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Encyclopedia > Computational neuroscience

Computational neuroscience is an interdisciplinary science that links the diverse fields of neuroscience, cognitive science, electrical engineering, computer science, physics and mathematics. Historically, the term was introduced by Eric L. Schwartz, who organized a conference, held in 1985 in Carmel, California at the request of the Systems Development Foundation, to provide a summary of the current status of a field which until that point was referred to by a variety of names, such as neural modeling, brain theory and neural networks. The proceedings of this definitional meeting were later published as the book "Computational Neuroscience", MIT Press(1990). The early historical roots of the field can be traced to the work of people such as Hodgkin & Huxley, Hubel & Wiesel, and David Marr, to name but a few. Hodgkin & Huxley developed the voltage clamp and created the first mathematical model of the action potential. Hubel & Wiesel discovered that neurons in primary visual cortex, the first cortical area to process information coming from the retina, have oriented receptive fields and are organized in columns (Hubel & Wiesel, 1962). David Marr's work focused on the interactions between neurons, suggesting computational approaches to the study of how functional groups of neurons within the hippocampus and neocortex interact, store, process, and transmit information. Computational modeling of biophysically realistic neurons and dendrites began with the work of Wilfrid Rall, with the first multicompartmental model using cable theory. Drawing of the cells in the chicken cerebellum by S. Ramón y Cajal Neuroscience is a field that is devoted to the scientific study of the nervous system. ... Cognitive science is usually defined as the scientific study either of mind or of intelligence (e. ... Electrical Engineers design power systems… … and complex electronic circuits. ... Computer science, or computing science, is the study of the theoretical foundations of information and computation and their implementation and application in computer systems. ... A magnet levitating above a high-temperature superconductor demonstrates the Meissner effect. ... For other meanings of mathematics or uses of math and maths, see Mathematics (disambiguation) and Math (disambiguation). ... Sir Alan Lloyd Hodgkin (February 5, 1914 _ December 20, 1998) was a British physiologist and biophysicist, who won the 1963 Nobel Prize in Physiology or Medicine for his work with Andrew Fielding Huxley on the basis of nerve action potentials, the electrical impulses that enable the activity of an... Andrew Huxley at Trinity College, Cambridge, July 2005 Family tree Sir Andrew Fielding Huxley, OM, FRS (born 22 November 1917, Hampstead, London) is an English physiologist and biophysicist, who won the 1963 Nobel Prize in Physiology or Medicine for his work with Alan Lloyd Hodgkin on the basis of nerve... David Hunter Hubel (b. ... Torsten Nils Wiesel (b. ... David Marr (January 19, 1945 - November 17, 1980) was a British psychologist. ... A. A schematic view of an idealized action potential illustrates its various phases as the action potential passes a point on a cell membrane. ... Brodmann area 17 (primary visual cortex) is shown in red in this image which also shows area 18 (orange) and 19 (yellow) The primary visual cortex (usually called V1) is the most well-studied visual area in the brain. ... Human eye cross-sectional view. ... For other uses, see Hippocampus (disambiguation). ... // [edit] Overview Figure. ...


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 neural systems) and their physiology and dynamics. These models capture the essential features of the biological system at multiple spatial-temporal scales, from membrane currents, protein and chemical coupling to network oscillations, columnar and topographic architecture and learning and memory. These computational models are used to test hypotheses that can be directly verified by current or future biological experiments. Connectionism is an approach in the fields of artificial intelligence, cognitive science, neuroscience, psychology and philosophy of mind. ... As a broad subfield of artificial intelligence, machine learning is concerned with the design and development of algorithms and techniques that allow computers to learn. At a general level, there are two types of learning: inductive, and deductive. ... A neural network is an interconnected group of neurons. ... Statistical learning theory is an ambiguous term. ...


