Archive for the ‘brain connectivity’ Category

How are values computed in the brain? Rewards can be as many things: the expectation when having just ordered your favourite dish; the child’s joy at Christmas Eve; the enjoyment of good music or the wonderful taste of strawberries.

But how does the brain process these many different kinds of rewards? Does it treat all types of rewards equally or does the brain distinguish between different kinds of rewards? Rewards can come in many different forms: from sex, social recognition, food when you’re hungry, or money. But it is still an open question whether the brain processes such rewards in different ways, or whether there is a “common currency” in the brain for all types of rewards.

Guillaume Sescousse and his colleagues in Lyon recently reported a study on how the brain reacts differently to money and sex. A group of men were scanned with functional MRI. While being tested, subjects played a game in which they sometimes reveiwed a reward. The reward could be money or it could be the sight of a lightly dressed woman. So there were two types of rewards. Money can be said to be an indirect reward, and the sexual images can be seen as more immediately rewarding (at least for most heterosexual men). But how did the brain process these rewards?

The researchers found that there were unique activations for both sex and money, but that there were also overlapping regions of activity. On one hand, for both types of reward was a general activation of what we often refer to as the brain’s reward system (ventral striatum, anterior insula, anterior cingulate cortex and midbrain; see figure 1). The brain thus uses the some structures to respond to both types of reward.

Regions of common activations

But there were also specific activations for erotic pictures and money. And this difference was primarily made in the brain’s prefrontal cortex, especially the orbitofrontal cortex (OfC). Here, it was found that monetary rewards engaged more anterior OfC regions, while erotic images activated more posterior OfC regions.

This could suggest that the brain also treats the two types of reward differently. The crux of this paper, however, is how one explains the difference. As noted, the researchers used two different kinds of reward, but they differ in several ways which I will try to summarize here:

  • Direct vs indirect
    • Money is indirectly rewarding, because money can not be ‘consumed’ in itself. They are rewarding to the extent they could be exchanged for other things. Erotic images are in themselves directly rewarding. Not because they symbolize sex, or the possibility of sex, but because they have an immediate rewarding effects.
  • Abstraction level
    • Another option is to say that erotic pictures and money differ in their level of abstraction: Erotic images are concrete, while money is an abstract reward.
  • Time interval
    • A final possibility is that there are differences in the time interval: Erotic images are immediately rewarding, while the money can only be converted into real value after a while (for example, after scanning, or after a few days where you spend the money). We already know that the frontopolar regions of the brain is among the regions that are most developed in humans compared to other primates, and is linked to our unique ability to think about the future, i.e. prospective memory and planning, and through this to use complex abstractions for rewards, including money.

Regions of distinct activations: orange = monetary rewards, green = sexual rewards

What the exact cause of this common currency as well as the separation between money and erotic pictures is still unclear and warrants further studies (which I am currently undertaking). The essential addition of this study is the separation between the posterior and anterior parts of the OFC in processing different kinds of rewards. By showing common and distinct regions, this study may resolve some of the ongoing debates in the decision neuroscience / neuroeconomic literature. But as always found in science, this study generates more questions than it resolves, and we can only hope that future studies can add to this knowledge.


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Emotional reactions may come in many forms and have different causes. But one of the main responses is the fear response, which has been shown to involved the amygdala. Different nuclei of the amygdala may contribute differentially to the fear response process.

One vital feature of emotion and amygdala is that emotional responses can be reduced, and eventually diminish. This is one of the basic mechanisms at play when we habituate to (or even extinguish) fearful stimuli. But is is also possible to reduce fear responses through more controlled processes, what has been termed cognitive emotion regulation. Such basic cognitive mechanisms underlie the psychological treatment of, e.g., phobias. In other words, there are two ways of reducing fear responses of the amygdala: 1) through habituation/extinction and 2) through cognitive (“rational”?) processing.

