Magnet mistakes

This is just a short post on the many ways in which films and telly often get MRI wrong, and one thing that they tend to get right. Also, it is a good excuse to post a few interesting MRI videos.

1. The magnet is ALWAYS on. You don’t turn on an MRI. Nor do you turn it off. The machine uses a magnetic field which is always on as long as the machine is operational (whether scans are taken or not). This field can be pretty strong, and will trap ferrous metal objects in the bore, even if there is no scan running. Actually turning off the magnetic field (quenching it) is only done if the scanner is being decommissioned or in life-threatening situations, as puts it out of action for at least a week and cost a lot to restart (>£20,000), even if it has not been damaged by the quench.

2. Pressing the red button is usually bad news. There are two types of big red button. One is an emergency stop which does not turn off the magnet per se, but turns off power to consoles, lights (not emergency lights) and so on. The other quenches the magnet (rarely done, see the above point) and it looks like this:

The video above is a magnet being quenched at 1% helium capacity, which is to say that it is not nearly as big an event as it could be.

3. The magnet is as strong as it is. Variable field strength is not a thing. You cannot turn up the field, and you cannot turn it down.

4. Scans typically take time to acquire and interpret. If it was possible to put a person in and read out the data within seconds, that would be great. However, a good structural scan takes minutes, and a functional scan often even longer plus it requires additional processing steps that can take hours or days. There are also setup scans typically run before the main scan, and these also take time. It is unfortunately not plug and play. Caveat: real-time MRI is a thing, but it is mostly used for cardiac imaging and rare cases of functional MRI neurofeedback sequences. Typically, these are not the ones portrayed in the offending films.

5. Colours? Scans usually don’t come automatically in pretty colours. Structural scans are in more-or-less grainy black and white, and while functional scans can be presented in colour, this requires a lot of processing after the scan has been completed (see above). And what you get out is typically a statistical map of the signal, not the actual measurements themselves. In short: colours usually means lots of stats, stats usually means lots of time.

6. It’s noisy! And not simply high-tech whirr either: it can sound like a construction site in there.

7. There’s often a coil. At least with neuroimaging, where the coil is a cage-like structure placed around the head. This mistake can be forgiven if the scan in question would use a body coil, which can be pretty invisible and look like a part of the table.

There are plenty of films getting MRI wrong, for example Die Another Day (although the MRI bloopers are arguably not the biggest problem with that film) and Terminator Genisys that manage to get not only the turn it on and off again wrong, but also the variable field strength, plus introducing a conveniently appalling lack of shielding (meaning that the fringe field (the magnetic field that surrounds the magnet) is so large it reaches the control room). Go watch the Terminator clip over on youtube (from 1 min) to see for yourself. I feel for that poor MRI scanner.

+1. It’s strong. This is the one most get right. The magnetic field is strong – it will pull ferrous items into the bore of the magnet, wreck the item (and sometimes itself), and you’re probably not strong enough to stop it.

That being said, there are plenty of films where metal props are far too close to the magnet to be believable, and the ‘patients’ are allowed to keep on items of clothing such as underwired bras and watches, and even bring handbags or other personal items into the scan room. Even if such items are not ferrous, they can still cause image artefacts, and are typically removed. I’ve been told there is a Grey’s Anatomy episode where an MRI was requested for a patient with a fork stuck in the neck – the less said about that the better.



Following my list of resources for fresh neuroscientists, I figured I’d share something for those interested in exploring neuroscience but not quite ready to pick up a textbook, namely neurocomic.

Neurocomic is a Wellcome Trust supported project that aims to explain neuroscience ideas to a lay audience using comics. The brainchild of neuroscientists Hana Ros (UCL) and Matteo Farinella (who is also the artist), the story follows a man as he is trapped inside a brain and journeys to escape. The quest takes him through neuron forests, distinct brain regions and visual metaphors of common concepts in neuroscience and psychology, encountering various beasts and scientists along the way. Judging by its reviews, most people find it accessible and accurate, if a bit short (and short on women). Personally, I am particularly enthused by the medium.

