Multimodal Control Research Articles

Effects of a Multimodal Pain Control Protocol Using 2% Lidocaine Intradermal and Meloxicam Intramuscular on Mitigating Behavioral Castration Pain in Piglets Using a Needleless System

ABSTRACT Mitigating piglet castration pain is critical to minimize negative experiences and contribute to a positive affective state. A multimodal pain control protocol (needleless 2% lidocaine intradermal/0.4 mg/kg meloxicam intramuscular) was evaluated. Males were administered one of four treatments: (1) needleless lidocaine/meloxicam intramuscular (LM), (2) needleless lidocaine/saline intramuscular (LS), (3) needleless saline/meloxicam intramuscular (SM), and (4) needleless saline/saline intramuscular (SS). Females were sham castrated (SH). Piglets were recorded 24h pre-castration (M1) and 15min (M2), 3h (M3), and 24h post-castration (M4). The Unesp-Botucatu Composite Acute Pain Scale (UPAPS) was used to assess pain behavior. From a treatment standpoint, scores did not differ at M1 (P = 1.00) or M4 (P ≥ 0.36). However, at M2, LS piglets had (P < 0.01) higher scores (3.4) than LM piglets (1.6) and SH piglets had (P ≤ 0.01) the lowest scores (0.02). From a timepoint standpoint, piglets in the LS, LM, SM, and SS groups had (P ≤ 0.05) higher scores at M2 compared with their baseline scores at M1. These results indicate that needleless lidocaine and intramuscular meloxicam offered no analgesic benefit.

Quantifying fluid retention following modern pain management in TKA: an observational study

BackgroundBody fluid retention after major surgeries, including total knee arthroplasty (TKA), is well documented in the literature. Currently, multimodal pain control protocols consisting of several medications together with early discharge protocol may magnify this adverse event after a patient’s discharge. However, no study has focused on the quantitative and chronological changes in body fluids following modern pain management protocols for TKA. The aim of this study was to investigate the perioperative total body water (TBW) change in patient undergoing TKA.Patients and methodsA consecutive series of 85 patients undergoing primary unilateral TKA, with uniform hospital admission, multimodal pain control, and rehabilitation protocol, had five consecutive multifrequency bioelectrical impedance analysis (BIA) scans; baseline, postoperative day 1 (POD 1), postoperative day 3 (POD 3), 2 weeks, and 6 weeks. Changes in TBW, body weight, corticosteroid-fluid retention dose–response relationship, and complications were evaluated.ResultsSeventy patients completed all five scans and follow-ups. Female patients were dominant, with a mean age of 69.5 years. There were no perioperative complications. At 24 h, the mean total fluid input and output were 3695.14 mL and 1983.43 mL, respectively, with 1711.71 mL increments and a mean accumulative dosage of dexamethasone of 15.14 mg. The mean TBW increased by 2.61 L on POD 1 and continued to peak at 3.2 L on POD 3, then gradually decreased at 2 weeks and reached the baseline level at 6 weeks postoperatively. Similarly, the mean body weight increased to 2.8 kg on POD 1, reached the maximum point at 3.42 kg on POD 3, and returned to baseline at 6 weeks.ConclusionsFluid retention following multimodal pain control in TKA increased from POD 1, peaked on POD 3, and gradually returned to the baseline at 6 weeks. With early discharge protocol, patient education regarding fluid retention after discharge should be considered.

Efficacy of Antimicrobial Dry Fog in Improving the Environmental Microbial Burden in an Inpatient Ward

Background/Objectives: In healthcare environments with high microbial loads, effective infection control measures are critical for reducing airborne and surface contamination. One of the novel modalities in the achievement of these goals is the use of antimicrobial mists, such as droplets, in the form of dry fog. Although the usage of dry fog in the disinfection of contained healthcare microenvironments is well known, the effect of such a system in terms of a meaningful reduction in the microbial burden in an open inpatient ward is unclear. Our objective was to assess the impact of scheduled dry fogging on microbial reduction in such settings. Methods: We collected air and surface samples from rooms receiving daily, biweekly, or no fogging (controls) over six months, establishing the baseline contamination and evaluating the reduction trends in treated rooms. The “reduction effect” was measured by tracking microbial isolation trends before and after treatment, while the “degree of reduction” assessed differences across rooms with varied disinfection schedules. Results: The results indicate that scheduled dry fogging significantly reduced microbial loads in treated rooms, especially with daily disinfection (SE = 64.484, p = 0.002). The airborne contamination in treated rooms showed a strong downward trend over time (SE = 19.192, p &lt; 0.001). Surface contamination remained challenging due to frequent recontamination; however, treated rooms exhibited a consistent reduction in microbial presence (SE = 2.002, p = 0.010), confirming dry fogging’s role as a valuable adjunct to routine cleaning. Conclusions: In conclusion, this study highlights that dry fogging effectively reduces microbial loads in open, high-traffic healthcare environments, supporting its use as part of a multimodal infection control strategy.

