Are the contents of your mind really 'confidential' or will your thoughts one day be accessible to others?

Media reports into recent research have claimed that neuroscientists are now effectively able to perform ‘mind reading’. Such reporting inevitable raises ethical questions about what applications such research might eventually be put to, and, judging by some of the comments that the on-line versions of these articles have provoked, have alarmed some people regarding the eventual path that such research might take. But how accurate is the claim that neuroscientific techniques can read minds?

Early this year an article in the Guardian  ( http://www.guardian.co.uk/science/2012/jan/31/mind-reading-program-brain-words ) reported that:

‘Scientists have picked up fragments of people’s thoughts by decoding the brain activity caused by words that they hear.’

Reporting on the same experiment the Daily Mail ( http://www.dailymail.co.uk/sciencetech/article-2095214/As-scientists-discover-translate-brainwaves-words–Could-machine-read-innermost-thoughts.html ) claimed:

 ’It’s a staggering development that could have tremendous implications….judges could use mind-reading machines to find out if murder suspects are telling the truth….mind reading devices might be used to eavesdrop covertly on the most private thoughts and dreams.’

The experiment in question, conducted by Dr Brian Pasley and colleagues (1) involved the recruitment of patients who were to undergo brain surgery. The researchers placed electrodes upon the auditory areas of the brain during the period when the patients’ skulls were open and their cerebral cortex exposed. They then played the patients a sequence of different words and recorded the electrical activity generated by the auditory cortex in response to this speech. Using complex modeling procedures they were able to reconstruct the spoken words solely from the neural signals recorded by the electrodes. Furthermore they were able to successfully apply this model to the electrical responses generated by a separate set of words that had not been used in creation of the model (e.g. which were in effect ‘novel’ to the model) suggesting that the model could theoretically be applied to reconstruct any speech heard by the patient.

While these results are undoubtedly impressive, has the media coverage of them been accurate? In terms of the Guardian’s report, their claim that this represents a decoding of ‘fragments of thoughts’ seems to depend on a rather broad definition of the term ‘thoughts’. What the research did was to reconstruct auditory stimuli that the auditory cortex was in the process of analysing. What has been achieved therefore is the decoding, at a detailed level, of the perceptual process, NOT the reading of internally generated thoughts. This is a significant step away from ‘decoding thoughts’ as the  process being decoded is entirely dependent on the presentation of an external stimulus. This doesn’t therefore represent ‘mind reading’ because the same result could theoretically be achieved without reference to the brain, e.g. by taking measurements from the relevant sensory organ or by just observing the sensory stimulus itself (2). Even if the research did represent mind reading, there seems little justification for the Daily Mail’s claim that the research could lead to ‘covert eavesdropping’. It should be obvious that the methodology required not only the opening up of the participant’s skull, but also the co-operation of the participant in allowing data to be taken for the construction of the model. Furthermore what is not mentioned by either article is that the reconstructed words were not actually intelligible to a human listener, but had to be ‘recognised’ via a speech recognition algorithm (an example of the reconstructed speech can be heard here:  http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001251#s5).

Actual Mind Reading?

