Maximum likelihood estimators for truncated and censored power-law distributions show how neuronal avalanches may be misevaluated.
Phys Rev E Stat Nonlin Soft Matter Phys
; 89(1): 012709, 2014 Jan.
Article
in En
| MEDLINE
| ID: mdl-24580259
ABSTRACT
The coordination of activity amongst populations of neurons in the brain is critical to cognition and behavior. One form of coordinated activity that has been widely studied in recent years is the so-called neuronal avalanche, whereby ongoing bursts of activity follow a power-law distribution. Avalanches that follow a power law are not unique to neuroscience, but arise in a broad range of natural systems, including earthquakes, magnetic fields, biological extinctions, fluid dynamics, and superconductors. Here, we show that common techniques that estimate this distribution fail to take into account important characteristics of the data and may lead to a sizable misestimation of the slope of power laws. We develop an alternative series of maximum likelihood estimators for discrete, continuous, bounded, and censored data. Using numerical simulations, we show that these estimators lead to accurate evaluations of power-law distributions, improving on common approaches. Next, we apply these estimators to recordings of in vitro rat neocortical activity. We show that different estimators lead to marked discrepancies in the evaluation of power-law distributions. These results call into question a broad range of findings that may misestimate the slope of power laws by failing to take into account key aspects of the observed data.
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Collection:
01-internacional
Database:
MEDLINE
Main subject:
Action Potentials
/
Models, Statistical
/
Artifacts
/
Electroencephalography
/
Models, Neurological
/
Nerve Net
/
Neurons
Type of study:
Diagnostic_studies
/
Prognostic_studies
/
Risk_factors_studies
Limits:
Animals
Language:
En
Journal:
Phys Rev E Stat Nonlin Soft Matter Phys
Journal subject:
BIOFISICA
/
FISIOLOGIA
Year:
2014
Document type:
Article