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Neurotransmitter based imaging techniques

Neurotransmitter based imaging techniques



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All the brain imaging techniques I know fall into two categories:

  1. Tracking blood

    1. Either by looking at the magnetic (fMRI), or near-infared absorption (diffuse optical imaging, NIRS) properties of hemoglobin, or

    2. Injecting tracers into the blood stream (PET, SPECT)

  2. Tracking electric and magnetic fields in neurons (EEG, MEG).

The problem with the first approach is that it is fundamentally secondary in nature: it tracks the response of the vascular system to brain activity. Although the BOLD signal correlates well with neural activity, it is still an indirect indicator of firing rate, has time lags, and limited spatial (limited by distribution of capillaries) and temporal (limited by flow rate) resolution.

The second approach is better, but still not perfect from a pharmacology perspective. Although it gives us good information about the post-synaptic potential (EEG) or intraneuron potential (MEG), it still provides no information on specific neurotransmitters released. The approach also suffers from limitations on spatial resolution and the fact that EM-fields follow the superposition principle and thus it is mathematically impossible to reconstruct signals that interfere destructively outside the neuron but before the sensors.

The perfect approach for a pharmacologist would be to track individual types on neurotransmitters. Are there imagining techniques that use the resonance, absorption, or other properties of neurotransmitters (instead of hemoglobin)? Or is there a fundamental reason why this won't work?

I know that the same exact techniques as for hemoglobin won't work (since as far as I know most neurotransmitters don't contain nice things like iron to play with), but is there a reason other resonance or scattering techniques wouldn't work?


The closest work I know in this direction is the event-related optical signal (Gratton & Fabiani, 2001) because it tracks the light-scattering properties of something other than hemoglobin: neural tissue. Unfortunately, this is still tracking activity of the neuron and not neurotransmitters.


Resonance methods can be used to measure neurotransmitter levels. Magnetic Resonance Spectroscopy can measure the levels of a large number of neurotransmitters. However, this has always been viewed as a fairly static measure of neurotransmitter levels, and so has not been widely used as a measure of neural activity. However, Paul Mullins at Bangor University has been doing some work using spectroscopy to measure neurotransmitter levels in different parts of the brain. From the work I have seen him present so far, it is sensitive enough to track stimulus driven changes in neurotransmitter levels with a standard blocked design (ie 18sec blocks of stimulation followed by 18sec of rest). I'm not too sure whether it has the same functional contrast-to-noise as the BOLD response and it definitely has a lower spatial resolution than BOLD techniques. This work is currently being prepared for publication so I shouldn't say too much.

References

Novotny, E. J., Fulbright, R. K., Pearl, P. L., Gibson, K. M., & Rthman D. L. (2003). Magnetic resonance spectroscopy of neurotransmitters in human brain, Annals of Neurology, 54, S25-S31. PubMed.


I found an example of a system that researchers are aiming to use in the future for determining the level of neurotransmitter activity in the brain using MRI. You were on the right track with the utility of hemoglobin. The molecule used is somewhat similar. To understand how the probes were generated requires a bit of a biological detour.

There are enzymes in the body known as P450 cytochromes, so named because they were observed as absorbing light in the 450 nm range. They are membrane bound (e.g., in the mitochondria) and one of their primary purposes is to carry out monooxygenase reactions, and liver-based P450s are responsible much of the drug metabolism that goes on in the body. So, different classes of these enzymes have a high affinity for certain molecules. The most important characteristic that the P450s possess is a heme group, which is paramagnetic, and will produce a signal in an MRI.

These P450 enzymes are also found in bacteria, which can be readily used as a test bed due to their rapid cell division. What these scientists have done is repeatedly mutated bacteria and tested the affinity of the P450s of the resulting mutants for various molecules (in this case serotonin and dopamine).

So, in retaining a culture of the bacteria, scientists can mass produce the mutated heme groups from the bacterial P450s. Presumably once the sequence of the subunit is determined, it could be created using standard techniques.

Some challenges remain. Primarily, the probes will have to be checked for safety, and measures will have to be taken to make them into robust MRI contrast agents, and ensure that they can localize and persist in the brain for the duration of testing. Presumably, the proper correlations between strength of signal and local transmitter concentration can be established with in vitro studies. It sounds like we're fairly close to non-invasive methods of measuring neurotransmitter levels.

Reproduced from here

Brustad, E.M., Lelyveld, V.S., et al (2012). Structure-guided directed evolution of highly selective P450-based magnetic resonance imaging sensors for dopamine and serotonin. Journal of Molecular Biology, in press, doi.


It's a bit of an art, currently. Following is one technique I witnessed in a lab that takes electrophysiological recordings of tadpole and rat neurvous sytems.

The lab that I worked with entrains the neuron, recording it's electrical activity (in a series of drug tests) and injects a marker that goes into the neuron (a GFP-like protein that binds to precursors for serotonin or dopamine or GABA and glows in pictures). Then they mark the brain tissue and the recording so they'll be associated, then after they have a bunch of recordings, they look at all the brain tissues and see which ones expressed the dopamine, GABA, or serotonin.

Now they can associate electrophysiological behavior with a particular neurotransmitter.

In addition to this, there's a general neurochemical anatomy that's known. Serotonergic neurons are only found in the brainstem, for instance and dopamine is only in the substantia nigra pars compacta, ventral tegmental area, and hypothalamus and has four different types of projections to other cell bodies.

Of course, for proof, staining (as described above) is still preferred by reviewers.


Neuroimaging (Brain Imaging)

Neuroimaging or brain imaging is the use of various techniques to either directly or indirectly image the structure, function, or pharmacology of the nervous system. It is a relatively new discipline within medicine, neuroscience, and psychology.[1] Physicians who specialize in the performance and interpretation of neuroimaging in the clinical setting are neuroradiologists.

Neuroimaging falls into two broad categories:

  • Structural imaging, which deals with the structure of the nervous system and the diagnosis of gross (large scale) intracranial disease (such as a tumor) and injury.
  • Functional imaging, which is used to diagnose metabolic diseases and lesions on a finer scale (such as Alzheimer's disease) and also for neurological and cognitive psychology research and building brain-computer interfaces.

Functional imaging enables, for example, the processing of information by centers in the brain to be visualized directly. Such processing causes the involved area of the brain to increase metabolism and "light up" on the scan. One of the more controversial uses of neuroimaging has been researching "thought identification" or mind-reading.

The first chapter of the history of neuroimaging traces back to the Italian neuroscientist Angelo Mosso who invented the 'human circulation balance', which could non-invasively measure the redistribution of blood during emotional and intellectual activity.[2] However, although briefly mentioned by William James in 1890, the details and precise workings of this balance and the experiments Mosso performed with it have remained largely unknown until the recent discovery of the original instrument as well as Mosso&rsquos reports by Stefano Sandrone and colleagues.[3]

In 1918 the American neurosurgeon Walter Dandy introduced the technique of ventriculography. X-ray images of the ventricular system within the brain were obtained by injection of filtered air directly into one or both lateral ventricles of the brain. Dandy also observed that air introduced into the subarachnoid space via lumbar spinal puncture could enter the cerebral ventricles and also demonstrate the cerebrospinal fluid compartments around the base of the brain and over its surface. This technique was called pneumoencephalography.

In 1927 Egas Moniz introduced cerebral angiography, whereby both normal and abnormal blood vessels in and around the brain could be visualized with great precision.

In the early 1970s, Allan McLeod Cormack and Godfrey Newbold Hounsfield introduced computerized axial tomography (CAT or CT scanning), and ever more detailed anatomic images of the brain became available for diagnostic and research purposes. Cormack and Hounsfield won the 1979 Nobel Prize for Physiology or Medicine for their work. Soon after the introduction of CAT in the early 1980s, the development of radioligands allowed single photon emission computed tomography (SPECT) and positron emission tomography (PET) of the brain.

More or less concurrently, magnetic resonance imaging (MRI or MR scanning) was developed by researchers including Peter Mansfield and Paul Lauterbur, who were awarded the Nobel Prize for Physiology or Medicine in 2003. In the early 1980s MRI was introduced clinically, and during the 1980s a veritable explosion of technical refinements and diagnostic MR applications took place. Scientists soon learned that the large blood flow changes measured by PET could also be imaged by the correct type of MRI. Functional magnetic resonance imaging (fMRI) was born, and since the 1990s, fMRI has come to dominate the brain mapping field due to its low invasiveness, lack of radiation exposure, and relatively wide availability.

In the early 2000s, the field of neuroimaging reached the stage where limited practical applications of functional brain imaging have become feasible. The main application area is crude forms of brain-computer interface.

Indications

Neuroimaging follows a neurological examination in which a physician has found cause to more deeply investigate a patient who has or may have a neurological disorder.

One of the more common neurological problems which a person may experience is simple syncope.[4][5] In cases of simple syncope in which the patient's history does not suggest other neurological symptoms, the diagnosis includes a neurological examination but routine neurological imaging is not indicated because the likelihood of finding a cause in the central nervous system is extremely low and the patient is unlikely to benefit from the procedure.[5]

Neuroimaging is not indicated for patients with stable headaches which are diagnosed as migraine.[6] Studies indicate that presence of migraine does not increase a patient's risk for intracranial disease.[6] A diagnosis of migraine which notes the absence of other problems, such as papilledema, would not indicate a need for neuroimaging.[6] In the course of conducting a careful diagnosis, the physician should consider whether the headache has a cause other than the migraine and might require neuroimaging.[6]

Another indication for neuroimaging is CT-, MRI- and PET-guided stereotactic surgery or radiosurgery for treatment of intracranial tumors, arteriovenous malformations and other surgically treatable conditions.[7][8][9][10]

Brain imaging techniques

Computed axial tomography

Computed tomography (CT) or Computed Axial Tomography (CAT) scanning uses a series of x-rays of the head taken from many different directions. Typically used for quickly viewing brain injuries, CT scanning uses a computer program that performs a numerical integral calculation (the inverse Radon transform) on the measured x-ray series to estimate how much of an x-ray beam is absorbed in a small volume of the brain. Typically the information is presented as cross-sections of the brain.[11]

Diffuse optical imaging

Diffuse optical imaging (DOI) or diffuse optical tomography (DOT) is a medical imaging modality which uses near infrared light to generate images of the body. The technique measures the optical absorption of haemoglobin, and relies on the absorption spectrum of haemoglobin varying with its oxygenation status. High-density diffuse optical tomography (HD-DOT) has been compared directly to fMRI using response to visual stimulation in subjects studied with both techniques, with reassuringly similar results.[12] HD-DOT has also been compared to fMRI in terms of language tasks and resting state functional connectivity.[13]

Event-related optical signal

Event-related optical signal (EROS) is a brain-scanning technique which uses infrared light through optical fibers to measure changes in optical properties of active areas of the cerebral cortex. Whereas techniques such as diffuse optical imaging (DOT) and near-infrared spectroscopy (NIRS) measure optical absorption of haemoglobin, and thus are based on blood flow, EROS takes advantage of the scattering properties of the neurons themselves and thus provides a much more direct measure of cellular activity. EROS can pinpoint activity in the brain within millimeters (spatially) and within milliseconds (temporally). Its biggest downside is the inability to detect activity more than a few centimeters deep. EROS is a new, relatively inexpensive technique that is non-invasive to the test subject. It was developed at the University of Illinois at Urbana-Champaign where it is now used in the Cognitive Neuroimaging Laboratory of Dr. Gabriele Gratton and Dr. Monica Fabiani.

Magnetic resonance imaging

Magnetic resonance imaging (MRI) uses magnetic fields and radio waves to produce high quality two- or three-dimensional images of brain structures without the use of ionizing radiation (X-rays) or radioactive tracers.

Functional magnetic resonance imaging

Functional magnetic resonance imaging (fMRI) and arterial spin labeling (ASL) relies on the paramagnetic properties of oxygenated and deoxygenated hemoglobin to see images of changing blood flow in the brain associated with neural activity. This allows images to be generated that reflect which brain structures are activated (and how) during the performance of different tasks or at resting state. According to the oxygenation hypothesis, changes in oxygen usage in regional cerebral blood flow during cognitive or behavioral activity can be associated with the regional neurons as being directly related to the cognitive or behavioral tasks being attended.

Most fMRI scanners allow subjects to be presented with different visual images, sounds and touch stimuli, and to make different actions such as pressing a button or moving a joystick. Consequently, fMRI can be used to reveal brain structures and processes associated with perception, thought and action. The resolution of fMRI is about 2-3 millimeters at present, limited by the spatial spread of the hemodynamic response to neural activity. It has largely superseded PET for the study of brain activation patterns. PET, however, retains the significant advantage of being able to identify specific brain receptors (or transporters) associated with particular neurotransmitters through its ability to image radiolabelled receptor "ligands" (receptor ligands are any chemicals that stick to receptors).

