Research Briefing: Testing sensory evidence against mnemonic templates

In a new study, published in eLife, we investigated how visual search templates are reactivated to act as input filters for target detection. How the brain maintains a template of the target of your search (your house keys, for example) has been a much-debated topic in neuroscience for the past 30 years. Previous research has indicated that neurons specialized for detecting the sought-after object when it is in view are also pre-activated when we are seeking it. This would mean that these ‘template’ neurons are active the entire time that we are searching.

We recorded brain activity from human volunteers using magnetoencephalography (MEG) as they tried to detect when a particular shape appeared on a computer screen. The patterns of brain activity could be analyzed to identify the template that observers had in mind, and to trace when it became active. This revealed that the template was only activated around the time when a target was likely to appear, after which the activation pattern quickly subsided again.

We also found that holding a template in mind largely corresponded with different MEG patterns to those activated after a stimulus with the same orientation appeared on a computer screen. This is contrary to the idea that the same cells are responsible both for maintaining a template and for perceiving its presence in our surroundings. The brief activation of the template suggests templates may come online just in time to filter new sensory evidence to detect targets. This mechanism could be advantageous because it lowers the amount of neural activity (and hence energy) needed for the task. Although this points to a more efficient way in which the brain searches for targets, these findings need to be replicated using other methods and task settings to confirm whether the brain generally uses templates in this way. For instance, we would like to know more about where in the brain such a filter may be set up.

Reference: 

Myers, N. E., G. Rohenkohl, V. Wyart, M. W. Woolrich, A. C. Nobre and M. G. Stokes (2015). "Testing sensory evidence against mnemonic templates." Elife 4.

Research Briefing: organising the contents of working memory

Figure 1. Nicholas Myers

Research Briefing, by Nicholas Myers

Everyone has been in this situation: you are stuck in an endless meeting, and a colleague drones on about a topic of marginal relevance. You begin to zone out and focus on the art hanging in your boss’s office, when suddenly you hear your name mentioned. On high alert, you suddenly shift back to the meeting and scramble to retrieve your colleague’s last sentences. Miraculously, you are able to retrieve a few key words – they must have entered your memory a moment ago, but would have been quickly forgotten if hearing your name had not cued them as potentially vital bits of information.

This phenomenon, while elusive in everyday situations, has been studied experimentally for a number of years now: cues indicating the relevance of a particular item in working memory have a striking benefit to our ability to recall it, even if the cue is presented after the item has already entered memory. See our previous Research Briefing on how retrospective cueing can restore information to the focus of attention in working memory.

In a new article, published in the Journal of Cognitive Neuroscience, we describe a recent experiment that set out to add to our expanding knowledge of how the brain orchestrates these retrospective shifts of attention. We were particularly interested in the potential role of neural synchronization of 10 Hz (or alpha-band) oscillations, because they are important in similar prospective shifts of attention.

Figure 2. Experimental Task Design. [from Myers et al, 2014]

We wanted to examine the similarity of alpha-band responses (and other neural signatures of the engagement of attention) both to retrospective and prospective attention shifts. We needed to come up with a new task that allowed for this comparison. On each trial in our task, experiment volunteers first memorized two visual stimuli. Two seconds later, a second set of two stimuli appeared, so that a total of four stimuli was kept in mind. After a further delay, participants recalled one of the four items.  

In between the presentation of the first and the second set of two items, we sometimes presented a cue: this cue indicated which of the four items would likely be tested at the end of the trial. Crucially, this cue could have either a prospective or a retrospective function, depending on whether it pointed to location where an item had already been presented (a retrospective cue, or retrocue), or to a location where a stimulus was yet to appear (a prospective cue, or precue). This allowed us to examine neural responses to attention-guiding cues that were identical with respect to everything but their forwards- or backwards-looking nature. See Figure 2 for a task schematic.

