How your brain plans actions with different body parts

Got your hands full? – How the brain plans actions with different body parts

by Phyllis Mania

STEM editor: Francesca Farina

Imagine you’re carrying a laundry basket in your hand, dutifully pursuing your domestic tasks. You open the door with your knee, press the light switch with your elbow, and pick up a lost sock with your foot. Easy, right? Normally, we perform these kinds of goal-directed movements with our hands. Unsurprisingly, hands are also the most widely studied body part, or so-called effector, in research on action planning. We do know a fair bit about how the brain prepares movements with a hand (not to be confused with movement execution). You see something desirable, say, a chocolate bar, and that image goes from your retina to the visual cortex, which is roughly located at the back of your brain. At the same time, an estimate of where your hand is in space is generated in somatosensory cortex, which is located more frontally. Between these two areas sits an area called posterior parietal cortex (PPC), in an ideal position to bring these two pieces of information – the seen location of the chocolate bar and the felt location of your hand – together (for a detailed description of these so-called coordinate transformations see [1]). From here, the movement plan is sent to primary motor cortex, which directly controls movement execution through the spinal cord. What’s interesting about motor cortex is that it is organised like a map of the body, so the muscles that are next to each other on the “outside” are also controlled by neuronal populations that are next to each other on the “inside”. Put simply, there is a small patch of brain for each body part we have, a phenomenon known as the motor homunculus [2].


Photo of an EEG, by Gabriele Fischer-Mania

As we all know from everyday experience, it is pretty simple to use a body part other than the hand to perform a purposeful action. But the findings from studies investigating movement planning with different effectors are not clear-cut. Usually, the paradigm used in this kind of research works as follows: The participants look at a centrally presented fixation mark and rest their hand in front of the body midline. Next, a dot indicating the movement goal is presented to the left or right of fixation. The colour of the dot tells the participants, whether they have to use their hand or their eyes to move towards the dot. Only when the fixation mark disappears, the participants are allowed to perform the movement with the desired effector. The delay between the presentation of the goal and the actual movement is important, because muscle activity affects the signal that is measured from the brain (and not in a good way). The subsequent analyses usually focus on this delay period, as the signal emerging throughout is thought to reflect movement preparation. Many studies assessing the activity preceding eye and hand movements have suggested that PPC is organised in an effector-specific manner, with different sub-regions representing different body parts [3]. Other studies report contradicting results, with overlapping activity for hand and eye [4].


EEG photo, as before.

But here’s the thing: We cannot stare at a door until it finally opens itself and I imagine picking up that lost piece of laundry with my eye to be rather uncomfortable. Put more scientifically, hands and eyes are functionally different. Whereas we use our hands to interact with the environment, our eyes are a key player in perception. This is why my supervisor came up with the idea to compare hands and feet, as virtually all goal-directed actions we typically perform using our hands can also be performed with our feet (e.g., see for mouth and foot painting artists). Surprisingly, it turned out that the portion of PPC that was previously thought to be exclusively dedicated to hand movement planning showed virtually the same fMRI activation during foot movement planning [5]. That is, the brain does not seem to differentiate between the two limbs in PPC. Wait, the brain? Whereas fMRI is useful to show us where in the brain something is happening, it does not tell us much about what exactly is going on in neuronal populations. Here, the high temporal resolution of EEG allows for a more detailed investigation of brain activity. During my PhD, I used EEG to look at hands and feet from different angles (literally – I looked at a lot of feet). One way to quantify possible effects is to analyse the signal in the frequency domain. Different cognitive functions have been associated with power changes in different frequency bands. Based on a study that found eye and hand movement planning to be encoded in different frequencies [6], my project focused on identifying a similar effect for foot movements.


Source: Pixabay

This is not as straightforward as it might sound, because there are a number of things that need to be controlled for: To make a comparison between the two limbs as valid as possible, movements should start from a similar position and end at the same spot. And to avoid expectancy effects, movements with both limbs should alternate randomly. As you can imagine, it is quite challenging to find a comfortable position to complete this task (most participants did still talk to me after the experiment, though). Another important thing to keep in mind is the fact that foot movements are somewhat more sluggish than hand movements, owing to physical differences between the limbs. This circumstance can be accounted for by performing different types of movements; some easy, some difficult. When the presented movement goal is rather big, it’s easier to hit than when it’s smaller. Unsurprisingly, movements to easy targets are faster than movements to difficult targets, an effect that has long been known for the hand [7] but had not been shown for the foot yet. Even though this effect is obviously observed during movement execution, it has been shown to already arise during movement planning [8].