Currently, the field is undergoing a rapid expansion. There are many software packages, such as GENESIS and NEURON, that allow rapid and systematic in silico modeling of realistic neurons. Blue Brain, a collaboration between IBM and École Polytechnique Fédérale de Lausanne, aims to construct a biophysically detailed simulation of a cortical column on the Blue Gene supercomputer. GENESIS (The GEneral NEural SImulation System) is a simulation environment for constructing realistic models of neurobiological systems at many levels of scale including subcellular processes, individual neurons, networks of neurons, and neuronal systems. ... NEURON is a simulation environment for modeling individual neurons and networks of neurons. ... Blue Brain is a project to begin the construction of a simulated brain. ... For other uses, see IBM (disambiguation) and Big Blue. ... Location: Polytechnic of Lausanne, in western Switzerland The École Polytechnique Fédérale de Lausanne (EPFL) is the Swiss Federal Institute of Technology in Lausanne, Switzerland. ... This article is about the supercomputer. ... For other uses, see Supercomputer (disambiguation). ...

Contents

Major Topics

Research in computational neuroscience can be roughly categorized into several lines of inquiries. Most computational neuroscientists collaborate closely with experimentalists in analyzing novel data and synthesizing new models of biological phenomena.


Single Neuron Modeling

Main article: Biological neuron models

Even single neurons have complex biophysical characteristics. Hodgkin and Huxley's original model only employed two voltage-sensitive currents, the fast-acting sodium and the inward-rectifying potassium. Though successful in predicting the timing and qualitative features of the action potential, it nevertheless failed to predict a number of important features such as adaptation and shunting. Scientists now believe that there are a wide variety of voltage-sensitive currents, and the implications of the differing dynamics, modulations and sensitivity of these currents is an important topic of computational neuroscience (for reference, see Johnston and Wu, 1994). A biological neuron model is a mathematical description of the properties of nerve cells, or neurons, that is designed to accurately describe and predict biological processes. ... The Hodgkin-Huxley Model is a set of non-linear ordinary differential equations, named after Alan Lloyd Hodgkin and Andrew Huxley, that approximates the electrical characteristics of excitable cells such as neurons and cardiac myocytes. ...


The computational functions of complex dendrites are also under intense investigation. There is a large body of literature regarding how different currents interact with geometric properties of neurons (for reference, see Koch, 1998). In biology, a dendrite is a slender, typically branched projection of a nerve cell, or neuron, which conducts the electrical stimulation received from other cells to the body or soma of the cell from which it projects. ...


Some models are also tracking biochemical pathways at very small scales such as spines or synaptic clefts.


Development, Axonal Patterning and Guidance

How do axons and dendrites form during development? How do axons know where to target and how to reach these targets? How do neurons migrate to the proper position in the central and peripheral systems? How do synapses form? We know from molecular biology that distinct parts of the nervous system release distinct chemical cues, from growth factors to hormones that modulate and influence the growth and development of functional connections between neurons. An axon, or nerve fiber, is a long slender projection of a nerve cell, or neuron, which conducts electrical impulses away from the neurons cell body or soma. ... In biology, a dendrite is a slender, typically branched projection of a nerve cell, or neuron, which conducts the electrical stimulation received from other cells to the body or soma of the cell from which it projects. ... Growth factor is any of about twenty small proteins that attach to specific receptors on the surface of stem cells in bone marrow and promote differentiation and maturation of these cells into morphotic constituents of blood. ... Hormone is also the NATO reporting name for the Soviet/Russian Kamov Ka-25 military helicopter. ...


Theoretical investigations into the formation and patterning of synaptic connection and morphology is still nascent. One hypothesis that has recently garnered some attention is the minimal wiring hypothesis, which postulates that the formation of axons and dendrites effectively minimizes resource allocation while maintaining maximal information storage. (for a review, see Chklovskii, 2004)


Sensory processing

Early models of sensory processing understood within a theoretical framework is credited to Horace Barlow. Somewhat similar to the minimal wiring hypothesis described in the preceding section, Barlow understood the processing of the early sensory systems to be a form of efficient coding, where the neurons encoded information which minimized the number of spikes. Experimental and computational work have since supported this hypothesis in one form or another. Professor Horace Basil Barlow FRS (born December 8, 1921) is a British visual neuroscientist. ... The efficient coding hypothesis was proposed by Horace Barlow in 1961 as a theoretical model of sensory coding in the brain. ...


