Complex Worlds From Simpler Nervous Systems

Examining the surprisingly complex perceptual abilities of so-called "simpler" animals, including jumping spiders, bees, praying mantids, butterflies, cockroaches, bladder grasshoppers, crayfish, mantis shrimps, octopuses, and toads.

Depending on your point of view the brain is an organ, a machine, a biological computer, or simply the most important component of the nervous system. How does it work as a whole? What are its major parts and how are they interconnected to generate thinking, feelings, and behavior? This book surveys 2,500 years of scientific thinking about these profoundly important questions from the perspective of fundamental architectural principles, and then proposes a new model for the basic plan of neural systems organization based on an explosion of structural data emerging from the neuroanatomy revolution of the 1970's. The importance of a balance between theoretical and experimental morphology is stressed throughout the book. Great advances in understanding the brain's basic plan have come especially from two traditional lines of biological thought-- evolution and embryology, because each begins with the simple and progresses to the more complex. Understanding the organization of brain circuits, which contain thousands of links or pathways, is much more difficult. It is argued here that a four-system network model can explain the structure-function organization of the brain. Possible relationships between neural networks and gene networks revealed by the human genome project are explored in the final chapter. The book is written in clear and sparkling prose, and it is profusely illustrated. It is designed to be read by anyone with an interest in the basic organization of the brain, from neuroscience to philosophy to computer science to molecular biology. It is suitable for use in neuroscience core courses because it presents basic principles of the structure of the nervous system in a systematic way.

Evolutionary Neuroscience is a collection of articles in brain evolution selected from the recent comprehensive reference, Evolution of Nervous Systems (Elsevier, Academic Press, 2007). The selected chapters cover a broad range of topics from historical theory to the most recent deductions from comparative studies of brains. The articles are organized in sections focused on theories and brain scaling, the evolution of brains from early vertebrates to present-day fishes, amphibians, reptiles and birds, the evolution of mammalian brains, and the evolution of primate brains, including human brains. Each chapter is written by a leader or leaders in the field, and has been reviewed by other experts. Specific topics include brain character reconstruction, principles of brain scaling, basic features of vertebrate brains, the evolution of the major sensory systems, and other parts of brains, what we can learn from fossils, the origin of neocortex, and the evolution of specializations of human brains. The collection of articles will be interesting to anyone who is curious about how brains evolved from the simpler nervous systems of the first vertebrates into the many different complex forms now found in present-day vertebrates. This book would be of use to students at the graduate or undergraduate levels, as well as professional neuroscientists, cognitive scientists, and psychologists. Together, the chapters provide a comprehensive list of further reading and references for those who want to inquire further. The most comprehensive, authoritative and up-to-date single volume collection on brain evolution Full color throughout, with many illustrations Written by leading scholars and experts

The visual world of animals is highly diverse and often very different from that of humans. This book provides an extensive review of the latest behavioral and neurobiological research on animal vision, detailing fascinating species similarities and differences in visual processing.

This book shows how mathematics, computer science and science can be usefully and seamlessly intertwined. It begins with a general model of cognitive processes in a network of computational nodes, such as neurons, using a variety of tools from mathematics, computational science and neurobiology. It then moves on to solve the diffusion model from a low-level random walk point of view. It also demonstrates how this idea can be used in a new approach to solving the cable equation, in order to better understand the neural computation approximations. It introduces specialized data for emotional content, which allows a brain model to be built using MatLab tools, and also highlights a simple model of cognitive dysfunction.

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