While the results of Dr Pasley’s study required the participant’s brains to be exposed, other neuroimaging methods are not so intrusive, and could therefore be considered closer to the covert mind-reading reported by the Mail. Magnetic Resonance Imaging (MRI) allows brain activity to be measured in a non-invasive way, so that no surgery of any kind is required (although lying down in a scanner which costs millions of pounds and is the size of a small boat, is still required, making it far from ‘covert’!). MRI studies have produced some equivalent results to that of Pasley’s study, but using visual stimuli; with images (3) and short movies (4) having been reconstructed purely from data obtained from MRI scans. Of course such results don’t represent mind reading any more than Dr Pasley’s study, since they reflect a reconstruction of external sensory information. However other MRI studies have produced results that have allowed scientists to predict processes occurring within a participant’s brain that are not directly tied to the characteristic of external stimuli. A couple of studies by Yukiyasu Kamitani and Frank Tong (5,6) have shown that models can be created that allow an observer to identify to which stimulus a participant is (covertly) attending to. In effect these studies, and others like them, use the output from the perceptual processing mechanisms of the brain to identify how ‘top-down’ influences (such as expectation and attention) are driving perception. Strictly speaking they represent mindreading as although the mental processes in question are still involved in analysing external stimuli, it is not necessarily possible to garner the information provided by the MRI data in any other way (short of asking the person themselves). This is because the ‘top-down influences’ in question arise internally from the brain, rather than being a function of the external stimulus. Neuroimaging has enabled the concept of mind reading to be taken further however, into the realms of decoding mental events that don’t rely on any external stimulation at all. Recent studies have found that it is possible to decode what broad categories of objects someone is imagining, in the absence of any coincident external stimulation (7) although the performance level of the model is reasonably modest (~ 50%). Similarly, it also appears that the results of basic decision making processes can be identified from brain activity, with decisions relating to which button to press and when to press it (8) and whether a participant in lying (9) being decipherable using models constructed in a similar way to those already described. Interestingly the neural information that allows these decisions to be decoded occurs many seconds BEFORE the decision has actually been made, highlighting how conscious actions are likely driven by brain processes that are outside conscious awareness, rather than being the result of conscious ‘free will’. Most recently such work has been extended to more complex scenarios, with MRI data being used to predict at what point in solving an algebraic problem a child is at, and whether they are performing the calculation correctly (10).

The possibility of covert mind reading?

Clearly the aforementioned examples reflect mind reading, but do they represent the top of a ‘slippery slope’ that will lead to technology that will allow the sort of covert eavesdropping envisioned by the Daily Mail? The first impediment to such technology is the process of neuroimaging itself. MRI scanners are far from being portable enough to allow forced or covert application of brain scanning. Furthermore MRI scanning involves the production of a large magnetic field and the firing of electromagnetic pulses towards the object being imaged, both functions that would be totally impractical outside a controlled, isolated environment. Other neuroimaging methods, such as EEG, function by recording the electrical remnants of brain activity from outside the skull, and are therefore cheaper and more portable than MRI. However they lack the spatial resolution that would be required for any sophisticated mind reading application, and in any case they are extremely sensitive to external noise, again making them unsuitable for use outside of controlled environments.

Even if we assume that future technological advances would allow systems to be developed that would enable covert collection brain activity data, would such technology enable your innermost thoughts to be deciphered? There are a number of reasons to doubt that this would be possible. Current mind reading models are only able to distinguish between very broad categories of thoughts, or between very coarse categories of decisions (e.g. lie/truth, attending to one or other stimulus). To be able to read the specific details of an individual’s thoughts you would need models that distinguished between the literally billions of different things that someone could be thinking about, and the multitude of different decisions that they could make. To even create such models would involve the co-operation of individuals in a data collection process that would take an incalculable length of time. Even if such data were collected, and the subsequent required level of computation to create accurate models were possible, the ability to generalize such models to the brain activity of other individuals would rely on an assumption that every person’s brain being identical in terms of where different individual thoughts and memories are stored. This seems extremely unlikely, and is in fact counter to what we know about individual differences in brain anatomy and function. Thus while it is possible to aggregate data across participant to produce mind-reading for coarse decisions, it would be impossible to replicate such a method to distinguish between more subtle categories of thought. Even in situations where co-operation of the participant is attained, and only a coarse distinction between different psychological states is required, such mind reading techniques are problematic. Taking the example of the mooted ‘MRI Lie detector’ such a system will always be somewhat unreliable because, just like the current physiological lie detectors, they could be easily deceived if the participant can train themselves to act as if the truth is a lie (or vice versa). This is because the brain activity which is associated with lying most likely relates to the emotional and cognitive processes involved in creating a false story, rather than to lying per se. It follows that simply engaging in these same emotional and cognitive processes while telling the truth should produce neural activity which mimics that produced by a lie. If even the decoding of simple decisions can be subverted easily, it would seem impossible that attempts at more subtle discriminations of different thoughts would not be subject to even greater uncertainty. Finally it is important to note that all the forms of mind reading reviewed here are the result of probabilistic calculations. The parts of the brain that are deemed active at a certain point in time are the result of statistical computations as to whether a small signal is reflective of task-related neural activity or noise. Likewise the classification of such activity as belonging to one category of thought/decision over another is also based off probabilistic inference. There is no certainty in such a process; in fact it is fraught with uncertainty.