However, the exact neurobiological nature of these processes have been unknown. In a recent paper in Neuron, authored by Mauricio Delgado, and including prominent emotion researchers such as Joseph LeDoux, Elisabeth Phelps, looks at precicely this relationship. Using an emotion regulation strategy, the researchers compared the brain mechanisms (using fMRI) for conditioned fear regulation and for classic extinction.

From the methods section, one can read:

Each trial began with the presentation of a word cue, presented for 2 s, which instructed the participant on the type of trial. It was followed by either a blue or yellow square that served as a conditioned stimulus (CS) and was presented for 4 s. A mild shock to the wrist served as the unconditioned stimulus (US) and was administered during the last 200 ms for six of the CS trials. During one experimental session, a specific colored square (e.g., blue) was paired with the US, thus serving as the CS+, while the other square (e.g., yellow) served as the CS−. This contingency was counterbalanced across participants. The trial concluded with a 12 s intertrial interval.

When instructed to “attend,” participants were asked to view the stimulus and attend to their natural feelings regarding which CS was presented. In these Attend trials, for example, participants might focus on the fact that they may receive a shock (if the cue was followed by a CS+) or would never receive a shock (if the cue was followed by a CS−). When instructed to “reappraise,” participants were asked to view the CS and try to imagine something in nature that was calming, prompted by the color of the CS. During these Regulation trials, for example, participants could think of an image of the ocean or a blue sky when viewing the blue square, or they could think of the sunshine or a field of daffodils when viewing the yellow square.

During both cases of fear reduction, the amygdala (red in top image) activation level went from high to low, for both What the researchers found was that during extinction learning, the ventromedial prefrontal cortex (orange in top) showed a higher activity, and this was thought to cause the observed reduction in amygdala activation. In contrast, cognitive emotion control lead to a higher activation in the dorsolateral PfC (blue in top image).

So this is a very nice demonstration of two different mechanisms of emotion regulation. However, it stills seems open to me whether the two are overlapping or very different mechanisms. One way of assuming the relationship is that the dorsolateral PfC works through the ventromedial PfC on regulating the amygdala. However, it may also be possible that the dorsolateral PfC bypasses the ventromedial PfC altogether. By comparing the activation patterns of all three structures, the findings suggested that the dorsolateral PfC works on the amygdala through the ventromedial PfC. Or, as put by the authors:

Our results support a model in which the lateral PFC regions engaged by the online manipulation of information characteristic of cognitive emotion regulation strategies (for review see Ochsner and Gross, 2005) influences amygdala function through connections to vmPFC regions that are also thought to inhibit the amygdala during extinction (Milad and Quirk, 2002). These results are consistent with the suggestion that vmPFC may play a general regulatory role in diminishing fear across a range of paradigms (e.g., [Kim et al., 2003] and [Urry et al., 2006]).

The implications of these findings may be plenty, but a few immediately comes to mind: first, the identification of the dorsolateral PfC in controlling emotions may, in general, be used as a marker for emotional regulation in different psychological states. Lie detection may be one issue, and studies of implicit racism seem to suggest the same. Another interesting consequence is in the modelling of the phylogeny and ontogeny of emotion regulation in primates. The present results may suggest that the dorsolateral PfC role in emotion regulation has occurred later in primate evolution, and that it works through a more “ancient” ventromedial PfC basic regulation of the amygdala. It may even be possible that developmental studies can show that the later maturation of the dorsolateral PfC also corresponds to the development of emotional control. Finally, this idea may also serve as a good model for studying brain injury and the consequences of emotion regulation.


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I’m having the pleasure of reading The brain that changes itself by Norman Doidge, as a reviewer for a potential translation here in Denmark. Brain plasticity, or neuroplasticity, has always been a hot topic, from it’s (re)birth in modern neuroscience, and all the way up until today, where researchers are still fiercely debating how plastic the brain is and how functions relate to brain structures – aka the debate of modularism. In its early days, the neuroscientific community strongly believed that the modularity of the brain was established during childhood, and that little, if any, change could occur later on. Researchers suggesting otherwise were eschewed, heavily criticized on the ground that their data/ideas did not fit into the existing model. The land did not fit onto the map, so to say. This book is dedicated to the idea of neuroplasticity.

