Artificial synaptic modification reveals a dynamical invariant in the pyloric CPG

Reyes, Marcelo Bussotti; Huerta, Ramón; Rabinovich, M. I.; Selverston, Allen I.

doi:10.1007/s00421-007-0635-0

Cited by 11 publications

(9 citation statements)

References 37 publications

(45 reference statements)

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“…4 C ) because the AB/PD cell maintains a fixed duty cycle—the ratio of the burst duration to the cell period (Fig. S3)—which is consistent with recent experimental evidence from spiny lobsters (Reyes et al, 2008). …”

Section: Resultssupporting

confidence: 88%

Model Calcium Sensors for Network Homeostasis: Sensor and Readout Parameter Analysis from a Database of Model Neuronal Networks

Günay¹,

Prinz²

2010

J. Neurosci.

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In activity-dependent homeostatic regulation (ADHR) of neuronal and network properties, the intracellular Ca 2ϩ 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 2ϩ . At the same time, several intracellular pathways have been discovered for Ca 2ϩ -dependent regulation of ion channels. To generate testable predictions for dynamics of these signaling pathways, we undertook a parameter study of model Ca 2ϩ 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.

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Section: Resultssupporting

confidence: 88%

Model Calcium Sensors for Network Homeostasis: Sensor and Readout Parameter Analysis from a Database of Model Neuronal Networks

Günay¹,

Prinz²

2010

J. Neurosci.

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“…This shows that the mean-field equations capture the trends of all populations and can be used to give a simplified view of this hypothalamic network. spike timing advances is not excessively rare, and we can cite for instance bursting neurons in central pattern generators [50].…”

Section: Discussionmentioning

confidence: 99%

Control of sleep-to-wake transitions via fast amino acid and slow neuropeptide transmission

2014

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The Locus Coeruleus (LC) modulates cortical, subcortical, cerebellar, brainstem and spinal cord circuits and it expresses receptors for neuromodulators that operate in a time scale of several seconds. Evidences from anatomical, electrophysiological and optogenetic experiments have shown that LC neurons receive input from a group of neurons called Hypocretins (HCRTs) that release a neuropeptide called hypocretin. It is less known how these two groups of neurons can be coregulated using GABAergic neurons. Since the time scales of GABAA inhibition is several orders of magnitude faster than the hypocretin neuropeptide effect, we investigate the limits of circuit activity regulation using a realistic model of neurons. Our investigation shows that GABAA inhibition is insufficient to control the activity levels of the LCs. Despite slower forms of GABAA can in principle work, there is not much plausibility due to the low probability of the presence of slow GABAA and lack of robust stability at the maximum firing frequencies. The best possible control mechanism predicted by our modeling analysis is the presence of inhibitory neuropeptides that exert effects in a similar time scale as the hypocretin/orexin. Although the nature of these inhibitory neuropeptides has not been identified yet, it provides the most efficient mechanism in the modeling analysis. Finally, we present a reduced mean-field model that perfectly captures the dynamics and the phenomena generated by this circuit. This investigation shows that brain communication involving multiple time scales can be better controlled by employing orthogonal mechanisms of neural transmission to decrease interference between cognitive processes and hypothalamic functions.

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“…Considering regular bursting activity and a dynamic-clamp protocol that altered a CPG synapse, previous work reported a dynamical invariant in which the ratio between the resulting change in average burst duration and the change in average phase lag between PD and LP neurons was tightly preserved in all preparations. 51 Here we follow this terminology, but we refer to robustly preserved instantaneous interval relationships within the variability of a preparation, as opposed to cross-preparation averaged phase maintenance. We believe this term better reflects the transient information exchange in the circuit.…”

Section: Introductionmentioning

confidence: 99%

Robust dynamical invariants in sequential neural activity

Elices

Levi

Arroyo

et al. 2018

Preprint

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By studying different sources of temporal variability in central pattern generator circuits, in this paper we unveil distinct aspects of the instantaneous balance between flexibility and robustness in sequential dynamics -a property that characterizes many systems that display neural rhythms. The level of irregularity and coordination was characterized using intrinsic time references and intervals in long recordings of the pyloric central pattern generator. The analysis demonstrated strong robustness of transient dynamics in keeping not only the activation sequences but also specific cycle-by-cycle temporal relationships in the form of dynamical invariants. The rich dynamics of neurons and connections balance flexibility and coordination to readily negotiate the interactions between neurons and produce the resultant rhythm. In particular, two dynamical invariants were identified between time intervals that build the sequence, existing even outside steady states. We suggest that invariant temporal sequence relationships could be present in other networks, including those related to brain rhythms, and underlie rhythm programming and functionality.

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Artificial synaptic modification reveals a dynamical invariant in the pyloric CPG

Cited by 11 publications

References 37 publications

Model Calcium Sensors for Network Homeostasis: Sensor and Readout Parameter Analysis from a Database of Model Neuronal Networks

Model Calcium Sensors for Network Homeostasis: Sensor and Readout Parameter Analysis from a Database of Model Neuronal Networks

Control of sleep-to-wake transitions via fast amino acid and slow neuropeptide transmission

Robust dynamical invariants in sequential neural activity

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