Current research in sensory processing is divided among biophysical modelling of different subsystems and more theoretical modelling function of perception. Current models of perception have suggested that the brain performs some form of Bayesian inference and integration of different sensory information in generating our perception of the physical world. Bayesian inference is statistical inference in which evidence or observations are used to update or to newly infer the probability that a hypothesis may be true. ...


Memory and synaptic plasticity

Main article: Synaptic plasticity

Earlier models of memory are primarily based on the postulates of Hebbian learning. Biologically relevant models such as Hopfield net have been developed to address the properties of associative, rather than content-addressable style of memory that occur in biological systems. These attempts are primarily focusing on the formation of medium-term and long-term memory, localizing in the hippocampus. Models of working memory, relying on theories of network oscillations and persistent activity, have been built to capture some features of the prefrontal cortex in context-related memory. (For review, see Durstewitz et al, 2000) In neuroscience, synaptic plasticity is the ability of the connection, or synapse, between two neurons to change in strength. ... Hebbian learning is a hypothesis for how neuronal connections are enforced in mammalian brains; it is also a technique for weight selection in artificial neural networks. ... A Hopfield net is a form of recurrent artificial neural network invented by John Hopfield. ...


One of the major problems in biological memory is how it is maintained and changed through multiple time scales. Unstable synapses are easy to train but also prone to stochastic disruption. Stable synapses forget less easily, but they are also harder to consolidate. One recent computational hypothesis involves cascades of plasticity (Fusi et al, 2005) that allow synapses to function at multiple time scales. Stereochemically detailed models of the acetylcholine receptor-based synapse with Monte Carlo method, working at the time scale of microseconds, have been built (Coggan et al, 2005). It is likely that computational tools will contribute greatly to our understanding of how synapses function and change in relation to external stimulus in the coming decades. Synapses allow nerve cells to communicate with one another through axons and dendrites, converting electrical signals into chemical ones. ... Synapses allow nerve cells to communicate with one another through axons and dendrites, converting electrical signals into chemical ones. ... An acetylcholine receptor (abbreviated AChR) is an integral membrane protein that responds to the binding of the neurotransmitter acetylcholine. ... Monte Carlo methods are a widely used class of computational algorithms for simulating the behavior of various physical and mathematical systems, and for other computations. ...


Behaviors of Networks

Biological neurons are connected to each other in a complex, recurrent fashion. These connections are, unlike most artificial neural networks, sparse and most likely, specific. It is not known how information is transmitted through such sparsely connected networks. It is also unknown what the computational functions, if any, of these specific connectivity patterns are. A neural network is an interconnected group of neurons. ...


The interactions of neurons in a small network can be often reduced to simple models such as the Ising model. The statistical mechanics of such simple systems are well-characterized theoretically. There have been some recent evidence that suggests that dynamics of arbitrary neuronal networks can be reduced to pairwise interactions (Schneidman et al, 2006; Shlens et al, 2006.) It's unknown, however, whether such descriptive dynamics impart any important computational function. With the emergence of two-photon microscopy and calcium imaging, we now have powerful experimental methods with which to test the new theories regarding neuronal networks. The Ising model, named after the physicist Ernst Ising, is a mathematical model in statistical mechanics. ... Statistical mechanics is the application of probability theory, which includes mathematical tools for dealing with large populations, to the field of mechanics, which is concerned with the motion of particles or objects when subjected to a force. ... Two-photon excitation microscopy is a technique that allows imaging living tissue up to a depth of one millimeter. ... There are very few or no other articles that link to this one. ...


While many neuro-theorists prefer models with reduced complexity, others argue that uncovering structure function relations depends on including as much neuronal and network structure as possible. Models of this type are typically built in large simulations platforms like GENESIS_(software) or Neuron_(software). There have been some attempts to provide unified methods that bridge, and integrate, these levels of complexity (Eliasmith & Anderson, 2003). GENESIS (The GEneral NEural SImulation System) is a simulation environment for constructing realistic models of neurobiological systems at many levels of scale including subcellular processes, individual neurons, networks of neurons, and neuronal systems. ... NEURON is a simulation environment for modeling individual neurons and networks of neurons. ...


