Regionally localized thinning of the cerebral cortex in schizophrenia

Elevated intrinsic cortical curvature in treatment-resistant schizophrenia: Evidence of structural deformation in functional connectivity areas and comparison with alternate indices of structure

BACKGROUND

Research suggests structural and connectivity abnormalities in patients with treatment-resistant schizophrenia (TRS) compared to first-line responders and healthy-controls. However, measures of these abnormalities are often influenced by external factors like nicotine and antipsychotics, limiting their clinical utility. Intrinsic-cortical-curvature (ICC) presents a millimetre-scale measure of brain gyrification, highly sensitive to schizophrenia differences, and associated with TRS-like traits in early stages of the disorder. Despite this evidence, ICC in TRS remains unexplored. This study investigates ICC as a marker for treatment resistance in TRS, alongside structural indices for comparison.

METHODS

We assessed ICC in anterior cingulate, dorsolateral prefrontal, temporal, and parietal cortices of 38 first-line responders, 30 clozapine-resistant TRS, 37 clozapine-responsive TRS, and 52 healthy-controls. For comparative purposes, Fold and Curvature indices were also analyzed.

RESULTS

Adjusting for age, sex, nicotine-use, and chlorpromazine equivalence, principal findings indicate ICC elevations in the left hemisphere dorsolateral prefrontal (p < 0.001, η2partial = 0.142) and temporal cortices (LH p = 0.007, η2partial = 0.060; RH p = 0.011, η2partial = 0.076) of both TRS groups, and left anterior cingulate cortex of clozapine-resistant TRS (p = 0.026, η2partial = 0.065), compared to healthy-controls. Elevations that correlated with reduced cognition (p = 0.001) and negative symptomology (p < 0.034) in clozapine-resistant TRS. Fold and Curvature indices only detected group differences in the right parietal cortex, showing interactions with age, sex, and nicotine use. ICC showed interactions with age.

CONCLUSION

ICC elevations were found among patients with TRS, and correlated with symptom severity. ICCs relative independence from sex, nicotine-use, and antipsychotics, may support ICC's potential as a viable marker for TRS, though age interactions should be considered.

The pattern of cortical thickness associated with executive dysfunction in MCI and SCC: The MEMENTO cohort

BACKGROUND

The association between the pattern of cortical thickness (CT) and executive dysfunction (ED) in mild cognitive impairment (MCI) and subjective cognitive complaints (SCC) is still poorly understood. We aimed to investigate the association between CT and ED in a large French cohort (MEMENTO) of 2323 participants with MCI or SCC.

METHODS

All participants with available CT and executive function data (verbal fluency and Trail Making Test [TMT]) were selected (n=1924). Linear regressions were performed to determine relationships between executive performance and the brain parenchymal fraction (BPF) and CT using FreeSurfer.

RESULTS

The global executive function score was related to the BPF (sß: 0.091, P<0.001) and CT in the right supramarginal (sß: 0.060, P=0.041) and right isthmus cingulate (sß: 0.062, P=0.011) regions. Literal verbal fluency was related to the BPF (sß: 0.125, P<0.001) and CT in the left parsorbitalis region (sß: 0.045, P=0.045). Semantic verbal fluency was related to the BPF (sß: 0.101, P<0.001) and CT in the right supramarginal region (sß: 0.061, P=0.042). The time difference between the TMT parts B and A was related to the BPF (sß: 0.048, P=0.045) and CT in the right precuneus (sß: 0.073, P=0.019) and right isthmus cingulate region (sß: 0.054, P=0.032).

CONCLUSIONS

In a large clinically based cohort of participants presenting with either MCI or SCC (a potential early stage of Alzheimer's disease [AD]), ED was related to the BPF and CT in the left pars orbitalis, right precuneus, right supramarginal, and right isthmus cingulate regions. This pattern of lesions adds knowledge to the conventional anatomy of ED and could contribute to the early diagnosis of AD.

Clinical predictors of Alzheimer's disease-like brain atrophy in individuals with memory complaints

OBJECTIVES

The definition and assessment methods for subjective cognitive decline (SCD) vary among studies. We aimed to investigate which features or assessment methods of SCD best predict Alzheimer's disease (AD)-related structural atrophy patterns.

METHODS

We assessed 104 individuals aged 55+ with memory complaints but normal cognitive screening. Our research questions were as follows: To improve the prediction of AD related morphological changes, (1) Would the use of a standardized cognitive screening scale be beneficial? (2) Is conducting a thorough neuropsychological evaluation necessary instead of relying solely on cognitive screening tests? (3) Should we apply SCD-plus research criteria, and if so, which criterion would be the most effective? (4) Is it necessary to consider medical and psychiatric comorbidities, vitamin deficiencies, vascular burden on MRI, and family history? We utilized Freesurfer to analyze cortical thickness and regional brain volume meta-scores linked to AD or predicting its development. We employed multiple linear regression models for each variable, with morphology as the dependent variable.

RESULTS

AD-like morphology was associated with subjective complaints in males, individuals with advanced age, and higher education. Later age of onset for complaints, complaints specifically related to memory, excessive deep white matter vascular lesions, and using medications that have negative implications for cognitive health (according to the Beers criteria) were predictive of AD-related morphology. The subjective cognitive memory questionnaire scores were found to be a better predictor of reduced volumes than a single-question assessment. It is important to note that not all SCD-plus criteria were evaluated in this study, particularly the APOE genotype, amyloid, and tau status, due to resource limitations.

CONCLUSIONS

The detection of AD-related structural changes is impacted by demographics and assessment methods. Standardizing SCD assessment methods can enhance predictive accuracy.

Association between cortical thickness or surface area and divergent thinking in patients with bipolar disorder

OBJECTIVE

Divergent thinking is a critical creative cognitive process. Its neural mechanisms have been well-studied through structural and functional imaging in healthy individuals but are less explored in patients with bipolar disorder (BD). Because of the traditional link between creativity and BD, this study investigated the structural correlates of divergent thinking in patients with BD through surface-based morphometry.

METHODS

Fifty-nine patients diagnosed with BD I or BD II (35.3 ± 8.5 years) and 56 age- and sex-matched controls (33.9 ± 7.4 years) were recruited. The participants underwent structural magnetic resonance imaging and an evaluation of divergent thinking by using the Chinese version of the Abbreviated Torrance Test for Adults (ATTA). FreeSurfer 7.0 was used to generate thickness and surface area maps for each participant. Brainwise regression of the association between cortical thickness or surface area and ATTA performance was conducted using general linear models.

RESULTS

Divergent thinking performance did not differ significantly between the patients with BD and the healthy controls. In these patients, total ATTA score was negatively correlated with cortical thickness in the right middle frontal gyrus, right occipital, and left precuneus but positively correlated with the surface area of the right superior frontal gyrus. By contrast, total ATTA scores and cortical thickness or surface area were not significantly correlated among the controls.

CONCLUSION

The findings indicate that divergent thinking involves cerebral structures for executive control, mental imagery, and visual processing in patients with BD, and the right prefrontal cortex might be the most crucial of these structures.

Environmental and sociocultural factors are associated with pain-related brain structure among diverse individuals with chronic musculoskeletal pain: intersectional considerations

Chronic musculoskeletal pain including knee osteoarthritis (OA) is a leading cause of disability worldwide. Previous research indicates ethnic-race groups differ in the pain and functional limitations experienced with knee OA. However, when socioenvironmental factors are included in analyses, group differences in pain and function wane. Pain-related brain structures are another area where ethnic-race group differences have been observed. Environmental and sociocultural factors e.g., income, education, experiences of discrimination, and social support influence brain structures. We investigate if environmental and sociocultural factors reduce previously observed ethnic-race group differences in pain-related brain structures. Data were analyzed from 147 self-identified non-Hispanic black (NHB) and non-Hispanic white (NHW), middle and older aged adults with knee pain in the past month. Information collected included health and pain history, environmental and sociocultural resources, and brain imaging. The NHB adults were younger and reported lower income and education compared to their NHW peers. In hierarchical multiple regression models, sociocultural and environmental factors explained 6-37% of the variance in pain-related brain regions. Self-identified ethnicity-race provided an additional 4-13% of explanatory value in the amygdala, hippocampus, insula, bilateral primary somatosensory cortex, and thalamus. In the rostral/caudal anterior cingulate and dorsolateral prefrontal cortex, self-identified ethnicity-race was not a predictor after accounting for environmental, sociocultural, and demographic factors. Findings help to disentangle and identify some of the factors contributing to ethnic-race group disparities in pain-related brain structures. Numerous arrays of environmental and sociocultural factors remain to be investigated. Further, the differing sociodemographic representation of our NHB and NHW participants highlights the role for intersectional considerations in future research.

Culture, prefrontal volume, and memory

Prior cross-cultural studies have demonstrated differences among Eastern and Western cultures in memory and cognition along with variation in neuroanatomy and functional engagement. We further probed cultural neuroanatomical variability in terms of its relationship with memory performance. Specifically, we investigated how memory performance related to gray matter volume in several prefrontal lobe structures, including across cultures. For 58 American and 57 Taiwanese young adults, memory performance was measured with the California Verbal Learning Test (CVLT) using performance on learning trial 1, on which Americans had higher scores than the Taiwanese, and the long delayed free recall task, on which groups performed similarly. MRI data were reconstructed using FreeSurfer. Across both cultures, we observed that larger volumes of the bilateral rostral anterior cingulate were associated with lower scores on both CVLT tasks. In terms of effects of culture, the relationship between learning trial 1 scores and gray matter volumes in the right superior frontal gyrus had a trend for a positive relationship in Taiwanese but not in Americans. In addition to the a priori analysis of select frontal volumes, an exploratory whole-brain analysis compared volumes-without considering CVLT performance-across the two cultural groups in order to assess convergence with prior research. Several cultural differences were found, such that Americans had larger volumes in the bilateral superior frontal and lateral occipital cortex, whereas Taiwanese had larger volumes in the bilateral rostral middle frontal and inferior temporal cortex, and the right precuneus.

