A voxel-based morphometric study of ageing in 465 normal adult human brains

Hemispheric asymmetry in language-related brain regions

Structural asymmetries of the human brain have been widely studied in previous research. However, there is a lack of consistency across studies in terms of whether brain regions are larger in the left hemisphere than the right (leftward asymmetry), larger in the right hemisphere than the left (rightward asymmetry), or similar in both hemispheres (no asymmetry). Moreover, some of the existing studies exploring brain asymmetry were based on only small sample sizes and/or restricted to younger participants. Thus, here we analysed brain asymmetry in a well-powered sample (n = 532) later in life (mean age: 67 years). Given that language is known to be strongly lateralized in the brain, the current study focused on regions related to language. When assessing cortical volumes and surface areas, we observed significant leftward asymmetries for the superior temporal gyrus, superior temporal sulcus, supramarginal gyrus, pars opercularis, transverse gyrus, and temporal gyrus, whereas the pars triangularis showed a significant rightward asymmetry. In contrast, when assessing cortical thickness, we detected a significant leftward asymmetry for the pars triangularis and a significant rightward asymmetry for the superior temporal sulcus. The present observations on asymmetry in language-related brain regions in a large sample of older but neurologically healthy participants may serve as a normative framework against which data from clinical samples can be compared.

Exploring neural changes associated with suicidal ideation and attempts in major depressive disorder: A multimodal study

Suicidal ideation (SI) and suicide attempts (SA) are highly prevalent in individuals with major depressive disorder (MDD). To explore the structural and functional neural changes associated with SI and SA, we analyzed multimodal Magnetic Resonance Imaging (MRI) data from 159 participants, including those with MDD with suicide attempts (SA group, n = 34), those with MDD with suicidal ideation but not attempts (SI group, n = 53), those with MDD without suicidal ideation (NSI group, n = 14), and healthy controls (HC, n = 59). Voxel-based morphometry (VBM) analysis was performed to estimate and compare gray matter volume (GMV) across groups. Subsequently, a seed-based resting-state functional connectivity (rsFC) analysis was conducted to explore the functional networks associated with the structural brain changes related to suicidal ideation and suicide attempts. Compared with the HC and NSI groups, the SI group showed decreased GMV in the left dorsolateral prefrontal cortex (DLPFC), insula, fusiform gyrus, right posterior cerebellum, and right middle temporal gyrus. Additionally, when compared to the HC and SI groups, the SA group demonstrated smaller GMV in the right superior medial frontal gyrus (SFGmed), left superior and inferior occipital gyri, and superior temporal gyrus (STG), and right cuneus, but larger GMV in the right STG. Moreover, GMV in the insula, cerebellum posterior lobe, and SFGmed was negatively correlated with the scores of the Beck Scale for Suicide Ideation (BSSI). The rsFC analysis revealed weaker rsFC between the left insula and the left SFG as well as between the bilateral middle frontal orbital gyrus and the right SFGmed and the left middle occipital gyrus, but stronger rsFC of the right cerebellum posterior lobe with the left precentral gyrus and right parahippocampal gyrus among the SI group compared to the NSI group and HCs. Additionally, the SA group demonstrated weaker rsFC between the right cerebellum posterior lobe and the left cerebellum posterior lobe as well as the right lingual gyrus, but stronger rsFC between the right SFGmed and the left middle temporal gyrus and right inferior parietal lobule compared to the SI group. Our results indicate that structural and functional changes related to insula, DLPFC and cerebellum posterior lobe are associated with the generation and escalation of SI in MDD, while the structural and functional changes related to SFGmed and STG play a crucial role in the transformation from SI to SA in MDD.

Changes in topological properties of brain structural covariance networks and alertness in temporal lobe epilepsy with and without focal to bilateral tonic-clonic seizures

This study investigated brain structural covariance network (SCN) topological changes and alertness in temporal lobe epilepsy (TLE) with and without focal to bilateral tonic-clonic seizures (FBTCS). Seventy-eight subjects, including 32 TLE patients with FBTCS (TLE-FBTCS), 46 TLE patients without FBTCS (TLE-FS), and 42 healthy controls (HCs), underwent the Attention Network Test to assess alertness and volumetric MRI scans. SCNs were constructed and analyzed using graph theory. Results showed that TLE-FS patients had lower total cerebral volume than HCs, and the lowest volume was observed in the TLE-FBTCS group. Compared to HCs and TLE-FBTCS patients, TLE-FS patients exhibited increased small-worldness, normalized clustering coefficient, global efficiency, and modularity, but decreased normalized characteristic shortest path length and assortativity. Specific brain regions, such as the hippocampus, thalamus, and superior temporal sulcus, showed changes in nodal clustering coefficients and efficiency in TLE-FS patients. Further analysis revealed decreased intrinsic/phasic alertness in TLE-FBTCS patients. Correlation analysis indicated that SCN topological properties were associated with alertness in TLE-FS patients but not in TLE-FBTCS patients. These findings suggest that TLE-FS and TLE-FBTCS patients show different changes in SCN integration and segregation, with TLE-FS alertness linked to SCN topological properties, providing insights into TLE's neuropathological mechanisms.

Longitudinal analysis highlights structural changes in grey- and white-matter within military personnel exposed to blast

OBJECTIVE

The purpose of this study was to determine whether gray matter volume and diffusion-based metrics in associated white matter changed in breachers who had neuroimaging performed at two timepoints. A secondary purpose was to compare these changes in a group who had a one-year interval between their imaging timepoints to a group that had a two-year interval between imaging.

METHODS

Between timepoints, clusters with significantly different gray matter volume were used as seeds for reconstruction of associated structural networks using diffusion metrics.

RESULTS

Of 92 eligible participants, 62 had imaging at two timepoints, 36 with a one-year interval between scans and 26 with a two-year interval between scans. A significant effect of time was documented in the midcingulate cortex, but there was no effect of timepoint (1 versus 2 years). The associated white matter in this cluster had three regions with differences in fractional anisotropy compared to baseline, while there was no effect of timepoint (1 versus 2 years).

CONCLUSIONS

This study provides preliminary evidence that military personnel involved in repetitive exposure to sub-concussive blast overpressures may experience changes to both gray matter and white matter structures.

Pediatric Opsoclonus-Myoclonus-Ataxia Syndrome can Lead to Long-Term Neurological, Neuropsychological, and Cognitive Sequelae Associated with Cerebellar Atrophy

To outline the long-term neuropsychological profile of a pediatric cohort with Opsoclonus-Myoclonus-Ataxia Syndrome (OMAS), and evaluate whether volumetric brain abnormalities correlate with clinical findings years after onset. Twelve patients diagnosed with OMAS between 2008 and 2020 (6 males, mean age 9.6 years, median follow-up 5.4 years) underwent a videorecorded neurological examination and a standardized cognitive and neuropsychological assessment. Patients and 12 age-matched controls underwent advanced 3-Tesla brain MRI studies. Voxel-Based Morphometry (VBM) and targeted cerebellar evaluation using ACAPULCO and ENIGMA pipelines were performed. The results were correlated with neuropsychological scores. Nine subjects (75%) had abnormal neurological findings (dysmetria n = 7, balance deficit n = 7, and speech impairment n = 6). The mean Full-Scale IQ was 76, with borderline IQ in 2 cases, intellectual disability in 5, visuospatial processing impairments in 6, and affective and internalizing issues in 7. Brain MRI and VBM showed mild cerebellar atrophy (41.6%), especially in Crus I-II, IV, VIIIa and VIIb lobules. Reduced gray matter volumes were noted in the precentral, inferior-occipital and middle orbitofrontal gyrus, while larger volumes were found in the ventral diencephalon fusiform and inferior temporal gyri. Lower white matter volumes were found in the cerebellum, superior frontal gyrus, midbrain, postcentral and precentral gyri. Patients with lower cognitive scores, especially in Working Memory and Processing Speed, had smaller volumes in several cerebellar lobules (p = 0.001). Smaller cerebellar volumes correlate with lower cognitive scores at long-term follow-up, confirming not only the role of the cerebellum in the pathogenesis of OMAS, but also its role in cognitive functioning.

AI-based association analysis for medical imaging using latent-space geometric confounder correction

This study addresses the challenges of confounding effects and interpretability in artificial-intelligence-based medical image analysis. Whereas existing literature often resolves confounding by removing confounder-related information from latent representations, this strategy risks affecting image reconstruction quality in generative models, thus limiting their applicability in feature visualization. To tackle this, we propose a different strategy that retains confounder-related information in latent representations while finding an alternative confounder-free representation of the image data. Our approach views the latent space of an autoencoder as a vector space, where imaging-related variables, such as the learning target (t) and confounder (c), have a vector capturing their variability. The confounding problem is addressed by searching a confounder-free vector which is orthogonal to the confounder-related vector but maximally collinear to the target-related vector. To achieve this, we introduce a novel correlation-based loss that not only performs vector searching in the latent space, but also encourages the encoder to generate latent representations linearly correlated with the variables. Subsequently, we interpret the confounder-free representation by sampling and reconstructing images along the confounder-free vector. The efficacy and flexibility of our proposed method are demonstrated across three applications, accommodating multiple confounders and utilizing diverse image modalities. Results affirm the method's effectiveness in reducing confounder influences, preventing wrong or misleading associations, and offering a unique visual interpretation for in-depth investigations by clinical and epidemiological researchers. The code is released in the following GitLab repository: https://gitlab.com/radiology/compopbio/ai_based_association_analysis.

