I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

Principles of Neural Science

Software implementations of brain-inspired computing underlie many important computational tasks, from image processing to speech recognition, artificial intelligence and deep learning applications. Yet, unlike real neural tissue, traditional computing architectures physically separate the core computing functions of memory and processing, making fast, efficient and low-energy computing difficult to achieve. To overcome such limitations, an attractive alternative is to design hardware that mimics neurons and synapses. Such hardware, when connected in networks or neuromorphic systems, processes information in a way more analogous to brains. Here we present an all-optical version of such a neurosynaptic system, capable of supervised and unsupervised learning. We exploit wavelength division multiplexing techniques to implement a scalable circuit architecture for photonic neural networks, successfully demonstrating pattern recognition directly in the optical domain. Such photonic neurosynaptic networks promise access to the high speed and high bandwidth inherent to optical systems, thus enabling the direct processing of optical telecommunication and visual data. An optical version of a brain-inspired neurosynaptic system, using wavelength division multiplexing techniques, is presented that is capable of supervised and unsupervised learning.

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All-optical spiking neurosynaptic networks with self-learning capabilities.

Bio-integrated wearable systems can measure a broad range of biophysical, biochemical, and environmental signals to provide critical insights into overall health status and to quantify human performance. Recent advances in material science, chemical analysis techniques, device designs, and assembly methods form the foundations for a uniquely differentiated type of wearable technology, characterized by noninvasive, intimate integration with the soft, curved, time-dynamic surfaces of the body. This review summarizes the latest advances in this emerging field of “bio-integrated” technologies in a comprehensive manner that connects fundamental developments in chemistry, material science, and engineering with sensing technologies that have the potential for widespread deployment and societal benefit in human health care. An introduction to the chemistries and materials for the active components of these systems contextualizes essential design considerations for sensors and associated platforms that appear in f...

Bio-Integrated Wearable Systems: A Comprehensive Review

The English-language dictionary defines wrinkles as "small furrows, ridges, or creases on a normally smooth surface, caused by crumpling, folding, or shrinking". In this paper we review the scientific aspects of wrinkling and the related phenomenon of buckling. Specifically, we discuss how and why wrinkles/buckles form in various materials. We also describe several examples from everyday life, which demonstrate that wrinkling or buckling is indeed a commonplace phenomenon that spans a multitude of length scales. We will emphasize that wrinkling is not always a frustrating feature (e.g., wrinkles in human skin), as it can help to assemble new structures, understand important physical phenomena, and even assist in characterizing chief material properties.

Soft matter with hard skin : From skin wrinkles to templating and material characterization

Wearable sensors have received considerable interest over the past decade owing to their tremendous promise for monitoring the wearers’ health, fitness, and their surroundings. However, only limited attention has been directed at developing wearable chemical sensors that offer more comprehensive information about a wearer’s well-being. The development of wearable chemical sensors faces multiple challenges on various fronts. This perspective reviews key challenges and technological gaps impeding the successful realization of effective wearable chemical sensor systems, related to materials, power, analytical procedure, communication, data acquisition, processing, and security. Size, rigidity, and operational requirements of present chemical sensors are incompatible with wearable technology. Sensor stability and on-body sensor surface regeneration constitute key analytical challenges. Similarly, present wearable power sources are incapable of meeting the requirements for wearable electronics owing to their l...

Wearable Chemical Sensors: Present Challenges and Future Prospects

Neuromorphic architectures are hardware systems that aim to use the principles of neural function for their basis of operation. Their goal is to harness biologically inspired concepts such as weighted connections, activation thresholds, short-and long-term potentiation, and inhibition to solve problems in distributed computation. Compared with today’s methods of emulating neural function in software on conventional von Neumann hardware, neuromorphic systems provide the promise of inherently low power and fault-tolerant operation directly implemented into hardware, for application in distributed and embedded computing tasks, where the vast scaling of today’s architectures does not provide a long-term solution. This mini review is intended for a general engineering audience not currently familiar with this exciting research area. It provides descriptions of some of the recent advances, including supercomputer and single-device implementations, approaches based on spiking and nonspiking neurons, machine learning hardware accelerators, and those utilizing memristive devices. Hardware implementations utilizing both conventional electronic materials and organic electronic materials are reviewed.

A Mini Review of Neuromorphic Architectures and Implementations

Self-Adhesive and Ultra-Conformable, Sub-300 nm Dry Thin-Film Electrodes for Surface Monitoring of Biopotentials

300-nm Imperceptible, Ultraflexible, and Biocompatible e-Skin Fit with Tactile Sensors and Organic Transistors

Super‐ and Ultrathin Organic Field‐Effect Transistors: from Flexibility to Super‐ and Ultraflexibility

Flexible electronics enable various technologies to be integrated into daily life and fuel the quests to develop revolutionary applications, such as artificial skins, intelligent textiles, e-skin patches, and on-skin displays. Mechanical characteristics, including the total thickness and the bending radius, are of paramount importance for physically flexible electronics. However, the limitation regarding semiconductor fabrication challenges the mechanical flexibility of thin-film electronics. Thin-Film Transistors (TFTs) are a key component in thin-film electronics that restrict the flexibility of thin-film systems. Here, we provide a brief overview of the trends of the last three decades in the physical flexibility of various semiconducting technologies, including amorphous-silicon, polycrystalline silicon, oxides, carbon nanotubes, and organics. The study demonstrates the trends of the mechanical properties, including the total thickness and the bending radius, and provides a vision for the future of flexible TFTs.

Robert A. Nawrocki

Papers

A Mini Review of Neuromorphic Architectures and Implementations

Self-Adhesive and Ultra-Conformable, Sub-300 nm Dry Thin-Film Electrodes for Surface Monitoring of Biopotentials

300-nm Imperceptible, Ultraflexible, and Biocompatible e-Skin Fit with Tactile Sensors and Organic Transistors

Super‐ and Ultrathin Organic Field‐Effect Transistors: from Flexibility to Super‐ and Ultraflexibility

A Review of the Progress of Thin-Film Transistors and Their Technologies for Flexible Electronics