Functional Connectivity in the Default Mode Network is Reduced in Association with Nocturnal Awakening in Mild Cognitive Impairment

Memory performance mediates subjective sleep quality associations with cerebrospinal fluid Alzheimer's disease biomarker levels and hippocampal volume among individuals with mild cognitive symptoms

Sleep disturbances are prevalent in Alzheimer's disease (AD), affecting individuals during its early stages. We investigated associations between subjective sleep measures and cerebrospinal fluid (CSF) biomarkers of AD in adults with mild cognitive symptoms from the European Prevention of Alzheimer's Dementia Longitudinal Cohort Study, considering the influence of memory performance. A total of 442 participants aged >50 years with a Clinical Dementia Rating (CDR) score of 0.5 completed the Pittsburgh Sleep Quality Index questionnaire and underwent neuropsychological assessment, magnetic resonance imaging acquisition, and CSF sampling. We analysed the relationship of sleep quality with CSF AD biomarkers and cognitive performance in separated multivariate linear regression models, adjusting for covariates. Poorer cross-sectional sleep quality was associated with lower CSF levels of phosphorylated tau and total tau alongside better immediate and delayed memory performance. After adjustment for delayed memory scores, associations between CSF biomarkers and sleep quality became non-significant, and further analysis revealed that memory performance mediated this relationship. In post hoc analyses, poorer subjective sleep quality was associated with lesser hippocampal atrophy, with memory performance also mediating this association. In conclusion, worse subjective sleep quality is associated with less altered AD biomarkers in adults with mild cognitive symptoms (CDR score 0.5). These results could be explained by a systematic recall bias affecting subjective sleep assessment in individuals with incipient memory impairment. Caution should therefore be exercised when interpreting subjective sleep quality measures in memory-impaired populations, emphasising the importance of complementing subjective measures with objective assessments.

Sleep and physical activity measures are associated with resting-state network segregation in non-demented older adults

Greater physical activity and better sleep are associated with reduced risk of cognitive decline and dementia among older adults, but little is known about their combined associations with measures of brain function and neuropathology. This study investigated potential independent and interactive cross-sectional relationships between actigraphy-estimated total volume of physical activity (TVPA) and sleep patterns [i.e., total sleep time (TST), sleep efficiency (SE)] with resting-state functional magnetic resonance imaging (rs-fMRI) measures of large scale network connectivity and positron emission tomography (PET) measures of amyloid-β. Participants were 135 non-demented older adults from the BIOCARD study (116 cognitively normal and 19 with mild cognitive impairment; mean age = 70.0 years). Using multiple linear regression analyses, we assessed the association between TVPA, TST, and SE with connectivity within the default-mode, salience, and fronto-parietal control networks, and with network modularity, a measure of network segregation. Higher TVPA and SE were independently associated with greater network modularity, although the positive relationship of SE with modularity was only present in amyloid-negative individuals. Additionally, higher TVPA was associated with greater connectivity within the default-mode network, while greater SE was related to greater connectivity within the salience network. In contrast, longer TST was associated with lower network modularity, particularly among amyloid-positive individuals, suggesting a relationship between longer sleep duration and greater network disorganization. Physical activity and sleep measures were not associated with amyloid positivity. These data suggest that greater physical activity levels and more efficient sleep may promote more segregated and potentially resilient functional networks and increase functional connectivity within specific large-scale networks and that the relationship between sleep and functional networks connectivity may depend on amyloid status.

Predicting neurodegeneration from sleep related biofluid changes

Sleep-wake disturbances are common in neurodegenerative diseases and may occur years before the clinical diagnosis, potentially either representing an early stage of the disease itself or acting as a pathophysiological driver. Therefore, discovering biomarkers that identify individuals with sleep-wake disturbances who are at risk of developing neurodegenerative diseases will allow early diagnosis and intervention. Given the association between sleep and neurodegeneration, the most frequently analyzed fluid biomarkers in people with sleep-wake disturbances to date include those directly associated with neurodegeneration itself, such as neurofilament light chain, phosphorylated tau, amyloid-beta and alpha-synuclein. Abnormalities in these biomarkers in patients with sleep-wake disturbances are considered as evidence of an underlying neurodegenerative process. Levels of hormonal sleep-related biomarkers such as melatonin, cortisol and orexin are often abnormal in patients with clinical neurodegenerative diseases, but their relationships with the more standard neurodegenerative biomarkers remain unclear. Similarly, it is unclear whether other chronobiological/circadian biomarkers, such as disrupted clock gene expression, are causal factors or a consequence of neurodegeneration. Current data would suggest that a combination of fluid biomarkers may identify sleep-wake disturbances that are most predictive for the risk of developing neurodegenerative disease with more optimal sensitivity and specificity.