Neuroplastic changes in patients with functional seizures following neurobehavioral therapy

Given the high prevalence of functional neurological symptom disorder and its negative effects on the individual, family, and society, the development of interventions to treat it-including the subtype of functional seizures (FS)-is critical.Although we have limited understanding of the neurobiological effects of neurobehavioral therapy (NBT), studies indicate that NBT reduces seizures and improves psychological comorbidities in FS. In this study, healthy adults (N = 33) and patients with a history of TBI with (TBI-FS; N = 50) and without FS (TBI-only; N = 50) underwent magnetic resonance imaging (MRI) at 3 T approximately 12 weeks apart. TBI-FS participants underwent up to 12 sessions of NBT between scans. Structural MRI data were analyzed using voxel-based morphometry. A voxelwise repeated measures ANOVA tested changes in grey matter volume (GMV) between groups over time. Following treatment with NBT, TBI-FS participants showed a 1.23 % GMV increase in the left inferior and middle temporal gyri (pFWE < 0.05) along with a 35.78 % reduction in seizure events and decrease in depressive (p < 0.001) and anxiety (p = 0.01) symptoms. Left temporal GMV increases were directly associated (p = 0.04, r = 0.26) with improvements in overall psychological, social, and occupational functioning (p < 0.001). We observed structural brain changes within the left inferior temporal gyrus following NBT that correspond to functional and psychological improvements in patients with TBI-FS. This work highlights the need for further research into the neurobiological effects of NBT, building on the relationship between NBT and brain plasticity and demonstrating putative targets for interventions.

Comparing high and low amyloid producers in Alzheimer's disease: An in-depth analysis

BACKGROUND

The cerebrospinal fluid (CSF) Aβ42/40 ratio has proven to be a more reliable biomarker for amyloid pathology than CSF Aβ42 in Alzheimer's disease (AD), helping to correctly classify patients with positive tau biomarkers (T+) that would otherwise have remained outside of the AD continuum. It was shown that the Aβ42/40 ratio better captures a relative decrease of Aβ42 in patients with high CSF Aβ. However, whether patients with high-amyloid (HiA) AD, in whom A+ is defined by the Aβ42/40 ratio, exactly compare with their low-amyloid (LoA) counterparts, in whom A+ is defined by Aβ42 solely, deserves further analysis.

METHODS

We retrospectively included patients with A+T+ AD and evidence of cognitive and neurodegenerative changes (N+). LoA patients were operationally defined as patients with T+N+ and low CSF Aβ42, while HiA patients were defined as patients with T+N+ and normal CSF Aβ42 but abnormal Aβ42/40 ratio. Tau CSF biomarkers, neuropsychological profile, rates of cognitive decline, structural and metabolic imaging, ApoE genotype and brain neuropathology were compared between the HiA and LoA groups.

RESULTS

At the time of the lumbar puncture, LoA patients were significantly younger than the HiA patients (68.9±8.7years vs. 71.8±9.4; P=0.0015) and had a lower Mini-Mental Status Examination (MMSE) (18.7±6.4 vs. 20.7±6.2; P=0.0005). There was no difference in the neuropsychological profile nor in the annual rates of cognitive decline between the two groups with early AD. No differences were retrieved between groups on CSF Tau and P-Tau biomarkers, atrophy and brain metabolism, distribution of the APOE4 allele and APOE4/E4 genotype, and neuropathology.

CONCLUSIONS

Overall, our study supports the surrogate use of the Aβ42/40 ratio as an equivalent to Aβ42 to define AD. We showed that HiA CSF profiles were not associated with differences in cognition, brain structures and metabolism, APOE genotype tau CSF biomarkers or the rates of cognitive decline, but may be the associated with later-onset and early-stage AD.

Sex differences in clinical phenotypes of behavioral variant frontotemporal dementia

INTRODUCTION

Higher male prevalence in sporadic behavioral variant frontotemporal dementia (bvFTD) has been reported. We hypothesized differences in phenotypes between genetic and sporadic bvFTD females resulting in underdiagnosis of sporadic bvFTD females.

METHODS

We included genetic and sporadic bvFTD patients from two multicenter cohorts. We compared behavioral and cognitive symptoms, and gray matter volumes, between genetic and sporadic cases in each sex.

RESULTS

Females with sporadic bvFTD showed worse compulsive behavior (p = 0.026) and language impairments (p = 0.024) compared to females with genetic bvFTD (n = 152). Genetic bvFTD females had smaller gray matter volumes than sporadic bvFTD females, particularly in the parietal lobe.

DISCUSSION

Females with sporadic bvFTD exhibit a distinct clinical phenotype compared to females with genetic bvFTD. This difference may explain the discrepancy in prevalence between genetic and sporadic cases, as some females without genetic mutations may be misdiagnosed due to atypical bvFTD symptom presentation.

HIGHLIGHTS

Sex ratio is equal in genetic behavioral variant of frontotemporal dementia (bvFTD), whereas more males are present in sporadic bvFTD. Distinct neuropsychiatric phenotypes exist between sporadic and genetic bvFTD in females. Phenotype might explain the sex ratio difference between sporadic and genetic cases.

Olfactory Testing and Gray Matter Volume: A Combined Approach to Predict the Conversion to Alzheimer

Background/Objectives: Olfactory decline is common in normal aging and frequent in neurodegenerative diseases such as Alzheimer's disease (AD). Therefore, it has been suggested as a marker for the Mild Cognitive Impairment (MCI) progression to AD. Although suggested, the relationship between olfactory deficits and cerebral atrophy in MCI conversion to AD is still debated. This study aims at investigating the olfaction-related morphological and behavioural alterations in MCI in order to understand whether they can predict the progression to AD. Methods: Twenty-seven MCI patients and thirty-five healthy controls (HCs) took part in the study, with follow-up showing conversion to AD in thirteen patients (converter-MCI, cMCI). The Burgarth Sniffin' Sticks Tests (threshold-TT, discrimination-DT, identification-IT) assessed the olfactory capacities. The Voxel-Based Morphometry (VBM) analysis investigated the atrophic patterns. Results: The Receiving Operating Characteristics analyses demonstrated that DT and IT could distinguish HC from MCI (DT Area Under Curve-AUC = 0.8; IT AUC = 0.8), as well as cMCI from sMCI (stable) patients (DT AUC = 0.7; IT AUC = 0.6), similarly to memory and executive functions tests. Olfactory performance positively correlated with memory tests in sMCI (all rhos ≥ 0.8, all ps < 0.01), whereas it positively correlated with executive functions in cMCI (all rhos ≥ 0.6, all ps < 0.05). VBM results revealed distinct atrophic patterns in cMCI, especially in the olfactory cortex, that were already present at the MCI diagnosis, before AD conversion. A larger volume of the olfactory cortex was associated with better memory and executive functions. Conclusions: Quantitative olfactory and morphological patterns represent non-invasive, predictive biomarkers of the MCI progression to AD; thus, their assessments at MCI onset allows earlier interventions for MCI patients.

Ethnoracial disparities in gray matter atrophy are mediated by structural disconnectivity in multiple sclerosis

OBJECTIVE

To investigate ethnoracial disparities in gray matter (GM) atrophy, the contribution of white matter lesions and consequent structural disconnectivity among patients with multiple sclerosis (MS).

METHODS

This retrospective study included 297 patients with MS (pwMS), 98 Hispanic/Latinx (H-MS), 82 non-Hispanic Black (B-MS), and 117 non-Hispanic White (W-MS). GM atrophy was assessed using univariate, voxel-based morphometry, and multivariate techniques, source-based morphometry. Structural disconnectivity secondary to white matter lesions was evaluated using the network modification tool. Mediation analyses explored relationships between ethnoracial groups, white matter lesions, structural disconnectivity, and gray matter atrophy.

RESULTS

B-MS and H-MS generally exhibited greater gray matter atrophy compared to W-MS, particularly in temporal, parahippocampal, precuneus, and cuneus GM. Structural disconnectivity differences were most prominent in the hippocampal, cingulate, precuneus, and deep gray matter regions. Mediation analyses revealed that lesion load significantly mediated group differences in global GM atrophy (percent mediated = 52.4%), while structural disconnectivity mediated some differences in specific gray matter components, notably in deep gray matter, insular, and anterior cingulate regions.

INTERPRETATION

Significant ethnoracial disparities exist in GM atrophy and its patterns among diverse MS patients, partially mediated by white matter lesions and consequent structural disconnectivity. These findings underscore the importance of considering ethnoracial factors in MS research and clinical practice, potentially informing personalized treatment strategies and emphasizing the need for diverse representation in clinical trials.

Volumetric alterations in auditory and visual subcortical nuclei following perinatal deafness in felines

In response to sensory deprivation, the brain adapts to efficiently navigate a modified perceptual environment through a process referred to as compensatory crossmodal plasticity, allowing the remaining senses to repurpose deprived regions and networks. A mechanism that has been proposed to contribute to this plasticity involves adaptations within subcortical nuclei that trigger cascading effects throughout the brain. The current study uses 7T MRI to investigate the effect of perinatal deafness on the volumes of subcortical structures in felines, focusing on key sensory nuclei within the brainstem and thalamus. Using both ROI-based and morphometric approaches, the regional macrostructure of four auditory and two visual nuclei were studied, as well as the corresponding volumetric asymmetries within and across groups. In the auditory pathway, significant bilateral volumetric reductions were revealed within the lower-level structures (cochlear nucleus, superior olivary complex, and inferior colliculus), alongside a shrinkage of solely the left medial geniculate body. Within the visual pathway, a significant bilateral volumetric reduction was found in the lateral geniculate nucleus, with the superior colliculus largely unaffected. These regional alterations, along with an extensive loss of volume throughout the brainstem of deprived cats, were attributed to disuse-driven atrophy corresponding to evolved functional demands reflective of a modified perceptual environment. Furthermore, the left-right volumetric symmetries of the control subcortex were preserved following deafness. Overall, the current study reinforces the notion that subcortical structures likely contribute to compensatory crossmodal plasticity prior to cortical processing, and that these deafness-induced adaptations appear to be influenced by both the level of the affected structure within its respective sensory processing hierarchy and the specifics of its afferent profile.

