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Neuroscience

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Retraining Subconscious Awareness

This is a book for readers who want to probe more deeply into mindfulness. It goes beyond the casual, once-in-awhile meditation in popular culture, grounding mindfulness in daily practice, Zen teachings, and recent research in neuroscience. In Living Zen Remindfully, James Austin, author of the groundbreaking Zen and the Brain, describes authentic Zen training—the commitment to a process of regular, ongoing daily life practice. This training process enables us to unlearn unfruitful habits, develop more wholesome ones, and lead a more genuinely creative life.

Philosophers from Descartes to Kripke have struggled with the glittering prize of modern and contemporary philosophy: the mind-body problem. The brain is physical. If the mind is physical, we cannot see how. If we cannot see how the mind is physical, we cannot see how it can interact with the body. And if the mind is not physical, it cannot interact with the body. Or so it seems.

Learning Invariant Representations

The ventral visual stream is believed to underlie object recognition in primates. Over the past fifty years, researchers have developed a series of quantitative models that are increasingly faithful to the biological architecture. Recently, deep learning convolution networks—which do not reflect several important features of the ventral stream architecture and physiology—have been trained with extremely large datasets, resulting in model neurons that mimic object recognition but do not explain the nature of the computations carried out in the ventral stream.

Fifty years ago, neuroscientists thought that a mature brain was fixed like a fly in amber, unable to change. Today, we know that our brains and nervous systems change throughout our lifetimes. This concept of neuroplasticity has captured the imagination of a public eager for self-improvement—and has inspired countless Internet entrepreneurs who peddle dubious “brain training” games and apps.

In this book, Frank Guenther offers a comprehensive, unified account of the neural computations underlying speech production, with an emphasis on speech motor control rather than linguistic content. Guenther focuses on the brain mechanisms responsible for commanding the musculature of the vocal tract to produce articulations that result in an acoustic signal conveying a desired string of syllables.

From Place Cells to Episodic Memory

There are currently two major theories about the role of the hippocampus, a distinctive structure in the back of the temporal lobe. One says that it stores a cognitive map, the other that it is a key locus for the temporary storage of episodic memories. A. David Redish takes the approach that understanding the role of the hippocampus in space will make it possible to address its role in less easily quantifiable areas such as memory.

Neurobiological and Molecular Mechanisms of Sexual Motivation

What arouses an animal or human from an inactive, nonresponsive state to a condition of activity and responsiveness? What are the biological mechanisms for this change? In this book Donald W. Pfaff focuses on a reproductive behavior typical of many female animals. Sensory stimuli from the male trigger responses in a well-defined circuit of nerve cells. At the top of the circuit, certain nerve cells receive and retain sex hormones such as estrogens and progesterone.

Pain, although very common, is little understood. Worse still, according to Valerie Gray Hardcastle, both professional and lay definitions of pain are wrongheaded—with consequences for how pain and pain patients are treated, how psychological disorders are understood, and how clinicians define the mind/body relationship.

Foundations of Neural Computation

Since its founding in 1989 by Terrence Sejnowski, Neural Computation has become the leading journal in the field. Foundations of Neural Computationcollects, by topic, the most significant papers that have appeared in the journal over the past nine years.This volume of Foundations of Neural Computation, on unsupervised learning algorithms, focuses on neural network learning algorithms that do not require an explicit teacher. The goal of unsupervised learning is to extract an efficient internal representation of the statistical structure implicit in the inputs.

Toward Action-Oriented Views in Cognitive Science

Cognitive science is experiencing a pragmatic turn away from the traditional representation-centered framework toward a view that focuses on understanding cognition as “enactive.” This enactive view holds that cognition does not produce models of the world but rather subserves action as it is grounded in sensorimotor skills. In this volume, experts from cognitive science, neuroscience, psychology, robotics, and philosophy of mind assess the foundations and implications of a novel action-oriented view of cognition.

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