A few days ago I got an email from a colleague of mine pointing me to a video about birds of paradise. I am happy I went and looked at it because it is quite amazing. There is no question why this group of birds stand apart from others – they are not beautiful to watch, but their behaviour, too, is quite amazing. Watch:
There are other birds that I find absolutely amazing. The Lyrebird for example, incorporates into its song sounds that it hears as it goes about life. There are two types of song learning birds (songbirds). Some will learn to imitate a song from an adult tutor as they are growing up, and pretty much sing that song as adults. Others can continue to incorporate elements to their song as adults. The lyrebird falls into this last group. But what I find amazing about the lyrebird is not that it incorporates new song elements, but that some of those sounds are not “natural” sounds. Watch:
Another amazing bird is the New Caledonian crow. A while back Gavin Hunt (now at the University of Auckland) came to find out that these birds were able to manufacture tools in the wild. They modify leaves and twigs from local plants to make different types of tools which they then use to get food. This finding spurred a large body of work on bird intelligence. Watch:
And if you are interested of where these wonderful animals all came from, there is a fantastic blog by Ed Yong over at national Geographic. Read:
When a President annouces a scientific project as publicly as President Obama did, the world listens. The US is planning to put signifcant resources behind a huge effort to try to map the brain. There has been a lot said about this BRAIN project , and I have been quietly reading trying to make sense of the disparate reactions that this ‘launch’ had – and trying to escape the hype.
I can understand the appeal – the brain is a fascinating invention of nature. I fell in love with its mysteries as an undergraudate in Argentina and I continue to be fascinated by every new finding. What fascinates me about the discipline is that, unlike trying to understand the kidney for example, neuroscience consists of the brain trying to understand itself . That we can even ask the right questions, let alone design and perform the experiments to answer them is what gets me out of bed in the morning.
Trying to understand the brain is definitely not a 21st Century thing. For centuries we have been asking what makes animals behave the way they do. And yet we still don’t really know what it is about our brains that makes us the only species able to ask the right questions, and design and perform the experiments to answer them?
Many of us neuroscientists might agree that how we think about the brain came about from two major sets of finding. Towards the end of the 19th Centrury it finally became accepted that the brain, like other parts of the body, was made up of cells. It was Santiago Ramon y Cajal’s tireless work (with the invaluable assistance of his brother Pedro) that was fundamental in this shift. This meant that we could apply the knowledge of cell biology to the brain. The second game changer was the demonstration that neurons could actively produce electric signals. In doing so, Hodgkin and Huxley beautifully put to rest the old argument between Volta and Galvani. This meant we had a grip on how information was coded in the brain.
From this pioneering work, neuroscience evolved directing most of its attention to the neurons and their electrical activity. After all, that is where the key to understanding the brain was supposed to be found. Most of what happened over the twentieth century was based on this premise. Neurons are units that integrate inputs and put together an adequate output passing the information to another neuron or set of neurons down the line until you get to the end. In a way, this view of the brain is not too different from a wiring diagram of an electronic circuit.
Trying to understand the wiring of the brain, however, is, not easy. There are thousands and thousands of neurons each with a multitude of inputs and outputs. You can quickly run out of ink trying to draw the wiring diagram, It is because of this complexity that neuroscientists (just like scientists in many other disciplines) turn to simpler models. We have come to know some secrets about learning from studying the sea slug Aplysia, about how the brain gets put together from flies and frogs, and even about how neurons are born in adult brains from singing canaries. What all these models have in common is that we can tie pretty well a very specific aspect of brain function to a circuit we can define rather well. And we have learned, and keep learning, heaps from these models. The main thing we learn (and the reason why these models continue to be so useful and fundamental for progress) is that the ‘basics’ of brains are quite universal – and once we know those basics well, it is a lot easier to work out the specifics in more complex brains.
Trying to understand the architecture of circuits has proven to be of major value (and this is what the connectome is about). But building the connections is not just about drawing the wires – you need to build in some variability – some connections excite while others inhibit, some neurons respond in predictable linear ways, others don’t. And when you are done with that, you will still need to start thinking about the stuff we have not spent a lot of time thinking about: those other cells (glia) and the stuff that exists in between cells (the extracellular matrix). More and more, we are being reminded that glia and extracellular matrix do more than just be there to support the neurons.