The effect of age on ankle joint position sense differs between contralateral matching and ipsilateral reproduction tasks

Ankle joint angle position sense (JPS) plays a crucial role in maintaining balance and coordinating movements, yet its changes across the lifespan remain unclear. This cross-sectional study aimed to investigate changes in ankle JPS across the lifespan using an ipsilateral reproduction task (IRT) and a contralateral concurrent matching task (CMT). One hundred and fifty eight individuals (6-92yrs) were allocated into 6 groups: Young-children (YC; n = 14) and Old-children (OC; n = 15), Young (Y: 19-39yrs; n = 33), Middle-aged (M: 40-59yrs; n = 41), Young-Old (YO: 60-5yrs; n = 24) and Old-Old (OO: >76yrs; n = 31) adults. The IRT consisted of reproducing a previously experienced ankle angle with the same limb. The CMT consisted of matching the passively held target ankle angle of one limb with the contralateral ankle. Both tests were performed blind-folded from 5° and 20° plantar flexion position to a 5° dorsiflexion target position. Error was expressed in absolute (AE) and constant (CE) values. In IRT, no difference was observed for AE and CE (p > 0.05) between groups, regardless of the initial position (5° or 20°). For the CMT, no age effect was observed for AE (p > 0.05), but children and older adults showed more positive (overestimation) and more negative (underestimation) CE, respectively, regardless of the initial position (p < 0.001). These results indicate that age affects the direction of the error (CE) rather than the magnitude of the error (AE), regardless of the angular range. They further suggest that CMT and CE could be more relevant when comparing ankle JPS between populations of different ages.

Examining neuroanatomical correlates of win-stay, lose-shift behaviour

This study aimed to better understand the neuroanatomical correlates of decision-making strategies, particularly focusing on win-stay and lose-shift behaviours, using voxel-based morphometry (VBM) in a large cohort of healthy adults. Participants completed a forced-choice card-guessing task designed to elicit behavioural responses to rewards and losses. Using this task, we investigated the relationship between win-stay and lose-shift behaviour and both grey matter volume (GMV) and white matter volume (WMV). The frequency of win-stay and lose-shift behaviours was calculated for each participant and entered into VBM analyses alongside GMV and WMV measures. Our results revealed that increased lose-shift behaviour was associated with reduced GMV in key brain regions, comprising of the left superior temporal gyrus, right middle temporal gyrus, and the bilateral superior lateral occipital cortices. Interestingly, no significant associations were found between GMV or WMV, and win-stay behaviour. These results suggest that specific regions within the temporal and occipital lobes may be involved in modulating decision-making strategies following negative outcomes. Further analyses revealed that increased lose-shift behaviour was also associated with increased WMV in the left superior temporal gyrus. The absence of significant findings in relation to win-stay behaviour and the differential involvement of brain structures in lose-shift responses indicate that decision-making in the face of losses may involve distinct neuroanatomical mechanisms compared to decision-making following wins. This study advances our understanding of the structural brain correlates linked to decision-making strategies and highlights the complexity of brain-behaviour relationships in choice behaviour.

An Update on Neuroaging on Earth and in Spaceflight

Over 400 articles on the pathophysiology of brain aging, neuroaging, and neurodegeneration were reviewed, with a focus on epigenetic mechanisms and numerous non-coding RNAs. In particular, this review the accent is on microRNAs, the discovery of whose pivotal role in gene regulation was recognized by the 2024 Nobel Prize in Physiology or Medicine. Aging is not a gradual process that can be easily modeled and described. Instead, multiple temporal processes occur during aging, and they can lead to mosaic changes that are not uniform in pace. The rate of change depends on a combination of external and internal factors and can be boosted in accelerated aging. The rate can decrease in decelerated aging due to individual structural and functional reserves created by cognitive, physical training, or pharmacological interventions. Neuroaging can be caused by genetic changes, epigenetic modifications, oxidative stress, inflammation, lifestyle, and environmental factors, which are especially noticeable in space environments where adaptive changes can trigger aging-like processes. Numerous candidate molecular biomarkers specific to neuroaging need to be validated to develop diagnostics and countermeasures.

The subcortical correlates of self-reported sleep quality

Study objectives

To assess the association between self-reported measures of sleep quality and cortical and subcortical local morphometry.

Methods

Sleep quality, operationalized with the Pittsburgh Sleep Quality Index (PSQI), and neuroanatomical data from the full release of the young adult Human Connectome Project dataset were analyzed (N=1,112; 46% female; mean age: 28.8 years old). Local cortical and subcortical morphometry was measured with subject-specific segmentations resulting in voxelwise gray matter difference (i.e., voxel based morephometry) measurements for cortex and local shape measurements for subcortical regions. Associations between the total score of PSQI, two statistical groupings of its subcomponents (obtained with a principal component analysis), and their interaction with demographic (i.e., sex, age, handedness, years of education) and biometric (i.e., BMI) variables were assessed using a general linear model and a nonparametric permutation approach.

Results

Sleep quality-related variance was significantly associated with subcortical morphometry, particularly in the bilateral caudate, putamen, and left pallidum, where smaller shape measures correlated with worse sleep quality. Notably, these associations were independent of demographic and biometric factors. In contrast, cortical morphometry, along with additional subcortical sites, showed no direct associations with sleep quality but demonstrated interactions with demographic and biometric variables.

Conclusions

This study reveals a specific link between self-reported sleep quality and subcortical morphometry, particularly within the striatum and pallidum, reinforcing the role of these regions in sleep regulation. These findings underscore the importance of considering subcortical morphology in sleep research and highlight potential neuromodulatory targets for sleep-related interventions.

A high fat, high sugar diet exacerbates persistent post-surgical pain and modifies the brain-microbiota-gut axis in adolescent rats

Persistent post-surgical pain (PPSP) occurs in a proportion of patients following surgical interventions. Research suggests that specific microbiome components are important for brain development and function, with recent studies demonstrating that chronic pain results in changes to the microbiome. Consumption of a high fat, high sugar (HFHS) diet can drastically alter composition of the microbiome and is a modifiable risk factor for many neuroinflammatory conditions. Therefore, we investigated how daily consumption of a HFHS diet modified the development of PPSP, brain structure and function, and the microbiome. In addition, we identified significant correlations between the microbiome and brain in animals with PPSP. Male and female rats were maintained on a control or HFHS diet. Animals were further allocated to a sham or surgery on postnatal day (p) p35. The von Frey task measured mechanical nociceptive sensitivity at a chronic timepoint (p65-67). Between p68-72 rats underwent in-vivo MRI to examine brain volume and diffusivity. At p73 fecal samples were used for downstream 16 s rRNA sequencing. Spearman correlation analyses were performed between individual microbial abundance and MRI diffusivity to determine if specific bacterial species were associated with PPSP-induced brain changes. We found that consumption of a HFHS diet exacerbated PPSP in adolescents. The HFHS diet reduced overall brain volume and increased white and grey matter density. The HFHS diet interacted with the surgical intervention to modify diffusivity in numerous brain regions which were associated with specific changes to the microbiome. These findings demonstrate that premorbid characteristics can influence the development of PPSP and advance our understanding of the contribution that the microbiome has on function of the brain-microbiota-gut axis.

The effects of flight training on flying cadets' brain structure

In recent years, the impact of professional training on brain structure has sparked extensive research interest. Research into pilots as a high-demand, high-load, and high-cost occupation holds significant academic and economic value. The aim of this study is to investigate the effects of flight training on the brain structure and cognitive functions of flying cadets. The structural magnetic resonance imaging (sMRI) data from 39 flying cadets and 37 general college students underwent analysis using voxel-based morphometry (VBM) and surface-based morphometry (SBM) methods to quantitatively detect and compute multiple indicators, including gray matter volume (GMV), curvature, mean curvature of the white matter surface (MC-WMS), the percentage of surface white matter gray matter (WM-GM percentage), surface Jacobi (S-Jacobi), and Gaussian curvature of white matter surface (GC-WMS). At the voxel level, the GMV in the left temporal pole: middle temporal gyrus region of flying cadets significantly decreased (Gaussian random field, GRF, P < 0.05). At the surface level, there was a significant increase in curvature, MC-WMS, and S-Jacobi in the lateral occipital region of flight cadets (Monte Carlo block level correction, MCBLC, P<0.05), a significant increase in WM-GM percentage in the cuneus region of flight cadets (MCBLC, P<0.05), and a significant increase in GC-WMS in the middle temporal region of flight cadets (MCBLC, P<0.05). In addition, these changes were correlated with behavioral tests. Research suggested that flight training might induce changes in certain brain regions of flying cadets, enabling them to adapt to evolving training content and environments, thereby enhancing their problem-solving and flight abilities. By analyzing multiple indicators at the voxel and surface levels in an integrated manner, it advances our understanding of brain structure, function, and plasticity, while also facilitating a more profound exploration of the neural mechanisms within the pilot's brain.

COLLATOR: Consistent spatial-temporal longitudinal atlas construction via implicit neural representation

Longitudinal brain atlases that present brain development trend along time, are essential tools for brain development studies. However, conventional methods construct these atlases by independently averaging brain images from different individuals at discrete time points. This approach could introduce temporal inconsistencies due to variations in ontogenetic trends among samples, potentially affecting accuracy of brain developmental characteristic analysis. In this paper, we propose an implicit neural representation (INR)-based framework to improve the temporal consistency in longitudinal atlases. We treat temporal inconsistency as a 4-dimensional (4D) image denoising task, where the data consists of 3D spatial information and 1D temporal progression. We formulate the longitudinal atlas as an implicit function of the spatial-temporal coordinates, allowing structural inconsistency over the time to be considered as 3D image noise along age. Inspired by recent self-supervised denoising methods (e.g. Noise2Noise), our approach learns the noise-free and temporally continuous implicit function from inconsistent longitudinal atlas data. Finally, the time-consistent longitudinal brain atlas can be reconstructed by evaluating the denoised 4D INR function at critical brain developing time points. We evaluate our approach on three longitudinal brain atlases of different MRI modalities, demonstrating that our method significantly improves temporal consistency while accurately preserving brain structures. Additionally, the continuous functions generated by our method enable the creation of 4D atlases with higher spatial and temporal resolution. Code: https://github.com/maopaom/COLLATOR.