So, taking a closer look at actual movements can also tell us a fair bit about the underlying planning processes. In my case, “looking closer” meant recording hand and foot movements using infrared lights, a procedure called motion capture. Basically the same method is used to create the characters in movies like Avatar and the Hobbit, but rather than making fancy films I used the trajectories to extract kinematic measures like velocity and acceleration. Again, it turned out that hands and feet have more in common than it may seem at first sight. And it makes sense – as we evolved from quadrupeds (i.e., mammals walking on all fours) to bipeds (walking on two feet), the neural pathways that used to control locomotion with all fours likely evolved into the system now controlling skilled hand movements [9].

What’s most fascinating to me is the incredible speed and flexibility with which all of this happens. We hardly ever give a thought to the seemingly simple actions we perform every minute (and it’s useful not to, otherwise we’d probably stand rooted to the spot). Our brain is able to take in such a vast amount of information – visually, auditory, somatosensory – filter it effectively and generate motor commands in the range of milliseconds. And we haven’t even found out a fraction of how all of it works. Or to use a famous quote [10]: “If the human brain were so simple that we could understand it, we would be so simple that we couldn’t.”

 [1] Batista, A. (2002). Inner space: Reference frames. Current Biology, 12(11), R380-R383.

[2] Penfield, W., & Boldrey, E. (1937). Somatic motor and sensory representation in the cerebral cortex of man as studied by electrical stimulation. Brain, 60(4), 389-443.

[3] Connolly, J. D., Andersen, R. A., & Goodale, M. A. (2003). FMRI evidence for a ‘parietal reach region’ in the human brain. Experimental Brain Research153(2), 140-145.

[4] Beurze, S. M., Lange, F. P. de, Toni, I., & Medendorp, W. P. (2009). Spatial and Effector Processing in the Human Parietofrontal Network for Reaches and Saccades. Journal of Neurophysiology, 101(6), 3053–3062

[5] Heed, T., Beurze, S. M., Toni, I., Röder, B., & Medendorp, W. P. (2011). Functional rather than effector-specific organization of human posterior parietal cortex. The Journal of Neuroscience31(8), 3066-3076.

[6] Van Der Werf, J., Jensen, O., Fries, P., & Medendorp, W. P. (2010). Neuronal synchronization in human posterior parietal cortex during reach planning. Journal of Neuroscience30(4), 1402-1412.

[7] Fitts, P. M. (1954). The information capacity of the human motor system in controlling the amplitude of movement. Journal of experimental psychology47(6), 381.

[8] Bertucco, M., Cesari, P., & Latash, M. L. (2013). Fitts’ Law in early postural adjustments. Neuroscience231, 61-69.

[9] Georgopoulos, A. P., & Grillner, S. (1989). Visuomotor coordination in reaching and locomotion. Science, 245(4923), 1209–1210.

[10] Pugh, Edward M, quoted in George Pugh (1977). The Biological Origin of Human Values.



Space weather – predicting the future

by Aoife McCloskey

Early Weather Prediction

Weather is a topic that humans have been fascinated by for centuries and, dating back to the earliest civilisations ’till the present day, we have been trying to predict it. In the beginning, using the appearance of clouds or observing recurring astronomical events, humans were able to better predict seasonal changes and weather patterns. This was, of course, motivated by reasons of practicality such as agriculture or knowing when the best conditions to travel were, but additionally it stemmed from the innate human desire to develop a better understanding of the world around us.

Weather prediction has come a long way from it’s primordial beginning, and with the exponential growth of technological capabilities in the past century we are now able to model conditions in the Earth’s atmosphere with unprecedented precision. However, until the late 1800’s, we had been blissfully unaware that weather is not confined solely to our planet, but also exists in space.

