Related Research Articles
Functional 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.
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.
Functional near-infrared spectroscopy (fNIRS) is an optical brain monitoring technique which uses near-infrared spectroscopy for the purpose of functional neuroimaging. Using fNIRS, brain activity is measured by using near-infrared light to estimate cortical hemodynamic activity which occur in response to neural activity. Alongside EEG, fNIRS is one of the most common non-invasive neuroimaging techniques which can be used in portable contexts. The signal is often compared with the BOLD signal measured by fMRI and is capable of measuring changes both in oxy- and deoxyhemoglobin concentration, but can only measure from regions near the cortical surface. fNIRS may also be referred to as Optical Topography (OT) and is sometimes referred to simply as NIRS.
The posterior cingulate cortex (PCC) is the caudal part of the cingulate cortex, located posterior to the anterior cingulate cortex. This is the upper part of the "limbic lobe". The cingulate cortex is made up of an area around the midline of the brain. Surrounding areas include the retrosplenial cortex and the precuneus.
Event-related functional magnetic resonance imaging (efMRI) is a technique used in magnetic resonance imaging of medical patients.
Connectomics is the production and study of connectomes: comprehensive maps of connections within an organism's nervous system. More generally, it can be thought of as the study of neuronal wiring diagrams with a focus on how structural connectivity, individual synapses, cellular morphology, and cellular ultrastructure contribute to the make up of a network. The nervous system is a network made of billions of connections and these connections are responsible for our thoughts, emotions, actions, memories, function and dysfunction. Therefore, the study of connectomics aims to advance our understanding of mental health and cognition by understanding how cells in the nervous system are connected and communicate. Because these structures are extremely complex, methods within this field use a high-throughput application of functional and structural neural imaging, most commonly magnetic resonance imaging (MRI), electron microscopy, and histological techniques in order to increase the speed, efficiency, and resolution of these nervous system maps. To date, tens of large scale datasets have been collected spanning the nervous system including the various areas of cortex, cerebellum, the retina, the peripheral nervous system and neuromuscular junctions.
In neuroscience, the default mode network (DMN), also known as the default network, default state network, or anatomically the medial frontoparietal network (M-FPN), is a large-scale brain network primarily composed of the dorsal medial prefrontal cortex, posterior cingulate cortex, precuneus and angular gyrus. It is best known for being active when a person is not focused on the outside world and the brain is at wakeful rest, such as during daydreaming and mind-wandering. It can also be active during detailed thoughts related to external task performance. Other times that the DMN is active include when the individual is thinking about others, thinking about themselves, remembering the past, and planning for the future.
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.
Resting state fMRI is a method of functional magnetic resonance imaging (fMRI) that is used in brain mapping to evaluate regional interactions that occur in a resting or task-negative state, when an explicit task is not being performed. A number of resting-state brain networks have been identified, one of which is the default mode network. These brain networks are observed through changes in blood flow in the brain which creates what is referred to as a blood-oxygen-level dependent (BOLD) signal that can be measured using fMRI.
The following outline is provided as an overview of and topical guide to brain mapping:
Dynamic functional connectivity (DFC) refers to the observed phenomenon that functional connectivity changes over a short time. Dynamic functional connectivity is a recent expansion on traditional functional connectivity analysis which typically assumes that functional networks are static in time. DFC is related to a variety of different neurological disorders, and has been suggested to be a more accurate representation of functional brain networks. The primary tool for analyzing DFC is fMRI, but DFC has also been observed with several other mediums. DFC is a recent development within the field of functional neuroimaging whose discovery was motivated by the observation of temporal variability in the rising field of steady state connectivity research.
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.
Large-scale brain networks are collections of widespread brain regions showing functional connectivity by statistical analysis of the fMRI BOLD signal or other recording methods such as EEG, PET and MEG. An emerging paradigm in neuroscience is that cognitive tasks are performed not by individual brain regions working in isolation but by networks consisting of several discrete brain regions that are said to be "functionally connected". Functional connectivity networks may be found using algorithms such as cluster analysis, spatial independent component analysis (ICA), seed based, and others. Synchronized brain regions may also be identified using long-range synchronization of the EEG, MEG, or other dynamic brain signals.
Russell "Russ" Alan Poldrack is an American psychologist and neuroscientist. He is a professor of psychology at Stanford University, associate director of Stanford Data Science, member of the Stanford Neuroscience Institute and director of the Stanford Center for Reproducible Neuroscience and the SDS Center for Open and Reproducible Science.