Individualized brain radiomics-based network tracks distinct subtypes and abnormal patterns in prodromal Parkinson's disease

Individuals in the prodromal phase of Parkinson's disease (PD) exhibit significant heterogeneity and can be divided into distinct subtypes based on clinical symptoms, pathological mechanisms, and brain network patterns. However, little has been done regarding the valid subtyping of prodromal PD, which hinders the early diagnosis of PD. Therefore, we aimed to identify the subtypes of prodromal PD using the brain radiomics-based network and examine the unique patterns linked to the clinical presentations of each subtype. Individualized brain radiomics-based network was constructed for normal controls (NC; N = 110), prodromal PD patients (N = 262), and PD patients (N = 108). A data-driven clustering approach using the radiomics-based network was carried out to cluster prodromal PD patients into higher-/lower-risk subtypes. Then, the dissociated patterns of clinical manifestations, anatomical structure alterations, and gene expression between these two subtypes were evaluated. Clustering findings indicated that one prodromal PD subtype closely resembled the pattern of NCs (N-P; N = 159), while the other was similar to the pattern of PD (P-P; N = 103). Significant differences were observed between the subtypes in terms of multiple clinical measurements, neuroimaging for morphological changes, and gene enrichment for synaptic transmission. Identification of prodromal PD subtypes based on brain connectomes and a full understanding of heterogeneity at this phase could inform early and accurate PD diagnosis and effective neuroprotective interventions.

Investigation of brain volume changes associated with aging: Results from the fourth research on osteoarthritis/osteoporosis against disability survey

AIM

This study aims to investigate the impact of aging on brain volume among community residents in Japan, focusing on trends over time and specific brain structures.

METHODS

We analyzed data from the fourth survey (2015-2016) of the Research on Osteoarthritis/Osteoporosis Against Disability project, encompassing 2146 community residents from Japan's mountainous and coastal regions. A total of 1755 participants (81.8% of the baseline population) underwent extensive data collection including lifestyle and health questionnaires, anthropometric measurements and brain magnetic resonance imaging. The imaging data were processed to examine correlations between total brain volume, gray matter volume (GMV), white matter volume (WMV), cerebrospinal fluid volume and participant age.

RESULTS

Analysis showed significant sex differences in total brain volume, with GMV demonstrating a strong negative correlation with age - more pronounced than the moderate negative correlation seen in WMV. Cerebrospinal fluid volume exhibited a strong positive correlation with age. Notably, specific brain regions such as the bilateral amygdala, hippocampus, thalamus and primary motor cortex showed significant age-related volume reductions.

CONCLUSION

This study confirms that GMV and WMV are smaller in older individuals in the Japanese population, with more pronounced differences in GMV. The amygdala, hippocampus, thalamus and primary motor cortex were particularly affected. Geriatr Gerontol Int 2025; 25: 279-286.

Comparative analysis of Voxel-based morphometry using T1 and T2-weighted magnetic resonance imaging to explore the relationship between brain structure and cognitive abilities

Voxel-based morphometry (VBM) of T1-weighted (T1-w) magnetic resonance imaging (MRI) is primarily used to study the association of brain structure with cognitive functions. However, in theory, T2-weighted (T2-w) MRI could also be used in VBM studies because of its sensitivity to pathology and tissue changes. We aimed to compare the T1-w and T2-w images to study brain structures in association with cognitive abilities. VBM analysis was applied to T1-w and T2-w MRI data of 120 healthy participants aged 20 to 40. The MRI data was collected using a 3T machine, and it was analyzed with CAT12 to extract maps of Gray matter(GM). We used six cognitive tasks to assess cognitive abilities, including the balloon analog risk task (BART), block design, forward and backward digit span (FDST and BDST), and trail-making tasks A and B. Compared to T2-w, T1-w data showed more brain voxels in the BART, block design, FDST, TMT-A, and TMT-B tasks. However, T2-w imaging identified a greater number of voxels in the BDST. T1-w images identified more correlated brain regions with cognitive scores in the FDST, TMT-A, and B tasks than T2-w. In BART and Block design tasks, both methods revealed the same number of correlated regions, and T2-w just showed more regions than T1-w in the BDST. Findings revealed distinct patterns of sensitivity between T1-w and T2-w imaging in detecting brain regions associated with cognition. The two approaches demonstrated different strengths in identifying areas correlated with cognitive abilities. This study provides valuable guidance for selecting appropriate methods for identifying the optimal approach for detecting brain regions that exhibit the strongest correlations with cognitive abilities.

Combined cognitive assessment and automated MRI volumetry improves the diagnostic accuracy of detecting MCI due to Alzheimer's disease

BACKGROUND

Mild cognitive impairment (MCI) confers a high annual risk of 10-15 % of conversion to Alzheimer's disease (AD) dementia. MRI atrophy patterns derived from automated ROI analysis, particularly hippocampal subfield volumes, were reported to be useful in diagnosing early clinical stages of Alzheimer's disease.

OBJECTIVE

The aim of the present study was to combine automated ROI MRI morphometry of hippocampal subfield volumes and cortical thickness estimates using FreeSurfer 6.0 with cognitive measures to predict disease progression and time to conversion from MCI to AD dementia.

METHODS

Baseline (Neuropsychology, MRI) and clinical follow-up data from 62 MCI patients were analysed retrospectively. Individual cortical thickness and volumetric measures were obtained from T1-weighted MRI. Linear discriminant analysis (LDA) of both, cognitive measures and MRI measures (hippocampal subfields, temporal and parietal lobe volumes), were performed to differentiate MCI converters from stable MCI patients.

RESULTS

Out of 62 MCI patients 21 (34 %) converted to AD dementia within a mean follow-up time of 74.7 ± 36.8 months (mean ± SD, range 12 to 130 months). LDA identified temporal lobe atrophy and hippocampal subfield volumes in combination with cognitive measures of verbal memory, verbal fluency and executive functions to correctly classify 71.4.% of MCI subjects converting to AD dementia and 92.7 % with stable MCI. Lower baseline GM volume of the subiculum and the superior temporal gyrus was associated with faster disease progression of MCI converters.

CONCLUSION

Combining cognitive assessment with automated ROI MRI morphometry is superior to using a single test in order to distinguish MCI due to AD from non converting MCI patients.

Predicting brain age with global-local attention network from multimodal neuroimaging data: Accuracy, generalizability, and behavioral associations

Brain age, an emerging biomarker for brain diseases and aging, is typically predicted using single-modality T1-weighted structural MRI data. This study investigates the benefits of integrating structural MRI with diffusion MRI to enhance brain age prediction. We propose an attention-based deep learning model that fuses global-context information from structural MRI with local details from diffusion metrics. The model was evaluated using two large datasets: the Human Connectome Project (HCP, n = 1064, age 22-37) and the Cambridge Center for Aging and Neuroscience (Cam-CAN, n = 639, age 18-88). It was tested for generalizability and robustness on three independent datasets (n = 546, age 20-86), reproducibility on a test-retest dataset (n = 44, age 22-35), and longitudinal consistency (n = 129, age 46-92). We also examined the relationship between predicted brain age and behavioral measures. Results showed that the multimodal model improved prediction accuracy, achieving mean absolute errors (MAEs) of 2.44 years in the HCP dataset (sagittal plane) and 4.36 years in the Cam-CAN dataset (axial plane). The corresponding R2 values were 0.258 and 0.914, respectively, reflecting the model's ability to explain variance in the predictions across both datasets. Compared to single-modality models, the multimodal approach showed better generalization, reducing MAEs by 10-76 % and enhancing robustness by 22-82 %. While the multimodal model exhibited superior reproducibility, the sMRI model showed slightly better longitudinal consistency. Importantly, the multimodal model revealed unique associations between predicted brain age and behavioral measures, such as walking endurance and loneliness in the HCP dataset, which were not detected with chronological age alone. In the Cam-CAN dataset, brain age and chronological age exhibited similar correlations with behavioral measures. By integrating sMRI and dMRI through an attention-based model, our proposed approach enhances predictive accuracy and provides deeper insights into the relationship between brain aging and behavior.

Neuroanatomical alterations in young boys and adolescents with Klinefelter syndrome

Klinefelter syndrome (KS, 47,XXY) is a common sex chromosome aneuploidy in males that is characterized by pubertal developmental delays and a wide range of alterations in cognitive, social and emotional functioning. The neural bases of these behavioral symptoms, however, are unclear. A total of 130 boys and adolescents, including 67 males with KS (11.5 ± 2.8 years) and 63 typically developing (TD; control) males (10.6 ± 2.8 years) underwent MRI scanning and pubertal assessment. Group differences in regional gray matter volume was examined using voxel-based morphometry while controlling for age at scan and total gray matter volume. Thresholded statistical significance maps indicated widespread reductions in frontal and temporal and cerebellar gray matter in males with KS relative to TD males, as well as increases in parietal and occipital gray matter. Secondary analyses explored potential associations between GMV in these regions and pubertal development. Lower testicular volume was a significant predictor of reduced GMV in frontal, temporal and cerebellar subregions, even after accounting for group status (KS, TD). Taken together, these findings add support for a neuroanatomical phenotype of KS and provide initial evidence for a role of pubertal development in KS-associated differences in gray matter structure. Future studies that examine the influence of testosterone supplementation on GMV in males with KS are warranted.

