Salient Cues Research Articles

The presence of drum and bass modulates responses in the auditory dorsal pathway and mirror-related regions to pop songs

In pop music, drum and bass components are crucial for generating the desire to move one’s body, primarily due to their role in delivering salient metrical cues. This study explored how the presence of drum and bass influences neural responses to unfamiliar pop songs. Using AI-based algorithms, we isolated the drum and bass components from the musical excerpts, creating two additional versions: one that included only the drum and bass (excluding vocals and other instruments), and another that excluded the drum and bass (consisting solely of vocals and other instruments). Twenty-five participants were subjected to fMRI scans while listening to these musical stimuli. Analysis of fMRI data indicated that the removal of drum and bass led to increased activity in the auditory dorsal pathway, suggesting that the absence of these metrical cues demands greater cognitive effort to process the beats. In contrast, the version featuring only drum and bass elicited stronger activation in frontal regions associated with mirror properties, including the right ventral premotor cortex (extending into the inferior frontal gyrus) and left dorsolateral prefrontal cortex, compared to the original version. Overall, this study contributed insights into the foundational role of drum and bass in imparting metrical salience to pop songs, enriching our understanding of listeners’ sensorimotor processing of musical genres that prominently feature these two elements.

Multi-Prior Driven Network for RGB-D Salient Object Detection

Most existing RGB-D salient object detection (SOD) methods rely on high-quality depth images. However, their performance is limited when processing low-quality depth maps. This paper exploits more complementary image priors to guide the model to learn on variable depth maps, and a novel multi-prior driven network called MPDNet is proposed for RGB-D SOD. MPDNet utilizes four processing pipelines to process RGB images and other priors, which include an RGB image processing pipeline, a depth map processing pipeline, a fine-grained and gradient prior processing pipeline, and an edge learning pipeline. Specifically, fine-grained and gradient priors are input to the same processing pipeline. For the depth maps, fine-grained and gradient priors, a prior channel attention module utilizes the channel attention mechanism to filter noises and highlights the salient cues. The RGB image processing pipeline uses a multi-feature progressive enhancement module to fuse and enhance features from depth maps. And a multi-feature prediction decoder decodes initial salient masks. In the edge learning pipeline, edge prior serves as an edge label and is captured by an edge capture module. Finally, the clear salient masks are obtained by fusing the salient information from the four pipelines. The experimental results on six benchmarks indicate that the proposed method outperforms thirteen state-of-the-art methods in six evaluation metrics.

Using Geovisualizations to Educate the Public About Environmental Health Hazards: What Works and Why.

Informing the public about environmental risks to health is crucial for raising awareness around hazards, and promoting actions that minimize exposures. Geographic visualizations-geovisualizations-have become an increasingly common way to disseminate web-based information about environmental hazards, displaying spatial variations in exposures and health outcomes using a map. Unfortunately, ineffective geovisualizations can result in inaccurate inferences about a hazard, leading to misguided actions or policies. In this narrative review, we discuss key considerations for the use of geovisualizations to promote environmental health literacy. Many conventional geovisualizations used for hazard education and risk communication fail to consider how people process visual information. Design choices that prompt viewers to think and feel, leveraging processes such as individual attention, memory, and emotion, could promote improved comprehension and decision making around environmental health risks using geovisualizations. Based on the studies reviewed, we recommend six strategies for designing effective, evidence-based geovisualizations, synthesizing evidence from the cognitive sciences, cartography, and environmental health. These strategies include: Displaying only key data, tailoring and testing geovisualizations with the desired audience, using salient cues, leveraging emotion, aiding pattern recognition, and limiting visual distractions. Geovisualizations offer a promising avenue for advancing public awareness and fostering proactive measures in addressing complex environmental health challenges. This review highlights how incorporating evidence-based design principles into geovisualizations could promote environmental health literacy. More experimental research evaluating geovisualizations, using interdisciplinary approaches, is needed.

Robustly encoding certainty in a metastable neural circuit model.

