Pitshaporn Leelaarporn, Marshall A. Dalton, R. Stirnberg, Tony Stöcker, A. Spottke, Anja Schneider, Cornelia McCormick
the comparison between the percentage of the signal change during
期间信号变化百分比的比较
{"title":"Correction to: Hippocampal subfields and their neocortical interactions during autobiographical memory","authors":"Pitshaporn Leelaarporn, Marshall A. Dalton, R. Stirnberg, Tony Stöcker, A. Spottke, Anja Schneider, Cornelia McCormick","doi":"10.1162/imag_x_00159","DOIUrl":"https://doi.org/10.1162/imag_x_00159","url":null,"abstract":"the comparison between the percentage of the signal change during","PeriodicalId":507939,"journal":{"name":"Imaging Neuroscience","volume":" 59","pages":"1-2"},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141132037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract During states of anxiety, fundamental threat circuitry in the brain can increase heart rate via alterations in autonomic balance (increased sympathetic activity and parasympathetic withdrawal) and may serve to promote interoceptive integration and awareness of cardiac signals. Moreover, evidence indicates pathological anxiety could be associated with increased communication between the brain and the heart. Yet, this phenomenon remains not well understood. For instance, studies in this area have been conducted within the confines of tightly controlled experimental paradigms. Whether anxiety impacts brain-heart communication outside of such experimental settings, and in relatively more naturalistic contexts, is less clear. Here, we used a suspenseful movie fMRI paradigm to study induced anxiety (n = 29 healthy volunteers; Caltech Conte dataset; Kliemann et al., 2022). We predicted that brain responses across an anxiety-relevant “defensive response network” (amygdala, hypothalamus, periaqueductal gray, bed nucleus of the stria terminalis, dorsomedial prefrontal cortex, ventromedial prefrontal cortex, subgenual anterior cingulate, and anterior insula; Abend et al., 2022) would show increased coherence with heart rate as participants watched a suspenseful movie clip compared to a non-suspenseful movie clip. Counter to our predictions, we found decreased coherence between heart rate and brain responses during increased anxiety, namely in amygdala-prefrontal circuitry. We suggest these alterations may be underpinned by parasympathetic withdrawal and/or decreased interoceptive awareness during suspenseful movie-watching.
{"title":"Preliminary evidence for altered brain-heart coherence during anxiogenic movies","authors":"Peter A. Kirk, Oliver J. Robinson","doi":"10.1162/imag_a_00156","DOIUrl":"https://doi.org/10.1162/imag_a_00156","url":null,"abstract":"Abstract During states of anxiety, fundamental threat circuitry in the brain can increase heart rate via alterations in autonomic balance (increased sympathetic activity and parasympathetic withdrawal) and may serve to promote interoceptive integration and awareness of cardiac signals. Moreover, evidence indicates pathological anxiety could be associated with increased communication between the brain and the heart. Yet, this phenomenon remains not well understood. For instance, studies in this area have been conducted within the confines of tightly controlled experimental paradigms. Whether anxiety impacts brain-heart communication outside of such experimental settings, and in relatively more naturalistic contexts, is less clear. Here, we used a suspenseful movie fMRI paradigm to study induced anxiety (n = 29 healthy volunteers; Caltech Conte dataset; Kliemann et al., 2022). We predicted that brain responses across an anxiety-relevant “defensive response network” (amygdala, hypothalamus, periaqueductal gray, bed nucleus of the stria terminalis, dorsomedial prefrontal cortex, ventromedial prefrontal cortex, subgenual anterior cingulate, and anterior insula; Abend et al., 2022) would show increased coherence with heart rate as participants watched a suspenseful movie clip compared to a non-suspenseful movie clip. Counter to our predictions, we found decreased coherence between heart rate and brain responses during increased anxiety, namely in amygdala-prefrontal circuitry. We suggest these alterations may be underpinned by parasympathetic withdrawal and/or decreased interoceptive awareness during suspenseful movie-watching.","PeriodicalId":507939,"journal":{"name":"Imaging Neuroscience","volume":"120 7","pages":"1-15"},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141033678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Madison Long, Curtis Ostertag, Jess E. Reynolds, Jing Zheng, Bennett Landman, Yuankai Huo, Nils D. Forkert, Catherine Lebel