Neurostructural correlates of harm action/outcome aversion: The role of empathy

Harm aversion is essential for normal human functioning; however, the neuroanatomical mechanisms underlying harm aversion remain unclear. To explore this issue, we examined the brain structures associated with the two distinct dimensions of harm aversion (harm action/outcome aversion) and the potential mediating role of the four aspects of empathy: fantasy, perspective-taking, empathic concern, and personal distress. A sample of 214 healthy young adults underwent structural magnetic resonance imaging. Voxel-based morphometry was used to assess regional gray matter volume (rGMV) and regional gray matter density (rGMD). Whole-brain multiple regression analysis revealed significant correlations between harm action aversion and rGMV/rGMD in various brain regions, including the inferior frontal gyrus (IFG) and precuneus for both rGMV and rGMD, the cerebellum for rGMV, and the superior frontal gyrus for rGMD. The rGMV/rGMD in the IFG and the rGMD in the primary somatosensory cortex (S1) were correlated with harm outcome aversion. Utilizing 10-fold balanced cross-validation analysis, we confirmed the robustness of these significant associations between rGMV/rGMD in these brain regions and harm action/outcome aversion. Importantly, mediation analysis revealed that empathic concern mediated the relationship between rGMV/rGMD in the precuneus and harm action aversion. Additionally, empathic concern, personal distress, and total empathy mediated the relationship between rGMD in the S1 and harm outcome aversion. These findings enhance our understanding of the neural mechanism of harm aversion by integrating insights from the brain structure, harm aversion, and the personality hierarchy models while also extending the frontal asymmetry model of Emotion.

The Modulatory Effects of Transcranial Alternating Current Stimulation on Brain Oscillatory Patterns in the Beta Band in Healthy Older Adults

Background: In the last few years, transcranial alternating current stimulation (tACS) has attracted attention as a promising approach to interact with ongoing oscillatory cortical activity and, consequently, to enhance cognitive and motor processes. While tACS findings are limited by high variability in young adults' responses, its effects on brain oscillations in older adults remain largely unexplored. In fact, the modulatory effects of tACS on cortical oscillations in healthy aging participants have not yet been investigated extensively, particularly during movement. This study aimed to examine the after-effects of 20 Hz and 70 Hz High-Definition tACS on beta oscillations both during rest and movement. Methods: We recorded resting state EEG signals and during a handgrip task in 15 healthy older participants. We applied 10 min of 20 Hz HD-tACS, 70 Hz HD-tACS or Sham stimulation for 10 min. We extracted resting-state beta power and movement-related beta desynchronization (MRBD) values to compare between stimulation frequencies and across time. Results: We found that 20 Hz HD-tACS induced a significant reduction in beta power for electrodes C3 and CP3, while 70 Hz did not have any significant effects. With regards to MRBD, 20 Hz HD-tACS led to more negative values, while 70 Hz HD-tACS resulted in more positive ones for electrodes C3 and FC3. Conclusions: These findings suggest that HD-tACS can modulate beta brain oscillations with frequency specificity. They also highlight the focal impact of HD-tACS, which elicits effects on the cortical region situated directly beneath the stimulation electrode.

The CSF p-tau/β-amyloid 42 ratio correlates with brain structure and fibrillary β-amyloid deposition in cognitively unimpaired individuals at the earliest stages of pre-clinical Alzheimer's disease

CSF concentrations of β-amyloid 42 (Aβ42) and phosphorylated tau (p-tau) are well-established biomarkers of Alzheimer's disease and have been studied in relation to several neuropathological features both in patients and in cognitively unimpaired individuals. The CSF p-tau/Aβ42 ratio, a biomarker combining information from both pathophysiological processes, has emerged as a promising tool for monitoring disease progression, even at pre-clinical stages. Here, we studied the association between the CSF p-tau/Aβ42 ratio with downstream markers of pre-clinical Alzheimer's disease progression including brain structure, glucose metabolism, fibrillary Aβ deposition and cognitive performance in 234 cognitively unimpaired individuals, who underwent cognitive testing, a lumbar puncture, MRI, 18F-fluorodeoxyglucose and 18F-flutemetamol PET scanning. We evaluated both main effects and interactions with Alzheimer's disease risk factors, such as older age, female sex and the apoliporoptein E (APOE)-ɛ4 allele, in a priori defined regions of interest and further examined the associations on the whole-brain using voxel-wise regressions. In addition, as the association between CSF Alzheimer's disease biomarkers and brain structure and function may be non-linear, we tested the interaction between the CSF p-tau/Aβ42 ratio and stages of pre-clinical Alzheimer's disease defined using the amyloid (A) and tau (T) classification. We found significantly positive associations between CSF p-tau/Aβ42 and both cortical Aβ deposition and regional grey matter volume while no effect was observed for brain metabolism. A significant interaction with age indicated that, for the same level of CSF p-tau/Aβ42, older individuals displayed both increased Aβ deposition and lower grey matter volume, in widespread cortical areas. In addition, we found that women compared with men had a greater Aβ fibrillary accumulation in midline cortical areas and inferior temporal regions, for the same level of the CSF biomarker. The impact of CSF p-tau/Aβ42 on grey matter volume was modulated by AT stages, with A+T+ individuals displaying significantly less positive associations in areas of early atrophy in the Alzheimer's continuum. Finally, we found that sex and APOE-ɛ4 modulated the association between the CSF biomarker and episodic memory as well as abstract reasoning, respectively. Our data indicate that the CSF p-tau/Aβ42 ratio is strongly associated with multiple downstream neuropathological events in cognitively unimpaired individuals and may thus serve as a potent biomarker to investigate the earliest changes in pre-clinical Alzheimer's disease. Given that its impact on both Aβ deposition and grey matter volume is modulated by specific risk factors, our results highlight the need to take into account such predisposing variables in both clinical practice and prevention trials.

Effects of mixed metal exposure on MRI metrics in basal ganglia

Welding fumes contain various metals. Past studies, however, mainly focused on Manganese (Mn)-related neurotoxicity. This study investigated welding-related mixed metal exposure effects on MRI metrics in the basal ganglia (BG) and their dose-response relationship. Subjects with (N = 23) and without (N = 24) a welding exposure history were examined. Metal exposure was estimated with an exposure history questionnaire and whole blood metal levels. T1 (weighted-intensity and relaxation time; estimates of brain Mn accumulation), diffusion tensor imaging (axial [AD], mean [MD], radial diffusivity, and fractional anisotropy [FA]; estimates of microstructural differences) metrics in BG (caudate nucleus, putamen, and globus pallidus [GP]), and voxel-based morphometry (for volume) were examined and related with metal exposure measures. Compared with controls, welders showed higher GP R1 (1/T1; P = 0.034) but no differences in blood metal and T1-weighted (T1W) values in any ROIs (P's > 0.120). They also had higher AD and MD values in the GP (P's < 0.033) but lower FA values in the putamen (P = 0.039) with no morphologic differences. In welders, higher blood Mn and Vanadium (V) levels predicted higher BG R1 and T1W values (P's < 0.015). There also were significant overall metal mixture effects on GP T1W and R1 values. Moreover, GP AD and MD values showed nonlinear associations with BG T1W values: They increased with increasing T1W values only above certain threshold of T1 values. The current findings suggest that Mn and V individually but also metal mixtures jointly predict GP T1 signals that may in turn contribute to altered DTI metrics in the BG after certain exposure threshold levels.

Multimodal prediction of the need of clozapine in treatment resistant schizophrenia; a pilot study in first-episode psychosis

As many as one third of the patients diagnosed with schizophrenia do not respond to first-line antipsychotic medication. This group may benefit from the atypical antipsychotic medication clozapine, but initiation of treatment is often delayed, which may worsen prognosis. Predicting which patients do not respond to traditional antipsychotic medication at the onset of symptoms would provide fast-tracked treatment for this group of patients. We collected data from patient records of 38 first-episode psychosis patients, of whom seven did not respond to traditional antipsychotic medications. We used clinical data including medical records, voxel-based morphometry MRI data and inter-subject correlation fMRI data, obtained during movie viewing, to predict future treatment resistance. Using a neural network model, we correctly predicted future treatment resistance in six of the seven treatment resistance patients and 25 of 31 patients who did not require clozapine treatment. Prediction improved significantly when using imaging data in tandem with clinical data. The accuracy of the neural network model was significantly higher than the accuracy of a support vector machine algorithm. These results support the notion that treatment resistant schizophrenia could represent a separate entity of psychotic disorders, characterized by morphological and functional changes in the brain which could represent biomarkers detectable at early onset of symptoms.

Neuroanatomical substrates of depression in dementia with Lewy bodies and Alzheimer's disease

Dementia with Lewy bodies (DLB) and Alzheimer's disease (AD) are often associated with depressive symptoms from the prodromal stage. The aim of the present study was to investigate the neuroanatomical correlates of depression in prodromal to mild DLB patients compared with AD patients. Eighty-three DLB patients, 37 AD patients, and 18 healthy volunteers were enrolled in this study. Depression was evaluated with the Mini International Neuropsychiatric Interview (MINI), French version 5.0.0. T1-weighted three-dimensional anatomical images were acquired for all participants. Regression and comparison analyses were conducted using a whole-brain voxel-based morphometry (VBM) approach on the grey matter volume (GMV). DLB patients presented a significantly higher mean MINI score than AD patients (p = 0.004), 30.1% of DLB patients had clinical depression, and 56.6% had a history of depression, while 0% of AD patients had clinical depression and 29.7% had a history of depression. VBM regression analyses revealed negative correlations between the MINI score and the GMV of right prefrontal regions in DLB patients (p < 0.001, uncorrected). Comparison analyses between DLB patients taking and those not taking an antidepressant mainly highlighted a decreased GMV in the bilateral middle/inferior temporal gyrus (p < 0.001, uncorrected) in treated DLB patients. In line with the literature, our behavioral analyses revealed higher depression scores in DLB patients than in AD patients. We also showed that depressive symptoms in DLB are associated with decreased GMV in right prefrontal regions. Treated DLB patients with long-standing depression would be more likely to experience GMV loss in the bilateral middle/inferior temporal cortex. These findings should be taken into account when managing DLB patients.