Cognition, Discrimination and Learning

Computational modeling of higher cognitive functions has only begun recently. Experimental data comes primarily from single unit recording in primates. The frontal lobe and parietal lobe function as integrators of information from multiple sensory modalities. There are some tentative ideas regarding how simple mutually inhibitory functional circuits in these areas may carry out biologically relevant computation (Machens et al, 2005). Single unit recording refers to the use of an electrode to record the electrophysiological activity (action potentials) from a single neuron. ... For the ecclesiastical use of this term, see primate (religion) Families 13, See classification A primate is any member of the biological order Primates, the group that contains all lemurs, monkeys, and apes, including humans. ... The frontal lobe is an area in the brain of mammals. ... The parietal lobe is a lobe in the brain. ...


The brain seems to be able to discriminate and adapt particularly well in certain contexts. For instance, human beings seem to have an enormous capacity for memorizing and recognizing faces. One of the key goals of computational neuroscience is to dissect how biological systems carry out these complex computations efficiently and potentially replicate these processes in building intelligent machines. Human brain In animals, the brain (enkephale) (Greek for in the skull), is the control center of the central nervous system, responsible for behavior. ...


Consciousness

The ultimate goal of neuroscience is to be able to explain the every day experience of conscious life. Francis Crick and Christof Koch made some attempts in formulating a consistent framework for future work in neural correlates of consciousness (NCC), though much of the work in this field remains speculative. (for a review, see Koch and Crick, 2003). Another attemt is done by Andrew & Alexander Fingelkurts: they are developing the Operational Architectonics theory of brain-mind functioning. This theory treats consciousness as a biological phenomenon in the brain which is realized by the highly organized macro-level electrophysiological (EEG) phenomena (metastable operational modules), which are brought to existence by the coordinated electrical activity (operational synchrony) of many neuronal populations dispersed throughout the brain (for a review see Fingelkurts An.A. and Fingelkurts Al.A., 2001; 2004; 2006). Francis Harry Compton Crick OM FRS (8 June 1916 – 28 July 2004) was an English molecular biologist, physicist, and neuroscientist, who is most noted for being one of the co-discoverers of the structure of the DNA molecule in 1953. ... Christof Koch (born November 13, 1956) is an American neuroscientist. ... A neural correlate of a content of experience is any bodily component, such as an electroneurobiological state or the state assumed by some biophysical subsystem of the brain, whose presence necessarily and regularly correlates with such a specific content of experience. ...


See also

Connectionism is an approach in the fields of artificial intelligence, cognitive science, neuroscience, psychology and philosophy of mind. ... // Traditionally, the term neural network had been used to refer to a network or circuitry of biological neurons. ... A biological neuron model is a mathematical description of the properties of nerve cells, or neurons, that is designed to accurately describe and predict biological processes. ... Current Clamp is a common technique in electrophysiology. ... To meet Wikipedias quality standards, this article or section may require cleanup. ... // A brain-computer interface (BCI), sometimes called a direct neural interface or a brain-machine interface, is a direct communication pathway between a human or animal brain (or brain cell culture) and an external device. ... It has been suggested that Neuro cybernetics be merged into this article or section. ... Neurotechnology is the set of tools that analyze and influence the human nervous system, especially the brain. ... It has been suggested that this article or section be merged with Computational neuroscience. ... Computational Neurogenetic Modeling (CNGM) is concerned with the study and development of dynamic neuronal models for modeling brain functions with respect to genes and dynamic interactions between genes. ...