Abstract Sex-specific developmental differences in brain structure have been documented in older children and adolescents, with females generally showing smaller overall brain volumes and earlier peak ages than males. However, sex differences in gray matter structural development in early childhood are less studied. We characterized sex-specific trajectories of gray matter volume development in children aged 2–8 years. We acquired anatomical magnetic resonance imaging (MRI) of the brain at the Alberta Children's Hospital in 123 typically developing children. Most children were scanned multiple times, for a total of 393 scans (mean = 3.2 scans/subject). We segmented T1-weighted structural MRI with MaCRUISE to define 116 regions and measured both absolute volumes (mm3) and proportional volumes (percent of intracranial volume). We characterized growth trajectories of gray matter volume for these brain regions between 2 and 8 years using mixed-effects models, showing volume increases, with most posterior and temporo-parietal regions peaking before 8 years. We found widespread main effects of sex, with males having larger volumes in 86% of brain regions. However, there were no significant sex differences in trajectories (age or age2 terms) for absolute volume. Proportional volumes of the right occipital fusiform gyrus and left medial postcentral gyrus showed significant age-by-sex interactions where females had steeper volume decreases than males. This study also confirms regional patterns observed in previous studies of older children, such as posterior-to-anterior timing of brain maturation. These results provide a comprehensive picture of gray matter volume development across early childhood, and suggest that sex differences do not emerge until later in development.
{"title":"Few sex differences in regional gray matter volume growth trajectories across early childhood","authors":"Madison Long, Curtis Ostertag, Jess E. Reynolds, Jing Zheng, Bennett Landman, Yuankai Huo, Nils D. Forkert, Catherine Lebel","doi":"10.1162/imag_a_00154","DOIUrl":"https://doi.org/10.1162/imag_a_00154","url":null,"abstract":"Abstract Sex-specific developmental differences in brain structure have been documented in older children and adolescents, with females generally showing smaller overall brain volumes and earlier peak ages than males. However, sex differences in gray matter structural development in early childhood are less studied. We characterized sex-specific trajectories of gray matter volume development in children aged 2–8 years. We acquired anatomical magnetic resonance imaging (MRI) of the brain at the Alberta Children's Hospital in 123 typically developing children. Most children were scanned multiple times, for a total of 393 scans (mean = 3.2 scans/subject). We segmented T1-weighted structural MRI with MaCRUISE to define 116 regions and measured both absolute volumes (mm3) and proportional volumes (percent of intracranial volume). We characterized growth trajectories of gray matter volume for these brain regions between 2 and 8 years using mixed-effects models, showing volume increases, with most posterior and temporo-parietal regions peaking before 8 years. We found widespread main effects of sex, with males having larger volumes in 86% of brain regions. However, there were no significant sex differences in trajectories (age or age2 terms) for absolute volume. Proportional volumes of the right occipital fusiform gyrus and left medial postcentral gyrus showed significant age-by-sex interactions where females had steeper volume decreases than males. This study also confirms regional patterns observed in previous studies of older children, such as posterior-to-anterior timing of brain maturation. These results provide a comprehensive picture of gray matter volume development across early childhood, and suggest that sex differences do not emerge until later in development.","PeriodicalId":507939,"journal":{"name":"Imaging Neuroscience","volume":"26 S71","pages":"1-26"},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141135775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
F. Gregersen, Hasan H Eroğlu, Cihan Göksu, O. Puonti, Zhentao Zuo, Axel Thielscher, Lars G. Hanson
Abstract Volume conductor models of the human head are routinely used to estimate the induced electric fields in transcranial brain stimulation (TBS) and for source localization in electro- and magnetoencephalography (EEG and MEG). Magnetic resonance current density imaging (MRCDI) has the potential to act as a non-invasive method for dose control and model validation but requires very sensitive MRI acquisition approaches. A double-echo echo-planar imaging (EPI) method is here introduced. It combines fast and sensitive imaging of the magnetic fields generated by the current flow of transcranial electric stimulation with increased robustness to physiological noise. For validation, noise floor measurements without injected currents were obtained in five subjects for an established multi-echo gradient-echo (MGRE) sequence and the new EPI method. In addition, data with current injection were acquired in each subject with a right-left (RL) and anterior-posterior (AP) electrode montage with both sequences to assess the accuracy of subject-specific detailed head models. In line with previous findings, the noise floor measurements showed that the MGRE results suffered from spatial low-frequency noise patterns, which were mostly absent in the EPI data. A recently published approach optimizes the ohmic conductivities of subject-specific head models by minimizing the difference between simulated and measured current-induced magnetic fields. Here, simulations demonstrated that the MGRE noise patterns have a larger negative impact on the optimization results than the EPI noise. For the current injection measurements, a larger discrepancy was found for the RL electrode montage compared with the AP electrode montage consistently for all subjects. This discrepancy that remained in part also after optimization of the ohmic conductivities, was similar for the data of the two sequences and larger than the measurement noise, and thus demonstrates systematic biases in the volume conductor models. We have shown that EPI-based MRCDI is superior to established techniques by mitigating the effects of previously reported spatial low-frequency noise in MRCDI if limited spatial resolution is acceptable. Additionally, the consistent inter-subject results indicate that MRCDI is capable of picking up inaccuracies in computational head models and will be useful to guide systematic improvements.
