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A Framework for Quantitative Modeling of Neural Circuits Involved in Sleep-to-Wake Transition.

Sorooshyari S, Huerta R, de Lecea L - Front Neurol (2015)

Bottom Line: The optogenetically driven data do not yet provide a multi-dimensional schematic of the mechanisms underlying changes in vigilance states.We identify feedback, redundancy, and gating hierarchy as three fundamental aspects of this model.The presented model is expected to expand as additional data on the contribution of each transmitter to a vigilance state becomes available.

View Article: PubMed Central - PubMed

Affiliation: Bell Laboratories, Alcatel-Lucent , Murray Hill, NJ , USA.

ABSTRACT
Identifying the neuronal circuits and dynamics of sleep-to-wake transition is essential to understanding brain regulation of behavioral states, including sleep-wake cycles, arousal, and hyperarousal. Recent work by different laboratories has used optogenetics to determine the role of individual neuromodulators in state transitions. The optogenetically driven data do not yet provide a multi-dimensional schematic of the mechanisms underlying changes in vigilance states. This work presents a modeling framework to interpret, assist, and drive research on the sleep-regulatory network. We identify feedback, redundancy, and gating hierarchy as three fundamental aspects of this model. The presented model is expected to expand as additional data on the contribution of each transmitter to a vigilance state becomes available. Incorporation of conductance-based models of neuronal ensembles into this model and existing models of cortical excitability will provide more comprehensive insight into sleep dynamics as well as sleep and arousal-related disorders.

No MeSH data available.


Related in: MedlinePlus

An algorithmic explanation for the role of feedback in the sleep–wake system. (A) A generic control system with output feedback. (B) This figure depicts the feedback provided by the neocortex to Hcrt neurons (referred to as state feedback) as well as the feedback from the occurrence of a sleep-to-wake transition to the neural activity in the neocortex (referred to as output feedback). The right-most block is a threshold device, which outputs a signal contingent on its input exceeding/not-exceeding a specific threshold. (C) An “engineered” version of the prior schematic with the green arrows indicating where optogenetic stimulation/inhibition can be applied so as to drive the feedback control system to particular states and induce an ensuing behavior.
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Figure 8: An algorithmic explanation for the role of feedback in the sleep–wake system. (A) A generic control system with output feedback. (B) This figure depicts the feedback provided by the neocortex to Hcrt neurons (referred to as state feedback) as well as the feedback from the occurrence of a sleep-to-wake transition to the neural activity in the neocortex (referred to as output feedback). The right-most block is a threshold device, which outputs a signal contingent on its input exceeding/not-exceeding a specific threshold. (C) An “engineered” version of the prior schematic with the green arrows indicating where optogenetic stimulation/inhibition can be applied so as to drive the feedback control system to particular states and induce an ensuing behavior.

Mentions: We will restrict attention to two feedback loops that are present in Figures 4–6: the feedback signal from sleep-to-wake transition to the NC, and a feedback signal from the NC to Hcrt. It is productive to describe such signaling via incipient models that will be proximately advanced to capture more detailed and elegant aspects of the biological network. The uppermost schematic in Figure 8 depicts a rudimentary feedback control system discussed at length in textbooks such as Brogan (71). The schematic shows what is referred to as output feedback because the output of the system is relayed to the input of the controller for subsequent processing. The purpose of the first schematic is to motivate the middle schematic of Figure 8, which is a control-theoretic model for the two feedback loops that we have mentioned. Interestingly, both output feedback and state feedback are necessary to describe the neuronal interactions taking place even in such a simple depiction of this complex process. The signal from the NC to Hcrt depicts the state feedback, and the sleep/wake signal relayed from the output of the threshold device to the NC depicts the output feedback. It is important to note that Figure 8B does not contain a discernible controller. A controller (or several coupled controllers) must exist for proper neurological operation; however, such controllers are embedded in the system rather than being entities that can be optimized via an engineering procedure. A controller can be instantiated within the neural system by optogenetically applying extrinsic stimulation/inhibition to the neuronal populations as shown in the lower schematic of Figure 8. It should be apparent that this schematic is a gross simplification of the models that we have discussed in Section “Modeling Neural Circuit Interactions During Sleep-to-Wake Transition,” for instance, the direct interaction from the NE/LC to Hcrt neurons has not been considered in Figure 8. Nevertheless, the utility of considering such a scheme is its conduciveness to real-time control of the three neurological units. In fact, preliminary results from various points in this schematic have been studied by recording behavior and EEG signals in Carter et al. (30, 32).


