Potential Field Research Articles

Fault structure and hydrocarbon prospects of the Palawan Basin on the southeastern margin of the South China Sea based on gravity, magnetic, and seismic data

To study the structural features and hydrocarbon prospects of the Palawan Basin in the South China Sea (SCS), the authors collect and collate the existing gravity and magnetic data and obtain edge recognition information from the potential fields. Combined with the seismic profile data, this paper analyzes the features of the gravity and magnetic anomalies and the edge recognition information of the potential fields, determines the fault system, and delineates favorable areas for oil and gas exploration in the Palawan Basin. The results indicate that four main groups of faults with northeast, northwest, near east–west, and near south–north trends developed in the Palawan Basin and adjacent areas in the SCS. The northeast-trending fault is the regional fault, whereas the northwest-trending fault is the main fault. The northwest-trending fault often terminated at the northeast-trending fault, indicating that the northwest-trending fault is formed subsequently. This investigation has characterized two different types of exploration favorable areas (type I and type II) based on the characteristics observed. The most notable characteristic of these exploration favorable areas is that they are located in the high-value zones of the local anomaly of the Bouguer gravity anomaly and their development is obviously controlled by the faults. The amplitude of the gravity anomalies is higher and the gradient of the gravity anomalies is steeper, and there are oil and gas wells and fields distributed in the type I favorable areas for exploration. Compared with the type I favorable areas, the amplitude of gravity anomalies is relatively small, and the gradient of the gravity anomalies is relatively gentle, corresponding to the type II favorable areas.

Adenosine mediates the amelioration of social novelty deficits during rhythmic light treatment of 16p11.2 deletion female mice.

Non-invasive brain stimulation therapy for autism spectrum disorder (ASD) has shown beneficial effects. Recently, we and others demonstrated that visual sensory stimulation using rhythmic 40 Hz light flicker effectively improved cognitive deficits in mouse models of Alzheimer's disease and stroke. However, whether rhythmic visual 40 Hz light flicker stimulation can ameliorate behavioral deficits in ASD remains unknown. Here, we show that 16p11.2 deletion female mice exhibit a strong social novelty deficit, which was ameliorated by treatment with a long-term 40 Hz light stimulation. The elevated power of local-field potential (LFP) in the prefrontal cortex (PFC) of 16p11.2 deletion female mice was also effectively reduced by 40 Hz light treatment. Importantly, the 40 Hz light flicker reversed the excessive excitatory neurotransmission of PFC pyramidal neurons without altering the firing rate and the number of resident PFC neurons. Mechanistically, 40 Hz light flicker evoked adenosine release in the PFC to modulate excessive excitatory neurotransmission of 16p11.2 deletion female mice. Elevated adenosine functioned through its cognate A1 receptor (A1R) to suppress excessive excitatory neurotransmission and to alleviate social novelty deficits. Indeed, either blocking the A1R using a specific antagonist DPCPX or knocking down the A1R in the PFC using a shRNA completely ablated the beneficial effects of 40 Hz light flicker. Thus, this study identified adenosine as a novel neurochemical mediator for ameliorating social novelty deficit by reducing excitatory neurotransmission during 40 Hz light flicker treatment. The 40 Hz light stimulation warrants further development as a non-invasive ASD therapeutics.

Trust region framework-based design of sub-6 GHz m-MIMO antenna and evaluation of SAR