Multimodal Human–Robot Interaction Using Gestures and Speech: A Case Study for Printed Circuit Board Manufacturing

In recent years, technologies for human–robot interaction (HRI) have undergone substantial advancements, facilitating more intuitive, secure, and efficient collaborations between humans and machines. This paper presents a decentralized HRI platform, specifically designed for printed circuit board manufacturing. The proposal incorporates many input devices, including gesture recognition via Leap Motion and Tap Strap, and speech recognition. The gesture recognition system achieved an average accuracy of 95.42% and 97.58% for each device, respectively. The speech control system, called Cellya, exhibited a markedly reduced Word Error Rate of 22.22% and a Character Error Rate of 11.90%. Furthermore, a scalable user management framework, the decentralized multimodal control server, employs biometric security to facilitate the efficient handling of multiple users, regulating permissions and control privileges. The platform’s flexibility and real-time responsiveness are achieved through advanced sensor integration and signal processing techniques, which facilitate intelligent decision-making and enable accurate manipulation of manufacturing cells. The results demonstrate the system’s potential to improve operational efficiency and adaptability in smart manufacturing environments.

Multi-Modal and Adaptive Robot Control through Hierarchical Quadratic Programming

This paper proposes a novel Hierarchical Quadratic Programming (HQP)-based framework that enables multi-tasking control under multiple Human-Robot Interaction (HRI) scenarios. The proposed controllers’ formulations are inspired by real-world contact-rich scenarios, which currently constitute one of the main limitations in terms of widespread practical deployment. Indeed, HRI can occur through different modalities, based on human’s needs. The objective is to create a unique framework for various types of possible interactions, avoiding the necessity of switching between different control architectures, which requires dealing with discontinuities. To achieve this, we firstly propose a HQP-based hybrid Cartesian/joint space impedance control formulation. Based on the robot’s dynamics, this controller enables an adaptive compliance behaviour, while achieving hierarchical motion control. This is validated through a series of experiments that show the accuracy of trajectory tracking, which remains in the order of 10mm during fast motions thanks to the addition of the robot dynamics. Besides, the hybrid compliance behaviour allows to deviate from such accuracy when an interaction is present. We then consider the case in which the human needs to move the robot directly, by proposing a hybrid admittance/impedance controller, that is again based on a HQP formulation and provides inherent softening when conflicting tasks are present, or in close-to-limit and near-singular configurationsa. This is validated through several experiments in which the human easily moves the robot in the workspace via direct physical interaction. Next, we formulate an additional hierarchy that enables force control and allows to maintain a specific interaction force at the end effector. We then extend this to simultaneous force and trajectory tracking. Overall, we obtain a multi-purpose HQP-based control framework, that seamlessly switchwes between interaction modes, enabling multiple hierarchical behaviours, and covering a wide spectrum of interaction types, essential for synergistic HRI.

Adaptive Control of Multimodal Permanent Magnet Synchronous Motor Based on Embedded Neural Network

Permanent magnet synchronous motors (PMSMs) occupy a core position in various industrial and household equipment due to their excellent energy efficiency, high-power density, and low-noise characteristics. However, facing dynamic factors such as load fluctuations, environmental temperature changes, and manufacturing tolerances, the stability and optimization of its operational efficiency have become a major challenge. To address these issues, this study innovatively proposes a multimodal adaptive control strategy based on embedded neural networks, aiming to enhance the adaptability of PMSM to complex working environments through intelligent learning and optimized decision-making. The core of the research is to construct a control system based on embedded neural networks, which can capture the characteristics of PMSM in different operating modes in real time and learn the corresponding optimal control strategy. The advantages of embedded neural networks lie in their compact model design and efficient computing power, making them highly suitable for resource-constrained motor control systems. Through multimodal learning, the system can recognize and adapt to various states of motor operation, such as start-up, acceleration, steady-state operation, and deceleration, thereby achieving precise control of motor performance.