As well as research on healthy subjects, fMRI is increasingly used for the medical diagnosis of disease. Because fMRI is exquisitely sensitive to oxygen usage in blood flow, it is extremely sensitive to early changes in the brain resulting from ischemia (abnormally low blood flow), such as the changes which follow stroke. Early diagnosis of certain types of stroke is increasingly important in neurology, since substances which dissolve blood clots may be used in the first few hours after certain types of stroke occur, but are dangerous to use afterward. Brain changes seen on fMRI may help to make the decision to treat with these agents. With between 72% and 90% accuracy where chance would achieve 0.8%,[14] fMRI techniques can decide which of a set of known images the subject is viewing.[15]

Magnetoencephalography

Magnetoencephalography (MEG) is an imaging technique used to measure the magnetic fields produced by electrical activity in the brain via extremely sensitive devices such as superconducting quantum interference devices (SQUIDs) or spin exchange relaxation-free[16] (SERF) magnetometers. MEG offers a very direct measurement of neural electrical activity (compared to fMRI for example) with very high temporal resolution but relatively low spatial resolution. The advantage of measuring the magnetic fields produced by neural activity is that they are likely to be less distorted by surrounding tissue (particularly the skull and scalp) compared to the electric fields measured by electroencephalography (EEG). Specifically, it can be shown that magnetic fields produced by electrical activity are not affected by the surrounding head tissue, when the head is modeled as a set of concentric spherical shells, each being an isotropic homogeneous conductor. Real heads are non-spherical and have largely anisotropic conductivities (particularly white matter and skull). While skull anisotropy has a negligible effect on MEG (unlike EEG), white matter anisotropy strongly affects MEG measurements for radial and deep sources.[17] Note, however, that the skull was assumed to be uniformly anisotropic in this study, which is not true for a real head: the absolute and relative thicknesses of diploë and tables layers vary among and within the skull bones. This makes it likely that MEG is also affected by the skull anisotropy,[18] although probably not to the same degree as EEG.

There are many uses for MEG, including assisting surgeons in localizing a pathology, assisting researchers in determining the function of various parts of the brain, neurofeedback, and others.

Positron emission tomography

Positron emission tomography (PET) and brain positron emission tomography, measure emissions from radioactively labeled metabolically active chemicals that have been injected into the bloodstream. The emission data are computer-processed to produce 2- or 3-dimensional images of the distribution of the chemicals throughout the brain.[19]:57 The positron emitting radioisotopes used are produced by a cyclotron, and chemicals are labeled with these radioactive atoms. The labeled compound, called a radiotracer, is injected into the bloodstream and eventually makes its way to the brain. Sensors in the PET scanner detect the radioactivity as the compound accumulates in various regions of the brain. A computer uses the data gathered by the sensors to create multicolored 2- or 3-dimensional images that show where the compound acts in the brain. Especially useful are a wide array of ligands used to map different aspects of neurotransmitter activity, with by far the most commonly used PET tracer being a labeled form of glucose (see Fludeoxyglucose (18F) (FDG)).

The greatest benefit of PET scanning is that different compounds can show blood flow and oxygen and glucose metabolism in the tissues of the working brain. These measurements reflect the amount of brain activity in the various regions of the brain and allow to learn more about how the brain works. PET scans were superior to all other metabolic imaging methods in terms of resolution and speed of completion (as little as 30 seconds) when they first became available. The improved resolution permitted better study to be made as to the area of the brain activated by a particular task. The biggest drawback of PET scanning is that because the radioactivity decays rapidly, it is limited to monitoring short tasks.[19]:60 Before fMRI technology came online, PET scanning was the preferred method of functional (as opposed to structural) brain imaging, and it continues to make large contributions to neuroscience.

PET scanning is also used for diagnosis of brain disease, most notably because brain tumors, strokes, and neuron-damaging diseases which cause dementia (such as Alzheimer's disease) all cause great changes in brain metabolism, which in turn causes easily detectable changes in PET scans. PET is probably most useful in early cases of certain dementias (with classic examples being Alzheimer's disease and Pick's disease) where the early damage is too diffuse and makes too little difference in brain volume and gross structure to change CT and standard MRI images enough to be able to reliably differentiate it from the "normal" range of cortical atrophy which occurs with aging (in many but not all) persons, and which does not cause clinical dementia.

Single-photon emission computed tomography

Single-photon emission computed tomography (SPECT) is similar to PET and uses gamma ray-emitting radioisotopes and a gamma camera to record data that a computer uses to construct two- or three-dimensional images of active brain regions.[20] SPECT relies on an injection of radioactive tracer, or "SPECT agent," which is rapidly taken up by the brain but does not redistribute. Uptake of SPECT agent is nearly 100% complete within 30 to 60 seconds, reflecting cerebral blood flow (CBF) at the time of injection. These properties of SPECT make it particularly well-suited for epilepsy imaging, which is usually made difficult by problems with patient movement and variable seizure types. SPECT provides a "snapshot" of cerebral blood flow since scans can be acquired after seizure termination (so long as the radioactive tracer was injected at the time of the seizure). A significant limitation of SPECT is its poor resolution (about 1 cm) compared to that of MRI. Today, SPECT machines with Dual Detector Heads are commonly used, although Triple Detector Head machines are available in the marketplace. Tomographic reconstruction, (mainly used for functional "snapshots" of the brain) requires multiple projections from Detector Heads which rotate around the human skull, so some researchers have developed 6 and 11 Detector Head SPECT machines to cut imaging time and give higher resolution.[21][22]

Like PET, SPECT also can be used to differentiate different kinds of disease processes which produce dementia, and it is increasingly used for this purpose. Neuro-PET has a disadvantage of requiring the use of tracers with half-lives of at most 110 minutes, such as FDG. These must be made in a cyclotron, and are expensive or even unavailable if necessary transport times are prolonged more than a few half-lives. SPECT, however, is able to make use of tracers with much longer half-lives, such as technetium-99m, and as a result, is far more widely available.

Cranial ultrasound

Cranial ultrasound is usually only used in babies, whose open fontanelles provide acoustic windows allowing ultrasound imaging of the brain. Advantages include the absence of ionising radiation and the possibility of bedside scanning, but the lack of soft-tissue detail means MRI is preferred for some conditions.

Advantages and Concerns of Neuroimaging Techniques

Functional Magnetic Resonance Imaging (fMRI)

fMRI is commonly classified as a minimally-to-moderate risk due to its non-invasiveness compared to other imaging methods. fMRI uses blood oxygenation level dependent (BOLD)-contrast in order to produce its form of imaging. BOLD-contrast is a naturally occurring process in the body so fMRI is often preferred over imaging methods that require radioactive markers to produce similar imaging.[23] A concern in the use of fMRI is its use in individuals with medical implants or devices and metallic items in the body. The magnetic resonance (MR) emitted from the equipment can cause failure of medical devices and attract metallic objects in the body if not properly screened for. Currently, the FDA classifies medical implants and devices into three categories, depending on MR-compatibility: MR-safe (safe in all MR environments), MR-unsafe (unsafe in any MR environment), and MR-conditional (MR-compatible in certain environments, requiring further information).[24]

Computed Tomography (CT) Scan

The CT scan was introduced in the 1970s and quickly became one of the most widely used methods of imaging. A CT scan can be performed in under a second and produce rapid results for clinicians, with its ease of use leading to an increase in CT scans performed in the United States from 3 million in 1980 to 62 million in 2007. Clinicians oftentimes take multiple scans, with 30% of individuals undergoing at least 3 scans in one study of CT scan usage[26]. CT scans can expose patients to levels of radiation 100-500 times higher than traditional x-rays, with higher radiation doses producing better resolution imaging.[27] While easy to use, increases in CT scan use, especially in asymptomatic patients, is a topic of concern since patients are exposed to significantly high levels of radiation[26].

Positron Emission Tomography (PET)

In PET scans, imaging does not rely on intrinsic biological processes, but relies on a foreign substance injected into the bloodstream traveling to the brain. Patients are injected with radioisotopes that are metabolized in the brain and emit positrons to produce a visualization of brain activity.[23] The amount of radiation a patient is exposed to in a PET scan is relatively small, comparable to the amount of environmental radiation an individual is exposed to across a year. PET radioisotopes have limited exposure time in the body as they commonly have very short half-lives (

2 hours) and decay rapidly.[28] Currently, fMRI is a preferred method of imaging brain activity compared to PET, since it does not involve radiation, has a higher temporal resolution than PET, and is more readily available in most medical settings.[23]

Magnetoencephalography (MEG) & Electroencephalography (EEG)

The high temporal resolution of MEG and EEG allow these methods to measure brain activity down to the millisecond. Both MEG and EEG do not require exposure of the patient to radiation to function. EEG electrodes detect electrical signals produced by neurons to measure brain activity and MEG uses oscillations in the magnetic field produced by these electrical currents to measure activity. A barrier in the widespread usage of MEG is due to pricing, as MEG systems can cost millions of dollars. EEG is a much more widely used method to achieve such temporal resolution as EEG systems cost much less than MEG systems. A disadvantage of EEG and MEG is that both methods have poor spatial resolution when compared to fMRI.[23]

Criticism and cautions

Some scientists have criticized the brain image-based claims made in scientific journals and the popular press, like the discovery of "the part of the brain responsible" for functions like talents, specific memories, or generating emotions such as love. Many mapping techniques have a relatively low resolution, including hundreds of thousands of neurons in a single voxel. Many functions also involve multiple parts of the brain, meaning that this type of claim is probably both unverifiable with the equipment used, and generally based on an incorrect assumption about how brain functions are divided. It may be that most brain functions will only be described correctly after being measured with much more fine-grained measurements that look not at large regions but instead at a very large number of tiny individual brain circuits. Many of these studies also have technical problems like small sample size or poor equipment calibration which means they cannot be reproduced - considerations which are sometimes ignored to produce a sensational journal article or news headline. In some cases the brain mapping techniques are used for commercial purposes, lie detection, or medical diagnosis in ways which have not been scientifically validated.[29]

This article is licensed under the GNU Free Documentation License. It uses material from the Wikipedia article "Neuroimaging."


Long-range effects

After analyzing dopamine release in the striatum, the researchers set out to determine this dopamine might affect more distant locations in the brain. To do that, they performed traditional fMRI imaging on the brain while also mapping dopamine release in the striatum. “By combining these techniques we could probe these phenomena in a way that hasn’t been done before,” Jasanoff says.

The regions that showed the biggest surges in activity in response to dopamine were the motor cortex and the insular cortex. If confirmed in additional studies, the findings could help researchers understand the effects of dopamine in the human brain, including its roles in addiction and learning.

“Our results could lead to biomarkers that could be seen in fMRI data, and these correlates of dopaminergic function could be useful for analyzing animal and human fMRI,” Jasanoff says.

The research was funded by the National Institutes of Health and a Stanley Fahn Research Fellowship from the Parkinson’s Disease Foundation.


The Basics of Brain Imaging

This is archived NIDA Notes content. For current NIDA Notes, please visit drugabuse.gov.

Cite this article

NIDA. (1996, December 1). The Basics of Brain Imaging. Retrieved from https://archives.drugabuse.gov/news-events/nida-notes/1996/12/basics-brain-imaging

NIDA. "The Basics of Brain Imaging." National Institute on Drug Abuse, 1 Dec. 1996, https://archives.drugabuse.gov/news-events/nida-notes/1996/12/basics-brain-imaging.

NIDA. The Basics of Brain Imaging. National Institute on Drug Abuse website. https://archives.drugabuse.gov/news-events/nida-notes/1996/12/basics-brain-imaging. December 1, 1996.

The major neuroimaging techniques used in drug abuse research are positron emission tomography (PET), single photon emission computed tomography (SPECT),and magnetic resonance imaging (MRI), along with electro-encephalography(EEG), an earlier technique for monitoring brain activity. Advances in all these techniques are enabling scientists to produce remarkably detailed computer-screen images of brain structures and to observe neurochemical changes that occur in the brain as it processes information or responds to various stimuli such as drugs of abuse or drug abuse treatment medications.