Purpose Currently, massive multiple-input multiple-output (m-MIMO) antennas are typically designed using complex trial-and-error methods. The purpose of this study is to determine an effective optimization method to achieve more efficient antenna design processes. Design/methodology/approach This paper presents the design stages of a m-MIMO antenna array compatible with 5G smartphones operating in long term evolution (LTE) bands 42, 43 and 46, based on a specific algorithm. Each antenna element in the designed 10-port m-MIMO antenna array is intended to perfectly cover the three specified LTE bands. The optimization methods used for this purpose include the Nelder–Mead simplex algorithm, covariance matrix adaptation evolution strategy, particle swarm optimization and trust region framework (TRF). Findings Among the primary optimization algorithms, the TRF algorithm met the defined objectives most effectively. The achieved antenna efficiency values exceeded 60.81% in the low band and 68.39% in the high band, along with perfect coverage of the desired bands, demonstrating the success of the design with the TRF algorithm. In addition, the potential electromagnetic field exposure caused by the designed m-MIMO antenna array is elaborated upon in detail using computational human models through specific absorption rate analysis. Originality/value The comparison of four different algorithms (two local and two global) for use in the design of a 10-element m-MIMO antenna array with a complex structural configuration and the success of the design implemented with the selected algorithm distinguish this study from others.

The Impact of CSI SEEE Carbon Neutral Index Launched on Order Aggressiveness

In the context of carbon peaking and carbon neutrality goals, in order to clarify the investment direction for investors, China Securities Index Co., Ltd. (CSI) has collaborated with the Shanghai Environmental Energy Exchange to develop the CSI SEEE Carbon Neutral Index (CSCNI), which has also played a leading role in the subsequent preparation of the Green Finance Index. The launch of this index has sparked research interest among scholars in stimulating investor order aggressiveness. This study employs event study methodology to examine the impact of the CSCNI launch on order aggressiveness. The sample companies are categorized into two groups: deep low-carbon and high-carbon reduction, with a focus on studying buy and sale order aggressiveness. The results indicate that the launch of CSCNI has mobilized order aggressiveness but has led to a negative stock price effect as investors anticipate an increase in environmental costs for the sample companies. Furthermore, we reveal that the long-term growth potential of the deep low-carbon field is more promising compared to the high-carbon reduction sector, making stocks in the deep low-carbon field more attractive. The launch of CSCNI has shown contrasting effects on the buy and sale order aggressiveness of investors, with the impact of the index announcement being more significant on the sample companies. This research provides valuable insights for evaluating the impact of green finance indices and contributes to the understanding of internal mechanisms. It provides an important reference for financial regulators to evaluate the development of the current green index. At the same time, it expands the domestic research on order aggressiveness, which studies the action mechanism of the stock price effect of the green stock index from the perspective of order aggressiveness.

Geochemical and geochronologic evidence for a contiguous northeastern Wyoming Province

The extent and nature of the Wyoming Province, an Archean craton in southwestern Laurentia, are poorly understood due to limited exposure between spatially isolated basement-cored uplifts. This lack of exposure has led to debate about whether the northeastern Wyoming Province is underlain by contiguous Archean crust or Proterozoic rocks and suture zone associated with the Trans-Hudson orogeny. To assess these models we analyzed samples recovered from drill cores in the buried northeastern Wyoming Province that straddle the proposed Proterozoic suture. Whole-rock geochemical and Nd-Pb-O isotopic data suggest the rocks formed by partial melting of > 3.5 Ga hydrated mafic to tonalitic sources similar to elsewhere in the northern Wyoming Province. Zircon U-Pb dates record Mesoarchean magmatism and metamorphism (3.0–2.8 Ga). Published whole-rock Rb-Sr, hornblende and biotite K-Ar, and apatite fission track dates suggest these rocks have not been heated above 300 °C since 2.5–2.1 Ga. Geophysical potential field data are consistent across northeastern Wyoming contrasting with major discontinuities associated with documented Proterozoic orogens on all other margins of the Wyoming Province. Hence, geochemical, isotopic, and geochronologic data along with geophysical imaging can be most simply interpreted in terms of continuous Archean crust in the northeastern Wyoming Province. A geophysically-imaged reflector east of the Bighorn Mountains may juxtapose Archean terranes with similar ages and sources, similar to the boundary between the Montana metasedimentary terrane and Beartooth-Bighorn magmatic zone in the northwestern Wyoming Province. This work emphasizes the value of integrating geologic and geophysical constraints to constrain Archean provinces and their tectonic evolution.

