Muscle contractionMuscle contraction is the activation of tension-generating sites within muscle cells. In physiology, muscle contraction does not necessarily mean muscle shortening because muscle tension can be produced without changes in muscle length, such as when holding something heavy in the same position. The termination of muscle contraction is followed by muscle relaxation, which is a return of the muscle fibers to their low tension-generating state.
Lateralization of brain functionThe lateralization of brain function (or hemispheric dominance/ latralisation ) is the tendency for some neural functions or cognitive processes to be specialized to one side of the brain or the other. The median longitudinal fissure separates the human brain into two distinct cerebral hemispheres, connected by the corpus callosum. Although the macrostructure of the two hemispheres appears to be almost identical, different composition of neuronal networks allows for specialized function that is different in each hemisphere.
BrainA brain is an organ that serves as the center of the nervous system in all vertebrate and most invertebrate animals. It is located in the head, usually close to the sensory organs for senses such as vision. It is the most complex organ in a vertebrate's body. In a human, the cerebral cortex contains approximately 14–16 billion neurons, and the estimated number of neurons in the cerebellum is 55–70 billion. Each neuron is connected by synapses to several thousand other neurons.
Recurrent neural networkA recurrent neural network (RNN) is one of the two broad types of artificial neural network, characterized by direction of the flow of information between its layers. In contrast to uni-directional feedforward neural network, it is a bi-directional artificial neural network, meaning that it allows the output from some nodes to affect subsequent input to the same nodes. Their ability to use internal state (memory) to process arbitrary sequences of inputs makes them applicable to tasks such as unsegmented, connected handwriting recognition or speech recognition.
ProprioceptionProprioception (ˌproʊpri.oʊˈsɛpʃən,_-ə- ), also called kinaesthesia (or kinesthesia), is the sense of self-movement, force, and body position. Proprioception is mediated by proprioceptors, mechanosensory neurons located within muscles, tendons, and joints. Most animals possess multiple subtypes of proprioceptors, which detect distinct kinematic parameters, such as joint position, movement, and load. Although all mobile animals possess proprioceptors, the structure of the sensory organs can vary across species.
Muscle cellA muscle cell is also known as a myocyte when referring to either a cardiac muscle cell (cardiomyocyte) or a smooth muscle cell, as these are both small cells. A skeletal muscle cell is long and threadlike with many nuclei and is called a muscle fiber. Muscle cells (including myocytes and muscle fibers) develop from embryonic precursor cells called myoblasts. Myoblasts fuse from multinucleated skeletal muscle cells known as syncytia in a process known as myogenesis.
MuscleMuscle is a soft tissue, one of the animal tissues that makes up the three different types of muscle. Muscle tissue gives skeletal muscles the ability to contract. Muscle is formed during embryonic development, in a process known as myogenesis. Muscle tissue contains special contractile proteins called actin and myosin which interact to cause movement. Among many other muscle proteins present are two regulatory proteins, troponin and tropomyosin. Muscle tissue varies with function and location in the body.
Smooth muscleSmooth muscle is an involuntary non-striated muscle, so-called because it has no sarcomeres and therefore no striations (bands or stripes). It is divided into two subgroups, single-unit and multiunit smooth muscle. Within single-unit muscle, the whole bundle or sheet of smooth muscle cells contracts as a syncytium. Smooth muscle is found in the walls of hollow organs, including the stomach, intestines, bladder and uterus. In the walls of blood vessels, and lymph vessels, (excluding blood and lymph capillaries) it is known as vascular smooth muscle.
Human brainThe human brain is the central organ of the human nervous system, and with the spinal cord makes up the central nervous system. The brain consists of the cerebrum, the brainstem and the cerebellum. It controls most of the activities of the body, processing, integrating, and coordinating the information it receives from the sense organs, and making decisions as to the instructions sent to the rest of the body. The brain is contained in, and protected by, the skull bones of the head.
