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85 relations: Aging movement control, Artificial neural network, Axon, Barbara Shinn-Cunningham, Binding problem, Binocular neurons, Brain code, Bursting, Capsule neural network, Code, Coding theory, Compartmental modelling of dendrites, Compressed sensing, Computational neuroscience, Connectome, Cortical implant, Deep learning, Efficient coding hypothesis, Ephaptic coupling, Feature learning, Gain-field encoding, Gamma distribution, Grandmother cell, H1 neuron, Hierarchical temporal memory, Hippocampal replay, Inferior colliculus, Infographic, John O'Keefe (neuroscientist), Lateral line, Machine learning, Matrix norm, Maximally informative dimensions, Michale Fee, MLPACK (C++ library), Models of neural computation, Motor unit, Multielectrode array, Muscle weakness, Musical semantics, Neural binding, Neural circuit, Neural clique, Neural coding, Neural correlate, Neural decoding, Neural engineering, Neural ensemble, Neural oscillation, Neuron, ..., Neurophysiology, Neurotrophic electrode, Nigel G. Stocks, Nina Kraus, Non-negative matrix factorization, Outline of biophysics, Patricia Janak, Phase precession, Pinnatoxin, Primary motor cortex, Pulse-density modulation, Pulse-frequency modulation, Recognition memory, Richard F. Lyon, Self-organizing map, Sensory nervous system, Sensory neuron, Sensory neuroscience, Sharp waves and ripples, Sparse dictionary learning, Sparse distributed memory, Spike directivity, Spiking neural network, Stephen Kuffler, Surround suppression, Systems biology, Vector quantization, Vernon Benjamin Mountcastle, Visual adaptation, Visual tilt effects, Wavelet, Weakness, Weber–Fechner law, William Bialek, Yngve Zotterman. Expand index (35 more) »
Aging movement control
Normal aging movement control in humans is about the changes in the muscles, motor neurons, nerves, sensory functions, gait, fatigue, visual and manual responses, in men and women as they get older but who do not have neurological, muscular (atrophy, dystrophy...) or neuromuscular disorder.
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Artificial neural network
Artificial neural networks (ANNs) or connectionist systems are computing systems vaguely inspired by the biological neural networks that constitute animal brains.
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Axon
An axon (from Greek ἄξων áxōn, axis) or nerve fiber, is a long, slender projection of a nerve cell, or neuron, that typically conducts electrical impulses known as action potentials, away from the nerve cell body.
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Barbara Shinn-Cunningham
Barbara Shinn-Cunningham (born 1964) is a Professor of Biomedical Engineering at Boston University (BU).
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Binding problem
The binding problem is a term used at the interface between neuroscience, cognitive science and philosophy of mind that has multiple meanings.
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Binocular neurons
Binocular neurons are neurons in the visual system that assist in the creation of stereopsis from binocular disparity.
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Brain code
"Brain Code", sometimes also referred to as "mind code" or less general "neural code" refers to the interpretation of neural activity in the cerebral cortex as data structure for the representation of mental content, together with basic mechanisms of organization of activity and of structure.
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Bursting
Bursting, or burst firing, is an extremely diverse general phenomenon of the activation patterns of neurons in the central nervous system and spinal cord where periods of rapid action potential spiking are followed by G0 phase quiescent periods.
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Capsule neural network
A Capsule Neural Network (CapsNet) is a machine learning system that is a type of artificial neural network (ANN) that can be used to better model hierarchical relationships.
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Code
In communications and information processing, code is a system of rules to convert information—such as a letter, word, sound, image, or gesture—into another form or representation, sometimes shortened or secret, for communication through a communication channel or storage in a storage medium.
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Coding theory
Coding theory is the study of the properties of codes and their respective fitness for specific applications.
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Compartmental modelling of dendrites
Compartmental modelling of dendrites deals with multi-compartment modelling of the dendrites, to make the understanding of the electrical behavior of complex dendrites easier.
