Neuroimage. Reports最新文献

{"title":"Phase matters when there is power: Phasic modulation of corticospinal excitability occurs at high amplitude sensorimotor mu-oscillations","authors":"Recep A. Ozdemir ,&nbsp;Sofia Kirkman ,&nbsp;Justine R. Magnuson ,&nbsp;Peter J. Fried ,&nbsp;Alvaro Pascual-Leone ,&nbsp;Mouhsin M. Shafi","doi":"10.1016/j.ynirp.2022.100132","DOIUrl":"10.1016/j.ynirp.2022.100132","url":null,"abstract":"<div><p>Prior studies have suggested that oscillatory activity in cortical networks can modulate stimulus-evoked responses through time-varying fluctuations in neural excitation-inhibition dynamics. Studies combining transcranial magnetic stimulation (TMS) with electromyography (EMG) and electroencephalography (EEG) can provide direct measurements to examine how instantaneous fluctuations in cortical oscillations contribute to variability in TMS-induced corticospinal responses. However, the results of these studies have been conflicting, as some reports showed consistent phase effects of sensorimotor mu-rhythms with increased excitability at the negative mu peaks, while others failed to replicate these findings or reported unspecific mu-phase effects across subjects. Given the lack of consistent results, we systematically examined the modulatory effects of instantaneous and pre-stimulus sensorimotor mu-rhythms on corticospinal responses with offline EEG-based motor evoked potential (MEP) classification analyses across five identical visits. Instantaneous sensorimotor mu-phase or pre-stimulus mu-power alone did not significantly modulate MEP responses. Instantaneous mu-power analyses showed weak effects with larger MEPs during high-power trials at the overall group level analyses, but this trend was not reproducible across visits. However, TMS delivered at the negative peak of high magnitude mu-oscillations generated the largest MEPs across all visits, with significant differences compared to other peak-phase combinations. High power effects on MEPs were only observed at the trough phase of ongoing mu oscillations originating from the stimulated region, indicating site and phase specificity, respectively. More importantly, such phase-dependent power effects on corticospinal excitability were reproducible across multiple visits. We provide further evidence that fluctuations in corticospinal excitability indexed by MEP amplitudes are partially driven by dynamic interactions between the magnitude and the phase of ongoing sensorimotor mu oscillations at the time of TMS, and suggest promising insights for (re)designing neuromodulatory TMS protocols targeted to specific cortical oscillatory states.</p></div>","PeriodicalId":74277,"journal":{"name":"Neuroimage. Reports","volume":"2 4","pages":"Article 100132"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/eb/b3/nihms-1855866.PMC9784422.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10453797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fatness, fitness and the aging brain: A cross sectional study of the associations between a physiological estimate of brain age and physical fitness, activity, sleep, and body composition","authors":"David Wing ,&nbsp;Lisa T. Eyler ,&nbsp;Eric J. Lenze ,&nbsp;Julie Loebach Wetherell ,&nbsp;Jeanne F. Nichols ,&nbsp;Romain Meeusen ,&nbsp;Job G. Godino ,&nbsp;Joshua S. Shimony ,&nbsp;Abraham Z. Snyder ,&nbsp;Tomoyuki Nishino ,&nbsp;Ginger E. Nicol ,&nbsp;Guy Nagels ,&nbsp;Bart Roelands","doi":"10.1016/j.ynirp.2022.100146","DOIUrl":"10.1016/j.ynirp.2022.100146","url":null,"abstract":"<div><h3>Introduction</h3><p>Changes in brain structure and function occur with aging. However, there is substantial heterogeneity both in terms of when these changes begin, and the rate at which they progress. Understanding the mechanisms and/or behaviors underlying this heterogeneity may allow us to act to target and slow negative changes associated with aging.</p></div><div><h3>Methods</h3><p>Using T1 weighted MRI images, we applied a novel algorithm to determine the physiological age of the brain (brain-predicted age) and the predicted age difference between this physiologically based estimate and chronological age (BrainPAD) to 551 sedentary adults aged 65 to 84 with self-reported cognitive complaint measured at baseline as part of a larger study. We also assessed maximal aerobic capacity with a graded exercise test, physical activity and sleep with accelerometers, and body composition with dual energy x-ray absorptiometry. Associations were explored both linearly and logistically using categorical groupings.</p></div><div><h3>Results</h3><p>Visceral Adipose Tissue (VAT), Total Sleep Time (TST) and maximal aerobic capacity all showed significant associations with BrainPAD. Greater VAT was associated with higher (i.e,. older than chronological) BrainPAD (r = 0.149 p = 0.001)Greater TST was associated with higher BrainPAD (r = 0.087 p = 0.042) and greater aerobic capacity was associated with lower BrainPAD (r = −0.088 p = 0.040). With linear regression, both VAT and TST remained significant (p = 0.036 and 0.008 respectively). Each kg of VAT predicted a 0.741 year increase in BrainPAD, and each hour of increased TST predicted a 0.735 year increase in BrainPAD. Maximal aerobic capacity did not retain statistical significance in fully adjusted linear models.