SFN: Brain Romance: Larry Young and Social Bonding

First up on this last morning at SFN2010 is Larry Young from Emory who will be discussing the Neurobiology of Social Bonding and Monogamy: Implications for Autism Spectrum Disorders. To start out the talk, Young discusses examples of pair bonding and monogamy in the animal kingdom. First, some jokes regarding human monogamy, which went by two fast for me to type down. These are followed by a brief mention of prairie vole pair bonding, to which Young will return multiple times during the course of the talk. And finally, a more exotic example: monogamy in the deep sea. The deep sea angler fish live deep in oceans, and displays a rather extreme form of pair bonding. To quote Larry Young*,  “a male can spend half of his lifetime searching for a female. So when the male finds the female, he forms a bond. And not an emotional bond. A physical bond.” These extreme changes in the male’s circumstances ensure that the male WILL reproduce every time the female spawns.

Did pair bonding evolve by tweaking mechanisms that promote maternal bonding? Pair bonding has evolved multiple times, and it seems unlikely that such behavior would have evolved newly each time. So the hypothesis is that pair bonding is a tweaking of the maternal bond that is evident in many (if not all) mammals. It is known that the chemical oxytocin is highly involved in regulating the peripheral physiology of reproduction, as well as the transition to maternal behavior following successful reproduction.

An example: virgin rats avoid pups, but a day before they give birth, there is a behavioral change in that pregnant rat will start to seek out pups. Oxytocin is critical for this behavioral switch – injection of oxytocin into virgin rats will cause them to seek out pups. The same is true for sheep and bonding with lambs (except with oxytocin release stimulated via cervicovaginal stimulation of the female sheep).

And so back to pair bonding in voles. The basic behavioral assay is called the Partner Preference Test, details of this assay can be found in the literature, but, in brief, involves allowing a female and male to mate, and then presenting the male with a novel female and its mating partner. The male will spend the vast majority of its time with its mating partner, and will in fact display aggressive behavior towards the novel female. [Bloggers note: video of the pair bonded voles clearly demonstrates the complete adorability of social interactions between pair bonded animals.] Oxytocin is required for female pair bonding.

And now we move onto the prairie vole versus meadow vole story. I highly recommend reading the original papers, but the basic gist of the research is that prairie voles display social pair bonding while meadow voles do not.

Oxytocin release into nucleus accumbens causes pair bonding. It makes sense that there is a conserved oxytocin mechanism underlying both pair bonding and maternal bonding. Think back to the research showing that in female sheep, cervicovaginal stimulation (which simulates birthing) releases oxytocin and results in maternal bonding. This mechanism of oxytocin release could easily also underlie pair bonding because, to quote, “there is a heck of a lot of cervicovagina stimulation going on when females are mating with males.”

So female bonding involves release of oxytocin, but what about male pair bonding. Vasopressin plays an important role in pair bonding in male prairie voles (also underlying territorial behavior, scent marking, and aggression).  A bit of wild speculation – female pair bonding may have evolved from the maternal bond mechanisms, whereas perhaps male pair bonding evolved from the territorial processes. Another great quote (paraphrase, really): “So male voles consider females to be part of their territory. I’m only talking about prairie voles here.” Animals without of oxytocin and vasopressin have social amnesia.

Other molecules required for partner preference include dopamine and opiates, which suggests a link between mating and the classical reward circuitry in the brain. How does mating activate the reward system? During mating, the sensory stimuli activate the VTA causing release of dopamine/opiates into reward areas of the brain. Experimental evidence of a link between sex and reward learning: “we know that a male rat will press a lever to get a female rat to drop out of the ceiling”.

Why do meadow voles not form pair bonding? Interestingly, there is a lack of vasopressin receptors in the ventral pallidum in meadow voles, but not in prairie voles. Expressing vasopressin receptors in this area in meadow voles causes all of the “transgenic” voles to form pair bonding. Looking at the genetic mechanisms underlying the difference in vasopressin receptor expression, they first looked at differences between species (see previously published work for this story), but then ended up looking at individual variation within the avpr1a gene (vasopressin receptor) within the prairie voles. Interestingly, variation in the length of the microsatellite associated with the avpr1a gene can predict how likely the animal is to form a pair bond. Males with short microsatellite sequences are less likely to form a pair bond than males with long microsatellite sequences.

Is the work in voles applicable to humans? Another great quote (again, probably a paraphrase) “I work at a medical school, so I’m always asked, ‘Well these prairie voles are cute and everything, but how can we use…profit… off of this’”. Several groups are looking at human pair bonding, as well as levels of oxytocin and vasopressin in humans. On example is a recent paper that showed that genetic variations in the vasopressin receptor (again, avpr1a) predict whether human males will report a crisis in their marriage. (Bloggers note: commentary from the grad student sitting next to me: “All right, I’m getting a spit test.”). Further studies regarding the role of oxytocin in human relationships involve giving humans oxytocin, and how shown that this treatment can:  improve “mind-reading” in humans, improve the likelihood of eye contact between partners, increase emotional empathy and enhance socially reinforced learning. From these studies came the hypothesis is that oxytocin is acting by increasing the social saliency of the task stimuli, and this hypothesis brings us to the topic of autism. Autism spectrum disorder is characterized by a deficit in social interactions. Current strategies for enhancing oxytocin function involve identifying novel drug targets for promoting endogenous oxytocin release. One identified drug is melanotan II, which is also used in tanning and erectile dysfunction. Importantly, meadow voles that are given melanotan II form pair bonds, most likely because the drug stimulates endogenous release of oxytocin. This research has suggested that meadow voles might be a useful model for screening drugs for enhancing social cognition – this possibility is being explored, alongside work to develop primate models that could be used to test any drugs identified in the vole model as possibly enhancing social cognition.

And finally, a plug for Emory Universities new center for translational work.

For more information of Larry Young and his lab's current work, visit his lab website.

*I have attempted to quote verbatim from Larry Young's talk. All attempts to do so are indicated by quotations. However, given discrepancies in speed of his speech versus my typing, some quotations may not be exact.

