Anja Hohmann, Ke Zhang, J. M. Jende, Christoph M Mooshage, Kai Görgen, Lukas T. Rotkopf, H. Schlemmer, Philipp Vollmuth, Martin Bendszus, W. Wick, Felix T. Kurz
Abstract Objectives: Previous studies indicate region-specific age- and sex-related changes in cerebral microvasculature. Using whole-brain vascular architecture mapping (VAM), our objective was to map and assess these changes in human microvasculature in vivo. Materials and methods: Cardiovascular healthy women (n = 40) and men (n = 32) with unifocal low-grade glioma, matched for age [range: 20-70 years] and BMI, were examined on the non-tumor hemisphere with a combined spin and gradient echo echo-planar imaging sequence at 3 T MRI. Vessel vortex curves were obtained by pair-wise plotting changes in relaxation rates R2* and R2 during contrast agent bolus passage, which each generate a set of VAM parameters that characterize microvascular properties, such as vessel type, lumen size, or blood flow. Averaged VAM values of cortical grey matter, white matter, putamen, globus pallidus, caudate nucleus, thalamus, insular cortex, and hippocampus were assessed for age- and sex-related changes. Results: With age, dominant vessel types changed from capillaries to an arteriole-dominated profile, particularly in insula, thalamus, and globus pallidus. In white matter, blood flow velocity decreased significantly with aging for both sexes (r = −0.33, p = 0.004). In women, aging was associated with an increase in microvessel caliber, particularly in thalamus (r = 0.39, p = 0.01) and insula (r = 0.34, p = 0.03). In all grey matter areas, women had a higher microvessel density than men (4.33 ± 0.26ˑ102 ms-1/3 vs. 4.18 ± 0.26ˑ102 ms-1/3; p = 0.025, respectively). Conclusions: Aging affects microvasculature differently across brain regions in women and men, especially in thalamus and insula.
{"title":"Vascular architecture mapping reveals sex-specific changes in cerebral microvasculature with aging","authors":"Anja Hohmann, Ke Zhang, J. M. Jende, Christoph M Mooshage, Kai Görgen, Lukas T. Rotkopf, H. Schlemmer, Philipp Vollmuth, Martin Bendszus, W. Wick, Felix T. Kurz","doi":"10.1162/imag_a_00066","DOIUrl":"https://doi.org/10.1162/imag_a_00066","url":null,"abstract":"Abstract Objectives: Previous studies indicate region-specific age- and sex-related changes in cerebral microvasculature. Using whole-brain vascular architecture mapping (VAM), our objective was to map and assess these changes in human microvasculature in vivo. Materials and methods: Cardiovascular healthy women (n = 40) and men (n = 32) with unifocal low-grade glioma, matched for age [range: 20-70 years] and BMI, were examined on the non-tumor hemisphere with a combined spin and gradient echo echo-planar imaging sequence at 3 T MRI. Vessel vortex curves were obtained by pair-wise plotting changes in relaxation rates R2* and R2 during contrast agent bolus passage, which each generate a set of VAM parameters that characterize microvascular properties, such as vessel type, lumen size, or blood flow. Averaged VAM values of cortical grey matter, white matter, putamen, globus pallidus, caudate nucleus, thalamus, insular cortex, and hippocampus were assessed for age- and sex-related changes. Results: With age, dominant vessel types changed from capillaries to an arteriole-dominated profile, particularly in insula, thalamus, and globus pallidus. In white matter, blood flow velocity decreased significantly with aging for both sexes (r = −0.33, p = 0.004). In women, aging was associated with an increase in microvessel caliber, particularly in thalamus (r = 0.39, p = 0.01) and insula (r = 0.34, p = 0.03). In all grey matter areas, women had a higher microvessel density than men (4.33 ± 0.26ˑ102 ms-1/3 vs. 4.18 ± 0.26ˑ102 ms-1/3; p = 0.025, respectively). Conclusions: Aging affects microvasculature differently across brain regions in women and men, especially in thalamus and insula.","PeriodicalId":507939,"journal":{"name":"Imaging Neuroscience","volume":"15 12","pages":"1-15"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139457074","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}
Wenchuan Wu, Sebastian W Rieger, L. Baxter, Eleri Adams, Jesper L. R. Andersson, Maria M. Cobo, Foteini Andritsou, Matteo Bastiani, Ria Evans Fry, Robert Frost, Sean Fitzgibbon, S. Foxley, Darren Fowler, Chris Gallagher, A. Howard, J. Hajnal, Fiona Moultrie, V. Monk, David A Porter, Daniel Papp, Anthony Price, J. Sallet, Michael Sanders, Dominic Wilkinson, Rebeccah Slater, Karla L. Miller
Abstract Diffusion MRI of the infant brain allows investigation of the organizational structure of maturing fibers during brain development. Post-mortem imaging has the potential to achieve high resolution by using long scan times, enabling precise assessment of small structures. Technical development for post-mortem diffusion MRI has primarily focused on scanning of fixed tissue, which is robust to effects like temperature drift that can cause unfixed tissue to degrade. The ability to scan unfixed tissue in the intact body would enable post-mortem studies without organ donation, but poses new technical challenges. This paper describes our approach to scan setup, protocol optimization, and tissue protection in the context of the Developing Human Connectome Project (dHCP) of neonates. A major consideration was the need to preserve the integrity of unfixed tissue during scanning in light of energy deposition at ultra-high magnetic field strength. We present results from one of the first two subjects recruited to the study, who died on postnatal day 46 at 29+6 weeks postmenstrual age, demonstrating high-quality diffusion MRI data. We find altered diffusion properties consistent with post-mortem changes reported previously. Preliminary voxel-wise and tractography analyses are presented with comparison to age-matched in vivo dHCP data. These results show that high-quality, high-resolution post-mortem data of unfixed tissue can be acquired to explore the developing human brain.
