Recent research has suggested that sleep problems might be a risk factor in developing Alzheimer’s, and in mild cognitive impairment. A new study adds to this gathering evidence by connecting reduced slow-wave sleep in older adults to brain atrophy and poorer learning.

The study involved 18 healthy young adults (mostly in their 20s) and 15 healthy older adults (mostly in their 70s). Participants learned 120 word- nonsense word pairs and were tested for recognition before going to bed. Their brain activity was recorded while they slept. Brain activity was also measured in the morning, when they were tested again on the word pairs.

As has been found previously, older adults showed markedly less slow-wave activity (both over the whole brain and specifically in the prefrontal cortex) than the younger adults. Again, as in previous studies, the biggest difference between young and older adults in terms of gray matter volume was found in the medial prefrontal cortex (mPFC). Moreover, significant differences were also found in the insula and posterior cingulate cortex. These regions, like the mPFC, have also been associated with the generation of slow waves.

When mPFC volume was taken into account, age no longer significantly predicted the extent of the decline in slow-wave activity — in other words, the decline in slow-wave activity appears to be due to the brain atrophy in the medial prefrontal cortex. Atrophy in other regions of the brain (precuneus, hippocampus, temporal lobe) was not associated with the decline in slow-wave activity when age was considered.

Older adults did significantly worse on the delayed recognition test than young adults. Performance on the immediate test did not predict performance on the delayed test. Moreover, the highest performers on the immediate test among the older adults performed at the same level as the lowest young adult performers — nevertheless, these older adults did worse the following day.

Slow-wave activity during sleep was significantly associated with performance on the next day’s test. Moreover, when slow-wave activity was taken into account, neither age nor mPFC atrophy significantly predicted test performance.

In other words, age relates to shrinkage of the prefrontal cortex, this shrinkage relates to a decline in slow-wave activity during sleep, and this decline in slow-wave sleep relates to poorer cognitive performance.

The findings confirm the importance of slow-wave brainwaves for memory consolidation.

All of this suggests that poorer sleep quality contributes significantly to age-related cognitive decline, and that efforts should be made to improve quality of sleep rather than just assuming lighter, more disturbed sleep is ‘natural’ in old age!

A new study adds more support to the idea that the increasing difficulty in learning new information and skills that most of us experience as we age is not down to any difficulty in acquiring new information, but rests on the interference from all the old information.

Memory is about strengthening some connections and weakening others. A vital player in this process of synaptic plasticity is the NMDA receptor in the hippocampus. This glutamate receptor has two subunits (NR2A and NR2B), whose ratio changes as the brain develops. Children have higher ratios of NR2B, which lengthens the time neurons talk to each other, enabling them to make stronger connections, thus optimizing learning. After puberty, the ratio shifts, so there is more NR2A.

Of course, there are many other changes in the aging brain, so it’s been difficult to disentangle the effects of this changing ratio from other changes. This new study genetically modified mice to have more NR2A and less NR2B (reflecting the ratio typical of older humans), thus avoiding the other confounds.

To the researchers’ surprise, the mice were found to be still good at making strong connections (‘long-term potentiation’ - LTP), but instead had an impaired ability to weaken existing connections (‘long-term depression’ - LTD). This produces too much noise (bear in mind that each neuron averages 3,000 potential points of contact (i.e., synapses), and you will see the importance of turning down the noise!).

Interestingly, LTD responses were only abolished within a particular frequency range (3-5 Hz), and didn’t affect 1Hz-induced LTD (or 100Hz-induced LTP). Moreover, while the mice showed impaired long-term learning, their short-term memory was unaffected. The researchers suggest that these particular LTD responses are critical for ‘post-learning information sculpting’, which they suggest is a step (hitherto unknown) in the consolidation process. This step, they postulate, involves modifying the new information to fit in with existing networks of knowledge.

Previous work by these researchers has found that mice genetically modified to have an excess of NR2B became ‘super-learners’. Until now, the emphasis in learning and memory has always been on long-term potentiation, and the role (if any) of long-term depression has been much less clear. These results point to the importance of both these processes in sculpting learning and memory.

The findings also seem to fit in with the idea that a major cause of age-related cognitive decline is the failure to inhibit unwanted information, and confirm the importance of keeping your mind actively engaged and learning, because this ratio is also affected by experience.