Comparative neuroimaging of sex differences in human and mouse brain anatomy

In vivo neuroimaging studies have established several reproducible volumetric sex differences in the human brain, but the causes of such differences are hard to parse. While mouse models are useful for understanding the cellular and mechanistic bases of sex-specific brain development, there have been no attempts to formally compare human and mouse neuroanatomical sex differences to ascertain how well they translate. Addressing this question would shed critical light on the use of the mouse as a translational model for sex differences in the human brain and provide insights into the degree to which sex differences in brain volume are conserved across mammals. Here, we use structural magnetic resonance imaging to conduct the first comparative neuroimaging study of sex-specific neuroanatomy of the human and mouse brain. In line with previous findings, we observe that in humans, males have significantly larger and more variable total brain volume; these sex differences are not mirrored in mice. After controlling for total brain volume, we observe modest cross-species congruence in the volumetric effect size of sex across 60 homologous regions (r=0.30). This cross-species congruence is greater in the cortex (r=0.33) than non-cortex (r=0.16). By incorporating regional measures of gene expression in both species, we reveal that cortical regions with greater cross-species congruence in volumetric sex differences also show greater cross-species congruence in the expression profile of 2835 homologous genes. This phenomenon differentiates primary sensory regions with high congruence of sex effects and gene expression from limbic cortices where congruence in both these features was weaker between species. These findings help identify aspects of sex-biased brain anatomy present in mice that are retained, lost, or inverted in humans. More broadly, our work provides an empirical basis for targeting mechanistic studies of sex-specific brain development in mice to brain regions that best echo sex-specific brain development in humans.

Neuroimaging data repositories and AI-driven healthcare-Global aspirations vs. ethical considerations in machine learning models of neurological disease

Neuroimaging data repositories are data-rich resources comprising brain imaging with clinical and biomarker data. The potential for such repositories to transform healthcare is tremendous, especially in their capacity to support machine learning (ML) and artificial intelligence (AI) tools. Current discussions about the generalizability of such tools in healthcare provoke concerns of risk of bias-ML models underperform in women and ethnic and racial minorities. The use of ML may exacerbate existing healthcare disparities or cause post-deployment harms. Do neuroimaging data repositories and their capacity to support ML/AI-driven clinical discoveries, have both the potential to accelerate innovative medicine and harden the gaps of social inequities in neuroscience-related healthcare? In this paper, we examined the ethical concerns of ML-driven modeling of global community neuroscience needs arising from the use of data amassed within neuroimaging data repositories. We explored this in two parts; firstly, in a theoretical experiment, we argued for a South East Asian-based repository to redress global imbalances. Within this context, we then considered the ethical framework toward the inclusion vs. exclusion of the migrant worker population, a group subject to healthcare inequities. Secondly, we created a model simulating the impact of global variations in the presentation of anosmia risks in COVID-19 toward altering brain structural findings; we then performed a mini AI ethics experiment. In this experiment, we interrogated an actual pilot dataset (n = 17; 8 non-anosmic (47%) vs. 9 anosmic (53%) using an ML clustering model. To create the COVID-19 simulation model, we bootstrapped to resample and amplify the dataset. This resulted in three hypothetical datasets: (i) matched (n = 68; 47% anosmic), (ii) predominant non-anosmic (n = 66; 73% disproportionate), and (iii) predominant anosmic (n = 66; 76% disproportionate). We found that the differing proportions of the same cohorts represented in each hypothetical dataset altered not only the relative importance of key features distinguishing between them but even the presence or absence of such features. The main objective of our mini experiment was to understand if ML/AI methodologies could be utilized toward modelling disproportionate datasets, in a manner we term "AI ethics." Further work is required to expand the approach proposed here into a reproducible strategy.

Cortical impoverishment in a stable subgroup of schizophrenia: Validation across various stages of psychosis

BACKGROUND

Cortical thinning is a well-known feature in schizophrenia. The considerable variation in the spatial distribution of thickness changes has been used to parse heterogeneity. A 'cortical impoverishment' subgroup with a generalized reduction in thickness has been reported. However, it is unclear if this subgroup is recoverable irrespective of illness stage, and if it relates to the glutamate hypothesis of schizophrenia.

METHODS

We applied hierarchical cluster analysis to cortical thickness data from magnetic resonance imaging scans of three datasets in different stages of psychosis (n = 288; 160 patients; 128 healthy controls) and studied the cognitive and symptom profiles of the observed subgroups. In one of the samples, we also studied the subgroup differences in 7-Tesla magnetic resonance spectroscopy glutamate concentration in the dorsal anterior cingulate cortex.

RESULTS

Our consensus-based clustering procedure consistently produced 2 subgroups of participants. Patients accounted for 75%-100% of participants in one subgroup that was characterized by significantly lower cortical thickness. Both subgroups were equally symptomatic in clinically unstable stages, but cortical impoverishment indicated a higher symptom burden in a clinically stable sample and higher glutamate levels in the first-episode sample. There were no subgroup differences in cognitive and functional outcome profiles or antipsychotic exposure across all stages.

CONCLUSIONS

Cortical thinning does not vary with functioning or cognitive impairment, but it is more prevalent among patients, especially those with glutamate excess in early stages and higher residual symptom burden at later stages, providing an important mechanistic clue to one of the several possible pathways to the illness.

Sex- and age-based differences in fetal and early childhood hippocampus maturation: a cross-sectional and longitudinal analysis

The hippocampus, essential for cognitive and affective processes, develops exponentially with differential trajectories seen in girls and boys, yet less is known about its development during early fetal life until early childhood. In a cross-sectional and longitudinal study, we examined the sex-, age-, and laterality-related developmental trajectories of hippocampal volumes in fetuses, infants, and toddlers associated with age. Third trimester fetuses (27-38 weeks' gestational age), newborns (0-4 weeks' postnatal age), infants (5-50 weeks' postnatal age), and toddlers (2-3 years postnatal age) were scanned with magnetic resonance imaging. A total of 133 datasets (62 female, postmenstrual age [weeks] M = 69.38, SD = 51.39, range = 27.6-195.3) were processed using semiautomatic segmentation methods. Hippocampal volumes increased exponentially during the third trimester and the first year of life, beginning to slow at approximately 2 years. Overall, boys had larger hippocampal volumes than girls. Lateralization differences were evident, with left hippocampal growth beginning to plateau sooner than the right. This period of rapid growth from the third trimester, continuing through the first year of life, may support the development of cognitive and affective function during this period.

Structural brain correlates of non-verbal cognitive ability in 5-year-old children: Findings from the FinnBrain birth cohort study

Non-verbal cognitive ability predicts multiple important life outcomes, for example, school and job performance. It has been associated with parieto-frontal cortical anatomy in prior studies in adult and adolescent populations, while young children have received relatively little attention. We explored the associations between cortical anatomy and non-verbal cognitive ability in 165 5-year-old participants (mean scan age 5.40 years, SD 0.13; 90 males) from the FinnBrain Birth Cohort study. T1-weighted brain magnetic resonance images were processed using FreeSurfer. Non-verbal cognitive ability was measured using the Performance Intelligence Quotient (PIQ) estimated from the Block Design and Matrix Reasoning subtests from the Wechsler Preschool and Primary Scale of Intelligence (WPPSI-III). In vertex-wise general linear models, PIQ scores associated positively with volumes in the left caudal middle frontal and right pericalcarine regions, as well as surface area in left the caudal middle frontal, left inferior temporal, and right lingual regions. There were no associations between PIQ and cortical thickness. To the best of our knowledge, this is the first study to examine structural correlates of non-verbal cognitive ability in a large sample of typically developing 5-year-olds. The findings are generally in line with prior findings from older age groups, with the important addition of the positive association between volume / surface area in the right medial occipital region and non-verbal cognitive ability. This finding adds to the literature by discovering a new brain region that should be considered in future studies exploring the role of cortical structure for cognitive development in young children.

The effect of processing pipelines, input images and age on automatic cortical morphology estimates

BACKGROUND AND OBJECTIVE

Magnetic resonance imaging of the brain allows to enrich the study of the relationship between cortical morphology, healthy ageing, diseases and cognition. Since manual segmentation of the cerebral cortex is time consuming and subjective, many software packages have been developed. FreeSurfer (FS) and Advanced Normalization Tools (ANTs) are the most used and allow as inputs a T1-weighted (T1w) image or its combination with a T2-weighted (T2w) image. In this study we evaluated the impact of different software and input images on cortical estimates. Additionally, we investigated whether the variation of the results depending on software and inputs is also influenced by age.

METHODS

For 240 healthy subjects, cortical thickness was computed with ANTs and FreeSurfer. Estimates were derived using both the T1w image and adding the T2w image. Significant effects due to software, input images and age range were investigated with ANOVA statistical analysis. Moreover, the accuracy of the cortical thickness estimates was assessed based on their age-prediction precision.

RESULTS

Using FreeSurfer and ANTs with T1w or T1w-T2w images resulted in significant differences in the cortical thickness estimates. These differences change with the age range of the subjects. Regardless of the images used, the more recent FS version tested exhibited the best performances in terms of age prediction.

CONCLUSIONS

Our study points out the importance of i) consistently processing data using the same tool; ii) considering the software, input images and the age range of the subjects when comparing multiple studies.

