Category Archives: Cognitive Psychology

Can a neuroscientist read your mind?

Posted on by
Reply

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

 

The dangers of self-report

Posted on by
2

A common methodology in behavioural science is to use self-report questionnaires to gather data. Data from these questionnaire can be used to identify relationships between scores on the variable(s) that the questionnaire is assumed to measure and either performance on behavioural tasks, physiological measures taken during an experiment, or even scores obtained from other questionnaires (some studies just report on the correlations between batches of self-report measures!). Self-report measures are popular for a number of reasons. Firstly they represent a ‘cheap’ way (in terms of both time and cost) of obtaining data. Secondly they can be easily implemented to large samples, especially with the advent of on-line questionnaire distribution sites such as Survey Monkey. Finally they can be used to measure constructs that would be difficult to obtain with behavioural or physiological measures (for example facets of personality such as introversion). This issue of self-report methodology is important because studies that use this method are regularly reported in the media (see http://www.bbc.co.uk/news/health-17209448 for a recent example) and therefore have a significant impact on how the general public perceive scientific research. I therefore think it is important to discuss potential problems with self-report measures.

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.

Humans as data sources!

Posted on by
Reply

I have recently begun collecting data for an experiment.  Data collection is the ‘bread and butter’ of science, without it there is no data, and therefore no results, conclusions or theories. While scientists can collect data from almost anything, as I am involved in behavioural science the data I require almost always comes from people; volunteers who agree to participate in an experiment. Using human participants (volunteers were previously referred to as ‘subjects’, but this term was dropped because it suggests that the volunteer is ‘subject’ to the experiment, rather than a willing participant) as your main data source produces additional (or at least different) problems to that presented from other data sources. I presume that in natural sciences, materials are ordered from a supplier, and therefore can be (hopefully) acquired to a predetermined timescale at a predictable cost. This is not the case with using participants, whose availability depends on the willingness of the local (normally student) population to submit to your study. Likewise whereas physical data-sources presumably perform reasonably consistently (i.e. putting the same quantity of lithium into the same quantity of water will always produce similar results, as long as other relevant variables are held constant) the same cannot be said for humans. The performance of two participants, tested under identical conditions, can vary drastically, even when the participants are from very similar backgrounds. Similarly an individual participant’s performance can vary widely during an experiment as concentration and motivation fluctuate. These factors produces a large amount of variance in the resulting data that is not due to the experimental manipulations the study is designed to investigate. The consequence of this is that the amount of data that needs to be collected in order to overcome such variance, and therefore provide a valid result, increases.

The variability in human performance also generates the further problem of generalisation. How can you be sure that the participants you have used in your study provide data that can be generalised to humans in general, given that individuals vary widely on how they perform the task? Larger samples (more data collection!) can make a sample more representative, but as undergraduates are usually the easiest source of data, inevitably most studies involving humans utilise samples that are non-representative of the general population to a greater or lesser extent. You could write an entire book on the issues around sampling and generalisation (indeed many have (1)) suffice to say that when you read any behavioural science research, especially that which is weighted towards the ‘social science’ end of the spectrum, it is worth considering the sort of people who may have participated in the research, and how that may effect the results that were found.

There are other, more basic problems with using humans as a data source.  Participants may fail to show up for the study, they may fail to understand what is required of them in ways that you couldn’t predict, they may even not take the experiment seriously, making little effort or deliberately producing nonsensical data. In physical science I suspect the main problem that can occur with an experiment is equipment failure. This is also a danger with behavioural experiments, but ‘participant failure’ is often a more pressing concern.

A final issue with using humans as a data source is that any study involving humans requires ethical approval, meaning that the research design is scrutinized by a committee prior to data collection for anything that might be deemed unacceptable. Ethical procedures are in place for a good reason, as in the past certain scientists were subjecting volunteers to all sorts of unpleasant and/or morally dubious procedures in the name of science (2). However perhaps inevitably ethical checks tend towards the cautious in terms of their application. While for many behavioural and social science research, ethical approval is merely a formality, it can restrict scientific enquiry for those of us that are interested in the facets of human behaviour that can only be evoked through manipulations of the participant’s emotional state or physical comfort.