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Compressed sensing
Compressed sensing (also known as compressive sensing, compressive sampling, or sparse sampling) is a signal processing technique for efficiently acquiring and reconstructing a signal, by finding solutions to underdetermined linear systems.
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Computational neuroscience
Computational neuroscience (also known as theoretical neuroscience or mathematical neuroscience) is a branch of neuroscience which employs mathematical models, theoretical analysis and abstractions of the brain to understand the principles that govern the development, structure, physiology and cognitive abilities of the nervous system.
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Connectome
A connectome is a comprehensive map of neural connections in the brain, and may be thought of as its "wiring diagram".
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Cortical implant
A cortical implant is a subset of neuroprosthetics that is in direct connection with the cerebral cortex of the brain.
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Deep learning
Deep learning (also known as deep structured learning or hierarchical learning) is part of a broader family of machine learning methods based on learning data representations, as opposed to task-specific algorithms.
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Efficient coding hypothesis
The efficient coding hypothesis was proposed by Horace Barlow in 1961 as a theoretical model of sensory coding in the brain.
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Ephaptic coupling
Ephaptic coupling is a form of communication within the nervous system and is distinct from direct communication systems like electrical synapses and chemical synapses.
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Feature learning
In machine learning, feature learning or representation learning is a set of techniques that allows a system to automatically discover the representations needed for feature detection or classification from raw data.
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Gain-field encoding
Gain field encoding is a hypothesis about the internal storage and processing of limb motion in the brain.
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Gamma distribution
In probability theory and statistics, the gamma distribution is a two-parameter family of continuous probability distributions.
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Grandmother cell
The grandmother cell is a hypothetical neuron that represents a complex but specific concept or object.
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H1 neuron
The H1 neuron is located in the visual cortex of true flies of the order Diptera and mediates motor responses to visual stimuli.
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Hierarchical temporal memory
Hierarchical temporal memory (HTM) is a technology based on a realistic biologically-constrained model of the pyramidal neuron that reflects today’s most recent neocortical research originally described in the 2004 book On Intelligence by Jeff Hawkins with Sandra Blakeslee.
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Hippocampal replay
Hippocampal replay is a phenomenon observed in rats, mice, cats, rabbits, songbirds and monkeys.
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Inferior colliculus
The inferior colliculus (IC) (Latin for lower hill) is the principal midbrain nucleus of the auditory pathway and receives input from several peripheral brainstem nuclei in the auditory pathway, as well as inputs from the auditory cortex.
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Infographic
Infographics (a clipped compound of "information" and "graphics") are graphic visual representations of information, data or knowledge intended to present information quickly and clearly.
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John O'Keefe (neuroscientist)
John O'Keefe, (born November 18, 1939) is an American-British neuroscientist and a professor at the Sainsbury Wellcome Centre for Neural Circuits and Behaviour and the Research Department of Cell and Developmental Biology at University College London.
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Lateral line
The lateral line is a system of sense organs found in aquatic vertebrates, used to detect movement, vibration, and pressure gradients in the surrounding water.
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Machine learning
Machine learning is a subset of artificial intelligence in the field of computer science that often uses statistical techniques to give computers the ability to "learn" (i.e., progressively improve performance on a specific task) with data, without being explicitly programmed.
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Matrix norm
In mathematics, a matrix norm is a vector norm in a vector space whose elements (vectors) are matrices (of given dimensions).
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Maximally informative dimensions
Maximally informative dimensions is a dimensionality reduction technique used in the statistical analyses of neural responses.
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Michale Fee
Michale Sean Fee (born November 6, 1964, Pasadena CA) is a neuroscientist who works on the neural mechanisms of sequence generation and learning.
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MLPACK (C++ library)
mlpack is a machine learning software library for C++, built on top of the Armadillo library.
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Models of neural computation
Models of neural computation are attempts to elucidate, in an abstract and mathematical fashion, the core principles that underlie information processing in biological nervous systems, or functional components thereof.
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Motor unit
A motor unit is made up of a motor neuron and the skeletal muscle fibers innervated by that motor neuron's axonal terminals.