Dynamic causal modeling (DCM) is a framework for specifying models, fitting them to data and comparing their evidence using Bayesian model comparison. It uses nonlinear state-space models in continuous time, specified using stochastic or ordinary differential equations. DCM was initially developed for testing hypotheses about neural dynamics. In this setting, differential equations describe the interaction of neural populations, which directly or indirectly give rise to functional neuroimaging data e.g., functional magnetic resonance imaging (fMRI), magnetoencephalography (MEG) or electroencephalography (EEG). Parameters in these models quantify the directed influences or effective connectivity among neuronal populations, which are estimated from the data using Bayesian statistical methods.
Brain–body interactions are patterns of neural activity in the central nervous system to coordinate the activity between the brain and body. The nervous system consists of central and peripheral nervous systems and coordinates the actions of an animal by transmitting signals to and from different parts of its body. The brain and spinal cord are interwoven with the body and interact with other organ systems through the somatic, autonomic and enteric nervous systems. Neural pathways regulate brain–body interactions and allow to sense and control its body and interact with the environment.
Neuro-Information-Systems (NeuroIS) is a subfield of the information systems (IS) discipline, which relies on neuroscience and neurophysiological knowledge and tools to better understand the development, use, and impact of information and communication technologies. The field has been formally established at the International Conference on Information Systems (ICIS) in 2007.
Network neuroscience is an approach to understanding the structure and function of the human brain through an approach of network science, through the paradigm of graph theory. A network is a connection of many brain regions that interact with each other to give rise to a particular function. Network Neuroscience is a broad field that studies the brain in an integrative way by recording, analyzing, and mapping the brain in various ways. The field studies the brain at multiple scales of analysis to ultimately explain brain systems, behavior, and dysfunction of behavior in psychiatric and neurological diseases. Network neuroscience provides an important theoretical base for understanding neurobiological systems at multiple scales of analysis.
Functional MRI imaging methods have allowed researchers to combine neurocognitive testing with structural neuroanatomical measures, take into consideration both cognitive and affective paradigms, and subsequently create computer-aided diagnosis techniques and algorithms. Functional MRI has several benefits, such as its non-invasive quality, relatively high spatial resolution, and decent temporal resolution. One particular method used in recent research is resting-state functional magnetic resonance imaging, rs-fMRI. fMRI imaging has been applied to numerous behavioral studies for schizophrenia, the findings of which have hinted toward potential brain regions that govern key characteristics in cognition and affect.
References
- 1 2 Friston KJ, Buechel C, Fink GR, Morris J, Rolls E, Dolan RJ (October 1997). "Psychophysiological and modulatory interactions in neuroimaging". NeuroImage. 6 (3): 218–29. CiteSeerX 10.1.1.8.1112 . doi:10.1006/nimg.1997.0291. PMID 9344826.
- ↑ Friston KJ (January 2011). "Functional and effective connectivity: a review". Brain Connectivity. 1 (1): 13–36. CiteSeerX 10.1.1.222.9471 . doi:10.1089/brain.2011.0008. PMID 22432952.
- ↑ O'Reilly JX, Woolrich MW, Behrens TE, Smith SM, Johansen-Berg H (June 2012). "Tools of the trade: psychophysiological interactions and functional connectivity". Social Cognitive and Affective Neuroscience. 7 (5): 604–9. doi:10.1093/scan/nss055. PMC 3375893 . PMID 22569188.
- ↑ Gitelman, Darren; Penny, William; Ashburner, John; Friston, Karl (2003). "Modeling regional and psychophysiologic interactions in fMRI: the importance of hemodynamic deconvolution". NeuroImage. 19 (1): 200–207. doi:10.1016/S1053-8119(03)00058-2.
- ↑ Di X, Reynolds RC, Biswal BB (April 2017). "Imperfect (de)convolution may introduce spurious psychophysiological interactions and how to avoid it". Human Brain Mapping. 38 (4): 1723–1740. doi: 10.1002/hbm.23413 . PMC 6866926 . PMID 28105655.
- ↑ McLaren DG, Ries ML, Xu G, Johnson SC (July 2012). "A generalized form of context-dependent psychophysiological interactions (gPPI): a comparison to standard approaches". NeuroImage. 61 (4): 1277–86. doi:10.1016/j.neuroimage.2012.03.068. PMC 3376181 . PMID 22484411.
- ↑ Di X, Biswal BB (April 2019). "Toward Task Connectomics: Examining Whole-Brain Task Modulated Connectivity in Different Task Domains". Cerebral Cortex. 29 (4): 1572–1583. doi:10.1093/cercor/bhy055. PMC 7302740 . PMID 29931116.
 | This neuroscience article is a stub. You can help Wikipedia by expanding it. |