So it is not surprising to find some skepticism around these large brain projects. Over at Scientific American, John Hogan raises some valid criticisms about how realistic the ambitions of these projects are given the current state of neuroscience (read him here and here). Other lines of skepticism center around the involvement of DARPA in the BRAIN project (read Peter Freed’s views on that here or Luke Dittrich’s views here). Others criticize the lack of a clear roadmap (read Erin McKiernan’s views here). Others have expressed their concerns that too strong expectations on advancing our knowledge of the human brain will overlook the importance of exploring simpler circuits, something that had been stated clearly in the original proposal .
Is now the right time?
Back in the ‘90’s the decade of the brain had insinuated it would solve many of these problems, I don’t think it did. Despite the neuroscience revolution from about a century ago and the work that followed, we still have not been able to solve the mysteries of the brain.
But this decade is somewhat different. I am reading more and more stuff that has to do with the emergent properties of the brain – not just the properties of the neurons. And for the first time since I started my road as a neuroscientists I am being able to ask slightly different questions. I did not think that successful brain machine interfaces would be something I’d get to see in my lifetime. And I was wrong. Even less did I think I would get to see brain to brain interfaces. But the works is moving forward there too.
The BRAIN project is not alone. In Europe the Human Brain Project received similar attention. We all expect that such boosts in funding for multidisciplinary research will go a long way in making things move forward.
It is inevitable to think of the parallels of the approach to these Big Brain projects and the National Science Challenges – which are wonderfully expressed by John Pickering here.
I think that Erin McKiernan’s cautionary words about the BRAIN project might be quite appropriate for both:
Investing in neuroscience is a great idea, but this is not a general boost in funding for neuroscience research. This is concentrating funds on one project, putting many eggs in one basket.
 Brain Research through Advancing Innovative Neurotechnologies,
 Alivisatos, A. P., Chun, M., Church, G. M., Greenspan, R. J., Roukes, M. L., & Yuste, R. (2012). The Brain Activity Map Project and the Challenge of Functional Connectomics. Neuron, 74(6), 970–974. doi:10.1016/j.neuron.2012.06.006
[Cross posted from Talking Teaching]
Ed Yong in Not Exactly Rocket science alerted me to an article published in
Biological Letters Biology Letters from the Royal Society. I will not discuss the content of the article, Ed Yong has (as usual) done a wonderful job. I would like instead to share the ‘concept’ of the article.
The article reports on some research that shows that bumble-bees use both colour and spatial relationship in their foraging behaviour. But enough about that. What is unique about this article is that the research was conducted by a group of school children. It is also unique in that it is written by a group of school children (in their language). And the icing on the cake are the figures: pencil coloured; no fancy graphic software.
This is, in my opinion, authentic teaching at its best. And authentic learning. And while we are at it, authentic publishing.
So what have I learned from this group of children? That, as they say, science is fun. And that teaching science, whatever the student age group, can be made fun and authentic and can get children motivated.
The background reads:
Although the historical context of any study is of course important, including references in this instance would be disingenuous for two reasons. First, given the way scientific data are naturally reported, the relevant information is simply inaccessible to the literate ability of 8- to 10-year-old children, and second, the true motivation for any scientific study (at least one of integrity) is one’s own curiosity, which for the children was not inspired by the scientific literature, but their own observations of the world.
I could not agree more. I love biology because I ‘played’ with biology as a child. I was fortunate enough to have a father who never answered my question with ‘I don’t know’ without following that up with ‘but lets try to find out’. As a child my father valued my questions and my curiosity, more so about things he didn’t have an answer for. And I will always be grateful to him for that. For my teachers, well, that was a different issue: rather annoying having a pupil in the class that just refused to overcome the ‘why?’ stage.
And these children have been given a great gift by being it let known that their thoughts and ideas have value. And that, once that barriers that have to do with the specific language of the scientific literature are withdrawn, their ideas and thoughts can bring about new knowledge.
These children will also grow up having learned a few fundamental things about science: How an idea is brought into shape, how scientific questions are narrowed, and the hard work and discipline that is needed to see an experiment through. Oh yes, and that no matter how good an idea may be, reviewers may still reject your grant.
None of this they could have learned from a science textbook.
