data.txt

经典的算法实例

psychophysical performance;movement direction;neurons;cortex;variability;discharge;dynamics;monkey
motor cortex;organization;potentiation;plasticity;pictures;spoken
long-term potentiation;bidirectional synaptic plasticity;neocortical pyramidal neurons;rabbit following stimulation;timing dependent plasticity;selective simple cells;hebbian plasticity;nmda receptors;lasting potentiation;hippocampal-neurons
reaching movements;arm;dynamics;model
learning-theory;networks
neural-networks
neural spike trains;visual-cortex;information-theory;channel capacity;code;variability;patterns;cat;communication;transmission
cat striate cortex;primary visual-cortex;binocular depth discrimination;classical receptive-field;macaque v1 neurons;simple cells;neural mechanisms;stereo disparity;complex cells;listings law
guided eye-movements;population codes;visual-cortex;helmholtz machine;parietal cortex;reaction-time;neurons;model;motion;recognition
artificial neural-networks;learning machine;systems
event-related potentials;classification;decomposition;algorithms;transform;packets;model
neural-networks;neurons;behavior;dynamics;thresholds;synapses;memory
hidden units;model
white-noise analysis;train data-analysis;visual information;spike trains;firing rate;neurons;population;responses;cells;time

independent component analysis;matrix factorization;constraints;algorithms
backpropagation
probability-distributions;information
approximation bounds;networks
retinal ganglion-cells;primary visual-cortex;direction selectivity;neocortical circuits;cat;neurons;plasticity;mechanism;model;input
primary visual-cortex;human motor cortex;silent period;orientation selectivity;occipital cortex;humans;motion;excitability;inhibition;luminance
asymmetric hebbian plasticity;neural-network;distributed synchrony;synaptic plasticity;neuronal-activity;firing rates;dynamics;input;cortex;connectivity
double bouquet cells;human visual-system;cerebral-cortex;columnar organization;neural networks;monkey;representations;axons;competition;neocortex
self-organizing map;intrinsic dimensionality
blind source separation;high-order contrasts;algorithm;infomax

hybrid multichannel filters;decomposition methods;impulsive noise;algorithms;removal
overcomplete representations;decomposition
neural-network model;pattern-recognition;object recognition;visual-attention;receptive-fields;natural images;cortex;responses;information;neurons
hippocampal place cells;patterns
primate prefrontal cortex;short-term-memory;low firing rates;persistent activity;neuronal networks;neural-networks;associative memory;inferotemporal cortex;intrinsic dynamics;working-memory
fire neurons;model;distributions;probability;adaptation;discharge;dynamics;cortex;noise;time
gene-expression;molecular classification;patterns
spike-frequency adaptation;cortical network model;fire neurons;neocortical neurons;pyramidal neurons;asynchronous states;neural-networks;synaptic input;firing rates;dynamics
neurons;information
lateral geniculate-nucleus;cat visual-cortex;oscillatory neuronal synchronization;ganglion-cell responses;sensorimotor cortex;awake monkeys;potentials;connections;specificity;sensitivity
lamprey spinal-cord;visual-spatial attention;superior colliculus;locomotion;behavior;deactivation;interneurons;recognition;generation;cortex
single neuron;statistical classifiers;learning algorithm;evolution;complexity;networks;size

classifiers;margin
spatial receptive-fields;auditory-cortex;neurons
reproduce spiking statistics;stochastic point-processes;fractal renewal processes;action-potentials;1/f fluctuations;temporal integration;correlated inputs;output jitter;visual-system;time scales
recognition
belief propagation
learning-curves;criterion;networks
associative memory;mushroom body;neural-networks;antennal lobes;odor representations;apis-mellifera;term-memory;fly brain;drosophila;neurons
digital-filters;networks;zeros;factorization;algorithm;systems
primary visual-cortex;adult owl monkeys;texture-discrimination;cortical plasticity;dynamical map;orientation;hyperacuity;simulation;mechanisms;frequency
graphical models;algorithm;correctness
neural-network regression;selection