Figure 3. Results: retro-cueing and pre-cueing
trigger different attention-related ERPs.
[from Myers et al, 2014]

We found marked differences in event-related potential (ERP) profiles between the precue and retrocue conditions. We found evidence that precues primarily generate an anticipatory shift of attention toward the location of an upcoming item: potentials just before the expected appearance of the second set of stimuli reflected the location where volunteers were attending. These included the so-called early directing attention negativity (or 'EDAN') and the late directing attention-related positivity (or 'LDAP'; see Figure 3, middle panel; and see here for a review of attention-related ERPs). Retrocues elicited a different pattern of ERPs that was compatible with an early selection mechanism, but not with stimulus anticipation (i.e., no LDAP, see Figure 3, upper panel). The latter seems plausible, since the cued information was already in memory, and upcoming stimuli were therefore not deserving of attention. In contrast to the distinct ERP patterns, alpha band (8-14 Hz) lateralization was indistinguishable between cue types (reflecting, in both conditions, the location of the cued item; see Figure 4).

Figure 4. Results: retro-cueing and pre-cueing trigger similar patters
of de-synchronisation in low frequency activity (alpha band at ~10Hz).
[from Myers et al, 2014]

What did we learn from this study? Taken together with the ERP results, it seems that alpha-band lateralization can have two distinct roles: after a precue it likely enables anticipatory attention. After a retrocue, however, the alpha-band response may reflect the controlled retrieval of a recently memorized piece of information that has turned out to be more useful than expected, without influencing the brain’s response to upcoming stimuli.

It seems that our senses are capable of storing a limited amount of information on the off chance that it may suddenly become relevant. When this turns out to be the case, top-down control allows us to pick out the relevant information from among all the items quietly rumbling around in sensory brain regions.

Many interesting questions remain that we were not able to address in this study. For example, how do cortical areas responsible for top-down control activate in response to a retrocue, and how do they shuttle cued information into a state that can guide behaviour? 



Key Reference: 

Myers, Walther, Wallis, Stokes & Nobre (2014) Temporal Dynamics of Attention during Encoding versus Maintenance of Working Memory: Complementary Views from Event-related Potentials and Alpha-band Oscillations. Journal of Cognitive Neuroscience (Open Access)

Research Briefing: Oscillatory Brain State and Variability in Working Memory

Hot off the press: Oscillatory Brain State and Variability in Working Memory

In a new paper, Nick Myers and colleagues show how spontaneous fluctuations in

alpha-band synchronization over visual cortex predict the trial-by-trial accuracy of items stored in visual working memory. The pre-stimulus desynchronization of alpha oscillations correlated with the accuracy of memory recall. A model-based analysis indicated that this effect arises from a modulation in the precision of memorized items, but not the likelihood of remembering them (the recall rate). The phase of posterior alpha oscillations preceding the memorized item also predicted memory accuracy. The study highlights the influence of spontaneous changes in cortical excitability on higher visual cognition, and how these state changes contribute to large amounts of variability in what is normally thought of as a stable aspect of behavior.

 

From Figure 2 in Myers et al. (2014)

Reference: 

Myers, N. E., M. G. Stokes, et al. (2014). "Oscillatory brain state predicts variability in working memory." J Neurosci 34(23): 7735-7743 http://www.jneurosci.org/content/34/23/7735.short

Research Briefing: Dynamic population coding for flexible cognition

Dynamic population coding in prefrontal cortex

Our environment is in constant flux. At any given moment there could be a shift in scenario that demands an equally rapid shift in how we interpret the world around us. For example, the meaning of a simple traffic light critically depends on whether you are driving to work or travelling on foot. Our brains must constantly adapt to accommodate an enormous range of such possible scenarios - in this study, we applied new analysis tools to explore how patterns of brain activity change for different task contexts, allowing for flexible cognitive processing (in Stokes et al., 2013, Neuron; see also Comment by Miller and Fusi in the same issue).

Prefontal Cortex

Adapted from Fig 1

We focused our investigation on an area in the frontal lobe known as lateral prefrontal cortex. This brain area has long been implicated in flexible cognitive processing. Damage to prefrontal cortex is classically associated with reduced cognitive flexibility (Luria, 1966) as part of a more general dysexecutive syndrome. In studies using functional magnetic resonance imaging (fMRI), lateral frontal cortex is also usually more active when participants perform tasks that demand cognitive flexibility (Wager et al., 2004). It it widely believed that prefrontal cortex is especially important for representing information about our environment and task goals in mind for guiding flexible behaviour (Baddeley, 2003; Miller, 2000).

