Automatically parcellating the human cerebral cortex

The study on agitation and structure of orbitofrontal cortex subregion in first-episode drug-naïve patients with schizophrenia

Agitation is one of the core symptoms of schizophrenia. The occurrence of agitation may be related to orbitofrontal cortex dysfunction. However, due to methodological heterogeneity, the relationship between agitation and orbitofrontal cortex subregions remains unclear. Based on the multi-dimensional structure of the orbitofrontal cortex subregion, this study aims to explore the relationship between orbitofrontal cortex structure and agitation in first-episode drug-naïve patients with schizophrenia. The study subjects included 50 first-episode drug-naïve patients with schizophrenia and 29 healthy controls. All participants underwent structure magnetic resonance imaging scanning. The patients' clinical symptoms were assessed using the Positive and Negative Syndrome Scale, and the agitation were evaluated using the Brief Agitation Rating Scale. SPSS 26.0 was used to compare the differences in the orbitofrontal cortex subregion between the two groups in different structure dimensions and then conduct a Pearson's partial correlations analysis to observe the relationship between orbitofrontal cortex subregion structure and agitation. There were no significant differences in demographic factors between the two groups. Our results show the folding index of the orbitofrontal cortex subregion in patients with schizophrenia were significantly smaller compared to the healthy controls. The surface area in the orbitofrontal cortex subregion is significantly negatively correlated with agitation in first-episode drug-naïve schizophrenia patients. These results suggest that structure alterations in the orbitofrontal cortex subregion may be involved in schizophrenia agitation.

Association between twin status with cognitive, behavioral development and brain structure in early adolescence: a retrospective cohort analysis based on the Adolescent Brain Cognitive Development Study

Twin births are related with maternal and fetal adverse outcomes. Little was known about the comparability of the cognitive, behavioral development and brain structure between twins and singletons in early adolescence. This retrospective cohort study was based on data from the United States population-based, prospective, longitudinal observational Adolescent Brain Cognitive Development study. Children with complete twin status information were enrolled, and the exposure variable was twin status. Primary outcomes were cognitive, behavioral development and brain structure in early adolescence. Cognitive and behavioral outcomes were assessed by using the NIH Toolbox and Child Behavioral Checklist, respectively. Brain structure was evaluated by the cortical thickness, area, and volume extracted from the magnetic resonance imaging (MRI) data. Subgroup analyses were conducted by prematurity, birth weight, with sibling, genetic profiles, and twin types (zygosity). From 1st September 2016 to 15th November 2018, 11545 children (9477 singletons and 2068 twins) aged 9-10 years were enrolled. Twins showed mildly lower cognitive performance (|t|> 5.104, P-values < 0.001, False Discovery Rate [FDR] < 0.001), better behavioral outcome (|t|> 2.441, P-values < 0.015, FDR < 0.042), such as lower scores for multiple psychiatric disorders and behavioral issues, and smaller cortical volume (t = - 3.854, P-values < 0.001, FDR < 0.001) and cortical area (t = - 3.872, P-values < 0.001, FDR < 0.001). The observed differences still held when stratified for prematurity, birth weight, presence of siblings, genetic profiles, and twin types (zygosity). Furthermore, analyses on the two-year follow-up data showed consistent results with baseline data. Twin status is associated with lower cognitive and better behavioral development in early adolescence accompanied by altered brain structure. Clinicians should be aware of the possible difference when generalizing results from adolescent twin samples to singletons.

Insomnia Subtypes Have Differentiating Deviations in Brain Structural Connectivity

BACKGROUND

Insomnia disorder is the most common sleep disorder. A better understanding of insomnia-related deviations in the brain could inspire better treatment. Insufficiently recognized heterogeneity within the insomnia population could obscure detection of involved brain circuits. In the current study, we investigated whether structural brain connectivity deviations differed between recently discovered and validated insomnia subtypes.

METHODS

Structural and diffusion-weighted 3T magnetic resonance imaging data from 4 independent studies were harmonized. The sample consisted of 73 control participants without sleep complaints and 204 participants with insomnia who were grouped into 5 insomnia subtypes based on their fingerprint of mood and personality traits assessed with the Insomnia Type Questionnaire. Linear regression correcting for age and sex was used to evaluate group differences in structural connectivity strength, indicated by fractional anisotropy, streamline volume density, and mean diffusivity and evaluated within 3 different atlases.

RESULTS

Insomnia subtypes showed differentiating profiles of deviating structural connectivity that were concentrated in different functional networks. Permutation testing against randomly drawn heterogeneous subsamples indicated significant specificity of deviation profiles in 4 of the 5 subtypes: highly distressed, moderately distressed reward sensitive, slightly distressed low reactive, and slightly distressed high reactive. Connectivity deviation profile significance ranged from p = .001 to p = .049 for different resolutions of brain parcellation and connectivity weight.

CONCLUSIONS

Our results provide an initial indication that different insomnia subtypes exhibit distinct profiles of deviations in structural brain connectivity. Subtyping insomnia may be essential for a better understanding of brain mechanisms that contribute to insomnia vulnerability.