</p></div><div><h3>Discussion</h3><p>Accumulation of visceral adipose tissue and greater total sleep time, but not aerobic capacity, total daily physical activity, or sleep quantity and/or quality are associated with brains that are physiologically older than would be expected based upon chronological age alone (BrainPAD).</p></div>","PeriodicalId":74277,"journal":{"name":"Neuroimage. Reports","volume":"2 4","pages":"Article 100146"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/d4/07/nihms-1855870.PMC9894084.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10663229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Incidental neuroimaging findings in South African adult research participants with and without neuropsychiatric disorders","authors":"Chanellé Hendrikse ,&nbsp;Tina Malan ,&nbsp;Stéfan du Plessis ,&nbsp;Jonathan Carr ,&nbsp;Martin Kidd ,&nbsp;Robin Emsley ,&nbsp;Soraya Seedat","doi":"10.1016/j.ynirp.2022.100130","DOIUrl":"10.1016/j.ynirp.2022.100130","url":null,"abstract":"<div><p>There is a lack of comparative data on the occurrence and clinical significance of incidental neuroimaging findings (IFs) in adult research participants with neuropsychiatric disorders and healthy controls. We investigated and compared the frequency, clinical significance and predictors of IFs on structural brain magnetic resonance imaging (MRI) scans of research participants between the ages of 18–78 years living in Cape Town, South Africa. Our sample (<em>N</em> = 295) included individuals with posttraumatic stress disorder (<em>n</em> = 122) or Parkinson's disease (<em>n</em> = 21), and healthy controls (<em>n</em> = 152). T1 ME-MPRAGE weighted structural MRI scans were acquired and subsequently reviewed for IFs by radiologists. A neurologist reviewed radiological reports and categorised IFs according to their estimated clinical significance. IFs were observed on the scans of 95 (32%) participants but most IFs were either judged to be clinically non-significant (49%) or of unknown clinical significance (32%). Eighteen participants (6%) had clinically significant findings that required referral for further clinical management. Age was a significant predictor of having an IF, whereas a diagnosis of Parkinson's disease was a significant predictor of having a clinically significant IF.</p></div>","PeriodicalId":74277,"journal":{"name":"Neuroimage. Reports","volume":"2 4","pages":"Article 100130"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266695602200054X/pdfft?md5=bb579ff030a08357bae4c916e2b288af&pid=1-s2.0-S266695602200054X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44086378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The neural signatures of the psychological construct “flow”: A replication study","authors":"Martin Ulrich ,&nbsp;Filip Niemann ,&nbsp;Georg Grön","doi":"10.1016/j.ynirp.2022.100139","DOIUrl":"10.1016/j.ynirp.2022.100139","url":null,"abstract":"<div><p>The psychological construct “flow” has received major attention during the last decade by various scientific branches in the fields of psychology and neuroscience. Flow is operationally defined in relation to the boundary conditions of boredom and overload. According to the conditions’ arrangement, two major neural flow effects are of interest, inferred by quadratic trends of neural activation. The inverted U-shaped pattern of neural activation is characterized by greater neural activation during the flow condition relative to boredom and overload, while the U-shaped pattern is the reverse, that is, lower neural activation during flow relative to its boundary conditions. Both effects have repeatedly been reported during the last years and have seen greater scientific resonance, which is why we found it necessary to try to replicate recent findings. A fresh sample of 41 healthy male participants was investigated with BOLD functional magnetic resonance imaging in combination with our flow paradigm. Electrodermal activation served as read-out of the flow effect on the psychophysiological level. Evidence of replication was quantified in terms of the replication Bayes factor. We observed strong replication evidence for electrodermal activation and decisive evidence of replication for both neural flow effects. Aspects of dorsolateral prefrontal cortex, anterior insula and parietal cortex showed inverted U-shaped activation. U-shaped activation was predominant in aspects of medial prefrontal cortex, ventral striatum, amygdala and along the cingulate cortex (subgenual, middle and posterior). Despite its strong replicability, the flow paradigm has been administered in men-only samples so far. Therefore, present results still await empirical replication in women-only samples.