Weather in Space

Weather, in this context, refers to the changing conditions in the Solar System and can affect not only our planet, but other solar system planets too. But what is the source of this weather in space? The answer is the biggest object in our solar system, the Sun. Our humble, middle-aged star is the reason we are here at all in the first place and has been our reliable source of energy for the past 4.6 billion years.

However, the Sun is not as stable or dependable as we perceive it to be. The Sun is in fact a very dynamic object, made up of extremely high temperature gases (also known as plasma). Just like the Earth, the Sun also generates its own magnetic field, albeit on a much larger scale than our planet. This combination of strong magnetic fields, and the fact that the Sun is not a solid body, leads to the build up of energy and, consequently, energy release. This energy release is what is known as a solar flare, simply put it is an explosion in the atmosphere of the Sun that produces extremely high-energy radiation and spits out particles that can travel at near-light speeds into the surrounding interplanetary space.

The Sun: Friend or Foe?

Sounds dangerous, right? Well yes, if you were an astronaut floating around in space, beyond the protection of the Earth, you would find yourself in a very undesirable position if a solar flare were to happen at the same time. For us here on Earth, the story is a bit different when it comes to being hit with the by-products of a solar flare. As I said earlier, our planet Earth produces its very own magnetic field, similar to that of a bar magnet. For those who chose to study science at secondary school, I’m sure you may recall the lead shavings and magnet experiment. Well, that’s pretty much what our magnetic field looks like, and luckily for us it acts as a protective shield against the high-energy particles that come hurtling our way on a regular basis from the Sun. One of the most well-known phenomena caused by the Sun is actually the Aurora Borealis, i.e., the northern lights (or southern lights depending on the hemisphere of the world you live).


Picture of the Aurora Borealis, taken during Aoife’s trip to Iceland in January 2016.

This phenomenon has been happening for millennia, yet until recent centuries we didn’t really understand why. What we know now is that the aurorae are caused by high-energy particles from the Sun colliding with our magnetic field, spiralling along the field lines and making contact with our atmosphere at both the north and south magnetic poles. While the aurorae are actually a favourable effect of space weather, as they are astonishingly beautiful to watch and photograph, there are unfortunately some negative effects too. These effects here on Earth range from satellite damage (GPS in particular), to radio communication blackout, to the more extreme case of electrical grid failure. Other effects are illustrated in the image below:

My PhD – Space Weather Forecasting

So, how do we predict when there is an event on the Sun that could have negative impacts here on Earth? Science, of course! In particular, in the area of Solar Physics there has been increasing focus on understanding the physical processes that lead to space weather phenomena and trying to find the best methods to predict when something such as a solar flare might occur.

It is well known that one should not directly view the Sun with the naked eye, therefore traditionally the image of the Sun was projected onto pieces of paper. Using this method, one of the first features observed on the Sun were large, dark spots that are now known as sunspots. These fascinated astronomers for quite some time and there is an extensive record of sunspots kept since the early 1800’s. These sunspots were initially traced by hand, on a daily basis, until photographic plates were invented and this practice became redundant. After many decades of recording these spots there appeared to be a pattern emerging, corresponding to a roughly 11-year cycle, where the number of spots would increase to a maximum and gradually decrease again. It was shown that this 11-year cycle was correlated with the level of solar activity, in other words the number of solar flares and how much energy they release can also be seen to follow this pattern.


Sunspot drawing by Richard Carrington, 01 September 1859

Leading on from this, it is clear that there exists a relationship between sunspots and solar flares, so logically they are the place to start when trying to forecast. My PhD project focuses on sunspots and how they evolve to produce flares. For a long time, sunspots have been classified according to their appearance. One of the most famous classification schemes was developed by Patrick McIntosh and has been used widely by the community to group sunspots by their size, symmetry and compactness (how closely packed are the spots) [1]. Generally, the biggest, baddest and ugliest groups of sunspots produce the most energetic, and potentially hazardous, flares. Our most recent work has been studying data from past solar cycles (1988-2010) and looking at how the evolution of these sunspot groups relates to the flares they produce [2]. I found that those that increase in size produce more flares than those that decrease in size. This has been something that has been postulated before in the past, and additionally it helps to answer an open question in the community as to whether sunspots produce more flares when they increase in size (grow) or when they decrease in size (decay). Using these results, I am now implementing a new way to predict the likelihood of a sunspot group to produce flares and additionally the magnitude of those flares.


