part of the prefrontal cortex, associated with tasks that require concentration, such as reading
A study has found that brain regions responsible for making decisions continue to be active even when the conscious brain is distracted with a different task.
New findings support a mathematical model predicting that the slow, steady firing of neurons in the dorsolateral
Emotionally arousing images that are remembered more vividly were seen more vividly. This may be because the amygdala focuses visual attention rather than more cognitive attention on the image.
We know that emotion affects memory. We know that attention affects perception (see, e.g., Visual perception heightened by meditation training; How mindset can improve vision). Now a new study ties it all together. The study shows that emotionally arousing experiences affect how well we see them, and this in turn affects how vividly we later recall them.
The study used images of positively and negatively arousing scenes and neutral scenes, which were overlaid with varying amounts of “visual noise” (like the ‘snow’ we used to see on old televisions). College students were asked to rate the amount of noise on each picture, relative to a specific image they used as a standard. There were 25 pictures in each category, and three levels of noise (less than standard, equal to standard, and more than standard).
Different groups explored different parameters: color; gray-scale; less noise (10%, 15%, 20% as compared to 35%, 45%, 55%); single exposure (each picture was only presented once, at one of the noise levels).
Regardless of the actual amount of noise, emotionally arousing pictures were consistently rated as significantly less noisy than neutral pictures, indicating that people were seeing them more clearly. This was true in all conditions.
Eye-tracking analysis ruled out the idea that people directed their attention differently for emotionally arousing images, but did show that more eye fixations were associated both with less noisy images and emotionally arousing ones. In other words, people were viewing emotionally important images as if they were less noisy.
One group of 22 students were given a 45-minute spatial working memory task after seeing the images, and then asked to write down all the details they could remember about the pictures they remembered seeing. The amount of detail they recalled was taken to be an indirect measure of vividness.
A second group of 27 students were called back after a week for a recognition test. They were shown 36 new images mixed in with the original 75 images, and asked to rate them as new, familiar, or recollected. They were also asked to rate the vividness of their recollection.
Although, overall, emotionally arousing pictures were not more likely to be remembered than neutral pictures, both experiments found that pictures originally seen as more vivid (less noise) were remembered more vividly and in more detail.
Brain scans from 31 students revealed that the amygdala was more active when looking at images rated as vivid, and this in turn increased activity in the visual cortex and in the posterior insula (which integrates sensations from the body). This suggests that the increased perceptual vividness is not simply a visual phenomenon, but part of a wider sensory activation.
There was another neural response to perceptual vividness: activity in the dorsolateral prefrontal cortex and the posterior parietal cortex was negatively correlated with vividness. This suggests that emotion is not simply increasing our attentional focus, it is instead changing it by reducing effortful attentional and executive processes in favor of more perceptual ones. This, perhaps, gives emotional memories their different ‘flavor’ compared to more neutral memories.
These findings clearly need more exploration before we know exactly what they mean, but the main finding from the study is that the vividness with which we recall some emotional experiences is rooted in the vividness with which we originally perceived it.
The study highlights how emotion can sharpen our attention, building on previous findings that emotional events are more easily detected when visibility is difficult, or attentional demands are high. It is also not inconsistent with a study I reported on last year, which found some information needs no repetition to be remembered because the amygdala decrees it of importance.
I should add, however, that the perceptual effect is not the whole story — the current study found that, although perceptual vividness is part of the reason for memories that are vividly remembered, emotional importance makes its own, independent, contribution. This contribution may occur after the event.
It’s suggested that individual differences in these reactions to emotionally enhanced vividness may underlie an individual’s vulnerability to post-traumatic stress disorder.
 Todd, R. M., Talmi D., Schmitz T. W., Susskind J., & Anderson A. K.
(2012). Psychophysical and Neural Evidence for Emotion-Enhanced Perceptual Vividness.
The Journal of Neuroscience. 32(33), 11201 - 11212.
The protein associated with Alzheimer's disease appears to impair cognitive function many years before symptoms manifest. Higher levels of this protein are more likely in carriers of the Alzheimer’s gene, and such carriers may be more affected by the protein’s presence.
Another study adds to the evidence that changes in the brain that may lead eventually to Alzheimer’s begin many years before Alzheimer’s is diagnosed. The findings also add to the evidence that what we regard as “normal” age-related cognitive decline is really one end of a continuum of which the other end is dementia.
