Brain, n. An apparatus with which we think that we think

Elements of episodic memory

2012-01-11T11:48:00.000Z

Keen students of memorywill recognise that the title of this post is an homage to the seminal book ofthe same title by the great memory researcher, Endel Tulving. To my mind, Tulving’s Elements is one of thefinest books that has been written about memory, along with William James’s Principles of Psychology and Dan Schacter’s Searching for Memory. (It’s quite possiblethat Charles Fernyhough’s forthcoming Pieces of Light may soon join thatlist).

In Tulving’s book, he describeshow episodic memories of experienced events are unlikely to be stored as fixed,separate, discrete “memory traces”, but rather as “bundles” of features. It makes sense, given the enormous number ofevents we may have to remember over a lifetime, that our brains would haveevolved a more efficient strategy than simply storing each event separately, asa bound trace comprising all its different components. The redundancy would be huge. Instead, it appears that we store single representationsof features distributed around the brain which are then shared between differentevent memories via associative networks. Tulving acknowledges that “we have noidea about the number and identity of features that the human mind or itsmemory system has at its disposal” (p. 161). However, he speculates that “the features of the mind correspond todiscriminable differences in our perceptual environment and to the categoriesand the concepts that the language we use imposes on the world.” (ibid)

Tulving’s conception ofmemories as comprising associations between visual, auditory, and other sensoryfeatures of events, as well as representations of thoughts and feelings we mayhave had when experiencing them, has been hugely influential. Among the many reasons for this has been itsability to explain aspects of forgetting. One of the principal causes of forgetting from episodic memory appearsto be similarity between the features comprising different events. Our memories are very susceptible tointerference, either from previously-encoded events (so-called “proactive”interference) or from subsequent events disrupting earlier memories (“retroactive”interference). The extent to which thisinterference leads us to confuse different events depends, in large part, on howmuch the features of those events overlap, or are similar.

A simple but strikingway in which this can be demonstrated is the “release from proactiveinterference” effect, described by Delos Wickens. If participants are asked to remember astring of consonants, their memory diminishes as the list grows longer becauseof interference between the items. However, if the task involves remembering consonants for the first fewtrials and then switches to numbers, memory performance reverts to almostperfect levels.

The release from proactive interference effect

The release fromproactive interference effect can be generalised to many other sensory featuresof events, and even to more abstract features such as meaning. For example, a similar effect is observed ifthe first few trials comprise vegetables and then the stimuli switch to fruit (e.g.,“spinach”, “beans”, “potato”, “orange”, ...) A more recent experiment even found that the effect could be generalisedto TV news bulletins. Gunter andcolleagues asked participants to watch a series of TV news items before askingthem to recall the content of the stories they had just watched. If the news stories all related to home newsor all to foreign news, the typical effect of proactive interference wasobserved. However, if the fourth news itemwas a different topic to the others (home news followed by world affairs, forexample), release from proactive interference occurred (shown by the dashed line in the figure to the right).

Despite the prevalenceof such interference effects, typically we’re actually quite good atdiscriminating similar events from one another. Even when tasks are specifically designed to manipulate the extent to whichthe features of different events may overlap, people are often able to remembereach experience pretty well, without getting them confused.

It is this fascinating ability that we are exploring with our onlinememory experiment, in collaboration with the Guardian, which we have launchedthis week. We are hoping that thousandsof people will take part, and make this the biggest memory experiment ever.

Anybody can participateby clicking http://www.guardian.co.uk/memorystudy to go to the Guardianexperiment website and test their memory abilities for free from the comfort oftheir own homes.

Please do take part!

When the data are in, I’llreport back on what exactly the experiment was about, and what we found.

Gunter, B., Berry, C., & Clifford, B. (1981). Proactive interference effects with television news items: Further evidence. Journal of Experimental Psychology: Human Learning & Memory, 7 (6), 480-487 DOI: 10.1037/0278-7393.7.6.480

Wickens, D., Born, D., & Allen, C. (1963). Proactive inhibition and item similarity in short-term memory Journal of Verbal Learning and Verbal Behavior, 2 (5-6), 440-445 DOI: 10.1016/S0022-5371(63)80045-6

Why Jon Driver was an inspiration to me

2011-12-01T11:07:00.001Z

Jon Driver studied ExperimentalPsychology at Oxford before taking up a University Lectureship at Cambridge. Within eight years of obtaining his DPhildoctoral degree he was a Professor at Birkbeck, and from 1998 a Professor atthe UCL Institute of Cognitive Neuroscience (ICN), one of the world’s leading centresof research into the brain basis of cognition. He was Director of the ICN from 2004-2009, before being one of a smallhandful of researchers from all across the sciences to be selected for a prestigiousRoyal Society Anniversary Research Professorship in 2009. He died this week, tragically young at theage of 49, leaving a young family.

I never worked with Jondirectly, and wouldn’t say that I knew him particularly well. More comprehensive and better informedassessments of his life and career will no doubt be found elsewhere. However, the times I did spend with Jon weresufficient to leave a lasting impression on me, which is what I wanted toreflect on in these brief thoughts.

First of all, he was anexceptional scientist and an inspirational research leader. He published somewhere approaching 300 papersin all, including eight in Nature and Science during the first decade of hiscareer alone. Much of his work,particularly in those early years, was enormously influential, comprising thebuilding blocks on which fields such as visual attention, neglect, andmultisensory integration now stand. Itwas also often highly innovative, taking previously established ideas andturning them on their head with ingeniously designed experiments.

Here’s just one exampleof this that sticks with me as a non-expert in the field (apologies if realexperts think there are better examples). For a long time, it was thought that attention worked like a spotlight,roving around the visual field and selecting regions of space that might beworth processing further. Evidence frompatients suffering from the disorder of visuospatial neglect was consideredstrong evidence for this view. Suchpatients, who often have an injury to the right side of their brain, characteristicallyfail to attend to the left side of space. For example, they may not notice an object placed to their left or, inan example beloved of generations of undergraduates, may only eat the righthalf of a plate of food. Thus, the consensuswas that attention selects regions of space and attentional impairments arelikely to be spatial in nature.

Jon’s insight (and, asa non-expert, apologies if he may not have been alone in this) was that it’s surelynot that advantageous to attend to regions of space; what’s really useful is tofocus on the objects located in those regions. His brilliant way of demonstrating that was to take visual shapes thathad a clear principal axis (in other words, an obvious “right way up”) such asthose shown on the left of the figure below. Becausethe shapes differed on their left side, patients with neglect were unable tojudge whether they were the same or different. This was the standard finding, consistent with the idea of an impairmentattending to the left side of space. Jon’sbrilliant innovation was to then present similar shapes tilted by 45 degrees (as on the right of the figure). Now the shapes still differedon their left side, but critically the difference was located on the right sideof the patient. Strikingly, the patientsstill failed to detect differences between the shapes, demonstrating that attentionmust select objects and not just regions of space.