References

  • Chklovskii, DB (2004) "Synaptic connectivity and neuronal morphology: two sides of the same coin", Neuron. 43(5):609-17
  • Churchland, P. S. & T. J. Sejnowski (1992) The Computational Brain, MIT Press, ISBN 0-262-03188-4.
  • Eliasmith, C & C.H. Anderson (2003). Neural Engineering: Computation, Representation, and Dynamics in Neurobiological Systems MIT Press, ISBN 0-262-55060-1.
  • Coggan JS, Bartol TM, Esquenazi E et al, "Evidence for ectopic neurotransmission at a neuronal synapse.", Science.,2005 Jul 15;309(5733):446-51
  • Peter Dayan, L.F. Abbott: Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems, MIT Press, 2001, ISBN 0-262-04199-5.
  • Durstewitz D, Seamans JK, Sejnowski TJ., (2000) "Neurocomputational models of working memory.", Nat Neurosci. 2000 Nov; Suppl:1184-91.
  • Fingelkurts An.A. and Fingelkurts Al.A., (2001) "Operational architectonics of the human brain biopotential field: towards solving the mind-brain problem." Brain and Mind 2:261–296
  • Fingelkurts An.A. and Fingelkurts Al.A., (2004) "Making complexity simpler: multivariability and metastability in the Brain." Int. J. Neurosci., vol. 114, pp. 843-862
  • Fingelkurts An.A. and Fingelkurts Al.A., (2006) "Timing in cognition and EEG brain dynamics: discreteness versus continuity." Cognitive Proces., vol. 7, pp. 135-162
  • Fusi S, Drew PJ, Abbott LF., "Cascade models of synaptically stored memories", Neuron. 2005 Feb 17;45(4):599-611
  • Johnston D and Wu SM, Foundations of Cellular Neurophysiology, MIT Press, 1994, ISBN 0-262-10053-3.
  • Hodgkin, A. L. and Huxley, A. F. (1952) "A Quantitative Description of Membrane Current and its Application to Conduction and Excitation in Nerve" Journal of Physiology 117:500-544
  • Hubel DH, Wiesel TN (1962) "Receptive fields, binocular interaction and functional architecture in the cat's visual cortex" Journal of Physiology 160:106-154.
  • Koch C Biophysics of Computation: Information Processing in Single Neurons, Oxford University Press, 1998, ISBN 0-19-510491-9.
  • Koch, C and Crick, F (2003) "A framework for consciousness", Nat Neurosci. 2003 Feb;6(2):119-26.
  • Machens CK, Romo R, Brody CD. (2005) "Flexible control of mutual inhibition: a neural model of two-interval discrimination.", Science. 2005 Feb 18;307(5712):1121-4.
  • F. Rieke, D. Warland, W. Bialek and R. de Ruyter van Steveninck: Spikes: Exploring the Neural Code, MIT Press, 1999, ISBN 0-262-68108-0.
  • Schneidman E, Berry MJ 2nd, Segev R, Bialek W. (2006) "Weak pairwise correlations imply strongly correlated network states in a neural population.", Nature. 2006 Apr 20;440(7087):1007-12.
  • Eric L. Schwartz, ed.: Computational Neuroscience, MIT Press, 1990, ISBN 0-262-19291-8.
  • Erik de Schutter, ed.: Computational Neuroscience - Realistic Modeling for Experimentalists, CRC Press, 2000, ISBN 0-8493-2068-2.
  • J. L.. van Hemmen, T. J. Sejnowski, eds.: 23 Problems in Systems Neuroscience Oxford University Press, 2005 ISBN 0-19-514822-3.

MIT Press Books The MIT Press is a university publisher affiliated with the Massachusetts Institute of Technology (MIT) in Cambridge, Massachusetts. ... MIT Press Books The MIT Press is a university publisher affiliated with the Massachusetts Institute of Technology (MIT) in Cambridge, Massachusetts. ... MIT Press Books The MIT Press is a university publisher affiliated with the Massachusetts Institute of Technology (MIT) in Cambridge, Massachusetts. ... MIT Press Books The MIT Press is a university publisher affiliated with the Massachusetts Institute of Technology (MIT) in Cambridge, Massachusetts. ... Oxford University Press (OUP) is a highly-respected publishing house and a department of the University of Oxford in England. ... MIT Press Books The MIT Press is a university publisher affiliated with the Massachusetts Institute of Technology (MIT) in Cambridge, Massachusetts. ... MIT Press Books The MIT Press is a university publisher affiliated with the Massachusetts Institute of Technology (MIT) in Cambridge, Massachusetts. ... The CRC Press, LLC is a publishing group which specializes in producing technical books in a wide range of subjects. ... Oxford University Press (OUP) is a highly-respected publishing house and a department of the University of Oxford in England. ...