Space weather is a topic that is now, more than ever, of great importance to our technology-dependent society. That is not to say that there will definitely be any catastrophic event in the near-future, but it is certainly a potential hazard that needs to be addressed on a global scale. In recent years there has been some significant investment in space weather prediction, with countries such as the UK and the U.S. both establishing dedicated space weather forecasting services. Here in Ireland, our research group at Trinity College has been working on improving the understanding of and prediction of space weather for the past ten years. I hope, in the near future, space weather forecasting will reach the same level of importance as the daily weather forecast, but for now – watch this space.

  1. McIntosh, Patrick S (1990), ‘The Classification of Sunspots’,  Solar Physics, p.251-267.
  2. McCloskey, Aoife (2016), ‘Flaring Rates and the Evolution of Sunspot Group McIntosh Classifications’, Solar Physics, p.1711-1738.

Maths: the same in every country?

by Rose Cook, PhD candidate at the Institute of Education, University College London.

Think women aren’t good at maths? Depends on where you’re a woman. 


(We never miss a chance to quote Mean Girls here at Women Are Boring)

Do you know the difference between Celsius and Fahrenheit? Can you interpret information from line graphs in news articles? Calculate how many wind turbines would be needed to produce a certain amount of energy (given the relevant information)?

These may seem like basic tasks, but if you are a woman living in the UK, Germany or Norway, the chances are you would struggle with them more than a comparable man. If you live in Poland, however, you might even outperform a male counterpart.

Why this variation in skills, and why does it appear in some countries and not others?

For some, these findings, from the 2011 international survey of adult skills, run by the OECD,  will confirm their existing beliefs. In spite of women being more academically successful than men, the perception that ‘women can’t do maths’ is widely held. A recent experiment [1] showed that both genders believe this to be true: both male and female subjects were more likely to select men to perform a mathematical task that, objectively, both genders fulfil equally well. In her successful book ‘The Female Brain’, Louann Brinzedine argued that women are ‘hard wired’ for communication and emotional connection, while men’s brains are oriented towards achievement, solitary work and analytical pursuits.

Another camp of social scientists argue that such narratives misrepresent the facts.  Janet Shibley Hyde and colleagues insist that, at least in the United States, men and women’s cognitive abilities are characterised by similarity rather than difference. Reviewing findings across many studies of gender differences on standardised mathematics tests, these authors found that ‘even for difficult items requiring substantial depth of knowledge, gender differences were still quite small’[2].

The fact that gender differences show up on an international survey of numeracy skills is a puzzling addition to an already contentious picture. Of course, not all maths tests are created equal. The difference may in some way reflect the way the survey conceptualises skills. Distinct from mathematical ability, applied numeracy skills are described as:

‘the ability to use, apply, interpret, and communicate mathematical information and ideas’.[3]

Crucially, individuals who are ‘numerate’ should be able to apply these abilities to situations in everyday life. Perhaps these ‘everyday’ maths skills are more biased by gender than the measures used in other studies?

Numeracy: the ‘new literacy

I argue that we should take these gender differences seriously. More and more, jobs now require numeracy skills, both to perform basic tasks and to support ICT skills. Outside work, numeracy skills are increasingly required to make sense of the world around us. They help us to grasp concepts such as interest rates and inflation, which help us to deal with money. Moreover, according to the British Academy,

‘the ability to understand and interpret data is an essential feature of life in the 21st century: vital for the economy, for our society and for us as individuals. The ubiquity of statistics makes it vital that citizens, scientists and policy makers are fluent with numbers’.

The importance of numeracy has been recognised recently in the UK with the establishment of an All-Party Parliamentary Group for Maths and Numeracy, the National Numeracy charity, and initiatives such as Citizen Maths.

