I have been neglecting my writing duties, for which I apologise. Sorry you two.

I’ve been all over the place of late: Copenhagen visiting friends at the end of July, from whence we drove to the Wacken metal festival in Germany (best shows: Nasum, Kylesa, Volbeat). This proved true and brutal, as usual, but particularly so this year because of the mud baths created by the aggressive precipitation. Still managed to come back with a sun tan. After a fleeting visit to Hamburg, I spent most of the next week recovering, then undid most of that recovery with a visit to my sister for birthday celebrations, followed by a truly wonderful gig by Refused in London. I have a total man crush on the vocalist. The return to Newcastle on Monday took six hours: our train broke down. I managed to read a Viz from cover-to-cover though, so it wasn’t time entirely wasted.

This week I have been mostly analysing electrophysiology data from our experimental collaborators (details to follow, tomorrow maybe…), partly using a nice little toolbox for Matlab called Chronux. Unfortunately, it doesn’t seem to be under active development – the last release was in 2008 – as it has some nice functionality, but needs a little tidying up in places (one of the main authors, Partha Mitra, has co-authored a very interesting and useful book on neural data analysis and some philosophical background, but his web-site seems mysteriously inactive). If anyone knows any more details, please comment!

Passed out body

Do not pass out at Wacken

Woman’s bag

I went to the post office this morning to pick up my fabulous new shoes:

My lovely new shoes

A child there, who it seems was the son of the people running the shop, accused me of having a “girl’s bag”. This is my bag:

My nice bag

I would suggest that this bag could be worn proudly by someone of any gender, but apparently I am mistaken. Unfortunately I couldn’t say what I was thinking (“yeah, well you’ve got a girl’s FACE”) as his dad was there, and he looked significantly harder than me. I’m never sure quite how far you can take banter with seven year olds, anyway. I tried to assure him it was definitely a man sack but he was having none of it. “Hahah, girl’s bag, girl’s bag!” So picked up my parcel and left with my tail between my legs.

It could have been worse – his mum told me that last week he’d asked a lady posting a letter why she was so fat. Oh, sweet innocence.

Reproducing computational research

Reproducing results is a crucial part of the scientific process – given uncertainties in measurements, inherent variability and often randomness in systems under investigation, and the likelihood of human error, the only way to establish the truth of a reported result is by repeating the experiment to see if the results match. In the ironically named “soft” sciences (many of the -ologies) in particular, the systems under investigation are highly variable and almost always involve elements of randomness, so even the most careful experiments can only produce tentative results (though you’d believe otherwise from reading the news), thus requiring many repetitions in order for them to be accepted as reliable.

Computing has helped to eliminate some human errors from research, and allowed increasingly more complex and large experiments (e.g. human genome project and large hadron collider would not have been possible without advances in computer science). Computers have become essential for instrument control, data collection and storage, and automated data analysis. Additionally, computers allow very detailed and complex systems to be simulated, helping to generate or refine hypotheses that can then be tested experimentally. This is what I try to do – simulate the electrical activity in brain tissue in order to investigate hypotheses about the causes of diseases like epilepsy.

Unlike experiments in the soft sciences, computer simulations are easily reproducible*: a computer runs calculations reliably, so the same code run many times should give the same results. Unfortunately, the reality is far removed from this ideal. Complex systems require complex software to simulate them, and the more complex a piece of software, the more likely it is to contain errors. Different scientists using different operating systems with different software versions installed may not be able to run each other’s code reliably. Simulations will contain so many parameters that it is impossible to remember them all, especially when some are changed in order to alter the simulation behaviour. Even something as seemingly simple as a change in the numerical method used to solve equations can have drastic consequences on the simulation results.

Conventional software engineering techniques exist to help prevent these kinds of problems and ensure software reliability across multiple computers/operating systems etc., but many scientists have never learned anything about software engineering. ALL IS NOT LOST! Andrew Davison at the Centre National de la Recherche Scientifique in Paris has written a tutorial on best practices for writing code with reproducibility in mind. The examples are computational neuroscience oriented, but the observations and advice should apply to any scientific computing area. He makes the important point that the lack of reproducibility of many results can seriously damage the field’s credibility (cf. “Climategate” in climate science) as well as hindering scientific progress.