So, given that I have just spent 700 words complaining about the problems of using humans as data sources,  why have I chosen a career path which relies so heavily on collecting data from humans? Well there are some advantages of performing research on humans. Most importantly humans are (to me at least) the most interesting subject in science. You can keep your chromatography, your mutagenesis and your particle accelerators, nothing they produce will ever be as interesting to me as investigations into human mind and behaviour. The variability in human performance which causes us so many problems is actually the main reason the subject of psychology is so interesting. A second advantage to behavioural research is that it allows you to meet a lot of different people who volunteer for your study for a variety of different reasons. The fact that certain people are prepared to give up their time and submit themselves to the often unpleasant or tedious tasks that make up your research project has helped reaffirm my faith in human nature after years of working in soul-destroying office jobs. Apart form anything else, the actual data collection part of a behavioural study certainly helps to break up a research process which would otherwise mainly consist of reading journal articles and staring at a matrix of numbers on a computer screen.

I’ll be coming to the end of the data collection process soon. I will then have weeks of grappling with the resultant data to look forward to!! As a final plea, if there are any men out there who fancy participating in my research then get in contact, as I still need a few human ‘data sources’ to complete my study!

(1) Rao (2000) Sampling methodologies with applications. Chapman & Hall
(2) See the early chapters of Naomi Klein’s book “The Shock Doctrine” (Penguin, 2008) for a description of some particularly unethical experiments performed in the US.

What is cognitive neuroscience, and why should anyone care?

Posted on by
2

I often have trouble explaining to people what I am doing for my PhD. This is not a consequence of the topic being so fiendishly complex that no-one else can understand it. Instead it comes from a fact that the area of study seems to fall between several difference subject areas. When I tell people that I am doing my PhD within the Neuroscience department I imagine this provokes images of test-tubes, microscopes and pipettes, and perhaps associations with genetics, animal testing and stem cells. In reality I have little knowledge or experience of any of these topics, having last done ‘traditional’ lab work while I was at secondary school. If you asked me to dissect something, I would probably run a mile! When I instead say that I work within the psychiatry department this probably brings up an altogether different set of images, of drug therapies, ECT and perhaps of ‘talking therapies’ such as CBT (cognitive behavioural therapy). In fact both the above statements regarding my PhD are true, as the Psychiatry department sits within the Neuroscience department, but neither appear to give an accurate impression of what I actually do.

The best description of my area of research is ‘cognitive neuroscience’, but what does this mean? Cognitive Neuroscience relates to the study of the neural basis of behaviour. Roughly, it bridges the gap between biological sciences, and behavioural sciences such as psychology and psychiatry. It attempts to determine how the brain achieves the legion of processes that it performs – crudely ‘what part of the brain does what’! Cognitive neuroscience has only been seen as a separate area of study relatively recently, partly because the advanced brain imaging techniques which the discipline now heavily relies on have only been developed within the last 30 years (according to Wikipedia the term ‘cognitive neuroscience’ itself was coined in the back of a taxi in 1979!!). However scientists from various disciplines have been trying to understand how the brain functions, using whatever methods were available, since at least the 19th century.

Cognitive Neuroscience relies heavily on work done within behavioural sciences, which have served to define how human behaviour and cognition can be classified into concepts that can be studied. Unsurprisingly therefore, cognitive neuroscience research normally involves the application of a behavioural task which has already been utilised without the use of brain imaging techniques. One question this raises is what does knowing how the brain achieves it function tell us that purely behavioural science does not?  Psychologists have been ably investigating the details of mental processes for well over a century without knowing (or even caring) what part(s) of the brain are involved. The knowledge that spatial processing is largely dependent on the Hippocampus is not necessary for studying the intricacies and individual differences in spatial processing. So what does an understanding of the neural basis of mental processes achieve?

