiment 1, the subjects were trained to match 1 part of a 2-part object to its other part, match a tool to its assembled object, match a container to its tool, and match a tool to its container. In Experiment 2, the subjects were trained to match a picture of the sample. One subject learned this type of matching task and was then tested on whether she could choose the pictures of related items in Experiment 1. Although the subject was reinforced irrespective of her choices, she chose pictures of items related to the sample when there was no picture of the sample. Experiment 3 showed that the subject was able to match a picture of the item among related items. The results suggest that the subject might integrate information about relationships acquired in Experiment 1 and organize it to make networks of related items.
The effects of two different kinds of categorization training were investigated. In observational training, observers are presented with a category label and then shown an exemplar from that category. In feedback training, they are shown an exemplar, asked to assign it to a category, and then given feedback about the accuracy of their response. These two types of training were compared as observers learned two types of category structures--those in which optimal accuracy could be achieved via some explicit rule-based strategy, and those in which optimal accuracy required integrating information from separate perceptual dimensions at some predecisional stage. There was an overall advantage for feedback training over observational training, but most importantly, type of training interacted strongly with type of category structure. With rule-based structures, the effects of training type were small, but with information-integration structures, accuracy was substantially higher with feedback training, and people were less likely to use suboptimal rule-based strategies. The implications of these results for current theories of category learning are discussed.
BACKGROUND: Consciousness poses two main problems. The first is understanding the conditions that determine to what extent a system has conscious experience. For instance, why is our consciousness generated by certain parts of our brain, such as the thalamocortical system, and not by other parts, such as the cerebellum? And why are we conscious during wakefulness and much less so during dreamless sleep? The second problem is understanding the conditions that determine what kind of consciousness a system has. For example, why do specific parts of the brain contribute specific qualities to our conscious experience, such as vision and audition? PRESENTATION OF THE HYPOTHESIS: This paper presents a theory about what consciousness is and how it can be measured. According to the theory, consciousness corresponds to the capacity of a system to integrate information. This claim is motivated by two key phenomenological properties of consciousness: differentiation - the availability of a very large number of conscious experiences; and integration - the unity of each such experience. The theory states that the quantity of consciousness available to a system can be measured as the Phi value of a complex of elements. Phi is the amount of causally effective information that can be integrated across the informational weakest link of a subset of elements. A complex is a subset of elements with Phi>0 that is not part of a subset of higher Phi. The theory also claims that the quality of consciousness is determined by the informational relationships among the elements of a complex, which are specified by the values of effective information among them. Finally, each particular conscious experience is specified by the value, at any given time, of the variables mediating informational interactions among the elements of a complex. TESTING THE HYPOTHESIS: The information integration theory accounts, in a principled manner, for several neurobiological observations concerning consciousness. As shown here, these include the association of consciousness with certain neural systems rather than with others; the fact that neural processes underlying consciousness can influence or be influenced by neural processes that remain unconscious; the reduction of consciousness during dreamless sleep and generalized seizures; and the time requirements on neural interactions that support consciousness. IMPLICATIONS OF THE HYPOTHESIS: The theory entails that consciousness is a fundamental quantity, that it is graded, that it is present in infants and animals, and that it should be possible to build conscious artifacts.
This article examines decision processes in the perception and categorization of stimuli composed of the separable psychological dimensions, orientation and size. The randomization technique (Ashby & Gott, 1988) of general recognition theory, which allows accurate estimation of a subject's decision boundary in a categorization task, is used in 4 experiments. Even though the stimulus components are clearly separable, it was found that Ss were not constrained to use separable response strategies, nor were they constrained to attend to distance to the prototypes. Instead, they used decision rules that were nearly optimal, even if this required information integration or for the Ss to attend to higher level category properties such as component correlation.
