Resolving inconsistent effects of tDCS on learning using a homeostatic structural plasticity model

Han Lu^1,2,3,4Lukas Frase⁵Claus Normann^6,7Stefan Rotter^1,2*

• ¹Bernstein Center Freiburg, University of Freiburg, Freiburg im Breisgau, Germany
• ²Faculty of Biology, University of Freiburg, Freiburg, Germany
• ³Institut des Neurosciences Cellulaires et Intégratives, Faculté des Sciences de la Vie, Université de Strasbourg, Strasbourg, Alsace, France
• ⁴Jülich Supercomputing Center, Institute for Advanced Simulation, Julich Research Center, Helmholtz Association of German Research Centers (HZ), Jülich, North Rhine-Westphalia, Germany
• ⁵Clinic for Psychosomatic Medicine and Psychotherapy, Center for Mental Health, Faculty of Medicine, University of Freiburg, Freiburg, Germany
• ⁶Department of Psychiatry and Psychotherapy, University of Freiburg Medical Center, Freiburg, Germany
• ⁷Center for Basics in Neuromodulation, Faculty of Medicine, University of Freiburg, Freiburg, Germany

Transcranial direct current stimulation (tDCS) is increasingly used to modulate motor learning. Current polarity and intensity, electrode montage, and application before or during learning had mixed effects. Both Hebbian and homeostatic plasticity were proposed to account for the observed effects, but the explanatory power of these models is limited. In a previous modeling study, we showed that homeostatic structural plasticity (HSP) can explain long-lasting after-effects of tDCS and transcranial magnetic stimulation (TMS). The interference between motor learning and tDCS, which are both based on HSP in our model, is a candidate mechanism to resolve complex and seemingly contradictory experimental observations. We implemented motor learning and tDCS in a spiking neural network subject to HSP. The anatomical connectivity of the engram induced by motor learning was used to quantify the impact of tDCS on motor learning. Our modeling results demonstrated that transcranial direct current stimulation applied before learning had weak modulatory effects. It led to a small reduction in connectivity if it was applied uniformly. When applied during learning, targeted anodal stimulation significantly strengthened the engram, while targeted cathodal or uniform stimulation weakened it. Applied after learning, targeted cathodal, but not anodal, tDCS boosted engram connectivity.Strong tDCS would distort the engram structure if not applied in a targeted manner. Our model explained both Hebbian and homeostatic phenomena observed in human tDCS experiments by assuming memory strength positively correlates with engram connectivity. This includes applications with different polarity, intensity, electrode montage, and timing relative to motor learning. The HSP model provides a promising framework for unraveling the dynamic interaction between learning and transcranial DC stimulation.