Deep brain stimulation (DBS) is a surgical procedure that implants a neurostimulator and electrodes which sends electrical impulses to specified targets in the brain responsible for movement control. The treatment is designed for a range of movement disorders such as Parkinson's disease, essential tremor, and dystonia, as well as for certain neuropsychiatric conditions like obsessive-compulsive disorder (OCD) and epilepsy. The exact mechanisms of DBS are complex and not entirely clear, but it is known to modify brain activity in a structured way.
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.
Electrocorticography (ECoG), a type of intracranial electroencephalography (iEEG), is a type of electrophysiological monitoring that uses electrodes placed directly on the exposed surface of the brain to record electrical activity from the cerebral cortex. In contrast, conventional electroencephalography (EEG) electrodes monitor this activity from outside the skull. ECoG may be performed either in the operating room during surgery or outside of surgery. Because a craniotomy is required to implant the electrode grid, ECoG is an invasive procedure.
FreeSurfer is brain imaging software originally developed by Bruce Fischl, Anders Dale, Martin Sereno, and Doug Greve. Development and maintenance of FreeSurfer is now the primary responsibility of the Laboratory for Computational Neuroimaging at the Athinoula A. Martinos Center for Biomedical Imaging. FreeSurfer contains a set of programs with a common focus of analyzing magnetic resonance imaging (MRI) scans of brain tissue. It is an important tool in functional brain mapping and contains tools to conduct both volume based and surface based analysis. FreeSurfer includes tools for the reconstruction of topologically correct and geometrically accurate models of both the gray/white and pial surfaces, for measuring cortical thickness, surface area and folding, and for computing inter-subject registration based on the pattern of cortical folds.
Helen S. Mayberg, is an American neurologist. Mayberg is known in particular for her work delineating abnormal brain function in patients with major depression using functional neuroimaging. This work led to the first pilot study of deep brain stimulation (DBS), a reversible method of selective modulation of a specific brain circuit, for patients with treatment-resistant depression. As of August 2019, she has published 211 original peer-reviewed articles, 31 books and book chapters, and acted as principal investigator on 24 research grants. Mayberg is coinventor with Andres Lozano of “Method for Treating Depression Mood Disorders and Anxiety Disorders using Neuromodulation,” US patent 2005/0033379A1. St. Jude Medical Neuromodulation licensed her intellectual property to develop Subcallosal Cingulate Deep Brain Stimulation for Treatment-Resistant Unipolar and Bipolar Depression for the treatment of severe depression. As of 2018, Mayberg holds positions as Professor of Neurology and Neurosurgery and Professor, Psychiatry and Neuroscience, both at Mount Sinai Medical School, and Professor of Psychiatry, Emory University; Emory University Hospital. Since 2018, she has served as Director, Nash Family Center for Advanced Circuit Therapeutics at the Icahn School of Medicine at Mount Sinai.
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.
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.
Mango is a non-commercial software for viewing, editing and analyzing volumetric medical images. Mango is written in Java, and distributed freely in precompiled versions for Linux, Mac OS and Microsoft Windows. It supports NIfTI, ANALYZE, NEMA and DICOM formats and is able to load and save 2D, 3D and 4D images.
Psychophysiological interaction (PPI) is a brain connectivity analysis method for functional brain imaging data, mainly functional magnetic resonance imaging (fMRI). It estimates context-dependent changes in effective connectivity (coupling) between brain regions. Thus, PPI analysis identifies brain regions whose activity depends on an interaction between psychological context and physiological state of the seed region.
Neurostimulation is the purposeful modulation of the nervous system's activity using invasive or non-invasive means. Neurostimulation usually refers to the electromagnetic approaches to neuromodulation.
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.
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.
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.
John-Dylan Haynes is a British-German brain researcher.
Social cognitive neuroscience is the scientific study of the biological processes underpinning social cognition. Specifically, it uses the tools of neuroscience to study "the mental mechanisms that create, frame, regulate, and respond to our experience of the social world". Social cognitive neuroscience uses the epistemological foundations of cognitive neuroscience, and is closely related to social neuroscience. Social cognitive neuroscience employs human neuroimaging, typically using functional magnetic resonance imaging (fMRI). Human brain stimulation techniques such as transcranial magnetic stimulation and transcranial direct-current stimulation are also used. In nonhuman animals, direct electrophysiological recordings and electrical stimulation of single cells and neuronal populations are utilized for investigating lower-level social cognitive processes.
Alfonso Nieto-Castanon is a Spanish computational neuroscientist and developer of computational neuroimaging analysis methods and tools. He is a visiting researcher at the Boston University College of Health and Rehabilitation Sciences, and research affiliate at MIT McGovern Institute for Brain Research. His research focuses on the understanding and characterization of human brain dynamics underlying mental function.
Adaptive Deep Brain Stimulation (aDBS), also known as Closed Loop Deep Brain stimulation (clDBS), is a neuro-modulatory technique currently under investigation for the treatment of neurodegenerative diseases.
Lesion network mapping is a neuroimaging technique that analyzes the connectivity pattern of brain lesions to identify neuroanatomic correlates of symptoms. The technique was developed by Michael D. Fox and Aaron Boes to understand the network anatomy of lesion induced neurologic and psychiatric symptoms that can not be explained by focal anatomic localization. Lesion network mapping applies a network-based approach to identify connected brain networks, rather than focal brain regions, that correlate with a specific symptom.