Gut Microbiota and Immune System in Necrotizing Enterocolitis and Related Sepsis

A severe condition of sepsis can be a complication of necrotizing enterocolitis (NEC), which can occur in premature infants and becomes a medical challenge in the neonatal intensive care unit (NICU). It is a multifactorial intestinal disease (can affect both the small and large intestine) that can lead to ischemia of the intestinal tissues that evolves into acute organ necrosis. One of these factors is that different types of nutrition can influence the onset or the progression of the disease. Cow-milk-based infant formulas have been shown to cause it in premature infants more frequently than human milk. Recently, nutrition has been shown to be beneficial after surgery. Several issues still under study, such as the pathogenesis and the insufficient and often difficult therapeutic approach, as well as the lack of a common and effective prevention strategy, make this disease an enigma in daily clinical practice. Recent studies outlined the emerging role of the host immune system and resident gut microbiota, showing their close connection in NEC pathophysiology. In its initial stages, broad-spectrum antibiotics, bowel rest, and breastfeeding are currently used, as well as probiotics to help the development of the intestinal microbiota and its eubiosis. This paper aims to present the current knowledge and potential fields of research in NEC pathophysiology and therapeutic assessment.

Neurophysiological features of STN LFP underlying sleep fragmentation in Parkinson’s disease

BackgroundSleep fragmentation is a persistent problem throughout the course of Parkinson’s disease (PD). However, the related neurophysiological patterns and the underlying mechanisms remained unclear.MethodWe recorded subthalamic nucleus (STN) local field...

An asymmetric orifice-based active micromixer in the microfluidic chip with 3D microelectrode

The fluid mixing in microscale is central to the development of flow patterns in microfluidic chips for particles separation and biological analysis. Yet, as the size of the fluid decreases, the mixing becomes challenging to change this state of flow. In this work, a novel active micromixer for enhancing the mixing performance in the micromixer with asymmetric orifices is presented. To induce the electric-driven micromixing, an AC electric field is employed to the inserted 3D microelectrodes to produce the local electric field through the asymmetric orifices located on the opposite channel walls, which is perpendicular to the main microchannel. Then the mixing experiments were conducted in a microfluidic chip comprising microelectrode with asymmetric orifices, specifically exploiting the mixing efficiency varying with the asymmetric orifice pairs, applied electric potential and frequency of the AC electric field, and flow rate. The bending degree of the mixing interface was calculated and found increasing as a function of applied electric voltage at a given AC frequency, thus enabling effective mixing crossing the microelectrode's area. The predictions are confirmed by optical microscopy experiments and the micromixing can be significantly improved as they experience longer-exposed electrical forces. The integration of multiple asymmetric orifices leads a larger zone to increase mixing efficiency and makes it a promising method for rapid and stable fluid mixing in microscale.

Multi-scene application of intelligent inspection robot based on computer vision in power plant

As industries develop, the automation and intelligence level of power plants is constantly improving, and the application of patrol robots is also increasingly widespread. This research combines computer vision technology and particle swarm optimization algorithm to build an obstacle recognition model and obstacle avoidance model of an intelligent patrol robot in a power plant respectively. Firstly, the traditional convolutional recurrent neural network is optimized, and the obstacle recognition model of an intelligent patrol robot is built by combining the connection timing classification algorithm. Then, the artificial potential field method optimizes the traditional particle swarm optimization algorithm, and an obstacle avoidance model of an intelligent patrol robot is built. The performance of the two models was tested, and it was found that the highest precision, recall, and F1 values of the identification model were 0.978, 0.974, and 0.975. The highest precision, recall, and F1 values of the obstacle avoidance model were 0.97, 0.96, and 0.96 respectively. The two optimization models designed in this research have better performance. In conclusion, the two models in this study are superior to the traditional methods in recognition effect and obstacle avoidance efficiency, providing an effective technical scheme for intelligent patrol inspection of power plants.

