Time to think about visual neuroscience

by Poppy Sharp, PhD candidate at the Center for Mind/Brain Sciences, University of Trento.

All is not as it seems

We all delight in discovering that what we see isn’t always the truth. Think optical illusions: as a kid I loved finding the hidden images in Magic Eye stereogram pictures. Maybe you remember a surprising moment when you realised you can’t always trust your eyes. Here’s a quick example. In the image below, cover your left eye and stare at the cross, then slowly move closer towards the screen. At some point, instead of seeing what’s really there, you’ll see a continuous black line. This happens when the WAB logo falls in a small patch on the retinae of your eyes where the nerve fibres leave in a bundle, and consequently this patch has no light receptors – a blind spot. When the logo is in your blind spot, your visual system fills in the gap using the available information. Since there are lines on either side, the assumption is made that the line continues through the blind spot.

Illusions reveal that our perception of the world results from the brain building our visual experiences, using best guesses as to what’s really out there. Most of the time you don’t notice, because the visual system has been adapted over years of evolution and then been honed by your lifetime of perceptual experiences, and is pretty good at what it does.

WAB vision

For vision scientists, illusions can provide clues about the way the visual system builds our experiences. We refer to our visual experience of something as a ‘percept’, and use the term ‘stimulus’ for the thing which prompted that percept. The stimulus could be something as simple as a flash of light, or more complex like a human face. Vision science is all about carefully designing experiments so we can tease apart the relationship between the physical stimulus out in the world and our percept of it. In this way, we learn about the ongoing processes in the brain which allow us to do everything from recognising objects and people, to judging the trajectory of a moving ball so we can catch it.

We can get insight into what people perceived by measuring their behavioural responses. Take a simple experiment: we show people an arrow to indicate whether to pay attention to the left or the right side of the screen, then they see either one or two flashes of light flash quickly on one side, and have to press a button to indicate how many flashes they saw. There are several behavioural measures we could record here. Did the cue help them be more accurate at telling the difference between one or two flashes? Did the cue allow them to respond more quickly? Were they more confident in their response? These are all behavioural measures. In addition, we can also look at another type of measure: their brain activity. Recording brain activity allows unique insights into how our experiences of the world are put together, and investigation of exciting new questions about the mind and brain.

Rhythms of the brain

Your brain is a complex network of cells using electrochemical signals to communicate with one another. We can take a peek at your brain waves by measuring the magnetic fields associated with the electrical activity of your brain. These magnetic fields are very small, so to record them we need a machine called an MEG scanner (magnetoencephalography) which has many extremely sensitive sensors called SQUIDs (superconducting quantum interference devices). The scanner somewhat resembles a dryer for ladies getting their blue rinse done, but differs in that it’s filled with liquid helium and costs about three million euros.

A single cell firing off an electrical signal would have too small a magnetic field to be detected, but since cells tend to fire together as groups, we can measure these patterns of activity in the MEG signal. Then we look for differences in the patterns of activity under different experimental conditions, in order to reveal what’s going on in the brain during different cognitive processes. For example, in our simple experiment from before with a cue and flashes of light, we would likely find differences in brain activity when these flashes occur at an expected location as compared to an unexpected one.

One particularly fascinating way we can characterise patterns of brain activity is in terms of the the rhythms of the brain. Brain activity is an ongoing symphony of multiple groups of cells firing in concert. Some groups fire together more often (i.e. at high frequency), whereas others may also be firing together in a synchronised way, but firing less often (low frequency). These different patterns of brain waves generated by cells forming different groups and firing at various frequencies are vital for many important processes, including visual perception.

What I’m working on

For as many hours of the day as your eyes are open, a flood of visual information is continuously streaming into your brain. I’m interested in how the visual system makes sense of all that information, and prioritises some things over others. Like many researchers, the approach we use is to show simple stimuli in a controlled setting, in order to ask questions about fundamental low level visual processes. We then hope that our insights generalise to more natural processing in the busy and changeable visual environment of the ‘real world’. My focus is on temporal processing. Temporal processing can refer to a lot of things, but as far as my projects go we mean how you deal with stimuli occurring very close together in time (tens of milliseconds apart). I’m investigating how this is influenced by expectations, so in my experiments we manipulate expectations about where in space stimuli will be, and also your expectations about when they will appear. This is achieved using simple visual cues to direct your attention to, for example, a certain area of the screen.

