NeurostimulationNeurostimulation is the purposeful modulation of the nervous system's activity using invasive (e.g. microelectrodes) or non-invasive means (e.g. transcranial magnetic stimulation or transcranial electric stimulation, tES, such as tDCS or transcranial alternating current stimulation, tACS). Neurostimulation usually refers to the electromagnetic approaches to neuromodulation.
Activation functionActivation function of a node in an artificial neural network is a function that calculates the output of the node (based on its inputs and the weights on individual inputs). Nontrivial problems can be solved only using a nonlinear activation function. Modern activation functions include the smooth version of the ReLU, the GELU, which was used in the 2018 BERT model, the logistic (sigmoid) function used in the 2012 speech recognition model developed by Hinton et al, the ReLU used in the 2012 AlexNet computer vision model and in the 2015 ResNet model.
Transcranial magnetic stimulationTranscranial magnetic stimulation (TMS) is a noninvasive form of brain stimulation in which a changing magnetic field is used to induce an electric current at a specific area of the brain through electromagnetic induction. An electric pulse generator, or stimulator, is connected to a magnetic coil connected to the scalp. The stimulator generates a changing electric current within the coil which creates a varying magnetic field, inducing a current within a region in the brain itself.
ElectrodeAn electrode is an electrical conductor used to make contact with a nonmetallic part of a circuit (e.g. a semiconductor, an electrolyte, a vacuum or air). Electrodes are essential parts of batteries that can consist of a variety of materials depending on the type of battery. The electrophore, invented by Johan Wilcke, was an early version of an electrode used to study static electricity. Electrodes are an essential part of any battery. The first electrochemical battery made was devised by Alessandro Volta and was aptly named the Voltaic cell.
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.
Feedforward neural networkA feedforward neural network (FNN) is one of the two broad types of artificial neural network, characterized by direction of the flow of information between its layers. Its flow is uni-directional, meaning that the information in the model flows in only one direction—forward—from the input nodes, through the hidden nodes (if any) and to the output nodes, without any cycles or loops, in contrast to recurrent neural networks, which have a bi-directional flow.
Transcranial direct-current stimulationTranscranial direct current stimulation (tDCS) is a form of neuromodulation that uses constant, low direct current delivered via electrodes on the head. It was originally developed to help patients with brain injuries or neuropsychiatric conditions such as major depressive disorder. It can be contrasted with cranial electrotherapy stimulation, which generally uses alternating current the same way, as well as transcranial magnetic stimulation. Research shows increasing evidence for tDCS as a treatment for depression.
Convolutional neural networkConvolutional neural network (CNN) is a regularized type of feed-forward neural network that learns feature engineering by itself via filters (or kernel) optimization. Vanishing gradients and exploding gradients, seen during backpropagation in earlier neural networks, are prevented by using regularized weights over fewer connections. For example, for each neuron in the fully-connected layer 10,000 weights would be required for processing an image sized 100 × 100 pixels.
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.
Liquid metal electrodeA liquid metal electrode is an electrode that uses a liquid metal, such as mercury, Galinstan, and NaK. They can be used in electrocapillarity, voltammetry, and impedance measurements. The dropping mercury electrode (DME) is a working electrode made of mercury and used in polarography. Experiments run with mercury electrodes are referred to as forms of polarography even if the experiments are identical or very similar to a corresponding voltammetry experiment which uses solid working electrodes.
Spinal cord stimulatorA spinal cord stimulator (SCS) or dorsal column stimulator (DCS) is a type of implantable neuromodulation device (sometimes called a "pain pacemaker") that is used to send electrical signals to select areas of the spinal cord (dorsal columns) for the treatment of certain pain conditions. SCS is a consideration for people who have a pain condition that has not responded to more conservative therapy. There are also spinal cord stimulators under research and development that could enable patients with spinal cord injury to walk again via epidural electrical stimulation (EES).
Rectifier (neural networks)In the context of artificial neural networks, the rectifier or ReLU (rectified linear unit) activation function is an activation function defined as the positive part of its argument: where x is the input to a neuron. This is also known as a ramp function and is analogous to half-wave rectification in electrical engineering. This activation function was introduced by Kunihiko Fukushima in 1969 in the context of visual feature extraction in hierarchical neural networks.
Standard hydrogen electrodeIn electrochemistry, the standard hydrogen electrode (abbreviated SHE), is a redox electrode which forms the basis of the thermodynamic scale of oxidation-reduction potentials. Its absolute electrode potential is estimated to be 4.44 ± 0.02 V at 25 °C, but to form a basis for comparison with all other electrochemical reactions, hydrogen's standard electrode potential (E°) is declared to be zero volts at any temperature. Potentials of all other electrodes are compared with that of the standard hydrogen electrode at the same temperature.
Artificial neuronAn artificial neuron is a mathematical function conceived as a model of biological neurons, a neural network. Artificial neurons are elementary units in an artificial neural network. The artificial neuron receives one or more inputs (representing excitatory postsynaptic potentials and inhibitory postsynaptic potentials at neural dendrites) and sums them to produce an output (or , representing a neuron's action potential which is transmitted along its axon).
Reference electrodeA reference electrode is an electrode that has a stable and well-known electrode potential. The overall chemical reaction taking place in a cell is made up of two independent half-reactions, which describe chemical changes at the two electrodes. To focus on the reaction at the working electrode, the reference electrode is standardized with constant (buffered or saturated) concentrations of each participant of the redox reaction. There are many ways reference electrodes are used.
Microelectrode arrayMicroelectrode arrays (MEAs) (also referred to as multielectrode arrays) are devices that contain multiple (tens to thousands) microelectrodes through which neural signals are obtained or delivered, essentially serving as neural interfaces that connect neurons to electronic circuitry. There are two general classes of MEAs: implantable MEAs, used in vivo, and non-implantable MEAs, used in vitro. Neurons and muscle cells create ion currents through their membranes when excited, causing a change in voltage between the inside and the outside of the cell.
Neural oscillationNeural oscillations, or brainwaves, are rhythmic or repetitive patterns of neural activity in the central nervous system. Neural tissue can generate oscillatory activity in many ways, driven either by mechanisms within individual neurons or by interactions between neurons. In individual neurons, oscillations can appear either as oscillations in membrane potential or as rhythmic patterns of action potentials, which then produce oscillatory activation of post-synaptic neurons.
Spinal cord injury researchSpinal cord injury research seeks new ways to cure or treat spinal cord injury in order to lessen the debilitating effects of the injury in the short or long term. There is no cure for SCI, and current treatments are mostly focused on spinal cord injury rehabilitation and management of the secondary effects of the condition. Two major areas of research include neuroprotection, ways to prevent damage to cells caused by biological processes that take place in the body after the injury, and neuroregeneration, regrowing or replacing damaged neural circuits.
Spinal cord injuryA spinal cord injury (SCI) is damage to the spinal cord that causes temporary or permanent changes in its function. Symptoms may include loss of muscle function, sensation, or autonomic function in the parts of the body served by the spinal cord below the level of the injury. Injury can occur at any level of the spinal cord and can be complete, with a total loss of sensation and muscle function at lower sacral segments, or incomplete, meaning some nervous signals are able to travel past the injured area of the cord up to the Sacral S4-5 spinal cord segments.
Auxiliary electrodeIn electrochemistry, the auxiliary electrode, often also called the counter electrode, is an electrode used in a three-electrode electrochemical cell for voltammetric analysis or other reactions in which an electric current is expected to flow. The auxiliary electrode is distinct from the reference electrode, which establishes the electrical potential against which other potentials may be measured, and the working electrode, at which the cell reaction takes place.
