Multimodal cues displayed by submissive rats promote prosocial choices by dominants

Animals often display prosocial behaviours, performing actions that benefit others. Although prosociality is essential for social bonding and cooperation, we still know very little about how animals integrate behavioural cues from those in need to make decisions that increase their wellbeing. To address this question, we used a two-choice task where rats can provide rewards to a conspecific in the absence of self-benefit, and interrogated which conditions promote prosociality by manipulating the social context of the interacting animals. While sex or degree of familiarity did not affect prosocial choices in rats, social hierarchy revealed to be a potent modulator, with dominant decision-makers showing faster emergence and higher levels of prosocial choices towards their submissive cage-mates. Leveraging quantitative analysis of multimodal social dynamics prior to choice, we identified that pairs with dominant decision-makers exhibited more proximal interactions in social distance. Interestingly, these more coordinated interactions were driven by submissive animals that modulated their position and movement towards their dominants and increased 50kHz vocalisation rate when their partners were going to behave selfishly. This display of multimodal cues by submissive animals while signalling need promoted social saliency and a faster emergence of prosocial choices from dominant rats. Multivariate analysis highlighted non-canonical body language as the main information dominants use on a trial-by-trial basis to learn that their actions have effects on others. Our results provide a refined understanding of the behavioural dynamics that rats use for action-selection upon perception of socially relevant cues and navigate social decision-making.

Dopamine firing plays a dual role in coding reward prediction errors and signaling motivation in a working memory task

Little is known about how dopamine (DA) neuron firing rates behave in cognitively demanding decision-making tasks. Here, we investigated midbrain DA activity in monkeys performing a discrimination task in which the animal had to use working memory (WM) to report which of two sequentially applied vibrotactile stimuli had the higher frequency. We found that perception was altered by an internal bias, likely generated by deterioration of the representation of the first frequency during the WM period. This bias greatly controlled the DA phasic response during the two stimulation periods, confirming that DA reward prediction errors reflected stimulus perception. In contrast, tonic dopamine activity during WM was not affected by the bias and did not encode the stored frequency. More interestingly, both delay-period activity and phasic responses before the second stimulus negatively correlated with reaction times of the animals after the trial start cue and thus represented motivated behavior on a trial-by-trial basis. During WM, this motivation signal underwent a ramp-like increase. At the same time, motivation positively correlated with accuracy, especially in difficult trials, probably by decreasing the effect of the bias. Overall, our results indicate that DA activity, in addition to encoding reward prediction errors, could at the same time be involved in motivation and WM. In particular, the ramping activity during the delay period suggests a possible DA role in stabilizing sustained cortical activity, hypothetically by increasing the gain communicated to prefrontal neurons in a motivation-dependent way.

Keeping time and rhythm by replaying a sensory-motor engram

Imagine practicing a piece of music, or a speech, solely within the mind, without any sensory input or motor output. Our ability to implement dynamic internal representations is key for successful behavior, yet how the brain achieves this is not fully understood. Here we trained primates to perceive, and internally maintain, rhythms of different tempos and performed large-scale recordings of neuronal activity across multiple areas spanning the sensory-motor processing hierarchy. Results show that perceiving and maintaining rhythms engage multiple brain areas, including visual, parietal, premotor, prefrontal, and hippocampal regions. Each area displayed oscillatory activity that reflected the temporal and spatial characteristics of an internal metronome which flexibly encoded fast, medium, and slow tempos on a trial-by-trial basis. The presence of widespread metronome-related activity across the brain, in the absence of stimuli and overt actions, is consistent with the idea that time and rhythm are maintained by a mechanism that internally replays the stimuli and actions that define well-timed behavior.

Clustering analysis of movement kinematics in reinforcement learning

Reinforcement learning has been used as an experimental model of motor skill acquisition, where at times movements are successful and thus reinforced. One fundamental problem is to understand how humans select exploration over exploitation during learning. The decision could be influenced by factors such as task demands and reward availability. In this study, we applied a clustering algorithm to examine how a change in the accuracy requirements of a task affected the choice of exploration over exploitation. Participants made reaching movements to an unseen target using a planar robot arm and received reward after each successful movement. For one group of participants, the width of the hidden target decreased after every other training block. For a second group, it remained constant. The clustering algorithm was applied to the kinematic data to characterize motor learning on a trial-to-trial basis as a sequence of movements, each belonging to one of the identified clusters. By the end of learning, movement trajectories across all participants converged primarily to a single cluster with the greatest number of successful trials. Within this analysis framework, we defined exploration and exploitation as types of behaviour in which two successive trajectories belong to different or similar clusters, respectively. The frequency of each mode of behaviour was evaluated over the course learning. It was found that by reducing the target width, participants used a greater variety of different clusters and displayed more exploration than exploitation. Excessive exploration relative to exploitation was found to be detrimental to subsequent motor learning.

Development and Evaluation of a Web-Based System to Learn Skills for Removing Personal Protective Equipment for Highly Infectious Diseases

We developed a web-based learning system for healthcare workers to learn the skills for removing personal protective equipment for highly infectious diseases. The system was implemented on a trial basis and healthcare workers evaluated its usability and their motivation to learn. Usability was similar to that of typical systems. Motivation scores were high, indicating confidence and satisfaction with the system.