Anchoring functional connectivity to individual sulcal morphology yields insights in a pediatric study of reasoning

A salient neuroanatomical feature of the human brain is its pronounced cortical folding, and there is mounting evidence that sulcal morphology is relevant to functional brain architecture and cognition. However, our understanding of the relationships between sulcal anatomy, brain activity, and behavior is still in its infancy. We previously found the depth of three small, shallow sulci in lateral prefrontal cortex (LPFC) was linked to reasoning performance in childhood and adolescence (Voorhies et al., 2021). These findings beg the question: what is the linking mechanism between sulcal morphology and cognition? To shed light on this question, we investigated functional connectivity among sulci in LPFC and lateral parietal cortex (LPC). We leveraged manual parcellations (21 sulci/hemisphere, total of 1806) and functional magnetic resonance (fMRI) data from a reasoning task from 43 participants aged 7-18 years (20 female). We conducted clustering and classification analyses of individual-level functional connectivity among sulci. Broadly, we found that 1) the connectivity patterns of individual sulci could be differentiated - and more accurately than rotated sulcal labels equated for size and shape; 2) sulcal connectivity did not consistently correspond with that of probabilistic labels or large-scale networks; 3) sulci clustered together into groups with similar patterns, not dictated by spatial proximity; and 4) across individuals, greater depth was associated with higher network centrality for several sulci under investigation. These results highlight that functional connectivity can be meaningfully anchored to individual sulcal anatomy, and demonstrate that functional network centrality can vary as a function of sulcal depth.

Individual differences in intolerance of uncertainty is primarily linked to the structure of inferior frontal regions

Increased intolerance of uncertainty (IU), or distress felt when encountering situations with unknown outcomes, occurs transdiagnostically across various forms of psychopathology and is targeted in therapeutic intervention. Increased intolerance of uncertainty shows overlap with symptoms of internalizing disorders, such as depression and anxiety, including negative affect and anxious apprehension (worry). While neuroanatomical correlates of IU have been reported, previous investigations have not disentangled the specific neural substrates of IU above and beyond any overlapping relationships with aspects of internalizing psychopathology. The current study did so in a sample of 42 adults and 79 adolescents, who completed questionnaires assessing IU and internalizing symptoms, and underwent structural MRI. When controlling for internalizing symptoms, across adults and adolescents, specific associations of IU were found with the structure of the inferior frontal cortex and orbitofrontal cortex, regions implicated in cognitive control and emotional valuation/regulation. In addition, in adolescents, associations were observed with rostral middle frontal cortex and portions of the cingulate cortex. No associations were observed with threat-related regions, such as the amygdala. Potential cognitive/emotional mechanisms that might explain the association between individual differences in intolerance of uncertainty and morphology of the inferior frontal cortex are discussed.

Human response times are governed by dual anticipatory processes with distinct neural signatures

Human behavior is strongly influenced by anticipation, but the underlying neural mechanisms are poorly understood. We obtained intracranial electrocephalography (iEEG) measurements in neurosurgical patients as they performed a simple sensory-motor task with variable (short or long) foreperiod delays that affected anticipation of the cue to respond. Participants showed two forms of anticipatory response biases, distinguished by more premature false alarms (FAs) or faster response times (RTs) on long-delay trials. These biases had distinct neural signatures in prestimulus neural activity modulations that were distributed and intermixed across the brain: the FA bias was most evident in preparatory motor activity immediately prior to response-cue presentation, whereas the RT bias was most evident in visuospatial activity at the beginning of the foreperiod. These results suggest that human anticipatory behavior emerges from a combination of motor-preparatory and attention-like modulations of neural activity, implemented by anatomically widespread and intermixed, but functionally identifiable, brain networks.

Amygdala Nuclei Atrophy in Cognitive Impairment and Dementia: Insights from High-Resolution Magnetic Resonance Imaging

Background and Objectives: Cognitive impairment affects memory, reasoning, and problem-solving, with early detection being critical for effective management. The amygdala, a key structure in emotional processing and memory, may play a pivotal role in detecting cognitive decline. This study examines differences in amygdala nuclei volumes in patients with varying levels of cognitive performance to evaluate its potential as a biomarker. Material and methods: This cross-sectional study of 35 participants was conducted and classified into three groups: the normal (≥26), moderate (15-25), and low (≤14) cognitive performance groups based on the Montreal Cognitive Assessment (MoCA) scores. High-resolution magnetic resonance imaging at 3.0 T scanner was used to assess amygdala nuclei volumes. Results: Significant amygdala atrophy was observed in multiple amygdala nuclei across cognitive performance groups, with more pronounced changes in the low-performance group. The right hemisphere nuclei, including the lateral and basal nuclei, showed more significant differences, indicating their sensitivity to cognitive decline. Conclusions: This study highlights the potential of amygdala nuclei atrophy as a biomarker for cognitive impairment. Additional research with larger sample sizes and longitudinal designs is needed to confirm these findings and determine their diagnostic value.