International variation

Particularly curious is the large variation across countries in the size of the gender difference. Figure 1, below, shows that, among adults aged between 16 and 65, the male advantage in applied numeracy skills is particularly large in Germany, the Netherlands and Norway, while it is virtually non-existent in Poland and Slovakia. The graph shows raw differences in average skill scores; although gaps reduce somewhat when controlling for age, family and immigration background and education, they remain.

Figure 1: Mean numeracy skills by gender, International Survey of Adult Skills, 2012


Source: Author’s calculations using data from the OECD Survey of Adult Skills (PIAAC). Survey and replicate weights are applied. Numeracy scores range from zero to 500. For more information on the survey, please see:

Any genetic component is unlikely to vary internationally [4], suggesting a substantial role for cultural, institutional or economic factors that vary across countries.

My PhD study

Given that the survey tests adults who have many experiences behind them, isolating the causes of gender differences and cross-country variation is far from simple. We are socialised into gendered preferences, motivations and skills from our earliest years [5]. We go on to make gendered choices in our educational lives, our careers and our leisure activities. All of these life domains contribute to the skills we end up with in adulthood. To some, a choice-based explanation is unproblematic; determining one’s own destiny is a core value in many contemporary societies. However, this side-steps the question of where preferences come from. Skill differences in adulthood may well reflect individuals’ choices; however, the choices themselves are likely to be influenced by a complex mixture of cultural, educational, economic and institutional factors; which vary in their salience across countries.

In my PhD study, I focus on education and labour market explanations. A key task for my research is disentangling why gender differences in numeracy skills are relatively large in countries typically considered ‘gender egalitarian’. For example, Scandinavian countries consistently top the rankings of  the World Economic Forum’s Global Gender Gap Report, and are held up as bastions of gender equality. Yet Norway, Sweden and Denmark show among the largest gender differences in adults’ applied numeracy skills. Poland, Slovakia and Spain are not known for being particularly progressive on gender equality, yet they show among the smallest differences.

School and skills

One possibility is that gender differences arise from what girls and boys are exposed to while they are at school. Despite a similar basic structure, education systems across the world differ in the extent to which subjects are optional or compulsory. For example, in the UK, mathematics was not compulsory in upper secondary education until recently; whereas in other countries this has long been the case. Where numerate subjects are not compulsory, they may be less valued, and this could have created more scope for gender to affect subject and career choices. There is also wide variation in the types of mathematics learning boys and girls are exposed to across countries, as well as between schools and classes within countries.

Work and skills

Another possibility is that differences in skills are related to the types of jobs that women and men pursue once they leave education. In the majority of countries in the study, occupational segregation is still widespread in spite of female’s superior performance in education, and is partly to blame for the continuing gender pay gap.  Gender occupational segregation is particularly rife in Scandinavian countries, although this has been improving in recent years [6]. Countries with strong gender segregation in jobs promote gender norms about what careers are appropriate and accessible for men and women. This is likely to drive the early choices that contribute to skills in adulthood. In contrast, in some countries gender segregation of jobs is less pronounced, which may set more egalitarian norms for skill development. Moreover, given the link between more demanding, highly skilled jobs and skill development in adulthood, concentration into lower paid, more routine jobs could affect the extent to which women are able to gain skills at work. In some countries’ labour markets, women may perceive weaker incentives to develop mathematical skills than their male counterparts, preferring more typically ‘feminine’ ones, such as communication and literacy skills.

In my view, skills gaps are among the hurdles we need to overcome in order to attain full economic equality between men and women. Using international comparisons, my research aims to locate gender differences in applied numeracy skills within a broader, institutional context.  This is important both to correct the assumption that differences are ‘fundamental’ or ‘natural’, and to design effectively-targeted policies to equalise skills. I use a variety of quantitative techniques in my research which isolate factors associated with gender differences at both the individual and country levels. This should broaden the discussion beyond the common focus on encouraging girls to make gender ‘atypical’ choices in education, which neglects both males and the broader social context in which skill differences develop. Moreover, while there is a large amount of research on gender and education, skills inequalities among adults are less often addressed. Yet they affect adults’ lives in profound ways [7]. I hope to show some of the ways in which skill differences among adults are not fixed by early experiences and biology, but malleable according to social context.


