mediotemporal lobe

includes the hippocampus, the amygdala, and the entorhinal and perirhinal cortices. Although given this name, the idea that this is an integrated memory system with a common function has recently been questioned. It is observed that the various components evolved at different points. Nevertheless, we may say that the MTL appears to be involved in declarative learning (facts and events), being particularly important during initial learning. There is some evidence that long-term consolidation of memories is guided by the MTL, in particular by the entorhinal cortex (which is damaged in the early stages of Alzheimer’s disease). Moreover, a recent study showed that progressive atrophy in the medial temporal lobe was the most significant predictor of cognitive decline in seniors.

More evidence for link between sleep apnea and Alzheimer's

A new study adds to growing evidence of a link between sleep problems and Alzheimer’s. The interesting thing is that this association – between sleep apnea and Alzheimer’s biomarkers — wasn’t revealed until the data was separated out according to BMI.

05/2013

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Cut ‘visual clutter’ to help MCI & Alzheimer’s

October, 2012

A small study shows that those with MCI perform poorly on a visual discrimination task under high interference conditions, suggesting that reducing interference may improve cognitive performance.

Memory problems in those with mild cognitive impairment may begin with problems in visual discrimination and vulnerability to interference — a hopeful discovery in that interventions to improve discriminability and reduce interference may have a flow-on effect to cognition.

The study compared the performance on a complex object discrimination task of 7 patients diagnosed with amnestic MCI, 10 older adults considered to be at risk for MCI (because of their scores on a cognitive test), and 19 age-matched controls. The task involved the side-by-side comparison of images of objects, with participants required to say, within 15 seconds, whether the two objects were the same or different.

In the high-interference condition, the objects were blob-like and presented as black and white line-drawings, with some comparison pairs identical, while others only varied slightly in either shape or fill pattern. Objects were rotated to discourage a simple feature-matching strategy. In the low-interference condition, these line-drawings were interspersed with color photos of everyday objects, for which discriminability was dramatically easier. The two conditions were interspersed by a short break, with the low interference condition run in two blocks, before and after the high interference condition.

A control task, in which the participants compared two squares that could vary in size, was run at the end.

The study found that those with MCI, as well as those at risk of MCI, performed significantly worse than the control group in the high-interference condition. There was no difference in performance between those with MCI and those at risk of MCI. Neither group was impaired in the first low-interference condition, although the at-risk group did show significant impairment in the second low-interference condition. It may be that they had trouble recovering from the high-interference experience. However, the degree of impairment was much less than it was in the high-interference condition. It’s also worth noting that the performance on this second low-interference task was, for all groups, notably higher than it was on the first low-interference task.

There was no difference between any of the groups on the control task, indicating that fatigue wasn’t a factor.

The interference task was specifically chosen as one that involved the perirhinal cortex, but not the hippocampus. The task requires the conjunction of features — that is, you need to be able to see the object as a whole (‘feature binding’), not simply match individual features. The control task, which required only the discrimination of a single feature, shows that MCI doesn’t interfere with this ability.

I do note that the amount of individual variability on the interference tasks was noticeably greater in the MCI group than the others. The MCI group was of course smaller than the other groups, but variability wasn’t any greater for this group in the control task. Presumably this variability reflects progression of the impairment, but it would be interesting to test this with a larger sample, and map performance on this task against other cognitive tasks.

Recent research has suggested that the perirhinal cortex may provide protection from visual interference by inhibiting lower-level features. The perirhinal cortex is strongly connected to the hippocampus and entorhinal cortex, two brain regions known to be affected very early in MCI and Alzheimer’s.

The findings are also consistent with other evidence that damage to the medial temporal lobe may impair memory by increasing vulnerability to interference. For example, one study has found that story recall was greatly improved in patients with MCI if they rested quietly in a dark room after hearing the story, rather than being occupied in other tasks.

There may be a working memory component to all this as well. Comparison of two objects does require shifting attention back and forth. This, however, is separate to what the researchers see as primary: a perceptual deficit.

All of this suggests that reducing “visual clutter” could help MCI patients with everyday tasks. For example, buttons on a telephone tend to be the same size and color, with the only difference lying in the numbers themselves. Perhaps those with MCI or early Alzheimer’s would be assisted by a phone with varying sized buttons and different colors.

The finding also raises the question: to what extent is the difficulty Alzheimer’s patients often have in recognizing a loved one’s face a discrimination problem rather than a memory problem?

Finally, the performance of the at-risk group — people who had no subjective concerns about their memory, but who scored below 26 on the MoCA (Montreal Cognitive Assessment — a brief screening tool for MCI) — suggests that vulnerability to visual interference is an early marker of cognitive impairment that may be useful in diagnosis. It’s worth noting that, across all groups, MoCA scores predicted performance on the high-interference task, but not on any of the other tasks.