The relative brain signal variability increases in the behavioral variant of frontotemporal dementia and Alzheimer's disease but not in schizophrenia

Overlapping symptoms between Alzheimer's disease (AD), behavioral variant of frontotemporal dementia (bvFTD), and schizophrenia (SZ) can lead to misdiagnosis and delays in appropriate treatment, especially in cases of early-onset dementia. To determine the potential of brain signal variability as a diagnostic tool, we assessed the coefficient of variation of the BOLD signal (CVBOLD) in 234 participants spanning bvFTD (n = 53), AD (n = 17), SZ (n = 23), and controls (n = 141). All underwent functional and structural MRI scans. Data unveiled a notable increase in CVBOLD in bvFTD patients across both datasets (local and international, p < 0.05), revealing an association with clinical scores (CDR and MMSE, r = 0.46 and r = -0.48, p < 0.0001). While SZ and control group demonstrated no significant differences, a comparative analysis between AD and bvFTD patients spotlighted elevated CVBOLD in the frontopolar cortices for the latter (p < 0.05). Furthermore, CVBOLD not only presented excellent diagnostic accuracy for bvFTD (AUC 0.78-0.95) but also showcased longitudinal repeatability. During a one-year follow-up, the CVBOLD levels increased by an average of 35% in the bvFTD group, compared to a 2% increase in the control group (p < 0.05). Our findings suggest that CVBOLD holds promise as a biomarker for bvFTD, offering potential for monitoring disease progression and differentiating bvFTD from AD and SZ.

Structural white matter connectivity differences independent of gray matter loss in mild cognitive impairment with neuropsychiatric symptoms: Early indicators of Alzheimer's disease using network-based statistics

BACKGROUND

Depression and circadian rhythm disruptions are non-cognitive neuropsychiatric symptoms (NPS) that can appear at any stage of the Alzheimer's disease (AD) continuum. Evidence suggests that NPS are linked to AD pathophysiology and hippocampal dysfunction.

OBJECTIVE

To examine structural white matter (WM) connectivity and its association with gray matter (GM) atrophy and to identify specific AD-related neural networks linked to NPS in individuals with mild cognitive impairment (MCI).

METHODS

Ninety-six older adults participants were divided into three groups based on the Global Depression Scale, Neuropsychiatric Inventory, Clinical Dementia Rating, and Mini-Mental Status Examination. Twelve individuals with MCI and NPS (MCI+) and 49 without NPS (MCI-) were classified, along with 35 age and gender-matched healthy individuals. Voxel-based morphometry and tract-based spatial statistics were employed to identify structural and microstructural alterations. Network-based statistics analyzed structural WM connectivity differences between MCI groups and healthy controls.

RESULTS

Significant structural WM connectivity and GM loss were exclusively observed in MCI+ individuals compared to controls. The hippocampus, amygdala, and sensory cortex showed GM atrophy (p < 0.05), while the thalamus, pallidum, putamen, caudate, hippocampus, and sensory and frontal cortices exhibited structural WM connectivity loss (p < 0.01). These data indicate early limbic system involvement even without GM atrophy.

CONCLUSIONS

Structural WM connectivity loss within the Papez circuit may precede and potentially predict GM atrophy in the temporal lobe of individuals with MCI+. These findings highlight the importance of investigating structural WM alterations in the prodromal phase of AD, which may inform diagnostic and therapeutic strategies in early AD.

Exploring age-related differences in the relationship between spatial and temporal contributions to step length asymmetry during split-belt adaptation

Gait adaptability is crucial for meeting environmental demands, and impaired gait adaptation increases fall risk, particularly in older adults. While prior research exists on older adults' gait adaptation, particularly in perturbation studies, the specific contributions of temporal and spatial adaptation strategies to step length asymmetry (SLA) during split-belt treadmill walking require further examination. This study fills this gap by evaluating how distinct adaptation strategies contribute to SLA in healthy young and older adults. 19 healthy young adults (20.4 ± 1.1 years) and 19 healthy older adults (68.3 ± 8.1 years) walked on a split-belt treadmill requiring their non-dominant leg to move twice as fast as their dominant leg. Repeated measures ANOVA investigated (1) spatial and temporal contributions to SLA, (2) SLA across gait adaptation epochs, and (3) rates of adaptation and deadaptation. Older adults displayed reduced temporal contributions to SLA compared to younger adults (F1,36 = 6.42, p = .02, ŋ2 = .15), but no group differences were observed in spatial contributions to SLA (F1,36 = 3.23, p = .08, ŋ2 = .082). SLA during adaptation and deadaptation did not differ by age group, nor did the rate of adaptation (F1,34.7 = 0.594, p = .45) or deadaptation F1,33.6 = 2.886, p = .09). These findings suggest that while older adults rely less on temporal strategies for gait adaptation, but maintain overall adaptability comparable to younger adults. Findings enhance our understanding of age-related changes in gait adaptation mechanisms and may inform targeted interventions to improve gait adaptability in older populations.

Temporal atrophy together with verbal encoding impairment is highly predictive for cognitive decline in typical Alzheimer's dementia - a retrospective follow-up study

Introduction

The increasing prevalence of Alzheimer's disease (AD) has created an urgent need for rapid and cost-effective methods to diagnose and monitor people at all stages of the disease. Progressive memory impairment and hippocampal atrophy are key features of the most common so-called typical variant of AD. However, studies evaluating detailed cognitive measures combined with region of interest (ROI)-based imaging markers of progression over the long term in the AD dementia (ADD) stage are rare.

Method

We conducted a retrospective longitudinal follow-up study in patients with mild to moderate ADD (aged 60-92 years). They underwent magnetic resonance imaging (MRI; 3 Tesla, MPRAGE) as well as clinical and neuropsychological examination (Consortium to Establish a Registry for Alzheimer's Disease [CERAD] -Plus test battery) at baseline and at least one follow-up visit. ROI-based brain structural analysis of baseline MRIs was performed using the Computational Anatomy Toolbox (CAT) 12. Clinical dementia progression (progression index [PI]) was measured by the annual decline in the Mini Mental State Examination (MMSE) scores. MRI, demographic, and neuropsychological data were included in univariate and multiple linear regression models to predict the PI.

Results

104 ADD patients (age 63 to 90 years, 73% female, mean MMSE score 22.63 ± 3.77, mean follow-up 4.27 ± 2.15 years) and 32 age- and gender-matched cognitively intact controls were included. The pattern of gray matter (GM) atrophy and the cognitive profile were consistent with the amnestic/typical variant of ADD in all patients. Deficits in word list learning together with temporal lobe GM atrophy had the highest predictive value for rapid cognitive decline in the multiple linear regression model, accounting for 25.4% of the PI variance.

Discussion

Our results show that temporal atrophy together with deficits in the encoding of verbal material, rather than in immediate or delayed recall, is highly predictive for rapid cognitive decline in patients with mild to moderate amnestic/typical ADD. These findings point to the relevance of combining detailed cognitive and automated structural imaging analyses to predict clinical progression in patients with ADD.

The interplay of age, gender and amyloid on brain and cognition in mid-life and older adults

Deficits in memory are seen as a canonical sign of aging and a prodrome to dementia in older adults. However, our understanding of age-related cognition and brain morphology occurring throughout a broader spectrum of adulthood remains limited. We quantified the relationship between cognitive function and brain morphology (sulcal width, SW) using three cross-sectional observational datasets (PISA, AIBL, ADNI) from mid-life to older adulthood, assessing the influence of age, sex, amyloid (Aβ) and genetic risk for dementia. The data comprised cognitive, genetic and neuroimaging measures of a total of 1570 non-clinical mid-life and older adults (mean age 72, range 49-90 years, 1330 males) and 1365 age- and sex-matched adults with mild cognitive impairment (MCI) or Alzheimer's disease (AD). Among non-clinical adults, we found robust modes of co-variation between regional SW and multidomain cognitive function that differed between the mid-life and older age range. These cortical and cognitive profiles derived from healthy cohorts predicted out-of-sample AD and MCI. Furthermore, Aβ-deposition and educational attainment levels were associated with cognition but not SW. These findings underscoring the complex interplay between factors influencing cognition and brain structure from mid-life onwards, providing valuable insights for future research into neurodegeneration and the development of future screening algorithms.

Structural MRI findings in the brain related to pain distribution in chronic overlapping pain conditions: An explorative case-control study in females with fibromyalgia, temporomandibular disorder-related chronic pain and pain-free controls

BACKGROUND

Few neuroimaging studies have investigated structural brain differences associated with variations in pain distribution.

OBJECTIVE

To explore structural differences of the brain in fibromyalgia (FM), temporomandibular disorder pain (TMD) and healthy pain-free controls (CON) using structural and diffusion MRI.

METHODS

A case-control exploratory study with three study groups with different pain distribution were recruited: FM (n = 16; mean age [standard deviation]: 44 [14] years), TMD (n = 17, 39 [14] years) and CON (n = 10, 37 [14] years). Participants were recruited at the University Dental Clinic in Malmö, Sweden. T1-weighted and diffusion MRIs were acquired, clinical and psychosocial measures were obtained. Main outcome measures were subcortical volume, cortical thickness, white matter microstructure and whole brain grey matter intensity.

RESULTS

Patients with FM had smaller volume in the right thalamus than patients with TMD (p = .020) and CON (p = .030). The right thalamus volume was negatively correlated to pain intensity (r = -0.37, p = .022) and pain-related disability (r = -0.45, p = .004). The FM group had lower cortical thickness in the right anterior prefrontal cortex than CON (p = .005). Cortical thickness in this area was negatively correlated to pain intensity (r [37] = - 0.48, p = .002).

CONCLUSIONS

This study suggests that thalamus grey matter alterations are associated with FM and TMD, and that anterior prefrontal cortex grey matter alterations are associated with FM but not TMD. Studies on chronic overlapping pain conditions are needed in relation to possible nociplastic pain mechanisms in the brain and central nervous system.