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Multielectrode array
| --> Multielectrode arrays (MEAs) or microelectrode arrays are devices that contain multiple plates or shanks through which neural signals are obtained or delivered, essentially serving as neural interfaces that connect neurons to electronic circuitry.
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Muscle weakness
Muscle weakness or myasthenia (my- from Greek μυο meaning "muscle" + -asthenia ἀσθένεια meaning "weakness") is a lack of muscle strength.
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Musical semantics
Music semantics refers to the ability of music to convey semantic meaning.
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Neural binding
Neural binding refers to the neuroscientific aspect of what is commonly known as the binding problem.
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Neural circuit
A neural circuit, is a population of neurons interconnected by synapses to carry out a specific function when activated.
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Neural clique
Neural cliques are network-level memory coding units in the hippocampus.
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Neural coding
Neural coding is a neuroscience field concerned with characterising the hypothetical relationship between the stimulus and the individual or ensemble neuronal responses and the relationship among the electrical activity of the neurons in the ensemble.
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Neural correlate
A neural correlate of a content of experience is any bodily component, such as an electro-neuro-biological 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.
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Neural decoding
Neural decoding is a neuroscience field concerned with the hypothetical reconstruction of sensory and other stimuli from information that has already been encoded and represented in the brain by networks of neurons.
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Neural engineering
Neural engineering (also known as neuroengineering) is a discipline within biomedical engineering that uses engineering techniques to understand, repair, replace, enhance, or otherwise exploit the properties of neural systems.
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Neural ensemble
A neural ensemble is a population of nervous system cells (or cultured neurons) involved in a particular neural computation.
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Neural oscillation
Neural oscillations, or brainwaves, are rhythmic or repetitive patterns of neural activity in the central nervous system.
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Neuron
A neuron, also known as a neurone (British spelling) and nerve cell, is an electrically excitable cell that receives, processes, and transmits information through electrical and chemical signals.
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Neurophysiology
Neurophysiology (from Greek νεῦρον, neuron, "nerve"; φύσις, physis, "nature, origin"; and -λογία, -logia, "knowledge") is a branch of physiology and neuroscience that is concerned with the study of the functioning of the nervous system.
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Neurotrophic electrode
The neurotrophic electrode is an intracortical device designed to read the electrical signals that the brain uses to process information.
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Nigel G. Stocks
Nigel Geoffrey Stocks (born 6 September 1964) is an engineer and physicist, notable for discovering suprathreshold stochastic resonance (SSR) and its application to cochlear implant technology.
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Nina Kraus
Nina Kraus is a professor at Northwestern University, investigating the neural encoding of speech and music and its plasticity where she is the Hugh S. Knowles Chair in audiology.
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Non-negative matrix factorization
Non-negative matrix factorization (NMF or NNMF), also non-negative matrix approximation is a group of algorithms in multivariate analysis and linear algebra where a matrix is factorized into (usually) two matrices and, with the property that all three matrices have no negative elements.
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Outline of biophysics
The following outline is provided as an overview of and topical guide to biophysics: Biophysics – interdisciplinary science that uses the methods of physics to study biological systems.
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Patricia Janak
Patricia Janak is a Bloomberg Distinguished Professor at Johns Hopkins University who studies the biological basis of behavior through associative learning.
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Phase precession
Phase precession is a neurophysiological process in which the firing of action potentials by individual neurons is timed in relation to the phase of neural oscillations in the surrounding cells.
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Pinnatoxin
Pinnatoxins are neurotoxic chemical compounds that inhibit neuronal and muscle-type nicotine acetylcholine receptors.
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Primary motor cortex
The primary motor cortex (Brodmann area 4) is a brain region that in humans is located in the dorsal portion of the frontal lobe.
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Pulse-density modulation
Pulse-density modulation, or PDM, is a form of modulation used to represent an analog signal with a binary signal.
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Pulse-frequency modulation
Pulse-Frequency Modulation (PFM) is a modulation method for representing an analog signal using only two levels (1 and 0).
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Recognition memory
Recognition memory, a subcategory of declarative memory, is the ability to recognize previously encountered events, objects, or people.