I am certainly guilty of ignoring many of the good practices Andrew wisely advocates, so it’s great to have a concise tutorial specific to scientific computing to refer to in future. I am currently in the process of restructuring a lot of my code, too, so it couldn’t have come at a better time from my perspective…



Music in the brain

Well not really, but indulge the metaphor because it’s a nice description of a phenomenon observed in epileptic brains. A recent paper in the journal Epilepsia (unfortunately behind a paywall, sorry) describes a pattern of electrical activity recorded from the brains of epilepsy patients that may be helpful in predicting when seizures occur. The paper is a good example of useful cross-disciplinary work: it combines clinical, basic and computational research to arrive at a convincing mechanistic explanation for the observed electrical patterns, and proposes some hypotheses about epileptic seizures that, if correct, could lead to better treatments for patients [conflict of interest warning: one of the authors is my second supervisor].

The pattern described is an electrical rhythm that rapidly increases in frequency over a time span of about one second, which seems to happen shortly before a seizure occurs. The electrical signal recorded from the patient’s brain rapidly increases in frequency; in our musical analogy, this electrical pattern is similar to the sound pattern produced when you rapidly slide your hand up the notes of a piano, from low to high. In music, this slide is called a glissando, and the authors adopted this name to describe the pattern of brain activity. This pattern was noticed in electrocorticogram (ECoG) signals – recordings made by placing electrodes directly on the surface of the brain, usually used before epilepsy surgery to give the surgical team information on the location of the small region of brain tissue that initiates seizures (the seizure focus). After surgery, the tissue removed from the seizure focus was kept alive and studied in the lab. Recordings from this removed brain tissue also displayed the glissando pattern of activity.

The mechanism proposed by the authors is complex and derives from a lot of the previous literature on the subject of brain rhythms in epilepsy (for a technical review, see this book). Much previous work on fast rhythms, as seen in glissandi, has pointed towards the importance of electrical connections, called gap junctions, between neurons as being crucial, rather than more conventional chemical synapses. Specifically, the proposed mechanism requires gap junctions to exist between the axons of excitatory neurons (the axon being the part of the neuron that transmits electrical signals to other neurons, which then receive these signals via chemical synapses). When a neuron sends a signal down its axon in the form of an electrical spike and the axon is connected to other axons by gap junctions, under some conditions the spike can be transmitted into these other axons, causing a wide spread of excitatory signals in the neuron network. This spread is fast, as the direct electrical connection of a gap junction transmits signals more rapidly than conventional chemical synapses. A proposed property of the gap junctions between axons is that their electrical resistance decreases the more alkaline their surroundings are*. As shown in the paper, this decrease in resistance allows even faster propagation of electrical spikes between axons, so when the alkalinity of the tissue increases, the frequency of the activity increases, creating the glissando effect.

Previous clinical reports have suggested that increased alkalinity can contribute to starting seizures in some cases, and this paper proposes a mechanism for how this alkalinisation could contribute. Further experiments are required to establish this proposed mechanism as correct, but if it is proved right, it opens up some interesting possibilities for treatment in some patients. If suitable monitoring equipment could be worn, glissandi could be used to predict seizures, and local brain alkalinity controlled in response. Alternatively, drugs acting on gap junctions between excitatory cell axons could be used – though the significance of axonal gap junctions in healthy brain function is unknown.

You can read the Newcastle University press release about this research here.

*other types of gap junction apparently increase in resistance under alkaline conditions

On mud and blog titles

I was away this past weekend doing Tough Mudder in Scotland. It was fun, but I could barely move afterwards. We ran on Saturday and I’m still aching on Tuesday. Then again, I am very unfit. I would recommend it if you fancy a nice long run but find the thought of a marathon tedious, or if you are a masochist.

I’ll have something to post on our wonderful EURO 2012 league soon, complete with analysis of the non-linear complex scoring function, but I still need to make some graphs. In the mean-time, here’s a little something about autapses:  Massive Autaptic Self-Innervation of GABAergic Neurons in Cat Visual Cortex. It’s an oldish paper quantifying the number of connections that different types of neurons make back onto themselves (background: most current brain theories consider the brain to generate and process information in networks of neurons, which communicate by sending electrical and chemical signals to each other – more here. In most of the brain, neurons can be divided into two categories, excitatory and inhibitory, depending on whether they send signals that make other neurons more or less likely to send on signals of their own). The authors found that, in cat visual cortex at least, inhibitory (GABAergic) neurons made substantially more self-connections than excitatory neurons, meaning that when they “spike” and send inhibitory signals to other neurons, they also inhibit their own spiking, thus stopping themselves from sending out more signals. This provides another mechanism for inhibitory neurons to control their output, in addition to the inhibition provided to them by the many connections from other inhibitory neurons in the network, that is separate from the inhibition provided by these other neurons.