Firstly understanding the neural basis of a mental process can help distinguish between different theories relating to how that process is performed. Behavioural data is often not sufficient to distinguish between competing theories (e.g. whether a particular process is performed in totality, or whether it is split into components processes that are dealt with separately, and whether such component processes are performed in parallel or in series). Neuroimaging data can be used to provide strong evidence in relation to these questions (1).  Secondly cognitive neuroscience can provide insight into areas of cognition that were difficult or impossible to address without neuroimaging techniques. For example much work has been done on trying to understand what the brain does ‘at rest’ (i.e. when no task is being performed, effectively ‘mind wandering’) which can allow us to understand how the brain might work as an self-contained integrative mechanism. As, by definition, non-task related mental processes can’t be manipulated systematically, it is hard to investigate these processes from a purely behavioural standpoint. Similarly neuroimaging has enabled scientists to begin to uncover the neural basis of ‘consciousness’, raising interesting questions about how our experience of the world is constructed (3). These achievements of cognitive neuroscience help elucidate the nature of human thought and behaviour, shedding light on why we act the way that we do. 

On a larger scale, understanding how the brain is able to processes such a large variety of information, and produce such a wide variety of responses, can help guide the design of artificial intelligence systems intended to mimic human abilities, facilitating advances in medicine and engineering. Finally, and perhaps most importantly, knowing how the brain produces certain responses can lead to the development of interventions to alter the functioning of the appropriate brain areas when those responses become problematic (e.g. during mental health disorders). One of the major aims of cognitive neuroscience is to identify the neural deficiencies that mark various psychiatry and neurodegenerative disorders. From this information it becomes potentially possible to identify methods of combating such deficiencies. Indeed biological interventions are being developed that can target specific brain areas, potentially offering great hope for improving the therapeutic treatment of mental disorders.  

References

(1) Jonides et al (2006). What has Functional Neuroimaging told us about the Mind? So many examples, so little space. Cortex, 42, 414-417

(2) Van den Heuval & Pol (2010) Exploring the brain network: A review on resting-state fMRI functional connectivity. European Neuropsychopharmacology, 20(8), 519-534

(3) Dehaene & Changeux (2011) Experimental and Theoretical Approaches to Conscious Processing. Neuron, 70. 200-225

Grabbing attention

Posted on by
Reply

 

 

There are certain things in the environment that grab our attention – loud noises, flashes of light and rapidly moving objects.

These are all reasons why we are likely to spot ambulances dashing towards us and mean that we can act in time to get out of the way.

However, there are also more subtle things that attract attention when we are surrounded by a more mundane environment.

Certain properties of the world are more SALIENT to our visual system than others.

These are: changes in colour (e.g. red to green); changes in contrast (e.g. sharp to blurred ); changes in intensity (e.g. bright to dim); changes in orientation (e.g. vertical to horizontal).

These are some of the reasons why human EYES are so effective in capturing attention – the iris is coloured, there is a sharp contrast between the pupil, iris and sclera and there is a change in orientation of the contrast boundaries around the eye.

In our environment there are often many other things that share these features that compete for our attention e.g. traffic signs, advertisements, bright clothing. As we look around some of the things we look at are influenced by this change in VISUAL SALIENCY.


When we look at pictures, we can break them down into their constituent properties. Below are two photograph and their associated VISUAL SALIENCY maps.

These maps can predict where you will look in a scene on the basis of visual saliency. The little “1″ on the maps above show the most salient point. The following 9 most salient points can be found by following the red line around the photos.

The model doesn’t get it exactly right as we are able to over-power these properties and CHOOSE to look where we want but when we first see pictures we are more likely to look at the salient regions, before we’ve got the gist of what is going on.



At Sheffield, we’ve recently published a paper which investigates whether people with autism and Aspergers look at scenes in the same way.