Neural networkA neural network can refer to a neural circuit of biological neurons (sometimes also called a biological neural network), a network of artificial neurons or nodes in the case of an artificial neural network. Artificial neural networks are used for solving artificial intelligence (AI) problems; they model connections of biological neurons as weights between nodes. A positive weight reflects an excitatory connection, while negative values mean inhibitory connections. All inputs are modified by a weight and summed.
NociceptionNociception (also nocioception, from Latin nocere to harm or hurt) is the sensory nervous system's process of encoding noxious stimuli. It deals with a series of events and processes required for an organism to receive a painful stimulus, convert it to a molecular signal, and recognize and characterize the signal to trigger an appropriate defensive response. In nociception, intense chemical (e.g., capsaicin present in chili pepper or cayenne pepper), mechanical (e.g.
Artificial neural networkArtificial neural networks (ANNs, also shortened to neural networks (NNs) or neural nets) are a branch of machine learning models that are built using principles of neuronal organization discovered by connectionism in the biological neural networks constituting animal brains. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons.
Machine learningMachine learning (ML) is an umbrella term for solving problems for which development of algorithms by human programmers would be cost-prohibitive, and instead the problems are solved by helping machines 'discover' their 'own' algorithms, without needing to be explicitly told what to do by any human-developed algorithms. Recently, generative artificial neural networks have been able to surpass results of many previous approaches.
Striated muscle tissueStriated muscle tissue is a muscle tissue that features repeating functional units called sarcomeres. The presence of sarcomeres manifests as a series of bands visible along the muscle fibers, which is responsible for the striated appearance observed in microscopic images of this tissue. There are two types of striated muscle: Cardiac muscle (heart muscle) Skeletal muscle (muscle attached to the skeleton) Striated muscle tissue contains T-tubules which enables the release of calcium ions from the sarcoplasmic reticulum.
Gut–brain axisThe gut–brain axis is the two-way biochemical signaling that takes place between the gastrointestinal tract (GI tract) and the central nervous system (CNS). The term "gut–brain axis" is occasionally used to refer to the role of the gut microbiota in the interplay as well. The "microbiota–gut–brain (MGB or BGM) axis" explicitly includes the role of gut microbiota in the biochemical signaling events that take place between the GI tract and the CNS.
Split-brainSplit-brain or callosal syndrome is a type of disconnection syndrome when the corpus callosum connecting the two hemispheres of the brain is severed to some degree. It is an association of symptoms produced by disruption of, or interference with, the connection between the hemispheres of the brain. The surgical operation to produce this condition (corpus callosotomy) involves transection of the corpus callosum, and is usually a last resort to treat refractory epilepsy.
Types of artificial neural networksThere are many types of artificial neural networks (ANN). Artificial neural networks are computational models inspired by biological neural networks, and are used to approximate functions that are generally unknown. Particularly, they are inspired by the behaviour of neurons and the electrical signals they convey between input (such as from the eyes or nerve endings in the hand), processing, and output from the brain (such as reacting to light, touch, or heat). The way neurons semantically communicate is an area of ongoing research.
Pattern recognitionPattern recognition is the automated recognition of patterns and regularities in data. While similar, pattern recognition (PR) is not to be confused with pattern machines (PM) which may possess (PR) capabilities but their primary function is to distinguish and create emergent pattern. PR has applications in statistical data analysis, signal processing, , information retrieval, bioinformatics, data compression, computer graphics and machine learning.
Speech recognitionSpeech recognition is an interdisciplinary subfield of computer science and computational linguistics that develops methodologies and technologies that enable the recognition and translation of spoken language into text by computers. It is also known as automatic speech recognition (ASR), computer speech recognition or speech to text (STT). It incorporates knowledge and research in the computer science, linguistics and computer engineering fields. The reverse process is speech synthesis.
Online machine learningIn computer science, online machine learning is a method of machine learning in which data becomes available in a sequential order and is used to update the best predictor for future data at each step, as opposed to batch learning techniques which generate the best predictor by learning on the entire training data set at once. Online learning is a common technique used in areas of machine learning where it is computationally infeasible to train over the entire dataset, requiring the need of out-of-core algorithms.