Dynamic coding population coding

Dynamic trajectory through state-space

In this study, we observe a highly dynamic process underlying flexible cognitive processing using a statistical approach that allows us to decode the patterns of population-level activity in prefrontal cortex at high temporal resolution. During a task that requires a different stimulus-response mapping according to trial-by-trial instruction cues (see Fig 1), we found that the pattern of activity rapidly changes during processing of the instructive cue stimulus. After this complex cascade through activity state-space (for more info, see Stokes, 2011), overall activity levels return to baseline for the remainder of a delay period spanning the instruction cue and a possible target stimulus.

Adapted from Fig 5

However, the effect of the cue response lingers on. Subsequent stimuli elicit a population response that critically depends on the previous cue identity. In other words, the dynamic population response triggered by the cue stimulus shifts the response profile of the network of prefrontal cells. This shift in tuning profile allows us to decode the current task-rule (i.e., cue indentify) based on a simple driving stimulus (i.e., neutral stimuli, see Fig 5).

Adapted from Fig 6

More importantly, the shift in the network response profile could also underlie task-dependent target processing (i.e., choice stimuli, see Fig 6). The population response to potential target stimuli rapidly evolved from a stimulus-specific coding scheme, to a more abstract code that distinguishes only between different target and non-target items. This dynamic tuning property is ideal for flexible cognition (Duncan, 2001).

Putative mechanism: flexible connectivity

The flow of brain activity critically depends on the pattern of connections between neurons. Contrary to intuition, these connections are always changing. The pattern of connections that make up the very essence of personal experience is constantly adjusting and adapting to the myriad changes experienced throughout life.

Synaptic Plasticity [wiki commons]

Extensive research focuses on long-term structural changes in connectivity through synaptic plasticity, however the rapid changes we experience from moment-to-moment requires a more flexible kind of memory that can represent the transient features of a given scenario. This kind of flexible "online" memory is typically referred to as ‘working memory’.

It has long been assumed that working memory is maintained by keeping a specific thought in mind, like a static snapshot of a visual image or an abstract goal such as ‘turn left at the next set of lights’. However, more recent evidence suggests that working memory can also be stored by laying down specific, but temporary neural pathways (e.g., Mongillo, Barak & Tsodyks, 2008). Neural pathways are formed by synaptic connections. In a comprehensive review of the literature on short-term synaptic plasticity, Zucker (1989) writes: “Chemical synapses are not static. Postsynaptic potentials wax and wane, depending on the recent history of presynaptic activity”. Short-term plasticity could provide a key mechanisms for flexible connectivity that is necessary for rapid, but temporary changes in network behaviour.

This new idea allows for a more dynamic theory of brain function, which is more consistent with the everyday experience of continuous thought processes that seem to evolve through time, rather than persist as a static representation. We suggest that short-term plasticity could help explain our data:

Adapted from Fig 7

The initial instruction cue stimulus establishes a specific (but temporary) connectivity state during the most active phase of the response. This would explain why the pattern constantly changes - if the synapse are constantly changing, then even identical input to the system will result in constantly shifting output patterns (Buonomano and Maass, 2009). This temporary shift in the response sensitivity of the prefrontal network allows the identity of previous input to be decoded by the patterned response to subsequent input, consistent with the silent memory hypothesis. Finally, dynamic changes in connectivity could also be used to rapidly shift the tuning profile of the prefrontal network to accommodate changes in what specific stimuli mean for behaviour (see Fig. 7).

Broader implications

Brain activity is inherently non-stationary - the continuity/stability of cognitive states are unlikely to depend on static activity states, but rather rapid changes in temporary connectivity patterns. This research also raises the intriguing possibility that cognitive capacity limits are not so much constrained by the sheer amount of information that we can keep in mind, but rather how we can put that information to use. Further research in our lab will explore these exciting possibilities.


