Cortical surface complexity in frontal and temporal areas varies across subgroups of schizophrenia

A new transfer entropy method for measuring directed connectivity from complex-valued fMRI data

Background

Inferring directional connectivity of brain regions from functional magnetic resonance imaging (fMRI) data has been shown to provide additional insights into predicting mental disorders such as schizophrenia. However, existing research has focused on the magnitude data from complex-valued fMRI data without considering the informative phase data, thus ignoring potentially important information.

Methods

We propose a new complex-valued transfer entropy (CTE) method to measure causal links among brain regions in complex-valued fMRI data. We use the transfer entropy to model a general non-linear magnitude-magnitude and phase-phase directed connectivity and utilize partial transfer entropy to measure the complementary phase and magnitude effects on magnitude-phase and phase-magnitude causality. We also define the significance of the causality based on a statistical test and the shuffling strategy of the two complex-valued signals.

Results

Simulated results verified higher accuracy of CTE than four causal analysis methods, including a simplified complex-valued approach and three real-valued approaches. Using experimental fMRI data from schizophrenia and controls, CTE yields results consistent with previous findings but with more significant group differences. The proposed method detects new directed connectivity related to the right frontal parietal regions and achieves 10.2-20.9% higher SVM classification accuracy when inferring directed connectivity using anatomical automatic labeling (AAL) regions as features.

Conclusion

The proposed CTE provides a new general method for fully detecting highly predictive directed connectivity from complex-valued fMRI data, with magnitude-only fMRI data as a specific case.

White matter integrity in bipolar disorder investigated with diffusion tensor magnetic resonance imaging and fractal geometry

BACKGROUND

Growing evidence suggests the presence of white matter (WM) alterations in bipolar disorder (BD). In this study we aimed to investigate the state of WM structures, in terms of tissue integrity and morphological complexity, in BD patients compared to healthy controls (HC), in an attempt to better elucidate the microstructural changes associated with BD.

METHODS

We collected a dataset of 399 Diffusion Tensor Magnetic Resonance Imaging (167 BD and 232 healthy controls) images, acquired at five different sites, which was processed with Tract-Based Spatial Statistics (TBSS) and fractal analysis.

RESULTS

The TBSS analysis demonstrated significantly lower FA values in the BD group. Diffusion abnormalities were primarily located in the temporo-parietal network. The Fractal Dimension (FD) analysis did not reveal consistent significant differences in the morphological complexity of WM structures between the groups. When the FD values of patients were considered individually, it is possible to notice some localized significant deviations from the healthy population.

LIMITATIONS

DTI sequences have not been harmonized before acquisition, samples' sizes are heterogeneous.

CONCLUSIONS

This study, by applying both TBSS and FD analyses, allows to evaluate diffusion and structural alterations of WM at the same time. The evaluation of WM integrity from these two different perspectives could be useful to better understand the pathophysiological and morphological changes underpinning bipolar disorder.

Fractal Dimension Studies of the Brain Shape in Aging and Neurodegenerative Diseases

The fractal dimension is a morphometric measure that has been used to investigate the changes of brain shape complexity in aging and neurodegenerative diseases. This chapter reviews fractal dimension studies in aging and neurodegenerative disorders in the literature. Research has shown that the fractal dimension of the left cerebral hemisphere increases until adolescence and then decreases with aging, while the fractal dimension of the right hemisphere continues to increase until adulthood. Studies in neurodegenerative diseases demonstrated a decline in the fractal dimension of the gray matter and white matter in Alzheimer's disease, amyotrophic lateral sclerosis, and spinocerebellar ataxia. In multiple sclerosis, the white matter fractal dimension decreases, but conversely, the fractal dimension of the gray matter increases at specific stages of disease. There is also a decline in the gray matter fractal dimension in frontotemporal dementia and multiple system atrophy of the cerebellar type and in the white matter fractal dimension in epilepsy and stroke. Region-specific changes in fractal dimension have also been found in Huntington's disease and Parkinson's disease. Associations were found between the fractal dimension and clinical scores, showing the potential of the fractal dimension as a marker to monitor brain shape changes in normal or pathological processes and predict cognitive or motor function.

Diffuse glioma-induced structural reorganization in close association with preexisting syntax-related networks

Glioma in the left frontal cortex has been reported to cause agrammatic comprehension and induce global functional connectivity alterations within the syntax-related networks. However, it remains unclear to what extent the structural reorganization is affected by preexisting syntax-related networks. We examined 28 patients with a diffuse glioma in the left hemisphere and 23 healthy participants. Syntactic abilities were assessed by a picture-sentence matching task with various sentence types. The lesion responsible for agrammatic comprehension was identified by region-of-interest-based lesion-symptom mapping (RLSM). Cortical structural alterations were examined by surface-based morphometry (SBM), in which the cortical thickness and fractal dimension were measured with three-dimensional magnetic resonance imaging (MRI). Fiber tracking on the human population-averaged diffusion MRI template was performed to examine whether the cortical structural alterations were associated with the syntax-related networks. The RLSM revealed associations between agrammatic comprehension and a glioma in the posterior limb of the left internal capsule. The SBM demonstrated that decreased cortical thickness and/or increased complexity of the right posterior insula were associated not only with agrammatic comprehension of the patients but also with the syntactic abilities of healthy participants. The fiber tracking revealed that the route between these two regions was anatomically integrated into the preexisting syntax-related networks previously identified. These results suggest a potential association between agrammatic comprehension in patients with diffuse glioma and structural variations in specific tracts and cortical regions, which may be closely related to the syntax-related networks.

Less cortical complexity in ventromedial prefrontal cortex is associated with a greater preference for risky and immediate rewards

In our everyday lives, we are often faced with situations in which we have to make choices that involve risky or delayed rewards. However, the extent to which we are willing to accept larger risky (over smaller certain) or larger delayed (over smaller immediate) rewards vary across individuals. Here we investigated the relationship between cortical surface complexity in medial prefrontal cortex and individual differences in risky and intertemporal preferences. We found that lower cortical complexity in ventromedial prefrontal cortex (vmPFC) was associated with a greater preference for risky and immediate rewards. In addition to these common structural associations in mPFC, we also found associations between lower cortical complexity and a greater preference for immediate rewards that extended into left dorsomedial prefrontal cortex and right vmPFC. Taken together, the shared association suggests that lower cortical complexity in vmPFC may be a structural marker for individual differences in impulsive behavior.