{"title":"High-resolution diffusion imaging in the unfixed post-mortem infant brain at 7 T","authors":"Wenchuan Wu, Sebastian W Rieger, L. Baxter, Eleri Adams, Jesper L. R. Andersson, Maria M. Cobo, Foteini Andritsou, Matteo Bastiani, Ria Evans Fry, Robert Frost, Sean Fitzgibbon, S. Foxley, Darren Fowler, Chris Gallagher, A. Howard, J. Hajnal, Fiona Moultrie, V. Monk, David A Porter, Daniel Papp, Anthony Price, J. Sallet, Michael Sanders, Dominic Wilkinson, Rebeccah Slater, Karla L. Miller","doi":"10.1162/imag_a_00069","DOIUrl":"https://doi.org/10.1162/imag_a_00069","url":null,"abstract":"Abstract Diffusion MRI of the infant brain allows investigation of the organizational structure of maturing fibers during brain development. Post-mortem imaging has the potential to achieve high resolution by using long scan times, enabling precise assessment of small structures. Technical development for post-mortem diffusion MRI has primarily focused on scanning of fixed tissue, which is robust to effects like temperature drift that can cause unfixed tissue to degrade. The ability to scan unfixed tissue in the intact body would enable post-mortem studies without organ donation, but poses new technical challenges. This paper describes our approach to scan setup, protocol optimization, and tissue protection in the context of the Developing Human Connectome Project (dHCP) of neonates. A major consideration was the need to preserve the integrity of unfixed tissue during scanning in light of energy deposition at ultra-high magnetic field strength. We present results from one of the first two subjects recruited to the study, who died on postnatal day 46 at 29+6 weeks postmenstrual age, demonstrating high-quality diffusion MRI data. We find altered diffusion properties consistent with post-mortem changes reported previously. Preliminary voxel-wise and tractography analyses are presented with comparison to age-matched in vivo dHCP data. These results show that high-quality, high-resolution post-mortem data of unfixed tissue can be acquired to explore the developing human brain.","PeriodicalId":507939,"journal":{"name":"Imaging Neuroscience","volume":"92 12","pages":"1-20"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139538640","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 Numerous studies have demonstrated the beneficial effects of anodal prefrontal transcranial direct current stimulation (tDCS) on working memory. However, a large variability exists in the applied tDCS parameters and working memory outcome measures. Using a meta-modeling approach, we investigated the relationship between tDCS electric fields in the left prefrontal cortex and improvements in working memory performance. Using this approach, a vector of outcome measures is correlated with the tDCS-related electric fields across several studies. These performance-electric field correlations (PEC) are calculated for each spatial location of the grey matter. Extracting 354 data points from 67 studies, we compared the spatial maps of tDCS effects on I) working memory accuracy and speed (regardless of working memory type and time of assessment), II) verbal and visuospatial working memory (regardless of performance measurement and time of assessment), and III) performance during and after stimulation (regardless of performance measurement and working memory type). We found that accuracy improves when anodal tDCS is applied to inferior frontal regions (Brodmann area 47) while working memory speed benefits from stimulation to dorsolateral and anterior prefrontal areas (Brodmann areas 9/10). Furthermore, the beneficial effects of left prefrontal tDCS are exclusive to verbal working memory, with no improvements in visuospatial working memory. We also observed region-specific effects only for task performance during, but not after, stimulation. The results of this study elucidate the causal involvement of prefrontal regions in working memory and can help guide tDCS placement for therapeutic application in disorders that involve working memory deficits.