The process and ideas behind the project are explained in the video below, and might be of interest to potential readers and to researchers considering tools for effective science communication.

Using illustrations to communicate science (or any information, really) can be powerful. I tend to draw quite a lot in my work, and find that visualising problems helps me work through them faster and see connections that might not be immediately apparent. It works great as a study method too (see this paper for example), helping students remember content better. As for communicating information, it is superb. I have a list of favourite science comics that have introduced me to new concepts more than once (I am particularly looking at you, xkcd, and your lovely comic explanation wiki). While three-panel strips rarely provide a full picture of a scientific concept, they can certainly offer a brief and memorable introduction. Similarly, neurocomic’s 150 pages are not enough to encompass the entire history and science of brain research, but it is a good place to start to get a flavour for some of the ideas in the field.

Neurocomic is on twitter @neurocomic

Resources for new neuroscientists

Analysis can be tricky at times, especially in neuroscience. Our business is one of maths and stats, and it can all be a bit complex, especially for those new to the field. Below is a short list of resources available to neuroscientists that may be useful when trying to make sense of the data:

1. The Q&A forum. There is a new resource in town for those new to neuroscience and stuck on some technical or analysis problem: It is a discussion forum where you can post your questions and (hopefully) get answers from the community. It has been open since December 2016, and from what I can tell, most questions posed on the forum has received at least one answer. It is not limited to any particular software library and it has a search function that can help you figure out if anyone has asked your question before. Whilst I have not used it myself (yet), it seems like a good resource.

2. The forum for (mostly) FSL. There is also FSL’s JISCmail site which works on the same principle as neurostars. As the name suggests, this is a discussion forum for FMRIB’s Software Library (FSL), but the topics span everything from the highly technical to basic model design, which means it could be useful for those favouring other software. As a FSL user, I’ve found this site immensely helpful whenever I’ve been stuck, and I can vouch for the quality of the answers on the forum. Records go back to 2001, making this a huge resource where you can be almost guaranteed to find the answer you need. However, make sure that the Q&A is not too old, as analysis tools do evolve.

3. The introduction to analysis. Finally, if you don’t really have a specific question, but rather would like an introduction to MRI analysis, I can thoroughly recommend Jeanette Mumford’s youtube channel, mumfordbrainstats. It’s clear and understandable, and it will make sure you understand what goes on under the bonnet of your analysis. She also created this nifty power calculator for fMRI – fmripower – which can give you a better indicator of power in your next experiment beyond “other people have used X subjects, so we’re going to go with that”. While it is not infallible in that it can only calculate power for a limited number of statistical tests, it is still a very useful starting point.

I’m willing to bet that at least one of the above will be able to help should you find that your analysis suddenly doesn’t work the way you expected it to.


How small is too small? MRI of tiny structures

MRI is great for imaging tissues and organs, as it does not involve any invasive procedures (such as drugs, radiation or even needles/scalpels). It allows us to quickly and safely get a good idea of what goes on under the skin. However, just as with a photo, it can become pixelated and useless, especially if you are looking at small structures. Imagine taking a holiday snapshot of a distant landmark, say, the Eiffel tower, but when you zoom in, it becomes hard to see what is tower and what is sky. Up close, the image is hard to interpret, and determining the exact size of the structure in the image may become impossible. In a pixelated image of the Eiffel tower, one pixel may contain both tower and sky, and you can’t tell where the exact line between the two goes. This is also the case with MRI.


The MRI image is divided into voxels (same as pixels, just three-dimensional – think of it as a set of tiny cubes making up the image). The quality of your image depends on the number of voxels and the signal from these. Too few voxels, not enough information. It would be like having just a few pixels covering the spire of the Eiffel tower – it won’t look good. One voxel covering a big chunk of the brain of a human participant won’t be very useful as there simply is not enough resolution to determine what’s what.

