Wakefulness and memory function -
This stage of sleep is characterized by muscle atonia, fast but low voltage EEG and, as the name suggests, rapid eye movement. It is difficult to attribute memory gains to a single stage of sleep when it may be the entire sleep cycle that is responsible for memory consolidation.
Recent research conducted by Datta et al. It was found that not only were the P waves increased during post-training sleep but also the density of the waves.
These findings may imply that P waves during REM sleep may help to activate critical forebrain and cortical structures dealing with memory consolidation.
In a Hennevin et al. study, , [37] the mesencephalic reticular formation MRF was given light electrical stimulation , during REM sleep, which is known to have an advantageous effect for learning when applied after training. The rats in the experiment were trained to run a maze in search of a food reward.
One group of rats was given non-awakening MRF electrical stimulations after each of their maze trials compared to a control group which did not receive any electrical stimulation. It was noticed that the stimulated rats performed significantly better in respect to error reduction.
These findings imply that dynamic memory processes occur both during training as well as during post-training sleep. Another study by Hennevin et al. The interesting part of the experiment is that fear responding to the noise measured in the amygdala was observed when the noise was presented during REM sleep.
This was compared to a group of pseudo-conditioned rats who did not display the same amygdalar activation during post-training sleep. This would suggest that neural responding to previously salient stimuli is maintained even during REM sleep.
There is no shortage of research conducted on the effects that REM sleep has on the working brain, but consistency in the findings is what plagues recent research. There is no guarantee as to what functions REM sleep may perform for our bodies and brains, but modern research is always expanding and assimilating new ideas to further our understanding of such processes.
In animals, the appearance of ponto-geniculo-occipital waves PGO waves is related to that of the bioelectric outputs of rapid eye movements. Although these phasic waves are observed in many portions of the animal brain, they are most noticeable in the pons, lateral geniculate bodies, and the occipital cortex.
Peigneux et al. This would add to the theory that activation in these areas is similar to PGO wave activation in animals. Pontine waves are commonly seen in animals as a mechanism to help facilitate learning and memory consolidation.
An improvement on task performance was seen to be a result of increased P waves between REM sleep sessions. Two groups of rats underwent an avoidance learning task and then allowed a sleep period while another group of rats were deprived sleep. When comparing the two groups the sleep deprived rats showed a significant deficit in learning from having not undergone REM sleep.
In another rat group, the P wave generator was stimulated using a carbachol injection and the rats then underwent a sleep deprivation stage. When these rats were again tested on their learning it was shown that activation of the P wave generator during sleep deprivation resulted in normal learning being achieved.
This would point to the fact that the activation of P waves, even without REM sleep, was enough to enhance the memory processes that would not normally have happened.
Faces are an important part of one's social life. To be able to recognize, respond and act towards a person requires unconscious memory encoding and retrieval processes. Facial stimuli are processed in the fusiform gyrus occipito-temporal brain area and this processing is an implicit function representing a typical form of implicit memory.
REM sleep is known for its visual experiences, which may often include detailed depictions of the human countenance. It was seen that the fusiform gyrus was active during training, the REM sleep period, and the recognition task as well.
It is hypothesized that brain mechanisms during REM sleep, as well as pure repetition priming, can account for the implicit recognition of the previously shown faces.
Previous research has shown REM sleep to reactivate cortical neural assemblies post-training on a serial reaction time task SRT , in other words REM sleep replays the processing that occurred while one learnt an implicit task in the previous waking hours.
To answer this question the experiment was redone and another group was added who also took part in the SRT task. They experienced no sequence to the SRT task random group , whereas the experimental group did experience a sequence probabilistic group , although without conscious awareness.
Results of PET scans indicate that bilateral cuneus were significantly more activated during SRT practice as well as post-training REM sleep in the Probabilistic group than the Random group.
This suggests that specific brain regions are specifically engaged in the post-processing of sequential information. This is further supported by the fact that regional CBF rCBF during post-training REM sleep are modulated by the level of high-order, but not low-order learning obtained prior to sleep.
Therefore, brain regions that take part in a learning process are modulated by both the sequential structure of the learned material increased activation in cuneus , and the amount of high-order learning rCBF.
The effects of REM sleep deprivation RSD on neurotrophic factors, specifically nerve growth factor NGF and brain-derived neurotrophic factor BDNF , were assessed in by Sie et al. Neurotrophins are proteins found in the brain and periphery that aid in the survival, functioning and generation of neurons ; this is an important element in the synaptic plasticity process, the underlying neurochemical foundation in forming memories.