To conclude it seems very unlikely that neuroimaging methods will ever be able to perform the sort of mind reading predicted by scare stories in the press. In some cases such methods may not even represent a particular improvement on the sort of mind reading applications that already exist. What the mind reading research discussed in this article does allow is a greater understanding of how the brain works, which in turn provides insight into how the brain achieves the myriad feats it performs so frequently with apparent ease. The most fruitful practical application of such knowledge is likely to be in the treatment of patients with brain damage. For example the limited mind reading functions possible from existing neuroimaging methods may allow technology to be developed that would allow patients who suffer from brain damage to the extent that they cannot communicate using their peripheral nervous system, some primitive form of communication through their brain activity. In contrast your private thought and memories are likely to remain safe from the prying eyes of neuroscientists!

Image (top right) courtesy of Idea Go:  http://www.freedigitalphotos.net/images/view_photog.php?photogid=809

References

(1) Pasley BN, David SV, Mesgarani N, Flinker A, Shamma SA, et al. (2012) Reconstructing Speech from Human Auditory Cortex. PLoS Biol 10(1): e1001251. doi:10.1371/journal.pbio.1001251

(2) Tong, F. & Pratte, M.S. (2012) Decoding Patterns of Human Brain Activity. Annual Review of Psychology, 63: 483-509.

(3)  Miyawaki, Y. Uchida, H. et al (2008) Visual Image Reconstruction from Human Brain Activity using a Combination of Multi-scale Local Image Decoders.. Neuron 60, 915–929,

(4)  Nishimoto, S., Vu, A.T., et al (2011) Reconstructing Visual Experiences from Brain Activity Evoked by Natural Movies. Current Biology 21, 1641–1646

(5) Kamitani Y, Tong F. 2005. Decoding the visual and subjective contents of the human brain. Nat. Neurosci. 8:679–85

(6) Kamitani Y, Tong F. 2006. Decoding seen and attended motion directions from activity in the human visual cortex. Curr. Biol. 16:1096–102

(7) Reddy, L., Tsuchiya, N. & Serre, T. (2010). Reading the mind’s eye: Decoding category information during mental imagery. Neuroimage. 50(2) 818-825

(8) Soon CS, Brass M, Heinze HJ, Haynes JD. 2008. Unconscious determinants of free decisions in the human brain. Nat. Neurosci. 11:543–45

(9) Davatzikos C, Ruparel K, Fan Y, Shen DG, Acharyya M, et al. 2005. Classifying spatial patterns of brain activity with machine learning methods: application to lie detection. NeuroImage 28:663–68

(10) Anderson, J.R. (2012) Tracking Problem Solving by Multivariate Pattern Analysis and Hidden Markov Model algorithms

Researchers led by Evgeny Katz, the Milton Kerker Chaired Professor of Colloid Science at Clarkson University, have implanted a biofuel cell in a living snail. Their findings were published in the Journal of The American Chemical Society.

Researchers led by Evgeny Katz, the Milton Kerker Chaired Professor of Colloid Science at Clarkson University, have implanted a biofuel cell in a living snail. This is the first incidence of an implanted biofuel cell continuously operating in a snail and producing electrical power over a long period of time using the snail’s physiologically produced glucose as a fuel. (Credit: Image courtesy of Clarkson University)

The “implanted battery” can generate electrical power for several months driven by glucose, which is produced by the snail.

This is the first reported incident of an implanted biofuel cell operating in a snail and producing electrical power over a long period of time using as fuel the glucose that is physiologically generated by its host.

Implantable biofuel cells have been suggested as sustainable micropower sources operating in living organisms, but such systems are still very challenging to design. In the future, implanted fuel cells that are driven by glucose generated by their host could power medical devices in humans or environmental sensors in animals.

Evgeny Katz and his colleagues made the electrodes of their fuel cell out of densely packed carbon nanotubes, and attached glucose-oxidizing and oxygen-reducing enzymes to them. The authors then implanted the electrodes into a snail (Neohelix albolabris). After decreasing the rate of current extraction to match the snail’s slow glucose transport and metabolism, they got continuous electrical output for an hour. The amount of electricity produced was far below that of just one AAA battery, but the group of scientists aim to increase it in future experiments. The fuel cell remained functional in the snail for several months during which the animal was allowed to roam freely and live an almost normal life.

