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Google summer of code 2012

As a PhD student at INI, I have had the pleasure this summer to 
participate to the Google Summer of Code 2012 
(http://code.google.com/soc/), a worldwide program run by Google that 
funds students to work for three months for open source organisations as 
software developers. Among the participating 180 open source 
organisations this year, there have been many projects related to the 
development of tools for scientific purposes, such as bioinformatic 
software, crowdsourcing biological games to involve the general public, 
libraries for hardware and sensors, and even the International 
Neuroinformatics Coordinating Facility (http://www.incf.org/) has hosted 
6 interesting projects.

Personally I have contributed to the development of an application for 
Cytoscape 3.0 (http://www.cytoscape.org/) to support visualisation and 
analysis of dynamic networks. Cytoscape is a powerful tool to visualise 
network data in the form of graphs with nodes, edges, and attributes, 
but until now focused mainly on static data. Developing the software 
infrastructure to deal with dynamic data, that is graphs that change in 
time, while the main code of Cytoscape 3.0 was under active development, 
has been an interesting - and successful- challenge.

http://www.youtube.com/watch?v=R6RkMQpOmDs

The ability to visualize and understand dynamic data is very important 
in our own research, which addresses how genetic regulatory programs 
orchestrate the development of cortical architectures in different 
species. The development of open source tools to address this type of 
data is not only of personal interest, but is also directed to reach a 
broader scientific community, and possibly involve more people in the 
future of this project. I'm looking forward to what the next Google 
Summer of Code has to bring!
 
- S. Pfister 

Two questions on VISION and OLFACTION


As a human, I know that I’m a very visual creature, spending most of my work hours reading papers (cough) and examining interesting objects in my visual field (ahem). A greater proportion of the information that the human brain has to process comes from the visual system. Most of our memories are stored as visual imagery. Taking this into account, when one compares the anatomical structures and connectivity of the visual system to the olfactory system, which processes the sense of smell, one finds a curious imbalance: the olfactory system seems to be directly connected to our emotion-cognitive brain structures such as the Amygdala and the Hypothalamus, as well as the more decision oriented frontal cortex, and even more astonishingly, it is the only sensory system which has – in its sensory layer in the epithelium of our nose – the ability to replace and renew olfactory sensory neurons. The visual system, or for that matter any other sensory system, does not possess these special characteristics. The direct connectivity to the Amygdala probably allows us to assign positive or negative associations to certain smells which directly influences our behavior towards them. We know that the smell of something putrid will invoke an immediate aversive response from us (or any other animal), and a unique smell, like the smell of fresh linen, can instantly and almost involuntarily trigger a recall of memories from the remote past. Here in lies the first of my two questions, why does visual input lag behind olfactory input in stimulating behavior directly and effectively? Does the answer lie in a stronghold maintained by the evolutionary older olfactory system?

It is obvious that the olfactory system is of great importance to many species of animals: insects such as the widely studied fruit fly, rodents such as mice, and our very own best friend the dog, are all highly dependent on their sense of smell for survival, and it is well known that their sense of smell is much more refined and has a much larger range than ours; for example, the sensory epithelium of a dog has a surface area forty times that of humans. Through the course of evolution, as animals moved to land from water bodies, the greater variety of smells they encountered on land required a larger and more complex olfactory system to be able to perceive and discriminate smells. This is the reason why fish possess fewer olfactory coding genes (about 100) than mice (1000 genes, the work of Nobel laureates Axel and Buck). There is a certain trend, in our species and related species such as the Gorilla, to have become less dependent on olfaction and more dependent on vision; evidence comes from studies in loss of gene function (carta.anthropogeny.org). So it seems that evolution is driving us toward becoming more and more visually oriented animals. Here’s a surprise though: a recent study by Bastir and colleagues (Nature communications 2011) reports an increase in olfactory bulb and orbito-frontal cortex size (both involved in olfactory processing) in modern humans compared to Neanderthals. As we all know, Neanderthals are extinct and we are thriving! I wouldn’t want to read too far into the results but they do seem to confuse the evolutionary trend!

The second question is more of a wild conjecture into the remote unknown future of  humanity: how will our brain look like in another, say ten thousand years, assuming the rate of evolutionary changes in the brain is increasing and we haven’t done anything calamitously stupid? Will the evolutionary relaxation on selection of the olfactory system result in a changed anatomy? Will the visual system start projecting directly to our emotive and cognitive structures?  Will the olfactory system shrink in comparison? Will we start regenerating cells in our retina and lose this ability in our nasal epithelium? It would be sad though, because I definitely love the smell of tea and Indian food, and I don’t think their appearance alone would suffice ;-)

- G. Narula

Beware of fashion...


Reading through yet another study (Huebner and Gegenfurtner, 2012) using natural images as stimuli, I started thinking about their contribution to our understanding of visual processes. Using natural images has undeniably shown that current models of visual processing are still incomplete. Indeed, most model based predictions of neuronal responses to natural images are poor, including for cells in primate primary visual cortex (V1), a cortical area considered by many to be relatively “well-understood”.
Knowing that a model is inaccurate or incomplete and gaining insight into the causes of its failures are, however, two very different things. In my opinion, using “natural” stimuli has hardly, if at all, contributed to the latter. I do believe that the most important results concerning the functional properties of visual neurons have been obtained, and will for a while continue to be, using simple stimuli. Sinusoidal gratings, for example, allow us to use the powerful tools of linear system theory , to systematically study failures of simple linear models, and to uncover the important non-linearities in visual signal processing.

Why is it then that the number of studies using natural images has grown so much in recent years (by my counting, only 2 papers used them in 1990, they were 62 in 2010, and there are already 62 half-way through 2012)? I think it became a fashion due to the increasing ease with which these stimuli can be stored, displayed and manipulated, and to the erroneous notion that using “natural” stimuli would bring us closer an understanding of what neurons do outside of the lab, in “nature”. Such a notion would make us  believe that Galileo Galilei should not have performed   his inclined plane experiments to study mechanics. Instead, he should have saved the trouble by simply observing falling bodies in nature, thereby gaining simultaneous insight into the laws of motion, inertia, acceleration, gravitation and turbulent  air resistance. Well, the inclined plane experiments are now considered seminal in mechanics and a monument of reductionist science, the fabled dropping of objects from the tower of Pisa apparently never  even occurred...

It may be appealing to use complex stimuli to study the complexity of nature, it may even become very fashionable, but the complexity may be so high that it masks the underlying processes. Similar thoughts occur to me when I hear people criticizing such old fashioned methods as extracellular single cell recordings. It is of course much more fashionable to use optogenetics or two-photon calcium imaging. The main question for me is whether we have learned everything we can learn from the old methods using simple stimuli. New methods are great but it doesn’t mean old ones should be abandoned…

- D. Kiper