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Neural network coding model
The convolutional sparse coding paradigm is an extension of the global sparse coding model, in which a redundant dictionary is modeled as a concatenation
Convolutional_sparse_coding
Type of feedforward neural network
processing, standard convolutional layers can be replaced by depthwise separable convolutional layers, which are based on a depthwise convolution followed by a
Convolutional_neural_network
Linear error correcting code
turbo codes, they have gained prominence in coding theory and information theory since the late 1990s. The codes today are widely used in applications ranging
Low-density_parity-check_code
Concept in mathematics
Papyan, V. Romano, Y. and Elad, M. (2017). "Convolutional Neural Networks Analyzed via Convolutional Sparse Coding" (PDF). Journal of Machine Learning Research
Sparse_approximation
Scheme for controlling errors in data over noisy communication channels
codes and convolutional codes are frequently combined in concatenated coding schemes in which a short constraint-length Viterbi-decoded convolutional
Error_correction_code
Neural network technology
neural networks, a convolutional layer is a type of network layer that applies a convolution operation to the input. Convolutional layers are some of
Convolutional_layer
Neural network that learns efficient data encoding in an unsupervised manner
Inspired by the sparse coding hypothesis in neuroscience, sparse autoencoders (SAE) are variants of autoencoders, such that the codes E ϕ ( x ) {\displaystyle
Autoencoder
Integral expressing the amount of overlap of one function as it is shifted over another
Hardware Cost of a Convolutional Neural Network". Neurocomputing. 407: 439–453. doi:10.1016/j.neucom.2020.04.018. S2CID 219470398. Convolutional neural networks
Convolution
Type of error correcting code
a convolutional pre-transformation before polar coding. These pre-transformed variant of polar codes were dubbed polarization-adjusted convolutional (PAC)
Polar_code_(coding_theory)
Representation learning method
Sparse dictionary learning (also known as sparse coding or SDL) is a representation learning method which aims to find a sparse representation of the
Sparse_dictionary_learning
Computer Networking Program
more general versions of linearity such as convolutional coding and filter-bank coding. Finding optimal coding solutions for general network problems with
Linear_network_coding
Type of convolutional neural network
U-Net is a convolutional neural network that was developed for image segmentation. The network is based on a fully convolutional neural network whose
U-Net
Branch of machine learning
deep learning. Deep learning architectures for convolutional neural networks (CNNs) with convolutional layers and downsampling layers began with the Neocognitron
Deep_learning
Convolutional neural network structure
motifs of modern convolutional neural networks, such as convolutional layer, pooling layer and full connection layer. Every convolutional layer includes
LeNet
Binary Golay code Binary Goppa code Bipolar violation CRHF Casting out nines Check digit Chien's search Chipkill Cksum Coding gain Coding theory Constant-weight
List of algebraic coding theory topics
List_of_algebraic_coding_theory_topics
Database of handwritten digits
single convolutional neural network best performance was 0.25 percent error rate. As of August 2018, the best performance of a single convolutional neural
MNIST_database
coding: adaptive coding technique based on Huffman coding Package-merge algorithm: Optimizes Huffman coding subject to a length restriction on code strings
List_of_algorithms
Algorithm for noise reduction in images
that integrates a convolutional neural network has been proposed and shows better results (albeit with a slower runtime). MATLAB code has been released
Block-matching and 3D filtering
Block-matching_and_3D_filtering
Biological theory of intelligence
(2017). "The HTM Spatial Pooler—A Neocortical Algorithm for Online Sparse Distributed Coding". Frontiers in Computational Neuroscience. 11 111. doi:10.3389/fncom
Hierarchical_temporal_memory
Algorithms for matrix decomposition
r.t. shifts along these dimensions can be learned by Convolutional NMF. In this case, W is sparse with columns having local non-zero weight windows that
Non-negative matrix factorization
Non-negative_matrix_factorization
plotted for conventional codes like Reed–Solomon codes under algebraic decoding or for convolutional codes under Viterbi decoding, the BER steadily decreases
Error_floor
Multidimensional data algorithm
