Do we need language to understand concepts?

July 14, 2009

AK doesn’t think so.

In another of his lengthy and well-researched posts, he argues that the understanding of more or less abstract concepts occurred in primates before a language based on words. This is based on a recent study of the mirror neurons in rhesus macaques. This research seems to indicate that rhesuses divide other rhesuses into two categories when the mirror neurons are activated: those within such a short distance that interaction is immediately possible, and those further away.

The post also includes an interesting reflection on how visual information is encoded in terms of a set of vectors in multidimensional space, suggesting that the same principle applies as a general form for representation in the brain.

In the process, AK also manages to discredit Plato’s idea that concepts are classes of things resembling an “ideal” concept that is by definition beyond our grasp. Instead, we construct concepts “bottom-up”, by grouping together objects and ideas that appear to us to have many similarities.

Implicit to AK’s argument is also the notion of a well-developed spatial modularity in the brain, with different areas encoding different concepts. While there is strong evidence for spatial modularity e.g. from split-brain experiments, showing that the two hemispheres can accurately identify and interact with objects independently of each other, it is very likely that at least some concepts are represented only by the concurrent activation of several areas in synchrony.


Monstrous effort to map a transcriptional network

July 8, 2009

ResearchBlogging.orgThe FANTOM consortium report in the latest issue of Nature Genetics that they have measured what happens with the entire, total, gene expression during the specific differentiation of a cell line called THP-1. Not the expression of just the 10 000 most important genes, all of them. At the same time.

Their findings are a heap of data which is probably larger than the whole body of research on medicine and biology up until the early 1900’s. If I try to say what their main finding is, I’d lean towards the interconnectedness of the signaling network. It doesn’t have one single weak spot, where you could knock out a certain gene and profoundly change the network dynamics. Knock-out of some genes had effects on many other parts of the network, but in general the system seems to be robust because of redundancy and interconnectedness. I have drawn similar conclusions in my own latest paper, though my methodology is a pair of binoculars compared to their multinational telescope.

Professor Hayashizaki of the RIKEN Omics Science Center was the general organiser of this study.

Professor Hayashizaki of the RIKEN Omics Science Center was the general organiser of this study.

My main thoughts, however, upon reading this paper were not so much about the actual research, but more about the way it was done.

  1.  With the advent of large-scale initiatives like these, we will perhaps have charted most of the “connectome” of the cell within the next decades. This is the map of the decision-making pathways. The neuroanatomy of the cell, if you wish. It has enormous potential to explain how, exactly, things go wrong in diseases such as cancer.
  2.  Biology is starting to resemble some branches of physics, where research advances through large concerted efforts. The author list of this paper is half a page long, with the authors’ affiliations taking up another half page. There will be less space for the nerdy loner scientists and greater demand for the entrepreneurial, outgoing kind of researcher in the future.
  3.  Seventeen figures and fourteen tables, and the whole methods section, have been relegated to the “supplementary material” that is only available online. Reporting on this kind of science in an 8-page article is like writing a short essay on “World War II”. I’m sure the best parts are in there, but you can’t begin to reenact it based on their descriptions. Lots of the interesting sub-analyses, which I presume must have been performed, will never see daylight. This is exactly the sort of science that benefits from the innovation of the online journal. No page limitations are needed there. Just last week, for example, I noticed that PlosOne had published a paper entitled “New Mid-Cretaceous (Latest Albian) Dinosaurs from Winton, Queensland, Australia”, which is 51 pages long and contains 40 illustrations, mainly of various bones photographed from different angles. Try getting that into a conventional journal!