Age-associated sex and asymmetry differentiation in hemispheric and lobar cortical ribbon complexity across adulthood: A UK Biobank imaging study

Cortical morphology changes with ageing and age-related neurodegenerative diseases. Previous studies suggest that the age effect is more pronounced in the frontal lobe. However, our knowledge of structural complexity changes in male and female brains is still limited. We measured cortical ribbon complexity through fractal dimension (FD) analysis at the hemisphere and lobe level in 7010 individuals from the UK Biobank imaging cohort to study age-related sex differences (3332 males, age ranged 45-79 years). FD decreases significantly with age and sexual dimorphism exists. With correction for brain size, females showed higher complexity in the left hemisphere and left and right parietal lobes whereas males showed higher complexity in the right temporal and left and right occipital lobes. A nonlinear age effect was observed in the left and right frontal, and right temporal lobes. Differential patterns of age effects were observed in both sexes with relatively more age-affected regions in males. Significantly higher rightward asymmetries at hemisphere, frontal, parietal, and occipital lobe level and higher leftward asymmetry in temporal lobe were observed. There was no age-by-sex-by asymmetry interaction in any region. When controlling for brain size, the leftward hemispheric, and temporal lobe asymmetry decreased with age. Males had significantly lower asymmetry between hemispheres and higher asymmetry in the parietal and occipital lobes than females. This work provides distinct patterns of age-related sex and asymmetry differences that can aid in the future development of sex-specific models of the normal brain to ascribe cognitive functional significance of these patterns in ageing.

Mendelian randomization analyses support causal relationships between brain imaging-derived phenotypes and risk of psychiatric disorders

Observational studies have reported the correlations between brain imaging-derived phenotypes (IDPs) and psychiatric disorders; however, whether the relationships are causal is uncertain. We conducted bidirectional two-sample Mendelian randomization (MR) analyses to explore the causalities between 587 reliable IDPs (N = 33,224 individuals) and 10 psychiatric disorders (N = 9,725 to 161,405). We identified nine IDPs for which there was evidence of a causal influence on risk of schizophrenia, anorexia nervosa and bipolar disorder. For example, 1 s.d. increase in the orientation dispersion index of the forceps major was associated with 32% lower odds of schizophrenia risk. Reverse MR indicated that only genetically predicted schizophrenia was positively associated with two IDPs, the cortical surface area and the volume of the right pars orbitalis. We established the BrainMR database ( http://www.bigc.online/BrainMR/ ) to share our results. Our findings provide potential strategies for the prediction and intervention for psychiatric disorder risk at the brain-imaging level.

Prognostic associations of cortical gyrification in minimally medicated schizophrenia in an early intervention setting

The aberration in cortical gyrification seen in schizophrenia likely originates in the earliest phase of life, as gyrification begins in utero and reaches its peak in infancy. However, emerging observations have indicated a later reduction in gyrification, especially in early adulthood, may also occur in schizophrenia. At present, it is unclear whether the baseline and later gyrification reduction has any prognostic importance in schizophrenia. We address this question in a longitudinal design in patients minimally medicated at inception. About 108 minimally medicated (duration of medication = <14 days of antipsychotics) patients and 106 healthy controls underwent structural magnetic resonance imaging, with 34 patients being selectively re-scanned when clinically stable following antipsychotic treatment. The cortical surface from each structural image was reconstructed, and the local gyrification index and cortical thickness were computed for each vertex on the surface. We found minimally medicated schizophrenia patients during the first episode had a relatively higher gyrification in bilateral supramarginal, left superior temporal, and right posterior cingulate and paracentral regions. However, poor prognostic features were more likely in patients with lower baseline gyrification. Longitudinal reductions in left superior parietal and right precentral gyrification were associated with lower improvements in both positive and negative symptoms over time. The spatial pattern of longitudinal changes in gyrification was distinct from the changes in cortical thickness. These results indicated that schizophrenia is characterized by a relative hypergyrification in parieto-temporal and medial cortical areas at a group level at first presentation, but poor outcomes relate to lower-gyrification elsewhere both at the onset and during the early course. The early post-onset reduction of gyrification is rather limited in space and magnitude, but occurs unrelated to the progressive thinning, representing a distinct, prognostically important structural trajectory.

Using fractal dimension analysis to assess the effects of normal aging and sex on subregional cortex alterations across the lifespan from a Chinese dataset

Fractal dimension (FD) is used to quantify brain structural complexity and is more sensitive to morphological variability than other cortical measures. However, the effects of normal aging and sex on FD are not fully understood. In this study, age- and sex-related differences in FD were investigated in a sample of 448 adults age of 19–80 years from a Chinese dataset. The FD was estimated with the surface-based morphometry (SBM) approach, sex differences were analyzed on a vertex level, and correlations between FD and age were examined. Generalized additive models (GAMs) were used to characterize the trajectories of age-related changes in 68 regions based on the Desikan–Killiany atlas. The SBM results showed sex differences in the entire sample and 3 subgroups defined by age. GAM results demonstrated that the FD values of 51 regions were significantly correlated with age. The trajectories of changes can be classified into 4 main patterns. Our results indicate that sex differences in FD are evident across developmental stages. Age-related trajectories in FD are not homogeneous across the cerebral cortex. Our results extend previous findings and provide a foundation for future investigation of the underlying mechanism.

Sexual dimorphism in the relationship between brain complexity, volume and general intelligence (g): a cross-cohort study

Changes in brain morphology have been reported during development, ageing and in relation to different pathologies. Brain morphology described by the shape complexity of gyri and sulci can be captured and quantified using fractal dimension (FD). This measure of brain structural complexity, as well as brain volume, are associated with intelligence, but less is known about the sexual dimorphism of these relationships. In this paper, sex differences in the relationship between brain structural complexity and general intelligence (g) in two diverse geographic and cultural populations (UK and Indian) are investigated. 3D T1-weighted magnetic resonance imaging (MRI) data and a battery of cognitive tests were acquired from participants belonging to three different cohorts: Mysore Parthenon Cohort (MPC); Aberdeen Children of the 1950s (ACONF) and UK Biobank. We computed MRI derived structural brain complexity and g estimated from a battery of cognitive tests for each group. Brain complexity and volume were both positively corelated with intelligence, with the correlations being significant in women but not always in men. This relationship is seen across populations of differing ages and geographical locations and improves understanding of neurobiological sex-differences.