Resting-State EEG Alpha Rhythms Are Related to CSF Tau Biomarkers in Prodromal Alzheimer's Disease

Patients with mild cognitive impairment due to Alzheimer's disease (ADMCI) typically show abnormally high delta (<4 Hz) and low alpha (8-12 Hz) rhythms measured from resting-state eyes-closed electroencephalographic (rsEEG) activity. Here, we hypothesized that the abnormalities in rsEEG activity may be greater in ADMCI patients than in those with MCI not due to AD (noADMCI). Furthermore, they may be associated with the diagnostic cerebrospinal fluid (CSF) amyloid-tau biomarkers in ADMCI patients. An international database provided clinical-demographic-rsEEG datasets for cognitively unimpaired older (Healthy; N = 45), ADMCI (N = 70), and noADMCI (N = 45) participants. The rsEEG rhythms spanned individual delta, theta, and alpha frequency bands. The eLORETA freeware estimated cortical rsEEG sources. Posterior rsEEG alpha source activities were reduced in the ADMCI group compared not only to the Healthy group but also to the noADMCI group (p < 0.001). Negative associations between the CSF phospho-tau and total tau levels and posterior rsEEG alpha source activities were observed in the ADMCI group (p < 0.001), whereas those with CSF amyloid beta 42 levels were marginal. These results suggest that neurophysiological brain neural oscillatory synchronization mechanisms regulating cortical arousal and vigilance through rsEEG alpha rhythms are mainly affected by brain tauopathy in ADMCI patients.

Neuroanatomical prediction of individual anxiety problems level using machine learning models: A population-based cohort study of young adults

Anxiety, a mental state in healthy individuals, is characterized by apprehension of potential future threats. Though the neurobiological basis of anxiety has been investigated widely in the clinical populations, the underly mechanism of neuroanatomical correlates with anxiety level in healthy young adults is still unclear. In this study, 1080 young adults were enrolled from the Human Connectome Project Young Adult dataset, and machine learning-based elastic net regression models with cross validation, together with linear mix effects (LME) models were adopted to investigate whether the neuroanatomical profiles of structural magnetic resonance imaging indicators associated with anxiety level in healthy young adults. We found multi-region neuroanatomical profiles predicted anxiety problems level and it was still robust in an out-of-sample. The neuroanatomical profiles had widespread brain nodes, including the dorsal lateral prefrontal cortex, supramarginal gyrus, and entorhinal cortex, which implicated in the default mode network and frontoparietal network. This finding was further supported by LME models, which showed significant univariate associations between brain nodes with anxiety. In sum, it's a large sample size study with multivariate analysis methodology to provide evidence that individual anxiety problems level can be predicted by machine learning-based models in healthy young adults. The neuroanatomical signature including hub nodes involved theoretically relevant brain networks robustly predicts anxiety, which could aid the assessment of potential high-risk of anxiety individuals.

Reduced interhemispheric connectivity in traumatic brachial plexopathies after bionic reconstruction

Traumatic brachial plexus lesions (TBPL) can lead to permanent impairment of hand function despite timely brachial plexus surgical treatment. In selected cases with no recovery of hand function, the affected forearm can be amputated and replaced by a bionic hand to regain prehensile function. This cross-sectional study aimed to assess (sub)cortical motor activity and functional connectivity changes after TBPL and bionic reconstruction. Cortical activity was measured with functional MRI (fMRI) during execution, and imagery of hand closing movements with the affected and healthy arm and single subject analysis was performed on the fMRI data. An electromyography training session was performed before fMRI to ensure correct task performance. Additionally, functional connectivity, diffusion tensor imaging (DTI), and cortical thickness were analyzed. Six healthy controls (4 men, median age 27, range 22-54), three TBPL patients without prosthetic reconstruction (3 men, median age 50, range 19-58), and two TBPL patients with a prosthetic reconstruction (2 men, median age 41, range 40-41) were included. In patients, cortical activity in the premotor gyrus and supplementary motor cortex (SMC) was higher and more widespread during both actual and imagery movements of the affected as well as the unaffected arm. Moreover, patients showed increased interhemispheric functional connectivity from the most active voxel in the precentral gyrus and SMC in the actual movement task. Subcortical activation of the thalamus and pallidum was observed only in non-prosthesis patients during actual movements. Corticothalamic functional connectivity was increased mainly in patients without prosthesis during actual and imagery movements. There were no differences in cortical thickness between participants. TBPL patients showed fewer structural DTI-based interhemispheric connections between the left and right precentral gyrus and superior frontal gyrus than controls. Patients without prosthesis also exhibited fewer structural connections between the left and right thalamus and pallidum, whereas those with prosthesis demonstrated increased structural connectivity compared to controls. The increased and more widespread cortical activity and functional connectivity after TBPL may be due to increased central effort necessary for motor execution and planning, representing a compensation mechanism for the decrease of interhemispheric and subcortical connectivity. The initial loss of white matter may be counteracted by increased function and grey matter recruitment, which seems necessary even after white matter recovery later with prosthesis use. The clinical implication of our findings is that a selected group of TBPL patients may benefit from an earlier timing of bionic restoration of hand function.