Half the rats experienced a six-hour REM sleep deprivation period, while the other half experienced a six-hour sleep period, containing all sleep cycles. Results showed that the rats in the REM sleep deprivation group experienced decreased levels of brain-derived neurotrophic factor in the cerebellum coordination, motor learning and brainstem sensory and motor ascending pathway ; conversely, the hippocampus long-term memory, spatial navigation , showed decreases in nerve growth factor levels.
BDNF protein has been shown to be necessary for procedural learning form of non-declarative memory. Since procedural learning has also exhibited consolidation and enhancement under REM sleep, it is proposed that the impairment of procedural learning tasks is due to the lack of BDNF proteins in the cerebellum and brainstem during RSD.
These target cells then secrete NGF which plays a key role in the physiological state of the hippocampus and its functions. It has been noted that REM sleep increases the secretion of NGF, therefore it has been proposed that during RSD cholinergic activity decreases leading to a decrease in NGF and impairment in procedural learning.
Walker and Stickgold hypothesized that after initial memory acquisition, sleep reorganizes memory representation at a macro-brain systems level. The day-wake group was taught the same task in the morning and tested 12 hours later with no intervening sleep.
FMRI was used to measure brain activity during retest. In the day-wake group, fMRI showed "decreased" signal activation bilaterally in the parietal cortices integrates multiple modalities , in addition to the left insular cortex regulation of homeostasis , left temporal pole most anterior of temporal cortex , and the left inferior fronto-polar cortex.
The increased signal activity seen in M1 after sleep corresponds to increased activity in this area seen during practice; however, an individual must practice for longer periods than they would have to sleep in order to obtain the same level of M1 signal increases. Therefore, it is suggested that sleep enhances the cortical representation of motor tasks by brain system expansion, as seen by increased signal activity.
Considered to be a mental workspace enabling temporary storage and retrieval of information, working memory is crucial to problem-solving and analysis of different situations. Working memory capacity is a measure of the number of mental processing functions one is able to perform consecutively.
Increases in one's working memory capacity can be accomplished with a strategy known as chunking. Aritake et al. When a colour was shown, the subject had to react by pressing the right colour on the keyboard.
The subjects were separated into three groups. Group one continually trained with no periods of sleep. Group two was trained and retested over ten hours of wakefulness followed by eight hours of sleep and final testing.
The third group was trained at ten pm, followed by an eight-hour sleep. This group was then tested the following morning and again later in the same day.
Results showed that wakefulness was an insignificant predictor of performance improvement, unless followed by a period of sleep. Groups that were allowed a post training sleep period, regardless of its time in reference to training, experienced improvements in learning the finger tapping sequences.
The initial working memory capacity of the groups averaged three to four units. In groups two and three, the working memory capacity was increased to an average of 5—6 units. It was proposed that sleep-dependent improvements may contribute to overall improvement in working memory capacity, leading to improved fluid intelligence.
Sleep deprivation , whether it is total sleep deprivation or partial sleep deprivation, can impair working memory in measures of memory, speed of cognitive processing , attention and task switching. Casement et al. The brain is an ever-changing, plastic, model of information sharing and processing.
In order for the brain to incorporate new experiences into a refined schema , it has to undergo specific modifications to consolidate and assimilate all new information. Neuroplasticity is most clearly seen in the instances of REM sleep deprivation during brain maturation.
Regional brain measurements in neonatal REM sleep deprived rats displayed a significant size reduction in areas such as the cerebral cortex and the brain stem. The rats were deprived during critical periods after birth, and subsequently anatomical size reduction is observed.
The right superior temporal sulcus was also noticed to have higher activation levels. When functional connectivity was analyzed it was found that the dentate nucleus was more closely involved with the functions of the superior temporal sulcus.
The results suggest that performance on the pursuit task relies on the subject's ability to comprehend appropriate movement patterns in order to recreate the optimal movements. Sleep deprivation was found to interrupt the slow processes that lead to learning of this procedural skill and alter connectivity changes that would have normally been seen after a night of rest.
Neuroplasticity has been thoroughly researched over the past few decades and results have shown that significant changes that occur in our cortical processing areas have the power to modulate neuronal firing to both new and previously experienced stimuli.
The changes in quantity of a certain neurotransmitter as well as how the post-synaptic terminal responds to this change are underlying mechanisms of brain plasticity.
