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Environmental Factor

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June 2018

NIEHS scientists develop new technique to study brain disease

A new tool developed by NIEHS researchers has determined, for the first time, how two distinct sets of neurons in the mouse brain work together to control movement. The scientists plan to use the technique to better understand what goes wrong in neurological disorders such as Parkinson’s disease (PD).

The method, which is called spectrally resolved fiber photometry (SRFP), can be used to measure the activity of two neuron groups in healthy mice and in mice with brain disease. The study appeared online May 3 in the journal Neuron.

Tool to study movement disorders

Guohong Cui "We developed the tool, not only for the questions we’re interested in, but for the broader neuroscience community," Cui said. (Photo courtesy of Steve McCaw)

According to Guohong Cui, M.D., Ph.D., head of the NIEHS In Vivo Neurobiology Group, the project began because he wanted to find out why patients with PD have problems with movement. Typically, PD motor symptoms include tremor, muscle stiffness, slowness of movement, and impaired balance.

Cui explained that an animal’s ability to move was controlled by two groups of neurons in the brain, the direct pathway (D1) and the indirect pathway (D2). Based on clinical studies of patients with PD and primate models, some researchers hypothesized that the loss of the neurotransmitter dopamine in the midbrain resulted in an imbalance of neural activities between D1 and D2. Because previous methods could not effectively distinguish different cell types in the brain, the hypothesis remained under debate. However, using SRFP, Cui’s team was able to label D1 and D2 neurons with green and red fluorescent sensors to report their neural activity.

Chengbo Meng Meng said the new technique uses optical signals, using photons for color that make the cells fluoresce. (Photo courtesy of Steve McCaw)

"Our method allowed us to simultaneously measure neural activity of both pathways in a mouse as the animal performed tasks," Cui said. "In the future, we could potentially use SRFP to measure the activity of several cell populations utilizing various colors and sensors."

Mouse movements

With SRFP, Cui and colleagues found that when neural activity in D1 neurons is stronger than that in D2 neurons, the animal does a start and go, which means it starts and moves to another location. However, when the activity of D2 neurons is stronger than that of D1 neurons, the mouse does a start and stop, meaning it initiates a movement, but stops immediately.

Cui said both movements are normal for mice and analyzing them may help researchers predict what kind of movement the animal will make based on its neural activity. This advance may help explain what happens in the brains of mice with PD.

Two of Cui’s team members, NIEHS Visiting Fellows Chengbo Meng, Ph.D., and Jingheng Zhou, Ph.D., share first-authorship of the Neuron article.

Jingheng Zhou As a member of Cui’s group, Zhou monitors and manipulates cellular events in rodent neurons. (Photo courtesy of Steve McCaw)

"The traditional method of electrophysiological recording is good when you want to measure electrical outputs of neurons, but it cannot tell you what type of neurons are generating those signals," Meng said. "SRFP is more specific, because we can distinguish between groups of neurons and see their activity."

Although Cui’s group is mainly interested in understanding PD, Zhou said SRFP will help researchers studying other brain conditions, such as Alzheimer’s disease, stroke, multiple sclerosis, and addiction.

CitationMeng C, Zhou J, Papaneri A, Peddada T, Xu K, Cui G. 2018. Spectrally resolved fiber photometry for multi-component analysis of brain circuits. Neuron 98(4):707–717.e4.


D1 red neurons and D2 green neurons controlling movement

The striatum, part of the brain’s basal ganglia, is involved in movement control. Using the SRFP technique, Cui’s team found that different activity patterns in the D1, red, and the D2, green, pathways led to different types of movement. (Photo courtesy of Guohong Cui)

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