A Multi-Mode Pressure Stabilization Control Method for Pump–Valve Cooperation in Liquid Supply System

In order to solve the problems of frequent pressure fluctuations caused by frequent action of the unloading valve of the pump station and serious hydraulic shock due to the variable amount of fluid used in the hydraulic support system of the coal mining face and the irregularity of the load suffered by the system, a pump–valve cooperative multi-mode stabilizing control method based on a digital unloading valve was proposed. Firstly, a prototype of a digital unloading valve under high-pressure and high water-based conditions was developed, and a digital control scheme was proposed to control the pilot valve by a servo motor to adjust the system pressure in real time. Then, an experimental platform for simulating the hydraulic bracket and a co-simulation model was constructed, and the validity of the co-simulation model was verified through experiments. Secondly, a collaborative multi-mode pressure stabilization control method for the pump valve based on a GRNN (General Regression Neural Network) was established to control the flow and pressure output of the emulsion pumping station according to the actual working conditions. Finally, numerical research and experimental verification were carried out for different working conditions to prove the effectiveness of this method. The results showed that the proposed pressure stabilization control method could adaptively adjust the working state of the digital unloading valve and the liquid supply flow of the emulsion pump station according to the working condition of the hydraulic support, effectively reducing the frequency and amplitude of the system pressure fluctuations and making the system pressure more stable.

The neurologically intact patient with TLICS 4 or 5 burst fracture should be given a trial of nonoperative management.

Thoracolumbar burst fracture treatment in neurologically intact patients is controversial with many classification systems to help guide management. Thoracolumbar Injury Classification and Severity score (TLICS) provides a framework, but evidence is limited, and recommendations are primarily based on expert opinion. In this retrospective cohort study, data was reviewed for patients with thoracolumbar burst fractures at a Level-1 Trauma Center in New England from 2013 to 2018. Neurologically intact patients without subluxation/dislocation on supine computed tomography were included. Multimodal pain control and early mobilization were encouraged. Patients that failed to mobilize due to pain were treated with operative stabilization. Outcome measures include degree of kyphosis, visual analog scale pain scores, and neurological function. Thirty-one patients with thoracolumbar burst fractures with TLICS scores of 4 or 5 were identified, of which 21 were treated nonoperatively. Kyphosis at final follow-up was 26.4 degrees for the nonoperative cohort versus 13.5 degrees for the operative group (P < .001). Nonoperative patients tended towards shorter hospital lengths-of-stay (3.0 vs 7.1 days, P = .085) and lower final pain scores (2.0 vs 4.0, P = .147) compared to the operative group. Two patients (6%) developed radicular pain with mobilization, which resolved after surgical intervention. No patients experienced decline in neurologic function. A trial of mobilization for neurologically intact TLICS grade 4 and 5 thoracolumbar burst fractures is a safe and reasonable treatment option that resulted in successful nonoperative management of 21 out of 31 (68%) patients.

PLC based laser scanning system for conveyor belt surface monitoring

This paper presents the design, implementation, and testing of an advanced conveyor belt surface monitoring system, specifically engineered for harsh and complex industrial environments. The system integrates multiple cutting-edge technologies, including programmable logic controllers (PLC), laser scanning, industrial-grade cameras, and deep learning algorithms, particularly YOLOv7, to achieve real-time, high-precision monitoring of conveyor belt conditions. Key innovations include optimized detection location based on failure modes, advanced PLC integration for seamless automation, and intelligent dust-proof features to maintain accuracy in challenging conditions. Through strategic placement of detection devices and multi-mode control strategies (local, remote, and automatic), the system offers unparalleled adaptability and responsiveness. The system leverages robust data management for trend analysis and predictive maintenance, enhancing operational efficiency. The hardware architecture comprises PLC-based control systems, high-resolution industrial cameras, and laser emitters, while the software features a two-tier structure combining human-machine interaction (HMI) with real-time data processing capabilities. Experimental results show that the system is highly effective in detecting common belt defects such as foreign objects, tears, and shallow scratches, ensuring optimal operational efficiency and minimizing downtime. The system’s scalability, robust data management, and adaptability to low-light and dusty conditions make it ideal for deployment in large-scale industrial operations, where continuous monitoring and early fault detection are critical to maintaining productivity and safety.