Subjective memory complaints are associated with decreased cortical thickness in Veterans with histories of mild traumatic brain injury

Objective: Memory problems are frequently endorsed in Veterans following mild traumatic brain injury (mTBI), but subjective complaints are poorly associated with objective memory performance. Few studies have examined associations between subjective memory complaints and brain morphometry. We investigated whether self-reported memory problems were associated with objective memory performance and cortical thickness in Veterans with a history of mTBI. Methods: 40 Veterans with a history of remote mTBI and 29 Veterans with no history of TBI completed the Prospective-Retrospective Memory Questionnaire (PRMQ), PTSD Checklist (PCL), California Verbal Learning Test-2nd edition (CVLT-II), and 3 T T1 structural magnetic resonance imaging. Cortical thickness was estimated in 14 a priori frontal and temporal regions. Multiple regressions adjusting for age and PCL scores examined associations between PRMQ, CVLT-II scores, and cortical thickness within each Veteran group. Results: Greater subjective memory complaints on the PRMQ were associated with lower cortical thickness in the right middle temporal gyrus (β = 0.64, q = .004), right inferior temporal gyrus (β = 0.56, q = .014), right rostral middle frontal gyrus (β = 0.45, q = .046), and right rostral anterior cingulate gyrus (β = 0.58, q = .014) in the mTBI group but not the control group (q's > .05). These associations remained significant after adjusting for CVLT-II learning. CVLT-II performance was not associated with PRMQ score or cortical thickness in either group. Conclusions: Subjective memory complaints were associated with lower cortical thickness in right frontal and temporal regions, but not with objective memory performance, in Veterans with histories of mTBI. Subjective complaints post-mTBI may indicate underlying brain morphometry independently of objective cognitive testing.

Environmental and sociocultural factors are associated with pain-related brain structure among diverse individuals with chronic musculoskeletal pain

Chronic musculoskeletal pain is a leading cause of disability worldwide. Previous research indicates ethnic/race groups are disproportionately affected by chronic pain conditions. However, when considering socioenvironmental factors these disparities are no longer observed. Ethnic/race group differences have also been reported in pain-related brain structure. Given that environmental and sociocultural factors influence biology and health outcomes, this study aimed to investigate possible environmental and sociocultural contributions to structural differences in pain-related brain regions. A total of 147 non-Hispanic black and non-Hispanic white, middle and older aged adults with knee pain in the past month and a brain MRI are included in the analyses. Individuals also provided information specific to health and pain history and environmental and sociocultural resources. In hierarchical multiple regression models, sociocultural and environmental factors explained 6%-37% of the variance in thickness of pain-related brain regions, with seven of the eight brain regions being statistically significant. In the amygdala, hippocampus, insula, bilateral primary somatosensory cortex, and thalamus, ethnicity/race provided an additional 4%-13% of explanatory value. In the rostral/caudal anterior cingulate and dorsolateral prefrontal cortex, ethnicity/race was not a predictor after accounting for environmental, sociocultural, and other demographic measures. Findings inform health disparities research by elucidating the complexity of factors contributing to previously reported ethnicity/race group differences.

To respond or not to respond: exploring empathy-related psychological and structural brain differences between placebo analgesia responders and non-responders

Introduction

Placebo responsiveness is highly variable across individuals. In the domain of pain, it may range from pronounced hypoalgesia to no response at all. Which factors predict such variation awaits clarification, as the available literature is characterized by mixed and inconclusive results. Particularly interesting in this case are social factors such as empathy or prosocial behavior, as prior work has stressed the connection between feeling pain yourself and empathizing with pain observed in others.

Methods

In a mixed confirmatory and exploratory approach, this study investigated potential psychological and structural brain differences between placebo responders and non-responders in the domain of pain. We aggregated data of four behavioral and neuroimaging studies that had been designed to investigate the effects of placebo analgesia on empathy.

Results

Analyses comparing groups of placebo responders and non-responders showed significant group differences in trait characteristics, with responders reporting increased helping behavior and lower psychopathic traits compared to non-responders. Uncorrected results further showed higher pain-related empathic concern in responders vs. non-responders. These results were accompaniedby tentative group differences in brain structure: placebo analgesia non-responders exhibited increased gray matter volume in left inferior temporal and parietal supramarginal cortical areas, and an increased cortical surface area in bilateral middle temporal cortex.

Discussion

Together, our findings suggest that modifiability of one's pain perception by means of placebo effects is linked to personality traits characterizing social emotions and behavior. They also hint that these psychological as well as brain structural characteristics might be beneficial for the identification of placebo responders. At the same time, they stress the importance of considering contextual factors such as the study setting or paradigm when investigating the association between individual characteristics and placebo responding.

Medial Prefrontal Cortex Dysfunction Mediates Working Memory Deficits in Patients With Schizophrenia

Background

Schizophrenia (SCZ) is marked by working memory (WM) deficits, which predict poor functional outcome. While most functional magnetic resonance imaging studies of WM in SCZ have focused on the dorsolateral prefrontal cortex (PFC), some recent work suggests that the medial PFC (mPFC) may play a role. We investigated whether task-evoked mPFC deactivation is associated with WM performance and whether it mediates deficits in SCZ. In addition, we investigated associations between mPFC deactivation and cortical dopamine release.

Methods

Patients with SCZ (n = 41) and healthy control participants (HCs) (n = 40) performed a visual object n-back task during functional magnetic resonance imaging. Dopamine release capacity in mPFC was quantified with [11C]FLB457 in a subset of participants (9 SCZ, 14 HCs) using an amphetamine challenge. Correlations between task-evoked deactivation and performance were assessed in mPFC and dorsolateral PFC masks and were further examined for relationships with diagnosis and dopamine release.

Results

mPFC deactivation was associated with WM task performance, but dorsolateral PFC activation was not. Deactivation in the mPFC was reduced in patients with SCZ relative to HCs and mediated the relationship between diagnosis and WM performance. In addition, mPFC deactivation was significantly and inversely associated with dopamine release capacity across groups and in HCs alone, but not in patients.

Conclusions

Reduced WM task-evoked mPFC deactivation is a mediator of, and potential substrate for, WM impairment in SCZ, although our study design does not rule out the possibility that these findings could relate to cognition in general rather than WM specifically. We further present preliminary evidence of an inverse association between deactivation during WM tasks and dopamine release capacity in the mPFC.

Comparative neuroimaging of sex differences in human and mouse brain anatomy

In vivo neuroimaging studies have established several reproducible volumetric sex differences in the human brain, but the causes of such differences are hard to parse. While mouse models are useful for understanding the cellular and mechanistic bases of sex-biased brain development in mammals, there have been no attempts to formally compare mouse and human sex differences across the whole brain to ascertain how well they translate. Addressing this question would shed critical light on use of the mouse as a translational model for sex differences in the human brain and provide insights into the degree to which sex differences in brain volume are conserved across mammals. Here, we use cross-species structural magnetic resonance imaging to carry out the first comparative neuroimaging study of sex-biased neuroanatomical organization of the human and mouse brain. In line with previous findings, we observe that in humans, males have significantly larger and more variable total brain volume; these sex differences are not mirrored in mice. After controlling for total brain volume, we observe modest cross-species congruence in the volumetric effect size of sex across 60 homologous brain regions (r=0.30; e.g.: M>F amygdala, hippocampus, bed nucleus of the stria terminalis, and hypothalamus and F>M anterior cingulate, somatosensory, and primary auditory cortices). This cross-species congruence is greater in the cortex (r=0.33) than non-cortex (r=0.16). By incorporating regional measures of gene expression in both species, we reveal that cortical regions with greater cross-species congruence in volumetric sex differences also show greater cross-species congruence in the expression profile of 2835 homologous genes. This phenomenon differentiates primary sensory regions with high congruence of sex effects and gene expression from limbic cortices where congruence in both these features was weaker between species. These findings help identify aspects of sex-biased brain anatomy present in mice that are retained, lost, or inverted in humans. More broadly, our work provides an empirical basis for targeting mechanistic studies of sex-biased brain development in mice to brain regions that best echo sex-biased brain development in humans.

The Interplay of Oxytocin and Attachment in Schizophrenic Patients: An fMRI Study

BACKGROUND

Attachment theory offers an important framework for understanding interpersonal interaction experiences. In the present study, we examined the neural correlates of attachment patterns and oxytocin in schizophrenic patients (SZP) compared to healthy controls (HC) using fMRI. We assumed that male SZP shows a higher proportion of insecure attachment and an altered level of oxytocin compared to HC. On a neural level, we hypothesized that SZP shows increased neural activation in memory and self-related brain regions during the activation of the attachment system compared to HC.

METHODS

We used an event-related design for the fMRI study based on stimuli that were derived from the Adult Attachment Projective Picture System to examine attachment representations and their neural and hormonal correlates in 20 male schizophrenic patients compared to 20 male healthy controls.

RESULTS

A higher proportion of insecure attachment in schizophrenic patients compared to HC could be confirmed. In line with our hypothesis, Oxytocin (OXT) levels in SZP were significantly lower than in HC. We found increasing brain activations in SZP when confronted with personal relevant sentences before attachment relevant pictures in the precuneus, TPJ, insula, and frontal areas compared to HC. Moreover, we found positive correlations between OXT and bilateral dlPFC, precuneus, and left ACC in SZP only.

CONCLUSION

Despite the small sample sizes, the patients' response might be considered as a mode of dysregulation when confronted with this kind of personalized attachment-related material. In the patient group, we found positive correlations between OXT and three brain areas (bilateral dlPFC, precuneus, left ACC) and may conclude that OXT might modulate within this neural network in SZP.