PET, SPECT, MRI, and EEG are noninvasive procedures that can measure biological activity through the skull and reveal the living human brain at work. Each technique has its own advantages and each provides different information about brain structure and function. For this reason, scientists increasingly are conducting studies that integrate two or more techniques. For example, merging a PET scan image that shows activity at brain molecular sites, or receptors, with a highly detailed MRI image of brain structure can produce a composite image that makes it possible to identify more precisely where in the brain the activity is occurring.


Techniques Involving Electrical Activity

In some situations, it is helpful to gain an understanding of the overall activity of a person’s brain, without needing information on the actual location of the activity. Electroencephalography (EEG) serves this purpose by providing a measure of a brain’s electrical activity. An array of electrodes is placed around a person’s head (Figure 4). The signals received by the electrodes result in a printout of the electrical activity of his or her brain, or brainwaves, showing both the frequency (number of waves per second) and amplitude (height) of the recorded brainwaves, with an accuracy within milliseconds. Such information is especially helpful to researchers studying sleep patterns among individuals with sleep disorders.

Figure 4. Using caps with electrodes, modern EEG research can study the precise timing of overall brain activities. (credit: SMI Eye Tracking)


Neuroimaging Part I

Bradley R. Buchbinder , in Handbook of Clinical Neurology , 2016

Synaptic activity dominantly drives signaling-related energy metabolism

Functional neuroimaging has often been assumed to reflect the regional intensity of action potentials (APs) ( Raichle and Mintun, 2006 ). However, APs only represent the output of the postsynaptic neuron, while excitatory and inhibitory postsynaptic potentials (EPSPs, IPSPs) represent its input. The relative contributions of the input synaptic activity and output spike activity to functional neuroimaging signals are important to their meaningful interpretation.

The relative energies consumed by postsynaptic potentials and APs inform their contributions to functional neuroimaging signals. Most signaling-related energy (91%) is expended by Na + /K + ATPase to restore transmembrane ion gradients, which are dissipated by excitatory, primarily glutamatergic, synaptic signaling and to maintain the resting potential ( Attwell and Laughlin, 2001 Howarth et al., 2012 ). Processes related to neurotransmitter release, recycling, and vesicular repackaging account for the remaining 9%. Inhibitory synaptic activity, most commonly mediated by γ-aminobutyric acid (GABA), consumes negligible energy itself. Of the signaling-related energy expenditures, EPSPs account for 50%, APs for 21%, the resting potential for 20%, presynaptic glutamate release for 5%, and glutamate recycling for 4%. Thus, compared with output spike activity (21%), excitatory input synaptic activity accounts for the majority (59%) of cortical signaling-related energy expenditure.


Brain imaging study pinpoints neurotransmitter that may be responsible for yoga’s mood-boosting effect

A recent study found tentative evidence to suggest that yoga exerts its mood-boosting effect by increasing GABA activity among individuals with depression. The study, published in the Journal of Alternative and Complementary Medicine, further suggests that yoga’s beneficial effects on mood are time-limited.

While medication can be highly effective in reducing symptoms of major depressive disorder (MDD), many individuals do not reach remission without additional treatment. Interestingly, yoga interventions have shown promise in reducing depressive symptoms, although it is not clear why.

“Integrative medicine includes consideration of the mind-body interface. Yoga can be used to address many form of illness especially those due to Life Style Choices,” said study author Chris C. Streeter, an associate professor of psychiatry and neurology at the Boston University School of Medicine.

“Many form of western medicine help reduce symptoms but to do completely return people to wellness, the addition of yoga to a treatment regime can increase wellness/decrease symptoms.”

Streeter and her colleagues set out to explore the idea that a yoga intervention increases mood through its effect on an amino acid neurotransmitter called gamma-aminobutyric acid (GABA). The researchers were motivated by findings linking the neurotransmitter to depression.

Specifically, insufficiency in the GABA system has been linked to depressive symptoms, and individuals with MDD have been found to have low GABA levels. On the other hand, yoga interventions have been purported to increase GABA activity.

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Streeter and team recruited 32 adults with MDD for a 12-week yoga intervention. Patients were assigned to either a high-dose intervention of three yoga sessions a week or a low-dose intervention of two yoga sessions a week. The yoga sessions included 60 minutes of Iyengar yoga, 10 minutes of relaxation, 20 minutes of breathing practice, and homework exercises.

Throughout the study, the patients underwent magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) scans before the 12-week intervention and following the intervention. At the end of the intervention, all participants took part in an additional 90-minute yoga session and then a third and final brain scan.

The researchers found that the overall direction of the data when considering all participants, pointed to increases in GABA levels between the first and last scans, and the second and third scans. However, there were no differences between the high-dose yoga and low-dose yoga groups.

The findings provide evidence that “yoga is a low cost, low side effect means of improving mood and decreasing anxiety,” Streeter told PsyPost.

The researchers did find that the number of days since a subject’s latest yoga class appeared to be important, perhaps more so than the amount of yoga practice. Specifically, those who showed increased GABA levels at Scan 2 compared to Scan 1, had an average of 3.93 days since their last yoga session. Those whose GABA levels did not go up had an average of 7.83 days since their last yoga session.

“It is probable that the effects of yoga sessions, like pharmacologic treatments, are time limited,” the researchers remark. “The yoga tradition advocates daily practice. The increase in GABA levels seen after a yoga intervention was observed after an average of 4 days, but no longer observed after an average of 8 days.”

The participants had also completed assessments of depressive symptoms at various timepoints. The researchers found that subjects’ GABA levels were not significantly linked to their depressive symptoms. However, changes in depressive symptoms were inversely tied to GABA levels among the high-dose group. As the authors say, this means that depressive symptoms dropped as GABA levels rose.

With a very small sample size, the authors express that their findings are encouraging yet tentative, and future studies should explore the topic among a larger sample.

“The use of yoga for depression needs to be compared to antidepressants in a randomized controlled trial and in combination with anti-depressants,” Streeter said.

Still, the findings suggest that the GABA system may be a mechanism through which yoga improves mood, and practicing yoga at least one time a week may be the key to seeing these benefits.

“There are no magic bullets or pills that completely treat depression or anxiety — yoga is another tool available,” Streeter added. “Many stress-related disorders are associated with an imbalance in the autonomic nervous system with too much sympathetic (fight or flight) and to little parasympathetic (rest, renewal and social engagement). Yoga helps to correct this imbalance.”

The study, “Thalamic Gamma Aminobutyric Acid Level Changes in Major Depressive Disorder After a 12-Week Iyengar Yoga and Coherent Breathing Intervention”, was authored by Chris C. Streeter, Patricia L. Gerbarg, Richard P. Brown, Tammy M. Scott, Greylin H. Nielsen, Liz Owen, Osamu Sakai, Jennifer T. Sneider, Maren B. Nyer, and Marisa M. Silveri.


Imaging technique maps serotonin activity in living brains

Molecular fMRI data showing signal changes from serotonin sensors in the absence (left) and presence (right) of the antidepressant Prozac, with each square denoting an individual brain voxel. Red squares indicate the signal has increased, as more serotonin is absorbed into neurons blue squares indicate the signal has decreased, as less serotonin is absorbed into neurons. Dotted and solid lines graphed in each square show how the signal changes over time. The swirling black lines indicate features of the brain. A computer model uses this data to estimate neurotransmitter reuptake across the brain. Credit: Massachusetts Institute of Technology

Serotonin is a neurotransmitter that's partly responsible for feelings of happiness and for mood regulation in humans. This makes it a common target for antidepressants, which block serotonin from being reabsorbed by neurons after it has dispatched its signal, so more of it stays floating around the brain.

Now MIT researchers have developed an imaging technique that, for the first time, enables three-dimensional mapping of serotonin as it's reabsorbed into neurons, across multiple regions of the living brain. This technique, the researchers say, gives an unprecedented view of serotonin dynamics, and could be a powerful tool for the research and development of antidepressants.

"Until now, it was not possible to look at how neurotransmitters are transported into cells across large regions of the brain," says Aviad Hai, a postdoc in the Department of Biological Engineering and first author of a paper describing the technique in today's issue of Neuron. "It's the first time you can see the inhibitors of serotonin reuptake, like antidepressants, working in different parts of the brain, and you can use this information to analyze all sorts of antidepressant drugs, discover new ones, and see how those drugs affect the serotonin system across the brain."

The paper's other authors are Alan Jasanoff, a professor of biological engineering and three other researchers in Jasanoff's lab: Lili X. Cai, Taekwan Lee, and Victor S. Lelyveld.

Many antidepressants that target serotonin work by blocking serotonin transporters that reabsorb the neurotransmitter into a neuron, so it can be reused after it has sent a chemical signal. Aptly called "selective serotonin reuptake inhibitors" (SSRIs), these drugs increase levels of serotonin in the brain, alleviating feelings of anxiety and depression caused by low levels of the neurotransmitter.

Researchers most commonly study the effect of antidepressants using a technique known as microdialysis, in which they insert a probe into the brain to take tiny chemical samples from the tissue. But this method is time-consuming and limited in scope, as it allows them to study only a single location at a time.

For the new imaging technique, the researchers engineered a protein to act as a sensor that latches onto serotonin and detaches at the moment of reuptake. The sensor is injected, along with serotonin, and emits a signal that can be read by functional magnetic resonance imaging (fMRI). The trick is that the sensor remains off—emitting a low signal—when bound to serotonin, and turns on—creating a much brighter signal—when serotonin is removed.

In the new system, a mathematical model uses the fMRI signal data to construct a 3-D map that consists of more than 1,000 voxels (pixels in three dimensions), with each voxel representing a single point of measurement of serotonin reuptake. Based on the signal strength at each point, the model calculates the amount of serotonin that gets absorbed, in the presence and absence of SSRIs.

"Basically, what we've seen in this work is a method for measuring how much of a neurotransmitter is being [absorbed], and how that amount, or rate, is affected by different drugs . in a highly parallel fashion across much of the brain," Jasanoff says. That information could be very valuable for testing drug efficacy, he says.

Mapping antidepressant dynamics

To validate the sensor, the researchers successfully measured the expected effect of the SSRI fluoxetine, commonly called Prozac, on serotonin transporters in six subregions of a brain area known as the basal ganglia. These subregions are thought to play a role in motivation, reward, cognition, learning, emotion, and other functions and behaviors.

In doing so, the researchers simultaneously recorded a stronger decrease of serotonin reuptake in response to Prozac among three of the subregions, while noting a very weak response in one other region. These results were, more or less, anticipated, Jasanoff says. "But now we're able to map that effect in three dimensions, across brain regions," he says, which could lead to advances in studying the effects of drugs on specific parts of the brain.

But the researchers did uncover a surprising finding. While mapping the effects of a dopamine transport reuptake inhibitor—made to target only dopamine—they found the drug reduced serotonin reuptake, to an extent comparable to that of SSRIs, in three subregions, one of which is known for high dopamine transporter expression. Previous studies had indicated that dopamine transporter proteins can aid in low levels of serotonin reuptake, but the new findings show the effect is widespread in the living brain, Jasanoff says.

This experiment provides further proof of a strong interplay between the serotonin and dopamine systems, and indicates that antidepressants may be less effective when targeting just one of the two neurotransmitters, Hai says. "It may not be sufficient to just block serotonin reuptake, because there's another system—dopamine—that plays a role in serotonin transport as well," he says. "It's almost proof that when you use antidepressants that . target both systems, it could be more effective."

Next steps for the researchers are to explore different regions of the brain with this sensor, including the dorsal raphe, which produces most of the brain's serotonin. They're also making another nanoparticle-based sensor that is more sensitive than one used for this study.


