Researchers found that shared neuronal noise slows information growth but does not impose a definitive limit on how much visual data the brain can process.
Key facts
- •The study analyzed between 18,000 and 21,000 neurons from the primary visual cortex of five mice.
- •Researchers identified two power laws that remain consistent regardless of population size.
- •The findings challenge the long-held expectation that shared neural fluctuations cause information to saturate.
- •The results were published in the journal Science Advances.
- •The study's theoretical framework may assist in the design of noisy computing systems.
An international research team has determined that the brain's ability to process visual information does not necessarily reach a ceiling due to shared neuronal noise. By analyzing recordings from the primary visual cortex of mice, the study suggests that adding more neurons continues to improve information capacity even when signals fluctuate together.
Analyzing Neuronal Variability
Researchers from Kyoto University, Harvard University, and the University of California, Los Angeles, examined recordings of approximately 18,000 to 21,000 neurons from each of five mice. As the mice viewed visual stimuli, the team measured how information scaled as they included increasingly large groups of neurons in their analysis.
Scaling Laws and Information Growth
The team identified two power laws that describe the distribution of noise strengths and how noise patterns align with signals. These laws indicate that while stronger noise components can align with signals, the brain also utilizes less variable activity patterns to convey information. Consequently, shared noise slows the rate at which information grows as more neurons are added, but it does not stop the process entirely.
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This article was independently rewritten by ManyPress editorial AI from reporting originally published by Medical Xpress.
