Mediotemporal Lobe

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.

Those with sleep apnea and a BMI under 25 showed several Alzheimer’s biomarkers (increased levels of tau in the cerebrospinal fluid, greater atrophy of the hippocampus, glucose hypometabolism in regions vulnerable to Alzheimer’s). This (with the exception of glucose hypometabolism in the mediotemporal lobe only) was not found in those with sleep apnea and a higher BMI.

The study involved 68 healthy older adults (average age 71), of whom 18 had normal breathing, 33 mild sleep apnea, and 17 moderate-severe apnea. Those in the latter group tended to have higher BMIs.

Some 10-20% of middle-aged adults in the U.S. have sleep apnea, and this jumps dramatically in those over 65 (30-60%), where the link to obesity is much smaller. The researchers suggest that early preclinical Alzheimer’s damage might be a reason, and plan follow-up research to assess what impact CPAP therapy for sleep apnea has on the Alzheimer’s biomarkers.

Those interested in the relationship between poor sleep and later development of Alzheimer’s might also like to read a Guardian article on the subject.

http://www.eurekalert.org/pub_releases/2013-05/ats-sft051413.php

Osorio, R.S. et al. 2013. Sleep-Disordered Breathing, Aging And Risk For Alzheimer's Disease In Cognitively Normal Subjects. Abstract 38456. Presented at the ATS 2013 International Conference.

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?

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.

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.

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.

[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.

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.

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.

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.)

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

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.

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.

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.

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.

Older news items (pre-2010) brought over from the old website

December 2008

MRI brain scans accurate in early diagnosis of Alzheimer's disease

Adding to the growing body of evidence indicating MRI brain scans provide valuable diagnostic information about Alzheimer's disease, a study in which a new visual rating system for evaluating the severity of shrinkage in the medial temporal lobe was used on brain scans of 260 people has found that scores accurately distinguished those with Alzheimer’s from those with mild cognitive impairment and those without memory problems. The test also accurately predicted those who would move from one group to another within a year or two.

Duara, R. et al. 2008. Medial temporal lobe atrophy on MRI scans and the diagnosis of Alzheimer disease. Neurology, 71, 1986-1992.

http://www.eurekalert.org/pub_releases/2008-12/uosf-mbs121808.php

August 2007

Maturity brings richer memories

New research suggests adults can remember more contextual details than children, and that this is related to the development of the prefrontal cortex. While in a MRI scanner, 49 volunteers aged eight to 24 were shown pictures of 250 common scenes and told they would be tested on their memory of these scenes. In both children and adults, correct recognition of a scene was associated with higher activation in several areas of the prefrontal cortex and the medial temporal lobe when they were studying the pictures. However, the older the volunteers, the more frequently their correct answers were enriched with contextual detail. These more detailed memories correlated with more intense activation in a specific region of the PFC. A number of studies have suggested that the PFC develops later than other brain regions.

The report appeared in the August 5 advance online edition of Nature Neuroscience.

http://www.physorg.com/news105549812.html
http://www.eurekalert.org/pub_releases/2007-08/miot-msm080107.php

August 2005

Rating familiarity: how we do it

Previous research has indicated that recognizing a familiar object is accompanied by a reduction in activity in the medial temporal lobe. A new imaging study has confirmed the reduced activity and demonstrated that the degree of reduction is correlated with the degree of familiarity of the object (a face in this instance). The reduction began very rapidly in the recognition process. The researchers suggested that the graded response of medial temporal structures are what allows us to assess how familiar an object is.