The book introduces brain plasticity in a very vivid and close-up manner, as Doidge tells the story from the inside, through some of the biggest names in this research, including the late Paul Bach-y-Rita, Michael Merzenich, and Gerald Edelman. Not only is the book very interesting to read as a historical background, but it also takes a look behind the scenes in two ways. Doidge has talked the researchers himself, and bring their experience of how plasticity came to go from a ignored (and carreer risky business) field, to a scientifically acceptable and highly influential topic. Even today, one may claim that we do not fully comprehend or apply the insights from this research.

Doidge also does a great job in describing patient cases of brain plasticity, including:

(…) a woman born with half a brain that rewired itself to work as a whole, a woman labeled retarded who cured her deficits with brain exercises and now cures those of others, blind people learning to see, learning disorders cured, IQs raised, aging brains rejuvenated, painful phantom limbs erased, stroke patients recovering their faculties, children with cerebral palsy learning to move more gracefully, entrenched depression and anxiety disappearing, and lifelong character traits altered.

(from the book cover)

The stories from both researchers and patients are written in a most vivid and entertaining way, and the first 100 pages alone makes the book a page-turner. The book as a whole is filled with these fantastic descriptions and stories that equal great writers such as Oliver Sacks.

So how about the sex part? Yes, this is where I got a little puzzled, too. Going from the insights of neuroplasticity, Doidge turns his attention to sexual disorders and abberations. This is, of course, both a very interesting, challenging and risky choice, but it is also a topic that Doidge is intimately close to through his clinical work. In much the same manner as the description of neuroplasticity cases, we are presented to patients of Doidge (or his peers) that suffer from psychological illnesses, in particular sex related problems. Interestingly, it seems that the insights from plasticity can be applied to these disorders and problems, and Doidge does a great job in presenting and discussing these issues.

My quarrel, however, is with Doidge’s theoretical position — psychoanalysis. Is it not itself strange to combine the insights from the edgy yet stringent scientific approaches of neuroplasticity with the unscientific theoretical (armchair) century old approach? Doidge does use the suggestions from Freud to interpret the psychological cases he presents. This includes the interpretation of dreams, a business receiving a lot of criticism, too. At best, I think this part of the book becomes an anachronism. The problem lies in why, at all, Doidge needs to invoke a theoretical position like psychoanalysis at all in order to understand what is going on. This is where science becomes fiction, and where the book breaks down. But not totally. If one is aware of the problems associated with psychoanalysis and science, the book is still a wonderful read.


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aniston.jpegHow specific — or sparse — is the neural representation of a memory trace? Quian Quiroga and colleagues now have an article in Neuron (PDF), where they describe their well-known studies using single-cell recordings to well-known faces. As you most likely know, this has given rise to the debate about the “Jennifer Aniston neuron”. Their findings, briefly put, have demonstrated that single cells show quite specific responses to very specific visual stimuli. While one cell may have a preferential response to the Sidney Opera House, another responds dramatically more to Hale Berry, while yet another cell responds to, well, Jennifer Aniston.

The Quiroga studies have re-iterated the debate (if it ever went dead) about how specific the neural coding is in the brain. Is it really so that the brain has such a specific code that one cell can represent one percept? Do we have a grandmother cell, a President Nixon cell and Marilyn Monroe cell?

Today, there is wide agreement that the one-cell-one-percept idea is untenable and unsupported by the literature. Rather than cingle cells, we see that networks represent a percept, rather than single cells. However, the findings by Quiroga et al. have nevertheless stunned the scientific (and global) community with regard to just how specific the neural code can be, and that it can be detected in a single neuron. The findings that we can record how one single neuron responds to one, and only one, percept, is quite surprising.