So how much cognitive impairment rests on problems with interference?

Reference: 

Newsome, R. N., Duarte, A., & Barense, M. D. (2012). Reducing Perceptual Interference Improves Visual Discrimination in Mild Cognitive Impairment : Implications for a Model of Perirhinal Cortex Function, Hippocampus, 22, 1990–1999. doi:10.1002/hipo.22071

Della Sala S, Cowan N, Beschin N, Perini M. 2005. Just lying there, remembering: Improving recall of prose in amnesic patients with mild cognitive impairment by minimising interference. Memory, 13, 435–440.

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Sleep learning making a comeback?

August, 2012

Two new studies provide support for the judicious use of sleep learning — as a means of reactivating learning that occurred during the day.

Back when I was young, sleep learning was a popular idea. The idea was that a tape would play while you were asleep, and learning would seep into your brain effortlessly. It was particularly advocated for language learning. Subsequent research, unfortunately, rejected the idea, and gradually it has faded (although not completely). Now a new study may presage a come-back.

In the study, 16 young adults (mean age 21) learned how to ‘play’ two artificially-generated tunes by pressing four keys in time with repeating 12-item sequences of moving circles — the idea being to mimic the sort of sensorimotor integration that occurs when musicians learn to play music. They then took a 90-minute nap. During slow-wave sleep, one of the tunes was repeatedly played to them (20 times over four minutes). After the nap, participants were tested on their ability to play the tunes.

A separate group of 16 students experienced the same events, but without the playing of the tune during sleep. A third group stayed awake, during which 90-minute period they played a demanding working memory task. White noise was played in the background, and the melody was covertly embedded into it.

Consistent with the idea that sleep is particularly helpful for sensorimotor integration, and that reinstating information during sleep produces reactivation of those memories, the sequence ‘practiced’ during slow-wave sleep was remembered better than the unpracticed one. Moreover, the amount of improvement was positively correlated with the proportion of time spent in slow-wave sleep.

Among those who didn’t hear any sounds during sleep, improvement likewise correlated with the proportion of time spent in slow-wave sleep. The level of improvement for this group was intermediate to that of the practiced and unpracticed tunes in the sleep-learning group.

The findings add to growing evidence of the role of slow-wave sleep in memory consolidation. Whether the benefits for this very specific skill extend to other domains (such as language learning) remains to be seen.

However, another recent study carried out a similar procedure with object-location associations. Fifty everyday objects were associated with particular locations on a computer screen, and presented at the same time with characteristic sounds (e.g., a cat with a meow and a kettle with a whistle). The associations were learned to criterion, before participants slept for 2 hours in a MR scanner. During slow-wave sleep, auditory cues related to half the learned associations were played, as well as ‘control’ sounds that had not been played previously. Participants were tested after a short break and a shower.

A difference in brain activity was found for associated sounds and control sounds — associated sounds produced increased activation in the right parahippocampal cortex — demonstrating that even in deep sleep some sort of differential processing was going on. This region overlapped with the area involved in retrieval of the associations during the earlier, end-of-training test. Moreover, when the associated sounds were played during sleep, parahippocampal connectivity with the visual-processing regions increased.

All of this suggests that, indeed, memories are being reactivated during slow-wave sleep.

Additionally, brain activity in certain regions at the time of reactivation (mediotemporal lobe, thalamus, and cerebellum) was associated with better performance on the delayed test. That is, those who had greater activity in these regions when the associated sounds were played during slow-wave sleep remembered the associations best.

The researchers suggest that successful reactivation of memories depends on responses in the thalamus, which if activated feeds forward into the mediotemporal lobe, reinstating the memories and starting the consolidation process. The role of the cerebellum may have to do with the procedural skill component.

The findings are consistent with other research.

All of this is very exciting, but of course this is not a strategy for learning without effort! You still have to do your conscious, attentive learning. But these findings suggest that we can increase our chances of consolidating the material by replaying it during sleep. Of course, there are two practical problems with this: the material needs an auditory component, and you somehow have to replay it at the right time in your sleep cycle.

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Brain atrophy may predict risk for early Alzheimer's disease

January, 2012
  • Shrinking of certain brain regions predicts age-related cognitive decline and dementia, with greater brain tissue loss markedly increasing risk.

A study involving 159 older adults (average age 76) has confirmed that the amount of brain tissue in specific regions is a predictor of Alzheimer’s disease development. Of the 159 people, 19 were classified as at high risk on the basis of the smaller size of nine small regions previously shown to be vulnerable to Alzheimer's), and 24 as low risk. The regions, in order of importance, are the medial temporal, inferior temporal, temporal pole, angular gyrus, superior parietal, superior frontal, inferior frontal cortex, supramarginal gyrus, precuneus.

