The energy scale of thermal fluctuations at ambient conditions are comparable to the constituent interaction energies that stabilize macromolecular structures. Therefore, thermal noise is a fundamental bottleneck to achieving functional efficiency and structural stability. We’ve recently shown that intramolecular correlations in timing allows proteins to exceed this thermodynamic communication limit, explaining how long-range intra-protein communication can occur without measureable conformational change. We devised a new function, called the conditional activity, which measures the correlations in timing between events, which is applicable for systems that are non-Markovian (i.e. history-dependent). In addition to proteins, we are applying this methodology to find collective dynamical modes in gene regulatory and neural networks that are not captured by existing structural correlation functions such as the mutual information.