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Pain

John Wood (University College London) Pain, mechanosensation and sodium channels (Brambell Translational Neuroscience Seminar Series, 26/4/2012).

A talk about pain and analgesia: by identifying signaling mechanisms for pain we can find new drug targets, hopefully the neurons involved will be outside the blood-brain barrier so that the drugs will have fewer side-effects. As always with talks about metabolic systems and pathways I didn’t get much out of it. I learned that the somatosensory pathway has neurons which are pseudo-unipolar, meaning that the axons splits and goes in two directions

I learned that the origin of pain has been controversial with a dispute as to whether it represented by a neuron which always signals signalling beyond a threshold, or the onset of signalling by a neuron whose function it is to detect pain; the latter is now preferred. Finally, the interaction between the somatosensory system and the sympathetic nervous system is, in the view of the speaker, something that is becoming interesting again, classic work from the fifties and sixties should be revisited he suggests.

He introduced his talk, about chronic pain, with Frida Kahlo’s powerful painting The Broken Column.

Movement of crowds and of urban traffic.

Anders Johansson (University of Bristol) Multi-scale human mobility (BCCS seminar Tuesday, 24/4/2012).

A talk about how people move, with sections about people walking in crowds and crowd safety, for example, at the Hajj and about traffic and road usage. It was an overview talk so hard to summarize, one of the most interesting pieces was a video of a large crowd at the Hajj walking to Ramy al-Jamarat for the stoning of the Devil. In the video the density had been color coded, so that back-ward moving stop-go waves were clearly visible. This is apparently the source of danger, you should avoid large unsegregated crowds where complicated internal crowd dynamics occurs, so several narrower passages would be safer. The speaker and his team do crowd modelling by taking video and removing individual and replacing them with a modeled individual but leaving the other members of the group as before, the error is the displacement of the modeled individual from the position of the individual they replace, this is then optimized by changing the rules governing the movement of the model. The model is basically a speed adjustment coming from a function of the displacement of nearby individuals, it depends on $r$ and $\theta$ but they assume the function is separable into a $r$ function and a $\theta$ function. It is hard not to worry that the error function is poor since it doesn’t take into account the adjustments the other individuals would’ve made in response to the movement of the modeled individual, but I suppose that doesn’t matter for small values. Anyway, there model accounts for lane-formation in crowds moving in two directions along a corridor. This is some interesting function of densities, with some sort of lane formation transition, there was a question about this, but it wasn’t really discussed. There was also mention of a crowd movement experiment, people were told they had to keep moving and keep within a meter of at least one other person, five people were secretly told to move in a specific way, this was enough to entrain a crowd of 100. Conversely, in fire alarm test, if the alarm is a simple bell people often pause and wait from someone else to move first and determine the route, if the alarm gives simple spoke instruction evacuation happens much quicker. There was also lots about traffic, with courier data for London, but not many details given.

Direction cells.

Paul Dudchenko (Stirling) The neural encoding of destination and direction. (Brambell Translational Neuroscience Seminar Series, 19/4/2012).

Unfortunately I had to leave this early, so I missed most of the speakers own recent work, what I did hear was partly review and partly older work, which was still all new to me.

Rats are known to have direction cells, a given direction cell has a tuning curve and fires when the rat’s head is pointed in a specific direction. If the experimental arena has a visual cue that seems to be what the rat uses to orient itself, so if the area is circular with only one cue and rat is removed from the arena and the cue moved, the direction cell tuning curve is moved by the same amount. If there are no visual cues, the rat will develop a tuning curve anyway, but if a visual cue is introduced, the rat will incorporate this into its sense of orientation, so if more than eight minutes after the cue is introduced, the cue is moved, the direction tuning curve moves by the same amount.

