Rapid individual cognitive phenotyping holds the potential to revolutionize domains as wide‐ranging as personalized learning, employment practices, and precision psychiatry. Going beyond limitations imposed by traditional lab‐based experiments, new efforts have been underway toward greater ecological validity and participant diversity to capture the full range of individual differences in cognitive abilities and behaviors across the general population. Building on this, we developed Skill Lab, a novel game‐based tool that simultaneously assesses a broad suite of cognitive abilities while providing an engaging (...) narrative. Skill Lab consists of six mini‐games as well as 14 established cognitive ability tasks. Using a popular citizen science platform (N = 10,725), we conducted a comprehensive validation in the wild of a game‐based cognitive assessment suite. Based on the game and validation task data, we constructed reliable models to simultaneously predict eight cognitive abilities based on the users’ in‐game behavior. Follow‐up validation tests revealed that the models can discriminate nuances contained within each separate cognitive ability as well as capture a shared main factor of generalized cognitive ability. Our game‐based measures are five times faster to complete than the equivalent task‐based measures and replicate previous findings on the decline of certain cognitive abilities with age in our large cross‐sectional population sample (N = 6369). Taken together, our results demonstrate the feasibility of rapid in‐the‐wild systematic assessment of cognitive abilities as a promising first step toward population‐scale benchmarking and individualized mental health diagnostics. (shrink)

Proponents of the predictive processing (PP) framework often claim that one of the framework’s significant virtues is its unificatory power. What is supposedly unified are predictive processes in the mind, and these are explained in virtue of a common prediction error-minimisation (PEM) schema. In this paper, I argue against the claim that PP currently converges towards a unified explanation of cognitive processes. Although the notion of PEM systematically relates a set of posits such as ‘efficiency’ and ‘hierarchical coding’ into a (...) unified conceptual schema, neither the frameworks’ algorithmic specifications nor its hypotheses about their implementations in the brain are clearly unified. I propose a novel way to understand the fruitfulness of the research program in light of a set of research heuristics that are partly shared with those common to Bayesian reverse engineering. An interesting consequence of this proposal is that pluralism is at least as important as unification to promote the positive development of the predictive mind. (shrink)

We present computational modeling results based on a self‐paced reading study investigating number attraction effects in Eastern Armenian. We implement three novel computational models of agreement attraction in a Bayesian framework and compare their predictive fit to the data using k‐fold cross‐validation. We find that our data are better accounted for by an encoding‐based model of agreement attraction, compared to a retrieval‐based model. A novel methodological contribution of our study is the use of comprehension questions with open‐ended responses, so that (...) both misinterpretation of the number feature of the subject phrase and misassignment of the thematic subject role of the verb can be investigated at the same time. We find evidence for both types of misinterpretation in our study, sometimes in the same trial. However, the specific error patterns in our data are not fully consistent with any previously proposed model. (shrink)

Cognitive Science, Volume 46, Issue 9, September 2022.

Recently, the mechanistic framework of active inference has been put forward as a principled foundation to develop an overarching theory of consciousness which would help address conceptual disparities in the field (Wiese 2018 ; Hohwy and Seth 2020 ). For that promise to bear out, we argue that current proposals resting on the active inference scheme need refinement to become a process theory of consciousness. One way of improving a theory in mechanistic terms is to use formalisms such as computational (...) models that implement, attune and validate the conceptual notions put forward. Here, we examine how computational modelling approaches have been used to refine the theoretical proposals linking active inference and consciousness, with a focus on the extent and success to which they have been developed to accommodate different facets of consciousness and experimental paradigms, as well as how simulations and empirical data have been used to test and improve these computational models. While current attempts using this approach have shown promising results, we argue they remain preliminary in nature. To refine their predictive and structural validity, testing those models against empirical data is needed i.e., new and unobserved neural data. A remaining challenge for active inference to become a theory of consciousness is to generalize the model to accommodate the broad range of consciousness explananda; and in particular to account for the phenomenological aspects of experience. Notwithstanding these gaps, this approach has proven to be a valuable avenue for theory advancement and holds great potential for future research. (shrink)

Existing research has identified the importance of role models in the imitation of cooperative behaviors. This Pre-Study attempted to explore the contagion effects of cooperative models. Drawing on goal contagion theory, we proposed that encountering cooperative models could catalyze participants’ cooperation when participants joined new groups without role models, and that moral elevation and calling would play a chain-mediating role in this process. To test the hypothesis, we designed a four-person public goods game consisting of two phases in which participants (...) were formed into teams with different people in each phase. We randomly assigned 108 participants to either a consistent contributor (CC) or control condition. The only difference was that participants in the CC condition encountered a cooperative role model (i.e., CC) in the first phase, while those in the control group did not. The results moderately supported all hypotheses. Briefly, our findings provide empirical evidence supporting the two processes of goal contagion theory: when individuals encounter a CC, they first make inferences about the CC’s goal, as reflected by moral elevation, and then adopt the model’s prosocial goals (i.e., calling), resulting in increased cooperative behaviors in new groups. These findings could extend our understanding of the contagion effect of cooperative modeling, but require high-powered replication studies before such conclusions can be drawn. (shrink)

Can sentence comprehension impairments in aphasia be explained by difficulties arising from dependency completion processes in parsing? Two distinct models of dependency completion difficulty are investigated, the Lewis and Vasishth (2005) activation-based model and the direct-access model (DA; McElree, 2000). These models' predictive performance is compared using data from individuals with aphasia (IWAs) and control participants. The data are from a self-paced listening task involving subject and object relative clauses. The relative predictive performance of the models is evaluated using k-fold (...) cross-validation. For both IWAs and controls, the activation-based model furnishes a somewhat better quantitative fit to the data than the DA. Model comparisons using Bayes factors show that, assuming an activation-based model, intermittent deficiencies may be the best explanation for the cause of impairments in IWAs, although slowed syntax and lexical delayed access may also play a role. This is the first computational evaluation of different models of dependency completion using data from impaired and unimpaired individuals. This evaluation develops a systematic approach that can be used to quantitatively compare the predictions of competing models of language processing. (shrink)

Can sentence comprehension impairments in aphasia be explained by difficulties arising from dependency completion processes in parsing? Two distinct models of dependency completion difficulty are investigated, the Lewis and Vasishth (2005) activation‐based model and the direct‐access model (DA; McElree, 2000). These models' predictive performance is compared using data from individuals with aphasia (IWAs) and control participants. The data are from a self‐paced listening task involving subject and object relative clauses. The relative predictive performance of the models is evaluated using k‐fold (...) cross‐validation. For both IWAs and controls, the activation‐based model furnishes a somewhat better quantitative fit to the data than the DA. Model comparisons using Bayes factors show that, assuming an activation‐based model, intermittent deficiencies may be the best explanation for the cause of impairments in IWAs, although slowed syntax and lexical delayed access may also play a role. This is the first computational evaluation of different models of dependency completion using data from impaired and unimpaired individuals. This evaluation develops a systematic approach that can be used to quantitatively compare the predictions of competing models of language processing. (shrink)