The aim of this research is creating insect cyborgs, an idea that has been funded by the U.S. Department of Defense.

Reference

Lenka Halámková, Jan Halámek, Vera Bocharova, Alon Szczupak, Lital Alfonta, Evgeny Katz. Implanted Biofuel Cell Operating in a Living Snail. Journal of the American Chemical Society, 2012; : 120308155036002 DOI:10.1021/ja211714w

You can find the article here:  http://pubs.acs.org/doi/abs/10.1021/ja211714w 

Researchers at the University of Leicester may have solved a long-standing mystery in astrophysics, namely: how do black holes grow so massive? In a recent paper in the journal Notes of the Royal Astronomical Society, Christopher Nixon and Andrew King from the University of Leicester, along with their collaborator Daniel Price from Monash University in Australia, put forward a new theory of black hole growth in which the gluttonous space-time singularities are able to put on weight more than 100 times faster than their conventional diet allows.

Black holes are ubiquitous in the universe, but the real heavyweights reside at the centre of galaxies like our own Milky Way, and can weigh in anywhere up to 10 billion times the mass of the Sun. They grow by a process called accretion, gobbling up gas from a disc around their equator as it gradually loses angular momentum and spirals inwards, like water down a plug hole.

Except that this can’t possibly be correct, as Professor King explains: “These hugely massive black holes were already full-grown when the universe was very young, less than a tenth of its present age.”

“We needed a faster mechanism,” says Chris Nixon, also at Leicester, “so we wondered what would happen if gas came in from different directions.”

The team made a computer simulation of a black hole orbited by two accretion discs at different angles. At the points where the discs collide, the angular momentum keeping the gas in orbit cancels out, and the gas quickly falls into the central regions, either becoming the black hole’s next meal, or recircularising into a smaller disc, depending on how much angular momentum it managed to hold onto (see picture below).

Simulation of a black hole orbited by two accretion discs, after evolving for approximately 10 orbits. The structure of the two original discs can be seen in blue, whereas the white disc near the centre is formed of gas that has collided and fallen in, before restabilising at a smaller radius.

“If two guys ride motorbikes on a Wall of Death and they collide, they lose the centrifugal force holding them to the walls and fall,” says King. The same thing happens to the gas in these discs, and it falls in towards the hole.

The regions at the centre of young galaxies provide the chaotic conditions thought to give rise to such double-disc accretion systems, providing the greedy young black holes with all the gaseous sustainence they need to grow into the giants we observe today.

The group’s paper can be found at: http://www.astro.le.ac.uk/~cjn12/papers/twist.pdf

Strongly scented foods encourage people to take smaller bites, a method commonly thought to help dieters with portion control, say researchers from Wageningen University, Netherlands.

Participants in the study were given control of how much custard they were served by pushing a button, as they were repeatedly exposed to different scents. The study showed that people would eat as much as 10% less pudding when they were presented with stronger or more unfamiliar smells.

“Bite size was associated with the aroma presented for that bite, and also for subsequent bites (especially the second to last bite),” said Dr Rene A de Wijk, project leader.

Generally, people will take smaller bites if a food is unfamiliar or unpleasant, to keep the amount of flavour they are exposed to as small as possible.

“Perhaps [...] there is an unconscious feedback loop using bite size to regulate the amount of flavour experienced,” said Dr de Wijk.

Previous research has shown the brain associates smaller bites with food that needs to be chewed more thoroughly, and can reduce how much is eaten in a single meal.

Understanding how altering the smell of food could fool the brain into believing the stomach is full would be a bonus for those trying to reduce their fat intake. Combined with healthy eating, it could even be worked into a plausible diet plan.

The team’s research has been published in the newly launched, open access journal, Flavour.

Reference

R. A. De Wijk, I. A. Polet, W. Boek, S. Conraad and J. H. F. Bult, Food aroma affects bite size, Flavour  (in press)

You can download the article from here: http://www.flavourjournal.com/content/1/1/3

Curcumin, found in turmeric, has been shown to prevent protein clumping in the brain. This clumping has been recognised as an early stage of Parkinson’s disease.

