Retinal Computation summarizes current progress in defining the computations performed by the retina, also including the synaptic and circuit mechanisms by which they are implemented. Each chapter focuses on a single retinal computation that includes the definition of the computation and its neuroethological purpose, along with the available information on its known and unknown neuronal mechanisms. All chapters contain end-of-chapter questions associated with a landmark paper, as well as programming exercises. This book is written for advanced graduate students, researchers and ophthalmologists interested in vision science or computational neuroscience of sensory systems. While the typical textbook's description of the retina is akin to a biological video camera, the real retina is actually the world's most complex image processing machine. As part of the central nervous system, the retina converts patterns of light at the input into a rich palette of representations at the output. The parallel streams of information in the optic nerve encode features like color, contrast, orientation of edges, and direction of motion. Image processing in the retina is undeniably complex, but as one of the most accessible parts of the central nervous system, the tools to study retinal circuits with unprecedented precision are up to the task. This book provides a practical guide and resource about the current state of the field of retinal computation. - Provides a practical guide on the field of retinal computation - Summarizes and clearly explains important topics such as luminance, contrast, spatial features, motion and other computations - Contains discussion questions, a landmark paper, and programming exercises within each chapter

Retinal Computation summarizes current progress in defining the computations performed by the retina, also including the synaptic and circuit mechanisms by which they are implemented. Each chapter focuses on a single retinal computation that includes the definition of the computation and its neuroethological purpose, along with the available information on its known and unknown neuronal mechanisms. All chapters contain end-of-chapter questions associated with a landmark paper, as well as programming exercises. This book is written for advanced graduate students, researchers and ophthalmologists interested in vision science or computational neuroscience of sensory systems. While the typical textbook's description of the retina is akin to a biological video camera, the real retina is actually the world's most complex image processing machine. As part of the central nervous system, the retina converts patterns of light at the input into a rich palette of representations at the output. The parallel streams of information in the optic nerve encode features like color, contrast, orientation of edges, and direction of motion. Image processing in the retina is undeniably complex, but as one of the most accessible parts of the central nervous system, the tools to study retinal circuits with unprecedented precision are up to the task. This book provides a practical guide and resource about the current state of the field of retinal computation. Editorial Reviews: ".this book is also a unique overview of our current understanding of the why and the how of retinal computation and there is something here for anyone with a grounding in vision science who recognises that there is more to what the retina does than. meets the eye." -- Prof Steven Dakin, New Zealand Optics, May 28, 2022. "I want to commend Dr. Schwartz for assembling this incredible resource and strongly recommend Retinal Computation to everyone who is a student of vision. The vast majority of modern topics in retina are covered yet in a fashion that is clear, and concise. The book covers the cellular and circuit basis of computations ranging from those covered by most textbooks, such as center-surround receptive field or direction selectivity , to those you probably do not associated with the retina such as "motion anticipation" and "threat detection". Each chapter is self-contained, meaning you can easily "pick and choose" the topics. A quick perusal of the chapter titles are almost certainly going to pique your interest. For example, you may know that the retina has single photon sensitivity but do you know "How many photons does it take to create a percept"? (Chapter 1). How does the retina encode texture (i.e. spatial fluctuations within the receptive field)? (Chapter 7). Is object motion sensitivity related to Direction selectivity? (Chapter 12). The list goes on. This book will also serve as a great resource for those teaching advanced undergraduate or graduate level vision courses for students with backgrounds in experimental or computational vision science. Each chapter contains what Dr. Schwartz's considers a "landmark paper" in the field, with a set of questions that can be used as a guide for reading these papers. And finally he includes programming exercises that can be easily implemented in Matlab to address basic concepts introduced in the chapter. The instructions are detailed so that even those new to Matlab will be able to implement these exercises these straightforward. It is this combination - textbook chapter + primary literature + quantitative exercises that will solidify these concepts. There are many vision science topics not covered in the book. For example, there is little on retinal disease or development. But these limitations are far outweighed by where the book succeeds. The vast majority of the book is written by Dr. Schwartz, giving it a uniformity that is welcome. Despite tackling quite modern questions where there is ongoing progress, Dr.Schwartz has extracted what are key findings that are likely to stand the test of time. And finally, it is really interesting! For those who think that the retina is "solved", think again. Retinal computations is a fantastic way for all circuit neuroscientist to learn how much computations can be achieved with very few synapses." -- Marla B. Feller, Ph. D., Paul Licht Distinguished Professor in Biological Sciences, Division of Neurobiology, Department of Molecular and Cell Biology & Helen Wills Neuroscience Institute University of California, Berkeley "This fantastic new textbook from a rising star in the field clearly and thoroughly updates our picture of what the retina computes. It is detailed enough for senior researchers but also pedagogical, providing a go-to reference for students. The illustrations within the text and for the chapter headings are both beautiful and informative." -- Stephanie E. Palmer, Ph.D., Associate Professor, Department of Organismal Biology and Anatomy, Department of Physics, University of Chicago "This book summarizes the impressive recent progress in understanding how visual computations are performed by retinal circuits. The book is an important resource not only for retinal experts, but more generally for anyone seeking to explain how the brain works at the level of neural circuits. Greg Schwartz and his co-authors have made a major contribution to the field." -- Sebastian Seung, Anthony B. Evnin '62 Professor, Neuroscience Institute and Computer Science Dept., Princeton University "This is a wonderful book from a true expert in the retina field. It is a fantastic resource for researchers, lecturers, and students alike. The book nicely covers the many facets of how the retina processes the visual input that enters the eye. Despite the richness in material, the presentation manages to stay accessible and always connects back to fundamental questions of visual processing. Each chapter by itself is a great entry point into a particular area of how the neural network of the retina deals with a specific set of visual challenges. I have thoroughly enjoyed this wonderful overview of retinal computation, served on a silver platter, and I will use the book both as background material for research and as a resource for teaching. I particularly like the sets of exercises that conclude each chapter." -- Dr. Tim Gollisch, Professor for Sensory Processing in the Retina, Department of Ophthalmology, University Medical Center Göttingen