Longitudinal study of the effect of a 5-year exercise intervention on structural brain complexity in older adults. A Generation 100 substudy

Physical inactivity has been identified as an important risk factor for dementia. High levels of cardiorespiratory fitness (CRF) have been shown to reduce the risk of dementia. However, the mechanism by which exercise affects brain health is still debated. Fractal dimension (FD) is an index that quantifies the structural complexity of the brain. The purpose of this study was to investigate the effects of a 5-year exercise intervention on the structural complexity of the brain, measured through the FD, in a subset of 105 healthy older adults participating in the randomized controlled trial Generation 100 Study. The subjects were randomized into control, moderate intensity continuous training, and high intensity interval training groups. Both brain MRI and CRF were acquired at baseline and at 1-, 3- and 5-years follow-ups. Cortical thickness and volume data were extracted with FreeSurfer, and FD of the cortical lobes, cerebral and cerebellar gray and white matter were computed. CRF was measured as peak oxygen uptake (VO_2peak) using ergospirometry during graded maximal exercise testing. Linear mixed models were used to investigate exercise group differences and possible CRF effects on the brain's structural complexity. Associations between change over time in CRF and FD were performed if there was a significant association between CRF and FD. There were no effects of group membership on the structural complexity. However, we found a positive association between CRF and the cerebral gray matter FD (p < 0.001) and the temporal lobe gray matter FD (p < 0.001). This effect was not present for cortical thickness, suggesting that FD is a more sensitive index of structural changes. The change over time in CRF was associated with the change in temporal lobe gray matter FD from baseline to 5-year follow-up (p < 0.05). No association of the change was found between CRF and cerebral gray matter FD. These results demonstrated that entering old age with high and preserved CRF levels protected against loss of structural complexity in areas sensitive to aging and age-related pathology.

Cortical Complexity Estimation Using Fractal Dimension: A Systematic Review of the Literature on Clinical and Nonclinical Samples

Fractal geometry has recently been proposed as a useful tool for characterizing the complexity of the brain cortex, which is likely to derive from the recurrence of sulci–gyri convolution patterns. The index used to describe the cortical complexity is called fractal dimensional (FD) and was employed by different research exploring the neurobiological correlates of distinct pathological and nonpathological conditions. This review aims to describe the literature on the application of this index, summarize the heterogeneities between studies and inform future research on this topic. Sixty‐two studies were included in the systematic review. The main research lines concern neurodevelopment, aging and the neurobiology of specific psychiatric and neurological disorders. Overall, the included papers indicate that cortical complexity is likely to reduce during aging and in various pathological processes affecting the brain. Nevertheless, the high heterogeneity between studies strongly prevents the possibility of drawing conclusions. Further research considering this index besides other morphological values is needed to better clarify the role of FD in characterizing the cortical structure.

Fractal dimension (FD) is a useful tool for the assessment of cortical complexity. In healthy controls, FD is associated with development, aging and cognition. Alterations in FD have been observed in different neurological and psychiatric disorders.

Brain structural correlates of schizotypal signs and subclinical schizophrenia nuclear symptoms in healthy individuals

BACKGROUND

Subclinical psychotic-like experiences (PLE), resembling key symptoms of psychotic disorders, are common throughout the general population and possibly associated with psychosis risk. There is evidence that such symptoms are also associated with structural brain changes.

METHODS

In 672 healthy individuals, we assessed PLE and associated distress with the symptom-checklist-90R (SCL-90R) scales 'schizotypal signs' (STS) and 'schizophrenia nuclear symptoms' (SNS) and analysed associations with voxel- and surfaced-based brain structural parameters derived from structural magnetic resonance imaging at 3 T with CAT12.

RESULTS

For SNS, we found a positive correlation with the volume in the left superior parietal lobule and the precuneus, and a negative correlation with the volume in the right inferior temporal gyrus [p < 0.05 cluster-level Family Wise Error (FWE-corrected]. For STS, we found a negative correlation with the volume of the left and right precentral gyrus (p < 0.05 cluster-level FWE-corrected). Surface-based analyses did not detect any significant clusters with the chosen statistical threshold of p < 0.05. However, in exploratory analyses (p < 0.001, uncorrected), we found a positive correlation of SNS with gyrification in the left insula and rostral middle frontal gyrus and of STS with the left precuneus and insula, as well as a negative correlation of STS with gyrification in the left temporal pole.

CONCLUSIONS

Our results show that brain structures in areas implicated in schizophrenia are also related to PLE and its associated distress in healthy individuals. This pattern supports a dimensional model of the neural correlates of symptoms of the psychotic spectrum.

Cortical complexity in world trade center responders with chronic posttraumatic stress disorder

Approximately 23% of World Trade Center (WTC) responders are experiencing chronic posttraumatic stress disorder (PTSD) associated with their exposures at the WTC following the terrorist attacks of 9/11/2001, which has been demonstrated to be a risk factor for cognitive impairment raising concerns regarding their brain health. Cortical complexity, as measured by analyzing Fractal Dimension (FD) from T1 MRI brain images, has been reported to be reduced in a variety of psychiatric and neurological conditions. In this report, we hypothesized that FD would be also reduced in a case-control sample of 99 WTC responders as a result of WTC-related PTSD. The results of our surface-based morphometry cluster analysis found alterations in vertex clusters of complexity in WTC responders with PTSD, with marked reductions in regions within the frontal, parietal, and temporal cortices, in addition to whole-brain absolute bilateral and unilateral complexity. Furthermore, region of interest analysis identified that the magnitude of changes in regional FD severity was associated with increased PTSD symptoms (reexperiencing, avoidance, hyperarousal, negative affect) severity. This study confirms prior findings on FD and psychiatric disorders and extends our understanding of FD associations with posttraumatic symptom severity. The complex and traumatic experiences that led to WTC-related PTSD were associated with reductions in cortical complexity. Future work is needed to determine whether reduced cortical complexity arose prior to, or concurrently with, onset of PTSD.

Changes of cerebral cortical structure and cognitive dysfunction in "healthy hemisphere" after stroke: a study about cortical complexity and sulcus patterns in bilateral ischemic adult moyamoya disease

Background

Moyamoya disease (MMD) is an uncommon cerebrovascular disease which leads to progressive stenosis and occlusion of the bilateral internal carotid artery and main intracerebral arteries. Concerns are always on how the hemisphere with infarction affects cognitive function, while little attention is paid to the role that the non-infarcted hemisphere plays. Therefore, we aimed to detect cortical indexes, especially cortical complexity in the left or right hemisphere separately in patients with MMD after stroke.