In the study, brain scans were taken of 137 highly educated people aged 30-89 (participants in the Dallas Lifespan Brain Study). The amount of amyloid-beta (characteristic of Alzheimer’s) was found to increase with age, and around a fifth of those over 60 had significantly elevated levels of the protein. These higher amounts were linked with worse performance on tests of working memory, reasoning and processing speed.
More specifically, across the whole sample, amyloid-beta levels affected processing speed and fluid intelligence (in a dose-dependent relationship — that is, as levels increased, these functions became more impaired), but not working memory, episodic memory, or crystallized intelligence. Among the elevated-levels group, increased amyloid-beta was significantly associated with poorer performance for processing speed, working memory, and fluid intelligence, but not episodic memory or crystallized intelligence. Among the group without elevated levels of the protein, increasing amyloid-beta only affected fluid intelligence.
These task differences aren’t surprising: processing speed, working memory, and fluid intelligence are the domains that show the most decline in normal aging.
Those with the Alzheimer’s gene APOE4 were significantly more likely to have elevated levels of amyloid-beta. While 38% of the group with high levels of the protein had the risky gene variant, only 15% of those who didn’t have high levels carried the gene.
Note that, while the prevalence of carriers of the gene variant matched population estimates (24%), the proportion was higher among those in the younger age group — 33% of those under 60, compared to 19.5% of those aged 60 or older. It seems likely that many older carriers have already developed MCI or Alzheimer’s, and thus been ineligible for the study.
The average age of the participants was 64, and the average years of education 16.4.
Amyloid deposits varied as a function of age and region: the precuneus, temporal cortex, anterior cingulate and posterior cingulate showed the greatest increase with age, while the dorsolateral prefrontal cortex, orbitofrontal cortex, parietal and occipital cortices showed smaller increases with age. However, when only those aged 60+ were analyzed, the effect of age was no longer significant. This is consistent with previous research, and adds to evidence that age-related cognitive impairment, including Alzheimer’s, has its roots in damage occurring earlier in life.
In another study, brain scans of 408 participants in the Mayo Clinic Study of Aging also found that higher levels of amyloid-beta were associated with poorer cognitive performance — but that this interacted with APOE status. Specifically, carriers of the Alzheimer’s gene variant were significantly more affected by having higher levels of the protein.
This may explain the inconsistent findings of previous research concerning whether or not amyloid-beta has significant effects on cognition in normal adults.
As the researchers of the first study point out, what’s needed is information on the long-term course of these brain changes, and they are planning to follow these participants.
In the meantime, all in all, the findings do provide more strength to the argument that your lifestyle in mid-life (and perhaps even younger) may have long-term consequences for your brain in old age — particularly for those with a genetic susceptibility to Alzheimer’s.
 Rodrigue, K. M., Kennedy K. M., Devous M. D., Rieck J. R., Hebrank A. C., Diaz-Arrastia R., et al.
(2012). Β-Amyloid Burden in Healthy Aging Regional Distribution and Cognitive Consequences.
Neurology. 78(6), 387 - 395.
 Kantarci, K., Lowe V., Przybelski S. a, Weigand S. d, Senjem M. l, Ivnik R. J., et al.
(2012). APOE modifies the association between Aβ load and cognition in cognitively normal older adults.
Neurology. 78(4), 232 - 240.
New study modifies findings that younger adults are better decision-makers by showing older adults are better when the scenarios involve multiple considerations.
Research has shown that younger adults are better decision makers than older adults — a curious result. A new study tried to capture more ‘real-world’ decision-making, by requiring participants to evaluate each result in order to strategize the next choice.
This time (whew!), the older adults did better.
In the first experiment, groups of older (60-early 80s) and younger (college-age) adults received points each time they chose from one of four options and tried to maximize the points they earned. For this task, the younger adults were more efficient at selecting the options that yielded more points.
In the second experiment, the rewards received depended on the choices made previously. The “decreasing option” gave a larger number of points on each trial, but caused rewards on future trials to be lower. The “increasing option” gave a smaller reward on each trial but caused rewards on future trials to increase. In one version of the test, the increasing option led to more points earned over the course of the experiment; in another, chasing the increasing option couldn’t make up for the points that could be accrued grabbing the bigger bite on each trial.
The older adults did better on every permutation.
