Basal Ganglia Neuromodulation Over Multiple Temporal and Structural Scales—Simulations of Direct Pathway MSNs Investigate the Fast Onset of Dopaminergic Effects and Predict the Role of Kv4.2

Abstract

The basal ganglia are involved in the motivational and habitual control of motor and cognitive behaviors. Striatum, the largest basal ganglia input stage, integrates cortical and thalamic inputs in functionally segregated cortico-basal ganglia-thalamic loops, and in addition the basal ganglia output nuclei control targets in the brainstem. Striatal function depends on the balance between the direct pathway medium spiny neurons (D1-MSNs) that express D1 dopamine receptors and the indirect pathway MSNs that express D2 dopamine receptors. The striatal microstructure is also divided into striosomes and matrix compartments, based on the differential expression of several proteins. Dopaminergic afferents from the midbrain and local cholinergic interneurons play crucial roles for basal ganglia function, and striatal signaling via the striosomes in turn regulates the midbrain dopaminergic system directly and via the lateral habenula. Consequently, abnormal functions of the basal ganglia neuromodulatory system underlie many neurological and psychiatric disorders. Neuromodulation acts on multiple structural levels, ranging from the subcellular level to behavior, both in health and disease. For example, neuromodulation affects membrane excitability and controls synaptic plasticity and thus learning in the basal ganglia. However, it is not clear on what time scales these different effects are implemented. Phosphorylation of ion channels and the resulting membrane effects are typically studied over minutes while it has been shown that neuromodulation can affect behavior within a few hundred milliseconds. So how do these seemingly contradictory effects fit together? Here we first briefly review neuromodulation of the basal ganglia, with a focus on dopamine. We furthermore use biophysically detailed multi-compartmental models to integrate experimental data regarding dopaminergic effects on individual membrane conductances with the aim to explain the resulting cellular level dopaminergic effects. In particular we predict dopaminergic effects on Kv4.2 in D1-MSNs. Finally, we also explore dynamical aspects of the onset of neuromodulation effects in multi-scale computational models combining biochemical signaling cascades and multi-compartmental neuron models.

The microcircuits of striatum in silico

“…Synaptic plasticity is not yet implemented, and this is obviously a critical element when considering reward and reinforcement learning. An example of how to integrate a receptorinduced cascade affecting membrane or receptor properties is already explored in Lindroos et al (106) and in future work can be introduced also into the microcircuit platform. A further limitation of these models is that we have not implemented dendritic spines, which represent one major structure for synaptic plasticity (long-term potentiation [LTP]), and neither have we modeled presynaptic long-term depression (LTD).…”

An efficient analytical reduction of detailed nonlinear neuron models

“…Two additional models were obtained from the Allen Institute cell-type database 11 : an L4 spiny cell and an L1 aspiny cell from the mouse visual cortex. Medium spiny neuron from the mouse basal ganglia 54 ; two rat thalamocortical neurons 55 ; Golgi cell from mouse cerebellar cortex; and one inhibitory hippocampal neuron from the rat 56 . We also took two additional neuron models from our laboratory: rat L2/3 large basket cell 57 and a model of a human L2/3 pyramidal cell from the temporal cortex 58 .…”

An efficient analytical reduction of detailed nonlinear neuron models

“…Aspiny Cell from the mouse visual cortex. Medium spiny neuron from the mouse basal ganglia 54 ; two rat thalamocortical neurons 55 ; Golgi cell from mouse cerebellar cortex and one inhibitory hippocampal neuron from the rat 56 . We also took two additional neuron models from our laboratory: rat L2/3 large basket cell 57 and a model of a human L2/3 pyramidal cell from the temporal cortex 58 .…”