Charged Interfaces in the Brain: How Electrostatic Forces May Guide Cerebrospinal Fluid Dynamics

Cerebrospinal fluid (CSF) flows play a main role in maintaining brain homeostasis, supporting waste clearance, nutrient delivery, and interstitial solute exchange. Although current models emphasize mechanical drivers like cardiac pulsation, respiration, and ciliary motion, these mechanisms alone fall short of explaining the nuanced spatiotemporal regulation of CSF flow observed under physiological and pathological conditions—even when accounting for the glymphatic framework. We hypothesize that electrostatic forces arising from charged cellular interfaces may contribute to CSF movement through electro‐osmotic mechanisms. We begin by examining the biological basis for surface charge in the brain, highlighting the presence of charged glycoproteins, ion channels, and dynamic membrane potentials on ependymal/glial cells interfacing directly with CSF pathways. Next, we describe key electro‐osmotic principles in confined geometries, emphasizing how nanoscale surface charges can modulate fluid motion without mechanical input. Drawing from nanofluidic research, biophysics, and electrohydrodynamic theory, we argue that the conditions required for electro‐osmotic coupling, i.e., ionic fluid, narrow conduits, and patterned surface charge, are present within brain microenvironments. To test plausibility, we present computational simulations demonstrating that surface charge patterns alone can induce structured fluid flow/solute transport, including nonlinear transitions and oscillatory behaviors that resemble physiological rhythms. These findings support the idea that electrostatics may play a modulatory role in CSF regulation, complementing mechanical drivers. By integrating different disciplines, we propose a testable, mechanistically grounded hypothesis reframing CSF dynamics as electrohydrodynamically sensitive processes. Our approach could inspire novel diagnostics/therapeutic strategies in hydrocephalus and neurodegenerative disease and inform the design of targeted drug delivery systems.