Computational neuroscience is often referred to as theoretical neuroscience. Neurology, psychiatry, neurosurgery, psychosurgery, anesthesiology and pain Neuroscience is the scientific study of the nervous system (the brain, spinal cord, and peripheral nervous system), its functions, and its disorders. It is a multidisciplinary science that combines physiology, anatomy, molecular biology, developmental biology, cytology, psychology, physics, computer science, chemistry, medicine, statistics, and mathematical modeling to understand the fundamental a Questions in computational neuroscience can span a wide range of levels of traditional analysis, such as development, structure, and cognitive functions of the brain. Research in this field utilizes mathematical models, theoretical analysis, and computer simulation to describe and verify biologically plausible neurons and nervous systems. For example, biological neuron models are mathematical descriptions of spiking neurons which can be used to describe both the behavior of single neurons as well as the dynamics of neural networks. Computational neuroscience is often referred to as theoretical neuroscience. In 1909, German anatomist Korbinian Brodmann published his original research on brain mapping, defining 52 distinct regions of the cerebral cortex, known as Brodmann areas. Modern research through neuroimaging techniques, still uses the Brodmann cerebral cytoarchitectonic map (referring to the study of cell structure) anatomical definitions from this era in continuing to show that distinct areas of the cortex are activated in the execution of specific tasks. During the 20th century, neuroscience began to be recognized as a distinct academic discipline in its own right, rather than as studies of the nervous system within other disciplines. Eric Kandel and collaborators have cited David Rioch, Francis O. Schmitt, and Stephen Kuffler as having played critical roles in establishing the field. Rioch originated the integration of basic anatomical and physiological research with clinical psychiatry at the Walter Reed Army Institute of Research, starting in the 1950s. During the same period, Schmitt established a neuroscience research program within the Biology Department at the Massachusetts Institute of Technology, bringing together biology, chemistry, physics, and mathematics. The first freestanding neuroscience department (then called Psychobiology) was founded in 1964 at the University of California, Irvine by James L. McGaugh. This was followed by the Department of Neurobiology at Harvard Medical School, which was founded in 1966 by Stephen Kuffler. The scientific study of the nervous system increased significantly during the second half of the twentieth century, principally due to advances in molecular biology, electrophysiology, and computational neuroscience. This has allowed neuroscientists to study the nervous system in all its aspects: how it is structured, how it works, how it develops, how it malfunctions, and how it can be changed. Compared to psychiatry and psychology, which also study the functioning of the brain, Neuroscience emerged from the earlier fields of Neuro-Immuno-Modulation and Neuroimmunology, which made remarkable breakthroughs beginning with 1945. For example, it became possible to understand, in much detail, the complex processes occurring within a single neuron. Neurons are cells specialized for communication. They are able to communicate with neurons and other cell types through specialized junctions called synapses, at which electrical or electrochemical signals can be transmitted from one cell to another. Many neurons extrude a long thin filament of axoplasm called an axon, which may extend to distant parts of the body and are capable of rapidly carrying electrical signals, influencing the activity of other neurons, muscles, or glands at their termination points. A nervous system emerges from the assemblage of neurons that are connected to each other in neural circuits, and networks. The vertebrate nervous system can be split into two parts: the central nervous system (defined as the brain and spinal cord), and the peripheral nervous system. In many species—including all vertebrates—the nervous system is the most complex organ system in the body, with most of the complexity residing in the brain. The human brain alone contains around one hundred billion neurons and one hundred trillion synapses; it consists of thousands of distinguishable substructures, connected to each other in synaptic networks whose intricacies have only begun to be unraveled. At least one out of three of the approximately 20,000 genes belonging to the human genome is expressed mainly in the brain. Due to the high degree of plasticity of the human brain, the structure of its synapses and their resulting functions change throughout life. Making sense of the nervous system's dynamic complexity is a formidable research challenge. Ultimately, neuroscientists would like to understand every aspect of the nervous system, including how it works, how it develops, how it malfunctions, and how it can be altered or repaired. Analysis of the nervous system is therefore performed at multiple levels, ranging from the molecular and cellular levels to the systems and cognitive levels. The specific topics that form the main focus of research change Questions in computational neuroscience can span a wide range of levels of traditional analysis, such as development, structure, and cognitive functions of the brain. Research in this field utilizes mathematical models, theoretical analysis, and computer simulation to describe and verify biologically plausible neurons and nervous systems. For example, biological neuron models are mathematical descriptions of spiking neurons which can be used to describe both the behavior of single neurons as well as the dynamics of neural networks. Computational neuroscience is often referred to as theoretical neuroscience.

Despite similar computational approaches, there is surprisingly little interaction between the computational neuroscience and the systems biology research communities. In this review I reconstruct the history of the two disciplines and show that this may explain why they grew up apart. The separation is a pity, as both fields can learn quite a bit from each other. Several examples are given, covering sociological, software technical, and methodological aspects. Systems biology is a better organized community which is very effective at sharing resources, while computational neuroscience has mor