How many times did Pavlov ring the bell before his dogs' meals until the dogs began to salivate? Surely, the number of experiences must make a difference, as anyone who's trained a dog would attest. As described in a brilliant article by C.R. Gallistel (in Psych. Review; preprint here), this has been thought so self-evident "as to not require experimental demonstration" - yet information theoretic analysis suggest the idea is incorrect, at least when the time from the bell to the food is constant. More problematic is the fact that the whole issue is ill-formed for experimental verification: technically speaking, one can never actually accept the (null) hypothesis that some experimental manipulation has no effect. But as Gallistel says, while "conventional statistical analysis cannot support [the null hypothesis]; Bayesian analysis can."
Don't think of a white bear. Doesn't work so well, does it? Yet under some circumstances, people appear to be able to do precisely this: as described last week, young adults are thought (by some) to actually suppress the neural activity related to to-be-ignored stimuli, and even delay the peak of this neural activity, relative to a situation in which stimuli are to be just passively-viewed. In a follow-up paper at Nature Neuroscience, Gazzaley et al report that cognitively-intact older adults (60-77 years of age) show an impairment in this ability, without concomitant impairments in the enhancement effects normally observed to to-be-attended stimuli.
The cognitive neurosciences have had high frequency oscillations on the brain: so called "gamma-waves", as recorded on the scalp, have been linked to working memory processes (via their interaction with slower "theta waves"), to cognitive insight, and even to consciousness. (I think there's an unwritten rule that whenever someone mentions consciousness, they'll be made to look foolish by a subsequent paper). In the midst of these "inflationary accounts" of the role of gamma oscillations, a debate has emerged: could these oscillations (at least, as recorded on the scalp) reflect simply the movements of the eyes, as now appears to largely be the case? More interestingly, is that necessarily incompatible with the more lofty interpretations of gamma? And what is the relationship between these movement-related artifacts on scalp recordings, and the well-established importance of gamma waves as recorded on or inside the brain?
(UPDATE: first para edited to emphasize scalp- vs. i-EEG distinction; thanks Alex & farraway).
By many current theories, we accomplish control over behavior by using the prefrontal cortex to "bias" the competitive dynamics playing out in the rest of the brain. By some models, this bias is positive - it helps the goal-relevant representations win the competition. By other models, the bias is also negative - it can help the goal-irrelevant representations lose the competition. Regardless, this "prefrontal biasing" is usually considered in terms of the amount of activity in a particular area (higher when that area is under a positive bias, and lower when under a negative bias). But Gazzaley et al's excellent 2005 JoCN article demonstrates that this kind of top-down modulation can also have effects on the speed of neural processing, where positive and negative biasing actually have opposite effects on the latency of some well known ERP components.
To demonstrate this, Gazzaley et al asked 11 subjects to participate in a two session experiment (one in the fMRI scanner and one with electrodes pasted to their heads) in which they saw sequences of pictures of faces and places, in random order. These randomized sequences were preceded by instructions to pay attention to one or the other type of picture while ignoring the other, to pay attention to both, or to just passively view the pictures. A subsequent memory test showed that people were better able to recognize the pictures they'd been told to remember than those they'd passively viewed, and that this advantage was reduced when subjects had been asked to remember both types of stimuli relative to just one. This pattern is consistent with the idea that enhancement of task-relevant information is a resource-limited process that is less effective when it needs to be used more. However, the authors didn't report any reduction in recognizing the to-be-ignored stimuli - perhaps indicating that negative biasing either didn't occur or wasn't effective.
On the other hand, the fMRI results told a different story - one that includes some putative suppression effects. Although fMRI has poor temporal resolution, its excellent spatial resolution allowed the authors to show that neural activity in face- and place-selective regions of the cortex (the FFA and PPA, respectively) was increased when the respective stimulus type was to-be-attended, and decreased when the respective stimulus type was to-be-ignored, relative to the case where both stimulus types were to be passively viewed (the latter "suppression" effect was significant only for the place-selective region, but was in the right direction for the face-stimuli too). Similarly, when subjects had been instructed to remember both stimulus types, this increase in neural activity was reduced (at least for the place-selective region; they didn't report results from the face-selective region), again indicating that top-down enhancement is resource demanding. These effects demonstrate that there is a robust top-down enhancement effect, and also suggest some suppression effect, on the magnitude of neural activity as measured by fMRI.