Functional and microstructural plasticity following social and interoceptive mental training

The human brain supports social cognitive functions, including Theory of Mind, empathy, and compassion, through its intrinsic hierarchical organization. However, it remains unclear how the learning and refinement of social skills shapes brain function and structure. We studied if different types of social mental training induce changes in cortical function and microstructure, investigating 332 healthy adults (197 women, 20-55 years) with repeated multimodal neuroimaging and behavioral testing. Our neuroimaging approach examined longitudinal changes in cortical functional gradients and myelin-sensitive T1 relaxometry, two complementary measures of cortical hierarchical organization. We observed marked changes in intrinsic cortical function and microstructure, which varied as a function of social training content. In particular, cortical function and microstructure changed as a result of attention-mindfulness and socio-cognitive training in regions functionally associated with attention and interoception, including insular and parietal cortices. Conversely, socio-affective and socio-cognitive training resulted in differential microstructural changes in regions classically implicated in interoceptive and emotional processing, including insular and orbitofrontal areas, but did not result in functional reorganization. Notably, longitudinal changes in cortical function and microstructure predicted behavioral change in attention, compassion and perspective-taking. Our work demonstrates functional and microstructural plasticity after the training of social-interoceptive functions, and illustrates the bidirectional relationship between brain organisation and human social skills.

Modular pipeline for reconstruction and localization of implanted intracranial ECoG and sEEG electrodes

Implantation of electrodes in the brain has been used as a clinical tool for decades to stimulate and record brain activity. As this method increasingly becomes the standard of care for several disorders and diseases, there is a growing need to quickly and accurately localize the electrodes once they are placed within the brain. We share here a protocol pipeline for localizing electrodes implanted in the brain, which we have applied to more than 260 patients, that is accessible to multiple skill levels and modular in execution. This pipeline uses multiple software packages to prioritize flexibility by permitting multiple different parallel outputs while minimizing the number of steps for each output. These outputs include co-registered imaging, electrode coordinates, 2D and 3D visualizations of the implants, automatic surface and volumetric localizations of the brain regions per electrode, and anonymization and data sharing tools. We demonstrate here some of the pipeline's visualizations and automatic localization algorithms which we have applied to determine appropriate stimulation targets, to conduct seizure dynamics analysis, and to localize neural activity from cognitive tasks in previous studies. Further, the output facilitates the extraction of information such as the probability of grey matter intersection or the nearest anatomic structure per electrode contact across all data sets that go through the pipeline. We expect that this pipeline will be a useful framework for researchers and clinicians alike to localize implanted electrodes in the human brain.

Relationship between function and structure in the visual cortex in healthy individuals and in patients with severe mental disorders

Patients with schizophrenia spectrum disorders (SCZ_spect) and bipolar disorders (BD) show impaired function in the primary visual cortex (V1), indicated by altered visual evoked potential (VEP). While the neural substrate for altered VEP in these patients remains elusive, altered V1 structure may play a role. One previous study found a positive relationship between the amplitude of the P100 component of the VEP and V1 surface area, but not V1 thickness, in a small sample of healthy individuals. Here, we aimed to replicate these findings in a larger healthy control (HC) sample (n = 307) and to examine the same relationship in patients with SCZ_spect (n = 30) or BD (n = 45). We also compared the mean P100 amplitude, V1 surface area and V1 thickness between controls and patients and found no significant group differences. In HC only, we found a significant positive P100-V1 surface area association, while there were no significant P100-V1 thickness relationships in HC, SCZ_spect or BD. Together, our results confirm previous findings of a positive P100-V1 surface area association in HC, whereas larger patient samples are needed to further clarify the function-structure relationship in V1 in SCZ_spect and BD.

The neuroanatomical hallmarks of chronic tinnitus in comorbidity with pure-tone hearing loss

Tinnitus is one of the main hearing impairments often associated with pure-tone hearing loss, and typically manifested in the perception of phantom sounds. Nevertheless, tinnitus has traditionally been studied in isolation without necessarily considering auditory ghosting and hearing loss as part of the same syndrome. Hence, in the present neuroanatomical study, we attempted to pave the way toward a better understanding of the tinnitus syndrome, and compared two groups of almost perfectly matched individuals with (TIHL) and without (NTHL) pure-tone tinnitus, but both characterized by pure-tone hearing loss. The two groups were homogenized in terms of sample size, age, gender, handedness, education, and hearing loss. Furthermore, since the assessment of pure-tone hearing thresholds alone is not sufficient to describe the full spectrum of hearing abilities, the two groups were also harmonized for supra-threshold hearing estimates which were collected using temporal compression, frequency selectivity und speech-in-noise tasks. Regions-of-interest (ROI) analyses based on key brain structures identified in previous neuroimaging studies showed that the TIHL group exhibited increased cortical volume (CV) and surface area (CSA) of the right supramarginal gyrus and posterior planum temporale (PT) as well as CSA of the left middle-anterior part of the superior temporal sulcus (STS). The TIHL group also demonstrated larger volumes of the left amygdala and of the left head and body of the hippocampus. Notably, vertex-wise multiple linear regression analyses additionally brought to light that CSA of a specific cluster, which was located in the left middle-anterior part of the STS and overlapped with the one found to be significant in the between-group analyses, was positively associated with tinnitus distress level. Furthermore, distress also positively correlated with CSA of gray matter vertices in the right dorsal prefrontal cortex and the right posterior STS, whereas tinnitus duration was positively associated with CSA and CV of the right angular gyrus (AG) and posterior part of the STS. These results provide new insights into the critical gray matter architecture of the tinnitus syndrome matrix responsible for the emergence, maintenance and distress of auditory phantom sensations.

The Effect of Physical Exercise on People with Psychosis: A Qualitative Critical Review of Neuroimaging Findings

Recently, genuine motor abnormalities have been recognized as prodromal and predictive signs of psychosis onset and progression. Therefore, physical exercise could represent a potentially relevant clinical tool in promoting the reshaping of neural connections in motor circuitry. The aim of this review is to provide an overview of the literature on neuroimaging findings as a result of physical treatment in psychosis cohorts. Twenty-one studies, all research articles, were included and discussed in this narrative review. Here, we first outlined how the psychotic brain is susceptible to structural plastic changes after aerobic physical training in pathognomic brain areas (i.e., temporal, hippocampal and parahippocampal regions). Secondly, we focused on functional changes, both region-specific and in terms of connections, to gain insights into the involvement of distant but inter-related neural regions in the plastic process occurring after treatment. Third, we attempted to bridge neural plastic changes occurring after physical interventions with clinical and cognitive outcomes of psychotic patients in order to assess the relevance of such neural reshaping in the psychiatric rehabilitation field. In conclusion, we suggest that the current state of the art is presenting physical intervention as effective in promoting neural changes for patients with psychosis; it is not only useful at the onset of the pathology but also in improving the course of the illness and its functional outcome. However, more evidence is needed to improve our knowledge of the efficacy of physical exercise in plastically reorganizing the psychotic brain in the long term, especially within regions lacking specific investigations, such as motor circuitry.

Differential Structural Brain Changes Between Responders and Nonresponders After Physical Exercise Therapy for Chronic Nonspecific Neck Pain

OBJECTIVES

Physical exercise therapy is effective for some people with chronic nonspecific neck pain but not for others. Differences in exercise-induced pain-modulatory responses are likely driven by brain changes. We investigated structural brain differences at baseline and changes after an exercise intervention. The primary aim was to investigate changes in structural brain characteristics after physical exercise therapy for people with chronic nonspecific neck pain. The secondary aims were to investigate (1) baseline differences in structural brain characteristics between responders and nonresponders to exercise therapy, and (2) differential brain changes after exercise therapy between responders and nonresponders.

MATERIALS AND METHODS

This was a prospective longitudinal cohort study. Twenty-four participants (18 females, mean age 39.7 y) with chronic nonspecific neck pain were included. Responders were selected as those with ≥20% improvement in Neck Disability Index. Structural magnetic resonance imaging was obtained before and after an 8-week physical exercise intervention delivered by a physiotherapist. Freesurfer cluster-wise analyses were performed and supplemented with an analysis of pain-specific brain regions of interest.

RESULTS

Various changes in grey matter volume and thickness were found after the intervention, for example, frontal cortex volume decreased (cluster-weighted P value = 0.0002, 95% CI: 0.0000-0.0004). We found numerous differences between responders and nonresponders, most notably, after the exercise intervention bilateral insular volume decreased in responders, but increased in nonresponders (cluster-weighted P value ≤ 0.0002).

DISCUSSION

The brain changes found in this study may underpin clinically observed differential effects between responders and nonresponders to exercise therapy for people with chronic neck pain. Identification of these changes is an important step toward personalized treatment approaches.

One Size Does Not Fit All: Methodological Considerations for Brain-Based Predictive Modeling in Psychiatry

Psychiatric illnesses are heterogeneous in nature. No illness manifests in the same way across individuals, and no two patients with a shared diagnosis exhibit identical symptom profiles. Over the last several decades, group-level analyses of in vivo neuroimaging data have led to fundamental advances in our understanding of the neurobiology of psychiatric illnesses. More recently, access to computational resources and large, publicly available datasets alongside the rise of predictive modeling and precision medicine approaches have facilitated the study of psychiatric illnesses at an individual level. Data-driven machine learning analyses can be applied to identify disease-relevant biological subtypes, predict individual symptom profiles, and recommend personalized therapeutic interventions. However, when developing these predictive models, methodological choices must be carefully considered to ensure accurate, robust, and interpretable results. Choices pertaining to algorithms, neuroimaging modalities and states, data transformation, phenotypes, parcellations, sample sizes, and populations we are specifically studying can influence model performance. Here, we review applications of neuroimaging-based machine learning models to study psychiatric illnesses and discuss the effects of different methodological choices on model performance. An understanding of these effects is crucial for the proper implementation of predictive models in psychiatry and will facilitate more accurate diagnoses, prognoses, and therapeutics.