[1] Reuben, E., Sapienza, P. and Zingales, L. (2014). ‘How stereotypes impair women’s careers in science.’ Proceedings of the National Academy of Sciences, 111 (12), 4403-4408.

[2] Hyde, Janet S., et al. (2008) Gender similarities characterize math performance. Science 321 (5888) pp. 494-495 (p.495)

[3] OECD (2013) PIAAC Numeracy: A conceptual framework (p. 20) Paris: OECD.[4]

[4] Penner, A.M. (2008) Gender differences in extreme mathematical achievement: An international perspective on biological, social, and societal factors. American Journal of Sociology 114 (supplement) S138–S170.

[5] Maccoby, E. E., and D’Andrade, R. G. (1966) The development of sex differences. Stanford University Press.

[6] Bettio F and Verashchagina A (2009) Gender Segregation in the Labour Market: Root Causes, Implications and Policy Responses in the EU. Brussels: European Commission.

[7] Carpentieri, J. C., Lister, J., Frumkin, L., & Carpentieri, J. (2010). Adult numeracy: a review of research. London: NRDC.

Detecting Parkinson’s Disease with your mobile phone


by Reham Badaway, in collaboration with Dr. Max Little.

So, what if I told you that in your pocket right now, you have a device that may be able to detect for the symptoms of a brain disease called Parkinson’s, much earlier than doctors themselves can detect for the disease? I’ll give you a minute to empty out the contents of your pockets. Have you guessed what it is? It’s your smartphone! Not only can your trusty smartphone keep you in touch with family and friends, or help you look busy at a party that you know no-one at, it can also detect for the very early symptoms of a debilitating disease. One more reason to love your smartphone!

What is Parkinson’s disease?

So, what is Parkinson’s disease (PD)? PD is a brain disease which significantly restricts movement. Some of the symptoms of PD include slowness of movement, trembling of the hands and legs, the resistance of the muscles to movement, and loss of balance. All of these movement problems (symptoms) are extremely debilitating and affect the quality of life for those diagnosed with the disease. Unfortunately, it is only in the late stages of the disease, i.e. when the symptoms of the disease are extremely apparent, that doctors can confidently detect PD. There is currently no cure for the disease. Detecting the disease early on can help us find a cure, or find medicines that aim to slow down disease progression. Thus, methods that can detect PD before doctors themselves can detect for the disease, i.e. in the early stages of the disease, are pivotal.

Smartphone sensing

So, how can we go about detecting the disease early on in a non-invasive, cheap and easily accessible manner? Well, we believe that smartphones are the solution. Smartphones come equipped with a large variety of sensors to enhance your experience with your smartphone (Fig 1). Over the last few years, abnormal characteristics in the walking pattern of individuals with PD have been successfully detected using a smartphone sensor known as an accelerometer. Accelerometers can detect movement with high precision at very low cost, making them perfect for wide-scale application.


Fig 1: Sensors, satellites and radio frequency in Smartphones

Detecting Parkinson’s disease before symptoms arise

Interestingly, subtle movement problems have been reported in individuals with a high risk of developing PD using sensors similar to those found in smartphones, specifically when given a difficult activity to do such as walking while counting backwards. Individuals at risk of developing the disease are individuals who are expected to develop the disease in the later stages of their life due to say a genetic mutation, but have not yet developed the key symptoms required for PD diagnosis. The presence of subtle movement problems in individuals with a high risk of developing PD indicates that the symptoms of PD exist in the early stages of the disease progression, just subtly. Unfortunately, these subtle movement problems are so subtle that individuals at risk of developing PD, as well as doctors, cannot detect them – so we must go looking for them. It is crucial that we can screen individuals for these subtle movement problems if we are to detect the disease in the early stages. The ability of smartphone sensors to detect the subtle movement problems in the early stages of PD has not yet been investigated. Using smartphones as a screening tool for detecting PD early on will mean a more widely accessible and cost-effective screening method.

Our solution to the problem

We aim to distinguish individuals at risk of developing PD from risk-free individuals by analysing their walking pattern measured using a smartphone accelerometer.

How does it work?