The editors of the Royal Society should also be commended for not requiring that the manuscript adjust to the traditional publishing formats and allowing the authentic voice of the children to come through. This paper should become obligatory reading in science classes. If nothing else, children will recognise their own voices and curiosity in the reading, and, who knows, other groups of children with innovative teachers may teach us (adult scientists) another thing or two.
P. S. Blackawton, S. Airzee, A. Allen, S. Baker, A. Berrow, C. Blair, M. Churchill, J. Coles, R. F.-J. Cumming, L. Fraquelli, C. Hackford, A. Hinton Mellor1, M. Hutchcroft, B. Ireland, D. Jewsbury, A. Littlejohns, G. M. Littlejohns, M. Lotto, J. McKeown, A. O’Toole, H. Richards, L. Robbins-Davey, S. Roblyn, H. Rodwell-Lynn, D. Schenck, J. Springer, A. Wishy, T. Rodwell-Lynn, D. Strudwick and R. B. Lotto (2010) Blackawton bees. Biology Letters DOI:10.1098/rsbl.2010.1056
Imagine you drive into a motel in Gatlinburg TN, and see behind an open room door 2 guys setting up cameras pointing at the beds while two young women peek from the parking lot. Well, if it was in the mid ’90’s it might have been Drs Moiseff and Copeland setting up the equipment before venturing into Elkmont in the Smoky Mountains to study the local fireflies. (And one of the two women would have been me.)
Andy Moiseff and Jon Copeland started studying the population of fireflies in the Smoky Mountains National Park after learning from Lynn Faust, who had grown up in the area, that they produced their flashes in a synchronous pattern.
In the species they are studying (Photinus carolinus) the males produce a series or bursts of rhythmic flashes that are followed by a ‘quiet period’. But what is particularly interesting about this species is that nearby males do this in synchrony with each other. If you stand in the dark forest, what you see is groups of lightning bugs beating their lights together in the dark night pumping light into the forest in one of nature’s most beautiful displays.
Females flash in a slightly different manner and, as far as I know, they don’t do it synchronously either with other females nor with the males. One interesting thing in Elkmont is that there are several species of fireflies, and you can pretty much tell them apart by their flashing patterns. But as useful as this is for us biologists (since it avoids having to go through extensive testing for species determination), the question still remained of whether the flashing patterns played a biological role.
And this is what Moiseff and Copeland addressed in their latest study published in Science. They put females in a room where LEDs controlled by a computer simulated individual male fireflies. The LEDs were made to flash with different degrees of synchronisation and they looked at the responses of the females. They found that while the females responded to synchronous flashes of the LEDs, they really didn’t seem to respond when the flashes were not synchronous. Even more, they responded better to many LEDs but not much to a single one. What this means, is that if you are a male of Photinus carolinus, you better play nice with your mates if you want to get the girl.
What *I* want to know is how this behaviour is wired in the brain. At first hand, this seems like a rather complex behaviour, but in essence all that it seems to require is a series of if/then computations, which should not be too hard to build (at least not from an ‘electronic circuit’ point of view). But Bjoern Brembs reminded me of a basic concept in neuroscience: brains are evolved circuits, not engineered circuits. So, Andy and Jon, how *do* they do it?
Original article: Moiseff, A., & Copeland, J. (2010). Firefly Synchrony: A Behavioral Strategy to Minimize Visual Clutter Science, 329 (5988), 181-181 DOI: 10.1126/science.1190421
If you have been paying attention, you might have been hearing a rise in stories related to brains in the media (I will be blogging about some of them soon). This is because this has been Brain Awareness Week. My first (ever) post on a blog (now defunct and reborn here) was indeed one describing my last year’s experience organizing for the 3rd time the Open Brain Day at the University of Auckland.
A year has gone by, and I am sitting at this year’s Brain Day that is being held at the Business School’s Owen Glenn Building at the University of Auckland. This year we are also celebrating the launch of the Centre of Brain Research, which launched towards the end of last year, finally replacing the Auckland Neuroscience Network.
For the first time, I can look at the day without the pressure of running after a myriad of details. And this year we are bigger, longer and uncut. (Well, the latter not so true since we have some cut brains to show you what they look like on the inside).
If you have come to brain open days before, check it out again. If you haven’t then this would be a great time to start.