Cortical oscillations and synchrony have long been touted as candidate mechanisms to solve the ‘binding problem’ in theoretical neuroscience: when we examine the world around us, how do our brains group multiple parts of the same object together into a coherent whole? A simple example is the cat standing behind a fence. Even though whole segments of the kitty might be blocked off from our view, we still perceive it as a single object. This happens even when the segments of the visual scene are too far apart to be seen by overlapping cells in the retina – so the information must be ‘bound’ somewhere else in the brain.
Experimental evidence implicating oscillations in this process was first found by Wolf Singer’s lab in Germany in the late 1980s (Gray et al, 1989). They reported that spatially seperated neurons in cat visual cortex mostly fired at the same time when the cat was presented with moving bars of light, as long as the neurons both preferred bars of the same orientation and were aligned in the same direction as the moving bar stimulus. This might seem like a banal result, but it hinted for the first time that neurons in the neocortex might encode information in the exact timing of their spikes (relative to some external osciallation), rather than just through their firing rate over longer time periods. In this way, spatially seperated neurons might somehow co-ordinate their firing patterns to become part of the same neuronal ensemble, and maybe represent specific features of the outside world.
Following this discovery, a sustained experimental and theoretical scientific interest has resulted in a huge library of data exploring the theory, and even implicating oscillations in attention and consciousness. Many, many debates and arguments have ensued over the origins of these oscillations and whether or not they are really used by the brain to code information. I am not going to attempt to dip my toe into this ocean here. If you’re interested, I suggest looking up the experimental work both of Wolf Singer and his former student Pascal Fries, who now runs his own lab in Nijmegen, Netherlands. BU’s Nancy Kopell has been a driving force on the more theoretical aspects of oscillations.
Despite the mountain of work on this topic, a real mechanistic description of these oscillations has yet to be demonstrated in a realistic computational model of the brain. The Blue Brain project – that other big science experiment in Switzerland – might finally make the link. Earlier this week at the inagural INCF conference on Neuroinformatics, Henry Markam reported that a recent modification to their detailed simulation of a rat cortical column produced persistent oscillatory activity in the gamma frequency band (roughly 40-80Hz).
This is significant, because the model wasn’t designed in any way to produce this behaviour. It simply emerged after setting up the cortical column of 10,000 cells with realisitic connectivity patterns and electrophysiological properties. As far as I understood, they simply stimulated layer IV and watched a wave of activity build up, propagate throughout the column via layer II/III and initiate gamma ocillatory activity in layer V. This behaviour only emerged following one of their weekly updates to the simulation. Markram wouldn’t say exactly what changes they made, unsurprisingly enough. Expect a publication forthcoming.
We could argue all day about the Blue Brain project and its significance. Many people (especially other experts) do. I had seen several presentations from the BB team before, and I suppose that I had kind of made up my mind that it was probably going to be a useful logistical excercise which would generate new tools for neural data sharing and analysis, but ultimately hopeless in helping us to understand the brain. As Markram himself admitted, the whole model is “half-baked”, and the experiment was done without a hypothesis. There are so many gaps in our knowledge (e.g. plasticity rules, dendritic ion channel distributions, neuromodulation) that the whole endeavour seemed to me to be a waste of time. But after seeing Markram’s talk last Monday, I am sold. This is mainly for two reasons:
- Of course the current model isn’t perfect. But it is a first step on the long road to a biologically realistic large-scale model of the brain. This will be a slow, iterative process.
- Despite the astronomical number of parameters, the model is actually fairly well constrained by biology. It’s in the right ball park. There are many phenomena you can reproduce in any abstract network model which wouldn’t work in the Blue Brain (or a real brain for that matter). As Markram says, why explore all of theoretical parameter space when we can focus on the biogically relevant subregion within it?
You can watch Markram’s talk here. The gamma oscillations are demonstrated 47 minutes in.
- Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties.
C M Gray, P König, A K Engel, W Singer.
Nature (1989) vol. 338 (6213) pp. 334-7