Magnetic resonance imagingMagnetic 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 computed tomography (CT) and positron emission tomography (PET) scans.
Cognitive impairmentCognitive impairment is an inclusive term to describe any characteristic that acts as a barrier to the cognition process or different areas of cognition. Cognition, also known as cognitive function, refers to the mental processes of how a person gains knowledge, uses existing knowledge, and understands things that are happening around them using their thoughts and senses. A cognitive impairment can be in different domains or aspects of a person's cognitive function including memory, attention span, planning, reasoning, decision-making, language (comprehension, writing, speech), executive functioning, and visuospatial functioning.
Mild cognitive impairmentMild cognitive impairment (MCI) is a neurocognitive disorder which involves cognitive impairments beyond those expected based on an individual's age and education but which are not significant enough to interfere with instrumental activities of daily living. MCI may occur as a transitional stage between normal aging and dementia, especially Alzheimer's disease. It includes both memory and non-memory impairments.
Support vector machineIn machine learning, support vector machines (SVMs, also support vector networks) are supervised learning models with associated learning algorithms that analyze data for classification and regression analysis. Developed at AT&T Bell Laboratories by Vladimir Vapnik with colleagues (Boser et al., 1992, Guyon et al., 1993, Cortes and Vapnik, 1995, Vapnik et al., 1997) SVMs are one of the most robust prediction methods, being based on statistical learning frameworks or VC theory proposed by Vapnik (1982, 1995) and Chervonenkis (1974).
Functional magnetic resonance imagingFunctional magnetic resonance imaging or functional MRI (fMRI) measures brain activity by detecting changes associated with blood flow. This technique relies on the fact that cerebral blood flow and neuronal activation are coupled. When an area of the brain is in use, blood flow to that region also increases. The primary form of fMRI uses the blood-oxygen-level dependent (BOLD) contrast, discovered by Seiji Ogawa in 1990.
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.
Medical image computingMedical image computing (MIC) is an interdisciplinary field at the intersection of computer science, information engineering, electrical engineering, physics, mathematics and medicine. This field develops computational and mathematical methods for solving problems pertaining to medical images and their use for biomedical research and clinical care. The main goal of MIC is to extract clinically relevant information or knowledge from medical images.
Computer-aided diagnosisComputer-aided detection (CADe), also called computer-aided diagnosis (CADx), are systems that assist doctors in the interpretation of medical images. Imaging techniques in X-ray, MRI, Endoscopy, and ultrasound diagnostics yield a great deal of information that the radiologist or other medical professional has to analyze and evaluate comprehensively in a short time. CAD systems process digital images or videos for typical appearances and to highlight conspicuous sections, such as possible diseases, in order to offer input to support a decision taken by the professional.
Diffusion MRIDiffusion-weighted magnetic resonance imaging (DWI or DW-MRI) is the use of specific MRI sequences as well as software that generates images from the resulting data that uses the diffusion of water molecules to generate contrast in MR images. It allows the mapping of the diffusion process of molecules, mainly water, in biological tissues, in vivo and non-invasively. Molecular diffusion in tissues is not random, but reflects interactions with many obstacles, such as macromolecules, fibers, and membranes.
MyelinIn most vertebrates (including humans), myelin is a lipid-rich material that surrounds nerve cell axons (the nervous system's "wires") to insulate them and increase the rate at which electrical impulses (called action potentials) are passed along the axon. The myelinated axon can be likened to an electrical wire (the axon) with insulating material (myelin) around it. However, unlike the plastic covering on an electrical wire, myelin does not form a single long sheath over the entire length of the axon.
Aging brainAging of the brain is a process of transformation of the brain in older age, including changes all individuals experience and those of illness (including unrecognised illness). Usually this refers to humans. Since life extension is only pertinent if accompanied by health span extension, and, more importantly, by preserving brain health and cognition, finding rejuvenating approaches that act simultaneously in peripheral tissues and in brain function is a key strategy for development of rejuvenating technology.