{\displaystyle f} . Such sparse representations are desirable for signal coding and compression. More precisely, the sparsity problem that matching pursuit
Matching_pursuit
Computerized information extraction from images
Hardware Cost of a Convolutional Neural Network". Neurocomputing. 407: 439–453. doi:10.1016/j.neucom.2020.04.018. S2CID 219470398. Convolutional neural networks
Computer_vision
Discrete Fourier transform algorithm
computes such transformations by factorizing the DFT matrix into a product of sparse (mostly zero) factors. As a result, it manages to reduce the complexity
Fast_Fourier_transform
Problem in information theory and communication
framework for sparse matrix ensembles and maximum-likelihood coding, proving achievability for Wyner-Ziv coding and related source-coding problems. Similar
Distributed_source_coding
Set of learning techniques in machine learning
Coates and Ng note that certain variants of k-means behave similarly to sparse coding algorithms. In a comparative evaluation of unsupervised feature learning
Feature_learning
Classification of Artificial Neural Networks (ANNs)
Boltzmann machines (DBM), deep auto encoders, convolutional variants, ssRBMs, deep coding networks, DBNs with sparse feature learning, RNNs, conditional DBNs
Types of artificial neural networks
Types_of_artificial_neural_networks
Transform in numerical harmonic analysis
characteristics and design considerations for temporal subband video coding". ITU-T. Video Coding Experts Group. Retrieved 13 September 2019. Bovik, Alan C. (2009)
Discrete_wavelet_transform
Image classification model
detailed comparison of coding and pooling methods for BoW has shown that second-order statistics combined with Sparse Coding and an appropriate pooling
Bag-of-words model in computer vision
Bag-of-words_model_in_computer_vision
Dictionary learning algorithm
clustering method, and it works by iteratively alternating between sparse coding the input data based on the current dictionary, and updating the atoms
K-SVD
Ability of a computer to receive and interpret intelligible handwritten input
error rate, by using an approach to convolutional neural networks that evolved (by 2017) into "sparse convolutional neural networks". AI effect Applications
Handwriting_recognition
Topological quantum error correcting code
on each qubit, both with probability p. When p is low, this will create sparsely distributed pairs of anyons which have not moved far from their point of
Surface_code
Statistical law in machine learning
adversarial robustness, distillation, sparsity, retrieval, quantization, pruning, fairness, molecules, computer programming/coding, math word problems, arithmetic
Neural_scaling_law
Interdisciplinary research area
the quantum convolutional filter are: the encoder, the parameterized quantum circuit (PQC), and the measurement. The quantum convolutional filter can be
Quantum_machine_learning
Subset of artificial intelligence
representation is low-dimensional. Sparse coding algorithms attempt to do so under the constraint that the learned representation is sparse, meaning that the mathematical
Machine_learning
Function in discrete mathematics
also a well-known deterministic uncertainty principle that uses signal sparsity (or the number of non-zero coefficients). Let ‖ x ‖ 0 {\displaystyle
Discrete_Fourier_transform
unsymmetric sparse linear systems Fast Artificial Neural Network — open-source artificial neural network library Darknet — framework for convolutional neural
List_of_C_software_and_tools
S.; Krause, M. R.; Mazer, J. A. (2012). "Surround suppression and sparse coding in visual and barrel cortices". Frontiers in Neural Circuits. 6: 43
Surround_suppression
Algorithm for modelling sequential data
multimodal. The vision transformer, in turn, stimulated new developments in convolutional neural networks. Image and video generators like DALL-E (2021), Stable
Transformer_(deep_learning)
Method of data analysis
regression Singular spectrum analysis Singular value decomposition Sparse PCA Transform coding Weighted least squares Gewers, Felipe L.; Ferreira, Gustavo R
Principal_component_analysis
Linear filter used for texture analysis
Drettakis, George; Dutré, Philip (2009). "Procedural Noise using Sparse Gabor Convolution". ACM Transactions on Graphics. 28 (3): 1. CiteSeerX 10.1.1.232
Gabor_filter
Function for integral Fourier-like transform
acoustics, vibration signals, computer graphics, multifractal analysis, and sparse coding. In computer vision and image processing, the notion of scale space
Wavelet
Technique for wavelet analysis
P. (Nov 7–9, 2007). "Generalized Lifting for Sparse Image Representation and Coding". Picture Coding Symposiu, PCS 2007. Rolón, Julio C.; Salembier