primary visual-cortex;shunting inhibition;population codes;striate cortex;corticocortical connections;orientation selectivity;horizontal connections;intrinsic connections;contour integration;corner detection
innervating glabrous skin;2 vibrating probes;human hand;mechanoreceptive afferents;tactile sensibility;monkey;units;responses;microstimulation;stimulation
growth cone guidance;interference contrast microscopy;nerve growth;motor axons;slit proteins;netrin-1;repulsion;chemoattractant;chemotaxis;calcium
primary visual-cortex;neural spike trains;stochastic synapses;natural scenes;neurons;depression;release;energy;plasticity;adaptation
backpropagation algorithm
regularization;algorithm;convergence;feedforward;systems;models
oscillating neural assemblies;output neurons;representation;inhibition;honeybee;atlas
motion-sensitive interneurons;receptive-field organization;fly visual-system;optic flow;neurons;information
blind signal separation;instantaneous mixture;maximum-entropy;deconvolution;algorithms;contrasts
receptive-field plasticity;entorhinal cortex;hippocampus;monkeys;adult;representations;patterns;rat;map
primary visual-cortex;figure-ground organization;temporal correlation hypothesis;object recognition processes;oscillatory correlation;change blindness;neural-network;contextual modulation;feature integration;image segmentation
primate temporal cortex;long-term-memory;neural-networks;working-memory;associative memory;synaptic plasticity;persistent activity;cortical network;fire neurons;firing rates
optimization;connectivity
cats visual-cortex;binocular disparity;neural mechanisms;striate cortex;complex cells;spatiotemporal organization;spatial-frequency;stereo disparity;depth;fusion
spatial working-memory;dorsolateral prefrontal cortex;functional magnetic-resonance;posterior parietal cortex;hippocampal place cells;visual tracking neurons;network model;space;representation;dynamics
neurotransmitter release probability;asymmetric hebbian plasticity;long-term potentiation;synaptic plasticity;quantal amplitude;excitatory synapses;glutamate receptors;perforant path;visual-cortex;neuronal gain
weakly coupled oscillators;spiking neurons;firing probability;locus-coeruleus;systems;networks;locking;model;noise;transients
classifiers;trees
self-organized criticality;random boolean networks;annealed approximation;evolution;dynamics
cat visual-cortex;neurons in-vivo;pyramidal neurons;cortical-neurons;spiny neurons;coincidence detection;synaptic integration;striatal neurons;synchronization;impact
cat striate cortex;functional architecture;intrinsic connections;cortical-cells;orientation;curvature;fields;model;perception;topography
nonlinear dimensionality reduction
area mt;neural mechanisms;aperture problem;optical-flow;cortical-neurons;selection model;segmentation;integration;cortex;perception

neural-networks;attributes;induction;system
hippocampal place cells;lateral geniculate-nucleus;retinal ganglion-cells;visual information;cortical-neurons;spiking activity;population;reconstruction;code;construction
individual sequences;information;mechanisms;adaptation
retrieval;surface;microwave;land;temperature;ssm/i
primate motor cortex;free arm movements;interspike intervals;3-dimensional space;nonlinear dynamics;cell discharge;visual targets;monkeys;plasticity;direction
single units;pattern-recognition;vision;cat;channel;cells;synchronization;integration;mechanism;code
exponential stability;orientation;neurons;cortex
scattered-data;stability;interpolation;networks
networks
em algorithm;statistical physics;objective functions;neural networks;optimization;dynamics;models
neural networks;algorithm;neurons
cortex;codes;orientation;information;direction;representation;dynamics;field
object recognition;invariances
inferior temporal cortex;superior colliculus;movement;neurons;vision;models;v1
human cerebral-cortex;horizontal propagation;object recognition;striate cortex;monkey;stimuli;representation;topography;field;brain
independent component analysis;visual-system;3-dimensional objects;face recognition;natural images;network;cortex;architecture;binding;computation
algebraic analysis;machines
graph
maximum-likelihood;algorithm
adaptive observers;neural networks;nonlinear-systems;universal approximation;feedforward networks;exponential rate;identification;time;convergence;derivatives
two-dimensional patterns;single units;optic flow;cortical-neurons;visual-cortex;monkey;motion
cortical-neurons;resonance;networks;driven;noise;input
finite-state automata;iterated function systems;languages;time;dimension
independent component analysis;blind separation;information;convergence