Localized persistent neural activity can encode delayed estimates of continuous variables. Common experiments require that subjects store and report the feature value (e.g., orientation) of a particular cue (e.g., oriented bar on a screen) after a delay. Visualizing recorded activity of neurons along their feature tuning reveals activity bumps whose centers wander stochastically, degrading the estimate over time. Bump position therefore represents the remembered estimate. Recent work suggests bump amplitude may represent estimate certainty reflecting a probabilistic population code for a Bayesian posterior. Idealized models of this type are fragile due to the fine tuning common to constructed continuum attractors in dynamical systems. Here we propose an alternative metastable model for robustly supporting multiple bump amplitudes by extending neural circuit models to include quantized nonlinearities. Asymptotic projections of circuit activity produce low-dimensional evolution equationsfor the amplitude and position of bump solutions in response to external stimuli and noise perturbations. Analysis of reduced equationsaccurately characterizes phase variance and the dynamics of amplitude transitions between stable discrete values. More salient cues generate bumps of higher amplitude which wander less, consistent with experiments showing certainty correlates with more accurate memories.

The message matters: changes to binary Computer Aided Detection recommendations affect cancer detection in low prevalence search

Computer Aided Detection (CAD) has been used to help readers find cancers in mammograms. Although these automated systems have been shown to help cancer detection when accurate, the presence of CAD also leads to an over-reliance effect where miss errors and false alarms increase when the CAD system fails. Previous research investigated CAD systems which overlayed salient exogenous cues onto the image to highlight suspicious areas. These salient cues capture attention which may exacerbate the over-reliance effect. Furthermore, overlaying CAD cues directly on the mammogram occludes sections of breast tissue which may disrupt global statistics useful for cancer detection. In this study we investigated whether an over-reliance effect occurred with a binary CAD system, which instead of overlaying a CAD cue onto the mammogram, reported a message alongside the mammogram indicating the possible presence of a cancer. We manipulated the certainty of the message and whether it was presented only to indicate the presence of a cancer, or whether a message was displayed on every mammogram to state whether a cancer was present or absent. The results showed that although an over-reliance effect still occurred with binary CAD systems miss errors were reduced when the CAD message was more definitive and only presented to alert readers of a possible cancer.

Emotional Overshadowing: Pleasant and Unpleasant Cues Overshadow Neutral Cues in Human Associative Learning.

The online version contains supplementary material available at 10.1007/s42761-024-00270-0.

Cue relevance drives early quitting in visual search

Irrelevant salient distractors can trigger early quitting in visual search, causing observers to miss targets they might otherwise find. Here, we asked whether task-relevant salient cues can produce a similar early quitting effect on the subset of trials where those cues fail to highlight the target. We presented participants with a difficult visual search task and used two cueing conditions. In the high-predictive condition, a salient cue in the form of a red circle highlighted the target most of the time a target was present. In the low-predictive condition, the cue was far less accurate and did not reliably predict the target (i.e., the cue was often a false positive). These were contrasted against a control condition in which no cues were presented. In the high-predictive condition, we found clear evidence of early quitting on trials where the cue was a false positive, as evidenced by both increased miss errors and shorter response times on target absent trials. No such effects were observed with low-predictive cues. Together, these results suggest that salient cues which are false positives can trigger early quitting, though perhaps only when the cues have a high-predictive value. These results have implications for real-world searches, such as medical image screening, where salient cues (referred to as computer-aided detection or CAD) may be used to highlight potentially relevant areas of images but are sometimes inaccurate.

Measuring User Response to Attention Guidance Using the Integrated Cognitive User Assistance System

Humans are limited in their attentional capacity and miss salient cues when multitasking. We built a platform, ICUa (Integrated Cognitive User assistance) that simulates parts of MATBII, a computer-based multitasking testbed, adding gaze-based attention guidance in an attempt to improve multitasking performance. ICUa uses software agents for monitoring the interface, human behavior and eye gaze in order to guide attention (displaying highlights and arrows). We varied the difficulty of our testbed and found effects on human performance (based on error times) and characterized the types of errors that occurred with higher difficulty and how agent response changed. There was no clear effect of ICUa guidance on gaze patterns or human performance. The visual guidance we deployed may not be sufficient to measurably influence behavior. Future work will develop the detection eye gaze patterns and effective cues to redirect attention using this human-agent interface for experiments on attention guidance.

The role of cue salience in prospective memory commission errors in nonperformed nonfocal tasks.