Decreased Structural Connectivity Between Thalamic Nuclei and Hippocampus in Temporal Lobe Epilepsy-A Diffusion Tensor Imaging-Based Study

BACKGROUND

Temporal lobe epilepsy (TLE) can lead to structural brain abnormalities, with thalamus atrophy being the most common extratemporal alteration. This study used probabilistic tractography to investigate the structural connectivity between individual thalamic nuclei and the hippocampus in TLE.

METHODS

Thirty-six TLE patients who underwent pre-surgical 3 Tesla magnetic resonance imaging (MRI) and 18 healthy controls were enrolled in this study. Patients were subdivided into TLE with HS (TLE-HS) and MRI-negative TLE (TLE-MRneg). Tractography and whole brain segmentation, including thalamus parcellation, were performed to determine the number of streamlines per mm3 between the thalamic nuclei and hippocampus. Connectivity strength and volume of regions were correlated with clinical data.

RESULTS

The volume of the entire thalamus ipsilateral to seizure onset was significantly decreased in TLE-HS compared to controls (Mann-Whitney-U test: pFDR < 0.01) with the anterior thalamic nuclei (ANT) as important contributor. Furthermore, decreased ipsilateral connectivity strength between the hippocampus and ANT was detected in TLE-HS (pFDR < 0.01) compared to TLE-MRneg and controls which correlated negatively with the duration of epilepsy (ρ = -0.512, p = 0.025) and positively with seizure frequency (ρ = 0.603, p = 0.006). Moreover, ANT volume correlated negatively with epilepsy duration in TLE-HS (ρ = -0.471, p = 0.042).

CONCLUSIONS

ANT showed atrophy and decreased connectivity in TLE-HS, which correlated with epilepsy duration and seizure frequency. Understanding the dynamics of epileptogenic networks has the potential to shed light on surgery-resistant epilepsy and refine the selection process for ideal neurosurgical candidates, consequently enhancing post-surgical outcomes.

Mismatch Negativity as an Index of Auditory Short-Term Plasticity: Associations with Cortisol, Inflammation, and Gray Matter Volume in Youth at Clinical High Risk for Psychosis

Mismatch negativity (MMN) event-related potential (ERP) component reduction, indexing N-methyl-D-aspartate receptor (NMDAR)-dependent auditory echoic memory and short-term plasticity, is a well-established biomarker of schizophrenia that is sensitive to psychosis risk among individuals at clinical high-risk (CHR-P). Based on the NMDAR-hypofunction model of schizophrenia, NMDAR-dependent plasticity is predicted to contribute to aberrant neurodevelopmental processes involved in the pathogenesis of schizophrenia during late adolescence or young adulthood, including gray matter loss. Moreover, stress and inflammation disrupt plasticity. Therefore, using data collected during the 8-center North American Prodrome Longitudinal Study (NAPLS-2), we explored relationships between MMN amplitudes and salivary cortisol, gray matter volumes, and inflammatory cytokines. Participants included 303 CHR-P individuals with baseline electroencephalography (EEG) data recorded during an MMN paradigm as well as structural magnetic resonance imaging (MRI) and salivary cortisol, of which a subsample (n = 57) also completed blood draws. More deficient MMN amplitudes were associated with greater salivary cortisol and pro-inflammatory cytokine levels in future CHR-Converters, but not among those who did not convert to psychosis within the next two years. More deficient MMN amplitude was also associated with smaller total gray matter volume across participants regardless of future clinical outcomes, and with subcortical gray matter volumes among future CHR-Converters only. These findings are consistent with the theory that deficient NMDAR-dependent plasticity results in an overabundance of weak synapses that are subject to over-pruning during psychosis onset, contributing to gray matter loss. Further, MMN plasticity mechanisms may interact with stress, cortisol, and neuroinflammatory processes, representing a proximal influence of psychosis.

Biomarker and neuropsychological correlates of the N400 event-related potential in Alzheimer's disease

OBJECTIVE

The current study sought to characterize the relationship of the N400 (N4) effect event-related potential to Alzheimer's disease (AD) biomarkers and broader cognition in older adults on the late-life cognitive continuum.

METHOD

Participants who were cognitively intact (n = 43), or had amnestic mild cognitive impairment (MCI; n = 19), or mild AD (n = 12), completed a word-pair judgement task during concurrent EEG recording to elicit the N400. The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) and biomarker data (PET-imaged beta-amyloid (aβ) deposition, apolipoprotein-E ε4 (APOE4) allele status, hippocampal volumes) were collected as part of a larger study.

RESULTS

The AD group had slower response times and poorer accuracy on the word-pair judgement task than the intact group. The N4 effect was smaller and occurred later in AD relative to intact participants. MCI participants' values were intermediate. N4 effect amplitudes were not associated with RBANS scores but were positively associated with aβ deposition. Conversely, poorer performance across most RBANS Indexes and the Total score was associated with longer N4 latencies. There was also a negative association between hippocampal volumes and the N4 latency and a positive association between aβ deposition and latency. Finally, the latency of the N4 independently predicted variance in RBANS Total scores, above and beyond aβ deposition, hippocampal volumes, and APOE4 allele status.

