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Event-related Functional Magnetic Resonance Imaging
Event-related functional magnetic resonance imaging (efMRI) is a technique used in magnetic resonance imaging of medical patients. EfMRI is used to detect changes in the BOLD ( blood oxygen level dependent) hemodynamic response to neural activity in response to certain events.Henson Description Within fMRI methodology, there are two different ways that are typically employed to present stimuli. One method is a block related design, in which two or more different conditions are alternated in order to determine the differences between the two conditions, or a control may be included in the presentation occurring between the two conditions. By contrast, event related designs are not presented in a set sequence; the presentation is randomized and the time in between stimuli can vary. efMRI attempts to model the change in fMRI signal in response to neural events associated with behavioral trials. According to D'Esposito, "event-related fMRI has the potential to address a number ...
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Magnetic Resonance Imaging
Magnetic resonance imaging (MRI) is a medical imaging technique used in radiology to form pictures of the anatomy and the physiological processes of the body. MRI scanners use strong magnetic fields, magnetic field gradients, and radio waves to generate images of the organs in the body. MRI does not involve X-rays or the use of ionizing radiation, which distinguishes it from CT and PET scans. MRI is a medical application of nuclear magnetic resonance (NMR) which can also be used for imaging in other NMR applications, such as NMR spectroscopy. MRI is widely used in hospitals and clinics for medical diagnosis, staging and follow-up of disease. Compared to CT, MRI provides better contrast in images of soft-tissues, e.g. in the brain or abdomen. However, it may be perceived as less comfortable by patients, due to the usually longer and louder measurements with the subject in a long, confining tube, though "Open" MRI designs mostly relieve this. Additionally, implants and oth ...
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Hemoglobin
Hemoglobin (haemoglobin BrE) (from the Greek word αἷμα, ''haîma'' 'blood' + Latin ''globus'' 'ball, sphere' + ''-in'') (), abbreviated Hb or Hgb, is the iron-containing oxygen-transport metalloprotein present in red blood cells (erythrocytes) of almost all vertebrates (the exception being the fish family Channichthyidae) as well as the tissues of some invertebrates. Hemoglobin in blood carries oxygen from the respiratory organs (''e.g.'' lungs or gills) to the rest of the body (''i.e.'' tissues). There it releases the oxygen to permit aerobic respiration to provide energy to power functions of an organism in the process called metabolism. A healthy individual human has 12to 20grams of hemoglobin in every 100mL of blood. In mammals, the chromoprotein makes up about 96% of the red blood cells' dry content (by weight), and around 35% of the total content (including water). Hemoglobin has an oxygen-binding capacity of 1.34mL O2 per gram, which increases the total blood oxygen ...
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Working Memory
Working memory is a cognitive system with a limited capacity that can hold information temporarily. It is important for reasoning and the guidance of decision-making and behavior. Working memory is often used synonymously with short-term memory, but some theorists consider the two forms of memory distinct, assuming that working memory allows for the manipulation of stored information, whereas short-term memory only refers to the short-term storage of information. Working memory is a theoretical concept central to cognitive psychology, neuropsychology, and neuroscience. History The term "working memory" was coined by Miller, Galanter, and Pribram, and was used in the 1960s in the context of theories that likened the mind to a computer. In 1968, Atkinson and Shiffrin used the term to describe their "short-term store". What we now call working memory was formerly referred to variously as a "short-term store" or short-term memory, primary memory, immediate memory, operant memo ...
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Object Recognition
Object recognition – technology in the field of computer vision for finding and identifying objects in an image or video sequence. Humans recognize a multitude of objects in images with little effort, despite the fact that the image of the objects may vary somewhat in different view points, in many different sizes and scales or even when they are translated or rotated. Objects can even be recognized when they are partially obstructed from view. This task is still a challenge for computer vision systems. Many approaches to the task have been implemented over multiple decades. Approaches based on CAD-like object models * Edge detection * Primal sketch * Marr, Mohan and Nevatia * Lowe * Olivier Faugeras Recognition by parts * Generalized cylinders (Thomas Binford) * Geon (psychology), Geons (Irving Biederman) * Dickinson, Forsyth and Ponce Appearance-based methods * Use example images (called templates or exemplars) of the objects to perform recognition * Objects ...
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Priming (psychology)
Priming is a phenomenon whereby exposure to one stimulus influences a response to a subsequent stimulus, without conscious guidance or intention. The priming effect refers to the positive or negative effect of a rapidly presented stimulus (priming stimulus) on the processing of a second stimulus (target stimulus) that appears shortly after. Generally speaking, the generation of priming effect depends on the existence of some positive or negative relationship between priming and target stimuli. For example, the word ''nurse'' is recognized more quickly following the word ''doctor'' than following the word ''bread''. Priming can be perceptual, associative, repetitive, positive, negative, affective, semantic, or conceptual. Priming effects involve word recognition, semantic processing, attention, unconscious processing, and many other issues, and are related to differences in various writing systems. Research, however, has yet to firmly establish the duration of priming effects, yet th ...
