June 18, 2021


by: admin


Tags: Autism, captures, model, mouse, network, Neural, neurons, noisy, Spectrum


Categories: autism

Neural community captures noisy neurons in autism mouse mannequin | Spectrum

Mice lacking the autism-related SHANK3 gene use more neurons to engage in social behavior than control mice, reflecting a more disorganized, less efficient signaling network in the brain, according to a new study.

Mutations in SHANK3 occur in 1 to 2 percent of autistic people and can also lead to a related disorder called Phelan-McDermid syndrome. The gene codes for a protein that, among other things, supports a receptor for glutamate, an exciting chemical messenger substance that stimulates neurons to fire. Experts suggest that autism characteristics are based on an imbalance between excitatory and inhibitory signals.

In the new study, scientists monitored the brain activity of free-moving mice to determine which groups of neurons or ensembles were activated during social behavior. Mice lacking a copy of SHANK3 had more neural ensembles that were activated together compared to control mice, as shown by neural network analysis. But the ensembles did not necessarily work together: the SHANK3 mice overlapped rather by chance, whereby neural ensembles that are not involved in social behavior also became active.

The results suggest that SHANK3 mutations disrupt the signal-to-noise ratio in the social brain network, says lead researcher Vikaas Sohal, associate professor of psychiatry and behavioral science at the University of California, San Francisco.

“This study is about a very important topic in neuroscience that we just don’t know much about, which is how the brain represents social information,” said Alex Kwan, an adjunct professor of psychiatry and neuroscience at Yale University who is not at The study involved new work. “[It] offers some progress towards this understanding. “

Ensemble cast:

Sohal and his team recorded the activity of neural ensembles in mice both in their home cage and in the presence of an unknown young mouse using miniature microscopes that were implanted in the animals’ prefrontal cortex. The microscopes detect the influx of calcium ions into neurons that occurs when the cells fire.

Characteristic patterns of activity emerged in control mice: some ensembles became more synchronized as soon as a new mouse appeared, while others less so.

The team fed this data into a series of algorithms to simulate the response of downstream neurons – the ones that could translate prefrontal cortex activity into behavior. And they commissioned this neural network to classify the behavior of the animal as social or non-social based solely on the activity of the neural ensembles.

“This allows them to isolate the neuron ensembles that are most telling about the state of the mouse,” says Ofer Yizhar, professor of neuroscience at the Weizmann Institute of Science in Rehovot, Israel, who was not involved in the study. “This is a really interesting approach because it creates a kind of brain-computer hybrid that allows them to precisely characterize the information that the recorded neurons could provide to the neurons in the mouse brain that“ listen ”to them. ”

SHANK3 mice spent significantly less time interacting with unknown mice than their wild-type littermates, the team found. And their neural ensembles were more active but less informative about whether or not the mice were in a social situation, as the neural network showed.

The results were published in PLOS Biology in May.

Unknown players:

The results seem to suggest that “the cortical network in these mice is less efficient at transmitting the information they need,” says Yizhar. And that’s in line with a 2019 study by Yizhar’s team that showed that social deficits in mice lacking the autism-related gene CNTNAP2 are accompanied by excessive noise in the prefrontal cortex.

Even so, calcium signal recordings don’t illuminate the full extent of brain activity that occurs during social interactions, says Yizhar. They show which neural ensembles are active and when, but they lack the sensitivity to uncover the activity of individual neurons.

And while the study combines a cutting-edge technical approach with a novel analytical technique, it also raises new questions, says Kwan. The imaging process does not include the cells that receive a signal during social interactions, only those that send it.

“What is the nature of these cells?” says Kwan. “What is the downstream region that is reading this information and actually performing this behavior?”

The team plans to answer these questions by mapping multiple brain regions at once, says co-researcher Nicholas Frost, assistant professor of neurology at the University of Utah in Salt Lake City.

His team has also started studying how different neural ensembles are recruited during social behavior compared to fear-related behaviors in mice.


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