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The putamen is a round structure located at the base of the forebrain (telencephalon). The putamen and caudate nucleus together form the dorsal striatum. It is also one of the structures that compose the basal nuclei. Through various pathways, the putamen is connected to the substantia nigra, the globus pallidus, the claustrum, and the thalamus, in addition to many regions of the cerebral cortex. A primary function of the putamen is to regulate movements at various stages and influence various types of learning. It employs GABA, acetylcholine, and enkephalin to perform its functions. The putamen also plays a role in degenerative neurological disorders, such as Parkinson's disease.
A meta-analysis is a statistical analysis that combines the results of multiple scientific studies. Meta-analyses can be performed when there are multiple scientific studies addressing the same question, with each individual study reporting measurements that are expected to have some degree of error. The aim then is to use approaches from statistics to derive a pooled estimate closest to the unknown common truth based on how this error is perceived. It is thus a basic methodology of Metascience. Meta-analytic results are considered the most trustworthy source of evidence by the evidence-based medicine literature.
The caudate nucleus is one of the structures that make up the corpus striatum, which is a component of the basal ganglia in the human brain. While the caudate nucleus has long been associated with motor processes due to its role in Parkinson's disease, it plays important roles in various other nonmotor functions as well, including procedural learning, associative learning and inhibitory control of action, among other functions. The caudate is also one of the brain structures which compose the reward system and functions as part of the cortico–basal ganglia–thalamic loop.
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.
Functional integration is the study of how brain regions work together to process information and effect responses. Though functional integration frequently relies on anatomic knowledge of the connections between brain areas, the emphasis is on how large clusters of neurons – numbering in the thousands or millions – fire together under various stimuli. The large datasets required for such a whole-scale picture of brain function have motivated the development of several novel and general methods for the statistical analysis of interdependence, such as dynamic causal modelling and statistical linear parametric mapping. These datasets are typically gathered in human subjects by non-invasive methods such as EEG/MEG, fMRI, or PET. The results can be of clinical value by helping to identify the regions responsible for psychiatric disorders, as well as to assess how different activities or lifestyles affect the functioning of the brain.
Analysis of Functional NeuroImages (AFNI) is an open-source environment for processing and displaying functional MRI data—a technique for mapping human brain activity.
In statistics, (between-) study heterogeneity is a phenomenon that commonly occurs when attempting to undertake a meta-analysis. In a simplistic scenario, studies whose results are to be combined in the meta-analysis would all be undertaken in the same way and to the same experimental protocols. Differences between outcomes would only be due to measurement error. Study heterogeneity denotes the variability in outcomes that goes beyond what would be expected due to measurement error alone.
Talairach coordinates, also known as Talairach space, is a 3-dimensional coordinate system of the human brain, which is used to map the location of brain structures independent from individual differences in the size and overall shape of the brain. It is still common to use Talairach coordinates in functional brain imaging studies and to target transcranial stimulation of brain regions. However, alternative methods such as the MNI Coordinate System have largely replaced Talairach for stereotaxy and other procedures.
Voxel-based morphometry is a computational approach to neuroanatomy that measures differences in local concentrations of brain tissue, through a voxel-wise comparison of multiple brain images.
In statistics, Fisher's method, also known as Fisher's combined probability test, is a technique for data fusion or "meta-analysis" (analysis of analyses). It was developed by and named for Ronald Fisher. In its basic form, it is used to combine the results from several independence tests bearing upon the same overall hypothesis (H0).
A plot is a graphical technique for representing a data set, usually as a graph showing the relationship between two or more variables. The plot can be drawn by hand or by a computer. In the past, sometimes mechanical or electronic plotters were used. Graphs are a visual representation of the relationship between variables, which are very useful for humans who can then quickly derive an understanding which may not have come from lists of values. Given a scale or ruler, graphs can also be used to read off the value of an unknown variable plotted as a function of a known one, but this can also be done with data presented in tabular form. Graphs of functions are used in mathematics, sciences, engineering, technology, finance, and other areas.
The biology of obsessive–compulsive disorder (OCD) refers biologically based theories about the mechanism of OCD. Cognitive models generally fall into the category of executive dysfunction or modulatory control. Neuroanatomically, functional and structural neuroimaging studies implicate the prefrontal cortex (PFC), basal ganglia (BG), insula, and posterior cingulate cortex (PCC). Genetic and neurochemical studies implicate glutamate and monoamine neurotransmitters, especially serotonin and dopamine.
