Ebner, C. | bioRxiv Science

bioRxiv2025

Tuft dendrites in frontal motor cortex enable flexible learning

Flexible learning relies on integrating sensory and contextual information to adjust behavioral output in different environments. The anterolateral motor cortex (ALM) is a frontal area critical for action selection in rodents. Here we show that inputs critical to decision-making converge on the apical tuft dendrites of L5b pyramidal neurons in ALM. We therefore investigated the role of these dendrites in a rule-switching paradigm. Activation of dendrite-inhibiting layer 1 interneurons impaired relearning, without affecting previously learned behavior. Remarkably, this inhibition profoundly suppressed calcium activity selectively in dendritic shafts but not spines while reducing burst firing. Moreover, excitatory synaptic inputs to tuft dendrites exhibited rule-dependent clustering. We conclude that active dendritic integration is a key computational component of flexible learning.

neuroscience↗

bioRxiv2024

Multi-scale modelling of location- and frequency-dependent synaptic plasticity induced by transcranial magnetic stimulation in the dendrites of pyramidal neurons

BackgroundRepetitive transcranial magnetic stimulation (rTMS) induces long-term changes of synapses, but the mechanisms behind these modifications are not fully understood. Al- though there has been progress in the development of multi-scale modeling tools, no com- prehensive module for simulating rTMS-induced synaptic plasticity in biophysically realistic neurons exists.. ObjectiveWe developed a modelling framework that allows the replication and detailed prediction of long-term changes of excitatory synapses in neurons stimulated by rTMS. MethodsWe implemented a voltage-dependent plasticity model that has been previously established for simulating frequency-, time-, and compartment-dependent spatio-temporal changes of excitatory synapses in neuronal dendrites. The plasticity model can be incorporated into biophysical neuronal models and coupled to electrical field simulations. ResultsWe show that the plasticity modelling framework replicates long-term potentiation (LTP)-like plasticity in hippocampal CA1 pyramidal cells evoked by 10-Hz repetitive magnetic stimulation (rMS). This plasticity was strongly distance dependent and concentrated at the proximal synapses of the neuron. We predicted a decrease in the plasticity amplitude for 5 Hz and 1 Hz protocols with decreasing frequency. Finally, we successfully modelled plasticity in distal synapses upon local electrical theta-burst stimulation (TBS) and predicted proximal and distal plasticity for rMS TBS. Notably, the rMS TBS-evoked synaptic plasticity exhibited robust facilitation by dendritic spikes and low sensitivity to inhibitory suppression. ConclusionThe plasticity modelling framework enables precise simulations of LTP-like cellular effects with high spatio-temporal resolution, enhancing the efficiency of parameter screening and the development of plasticity-inducing rTMS protocols. HighlightsO_LIFirst rigorously validated model of TMS-induced long-term synaptic plasticity in ex- tended neuronal dendrites that goes beyond point-neuron and mean-field modelling C_LIO_LIRobust simulations of experimental data on LTP-like plasticity in the proximal dendrites of CA1 hippocampal pyramidal cells evoked by 10 Hz repetitive magnetic stimulation (rMS) C_LIO_LIReplication of distal synaptic plasticity for a local electrical theta burst stimulation (TBS) protocol C_LIO_LIPrediction of distal and proximal LTP-like plasticity for rMS TBS C_LIO_LI1 Hz rMS does not induce long-term depression C_LI

neuroscience↗