I’m unaware of how much work has been done on the functional significance of autapses, but they are a rather interesting concept and usually ignored in the kind of neuronal network research that I am involved in. More digging required.

Networking with myself

These are the papers I referred to at Bright Club:

The Web of Human Sexual Contacts: this paper was published in Nature in 2001 (the link is to a preprint version). The authors analysed a 1996 Swedish survey of sexual behaviour (2810 respondents) and found that the number of sexual partners reported, both in the short term (12 months prior to survey) and long term (lifetime), varied according to a power law. This means that most people haven’t had that many sexual partners, a few people have had a few more, but a very small number of people have had very many partners; in the picture on the Wikipedia page (showing an idealised power law distribution), the x-axis would represent number of sexual partners, and the y-axis the cumulative distribution (i.e. as you go up the y-axis, you see more and more people having had a smaller number of partners). When plotted on a log-log scale (linked-to graph shows example simulated data), the curve becomes a straight line with a negative gradient – the gradient is the exponent of the power law. This kind of network is called scale-free, because whatever scale you consider the network at, its statistics are similar.

The small number of people with a very large number of connections to others are referred to as network ‘hubs’, analogous to a transport hub, as disparate parts of the network are linked up through them. Knowing the structure of a sexual network is very important for targeting effective interventions dealing with the spread of sexually transmitted infections, so this research has serious implications for public health policy. An important feature of scale-free networks is their resilience against random ‘node deletions’: removing a random person from the sexual network (I know what you’re thinking – no, not in any sinister way) will have very little effect on how disease spreads. However, by specifically targeting the network hubs, disease spread can be reduced dramatically just by influencing a small number of hub people, simultaneously reducing cost and improving efficacy. The trick is successfully identifying your hub nodes…

Hubs are also a frequent (though not defining) feature in small-world networks.

Sexual network analysis of a gonorrhoea outbreak: analysis of a gonorrhoea outbreak using network theory. The authors trace the initial spread to patrons frequenting a certain motel bar in Alberta, which they don’t actually name in the paper presumably for legal reasons. The main interesting findings were that cheaper network analysis methods could be used instead of standard case-control analysis to arrive at similar results, including the identification of the causal link between several seemingly isolated disease outbreaks.

Chains of Affection: analysis of a high-school “romance network”. This revealed a very different network structure, with long chains of links between students rather than clear hubs, with obviously different implications for STI spread through the network. The authors suggest the different structure arises from the social rules that operate at high-school: not dating your friend’s ex, for example.

Finally I used this lovely picture from the Human Connectome Project. Yes, your brain is riddled with STIs*.

*not really. Probably.

Signs of the Apocalypse

Well, Bright Club went pretty well I think, some people laughed at least once, plus I received some surprisingly enthusiastic support from the two heavy metal fans in the audience who enjoyed my Kreator t-shirt. I will put up something about the science behind my talk later when I have access to a more reliable internet connection. Everyone else was fabulous, plus I have now experienced the joys of Stephen Friz Frizzle, comedy songsmith extraordinaire. See him if you get the chance – his next gig is in Newcastle at Bar Loco on Sunday 1st July.

Skeptics in the Pub were ready for further geek comedy in the form of Helen Arney yesterday. Her arrival sparked scenes of apocalyptic devastation in Newcastle, an unexpected intense downpour and rather spectacular thunder and lightning managing to cripple the entire North East’s transport systems in the space of about twenty minutes. As such we had a somewhat smaller than expected turnout, but Helen was very relaxed about the whole thing and took the opportunity to try out some new material on us. Sounds like her Edinburgh show is going to be a corker. Attend.

I am currently heading back dahn sahth for the weekend, a day later than expected because of the biblical storms, and may pop along to the Henley regatta. I have never been, because it sounds horrific, but with enough Pimms it could be amusing. We shall see.

Newcastle Bright Club

IT’S TONIGHT, AND I’M SPEAKING! Wed 27th June 2012, 7.30pm at the Black Swan (on Westgate Road near the Academy), the “thinking person’s variety night” returns to bring you a fragrant blend of music, research and comedy.