Scientists at Michigan State University have used lasers to watch proteins being rescued by curcumin, building on research released earlier this year into the mechanism of clumping.

“Our research shows that curcumin can rescue proteins from aggregation, the first steps to many debilitating diseases,” said Lisa Lapidus, co-author of the study.

Proteins are needed to carry out most of the work done by cells, and are built through a process known as folding. If the protein does not fold fast enough, it begins to clump and bind to other proteins around it. Curcumin not only stops this binding from happening, but speeds up the folding process, lowering the chances of it starting again. However, there is still more research to be done before curcumin becomes a routine treatment.

“Curcumin’s usefulness as an actual drug may be pretty limited since it doesn’t go into the brain easily,” said Professor Lapidus. “But this kind of study showcases the technique of measuring reconfiguration and opens the door for developing drug treatments.”

Curcumin is being currently investigated for possible benefits in various clinical conditions such as Alzheimer’s disease, and some types of cancer.

Reference:

B. Ahmad and L. J. Lapidus, Curcumin Prevents Aggregation in α-synuclein by Increasing the Reconfiguration Rate, Journal of Biological Chemistry, 2012.

You can find the original article here: http://www.jbc.org/content/287/12/9193.abstract

Anxious people have a heightened sense of smell, when it comes to sniffing out a threat, according to a new study by Elizabeth Krusemark and Wen Li from the University of Wisconsin-Madison in the US. The results of their study will be published online in the journal Chemosensory Perception.

The sense of smell is an essential tool for survival in animals. It allows them to detect, locate and identify predators in the surrounding environment. In fact, the olfactory-mediated defence system is so important in animals, that the mere presence of predator odours can evoke potent fear and anxiety responses.

Smells also evoke powerful emotional responses in humans. Krusemark and Li hypothesized that in humans, detection of a particular bad smell may signal danger of a noxious airborne substance, or a decaying object that carries disease. Also, they speculated that the level of response to the above could underlie phobias or anxiety related disorders.

The researchers tested their hypotheses by combining assessment of state-level anxiety, psychophysical testing, and functional magnetic resonance imaging (fMRI) techniques.  They recruited 14 young adult participants who were exposed to three types of odours: neutral pure odor, neutral odor mixture, and negative odor mixture. The participants were asked to detect the presence or absence of an odour in an MRI scanner. During scanning, the researchers also measured skin conductance response (a measure of arousal level), and monitored the subjects’ breathing patterns. After completing the odour detection task, the participants were asked to rate their current level of anxiety using a standardised clinical test.

The authors found that as anxiety levels rose, so did the subjects’ ability to discriminate negative odours accurately – suggesting a ‘remarkable’ olfactory acuity to threat in anxious subjects. The same pattern was found in the skin conductance results which showed that anxiety also heightened emotional arousal to smell-induced threats.

Krusemark and Li uncovered amplified communication between the sensory and emotional areas of the brain in response to negative odours, particularly in anxiety. This increased connectivity could be responsible for the heightened arousal to threats.

These findings could help researchers elucidate the aetiology of the unfortunate and debilitating symptoms that perpetuate anxiety disorders.

Reference:

Krusemark EA & Li W (2012). Enhanced olfactory sensory perception of threat in anxiety: an event-related fMRI study. Chemosensory Perception. DOI 10.1007/s12078-011-9111-7

You can find the article here: http://www.springerlink.com/content/a268t518p1x59v68/

A robotic jellyfish made of smart materials could be used in search and rescue operations, say researchers from Virginia Tech.

The tentacled creation, known as Robojelly, is made from a collection of materials that change shape or size to match their environment, held in place with carbon nanotubes. As well as its intelligent build, it could theoretically run forever – the clever cnidaria is powered entirely by hydrogen.

“To our knowledge, this is the first successful powering of an underwater robot using external hydrogen as a fuel source”, said Yonas Tadesse, the lead author of the study.

Robojelly is made from “shape memory alloys”, which are smart materials that remember their original shape. These materials are wrapped in carbon nanotubes and coated in platinum powder, which is the key to the fuel source. The platinum powder reacts with oxygen and hydrogen from the surround water and produces heat, which powers the robot’s movements.