{"title":"Meta-modeling the effects of anodal left prefrontal transcranial direct current stimulation on working memory performance","authors":"M. Wischnewski, Taylor Berger, Alexander Opitz","doi":"10.1162/imag_a_00078","DOIUrl":"https://doi.org/10.1162/imag_a_00078","url":null,"abstract":"Abstract Numerous studies have demonstrated the beneficial effects of anodal prefrontal transcranial direct current stimulation (tDCS) on working memory. However, a large variability exists in the applied tDCS parameters and working memory outcome measures. Using a meta-modeling approach, we investigated the relationship between tDCS electric fields in the left prefrontal cortex and improvements in working memory performance. Using this approach, a vector of outcome measures is correlated with the tDCS-related electric fields across several studies. These performance-electric field correlations (PEC) are calculated for each spatial location of the grey matter. Extracting 354 data points from 67 studies, we compared the spatial maps of tDCS effects on I) working memory accuracy and speed (regardless of working memory type and time of assessment), II) verbal and visuospatial working memory (regardless of performance measurement and time of assessment), and III) performance during and after stimulation (regardless of performance measurement and working memory type). We found that accuracy improves when anodal tDCS is applied to inferior frontal regions (Brodmann area 47) while working memory speed benefits from stimulation to dorsolateral and anterior prefrontal areas (Brodmann areas 9/10). Furthermore, the beneficial effects of left prefrontal tDCS are exclusive to verbal working memory, with no improvements in visuospatial working memory. We also observed region-specific effects only for task performance during, but not after, stimulation. The results of this study elucidate the causal involvement of prefrontal regions in working memory and can help guide tDCS placement for therapeutic application in disorders that involve working memory deficits.","PeriodicalId":507939,"journal":{"name":"Imaging Neuroscience","volume":"131 1","pages":"1-14"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139638086","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}
J. Hamilton, K. Xu, N. Geremia, Vania F Prado, M. A. Prado, A. Brown, Corey Baron
Abstract Frequency-dependent diffusion MRI (dMRI) using oscillating gradient encoding and diffusional kurtosis imaging (DKI) techniques have been shown to provide additional insight into tissue microstructure compared to conventional dMRI. However, a technical challenge when combining these techniques is that the generation of the large b-values (≥2000 s/mm2) required for DKI is difficult when using oscillating gradient diffusion encoding. While efficient encoding schemes can enable larger b-values by maximizing multiple gradient channels simultaneously, they do not have sufficient directions to enable the estimation of directional kurtosis parameters. Accordingly, we investigate a DKI fitting algorithm that combines axisymmetric DKI fitting, a prior that enforces the same axis of symmetry for all oscillating gradient frequencies, and spatial regularization, which together enable robust DKI fitting for a 10-direction scheme that offers double the b-value compared to traditional encoding schemes. Using data from mice (oscillating frequencies of 0, 60, and 120 Hz) and humans (0 Hz only), we first show that axisymmetric DKI fitting provides comparable or even slightly improved image quality as compared to kurtosis tensor fitting, and improved DKI map quality when using an efficient encoding scheme with averaging as compared to a traditional scheme with more encoding directions. We also demonstrate that enforcing consistent axes of symmetries across frequencies improves fitting quality, and spatial regularization during fitting preserves spatial features better than using Gaussian filtering prior to fitting, which is an oft-reported pre-processing step for DKI. Thus, the use of an efficient 10-direction scheme combined with the proposed DKI fitting algorithm provides robust maps of frequency-dependent directional kurtosis which may offer increased sensitivity to cytoarchitectural changes that occur at various cellular spatial scales over the course of healthy aging, and due to pathological alterations.
