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      The Brain Structure and Intrinsic Characters of Falsification Thinking in Conditional Proposition Testing

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          Abstract

          Wason's selection task (WST) as a representative of the field of conditional proposition testing has been explored by multiple disciplines for more than 50 years, but the neural basis of its key falsification thinking remains unclear. Considering that the accuracy of individuals in WST has stability over time, we believe that falsification thinking has a specific brain structural basis and intrinsic neural characteristics. To test this hypothesis, we studied individuals who were able to complete the WST using T1-weighted MRI (using voxel-based morphology (VBM) analysis) and resting electroencephalogram (EEG) (using microstate analysis, which can reflect stable cognitive characteristics of individuals) techniques. First, VBM analysis found that, compared with the verification group, the gray matter volume (GMV) of the left inferior temporal gyrus and the right superior temporal region of the falsification group was larger, whereas the GMV in the cerebellum of the verification group was significantly larger than that of the falsification group. Subsequently, the results of the microstate analysis of the resting EEG data showed that the contribution of class A of the falsification group, which is closely related to the language network, is significantly higher than that of the verification group. Our structural MRI and resting EEG results consistently show that the structure and intrinsic activity pattern of the temporal lobe in individuals with falsification thinking are specific. Furthermore, the findings may provide potential insights into the role of the temporal lobe (which is also a brain region of language processing) in thought.

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          Most cited references95

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          EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis

          We have developed a toolbox and graphic user interface, EEGLAB, running under the crossplatform MATLAB environment (The Mathworks, Inc.) for processing collections of single-trial and/or averaged EEG data of any number of channels. Available functions include EEG data, channel and event information importing, data visualization (scrolling, scalp map and dipole model plotting, plus multi-trial ERP-image plots), preprocessing (including artifact rejection, filtering, epoch selection, and averaging), independent component analysis (ICA) and time/frequency decompositions including channel and component cross-coherence supported by bootstrap statistical methods based on data resampling. EEGLAB functions are organized into three layers. Top-layer functions allow users to interact with the data through the graphic interface without needing to use MATLAB syntax. Menu options allow users to tune the behavior of EEGLAB to available memory. Middle-layer functions allow users to customize data processing using command history and interactive 'pop' functions. Experienced MATLAB users can use EEGLAB data structures and stand-alone signal processing functions to write custom and/or batch analysis scripts. Extensive function help and tutorial information are included. A 'plug-in' facility allows easy incorporation of new EEG modules into the main menu. EEGLAB is freely available (http://www.sccn.ucsd.edu/eeglab/) under the GNU public license for noncommercial use and open source development, together with sample data, user tutorial and extensive documentation.
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            Control of mental activities by internal models in the cerebellum.

            Masao ITO (2008)
            The intricate neuronal circuitry of the cerebellum is thought to encode internal models that reproduce the dynamic properties of body parts. These models are essential for controlling the movement of these body parts: they allow the brain to precisely control the movement without the need for sensory feedback. It is thought that the cerebellum might also encode internal models that reproduce the essential properties of mental representations in the cerebral cortex. This hypothesis suggests a possible mechanism by which intuition and implicit thought might function and explains some of the symptoms that are exhibited by psychiatric patients. This article examines the conceptual bases and experimental evidence for this hypothesis.
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              BOLD correlates of EEG topography reveal rapid resting-state network dynamics.

              Resting-state functional connectivity studies with fMRI showed that the brain is intrinsically organized into large-scale functional networks for which the hemodynamic signature is stable for about 10s. Spatial analyses of the topography of the spontaneous EEG also show discrete epochs of stable global brain states (so-called microstates), but they remain quasi-stationary for only about 100 ms. In order to test the relationship between the rapidly fluctuating EEG-defined microstates and the slowly oscillating fMRI-defined resting states, we recorded 64-channel EEG in the scanner while subjects were at rest with their eyes closed. Conventional EEG-microstate analysis determined the typical four EEG topographies that dominated across all subjects. The convolution of the time course of these maps with the hemodynamic response function allowed to fit a linear model to the fMRI BOLD responses and revealed four distinct distributed networks. These networks were spatially correlated with four of the resting-state networks (RSNs) that were found by the conventional fMRI group-level independent component analysis (ICA). These RSNs have previously been attributed to phonological processing, visual imagery, attention reorientation, and subjective interoceptive-autonomic processing. We found no EEG-correlate of the default mode network. Thus, the four typical microstates of the spontaneous EEG seem to represent the neurophysiological correlate of four of the RSNs and show that they are fluctuating much more rapidly than fMRI alone suggests. Copyright 2010 Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                Journal
                Front Hum Neurosci
                Front Hum Neurosci
                Front. Hum. Neurosci.
                Frontiers in Human Neuroscience
                Frontiers Media S.A.
                1662-5161
                23 August 2021
                2021
                : 15
                : 684470
                Affiliations
                [1] 1Department of Psychology, Xinxiang Medical University , Xinxiang, China
                [2] 2Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University , Xinxiang, China
                Author notes

                Edited by: Lingzhong Fan, Institute of Automation, Chinese Academy of Sciences, China

                Reviewed by: Junhai Xu, Tianjin University, China; Jiaojian Wang, University of Electronic Science and Technology of China, China

                This article was submitted to Cognitive Neuroscience, a section of the journal Frontiers in Human Neuroscience

                †These authors share first authorship

                Article
                10.3389/fnhum.2021.684470
                8419331
                5bcbc97e-5ce8-4f10-b3cf-05b152d2a05d
                Copyright © 2021 Zhang, Wang, Zou, Wang and Wu.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 24 March 2021
                : 21 July 2021
                Page count
                Figures: 3, Tables: 3, Equations: 0, References: 95, Pages: 10, Words: 7689
                Categories
                Human Neuroscience
                Original Research

                Neurosciences
                wason's selection task,voxel-based morphology,microstate,temporal lobe,falsification thinking

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