Its swimming technique mimics that of a jellyfish – the “bell” chamber  fills with water, which then collapses, forcing the water out and driving the body forwards. In jellyfish, this is done with muscle contractions, but Robojelly makes use of heat produced by the fuel cell to transform its smart material body. However, although Robojelly has been successfully tested in a water tank, it’s not quite ready for service yet. Developers need to add individual controls to each segment of the robot, which will allow it to be steered in different directions. Until then, it can be seen in testing phase below:

Y. Tadesse, A. Villanueva, C. Haines, D. Novitski, R. Baughman and S. Priya, Hydrogen-fuel-powered bell segments of biomimetic jellyfish, Smart Materials and Structures, 21, 2012.

The paper can be found at: http://iopscience.iop.org/0964-1726/21/4/045013

Physicists were shocked last September when a paper published by the OPERA collaboration suggested that neutrinos in their detector in the Gran Sasso underground lab in Italy had been caught travelling faster than the speed of light. If correct, the result calls into question Einstein’s Theory of Relativity, and open the door to all sorts of weird and wonderful effects such as the reversal of causality and time travel. In fact, so perturbed were the researchers at the implications of their results, that they delayed publishing their findings for 5 months while they meticulously checked the experiment for errors, before finally concluding that they could do no more without the help of the wider particle physics community.

Unsurprisingly, interest has been huge, and as of today (February 26^th 2012) a search of the keywords ‘superluminal neutrino’ on arXiv.org yields 163 papers on the subject. However, despite the focused attention of some of the world’s top minds, until recently no mistakes in the experimental method or data analysis had come to light. Indeed, the OPERA collaboration repeated their experiment with a neutrino beam configuration that allows for more precise timing, and found the same effect. Many scientists still doubted the result though, and last December Ramanath Cowsik, professor of physics in Arts & Sciences and director of the McDonnell Center for the Space Sciences at Washington University in St. Louis, and his team of collaborators pointed out a glaring problem which had been overlooked.

Neutrino beams for particle physics experiments are produced in a three-step process that begins by accelerating protons to 99.9999991% the speed of light, in an accelerator such as the Large Hadron Collider at CERN in Switzerland. These ultra-relativistic protons are then smashed into a graphite target producing, amongst other debris, secondary particles called pions. Finally, these short-lived pions are focussed into a tight beam by magnetic horns before they quickly decay into a beam of neutrinos and charged sister particles of the electron called muons, each of which carries off some fraction of the total pion momentum. Finally a ‘beam dump’ at the end of the decay pipe stops all particles other than the neutrinos, leaving a pure neutrino beam.

The trouble is that in order to produce the high energy neutrinos observed at OPERA, the fraction of momentum carried off by the neutrinos needs to be less than about 0.05. This, in turn, implies that the decaying pions must have an extremely high momentum, and Einstein’s theory of relativity tells us that this very high momentum would extend the pions’ lifetime so much that they would not have time to decay in the beam pipe at CERN before smashing into the concrete beam dump.

“We’ve shown in this paper that if the neutrino that comes out of a pion decay were going faster than the speed of light, the pion lifetime would get longer, and the neutrino would carry a smaller fraction of the energy shared by the neutrino and the muon,” Cowsik says. “So we are saying that in the present framework of physics, superluminal neutrinos would be difficult to produce.”

Now, it seems as though Cowsik was right to be skeptical, as an email from CERN Director General Rolf Heuer to CERN staff last week announced that the OPERA collaboration had identified two possible sources of error in their neutrino velocity measurement. The first has to do with an oscillator used in the timing system of the experiment, and could only increase the size of the faster-than-light effect. The second, though, concerns a potentially faulty optical fibre connection that sends an external GPS signal to the OPERA master clock, and could serve to bring the velocity of the neutrinos back down to the sub-light-speeds physicists are used to.

The OPERA collaboration have fixed the problems and are now in the process of determining the effect they may have had on the results. New data taken with the repaired detector is expected in May, but for now scientists around the world are applauding the OPERA team for the open and transparent way in which they have reported their surprising result. In an interview for BBC News Sergio Bertolucci, director of research at CERN, said “One has to realise that the collaboration has never stopped to try to ‘kill’ the measurement (proving that it was erroneous)”. Even if the result turns out to be a false alarm due to loose wiring, the story has been a textbook example of good scientific practice.