Examples of stimuli from Driver & Halligan (1991)

As inspirational as hiswork was, the main influence Jon had on me was more personal. I got to know him when I was the postdocrepresentative on the ICN group leaders’ committee during the early part of hisDirectorship, sometime around 2004. Hewas, to me at least, a slightly intimidating figure, even amongst the other scientificgiants who made up the group leaders at that time. He tended to speak in quite short, decisivetones during committee meetings, sometimes cutting people off if he disagreed with them, andoften failing to hide his displeasure at discussions that went on beyond whathe considered justified. He had somethingof a reputation as single-minded, determined, driving his people hard, and notsuffering fools gladly.

Thus, I was relativelysurprised when he and I spent quite a bit of time together early in hisDirectorship on an in-depth consultation of the junior research staff at theICN. Jon was very keen to find out whatthese individuals, who in many departments can feel rather undervalued andignored, thought and felt about the way the place was run. He worked hard and spent considerable timefinding ways to encourage the researchers to disclose the issues that botheredthem, and then took steps to address each of the concerns raised. When I asked him why he was spending so muchtime on this, he made a point that was very interesting to me. He said that he believed everyone had thepotential for greatness in them, if they were only challenged hard enough andthen made to feel they had all the support and resources necessary to achieve. Given that, as Director, he would only everbenefit very indirectly from work that might be done by a postdoc in a research group other than his own, I was very struck by his determination on this issue. I also know that when, some time after ourconsultation initiative, junior researchers went to Jon with academic issues orpersonal difficulties, he typically gave them considerable time and support inhelping them resolve their concerns.

So Jon made animpression on me in two ways: in his innovative and ingenious science, and inhis determination to see the greatness in others and to give them everyopportunity to achieve that greatness.

He was an inspirationalfigure and the field is significantly poorer for his passing.

The future of cognitive neuroscience

2011-09-15T17:06:00.002+01:00

I have previously written about how I think that cognitive neuroscience as a scientific discipline (and I know that this is not a universally held view) has largely moved on from publishing studies demonstrating the neural correlates of “x”, where x might be behaviours as diverse as maternal love, urinating, or thinking about god. There are still a few of these sorts of studies published each year, and because the public are, it seems, fascinated by stories about blobs on brains, the media portrayal of cognitive neuroscience tends to focus on such findings.

Some blobs on a brain

This is all very entertaining if you like your science presented to you in a breakfast TV sofa sort of way. However, the downside is that people who are not regular readers of the fMRI research literature think that the media portrayal of cognitive neuroscience is an accurate representation of the field. In fact, I would argue, this is far from the case. In my experience of working in cognitive neuroscience for the last decade or more, most researchers I have encountered are not interested in so-called “blobology”. Instead, they work very hard each day carefully designing theoretically motivated experiments using cognitive neuroscience techniques to produce empirical data that can be used to differentiate between cognitive theories about how functions like memory, language, vision, attention, and so on, might operate.

However, the field of cognitive neuroscience is still relatively young. As such, its accepted methodological and analytic conventions are still being worked out. There are some statistical methods that have been used quite widely in the field, but which people are starting to identify as not being sufficiently rigorous for the kinds of interpretations that have been made. The widespread use of these practices has happened mainly because new researchers have tended to learn fMRI methods informally through knowledge handed down by other researchers in the lab, who themselves will have learned from previous researchers, and so on, as there has been no standard textbook with a validated and generally accepted set of approved methods. Recent articles highlighting issues such as that it is usually inappropriate to use the same dataset for selection and selective analysis, and that interaction analyses are often conducted incorrectly, have served the very useful purpose of alerting neuroscience researchers to ways in which they might improve the rigour of their analytical methods.

As far as I’m concerned, these articles have been a thoroughly excellent contribution to the field, and a sign of a healthy, thriving scientific discipline that is willing to examine its core methods for possible weaknesses and, if they are found, to highlight them prominently. While it might seem odd that a field would allow a paper that does little more than count statistical errors in other papers to be published in the field’s flagship journal, I think it is splendid. Other fields should care as much about their time-honoured, adamantine practices.

It is a shame that some commentators see these articles as a sign that cognitive neuroscience is weak or inherently flawed or, as one prominent figure has described it, “the soft end of science... really just at the stamp-collecting stage. There aren't any real hypotheses, more just post hoc rationalisations.” These commentators have a tendency to dismiss the field of cognitive neuroscience with the disdain they usually lavish on areas like homeopathy, chiropractics and other such mumbo jumbo. I feel such views are narrow-minded, and reflect the personal prejudices of people who, if they really value science and wish to encourage those who seek to practice it with the most rigour they can, might like to reconsider their preconceptions.

I just today came across an article that, to me, is a prime example of the way in which cognitive neuroscience is constantly seeking to improve as an empirical discipline. Russ Poldrack, widely regarded as one the most sensible methodologists in the field, has a paper in press in the journal NeuroImage entitled “The Future of fMRI in Cognitive Neuroscience”. In the article, he outlines how over the next 20 years, the field needs to increase its methodological rigour, consistently use more robust methods for statistical inference, concentrate to a greater degree on identifying connectivity patterns across the brain rather than focusing on single regions, and make other improvements to the way in which theoretical inferences are drawn from neuroimaging data. This is an important paper, and all cognitive neuroscientists should read it. But I believe all commentators who are sceptical about cognitive neuroscience should also read it. It may change their view.

As Poldrack concludes:

fMRI has advanced cognitive neuroscience research in a way that has been nothing short of revolutionary, though at the same time there are fundamental limits to the standard imaging approach that have not been widely appreciated. I am hopeful that 20 years from now, the history of fMRI in cognitive neuroscience will show that the field attacked this problem head on and developed new, robust methods for better understanding the relation between mental processes and brain function.

I very much agree, and think that there is a good chance that Poldrack’s hope will be fulfilled.

Poldrack RA (2011). The future of fMRI in cognitive neuroscience. NeuroImage PMID: 21856431

(edited on 15/9/11 to include ResearchBlogging citation - thanks @deevybee!)

Exploring how the brain helps you keep a grip on reality

2011-05-27T23:52:00.000+01:00

This is based on a piece about our research that I was asked to write for a thing after recently being selected to receive the Experimental Psychology Society Prize. The EPS is one of the most venerable and respected learned societies in my field, and it was a real honour for our work to be recognised by them.

