| Abstract No.: | C-B3040 |
| Country: | Canada |
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| Title: | PREDICTING SYNCHRONY AND ASYNCHRONY IN BASKET CELL NETWORKS COUPLED BY MULTIPLE DENDRITIC GAP JUNCTIONS |
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| Authors/Affiliations: | 1 Tariq Zahid*; 2 Frances Skinner;
1 Toronto Western Research Institute (TWRI), University Health Network (UHN), ON, Canada; 2 TWRI/UHN, Departments of Medicine (Neurology), Physiology and IBBME, University of Toronto, ON, Canada
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| Content: | Objectives: Basket cells in hippocampus form mutually inhibitory networks and are major players in the production of gamma rhythms both in vitro and in vivo. Theoretical and modeling studies have shown that synchronous output from basket cell networks are important contributors to gamma rhythms. Basket cells are known to be electrically coupled with gap junctions at multiple locations between their apical and basal dendrites, up to several hundred microns from their somata. Given that direct electrical communication between neurons plays an important role in shaping network output, our objective is to understand how non-proximally located gap junctions might contribute to producing synchronous output, thus influencing population activities such as gamma rhythms. In this work, we use compartmental models of basket cells endowed with active dendrites and we use weakly coupled oscillator theory applied to reduced compartmental models to understand and predict output from basket cells coupled with multiple, non-proximal gap junctions.
Materials and Methods: We use the morphology and passive properties of our previously built basket cell compartmental model, but use a variety of different distributions of ion channels (Na+ and K+) in basal and apical dendrites that reproduce basket cell electrophysiological characteristics. We compare full (372 compartments) and reduced (3 compartments) compartmental models coupled by gap junctions at a single site to define synchronous and asynchronous regimes. We generate phase response curves (PRCs) for the reduced models, and quantify them in terms of their skewness (relative area under the curve) to predict the network dynamics (synchronous or asynchronous) using weakly coupled oscillatory theory. We generate PRCs at apical and basal dendritic sites using the full models and we perform two-cell network simulations with the full basket cell models at a physiological range of gap junction strengths. We use one, two and three sites for gap junction coupling in the simulations. For multiple sites, we determine an average of the multiple PRCs obtained at each site and quantify the skewness of the averaged PRC.
Results: As indicated from a comparison of full and reduced models, synchronous states refer to phase lags that are less than 10%. Our skewness quantification of PRCs (based on the reduced models) held for the full models, thus predicting network synchrony or asynchrony. Specifically, if less than 43% of the area under the PRC was to the left, this was sufficient to predict synchrous output. If this left area exceeded 53%, then the result was asynchrony. Interestingly, the skewness quantification of the averaged PRCs correctly predicted the network output when multiple gap junction couplings were used.
Conclusion: Quantification of PRCs obtained from neuronal models of basket cells can be used to predict synchronous and asynchronous output in networks coupled by gap junctions at single and multiple sites. We thus suggest that PRCs obtained from real basket cells could be used to predict whether gap junctions located at different and multiple sites enhance synchrony or not.
Acknowledgements
We thank NSERC for funding, and F. Saraga for help with the compartmental models. |
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