Contents

Personality can be defined as a set of characteristics or traits that drive individual differences in human behavior. From a biological perspective, these traits can be traced back to brain structures and neural mechanisms. However, this definition and theory of biological basis is not universally accepted. There are many conflicting theories of personality in the fields of psychology, psychiatry, philosophy, and neuroscience. A few examples of this are the nature vs. nurture debate and how the idea of a 'soul' fits into biological theories of personality. [1]

Since the time of the ancient Greeks, humankind has attempted to explain personality through spiritual beliefs, philosophy, and psychology. Historically, studies of personality have traditionally come from the social sciences and humanities, but in the past two decades neuroscience has begun to be more influential in the understanding of human personality. [2]

However, the most cited and influential figures in publishing the first biology-based personality theories are Hans Eysenck and Jeffrey Alan Gray. Eysenck used both behavioral and psychophysiological methodologies to test and develop his theories. [3] He published a book in 1947 called Dimensions of Personality, describing the personality dimensions of Extraversion and Neuroticism. Gray, a student of Eysenck, studied personality traits as individual differences in sensitivity to rewarding and punishing stimuli. [3] The significance of Gray's work and theories was his use of biology to define behavior, which stimulated a lot of subsequent research. [4]

In 1951, Hans Eysenck and Donald Prell published an experiment in which identical (monozygotic) and fraternal (dizygotic) twins, ages 11 and 12, were tested for neuroticism. It is described in detail in an article published in the Journal of Mental Science. in which Eysenck and Prell concluded that, "The factor of neuroticism is not a statistical artifact, but constitutes a biological unit which is inherited as a whole. neurotic predisposition is to a large extent hereditarily determined." [5] The study concluded that the neuroticism trait was a result of up to eighty percent of genetics. There was a stronger correlation among identical twins rather than fraternal twins. [6]

The idea of biology-based personality research is relatively new, but growing in interest and number of publications. [7] In August 2004, there was a conference specifically on the topic, called The Biological Basis of Personality and Individual Differences. [8] This allowed for presenting and sharing of ideas between psychologists, psychiatrists, molecular geneticists, and neuroscientists, and eventually gave birth to the book under the same title. [8] The book is a collection of current research (as of 2006) in the field contributed by many authors and edited by Turhan Canli. Recently, psychology professor Colin G. DeYoung has even named the idea as the field of "Personality Neuroscience." [9] Furthermore, a journal devoted to cultivating research investigating the neurobiological basis of personality has recently been established and is called "Personality Neuroscience." [10]

There are many theories of personality that centre on the identification of a set of traits that encompass human personality. Few however, are biologically based. This section will describe some theories of personality that have a biological basis.

Eysenck's three-factor model of personality Edit

Eysenck's three-factor model of personality was a causal theory of personality based on activation of reticular formation and limbic system. The reticular formation is a region in the brainstem that is involved in mediating arousal and consciousness. The limbic system is involved in mediating emotion, behavior, motivation, and long-term memory.

    (E) – degree to which people are outgoing and are interactive with people, which is mediated by the activation of the reticular formation. (N) – degree of emotional instability, which is associated with the limbic system. (P) – degree of aggression and interpersonal hostility.

Gray's reinforcement sensitivity theory Edit

Gray's reinforcement sensitivity theory (RST) is based on the idea that there are three brain systems that all differently respond to rewarding and punishing stimuli. [3]

    (FFFS) – mediates the emotion of fear (not anxiety) and active avoidance of dangerous situations. The personality traits associated with this system is fear-proneness and avoidance. (BIS) – mediates the emotion of anxiety and cautious risk-assessment behavior when entering dangerous situations due to conflicting goals. The personality traits associated with this system is worry-proneness and anxiety. (BAS) – mediates the emotion of 'anticipatory pleasure,' resulting from reactions to desirable stimuli. The personality traits associated with this system are optimism, reward-orientation, and impulsivity.

Cloninger model of personality Edit

This model of personality is based on the idea that different responses to punishing, rewarding, and novel stimuli the main characteristics of the human mind is caused by an interaction of the three dimensions below:

    (NS) – degree to which people are impulsive, correlated with low dopamine activity. (HA) – degree to which people are anxious, correlated with high serotonin activity. (RD) – degree to which people are approval seeking, correlated with low norepinephrine activity.

Five factor model of personality Edit

The five factor model (also known as the Big Five) is a widely used personality assessment that describes five core traits that a person possesses:

    – degree to which people enjoy experiencing new stimuli – degree to which people are dutiful and goal-oriented – degree to which people seek stimuli outside of themselves – degree to which people aim to cooperate and please others – degree to which people are emotionally unstable

There is large body of research relating the Big Five traits to individual differences in the brain's structure and function, as measured by MRI-based techniques. A selection of these findings are outlined in the "Brain imaging basis of personality" section below.

Two factor model of personality Edit

A higher-order factor structure can be derived from the Big Five traits, as these traits have often been found to be correlated. Agreeableness, Conscientiousness, and Neuroticism (reversed) can be distilled into a single factor α, or the Stability factor. On the other hand, Extraversion and Openness can be distilled into a single factor β, or the Plasticity factor. [11] [12] These two meta-traits have been shown to be significantly heritable using behavior genetic analysis, [13] which suggests a neurobiological basis that is unique and specific to these meta-traits. Indeed, a growing body of evidence demonstrates that serotonin is associated with Stability and dopamine is associated with Plasticity. [11] [12] [14]

There are many experimental techniques for measuring the biology of the brain, but there are five main methods used to investigate the biological basis of personality. [15] The biological data from these methods are commonly correlated with personality traits. These personality traits are often determined by personality questionnaires. However, personality questionnaires may be biased because they are self-reported. As a result, scientists emphasize using several different measures of personality, [15] [16] rather than solely self-reported measures of personality. For example, another measure of personality traits is observation of behavior. Both humans and animals have been observed to measure personality traits, but animals are particularly useful for studying the long-term behavioral-biological relationship of personality. [17]

Another interesting method that has become more sophisticated and affordable to researchers is the method of whole genome expression analysis. This method involves collecting data for a large number of genes simultaneously which provides many advantages in studying personality. In an article written by Alison M. Bell and Nadia Aubin-Horth, they describe the advantages very clearly by stating, "For one, it is probable that the genetic basis of personality is polygenic, so it makes sense to simultaneously study many genes. In addition, gene products rarely act alone. Instead, they perform their function by interacting together in pathways and networks. As a result, the molecular changes that characterize a phenotype are frequently not based on a single marker or gene, but rather on an entire pathway. Whole genome expression profiling therefore has the potential to reveal new candidates genes and pathways." [18]

Method Function Significance
Electroencephalography (EEG) This method measures electrical activity on the surface of the brain through the scalp, and has the high temporal resolution. [15] Before the advent of brain imaging technology, the only method to measure brain activity was electroencephalography (EEG). [15]
Brain Imaging Brain imaging can refer to either structural or functional imaging. Structural imaging allows for analysis using structural characteristics of the brain, whereas functional imaging involves measuring brain activity. Structural imaging of the brain can be accomplished by using Magnetic Resonance Imaging (MRI). Examples of functional imaging methods include Positron Emission Tomography (PET) and functional MRI (fMRI). PET scans measure the metabolism associated with brain activity, and fMRI measures the flow of blood in the brain, which reflects local brain activity. MRI has particularly high spatial resolution and is entirely non-invasive, whereas PET scans require the injection of radioactive tracers. Brain imaging has catalyzed research of the neurobiological correlates of personality. [3]
Molecular genetics This method is used to analyze a gene-trait link, by measuring the structure and function of genes in the brain. [15] The use of molecular genetics in biology-based personality research is expected to grow. [7]
Molecular assays This method is used to analyze the amount of psychoactive substances, such as hormones and neurotransmitters. Together, these two methods can specifically quantify, define, and manipulate the effects of brain molecules on behavior and personality traits. This has great clinical significance for treatment of personality disorders.
Pharmacological Manipulation This method is used to alter the levels of biochemicals, and observe the effects on behavior.

Neurotransmitters Edit

The biology-based personality theories (discussed below) are based on correlating personality traits with behavioral systems related to motivation, reward, and punishment. On a broad level, this involves the autonomic nervous system, fear-processing circuits in the amygdala, the reward pathway from the ventral tegmental area (VTA) to the nucleus accumbens and prefrontal cortex. All of these circuits heavily rely on neurotransmitters and their precursors, but there has been the most research support for dopamine and serotonin pathways:

    : Dopamine is a monoamine neurotransmitter that has been found to promote exploratory behavior. [19] Dopaminergic pathways have been specifically correlated with the extraversion trait of the Five Factor Model of Personality. [15] The monoamine oxidase (MAO) enzyme has a preferential affinity for dopamine, and its levels are inversely correlated with sensation seeking. [16] : Serotonin is a monoamine neurotransmitter, and has been found to promote avoidance behavior through inhibitory pathways. [19] Specifically, serotonin has been associated with Neuroticism, Agreeableness, and Conscientiousness (traits defined by the Five Factor Model of Personality). [15]

Genes Edit

Previous studies show that genes account for at most 50 percent of a given trait. [1] However, it is widely accepted that variance in gene sequence affect behavior, and genes are a significant risk factor for personality disorders. [20] With the growing interest in using molecular genetics in tracing the biological basis of personality, [8] there may be more gene-trait links found in the future.

Varying polymorphisms and sequence repeats in the gene for dopamine receptor D4 and serotonin transporter gene 5-HTTLPR, have both been found to influence the extraversion trait in adults. Specifically, study participants with at least one copy of the 7-repeat variant of the dopamine receptor D4 gene had higher scores of self-reported extraversion. [8] This suggests that dopamine and serotonin interact to regulate the conflicting behavioral traits of careless exploration vs. cautious inhibition. [19]

Synaptic plasticity Edit

Synaptic plasticity refers to the ability of neurons to strengthen or weaken the connections between them. According to Hebbian theory, these connections are strengthened and maintained through repeated stimulation between neurons. Specifically, there is an emphasis on long-term potentiation (LTP), which is the prolonged strengthening of synaptic connections that facilitate learning from experience.

On a larger scale, there are many pathways and brain regions that are interdependent and contribute to a cohesive, stable personality. For example, the amygdala and hippocampus of the limbic system mediate emotional intensity and consolidate memory of these experiences. But the basic mechanism by which these pathways and brain regions perform these functions, is synaptic plasticity. Ultimately, it boils down to this feature of neurons that allows the brain to learn from repeated experiences, retain memories, and ultimately maintain personality. [21] Joseph LeDoux, an award-winning neuroscientist, asserts that although humans share the same brain systems, it is the unique wiring of neurons that is different in each person and makes their personality. [21]

Over the past two decades, structural magnetic resonance imaging (sMRI) and functional magnetic resonance imaging (fMRI) techniques have been used to study associations between neural activations in the brain and personality traits and other cognitive, social, and emotional processes that characterize personality. Using MRI-based methods for such studies has become increasingly popular due to the non-invasive nature of MRI and the high resolution of MRI.

Structural magnetic resonance imaging Edit

The use of structural magnetic resonance imaging (sMRI) to understand the neurobiological basis of personality and sociocognitive functioning involves assessing the relationship between individual differences in these factors and individual differences in measures of brain structure, such as gray matter volume, cortical thickness, or structural integrity of white matter tracts.

Studies have shown that brain volume is meaningfully correlated with four of the Big Five personality measures. Extraversion was associated with increased volume of medial orbitofrontal cortex, a region associated with processing reward-related stimuli. Conscientiousness was associated with increased volume in the lateral prefrontal cortex, a region involved in planning and the voluntary control of behavior. Agreeableness was associated with increased volume in regions involved in mentalizing, which is the ability to infer the intentions and mental states of other individuals. Neuroticism was associated with increased volume of brain regions associated with threat, punishment, and negative emotions. Openness/Intellect was not significantly correlated with the volume of any brain structures. [22] In another study, neuroticism was negatively correlated with the gray matter volume of the right amygdala, whereas extraversion was positively correlated with gray matter volume of the left amygdala. [23] A separate study also reported a significant association between neuroticism scores and gray matter volume of the left amygdala. [24] In one MRI study, [25] Novelty Seeking correlated with increased grey matter volume in regions of the cingulate cortex, Harm Avoidance correlated with decreased grey matter volume in the orbitofrontal, occipital, and parietal cortex. Reward Dependence correlated with decreased grey matter volume in the caudate nucleus.