Reference:

Stokes, Kusunoki, Sigala, Nili, Gaffan and Duncan (2013). Dynamic Coding for Cognitive Control in Prefrontal Cortex. Neuron, 78, 364-375 [here]

Also see coverage: Miller Lab (MIT), Neuron Preview


Other literature cited:

Baddeley, A. (2003). Working memory: looking back and looking forward. Nat. Rev. Neurosci. 4, 829–839. [here]

Buonomano, D.V., and Maass, W. (2009). State-dependent computations: spatiotemporal processing in cortical networks. Nat. Rev. Neurosci. 10, 113–125. [here]

Luria, A.R. (1966). Higher Cortical Functions in Man (New York: Basic Books).

Miller, E.K. (2000). The prefrontal cortex and cognitive control. Nat. Rev. Neurosci. 1, 59–65. [here]

Mongillo, G., Barak, O., and Tsodyks, M. (2008). Synaptic theory of working memory. Science 319, 1543–1546. [here]

Wager, T.D., Jonides, J., and Reading, S. (2004). Neuroimaging studies of shifting attention: a meta-analysis. Neuroimage 22, 1679–1693. [here]

Zucker (1989) Short-term synaptic plasticity. Ann. Rev. Neurosci, 12: 13-31 [here]

Research Briefing: Attention restores forgotten items to visual short-term memory

Our paper, just out in Psychological Science, describes the final series of experiments conducted by Alexandra Murray during her PhD with Kia Nobre and myself at the Department of Experimental Psychology, Oxford University. Building on previous research by Kia and others in the Brain and Cognition Lab, these studies were designed to test how selective attention modulates information being held in mind, in a format known as visual short-term memory (VSTM).

Typically, VSTM is thought of as a temporary buffer for storing a select subset of information extracted during perceptual processing. This buffer is typically assumed to be insulated from the constant flux of sensory input streaming continuously into the brain, allowing the most important information to be held in mind beyond the duration of sensory stimulation. This way, VSTM enables us to use visual information to achieve longer-term goals, helping to free us from direct stimulus-response contingencies (right).

Previous studies have shown that attention is important for keeping visual information in mind. For example, Ed Awh and colleagues have suggested that selective attention is crucial for rehearsing spatial information in VSTM, just like inner speech helps us keep a telephone number in mind. Our results described in this paper further suggest that attention is not simply a mechanisms for maintenance, but is also important for converting information into a retrievable format.

In long term-memory research, retrieval mechanisms are often considered as important to memory performance as the storage format. It is all well and good if the information is stored, but to what end if it cannot be retrieved? We think that retrieval is also important in VSTM - valuable information could be stored in short-term traces that are not directly available for memory retrieval. In this study, we show that attention can be directed to such memory traces to convert them into a format that is easier to use (i.e., retrieve). In this respect, attention can be used to restore information to VSTM for accurate recall.

We combined behavioural and psychophysical approaches to show that attention, directed to memory items about one second after they had been presented, increases the discrete probability of recall, rather than a more perceptual improvement in the precision of recall judgements (for relevant methods, see also here). This combination of approaches was necessary to infer a discrete state transition between retrievable and non-retrievable formats.

Next step? Tom Hartley asked on twitter: what happened to the unattended items in memory? We did not address this question in this study, and the current literature presents a mixed picture, some suggesting the attention during maintenance impairs memory for unattended items (see), whereas others find no such suppression effect (see). It is possible that differences in strategy could account for some of the confusion.

To test the effect on unattended items in behavioural studies, researchers typically probe memory for unattended items every so often. This presents a contradiction to the participant - sometimes uncued items will be relevant for task performance, therefore individuals need to decide on an optimal strategy (i.e., how much attention to allocate to uncued items, just in case...). A cleaner approach is to use brain imaging to measure the neural consequence for unattended items. The principal advantage is that you don't need to confuse your participants with a mixed message: attend to the cued item, even though we might ask you about one of the other ones!!

References:

Awh & Jonides (2001) Overlapping mechanisms of attention and spatial working memory. TICS (pdf)

Bays & Husain (2008) Dynamic shifts of limited working memory resources in human vision. Science (pdf)

Landman, Spekreijse, & Lamme (2003). Large capacity storage of integrated objects before change blindness. Vision Research (link).

Matsukura, Luck, & Vecera (2007). Attention effects during visual short-term memory maintenance: Protection or prioritization? Perception & Psychophysics (link).