There was no difference between the three risk groups at the beginning of the study on global cognitive measures (MMSE; Alzheimer’s Disease Assessment Scale—cognitive subscale; Clinical Dementia Rating—sum of boxes), or in episodic memory. The high-risk group did perform significantly more slowly on the Trail-making test part B, with similar trends on the Digit Symbol and Verbal Fluency tests.

After three years, 125 participants were re-tested. Nine met the criteria for cognitive decline. Of these, 21% were from the small high-risk group (3/14) and 7% from the much larger average-risk group (6/90). None were from the low-risk group.

The results were even more marked when less stringent criteria were used. On the basis of an increase on the Clinical Dementia Rating, 28.5% of the high-risk group and 9.7% of the average-risk group showed decline. On the basis of declining at least one standard deviation on any one of the three neuropsychological tests, half the high-risk group, 35% of the average risk group, and 14% (3/21) of the low-risk group showed decline. (The composite criteria required both of these criteria.)

Analysis estimated that every standard deviation of cortical thinning (reduced brain tissue) was associated with a nearly tripled risk of cognitive decline.

The 84 individuals for whom amyloid-beta levels in the cerebrospinal fluid were available also revealed that 60% of the high-risk group had levels consistent with the presence of Alzheimer's pathology, compared to 36% of those at average risk and 19% of those at low risk.

The findings extend and confirm the evidence that brain atrophy in specific regions is a biomarker for developing Alzheimer’s.

Reference: 

[2709] Dickerson, B. C., & Wolk D. A.
(2012).  MRI cortical thickness biomarker predicts AD-like CSF and cognitive decline in normal adults.
Neurology. 78(2), 84 - 90.

Dickerson BC, Bakkour A, Salat DH, et al. 2009. The cortical signature of Alzheimer’s disease: regionally specific cortical thinning relates to symptom severity in very mild to mild AD dementia and is detectable in asymptomatic amyloidpositive individuals. Cereb Cortex;19:497–510.

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Why a select group of seniors retain their cognitive abilities

December, 2011
  • Comparison of the brains of octogenarians whose memories match those of middle-aged people reveals important differences between their brains and those of cognitively-normal seniors.

A certain level of mental decline in the senior years is regarded as normal, but some fortunate few don’t suffer from any decline at all. The Northwestern University Super Aging Project has found seniors aged 80+ who match or better the average episodic memory performance of people in their fifties. Comparison of the brains of 12 super-agers, 10 cognitively-normal seniors of similar age, and 14 middle-aged adults (average age 58) now reveals that the brains of super-agers also look like those of the middle-aged. In contrast, brain scans of cognitively average octogenarians show significant thinning of the cortex.

The difference between the brains of super-agers and the others was particularly marked in the anterior cingulate cortex. Indeed, the super agers appeared to have a much thicker left anterior cingulate cortex than the middle-aged group as well. Moreover, the brain of a super-ager who died revealed that, although there were some plaques and tangles (characteristic, in much greater quantities, of Alzheimer’s) in the mediotemporal lobe, there were almost none in the anterior cingulate. (But note an earlier report from the researchers)

Why this region should be of special importance is somewhat mysterious, but the anterior cingulate is part of the attention network, and perhaps it is this role that underlies the superior abilities of these seniors. The anterior cingulate also plays a role error detection and motivation; it will be interesting to see if these attributes are also important.

While the precise reason for the anterior cingulate to be critical to retaining cognitive abilities might be mysterious, the lack of cortical atrophy, and the suggestion that super-agers’ brains have much reduced levels of the sort of pathological damage seen in most older brains, adds weight to the growing evidence that cognitive aging reflects clinical problems, which unfortunately are all too common.

Sadly, there are no obvious lifestyle factors involved here. The super agers don’t have a lifestyle any different from their ‘cognitively average’ counterparts. However, while genetics might be behind these people’s good fortune, that doesn’t mean that lifestyle choices don’t make a big difference to those of us not so genetically fortunate. It seems increasingly clear that for most of us, without ‘super-protective genes’, health problems largely resulting from lifestyle choices are behind much of the damage done to our brains.

It should be emphasized that these unpublished results are preliminary only. This conference presentation reported on data from only 12 of 48 subjects studied.

Reference: 

Harrison, T., Geula, C., Shi, J., Samimi, M., Weintraub, S., Mesulam, M. & Rogalski, E. 2011. Neuroanatomic and pathologic features of cognitive SuperAging. Presented at a poster session at the 2011 Society for Neuroscience conference.

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Preventing interference between topics or skills

September, 2011

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.)

Reference: 

[2338] Cohen, D. A., & Robertson E. M.
(2011).  Preventing interference between different memory tasks.
Nat Neurosci. 14(8), 953 - 955.

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How we can control individual neurons

November, 2010

Every moment a multitude of stimuli compete for our attention. Just how this competition is resolved, and how we control it, is not known. But a new study adds to our understanding.