When stimuli rapidly follow one another in time, sometimes it’s important to be parse them into separate percepts whereas other times it’s more appropriate to integrate them together. There’s always a tradeoff between the precision and stability of the percepts built by the visual system.  The right balance between splitting up stimuli into separate percepts as opposed to blending them into a combined percept depends on the situation and what you’re trying to achieve at that moment.

Let’s illustrate some aspects of this idea about parsing versus integrating stimuli with a story, out in the woods at night. If some flashes of light come in quick succession from the undergrowth, this could be the moonlight reflecting off the eyes of a moving predator. In this case, your visual system needs to integrate these stimuli into a percept of the predator moving through space. But a similar set of several stimuli flashing up from the darkness could also be multiple predators next to each other, in which case it’s vital that you parse the incoming information and perceive them separately. Current circumstances and goals determine the mode of temporal processing that is most appropriate.

I’m investigating how expectations about where stimuli will be can influence your ability to either parse them into separate percepts or to form an integrated percept. Through characterising how expectations influence these two fundamental but opposing temporal processes, we hope to gain insights not only into the processes themselves, but also into the mechanisms of expectation in the visual system. By combining behavioural measures with measures of brain activity (collected using the MEG scanner), we are working towards new accounts of the dynamics of temporal processing and factors which influence it. In this way, we better our understanding of the visual system’s impressive capabilities in building our vital visual experiences from the lively stream of information entering our eyes.


Deep Time Diversity: Decoding 375 Million Years of Life on Land

By: Emma Dunne (@emmadnn)

Across the world today we can see a tremendous amount of biodiversity. Animals occupy every corner of the globe, from the lush rainforests at the equator to the vast icy expanses at the poles and the plethora of grasslands, deserts, and forests in between. Nature is outstanding in its variation of animal forms; animals have mastered flight, can tolerate extreme environments, demonstrate complex behaviours, and some can even use tools. But exactly how life on land became so diverse remains largely uncertain.



Chameleons are a distinctive group of reptiles which contains many different species that vary greatly in colour. Image: Pixabay.

Life has been around for an extremely long time – 3.8 billion years to be exact. Now, that’s a very long time indeed, but for the first 3.795 or so billion years life was microscopic. It wasn’t until 542 million years ago that animals became a little more complex – during the ‘Cambrian Explosion’ when most major groups, such as arthropods, first evolved. To put things into perspective, wherever you are right now stick both of your arms out straight to the side (don’t be shy!). The very tip of your left index finger represents the present day, and the tip of your right index finger represents the point about 542 million years in the past. Moving from right to left, the first fish appear somewhere in the middle of your right forearm just after the Cambrian Explosion. Plants emerged on land around 425 million years ago, a little closer to your right elbow. It wasn’t until the point just before your right shoulder that vertebrates first ventured onto land, beginning the process of evolving into the beasts we are all familiar with today. At the point in the middle of your body, the continents were all squashed together in a landmass known as Pangaea, while reptiles, such as the sailbacked Dimetrodon, ruled the hot and arid lands around the equator. Dinosaurs first appear somewhere on your left shoulder (about 240 million years ago), followed very closely by the first mammals. Dinosaurs are wiped out just before we reach your left wrist (66 million years ago), paving the way for mammals to begin ruling the land. And now to make you really feel like a big fish in a small pond: Humans did not appear until the very tip of your left index finger, occupying a slice of your makeshift timescale no thicker than your fingernail. So, our species really hasn’t been around for long at all!

2 Dimetrodon

Dimetrodon grandis, an extinct reptile that lived 295-272 million years ago during the Permian period in the wetlands of the supercontinent Euramerica. Illustration: Scott Hartman (www.skeletaldrawing.com)


With all of these different animals evolving and going extinct at different points throughout Earth’s history, biodiversity has fluctuated, with increases in diversity punctuated by significant decreases known as extinction events, some more severe than others.

Over the last 50 years palaeobiologists have been trying to quantify exactly how significant these rises and falls in diversity have been using computational methods.

Typically, these analyses involve tallying the number of fossil families for specific time intervals and comparing the totals between neighbouring intervals. Previous studies using this method estimate that diversity on land has risen exponentially, or continued to rise faster and faster over time. A number of reasons have been given for this pattern, including the availability of suitable niches and favourable climatic conditions allowing species to thrive and diversify further.

