Reliability and statistical power analysis of cortical and subcortical FreeSurfer metrics in a large sample of healthy elderly

Subcortical white matter differences according to presence of disorders of consciousness in hypoxic-ischemic brain injury: a tract-based spatial statistics study

We investigated differences in subcortical white matter according to the presence disorders of consciousness (DOC) in patients with hypoxic-ischemic brain injury (HI-BI), using tract-based spatial statistics (TBSS). Thirty-two consecutive patients with HI-BI were recruited. The patients were assigned in group A [preserved consciousness (Glasgow Coma Scale: 15 and Coma Recovery Scale-revised (CRS-R): 23, 9 patients)] or group B [DOC present (Glasgow Coma Scale <15 and CRS-R < 23, 20 patients)]. Voxel-wise statistical analysis of fractional anisotropy data was performed by using TBSS as implemented in the FMRIB Software Library. We calculated mean fractional anisotropy values across the white matter skeleton and within 48 regions of interest (ROIs) based on intersections between the skeleton and the probabilistic Johns Hopkins University white matter atlases. Among the 48 ROIs examined, the fractional anisotropy values of two ROIs (the left superior corona radiata, and left tapetum) were significantly lower in group B than in group A ( P  < 0.05). No significant differences were observed, however, in the other 46 ROIs ( P  > 0.05). Our results suggest that abnormalities of the superior corona radiata and tapetum may be critical for DOC presence in patients with HI-BI.

A multidimensional characterization of the neurocognitive architecture underlying age-related temporal speech processing

Healthy aging is often associated with speech comprehension difficulties in everyday life situations despite a pure-tone hearing threshold in the normative range. Drawing on this background, we used a multidimensional approach to assess the functional and structural neural correlates underlying age-related temporal speech processing while controlling for pure-tone hearing acuity. Accordingly, we combined structural magnetic resonance imaging and electroencephalography, and collected behavioral data while younger and older adults completed a phonetic categorization and discrimination task with consonant-vowel syllables varying along a voice-onset time continuum. The behavioral results confirmed age-related temporal speech processing singularities which were reflected in a shift of the boundary of the psychometric categorization function, with older adults perceiving more syllable characterized by a short voice-onset time as /ta/ compared to younger adults. Furthermore, despite the absence of any between-group differences in phonetic discrimination abilities, older adults demonstrated longer N100/P200 latencies as well as increased P200 amplitudes while processing the consonant-vowel syllables varying in voice-onset time. Finally, older adults also exhibited a divergent anatomical gray matter infrastructure in bilateral auditory-related and frontal brain regions, as manifested in reduced cortical thickness and surface area. Notably, in the younger adults but not in the older adult cohort, cortical surface area in these two gross anatomical clusters correlated with the categorization of consonant-vowel syllables characterized by a short voice-onset time, suggesting the existence of a critical gray matter threshold that is crucial for consistent mapping of phonetic categories varying along the temporal dimension. Taken together, our results highlight the multifaceted dimensions of age-related temporal speech processing characteristics, and pave the way toward a better understanding of the relationships between hearing, speech and the brain in older age.

Impact of social isolation on grey matter structure and cognitive functions: A population-based longitudinal neuroimaging study

Background

Social isolation has been suggested to increase the risk to develop cognitive decline. However, our knowledge on causality and neurobiological underpinnings is still limited.

Methods

In this preregistered analysis, we tested the impact of social isolation on central features of brain and cognitive ageing using a longitudinal population-based magnetic resonance imaging (MRI) study. We assayed 1992 cognitively healthy participants (50-82years old, 921women) at baseline and 1409 participants after~6y follow-up.

Results

We found baseline social isolation and change in social isolation to be associated with smaller volumes of the hippocampus and clusters of reduced cortical thickness. Furthermore, poorer cognitive functions (memory, processing speed, executive functions) were linked to greater social isolation, too.

Conclusions

Combining advanced neuroimaging outcomes with prevalent lifestyle characteristics from a well-characterized population of middle- to older aged adults, we provide evidence that social isolation contributes to human brain atrophy and cognitive decline. Within-subject effects of social isolation were similar to between-subject effects, indicating an opportunity to reduce dementia risk by promoting social networks.

Funding

European Union, European Regional Development Fund, Free State of Saxony, LIFE-Leipzig Research Center for Civilization Diseases, University of Leipzig, German Research Foundation.

Traumatic brain injury alters the relationship between brain structure and episodic memory

BACKGROUND

Focal and diffuse pathology resulting from traumatic brain injury (TBI) often disrupts brain circuitry that is critical for episodic memory, including medial temporal lobe and prefrontal regions. Prior studies have focused on unitary accounts of temporal lobe function, associating verbally learned material and brain morphology. Medial temporal lobe structures, however, are domain-sensitive, preferentially supporting different visual stimuli. There has been little consideration of whether TBI preferentially disrupts the type of visually learned material and its association with cortical morphology following injury. Here, we investigated whether (1) episodic memory deficits differ according to the stimulus type, and (2) the pattern in memory performance can be linked to changes in cortical thickness.

METHODS

Forty-three individuals with moderate-severe TBI and 38 demographically similar healthy controls completed a recognition task in which memory was assessed for three categories of stimuli: faces, scenes, and animals. The association between episodic memory accuracy on this task and cortical thickness was subsequently examined within and between groups.

RESULTS

Our behavioral results support the notion of category-specific impairments: the TBI group had significantly impaired accuracy for memory for faces and scenes, but not animals. Moreover, the association between cortical thickness and behavioral performance was only significant for faces between groups.

CONCLUSION

Taken together, these behavioral and structural findings provide support for an emergent memory account, and highlight that cortical thickness differentially affects episodic memory for specific categories of stimuli.

Quantifying numerical and spatial reliability of hippocampal and amygdala subdivisions in FreeSurfer

On-going, large-scale neuroimaging initiatives can aid in uncovering neurobiological causes and correlates of poor mental health, disease pathology, and many other important conditions. As projects grow in scale with hundreds, even thousands, of individual participants and scans collected, quantification of brain structures by automated algorithms is becoming the only truly tractable approach. Here, we assessed the spatial and numerical reliability for newly deployed automated segmentation of hippocampal subfields and amygdala nuclei in FreeSurfer 7. In a sample of participants with repeated structural imaging scans (N = 928), we found numerical reliability (as assessed by intraclass correlations, ICCs) was reasonable. Approximately 95% of hippocampal subfields had "excellent" numerical reliability (ICCs ≥ 0.90), while only 67% of amygdala subnuclei met this same threshold. In terms of spatial reliability, 58% of hippocampal subfields and 44% of amygdala subnuclei had Dice coefficients ≥ 0.70. Notably, multiple regions had poor numerical and/or spatial reliability. We also examined correlations between spatial reliability and person-level factors (e.g., participant age; T1 image quality). Both sex and image scan quality were related to variations in spatial reliability metrics. Examined collectively, our work suggests caution should be exercised for a few hippocampal subfields and amygdala nuclei with more variable reliability.

Plasma TDP-43 Reflects Cortical Neurodegeneration and Correlates with Neuropsychiatric Symptoms in Huntington's Disease

PURPOSE

Huntington's disease (HD) is a monogenic neurodegenerative disease with no effective treatment currently available. The pathological hallmark of HD is the aggregation of mutant huntingtin in the medium spiny neurons of the striatum, leading to severe subcortical atrophy. Cortical degeneration also occurs in HD from its very early stages, although its biological origin is poorly understood. Among the possible pathological mechanisms that could promote cortical damage in HD, the in vivo study of TDP-43 pathology remains to be explored, which was the main objective of this work.

METHODS

We investigated the clinical and structural brain correlates of plasma TDP-43 levels in a sample of 36 HD patients. Neuroimaging alterations were assessed both at the macrostructural (cortical thickness) and microstructural (intracortical diffusivity) levels. Importantly, we controlled for mutant huntingtin and tau biomarkers in order to assess the independent role of TDP-43 in HD neurodegeneration.

RESULTS

Plasma TDP-43 levels in HD specifically correlated with the presence and severity of apathy (p = 0.003). The TDP-43 levels also reflected cortical thinning and microstructural degeneration, especially in frontal and anterior-temporal regions (p < 0.05 corrected). These TDP-43-related brain alterations correlated, in turn, with the severity of cognitive, motor and behavioral symptoms.