The Effects of Transcutaneous Vagus Nerve Stimulation on Functional Connectivity Within Semantic and Hippocampal Networks in Mild Cognitive Impairment

Better treatments are needed to improve cognition and brain health in people with mild cognitive impairment (MCI) and Alzheimer's disease (AD). Transcutaneous vagus nerve stimulation (tVNS) may impact brain networks relevant to AD through multiple mechanisms including, but not limited to, projection to the locus coeruleus, the brain's primary source of norepinephrine, and reduction in inflammation. Neuropathological data suggest that the locus coeruleus may be an early site of tau pathology in AD. Thus, tVNS may modify the activity of networks that are impaired and progressively deteriorate in patients with MCI and AD. Fifty patients with MCI (28 women) confirmed via diagnostic consensus conference prior to MRI (sources of info: Montreal Cognitive Assessment Test (MOCA), Clinical Dementia Rating scale (CDR), Functional Activities Questionnaire (FAQ), Hopkins Verbal Learning Test - Revised (HVLT-R) and medical record review) underwent resting state functional magnetic resonance imaging (fMRI) on a Siemens 3 T scanner during tVNS (left tragus, n = 25) or sham control conditions (left ear lobe, n = 25). During unilateral left tVNS, compared with ear lobe stimulation, patients with MCI showed alterations in functional connectivity between regions of the brain that are important in semantic and salience functions including regions of the temporal and parietal lobes. Furthermore, connectivity from hippocampi to several cortical and subcortical clusters of ROIs also demonstrated change with tVNS compared with ear lobe stimulation. In conclusion, tVNS modified the activity of brain networks in which disruption correlates with deterioration in AD. These findings suggest afferent target engagement of tVNS, which carries implications for the development of noninvasive therapeutic intervention in the MCI population.

MRI-based machine learning model: A potential modality for predicting cognitive dysfunction in patients with type 2 diabetes mellitus

Background: Type 2 diabetes mellitus (T2DM) is a crucial risk factor for cognitive impairment. Accurate assessment of patients' cognitive function and early intervention is helpful to improve patient's quality of life. At present, neuropsychiatric screening tests is often used to perform this task in clinical practice. However, it may have poor repeatability. Moreover, several studies revealed that machine learning (ML) models can effectively assess cognitive impairment in Alzheimer's disease (AD) patients. We investigated whether we could develop an MRI-based ML model to evaluate the cognitive state of patients with T2DM. Objective: To propose MRI-based ML models and assess their performance to predict cognitive dysfunction in patients with type 2 diabetes mellitus (T2DM). Methods: Fluid Attenuated Inversion Recovery (FLAIR) of magnetic resonance images (MRI) were derived from 122 patients with T2DM. Cognitive function was assessed using the Chinese version of the Montréal Cognitive Assessment Scale-B (MoCA-B). Patients with T2DM were separated into the Dementia (DM) group (n = 40), MCI group (n = 52), and normal cognitive state (N) group (n = 30), according to the MoCA scores. Radiomics features were extracted from MR images with the Radcloud platform. The variance threshold, SelectKBest, and least absolute shrinkage and selection operator (LASSO) were used for the feature selection. Based on the selected features, the ML models were constructed with three classifiers, k-NearestNeighbor (KNN), Support Vector Machine (SVM), and Logistic Regression (LR), and the validation method was used to improve the effectiveness of the model. The area under the receiver operating characteristic curve (ROC) determined the appearance of the classification. The optimal classifier was determined by the principle of maximizing the Youden index. Results: 1,409 features were extracted and reduced to 13 features as the optimal discriminators to build the radiomics model. In the validation set, ROC curves revealed that the LR classifier had the best predictive performance, with an area under the curve (AUC) of 0.831 in DM, 0.883 in MIC, and 0.904 in the N group, compared with the SVM and KNN classifiers. Conclusion: MRI-based ML models have the potential to predict cognitive dysfunction in patients with T2DM. Compared with the SVM and KNN, the LR algorithm showed the best performance.