Interoceptive Accuracy Enhances Deception Detection in Older Adults

OBJECTIVES

Difficulties with deception detection may leave older adults especially vulnerable to fraud. Interoception, that is, the awareness of one's bodily signals, has been shown to influence deception detection, but this relationship has not been examined in aging yet. The present study investigated effects of interoceptive accuracy on 2 forms of deception detection: detecting interpersonal lies in videos and identifying text-based deception in phishing emails.

METHODS

Younger (18-34 years) and older (53-82 years) adults completed a heartbeat detection task to determine interoceptive accuracy. Deception detection was assessed across 2 distinct, ecologically valid tasks: (i) a lie detection task in which participants made veracity judgments of genuine and deceptive individuals, and (ii) a phishing email detection task to capture online deception detection. Using multilevel logistic regression models, we determined the effect of interoceptive accuracy on lie and phishing detection in younger versus older adults.

RESULTS

In older, but not younger, adults greater interoceptive accuracy was associated with better accuracy in both detecting deceptive people and phishing emails.

DISCUSSION

Interoceptive accuracy was associated with both lie detection and phishing detection accuracy among older adults. Our findings identify interoceptive accuracy as a potential protective factor for fraud susceptibility, as measured through difficulty detecting deception. These results support interoceptive accuracy as a relevant factor for consideration in interventions targeted at fraud prevention among older adults.

Frontoparietal atrophy trajectories in cognitively unimpaired elderly individuals using longitudinal Bayesian clustering

INTRODUCTION

Frontal and/or parietal atrophy has been reported during aging. To disentangle the heterogeneity previously observed, this study aimed to uncover different clusters of grey matter profiles and trajectories within cognitively unimpaired individuals.

METHODS

Structural magnetic resonance imaging (MRI) data of 307 Aβ-negative cognitively unimpaired individuals were modelled between ages 60-85 from three cohorts worldwide. We applied unsupervised clustering using a novel longitudinal Bayesian approach and characterized the clusters' cerebrovascular and cognitive profiles.

RESULTS

Four clusters were identified with different grey matter profiles and atrophy trajectories. Differences were mainly observed in frontal and parietal brain regions. These distinct frontoparietal grey matter profiles and longitudinal trajectories were differently associated with cerebrovascular burden and cognitive decline.

DISCUSSION

Our findings suggest a conciliation of the frontal and parietal theories of aging, uncovering coexisting frontoparietal GM patterns. This could have important future implications for better stratification and identification of at-risk individuals.

Gray matter volume differences in intimate partner violence perpetrators and its role in explaining dropout and recidivism

AIM

Psychological instruments that are employed to adequately explain treatment compliance and recidivism of intimate partner violence (IPV) perpetrators present a limited ability and certain biases. Therefore, it becomes necessary to incorporate new techniques, such as magnetic resonance imaging (MRI), to be able to surpass those limitations and measure central nervous system characteristics to explain dropout (premature abandonment of intervention) and recidivism.

METHOD

The main objectives of this study were: 1) to assess whether IPV perpetrators (n = 60) showed differences in terms of their brain's regional gray matter volume (GMV) when compared to a control group of non-violent men (n = 57); 2) to analyze whether the regional GMV of IPV perpetrators before starting a tailored intervention program explain treatment compliance (dropout) and recidivism rate.

RESULTS

IPV perpetrators presented increased GMV in the cerebellum and the occipital, temporal, and subcortical brain regions compared to controls. There were also bilateral differences in the occipital pole and subcortical structures (thalamus, and putamen), with IPV perpetrators presenting reduced GMV in the above-mentioned brain regions compared to controls. Moreover, while a reduced GMV of the left pallidum explained dropout, a considerable number of frontal, temporal, parietal, occipital, subcortical and limbic regions added to dropout to explain recidivism.

CONCLUSIONS

Our study found that certain brain structures not only distinguished IPV perpetrators from controls but also played a role in explaining dropout and recidivism. Given the multifactorial nature of IPV perpetration, it is crucial to combine neuroimaging techniques with other psychological instruments to effectively create risk profiles of IPV perpetrators.

When Maturation is Not Linear: Brain Oscillatory Activity in the Process of Aging as Measured by Electrophysiology

Changes in brain oscillatory activity are commonly used as biomarkers both in cognitive neuroscience and in neuropsychiatric conditions. However, little is known about how its profile changes across maturation. Here we use regression models to characterize magnetoencephalography power changes within classical frequency bands in a sample of 792 healthy participants, covering the range 13 to 80 years old. Our findings unveil complex, non-linear power trajectories that defy the traditional linear paradigm, with notable cortical region variations. Interestingly, slow wave activity increases correlate with improved cognitive performance throughout life and larger gray matter volume in the elderly. Conversely, fast wave activity diminishes in adulthood. Elevated low-frequency activity during aging, traditionally seen as compensatory, may also signify neural deterioration. This dual interpretation, highlighted by our study, reveals the intricate dynamics between brain oscillations, cognitive performance, and aging. It advances our understanding of neurodevelopment and aging by emphasizing the regional specificity and complexity of brain rhythm changes, with implications for cognitive and structural integrity.

Reorganization of integration and segregation networks in brain-based visual impairment

Growing evidence suggests that cerebral connectivity changes its network organization by altering modular topology in response to developmental and environmental experience. However, changes in cerebral connectivity associated with visual impairment due to early neurological injury are still not fully understood. Cerebral visual impairment (CVI) is a brain-based visual disorder associated with damage and maldevelopment of retrochiasmal pathways and areas implicated in visual processing. In this study, we used a multimodal imaging approach and connectomic analyses based on structural (voxel-based morphometry; VBM) and resting state functional connectivity (rsfc) to investigate differences in weighted degree and link-level connectivity in individuals with CVI compared to controls with neurotypical development. We found that participants with CVI showed significantly reduced grey matter volume within the primary visual cortex and intraparietal sulcus (IPS) compared to controls. Participants with CVI also exhibited marked reorganization characterized by increased integration of visual connectivity to somatosensory and multimodal integration areas (dorsal and ventral attention regions) and lower connectivity from visual to limbic and default mode networks. Link-level functional changes in CVI were also associated with key clinical outcomes related to visual function and development. These findings provide early insight into how visual impairment related to early brain injury distinctly reorganizes the functional network architecture of the human brain.

Increased functional integration of emotional control network in late adulthood

Across the adult lifespan, emotion regulation ability remains stable or even improves. The corresponding effects, however, in the emotion regulation networks in the brain remain underexplored. By utilizing large-scale datasets such as the Human Connectome Project (HCP-Aging, N=621, 349 females) and Cambridge Centre for Ageing and Neuroscience (Cam-CAN, N=333, 155 females), we were able to investigate how emotion regulation networks' functional topography differs across the entire adult lifespan. Based on previous meta-analytic work that identified four large-scale functional brain networks involved in emotion generation and regulation, we investigated the association between the integration of these emotion regulation networks and measures of mental wellbeing with age in the HCP-Aging dataset. We found an increase in the functional integration of the emotional control network among older adults, which was replicated using the Cam-CAN data set. Further we found that the network that is mediating emotion generative and regulative processes, and carries our introspective and reflective functions, is less integrated in higher age. Our study highlights the importance of identifying topological changes in the functional emotion network architecture across the lifespan, as it allows for a better understanding of functional brain network changes that accompany emotional aging.

Gray matter volumetric changes in tinnitus: The impact of hearing loss and severity

Tinnitus is a phantom auditory sensation that commonly co-occurs with hearing loss. Both tinnitus and hearing loss can impact the quality of life, emotional well-being, and cognitive functioning of the affected individuals. While previous studies have highlighted structural alterations in hearing loss and/or tinnitus, the fundamental neural mechanisms underpinning tinnitus severity remain poorly understood. In this study, we conducted a voxel-based morphometry to investigate gray matter (GM) volume differences among groups of participants with varying tinnitus severity and hearing status, and controls within a large sample. We observed reduced GM volume in the left anterior insula and right planum polare in participants with hearing loss, regardless of their tinnitus status, compared to normal hearing controls. We noted decreased GM volume in the bilateral anterior and posterior insula for those with tinnitus and normal hearing compared to a normal hearing control group. Further, the tinnitus with hearing loss group showed decreased GM volume in the left planum polare, left inferior temporal gyrus, bilateral anterior temporal gyri, and right superior frontal gyrus compared to the normal hearing control group, suggesting a combined effect of hearing loss and tinnitus. While tinnitus severity did not show a significant overall effect, there was a significant positive correlation between tinnitus distress and GM volume in bilateral planum polare. Our findings enhance the understanding of structural brain changes related to hearing loss and tinnitus, and advance the overall knowledge of tinnitus pathophysiology, which can contribute to the development of more effective treatments for tinnitus.

Generative artificial intelligence model for simulating structural brain changes in schizophrenia

Background

Recent advancements in generative artificial intelligence (AI) for image generation have presented significant opportunities for medical imaging, offering a promising way to generate realistic virtual medical images while ensuring patient privacy. The generation of a large number of virtual medical images through AI has the potential to augment training datasets for discriminative AI models, particularly in fields with limited data availability, such as neuroimaging. Current studies on generative AI in neuroimaging have mainly focused on disease discrimination; however, its potential for simulating complex phenomena in psychiatric disorders remains unknown. In this study, as examples of a simulation, we aimed to present a novel generative AI model that transforms magnetic resonance imaging (MRI) images of healthy individuals into images that resemble those of patients with schizophrenia (SZ) and explore its application.

Methods

We used anonymized public datasets from the Center for Biomedical Research Excellence (SZ, 71 patients; healthy subjects [HSs], 71 patients) and the Autism Brain Imaging Data Exchange (autism spectrum disorder [ASD], 79 subjects; HSs, 105 subjects). We developed a model to transform MRI images of HSs into MRI images of SZ using cycle generative adversarial networks. The efficacy of the transformation was evaluated using voxel-based morphometry to assess the differences in brain region volumes and the accuracy of age prediction pre- and post-transformation. In addition, the model was examined for its applicability in simulating disease comorbidities and disease progression.