Methods

28 patients with MMD (14 males, 14 females) and 14 healthy controls were included in this study. All participants underwent cognitive tests and magnetic resonance imaging (MRI) scan. The preprocessing of three-dimensional T1 weighted images were performed by standard surface-based morphometry. Surface-based morphometry statistical analysis was carried out with a threshold of False Discovery Rate (FDR) P < 0.05 and fractal dimension (FD) was used to provide a quantitative description of cerebral cortical complexity.

Results

Widespread cognitive dysfunctions were found in MMD patient with stroke. Extensive FD reduction in the left hemisphere with right-sided infarction, mainly in the superior temporal, inferior frontal, and insula, while the post central gyrus, superior parietal, and inferior parietal gyrus also showed a wide range of significant differences (FDR corrected P < 0.05). Meanwhile, FD changes in the right hemisphere with left-sided infarction are restricted to the precuneus and cingulate isthmus (FDR corrected P < 0.05).

Conclusions

Extensive cognitive impairment was reconfirmed in Moyamoya disease with stroke, while wild and asymmetrical decrease of cortical complexity is observed on both sides. These differences could be relative to unbalanced cognitive dysfunction, and may be the result of a long-term chronic ischemia and compensatory of the contralateral hemisphere to the infarction.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12868-021-00672-x.

Association of altered cortical gyrification and psychopathological symptoms in patients with first-episode drug-naïve schizophrenia

Altered brain gyrification in diverse cortical regions has been reported in patients with schizophrenia, which possibly reflects deviations in early neurodevelopment. The main purpose of this study was to examine the relationship between clinical symptoms and abnormal cortical gyrification in drug-naïve patients with schizophrenia in a Chinese Han population. We calculated the whole-brain cortical gyrification of 41 patients with first-episode drug-naïve schizophrenia and 30 age- and sex-matched healthy controls. The Positive and Negative Syndrome Scale (PANSS) was used to evaluate the psychopathology of patients with schizophrenia. Our results showed that compared to healthy controls, patients had higher cortical gyrification in the left lateral occipital cortex, but lower cortical gyrification in the left transverse temporal cortex. Moreover, the cortical gyrification in the left entorhinal cortex and left fusiform were both positively correlated with the general psychopathology of PANSS. Our findings indicate that abnormal cortical gyrification has occurred in the early stage of schizophrenia, suggesting that abnormal cortical gyrification may play an important role in the pathogenesis and symptomatology of schizophrenia.

Differential Effects of a Left Frontal Glioma on the Cortical Thickness and Complexity of Both Hemispheres

Glioma is a type of brain tumor that infiltrates and compresses the brain as it grows. Focal gliomas affect functional connectivity both in the local region of the lesion and the global network of the brain. Any anatomical changes associated with a glioma should thus be clarified. We examined the cortical structures of 15 patients with a glioma in the left lateral frontal cortex and compared them with those of 15 healthy controls by surface-based morphometry. Two regional parameters were measured with 3D-MRI: the cortical thickness (CT) and cortical fractal dimension (FD). The FD serves as an index of the topological complexity of a local cortical surface. Our comparative analyses of these parameters revealed that the left frontal gliomas had global effects on the cortical structures of both hemispheres. The structural changes in the right hemisphere were mainly characterized by a decrease in CT and mild concomitant decrease in FD, whereas those in the peripheral regions of the glioma (left hemisphere) were mainly characterized by a decrease in FD with relative preservation of CT. These differences were found irrespective of tumor volume, location, or grade. These results elucidate the structural effects of gliomas, which extend to the distant contralateral regions.

Cortical complexity and gyrification patterns in Parkinson's disease

This study aimed to investigate the cortical complexity and gyrification patterns in Parkinson's disease (PD) using local fractional dimension (LFD) and local gyrification index (LGI), respectively. In a cross-sectional study, LFD and LGI in 60 PD patients without dementia and 56 healthy controls (HC) were investigated using brain structural MRI data. LFD and LGI were estimated using the Computational Anatomy Toolbox (CAT12) and statistically analyzed between groups on a vertex level using statistical parametric mapping 12 (SPM12). Additionally, correlations between structural changes and clinical indices were further examined. PD patients showed widespread LFD reductions mainly in the left pre- and postcentral cortex, the left superior frontal cortex, the left caudal middle frontal cortex, the bilaterally superior parietal cortex and the right superior temporal cortex compared to HC. For LGI, there was no significant difference between PD and HC. In PD patients group, a significant negative correlation was found between LFD of the left postcentral cortex and duration of illness (DOI). Our results of widespread LFD reductions, but not LGI, indicate that LFD may provide a more sensitive diagnostic biomarker and encode specific information of PD. The significant negative correlation between LFD of the left postcentral cortex and DOI suggests that LFD may be a biomarker to monitor disease progression in PD.

Surface-based Cortical Morphometry, White Matter Hyperintensity, and Multidomain Cognitive Performance in Asymptomatic Carotid Stenosis

Carotid stenosis is a major contributor to vascular dementia. Recent studies suggest that even clinically "asymptomatic" carotid stenosis is linked with cognitive decline and neuroimaging changes. Here we examined surface-based cortical morphometry, white matter hyperintensity (WMH), and multidomain cognitive performance in unilateral severe (>70% narrowing) asymptomatic carotid stenosis (SACS). We included 24 SACS patients (19 males/5 females; 64.25 ± 7.18 years) and 24 comorbidities-matched controls (19 males/5 females; 67.16 ± 6.10 years), and measured cortical thickness, sulcal depth, gyrification, cortical complexity, and WMH loads with structural MRI images. The SACS patients exhibited: (1) thinner cortex in bilateral somatosensory/motor, bilateral inferior frontal, bilateral fusiform, and left lateral temporal areas; (2) shallower sulci in left lateral temporal, parietal, insular and somatosensory/motor areas; (3) both hyper- and hypo-gyrification in lateral temporal and frontal cortices; (4) lower complexity (fractal dimension) in left insular and right superior temporal areas. Further association analyses showed that the cortical alterations were significantly correlated with verbal memory and WMH burden in SACS. These results suggest that SACS patients present a left-dominated damage tendency, especially in the Perisylvian cortices that span across several large-scale systems of somatosensory/motor and language. Our findings also provide cortical anatomy evidence for cognitive impairment in SACS, suggesting a neuroanatomical predisposition to dementia and cerebrovascular events.

Effects of polygenic risk for major mental disorders and cross-disorder on cortical complexity

BACKGROUND

MRI-derived cortical folding measures are an indicator of largely genetically driven early developmental processes. However, the effects of genetic risk for major mental disorders on early brain development are not well understood.

