More focal, less heterogeneous? Multi-level Meta-Analysis of Cathodal High-Definition Transcranial Direct Current Stimulation Effects on Language and Cognition

High-definition transcranial direct current stimulation (HD-tDCS) is a relatively focal, novel non-invasive brain stimulation method with the potential to investigate causal contribution of specific cortical brain regions to language and cognition. Studies with HD-tDCS typically employ a 4×1 electrode design with a single central target electrode surrounded by four return electrodes, among which return current intensity is evenly distributed. With cathodal HD-tDCS, neural excitability in the target region is assumed to be reduced, which offers interesting perspectives for psychological research and interventions. This multi-level meta-analysis compiles published studies using cathodal HD-tDCS in 4×1 configuration to modulate cognition and behavior. In total, 11 eligible reports were included with 2-15 effect sizes within each study, yielding 77 effect sizes in total. We observed no significant overall effect and no moderation by within-study and between-study variables. However, studies varied tremendously in task parameters, outcomes, and even technical parameters. Interestingly, within-study heterogeneity exceeded between-study heterogeneity in the present sample, and moderators hardly reduced the residual heterogeneity. Across domains and configurations, both positive and negative effect sizes are possible. We discuss the findings in relation to conventional cathodal tDCS and the framework of polarity specificity. Fundamental aspects of cathodal HD-tDCS are still to be addressed in future research.

Multiple representational and dynamic conceptual analysis in the wild

Cognitive semantics has different research methods, such as introspection, corpora analysis, interaction analysis, and experiments. The analysis of “data in the wild” (corpora and interaction) is generally informed by theories, but rarely by the current landscape of experiments’ findings on language and cognition. The goal of this paper is twofold: first, we want to highlight the possibility and importance of shortening the gap between theory, empirical evidence, and analysis of data in the wild in the study of cognition. Second, we suggest that resorting to the state of the art of empirical research about language and cognition allows for more flexible analyses, which may surpass the limits of current theories. In order to do that, we (i) provide a current overview of neuro and psycholinguistic findings about the grounding of concrete and abstract concepts, (ii) discuss how these findings can support linguistic data analysis, and (iii) emphasize trends toward multiple representation theories and dynamic systems.

The intrinsic frame of reference and the Dhivehi ‘FIBO’ system

While geocentric and relative frames of reference have figured prominently in the literature on spatial language and cognition, the intrinsic frame of reference has received less attention, though various subtypes of the intrinsic frame have been proposed. This paper presents a revised classification of the intrinsic frame, distinguishing between three subtypes: a ‘direct’ subtype, an ‘object-centered’ subtype and a ‘figure-anchored’ subtype, with a cross-cutting distinction between ‘function-based’ and ‘shape-based’ systems. In addition, the ‘FIBO’ (front = inner, back = outer) system in Dhivehi is analyzed as an example of a borderline case, with some important features of the intrinsic frame but also some differences, presenting a challenge for existing frame of reference classifications. The rotational properties of these various systems are also considered. The analysis underscores the considerable diversity within intrinsic systems but also points to a closer relationship between intrinsic and extrinsic frames than has previously been appreciated. This may have implications for broader theoretical issues including how frames of reference are acquired, how speech communities come to use different frames and whether patterns of frame use in discourse shape patterns of non-verbal frame use.

Laminar Computing by Cerebral Cortex

The cerebral cortex computes the highest forms of biological intelligence in all sensory and cognitive modalities. Neocortical cells are organized into circuits that form six cortical layers in all cortical areas that carry out perception and cognition. Variations in cell properties within these layers and their connections have been used to classify the cerebral cortex into more than fifty divisions, or areas, to which distinct functions have been attributed. Why the cortex has a laminar organization for the control of behavior has, however, remained a mystery until recently. Also mysterious has been how variations on this ubiquitous laminar cortical design can give rise to so many different types of intelligent behavior. This chapter explains how Laminar Computing contributes to biological intelligence, and how layered circuits of neocortical cells support all the various kinds of higher-order biological intelligence, including vision, language, and cognition, using variations of the same canonical laminar circuit. This canonical circuit can be used in general-purpose VLSI chips that can be specialized to carry out different kinds of biological intelligence, and seamlessly joined together to control autonomous adaptive algorithms and mobile robots. These circuits show how preattentive automatic bottom-up processing and attentive task-selective top-down processing are joined together in the deeper cortical layers to form a decision interface. Here, bottom-up and top-down constraints cooperate and compete to generate the best decisions, by combining properties of fast feedforward and feedback processing, analog and digital computing, and preattentive and attentive learning, including laminar ART properties such as analog coherence.