External links

Journals

Software

  • Genesis, a general neural simulation system
  • Neuron, a neural network simulator
  • NEST, a simulation tool for large neuronal systems.
  • Neuroconstruct, software for developing biologically realistic 3D neural networks.
  • Neurofitter, a parameter tuning package for electrophysiological neuron models.
  • Neurojet, a neural network simulator specialized for the hippocampus
  • HHsim, a neuronal membrane simulator
  • MCell, A Monte Carlo Simulator of Cellular Microphysiology
  • Emergent, neural simulation software
  • Python tools : http://neuralensemble.org/
    • pyNN

Emergent (formerly PDP++) is neural simulation software that is primarily intended for creating complex, sophisticated models of the brain and cognitive processes, but can also be used for any task to which neural networks are suited. ...

Conferences

  • Computational and Systems Neuroscience (COSYNE) - a computational neuroscience meeting with a systems neuroscience focus.
  • Annual Computational Neuroscience Meeting (CNS) - a yearly computational neuroscience meeting.
  • Neural Information Processing Systems (NIPS) - a leading annual conference covering other machine learning topics as well.
  • Computational Cognitive Neuroscience Conference (CCNC) - a yearly conference.
  • International Conference on Cognitive Neurodynamics (ICCN) - a yearly conference.

Websites

  • Neurosecurity, Articles and lectures on Computational neuroscience.
  • Perlewitz's computational neuroscience on the web
  • compneuro.org, books and programs for neural modeling
  • Encyclopedia of Computational Neuroscience, part of Scholarpedia, an online expert curated encyclopedia on computational neuroscience, dynamical systems and machine intelligence
  • NeuroWiki, a wiki discussion forum about neuroscience research, especially systems, theoretical/computational, and cognitive neuroscience

Scholarpedia is an online wiki-based encyclopedia in which articles are written by invited expert authors and are subject to peer review. ...

Courses

  • NeuroWiki:CompNeuroCourses, a list of comp neuro courses with material available online
  • http://www.mbl.edu/education/courses/special_topics/mcn.html Summer course at the MBL, which features major figures in the field (Abbott, Bialek, Sejnowski, et.al.) as guest faculty.

Research Groups

  • Bernstein Centers for Computational Neuroscience Germany
  • Bernstein Center for Computational Neuroscience Berlin
  • Bernstein Center for Computational Neuroscience Freiburg
  • Bernstein Center for Computational Neuroscience Goettingen
  • Bernstein Center for Computational Neuroscience Munich
  • BM-Science - Brain & Mind Technologies Research Centre, Finland
  • Neuroengineering Laboratory at the University of Pennsylvania
  • Computational Neuroscience Group at the KFKI RIPNP of the Hungarian Academy of Sciences
  • Computational Neurobiology Laboratory at the Salk Institute (CNL)
  • Centre for Theoretical Neuroscience (CTN) at the University of Waterloo
  • MIT Media Lab, Neuroengineering and Neuromedia Group
  • Institute for Theoretical Biology, Humboldt-Universitaet zu Berlin
  • Computational Neuroscience Group at King's College London
  • MIT Center for Biological & Computational Learning (CBCL)
  • Center for Theoretical Neuroscience at Columbia University
  • Interdisciplinary Center for Neural Computation at Hebrew University
  • Gatsby Computational Neuroscience Unit at University College London
  • Martinos Computational Neuroscience Center for integrating neuroimaging and computational neuroscience
  • Georgetown Laboratory for Computational Cognitive Neuroscience
  • Hertie Center for Clinical Brain Research, Laboratory for Action Representation and Learning
  • Computational Neuroscience Lab, University of Queensland
  • Computational Cognitive Neuroscience Lab, University of Colorado at Boulder
  • Theoretical Neuroscience Group, Florida Atlantic University
  • Centre for Cognitive Neuroscience and Cognitive Systems at the University of Kent
  • Computational Neuroscience Engineering Lab, University of Florida
  • Institute for Adaptive and Neural Computation, University of Edinburgh
  • Centre for Theoretical and Computational Neuroscience, University of Plymouth
  • Theoretical Neurobiology Lab, University of Antwerp
  • Computational Neuroscience Unit, Okinawa Institute of Science and Technology

Papers

  • Review - Sejnowski, T. J.; Koch, C.; Churchland, P. S.; Computational Neuroscience, Science, 241, 1299-1306, 1988
  • A Theory of Object Recognition: Computations and Circuits in the Feedforward Path of the Ventral Stream in Primate Visual Cortex - Biologically-based vision algorithm

Neuroscience subfields: Drawing of the cells in the chicken cerebellum by S. Ramón y Cajal Neuroscience is a field that is devoted to the scientific study of the nervous system. ...