Understanding more complex scenarios is where experience tells. The difference in performance also may reflect the different ways younger and older adults use their brains. Decision-making can involve two different reward learning systems, according to recent thinking. In the model-based system, a cognitive model is constructed that shows how various actions and their rewards are connected to each other. Decisions are made by simulating how one decision will affect future decisions. In the model-free system, on the other hand, only values associated with each choice are considered.
These systems are rooted in different parts of the brain. The model-based system uses the intraparietal sulcus and lateral prefrontal cortex, while the model-free system uses the ventral striatum. There is some evidence that younger adults use the ventral striatum (involved in habitual, reflexive learning and immediate reward) for decision-making more than older adults, and older adults use the dorsolateral prefrontal cortex (involved in more rational, deliberative thinking) more than younger adults.
 Worthy, D. A., Gorlick M. A., Pacheco J. L., Schnyer D. M., & Maddox T. W.
(2011). With Age Comes Wisdom.
Learning two tasks or subjects one after another typically leads to poorer remembering of the first. A new study indicates the cause and suggests a remedy.
Trying to learn two different things one after another is challenging. Almost always some of the information from the first topic or task gets lost. Why does this happen? A new study suggests the problem occurs when the two information-sets interact, and demonstrates that disrupting that interaction prevents interference. (The study is a little complicated, but bear with me, or skip to the bottom for my conclusions.)
In the study, young adults learned two memory tasks back-to-back: a list of words, and a finger-tapping motor skills task. Immediately afterwards, they received either sham stimulation or real transcranial magnetic stimulation to the dorsolateral prefrontal cortex or the primary motor cortex. Twelve hours later the same day, they were re-tested.
As expected from previous research, word recall (being the first-learned task) declined in the control condition (sham stimulation), and this decline correlated with initial skill in the motor task. That is, the better they were at the second task, the more they forgot from the first task. This same pattern occurred among those whose motor cortex had been stimulated. However, there was no significant decrease in word recall for those who had received TMS to the dorsolateral prefrontal cortex.
Learning of the motor skill didn't differ between the three groups, indicating that this effect wasn't due to a disruption of the second task. Rather, it seems that the two tasks were interacting, and TMS to the DLPFC disrupted that interaction. This hypothesis was supported when the motor learning task was replaced by a motor performance task, which shouldn’t interfere with the word-learning task (the motor performance task was almost identical to the motor learning task except that it didn’t have a repeating sequence that could be learned). In this situation, TMS to the DLPFC produced a decrease in word recall (as it did in the other conditions, and as it would after a word-learning task without any other task following).
In the second set of experiments, the order of the motor and word tasks was reversed. Similar results occurred, with this time stimulation to the motor cortex being the effective intervention. In this case, there was a significant increase in motor skill on re-testing — which is what normally happens when a motor skill is learned on its own, without interference from another task (see my blog post on Mempowered for more on this). The word-learning task was then replaced with a vowel-counting task, which produced a non-significant trend toward a decrease in motor skill learning when TMS was applied to the motor cortex.
The effect of TMS depends on the activity in the region at the time of application. In this case, TMS was applied to the primary motor cortex and the DLPFC in the right hemisphere, because the right hemisphere is thought to be involved in integrating different types of information. The timing of the stimulation was critical: not during learning, and long before testing. The timing was designed to maximize any effects on interference between the two tasks.
The effect in this case mimics that of sleep — sleeping between tasks reduces interference between them. It’s suggested that both TMS and sleep reduce interference by reducing the communication between the prefrontal cortex and the mediotemporal lobe (of which the hippocampus is a part).
Here’s the problem: we're consolidating one set of memories while encoding another. So, we can do both at the same time, but as with any multitasking, one task is going to be done better than the other. Unsurprisingly, encoding appears to have priority over consolidation.
So something needs to regulate the activity of these two concurrent processes. Maybe something looks for commonalities between two actions occurring at the same time — this is, after all, what we’re programmed to do: we link things that occur together in space and time. So why shouldn’t that occur at this level too? Something’s just happened, and now something else is happening, and chances are they’re connected. So something in our brain works on that.
If the two events/sets of information are connected, that’s a good thing. If they’re not, we get interference, and loss of data.
So when we apply TMS to the prefrontal cortex, that integrating processor is perhaps disrupted.
