Network remodeling induced by transcranial brain stimulation: A computational model of tDCS-triggered cell assembly formation

Abstract

Transcranial direct current stimulation (tDCS) is a variant of non-invasive neuromodulation, which promises treatment for brain diseases like major depressive disorder. In experiments, long-lasting aftereffects were observed, suggesting that persistent plastic changes are induced. The mechanism underlying the emergence of lasting aftereffects, however, remains elusive. Here we propose a model, which assumes that tDCS triggers a homeostatic response of the network involving growth and decay of synapses. The cortical tissue exposed to tDCS is conceived as a recurrent network of excitatory and inhibitory neurons, with synapses subject to homeostatically regulated structural plasticity. We systematically tested various aspects of stimulation, including electrode size and montage, as well as stimulation intensity and duration. Our results suggest that transcranial stimulation perturbs the homeostatic equilibrium and leads to a pronounced growth response of the network. The stimulated population eventually eliminates excitatory synapses with the unstimulated population, and new synapses among stimulated neurons are grown to form a cell assembly. Strong focal stimulation tends to enhance the connectivity within new cell assemblies, and repetitive stimulation with well-chosen duty cycles can increase the impact of stimulation even further. One long-term goal of our work is to help optimizing the use of tDCS in clinical applications.

Time course of homeostatic structural plasticity in response to optogenetic stimulation in mouse anterior cingulate cortex

“…In experiments, transcranial direct current stimulation (tDCS) (Reato et al, 2013) and optogenetic stimulation (Cardin et al, 2010;Barthas et al, 2015) are often employed to perturb neural network activity and induce synaptic plasticity. We showed in another recent simulation study that the long-lasting after-effects of tDCS could be explained by homeostatic structural plasticity (Lu et al, 2019). In our present experimental study, we evaluated the time course of synaptic connectivity changes driven by optogenetic stimulation in mice.…”

“…We used the same neuron model, synapse model, and network architecture, as published in our previous paper on transcranial electric stimulation (Lu et al, 2019). All the plastic neuronal network simulations of the current study were performed with the NEST simulator using a MPI-based parallel configuration (Linssen et al, 2018).…”

“…All connections involving inhibitory neurons in this network were established randomly with 10% connection probability and then kept fixed. Only excitatory to excitatory (E-E) connections were subject to homeostatic structural plasticity (HSP) (Gallinaro and Rotter, 2018;Lu et al, 2019). Each excitatory neuron monitors its own firing rate using its intracellular calcium concentration and grows or retracts its spines and boutons to form or break synapses ( Figure 1A, see Supplementary Materials for details).…”

Homeostatic control of synaptic rewiring in recurrent networks induces the formation of stable memory engrams

“…Concerning the interplay between Hebbian and homeostatic plasticity, we have recently demonstrated by simulations that homeostatic structural plasticity alone can lead to the formation of assemblies of strongly interconnected neurons, and that this process of memory formation has associative properties [12]. Moreover, we found that varying the strength of the stimulation and the fraction of stimulated neurons in combination with repetitive protocols can lead to even stronger assemblies [32]. In both papers, we used a structural plasticity model based on firing rate homeostasis, which had been used before to study synaptic rewiring linked with neurogenesis [6,7], and the role of structural plasticity after focal stroke [3,5] and after retinal lesion [2].…”

“…The baseline period is followed by an encoding period, in which C1 is paired with US, while C2 is always presented in isolation. Simultaneous stimulation of neurons in a recurrent network with homeostatic structural plasticity can lead to the formation of reinforced ensembles [12], which are strengthened by repetitive stimulation [32]. After the encoding period, each of the three neuronal ensembles has increased within-ensemble connectivity, as compared to baseline.…”