{"title":"MR imaging of the magnetic fields induced by injected currents can guide improvements of individualized head volume conductor models","authors":"F. Gregersen, Hasan H Eroğlu, Cihan Göksu, O. Puonti, Zhentao Zuo, Axel Thielscher, Lars G. Hanson","doi":"10.1162/imag_a_00176","DOIUrl":"https://doi.org/10.1162/imag_a_00176","url":null,"abstract":"Abstract Volume conductor models of the human head are routinely used to estimate the induced electric fields in transcranial brain stimulation (TBS) and for source localization in electro- and magnetoencephalography (EEG and MEG). Magnetic resonance current density imaging (MRCDI) has the potential to act as a non-invasive method for dose control and model validation but requires very sensitive MRI acquisition approaches. A double-echo echo-planar imaging (EPI) method is here introduced. It combines fast and sensitive imaging of the magnetic fields generated by the current flow of transcranial electric stimulation with increased robustness to physiological noise. For validation, noise floor measurements without injected currents were obtained in five subjects for an established multi-echo gradient-echo (MGRE) sequence and the new EPI method. In addition, data with current injection were acquired in each subject with a right-left (RL) and anterior-posterior (AP) electrode montage with both sequences to assess the accuracy of subject-specific detailed head models. In line with previous findings, the noise floor measurements showed that the MGRE results suffered from spatial low-frequency noise patterns, which were mostly absent in the EPI data. A recently published approach optimizes the ohmic conductivities of subject-specific head models by minimizing the difference between simulated and measured current-induced magnetic fields. Here, simulations demonstrated that the MGRE noise patterns have a larger negative impact on the optimization results than the EPI noise. For the current injection measurements, a larger discrepancy was found for the RL electrode montage compared with the AP electrode montage consistently for all subjects. This discrepancy that remained in part also after optimization of the ohmic conductivities, was similar for the data of the two sequences and larger than the measurement noise, and thus demonstrates systematic biases in the volume conductor models. We have shown that EPI-based MRCDI is superior to established techniques by mitigating the effects of previously reported spatial low-frequency noise in MRCDI if limited spatial resolution is acceptable. Additionally, the consistent inter-subject results indicate that MRCDI is capable of picking up inaccuracies in computational head models and will be useful to guide systematic improvements.","PeriodicalId":507939,"journal":{"name":"Imaging Neuroscience","volume":"62 5","pages":"1-15"},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141135127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bartholomew P. A. Quinn, David M. Watson, Kira Noad, Timothy J. Andrews
Abstract Neuroimaging studies have revealed a network of regions in both hemispheres of the human brain that respond selectively to faces. Neural models of face processing have typically focused on functional connectivity between regions in the same hemisphere (intrahemispheric), with a particular bias toward the right hemisphere. Here, we explored the role of interhemispheric connectivity using fMRI. We used three datasets to compare functional connectivity, as shown by correlations between the time-courses of neural activity of face regions during different natural viewing paradigms. We found higher correlations of neural activity between corresponding interhemispheric regions (e.g., rFFA–lFFA) than between intrahemispheric regions (e.g., rFFA–rOFA), indicating a bias towards higher interhemispheric than intrahemispheric connectivity. A similar interhemispheric bias was evident in scene-selective regions. In contrast, we did not find an interhemispheric bias in early visual regions (V1–V3), where intrahemispheric connectivity between corresponding regions was generally higher than interhemispheric connectivity. Next, we asked whether the higher interhemispheric connectivity in the face and scene networks between corresponding regions was consistent across participants. We found that the interhemispheric bias was significantly attenuated when we compared the time-course of response across participants. This shows that interhemispheric bias in connectivity between corresponding regions in the face and scene networks is specific to the individual. These findings raise the possibility that idiosyncratic variation in interhemispheric connectivity may explain individual differences in perception.