Murray, Nobre, Clark, Cravo & Stokes (2013) Attention Restores Discrete Items to Visual Short-Term Memory. Psychological Science (pdf)

Research Briefing: Targeting "silent" brain areas with TMS

A major challenge in neuroscience is how to study brain processes that are securely encased within the skull. Over the last twenty years, there has been enormous progress in non-invasive brain imaging methods. In particular, functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) allow researchers to measure brain activity from outside the head.

Although brain imaging methods allow us to peer inside the head and watch the brain in action, we also need to be able to perturb brain function to understand more fully what observed brain activity is actually doing. We will never understand the brain by just watching it - we also need to be able to poke around to see what happens when certain processes are disrupted. In formal terms, we can only verify causality by disrupting brain activity and observing the consequences.

The most effective method for non-invasive brain disruption is transcranial magnetic stimulation (TMS). TMS is able to disrupt brain activity by delivering a focal magnetic pulse to the overlying scalp surface. The magnetic field passes through the scalp and skull, stimulating brain cells, thereby disrupting brain function.

TMS is the only method currently available in human neuroscience to disrupt specific brain areas and measure the consequence on brain function. TMS has been in use in labs across the world for more than 25 years, and sophisticated methods have been developed for targeting specific brain areas (see neuronavigation, pictured right). Nevertheless, it remain relatively unclear exactly how best to set stimulate intensity.

Setting the right stimulation level is essential for safe and effective use of TMS. Over-stimulation can cause adverse effects, such as seizure. From an experimental point of view, over-stimulation also reduces the focality of disruption, therefore complicating the interpretation of any effects. On the other hand, under-stimulation could compromise treatment in clinical settings, and lead to false negative results in research. Poor control over the stimulation intensity also compromises experimental comparisons between treatment conditions.

In a series of methodological studies performed with Chris Chambers and others, we previously explored the effect of skull thickness on brain stimulation. It is well known that the flux density of a magnetic field declines as a function of distance. As a direct consequence, if people have thicker skulls, they will require a higher intensity field at the scalp surface to activate underlying brain areas. To quantify this dependency, we varied TMS distance over motor cortex.


When TMS is applied to primary motor cortex, stimulation triggers a twitch in the muscle associated with the stimulated portion of the motor map (pictured left). This an extremely reliable and repeatable effect, and therefore provides a very useful tool for assessing the effect of TMS. We simply varied distance between the stimulation coil and the target brain region to characterise the relationship between distance and TMS effect (pictured right). From these initial studies, we suggested that TMS protocols could be usefully calibrated at motor cortex, and corrected for distance to derive a distance-independent estimate of cortical excitability. Distance-corrected levels could then be used to determine the appropriate stimulation intensity for 'silent' brain areas, such as non-motor brain areas for which there is no simple index of effective stimulation.

However, distance adjusted TMS still relies on the assumption that individual differences in response to TMS are due to variations in a general factor of cortical excitability. In this new study we tested this key assumption. We compared peoples' sensitivity to stimulation of motor cortex with stimulation of their visual cortex (indexed by a visual percept known as a phosphene). We found a systematic relationship between individual differences in sensitivity across stimulation sites, consistent with the idea that a common factor of cortical excitability might account for individual differences in the response to TMS.

In conclusion, this research suggests that TMS intensity can be calibrated to distance adjusted motor threshold, and applied to other brain areas. For further information, please see our paper here, or contact me directly.


References

Stokes, Barker, Dervinis, Verbruggen, Maizey, Adams & Chambers (2013) Biophysical Determinants of Transcranial Magnetic Stimulation: Effects of Excitability and Depth of Targeted Area. Journal of Neurophysiology, 109: 437– 444 [pdf]

Stokes, Chambers, Gould, English, McNaught, McDonald & Mattingley (2007) Distance-adjusted motor threshold for transcranial magnetic stimulation. Clinical Neurophysiology, 118(7): 1617-1625 [pdf]

Stokes, Chambers, Gould, Henderson, Janko, Allen & Mattingley (2005) A simple metric for scaling motor threshold based on scalp-cortex distance: application to studies using transcranial magnetic stimulation. Journal of Neurophysiology, 94(6): 4520-4527 [pdf]

Research Briefing: Lacking Control over the Trade-off between Quality and Quantity in Visual Short-Term Memory

This paper, just out in PLoS One, describes research led by Alexandra Murray during her doctoral studies with Kia Nobre and myself. The series of behavioural experiments began with a relatively simple question: how do people prepare for encoding into visual short-term memory (VSTM)?

