scholarly journals Open-loop organization of thalamic reticular nucleus and dorsal thalamus: a computational model

2015 ◽  
Vol 114 (4) ◽  
pp. 2353-2367 ◽  
Author(s):  
Adam M. Willis ◽  
Bernard J. Slater ◽  
Ekaterina D. Gribkova ◽  
Daniel A. Llano
Keyword(s):  
Closed Loop ◽  
Open Loop ◽  
Tunable Filter ◽  
Cortical Activation ◽  
Thalamic Reticular Nucleus ◽  
Reticular Nucleus ◽  
Loop Model ◽  
Dependent Manner ◽  
Dorsal Thalamus ◽  
Low Threshold

The thalamic reticular nucleus (TRN) is a shell of GABAergic neurons that surrounds the dorsal thalamus. Previous work has shown that TRN neurons send GABAergic projections to thalamocortical (TC) cells to form reciprocal, closed-loop circuits. This has led to the hypothesis that the TRN is responsible for oscillatory phenomena, such as sleep spindles and absence seizures. However, there is emerging evidence that open-loop circuits are also found between TRN and TC cells. The implications of open-loop configurations are not yet known, particularly when they include time-dependent nonlinearities in TC cells such as low-threshold bursting. We hypothesized that low-threshold bursting in an open-loop circuit could be a mechanism by which the TRN could paradoxically enhance TC activation, and that enhancement would depend on the relative timing of TRN vs. TC cell stimulation. To test this, we modeled small circuits containing TC neurons, TRN neurons, and layer 4 thalamorecipient cells in both open- and closed-loop configurations. We found that open-loop TRN stimulation, rather than universally depressing TC activation, increased cortical output across a broad parameter space, modified the filter properties of TC neurons, and altered the mutual information between input and output in a frequency-dependent and T-type calcium channel-dependent manner. Therefore, an open-loop model of TRN-TC interactions, rather than suppressing transmission through the thalamus, creates a tunable filter whose properties may be modified by outside influences onto the TRN. These simulations make experimentally testable predictions about the potential role for the TRN for flexible enhancement of cortical activation.

scholarly journals Propagation of cortical activity via open-loop intrathalamic architectures: a computational analysis

2019 ◽  
Author(s):  
Jeffrey W. Brown ◽  
Aynaz Taheri ◽  
Robert V. Kenyon ◽  
Tanya Berger-Wolf ◽  
Daniel A. Llano
Keyword(s):  
Closed Loop ◽  
Neural Model ◽  
Signal Propagation ◽  
Open Loop ◽  
Thalamic Reticular Nucleus ◽  
Oscillatory Activity ◽  
Reticular Nucleus ◽  
Dorsal Thalamus ◽  
In Series ◽  
Intracortical Connectivity

AbstractPropagation of signals across the cerebral cortex is a core component of many cognitive processes and is generally thought to be mediated by direct intracortical connectivity. The thalamus, by contrast, is considered to be devoid of internal connections and organized as a collection of parallel inputs to the cortex. Here, we provide evidence that “open-loop” intrathalamic connections involving the thalamic reticular nucleus (TRN) can support propagation of oscillatory activity across the cortex. Recent studies support the existence of open-loop thalamo-reticulo-thalamic (TC-TRN-TC) synaptic motifs in addition to traditional closed-loop architectures. We hypothesized that open-loop structural modules, when connected in series, might underlie thalamic and, therefore cortical, signal propagation. Using a supercomputing platform to simulate thousands of permutations of a thalamo-reticular-cortical network and allowing select synapses to vary both by class and individually, we evaluated the relative capacities of closed- and open-loop TC-TRN-TC synaptic configurations to support both propagation and oscillation. We observed that 1) signal propagation was best supported in networks possessing strong open-loop TC-TRN-TC connectivity; 2) intrareticular synapses were neither primary substrates of propagation nor oscillation; and 3) heterogeneous synaptic networks supported more robust propagation of oscillation than their homogeneous counterparts. These findings suggest that open-loop heterogeneous intrathalamic architectures complement direct intracortical connectivity to facilitate cortical signal propagation.Significance StatementInteractions between the dorsal thalamus and thalamic reticular nucleus (TRN) are speculated to contribute to phenomena such as arousal, attention, sleep, and seizures. Despite the importance of the TRN, the synaptic microarchitectures forming the basis for dorsal thalamus-TRN interactions are not fully understood. The computational neural model we present incorporates “open-loop” thalamo-reticular-thalamic (TC-TRN-TC) synaptic motifs, which have been experimentally observed. We elucidate how open-loop motifs possess the capacity to shape the propagative properties of signals intrinsic to the thalamus and evaluate the wave dynamics they support relative to closed-loop TC-TRN-TC pathways and intrareticular synaptic connections. Our model also generates predictions regarding how different spatial distributions of reticulothalamic and intrareticular synapses affect these signaling properties.

scholarly journals Thalamic reticular control of local sleep in mouse sensory cortex

