Sign language (SL) conveys linguistic information using gestures instead of sounds. Here, we apply a meta‐analytic estimation approach to neuroimaging studies (N = 23; subjects = 316) and ask whether SL comprehension in deaf signers relies on the same primarily left‐hemispheric cortical network implicated in spoken and written language (SWL) comprehension in hearing speakers. We show that: (a) SL recruits bilateral fronto‐temporo‐occipital regions with strong left‐lateralization in the posterior inferior frontal gyrus known as Broca's area, mirroring functional asymmetries observed for SWL. (b) Within this SL network, Broca's area constitutes a hub which attributes abstract linguistic information to gestures. (c) SL‐specific voxels in Broca's area are also crucially involved in SWL, as confirmed by meta‐analytic connectivity modeling using an independent large‐scale neuroimaging database. This strongly suggests that the human brain evolved a lateralized language network with a supramodal hub in Broca's area which computes linguistic information independent of speech.

Synaptic plasticity is widely considered to be the neurobiological basis of learning and memory by neuroscientists and researchers in adjacent fields, though diverging opinions are increasingly being recognized. From the perspective of what we might call “classical cognitive science” it has always been understood that the mind/brain is to be considered a computational-representational system. Proponents of the information-processing approach to cognitive science have long been critical of connectionist or network approaches to (neuro-)cognitive architecture, pointing to the shortcomings of the associative psychology that underlies Hebbian learning as well as to the fact that synapses are practically unfit to implement symbols. Recent work on memory has been adding fuel to the fire and current findings in neuroscience now provide first tentative neurobiological evidence for the cognitive scientists' doubts about the synapse as the (sole) locus of memory in the brain. This paper briefly considers the history and appeal of synaptic plasticity as a memory mechanism, followed by a summary of the cognitive scientists' objections regarding these assertions. Next, a variety of tentative neuroscientific evidence that appears to substantiate questioning the idea of the synapse as the locus of memory is presented. On this basis, a novel way of thinking about the role of synaptic plasticity in learning and memory is proposed.

Synaptic plasticity is widely considered to be the neurobiological basis of learning and memory by neuroscientists and researchers in adjacent fields, though diverging opinions are increasingly being recognized. From the perspective of what we might call "classical cognitive science" it has always been understood that the mind/brain is to be considered a computational-representational system. Proponents of the information-processing approach to cognitive science have long been critical of connectionist or network approaches to (neuro-)cognitive architecture, pointing to the shortcomings of the associative psychology that underlies Hebbian learning as well as to the fact that synapses are practically unfit to implement symbols. Recent work on memory has been adding fuel to the fire and current findings in neuroscience now provide first tentative neurobiological evidence for the cognitive scientists' doubts about the synapse as the (sole) locus of memory in the brain. This paper briefly considers the history and appeal of synaptic plasticity as a memory mechanism, followed by a summary of the cognitive scientists' objections regarding these assertions. Next, a variety of tentative neuroscientific evidence that appears to substantiate questioning the idea of the synapse as the locus of memory is presented. On this basis, a novel way of thinking about the role of synaptic plasticity in learning and memory is proposed.

Researchers in the fields of sign language and gesture studies frequently present their participants with video stimuli showing actors performing linguistic signs or co-speech gestures. Up to now, such video stimuli have been mostly controlled only for some of the technical aspects of the video material (e.g., duration of clips, encoding, framerate, etc.), leaving open the possibility that systematic differences in video stimulus materials may be concealed in the actual motion properties of the actor’s movements. Computer vision methods such as OpenPose enable the fitting of body-pose models to the consecutive frames of a video clip and thereby make it possible to recover the movements performed by the actor in a particular video clip without the use of a point-based or markerless motion-tracking system during recording. The OpenPoseR package provides a straightforward and reproducible way of working with these body-pose model data extracted from video clips using OpenPose, allowing researchers in the fields of sign language and gesture studies to quantify the amount of motion (velocity and acceleration) pertaining only to the movements performed by the actor in a video clip. These quantitative measures can be used for controlling differences in the movements of an actor in stimulus video clips or, for example, between different conditions of an experiment. In addition, the package also provides a set of functions for generating plots for data visualization, as well as an easy-to-use way of automatically extracting metadata (e.g., duration, framerate, etc.) from large sets of video files.