We had a little rehearsal last night and I can tell you all now that you are in for a right good treat, as the other speakers at least are fabulous. Helen Keen returns to compère – she’s been helping us out with our sets, so to be honest you can blame her if you don’t enjoy it. I have to say, talking to a comedian about your own jokes is a strangely intimidating experience, even though she is both very nice and very helpful.

I’m going to be speaking about network science and the brain. It will be sexed-up to the point that Labour will want to use it to force through policy decisions if they ever manage to weasel back into power. Sod the football, come to Bright Club.

P.S. If you’re interested in either network science or the brain, or both, have a look at our lab’s web-site. These articles are good overviews of using network science to learn more about the brain:

Organization, development and function of complex brain networks

A tutorial in connectome analysis


Hey Simon [Sing(h)]

Back in March we did an open mic night at Newcastle Skeptics in the Pub as part of Newcastle Science Fest 2012. It produced some great talks ranging from cyborgs to exploding breasts, all from local speakers, and I suspect we’ll be holding another one in the future. I did a lovely song in honour of the Simon Singh vs. the British Chiropractic Association libel case. You may recognise the tune.

For more information on UK libel law failings, see the UK Libel Reform Campaign.

Some content

This is all new and fun, so while I’m gathering my thoughts for wonderfully exciting content, here’s a post I wrote a while ago for The 21st Floor.


Human Cloning Is Not Immoral

I promise I’m not just writing this for shock value, but with a title like that, I should explain exactly what I mean as it’s crucial to this argument. Moral issues are often separated into extrinsic and intrinsic concerns: extrinsic covering considerations about the consequences of an action, and intrinsic meaning the action is inherently wrong in itself. I agree that, currently, human cloning could be considered extrinsically immoral because of questions about the safety of the technique with regard to the clone, and I don’t intend to argue against that position. However, I have come across an assumption amongst many that human cloning is somehow intrinsically immoral – that creating humans other than by combining two people’s DNA is fundamentally wrong for some reason, and this is the assumption I want to address.

As with genetic modification (GM), intrinsic arguments against human cloning tend to centre around it being unnatural, and therefore bad – those particularly on the ball will recognize this as a form of the naturalistic fallacy. In the GM argument, GM proponents will often reply against this accusation of unnaturalness by remarking that genetic changes occur naturally, and that GM is not fundamentally different from, for example, selective breeding. While this is a position I agree with, it is not an ideal defense against the initial accusation as it leaves the assumption that unnatural=bad unaddressed; it has merely asserted that GM is, in fact, also natural. The assumption that what is natural is good and unnatural not good not only means creating artificial (or unnatural, if you prefer) boundaries to separate natural from unnatural, but also ascribes moral positions to nature, which cannot possibly be known. Cloning is, of course, not the natural way for humans to reproduce, but it effectively occurs whenever monozygotic twins are conceived. So, while some will argue that cloning is unnatural and others will reply that identical twins are nature’s clones, it does not actually matter, as the naturalness or otherwise is totally irrelevant to the morality.

The argument that humans should not “play god” is similar, in that it attributes desires to an entity that cannot possibly be known (except perhaps if you’re Phil Collins) – the god or gods may well be very happy that we’ve advanced technology to the point where human cloning has become a possibility just as much as they may be unhappy. This phrase is often used as an allusion to human hubris as well as literally, but in this sense it would sidle across into the extrinsic category – to beware the unforeseen consequences, as science fiction revels in reminding us – so cannot be regarded as a solid argument against the intrinsic morality of human cloning.

The purpose of creating the clone is a primary consideration given that it will be a sentient person just like any other. Bringing a human life into the world is a very serious matter, which should not be done without consideration for the created person. Creating a clone of oneself should not be treated differently from having a child in a conventional manner, then. Deciding to have a child is usually a selfish act; unless someone becomes pregnant accidentally and is compelled by their own or others’ morals to keep the baby (I suppose you could argue that’s selfish too if you really wanted, as they would be having the child so that they could feel better about themselves/not anger others/still get into heaven/etc.), then they have chosen to have a child because they want one, rather than for any consideration about the needs of others. Perhaps in some cases It’s A Bit More Complicated Than That, but the point is that having children is not immoral, even if you are only doing so for selfish reasons, so why should it be considered immoral to create a clone of yourself? Your clone would be your twin rather than your child per se; is it immoral for someone to create a sibling for themselves, but not for a parent to create a sibling for them?

Originally published at The 21st Floor