{"title":"Idiosyncratic patterns of interhemispheric connectivity in the face and scene networks of the human brain","authors":"Bartholomew P. A. Quinn, David M. Watson, Kira Noad, Timothy J. Andrews","doi":"10.1162/imag_a_00181","DOIUrl":"https://doi.org/10.1162/imag_a_00181","url":null,"abstract":"Abstract Neuroimaging studies have revealed a network of regions in both hemispheres of the human brain that respond selectively to faces. Neural models of face processing have typically focused on functional connectivity between regions in the same hemisphere (intrahemispheric), with a particular bias toward the right hemisphere. Here, we explored the role of interhemispheric connectivity using fMRI. We used three datasets to compare functional connectivity, as shown by correlations between the time-courses of neural activity of face regions during different natural viewing paradigms. We found higher correlations of neural activity between corresponding interhemispheric regions (e.g., rFFA–lFFA) than between intrahemispheric regions (e.g., rFFA–rOFA), indicating a bias towards higher interhemispheric than intrahemispheric connectivity. A similar interhemispheric bias was evident in scene-selective regions. In contrast, we did not find an interhemispheric bias in early visual regions (V1–V3), where intrahemispheric connectivity between corresponding regions was generally higher than interhemispheric connectivity. Next, we asked whether the higher interhemispheric connectivity in the face and scene networks between corresponding regions was consistent across participants. We found that the interhemispheric bias was significantly attenuated when we compared the time-course of response across participants. This shows that interhemispheric bias in connectivity between corresponding regions in the face and scene networks is specific to the individual. These findings raise the possibility that idiosyncratic variation in interhemispheric connectivity may explain individual differences in perception.","PeriodicalId":507939,"journal":{"name":"Imaging Neuroscience","volume":"30 35","pages":"1-20"},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141136418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
K. Schilling, Jordan A. Chad, Maxime Chamberland, Victor Nozais, F. Rheault, D. Archer, Muwei Li, Yurui Gao, Leon Cai, Flavio Del’Acqua, Allen Newton, Daniel Moyer, John C. Gore, Catherine Lebel, Bennett A. Landman
{"title":"Correction to: White matter tract microstructure, macrostructure, and associated cortical gray matter morphology across the lifespan","authors":"K. Schilling, Jordan A. Chad, Maxime Chamberland, Victor Nozais, F. Rheault, D. Archer, Muwei Li, Yurui Gao, Leon Cai, Flavio Del’Acqua, Allen Newton, Daniel Moyer, John C. Gore, Catherine Lebel, Bennett A. Landman","doi":"10.1162/imag_x_00158","DOIUrl":"https://doi.org/10.1162/imag_x_00158","url":null,"abstract":"","PeriodicalId":507939,"journal":{"name":"Imaging Neuroscience","volume":" 7","pages":"1-2"},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141131823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Discriminating patterns of brain activity corresponding to multiple hand movements are a challenging problem at the limit of the spatial resolution of magnetoencephalography (MEG). Here, we use the combination of MEG, a novel experimental paradigm, and a recently developed convolutional-neural-network-based classifier to demonstrate that four goal-directed real and imaginary movements—all performed by the same hand—can be detected from the MEG signal with high accuracy: >70% for real movements and >60% for imaginary movements. Additional experiments were used to control for possible confounds and to establish the empirical chance level. Investigation of the patterns informing the classification indicated the primary contribution of signals in the alpha (8–12 Hz) and beta (13–30 Hz) frequency range in the contralateral motor areas for the real movements, and more posterior parieto–occipital sources for the imagined movements. The obtained high accuracy can be exploited in practical applications, for example, in brain–computer interface-based motor rehabilitation.
