Effects of aging on slow-wave sleep dynamics and human spatial navigational memory consolidation

Abstract

The consolidation of spatial navigational memory during sleep is supported by electrophysiological and behavioral evidence. The features of sleep that mediate this ability may change with aging, as percentage of slow wave sleep is canonically thought to decrease with age, and slow waves are thought to help orchestrate hippocampal-neocortical dialogue that supports systems level consolidation. In this study, groups of younger and older subjects performed timed trials before and after polysomnographically recorded sleep on a 3D spatial maze navigational task. Although younger subjects performed better than older subjects at baseline, both groups showed similar improvement across pre-sleep trials. However, younger subjects experienced significant improvement in maze performance during sleep that was not observed in older subjects, without differences in morning psychomotor vigilance between groups. Older subjects had sleep quality marked by decreased amount of slow wave sleep and increased fragmentation of slow wave sleep, resulting in decreased slow wave activity. Across all subjects, frontal slow wave activity was positively correlated with both overnight change in maze performance and medial prefrontal cortical volume, illuminating a potential neuroanatomical substrate for slow wave activity changes with aging and underscoring the importance of slow wave activity in sleep-dependent spatial navigational memory consolidation.

Sleep and Human Aging

“…Recent studies in humans have further established that Aβ is selectively associated with the loss of <1 Hz NREM sleep oscillations (Mander et al, 2015). This association between Aβ and <1 Hz NREM oscillations appears to be unique and distinct from general age-related reductions in the broader SWA range of 0.6–4.8 Hz; with the latter linked, instead, to gray matter atrophy within the medial prefrontal cortex (Dubé et al, 2015; Mander et al, 2013; Varga et al, 2016). Aβ further correlates with reduced REM sleep amount in healthy older adults (Mander et al, 2015) and patients with AD (Liguori et al, 2014).…”

“…Atrophy within similar PFC brain regions, measured by both gray matter volume and cortical thickness, predicts the severity of impairment in NREM slow wave features in older adults (Dubé et al, 2015; Mander et al, 2013; Varga et al, 2016). This association with gray matter atrophy is especially pronounced in medial and lateral PFC regions (Figure 5).…”

“…This would suggest that age-related changes in NREM sleep oscillations are not simply a consequence of generalized, non-specific whole-brain atrophy (Mander et al, 2013), but regionally specific cortical atrophy in frontal regions (Dubé et al, 2015; Mander et al, 2013; Varga et al, 2016). However, cortical thinning of gray matter in posterior brain regions, including the superior parietal cortex, does mediate age-related changes in slow wave amplitude (Dubé et al, 2015), inferring that atrophy within specific regions beyond the PFC can indirectly contribute to age-related disruptions in slow wave expression.…”

“…Alcohol has marked effects on the quantity and quality of sleep (Thakkar et al, 2015). Indirect effects of alcohol are also possible: greater alcohol intake is associated with greater medial prefrontal atrophy (Rando et al, 2011), and the integrity and functionality of the medial prefrontal cortex is critical for NREM slow wave generation (Dubé et al, 2015; Mander et al, 2013; Murphy et al, 2009; Varga et al, 2016). Nevertheless, all these proposed mechanisms remain speculative.…”

Reduced Slow-Wave Sleep Is Associated with High Cerebrospinal Fluid Aβ42 Levels in Cognitively Normal Elderly

“…No subjects were excluded due to these abnormalities. In view of recent evidence suggesting that frontal atrophy is associated with reduced SWS in normal elderly, 15,16 we measured cortical volumes from MPRAGE sequences using the FreeSurfer toolkit 17 and computed gray matter volumes to create a medial prefrontal cortex (mPFC) region of interest (ROI) using the following bilateral ROIs: caudal anterior cingulate cortex, medial orbitofrontal cortex, rostral anterior cingulate cortex and superior frontal gyrus. 18 Resulting ROIs were adjusted (residualized) to their intracranial volume using linear regression.…”