CONCLUSIONS

These findings support the relevance of the N4 effect in individuals along the late-life cognitive continuum, and motivate future studies into its potential as a longitudinal predictor in AD.

Latent cognitive phenotypes in juvenile myoclonic epilepsy: Clinical, sociodemographic, and neuroimaging associations

OBJECTIVE

Application of cluster analytic procedures has advanced understanding of the cognitive heterogeneity inherent in diverse epilepsy syndromes and the associated clinical and neuroimaging features. Application of this unsupervised machine learning approach to the neuropsychological performance of persons with juvenile myoclonic epilepsy (JME) has yet to be attempted, which is the intent of this investigation.

METHODS

A total of 77 JME participants, 19 unaffected siblings, and 44 unrelated controls, 12 to 25 years of age, were administered a comprehensive neuropsychological battery (intelligence, language, memory, executive function, and processing speed), which was subjected to factor analysis followed by K-means clustering of the resultant factor scores. Identified cognitive phenotypes were characterized and related to clinical, family, sociodemographic, and cortical and subcortical imaging features.

RESULTS

Factor analysis revealed three underlying cognitive dimensions (general ability, speed/response inhibition, and learning/memory), with JME participants performing worse than unrelated controls across all factor scores, and unaffected siblings performing worse than unrelated controls on the general mental ability and learning/memory factors, with no JME vs sibling differences. K-means clustering of the factor scores revealed three latent groups including above average (31.4% of participants), average (52.1%), and abnormal performance (16.4%). Participant groups differed in their distributions across the latent groups (p < 0.001), with 23% JME, 22% siblings, and 2% unrelated controls in the abnormal performance group; and 18% JME, 21% siblings, and 59% unrelated controls in the above average group. Clinical epilepsy variables were unassociated with cluster membership, whereas family factors (lower parental education) and abnormally increased thickness and/or volume in the frontal, parietal, and temporal-occipital regions were associated with the abnormal cognition group.

SIGNIFICANCE

Distinct cognitive phenotypes characterize the spectrum of neuropsychological performance of patients with JME for which there is familial (sibling) aggregation. Phenotypic membership was associated with parental (education) and imaging characteristics (increased cortical thickness and volume) but not basic clinical seizure features.

Structural MRI study of Pareidolia and Visual Hallucinations in Drug-Naïve Parkinson's disease

Visual hallucinations (VH) and pareidolia, a type of minor hallucination, share common underlying mechanisms. However, the similarities and differences in their brain regions remain poorly understood in Parkinson's disease (PD). A total of 104 drug-naïve PD patients underwent structural MRI and were assessed for pareidolia using the Noise Pareidolia Test (NPT) were enrolled. Subcortical gray matter volume and cortical surface volume were analyzed using the FreeSurfer software. Structural analyses revealed associations between NPT scores and atrophy in the right thalamus, right hippocampus, right temporal cortex, and right orbitofrontal cortex in all PD participants. These results were almost the same after adjusting for right-handed 97 patients with PD. It is considered that hallucinations in patients with PD are related to altered integration of sensory input (bottom-up) and prior knowledge (top-down) within the visual system. Our findings indicate that pareidolia in PD involves both bottom-up (thalamus and temporal cortex) and top-down (orbitofrontal cortex) processing disturbances; in contrast, VH predominantly involves bottom-up but not top-down regions. Understanding these distinctions could aid in the development of targeted interventions for hallucinations in patients with PD.

Machine Learning Recognizes Stages of Parkinson's Disease Using Magnetic Resonance Imaging

Neurodegenerative diseases (NDs), such as Alzheimer's disease (AD) and Parkinson's disease (PD), are debilitating conditions that affect millions worldwide, and the number of cases is expected to rise significantly in the coming years. Because early detection is crucial for effective intervention strategies, this study investigates whether the structural analysis of selected brain regions, including volumes and their spatial relationships obtained from regular T1-weighted MRI scans (N = 168, PPMI database), can model stages of PD using standard machine learning (ML) techniques. Thus, diverse ML models, including Logistic Regression, Random Forest, Support Vector Classifier, and Rough Sets, were trained and evaluated. Models used volumes, Euclidean, and Cosine distances of subcortical brain structures relative to the thalamus to differentiate among control (HC), prodromal (PR), and PD groups. Based on three separate experiments, the Logistic Regression approach was optimal, providing low feature complexity and strong predictive performance (accuracy: 85%, precision: 88%, recall: 85%) in PD-stage recognition. Using interpretable metrics, such as the volume- and centroid-based spatial distances, models achieved high diagnostic accuracy, presenting a promising framework for early-stage PD identification based on MRI scans.

A visual scale to rate amygdalar atrophy on MRI

BACKGROUND

Visual rating scales are routinely used in clinical radiology to assess brain atrophy on scans of patients with suspected neurodegenerative conditions. Limbic predominant age-related TDP-43 encephalopathy (LATE) has recently been described, featuring early and severe atrophy of the amygdala. However, there is currently no scoring system specifically designed to assess amygdalar atrophy on MRI.