Now, rats also use path integration to determine direction, if a rat is allowed to move from one box to another through a door, the tuning curve in the second box will be close in orientation to the one in the first, in fact, there is a precession of about 20 degrees. One interesting experiment compared visual cues and path integration. The rat spends time in one box (a), it was then moved to another (c) but only after being moved around enough the lab a bit in a box. The direction tuning curve was different in each box. Now, four boxes were linked by doors, the two boxes the rat had been in before, a and c, and two novel boxes, b and d, with b between a and c and d after c. The rat was allow to spend time in each box before a door opened allowing the rat to move into the next box. the door then closed. Path integration meant that the tuning curve in b was almost the same as in a, the question is, would c be like b, as dictated by path integration, or as it was before, as dictated by visual cues. The answer was the latter and when the rat moved into d its direction tuning curve there was similar to the one for c. Hence, memory of visual cues beats path integration!

Synapses and actin.

Jon Hanley (Bristol): Actin dynamics in dendritic spines (Neural Dynamics Forum, 16/3/2012).

So there were lots of details in this interesting talk and lots of pictures of glowing dendritic spines; the basic topic was the changes that occur in dendritic spines during long term plasticity and the role actin plays. One thing I learned was that there are two processes at work in long term plasticity, a relatively quick one in which receptors are removed and sequestered away from the membrane and a slower one in which the spine itself changes size. Since, to the first approximation, the strength of the synapse depends on the number of receptors, the first process is sufficient to effect the plasticity: it would be interesting to know if the plasticity is somehow more provisional, more reversible, before the spine changes size and consolidates the change, I asked about this but it isn’t known. The spines themselves are not as button shaped as I expected, they are more like mushrooms, with a neck and a blob; the actin are long proteins that seem to lie along the inside of the spine and are continually being build and broken apart.

Plankton

Fanny Monteiro (Bristol) Modelling diversity of marine phytoplankton (BCCS seminar Tuesday, 20/3/2012).

Phytoplankton play an important part of oceanic storage of carbon, they live near the ocean top, absorb carbon, die and sometimes sink to the depth where the carbon is sequestered. They come in diverse types, some with shells, shells of silica or calcium, some that can fix nitrogen. Originally modelling was done in a top down way, with different species examined in the lab and added to a simulation, now, a range of random artificial plankton are created with different efficiency and resource limitation trade-offs, grown in the simulated world oceans and then matched to known populations. This seems to work well, here it was used to examine distributions of nitrogen fixing plankton, the model is consistent with the limited experimental data, and predicts that unicellular nitrogen fixing plankton are more common and more significant than previously believed: the larger, colony based nitrogen fixing plankton are more common where there is more iron in the water, near deserts, and this is where data is more available. The distribution of nitrogen fixing plankton is explained by nitrogen availability, where it is available, usually because of up welling from the depths, they are out competed by other plankton species.

Bumble Bee size.

Margaret Coulvillon (Sussex): The hows and whys of bumble bee size variation (BCCS seminar Tuesday, 6/3/2012).

So bumble bees live in nests, like honey bees, who knew? Unlike other social insects, for bumble bees, there isn’t such a clear distinction between different roles, either by body type, or age. There is, however, a dramatic variation in size, the biggest bumble bees are ten times the size of the smallest. Now, bigger bumble bees are more commonly found foraging and smaller, tending to the young; there is no bimodal size split though. It seems by removing parts of the population it can be observed that bigger bees are better at foraging, surprisingly though, they are also better at looking after the nest. Why the range of sizes then: it turns out that smaller bees survive starvation better so the fitness and robustness curves slope opposite ways with bee size and rather than choosing a sweet spot, it is better to have a variation so some bees survive protracted starvation, by tending the young they ensure the nest’s genetic material will survive.

Bees laid closer to the center of the nest get fed more before they emerge and end up bigger. The egg location depends on the apparently random peregrination of the queen. I wondered if the balance is maintained by always having the same laying behavior or if the queen steers it to the ideal by modifying her laying behavior based on local cues. This isn’t known.

This leaves out lots of the great bumble bee details in the talks and the description of the many experiments on nests to work out what is described here and to rule out other hypothesizes about the bee size.