Full reference:
Suzuki, H., Forrest, A., van Nimwegen, E., Daub, C., Balwierz, P., Irvine, K., Lassmann, T., Ravasi, T., Hasegawa, Y., de Hoon, M., Katayama, S., Schroder, K., Carninci, P., Tomaru, Y., Kanamori-Katayama, M., Kubosaki, A., Akalin, A., Ando, Y., Arner, E., Asada, M., Asahara, H., Bailey, T., Bajic, V., Bauer, D., Beckhouse, A., Bertin, N., Björkegren, J., Brombacher, F., Bulger, E., Chalk, A., Chiba, J., Cloonan, N., Dawe, A., Dostie, J., Engström, P., Essack, M., Faulkner, G., Fink, J., Fredman, D., Fujimori, K., Furuno, M., Gojobori, T., Gough, J., Grimmond, S., Gustafsson, M., Hashimoto, M., Hashimoto, T., Hatakeyama, M., Heinzel, S., Hide, W., Hofmann, O., Hörnquist, M., Huminiecki, L., Ikeo, K., Imamoto, N., Inoue, S., Inoue, Y., Ishihara, R., Iwayanagi, T., Jacobsen, A., Kaur, M., Kawaji, H., Kerr, M., Kimura, R., Kimura, S., Kimura, Y., Kitano, H., Koga, H., Kojima, T., Kondo, S., Konno, T., Krogh, A., Kruger, A., Kumar, A., Lenhard, B., Lennartsson, A., Lindow, M., Lizio, M., MacPherson, C., Maeda, N., Maher, C., Maqungo, M., Mar, J., Matigian, N., Matsuda, H., Mattick, J., Meier, S., Miyamoto, S., Miyamoto-Sato, E., Nakabayashi, K., Nakachi, Y., Nakano, M., Nygaard, S., Okayama, T., Okazaki, Y., Okuda-Yabukami, H., Orlando, V., Otomo, J., Pachkov, M., Petrovsky, N., Plessy, C., Quackenbush, J., Radovanovic, A., Rehli, M., Saito, R., Sandelin, A., Schmeier, S., Schönbach, C., Schwartz, A., Semple, C., Sera, M., Severin, J., Shirahige, K., Simons, C., St. Laurent, G., Suzuki, M., Suzuki, T., Sweet, M., Taft, R., Takeda, S., Takenaka, Y., Tan, K., Taylor, M., Teasdale, R., Tegnér, J., Teichmann, S., Valen, E., Wahlestedt, C., Waki, K., Waterhouse, A., Wells, C., Winther, O., Wu, L., Yamaguchi, K., Yanagawa, H., Yasuda, J., Zavolan, M., Hume, D., Arakawa, T., Fukuda, S., Imamura, K., Kai, C., Kaiho, A., Kawashima, T., Kawazu, C., Kitazume, Y., Kojima, M., Miura, H., Murakami, K., Murata, M., Ninomiya, N., Nishiyori, H., Noma, S., Ogawa, C., Sano, T., Simon, C., Tagami, M., Takahashi, Y., Kawai, J., & Hayashizaki, Y. (2009). The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line Nature Genetics, 41 (5), 553-562 DOI: 10.1038/ng.375


Reversible apoptosis: cancers can postpone the point of no return

April 21, 2009

ResearchBlogging.orgApoptosis – programmed cell death – is one of those processes that are only supposed to go one way. Once begun, there is no turning back. The cell begins to degrade itself through the activation of caspases, proteolytic enzymes that cleave the structural elements of the cell, leading to a series of morphological and biochemical changes. The cell digests itself from the inside, turning itself to a soup of dead organic molecules inside the cell membrane. In the end, it fragments neatly into membrane-enclosed bags that are small enough for nearby cells to phagocytose, i.e. eat up.

Evidence for reversible apoptosis
In a recent paper in the British Journal of Cancer, Tang et al. show that apoptosis may be reversible. They have taken a panel of several cancer cell lines and treated them with an inducer of apoptosis for a few hours, and then washed it off. When they monitored the cells over the next hours, they found that many cells transiently exhibit morphological signs of apoptosis: they shrunk, the nuclei condensed, and mitochondria were degraded, but a few hours later the cells returned to their normal shape. The limiting event from which the cells had no chance of return was when degradation of the nucleus had begun. Caspases were activated at the same modest level from 3 up to 48 h after induction, even though the cells were back to their normal shape before 24 h.

Human fibroblast undergoing nuclear fragmentation in a late stage of apoptosis. The nucleus is stained in blue and the cytoplasm in green. Photomicrograph by Joerg Schroeer.

Human fibroblast undergoing nuclear fragmentation in a late stage of apoptosis. The nucleus is stained in blue and the cytoplasm in green. Photomicrograph by Joerg Schroeer.

Loss of bistability in the apoptosis signalling network
In terms of the signalling network, apoptosis should be a bistable process. The cell should very firmly be either apoptotic or non-apoptotic. Cells that start to digest themselves and then stop should have a strong fitness penalty. We would expect the evolutionary process to select strongly against a reversibility trait both in an organism and in a group of cells. Contrary to this expectation, the reversibility trait predominates in all the cell lines investigated in this study. Something has been lost, or gained, in their signalling network. But how can they survive a partial self-degradation?

