Coexistence of critical sensitivity and subcritical specificity can yield optimal population coding

Abstract

The vicinity of phase transitions selectively amplifies weak stimuli, yielding optimal sensitivity to distinguish external input. Along with this enhanced sensitivity, enhanced levels of fluctuations at criticality reduce the specificity of the response. Given that the specificity of the response is largely compromised when the sensitivity is maximal, the overall benefit of criticality for signal processing remains questionable. Here it is shown that this impasse can be solved by heterogeneous systems incorporating functional diversity, in which critical and subcritical components coexist. The subnetwork of critical elements has optimal sensitivity, and the subnetwork of subcritical elements has enhanced specificity. Combining segregated features extracted from the different subgroups, the resulting collective response can maximise the tradeoff between sensitivity and specificity measured by the dynamic-range-to-noise-ratio. Although numerous benefits can be observed when the entire system is critical, our results highlight that optimal performance is obtained when only a small subset of the system is at criticality.

arXiv comment7 pages, 4 figures

References in corpus (19)

• Emergent complex neural dynamics
• Scale-free correlations in bird flocks
• Optimal Dynamical Range of Excitable Networks at Criticality
• Are biological systems poised at criticality?
• Essential nonlinearities in hearing
• Auditory Sensitivity Provided by Self-tuned Critical Oscillations of Hair Cells
• Critical brain networks
• Diversity-induced resonance
• Inhibition causes ceaseless dynamics in networks of excitable nodes
• Quasi-Critical Brain Dynamics on a Non-Equilibrium Widom Line
• Active dendrites enhance neuronal dynamic range
• Stochastic resonance and optimal information transfer at criticality on a network model of the human connectome
• Emergent global oscillations in heterogeneous excitable media: The example of pancreatic beta cells
• Self-organized criticality in single neuron excitability
• Single-Neuron Criticality Optimizes Analog Dendritic Computation
• Statistical Physics approach to dendritic computation: The excitable-wave mean-field approximation
• Signal integration enhances the dynamic range in neuronal systems
• Diversity improves performance in excitable networks
• Optimal Channel Efficiency in a Sensory Network

Cited by in corpus (7)

• Criticality in the brain: A synthesis of neurobiology, models and cognition
• Between perfectly critical and fully irregular: a reverberating model captures and predicts cortical spike propagation
• Self-organization toward criticality by synaptic plasticity
• Dynamic Adaptive Computation: Tuning network states to task requirements
• Tracking the distance to criticality in systems with unknown noise
• Discrete scaling and criticality in a chain of adaptive excitable integrators
• 25 years of criticality in neuroscience -- established results, open controversies, novel concepts