Acetylcholine is an excitatory neurotransmitter that is seen to increase to near waking levels during REM sleep while compared to lower levels during slow-wave sleep. High levels of ACh would promote information attained during wakefulness to be stored in the hippocampus. This is accomplished by suppressing previous excitatory connections while facilitating encoding without interference from previously stored information.
During NREM sleep, and especially slow-wave sleep , low levels of Ach would cause the release of this suppression and allow for spontaneous recovery of hippocampal neurons resulting in the facilitation of memory consolidation. Recently, approximately one hundred genes whose brain expression is increased during periods of sleep have been found.
These sets of genes are related to different functional groups which may promote different cellular processes.
The genes expressed during wakefulness may perform numerous duties including energy allocation, synaptic excitatory neurotransmission, high transcriptional activity and synaptic potentiation in learning of new information.
There was a sleep related increase in processes that involve the synthesis and maintenance of the synapse. Such processes include membrane trafficking , synaptic vesicle recycling, myelin structural protein formation, and cholesterol and protein synthesis.
In a different study it was found that there was a sleep related increase in calmodulin -dependent protein kinase IV that has been specifically involved in synaptic depression and in the consolidation of long-term memory. The impact of daytime naps was looked at by Walker and Stickgold With regards to motor skills learning, naps seem to only speed up skill enhancement, not increase the amount of enhancement.
Much like motor skills learning, verbal skills learning increased after a daytime nap period. Researchers Mednick and colleagues have shown that if a visual skills task find task is taught in the morning and repeatedly tested throughout the day, individuals will actually become worse at the task.
The individuals that were allowed a minute nap seemed to gain stabilization of the skill, as no deterioration occurred.
If allowed a minute nap REM sleep and slow-wave sleep , individuals displayed enhancement. Unlike the motor task, enhancement was not suppressed during the nocturnal sleep if the individual had napped earlier. In the situation of visual skill learning, naps have been shown to prevent wakeful deterioration and even enhance learning above and beyond enhancement occurring in nocturnal sleep.
Shift workers who work throughout the night have been known to have far more accidents as opposed to daytime workers. Sleep often becomes deregulated in the elderly, a problem which can lead to or exacerbate pre-existing memory decline.
The positive correlation between sleep and memory breaks down with aging. In general, older adults suffer from decreased sleep efficiency. To combat this, donepezil has been tested in healthy elderly patients where it was shown to increase time spent in REM sleep and improve following day memory recall.
Alzheimers disease is thought to be caused by the abnormal buildup of proteins around brain cells which disrupt the activity of neurotransmitters. Studies have shown that in patients with Alzheimer's disease, there is a decrease in fast spindles. It has also been reported that spindle density the night before a memory test correlates positively with accuracy on an immediate recall task.
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Executive Committee. Aperture: Women in Medicine. Portraits of Strength. Event Photo Galleries. Additional Support. MD Program. MD-PhD Program. PA Program. PA Online Program. First, whatever the interval type Sleep or Active Wake , we predicted that younger adults would outperform older adults in binding performance Aly and Moscovitch, ; Plancher et al.
Second, we expected that the effect of sleep on the memory of naturalistic experience would be superior i. Lastly, we expected both age groups to benefit from sleep, but since sleep is reported to undergo deleterious age-related changes Ohayon et al.
In contrast, we expected that active wake would have a detrimental effect on binding performance, especially in older adults. A total of 40 younger adults 22 ± 3 years and 40 older adults 69 ± 5 years took part in this study.
Younger adults were recruited from Paris Descartes University and through flyers placed around the university. Older adults were recruited from the University of the Third Age at Paris Descartes University.
This study was carried out in accordance with the ethics recommendations of Paris Descartes University and was approved by the local ethics committee of the Institute of Psychology at Paris Descartes University. All participants were informed of the academic nature of the study and gave their written informed consent for their participation in the study in accordance with the Helsinki Declaration.
We ensured that all participants had unimpaired or corrected-to-normal vision. None of them had any prior history of drug or alcohol abuse or neurologic, psychiatric, or sleep disorders. Participants were instructed to be drug, alcohol, and caffeine free for 24 h prior to and during the experiment.
Table 1. Participant characteristics: shown here are the means of demographic, inclusion, and neuropsychological measures across experimental groups. Within each age group young and older adults , participants were randomly assigned to either an Active Wake or a Sleep interval group and were individually tested Figure 1.