Single-trial detection of EEG error-related potentials in serial visual presentation paradigm

When the outcome of an event is not the same as expected, the cognitive state that monitors performance elicits a time-locked brain response termed as Error-Related Potential (ErrP). Objective – In the existing work, ErrP is not recorded when there is a disassociation between an object and its description. The objective of this work is to propose a Serial Visual Presentation (SVP) experimental paradigm to record ErrP when an image and its label are disassociated. Additionally, this work aims to propose a novel method for detecting ErrP on a single-trial basis. Method – The method followed in this work includes designing of SVP paradigm in which labeled images from six categories (bike, car, flower, fruit, cat, and dog) are presented serially. In this work, a text (visual) or an audio clip describing the image in one word is presented as the label. Further, the ErrP is detected on a single-trial basis using novel electrode-averaged features. Results - The ErrP data recorded from 11 subjects’ have consistent characteristics compared to existing ErrP literature. Detection of ErrP on a single-trial basis is carried out using a novel feature extraction method on two type labeling types separately. The best average classification accuracy achieved is 69.09±4.70% and 63.33±4.56% for the audio and visual type of labeling the image, respectively. The proposed feature extraction method achieved higher classification accuracy when compared with two existing feature extraction methods. Significance - The significance of this work is that it can be used as a Brain-Computer Interface (BCI) system for quantitative evaluation and treatment of mild cognitive impairment. This work can also find non-clinical BCI applications such as image annotation.

Sustainable Production Enhancement of Valuable Products Via Operational Rectification

ADNOC LNG lies in the middle stream of the value chain, receiving and processing LP and HP gases from ADNOC Offshore. Supporting ADNOC Upstream's current oil production and future growth strategy while reducing its associated emissions of the process by delivering the associated gases to ADNOC LNG battery limit ADNOC LNG processes associated and non-associated gases to produce LNG (Liquefied Natural Gas), Propane, Butane, Paraffinic Naphtha (P. Naphtha) and Sulfur. LNG constitutes Methane, Ethane and a little Propane and butane, with minimum constraints on GHV and density. In order to deal with market competitiveness in the context of a potentially prolonged low-price environment, ADNOC LNG has embarked on various initiatives to maximize its production by driving agility and efficiency throughout the value chain process. Delivering upon efficiency improvements, one of the contributing studies included optimizing the propane content i.e. reducing the C3 content, in LNG Propane content in LNG has been varied, within operational limits, to maximize production of propane, which is more valuable/profitable when compared to LNG, whilst maintaining minimum LNG specification. In addition, slighting higher feed gas has been processed, to maintain LNG production rate. This has been achieved without hampering the plant stability. The extensive review and analysis of the rectification units has been conducted as well as optimization in terms of temperature profiles and reflux flow rates was able to generate overall better product purification, thereby increasing production of desired and more valuable products. This study has driven the investigation of additional benefits in production enhancement and quality improvements as the market value of Propane is relatively higher than that of LNG and thus yielding greater benefits. The overall performance trial basis deduced a total added benefit equivalent to 9 MMUSD/year YTD for train 3.

Speed Is Associated With, But Does Not Cause, Polarization in the Moral Evaluation of Real-World Images

In human perceptual decision-making, the speed-accuracy tradeoff establishes a causal link between urgency and reduced accuracy. Less is known about how urgency affects the moral evaluation of visual images. Here, we asked participants to give ratings for a diverse set of real-world images on a continuous scale from -10 (“very immoral”) to +10 (“very moral”). We used a cueing procedure to inform the participants on a trial-by-trial basis whether they could make a Self-Paced (SP) evaluation or whether they had to perform a Time-Limited (TL) evaluation within 2 seconds. In the SP condition, fast responses were associated with more extreme evaluations. Compared to the SP condition, the responses in the TL condition were much faster, indicating that our urgency manipulation was successful. However, comparing the SP versus TL conditions, we found no significant differences in the moral evaluation of the real-world images. The data indicated that, while speed is associated with polarization, urgency does not cause participants to make more extreme evaluations. Instead, the correlation between speed and polarization likely reflects the ease of processing. Images that are obviously moral or immoral are categorized faster and given more extreme evaluations than images for which the moral interpretation is uncertain.

Alpha power and stimulus-evoked activity dissociate metacognitive reports of attention, visibility and confidence in a visual detection task

Variability in the detection and discrimination of weak visual stimuli has been linked to prestimulus neural activity. In particular, the power of oscillatory activity in the alpha-band (8-12 Hz) has been shown to impact upon the objective likelihood of stimulus detection, as well as measures of subjective visibility, attention, and decision confidence. We aimed to clarify how prestimulus alpha influences performance and phenomenology, by recording simultaneous subjective measures of attention and confidence (Experiment 1), or attention and visibility (Experiment 2) on a trial-by-trial basis in a visual detection task. Across both experiments, prestimulus alpha power was negatively and linearly correlated with the intensity of subjective attention. In contrast to this linear relationship, we observed a quadratic relationship between the strength of prestimulus alpha power and subjective ratings of confidence and visibility. We find that this same quadratic relationship links prestimulus alpha power to the strength of stimulus evoked responses. Visibility and confidence judgements corresponded to the strength of evoked responses, but confidence, uniquely, incorporated information about attentional state. As such, our findings reveal distinct psychological and neural correlates of metacognitive judgements of attentional state, stimulus visibility, and decision confidence.

Entropy-based metrics for predicting choice behavior based on local response to reward

For decades, behavioral scientists have used the matching law to quantify how animals distribute their choices between multiple options in response to reinforcement they receive. More recently, many reinforcement learning (RL) models have been developed to explain choice by integrating reward feedback over time. Despite reasonable success of RL models in capturing choice on a trial-by-trial basis, these models cannot capture variability in matching behavior. To address this, we developed metrics based on information theory and applied them to choice data from dynamic learning tasks in mice and monkeys. We found that a single entropy-based metric can explain 50% and 41% of variance in matching in mice and monkeys, respectively. We then used limitations of existing RL models in capturing entropy-based metrics to construct more accurate models of choice. Together, our entropy-based metrics provide a model-free tool to predict adaptive choice behavior and reveal underlying neural mechanisms.