Neuroimage. Reports最新文献

{"title":"Cortical thickness in brain imaging studies using FreeSurfer and CAT12: A matter of reproducibility","authors":"Maria de Fátima Machado Dias ,&nbsp;Paulo Carvalho ,&nbsp;Miguel Castelo-Branco ,&nbsp;João Valente Duarte","doi":"10.1016/j.ynirp.2022.100137","DOIUrl":"10.1016/j.ynirp.2022.100137","url":null,"abstract":"<div><p>A reproducibility crisis has been reported across many research fields, including neuroimaging, reaching up to 70% of studies. Neuroimaging data, such as magnetic resonance imaging (MRI), requires pre-processing to allow for inter-subject comparison, increase signal contrast and noise reduction. As manual MRI pre-processing is time consuming and requires expertise, multiple automatic pre-processing frameworks have been proposed. However, neuroimaging studies often report divergent results, even for similar populations, thus it is important to determine whether this occurs as a result of different processing tools. Two of the most used tools are FreeSurfer and the Computational Anatomy Toolbox (CAT12). In this study we assessed the reproducibility between these two automatic pre-processing frameworks for structural MRI and test-retest reliability within framework on estimation of cortical thickness. Our results show that the reproducibility between the frameworks is lower at the region-of-interest (ROI) level than at individual level. Furthermore, we found that the reproducibility was lower in paediatric samples than in adults. Finally, an acquisition site effect was also identified. Given the widespread use of these frameworks in basic and clinical neuroscience, the results of multicentric cross-sectional studies must be interpreted with caution, particularly with paediatric samples. The observed reproducibility issue might be one of the sources of discrepancies reported in neuroimaging studies. On a positive note, framework test-retest reliability within subject is high, suggesting that inconsistency of results may be less concerning in longitudinal studies. The code is available at: <span>https://cibit-uc.github.io/fs-cat12-cortical-thickness-reproducibility</span><svg><path></path></svg>.</p></div>","PeriodicalId":74277,"journal":{"name":"Neuroimage. Reports","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666956022000617/pdfft?md5=d737a1923d590697d8099543175efcd5&pid=1-s2.0-S2666956022000617-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41760192","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":"Domain-specific neural substrates underlie the framing effect","authors":"Sai Sun ,&nbsp;Jianping Hu ,&nbsp;Rongjun Yu","doi":"10.1016/j.ynirp.2022.100119","DOIUrl":"https://doi.org/10.1016/j.ynirp.2022.100119","url":null,"abstract":"<div><p>Human decision making can be influenced by presenting different options with positive or negative connotations. This phenomenon is termed the framing effect. Neuroeconomic studies have found that the amygdala plays a significant role in the framing effect, as it incorporates emotional (or intuitive) information into the decision process, which may lead to bias or irrationality. However, previous studies have focused only on the gain domain, in which the initial state is positive (appetitive). The mechanisms underlying the framing effect in the loss (aversive) domain are less well understood, despite their importance for evolution and survival. In this study, we first replicated the findings of De Martino et al. on the framing effect in the gain domain. We then searched for similarities and differences between the gain and loss domains using a similar experimental design combined with functional magnetic resonance imaging. Behaviorally, the participants showed comparable effects for both frame types, suggesting a frame-indiscriminate decision bias. In contrast, at the neuronal level, we found that the amygdala specifically represented the framing effect in the gain domain, and its connectivity to the ventromedial prefrontal cortex was positively modulated by the framing bias, similar to the findings of De Martino et al. However, the striatum was found to represent the framing effect in the loss domain. Striatal connectivity to the dorsomedial prefrontal cortex was similarly affected by the framing bias, suggesting domain-specific neural substrates. Our study emphasizes the importance of distinguishing between gain and loss domains when studying decision making, and highlights the governing role of the cortical–striatal–limbic network in the framing effect.