working memory

Neurofeedback offers hope for attention training

May, 2011

Receiving immediate feedback on the activity in a brain region enabled people to improve their control of that region’s activity, thus improving their concentration.

I’ve always been intrigued by neurofeedback training. But when it first raised its head, technology was far less sophisticated. Now a new study has used real-time functional Magnetic Resonance Imaging (fMRI) feedback from the rostrolateral prefrontal cortex to improve people's ability to control their thoughts and focus their attention.

In the study, participants performed tasks that either raised or lowered mental introspection in 30-second intervals over four six-minute sessions. Those with access to real-time fMRI feedback could see their RLPFC activity increase during introspection and decrease during non-introspective thoughts, such as mental tasks that focused on body sensations. These participants became significantly better at controlling their thoughts and performing the mental tasks. Moreover, the improved regulation was reflected only in activity in the rostrolateral prefrontal cortex. Those given inaccurate or no brain feedback showed no such improvement.

The findings point to a means of improving attentional control, and also raise hope for clinical treatments of conditions that can benefit from improved awareness and regulation of one's thoughts, including depression, anxiety, and obsessive-compulsive disorders.

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Mindfulness meditation may help attention through better control of alpha rhythms

May, 2011

New research suggests that meditation can improve your ability to control alpha brainwaves, thus helping you block out distraction.

As I’ve discussed on many occasions, a critical part of attention (and working memory capacity) is being able to ignore distraction. There has been growing evidence that mindfulness meditation training helps develop attentional control. Now a new study helps fill out the picture of why it might do so.

The alpha rhythm is particularly active in neurons that process sensory information. When you expect a touch, sight or sound, the focusing of attention toward the expected stimulus induces a lower alpha wave height in neurons that would handle the expected sensation, making them more receptive to that information. At the same time the height of the alpha wave in neurons that would handle irrelevant or distracting information increases, making those cells less receptive to that information. In other words, alpha rhythm helps screen out distractions.

In this study, six participants who completed an eight-week mindfulness meditation program (MBSR) were found to generate larger alpha waves, and generate them faster, than the six in the control group. Alpha wave activity in the somatosensory cortex was measured while participants directed their attention to either their left hand or foot. This was done on three occasions: before training, at three weeks of the program, and after the program.

The MBSR program involves an initial two-and-a-half-hour training session, followed by daily 45-minute meditation sessions guided by a CD recording. The program is focused on training participants first to pay close attention to body sensations, then to focus on body sensations in a specific area, then being able to disengage and shifting the focus to another body area.

Apart from helping us understand why mindfulness meditation training seems to improve attention, the findings may also explain why this meditation can help sufferers of chronic pain.

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More evidence linking heart disease risk factors and cognitive decline

May, 2011

Another study confirms that cardiovascular risk factors are also risk factors for cognitive decline.

A study involved 117 older adults (mean age 78) found those at greater risk of coronary artery disease had substantially greater risk for decline in verbal fluency and the ability to ignore irrelevant information. Verbal memory was not affected.

The findings add to a growing body of research linking cardiovascular risk factors and age-related cognitive decline, leading to the mantra: What’s good for the heart is good for the brain.

The study also found that the common classification into high and low risk groups was less useful in predicting cognitive decline than treating risk as a continuous factor. This is consistent with a growing view that no cognitive decline is ‘normal’, but is always underpinned by some preventable damage.

Risk for coronary artery disease was measured with the Framingham Coronary Risk Score, which uses age, cholesterol levels, blood pressure, presence of diabetes, and smoking status to generate a person's risk of stroke within 10 years. 37 (31%) had high scores. Age, education, gender, and stroke history were controlled for in the analysis.

Reference: 

Gooblar, J., Mack, W.J., Chui, H.C., DeCarli, C., Mungas, D., Reed, B.R. & Kramer, J.H. 2011. Framingham Coronary Risk Profile Predicts Poorer Executive Functioning in Older Nondemented Adults. Presented at the American Academy of Neurology annual meeting on Tuesday, April 12, 2011.

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Prenatal exposure to common insecticide linked to lower IQ at age 7

May, 2011

Two longitudinal studies, one rural and one urban, have reported an association between prenatal pesticide exposure and significantly lower IQ at age 7.

A study of 265 New York City minority children has found that those born with higher amounts of the insecticide chlorpyrifos had lower IQ scores at age 7. Those most exposed (top 25%) scored an average 5.3 points lower on the working memory part of the IQ test (WISC-IV), and 2.7 points lower on the full IQ test, compared to those in the lowest quartile.

The children were born prior to the 2001 ban on indoor residential use of the common household pesticide in the US. The babies' umbilical cord blood was used to measure exposure to the insecticide.

Previous research had found that, prior to the ban, chlorpyrifos was detected in all personal and indoor air samples in New York, and 70% of umbilical cord blood collected from babies. The amount of chlorpyrifos in babies' blood was associated with neurodevelopmental problems at age three. The new findings indicate that these problems persist.

While exposure to the organophosphate has measurably declined, agricultural use is still permitted in the U.S.