Sounds simple, right? Not quite…


The currently accepted pattern of changes in diversity on land constructed using counts of fossil tetrapod (four-limbed vertebrates) families through time. This pattern shows an “exponential rise” in diversity and more and more families appear on land as time goes on. From Sahney et al. (2010) Biol. Lett. (Numbered 1-3 are the end-Permian, end-Triassic and the Cretaceous/Paleogene boundary mass extinctions)

The problem is the fossil record is inherently biased. When you think of a fossil I could almost be certain that you would think of a skeleton in a piece of rock. And that’s not wrong! Hard parts, such as bones, shells, and teeth, are much easier to preserve than soft squishy bits – bias number one. Luckily for vertebrate palaeontologists, like myself, we don’t usually run into this issue as our study subjects have bones. But we do unfortunately encounter other biases. Some groups of animals contain many more individuals than others, and are therefore more likely to leave fossils behind (think huge herds of wildebeest vs. a pride of lions). Similarly, different habitats allow more diversity than others (for example the Siberian Tundra vs. the African savannah). These ‘biological factors’ come in to play even before the fossilisation process even begins!


Groups of animals that exist in large numbers such as wildebeest or antelope, are much more likely to leave behind some fossils for us to find that animals who don’t exist in such large numbers, such as lions. These biological factors affect the fossilisation potential of an organisms waaay before the geological processes kick in!

The chances of an animal becoming a fossil are very slim indeed. Usually, after an animal dies its body rots away or is devoured by predators and scavengers, never to be seen again. But sometimes conditions are just right, and once the body is buried quickly with mud or sand, rock can begin to form and the remains can be fossilised. As we look back further in time our picture of the past gets a little fuzzier, as older rocks get overlain by younger rocks and mashed up by geological forces such as earthquakes and erosion. Fossils also only occur in sedimentary rocks (if you can remember back to your high school geography classes, you might remember that there are three types of rock: igneous, metamorphic, and sedimentary!), and sedimentary rocks are not found uniformly across the globe. So even finding a fossil is an extremely rare occurrence!

Human biases permeate all scientific disciplines, and palaeontology is no exception.

Sometimes it is easy to stumble across a large ‘mass grave’ containing hundreds of fossils, and sometimes these sites can be in very sunny, very beautiful countries worth visiting. Other times fossils have been found in isolation in areas where conditions are harsh, such as the important transitional fossil Acanthostega found in eastern Greenland. So, who’s up for a fun expedition to the wilds of Siberia in search of reptile fossils in the dead of winter? What, no? Yeah, me neither.

All of these factors (biological, geological, and human in origin) contribute to what are known as ‘sampling biases’, or biases that influence the amount and type of fossil data we have available for us to study.


An exquisitely preserved full body fossil of the extinct amphibian Phlegethontia longissima from the Mazon Creek fossil beds in Illinois, USA. Finds like this little fella are very rare indeed. Specimen housed at the Burpee Museum.

With these sampling biases stacked against us, it seems unwise to use simple counts of fossils to illuminate important patterns of diversity through time. This is where my research comes in. We are currently building a shiny new dataset within the publically accessible Paleobiology Database (paleobiodb.org). With this dataset, we are able to apply more sophisticated statistical methods to our analyses and rigorously test the patterns of diversity change on land over the last 375 million years.

My research will allow palaeobiologists to answer the question; are we able to identify genuine patterns of diversity change, or are we simply viewing changes in the number of fossils available to study through time?

So, with so many millions of years to get through, where’s the best place to start? Why, at the beginning of course! My current work surrounds the interval of geological time when the first vertebrates appeared on land and began to diversify over the next 100 million years. Given that the rocks containing these fossils are very old and are poorly surveyed, our ability to identify genuine diversity patterns is significantly distorted. However, the story does begin to improve as we move into the next 100 million years and we begin to see the fossils reflecting the true patterns of diversity.


Map of the world from the Paleobiology Database (paleobiodb.org) showing the locations across the world where tetrapod fossils have been found from the time they first appeared approximately 375 million years ago right up to the present day. You can create maps such as this for yourself at: paleobiodb.org/navigator!

My research has just begun to scratch the surface of decoding the diversity of life on land, and there’s still a long way to go! Studies such as ours are becoming increasingly relevant today as we try to anticipate the effects of the current biodiversity crisis happening across the world. Many animals worldwide are currently under threat of extinction, and if this pattern is to continue we might well see ourselves experiencing the terrifying prospect of a 6th major mass extinction.