A separate but similar line of research has used diffusion tensor imaging to measure the structural integrity of white matter in the brain. One study has shown that neuroticism is negatively correlated with the structural integrity of white matter tracts that connect various brain regions, such as the prefrontal cortex, parietal cortex, amygdala, and other regions in the subcortex. On the other hand, Openness and Agreeableness are positively associated with the structural integrity of these white matter tracts. Openness was also positively associated with the structural integrity of white matter interconnecting dorsolateral prefrontal cortex in both hemispheres. [26]

Functional magnetic resonance imaging Edit

Functional magnetic resonance imaging (fMRI) involves the indirect measurement of neural activity by measuring disturbances in local magnetic fields in the brain. These local disturbances are linked to differential amounts of blood flow to the brain, which is linked to neural activity. Early work using fMRI has studied whether individual differences in personality traits and sociocognitive functioning are associated with individual differences in neural activations in certain brain regions during certain tasks. Such studies have demonstrated associations between single brain regions’ neural responses to certain tasks and individual differences in a wide range of sociocognitive functioning, such as approach/avoidance behavior, [27] sensitivity to rejection, [28] conceptions of the self, [29] [30] and susceptibility to persuasive messages. [31] A small collection of fMRI studies have also demonstrated a significant relationship between brain responses to certain tasks and personality survey measures, such as extraversion and neuroticism. [32] [33]

Over time, neuroscience researchers have recognized that brain regions do not operate in isolation. In fact, the synchronization of firing rates of neurons across different brain regions helps mediate the integration and processing of information across the brain. [34] [35] Thus, studies relating neural activation in single regions to personality measures and associated sociocognitive functioning ignore information about how personality and sociocognitive functioning relate to neural activations across multiple regions in the brain. For example, it is unlikely that neural activation in a single brain region is unilaterally associated with individual differences in personality measures, such as the tendency to down-regulate negative emotions. However, the functional connectivity, or the synchronization of neural activity, between two brain regions can be related to individual differences in personality and sociocognitive functioning. For example, one study found that in an emotion regulation task, coupling of neural responses in the amygdala and the prefrontal cortex was significantly associated with more successful regulation of negative emotions. [36] Other studies shown that neuroticism is associated with relatively low functional connectivity between amygdala and anterior cingulate cortex during a variety of tasks, such as viewing negative emotional stimuli [37] [38] and during a classical conditioning reward task. [39]

Resting-state functional connectivity Edit

Functional connectivity can also be measured at rest, during which individuals are not explicitly engaged in any task. [40] These resting-state functional connectivities can also be related to personality measures and other sociocognitive functioning. For instance, one study found that functional connectivity patterns originating from the amygdala are predictive of neuroticism and extraversion scores. [41] However, personality measures and sociocognitive functioning are not subserved solely by the functional connectivity between two given brain regions. Indeed, examining functional connectivity across the brain may shed more light on the neurobiological basis of personality and sociocognitive functioning. [42] For example, a recent line of research has demonstrated that individual differences in functional connectomes, which are characterized by patterns of spontaneous synchronization of neural activations across the entire brain, are predictive of individual differences in personality and sociocognitive functioning, such as openness to experience, [43] fluid intelligence, [44] and trait levels of paranoia. [45] The use of functional connectomes to predict individual differences is known as “functional connectome fingerprinting” and allows researcher to construct models of personality and sociocognitive functioning based on neural activity across the whole brain rather than within single regions (if using neural activations) or single pairs of regions (if using functional connectivity). [46]


Brain Imaging / Scanning Techniques (Neuroimaging)

Below is a compilation of brain imaging (neuroimaging) or brain scanning techniques that have been utilized throughout history along with a brief description of how they work, the associated advantages, and disadvantages associated with each development. While the fMRI currently remains the most popular brain scanning technology, various other techniques such as: CT, PET, and SPECT are still commonly used for various purposes. In addition, many of the brain imaging technologies are used simultaneously as “combined” scans.


Brain imaging study pinpoints neurotransmitter that may be responsible for yoga’s mood-boosting effect

A recent study found tentative evidence to suggest that yoga exerts its mood-boosting effect by increasing GABA activity among individuals with depression. The study, published in the Journal of Alternative and Complementary Medicine, further suggests that yoga’s beneficial effects on mood are time-limited.

While medication can be highly effective in reducing symptoms of major depressive disorder (MDD), many individuals do not reach remission without additional treatment. Interestingly, yoga interventions have shown promise in reducing depressive symptoms, although it is not clear why.

“Integrative medicine includes consideration of the mind-body interface. Yoga can be used to address many form of illness especially those due to Life Style Choices,” said study author Chris C. Streeter, an associate professor of psychiatry and neurology at the Boston University School of Medicine.

“Many form of western medicine help reduce symptoms but to do completely return people to wellness, the addition of yoga to a treatment regime can increase wellness/decrease symptoms.”

Streeter and her colleagues set out to explore the idea that a yoga intervention increases mood through its effect on an amino acid neurotransmitter called gamma-aminobutyric acid (GABA). The researchers were motivated by findings linking the neurotransmitter to depression.

Specifically, insufficiency in the GABA system has been linked to depressive symptoms, and individuals with MDD have been found to have low GABA levels. On the other hand, yoga interventions have been purported to increase GABA activity.

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Streeter and team recruited 32 adults with MDD for a 12-week yoga intervention. Patients were assigned to either a high-dose intervention of three yoga sessions a week or a low-dose intervention of two yoga sessions a week. The yoga sessions included 60 minutes of Iyengar yoga, 10 minutes of relaxation, 20 minutes of breathing practice, and homework exercises.

Throughout the study, the patients underwent magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) scans before the 12-week intervention and following the intervention. At the end of the intervention, all participants took part in an additional 90-minute yoga session and then a third and final brain scan.

The researchers found that the overall direction of the data when considering all participants, pointed to increases in GABA levels between the first and last scans, and the second and third scans. However, there were no differences between the high-dose yoga and low-dose yoga groups.

The findings provide evidence that “yoga is a low cost, low side effect means of improving mood and decreasing anxiety,” Streeter told PsyPost.

The researchers did find that the number of days since a subject’s latest yoga class appeared to be important, perhaps more so than the amount of yoga practice. Specifically, those who showed increased GABA levels at Scan 2 compared to Scan 1, had an average of 3.93 days since their last yoga session. Those whose GABA levels did not go up had an average of 7.83 days since their last yoga session.

“It is probable that the effects of yoga sessions, like pharmacologic treatments, are time limited,” the researchers remark. “The yoga tradition advocates daily practice. The increase in GABA levels seen after a yoga intervention was observed after an average of 4 days, but no longer observed after an average of 8 days.”

The participants had also completed assessments of depressive symptoms at various timepoints. The researchers found that subjects’ GABA levels were not significantly linked to their depressive symptoms. However, changes in depressive symptoms were inversely tied to GABA levels among the high-dose group. As the authors say, this means that depressive symptoms dropped as GABA levels rose.

With a very small sample size, the authors express that their findings are encouraging yet tentative, and future studies should explore the topic among a larger sample.

“The use of yoga for depression needs to be compared to antidepressants in a randomized controlled trial and in combination with anti-depressants,” Streeter said.

Still, the findings suggest that the GABA system may be a mechanism through which yoga improves mood, and practicing yoga at least one time a week may be the key to seeing these benefits.

“There are no magic bullets or pills that completely treat depression or anxiety — yoga is another tool available,” Streeter added. “Many stress-related disorders are associated with an imbalance in the autonomic nervous system with too much sympathetic (fight or flight) and to little parasympathetic (rest, renewal and social engagement). Yoga helps to correct this imbalance.”

The study, “Thalamic Gamma Aminobutyric Acid Level Changes in Major Depressive Disorder After a 12-Week Iyengar Yoga and Coherent Breathing Intervention”, was authored by Chris C. Streeter, Patricia L. Gerbarg, Richard P. Brown, Tammy M. Scott, Greylin H. Nielsen, Liz Owen, Osamu Sakai, Jennifer T. Sneider, Maren B. Nyer, and Marisa M. Silveri.


The Basics of Brain Imaging

This is archived NIDA Notes content. For current NIDA Notes, please visit drugabuse.gov.

Cite this article

NIDA. (1996, December 1). The Basics of Brain Imaging. Retrieved from https://archives.drugabuse.gov/news-events/nida-notes/1996/12/basics-brain-imaging

NIDA. "The Basics of Brain Imaging." National Institute on Drug Abuse, 1 Dec. 1996, https://archives.drugabuse.gov/news-events/nida-notes/1996/12/basics-brain-imaging.

NIDA. The Basics of Brain Imaging. National Institute on Drug Abuse website. https://archives.drugabuse.gov/news-events/nida-notes/1996/12/basics-brain-imaging. December 1, 1996.

The major neuroimaging techniques used in drug abuse research are positron emission tomography (PET), single photon emission computed tomography (SPECT),and magnetic resonance imaging (MRI), along with electro-encephalography(EEG), an earlier technique for monitoring brain activity. Advances in all these techniques are enabling scientists to produce remarkably detailed computer-screen images of brain structures and to observe neurochemical changes that occur in the brain as it processes information or responds to various stimuli such as drugs of abuse or drug abuse treatment medications.

PET, SPECT, MRI, and EEG are noninvasive procedures that can measure biological activity through the skull and reveal the living human brain at work. Each technique has its own advantages and each provides different information about brain structure and function. For this reason, scientists increasingly are conducting studies that integrate two or more techniques. For example, merging a PET scan image that shows activity at brain molecular sites, or receptors, with a highly detailed MRI image of brain structure can produce a composite image that makes it possible to identify more precisely where in the brain the activity is occurring.


Brain Imaging / Scanning Techniques (Neuroimaging)

Below is a compilation of brain imaging (neuroimaging) or brain scanning techniques that have been utilized throughout history along with a brief description of how they work, the associated advantages, and disadvantages associated with each development. While the fMRI currently remains the most popular brain scanning technology, various other techniques such as: CT, PET, and SPECT are still commonly used for various purposes. In addition, many of the brain imaging technologies are used simultaneously as “combined” scans.


Techniques Involving Electrical Activity

In some situations, it is helpful to gain an understanding of the overall activity of a person’s brain, without needing information on the actual location of the activity. Electroencephalography (EEG) serves this purpose by providing a measure of a brain’s electrical activity. An array of electrodes is placed around a person’s head (Figure 4). The signals received by the electrodes result in a printout of the electrical activity of his or her brain, or brainwaves, showing both the frequency (number of waves per second) and amplitude (height) of the recorded brainwaves, with an accuracy within milliseconds. Such information is especially helpful to researchers studying sleep patterns among individuals with sleep disorders.

Figure 4. Using caps with electrodes, modern EEG research can study the precise timing of overall brain activities. (credit: SMI Eye Tracking)


Long-range effects

After analyzing dopamine release in the striatum, the researchers set out to determine this dopamine might affect more distant locations in the brain. To do that, they performed traditional fMRI imaging on the brain while also mapping dopamine release in the striatum. “By combining these techniques we could probe these phenomena in a way that hasn’t been done before,” Jasanoff says.

The regions that showed the biggest surges in activity in response to dopamine were the motor cortex and the insular cortex. If confirmed in additional studies, the findings could help researchers understand the effects of dopamine in the human brain, including its roles in addiction and learning.

“Our results could lead to biomarkers that could be seen in fMRI data, and these correlates of dopaminergic function could be useful for analyzing animal and human fMRI,” Jasanoff says.

The research was funded by the National Institutes of Health and a Stanley Fahn Research Fellowship from the Parkinson’s Disease Foundation.


Contents

Personality can be defined as a set of characteristics or traits that drive individual differences in human behavior. From a biological perspective, these traits can be traced back to brain structures and neural mechanisms. However, this definition and theory of biological basis is not universally accepted. There are many conflicting theories of personality in the fields of psychology, psychiatry, philosophy, and neuroscience. A few examples of this are the nature vs. nurture debate and how the idea of a 'soul' fits into biological theories of personality. [1]

Since the time of the ancient Greeks, humankind has attempted to explain personality through spiritual beliefs, philosophy, and psychology. Historically, studies of personality have traditionally come from the social sciences and humanities, but in the past two decades neuroscience has begun to be more influential in the understanding of human personality. [2]

However, the most cited and influential figures in publishing the first biology-based personality theories are Hans Eysenck and Jeffrey Alan Gray. Eysenck used both behavioral and psychophysiological methodologies to test and develop his theories. [3] He published a book in 1947 called Dimensions of Personality, describing the personality dimensions of Extraversion and Neuroticism. Gray, a student of Eysenck, studied personality traits as individual differences in sensitivity to rewarding and punishing stimuli. [3] The significance of Gray's work and theories was his use of biology to define behavior, which stimulated a lot of subsequent research. [4]

In 1951, Hans Eysenck and Donald Prell published an experiment in which identical (monozygotic) and fraternal (dizygotic) twins, ages 11 and 12, were tested for neuroticism. It is described in detail in an article published in the Journal of Mental Science. in which Eysenck and Prell concluded that, "The factor of neuroticism is not a statistical artifact, but constitutes a biological unit which is inherited as a whole. neurotic predisposition is to a large extent hereditarily determined." [5] The study concluded that the neuroticism trait was a result of up to eighty percent of genetics. There was a stronger correlation among identical twins rather than fraternal twins. [6]

The idea of biology-based personality research is relatively new, but growing in interest and number of publications. [7] In August 2004, there was a conference specifically on the topic, called The Biological Basis of Personality and Individual Differences. [8] This allowed for presenting and sharing of ideas between psychologists, psychiatrists, molecular geneticists, and neuroscientists, and eventually gave birth to the book under the same title. [8] The book is a collection of current research (as of 2006) in the field contributed by many authors and edited by Turhan Canli. Recently, psychology professor Colin G. DeYoung has even named the idea as the field of "Personality Neuroscience." [9] Furthermore, a journal devoted to cultivating research investigating the neurobiological basis of personality has recently been established and is called "Personality Neuroscience." [10]

There are many theories of personality that centre on the identification of a set of traits that encompass human personality. Few however, are biologically based. This section will describe some theories of personality that have a biological basis.