stochastic properties;alternations;dynamics
time;hippocampus;code;rat
neural networks;complexity;systems;power;noise
symmetric hopfield nets;ising spin-glass;threshold circuits;spiking neurons;boolean functions;discrete-time;approximation algorithms;associative memory;analog computation;majority circuits
visual-cortex;shunting inhibition;spiking neurons;dynamics;cat;population;orientation;input;neocortex;responses
prefrontal cortex;behaving rat;supplementary;information;reliability;statistics

pyramidal cells;place cells;nmda channels;term-memory;model;rat;sequences;rhythm;potentiation;ca3
systems;approximation
primate prefrontal neurons;primary visual-cortex;frontal eye field;binocular-rivalry;persistent activity;neural networks;premotor cortex;working-memory;somatosensory cortex;intrinsic dynamics
auditory space map;cue integration;striate cortex;optic tectum;information;owls;orientation;perception;plasticity;receivers
neocortical pyramidal neurons;visual cortical-neurons;noisy cable structures;background activity;in-vivo;synaptic input;motor cortex;electrophysiological characterization;potential fluctuations;multiplicative noise
population-density approach;synaptic conductances;neural networks;fire neurons;synapses;cortex;rates;model
motor cortical representation;arm movements;voluntary movement;spastic hemiparesis;visual targets;cortex;direction;primate;hand;organization
deterministic dynamics;networks;representations;attractors;systems
striate cortical activity;ganglion-cells;neuronal oscillations;response latencies;backward-masking;macaque monkey;alert macaque;cortex;binding;synchronization
primary visual-cortex;natural images;local circuits;orientation selectivity;horizontal connections;contrast sensitivity;prenatal development;contour integration;striate cortex;macaque monkey
synaptic plasticity;prediction;model;space;rules

nonlinear dimensionality reduction;model
cat superior colliculus;inferior temporal neurons;zona incerta;somatosensory convergence;substantia nigra;receptive-fields;cortical areas;output neurons;visual-stimuli;eye-movements
distributions;convergence;theorems;samples;bounds;bias
cortical pyramidal neurons;coupled phase oscillators;inhibitory neurons;gamma oscillations;k+ channels;networks;cortex;neocortex;dynamics;hypothesis
retinal ganglion-cells;cat striate cortex;directional selectivity;apparent motion;visual-cortex;neocortical circuits;dendritic structure;receptive-fields;complex cells;computation
cortical-cells;firing rate;neuron
neocortical pyramidal neurons;excitatory synapses;multivesicular release;visual-cortex;single;cells;synchronization;sites;probability;plasticity
neocortical pyramidal neurons;cortical-neurons;synaptic efficacy;visual-cortex;synchronization;dynamics;information;model;propagation;responses
cat visual-cortex;stochastic resonance;coherence resonance;coincidence detector;cortical neuron;firing rates;noise;dynamics;synchronization;model
warm-start
absolute stability;graded response;convergence;circuits;systems;neurons;model
stochastic resonance;oscillations;variability;dynamics;networks;system;model;state
chain monte-carlo;protein structural classes;computation;recognition
lateral-line lobe;neural networks;differential equations;temporal association;recurrent excitation;neuronal networks;negative feedback;fire oscillators;stability;synchronization
integrate-and-fire;in-vivo;cortical-neurons;firing rate;correlated inputs;cross-correlation;synaptic input;variability;cortex;impact
independent component analysis;minimum norm algorithm;overcomplete representations;blind separation;natural images;entropy;decomposition;focuss;code
universal approximators;classification
neural networks;backpropagation;equalization


complex cells;striate cortex;statistics;integration;images
hierarchical mixtures;cortex;recognition;experts;neurons;models;speed
term synaptic plasticity;visual-cortex;pyramidal cells;nmda receptors;dependence;experience;neurons;model;ltp
task