摘要 采用振荡梯度编码和弥散峰度成像（DKI）技术的频率依赖性弥散磁共振成像（dMRI）已被证明比传统的 dMRI 更能深入了解组织的微观结构。然而，将这些技术结合起来的一个技术难题是，使用振荡梯度扩散编码时很难生成 DKI 所需的大 b 值（≥ 2000 s/mm2）。虽然高效的编码方案可以通过同时最大化多个梯度通道来获得更大的 b 值，但它们没有足够的方向性来估算方向性峰度参数。因此，我们研究了一种 DKI 拟合算法，该算法结合了轴对称 DKI 拟合、对所有振荡梯度频率强制执行同一对称轴的先验和空间正则化，共同实现了 10 个方向方案的稳健 DKI 拟合，与传统编码方案相比，该方案可提供双倍的 b 值。通过使用小鼠（振荡频率为 0、60 和 120 Hz）和人类（仅 0 Hz）的数据，我们首先证明了轴对称 DKI 拟合与峰度张量拟合相比，可提供相当甚至略有改善的图像质量，而且与具有更多编码方向的传统方案相比，使用具有平均化功能的高效编码方案可改善 DKI 地图质量。我们还证明，在不同频率之间强制使用一致的对称轴可以提高拟合质量，在拟合过程中进行空间正则化比在拟合前使用高斯滤波能更好地保留空间特征，而高斯滤波是经常被报道的 DKI 预处理步骤。因此，使用高效的 10 个方向方案与所提出的 DKI 拟合算法相结合，可提供稳健的频率相关方向峰度图，从而提高对细胞结构变化的敏感性，这些变化发生在健康衰老过程中的各种细胞空间尺度上，也可能是病理改变所致。
{"title":"Robust frequency-dependent diffusional kurtosis computation using an efficient direction scheme, axisymmetric modelling, and spatial regularization","authors":"J. Hamilton, K. Xu, N. Geremia, Vania F Prado, M. A. Prado, A. Brown, Corey Baron","doi":"10.1162/imag_a_00055","DOIUrl":"https://doi.org/10.1162/imag_a_00055","url":null,"abstract":"Abstract Frequency-dependent diffusion MRI (dMRI) using oscillating gradient encoding and diffusional kurtosis imaging (DKI) techniques have been shown to provide additional insight into tissue microstructure compared to conventional dMRI. However, a technical challenge when combining these techniques is that the generation of the large b-values (≥2000 s/mm2) required for DKI is difficult when using oscillating gradient diffusion encoding. While efficient encoding schemes can enable larger b-values by maximizing multiple gradient channels simultaneously, they do not have sufficient directions to enable the estimation of directional kurtosis parameters. Accordingly, we investigate a DKI fitting algorithm that combines axisymmetric DKI fitting, a prior that enforces the same axis of symmetry for all oscillating gradient frequencies, and spatial regularization, which together enable robust DKI fitting for a 10-direction scheme that offers double the b-value compared to traditional encoding schemes. Using data from mice (oscillating frequencies of 0, 60, and 120 Hz) and humans (0 Hz only), we first show that axisymmetric DKI fitting provides comparable or even slightly improved image quality as compared to kurtosis tensor fitting, and improved DKI map quality when using an efficient encoding scheme with averaging as compared to a traditional scheme with more encoding directions. We also demonstrate that enforcing consistent axes of symmetries across frequencies improves fitting quality, and spatial regularization during fitting preserves spatial features better than using Gaussian filtering prior to fitting, which is an oft-reported pre-processing step for DKI. Thus, the use of an efficient 10-direction scheme combined with the proposed DKI fitting algorithm provides robust maps of frequency-dependent directional kurtosis which may offer increased sensitivity to cytoarchitectural changes that occur at various cellular spatial scales over the course of healthy aging, and due to pathological alterations.","PeriodicalId":507939,"journal":{"name":"Imaging Neuroscience","volume":"119 9","pages":"1-22"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139395967","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}
Paul M. Briley, Clement Boutry, Lucy Webster, D. Veniero, Catherine Harvey-Seutcheu, Jeyoung Jung, Peter F Liddle, Richard Morriss
Abstract Repetitive transcranial magnetic stimulation (rTMS), delivered to left dorsolateral prefrontal cortex, is an FDA-approved, and NICE-recommended, neuromodulation therapy for major depressive disorder (MDD). However, there is considerable inter-individual variability in rate and extent of clinical response, leading to a focus on approaches for optimising its effectiveness. We present findings from a non-patient study evaluating an approach that combines an efficient type of rTMS—“intermittent theta burst stimulation” (iTBS)—with a second neuromodulation technique—“transcranial alternating current stimulation” (tACS). tACS is delivered in synchrony with the iTBS with the intent of optimising the brain state during stimulation. In four separate sessions, we delivered 3 minutes of iTBS+tACS, iTBS+sham, sham+tACS, or double sham. We measured changes from pre- to post-stimulation in brain theta (4–8 Hz) oscillatory activity using electroencephalography, and we measured emotional bias post-stimulation using a well-studied emotion identification task. Theta activity has previously shown relationships with response to rTMS, and emotional bias has been proposed as a marker of potential antidepressant efficacy. We found that frontal theta power was enhanced following the dual therapy, building up over the 15-minute post-stimulation period to exceed that following either stimulation technique alone or double sham. Emotional bias, measured 20 minutes post-stimulation, was also significantly more positive following dual therapy. These findings indicate that tACS-synchronised iTBS (tsiTBS) holds promise as an augmentation approach for rTMS, which awaits validation in multi-session patient studies.
