This image illustrates the dissociation between primary and secondary rewards in the orbitofrontal cortex, a frontal region of the brain that is known to play a role in the evaluation of gratification. The more primitive region (in the back, shown in yellow) represents the value of erotic images shown to the participants, while the most recent region (in the front, in blue) represents the value of monetary prizes won by the volunteers in the experiment. Credit: © Sescousse / Dreher
A team of French researchers headed by Jean-Claude Dreher of the Centre de Neuroscience Cognitive in Lyon, France, has provided the first evidence that the orbitofrontal cortex (located in the anterior ventral part of the brain) contains distinct regions that respond to secondary rewards like money as well as more primary gratifications like erotic images. These findings, published in The Journal of Neuroscience, open new perspectives in the understanding of certain pathologies, such as gambling addiction, and the study of the neural networks involved in motivation and learning.
In our everyday lives, we often encounter various types of “rewards”: a 20-euro bill, a chocolate bar, a glass of good wine… Moreover, we must often choose between them, or trade one for another. To do this, we must be able to compare their relative value on a single consistent scale, which suggests that all types of rewards are assessed in the same brain areas. At the same time it is possible that, due to their individual characteristics, different rewards may activate distinct cerebral regions. In particular, there could be a dissociation between so-called “primary” gratifications such as food or sex, which satisfy basic vital needs and have an innate value, and more “secondary” rewards such as money or power, which are not essential for survival and whose value is assessed by association with primary gratifications.
To verify these hypotheses, Jean-Claude Dreher and Guillaume Sescousse conducted an original experiment in the form of a game that rewarded 18 volunteers with money or erotic images, while their cerebral activity was monitored using an FMRI (functional magnetic resonance imaging) scanner.
The experiment showed that the rewards are indeed evaluated in partially shared cerebral regions, namely the ventral striatum, insula, mesencephalon and anterior cingulate cortex. The researchers have also confirmed that there is a dissociation between primary and secondary rewards in the orbitofrontal cortex. Its posterior region (more primitive) is specifically stimulated by erotic images (a primary reward), while its anterior region (which is more recent in man) is activated by monetary gain (a secondary reward). The more abstract and complex the reward, the more its representation stimulates the anterior regions of the orbitofrontal cortex.
The volunteers in the experiment played a game in which they could win money or view erotic images, while their cerebral activity was recorded using an FMRI scanner. Credit: © CERMEP – Imagerie du Vivant
These results provide the first evidence of a dissociation in the brain between two types of reward, suggesting the existence of distinct regions corresponding to various gratifications. Dreher and Sescousse’s research could lead to a better understanding of certain psychiatric disorders, including gambling addiction.
More information: G. Sescousse, J. Redouté, J-C Dreher (2010) The architecture of reward value coding in the orbitofrontal cortex. J Neurosci, 30 (39)
Provided by CNRS
G. Sescousse, J. Redoute, J.-C. Dreher. The Architecture of Reward Value Coding in the Human Orbitofrontal Cortex. Journal of Neuroscience, 2010; 30 (39): 13095 DOI: 10.1523/JNEUROSCI.3501-10.2010
Synesthesia is a neurological condition in which affected individuals experience one sense (e.g. hearing) as another sense (e.g. visual colours). Ramachandran’s latest study investigated grapheme-colour synesthetes who experience specific colours when they view specific graphemes (i.e., letters and numbers). The results demonstrate that two brain areas – for grapheme and colour representation respectively – are activated at virtually the same time in the brains of synesthetes who are viewing letters and numbers. On the other hand, normal controls viewing the same thing exhibit activity in the grapheme region but not the colour region.
This is the first study of synesthesia to demonstrate simultaneous activation of the two brain areas, known as the posterior temporal grapheme area (PTGA) and colour area V4 (pictured below in the brain of a representative synesthete). The finding was made possible because the researchers used a neuroimaging technique called magnetoencephalography (MEG) to measure weak magnetic fields emitted by specific areas of the brain while the subjects viewed graphemes. Compared to other neuroimaging techniques, such as fMRI and EEG, MEG offers the best combination of temporal and spatial precision in measuring brain activation.
If you read the Wikipedia page, you know that there are two main theories that attempt to explain how synesthesia occurs in the brain: the cross-activation theory and the disinhibited feedback theory. Let’s call them Theory 1 and Theory 2 for simplicity. Theory 1 posits that the grapheme and colour brain areas are ‘hyper-connected’ such that activity in the grapheme area evoked by viewing a letter or number immediately leads to activity in the colour area and conscious perception of colour. Theory 2 maintains that there are ‘executive’ brain areas that control the communication between the grapheme and colour areas, and in synesthetes this control is disrupted. To reiterate, Theory 1 says that normal brains are anatomically different than synesthete brains, whereas Theory 2 says that normal brains are the same as synesthete brains but the two brains act differently.
The results of Ramachandran’s group support Theory 1, the cross-activation theory, since this model predicts that the colour and grapheme areas should be activated at roughly the same time in synesthetes looking at graphemes.
