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	Computational neuroscience - Wikipedia, the free encyclopedia
		Computational Neuroscience is an interdisciplinary science that links the diverse fields of neuroscience, computer science, physics and applied mathematics together.
		Computational neuroscience traces its historical roots to the the work of people such as Andrew Huxley, Alan Hodgkin, and David Marr.
		Computational neuroscience is distinct from psychological connectionism and theories of learning from disciplines such as machine learning,neural networks and statistical learning theory in that it emphasizes descriptions of functional and biologically realistic neurons and their physiology and dynamics.
	en.wikipedia.org /wiki/Computational_neuroscience (1623 words)

	The Committee on Computational Neuroscience
		This tradition is continued in the Committee on Computational Neuroscience, which draws on faculty from many departments in all four graduate divisions in the University to create a multidisciplinary program in neuroscience.
		Computational neuroscience is a relatively new area of inquiry that is concerned with how components of animal and human nervous systems interact to produce behaviors.
		Computational neuroscience is inherently interdisciplinary, and most students doing graduate work in this area will have strengths in one of the relevant areas and weaknesses in others.
	catalogs.uchicago.edu /divisions/compneuro.html (1116 words)

	Computational Neuroscience Research in the Computer Science Department at Carnegie Mellon
		As an interdisciplinary field, computational neuroscience is closely aligned with computer science in that it goes beyond applying computational techniques to biology but is in fact focused on the study of the computational principles of the brain itself.
		Computational neuroscience research in CSD is distinguished by three key traits: (1) principled approaches with an emphasis on computational theory, (2) rigorous investigation of real neural phenomena and/or implementation of real computational systems, and (3) synergistic integration with robotics, AI and computer science research.
		Computational neuroscience research in CSD is no exception; indeed, it is distinguished by its close contact with contemporary robotics and computer vision research efforts.
	www.csd.cs.cmu.edu /research/areas/compneuro (1077 words)

	The semantic challenge to computational neuroscience.
		Computers running the right software can be used to simulate a vast range of phenomena, from the antics of sub-atomic particles within a nucleus to the ways in which minor variations in conditions just following big bang might effect the distribution of matter throughout the universe.
		In effect, every question that cognitive neuroscience ought to be able to answer if in fact it is the physical structure of the brain that explains thought, cognition, imagination, perception, etc., will turn out to be a question beyond the reach of cognitive neuroscience and computational neuroscience.
		Given that computers are general purpose (one may need to make idealizations about amount of memory here, of course), meaning that they can execute any computable function, having a computable function is sufficient for being able to implement it in a general purpose computer.
	mind.ucsd.edu /papers/semantic_challenge/sem_neuro.html (6169 words)

	computational neuroscience
		Computational neuroscience provides theoretical and computational tools that transcend many different levels of organization.
		Its approach is expanding into conventional neuroscience laboratories as the need for comprehensive analysis and interpretation of complex experimental data becomes increasingly difficult and important.
		The main goal of the computational neuroscience work in the McGovern Institute is to develop theories of higher brain functions that can be used as powerful tools to summarize existing data from system physiology and imaging, to interpret new results, and to plan new experiments in close collaboration with other experimental groups in the Institute.
	web.mit.edu /mcgovern/html/Areas_of_Research/computational_neuroscience.shtml (435 words)

	CMU SCS - Computational Neuroscience Research and Education
		Today, faculty in computer science, robotics, computational and statistical learning, statistics, and psychology are applying multidisciplinary and interdisciplinary techniques to study the computational principles and neural basis of perception, language, cognition, behavior and natural intelligence.
		Faculty in the School of Computer Science are engaged in a wide range of cross-disciplinary research activities in computational neuroscience in four major research centers: (1) Center for the Neural Basis of Cognition (CNBC), (2) Robotics Institute, (3) Center for Cognitive Brain Imaging (CCBI), and (4) Pittsburgh Supercomputing Center (PSC).
		He is interested in the computational principles and neural basis of learning and adaptation, and the nature of hierarchical computation in the visual systems.
	www.cnbc.cmu.edu /~tai/csd-cn.html (780 words)

