Dataset: Language and semantic processing in blind and sighted individuals. A simulation study

<p>-------------------<br> GENERAL INFORMATION<br> -------------------</p> <p>1. Title of Dataset&nbsp;<br> &nbsp;&nbsp; &nbsp;<br> Dataset_SimulationsOutput_BlindvsSightedModels<br> &nbsp;&nbsp; &nbsp;<br> 2. Author Information</p> <p>This dataset is being made public to act as supplementary data for publication. Running title:&nbsp;</p> <p>R. Tomasello, M. Garagnani, T. Wennekers, and F. Pulverm&uuml;ller, Recruitment of visual cortex for language processing in blind individuals is explained by Hebbian learning.</p> <p>&nbsp; Corresponding author:<br> &nbsp; &nbsp; &nbsp; &nbsp; Name: &nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;Rosario Tomasello&nbsp;<br> &nbsp; &nbsp; &nbsp; &nbsp; Institution: &nbsp;&nbsp; &nbsp;Brain Language Laboratory, Freie Universit&auml;t Berlin<br> &nbsp; &nbsp; &nbsp; &nbsp; Address: &nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;Habelschwerdter Allee 45, 14195 Berlin<br> &nbsp; &nbsp; &nbsp; &nbsp; Email: &nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;Tomasello.r@fu-berlin.de</p> <p>--------------------------<br> RESEARCH PROJECT &amp; METHODOLOGICAL INFORMATION<br> --------------------------</p> <p>The data were generated by a neurobiologically constrained cortex model of the fronto-temporal-occipital lobes applied to simulate word meaning acquisition of object- and action-related words in action and perception system under undeprived and visually deprived conditions. The purpose of this study was to investigate how and why the visual system is recruited for language processing in blind individuals, as documented by neurocognitive empirical experiments.</p> <p>The files listed above shows the cell assemblies (CA) distributions across the different cortical areas spontaneously emerged as a result of Hebbian learning. For more information about the general features of the model see our previous publications:</p> <p>R. Tomasello, M. Garagnani, T. Wennekers, and F. Pulverm&uuml;ller, (2018) A Neurobiologically Constrained Cortex Model of Semantic Grounding With Spiking Neurons and Brain-Like Connectivity, Front. Comput. Neurosci., vol. 12, p. 88.</p> <p>M. Garagnani, G. Lucchese, R. Tomasello, T. Wennekers, and F. Pulverm&uuml;ller, (2017) A Spiking Neurocomputational Model of High-Frequency Oscillatory Brain Responses to Words and Pseudowords, Front. Comput. Neurosci., vol. 10, no. January, pp. 1&ndash;19.</p> <p><br> ---------------------<br> DATA &amp; FILE OVERVIEW<br> ---------------------</p> <p><br> 1. File List<br> &nbsp; &nbsp;<br> &nbsp;&nbsp; &nbsp;Filename: CA_Structure_Blind VS SightedModel.xlsx (size 150KB) &nbsp; &nbsp;&nbsp;<br> &nbsp;&nbsp; &nbsp;<br> The excel file includes the cell assembly (CA) distributions of the learnt action and object words of both sighted and blind models along with their CA structure comparisons and the related figures.&nbsp;<br> &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;<br> &nbsp;&nbsp; &nbsp;Folders: Raw_Data_SightedModel (size 6KB) &amp; Raw_Data_BlindModel (size 6KB)<br> &nbsp; &nbsp; &nbsp;&nbsp;<br> These folders include the raw data output of the CA structure of the 13 sighted and 13 blind simulated models after word meaning acquisition.&nbsp;</p>