Detecting Cortical Thickness Changes in Epileptogenic Lesions Using Machine Learning

Epilepsy is a neurological disorder characterized by abnormal brain activity. Epileptic patients suffer from unpredictable seizures, which may cause a loss of awareness. Seizures are considered drug resistant if treatment does not affect success. This leads practitioners to calculate the cortical thickness to measure the distance between the brain’s white and grey matter surfaces at various locations to perform a surgical intervention. In this study, we introduce using machine learning as an approach to classify extracted measurements from T1-weighted magnetic resonance imaging. Data were collected from the epilepsy unit at King Abdulaziz University Hospital. We applied two trials to classify the extracted measurements from T1-weighted MRI for drug-resistant epilepsy and healthy control subjects. The preprocessing sequence on T1-weighted MRI images was performed using C++ through BrainSuite’s pipeline. The first trial was performed on seven different combinations of four commonly selected measurements. The best performance was achieved in Exp6 and Exp7, with 80.00% accuracy, 83.00% recall score, and 83.88% precision. It is noticeable that grey matter volume and white matter volume measurements are more significant than the cortical thickness measurement. The second trial applied four different machine learning classifiers after applying 10-fold cross-validation and principal component analysis on all extracted measurements as in the first trial based on the mentioned previous works. The K-nearest neighbours model outperformed the other machine learning classifiers with 97.11% accuracy, 75.00% recall score, and 75.00% precision.

A Cross-Species Neuroimaging Study of Sex Chromosome Dosage Effects on Human and Mouse Brain Anatomy

All eutherian mammals show chromosomal sex determination with contrasting sex chromosome dosages (SCDs) between males (XY) and females (XX). Studies in transgenic mice and humans with sex chromosome trisomy (SCT) have revealed direct SCD effects on regional mammalian brain anatomy, but we lack a formal test for cross-species conservation of these effects. Here, we develop a harmonized framework for comparative structural neuroimaging and apply this to systematically profile SCD effects on regional brain anatomy in both humans and mice by contrasting groups with SCT (XXY and XYY) versus XY controls. Total brain size was substantially altered by SCT in humans (significantly decreased by XXY and increased by XYY), but not in mice. Robust and spatially convergent effects of XXY and XYY on regional brain volume were observed in humans, but not mice, when controlling for global volume differences. However, mice do show subtle effects of XXY and XYY on regional volume, although there is not a general spatial convergence in these effects within mice or between species. Notwithstanding this general lack of conservation in SCT effects, we detect several brain regions that show overlapping effects of XXY and XYY both within and between species (cerebellar, parietal, and orbitofrontal cortex), thereby nominating high priority targets for future translational dissection of SCD effects on the mammalian brain. Our study introduces a generalizable framework for comparative neuroimaging in humans and mice and applies this to achieve a cross-species comparison of SCD effects on the mammalian brain through the lens of SCT.SIGNIFICANCE STATEMENT Sex chromosome dosage (SCD) affects neuroanatomy and risk for psychopathology in humans. Performing mechanistic studies in the human brain is challenging but possible in mouse models. Here, we develop a framework for cross-species neuroimaging analysis and use this to show that an added X- or Y-chromosome significantly alters human brain anatomy but has muted effects in the mouse brain. However, we do find evidence for conserved cross-species impact of an added chromosome in the fronto-parietal cortices and cerebellum, which point to regions for future mechanistic dissection of sex chromosome dosage effects on brain development.

Cortical connectomic mediations on gamma band synchronization in schizophrenia

Aberrant gamma frequency neural oscillations in schizophrenia have been well demonstrated using auditory steady-state responses (ASSR). However, the neural circuits underlying 40 Hz ASSR deficits in schizophrenia remain poorly understood. Sixty-six patients with schizophrenia spectrum disorders and 85 age- and gender-matched healthy controls completed one electroencephalography session measuring 40 Hz ASSR and one imaging session for resting-state functional connectivity (rsFC) assessments. The associations between the normalized power of 40 Hz ASSR and rsFC were assessed via linear regression and mediation models. We found that rsFC among auditory, precentral, postcentral, and prefrontal cortices were positively associated with 40 Hz ASSR in patients and controls separately and in the combined sample. The mediation analysis further confirmed that the deficit of gamma band ASSR in schizophrenia was nearly fully mediated by three of the rsFC circuits between right superior temporal gyrus-left medial prefrontal cortex (MPFC), left MPFC-left postcentral gyrus (PoG), and left precentral gyrus-right PoG. Gamma-band ASSR deficits in schizophrenia may be associated with deficient circuitry level connectivity to support gamma frequency synchronization. Correcting gamma band deficits in schizophrenia may require corrective interventions to normalize these aberrant networks.

Neurocognitive considerations in the treatment of meningioma with radiation therapy: applications for quantitative neuroimaging and precision radiation medicine

This article focuses on the role of radiotherapy in the management of meningioma, in the definitive and adjuvant setting and across the spectrum of meningioma grade. Treatment paradigms, informed by clinical evidence, are discussed. Notably, we focus on the impact of radiotherapy on normal brain tissues and neurocognitive function, particularly the dose-dependent changes in white matter and cerebral cortex thickness. Novel imaging techniques have allowed the identification of microstructural changes to eloquent white matter, cortex, and subcortical regions as biomarkers for understanding RT-induced changes in cognitive functioning. Deficits in multiple domains including attention, memory, language and executive function can become more pronounced following radiation. Longitudinal assessment with imaging and neurocognitive testing pre- and post-radiation have allowed correlation between dose to specific regions of the brain and decline in associated domains of neurocognitive function. These findings suggest incorporation of areas at higher risk for neurocognitive sequelae into precision radiation planning. Volumetric arc therapy, advanced planning with cortical sparing, proton therapy and stereotactic radiosurgery are reviewed as options for delivering therapeutic dose to target volumes while minimizing risk to adjacent sensitive regions. The treatment of meningioma is an evolving area, with improving outcomes for higher grade disease in modern trials, where care must be taken to maximize both disease control as well as quality of life for patients.

Impact of Eating a Carbohydrate-Restricted Diet on Cortical Atrophy in a Cross-Section of Amyloid Positive Patients with Alzheimer's Disease: A Small Sample Study

BACKGROUND

A carbohydrate-restricted diet aimed at lowering insulin levels has the potential to slow Alzheimer's disease (AD). Restricting carbohydrate consumption reduces insulin resistance, which could improve glucose uptake and neural health. A hallmark feature of AD is widespread cortical thinning; however, no study has demonstrated that lower net carbohydrate (nCHO) intake is linked to attenuated cortical atrophy in patients with AD and confirmed amyloidosis.

OBJECTIVE

We tested the hypothesis that individuals with AD and confirmed amyloid burden eating a carbohydrate-restricted diet have thicker cortex than those eating a moderate-to-high carbohydrate diet.

METHODS

A total of 31 patients (mean age 71.4±7.0 years) with AD and confirmed amyloid burden were divided into two groups based on a 130 g/day nCHO cutoff. Cortical thickness was estimated from T1-weighted MRI using FreeSurfer. Cortical surface analyses were corrected for multiple comparisons using cluster-wise probability. We assessed group differences using a two-tailed two-independent sample t-test. Linear regression analyses using nCHO as a continuous variable, accounting for confounders, were also conducted.

RESULTS

The lower nCHO group had significantly thicker cortex within somatomotor and visual networks. Linear regression analysis revealed that lower nCHO intake levels had a significant association with cortical thickness within the frontoparietal, cingulo-opercular, and visual networks.

CONCLUSIONS

Restricting carbohydrates may be associated with reduced atrophy in patients with AD. Lowering nCHO to under 130 g/day would allow patients to follow the well-validated MIND diet while benefiting from lower insulin levels.

Brain magnetic resonance imaging surface-based analysis and cortical thickness measurement in relapsing remission multiple sclerosis

Background

Damage occurs in the brain tissue in MS which appears normal on standard conventional imaging (normal appearing brain tissue). This slow, evolving damage can be monitored by nonconventional advanced MR imaging techniques. New techniques for the measurement of cortical thickness have been validated against histological analysis and manual measurements. The aim of our study was to study the role of MRI surface-based analysis and cortical thickness measurement in the evaluation of patients with Relapsing Remitting Multiple Sclerosis and to detect if there is localized rather than generalized cortical atrophy in Multiple Sclerosis patients and correlating these findings with clinical data.

Results

30 patients and 30 healthy control were included in this study and they were subjected to cortical thickness analysis using MRI. The patients in our study showed decreased thickness of the precentral, paracentral, postcentral, posterior cingulate cortices and mean cortical thickness in both hemispheres when compared with the normal control group. Statistical analysis was significant (P value < 0.05) for the precentral, paracentral, postcentral, posterior cingulate cortices and mean cortical thickness in both hemispheres. On the other hand, statistical analysis was not significant (P value > 0.05) for other cortices. There was a significant negative correlation between the precentral, paracentral, postcentral, posterior cingulate cortices and mean cortical thickness in both hemispheres and EDSS scores with correlation coefficients ranging from − 0.9878 to − 0.7977.

Conclusions

MRI and post-processing segmentation analysis for cortical thickness is non-invasive imaging techniques that can increase the level of diagnostic confidence in diagnosis of MS patients and should be included as routine modality when evaluating patients with MS.