</p></div>","PeriodicalId":74277,"journal":{"name":"Neuroimage. Reports","volume":"2 4","pages":"Article 100139"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666956022000630/pdfft?md5=a53390eec48ac95ff8a3e6de91a94c67&pid=1-s2.0-S2666956022000630-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44961858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Segmentation of intrinsically very low contrast magnetic resonance brain images using tensor-based DTI registration","authors":"M.L. Al-Saady ,&nbsp;N.I. Wolf ,&nbsp;P.J.W. Pouwels","doi":"10.1016/j.ynirp.2022.100120","DOIUrl":"https://doi.org/10.1016/j.ynirp.2022.100120","url":null,"abstract":"<div><h3>Background</h3><p>In patients with hypomyelinating leukodystrophies, contrast of T1-weighted brain MRI is very low due to the lack of myelin, preventing a reliable segmentation. In diffusion tensor images the contrast is higher, thanks to anisotropy and orientation of white matter (WM) tracts. We aimed to develop and assess a tensor-guided atlas-based segmentation method suitable for segmentation of very low contrast images.</p></div><div><h3>Methods</h3><p>17 control subjects (mean age 8.0 yrs (SD 8.0)) and 27 subjects with hypomyelinating leukodystrophies (mean age 10.7 yrs (SD 10.2)) were included. DTI and 3D T1 images were segmented using a DTI-TK tensor-guided IIT-atlas-based segmentation method. For the control subjects, these segmentations were compared with a conventional segmentation of their 3D T1-weighted images. A qualitative visual assessment and a quantitative assessment using DTI metrics was performed to assess the patient segmentations.</p></div><div><h3>Results</h3><p>In control subjects, the tensor-based method performed as can be expected for atlas-based segmentation methods, with Dice coefficients of 0.65, 0.72, 0.81 and 0.86 for cortical grey matter (GM), WM, deep grey matter (DGM), and thalamus, respectively. In patients with hypomyelination the visual assessment showed anatomically adequate segmentations. All tissue-specific DTI metrics differed between patients and controls. Patients with hypomyelination had reduced FA and increased mean, axial and radial diffusivities, not only in total WM, but also in the corticospinal tracts, optic radiations and thalamus.</p></div><div><h3>Conclusion</h3><p>Even in the absence of normal myelin, the presence and direction of axons allowed tensor-based registration and thereby atlas-based segmentation. We showed the applicability of the segmentation method in the context of quantitative MRI, allowing for whole-brain or regional tissue-specific and tract-specific analyses of very low contrast images.</p></div>","PeriodicalId":74277,"journal":{"name":"Neuroimage. Reports","volume":"2 4","pages":"Article 100120"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666956022000447/pdfft?md5=755e5f396601e2ffa609fa8f8d63c401&pid=1-s2.0-S2666956022000447-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136427114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Midfrontal theta is associated with errors, but no evidence for a link with error-related memory","authors":"Xiaochen Y. Zheng ,&nbsp;Syanah C. Wynn","doi":"10.1016/j.ynirp.2022.100129","DOIUrl":"https://doi.org/10.1016/j.ynirp.2022.100129","url":null,"abstract":"<div><p>Midfrontal theta is widely observed in situations with increased demand for cognitive control, such as monitoring response errors. It also plays an important role in the cognitive control involved in memory, supporting processes like the binding of single items into a memory representation or encoding contextual information. In the current study, we explored the link between midfrontal theta and error-related memory. To this end, we recorded EEG from 31 participants while they performed a modified flanker task. Their memory for the errors made during the task was assessed after each experimental block, and its relationship with error-related midfrontal theta effects was investigated. We have replicated the error-related increase in midfrontal theta power, reported in previous literature. However, this error-related theta effect could not predict subsequent memory of the committed errors. Our findings add to a growing literature on the prefrontal cortex-guided control process in error monitoring and memory.</p></div>","PeriodicalId":74277,"journal":{"name":"Neuroimage. Reports","volume":"2 4","pages":"Article 100129"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666956022000538/pdfft?md5=b104fb511e8ff1a27ca3b7e6b462dfd8&pid=1-s2.0-S2666956022000538-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136427115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mediating effect of pubertal stages on the family environment and neurodevelopment: An open-data replication and multiverse analysis of an ABCD Study®","authors":"Michael I. Demidenko ,&nbsp;Dominic P. Kelly ,&nbsp;Felicia A. Hardi ,&nbsp;Ka I. Ip ,&nbsp;Sujin Lee ,&nbsp;Hannah Becker ,&nbsp;Sunghyun Hong ,&nbsp;Sandra Thijssen ,&nbsp;Monica Luciana ,&nbsp;Daniel P. Keating","doi":"10.1016/j.ynirp.2022.100133","DOIUrl":"10.1016/j.ynirp.2022.100133","url":null,"abstract":"<div><p>Increasing evidence demonstrates that environmental factors meaningfully