CONCLUSION

Our results suggest that the presence of TDP-43 pathology in HD has an independent contribution to the severity of neuropsychiatric symptoms and frontotemporal degeneration. These findings point out the importance of TDP-43 as an additional pathological process to be taken into consideration in this devastating disorder.

The thickness of the ventral medial prefrontal cortex predicts the prior-entry effect for allocentric representation in near space

Neuropsychological studies have demonstrated that the preferential processing of near-space and egocentric representation is associated with the self-prioritization effect (SPE). However, relatively little is known concerning whether the SPE is superior to the representation of egocentric frames or near-space processing in the interaction between spatial reference frames and spatial domains. The present study adopted the variant of the shape-label matching task (i.e., color-label) to establish an SPE, combined with a spatial reference frame judgment task, to examine how the SPE leads to preferential processing of near-space or egocentric representations. Surface-based morphometry analysis was also adopted to extract the cortical thickness of the ventral medial prefrontal cortex (vmPFC) to examine whether it could predict differences in the SPE at the behavioral level. The results showed a significant SPE, manifested as the response of self-associated color being faster than that of stranger-associated color. Additionally, the SPE showed a preference for near-space processing, followed by egocentric representation. More importantly, the thickness of the vmPFC could predict the difference in the SPE on reference frames, particularly in the left frontal pole cortex and bilateral rostral anterior cingulate cortex. These findings indicated that the SPE showed a prior entry effect for information at the spatial level relative to the reference frame level, providing evidence to support the structural significance of the self-processing region.

Genetic variants associated with longitudinal changes in brain structure across the lifespan

Human brain structure changes throughout the lifespan. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental and neurodegenerative diseases. In this study, we identified common genetic variants that affect rates of brain growth or atrophy in what is, to our knowledge, the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal magnetic resonance imaging data from 15,640 individuals were used to compute rates of change for 15 brain structures. The most robustly identified genes GPR139, DACH1 and APOE are associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and aging.

Lower glutamate and GABA levels in auditory cortex of tinnitus patients: a 2D-JPRESS MR spectroscopy study

We performed magnetic resonance spectroscopy (MRS) on healthy individuals with tinnitus and no hearing loss (n = 16) vs. a matched control group (n = 17) to further elucidate the role of excitatory and inhibitory neurotransmitters in tinnitus. Two-dimensional J-resolved spectroscopy (2D-JPRESS) was applied to disentangle Glutamate (Glu) from Glutamine and to estimate GABA levels in two bilateral voxels in the primary auditory cortex. Results indicated a lower Glu concentration (large effect) in right auditory cortex and lower GABA concentration (medium effect) in the left auditory cortex of the tinnitus group. Within the tinnitus group, Glu levels positively correlated with tinnitus loudness measures. While the GABA difference between groups is in line with former findings and theories about a dysfunctional auditory inhibition system in tinnitus, the novel finding of reduced Glu levels came as a surprise and is discussed in the context of a putative framework of inhibitory mechanisms related to Glu throughout the auditory pathway. Longitudinal or interventional studies could shed more light on interactions and causality of Glu and GABA in tinnitus neurochemistry.

Amygdala and subregion volumes are associated with photoperiod and seasonal depressive symptoms: A cross-sectional study in the UK Biobank cohort

Although seasonal changes in amygdala volume have been demonstrated in animals, seasonal differences in human amygdala subregion volumes have yet to be investigated. Amygdala volume has also been linked to depressed mood. Therefore, we hypothesised that differences in photoperiod would predict differences in amygdala or subregion volumes and that this association would be linked to depressed mood. 10,033 participants ranging in age from 45 to 79 years were scanned by MRI in a single location. Amygdala subregion volumes were obtained using automated processing and segmentation algorithms. A mediation analysis tested whether amygdala volume mediated the relationship between photoperiod and mood. Photoperiod was positively associated with total amygdala volume (p < .001). Multivariate (GLM) analyses revealed significant effects of photoperiod across all amygdala subregion volumes for both hemispheres (p < .001). Post hoc univariate regression analyses revealed significant associations of photoperiod with each amygdala subregion volume (p < .001). PLS showed the highest loadings of amygdala subregions in lateral nucleus, ABN, basal nucleus, CAT, PLN, AAA, central nucleus, cortical nucleus and medial nucleus for left hemisphere and ABN, lateral nucleus, CAT, PLN, cortical nucleus, AAA, central nucleus and medial nucleus for right hemisphere. There were no significant associations between photoperiod and mood nor between mood scores and amygdala volumes, and due to the lack of these associations, the mediation hypothesis was not supported. This study is the first to demonstrate an association between photoperiod and amygdala volume. These findings add to the evidence supporting the role of photoperiod on brain structural plasticity.

Reliability of structural MRI measurements: The effects of scan session, head tilt, inter-scan interval, acquisition sequence, FreeSurfer version and processing stream

BACKGROUND

Large-scale longitudinal and multi-centre studies are used to explore neuroimaging markers of normal ageing, and neurodegenerative and mental health disorders. Longitudinal changes in brain structure are typically small, therefore the reliability of automated techniques is crucial. Determining the effects of different factors on reliability allows investigators to control those adversely affecting reliability, calculate statistical power, or even avoid particular brain measures with low reliability. This study examined the impact of several image acquisition and processing factors and documented the test-retest reliability of structural MRI measurements.

METHODS

In Phase I, 20 healthy adults (11 females; aged 20-30 years) were scanned on two occasions three weeks apart on the same scanner using the ADNI-3 protocol. On each occasion, individuals were scanned twice (repetition), after re-entering the scanner (reposition) and after tilting their head forward. At one year follow-up, nine returning individuals and 11 new volunteers were recruited for Phase II (11 females; aged 22-31 years). Scans were acquired on two different scanners using the ADNI-2 and ADNI-3 protocols. Structural images were processed using FreeSurfer (v5.3.0, 6.0.0 and 7.1.0) to provide subcortical and cortical volume, cortical surface area and thickness measurements. Intra-class correlation coefficients (ICC) were calculated to estimate test-retest reliability. We examined the effect of repetition, reposition, head tilt, time between scans, MRI sequence and scanner on reliability of structural brain measurements. Mean percentage differences were also calculated in supplementary analyses.

RESULTS

Using the FreeSurfer v7.1.0 longitudinal pipeline, we observed high reliability for subcortical and cortical volumes, and cortical surface areas at repetition, reposition, three weeks and one year (mean ICCs>0.97). Cortical thickness reliability was lower (mean ICCs>0.82). Head tilt had the greatest adverse impact on ICC estimates, for example reducing mean right cortical thickness to ICC=0.74. In contrast, changes in ADNI sequence or MRI scanner had a minimal effect. We observed an increase in reliability for updated FreeSurfer versions, with the longitudinal pipeline consistently having a higher reliability than the cross-sectional pipeline.

DISCUSSION

Longitudinal studies should monitor or control head tilt to maximise reliability. We provided the ICC estimates and mean percentage differences for all FreeSurfer brain regions, which may inform power analyses for clinical studies and have implications for the design of future longitudinal studies.

Prediction of Cognitive Progression in Individuals with Mild Cognitive Impairment Using Radiomics as an Improvement of the ATN System: A Five-Year Follow-Up Study

Objective

To improve the N biomarker in the amyloid/tau/neurodegeneration system by radiomics and study its value for predicting cognitive progression in individuals with mild cognitive impairment (MCI).

Materials and Methods

A group of 147 healthy controls (HCs) (72 male; mean age ± standard deviation, 73.7 ± 6.3 years), 197 patients with MCI (114 male; 72.2 ± 7.1 years), and 128 patients with Alzheimer’s disease (AD) (74 male; 73.7 ± 8.4 years) were included. Optimal A, T, and N biomarkers for discriminating HC and AD were selected using receiver operating characteristic (ROC) curve analysis. A radiomics model containing comprehensive information of the whole cerebral cortex and deep nuclei was established to create a new N biomarker. Cerebrospinal fluid (CSF) biomarkers were evaluated to determine the optimal A or T biomarkers. All MCI patients were followed up until AD conversion or for at least 60 months. The predictive value of A, T, and the radiomics-based N biomarker for cognitive progression of MCI to AD were analyzed using Kaplan-Meier estimates and the log-rank test.