Computational Retinal Image Analysis: Tools, Applications and Perspectives gives an overview of contemporary retinal image analysis (RIA) in the context of healthcare informatics and artificial intelligence. Specifically, it provides a history of the field, the clinical motivation for RIA, technical foundations (image acquisition modalities, instruments), computational techniques for essential operations, lesion detection (e.g. optic disc in glaucoma, microaneurysms in diabetes) and validation, as well as insights into current investigations drawing from artificial intelligence and big data. This comprehensive reference is ideal for researchers and graduate students in retinal image analysis, computational ophthalmology, artificial intelligence, biomedical engineering, health informatics, and more.

Computational Retinal Image Analysis: Tools, Applications and Perspectives gives an overview of contemporary retinal image analysis (RIA) in the context of healthcare informatics and artificial intelligence. Specifically, it provides a history of the field, the clinical motivation for RIA, technical foundations (image acquisition modalities, instruments), computational techniques for essential operations, lesion detection (e.g. optic disc in glaucoma, microaneurysms in diabetes) and validation, as well as insights into current investigations drawing from artificial intelligence and big data. This comprehensive reference is ideal for researchers and graduate students in retinal image analysis, computational ophthalmology, artificial intelligence, biomedical engineering, health informatics, and more. - Provides a unique, well-structured and integrated overview of retinal image analysis - Gives insights into future areas, such as large-scale screening programs, precision medicine, and computer-assisted eye care - Includes plans and aspirations of companies and professional bodies

This open access book provides a comprehensive overview of the application of the newest laser and microscope/ophthalmoscope technology in the field of high resolution imaging in microscopy and ophthalmology. Starting by describing High-Resolution 3D Light Microscopy with STED and RESOLFT, the book goes on to cover retinal and anterior segment imaging and image-guided treatment and also discusses the development of adaptive optics in vision science and ophthalmology. Using an interdisciplinary approach, the reader will learn about the latest developments and most up to date technology in the field and how these translate to a medical setting. High Resolution Imaging in Microscopy and Ophthalmology – New Frontiers in Biomedical Optics has been written by leading experts in the field and offers insights on engineering, biology, and medicine, thus being a valuable addition for scientists, engineers, and clinicians with technical and medical interest who would like to understand the equipment, the applications and the medical/biological background. Lastly, this book is dedicated to the memory of Dr. Gerhard Zinser, co-founder of Heidelberg Engineering GmbH, a scientist, a husband, a brother, a colleague, and a friend.

Advances in semi-automated high-throughput image data collection routines, coupled with a decline in storage costs and an increase in high-performance computing solutions have led to an exponential surge in data collected by biomedical scientists and medical practitioners. Interpreting this raw data is a challenging task, and nowhere is this more evident than in the field of opthalmology. The sheer speed at which data on cataracts, diabetic retinopathy, glaucoma and other eye disorders are collected, makes it impossible for the human observer to directly monitor subtle, yet critical details.This book is a novel and well-timed endeavor to present, in an amalgamated format, computational image modeling methods as applied to various extrinsic scientific problems in ophthalmology. It is self-contained and presents a highly comprehensive array of image modeling algorithms and methodologies relevant to ophthalmologic problems. The book is the first of its kind, bringing eye imaging and multi-dimensional hyperspectral imaging and data fusion of the human eye, into focus.The editors are at the top of their fields and bring a strong multidisciplinary synergy to this visionary volume. Their “inverted-pyramid” approach in presenting the content, and focus on core applications, will appeal to students and practitioners in the field.

The two volumes LNCS 10337 and 10338 constitute the proceedings of the International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2017, held in Corunna, Spain, in June 2017. The total of 102 full papers was carefully reviewed and selected from 194 submissions during two rounds of reviewing and improvement. The papers are organized in two volumes, one on natural and artificial computation for biomedicine and neuroscience, addressing topics such as theoretical neural computation; models; natural computing in bioinformatics; physiological computing in affective smart environments; emotions; as well as signal processing and machine learning applied to biomedical and neuroscience applications. The second volume deals with biomedical applications, based on natural and artificial computing and addresses topics such as biomedical applications; mobile brain computer interaction; human robot interaction; deep learning; machine learning applied to big data analysis; computational intelligence in data coding and transmission; and applications.