Gonsalves, B.D., Curran, T., Norman, K.A. & Wagner, A.D. 2005. Memory Strength and Repetition Suppression: Multimodal Imaging of Medial Temporal Cortical Contributions to Recognition. Neuron, 47, 751–761.

http://www.eurekalert.org/pub_releases/2005-08/cp-tt082505.php

June 2005

Single cell recognition research finds specific neurons for concepts

An intriguing study surprises cognitive researchers by showing that individual neurons in the medial temporal lobe are able to recognize specific people and objects. It’s long been thought that concepts such as these require a network of cells, and this doesn’t deny that many cells are involved. However, this new study points to the importance of a single brain cell. The study of 8 epileptic subjects found variable responses from subjects, but within subjects, individuals showed remarkably specific responses to concepts. For example, a single neuron in the left posterior hippocampus of one subject responded to all pictures of actress Jennifer Aniston, and also to Lisa Kudrow, her co-star on the TV hit "Friends", but not to pictures of Jennifer Aniston together with actor Brad Pitt, and not, or only very weakly, to other famous and non-famous faces, landmarks, animals or objects. In another patient, pictures of actress Halle Berry activated a neuron in the right anterior hippocampus, as did a caricature of the actress, images of her in the lead role of the film "Catwoman," and a letter sequence spelling her name. The results suggest an invariant, sparse and explicit code, which might be important in the transformation of complex visual percepts into long-term and more abstract memories.

Quiroga, R.Q., Reddy, L., Kreiman, G., Koch, C & Fried, I. 2005. Invariant visual representation by single neurons in the human brain. Nature, 435, 1102-1107.

http://www.eurekalert.org/pub_releases/2005-06/uoc--scr062005.php

May 2005

Long-term storage of autobiographical memories

By studying in detail the ability of patients with selective brain damage to recall events in their past, researchers have helped settle a long-standing controversy about whether long-term memory of one's personal experiences continue to be stored in the medial temporal lobe, or whether they gradually become independent of this area. The evidence from this new study suggests that autobiographical memories gradually become distributed throughout the neocortex.

Bayley, P.J., Gold, J.J., Hopkins, R.O. & Squire, L.R. 2005. The Neuroanatomy of Remote Memory. Neuron, 46, 799–810.

http://www.eurekalert.org/pub_releases/2005-06/cp-wlm052605.php

October 2004

Development of working memory with age

An imaging study of 20 healthy 8- to 30-year-olds has shed new light on the development of working memory. The study found that pre-adolescent children relied most heavily on the prefrontal cortex and parietal regions of the brain during the working memory task; adolescents used those regions plus the anterior cingulate; and in adults, a third area of the brain, the medial temporal lobe, was brought in to support the functions of the other areas. Adults performed best. The results support the view that a person's ability to have voluntary control over behavior improves with age because with development, additional brain processes are used.

http://www.eurekalert.org/pub_releases/2004-10/uopm-dow102104.php

September 2004

New technique sheds light on autobiographical memory

A new technique for studying autobiographical memory has revealed new findings about autobiographical memory, and may prove useful in studying age-related cognitive impairment. Previous inconsistencies between controlled laboratory studies of memory (typically, subjects are asked to remember items they have previously seen in the laboratory, such as words presented on a computer screen) and studies of autobiographical memory have seemed to indicate that the brain may function differently in the two processes. However, such differences might instead reflect how the memories are measured. In an effort to provide greater control over the autobiographical memories, volunteer subjects were given cameras and instructed to take pictures of campus scenes. The subjects were also instructed to remember the taking of each picture as an individual event, noting the physical conditions and their psychological state, such as their mood and associations with the subject of the images. The subjects were then shown a selection of campus photos they had not taken. While their brains were scanned, they were then shown a mix of their own photos with those they had not taken, and asked to indicate whether each photo was new, seen earlier in the lab, or one they had taken themselves. The researchers found that recalling the autobiographical memories activated many of the same brain areas as laboratory memories (the medial temporal lobe and the prefrontal cortex); however, they also activated brain areas associated with "self-referential processing" (processing information about one's self), and regions associated with retrieval of visual and spatial information, as well as showing a higher level of activity in the recollection areas in the hippocampus.