SFN: Area PITd, a novel cortical area controlling visual attention?

I’ll admit that I listened to this talk only because it immediately preceded a talk on cholinergic modulation of visual and olfactory attention. However, I’ll be posting my notes from this talk. My reasons are two-fold: 1) the visual/olfaction talk was not as satisfying as I had hoped and 2) this talk appeared to reflect a solid scientific effort. Working on a mid-brain structure (the superior colliculus, thus the interest in attention), I am not as familiar as some about different cortical areas, and the process of identifying the involvement of those areas in particular processes. Those readers who are more familiar, please comment on your impressions of the research below. Without further ado…

This talk was entitled Cortical Area PITd, a ventral pathway area for the control of spatial visual attention?, by H. Stemman and W. Freiwald from Rockefeller University. As suggested by the title, the research identifies a role for a novel cortical region in the control of attention.

Starting off, the speaker (Stemmann) defined the functional properties that a region must exhibit in order to be classified as an attention control area. First, neurons within the region must encode visual information in a featureless manner. Second, the area should be involved in different kinds of attention. Finally, and most critically, electrical stimulation of the region must enhance the representation, and facilitate the recognition of objects in a spatially specific way.

The researchers started out using fMRI on monkeys to detect brain areas showing attention-related enhancement of activity. Their study identified an area in the inferior temporal cortex: dorsal posterior inferior temporal cortex. They note the magnitude of the attentional modulation in PITd was similar to modulation also seen in V1, V2, MT, FEF and LIP of their monkeys.

The researchers then recorded from PITd with multiunit electrodes while presenting the monkey with a variety of visual stimuli. They found no direction selectivity, but they did see enhanced firing activity when animal is directing its spatial attention to an area inside the receptive field of a recorded neuron. They recorded activity during a behavioral task, and were able to infer the trial outcome based on the spiking activity of the neuron (enhancement of firing rate was that strong). Furthermore, responses of PITd neurons accurately predicted task errors. This high degree of predictive ability was true for their entire cohort of 56 neurons.

Although they found no explicit direction selectivity, the researchers wondered whether the activity of PITd neurons was dependent stimulus motion (given that their stimulus involved fields of moving dots)? In order to confirm that the attentional effects/activity was not dependent of stimulus motion, they switched paradigms to a color discrimination task. They found that PITd neurons had no color tuning, but were still strongly modulated by attention.

From these results, they concluded that neurons located in PITd do not encode visual features of the stimulus, and therefore encode visual information in a featureless manner, and are involved in different kinds of attentional tasks (based on attentional modulation during two distinct task paradigms).

With confirmation that PITd satisfied two of the criteria for categorization as an area involved in controlling attention, the researchers next attempted to determine whether the region satisfied the third criteria. They asked whether electrical stimulation of PITd would cause changes in attention. Stimulation of PITd neurons when the visual target was inside the neurons’ receptive field result stimulated PITd when the target was inside the receptive field, saw an increase i

Electrical micro-stimulation inside receptive field of a PITd neuron made the monkey perform the visual task better. Micro-stimulation of PITd outside the receptive field caused the monkey to make significantly more errors as if attention was being directed to a spatial location outside the receptive field. Put another way, following micro-stimulation outside the receptive field, the monkey used the motion information encoded by the distracter to make their decision, not the cued location to which they should have been paying attention. These results suggested that by stimulating PITd, they could shift the spotlight of attention from to the cued location to the micro-stimulated location.

In summary, the presenter concludes that his research suggests that cortical area PITd, a ventral pathway area, may be involved in the control of visual attention.

A note that it is unclear (at least to me) what are the efferent and afferent connections to PITd, or how PITd fits into the established cortical attention circuit. However, the strength of the attentional modulation of PITd neurons, and their apparent ability to shift spatial attention is certainly impressive.

Sfn: An ode to #SFN10banter

Last night, I attended #sfn10banter, a social gathering of science bloggers and Twitter users. As promised*, a poetic celebration of the event:

The tweeters said "Hey we should meet up!" "Get some drinks, shoot the shit, put our feet up." We came at a canter, For SFNbanter. Great to meet everyone at the tweet-up.

*@Tideliar: as promised, official, poetic coverage

SFN: Neuroethics: Hank Greely on the impact of neuroscience on society

First up for me this morning: Hank Greely's talk entitled The Neuroscience Revolution and Society. For those of you not familiar with Hank Greely, he is a law professor at Stanford University who is (to quote his faculty website), a "leading expert on the legal, ethical, and social issues surrounding health law and the biosciences" who specializes in  the"implications of new biomedical technologies, especially those related to neuroscience, genetics, and stem cell research." I have heard Greely speak 2 times previously, discussing the implications of neuroscience (in particular fMRI technology) for society and the law. Last month, Greely chaired a discussion panel on neuroscience evidence in the courtroom - my blog coverage of the event can be read at the link.

He will talk about the ethical challenges that neuroscience raises, and what we, as scientists can do about it. Greely takes us back to 1969, what he calls the peaking of the first modern neuroscience ethics panic, during which the public came together in concern over many neuroscience themes, including neuroscience’s ability to control minds. He notes that concern over mind control led to many regulations being put in to place, based purely on speculative science. Greely fast forwards to today, where he sees the same trend towards public concern, whereas now the panic is caused by science that is actually available, as opposed to the more speculative nature of the science that was causing concern in 1969.

Greely discusses the problem with public policy being established based upon science that isn’t very good – for example eugenics programs based on our knowledge of genetics. He notes that in the case of genetics, fair and responsible public polities are well established, and the maturity of this process is about 10 years ahead of neuroscience.

What are the issues raised by neuroscience? Greely notes we are in a golden age of neuroscience, we are learning a phenomenon amount about neuroscience, and we care a great deal, both at the individual and the social level, about neuroscience given the close association between our brains and our minds. As we learn more about the brain, we will learn more about human thought and motivations. The ethical issues being raised fall into several categories. The first one of these is research ethics – as we learn more about the neuroscience, we will begin to consider questions regarding the ethics of doing research. For instance, what are the ethics regarding incidental information gathered during experiments – for instance tumors discovered during fMRI studies. Alternatively, ethical issues generated by storing brain images of participants in a database – can those images be used to advance information in ways the participants disagree with?