{"title":"Intermittent theta burst stimulation with synchronised transcranial alternating current stimulation leads to enhanced frontal theta oscillations and a positive shift in emotional bias","authors":"Paul M. Briley, Clement Boutry, Lucy Webster, D. Veniero, Catherine Harvey-Seutcheu, Jeyoung Jung, Peter F Liddle, Richard Morriss","doi":"10.1162/imag_a_00073","DOIUrl":"https://doi.org/10.1162/imag_a_00073","url":null,"abstract":"Abstract Repetitive transcranial magnetic stimulation (rTMS), delivered to left dorsolateral prefrontal cortex, is an FDA-approved, and NICE-recommended, neuromodulation therapy for major depressive disorder (MDD). However, there is considerable inter-individual variability in rate and extent of clinical response, leading to a focus on approaches for optimising its effectiveness. We present findings from a non-patient study evaluating an approach that combines an efficient type of rTMS—“intermittent theta burst stimulation” (iTBS)—with a second neuromodulation technique—“transcranial alternating current stimulation” (tACS). tACS is delivered in synchrony with the iTBS with the intent of optimising the brain state during stimulation. In four separate sessions, we delivered 3 minutes of iTBS+tACS, iTBS+sham, sham+tACS, or double sham. We measured changes from pre- to post-stimulation in brain theta (4–8 Hz) oscillatory activity using electroencephalography, and we measured emotional bias post-stimulation using a well-studied emotion identification task. Theta activity has previously shown relationships with response to rTMS, and emotional bias has been proposed as a marker of potential antidepressant efficacy. We found that frontal theta power was enhanced following the dual therapy, building up over the 15-minute post-stimulation period to exceed that following either stimulation technique alone or double sham. Emotional bias, measured 20 minutes post-stimulation, was also significantly more positive following dual therapy. These findings indicate that tACS-synchronised iTBS (tsiTBS) holds promise as an augmentation approach for rTMS, which awaits validation in multi-session patient studies.","PeriodicalId":507939,"journal":{"name":"Imaging Neuroscience","volume":"21 8","pages":"1-14"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139633577","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}
A. Jaggi, E. L. Conole, Z. Raisi-Estabragh, P. Gkontra, C. Mccracken, Liliana Szabo, S. Neubauer, Steffen E. Petersen, Simon Cox, K. Lekadir
Abstract Elevated vascular disease risk associates with poorer cognitive function, but the mechanism for this link is poorly understood. A leading theory, the structural-functional model argues that vascular risk may drive adverse cardiac remodelling, which, in turn, leads to chronic cerebral hypoperfusion and subsequent brain structural damage. This model predicts that variation in heart and brain structure should associate with both greater vascular risk and lower cognitive function. This study tests that prediction in a large sample of the UK Biobank (N = 11,962). We assemble and summarise vascular risk factors, cardiac magnetic resonance radiomics, brain structural and diffusion MRI indices, and cognitive assessment. We also extract “heart-brain axes” capturing the covariation in heart and brain structure. Many heart and brain measures partially explain the vascular risk—cognitive function association, like left ventricular end-diastolic volume and grey matter volume. Notably, a heart-brain axis, capturing correlation between lower myocardial intensity, lower grey matter volume, and poorer thalamic white matter integrity, completely mediates the association, supporting the structural-functional model. Our findings also complicate this theory by finding that brain structural variation cannot completely explain the heart structure—cognitive function association. Our results broadly offer evidence for the structural functional hypothesis, identify imaging biomarkers for this association by considering covariation in heart and brain structure, and generate novel hypotheses about how cardiovascular risk may link to cognitive function.