The report will appear in the November issue of the Journal of Cognitive Neuroscience.

http://www.eurekalert.org/pub_releases/2004-09/du-blm092904.php

November 2003

Questioning the medial temporal lobe

The medial temporal lobe includes the hippocampus, the amygdala, and the entorhinal and perirhinal cortices. It is often talked about as a single unit, but recently a prominent neurobiologist has questioned this usage. For one thing, the region didn’t evolve as one unit — the different regions arose at different times during primate evolution. Therefore, can it really be an integrated system with a common function? Her work with rhesus monkeys suggests rather that these different parts may serve cooperative and even competitive functions.

Magnetic resonance imaging may help predict future memory decline

A six-year imaging study of 45 healthy seniors assessed changes in brain scans against cognitive decline. They found that progressive atrophy in the medial temporal lobe was the most significant predictor of cognitive decline, which occurred in 29% of the subjects.

Rusinek, H., De Santi, S., Frid, D., Tsui, W-H., Tarshish, C.Y., Convit, A., & de Leon, M.J. 2003. Regional Brain Atrophy Rate Predicts Future Cognitive Decline: 6-year Longitudinal MR Imaging Study of Normal Aging. Radiology, 229, 691-696.

http://www.eurekalert.org/pub_releases/2003-11/rson-mhr111703.php

March 2003

Activity in the mediotemporal lobe lower in elderly with poor memory

An imaging study has revealed that, although there is no difference on standard MRI scans,scans showing the amount of oxygen (and thus activity) find that elderly persons with a poor memory have less activity in the mediotemporal lobe when storing new information than elderly persons with a normally functioning memory.This more sensitive scan may help early diagnosis of Alzheimer's.

The research was done as part of a doctoral thesis by Dr Sander Daselaar.

http://www.eurekalert.org/pub_releases/2003-03/nofs-svp032103.php

November 2001

Imaging study confirms role of medial temporal lobe in memory consolidation

Lesions in the medial temporal lobe (MTL) typically produce amnesia characterized by the disproportionate loss of recently acquired memories. Such memory loss has been interpreted as evidence for a memory consolidation process guided by the MTL. A recent imaging study confirms this view by showing temporally graded changes in MTL activity in healthy older adults taking a famous faces remote memory test. Evidence for such temporally graded change in the hippocampal formation was mixed, suggesting it may participate only in consolidation processes lasting a few years. The entorhinal cortex (also part of the MTL) was associated with temporally graded changes extending up to 20 years, suggesting that it is the entorhinal cortex, rather than the hippocampal formation, that participates in memory consolidation over decades. The entorhinal cortex is damaged in the early stages of Alzheimer’s disease (AD).

Haist, F., Gore, J.B. & Mao, H. 2001. Consolidation of human memory over decades revealed by functional magnetic resonance imaging. Nature neuroscience, 4 (11), 1139-1145.

http://www.nature.com/neurolink/v4/n11/abs/nn739.html

Competition between memory systems

Learning and memory in humans rely upon several memory systems. For example, the medial temporal lobe (MTL) is associated with declarative learning (facts and events). The basal ganglia is associated with nondeclarative learning (learning you derive from experience, that may not be conscious). A recent imaging study looked at how these memory systems interact during classification learning. During the nondeclarative learning task, there was an increase in activity in the basal ganglia, and a decrease in activity in the MTL. During the memorization task (testing declarative learning), the reverse was true. Further examination found rapid modulation of activity in these regions at the beginning of learning, suggesting that subjects relied upon the medial temporal lobe early in learning. However, this dependence rapidly declined with training.

Poldrack, R.A., Clark, J., Paré-blagoev, E.J., Shohamy, D., Moyano, J.C., Myers, C. & Gluck, M.A. 2001. Interactive memory systems in the human brain. Nature, 414, 546 - 550.

http://www.nature.com/cgi-taf/DynaPage.taf?file=/nature/journal/v414/n6863/abs/414546a0_fs.html
http://www.eurekalert.org/pub_releases/2001-11/mgh-isi112601.php

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