Multi-modal recognition control system for real-time robot welding penetration control and quality enhancement

Multi-modal recognition control system for real-time robot welding penetration control and quality enhancement

Hydrogen production efficiency enhancement for alkaline water electrolyzers operating at varying temperature via an adaptive multi-mode control

The low-load efficiency performance of alkaline water electrolyzers (AWEs) is poor so its operation range is limited. It is unfeasible for AWEs to follow the fluctuant renewable energy sources (RESs). Besides, the power fluctuation will lead to the electrolyzer temperature variation. The efficiency performance is negatively influenced. Focusing on these problems, an efficiency enhancement control strategy for AWEs operating at varying temperature is introduced in this paper. First, the efficiency model of AWEs is established. Then, a multi-mode adaptive control strategy is proposed to improve the hydrogen production efficiency of AWEs. Based on the U–I curves of AWEs, parameter identification method is used to obtain the key parameters of proposed efficiency model. Finally, the feasibility of the control strategy is experimentally validated on a 10 kW AWE. The experimental outcome shows that by applying the proposed method, the low-load hydrogen production efficiency of AWEs can be improved at different temperatures. At 15% rated load, the electrolyzer efficiency increases from 21.54% to 42.73% at 80°C. The operation range of the electrolyzer can be extended from 30% to 100%–21%∼100% of rated load at 80°C.© 2024 The Authors. Published by Elsevier Ltd.

Postoperative Opioid Reduction Using a Multimodal Pain Protocol for Outpatient Orthopaedic Sports Medicine Surgery.

Orthopaedic surgery regularly employs opioids for postoperative pain management. Multimodal pain protocols have been shown to reduce opioid prescriptions in orthopaedic surgery. To analyze the impact of a division-level multimodal pain protocol for orthopaedic sports medicine surgery on opioid prescription reduction and pain level postoperatively. Cohort study; Level of evidence, 3. All orthopaedic sports medicine procedures at a military treatment facility were categorized into 1 of 3 pain tiers. A pain protocol emphasizing multimodal pain control was implemented for each tier. A retrospective cohort study compared pre- and postprotocol pain groups for each respective tier (n = 40 in each) for visual analog scale (VAS) for pain scores 2 weeks postoperatively, postoperative opioid prescription, and time to discontinuation of postoperative opioids. The mean number of opioid pills prescribed for all tiers decreased by 43.6% (preprotocol 35.7 ± 3.1; postprotocol 20.1 ± 1.5; P < .0001) after pain protocol implementation. Of the total opioids prescribed in the postprotocol cohort, a mean of 64.1% were consumed. There was no significant difference in overall visual analog scale for pain scores at 2 weeks postoperatively (preprotocol 2.72 ± 0.41; postprotocol 2.99 ± 0.43; P = .40). At 2 weeks postoperatively, only 1 patient continued opioids in the postprotocol group compared with 20 patients with continued opioid use in the preprotocol group (P < .001). A division-level multimodal pain protocol applied to orthopaedic sports medicine procedures led to decreased opioid prescription postoperatively with no significant difference in 2-week postoperative pain scores compared with more opioid reliant and variable protocols in a cohort of military service members. Despite the reduced prescription, patients consumed a mean of 64.1% of pills, indicating continued overprescription.

Multi-modal vibration control method combining modal decoupling and active disturbance rejection for wind tunnel models

When excited by broadband wind load, the wind tunnel model support system with low stiffness and damping is easy to produce multi-modal coupling vibration. It not only leads to inaccurate experimental data but also has potential safety hazards. Therefore, to ensure the reliable development of wind tunnel tests, a multi-modal vibration control method with multi-damping is proposed. Firstly, a multi-damping vibration suppression structure is designed based on the vibration analysis results. Next, the modal filter is designed by identifying the modal decoupling matrix, which can get the independent feedback signals of each mode. Then, considering the external disturbance of the environment and the internal disturbance between dampers, a multi-modal linear active disturbance rejection controller is designed to control the vibration and total disturbance. Finally, the multi-modal vibration suppression system of the UAV model is built, and the sweep frequency identification and hammering experiment are carried out. The results show that the proposed method can reduce the power spectral density of the first and second modes by 42.500 dB/Hz and 12.442 dB/Hz respectively, and increase the damping ratio by 14.659 times and 2.898 times respectively. Compared with the traditional control methods, the proposed method possesses obvious advantages in multi-modal vibration control. Therefore, ensured that wind tunnel tests were conducted smoothly.