{"title":"Robust discrimination of multiple naturalistic same-hand movements from MEG signals with convolutional neural networks","authors":"I. Zubarev, Mila Nurminen, L. Parkkonen","doi":"10.1162/imag_a_00178","DOIUrl":"https://doi.org/10.1162/imag_a_00178","url":null,"abstract":"Abstract Discriminating patterns of brain activity corresponding to multiple hand movements are a challenging problem at the limit of the spatial resolution of magnetoencephalography (MEG). Here, we use the combination of MEG, a novel experimental paradigm, and a recently developed convolutional-neural-network-based classifier to demonstrate that four goal-directed real and imaginary movements—all performed by the same hand—can be detected from the MEG signal with high accuracy: >70% for real movements and >60% for imaginary movements. Additional experiments were used to control for possible confounds and to establish the empirical chance level. Investigation of the patterns informing the classification indicated the primary contribution of signals in the alpha (8–12 Hz) and beta (13–30 Hz) frequency range in the contralateral motor areas for the real movements, and more posterior parieto–occipital sources for the imagined movements. The obtained high accuracy can be exploited in practical applications, for example, in brain–computer interface-based motor rehabilitation.","PeriodicalId":507939,"journal":{"name":"Imaging Neuroscience","volume":"49 S244","pages":"1-15"},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141134880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dominik Kraft, G. M. Bon, Édith Breton, Philipp Seidel, Tobias Kaufmann
Abstract Scan site harmonization is a crucial part of any neuroimaging analysis when data have been pooled across different study sites. Zhang and colleagues recently introduced the multivariate harmonization method RELIEF (REmoval of Latent Inter-scanner Effects through Factorization), aiming to remove explicit and latent scan site effects. Their initial validation in an adult sample showed superior performance compared to established methods. We here sought to investigate utility of RELIEF in harmonizing data from the Adolescent Brain and Cognitive Development (ABCD) study, a widely used resource for developmental brain imaging. We benchmarked RELIEF against unharmonized, ComBat, and CovBat harmonized data and investigated the impact of manufacturer type, sample size, and a narrow sample age range on harmonization performance. We found that in cases where sites with sufficiently large samples were harmonized, RELIEF outperformed other techniques, yet in cases where sites with very small samples were included there was substantial performance variation unique to RELIEF. Our results therefore highlight the need for careful quality control when harmonizing data sets with imbalanced samples like the ABCD cohort. Our comment alongside shared scripts may provide guidance for other scholars wanting to integrate best practices in their ABCD related work.
