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Should I stay or should I go? On the importance of aversive memories and the endogenous cannabinoid system

Memory is not a simple box of souvenirs; it is also, and most importantly, a safety system for organisms. With the help of negative memories, known as aversive memories, we can avoid a threat that we have already confronted. Researchers from Inserm and University of Bordeaux have just discovered that the cannabinoid receptors of the brain control these memories that are crucial for survival. This study is published in Neuron.

When confronted by danger, every individual has to make a crucial choice. This type of simple decision may determine his/her destiny: if the fire alarm goes off, we have learned to heed it and flee, and not to ignore it. In the same way, we avoid food and drinks that might have made us sick in the past.

The body is thus equipped with neurological mechanisms that help it to adjust its behaviour in response to a stimulus. Such is the case with aversive memories, a key survival process, which prepares the body to avoid these potential dangers effectively. These memories are accompanied by physiological responses (fright and flight) that enable one to get away from a dangerous situation.

Although the role of the habenula, a central region of the brain, in this phenomenon has received a great deal of attention in recent years, the same is not true of the endogenous cannabinoid system of the habenular neurons, on which Giovanni Marsicano and his team (particularly Edgar Soria-Gomez) have focused. This system involves the type 1 cannabinoid receptors. These receptors, the activity of which is normally regulated by endocannabinoids the bodys own molecules are the target of the main psychoactive components of cannabis.

The researchers conditioned mice so that they reacted to certain danger signals (sounds or smells). When they exposed them to these signals, mice that were deficient in cannabinoid receptors in the habenula expressed neither the fear nor the repulsion observed in normal mice. Interestingly, this impaired reaction did not apply to neutral or positive memories, which remained unchanged in these mice.

At molecular level, the scientists observed that, although the functioning of the habenula normally involves two molecules (acetylcholine and glutamate), the defect observed in these mice is caused by an imbalance in neurotransmission involving only acetylcholine.

These results demonstrate that the endogenous cannabinoid system in the habenula exclusively controls the expression of aversive memories, without influencing neutral or positive memories, and does so by selectively modulating acetylcholine in the neural circuits involved, explains Giovanni Marsicano, Inserm Research Director.

The control of these particular memories is an integral part of diseases associated with the emotional process, such as depression, anxiety or drug addiction. As a consequence, the endogenous cannabinoid system of the habenula might represent a new therapeutic target in the management of these conditions.

Filed under memory habenula endocannabinoids cannabinoid system acetylcholine neuroscience science

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Stem Cell Research Hints at Evolution of Human Brain

The human cerebral cortex contains 16 billion neurons, wired together into arcane, layered circuits responsible for everything from our ability to walk and talk to our sense of nostalgia and drive to dream of the future. In the course of human evolution, the cortex has expanded as much as 1,000-fold, but how this occurred is still a mystery to scientists.

Now, researchers at UC San Francisco have succeeded in mapping the genetic signature of a unique group of stem cells in the human brain that seem to generate most of the neurons in our massive cerebral cortex.

The new findings, published Sept. 24 in the journal Cell, support the notion that these unusual stem cells may have played an important role in the remarkable evolutionary expansion of the primate brain.

We want to know what it is about our genetic heritage that makes us unique, said Arnold Kriegstein, MD, PhD, professor of developmental and stem cell biology and director of the Eli and Edyth Broad Center of Regeneration Medicine and Stem Cell Research at UCSF. Looking at these early stages in development is the best opportunity to understand our brains evolution.

Building a Brain from the Inside Out

The grand architecture of the human cortex, with its hundreds of distinct cell types, begins as a uniform layer of neural stem cells and builds itself from the inside out during several months of embryonic development.

Until recently, most of what scientists knew about this process came from studies of model organisms such as mice, where nearly all neurons are produced by stem cells called ventricular radial glia (vRGs) that inhabit a fertile layer of tissue deep in the brain called the ventricular zone (VZ). But recent insights suggested that the development of the human cortex might have some additional wrinkles.

In 2010, Kriegsteins lab discovered a new type of neural stem cell in the human brain, which they dubbed outer radial glia (oRGs) because these cells reside farther away from the nurturing ventricles, in an outer layer of the subventricular zone (oSVZ). To the researchers surprise, further investigations revealed that during the peak of cortical development in humans, most of the neuron production was happening in the oSVZ rather than the familiar VZ.

oRG stem cells are extremely rare in mice, but common in primates, and look and behave quite differently from familiar ventricular radial glia. Their discovery immediately made Kriegstein and colleagues wonder whether this unusual group of stem cells could be a key to understanding what allowed primate brains to grow to their immense size and complexity.

We wanted to know more about the differences between these two different stem cell populations, said Alex Pollen, PhD, a postdoctoral researcher in Kriegsteins lab and co-lead author of the new study. We predicted oRGs could be a major contributor to the development of the human cortex, but at first we only had circumstantial evidence that these cells even made neurons.

Outsider Stem Cells Make Their Own Niche

In the new research, Pollen and co-first author Tomasz Nowakowski, PhD, also a postdoctoral researcher in the Kriegstein lab, partnered with Fluidigm Corp. to develop a microfluidic approach to map out the transcriptional profile the set of genes that are actively producing RNA of cells collected from the VZ and SVZ during embryonic development.

They identified gene expression profiles typical of different types of neurons, newborn neural progenitors and radial glia, as well as molecular markers differentiating oRGs and vRGs, which allowed the researchers to isolate these cells for further study.

The gene activity profiles also provided several novel insights into the biology of outer radial glia. For example, researchers had previously been puzzled as to how oRG cells could maintain their generative vitality so far away from the nurturing VZ. In the mouse, as cells move away from the ventricles, they lose their ability to differentiate into neurons, Kriegstein explained.

But the new data reveals that oRGs bring a support group with them: The cells express genes for surface markers and molecular signals that enhance their own ability to proliferate, the researchers found.

This is a surprising new feature of their biology, Pollen said. They generate their own stem cell niche.