So forget about the grandmother cell, right? Or maybe not. After all, following the idea from these findings, we should not be surprised that there would in fact be one neuron that responded preferentially to our grandmother. Yes, it would be an expression of a “network code” representing our grandmothers as such, but nevertheless, you may in fact have that one neuron that responds to ol’ granny.

While we leave it at that, it is still surprising that this team of researchers use the term “medial temporal lobe” (or MTL for short). Why doe they say that there is sparse coding in the MTL? It’s a rather big region, and a region packed with qualitatively different regions. Not only are these regions different anatomically, but also functionally, they are thought to be involved in different functions. The perirhinal cortex is involved in processing (and encoding) of complex visual objects as well as novelty processing and working memory, the (posterior) parahippocampal cortex is involved in spatial processing (remember the parahippocampal place area). The entorhinal cortex has a medial and lateral part that deal with spatial and object information, respectively. And in addition to the hippocampus and amygdala, with their quite different functions, we may extend the MTL concept to include the temporopolar cortex, and maybe even the inferotemporal cortex.

Where in this complex system do Quiroga et al. find their sparse coding? Everywhere? My bet is on the perirhinal cortex due to its involvement in complex visual object processing. I’ve come to know that the researchers have not had structural scans available to determine the exact location of their electrodes. The scans have obviously been made, but they have not been able to use that information (hush hush, don’t tell anyone…).

So, while these studies are indeed important to our understanding of the coding of specific information, we’re left with a huge gap in terms of their anatomical properties. While most of the research community focuses on MTL subdivisions to an increasing extent, it is a bit puzzling to me that nobody have ever criticised these studies for their sparsity of anatomical information. Maybe I’ll be the first?


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sadchild.jpegPhysorg reports about an interesting forthcoming MRI study linking paedophilia to regional changes in white matter. Analysing structural MRI using voxel-based morphometry, paedophiles were found to have significantly smaller white matter volumes in specific regions, as the abstract demonstrates:

The present investigation sought to identify which brain regions distinguish pedophilic from nonpedophilic men, using unbiased, automated analyses of the whole brain. T1-weighted magnetic resonance images (MRIs) were acquired from men who demonstrated illegal or clinically significant sexual behaviors or interests (n = 65) and from men who had histories of nonsexual offenses but no sexual offenses (n = 62). Sexual interest in children was assessed by participants’ admissions of pedophilic interest, histories of committing sexual offenses against children, and psychophysiological responses in the laboratory to erotic stimuli depicting children or adults. Automated parcellation of the MRIs revealed significant negative associations between pedophilia and white matter volumes of the temporal and parietal lobes bilaterally. Voxel-based morphometry corroborated the associations and indicated that the regions of lower white matter volumes followed, and were limited to, two major fiber bundles: the superior fronto-occipital fasciculus and the right arcuate fasciculus. No significant differences were found in grey matter or in cerebrospinal fluid (CSF). Because the superior fronto-occipital and arcuate fasciculi connect the cortical regions that respond to sexual cues, these results suggest (1) that those cortical regions operate as a network for recognizing sexually relevant stimuli and (2) that pedophilia results from a partial disconnection within that network.

Now, a few things strikes me odd in this analysis and interpretation. First of all, why is the comparison group nonsexual offenders? After all, that the crime is of a sexual nature is absolutely central to the present question, and especially that the sexual offender has been interested in children. The obvious choice would be to compare paedophilic sexual offenders to sexual offenders who had adult victims (typically a male offending a woman). Here, the act of sexual offence is similar between the two groups, while the sexual “object” is the vital difference. In the present study, any significant difference could just as well be explained by the nature of the crime as the sexual inclination of the subjects. It’s a classic case of poor control of confounding variables.