The situation may be a little different where the motor task is followed by the word-list, because motor skill consolidation (during wakefulness at least) may not depend on the hippocampus (although declarative encoding does). However, the primary motor cortex may act as a bridge between motor skills and declarative memories (think of how we gesture when we explain something), and so it may this region that provides a place where the two types of information can interact (and thus interfere with each other).
In other words, the important thing appears to be whether consolidation of the first task occurs in a region where the two sets of information can interact. If it does, and assuming you don’t want the two information-sets to interact, then you want to disrupt that interaction.
Applying TMS is not, of course, a practical strategy for most of us! But the findings do suggest an approach to reducing interference. Sleep is one way, and even brief 20-minute naps have been shown to help learning. An intriguing speculation (I just throw this out) is that meditation might act similarly (rather like a sorbet between courses, clearing the palate).
Failing a way to disrupt the interaction, you might take this as a warning that it’s best to give your brain time to consolidate one lot of information before embarking on an unrelated set — even if it's in what appears to be a completely unrelated domain. This is particularly so as we get older, because consolidation appears to take longer as we age. For children, on the other hand, this is not such a worry. (See my blog post on Mempowered for more on this.)
 Cohen, D. A., & Robertson E. M.
(2011). Preventing interference between different memory tasks.
Nat Neurosci. 14(8), 953 - 955.
A study has successfully countered reduced activity in the prefrontal cortex seen in older monkeys. Clinical trials are now investigating whether the drug can improve working memory in older humans.
A study comparing activity in the dorsolateral prefrontal cortex in young, middle-aged and aged macaque monkeys as they performed a spatial working memory task has found that while neurons of the young monkeys maintained a high rate of firing during the task, neurons in older animals showed slower firing rates. The decline began in middle age.
Neuron activity was recorded in a particular area of the dorsolateral prefrontal cortex that is most important for visuospatial working memory. Some neurons only fired when the cue was presented (28 CUE cells), but most were active during the delay period as well as the cue and response periods (273 DELAY neurons). Persistent firing during the delay period is of particular interest, as it is required to maintain information in working memory. Many DELAY neurons increased their activity when the preferred spatial location was being remembered.
While the activity of the CUE cells was unaffected by age, that of DELAY cells was significantly reduced. This was true both of spontaneous activity and task-related activity. Moreover, the reduction was greatest during the cue and delay periods for the preferred direction, meaning that the effect of age was to reduce the ability to distinguish preferred and non-preferred directions.
It appeared that the aging prefrontal cortex was accumulating excessive levels of an important signaling molecule called cAMP. When cAMP was inhibited or cAMP-sensitive ion channels were blocked, firing rates rose to more youthful levels. On the other hand, when cAMP was stimulated, aged neurons reduced their activity even more.
The findings are consistent with rat research that has found two of the agents used — guanfacine and Rp-cAMPS — can improve working memory in aged rats. Guanfacine is a medication that is already approved for treating hypertension in adults and prefrontal deficits in children. A clinical trial testing guanfacine's ability to improve working memory and executive functions in elderly subjects who do not have dementia is now taking place.
 Wang, M., Gamo N. J., Yang Y., Jin L. E., Wang X-J., Laubach M., et al.
(2011). Neuronal basis of age-related working memory decline.
Nature. advance online publication,
Another recent meditation study has found that experienced Buddhist meditators use different brain regions than controls when making decisions in a ‘fairness’ game.
The study involved 26 experienced Buddhist meditators and 40 control subjects. Scans of their brains while they played the "ultimatum game," in which the first player proposes how to divide a sum of money and the second can accept or reject the proposal, revealed that the two groups engaged different parts of the brain when making these decisions.
Consistent with earlier studies, controls showed increased activity in the anterior insula (involved in disgust and emotional reactions to unfairness and betrayal) when the offers were unfair. However the Buddhist meditators showed higher activity instead in the posterior insula (involved in interoception and attention to the present moment). In other words, rather than dwelling on emotional reactions and imaginary what-if scenarios, the meditators concentrated on the interoceptive qualities that accompany any reward, no matter how small.
The meditators accepted unfair offers on more than half of the trials, whereas controls only accepted unfair offers on a quarter of the trials.
Moreover, those controls who did in fact play the game ‘rationally’ (that is, mostly accepting the unfair offers) showed activity in the dorsolateral prefrontal cortex, while rational meditators displayed increased activity in the somatosensory cortex and posterior superior temporal cortex.