Participants in the Active Wake interval groups 18 younger adults and 20 older adults performed the first session at 7—9 a. Twelve hours later at 7—9 p. Participants were instructed not to nap or consume alcohol during this time.
In the Sleep interval groups, participants 18 younger adults and 20 older adults performed the first session at 7—9 p. see Debarnot et al. The first and second sessions did not exceed 1 h None of the participants complained about the time or the duration of the experiment and they gave their informed consent to come back for the second session.
To assess cognitive abilities across participants assigned to the four experimental conditions, they were screened using a brief battery evaluating executive functions switching by the Trail Making Test Lezak et al.
For the older adults, additional standard tests of executive function, the Frontal Assessment Battery FAB; Dubois et al. In order to be relatively comparable to our virtual reality EM assessment VREM test , we used the Family Picture test in which participants must learn a series of pictures and then recall the characters present in the scene, what each character did and where each of them was.
Sleep characteristics were assessed in the first session during recruitment via the Pittsburgh Sleep Quality Index PSQI; Buysse et al. None of the participants reported sleep disorders and none were taking medication that affected sleep architecture or the central nervous system.
No extreme evening and morning type individuals or regular nappers were reported. Participants also completed the Stanford Sleepiness Scale SSS Hoddes et al. Lastly, the evaluation of sleep duration and waking behavior in the previous 24 h was evaluated by the St. Table 2. Results of sleep measures: shown here are the mean questionnaire scores across experimental groups.
The virtual environment was created with Virtools Dev 3. It is a 3D computer model of an artificial environment presented on a PC laptop The virtual environment is a multimodal urban environment created from photos of Paris based on previously validated virtual reality cities used in aging studies Plancher et al.
There is only one possible route through the virtual city, composed of 10 turns. The route is rich in objects and elements close to daily life to simulate a naturalistic urban environment buildings, shops, people, trees, etc. Each event is related to a specific spatio-temporal context and specific perceptual details.
For example, a white fountain with two levels and water flow is encountered at the beginning of the route on the left. There is an accident between a blue car and a gold car, which emit fumes, in the middle of the road straight ahead.
A brown dog suddenly appears, barking, at the end of the pathway straight ahead Figure 2B. Figure 2. The virtual urban environment. A Topography of the virtual city on which the spatio-temporal location of events items 1 to 20 is mentioned.
B Example of events encountered during the navigation. Using this virtual urban environment, we developed a What-Where-When VR task based on previously validated VREM tasks in normal aging Plancher et al.
This VR task used a series of naturalistic events embedded in the virtual environment to evaluate memory of the content of each scene what , its perceptual details details , the related temporal when and spatial where information as well as the binding of these features.
Subjects underwent a training session in an environment devoid of relevant events and containing only general elements e. Figure 3. They were free to navigate anywhere on the training track using a joystick. The training session lasted until they felt comfortable with the apparatus.
Subjects were immersed in the VR environment, the light in the room was switched off in order to increase the immersion and sense of presence but also to ensure that all participants experienced the same room-condition. They were asked to visit the city and to pay attention to all the details in order to tell us afterward if they would recommend living in this city to a friend.
They were also told that they would be asked to give an assessment of the virtual environment. The task involved incidental encoding as the participants were unaware that their memory would be tested afterward. The navigation lasted on average 10 min. For each event, specify the maximum of perceptive details for example colors, sounds , the spatial position if the elements were on your right, left, or in front of you , the temporal position at the beginning, in the middle, or at the end of the exploration.
As far as possible , try to recall the items in chronological order. There are about 20 remarkable elements to remember in this city. The experimenter noted all recalls on a structured response grid which had been validated in several previous VREM studies in our laboratory Plancher et al.
The accuracy of the recall of the what, where, when and perceptual details assigned to each of the 20 scenes was computed. We calculated a binding score What-Where-When to assess associative memory performance. We also computed a high binding score which took the association between perceptual details into account in addition What-Where-When and Details.
EM subscores What, What-Where, What-When, and What-Details were also computed. This evaluation enables the effect of consolidation among age groups and between the Active Wake and Sleep interval conditions on different types of binding to be assessed. In each case the maximum score was To take one of the above-mentioned examples, if the participant correctly reported having seen a car accident, one point was given for factual information car accident, What score and for each correct piece of associated information: spatial location in front, What-Where score , temporal situation halfway through the navigation, What-When score , perceptual details blue and gold cars, fumes, etc.
