Latest Research News
A new study involving 96 older adults initially free of dementia at the time of enrollment, of whom 12 subsequently developed mild Alzheimer’s, has clarified three fundamental issues about Alzheimer's: where it starts, why it starts there, and how it spreads.
Specifically, it begins in the lateral entorhinal cortex (LEC), a gateway to the hippocampus. Over time, Alzheimer's spreads from the LEC directly to other areas of the cerebral cortex, in particular the parietal cortex. It’s thought that it spreads by compromising the function of neurons in the LEC, which then compromises the integrity of neurons in adjoining areas.
Mouse models comparing the effects of elevated levels of tau in the LEC with elevated levels of APP, and with elevated levels of both, found that LEC dysfunction occurred only in the mice with high levels of both tau and APP. The LEC normally accumulates tau, making it more vulnerable to the accumulation of APP.
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.
I’ve always felt that better thinking was associated with my brain working ‘in a higher gear’ — literally working at a faster rhythm. So I was particularly intrigued by the findings of a recent mouse study that found that brainwaves associated with learning became stronger as the mice ran faster.
In the study, 12 male mice were implanted with microelectrodes that monitored gamma waves in the hippocampus, then trained to run back and forth on a linear track for a food reward. Gamma waves are thought to help synchronize neural activity in various cognitive functions, including attention, learning, temporal binding, and awareness.
We know that the hippocampus has specialized ‘place cells’ that record where we are and help us navigate. But to navigate the world, to create a map of where things are, we need to also know how fast we are moving. Having the same cells encode both speed and position could be problematic, so researchers set out to find how speed was being encoded. To their surprise and excitement, they found that the strength of the gamma rhythm grew substantially as the mice ran faster.
The results also confirmed recent claims that the gamma rhythm, which oscillates between 30 and 120 times a second, can be divided into slow and fast signals (20-45 Hz vs 45-120 Hz for mice, consistent with the 30-55 Hz vs 45-120 Hz bands found in rats) that originate from separate parts of the brain. The slow gamma waves in the CA1 region of the hippocampus were synchronized with slow gamma waves in CA3, while the fast gamma in CA1 were synchronized with fast gamma waves in the entorhinal cortex.
The two signals became increasingly separated with increasing speed, because the two bands were differentially affected by speed. While the slow waves increased linearly, the fast waves increased logarithmically. This differential effect could have to do with mechanisms in the source regions (CA3 and the medial entorhinal cortex, respectively), or to mechanisms in the different regions in CA1 where the inputs terminate (the waves coming from CA3 and the entorhinal cortex enter CA1 in different places).
In the hippocampus, gamma waves are known to interact with theta waves. Further analysis of the data revealed that the effects of speed on gamma rhythm only occurred within a narrow range of theta phases — but this ‘preferred’ theta phase also changed with running speed, more so for the slow gamma waves than the fast gamma waves (which is not inconsistent with the fact that slow gamma waves are more affected by running speed than fast gamma waves). Thus, while slow and fast gamma rhythms preferred similar phases of theta at low speeds, the two rhythms became increasingly phase-separated with increasing running speed.
What’s all this mean? Previous research has shown that if inputs from CA3 and the entorhinal cortex enter CA1 at the same time, the kind of long-term changes at the synapses that bring about learning are stronger and more likely in CA1. So at low speeds, synchronous inputs from CA3 and the entorhinal cortex at similar theta phases make them more effective at activating CA1 and inducing learning. But the faster you move, the more quickly you need to process information. The stronger gamma waves may help you do that. Moreover, the theta phase separation of slow and fast gamma that increases with running speed means that activity in CA3 (slow gamma source) increasingly anticipates activity in the medial entorhinal cortex (fast gamma source).
What does this mean at the practical level? Well at this point it can only be speculation that moving / exercising can affect learning and attention, but I personally am taking this on board. Most of us think better when we walk. This suggests that if you’re having trouble focusing and don’t have time for that, maybe walking down the hall or even jogging on the spot will help bring your brain cells into order!
Pushing speculation even further, I note that meditation by expert meditators has been associated with changes in gamma and theta rhythms. And in an intriguing comparison of the effect of spoken versus sung presentation on learning and remembering word lists, the group that sang showed greater coherence in both gamma and theta rhythms (in the frontal lobes, admittedly, but they weren’t looking elsewhere).