Behavioral Neurology | Biological Psychology | Cognitive Neuroscience | Cognitive Psychophysiology | Computational Neuroscience | Molecular Cellular Cognition | Neural Engineering | Neuroanatomy | Neurobiology | Neurochemistry | Neuroendocrinology | Neuroimaging | Neurolinguistics | Neurology | Neuromonitoring | Neuropharmacology | Neurophysiology | Neuropsychology | Neuropsychiatry | Neurosurgery | Psychiatry | Psychobiology | Psychopharmacology | Psychophysiology | Systems Neuroscience

Psychology subfields: Behavioral neurology is a subspecialty of neurology that studies the neurological basis of behavior, memory, and cognition, the impact of neurological damage and disease upon these functions, and the treatment thereof. ... means basic pussy and the dick In psychology, biological psychology or psychobiology[1] is the application of the principles of biology to the study of mental processes and behavior. ... The field of cognitive neuroscience concerns the scientific study of the neural mechanisms underlying cognition and is a branch of neuroscience. ... This article does not cite any references or sources. ... Computational neuroscience is an interdisciplinary science that links the diverse fields of neuroscience, cognitive science, electrical engineering, computer science, physics and mathematics. ... Key goals of studies in the field of molecular cellular cognition (MCC) include the derivation of explanations of cognitive processes that integrate molecular, cellular, and behavioral mechanisms, and finding mechanism and treatments for cognitive disorders. ... It has been suggested that Neuro cybernetics be merged into this article or section. ... Neuroanatomy is the anatomy of the nervous system. ... Neurobiology is the study of cells of the nervous system and the organization of these cells into functional circuits that process information and mediate behavior. ... Neurochemistry is a branch of neuroscience that is heavily devoted to the study of neurochemicals. ... Neuroendocrinology is the study of the interactions between the nervous system and the endocrine system. ... It has been suggested that this article or section be merged with functional neuroimaging. ... Neurolinguistics is the science concerned with the human brain mechanisms underlying the comprehension, production, and abstract knowledge of language, be it spoken, signed, or written. ... Neurology is a branch of medicine dealing with disorders of the nervous system. ... The scientific practice of neuromonitoring takes place in the surgical suite (OR). ... Neuropharmacology is the branch of health science concerned with the study of drugs on the nervous system. ... Neurophysiology is a part of physiology as a science, which is concerned with the study of the nervous system. ... Neuropsychology is a branch of psychology and neurology that aims to understand how the structure and function of the brain relate to specific psychological processes and overt behaviors. ... Neuropsychiatry is the branch of medicine dealing with mental disorders attributable to diseases of the nervous system. ... Insertion of an electrode during neurosurgery for Parkinsons disease. ... An MRI scan of a human brain and head. ... This article or section should be merged with biological psychology Psychobiology, also called biopsychology, is the scientific study of mental functioning and behavior in relation to other biological processes, or put another way, of the effects of cognition, emotions, and experience on animal physiology. ... Psychopharmacology is the study of the effects of any psychoactive drug that acts upon the mind by affecting brain chemistry. ... This article does not cite any references or sources. ... Systems neuroscience is a subdicipline of neuroscience which studies the neural circuit function, most commonly in awake, behaving intact organisms. ... Psychological science redirects here. ...

Behavioral Neurology | Cognitive Psychology | Cognitive Neuroscience | Biological Psychology | Neuroimaging | Psycholinguistics | Psychophysics | Psychophysiology | Neuropsychology | Neuropsychiatry | Psychopharmacology | Systems Neuroscience | Mathematical Psychology | Developmental Psychology | Social Psychology | Clinical Psychology | Evolutionary Psychology | Forensic Psychology

  Results from FactBites:
 
Computational neuroscience - Wikipedia, the free encyclopedia (1623 words)
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.
The Committee on Computational Neuroscience (1116 words)
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.
  More results at FactBites »

 
 

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