The paper announcing the superluminal measurement can be found at:  http://arxiv.org/abs/1109.4897, whilst a preprint of Cowsik’s work detailing the problems raised by pion decay kinematics appears here: http://arxiv.org/abs/1110.0241v2.

Most (but certainly not all) questionnaires that are used in behavioural research undergo  testing for reliability, to check that they produce consistent results when applied to the same population over time. More importantly they are normally also tested for validity, to check that the questionnaire measures what it claims to measure. Such tests are done following the logic that the questionnaire should be able to discriminate participants in a similar way to relevant non-self report measures. For example scores on a questionnaire measuring depression should be able to discriminate between depressed patients and controls, while scores on a questionnaire measuring diet should be able to predict the ‘Body Fat Percentage’ of respondents with reasonable accuracy. While such tests can act to increase confidence that a questionnaire is measuring what it claims to measure they are not foolproof. For example just because a depression questionnaire can discriminate between patients and controls does not mean that it measures depression well, as the two groups will likely vary in several different ways. Likewise a questionnaire that distinguishes between patients and controls may not be able to identify the (presumably) more subtle differences between depressed and non-depressed healthy individuals, or the range of depressive tendencies within the healthy population. In fact that are a large number of reasons why questionnaire may not be entirely valid, including the following:

Honesty/Image management – researchers who use self-report questionnaires are relying on the honesty of their participants. The degree to which this is a problem will undoubtedly vary with the topic of the questionnaire, for example participants are less likely to be honest about measures relating to sexual behaviour, or drug use, than they are about caffeine consumption, although it is unwise to assume, even when you are measuring something relatively benign, that participants will always be truthful. Worse, the level at which participants will want to manage how they appear will no doubt vary depending on personality, which means that the level of dishonesty may vary significantly between different groups that a study is trying to compare.

Introspective ability – Even if a participant is trying to be honest, they may lack the introspective ability to provide an accurate response to a question. We are probably all aware of people who appear to view themselves in a completely different light to how others see them. Undoubtedly we are all to some extent unable to introspectively assess ourselves completely accurately. Therefore any self-report information we provide may be incorrect despite our best efforts to be honest and accurate.

Understanding – Participants may also varying regarding their understanding or interpretation of particular questions. This is less a problem with questionnaires measuring concrete things like alcohol consumption, but is a very big problem when measuring more abstract concepts such as personality. From personal experience I have participated in an experiment where I was asked at regular intervals to report how ‘dominant’ I felt. As I can honestly say I don’t monitor my feelings of ‘dominance’ and how they change over time, I know that my responses to the question were pretty random. Even if I could conjure an understanding of what the question was getting at, it would be impossible to ensure that everyone who completed the questionnaire interpreted that question in the same way that I did.

Rating scales – Many questionnaires use rating scales to allow respondents to provide more nuanced responses than just yes/no. While yes/no questions do often appear restrictive in terms of how you can respond, using rating scales can bring their own problems. People interpret and use scales differently, what I might rate as ’8′ on a 10 point scale, someone with the same opinion might only rate as a ’6′ because they interpret the meanings of the scale points differently. There is research which suggests that people have different ways of filling out ratings scales (1). Some people are ‘extreme responders’ who like to use the edges of the scales, whereas other like to hug around the midpoints and rarely use the most outer points. This naturally produces differences in scores between participants that reflects something other than what the questionnaire was designed to measure. A related problem is that of producing nonsense distinctions. For example studies sometimes appear where participants are given a huge rating scale to choose from, for example a scale of 1-100 to rate the confidence of a decision as to whether two lines are the same length (2).  Is anyone really capable of segmenting their certainty over such a decision into 100 different units? Is there really any meaningful difference, even within the same individual, between a certainty of 86 and a certainty of 72 in such a paradigm? Any differences found in such experiments therefore run the risk of being spurious.

Response bias – This refers to individual’s tendency to respond a certain way, regardless of the actual evidence they are assessing. For example on a yes/no questionnaire asking about personal experiences, some participants might be biased towards responding yes (i.e. they may only require minimal evidence to decide on a yes response, so if an experience has happened only once they may still respond ‘yes’ to a question relating to whether they have had that experience). Alternatively other participants may have a conservative response bias and only respond positively to such questions if the experience being inquired about has happened regularly. This is a particular problem when the relationship between different questionnaires is assessed, as a correlation between two different questionnaires may simply reflect the response bias of the participants being consistent across questionnaires, rather than any genuine relationship between the variables the questionnaire is measuring.