Right Superior Frontal Gyrus Cortical Thickness in Pediatric ADHD

OBJECTIVE

We investigated the right Superior Frontal Gyrus (right-SFG) and Anterior Cingulate Cortex (ACC) in children with ADHD and their clinical relevance with Executive Function (EF) and ADHD symptom severity.

METHODS

About 26 children with ADHD and 24 typically developing children (TDC; 7‒16 years) underwent Magnetic Resonance Imaging (MRI) and completed an EF assessment battery.

RESULTS

Significantly thinner right-SFG in the ADHD group was found compared to the TDC group (t (48) = 2.81, p = .007, Cohen's d = 0.84). Linear regression models showed that 12.5% of inattention, 13.6% of hyperactivity, and 9.0% of EF variance was accounted for by the right-SFG thickness.

CONCLUSIONS

Differences in the right-SFG thickness were found in our ADHD group and were associated with parent ratings of inattentive and hyperactive symptoms as well with EF ratings. These results replicate previous findings of thinner right-SFG and are consistent with the delayed cortical maturation theory of ADHD.

Machine learning based multi-modal prediction of future decline toward Alzheimer's disease: An empirical study

Alzheimer's disease (AD) is a neurodegenerative condition that progresses over decades. Early detection of individuals at high risk of future progression toward AD is likely to be of critical significance for the successful treatment and/or prevention of this devastating disease. In this paper, we present an empirical study to characterize how predictable an individual subjects' future AD trajectory is, several years in advance, based on rich multi-modal data, and using modern deep learning methods. Crucially, the machine learning strategy we propose can handle different future time horizons and can be trained with heterogeneous data that exhibit missingness and non-uniform follow-up visit times. Our experiments demonstrate that our strategy yields predictions that are more accurate than a model trained on a single time horizon (e.g. 3 years), which is common practice in prior literature. We also provide a comparison between linear and nonlinear models, verifying the well-established insight that the latter can offer a boost in performance. Our results also confirm that predicting future decline for cognitively normal (CN) individuals is more challenging than for individuals with mild cognitive impairment (MCI). Intriguingly, however, we discover that prediction accuracy decreases with increasing time horizon for CN subjects, but the trend is in the opposite direction for MCI subjects. Additionally, we quantify the contribution of different data types in prediction, which yields novel insights into the utility of different biomarkers. We find that molecular biomarkers are not as helpful for CN individuals as they are for MCI individuals, whereas magnetic resonance imaging biomarkers (hippocampus volume, specifically) offer a significant boost in prediction accuracy for CN individuals. Finally, we show how our model's prediction reveals the evolution of individual-level progression risk over a five-year time horizon. Our code is available at https://github.com/batuhankmkaraman/mlbasedad.

Common gray matter loss in the frontal cortex in patients with methamphetamine-associated psychosis and schizophrenia

BACKGROUND AND HYPOTHESIS

Methamphetamine (MA)-associated psychosis has become a public concern. However, its mechanism is not clear. Investigating similarities and differences between MA-associated psychosis and schizophrenia in brain alterations would be informative for neuropathology.

STUDY DESIGN

This study compared gray matter volumes of the brain across four participant groups: healthy controls (HC, n = 53), MA users without psychosis (MA, n = 22), patients with MA-associated psychosis (MAP, n = 34) and patients with schizophrenia (SCZ, n = 33). Clinical predictors of brain alterations, as well as association of brain alterations with psychotic symptoms and attention impairment were further investigated.

STUDY RESULTS

Compared with the HC, the MAP and the SCZ showed similar gray matter reductions in the frontal cortex, particularly in prefrontal areas. Moreover, a stepwise extension of gray matter reductions was exhibited across the MA - MAP - SCZ. Duration of abstinence was associated with regional volumetric recovery in the MAP, while this amendment in brain morphometry was not accompanied with symptom's remission. Illness duration of psychosis was among the predictive factors of regional gray matter reductions in both psychotic groups. Volume reductions were found to be associated with attention impairment in the SCZ, while this association was reversed in the MAP in frontal cortex.

CONCLUSIONS

This study suggested MA-associated psychosis and schizophrenia had common neuropathology in cognitive-related frontal cortices. A continuum of neuropathology between MA use and schizophrenia was tentatively implicated. Illness progressions and glial repairments could both play roles in neuropathological changes in MA-associated psychosis.

White Matter Microstructure and Gray Matter Volume in Cannabis-Induced Psychosis and Schizophrenia With Cannabis Use

OBJECTIVE

This study explored the differences in white matter (WM) microstructural integrity and gray matter (GM) volume between cannabis-induced psychosis (CIP) and schizophrenia with cannabis use (SZC).

METHODS

This cross-sectional study with convenience sampling involved three groups of 20 participants each (CIP, SZC, and a control group without substance use), matched on age, handedness, and education. CIP and SZC were diagnosed with the Psychiatric Research Interview for Substance and Mental Disorders. Diffusion tensor and kurtosis imaging were done, and fractional anisotropy (FA), mean diffusivity, and mean kurtosis were estimated. GM volume was measured with voxel-based morphometry.

RESULTS

Group comparisons revealed comparable age at initiation and duration and frequency of cannabis use between participants in the SZC and CIP groups. Participants with SZC had lower FA than controls in the anterior and retrolenticular internal capsule limbs, cingulate gyrus hippocampal formation, fornix, and superior fronto-occipital fasciculus (all p<0.05). Participants with CIP had lower FA than controls in the left fornix and right superior fronto-occipital fasciculus but higher FA than those with SZC in the left corticospinal tract (all p<0.05). On morphometry, participants with CIP had greater cerebellar GM volume than those with SZC and greater inferior frontal gyrus volumes than controls (all p<0.05).

CONCLUSIONS

Widespread WM microstructural abnormalities were observed in participants with SZC, and fewer but significant WM disruptions were observed in those with CIP. Better WM integrity in some WM fiber tracts and greater GM volumes in crucial brain areas among those with CIP may have prevented the transition to schizophrenia.

Association of reduced cortical thickness and psychopathological symptoms in patients with first-episode drug-naïve schizophrenia

OBJECTIVE

There is growing evidence that reduced cortical thickness has been considered to be a central abnormality in schizophrenia. Brain imaging studies have demonstrated that the cerebral cortex becomes thinner in patients with first-episode schizophrenia. This study aimed to examine whether cortical thickness is altered in drug-naïve schizophrenia in a Chinese Han population and the relationship between cortical thickness and clinical symptoms.

METHODS

We compared cortical thickness in 41 schizophrenia patients and 30 healthy controls. Psychopathology of patients with schizophrenia was assessed using the Positive and Negative Syndrome Scale (PANSS).

RESULTS

The cortical thickness of left banks of superior temporal sulcus, left lateral occipital gyrus, left rostral middle frontal gyrus, right inferior parietal lobule and right lateral occipital gyrus in schizophrenia patients was generally thinner compared with healthy controls. Correlation analysis revealed a negative correlation between cortical thickness of the left banks of superior temporal sulcus and general psychopathology of PANSS.

CONCLUSIONS

Our results suggest that cortical thickness abnormalities are already present early in the onset of schizophrenia and are associated with psychopathological symptoms, suggesting that it plays an important role in the pathogenesis and symptomatology of schizophrenia.Key points(1) The first-episode drug-naïve schizophrenia had reduced cortical thickness than the controls.(2) Cortical thickness was associated with psychopathological symptoms in patients with schizophrenia.

The impact of smoking status on cognition and brain morphology in schizophrenia spectrum disorders

BACKGROUND

Cigarette smoking is associated with worse cognition and decreased cortical volume and thickness in healthy cohorts. Chronic cigarette smoking is prevalent in schizophrenia spectrum disorders (SSD), but the effects of smoking status on the brain and cognition in SSD are not clear. This study aimed to understand whether cognitive performance and brain morphology differed between smoking and non-smoking individuals with SSD compared to healthy controls.

METHODS

Data were obtained from the Australian Schizophrenia Research Bank. Cognitive functioning was measured in 299 controls and 455 SSD patients. Cortical volume, thickness and surface area data were analysed from T1-weighted structural scans obtained in a subset of the sample (n = 82 controls, n = 201 SSD). Associations between smoking status (cigarette smoker/non-smoker), cognition and brain morphology were tested using analyses of covariance, including diagnosis as a moderator.

RESULTS

No smoking by diagnosis interactions were evident, and no significant differences were revealed between smokers and non-smokers across any of the variables measured, with the exception of a significantly thinner left posterior cingulate in smokers compared to non-smokers. Several main effects of smoking in the cognitive, volume and thickness analyses were initially significant but did not survive false discovery rate (FDR) correction.

CONCLUSIONS

Despite the general absence of significant FDR-corrected findings, trend-level effects suggest the possibility that subtle smoking-related effects exist but were not uncovered due to low statistical power. An investigation of this topic is encouraged to confirm and expand on our findings.