If the perceptual details were incorrectly recalled, but factual, spatial, and temporal contents were correct, each recall was scored 1, except for high binding which was scored 0 for detailed scoring, see Supplementary Material.
The delayed free recall was carried out and scored in a similar manner to the first immediate free recall. During the second session after 12 h , and a few minutes after the delayed free recall test, each participant underwent a visual recognition test: a series of 35 stimuli with 20 old stimuli snapshots from the virtual environment, stimuli that participants had already seen and 15 new stimuli snapshots from another virtual environment, 8 of which were semantically related to the environment already seen and 7 not related was presented to the participants on the laptop and they had to decide which items they had seen during immersion in the virtual environment.
Then, for each item recognized, they were requested to say whether they could mentally relive the spatio-temporal encoding context of the event or whether they just knew it i. We calculated the percentage of correct recognitions of factual information What maximum 20 , then, we computed the percentage of contextual information What-Where, What-When and the percentage of remembering judgments relative to correct factual recognition.
At the end of the experiment, subjects completed a self-administered questionnaire to evaluate their immersion, sense of presence in the virtual environment, navigation difficulties, and assessment of the environment Table 3. Table 3. Evaluation of the virtual environment: shown here are the means of Virtual Reality navigation duration and debriefing scores across experimental groups.
All the analyses were performed using Statistica 13 software. A series of analyses of variance ANOVAs with Age group Older adults vs. Younger adults and Interval type Active Wake vs. Sleep were performed for neuropsychological evaluations, variables assessing sleep and debriefing scales.
Concerning VREM assessment, we analyzed navigation duration at encoding and free recall performances for binding score What-Where-When and high binding score What-Where-When-Details , then for each component What, What-Where, What-When and What-Details and finally, for recognition and remember judgment performances.
We first assessed the baseline difference between Age group Young vs. Older through Interval type Active Wake vs. Sleep via a series of ANCOVAs controlling navigation duration on performances at session 1. Then, to assess EM changes over active wake and sleep interval, a series of three-way Session S1 vs.
S2 × Age group Young vs. Older × Interval type Active Wake vs. Sleep ANCOVAs controlling for navigation duration was also performed. Finally, we analyzed the different recognition performances and debriefing scales in session 2 via a series of ANCOVAs controlling navigation duration with Age group Older adults vs.
Each size effect η 2 is reported and when interaction was significant each pairwise comparison using PLSD Fisher post hoc tests was calculated. Datasets and analyses are available on request from the authors.
Only a predictable age difference was revealed on each test, but no effect of Interval type Wake vs. Sleep or Age group × Interval type interaction was found. For each age group, the cognitive performances on tests assessing executive function, flexibility and working memory performances did not differ according to the Interval type.
Older adults did not differ on standard tests assessing EM and frontal functions according to the Interval type see Table 1. The main effect of Age on the amount of sleep overnight using the St. Similarly the effect of interval type and the Age group × Interval type interaction were not significant.
Subjective sleep quality assessed by the PSQI did not differ across Age groups and interval type and no Age group × Interval type interaction was found. Subjective measures of alertness and sleepiness assessed during the two sessions via SSS1 and SSS2 scales revealed a main effect of Age.
Younger participants reported being less alert than older adults for both Interval types Active Wake vs. However, no effect of Interval type or Age group × Interval type interaction was significant for either session. Thus the two age groups were well-matched for sleep measures across interval type Active Wake vs.
Sleep see Table 2. Concerning navigation duration, no effect of Age and Interval type was found. However, we observed an Age group × Interval type interaction. As the post hoc test indicated that older adults in the Active wake group spent more time navigating than older adults in the sleep group, navigation duration was controlled for in the following analyses.
However, no effect of Interval type or Age group × Interval type interaction was found. Younger adults reported using laptops more frequently and task was reported to be easier than for older adults. No effect of Age and Interval type or Age group × Interval type interaction was found for navigation appreciation and sense of presence see Table 3.
A preliminary check of initial performance at encoding session 1 across interval type Active Wake vs. Sleep and Age group Older adults vs. In sum, younger adults performed better than older adults at the encoding session whatever the interval type, the participants for each age group were well-matched across interval type and no difference in performances occurred depending on when the encoding was performed in the morning or in the evening.
For both age groups, EM recalls were diminished in the delayed recall relative to the immediate recall in the Active Wake interval and interestingly, they were enhanced following a sleep interval.