Executive functionsIn cognitive science and neuropsychology, executive functions (collectively referred to as executive function and cognitive control) are a set of cognitive processes that are necessary for the cognitive control of behavior: selecting and successfully monitoring behaviors that facilitate the attainment of chosen goals. Executive functions include basic cognitive processes such as attentional control, cognitive inhibition, inhibitory control, working memory, and cognitive flexibility.
Nucleus accumbensThe nucleus accumbens (NAc or NAcc; also known as the accumbens nucleus, or formerly as the nucleus accumbens septi, Latin for "nucleus adjacent to the septum") is a region in the basal forebrain rostral to the preoptic area of the hypothalamus. The nucleus accumbens and the olfactory tubercle collectively form the ventral striatum. The ventral striatum and dorsal striatum collectively form the striatum, which is the main component of the basal ganglia.
Pedunculopontine nucleusThe pedunculopontine nucleus (PPN) or pedunculopontine tegmental nucleus (PPT or PPTg) is a collection of neurons located in the upper pons in the brainstem. It lies caudal to the substantia nigra and adjacent to the superior cerebellar peduncle. It has two divisions of subnuclei; the pars compacta containing mainly cholinergic neurons, and the pars dissipata containing mainly glutamatergic neurons and some non-cholinergic neurons. The pedunculopontine nucleus is one of the main components of the reticular activating system.
Basal gangliaThe basal ganglia (BG), or basal nuclei, are a group of subcortical nuclei, of varied origin, in the brains of vertebrates. In humans, and some primates, there are some differences, mainly in the division of the globus pallidus into an external and internal region, and in the division of the striatum. The basal ganglia are situated at the base of the forebrain and top of the midbrain. Basal ganglia are strongly interconnected with the cerebral cortex, thalamus, and brainstem, as well as several other brain areas.
Human brainThe human brain is the central organ of the human nervous system, and with the spinal cord makes up the central nervous system. The brain consists of the cerebrum, the brainstem and the cerebellum. It controls most of the activities of the body, processing, integrating, and coordinating the information it receives from the sense organs, and making decisions as to the instructions sent to the rest of the body. The brain is contained in, and protected by, the skull bones of the head.
Magnetic resonance angiographyMagnetic resonance angiography (MRA) is a group of techniques based on magnetic resonance imaging (MRI) to image blood vessels. Magnetic resonance angiography is used to generate images of arteries (and less commonly veins) in order to evaluate them for stenosis (abnormal narrowing), occlusions, aneurysms (vessel wall dilatations, at risk of rupture) or other abnormalities. MRA is often used to evaluate the arteries of the neck and brain, the thoracic and abdominal aorta, the renal arteries, and the legs (the latter exam is often referred to as a "run-off").
Multiclass classificationIn machine learning and statistical classification, multiclass classification or multinomial classification is the problem of classifying instances into one of three or more classes (classifying instances into one of two classes is called binary classification). While many classification algorithms (notably multinomial logistic regression) naturally permit the use of more than two classes, some are by nature binary algorithms; these can, however, be turned into multinomial classifiers by a variety of strategies.
Cognitive neuroscienceCognitive neuroscience is the scientific field that is concerned with the study of the biological processes and aspects that underlie cognition, with a specific focus on the neural connections in the brain which are involved in mental processes. It addresses the questions of how cognitive activities are affected or controlled by neural circuits in the brain. Cognitive neuroscience is a branch of both neuroscience and psychology, overlapping with disciplines such as behavioral neuroscience, cognitive psychology, physiological psychology and affective neuroscience.
Linear classifierIn the field of machine learning, the goal of statistical classification is to use an object's characteristics to identify which class (or group) it belongs to. A linear classifier achieves this by making a classification decision based on the value of a linear combination of the characteristics. An object's characteristics are also known as feature values and are typically presented to the machine in a vector called a feature vector.