Lifting_scheme
Type of large language model
You Need. Researchers proposed a number of efficiency improvements like sparse attention mechanisms and memory-efficient architectures that reduce computational
Generative pre-trained transformer
Generative_pre-trained_transformer
Property of artificial neural networks
Wen-Liang (2020). "Refinement and Universal Approximation via Sparsely Connected ReLU Convolution Nets". IEEE Signal Processing Letters. 27: 1175–1179. Bibcode:2020ISPL
Universal approximation theorem
Universal_approximation_theorem
AI whose outputs can be understood by humans
expected to significantly improve the safety of frontier AI models. For convolutional neural networks, DeepDream can generate images that strongly activate
Explainable artificial intelligence
Explainable_artificial_intelligence
Quantum algorithm for solving systems of linear equations
factoring algorithm and Grover's search algorithm. Assuming the system is sparse, has a low condition number κ {\displaystyle \kappa } , and that the user
HHL_algorithm
Artificial neural network that mimics neurons
(March 2002). "Unsupervised clustering with spiking neurons by sparse temporal coding and multilayer RBF networks". IEEE Transactions on Neural Networks
Spiking_neural_network
Software for understanding biological data
extraction makes CNNs a desirable model. A phylogenetic convolutional neural network (Ph-CNN) is a convolutional neural network architecture proposed by Fioranti
Machine learning in bioinformatics
Machine_learning_in_bioinformatics
Machine learning software library
Comparative Analysis of Gradient Descent-Based Optimization Algorithms on Convolutional Neural Networks". 2018 International Conference on Computational Techniques
TensorFlow
Eigenvalue algorithm
matrix A {\displaystyle A} by a vector, so it is effective for a very large sparse matrix with appropriate implementation. The speed of convergence is like
Power_iteration
Vector quantization algorithm minimizing the sum of squared deviations
integration of k-means clustering with deep learning methods, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs), to enhance
K-means_clustering
Algorithm to be run on quantum computers
a given linear system of equations. Provided that the linear system is sparse and has a low condition number κ {\displaystyle \kappa } , and that the
Quantum_algorithm
Method in natural language processing
distributional data implemented in their simplest form results in a very sparse vector space of high dimensionality (cf. curse of dimensionality). Reducing
Word_embedding
Sutskever, and Geoffrey E. Hinton. "Imagenet classification with deep convolutional neural networks." Advances in neural information processing systems
List of datasets in computer vision and image processing
List_of_datasets_in_computer_vision_and_image_processing
Deep learning generative model to encode data representation
expectation-maximization meta-algorithm (e.g. probabilistic PCA, (spike & slab) sparse coding). Such a scheme optimizes a lower bound of the data likelihood, which
Variational_autoencoder
(RANN) Simple Least-Squares Linear Regression (and Ridge Regression) Sparse Coding, Sparse dictionary learning Tree-based Neighbor Search (all-k-nearest-neighbors
Mlpack
Optimization algorithms using quantum computing
suggests an exponential improvement in the case where F {\displaystyle F} is sparse and the condition number (namely, the ratio between the largest and the
Quantum optimization algorithms
Quantum_optimization_algorithms
2020 text-generating language model
transformer model of deep neural network, which supersedes recurrence and convolution-based architectures with a technique known as "attention". This attention
GPT-3
Simulators of quantum mechanical systems
Sanders, Barry C. (2007). "Efficient quantum algorithms for simulating sparse Hamiltonians". Communications in Mathematical Physics. 270 (2): 359–371
Quantum_simulator
Recursive integer sequence
0) to (r,s) that never go above the line ry = sx. The Catalan k-fold convolution is: ∑ i 1 + ⋯ + i k = n i 1 , … , i k ≥ 0 C i 1 ⋯ C i k = k 2 n + k (
Catalan_number
Connection graph of the brain of the fruit fly Drosophila melanogaster
was available for sparse tracing of selected circuits. Six years later, in 2023, Sebastian Seung's lab at Princeton used convolutional neural networks (CNNs)
Drosophila_connectome
Any technique to improve resolution of an imaging system beyond conventional limits
computing to perform super-resolution image construction. For example, deep convolutional networks were used to generate a 1500x scanning electron microscope
Super-resolution_imaging
