Local cortical surface complexity maps from spherical harmonic reconstructions

Sex effects on cortical morphological networks in healthy young adults

Understanding sex-related differences across the human cerebral cortex is an important step in elucidating the basis of psychological, behavioural and clinical differences between the sexes. Prior structural neuroimaging studies primarily focused on regional sex differences using univariate analyses. Here we focus on sex differences in cortical morphological networks (CMNs) derived using multivariate modelling of regional cortical measures of volume and surface from high-quality structural MRI scans from healthy participants in the Human Connectome Project (HCP) (n = 1,063) and the Southwest University Longitudinal Imaging Multimodal (SLIM) study (n = 549). The functional relevance of the CMNs was inferred using the NeuroSynth decoding function. Sex differences were widespread but not uniform. In general, females had higher volume, thickness and cortical folding in networks that involve prefrontal (both ventral and dorsal regions including the anterior cingulate) and parietal regions while males had higher volume, thickness and cortical folding in networks that primarily include temporal and posterior cortical regions. CMN loading coefficients were used as input features to linear discriminant analyses that were performed separately in the HCP and SLIM; sex was predicted with a high degree of accuracy (81%-85%) across datasets. The availability of behavioral data in the HCP enabled us to show that male-biased surface-based CMNs were associated with externalizing behaviors. These results extend previous literature on regional sex-differences by identifying CMNs that can reliably predict sex, are relevant to the expression of psychopathology and provide the foundation for the future investigation of their functional significance in clinical populations.

Altered cortical morphology in major depression disorder patients with suicidality

Background

Major depressive disorder (MDD) is associated with high risk of suicide, but the biological underpinnings of suicidality in MDD patients are far from conclusive. Previous neuroimaging studies using voxel-based morphometry (VBM) demonstrated that depressed individuals with suicidal thoughts or behaviors exhibit specific cortical structure alterations. To complement VBM findings, surface-based morphometry (SBM) can provide more details into gray matter structure, including the cortical complexity, cortical thickness and sulcal depth for brain images.

Objective

This study aims to use SBM to investigate cortical morphology alterations to obtain evidence for neuroanatomical alterations in depressed patients with suicidality.

Methods

Here, 3D T1-weighted MR images of brain from 39 healthy controls, 40 depressed patients without suicidality (patient controls), and 39 with suicidality (suicidal groups) were analyzed based on SBM to estimate the fractal dimension, gyrification index, sulcal depth, and cortical thickness using the Computational Anatomy Toolbox. Correlation analyses were performed between clinical data and cortical surface measurements from patients.

Results

Surface-based morphometry showed decreased sulcal depth in the parietal, frontal, limbic, occipital and temporal regions and decreased fractal dimension in the frontal regions in depressed patients with suicidality compared to both healthy and patient controls. Additionally, in patients with depression, the sulcal depth of the left caudal anterior cingulate cortex was negatively correlated with Hamilton Depression Rating Scale scores.

Conclusions

Depressed patients with suicidality had abnormal cortical morphology in some brain regions within the default mode network, frontolimbic circuitry and temporal regions. These structural deficits may be associated with the dysfunction of emotional processing and impulsivity control. This study provides insights into the underlying neurobiology of the suicidal brain.

Occupation-related effects on motor cortex thickness among older, cognitive healthy individuals

Both, decline of sensorimotor functions and cortical thickness are known processes in healthy aging. Physical activity has been suggested to enhance the execution of daily routine activities and to extend the time of functional independence in advanced age. We hypothesized that cortical thickness of motor areas in retired individuals could be related to physical demands of the profession carried out during working life. Depending on their former occupations, 69 cognitively healthy individuals (range 70–85 years) were divided into higher and lower physically complex occupations (HPCO n = 27 and LPCO n = 42) according to the international standard classification of occupations (ISCO-08). Participants underwent a high-resolution 3T T1-weighted MRI scan. Surface-based analysis revealed higher cortical thickness in the left precentral (P = 0.001) and postcentral gyrus (P < 0.001) and right postcentral gyrus (P = 0.001) for the HPCO relative to the LPCO group (corrected for multiple comparisons, sex, age and leisure activities in the past 20 years). Physical leisure activities associated with exertion were positively correlated with cortical thickness in the left pre- and postcentral gyrus (P = 0.037) of the LPCO group. Time since retirement was negatively associated with cortical thickness in the left postcentral gyrus (P = 0.004) of the HPCO group. Executing a higher physically complex occupation before retirement was related to relative higher cortical thickness in the primary motor and somatosensory cortex in later life, supporting the hypothesis that physical activity contributes to neural reserve in these regions. However, these benefits appear to vanish when physical activity is reduced due to retirement.

Gray Matter Deterioration Pattern During Alzheimer's Disease Progression: A Regions-of-Interest Based Surface Morphometry Study

Accurate detection of the regions of Alzheimer's disease (AD) lesions is critical for early intervention to effectively slow down the progression of the disease. Although gray matter volumetric abnormalities are commonly detected in patients with mild cognition impairment (MCI) and patients with AD, the gray matter surface-based deterioration pattern associated with the progression of the disease from MCI to AD stages is largely unknown. To identify group differences in gray matter surface morphometry, including cortical thickness, the gyrification index (GI), and the sulcus depth, 80 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database were split into healthy controls (HCs; N = 20), early MCIs (EMCI; N = 20), late MCIs (LMCI; N = 20), and ADs (N = 20). Regions-of-interest (ROI)-based surface morphometry was subsequently studied and compared across the four stage groups to characterize the gray matter deterioration during AD progression. Co-alteration patterns (Spearman's correlation coefficient) across the whole brain were also examined. Results showed that patients with MCI and AD exhibited a significant reduction in cortical thickness (p < 0.001) mainly in the cingulate region (four subregions) and in the temporal (thirteen subregions), parietal (five subregions), and frontal (six subregions) lobes compared to HCs. The sulcus depth of the eight temporal, four frontal, four occipital, and eight parietal subregions were also significantly affected (p < 0.001) by the progression of AD. The GI was shown to be insensitive to AD progression (only three subregions were detected with a significant difference, p < 0.001). Moreover, Spearman's correlation analysis confirmed that the co-alteration pattern of the cortical thickness and sulcus depth indices is predominant during AD progression. The findings highlight the relevance between gray matter surface morphometry and the stages of AD, laying the foundation for in vivo tracking of AD progression. The co-alteration pattern of surface-based morphometry would improve the researchers' knowledge of the underlying pathologic mechanisms in AD.

Multiparametric and multilevel characterization of morphological alterations in patients with transient ischemic attack

Transient ischemic attack (TIA), an important risk factor for stroke, is associated with widespread disruptions of functional brain architecture. However, TIA-related structural alterations are not well established. By analyzing structural MRI data from 50 TIA patients versus 40 healthy controls (HCs), here we systematically investigated TIA-related morphological alterations in multiple cortical surface-based indices (cortical thickness [CT], fractal dimension [FD], gyrification index [GI], and sulcal depth [SD]) at multiple levels (local topography, interregional connectivity and whole-brain network topology). For the observed alterations, their associations with clinical risk factors and abilities as diagnostic and prognostic biomarkers were further examined. We found that compared with the HCs, the TIA patients showed widespread morphological alterations and the alterations depended on choices of morphological index and analytical level. Specifically, the patients exhibited: (a) regional CT decreases in the transverse temporal gyrus and lateral sulcus; (b) impaired FD- and GI-based connectivity mainly involving visual, somatomotor and ventral attention networks and interhemispheric connections; and (c) altered GI-based whole-brain network efficiency and decreased FD-based nodal centrality in the middle frontal gyrus. Moreover, the impaired morphological connectivity showed high sensitivities and specificities for distinguishing the patients from HCs. Altogether, these findings demonstrate the emergence of morphological index-dependent and analytical level-specific alterations in TIA, which provide novel insights into neurobiological mechanisms underlying TIA and may serve as potential biomarkers to help diagnosis of the disease. Meanwhile, our findings highlight the necessity of using multiparametric and multilevel approaches for a complete mapping of cerebral morphology in health and disease.