Epigenetic Effects in HPA Axis Genes Associated with Cortical Thickness, ERP Components and SUD Outcome

Association between familial loading for alcohol use disorders (AUD) and event-related potentials (ERPs) suggests a genetic basis for these oscillations though much less is known about epigenetic pathways influenced by environmental variation. Early life adversity (ELA) influences negative outcomes much later in life. The stress-activated neuropeptide corticotropin-releasing hormone (CRH) contributes to the deleterious effects of ELA on brain structure and function in animals. Accordingly, we hypothesized that ELA would be related to cortical thickness and electrophysiological characteristics through an epigenetic effect on CRH receptor type-1 (CRHR1) methylation. A total of 217 adolescent and young adult participants from either multiplex alcohol dependence or control families were scanned using magnetic resonance imaging (MRI) at 3T and cortical thickness was determined. Longitudinal follow-up across childhood, adolescence, and young adulthood provided developmental ERP data and measures of adversity. Blood samples for genetic and epigenetic analyses were obtained in childhood. Cortical thickness and visual ERP components were analyzed for their association and tested for familial risk group differences. Visual P300 amplitude at Pz and cortical thickness of the left lateral orbitofrontal region (LOFC), were significantly related to risk group status. LOFC cortical thickness showed a negative correlation with CRHR1 methylation status and with childhood total stress scores from the Life Stressors and Social Resources Inventory (LISRES). Stress scores were also significantly related to P300 amplitude recorded in childhood. The present results suggest that early life adversity reflected in greater total LISRES stress scores in childhood can impact the methylation of the CRHR1 gene with implications for brain development as seen in cortical thickness and electrophysiological signals emanating from particular brain regions.

Dopamine, Psychosis, and Symptom Fluctuation: A Narrative Review

It has been hypothesized since the 1960s that the etiology of schizophrenia is linked to dopamine. In the intervening 60 years, sophisticated brain imaging techniques, genetic/epigenetic advances, and new experimental animal models of schizophrenia have transformed schizophrenia research. The disease is now conceptualized as a heterogeneous neurodevelopmental disorder expressed phenotypically in four symptom domains: positive, negative, cognitive, and affective. The aim of this paper is threefold: (a) to review recent research into schizophrenia etiology, (b) to review papers that elicited subjective evidence from patients as to triggers and repressors of symptoms such as auditory hallucinations or paranoid thoughts, and (c) to address the potential role of dopamine in schizophrenia in general and, in particular, in the fluctuations in schizophrenia symptoms. The review also includes new discoveries in schizophrenia research, pointing to the involvement of both striatal neurons and glia, signaling pathway convergence, and the role of stress. It also addresses potential therapeutic implications. We conclude with the hope that this paper opens up novel avenues of research and new possibilities for treatment.

Lithium increases cortical and subcortical volumes in subjects with bipolar disorder

Bipolar disorder (BD) is a highly variable and burdensome disease for patients and caregivers. A BD diagnosis almost triples the likelihood of developing dementia as the disease progresses. Neurocognitive reserve appears to be one of the most important influences on lifelong functional outcomes and quality of life in BD. Though several prior studies have assessed the effects of lithium on regional gray and white matter volumes in this population, representative cohorts are typically middle-aged, have a more severe pathology, and are not as commonly assessed in the depressive phase (which represents the majority of most patients' lifespans outside of remission). Here we have shown that positive adaptations with lithium can be observed throughout the brain after only six weeks of monotherapy at low-therapeutic serum levels. Importantly, these results remove some confounders seen in prior studies (patients were treatment free at time of enrollment and mostly treatment naïve). This cohort also includes underrepresented demographics in the literature (young adult patients, mostly bipolar II, and exclusively in the depressed phase). These findings bolster the extensive body of evidence in support of long-term lithium therapy in BD, furthering the possibility of its expanded use to wider demographics.

Frequency-Specific Analysis of the Dynamic Reconfiguration of the Brain in Patients with Schizophrenia

The analysis of resting-state fMRI signals usually focuses on the low-frequency range/band (0.01−0.1 Hz), which does not cover all aspects of brain activity. Studies have shown that distinct frequency bands can capture unique fluctuations in brain activity, with high-frequency signals (>0.1 Hz) providing valuable information for the diagnosis of schizophrenia. We hypothesized that it is meaningful to study the dynamic reconfiguration of schizophrenia through different frequencies. Therefore, this study used resting-state functional magnetic resonance (RS-fMRI) data from 42 schizophrenia and 40 normal controls to investigate dynamic network reconfiguration in multiple frequency bands (0.01−0.25 Hz, 0.01−0.027 Hz, 0.027−0.073 Hz, 0.073−0.198 Hz, 0.198−0.25 Hz). Based on the time-varying dynamic network constructed for each frequency band, we compared the dynamic reconfiguration of schizophrenia and normal controls by calculating the recruitment and integration. The experimental results showed that the differences between schizophrenia and normal controls are observed in the full frequency, which is more significant in slow3. In addition, as visual network, attention network, and default mode network differ a lot from each other, they can show a high degree of connectivity, which indicates that the functional network of schizophrenia is affected by the abnormal brain state in these areas. These shreds of evidence provide a new perspective and promote the current understanding of the characteristics of dynamic brain networks in schizophrenia.

Longitudinal Allometry of Sulcal Morphology in Health and Schizophrenia

Scaling between subcomponents of folding and total brain volume (TBV) in healthy individuals (HIs) is allometric. It is unclear whether this is true in schizophrenia (SZ) or first-episode psychosis (FEP). This study confirmed normative allometric scaling norms in HIs using discovery and replication samples. Cross-sectional and longitudinal diagnostic differences in folding subcomponents were then assessed using an allometric framework. Structural imaging from a longitudinal (Sample 1: HI and SZ, nHI Baseline = 298, nSZ Baseline = 169, nHI Follow-up = 293, nSZ Follow-up = 168, totaling 1087 images, all individuals ≥ 2 images, age 16-69 years) and a cross-sectional sample (Sample 2: nHI = 61 and nFEP = 89, age 10-30 years), all human males and females, is leveraged to calculate global folding and its nested subcomponents: sulcation index (SI, total sulcal/cortical hull area) and determinants of sulcal area: sulcal length and sulcal depth. Scaling of SI, sulcal area, and sulcal length with TBV in SZ and FEP was allometric and did not differ from HIs. Longitudinal age trajectories demonstrated steeper loss of SI and sulcal area through adulthood in SZ. Longitudinal allometric analysis revealed that both annual change in SI and sulcal area was significantly stronger related to change in TBV in SZ compared with HIs. Our results detail the first evidence of the disproportionate contribution of changes in SI and sulcal area to TBV changes in SZ. Longitudinal allometric analysis of sulcal morphology provides deeper insight into lifespan trajectories of cortical folding in SZ.SIGNIFICANCE STATEMENT Psychotic disorders are associated with deficits in cortical folding and brain size, but we lack knowledge of how these two morphometric features are related. We leverage cross-sectional and longitudinal samples in which we decompose folding into a set of nested subcomponents: sulcal and hull area, and sulcal depth and length. We reveal that, in both schizophrenia and first-episode psychosis, (1) scaling of subcomponents with brain size is different from expected scaling laws and (2) caution is warranted when interpreting results from traditional methods for brain size correction. Longitudinal allometric scaling points to loss of sulcal area as a principal contributor to loss of brain size in schizophrenia. These findings advance the understanding of cortical folding atypicalities in psychotic disorders.

Feasibility of FreeSurfer Processing for T1-Weighted Brain Images of 5-Year-Olds: Semiautomated Protocol of FinnBrain Neuroimaging Lab

Pediatric neuroimaging is a quickly developing field that still faces important methodological challenges. Pediatric images usually have more motion artifact than adult images. The artifact can cause visible errors in brain segmentation, and one way to address it is to manually edit the segmented images. Variability in editing and quality control protocols may complicate comparisons between studies. In this article, we describe in detail the semiautomated segmentation and quality control protocol of structural brain images that was used in FinnBrain Birth Cohort Study and relies on the well-established FreeSurfer v6.0 and ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) consortium tools. The participants were typically developing 5-year-olds [n = 134, 5.34 (SD 0.06) years, 62 girls]. Following a dichotomous quality rating scale for inclusion and exclusion of images, we explored the quality on a region of interest level to exclude all regions with major segmentation errors. The effects of manual edits on cortical thickness values were relatively minor: less than 2% in all regions. Supplementary Material cover registration and additional edit options in FreeSurfer and comparison to the computational anatomy toolbox (CAT12). Overall, we conclude that despite minor imperfections FreeSurfer can be reliably used to segment cortical metrics from T1-weighted images of 5-year-old children with appropriate quality assessment in place. However, custom templates may be needed to optimize the results for the subcortical areas. Through visual assessment on a level of individual regions of interest, our semiautomated segmentation protocol is hopefully helpful for investigators working with similar data sets, and for ensuring high quality pediatric neuroimaging data.

Advanced Brain-Age in Psychotic Psychopathology: Evidence for Transdiagnostic Neurodevelopmental Origins

Schizophrenia is characterized by abnormal brain structure such as global reductions in gray matter volume. Machine learning models trained to estimate the age of brains from structural neuroimaging data consistently show advanced brain-age to be associated with schizophrenia. Yet, it is unclear whether advanced brain-age is specific to schizophrenia compared to other psychotic disorders, and whether evidence that brain structure is "older" than chronological age actually reflects neurodevelopmental rather than atrophic processes. It is also unknown whether advanced brain-age is associated with genetic liability for psychosis carried by biological relatives of people with schizophrenia. We used the Brain-Age Regression Analysis and Computation Utility Software (BARACUS) prediction model and calculated the residualized brain-age gap of 332 adults (163 individuals with psychotic disorders: 105 schizophrenia, 17 schizoaffective disorder, 41 bipolar I disorder with psychotic features; 103 first-degree biological relatives; 66 controls). The model estimated advanced brain-ages for people with psychosis in comparison to controls and relatives, with no differences among psychotic disorders or between relatives and controls. Specifically, the model revealed an enlarged brain-age gap for schizophrenia and bipolar disorder with psychotic features. Advanced brain-age was associated with lower cognitive and general functioning in the full sample. Among relatives, cognitive performance and schizotypal symptoms were related to brain-age gap, suggesting that advanced brain-age is associated with the subtle expressions associated with psychosis. Exploratory longitudinal analyses suggested that brain aging was not accelerated in individuals with a psychotic disorder. In sum, we found that people with psychotic disorders, irrespective of specific diagnosis or illness severity, show indications of non-progressive, advanced brain-age. These findings support a transdiagnostic, neurodevelopmental formulation of structural brain abnormalities in psychotic psychopathology.