Results

The model successfully transformed HS images into SZ images and identified brain volume changes consistent with existing case-control studies. We also applied this model to ASD MRI images, where simulations comparing SZ with and without ASD backgrounds highlighted the differences in brain structures due to comorbidities. Furthermore, simulating disease progression while preserving individual characteristics showcased the model's ability to reflect realistic disease trajectories.

Discussion

The results suggest that our generative AI model can capture subtle changes in brain structures associated with SZ, providing a novel tool for visualizing brain changes in different diseases. The potential of this model extends beyond clinical diagnosis to advances in the simulation of disease mechanisms, which may ultimately contribute to the refinement of therapeutic strategies.

The Influence of Structural Brain Changes on Cognition in the Context of Healthy Aging: Exploring Mediation Effects Through gBAT-The Graphical Brain Association Tool

The contribution of age-related structural brain changes to the well-established link between aging and cognitive decline is not fully defined. While both age-related regional brain atrophy and cognitive decline have been extensively studied, the specific mediating role of age-related regional brain atrophy on cognitive functions is unclear. This study introduces an open-source software tool with a graphical user interface that streamlines advanced whole-brain mediation analyses, enabling researchers to systematically explore how the brain acts as a mediator in relationships between various behavioral and health outcomes. The tool is showcased by investigating regional brain volume as a mediator to determine the contribution of age-related brain volume loss toward cognition in healthy aging. We analyzed regional brain volumes and cognitive testing data (Montreal Cognitive Assessment [MoCA]) from a cohort of 131 neurologically healthy adult participants (mean age 50 ± 20.8 years, range 20-79, 73% females) drawn from the Aging Brain Cohort Study at the University of South Carolina. Using our open-source tool developed for evaluating brain-behavior associations across the brain and optimized for exploring mediation effects, we conducted a series of mediation analyses using participant age as the predictor variable, total MoCA and MoCA subtest scores as the outcome variables, and regional brain volume as potential mediators. Age-related atrophy within specific anatomical networks was found to mediate the relationship between age and cognition across multiple cognitive domains. Specifically, atrophy in bilateral frontal, parietal, and occipital areas, along with widespread subcortical regions mediated the effect of age on total MoCA scores. Various MoCA subscores were influenced by age through atrophy in distinct brain regions. These involved prefrontal regions, sensorimotor cortex, and parieto-occipital areas for executive function subscores, prefrontal and temporo-occipital regions, along with the caudate nucleus for attention and concentration subscores, frontal and parieto-occipital areas, alongside connecting subcortical areas such as the optic tract for visuospatial subscores and frontoparietal areas for language subscores. Brain-based mediation analysis offers a causal framework for evaluating the mediating role of brain structure on the relationship between age and cognition and provides a more nuanced understanding of cognitive aging than previously possible. By validating the applicability and effectiveness of this approach and making it openly available to the scientific community, we facilitate the exploration of causal mechanisms between variables mediated by the brain.

Gray matter volume of the feline cerebral cortex and structural plasticity following perinatal deafness

In response to sensory deprivation, the brain adapts according to contemporary demands to efficiently navigate a modified perceptual environment. This reorganization may result in improved processing of the remaining senses-a phenomenon referred to as compensatory crossmodal plasticity. One approach to explore this neuroplasticity is to consider the macrostructural changes in neural tissue that mirror this functional optimization. The current study is the first of its kind to measure MRI-derived gray matter (GM) volumes of control felines (n=30), while additionally identifying volumetric differences in response to perinatal deafness (30 ototoxically-deafened cats). To accomplish this purpose, regional and morphometric methods were performed in parallel. The regional analysis evaluated volumetric alterations of global GM, as well as the volumes of 146 regions of interest (ROIs) and 12 functional subgroupings of these ROIs. Results revealed whole-brain GM preservation; however, somatosensory and visual cortices exhibited an overall increase in volume. On a smaller scale, this analysis uncovered two auditory ROIs (second auditory cortex, A2, and ventral auditory field, VAF) that decreased in volume alongside two visual regions (anteromedial lateral suprasylvian area, AMLS and splenial visual area, SVA) that increased-all localized within the right hemisphere. Comparatively, the findings of tensor-based morphometry (TBM) generally aligned with those of the ROI-based method, as this voxel-wise approach demonstrated clusters of expansion coincident with visual- and somatosensory-related loci; although, it failed to detect any GM reductions following deafness. As distinct differences were identified in each analysis, the current study highlights the importance of employing multiple methods when exploring MRI volumetry. Overall, this study proposes that volumetric alterations within sensory loci allude to a redistribution of cortical space arising from modified perceptual demands following auditory deprivation.

Increases in regional brain volume across two native South American male populations

Industrialized environments, despite benefits such as higher levels of formal education and lower rates of infections, can also have pernicious impacts upon brain atrophy. Partly for this reason, comparing age-related brain volume trajectories between industrialized and non-industrialized populations can help to suggest lifestyle correlates of brain health. The Tsimane, indigenous to the Bolivian Amazon, derive their subsistence from foraging and horticulture and are physically active. The Moseten, a mixed-ethnicity farming population, are physically active but less than the Tsimane. Within both populations (N = 1024; age range = 46-83), we calculated regional brain volumes from computed tomography and compared their cross-sectional trends with age to those of UK Biobank (UKBB) participants (N = 19,973; same age range). Surprisingly among Tsimane and Moseten (T/M) males, some parietal and occipital structures mediating visuospatial abilities exhibit small but significant increases in regional volume with age. UKBB males exhibit a steeper negative trend of regional volume with age in frontal and temporal structures compared to T/M males. However, T/M females exhibit significantly steeper rates of brain volume decrease with age compared to UKBB females, particularly for some cerebro-cortical structures (e.g., left subparietal cortex). Across the three populations, observed trends exhibit no interhemispheric asymmetry. In conclusion, the age-related rate of regional brain volume change may differ by lifestyle and sex. The lack of brain volume reduction with age is not known to exist in other human population, highlighting the putative role of lifestyle in constraining regional brain atrophy and promoting elements of non-industrialized lifestyle like higher physical activity.

Structural lesions and transcriptomic specializations shape gradient perturbations in Wilson disease

Functional dysregulations in multiple regions are caused by excessive copper deposition in the brain in Wilson disease (WD) patients. The genetic mechanism of WD is thought to involve the abnormal expression of ATP7B in the liver, whereas the biological and molecular processes involved in functional dysregulation within the brain remain unexplored. The objective of this study was to unravel the underpinnings of functional gradient perturbations underlying structural lesions and transcriptomic specializations in WD. In this study, we included 105 WD patients and 93 healthy controls who underwent structural and functional MRI assessments. We used the diffusion mapping embedding model to derive the functional connectome gradient and further employed gray matter volume to uncover structure-function decoupling for WD. Then, we used Neurosynth, clinical data, and whole-brain gene expression data to examine the meta-analytic cognitive function, clinical phenotypes, and transcriptomic specializations related to WD gradient alterations. Compared with controls, WD patients exhibited global topographic changes in the principal pramary-to-transmodal gradient. Meta-analytic terms and clinical characteristics were correlated with these gradient alterations in motor-related processing, higher-order cognition, neurological symptoms, and age. Spatial correlations revealed structure-function decoupling in multiple networks, especially in subcortical and visual networks. Within the cortex, the spatial association between gradient alterations and gene expression profiles has revealed transcriptomic specilizations in WD that display properties indicative of ion homeostasis, neural development, and motor control. Furthermore, for the first time, we characterized the role of the ATP7B gene in impacting subcortical function. The transcriptomic specializations of WD were also associated with other neurological and psychiatric disorders. Finally, we revealed that structural lesions and gradient perturbations may share similar transcriptomic specializations in WD. In conclusion, these findings bridged functional gradient perturbations to structural lesions and gene expression profiles in WD patients, possibly promoting our understanding of the neurobiological mechanisms underlying the emergence of complex neurological and psychiatric phenotypes.

Unraveling the complexity of human brain: Structure, function in healthy and disease states

The human brain stands as an intricate organ, embodying a nexus of structure, function, development, and diversity. This review delves into the multifaceted landscape of the brain, spanning its anatomical intricacies, diverse functional capacities, dynamic developmental trajectories, and inherent variability across individuals. The dynamic process of brain development, from early embryonic stages to adulthood, highlights the nuanced changes that occur throughout the lifespan. The brain, a remarkably complex organ, is composed of various anatomical regions, each contributing uniquely to its overall functionality. Through an exploration of neuroanatomy, neurophysiology, and electrophysiology, this review elucidates how different brain structures interact to support a wide array of cognitive processes, sensory perception, motor control, and emotional regulation. Moreover, it addresses the impact of age, sex, and ethnic background on brain structure and function, and gender differences profoundly influence the onset, progression, and manifestation of brain disorders shaped by genetic, hormonal, environmental, and social factors. Delving into the complexities of the human brain, it investigates how variations in anatomical configuration correspond to diverse functional capacities across individuals. Furthermore, it examines the impact of neurodegenerative diseases on the structural and functional integrity of the brain. Specifically, our article explores the pathological processes underlying neurodegenerative diseases, such as Alzheimer's, Parkinson's, and Huntington's diseases, shedding light on the structural alterations and functional impairments that accompany these conditions. We will also explore the current research trends in neurodegenerative diseases and identify the existing gaps in the literature. Overall, this article deepens our understanding of the fundamental principles governing brain structure and function and paves the way for a deeper understanding of individual differences and tailored approaches in neuroscience and clinical practice-additionally, a comprehensive understanding of structural and functional changes that manifest in neurodegenerative diseases.