METHODS

We extracted cortical complexity values from structural MRI data of 580 healthy participants using the CAT12 toolbox. Polygenic risk scores (PRS) for schizophrenia, bipolar disorder, major depression, and cross-disorder (incorporating cumulative genetic risk for depression, schizophrenia, bipolar disorder, autism spectrum disorder, and attention-deficit hyperactivity disorder) were computed and used in separate general linear models with cortical complexity as the regressand. In brain regions that showed a significant association between polygenic risk for mental disorders and cortical complexity, volume of interest (VOI)/region of interest (ROI) analyses were conducted to investigate additional changes in their volume and cortical thickness.

RESULTS

The PRS for depression was associated with cortical complexity in the right orbitofrontal cortex (right hemisphere: p = 0.006). A subsequent VOI/ROI analysis showed no association between polygenic risk for depression and either grey matter volume or cortical thickness. We found no associations between cortical complexity and polygenic risk for either schizophrenia, bipolar disorder or psychiatric cross-disorder when correcting for multiple testing.

CONCLUSIONS

Changes in cortical complexity associated with polygenic risk for depression might facilitate well-established volume changes in orbitofrontal cortices in depression. Despite the absence of psychopathology, changed cortical complexity that parallels polygenic risk for depression might also change reward systems, which are also structurally affected in patients with depressive syndrome.

A hybrid deep neural network for classification of schizophrenia using EEG Data

Schizophrenia is a serious mental illness that causes great harm to patients, so timely and accurate detection is essential. This study aimed to identify a better feature to represent electroencephalography (EEG) signals and improve the classification accuracy of patients with schizophrenia and healthy controls by using EEG signals. Our research method involves two steps. First, the EEG time series is preprocessed, and the extracted time-domain and frequency-domain features are transformed into a sequence of red-green-blue (RGB) images that carry spatial information. Second, we construct hybrid deep neural networks (DNNs) that combine convolution neural networks and long short-term memory to address RGB images to classify schizophrenic patients and healthy controls. The results show that the fuzzy entropy (FuzzyEn) feature is more significant than the fast Fourier transform (FFT) feature in brain topography. The deep learning (DL) method that we propose achieves an average accuracy of 99.22% with FuzzyEn and an average accuracy of 96.34% with FFT. These results show that the best effect is to extract fuzzy features as input features from EEG time series and then use a hybrid DNN for classification. Compared with the most advanced methods in this field, significant improvements have been achieved.

Altered Complexity of Spontaneous Brain Activity in Schizophrenia and Bipolar Disorder Patients

BACKGROUND

Schizophrenia (SC) and bipolar disorder (BP) share elements of symptoms and the underlying neural mechanisms for both remain unclear. Recently, the complexity of spontaneous functional MRI (fMRI) signals in brain activity has been investigated in SC and BP using multiscale sample entropy (MSE) with inconsistent results.

PURPOSE

To perform MSE analysis across five time scales to assess differences in resting-state fMRI signal complexity in SC, BP, and normal controls (NC).

STUDY TYPE

Retrospective.

POPULATION

Fifty SC, 49 BP, and 49 NC.

FIELD STRENGTH/SEQUENCE

A 3 T, T2* weighted echo planar imaging (EPI) sequence.

ASSESSMENT

The mean MSEs of all gray matter (GM) and of 12 regions of interest (ROIs) were extracted using masks across the five scales. The regional homogeneity (ReHo) and amplitude of low-frequency fluctuation (ALFF) in these ROIs were also determined and the relationship between the three measures was investigated. The correlations between cognitive assessment scores and MSE values were also explored.

STATISTICAL TESTS

Bonferroni correction, One-way ANOVA, Spearman rank correlation coefficient (r), Gaussian random field (GRF) correction.

RESULTS

There were decreased GM MSE values in the patient groups (F = 9.629, P < 0.05). SC and BP patients demonstrated lower complexity than NCs in the calcarine fissure, precuneus, inferior occipital gyrus, lingual gyrus and cerebellum, and higher complexity in the median cingulate, thalamus, hippocampus, middle temporal gyrus and middle frontal gyrus. There were significant differences between SC and BP patients in the precuneus (F = 4.890, P < 0.05) and inferior occipital gyrus (F = 5.820, P < 0.05). Calcarine fissure, cingulate, temporal gyrus, occipital gyrus, hippocampus, precuneus, frontal gyrus, and lingual gyrus MSE values were significantly correlated with both ReHo (r > 0.282, P < 0.05) and ALFF (r > 0.278, P < 0.05). Furthermore, median temporal MSE (r = -0.321, P < 0.05) on scale 3 and (r = -0.307, P < 0.05) on scale 4 and median cingulate MSE (r = -0.337, P < 0.05) on scale 5 was significantly negatively correlated with cognitive assessment scores.

DATA CONCLUSION

These data highlight different patterns of brain signal intensity complexity in SC and BP.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY: Stage 1.

Self-perceived cognitive lapses and psychological well-being in schizotypy: Generalized and domain-specific associations

A critical link between schizotypy and schizophrenia is impoverished cognitive functioning. In the majority of studies, though: (1) cognition is examined with standard neuropsychological tasks; and (2) high-schizotypal individuals are defined according to criteria applied in the respective study sample. Taking these considerations into account, the aims of the present study were to examine: (1) differences between four pre-defined, according to normative criteria, schizotypal (paranoid, negative, disorganized and cognitive-perceptual) and one control groups in self-perceived cognitive lapses; and (2) associations between schizotypal dimensions, self-perceived cognitive lapses and psychological well-being. Two hundred and sixty-one participants were administered the Schizotypal Personality Questionnaire, the Cognitive Failures Questionnaire (CFQ) and the Flourishing Scale, which assesses psychological well-being. Negative schizotypals reported higher scores in almost all CFQ measures compared with the control group (all p values < 0.01) along with poorer psychological well-being compared with the control and the cognitive-perceptual groups (both p values < 0.001). The disorganized group had higher scores in distractibility, blunders and total CFQ scores compared with the control group (all p values < 0.001). High psychological well-being was significantly associated with low negative schizotypy and CFQ blunders along with high cognitive-perceptual schizotypy (all p values < 0.05). To summarize, negative schizotypy is associated with a profile of "generalized" self-perceived cognitive lapses while disorganized schizotypy is characterized by self-perceived cognitive slips that have previously been shown to be mediated by a fronto-parietal network. Although psychological well-being is negatively associated with social-context specific cognitive failures and negative schizotypy, it is positively associated with cognitive-perceptual schizotypy.

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.