Eysenck's three-factor model of personality Edit

Eysenck's three-factor model of personality was a causal theory of personality based on activation of reticular formation and limbic system. The reticular formation is a region in the brainstem that is involved in mediating arousal and consciousness. The limbic system is involved in mediating emotion, behavior, motivation, and long-term memory.

    (E) – degree to which people are outgoing and are interactive with people, which is mediated by the activation of the reticular formation. (N) – degree of emotional instability, which is associated with the limbic system. (P) – degree of aggression and interpersonal hostility.

Gray's reinforcement sensitivity theory Edit

Gray's reinforcement sensitivity theory (RST) is based on the idea that there are three brain systems that all differently respond to rewarding and punishing stimuli. [3]

    (FFFS) – mediates the emotion of fear (not anxiety) and active avoidance of dangerous situations. The personality traits associated with this system is fear-proneness and avoidance. (BIS) – mediates the emotion of anxiety and cautious risk-assessment behavior when entering dangerous situations due to conflicting goals. The personality traits associated with this system is worry-proneness and anxiety. (BAS) – mediates the emotion of 'anticipatory pleasure,' resulting from reactions to desirable stimuli. The personality traits associated with this system are optimism, reward-orientation, and impulsivity.

Cloninger model of personality Edit

This model of personality is based on the idea that different responses to punishing, rewarding, and novel stimuli the main characteristics of the human mind is caused by an interaction of the three dimensions below:

    (NS) – degree to which people are impulsive, correlated with low dopamine activity. (HA) – degree to which people are anxious, correlated with high serotonin activity. (RD) – degree to which people are approval seeking, correlated with low norepinephrine activity.

Five factor model of personality Edit

The five factor model (also known as the Big Five) is a widely used personality assessment that describes five core traits that a person possesses:

    – degree to which people enjoy experiencing new stimuli – degree to which people are dutiful and goal-oriented – degree to which people seek stimuli outside of themselves – degree to which people aim to cooperate and please others – degree to which people are emotionally unstable

There is large body of research relating the Big Five traits to individual differences in the brain's structure and function, as measured by MRI-based techniques. A selection of these findings are outlined in the "Brain imaging basis of personality" section below.

Two factor model of personality Edit

A higher-order factor structure can be derived from the Big Five traits, as these traits have often been found to be correlated. Agreeableness, Conscientiousness, and Neuroticism (reversed) can be distilled into a single factor α, or the Stability factor. On the other hand, Extraversion and Openness can be distilled into a single factor β, or the Plasticity factor. [11] [12] These two meta-traits have been shown to be significantly heritable using behavior genetic analysis, [13] which suggests a neurobiological basis that is unique and specific to these meta-traits. Indeed, a growing body of evidence demonstrates that serotonin is associated with Stability and dopamine is associated with Plasticity. [11] [12] [14]

There are many experimental techniques for measuring the biology of the brain, but there are five main methods used to investigate the biological basis of personality. [15] The biological data from these methods are commonly correlated with personality traits. These personality traits are often determined by personality questionnaires. However, personality questionnaires may be biased because they are self-reported. As a result, scientists emphasize using several different measures of personality, [15] [16] rather than solely self-reported measures of personality. For example, another measure of personality traits is observation of behavior. Both humans and animals have been observed to measure personality traits, but animals are particularly useful for studying the long-term behavioral-biological relationship of personality. [17]

Another interesting method that has become more sophisticated and affordable to researchers is the method of whole genome expression analysis. This method involves collecting data for a large number of genes simultaneously which provides many advantages in studying personality. In an article written by Alison M. Bell and Nadia Aubin-Horth, they describe the advantages very clearly by stating, "For one, it is probable that the genetic basis of personality is polygenic, so it makes sense to simultaneously study many genes. In addition, gene products rarely act alone. Instead, they perform their function by interacting together in pathways and networks. As a result, the molecular changes that characterize a phenotype are frequently not based on a single marker or gene, but rather on an entire pathway. Whole genome expression profiling therefore has the potential to reveal new candidates genes and pathways." [18]

Method Function Significance
Electroencephalography (EEG) This method measures electrical activity on the surface of the brain through the scalp, and has the high temporal resolution. [15] Before the advent of brain imaging technology, the only method to measure brain activity was electroencephalography (EEG). [15]
Brain Imaging Brain imaging can refer to either structural or functional imaging. Structural imaging allows for analysis using structural characteristics of the brain, whereas functional imaging involves measuring brain activity. Structural imaging of the brain can be accomplished by using Magnetic Resonance Imaging (MRI). Examples of functional imaging methods include Positron Emission Tomography (PET) and functional MRI (fMRI). PET scans measure the metabolism associated with brain activity, and fMRI measures the flow of blood in the brain, which reflects local brain activity. MRI has particularly high spatial resolution and is entirely non-invasive, whereas PET scans require the injection of radioactive tracers. Brain imaging has catalyzed research of the neurobiological correlates of personality. [3]
Molecular genetics This method is used to analyze a gene-trait link, by measuring the structure and function of genes in the brain. [15] The use of molecular genetics in biology-based personality research is expected to grow. [7]
Molecular assays This method is used to analyze the amount of psychoactive substances, such as hormones and neurotransmitters. Together, these two methods can specifically quantify, define, and manipulate the effects of brain molecules on behavior and personality traits. This has great clinical significance for treatment of personality disorders.
Pharmacological Manipulation This method is used to alter the levels of biochemicals, and observe the effects on behavior.

Neurotransmitters Edit

The biology-based personality theories (discussed below) are based on correlating personality traits with behavioral systems related to motivation, reward, and punishment. On a broad level, this involves the autonomic nervous system, fear-processing circuits in the amygdala, the reward pathway from the ventral tegmental area (VTA) to the nucleus accumbens and prefrontal cortex. All of these circuits heavily rely on neurotransmitters and their precursors, but there has been the most research support for dopamine and serotonin pathways:

    : Dopamine is a monoamine neurotransmitter that has been found to promote exploratory behavior. [19] Dopaminergic pathways have been specifically correlated with the extraversion trait of the Five Factor Model of Personality. [15] The monoamine oxidase (MAO) enzyme has a preferential affinity for dopamine, and its levels are inversely correlated with sensation seeking. [16] : Serotonin is a monoamine neurotransmitter, and has been found to promote avoidance behavior through inhibitory pathways. [19] Specifically, serotonin has been associated with Neuroticism, Agreeableness, and Conscientiousness (traits defined by the Five Factor Model of Personality). [15]

Genes Edit

Previous studies show that genes account for at most 50 percent of a given trait. [1] However, it is widely accepted that variance in gene sequence affect behavior, and genes are a significant risk factor for personality disorders. [20] With the growing interest in using molecular genetics in tracing the biological basis of personality, [8] there may be more gene-trait links found in the future.

Varying polymorphisms and sequence repeats in the gene for dopamine receptor D4 and serotonin transporter gene 5-HTTLPR, have both been found to influence the extraversion trait in adults. Specifically, study participants with at least one copy of the 7-repeat variant of the dopamine receptor D4 gene had higher scores of self-reported extraversion. [8] This suggests that dopamine and serotonin interact to regulate the conflicting behavioral traits of careless exploration vs. cautious inhibition. [19]

Synaptic plasticity Edit

Synaptic plasticity refers to the ability of neurons to strengthen or weaken the connections between them. According to Hebbian theory, these connections are strengthened and maintained through repeated stimulation between neurons. Specifically, there is an emphasis on long-term potentiation (LTP), which is the prolonged strengthening of synaptic connections that facilitate learning from experience.

On a larger scale, there are many pathways and brain regions that are interdependent and contribute to a cohesive, stable personality. For example, the amygdala and hippocampus of the limbic system mediate emotional intensity and consolidate memory of these experiences. But the basic mechanism by which these pathways and brain regions perform these functions, is synaptic plasticity. Ultimately, it boils down to this feature of neurons that allows the brain to learn from repeated experiences, retain memories, and ultimately maintain personality. [21] Joseph LeDoux, an award-winning neuroscientist, asserts that although humans share the same brain systems, it is the unique wiring of neurons that is different in each person and makes their personality. [21]

Over the past two decades, structural magnetic resonance imaging (sMRI) and functional magnetic resonance imaging (fMRI) techniques have been used to study associations between neural activations in the brain and personality traits and other cognitive, social, and emotional processes that characterize personality. Using MRI-based methods for such studies has become increasingly popular due to the non-invasive nature of MRI and the high resolution of MRI.

Structural magnetic resonance imaging Edit

The use of structural magnetic resonance imaging (sMRI) to understand the neurobiological basis of personality and sociocognitive functioning involves assessing the relationship between individual differences in these factors and individual differences in measures of brain structure, such as gray matter volume, cortical thickness, or structural integrity of white matter tracts.

Studies have shown that brain volume is meaningfully correlated with four of the Big Five personality measures. Extraversion was associated with increased volume of medial orbitofrontal cortex, a region associated with processing reward-related stimuli. Conscientiousness was associated with increased volume in the lateral prefrontal cortex, a region involved in planning and the voluntary control of behavior. Agreeableness was associated with increased volume in regions involved in mentalizing, which is the ability to infer the intentions and mental states of other individuals. Neuroticism was associated with increased volume of brain regions associated with threat, punishment, and negative emotions. Openness/Intellect was not significantly correlated with the volume of any brain structures. [22] In another study, neuroticism was negatively correlated with the gray matter volume of the right amygdala, whereas extraversion was positively correlated with gray matter volume of the left amygdala. [23] A separate study also reported a significant association between neuroticism scores and gray matter volume of the left amygdala. [24] In one MRI study, [25] Novelty Seeking correlated with increased grey matter volume in regions of the cingulate cortex, Harm Avoidance correlated with decreased grey matter volume in the orbitofrontal, occipital, and parietal cortex. Reward Dependence correlated with decreased grey matter volume in the caudate nucleus.

A separate but similar line of research has used diffusion tensor imaging to measure the structural integrity of white matter in the brain. One study has shown that neuroticism is negatively correlated with the structural integrity of white matter tracts that connect various brain regions, such as the prefrontal cortex, parietal cortex, amygdala, and other regions in the subcortex. On the other hand, Openness and Agreeableness are positively associated with the structural integrity of these white matter tracts. Openness was also positively associated with the structural integrity of white matter interconnecting dorsolateral prefrontal cortex in both hemispheres. [26]

Functional magnetic resonance imaging Edit

Functional magnetic resonance imaging (fMRI) involves the indirect measurement of neural activity by measuring disturbances in local magnetic fields in the brain. These local disturbances are linked to differential amounts of blood flow to the brain, which is linked to neural activity. Early work using fMRI has studied whether individual differences in personality traits and sociocognitive functioning are associated with individual differences in neural activations in certain brain regions during certain tasks. Such studies have demonstrated associations between single brain regions’ neural responses to certain tasks and individual differences in a wide range of sociocognitive functioning, such as approach/avoidance behavior, [27] sensitivity to rejection, [28] conceptions of the self, [29] [30] and susceptibility to persuasive messages. [31] A small collection of fMRI studies have also demonstrated a significant relationship between brain responses to certain tasks and personality survey measures, such as extraversion and neuroticism. [32] [33]

Over time, neuroscience researchers have recognized that brain regions do not operate in isolation. In fact, the synchronization of firing rates of neurons across different brain regions helps mediate the integration and processing of information across the brain. [34] [35] Thus, studies relating neural activation in single regions to personality measures and associated sociocognitive functioning ignore information about how personality and sociocognitive functioning relate to neural activations across multiple regions in the brain. For example, it is unlikely that neural activation in a single brain region is unilaterally associated with individual differences in personality measures, such as the tendency to down-regulate negative emotions. However, the functional connectivity, or the synchronization of neural activity, between two brain regions can be related to individual differences in personality and sociocognitive functioning. For example, one study found that in an emotion regulation task, coupling of neural responses in the amygdala and the prefrontal cortex was significantly associated with more successful regulation of negative emotions. [36] Other studies shown that neuroticism is associated with relatively low functional connectivity between amygdala and anterior cingulate cortex during a variety of tasks, such as viewing negative emotional stimuli [37] [38] and during a classical conditioning reward task. [39]

Resting-state functional connectivity Edit

Functional connectivity can also be measured at rest, during which individuals are not explicitly engaged in any task. [40] These resting-state functional connectivities can also be related to personality measures and other sociocognitive functioning. For instance, one study found that functional connectivity patterns originating from the amygdala are predictive of neuroticism and extraversion scores. [41] However, personality measures and sociocognitive functioning are not subserved solely by the functional connectivity between two given brain regions. Indeed, examining functional connectivity across the brain may shed more light on the neurobiological basis of personality and sociocognitive functioning. [42] For example, a recent line of research has demonstrated that individual differences in functional connectomes, which are characterized by patterns of spontaneous synchronization of neural activations across the entire brain, are predictive of individual differences in personality and sociocognitive functioning, such as openness to experience, [43] fluid intelligence, [44] and trait levels of paranoia. [45] The use of functional connectomes to predict individual differences is known as “functional connectome fingerprinting” and allows researcher to construct models of personality and sociocognitive functioning based on neural activity across the whole brain rather than within single regions (if using neural activations) or single pairs of regions (if using functional connectivity). [46]


Neuroimaging (Brain Imaging)

Neuroimaging or brain imaging is the use of various techniques to either directly or indirectly image the structure, function, or pharmacology of the nervous system. It is a relatively new discipline within medicine, neuroscience, and psychology.[1] Physicians who specialize in the performance and interpretation of neuroimaging in the clinical setting are neuroradiologists.

