Cognitive Code

As the second decade of the twenty-first century draws to a close, the cultural, social, and economic effects of artificial intelligence are becoming ever more apparent. Despite their long-intertwined histories, the fields of neuroscience and artificial intelligence research are notoriously divided. In Cognitive Code Johannes Bruder argues that seemingly incompatible scales of intelligence – the brain and the planet – are now intimately linked through neuroscience-inspired AI and computational cognitive neuroscience. Building on ethnographic fieldwork in brain imaging labs in the United Kingdom and Switzerland, alongside analyses of historical and contemporary literature, Cognitive Code examines how contemporary research on the brain makes routine use of engineering epistemologies and practices. Bruder elaborates on how the question of mimicking human cognition and thought on the scale of computer chips and circuits has gradually evolved into a comprehensive restructuring of the world through "smart" infrastructures. The brain, traditionally treated as a discrete object that thinks, is becoming part of the larger thinking network we now know as "the Cloud." The author traces a recent shift in the goals of brain imaging to show that the introduction of novel statistical and computational techniques has upset traditional paradigms and disentangled cognition from its biological substrate. Investigating understandings of intelligence from the micro to the macro, Cognitive Code explains how the future of human psychology is increasingly determined by engineering and design.

This volume features the complete text of all regular papers, posters, and summaries of symposia presented at the 15th annual meeting of the Cognitive Science Society.

The ELT & Linguistics Dictionary is a companion to the English language as a second / foreign language study. The Dictionary is more likely a reference/guide book for ELT professionals and students who have been taking up EFL/ESL courses at their graduate and post graduate education. So it is; Comprehensive: almost 2321 entries covering all integrated skills in English language training, linguistic terms closely related to ELT, EFL, ELL, ESL, ESOL, FLL, FLT, TEFL, TESL, & TESOL ; Informative: it provides bibliographies for most of the entries and a wide range of cross-referencing for more conceptual headwords; Referential: it gives a hand to the ELT professionals to understand the concepts more specifically used in ELT literature with the original definitions from the prolific writers in the ELT world.

Cognitive Disability Aesthetics explores the invisibility of cognitive disability in theoretical, historical, social, and cultural contexts. Benjamin Fraser's cutting edge research and analysis signals a second-wave in disability studies that prioritizes cognition. Fraser expands upon previous research into physical disability representations and focuses on those disabilities that tend to be least visible in society (autism, Down syndrome, Alzheimer's disease, schizophrenia). Moving beyond established literary approaches analyzing prose representations of disability, the book explores how iconic and indexical modes of signification operate in visual texts. Taking on cognitive disability representations in a range of visual media (painting, cinema, and graphic novels), Fraser showcases the value of returning to impairment discourse. Cognitive Disability Aesthetics successfully reconfigures disability studies in the humanities and exposes the chasm that exists between Anglophone disability studies and disability studies in the Hispanic world.

An introduction to computational modeling for cognitive neuroscientists, covering both foundational work and recent developments. Cognitive neuroscientists need sophisticated conceptual tools to make sense of their field’s proliferation of novel theories, methods, and data. Computational modeling is such a tool, enabling researchers to turn theories into precise formulations. This book offers a mathematically gentle and theoretically unified introduction to modeling cognitive processes. Theoretical exercises of varying degrees of difficulty throughout help readers develop their modeling skills. After a general introduction to cognitive modeling and optimization, the book covers models of decision making; supervised learning algorithms, including Hebbian learning, delta rule, and backpropagation; the statistical model analysis methods of model parameter estimation and model evaluation; the three recent cognitive modeling approaches of reinforcement learning, unsupervised learning, and Bayesian models; and models of social interaction. All mathematical concepts are introduced gradually, with no background in advanced topics required. Hints and solutions for exercises and a glossary follow the main text. All code in the book is Python, with the Spyder editor in the Anaconda environment. A GitHub repository with Python files enables readers to access the computer code used and start programming themselves. The book is suitable as an introduction to modeling cognitive processes for students across a range of disciplines and as a reference for researchers interested in a broad overview.

This textbook provides a general introduction to the field of neural networks. Thoroughly revised and updated from the previous editions of 1991 and 2000, the current edition concentrates on networks for modeling brain processes involved in cognitive and behavioral functions. Part one explores the philosophy of modeling and the field’s history starting from the mid-1940s, and then discusses past models of associative learning and of short-term memory that provide building blocks for more complex recent models. Part two of the book reviews recent experimental findings in cognitive neuroscience and discusses models of conditioning, categorization, category learning, vision, visual attention, sequence learning, behavioral control, decision making, reasoning, and creativity. The book presents these models both as abstract ideas and through examples and concrete data for specific brain regions. The book includes two appendices to help ground the reader: one reviewing the mathematics used in network modeling, and a second reviewing basic neuroscience at both the neuron and brain region level. The book also includes equations, practice exercises, and thought experiments.

This volume brings together theory, research and development in cognitive neuro-science. It investigates the neural processes involved in cognition and learning, using developments in computer technology to study the brain in action and other topographic brain mapping. Electrical activity patterns of the brain in the learning processes are displayed through these techniques. Part 1 delineates neuroscience application to educational perspectives. Part 2 reports on emotional and learning disorders, such as autism, while Part 3 applies cognitive science to educational and mental health, as well as to settings such as the classroom, rehabilitation centre or doctor’s office.

The Mind and Brain are usually considered as one and the same nonlinear, complex dynamical system, in which information processing can be described with vector and tensor transformations and with attractors in multidimensional state spaces. Thus, an internal neurocognitive representation concept consists of a dynamical process which filters out statistical prototypes from the sensorial information in terms of coherent and adaptive n-dimensional vector fields. These prototypes serve as a basis for dynamic, probabilistic predictions or probabilistic hypotheses on prospective new data (see the recently introduced approach of "predictive coding" in neurophilosophy). Furthermore, the phenomenon of sensory and language cognition would thus be based on a multitude of self-regulatory complex dynamics of synchronous self-organization mechanisms, in other words, an emergent "flux equilibrium process" ("steady state") of the total collective and coherent neural activity resulting from the oscillatory actions of neuronal assemblies. In perception it is shown how sensory object informations, like the object color or the object form, can be dynamically related together or can be integrated to a neurally based representation of this perceptual object by means of a synchronization mechanism ("feature binding"). In language processing it is shown how semantic concepts and syntactic roles can be dynamically related together or can be integrated to neurally based systematic and compositional connectionist representations by means of a synchronization mechanism ("variable binding") solving the Fodor-Pylyshyn-Challenge. Since the systemtheoretical connectionism has succeeded in modeling the sensory objects in perception as well as systematic and compositional representations in language processing with this vector- and oscillation-based representation format, a new, convincing theory of neurocognition has been developed, which bridges the neuronal and the cognitive analysis level. The book describes how elementary neuronal information is combined in perception and language, so it becomes clear how the brain processes this information to enable basic cognitive performance of the humans.