In the journal Neuropsychologia, we have shown that people with autism also show this bias for looking at salient regions when they first see scenes (Freeth, Foulsham & Chapman, 2011).

However, we also showed that both typically developing viewers and viewers with autism and Aspergers are more strongly drawn to looking at social aspects of scenes – the people – even when they are not “visually salient”.

This finding is very surprising as it was previously thought that people with autism wouldn’t be drawn to look at people.

However, there was also an important difference: participants with autism/Aspergers were significantly slower to look at people’s head and faces when they were looking at scenes than the typically developing participants.

It seems that the fast-track mechanism to attend to other people is absent in people who have autism/Aspergers.

Analysing Brainwaves

Posted on by
Reply

 

Everything we see, hear and touch is processed by our brains. Every time we experience something the neurons in our brains start to fire and emit little pulses of electrical activity. All of these millions of tiny neurons fire in a systematic way in big chains of networks. Different parts of networks communicate with each other so that we can interpret all of the complex stimuli that are entering our senses every second.

Of course, everyone’s brain interprets the world in a slightly different way but there are also many similarities. Understanding the processes that go on in the brain and how the networks of neurons work can help us to understand and predict behaviour.




One way of working out how all of these processes work is to measure brain activity by recording the electrical signals produced when neurons fire – when we are thinking. This can be done using electroencephalography (EEG) equipment. This technique involves wearing a big net of recording devices that measure the electrical activity that is going on in your brain. In Sheffield, we have state of the art equipment which contains 128 extremely sensitive recording channels. This technique is absolutely fantastic for working out the exact timing of the processes that go on in the brain. Recordings are typically taken 250 times each second. Now, just imagine how much data you get from 128 recording sites taking readings 250 times each second – phew! Thankfully, we have computer programs to process this data but even with our really powerful computers, some types of analyses may need to be run overnight.


Here are some examples of what electrical activity in the brain can look like. Certain things we do produce very distinctive signals. A big peak is usually produced by blinking. We can also usually see swallows or other small movements in the EEG signal.

 

We can also tell how alert someone is. If someone is nearly falling asleep they start producing a lot of alpha frequency signal (about 10Hz) which produces a very distinctive signal. If this happens, we know we’ve produced a very boring experiment!


The EEG studies that we are running at the moment mainly investigate different aspects of attention. We are looking at the brain’s very early response to seeing a new stimulus. We can see changes in brainwaves as soon as 0.1 seconds after things appear, if not before. We are also trying to understand how the brain puts together information about different features, such as colour and shape.


Here is an example of some data we recorded from one of our volunteers.

This is the average waveform produced from hundreds of trials recorded from site 62.

Below are scalp maps showing different time points in the trials

 


We are always looking for volunteers to participate in our studies to try to understand more about how the brain works. If you are interested in finding out more, get in touch and we’ll let you know if we have any studies suitable for you to participate in right now. The EEG lab at Sheffield is run by Dr Elizabeth Milne who also runs the Autism Research Lab. Other researchers in the lab are Dr Megan Freeth, Tom Bullock, Cigir Kalfaoglu and Mandeep Jabbal.

If you would like to participate in one of our studies, get in touch with us at the Sheffield Autism Research Lab.

When trying harder makes things worse

Posted on by
4

 Hi, I’m Lauren! I am a second year Psychology student at the University of Sheffield and I have just completed a summer placement here.


My project title has been “When trying harder makes things worse” and I’ve been investigating what happens to skill performance when you pay attention to what you are doing or how you are doing it. I’ve been looking at to different types of attentional focus:

 ’internal focus‘ is attention directed to body movements

 ’external focus’ is attention directed to the external environment

 

Previous research on this has primarily looked at how these types of attention impact on target sports, for example football which it topical considering the recent world cup! What is interesting about my project is that unlike previous research, I have investigated the effects on touch-typing.

To test how attention focus affected typing, we asked touch-typists to type two short stories. We measured their speed and accuracy and combined them into a single measure of ‘inefficiency’ (i.e. higher scores mean worse typing performance).