Research into past extinction events can determine how ecosystems and animal communities responded in the aftermath of dramatic decreases in diversity, and I hope that my research looking into the geological past will give us some hope for the future.

Find out more:




Monkeys, happiness, and winning debates

By: Lauren Robinson


Monkeys you say? Tell me more.
Jane Goddsfodall once asked me, “Was it you, was it you who put a monkey in the loo?!” If you’re wondering, no it was not. Thankfully she was referring to a poster rather than an actual monkey. Yet, I take it as a point of pride to have been asked and to be working in a field where I regularly get close enough to monkeys to have been slapped by one (truthfully
it’s more than that but I’ve lost count). It was my fault; I was observing the monkeys and how dare that require looking at them. Primatology, the study of nonhuman primates ckvsn(monkeys, chimpanzees, gorillas, etc.), is not for the faint of heart or slow of reflex. It’s a field I fell in love with (I mean look at the baby Sulawesi macaque on the right, it has a heart shaped bum!) during my Masters dissertation studying Japanese macaques (see: photo above of suckling infant).
There are a lot of different things about primates that I could study (having anecdotally and painfully observed their speed) and the area of primatology that I am most interested is primate welfare. What do I mean when I say “welfare”? Well, I use a very broad definition and define welfare as the mental and physical health of an animal. In order to study animal welfare, researchers, such as myself, use methods that cross between the fields of animal behaviour, psychology, and physiology, among others. We observe animals for unusual behaviours, assess them for increased stress levels, and look for signs of injury and illness. Animal welfare science is a growing field and, with pioneers such as Marian Dawkins (Dawkins, 1980) and Temple Grandin, it is one with multiple strong and well known female scientists to look up to.

Enough of that, let’s talk about me.

My research focuses on the individual animal, which is why I’m currently in a psychology department studying individual differences in animal personality. I take the approach that an animal’s welfare is an individual experience and we need to understand the individual differences associated with it, specifically personality. Most of us have a general idea of what personality is, especially when asked to list the traits we love or hate about other people.fvsdknv Over the last couple decades it has become more accepted to talk about animals having personality as well (Gosling, 2001). It’s rare that someone describes their dog as “consistently approaching unfamiliar people and animals in a nonaggressive manner”. Instead, they say their dog is friendly and sociable. In the case of my dog Juneau (left), we describe her as eccentric and too clever for her own good. While some scientists may be on the fence about animal personality my experience has been that the public isn’t, they get it and they believe that animals have it. In order to understand primate welfare I look for the personality differences that influence it, which is the focus of my research. I want to know if certain personality traits make animals more likely to be do well in captivity, in the same way that people with certain personality traits do better in life. For example, more extraverted and sociable people tend to be healthier and happier (Costa & McCrae, 1980; Deary, Weiss, & Batty, 2010).

I started as PhD student at the University of Edinburgh in 2013 working with Dr Alex Weiss. Alex and I have different scientific backgrounds and naturally, we disagree on some things. Key among the disagreements we’ve had over the years is the difference between welfare and happiness in animals. Alex felt that if an animal had everything it needed in captivity (safety, food, companionship, good physical health) then it had high welfare. He noted then even when animals have all these things they can be unhappy, which to him meant that happiness and welfare did not necessarily go together for animals. Alex based this on the observation that some people appear to have everything they could want for (money, friends, shelter) but aren’t happy. I felt differently. As I said earlier, I take the approach that an animal’s welfare is an individual experience. Therefore, if the animal appears to have everything it needs but is still unhappy then, by definition, that animal has reduced welfare. How to find out who is right though? To the Batcave! Yeah, sadly not. Instead it was off to Google Scholar to research and come up with a way of testing my hypothesis that primate happiness and welfare were one and the same.skndcs

What I found was a great article by Franklin McMillan (2005), who says that there are five main things that influence an animal’s welfare: mental stimulation, physical health, stress, social relationships, and control of physical and social environment. When psychologists look at human happiness they typically use questionnaires (Sandvik, Diener, & Seidlitz, 1993) and there is a questionnaire to measure primate happiness (King & Landau, 2003) but animal welfare scientists don’t typically use questionnaires as there are concerns about the accuracy of ratings.
This hasn’t been well studied though so I took McMillan’s five things and created a questionnaire for staff familiar with animals to fill out. To test if it worked I took my welfare questionnaire and the primate happiness questionnaire and sent them out to zoos and research facilities.


Well, you win the debate or not?