Neuroimaging falls into two broad categories:

  • Structural imaging, which deals with the structure of the nervous system and the diagnosis of gross (large scale) intracranial disease (such as a tumor) and injury.
  • Functional imaging, which is used to diagnose metabolic diseases and lesions on a finer scale (such as Alzheimer's disease) and also for neurological and cognitive psychology research and building brain-computer interfaces.

Functional imaging enables, for example, the processing of information by centers in the brain to be visualized directly. Such processing causes the involved area of the brain to increase metabolism and "light up" on the scan. One of the more controversial uses of neuroimaging has been researching "thought identification" or mind-reading.

The first chapter of the history of neuroimaging traces back to the Italian neuroscientist Angelo Mosso who invented the 'human circulation balance', which could non-invasively measure the redistribution of blood during emotional and intellectual activity.[2] However, although briefly mentioned by William James in 1890, the details and precise workings of this balance and the experiments Mosso performed with it have remained largely unknown until the recent discovery of the original instrument as well as Mosso&rsquos reports by Stefano Sandrone and colleagues.[3]

In 1918 the American neurosurgeon Walter Dandy introduced the technique of ventriculography. X-ray images of the ventricular system within the brain were obtained by injection of filtered air directly into one or both lateral ventricles of the brain. Dandy also observed that air introduced into the subarachnoid space via lumbar spinal puncture could enter the cerebral ventricles and also demonstrate the cerebrospinal fluid compartments around the base of the brain and over its surface. This technique was called pneumoencephalography.

In 1927 Egas Moniz introduced cerebral angiography, whereby both normal and abnormal blood vessels in and around the brain could be visualized with great precision.

In the early 1970s, Allan McLeod Cormack and Godfrey Newbold Hounsfield introduced computerized axial tomography (CAT or CT scanning), and ever more detailed anatomic images of the brain became available for diagnostic and research purposes. Cormack and Hounsfield won the 1979 Nobel Prize for Physiology or Medicine for their work. Soon after the introduction of CAT in the early 1980s, the development of radioligands allowed single photon emission computed tomography (SPECT) and positron emission tomography (PET) of the brain.

More or less concurrently, magnetic resonance imaging (MRI or MR scanning) was developed by researchers including Peter Mansfield and Paul Lauterbur, who were awarded the Nobel Prize for Physiology or Medicine in 2003. In the early 1980s MRI was introduced clinically, and during the 1980s a veritable explosion of technical refinements and diagnostic MR applications took place. Scientists soon learned that the large blood flow changes measured by PET could also be imaged by the correct type of MRI. Functional magnetic resonance imaging (fMRI) was born, and since the 1990s, fMRI has come to dominate the brain mapping field due to its low invasiveness, lack of radiation exposure, and relatively wide availability.

In the early 2000s, the field of neuroimaging reached the stage where limited practical applications of functional brain imaging have become feasible. The main application area is crude forms of brain-computer interface.

Indications

Neuroimaging follows a neurological examination in which a physician has found cause to more deeply investigate a patient who has or may have a neurological disorder.

One of the more common neurological problems which a person may experience is simple syncope.[4][5] In cases of simple syncope in which the patient's history does not suggest other neurological symptoms, the diagnosis includes a neurological examination but routine neurological imaging is not indicated because the likelihood of finding a cause in the central nervous system is extremely low and the patient is unlikely to benefit from the procedure.[5]

Neuroimaging is not indicated for patients with stable headaches which are diagnosed as migraine.[6] Studies indicate that presence of migraine does not increase a patient's risk for intracranial disease.[6] A diagnosis of migraine which notes the absence of other problems, such as papilledema, would not indicate a need for neuroimaging.[6] In the course of conducting a careful diagnosis, the physician should consider whether the headache has a cause other than the migraine and might require neuroimaging.[6]

Another indication for neuroimaging is CT-, MRI- and PET-guided stereotactic surgery or radiosurgery for treatment of intracranial tumors, arteriovenous malformations and other surgically treatable conditions.[7][8][9][10]

Brain imaging techniques

Computed axial tomography

Computed tomography (CT) or Computed Axial Tomography (CAT) scanning uses a series of x-rays of the head taken from many different directions. Typically used for quickly viewing brain injuries, CT scanning uses a computer program that performs a numerical integral calculation (the inverse Radon transform) on the measured x-ray series to estimate how much of an x-ray beam is absorbed in a small volume of the brain. Typically the information is presented as cross-sections of the brain.[11]

Diffuse optical imaging

Diffuse optical imaging (DOI) or diffuse optical tomography (DOT) is a medical imaging modality which uses near infrared light to generate images of the body. The technique measures the optical absorption of haemoglobin, and relies on the absorption spectrum of haemoglobin varying with its oxygenation status. High-density diffuse optical tomography (HD-DOT) has been compared directly to fMRI using response to visual stimulation in subjects studied with both techniques, with reassuringly similar results.[12] HD-DOT has also been compared to fMRI in terms of language tasks and resting state functional connectivity.[13]

Event-related optical signal

Event-related optical signal (EROS) is a brain-scanning technique which uses infrared light through optical fibers to measure changes in optical properties of active areas of the cerebral cortex. Whereas techniques such as diffuse optical imaging (DOT) and near-infrared spectroscopy (NIRS) measure optical absorption of haemoglobin, and thus are based on blood flow, EROS takes advantage of the scattering properties of the neurons themselves and thus provides a much more direct measure of cellular activity. EROS can pinpoint activity in the brain within millimeters (spatially) and within milliseconds (temporally). Its biggest downside is the inability to detect activity more than a few centimeters deep. EROS is a new, relatively inexpensive technique that is non-invasive to the test subject. It was developed at the University of Illinois at Urbana-Champaign where it is now used in the Cognitive Neuroimaging Laboratory of Dr. Gabriele Gratton and Dr. Monica Fabiani.

Magnetic resonance imaging

Magnetic resonance imaging (MRI) uses magnetic fields and radio waves to produce high quality two- or three-dimensional images of brain structures without the use of ionizing radiation (X-rays) or radioactive tracers.

Functional magnetic resonance imaging

Functional magnetic resonance imaging (fMRI) and arterial spin labeling (ASL) relies on the paramagnetic properties of oxygenated and deoxygenated hemoglobin to see images of changing blood flow in the brain associated with neural activity. This allows images to be generated that reflect which brain structures are activated (and how) during the performance of different tasks or at resting state. According to the oxygenation hypothesis, changes in oxygen usage in regional cerebral blood flow during cognitive or behavioral activity can be associated with the regional neurons as being directly related to the cognitive or behavioral tasks being attended.

Most fMRI scanners allow subjects to be presented with different visual images, sounds and touch stimuli, and to make different actions such as pressing a button or moving a joystick. Consequently, fMRI can be used to reveal brain structures and processes associated with perception, thought and action. The resolution of fMRI is about 2-3 millimeters at present, limited by the spatial spread of the hemodynamic response to neural activity. It has largely superseded PET for the study of brain activation patterns. PET, however, retains the significant advantage of being able to identify specific brain receptors (or transporters) associated with particular neurotransmitters through its ability to image radiolabelled receptor "ligands" (receptor ligands are any chemicals that stick to receptors).

As well as research on healthy subjects, fMRI is increasingly used for the medical diagnosis of disease. Because fMRI is exquisitely sensitive to oxygen usage in blood flow, it is extremely sensitive to early changes in the brain resulting from ischemia (abnormally low blood flow), such as the changes which follow stroke. Early diagnosis of certain types of stroke is increasingly important in neurology, since substances which dissolve blood clots may be used in the first few hours after certain types of stroke occur, but are dangerous to use afterward. Brain changes seen on fMRI may help to make the decision to treat with these agents. With between 72% and 90% accuracy where chance would achieve 0.8%,[14] fMRI techniques can decide which of a set of known images the subject is viewing.[15]

Magnetoencephalography

Magnetoencephalography (MEG) is an imaging technique used to measure the magnetic fields produced by electrical activity in the brain via extremely sensitive devices such as superconducting quantum interference devices (SQUIDs) or spin exchange relaxation-free[16] (SERF) magnetometers. MEG offers a very direct measurement of neural electrical activity (compared to fMRI for example) with very high temporal resolution but relatively low spatial resolution. The advantage of measuring the magnetic fields produced by neural activity is that they are likely to be less distorted by surrounding tissue (particularly the skull and scalp) compared to the electric fields measured by electroencephalography (EEG). Specifically, it can be shown that magnetic fields produced by electrical activity are not affected by the surrounding head tissue, when the head is modeled as a set of concentric spherical shells, each being an isotropic homogeneous conductor. Real heads are non-spherical and have largely anisotropic conductivities (particularly white matter and skull). While skull anisotropy has a negligible effect on MEG (unlike EEG), white matter anisotropy strongly affects MEG measurements for radial and deep sources.[17] Note, however, that the skull was assumed to be uniformly anisotropic in this study, which is not true for a real head: the absolute and relative thicknesses of diploë and tables layers vary among and within the skull bones. This makes it likely that MEG is also affected by the skull anisotropy,[18] although probably not to the same degree as EEG.

There are many uses for MEG, including assisting surgeons in localizing a pathology, assisting researchers in determining the function of various parts of the brain, neurofeedback, and others.

Positron emission tomography

Positron emission tomography (PET) and brain positron emission tomography, measure emissions from radioactively labeled metabolically active chemicals that have been injected into the bloodstream. The emission data are computer-processed to produce 2- or 3-dimensional images of the distribution of the chemicals throughout the brain.[19]:57 The positron emitting radioisotopes used are produced by a cyclotron, and chemicals are labeled with these radioactive atoms. The labeled compound, called a radiotracer, is injected into the bloodstream and eventually makes its way to the brain. Sensors in the PET scanner detect the radioactivity as the compound accumulates in various regions of the brain. A computer uses the data gathered by the sensors to create multicolored 2- or 3-dimensional images that show where the compound acts in the brain. Especially useful are a wide array of ligands used to map different aspects of neurotransmitter activity, with by far the most commonly used PET tracer being a labeled form of glucose (see Fludeoxyglucose (18F) (FDG)).

The greatest benefit of PET scanning is that different compounds can show blood flow and oxygen and glucose metabolism in the tissues of the working brain. These measurements reflect the amount of brain activity in the various regions of the brain and allow to learn more about how the brain works. PET scans were superior to all other metabolic imaging methods in terms of resolution and speed of completion (as little as 30 seconds) when they first became available. The improved resolution permitted better study to be made as to the area of the brain activated by a particular task. The biggest drawback of PET scanning is that because the radioactivity decays rapidly, it is limited to monitoring short tasks.[19]:60 Before fMRI technology came online, PET scanning was the preferred method of functional (as opposed to structural) brain imaging, and it continues to make large contributions to neuroscience.