Prospective memory (PM) refers to the ability to remember to execute an intention in the future without having a permanent reminder. These intentions can be performed when they are not relevant or become no-longer needed, the so-called "commission errors". The present study aims to understand the effect of cue salience on PM commission errors with unperformed intentions and on the ongoing task performance-associated costs. Through a between-subjects design, eighty-one participants were assigned to 3 conditions: the no-PM condition, which served as control, and the salient and nonsalient conditions, which were asked to perform a lexical decision task and an incomplete nonfocal prospective memory task (i.e. no PM cues were presented). Subsequently, participants were instructed to no longer execute the prospective intention. In the second phase, a lexical decision task occurred again, including irrelevant PM cues, which should not be answered as such. In the salient condition, cues were salient (i.e. presented in red or blue background). In contrast, in the nonsalient condition, PM cues appeared on a black background, as any other stimuli. In the no-PM control condition, participants only performed an LDT. A commission error occurred when the (irrelevant) intention was performed in this second phase. Results showed that more participants performed a commission error in the presence of salient cues, even when PM intentions became irrelevant. Additionally, when cues were not salient, participants took longer to answer the LDT, as reasoned by the spontaneous retrieval theory. These findings are discussed according to the dual-mechanism account.

Design of Adaptive Target Tracking Algorithm for Robots Based on Visual Attention Mechanism

Adaptive target tracking with visual attention represents a sophisticated approach to object detection and localization in dynamic environments. With principles inspired by human visual perception, this methodology employs mechanisms of selective attention to prioritize relevant visual information for tracking moving targets. By dynamically adjusting attentional focus based on salient visual cues and target motion characteristics, adaptive target tracking enhances the efficiency and accuracy of object localization in cluttered scenes. This research presents a novel adaptive target tracking algorithm designed for robotic systems, integrating a visual attention mechanism with the Fuzzy Clustering Multi-Point Tracking utilizing the Green Channel (FC-MPT-GC) approach. The proposed FC-MPT-GC model comprises of Fuzzy Clustering for the extraction of features in the robots-based environment. The FC-MPT-GC model uses the estimation of green channels in the classification environment. With the estimation of features in the environment with Fuzzy C-means clustering green channels are deployed in the deep learning, The proposed algorithm aims to enhance the adaptability and precision of target tracking in dynamic environments. By incorporating a visual attention mechanism, the algorithm dynamically allocates attentional focus to salient regions of the visual input, optimizing the tracking process for moving targets. The FC-MPT-GC methodology further refines target localization by utilizing fuzzy clustering and multi-point tracking strategies, particularly leveraging information from the Green Channel to improve robustness in various lighting conditions. Simulation analysis demonstrated that the proposed FC-MPT-GC model tracking accuracy is achieved at 95.1% with the minimal computation time of 15.2 ms.

Changing the food environment in secondary school canteens to promote healthy dietary choices: a qualitative study with school caterers

BackgroundTypical adolescent diets do not meet current dietary recommendations. There is a need to address these dietary patterns to reduce the risk of obesity and other diet-related diseases. Schools provide an opportune setting to do so, as students consume a substantial proportion of their daily dietary intake whilst at school. There is a developing evidence base on the use of choice architecture (food choice cues) to promote healthy eating in school contexts. It is necessary to understand the acceptability and feasibility of implementing such interventions. We aimed to explore these factors from the perspectives of secondary school caterers.MethodsWe conducted qualitative interviews with caterers from secondary schools across the West Midlands, UK and national/regional catering representatives. A semi-structured topic guide and visual aid were used to guide interviews. Interviews were recorded and transcribed. Framework analysis was conducted in NVivo v12.ResultsTwelve participants took part. Seven themes were identified and grouped into three categories: Acceptability (Suitability; Salient cues; Student engagement), Barriers (Catering decision drivers; Limits of influence), and Enablers (Perceived role; Opportunities). Caterers considered healthy food cues to be suited to adolescents as they require minimal reflective motivation. Salient cues included enhancing the placement, presentation and portability of healthy items, improving the dining environment and focusing pricing/incentive strategies on increased quantity. Student engagement was considered important. Some catering decision drivers conflicted with healthy food cues, and many felt that their role in healthy eating was limited due to the overwhelming influence of external food environments, adolescent resistance, and features of the secondary school canteen setting e.g. short duration of lunchtime, lack of space. However, caterers appeared motivated to implement healthy food cues and identified key opportunities for implementation, including integration into whole-school approaches to healthy eating.ConclusionsInterventions using healthy food cues appeared acceptable to secondary school caterers, key potential implementers of these strategies. Future interventions could incorporate strategies relating to placement, presentation and pricing to prompt healthy selections, and actions to engage the student body and improve the dining environment. Evaluations should consider potential impacts upon food purchasing, consumption and waste to address caterers’ concerns about these issues.