Results

The radiomics-based N biomarker showed an ROC curve area of 0.998 for discriminating between AD and HC. CSF Aβ42 and p-tau proteins were identified as the optimal A and T biomarkers, respectively. For MCI patients on the Alzheimer’s continuum, isolated A+ was an indicator of cognitive stability, while abnormalities of T and N, separately or simultaneously, indicated a high risk of progression. For MCI patients with suspected non-Alzheimer’s disease pathophysiology, isolated T+ indicated cognitive stability, while the appearance of the radiomics-based N+ indicated a high risk of progression to AD.

Conclusion

We proposed a new radiomics-based improved N biomarker that could help identify patients with MCI who are at a higher risk for cognitive progression. In addition, we clarified the value of a single A/T/N biomarker for predicting the cognitive progression of MCI.

Advantages of Using Both Voxel- and Surface-based Morphometry in Cortical Morphology Analysis: A Review of Various Applications

Surface-based morphometry (SBM) is extremely useful for estimating the indices of cortical morphology, such as volume, thickness, area, and gyrification, whereas voxel-based morphometry (VBM) is a typical method of gray matter (GM) volumetry that includes cortex measurement. In cases where SBM is used to estimate cortical morphology, it remains controversial as to whether VBM should be used in addition to estimate GM volume. Therefore, this review has two main goals. First, we summarize the differences between the two methods regarding preprocessing, statistical analysis, and reliability. Second, we review studies that estimate cortical morphological changes using VBM and/or SBM and discuss whether using VBM in conjunction with SBM produces additional values. We found cases in which detection of morphological change in either VBM or SBM was superior, and others that showed equivalent performance between the two methods. Therefore, we concluded that using VBM and SBM together can help researchers and clinicians obtain a better understanding of normal neurobiological processes of the brain. Moreover, the use of both methods may improve the accuracy of the detection of morphological changes when comparing the data of patients and controls.

In addition, we introduce two other recent methods as future directions for estimating cortical morphological changes: a multi-modal parcellation method using structural and functional images, and a synthetic segmentation method using multi-contrast images (such as T1- and proton density-weighted images).

Structural Brain Network Reproducibility: Influence of Different Diffusion Acquisition and Tractography Reconstruction Schemes on Graph Metrics

Background: Graph metrics of structural brain networks demonstrate to be a powerful tool for investigating brain topology at a large scale. However, the variability of the results related to applying different magnetic resonance acquisition schemes and tractography reconstruction techniques is not fully characterized. Materials and Methods: The present work aims to evaluate the influence of different combinations of diffusion acquisition schemes (single and multishell), diffusion models (tensor and spherical deconvolution), and tractography reconstruction approaches (deterministic and probabilistic) on the reproducibility of graph metrics derived from structural connectome on test/retest (TRT) data released by the Human Connectome Project. From each implemented experimental setup, both global and local graph metrics were evaluated and their reproducibility was estimated by the intraclass correlation coefficient (ICC). Moreover, the percentage relative standard deviation (pRSD) from the ICC values of local graph metrics was calculated to quantify how much the reproducibility varied across nodes within each experimental setup. Results: The presented results show that different combinations of diffusion acquisition schemes, diffusion models, and tractography algorithms can strongly affect the reproducibility of global and local graph metrics. The combination of constrained spherical deconvolution (CSD) and deterministic tractography gave generally high reproducibility (ICCs >0.75) and lowest pRSD for the considered graph metrics, meanwhile probabilistic CSD with a high b-value returned the highest reproducibility. Notably, the introduction of streamline selection filters on CSD can substantially affect the reproducibility. Discussion: This work demonstrates that the TRT reproducibility of graph metrics is generally high but can vary substantially with different combinations of acquisition and reconstruction schemes. Impact statement This work demonstrates the influence of different diffusion acquisition schemes, diffusion models, and tractography reconstruction approaches on the reproducibility of graph metrics derived from structural connectome. The presented findings impact on the choice of both acquisition protocol and processing pipeline for topological analyses to produce reproducible measurements for brain network studies.

Multimodal MRI cerebral correlates of verbal fluency switching and its impairment in women with depression

BACKGROUND

The search of biomarkers in the field of depression requires easy implementable tests that are biologically rooted. Qualitative analysis of verbal fluency tests (VFT) are good candidates, but its cerebral correlates are unknown.

METHODS

We collected qualitative semantic and phonemic VFT scores along with grey and white matter anatomical MRI of depressed (n = 26) and healthy controls (HC, n = 25) women. Qualitative VFT variables are the "clustering score" (i.e. the ability to produce words within subcategories) and the "switching score" (i.e. the ability to switch between clusters). The clustering and switching scores were automatically calculated using a data-driven approach. Brain measures were cortical thickness (CT) and fractional anisotropy (FA). We tested for associations between CT, FA and qualitative VFT variables within each group.

RESULTS

Patients had reduced switching VFT scores compared to HC. Thicker cortex was associated with better switching score in semantic VFT bilaterally in the frontal (superior, rostral middle and inferior gyri), parietal (inferior parietal lobule including the supramarginal gyri), temporal (transverse and fusiform gyri) and occipital (lingual gyri) lobes in the depressed group. Positive association between FA and the switching score in semantic VFT was retrieved in depressed patients within the corpus callosum, right inferior fronto-occipital fasciculus, right superior longitudinal fasciculus extending to the anterior thalamic radiation (all p < 0.05, corrected).

CONCLUSION

Together, these results suggest that automatic qualitative VFT scores are associated with brain anatomy and reinforce its potential use as a surrogate for depression cerebral bases.

The effect of a post-scan processing denoising system on image quality and morphometric analysis

PURPOSE

MR image quality and subsequent brain morphometric analysis are inevitably affected by noise. The purpose of this study was to evaluate the effectiveness of an artificial intelligence (AI)-based post-scan processing denoising system, intelligent Quick Magnetic Resonance (iQMR), on MR image quality and brain morphometric analysis.

METHODS

We used 1.5T MP-RAGE MR images acquired from the Alzheimer's Disease Neuroimaging Initiative 1 database. The images of 21 subjects were used for cross-sectional analysis and 15 for longitudinal analysis. In the longitudinal analysis, two timepoints over a 2-year interval were used. Each subject was scanned twice at each timepoint. MR images processed with and without the denoising system were compared both visually and objectively using FreeSurfer cortical thickness analysis.

RESULTS

The denoising system reduced the noise with good white-gray matter contrast (noise: p < 0.001; contrast: p = 0.49). The mean intraclass correlation coefficients (ICCs) of cortical thickness were slightly better in the images processed with the denoising system (0.739/0.859/0.883; Gaussian smoothing kernel of full width at half maximum = 0/10/20) compared with the unprocessed images (0.718/0.854/0.880). In the longitudinal analysis, the mean ICCs of symmetrized percent change improved in images processed with the denoising system (0.202/0.349/0.431) compared with the unprocessed images (0.167/0.325/0.404). In addition, the detectability of significant cortical thickness atrophy improved with denoising.

CONCLUSION

We confirm that the AI-based denoising system could effectively reduce the noise while retaining the contrast. We also confirm the improvement of the reliability and detectability of brain morphometric analysis with the denoising system.

Estimating the effect of a scanner upgrade on measures of grey matter structure for longitudinal designs

Longitudinal imaging studies are crucial for advancing the understanding of brain development over the lifespan. Thus, more and more studies acquire imaging data at multiple time points or with long follow-up intervals. In these studies changes to magnetic resonance imaging (MRI) scanners often become inevitable which may decrease the reliability of the MRI assessments and introduce biases. We therefore investigated the difference between MRI scanners with subsequent versions (3 Tesla Siemens Verio vs. Skyra) on the cortical and subcortical measures of grey matter in 116 healthy, young adults using the well-established longitudinal FreeSurfer stream for T1-weighted brain images. We found excellent between-scanner reliability for cortical and subcortical measures of grey matter structure (intra-class correlation coefficient > 0.8). Yet, paired t-tests revealed statistically significant differences in at least 67% of the regions, with percent differences around 2 to 4%, depending on the outcome measure. Offline correction for gradient distortions only slightly reduced these biases. Further, T1-imaging based quality measures reflecting gray-white matter contrast systematically differed between scanners. We conclude that scanner upgrades during a longitudinal study introduce bias in measures of cortical and subcortical grey matter structure. Therefore, before upgrading a MRI scanner during an ongoing study, researchers should prepare to implement an appropriate correction method for these effects.