So, how would it work? Users download a smartphone app, in which they are instructed to place their smartphone in their pocket and walk in a straight line for 30 seconds. During these 30 seconds, a smartphone accelerometer records the user’s walking pattern (Fig 2).


Fig 2: Smartphone records user walking

The data collected from the accelerometer is then downloaded on to a computer so we can examine the presence of subtle movement problems in an individual’s walking pattern. However, to ensure that the subtle movement problems that we observe in an individual’s walking pattern is due to PD, we aim to simulate the user’s walking pattern via modelling the underlying mechanisms that occur in the brain during PD. If the simulated walking pattern matches the walking pattern collected from the user’s smartphone (Fig 3), we can look back at our model of the basal ganglia (BG)- an area in the brain often associated with PD – to see if it is predictive of PD.




If it is predictive of PD, and we observe subtle movement problems in the user’s walking pattern, we can classify an individual as being at risk of developing PD. Thus, an individual’s health status will be based on a plausible link between their physical and biological characteristics. In cases in which the biological and physical evidence do not stack up, for example when we observe subtle movement problems in an individual’s walking pattern but the information drawn from the BG is not indicating PD, we can dismiss the results in order to prevent a misdiagnosis. A misdiagnosis can have a significant impact on an individual’s health and psychology. Thus, it is pivotal that the methods that we build allow us to identify scenarios in which the model is not capable of accurately predicting an individual’s health status, a problem which a lot of current techniques in the field lack.

To simulate the user’s walking pattern, we aim to mathematically model the BG and use it as input into another mathematical model of the mechanics of human walking. The BG model consists of many variables to make it work. To find the values for the different variables of the BG model such that it simulates the user’s walking pattern, we will use a statistical technique known as Approximate Bayesian Computation (ABC). ABC works by running many simulations of the BG model until it simulates a walking pattern that is a close match to the user’s walking pattern.

Ultimately our approach aims to provide insight into an individual’s brain deterioration through their walking pattern, measured using smartphone accelerometers, in order to know how their health is changing.


As well as identifying those at risk of developing PD from healthy individuals, our approach provides the following benefits:

  • Providing insight into how the disease affects movement both before and after diagnosis.
  • Identifying disease severity in order to decide on the right dosage of medication for patients.
  • Tracking the effect of drugs on symptom severity for PD patients and those at risk.


Apple recently launched ResearchKit, which is a collection of smartphone applications that aims to monitor an individual’s health. Companies such as Apple are realising the potential of smartphones to screen for diseases. The ability to monitor patients long-term, in a non-invasive manner, through smartphones is promising, and can provide a more accurate picture of an individual’s health.

Advances in smartphone sensing are likely to have a substantial impact in many areas of our lives. However, how far can we go with monitoring people without jeopardizing their privacy? How do we prevent the leakage of sensitive information collected from millions of people? The growing evolution of sensor-enabled smartphones presents innovative opportunities for mobile sensing research, but it comes with many challenges that need to be addressed.

L’Oreal-UNESCO For Women in Science Awards

By: Grace McDermott, Co-Founder of Women Are Boring.

The Awards:

Last week, Women Are Boring had the honour of attending the L’Oreal-UNESCO Women in Science Awards. We had the chance to meet and learn about some of the women carrying out ground-breaking scientific research work in Ireland and the UK.

Approximately 30% of researchers in the world are women*, a statistic which is notoriously lower for women in the Sciences, Technology, Engineering and Math (STEM). Women comprise  a mere 15% of the UK STEM workforce, and to this day only 3% of all Nobel prizes in the sciences have been awarded women. As such, it is no surprise that a recent study showed that some 23% of current female science students in the UK “won’t” or “aren’t sure” whether they will pursue a career in science.

The L’Oreal Women in Science Programme “recognizes the achievements and contributions of exceptional females across the globe, by awarding promising scientists with Fellowships to help further their research.” Founded eighteen years ago, on the premise that ‘the world needs science and science needs women’ over 2000 women from across the globe have been recognised  and received funding to further their research. 