Array of numbers
ISBN 978-0-486-13930-2 Scott, J.; Tůma, M. (2023), "Sparse Matrices and Their Graphs", Algorithms for Sparse Linear Systems, Nečas Center Series, Cham: Birkhäuser
Matrix_(mathematics)
Smooth approximation of one-hot arg max
its support. Other functions like sparsemax or α-entmax can be used when sparse probability predictions are desired. Also the Gumbel-softmax reparametrization
Softmax_function
Optimization algorithm
over standard stochastic gradient descent in settings where data is sparse and sparse parameters are more informative. Examples of such applications include
Stochastic_gradient_descent
Mathematical technique used in data compression and analysis
concentrated in just a few coefficients. This principle is called transform coding. After that, the coefficients are quantized and the quantized values are
Wavelet_transform
code Somers' D Sørensen similarity index Spaghetti plot Sparse binary polynomial hashing Sparse PCA – sparse principal components analysis Sparsity-of-effects
List_of_statistics_articles
Text captured as part of outdoor surroundings in a photograph
text. Machine learning approaches such as support vector machine and convolutional neural networks are used to classify the components into text and non-text
Scene_text
Use of a GPU for computations typically assigned to CPUs
of data structures can be represented on the GPU: Dense arrays Sparse matrices (sparse array) – static or dynamic Adaptive structures (union type) The
General-purpose computing on graphics processing units
General-purpose_computing_on_graphics_processing_units
Set of methods for supervised statistical learning
significant advantages over the traditional approach when dealing with large, sparse datasets—sub-gradient methods are especially efficient when there are many
Support_vector_machine
Function used in signal processing
for understanding the use of "bins" for the x-axis in these plots. The sparse sampling of a discrete-time Fourier transform (DTFT) such as the DFTs in
Window_function
Field of machine learning
Extending FRL with Fuzzy Rule Interpolation allows the use of reduced size sparse fuzzy rule-bases to emphasize cardinal rules (most important state-action
Reinforcement_learning
Type of artificial neural network
result in different learning algorithms for regression, classification, sparse coding, compression, feature learning and clustering. As a special case, a
Extreme_learning_machine
Class of artificial neural network
modeling and Multilingual Language Processing. Also, LSTM combined with convolutional neural networks (CNNs) improved automatic image captioning. The idea
Recurrent_neural_network
Computational complexity of quantum algorithms
represented as 2 S ( n ) × 2 S ( n ) {\displaystyle 2^{S(n)}\times 2^{S(n)}} sparse matrices. So to account for the application of each of the T ( n ) {\displaystyle
Quantum_complexity_theory
Process of removing noise from a signal
restoration tasks. Deep Image Prior is one such technique that makes use of convolutional neural network and is notable in that it requires no prior training
Noise_reduction
Statistical method in data analysis
in the embedded space to obtain initial clusters, (iii) constructing a sparse k-nearest neighbor graph between clusters with edge weights derived from
Hierarchical_clustering
Feature detection algorithm in computer vision
due to its open source code. KAZE was originally made by Pablo F. Alcantarilla, Adrien Bartoli and Andrew J. Davison. Convolutional neural network Image
Scale-invariant feature transform
Scale-invariant_feature_transform
Function whose domain is the positive integers
called the Dirichlet convolution of a and b, and is denoted by a ∗ b {\displaystyle a*b} . A particularly important case is convolution with the constant
Arithmetic_function
Producing images of 3D scenes
availability of GPUs that can evaluate neural networks (especially convolutional neural networks) quickly. Neural networks and Gaussian mixture models
Rendering_(computer_graphics)
Machine learning technique useful for dimensionality reduction
vector quantization Liquid state machine Neocognitron Neural gas Sparse coding Sparse distributed memory Topological data analysis Kohonen, Teuvo (January
Self-organizing_map
Numbers with many divisors
347. JFM 45.1248.01. Kahane, Jean-Pierre (February 2015), "Bernoulli convolutions and self-similar measures after Erdős: A personal hors d'oeuvre", Notices
Highly_composite_number
Cryptography based on quantum mechanical phenomena
York, introduced the concept of quantum conjugate coding. His seminal paper titled "Conjugate Coding" was rejected by the IEEE Information Theory Society
