Correction: Sleep loss leads to the withdrawal of human helping across individuals, groups, and large-scale societies.

[This corrects the article DOI: 10.1371/journal.pbio.3001733.].

Sleep Loss Influences the Interconnected Brain-Body Regulation of Cardiovascular Function in Humans.

OBJECTIVE: Poor sleep is associated with hypertension, a major risk factor for cardiovascular disease. However, the mechanism(s) through which sleep loss affects cardiovascular health remains largely unknown, including the brain and body systems that regulate vascular function. METHODS: Sixty-six healthy adults participated in a repeated-measures, crossover, experimental study involving assessments of cardiovascular function and brain connectivity after a night of sleep and a night of sleep deprivation. RESULTS: First, sleep deprivation significantly increased blood pressure-both systolic and diastolic. Interestingly, this change was independent of any increase in heart rate, inferring a vasculature-specific rather than direct cardiac pathway. Second, sleep loss compromised functional brain connectivity within the vascular control network, specifically the insula, anterior cingulate, amygdala, and ventral and medial prefrontal cortices. Third, sleep loss-related changes in brain connectivity and vascular tone were not independent, but significantly interdependent, with changes within the vascular control brain network predicting the sleep-loss shift toward hypertension. CONCLUSIONS: These findings establish an embodied framework in which sleep loss confers increased risk of cardiovascular disease through an impact upon central brain control of vascular tone, rather than a direct impact on accelerated heart rate itself.

The sleep-deprived human brain.

How does a lack of sleep affect our brains? In contrast to the benefits of sleep, frameworks exploring the impact of sleep loss are relatively lacking. Importantly, the effects of sleep deprivation (SD) do not simply reflect the absence of sleep and the benefits attributed to it; rather, they reflect the consequences of several additional factors, including extended wakefulness. With a focus on neuroimaging studies, we review the consequences of SD on attention and working memory, positive and negative emotion, and hippocampal learning. We explore how this evidence informs our mechanistic understanding of the known changes in cognition and emotion associated with SD, and the insights it provides regarding clinical conditions associated with sleep disruption.

Losing Neutrality: The Neural Basis of Impaired Emotional Control without Sleep.

Sleep deprivation has been shown recently to alter emotional processing possibly associated with reduced frontal regulation. Such impairments can ultimately fail adaptive attempts to regulate emotional processing (also known as cognitive control of emotion), although this hypothesis has not been examined directly. Therefore, we explored the influence of sleep deprivation on the human brain using two different cognitive-emotional tasks, recorded using fMRI and EEG. Both tasks involved irrelevant emotional and neutral distractors presented during a competing cognitive challenge, thus creating a continuous demand for regulating emotional processing. Results reveal that, although participants showed enhanced limbic and electrophysiological reactions to emotional distractors regardless of their sleep state, they were specifically unable to ignore neutral distracting information after sleep deprivation. As a consequence, sleep deprivation resulted in similar processing of neutral and negative distractors, thus disabling accurate emotional discrimination. As expected, these findings were further associated with a decrease in prefrontal connectivity patterns in both EEG and fMRI signals, reflecting a profound decline in cognitive control of emotion. Notably, such a decline was associated with lower REM sleep amounts, supporting a role for REM sleep in overnight emotional processing. Altogether, our findings suggest that losing sleep alters emotional reactivity by lowering the threshold for emotional activation, leading to a maladaptive loss of emotional neutrality. Significance statement: Sleep loss is known as a robust modulator of emotional reactivity, leading to increased anxiety and stress elicited by seemingly minor triggers. In this work, we aimed to portray the neural basis of these emotional impairments and their possible association with frontal regulation of emotional processing, also known as cognitive control of emotion. Using specifically suited EEG and fMRI tasks, we were able to show that sleep deprivation alters emotional reactivity by triggering enhanced processing of stimuli regarded previously as neutral. These changes were further accompanied by diminished frontal connectivity, reduced REM sleep, and poorer performance. Therefore, we suggest that sleep loss alters emotional reactivity by lowering the threshold for emotional activation, leading to a maladaptive loss of emotional neutrality.

RichMind: A Tool for Improved Inference from Large-Scale Neuroimaging Results.

As the use of large-scale data-driven analysis becomes increasingly common, the need for robust methods for interpreting a large number of results increases. To date, neuroimaging attempts to interpret large-scale activity or connectivity results often turn to existing neural mapping based on previous literature. In case of a large number of results, manual selection or percent of overlap with existing maps is frequently used to facilitate interpretation, often without a clear statistical justification. Such methodology holds the risk of reporting false positive results and overlooking additional results. Here, we propose using enrichment analysis for improving the interpretation of large-scale neuroimaging results. We focus on two possible cases: position group analysis, where the identified results are a set of neural positions; and connection group analysis, where the identified results are a set of neural position-pairs (i.e. neural connections). We explore different models for detecting significant overrepresentation of known functional brain annotations using simulated and real data. We implemented our methods in a tool called RichMind, which provides both statistical significance reports and brain visualization. We demonstrate the abilities of RichMind by revisiting two previous fMRI studies. In both studies RichMind automatically highlighted most of the findings that were reported in the original studies as well as several additional findings that were overlooked. Hence, RichMind is a valuable new tool for rigorous inference from neuroimaging results.