VSTM is capacity limited. To some extent, increasing the number of items in memory reduces the quality of each representation. However, this trade-off does not seem to continue ad infinitum. If there are too many items to encode, people tend to remember only a subset of possible items, but with reasonable precision, rather than a more vague recollection of all the items. 

Previously, we and others had shown that directing participants to encode only a subset of items from a larger set of possible memory items increases the likelihood that the cued items would be recalled after a memory delay. Using electroencephalogram (EEG), we further showed that the brain mechanisms associated with preparation for selective VSTM encoding were similar to those previously associated with selective attention. 

To follow up on this previous research, Murray further asked whether can people strategically fine tune the trade-off between the number and quality of items in VSTM? Given foreknowledge of the likely demands (i.e., many or few memory items, difficult or easy memory test), can people engage an encoding strategy that favours quality over quality, or vice versa?  

From the outset, we were pretty confident that people would be able to fine-tune their encoding strategy according to such foreknowledge. Extensive previous evidence, including our own mentioned above, had revealed a variety of control mechanisms that optimise VSTM encoding according to expected task demands. Our first goal was simply to develop a nice behavioural task that would allow us to explore in future brain imaging experiments the neural principles underlying preparation for encoding strategy, relative to other forms of preparatory control. But this particular line of enquiry never got that far! Instead, we encountered a stubborn failure of our manipulations to influence encoding strategy. We started with quite an optimistic design in the first experiment, but progressively increased the power of our experiments to detect any influence of foreknowledge over expected memory demands - and still nothing at all! The figure on the right summarises the final experiment in the series. The red squares in the data plot (i.e., panel b) highlight the two conditions that should differ if our hypothesis was correct.  

By this stage it was clear that we would have to rethink our plans for subsequent brain imaging experiments. But in the interim, we had also potentially uncovered an important limit to VSTM encoding flexibility that we had not expected. The data just kept on telling us: people seem to encode as many task-relevant items as possible, irrespective of how many items they expect, or how difficult the expected memory test at the end of the trial. In other words, this null effect had revealed an important boundary condition for encoding flexibility in VSTM. Rather than condemn these data to the file draw, shelved as a dead-end line of enquiry, we decided that we should definitely try to publish this important, and somewhat surprising null effect. We decided PLoS One would be the perfect home for this kind of robust null effect. The experimental designs were sensible, with a logical progression of manipulations, the experiments were well-conducted and the data were otherwise clean. There was just no evidence that our key manipulations influenced short-term memory performance. 

As we were preparing our manuscript for submission, a highly relevant paper by Zhang and Luck came out in Psychological Sciences (see here). Like us, they found no evidence that people can strategically alter the trade-off between remembering many items poorly and/or few items well. If it is possible to be scooped on a null effect, then I guess we were scooped! But in a way, the precedent only increased our confidence that our null effect was real and interesting, and definitely worth publishing. Further, PLoS One is also a great place for replication studies, and so surely a replication of a null effect makes it a doubly ideal! 

For further details, see:

Murray, Nobre & Stokes (2012) Lacking control over the trade-off between quality and quantity in VSTM. PLoS One

Murray, Nobre & Stokes (2011). Markers of preparatory attention predict visual short-term memory. Neuropsychologia, 49:1458-1465.

Zhang W, Luck SJ (2011) The number and quality of representations in working memory. Psychol Sci. 22: 1434–1441

Research Briefing: How memory influences attention

Background

In the late 19^th Century, the great polymath Hermann von Helmholtz eloquently described how our past experiences shape how we see the world. Given the optical limitations of the eye, he concluded that the rich experience of vision must be informed by a lot more than meets the eye. In particular, he argued that we use our past experiences to infer the perceptual representation from the imperfect clues that pass from the outside world to the brain. 

