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Reconstructing the three-dimensional GABAergic microcircuit of the striatum.

Humphries MD, Wood R, Gurney K - PLoS Comput. Biol. (2010)

Bottom Line: From these, we found the probabilities of intersection between the neurites of two neurons given their inter-somatic distance, and used these to construct three-dimensional striatal networks.We show that both properties influence striatal dynamics: the most potent inhibition of a MSN arises from a region of striatum at the edge of its dendritic field; and the combination of local gap junction and distal synaptic networks between FSIs sets a robust input-output regime for the MSN population.Our models thus intimately link striatal micro-anatomy to its dynamics, providing a biologically grounded platform for further study.

View Article: PubMed Central - PubMed

Affiliation: Adaptive Behaviour Research Group, Department of Psychology, University of Sheffield, Sheffield, United Kingdom. m.d.humphries@shef.ac.uk

ABSTRACT
A system's wiring constrains its dynamics, yet modelling of neural structures often overlooks the specific networks formed by their neurons. We developed an approach for constructing anatomically realistic networks and reconstructed the GABAergic microcircuit formed by the medium spiny neurons (MSNs) and fast-spiking interneurons (FSIs) of the adult rat striatum. We grew dendrite and axon models for these neurons and extracted probabilities for the presence of these neurites as a function of distance from the soma. From these, we found the probabilities of intersection between the neurites of two neurons given their inter-somatic distance, and used these to construct three-dimensional striatal networks. The MSN dendrite models predicted that half of all dendritic spines are within 100µm of the soma. The constructed networks predict distributions of gap junctions between FSI dendrites, synaptic contacts between MSNs, and synaptic inputs from FSIs to MSNs that are consistent with current estimates. The models predict that to achieve this, FSIs should be at most 1% of the striatal population. They also show that the striatum is sparsely connected: FSI-MSN and MSN-MSN contacts respectively form 7% and 1.7% of all possible connections. The models predict two striking network properties: the dominant GABAergic input to a MSN arises from neurons with somas at the edge of its dendritic field; and FSIs are inter-connected on two different spatial scales: locally by gap junctions and distally by synapses. We show that both properties influence striatal dynamics: the most potent inhibition of a MSN arises from a region of striatum at the edge of its dendritic field; and the combination of local gap junction and distal synaptic networks between FSIs sets a robust input-output regime for the MSN population. Our models thus intimately link striatal micro-anatomy to its dynamics, providing a biologically grounded platform for further study.

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Probability of a branch or termination event as a function of the diameter of the dendrite.The dashed line plots the probability function for termination; the solid line plots the probability function for branching, given by equation (2). A The original functions from [52]. Branching probability is given by two exponential functions. B Probability functions found for the MSN dendrite models. C Probability functions found for the FSI dendrite models. The searches for both MSN and FSI dendrite models suggest that only a single exponential function is needed to describe the branching probability in these neurons.
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pcbi-1001011-g003: Probability of a branch or termination event as a function of the diameter of the dendrite.The dashed line plots the probability function for termination; the solid line plots the probability function for branching, given by equation (2). A The original functions from [52]. Branching probability is given by two exponential functions. B Probability functions found for the MSN dendrite models. C Probability functions found for the FSI dendrite models. The searches for both MSN and FSI dendrite models suggest that only a single exponential function is needed to describe the branching probability in these neurons.

Mentions: The probability of a dendritic segment branching or terminating is a function of its diameter. To determine these probability functions, Burke et al [52] pooled morphological analyses of six spinal -motor neurons to obtain a distribution of the number of branch and termination points at each dendritic diameter, and found the probability per-unit-length of either termination or branching; all their resulting probability functions had the exponential form(1)for the probability of event (termination or branching ), given dendrite diameter and the free parameters and . A single function of this form was sufficient to fit the termination probability data; two functions of this form and were required to fit the branch probability data. The single branching probability was obtained by evaluating both and using the minimum value:(2)Figure 3A shows the termination and branch probability functions obtained from the -motor neuron data by [52] (for a segment length of ).


