Positive Relationship Physical Activity Has on Cognitive Function in High School Students

Research shows a link between physical activity and cognitive function. This connection sheds light on the idea that physical activity can improve cognitive function. Penning et al., (2017) mentions that adolescents have high levels of sedentary behavior which makes them vulnerable for health concerns. During the school day students spend most of their time sitting and staying at a resting heart rate. Vazou, Pesce, Lakes, and Smiley-Owen (2019) found consistent evidence that aerobic or motor skill physical activity, enhanced children’s spatial abilities and working memory. Many hours were spent searching through data bases to find articles on this topic. The most common finding was that cognitive function improves, depending on the specific type of physical activity performed. Specific keyword searchers were performed to find the correct articles. Information was then sorted by keyword search and the types of physical activity performed. Data and articles were put into tables. In conclusion, there is viable information to prove physical activity can improve cognitive function

The neural basis of sign language processing in deaf signers: An activation likelihood estimation meta-analysis

The neurophysiological response during processing of sign language (SL) has been studied since the advent of Positron Emission Tomography (PET) and functional Magnetic Resonance Imaging (fMRI). Nevertheless, the neural substrates of SL remain subject to debate, especially with regard to involvement and relative lateralization of SL processing without production in (left) inferior frontal gyrus (IFG; e.g., Campbell, MacSweeney, & Waters, 2007; Emmorey, 2006, 2015). Our present contribution is the first to address these questions meta-analytically, by exploring functional convergence on the whole-brain level using previous fMRI and PET studies of SL processing in deaf signers. We screened 163 records in PubMed and Web of Science to identify studies of SL processing in deaf signers conducted with fMRI or PET that reported foci data for one of the two whole-brain contrasts: (1) “SL processing vs. control” or (2) “SL processing vs. low-level baseline”. This resulted in a total of 21 studies reporting 23 experiments matching our selection criteria. We manually extracted foci data and performed a coordinate-based Activation Likelihood Estimation (ALE) analysis using GingerALE (Eickhoff et al., 2009). Our selection criteria and the ALE method allow us to identify regions that are consistently involved in processing SL across studies and tasks. Our analysis reveals that processing of SL stimuli of varying linguistic complexity engages widely distributed bilateral fronto-occipito-temporal networks in deaf signers. We find significant clusters in both hemispheres, with the largest cluster (5240 mm3) being located in left IFG, spanning Broca’s region (posterior BA 45 and the dorsal portion of BA 44). Other clusters are located in right middle and inferior temporal gyrus (BA 37), right IFG (BA 45), left middle occipital gyrus (BA 19), right superior temporal gyrus (BA 22), left precentral and middle frontal gyrus (BA 6 and 8), as well as left insula (BA 13). On these clusters, we calculated lateralization indices using hemispheric and anatomical masks: SL comprehension is slightly left-lateralized globally, and strongly left-lateralized in Broca’s region. Sub-regionally, left-lateralization is strongest in BA 44 (Table 1). Next, we performed a contrast analysis between SL and an independent dataset of action observation in hearing non-signers (Papitto, Friederici, & Zaccarella, 2019) to determine which regions are associated with processing of human actions and movements irrespective of the presence of linguistic information. Only studies of observation of non-linguistic manual actions were included in the final set (n = 26), for example, excluding the handling of objects. Significant clusters involved in the linguistic aspects of SL comprehension were found in left Broca’s region (centered in dorsal BA 44), right superior temporal gyrus (BA 22), and left middle frontal and precentral gyrus (BA 6 and 8; Figure 1A, B, D and E). Meta-analytic connectivity modelling for the surviving cluster in Broca’s region using the BrainMap database then revealed that it is co-activated with the classical language network and functionally primarily associated with cognition and language processing (Figure 1C and D). In line with studies of spoken and written language processing (Zaccarella, Schell, & Friederici, 2017; Friederici, Chomsky, Berwick, Moro, & Bolhuis, 2017), our meta-analysis points to Broca’s region and especially left BA 44 as a hub in the language network that is involved in language processing independent of modality. Right IFG activity is not language-specific but may be specific to the visuo-gestural modality (Campbell et al., 2007). References Amunts, K., Schleicher, A., Bürgel, U., Mohlberg, H., Uylings, H. B., & Zilles, K. (1999). Broca’s region revisited: Cytoarchitecture and intersubject variability. The Journal of Comparative Neurology, 412(2), 319-341. Campbell, R., MacSweeney, M., & Waters, D. (2007). Sign language and the brain: A review. Journal of Deaf Studies and Deaf Education, 13(1), 3-20. doi: 10.1093/deafed/enm035 Eickhoff, S. B., Laird, A. R., Grefkes, C., Wang, L. E., Zilles, K., & Fox, P. T. (2009). Coordinate-based activation likelihood estimation meta-analysis of neuroimaging data: A random-effects approach based on empirical estimates of spatial uncertainty. Human Brain Mapping, 30(9), 2907-2926. doi: 10.1002/hbm.20718 Emmorey, K. (2006). The role of Broca’s area in sign language. In Y. Grodzinsky & K. Amunts (Eds.), Broca’s region (p. 169-184). Oxford, England: Oxford UP. Emmorey, K. (2015). The neurobiology of sign language. In A. W. Toga, P. Bandettini, P. Thompson, & K. Friston (Eds.), Brain mapping: An encyclopedic reference (Vol. 3, p. 475-479). London, England: Academic Press. doi: 10.1016/B978-0-12-397025-1.00272-4 Friederici, A. D., Chomsky, N., Berwick, R. C., Moro, A., & Bolhuis, J. J. (2017). Language, mind and brain. Nature Human Behaviour. doi: 10.1038/s41562-017-0184-4 Matsuo, K., Chen, S.-H. A., & Tseng, W.-Y. I. (2012). AveLI: A robust lateralization index in functional magnetic resonance imaging using unbiased threshold-free computation. Journal of Neuroscience Methods, 205(1), 119-129. doi: 10.1016/j.jneumeth.2011.12.020 Papitto, G., Friederici, A. D., & Zaccarella, E. (2019). A neuroanatomical comparison of action domains using Activation Likelihood Estimation meta-analysis [Unpublished Manuscript, Max Planck Institute for Human Cognitive & Brain Sciences]. Leipzig, Germany. Zaccarella, E., Schell, M., & Friederici, A. D. (2017). Reviewing the functional basis of the syntactic Merge mechanism for language: A coordinate-based activation likelihood estimation meta-analysis. Neuroscience & Biobehavioral Reviews, 80, 646-656. doi: 10.1016/j.neubiorev.2017.06.01

