Linking Symptom Inventories using Semantic Textual Similarity

An extensive library of symptom inventories has been developed over time to measure clinical symptoms, but this variety has led to several long standing issues. Most notably, results drawn from different settings and studies are not comparable, which limits reproducibility. Here, we present an artificial intelligence (AI) approach using semantic textual similarity (STS) to link symptoms and scores across previously incongruous symptom inventories. We tested the ability of four pre-trained STS models to screen thousands of symptom description pairs for related content - a challenging task typically requiring expert panels. Models were tasked to predict symptom severity across four different inventories for 6,607 participants drawn from 16 international data sources. The STS approach achieved 74.8% accuracy across five tasks, outperforming other models tested. This work suggests that incorporating contextual, semantic information can assist expert decision-making processes, yielding gains for both general and disease-specific clinical assessment

Toward a global and reproducible science for brain imaging in neurotrauma: the ENIGMA adult moderate/severe traumatic brain injury working group

Abstract: The global burden of mortality and morbidity caused by traumatic brain injury (TBI) is significant, and the heterogeneity of TBI patients and the relatively small sample sizes of most current neuroimaging studies is a major challenge for scientific advances and clinical translation. The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Adult moderate/severe TBI (AMS-TBI) working group aims to be a driving force for new discoveries in AMS-TBI by providing researchers world-wide with an effective framework and platform for large-scale cross-border collaboration and data sharing. Based on the principles of transparency, rigor, reproducibility and collaboration, we will facilitate the development and dissemination of multiscale and big data analysis pipelines for harmonized analyses in AMS-TBI using structural and functional neuroimaging in combination with non-imaging biomarkers, genetics, as well as clinical and behavioral measures. Ultimately, we will offer investigators an unprecedented opportunity to test important hypotheses about recovery and morbidity in AMS-TBI by taking advantage of our robust methods for large-scale neuroimaging data analysis. In this consensus statement we outline the working group’s short-term, intermediate, and long-term goals

Toward a global and reproducible science for brain imaging in neurotrauma: the ENIGMA adult moderate/severe traumatic brain injury working group

Abstract: The global burden of mortality and morbidity caused by traumatic brain injury (TBI) is significant, and the heterogeneity of TBI patients and the relatively small sample sizes of most current neuroimaging studies is a major challenge for scientific advances and clinical translation. The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Adult moderate/severe TBI (AMS-TBI) working group aims to be a driving force for new discoveries in AMS-TBI by providing researchers world-wide with an effective framework and platform for large-scale cross-border collaboration and data sharing. Based on the principles of transparency, rigor, reproducibility and collaboration, we will facilitate the development and dissemination of multiscale and big data analysis pipelines for harmonized analyses in AMS-TBI using structural and functional neuroimaging in combination with non-imaging biomarkers, genetics, as well as clinical and behavioral measures. Ultimately, we will offer investigators an unprecedented opportunity to test important hypotheses about recovery and morbidity in AMS-TBI by taking advantage of our robust methods for large-scale neuroimaging data analysis. In this consensus statement we outline the working group’s short-term, intermediate, and long-term goals

An investigation of striatal activity during delayed and effort-based learning

Motivation influences human learning and outcome valuation. Depending on the context, one can interpret an outcome in a positive way or not pay attention to the action outcome at all. The striatum is one of the primary structures involved in outcome valuation and learning and of action-outcome contingencies. Striatal activity has been shown to be context-dependent and to reflect individuals’ subjective preferences. This dissertation examined striatal activity in the context of delayed and effort-based learning, as well as whether people are willing to overcome effort costs in order to benefit an unfamiliar disadvantaged person. Two functional magnetic resonance imaging experiments were conducted examining striatal activity during performance-related feedback under different time frames (Experiment 1) and following different cognitive effort requirements (Experiment 2). Behavioral Experiment 3 looked at whether individuals are willing to exert cognitive effort during learning to reduce inequity between themselves and a disadvantaged individual. Experiment 1 replicated previous findings of ventral striatal activation to immediate feedback presentation. It was also shown that when feedback is presented after a substantial delay of 25 minutes, processing of feedback switches away from the striatum to posterior parts of the basal ganglia. Experiment 2 revealed that activity of the ventral striatum associated with feedback reflects effort expenditure required to obtain it. Experiment 3 showed that unfair social context can motivate individuals to exert cognitive effort during learning. This work shows that striatal response to learning outcomes is differentially influenced by delay and effort requirements and that effort costs can motivate learning.Ph. D.Includes bibliographical referencesIncludes vitaby Ekaterina Dobryakov

Neural Correlates of Outcome Anticipation in Multiple Sclerosis

Outcome anticipation is not only a mental preparation for upcoming consequences, but also an essential component of learning and decision-making. Thus, anticipation of consequences is a key process in everyday functioning. The striatum and the ventromedial prefrontal cortex are among the key regions that have been shown to be involved in outcome anticipation. However, while structural abnormalities of these regions as well as altered decision-making have been noted in individuals with multiple sclerosis (MS), neural correlates of outcome anticipation have not been explored in this population. Thus, we examined the neural correlates of outcome anticipation in MS by analyzing brain activation in individuals with MS while they performed a modified version of a card-guessing task. Seventeen MS and 13 healthy controls performed the task while functional magnetic resonance imaging (fMRI) was obtained. To achieve maximal anticipatory response and prevent the possibility of differential performance on the task, participants were presented with monetary rewards only on 50% of the trials. While replicating previous evidence of structural abnormalities of the striatum in MS, our results further showed that individuals with MS exhibited greater activation in the putamen, right hippocampus, and posterior cingulate cortex during outcome anticipation compared to healthy controls. Furthermore, even though there was no strategy that participants could learn in order to predict outcomes, 76% of participants with MS indicated that they used strategies while performing the task. We thus propose that the increased neural activation observed in MS during outcome anticipation might be explained by a failure in recognizing the lack of regularity in the task structure that could result in using strategies to perform the task