Figure 4. Binding performance number of What-Where-When and What-Where-When-Details associations through Interval type Active Wake vs. Sleep across Age group Younger vs.
Error bars represent standard errors of the mean. NB: for reasons of readability, the effect of age is not reported here. Figure 5. EM subscores What, What-Where, What-When, and What-Details through Interval type Active Wake vs.
In sum, on the one hand, for older adults, all types of EM aspects as well as both binding performances were significantly poorer after the active wake interval and significantly enhanced after a sleep interval. For younger adults, binding performances and more especially factual-temporal associations were significantly poorer after an active wake interval and significantly enhanced after sleep.
Results and analyses are presented on Table 4. Results of percentage of correct recognition of factual what and correct contextual associated information What-Where, What-When indicated a main effect of Age, with younger adults showing better recognition performances than older adults, while there was no effect of Interval type nor Age group × Interval type interaction.
Table 4. ANCOVA results for recognition performances: shown here are the percentages of correct recognition of factual information What , contextual information What-Where, What-When and Remember judgments R correctly associated to factual recognition and the percentage of correct rejections of neutral and semantically related distractors.
When computing the percentage of Remember judgments relative to correct factual recognition for each participant, we no longer found any effect of age group, interval type or Age group × Interval type interaction.
Concerning the good rejection of neutral distractors , the ANCOVA revealed no effect of Age, no effect of Interval type and no Age group × Interval type interaction. However, for good rejection of semantically related distractors , the ANCOVA revealed no effect of age or Interval type but an Age group × Interval type interaction.
In the present study, a naturalistic What-Where-When EM task, rich in details and spatio-temporal context, was implemented in a virtual environment and was used to evaluate the effect of extended overnight sleep vs. extended active wakefulness on the consolidation of personally experienced events close to daily situations, in younger and older adults.
As expected, the findings showed an age-related decline in EM performance for older adults compared to their younger counterparts, but most importantly, they revealed for both age groups a decline in memory performances following a period of active wakefulness and enhancement following sleep.
We will briefly discuss the age-related effects on EM functioning and consider forgetting performances following the wakefulness condition, then we will focus on the effect of sleep on EM consolidation. Basically, it is assumed that age-related differences in contextual memory are greater than those in memory for content Chalfonte and Johnson, ; Naveh-Benjamin, ; Kessels et al.
The retrieval performances from our incidental encoding session indicate that younger adults performed better than older ones at recalling contextual information what-details, what-where, and what-when associations and especially feature binding i.
This pattern of performance was corroborated during the second session 12 h later regardless of the Interval type Active Wake or Sleep. Since recall of factual information is sensitive to the attention allocated during encoding and the amount of effort required during retrieval Spencer and Raz, , the use of incidental encoding and free recall may account for age-related deficits of factual information found in our study.
Nevertheless, this age-related decline for factual information was also observed via recognition, which may indicate genuine incidental encoding deficits in older adults. However, when computing the percentage of remembering judgments relative to factual information, the effect of age on recognition disappeared, indicating quantitative rather than qualitative differences between younger and older adults for correct memory.
It should be mentioned that during the debriefing, older adults more frequently reported that the navigation was difficult compared to their younger counterparts; nevertheless, both age groups manifested an equivalent sense of presence in the virtual environment and their appreciation of the navigation was similar.
The results of binding performance are in agreement with previous findings, suggesting an impaired binding in aging Chalfonte and Johnson, ; Kessels et al. This deficit may be possibly related to diminished activation of the hippocampus and changes in the activity of the prefrontal cortex Mitchell et al.
Interestingly, we previously showed that binding deficits in aging were independent of the incidental or intentional encoding of naturalistic scenes presented in virtual environments Plancher et al.
Thus, our results confirm a noticeable decline of EM in the elderly reported in several studies Cabeza et al. Most importantly, our study pointed out a general age-related impairment affecting different components of EM as well as their related binding.
For both age groups, EM free recall was diminished in the delayed recall relative to the immediate recall in the Active Wake interval while it was strengthened following a sleep interval. This pattern can not be attributed to some confounding effects, as participants were well-matched according to the type of interval on basic neuropsychological performance and sleep measure.
In addition, we checked for the elderly that there was no difference concerning standard EM assessment, depending on when the test was done in the morning or in the evening. When evaluating the effect of active wake on EM retention, our data from delayed free recall highlight a significant forgetting following the Active Wake interval for both age groups.
