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Cognitive Training Improves Sleep Quality and Cognitive Function among Older Adults with Insomnia

Scientific publication on improving sleep quality through cognitive training

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Original Name: Cognitive Training Improves Sleep Quality and Cognitive Function among Older Adults with Insomnia.

Authors: Iris Haimov1, Evelyn Shatil1,2.

  • 1. Department of Psychology and the Center for Psychobiological Research, Yezreel Academic College, Emek Yezreel, Israel.
  • 2. CogniFit Inc., New York, New York, United States of America.

Journal: PloS ONE (2013), vol. 8 (4): 1-17.

References to this article (APA style):

  • Haimov, I., Shatil, E. (2013). Cognitive Training Improves Sleep Quality and Cognitive Function among Older Adults with Insomnia. PLoS ONE, 8 (4), 1-17.

Study Conclusion

CogniFit personalized cognitive training has been able to improve sleep quality and cognitive function in older adults with insomnia through 20-30 minutes a day, three non-consecutive days a week, for 8 weeks. Sleeping time: 38.42±40.58 to 24.76±32.32 minutes (p=. 001); Sleeping efficiency: 73.54±12.56 to 80.28±13.78% (p=. 001); Total sleep time: 296.37±78.07 to 310.44±72.96 minutes; Awakening time: 72.06±40.89 to 58.89±45 Memory: F=15.65±1.35 (p=. 001); Visual memory: F=14.03±1.35 (p=. 001); Working memory: F=13.92±1.35) (p=. 001)

Study summary

Given the high incidence of insomnia in older people, this study aimed to learn about the effects of computerized cognitive training on sleep quality and cognitive status in this population.

A total of 51 older adults over 65 to 85 years old were randomly divided into the experimental group (which performed cognitive training) and the control group (which did not). The experimental group performed CogniFit personalized cognitive training for 8 weeks from their respective homes, using their own computer. The control group, on the other hand, carried out a computerized program of activities that did not imply high-level cognitive functioning for 8 weeks. Cognitive status of these participants was measured with CogniFit before and after training. In addition, sleep was also monitored for a week before and after. Different results were taken into account:

  • Sleep quality: Time it took the person to fall asleep and the percentage of the time he or she was asleep (sleeping efficiency).
  • Cognitive state: Ability to avoid distractions, working memory, visual memory, general memory and denomination.

Statistical analyses indicated some interesting data:

  • A better visual scanning is related to an earliest onset of sleep.
  • A better naming is related to a smaller number of awakenings after initiating sleep.
  • Increased capacity to avoid distractions was related to a longer sleep duration.
  • The control group showed that worse working memory is associated with a a rise in the time needed to fall asleep

The results indicate that new learning is essential when initiating and maintaining sleep in the elderly with insomnia. CogniFit cognitive personalized training can help create the type of learning that is needed to bring about improvements in sleep and cognitive status.


Between 20 and 50% of elderly people suffer from insomnia, being more common in women than men. This disorder is related to changes in sleep architecture (less time in slow wave sleep, less REM sleep time, less delta wave amplitude, decreased activity, REM sleep density, and spindles). This results in a fragmented sleep and a greater difficulty to fall asleep. The causes of this type of insomnia can be varied. However, the most common treatment for this disorder is pharmacological.

With age, apart from sleep problems, some degree of cognitive deterioration usually appears, which can affect processing speed, perception, executive functioning, concentration, attention, inhibition, and memory. Elders with insomnia tend to have greater deterioration patterns than those without sleep problems, such as episodic memory problems, distractibility, etc. Fortunately, it has been shown that people with insomnia can benefit from some activities such as:

  • Cognitive training aimed at rehabilitating cognitive abilities.
  • Acquisition of new visual and verbal learning.

On the other hand, evidence from recent years has shown that sleep is necessary for memory consolidation. This is due to the fact that sleep favors synaptic plasticity, promotes procedural learning processes, facilitates the consolidation of declarative memory, and plays a crucial role in the acquisition of new memories. In the opposite sense, it has been observed that acquisition of new learning has positive effects on the sleep architecture. After learning, the REM sleep ratio increases, rapid eye movements increase during this phase, slow wave activity increases, the duration of sleep Phase 2 increases, as well as the number and density of sleep spindles.

With all this, it is reasonable to suppose that the new learning derived from an appropriate cognitive training can help:

  • Change sleep architecture.
  • Improve sleep quality.
  • Improve cognitive state.


Study Design

An 11-week randomised controlled clinical trial was conducted in independent elderly people with insomnia using a two-group design: CogniFit intervention (experimental group) and non-specific intervention (control group).

A cognitive measurement of the participants was performed before starting the training and another at the end of the training. For this purpose, the CogniFit Assessment Battery was used. A research assistant came to the participants' house to register to the CogniFit platform. Attendees called the participants every two weeks to encourage adherence to the treatment.


Participants were contacted through advertisements and speeches in senior centers. They were all elders complaining about problems initiating or maintaining sleep at least three nights a week. They also had to have poor sleep quality from at least six months ago. Patients were excluded if they had a score of <26 on the MMSE (Mini-mental state examination), a score of >40 on the ZSDS (Zung Self-rating Depression Scale) and a score of >60 on a small anxiety questionnaire. Also excluded from the study were those patients with significant vision or hearing problems, relevant medical or neurological illnesses, those with alcoholism or other substance problems, psychiatric disorders, sleep apnea, sporadic leg movement syndrome, and those using medications that affected the central nervous system (except those used for sleeping).

Group Control Intervention

The control group received an 8-week training program that, unlike CogniFit, did not train any particular cognitive abilities, did not fit the participants' performance and did not provide any feedback. They only had to do a few simple, computerized reading and painting tasks.

Variables measured:

CogniFit was used to evaluate 17 cognitive skills. In addition, by means of a device placed on the participants' wrist, other variables were also measured:

  • Total time of sleep: From the time they went to bed until they got up.
  • Sleep onset latency: Time it took them to fall asleep since they went to bed.
  • Sleep Efficiency: Percentage of sleep time in relation to the time spent in bed.
  • Wake-up time since the beginning of sleep: Wake-up time after initially falling asleep.
  • Number of awakenings: Times they woke up since they first fell asleep.


The SPSS 19 was used to conduct statistical analysis. To assess differences in the five sleep variables and different cognitive abilities between the two groups, mixed-effect models were used for repeated measures, with one model for each variable. Pearson's correlation timing and a hierarchical regression analysis were also calculated to see if there was a relationship between cognitive improvements and improvements in sleep quality.

Results and conclusions

A correlation was detected between the experimental group's naming capacity and sleep efficiency, waking time from the beginning of sleep and the number of awakenings. The total sleep time correlated with the capacity of avoiding distractions. On the other hand, there was also a significant correlation in awareness of the onset of sleep and visual scanning. In the case of the control group, a negative correlation was detected between time it took to fall asleep and working memory, visual memory and memory in general. The remaining cognitive abilities showed no significant correlation with sleep parameters.

In short, it can be concluded that CogniFit cognitive training can improve the onset and maintenance of sleep, in addition to cognitive capabilities. This type of therapy can be an alternative or a good complement to current drug treatments for treating insomnia.

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