Logistic Mixed Models to Investigate Implicit and Explicit Belief Tracking.
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ABSTRACT:
SUBMITTER: Lages M
PROVIDER: S-EPMC5090957 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Humans rely on their ability to infer another person's mental state to understand and predict others' behavior ("theory of mind," ToM). Multiple lines of research suggest that not only are humans able to consciously process another person's belief state, but also are able to do so implicitly. Here we explored how general implicit belief states are represented in the brain, compared to those substrates involved in explicit ToM processes. Previous work on this topic has yielded conflicting results, and thus, the extent to which the implicit and explicit ToM systems draw on common neural bases is unclear. Participants were presented with "Sally-Anne" type movies in which a protagonist was falsely led to believe a ball was in one location, only for a puppet to later move it to another location in their absence (false-belief condition). In other movies, the protagonist had their back turned the entire time the puppet moved the ball between the two locations, meaning that they had no opportunity to develop any pre-existing beliefs about the scenario (no-belief condition). Using a group of independently localized explicit ToM brain regions, we found greater activity for false-belief trials, relative to no-belief trials, in the right temporoparietal junction, right superior temporal sulcus, precuneus, and left middle prefrontal gyrus. These findings extend upon previous work on the neural bases of implicit ToM by showing substantial overlap between this system and the explicit ToM system, suggesting that both abilities might recruit a common set of mentalizing processes/functional brain regions. Hum Brain Mapp 38:4760-4772, 2017. © 2017 Wiley Periodicals, Inc.
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Project description:To study social sequence learning, earlier functional magnetic resonance imaging (fMRI) studies investigated the neural correlates of a novel Belief Serial Reaction Time task in which participants learned sequences of beliefs held by protagonists. The results demonstrated the involvement of the mentalizing network in the posterior cerebellum and cerebral areas (e.g. temporoparietal junction, precuneus and temporal pole) during implicit and explicit social sequence learning. However, little is known about the neural functional interaction between these areas during this task. Dynamic causal modeling analyses for both implicit and explicit belief sequence learning revealed that the posterior cerebellar Crus I & II were effectively connected to cerebral mentalizing areas, especially the bilateral temporoparietal junction, via closed loops (i.e. bidirectional functional connections that initiate and terminate at the same cerebellar and cerebral areas). There were more closed loops during implicit than explicit learning, which may indicate that the posterior cerebellum may be more involved in implicitly learning sequential social information. Our analysis supports the general view that the posterior cerebellum receives incoming signals from critical mentalizing areas in the cerebrum to identify sequences of social actions and then sends signals back to the same cortical mentalizing areas to better prepare for others' social actions and one's responses to it.
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Project description:Schizophrenia has been characterized by an impaired mentalizing. It has been suggested that distinguishing implicit from explicit processes is crucial in social cognition, and only the latter might be affected in schizophrenia. Two other questions remain open: (1) Is schizophrenia characterized by an hypo- or hyper attribution of intentions? (2) Is it characterized by a deficit in the attribution of intention or of contingency? To test these three questions, spontaneous mentalizing was tested in 29 individuals with schizophrenia and 29 control subjects using the Frith-Happé animations, while eye movements were recorded. Explicit mentalizing was measured from participants' verbal descriptions and was contrasted with implicit mentalizing measured through eye tracking. As a group, patients made less accurate and less intentional descriptions of the goal-directed and theory of mind animations. No group differences were found in the attribution of contingency. Eye tracking results revealed that patients and controls showed a similar modulation of eye movements in response to the mental states displayed in the Frith-Happé animations. To conclude, in this paradigm, participants with schizophrenia showed a dissociation between explicit and implicit mentalizing, with a decrease in the explicit attribution of intentions, whereas their eye movements suggested a preserved implicit perception of intentions.
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Project description:We propose a consistent and locally efficient estimator to estimate the model parameters for a logistic mixed effect model with random slopes. Our approach relaxes two typical assumptions: the random effects being normally distributed, and the covariates and random effects being independent of each other. Adhering to these assumptions is particularly difficult in health studies where in many cases we have limited resources to design experiments and gather data in long-term studies, while new findings from other fields might emerge, suggesting the violation of such assumptions. So it is crucial if we could have an estimator robust to such violations and then we could make better use of current data harvested using various valuable resources. Our method generalizes the framework presented in Garcia & Ma (2016) which also deals with a logistic mixed effect model but only considers a random intercept. A simulation study reveals that our proposed estimator remains consistent even when the independence and normality assumptions are violated. This contrasts from the traditional maximum likelihood estimator which is likely to be inconsistent when there is dependence between the covariates and random effects. Application of this work to a Huntington disease study reveals that disease diagnosis can be further improved using assessments of cognitive performance.
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Project description:The precise description of solute-water interactions is essential to understand the chemo-physical nature in hydration processes. Such a hydration thermodynamics for various solutes has been explored by means of explicit or implicit solvation methods. Using the Poisson-Boltzmann solvation model, the implicit models are well designed to reasonably predict the hydration free energies of polar solutes. The implicit model, however, is known to have shortcomings in estimating those for non-polar aromatic compounds. To investigate a cause of error, we employed a novel systematic framework of quantum-mechanical/molecular-mechanical (QM/MM) coupling protocol in explicit solvation manner, termed DFT-CES, based on the grid-based mean-field treatment. With the aid of DFT-CES, we delved into multiple energy parts, thereby comparing DFT-CES and PB models component-by-component. By applying the modified PB model to estimate the hydration free energies of non-polar solutes, we find a possibility to improve the predictability of PB models. We expect that this study could shed light on providing an accurate route to study the hydration thermodynamics for various solute compounds.