The researchers used their new molecular insights to isolate oRGs in culture for the first time, and showed that these cells are prolific neuron factories. In contrast to mouse vRGs, which produce 10 to 100 daughter cells during brain development, a single human oRG can produce thousands of daughter neurons, as well as glial cellsnon-neuronal brain cells increasingly recognized as being responsible for a broad array of maintenance functions in the brain.

New Insights into Brain Evolution, Development and Disease

The discovery of human oRGs self-renewing niche and remarkable generative capacity reinforces the idea that these cells may have been responsible for the expansion of the cerebral cortex in our primate ancestors, the researchers said.

The research also presents an opportunity to greatly improve techniques for growing brain circuits in a dish that reflect the true diversity of the human brain, they said. Such techniques have the potential to enhance research into the origins of neurodevelopmental and neuropsychiatric disorders such as microcephaly, lissencephaly, autism and schizophrenia, which are thought to affect cell types not found in the mouse models that are often used to study such diseases.

The findings may even have implications for studying glioblastoma, a common brain cancer whose ability to grow, migrate and hack into the brains blood supply appears to rely on a pattern of gene activity similar to that now identified in these neural stem cells.

The cerebral cortex is so different in humans than in mice, Kriegstein said. If youre interested in how our brains evolved or in diseases of the cerebral cortex, this is a really exciting discovery.

The study represents the first salvo of a larger BRAIN Initiative-funded project in Kriegsteins lab to understand the thousands of different cell types that occupy the developing human brain

At the moment, we simply dont have a good understanding of the brains parts list, Kriegstein said, but studies like this are beginning to give us a real blueprint of how our brains are built.

Filed under stem cells radial glia glial cells cerebral cortex evolution gene expression neuroscience science

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Reproducible neuroscience with real tango Consonant results resonate in the brain

Most neuroscientific studies rely on a single experiment and assume their findings to be reliable. However, the validity of this assumption needs to be tested before accepting the findings as the ground truth. Indeed, the lack of replication studies in addition to the inconsistency of neuroimaging findings severely limits the advancement of knowledge in the field of neuroscience, all of which has recently become a hot topic within the neuroscientific community.

Concerned about this state of affairs, researchers at the Finnish Centre for Interdisciplinary Music Research (CIMR), University of Jyvskyl, in Finland, and from Aarhus University, in Denmark, aimed to replicate previous findings on how the brain processes music using a novel, naturalistic free listening context. Their results, published in Neuroimage, demonstrate that laboratory conditions resembling real-life contexts can yield reliable results, making findings more ecologically valid. The more we can simulate reality in a lab in a reliable way, the more truetolife the findings will be, and this is critical to modelling the way the brain actually understands the world, sums up Doctoral Student Iballa Burunat, the lead author of the study.

The research team employed an identical methodology as in the original study, but using a new group of participants. As in the original study, participants had to just listen to the musical piece Adis Nonino by A. Piazzolla. Researchers assessed how similar the observed brain activity was between the original and the new study. Replicating the experiment allowed the researchers to fine-tune the findings of the previous study, concluding what brain areas are involved in the processing of different musical elements, like tonality, timbre, and rhythm, and how accurately the neural correlates could be replicated for each of these musical elements. For instance, they observed that highlevel musical features, such as tonality and rhythm, were less replicable than lowlevel (timbral) ones. One reason for this may be that the neural processing of highlevel musical features is more sensitive to state and traits of the listeners compared to the processing of lowlevel features, which may hinder the replication of previous findings, says Academy Professor Petri Toiviainen, from the University of Jyvskyl, a co-author of the study.

When listening to a piece of music, we cant separate its auditory characteristics from its affective, cognitive, and contextual dimensions. It is precisely the integration of all these aspects that gives coherence to our listening experience. This is why taking a more naturalistic approach makes neuroscience more faithful to reality, a goal that a fully controlled setting that uses very simple and artificially created sounds falls short of. The success in replicating these findings should encourage scientists to move towards more reallife paradigms that capture the complexity of the real world.

The neuroscientific community needs to challenge the current scientific model driven by dysfunctional research practices tacitly encouraged by the publish or perish doctrine, which is precisely leading to the low reliability and the high discrepancy of results, states Iballa Burunat. The authors stress that more incentives are needed for replicating experiments, and agree that scientific journals should more often than not welcome replication studies to ensure that published research is robust and reliable.

Filed under brain activity neuroimaging music neuroscience science

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(Image caption: Lateral view of the Paranthropus robustus skull SK 46 from the site of Swartkrans, South Africa showing the 3D virtual reconstruction of the ear and the hearing results for the early hominins. Credit: Rolf Quam)

2-Million-Year-Old Fossils Reveal Hearing Abilities of Early Humans

Research into human fossils dating back to approximately two million years ago reveals that the hearing pattern resembles chimpanzees, but with some slight differences in the direction of humans.

Rolf Quam, assistant professor of anthropology at Binghamton University, led an international research team in reconstructing an aspect of sensory perception in several fossil hominin individuals from the sites of Sterkfontein and Swartkrans in South Africa. The study relied on the use of CT scans and virtual computer reconstructions to study the internal anatomy of the ear. The results suggest that the early hominin species Australopithecus africanus and Paranthropus robustus, both of which lived around 2 million years ago, had hearing abilities similar to a chimpanzee, but with some slight differences in the direction of humans.

Humans are distinct from most other primates, including chimpanzees, in having better hearing across a wider range of frequencies, generally between 1.0-6.0 kHz. Within this same frequency range, which encompasses many of the sounds emitted during spoken language, chimpanzees and most other primates lose sensitivity compared to humans.

We know that the hearing patterns, or audiograms, in chimpanzees and humans are distinct because their hearing abilities have been measured in the laboratory in living subjects, said Quam. So we were interested in finding out when this human-like hearing pattern first emerged during our evolutionary history.

