Active Working Memory and Simple Cognitive Operations

Working memory is thought to serve as a buffer for ongoing cognitive operations, even in tasks that have no obvious memory requirements. This conceptualization has been supported by dual-task experiments, in which interference is observed between a primary task involving short-term memory storage and a secondary task that presumably requires the same buffer as the primary task. Little or no interference is typically observed when the secondary task is very simple. Here, we test the hypothesis that even very simple tasks require the working memory buffer, but interference can be minimized by using activity-silent representations to store the information from the primary task. We tested this hypothesis using dual-task paradigm in which a simple discrimination task was interposed in the retention interval of a change detection task. We used contralateral delay activity (CDA) to track the active maintenance of information for the change detection task. We found that the CDA was massively disrupted after the interposed task. Despite this disruption of active maintenance, we found that performance in the change detection task was only slightly impaired, suggesting that activity-silent representations were used to retain the information for the change detection task. A second experiment replicated this result and also showed that automated discriminations could be performed without producing a large CDA disruption. Together, these results suggest that simple but non-automated discrimination tasks require the same processes that underlie active maintenance of information in working memory.

Similarity of Computations Across Domains Does Not Imply Shared Implementation: The Case of Language Comprehension

Understanding language requires applying cognitive operations (e.g., memory retrieval, prediction, structure building) that are relevant across many cognitive domains to specialized knowledge structures (e.g., a particular language’s lexicon and syntax). Are these computations carried out by domain-general circuits or by circuits that store domain-specific representations? Recent work has characterized the roles in language comprehension of the language network, which is selective for high-level language processing, and the multiple-demand (MD) network, which has been implicated in executive functions and linked to fluid intelligence and thus is a prime candidate for implementing computations that support information processing across domains. The language network responds robustly to diverse aspects of comprehension, but the MD network shows no sensitivity to linguistic variables. We therefore argue that the MD network does not play a core role in language comprehension and that past findings suggesting the contrary are likely due to methodological artifacts. Although future studies may reveal some aspects of language comprehension that require the MD network, evidence to date suggests that those will not be related to core linguistic processes such as lexical access or composition. The finding that the circuits that store linguistic knowledge carry out computations on those representations aligns with general arguments against the separation of memory and computation in the mind and brain.

Distinct Contributions of the Cerebellum and Basal Ganglia to Arithmetic Procedures

Humans exhibit complex mathematical skills, often attributed to the exceptionally large neocortex. Using a neuropsychological approach, we report that degeneration within two subcortical structures, the basal ganglia and cerebellum, impairs performance in symbolic arithmetic. Moreover, we identify distinct computational impairments in individuals with Parkinson’s disease (PD) or cerebellar degeneration (CD). The CD group exhibited a disproportionate cost when arithmetic sum increased, suggesting that the cerebellum is critical for iterative procedures required for calculations. The PD group exhibited a disproportionate cost for equations with an increasing number of addends, suggesting that the basal ganglia are critical for the coordination of multiple cognitive operations. In Experiment 2, the two patient groups exhibited intact practice gains for repeated equations at odds with an alternative hypothesis that these impairments were related to memory retrieval. Overall, the results provide a novel demonstration of the contribution of subcortical structures to the computations required for complex cognition.

Couching the brain's multiple-demand and language-specific systems within a macroscale gradient of cortical connectivity

The cerebrum comprises a set of specialised systems that tile across the cortical sheet, forming a tapestry-like configuration. For example, the multiple-demand and language-specific systems occupy largely separate neural estates and exhibit disparate functional profiles. Although delimiting the boundary between systems informs where cortical sheet functionally fractionates, it remains unclear why different systems' topographical placements are spatially configured in typical manners and how a macroscale architecture arises from this topography. Novel approaches have tackled this challenge by condensing the topography into a principal gradient, which represents the workflow of information processing from sensory-motoric to abstract-cognitive. To understand how the multiple-demand and language-specific systems are accommodated in the gradient framework, here we used fMRI to probe cognitive operations in semantic vs. visuospatial domains and projected functional activities onto the principal gradient. We found that the two systems showed distinct trajectories of distribution along gradient tiers, suggesting different roles in the transition from sensation to cognition. Critically, when semantic processing became difficult, the brain recruited a specialised 'semantic-control' system that was a functional and anatomical 'hybrid' juxtaposed between the multi-demand and language systems. We discuss how the brain's modular division can be better understood through the lens of a dimensionality-reduced gradient-like architecture.