Objective Sleep Quality and the Underlying Functional Neural Correlates Among Older Adults with Possible Mild Cognitive Impairment

BACKGROUND

Poor sleep quality is common among older individuals with mild cognitive impairment (MCI) and may be a consequence of functional alterations in the brain; yet few studies have investigated the underlying neural correlates of actigraphy-measured sleep quality in this cohort.

OBJECTIVE

The objective of this study was to examine the relationship between brain networks and sleep quality measured by actigraphy.

METHODS

In this cross-sectional analysis, sleep efficiency and sleep fragmentation were estimated using Motionwatch8 (MW8) over a period of 14 days in 36 community-dwelling older adults with possible MCI aged 65-85 years. All 36 participants underwent resting-state functional magnetic resonance imaging (fMRI) scanning. Independent associations between network connectivity and MW8 measures of sleep quality were determined using general linear modeling via FSL. Networks examined included the somatosensory network (SMN), frontoparietal network (FPN), and default mode network (DMN).

RESULTS

Across the 36 participants (mean age 71.8 years; SD = 5.2 years), mean Montreal Cognitive Assessment score was 22.5 (SD = 2.7) and Mini-Mental State Examination score was 28.3 (SD = 1.5). Mean sleep efficiency and fragmentation index was 80.1% (SD = 10.0) and 31.8 (SD = 10.4) respectively. Higher sleep fragmentation was significantly correlated with increased connectivity between the SMN and insula, the SMN and posterior cingulate, as well as FPN and primary motor area (FDR-corrected, p <  0.004).

CONCLUSION

Functional connectivity between brain regions involved in attentional and somatosensory processes may be associated with disrupted sleep in older adults with MCI.

Brain Stimulation for Improving Sleep and Memory

Over the past few decades, the importance of sleep has become increasingly recognized for many physiologic functions, including cognition. Many studies have reported the deleterious effect of sleep loss or sleep disruption on cognitive performance. Beyond ensuring adequate sleep quality and duration, discovering methods to enhance sleep to augment its restorative effects is important to improve learning in many populations, such as the military, students, age-related cognitive decline, and cognitive disorders.

Poor sleep accelerates hippocampal and posterior cingulate volume loss in cognitively normal healthy older adults

Poor sleep quality is a known risk factor for Alzheimer's disease. This longitudinal imaging study aimed to determine the acceleration in the rates of tissue loss in cognitively critical brain regions due to poor sleep in healthy elderly individuals. Cognitively-normal healthy individuals, aged ≥60 years, reported Pittsburgh Sleep Quality Index (PSQI) and underwent baseline and 2-year follow-up magnetic resonance imaging brain scans. The links between self-reported sleep quality, rates of tissue loss in cognitively-critical brain regions, and white matter hyperintensity load were assessed. A total of 48 subjects were classified into normal (n = 23; PSQI score <5) and poor sleepers (n = 25; PSQI score ≥5). The two groups were not significantly different in terms of age, gender, years of education, ethnicity, handedness, body mass index, and cognitive performance. Compared to normal sleepers, poor sleepers exhibited much faster rates of volume loss, over threefold in the right hippocampus and fivefold in the right posterior cingulate over 2 years. In contrast, there were no significant differences in the rates of volume loss in the cerebral and cerebellar grey and white matter between the two groups. Rates of volume loss in the right posterior cingulate were negatively associated with global PSQI scores. Poor sleep significantly accelerates volume loss in the right hippocampus and the right posterior cingulate cortex. These findings demonstrate that self-reported sleep quality explains inter-individual differences in the rates of volume loss in cognitively-critical brain regions in healthy older adults and provide a strong impetus to offer sleep interventions to cognitively normal older adults who are poor sleepers.