You can also have enough voxels but too little signal. Too little signal means not enough information. It would be like taking the photo without any light. In photography, light creates the image. If you have plenty of light, you can typically get more detail from each part of your image, and so your resolution can be better. Not enough signal means you need to keep your shutter open for longer, to let more light in. You can do that, but you probably need a tripod, and any movement (birds, people, wind, clouds, a bus rumbling past) will affect your picture and make it blurry. Same with MRI. You can increase signal by increasing scan time, but that’s not always possible and means you have to keep people still and in the scanner for longer.


Typically, the stronger your field strength, the more signal (light) you can get from your voxels. More signal means you can reduce voxel size as you will be getting more detail from each part of your scan. This typically results in better resolution. Or, you can get the same resolution, just faster (i.e. keep the shutter open for a shorter period). This can be useful if what you’re wanting to scan moves. For some tissues, it is invaluable to be able to get quick images. Imagine getting an image of a beating heart, for example. You need a quick scan sequence, and you typically need to do it several times over to get a nice, detailed image. That is the equivalent of taking lots of quick shots of the Eiffel tower (swaying in the wind, perhaps), and piecing them together to get all the fine details. This process of getting many snapshots of the same thing and taking the average to get a good image is very common in MRI, and it helps with a third issue: noise.

Everything you see in an MRI image is either signal, or it is noise. We call the relationship between signal and noise a signal-to-noise ratio (SNR), and we want it to be as high as possible (more signal, less noise). Noise in MRI images is usually caused by particles with an electrical charge moving around slightly in the human body, or by electrical resistance in the MRI machine itself. Together, these cause variations in signal intensity. Again, in our photo of the Eiffel tower, this is much the same: small visual distortions that gives it a grainy quality.


When we have smaller voxels, we typically get less signal and more noise per voxel (a low SNR). The way around it is to increase the number of averages that we run – i.e. take more snapshots, get a better image. Unfortunately, this takes time. Usually, then, we end up with a compromise of how good a resolution we want and how long we want the scanning to take, and this is greatly dependent on the kind of signal we can get.

The good news is that signal is, as mentioned earlier, grossly dependent on the field strength of our magnet. And we have some strong magnets available to us. For a human scan with a field strength of 3 Tesla (T), a resolution of 1mm x 1mm is easily obtained in about 5 minutes. That is fine for a structural scan of, say, a human brain. But what if you want to scan something smaller? Humans move, no matter how hard they try not to, even if it is only to draw breath. Higher resolutions means you’ll pick up on these small movements. A tiny motion can shift a small voxel completely out of place, while a bigger voxel would be less affected. In short, smaller makes things more difficult.

So, how small is too small?

For higher-field machines in humans, such as 7T, you can go small. 0.5mm x 0.5mm for 7T is easily doable, and some post mortem scans has gone down to 0.14mm x 0.14mm [1]. For our 9.4T scanner, we have scanned with resolutions of 0.03mm x 0.03mm (post mortem), and resolutions at 0.06mm x 0.06mm should be possible for scans that are not post mortem. That means with 9.4T, we can in theory image structures as small as 0.25mm across with some clarity (remember, you need to have at least a few voxels of the thing you want to image to properly see the edges and detail of it). Our scanner is too small for a whole human, but there exists 9.4T MRI machines for humans. And an 11.75T magnet is underway (see the BBC news story here), which will be able to get resolutions down to 0.1mm (or possibly more) in humans. So at present, anything less than 0.25mm is probably too small for MRI.

Smaller than that, and we have to use other methods. Microbiologists and their microscopes are likely to laugh in the face of 0.25mm. Below is a picture with a 9.4T image and histology image of testicular tissue [2], showing how much detail both techniques afford. Histology is obviously better. Sadly, however, it still requires scalpels, and MRI does not.


