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Barfield, J. H.

Publications and source records attributed to Barfield, J. H..

2 recordsLinked to original sources

When random variation results in functional significance

Many functional properties vary dramatically across neurons in cerebral cortex. Two fundamental goals of systems neuroscience are to determine which neurons execute which functions and how the different functional properties of a neuron are related. Often, it is assumed that if two properties are uncorrelated, then there is no important relationship to report. Here we show that this assumption can lead to wrong conclusions; functional segregation can emerge, by chance, due to random variation when that variation is distributed according to skewed, heavy-tailed distributions. We reinterpret the results we previously reported in Kells et al 2019 [1], showing that they are a prime example of functional segregation due to random variation.

neuroscience↗

Scale-free behavioral dynamics directly linked with scale-free cortical dynamics

Naturally occurring body movements and collective neural activity both exhibit complex dynamics, often with scale-free, fractal spatiotemporal structure. Scale-free dynamics of both brain and behavior are each associated with functional benefits to the organism. Despite their similarities, scale-free brain activity and scale-free behavior have been studied separately, without a unified explanation. Here we show that scale-free dynamics of behavior and certain subsets of cortical neurons are strongly related. Surprisingly, the scale-free neural subsets exhibit stochastic winner-take-all competition with other neural subsets. This observation is inconsistent with current theory of critical phenomena in neural systems. We develop a computational model which incorporates known cell-type-specific circuit structure, explaining our findings with a new type of criticality. Our results establish neural underpinnings of scale-free behavior and clear behavioral relevance of scale-free neural activity. Popular SummaryOver the past 2 decades many measurements of brain activity have revealed a peculiar property; the activity is statistically similar when examined at different scales. This self-similar, fractal nature of brain activity has attracted the interest of neuroscientists and physicists alike. In physics, fractal structure shows up in certain non-living systems when they are operating near the tipping point of a phase transition (e.g. liquid water turning into gaseous vapor). This led to the criticality hypothesis, which posits that the brain may also operate near the tipping point of a phase transition, i.e. near criticality. Initially the criticality hypothesis was very exciting at a basic level - physical principles of phase transitions promised to help us understand how the brain works. However, a important question naturally arose and remains unresolved. What do the scale-free, fractal fluctuations of brain activity have to do with the behavior of the organism? Is it just background noise in the brain or is there something fractal-like about how we behave and interact with the world? Here we show for the first time that scale-free fluctuations of brain activity are directly related to moment-to-moment fluctuations in behavior. In fact, we show that both the brain activity and mouse behavior have very similar fractal structure. These results take the criticality hypothesis to a new level of biological and, perhaps, psychological relevance. Scale-free brain dynamics are not just background noise; they correspond to the dynamics of behavior.

neuroscience↗