Insects are among the most diverse and adaptable organisms on Earth. They have long been our chief competitors for food and are responsible for spreading devastating afflictions such as malaria and encephalitis. The insects' ability to thrive is due in large part to their well-developed sensory systems, which present a host of novel physiological,

Synthesizing current information about sensory-motor plasticity, Neural Plasticity in Adult Somatic Sensory-Motor Systems provides an up-to-date description of the dynamic processes that occur in somatic sensory-motor cortical circuits or somatic sensory pathways to the cortex due to experience, learning, or damage to the nervous system. The book e

Extensively updated and expanded, this second edition of a bestseller distills the current state-of-the-science and provides the nuts and bolts foundation of the methods involved in this rapidly growing science. With contributions from pioneering researchers, it includes microwire array design for chronic neural recordings, new surgical techniques for chronic implantation, microelectrode microstimulation of brain tissue, multielectrode recordings in the somatosensory system and during learning, as well as recordings from the central gustatory-reward pathways. It explores the use of Brain-Machine Interface to restore neurological function and proposes conceptual and technical approaches to human neural ensemble recordings in the future.

It has become accepted in the neuroscience community that perception and performance are quintessentially multisensory by nature. Using the full palette of modern brain imaging and neuroscience methods, The Neural Bases of Multisensory Processes details current understanding in the neural bases for these phenomena as studied across species, stages

Since the first TRP ion channel was discovered in Drosophila melanogaster in 1989, the progress made in this area of signaling research has yielded findings that offer the potential to dramatically impact human health and wellness. Involved in gateway activity for all five of our senses, TRP channels have been shown to respond to a wide range of st

Recognition that aging is not the accumulation of disease, but rather comprises fundamental biological processes that are amenable to experimental study, is the basis for the recent growth of experimental biogerontology. As increasingly sophisticated studies provide greater understanding of what occurs in the aging brain and how these changes occur

Statistical Techniques for Neuroscientists introduces new and useful methods for data analysis involving simultaneous recording of neuron or large cluster (brain region) neuron activity. The statistical estimation and tests of hypotheses are based on the likelihood principle derived from stationary point processes and time series. Algorithms and software development are given in each chapter to reproduce the computer simulated results described therein. The book examines current statistical methods for solving emerging problems in neuroscience. These methods have been applied to data involving multichannel neural spike train, spike sorting, blind source separation, functional and effective neural connectivity, spatiotemporal modeling, and multimodal neuroimaging techniques. The author provides an overview of various methods being applied to specific research areas of neuroscience, emphasizing statistical principles and their software. The book includes examples and experimental data so that readers can understand the principles and master the methods. The first part of the book deals with the traditional multivariate time series analysis applied to the context of multichannel spike trains and fMRI using respectively the probability structures or likelihood associated with time-to-fire and discrete Fourier transforms (DFT) of point processes. The second part introduces a relatively new form of statistical spatiotemporal modeling for fMRI and EEG data analysis. In addition to neural scientists and statisticians, anyone wishing to employ intense computing methods to extract important features and information directly from data rather than relying heavily on models built on leading cases such as linear regression or Gaussian processes will find this book extremely helpful.