The super‐recogniser advantage extends to the detection of hyper‐realistic face masks

AbstractHyper‐realistic silicone masks provide a viable route to identity fraud. Over the last decade, more than 40 known criminal acts have been committed by perpetrators using this type of disguise. With the increasing availability and bespoke sophistication of these masks, research must now focus on ways to enhance their detection. In this study, we investigate whether super‐recognisers (SRs), people who excel at identity recognition, are more likely to detect this type of fraud, in comparison to typical‐recogniser controls. Across three tasks, we examined mask detection rates in the absence of a pre‐task prompt (covert task), and again after making participants aware of their use in criminal settings (explicit task). Finally, participants were asked to indicate which aspects of the masks could support their detection (regions of interest task). The findings show an SR advantage for the detection of hyper‐realistic masks across the covert and explicit mask detection tasks. In addition, the eye, mouth, and nose regions appear to be particularly indicative of the presence of a mask. The lack of natural skin texture, proportional features, expressiveness, and asymmetry are also salient cues. The theoretical and applied implications of these findings are discussed.

Predictive Processing During Cue-Outcome Associative Learning in Autistic Children.

Predictive coding theories posit that autism is characterized by an over-adjustment to prediction errors, resulting in frequent updates of prior beliefs. Atypical weighting of prediction errors is generally considered to negatively impact the construction of stable models of the world, but may also yield beneficial effects. In a novel associative learning paradigm, we investigated whether unexpected events trigger faster learning updates in favour of subtle but fully predictive cues in autistic children compared to their non-autistic counterparts. We also explored the relationship between children's language proficiency and their predictive performances. Anticipatory fixations and explicit predictions were recorded during three associative learning tasks with deterministic or probabilistic contingencies. One of the probabilistic tasks was designed so that a fully predictive but subtle cue was overshadowed by a less predictive salient one. Both autistic and non-autistic children based their learning on the salient cue, and, contrary to our predictions, showed no signs of updating in favour of the subtle cue. While both groups demonstrated associative learning, autistic children made less accurate explicit predictions than their non-autistic peers in all tasks. Explicit prediction performances were positively correlated with language proficiency in non-autistic children, but no such correlation was observed in autistic children. These results suggest no over-adjustment to prediction errors in autistic children and highlight the need to control for general performance in cue-outcome associative learning in predictive processing studies. Further research is needed to explore the nature of the relationship between predictive processing and language development in autism.

Tobacco Images Choice and Its Association with Craving and Dependence in People who Smoke Cigarettes.

Increased salience of drug-related cues over non-drug reinforcers can drive drug use and contribute to tobacco use disorder (TUD). An important scientific and clinical goal is to effectively measure this elevated drug-seeking behavior in TUD. However, most TUD assessments rely on self-reported cravings and cigarette consumption, not providing an objective measure of the impact of drug-cues on biasing behavior towards drugs. The probabilistic image choice (PIC) task investigates the choice of viewing drug-related pictures as compared to other salient pictures (e.g., pleasant and unpleasant). This study aimed to develop and validate the PIC task for TUD and evaluate the associations between behavioral choice and tobacco craving, daily cigarette consumption, quit attempts and motivation to quit, and nicotine dependence (the Fagerström score). We recruited 468 smokers and 121 nonsmokers using the Prolific online platform. Participants performed the PIC task twice (at a one-month interval) and completed other measures relevant to TUD. compared to nonsmokers, tobacco smokers selected to view significantly more tobacco images and less pleasant (non-drug reinforcer) images, a profile that remained stable at retest. Individual differences in choice of tobacco as compared to pleasant images on the PIC task were associated with craving but not with the other tobacco dependence measures, suggesting that the task may serve as a behavioral proxy measure of drug "wanting" rather than of cumulative nicotine exposure or physical dependence. these results suggest that the PIC task can be a valuable tool for objectively assessing craving-associated tobacco seeking in TUD. which should provide a brief description about what the study addsMost of the current measures of tobacco use disorder (TUD) rely on self-reports of consumption, dependence and craving and do not take into consideration the role of drug-related cues in driving tobacco seeking. This study shows that the probabilistic image choice (PIC) task provides an objective, reliable proxy measure of tobacco image seeking behavior in people who smoke cigarettes that is linked to craving (desire) for smoking but not to other measures of TUD. Therefore, the PIC task may be a useful complementary tool for the classification, diagnosis, and prognosis of TUD.

Re-wiring of the bonded brain: Gene expression among pair bonded female prairie voles changes as they transition to motherhood.