Whenever old friends get together, it rarely takes long for people to start reminiscing about the past. Amusing (sometimes, bawdy) tales might be told about events that may have occurred many years ago. As a listener, you can find yourself mentally transported back in time, re-living a fondly-remembered episode as if it were playing out in front of you once again. Except – how do you know that you were actually there when the event originally took place? How can you be sure that you’re remembering a faithful representation of what happened, as opposed to a fictitious recollection of an event that might have been entirely imagined? In short, how do we determine whether our memories are real?

We have spent the last few years pondering these questions, seeking answers by undertaking experiments using cognitive neuroscience methods like functional brain imaging of healthy volunteers and studies of neurological and psychiatric disorders, as well as of normal aging. Our aim is to understand how the brain supports our capacity to distinguish what is real from what we imagined, an ability that Marcia Johnson has termed “reality monitoring” which is vital for maintaining confidence in our memories, and in understanding ourselves as individuals with a past and a future. In characterising how these processes might be organised in the brain, we can better understand the way in which they may break down in disorders like schizophrenia, in which perceptions of reality can be altered.

View of brain showing
anterior prefrontal cortex

One brain area that has emerged as playing a key role in discriminating imagination from reality is anterior prefrontal cortex. This is a region right at the front of the brain, just behind your forehead. It is an area that, in relative terms, is roughly twice as large in the human brain as in even our closest non-human cousins, the great apes. It is thought to be among the last areas to achieve myelination, the neurodevelopmental process that continues into adolescence and enables nerve cells to transmit information more rapidly, allowing for more complex cognitive abilities. As such, although the functions performed by this area are not well understood, they have generally been considered likely to be among the “higher” levels of human complex cognition.

In the field of memory research, scientists sought to use functional brain imaging techniques to identify brain areas that were active when people undertook complex memory tasks like recollecting the context in which previous events were experienced, but found it difficult to characterise what role anterior prefrontal cortex might play. Some studies reported memory-related activation there whereas other, equally well conducted, apparently very similar studies failed to identify activity in that region. We hypothesised that the discrepancy between studies might be because the kinds of information participants were being asked to remember differed according to whether it had been generated by internal cognitive functions such as thought and imagination, or derived from the outside world by perceptual processes.

Anterior prefrontal cortex (L)
contributes with areas like the
medial temporal lobe (R)
to reality monitoring

In the last few years, we have tested this hypothesis in a number of experiments. We have shown, for example, that activity in anterior prefrontal cortex differentiates between stimuli that were previously seen or merely imagined. To demonstrate this, in one experiment we presented volunteers either with well-known word-pairs like “Laurel and Hardy” or with the first word of a word-pair and a question mark (“Laurel and ?”). In the latter condition, participants were instructed to imagine the second word of the word-pair. Later, we scanned participants’ brains using functional magnetic resonance imaging (MRI) while they tried to remember whether they had seen or imagined the second word of each previously-encountered word-pair. A number of brain areas showed activity that could be related to general memory retrieval processes. But the one region consistently to emerge across a number of similar experiments from our laboratory and others as contributing to the distinction between seen and imagined information has been anterior prefrontal cortex.

One of the applications of this work has been to inform understanding of the cognitive dysfunction seen in clinical disorders, such as schizophrenia. Although schizophrenia can vary in its presentation, among the positive symptoms often observed are hallucinations, whereby patients report, for example, hearing voices when none are present. It has been suggested by Chris Frith and others that these symptoms may result from a difficulty in discriminating between information that is perceived in the external world and information that is imagined. For example, you might imagine a voice conveying a message, but misattribute that voice as real, coming from another person.

Regions involved in reality monitoring
overlap with areas dysfunctional
in schizophrenia

We have tested a number of the predictions that arise from this suggestion. First, individuals with schizophrenia are impaired on the kinds of seen vs. imagined memory tasks that we have shown to elicit anterior prefrontal cortex activity. Second, the anterior prefrontal area we have identified overlaps closely with an area that is among those that tend to be functionally disrupted in schizophrenia. Third, healthy volunteers who exhibit reduced levels of activity in this region tend to make more of the misattribution errors typically observed in schizophrenia, mistakenly endorsing imagined items as having been seen. Finally, colleagues in San Francisco have shown that patients with schizophrenia exhibit reduced activity in anterior prefrontal cortex during performance of reality monitoring tasks.

Thus, although there is much work to do before we can claim to understand the functions supported by anterior prefrontal cortex, evidence is mounting that one of its key roles may be to help us keep a grip on reality.

Update on exercise and memory story

2011-04-20T12:26:00.012+01:00

A few months ago, I wrote a blog post in response to a “pre-arranged” submission by Kirk Erickson and colleagues to Proceedings of the National Academy of Sciences (PNAS), which purported to find evidence that moderate exercise leads to substantial improvements in memory. The article in question received a great deal of media attention, with big claims being made that older adults, who tend to be worried about declining memory abilities, might be able to hold off the effects of old age on memory with a simple exercise regime.

Unfortunately, when the data were looked at more closely, it was clear that the picture was more complicated. For one thing, although the experimental group that performed exercise for one year did show a 2.3% increase in memory score, a control group who did not perform the exercise showed a 3.7% increase over the same period. In other words, the exercise group did not show any increase in memory performance relative to the control group.

When I published this blog post, there was quite a bit of correspondence over Twitter, and Susan Krauss Whitbourne wrote a follow-up article that included an interesting interview with one of the authors of the experiment, defending the findings.

Now, Robert Coen and colleagues have published a letter in the same journal as the original article, PNAS, arguing strongly that the Erickson memory results are flawed. As they say:

Contrary to both the title and abstract, there is virtually no evidence in this article that exercise improved memory. After 1 y there were no differences between the exercise and control groups.

They go on to argue that “both the title and abstract are misleading and a major overstatement of the findings.”

For those not used to the usually fairly genteel nature of published academic debate (as opposed, perhaps, to the occasionally more robust discussions during conferences), the wording used by Coen and colleagues in their letter is very strong and represents quite a rebuke.

Erickson and colleagues have written a reply to Coen’s letter in which, to all intents and purposes, they acknowledge the charges brought. As they say: “We agree that the title and abstract could have been clearer on the lack of a difference between the groups in terms of spatial memory performance.”

They go on to suggest the possibility that brain regions other than the one they focused on in the original article, the hippocampus, might have contributed to the effects reported.

Erickson et al. also make the extraordinary point that “our study was not conducted in a vacuum, and our results are consistent with other research on the effects of exercise on memory.”

In other words, they appear to be saying that it’s ok to overstate your results if the effects you erroneously claim to have found are consistent with previous research.