Previously, Quam and colleagues studied the hearing abilities in several fossil hominin individuals from the site of the Sima de los Huesos (Pit of the Bones) in northern Spain. These fossils are about 430,000 years old and are considered to represent ancestors of the later Neandertals. The hearing abilities in the Sima hominins were nearly identical to living humans. In contrast, the much earlier South African specimens had a hearing pattern that was much more similar to a chimpanzee.

In the South African fossils, the region of maximum hearing sensitivity was shifted towards slightly higher frequencies compared with chimpanzees, and the early hominins showed better hearing than either chimpanzees or humans from about 1.0-3.0 kHz. It turns out that this auditory pattern may have been particularly favorable for living on the savanna. In more open environments, sound waves dont travel as far as in the rainforest canopy, so short range communication is favored on the savanna.

We know these species regularly occupied the savanna since their diet included up to 50 percent of resources found in open environments said Quam. The researchers argue that this combination of auditory features may have favored short-range communication in open environments.

That sounds a lot like language. Does this mean these early hominins had language? No, said Quam. Were not arguing that. They certainly could communicate vocally. All primates do, but were not saying they had fully developed human language, which implies a symbolic content.

The emergence of language is one of the most hotly debated questions in paleoanthropology, the branch of anthropology that studies human origins, since the capacity for spoken language is often held to be a defining human feature. There is a general consensus among anthropologists that the small brain size and ape-like cranial anatomy and vocal tract in these early hominins indicates they likely did not have the capacity for language.

We feel our research line does have considerable potential to provide new insights into when the human hearing pattern emerged and, by extension, when we developed language, said Quam.

Ignacio Martinez, a collaborator on the study, said, Were pretty confident about our results and our interpretation. In particular, its very gratifying when several independent lines of evidence converge on a consistent interpretation.

How do these results compare with the discovery of a new hominin species, Homo naledi, announced just two weeks ago from a different site in South Africa?

It would be really interesting to study the hearing pattern in this new species, said Quam. Stay tuned.

The study was published on Sept. 25 in the journal Science Advances.

Filed under hearing evolution australopithecus paranthropus communication neuroscience science

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Of brains and bones: How hunger neurons control bone mass

In an advance that helps clarify the role of a cluster of neurons in the brain, Yale School of Medicine researchers have found that these neurons not only control hunger and appetite, but also regulate bone mass.

The study is published Sept. 24 online ahead of print in the journal Cell Reports.

We have found that the level of your hunger could determine your bone structure, said one of the senior authors, Tamas L. Horvath, the Jean and David W. Wallace Professor of Comparative Medicine, and professor of neurobiology and obstetrics, gynecology, and reproductive sciences. Horvath is also director of the Yale Program in Integrative Cell Signaling and Neurobiology of Metabolism.

The less hungry you are, the lower your bone density, and surprisingly, the effects of these neurons on bone mass are independent of the effect of the hormone leptin on these same cells.

Horvath and his team focused on agouti-related peptide (AgRP) neurons in the hypothalamus, which control feeding and compulsive behaviors. Using mice that were genetically-engineered so their cells selectively interfere with the AgRP neurons, the team found that these same cells are also involved in determining bone mass.

The team further found that when the AgRP circuits were impaired, this resulted in bone loss and osteopenia in mice the equivalent of osteoporosis in women. But when the team enhanced AgRP neuronal activity in mice, this actually promoted increased bone mass.

Taken together, these observations establish a significant regulatory role for AgRP neurons in skeletal bone metabolism independent of leptins action, said co-senior author Dr. Karl Insogna, professor of medicine, and director of the Yale Bone Center. Based on our findings, it seems that the effect of AgRP neurons on bone metabolism in adults is mediated at least in part by the sympathetic nervous system, but more than one pathway is likely involved.

There are other mechanisms by which the AgRP system can affect bone mass, including actions on the thyroid, adrenal and gonad systems, Insogna added. Further studies are needed to assess the hormonal control of bone metabolism as a pathway modulated by AgRP neurons.

Filed under AgRP neurons hypothalamus leptin neural circuits bone mass neuroscience science

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From brain, to fat, to weight loss

Weight is controlled by the hormone leptin, which acts in the brain to regulate food intake and metabolism. However, it was largely unknown until now, how the brain signals back to the fat tissue to induce fat breakdown. Now, a breakthrough study led by Ana Domingos at Instituto Gulbenkian de Cincia (IGC; Portugal), in collaboration with Jeffrey Friedmans group at Rockefeller University (USA), has shown that fat tissue is innervated and that direct stimulation of neurons in fat is sufficient to induce fat breakdown. These results, published in the latest issue of the prestigious journal Cell, set up the stage for developing novel anti-obesity therapies.

Fat tissue constitutes 20 to 25% of human body weight being an energy storage container, in the form of triglycerides. Twenty years ago Jeffrey Friedman and colleagues identified the hormone leptin, which is produced by fat cells in amounts that are proportional to the amount of fat, and informs the brain about how much fat is available in the body. Leptin functions as an adipostat neuro-endocrine signal that preserves bodys fat mass in a relatively narrow range of variation. Low leptin levels increase appetite and lower basal metabolism, whereas high leptin levels blunt appetite and promote fat breakdown. However, until now it was largely unknown what circuits close the neuroendocrine loop, such that leptin action in the brain signals back to the fat.

Now, the research team led by Ana Domingos, combined a variety of techniques to functionally establish, for the first time, that white fat tissue is innervated. We dissected these nerve fibers from mouse fat, and using molecular markers identified these as sympathetic neurons, explains Ana Domingos. But most remarkable, when we used an ultra sensitive imaging technique, on the intact white fat tissue of a living mouse, we observed that fat cells can be encapsulated by these sympathetic neural terminals.

Next, researchers used genetic engineered mice, whose sympathetic neurons could be activated by blue light, to assess the functional relevance of these fat projecting neurons. Roksana Pirzgalska, a doctorate student in Domingos laboratory and co-first author of the study explains: We used a powerful technique called optogenetics, to locally activate these sympathetic neurons in fat pads of mice, and observed fat breakdown and fat mass reduction. Ana Domingos adds: The local activation of these neurons, leads to the release of norepinephrine, a neurotransmitter, that triggers a cascade of signals in fat cells leading to fat hydrolysis. Without these neurons, leptin is unable to drive fat-breakdown. The conclusions and future directions are clear according to Ana Domingos: This result provides new hopes for treating central leptin resistance, a condition in which the brains of obese people are insensitive to leptin. Senior co-author Jeffrey Friedman adds: These studies add an important new piece to the puzzle that enables leptin to induce fat loss.