	Gatsby Unit \| Research (Site not responding. Last check: 2007-11-03)
		In neuroscience, we have particular interests in plasticity, neuromodulation, population coding and neural dynamics; applied to the fields of audition, control/action selection, and vision.
		Starting from a computational analysis of appetitive conditioning, which suggests that the phasic release of dopamine reports a (temporal difference) prediction error for summed future reward, we are extending our studies to consider attentional aspects of dopamine and opponency between serotonin and dopamine.
		We study the organisational and computational principles that lie behind physiological, anatomical, and psychophysical observations in biological vision.
	www.gatsby.ucl.ac.uk /research.html (1119 words)

	MBB Harvard Undergraduates - Computational Neuroscience Track (Site not responding. Last check: 2007-11-03)
		Computational neuroscience attempts to understand mental abilities -- such as perception, language, motor control, and learning -- by designing artificial systems with similar capabilities.
		The theories developed in computational neuroscience are often motivated by findings about biological systems and, in turn, they provide theoretical models for psychologists and biologists to investigate.
		Computational neuroscience is interdisciplinary and there is a growing, and very exciting, interaction between it and cognitive neuroscience.
	mbb.harvard.edu /track_computer_science.html (242 words)

	systems and computational neuroscience
		Systems and computational neuroscience involve the study of information processing within circuits of neurons in the brain using experimental and computational techniques.
		Computational neuroscience provides tools, under the form of quantitative models, to summarize the increasing wealth of complex physiological data, interpret and analyze them, and plan new experiments.
		At the McGovern Institute, the combination of systems and computational neuroscience will represent an integrative focus for framing well-defined questions about higher neural functions and for experimental investigation of these questions.
	web.mit.edu /mcgovern/html/Areas_of_Research/systems_comp_neuro.shtml (298 words)

	Computational Neuroscience at WSU (Site not responding. Last check: 2007-11-03)
		Computational neuroscience links the information processing features of the brain and nervous system with the information processing systems of computer hardware and software.
		Courses in computer science and engineering are selected to provide as broad an exposure as possible to subjects that underlie the basic neural and computational sciences.
		A bachelor’s degree in computational neuroscience uniquely prepares graduates to enter the rapidly growing industries of software and computer design, biotechnology, and pharmaceuticals, where much research is devoted to neurodegenerative diseases.
	academics.wsu.edu /fields/study.asp?ID=CP_NS (850 words)

	nsf.gov - Funding - Collaborative Research in Computational Neuroscience - US National Science Foundation (NSF) (Site not responding. Last check: 2007-11-03)
		Computational neuroscience provides a theoretical foundation and set of technological approaches that may enhance our understanding of nervous system function by providing analytical and modeling tools that describe, traverse and integrate different levels of organization, spanning vast temporal and spatial scales and levels of abstraction.
		Computational approaches are needed in the study of neuroscience as the requirement for comprehensive analysis and interpretation of complex data sets becomes increasingly important.
		Computational understanding of the nervous system may also have a significant impact on the theory and design of engineered systems.
	www.nsf.gov /funding/pgm_summ.jsp?pims_id=5147 (279 words)

	RFA-DA-06-010: Training in Computational Neuroscience: From Biology to Model and Back Again (T90)
		The Neuroscience Blueprint (http://neuroscienceblueprint.nih.gov/) is a collaboration among 16 NIH institutes and centers (http://neuroscienceblueprint.nih.gov/participating.html) that was established to create and support cooperative activities with broad impact in neuroscience.
		Computational neuroscience provides a theoretical foundation and set of technological approaches to meet these challenges and offers significant opportunities to investigate nervous system function across a range of scales: parts of cells, networks, whole brain function, and behavior.
		This individual should be an established researcher with acknowledged accomplishments in computational neuroscience or a related area, and in neuroscience training, and should be capable of providing both administrative and scientific leadership to the development and implementation of the proposed program.
	grants.nih.gov /grants/guide/rfa-files/RFA-DA-06-010.html (14164 words)