Reversal of neurovascular coupling in the default mode network: Evidence from hypoxia

Local changes in cerebral blood flow are thought to match changes in neuronal activity, a phenomenon termed neurovascular coupling. Hypoxia increases global resting cerebral blood flow, but regional cerebral blood flow (rCBF) changes are non-uniform. Hypoxia decreases baseline rCBF to the default mode network (DMN), which could reflect either decreased neuronal activity or altered neurovascular coupling. To distinguish between these hypotheses, we characterized the effects of hypoxia on baseline rCBF, task performance, and the hemodynamic (BOLD) response to task activity. During hypoxia, baseline CBF increased across most of the brain, but decreased in DMN regions. Performance on memory recall and motion detection tasks was not diminished, suggesting task-relevant neuronal activity was unaffected. Hypoxia reversed both positive and negative task-evoked BOLD responses in the DMN, suggesting hypoxia reverses neurovascular coupling in the DMN of healthy adults. The reversal of the BOLD response was specific to the DMN. Hypoxia produced modest increases in activations in the visual attention network (VAN) during the motion detection task, and had no effect on activations in the visual cortex during visual stimulation. This regional specificity may be particularly pertinent to clinical populations characterized by hypoxemia and may enhance understanding of regional specificity in neurodegenerative disease pathology.

Nocturnal Hypoxemia Is Associated with Altered Parahippocampal Functional Brain Connectivity in Older Adults at Risk for Dementia

BACKGROUND

Obstructive sleep apnea is associated with an increased risk of developing mild cognitive impairment and dementia. Intermittent nocturnal hypoxemia in obstructive sleep apnea is associated with brain changes in key regions that underpin memory.

OBJECTIVE

To determine whether older adults with severe nocturnal hypoxemia would exhibit reduced functional connectivity within these regions, with associated deficits in memory.

METHODS

Seventy-two participants 51 years and over underwent polysomnography with continuous blood oxygen saturation recorded via oximetry. The oxygen desaturation index (ODI, 3% dips in oxygen levels per hour) was the primary outcome measure. ODI was split into tertiles, with analyses comparing the lowest and highest tertiles (N = 48). Thirty-five of the 48 participants from these two tertiles had mild cognitive impairment. Participants also underwent resting-state fMRI and comprehensive neuropsychological, medical, and psychiatric assessment.

RESULTS

The highest ODI tertile group demonstrated significantly reduced connectivity between the left and right parahippocampal cortex, relative to the lowest ODI tertile group (t(42) = -3.26, p = 0.041, beta = -1.99).The highest ODI tertile group also had poorer working memory performance. In the highest ODI tertile group only, higher left-right parahippocampal functional connectivity was associated with poorer visual memory recall (between-groups z = -2.93, p = 0.0034).

CONCLUSIONS

Older adults with severe nocturnal hypoxemia demonstrate impaired functional connectivity in medial temporal structures, key regions involved in sleep memory processing and implicated in dementia pathophysiology. Oxygen desaturation and functional connectivity in these individuals each relate to cognitive performance. Research is now required to further elucidate these findings.

Resting State Abnormalities of the Default Mode Network in Mild Cognitive Impairment: A Systematic Review and Meta-Analysis

BACKGROUND

Large-scale brain networks such as the default mode network (DMN) are often disrupted in Alzheimer's disease (AD). Numerous studies have examined DMN functional connectivity in those with mild cognitive impairment (MCI), a presumed AD precursor, to discover a biomarker of AD risk. Prior reviews were qualitative or limited in scope or approach.

OBJECTIVE

We aimed to systematically and quantitatively review DMN resting state fMRI studies comparing MCI and healthy comparison (HC) groups.

METHODS

PubMed was searched for relevant articles. Study characteristics were abstracted and the number of studies showing no group difference or hyper- versus hypo-connnectivity in MCI was tallied. A voxel-wise (ES-SDM) meta-analysis was conducted to identify regional group differences.

RESULTS

Qualitatively, our review of 57 MCI versus HC comparisons suggests substantial inconsistency; 9 showed no group difference, 8 showed MCI > HC and 22 showed HC > MCI across the brain, and 18 showed regionally-mixed directions of effect. The meta-analysis of 31 studies revealed areas of significant hypo- and hyper-connectivity in MCI, including hypoconnectivity in the posterior cingulate cortex/precuneus (z = -3.1, p < 0.0001). Very few individual studies, however, showed patterns resembling the meta-analytic results. Methodological differences did not appear to explain inconsistencies.

CONCLUSIONS

The pattern of altered resting DMN function or connectivity in MCI is complex and variable across studies. To date, no index of DMN connectivity qualifies as a useful biomarker of MCI or risk for AD. Refinements to MCI diagnosis, including other biological markers, or longitudinal studies of progression to AD, might identify DMN alterations predictive of AD risk.