Currently, I’m working on finishing my PhD (send whisky for my woes) and have used the questionnaires to study welfare and happiness in three species: Brown capuchins, chimpanzees, and rhesus macaques. First thing I found was that staff familiar with the animals I studied were really good at rating animal welfare. They agreed to the same degree that people do when they rate their friends and family member’s personality. The next thing I found, much to my own happiness, was that welfare and happiness are really one and the same in those three species (I won!). Three species and some pretty compelling results (Robinson et al., 2016; in review; in prep) were convincing enough to get my supervisor to rethink his opinion on happiness and welfare. Did you catch that? The PhD student actually won one! Sure, Alex has taught me a billion things to this one thing I taught him, but I will take it.

So, what about personality and welfare? Personality does influence primate welfare, similar to what we see in people. Animals with certain personality traits have higher happiness and welfare. The brown capuchins that were more sociable, assertive, attentive, and more emotionally stable were those that had higher happiness and welfare. For chimpanzees, seems to be about extraversion and emotional stability. Rhesus macaques, it’s all about confidence; those with more confident personalities had higher welfare and happiness. It’s my hope that now we know more about welfare, happiness, and personality we can use this information to improve the lives of animals. This could be done by using the questionnaire as another tool for measuring animal welfare or by trying to provide more care for animals with personality traits that tend to be related to unhappiness.

Upon reflection…

bfkjdfWhile my research results are better than I could have hoped for the best part of this research were the experiences I gained along the way. As I get to the end of my PhD, and this post, I’m starting to put thesis together and I’m all about reflection about my past three years (when I’m not panicking about the next three). I’ve gotten to study three species of primates, worked in zoos and research facilities (many of you will have thoughts on animals in research, I get that but don’t have room to get into that topic without a separate post), and collaborated with tons of amazing researchers. All of that is fantastic but let’s be honest, the monkeys are the best part.

You may be wondering what monkeys are like. I’ve worked directly with over 100 macaques and there is no doubt in my mind that each one is an individual with very different personality. Some are funny, some are playful, some are grumpy, and plenty are aggressive (learned that the hard way). While I hope that I’ve piqued your interest in primates, their amazing personalities, and their welfare I would be remiss if I didn’t state that primate are not pets (see resources below). I know I’ve spoken of my passion for working with primates but only in professional manner and environment and I never treat them as less than they are, which is wild animals. Primates are far too clever and socially complex to be kept as pets. Anyone that tells you otherwise is flat out wrong. No exceptions to the rule, no anecdotes, no to primates as pets.

Having said my warning, I will finish by acknowledging that while there are a lot of words to describe what I do (science, animal welfare, primatology) the one that always stands out to me is ‘privileged’. Working with primates is a privilege. Studying and working to improve their welfare is the best way I know to show my appreciation of that privilege.

If you’re interested in learning more about primate welfare, there are some public engagement resources that I’m a big fan of:

NC3Rs macaque page

Online tour of German Primate Center

Why monkeys shouldn’t be pets

Animal welfare legislation resources

Costa, P. T., & McCrae, R. R. (1980). Influence of extraversion and neuroticism on subjective well-being: happy and unhappy people. Journal of Personality and Social Psychology, 38(4), 668–678.

Dawkins, M. S. (1980). Animal suffering: The science of animal welfare. Ethology (Vol. 114). New York: Chapman and Hall.

Deary, I. J., Weiss, A., & Batty, G. D. (2010). Intelligence and Personality as Predictors of Illness and Death: How Researchers in Differential Psychology and Chronic Disease Epidemiology Are Collaborating to Understand and Address Health Inequalities. Psychological Science in the Public Interest.

Gosling, S. D. (2001). From mice to men: What can we learn about personality from animal research? Psychological Bulletin, 127(1), 45–86.

King, J. E., & Landau, V. I. (2003). Can chimpanzee (Pan troglodytes) happiness be estimated by human raters? Journal of Research in Personality, 37(1), 1–15.

McMillan, F. (2005). Mental wellness: The concept of quality of life in animals. In Mental Health and Well-Being in Animals.

Robinson, L. M., Waran, N. K., Leach, M. C., Morton, F. B., Paukner, A., Lonsdorf, E., Handel, I., Wilson V. A. D., Morton, F. B., Brosnan, S., & Weiss, A. (2016). Happiness is positive welfare in brown capuchins (Sapajus apella). Applied Animal Behaviour Science, 181, 145-151.