Greely turns to the question of how neuroscience will change our society, including changing education, medical care, and the law. Greely will talk about 6 different ways that neuroscience will impact the society – prediction, mind-reading, responsibility, consciousness, treatment and enhancement.

Prediction: neuroscience is helping us predict better things about people’s behavior. Sometimes, this involves predicting future disease states – neuroimaging or genetic predictions of who will develop Alzheimer’s. Now, this seems like a good thing, but what are the implications. If our ability to predict Alzheimer’s was coupled with a treatment, this would be fantastic. But as in the case of many genetic predictions, we often are able to predict despite being unable to prevent the occurrence of the disease. Greely notes that we are protected under federal law from discrimination based on genetic predispositions, but not predictions based upon brain scans. Predictive information is not just information - it has consequences, both good and bad. Greely poses the question of who will be responsible for producing the predictions (doctors, companies), and who will be able to have access to the information, beyond the patient. He wonders what we would do with information that predicted with 100% accuracy which 8/1000 children will develop schizophrenia, or make accurate predictions on future criminal/violent behavior. He states that if we can ask the question (what do we do with the information), someone will want to answer it.

Mind-Reading: Greely repeats a line I have heard from him before, that humans are all mind-readers. It is important for us to figure out what those around us are thinking, generally using facial cues, body language, etc… He comment that we all try to do it, but we just aren’t very good at it, and the world would look a lot different if we were better at it. And with neuroscience, we are getting better at it. There are many examples of imaging research where scientists look at activity and make suppositions about what the subjects are subjectively thinking. Now, much of that research involves figuring out whether, for example, a person is thinking of a place or a face – this is not of immediate applicability in the courtroom. But what is applicable is research that is attempting to figure out what people believe or think: e.g. lie detection, figuring out whether people are actually feeling chronic pain, whether people are biased. He introduces the current two commercial companies that offer lie detection, and the two recent court cases that asked whether they would allow fMRI-based lie detection as evidence (they both said no). Greely notes that there is currently no regulation of this field but people are still applying the technology.

Responsibility: Greely discusses recent court cases where the defendants use neuroscience brain scans to claim insanity. A more common argument in these court cases is that its not the defendants fault, it is the fault of their brain and how it works. What will juries do when told that a defendant is a psychopath, and their brain makes them a murder?

Consciousness: Greely brings up the recent paper where two groups showed that of a group of 54 patients diagnosed as being in a vegetative or minimally-conscious state, fMRI scans showed that in 5 patients, being told to plan a motor task resulted in activity in the motor planning area. In addition, 4 patients showed activity in brain regions responsible for navigation when told to imagine walking through their homes. Finally, they took one patient, who had been diagnosed in a vegetative state for 5 years, and showed that he was able to answer personal questions by selectively activating either the motor planning or navigation area. What will we do with that information? Greely comments that doctors at Stanford have already started having families of patients diagnosed as being in a vegetative state ask that the patient be put into an fMRI scanner.

Treatment: Greely wonders what happens when we learn how to “cure” things that are not diseases, such as “deviant sexual behaviors”? What happens when a neuroscience attempts to cure addition with brain lesions, as happened recently in China, where doctors made electrolytic lesions of the nucleus accumbens of soldiers addicted to opium. They reported that after the lesion, soldiers did not crave opium, but Greely notes that the peer-reviewed paper did not report what else the soldiers did not crave. Another example are laws requiring that people convicted of a long list of sexual offenses are required to undergo chemical castration, despite the fact that we don’t have much information regarding the efficacy or safety of the chemicals used for the castration. In addition, even if we know that treatments for addition, psychological diseases, etc… are efficacious and safe, when do we mandate their use?

Enhancement: Many (most) scientists use mind-altering drugs – caffeine and chocolate both alter brain chemistry. But there are greater numbers of students who are now using Ritalin without a prescription to enhance their cognitive abilities. Of course, Ritalin and other drugs like it are not that good at enhancing cognition. But what about memory-enhancing drugs developed to treat diseases such as dementia and Alzheimer’s? What do we do if these drugs work on 20-year olds? What should universities or medical schools do about the availability of these drugs? Greely states emphatically that the single greatest cognitive enhancer is primary education, the ability to read and write. What did we do about it? We made it mandatory. How will be respond to a new host of drugs.

And lastly, Greely turns to the question of how society will respond to neuroscience research regarding the human condition. How will we assimilate information regarding the differences (or lack thereof) between the brains of humans and other animals? What about consciousness – when we can identify it, how will this alter how we treat patients, or fetuses? What about free will – how society react once we can identify the exact mechanisms that lead to our decisions, when we can show that circuits in our brains have made a decision long before we consciously acknowledge that decision. How will religion be affected? Greely imagines that it won’t affect society too much – the general public will continue to believe in free will not matter what evidence neuroscience throws at them.

Having talked about these issues, Greely turns to how neuroscience should start to handle them. The first step is to conduct research to show conclusively whether the techniques mentioned over the past hour are effective and safe. Going further, are questions about how we use these techniques if they are effective and safe? Neuroscientists have perhaps a smaller role, but an important one in making sure the public is aware of the complexities of the science and the techniques. And lastly, the deeper existential questions – and here Greely states that neuroscientists and non-neuroscientists all are on an equal footing, each with something to contribute.

So what can we, as neuroscientists, do? Greely calls us to consider the ethical issues of our own work, and to talk about these ethical issues, whether they come out of our own work or the work of others. He encourages neuroscientists to get involved, to join the Society for Neuroethics, to communicate with the public on these issues, to bring our sophisticated understanding of the strengths, weaknesses and limitations of neuroscience to discussions in the public domain. Greely tells us that he must believe that the more we discuss these ethical issues, the less likely we are to mess up the big decisions. In conclusion, he hopes he made us think about the short and long term implications for neuroscience on society, and that he had convinced us of the critical need for educated neuroscientists go get involved in the introduction of our knowledge into society.