[1] Stucht D, Danishad KA, Schulze P, Godenschweger F, Zaitsev M, Speck O. Highest Resolution In Vivo Human Brain MRI Using Prospective Motion Correction. PLoS ONE. 2015;10(7):e0133921. Link:
[2] Herigstad MGranados-Aparici SPacey APaley MReynolds S. 

The wiring of DIN plugs

I get to do all sorts of practical stuff at work, some of which has nothing to do with physiology or imaging. One such thing is producing custom-made cables and plugs. Since I’ve had the pleasure of doing a fair few of these recently, I thought I’d put up a short how-to blog post on wiring up a DIN connector.

DIN stands for Deutsches Institut fur Normung, which translates to the German Institute for Standardisation. A DIN connector is, in short, a standardized connector, which come in a similar size. You may have seen them as they are often used for analog audio. The male DIN plug is typically 13.2 mm in diameter, and it often has a notch at the bottom to make sure the plug goes in the right way. Male plugs have a set of round pins, 1.45mm in diameter, that are equally spaced within the plug. The different types of DIN plugs have different numbers and configurations of pins. Below is an overview of some typical pin configurations.


There are, of course, variations over these themes, as well as specialized plugs with more than 10 pins. Pins on male connectors are numbered. The numbering goes from right to left, viewed from the outside of the connector with the pins upward and facing the viewer. The female counterparts are the inverse of the male plugs, and their numbering is from left to right. Usually, only corresponding male-female pairs work together, but you may be able to fit a 3-pin plug with a 5-pin 180 degree plug.

So how to attach a DIN plug to a cable? 

  1. Take the cable and snip off a few centimetres of plastic and remove padding. Snip off the insulation (about 1 cm) of the individual internal cables (cores). Slide the DIN metal sheet over the wire.
  2. Make sure that each core fits neatly into holes of DIN plug. This might mean cutting some of the wires. Move the unisolated wires (the ground) to one side.
  3.  Solder the core wires together and test that they still fit the holes in the plug.
  4. (Now comes the fiddly part). Add solder tin (a small amount is best) to the DIN plug holes, heat with the solder and push the tinned cores into holes. Remove solder iron and let the tin solidify (a few seconds only). Test that the solder holds by pulling firmly on the plug and cores. Attach the metal clamp around the cores (see second of figures below).
  5. Wrap the ground wires around the base of the metal clamp. Make sure the ground does NOT touch the cores. Test that there is no connection between wires and between wires and ground using a multimeter. Slide the metal sheet over the structure and plastic, and screw on the release catch where this overlays hole on metal clamp.


Reblog: The dreaded Q/A session

The Q/A session can be a daunting prospect, not only for the presenter but also for the audience members. Many of us have been in the position of having a question after a talk, but not quite daring to voice it. In a blog post over at The Female Scientist, immunologist Viki Male, suggests 7 steps to overcoming the fear of the Q/A and instead learn to use it to engage with the community and further your career goals. The post has some really good points – my favourite being “Let go of the idea that you have to ask “clever” questions. The most successful questions are usually the genuine ones.” It is worth a read.

How I Learned to Stop Worrying and Love Q&A Sessions!

The gender gap in asking questions is problematic because doing so is good for your career. Here are some tips on how to overcome your nerves and to get involved in Q&A sessions!

The evidence suggests that women ask fewer questions than men at conferences. It’s possible – indeed likely – that some of this effect can be accounted for by women being called on less often by the chair. But at least part of the problem is lacking the confidence to ask questions in front of an audience, and this seems to affect women more than men.

The gender gap in asking questions is problematic because doing so is good for your career. If you ask questions in departmental seminars, you will be noticed as an engaged scientist and good departmental citizen. This will be mentioned to your potential future employers and collaborators. When going up for internal awards, your engagement – or lack of it – will be noted and does influence your chance of success.


