Author response: Optogenetic feedback control of neural activity

Optimizing frequency noise calibration and manipulation in an active feedback control loop

Viscoelastic materials both stores and dissipate energies and have frequency and temperature dependent properties and hence by tuning and optimizing their damping (viscous) and stiffness (elastic) properties they can be used as passive controlling devices in wide range of vibration applications. If the control of viscoelastic systems (viscoelastic structures or structures composed of viscoelastic elements) to be realized by active means, then an accurate mathematical modeling of the viscoelastic system is needed. In practice, various material models and approximation techniques such as Biot model, Golla-Hughes-McTavish (GHM) model and Anelastic Displacement Field (ADF) methods are used to model the dynamic behavior of viscoelastic systems. These models are then transformed into approximating state space models which introduces several challenges: (i) they increase the size of the related eigenvalue problems, (ii) state space realization introduces non-physical internal state variables, and, (iii) the feedback control implementation poses practical challenges such as observer and state estimator design. In this research it is shown that the active control for viscoelastic structures can be designed accurately by only utilizing the available transfer functions. These transfer functions can be obtained from dynamic experiments and the active feedback control is designed without having the knowledge of approximated state-space system matrices. The problem associated with the active control for viscoelastic system is formulated as feedback control problems in frequency domain by using the receptance method. Active control for poles and zeros assignment of the viscoelastic systems is demonstrated using numerical examples associated with the multi-degree-degree of freedom systems. It is also shown that a nested active controller can also be designed for continuous structures (beams/rods) supported by viscoelastic elements. It is highlighted that such a controller design requires modest size of transfer functions and solution of the set of linear system of equations.

Histamine is a neurotransmitter that modulates neuronal activity and regulates various brain functions. Histamine H3 receptor (H3R) antagonists/inverse agonists enhance its release in most brain regions, including the cerebral cortex, which improves learning and memory and exerts an antiepileptic effect. However, the mechanism underlying the effect of H3R antagonists/inverse agonists on cortical neuronal activity in vivo remains unclear. Here, we show the mechanism by which pitolisant, an H3R antagonist/inverse agonist, influenced perirhinal cortex (PRh) activity in individual neuron and neuronal population levels. We monitored neuronal activity in the PRh of freely moving mice using in vivo Ca2+ imaging through a miniaturized one-photon microscope. Pitolisant increased the activity of some PRh neurons while decreasing the activity of others without affecting the mean neuronal activity across neurons. Moreover, it increases neuron pairs with synchronous activity in excitatory-responsive neuronal populations. Furthermore, machine learning analysis revealed that pitolisant altered the neuronal population activity. The changes in the population activity were dependent on the neurons that were excited and inhibited by pitolisant treatment. These findings indicate that pitolisant influences the activity of a subset of PRh neurons by increasing the synchronous activity and modifying the population activity.

Active feedback control was applied to suppress oscillations in thermocapillary convection in a half-zone liquid bridge. The experiment is on a unit-aspect-ratio liquid bridge where the most unstable azimuthal mode has wavenumber 2 when control is absent. Active control was realized by locally modifying the surface temperature using the local temperature measured at different locations fed back through a simple control law. The performance of the control process was quantified by analysing local temperature signals, and the flow structure was simultaneously identified by flow visualization. With optimal placement of sensors and heaters, proportional control can raise the critical Marangoni number by more than 40%. The amplitude of the oscillation can be suppressed to less than 30% of the initial value for a wide range of Marangoni number, up to 90% of the critical value. The proportional control was tested for a period-doubling state and it stabilized the oscillation to a periodic state. Weakly nonlinear control was applied by adding a cubic term to the control law to improve the performance of the control and alter the bifurcation characteristics.

This paper presents a model and experimental validation of the learning process during operation of a closed-loop brain-machine interface. The model consists of a population of simulated cortical neurons, a decoder that transforms neural activity into motor output, a feedback controller whose role is to reduce the error based on an error-descent algorithm, and an open-loop controller whose parameters are updated based on the corrections made by the feedback controller. Using this approach, we show that the population of neurons can learn the inverse model of the decoder. Then, we validate the model by comparing its predictions with real experimental data recorded from a macaque monkey. Such a simulation tool will be useful to predict the behavior of a closed-loop BMI and in the design of optimal decoders.

