Data offers new neurobiological insight into insomnia

A recent study provided the first in vivo evidence supporting a strong relationship between ascending arousal network (ON) and insomnia. The study specifically focused on patients with chronic insomnia disorder (CID) associated with mental health disorders and an increased risk of depression and anxiety.

The team of researchers, led by Liang Gong, Department of Neurology, Chengdu Second People’s Hospital, stated that despite being the second most common neurophysical disorder, there is limited understanding about the neurobiological mechanisms of chronic insomnia.

Recent insights on the pathogenesis of insomnia have been provided by the brain hyperarousal process model and the experience of hyperarousal is a persistent feature of patients with insomnia. The aim of this study was to explore the ascending arousal network, changes and connections to cortical networks in chronic insomnia.

Assessing the arousal network and sleep

A population of 60 patients with the chronic condition was evaluated alongside a control population of 60 demographically matched individuals considered to be good sleepers. Researchers performed a series of neuropsychological tests followed by an MRI scan for all participants.

There were 9 regions of interest (ROIs) for imaging: the dorsal raphe nucleus, LC, mesencephalic reticular formation (MRF), median raphe nucleus (MR), PAG, PBC, pontine nucleus oral (PO), PPN, and ventral tegmental area. As for the 8 cortical functional networks, the researchers focused on DMN, 4 nodes; SN, 7 nodes; THEN, 4 nodes; FPN, 4 nodes; SMN, 3 nodes; visual network (UN), 4 nodes; language network (LN), 4 nodes; and cerebellar network (CBN), 2 nodes.

Insomnia severity and subjective sleep quality were assessed with the PSQI scale. Zung’s Self-Rating Depression Scale (SDS) and Anxiety Scale (SAS) were implemented for measures of depression and anxiety.

The final analysis consisted of 57 patients in the study group and 56 in the control group. An independent dataset with 30 patients with CID and 30 in the control group was also provided for classification and regression model validation.

Understanding the pathophysiology of insomnia

Findings demonstrated changes in the brain’s functional connectivity between the ascending arousal network and 8 cortical networks in patients with chronic insomnia, as well as the control group. To predict clinical symptoms of insomnia and distinguish between the groups, researchers applied a multivariate pattern analysis in the main study groups and the external data set for further verification.

Increased functional connectivity in the ascending arousal network was identified in patients with CID. In addition, these patients showed increased functional connectivity between the ON and default mode, cerebellar, sensorimotor and dorsal attentional networks.

“These AAN-related FC patterns and the MVPA classification model could be used to differentiate CID patients from GSCs with 88% accuracy in the first cohort and 77% accuracy in the validation cohort,” the researchers said.

The prediction models were even able to predict insomnia and anxiety symptoms separately in the independent cohort groups. Overall, the data highlighted the role of the ascending arousal network in the pathophysiology of insomnia, along with the co-morbidities of mental symptoms.

“Our findings indicated that AAN contributed to the neurobiological mechanism of insomnia and emphasized that fMRI-based markers and machine learning techniques can facilitate the evaluation of insomnia and its comorbid mental symptoms,” the team concluded.

The study “The role of ascending arousal network in patients with chronic insomnia” was published in: Mapping the human brain.

Data offers new neurobiological insight into insomnia

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