Robinson, L. M., Altschul, D., Wallace, E. K., Ubeda, Y., Machanda, Z., Slocombe, K. E., Llorente, M., Leach, M. C., Waran, N. K., & Weiss, A. (In press). Chimpanzees with positive welfare are happier, extraverted, and emotionally stable. Applied Animal Behaviour Science. 10.1016/j.applanim.2017.02.008.

Robinson, L. M., Capitanio, J. P., Leach, M. C., Waran, N. K., & Weiss, A. (In prep). The influence of personality on rhesus macaque health, welfare, and happiness.

Sandvik, E., Diener, E., & Seidlitz, L. (1993). Subjective Well-Being – the Convergence and Stability of Self-Report and Non-Self-Report Measures. Journal of Personality, 61(3), 318–342.


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 http://www.mfpa.uk 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.


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.

The wonders of kelp, and why we need to save it.

‘Deforestation of the Sea: A closer look at valuable kelp forests in shallow seas around Britain’ by Jess Fisher.

 ‘I can only compare these great aquatic forests… with the terrestrial ones in the intertropical regions. Yet if in any country a forest was destroyed, I do not believe nearly so many species of animals would perish as would here, from the destruction of the kelp’

Charles Darwin (1834) Tierra del Fuego, Chile

Kelp forests: the rainforests of the ocean

A few weeks ago, I settled happily into Finding Dory on a Saturday night. Towards the end, the little blue fish drifts through the giant kelp forests, devoid of life, and sadly proclaims ‘…there’s nothing here but kelp!’. Having studied this oceanic plant, I can confirm that this is 100% scientifically incorrect: well done Pixar.

Kelp forests actually have around the same levels of biodiversity as a tropical rainforest. But why should you care?

Because kelp can do everything: it’s home to hundreds of thousands of marine species, it can be used as a fertiliser and a biofuel, it can be extracted to use in cosmetics like make-up and toothpaste, amongst many more uses. In 1908, Japanese biochemist Professor Ikeda isolated monosodium glutamate (or MSG – one of the things that makes Asian food so great) from kelp. Who knew science could be so delicious?!

Why is kelp disappearing?

Unfortunately, kelp is reported to be disappearing. This is mostly because of climate change making the oceans uninhabitable for some species, but also that more people are harvesting kelp from the wild. Lots of people are even beginning to call it a superfood. While its rapid growth rate (up to half a metre per day in some species) suggests that harvesting kelp should not really be a problem, conservation scientists are worried that all the marine life living in kelp forests will take quite a bit longer to return. Britain is especially important for kelp (because of the variation in habitats and rocky shores) which is why I started working on a project looking to test novel monitoring methods for kelp, so we can potentially measure what is actually happening.

How our project works

Kayaking into the open ocean near Plymouth, we fought through choppy waves into a prevailing wind, whilst I continually threw cold seawater with my paddle onto my kayak-partner, who was sitting behind me! Lots of kelp lives in the subtidal zone (beneath the sea surface even at low tide), and so the plan was to beam sonar onto the seabed from a kayak, look at the graph that the sonar gives back, and then use a GoPro camera to visually verify assumptions that we were making about which graphic patterns denoted kelp. For example:


 This was one of four kayak trips the team made to test the method. Amongst some other objectives, the main aim is to ask whether sonar can be used to monitor kelp at a Britain-wide scale. The findings will be given to our funder, The Crown Estate, who manages development on the British coastline (The Crown Estate is owned by the Queen of the United Kingdom). They would like to eventually create some guidelines for sustainably harvesting wild kelp, so that this valuable seaweed resource (and its associated flora and fauna) will be available for future generations for years to come. Some kelp snapshots from the seabed:

Counting the cost of losing kelp forests

Kelp forests are reported to be worth billions of pounds. In the northeast Atlantic, young lobster live in the kelp, and are eventually fished by a lobster industry worth £30 million alone. Is it worth keeping? Certainly. Is it worth monitoring incase of declines? Definitely.

 Inspired? Check out the Big Seaweed Search, Capturing Our Coast, and Floating Forests for some citizen science kelp-focussed initiatives. You can also read about the project on ZSL Wild Science.


