The log-dynamic brain: how skewed distributions affect network operations György Buzsáki and Kenji Mizuseki review the role of skewed, lognormal distributions in brain function. They argue that many brain parameters, such as synaptic weights, firing rates, and population synchrony, follow skewed distributions rather than normal ones. This has implications for data collection and analysis, and may help explain how different levels of brain organization are related. The authors discuss how skewed distributions arise from multiplicative and synergistic interactions in biological systems, and how they affect network operations at various levels, from synapses to cognition. They also explore how lognormal distributions are observed in brain activity, such as in the power and frequency relationships of local field potentials, and how they relate to synaptic strength and firing rates. The review highlights the importance of lognormal distributions in understanding brain function, and suggests that future research should focus on quantifying these distributions to better understand brain dynamics and plasticity.The log-dynamic brain: how skewed distributions affect network operations György Buzsáki and Kenji Mizuseki review the role of skewed, lognormal distributions in brain function. They argue that many brain parameters, such as synaptic weights, firing rates, and population synchrony, follow skewed distributions rather than normal ones. This has implications for data collection and analysis, and may help explain how different levels of brain organization are related. The authors discuss how skewed distributions arise from multiplicative and synergistic interactions in biological systems, and how they affect network operations at various levels, from synapses to cognition. They also explore how lognormal distributions are observed in brain activity, such as in the power and frequency relationships of local field potentials, and how they relate to synaptic strength and firing rates. The review highlights the importance of lognormal distributions in understanding brain function, and suggests that future research should focus on quantifying these distributions to better understand brain dynamics and plasticity.