Activity Dynamics and Signal Representation in a Striatal Network Model with Distance-Dependent Connectivity

Abstract

The striatum is the main input nucleus of the basal ganglia. Characterizing striatal activity dynamics is crucial to understanding mechanisms underlying action-selection, -initiation and -execution. Here, we studied the effects of spatial network connectivity on the spatio-temporal structure of striatal activity. We show that a striatal network with non-monotonically changing distance-dependent connectivity (according to a Gamma distribution) can exhibit a wide repertoire of spatio-temporal dynamics, ranging from spatially homogeneous asynchronous-irregular (AI) activity to a state with stable, spatially localized activity bumps, as in ‘winner-take-all’ (WTA) dynamics. Among these regimes, the unstable activity bumps (Transition Activity, TA) regime closely resembles the experimentally observed spatio-temporal activity dynamics and neuronal assemblies in the striatum. By contrast, striatal networks with monotonically decreasing distance-dependent connectivity (in a Gaussian fashion) can only exhibit an AI state. Thus, given the observation of spatially compact neuronal clusters in the striatum, our model suggests that recurrent connectivity among striatal projection neurons should vary non-monotonically. In brain disorders such as Parkinson’s disease, increased cortical inputs and high striatal firing rates are associated with a reduction in stimulus sensitivity. Consistent with this, our model suggests that strong cortical inputs drive the striatum to a WTA state, leading to low stimulus sensitivity and high variability. By contrast, the AI and TA states show high stimulus sensitivity and reliability. Thus, based on these results, we propose that in a healthy state the striatum operates in a AI/TA state and that lack of dopamine pushes it into a WTA state.

Significance Statement Recent findings suggest that striatal activity is organized in spatially compact neuron clusters. Here, we show that striatal projection neurons should have a non-monotonically changing distance-dependent connectivity to obtain spatially localized activity patterns in striatum. Among the different states a striatal network can show, asynchronous-irregular and transition activity states closely resemble striatal activity in the healthy state. By contrast, strong cortical inputs as observed in Parkinson’s disease (PD) drive the network into a winner-take-all state, in which the striatum looses its stimulus sensitivity. Thus, our model makes specific predictions about the spatial network connectivity in the striatum and provides new insights about how the striatum might make a transition from a healthy state to a PD state.