RT Journal Article SR Electronic T1 Neuronal networks quantified as vector fields JF bioRxiv FD Cold Spring Harbor Laboratory SP 2024.06.29.601314 DO 10.1101/2024.06.29.601314 A1 Szeier, Szilvia A1 Jörntell, Henrik YR 2024 UL http://biorxiv.org/content/early/2024/07/02/2024.06.29.601314.abstract AB Brain function is defined by the interactions between the neurons of the brain. But these neurons exist in tremendous numbers, are continuously active and densely interconnected. Thereby they form one of the most complex dynamical systems known and there is a lack of approaches to characterize the functional properties of such biological neuronal networks. Here we introduce an approach to describe these functional properties by using its constituents, the weights of the synaptic connections and the current activity of its neurons. We show how a high-dimensional vector field, which describes how the activity of each individual neuron is impacted at each instant of time, naturally emerges from these constituents. We show the factors that impact the structural richness of that vector field, including how rapid changes in neuron activity continually reshapes its structure. We argue that this structural richness is the foundation of the functional diversity and thereby the adaptability that characterizes biological behavior.Competing Interest StatementThe authors have declared no competing interest.