Note: Greely suggests that those interested in asking him questions should email him at hgreely@stanford.edu.

SFN: Mark Bear on fulfilling the promise of molecular medicine in autism

Sorry folks - getting a little behind on these, but I hope they're still interesting and helpful! On Saturday, I attended Public Symposium 2 on Autism, Progress & Prospects to hear what Mark Bear had to say about "fullfilling the promise of molecular medicine in Autism" Bear outlined two principle problems with the quest for molecular medicines - the brain is a complicated place, and most neurological disorders are as yet poorly defined (ie. symptomatically rather than biologically). Much of autism is of unknown genetic etiology, but the field has had more success studying syndromic forms of ASDs such as Rett Syndrome and Fragile X Syndrome, the latter of which is studied by the Bear lab.

Bear showed how the successes in fragile X research fit into a general model of the strategy for solving neurological disorders. The syndrome was characterized in 1943, but not identified as a silencing of the gene FMR1 by a CGG repeat until 1991, and a knockout mouse was made in 1994. A hypothesis of the involvement of excess mGluR5 was developed in 2002, and the phenotype of the Fmr1-KO was rescued by reduction in mGluR5 in a 2007 study. Currently mGluR5 NAM inhibitors are in phase 2 clinical trials.

Bear reminded us of the role of precise synaptic connections in sensory processing, and that the basis for this specificity is not genetics alone, but that experience modifies this connectivity during postnatal development, as Hubel and Wiesel showed in their studies of monocular deprivation. Bear has long been interested in the role of Group 1 mGluRs in the weakening of deprived eye synapses. In Huber et al, 2000, LTD was induced by administration of DHPG, an agonist of Group 1 mGluRs. This effect requires synthesis of protein at the synapse, leading to the hypothesis that mGluR5 signaling directly leads to removal of AMPA-Rs from the membrane, but additional protein synthesis is required to stabilize this cache and prevent them from returning back into the membrane. One of these proteins is FMRP.

Bear paused to discuss Fragile X, which is reported to be the most common inherited form of mental retardation, and is a "syndromic" disorder, meaning that there are many phenotypic components, ranging from physical abnormalities to cognitive/behavioral deficits.

But how is this related to the mechanism of LTD? Excessive mGluR activity may affect protein synthesis at many points in the brain, which could produce the syndromic nature of the disorder. Further, downregulation of mGluR5 seems to correct aspects of Fragile X syndrome. FMRP does seem to be important for regulating protein synthesis, as 25% increase in protein synthesis was observed in hippocampus of the FMRP-KO animal. But, Bear asked, are psychiatric symptoms a consequence of excessive mGluR5 activity? His group crossed the FMRP-KO with animals heterozygous for mGluR5, and found that decreased mGluR5 rescued excessive protein synthesis in HC as well as many phenotypes of excess (such as increased spine density) through the brain. Bear hoped that this could be a valid therapeutic target - MGluR5 antagonist MPEP has worked in mouse and even fruitfly models of fragile X disorder.

Bear presented a model in which mGluR5 signaling produces increased translation, while FMRP acts as a brake on protein synthesis, such that when FMRP is impaired, excess synthesis results in response to normal mGluR5 signaling, which can be corrected by decreasing mGluR5 activity. This avenue has recently led to exciting results in phase 2 clinical trials of mGluR antagonists, although there are still many important considerations, however, including determining appropriate treatment age, dose, duration of treatment, and domains and instruments to measure improvement in the syndrome.

Bear proposes that the findings on single-gene disorders may suggest a final common pathway to all autism spectrum disorders. Many of the syndromes involve proteins in the synaptic protein synthesis cascade: NF1, PTEN, TSC1/2, FMRP etc. are all repressors of synthesis at the synapse. Could Autism Spectrum Disorders involve a common dysregulation of synaptic protein synthesis?

Bear outlines once more his proposed roadmap to treatment of neurological disorders and ASDs: Study genetically engineered animal models of rare highly penetrant causes of ASDs to understand pathophysiology and discover therapeutic targets. Test shared pathophysiology hypothesis in animals. Connect the dots to discern relevant genes. Focus on variants. Conduct clinical trials.

SFN: The genetic approach to the auditory system

Fred Kavli Distinguished International Scientist Lecture Understanding Sound Processing in the Auditory System: Advances Rooted in the Genetic Approach

Christine Petit, MD, PhD, College de France and Pasteur Institute

Yesterday morning, Dr. Christine Petit of Paris’ Pasteur Institute explained what genetic studies of families with early-onset deafness have told us about auditory processing. After giving an overview of what we know about the physiology of audition, particularly the cochlea, she described her work on the molecular basis of congenital early-onset deafness, and finally discussed advances in our understanding of the molecular basis of hearing that has come out of this approach.

Dr. Petit began by pointing out that auditory communication takes up more than 20% of our lifetimes, and perhaps more for some people! (I can't believe that never occurred to me before.) Humans can communicate not only with speech, but also can somehow convey emotion through music. Information is contained in the frequency composition of both these types of sounds—in the example she gave, “son” (French for “sound”), the “s” is broadband and contains higher frequencies, while the “on” phoneme is composed of lower frequencies and shows a cleaner harmonic structure. We know that the left auditory cortex is involved in speech and language, while the right auditory cortex tends to be associated with voice, prosody and music processing.

The cochlea performs several steps in the analysis that allows us to extract information from auditory inputs. It performs mechano-electrical transduction, changing sound waves into neural activity; frequency analysis (AKA Fourier transformations!); amplification; generation of distortions known as Tortini sounds or effects; and generation of suppressive masking, which increases the contrast between sounds and is necessary to make speech intelligible.

Next, the speaker gave an overview of cochlear anatomy and how mechanotransduction occurs. People in the audience might have caught a shout out to Stanford’s own Tony Ricci, for whom it is unclear whether auditory physiology or softball is a bigger obsession. I’ll spare you the nitty-gritty of the basilar membrane et al. for the moment, and simply say that critical steps in mechanotransduction occur at the delicate connections between hair cells and the basilar and tectorial membranes that sandwich them. Almost all congenital deafness, it turns out, involves cochlear defects in processes such as ionic homeostasis, inner hair cell synaptic defects, or mechanotransduction defects.