This is perhaps the strongest evidence for the cross-activation theory of synesthesia to date. But to complicate things, Ramachandran’s group proposed a new theory called ‘cascaded cross-tuning model,’ which is essentially a refinement of the cross-activation model (let’s call it Theory 1.1).
According to Theory 1.1, when a synesthete views a number, a series of simultaneous activations lead to perception of a colour. First, a subcomponent of the grapheme area responds to features of the number (e.g. the “o” that makes up the top of the number 9). This leads to activity in other subcomponents of the grapheme area representing possible numbers that the feature is part of (e.g. the “o” could be a component of the numbers 6, 8, or 9) as well as the colour area V4. At this point however, colour is not consciously perceived. Next, when the grapheme area identifies the number 6 (based on monitoring by other brain areas), activity in V4 is triggered, leading to conscious perception of the colour associated with the number 6.
Cool theory? Cool theory.
Note, however, that it only applies to ‘projector’ synesthetes who see colours in the outside world when they see numbers, but not ‘associator’ synesthetes who perceive the colours in the “mind’s eye.” Also, it doesn’t yet apply to other forms of synesthesia, such as acquired synesthesias (e.g. synesthesia for pain).
Yeah, it’s only a matter of time before Theory 1.2 takes over.
Brang D, Hubbard EM, Coulson S, Huang M, & Ramachandran VS (2010). Magnetoencephalography reveals early activation of V4 in grapheme-color synesthesia. NeuroImage PMID: 20547226
This is an illustration of how brain rhythms organize distributed groups of neurons into functional cell assemblies. The colors represent different cell assemblies. Neurons in widely separated brain areas often need to work together without interfering with other, spatially overlapping groups. Each assembly is sensitive to different frequencies, producing independent patterns of coordinated neural activity, depicted as color traces to the right of each network. Credit: Ryan Canolty, UC Berkeley
When it comes to conducting complex tasks, it turns out that the brain needs rhythm, according to researchers at the University of California, Berkeley.
Specifically, cortical rhythms, or oscillations, can effectively rally groups of neurons in widely dispersed regions of the brain to engage in coordinated activity, much like a conductor will summon up various sections of an orchestra in a symphony.
Even the simple act of catching a ball necessitates an impressive coordination of multiple groups of neurons to perceive the object, judge its speed and trajectory, decide when it’s time to catch it and then direct the muscles in the body to grasp it before it whizzes by or drops to the ground.
Until now, neuroscientists had not fully understood how these neuron groups in widely dispersed regions of the brain first get linked together so they can work in concert for such complex tasks.
The UC Berkeley findings are to be published the week of Sept. 20 in the online early edition of the journal Proceedings of the National Academy of Sciences.
“One of the key problems in neuroscience right now is how you go from billions of diverse and independent neurons, on the one hand, to a unified brain able to act and survive in a complex world, on the other,” said principal investigator Jose Carmena, UC Berkeley assistant professor at the Department of Electrical Engineering and Computer Sciences, the Program in Cognitive Science, and the Helen Wills Neuroscience Institute. “Evidence from this study supports the idea that neuronal oscillations are a critical mechanism for organizing the activity of individual neurons into larger functional groups.”
The idea behind anatomically dispersed but functionally related groups of neurons is credited to neuroscientist Donald Hebb, who put forward the concept in his 1949 book “The Organization of Behavior.”
“Hebb basically said that single neurons weren’t the most important unit of brain operation, and that it’s really the cell assembly that matters,” said study lead author Ryan Canolty, a UC Berkeley postdoctoral fellow in the Carmena lab.
It took decades after Hebb’s book for scientists to start unraveling how groups of neurons dynamically assemble. Not only do neuron groups need to work together for the task of perception – such as following the course of a baseball as it makes its way through the air – but they then need to join forces with groups of neurons in other parts of the brain, such as in regions responsible for cognition and body control.
At UC Berkeley, neuroscientists examined existing data recorded over the past four years from four macaque monkeys. Half of the subjects were engaged in brain-machine interface tasks, and the other half were participating in working memory tasks. The researchers looked at how the timing of electrical spikes – or action potentials – emitted by nerve cells was related to rhythms occurring in multiple areas across the brain.
Among the squiggly lines, patterns emerged that give literal meaning to the phrase “tuned in.” The timing of when individual neurons spiked was synchronized with brain rhythms occurring in distinct frequency bands in other regions of the brain. For example, the high-beta band – 25 to 40 hertz (cycles per second) – was especially important for brain areas involved in motor control and planning.
“Many neurons are thought to respond to a receptive field, so that if I look at one motor neuron as I move my hand to the left, I’ll see it fire more often, but if I move my hand to the right, the neuron fires less often,” said Carmena. “What we’ve shown here is that, in addition to these traditional ‘external’ receptive fields, many neurons also respond to ‘internal’ receptive fields. Those internal fields focus on large-scale patterns of synchronization involving distinct cortical areas within a larger functional network.”
The researchers expressed surprise that this spike dependence was not restricted to the neuron’s local environment. It turns out that this local-to-global connection is vital for organizing spatially distributed neuronal groups.