	[No title]
		The 2nd Annual Computational Cognitive Neuroscience Conference (CCNC) will be held the two days prior to the 2006 Psychonomic Society Conference, Houston, and in subsequent years on a rotating basis with other meetings.
		The emerging field of Computational Cognitive Neuroscience (CCN) is ideally suited to help fill this need through the use of mathematical analysis and explicit computational models that bridge the gap between biological mechanisms and cognitive function.
		This meeting focuses on research at the intersection of neuroscience, cognitive psychology, and computational modeling, where neuroscience-based computational models are used to simulate and understand cognitive functions such as perception, attention, learning and memory, language, and higher-level cognitive functions.
	www.ccnconference.org (274 words)

	CMU SCS - Computational Biology and Neuroscience Research
		Faculty in the School of Computer Science are engaged in a wide range of cross-disciplinary research activity in computational biology and computational neuroscience.
		The newer generation of CS faculty, fostered by the Center for the Neural Basis of Cognition, are exploring the use of physiological techniques (electrophysiological and functional imaging) and statistical learning theories to connect the computational study of brain function to neural processes in the brain.
		Undergraduate and graduate SCS students are eligible for the Merck fellowship in Computational Biology and Chemistry in the Mellon Collge of Science.
	www.cnbc.cmu.edu /~tai/csd-bio.htm (511 words)

	CSHL - Swartz Foundation Establishes Computational Neuroscience Center
		In a landmark move to expand the understanding of the brain, the Swartz Foundation is establishing a research initiative at Cold Spring Harbor Laboratory, creating a Swartz Center for Computational Neuroscience (SCCN) at the Long Island-based facility.
		The new Center at CSHL will also bring together senior neuroscience faculty — many, leaders in that field — to direct research in system neurobiology and computational neuroscience.
		Through a “virtual neuroscience centers” approach, we are creating a sophisticated interdisciplinary strategy to resolve issues of integrated brain functioning.
	www.cshl.edu /public/releases/swartz.html (597 words)

	Computational Neuroscience Undergraduate Curriculum (Site not responding. Last check: 2007-11-03)
		Computational Neuroscience links the information processing features of the nervous system with information processing of computer systems.
		Furthermore, the program is designed to allow students to acquire breadth in computational subjects or, alternatively, to focus on either software or hardware aspects of computation.
		Students choosing to acquire breadth in computational subjects will be well prepared for graduate study in most areas of neural and biomedical science, including bioengineering.
	www.vetmed.wsu.edu /depts-vcapp/neurosci/comp_neuro_curriculum.asp (710 words)

	Computational Neuroscience of Vision (Site not responding. Last check: 2007-11-03)
		The Computational Neuroscience of Vision focuses on the visual information processing and computational operations in the visual system that lead to representations of objects in the brain.
		Chapter 8 describes different computational approaches to the recognition of objects, and then develops a computational approach to understanding how the visual system actually forms representations of objects.
		In addition to purely visual processing, Computational Neuroscience of Vision also considers how visual inputs reach and are involved in the computations underlying a range of behaviours, including short-term memory, long-term memory, emotion and motivation, and the initiation of action.
	www.cns.ox.ac.uk /b6_text.html (246 words)

	Amazon.ca: Fundamentals of Computational Neuroscience: Books: Thomas Trappenberg (Site not responding. Last check: 2007-11-03)
		Computational neuroscience is the theoretical study of the brain to uncover the principles and mechanisms that guide the development, organization, information processing, and mental functions of the nervous system.
		Although not a new area, it is only recently that enough knowledge has been gathered to establish computational neuroscience as a scientific discipline in its own right.
		It introduces the theoretical foundations of neuroscience with a focus on the nature of information processing in the brain.
	www.amazon.ca /Fundamentals-Computational-Neuroscience-Thomas-Trappenberg/dp/0198515839 (437 words)

