Why the Brain and Breath Part Ways During Heavy Slumber

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Parkinson’s Disease May Have Link to Stroke March 2017 

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Why the Brain and Breath Part Ways During Heavy Slumber

Summary: Does your brain stop “listening” to your lungs when you fall into a deep sleep? According to a new study, the answer is yes. Researchers discovered that during the deepest stages of non-REM sleep (characterized by slow delta waves), the brain’s activity becomes increasingly independent of the rhythm of breathing.

By focusing on the substantia nigra—a deep-brain region that produces dopamine and controls movement—scientists found that the usual “coupling” between breath and brain waves seen during wakefulness and lighter sleep essentially dissolves during deep rest. This discovery offers vital clues into the mechanics of anesthesia and could lead to new treatments for Parkinson’s disease, where both sleep and breathing are often severely disrupted.

Key Facts

• The “Disconnect”: While brain waves and breathing patterns are usually synchronized during quiet wakefulness and light sleep, they become mostly independent during the “slow delta” activity of the deepest non-REM sleep.
• Focus on the Substantia Nigra: This is the first study to detail how breathing affects this critical deep-brain region, which is responsible for dopamine production and motor control.
• Parkinson’s Link: Because the substantia nigra is the primary area damaged in Parkinson’s disease, understanding its “rhythm” during sleep could explain why Parkinson’s patients suffer from both sleep apnea and insomnia.
• Anesthesia Insights: The study also compared sleep states to ketamine anesthesia, finding that different states of “unconsciousness” have unique ways of linking (or unlinking) the brain to peripheral rhythms like breathing.
• The Primary Motor Cortex: In addition to the deep brain, researchers tracked the motor cortex, showing that this “breath-brain decoupling” is a widespread phenomenon during deep restorative sleep.

Source: HMH

Could the deepest parts of the brain hold some of the secrets of sleep that still remain elusive to science?

A team from Hackensack Meridian Health and its Center for Discovery and Innovation (CDI) have produced a new in-depth study penetrating into the brain, finding that during the deepest sleep, breathing patterns and brain activity become more independent from one another – unlike lighter sleep or quiet wakefulness.

Scientists have discovered that during the deepest stages of sleep, the brain’s neural activity operates independently from the rhythm of respiration. Credit: Neuroscience News

The study was published in The Journal of Neuroscience in January, with the team led by CDI author Bon-Mi Gu, Ph.D., also of the Hackensack Meridian School of Medicine. The research team includes Kolsoum Dehdar, Ph.D., and Elliot Neuberg, and recently relocated from the Neuroscience Institute at Hackensack Meridian JFK University Medical Center to the CDI.

The paper focuses on the basal ganglia, clusters of neurons responsible for motor control and other roles. Of prime interest to the scientists is the tiny region called the substantia nigra, which controls movements and produces dopamine, among other functions.

The relation between these structures and sleep – and how they relate to each other’s rhythm has not heretofore been widely studied, according to the scientists.

“In this study, we provide the first detailed characterization of respiration-neural coupling across multiple states – including quiet wakefulness, non-REM sleep, REM sleep, and anesthesia – in the substantia nigra and the primary motor cortex, two regions not previously studied in this context,” write the authors.

The team measured the sleep cycles of mice, comparing electrical brain activity and breathing and how the two timed off one another. They also assessed the mice during wakefulness, as well as under ketamine anesthesia.

The scientists found nuances and variations in all states. But one consistent thread was that the deepest non-REM sleep had breathing mostly independent of the brain waves, especially with the “slow delta” activity during the deepest part of slumber.

“The strength of respiration-neural coupling varied across multiple states, including NREM sleep, REM sleep, quiet wakefulness, and anesthesia, and was directly related to the delta power, a hallmark of NREM sleep,” write the authors.

The conclusions could pave the way into better understanding of how sleep works – and could help with some disease states, they find.

“These findings provide new insights into how internal brain states interact with peripheral rhythms like respiration, with important functional implications for both sleep and anesthesia,” write the scientists.

“Furthermore,” they add, “elucidating the mechanisms underlying respiration-neural coupling, especially within basal ganglia circuits, will shed light on the pathophysiology of conditions such as Parkinson’s disease, where both sleep and respiration are commonly disrupted.”

Key Questions Answered:

Q: If my brain and breath “disconnect,” is that dangerous?

