Neurolinguistics is the study of the neural mechanisms in the human brain that control the comprehension, production, and acquisition of language. As an interdisciplinary field, neurolinguistics draws methods and theories from fields such as neuroscience, linguistics, cognitive science, communication disorders and neuropsychology. Researchers are drawn to the field from a variety of backgrounds, bringing along a variety of experimental techniques as well as widely varying theoretical perspectives. Much work in neurolinguistics is informed by models in psycholinguistics and theoretical linguistics, and is focused on investigating how the brain can implement the processes that theoretical and psycholinguistics propose are necessary in producing and comprehending language. Neurolinguists study the physiological mechanisms by which the brain processes information related to language, and evaluate linguistic and psycholinguistic theories, using aphasiology, brain imaging, electrophysiology, and computer modeling.
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 neuroimaging is the use of neuroimaging technology to measure an aspect of brain function, often with a view to understanding the relationship between activity in certain brain areas and specific mental functions. It is primarily used as a research tool in cognitive neuroscience, cognitive psychology, neuropsychology, and social neuroscience.
Brodmann area 9, or BA9, is part of the frontal cortex in the brain of humans and other primates. It contributes to the dorsolateral and medial prefrontal cortex.
An event-related potential (ERP) is the measured brain response that is the direct result of a specific sensory, cognitive, or motor event. More formally, it is any stereotyped electrophysiological response to a stimulus. The study of the brain in this way provides a noninvasive means of evaluating brain functioning.
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.
Social neuroscience is an interdisciplinary field devoted to understanding the relationship between social experiences and biological systems. Humans are fundamentally a social species, rather than individualists. As such, Homo sapiens create emergent organizations beyond the individual—structures that range from dyads, families, and groups to cities, civilizations, and cultures. In this regard, studies indicate that various social influences including life events, poverty, unemployment and loneliness can influence health related biomarkers. The term "social neuroscience" can be traced to a publication entitled "Social Neuroscience Bulletin" that was published quarterly between 1988 and 1994. The term was subsequently popularized in an article by John Cacioppo and Gary Berntson, published in the American Psychologist in 1992. Cacioppo and Berntson are considered as the legitimate fathers of social neuroscience. Still a young field, social neuroscience is closely related to affective neuroscience and cognitive neuroscience, focusing on how the brain mediates social interactions. The biological underpinnings of social cognition are investigated in social cognitive neuroscience.
Sensory neuroscience is a subfield of neuroscience which explores the anatomy and physiology of neurons that are part of sensory systems such as vision, hearing, and olfaction. Neurons in sensory regions of the brain respond to stimuli by firing one or more nerve impulses following stimulus presentation. How is information about the outside world encoded by the rate, timing, and pattern of action potentials? This so-called neural code is currently poorly understood and sensory neuroscience plays an important role in the attempt to decipher it. Looking at early sensory processing is advantageous since brain regions that are "higher up" contain neurons which encode more abstract representations. However, the hope is that there are unifying principles which govern how the brain encodes and processes information. Studying sensory systems is an important stepping stone in our understanding of brain function in general.
Repetition priming refers to improvements in a behavioural response when stimuli are repeatedly presented. The improvements can be measured in terms of accuracy or reaction time, and can occur when the repeated stimuli are either identical or similar to previous stimuli. These improvements have been shown to be cumulative, so as the number of repetitions increases the responses get continually faster up to a maximum of around seven repetitions. These improvements are also found when the repeated items are changed slightly in terms of orientation, size and position. The size of the effect is also modulated by the length of time the item is presented for and the length time between the first and subsequent presentations of the repeated items.
Integrative neuroscience is the study of neuroscience that works to unify functional organization data to better understand complex structures and behaviors. The relationship between structure and function, and how the regions and functions connect to each other. Different parts of the brain carrying out different tasks, interconnecting to come together allowing complex behavior. Integrative neuroscience works to fill gaps in knowledge that can largely be accomplished with data sharing, to create understanding of systems, currently being applied to simulation neuroscience: Computer Modeling of the brain that integrates functional groups together.