Changes in the connection network of whole-brain fiber tracts in patients with Alzheimer's disease have a tendency of lateralization

Alzheimer's disease is a common progressive neurodegenerative disorder in the elderly. Diffusion tensor imaging (DTI) has been widely used to explore structural integrity and to describe white matter degeneration in Alzheimer's disease. Previous research has indicated that the change of connections between white matter fiber tracts is very important for investigating the brain function of Alzheimer's disease patients. However, whether white matter features can be used as potential biomarkers for predicting Alzheimer's disease tendency requires more in-depth research. In this study, we investigated the relationship between the damage in white matter tracts and the decline of cognitive function in Alzheimer's disease. DTI data were collected from 38 Alzheimer's disease patients and 30 normal controls. Fiber assignment by continuous tracking approach was used to establish connections between different brain regions of the whole brain, network-based statistical analysis and support vector machine classification analysis were used to explore the connection of whole-brain fiber bundles between the two groups. Most importantly, our results showed that the connections between brain regions of Alzheimer's disease patients were damaged, and the damage were mainly located in the right hemisphere, there was a certain degree of lateralization effect. Using whole-brain fiber bundle connection network as a feature for classification, we found it helped to improve the classification accuracy in Alzheimer's disease patients, which is useful for early clinical diagnosis of Alzheimer's disease. These findings further suggested that we can use the whole-brain fiber bundle connection network of Alzheimer's disease patients as a potential diagnostic indicator of Alzheimer's disease in the future.

Antioxidative Defense Genes and Brain Structure in Youth Bipolar Disorder

BACKGROUND

Oxidative stress is implicated in the neuropathology of bipolar disorder (BD). We investigated the association of single-nucleotide polymorphisms (SNPs) in the antioxidative genes superoxide dismutase 2 (SOD2) and glutathione peroxidase 3 (GPX3) with structural neuroimaging phenotypes in youth BD.

METHODS

SOD2 rs4880 and GPX3 rs3792797 SNP genotypes, along with structural magnetic resonance imaging, were obtained from 147 youth (BD = 75; healthy controls = 72). Images were processed using FreeSurfer, yielding surface area, volume, and thickness values for regions of interest (prefrontal cortex [PFC], caudal anterior cingulate cortex, hippocampus) and for vertex-wise whole-brain analysis. Analyses controlled for age, sex, race, and intracranial volume for volume, area, and thickness analyses.

RESULT

Regions of interest analyses revealed diagnosis-by-SOD2 rs4880 interaction effects for caudal anterior cingulate cortex volume and surface area as well as PFC volume; in each case, there was lower volume/area in the BD GG genotype group vs the healthy controls GG genotype group. There was a significant BD diagnosis × GPX3 rs3793797 interaction effect for PFC surface area, where area was lower in the BD A-allele carrier group vs the other genotype groups. Vertex-wise analyses revealed significant interaction effects in frontal, temporal, and parietal regions related to smaller brain structure in the BD SOD2 rs4880 GG group and BD GPX3 rs3793797 A-allele carrier group.

CONCLUSION

We found preliminary evidence that SOD2 rs4880 and GPX3 rs3792797 are differentially associated with brain structures in youth with BD in regions that are relevant to BD. Further studies incorporating additional neuroimaging phenotypes and blood levels of oxidative stress markers are warranted.

A Simulation Toolkit for Testing the Sensitivity and Accuracy of Corticometry Pipelines

In recent years, the replicability of neuroimaging findings has become an important concern to the research community. Neuroimaging pipelines consist of myriad numerical procedures, which can have a cumulative effect on the accuracy of findings. To address this problem, we propose a method for simulating artificial lesions in the brain in order to estimate the sensitivity and specificity of lesion detection, using different automated corticometry pipelines. We have applied this method to different versions of two widely used neuroimaging pipelines (CIVET and FreeSurfer), in terms of coefficients of variation; sensitivity and specificity of detecting lesions in 4 different regions of interest in the cortex, while introducing variations to the lesion size, the blurring kernel used prior to statistical analyses, and different thickness metrics (in CIVET). These variations are tested in a between-subject design (in two random groups, with and without lesions, using T1-weigted MRIs of 152 individuals from the International Consortium of Brain Mapping (ICBM) dataset) and in a within-subject pre-/post-lesion design [using 21 T1-Weighted MRIs of a single adult individual, scanned in the Infant Brain Imaging Study (IBIS)]. The simulation method is sensitive to partial volume effect and lesion size. Comparisons between pipelines illustrate the ability of this method to uncover differences in sensitivity and specificity of lesion detection. We propose that this method be adopted in the workflow of software development and release.

Age-related decline in the brain: a longitudinal study on inter-individual variability of cortical thickness, area, volume, and cognition

Magnetic Resonance Imaging (MRI) studies have shown that cortical volume declines with age. Although volume is a multiplicative measure consisting of thickness and area, few studies have focused on both its components. Information on decline variability and associations between person-specific changes of different brain metrics, brain regions, and cognition is sparse. In addition, the estimates have often been biased by the measurement error, because three repeated measures are minimally required to separate the measurement error from person-specific changes. With a sample size of N = 231, five repeated measures, and an observational time span of seven years, this study explores the associations between changes of different brain metrics, brain regions, and cognitive abilities in aging. Person-specific changes were obtained by latent growth curve models using Bayesian estimation. Our data indicate that both thickness and area are important contributors to volumetric changes. In most brain regions, area clearly declined on average over the years, while thickness showed only little decline. However, there was also substantial variation around the average slope in thickness and area. The correlation pattern of changes in thickness between brain regions was strong and largely homogenous. The pattern for changes in area was similar but weaker, indicating that factors affecting area may be more region-specific. Changes in thickness and volume were substantially correlated with changes in cognition. In some brain regions, changes in area were also related to changes in cognition. Overall, studying the associations between the trajectories of brain regions in different brain metrics provides insights into the regional heterogeneity of structural changes. SIGNIFICANCE STATEMENT: Many studies have described volumetric brain changes in aging. Few studies have focused on both its individual components: area and thickness. Longitudinal studies with three or more time points are highly needed, because they provide more precise average change estimates and, more importantly, allow us to quantify the associations between changes in the different brain metrics, brain regions, and other variables (e.g. cognitive abilities). Studying these associations is important because they can provide information regarding possible underlying factors of these changes. Our study, with a large sample size, five repeated measures, and an observational time span of seven years, provides new insights about the associations between person-specific changes in thickness, area, volume, and cognitive abilities.

Comparison of structural MRI brain measures between 1.5 and 3 T: Data from the Lothian Birth Cohort 1936

Multi‐scanner MRI studies are reliant on understanding the apparent differences in imaging measures between different scanners. We provide a comprehensive analysis of T₁‐weighted and diffusion MRI (dMRI) structural brain measures between a 1.5 T GE Signa Horizon HDx and a 3 T Siemens Magnetom Prisma using 91 community‐dwelling older participants (aged 82 years). Although we found considerable differences in absolute measurements (global tissue volumes were measured as ~6–11% higher and fractional anisotropy [FA] was 33% higher at 3 T than at 1.5 T), between‐scanner consistency was good to excellent for global volumetric and dMRI measures (intraclass correlation coefficient [ICC] range: .612–.993) and fair to good for 68 cortical regions (FreeSurfer) and cortical surface measures (mean ICC: .504–.763). Between‐scanner consistency was fair for dMRI measures of 12 major white matter tracts (mean ICC: .475–.564), and the general factors of these tracts provided excellent consistency (ICC ≥ .769). Whole‐brain structural networks provided good to excellent consistency for global metrics (ICC ≥ .612). Although consistency was poor for individual network connections (mean ICCs: .275−.280), this was driven by a large difference in network sparsity (.599 vs. .334), and consistency was improved when comparing only the connections present in every participant (mean ICCs: .533–.647). Regression‐based k‐fold cross‐validation showed that, particularly for global volumes, between‐scanner differences could be largely eliminated (R² range .615–.991). We conclude that low granularity measures of brain structure can be reliably matched between the scanners tested, but caution is warranted when combining high granularity information from different scanners.