{"title":"Removing scanner effects with a multivariate latent approach: A RELIEF for the ABCD imaging data?","authors":"Dominik Kraft, G. M. Bon, Édith Breton, Philipp Seidel, Tobias Kaufmann","doi":"10.1162/imag_a_00157","DOIUrl":"https://doi.org/10.1162/imag_a_00157","url":null,"abstract":"Abstract Scan site harmonization is a crucial part of any neuroimaging analysis when data have been pooled across different study sites. Zhang and colleagues recently introduced the multivariate harmonization method RELIEF (REmoval of Latent Inter-scanner Effects through Factorization), aiming to remove explicit and latent scan site effects. Their initial validation in an adult sample showed superior performance compared to established methods. We here sought to investigate utility of RELIEF in harmonizing data from the Adolescent Brain and Cognitive Development (ABCD) study, a widely used resource for developmental brain imaging. We benchmarked RELIEF against unharmonized, ComBat, and CovBat harmonized data and investigated the impact of manufacturer type, sample size, and a narrow sample age range on harmonization performance. We found that in cases where sites with sufficiently large samples were harmonized, RELIEF outperformed other techniques, yet in cases where sites with very small samples were included there was substantial performance variation unique to RELIEF. Our results therefore highlight the need for careful quality control when harmonizing data sets with imbalanced samples like the ABCD cohort. Our comment alongside shared scripts may provide guidance for other scholars wanting to integrate best practices in their ABCD related work.","PeriodicalId":507939,"journal":{"name":"Imaging Neuroscience","volume":"41 8","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141044944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Y. Chai, A. T. Morgan, Hua Xie, Linqing Li, Laurentius Huber, Peter A. Bandettini, Bradley P. Sutton
Abstract Neuroscientific investigations at the cortical layer level not only enrich our knowledge of cortical micro-circuitry in vivo, but also help bridge the gap between macroscopic (e.g., conventional fMRI, behavior) and microscopic (e.g., extracellular recordings) measures of brain function. While laminar fMRI studies have extensively explored the evoked cortical response in multiple subsystems, the investigation of the laminar component of functional networks throughout the entire brain has been hindered due to constraints in high-resolution layer-fMRI imaging methodologies. Our study addresses this gap by introducing an innovative layer-specific 3D VAPER (integrated VASO and Perfusion contrast) technique in humans at 7 T, for achieving fMRI at high resolution (800 µm isotropic), high specificity (not biased toward unspecific vein signals as BOLD), high sensitivity (robust measurement at submillimeter resolution), high spatial accuracy (analysis in native fMRI space), near-whole-brain coverage (cerebellum not included), and eventually extending layer fMRI to more flexible connectivity-based experiment designs. To demonstrate its effectiveness, we collected 0.8-mm isotropic fMRI data during both resting-state and movie-watching scenarios, established a layer-specific functional connectivity analysis pipeline from individual to group levels, and explored the role of different cortical layers in maintaining functional networks. Our results revealed distinct layer-specific connectivity patterns within the default mode, somatomotor, and visual networks, as well as at the global hubness level. The cutting-edge technique and insights derived from our exploration into near-whole-brain layer-specific connectivity provide unparalleled understanding of the organization principles and underlying mechanisms governing communication between different brain regions.
{"title":"Unlocking near-whole-brain, layer-specific functional connectivity with 3D VAPER fMRI","authors":"Y. Chai, A. T. Morgan, Hua Xie, Linqing Li, Laurentius Huber, Peter A. Bandettini, Bradley P. Sutton","doi":"10.1162/imag_a_00140","DOIUrl":"https://doi.org/10.1162/imag_a_00140","url":null,"abstract":"Abstract Neuroscientific investigations at the cortical layer level not only enrich our knowledge of cortical micro-circuitry in vivo, but also help bridge the gap between macroscopic (e.g., conventional fMRI, behavior) and microscopic (e.g., extracellular recordings) measures of brain function. While laminar fMRI studies have extensively explored the evoked cortical response in multiple subsystems, the investigation of the laminar component of functional networks throughout the entire brain has been hindered due to constraints in high-resolution layer-fMRI imaging methodologies. Our study addresses this gap by introducing an innovative layer-specific 3D VAPER (integrated VASO and Perfusion contrast) technique in humans at 7 T, for achieving fMRI at high resolution (800 µm isotropic), high specificity (not biased toward unspecific vein signals as BOLD), high sensitivity (robust measurement at submillimeter resolution), high spatial accuracy (analysis in native fMRI space), near-whole-brain coverage (cerebellum not included), and eventually extending layer fMRI to more flexible connectivity-based experiment designs. To demonstrate its effectiveness, we collected 0.8-mm isotropic fMRI data during both resting-state and movie-watching scenarios, established a layer-specific functional connectivity analysis pipeline from individual to group levels, and explored the role