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Updated: Jul 25, 2025

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
Published on: May 8, 2021
Control systems theory revisited: new insights on the brain clocks of time-to-action
Sari Goldstein Ferber1,2, Aron Weller1, Hermona Soreq3
1Department of Psychology, Gonda Brain Research Center, Bar-Ilan University, Ramat Gan, Israel.
Abstract:
To outline the complex biological rhythms underlying the time-to-action of goal-oriented behavior in the adult brain, we employed a Boolean Algebra model based on Control Systems Theory. This suggested that "timers" of the brain reflect a metabolic excitation-inhibition balance and that healthy clocks underlying goal-oriented behavior (optimal range of signal variability) are maintained by XOR logic gates in parallel sequences between cerebral levels. Using truth tables, we found that XOR logic gates reflect healthy, regulated time-to-action events between levels. We argue that the brain clocks of time-to-action are active within multileveled, parallel-sequence complexes shaped by experience. We show the metabolic components of time-to-action in levels ranging from the atom level through molecular, cellular, network and inter-regional levels, operating as parallel sequences. We employ a thermodynamic perspective, suggest that clock genes calculate free energy versus entropy and derived time-to-action level-wise as a master controller, and show that they are receivers, as well as transmitters of information. We argue that regulated multileveled time-to-action processes correspond to Boltzmann's thermodynamic theorem of micro- and macro-states, and that the available metabolic free-energy-entropy matrix determines the brain's reversible states for its age-appropriate chrono-properties at given moments. Thus, healthy timescales are not a precise number of nano- or milliseconds of activity nor a simple phenotypic distinction between slow vs. quick time-to-action, but rather encompass a range of variability, which depends on the molecules' size and dynamics with the composition of receptors, protein and RNA isoforms.
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