Isolating components of hair bundles is difficult due to their small size and the difficulty of extracting them. To get around this barrier, the speaker has taken the tack of finding large, intramarrying families with different types of congenital deafness and looking for mutations they share. This search took her to Tunisia, Lebanon and several other countries. They have identified several genes of interest, different ones causing deafness in different families. For example, they found defects in connexin26, a gap junction protein. Mutations in this gap junction are apparently responsible for a large proportion of inherited deafness, up to 30-50% (in Caucasian populations).

At this point the focus shifted to describing several genes that have come out of this work. First came otoferlin, a member of the ferlin family. Otoferlin^-/- mice have defective synaptic exocytosis, probably due to vesicle priming or fusion issues. Dr. Petit attributed the incredible temporal reliability and precision of auditory transduction in part to the huge volume of vesicular release in the cochlea (as many as 1000 vesicles/synapse – compare that with the single vesicle released at a typical central synapse!). This points to an explanation for why otoferlin mutations result specifically in deficits in hearing and not all processes requiring synaptic exocytosis.

Next she described components of tip links that have been identified by this approach. For the uninitiated, tip links are molecular ties, heretofore of unknown structure and composition, that connect the delicate protrusions from the apical surface of a hair cell known as stereocilia. Stereocilia, which are grouped into “hair bundles”, are part of how mechanical deflection of hair cells by sound waves opens ion channels and generates electric currents.

She named two classes of relevant genes, Usher I and Usher II, and focused on Usher I genes, which she said are “the heart of the mechanotransduction machinery”. We now know that tip links are composed of two Usher I proteins, protocadherin15 and cadherin23. Another Usher I gene she discussed was harmonin b, a knockout of which appears to prevent full relaxation of the tip link. A few other genes were discussed more briefly - readers are welcome to contribute details!

SFN: Hikosaka on Motivation, Value, and Reward

Presidential Special Lecture for Sunday, 11/14/2010. Note that this is essentially a transcription of the talk as I understood it, and I have not added any editorial comments, though the content is certainly somewhat altered from its original form (though hopefully not its original sense) by its journey through my ears, brain, fingers. We all know what motivation is. It comes from within. In Oliver Sachs' Awakenings, some patients had an "absense of will" and would do nothing without external intervention. Without motivation, there would be no impetus to accomplish anything, so clearly there are societal implications for the study of motivation! A loop is proposed in which Motivational Network drives an Action Network, which produces an action, leading to an outcome, which then modulates or drives the motivational network. If this is broken, action could grind to a halt.

The Action Network is composed of a hierarchy Cortex, Basal Ganglia, and Motor Areas. The Limbic system is thought to be the core. Dopamine neurons located in Substantia Nigra and Ventral Tegmental Area have been implemented, but what controls these neurons and what signal they carry is still not clear.

Questions:

What is the signal underlying motivation?

How does motivation control actions?

Question 1: What underlies motivation?

A monkey undergoes a Reward-based saccade task in which one direction of saccade gives a much larger reward. After a number of random trials, this contingency is reversed. Latency of saccades to the same targer is always smaller in the big reward than the small reward condition, suggesting a higher level of motivation.

Dopamine neurons are clustered in VTA. Parkinson's disease caused by loss of dopamine neurons, and lack of motivation has been ascribed to these patients. When a rat can stimulate electrical activity in its own brain, Corbett & Wise (1980), the lowest thresholds were seen for stimulation of the area with the highest density of dopamine neurons. Dopamine neuron firing predicts future rewards.

Building a Circuit for Motivation: Where do dopaminergic neurons get their predictive powers? Proof of functional connections to this system has been rare. Christoph et al 1986 suggest connection to the habenula, which functions in response to stress and pain, avoidance learning and error monitoring, and has whose dysfunction has been implicated in major depression, schizophrenia, and drug-induced psychosis. This is quite different from the function of the dopaminergic system. However, LHb is involved in prediction error, though it responds with opposite activity (negative reward modulation) compared to the dopaminergic system (positive reward modulation). It may provide this prediction error to VTA via inhibition. This seems to be mediated through the rostromedial tegmental nucleus. Where does LHb get its prediction error signal? Globus Pallidus neurons responsive to reward project to LHb. Specifically, negative reward signals seem to be transmitted to LHb from GPb. Habenula also projects to Raphe nuclei (directly or indirectly) to modulate serotonin (5-HT) release. dRN seem to represent the current reward state, whereas dopamine system seems to represent the derivative of (change in) reward state.

One can be highly motivated to differentiate cues - imagine being a hiker who sees animal droppings - you will be very motivated to determine whether they are dear or bear droppings! A task is described in which red target gives prediction of which subsequent cue will give a bigger reward, while green target indicates that the outcomes of the subsequent cues will be random. After several days of training in which either target can be chosen, the monkey will nearly always chose to get information about how the cues.predict reward. Experiments suggest that habenula & dopamine circuits contribute to this desire for information.

As a hiker, you will keep going because the best reward may hide behind some risk. A task is described in which one saccade target predicts juice reward while a second predicts no reward. As expected, latency to saccade is less to the juice-predictive image. However, when one image predicts air-puff and another no air puff, the latency to the air puff predictive stimulus is shorter. The monkey is more motivated to obtain information predicting events either good or bad. LHb is inhibited by 100% reward CS and 50% reward CS, but excited by 0% reward CS. They are also excited by 100% or 50% Airpuff CS, but inhibited by 0% Airpuff CS. They seem to respond to least rewarding / most aversive stimuli. In STc/VTA, on the other hand, many neurons response is the reverse, responding most to the least aversive/most rewarding stimuli. Other neurons, on the other hand, respond more to salience than to value (responding to most to 100% likelihood of either positive or negative events). The first population is located in ventromedial STc/VTA (which projects to ventral Striatum), the second, in dorsolateral STc (which projects to dorsal Striatum). Salience signal may originate with amigdala, superiuor colliculus PPTg, whereas motivational value is thought to originate in GPb, LHb, RMTg. While value is thought to be important for learning, salience may be more important to promote exploration.