Following on from earlier studies that found individual neurons were associated with very specific memories (such as a particular person), new research has shown that we can actually regulate the activity of specific neurons, increasing the firing rate of some while decreasing the rate of others.

The study involved 12 patients implanted with deep electrodes for intractable epilepsy. On the basis of each individual’s interests, four images were selected for each patient. Each of these images was associated with the firing of specific neurons in the mediotemporal lobe. The firing of these neurons was hooked up to a computer, allowing the patients to make their particular images appear by thinking of them. When another image appeared on top of the image as a distraction, creating a composite image, patients were asked to focus on their particular image, brightening the target image while the distractor image faded. The patients were successful 70% of the time in brightening their target image. This was primarily associated with increased firing of the specific neurons associated with that image.

I should emphasize that the use of a composite image meant that the participants had to rely on a mental representation rather than the sensory stimuli, at least initially. Moreover, when the feedback given was fake — that is, the patients’ efforts were no longer linked to the behavior of the image on the screen — success rates fell dramatically, demonstrating that their success was due to a conscious, directed action.

Different patients used different strategies to focus their attention. While some simply thought of the picture, others repeated the name of the image out loud or focused their gaze on a particular aspect of the image.

Resolving the competition of multiple internal and external stimuli is a process which involves a number of different levels and regions, but these findings help us understand at least some of the process that is under our conscious control. It would be interesting to know more about the relative effectiveness of the different strategies people used, but this was not the focus of the study. It would also be very interesting to compare effectiveness at this task across age, but of course this procedure is invasive and can only be used in special cases.

The study offers hope for building better brain-machine interfaces.

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Distinguishing between working memory and long-term memory

November, 2010

A study with four brain-damaged people challenges the idea that the hippocampus is the hub of spatial and relational processing for short-term as well as long-term memory.

Because people with damage to their hippocampus are sometimes impaired at remembering spatial information even over extremely short periods of time, it has been thought that the hippocampus is crucial for spatial information irrespective of whether the task is a working memory or a long-term memory task. This is in contrast to other types of information. In general, the hippocampus (and related structures in the mediotemporal lobe) is assumed to be involved in long-term memory, not working memory.

However, a new study involving four patients with damage to their mediotemporal lobes, has found that they were perfectly capable of remembering for one second the relative positions of three or fewer objects on a table — but incapable of remembering more. That is, as soon as the limits of working memory were reached, their performance collapsed. It appears, therefore, that there is, indeed, a fundamental distinction between working memory and long-term memory across the board, including the area of spatial information and spatial-objection relations.

The findings also underscore how little working memory is really capable of on its own (although absolutely vital for what it does!) — in real life, long-term memory and working memory work in tandem.

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Change in our understanding of memory development

September, 2010

Children’s slowly developing memory for past events may not be due to the slow development of the prefrontal cortex, as was thought, but to changes in the hippocampus.

Children’s ability to remember past events improves as they get older. This has been thought by many to be due to the slow development of the prefrontal cortex. But now brain scans from 60 children (8-year-olds, 10- to 11-year-olds, and 14-year-olds) and 20 young adults have revealed marked developmental differences in the activity of the mediotemporal lobe.

The study involved the participants looking at a series of pictures (while in the scanner), and answering a different question about the image, depending on whether it was drawn in red or green ink. Later they were shown the pictures again, in black ink and mixed with new ones. They were asked whether they had seen them before and whether they had been red or green.

While the adolescents and adults selectively engaged regions of the hippocampus and posterior parahippocampal gyrus to recall event details, the younger children did not, with the 8-year-olds indiscriminately using these regions for both detail recollection and item recognition, and the 10- to 11-year-olds showing inconsistent activation. It seems that the hippocampus and posterior parahippocampal gyrus become increasingly specialized for remembering events, and these changes may partly account for long-term memory improvements during childhood.

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Alzheimer's expressed differently in carriers and noncarriers of the Alzheimer’s gene

July, 2010
  • A new study reveals that having the 'Alzheimer's gene' doesn't simply increase your risk of developing Alzheimer's, but affects how the brain is damaged.

A comprehensive study reveals how the ‘Alzheimer's gene’ (APOE ε4) affects the nature of the disease. It is not simply that those with the gene variant tend to be more impaired (in terms of both memory loss and brain damage) than those without. Different parts of the brain (and thus different functions) tend to be differentially affected, depending on whether the individual is a carrier of the gene or not. Carriers displayed significantly greater impairment on tests of memory retention, while noncarriers were more impaired on tests of working memory, executive control, and lexical access. Consistent with this, carriers showed greater atrophy in the mediotemporal lobe, and noncarriers greater atrophy in the frontoparietal area. The findings have implications both for diagnosis and treatment.

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