The ability of normal-hearing children (aged 4 through 7 years) and adults to integrate information was measured in an auditory sample discrimination task. On each trial a pair of tonal sequences was played whose component frequencies were randomly drawn from two equal-variance, Gaussian distributions with different means. The listeners task was to identify the sequence drawn from the distribution with the higher mean frequency. Performance was first evaluated as a function of the number of components in each sequence. Results showed that discrimination accuracy improved with increasing age until age 7, at which time performance was adult-like. The 7-year-olds and the adults discriminated the sequences with increasing accuracy as the sequence length was increased, but the 4-to 6-year-old listeners, as a group, did not. Data were fitted with a model with two free parameters, one representing resolution of the components and presumed to reflect peripheral processing, and another representing central noise added to the decision process after the component information is combined [R. Lutfi, J. Acoust. Soc. Am. 86, 934-944 (1989)]. On average, both parameters showed gradual changes as age increased, with adult-like values by 7 years of age. Individual data however suggest that the changes in central noise with age may be less gradual than the changes in peripheral resolution. In a second condition, increases in component duration produced improved performance for the 7-year-olds and the adults, while that of the younger listeners remained the same. Fitted parameters suggested improvements in component resolution for the older children, with no changes in central noise levels. In a third condition, reducing the overlap in the distributions improved performance for only a few of several younger children. This improvement was attributable to lower levels of central noise. Overall, these results suggest that with increasing age children are better able to discriminate between sounds that are variable and have overlapping acoustic characteristics. This age-related improvement may be attributed both to improvements in the ability to resolve the components and to reductions in central noise.
In three experiments, we investigated whether the amount of category overlap constrains the decision strategies used in category learning, and whether such constraints depend on the type of category structures used. Experiments 1 and 2 used a category-learning task requiring perceptual integration of information from multiple dimensions (an information-integration task) and Experiment 3 used a task requiring the application of an explicit strategy (a rule-based task). In the information-integration task, participants used perceptual-integration strategies at moderate levels of category overlap, but explicit strategies at extreme levels of overlap--even when such strategies were suboptimal. In contrast, in the rule-based task, participants used explicit strategies, regardless of the level of category overlap. These data are consistent with a multiple systems view of category learning, and suggest that categorization strategy depends on the type of task that is used, and on the degree to which each stimulus is probabilistically associated with the contrasting categories.
Information-integration category learning was examined in older and younger adults. Accuracy results indicated that older participants learned less well than younger participants in both linear and nonlinear conditions. Model-based analyses indicated that both groups in the linear condition tended to use information integration but that later in training younger participants were more likely to do so. In contrast, the 2 groups in the nonlinear condition were equally likely to use information integration. Further analysis indicated that younger adults were more accurate than older adults when an information-integration approach was adopted, whereas fewer age-related differences were observed when a rule-based approach was used, suggesting that age can have a negative impact on information-integration category learning processes but less impact on rule-based learning.
An information need (the problem) cannot be divorced from its context. The problem context determines the urgency, granularity of detail, authority, and level of certainty required for an acceptable answer and dictates the expertise and resources that can be brought to bear. The size and diversity of the sources that can be marshalled during clinical problem solving is cognitively unmanageable--too large and too complex for a single person to process effectively in a constrained timeframe. Can the clinical team, as currently constituted, collectively handle this information-processing task, or is there a need for special information expertise on the team? If there is such a need, what is the best way to prepare information specialists to participate in context-based problem solving? This article explores preparation for work in information-rich, problem-solving environments. The authors provide two case studies, one clinical and one bioscientific, that elucidate knowledge and training requirements for information specialists who work as peers in patient care and research settings.
The strategic importance of integrated information systems and resources for academic medical centers should not be underestimated. Ten years ago, the National Library of Medicine in collaboration with the Association of Academic Medical Centers initiated the Integrated Advanced Information Management System (IAIMS) program to assist academic medical centers in defining a process for addressing deficiencies in their information environments. The authors give a brief history of the IAIMS program, and they describe both the characteristics of an integrated information environment and the technical and organizational structures necessary to create such an environment. Strategies some institutions have used to implement integrated information systems are also outlined. Finally, the authors discuss the role of librarians in integrated information system design.
Information-integration category learning was examined in patients with Parkinson's disease (PD) and in healthy control participants in 2 different conditions. In the linear condition, optimal categorization required a nonverbalizable linear integration of information from the 2 stimulus dimensions, whereas in the nonlinear condition, a nonlinear integration of information was required. Each participant completed 600 trials in each condition and was given corrective feedback following each trial. Results indicated that PD patients were not impaired in the linear condition across all trials, whereas the same patients were impaired in the nonlinear condition, but only later in training. The authors conducted model-based analyses to identify participants who used an information-integration approach, and a comparison of the accuracy rates of those individuals further revealed a specific deficit in information-integration category learning in patients with PD. These findings suggest that the striatum may be particularly involved in information-integration category learning when the rule is highly complex.