Objective measurement of sleep in mild cognitive impairment: A systematic review and meta-analysis

Older adults with mild cognitive impairment (MCI) are at-risk of developing dementia, particularly Alzheimer's disease. While some research suggests that alterations in sleep architecture may mediate cognitive decline, the nature and magnitude of changes to sleep macro- (sleep stages) and micro-architecture (electroencephalography (EEG) oscillations) in MCI is not yet clear. This study aimed to systematically review and meta-analyse case-control studies objectively measuring sleep in MCI. A systematic search was conducted using PubMed, Scopus, Web of Science, Embase and Psycinfo databases and after review, a total of 10 studies met inclusion criteria. Of these, all reported sleep macro-architecture and four reported micro-architecture outcomes. A combined total of 430 participants (209 with and 221 without MCI) underwent objective sleep assessments in the included full text articles. Findings show that compared to healthy controls, those with MCI have pronounced changes in sleep macro-architecture with greater wake after sleep onset, reduced total sleep time, lower sleep efficiency, longer sleep onset latency, longer rapid eye movement sleep (REM) latency, reduced REM sleep, greater N1 sleep, and worse severity of hypoxemia. Pooling of sleep micro-architecture EEG measures was not possible due to limited studies, however reduced spindles in non-REM sleep and greater EEG slowing in REM sleep were reported.

Brain Stimulation for Improving Sleep and Memory

Given the critical role of sleep, particularly sleep slow oscillations, sleep spindles, and hippocampal sharp wave ripples, in memory consolidation, sleep enhancement represents a key opportunity to improve cognitive performance. Techniques such as transcranial electrical and magnetic stimulation and acoustic stimulation can enhance slow oscillations and sleep spindles and potentially improve memory. Targeted memory reactivation in sleep may enhance or stabilize memory consolidation. Each technique has technical considerations that may limit its broader clinical application. Therefore, neurostimulation to enhance sleep quality, in particular sleep slow oscillations, has the potential for improving sleep-related memory consolidation in healthy and clinical populations.

"Sleep Well, Think Well" Group Program for Mild Cognitive Impairment: A Randomized Controlled Pilot Study

Objective/Background: Sleep-wake disturbance is associated with poor cognitive functioning and several other adverse outcomes that increase dementia risk in older adults. Targeting sleep-wake disturbance in individuals at risk for dementia may be an important treatment. This study evaluated the efficacy of a four-session multicomponent group intervention for participants with mild cognitive impairment (MCI). Participants: Thirty-five older adults with MCI (mean age = 69.7 years, SD = 9.1), were recruited. MCI was determined via consensus from neuropsychological, medical, and neurological review. Methods: Participants were randomized to the "Sleep Well, Think Well" (SWTW) group condition or a passive control group. The SWTW group received four fortnightly face-to-face sessions conducted by an experienced sleep psychologist and neuropsychologist. The control group received written material detailing strategies to improve sleep quality. Both groups received fortnightly coaching phone calls. The primary outcome was subjective sleep quality, measured by the Pittsburgh Sleep Quality Index (PSQI). Secondary outcomes included actigraphy sleep measures, daytime sleepiness, cognitive functioning, and depression severity. Results: The SWTW intervention was associated with a large and statistically significant improvement in subjective sleep quality (Cohen's d = 0.83, p < 0.02). A moderate nonsignificant effect was evident in reducing daytime sleepiness (Cohen's d = 0.70, p = .08). No significant effects were found on actigraphy markers, depressive symptoms, or tests of cognitive functioning. Conclusions: The eight-week SWTW group intervention for MCI significantly improved subjective sleep quality when compared with a passive control condition. The program also had a moderate (nonsignificant) effect on reducing daytime sleepiness.

Advanced Circadian Timing and Sleep Fragmentation Differentially Impact on Memory Complaint Subtype in Subjective Cognitive Decline

BACKGROUND

Increased sleep fragmentation and advanced circadian timing are hallmark phenotypes associated with increased age-related cognitive decline. Subjective cognitive decline (SCD) is considered a prodromal stage of neurodegeneration and dementia; however, little is known about how sleep and circadian timing impact on memory complaints in SCD.

OBJECTIVE

To determine how sleep and circadian timing impact on memory complaint subtypes in older adults with SCD.

METHODS

Twenty-five older adults with SCD (mean age = 69.97, SD = 5.33) completed the Memory Functioning Questionnaire to characterize their memory complaints. They also underwent neuropsychological assessment, and completed 1 week of at-home monitoring of sleep with actigraphy and sleep diaries. This was followed by a two-night laboratory visit with overnight polysomnography and a dim light melatonin onset assessment to measure circadian timing.