Controlling video stimuli in sign language and gesture research: The OpenPoseR package for analyzing OpenPose motion tracking data in R

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

Language and action in Broca’s area: Computational differentiation and cortical segregation

Actions have been proposed to follow hierarchical principles similar to those hypothesized for language syntax. These structural similarities are claimed to be reflected in the common involvement of certain neural populations of Broca’s area, in the Inferior Frontal Gyrus (IFG). In this position paper, we follow an influential hypothesis in linguistic theory to introduce the syntactic operation Merge and the corresponding motor/conceptual interfaces. We argue that actions hierarchies do not follow the same principles ruling language syntax. We propose that hierarchy in the action domain lies in predictive processing mechanisms mapping sensory inputs and statistical regularities of action-goal relationships. At the cortical level, distinct Broca’s subregions appear to support different types of computations across the two domains. We argue that anterior BA44 is a major hub for the implementation of the syntactic operation Merge. On the other hand, posterior BA44 is recruited in selecting premotor mental representations based on the information provided by contextual signals. This functional distinction is corroborated by a recent meta-analysis (Papitto, Friederici, & Zaccarella, 2020). We conclude by suggesting that action and language can meet only where the interfaces transfer abstract computations either to the external world or to the internal mental world

Syntax through the looking glass: A review on two-word linguistic processing across behavioral, neuroimaging and neurostimulation studies