A Framework for Quantitative Modeling of Neural Circuits Involved in Sleep-to-Wake Transition.

Sorooshyari S, Huerta R, de Lecea L - Front Neurol (2015)

An algorithmic explanation for the role of feedback in the sleep–wake system. (A) A generic control system with output feedback. (B) This figure depicts the feedback provided by the neocortex to Hcrt neurons (referred to as state feedback) as well as the feedback from the occurrence of a sleep-to-wake transition to the neural activity in the neocortex (referred to as output feedback). The right-most block is a threshold device, which outputs a signal contingent on its input exceeding/not-exceeding a specific threshold. (C) An “engineered” version of the prior schematic with the green arrows indicating where optogenetic stimulation/inhibition can be applied so as to drive the feedback control system to particular states and induce an ensuing behavior.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4341569&req=5

Figure 8: An algorithmic explanation for the role of feedback in the sleep–wake system. (A) A generic control system with output feedback. (B) This figure depicts the feedback provided by the neocortex to Hcrt neurons (referred to as state feedback) as well as the feedback from the occurrence of a sleep-to-wake transition to the neural activity in the neocortex (referred to as output feedback). The right-most block is a threshold device, which outputs a signal contingent on its input exceeding/not-exceeding a specific threshold. (C) An “engineered” version of the prior schematic with the green arrows indicating where optogenetic stimulation/inhibition can be applied so as to drive the feedback control system to particular states and induce an ensuing behavior.
Mentions: We will restrict attention to two feedback loops that are present in Figures 4–6: the feedback signal from sleep-to-wake transition to the NC, and a feedback signal from the NC to Hcrt. It is productive to describe such signaling via incipient models that will be proximately advanced to capture more detailed and elegant aspects of the biological network. The uppermost schematic in Figure 8 depicts a rudimentary feedback control system discussed at length in textbooks such as Brogan (71). The schematic shows what is referred to as output feedback because the output of the system is relayed to the input of the controller for subsequent processing. The purpose of the first schematic is to motivate the middle schematic of Figure 8, which is a control-theoretic model for the two feedback loops that we have mentioned. Interestingly, both output feedback and state feedback are necessary to describe the neuronal interactions taking place even in such a simple depiction of this complex process. The signal from the NC to Hcrt depicts the state feedback, and the sleep/wake signal relayed from the output of the threshold device to the NC depicts the output feedback. It is important to note that Figure 8B does not contain a discernible controller. A controller (or several coupled controllers) must exist for proper neurological operation; however, such controllers are embedded in the system rather than being entities that can be optimized via an engineering procedure. A controller can be instantiated within the neural system by optogenetically applying extrinsic stimulation/inhibition to the neuronal populations as shown in the lower schematic of Figure 8. It should be apparent that this schematic is a gross simplification of the models that we have discussed in Section “Modeling Neural Circuit Interactions During Sleep-to-Wake Transition,” for instance, the direct interaction from the NE/LC to Hcrt neurons has not been considered in Figure 8. Nevertheless, the utility of considering such a scheme is its conduciveness to real-time control of the three neurological units. In fact, preliminary results from various points in this schematic have been studied by recording behavior and EEG signals in Carter et al. (30, 32).

Bottom Line: The optogenetically driven data do not yet provide a multi-dimensional schematic of the mechanisms underlying changes in vigilance states.We identify feedback, redundancy, and gating hierarchy as three fundamental aspects of this model.The presented model is expected to expand as additional data on the contribution of each transmitter to a vigilance state becomes available.

View Article: PubMed Central - PubMed

Affiliation: Bell Laboratories, Alcatel-Lucent , Murray Hill, NJ , USA.

ABSTRACT
Identifying the neuronal circuits and dynamics of sleep-to-wake transition is essential to understanding brain regulation of behavioral states, including sleep-wake cycles, arousal, and hyperarousal. Recent work by different laboratories has used optogenetics to determine the role of individual neuromodulators in state transitions. The optogenetically driven data do not yet provide a multi-dimensional schematic of the mechanisms underlying changes in vigilance states. This work presents a modeling framework to interpret, assist, and drive research on the sleep-regulatory network. We identify feedback, redundancy, and gating hierarchy as three fundamental aspects of this model. The presented model is expected to expand as additional data on the contribution of each transmitter to a vigilance state becomes available. Incorporation of conductance-based models of neuronal ensembles into this model and existing models of cortical excitability will provide more comprehensive insight into sleep dynamics as well as sleep and arousal-related disorders.

No MeSH data available.


Related in: MedlinePlus