Mitochondria – redundant in cancer cells?
The hallmarks of apoptosis that are investigated in the present study reflect degradation in three steps: First, the cytoskeleton, leading to cell shrinkage. Then, the mitochondria, shutting off the cell’s aerobic metabolism. And finally, the nucleus, with the entire gene regulatory system. But the cytoskeleton is made to be remodelled, so it’s not that surprising that the cells can cope. With the mitochondria, it’s a different story. Cancer cells almost universally switch to anaerobic metabolism during progression. This is known as the Warburg effect. It is a very curious phenomenon that still awaits explanation. Many of the mitochondria in tumour cells therefore lack any useful function. In a sense they are little more than decoration, present mainly for historical reasons.

The hen and the egg
Is it the case that tumour cells first acquire apoptosis resistance through mutations that repeal the bistability of their signalling network, and then are forced to rely less on their mitochondria because they are sometimes degraded? Or is it the other way around? Or are these two processes driven by unrelated factors, leading to reversibility of apoptosis by chance, as it were?

It is too early to draw any conclusions. Further studies should investigate reversibility in relation to biochemical and not just morphological parameters. I will write more on the properties of bistable signalling networks and their robustness during the coming week.

Full reference:
Tang, H., Yuen, K., Tang, H., & Fung, M. (2008). Reversibility of apoptosis in cancer cells British Journal of Cancer, 100 (1), 118-122 DOI: 10.1038/sj.bjc.6604802


A single-cell organism that communicates using light signals

April 7, 2009

Some multicellular organisms emit light in a conspicuous way. Fireflies carry beacons that shine in the night, and some deep-sea fishes use phosphorescent appendages to attract prey. However, the information content in these light emissions is probably no greater than “I am here”, or possibly “I am moving in a certain direction with a certain velocity”.

A few days ago, a paper appeared in PLoS One showing that the unicellular organism paramecium caudatus uses light signals of a specific wavelength to communicate. These signals influence the proliferation rate of the protozoa and imply that they not only have a sense of vision, but also a signal-generating organ, and an apparatus to translate the visual input into a representation of its environment, which in turn guides the organism’s behaviour.

Paramecium caudatum. Image borrowed from A Blog Around the Clock.

Paramecium caudatum. Image borrowed from A Blog Around the Clock.

I found this story through the most interesting Neurotypical blog, written by a neuroscientist who starts off almost apologetically by saying that this has nothing to do with neuroscience. I beg to differ.

Although the paramecium possesses no nervous system, it clearly has all the necessary faculties for information processing of the kind with which neuroscience concerns itself. It is not the substrate that determines the dynamics of an information processing system, but the structure and organisation of the network.

Check out the post by Neurotypical, as well as the the original paper, it’s open access!


Is the Central Limit Theorem an engine for biological stability?

March 25, 2009

Biological information systems, like any others, struggle constantly with randomness. Our bodies are precision instruments to measure very many things at the same time – light, vibrations, gas pressures, concentrations of salts and hormones, to mention a few. Any of these measurements can be thought of as a sample. Now, randomness can cause the sample to lie quite far off from the actual measure. A possible solution is to resample the sample! This is not intuitive, and I will explain it below. Perhaps this is the reason why many signalling pathways in biology have so many links in the chain from receiver to effector!

The Central Limit Theorem states that if you draw a sample from a population and calculate the mean of the sample, and then repeat it several times, the means will form a normal distribution around the true mean of the original population. This means that even if the original population has a wild distribution, repeated samples of the population come closer and closer to the true mean.

Take a look at this example to see what it means:

Image from Wikipedia

Image from Wikipedia

Here, the original distribution is on the top left – highly irregular. But if we take samples of two numbers at a time from this distribution and plot their means, we end up with the distribution on the top right – already a great step towards normality! With three and four in the sample, we get the bottom left and bottom right, respectively.

Nearly all cell surface receptors signal through a pathway of messenger molecules. Not just one, but a whole cascade. The traditional explanation for this phenomenon is that the signal can be easily amplified in this way. But perhaps the real driver is the stability of the readout that can be gained. There are similar organisational features in other places too, for example in the transmission of visual information from the retina. The signals pass through a few serially arranged neurons on their way to the visual cortex. Perhaps this is what prevents our field of view from flickering? (The rods are exquititely sensitive and can detect a single photon.)

Perhaps I should write this up and submit it to the journal of Medical Hypotheses? (This is one of the few scientific journals that require no proof whatsoever, and as a result the journal contains everything from well-supported testable hypotheses to completely far-out ideas, such as the benefits of masturbation against nasal congestion.)

What do you think? 🙂


Surely you’re joking, mr Ernberg!

March 20, 2009

Have we really solved the riddle of cancer? Yes, says Ingemar Ernberg, the venerable professor who has written the foreword to ”Prostatacancer”, hot off the presses of the Karolinska University Press.