{"title":"A structural heart-brain axis mediates the association between cardiovascular risk and cognitive function","authors":"A. Jaggi, E. L. Conole, Z. Raisi-Estabragh, P. Gkontra, C. Mccracken, Liliana Szabo, S. Neubauer, Steffen E. Petersen, Simon Cox, K. Lekadir","doi":"10.1162/imag_a_00063","DOIUrl":"https://doi.org/10.1162/imag_a_00063","url":null,"abstract":"Abstract Elevated vascular disease risk associates with poorer cognitive function, but the mechanism for this link is poorly understood. A leading theory, the structural-functional model argues that vascular risk may drive adverse cardiac remodelling, which, in turn, leads to chronic cerebral hypoperfusion and subsequent brain structural damage. This model predicts that variation in heart and brain structure should associate with both greater vascular risk and lower cognitive function. This study tests that prediction in a large sample of the UK Biobank (N = 11,962). We assemble and summarise vascular risk factors, cardiac magnetic resonance radiomics, brain structural and diffusion MRI indices, and cognitive assessment. We also extract “heart-brain axes” capturing the covariation in heart and brain structure. Many heart and brain measures partially explain the vascular risk—cognitive function association, like left ventricular end-diastolic volume and grey matter volume. Notably, a heart-brain axis, capturing correlation between lower myocardial intensity, lower grey matter volume, and poorer thalamic white matter integrity, completely mediates the association, supporting the structural-functional model. Our findings also complicate this theory by finding that brain structural variation cannot completely explain the heart structure—cognitive function association. Our results broadly offer evidence for the structural functional hypothesis, identify imaging biomarkers for this association by considering covariation in heart and brain structure, and generate novel hypotheses about how cardiovascular risk may link to cognitive function.","PeriodicalId":507939,"journal":{"name":"Imaging Neuroscience","volume":"70 7","pages":"1-18"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139454907","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}
Eddy Cavalli, V. Chanoine, Yufei Tan, Jean-Luc Anton, Bruno L. Giordano, Felipe Pegado, Johannes C. Ziegler
Abstract It has been argued that university students with dyslexia compensate for their reading deficits by a neural re-organization of the typical reading network, where the lexical representations of words are (re-)structured according to semantic rather than orthographic information. To investigate the re-organization of neural word representations more directly, we used multivariate representational similarity analyses (RSA) to find out which brain regions of the reading network respond to orthographic and semantic similarity between 544 pairs of words and whether there were any differences between typical and dyslexic readers. In accordance with the re-organization hypothesis, we predicted greater similarity (i.e., correlation of neural dissimilarity matrices) in adult dyslexic than in typical readers in regions associated with semantic processing and weaker similarity in regions associated with orthographic processing. Our results did not confirm these predictions. First, we found sensitivity to semantic similarity in all three subparts of the fusiform gyrus (FG1, FG2, and FG3) bilaterally. Adults with dyslexia showed less (rather than more) sensitivity to semantic similarity in the posterior subpart of fusiform gyrus (FG1) in the left hemisphere. Second, in typical readers, sensitivity to orthographic information was not only found in the left fusiform gyrus (FG1, FG2, and FG3) but also in left inferior frontal gyrus (IFG). Adults with dyslexia, in contrast, did not show sensitivity to orthographic information in left IFG. However, they showed increased sensitivity to orthographic information in the right hemisphere FG1. Together, the results show abnormal orthographic processing in left IFG and right FG1 and reduced semantic information in left FG1. While we found evidence for compensatory re-organization in adult dyslexia, the present results do not support the hypothesis according to which adults with dyslexia rely more heavily on semantic information. Instead, they revealed atypical hemispheric organization of the reading network that is not restricted to the typical left language hemisphere.
{"title":"Atypical hemispheric re-organization of the reading network in high-functioning adults with dyslexia: Evidence from representational similarity analysis","authors":"Eddy Cavalli, V. Chanoine, Yufei Tan, Jean-Luc Anton, Bruno L. Giordano, Felipe Pegado, Johannes C. Ziegler","doi":"10.1162/imag_a_00070","DOIUrl":"https://doi.org/10.1162/imag_a_00070","url":null,"abstract":"Abstract It has been argued that university students with dyslexia compensate for their reading deficits by a neural re-organization of the typical reading network, where the lexical representations of words are (re-)structured according to semantic rather than orthographic information. To investigate the re-organization of neural word representations more directly, we used multivariate representational similarity analyses (RSA) to find out which brain regions of the reading network respond to orthographic and semantic similarity between 544 pairs of words and whether there were any differences between typical and dyslexic readers. In accordance with the re-organization hypothesis, we predicted greater similarity (i.e., correlation of neural dissimilarity matrices) in adult dyslexic than in typical readers in regions associated with semantic processing and weaker similarity in regions associated with orthographic processing. Our results did not confirm these predictions. First, we found sensitivity to semantic similarity in all three subparts of the fusiform gyrus (FG1, FG2, and FG3) bilaterally. Adults with dyslexia showed less (rather than more) sensitivity to semantic similarity in the posterior subpart of fusiform gyrus (FG1) in the left hemisphere. Second, in typical readers, sensitivity to orthographic information was not only found in the left fusiform gyrus (FG1, FG2, and FG3) but also in left inferior frontal gyrus (IFG). Adults with dyslexia, in contrast, did not show sensitivity to orthographic information in left IFG. However, they showed increased sensitivity to orthographic information in the right hemisphere FG1. Together, the results show abnormal orthographic processing in left IFG and right FG1 and reduced semantic information in left FG1. While we found evidence for compensatory re-organization in adult dyslexia, the present results do not support the hypothesis according to which adults with dyslexia rely more heavily on semantic information. Instead, they revealed atypical hemispheric organization of the reading network that is not restricted to the typical left language hemisphere.","PeriodicalId":507939,"journal":{"name":"Imaging Neuroscience","volume":"25 14","pages":"1-23"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139540512","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}