Similarly, another study, involving 329 7-year-old children in a farming community in California, has found that those with the highest prenatal exposure to the pesticide dialkyl phosphate (DAP) had an average IQ 7 points lower than children whose exposure was in the lowest quintile. Prenatal pesticide exposure was linked to poorer scores for working memory, processing speed, verbal comprehension, and perceptual reasoning, as well as overall IQ.

Prenatal exposure was measured by DAP concentration in the mother’s urine. Urine was also collected from the children at age 6 months and 1, 2, 3½ and 5 years. However, there was no consistent link between children’s postnatal exposure and cognition.

While this was a farming community where pesticide exposure would be expected to be high, the levels were within the range found in the general population.

It’s recommended that people wash fruit and vegetables thoroughly, and limit their use of pesticides at home.

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People are poor at predicting their learning

April, 2011

A series of online experiments demonstrate that beliefs about memory, judgments of how likely you are to remember, and actual memory performance, are all largely independent of each other.

Research has shown that people are generally poor at predicting how likely they are to remember something. A recent study tested the theory that the reason we’re so often inaccurate is that we make predictions about memory based on how we feel while we're encountering the information to be learned, and that can lead us astray.

In three experiments, each involving about 80 participants ranging in age from late teens to senior citizens, participants were serially shown words in large or small fonts and asked to predict how well they'd remember each (actual font sizes depended on the participants’ browsers, since this was an online experiment and participants were in their own homes, but the larger size was four times larger than the other).

In the first experiment, each word was presented either once or twice, and participants were told if they would have another chance to study the word. The length of time the word was displayed on the first occasion was controlled by the participant. On the second occasion, words were displayed for four seconds, and participants weren’t asked to make a new prediction. At the end of the study phase, they had two minutes to type as many words as they remembered.

Recall was significantly better when an item was seen twice. Recall wasn’t affected by font size, but participants were significantly more likely to believe they’d recall those presented in larger fonts. While participants realized seeing an item twice would lead to greater recall, they greatly underestimated the benefits.

Because people so grossly discounted the benefit of a single repetition, in the next experiment the comparison was between one and four study trials. This time, participants gave more weight to having three repetitions versus none, but nevertheless, their predictions were still well below the actual benefits of the repetitions.

In the third experiment, participants were given a simplified description of the first experiment and either asked what effect they’d expect font size to have, or what effect having two study trials would have. The results (similar levels of belief in the benefits of each condition) neither resembled the results in the first experiment (indicating that those people’s predictions hadn’t been made on the basis of their beliefs about memory effects), or the actual performance (demonstrating that people really aren’t very good at predicting their memory performance).

These findings were confirmed in a further experiment, in which participants were asked about both variables (rather than just one).

The findings confirm other evidence that (a) general memory knowledge tends to be poor, (b) personal memory awareness tends to be poor, and (c) ease of processing is commonly used as a heuristic to predict whether something will be remembered.

 

Addendum: a nice general article on this topic by the lead researcher Nate Kornell has just come out in Miller-McCune

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Kornell, N., Rhodes, M. G., Castel, A. D., & Tauber, S. K. (in press). The ease of processing heuristic and the stability bias: Dissociating memory, memory beliefs, and memory judgments. Psychological Science.

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Why multitasking is more difficult with age

April, 2011

A new study reveals that older adults’ greater problems with multitasking stem from their impaired ability to disengage from an interrupting task and restore the original task.

Comparison of young adults (mean age 24.5) and older adults (mean age 69.1) in a visual memory test involving multitasking has pinpointed the greater problems older adults have with multitasking. The study involved participants viewing a natural scene and maintaining it in mind for 14.4 seconds. In the middle of the maintenance period, an image of a face popped up and participants were asked to determine its sex and age. They were then asked to recall the original scene.

As expected, older people had more difficulty with this. Brain scans revealed that, for both groups, the interruption caused their brains to disengage from the network maintaining the memory and reallocate resources to processing the face. But the younger adults had no trouble disengaging from that task as soon as it was completed and re-establishing connection with the memory maintenance network, while the older adults failed both to disengage from the interruption and to reestablish the network associated with the disrupted memory.

This finding adds to the evidence that an important (perhaps the most important) reason for cognitive decline in older adults is a growing inability to inhibit processing, and extends the processes to which that applies.

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A good mood reduces working memory capacity

April, 2011

A new study suggests a positive mood affects attention by using up some of your working memory capacity.

Following earlier research suggesting mood affects attention, a new study tries to pin down exactly what it’s affecting.

To induce different moods, participants were shown either a video of a stand-up comedy routine or an instructional video on how to install flooring. This was followed by two tests, one of working memory capacity (the Running Memory Span), during which numbers are presented through headphones at a rate of four numbers per second ending with subjects asked to recall the last six numbers in order, and one of response inhibition (the Stroop task).

Those that watched the comedy routine performed significantly worse on the RMS task but not on the Stroop task. To confirm these results, a second experiment used a different measure of response inhibition, the Flanker task. Again, those in a better mood performed worse on the span task but not the inhibition task.