Successful control of an environmental reservoir of NDM-producing Klebsiella pneumoniae associated with nosocomial transmissions in a low-incidence setting

BackgroundThe hospital wastewater system has been reported as a source of nosocomial acquisition of carbapenemase producing Enterobacteriaceae (CPE) in various settings. Cleaning and disinfection protocols or replacement of contaminated equipment often fail to eradicate these environmental reservoirs, which can lead to long-term transmission of CPE. We report a successful multimodal approach to control a New Delhi metallo-beta-lactamase positive Klebsiella pneumoniae (NDM-KP) nosocomial outbreak implicating contamination of sink traps in a low-incidence setting.MethodsFollowing the incidental identification of NDM-KP in a urine culture of an inpatient, we performed an epidemiological investigation, including patient and environmental CPE screening, and whole genome sequencing (WGS) of strains. We also implemented multimodal infection prevention and control (IPC) measures, namely the isolation of cases, waterless patient care, replacement of contaminated P-traps and connecting pieces, and bleach and steam disinfection of sinks for 6 months, followed by patient and environmental screenings for eradication.ResultsBetween February and May 2022, five NDM-KP cases were identified in an eight-bed neurosurgical intermediate care unit. Among the eight sink traps of the unit, three were positive for NDM-KP. Patient and environmental isolates belonged to multilocus sequence typing ST-268. All isolate genomes were genetically very similar suggesting cross-transmission and a potential role of the environment as the source of transmissions. Following the introduction of combined IPC measures, no new case was subsequently detected and sink traps remained negative for NDM-KP within 6 months after the intervention.ConclusionThe implementation of multimodal IPC measures, including waterless patient care combined with the replacement and disinfection of P-traps and connecting pieces, was successful in the control of NDM-KP after eight months. In a low-incidence setting, this approach has made it possible to pursue the objective of zero transmission of carbapenemase-producing Enterobacteriaceae (CPE).

Adaptive multimodal control of trans-media vehicle based on deep reinforcement learning

To solve the problem that the control system is prone to instability due to the sudden change of physical characteristics, strong interference, and nonlinear in the process of multimodal movement of trans-media vehicle, an adaptive control method combining the Deep Deterministic Policy Gradient (DDPG) and traditional Proportional-Integral-Derivative (PID) controller is proposed in this paper. In this approach, the upper-level DDPG controller continuously monitors the vehicle's state and environmental conditions, dynamically adjusting the PID parameters in real-time. The lower-level PID controller then utilizes these updated parameters to modulate the output thrust of the vehicle's motors, thereby achieving excellent control over the vehicle's entire movement. Firstly, according to the hydrodynamic analysis, the kinematics and dynamics mathematical model of the self-designed trans-media vehicle is constructed. This model includes the multi-stage motion modal process of aerial flight, underwater navigation, and cross-media motion, which is suitable for the simulation and verification of the control method. Then, an adaptive controller called RL-PID combining DDPG and PID is built, so that PID can adjust parameters in real-time according to the changes in the external environment. Finally, after theoretical stability proof, a comparison study is performed across three approaches, namely the novel RL-PID, Fuzzy PID, and PID. The experimental results illustrate the superiority of the proposed approach over the competing ones and the generalization of the proposed approach under different interference.

Multi-modal response control with multiple suspension-type tuned vibration absorbers

Due to complicated excitations, engineering structures are often subjected to multi-modal responses. Considering the feasibility in practical installation on slender structures, multiple Suspension-type Tuned Vibration Absorbers (S-TVAs) are investigated for multi-modal response control. Firstly, parametric optimization of a single S-TVA for single-modal response control is investigated analytically. The issues regarding to the optimal tuning, static and dynamic performances, and installation location are addressed. Subsequently, an optimal design method for multi-modal response control with multiple S-TVAs is presented. Two aspects on the optimization strategy are discussed. Consequently, the optimization should be performed with an inverse modal order sequence. And, the modal information should be updated considering the S-TVA optimized in the previous step. Finally, the effectiveness of the presented optimal design method is validated through practical wind-induced response control on a slender chimney. The most unfavorable response can be suppressed up to 59.7 %, which is 47.8 % better than traditional single-modal control approach. Moreover, it is interesting to find that the practical overall control performance may not be achieved with more controlled modes intuitively. It is recommended to select from several practical cases determined by the presented optimal design method. Practical installation and feasibility are highly required to be considered in practice.