Ordinal Measures – Almost all self-report measures produce ordinal data. Ordinal data is that which only tells you the order that units can be ranked in, not the distances between them. It is contrasted with interval data which tells you the exact distances between different units. This distinction is easiest to define by thinking of a race. The position in which each runner finishes in is an ordinal measure. It tells you who is fastest and slowest, but not the relative differences between the different runners. In contrast the finishing time is an interval measure, as it provides information relating to the relative differences between the runners. Even when the questionnaire measures something that could be measured in SI units, and is therefore theoretically an interval scale (i.e. alcohol consumption) it is doubtful whether the responses can really be treated as interval because of the problems relating to response accuracy raised above. More pertinently most self-report measures in behavioural science relate to constructs, such a personality measures, that can’t be measured in interval units and are therefore always ordinal. The problem with ordinal data is not the data itself, but the common practice of using parametric statistical techniques with such data, because these tests make assumptions about the distribution of the data that cannot be met when said data is ordinal. Deviations from such assumptions can lead to incorrect inferences being made (3) bringing the conclusions of such studies into question.

Control of sample – this has become more of an issue with the advent of online questionnaire distribution sites like Survey Monkey. Previously a researcher had to be present when a participant completed a questionnaire, now with these tools the researcher need never meet any of their participants. While this allows much bigger samples to be collected much more quickly, it does cause several concerns over the sample make up. For example there are few controls to stop the same person filling in the same questionnaire multiple times. There is also little disincentive for participants to respond with spurious responses, and there is little control over how much attention the participant pays to various parts of the questionnaire. Conversely, from personal experience, I know that sometimes it is hard to complete these questionnaires because there is no way of asking the researcher for clarification as to the meaning of various questions. Finally as the researcher has lost control over the make up of their sample, they may end up with a sample which is vastly skewed towards a certain type of person, as only certain types of people are likely to fill in such questionnaires. These issues existed even before the advent of online data collection (e.g. (4)), but collecting data ‘in absentia’ exacerbates the size of such problems.

Although there are many problems with using self-report questionnaires they will continue to be a popular methodology in behavioural science because of their utility. While it might be preferable for every variable a researcher wants to investigate to be manipulated systematically using behavioural techniques, this is in practice impossible as it would severely restrict what each individual research design could achieve, and would make certain topics effectively impossible to research. Self-report measures are therefore a necessary tool for behavioural research. Furthermore some of the problems listed above can be countered through the careful design and application of self-report measures. For example response bias can be removed by ‘reversing’ half the questions on a questionnaire so that the variable is scored by positive responses on half the questions and negative responses on the other half, thus cancelling out any response bias. Likewise statistical techniques are being devised to attempt to pick out dishonest reporting, a problem that can also be attenuated by ensuring anonymity and confidentiality of responses (e.g. the researcher leaving the room when the participant is completing the questionnaire). Given this it would be wrong to dismiss any findings that are reliant on self-report measures. However whenever you read about research where self-report measures have been used to draw conclusions about human behaviour, it is always worth bearing in mind the multitude of problems associated with such measures, and how they might impact on the validity of the conclusions that have been drawn.

(1) Austin, E. J., Gibson, G. J., Deary, I. J., McGregor, M. J., & Dent, J. B. (1998). Individual response spread in self-report scales: personality correlations and consequences. Personality and Individual Differences, 24, 421–438.

(2) Balakrishnan, J. D. (1999). Decision processes in discrimination: Fundamental misrepresentations of signal detection theory. Journal of Experimental Psychology: Human Perception & Performance, 25, 1189-1206.

(3) Wilcox, R. R. (2005). Introduction to robust estimation and hypothesis testing. Academic Press. ISBN: 0127515429

(4) Fan, X., Miller, B. C., Park, K., Winward, B. W., Christensen, M., Grotevant, H. D., et al. (2006). An exploratory study about inaccuracy and invalidity in adolescent self-report surveys. Field Methods,18, 223–244.