Neurons in a region of monkey extrastriate cortex, MSTd, respond to the components of optic flow stimulation. Some of these neurons (single-component neurons) are selective for a single type of motion such as inward- or outward-radial motion. Other neurons respond to multiple types of rotation, for example, rightward planar, clockwise circular, and inward radial. Rather than forming discrete groups, we think these neurons represent a continuum covering the range from single-component sensitivity to multiple-component sensitivity. By combining the optic flow stimuli, we have also been able to recognize that such combinations alter the response of cells in the continuum to varying degrees. At this point, while our evidence is consistent with the hypothesis that cells in area MSTd contribute to the processing of optic flow stimuli, we do not know whether these neurons do in fact serve this function. As in all single-cell recording experiments, even those in awake animals performing tasks closer to real-world tasks than we have succeeded in emulating here, the activity of the cell in relationship to the visual stimulation is simply a correlate of the optic flow stimulation and may or may not contribute to the processing of optic flow stimulation upon which behavior depends. Further information on a number of characteristics of these cells might clarify their role. Information on such factors as whether heading in the environment is conveyed by individual neurons, or whether this property is more likely to be conveyed over a population of neurons, and the role of changes in the point of fixation of the eyes are critical points. Generation of behavior on the basis of the optic flow stimulation and determination that this behavior is modified by selective lesion of MSTd would also strengthen the argument that visual motion processing in this area is related to analyzing optic flow information.

Nonlocal topological states in elastic wave metamaterials with active feedback control

Cues that predict the availability of food rewards influence motivational states and elicit food-seeking behaviors. If a cue no longer predicts food availability, then animals may adapt accordingly by inhibiting food-seeking responses. Sparsely activated sets of neurons, coined "neuronal ensembles," have been shown to encode the strength of reward-cue associations. Although alterations in intrinsic excitability have been shown to underlie many learning and memory processes, little is known about these properties specifically on cue-activated neuronal ensembles. We examined the activation patterns of cue-activated orbitofrontal cortex (OFC) and nucleus accumbens (NAc) shell ensembles using wild-type and Fos-GFP mice, which express green fluorescent protein (GFP) in activated neurons, after appetitive conditioning with sucrose and extinction learning. We also investigated the neuronal excitability of recently activated, GFP+ neurons in these brain areas using whole-cell electrophysiology in brain slices. Exposure to a sucrose cue elicited activation of neurons in both the NAc shell and OFC. In the NAc shell, but not the OFC, these activated GFP+ neurons were more excitable than surrounding GFP- neurons. After extinction, the number of neurons activated in both areas was reduced and activated ensembles in neither area exhibited altered excitability. These data suggest that learning-induced alterations in the intrinsic excitability of neuronal ensembles is regulated dynamically across different brain areas. Furthermore, we show that changes in associative strength modulate the excitability profile of activated ensembles in the NAc shell.SIGNIFICANCE STATEMENT Sparsely distributed sets of neurons called "neuronal ensembles" encode learned associations about food and cues predictive of its availability. Widespread changes in neuronal excitability have been observed in limbic brain areas after associative learning, but little is known about the excitability changes that occur specifically on neuronal ensembles that encode appetitive associations. Here, we reveal that sucrose cue exposure recruited a more excitable ensemble in the nucleus accumbens, but not orbitofrontal cortex, compared with their surrounding neurons. This excitability difference was not observed when the cue's salience was diminished after extinction learning. These novel data provide evidence that the intrinsic excitability of appetitive memory-encoding ensembles is regulated differentially across brain areas and adapts dynamically to changes in associative strength.