A: Not at all—it’s actually a hallmark of restorative sleep. During wakefulness, your brain is highly responsive to the world (and your own body). In deep sleep, the brain essentially “closes the curtains” to focus on internal maintenance and memory consolidation, allowing its waves to flow independently of your physical breathing rhythm.

Q: Why does this study focus on the “Substantia Nigra”?

A: This region is the brain’s “dopamine factory.” We already know it’s vital for movement, but we didn’t know how it behaved during sleep. If this region fails to “decouple” or “sync up” correctly, it might be the reason why people with Parkinson’s experience such restless, low-quality sleep.

Q: Could this lead to better anesthesia?

A: Yes. By understanding how breathing and brain waves interact under anesthesia versus natural sleep, doctors can develop more precise ways to monitor patients, ensuring they stay at the perfect level of unconsciousness without disrupting their vital rhythms.

Editorial Notes:

• This article was edited by a Neuroscience News editor.
• Journal paper reviewed in full.
• Additional context added by our staff.

About this sleep and neuroscience research news

Author: Seth Augenstein
Source: HMH
Contact: Seth Augenstein – HMH
Image: The image is credited to Neuroscience News

Night breathing patterns identify people with Parkinson’s disease

You'll want your doctor testing this on you to establish a baseline.

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Parkinson’s Disease May Have Link to Stroke March 2017 

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Night breathing patterns identify people with Parkinson’s disease

At a Glance

• An advanced computer program was able to identify people with Parkinson’s disease from their breathing patterns during sleep.
• The program was able to track small changes in the disease over time, and was more accurate than the tools used regularly by doctors.

The research team collected breathing data during sleep in two ways. Top, an on-body breathing belt. Bottom, a wireless sensor that senses harmless radio signals bounced off the body. Yang et al., Nature Medicine

In Parkinson’s disease, brain cells become damaged or die in the part of the brain that produces dopamine, a chemical needed to produce smooth, purposeful movement. Over time, this damage leads to unintended or uncontrollable movements such as shaking, stiffness, and difficulty with balance and coordination.

Symptoms of Parkinson’s disease usually begin gradually and worsen over time. Currently, there aren’t any markers that can be easily measured in the blood or in imaging tests to diagnose the condition. This has greatly slowed the development of treatments. It also means that people may wait years to get a diagnosis.

NIH-funded researchers led by Dr. Dina Katabi from the Massachusetts Institute of Technology have been testing ways to use artificial intelligence to diagnose Parkinson’s disease.

In a new study, they designed a computer program based on a model of how the brain works (called a neural network) to analyze breathing patterns collected during sleep. The areas of the brain that control breathing and sleep tend to be affected early in the course of Parkinson’s disease. The team tested whether differences in nighttime breathing patterns could be used to distinguish people with the disease from those without.

The researchers used two types of sleep data—breathing patterns and brain activity—to test their program. In the most common test, called a polysomnogram (PSG), people wore a chest belt while they slept to measure breathing patterns. These are often done to help determine why someone is having trouble sleeping. A second group of people participated in tests of a wireless sleep monitoring system. This system bounces radio signals off the body during sleep and uses that information to record breathing patterns without physical contact.

Using sleep breathing data from more than 7,600 people, including 757 with Parkinson’s disease, the team tested their program's ability to diagnose and track Parkinson’s disease in several datasets from multiple hospitals. The results were published on August 22, 2022, in Nature Medicine.

Using a single night of PSG breathing data, the program correctly identified the people with Parkinson’s about 80% of the time. That number rose to 86% when the program used a single night of wireless breathing data. Adding additional nights of wirelessly-collected breathing data increased accuracy. With 12 nights of data, the program’s ability to identify Parkinson’s disease rose to 95%.

In a small group of people who participated in at least two sleep studies, one before they were diagnosed with Parkinson’s disease, the program identified three-quarters of them as having the disease from the data collected before their official diagnosis.

The team also tested the ability of the program to track whether the disease got worse over time. The scales currently used to measure disease progression in the clinic are relatively insensitive. They can also provide different results when used by different doctors. Compared with two different scales, the program was better at identifying small changes in Parkinson’s symptoms.

If these results are confirmed, this program could help in the early detection of Parkinson’s disease and enable shorter clinical trials with fewer participants, accelerating the development of new therapies. More work will be needed to test the program in larger, diverse populations. Katabi points out, “The approach can potentially help in the assessment of Parkinson’s patients in traditionally underserved communities, including those who live in rural areas and those with difficulty leaving home due to limited mobility or cognitive impairment.”

—by Sharon Reynolds