Brain Cortical Complexity Alteration in Amyotrophic Lateral Sclerosis: A Preliminary Fractal Dimensionality Study

Objective

Fractal dimensionality (FD) analysis provides a quantitative description of brain structural complexity. The application of FD analysis has provided evidence of amyotrophic lateral sclerosis- (ALS-) related white matter degeneration. This study is aimed at evaluating, for the first time, FD alterations in a gray matter in ALS and determining its association with clinical parameters. Materials and Methods. This study included 22 patients diagnosed with ALS and 20 healthy subjects who underwent high-resolution T1-weighted imaging scanning. Disease severity was assessed using the revised ALS Functional Rating Scale (ALSFRS-R). The duration of symptoms and rate of disease progression were also assessed. The regional FD value was calculated by a computational anatomy toolbox and compared among groups. The relationship between cortical FD values and clinical parameters was evaluated by Spearman correlation analysis.

Results

ALS patients showed decreased FD values in the left precentral gyrus and central sulcus, left circular sulcus of insula (superior segment), left cingulate gyrus and sulcus (middle-posterior part), right precentral gyrus, and right postcentral gyrus. The FD values in the right precentral gyrus were positively correlated to ALSFRS-R scores (r = 0.44 and P = 0.023), whereas negatively correlated to the rate of disease progression (r = 0.44 and P = 0.023), whereas negatively correlated to the rate of disease progression (r = 0.44 and P = 0.023), whereas negatively correlated to the rate of disease progression (

Conclusions

Our results suggest an ALS-related reduction in structural complexity involving the gray matter. FD analysis may shed more light on the pathophysiology of ALS.

Cortical Complexity in People at Ultra-High-Risk for Psychosis Moderated by Childhood Trauma

Subjects with ultra-high risk (UHR) states for psychosis show brain structural volume changes similar to first-episode psychosis and also elevated incidence of environmental risk factors like childhood trauma. It is unclear, however, whether early neurodevelopmental trajectories are altered in UHR. We screened a total of 12,779 first-year Chinese students to enroll 36 UHR subjects (based on clinical interviews) and 59 non-UHR healthy controls for a case-control study of markers of early neurodevelopment. Subjects underwent 3T MRI scanning and clinical characterization, including the childhood trauma questionnaire (CTQ). We then used the CAT12 toolbox to analyse structural brain scans for cortical surface complexity, a spherical harmonics-based marker of early neurodevelopmental changes. While we did not find statistically significant differences between the groups, a trend level finding for reduced cortical complexity (CC) in UHR vs. non-UHR subjects emerged in the left superior temporal cortex (and adjacent insular and transverse temporal cortices), and this trend level association was significantly moderated by childhood trauma (CTQ score). Our findings indicate that UHR subjects tend to show abnormal cortical surface morphometry, in line with recent research; more importantly, however, this association seems to be considerably modulated by early environmental impacts. Hence, our results provide an indication of environmental or gene × environment interactions on early neurodevelopment leading up to elevated psychosis risk.

Effects of Cognitive Functioning and Education on Later-Life Health Numeracy

INTRODUCTION

Previous studies have shown an association between a high health numeracy and good cognitive functioning.

OBJECTIVE

To investigate the moderation effect of education on this relationship and which brain structures support health numeracy.

METHODS

We examined 70 healthy older persons (66% females; mean ± SD: age, 75.73 ± 4.52 years; education, 12.21 ± 2.94 years). The participants underwent a T1-weighted 3-T MRI and a neuropsychological assessment including a health numeracy task. Statistical parametric mapping was applied to identify focal changes in cortical thickness throughout the entire brain and to correlate image parameters with behavioral measures.

RESULTS

Executive functions and mental calculation emerged as predictors of health numeracy (B = 0.22, p < 0.05, and B = 0.38, p < 0.01). An interaction was found between education and executive functions (B = -0.16, p = 0.01) and between education and mental calculation (B = -0.11, p < 0.05). Executive functions and mental calculation had an impact on health numeracy in participants with a low to intermediate edu-cation (≤12 years) but not in those with a higher education (>12 years). Health numeracy scores were associated with cortical thickness in the right dorsomedial prefrontal cortex and the right superior temporal gyrus (p = 0.01).

CONCLUSIONS

Older people with a higher education perform better in health numeracy tasks than those with a lower education. They have access to previously acquired knowledge about ratio concepts and do not need to rely on executive functions and computational skills. This is highly relevant when decisions about health care have to be made.

Cortical Thickness Mediates the Association Between Self-Reported Pain and Sleep Quality in Community-Dwelling Older Adults

INTRODUCTION

Musculoskeletal pain is prevalent in older adults representing the leading cause of disability in this population. Similarly, nearly half of older adults complain of difficulty sleeping. We aimed to explore the relationship between sleep quality with self-reported musculoskeletal pain, somatosensory and pain thresholds in community-dwelling older adults and further explore brain regions that may contribute to this association.

METHODS

Older adults (>60 years old, n=69) from the NEPAL study completed demographic, pain and sleep assessments followed by a quantitative sensory testing battery. A subset (n=49) also underwent a 3T high-resolution, T1-weighted anatomical scan.

RESULTS

Poorer sleep quality using the Pittsburgh Sleep Quality Index was positively associated with self-reported pain measures (all p's >0.05), but not somatosensory and pain thresholds (all p's >0.05). Using a non-parametric threshold-free cluster enhancement (TFCE) approach, worse sleep quality was significantly associated with lower cortical thickness in the precentral, postcentral, precuneus, superior parietal, and lateral occipital regions (TFCE-FWE-corrected at p < 0.05). Further, only postcentral cortical thickness significantly mediated the association between sleep quality and self-reported pain intensity using bootstrapped mediation methods.

CONCLUSION

Our findings in older adults are similar to previous studies in younger individuals where sleep is significantly associated with self-reported pain. Specifically, our study implicates brain structure as a significant mediator of this association in aging. Future larger studies are needed to replicate our findings and to further understand if the brain can be a therapeutic target for both improved sleep and pain relief in older individuals.

Reduced cortical thickness in World Trade Center responders with cognitive impairment

INTRODUCTION

This study examined cortical thickness (CTX) in World Trade Center (WTC) responders with cognitive impairment (CI).

METHODS

WTC responders (N = 99) with/without CI, recruited from an epidemiologic study, completed a T1-MPRAGE protocol. CTX was automatically computed in 34 regions of interest. Region-based and surface-based morphometry examined CTX in CI versus unimpaired responders. CTX was automatically computed in 34 regions of interest. Region-based measures were also compared to published norms.

RESULTS

Participants were 55.8 (SD = 0.52) years old; 48 had CI. Compared to unimpaired responders, global mean CTX was reduced in CI and across 21/34 cortical subregions. Surface-based analyses revealed reduced CTX across frontal, temporal, and parietal lobes when adjusting for multiple comparisons. Both CI and unimpaired WTC groups had reduced CTX in the entorhinal and temporal cortices compared to published normative data.

DISCUSSION

Results from the first structural magnetic resonance imaging study in WTC responders identified reduced CTX consistent with a neurodegenerative disease of unknown etiology.

Articulation rehabilitation induces cortical plasticity in adults with non-syndromic cleft lip and palate

In this study, we investigated brain morphological changes in adults with non-syndromic cleft lip and palate (NSCLP) after articulation rehabilitation (AR). High-resolution T1 weighted brain magnetic resonance imaging data were analyzed from 45 adults with NSCLP after palatoplasty: 24 subjects were assessed before AR (bNSCLP) and 21 subjects were assessed after AR (aNSCLP). In addition, there were 24 age and sex matched controls. Intergroup differences of grey matter volume were evaluated as a comprehensive measure of the cortex; cortical thickness and cortical complexity (gyrification and fractal dimensions) were also analyzed. As compared to controls, the bNSCLP subjects exhibited altered indexes in frontal, temporal, and parietal lobes; these morphological changes are characteristic for adults with NSCLP. Importantly, as compared to the bNSCLP and control subjects, the aNSCLP subjects exhibited cortical plasticity in the regions involved in language, auditory, pronunciation planning, and execution functions. The AR-mediated cortical plasticity in aNSCLP subjects may be caused by AR-induced cortical neurogenesis, which might reflect the underlying neural mechanism during AR.