Second, I strongly dislike the over-interpretations offere in both the article and the news story. First, the authors find significant differences in the superior fronto-occipital and arcuate fasciculi, and link these regions to studies showing involvement in response to sexual stimuli. Following this, they suggest that paedophilia may occur due to a disconnection in this network. Just based on the reasons given in the previous section, these results may be interpreted just as well as brain alterations in sexual offence in general.

But more than this, if one just skims the literature on these regions (fasciculi), one can see that they have been implemented in language lateralization/function and hallucinations and delusions. So interpreting the differences as relevant to paedophilia is a long shot.

Furthermore, the physorg story suggest that this study:

challenges the commonly held belief that paedophilia is brought on by childhood trauma or abuse. This finding is the strongest evidence yet that paedophilia is instead the result of a problem in brain development.

This is a serious over-interpretation of the results. When understanding white matter (and any brain) changes during development, one should be cautious to claim that the changes observed are the mere cause of “brain development” and not experience-related phenomena. Here, we need to divide between two effects: neurogenetic and psychogenetic effects. Neurogenetic effects are, in this story, changes in the brain that are caused by biological factors. Age-related atrophy is a good example of this. The cause is the accumulation of junk within cells/neurons that eventually hinder cell division and function. Psychogenetic factors, on the other hand, are observed brain changes that are caused by behaviour, in its broadest sense. For example, if you learn to juggle, areas in the motor regions of the brain will alter their size and connectivity to a measurable extent. Likewise, London taxi drivers are known to have larger posterior hippocampi as a result of their prolonged training in navigation.

So in the case of paedophilia, observed changes in the brain cannot be said to support a brain-based (neurogenetic) interpretation, and to challenge psychogenetic causes. Rather, it has been suggested that many paedophiles have been subject to similar maltreatment when young. At the least, just because the brain shows a difference, one cannot conclude anything beyond this about causation.

As neuroscience enters the domain of social sciences, it holds the promise to both enlighten and naturalize these age-old discussions. However, the use of mere reporting and tailored interpretations are far from sufficient, and may even lead us astray in the goal to achieve a better understanding of these, and related, phenomena.


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pvs.jpgIt’s all in the news these days. A man who has been in a coma (or is it “coma-like”, “almost coma” or what?) since a car accident in 1984 has now regained consciousness, and cognitive abilibties such as his speech. It’s already been written so much about this topic, but little is actually addressing the science. Often, the sensationalism is only covered. You can get them all by this simple google.

So why start writing about this here at BrainEthics? The story should have been covered by now? I think there are several reasons to address this story in a bit more detail, one of them being that the science, ethics and philosophical consequences are not – or very superfluously – noted. Another good reason is that the article describing this case has come out, and it’s available for free (PDF). Before we get to it, let me briefly let you know what I’d like to mention here:

  • the diagnosis – coma, vegetative state and related mental states are still very hard to tell apart, even to specialists
  • the development – much has happened to our knowledge about these states, but this knowledge has neither reached the general public, science writers nor always professionals dealing with these patients
  • the future – in addition to developments in traditional diagnosis, neuroimaging is already having a significant impact on our understanding on the relations and distinctions between these different states
  • the ethics – should we reach a scientifically valid model about states of consciousness the next step is to determine who is conscious and who is not – but still we are likely to ask “are our judgements correct?

The Diagnosis

If you are involved in a car accident and lose consciousness, the time from when you lose consciousness until you wake up is characterized by different stages where the brain’s level of functioning changes; from improved primitive reflexes to cognitive and mental restoration. A soon as you reach a state where you become aware of your surroundings, even the feeblest sensation, you have reach a state that is called post-traumatic amnesia (PTA). The person is conscious and appears responsive and they may even be able to talk to family members and medical staff, however after a short time, the person will forget all recollection of conversations and actions. The person will be disorientated and may not know the date, where they are, or why they are there.