</p></div>","PeriodicalId":74277,"journal":{"name":"Neuroimage. Reports","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666956022000435/pdfft?md5=ad861fcf0ec8504e8a4b2a3e34c12316&pid=1-s2.0-S2666956022000435-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136429012","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":"Frontal midline theta and cross-frequency coupling during short term memory and resting state","authors":"András Puszta","doi":"10.1016/j.ynirp.2022.100124","DOIUrl":"https://doi.org/10.1016/j.ynirp.2022.100124","url":null,"abstract":"<div><p>This paper aims to establish how frontal midline theta and theta-gamma coupling are altered by memory load as well as by recall performance during a verbal digit span task using an open EEG dataset. Traditional behavioral scores, as well as new measure were used, as the recall accuracy as a function of the order of the digits followed a sigmoid curve. The new behavioral score was strongly correlated with traditional measures. The EEG results show that neither the resting state theta nor the theta during the digit span task is predictive of the task performance. However, there was a strong positive correlation between cognitive load and theta power as well as a negative correlation between cognitive load and theta peak frequency during the task. These results are in line with earlier studies indicating that frontal midline theta is modulated by cognitive load rather than memory performance. Furthermore, there was an increased alpha-beta cross frequency coupling during resting state but that was not correlated with the performance of the upcoming memory task. During the task the cross-frequency coupling was minimal, and it did not correlate with memory performance nor with task load, that raises the possibility that EEG is not sensitive enough for cross-frequency coupling measures.</p></div>","PeriodicalId":74277,"journal":{"name":"Neuroimage. Reports","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666956022000484/pdfft?md5=1f2cd44651fa1377f08c0d37eb7ff24d&pid=1-s2.0-S2666956022000484-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136429013","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":"fMRI BOLD and MEG theta power reflect complementary aspects of activity during lexicosemantic decision in adolescents with ASD","authors":"M. Wilkinson ,&nbsp;R.J. Jao Keehn ,&nbsp;A.C. Linke ,&nbsp;Y. You ,&nbsp;Y. Gao ,&nbsp;K. Alemu ,&nbsp;A. Correas ,&nbsp;B.Q. Rosen ,&nbsp;J.S. Kohli ,&nbsp;L. Wagner ,&nbsp;A. Sridhar ,&nbsp;K. Marinkovic ,&nbsp;R.-A. Müller","doi":"10.1016/j.ynirp.2022.100134","DOIUrl":"10.1016/j.ynirp.2022.100134","url":null,"abstract":"<div><p>Neuroimaging studies of autism spectrum disorder (ASD) have been predominantly unimodal. While many fMRI studies have reported atypical activity patterns for diverse tasks, the MEG literature in ASD remains comparatively small. Our group recently reported atypically increased event-related theta power in individuals with ASD during lexicosemantic processing. The current multimodal study examined the relationship between fMRI BOLD signal and anatomically-constrained MEG (aMEG) theta power. Thirty-three adolescents with ASD and 23 typically developing (TD) peers took part in both fMRI and MEG scans, during which they distinguished between standard words (SW), animal words (AW), and pseudowords (PW). Regions-of-interest (ROIs) were derived based on task effects detected in BOLD signal and aMEG theta power. BOLD signal and theta power were extracted for each ROI and word condition. Compared to TD participants, increased theta power in the ASD group was found across several time windows and regions including left fusiform and inferior frontal, as well as right angular and anterior cingulate gyri, whereas BOLD signal was significantly increased in the ASD group only in right anterior cingulate gyrus. No significant correlations were observed between BOLD signal and theta power. Findings suggest that the common interpretation of increases in BOLD signal and theta power as ‘activation’ require careful differentiation, as these reflect largely distinct aspects of regional brain activity. Some group differences in dynamic neural processing detected with aMEG that are likely relevant for lexical processing may be obscured by the hemodynamic signal source and low temporal resolution of fMRI.</p></div>","PeriodicalId":74277,"journal":{"name":"Neuroimage. Reports","volume":null,"pages":null},"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/ef/7e/nihms-1846542.PMC9683354.