Consider the degraded black and white image below. It is almost impossible to interpret, until you learn that it is a Dalmatian. Now it is almost impossible not to see the dog in dappled light.

More than one hundred years after Helmholtz, we are now starting to understand the brain mechanisms that mediate this interaction between memory and perception. One important direction follows directly from Helmholtz 's pioneering work. Often couched in more contemporary language, such as Bayesian inference, vision scientists are beginning to understand how our perceptual experience is determined by the interaction between sensory input and our perceptual knowledge established through past experience in the world. 

Prof Nobre (cognitive neuroscientist, University of Oxford) has approached this problem from a slightly different angle. Rather than ask how memory shapes the interpretation of sensory input, she took one step back to ask how past experience prepares the visual system to process memory-predicted visual input. With this move, Nobre's research draws on a rich history of cognitive neuroscientific research in attention and long-term memory. 

Although both attention and memory have been thoroughly studied in isolation, very is little is actually known of how these two core cognitive functions interact in everyday life. In 2006, Nobre and colleagues published the results of a brain imaging experiment designed to identify the brain areas involved in memory-guided attention (Summerfield et al., 2006, Neuron). Participants in this experiment first studied a large number of photographs depicting natural everyday scenes. The instruction was to find a small target object embedded in each scene, very much like the classic Where's Wally game.

After performing the search task a number of times, participants were able learned the location of the target in each scene. When Nobre and her team tested their participants again on a separate day, they found that people were able to use the familiar scenes to direct attention to the previously learned target location in the scene. 

Next, the research team repeated this experiment, but this time changes in brain activity were measured in each participant while they used their memories to direct the focus of their attention. With functional magnetic resonance imaging (fMRI), the team found an increase in neural activity in brain areas associated with memory (especially the hippocampus) as well as a network of brain areas associated with attention (especially parietal and prefrontal cortex). 

This first exploration of memory guided attention (1) confirmed that participants can use long-term memory to guide attention, and (2) further suggested that the brain areas that the mediate long-term could interact with attention-related areas to support this coalition. However, due to methodological limitations at the time, there was no way to separate activity associated with memory-guided preparatory attention, and the consequences of past-experience on perception (e.g., Helmholtzian inference). This was the aim of our follow-up study.

The Current Study: Design and Results 

In collaboration with Nobre and colleagues, we combined multiple brain imaging methods to show that past experience can change the activation state of visual cortex in preparation for memory-predicted input (Stokes, Atherton, Patai & Nobre, 2012, PNAS). Using electroencephalography (EEG), we demonstrated that the memories can reduce inhibitory neural oscillations in visual cortex at memory-specific spatial locations.

With fMRI, we further show that this change in electrical activity is also associated with an increase in activity for the brain areas that represent the memory-predicted spatial location. Together, these results provide key convergent evidence that past-experience alone can shape activity in visual cortex to optimise processing of memory-predicted information. 

Finally, we were also able to provide the most compelling evidence to date that memory-guided attention is mediated via the interaction between processing in the hippocampus, prefrontal and parietal cortex. However, further research is needed to verify this further speculation. In particular, we cannot yet confirm whether activation of the attention network is necessary for memory-guided preparation of visual cortex, or whether a direct pathway between the hippocampus and visual cortex is sufficient for the changes in preparatory activity observed with fMRI and EEG. This is now the focus of on-going research.

Research Briefings: A call for scientists to explain themselves!

Recently, Chris Chambers (neuroscience researcher, Cardiff University) posted a compelling argument for scientists to make their research findings more available to a wider audience via blogs. In his own words:


"The aim of such blog articles shouldn’t be to court publicity or to merely regurgitate our peer-reviewed publications. Instead we should try to provide an overview that is tailored specifically for non-scientists, using minimal jargon and assuming no background knowledge. In keeping with Tim Radford's 7th commandment, we should also avoid insulting the reader's intelligence."

So, to do my part, my next blog will review the findings, and implications, of a study that we recently published in the relatively generalists scientific journal, Proceedings of the National Academy of Sciences. I will aim to provide an informative overview that simplifies without insulting - and also does not read simply as a PR exercise in self-promotion! If this succeeds, I will try to make a habit it of it... so stay tuned for Research Briefings!