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Project description:With many sophisticated methods available for estimating migration, ecologists face the difficult decision of choosing for their specific line of work. Here we test and compare several methods, performing sanity and robustness tests, applying to large-scale data and discussing the results and interpretation. Five methods were selected to compare for their ability to estimate migration from spatially implicit and semi-explicit simulations based on three large-scale field datasets from South America (Guyana, Suriname, French Guiana and Ecuador). Space was incorporated semi-explicitly by a discrete probability mass function for local recruitment, migration from adjacent plots or from a metacommunity. Most methods were able to accurately estimate migration from spatially implicit simulations. For spatially semi-explicit simulations, estimation was shown to be the additive effect of migration from adjacent plots and the metacommunity. It was only accurate when migration from the metacommunity outweighed that of adjacent plots, discrimination, however, proved to be impossible. We show that migration should be considered more an approximation of the resemblance between communities and the summed regional species pool. Application of migration estimates to simulate field datasets did show reasonably good fits and indicated consistent differences between sets in comparison with earlier studies. We conclude that estimates of migration using these methods are more an approximation of the homogenization among local communities over time rather than a direct measurement of migration and hence have a direct relationship with beta diversity. As betadiversity is the result of many (non)-neutral processes, we have to admit that migration as estimated in a spatial explicit world encompasses not only direct migration but is an ecological aggregate of these processes. The parameter m of neutral models then appears more as an emerging property revealed by neutral theory instead of being an effective mechanistic parameter and spatially implicit models should be rejected as an approximation of forest dynamics.
| S-EPMC5478059 | biostudies-literature
Project description:Human movement can be guided automatically (implicit control) or attentively (explicit control). Explicit control may be engaged when learning a new movement, while implicit control enables simultaneous execution of multiple actions. Explicit and implicit control can often be assigned arbitrarily: we can simultaneously drive a car and tune the radio, seamlessly allocating implicit or explicit control to either action. This flexibility suggests that sensorimotor signals, including those that encode spatially overlapping perception and behavior, can be accurately segregated to explicit and implicit control processes.We tested human subjects' ability to segregate sensorimotor signals to parallel control processes by requiring dual (explicit and implicit) control of the same reaching movement and testing for interference between these processes. Healthy control subjects were able to engage dual explicit and implicit motor control without degradation of performance compared to explicit or implicit control alone. We then asked whether segregation of explicit and implicit motor control can be selectively disrupted by studying dual-control performance in subjects with no clinically manifest neurologic deficits in the presymptomatic stage of Huntington's disease (HD). These subjects performed successfully under either explicit or implicit control alone, but were impaired in the dual-control condition.The human nervous system can exert dual control on a single action, and is therefore able to accurately segregate sensorimotor signals to explicit and implicit control. The impairment observed in the presymptomatic stage of HD points to a possible crucial contribution of the striatum to the segregation of sensorimotor signals to multiple control processes.
| S-EPMC2760763 | biostudies-other
Project description:To investigate whether people can implicitly learn regularities in a social context, we developed a new implicit sequence learning task combining elements from classic false belief and serial reaction time tasks. Participants learned that protagonists were offered flowers at four locations. The protagonists' beliefs concerning the flowers were true or false, depending on their orientation, respectively, toward the scene (so that the flowers could be seen) or away from it. Unbeknown to the participants, there was a fixed belief-related sequence involving three dimensions (identity of the two protagonists, true-false belief orientation held by the protagonists, and flower location as believed by the protagonists). Participants had to indicate as fast as possible where the flowers were located (Experiment 1), or how many flowers were given (Experiment 2) according to the protagonists. Experiment 1 combined perceptual and motor processes (as both the belief-related sequence and motor responses referred to location), whereas Experiment 2 unconfounded the sequence and motor responses, allowing to investigate pure perceptual implicit learning. For reasons of comparison, two non-social conditions were created in Experiment 2 by replacing the protagonists with two non-social objects-colored cameras or shapes. Results revealed significant implicit sequence learning of all belief-related dimensions in Experiment 1, and of true-false belief orientation in Experiment 2, even without a motor confound. Importantly, there were faster reaction times and stronger sequence learning effects in the social than in the non-social conditions. The present findings demonstrate for the first time that people are able to implicitly learn belief-related sequences.
| S-EPMC8032999 | biostudies-literature
Project description:Purpose We present functional logistic mixed-effects models (FLMEMs) for estimating population and individual-level learning curves in longitudinal experiments. Method Using functional analysis tools in a Bayesian hierarchical framework, the FLMEM captures nonlinear, smoothly varying learning curves, appropriately accommodating uncertainty in various aspects of the analysis while also borrowing information across different model layers. An R package implementing our method is available as part of the Supplemental Materials . Results Application to speech learning data from Reetzke, Xie, Llanos, and Chandrasekaran (2018) and a simulation study demonstrate the utility of FLMEM and its many advantages over linear and logistic mixed-effects models. Conclusion The FLMEM is highly flexible and efficient in improving upon the practical limitations of linear models and logistic linear mixed-effects models. We expect the FLMEM to be a useful addition to the speech, language, and hearing scientist's toolkit. Supplemental Material https://doi.org/10.23641/asha.7822568.
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Project description:Distinct aspects of our fearful experiences appear to be mediated by separate explicit and implicit memory processes. To identify brain regions that support these separate memory processes, we measured contingency awareness, conditional fear expression, and functional magnetic resonance imaging signal during a Pavlovian fear conditioning procedure in which tones that predicted an aversive event were presented at supra and sub-threshold volumes. Contingency awareness developed in conjunction with learning-related hippocampal and parahippocampal activity on perceived conditioning trials only. In contrast, conditional fear and differential amygdala activity developed on both perceived and unperceived trials, regardless of whether contingency awareness was expressed. These findings demonstrate the distinct roles of these brain regions in explicit and implicit fear memory processes.
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