Single DA neurons seem to change their properties depending on the phase withing the goal-oriented behavior. They begin encoding salience, but when the goal is approached they mostly encode motivation.

Question 2:

How does Motivation Control Actions?

Superior Colliculus encodes saccadic eye movements, which can be paired with reward. We've discussed anterior striatum, but what is the function of the posterior striatum (ie. tail of caudate, posterior putamen)? Receives input from visual association cortical areas, and respond to some complex images (fractals) but with strong spatial and object specificity. Perhaps these biases depend on Monkey's experience? In a bias task, monkeys are rewarded for saccading to one category of 4 fractals, but not rewarded for another category of 4 fractals. Tested by simple free viewing of 4 of eight randomly chosen stimuli. After several days of training, clear bias arises in both behavior and neuronal activity. Most time was spent looking at pictures associated with reward, and avoiding others, and posterior striatum neurons responded more to reward-associated stimuli than no-reward predicting stimuli.

Motivational value signals projected from GPb, LHb, and RMTg, to ventromedial SNc/VTA, probably to ventral Striatum. Salience projects to dorsolateral SNc/VTA, which transmits to dorsal striatum. Anterior striatum may be used for fast adaptation, while posterior striatum may be used for slow but stable adaptations. This may allow the brain to adapt to a complex environment sufficiently and robustly.

[Updated: Additional coverage of the Hikosaka lecture, here.]

SFN: Hikosaka on Motivational Circuitry

Presidential Special Lecture: Motivational Neuronal Circuits for Value, Salience and Information - Okihide Hikosaka After an introduction from Mickey Goldburg*, Hikosaka takes the stage!

Hikosaka begins his talk with ruminations on the meaning of motivation, stating that motivation is the internal drive to accomplish goals. He presents a conceptual scheme describing two networks: action and motivation that work together to produce goal directed activity. Function of these networks is as follows: action network produces a motor action that produces an outcome, which is then evaluated by the motivation network, which either promotes or inhibits the action network. A key feature of the motivation network is its ability to predict the outcome of the action network. In hard neurophysiological terms, the motivational signal is thought be involve dopamine, but the exact signal, and its information content are not well described.

To examine motivational signals, Hikosaka uses the reward-based saccade task for monkeys, which requires a monkey to make a saccade in return for varying amounts of rewards, depending on the cued direction of the saccade. This biased reward paradigm allows the researchers to evaluate the saccade latency when large versus small rewards are expected. Indeed, saccade latencies are significantly faster when a larger reward is predicted. Using this paradigm, HIkosaka has found reward selective neurons in many areas. One such area is the substania nigra/VTA, which contains a population of dopaminergic neurons that project to multiple areas in the striatum, palidum, and cortical areas. The role of dopaminergic neurons in reward has been reported by multiple groups, but HIkosaka’s group has recorded single dopamine neurons, showing that these neurons are activated by reward, and inhibited by the lack of a reward, predicting the future outcome of the motor activity required by the behavioral task.

But what is driving this activity? Hikosaka notes that evidence for direct functional connectivity onto dopamine neurons has been slim. One exception was research suggesting that the habenula is a major input onto these dopaminergic neurons. The habenula is involved in responses to stress and pain, avoidance learning and error monitoring, all of which have been implicated in the etiology of major depression, schizophrenia, and drug-induced psychosis. These phenomenon are quite distinct from those associated with dopaminergic dysfunction. Recording directly from habenula neurons (in particular lateral habenula), they found neurons that responded to reward prediction errors, but with the opposite sign to responses in dopamine neurons.

What drives the lateral habenula? Many brain areas, but the globus pallidus appears likely to be an input important for encoding reward prediction errors. Recordings from the globus pallidus demonstrated neurons that are inhibited following stimuli predicting reward, and excited by stimuli predicting no reward. Further results suggested that negative reward signals are passed from globus pallidus to lateral habenula. Then, additional expeiments showed that the lateral habenula acts on dopaminergic neurons in the substania nigra/VTA is via rostromeidal tegmental nucleus (see the poster by S. Hong from Hikosaka’s lab later on in this week).

Switching subjects slightly, Hikosaka notes that serotonergic neurons in the dorsal raphe nucleus appear to encode current reward state, where as dopamine neurons encode changes in reward value.

Hikosaka states that motivation is often thought to be driven by reward. But Hikosaka suggests that motivation for research is also a valid type of motivation. To examine this potentially distinct expression of motivation, a new paradigm was created, one that presents the monkey with an information cue or a random cue – the information cue gives the monkey advanced information regarding the size of the reward it will get. They use this paradigm to ask which cue the monkey prefers – to know what reward they will get or not. After a few days of training, the monkeys preferred to know if advance whether they would get a large or small reward. What neural mechanisms underlie this desire/preference for advanced knowledge of reward?

Hikosaka’s group recorded from dopamine neurons, confirming that dopamine neurons encode reward prediction error, but also showing that dopamine neurons are excited by the presentation of the information target, but inhibited by the non-informative target. They also recorded from habenular neurons, and found similar responses. This suggests that the habenula/dopamine circuit contribute to the monkey’s desire for knowledge.

Another type of motivation: Motivation for Salience. A reward may come with risk – what are the neural mechanisms underlying the decision to take a risk for the possibility for reward. To test this, another paradigm was constructed wherein a particular image was shown right before a juice reward, with another image displayed before no reward. Building on this, a new picture was associated with an airpuff to the monkey’s face, and another picture with no airpuff. Similar to the reward condition, the latency to looking at the picture predicting the punishing airpuff was faster than the latency to looking at the picture predicting no punishment. The reward and the punishment have opposite valiances, but are both salient – how does the brain encode both? Research into this question was done by Matsumoto, and was published in 2009 (Bloggers note: this paper – Matsumoto and Hikosaka - is well worth a read), showing that lateral habenula neurons encode motivation value in the negative range. Recording from dopamine neurons in VTA, they found two populations, one of which were encoding value for positive valence, another of which encoded motivational salience, not motivational value. So in summary, they found two populations, one motivational value encoding neurons, and another that encode motivational salience. Matsumoto and Hikosaks worked to localize these two populations. They found that motivational value neurons were localized to ventromedial VTA, which is though to project to ventral striatum. Motivation salience neurons were located primarily in dorsolateral VTA, which may be projecting to dorsal striatum. Again, for a more detailed description of this research, see the published research, Matsumoto and Hikosaka, 2009.