Inter- and intratextual relations as components of micro-image in literary texts and ways of their translation

В статье интер- и интратекстуальные взаимодействия рассматриваются как важнейшие текстообразующие категории художественного произведения, назначение которых — обогатить авторские микрообразы новыми смыслами. На примере перевода отрывков из произведений А. П. Чехова на китайский язык и Лю Чжэньюня на русский язык доказывается работоспособность алгоритма передачи микрообраза, разработанного авторами с учетом когнитивных механизмов, лежащих в основе исследуемых аллюзивных отсылок. The article views inter- and intratextual relations as important textual categories of literary works enriching micro-images with new meanings and implications. The authors suggest an algorithm for rendering such micro-images, involving inter- and intratextual relations, to be used in the process of translation. A number of excerpts from A. Chekhov translated into Chinese and Liu Zhenyun translated into Russian the authors prove the algorithm suggested to be applicable and useful, as it takes into consideration the underlying cognitive operations and mechanisms.

A universal framework for vocal interaction

Vocal interaction is an important feature of social behavior across species, however the relation between vocal communication in humans and nonhumans remains unclear. To enable comparative investigations of this topic, we review the literature pertinent to interactive language use and identify the superset of cognitive operations involved in generating communicative behavior. We posit these functions to comprise three multistep pathways: (1) the Content Pathway, which selects the movements constituting a response, (2) the Timing Pathway, which temporally structures responses, and (3) the Affect Pathway, which modulates response parameters as a function of internal state. These processing streams form the basis of the Convergent Pathways for Interaction (CPI) Framework, which can be used to contextualize communicative behaviors across species by identifying specific behavioral and cognitive analogues.

A Theoretical Framework for a Hybrid View of the N400

In this study, we present a novel theoretical account of the N400 event-related potential (ERP) component. Hybrid views interpret this ERP component in terms of two cognitive operations: (i) access of information, which is related to predictions (predictability component), and (ii) integration of information, which is related to plausibility (plausibility component). Though there is an empirical evidence for this view, what has been left open so far is how these two operations can be defined. In our approach, both components are related to categorization. The critical word and the argument position it is related to are associated with categories that have a graded structure. This graded structure is defined in terms of weights both on attributes and values of features belonging to a category. The weights, in turn, are defined using probability distributions. The predictability component is defined in terms of the information gain with respect to non mismatched features between the two categories. The plausibility component is defined as the difference in the degree of typicality between the two categories. Finally, the N400 amplitude is defined as a function of both components.

Remote Usability Assessment of Topic Visualization Interfaces with Public Participation Data: A Case Study

Citizen participation often faces challenges of transparency and accountability. Visualizations’s usability becomes key for public consultation activities. The tree map is frequently used to disseminate data and to give it back to the population. The purpose of this study is to understand how tree maps and stacked barcharts differ in terms of effectiveness, efficiency, and satisfaction in tasks, like solving topic categorization and comparison analysis tasks. An experimental design was used to examine user performance based on a task-based usability test. 34 participants interacted remotely with data visualizations from an open 2016 participatory constitution-making process. The ANOVA showed that stacked barcharts work significantly better for comparison tasks than the tree map, but there are no significant differences in regards to categorization tasks. Public participation initiatives should first determine what cognitive operations their users perform before deciding which visualization interfaces will be more useful for the intended public.