Presentation is a Windows software application for conducting psychological and neurobehavioral experiments, developed by Neurobehavioral Systems Inc. and first released in 2003. It supports auditory and visual stimuli creation and delivery, records responses from nearly any input device and allows control of parallel port, serial port, TCP/IP and Ni-DAQ for communication to and from fMRI devices, response devices, eye trackers and brain imaging equipment. It also supports Microsoft Kinect for Windows. It is temporally accurate to less than a millisecond. Presentation has over 10,000 users worldwide. Presentation supports Unicode via the utf-8 specification.
Auditory spatial attention is a specific form of attention, involving the focusing of auditory perception to a location in space.
Difference due to memory (Dm) indexes differences in neural activity during the study phase of an experiment for items that subsequently are remembered compared to items that are later forgotten. It is mainly discussed as an event-related potential (ERP) effect that appears in studies employing a subsequent memory paradigm, in which ERPs are recorded when a participant is studying a list of materials and trials are sorted as a function of whether they go on to be remembered or not in the test phase. For meaningful study material, such as words or line drawings, items that are subsequently remembered typically elicit a more positive waveform during the study phase. This difference typically occurs in the range of 400–800 milliseconds (ms) and is generally greatest over centro-parietal recording sites, although these characteristics are modulated by many factors.
The visual N1 is a visual evoked potential, a type of event-related electrical potential (ERP), that is produced in the brain and recorded on the scalp. The N1 is so named to reflect the polarity and typical timing of the component. The "N" indicates that the polarity of the component is negative with respect to an average mastoid reference. The "1" originally indicated that it was the first negative-going component, but it now better indexes the typical peak of this component, which is around 150 to 200 milliseconds post-stimulus. The N1 deflection may be detected at most recording sites, including the occipital, parietal, central, and frontal electrode sites. Although, the visual N1 is widely distributed over the entire scalp, it peaks earlier over frontal than posterior regions of the scalp, suggestive of distinct neural and/or cognitive correlates. The N1 is elicited by visual stimuli, and is part of the visual evoked potential – a series of voltage deflections observed in response to visual onsets, offsets, and changes. Both the right and left hemispheres generate an N1, but the laterality of the N1 depends on whether a stimulus is presented centrally, laterally, or bilaterally. When a stimulus is presented centrally, the N1 is bilateral. When presented laterally, the N1 is larger, earlier, and contralateral to the visual field of the stimulus. When two visual stimuli are presented, one in each visual field, the N1 is bilateral. In the latter case, the N1's asymmetrical skewedness is modulated by attention. Additionally, its amplitude is influenced by selective attention, and thus it has been used to study a variety of attentional processes.
The oddball paradigm is an experimental design used within psychology research. Presentations of sequences of repetitive stimuli are infrequently interrupted by a deviant stimulus. The reaction of the participant to this "oddball" stimulus is recorded.
Linguistic prediction is a phenomenon in psycholinguistics occurring whenever information about a word or other linguistic unit is activated before that unit is actually encountered. Evidence from eyetracking, event-related potentials, and other experimental methods indicates that in addition to integrating each subsequent word into the context formed by previously encountered words, language users may, under certain conditions, try to predict upcoming words. In particular, prediction seems to occur regularly when the context of a sentence greatly limits the possible words that have not yet been revealed. For instance, a person listening to a sentence like, "In the summer it is hot, and in the winter it is..." would be highly likely to predict the sentence completion "cold" in advance of actually hearing it. A form of prediction is also thought to occur in some types of lexical priming, a phenomenon whereby a word becomes easier to process if it is preceded by a related word. Linguistic prediction is an active area of research in psycholinguistics and cognitive neuroscience.
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 conditions are identified in the brain, one of which is the default mode network. These resting brain state conditions 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.
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.
