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Abstract
The capacity that subjects have to rate confidence in their choices is a form of metacognition, and can be assessed according to bias, sensitivity and efficiency. Rich networks of domain-specific and domain-general regions of the brain are involved in the rating, and are associated with its quality and its use for regulating the processes of thinking and acting. Sensitivity and efficiency are often measured by quantities called meta–d′ and the M-ratio that are based on reverse engineering the potential accuracy of the original, primary, choice that is implied by the quality of the confidence judgements. Here, we advocate a straightforward measure of sensitivity, called meta–𝓘, which assesses the mutual information between the accuracy of the subject's choices and the confidence reports, and two normalized versions of this measure that quantify efficiency in different regimes. Unlike most other measures, meta–𝓘-based quantities increase with the number of correctly assessed bins with which confidence is reported. We illustrate meta–𝓘 on data from a perceptual decision-making task, and via a simple form of simulated second-order metacognitive observer.

This book is an updated version of the information theory classic, first published in 1990. About one-third of the book is devoted to Shannon source and channel coding theorems; the remainder addresses sources, channels, and codes and on information and distortion measures and their properties. New in this edition: Expanded treatment of stationary or sliding-block codes and their relations to traditional block codesExpanded discussion of results from ergodic theory relevant to information theoryExpanded treatment of B-processes -- processes formed by stationary coding memoryless sourcesNew mat.

"This highly interdisciplinary book discusses the phenomenon of life, including its origin and evolution, against the background of thermodynamics, statistical mechanics, and information theory. Among the central themes is the seeming contradiction between the second law of thermodynamics and the high degree of order and complexity produced by living systems. As the author shows, this paradox has its resolution in the information content of the Gibbs free energy that enters the biosphere from outside sources. Another focus of the book is the role of information in human cultural evolution, which is also discussed with the origin of human linguistic abilities. One of the final chapters addresses the merging of information technology and biotechnology into a new discipline - bioinformation technology. This third edition has been updated to reflect the latest scientific and technological advances. Professor Avery makes use of the perspectives of famous scholars such as Professor Noam Chomsky and Nobel Laureates John O'Keefe, May-Britt Moser and Edward Moser to cast light on the evolution of human languages. The mechanism of cell differentiation, and the rapid acceleration of information technology in the 21st century are also discussed. With various research disciplines becoming increasingly interrelated today, Information Theory and Evolution provides nuance to the conversation between bioinformatics, information technology, and pertinent social-political issues. This book is a welcome voice in working on the future challenges that humanity will face as a result of scientific and technological progress"--

The Director of the Institute of Communications Research at the University of Illinois discusses the nature of information theory and some of its possible applications to research on mass communications. There is an appendix on formulas, how to compute them, and suggested readings.

Capter 1 Introduction -- 1.1 Properties of Information -- 1.2 Levels of Information -- 1.3 Information Media -- 1.4 Reversible and Irreversible Processes -- I -- Capter 2 Noiseless Channels -- 3 Coding for Noiseless Channels -- 4 Joint Events, Natural Languages -- 5 Noisy Channel -- 6 Error Checking and Correcting Codes -- II -- 7 Properties of Continuous Channels -- Capter 8 Detection of Continuous Signals -- 9 Information Filters -- References -- Appendix A Fourier Transform and Related Concepts -- Appendix B Binary logarithms and Entropies -- Appendix C Problems.

Sound localization has been studied extensively. Curiously, although much is known about factors that affect errors, little is known about factors that influence response time. Three experiments were performed in an attempt to identify the separate influence of each of several different factors. All trials used a single broadband noise signal emanating from one of a subset of six loudspeakers equally spaced around the participant in the azimuthal plane. Both the size of the subset and the balance of relative probabilities from speaker to speaker were altered to evaluate the relationship between information content and the dependent variable, choice reaction time. Choice reaction time was found to be related to the information content of the sound stimulus in all cases. It was also found to be related to the presence of pairs of speakers that were symmetrically opposed in front of and behind the participant. Models of choice reaction time in a sound localization task have clear implications for practice. For example, they suggest that multiple auditory collision warnings may endanger drivers.

The statistical theory of selective information put forward by C. E. Shannon in Bell Systems Technology J., Vol 27, 379-423, is examined &explained. The model of COMM underlying this theory is constructed as a chain of 5 components in the following order: source of information, encoder, channel, decoder, `sink of information.' Sometimes the source &the sink are combined with their adjacent component into single units, which could be called respectively sender & receiver. The transmission channel is presented mathematically by a matrix of transition probabilities. This model is applied to natural languages & its mathematical concept is briefly summarized. It is asserted that an evaluation of the information theory model from other than an engineering point of view requires a general, unified theory of COMM, which does not exist as yet. The model may be useful in analyses of mass events in language which signif'ly characterize linguistics laws, stylistic trends, the balance of patterns &verbal behavior. The capacity of the mathematical formulae of this model to measure the statistical dependencies of serially ordered units is considered its `most attractive feature.' More res in psycholinguistics is called for in order to test the psychol'al status of the results obtained by applying the model. As examples of such has the following studies are mentioned: A. H. Roberts, A STATISTICAL LIN- GUISTIC ANALYSIS OF AMERICAN ENGLISH, Mouton & Co, 1965; G. Herdan, THE ADVANCED THEORY OF LANGUAGE AS CHOICE AND CHANCE, Berlin, Heidelberg, Germany, & New York, NY: Springer 1966; W. R. Garner, UNCERTAINTY AND STRUCTURE AS PSYCHOLOGICAL CONCEPTS, New York & London: Wiley, 1962. M. Maxfield.