Toward a more reliable characterization of fractal properties of the cerebral cortex of healthy subjects during the lifespan

The cerebral cortex manifests an inherent structural complexity of folding. The fractal geometry describes the complexity of structures which show self-similarity in a proper interval of spatial scales. In this study, we aimed at evaluating in-vivo the effect of different criteria for selecting the interval of spatial scales in the estimation of the fractal dimension (FD) of the cerebral cortex in T₁-weighted magnetic resonance imaging (MRI). We compared four different strategies, including two a priori selections of the interval of spatial scales, an automated selection of the spatial scales within which the cerebral cortex manifests the highest statistical self-similarity, and an improved approach, based on the search of the interval of spatial scales which presents the highest rounded R²_adj coefficient and, in case of equal rounded R²_adj coefficient, preferring the widest interval in the log–log plot. We employed two public and international datasets of in-vivo MRI scans for a total of 159 healthy subjects (age range 6–85 years). The improved approach showed strong associations of FD with age and yielded the most accurate machine learning models for individual age prediction in both datasets. Our results indicate that the selection of the interval of spatial scales of the cerebral cortex is thus critical in the estimation of FD.

The association of striatal volume and positive schizotypy in healthy subjects: intelligence as a moderating factor

BACKGROUND

Schizotypy, a putative schizophrenia endophenotype, has been associated with brain-structural variations partly overlapping with those in psychotic disorders. Variations in precuneus structure have been repeatedly reported, whereas the involvement of fronto-striatal networks - as in schizophrenia - is less clear. While shared genetic architecture is thought to increase vulnerability to environmental insults, beneficial factors like general intelligence might buffer their effect.

METHODS

To further investigate the role of fronto-striatal networks in schizotypy, we examined the relationship of voxel- and surface-based brain morphometry and a measure of schizotypal traits (Schizotypal Personality Questionnaire, with subscores Cognitive-Perceptual, Interpersonal, Disorganised) in 115 healthy participants [54 female, mean age (s.d.) = 27.57(8.02)]. We tested intelligence (MWT-B) as a potential moderator.

RESULTS

We found a positive association of SPQ Cognitive-Perceptual with putamen volume (p = 0.040, FWE peak level-corrected), moderated by intelligence: with increasing IQ, the correlation of SPQ Cognitive-Perceptual and striatal volume decreased (p = 0.022). SPQ Disorganised was positively correlated with precentral volume (p = 0.013, FWE peak level-corrected). In an exploratory analysis (p < 0.001, uncorrected), SPQ total score was positively associated with gyrification in the precuneus and postcentral gyrus, and SPQ Disorganised was negatively associated with gyrification in the inferior frontal gyrus.

CONCLUSIONS

Our findings support the role of fronto-striatal networks for schizotypal features in healthy individuals, and suggest that these are influenced by buffering factors like intelligence. We conclude that protective factors, like general cognitive capacity, might attenuate the psychosis risk associated with schizotypy. These results endorse the idea of a continuous nature of schizotypy, mirroring similar findings in schizophrenia.

Cortical Complexity in Anorexia Nervosa: A Fractal Dimension Analysis

Fractal Dimension (FD) has shown to be a promising means to describe the morphology of cortical structures across different neurologic and psychiatric conditions, displaying a good sensitivity in capturing atrophy processes. In this study, we aimed at exploring the morphology of cortical areas by means of FD in 58 female patients with Anorexia Nervosa (AN) (38 currently underweight and 20 fully recovered) and 38 healthy controls (HC). All participants underwent high-resolution MRI. Surface extraction was completed using FreeSurfer, FD was computed using the calcFD toolbox. The whole cortex mean FD value was lower in acute AN patients compared to HC (p < 0.001). Recovered AN patients did not show differences in the global FD when compared to HC. However, some brain areas showed higher FD in patients than controls, while others showed the opposite pattern. Parietal regions showed lower FD in both AN groups. In acute AN patients, the FD correlated with age (p < 0.001), body mass index (p = 0.019) and duration of illness (p = 0.011). FD seems to represent a feasible method to explore cortical complexity in patients with AN since it demonstrated to be sensitive to the effects of both severity and duration of malnutrition.

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.

[Brain imaging in schizophrenia : A review of current trends and developments]

Imaging methods have become the main approach for identifying dysfunctional neuronal networks in schizophrenia. This review article presents recent results of disorders of neuronal networks at structural and functional levels and summarizes the current developments. Large multicenter analyses have further established patterns of regional brain alterations, while novel methods in magnetic resonance (MR) morphometry have contributed to differentiating early from delayed brain structural changes. The use of machine learning approaches has not only enabled the establishment of classification models using biological data for future differential diagnostic use, it has also facilitated multivariate models for outcome prediction following therapeutic interventions. Novel methods, such as BrainAGE, a surrogate marker of accelerated brain aging processes, have added to longitudinal studies to gain insights into the brain structural dynamics from early brain developmental alterations to progressive structural brain changes after disease onset.

Dissecting the syndrome of schizophrenia: Associations between symptomatology and hormone levels in women with schizophrenia

Despite many studies implicating reproductive hormones in the development and outcome of schizophrenia, few have characterised the association between symptomatology and hormonal trajectories. To understand the influence of hormones on schizophrenia symptoms, serum steroids (estradiol, progesterone, follicular stimulating hormone (FSH), luteinising hormone (LH), and dehydroepiandrosterone (DHEA)) and psychopathology (The positive-and-negative-syndrome-scale(PANSS)) and depression (Montgomery-Asberg-Depression-Rating Scale(MADRS)) were collected across 12-weeks in 45 women (mean age 46) diagnosed with schizophrenia. To account for potential heterogeneity, Group-based-trajectory-modelling of psychopathology was used to identify distinct subgroups of individuals following a similar pattern of association between symptom score and hormone levels over-time. Two trajectories were identified for PANSS: one subgroup with lower symptom severity was associated with FSH, DHEA, LH, and another high severity subgroup associated with LH. Two trajectories were identified for MADRS: 'depressed' (associated with FSH), and non-depressed. The result delineates subpopulations with unique psychopathology and hormone associations that support the hypothesis that reproductive hormones play a role in the pathophysiology of schizophrenia, and that heterogeneity may exist in hormonal sensitivities in the schizophrenia population. Stratification of subjects according to biological phenotype may help improve existing treatments through personalised-medicine strategies. The endocrine system may be one such biological mechanism to continue dissecting the syndrome.