De-identification procedures for magnetic resonance images and the impact on structural brain measures at different ages

Surface rendering of MRI brain scans may lead to identification of the participant through facial characteristics. In this study, we evaluate three methods that overwrite voxels containing privacy‐sensitive information: Face Masking, FreeSurfer defacing, and FSL defacing. We included structural T1‐weighted MRI scans of children, young adults and older adults. For the young adults, test–retest data were included with a 1‐week interval. The effects of the de‐identification methods were quantified using different statistics to capture random variation and systematic noise in measures obtained through the FreeSurfer processing pipeline. Face Masking and FSL defacing impacted brain voxels in some scans especially in younger participants. FreeSurfer defacing left brain tissue intact in all cases. FSL defacing and FreeSurfer defacing preserved identifiable characteristics around the eyes or mouth in some scans. For all de‐identification methods regional brain measures of subcortical volume, cortical volume, cortical surface area, and cortical thickness were on average highly replicable when derived from original versus de‐identified scans with average regional correlations >.90 for children, young adults, and older adults. Small systematic biases were found that incidentally resulted in significantly different brain measures after de‐identification, depending on the studied subsample, de‐identification method, and brain metric. In young adults, test–retest intraclass correlation coefficients (ICCs) were comparable for original scans and de‐identified scans with average regional ICCs >.90 for (sub)cortical volume and cortical surface area and ICCs >.80 for cortical thickness. We conclude that apparent visual differences between de‐identification methods minimally impact reliability of brain measures, although small systematic biases can occur.

Generalizing Longitudinal Age Effects on Brain Structure - A Two-Study Comparison Approach

Cross-sectional studies indicate that normal aging is accompanied by decreases in brain structure. Longitudinal studies, however, are relatively rare and inconsistent regarding their outcomes. Particularly the heterogeneity of methods, sample characteristics and the high inter-individual variability in older adults prevent the deduction of general trends. Therefore, the current study aimed to compare longitudinal age-related changes in brain structure (measured through cortical thickness) in two large independent samples of healthy older adults (n = 161 each); the Longitudinal Healthy Aging Brain (LHAB) database project at the University of Zurich, Switzerland, and 1000BRAINS at the Research Center Juelich, Germany. Annual percentage changes in the two samples revealed stable to slight decreases in cortical thickness over time. After correction for major covariates, i.e., baseline age, sex, education, and image quality, sample differences were only marginally present. Results suggest that general trends across time might be generalizable over independent samples, assuming the same methodology is used, and similar sample characteristics are present.

Bilateral age-related atrophy in the planum temporale is associated with vowel discrimination difficulty in healthy older adults

In this study we investigated the association between age-related brain atrophy and behavioural as well as electrophysiological markers of vowel perception in a sample of healthy younger and older adults with normal pure-tone hearing. Twenty-three older adults and 27 younger controls discriminated a set of vowels with altered second formants embedded in consonant-vowel syllables. Additionally, mismatch negativity (MMN) responses were recorded in a separate oddball paradigm with the same set of stimuli. A structural magnet resonance scan was obtained for each participant to determine cortical architecture of the left and right planum temporale (PT). The PT was chosen for its function as a major processor of auditory cues and speech. Results suggested that older adults performed worse in vowel discrimination despite normal-for-age pure-tone hearing. In the older group, we found evidence that those with greater age-related cortical atrophy (i.e., lower cortical surface area and cortical volume) in the left and right PT also showed weaker vowel discrimination. In comparison, we found a lateralized correlation in the younger group suggesting that those with greater cortical thickness in only the left PT performed weaker in the vowel discrimination task. We did not find any associations between macroanatomical traits of the PT and MMN responses. We conclude that deficient vowel processing is not only caused by pure-tone hearing loss but is also influenced by atrophy-related changes in the ageing auditory-related cortices. Furthermore, our results suggest that auditory processing might become more bilateral across the lifespan.

Midlife aerobic exercise and brain structural integrity: Associations with age and cardiorespiratory fitness

Lower midlife physical activity is associated with higher risk of neurodegenerative disease in late life. However, it remains unknown whether physical exercise and fitness are associated with brain structural integrity during midlife. The purpose of this study was to compare brain structures between middle-aged aerobically trained adults (MA), middle-aged sedentary (MS), and young sedentary (YS) adults. Thirty MA (54±4 years), 30 MS (54±4 years), and 30 YS (32±6 years) participants (50% women) underwent measurements of brain volume, cortical thickness, and white matter (WM) fiber integrity using MRI. MA participants had aerobic training for 24.8±9.6 years and the highest cardiorespiratory fitness level (i.e., peak oxygen uptake: VO2peak) among all groups. Global WM integrity, as assessed with fractional anisotropy (FA) from diffusion tensor imaging, was lower in the MS compared with the YS group. However, global FA in the MA group was significantly higher than that in the MS group (P<0.05) and at a similar level to the YS group. Furthermore, tract-based spatial statistical analysis demonstrated that FA in the anterior, superior, and limbic WM tracts (e.g., the genu of the corpus callosum, superior longitudinal fasciculus, uncinate fasciculus) was higher in the MA compared with MS groups, and positively associated with VO2peak, independently from age and sex. From cortical thickness analysis, MS and MA participants showed thinner prefrontal and parieto-temporal areas than the YS group. On the other hand, the MA group exhibited thicker precentral, postcentral, pericalcarine, and lateral occipital cortices than the MS and YS groups. But, the insula and right superior frontal gyrus showed thinner cortical thickness in the MA compared with the MS groups. Collectively, these findings suggest that midlife aerobic exercise is associated with higher WM integrity and greater primary motor and somatosensory cortical thickness.

Cortical thickness in Parkinson's disease: a coordinate-based meta-analysis

Parkinson's disease (PD) is a common age-related neurodegenerative disease that affects the structural architecture of the cerebral cortex. Cortical thickness (CTh) via surface-based morphometry (SBM) analysis is a popular measure to assess brain structural alterations in the gray matter in PD. However, the results of CTh analysis in PD lack consistency and have not been systematically reviewed. We conducted a comprehensive coordinate-based meta-analysis (CBMA) of 38 CTh studies (57 comparison datasets) in 1,843 patients with PD using the latest seed-based d mapping software. Compared with 1,172 healthy controls, no significantly consistent CTh alterations were found in patients with PD, suggesting CTh as an unreliable neuroimaging marker for PD. The lack of consistent CTh alterations in PD could be ascribed to the heterogeneity in clinical populations, variations in imaging methods, and underpowered small sample sizes. These results highlight the need to control for potential confounding factors to produce robust and reproducible CTh results in PD.

Cortical Thickness, Volume, and Surface Area in the Motoric Cognitive Risk Syndrome

BACKGROUND

The motoric cognitive risk (MCR) syndrome is a pre-clinical stage of dementia characterized by slow gait and cognitive complaint. Yet, the brain substrates of MCR are not well established.

OBJECTIVE

To examine cortical thickness, volume, and surface area associated with MCR in the MCR-Neuroimaging Consortium, which harmonizes image processing/analysis of multiple cohorts.

METHODS

Two-hundred MRIs (M age 72.62 years; 47.74%female; 33.17%MCR) from four different cohorts (50 each) were first processed with FreeSurfer 6.0, and then analyzed using multivariate and univariate general linear models with 1,000 bootstrapped samples (n-1; with resampling). All models adjusted for age, sex, education, white matter lesions, total intracranial volume, and study site.

RESULTS

Overall, cortical thickness was lower in individuals with MCR than in those without MCR. There was a trend in the same direction for cortical volume (p = 0.051). Regional cortical thickness was also lower among individuals with MCR than individuals without MCR in prefrontal, insular, temporal, and parietal regions.

CONCLUSION

Cortical atrophy in MCR is pervasive, and include regions previously associated with human locomotion, but also social, cognitive, affective, and motor functions. Cortical atrophy in MCR is easier to detect in cortical thickness than volume and surface area because thickness is more affected by healthy and pathological aging.

Hearing loss is associated with gray matter differences in older adults at risk for and with Alzheimer's disease

Using data from the COMPASS-ND study we investigated associations between hearing loss and hippocampal volume as well as cortical thickness in older adults with subjective cognitive decline (SCD), mild cognitive impairment (MCI), and Alzheimer's dementia (AD). SCD participants with greater pure-tone hearing loss exhibited lower hippocampal volume, but more cortical thickness in the left superior temporal gyrus and right pars opercularis. Greater speech-in-noise reception thresholds were associated with lower cortical thickness bilaterally across much of the cortex in AD. The AD group also showed a trend towards worse speech-in-noise thresholds compared to the SCD group.