This is simply not good enough. Scientists often moan about how their cautiously-phrased, carefully-caveated journal article has been over-simplified and their findings misrepresented and sensationalized by journalists and the media. In this instance though, as I wrote in my previous blog post, the obscuring of the true nature of the findings seems to have been attributable to the way the scientists concerned chose to write them up in their paper.

As Coen and colleagues conclude in their letter, "it behooves us all to ensure rigor in our scientific reporting."

I couldn’t agree more.

(thanks to @markgbaxter for bringing the PNAS letters to my attention)

State-dependent memory: Remembering Heather Graham's phone number

2011-04-01T12:38:00.014+01:00

A few days ago I gave a talk at the Cambridge Memory Film Festival 2011, introducing some of the scientific themes raised in the Hollywood comedy, The Hangover. A couple of people were kind enough to suggest that I should write up what I said, so what follows is a brief summary.

“Why is there a tiger in the bathroom?”

The basic idea of the film is that Doug and a group of his best friends are in Las Vegas drunkenly celebrating the fact that he is soon to be married. The next morning, Doug’s friends wake up in their hotel suite with no memory of the previous night, and soon realise that Doug is missing. Furthermore, there is a baby in the wardrobe, a tiger in the bathroom, and a chicken is wandering around the suite. Hilarious consequences ensue.

The memory-impairing effects of alcohol are a staple topic for light-hearted treatment in popular culture, probably because most people can relate to the notion of waking up after a night on the tiles, not entirely sure about their recollection of everything that transpired. In psychology, this phenomenon is termed state-dependent memory.

One aspect of state-dependent memory, and the idea that the plot of The Hangover is based on, is that if you experience an event in one physiological state (e.g., drunk), your memory for the event is likely to be impaired if you later try to remember it in another physiological state (e.g., sober).

A further aspect of the phenomenon can be illustrated by imagining another scenario. Imagine that last night you were out drinking with your friends, and you happened to strike up a conversation with the Hollywood actress, Heather Graham (or, if you prefer, the Hollywood actor, Brad Pitt). (This sort of scenario occurs quite often in Cambridge, incidentally. Feel free to apply to work with us here).

You vaguely remember Heather (or Brad) leaning over to you at one point in the evening and whispering her (or his) phone number in your ear. The next morning, you wake up feeling terrible, but remember the conversation and decide that you must immediately call her (or him). However, of course, you cannot now for the life of you remember the number. The key question is this: Will you be more likely to remember the number, and save your chances of a date with Heather (or Brad), if you drink a whole lot more alcohol?

The evidence

Believe it or not, despite the fairly limited likelihood of the average psychologist ever needing to know how best to remember Heather Graham’s phone number, there are hundreds of studies out there that have investigated the issue. One of the first was by Donald Goodwin and colleagues, published in Science in 1969, who asked male volunteers to perform memory tasks that involved learning and remembering words while either sober or under the effects of alcohol.

Data from Goodwin et al. (1969)

As displayed in the figure, Goodwin et al. found, as would be expected, good retention of the words if the volunteers had been sober at learning and sober at recall. Perhaps unsurprisingly, if volunteers were sober at learning but drunk at recall, their memory was relatively impaired. And, as illustrated in The Hangover, volunteers who were drunk at learning and sober at recall were also amnesic.

The really interesting finding was that the group of volunteers who were intoxicated at learning (and we’re talking a mean of 111 mg of alcohol per 100 ml of breath, or roughly 3 times the UK drink driving limit), and were similarly inebriated during the retention test, nevertheless recalled a comparable amount to those who had been sober on both occasions. As Goodwin et al. concluded, the results indicated “that learning which the subject acquires while he is intoxicated may be more available to him while he is intoxicated than when he is sober.”

This striking result encouraged a whole assortment of follow-up studies, seeking to determine whether the effect of alcohol on memory could be generalised to other physiological states. Just to take a few examples, Kelemen and Creeley showed that drinking coffee at learning and recall led to just as good memory as drinking a placebo drink on each occasion, both of which were significantly better than if there was a change of drink between phases. Kenealy demonstrated similar results by playing music to volunteers to induce a happy or sad mood at learning and recall. In a famous study, Godden and Baddeley showed that the same effect could be elicited in deep sea divers who learned and subsequently tried to recall information either on land or 20 ft under water. Finally, Grant et al. found that noise while studying might not subsequently impair memory if testing occurred in a noisy environment, but that if, for example, an exam was to take place in a quiet exam hall, revising with music or other noise in the background might not be the most sensible policy. You can find other tips from psychology research for effective exam studying in my previous post here.

What’s going on?

To explain these phenomena, Endel Tulving proposed the Encoding Specificity Principle, according to which memory performance depends on the similarity between the information comprising a memory trace and the information available at recall.

The encoding specificity principle

When we are encoding an event into memory, the memory trace is made up of details about the event (who was there, what they said, etc), but also of the context in which the event occurred. Context in this sense is a broad term, encompassing elements such as where and when the event happened, who else was there, and also thoughts and feelings we had while experiencing the event. These internally-generated thoughts and feelings are likely to be influenced by many factors. For example, was it dark or light, warm or cold, noisy or quiet, were we happy or sad, drunk or sober, etc. All these elements are bound together to form the memory trace relating to that event.

What Tulving realised was that this isn’t the whole story, however. According to the encoding specificity principle, the context we are in when we try to retrieve a memory can also have a substantial impact on our likelihood of successfully accessing the correct memory trace. Specifically, the chances of retrieval success are directly determined by the overlap between the encoding and retrieval contexts. Thus, bizarre as it may seem, if we are drunk at encoding, our subsequent memory will be more successful if we are also drunk at retrieval.

Data from Park & Rugg (2008)

Brain imaging evidence from Park and Rugg supports the notion that memory performance depends, at least in part, on the overlap between processing operations at encoding and retrieval. They had participants learn everyday objects (e.g., apple) that were presented either as words or as pictures of the objects. At test, participants were asked to distinguish between studied and non-studied items. Each studied item was presented in a form that was either congruent (e.g., word at study and test) or incongruent (e.g., word at study, picture at test). Park and Rugg found that the highest memory success occurred in the congruent conditions, and was associated with overlap between the brain areas activated during learning and retrieval.

Memory as a reconstructive process

What this all means is that it’s not just what’s happening during the encoding of a memory that determines what we remember of an event. Our memories can be influenced greatly by factors at the time of retrieval. In this way, as William James noted over a century ago, memory “retrieval” is something of a misnomer. Remembering an event is not like picking a DVD off the shelf and re-playing it, but involves a reconstructive process. We store assorted sensory elements of an event, but to experience the subjective “re-living” of that event, we must construct a narrative structure at the time of retrieval that incorporates all the stored elements in a plausible, satisfying way.

