Modeling the Role of Striatum in Stochastic Multi Context Tasks

Decision making tasks in changing environments with probabilistic reward schemes present various challenges to the agents performing the task. These agents must use the experience gained in the past trials to characterize the environment which guides their actions. We present two models to predict an agent's behavior in these tasks-a theoretical model which defines a Bayes optimal solution to the problem under realistic task conditions. The second is a computational model of the basal ganglia which presents a neural mechanism to solve the same. Both the models are shown to reproduce results in behavioral experiments and are compared to each other. This comparison allows us to characterize the theoretical model as a bound on the neural model and the neural model as a biologically plausible implementation of the theoretical model. Furthermore, we predict the performance of the agents in various stochastic regimes which could be tested in future studies

On the role of theory and modeling in neuroscience

In recent years, the field of neuroscience has gone through rapid experimental advances and extensive use of quantitative and computational methods. This accelerating growth has created a need for methodological analysis of the role of theory and the modeling approaches currently used in this field. Toward that end, we start from the general view that the primary role of science is to solve empirical problems, and that it does so by developing theories that can account for phenomena within their domain of application. We propose a commonly-used set of terms - descriptive, mechanistic, and normative - as methodological designations that refer to the kind of problem a theory is intended to solve. Further, we find that models of each kind play distinct roles in defining and bridging the multiple levels of abstraction necessary to account for any neuroscientific phenomenon. We then discuss how models play an important role to connect theory and experiment, and note the importance of well-defined translation functions between them. Furthermore, we describe how models themselves can be used as a form of experiment to test and develop theories. This report is the summary of a discussion initiated at the conference Present and Future Theoretical Frameworks in Neuroscience, which we hope will contribute to a much-needed discussion in the neuroscientific community

A Biologically Plausible Architecture of the Striatum to Solve Context-Dependent Reinforcement Learning Tasks

Basal ganglia circuit is an important subcortical system of the brain thought to be responsible for reward-based learning. Striatum, the largest nucleus of the basal ganglia, serves as an input port that maps cortical information. Microanatomical studies show that the striatum is a mosaic of specialized input-output structures called striosomes and regions of the surrounding matrix called the matrisomes. We have developed a computational model of the striatum using layered self-organizing maps to capture the center-surround structure seen experimentally and explain its functional significance. We believe that these structural components could build representations of state and action spaces in different environments. The striatum model is then integrated with other components of basal ganglia, making it capable of solving reinforcement learning tasks. We have proposed a biologically plausible mechanism of action-based learning where the striosome biases the matrisome activity toward a preferred action. Several studies indicate that the striatum is critical in solving context dependent problems. We build on this hypothesis and the proposed model exploits the modularity of the striatum to efficiently solve such tasks

A confirmation bias due to approximate active inference

Collecting new information about the outside world is a key aspect of brain function. In the context of vision, we move our eyes multiple times per second to accumulate evidence about a scene. Prior studies have suggested that this process is goal-directed and close to optimal. Here, we show that this process of seeking new information suffers from a confirmation bias similar to what has been observed in a wide range of other contexts. We present data from a new gaze-contingent task that allows us to both estimate a participant's current belief, and compare that to their subsequent eye-movements. We find that these eye-movements are biased in a confirmatory way. Finally, we show that these empirical results can be parsimoniously explained under the assumption that the brain performs approximate, not exact, inference, with computations being more approximate in decision-making compared to sensory areas

A confirmation bias due to approximate active inference

Collecting new information about the outside world is a key aspect of brain function. In the context of vision, we move our eyes multiple times per second to accumulate evidence about a scene. Prior studies have suggested that this process is goal-directed and close to optimal. Here, we show that this process of seeking new information suffers from a confirmation bias similar to what has been observed in a wide range of other contexts. We present data from a new gaze-contingent task that allows us to both estimate a participant's current belief, and compare that to their subsequent eye-movements. We find that these eye-movements are biased in a confirmatory way. Finally, we show that these empirical results can be parsimoniously explained under the assumption that the brain performs approximate, not exact, inference, with computations being more approximate in decision-making compared to sensory areas

Prevalence of tobacco habits and oral health status of adolescents in Lucknow district: A cross-sectional descriptive study

Background: Tobacco use among youth is increasing in epidemic proportions across the world. Tobacco use among adolescents is a priority health risk behavior that contributes to increased morbidity and mortality, which is mostly preventable. Aim: To assess the prevalence of various tobacco habits among the adolescents of Lucknow and the related oral mucosal lesions present. Materials and Methods: A cross-sectional study was designed comprising urban and rural schoolgoing students (males and females); within 12-19 years of age in Lucknow. Areas from both urban and rural Lucknow were selected for the study. A pro forma with two parts was filled in details, and the oral hygiene was examined with Oral Hygiene status score. Results: The presence of oral mucosal condition was found in 11.53% of adolescents and had significant results (P < 0.001). The urban and rural adolescents were, respectively, at 1.9- and 9.66- times higher risk of developing dental caries in association with pan masala chewing habit (statistically significant; P < 0.0001). Conclusion: Dental practitioners should donate to enhance oral health by including oral examination as a mandatory daily clinical practice along with proper tobacco counseling and imparting satisfactory diet charts, and denoting patients to specific oral health clinicians for care

Task-uninformative visual stimuli improve auditory spatial discrimination in humans but not the ideal observer.

In order to survive and function in the world, we must understand the content of our environment. This requires us to gather and parse complex, sometimes conflicting, information. Yet, the brain is capable of translating sensory stimuli from disparate modalities into a cohesive and accurate percept with little conscious effort. Previous studies of multisensory integration have suggested that the brain's integration of cues is well-approximated by an ideal observer implementing Bayesian causal inference. However, behavioral data from tasks that include only one stimulus in each modality fail to capture what is in nature a complex process. Here we employed an auditory spatial discrimination task in which listeners were asked to determine on which side they heard one of two concurrently presented sounds. We compared two visual conditions in which task-uninformative shapes were presented in the center of the screen, or spatially aligned with the auditory stimuli. We found that performance on the auditory task improved when the visual stimuli were spatially aligned with the auditory stimuli-even though the shapes provided no information about which side the auditory target was on. We also demonstrate that a model of a Bayesian ideal observer performing causal inference cannot explain this improvement, demonstrating that humans deviate systematically from the ideal observer model

Leiomyosarcoma of inferior vena cava involving bilateral renal veins: Surgical challenges and reconstruction with upfront saphenous vein interposition graft for left renal vein outflow

Leiomyosarcoma of inferior vena cava (IVC) involving bilateral renal veins presents a surgical challenge. Herein, we report the successful management of two such cases using restoration of left renal venous outflow by saphenous vein interposition graft as first step of surgery. Then radical resection of tumor and right kidney was done. IVC was lastly reconstructed using Gore-Tex graft. This report highlights the surgical challenges to ensure radical resection. Furthermore, the importance of restoring left renal outflow in presence of concomitant right nephrectomy is discussed. Both the patients were disease free at six months with no loss of left renal glomerular filtration rate