Associations Between Individual Differences in Mathematical Competencies and Surface Anatomy of the Adult Brain

Previously conducted structural magnetic resonance imaging (MRI) studies on the neuroanatomical correlates of mathematical abilities and competencies have several methodological limitations. Besides small sample sizes, the majority of these studies have employed voxel-based morphometry (VBM)-a method that, although it is easy to implement, has some major drawbacks. Taking this into account, the current study is the first to investigate in a large sample of typically developed adults the associations between mathematical abilities and variations in brain surface structure by using surface-based morphometry (SBM). SBM is a method that also allows the investigation of brain morphometry by avoiding the pitfalls of VBM. Eighty-nine young adults were tested with a large battery of psychometric tests to measure mathematical competencies in four different areas: (1) simple arithmetic; (2) complex arithmetic; (3) higher-order mathematics; and (4) numerical intelligence. Also, we asked participants for their mathematics grades for their final school exams. Inside the MRI scanner, we collected high-resolution T1-weighted anatomical images from each subject. SBM analyses were performed with the computational anatomy toolbox (CAT12) and indices for cortical thickness, for cortical surface complexity, for gyrification, and sulcal depth were calculated. Further analyses revealed associations between: (1) the cortical surface complexity of the right superior temporal gyrus and numerical intelligence; (2) the depth of the right central sulcus and adults' ability to solve complex arithmetic problems; and (3) the depth of the left parieto-occipital sulcus and adults' higher-order mathematics competence. Interestingly, no relationships with previously reported brain regions were observed, thus, suggesting the importance of similar research to confirm the role of the brain regions found in this study.

Reduced Cortical Complexity in Cirrhotic Patients with Minimal Hepatic Encephalopathy

Purpose

Gray matter volume loss, regional cortical thinning, and local gyrification index alteration have been documented in minimal hepatic encephalopathy (MHE). Fractal dimension (FD), another morphological parameter, has been widely used to describe structural complexity alterations in neurological or psychiatric disease. Here, we conducted the first study to investigate FD alterations in MHE.

Methods and Materials

We performed high-resolution structural magnetic resonance imaging on cirrhotic patients with MHE (n = 20) and healthy controls (n = 21). We evaluated their cognitive performance using the psychometric hepatic encephalopathy score (PHES). The regional FD value was calculated by Computational Anatomy Toolbox (CAT12) and compared between groups. We further estimated the association between patients' cognitive performance and FD values.

Results

MHE patients presented significantly decreased FD values in the left precuneus, left supramarginal gyrus, right caudal anterior cingulate cortex, right isthmus cingulate cortex, right insula, bilateral pericalcarine cortex, and bilateral paracentral cortex compared to normal controls. In addition, the FD values in the right isthmus cingulate cortex and right insula were shown to be positively correlated with patients' cognitive performance.

Conclusion

Aberrant cortical complexity is an additional characteristic of MHE, and FD analysis may provide novel insight into the neurobiological basis of cognitive dysfunction in MHE.

Exploring cortical predictors of clinical response to electroconvulsive therapy in major depression

Electroconvulsive therapy (ECT) is a rapid and highly effective treatment option for treatment-resistant major depressive disorder (TRD). The neural mechanisms underlying such beneficial effects are poorly understood. Exploring associations between changes of brain structure and clinical response is crucial for understanding ECT mechanisms of action and relevant for the validation of potential biomarkers that can facilitate the prediction of ECT efficacy. The aim of this explorative study was to identify cortical predictors of clinical response in TRD patients treated with ECT. We longitudinally investigated 12 TRD patients before and after ECT. Twelve matched healthy controls were studied cross sectionally. Demographical, clinical, and structural magnetic resonance imaging data at 3 T and multiple cortical markers derived from surface-based morphometry (SBM) analyses were considered. Multiple regression models were computed to identify predictors of clinical response to ECT, as reflected by Hamilton Depression Rating Scale (HAMD) score changes. Symptom severity differences pre-post-ECT were predicted by models including demographic data, clinical data and SBM of frontal, cingulate, and entorhinal structures. Using all-subsets regression, a model comprising HAMD score at baseline and cortical thickness of the left rostral anterior cingulate gyrus explained most variance in the data (multiple R² = 0.82). The data suggest that SBM provides powerful measures for identifying biomarkers for ECT response in TRD. Rostral anterior cingulate thickness and HAMD score at baseline showed the greatest predictive power of clinical response, in contrast to cortical complexity, cortical gyrification, or demographical data.

Abnormal Cortical Thickness Is Associated With Deficits in Social Cognition in Patients With Myotonic Dystrophy Type 1

Aim: To investigate the cortical thickness in myotonic dystrophy type 1 (DM1) and its potential association with patients' genetic triplet expansion and social cognition deficits.

Methods: Thirty patients with DM1 underwent the Social Cognition Battery Test and magnetic resonance imaging (MRI) scanning at 3 T. Twenty-five healthy subjects (HSs) were enrolled in the study to serve as a control group for structural MRI data. To assess changes in cortical thickness in DM1 patients, they were compared to HSs using a t-test model. Correlations were used to assess potential associations between genetic and clinical characteristics and social cognition performances in the patient group. Additionally, multiple regression models were used to explore associations between cortical thickness, CTG triplet expansion size, and scores obtained by DM1 patients on the Social Cognition Battery.

Results: DM1 patients showed low performances in several subtests of the Social Cognition Battery. Specifically, they obtained pathological scores at Emotion Attribution Test (i.e., Sadness, Embarrassment, Happiness, and Anger) and at the Social Situations Test (i.e., recognition of normal situation, recognition of aberrant behavior). Significant negative correlations were found between CTG triplet expansion size and Embarrassment, and Severity of Aberrant Behavior. Similarly, a negative correlation was found between patients' MIRS scores and Sadness. DM1 patients compared to HSs showed reduced thickness in the right premotor cortex, angular gyrus, precuneus, and inferior parietal lobule. Significant associations were found between patients' CTG triplet expansion size and thickness in left postcentral gyrus and in the left primary somatosensory cortex, in the posterior cingulate cortex bilaterally, and in the right lingual gyrus. Finally, significant associations were found between cortical thickness and sadness in the superior temporal gyrus, the right precentral gyrus, the right angular gyrus, and the left medial frontal gyrus bilaterally. DM1 patients showed a negative correlation between cortical thickness in the bilateral precuneus and in the left lateral occipital cortex and performance at the Social Situations Test. Finally, DM1 patients showed a negative correlation between cortical thickness in the left precuneus and in the superior frontal gyrus and scores at the Moral Distinction Test.

Discussion: The present study shows both cortical thickness changes in DM1 patients compared to controls and significant associations between cortical thickness and patients' social cognition performances. These data confirm the presence of widespread brain damages associated with cognitive impairment in DM1 patients.

Fluid intelligence is associated with cortical volume and white matter tract integrity within multiple-demand system across adult lifespan

BACKGROUND

Fluid intelligence (Gf) is the innate ability of an individual to respond to complex and unexpected situations. Although some studies have considered that the multiple-demand (MD) system of the brain was the biological foundation for Gf, further characterization of their relationships in the context of aging is limited. The present study hypothesized that the structural metrics of the MD system, including cortical thickness, cortical volumes, and white matter (WM) tract integrity, was the brain correlates for Gf across the adult life span. Partial correlation analysis was performed to investigate whether the MD system could still explain Gf independent of the age effect. Moreover, the partial correlations between Gf and left/right structural metrics within the MD regions were compared to test whether the correlations displayed distinct lateralization.