R. Henriques, A. Ianuş, Lisa Novello, Jorge Jovicich, S. Jespersen, N. Shemesh
Abstract Marčenko-Pastur PCA (MPPCA) denoising is emerging as an effective means for noise suppression in MR imaging (MRI) acquisitions with redundant dimensions. However, MPPCA performance can be severely compromised by spatially correlated noise—an issue typically affecting most modern MRI acquisitions—almost to the point of returning the original images with little or no noise removal. In this study, we explore different threshold criteria for principal component analysis (PCA) component classification that enable efficient and robust denoising of MRI data even when noise exhibits high spatial correlations, especially in cases where data are acquired with Partial Fourier and when only magnitude data are available. We show that efficient denoising can be achieved by incorporating a-priori information about the noise variance into PCA denoising thresholding. Based on this, two denoising strategies developed here are: 1) General PCA (GPCA) denoising that uses a-priori noise variance estimates without assuming specific noise distributions; and 2) Threshold PCA (TPCA) denoising which removes noise components with a threshold computed from a-priori estimated noise variance to determine the upper bound of the Marčenko-Pastur (MP) distribution. These strategies were tested in simulations with known ground truth and applied for denoising diffusion MRI data acquired using pre-clinical (16.4T) and clinical (3T) MRI scanners. In synthetic phantoms, MPPCA denoising failed to denoise spatially correlated data, while GPCA and TPCA better classified components as dominated by signal/noise. In cases where the noise variance was not accurately estimated (as can be the case in many practical scenarios), TPCA still provides excellent denoising performance. Our experiments in pre-clinical diffusion data with highly corrupted by spatial correlated noise revealed that both GPCA and TPCA robustly denoised the data while MPPCA denoising failed. In in vivo diffusion MRI data acquired on a clinical scanner in healthy subjects, MPPCA weakly removed noised, while TPCA was found to have the best performance, likely due to misestimations of the noise variance. Thus, our work shows that these novel denoising approaches can strongly benefit future pre-clinical and clinical MRI applications.
{"title":"Efficient PCA denoising of spatially correlated redundant MRI data","authors":"R. Henriques, A. Ianuş, Lisa Novello, Jorge Jovicich, S. Jespersen, N. Shemesh","doi":"10.1162/imag_a_00049","DOIUrl":"https://doi.org/10.1162/imag_a_00049","url":null,"abstract":"Abstract Marčenko-Pastur PCA (MPPCA) denoising is emerging as an effective means for noise suppression in MR imaging (MRI) acquisitions with redundant dimensions. However, MPPCA performance can be severely compromised by spatially correlated noise—an issue typically affecting most modern MRI acquisitions—almost to the point of returning the original images with little or no noise removal. In this study, we explore different threshold criteria for principal component analysis (PCA) component classification that enable efficient and robust denoising of MRI data even when noise exhibits high spatial correlations, especially in cases where data are acquired with Partial Fourier and when only magnitude data are available. We show that efficient denoising can be achieved by incorporating a-priori information about the noise variance into PCA denoising thresholding. Based on this, two denoising strategies developed here are: 1) General PCA (GPCA) denoising that uses a-priori noise variance estimates without assuming specific noise distributions; and 2) Threshold PCA (TPCA) denoising which removes noise components with a threshold computed from a-priori estimated noise variance to determine the upper bound of the Marčenko-Pastur (MP) distribution. These strategies were tested in simulations with known ground truth and applied for denoising diffusion MRI data acquired using pre-clinical (16.4T) and clinical (3T) MRI scanners. In synthetic phantoms, MPPCA denoising failed to denoise spatially correlated data, while GPCA and TPCA better classified components as dominated by signal/noise. In cases where the noise variance was not accurately estimated (as can be the case in many practical scenarios), TPCA still provides excellent denoising performance. Our experiments in pre-clinical diffusion data with highly corrupted by spatial correlated noise revealed that both GPCA and TPCA robustly denoised the data while MPPCA denoising failed. In in vivo diffusion MRI data acquired on a clinical scanner in healthy subjects, MPPCA weakly removed noised, while TPCA was found to have the best performance, likely due to misestimations of the noise variance. Thus, our work shows that these novel denoising approaches can strongly benefit future pre-clinical and clinical MRI applications.","PeriodicalId":507939,"journal":{"name":"Imaging Neuroscience","volume":"27 10","pages":"1-26"},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139188016","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}
Nicholas E. Souter, L. Lannelongue, Gabrielle Samuel, Chris Racey, Lincoln J. Colling, Nikhil Bhagwat, Raghavendra Selvan, Charlotte L. Rae
Abstract Given that scientific practices contribute to the climate crisis, scientists should reflect on the planetary impact of their work. Research computing can have a substantial carbon footprint in cases where researchers employ computationally expensive processes with large amounts of data. Analysis of human neuroimaging data, such as Magnetic Resonance Imaging brain scans, is one such case. Here, we consider ten ways in which those who conduct human neuroimaging research can reduce the carbon footprint of their research computing, by making adjustments to the ways in which studies are planned, executed, and analysed; as well as where and how data are stored.