A healthy dose of chaos: Using fractal frameworks for engineering higher-fidelity biomedical systems

Optimal levels of chaos and fractality are distinctly associated with physiological health and function in natural systems. Chaos is a type of nonlinear dynamics that tends to exhibit seemingly random structures, whereas fractality is a measure of the extent of organization underlying such structures. Growing bodies of work are demonstrating both the importance of chaotic dynamics for proper function of natural systems, as well as the suitability of fractal mathematics for characterizing these systems. Here, we review how measures of fractality that quantify the dose of chaos may reflect the state of health across various biological systems, including: brain, skeletal muscle, eyes and vision, lungs, kidneys, tumours, cell regulation, skin and wound repair, bone, vasculature, and the heart. We compare how reports of either too little or too much chaos and fractal complexity can be damaging to normal biological function, and suggest that aiming for the healthy dose of chaos may be an effective strategy for various biomedical applications. We also discuss rising examples of the implementation of fractal theory in designing novel materials, biomedical devices, diagnostics, and clinical therapies. Finally, we explain important mathematical concepts of fractals and chaos, such as fractal dimension, criticality, bifurcation, and iteration, and how they are related to biology. Overall, we promote the effectiveness of fractals in characterizing natural systems, and suggest moving towards using fractal frameworks as a basis for the research and development of better tools for the future of biomedical engineering.

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.

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

Abnormal Entropy Modulation of the EEG Signal in Patients With Schizophrenia During the Auditory Paired-Stimulus Paradigm

The complexity change in brain activity in schizophrenia is an interesting topic clinically. Schizophrenia patients exhibit abnormal task-related modulation of complexity, following entropy of electroencephalogram (EEG) analysis. However, complexity modulation in schizophrenia patients during the sensory gating (SG) task, remains unknown. In this study, the classical auditory paired-stimulus paradigm was introduced to investigate SG, and EEG data were recorded from 55 normal controls and 61 schizophrenia patients. Fuzzy entropy (FuzzyEn) was used to explore the complexity of brain activity under the conditions of baseline (BL) and the auditory paired-stimulus paradigm (S1 and S2). Generally, schizophrenia patients showed significantly higher FuzzyEn values in the frontal and occipital regions of interest (ROIs). Relative to the BL condition, the normalized values of FuzzyEn of normal controls were decreased greatly in condition S1 and showed less variance in condition S2. Schizophrenia patients showed a smaller decrease in the normalized values in condition S1. Moreover, schizophrenia patients showed significant diminution in the suppression ratios of FuzzyEn, attributed to the higher FuzzyEn values in condition S1. These results suggested that entropy modulation during the process of sensory information and SG was obvious in normal controls and significantly deficient in schizophrenia patients. Additionally, the FuzzyEn values measured in the frontal ROI were positively correlated with positive scores of Positive and Negative Syndrome Scale (PANSS), indicating that frontal entropy was a potential indicator in evaluating the clinical symptoms. However, negative associations were found between the FuzzyEn values of occipital ROIs and general and total scores of PANSS, likely reflecting the compensation effect in visual processing. Thus, our findings provided a deeper understanding of the deficits in sensory information processing and SG, which contribute to cognitive deficits and symptoms in patients with schizophrenia.

Predicting age from cortical structure across the lifespan

Despite interindividual differences in cortical structure, cross-sectional and longitudinal studies have demonstrated a large degree of population-level consistency in age-related differences in brain morphology. This study assessed how accurately an individual's age could be predicted by estimates of cortical morphology, comparing a variety of structural measures, including thickness, gyrification and fractal dimensionality. Structural measures were calculated across up to seven different parcellation approaches, ranging from one region to 1000 regions. The age prediction framework was trained using morphological measures obtained from T1-weighted MRI volumes collected from multiple sites, yielding a training dataset of 1056 healthy adults, aged 18-97. Age predictions were calculated using a machine-learning approach that incorporated nonlinear differences over the lifespan. In two independent, held-out test samples, age predictions had a median error of 6-7 years. Age predictions were best when using a combination of cortical metrics, both thickness and fractal dimensionality. Overall, the results reveal that age-related differences in brain structure are systematic enough to enable reliable age prediction based on metrics of cortical morphology.

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.

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.

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.

Distinct neuronal activation patterns are associated with PCP-induced social withdrawal and its reversal by the endocannabinoid-enhancing drug URB597

The fatty acid amide hydrolase inhibitor, URB597, an endocannabinoid enhancing drug, reverses social withdrawal in the sub-chronic PCP rat model of schizophrenia, but reduces social interaction (SI) in controls. To identify the anatomical substrates associated with PCP-induced social withdrawal and the contrasting effects of URB597 on SI in PCP- versus saline-treated rats, we analyzed SI-induced c-Fos expression in 28 brain areas relevant to schizophrenia and/or social behavior following vehicle or URB597 administration. In saline-treated rats, SI was accompanied by changes in c-Fos expression in the infralimbic and orbitofrontal cortices, dorsomedial caudate putamen, ventrolateral nucleus of the septum, dorsolateral periaqueductal gray (dlPAG) and central amygdala. Except for the dlPAG, these changes were not observed in PCP-treated rats or in saline-treated rats receiving URB597. In the dorsomedial part of the bed nucleus of the stria terminalis (dmBNST), SI-induced c-Fos expression was observed only in PCP-treated rats. Interestingly, URB597 in PCP-treated rats restored a similar c-Fos expression pattern as observed in saline-treated rats: activation of the orbitofrontal cortex, inhibition of the central amygdala and suppression of activation of the dmBNST. These data suggest that orbitofrontal cortex, central amygdala and dmBNST play a critical role in the reversal of PCP-induced social withdrawal by URB597.

Dimensional approaches to schizophrenia: A comparison of the Bern Psychopathology scale and the five-factor model of the Positive and Negative Syndrome Scale

The aim was to examine to what extent the dimensions of the BPS map the five factors derived from the PANSS in order to explore the level of agreement of these alternative dimensional approaches in patients with schizophrenia. 149 inpatients with schizophrenia spectrum disorders were recruited. Psychopathological symptoms were assessed with the Bern Psychopathology Scale (BPS) and the Positive and Negative Syndrome Scale (PANSS). Linear regression analyses were conducted to explore the association between the factors and the items of the BPS. The robustness of patterns was evaluated. An understandable overlap of both approaches was found for positive and negative symptoms and excitement. The PANSS positive factor was associated with symptoms of the affect domain in terms of both inhibition and disinhibition, the PANSS negative factor with symptoms of all three domains of the BPS as an inhibition and the PANSS excitement factor with an inhibition of the affect domain and a disinhibition of the language and motor domains. The results show that here is only a partial overlap between the system-specific approach of the BPS and the five-factor PANSS model. A longitudinal assessment of psychopathological symptoms would therefore be of interest.