The fact that this narrative construction occurs at retrieval, and is thus subject to influence from our biases and expectations at the time of retrieval, is supported by a great deal of experimental evidence. Among the most famous is a series of studies by Elizabeth Loftus, who investigated the effect of leading questions on eyewitness testimony. She had participants watch films of various crime scenes, such as a car accident, and then asked them to recall details of the event. She found that the form of the question could have a considerable influence on the way the event was remembered. For example, if participants were asked “How fast were the cars going when they smashed into each other?”, they recalled the speed as significantly faster than if the word “contacted” was used instead of “smashed”.

For more on the nature of reconstructive memory, see this excellent blog post by Mo Costandi.

The implication of this, though, is that if you and some friends do decide to try to remember what happened last night by getting drunk again the next morning, there is a good chance you will all remember it differently.

Update on neuroscience funding

2011-02-22T11:50:00.006Z

I wrote last week about a series of recent funding body announcements that have left UK scientists (especially those in the neurosciences, but many others too) feeling very worried about the future. For example, in addition to the recent closure of a number of pharmaceutical company neuroscience research facilities, a previously major funder of basic cognitive neuroscience research, the BBSRC, announced it was re-prioritising its funding away from neuroscience. Even more concerning for the future of the field, several funding schemes aimed particularly at early-career researchers have recently been overhauled in a manner that, I argued, seemed to significantly reduce the ability of a new researcher to establish a neuroscience research group.

Even if some of the reports turn out not to reflect accurately the changes that have been made, these recent developments have caused a great deal of concern amongst researchers. As a result, it has been particularly welcome to see announcements and comments in the last few days from another major research council whose remit includes neuroscience, the MRC.

In a statement on 11 February entitled, “Setting the record straight on neuroscience funding,” Declan Mulkeen, director of research programmes, said that “neuroscience is a key feature in both the MRC’s strategy and delivery plan.” Some large-sounding sums of money apparently available for funding neuroscience research were quoted:

Neuroscience research received more than £123 million in 2009/10 from the MRC – and recently we have also committed a further £24m of investment for initiatives to boost neurodegeneration and mental health research.

One concern some neuroscience researchers have had about the MRC in recent years has been the move towards what has sometimes seemed to be an exclusive focus on so-called “translational neuroscience”, research that has direct and obvious applications to patient care. This shift has meant that it has not been clear whether the MRC has still been interested in funding basic, “blue-skies” neuroscience research.

Thus, comments in an interview with Times Higher Education reporter Paul Jump last week from the MRC chief executive, Sir John Savill, are very welcome. Tackling the concern about basic science head-on, Savill said that “blue-skies research is an important part of our activity because it is where the best ideas come from.” The move towards translational neuroscience was not, he argued, “a shift of emphasis: it is about having resources to do both (basic and applied research).”

Even more encouraging to see were comments indicating that Savill is aware of the need for greater support for early-career scientists who, as I discussed in my last post, are the most vulnerable and yet have been hit particularly hard by recent funding developments. The THE article mentioned that the MRC’s delivery plan published last month identified as a priority the need to boost the success rates of early-career researchers applying for grants:

To this end, Sir John thinks that rather than rejecting their applications outright, the MRC might "pump-prime" their ideas with a small short-term grant; combined with feedback, this would "allow them to come back in a stronger position to apply for a full grant".

It will be interesting to see whether these warm words are reflected in new funding schemes aimed at early-career researchers, or official policies put in place to provide small grants that might allow such researchers to collect the kinds of preliminary data that would strengthen future applications. In the meantime, it is at least reassuring to hear that neuroscientists at the start of their careers haven’t been entirely abandoned by the research funding community.

Is there a cognitive neuroscience funding crisis?

2011-02-14T10:16:00.003Z

When I started my lectureship (a position equivalent to assistant professor in the US system) way back in the good old days of 2007, one of the first things I had to think about was how to begin building a research group. My research interests are in understanding human memory using cognitive neuroscience techniques such as neuropsychology (studying the way memory is disrupted following brain damage or dementia) and neuroimaging (studying the brain areas that are particularly active while remembering). We are seeking a greater understanding of the way in which different memory processes are organised in the brain, as a means to determine how these processes might be preserved or impaired in neurological and psychiatric disorders.

Cognitive neuroscience often generates great excitement in the media and the public in general. This is apparent most obviously in the genuine fascination people have with seeing where in the brain “lights up” during a particular kind of behaviour. Perhaps somewhat less evident in the media, but still captivating to many who hear about it, are the many strange and wonderful examples of altered behaviour following brain injury or stroke. Indeed, it was through hearing vivid descriptions of neuropsychological behaviours from an inspirational undergraduate lecturer that I became hooked on the area as a student. Another reason perhaps for the great interest in cognitive neuroscience in this country is that the UK is very good at it. Considering the disparities in funding and resources compared with the US, for example, the UK is right up there among the world leaders in the field no matter which measure you choose. Just as one example, two of the top five (and three of the top ten) most highly cited scientists in the field work in the UK.

Cognitive neuroscience is still a relatively young field, but has – it seems to me at least – largely now moved on from the days in which studies demonstrating “the neural correlates of x” would always generate great excitement. Such straightforward studies can still be published, and can sometimes be interesting. However, researchers are often now more interested in using cognitive neuroscience techniques to inform the development of cognitive theories and to better understand cognitive disorders. Thus competency with the technically demanding methods of functional MRI, for example, needs to be coupled with the ability to design and implement cognitive paradigms that address closely the function of interest, allow theoretically motivated variables to be manipulated while others are controlled, and permit inferences that can be used to differentiate between competing cognitive hypotheses about how that function operates.

Building a group in which such multidisciplinary skills are represented is not straightforward, and gaining access to the methods (whether functional MRI scans of brain activity in healthy volunteers, or structural MRI scans of lesion locations and volumes in patients) does not come cheap. Thus, in 2007, I was very aware that I needed to apply for research funding. Back then, there were three main categories of funding body that I felt might be interested in funding cognitive neuroscience research:

Research Councils – the MRC (medical research), BBSRC (biotechnology and biological sciences research), and to a lesser extent, the ESRC (economic and social research)
Charities – primarily the Wellcome Trust, although also bodies such as the Alzheimer’s Research Trust
Industry – mainly pharmaceutical companies interested in funding cognitive neuroscience research that might advance drug development

As such, in addition to writing new lecture courses and trying to do some cheap experiments (often thanks to the help and generosity of colleagues and former advisors), I spent the first couple of years as a lecturer writing grants. In submitting applications and seeking opportunities in each of the three funding categories above, I was helped a great deal by the advice and support of senior colleagues in my department and elsewhere. In addition, many of the funding bodies interested in cognitive neuroscience had schemes particularly suited to early career researchers, such as small grant schemes and young investigator awards. It never seemed easy, and I was prepared for the fact that a very small proportion of my applications might be successful, but I did at least feel that there were a number of places I could go to seek funding.