The first story typed is the control condition where participants were instructed to type the story as quickly and accurately as possible. The second story is the experimental condition where different instructions were given to participants, according to whether they were assigned to the internal or external focus group. Internal focus participants were instructed to not type with their left hand’s ring finger and external focus participants were instructed to not type the letters w, s or x.

The thing to notice about these instructions is that they both result in the same behaviour – participants were essentially given different instructions to carry out the same task. This is because the left hand’s ring finger types out the letters w, s and x. So the only thing varying between the groups was the focus of their attention, not what we were asking them to do.

The results were really interesting:

**We found that telling people not to use one of their fingers caused significantly greater disruption to performance than telling people not to use certain keys – even though this meant missing out the same letters i.e. focussing attention internally (to fingers) made people significantly worse than focussing attention externally (to keys)**

This is shown in the graph below. Notice that both experimental conditions were worse than the control conditions (the specific instructions made the task harder for everyone), but our analysis shows that the internal focus was significantly more difficult again than the external focus condition. For my first ever experiment, these are great results!

My results can be used to support the ‘constrained action’ hypothesis. This hypothesis states that an attempt to consciously control our body movement disrupts functioning of motor system. This occurs by interfering with automatic control processes. Previous research coincides with my findings and this theory. My project indicates that trying harder makes things worse is observable in touch-typing and not just target sports. All in all my project was a great success and proves that you do not need to necessarily try harder at the things you are already good at!

This project was supervised by Dr Tom Stafford and Cigir Kalfaoglu.


Further reading: Logan, G. D., & Crump, M. J. (2009). The Left Hand Doesn’t Know What the Right Hand Is Doing. Psychological Science, 20(10), 1296.

 

Studying Autism – why is research important?

Posted on by
Reply

Working with children and adults with Autism Spectrum Disorders

Doing research in the area of cognitive psychology can tell us a lot about how the brain works and which systems and areas of the brain are involved when we do different tasks. We try to work this out for people who are typically developing but it is also important to try to work out exactly how the brain – and the mind – works in groups of people who have a-typical development.

This means that we can better understand the similarities and differences in how people who have autism think compared to typically developing people. A better understanding provides a good platform from which it is possible to identify and harness strengths and build on weaknesses that people with autism may have.

Autism is a very important issue as it affects approximately 1% of the population.

 

At the Universtiy of Sheffield, we do a lot of work with people who have Autism Spectrum Disorders (ASD) in the Sheffield Autism Research Lab (ShARL). These people usually have a diagnosis of “autism”, “high-functioning autism” or “Asperger syndrome”. People who have a diagnosis on the “autism spectrum” can be really diverse. The range of abilities can go from maths geniuses and amazing artists to people that have a very low IQ and are not able to speak at all.

This picture was drawn by Stephen Wiltshire, an autistic savant artist.

 The similarities that all of these individuals share is that they have difficulties in 3 core areas – called the “triad of impairments”:

  1. socialisation

  2. communication

  3. imagination/repetitive behaviours

 At the moment there are no genetic markers or neurological tests that can be done to identify whether someone is on the autistic spectrum or not so diagnosis is based on behavioural criteria. This means that when someone is assessed to decide if they are on the autistic spectrum they are asked to complete an assessment throughout which their behaviour is monitored. An assessment that is widely used for this throughout the world is the Autism Diagnostic Observation Schedule

At Sheffield, one of our goals is to improve the reliability of diagnosis, especially for marginal cases. We aim to do this by finding out and understanding what the world looks like to those that have autism and to identify the sometimes subtle differences in the way they think and understand the world around them. Some studies that we run answer these types of questions by asking people to wear an eye tracking device whilst they explore their environment.

Another goal is to look for bio-markers of autism using EEG to study brain activity. In the future this should lead to improved reliability of early diagnosis. This work is being conducted in collaboration with our colleagues in San Diego.