Here’s an encouraging study for all those who think that, because of age or physical damage, they must resign themselves to whatever cognitive impairment or decline they have suffered. In this study, older adults who had suffered from aphasia for a long time nevertheless improved their language function after six weeks of intensive training.

The study involved nine seniors with chronic aphasia and 10 age-matched controls. Those with aphasia were given six weeks of intensive and specific language therapy, after which they showed significantly better performance at naming objects. Brain scans revealed that the training had not only stimulated language circuits, but also integrated the default mode network (the circuits used when our brain is in its ‘resting state’ — i.e., not thinking about anything in particular), producing brain activity that was similar to that of the healthy controls.

Moreover, these new circuits continued to be active after training, with participants continuing to improve.

Previous research has implicated abnormal functioning of the default mode network in other cognitive disorders.

Although it didn’t reach significance, there was a trend suggesting that the level of integration of the default mode network prior to therapy predicted the outcome of the training.

The findings are especially relevant to the many seniors who no longer receive treatment for stroke damage they may have had for many years. They also add to the growing evidence for the importance of the default mode network. Changes in the integration of the default mode network with other circuits have also been implicated in age-related cognitive decline and Alzheimer’s.

Interestingly, some research suggests that meditation may help improve the coherence of brainwaves that overlap the default mode network. Meditation, already shown to be helpful for improving concentration and focus, may be of greater benefit for fighting age-related cognitive decline than we realize!

Previous research has pointed to an association between not having teeth and a higher risk of cognitive decline and dementia. One reason might have to do with inflammation — inflammation is a well-established risk factor, and at least one study has linked gum disease to a higher dementia risk. Or it might have to do with the simple mechanical act of chewing, reducing blood flow to the brain. A new study has directly investigated chewing ability in older adults.

The Swedish study, involving 557 older adults (77+), found that those with multiple tooth loss, and those who had difficulty chewing hard food such as apples, had a significantly higher risk of developing cognitive impairments (cognitive status was measured using the MMSE). However, when adjusted for sex, age, and education, tooth loss was no longer significant, but chewing difficulties remained significant.

In other words, what had caused the tooth loss didn’t matter. The important thing was to maintain chewing ability, whether with your own natural teeth or dentures.

This idea that the physical act of chewing might affect your cognitive function (on a regular basis; I don’t think anyone is suggesting that you’re brighter when you chew!) is an intriguing and unexpected one. It does, however, give even more emphasis to the importance of physical exercise, which is a much better way of increasing blood flow to the brain.

The finding also reminds us that there are many things going on in the brain that may deteriorate with age and thus lead to cognitive decline and even dementia.

New research suggests that reliance on the standard test Alzheimer's Disease Assessment Scale—Cognitive Behavior Section (ADAS-Cog) to measure cognitive changes in Alzheimer’s patients is a bad idea. The test is the most widely used measure of cognitive performance in clinical trials.

Using a sophisticated method of analysis ("Rasch analysis"), analysis of ADAS-Cog data from the AD Neuroimaging Initiative (675 measurements from people with mild Alzheimer's disease, across four time points over two years) revealed that although final patient score seemed reasonable, at the component level, a ceiling effect was revealed for eight out of the 11 parts of the ADAS-Cog for many patients (32-83%).

Additionally, for six components (commands, constructional praxis, naming objects and fingers, ideational praxis, remembering test instructions, spoken language), the thresholds (points of transition between response categories) were not ordered sequentially. The upshot of this is that, for these components, a higher score did not in fact confirm more cognitive impairment.

The ADAS-Cog has 11 component parts including memory tests, language skills, naming objects and responding to commands. Patients get a score for each section resulting in a single overall figure; different sections have different score ranges. A low total score signals better cognitive performance; total score range is 0-70, with 70 being the worst.

It seems clear from this that the test seriously underestimates cognitive differences between people and changes over time. Given that this is the most common cognitive test used in clinical trials, we have to consider whether these flaws account for the failure of so many drug trials to find significant benefits.

Among the recommended ways to improve the ADAS-Cognitive (including the need to clearly define what is meant by cognitive performance!), the researchers suggest that a number of the components should be made more difficult, and that the scoring function of those six components needs to be investigated.