{"title":"Ten recommendations for reducing the carbon footprint of research computing in human neuroimaging","authors":"Nicholas E. Souter, L. Lannelongue, Gabrielle Samuel, Chris Racey, Lincoln J. Colling, Nikhil Bhagwat, Raghavendra Selvan, Charlotte L. Rae","doi":"10.1162/imag_a_00043","DOIUrl":"https://doi.org/10.1162/imag_a_00043","url":null,"abstract":"Abstract Given that scientific practices contribute to the climate crisis, scientists should reflect on the planetary impact of their work. Research computing can have a substantial carbon footprint in cases where researchers employ computationally expensive processes with large amounts of data. Analysis of human neuroimaging data, such as Magnetic Resonance Imaging brain scans, is one such case. Here, we consider ten ways in which those who conduct human neuroimaging research can reduce the carbon footprint of their research computing, by making adjustments to the ways in which studies are planned, executed, and analysed; as well as where and how data are stored.","PeriodicalId":507939,"journal":{"name":"Imaging Neuroscience","volume":"12 1","pages":"1-15"},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139189285","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 The interpretation of social interactions between people is important in many daily situations. The coordination of the relative body movements between them may provide visual cues that observers use without attention to discriminate such social interactions from the actions of people acting independently of each other. Previous studies highlighted brain regions involved in the visual processing of interacting versus independently acting people, including posterior superior temporal sulcus, and areas of lateral occipitotemporal and parietal cortices. Unlike these previous studies, we focused on the incidental visual processing of social interactions; that is, the processing of the body movements outside the observers’ focus of attention. In the current study, we used functional imaging to measure brain activation while participants were presented with point-light dyads portraying communicative interactions or individual actions. However, their task was to discriminate the brightness of two crosses also on the screen. To investigate brain regions that may process the spatial and temporal relationships between the point-light displays, we either reversed the facing direction of one agent or spatially scrambled the local motion of the points. Incidental processing of communicative interactions elicited activation in right anterior STS only when the two agents were facing each other. Controlling for differences in local motion by subtracting brain activation to scrambled versions of the point-light displays revealed significant activation in parietal cortex for communicative interactions, as well as left amygdala and brain stem/cerebellum. Our results complement previous studies and suggest that additional brain regions may be recruited to incidentally process the spatial and temporal contingencies that distinguish people acting together from people acting individually.
{"title":"Incidental visual processing of spatiotemporal cues in communicative interactions: An fMRI investigation","authors":"Anthony P. Atkinson, Q. Vuong","doi":"10.1162/imag_a_00048","DOIUrl":"https://doi.org/10.1162/imag_a_00048","url":null,"abstract":"Abstract The interpretation of social interactions between people is important in many daily situations. The coordination of the relative body movements between them may provide visual cues that observers use without attention to discriminate such social interactions from the actions of people acting independently of each other. Previous studies highlighted brain regions involved in the visual processing of interacting versus independently acting people, including posterior superior temporal sulcus, and areas of lateral occipitotemporal and parietal cortices. Unlike these previous studies, we focused on the incidental visual processing of social interactions; that is, the processing of the body movements outside the observers’ focus of attention. In the current study, we used functional imaging to measure brain activation while participants were presented with point-light dyads portraying communicative interactions or individual actions. However, their task was to discriminate the brightness of two crosses also on the screen. To investigate brain regions that may process the spatial and temporal relationships between the point-light displays, we either reversed the facing direction of one agent or spatially scrambled the local motion of the points. Incidental processing of communicative interactions elicited activation in right anterior STS only when the two agents were facing each other. Controlling for differences in local motion by subtracting brain activation to scrambled versions of the point-light displays revealed significant activation in parietal cortex for communicative interactions, as well as left amygdala and brain stem/cerebellum. Our results complement previous studies and suggest that additional brain regions may be recruited to incidentally process the spatial and temporal contingencies that distinguish people acting together from people acting individually.","PeriodicalId":507939,"journal":{"name":"Imaging Neuroscience","volume":"6 2","pages":"1-25"},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139194119","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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