Now, however, the funding landscape for cognitive neuroscience research seems to have changed considerably.

In the last couple of years, a number of major pharmaceutical companies have closed their neuroscience research and development facilities. In addition, perhaps anticipating a cut in the government funding of science research that never materialised (in no small part thanks to the “Science is Vital” campaign), many of the charities and research councils revamped their funding schemes. These overhauls were announced as measures “to better reflect strategic priorities”, but the result seems to me to be a significant reduction in the funding opportunities available to early career investigators in cognitive neuroscience.

To give a few examples:

The ESRC recently announced the closure of its “small grants” scheme, which provided limited sums particularly suited to allowing early career researchers to develop paradigms and collect preliminary data that could be used to strengthen applications for larger grants in the future.

The Wellcome Trust has ended its project grant and programme grant schemes, the former of which provided the kind of support (one member of staff and research costs for three years) that was ideal as a first substantial grant for someone building their group. Instead, the Trust has replaced these schemes with investigator awards, aimed at “exceptional individuals” who “have been lead investigator on at least one significant research grant from a major funding body”.

Finally, as seen in all the papers and discussed on BBC Radio 4’s Today programme in the last few days, the BBSRC announced that it was “reprioritising” its funding away from neuroscience. This was reported as a complete axing of the council’s neuroscience budget, and possible closure of up to 30 research groups. However, after admitting an error in one of its media briefings, the BBSRC clarified that the changes would “only” mean a reduction of perhaps 20% in the funding directed at neuroscience research.

These developments mean that it is much more difficult to see how a new lecturer can build a cognitive neuroscience research group now. Many of the schemes directly aimed at those early in their career have either been axed or shifted to support individuals who have already led a research grant. But how are you supposed to develop the track record of having led a research grant if nobody will fund you before you have that track record?

Also, despite cognitive neuroscience being one of this country’s major science success stories in recent years, internationally competitive when compared against even the finest and best funded groups in the US and elsewhere, there is a concern that many of the UK funding bodies seem to be intent on moving away from funding cognitive neuroscience research. The recent move by the BBSRC, coupled with a shift by the MRC over the last few years to prioritise translational neuroscience research that has direct and clear applications to patient care, means that it is not clear which of the research councils now sees basic cognitive neuroscience research as within its funding remit.

Is there a cognitive neuroscience funding crisis? There is undoubtedly still a lot of money on offer: the MRC alone funds over £100 million of research in the general area of neuroscience. However, the perception among cognitive neuroscientists is that a very difficult situation has recently become much harder (David Colquhoun has mentioned that only around 7% of neuroscience and mental health grant applications were funded by the MRC in the most recent round). This is not helped when funding bodies announce changes, which may turn out to be relatively minor reprioritisations, in a way that lead to sensational media headlines about the “disastrous impact” of “draconian funding cuts”.

As a result, this is a worrying time to be a cognitive neuroscience researcher, but it is particularly concerning that the crucial first few rungs on the funding ladder for new researchers seem to be those most under threat. It is obvious that new researchers are the most vulnerable and in need of support in developing their research careers. If such individuals feel that the UK funding bodies are making it simply impossible for them to do that, they will either go abroad or leave science completely. And if that happens, a cutting edge field in which the UK has been one of the world leaders within only the last few years, will face a future of rapid and inescapable decline.

Exercise may be good for you, but it doesn’t boost your memory

2011-02-01T17:52:00.009Z

“Moderate exercise such as walking boosts memory power” claims the BBC.

“Exercise in middle age can improve your memory” says the Daily Mail.

“Older adults improve memory through exercise” reports CNN.

“Want to improve your memory? Take a walk” invites Time.

These are just some of the many headlines today resulting from the publication of a paper in Proceedings of the National Academy of Sciences (PNAS) entitled “Exercise training increases size of hippocampus and improves memory”, by Kirk Erickson from the University of Pittsburgh and colleagues from the University of Illinois. You can access the abstract of the article here, although you may need to pay to read the whole paper.

The authors of the article have provided helpfully excited quotes in many of the news stories. For example, senior author Art Kramer, from the University of Illinois, was quoted as saying “even modest amounts of exercise ... can lead to substantial improvements in memory.” Exciting findings indeed!

In the study, 120 older adult volunteers were randomly assigned to an aerobic exercise group or a stretching control group. Participants in the exercise group undertook supervised sessions of moderate intensity walking for 40 min each day, three days per week for one year. Those in the stretching control group were trained in various stretching and muscle toning exercises over a similar period. At the start, middle and end of the intervention, structural MRI scans were obtained, and participants undertook a computerized spatial memory task.

The MRI scans revealed that volume of the hippocampus, a brain area known to be important for spatial memory, increased by around 2% in the exercise group participants over the one-year period. Hippocampal volumes of participants in the stretching control group diminished by around 1.4% over the same period, as would be expected through age-related decline.

However, as illustrated by the headlines above, minor increases in volume of a brain structure with exercise appear to be less newsworthy than the suggestion that such exercise might “boost memory power”. A common worry among older adults is that forgetfulness, which may seem to be increasingly pervasive as years go by, will eventually result in the loss of their precious store of memories. If exercise really could “boost memory”, and potentially alleviate age-related memory decline, this would indeed be big news. Thus, it is this claim that is worth looking at more closely.

Unfortunately, to find the data on this issue, one has to study the paper very closely indeed, because the authors have not made it particularly easy to locate. However, buried in the text of the results section and in one row of a complex data table, one can read that the exercise group did indeed show increases in memory performance over the year period, going from an average score of 85.9% at the start of the intervention to 88.2% after 12 months, a 2.3% mean difference. However, the suggestion that the exercise regime was responsible for this “memory boost” is rather undermined by the observation that the stretching control group showed a 3.7% mean increase in their memory performance over the same period.

In other words, the exercise group did not show any increase in memory performance relative to the control group. Both groups showed similar small increases in spatial memory scores over the three testing sessions, which may be attributable to the well-known beneficial effects of practice when performing the same task repeatedly.

The fact that memory performance in the exercise group was no different to that achieved by the control group is a critical flaw in this study, and severely undermines the claims made throughout the paper, from the title onwards, that exercise training boosts memory. For example, in the abstract the authors state that “exercise training ... is accompanied by improved memory function.” Notably, in the abstract, discussion and main figures, no mention is made of the statistically identical memory boost in the control group. Indeed the main figure only displays memory data from the exercise group, “because it was the only group that showed an increase in volume across the intervention”, according to the figure legend. Why not show the data from both groups? Presumably because the control group’s data would reveal a negative correlation between hippocampal volume and memory scores, weakening the authors’ claims considerably.