METHODS

The participants were recruited from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) databank, comprising the images of 603 healthy participants aged 18-88 years acquired on a 3-T system. The MRI data included high-resolution T1-weighted and diffusion-weighted images, from which gray matter and WM structural metrics of the MD system were analyzed, respectively. The structural metrics of gray matter were quantified in terms of cortical volume/thickness of five pairs of cortical regions, and those of WM were quantified in terms of the mean axial diffusivity (D_A), radial diffusivity (D_R), mean diffusivity (D_M), and generalized fractional anisotropy (GFA) on five pairs of tracts. Partial correlation controlling for age and sex effects, was performed to investigate the associations of Gf scores with the mean D_A, D_R, D_M and GFA of all tracts in the MD system, those of left and right hemispheric tracts, and those of each tract. Fisher's exact test was used to compare the partial correlations between left and right MD regions.

RESULTS

The linear relationship between cortical volumes and Gf was evident across all levels of the MD system even after controlling for age and sex. For the WM integrity, diffusion indices including D_A, D_R, D_M and GFA displayed linear relationships with Gf scores at various levels of the MD system. Among the 10 WM tracts connecting the MD regions, bilateral superior longitudinal fasciculus I and bilateral frontal aslant tracts exhibited the strongest and significant associations. Our results did not show significant inter-hemispheric differences in the associations between structural metrics of the MD system and Gf.

CONCLUSION

Our results demonstrate significant associations between Gf and both cortical volumes and tract integrity of the MD system across the adult lifespan in a population-based cohort. We found that the association remained significant in the entire adult lifespan despite simultaneous decline of Gf and the MD system. Our results suggest that the MD system might be a structural underpinning of Gf and support the fronto-parietal model of cognitive aging. However, we did not find hemispheric differences in the Gf-MD correlations, not supporting the hemi-aging hypothesis.

Analysis of patients with obstructive sleep apnea with and without pharyngeal myopathy using brain neuroimaging

STUDY OBJECTIVES

Elements impairing upper airway anatomy or muscle function (e.g. pharyngeal neuromyopathy) contribute to obstructive sleep apnea syndrome (OSAS). Structural brain imaging may differ in patients with OSAS according to dilator muscle dysfunction. Magnetic resonance imaging (MRI) with voxel-based morphometry (VBM) and surface-based morphometry (SBM) was used to investigate this hypothesis.

METHODS

Eighteen patients with OSAS and 32 controls underwent 3T brain MRI. T1 volumetric images were used for structural analysis. Pharyngeal electroneuromyography was performed; patients with OSAS were classified as with or without neuromyopathy. VBM and SBM analyses were conducted using SPM12 and CAT12 software. Image processing was standard. Cortical surface parameters and gray and white matter volumes from participants with OSAS with and without neuromyopathy were compared with those from controls.

RESULTS

Eleven patients had OSAS with neuromyopathy and seven patients had OSAS without neuromyopathy (normal pharyngeal electroneuromyography). Comparing these groups to the controls, VBM revealed: four clusters (total volume 15,368 mm3) for patients with neuromyopathy, the largest cluster in the left cerebellum (9,263 mm3, p = 0.0001), and three clusters (total 8,971 mm3) for patients without neuromyopathy, the largest cluster in the left cerebellum (5,017 mm3, p = 0.002). Patients with OSAS with neuromyopathy showed increased proportion of atrophy (p < 0.0001). SBM showed abnormalities in patients without neuromyopathy (decreased cortical thickness, left precentral gyrus [672 vertices, p = 0.04]; increased cortical complexity, right middle temporal gyrus [578 vertices, p = 0.032]).

CONCLUSION

Damaged areas were larger in patients with OSAS with than in those without neuromyopathy, suggesting differences in brain involvement. Patients with OSAS and neuromyopathy may be more susceptible to cerebral damage.

Brain Morphological Dynamics of Procrastination: The Crucial Role of the Self-Control, Emotional, and Episodic Prospection Network

Globally, about 17% individuals are suffering from the maladaptive procrastination until now, which impacts individual's financial status, mental health, and even public policy. However, the comprehensive understanding of neuroanatomical understructure of procrastination still remains gap. 688 participants including 3 independent samples were recruited for this study. Brain morphological dynamics referred to the idiosyncrasies of both brain size and brain shape. Multilinear regression analysis was utilized to delineate brain morphological dynamics of procrastination in Sample 1. In the Sample 2, cross-validation was yielded. Finally, prediction models of machine learning were conducted in Sample 3. Procrastination had a significantly positive correlation with the gray matter volume (GMV) in the left insula, anterior cingulate gyrus (ACC), and parahippocampal gyrus (PHC) but was negatively correlated with GMV of dorsolateral prefrontal cortex (dlPFC) and gray matter density of ACC. Furthermore, procrastination was positively correlated to the cortical thickness and cortical complexity of bilateral orbital frontal cortex (OFC). In Sample 2, all the results were cross-validated highly. Predication analysis demonstrated that these brain morphological dynamic can predict procrastination with high accuracy. This study ascertained the brain morphological dynamics involving in self-control, emotion, and episodic prospection brain network for procrastination, which advanced promising aspects of the biomarkers for it.

The association of grey matter volume and cortical complexity with individual differences in children's arithmetic fluency

Only a small amount of studies have looked at the structural neural correlates of children's arithmetic. Furthermore, these studies mainly implemented voxel-based morphometry, which only takes the volume of regions into account, without looking at other structural properties. The current study aimed to contribute knowledge on which brain regions are important for children's arithmetic on a structural level, by not only implementing voxel-based morphometry, but also cortical complexity analyses, based on the fractal dimension index. This complexity measure describes a characteristic of surface shape. Data of 43 typically developing 9-10 year-olds were analyzed. All children were asked to take part in two test sessions: behavioral data collection and MRI data acquisition. For data analysis, mean values for volume and cortical complexity were estimated within regions of interest (ROIs) and extracted for further analysis. The selected ROIs were based on regions found to be related to children's mathematical abilities in previous research. Results point towards associations between arithmetic fluency and the volume of the right fusiform gyrus, as well as the cortical complexity of the left postcentral gyrus, right insular sulcus, and left lateral orbital sulcus. Remarkably, no significant associations were observed between the children's arithmetic fluency and the volume or cortical complexity of typically arithmetic-associated parietal regions, such as the superior parietal lobe, intraparietal sulcus, or angular gyrus. Accordingly, the current study highlights the importance of structural characteristics of brain regions other than these typically arithmetic-associated parietal regions for children's arithmetic fluency.

The relationship between bilingual experience and gyrification in adulthood: A cross-sectional surface-based morphometry study

Neuroimaging evidence suggests that bilingualism may act as a source of neural plasticity. However, prior work has mostly focused on bilingualism-induced alterations in gray matter volume and white matter tract microstructure, with additional effects related to other neurostructural indices that might have remained undetected. The degree of cortical folding or gyrification is a morphometric parameter which provides information about changes on the brain's surface during development, aging and disease. We used Surface-based Morphometry (SBM) to investigate the contribution of bilingual experience to gyrification from early adulthood to old age in a sample of bilinguals and monolingual controls. Despite widespread cortical folding reductions for all participants with increasing age, preserved gyrification exclusive to bilinguals was detected in the right cingulate and entorhinal cortices, regions vulnerable with normal and pathological brain aging. Our results provide novel insights on experience-related cortical reshaping and bilingualism-induced cortical plasticity in adulthood.