The important discussion here is that we are discussing whether a person is conscious, or if he has any chance of becoming conscious again. A person in a coma is not conscious – he cannot be awakened, fails to respond normally to pain or light, does not have sleep-wake cycles, and does not take voluntary action. Coma is separate from vegetative state, in which the patient still has no cognitive neurological function or awareness of the environment. However, he has noncognitive function and a preserved sleep-wake cycle. Even more perplexing, the patient may exhibit spontaneous movements and he may open his eyes in response to external stimuli, and even track moving objects (or people) with his eyes. So why is this person not conscious? We know this from the fact that 1) he does not respond to verbal commands; 2) he shows no voluntary movements, only reflexes; 2) reports from people in this stage that have awakened show that they have had no experience. This, of course, is coupled to a variety of theory-bound measures of preserved vs. non-operative reflexes, and more recently neuroimaging.

What makes the diagnosis of coma and vegetative state so hard is that there are cases where patients show almost exactly the same symptoms as these conditions, only that they are aware. Patients in a minimally conscious state are indeed conscious, they may drift in and out of awareness, but they show signs of voluntary movement and communication. Terry Wallis is thought to be in this state, not coma, nor vegetative state. Another condition is locked-in syndrome, in which the patient is aware and awake, but cannot move or communicate due to complete paralysis of all voluntary muscles in the body.

The frequency of misdiagnosis of these patients has not been reviewed in full, but the fear is that it happens more often that we would like to. The misdiagnosis goes both ways: sometimes a patient is thought to be conscious while actually being in a persistent vegetative state. Other times – and this is the most problematic error – a patient that has some level of awareness (e.g. locked-in) is diagnosed with a coma or vegetative state.

The Development

How can we be so wrong about these patients? One reason is that we have just began to explore this field at the level of detail that we do today, incorporating better diagnostic tools and multi-modal assessment tools such as EEG, SPECT and MRI. A willingness to study consciousness, that mongrel concept that we still really don’t know what means, is another reason for the recent developments in this field. In all, our ability to distinguish between conscious and unconscious states has gone from a dichotomic distinction to a range of possibilities that are sometimes hard to distinguish.

This development is often the reason to the sensational awakenings that we can hear from time to time. News about a person regaining consciousness after 20 years from a coma (!) should be taken with a grain of salt. 20 years ago the diagnosis and distinctions to other (conscious) conditions was notas developed as today. So we should maybe think of this rather as a sensational awakening of the science surrounding these patients, not the patients themselves. That’s a bit harsh, but it is true that the conceptual and diagnostic improvements in this fueld has come through the past few years only.

The Future

What can we expect to happen in this field? First of all we can expect that neuroimaging tools will be used more. Today we can record EEG to exclude ideas about brain death; we use MRI images to see where in the brain we find lesions. But studies showing differences in the brain’s activity between these different patients have been emerging – see this article (PDF). The problem with these studies are that they are group studies. As I have argued previously, going from group study mean differences to the ability to identify individual differences – and diagnosing people on this ground – is not a straightforward thing. So tools needs to be developed that makes it possible to look at an individual scan to determine whether a person is conscious or not. As Steven Laureys from the University of Liège says:

Chronically unconscious or minimally conscious patients represent unique problems for diagnosis, prognosis, treatment, and everyday management. They are vulnerable to being denied potentially life-saving therapy….. This case shows that old dogmas need to be oppugned.

It should be noted that efforts are already being made for developing a “consciousness meter“. This stems from the finding of mid-operational awakenings; people undergoing surgery that are put into anaesthesia nevertheless wake up during surgery yet without the ability to notify others about their presence, often suffering pain as their sensations are restored. In other words; an induced locked-in syndrome. However, interesting as it has been it’s been hard to find any updates on the effectiveness of this apparatus. But we should probably think along these lines. Saying that, the consciousness meter suggested is based on EEG, and any measurement of a traumatised brain is bound to show different signals. That needs to be kept in mind.