Thus, this appears not to be a story about misrepresentation of research by journalists, although there is much evidence that such errors do occur. Rather, it seems to be an example of the scientists involved in the research “talking up” their findings for the press and even, perhaps, obscuring the true nature of the results in the journal article.

One can also question the quality of the peer review and editorial control process in a journal that published such obviously flawed research. It is worth noting that the article states that it “had a prearranged editor”, in this case Fred Gage from the Salk Institute. There have been a number of previous discussions about the quality of the research published in PNAS (see e.g., here), mostly relating to a former article submission method, in which members of the National Academy of Science (NAS) could “arrange” publication of papers from non-members each year. Although this submission track no longer exists, the journal maintains the option for authors to “prearrange” for an NAS member to edit their article. It may well be the case that the editorial process in this instance was conducted with total care and probity. As a general point, though, it is difficult to believe that the “prearranged editor” option can be as impartial and rigorous as one might wish to be the case.

To sum up, the findings presented in this article do not support the notion that exercise will boost your memory, or will stop age-related memory decline. Whereas, of course, it won't hurt anyone to do more exercise, it is unfortunate that potentially vulnerable older people may be misled by this article and its attendant news coverage into thinking that the exercise will cure their memory problems.

What we know from science about how to pass your exams

2011-01-24T12:25:00.010Z

Whether you’re cramming your specialist subject for an appearance on Mastermind, or trying frantically to learn lecture material for an impending exam, there is abundant evidence from cognitive psychology of some strategies that might help.

For many years, researchers considered that the traditional method of simply repeating information over and over to yourself, while improving long-term memory for the information to some degree, was far less effective than so-called “elaborative” processing, which involves relating the to-be-remembered information to other associated facts and previous knowledge. However, new research published this week in Science by Jeffrey Karpicke and colleagues indicates that an even more successful strategy can be to repeatedly test yourself on the information.

Although the merits of so-called “retrieval practice” have been known for some time (see below), the students in Karpicke’s experiment who used the method showed a 50 percent improvement in retention after a week’s delay compared to those who used an elaborative learning strategy – a startling result. It remains to be seen whether the advantage for Karpicke’s retrieval practice method holds over the longer time-frames that may be relevant for an academic exam schedule, where knowledge might be tested several months after it was initially learned. However, this finding adds valuable impetus to the notion that active approaches to learning when revising for an upcoming exam can reap dividends for the students who adopt them.

Here is a brief run-down of some of the cognitive psychology evidence suggesting learning strategies that may be effective. At the end, I'll summarise some top tips to maximise your exam performance.

Rehearsal

It is well established that “rehearsing” information (repeating it to yourself, either out loud or sub-vocally) retains it in short-term memory, and increases the likelihood of that information being transferred into long-term memory. Just ask any actor! Pirolli & Anderson (1985) asked participants to rehearse sentences and examined the effects of this rehearsal on time taken to recognise the sentences as having been previously encountered. They found that long-term memory retrieval improved as a direct function of the amount of rehearsal that was undertaken.

Level of Processing

Craik & Lockhart (1972) demonstrated that the level of processing a stimulus receives during encoding has a considerable effect on its memorability. They asked participants to learn lists of words either using simple repetition or by thinking about the words’ meaning and relating them to associated words and previous knowledge. The meaning-based encoding processes resulted in much greater recall than did repetition. Craik & Tulving (1975) went on to confirm that the type, or “depth”, of the processing is important. They asked participants to learn words (e.g., table) using one of the following tasks: Perceptual – is the word written in capital letters? Phonological – does the word rhyme with “able”? Semantic – is the word an item of furniture? Highest levels of recall were observed following the “deeper” semantic task.

Elaboration

Anderson & Bower (1972) suggested that level of semantic processing may be less important than the extent to which the to-be-remembered information can be related to associated information and previous knowledge. They asked participants to remember sentences in two conditions: study alone (“The doctor hated the lawyer”) or elaborate (generating a continuation to the sentence, e.g. “The doctor hated the lawyer because of the malpractice suit”). The elaboration condition improved memory for the sentence, suggesting that participants were more likely to recall the elaboration because they had generated it themselves, which helped them to recall the associated word “lawyer”.

Stein & Bransford (1979) examined whether it is critical for elaborations to be participant-generated. They compared trials in which participants generated elaborations themselves with trials in which elaborations were provided by the experimenter. Experimenter elaborations produced better recall than participant-generated elaborations, but only if they were precisely relevant to the sentence content, suggesting that the critical factor is whether elaborations constrain the to-be-recalled information. Bransford et al. (1979) tested this idea further by asking participants to remember sentences with minimal elaborations (e.g., “A mosquito is like a doctor because they both draw blood”) or multiple elaborations (e.g., “A mosquito is like a raccoon because they both have heads, legs, and jaws”). Recall was much better for the minimally-elaborated sentences, although most studies show that the more elaboration the better. Bransford et al. suggested that the nature and degree of precision of elaborations in constraining the to-be-remembered information is key.

Frase (1975) examined how constrained elaboration can be applied to the real-life situation of studying material for exams. One group of participants were given topics in the form of questions to think about before reading a text, whereas the other group were just asked to study the text. Frase found that reviewing the text with questions in mind facilitated retention and subsequent recall of the material. This was particularly the case if the questions were relevant to the material (i.e., helped constrain and guide reading, anchoring new concepts to previous knowledge on the basis of meaning).

Organisation

Bower et al. (1969) investigated another influence on memory: the degree to which to-be-remembered information is organised. One group had words to be learned presented to them in an organisational hierarchy, whereas the second group were presented with a similar tree structure, but with the words positioned randomly. It was found that the organised group had an advantage in retention of the words. Analysis of the order in which the words were recalled indicated that participants had organised the material according to the tree hierarchy, and thus had a systematic way to go through and cue their memories for the words.

Spacing

Another factor shown to influence retention is the time over which encoding of information occurs. Massed practice is when many repeated trials with the same information are undertaken without interruption, whereas spaced practice is when increasing intervals of time are used between repetitions of the same information. Bahrick (1979) taught participants English-Spanish word-pairs using repeated training sessions that were massed, or separated by 1 or 30 days. It was found that for long-term retention, spaced study was better than massed, although over the short-term (immediate retention), massed study was optimal. As mentioned above, this has implications for the results of Karpicke’s study.