	BMBF: Bernstein Centers for Computational Neuroscience
		The central aim of Computational Neuroscience is to identify the neuronal basis of brain performance, from the processing of complex sensory stimuli to learning processes and calling up stored information, as well as the planning and precise coordination of behaviour-relevant movement patterns.
		With its funding measure "National Network for Computational Neuroscience", the Federal Ministry of Education and Science (BMBF) provides funding for this field of research and has founded four "Centres for Computational Neuroscience".
		The National Network for Computational Neuroscience is the central funding measure under the lead vision entitled "Understanding Thought".
	www.bernstein-zentren.de /en/index.php (743 words)

	CNS Course on Computational Neuroscience 2004
		The course is intended to provide graduate students and young researchers from all parts of neuroscience with working knowledge of theoretical and computational methods in neuroscience and to acquaint them with recent developments in this field.
		The speakers provide an overview on important aspects and recent developments in their fields of expertise by means of three-hour tutorials.
		It combines lecturing with an active interaction with the main ideas of the topical fields in a way which has proven efficient given the time constraints of the course.
	www.chaos.gwdg.de /CNS-course (187 words)

	2006 CSHL course on Computational Neuroscience: Vision (Site not responding. Last check: 2007-11-03)
		Computational approaches to neuroscience will produce important advances in our understanding of neural processing.
		The theme of the course is that an understanding of the computational problems, the constraints on solutions to these problems, and the range of possible solutions can help guide research in neuroscience.
		Through a combination of lectures and hands-on experience in a computer laboratory, this intensive course will examine color vision, spatial pattern analysis, motion analysis, oculomotor function, attention, and decision-making.
	meetings.cshl.edu /courses/c-visi06.shtml (168 words)

	Information for Introduction to Computational Neuroscience
		Introduction to Computational Neuroscience is being offered Spring 2004 as both MATH 490N and BIOL 595N.
		The course grade will be based on a midterm exam, a final exam, homework assignments that include computation using the packages Neuron and XPPAUT, and a group report on a published model (chosen by the group members) that was not covered in the lectures.
		It is expected that students will gain an appreciation for the kinds of information that mathematical and computational approaches can add to understanding the functioning of a neural system, for example, to realize that some systems are inherently more sensitive to changes in the input parameters than others.
	www.math.purdue.edu /~cowen/CompNeuro.html (1242 words)

	Computational Vision: Research Links
		Computer Vision and Pattern Recognition): 1996 / 1997 / 1998 / 1999 / 2000 / 2001 / 2003 / 2004 / 2005 / 2006 / 2007
		Computational Neuroscience: Vision A 2-week course held every other summer since 1987 at Cold Spring Harbor Labs.
		Methods in Computational Neuroscience: Annual summer course at the Woods Hole Oceanographic Institute, MA.
	www.cns.nyu.edu /~eero/vision-links.html (559 words)

	Amazon.com: The Computational Brain (Computational Neuroscience): Books: Patricia Churchland,Terrence J. Sejnowski (Site not responding. Last check: 2007-11-03)
		Churchland and Sejnowski address the foundational ideas of the emerging field of computational neuroscience, examine a diverse range of neural network models, and consider future directions of the field.
		This book can be viewed as one of the first attempts to use results from psychology, neuroscience, computer science, and philosophy with the intent of gaining an understanding of how the mind/brain works, but all of this is done within the "computational mind" paradigm.
		For students of neuroscience, computer science and psychology this book is extremely important, because it gives you the necessary fundamentals of this field(namely computational neuroscience) so you can get to more advanced levels easily.
	www.amazon.com /exec/obidos/tg/detail/-/0262531208?v=glance (1648 words)

	Courses in the Committee on Computational Neuroscience
		This three quarter sequence brings together the concepts from the neuroscience theme with the quantitative methods from the mathematical theme to discuss current issues in computational neuroscience.
		This course briefly reviews the historical development of computational neuroscience and discusses the functional properties of individual neurons.
		It discusses the basic anatomy and physiology of the retina and central visual pathways, and then examines computational approaches to vision based on linear and non-linear systems theory, and algorithms derived from computer vision.
	catalogs.uchicago.edu /divisions/compneuro-courses.html (514 words)

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