Reconstructing the three-dimensional GABAergic microcircuit of the striatum.

Humphries MD, Wood R, Gurney K - PLoS Comput. Biol. (2010)

Probability of a branch or termination event as a function of the diameter of the dendrite.The dashed line plots the probability function for termination; the solid line plots the probability function for branching, given by equation (2). A The original functions from [52]. Branching probability is given by two exponential functions. B Probability functions found for the MSN dendrite models. C Probability functions found for the FSI dendrite models. The searches for both MSN and FSI dendrite models suggest that only a single exponential function is needed to describe the branching probability in these neurons.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2991252&req=5

pcbi-1001011-g003: Probability of a branch or termination event as a function of the diameter of the dendrite.The dashed line plots the probability function for termination; the solid line plots the probability function for branching, given by equation (2). A The original functions from [52]. Branching probability is given by two exponential functions. B Probability functions found for the MSN dendrite models. C Probability functions found for the FSI dendrite models. The searches for both MSN and FSI dendrite models suggest that only a single exponential function is needed to describe the branching probability in these neurons.
Mentions: The probability of a dendritic segment branching or terminating is a function of its diameter. To determine these probability functions, Burke et al [52] pooled morphological analyses of six spinal -motor neurons to obtain a distribution of the number of branch and termination points at each dendritic diameter, and found the probability per-unit-length of either termination or branching; all their resulting probability functions had the exponential form(1)for the probability of event (termination or branching ), given dendrite diameter and the free parameters and . A single function of this form was sufficient to fit the termination probability data; two functions of this form and were required to fit the branch probability data. The single branching probability was obtained by evaluating both and using the minimum value:(2)Figure 3A shows the termination and branch probability functions obtained from the -motor neuron data by [52] (for a segment length of ).

Bottom Line: From these, we found the probabilities of intersection between the neurites of two neurons given their inter-somatic distance, and used these to construct three-dimensional striatal networks.We show that both properties influence striatal dynamics: the most potent inhibition of a MSN arises from a region of striatum at the edge of its dendritic field; and the combination of local gap junction and distal synaptic networks between FSIs sets a robust input-output regime for the MSN population.Our models thus intimately link striatal micro-anatomy to its dynamics, providing a biologically grounded platform for further study.

View Article: PubMed Central - PubMed

Affiliation: Adaptive Behaviour Research Group, Department of Psychology, University of Sheffield, Sheffield, United Kingdom. m.d.humphries@shef.ac.uk

ABSTRACT
A system's wiring constrains its dynamics, yet modelling of neural structures often overlooks the specific networks formed by their neurons. We developed an approach for constructing anatomically realistic networks and reconstructed the GABAergic microcircuit formed by the medium spiny neurons (MSNs) and fast-spiking interneurons (FSIs) of the adult rat striatum. We grew dendrite and axon models for these neurons and extracted probabilities for the presence of these neurites as a function of distance from the soma. From these, we found the probabilities of intersection between the neurites of two neurons given their inter-somatic distance, and used these to construct three-dimensional striatal networks. The MSN dendrite models predicted that half of all dendritic spines are within 100µm of the soma. The constructed networks predict distributions of gap junctions between FSI dendrites, synaptic contacts between MSNs, and synaptic inputs from FSIs to MSNs that are consistent with current estimates. The models predict that to achieve this, FSIs should be at most 1% of the striatal population. They also show that the striatum is sparsely connected: FSI-MSN and MSN-MSN contacts respectively form 7% and 1.7% of all possible connections. The models predict two striking network properties: the dominant GABAergic input to a MSN arises from neurons with somas at the edge of its dendritic field; and FSIs are inter-connected on two different spatial scales: locally by gap junctions and distally by synapses. We show that both properties influence striatal dynamics: the most potent inhibition of a MSN arises from a region of striatum at the edge of its dendritic field; and the combination of local gap junction and distal synaptic networks between FSIs sets a robust input-output regime for the MSN population. Our models thus intimately link striatal micro-anatomy to its dynamics, providing a biologically grounded platform for further study.

Show MeSH