Parallel Changes in Cognitive Function and Gray Matter Volume After Multi-Component Training of Cognitive Control (MTCC) in Adolescents

Adolescence is a unique period in which higher cognition develops to adult-level, while plasticity of neuron and behavior is at one of its peak. Notably, cognitive training studies for adolescents has been sparse and neural correlates of the training effects yet to be established. This study investigated the effects of multi-component training of cognitive control (MTCC) in order to examine whether the training enhanced adolescents' cognitive control ability and if the effects were generalizable to other cognitive domains. Cognitive control refers to the ability to adjust a series of thoughts and behaviors in correspondence to an internal goal, and involves inhibition, working memory, shifting, and dual tasking as subcomponents. The participants were middle school students (aged 11-14) and randomly assigned to either a training group or an active control group. The training group performed 30 min of MTCC per day for 6 weeks. To identify the training effects, we examined the cognitive performance, regional gray matter, and their relationship. The training group showed modest improvement in a visuospatial fluid intelligence test (Block Design) after MTCC, which was not significant after correcting for multiple comparisons. In addition, the training effect on the gray matter volume (time × group interaction) was observed in the right inferior cortex (rIFC). While the control group showed a typical reduction in the rIFC volume, the training group showed a relative increase in the homologous region. The relative change in rIFC volume was associated with the change in Stroop performance. These results imply that MTCC may affect brain structure relevant to inhibitory control process.

Shape-related characteristics of age-related differences in subcortical structures

OBJECTIVES

With an increasing aging population, it is important to understand biological markers of aging. Subcortical volume is known to differ with age; additionally considering shape-related characteristics may provide a better index of age-related differences. Fractal dimensionality is more sensitive to age-related differences, but is borne out of mathematical principles, rather than neurobiological relevance. We considered four distinct measures of shape and how they relate to aging and fractal dimensionality: surface-to-volume ratio, sphericity, long-axis curvature, and surface texture.

METHODS

Structural MRIs from a combined sample of over 600 healthy adults were used to measure age-related differences in the structure of the thalamus, putamen, caudate, and hippocampus. For each, volume and fractal dimensionality were calculated, as well as four distinct shape measures. These measures were examined for their utility in explaining age-related variability in brain structure.

RESULTS

The four shape measures were able to account for 80%-90% of the variance in fractal dimensionality. Of the distinct shape measures, surface-to-volume ratio was the most sensitive biomarker.

CONCLUSION

Though volume is often used to characterize inter-individual differences in subcortical structures, our results demonstrate that additional measures can be useful complements. Our results indicate that shape characteristics are useful biological markers of aging.

Neurocognitive basis of repetition deficits in primary progressive aphasia

Previous studies indicate that repetition is affected in primary progressive aphasia (PPA), particularly in the logopenic variant, due to limited auditory-verbal short-term memory (avSTM). We tested repetition of phrases varied by length (short, long) and meaning (meaningful, non-meaningful) in 58 participants (22 logopenic, 19 nonfluent, and 17 semantic variants) and 21 healthy controls using a modified Bayles repetition test. We evaluated the relation between cortical thickness and repetition performance and whether sub-scores could discriminate PPA variants. Logopenic participants showed impaired repetition across all phrases, specifically in repeating long phrases and any phrases that were non-meaningful. Nonfluent, semantic, and healthy control participants only had difficulty repeating long, non-meaningful phrases. Poor repetition of long phrases was associated with cortical thinning in left temporo-parietal areas across all variants, highlighting the importance of these areas in avSTM. Finally, Bayles repetition phrases can assist classification in PPA, discriminating logopenic from nonfluent/semantic participants with 89% accuracy.

Cortical neurodevelopment in pre-manifest Huntington's disease

Background

The expression of the HTT CAG repeat expansion mutation causes neurodegeneration in Huntington's disease (HD). Objectives: In light of the – mainly in-vitro – evidence suggesting an additional role of huntingtin in neurodevelopment we used 3T MRI to test the hypothesis that in CAG-expanded individuals without clinical signs of HD (preHD) there is evidence for neurodevelopmental abnormalities.

Methods

We specifically investigated the complexity of cortical folding, a measure of cortical neurodevelopment, employing a novel method to quantify local fractal dimension (FD) measures that uses spherical harmonic reconstructions.

Results

The complexity of cortical folding differed at a group level between preHD (n = 57) and healthy volunteers (n = 57) in areas of the motor and visual system as well as temporal cortical areas. However, there was no association between the complexity of cortical folding and the loss in putamen volume that was clearly evident in preHD.

Conclusions

Our results suggest that HTT CAG repeat length may have an influence on cortical folding without evidence that this leads to developmental pathology or was clinically meaningful. This suggests that the HTT CAG-repeat expansion mutation may influence the processes governing cortical neurodevelopment; however, that influence seems independent of the events that lead to neurodegeneration.

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Measures of cortical neurodevelopment in preclinical Huntington's disease (HD) gene carriers differ from healthy volunteers

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The influence on cortical folding of the HD gene was not associated with developmental pathology or clinically meaningful

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The influence of the HD gene on cortical neurodevelopment may differ from that on neurodegeneration

Is treated HIV infection still toxic to the brain?

Clinically apparent HIV infection, accompanied by CNS opportunistic infections and HIV encephalopathy, was often associated with profound structural and functional brain effects prior to the introduction of anti-retroviral therapy (ART). With treatment, HIV structural and functional brain effects are smaller and have not been as easily detected. With near complete elimination of CNS opportunistic infections, the HIV neuroimaging research community now grapples with the problem of detecting subtler structural and functional changes against a background of persisting confounds, such as comorbidities and clinical features common in the HIV infected population. This situation also raises the question of whether imaging measure changes that are reported as HIV brain effects are purely related to viral infection, rather than originating from confounding effects that might include age, substance use, hepatitis C coinfection, cerebrovascular risk factors, ART, premorbid cognitive skills and illness duration. In addition to cohort characteristics, variation in image acquisition and analysis techniques may also contribute to study outcome heterogeneity. We review the potential effects of these confounds on detection of HIV infection effects and discuss strategies to avoid or mitigate the effects of these confounds. We then present a systematic approach to measurement, design and analysis in HIV neuroimaging studies, combining both experimental and statistical control techniques to determine if HIV infection effects persist, fluctuate or worsen in groups achieving viral suppression from ART.

Evaluation of the 3D fractal dimension as a marker of structural brain complexity in multiple-acquisition MRI

Fractal analysis represents a promising new approach to structural neuroimaging data, yet systematic evaluation of the fractal dimension (FD) as a marker of structural brain complexity is scarce. Here we present in-depth methodological assessment of FD estimation in structural brain MRI. On the computational side, we show that spatial scale optimization can significantly improve FD estimation accuracy, as suggested by simulation studies with known FD values. For empirical evaluation, we analyzed two recent open-access neuroimaging data sets (MASSIVE and Midnight Scan Club), stratified by fundamental image characteristics including registration, sequence weighting, spatial resolution, segmentation procedures, tissue type, and image complexity. Deviation analyses showed high repeated-acquisition stability of the FD estimates across both data sets, with differential deviation susceptibility according to image characteristics. While less frequently studied in the literature, FD estimation in T2-weighted images yielded robust outcomes. Importantly, we observed a significant impact of image registration on absolute FD estimates. Applying different registration schemes, we found that unbalanced registration induced (a) repeated-measurement deviation clusters around the registration target, (b) strong bidirectional correlations among image analysis groups, and (c) spurious associations between the FD and an index of structural similarity, and these effects were strongly attenuated by reregistration in both data sets. Indeed, differences in FD between scans did not simply track differences in structure per se, suggesting that structural complexity and structural similarity represent distinct aspects of structural brain MRI. In conclusion, scale optimization can improve FD estimation accuracy, and empirical FD estimates are reliable yet sensitive to image characteristics.

Volumetric and surface characteristics of gray matter in adult dyslexia and dyscalculia

Dyslexia, dyscalculia and their comorbid manifestation are prevalent disorders associated with well-documented behavioral manifestations. However, attempts to relate these manifestations to abnormalities in brain structure have yielded mixed results, with no clear consistency across a range of measures. In this study, we used a unique design including adults with dyslexia, dyscalculia, both disorders and controls, to explore differences in gray matter characteristics across groups. Specifically, we examined whether dyslexia, dyscalculia, or their comorbid manifestation could be related to volumetric and surface characteristics of gray matter, using voxel-based and surface-based morphometry. We demonstrate with Bayesian analyses that the present data favor the null model of no differences between groups across the brain, a result that is in line with recent findings in this field of research. Importantly, we provide detailed statistical maps to enable robust assessment of our findings, and to promote cumulative evaluation of the evidence. Together, these findings suggest that gray matter differences associated with dyslexia and dyscalculia might not be as reliable as suggested by previous literature, with important implications for our understanding of these disorders.