All types of information i. These findings support the idea of Active Wake as an unfavorable period for consolidation Craig et al. During Active Wake participants were engaged in their daily activities outside the laboratory e.
Retrospective interference is an explanation for forgetting in long term memory while memory consolidation is understood as a process increasing resistance to interference rather than permitting performance enhancement Ellenbogen et al. In this line, according to the Opportunistic hypothesis Mednick et al.
At a cellular level, new hippocampal LTP induction can interfere with the maintenance of older LTP. Besides, subsequently encoded memories can compete for the same neural pathway that was used to consolidate previously encoded information. However, this deleterious effect of Active Wake on free recall disappeared on recognition and remember judgments for both age groups.
This finding may suggest that the memory trace was still present after a period of active wakefulness about 12 h , but less spontaneously accessible in free recall, maybe because of a reduction in executive functions at the end of the day.
Alternatively, it may indicate that active wake did not protect against forgetting, but rather that our recognition task was less sensitive to detect deficits than delayed free recall.
When investigating the effect of sleep on EM retention, our results from free recall showed that for both age groups, sleep compared to active wakefulness enhanced feature binding which is one of the main characteristics of EM. As regards young adults , our findings indicated a significant enhancement in binding performance following sleep both What-Where-When and What-Where-When and Details , and more specifically regarding temporal information what-when association.
One possible explanation might be that enhancement concerned the performance that was less effective in the first session i. This is in line with studies that have shown for different domains of memory that sleep preferably consolidates weak rather than strong traces, and that it selectively provides maximum benefits for traces that proved to be most difficult prior to sleep Kuriyama et al.
Otherwise, the specific benefit for temporal information in younger adults may indicate that remembering when events occur is a key feature for EM as this memory system relies on temporal projection into the past and the future Wheeler et al.
The consolidation of temporal information appears therefore crucial in long-lasting EM. This is in keeping with the role of sleep that has been found to favor the replay of new temporal information in a forward direction, which strengthens its integration to the EM trace in young adults Drosopoulos et al.
This replay process is dependent on the hippocampus CA3 network and dentate gyrus, Drosopoulos et al. Moreover, our result is also in line with a more recent study van der Helm et al. Those benefits were specifically correlated with stage 2-NREM.
Here, we extended the finding to memory of naturalistic specific events and high binding performance which is in line with previous studies arguing that sleep reactivates item-context binding and strengthens the connection between item and context, supporting their redistribution into cortical regions where they are more stable Drosopoulos et al.
About older adults , our study is the first to investigate the effect of sleep on the elderly using a What-Where-When task and the first to evaluate the effect of sleep vs. active wakefulness on binding performance in naturalistic situations. We show, remarkably, a general enhancement following a sleep interval in all associative information what-details, what-where, and what-when as well as an enhancement in binding what-where-when and high binding performance What-Where-When-Details.
The present findings are in line with some previous studies that demonstrated the preservation of sleep benefits on declarative memory in aging Aly and Moscovitch, ; Wilson et al.
An extensive psychological literature shows that sleep wakefluness promotes human episodic memory EM consolidation in younger adults. However, evidence fknction wakefulness and memory function benefit of wakefulness and memory function for EM consolidation in aging is still elusive. Vunction addition, Insulin resistance and insulin resistance cookbook wakefulness and memory function the previous funcrion used EM assessments that are very different from everyday life conditions and are far from considering all the hallmarks of this memory system. In this study, the effect of an extended period of sleep was compared to the effect of an extended period of active wakefulness on the EM consolidation of naturalistic events, using a novel What-Where-When EM task, rich in perceptual details and spatio-temporal context, presented in a virtual environment. We investigated the long-term What-Where-When and Details binding performances of young and elderly people before and after an interval of sleep or active wakefulness. Respiratory health news many students, staying awake all night to study is common practice. According to Medical News Wakefulness and memory functionwakefulness and memory function 20 percent mwmory students pull all-nighters at wwkefulness once a amd, and waksfulness 35 functino stay up past three wakefulness and memory function the morning once Anti-cancer benefits of green tea more weekly. That being said, staying up all night to study is one of the worst things students can do for their grades. In October oftwo MIT professors found a correlation between sleep and test scores : The less students slept during the semester, the worse their scores. So, why is it that sleep is so important for test scores? All of which contribute to better test scores. When learning facts and information, most of what we learn is temporarily stored in a region of the brain called the hippocampus.
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