Brain morphometry is a subfield of both morphometry and the brain sciences, concerned with the measurement of brain structures and changes thereof during development, aging, learning, disease and evolution. Since autopsy-like dissection is generally impossible on living brains, brain morphometry starts with noninvasive neuroimaging data, typically obtained from magnetic resonance imaging (MRI). These data are born digital, which allows researchers to analyze the brain images further by using advanced mathematical and statistical methods such as shape quantification or multivariate analysis. This allows researchers to quantify anatomical features of the brain in terms of shape, mass, volume, and to derive more specific information, such as the encephalization quotient, grey matter density and white matter connectivity, gyrification, cortical thickness, or the amount of cerebrospinal fluid. These variables can then be mapped within the brain volume or on the brain surface, providing a convenient way to assess their pattern and extent over time, across individuals or even between different biological species. The field is rapidly evolving along with neuroimaging techniques—which deliver the underlying data—but also develops in part independently from them, as part of the emerging field of neuroinformatics, which is concerned with developing and adapting algorithms to analyze those data.
Karl John Friston FRS FMedSci FRSB is a British neuroscientist and theoretician at University College London. He is an authority on brain imaging and theoretical neuroscience, especially the use of physics-inspired statistical methods to model neuroimaging data and other random dynamical systems. He is a key architect of the free energy principle and active inference. In imaging neuroscience he is best known for statistical parametric mapping and dynamic causal modelling. In October 2022, he joined VERSES Inc, a California-based cognitive computing company focusing on artificial intelligence designed using the principles of active inference, as Chief Scientist.
Meta-regression is defined to be a meta-analysis that uses regression analysis to combine, compare, and synthesize research findings from multiple studies while adjusting for the effects of available covariates on a response variable. A meta-regression analysis aims to reconcile conflicting studies or corroborate consistent ones; a meta-regression analysis is therefore characterized by the collated studies and their corresponding data sets—whether the response variable is study-level data or individual participant data. A data set is aggregate when it consists of summary statistics such as the sample mean, effect size, or odds ratio. On the other hand, individual participant data are in a sense raw in that all observations are reported with no abridgment and therefore no information loss. Aggregate data are easily compiled through internet search engines and therefore not expensive. However, individual participant data are usually confidential and are only accessible within the group or organization that performed the studies.
Medical 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.
Peter T. Fox is a neuroimaging researcher and neurologist at the University of Texas Health Science Center at San Antonio. He is a professor in the Department of Radiology with joint appointments in Radiology, Medicine, and Psychiatry. He is the founding director of the Research Imaging Institute.
CONN is a Matlab-based cross-platform imaging software for the computation, display, and analysis of functional connectivity in fMRI in the resting state and during task.
Joaquim Radua is a Spanish psychiatrist and developer of methods for meta-analysis of neuroimaging studies. He has been named as one of the most cited researchers in Psychiatry / Psychology.
References
- 1 2 3 4 Radua, Joaquim; Mataix-Cols, David (1 November 2009). "Voxel-wise meta-analysis of grey matter changes in obsessive–compulsive disorder". The British Journal of Psychiatry. 195 (5): 393–402. doi: 10.1192/bjp.bp.108.055046 . PMID 19880927.
- 1 2 3 4 Radua, Joaquim; Mataix-Cols, David; Phillips, Mary L.; El-Hage, Wissam; Kronhaus, Dina M.; Cardoner, Narcís; Surguladze, Simon. "A new meta-analytic method for neuroimaging studies that combines reported peak coordinates and statistical parametric maps". European Psychiatry. 27: 605–611. doi:10.1016/j.eurpsy.2011.04.001.
- ↑ Radua, Joaquim; Via, Esther; Catani, Marco; Mataix-Cols, David (2010). "Voxel-based meta-analysis of regional white-matter volume differences in autism spectrum disorder versus healthy controls". Psychological Medicine. 41: 1–12. doi:10.1017/S0033291710002187. PMID 21078227.
- ↑ Radua, Joaquim; van den Heuvel, Odile A.; Surguladze, Simon; Mataix-Cols, David (5 July 2010). "Meta-analytical comparison of voxel-based morphometry studies in obsessive-compulsive disorder vs other anxiety disorders". Archives of General Psychiatry. 67 (7): 701–711. doi:10.1001/archgenpsychiatry.2010.70. PMID 20603451.