Gazzaley et al's ERP results take this a step farther: the authors found that the peak latency of a electrical potential characteristic of face processing was earlier when face stimuli were to-be-attended, and later when face stimuli were to-be-ignored, relative to cases where face stimuli were to be passively viewed. In addition, this apparent enhancement of the speed of face processing was reduced when subjects had been instructed to remember both stimulus types, again suggesting that top-down enhancement is resource-limited.
In their discussion, the authors note that such latency shifts have not been observed in single-cell recording studies, suggesting that the top-down effects may be visible only at the level of the local field potential or the resulting ERP. They also note that the latency shifts have not been observed in other selective attention studies, and suggest that this may have to do with task difficulty or that the effect is specific to memory encoding. I found this a little speculative, given that face-selective can show up in either latency or amplitude, and observing one instead of the other is not necessarily informative (some have suggested that these two measures might trade-off).
In a concluding paragraph, the authors note that their effects pertain to the sites of control (i.e., face- and place-selective neural phenomena) and not to the source of that control (i.e., the prefrontal or parietal cortex). Gazzaley et al suggest that multivariate pattern recognition techniques could be used to identify such sources, which might be taken to imply that traditional averaging techniques used in this paper failed to identify those sources.
In summary, Gazzaley et al have collected compelling evidence that goals can be used to positively bias both the magnitude of activity in posterior cortex and the speed with which that processing reaches its peak amplitude. They've also shown some negative effects, such that the magnitude and speed of activity in regions selective for the to-be-ignored items can be reduced relative to passively viewing them, but this is a little less clear. While the enhancement effect is solid and robust, the suppression effect was a little less robust (not significant in the FFA), and did not result in any behavioral suppression effect (at least, not one that was reported).
One possibility here is that passive viewing and ignoring yield identical behavior because in both cases subjects are simply thinking about other things as they see the to-be-ignored or to-be-viewed stimuli. One might get a reduction in visual processing of to-be-ignored stimuli if subjects simply closed their eyes or focused on a different part of the display, and this need not reflect true top-down suppression. If something like this had occurred, it would be visible in the ERP data, because ERP's are exquisitely sensitive to blinking and saccades. Indeed, a relatively large proportion of subjects were excluded from ERP analysis due to excessive oculomotor activity (4/18), perhaps suggesting that just such a strategy was used by some subjects. Even those subjects who were not excluded for that reason nonetheless had very few included trials, due to the detection of oculomotor artifacts (or alpha waves, sometimes thought to reflect a cognitively "idle" state) on 66% of trials (on average; 160/240). It seems to me that this strategy is an alternative explanation not only for the neural "suppression" phenomena observed here but also for the apparent lack of a behavioral suppression effect in this particular study.
A new study suggests that physically stepping backwards may be associated with gains in the ability to deal with problematic situations. As newly reported in Psychological Science (hat tip to Hannah) by Koch, Holland, Hengstler & Knippenberg, people were better able to resolve interference in laboratory "Stroop" task after stepping backwards, relative to stepping to the side or forwards. The authors argue that stepping backwards is typically associated with problematic situations, which characteristically require cognitive control (the set of capacities which enable us to control our behavior and focus on important features of the environment). Koch et al conclude that stepping backwards allows one to more strongly engage these control processes!
The authors demonstrated this fascinating effect by testing 38 subjects on laptop-based Stroop task (in which subjects must name the colors of words while NOT reading the words themselves - e.g., RED). The laptop was mounted on a mobile cart, and subjects were asked to take a step in one of four possible directions (backwards, forwards, left or right) before 12 words were presented in sequence. These "blocks" of trials consisted of equal numbers of incongruent (RED), congruent (RED), and "neutral" trials in which non-color words were used (LOT). Each subject saw a total of 8 blocks, and verbal reaction times were measured by the onset time of the voice on trials that were both correct and within 2.5 standard deviations of their median reaction times.