Sign language offers a unique perspective on the human faculty of language by illustrating that linguistic abilities are not bound to speech and writing. In studies of spoken and written language processing, lexical variables such as, for example, age of acquisition have been found to play an important role, but such information is not as yet available for German Sign Language (Deutsche Gebärdensprache, DGS). Here, we present a set of norms for frequency, age of acquisition, and iconicity for more than 300 lexical DGS signs, derived from subjective ratings by 32 deaf signers. We also provide additional norms for iconicity and transparency for the same set of signs derived from ratings by 30 hearing non-signers. In addition to empirical norming data, the dataset includes machine-readable information about a sign’s correspondence in German and English, as well as annotations of lexico-semantic and phonological properties: one-handed vs. two-handed, place of articulation, most likely lexical class, animacy, verb type, (potential) homonymy, and potential dialectal variation. Finally, we include information about sign onset and offset for all stimulus clips from automated motion-tracking data. All norms, stimulus clips, data, as well as code used for analysis are made available through the Open Science Framework in the hope that they may prove to be useful to other researchers: 10.17605/OSF.IO/MZ8J4

This short piece addresses the confusion over terminology that has reigned, and partly still reigns, when it comes to the concept of Universal Grammar (UG). It is argued that whilst there might be changes in terminology and theory, conceptually UG cannot be eliminated. From a biolinguistic perspective, UG is not a hypothesis by any rational epistemological standard, but an axiom. Along these lines, the contemporary evolutionary perspective on the language faculty (FL) is briefly discussed to then argue that UG is necessarily part of FL in both a narrow and broad sense. Ultimately, regardless of terminology, UG is inevitably one of the factors determining the growth of FL.Keywords: Universal Grammar (UG), Faculty of Language (FL), I-language, language universals, minimalism, evolution of language, biolinguistics, cognitive science IntroductionDespite having been in active use by (mostly generative) linguists for a long time, the technical term Universal Grammar (UG) has led to ample confusion amongst linguists and non-linguists alike. As a consequence, Boeckx and Benítez Burraco (2014) have supplanted the label UG with talk about the "language-ready brain." Yet, conceptually, nothing has changed: A language-ready brain is a brain shaped by UG. In turn, UG is defined as genetic endowment with regard to language (Chomsky, 2005) and is one of the factors influencing the initial growth and further development of the human language faculty (FL). This short piece addresses the confusion over the "grammar" in UG because both, terminology and the concept of UG, have been subject to a multitude of debates and misunderstanding. Confusion over terminologyWith regard to terminology, UG was labelled as such as an homage to the ideas expressed in the Grammaire générale et raisonnée, the Port-Royal grammarians, and the Western philosophical tradition associated with them (in this context see McGilvray, 2009, pp. 24-35). Originally, the term UG was used by (mainly generative) linguists to denote whatever it turns out to be that humans bring along to the process of language acquisition. It was understood that the properties of FL are ' [...] determined by the nature of the mind' (Chomsky, 1967, p. 9). Decades after the cognitive revolution (Miller, 2003), presumably due to the success of Government and Binding theory (Chomsky, 1981(Chomsky, /1988, the term UG acquired a narrower and more specific meaning, denoting merely the genetic endowment enabling language growth (this change in terminology is critically evaluated by Boeckx and Leivada, 2014; for a more general summary of discussions on the past and present of UG also see Irurtzun, 2012, as well as the 2014 Language Sciences special issue).Generally speaking, the label UG has lead to ample confusion. Non-linguists as well as researchers who oppose the "biolinguistic research agenda" (Hauser and Bever, 2008) kind of a "theoretical biology" (Sklar, 1968) would often take the term Universal Grammar literally, thus interpreting it to imply that there in fact are aspect...

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Sign language offers a unique perspective on the human faculty of language by illustrating that linguistic abilities are not bound to speech and writing. In studies of spoken and written language processing, lexical variables such as, for example, age of acquisition have been found to play an important role, but such information is not as yet available for German Sign Language (Deutsche Gebärdensprache, DGS). Here, we present a set of norms for frequency, age of acquisition, and iconicity for more than 300 lexical DGS signs, derived from subjective ratings by 32 deaf signers. We also provide additional norms for iconicity and transparency for the same set of signs derived from ratings by 30 hearing non-signers. In addition to empirical norming data, the dataset includes machine-readable information about a sign’s correspondence in German and English, as well as annotations of lexico-semantic and phonological properties: one-handed vs. two-handed, place of articulation, most likely lexical class, animacy, verb type, (potential) homonymy, and potential dialectal variation. Finally, we include information about sign onset and offset for all stimulus clips from automated motion-tracking data. All norms, stimulus clips, data, as well as code used for analysis are made available through the Open Science Framework in the hope that they may prove be useful to other researchers: https://osf.io/mz8j4/