Neuronal firing plays a key role in the neuronal information transmission, and different neuronal firing patterns are reported, such as spiking, bursting. A number of neuron models are introduced to reproduce the firing patterns of single neuron or neuronal network. The key factors determining the firing pattern gain more and more attention in the study of neuron system, such as noise, network topology. Noise is able to induce sub-or super-threshold coherent neuronal firing easily, and a number of coherence resonances are reported in the noise induced firing. The network topology determines the synchronization of the firing patterns of the neuronal network, and the change of network topology may induce fruitful synchronization transitions. It is well known that synapses exhibit a high variability with a diverse origin during information transmission, such as the stochastic release of neurotransmitters, variations in chemical concentration through synapses, and spatial heterogeneity of synaptic response over dendrite tree. The collective effect of all of these factors might result in the notion of dynamic synapses. In reality, the neuronal network often involves time delay due to the ?nite signal propagation time in biological networks. Recently, neuronal networks with time delay have received considerable attention. Delay-sustained neuronal firing patterns may be relevant to neuronal networks for establishing a concept of collective information processing in the presence of delayed information transmission. According to the above-mentioned motivations, the firing dynamics of the single postsynapic neuron is investigated based on a simple postsynaptic neuron model by using numerical simulation and Fourier transform analysis. In this model, the postsynapic neuron receives dynamic synaptic currents from a population of presynaptic neurons. It is found that the firing rate resonance between the pre-and postsynaptic neuron determines the firing of the postsynaptic neuron. Stimulus currents in specific frequency range are easy to stimulate postsynaptic neuron firing. The random currents released from dynamic synapses determine the postsynaptic firing rate. Then the single postsynaptic neuron is extended to a neuronal network, in which 100 neurons connect to its 4 nearest neighbors regularly and receive delayed synaptic currents from connected neurons. All the neurons in the network receive the same dynamic synaptic currents from the presynaptic neurons. The results show that the synaptic coupling in the network is able to promote the neuron firing in the network, and time delay in the synaptic coupling could reinforce the promotion, but the mode of the promotion is not changed.

This paper deals with a theoretical analysis and experiments of a non-contact active feedback control, which is based on flow and aero-dynamical control, to suppress a leakage-flow-induced vibration of translational 1DOF system. In the proposed active feedback control method, the leakage-flow-induced vibration is suppressed by using a movable plate, as an actuator, set at inlet and outlet of the passage to control fluid force acting on the controlled target and fluid flow in the passage actively. The strategy of this active control method is based on active flow and aero-dynamical control which cancels the exciting fluid force acting on the rigid body. The root locus and critical flow velocity with and without control are calculated with changing the controller gain and phase-shift to evaluate the control performance, and experiments are conducted to verify the theoretical calculations. As a result, it is indicated that the leakage-flow-induced vibration is effectively suppressed by the proposed non-contact active control method and the suppression effect is very sensitive to the phase-shift and actuator position. For the inlet flow control, the vibration is effectively suppressed when the phase-shift is positive, and for the outlet flow control, the vibration is suppressed when the phase-shift is negative. The suppression effect of the inlet flow control is greater than that of outlet flow control.

Wireless sensor networks (WSNs) are emerging rapidly as a new generation of sensor networks. Despite intensive research in wireless sensor networks (WSNs), limited work has been found in the open literature in the field of WSNs. In particular, quality-of-service (QoS) management in WSNs remains an important issue yet to be investigated. As an attempt in this direction, this paper develops a logic for QoS management (LFQMS) scheme for WSNs with constrained resources and in dynamic and unpredictable environments. Taking advantage of the feedback control technology, this scheme deals with the impact of unpredictable changes in traffic load on the QoS of WSNs. It utilizes a logic controller inside each source sensor node to adapt sampling period to the deadline miss ratio associated with data transmission from the sensor to the sensor. The deadline miss ratio is maintained at a pre-determined desired level so that the required QoS can be achieved. The (LFQMS) has the advantages of generality, scalability, and simplicity. Simulation results show that the (LFQMS) can provide WSNs with QoS support.

Event-driven intermittent feedback control is a form of feedback control in which the corrective control action is only initiated intermittently when the variables of interest exceed certain threshold criteria. It has been reported in the literature that the CNS uses an event-driven intermittent control strategy to stabilize the human upright posture. However, whether the threshold criteria may change under different postural task conditions is not yet well understood. We employ a numerical study with inverted pendulum models and an experimental study with 51 young healthy individuals (13 females and 38 males; age: 27.8 ± 6.5 years) with stabilogram-diffusion, temporal and spectral analysis applied to COP (Center of Pressure) trajectories measured from these experiments to examine this aspect. The present study provides compelling evidence that inducing a natural arm swing during quiet stance appears to lead to higher sensory dead zone in neuronal control reflecting higher intermittency thresholds in active feedback control and a corresponding lower sensory dependence. Beyond the obvious scientific interest in understanding this aspect of how CNS controls the standing posture, an investigation of the said control strategy may subsequently help uncover insights about how control of quiet stance degrades with age and in diseased conditions. Additionally, such an understanding will also be of interest to the humanoid robotics community as it may lead to insights leading to improving control strategies for posture control in robots.