The most intriguing thing about all this is not so much that regular meditation might change the way your brain works (although that is undeniably interesting), but as a more general demonstration that we can train our brain to work in different ways. Something to add to the research showing how brain regions shift in function in those with physical damage to their brains or sense organs (eg, in those who become blind).
 Kirk, U.
(2011). Interoception drives increased rational decision-making in meditators playing the ultimatum game.
Frontiers in Decision Neuroscience. 5, 49 - 49.
A new imaging study reveals what’s going on in the brains of expert shogi players that’s different from those of amateurs. It’s all about developing instincts.
The mental differences between a novice and an expert are only beginning to be understood, but two factors thought to be of importance are automaticity (the process by which a procedure becomes so practiced that it no longer requires conscious thought) and chunking (the unitizing of related bits of information into one tightly integrated unit — see my recent blog post on working memory). A new study adds to our understanding of this process by taking images of the brains of professional and amateur players of the Japanese chess-like game of shogi.
Eleven professional, 9 high- and 8 low-rank amateur players of shogi were presented with patterns of different types (opening shogi patterns, endgame shogi patterns, random shogi patterns, chess, Chinese chess, as well as completely different stimuli — scenes, faces, other objects, scrambled patterns).
It was found that the board game patterns, but not the other patterns, stimulated activity in the posterior precuneus of all shogi players. This activity, for the professional players, was particularly strong for shogi opening and endgame patterns, and activity in the precuneus was the only regional activity that showed a difference between these patterns and the other board game patterns. For the amateurs however, there was no differential activity for the endgame patterns, and only the high-rank amateurs showed differential activity for the opening shogi patterns. Opening patterns tend to be more stereotyped than endgame patterns (i.e., endgame patterns are better reflections of expertise).
The players were then asked for the best next-move in a series of shogi problems (a) when they only had one second to study the pattern, and (b) when they had eight seconds. When professional players had only a second to study the problem, the caudate nucleus was active. When they had 8 seconds, activity was confined to the cerebral cortex, as it was for the amateurs in both conditions. This activity in the caudate, which is part of the basal ganglia, deep within the brain, is thought to reflect the development of an intuitive response.
The researchers therefore suggest that this type of intuition, an instinct achieved through training and experience, is what marks an expert. Making part of the process unconscious not only makes it faster, but frees up valuable space in working memory for aspects that need conscious thought.
The posterior precuneus directly connects with the dorsolateral prefrontal cortex, which in turn connects to the caudate. There is also a direct connection between the precuneus and the caudate. This precuneus-caudate circuit is therefore suggested as a key part of what makes a board-game expert an expert.
 Wan, X., Nakatani H., Ueno K., Asamizuya T., Cheng K., & Tanaka K.
(2011). The Neural Basis of Intuitive Best Next-Move Generation in Board Game Experts.
Science. 331(6015), 341 - 346.
Being actively involved improves learning significantly, and new research shows that the hippocampus is at the heart of this process.
We know active learning is better than passive learning, but for the first time a study gives us some idea of how that works. Participants in the imaging study were asked to memorize an array of objects and their exact locations in a grid on a computer screen. Only one object was visible at a time. Those in the "active study” group used a computer mouse to guide the window revealing the objects, while those in the “passive study” group watched a replay of the window movements recorded in a previous trial by an active subject. They were then tested by having to place the items in their correct positions. After a trial, the active and passive subjects switched roles and repeated the task with a new array of objects.
The active learners learned the task significantly better than the passive learners. Better spatial recall correlated with higher and better coordinated activity in the hippocampus, dorsolateral prefrontal cortex, and cerebellum, while better item recognition correlated with higher activity in the inferior parietal lobe, parahippocampal cortex and hippocampus.
The critical role of the hippocampus was supported when the experiment was replicated with those who had damage to this region — for them, there was no benefit in actively controlling the viewing window.
This is something of a surprise to researchers. Although the hippocampus plays a crucial role in memory, it has been thought of as a passive participant in the learning process. This finding suggests that it is actually part of an active network that controls behavior dynamically.
 Voss, J. L., Gonsalves B. D., Federmeier K. D., Tranel D., & Cohen N. J.
(2011). Hippocampal brain-network coordination during volitional exploratory behavior enhances learning.
Nat Neurosci. 14(1), 115 - 120.
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