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.
Common methods of functional neuroimaging include
PET, fMRI, fNIRS and fUS can measure localized changes in cerebral blood flow related to neural activity. These changes are referred to as activations. Regions of the brain which are activated when a subject performs a particular task may play a role in the neural computations which contribute to the behaviour. For instance, widespread activation of the occipital lobe is typically seen in tasks which involve visual stimulation (compared with tasks that do not). This part of the brain receives signals from the retina and is believed to play a role in visual perception.
Other methods of neuroimaging involve recording of electrical currents or magnetic fields, for example EEG and MEG. Different methods have different advantages for research; for instance, MEG measures brain activity with high temporal resolution (down to the millisecond level), but is limited in its ability to localize that activity. fMRI does a much better job of localizing brain activity for spatial resolution, but with a much lower time resolution [1] while functional ultrasound (fUS) can reach an interesting spatio-temporal resolution (down to 100 micrometer, 100 milliseconds, at 15 MHz in preclinical models) but is also limited by the neurovascular coupling.
Recently, Magnetic particle imaging has been proposed as a new sensitive imaging technique that has sufficient temporal resolution for functional neuroimaging based on the increase of cerebral blood volume. First pre-clinical trials have successfully demonstrated functional imaging in rodents. [2]
The measure used in a particular study is generally related to the particular question being addressed. Measurement limitations vary amongst the techniques. For instance, MEG and EEG record the magnetic or electrical fluctuations that occur when a population of neurons is active. These methods are excellent for measuring the time-course of neural events (on the order of milliseconds,) but generally bad at measuring where those events happen. PET and fMRI measure changes in the composition of blood near a neural event. Because measurable blood changes are slow (on the order of seconds), these methods are much worse at measuring the time-course of neural events, but are generally better at measuring the location.
Traditional "activation studies" focus on determining distributed patterns of brain activity associated with specific tasks. However, scientists are able to more thoroughly understand brain function by studying the interaction of distinct brain regions, as a great deal of neural processing is performed by an integrated network of several regions of the brain. An active area of neuroimaging research involves examining the functional connectivity of spatially remote brain regions. Functional connectivity analyses allow the characterization of interregional neural interactions during particular cognitive or motor tasks or merely from spontaneous activity during rest. FMRI and PET enable creation of functional connectivity maps of distinct spatial distributions of temporally correlated brain regions called functional networks. Several studies using neuroimaging techniques have also established that posterior visual areas in blind individuals may be active during the performance of nonvisual tasks such as Braille reading, memory retrieval, and auditory localization as well as other auditory functions. [3]
A direct method to measure functional connectivity is to observe how stimulation of one part of the brain will affect other areas. This can be done noninvasively in humans by combining transcranial magnetic stimulation with one of the neuroimaging tools such as PET, fMRI, or EEG. Massimini et al. (Science, September 30, 2005) used EEG to record how activity spreads from the stimulated site. They reported that in non-REM sleep, although the brain responds vigorously to stimulation, functional connectivity is much attenuated from its level during wakefulness. Thus, during deep sleep, "brain areas do not talk to each other".
Functional neuroimaging draws on data from many areas other than cognitive neuroscience and social neuroscience, including other biological sciences (such as neuroanatomy and neurophysiology), physics and maths, to further develop and refine the technology.
Functional neuroimaging studies have to be carefully designed and interpreted with care. Statistical analysis (often using a technique called statistical parametric mapping) is often needed so that the different sources of activation within the brain can be distinguished from one another. This can be particularly challenging when considering processes which are difficult to conceptualise or have no easily definable task associated with them (for example belief and consciousness).
Functional neuroimaging of interesting phenomena often gets cited in the press. In one case a group of prominent functional neuroimaging researchers felt compelled to write a letter to New York Times in response to an op-ed article about a study of so-called neuropolitics. [4] They argued that some of the interpretations of the study were "scientifically unfounded". [5]
The Hastings Center issued a report in March 2014 entitled "Interpreting Neuroimages: An Introduction to the Technology and Its Limits", [6] with articles by leading neuroscientists and bioethicists. The report briefly explains neuroimaging technologies and mostly critiques, but also somewhat defends, their current state, import and prospects.