What, then, about treatment? This is bound to follow the trace of our enhanced knowledge of these conditions. But what is interestig with the case of Terry Wallis is that he showed signes of rewiring of fibres in the brain. While these findings are in no way conclusive, they suggest that new intervention tools can be developed that focus on the regeneration of fibres in the brain. Not only general restitution, but maybe more focal, to the regions in which we have seen Wallis’ brain change (see changes in cerebellum, as indicated by white arrow below).


Diffusion tensor images of a brain at the first scan (left) and 18 months later (right). Color shows direction of white matter fibers, e.g., green for anterior-posterior fiber tracts. Large red area in second scan (arrow) shows what scientists think is growth of new neural processes in a part of the brain that controls movement. (Credit: Weill Cornell Citigroup Biomedical Imaging Center/Henning U. Voss.)

The Ethics

The growing knowledge about brain function and diagnosis of these cases should make us ask whether we are using the most up to date knowledge about these stages and states. Even more troublesome, spreading the knowledge to the entire world is a problematic affair, and even within the developed world. One thing is having an operational diagnostic system; an entirely different thing is seeing it implemented throughout the world. While the diagnosis of brain death is more or less universal across regions, cultures and religions, spreading the news about differential mental state diagnosis is only now beginning to spread. Hopefully, the use of evidence based medicine will provide the tools for such a knowledge dispersal.

Understanding that there is a tight relationship between the brain and the mind has a deep impact on our self-knowledge. Knowing how the brain works and breaks is a tale about yourself. It’s a direct relationship, not only a superficial association of flesh and mind. A loss of brain function is a loss of mental life (or part of it). All in all, the scientific study of unconscious states such as coma and persistent vegetative states are one part of the story that ties the brain and mind together tightly to a coherent picture of our minds as natural, biological phenomena.


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In a just published paper in PNAS by Le Bihan and colleagues, a technique called diffusion MRI is used to measure the activation of the brain. This is rather unusual. Diffusion MRI is normally used to measure the diffusion, or movement, of water in the brain. Grey matter is relatively disorganized and water is less restricted than in white matter, where myelinated fibres constrain the direction of molecular movements. This is illustrated by a figure that I have made for an upcoming Elsevier textbook (full size image opens in new window).

Using this method it is possible to map out the major fibre tracts in the brain. Even better, it is possible to do tractography: following the white matter fibre bundles from a seed point and calculate the physical connections from this (see figure below)

Le Bihan and colleagues takes diffusion MRI one step further by applying it to study the brain's activation! The background assumption is: as neurons get (relatively more) activated, a lot of physical movement occurs in and around the neurons. The neuron consumes more oxygen and nutrients; internally in the cell, a lot of movement of these substances, and the movement of signal substances occur, inaddition to energy distribution throughout the cell; and the whole cascade of neurotransmitter release and effects is due to movement across the synaptic cleft. So neural firing causes movement both inside and outside the cell.

Now, what did diffusion MRI do again? It measures the movement (!) of water molecules in the brain. As a brain region gets activated, molecules move relatively more than at rest. As a reult, it should be possible to measure brain activity by looking at where in the brain that molecule movement increases. This is exactly what Le Bihan and colleagues have done. And they provide neat results that it actually works! And, as they argue, diffusion fMRI is a more direct measure of neural activation than the more used BOLD fMRI, which is an index of a complex and delayed mechanism of relative blood oxygenation in regions of the brain.

What remains to find out is what the signal really represents. While it is thought that neuroimaning tools such as BOLD fMRI and EEG measures the activation and energy consumption in the dendrites, we know little about the underlying neural mechanism in diffusion fMRI. Could it be mostly due to movement across the synaptic cleft, and hence be a measure of action potentials; could it be due to movement within the cells; or due to transport of molecules (oxygen + nutrients) across the cell membrane; or all at once? Today, this is an open question. But the mere idea of having yet another MRI tool for measuring the brain's activation, and with good spatial resolution plus the promise of better temporal resolution, is really worth noticing.

