Model calcium sensors for network homeostasis: sensor and readout parameter analysis from a database of model neuronal networks.
In activity-dependent homeostatic regulation (ADHR) of neuronal and network properties, the intracellular Ca(2+) concentration is a good candidate for sensing activity levels because it is correlated with the electrical activity of the cell. Previous ADHR models, developed with abstract activity sensors for model pyloric neurons and networks of the crustacean stomatogastric ganglion, showed that functional activity can be maintained by a regulation mechanism that senses activity levels solely from Ca(2+). At the same time, several intracellular pathways have been discovered for Ca(2+)-dependent regulation of ion channels. To generate testable predictions for dynamics of these signaling pathways, we undertook a parameter study of model Ca(2+) sensors across thousands of model pyloric networks. We found that an optimal regulation signal can be generated for 86% of model networks with a sensing mechanism that activates with a time constant of 1 ms and that inactivates within 1 s. The sensor performed robustly around this optimal point and did not need to be specific to the role of the cell. When multiple sensors with different time constants were used, coverage extended to 88% of the networks. Without changing the sensors, it extended to 95% of the networks by letting the sensors affect the readout nonlinearly. Specific to this pyloric network model, the sensor of the follower pyloric constrictor cell was more informative than the pacemaker anterior burster cell for producing a regulatory signal. Conversely, a global signal indicating network activity that was generated by summing the sensors in individual cells was less informative for regulation.
Günay
Cengiz
C
Department of Biology, Emory University, Atlanta, Georgia 30322, USA. cgunay@emory.edu
Prinz
Astrid A
AA
D015374:Biosensing Techniques; D002118:Calcium / Q000378:metabolism*; D020013:Calcium Signaling / Q000502:physiology; D025461:Feedback, Physiological / Q000502:physiology*; D006706:Homeostasis / Q000502:physiology; D016014:Linear Models; D008959:Models, Neurological; D016571:Neural Networks, Computer; D009434:Neural Pathways / Q000378:metabolism; D017711:Nonlinear Dynamics; D011708:Pylorus / Q000294:innervation / Q000378:metabolism; D044169:Receptors, Calcium-Sensing / Q000378:metabolism; D013569:Synapses / Q000378:metabolism
D044169:Receptors, Calcium-Sensing; D002118:Calcium