A collision-avoidance decision-making scheme based on artificial potential fields and event-triggered control

In this paper, a collision-avoidance decision-making scheme is proposed based on improved artificial potential field (APF) and event-triggered nonlinear model predictive control. A calculation model is used to calculate the collision avoidance dynamic parameters between ships. In accordance with relevant rules of the International Regulations for Preventing Collisions at Sea (COLREGs), abovementioned collision avoidance parameters are used as the main index and applied to construct the repulsive potential field. Then, an anti-collision decision-making scheme is developed by incorporating event-triggered mechanism and improved APF method into the nonlinear model predictive control algorithm. Based on improved repulsive potential field, heading of the ship and orientation of the target point, the event-triggered conditions are set to save considerable computational resources. Following this approach, optimal collision avoidance actions in line with COLREGs is realised, and the adverse effects of ignoring the manoeuvrability characteristics of ships in the process of preventing collisions are eliminated. Finally, simulation examples verify the effectiveness and rationality of the proposed scheme for multi-ship encounter scenarios.

Trajectory Planning for Autonomous Formation of Wheeled Mobile Robots via Modified Artificial Potential Field and Improved PSO Algorithm

This paper addresses two substantial aspects in the field of robotics: trajectory planning and trajectory tracking for multi-robot systems. The collective movement of the multi-wheeled mobile robots is based on a formation control with a leader–follower strategy. To ensure safe navigation toward the destination within a workspace containing multiple obstacles, we skillfully combine the Modified Artificial Potential Field (MAPF) method and the Improved Particle Swarm Optimization (IPSO) algorithm for a group of nonholonomic mobile robots. A global planner based on IPSO algorithm is assigned to the leader robot, to find the optimal collision-free path. Compared to recent nature-inspired methodologies, the improvement suggested enhance the search capabilities of the algorithm, resulting in a 2% reduction in path length and a 29% decrease in computation time. Simultaneously, the follower robot has the ability to employ either a formation policy or a local planner using MAPF. The proposed modifications address the primary limitations of the conventional method, notably the susceptibility to local minima and the challenge of reaching goals near obstacles. Furthermore, this local planner is adept at evading both static and dynamic obstacles. Extensive real hardware experiments are conducted within multiple scenarios using the mobile robot Qbot-2e to corroborate the obtained simulation results and validate the effectiveness of the proposed approaches both in tracking the desired trajectories, finding the optimal feasible collision-free path and avoiding static and dynamic obstacles for multi-robot systems.

Strategic threat health response in Australia capital cities: Predicting the optimum locations for field hospitals through geospatial analysis

AbstractObjectiveThe advent of the COVID‐19 pandemic has accentuated the critical importance of epidemic preparedness within national healthcare systems. This study presents a geospatial analysis aimed at optimising the placement of field hospitals in Australia to ensure adequate healthcare access during pandemics.MethodsThe latest census data from the Australian Bureau of Statistics were integrated with the spatial locations of current emergency departments within Australian capitals. Buffer zones with a 7.5 km radius were created around the public emergency departments (EDs). Buffer zones outside the 7.5 km radius that exhibited high population densities were categorised into high‐density (red), moderate‐density (yellow) and low‐density (green) zones to prioritise and tailor healthcare responses during a pandemic. The identification of high‐density population areas outside the ED radius enabled the stratification of potential sites for ED facilities.ResultsNinety‐one potential field hospital sites were identified across Australia's capital cities. The findings indicate that the addition of these sites would place over 95% of the population within a 7.5 km radius of an ED facility. This network of proposed sites is designed to serve a spectrum of population densities, ensuring equitable healthcare access for both densely populated urban centres and less populated areas.ConclusionsThis study underscores the potential of field hospitals to strengthen Australia's public health system against emergencies. By advocating for the creation of 91 field hospitals within a 7.5 km reach for over 95% of urban dwellers across major cities, it demonstrates a strategic approach to ensure comprehensive ED coverage. Drawing on international examples, including China's Fangcang hospitals, the USA's post‐acute care (PAC) facilities and the United Kingdom's National Health Service (NHS) Nightingale Hospitals, it highlights the need for healthcare agility and scalability, especially during pandemic outbreaks. The research presents a blueprint for field hospital deployment, marking a significant advancement in public health logistics and protection across Australia's varied demographic and geographical landscapes.

