This title appears in the Scientific Report :
2017
Please use the identifier:
http://hdl.handle.net/2128/16153 in citations.
Please use the identifier: http://dx.doi.org/10.1523/ENEURO.0348-16.2017 in citations.
Activity Dynamics and Signal Representation in a Striatal Network Model with Distance-Dependent Connectivity
Activity Dynamics and Signal Representation in a Striatal Network Model with Distance-Dependent Connectivity
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 spatiotemporal structure of striat...
Saved in:
Personal Name(s): | Spreizer, Sebastian (Corresponding author) |
---|---|
Angelhuber, Martin / Bahuguna, Jyotika / Aertsen, Ad / Kumar, Arvind (Corresponding author) | |
Contributing Institute: |
Jara-Institut Brain structure-function relationships; INM-10 Computational and Systems Neuroscience; IAS-6 Computational and Systems Neuroscience; INM-6 |
Published in: | eNeuro, 4 (2017) 4, S. ENEURO.0348-16.2017 - |
Imprint: |
Washington, DC
Soc.
2017
|
PubMed ID: |
28840190 |
DOI: |
10.1523/ENEURO.0348-16.2017 |
Document Type: |
Journal Article |
Research Program: |
Connectivity and Activity (Dys-)function and Plasticity Theory, modelling and simulation |
Link: |
OpenAccess OpenAccess |
Publikationsportal JuSER |
Please use the identifier: http://dx.doi.org/10.1523/ENEURO.0348-16.2017 in citations.
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 spatiotemporal structure of striatal activity. We show that a striatal network with nonmonotonically changing distance-dependent connectivity (according to a gamma distribution) can exhibit a wide repertoire of spatiotemporal 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 spatiotemporal activity dynamics and neuronal assemblies in the striatum. In contrast, striatal networks with monotonically decreasing distance-dependent connectivity (in a Gaussian fashion) can exhibit only 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 nonmonotonically. 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. In 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. |