impact the development of the brain (<span>Hyde et al., 2020</span>; <span>McEwen and Akil, 2020</span>). Recent work from the Adolescent Brain Cognitive Development (ABCD) Study® suggests that puberty may indirectly account for some association between the family environment and brain structure and function (<span>Thijssen et al., 2020</span>). However, a limited number of large studies have evaluated what, how, and why environmental factors impact neurodevelopment. When these topics are investigated, there is typically inconsistent operationalization of variables between studies which may be measuring different aspects of the environment and thus different associations in the analytic models. Multiverse analyses (<span>Steegen et al., 2016</span>) are an efficacious technique for investigating the effect of different operationalizations of the same construct on underlying interpretations. While one of the assets of <span>Thijssen et al. (2020)</span> was its large sample from the ABCD data, the authors used an early release that contained 38% of the full ABCD sample. Then, the analyses used several ‘researcher degrees of freedom’ (<span>Gelman and Loken, 2014</span>) to operationalize key independent, mediating and dependent variables, including but not limited to, the use of a latent factor of preadolescents' environment comprised of different subfactors, such as parental monitoring and child-reported family conflict. While latent factors can improve reliability of constructs, the nuances of each subfactor and measure that comprise the environment may be lost, making the latent factors difficult to interpret in the context of individual differences. This study extends the work of <span>Thijssen et al. (2020)</span> by evaluating the extent to which the analytic choices in their study affected their conclusions. In Aim 1, using the same variables and models, we replicate findings from the original study using the full sample in Release 3.0. Then, in Aim 2, using a multiverse analysis we extend findings by considering nine alternative operationalizations of family environment, three of puberty, and five of brain measures (total of 135 models) to evaluate the impact on conclusions from Aim 1. In these results, 90% of the directions of effects and 60% of the <em>p</em>-values (e.g. <em>p</em> &gt; .05 and <em>p</em> &lt; .05) across effects were comparable between the two studies. However, raters agreed that only 60% of the effects had replicated. Across the multiverse analyses, there was a degree of variability in beta estimates across the environmental variables, and lack of consensus between parent reported and child reported pubertal development for the indirect effects. This study demonstrates the challenge in defining which effects replicate, the nuance across environmental variables in the ABCD data, and the lack of consensus across parent and child reported pu","PeriodicalId":74277,"journal":{"name":"Neuroimage. Reports","volume":"2 4","pages":"Article 100133"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9770593/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10534845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Individualized prediction of future cognition based on developmental changes in cortical anatomy","authors":"Budhachandra Khundrakpam ,&nbsp;Linda Booij ,&nbsp;Seun Jeon ,&nbsp;Sherif Karama ,&nbsp;Jussi Tohka ,&nbsp;Alan C. Evans","doi":"10.1016/j.ynirp.2022.100127","DOIUrl":"10.1016/j.ynirp.2022.100127","url":null,"abstract":"<div><p>Predictive modeling studies have started to reveal brain measures underlying cognition; however, most studies are based on cross-sectional data (brain measures acquired at one time point). Since brain development comprises of continuously ongoing events leading to cognitive development, predictive modeling studies need to consider <em>‘longitudinal brain change’</em> as opposed to ‘<em>cross-sectional brain measures’</em>. Using longitudinal neuroimaging and cognitive data (global executive composite score, an index of executive function) from 82 individuals (aged 5–14 years, scanned 3 times), we built highly accurate prediction models (<em>r</em> = 0.61, <em>p</em> = 1.6e-09) of future cognition (assessed at visit 3) based on developmental changes in cortical anatomy (from visit 1 to 2). More importantly, <em>longitudinal brain change</em> (i.e. change in cortical anatomy from visit 1 to 2) and <em>cross-sectional brain measures</em> (cortical anatomy at visit 1 and 2) were critical for predicting future cognition, suggesting the need for considering <em>longitudinal brain change</em> in predicting cognitive outcomes.