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Intraneural stimulation elicits discrimination of textural features by artificial fingertip in intact and amputee humans
Related concepts (24)
Biological neuron model
Biological neuron models, also known as a spiking neuron models, are mathematical descriptions of the properties of certain cells in the nervous system that generate sharp electrical potentials across their cell membrane, roughly one millisecond in duration, called action potentials or spikes (Fig. 2). Since spikes are transmitted along the axon and synapses from the sending neuron to many other neurons, spiking neurons are considered to be a major information processing unit of the nervous system.
Hippocampal sclerosis
Hippocampal sclerosis (HS) or mesial temporal sclerosis (MTS) is a neuropathological condition with severe neuronal cell loss and gliosis in the hippocampus. Neuroimaging tests such as magnetic resonance imaging (MRI) and positron emission tomography (PET) may identify individuals with hippocampal sclerosis. Hippocampal sclerosis occurs in 3 distinct settings: mesial temporal lobe epilepsy, adult neurodegenerative disease and acute brain injury.
Time
Time is the continued sequence of existence and events that occurs in an apparently irreversible succession from the past, through the present, into the future. It is a component quantity of various measurements used to sequence events, to compare the duration of events or the intervals between them, and to quantify rates of change of quantities in material reality or in the conscious experience. Time is often referred to as a fourth dimension, along with three spatial dimensions.
Recurrent neural network
A 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.
Artificial neural network
Artificial 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.
Perception
Perception () is the organization, identification, and interpretation of sensory information in order to represent and understand the presented information or environment. All perception involves signals that go through the nervous system, which in turn result from physical or chemical stimulation of the sensory system. Vision involves light striking the retina of the eye; smell is mediated by odor molecules; and hearing involves pressure waves.
Surge protector
A surge protector (or spike suppressor, surge suppressor, surge diverter, surge protection device (SPD) or transient voltage surge suppressor (TVSS) is an appliance or device intended to protect electrical devices from voltage spikes in alternating current (AC) circuits. A voltage spike is a transient event, typically lasting 1 to 30 microseconds, that may reach over 1,000 volts.
Overvoltage
In electrical engineering, overvoltage is the raising of voltage beyond the design limit of a circuit or circuit element. The conditions may be hazardous. Depending on its duration, the overvoltage event can be transient—a voltage spike—or permanent, leading to a power surge. Electronic and electrical devices are designed to operate at a certain maximum supply voltage, and considerable damage can be caused by voltage that is higher than that for which the devices are rated.
Neural engineering
Neural engineering (also known as neuroengineering) is a discipline within biomedical engineering that uses engineering techniques to understand, repair, replace, or enhance neural systems. Neural engineers are uniquely qualified to solve design problems at the interface of living neural tissue and non-living constructs (Hetling, 2008). The field of neural engineering draws on the fields of computational neuroscience, experimental neuroscience, neurology, electrical engineering and signal processing of living neural tissue, and encompasses elements from robotics, cybernetics, computer engineering, neural tissue engineering, materials science, and nanotechnology.
Types of artificial neural networks
There 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.