Find out more about the work that we do here at Sheffield by visiting our website: Sheffield Autism Research Lab.

If you or someone you know would like to participate in our research see the taking part section of the website.

Cognitive Psychology – Blog 2

Posted on by
1

The Cognitive Capacities of Young Children

You may wonder why on earth we bother running research projects with young children in the Cognitive Psychology group. I mean, they can’t understand language in the same way that us adults do; they can’t keep their attention focussed on one thing for very long; they can’t resist grabbing things and blurting out answers before they’ve listened to all of the options they have to choose from…yet these are some of the reasons that doing research with young children can be so fascinating. These little people are developing skills day by day that we, as adults, take for granted.

In the Cognitive Psychology group at the University of Sheffield we study these developing ways of thinking and behaviours. Finding out how these systems develop and which abilities precede and follow others can give us great insights into the best way to teach children new skills. There is a bit of a blurred boundary between whether these projects are classed as “Developmental Psychology” or “Cognitive Psychology” but as long as we are answering interesting and important questions we don’t really mind what classification the projects are given. Perhaps we’ll just stick with “Cognitive Development”.

Dr Danielle Mathews – Researcher in Cognitive Development

Danielle is a lecturer at Sheffield and is currently working on a number of different projects but her main interest is how children develop their communication skills. Some of the things she is most interested in are:

        How children learn to tell people what they want or what they are thinking about

·        How children learn to understand what other people are talking about

·        What kinds of things parents can do to help children learn to talk

·        How children learn to combine words so they can produce their own sentences


Research in Focus – Blog 2

A research study that Danielle and her colleagues have got ‘in press’ in a journal called Developmental Psychology investigated how children aged 3 – 5 years understand how other people talk about objects. This study will

be published later this year. Here’s a summary of their research paper:

There are often many different ways we can talk about that same thing. For example, if we’re trying to mend my washing machine, we could call one of the parts ‘a silver tube’ or ‘a shiny cylinder’. It wouldn’t make much difference which expression we used, both mean more or less the same thing. But, if I start using one expression, say ‘the silver tube’, you’ll expect me to stick to that term for the rest of our conversation.  So we might have a conversation like this:

 ”Can you pass me the silver tube? OK thanks. Let’s try putting it in here behind the wire. Oh no that doesn’t work. OK take the silver tube out again and pass me the clip.. etc.etc.”

 In the course of this conversation we have built up a ‘referential pact’ – an implicit agreement to use the term ‘silver tube’. If I now asked you to pass me a silver cylinder you might assume I was talking about something else or get confused. The point is that it’s only because we’ve already ‘agreed’ to call something a silver tube that saying ‘a shiny cylinder’ is confusing. If another person came in to the room and said ‘Oh do you need this shiny cylinder?’  we wouldn’t find it surprising if they just happened to talk about our silver tube in that way.

 Studies have shown that adults are slowed down (by about 700 milliseconds) if the person they are talking to creates a ‘referential pact’ like this and then switches terms for no reason.  However adults are not slowed down if one person creates a pact and then a new person comes along and uses a different term. These studies show that adults have very good memory for who has said what to them before and they use this memory to create predications about what people say next on a millisecond by millisecond basis.

Danielle and her colleagues were interested to find out whether young children are also able to keep track of who has said what and generate predictions just like adults. They asked children to move toy objects around on a shelf and measured how long it took them to react to different names for each object. Just like adults, even 3-year-olds could remember who had used which terms before and were slowed down by almost two seconds when a person created a pact and then used new term was used for no reason.

 There were only two differences between adults and children. First children we slowed down for much longer than adults (about 2 second instead of 700 milliseconds). Second, children we’re slowed down a little even when a new person came along and used a new term.

 So although children have excellent memories for who has said what, they might assume that everybody will talk about the same things in the same way, regardless of when they joined a conversation. Learning about why different people might use different expressions just takes a lot of experience!