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10648534","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":"Impact of face outline, parafoveal feature number and feature type on early face perception in a gaze-contingent paradigm: A mass-univariate re-analysis of ERP data","authors":"Seth B. Winward,&nbsp;James Siklos-Whillans,&nbsp;Roxane J. Itier","doi":"10.1016/j.ynirp.2022.100148","DOIUrl":"10.1016/j.ynirp.2022.100148","url":null,"abstract":"<div><p>Recent ERP research using a gaze-contingent paradigm suggests the face-sensitive N170 component is modulated by the presence of a face outline, the number of parafoveal facial features, and the type of feature in parafovea (Parkington and Itier, 2019). The present study re-analyzed these data using robust mass univariate statistics available through the LIMO toolbox, allowing the examination of the ERP signal across all electrodes and time points. We replicated the finding that the presence of a face outline significantly reduced ERP latencies and amplitudes, suggesting it is an important cue to the prototypical face template. However, we found that this effect began around 114 ms, and was maximal during the P1-N170 and N170-P2 intervals. The number of features present in parafovea also impacted the entire waveform, with systematic reductions in amplitude and latency as the number of features increased. This effect was maximal around 120 ms during the P1-N170 interval and around 170 ms between the N170 and P2. The ERP response was also modulated by feature type; contrary to previous findings this effect was maximal around 200 ms and the P2 peak. Although we provide partial replication of the previous results on the N170, the effects were more temporally distributed in the present analysis. These effects were generally maximal before and after the N170 and were the weakest at the N170 peak itself. This re-analysis demonstrates that classical ERP analysis can obscure important aspects of face processing beyond the N170 peak, and that tools like mass univariate statistics are needed to shed light on the whole time-course of face processing.</p></div>","PeriodicalId":74277,"journal":{"name":"Neuroimage. Reports","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666956022000721/pdfft?md5=88de926107abc91b7f5b26ea14540b5b&pid=1-s2.0-S2666956022000721-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43215016","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":"Replication of neural responses to monetary incentives and exploration of reward-influenced network connectivity in fibromyalgia","authors":"Su Hyoun Park ,&nbsp;Eden Z. Deng ,&nbsp;Anne K. Baker ,&nbsp;Kelly H. MacNiven ,&nbsp;Brian Knutson ,&nbsp;Katherine T. Martucci","doi":"10.1016/j.ynirp.2022.100147","DOIUrl":"10.1016/j.ynirp.2022.100147","url":null,"abstract":"<div><p>Neuroimaging research has begun to implicate alterations of brain reward systems in chronic pain. Previously, using functional magnetic resonance imaging (fMRI) and a monetary incentive delay (MID) task, <span>Martucci et al. (2018)</span> showed that neural responses to reward anticipation and outcome are altered in fibromyalgia. In the present study, we aimed to test the replicability of these altered neural responses to reward in a separate fibromyalgia cohort. In addition, the present study was conducted at a distinct U.S. location but involved a similar study design. For the present study, 20 patients with fibromyalgia and 20 healthy controls participated in MID task fMRI scan procedures and completed clinical/psychological questionnaires. fMRI analyses comparing patient and control groups revealed a consistent trend of main results which were largely similar to the prior reported results. Specifically, in the replication fibromyalgia cohort, medial prefrontal cortex (MPFC) response was reduced during gain anticipation and was increased during no-loss (non-punishment) outcome compared to controls. Also consistent with previous findings, the nucleus accumbens response to gain anticipation did not differ in patients vs. controls. Further, results from similarly-designed behavioral, correlational, and exploratory analyses were complementary to previous findings. Finally, a novel network-based functional connectivity analysis of the MID task fMRI data across patients vs. controls implied enhanced connectivity within the default mode network in participants with fibromyalgia. Together, based on replicating prior univariate results and new network-based functional connectivity analyses of MID task fMRI data, we provide further evidence of altered brain reward responses, particularly in the MPFC response to reward outcomes, in patients with fibromyalgia.</p></div>","PeriodicalId":74277,"journal":{"name":"Neuroimage. Reports","volume":null,"pages":null},"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/3a/6d/nihms-1855871.PMC9815752.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10519705","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":"Validation of cross-sectional and longitudinal ComBat harmonization methods for magnetic resonance imaging data on a travelling subject cohort","authors":"Sophie Richter ,&nbsp;Stefan Winzeck ,&nbsp;Marta M. Correia ,&nbsp;Evgenios N. Kornaropoulos ,&nbsp;Anne Manktelow ,&nbsp;Joanne Outtrim ,&nbsp;Doris Chatfield ,&nbsp;Jussi P. Posti ,&nbsp;Olli Tenovuo ,&nbsp;Guy B. Williams ,&nbsp;David K. Menon ,&nbsp;Virginia F.J. Newcombe","doi":"10.1016/j.ynirp.2022.100136","DOIUrl":"10.1016/j.ynirp.2022.100136","url":null,"abstract":"<div><h3>Background</h3><p>The growth in multi-center neuroimaging studies generated a need for methods that mitigate the differences in hardware and acquisition protocols across sites i.e., scanner effects. ComBat harmonization methods have shown promise but have not yet been tested on all the data types commonly studied with magnetic resonance imaging (MRI). This study aimed to validate neuroCombat, longCombat and gamCombat on both structural and diffusion metrics in both cross-sectional and longitudinal data.