So, while we’re a long way from pinning any of this down, it may be that all of these — movement, meditation, music — can be useful in synchronizing your brain rhythms in a way that helps attention and learning. This exciting discovery will hopefully be the start of an exploration of these possibilities.
Full text available at http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0021408
As we get older, when we suffer memory problems, we often laughingly talk about our brain being ‘full up’, with no room for more information. A new study suggests that in some sense (but not the direct one!) that’s true.
To make new memories, we need to recognize that they are new memories. That means we need to be able to distinguish between events, or objects, or people. We need to distinguish between them and representations already in our database.
We are all familiar with the experience of wondering if we’ve done something. Is it that we remember ourselves doing it today, or are we remembering a previous occasion? We go looking for the car in the wrong place because the memory of an earlier occasion has taken precedence over today’s event. As we age, we do get much more of this interference from older memories.
In a new study, the brains of 40 college students and older adults (60-80) were scanned while they viewed pictures of everyday objects and classified them as either "indoor" or "outdoor." Some of the pictures were similar but not identical, and others were very different. It was found that while the hippocampus of young students treated all the similar pictures as new, the hippocampus of older adults had more difficulty with this, requiring much more distinctiveness for a picture to be classified as new.
Later, the participants were presented with completely new pictures to classify, and then, only a few minutes later, shown another set of pictures and asked whether each item was "old," "new" or "similar." Older adults tended to have fewer 'similar' responses and more 'old' responses instead, indicating that they could not distinguish between similar items.
The inability to recognize information as "similar" to something seen recently is associated with “representational rigidity” in two areas of the hippocampus: the dentate gyrus and CA3 region. The brain scans from this study confirm this, and find that this rigidity is associated with changes in the dendrites of neurons in the dentate/CA3 areas, and impaired integrity of the perforant pathway — the main input path into the hippocampus, from the entorhinal cortex. The more degraded the pathway, the less likely the hippocampus is to store similar memories as distinct from old memories.
Apart from helping us understand the mechanisms of age-related cognitive decline, the findings also have implications for the treatment of Alzheimer’s. The hippocampus is one of the first brain regions to be affected by the disease. The researchers plan to conduct clinical trials in early Alzheimer's disease patients to investigate the effect of a drug on hippocampal function and pathway integrity.
Comparison of 17 people with severe obstructive sleep apnea (OSA) with 15 age-matched controls has revealed that those with OSA had reduced gray matter in several brain regions, most particularly in the left parahippocampal gyrus and the left posterior parietal cortex, as well as the entorhinal cortex and the right superior frontal gyrus. These areas were associated with deficits in abstract reasoning and executive function. Deficits in the left posterior parietal cortex were also associated with daytime sleepiness.
Happily, however, three months of treatment with continuous positive airway pressure (CPAP), produced a significant increase in gray matter in these regions, which was associated with significant improvement in cognitive function. The researchers suggest that the hippocampus, being especially sensitive to hypoxia and innervation of small vessels, is the region most strongly and quickly affected by hypoxic episodes.
The findings point to the importance of diagnosing and treating OSA.
Rodent studies have demonstrated the existence of specialized neurons involved in spatial memory. These ‘grid cells’ represent where an animal is located within its environment, firing in patterns that show up as geometrically regular, triangular grids when plotted on a map of a navigated surface. Now for the first time, evidence for these cells has been found in humans. Moreover, those with the clearest signs of grid cells performed best in a virtual reality spatial memory task, suggesting that the grid cells help us to remember the locations of objects. These cells, located particularly in the entorhinal cortex, are also critical for autobiographical memory, and are amongst the first to be affected by Alzheimer's disease, perhaps explaining why getting lost is one of the most common early symptoms.
Older news items (pre-2010) brought over from the old website
Growth factor protects key brain cells in Alzheimer's models
In a series of cell culture and animal studies, involving genetically engineered mice, rats, and rhesus monkeys, injections of brain-derived neurotrophic factor (BDNF) resulted in significant improvement in brain functioning and on learning and memory tests. The growth factor, important for neurogenesis, is normally produced in the entorhinal cortex, an area damaged early in Alzheimer’s disease.
Nagahara, A.H. et al. 2009. Neuroprotective effects of brain-derived neurotrophic factor in rodent and primate models of Alzheimer's disease. Nature Medicine, 15, 331–337.