</p></div>","PeriodicalId":74277,"journal":{"name":"Neuroimage. Reports","volume":"2 4","pages":"Article 100127"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666956022000514/pdfft?md5=4d13c7707cdd6f0401bd897e0de2ee0e&pid=1-s2.0-S2666956022000514-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41404849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Regional gray matter volume correlates to physical and mental fatigue in healthy middle-aged adults","authors":"Handityo Aulia Putra ,&nbsp;Kaechang Park ,&nbsp;Fumio Yamashita ,&nbsp;Kei Mizuno ,&nbsp;Yasuyoshi Watanabe","doi":"10.1016/j.ynirp.2022.100128","DOIUrl":"10.1016/j.ynirp.2022.100128","url":null,"abstract":"<div><p>Previous studies on neural/molecular mechanisms of fatigue focused on a variety of brain functions, morphological changes, and neurochemical functions such as neurotransmitter and neuroimmune dynamics. However, MRI morphological changes were adopted primarily to compare patients with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) and healthy controls. A few studies have been done on healthy subjects with fatigue scores; one study with 63 adults (their ages of 53.2 ± 8.3) showed the gray matter volume (GMV) reduction in good correlation with a higher score of fatigue. The other one with university students (their ages of 20.7 ± 1.8) demonstrated no significant correlation between regional GMV (rGMV) and fatigue severity. To elucidate the brain structural underpinning in parallel with fatigue development, a large number of healthy middle-aged adults (n = 1873; aged 54.1 ± 5.4) without ME/CFS were recruited, and the correlation between both rGMV in the cerebrum including basal ganglia and Chalder's fatigue questionnaire (CFQ) with physical and mental categories were investigated. A higher CFQ score denotes a higher perceived fatigue level by the participant. The physical fatigue scores of CFQ showed a significantly negative correlation (i.e., smaller rGMV for higher CFQ score) with the volume of the right planum temporale and supplemental motor cortex (SMC), while the left putamen, middle temporal gyrus (MTG), parietal operculum, and right precentral gyrus showed a significantly positive correlation (i.e., bigger rGMV for higher CFQ score). In the mental fatigue scores, the right SMC and left lateral orbital gyrus (LOG) showed a significantly negative correlation, while only the left fusiform gyrus showed a significantly positive correlation. In total scores of (both physical and mental) fatigue, the right SMC and orbital part of the inferior frontal gyrus (OIFG) showed a negative correlation, while the left putamen and MTG showed a positive correlation. Therefore, the right SMC may play a critical role in fatigue progression because of the only common factor among physical, mental, and total fatigue. The left putamen may play a compensatory role with a positive correlation to physical and total fatigue. Additionally, identifying the other gray matter regions that positively or negatively correlated to CFQ of healthy adults may help deepen the understanding of early-stage fatigue progression, leading to the future establishment of preventive measures through volumetrics by using MRI.</p></div>","PeriodicalId":74277,"journal":{"name":"Neuroimage. Reports","volume":"2 4","pages":"Article 100128"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666956022000526/pdfft?md5=3c927aba059d5e56accf4c28d87c1fd4&pid=1-s2.0-S2666956022000526-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44588190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamic functional connectivity associated with prospective memory success in children","authors":"Teruo Hashimoto ,&nbsp;Susumu Yokota ,&nbsp;Satoshi Umeda ,&nbsp;Ryuta Kawashima","doi":"10.1016/j.ynirp.2022.100144","DOIUrl":"10.1016/j.ynirp.2022.100144","url":null,"abstract":"<div><p>To remember the prospective intention successfully, going back and forth between the background task and the intention, i.e., the dynamics of these multiple processes can be critical. An executive function like task switching has been associated with the success of prospective memory (PM) in children, but the neural mechanism of PM in children has not been investigated. The purpose of this study was to reveal the dynamic functional connectivity underlying the success of PM in children. Healthy 108 children, aged 7 to 15, were engaged in a single trial PM task, with a 30-min delay. Temporal variabilities in their resting-state functional connectivity were analyzed, using sliding windows with seed regions of interest ROIs of the PM network. About 70% of children successfully remembered the intention; they showed greater dynamics in neural connectivity between the right dorsolateral prefrontal cortex (DLPFC) and intraparietal sulcus, and between the right DLPFC and insula as compared to children with PM failure. Everyday activities and the usual attention to ongoing processes can be associated with alertness in the right frontoparietal network and internal-state monitoring in the insula network, and those dynamics might be associated with one-time event PM success in children.</p></div>","PeriodicalId":74277,"journal":{"name":"Neuroimage. Reports","volume":"2 4","pages":"Article 100144"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266695602200068X/pdfft?md5=3fcfc7be988d65c7e6da3c88dc13b5b2&pid=1-s2.0-S266695602200068X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48280586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}