Filed under leptin fat tissue weight loss neurons lipolysis neuroscience science

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Liquid crystals are familiar to most of us as the somewhat humdrum stuff used to make computer displays and TVs. Even for scientists, it has not been easy to find other uses.

(Image caption: These magnified images show how untreated liquid crystals (top) respond to the human islet amyloid peptide (lower right), which forms aggregates and is involved in diabetes; and rat islet amyloid (lower left), which does not aggregate. The actual width of these panels is 280 microns, approximately the diameter of several human hairs lying side by side. Credit: Courtesy of Advanced Functional Materials, Sadati and others)

Now a group of researchers at the University of Chicagos Institute for Molecular Engineering is putting liquid crystals to work in a completely unexpected realm: as detectors for the protein fibers implicated in the development of neuro-degenerative diseases such as Alzheimers. Their novel approach promises an easier, less costly way to detect these fibers and to do so at a much earlier stage of their formation than has been possible beforethe stage when they are thought to be the most toxic.

It is extremely important to develop techniques that allow us to detect the formation of these so-called amyloid fibrils when theyre first starting to grow, said Juan de Pablo, whose group did the new work. We have developed a system that allows us to detect them in a simple and inexpensive manner. And the sensitivity appears to be extremely high.

Amyloid fibrils are protein aggregates that are associated with the development of neuro-degenerative diseases, including Huntingtons, Parkinsons, Alzheimers and mad cow disease, as well as in Type 2 diabetes, where they damage the pancreatic islets. Scientists would like to be able to study their formation both for therapeutic reasons and so they can test the effect of new drugs on inhibiting their growth. But the fibrils that are believed to be most harmful are too tiny to be seen using an optical microscope. So scientists have relied on elaborate and expensive fluorescence- or neutron scattering-based techniques to study them.

A different approach

The de Pablo group took a completely different approach. They exploited the way a liquid crystal responds to a disturbance on its surface. The scientists made a film of a liquid crystal molecule called 5CB, which de Pablo calls the fruit fly of liquid crystal research because it is so well studied. Then they applied chemicals to the 5CB film that caused the molecules to align in such a way as to block the passage of light. Floating on top of the film was a membrane made of molecules resembling those found in the membranes of biological cells. And on top of that was water, into which the scientists injected the molecules that spontaneously form the toxic aggregates.

As aggregates grow on the membrane, they imprint their shape into the liquid crystal underneath, said de Pablo, the Liew Family Professor in Molecular Engineering. The liquid crystal molecules that are at the interface become distorted: they adopt a different orientation, so that light can now go through.

This disturbance on the membranethe imprint of the protein fibersis transmitted down through the liquid crystal film, in effect amplifying it.

The fibers might be tens of nanometers in diameter and a hundred nanometers long, far smaller than a red blood cell. But the disturbance they create is magnified by the liquid crystal so that it is large enough to be seen in polarized light with a simple optical microscope.

Microscopic bright spots

Seen through the microscope, the aggregates appear as tiny bright spots in a sea of black: bright where the liquid crystal has been disturbed to let light pass. The liquid crystal is actually reporting whats happening to the aggregates at the interface, de Pablo said. And these bright spots become bigger and adopt the shape of the actual fibers that the protein is forming. Except youre not seeing the fibers, youre seeing the liquid crystals response to the fibers.

The work of de Pablos team was published online Sept. 9, 2015, by the journal Advanced Functional Materials. Co-authoring the article were IME scientists Monirosadat Sadati, Julio Armas-Perez, Jose Martinez-Gonzalez, and Juan Hernandez-Ortiz, as well as Aslin Izmitli-Apik and Nicholas Abbott of the University of Wisconsin at Madison.

They relied crucially on theoretical molecular models, both to help guide them through the real system and to help them understand what they were seeing. They are now developing sensors for the amyloid fibrils that may allow experimenters to use droplets of liquid crystals in emulsion rather than the flat surfaces used in the proof-of-concept experiments.

That, said de Pablo, would be a lot easier for people to use. He envisions scientists eventually being able to test small samples of blood or other body fluid using the new detectors, or for drug researchers to put the amyloid proteins in water, inject their drug, and study how the drug influences the growth of the aggregates over time.

For research in Type 2 diabetes, or Alzheimers or Parkinsons, having this simple platform to perform these tests at a fraction of the cost of whats required for fluorescence or neutron scattering would be very useful.

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Neuroscience

Affective neuroscience is the study of the neural mechanisms of emotion. This interdisciplinary field combines neuroscience with the psychological study of personality, emotion, and mood.[1]

Emotions are thought to be related to activity in brain areas that direct our attention, motivate our behavior, and determine the significance of what is going on around us. Pioneering work by Paul Broca (1878),[2]James Papez (1937),[3] and Paul D. MacLean (1952)[4] suggested that emotion is related to a group of structures in the center of the brain called the limbic system, which includes the hypothalamus, cingulate cortex, hippocampi, and other structures. Research has shown that limbic structures are directly related to emotion, but non-limbic structures have been found to be of greater emotional relevance. The following brain structures are currently thought to be involved in emotion:[5]

The Right Hemisphere has been proposed over time as being directly involved in the processing of emotion. Scientific theory regarding the role of the right hemisphere has developed over time and resulted in several models of emotional functioning. C.K. Mills was one of the first researchers to propose a direct link between the right hemisphere and emotional processing, having observed decreased emotional processing in patients with lesions to the right hemisphere.[26][27] Emotion was originally thought to be processed in the limbic system structures such as the hypothalamus and amygdala.[28] As of the late 1980s to early 1990s however, neocortical structures were shown to have an involvement in emotion.[29] These findings led to the development of the Right Hemisphere Hypothesis and the Valence Hypothesis.