Motherhood is a costly life-history transition accompanied by behavioral and neural plasticity necessary for offspring care. Motherhood in the monogamous prairie vole is associated with decreased pair bond strength, suggesting a trade-off between parental investment and pair bond maintenance. Neural mechanisms governing pair bonds and maternal bonds overlap, creating possible competition between the two. We measured mRNA expression of genes encoding receptors for oxytocin (oxtr), dopamine (d1r and d2r), mu-opioids (oprm1a), and kappa-opioids (oprk1a) within three brain areas processing salience of sociosensory cues (anterior cingulate cortex; ACC), pair bonding (nucleus accumbens; NAc), and maternal care (medial preoptic area; MPOA). We compared gene expression differences between pair bonded prairie voles that were never pregnant, pregnant (~day 16 of pregnancy), and recent mothers (day 3 of lactation). We found greater gene expression in the NAc (oxtr, d2r, oprm1a, and oprk1a) and MPOA (oxtr, d1r, d2r, oprm1a, and oprk1a) following the transition to motherhood. Expression for all five genes in the ACC was greatest for females that had been bonded for longer. Gene expression within each region was highly correlated, indicating that oxytocin, dopamine, and opioids comprise a complimentary gene network for social signaling. ACC-NAc gene expression correlations indicated that being a mother (oxtr and d1r) or maintaining long-term pair bonds (oprm1a) relies on the coordination of different signaling systems within the same circuit. Our study suggests the maternal brain undergoes changes that prepare females to face the trade-off associated with increased emotional investment in offspring, while also maintaining a pair bond.

The scent of cuteness-neural signatures of infant body odors.

The smell of the own baby is a salient cue for human kin recognition and bonding. We hypothesized that infant body odors function like other cues of the Kindchenschema by recruiting neural circuits of pleasure and reward. In two functional magnetic resonance imaging studies, we presented infantile and post-pubertal body odors to nulliparae and mothers (N = 78). All body odors increased blood-oxygen-level-dependent (BOLD) response and functional connectivity in circuits related to olfactory perception, pleasure and reward. Neural activation strength in pleasure and reward areas positively correlated with perceptual ratings across all participants. Compared to body odor of post-pubertal children, infant body odors specifically enhanced BOLD signal and functional connectivity in reward and pleasure circuits, suggesting that infantile body odors prime the brain for prosocial interaction. This supports the idea that infant body odors are part of the Kindchenschema. The additional observation of functional connectivity being related to maternal and kin state speaks for experience-dependent priming.

Redundancy can hinder adult L2 grammar learning: evidence from case markers of varying salience levels.

Grammatical redundancy is a widespread feature across languages. Although redundant cues can be seen to increase the complexity and processing burden of structures, it has been suggested that they can assist language acquisition. Here, we explored if this learning benefit can be observed from the very initial stages of second language (L2) acquisition and whether the effect of redundancy is modulated by the perceptual salience of the redundant linguistic cues. Across two experiments, three groups of adult native speakers of English were incidentally exposed to three different artificial languages; one that had a fixed word order, Verb-Object-Subject, and two in which thematic role assignment was additionally determined by a low-salient (Experiment 1) or a high-salient (Experiment 2) redundant case marker. While all groups managed to learn the novel language, our results pointed towards a hindering role of redundancy, with participants in the non-redundant condition achieving greater learning outcomes compared to those in both redundant conditions. Results also revealed that this impeding effect of redundancy on L2 learners can be attenuated by the salience of the redundant cue (Experiment 2). In conjunction with earlier findings, the present results suggest that the effect of redundancy on L2 acquisition can be differentially manifested depending on the stage of L2 development, learners' first language biases and age.

Neural Envelope Processing at Low Frequencies Predicts Speech Understanding of Children With Hearing Loss in Noise and Reverberation.

