The Journals division of the MIT Press began in 1969 with two quarterly publications. Today, we publish 30 titles in the arts and humanities, economics, international affairs, history, political science, science and technology. We were one of the first university presses to offer its titles electronically, and the division continues to adopt technologies that allow us to better support the scholarly mission and disseminate our content widely. The division publishes journals owned by the MIT Press as well as journals sponsored by various societies and associations. We offer a suite of traditional and digital services that can be customized to fit each journal’s needs.
The vast differences between the brain's neural circuitry and a computer's silicon circuitry might suggest that they have nothing in common. In fact, as Dana Ballard argues in this book, computational tools are essential for understanding brain function. Ballard shows that the hierarchical organization of the brain has many parallels with the hierarchical organization of computing; as in silicon computing, the complexities of brain computation can be dramatically simplified when its computation is factored into different levels of abstraction.Drawing on several decades of progress in computational neuroscience, together with recent results in Bayesian and reinforcement learning methodologies, Ballard factors the brain's principal computational issues in terms of their natural place in an overall hierarchy. Each of these factors leads to a fresh perspective. A neural level focuses on the basic forebrain functions and shows how processing demands dictate the extensive use of timing-based circuitry and an overall organization of tabular memories. An embodiment level organization works in reverse, making extensive use of multiplexing and on-demand processing to achieve fast parallel computation. An awareness level focuses on the brain's representations of emotion, attention and consciousness, showing that they can operate with great economy in the context of the neural and embodiment substrates.
Climate engineering -- which could slow the pace of global warming by injecting reflective particles into the upper atmosphere -- has emerged in recent years as an extremely controversial technology. And for good reason: it carries unknown risks and it may undermine commitments to conserving energy. Some critics also view it as an immoral human breach of the natural world. The latter objection, David Keith argues in <I>A Scientist's Case for Climate Engineering</I>, is groundless; we have been using technology to alter our environment for years. But he agrees that there are large issues at stake. A leading scientist long concerned about climate change, Keith offers no naïve proposal for an easy fix to what is perhaps the most challenging question of our time; climate engineering is no silver bullet. But he argues that after decades during which very little progress has been made in reducing carbon emissions we must put this technology on the table and consider it responsibly. That doesn't mean we will deploy it, and it doesn't mean that we can abandon efforts to reduce greenhouse gas emissions. But we must understand fully what research needs to be done and how the technology might be designed and used. This book provides a clear and accessible overview of what the costs and risks might be, and how climate engineering might fit into a larger program for managing climate change.
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