PET scanning is also used for diagnosis of brain disease, most notably because brain tumors, strokes, and neuron-damaging diseases which cause dementia (such as Alzheimer's disease) all cause great changes in brain metabolism, which in turn causes easily detectable changes in PET scans. PET is probably most useful in early cases of certain dementias (with classic examples being Alzheimer's disease and Pick's disease) where the early damage is too diffuse and makes too little difference in brain volume and gross structure to change CT and standard MRI images enough to be able to reliably differentiate it from the "normal" range of cortical atrophy which occurs with aging (in many but not all) persons, and which does not cause clinical dementia.

Single-photon emission computed tomography

Single-photon emission computed tomography (SPECT) is similar to PET and uses gamma ray-emitting radioisotopes and a gamma camera to record data that a computer uses to construct two- or three-dimensional images of active brain regions.[20] SPECT relies on an injection of radioactive tracer, or "SPECT agent," which is rapidly taken up by the brain but does not redistribute. Uptake of SPECT agent is nearly 100% complete within 30 to 60 seconds, reflecting cerebral blood flow (CBF) at the time of injection. These properties of SPECT make it particularly well-suited for epilepsy imaging, which is usually made difficult by problems with patient movement and variable seizure types. SPECT provides a "snapshot" of cerebral blood flow since scans can be acquired after seizure termination (so long as the radioactive tracer was injected at the time of the seizure). A significant limitation of SPECT is its poor resolution (about 1 cm) compared to that of MRI. Today, SPECT machines with Dual Detector Heads are commonly used, although Triple Detector Head machines are available in the marketplace. Tomographic reconstruction, (mainly used for functional "snapshots" of the brain) requires multiple projections from Detector Heads which rotate around the human skull, so some researchers have developed 6 and 11 Detector Head SPECT machines to cut imaging time and give higher resolution.[21][22]

Like PET, SPECT also can be used to differentiate different kinds of disease processes which produce dementia, and it is increasingly used for this purpose. Neuro-PET has a disadvantage of requiring the use of tracers with half-lives of at most 110 minutes, such as FDG. These must be made in a cyclotron, and are expensive or even unavailable if necessary transport times are prolonged more than a few half-lives. SPECT, however, is able to make use of tracers with much longer half-lives, such as technetium-99m, and as a result, is far more widely available.

Cranial ultrasound

Cranial ultrasound is usually only used in babies, whose open fontanelles provide acoustic windows allowing ultrasound imaging of the brain. Advantages include the absence of ionising radiation and the possibility of bedside scanning, but the lack of soft-tissue detail means MRI is preferred for some conditions.

Advantages and Concerns of Neuroimaging Techniques

Functional Magnetic Resonance Imaging (fMRI)

fMRI is commonly classified as a minimally-to-moderate risk due to its non-invasiveness compared to other imaging methods. fMRI uses blood oxygenation level dependent (BOLD)-contrast in order to produce its form of imaging. BOLD-contrast is a naturally occurring process in the body so fMRI is often preferred over imaging methods that require radioactive markers to produce similar imaging.[23] A concern in the use of fMRI is its use in individuals with medical implants or devices and metallic items in the body. The magnetic resonance (MR) emitted from the equipment can cause failure of medical devices and attract metallic objects in the body if not properly screened for. Currently, the FDA classifies medical implants and devices into three categories, depending on MR-compatibility: MR-safe (safe in all MR environments), MR-unsafe (unsafe in any MR environment), and MR-conditional (MR-compatible in certain environments, requiring further information).[24]

Computed Tomography (CT) Scan

The CT scan was introduced in the 1970s and quickly became one of the most widely used methods of imaging. A CT scan can be performed in under a second and produce rapid results for clinicians, with its ease of use leading to an increase in CT scans performed in the United States from 3 million in 1980 to 62 million in 2007. Clinicians oftentimes take multiple scans, with 30% of individuals undergoing at least 3 scans in one study of CT scan usage[26]. CT scans can expose patients to levels of radiation 100-500 times higher than traditional x-rays, with higher radiation doses producing better resolution imaging.[27] While easy to use, increases in CT scan use, especially in asymptomatic patients, is a topic of concern since patients are exposed to significantly high levels of radiation[26].

Positron Emission Tomography (PET)

In PET scans, imaging does not rely on intrinsic biological processes, but relies on a foreign substance injected into the bloodstream traveling to the brain. Patients are injected with radioisotopes that are metabolized in the brain and emit positrons to produce a visualization of brain activity.[23] The amount of radiation a patient is exposed to in a PET scan is relatively small, comparable to the amount of environmental radiation an individual is exposed to across a year. PET radioisotopes have limited exposure time in the body as they commonly have very short half-lives (

2 hours) and decay rapidly.[28] Currently, fMRI is a preferred method of imaging brain activity compared to PET, since it does not involve radiation, has a higher temporal resolution than PET, and is more readily available in most medical settings.[23]

Magnetoencephalography (MEG) & Electroencephalography (EEG)

The high temporal resolution of MEG and EEG allow these methods to measure brain activity down to the millisecond. Both MEG and EEG do not require exposure of the patient to radiation to function. EEG electrodes detect electrical signals produced by neurons to measure brain activity and MEG uses oscillations in the magnetic field produced by these electrical currents to measure activity. A barrier in the widespread usage of MEG is due to pricing, as MEG systems can cost millions of dollars. EEG is a much more widely used method to achieve such temporal resolution as EEG systems cost much less than MEG systems. A disadvantage of EEG and MEG is that both methods have poor spatial resolution when compared to fMRI.[23]

Criticism and cautions

Some scientists have criticized the brain image-based claims made in scientific journals and the popular press, like the discovery of "the part of the brain responsible" for functions like talents, specific memories, or generating emotions such as love. Many mapping techniques have a relatively low resolution, including hundreds of thousands of neurons in a single voxel. Many functions also involve multiple parts of the brain, meaning that this type of claim is probably both unverifiable with the equipment used, and generally based on an incorrect assumption about how brain functions are divided. It may be that most brain functions will only be described correctly after being measured with much more fine-grained measurements that look not at large regions but instead at a very large number of tiny individual brain circuits. Many of these studies also have technical problems like small sample size or poor equipment calibration which means they cannot be reproduced - considerations which are sometimes ignored to produce a sensational journal article or news headline. In some cases the brain mapping techniques are used for commercial purposes, lie detection, or medical diagnosis in ways which have not been scientifically validated.[29]

This article is licensed under the GNU Free Documentation License. It uses material from the Wikipedia article "Neuroimaging."


Neuroimaging Part I

Bradley R. Buchbinder , in Handbook of Clinical Neurology , 2016

Synaptic activity dominantly drives signaling-related energy metabolism

Functional neuroimaging has often been assumed to reflect the regional intensity of action potentials (APs) ( Raichle and Mintun, 2006 ). However, APs only represent the output of the postsynaptic neuron, while excitatory and inhibitory postsynaptic potentials (EPSPs, IPSPs) represent its input. The relative contributions of the input synaptic activity and output spike activity to functional neuroimaging signals are important to their meaningful interpretation.

The relative energies consumed by postsynaptic potentials and APs inform their contributions to functional neuroimaging signals. Most signaling-related energy (91%) is expended by Na + /K + ATPase to restore transmembrane ion gradients, which are dissipated by excitatory, primarily glutamatergic, synaptic signaling and to maintain the resting potential ( Attwell and Laughlin, 2001 Howarth et al., 2012 ). Processes related to neurotransmitter release, recycling, and vesicular repackaging account for the remaining 9%. Inhibitory synaptic activity, most commonly mediated by γ-aminobutyric acid (GABA), consumes negligible energy itself. Of the signaling-related energy expenditures, EPSPs account for 50%, APs for 21%, the resting potential for 20%, presynaptic glutamate release for 5%, and glutamate recycling for 4%. Thus, compared with output spike activity (21%), excitatory input synaptic activity accounts for the majority (59%) of cortical signaling-related energy expenditure.


Imaging technique maps serotonin activity in living brains

Molecular fMRI data showing signal changes from serotonin sensors in the absence (left) and presence (right) of the antidepressant Prozac, with each square denoting an individual brain voxel. Red squares indicate the signal has increased, as more serotonin is absorbed into neurons blue squares indicate the signal has decreased, as less serotonin is absorbed into neurons. Dotted and solid lines graphed in each square show how the signal changes over time. The swirling black lines indicate features of the brain. A computer model uses this data to estimate neurotransmitter reuptake across the brain. Credit: Massachusetts Institute of Technology

Serotonin is a neurotransmitter that's partly responsible for feelings of happiness and for mood regulation in humans. This makes it a common target for antidepressants, which block serotonin from being reabsorbed by neurons after it has dispatched its signal, so more of it stays floating around the brain.

Now MIT researchers have developed an imaging technique that, for the first time, enables three-dimensional mapping of serotonin as it's reabsorbed into neurons, across multiple regions of the living brain. This technique, the researchers say, gives an unprecedented view of serotonin dynamics, and could be a powerful tool for the research and development of antidepressants.

"Until now, it was not possible to look at how neurotransmitters are transported into cells across large regions of the brain," says Aviad Hai, a postdoc in the Department of Biological Engineering and first author of a paper describing the technique in today's issue of Neuron. "It's the first time you can see the inhibitors of serotonin reuptake, like antidepressants, working in different parts of the brain, and you can use this information to analyze all sorts of antidepressant drugs, discover new ones, and see how those drugs affect the serotonin system across the brain."

The paper's other authors are Alan Jasanoff, a professor of biological engineering and three other researchers in Jasanoff's lab: Lili X. Cai, Taekwan Lee, and Victor S. Lelyveld.

Many antidepressants that target serotonin work by blocking serotonin transporters that reabsorb the neurotransmitter into a neuron, so it can be reused after it has sent a chemical signal. Aptly called "selective serotonin reuptake inhibitors" (SSRIs), these drugs increase levels of serotonin in the brain, alleviating feelings of anxiety and depression caused by low levels of the neurotransmitter.

Researchers most commonly study the effect of antidepressants using a technique known as microdialysis, in which they insert a probe into the brain to take tiny chemical samples from the tissue. But this method is time-consuming and limited in scope, as it allows them to study only a single location at a time.

For the new imaging technique, the researchers engineered a protein to act as a sensor that latches onto serotonin and detaches at the moment of reuptake. The sensor is injected, along with serotonin, and emits a signal that can be read by functional magnetic resonance imaging (fMRI). The trick is that the sensor remains off—emitting a low signal—when bound to serotonin, and turns on—creating a much brighter signal—when serotonin is removed.

In the new system, a mathematical model uses the fMRI signal data to construct a 3-D map that consists of more than 1,000 voxels (pixels in three dimensions), with each voxel representing a single point of measurement of serotonin reuptake. Based on the signal strength at each point, the model calculates the amount of serotonin that gets absorbed, in the presence and absence of SSRIs.

"Basically, what we've seen in this work is a method for measuring how much of a neurotransmitter is being [absorbed], and how that amount, or rate, is affected by different drugs . in a highly parallel fashion across much of the brain," Jasanoff says. That information could be very valuable for testing drug efficacy, he says.

Mapping antidepressant dynamics

To validate the sensor, the researchers successfully measured the expected effect of the SSRI fluoxetine, commonly called Prozac, on serotonin transporters in six subregions of a brain area known as the basal ganglia. These subregions are thought to play a role in motivation, reward, cognition, learning, emotion, and other functions and behaviors.

In doing so, the researchers simultaneously recorded a stronger decrease of serotonin reuptake in response to Prozac among three of the subregions, while noting a very weak response in one other region. These results were, more or less, anticipated, Jasanoff says. "But now we're able to map that effect in three dimensions, across brain regions," he says, which could lead to advances in studying the effects of drugs on specific parts of the brain.

But the researchers did uncover a surprising finding. While mapping the effects of a dopamine transport reuptake inhibitor—made to target only dopamine—they found the drug reduced serotonin reuptake, to an extent comparable to that of SSRIs, in three subregions, one of which is known for high dopamine transporter expression. Previous studies had indicated that dopamine transporter proteins can aid in low levels of serotonin reuptake, but the new findings show the effect is widespread in the living brain, Jasanoff says.

This experiment provides further proof of a strong interplay between the serotonin and dopamine systems, and indicates that antidepressants may be less effective when targeting just one of the two neurotransmitters, Hai says. "It may not be sufficient to just block serotonin reuptake, because there's another system—dopamine—that plays a role in serotonin transport as well," he says. "It's almost proof that when you use antidepressants that . target both systems, it could be more effective."

Next steps for the researchers are to explore different regions of the brain with this sensor, including the dorsal raphe, which produces most of the brain's serotonin. They're also making another nanoparticle-based sensor that is more sensitive than one used for this study.


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