The YOUth cohort study: MRI protocol and test-retest reliability in adults

The YOUth cohort study is a unique longitudinal study on brain development in the general population. As part of the YOUth study, 2000 children will be included at 8, 9 or 10 years of age and planned to return every three years during adolescence. Magnetic resonance imaging (MRI) brain scans are collected, including structural T1-weighted imaging, diffusion-weighted imaging (DWI), resting-state functional MRI and task-based functional MRI. Here, we provide a comprehensive report of the MR acquisition in YOUth Child & Adolescent including the test-retest reliability of brain measures derived from each type of scan. To measure test-retest reliability, 17 adults were scanned twice with a week between sessions using the full YOUth MRI protocol. Intraclass correlation coefficients were calculated to quantify reliability. Global brain measures derived from structural T1-weighted and DWI scans were reliable. Resting-state functional connectivity was moderately reliable, as well as functional brain measures for both the inhibition task (stop versus go) and the emotion task (face versus house). Our results complement previous studies by presenting reliability results of regional brain measures collected with different MRI modalities. YOUth facilitates data sharing and aims for reliable and high-quality data. Here we show that using the state-of-the art YOUth MRI protocol brain measures can be estimated reliably.

Neuroanatomy of transgender persons in a Non-Western population and improving reliability in clinical neuroimaging

Although the neuroanatomy of transgender persons is slowly being charted, findings are presently discrepant. Moreover, the major body of work has focused on Western populations. One important factor is the issue of power and low signal-to-noise (SNR) ratio in neuroimaging studies of rare study populations including endocrine or neurological patient groups. The present study focused on the structural neuroanatomy of a Non-Western (Iranian) sample of 40 transgender men (TM), 40 transgender women (TW), 30 cisgender men (CM), and 30 cisgender women (CW), while assessing whether the reliability of findings across structural anatomical measures including gray matter volume (GMV), cortical surface area (CSA), and cortical thickness (CTh) could be increased by using two back-to-back within-session structural MRI scans. Overall, findings in transgender persons were more consistent with sex assigned at birth in GMV and CSA, while no group differences emerged for CTh. Repeated measures analysis also indicated that having a second scan increased SNR in all regions of interest, most notably bilateral frontal poles, pre- and postcentral gyri and putamina. The results suggest that a simple time and cost-effective measure to improve SNR in rare clinical populations with low prevalence rates is a second anatomical scan when structural MRI is of interest.

Cytoarchitectonic Mapping of MRI Detects Rapid Changes in Alzheimer's Disease

The clinical and pathological progression of Alzheimer's disease often proceeds rapidly, but little is understood about its structural characteristics over short intervals. This study evaluated the short temporal characteristics of the brain structure in Alzheimer's disease through the application of cytoarchitectonic probabilistic brain mapping to measurements of gray matter density, a technique which may provide advantages over standard volumetric MRI techniques. Gray matter density was calculated using voxel-based morphometry of T1-weighted MRI obtained from Alzheimer's disease patients and healthy controls evaluated at intervals of 0.5, 1.5, 3.5, 6.5, 9.5, 12, 18, and 24 months by the MIRIAD study. The Alzheimer's disease patients had 19.1% less gray matter at 1st MRI, and this declined 81.6% faster than in healthy controls. Atrophy in the hippocampus, amygdala, and basal forebrain distinguished the Alzheimer's disease patients. Notably, the CA2 of the hippocampus was found to have atrophied significantly within 1 month. Gray matter density measurements were reliable, with intraclass correlation coefficients exceeding 0.8. Comparative atrophy in the Alzheimer's disease group agreed with manual tracing MRI studies of Alzheimer's disease while identifying atrophy on a shorter time scale than has previously been reported. Cytoarchitectonic mapping of gray matter density is reliable and sensitive to small-scale neurodegeneration, indicating its use in the future study of Alzheimer's disease.

Brain structure and cognitive ability in healthy aging: a review on longitudinal correlated change

Little is still known about the neuroanatomical substrates related to changes in specific cognitive abilities in the course of healthy aging, and the existing evidence is predominantly based on cross-sectional studies. However, to understand the intricate dynamics between developmental changes in brain structure and changes in cognitive ability, longitudinal studies are needed. In the present article, we review the current longitudinal evidence on correlated changes between magnetic resonance imaging-derived measures of brain structure (e.g. gray matter/white matter volume, cortical thickness), and laboratory-based measures of fluid cognitive ability (e.g. intelligence, memory, processing speed) in healthy older adults. To theoretically embed the discussion, we refer to the revised Scaffolding Theory of Aging and Cognition. We found 31 eligible articles, with sample sizes ranging from n = 25 to n = 731 (median n = 104), and participant age ranging from 19 to 103. Several of these studies report positive correlated changes for specific regions and specific cognitive abilities (e.g. between structures of the medial temporal lobe and episodic memory). However, the number of studies presenting converging evidence is small, and the large methodological variability between studies precludes general conclusions. Methodological and theoretical limitations are discussed. Clearly, more empirical evidence is needed to advance the field. Therefore, we provide guidance for future researchers by presenting ideas to stimulate theory and methods for development.

White-matter microstructural properties of the corpus callosum: test-retest and repositioning effects in two parcellation schemes

We investigated test-retest reliability of two MRI-derived indices of white-matter microstructural properties in the human corpus callosum (CC): myelin water fraction (MWF) and geometric mean T₂ relaxation time of intra/extracellular water (geomT_2IEW), using a 3D gradient and multi spin-echo sequence in 20 healthy adults (aged 24-69 years, 10 men). For each person, we acquired two back-to-back acquisitions in a single session, and the third after a break and repositioning the participant in the scanner. We assessed the contribution of session-related variance to reliability, using intra-class effect decomposition (ICED) while comparing two CC parcellation schemes that divided the CC into five and ten regions. We found high construct-level reliability of MWF and geomT_2IEW in all regions of both schemes, except the posterior body-a slender region with a smaller number of large myelinated fibers. Only in that region, we observed significant session-specific variance in the MWF, interpreted as an effect of repositioning in the scanner. The geomT_2IEW demonstrated higher reliability than MWF across both parcellation schemes and all CC regions. Thus, in both CC parcellation approaches, MWF and geomT_2IEW have good test-retest reliability and are, therefore, suitable for longitudinal investigations in healthy adults. However, the five-region scheme appears more appropriate for MWF, whereas both schemes are suitable for geomT_2IEW studies. Given the lower reliability in the posterior body, which may reflect sensitivity to the repositioning of the participant in the scanner, caution should be exercised in interpreting differential findings in that region.

Short-interval intracortical inhibition is decreased in restless legs syndrome across a range of severity

BACKGROUND

Decreased short-interval intracortical inhibition (SICI) to transcranial magnetic stimulation (TMS) of the primary motor cortex was described in subjects with restless legs syndrome/Willis-Ekbom disease (RLS/WED). It remained to be determined whether the magnitude of SICI decrease would be similar across levels of RLS/WED severity. Moreover, it was unknown whether, in addition to decreases in SICI, changes in cortical thickness or area could be detected in subjects with RLS/WED compared to controls. The objective of this study was to compare SICI, cortical thickness, and cortical area in subjects with idiopathic mild to moderate RLS/WED, severe to very severe RLS/WED, and controls.

METHODS

The severity of RLS/WED was assessed by the International Restless Legs Syndrome Severity Scale (IRLSS). SICI and 3T magnetic resonance imaging (MRI) data of subjects with RLS/WED and controls were compared. A receiver operating characteristic curve for SICI was designed for discrimination of participants with RLS/WED from controls. Cortical thickness and area were assessed by automated surface-based analysis.

RESULTS

SICI was significantly reduced in patients with mild to moderate and severe to very severe RLS/WED, compared to controls (one-way analysis of variance: F = 9.62, p < 0.001). Receiver operating characteristic curve analysis predicted RLS/WED when SICI was above 35% (area under the curve = 0.79, 95% CI 0.67-0.91, p < 0.001). Analyses of the whole brain and of regions of interest did not reveal differences in gray matter thickness or area between controls and subjects with RLS/WED.