of different cortical layers in maintaining functional networks. Our results revealed distinct layer-specific connectivity patterns within the default mode, somatomotor, and visual networks, as well as at the global hubness level. The cutting-edge technique and insights derived from our exploration into near-whole-brain layer-specific connectivity provide unparalleled understanding of the organization principles and underlying mechanisms governing communication between different brain regions.","PeriodicalId":507939,"journal":{"name":"Imaging Neuroscience","volume":"180 1","pages":"1-20"},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140763712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. Ingwersen, C. Mayer, M. Petersen, B. Frey, J. Fiehler, U. Hanning, Simone Kühn, Jürgen Gallinat, R. Twerenbold, C. Gerloff, B. Cheng, G. Thomalla, E. Schlemm
Abstract We aimed to replicate recent findings on the association between the extent of cerebral small vessel disease (cSVD), functional brain network dedifferentiation, and cognitive impairment. We analyzed demographic, imaging, and behavioral data from the prospective population-based Hamburg City Health Study. Using a fully prespecified analysis pipeline, we estimated discrete brain states from structural and resting-state functional magnetic resonance imaging (MRI). In a multiverse analysis, we varied brain parcellations and functional MRI confound regression strategies. The severity of cSVD was operationalized as the volume of white matter hyperintensities of presumed vascular origin. Processing speed and executive dysfunction were quantified using the Trail Making Test (TMT). We hypothesized a) that a greater volume of supratentorial white matter hyperintensities would be associated with less time spent in functional MRI-derived brain states of high fractional occupancy; and b) that less time spent in these high-occupancy brain states associated with a longer time to completion in part B of the TMT. High-occupancy brain states were characterized by activation or suppression of the default mode network. Every 5.1-fold increase in WMH volume was associated with a 0.94-fold reduction in the odds of occupying DMN-related brain states (P = 5.01×10−8). Every 5% increase in time spent in high-occupancy brain states was associated with a 0.98-fold reduction in the TMT-B completion time (P = 0.0116). Findings were robust across most brain parcellations and confound regression strategies. In conclusion, we successfully replicated previous findings on the association between cSVD, functional brain occupancy, and cognition in an independent sample. The data provide further evidence for a functional network dedifferentiation hypothesis of cSVD-related cognitive impairment. Further research is required to elucidate the mechanisms underlying these associations.
{"title":"Functional MRI brain state occupancy in the presence of cerebral small vessel disease—a pre-registered replication analysis of the Hamburg City Health Study","authors":"T. Ingwersen, C. Mayer, M. Petersen, B. Frey, J. Fiehler, U. Hanning, Simone Kühn, Jürgen Gallinat, R. Twerenbold, C. Gerloff, B. Cheng, G. Thomalla, E. Schlemm","doi":"10.1162/imag_a_00122","DOIUrl":"https://doi.org/10.1162/imag_a_00122","url":null,"abstract":"Abstract We aimed to replicate recent findings on the association between the extent of cerebral small vessel disease (cSVD), functional brain network dedifferentiation, and cognitive impairment. We analyzed demographic, imaging, and behavioral data from the prospective population-based Hamburg City Health Study. Using a fully prespecified analysis pipeline, we estimated discrete brain states from structural and resting-state functional magnetic resonance imaging (MRI). In a multiverse analysis, we varied brain parcellations and functional MRI confound regression strategies. The severity of cSVD was operationalized as the volume of white matter hyperintensities of presumed vascular origin. Processing speed and executive dysfunction were quantified using the Trail Making Test (TMT). We hypothesized a) that a greater volume of supratentorial white matter hyperintensities would be associated with less time spent in functional MRI-derived brain states of high fractional occupancy; and b) that less time spent in these high-occupancy brain states associated with a longer time to completion in part B of the TMT. High-occupancy brain states were characterized by activation or suppression of the default mode network. Every 5.1-fold increase in WMH volume was associated with a 0.94-fold reduction in the odds of occupying DMN-related brain states (P = 5.01×10−8). Every 5% increase in time spent in high-occupancy brain states was associated with a 0.98-fold reduction in the TMT-B completion time (P = 0.0116). Findings were robust across most brain parcellations and confound regression strategies. In conclusion, we successfully replicated previous findings on the association between cSVD, functional brain occupancy, and cognition in an independent sample. The data provide further evidence for a functional network dedifferentiation hypothesis of cSVD-related cognitive impairment. Further research is required to elucidate the mechanisms underlying these associations.","PeriodicalId":507939,"journal":{"name":"Imaging Neuroscience","volume":"39 12","pages":"1-17"},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140771724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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