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Laura MJ Fernandez ◽  
Gil Vantomme ◽  
Alejandro Osorio-Forero ◽  
Romain Cardis ◽  
Elidie Béard ◽  
...  
Keyword(s):  
Brain Activity ◽  
Sensory Cortex ◽  
Thalamic Reticular Nucleus ◽  
Reticular Nucleus ◽  
Dependent Manner ◽  
Rapid Eye Movement Sleep ◽  
Sleep Regulation ◽  
Cortical Areas ◽  
Low Threshold ◽  
Local Sleep

Sleep affects brain activity globally, but many cortical sleep waves are spatially confined. Local rhythms serve cortical area-specific sleep needs and functions; however, mechanisms controlling locality are unclear. We identify the thalamic reticular nucleus (TRN) as a source for local, sensory-cortex-specific non-rapid-eye-movement sleep (NREMS) in mouse. Neurons in optogenetically identified sensory TRN sectors showed stronger repetitive burst discharge compared to non-sensory TRN cells due to higher activity of the low-threshold Ca2+ channel CaV3.3. Major NREMS rhythms in sensory but not non-sensory cortical areas were regulated in a CaV3.3-dependent manner. In particular, NREMS in somatosensory cortex was enriched in fast spindles, but switched to delta wave-dominated sleep when CaV3.3 channels were genetically eliminated or somatosensory TRN cells chemogenetically hyperpolarized. Our data indicate a previously unrecognized heterogeneity in a powerful forebrain oscillator that contributes to sensory-cortex-specific and dually regulated NREMS, enabling local sleep regulation according to use- and experience-dependence.

Model Predictive Control and Controller Parameter Optimisation of Combustion Instabilities

2019 ◽  
Vol 36 (2) ◽  
pp. 185-194 ◽  
Author(s):  
I. Yazar ◽  
F. Caliskan ◽  
R. Vepa
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Closed Loop ◽  
Combustion Process ◽  
Open Loop ◽  
Loop Model ◽  
Parameter Optimisation ◽  
Direct Adaptive Control ◽  
The Cost ◽  
Adaptive Control Algorithm

Abstract In this paper the application of model predictive control (MPC) to a two-mode model of the dynamics of the combustion process is considered. It is shown that the MPC by itself does not stabilize the combustor and the control gains obtained by applying the MPC algorithms need to be optimized further to ensure that the phase difference between the two modes is also stable. The results of applying the algorithm are compared with the open loop model amplitude responses and to the closed loop responses obtained by the application of a direct adaptive control algorithm. It is shown that the MPC coupled with the cost parameter optimisation proposed in the paper, always guarantees the closed loop stability, a feature that may not always be possible with an adaptive implementations.

Location model for a remanufacturing reverse logistics network based on adaptive genetic algorithm

SIMULATION ◽  
2019 ◽  
Vol 95 (11) ◽  
pp. 1069-1084 ◽  
Author(s):  
Rui Yan ◽  
Bo Yan
Keyword(s):  
Genetic Algorithm ◽  
Network Model ◽  
Reverse Logistics ◽  
Closed Loop ◽  
Value Added ◽  
Open Loop ◽  
Demand Elasticity ◽  
Mixed Integer ◽  
Adaptive Genetic Algorithm ◽  
Loop Model

Energy saving and environmental protection are important issues of today. Concerning the environmental and social need to increase the utilization of used products, this paper introduces two remanufacturing reverse logistics (RL) network models, namely, the open-loop model and the closed-loop model. In an open-loop RL system, used products are recovered by outside firms, while in a closed-loop RL system, they are returned to their original producers. The open-loop model features a location selection with two layers. For this model, a mixed-integer linear program (MILP) is built to minimize the total costs of the open-loop RL system, including the fixed cost, the freight between nodes, the operation cost of storage and remanufacturing centers, the penalty cost of unmet or remaining demand quantity, and the government-provided subsidy given to the enterprises that protect the environment. This MILP is solved using an adaptive genetic algorithm with MATLAB simulation. For a closed-loop RL network model, a special demand function considering the relationship between new and remanufactured products is developed. Remanufacturing rate, environmental awareness, service demand elasticity, value-added services, and their impacts on total profit of the closed-loop supply chain are analyzed. The closed-loop RL network model is proved effective through the analysis of a numerical example.

Pseudo-random binary sequence closed-loop system identification error with integration control

2009 ◽  
Vol 223 (6) ◽  
pp. 877-884 ◽  
Author(s):  
Z Ren ◽  
G G Zhu
Keyword(s):  
System Identification ◽  
Closed Loop ◽  
Binary Sequence ◽  
Open Loop ◽  
Loop System ◽  
Loop Model ◽  
Closed Loop System ◽  
Identification Error ◽  
Closed Loop Identification ◽  
Integral Controller

This paper studies the closed-loop system identification (ID) error when a dynamic integral controller is used. Pseudo-random binary sequence (PRBS) q-Markov covariance equivalent realization (Cover) is used to identify the closed-loop model, and the open-loop model is obtained based upon the identified closed-loop model. Accurate open-loop models were obtained using PRBS q-Markov Cover system ID directly. For closed-loop system ID, accurate open-loop identified models were obtained with a proportional controller, but when a dynamic controller was used, low-frequency system ID error was found. This study suggests that extra caution is required when a dynamic integral controller is used for closed-loop system identification. The closed-loop identification framework also has significant effects on closed-loop identification error. Both first- and second-order examples are provided in this paper.