Using magnetoencephalography, we investigated the spatiotemporal patterns of brain magnetic activity responsible for maintaining verbal and spatial information in either an integrated or an unintegrated fashion. Considering time dimension, we noted a greater activation of a fronto-parietal network in early latencies during the maintenance of integrated information, and a different pattern during the maintenance of unintegrated material, showing a greater activation in a fronto-posterior network in late latencies. The greater activation found in certain areas which are traditionally reported as being engaged in spatial working memory (i.e. superior frontal gyri, dorsolateral prefrontal cortex, superior and inferior parietal lobes) when subjects maintained integrated information could be explained by a greater weight of the spatial dimension. It is as if words somehow acquired a spatial attribute, thus exerting a greater load in a neural network specialized in spatial working memory. Alternatively, and not mutually exclusive, we also propose that during the maintenance of integrated information the allocation of cognitive resources is less interfering than during the maintenance of unintegrated information, making it easier.
Although multiple decision support systems have been built for physicians, efficient delivery of valid and complete medical knowledge remains an elusive goal. In this paper we describe a new project, the Stanford Health Information Network for Education (SHINE). SHINE unifies core medical resources in an intuitive interface to support clinical decision making. Included in the description is a novel paradigm for continuing medical education (CME).
The Legume Information System (LIS) (http://www.comparative-legumes.org), developed by the National Center for Genome Resources in cooperation with the USDA Agricultural Research Service (ARS), is a comparative legume resource that integrates genetic and molecular data from multiple legume species enabling cross-species genomic and transcript comparisons. The LIS virtual plant interface allows simplified and intuitive navigation of transcript data from Medicago truncatula, Lotus japonicus, Glycine max and Arabidopsis thaliana. Transcript libraries are represented as images of plant organs in different developmental stages, which are selected to query the analyzed and annotated data. Complex queries can be accomplished by adding modifiers, keywords and sequence names. The LIS also contains annotated genomic data featuring transcript alignments to validate gene predictions as well as motif and similarity analyses. The genomic browser supports comparative analysis via novel dynamic functional annotation comparisons. CMap, developed as part of the GMOD project (http://www.gmod.org/cmap/index.shtml), has been incorporated to support comparative analyses of community linkage and physical map data. LIS is being expanded to incorporate gene expression and biochemical pathways which will be seamlessly integrated forming a knowledge discovery framework.
Clinical observations have established that certain parts of the brain are essential for consciousness whereas other parts are not. For example, different areas of the cerebral cortex contribute different modalities and submodalities of consciousness, whereas the cerebellum does not, despite having even more neurons. It is also well established that consciousness depends on the way the brain functions. For example, consciousness is much reduced during slow wave sleep and generalized seizures, even though the levels of neural activity are comparable or higher than in wakefulness. To understand why this is so, empirical observations on the neural correlates of consciousness need to be complemented by a principled theoretical approach. Otherwise, it is unlikely that we could ever establish to what extent consciousness is present in neurological conditions such as akinetic mutism, psychomotor seizures, or sleepwalking, and to what extent it is present in newborn babies and animals. A principled approach is provided by the information integration theory of consciousness. This theory claims that consciousness corresponds to a system's capacity to integrate information, and proposes a way to measure such capacity. The information integration theory can account for several neurobiological observations concerning consciousness, including: (i) the association of consciousness with certain neural systems rather than with others; (ii) the fact that neural processes underlying consciousness can influence or be influenced by neural processes that remain unconscious; (iii) the reduction of consciousness during dreamless sleep and generalized seizures; and (iv) the time requirements on neural interactions that support consciousness.
Category number effects on rule-based and information-integration category learning were investigated. Category number affected accuracy and the distribution of best-fitting models in the rule-based task but had no effect on accuracy and little effect on the distribution of best-fining models in the information-integration task. In the 2 category conditions, rule-based learning was better than information-integration learning, whereas in the 4 category conditions, unidimensional and conjunctive rule-based learning was worse than information-integration learning. Rule-based strategies were used in the 2-category/rule-based condition, but about half of the observers used rule-based strategies in the 4-category unidimensional and conjunctive rule-based conditions. Information-integration strategies were used in the 4-category/ information-integration condition and by the end of training were used in the 2-category/information-integration condition.