Aberrant cortical neurodevelopment in major depressive disorder

BACKGROUND

There is strong neuroimaging evidence that cortical alterations represent a core pathophysiological feature of major depressive disorder (MDD). Differential contributions of cortical features of neurodevelopmental origin, which may distinctly contribute to MDD vulnerability, disease-onset, or symptom expression, are unclear at present.

METHODS

We investigated distinct markers of cortical neurodevelopment, i.e. local cortical gyrification (LGI) and thickness (CT) in patients with MDD (n = 38) and healthy controls (HC, n = 22) using 3 T structural magnetic resonance imaging data and surface-based data analysis techniques. CT and LGI were computed using the Computational Anatomy Toolbox (CAT12). Analyses were performed for the entire cortical surface followed by a complementary regions-of-interest approach.

RESULTS

MDD patients showed significantly greater LGI in frontal, cingulate, parietal, temporal, and occipital regions compared to HC (FDR-corrected at p < 0.05 using threshold-free cluster enhancement). No significant differences of CT were found. In the MDD-group, correlations were found between duration of illness in years and number of depressive episodes and LGI of frontal, temporal, and parietal regions (p < 0.05).

LIMITATIONS

Main limitations are the relatively modest sample size and a cross-sectional study design. We did not control for early environmental factors potentially influencing neurodevelopment, such as childhood trauma. We report associations uncorrected for multiple comparisons.

CONCLUSIONS

The data suggest different local trajectories of cortical change in MDD. In addition, our data support the notion that aberrant cortical development may serve as a vulnerability marker of MDD, as well as a potential predictor of disease course.

The neurocognitive correlates of academic diligence in adolescent girls

Academic diligence is the ability to regulate behavior in the service of goals, and a predictor of educational attainment. Here we combined behavioral, structural MRI, functional MRI and connectivity data to investigate the neurocognitive correlates of diligence. We assessed whether individual differences in diligence are related to the interplay between frontal control and striatal reward systems, as predicted by the dual-systems hypothesis of adolescent development. We obtained behavioral measures of diligence from 40 adolescent girls (aged 14-15 years) using the Academic Diligence Task. We collected structural imaging data for each participant, as well as functional imaging data during an emotional go-no-go self-control task. As predicted by the dual-systems hypothesis, we found that inferior frontal activation and gyrification correlated with academic diligence. However, neither striatal activation nor structure, nor fronto-striatal connectivity, showed clear associations with diligence. Instead, we found prominent activation of temporal areas during the go-no-go task. This suggests that academic diligence is associated with an extended network of brain regions.

Acute and long-lasting cortical thickness changes following intensive first-person action videogame practice

Recent evidence shows how an extensive gaming experience might positively impact cognitive and perceptual functioning, leading to brain structural changes observed in cross-sectional studies. Importantly, changes seem to be game-specific, reflecting gameplay styles and therefore opening to the possibility of tailoring videogames according to rehabilitation and enhancement purposes. However, whether if such brain effects can be induced even with limited gaming experience, and whether if they can outlast the gaming period, is still unknown. Here we quantified both cognitive and grey matter thickness changes following 15 daily gaming sessions based on a modified version of a 3D first-person shooter (FPS) played in laboratory settings. Twenty-nine healthy participants were randomly assigned to a control or a gaming group and underwent a cognitive assessment, an in-game performance evaluation and structural magnetic resonance imaging before (T0), immediately after (T1) and three months after the end of the experiment (T2). At T1, a significant increase in thickness of the bilateral parahippocampal cortex (PHC), somatosensory cortex (S1), superior parietal lobule (SPL) and right insula were observed. Changes in S1 matched the hand representation bilaterally, while PHC changes corresponded to the parahippocampal place area (PPA). Surprisingly, changes in thickness were still present at T2 for S1, PHC, SPL and right insula as compared to T0. Finally, surface-based regression identified the lingual gyrus as the best predictor of changes in game performance at T1. Results stress the specific impact of core game elements, such as spatial navigation and visuomotor coordination on structural brain properties, with effects outlasting even a short intensive gaming period.

Neural signatures of co-occurring reading and mathematical difficulties

Impaired abilities in multiple domains is common in children with learning difficulties. Co-occurrence of low reading and mathematical abilities (LRLM) appears in almost every second child with learning difficulties. However, little is known regarding the neural bases of this combination. Leveraging a unique and tightly controlled sample including children with LRLM, isolated low reading ability (LR), and isolated low mathematical ability (LM), we uncover a distinct neural signature in children with co-occurring low reading and mathematical abilities differentiable from LR and LM. Specifically, we show that LRLM is neuroanatomically distinct from both LR and LM based on reduced cortical folding of the right parahippocampal gyrus, a medial temporal lobe region implicated in visual associative learning. LRLM children were further distinguished from LR and LM by patterns of intrinsic functional connectivity between parahippocampal gyrus and brain circuitry underlying reading and numerical quantity processing. Our results critically inform cognitive and neural models of LRLM by implicating aberrations in both domain-specific and domain-general brain regions involved in reading and mathematics. More generally, our results provide the first evidence for distinct multimodal neural signatures associated with LRLM, and suggest that this population displays an independent phenotype of learning difficulty that cannot be explained simply as a combination of isolated low reading and mathematical abilities.

Harmonic analysis of surface instability patterns on colloidal particles

Wrinkling of colloidal particles alter a wide variety of interfacial properties but quantitative topographical descriptions have been explored experimentally to a very limited extent. In this study, we present a harmonic analysis of surface wrinkles and folds on submicron colloidal particles, obtained using an aerosol flow route, with small radius (<300 nm) and high crust thickness-to-radius ratio (>0.1). The particle surface coordinates were mapped in their entirety using cryo-electron tomography and subsequently reconstructed using spherical harmonics, allowing a spectral topographical description of the instability patterns and the identification of their surface modes by lateral wavelength. Wrinkled and crumpled particles showed a similar surface roughness spectrum, wherein differences were found most noticeable in the large wavelength region. The analysis of preferred directions of harmonic frequencies indicated a possible axial or planar alignment attributed to the directionality of the surface corrugations. The employed characterization methodology can further the study of topographical influences on colloidal interactions.

Structural Covariance Network of Cortical Gyrification in Benign Childhood Epilepsy with Centrotemporal Spikes

Benign childhood epilepsy with centrotemporal spikes (BECTS) is associated with cognitive and language problems. According to recent studies, disruptions in brain structure and function in children with BECTS are beyond a Rolandic focus, suggesting atypical cortical development. However, previous studies utilizing surface-based metrics (e.g., cortical gyrification) and their structural covariance networks at high resolution in children with BECTS are limited. Twenty-six children with BECTS (15 males/11 females; 10.35 ± 2.91 years) and 26 demographically matched controls (15 males/11 females; 11.35 ± 2.51 years) were included in this study and subjected to high-resolution structural brain MRI scans. The gyrification index was calculated, and structural brain networks were reconstructed based on the covariance of the cortical folding. In the BECTS group, significantly increased gyrification was observed in the bilateral Sylvain fissures and the left pars triangularis, temporal, rostral middle frontal, lateral orbitofrontal, and supramarginal areas (cluster-corrected p < 0.05). Global brain network measures were not significantly different between the groups; however, the nodal alterations were most pronounced in the insular, frontal, temporal, and occipital lobes (FDR corrected, p < 0.05). In children with BECTS, brain hubs increased in number and tended to shift to sensorimotor and temporal areas. Furthermore, we observed significantly positive relationships between the gyrification index and age (vertex p < 0.001, cluster-level correction) as well as duration of epilepsy (vertex p < 0.001, cluster-level correction). Our results suggest that BECTS may be a condition that features abnormal over-folding of the Sylvian fissures and uncoordinated development of structural wiring, disrupted nodal profiles of centrality, and shifted hub distribution, which potentially represents a neuroanatomical hallmark of BECTS in the developing brain.