Association of cognitive impairment and reduced cortical thickness in prefrontal cortex and anterior cingulate cortex with treatment-resistant depression

Accumulating evidence suggests the critical role of cortical thinning in the pathophysiology of major depressive disorder. However, the association of cortical thickness and cognitive impairment with treatment-resistant depression (TRD) has rarely been investigated. In total, 48 adult patients with TRD and 48 healthy controls were recruited and administered a series of neurocognitive and neuroimaging examinations, including 1-back and 2-back working memory tasks and brain magnetic resonance imaging (MRI). Whole-brain cortical thickness analysis was performed to investigate the differences in the cortical thickness between patients with TRD and controls. The patients had reduced cortical thickness in the frontal cortex, particularly at the left frontal pole, left inferior frontal cortex, and left anterior cingulate cortex, and left middle temporal cortex compared with the healthy controls. Moreover, in the 2-back working memory task, the cortical thickness in the left frontal pole and left anterior cingulate cortex was positively associated with mean error in the patients, but not in the controls. Reduced cortical thickness in the frontal pole and anterior cingulate cortex is associated with TRD and related cognitive impairment. Our study indicated the crucial effects of the frontal and temporal cortical thickness on the pathophysiology of TRD and cognitive impairment in patients with TRD.

Quantitative and histologically validated measures of the entorhinal subfields in ex vivo MRI

Neuroimaging studies have routinely used hippocampal volume as a measure of Alzheimer's disease severity, but hippocampal changes occur too late in the disease process for potential therapies to be effective. The entorhinal cortex is one of the first cortical areas affected by Alzheimer's disease; its neurons are especially vulnerable to neurofibrillary tangles. Entorhinal atrophy also relates to the conversion from non-clinical to clinical Alzheimer's disease. In neuroimaging, the human entorhinal cortex has so far mostly been considered in its entirety or divided into a medial and a lateral region. Cytoarchitectonic differences provide the opportunity for subfield parcellation. We investigated the entorhinal cortex on a subfield-specific level-at a critical time point of Alzheimer's disease progression. While MRI allows multidimensional quantitative measurements, only histology provides enough accuracy to determine subfield boundaries-the pre-requisite for quantitative measurements within the entorhinal cortex. This study used histological data to validate ultra-high-resolution 7 Tesla ex vivo MRI and create entorhinal subfield parcellations in a total of 10 pre-clinical Alzheimer's disease and normal control cases. Using ex vivo MRI, eight entorhinal subfields (olfactory, rostral, medial intermediate, intermediate, lateral rostral, lateral caudal, caudal, and caudal limiting) were characterized for cortical thickness, volume, and pial surface area. Our data indicated no influence of sex, or Braak and Braak staging on volume, cortical thickness, or pial surface area. The volume and pial surface area for mean whole entorhinal cortex were 1131 ± 55.72 mm³ and 429 ± 22.6 mm² (mean ± SEM), respectively. The subfield volume percentages relative to the entire entorhinal cortex were olfactory: 18.73 ± 1.82%, rostral: 14.06 ± 0.63%, lateral rostral: 14.81 ± 1.22%, medial intermediate: 6.72 ± 0.72%, intermediate: 23.36 ± 1.85%, lateral caudal: 5.42 ± 0.33%, caudal: 10.99 ± 1.02%, and caudal limiting: 5.91 ± 0.40% (all mean ± SEM). Olfactory and intermediate subfield revealed the most extensive intra-individual variability (cross-subject variance) in volume and pial surface area. This study provides validated measures. It maps individuality and demonstrates human variability in the entorhinal cortex, providing a baseline for approaches in individualized medicine. Taken together, this study serves as a ground-truth validation study for future in vivo comparisons and treatments.

Influence of pre-treatment structural brain measures on effects of action-based cognitive remediation on executive function in partially or fully remitted patients with bipolar disorder

Cognitive impairment is an emerging treatment target in patients with bipolar disorder (BD) but so far, no evidence-based treatment options are available. Recent studies indicate promising effects of Cognitive Remediation (CR) interventions, but it is unclear who responds most to these interventions. This report aimed to investigate whether pre-treatment dorsal prefrontal cortex (dPFC) thickness predicts improvement of executive function in response to Action-Based Cognitive Remediation (ABCR) in patients with BD. Complete baseline magnetic resonance imaging (MRI) data were available from 45 partially or fully remitted patients with BD from our randomized controlled ABCR trial (ABCR: n = 25, control group: n = 20). We performed cortical reconstruction and volumetric segmentation using FreeSurfer. Multiple linear regression analysis was conducted to assess the influence of dPFC thickness on ABCR-related executive function improvement, reflected by change in the One Touch Stocking of Cambridge performance from baseline to post-treatment. We also conducted whole brain vertex wise analysis for exploratory purposes. Groups were well-matched for demographic and clinical variables. Less pre-treatment dPFC thickness was associated with greater effect of ABCR on executive function (p = 0.02). Further, whole-brain vertex analysis revealed an association between smaller pre-treatment superior temporal gyrus volume and greater ABCR-related executive function improvement. The observed associations suggest that structural abnormalities in dPFC and superior temporal gyrus are key neurocircuitry treatment targets for CR interventions that target impaired executive function in BD.

Machine learning classification of schizophrenia patients and healthy controls using diverse neuroanatomical markers and Ensemble methods

Schizophrenia is a major psychiatric disorder that imposes enormous clinical burden on patients and their caregivers. Determining classification biomarkers can complement clinical measures and improve understanding of the neural basis underlying schizophrenia. Using neuroanatomical features, several machine learning based investigations have attempted to classify schizophrenia from healthy controls but the range of neuroanatomical measures employed have been limited in range to date. In this study, we sought to classify schizophrenia and healthy control cohorts using a diverse set of neuroanatomical measures (cortical and subcortical volumes, cortical areas and thickness, cortical mean curvature) and adopted Ensemble methods for better performance. Additionally, we correlated such neuroanatomical features with Quality of Life (QoL) assessment scores within the schizophrenia cohort. With Ensemble methods and diverse neuroanatomical measures, we achieved classification accuracies ranging from 83 to 87%, sensitivities and specificities varying between 90-98% and 65-70% respectively. In addition to lower QoL scores within schizophrenia cohort, significant correlations were found between specific neuroanatomical measures and psychological health, social relationship subscale domains of QoL. Our results suggest the utility of inclusion of subcortical and cortical measures and Ensemble methods to achieve better classification performance and their potential impact of parsing out neurobiological correlates of quality of life in schizophrenia.

Cortical Thickness and Clinical Findings in Prescholar Children With Autism Spectrum Disorder

The term autism spectrum disorder (ASD) includes a wide variability of clinical presentation, and this clinical heterogeneity seems to reflect a still unclear multifactorial etiopathogenesis, encompassing different genetic risk factors and susceptibility to environmental factors. Several studies and many theories recognize as mechanisms of autism a disruption of brain development and maturation time course, suggesting the existence of common neurobiological substrates, such as defective synaptic structure and aberrant brain connectivity. Magnetic resonance imaging (MRI) plays an important role in both assessment of region-specific structural changes and quantification of specific alterations in gray or white matter, which could lead to the identification of an MRI biomarker. In this study, we performed measurement of cortical thickness in a selected well-known group of preschool ASD subjects with the aim of finding correlation between cortical metrics and clinical scores to understand the underlying mechanism of symptoms and to support early clinical diagnosis. Our results confirm that recent brain MRI techniques combined with clinical data can provide some useful information in defining the cerebral regions involved in ASD although large sample studies with homogeneous analytical and multisite approaches are needed.

Vascular Mapping of the Human Hippocampus Using Ferumoxytol-Enhanced MRI

The hippocampus is a small but complex grey matter structure that plays an important role in spatial and episodic memory and can be affected by a wide range of pathologies including vascular abnormalities. In this work, we introduce the use of Ferumoxytol, an ultra-small superparamagnetic iron oxide (USPIO) agent, to induce susceptibility in the arteries (as well as increase the susceptibility in the veins) to map the hippocampal micro-vasculature and to evaluate the quantitative change in tissue fractional vascular density (FVD), in each of its subfields. A total of 39 healthy subjects (aged 35.4 ± 14.2 years, from 18 to 81 years old) were scanned with a high-resolution (0.22×0.44×1 mm³) dual-echo SWI sequence acquired at four time points during a gradual increase in Ferumoxytol dose (final dose = 4 mg/kg). The volumes of each subfield were obtained automatically from the pre-contrast T₁ -weighted data. The dynamically acquired SWI data were co-registered and adaptively combined to reduce the blooming artifacts from large vessels, preserving the contrast from smaller vessels. The resultant SWI data were used to segment the hippocampal vasculature and to measure the FVD ((volume occupied by vessels)/(total volume)) for each subfield. The hippocampal fissure, along with the fimbria, granular cell layer of the dentate gyrus and cornu ammonis layers (except for CA1), showed higher micro-vascular FVD than the other parts of hippocampus. The CA1 region exhibited a significant correlation with age (R = −0.37, p < 0.05). demonstrating an overall loss of hippocampal vascularity in the normal aging process. Moreover, the vascular density reduction was more prominent than the age correlation with the volume reduction (R = −0.1, p > 0.05) of the CA1 subfield, which would suggest that vascular degeneration may precede tissue atrophy.