</p></div><div><h3>Methods</h3><p>We used a travelling subject design whereby 73 healthy volunteers contributed 161 scans across two sites and four machines using one T1 and five diffusion MRI protocols. Scanner was defined as a composite of site, machine and protocol. A common pipeline extracted two structural metrics (volumes and cortical thickness) and two diffusion tensor imaging metrics (mean diffusivity and fractional anisotropy) for seven regions of interest including gray and (except for cortical thickness) white matter regions.</p></div><div><h3>Results</h3><p>Structural data exhibited no significant scanner effect and therefore did not benefit from harmonization in our particular cohort. Indeed, attempting harmonization obscured the true biological effect for some regions of interest. Diffusion data contained marked scanner effects and was successfully harmonized by all methods, resulting in smaller scanner effects and better detection of true biological effects. LongCombat less effectively reduced the scanner effect for cross-sectional white matter data but had a slightly lower probability of incorrectly finding group differences in simulations, compared to neuroCombat and gamCombat. False positive rates for all methods and all metrics did not significantly exceed 5%.</p></div><div><h3>Conclusions</h3><p>Statistical harmonization of structural data is not always necessary and harmonization in the absence of a scanner effect may be harmful. Harmonization of diffusion MRI data is highly recommended with neuroCombat, longCombat and gamCombat performing well in cross-sectional and longitudinal settings.</p></div>","PeriodicalId":74277,"journal":{"name":"Neuroimage. Reports","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9726680/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9506191","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":"Normative mammillary body volumes: From the neonatal period to young adult","authors":"Seralynne D. Vann ,&nbsp;Cornel Zachiu ,&nbsp;Karlijn M.E. Meys ,&nbsp;Sara Ambrosino ,&nbsp;Sarah Durston ,&nbsp;Linda S. de Vries ,&nbsp;Floris Groenendaal ,&nbsp;Maarten H. Lequin","doi":"10.1016/j.ynirp.2022.100122","DOIUrl":"10.1016/j.ynirp.2022.100122","url":null,"abstract":"<div><p>The mammillary bodies may be small, but they have an important role in encoding complex memories. Mammillary body pathology often occurs following thiamine deficiency but there is increasing evidence that the mammillary bodies are also compromised in other neurological conditions and in younger ages groups. For example, the mammillary bodies are frequently affected in neonates with hypoxic-ischemic encephalopathy. At present, there is no normative data for the mammillary bodies in younger groups making it difficult to identify abnormalities in neurological disorders. To address this, the present study set out to develop a normative dataset for neonates and for children to young adult. A further aim was to determine whether there were laterality or sex differences in mammillary body volumes. Mammillary body volumes were obtained from MRI scans from 506 participants across two datasets. Measures for neonates were acquired from the Developing Human Connectome Project database (156 male; 100 female); volumes for individuals aged 6–24 were acquired from the NICHE database (166 males; 84 females). Volume measurements were acquired using a semi-automated multi-atlas segmentation approach. Mammillary body volumes increased up to approximately 15 years-of-age. The left mammillary body was marginally, but significantly, larger than the right in the neonates with a similar pattern in older children/young adults. In neonates, the mammillary bodies in males were slightly bigger than females but no sex differences were present in older children/young adults. Given the increasing presentation of mammillary body pathology in neonates and children, these normative data will enable better assessment of the mammillary bodies in healthy and at-risk populations.</p></div>","PeriodicalId":74277,"journal":{"name":"Neuroimage. Reports","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9726681/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10333450","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":"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":null,"pages":null},"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":null,"pages":null},"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}