Quantum_cryptography
Set of machine learning methods
2009 Yang, H., Xu, Z., Ye, J., King, I., & Lyu, M. R. (2011). Efficient Sparse Generalized Multiple Kernel Learning. IEEE Transactions on Neural Networks
Multiple_kernel_learning
Mathematical operation on matrices
Cohen, Jérémy E.; Gribonval, Rémi (2018). "Learning Fast Dictionaries for Sparse Representations Using Low-Rank Tensor Decompositions". Latent Variable Analysis
Kronecker_product
Grouping a set of objects by similarity
areas of higher density than the remainder of the data set. Objects in sparse areas – that are required to separate clusters – are usually considered
Cluster_analysis
List of concepts in artificial intelligence
or overshoot and ensuring control stability. convolutional neural network In deep learning, a convolutional neural network (CNN, or ConvNet) is a class
Glossary of artificial intelligence
Glossary_of_artificial_intelligence
Probability distribution
similar to each other. Values of the concentration parameter below 1 prefer sparse distributions, i.e. most of the values within a single sample will be close
Dirichlet_distribution
Image processing method
Sylvain Fischer, Rafael Redondo, Laurent Perrinet, Gabriel Cristobal. Sparse approximation of images inspired from the functional architecture of the
Edge_detection
Rapidly rotating storm system
"Estimating tropical cyclone intensity by satellite imagery utilizing convolutional neural networks". American Meteorological Society. 34 (2): 448. Bibcode:2019WtFor
Tropical_cyclone
Computer graphics method
light field around each visible point on a surface. More recently, convolutional neural networks have been used to implement denoising filters, training
Path_tracing
Savalle, Pierre-Andre; Vayatis, Nicolas (2012). "Estimation of Simultaneously Sparse and Low Rank Matrices". arXiv:1206.6474 [cs.DS]. Richardson, Matthew; Burges
List of datasets for machine-learning research
List_of_datasets_for_machine-learning_research
Moving average and polynomial regression method for smoothing data
e. an unstable or singular design matrix) when fitting in regions with sparse data. For this reason, some authors[who?] choose to use the Gaussian kernel
Local_regression
Machine learning algorithm
arguably easier to understand than general decision trees due to their added sparsity,[citation needed] permit non-greedy learning methods and monotonic constraints
Decision_tree_learning
Analog of the continuous Laplace operator
) i {\displaystyle Lu=(\Delta u)_{i}} . Let C {\displaystyle C} be the (sparse) cotangent matrix with entries C i j = { 1 2 ( cot α i j + cot β i j
Discrete_Laplace_operator
Archaeological horizon of Neolithic Europe
believed untenanted or too sparsely populated by hunter-gatherers to be a significant factor. In 2005, researchers sequenced mtDNA coding region 15997–16409 from
Linear_Pottery_culture
requires less space. Sparse matrix A matrix with relatively few non-zero elements. Sparse matrix algorithms can tackle huge sparse matrices that are utterly
List_of_named_matrices
Interdisciplinary field
the main factor determining the form of this segmentation function. Convolutional neural networks (CNNs): The computer-assisted fully automated segmentation
Medical_image_computing
Count of permutations by cycles
be extended through the relations of these triangles to the Stirling convolution polynomials. Combinatorial proofs These identities may be derived by
Stirling numbers of the first kind
Stirling_numbers_of_the_first_kind
CONVOLUTIONAL SPARSE-CODING
CONVOLUTIONAL SPARSE-CODING
Surname or Lastname
English
English : variant of Speake.
Surname or Lastname
English
English : variant of Spear.
Surname or Lastname
English
English : patronymic from Spark 1.
Surname or Lastname
English
English : patronymic from Spear.
Male
English
Short form of English unisex Paisley, PAISE means "church."Â
Surname or Lastname
English (Suffolk)
English (Suffolk) : unexplained.
Surname or Lastname
English
English : variant spelling of Pass.French : possibly a nickname from passe ‘sparrow’.
Boy/Male
American, British, English
Gallant
Surname or Lastname
English
English : metonymic occupational name for someone who made bags or purses or for an official in charge of expenditure, from Middle English purse (via Old English from Latin bursa).Scottish : variant of Purser.
Female
English
English variant form of French Cerise, SHARISE means "cherry."Â
Surname or Lastname
English
English : from the Norman personal name Serlo, Germanic Sarilo, Serilo. This was probably originally a byname cognate with Old Norse Sorli, and akin to Old English searu ‘armor’, meaning perhaps ‘defender’, ‘protector’.