When Causality Does Not Imply Correlation: More Spadework at the Foundations of Scientific Psychology

2011 ◽  
Vol 108 (3) ◽  
pp. 943-954 ◽  
Author(s):  
Richard S. Marken ◽  
Brittany Horth
Keyword(s):  
Sensory Input ◽  
Closed Loop ◽  
Causal Model ◽  
Open Loop ◽  
Tracking Performance ◽  
Loop Model ◽  
Surprising Result ◽  
Scientific Psychology ◽  
Mouse Movements

Experimental research in psychology is based on an open-loop causal model which assumes that sensory input causes behavioral output. This model was tested in a tracking experiment where participants were asked to control a cursor, keeping it aligned with a target by moving a mouse to compensate for disturbances of differing difficulty. Since cursor movements (inputs) are the only observable cause of mouse movements (outputs), the open-loop model predicts that there will be a correlation between input and output that increases as tracking performance improves. In fact, the correlation between sensory input and motor output is very low regardless of the quality of tracking performance; causality, in terms of the effect of input on output, does not seem to imply correlation in this situation. This surprising result can be explained by a closed-loop model which assumes that input is causing output while output is causing input.

scholarly journals Closed-loop Controller Based on Reference Signal Tracking for Absence Seizures

2021 ◽  
Author(s):  
Hudong Zhang ◽  
Yuting Chen ◽  
Yan Xie ◽  
Yuan Chai
Keyword(s):  
Firing Rate ◽  
Closed Loop ◽  
Reference Signal ◽  
Absence Epilepsy ◽  
Open Loop ◽  
Recursive Least Squares ◽  
Biophysical Model ◽  
Reticular Nucleus ◽  
Cortical Region ◽  
Absence Seizures

Abstract Deep brain stimulation (DBS) targeting thalamus reticular nucleus (TRN) brain regions has been proven to play an irreplaceable role in the treatment of absence seizures. Compared with open-loop DBS, closed-loop DBS has been recognized by researchers for its advantages of significantly inhibiting seizures and having fewer side effects. However, due to the complexity of the nervous system, the mechanism of DBS control epilepsy is still unclear, which hinders the study of closed-loop DBS. In our study, based on the biophysical model jointly constituted by cortical, thalamic, and basal ganglia, we selected the 2-4 Hz spike and wave discharges (SWDs) of the cortical region as a biomarker for response to absence epilepsy, and the mean firing rate (MFR) of substantia nigra pars reticulata (SNr) was used as a reference signal for modulation of closed-loop DBS. Moreover, to obtain the linear relationship between the stimulus and the response, we adopted an algorithm that combines controlled auto-regressive (CAR) and recursive least squares (RLS), and we built a proportional integral (PI) controller to make the DBS stimulus parameters self-update to control the seizures. The numerical simulation results show that the closed-loop DBS controllers based on frequency modulation and amplitude modulation respectively not only successfully track the firing rate (FR) of SNr, but also significantly destroy the SWDs of cerebral cortex and restore it to the other two normal discharge modes.

scholarly journals Spindle oscillations are generated in the dorsal thalamus and modulated by the thalamic reticular nucleus

2008 ◽  
Author(s):  
Chun-Hua Liu ◽  
Yi Ping Guo ◽  
Xian-Kai Meng ◽  
Yan-Qin Yu ◽  
Ying Xiong ◽  
...  
Keyword(s):  
Thalamic Reticular Nucleus ◽  
Reticular Nucleus ◽  
Dorsal Thalamus

scholarly journals Iterative LQG Controller Design Through Closed-Loop Identification

1996 ◽  
Vol 118 (2) ◽  
pp. 366-372 ◽  
Author(s):  
Min-Hung Hsiao ◽  
Jen-Kuang Huang ◽  
David E. Cox
Keyword(s):  
Kalman Filter ◽  
State Feedback ◽  
Closed Loop ◽  
Controller Design ◽  
Open Loop ◽  
The State ◽  
Magnetic Suspension ◽  
Loop Model ◽  
Closed Loop Identification ◽  
Noise Statistics

This paper presents an iterative LQG controller design approach for a linear stochastic system with an uncertain openloop model and unknown noise statistics. This approach consists of closed-loop identification and controller redesign cycles. In each cycle, the closed-loop identification method is used to identify an open-loop model and a steady-state Kalman filter gain from closed-loop input/output test data obtained by using a feedback LQG controller designed from the previous cycle. Then the identified open-loop model is used to redesign the state feedback. The state feedback and the identified Kalman filter gain are used to form an updated LQG controller for the next cycle. This iterative process continues until the updated controller converges. The proposed controller design is demonstrated by numerical simulations and experiments on a highly unstable large-gap magnetic suspension system.

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