3D-AMM: a 3D artificial moment method for path planning of manipulator in multiple obstacles scenario

Purpose In response to the issue of traditional algorithms often falling into local minima or failing to find feasible solutions in manipulator path planning. The purpose of this paper is to propose a 3D artificial moment method (3D-AMM) for obstacle avoidance for the robotic arm's end-effector. Design/methodology/approach A new method for constructing temporary attractive points in 3D has been introduced using the vector triple product approach, which generates the attractive moments that attract the end-effector to move toward it. Second, distance weight factorization and spatial projection methods are introduced to improve the solution of repulsive moments in multiobstacle scenarios. Third, a novel motion vector-solving mechanism is proposed to provide nonzero velocity for the end-effector to solve the problem of limiting the solution of the motion vector to a fixed coordinate plane due to dimensionality constraints. Findings A comparative analysis was conducted between the proposed algorithm and the existing methods, the improved artificial potential field method and the rapidly-random tree method under identical simulation conditions. The results indicate that the 3D-AMM method successfully plans paths with smoother trajectories and reduces the path length by 20.03% to 36.9%. Additionally, the experimental comparison outcomes affirm the feasibility and effectiveness of this method for obstacle avoidance in industrial scenarios. Originality/value This paper proposes a 3D-AMM algorithm for manipulator path planning in Cartesian space with multiple obstacles. This method effectively solves the problem of the artificial potential field method easily falling into local minimum points and the low path planning success rate of the rapidly-exploring random tree method.

Deep reinforcement learning-based reactive trajectory planning method for UAVs

In order to improve the ability of avoiding dynamic threats during the flight of unmanned aerial vehicles (UAVs), a deep reinforcement learning-based reactive trajectory planning method is proposed in this paper. Firstly, a constrained Rapidly-exploring Random Tree-Connect algorithm (C-RRT-Connect) is proposed as the basic algorithm of reactive trajectory planning to globally plan for avoiding static obstacles in the environment. The C-RRT-Connect algorithm introduces the idea of target attraction to constrain the optimal growth point in the RRT-Connect algorithm. Then, based on the global trajectory, the local optimization is carried out according to the dynamic threats detected by the UAV during the flight. According to the real-time relative state between the UAV and the detected dynamic threat, the reaction sampling points and directional coefficients for avoiding the corresponding dynamic threat are generated online via the action network trained with the depth deterministic policy gradient algorithm (DDPG). And then the local trajectory is adjusted to modify the flight trajectory of the UAV to achieve reactive obstacle avoidance. The simulation experiment firstly compares the global trajectory planning performance of C-RRT-Connect and RRT-Connect in static environment, and secondly compares the local trajectory planning performance of DDPG algorithm and the artificial potential field method in dynamic environment. The experimental results show that in static environment, C-RRT-Connect algorithm has faster searching speed, less invalid samples and higher searching trajectory quality than RRT-Connect algorithm; In a dynamic environment, DDPG algorithm reduces the average running time by about 26% compared with the artificial potential field method, and has a stronger ability to evade dynamic threats in real time.

Transferable Anisotropic Mie Potential Force Field for Alkanediols.