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.

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.

Emotion processing in treatment-resistant schizophrenia patients treated with clozapine: An fMRI study

OBJECTIVES

To examine the neural correlates of emotion processing in treatment-resistant patients with schizophrenia (SCZ-TR).

METHODS

Twenty-two SCZ-TR patients on clozapine, 24 schizophrenia patients on antipsychotics other than clozapine, and 39 healthy controls were scanned using functional neuroimaging while viewing positive, negative and neutral images.

RESULTS

Emotionally-laden images (positive and negative) elicited hyper-activations in the dorso-medial prefrontal cortex and left cerebellum in SCZ-TR patients, compared to the two other groups. Similarly, neutral images prompted hyper-activations in the cingulate gyrus in SCZ-TR patients, relative to the two other groups.

CONCLUSIONS

Treatment resistance is associated with neuro-functional hyper-activations in schizophrenia patients during emotion processing.

Patterns of cortical thinning in different subgroups of schizophrenia

BACKGROUND

Alterations of cortical thickness have been shown in imaging studies of schizophrenia but it is unclear to what extent they are related to disease phenotype (including symptom profile) or other aspects such as genetic liability, disease onset and disease progression.

AIMS

To test the hypothesis that cortical thinning would vary across different subgroups of patients with chronic schizophrenia, delineated according to their symptom profiles.

METHOD

We compared high-resolution magnetic resonance imaging data of 87 patients with DSM-IV schizophrenia with 108 controls to detect changes in cortical thickness across the entire brain (P<0.05, false discovery rate-adjusted). The patient group was divided into three subgroups, consisting of patients with predominantly negative, disorganised or paranoid symptoms.

RESULTS

The negative symptoms subgroup showed the most extensive cortical thinning, whereas thinning in the other subgroups was focused in prefrontal and temporal cortical subregions.

CONCLUSIONS

Our findings support growing evidence of potential subtypes of schizophrenia that have different brain structural deficit profiles.

Brain structure in people at ultra-high risk of psychosis, patients with first-episode schizophrenia, and healthy controls: a VBM study

Early intervention research in schizophrenia has suggested that brain structural alterations might be present in subjects at high risk of developing psychosis. The heterogeneity of regional effects of these changes, which is established in schizophrenia, however, has not been explored in prodromal or high-risk populations. We used high-resolution MRI and voxel-based morphometry (VBM8) to analyze grey matter differences in 43 ultra high-risk subjects for psychosis (meeting ARMS criteria, identified through CAARMS interviews), 24 antipsychotic-naïve first-episode schizophrenia patients and 49 healthy controls (groups matched for age and gender). Compared to healthy controls, resp., first-episode schizophrenia patients had reduced regional grey matter in left prefrontal, insula, right parietal and left temporal cortices, while the high-risk group showed reductions in right middle temporal and left anterior frontal cortices. When dividing the ultra-high-risk group in those with a genetic risk vs. those with attenuated psychotic symptoms, the former showed left anterior frontal, right caudate, as well as a smaller right hippocampus, and amygdala reduction, while the latter subgroup showed right middle temporal cortical reductions (each compared to healthy controls). Our findings in a clinical psychosis high-risk cohort demonstrate variability of brain structural changes according to subgroup and background of elevated risk, suggesting frontal and possibly also hippocampal/amygdala changes in individuals with genetic susceptibility. Heterogeneity of structural brain changes (as seen in schizophrenia) appears evident even at high-risk stage, prior to potential onset of psychosis.

Cortical thickness correlates of psychotic experiences: examining the effect of season of birth using a genetically informative design

Season of birth has been shown to influence risk for several neuropsychiatric diseases. Furthermore, it has been suggested that season of birth modifies a number of brain morphological traits. Since cortical thickness alterations have been reported across some levels of the psychosis-spectrum, this study was aimed at i) assessing the scarcely explored relationship between cortical thickness and severity of subclinical psychotic experiences (PEs) in healthy subjects, and ii) evaluating the potential impact of season of birth in the preceding thickness-PEs relationship. As both PEs and brain cortical features are heritable, the current work used monozygotic twins to separately evaluate familial and unique environmental factors. High-resolution structural MRI scans of 48 twins (24 monozygotic pairs) were analyzed to estimate cortical thickness using FreeSurfer. They were then examined in relation to PEs, accounting for the effects of birth season; putative differential relationships between PEs and cortical thickness depending on season of birth were also tested. Current results support previous findings indicative of cortical thickening in healthy individuals with high psychometrically assessed psychosis scores, probably in line with theories of compensatory aspects of brain features in non-clinical populations. Additionally, they suggest distinct patterns of cortical thickness-PEs relationships depending on birth seasonality. Familial factors underlying the presence of PEs may drive these effects.

Cortical morphology of adolescents with bipolar disorder and with schizophrenia

INTRODUCTION

Recent evidence points to overlapping decreases in cortical thickness and gyrification in the frontal lobe of patients with adult-onset schizophrenia and bipolar disorder with psychotic symptoms, but it is not clear if these findings generalize to patients with a disease onset during adolescence and what may be the mechanisms underlying a decrease in gyrification.

METHOD

This study analyzed cortical morphology using surface-based morphometry in 92 subjects (age range 11-18 years, 52 healthy controls and 40 adolescents with early-onset first-episode psychosis diagnosed with schizophrenia (n=20) or bipolar disorder with psychotic symptoms (n=20) based on a two year clinical follow up). Average lobar cortical thickness, surface area, gyrification index (GI) and sulcal width were compared between groups, and the relationship between the GI and sulcal width was assessed in the patient group.

RESULTS

Both patients groups showed decreased cortical thickness and increased sulcal width in the frontal cortex when compared to healthy controls. The schizophrenia subgroup also had increased sulcal width in all other lobes. In the frontal cortex of the combined patient group sulcal width was negatively correlated (r=-0.58, p<0.001) with the GI.

CONCLUSIONS

In adolescents with schizophrenia and bipolar disorder with psychotic symptoms there is cortical thinning, decreased GI and increased sulcal width of the frontal cortex present at the time of the first psychotic episode. Decreased frontal GI is associated with the widening of the frontal sulci which may reduce sulcal surface area. These results suggest that abnormal growth (or more pronounced shrinkage during adolescence) of the frontal cortex represents a shared endophenotype for psychosis.