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      A shared model-based linguistic space for transmitting our thoughts from brain to brain in natural conversations

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            SciPy 1.0: fundamental algorithms for scientific computing in Python

            SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.
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              An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest.

              In this study, we have assessed the validity and reliability of an automated labeling system that we have developed for subdividing the human cerebral cortex on magnetic resonance images into gyral based regions of interest (ROIs). Using a dataset of 40 MRI scans we manually identified 34 cortical ROIs in each of the individual hemispheres. This information was then encoded in the form of an atlas that was utilized to automatically label ROIs. To examine the validity, as well as the intra- and inter-rater reliability of the automated system, we used both intraclass correlation coefficients (ICC), and a new method known as mean distance maps, to assess the degree of mismatch between the manual and the automated sets of ROIs. When compared with the manual ROIs, the automated ROIs were highly accurate, with an average ICC of 0.835 across all of the ROIs, and a mean distance error of less than 1 mm. Intra- and inter-rater comparisons yielded little to no difference between the sets of ROIs. These findings suggest that the automated method we have developed for subdividing the human cerebral cortex into standard gyral-based neuroanatomical regions is both anatomically valid and reliable. This method may be useful for both morphometric and functional studies of the cerebral cortex as well as for clinical investigations aimed at tracking the evolution of disease-induced changes over time, including clinical trials in which MRI-based measures are used to examine response to treatment.
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                Author and article information

                Contributors
                Journal
                Neuron
                Neuron
                Elsevier BV
                08966273
                August 2024
                August 2024
                Article
                10.1016/j.neuron.2024.06.025
                9f04d9e6-ee28-4110-b6eb-5eb3abbf1c0c
                © 2024

                https://www.elsevier.com/tdm/userlicense/1.0/

                https://www.elsevier.com/legal/tdmrep-license

                http://creativecommons.org/licenses/by/4.0/

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