In recent years a growing number of studies on syntactic processing has employed basic two-word constructions (e.g., “the tree”) to characterize the fundamental aspects of linguistic composition. This large body of evidence allows, for the first time, to closely examine which cognitive processes and neural substrates support the combination of two syntactic units into a more complex one, mirroring the nature of combinatory operations described in theoretical linguistics. The present review comprehensively examines behavioural, neuroimaging and neurostimulation studies investigating basic syntactic composition, covering more than 40 years of psycho- and neuro-linguistic research. Across several paradigms, four key features of syntactic composition have emerged: (1) the rule-based and (2) automatic nature of the combinatorial process, (3) a central role of Broca’s area and the posterior temporal lobe in representing and combining syntactic features, and (4) the reliance on efficient bottom-up integration rather than top-down prediction

Differential contributions of left-hemispheric language regions to basic semantic composition

Semantic composition, the ability to combine single words to form complex meanings, is a core feature of human language. Despite growing interest in the basis of semantic composition, the neural correlates and the interaction of regions within this network remain a matter of debate. We designed a well-controlled two-word fMRI paradigm in which phrases only differed along the semantic dimension while keeping syntactic information alike. Healthy participants listened to meaningful (“fresh apple”), anomalous (“awake apple”) and pseudoword phrases (“awake gufel”) while performing an implicit and an explicit semantic task. We identified neural signatures for distinct processes during basic semantic composition. When lexical information is kept constant across conditions and the evaluation of phrasal plausibility is examined (meaningful vs. anomalous phrases), a small set of mostly left-hemispheric semantic regions, including the anterior part of the left angular gyrus, is found active. Conversely, when the load of lexical information—independently of phrasal plausibility—is varied (meaningful or anomalous vs. pseudoword phrases), conceptual combination involves a wide-spread left-hemispheric network comprising executive semantic control regions and general conceptual representation regions. Within this network, the functional coupling between the left anterior inferior frontal gyrus, the bilateral pre-supplementary motor area and the posterior angular gyrus specifically increases for meaningful phrases relative to pseudoword phrases. Stronger effects in the explicit task further suggest task-dependent neural recruitment. Overall, we provide a separation between distinct nodes of the semantic network, whose functional contributions depend on the type of compositional process under analysis

Neural classification maps for distinct word combinations in Broca’s area

Humans are equipped with the remarkable ability to comprehend an infinite number of utterances. Relations between grammatical categories restrict the way words combine into phrases and sentences. How the brain recognises different word combinations remains largely unknown, although this is a necessary condition for combinatorial unboundedness in language. Here, we used functional magnetic resonance imaging and multivariate pattern analysis to explore whether distinct neural populations of a known language network hub —Broca’s area—are specialised for recognising distinct simple word combinations. The phrases consisted of a noun (flag) occurring either with a content word, an adjective (green flag), or with a function word, a determiner (that flag). The key result is that the distribution of neural populations classifying word combination in Broca’s area seems sensitive to neuroanatomical subdivisions within this area, irrespective of task. The information patterns for adjective + noun were localised in its anterior part (BA45) whereas those for determiner + noun were localised in its posterior part (BA44). Our findings provide preliminary answers to the fundamental question of how lexical and grammatical category information interact during simple word combination, with the observation that Broca’s area is sensitive to the recognition of categorical relationships during combinatory processing, based on different demands placed on syntactic and semantic information. This supports the hypothesis that the combinatorial power of language consists of some neural computation capturing phrasal differences when processing linguistic input

Syntax through the looking glass: A review on two-word linguistic processing across behavioral, neuroimaging and neurostimulation studies

In recent years a growing number of studies on syntactic processing has employed basic two-word constructions (e.g., “the tree”) to characterize the fundamental aspects of linguistic composition. This large body of evidence allows, for the first time, to closely examine which cognitive processes and neural substrates support the combination of two syntactic units into a more complex one, mirroring the nature of combinatory operations described in theoretical linguistics. The present review comprehensively examines behavioural, neuroimaging and neurostimulation studies investigating basic syntactic composition, covering more than forty years of psycho- and neuro-linguistic research. Across several paradigms, four key features of syntactic composition have emerged: (1) the rule-based and (2) automatic nature of the combinatorial process, (3) a central role of Broca’s area and the posterior temporal lobe in representing and combining syntactic features, and (4) the reliance on efficient bottom-up integration rather than top-down prediction