The results showed a clear effect of stepping backwards - subjects were remarkably faster to name the ink color of incongruent color-words (RED) when they had stepped backwards, relative to forwards or sideways! Moreover, there were no differences on the neutral or congruent trial types, although there was perhaps a trend towards longer reaction times on congruent trials when subjects had stepped backwards. Both effects are consistent with the idea that stepping backwards allowed subjects to better attend to color (or to better suppress word-reading, depending on your interpretation of what's involved in this task).
This work is remarkable not only for demonstrating how a very concrete and simple bodily experience can influence even the highest levels of cognitive processing (in this case, the so-called "cognitive control" processes that enable focused attention), but also because performance on the Stroop task is notoriously difficult to improve. Previous work indicates that meditation might improve performance on this task, but it requires months of training and yields only small or inconsistent effects. In contrast, more targeted "cognitive" training has shown no or very inconsistent effects on Stroop performance, even when that training is successful at improving performance on other tasks.
There's always the possibility that findings like this just reflect a very (un?)lucky set of researchers (that is, a Type I error), but I find this a little unlikely in this particular case. In particular, the trend towards increased reaction times for congruent trials when subjects had stepped backwards is very suggestive - and very consistent with the significant results found for the incongruent trials. Focusing on the important color features helps in incongruent trials, but could hurt you in congruent trials (where reading the word would actually give you the correct answer). If the influence of stepping backwards were actually random, and the significant improvement in reaction times on incongruent trials just a result of random chance, one wouldn't expect to see any evidence of the opposite effect on congruent trials. On the other hand...
Every now and then, I read some science from some other dimension. That is, the methods are so unusual, the relevant theories so fringe, or the conclusions so startling that I feel like the authors must be building on work from a completely separate science, with its own theories and orthodoxy. This can be good or bad, and is usually the latter. But in the case of Zhang & Luck's recent papers, it's very, very good.
To appreciate what they've done, here's a little background from this dimension's science - specifically, the science of forgetting. The phenomenon of "forgetting" has been the subject of much study, and a number of questions remain controversial:
- Is forgetting a process in which items completely vanish from memory, or are these items merely inaccessible to the way people search their memory?
- Does forgetting occur because memories simply decay over time, or because memories get overwritten? (either process could occur completely or partially, depending on the answer to the first question)
- Can forgetting occur intentionally (a la Freudian suppression) or does forgetting only emerge from secondary causes (for example, by practicing the retrieval of other competing items?)
These are just some of the questions addressed in decades of memory research, and clear answers continue to elude the field. But in the midst of these heated and long-standing debates, Zhang and Luck did the following:
1) developed two new theories based on a new question,
2) tested these theories with a new method to mathematically model behavior, and
3) were able to conclusively rule out one of these theories
Hopefully this gives you some appreciation for the sheer creativity required for this work to be done. Now, on to their question:
Is the precision of memory "analogue," such that memories differ in resolution, or is it more digital, such that memories are either present or absent, with fixed resolution?
There are three on-off light switches on the wall of the first floor of a building. One of the switches is initially off and controls an incandescent bulb in a lamp on the third floor of the building. The other two switches do not control the bulb or anything else (they are disconnected). How can you find out which one of the three switches turns the light bulb on and off? You can toggle the switches as many times as you want and for as long as you want, but you can walk only once to the third floor to check on the light bulb.
While you're working on that, I'll show you what you look like (no offense!):
(A hint and the solution to the problem are at the bottom of this post.)
It's thrilling when it happens, but what actually causes insight? New research in the Journal of Cognitive Neuroscience takes us one step closer to an answer: up to 8 seconds before people solve problems thought to require insight, a particular set of very fast oscillations are observable above the right frontal lobe.
Sheth, Sandkuehler & Bhattacharya gave 18 subjects a series of "insight problems" like the one at the start of this post, while the electrical activity on subjects' scalp was recorded via a sensor net with 32 electrodes. All the problems shared a number of features:
Most computational models of working memory do not explicitly specify the role of the parietal cortex, despite an increasing number of observations that the parietal cortex is particularly important for working memory. A new paper in PNAS by Edin et al remedies this state of affairs by developing a spiking neural network model that accounts for a number of behavioral and physiological phenomena related to working memory.
, Cognitive Neuroscience, Computational Modeling ] 