Cognitive Psychology – Blog 1

Posted on by
Reply

The Cog Blog

 

The Science Bit – What is Cognitive Psychology?

Cognitive Psychology is a branch of science that tries to understand the processes that go on in our brain. When we think, these processes combine together and enable us to perceive and understand the world effortlessly. As cognitive psychologists we treat the brain as one enormous information processing system that behaves in a highly predictable way. Each process can be broken down into constituent parts. We gain information on how these parts function by conducting experiments. We then put these bits of information that we have gained back together, with the aim of improving understanding of how the human mind works.

Who are we and what do we do?

The Cognitive Psychology research group at the University of Sheffield is a group of lecturers and researchers based in the Psychology Department. We work with both adults and children. We also work with clinical populations such as those with Autism Spectrum Disorders. We investigate the differences in the ways that people process available information in an attempt to make sense of the world around them.

Here are some questions that our research aims to answer:

·          How do we perceive colour and motion?

·           What captures and directs our attention in the environment?

·           How can we improve our hand-eye co-ordination?

·        Does too much information overload our ability to think clearly?

·        What makes some people good planners?

·        What stages do we go through before we make a decision?

 

How do we answer our research questions?

We have many tricks up our sleeves to try to get to the bottom of the questions we have, though from time to time certain bits of equipment that we have help us along.

One way of finding out about attention is to record what people look at while they are completing different tasks. We do this by tracing eye-movements using equipment such as this:

and this 

 A way of finding out exactly what is going on in our brains while we do tasks is by recording the electrical activity in the different parts. Some equipment we have here in the Psychology Department is fantastic for analysing the exact timings of this electrical activity. This technique is called electroencephalography (or EEG for short) and requires participants to wear rather stylish hair nets:

 

We’ll explain more about these bits of kit and some of the things we’ve found using this kit in future blogs.

 

Research in Focus – Blog 1

This blog’s “research in focus” is about a project that’s currently running called:

Action-Outcome Learning

The three researchers working on this project are:

Tom Stafford

Tom Walton


Martin Thirkettle                

           

Here’s a summary of what is going on from Martin:

Hi,

How do we learn complex and often highly nuanced motor actions? Everything from professional sports to snowball fights to simply changing gear when driving requires us to use environmental cues to guide our actions. Action-outcome learning is, as it sounds, the pairing of an event to the motor command that provoked it. At its heart is the understanding of a causal relationship between our bodies and the environment, but I like to think of it in terms of learning to make sure that next snowball finds its target.

Our current project is a part of a wider, European project called IM-CLeVeR (link here) which aims to produce robots which are able to learn autonomously and apply the skills they learn to novel situations. Learning in the most general terms is the use of a signal to refine an action or behaviour, and our contribution to the project focuses on how typical humans and patients with Parkinson’s disease learn and perform a novel motor action.

We already know that a sub-cortical area of the brain called the basal ganglia is deeply involved in this task, and working from this point we are studying both what it is about the environment and motor action that enables us to do this task, and how this area of the brain processes the necessary information. 

This means that we use a variety of actions and tasks to probe what can be learnt, and how patients with Parkinson’s disease, which affects the dopamine system in the basal ganglia, perform compared to typical performance.

My background is in visual perception so right now I’m looking into whether colour and luminance signals contribute differently to the learning of a joystick based task. Colour and luminance signals are processed independently by the visual system, and there is neurological evidence to suggest that luminance information has a much more direct path to the basal ganglia. By devising an experiment whereby success in a motor task is signalled by either a colour or luminance signal we hope to ascertain just how crucial direct input to the basal ganglia is to motor learning. This involves carefully designing and calibrating experimental stimuli to ensure that only the colour or luminance channel can access the success signal and means that day-to-day I’m usually to be found in a dark, windowless, room programming the specialised visual display system.

 

We hope you enjoyed this brief overview and insight into what we do. Our aim is to keep this blog updated regularly so you can find out more about what’s going on and the exciting discoveries we make.