OBJECTIVES

to develop and validate a visual rating scale for amygdalar atrophy.

MATERIALS AND METHODS

Stringent criteria were developed for no, mild/moderate, and severe amygdalar atrophy based on axial and coronal volumetric T1-weighted MRI scans. Inter- and intra-rater reliabilities were estimated by three independent expert neuroradiologists in 100 randomly selected scans from the Geneva Memory Center cohort selected to be representative of the variability of medial temporal atrophy. Convergent validity was evaluated versus amygdalar volumes extracted by FreeSurfer on 1943 consecutive patients. Criterion validity versus autopsy-confirmed LATE neuropathologic changes were studied in the pathological subset of the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort (N = 96).

RESULTS

Intra- and inter-rater agreements of amygdalar visual ratings were between substantial and almost perfect (weighted Cohen's Kappa 0.71 to 0.93). Visual ratings were strongly associated with amygdalar volumes (p ≤ 0.001 on the Kruskal-Wallis test). LATE neuropathologic changes were associated with visual ratings of amygdalar atrophy (p = 0.057 on a test for trend).

CONCLUSION

The proposed visual amygdalar atrophy scale is a reliable and valid tool to assess amygdalar atrophy on MRI and can be a useful adjunct in routine radiological reporting.

KEY POINTS

Question Assessment of amygdalar atrophy is crucial for diagnosing neurodegenerative diseases, as the limbic predominant age-related TDP-43 encephalopathy, yet no validated visual rating scale exists. Findings The proposed amygdalar atrophy scale demonstrated high intra-rater and inter-rater reliability, strong correlation with amygdalar volumetry, and association with limbic predominant age-related TDP-43 encephalopathy (LATE). Clinical relevance The amygdalar atrophy scale provides a reliable practical assessment tool that enhances diagnostic accuracy for dementia-related conditions, particularly aiding in identifying limbic predominant age-related TDP-43 encephalopathy.

Language aptitude is related to the anatomy of the transverse temporal gyri

Why is it that some people seem to learn new languages faster and more easily than others? The present study investigates the neuroanatomical basis of language learning aptitude, with a focus on the multiplication pattern of the transverse temporal gyrus/gyri (TTG/TTGs) of the auditory cortex. The size and multiplication pattern of the first TTG (i.e., Heschl's gyrus; HG) and of additional posterior TTGs, when present, are highly variable both between brain hemispheres and individuals. Previous work has shown the multiplication pattern of the TTGs to be related to musical and linguistic abilities. Specifically, one study found that high language learning aptitude correlated with more TTGs in the right hemisphere, even though language functions are generally left-lateralized. In this study, we used the recently developed TASH (Toolbox for the Automated Segmentation of Heschl's Gyrus) and MCAI (Multivariate Concavity Amplitude Index) toolboxes to automatically extract structural (e.g., cortical volume, surface area, thickness) and multiplication pattern measures of the TTGs from 82 MRI scans, and related them to participants' language aptitude scores. In contrast to previous results, we found that higher language aptitude was related to fewer TTGs in the right hemisphere and to greater surface area of the first right TTG and of the second left TTG. Furthermore, more languages learned in life were associated with higher language learning aptitude, opening up questions about the structure-function relationship of the TTGs and language learning, and about how language aptitude and language learning are related.

Identification and diagnosis of ultra-rapid progressive dementia: evidence from a prospective cohort study and systematic literature review

BACKGROUND AND OBJECTIVES

The term rapid progressive dementia (RPD) may be applied to patients who develop dementia within 1 year or complete incapacitation within 2 years of the first symptom of impairment. However, in select cases, cognitive impairment may emerge abruptly, with symptoms evolving across hours or days. We sought to determine the frequency, etiologies, and factors that associated with ultra-RPD.

METHODS

Ultra-RPD was defined as persistent dementia (global Clinical Dementia Rating® ≥ 1), developing within 7 days of initial symptoms. Patients with ultra-RPD were identified via case review of patients enrolled in a prospective study of RPD at two tertiary care centers (February 2016-September 2023) followed by a systematic review of multiple English-language databases, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (completed January 2024).

RESULTS

Three of 188 patients with RPD enrolled in our prospective series met the proposed definition for ultra-RPD (frequency = 1.6%). Systematic review yielded 57 additional cases from 47 publications (60 total cases). Ultra-RPD was attributed to vascular (40%), toxic/metabolic (22%), autoimmune/inflammatory (20%), and iatrogenic/structural (12%) causes. Lesions within the Papez circuit were detected in 52/59 (88%) of patients on neuroimaging. Twelve patients (20%) had potentially treatable causes of ultra-RPD.

DISCUSSION

Patients with ultra-RPD were rarely encountered in our prospective series, representing < 2% of cases of RPD, and rarely reported in the extant literature. The evaluation of patients with ultra-RPD should prioritize testing for vascular, toxic/metabolic, and autoimmune/inflammatory conditions that affect neuroanatomical structures or networks critical for memory formation and retrieval.