Studying Atlantic salmon eggs in Canada’s freezing winter – the forgotten study season

by Michelle Lavery

[Reworked from a post on The Fisheries Blog and an article in Fisheries Magazine]

 For many hydrologic regimes of the world, streams and rivers are ice covered for the majority of the year, yet minimal research is conducted during this period compared with the more “researcher-friendly” open-water period. Without a doubt, scientific progress is hampered by the logistical difficulties and high cost associated with conducting “winter” research. (Prowse, 2001 (part II))


[Credit: Michelle Lavery] A beautiful, -26°C or -15F° day on the Little Southwest Miramichi River

It seems as though every winter ecology paper contains some variant of this sentiment – we know that winter is important, but we’re not crazy enough to study it. As researchers, we’ve built sampling regimes that ignore an entire season because winter is considered harsh and unforgiving. It’s cold, sharp, and sometimes deadly to us, and so we operate under the assumption that the same goes for the creatures we study.

Alas, it is not so. There’s a lot going on under the snow, and even more going on under the ice. For example, Atlantic salmon eggs incubate in the gravel under river ice in Eastern Canada for six frigid, snowy months at water temperatures barely above freezing. They emerge from the gravel during the spring melt period, when ice jams bulldoze forests and water levels climb metres in minutes. These tiny fish are at the mercy of a dynamic and unpredictable season, yet we barely know anything about it.

As a pampered girl from ‘tropical’ Toronto, I never imagined myself riding a snowmobile and hacking through river ice in the middle of the woods. However, through a serendipitous connection, I found myself doing both – while pursuing a Masters degree supervised by Dr. Richard Cunjak at the Canadian Rivers Institute.


[Credit: Michelle Lavery] Winter is a dynamic season – here a seeping plume of warm, long-residence groundwater melts a thin trail through thick surface ice on the Little Southwest Miramichi River in northern New Brunswick, Canada.

In Eastern Canada’s Miramichi River system, salmon eggs incubate in the gravel riverbed from late October to early May, during which time they experience highly variable winter conditions. In November, air temperatures can drop dramatically overnight (usually to about -20°C or -4°F), causing water to reach its freezing point quickly and inconsistently. As water crystallizes, it can stick to itself and the bottom of the river, forming anchor ice – a squishy carpet of ice crystals on the riverbed. If this ice forms on top of salmon nests (or “redds”), it can block water flow through the gravel and alter the temperature and oxygen levels surrounding the developing eggs.

Once full ice cover forms and precipitation is locked up in the snowpack, long-residence groundwater may be the major contributor to river discharge. “Long-residence” groundwater refers to water that has spent a considerable amount of time in an aquifer deep underground. Consequently, it is often warmer than the surface water in the winter, and can have significantly lower oxygen concentrations (since it has not been recently aerated). As this groundwater seeps through the river bed, the conditions in salmon redds can change dramatically. Depending on the size of the seep, eggs may develop faster due to warmer water temperatures and require more oxygen to sustain this accelerated rate of development. However, the oxygen-poor groundwater is usually unable to meet their biological demands. Without enough oxygen, these eggs may die or experience “sub-lethal” effects – consequences that impact their survival later in life as free-swimming fish. These may include stunted growth or developmental deformities that impair gas exchange, swimming ability, neurological function, etc.


[Credit: Michelle Lavery] Studying an ecosystem during the season without snow only gives us half the story… There’s more going on under the ice than meets the eye!

During the spring melt period, silt and clay can be eroded into rivers by meltwater from the river banks. Depending on the grain size, these sediments may clog the egg membrane and prevent oxygen delivery to the embryo, effectively suffocating the fish. Furthermore, as ice breaks up and moves out of rivers, scour along the riverbed may significantly disturb the gravel and damage the embryos buried in the redds.

It is hard to believe, after considering all of the variation inherent in winter and its potential effects on one life stage of one species in one type of habitat, that winter goes largely unnoticed in the scientific literature. It is, certainly, a challenging season to research. I’ve had my fair share of winter mishaps, including digging a snowmobile out of a slush puddle for three hours, miscalculating ice thickness (not ideal!), hypothermic near-misses, and tethering myself to a tree during the spring melt. However, if we can get past our numb fingers and dripping noses, there’s a whole season waiting to be studied. One could argue that winter research is the last true frontier of freshwater ecology – there are so many unknowns to explore, and so many questions left unanswered. It might not be a “researcher-friendly” season, but it’s definitely exciting! Plus, who doesn’t love a good mid-river snowball fight?


[Credit: Aaron Fraser] When fighting Jack Frost, it helps to have a great pair of neoprene chest waders and some GoreTex mitts. You can take or leave the camouflage…