To form the light beads, Vaziri and his colleagues created a special mirror-lined cavity. When a pulse of light enters the cavity, it bounces around until it hits a partially reflective mirror: Some of the light passes through the mirror toward a microscope, while the rest is reflected back into the cavity for another round trip. Each trip shifts the beam’s focus to a slightly shallower depth and delays the beam by a few nanoseconds. Researchers can then assign fluorescence detected at different points in time to specific spots in the brain.
The team tested the technique by imaging the brains of awake mice whose neurons express a protein that fluoresces in the presence of calcium. They placed the mice on a treadmill and fixed the animals’ heads in place. In one experiment, the researchers recorded neurons firing in both brain hemispheres. In another test, they recorded from one hemisphere as the mouse was exposed to repeated stimuli, such as brushing the whiskers or presenting a moving image of black and white lines. The team also recorded movements in the animals’ limbs.
When tracking one hemisphere, the team captured more than 200,000 neurons firing in different brain regions. By analyzing correlations between the timing of neuronal activity and the onset of stimuli or movements, the researchers also identified groups of neurons tuned to distinct stimuli or spontaneous behavior.
As expected, neurons within brain regions known to be involved in processing sensory or visual information responded to whisker or visual stimulation, the researchers reported. More surprising was that neurons in many other cortical regions also lit up in response to these stimuli. And when whisker and visual stimulation were combined, the additional stimulus modulated the activity of some neurons tuned to the other stimulus. Individual neurons’ firing patterns also varied with each presentation of the stimuli.
These results highlight the importance of capturing wide-ranging brain activity at high speed to help untangle the complexity of neural networks, the researchers say.
Cite this article: https://doi.org/10.53053/MANL1452