Children with hearing loss experience greater difficulty understanding speech in the presence of noise and reverberation relative to their normal hearing peers despite provision of appropriate amplification. The fidelity of fundamental frequency of voice (f0) encoding-a salient temporal cue for understanding speech in noise-could play a significant role in explaining the variance in abilities among children. However, the nature of deficits in f0 encoding and its relationship with speech understanding are poorly understood. To this end, we evaluated the influence of frequency-specific f0 encoding on speech perception abilities of children with and without hearing loss in the presence of noise and/or reverberation. In 14 school-aged children with sensorineural hearing loss fitted with hearing aids and 29 normal hearing peers, envelope following responses (EFRs) were elicited by the vowel /i/, modified to estimate f0 encoding in low (<1.1 kHz) and higher frequencies simultaneously. EFRs to /i/ were elicited in quiet, in the presence of speech-shaped noise at +5 dB signal to noise ratio, with simulated reverberation time of 0.62 sec, as well as both noise and reverberation. EFRs were recorded using single-channel electroencephalogram between the vertex and the nape while children watched a silent movie with captions. Speech discrimination accuracy was measured using the University of Western Ontario Distinctive Features Differences test in each of the four acoustic conditions. Stimuli for EFR recordings and speech discrimination were presented monaurally. Both groups of children demonstrated a frequency-dependent dichotomy in the disruption of f0 encoding, as reflected in EFR amplitude and phase coherence. Greater disruption (i.e., lower EFR amplitudes and phase coherence) was evident in EFRs elicited by low frequencies due to noise and greater disruption was evident in EFRs elicited by higher frequencies due to reverberation. Relative to normal hearing peers, children with hearing loss demonstrated: (a) greater disruption of f0 encoding at low frequencies, particularly in the presence of reverberation, and (b) a positive relationship between f0 encoding at low frequencies and speech discrimination in the hardest listening condition (i.e., when both noise and reverberation were present). Together, these results provide new evidence for the persistence of suprathreshold temporal processing deficits related to f0 encoding in children despite the provision of appropriate amplification to compensate for hearing loss. These objectively measurable deficits may underlie the greater difficulty experienced by children with hearing loss.

WBNet: Weakly-supervised salient object detection via scribble and pseudo-background priors

Weakly supervised salient object detection (WSOD) methods endeavor to boost sparse labels to get more salient cues in various ways. Among them, an effective approach is using pseudo labels from multiple unsupervised self-learning methods, but inaccurate and inconsistent pseudo labels could ultimately lead to detection performance degradation. To tackle this problem, we develop a new multi-source WSOD framework, WBNet, that can effectively utilize pseudo-background (non-salient region) labels combined with scribble labels to obtain more accurate salient features. We first design a comprehensive salient pseudo-mask generator from multiple self-learning features. Then, we pioneer the exploration of generating salient pseudo-labels via point-prompted and box-prompted Segment Anything Models (SAM). Then, WBNet leverages a pixel-level Feature Aggregation Module (FAM), a mask-level Transformer-decoder (TFD), and an auxiliary Boundary Prediction Module (EPM) with a hybrid loss function to handle complex saliency detection tasks. Comprehensively evaluated with state-of-the-art methods on five widely used datasets, the proposed method significantly improves saliency detection performance. The code and results are publicly available at https://github.com/yiwangtz/WBNet.

Behavioral Interventions Can Improve Brain Injury-Induced Deficits in Behavioral Flexibility and Impulsivity Linked to Impaired Reward-Feedback Beta Oscillations.

Traumatic brain injury (TBI) affects a large population, resulting in severe cognitive impairments. Although cognitive rehabilitation is an accepted treatment for some deficits, studies in patients are limited in ability to probe physiological and behavioral mechanisms. Therefore, animal models are needed to optimize strategies. Frontal TBI in a rat model results in robust and replicable cognitive deficits, making this an ideal candidate for investigating various behavioral interventions. In this study, we report three distinct frontal TBI experiments assessing behavior well into the chronic post-injury period using male Long-Evans rats. First, we evaluated the impact of frontal injury on local field potentials recorded simultaneously from 12 brain regions during a probabilistic reversal learning (PbR) task. Next, a set of rats were tested on a similar PbR task or an impulsivity task (differential reinforcement of low-rate behavior [DRL]) and half received salient cues associated with reinforcement contingencies to encourage engagement in the target behavior. After intervention on the PbR task, brains were stained for markers of activity. On the DRL task, cue relevance was decoupled from outcomes to determine if beneficial effects persisted on impulsive behavior. TBI decreased the ability to detect reinforced outcomes; this was evident in task performance and reward-feedback signals occurring at beta frequencies in lateral orbitofrontal cortex (OFC) and associated frontostriatal regions. The behavioral intervention improved flexibility and increased OFC activity. Intervention also reduced impulsivity, even after cues were decoupled, which was partially mediated by improvements in timing behavior. The current study established a platform to begin investigating cognitive rehabilitation in rats and identified a strong role for dysfunctional OFC signaling in probabilistic learning after frontal TBI.