The circuitry mediating top-down control of dopamine (DA) neurons in the ventral tegmental area (VTA) is exceedingly complex. Characterizing these networks will be critical to our understanding of fundamental behaviors, such as motivation and reward processing, as well as several disease states. Previous work suggests that the medial prefrontal cortex (mPFC) exerts a profound influence on VTA DA neuron firing. Recently, our group reported that inhibition of the infralimbic subdivision of the medial prefrontal cortex (ilPFC) increases the proportion of VTA DA neurons that are spontaneously active (i.e., "population activity") and that this effect depends on activity in the ventral subiculum of the hippocampus (vSub). However, there is no direct projection from the mPFC to the vSub. Anatomical evidence suggests that communication between the two structures is mediated by the nucleus reuniens of the midline thalamus (RE). Here, we used in vivo electrophysiological and behavioral approaches in rats to explore the role of the RE in the circuitry governing VTA DA neuron firing. We show that pharmacological stimulation of the RE enhances VTA DA neuron population activity and amphetamine-induced hyperlocomotion, a behavioral indicator of an over-responsive DA system. Furthermore, the effect of RE stimulation on population activity is prevented if vSub is also inhibited. Finally, pharmacological inhibition of ilPFC enhances VTA DA neuron population activity, but this effect does not occur if RE is also inhibited. These findings suggest that disruption of ilPFC-RE-vSub communication could lead to a dysregulated, hyperdopaminergic state, and may play a role in psychiatric disorders. Dopamine (DA) neurons in the ventral tegmental area (VTA) are involved in a variety of fundamental brain functions. To understand the neurobiological basis for these functions it is essential to identify regions controlling DA neuron activity. The medial prefrontal cortex (mPFC) is emerging as a key regulator of DA neuron activity, but the circuitry by which it exerts its influence remains poorly described. Here, we show that the nucleus reuniens of the midline thalamus gates mPFC control of VTA DA neuron firing by the hippocampus. These data identify a unique role for this corticothalamic-hippocampal circuit, and suggest that dysfunction in these regions likely influences the pathophysiology of psychiatric disorders.

Inhalants, including toluene, target the addiction neurocircuitry and are often one of the first drugs of abuse tried by adolescents. The medial prefrontal cortex (mPFC) is involved in regulating goal-directed/reward-motivated behaviors and different mPFC sub-regions have been proposed to promote (prelimbic, PRL) or inhibit (infralimbic, IL) these behaviors. While this dichotomy has been studied in the context of other drugs of abuse, it is not known whether toluene exposure differentially affects neurons within PRL and IL regions. To address this question, we used whole-cell electrophysiology and determined the intrinsic excitability of PRL and IL pyramidal neurons in adolescent rats 24 h following a brief exposure to air or toluene vapor (10 500 p.p.m.). Prior to exposure, fluorescent retrobeads were injected into the NAc core (NAcc) or shell (NAcs) sub-regions to identify projection-specific mPFC neurons. In toluene treated adolescent rats, layer 5/6 NAcc projecting PRL (PRL5/6) neurons fired fewer action potentials and this was associated with increased rheobase, increased spike duration, and reductions in membrane resistance and amplitude of the Ih current. No changes in excitability were observed in layer 2/3 NAcc projecting PRL (PRL2/3) neurons. In contrast to PRL neurons, layer 5 IL (IL5) and layer 2/3 (IL2/3) NAcc projecting neurons showed enhanced firing in toluene-exposed animals and in IL5 neurons, this was associated with a reduction in rheobase and AHP. For NAcs projecting neurons, toluene exposure significantly decreased firing of IL5 neurons and this was accompanied by an increased rheobase, increased spike duration, and reduced Ih amplitude. The intrinsic excitability of PRL5, PRL2/3, and IL2/3 neurons projecting to the NAcs was not affected by exposure to toluene. The changes in excitability observed 24 h after toluene exposure were not observed when recordings were performed 7 days after the exposure. Finally, there were no changes in intrinsic excitability of any region in rats exposed to toluene as adults. These findings demonstrate that specific projections of the reward circuitry are uniquely susceptible to the effects of toluene during adolescence supporting the idea that adolescence is a critical period of the development that is vulnerable to drugs of abuse.

Representation of Spatial Goals in Rat Orbitofrontal Cortex