Gap Junctions among Dendrites of Cortical GABAergic Neurons Establish a Dense and Widespread Intercolumnar Network
Open Access
- 29 March 2006
- journal article
- Published by Society for Neuroscience in Journal of Neuroscience
- Vol. 26 (13) , 3434-3443
- https://doi.org/10.1523/jneurosci.4076-05.2006
Abstract
Gap junctions are common between cortical GABAergic interneurons but little is known about their quantitative distribution along dendritic profiles. Here, we provide direct morphological evidence that parvalbumin-containing GABAergic neurons in layer 2/3 of the cat visual cortex form dense and far-ranging networks through dendritic gap junctions. Gap junction-coupled networks of parvalbumin neurons were visualized using connexin36 immunohistochemistry and confocal laser-scanning microscopy (CLSM). The direct correspondence of connexin36-immunopositve puncta and gap junctions was confirmed by examining the same structures in both CLSM and electron microscopy. Single parvalbumin neurons with large somata (≥200 μm2) formed 60.3 ± 12.2 (mean ± SD) gap junctions with other cells whereby these contacts were not restricted to proximal dendrites but occurred at distances of up to 380 μm from the soma. In a Sholl analysis of large-type parvalbumin neurons, 21.9 ± 7.9 gap junctions were within 50 μm of the soma, 21.7 ± 7.6 gap junctions in a segment between 50 and 100 μm, 11.2 ± 4.7 junctions between 100 and 150 μm, and 5.6 ± 3.6 junctions were in more distal segments. Serially interconnected neurons could be traced laterally in a boundless manner through multiple gap junctions. Comparison to the orientation-preference columns revealed that parvalbumin-immunoreactive cells distribute randomly whereby their large dendritic fields overlap considerably and cover different orientation columns. It is proposed that this dense and homogeneous electrical coupling of interneurons supports the precise synchronization of neuronal populations with differing feature preferences thereby providing a temporal frame for the generation of distributed representations.Keywords
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