Physicists at Washington University in St. Louis researching the brain have demonstrated that monitoring signals from a single neuron may be as effective as gathering information from numerous neurons at once using large, expensive arrays of electrodes.
A key topic in neuroscience is what information single neurons get about overall brain network activity. For years, researchers in the laboratory of Ralf Wessel, professor of physics at Arts & Sciences, have used modern neurotechnology and physics-inspired data analysis to investigate sensory information processing in the brain.
“We know that in critical systems you can zoom in or out really far, and get the same statistical patterns. This property is called scale-freeness — or fractalness — and criticality may explain the origins of widely observed fractal activity in the brain,” said James K. Johnson, first author of the paper and a graduate student in the Wessel laboratory.
The researchers sought to zoom all the way down for their new experiment. They explained that evidence for criticality has been found at all greater scales. “The scale of the single cell was the last frontier,” Johnson said. “We cheated a bit, though. The statistical patterns used to evince criticality in the brain are called neuronal avalanches. Essentially, it’s just a spurt of ‘spiking,’ or messaging between neurons.”
“We cannot know if two randomly selected neurons are directly connected — and (even) if we could, spiking between those two is so rare that we would need hours of recordings from those two neurons,” Johnson said. “So instead, we ignored spiking and looked to see what neuronal avalanches look like from the neuron’s perspective.”
Single-cell recordings have been around for at least 70 years, but they have been surpassed by novel methods of recording numerous neurons at once. A previously utilized approach for recording electrochemical input variations from within a single neuron was upgraded and perfected by Washington University researchers.
“When our cell receives inputs, it looks like ‘blips’ or ‘piles of blips’ in our recordings,” Johnson said. “Usually, the neuroscience community focuses on the average value or some summative measure, and fluctuations are often modeled as pure noise. We did something new. We did the same statistical analysis on the precise geometry of the ‘blips’ that one normally does on neuronal avalanches when testing for criticality.”
When subjected to an intensive battery of tests, the single-cell data gathered by the researchers was nearly as consistent with systems at their critical point as data from huge arrays. “Being at the critical point offers many advantages for information transmission and processing that may underlie the resilience, adaptability and variability of brain function,” Johnson said.
Single-Cell Membrane Potential Fluctuations Evince Network Scale-Freeness and Quasicriticality, James K. Johnson, Nathaniel C. Wright, Jì Xià and Ralf Wessel
Published: June 2019