Hikosaka returns to his model of action and motivation network, and brings up the question of how the reward system alters the action network, specifically the connection between the dopamine system and the posterior striatum, which eventually feeds forward onto the superior colliculus, which is involved in saccadic eye movements. Hikosaka highlights a portion of the posterior striatum, the tail of the caudal and posterior putamen- this area is known to receive inputs from visual association areas. They recorded neurons from posterior striatum, finding to their surprise that a majority of neurons responded to visual images with a high degree of object and spatial selectivity. They wondered whether this selectivity was dependent on the experience of the monkeys – could previous reward associations influence the selectivity of posterior striatal neurons? They trained the monkeys on a task that associated a set of specific images with reward, and another set of images with no reward. They then recorded the neuronal activity during presentation of a random selection of these images. After several days of training, they started to see a clear preferential bias in monkey behavior and striatal neuron activity in response to the reward-associated images.

Posterior straitum is known to project to SNr – these neurons also bias, but in the opposite sign (excited by no reward-associated images, not activated by reward-associated images). Neurons in the SNr projected to the superior colliculus, where they are presumably influencing generation of the saccade.

Hikosaka concludes his talk by returning again to his model of action and motivation network, stating that the motivational network can control the action network in multiple ways, via multiple pathways. In summary, Hikosaka states that the heterogeneity of the motivation and action network may “allow the brain to adapt to a complex environment, efficiently and robustly”.

*Winner of the Stanford Neuroblog’s Award for Most Epic Bow Tie

[Updated: additional coverage of the Hikosaka lecture, here.]

Oh posters

First day of SFN. Ok I'm tired already. Went to good talks and some posters. Just wanted to make a quick comment before I collapse in bed. Ive been hearing a lot of complaints from students about the quality of posters at this SFN. Maybe it's not unique to this SFN and it's a problem every year, but it seems more talked about this year. Many people feel that presenters are not explaining their posters clearly enough and their descriptions are unintelligible to all except those working in that specific field. Presenters often ignore the big picture and go straight into their "data dive" which may not make much sense unless you've been working in that field for a while. Isn't the point of SFN to get people from various branches of neuroscience to come and be exposed to different ideas and techniques?

So why is it that most people are so inadequately prepared for presenting their posters? Could be that they don't have the presentation skills to lay out the big picture and put things in context before getting into the data on the poster. Or it could be that they do it on purpose so as to deter people not familiar with their research area from spending too much time at their poster (assuming their principal objective is to get good feedback regarding their experiments from people experienced in their field). Or it could just be that people are simply tired of going through everything for the 95th time and just skip to the bare essentials which are not enough to convey to the audience the information that they're trying to convey and hold their interest at the same time.

I don't know. I'm gonna do an experiment tomorrow to try to figure out. Day 2 here I come!

Suraj

SFN: Wurtz and Brain Circuits for Active Vision

Gruber Lecture: Brain Circuits for Active Vision. Robert Wurtz, PhD, National Eye Institute/National Institutes of Health After an brief introduction to the Gruber International Prize Program by Sarah Hreha, Executive Vice President of the Peter and Patricia Gruber Foundation, Michael Goldberg (and his excellent bow tie) present the 2010 International Research Award for Neuroscience to Laura Colgin and Jason Shepherd. Congratulations to them both.

This is followed by the presentation of the Gruber Prize to Robert Wurtz by Sten Grillner (chair of the Neuroscience selection advisory board for the Gruber Foundation). Wurtz long, auspicious career is described, highlighting his groundbreaking work on the visual system of awake-behaving primates. The official text of the award: “Honored for his pioneering work in the neurophysiology of visual cognition, which has led scientists to a deeper understanding of how the brain is organized to produce behavior.”

And after a few acknowledgements, Robert Wurtz begins his talk.

Wurtz notes the usefulness of having post-docs in the lab… for when a monkey gets loose.

When presented with a visual scene, we have the perception that we see every part of that scene with equal clarity at all times. However, neuroscience has shown that this is emphatically not true, we constantly make saccadic eye movements that focus our high acuity vision to examine different parts of the visual field at any time. These eye movements shift the fovea, and visual attention, displacing the retinal image of the visual scene and producing a blurred sweep of visual information during the saccade movement itself. And yet with all this movement and displacement, our brain computes the visual information to produce the illusion of a unified, clear visual field.

The talk will address four points: 1) an overview of the brain areas involved in active vision, 2) attention (enhancement of vision with saccades), 3) suppression (decreases of the inter-saccade blurring) and 4) the mechanism that generates saccades, which underlies both attention and suppression.

First, Wurtz describes the methodologies used to study active vision in awake monkeys. The basic setup is to record neuronal activity from head-fixed monkey who are fixating on a visual location.

Next, he outlines the basic system underlying the generation of saccadic eye movements. From V1, the pathway extends to the posterior parietal cortex and the frontal cortex, and thereon to the superior colliculus, and to the midbrain and pons for generation of motor output. To highlight the role of the superior colliculus, which is a critical component of the saccade generating circuit. For the purposes of the talk, the SC can be divided into two layers, a superficial, retinorecipient layer, and a deeper layer that encodes information regarding planned saccade movements. These visual-motor neurons display a burst of activity immediately prior to the eye movement.

With this type of activity introduced, Wurtz presents a two-fold experimental strategy: 1) correlation of neuron activity to behavior and 2) perturbation of neuron activity via activation or inactivation of neurons. He notes that in the second part of this strategy, classic techniques have been chemical or electrical means, but that recently they have turned to optogenetic inactivation of neurons located in the deep layers of the superior colliculus (this in collaboration with Ed Boyden’s lab).