Low-Rank Tensor Fusion for Enhanced Deep Learning-Based Multimodal Brain Age Estimation

Background/Objectives: A multimodal brain age estimation model could provide enhanced insights into brain aging. However, effectively integrating multimodal neuroimaging data to enhance the accuracy of brain age estimation remains a challenging task. Methods: In this study, we developed an innovative data fusion technique employing a low-rank tensor fusion algorithm, tailored specifically for deep learning-based frameworks aimed at brain age estimation. Specifically, we utilized structural magnetic resonance imaging (sMRI), diffusion tensor imaging (DTI), and magnetoencephalography (MEG) to extract spatial-temporal brain features with different properties. These features were fused using the low-rank tensor algorithm and employed as predictors for estimating brain age. Results: Our prediction model achieved a desirable prediction accuracy on the independent test samples, demonstrating its robust performance. Conclusions: The results of our study suggest that the low-rank tensor fusion algorithm has the potential to effectively integrate multimodal data into deep learning frameworks for estimating brain age.

Multilayer Network Analysis across Cortical Depths in Resting-State 7T fMRI

In graph theory, "multilayer networks" represent systems involving several interconnected topological levels. One example in neuroscience is the stratification of connections between different cortical depths or "laminae", which is becoming non-invasively accessible in humans using ultra-high-resolution functional MRI (fMRI). Here, we applied multilayer graph theory to examine functional connectivity across different cortical depths in humans, using 7T fMRI (1-mm3 voxels; 30 participants). Blood oxygenation level dependent (BOLD) signals were derived from five depths between the white matter and pial surface. We compared networks where the inter-regional connections were limited to a single cortical depth only ("layer-by-layer matrices") to those considering all possible connections between areas and cortical depths ("multilayer matrix"). We utilized global and local graph theory features that quantitatively characterize network attributes including network composition, nodal centrality, path-based measures, and hub segregation. Detecting functional differences between cortical depths was improved using multilayer connectomics compared to the layer-by-layer versions. Superficial depths of the cortex dominated information transfer and deeper depths drove clustering. These differences were largest in frontotemporal and limbic regions. fMRI functional connectivity across different cortical depths may contain neurophysiologically relevant information; thus, multilayer connectomics could provide a methodological framework for studies on how information flows across this stratification.

Cerebrospinal Fluid Biomarkers of Central Nervous System Inflammation Predict Cortical Decline in Bipolar Disorder and Ventricular Enlargement in Healthy Controls

INTRODUCTION

Bipolar disorder has been associated with significant structural brain changes, potentially driven by central nervous system (CNS) inflammation. This study aimed to investigate the relationship between inflammation biomarkers in cerebrospinal fluid (CSF) and longitudinal structural brain changes.

METHODS

We included 29 individuals with bipolar disorder and 34 healthy controls, analyzing three selected inflammation-related biomarkers - interleukin-6 (IL-6), interleukin-8 (IL-8), and chitinase-3-like protein 1 (YKL-40) - in both blood serum and CSF. Structural brain changes were assessed through magnetic resonance imaging at two timepoints, focusing on cortical thickness of the middle temporal cortex and inferior frontal gyrus, as well as ventricular volume.

RESULTS

In healthy controls, baseline CSF levels of YKL-40 predicted ventricular enlargement in both hemispheres. Among individuals with bipolar disorder, higher baseline levels of IL-8 were associated with a decline in cortical thickness in the right and left middle temporal cortex, as well as the right inferior frontal gyrus. No significant associations were observed with serum biomarkers.

CONCLUSIONS

These findings suggest that CSF IL-8 may contribute to cortical decline in bipolar disorder. The lack of association between serum biomarkers and brain changes highlights the specificity of CNS inflammation in these processes. Additionally, the observed link between CSF YKL-40 and ventricular enlargement in healthy controls may indicate a role of CNS inflammation processes in normal brain aging.

INTRODUCTION

Bipolar disorder has been associated with significant structural brain changes, potentially driven by central nervous system (CNS) inflammation. This study aimed to investigate the relationship between inflammation biomarkers in cerebrospinal fluid (CSF) and longitudinal structural brain changes.

METHODS

We included 29 individuals with bipolar disorder and 34 healthy controls, analyzing three selected inflammation-related biomarkers - interleukin-6 (IL-6), interleukin-8 (IL-8), and chitinase-3-like protein 1 (YKL-40) - in both blood serum and CSF. Structural brain changes were assessed through magnetic resonance imaging at two timepoints, focusing on cortical thickness of the middle temporal cortex and inferior frontal gyrus, as well as ventricular volume.

RESULTS

In healthy controls, baseline CSF levels of YKL-40 predicted ventricular enlargement in both hemispheres. Among individuals with bipolar disorder, higher baseline levels of IL-8 were associated with a decline in cortical thickness in the right and left middle temporal cortex, as well as the right inferior frontal gyrus. No significant associations were observed with serum biomarkers.