The Right Hemisphere Hypothesis asserts that the right hemisphere of the neocortical structures is specialized for the expression and perception of emotion.[30] The Right hemisphere has been linked with mental strategies that are nonverbal, synthetic, integrative, holistic, and Gestalt which makes it ideal for processing emotion.[29] The right hemisphere is more in touch with subcortical systems of autonomic arousal and attention as demonstrated in patients that have increased spatial neglect when damage is associated to the right brain as opposed to the left brain.[31] Right hemisphere pathologies have also been linked with abnormal patterns of autonomic nervous system responses.[32] These findings would help signify the relationship of the subcortical brain regions to the right hemisphere as having a strong connection.

The Valence Hypothesis acknowledges the right hemisphere's role in emotion, but asserts that it is mainly focused on the processing of negative emotions whereas the left hemisphere processes positive emotions. The mode of processing of the two hemispheres has been the discussion of much debate. One version suggests the lack of a specific mode of processes, stating that the right hemisphere is solely negative emotion and the left brain is solely positive emotion.[33] A second version suggests that there is a complex mode of processing that occurs, specifically that there is a hemispheric specialization for the expressing and experiencing of emotion, with the right hemisphere predominating in the experiencing of both positive and negative emotion.[34][35] More recently, the frontal lobe has been the focus of a large amount of research, stating that the frontal lobes of both hemispheres are involved in the emotional state, while the right posterior hemisphere, the parietal and temporal lobes, is involved in the processing of emotion.[36] Decreased right parietal lobe activity has been associated with depression[37] and increased right parietal lobe activity with anxiety arousal.[38] The increasing understanding of the role the different hemispheres play has led to increasingly complicated models, all based some way on the original valence model.[39]

In its broadest sense, cognition refers to all mental processes. However, the study of cognition has historically excluded emotion and focused on non-emotional processes (e.g., memory, attention, perception, action, problem solving and mental imagery).[40] As a result, the study of the neural basis of non-emotional and emotional processes emerged as two separate fields: cognitive neuroscience and affective neuroscience. The distinction between non-emotional and emotional processes is now thought to be largely artificial, as the two types of processes often involve overlapping neural and mental mechanisms.[41] Thus, when cognition is taken at its broadest definition, affective neuroscience could also be called the cognitive neuroscience of emotion.

The emotion go/no-go task has been frequently used to study behavioral inhibition, particularly emotional modulation of this inhibition.[42] A derivation of the original go/no-go paradigm, this task involves a combination of affective go cues, where the participant must make a motor response as quickly as possible, and affective no-go cues, where a response must be withheld. Because go cues are more common, the task is able to measure ones ability to inhibit a response under different emotional conditions.[43]

The task is common in tests of emotion regulation, and is often paired with neuroimaging measures to localize relevant brain function in both healthy individuals and those with affective disorders.[42][44][45] For example, go/no-go studies converge with other methodology to implicate areas of the prefrontal cortex during inhibition of emotionally valenced stimuli.[46]

The emotional Stroop task, an adaptation to the original Stroop, measures attentional bias to emotional stimuli.[47][48] Participants must name the ink color of presented words while ignoring the words themselves.[49] In general, participants have more difficulty detaching attention from affectively valenced words, than neutral words.[50][51] This interference from valenced words is measured by the response latency in naming the color of neutral words as compared with emotional words.[48]

This task has been often used to test selective attention to threatening and other negatively valenced stimuli, most often in relation to psychopathology.[52] Disorder specific attentional biases have been found for a variety of mental disorders.[52][53] For example, participants with spider phobia show a bias to spider-related words but not other negatively valenced words.[54] Similar findings have been attributed to threat words related to other anxiety disorders.[52] However, other studies have questioned these findings. In fact, anxious participants in some studies show the Stroop interference effect for both negative and positive words, when the words are matched for emotionality.[55][56] This means that the specificity effects for various disorders may be largely attributable to the semantic relation of the words to the concerns of the disorder, rather than simply the emotionality of the words.[52]

The Ekman faces task is used to measure emotion recognition of six basic emotions.[57][58] Black and white photographs of 10 actors (6 male, 4 female) are presented, with each actor displaying each basic emotion. Participants are usually asked to respond quickly with the name of the displayed emotion. The task is a common tool to study deficits in emotion regulation in patients with dementia, Parkinson's, and other cognitively degenerative disorders.[59] However, the task has also been used to analyze recognition errors in disorders such as borderline personality disorder, schizophrenia, and bipolar disorder.[60][61][62]

The emotional dot-probe paradigm is a task used to assess selective visual attention to and failure to detach attention from affective stimuli.[63][64] The paradigm begins with a fixation cross at the center of a screen. An emotional stimulus and a neutral stimulus appear side by side, after which a dot appears behind either the neutral stimulus (incongruent condition) or the affective stimulus (congruent condition). Participants asked to indicate when they see this dot, and response latency is measured. Dots that appear on the same side of the screen as the image the participant was looking at will be identified more quickly. Thus, it is possible to discern which object the participant was attending to by subtracting the reaction time to respond to congruent versus incongruent trials.[63]

The best documented research with the dot probe paradigm involves attention to threat related stimuli, such as fearful faces, in individuals with anxiety disorders. Anxious individuals tend to respond more quickly to congruent trials, which may indicate vigilance to threat and/or failure to detach attention from threatening stimuli.[63][65] A specificity effect of attention has also been noted, with individuals attending selectively to threats related to their particular disorder. For example, those with social phobia selectively attend to social threats but not physical threats.[66] However, this specificity may be even more nuanced. Participants with obsessive-compulsive disorder symptoms initially show attentional bias to compulsive threat, but this bias is attenuated in later trials due to habituation to the threat stimuli.[67]

