In this study we explore whether different types of iconic gestures (i.e., acting, drawing, representing) and their combinations are used systematically to distinguish between different semantic categories in production and comprehension. In Study 1, we elicited silent gestures from Mexican and Dutch participants to represent concepts from three semantic categories: actions, manipulable objects, and non-manipulable objects. Both groups favoured the acting strategy to represent actions and manipulable objects; while non-manipulable objects were represented through the drawing strategy. Actions elicited primarily single gestures whereas objects elicited combinations of different types of iconic gestures as well as pointing. In Study 2, a different group of participants were shown gestures from Study 1 and were asked to guess their meaning. Single-gesture depictions for actions were more accurately guessed than for objects. Objects represented through two-gesture combinations (e.g., acting + drawing) were more accurately guessed than objects represented with a single gesture. We suggest iconicity is exploited to make direct links with a referent, but when it lends itself to ambiguity, individuals resort to combinatorial structures to clarify the intended referent. Iconicity and the need to communicate a clear signal shape the structure of silent gestures and this in turn supports comprehension.

In human speech, a finite set of basic sounds is combined into a (potentially) unlimited set of well-formed morphemes. Hockett (1960) placed this phenomenon under the term ‘duality of patterning’ and included it as one of the basic design features of human language. Of the thirteen basic design features Hockett proposed, duality of patterning is the least studied and it is still unclear how it evolved in language. Recent work shedding light on this is summarized in this paper and experimental data is presented. This data shows that combinatorial structure can emerge in an artificial whistled language through cultural transmission as an adaptation to human cognitive biases and learning. In this work the method of experimental iterated learning (Kirby et al. 2008) is used, in which a participant is trained on the reproductions of the utterances the previous participant learned. Participants learn and recall a system of sounds that are produced with a slide whistle. Transmission from participant to participant causes the whistle systems to change and become more learnable and more structured. These findings follow from qualitative observations, quantitative measures and a follow-up experiment that tests how well participants can learn the emerged whistled languages by generalizing from a few examples.

Human cognition is unique in the way in which it relies on combinatorial (or compositional) structures. Language provides ample evidence for the existence of combinatorial structures, but they can also be found in visual cognition. To understand the neural basis of human cognition, it is therefore essential to understand how combinatorial structures can be instantiated in neural terms. In his recent book on the foundations of language, Jackendoff described four fundamental problems for a neural instantiation of combinatorial structures: the massiveness of the binding problem, the problem of 2, the problem of variables, and the transformation of combinatorial structures from working memory to long-term memory. This paper aims to show that these problems can be solved by means of neural “blackboard” architectures. For this purpose, a neural blackboard architecture for sentence structure is presented. In this architecture, neural structures that encode for words are temporarily bound in a manner that preserves the structure of the sentence. It is shown that the architecture solves the four problems presented by Jackendoff. The ability of the architecture to instantiate sentence structures is illustrated with examples of sentence complexity observed in human language performance. Similarities exist between the architecture for sentence structure and blackboard architectures for combinatorial structures in visual cognition, derived from the structure of the visual cortex. These architectures are briefly discussed, together with an example of a combinatorial structure in which the blackboard architectures for language and vision are combined. In this way, the architecture for language is grounded in perception. Perspectives and potential developments of the architectures are discussed.