RESULTS

Advanced circadian timing was associated with greater memory complaints, specifically poorer memory of past events (r = -0.688, p = 0.002), greater perceived decline over time (r = -0.568, p = 0.022), and increased reliance on mnemonic tools (r = -0.657, p = 0.004). Increased sleep fragmentation was associated with reduced self-reported memory decline (r = 0.529, p = 0.014), and reduced concern about everyday forgetfulness (r = 0.435, p = 0.038).

CONCLUSION

Advanced circadian timing was associated with a number of subjective memory complaints and symptoms. By contrast, sleep fragmentation was linked to lowered perceptions of cognitive decline, and less concern about memory failures. As circadian disruption is apparent in both MCI and Alzheimer's disease, and plays a key role in cognitive function, our findings further support a circadian intervention as a potential therapeutic tool for cognitive decline.

Relationships between sleep quality, depressive symptoms and MCI diagnosis: A path analysis

BACKGROUND

This study examined the complex relationships between sleep quality, depressive symptoms, and cognitive decline in older adults. We hypothesised that older age, lower education and greater medical comorbidities would each be associated with increased mild cognitive impairment (MCI) diagnosis risk through indirect effects via poorer sleep quality, and greater depressive symptomology.

METHODS

540 adults 44 years and over were recruited at the Brain and Mind Centre, Sydney, Australia. Participants underwent comprehensive psychiatric, neuropsychological, and medical assessment. Subjective sleep quality, current depressive symptomatology, and current medical burden were assessed.

RESULTS

There were significant indirect effects of each of age, comorbidities and education, that operated via both sleep and depression. Younger age, greater comorbidities and fewer years' education each predicted greater chance of MCI diagnosis via poorer sleep and in turn higher depressive symptomatology. Additionally, there was a significant direct effect of older age on MCI.

LIMITATIONS

The current study is cross-sectional and cannot determine whether poorer sleep quality and greater depressive symptomatology precede or arise as a result of the onset of cognitive decline in later-life. A longitudinal design may allow further explication of these relationships.

CONCLUSIONS

Both sleep and depression are linked with cognitive decline in older adults, with sleep disturbance appearing to predict depressive symptoms. These findings have implications for the management of MCI. Both greater depression symptomatology and sleep disturbance were shown to predict the risk of MCI diagnosis, with this effect strongest in those that are younger. Improved early detection and treatment of sleep problems in older adults may help prevent depressive symptom manifestation or exacerbation, in turn potentially reducing the risk of subsequent cognitive decline.

Alterations in Brain Network Topology and Structural-Functional Connectome Coupling Relate to Cognitive Impairment

According to the network-based neurodegeneration hypothesis, neurodegenerative diseases target specific large-scale neural networks, such as the default mode network, and may propagate along the structural and functional connections within and between these brain networks. Cognitive impairment no dementia (CIND) represents an early prodromal stage but few studies have examined brain topological changes within and between brain structural and functional networks. To this end, we studied the structural networks [diffusion magnetic resonance imaging (MRI)] and functional networks (task-free functional MRI) in CIND (61 mild, 56 moderate) and healthy older adults (97 controls). Structurally, compared with controls, moderate CIND had lower global efficiency, and lower nodal centrality and nodal efficiency in the thalamus, somatomotor network, and higher-order cognitive networks. Mild CIND only had higher nodal degree centrality in dorsal parietal regions. Functional differences were more subtle, with both CIND groups showing lower nodal centrality and efficiency in temporal and somatomotor regions. Importantly, CIND generally had higher structural-functional connectome correlation than controls. The higher structural-functional topological similarity was undesirable as higher correlation was associated with poorer verbal memory, executive function, and visuoconstruction. Our findings highlighted the distinct and progressive changes in brain structural-functional networks at the prodromal stage of neurodegenerative diseases.

Current sleep disturbance in older people with a lifetime history of depression is associated with increased connectivity in the Default Mode Network

BACKGROUND

The present study investigated Default Mode Network (DMN) functional connectivity in subjects with a lifetime history of major depression, comparing those with and without current sleep disturbance. Controls were included to assess DMN abnormalities specific to depression.