The development of force fields for polyfunctional molecules, such as alkanediols, requires a careful account of different average intramolecular conformations for gas states compared to dense liquid states, where intra- and intermolecular hydrogen bonds compete. In the present work, the transferable anisotropic Mie (TAMie) potential is extended to 1,n-alkanediols. Using the convention that intramolecular nonbonded interactions up to and including the third neighbor are excluded, all force field parameters developed previously for 1-alcohols were transferred to 1,5-pentanediol and beyond, with good agreement with experimental phase equilibrium data. To obtain trans-gauche ratios of 1,2-ethanediol and 1,3-propanediol that are consistent with experimental results, the propensities for intra- and intermolecular hydrogen bonds had to be balanced. This was achieved by parameterizing the intramolecular dihedral energy functions governing the O-C-C-O and O-C-C-C angles while intramolecular charge-charge interactions were active. All partial charges belonging to a functional group are collected in a charge group and all interactions among two charge groups are evaluated even if they are separated by less than three bonds. With this approach, it is possible to apply the nonbonded parameters from 1-alcohols to alkanediols without further refinement. The agreement with experimental phase equilibrium and shear viscosity data is of similar quality as for the 1-alcohols and the trans-gauche ratio agrees with literature results from spectroscopic measurements and ab initio calculations.

Regularization of vertical derivatives of potential field data using Morozov's discrepancy principle

AbstractThe calculation of the vertical derivatives of potential field methods can be carried out in a stable manner by Tikhonov regularization, but this procedure requires the appropriate selection of a regularization parameter. For this purpose, we introduce a criterion based on Morozov's discrepancy principle that uses a preliminary approximation given by the vertical derivative of the smoothed data. The smoothing may be performed by a physical or a mathematically based low‐pass filter. The filtered data are computed only for estimating the regularization parameter; once it is found, we evaluate the regularized vertical derivative from the original data (not from the smoothed one) in the frequency domain. We verified from experiments with noise‐corrupted synthetic data, as well as gravity and magnetic field data, that the regularized vertical derivative has about the same smoothness as the one obtained from filtered data, but true anomalies are more easily distinguished from noise and the shapes of the anomalies are better preserved.

3D position deployment and performance optimization of mmWave UAV-assisted HetIoT under jamming condition

Heterogeneous Internet of Things (HetIoT) has received widespread attention due to its provision of various convenient services in fields such as smart cities, intelligent transportation, environmental monitoring and security systems. Due to HetIoT inherently demands high data rates, bandwidth, and low latency, the application of millimeter-wave (mmWave) unmanned aerial vehicle (UAV) as emergency aerial base station (ABS) providing services to HetIoT users has become a low-cost and efficient means. However, due to the sensitivity of mmWave to obstacles and jamming, guaranteeing network performance has become a pressing issue. This paper considers a mmWave UAV-assisted HetIoT under jamming conditions, where auxiliary ABSs serve multiple ground users (GUs) who generate a large amount of sensor data. We establish a coverage maximization problem under the constraints of signal-to-interference ratio (SIR) threshold, maximum power of ABSs and maximum number of GUs that the base station can serve, and propose a novel ABS hovering deployment algorithm M-HiAPSO that combines the artificial potential field (APF) method and the improved particle swarm optimization (PSO) algorithm in a hierarchical manner. Specifically, the multi-element APF method is used to characterize the horizontal force between nodes, combined with the improved hierarchical adaptive PSO algorithm to adjust the horizontal position of the ABS to obtain the optimal UAV hovering position and power allocation strategy. Numerical results show that the coverage rate reached 96.2% when the number of iterations was 283, and it can reach up to 99.6%.