CONCLUSION

SICI is an accurate cortical biomarker that can support the diagnosis of RLS/WED even in subjects with mild symptoms, but cortical thickness and area were not useful for discriminating subjects with this condition from controls.

Associations between adolescent cannabis use frequency and adult brain structure: A prospective study of boys followed to adulthood

BACKGROUND

Few studies have tested the hypothesis that adolescent cannabis users show structural brain alterations in adulthood. The present study tested associations between prospectively-assessed trajectories of adolescent cannabis use and adult brain structure in a sample of boys followed to adulthood.

METHODS

Data came from the Pittsburgh Youth Study - a longitudinal study of ˜1000 boys. Boys completed self-reports of cannabis use annually from age 13-19, and latent class growth analysis was used to identify different trajectories of adolescent cannabis use. Once adolescent cannabis trajectories were identified, boys were classified into their most likely cannabis trajectory. A subset of boys (n = 181) subsequently underwent structural neuroimaging in adulthood, when they were between 30-36 years old on average. For this subset, we grouped participants according to their classified adolescent cannabis trajectory and tested whether these groups showed differences in adult brain structure in 14 a priori regions of interest, including six subcortical (volume only: amygdala, hippocampus, nucleus accumbens, caudate, putamen, and pallidum) and eight cortical regions (volume and thickness: superior frontal gyrus; caudal and rostral middle frontal gyrus; inferior frontal gyrus, separated into pars opercularis, pars triangularis, and pars orbitalis; lateral and medial orbitofrontal gyrus).

RESULTS

We identified four adolescent cannabis trajectories: non-users/infrequent users, desisters, escalators, and chronic-relatively frequent users. Boys in different trajectory subgroups did not differ on adult brain structure in any subcortical or cortical region of interest.

CONCLUSIONS

Adolescent cannabis use is not associated with structural brain differences in adulthood.

Normative cerebral cortical thickness for human visual areas

Studies of changes in cerebral neocortical thickness often rely on small control samples for comparison with specific populations with abnormal visual systems. We present a normative dataset for FreeSurfer-derived cortical thickness across 25 human visual areas derived from 960 participants in the Human Connectome Project. Cortical thickness varies systematically across visual areas, in broad agreement with canonical visual system hierarchies in the dorsal and ventral pathways. In addition, cortical thickness estimates show consistent within-subject variability and reliability. Importantly, cortical thickness estimates in visual areas are well described by a normal distribution, making them amenable to direct statistical comparison.

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Normative neocortical thickness values for human visual areas measured with FreeSurfer.

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A gradient of increasing neocortical thickness with visual area hierarchy.

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Consistent within- and between-subject variability in neocortical thickness across visual areas.

Quantifying deep grey matter atrophy using automated segmentation approaches: A systematic review of structural MRI studies

The deep grey matter (DGM) nuclei of the brain play a crucial role in learning, behaviour, cognition, movement and memory. Although automated segmentation strategies can provide insight into the impact of multiple neurological conditions affecting these structures, such as Multiple Sclerosis (MS), Huntington's disease (HD), Alzheimer's disease (AD), Parkinson's disease (PD) and Cerebral Palsy (CP), there are a number of technical challenges limiting an accurate automated segmentation of the DGM. Namely, the insufficient contrast of T1 sequences to completely identify the boundaries of these structures, as well as the presence of iso-intense white matter lesions or extensive tissue loss caused by brain injury. Therefore in this systematic review, 269 eligible studies were analysed and compared to determine the optimal approaches for addressing these technical challenges. The automated approaches used among the reviewed studies fall into three broad categories, atlas-based approaches focusing on the accurate alignment of atlas priors, algorithmic approaches which utilise intensity information to a greater extent, and learning-based approaches that require an annotated training set. Studies that utilise freely available software packages such as FIRST, FreeSurfer and LesionTOADS were also eligible, and their performance compared. Overall, deep learning approaches achieved the best overall performance, however these strategies are currently hampered by the lack of large-scale annotated data. Improving model generalisability to new datasets could be achieved in future studies with data augmentation and transfer learning. Multi-atlas approaches provided the second-best performance overall, and may be utilised to construct a "silver standard" annotated training set for deep learning. To address the technical challenges, providing robustness to injury can be improved by using multiple channels, highly elastic diffeomorphic transformations such as LDDMM, and by following atlas-based approaches with an intensity driven refinement of the segmentation, which has been done with the Expectation Maximisation (EM) and level sets methods. Accounting for potential lesions should be achieved with a separate lesion segmentation approach, as in LesionTOADS. Finally, to address the issue of limited contrast, R2*, T2* and QSM sequences could be used to better highlight the DGM due to its higher iron content. Future studies could look to additionally acquire these sequences by retaining the phase information from standard structural scans, or alternatively acquiring these sequences for only a training set, allowing models to learn the "improved" segmentation from T1-sequences alone.

Are global and specific interindividual differences in cortical thickness associated with facets of cognitive abilities, including face cognition?

Face cognition (FC) is a specific ability that cannot be fully explained by general cognitive functions. Cortical thickness (CT) is a neural correlate of performance and learning. In this registered report, we used data from the Human Connectome Project (HCP) to investigate the relationship between CT in the core brain network of FC and performance on a psychometric task battery, including tasks with facial content. Using structural equation modelling (SEM), we tested the existence of face-specific interindividual differences at behavioural and neural levels. The measurement models include general and face-specific factors of performance and CT. There was no face-specificity in CT in functionally localized areas. In post hoc analyses, we compared the preregistered, small regions of interest (ROIs) to larger, non-individualized ROIs and identified a face-specific CT factor when large ROIs were considered. We show that this was probably due to low reliability of CT in the functional localization (intra-class correlation coefficients (ICC) between 0.72 and 0.85). Furthermore, general cognitive ability, but not face-specific performance, could be predicted by latent factors of CT with a small effect size. In conclusion, for the core brain network of FC, we provide exploratory evidence (in need of cross-validation) that areas of the cortex sharing a functional purpose did also share morphological properties as measured by CT.

Cognitive profiles and associated structural brain networks in a multimorbid sample of marginalized adults

Introduction

Cognition is impaired in homeless and vulnerably housed persons. Within this heterogeneous and multimorbid group, distinct profiles of cognitive dysfunction are evident. However, little is known about the underlying neurobiological substrates. Imaging structural covariance networks provides a novel investigative strategy to characterizing relationships between brain structure and function within these different cognitive subgroups.

Method

Participants were 208 homeless and vulnerably housed persons. Cluster analysis was used to group individuals on the basis of similarities in cognitive functioning in the areas of attention, memory, and executive functioning. The principles of graph theory were applied to construct two brain networks for each cognitive group, using measures of cortical thickness and gyrification. Global and regional network properties were compared across networks for each of the three cognitive clusters.

Results

Three cognitive groups were defined by: higher cognitive functioning across domains (Cluster 1); lower cognitive functioning with a decision-making strength (Cluster 3); and an intermediate group with a relative executive functioning weakness (Cluster 2). Between-group differences were observed for cortical thickness, but not gyrification networks. The lower functioning cognitive group exhibited higher segregation and reduced integration, higher centrality in select nodes, and less spatially compact modules compared with the two other groups.

Conclusions

The cortical thickness network differences of Cluster 3 suggest that major disruptions in structural connectivity underlie cognitive dysfunction in a subgroup of people who have a high multimorbid illness burden and who are vulnerably housed or homeless. The origins, and possible plasticity of these structure-function relationships identified with network analysis warrant further study.

MRI Shows that Exhaustion Syndrome Due to Chronic Occupational Stress is Associated with Partially Reversible Cerebral Changes

The present study investigates the cerebral effects of chronic occupational stress and its possible reversibility. Forty-eight patients with occupational exhaustion syndrome (29 women) and 80 controls (47 women) underwent structural magnetic resonance imaging (MRI) and neuropsychological testing. Forty-four participants (25 patients, 19 controls) also completed a second MRI scan after 1-2 years. Only patients received cognitive therapy. The stressed group at intake had reduced thickness in the right prefrontal cortex (PFC) and left superior temporal gyrus (STG), enlarged amygdala volumes, and reduced caudate volumes. Except for the caudate volume, these abnormalities were more pronounced in females. They were all related to perceived stress, which was similar for both genders. Thickness of the PFC also correlated with an impaired ability to down-modulate negative emotions. Thinning of PFC and reduction of caudate volume normalized in the follow-up. The amygdala enlargement and the left STG thinning remained. Longitudinal changes were not detected among controls. Chronic occupational stress was associated with partially reversible structural abnormalities in key regions for stress processing. These changes were dynamically correlated with the degree of perceived stress, highlighting a possible causal link. They seem more pronounced in women, and could be a substrate for an increased cerebral vulnerability to stress-related psychiatric disorders.