I was somewhat surprised by his argument, which runs something like this: If there ever were a riddle of cancer, we have solved it by showing how the cell’s actions are controlled by gene regulatory networks. With ceaseless environmental perturbations of these networks, coupled with the powerful organizing principle of evolution, nothing mysterious remains.

Certainly, the advances in tumor biology have been tremendous over the past decades. And it is no coincidence that much of what we have learned about genetics and cell signaling has been discovered in the context of cancer. But can we really say that we understand these processes because we have identified the constituent parts and some of their connections?

If this were true, the riddle of consciousness was really solved in the 1800:s, when Golgi invented the silver staining that for the first time enabled us to see how neurons connect with axons and dendrites.

What professor Ernberg does not consider is the complexity that arises through the dynamic information transfer of the network. On this higher-order level, in cells just as in the nervous system, behavior emerges that cannot meaningfully be accounted for by cataloging the interactions of the component parts.

If this is not immediately obvious, consider the following. Certain genes, when upregulated, cause cells to proliferate a lot. An example is the c-myc gene. This gene can be accidentally moved to the place for the immunoglobulin gene in certain lymphocytes when they are infected with the Epstein-Barr virus. As a result, the lymphocytes proliferate enormously, and we have leukemia. Other genes, which sometimes cause cells to proliferate a lot, can also sometimes cause them to die a lot. An example is th JNK gene. There has been much controversy over whether JNK is pro- or antiproliferative. Now, it is generally accepted that it is both.

In total, we humans have around 20 000 genes. Even if each gene only interacts with 10% of the other genes, and the interaction is always linear, a model to explain the cell’s behaviour would be totally intractable even with enormous computing power. When many of the interactions are non-linear, it becomes clear that a successful description of this system, with the power to predict what it will do, must consider a higher level of organisation. Analogies abound; reading the Pickwick papers by Charles Dickens letter by letter vs. by the meaning of phrases and their conjunctions (D. Hofstadter, in Gödel, Escher, Bach), or understanding a city by copying the telephone directory vs. actually finding out where people are going every day and why (Sidney Brenner).

The riddle of cancer remains. The most important discovery we have made so far is that the riddle of cancer is identical the to riddle of Life itself; namely how the genes and proteins that are the basic units of biological information, as well as the basic operators on this information, together determine the fate of the cells which are the smallest units of life as we know it.

(I am indebted to professor Ernberg for having created much of the intellectual arena where I have encountered several of the more groundbreaking recent advances of thought in tumor biology, and I argue against him safe in the knowledge that he will only be pleased that his ideas are debated.)


The Meaning of Systems Biology

March 9, 2009

Today, I had the pleasure of meeting prof. Marc Kirschner. He is the chairman of the department for Systems Biology at the Harvard Medical School. It’s a visionary place with about 200 scientists, small by American standards but far larger than my current department.

Marc Kirschner

Marc Kirschner

Kirschner is one of the world’s foremost cell biologists, and one of the first to thoroughly explore the information-processing capabilities of the cell. In his 1997 book Cells, Embryos and Evolution (written together with J.C. Gerhart), he discusses, for example, the capability of the cell to be used as a computing machine, in principle.

I read up a bit before meeting him, and came across an article he wrote for Cell in 2005 titled “The Meaning of Systems Biology”. Here he endeavours to explain what this new field is about, really. And he is the right person to do it, since he is more or less one of the founding fathers of the field.

Rarely have I seen such an established scientist move with such caution in his own field. He describes systems biology as a scientific branch in the making, and argues that only in retrospect will we know exactly what has come of this fruitful entanglement of genetics, molecular biology, cell biology, physiology, and evolutionary theory, all coupled with new high-throughput techniques.

Systems biology is not all about an increased data-generating capacity. It is, in Kirschner’s opinion, also about “a smaller scale view, totally compatible with and partially dependent on the global analysis of high-throughput biology. This view spans in vitro biochemistry to what is now called synthetic biology and it has as its goal the reconstruction and description of partial but complex systems.”

In the end, Kirschner only very reluctantly offers a rather long definition, which he says must remain tentative. At its core, I think it means that systems biology is the study of biological complexity through modelling of the underlying mechanisms, quantitative measurement, and theory.

So how did our meeting go? Well, I pitched a project idea that I’d given a lot of thought, and that is in my own opinion extremely elegant, well-conceived and likely to change the way we see the world. One’s ideas become like babies sometimes if you allow them to.

He thought there might be something in it, and suggested I should talk to the person in his department who has got the methods I would require – incidentally, the only person in the world who does. I certainly will. And then we’ll see where this ends!