Shades of greenVarieties of the color green may differ in hue, chroma (also called saturation or intensity) or lightness (or value, tone, or brightness), or in two or three of these qualities. Variations in value are also called tints and shades, a tint being a green or other hue mixed with white, a shade being mixed with black. A large selection of these various colors is shown below. The color defined as green in the RGB color model is the brightest green that can be reproduced on a computer screen, and is the color named green in X11.
ElectrocorticographyElectrocorticography (ECoG), a type of intracranial electroencephalography (iEEG), is a type of electrophysiological monitoring that uses electrodes placed directly on the exposed surface of the brain to record electrical activity from the cerebral cortex. In contrast, conventional electroencephalography (EEG) electrodes monitor this activity from outside the skull. ECoG may be performed either in the operating room during surgery (intraoperative ECoG) or outside of surgery (extraoperative ECoG).
Brain–computer interfaceA brain–computer interface (BCI), sometimes called a brain–machine interface (BMI) or smartbrain, is a direct communication pathway between the brain's electrical activity and an external device, most commonly a computer or robotic limb. BCIs are often directed at researching, mapping, assisting, augmenting, or repairing human cognitive or sensory-motor functions. They are often conceptualized as a human–machine interface that skips the intermediary component of the physical movement of body parts, although they also raise the possibility of the erasure of the discreteness of brain and machine.
N200 (neuroscience)The N200, or N2, is an event-related potential (ERP) component. An ERP can be monitored using a non-invasive electroencephalography (EEG) cap that is fitted over the scalp on human subjects. An EEG cap allows researchers and clinicians to monitor the minute electrical activity that reaches the surface of the scalp from post-synaptic potentials in neurons, which fluctuate in relation to cognitive processing. EEG provides millisecond-level temporal resolution and is therefore known as one of the most direct measures of covert mental operations in the brain.
NeurolinguisticsNeurolinguistics is the study of neural mechanisms in the human brain that control the comprehension, production, and acquisition of language. As an interdisciplinary field, neurolinguistics draws methods and theories from fields such as neuroscience, linguistics, cognitive science, communication disorders and neuropsychology. Researchers are drawn to the field from a variety of backgrounds, bringing along a variety of experimental techniques as well as widely varying theoretical perspectives.
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.
Target audienceA target audience is the intended audience or readership of a publication, advertisement, or other message catered specifically to said intended audience. In marketing and advertising, it is a particular group of consumer within the predetermined target market, identified as the targets or recipients for a particular advertisement or message. Businesses that have a wide target market will focus on a specific target audience for certain messages to send, such as The Body Shops Mother's Day advertisements, which were aimed at the children and spouses of women, rather than the whole market which would have included the women themselves.
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.
