Mesoscale cortical calcium activity correlating with single cortical and thalamic cell spiking reveal rich dynamics and support a novel approach for investigating in vivo functional networks in the mammalian brain.

Multivariate data decomposition applied to local field potentials recorded from the primate amygdala revealed simultaneously active and functionally distinct networks, defined by anatomical boundaries between the nuclei.

Large-scale electrocorticography and big data analysis of brain-wide neuronal interactions reveal the architecture of network information flow for context processing in primate brain.

Naturalistic animal behavior exhibits a complex organization in the temporal domain, whose variability stems from hierarchical, contextual, and stochastic sources and can be naturally explained in terms of metastable attractor models.

Short-ranged and random connectivity are sufficient to explain complex, long-range activity patterns observed in macaque motor cortex that are, moreover, flexibly adaptable to behavior.

Mesoscopic properties of motor-microtubule assemblies, such as contractile rates and length scales, can be quantitatively connected to single-motor properties of kinesin motors.

A realistic model of the connections between local populations of neurons in the adult mouse brain can be constructed based on just two biologically plausible rules.

Dynamical properties of liquid condensates can be quantitatively assessed by combining phase separation theory and photobleaching, which opens new avenues to understand their physicochemical properties and functioning.

Experiments in macaques and humans reveal time-varying changes in prefrontal cortex activity that occur during decisions based on costs and benefits.

Direct estimation of the Hurst exponent shows that endosomes and lysosomes reside in regimes of persistent and anti-persistent motion with heavy-tailed residence time distributions and motion correlated with endocytic function.