Energy consumption analysis of trains based on multi-mode virtual coupling operation control strategies

Urban rail transit, as a main mode of travel, has always been concerned with the balanced relationship between energy consumption and transport efficiency. The advent of the virtually coupled train set (VCTS) has significantly enhanced the efficiency of existing railway lines. Both energy consumption and comfort during the operation of VCTS control technology have emerged as significant challenges for the development of VCTS since the inception of onsite testing. A review of the current research status of VCTS control systems has revealed that the majority of current formation control systems are focused on the safe operation of formation trains, the stability of train control systems, and safe train separation models. However, a case study has shown there is a strong correlation between train operating intervals, train control strategies, and train operating energy consumption. Therefore, it is necessary to design and plan the operation modes of formation trains for different train operation requirements. This paper presents four distinct control modes, developed through the integration of the most prevalent VCTS control strategies, operational modes, and operational requirements. The design of these control modes is guided by considerations of energy consumption, safety, and comfort during train operation. A case study of Beijing Subway Line 11 revealed a significant correlation between energy consumption, control mode, and safety under different control modes. In particular, the correlation between train running intervals and energy consumption in a high-precision tracking state provides valuable technical support for the future operation of VCTS technology in different periods, scenarios, and environments.

Time response of active sound control with a harmonic acoustic pneumatic source: simulations and experimental results

Active noise control is studied as a solution to reduce the blade passing frequency tonal noise of turbofans during landing and takeoff. A promising alternative to loudspeakers used as secondary sources is the Harmonic Acoustic Pneumatic Source (HAPS), that has been designed to generate a high harmonic noise level controllable in amplitude and phase using slow time varying signals. The objective is to design, characterize and optimize an active control system capable of following a time varying primary noise. A configuration with a loudspeaker acting as a primary source, a HAPS mounted laterally on a rectangular duct and an error microphone is considered. A first single-input-single-output controller for the case of plane wave control has been tested and allowed a convergence time of about 2 seconds to reach 20 dB attenuation of the acoustic pressure at 440 Hz. The results are consistent with simulations of the system and the convergence time can be explained by the dynamics of the HAPS. This study is a first step towards the objective of performing multimodal active noise control in duct with multiple sources in presence of flow.

On the use of multiple vibroimpact absorbers for multimodal vibration control

Vibroimpact absorption is a vibration attenuation strategy that consists of transferring the energy of a vibrating structure to high frequencies during impacts with a secondary oscillating mass. The energy transferred is dissipated, and the process thus generated is irreversible. The efficiency of a single absorber has been the subject of various experimental and numerical studies, and the aim here is to investigate the performance of a multiple configuration. To this end, a case study consisting of an aircraft wing model has been fitted with a network of absorbers whose properties in gap and position can be modified. By optimizing these properties, it has been shown that it is possible to simultaneously control several modes and improve attenuation efficiency.

Size-reduced DREADD derivatives for AAV-assisted multimodal chemogenetic control of neuronal activity and behavior

Designer receptors exclusively activated by designer drugs (DREADDs) are engineered G-protein-coupled receptors that afford reversible manipulation of neuronal activity invivo. Here, we introduce size-reduced DREADD derivatives miniDq and miniDi, which inherit the basic receptor properties from the Gq-coupled excitatory receptor hM3Dq and the Gi-coupled inhibitory receptor hM4Di, respectively, while being approximately 30% smaller in size. Taking advantage of the compact size of the receptors, we generated an adeno-associated virus (AAV) vector carrying both miniDq and the other DREADD family receptor (κ-opioid receptor-based inhibitory DREADD [KORD]) within the maximum AAV capacity (4.7 kb), allowing us to modulate neuronal activity and animal behavior in both excitatory and inhibitory directions using a single viral vector. We confirmed that expressing miniDq, but not miniDi, allowed activation of striatum activity in the cynomolgus monkey (Macaca fascicularis). The compact DREADDs may thus widen the opportunity for multiplexed interrogation and/or intervention in neuronal regulation in mice and non-human primates.