Cognitive 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. Cognitive neuroscience relies upon theories in cognitive science coupled with evidence from neurobiology, and computational modeling.
Magnetoencephalography (MEG) is a functional neuroimaging technique for mapping brain activity by recording magnetic fields produced by electrical currents occurring naturally in the brain, using very sensitive magnetometers. Arrays of SQUIDs are currently the most common magnetometer, while the SERF magnetometer is being investigated for future machines. Applications of MEG include basic research into perceptual and cognitive brain processes, localizing regions affected by pathology before surgical removal, determining the function of various parts of the brain, and neurofeedback. This can be applied in a clinical setting to find locations of abnormalities as well as in an experimental setting to simply measure brain activity.
Neurolinguistics is the study of 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.
Rehabilitation of sensory and cognitive function typically involves methods for retraining neural pathways or training new neural pathways to regain or improve neurocognitive functioning that have been diminished by disease or trauma. The main objective outcome for rehabilitation is to assist in regaining physical abilities and improving performance. Three common neuropsychological problems treatable with rehabilitation are attention deficit/hyperactivity disorder (ADHD), concussion, and spinal cord injury. Rehabilitation research and practices are a fertile area for clinical neuropsychologists, rehabilitation psychologists, and others.
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.
Neurophilosophy or philosophy of neuroscience is the interdisciplinary study of neuroscience and philosophy that explores the relevance of neuroscientific studies to the arguments traditionally categorized as philosophy of mind. The philosophy of neuroscience attempts to clarify neuroscientific methods and results using the conceptual rigor and methods of philosophy of science.
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 solitary. 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" which 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 personality neuroscience, 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.
Neuroimaging is the use of quantitative (computational) techniques to study the structure and function of the central nervous system, developed as an objective way of scientifically studying the healthy human brain in a non-invasive manner. Increasingly it is also being used for quantitative research studies of brain disease and psychiatric illness. Neuroimaging is highly multidisciplinary involving neuroscience, computer science, psychology and statistics, and is not a medical specialty. Neuroimaging is sometimes confused with neuroradiology.
Neuroergonomics is the application of neuroscience to ergonomics. Traditional ergonomic studies rely predominantly on psychological explanations to address human factors issues such as: work performance, operational safety, and workplace-related risks. Neuroergonomics, in contrast, addresses the biological substrates of ergonomic concerns, with an emphasis on the role of the human nervous system.
Developmental cognitive neuroscience is an interdisciplinary scientific field devoted to understanding psychological processes and their neurological bases in the developing organism. It examines how the mind changes as children grow up, interrelations between that and how the brain is changing, and environmental and biological influences on the developing mind and brain.
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.
Robert Turner is a British neuroscientist, physicist, and social anthropologist. He has been a director and professor at the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig, Germany, and is an internationally recognized expert in brain physics and magnetic resonance imaging (MRI). Coils inside every MRI scanner owe their shape to his ideas.
Anders Martin Dale is a prominent neuroscientist and professor of radiology, neurosciences, psychiatry, and cognitive science at the University of California, San Diego (UCSD), and is one of the world's leading developers of sophisticated computational neuroimaging techniques. He is the founding Director of the Center for Multimodal Imaging Genetics (CMIG) at UCSD.
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.
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.
Neural synchrony is the correlation of brain activity across two or more people over time. In social and affective neuroscience, neural synchrony specifically refers to the degree of similarity between the spatio-temporal neural fluctuations of multiple people. This phenomenon represents the convergence and coupling of different people's neurocognitive systems, and it is thought to be the neural substrate for many forms of interpersonal dynamics and shared experiences. Some research also refers to neural synchrony as inter-brain synchrony, brain-to-brain coupling, inter-subject correlation, between-brain connectivity, or neural coupling. In the current literature, neural synchrony is notably distinct from intra-brain synchrony—sometimes also called neural synchrony—which denotes the coupling of activity across regions of a single individual's brain.