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Design Matrix
In statistics and in particular in regression analysis, a design matrix, also known as model matrix or regressor matrix and often denoted by X, is a matrix of values of explanatory variables of a set of objects. Each row represents an individual object, with the successive columns corresponding to the variables and their specific values for that object. The design matrix is used in certain statistical models, e.g., the general linear model. It can contain indicator variables (ones and zeros) that indicate group membership in an ANOVA, or it can contain values of continuous variables. The design matrix contains data on the independent variables (also called explanatory variables) in statistical models which attempt to explain observed data on a response variable (often called a dependent variable) in terms of the explanatory variables. The theory relating to such models makes substantial use of matrix manipulations involving the design matrix: see for example linear regression. A n ...
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Statistical Parametric Mapping
Statistical parametric mapping (SPM) is a statistical technique for examining differences in brain activity recorded during functional neuroimaging experiments. It was created by Karl Friston. It may alternatively refer to software created by the Wellcome Department of Imaging Neuroscience at University College London to carry out such analyses. Approach Unit of measurement Functional neuroimaging is one type of 'brain scanning'. It involves the measurement of brain activity. The measurement technique depends on the imaging technology (e.g., fMRI and PET). The scanner produces a 'map' of the area that is represented as voxels. Each voxel represents the activity of a specific volume in three-dimensional space. The exact size of a voxel varies depending on the technology. fMRI voxels typically represent a volume of 27 mm3 in an equilateral cuboid. Experimental design Researchers examine brain activity linked to a specific mental process or processes. One approach involves aski ...
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Linear Relationship
In statistics, correlation or dependence is any statistical relationship, whether causal or not, between two random variables or bivariate data. Although in the broadest sense, "correlation" may indicate any type of association, in statistics it usually refers to the degree to which a pair of variables are ''linearly'' related. Familiar examples of dependent phenomena include the correlation between the height of parents and their offspring, and the correlation between the price of a good and the quantity the consumers are willing to purchase, as it is depicted in the so-called demand curve. Correlations are useful because they can indicate a predictive relationship that can be exploited in practice. For example, an electrical utility may produce less power on a mild day based on the correlation between electricity demand and weather. In this example, there is a causal relationship, because extreme weather causes people to use more electricity for heating or cooling. However ...
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Statistics
Statistics (from German language, German: ''wikt:Statistik#German, Statistik'', "description of a State (polity), state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model to be studied. Populations can be diverse groups of people or objects such as "all people living in a country" or "every atom composing a crystal". Statistics deals with every aspect of data, including the planning of data collection in terms of the design of statistical survey, surveys and experimental design, experiments.Dodge, Y. (2006) ''The Oxford Dictionary of Statistical Terms'', Oxford University Press. When census data cannot be collected, statisticians collect data by developing specific experiment designs and survey sample (statistics), samples. Representative sampling as ...
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Variance
In probability theory and statistics, variance is the expectation of the squared deviation of a random variable from its population mean or sample mean. Variance is a measure of dispersion, meaning it is a measure of how far a set of numbers is spread out from their average value. Variance has a central role in statistics, where some ideas that use it include descriptive statistics, statistical inference, hypothesis testing, goodness of fit, and Monte Carlo sampling. Variance is an important tool in the sciences, where statistical analysis of data is common. The variance is the square of the standard deviation, the second central moment of a distribution, and the covariance of the random variable with itself, and it is often represented by \sigma^2, s^2, \operatorname(X), V(X), or \mathbb(X). An advantage of variance as a measure of dispersion is that it is more amenable to algebraic manipulation than other measures of dispersion such as the expected absolute deviation; for e ...
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Hemodynamics
Hemodynamics or haemodynamics are the dynamics of blood flow. The circulatory system is controlled by homeostatic mechanisms of autoregulation, just as hydraulic circuits are controlled by control systems. The hemodynamic response continuously monitors and adjusts to conditions in the body and its environment. Hemodynamics explains the physical laws that govern the flow of blood in the blood vessels. Blood flow ensures the transportation of nutrients, hormones, metabolic waste products, oxygen, and carbon dioxide throughout the body to maintain cell-level metabolism, the regulation of the pH, osmotic pressure and temperature of the whole body, and the protection from microbial and mechanical harm. Blood is a non-Newtonian fluid, and is most efficiently studied using rheology rather than hydrodynamics. Because blood vessels are not rigid tubes, classic hydrodynamics and fluids mechanics based on the use of classical viscometers are not capable of explaining haemodynamics. The st ...
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Neuron
A neuron, neurone, or nerve cell is an electrically excitable cell that communicates with other cells via specialized connections called synapses. The neuron is the main component of nervous tissue in all animals except sponges and placozoa. Non-animals like plants and fungi do not have nerve cells. Neurons are typically classified into three types based on their function. Sensory neurons respond to stimuli such as touch, sound, or light that affect the cells of the sensory organs, and they send signals to the spinal cord or brain. Motor neurons receive signals from the brain and spinal cord to control everything from muscle contractions to glandular output. Interneurons connect neurons to other neurons within the same region of the brain or spinal cord. When multiple neurons are connected together, they form what is called a neural circuit. A typical neuron consists of a cell body (soma), dendrites, and a single axon. The soma is a compact structure, and the axon and dend ...
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