Differential Effects of the Factor Structure of the Wechsler Memory Scale-Revised on the Cortical Thickness and Complexity of Patients Aged Over 75 Years in a Memory Clinic Setting

The Wechsler Memory Scale-Revised (WMS-R) is one of the internationally well-known batteries for memory assessment in a general memory clinic setting. Several factor structures of the WMS-R for patients aged under 74 have been proposed. However, little is known about the factor structure of the WMS-R for patients aged over 75 years and its neurological significance. Thus, we conducted exploratory factor analysis to determine the factor structure of the WMS-R for patients aged over 75 years in a memory clinic setting. Regional cerebral blood flow (rCBF) was calculated from single-photon emission computed tomography data. Cortical thickness and cortical fractal dimension, as the marker of cortical complexity, were calculated from high resolution magnetic resonance imaging data. We found that the four factors appeared to be the most appropriate solution to the model, including recognition memory, paired associate memory, visual-and-working memory, and attention as factors. Patients with mild cognitive impairments showed significantly higher factor scores for paired associate memory, visual-and-working memory, and attention than patients with Alzheimer's disease. Regarding the neuroimaging data, the factor scores for paired associate memory positively correlated with rCBF in the left pericallosal and hippocampal regions. Moreover, the factor score for paired associate memory showed most robust correlations with the cortical thickness in the limbic system, whereas the factor score for attention correlated with the cortical thickness in the bilateral precuneus. Furthermore, each factor score correlated with the cortical fractal dimension in the bilateral frontotemporal regions. Interestingly, the factor scores for the visual-and-working memory and attention selectively correlated with the cortical fractal dimension in the right posterior cingulate cortex and right precuneus cortex, respectively. These findings demonstrate that recognition memory, paired associate memory, visual-and-working memory, and attention can be crucial factors for interpreting the WMS-R results of elderly patients aged over 75 years in a memory clinic setting. Considering these findings, the results of WMS-R in elderly patients aged over 75 years in a memory clinic setting should be cautiously interpreted.

Complexity analysis of cortical surface detects changes in future Alzheimer's disease converters

Alzheimer's disease (AD) is a neurological disorder that creates neurodegenerative changes at several structural and functional levels in human brain tissue. The fractal dimension (FD) is a quantitative parameter that characterizes the morphometric variability of the human brain. In this study, we investigate spherical harmonic-based FD (SHFD), thickness, and local gyrification index (LGI) to assess whether they identify cortical surface abnormalities toward the conversion to AD. We study 33 AD patients, 122 mild cognitive impairment (MCI) patients (50 MCI converters and 29 MCI nonconverters), and 32 healthy controls (HC). SHFD, thickness, and LGI methodology allowed us to perform not only global level but also local level assessments in each cortical surface vertex. First, we found that global SHFD decreased in AD and future MCI converters compared to HC, and in MCI converters compared to MCI nonconverters. Second, we found that local white matter SHFD was reduced in AD compared to HC and MCI mainly in medial temporal lobe. Third, local white-matter SHFD was significantly reduced in MCI converters compared to MCI nonconverters in distributed areas, including the medial frontal lobe. Thickness and LGI metrics presented a reduction in AD compared to HC. Thickness was significantly reduced in MCI converters compared to healthy controls in entorhinal cortex and lateral temporal. In summary, SHFD was the only surface measure showing differences between MCI individuals that will convert or remain stable in the next 4 years. We suggest that SHFD may be an optimal complement to thickness loss analysis in monitoring longitudinal changes in preclinical and clinical stages of AD. Hum Brain Mapp 38:5905-5918, 2017. © 2017 Wiley Periodicals, Inc.

Twin SVM-Based Classification of Alzheimer's Disease Using Complex Dual-Tree Wavelet Principal Coefficients and LDA

Alzheimer's disease (AD) is a leading cause of dementia, which causes serious health and socioeconomic problems. A progressive neurodegenerative disorder, Alzheimer's causes the structural change in the brain, thereby affecting behavior, cognition, emotions, and memory. Numerous multivariate analysis algorithms have been used for classifying AD, distinguishing it from healthy controls (HC). Efficient early classification of AD and mild cognitive impairment (MCI) from HC is imperative as early preventive care could help to mitigate risk factors. Magnetic resonance imaging (MRI), a noninvasive biomarker, displays morphometric differences and cerebral structural changes. A novel approach for distinguishing AD from HC using dual-tree complex wavelet transforms (DTCWT), principal coefficients from the transaxial slices of MRI images, linear discriminant analysis, and twin support vector machine is proposed here. The prediction accuracy of the proposed method yielded up to 92.65 ± 1.18 over the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, with a specificity of 92.19 ± 1.56 and sensitivity of 93.11 ± 1.29, and 96.68 ± 1.44 over the Open Access Series of Imaging Studies (OASIS) dataset, with a sensitivity of 97.72 ± 2.34 and specificity of 95.61 ± 1.67. The accuracy, sensitivity, and specificity achieved using the proposed method are comparable or superior to those obtained by various conventional AD prediction methods.

Cortical Surface Thickness in the Middle-Aged Brain with White Matter Hyperintense Lesions

Background and purpose: Previous voxel-based morphometry (VBM) studies have suggested that cortical atrophy is regionally distributed in middle-aged subjects with white matter hyperintense (WMH) lesions. However, few studies have assessed cortical thickness in middle-aged WMH subjects. In this study, we examined cortical thickness as well as cortical morphometry associated with the presence of WMH lesion load in middle-aged subjects. Participants and methods: Thirty-six middle-aged subjects with WMH lesions (WMH group) and without clinical cognitive impairment, and 34 demographically matched healthy control subjects (HCS group) participated in the study. Cortical thickness was estimated using an automated Computational Anatomy Toolbox (CAT12) as the distance between the gray-white matter border and the pial surface. Individual WMH lesions were manually segmented, and WMH loads were measured. Statistical cortical maps were created to estimate differences in cortical thickness between groups based on this cortex-wide analysis. The relationship between WMH lesion loads and cerebral cortical thickness was also analyzed in CAT12. Results: Cortical thickness was significantly lower in the WMH group than in the controls in multimodal integration regions, including the right and left dorsal anterior cingulate cortex (dACC), right and left frontal operculum (fO), right and left operculum parietale (OP), right and left middle temporal gyrus (MTG), and left superior temporal gyrus (STG; P < 0.01, family-wise error (FWE)-corrected). Additionally, cortical thickness was also lower in the recognition regions that contained the right temporal pole (TP), the right and left fusiform gyrus, and the left rolandic operculum (RO; P < 0.01, FWE-corrected). The results revealed that in the left superior parietal lobule (SPL), cortical thickness was higher in the WMH group than in the HCS group (P < 0.01, FWE-corrected). A voxel-wise negative correlation was found between cortical thickness and WMH lesion loads in the right orbitofrontal cortex (OFC), right dorsolateral prefrontal cortex (DLPFC), and right subcallosal cortex (P < 0.01, FWE-corrected). Conclusion: The main findings of this study suggest that middle-aged WMH subjects are more likely to exhibit cortical thinning, especially in multimodal integration and recognition- and motor-related regions. The current morphometry data provide further evidence for WMH-associated structural plasticity.

Test-retest reliability of brain morphology estimates

Metrics of brain morphology are increasingly being used to examine inter-individual differences, making it important to evaluate the reliability of these structural measures. Here we used two open-access datasets to assess the intersession reliability of three cortical measures (thickness, gyrification, and fractal dimensionality) and two subcortical measures (volume and fractal dimensionality). Reliability was generally good, particularly with the gyrification and fractal dimensionality measures. One dataset used a sequence previously optimized for brain morphology analyses and had particularly high reliability. Examining the reliability of morphological measures is critical before the measures can be validly used to investigate inter-individual differences.