Fear-potentiated startle (FPS) has been utilized as a psychophysiological index of fear reaction in both animals and humans.[68] FPS is most often assessed through the magnitude of the eyeblink startle reflex, which can be measured by electromyography.[69] This eyeblink reflex is an automatic defensive reaction to an abrupt elicitor, making it an objective indicator of fear.[70] Typical FPS paradigms involve bursts of noise or abrupt flashes of light transmitted while an individual attends to a set of stimuli.[70] Startle reflexes have been shown to be modulated by emotion. For example, healthy participants tend to show enhanced startle responses while viewing negatively valenced images and attenuated startle while viewing positively valenced images, as compared with neutral images.[71][72]

The startle response to a particular stimulus is greater under conditions of threat.[73] A common example given to indicate this phenomenon is that ones startle response to a flash of light will be greater when walking in a dangerous neighborhood at night than it would under safer conditions. In laboratory studies, the threat of receiving shock is enough to potentiate startle, even without any actual shock.[74]

Fear potentiated startle paradigms are often used to study fear learning and extinction in individuals with posttraumatic stress disorder and other anxiety disorders.[75][76][77] In fear conditioning studies, an initially neutral stimulus is repeatedly paired with an aversive one, borrowing from classical conditioning.[78] FPS studies have demonstrated that PTSD patients have enhanced startle responses during both danger cues and neutral/safety cues as compared with healthy participants.[78][79]

There are many ways affect plays a role during learning. Recently, affective neuroscience has done much to discover this role. Deep, emotional attachment to a subject area allows a deeper understanding of the material and therefore, learning occurs and lasts.[80] When reading, the emotions one is feeling in comparison to the emotions being portrayed in the content affects ones comprehension. Someone who is feeling sad will understand a sad passage better than someone feeling happy.[81] Therefore, a students emotion plays a big role during the learning process.

Emotion can also be embodied or perceived from words read on a page or a persons facial expression. Neuroimaging studies using fMRI have demonstrated that the same area of the brain being activated when one is feeling disgust is also activated when one observes another person feeling disgust.[82] In a traditional learning environment, the teacher's facial expression can play a critical role in students' language acquisition. Showing a fearful facial expression when reading passages that contain fearful tones facilitates students learning of the meaning of certain vocabulary words and comprehension of the passage.[83]

A meta-analysis is a statistical approach to synthesizing results across multiple studies. Several meta-analyses examining the brain basis of emotion have been conducted. In each meta-analysis, studies were included that investigate healthy, unmedicated adults and that used subtraction analysis to examine the areas of the brain that were more active during emotional processing that during a neutral control condition. The meta-analyses to date predominantly focus on two theoretical approaches, locationist approaches and psychological construction approaches.

These approaches to emotion hypothesize that several emotion categories (including happiness, sadness, fear, anger, and disgust) are biologically basic.[84][85] In this view, emotions are inherited biologically based modules that cannot be broken down into more basic psychological components.[84][85][86] Models following a locationist approach to emotion hypothesize that all mental states belonging to a single emotional category can be consistently and specifically localized to either a distinct brain region or a defined networks of brain regions.[85][87] Each basic emotion category also shares other universal characteristics: distinct facial behavior, physiology, subjective experience and accompanying thoughts and memories.[84]

This approach to emotion hypothesizes that emotions like happiness, sadness, fear, anger and disgust (and many others) are constructed mental states that occur when many different systems in the brain work together.[88] In this view, networks of brain regions underlie psychological operations (e.g., language, attention, etc.) that interact to produce many different kinds of emotion, perception, and cognition.[89] One psychological operation critical for emotion is the network of brain regions that underlie valence (feeling pleasant/unpleasant) and arousal (feeling activated and energized).[88] Emotions emerge when neural systems underlying different psychological operations interact (not just those involved in valence and arousal), producing distributed patterns of activation across the brain. Because emotions emerge from more basic components, there is heterogeneity within each emotion category; for example, a person can experience many different kinds of fear, which feel differently, and which correspond to different neural patterns in the brain. Thus, this view presents a different approach to understanding the neural bases of emotion than locationist approaches.

In the first neuroimaging meta-analysis of emotion, Phan et al. (2002) analyzed the results of 55 studies published in peer reviewed journal articles between January 1990 and December 2000 to determine if the emotions of fear, sadness, disgust, anger, and happiness were consistently associated with activity in specific brain regions. All studies used fMRI or PET techniques to investigate higher-order mental processing of emotion (studies of low-order sensory or motor processes were excluded). The authors analysis approach was to tabulate the number of studies that reported activation in specific brain regions during tasks inducing fear, sadness, disgust, anger, and happiness. For each brain region, statistical chi-squared analysis was conducted to determine if the proportion of studies reporting activation during one emotion was significantly higher than the proportion of studies reporting activation during the other emotions. Two regions showed this statistically significant pattern across studies. In the amygdala, 66% of studies inducing fear reported activity in this region, as compared to ~20% of studies inducing happiness, ~15% of studies inducing sadness (with no reported activations for anger or disgust). In the subcallosal cingulate, 46% of studies inducing sadness reported activity in this region, as compared to ~20% inducing happiness and ~20% inducing anger. This pattern of clear discriminability between emotion categories was in fact rare, with a number of other patterns occurring in limbic regions (including amydala, hippocampus, hypothalamus, and orbitofrontal cortex), paralimbic regions (including subcallosal cingulate, medial prefrontal cortex, anterior cingulate cortex, posterior cingulate cortex, insula, and temporal pole), and uni/heteromodal regions (including lateral prefrontal cortex, primary sensorimotor cortex, temporal cortex, cerebellum, and brainstem). Brain regions implicated across discrete emotion included the basal ganglia (~60% of studies inducing happiness and ~60% of studies inducing disgust reported activity in this region) and medial prefrontal cortex (happiness ~60%, anger ~55%, sadness ~40%, disgust ~40%, and fear ~30%).[90]