Active Retrieval

This is the strategy that Karpicke’s study focused on. It was Tulving (1967) who was among the first to examine whether manipulating the method of studying material (e.g., elaborative encoding) is the only way to influence retention or whether the act of retrieval itself might affect subsequent memory. In a number of experiments by Tulving and his colleagues, participants learned lists of words with three conditions: standard (study, test, study, test), repeated study (study, study, study, test), or repeated test (study, test, test, test). Because the repeated study group had three times as many study exposures to the material as the repeated test group, they should have had better memory if learning occurs only during study trials. But Tulving found equivalent learning across conditions, suggesting that test trials are as effective as further study trials in boosting learning. An extension of this work by Karpicke & Roediger (2006) showed that if retention is measured after a one-week delay, repeated retrieval testing can lead to better recall than repeated studying.

As discussed above, the new research from Karpicke and colleagues published this week takes this forward by indicating that repeated testing of retrieval may be by far the most effective of the strategies discussed here for a student to use when revising in order to improve their performance in an upcoming exam.

Summary

To maximise your performance, here are some top tips:

Always revise actively!

Process information deeply; don’t just rote memorise
Process information elaborately; think about connections between material
Organise information into logical structures(e.g., answers to essay questions)
Space study sessions as much as possible
Trying to retrieve information can be even more important than studying; test yourself repeatedly while learning

If you know of any more effective study strategies, let me know in the comments section.

What are we scientists trying to achieve in our interactions with the media?

2010-08-19T13:19:00.008+01:00

I've never written a blog before, and despite writing being one of the things I do for a living in my job as a scientist, I'm somewhat daunted by the prospect. Part of the reason I'm daunted is that blogging is a different form of expression than I'm used to, but I imagine that most new bloggers share the same fear. Another reason, though, is that I'm starting by writing about some of my fellow scientists, whom I generally admire greatly, but who I fear exhibited some of their less desirable qualities earlier this week. What happened upset me so much that I feel I need to write something down.

A summary: on 16th August, the Channel 4 News anchor Samira Ahmed used her Twitter account (@SamiraAhmedC4) to ask for advice on how to read out a complicated formula: p(h,r)=u(h,r)-pr=g(h, Zr)+f1[h, m(o,r)]+f2[h, m(o,r)]+E-pr, adding that it's "the formula to explain how Blackpool (like Bath before it) is becoming classier."

Within a few minutes, Ben Goldacre (@bengoldacre) had become involved. Most people interested in science and the media will be aware of Ben, perhaps through his regular Guardian columns or his blog, badscience.net. He somehow manages to combine a full-time job as a doctor with what must be an almost full-time hobby of challenging what he calls "dodgy scientific claims made by scaremongering journalists, dodgy government reports, evil pharmaceutical corporations, PR companies and quacks." The aspect of Ben's hobby that I most admire him for, because it relates most to my work as a scientist, is regularly reminding science journalists (and university PR people, and scientists) to be careful, and skeptical, and evidence-based, in the way they communicate science to the public. This is something that none of those groups of people can honestly say they do well enough often enough, and I think that Ben, and bloggers like him, should be applauded for continuing to stress its importance.

However, on 16th August, I felt that Ben, and some of his more than 50,000 followers on Twitter let down the cause of science and good science reporting by the way in which they treated Samira Ahmed. After reading Samira's tweet asking for advice about the formula, Ben replied "no, you just have to say 'by reading this out, i have lost all respect for myself as a journalist'." He then tweeted to his followers to "pre-mock C4 News, looks like theyre covering this bullshit" [referring to the Blackpool formula story]. There followed a torrent of sarcastic, pitying and abusive (and these are just a few examples of many) tweets from a number of different individuals to @SamiraAhmedC4. Being the subject of such a backlash must have been an extremely unpleasant experience, which Samira likened at the time to being "savaged ... by hounds".

Some minutes later, a peer-reviewed academic paper came to light, from which the Blackpool equation had been derived. Ben Goldacre immediately apologised to Samira, several times, and wrote a quick blog about the incident, saying that he had been "wrong" in his assumption that Samira's original tweet had been about "another bullshit equation story", and that "the formula was actually a serious piece of work from a real academic paper." Following this acknowledgement by Ben of his mistake, and a request from Samira, several others tweeted apologies to her.

So, this episode could simply be characterised as a bit of an online spat, which ended quickly with apologies all round, no harm done. Both main protagonists are seasoned, thick-skinned media operators, with years of experience in the way the world works. Science, and particularly, "skeptical science", is tough and critical and adversarial, and if you can't stand the heat, you should stay away from Twitter.

However, that view would miss the important and, it seems to me, highly undesirable consequence of "flaming" incidents such as this for the relationship between scientists and journalists. And this comes back to the question I posed in the title of this blog-post: what are we scientists trying to achieve in our interactions with the media? Are we seeking to use Twitter, and other online networks, as new and potentially valuable means of communicating with those journalists brave enough to go online, hopefully answering their questions and providing information and advice about the scientific evidence, and in doing so, helping them to write better stories? Or are we allowing our desire to impart "skepticism" to the media to cloud our judgement, leading us to a tendency to jump to false conclusions, assume journalists are all lazy, press-release copying dimwits, and to respond without thinking or checking the facts, sending sarcastic or abusive messages, chastising them for wasting their time on such rubbish, and so on and so forth. Because it would only be human nature if a journalist who asked scientists for advice and received a torrent of abuse in return, would be less likely next time to want to repeat the experience.

This morning, Samira Ahmed wrote a piece in the Independent, in which she made the point that she has in the past used Twitter to follow "a range of scientists ... to engage directly with people who might know more about the details of a complex issue." But, she says, "I just hope instances like this don't limit the potential of these social networks. It would be a pity to return to the old way of doing things: journalists only ringing up people they know well to sound out stories ... the same old faces."

This is an opinion that has since been repeated by several other journalists on Twitter this morning. For example, @edpmary tweeted "As a journo, if I can expect to have my publication mocked for asking basic q of scientists, I'll stop asking."

As a scientist, I think it would be a tragedy if the behaviour of some inadvertently led to journalists withdrawing from interacting with us, because the only result would be poorer science reporting and the public being even less informed about science than they already are. There is still such a high level of scientific ignorance amongst the public and, while this is not helped by some of the pseudo-scientific rubbish that does appear every day in the media, some journalists are trying to use new technology, such as Twitter, to engage with scientists and by so doing, to improve the quality of their science journalism. This gives us, as scientists, an invaluable opportunity to help to influence and guide science reporting towards greater consideration of evidence, questioning of unlikely claims, etc., and perhaps gradually to address the level of scientific illiteracy that remains so prevalent. We scientists should keep in mind that we are privileged to have the knowledge and expertise that we have worked hard to achieve, and that if we are interested in using them to improve the quality of science reporting and, thus, the public understanding of science, a constructive rather than antagonistic approach may be more fruitful.