Boy/Male
Gujarati, Hindu, Indian, Kannada, Malayalam, Marathi, Telugu
Feel; Healthy; Touch
Surname or Lastname
Portuguese
Portuguese : occupational name from soeiro ‘swineherd’, Latin suerius.English : patronymic from a nickname for someone with reddish hair, from Anglo-Norman French sor ‘chestnut (color)’.
Boy/Male
Afghan, Arabic, Iranian, Muslim, Parsi
Pious; Pure; Chaste; Holy
Girl/Female
Hindu, Indian
Touch
Surname or Lastname
Irish (Kerry)
Irish (Kerry) : Anglicized form of Gaelic Mac Saoghair, which in turn may be a patronymic from a Gaelicized form of the Old English personal name Saeger (see 2 below).English : patronymic from a Middle English personal name Saher or Seir (see Sayer 1).Americanized form of French Cyr.Richard Sears came to Plymouth, MA, from England about 1630.
Boy/Male
Anglo Saxon Welsh
Spares.
Surname or Lastname
English
English : patronymic from Spire 1.
Surname or Lastname
English
English : variant of Sparks.
Surname or Lastname
English
English : nickname for a frugal person, from Middle English spare ‘sparing’, ‘frugal’.
CONVOLUTIONAL SPARSE-CODING
CONVOLUTIONAL SPARSE-CODING
Boy/Male
American, Anglo, Australian, British, English
Swift; Quick as the Wind; Bright Friend
Boy/Male
Danish, French, German, Latin, Swedish
Worthy of Love; Lovable
Girl/Female
Assamese, Bengali, Celebrity, Finnish, Gujarati, Hindu, Indian, Kannada, Malayalam, Marathi, Oriya, Rajasthani, Sanskrit, Tamil, Telugu, Traditional
Season; Mausam
Boy/Male
Arabic, Pashtun
Success; Gift; Prosperity
Boy/Male
Indian, Punjabi, Sikh
Brave Under the Protection of God
Boy/Male
Indian
Awakens.
Girl/Female
Tamil
Born in the month of Chaitra, Blessed with a good memory
Surname or Lastname
English
English : variant of Creswell.
Girl/Female
Arabic, Muslim
Wise and Intelligent
Male
Italian
Pet form of Italian Angiolo, ANGIOLETTO means "angel, messenger."
CONVOLUTIONAL SPARSE-CODING
CONVOLUTIONAL SPARSE-CODING
CONVOLUTIONAL SPARSE-CODING
CONVOLUTIONAL SPARSE-CODING
CONVOLUTIONAL SPARSE-CODING
n.
The right of bowling again at a full set of pins, after having knocked all the pins down in less than three bowls. If all the pins are knocked down in one bowl it is a double spare; in two bowls, a single spare.
v. t.
Held in reserve, to be used in an emergency; as, a spare anchor; a spare bed or room.
imp. & p. p.
of Spare
v. t.
Scanty; not abundant or plentiful; as, a spare diet.
n.
Brilliancy; luster; as, the sparkle of a diamond.
v. t.
To sprinkle; to moisten by sprinkling; as, to sparge paper.
n.
One who parses.
v. t.
To sift through a sarse.
adv.
Sparsely; scatteredly; here and there.
superl.
Not refined; rough; rude; unpolished; gross; indelicate; as, coarse manners; coarse language.
n.
A fine sieve; a searce.
adv.
In a scattered or sparse manner.
v. t.
To inclose in a hearse; to entomb.
n.
One who spares.
imp. & p. p.
of Parse
superl.
Large in bulk, or composed of large parts or particles; of inferior quality or appearance; not fine in material or close in texture; gross; thick; rough; -- opposed to fine; as, coarse sand; coarse thread; coarse cloth; coarse bread.
n.
To emit sparks; to throw off ignited or incandescent particles; to shine as if throwing off sparks; to emit flashes of light; to scintillate; to twinkle; as, the blazing wood sparkles; the stars sparkle.
superl.
Thinly scattered; set or planted here and there; not being dense or close together; as, a sparse population.
a.
Having convolutions.
n.
An irregular, tortuous folding of an organ or part; as, the convolutions of the intestines; the cerebral convolutions. See Brain.