Human brain activity is intrinsically organized into resting-state networks (RSNs) that transiently activate or deactivate at the sub-second timescale. Few neuroimaging studies have addressed how Alzheimer's disease (AD) affects these fast temporal brain dynamics, and how they relate to the cognitive, structural and metabolic abnormalities characterizing AD. We aimed at closing this gap by investigating both brain structure and function using magnetoencephalography (MEG) and hybrid positron emission tomography-magnetic resonance (PET/MR) in 10 healthy elders, 10 patients with subjective cognitive decline (SCD), 10 patients with amnestic mild cognitive impairment (aMCI) and 10 patients with typical Alzheimer’s disease with dementia (AD). The fast activation/deactivation state dynamics of RSNs were assessed using hidden Markov modeling (HMM) of power envelope fluctuations at rest measured with MEG. Correlations were sought between temporal properties of HMM states and participants' cognitive test scores, whole hippocampal grey matter volume and regional brain glucose metabolism. The posterior default-mode network (DMN) was less often activated and for shorter durations in AD patients than matched healthy elders. No significant difference was found in patients with SCD or aMCI. The time spent by participants in the activated posterior DMN state did not correlate significantly with cognitive scores, nor with the whole hippocampal volume. However, it correlated positively with the regional glucose consumption in the right dorsolateral prefrontal cortex (DLPFC). AD patients present alterations of posterior DMN power activation dynamics at rest that identify an additional electrophysiological correlate of AD-related synaptic and neural dysfunction. The right DLPFC may play a causal role in the activation of the posterior DMN, possibly linked to the occurrence of mind wandering episodes. As such, these data might suggest a neural correlate of the decrease in mind wandering episodes reported in pathological aging.

This magnetoencephalography study aimed at characterizing age-related changes in resting-state functional brain organization from mid-childhood to late adulthood. We investigated neuromagnetic brain activity at rest in 105 participants divided into three age groups: children (6–9 years), young adults (18–34 years) and healthy elders (53–78 years). The effects of age on static resting-state functional brain integration were assessed using band-limited power envelope correlation, whereas those on transient functional brain dynamics were disclosed using hidden Markov modeling of power envelope activity. Brain development from childhood to adulthood came with (1) a strengthening of functional integration within and between resting-state networks and (2) an increased temporal stability of transient (100–300 ms lifetime) and recurrent states of network activation or deactivation mainly encompassing lateral or medial associative neocortical areas. Healthy aging was characterized by decreased static resting-state functional integration and dynamic stability within the primary visual network. These results based on electrophysiological measurements free of neurovascular biases suggest that functional brain integration mainly evolves during brain development, with limited changes in healthy aging. These novel electrophysiological insights into human brain functional architecture across the lifespan pave the way for future clinical studies investigating how brain disorders affect brain development or healthy aging.

Performance for controlled, resource‐demanding retrieval in episodic memory has been consistently found to be better at an optimal compared with non‐optimal time of the day, evidencing a synchrony effect. However, performance in memory tasks in which retrieval is mostly based on automatic processes was inconclusively found either to be better at a non‐optimal time of day or independent of synchrony effects. A caveat in most prior studies is that optimal/non‐optimal time of day is based on morningness–eveningness composite scores derived from chronotype questionnaires, which might not efficiently predict subjectively‐defined cognitive efficiency periods. An additional caveat is that separate tasks are used to assess explicit and implicit retrieval in verbal memory. Indeed, no task is process‐pure, and both controlled and automatic retrieval processes may potentially contribute to retrieval scores in different types of memory tasks. In the present study, we investigated the impact of individually defined subjective optimal/non‐optimal time of day on verbal memory retrieval, using an adaptation of the Process‐Dissociation Procedure that allows estimating the respective contributions of automatic and controlled memory retrieval processes within the same memory task. Our results disclose a higher involvement of controlled processes at subjectively optimal compared with non‐optimal time of day, but no differences for automatic processes. Synchrony effects and subjectively‐defined peaks and troughs of performance for controlled components of memory retrieval should be considered in the evaluation of episodic memory.

This magnetoencephalography study aimed at characterizing age-related changes in resting-state functional brain organization from mid-childhood to late adulthood. We investigated neuromagnetic brain activity at rest in 105 participants divided into three age groups: children (6-9 years), young adults (18-34 years) and healthy elders (53-78 years). The effects of age on static resting-state functional integration were assessed using band-limited power envelope correlation, whereas those on transient functional dynamics were disclosed using hidden Markov modeling of power envelope activity. Brain development from childhood to adulthood came with (i) a strengthening of functional integration within and between resting-state networks and (ii) an increased temporal stability of transient (100-300 ms lifetime) and recurrent states of network activation or deactivation mainly encompassing lateral or medial associative neocortical areas. Healthy aging was characterized by decreased static resting-state functional integration and dynamical stability within the visual network. These results based on electrophysiological measurements free of neurovascular biases suggest that functional brain integration mainly evolves during brain development, with limited changes in healthy aging.These novel electrophysiological insights into human brain functional architecture across the lifespan pave the way for future clinical studies investigating how brain disorders affect brain development or healthy aging.

Human brain activity is intrinsically organized into resting-state networks (RSNs) that transiently activate or deactivate at the sub-second timescale. Few neuroimaging studies have addressed how Alzheimer's disease (AD) affects these fast temporal brain dynamics, and how they relate to the cognitive, structural and metabolic abnormalities characterizing AD.We aimed at closing this gap by investigating both brain structure and function using magnetoencephalography (MEG) and hybrid positron emission tomography-magnetic resonance (PET/MR) in 10 healthy elders, 10 patients with Subjective Cognitive Decline (SCD), 10 patients with amnestic Mild Cognitive Impairment (aMCI) and 10 patients with typical Alzheimer's disease with dementia (AD). The fast activation/deactivation state dynamics of RSNs were assessed using hidden Markov modeling (HMM) of power envelope fluctuations at rest measured with MEG. HMM patterns were related to participants' cognitivetest scores, whole hippocampal grey matter volume and regional brain glucose metabolism.The posterior default-mode network (DMN) was less often activated and for shorter durations in AD patients than matched healthy elders. No significant difference was found in patients with SCD or aMCI. The time spent by participants in the activated posterior DMN state did not correlate significantly with cognitive scores. However, it correlated positively with the whole hippocampal volume and regional glucose consumption in the right temporo-parietal junctions and dorsolateral prefrontal cortex, and negatively with glucose consumption in the cerebellum.In AD patients, alterations of posterior DMN power activation dynamics at rest correlate with structural and neurometabolic abnormalities. These findings represent an additional electrophysiological correlate of AD-related synaptic and neural dysfunction.