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Richard F. Lyon
Richard Francis Lyon (born 1952) is an American inventor, scientist, and engineer.
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Self-organizing map
A self-organizing map (SOM) or self-organizing feature map (SOFM) is a type of artificial neural network (ANN) that is trained using unsupervised learning to produce a low-dimensional (typically two-dimensional), discretized representation of the input space of the training samples, called a map, and is therefore a method to do dimensionality reduction.
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Sensory nervous system
The sensory nervous system is a part of the nervous system responsible for processing sensory information.
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Sensory neuron
Sensory neurons also known as afferent neurons are neurons that convert a specific type of stimulus, via their receptors, into action potentials or graded potentials.
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Sensory neuroscience
Sensory neuroscience is a subfield of neuroscience which explores the anatomy and physiology of neurons that are part of sensory systems such as vision, hearing, and olfaction.
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Sharp waves and ripples
Sharp waves and ripples (SWRs) are oscillatory patterns in the mammalian brain hippocampus seen on an EEG during immobility and sleep.
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Sparse dictionary learning
Sparse dictionary learning is a representation learning method which aims at finding a sparse representation of the input data (also known as sparse coding) in the form of a linear combination of basic elements as well as those basic elements themselves.
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Sparse distributed memory
Sparse distributed memory (SDM) is a mathematical model of human long-term memory introduced by Pentti Kanerva in 1988 while he was at NASA Ames Research Center.
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Spike directivity
Spike directivity is a vector that quantifies changes in transient charge density during action potential propagation.
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Spiking neural network
Spiking neural networks (SNNs) fall into the third generation of artificial neural network models, increasing the level of realism in a neural simulation.
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Stephen Kuffler
Stephen William Kuffler (August 24 Tap, Hungary, 1913 – October 11, 1980) was a pre-eminent Hungarian-American neurophysiologist.
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Surround suppression
Surround suppression is a descriptive term referring to observations that the relative firing rate of a neuron may under certain conditions decrease when a particular stimulus is enlarged.
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Systems biology
Systems biology is the computational and mathematical modeling of complex biological systems.
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Vector quantization
Vector quantization (VQ) is a classical quantization technique from signal processing that allows the modeling of probability density functions by the distribution of prototype vectors.
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Vernon Benjamin Mountcastle
Vernon Benjamin Mountcastle (July 15, 1918 – January 11, 2015) was Professor Emeritus of Neuroscience at Johns Hopkins University.
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Visual adaptation
Visual adaptation is the temporary change in sensitivity or perception when exposed to a new or intense stimulus, and the lingering afterimage that may result when the stimulus is removed.
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Visual tilt effects
Due to the effect of a spatial context or temporal context, the perceived orientation of a test line or grating pattern can appear tilted away from its physical orientation.
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Wavelet
A wavelet is a wave-like oscillation with an amplitude that begins at zero, increases, and then decreases back to zero.
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Weakness
Weakness or asthenia is a symptom of a number of different conditions.
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Weber–Fechner law
The Weber–Fechner law refers to two related laws in the field of psychophysics, known as Weber's law and Fechner's law.
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William Bialek
William Bialek (born 1960 in Los Angeles, California) is a theoretical biophysicist and a professor at Princeton University and The Graduate Center, CUNY.
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Yngve Zotterman
Yngve Zotterman (20 September 1898 in Vadstena – 13 March 1982 in Stockholm) was a Swedish neurophysiologist who received his medical training at the Karolinska Institute.
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Correlation code, Correlation coding, Correlation encoding, Independent-spike code, Independent-spike coding, Independent-spike encoding, Neural code, Neural encoding, NeuroElectroDynamics, Neuroelectrodynamics, Neuronal code, Neuronal coding, Phase-of-firing code, Population code, Population coding, Population encoding, Rate code, Rate coding, Rate encoding, Sparse code, Sparse coding, Sparse encoding, Sparseness, Temporal code, Temporal coding, Temporal encoding.
References
[1] https://en.wikipedia.org/wiki/Neural_coding