These findings point to mood affecting storage capacity — something we already had evidence for in the case of negative mood, like anxiety, but a little more surprising to find it also applies to happy moods. Basically, it seems as if any emotion, whether good or bad, is likely to leave you less room in your working memory store for information processing. That shouldn’t be taken as a cue to go all Spock! But it’s something to be aware of.

Reference: 

[2180] Martin, E. A., & Kerns J. G.
(2011).  The influence of positive mood on different aspects of cognitive control.
Cognition & Emotion. 25(2), 265 - 265.

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Older adults have better implicit memory

April, 2011

A new study further confirms the idea that a growing inability to ignore irrelevancies is behind age-related cognitive decline.

A study involving 125 younger (average age 19) and older (average age 69) adults has revealed that while younger adults showed better explicit learning, older adults were better at implicit learning. Implicit memory is our unconscious memory, which influences behavior without our awareness.

In the study, participants pressed buttons in response to the colors of words and random letter strings — only the colors were relevant, not the words themselves. They then completed word fragments. In one condition, they were told to use words from the earlier color task to complete the fragments (a test of explicit memory); in the other, this task wasn’t mentioned (a test of implicit memory).

Older adults showed better implicit than explicit memory and better implicit memory than the younger, while the reverse was true for the younger adults. However, on a further test which required younger participants to engage in a number task simultaneously with the color task, younger adults behaved like older ones.

The findings indicate that shallower and less focused processing goes on during multitasking, and (but not inevitably!) with age. The fact that younger adults behaved like older ones when distracted points to the problem, for which we now have quite a body of evidence: with age, we tend to become more easily distracted.

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Working memory has more layers than thought

April, 2011

A new study provides further support for a three-tier model of working memory, where the core only holds one item, the next layer holds up to three, and further items can be passively held ready.

Readers of my books and articles will know that working memory is something I get quite excited about. It’s hard to understate the importance of working memory in our lives. Now a new study tells us that working memory is in fact made up of three areas: a core focusing on one active item, a surrounding area holding at least three more active items (called the outer store), and a wider region containing passive items that have been tagged for later retrieval. Moreover, the core region (the “focus of attention”) has three roles (one more than thought) — it not only directs attention to an item and retrieves it, but it also updates it later, if required.

In two experiments, 49 participants were presented with up to four types of colored shapes on a computer screen, with particular types (eg a red square) confined to a particular column. Each colored shape was displayed in sequence at the beginning with a number from 1 to 4, and then instances of the shapes appeared sequentially one by one. The participants’ task was to keep a count of each shape. Different sequences involved only one shape, or two, three, or four shapes. Participants controlled how quickly the shapes appeared.

Unsurprisingly, participants were slower and less accurate as the set size (number of shape types) increased. There was a significant jump in response time when the set-size increased from one to two, and a steady increase in RT and decline in accuracy as set-size increased from 2 to 4. Responses were also notably slower when the stimulus changed and they had to change their focus from one type of shape to another (this is called the switch cost). Moreover, this switch cost increased linearly with set-size, at a rate of about 240ms/item.

Without getting into all the ins and outs of this experiment and the ones leading up to it, what the findings all point to is a picture of working memory in which:

  • the focus contains only one item,
  • the area outside the focus contains up to three items,
  • this outer store has to be searched before the item can be retrieved,
  • more recent items in the outer store are not found any more quickly than older items in the outer store,
  • focus-switch costs increase as a direct function of the number of items in the outer store,
  • there is (as earlier theorized) a third level of working memory, containing passive items, that is quite separate from the two areas of active storage,
  • that the number of passive items does not influence either response time or accuracy for recalling active items.

It is still unclear whether the passive third layer is really a part of working memory, or part of long-term memory.

The findings do point to the need to use active loads rather than passive ones, when conducting experiments that manipulate cognitive load (for example, requiring subjects to frequently update items in working memory, rather than simply hold some items in memory while carrying out another task).

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Gestures provide a helping hand in problem solving

March, 2011

Another study confirms the value of gestures in helping you solve spatial problems, and suggests that gesturing can help you develop better mental visualization.

In the first of three experiments, 132 students were found to gesture more often when they had difficulties solving mental rotation problems. In the second experiment, 22 students were encouraged to gesture, while 22 were given no such encouragement, and a further 22 were told to sit on their hands to prevent gesturing. Those encouraged to gesture solved more mental rotation problems.

Interestingly, the amount of gesturing decreased with experience with these spatial problems, and when the gesture group were given new spatial visualization problems in which gesturing was prohibited, their performance was still better than that of the other participants. This suggests that the spatial computation supported by gestures becomes internalized. The third experiment increased the range of spatial visualization problems helped by gesture.

The researchers suggest that hand gestures may improve spatial visualization by helping a person keep track of an object in the mind as it is rotated to a new position, and by providing additional feedback and visual cues by simulating how an object would move if the hand were holding it.

Reference: 

[2140] Chu, M., & Kita S.
(2011).  The nature of gestures' beneficial role in spatial problem solving..
Journal of Experimental Psychology: General. 140(1), 102 - 116.

Full text of the article is available at http://www.apa.org/pubs/journals/releases/xge-140-1-102.pdf

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