“If neurons only cared about what was happening in their local environment, then it would be difficult to get neurons to work together if they happened to be in different cortical areas,” said Canolty. “But when multiple neurons spread all over the brain are tuned in to a specific pattern of electrical activity at a specific frequency, then whenever that global activity pattern occurs, those neurons can act as a coordinated assembly.”
The researchers pointed out that this mechanism of cell assembly formation via oscillatory phase coupling is selective. Two neurons that are sensitive to different frequencies or to different spatial coupling patterns will exhibit independent activity, no matter how close they are spatially, and will not be part of the same assembly. Conversely, two neurons that prefer a similar pattern of coupling will exhibit similar spiking activity over time, even if they are widely separated or in different brain areas.
“It is like the radio communication between emergency first responders at an earthquake,” Canolty said. “You have many people spread out over a large area, and the police need to be able to talk to each other on the radio to coordinate their action without interfering with the firefighters, and the firefighters need to be able to communicate without disrupting the EMTs. So each group tunes into and uses a different radio frequency, providing each group with an independent channel of communication despite the fact that they are spatially spread out and overlapping.”
The authors noted that this local-to-global relationship in brain activity may prove useful for improving the performance of brain-machine interfaces, or lead to novel strategies for regulating dysfunctional brain networks through electrical stimulation. Treatment of movement disorders through deep brain stimulation, for example, usually targets a single area. This study suggests that gentler rhythmic stimulation in several areas at once may also prove effective, the authors said.
Provided by University of California – Berkeley
The pulsing of a single neuron can switch a brain’s waves from the equivalent of a big ocean swell to ripples on a pond, according to new research from Howard Hughes Medical Institute investigator Yang Dan of the University of California, Berkeley.
The study reveals important new information about how the brain controls large-scale activity patterns and suggests that an individual cell has more influence than previously thought. The findings, published in the May 1, 2009, issue of the journal Science, could ultimately shed light on how chaotic brain patterns can lead to sleep disorders such as sleepwalking.
Brain cells use electrical pulses to talk with one another and guide functions ranging from heart rate and breathing to decision-making and navigation. Like the din of a crowd, the chatter of 100 billion neuronal cells in the human brain creates larger patterns of activity commonly called brain waves.
These patterns reveal the brain’s general state of arousal. For instance, large, slow brain waves that are synchronized throughout the brain are indicative of deep sleep. “Many neurons are doing the same thing at the same time,” says Dan. During so-called rapid eye movement (REM) sleep, on the other hand, different brain areas are less synchronized, firing in smaller and more frequent oscillations. And in an awake person, the brain broadcasts a rapid, uncoordinated pattern.
Dan and her colleagues wanted to understand how large-scale wave patterns influence the connection between two neurons. They knew that neuronal connections could strengthen or weaken over time, and these changes seem to underlie learning and memory. They wondered whether the overall pattern of brain activity altered nerve cells’ ability to change their connection strength.
Studying anesthetized rats, they used one electrode to spur a neuron to fire rapidly and used another electrode nearby to activate the local neuronal connections. A third electrode was used to pick up the larger pattern emitted by all the neurons in the area. They wanted the overall brain state to remain constant during the experiment, but instead found that tickling one neuron could cause the entire brain state to change.
“Initially, this was very inconvenient,” says Dan. But then the researchers realized that the phenomenon deserved more attention. Looking more closely, they verified that a neuron firing at high frequency could switch the brain from a “non-REM pattern” of activity to a “REM pattern,” and vice versa.
The result was counterintuitive. “Every neuron makes connections to roughly 1,000 other neurons, but most of those are quite weak,” says Dan. A target cell won’t respond unless many, many neurons that connect to it fire at the same time and therefore she says it’s surprising that a single neuron could change the activity of the whole brain. “Single neurons have more weight than we used to think,” she says.
Dan doesn’t yet know how one cell could exert such power. The researchers had to repeatedly and rapidly fire a cell to cause the pattern to switch, so they might be emulating the effect of many cells firing at once. A neuron doesn’t normally fire in that way, so it is an open question whether the activity of a single neuron could change overall brain pattern under normal circumstances.
The findings add a new twist to how brain patterns are established. Researchers know that certain brain structures, such as the hypothalamus and the brain stem, play a part in setting the pace of global brain activity. In this study, Dan and her team were tickling brain cells in a different area: the cortex, the thin sheet of neurons on the surface of the brain involved in such abilities as moving and seeing.
Dan isn’t certain how cells in the cortex might control brain state, but she posits that signaling there could link back to the thalamus and spur it to set up a new pattern. “We know that a lot of circuits are involved in controlling brain state,” says Dan. “We’re saying that cortex is also part of that loop.”
By providing new information about how brain states are controlled, the study might ultimately lead to new knowledge about what causes certain sleep disorders. “In sleepwalking, there is a mixed-up boundary between slow-wave sleep and the awake state,” says Dan. “Your muscles move, but you aren’t consciously aware of your surroundings.” Understanding the circuitry that establishes brain states could ultimately reveal how that mixed-up situation is established.
Next, Dan wants to study animals that are naturally awake or sleeping, rather than anesthetized, to see if under normal conditions, a single neuron or a few neurons really can turn the tide on the entire brain.