Possible Neurobiological Underpinnings of Homosexuality and Gender Dysphoria

Although frequently discussed in terms of sex dimorphism, the neurobiology of sexual orientation and identity is unknown. We report multimodal magnetic resonance imaging data, including cortical thickness (Cth), subcortical volumes, and resting state functional magnetic resonance imaging, from 27 transgender women (TrW), 40 transgender men (TrM), and 80 heterosexual (40 men) and 60 homosexual cisgender controls (30 men). These data show that whereas homosexuality is linked to cerebral sex dimorphism, gender dysphoria primarily involves cerebral networks mediating self-body perception. Among the homosexual cisgender controls, weaker sex dimorphism was found in white matter connections and a partly reversed sex dimorphism in Cth. Similar patterns were detected in transgender persons compared with heterosexual cisgender controls, but the significant clusters disappeared when adding homosexual controls, and correcting for sexual orientation. Instead, both TrW and TrM displayed singular features, showing greater Cth as well as weaker structural and functional connections in the anterior cingulate-precuneus and right occipito-parietal cortex, regions known to process own body perception in the context of self.

Neuroimaging in Psychiatry and Neurodevelopment: why the emperor has no clothes

Neuroimaging has been a dominant force in guiding research into psychiatric and neurodevelopmental disorders for decades, yet researchers have been unable to formulate sensitive or specific imaging tests for these conditions. The search for neuroimaging biomarkers has been constrained by limited reproducibility of imaging techniques, limited tools for evaluating neurochemistry, heterogeneity of patient populations not defined by brain-based phenotypes, limited exploration of temporal components of brain function, and relatively few studies evaluating developmental and longitudinal trajectories of brain function. Opportunities for development of clinically impactful imaging metrics include longer duration functional imaging data sets, new engineering approaches to mitigate suboptimal spatiotemporal resolution, improvements in image post-processing and analysis strategies, big data approaches combined with data sharing of multisite imaging samples, and new techniques that allow dynamical exploration of brain function across multiple timescales. Despite narrow clinical impact of neuroimaging methods, there is reason for optimism that imaging will contribute to diagnosis, prognosis, and treatment monitoring for psychiatric and neurodevelopmental disorders in the near future.

Automated ROI-Based Labeling for Multi-Voxel Magnetic Resonance Spectroscopy Data Using FreeSurfer

Purpose: Advanced analysis methods for multi-voxel magnetic resonance spectroscopy (MRS) are crucial for neurotransmitter quantification, especially for neurotransmitters showing different distributions across tissue types. So far, only a handful of studies have used region of interest (ROI)-based labeling approaches for multi-voxel MRS data. Hence, this study aims to provide an automated ROI-based labeling tool for 3D-multi-voxel MRS data. Methods: MRS data, for automated ROI-based labeling, was acquired in two different spatial resolutions using a spiral-encoded, LASER-localized 3D-MRS imaging sequence with and without MEGA-editing. To calculate the mean metabolite distribution within selected ROIs, masks of individual brain regions were extracted from structural T₁-weighted images using FreeSurfer. For reliability testing of automated labeling a comparison to manual labeling and single voxel selection approaches was performed for six different subcortical regions. Results: Automated ROI-based labeling showed high consistency [intra-class correlation coefficient (ICC) > 0.8] for all regions compared to manual labeling. Higher variation was shown when selected voxels, chosen from a multi-voxel grid, uncorrected for voxel composition, were compared to labeling methods using spatial averaging based on anatomical features within gray matter (GM) volumes. Conclusion: We provide an automated ROI-based analysis approach for various types of 3D-multi-voxel MRS data, which dramatically reduces hands-on time compared to manual labeling without any possible inter-rater bias.

Generalizing age effects on brain structure and cognition: A two-study comparison approach

Normal aging is accompanied by an interindividually variable decline in cognitive abilities and brain structure. This variability, in combination with methodical differences and differences in sample characteristics across studies, pose a major challenge for generalizability of results from different studies. Therefore, the current study aimed at cross-validating age-related differences in cognitive abilities and brain structure (measured using cortical thickness [CT]) in two large independent samples, each consisting of 228 healthy older adults aged between 65 and 85 years: the Longitudinal Healthy Aging Brain (LHAB) database (University of Zurich, Switzerland) and the 1000BRAINS (Research Centre Jülich, Germany). Participants from LHAB showed significantly higher education, physical well-being, and cognitive abilities (processing speed, concept shifting, reasoning, semantic verbal fluency, and vocabulary). In contrast, CT values were larger for participants of 1000BRAINS. Though, both samples showed highly similar age-related differences in both, cognitive abilities and CT. These effects were in accordance with functional aging theories, for example, posterior to anterior shift in aging as was shown for the default mode network. Thus, the current two-study approach provides evidence that independently on heterogeneous metrics of brain structure or cognition across studies, age-related effects on cognitive ability and brain structure can be generalized over different samples, assuming the same methodology is used.

Multimodal MRI suggests that male homosexuality may be linked to cerebral midline structures

The neurobiology of sexual preference is often discussed in terms of cerebral sex dimorphism. Yet, our knowledge about possible cerebral differences between homosexual men (HoM), heterosexual men (HeM) and heterosexual women (HeW) are extremely limited. In the present MRI study, we addressed this issue investigating measures of cerebral anatomy and function, which were previously reported to show sex difference. Specifically, we asked whether there were any signs of sex atypical cerebral dimorphism among HoM, if these were widely distributed (providing substrate for more general 'female' behavioral characteristics among HoM), or restricted to networks involved in self-referential sexual arousal. Cortical thickness (Cth), surface area (SA), subcortical structural volumes, and resting state functional connectivity were compared between 30 (HoM), 35 (HeM) and 38 (HeW). HoM displayed a significantly thicker anterior cingulate cortex (ACC), precuneus, and the left occipito-temporal cortex compared to both control groups. These differences seemed coordinated, since HoM also displayed stronger cortico-cortical covariations between these regions. Furthermore, functional connections within the default mode network, which mediates self- referential processing, and includes the ACC and precuneus were significantly weaker in HoM than HeM and HeW, whereas their functional connectivity between the thalamus and hypothalamus (important nodes for sexual behavior) was stronger. In addition to these singular features, HoM displayed 'female' characteristics, with a similar Cth in the left superior parietal and cuneus cortices as HeW, but different from HeM. These data suggest both singular and sex atypical features and motivate further investigations of cerebral midline structures in relation to male homosexuality.

Testosterone Effects on the Brain in Transgender Men

Transgender individuals experience incongruence between their gender identity and birth-assigned sex. The resulting gender dysphoria (GD), which some gender-incongruent individuals experience, is theorized to be a consequence of atypical cerebral sexual differentiation, but support for this assertion is inconsistent. We recently found that GD is associated with disconnected networks involved in self-referential thinking and own body perception. Here, we investigate how these networks in trans men (assigned female at birth with male gender identity) are affected by testosterone. In 22 trans men, we obtained T1-weighted, diffusion-weighted, and resting-state functional magnetic resonance imaging scans before and after testosterone treatment, measuring cortical thickness (Cth), subcortical volumes, fractional anisotropy (FA), and functional connectivity. Nineteen cisgender controls (male and female) were also scanned twice. The medial prefrontal cortex (mPFC) was thicker in trans men than controls pretreatment, and remained unchanged posttreatment. Testosterone treatment resulted in increased Cth in the insular cortex, changes in cortico-cortical thickness covariation between mPFC and occipital cortex, increased FA in the fronto-occipital tract connecting these regions, and increased functional connectivity between mPFC and temporo-parietal junction, compared with controls. Concluding, in trans men testosterone treatment resulted in functional and structural changes in self-referential and own body perception areas.