Activity-dependent plasticityActivity-dependent plasticity is a form of functional and structural neuroplasticity that arises from the use of cognitive functions and personal experience; hence, it is the biological basis for learning and the formation of new memories. Activity-dependent plasticity is a form of neuroplasticity that arises from intrinsic or endogenous activity, as opposed to forms of neuroplasticity that arise from extrinsic or exogenous factors, such as electrical brain stimulation- or drug-induced neuroplasticity.
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.
P200In neuroscience, the visual P200 or P2 is a waveform component or feature of the event-related potential (ERP) measured at the human scalp. Like other potential changes measurable from the scalp, this effect is believed to reflect the post-synaptic activity of a specific neural process. The P2 component, also known as the P200, is so named because it is a positive going electrical potential that peaks at about 200 milliseconds (varying between about 150 and 275 ms) after the onset of some external stimulus.
Linear discriminant analysisLinear discriminant analysis (LDA), normal discriminant analysis (NDA), or discriminant function analysis is a generalization of Fisher's linear discriminant, a method used in statistics and other fields, to find a linear combination of features that characterizes or separates two or more classes of objects or events. The resulting combination may be used as a linear classifier, or, more commonly, for dimensionality reduction before later classification.
Lateralized readiness potentialIn neuroscience, the lateralized readiness potential (LRP) is an event-related brain potential, or increase in electrical activity at the surface of the brain, that is thought to reflect the preparation of motor activity on a certain side of the body; in other words, it is a spike in the electrical activity of the brain that happens when a person gets ready to move one arm, leg, or foot. It is a special form of bereitschaftspotential (a general pre-motor potential).
N400 (neuroscience)The N400 is a component of time-locked EEG signals known as event-related potentials (ERP). It is a negative-going deflection that peaks around 400 milliseconds post-stimulus onset, although it can extend from 250-500 ms, and is typically maximal over centro-parietal electrode sites. The N400 is part of the normal brain response to words and other meaningful (or potentially meaningful) stimuli, including visual and auditory words, sign language signs, pictures, faces, environmental sounds, and smells.
Mu waveThe sensorimotor mu rhythm, also known as mu wave, comb or wicket rhythms or arciform rhythms, are synchronized patterns of electrical activity involving large numbers of neurons, probably of the pyramidal type, in the part of the brain that controls voluntary movement. These patterns as measured by electroencephalography (EEG), magnetoencephalography (MEG), or electrocorticography (ECoG), repeat at a frequency of 7.5–12.5 (and primarily 9–11) Hz, and are most prominent when the body is physically at rest.
Statistical classificationIn statistics, classification is the problem of identifying which of a set of categories (sub-populations) an observation (or observations) belongs to. Examples are assigning a given email to the "spam" or "non-spam" class, and assigning a diagnosis to a given patient based on observed characteristics of the patient (sex, blood pressure, presence or absence of certain symptoms, etc.). Often, the individual observations are analyzed into a set of quantifiable properties, known variously as explanatory variables or features.
Corner detectionCorner detection is an approach used within computer vision systems to extract certain kinds of features and infer the contents of an image. Corner detection is frequently used in motion detection, , video tracking, image mosaicing, panorama stitching, 3D reconstruction and object recognition. Corner detection overlaps with the topic of interest point detection. A corner can be defined as the intersection of two edges. A corner can also be defined as a point for which there are two dominant and different edge directions in a local neighbourhood of the point.
Scale-invariant feature transformThe scale-invariant feature transform (SIFT) is a computer vision algorithm to detect, describe, and match local features in images, invented by David Lowe in 1999. Applications include object recognition, robotic mapping and navigation, , 3D modeling, gesture recognition, video tracking, individual identification of wildlife and match moving. SIFT keypoints of objects are first extracted from a set of reference images and stored in a database.