Academic spam bingo

I have had a particularly generous season of conference-spam, journal-spam and laboratory-salespitches-spam this autumn. My current spam folder contains gems such as:

  • “academicians”
  • “You can attend this event from your comfort zone.”
  • “I have contacted you regarding your precious manuscript submission”
  • “We have gone through one of your publications which contains valuable information that guides the future research allies.”
  • “We believe that our journal will get a very good reputation in scientific community with your valuable submission. “
  • “This journal would offer you an enriching experience and achieve great successful endeavors”
  • “A galaxy of 500+ International experts from 40+ countries will be there to share their knowledge and wisdom”

So here it is: academic spam bingo


Appreciation post: ‘junk’ labs

This is a simple appreciation post for junk labs in general and my junk lab in particular. A junk lab arises organically from research that regularly requires new, bespoke equipment with limited funding and a reasonable amount of technical know-how. If this new stuff is built from old stuff, that’s usually easiest. So it’s a lab with a cache of old bits and bobs, scavenged and re-purposed, amended and adjusted. And it looks like this.


Smoking in the scanner?

There is a new paper out in Scientific Reports, titled “Investigating the neural correlates of smoking: Feasibility and results of combining electronic cigarettes with fMRI”. This is a study that have managed to combine actual smoking with functional MRI (fMRI).

Most studies looking at brain processing of smoking run into trouble with MRI. This is because smoking and scanning do not go well together. Hospitals don’t allow smoking, things should generally not be on fire in the MRI scanner, and ventilation is an issue when you’re lying in a narrow bore. Because of this, we haven’t been able to properly look at the sensations and behaviour of smoking alongside the effects of nicotine (and other active products in cigarette smoke). This study tries to get around these practical problems and also look at the brain response to real-time smoking.

For the practical part, the study used e-cigarettes. E-cigarettes solve some of the problems with smoking in the scanner (fire and ventilation to some extent), but can cause image artifacts and may also contain metal. The paper shows how smaller types of e-cigarettes did not cause image artifacts plus were safe to use in the scanner from a metal point of view. E-cigarette smoking is a good mimic for traditional smoking, so this is a workable model of ‘the real thing’ that fits with MRI.

In terms of brain responses, the authors found activation in several brain regions associated with smoking e-cigarettes. These regions included motor cortex, insula, cingulate, amygdala, putamen, thalamus, globus pallidus and cerebellum. There were also (relative) deactivations in the ventral striatum and orbitofrontal cortex associated with smoking.


Image from the paper showing brain responses when participants were instructed to smoke. Red-yellow is activation and blue is deactivation.

Some of this activation is (unsurprisingly) linked to movement. The motor cortex activation (stronger on the left hand side, which correspond to right-hand side motion) is most likely due to movements associated with smoking. Similarly, cerebellar activation is often related to motion. Other regions are associated more with the effects of smoking. The putamen is part of a brain region called the striatum, which plays a role in reward and in supporting addiction. The ventral striatum (and orbitofrontal cortex) are associated with drug craving.

From a personal point of view, having worked a great deal with breathing, I am excited that the paper showed activation in the insula and cingulate. Both are structures involved in breathing and breathlessness tasks. However, without behavioural measures to link the findings to, it is hard to say what this activation means in this setting. It is important to remember that just because a similar activation pattern occurs with two different tasks, it doesn’t necessarily follow that the activation means the same. Each region of the brain typically handle more than one thing, particularly cortical regions.

The authors also found that activation patterns was similar both if the participants were told when to smoke and when to stop (first scan), and if they could smoke at will (second scan). However, in the second scan, the activation was weaker. The authors suggest that this could be because this task was more variable, meaning more between-subject variance and poorer timing (from a fMRI point of view). It could also be an order effect, as the subjects had more nicotine in their system in the second scan. This fits with lower activation in reward-related brain regions in the second scan. Or it could simply be because to smoke on command or whenever one wants to are different situations. Again, it is hard to tell why without other measures.