Murphy, et al. 2003 analyzed 106 peer reviewed journals published between January 1994 and December 2001 to examine the evidence for regional specialization of discrete emotions (fear, disgust, anger, happiness and sadness) across a larger set of studies that Phan et al. Studies included in the meta-analysis measured activity in the whole brain and regions of interest (activity in individual regions of particular interest to the study). 3-D Kolmogorov-Smirnov (KS3) statistics were used to compare rough spatial distributions of 3-D activation patterns to determine if statistically significant activations (consistently activated across studies) were specific to particular brain regions for all emotional categories. This pattern of consistently activated, regionally specific activations was identified in four brain regions: amygdala with fear, insula with disgust, globus pallidus with disgust, and lateral orbitofrontal cortex with anger. The amygdala was consistently activated in ~40% of studies inducing fear, as compared to less than 20% studies inducing happiness, sadness, or anger. The insula was consistently activated in ~ 70% of studies inducing disgust, as compared to sadness (~40%), anger (~20%), fear (~20%), and happiness (~10%). Similar to the insula, the globus pallidus was consistently activated in ~70% of studies inducing disgust, as compared to less than 25% of studies inducing sadness, fear, anger or happiness. The lateral orbitofrontal cortex was consistently activated in over 80% of studies inducing anger, as compared to fear (~30%), sadness (~20%), happiness (< 20%) and disgust (< 20%). Other regions showed different patterns of activation across categories. For example, both the dorsal medial prefrontal cortex and the rostral anterior cingulate cortex showed consistent activity across emotions (happiness ~50%, sadness ~50%, anger ~ 40%, fear ~30%, and disgust ~ 20%).[91]

Barrett, et al. 2006 examined 161 studies published between 1990-2001, subsets of which were analyzed in previous meta-analyses (Phan, et al. 2002 and Murphy et al. 2003). In this review, the authors examined the locationist hypothesis by comparing the consistency and specificity of prior meta-analytic findings specific to each hypothesized basic emotion (fear, anger, sadness, disgust, and happiness). Consistent neural patterns were defined by brain regions showing increased activity for a specific emotion (relative to a neutral control condition), regardless of the method of induction used (for example, visual vs. auditory cue). Specific neural patterns were defined as architecturally separate circuits for one emotion vs. the other emotions (for example, the fear circuit must be discriminable from the anger circuit, although both circuits may include common brain regions). In general, the results supported consistency among the findings of Phan et al. and Murphy et al., but not specificity. Consistency was determined through the comparison of chi-squared analyses that revealed whether the proportion of studies reporting activation during one emotion was significantly higher than the proportion of studies reporting activation during the other emotions. Specificity was determined through the comparison of emotion-category brain-localizations by contrasting activations in key regions that were specific to particular emotions. Increased amygdala activation during fear was the most consistently reported across induction methods (but not specific). Both meta-analyses also reported increased activations in regions of the anterior cingulate cortex during sadness, although this finding was less consistent (across induction methods) and was not specific to sadness. Both meta-analyses also found that disgust was associated with increased activity in the basal ganglia, but these findings were neither consistent nor specific. Neither consistent nor specific activity was observed across the meta-analyses for anger or for happiness. This meta-analysis additionally introduced the concept of the basic, irreducible elements of emotional life as dimensions such as approach and avoidance. This dimensional approach involved in psychological constructionist approaches is further examined in later meta-analyses of Kober et al. 2008 and Lindquist et al. 2012.[88]

Instead of investigating specific emotions, Kober, et al. 2008 reviewed 162 neuroimaging studies published between 1990-2005 to determine if groups of brain regions show consistent patterns of activation during emotional experience (that is, actively experiencing an emotion first-hand) and during emotion perception (that is, perceiving a given emotion as experienced by another). This meta-analysis used multilevel kernal density analysis (MKDA) to examine fMRI and PET studies, a technique that prevents single studies from dominating the results (particularly if they report multiple nearby peaks) and that enables studies with large sample sizes (those involving more participants) to exert more influence upon the results. MKDA was used to establish a neural reference space that includes the set of regions showing consistent increases across all studies (for further discussion of MDKA see Wager et al. 2007).[92] Next, this neural reference space was partitioned into functional groups of brain regions showing similar activation patterns across studies by first using multivariate techniques to determine co-activation patterns and then using data-reduction techniques to define the functional groupings (resulting in six groups). Consistent with a psychological construction approach to emotion, the authors discuss each functional group in terms more basic psychological operations. The first Core Limbic group included the left amygdala, hypothalamus, periaqueductal gray/thalamus regions, and amygdala/ventral striatum/ventral globus pallidus/thalamus regions, which the authors discuss as an integrative emotional center that plays a general role in evaluating affective significance. The second Lateral Paralimbic group included the ventral anterior insula/frontal operculum/right temporal pole/ posterior orbitofrontal cortex, the anterior insula/ posterior orbitofrontal cortex, the ventral anterior insula/ temporal cortex/ orbitofrontal cortex junction, the midinsula/ dorsal putamen, and the ventral striatum /mid insula/ left hippocampus, which the authors suggest plays a role in motivation, contributing to the general valuation of stimuli and particularly in reward. The third Medial Prefrontal Cortex group included the dorsal medial prefrontal cortex, pregenual anterior cingulate cortex, and rostral dorsal anterior cingulate cortex, which the authors discuss as playing a role in both the generation and regulation of emotion. The fourth Cognitive/ Motor Network group included right frontal operculum, the right interior frontal gyrus, and the pre-supplementray motor area/ left interior frontal gyrus, regions that are not specific to emotion, but instead appear to play a more general role in information processing and cognitive control. The fifth Occipital/ Visual Association group included areas V8 and V4 of the primary visual cortex, the medial temporal lobe, and the lateral occipital cortex, and the sixth Medial Posterior group included posterior cingulate cortex and area V1 of the primary visual cortex. The authors suggest that these regions play a joint role in visual processing and attention to emotional stimuli.[93]