Correlating and perturbing neuronal activity leads to classical view of superior colliculus, namely that it is largely involved in motor generation of the saccade. Newer research has suggested that the superior colliculus is also a major source of ascending pathways to inform the cerebral cortex about the saccade. These ascending pathways leave the superior colliculus and go directly to the thalamus before going to cortical areas (for example, SC to MD to FEF; SC to Pulvinar to LIP/MT or SC to Reticular Nucleus to thalamocortical relay neurons (LGN)).  Wurtz will focus on the SC to Pulvinar to LIP/MT pathway.

We now turn to the topic of spatial attention, specifically looking at the phenomenon of change blindness. We are showed a demonstration of change blindness, which demonstrates the power of spatial attention to direct

Wurtz describes two types of attention. The first he calls onset attention, which generates saccades to new objection (also known as bottom up, or involuntary attention) – this is eliminated during the change blindness test. The second type is goal directed attention (aka top-down attention) which remains during the change blindness test. Wurtz will discuss this second form of attention, and the role of the superior colliculus. Results from experiments demonstrated a motor theory of attention which postulates that the mechanisms generating saccades to a target contribute to a shift of attention to that target – this theory was demonstrated particularly well by Tirin Moore’s 2002 experiments in stimulating FEF to shift attention and gaze.

The question for Wurtz examined was if the superior colliculus saccade generation activity contributes to attention modulation in cortex. They used a change blindness task, modulating SC activity to attempt to alter cortical processing of visual information. He first describes the paradigm of motion detection change blindness. Briefly, the subject fixates, is presented with 3 groups of dots that are moving in a direction, with out of those groups switching directions after a blank screen is shown (to induce change blindness). Cueing the participant to which group is likely to switch will shift visual attention, increasing the ability of the participant to detect the change in direction. If the visual cue is replaced by stimulation of the superior colliculus, they see a significant improvement in the ability of monkeys to detect change in the stimulus. So stimulating a neuronal component involved in saccade preparation produces a behavioral effect similar to attention. From this research, Wurtz notes with great satisfaction a cognitive function like spatial attention can be understood at the mechanistic level of neuronal activity.

Wurtz now moves on to the suppression of visual activity that occurs during the saccadic eye movement itself. The classic explanation involves corollary discharges, where information generated in sensorimotor processing is sent as a corollary discharge to other brain areas, where it informs those areas about the movement that is about to be made. Where are the saccade corollary discharges produced? Wurtz suggest it is the superior colliculus – he notes that they have identified two corollary discharge pathways: SC to MD to frontal cortex as well as SC to inferior pulvinar to occipital/parietal cortex. To summarize the research on this first pathway: the SC to FEF path provides a corollary discharge that acts of compensate for the displacement of the image on the retina. The second pathway may contribute to elimination of the blur from saccades (aka saccadic suppression).

Why look at superior colliculus as the origin of corollary discharge for saccadic suppression? Recordings from SC neurons show reduced responses to visual stimuli during movement. Furthermore, saccadic suppression starts before the saccade, and SC neurons demonstrate a decrease in responsiveness to visual stimuli immediately prior to saccadic movement. This resulted in a hypothesis stating that intermediate SC layers receive inhibitory inputs – slice recordings support this as occurring. But how does SC-mediated saccadic suppression get into the cortex? Recordings from MT neurons demonstrate saccadic suppression similar to the suppression seen in SC neurons. But are is this cortical suppression the result of the SC suppression? One problem is that it is not clear what the actual pathway is. Wurtz describes experiments that have been done to locate the pulvinar relate in the circuit between the SC and MT. He notes that they have found some relay neurons in a subregion of the inferior pulvinar that are connected to both SC and MT (this research done by Rebecca Berman and involved recording from pulvinar neurons while stimulating both SC and MT).

So does this circuit carry saccadic suppression? To test this, Berman has been recording MT neurons that show saccadic suppression while inactivating SC – her results show that in the absence of SC activity, there is an increase in MT neuron activity – suggesting that suppression in SC contributes of saccadic suppression in cortex. Wurtz notes that MT responses are a combination of SC and V1 inputs – inactivation of the SC removes one (inhibitory) input, leaving only the excitatory V1 inputs.

[Bloggers commentary: the role of the SC-pulvinar-MT connection in suppression of MT activity should perhaps be taken with a grain of salt. The exact components underlying the suppression of MT are not as clear as Wurtz suggested. The pulvinar is not an inhibitory area, so how it could be directly suppressing MT activity is not clear. One possibility is that inhibitory circuitry within in the SC is responsible but again, the exact players involved have not been identified. And intra-SC inhibition would not support their model of MT activity being the sum of SC and V1 inputs, with knocking out SC resulting in increased activity because of removal of inhibitory drive. Indeed, that model would require pulvinar to be responsible for inhibitory drive onto MT, something that is not supported by any currently described circuitry. If intra-SC inhibition is responsible, then you would expect that inactivation of SC would yield MT activation equal to drive from V1 (aka removal of additional excitatory drive), with no additional enhancement of MT (as might be expected if SC inactivation removed inhibitory drive, which Wurtz suggested is the case). In conclusion, the exact connections and role of the superior colliculus in attention and saccadic suppression have not yet been fully defined, End of commentary.]

To sum up his talk, Wurtz restates his claim that our perception of visual stability can be understood at the level of simple neuronal circuits. In conclusion, he notes that the brain circuits he has discussed all have the same basic structure, with their different functions dependent on what signals are conveyed and where those signals are directed. He notes that this structure suggests that corollary discharges and spatial attention can be viewed as variant of a general scheme. Finally, he point out the progress being made in elucidating the brain circuits that underlie cognitive processes for active vision. Still to be fully described are the mechanisms underlying decision for action, working memory, and rewards/values. He notes that understanding these cognitive functions depends on studying circuits at the highest levels of the cerebral cortex, and that understanding of these functions is necessary for comprehending the many diseases of the brain. He lends his support for research utilizing the monkey brain as an experimental model, stating the monkey brain provides unprecedented opportunities for understanding a wide range of cognitive processes and diseases.