Nevertheless, this is an interesting paper, both from a methods point of view and for those interested in smoking processing and effects on the brain. It’s also written in a nice and easily accessible way. I’d recommend looking it up:

Reference: Matthew B. Wall, Alexander Mentink, Georgina Lyons, Oliwia S. Kowalczyk, Lysia Demetriou & Rexford D. Newbould. Investigating the neural correlates of smoking: Feasibility and results of combining electronic cigarettes with fMRI. Scientific Reports 7, Article number: 11352 (2017)
DOI: 10.1038/s41598-017-11872-z


I have been thinking about art lately. The University of Sheffield’s annual Festival of Academic Writing is coming up and I have just finished reviewing a few papers and grant applications. Mostly, this has made me consider how scientists can suffocate enthusiasm for even the most exciting finding in a single passive paragraph (never mind a whole string of them), and I may do a post about the horrors of the ‘academese’ language at a later stage. However, as the planning for next year’s Festival of the Mind is also underway, I wanted to write about something more positive: how art and science can work together.

Science and art to me are two sides of the same coin. Both aim to understand and describe the world, each in their own way. Science is the more objective of the two, but the way we gather and interpret data is without doubt influenced by our assumptions and world view. Art, on the other hand, challenges these assumptions, offers new ways of looking at the world. In short, science can answer our questions, but art may just help us ask the right ones. We need both to progress.

I  have a great deal of time for art barging into the halls of data and analysis (or for that matter, science picking up the brushes and the paint). Either way, it is a bold move, and the results could be equally impressive. As a prime example on how art and science can work together, watch this video by Jan Fröjdman, who has painstakingly pieced together still images of Mars (from the HiRISE camera) to generate a representation of a ‘live’ flight over the red planet. It is an absolutely stunning interpretation of data.

A FICTIVE FLIGHT ABOVE REAL MARS by Jan Fröjdman (see Vimeo for image credit).

Sheffield has a thriving art scene, and one that is not frightened of interacting with the sciences. The before-mentioned annual Festival of Academic Writing lets academics write creative pieces for the Journal of Imaginary Research and poke fun at the near-obligatory passive voice to their little hearts’ content. I very much enjoyed taking part last year and have just signed up for the upcoming November workshop. There are plenty of art installations throughout both the year and the city that communicate hot-off-the-press research to the public alongside more traditional science outreach events. The winter gardens is a frequently used venue and a good place to go for a bit of lateral thinking. There are artists who specialise in the communication of science and medicine, for example through the live-drawing of conferences, and who manage to reduce complex concepts to easily-interpreted visuals. And how about the live art-rock soundtrack to footage from the Hubble Telescope (plus three Georges Méliès films for good measure)? These are excellent ways of communicating science, as well as perhaps offering up new ways of looking at old questions.

Above are examples of Sheffield’s Art+Science scene (all images reproduced with permission). At the top left, there is Luke Jerram’s giant inflatable E. Coli hovering in the Winter Gardens, which surely had the potential to inspire both budding microbiologists and nightmares during KrebsFest 2015. Top right is artist Kate Sully‘s excellent work for The Journey of Reproductive Life from the University of Sheffield’s 2016 Festival of the Mind. The 2018 Festival is already being planned, with the involvement of animators, musicians, visual and digital artists, dancers and performers. Below Sully’s art is the cover of the Journal of Imaginary Research, vol 2 (2017), with work on volume 3 starting in November 2017 for publication in early 2018. Bottom left is a beautiful representation of signal in the ovary created by Isam Sharum, Felicity Tournant and Sofia Granados-Aparici (Ovary Research Group, 2015) – one of several pieces of science-inspired art within the University of Sheffield and one which I get to admire every morning.

Art has a lot to offer the sciences. Of course, if one want to take the mercenary view, a collaboration with the arts would probably fit the parameters for an impact case for the Research Excellence Framework. But aside from the REF, art can be used to communicate science, to inspire curiosity, to guide our questions and to make a whole generation dream of jet packs and rocket ships.