We'll be tracking the development of this tool closely!


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The visual word form area (VWFA) is one of the most contested concepts of modern neuroscience. Its proponents claim that a dedicated slice of cortex in the occipitotemporal region of the brain – probably centered on the fusiform gyrus – underlie the ability to read. The most radical version of this hypothesis states that the VWFA is a specialized module – an idea that implicates some sort of genetical determinism. Since writing only has been around for some 6000 years many researchers doubt that there have been enough time for such a module to evolve. Instead, they expect reading to piggybackride on other, perhaps more general, visual processes.

The April 20 issue of Neuron contains a case study of man surgically treated for epilepsy that bears on these questions. As a consequence of excision of cortical tissue posterior to the putative VWFA this patient developed a case of pure alexia where, whereas before surgery he took ~600 ms to read a word, regardless of word lenght, after surgery his reading slowed to ~1000 ms for three-letter words and increased by ~100 ms per additional letter.

Crucially, postsurgical fMRI tests showed that the VWFA no longer responded more to words than to other objects, even when words were contrasted with viewing a simple fixation point. The authors suggest that this lack of activation is explained by the fact that postsurgically the VWFA is no longer receiving its normal input. Instead, a more widespread activation pattern, including frontal, parietal, and temporal sites, appear to "take over", resulting in a letter-by-letter reading strategy.

While the study clearly demonstrates that the VWFA plays some kind of (important) role in reading, it doesn't really illuminate what type of function the VWFA performs. And, at the same time, it cannot be said to settle the question of modularity, since the patient was a 46-old man who, of course, has had amble time to develop a reading skill from learning. As Alex Martin notes in a great accompanying resumé, the study do, however, leaves unresolved "the vexing problem of how to account for the intersubject consistency in the general location of the VWFA and other category-related regions in ventral occipitotemporal cortex. One possibility is that the VWFA performs a visual processing function that predisposed it to being co-opted for reading." But there may also be other reasons. In any case, it is a very nice study that will prove important for further debates on both reading and modularity.


Gaillard, R. et al. (2006): Direct intracranial, fMRI, and lesion evidence for the causal role of left inferotemporal cortex in reding. Neuron 50: 191-204.

Martin, A. (2006): Shades of Déjerine – forging a causal link between the visual word form area and reading. Neuron 50: 173-175.


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There is now an online-only published paper in PNAS from the Max Planck Institute on the evolution of language. What is surprising is that the researchers have used functional MRI to infer the evolutionary lineage from their results. Basically, what Angela Friederici and her colleagues have done is to compare language processing that is “simple” to processing that is “complex”. While simple processing activated left frontal operculum, a phylogenetically older region of the brain, more complex language processing also activated Broca’s area, which is thought to be a more recent development specific to humans. in addition, the researchers also studied the white matter connectivity of the two brain regions by using MR tractography. Here, they found that the two regions showed different structural connectivity signatures, further supporting the functional segregation of these two areas.

This makes the researchers conclude:
“Here we report findings pointing toward an evolutionary trajectory with respect to the computation of sequences, from processing simple probabilities to computing hierarchical structures, with the latter recruiting Broca’s area, a cortical region that is phylogenetically younger than the frontal operculum, the brain region dealing with the processing of transitional probabilities”I first found this through the Max Planck Society press release page. Just reflecting briefly on this, I think that despite the study is interesting itself in terms of functional segregation of language processes, I am not convinced about the argument about the phylogeny of the two regions. As we know from research on subcortical structures such as the “limbic system“, we cannot divide between the phylogenetic “old” and limbic brain and the “newer” cortical brain. It is today considered total gibberis, because evolution of “higher” areas in the cortical surface has had a dynamic and synergetic co-evolution of cortical and subcortical areas. In similar vein, I suspect that the evolutionary trajectories of the frontal operculum and Broca’s area share a lot, and that a clear-cut division between the two areas will prove hard to make.

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