It's been a few weeks since SFN. It was exceptionally well organized, San Diego was beautiful, and the scientific content overwhelming as always. Sebastian Seung's entertaining Presidential Lecture, The Once and Future Science of Neural Networks, generated more chatter and emotion than any I've seen at SFN.
There were two main neuroscience topics in Seung's talk, the hedonistic synapse and connectomics. I'll briefly review each topic, and then discuss why the talk generated so much discussion.
The hedonistic synapse
The hedonistic synapse (review article in Neuron here) refers to a hypothetical learning rule in which synaptic weights are adjusted in proportion to a global reward signal broadcast through the CNS. For example, if a presynaptic spike is followed immediately by a postsynaptic spike, that synapse will be strenghtened if dopamine is present. If the same series of spikes occurs without dopamine, there is no change in the weights. Technically, the weight change is a product of the global reward signal and an 'eligibility trace' which describes the relevant relations among spikes in the pre- and postsynaptic neurons.
Seung's group has shown that a network of neurons using the hedonistic rule will tend to maximize reward in the system. So, hedonistic synapses can in theory maximize animal reward.
Seung then discussed the model in the context of birdsong learning, hypothesizing that when a fledgling's birdsong closely matches the stored template, a reward signal is broadcast to the appropriate nucleus, inducing hedonistic synaptic changes that will eventually push the actual song into alignment with the template. For that work, see this paper.
I am interested to see what happens when experimentalists vary reward signals while performing the typical experiments to evoke synaptic weight change. Will the rules change depending on reward? That would be very cool.
I haven't studied Seung's model in enough detail to understand how it relates to the well-known experimental demonstrations of spike-timing dependent plasticity (STDP: for a review, see this paper). STDP studies show that the sign of a synaptic weight change depends on the relative timing of spikes in pre- and post-synaptic neurons. Many of these experiments were done in slice or culture, and to my knowledge did not modulate dopamine or other putative reward signals in the preparation.
Connectomics is the study of the distribution and abundance of synaptic connections among neurons in the brain, a kind of synaptic ecology. Seung described an exciting collaboration with Winfried Denk, in which they are reconstructing, at nanometer scales, the structure of relatively large chunks of neural tissue (for a review, see this paper). The technique is known as serial block-face scanning electron microscopy (SBFSEM). SBFSEM will yield not only the wonderful dendritic and axonal morphology in the tissue, but will provide a full description of the distribution of synaptic connections as well.
You can view a beautiful movie that shows an example of such a reconstruction carried out in the retina (inner plexiform layer) of the rabbit. This movie received spontaneous applause from much of the audience.
Of course, simply having a circuit diagram of a chunk of tissue is not sufficient to reconstruct its functional architecture. The anatomy doesn't tell you the biophysical properties of the individual neurons and synapses, and network properties can be dramatically influenced by the neuromodulatory mileau in which the circuits are bathed. However, ultimately we want to wed the detailed anatomical and functional stories, and this work is a promising step in that direction.
Incidentally, 'connectomics' is a cheesy mouthful of a word. Some words just weren't meant to be biologized with the -omics suffix, and 'connect' is one of them. 'Genomics,' cool. 'Proteomics,' a little annoying and not very creative. 'Connectomics,' stop the bus I want to get off. At the very least let's reserve the -omics for molecular biology. Thank goodness Bialek didn't try to pull us into the world of 'infomics.'
The scientific content of Seung's talk was cool. You'd think the reactions would be mostly positive. What generated the meta-talk was the style of his presentation. It was peppered with dramatic pauses (e.g., the above movie was prefaced with, "Ladies and gentleman, I present...the retina."), lots of jokes, and big-picture musings on neuroscience.
Many people sitting near us at the talk were scowling much of the time; some said his theatrics were out of proportion to any truly novel scientific content. It wasn't like he was presenting something on a par with General Relativity.
In contrast, my reaction was quite positive (and I think the split is about 50/50 on this: very few were neutral). I found it to be a fun, informative, and inspiring talk. At the end of a long day of staring at posters and concentrating on technical talks, to have a seasoned theoretician from physics (the Bell Labs cult no less) give a conversational, approachable, big-picture perspective on the field of systems neuroscience was refreshing and quite entertaining. I found his excitement infectious and wanted to go and start doing experiments right when the talk ended. Sure, it required that I tone down my usual enraged skeptic demeanor (as a good sport will do in a horror movie), but at the end of a day at SFN, I had no trouble with this.