Posted on by Dr. Francis Collins
Getting plenty of deep, restful sleep is essential for our physical and mental health. Now comes word of yet another way that sleep is good for us: it triggers rhythmic waves of blood and cerebrospinal fluid (CSF) that appear to function much like a washing machine’s rinse cycle, which may help to clear the brain of toxic waste on a regular basis.
The video above uses functional magnetic resonance imaging (fMRI) to take you inside a person’s brain to see this newly discovered rinse cycle in action. First, you see a wave of blood flow (red, yellow) that’s closely tied to an underlying slow-wave of electrical activity (not visible). As the blood recedes, CSF (blue) increases and then drops back again. Then, the cycle—lasting about 20 seconds—starts over again.
The findings, published recently in the journal Science, are the first to suggest that the brain’s well-known ebb and flow of blood and electrical activity during sleep may also trigger cleansing waves of blood and CSF. While the experiments were conducted in healthy adults, further study of this phenomenon may help explain why poor sleep or loss of sleep has previously been associated with the spread of toxic proteins and worsening memory loss in people with Alzheimer’s disease.
In the new study, Laura Lewis, Boston University, MA, and her colleagues at the Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston. recorded the electrical activity and took fMRI images of the brains of 13 young, healthy adults as they slept. The NIH-funded team also built a computer model to learn more about the fluid dynamics of what goes on in the brain during sleep. And, as it turns out, their sophisticated model predicted exactly what they observed in the brains of living humans: slow waves of electrical activity followed by alternating waves of blood and CSF.
Lewis says her team is now working to come up with even better ways to capture CSF flow in the brain during sleep. Currently, people who volunteer for such experiments have to be able to fall asleep while wearing an electroencephalogram (EEG) cap inside of a noisy MRI machine—no easy feat. The researchers are also recruiting older adults to begin exploring how age-related changes in brain activity during sleep may affect the associated fluid dynamics.
 Coupled electrophysiological, hemodynamic, and cerebrospinal fluid oscillations in human sleep. Fultz NE, Bonmassar G, Setsompop K, Stickgold RA, Rosen BR, Polimeni JR, Lewis LD. Science. 2019 Nov 1;366(6465):628-631.
Sleep and Memory (National Institute of Mental Health/NIH)
Sleep Deprivation and Deficiency (National Heart, Lung, and Blood Institute/NIH)
Alzheimer’s Disease and Related Dementias (National Institute on Aging/NIH)
NIH Support: National Institute of Mental Health; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke
Posted on by Dr. Francis Collins
Can you identify a familiar pattern in this image’s square grid? Yes, it’s the outline of the periodic table! But instead of organizing chemical elements, this periodic table sorts 46 different types of neurons present in the visual cortex of a mouse brain.
Scientists, led by Hongkui Zeng at the Allen Institute for Brain Science, Seattle, constructed this periodic table by assigning colors to their neuronal discoveries based upon their main cell functions . Cells in pinks, violets, reds, and oranges have inhibitory electrical activity, while those in greens and blues have excitatory electrical activity.
For any given cell, the darker colors indicate dendrites, which receive signals from other neurons. The lighter colors indicate axons, which transmit signals. Examples of electrical properties—the number and intensity of their “spikes”—appear along the edges of the table near the bottom.
To create this visually arresting image, Zeng’s NIH-supported team injected dye-containing probes into neurons. The probes are engineered to carry genes that make certain types of neurons glow bright colors under the microscope.
This allowed the researchers to examine a tiny slice of brain tissue and view each colored neuron’s shape, as well as measure its electrical response. They followed up with computational tools to combine these two characteristics and classify cell types based on their shape and electrical activity. Zeng’s team could then sort the cells into clusters using a computer algorithm to avoid potential human bias from visually interpreting the data.
Why compile such a detailed atlas of neuronal subtypes? Although scientists have been surveying cells since the invention of the microscope centuries ago, there is still no consensus on what a “cell type” is. Large, rich datasets like this atlas contain massive amounts of information to characterize individual cells well beyond their appearance under a microscope, helping to explain factors that make cells similar or dissimilar. Those differences may not be apparent to the naked eye.
Just last year, Allen Institute researchers conducted similar work by categorizing nearly 24,000 cells from the brain’s visual and motor cortex into different types based upon their gene activity . The latest research lines up well with the cell subclasses and types categorized in the previous gene-activity work. As a result, the scientists have more evidence that each of the 46 cell types is actually distinct from the others and likely drives a particular function within the visual cortex.
Publicly available resources, like this database of cell types, fuel much more discovery. Scientists all over the world can look at this table (and soon, more atlases from other parts of the brain) to see where a cell type fits into a region of interest and how it might behave in a range of brain conditions.
 Classification of electrophysiological and morphological neuron types in the mouse visual cortex. N Gouwens NW, et al. Neurosci. 2019 Jul;22(7):1182-1195.
 Shared and distinct transcriptomic cell types across neocortical areas. Tasic B, et al. Nature. 2018 Nov;563(7729):72-78.
Brain Basics: The Life and Death of a Neuron (National Institute of Neurological Disorders and Stroke/NIH)
Cell Types: Overview of the Data (Allen Brain Atlas/Allen Institute for Brain Science, Seattle)
Hongkui Zeng (Allen Institute)
NIH Support: National Institute of Mental Health; Eunice Kennedy Shriver National Institute of Child Health & Human Development