METHODS

A total of 93 adults aged 50 years and over were recruited from the Healthy Brain Ageing Clinic at the Brain and Mind Centre, Sydney, Australia. The sample comprised two groups, including 22 controls and 71 participants with a lifetime history of DSM-IV major depression (with depressive episode current or remitted). 52 of those with a lifetime history of depression also met criteria for Mild Cognitive Impairment (MCI). Participants underwent resting-state fMRI along with comprehensive psychiatric, neuropsychological, and medical assessment. Subjective sleep quality was assessed via the Pittsburgh Sleep Quality Index (PSQI). Sleep disturbance was defined as a PSQI score > 5. A total of 68% (n = 48) of cases with a lifetime history of depression met criteria for sleep-disturbance. DMN functional connectivity was assessed via ROI-to-ROI analyses.

RESULTS

Relative to controls, those with lifetime major depression demonstrated significantly increased functional connectivity between the ventromedial prefrontal cortex and the temporal pole. Within the depression group (n = 48), those with current sleep disturbance had significantly increased connectivity between the anterior medial prefrontal cortex and both the parahippocampal cortex and the hippocampal formation, relative to those without sleep disturbance (n = 23). These results were present after controlling for MCI diagnosis.

CONCLUSIONS

Current sleep disturbance together with depression is associated with distinct abnormalities in DMN functioning incorporating regions responsible for self-reflection and declarative memory processes. Impaired sleep is associated with increased connectivity between these regions. Future studies may augment these findings with complementary imaging techniques including cortical thickness and diffusion tensor imaging, as well as high density electroencephalogram recording.

Sleep disturbance in mild cognitive impairment: a systematic review of recent findings

PURPOSE OF REVIEW

Research interest in sleep as a risk factor for dementia has grown, warranting an update in advances over the last 18 months, particularly in the mild cognitive impairment (MCI) stage in which interventions may be best targeted.

RECENT FINDINGS

The current systematic review includes empiric research articles published since 2016 that have investigated sleep (excluding obstructive sleep apnea) in MCI. Published articles include case-control studies, those examining clinical correlates of sleep problems, sleep microarchitecture, neuroimaging studies and novel cerebrospinal and blood-based markers.

SUMMARY

Evidence accumulated since 2016 continues to demonstrate that people with MCI manifest sleep disturbance on self-report measures. Neurophysiologically, sleep disturbance in MCI appears to be associated with diminished sleep spindles, key processes involved in overnight memory consolidation. Those with both MCI and sleep disturbance appear to have more pronounced functional connectivity alterations in temporoparietal brain regions and higher levels of the wake-promoting neurotransmitter orexin in cerebrospinal fluid than those with MCI alone. Novel findings also suggest that sleep may mediate homocysteine and oxidative stress mechanisms, warranting further exploration. Further studies focusing on novel interventions for sleep and circadian disturbance in MCI are warranted, particularly those targeting sleep spindles, orexin/hypocretin and the oxidative stress system.

Do Older Adults Need Sleep? A Review of Neuroimaging, Sleep, and Aging Studies

PURPOSE OF REVIEW

Sleep habits, sleep physiology, and sleep disorders change with increasing age. However, there is a longstanding debate regarding whether older adults need sleep to maintain health and daily functioning (reduced-sleep-need view). An alternative possibility is that all older adults need sleep, but that many older adults have lost the ability to obtain restorative sleep (reduced-sleep-ability view). Prior research using behavioral and polysomnography outcomes has not definitively disentangled the reduced-sleep-need and reduced-sleep-ability views. Therefore, this review examines the neuroimaging literature to determine whether age-related changes in sleep cause-or are caused by-age-related changes in brain structure, function, and pathology.

RECENT FINDINGS

In middle-aged and older adults, poorer sleep quality, greater nighttime hypoxia, and shorter sleep duration related to cortical thinning in frontal regions implicated in slow wave generation, in frontoparietal networks implicated in cognitive control, and in hippocampal regions implicated in memory consolidation. Furthermore, poor sleep quality was associated with higher amyloid burden and decreased connectivity in the default mode network, a network that is disrupted in the pathway to Alzheimer's disease.

SUMMARY

All adults need sleep, but cortical thinning and amyloidal deposition with advancing age may weaken the brain's ability to produce restorative sleep. Therefore, sleep in older adults may not always support identical functions for physical, mental, and cognitive health as in young adults.