Cortical complexity in bipolar disorder applying a spherical harmonics approach

Recent studies using surface-based morphometry of structural magnetic resonance imaging data have suggested that some changes in bipolar disorder (BP) might be neurodevelopmental in origin. We applied a novel analysis of cortical complexity based on fractal dimensions in high-resolution structural MRI scans of 18 bipolar disorder patients and 26 healthy controls. Our region-of-interest based analysis revealed increases in fractal dimensions (in patients relative to controls) in left lateral orbitofrontal cortex and right precuneus, and decreases in right caudal middle frontal, entorhinal cortex, and right pars orbitalis, and left fusiform and posterior cingulate cortices. While our analysis is preliminary, it suggests that early neurodevelopmental pathologies might contribute to bipolar disorder, possibly through genetic mechanisms.

Kernel Methods for Riemannian Analysis of Robust Descriptors of the Cerebral Cortex

Typical cerebral cortical analyses rely on spatial normalization and are sensitive to misregistration arising from partial homologies between subject brains and local optima in nonlinear registration. In contrast, we use a descriptor of the 3D cortical sheet (jointly modeling folding and thickness) that is robust to misregistration. Our histogram-based descriptor lies on a Riemannian manifold. We propose new regularized nonlinear methods for (i) detecting group differences, using a Mercer kernel with an implicit lifting map to a reproducing kernel Hilbert space, and (ii) regression against clinical variables, using kernel density estimation. For both methods, we employ kernels that exploit the Riemannian structure. Results on simulated and clinical data shows the improved accuracy and stability of our approach in cortical-sheet analysis.

Age-related differences in the structural complexity of subcortical and ventricular structures

It has been well established that the volume of several subcortical structures decreases in relation to age. Different metrics of cortical structure (e.g., volume, thickness, surface area, and gyrification) have been shown to index distinct characteristics of interindividual differences; thus, it is important to consider the relation of age to multiple structural measures. Here, we compare age-related differences in subcortical and ventricular volume to those differences revealed with a measure of structural complexity, quantified as fractal dimensionality. Across 3 large data sets, totaling nearly 900 individuals across the adult lifespan (aged 18-94 years), we found greater age-related differences in complexity than volume for the subcortical structures, particularly in the caudate and thalamus. The structural complexity of ventricular structures was not more strongly related to age than volume. These results demonstrate that considering shape-related characteristics improves sensitivity to detect age-related differences in subcortical structures.

Fractal Dimension Analysis of Subcortical Gray Matter Structures in Schizophrenia

A failure of adaptive inference—misinterpreting available sensory information for appropriate perception and action—is at the heart of clinical manifestations of schizophrenia, implicating key subcortical structures in the brain including the hippocampus. We used high-resolution, three-dimensional (3D) fractal geometry analysis to study subtle and potentially biologically relevant structural alterations (in the geometry of protrusions, gyri and indentations, sulci) in subcortical gray matter (GM) in patients with schizophrenia relative to healthy individuals. In particular, we focus on utilizing Fractal Dimension (FD), a compact shape descriptor that can be computed using inputs with irregular (i.e., not necessarily smooth) surfaces in order to quantify complexity (of geometrical properties and configurations of structures across spatial scales) of subcortical GM in this disorder. Probabilistic (entropy-based) information FD was computed based on the box-counting approach for each of the seven subcortical structures, bilaterally, as well as the brainstem from high-resolution magnetic resonance (MR) images in chronic patients with schizophrenia (n = 19) and age-matched healthy controls (n = 19) (age ranges: patients, 22.7–54.3 and healthy controls, 24.9–51.6 years old). We found a significant reduction of FD in the left hippocampus (median: 2.1460, range: 2.07–2.18 vs. median: 2.1730, range: 2.15–2.23, p<0.001; Cohen’s effect size, U3 = 0.8158 (95% Confidence Intervals, CIs: 0.6316, 1.0)), the right hippocampus (median: 2.1430, range: 2.05–2.19 vs. median: 2.1760, range: 2.12–2.21, p = 0.004; U3 = 0.8421 (CIs: 0.5263, 1)), as well as left thalamus (median: 2.4230, range: 2.40–2.44, p = 0.005; U3 = 0.7895 (CIs: 0.5789, 0.9473)) in schizophrenia patients, relative to healthy individuals. Our findings provide in-vivo quantitative evidence for reduced surface complexity of hippocampus, with reduced FD indicating a less complex, less regular GM surface detected in schizophrenia.

Development of cortical shape in the human brain from 6 to 24months of age via a novel measure of shape complexity

The quantification of local surface morphology in the human cortex is important for examining population differences as well as developmental changes in neurodegenerative or neurodevelopmental disorders. We propose a novel cortical shape measure, referred to as the 'shape complexity index' (SCI), that represents localized shape complexity as the difference between the observed distributions of local surface topology, as quantified by the shape index (SI) measure, to its best fitting simple topological model within a given neighborhood. We apply a relatively small, adaptive geodesic kernel to calculate the SCI. Due to the small size of the kernel, the proposed SCI measure captures fine differences of cortical shape. With this novel cortical feature, we aim to capture comparatively small local surface changes that capture a) the widening versus deepening of sulcal and gyral regions, as well as b) the emergence and development of secondary and tertiary sulci. Current cortical shape measures, such as the gyrification index (GI) or intrinsic curvature measures, investigate the cortical surface at a different scale and are less well suited to capture these particular cortical surface changes. In our experiments, the proposed SCI demonstrates higher complexity in the gyral/sulcal wall regions, lower complexity in wider gyral ridges and lowest complexity in wider sulcal fundus regions. In early postnatal brain development, our experiments show that SCI reveals a pattern of increased cortical shape complexity with age, as well as sexual dimorphisms in the insula, middle cingulate, parieto-occipital sulcal and Broca's regions. Overall, sex differences were greatest at 6months of age and were reduced at 24months, with the difference pattern switching from higher complexity in males at 6months to higher complexity in females at 24months. This is the first study of longitudinal, cortical complexity maturation and sex differences, in the early postnatal period from 6 to 24months of age with fine scale, cortical shape measures. These results provide information that complement previous studies of gyrification index in early brain development.

Cortical complexity as a measure of age-related brain atrophy

The structure of the human brain changes in a variety of ways as we age. While a sizeable literature has examined age-related differences in cortical thickness, and to a lesser degree, gyrification, here we examined differences in cortical complexity, as indexed by fractal dimensionality in a sample of over 400 individuals across the adult lifespan. While prior studies have shown differences in fractal dimensionality between patient populations and age-matched, healthy controls, it is unclear how well this measure would relate to age-related cortical atrophy. Initially computing a single measure for the entire cortical ribbon, i.e., unparcellated gray matter, we found fractal dimensionality to be more sensitive to age-related differences than either cortical thickness or gyrification index. We additionally observed regional differences in age-related atrophy between the three measures, suggesting that they may index distinct differences in cortical structure. We also provide a freely available MATLAB toolbox for calculating fractal dimensionality.

Fractals in the Neurosciences, Part II

It has been ascertained that the human brain is a complex system studied at multiple scales, from neurons and microcircuits to macronetworks. The brain is characterized by a hierarchical organization that gives rise to its highly topological and functional complexity. Over the last decades, fractal geometry has been shown as a universal tool for the analysis and quantification of the geometric complexity of natural objects, including the brain. The fractal dimension has been identified as a quantitative parameter for the evaluation of the roughness of neural structures, the estimation of time series, and the description of patterns, thus able to discriminate different states of the brain in its entire physiopathological spectrum. Fractal-based computational analyses have been applied to the neurosciences, particularly in the field of clinical neurosciences including neuroimaging and neuroradiology, neurology and neurosurgery, psychiatry and psychology, and neuro-oncology and neuropathology. After a review of the basic concepts of fractal analysis and its main applications to the basic neurosciences in part I of this series, here, we review the main applications of fractals to the clinical neurosciences for a holistic approach towards a fractal geometry model of the brain.