Enhanced Hydrogen Evolution in Porous and Hybrid g‐C3N4/Pt‐PVDF Electrospun Membranes via Piezoelectricity from Water Flow Energy

AbstractInspired from seaweed swayed by waves, the enhanced hydrogen evolution is realized in porous and hybrid g‐C3N4/Pt‐PVDF electrospun membranes via piezoelectricity from water flow energy. The membranes are fabricated by dispersing g‐C3N4/Pt into the mixed solution of PVDF and PEO, followed by electrospinning and selective removal of PEO. By changing the PEO amount, the pore size in nanofibers is adjusted. Due to the hydrogen bonding between g‐C3N4/Pt and PVDF, the β phase of PVDF is increased, beneficial for the piezoelectricity performance. When the electrospun membranes are exposed to water flow, an additional potential field is triggered due to the deformation of PVDF. It not only eases the photogeneration of charge carriers from g‐C3N4/Pt but also hinders their recombination. The prolonged lifetime significantly improves the photocatalytic water splitting of g‐C3N4/Pt under visible light. The hydrogen evolution in the electrospun membranes (PVDF to PEO = 4:1) is profoundly improved to 9 278 µmol h−1 g−1, almost doubled to the pure g‐C3N4/Pt nanosheets (5 220 µmol h−1 g−1). Therefore, the seaweed‐inspired electrospun membrane is a promising strategy for the efficiently photocatalytic water splitting via g‐C3N4 in an aqueous environment, such as a natural sea and lake, by the piezoelectricity gained from the water flow energy.

Neurometric amplitude modulation detection in the inferior colliculus of Young and Aged rats

Amplitude modulation is an important acoustic cue for sound discrimination, and humans and animals are able to detect small modulation depths behaviorally. In the inferior colliculus (IC), both firing rate and phase-locking may be used to detect amplitude modulation. How neural representations that detect modulation change with age are poorly understood, including the extent to which age-related changes may be attributed to the inherited properties of ascending inputs to IC neurons. Here, simultaneous measures of local field potentials (LFPs) and single-unit responses were made from the inferior colliculus of Young and Aged rats using both noise and tone carriers in response to sinusoidally amplitude-modulated sounds of varying depths. We found that Young units had higher firing rates than Aged for noise carriers, whereas Aged units had higher phase-locking (vector strength), especially for tone carriers. Sustained LFPs were larger in Young animals for modulation frequencies 8–16 Hz and comparable at higher modulation frequencies. Onset LFP amplitudes were much larger in Young animals and were correlated with the evoked firing rates, while LFP onset latencies were shorter in Aged animals. Unit neurometric thresholds by synchrony or firing rate measures did not differ significantly across age and were comparable to behavioral thresholds in previous studies whereas LFP thresholds were lower than behavior.

Involvement of prelimbic cortex neurons and related circuits in the acquisition of a cooperative learning by pairs of rats

AbstractSocial behaviors such as cooperation are crucial for mammals. A deeper knowledge of the neuronal mechanisms underlying cooperation can be beneficial for people suffering from pathologies with impaired social behavior. Our aim was to study the brain activity when two animals synchronize their behavior to obtain a mutual reinforcement. In a previous work, we showed that the activity of the prelimbic cortex (PrL) was enhanced during cooperation in rats, especially in the ones leading most cooperative trials (leader rats). In this study, we investigated the specific cells in the PrL contributing to cooperative behaviors. To this end, we collected rats’ brains at key moments of the learning process to analyze the levels of c-FOS expression in the main cellular groups of the PrL. Leader rats showed increased c-FOS activity in cells expressing D1 receptors during cooperation. Besides, we analyzed the levels of anxiety, dominance, and locomotor behavior, finding that leader rats are in general less anxious and less dominant than followers. We also recorded local field potentials (LFPs) from the PrL, the nucleus accumbens septi (NAc), and the basolateral amygdala (BLA). A spectral analysis showed that delta activity in PrL and NAc increased when rats cooperated, while BLA activity in delta and theta bands decreased considerably during cooperation. The PrL and NAc also increased their connectivity in the high theta band during cooperation. Thus, the present work identifies the specific PrL cell types engaged in this behavior, as well as the way this information is propagated to selected downstream brain regions (BLA, NAc).