Vytal, et al. 2010 examined 83 neuroimaging studies published between 1993-2008 to examine whether neuroimaging evidence supports the idea of biologically discrete, basic emotions (i.e. fear, anger, disgust, happiness, and sadness). Consistency analyses identified brain regions that were associated with a given emotion. Discriminability analyses identified brain regions that were significantly, differentially active when contrasting pairs of discrete emotions. This meta-analysis examined PET or fMRI studies that reported whole brain analyses identifying significant activations for at least one of the five emotions relative to a neutral or control condition. The authors used activation likelihood estimation (ALE) to perform spatially sensitive, voxel-wise (sensitive to the spatial properties of voxels) statistical comparisons across studies. This technique allows for direct statistical comparison between activation maps associated with each discrete emotion. Thus, discriminability between the five discrete emotion categories was assessed on a more precise spatial scale than what had been accomplished in prior meta-analyses. Consistency was first assessed by comparing the ALE map generated across studies for each emotion (for example, the ALE map identifying regions consistently activated by studies inducing fear) to ALE map generated by random permutations. Discriminability was then assessed by pair-wise contrasts of individual emotion ALE maps (for example, fear ALE map vs. anger ALE map; fear ALE map vs. disgust map) across all basic emotions pairings. Consistent and discriminable patterns of neural activation were observed for the five emotional categories. Happiness was consistently associated with activity in 9 regional brain clusters, the largest located in the right superior temporal gyrus. For the first time, happiness was discriminated from the other emotional categories, with the largest clusters of activity specific to happiness (vs. the other emotion categories) located in right superior temporal gyrus and left rostral anterior cingulate cortex. Sadness was consistently associated with 35 clusters (the largest activation cluster located in the left medial frontal gyrus) and was discriminated from the other emotion categories by significantly greater activity in left medial frontal gyrus, right middle temporal gyrus, and right inferior frontal gyrus. Anger was consistently associated with activity in 13 clusters (the largest of which was located in the left inferior frontal gyrus), and was discriminated from the other emotion categories by significantly greater activity in bilateral inferior frontal gyrus, and in right parahippocampal gyrus. Fear was consistently associated with 11 clusters (the largest activation cluster in the left amygdala) and was discriminated from the other emotion categories by significantly greater activity in the left amygdala and left putamen. Disgust was consistently activated with 16 clusters (the largest activation cluster in the right insula/ right inferior frontal gyrus) and was discriminated from the other emotion categories by significantly greater activity in the right putamen and the left insula.[94]

Lindquist, et al. 2012 reviewed 91 PET and fMRI studies published between January 1990 and December 2007. The studies included in this meta-analysis used induction methods that elicit emotion experience or emotion perception of fear, sadness, disgust, anger, and happiness. The goal was to compare locationist approaches with psychological constructionist approaches to emotion. Similar to Kober et al. described above, a Multilevel Peak Kernel Density Analysis[92] transformed the individual peak activations reported across study contrasts into a neural reference space (in other words, the set of brain regions consistently active across all study contrasts assessing emotion experience or perception). The density analysis was then used to identify regions (or voxels) within the neural reference space with more consistent activations for a specific emotion category (anger, fear, happiness, sadness, and disgust) than all other emotions. Chi-squared analysis was used to create statistical maps that indicated if each previously identified and consistently active regions (those identified during density analysis) were more frequently activated in studies of each emotion category versus the average of all other emotions, regardless of activations elsewhere in the brain. Chi-squared analysis and density analysis both defined functionally consistent and selective regions, or regions which showed a relatively more consistent increase in activity for the experience or perception of one emotion category across studies in the literature. Thus, a selective region could present increased activations relatively more so to one emotion category while also having a response to multiple other emotional categories. A series of logistic regressions were then performed to identify if any of the regions that were identified as consistent and selective to an emotion category were additionally specific to a given category. Regions were defined as specific to a given emotion if they showed increased activations for only one emotional category, and never showed increased activity during instances of the other emotional categories. In other words, a region could be defined as consistent, selective and specific for e.g. fear perception if it only showed significantly greater increases in activation during the perception of fear and did not show increased activity during any other emotion categories. However, the same region would be defined as only consistent and selective (and not specific) to fear perception if it additionally displayed increased activations during anger perception. Strong support for the locationist approach was defined as evidence that basic emotion categories (anger, disgust, fear, happiness and sadness) consistently map onto areas of the brain that specifically activate in response to instances of only one emotional category. Strong support for the constructionist approach was defined as evidence that multiple psychological operations (some of which are not specific or selective to emotion) consistently occur across many brain regions and multiple emotional categories.

The results indicated that many brain regions demonstrated consistent and selective activations in the experience or perception of an emotion category (versus all the other emotion categories). Consistent with constructionist models, however, no region demonstrated functional specificity for the emotions of fear, disgust, happiness, sadness or anger. Based on the existing scientific literature, the authors proposed different roles for the brain regions that have traditionally been associated with only one emotion category. The authors propose that the amygdala, anterior insula, orbitofrontal cortex each contribute to core affect, which are basic feelings that are pleasant or unpleasant with some level of arousal. The amygdala, for example, appears to play a more general role in indicating if external sensory information is motivationally salient, and is particularly active when a stimulus is novel or evokes uncertainty. The anterior insula may represent core affective feelings in awareness across a number of emotion categories, driven largely by sensations originating in the body. The orbitofrontal cortex appears to function as a site for integrating sensory information from the body and sensory information from the world to guide behavior. Closely related to core affect, the authors propose that anterior cingulate and dorsolateral prefrontal cortex play vital roles in attention, with anterior cingulate supporting the use of sensory information for directing attention and motor responses during response selection and with dorsolateral prefrontal cortex supporting executive attention. In many psychological construction approaches, emotions also involve the act of interpreting ones situation in the world relative to the internal state of the body, or what is referred to as conceptualization. In support of this idea, the dorsomedial prefrontal cortex and hippocampus were consistently active in this meta-analysis, regions that appear to play an important role conceptualizing during emotion, which are also involved in simulating previous experience (e.g. knowledge, memory). Language is also central to conceptualizing, and regions that support language, including ventrolateral prefrontal cortex, were also consistently active across studies of emotion experience and perception.[89]

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