Despite an uphill battle for female STEM researchers across the globe, this year’s awards saw a record number of applications, a feat which proves that female scientists are not going away anytime soon. Out of 400 applications, 40 were longlisted and 8 academics made it to the final nomination list, a selection that L’Oreal’s Scientific Director, Steve Shiel called “ impossibly difficult”. The 8  nominated candidates included female mathematicians, chemists, paleo-biologists, nuclear physicists and the list goes on. In the end, five fellowships were awarded. 

There were two things about the awards that really stood out as newsworthy. Firstly, it was the importance of the research the nominees presented, and the simultaneous significance of presenting such work to audiences who would have otherwise never engaged with it. Secondly, it was the urgent need for a reexamination of what the research community and its supporters, consider valid research costs.


All of these women were impressive in their own right, taking on major issues that range from curing diseases, to perfecting wastewater treatments, or challenging accepted conceptions about how star clusters form. Shiel stated

“It’s hard to compare the work of paleobiologists to a medicinal scientist’s work but one thing was evident about all of the winners, and it was that they each had passion. They each had a palpable passion you could feel for what they did, but also this sense of curiosity and discovery.”

The importance of communication: 

Like any award ceremony, there was no shortage of deserving candidates, many of whom we intend to feature in the upcoming months, but one of the projects that stood out for us was Reham Bedawy, a short-listed PhD nominee who was working to support the early detection of Parkinson’s via a mobile phone app. If helping to diagnose life-threatening illness wasn’t enough, she was also able to clearly explain the operationalisation of her work and a seemingly complex disease to two social-science researchers (i.e. us!) who wouldn’t know the right end of a beaker. Her work is inarguably significant, regardless of whether or not a non-expert audience could understand it, but as a result of her interesting and translatable presentation, at least two new researchers who may have otherwise been completely unaware of Parkinson’s research, are now engaged and eager to learn more (follow Reham on Twitter here).

As a media researcher, I was surprised to find how much in common I had with a mathematician. As a large portion of my work focuses on the role of social media in revolutionary movements, I could draw parallels with some of the techno-focused aspects of her methodology. She made me consider how I may better leverage mobile apps for my own work, and above all she inspired me. Her presentation, like so many of the researchers’ presentations, exemplified the significance of not only individual female academics, but the power and influence of the collective. A room full of intelligent, motivated and successful women is something that is seldom seen and far less celebrated. As an aspiring academic, the presence and recognition of these accomplished women helped reignite my own confidence, and motivation to carry on with my work.

It made me think about what the world might look like if these women were splashed across our news headlines, Twitter feeds, or history books?

We need to redefine “direct research” costs:

Aside from inspiration, the awards led to a realization: supporting female academic achievement requires a redefinition of “direct research costs”. What we found particularly noteworthy about the awards was the fact that the winners were allowed to dictate the way in which there awards would be spent, sometimes in ways which are seemingly unconventional in the research community. Many of the past laureates spoke about the importance of using the awards to help facilitate childcare and family relocation to areas or institutions, which were crucial to the development of their work. Moreover, several nominees were pregnant, or brought their young children with them to the awards.

While all funding aimed at supporting equality in research is important, the seemingly non-direct costs of research careers are sometimes the most expensive and difficult to articulate. As such, the importance of funding opportunities which give female academics the power to control the use of their grants presents an equalizing potential that traditional research grants do not. The testimonies of an overwhelming number of past laureates attested to this.

Often, when we speak about female academic achievement the topic of motherhood is ignored. As the notion of motherhood so often consumes, and even stifles the narrative of women in the workplace, I often find myself intentionally discussing the achievements of female academics, or female professionals as an entirely separate entity from their roles as mothers or caretakers.  But these awards brought to the fore the importance of recognizing and funding female academics not only via direct research grants, but also by way of flexible and family-centric support. A recent article in the New York Times upheld this, finding that even seemingly gender-neutral family-friendly policies in many academic institutions tend to favor male academics.

These testimonies leave many open-ended questions, but highlight the need for a continued conversation on the meaning of gender equality and the importance of building female equity in the research space.

What is clear is that female academics experience a different professional reality than their male-counterparts. The awards, and each of the nominated women exemplified the importance of advocacy, not only in the context of each of our individual research work, but also in terms of our collective experiences.