E Book

Consciousness



Preface -- What is consciousness?- The Global Neuronal Workspace model. An introduction to information theory. The Shannon Coding Theorem. More heuristics: a 'tuning theorem'. The Shannon-McMillan Theorem. The Rate Distortion Theorem. Large deviations -- Fluctuations. The fundamental homology with statistical physics. Cognition as generalized language -- Theory. Two neural network examples. Interacting cognitive modules -- Representations. Language-on-a-network models. 'Biological' phase transitions. Universality class distribution. Universality class tuning. More on behavior far from the critical point. Extending the model. The simplest tunable retina. Tuning the visual retina. The torus and the sphere. Expanding the workspace. Energy efficiency and consciousness. Where does all this lead? Sociocultural context as selection pressure. Autocognitive developmental disorder. Toward a 'General Cognitive Model'. Evading the mereological fallacy -- References. Appendix on coarse graining."This book brings together the fundamental ideas of information theory and the statistical mechanics of phase transitions within the context of the neurosciences, culture, immunology and socio-psychological studies. Outlined is a program pertaining to a dynamic and semantic extension of current models for the global neuronal workspace as were previously introduced by Baars, Dretske and others. Topics include original applications of rate distortion and large deviations theory, biological renormalization, and retinal tuning as means towards understanding consciousness on the large scale. The overall treatment is concise, has been well thought out, and the mathematical details should be accessible to both students and researchers in the cognitive and life sciences." - James Glazebrook Ph.D, Eastern Illinois University, USA.


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Informasi Detil

Judul Seri
-
No. Panggil
-
Penerbit Springer : Boston, MA.,
Deskripsi Fisik
XIII, 116 p.online resource.
Bahasa
English
ISBN/ISSN
9780387252445
Klasifikasi
612.8
Tipe Isi
-

Informasi Lainnya

Anak judul
A Mathematical Treatment of the Global Neuronal Workspace Model
Judul asli
-
DOI/URL
https://doi.org/10.1007/b106970

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