CONCLUSIONS

These findings suggest that CSF IL-8 may contribute to cortical decline in bipolar disorder. The lack of association between serum biomarkers and brain changes highlights the specificity of CNS inflammation in these processes. Additionally, the observed link between CSF YKL-40 and ventricular enlargement in healthy controls may indicate a role of CNS inflammation processes in normal brain aging.

Dynamics of peripheral T cell exhaustion and monocyte subpopulations in neurocognitive impairment and brain atrophy in chronic HIV infection

BACKGROUND

HIV-associated neurocognitive disorders (HAND) is hypothesized to be a result of myeloid cell-induced neuro-inflammation in the central nervous system that may be initiated in the periphery, but the contribution of peripheral T cells in HAND pathogenesis remains poorly understood.

METHODS

We assessed markers of T cell activation (HLA-DR + CD38+), immunosenescence (CD57 + CD28-), and immune-exhaustion (TIM-3, PD-1 and TIGIT) as well as monocyte subsets (classical, intermediate, and non-classical) by flow cytometry in peripheral blood derived from individuals with HIV on long-term stable anti-retroviral therapy (ART). Additionally, normalized neuropsychological (NP) composite test z-scores were obtained and regional brain volumes were assessed by magnetic resonance imaging (MRI). Relationships between proportions of immune phenotypes (of T-cells and monocytes), NP z-scores, and brain volumes were analyzed using Pearson correlations and multiple linear regression models.

RESULTS

Of N = 51 participants, 84.3% were male, 86.3% had undetectable HIV RNA < 50 copies/ml, median age was 52 [47, 57] years and median CD4 T cell count was 479 [376, 717] cells/uL. Higher CD4 T cells expressing PD-1 + and/or TIM-3 + were associated with lower executive function and working memory and higher CD8 T cells expressing PD-1+ and/or TIM-3+ were associated with reduced brain volumes in multiple regions (putamen, nucleus accumbens, cerebellar cortex, and subcortical gray matter). Furthermore, higher single or dual frequencies of PD-1 + and TIM-3 + expressing CD4 and CD8 T-cells correlated with higher CD16 + monocyte numbers.

CONCLUSIONS

This study reinforces evidence that T cells, particularly those with immune exhaustion phenotypes, are associated with neurocognitive impairment and brain atrophy in people living with HIV on ART. Relationships revealed between T-cell immune exhaustion and inflammatory in CD16+ monocytes uncover interrelated cellular processes likely involved in the immunopathogenesis of HAND.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Beyond group classification: Probabilistic differential diagnosis of frontotemporal dementia and Alzheimer's disease with MRI and CSF biomarkers

Neuroimaging and fluid biomarkers are used to differentiate frontotemporal dementia (FTD) from Alzheimer's disease (AD). We implemented a machine learning algorithm that provides individual probabilistic scores based on magnetic resonance imaging (MRI) and cerebrospinal fluid (CSF) data. We investigated whether combining MRI and CSF levels could improve the diagnosis confidence. 215 AD patients, 103 FTD patients, and 173 healthy controls (CTR) were studied. With MRI data, we obtained an accuracy of 82 % for AD vs. FTD. A total of 74 % of FTD and 73 % of AD participants have a high probability of accurate diagnosis. Adding CSF-NfL and 14-3-3 levels improved the accuracy and the number of patients in the confidence group for differentiating FTD from AD. We obtain individual diagnostic probabilities with high precision to address the problem of confidence in the diagnosis. We suggest when MRI, CSF, or the combination are necessary to improve the FTD and AD diagnosis. This algorithm holds promise towards clinical applications as support to clinical findings or in settings with limited access to expert diagnoses.

Heschl's gyrus and the temporal pole: The cortical lateralization of language

The left lateralization of language has been attributed to hemispheric specialization for processing rapidly changing information. While interhemispheric differences in auditory cortex organization support this view, the macrostructure of the entire cerebral cortex has not been thoroughly examined from this perspective. This study investigated hemispheric asymmetries in cortical surface area and thickness and their relationship to pronunciation scores from oral reading using the Human Connectome Project Young Adult dataset (N=1113). Heschl's gyrus had the most left-lateralized surface area, while the temporal pole showed the strongest right-lateralization in thickness. These areas correspond to the core components of speech: sound and meaning. Notably, their structural features were the only ones also yielding a significant correlation with pronunciation scores. Additionally, Broca's area's posterior region (pars opercularis), involved in articulatory phonological processing, showed leftward lateralization, contrasting with the right-lateralized anterior portions. Left-hemisphere language areas were largely thinner and more extended than their right-sided homologs with a larger white-to-gray matter ratio. Cortical thickness was inversely related to surface area. The lateralization of auditory-related language areas and their structure's correlation with pronunciation in oral reading supports a genetically based auditory foundation for language. A thinner, more efficient cortex with larger surface areas and increased myelination likely underlies the left-hemispheric dominance of language. Thinner, more extended brain areas have been linked to more myelination and wider cortical columns and intercolumnar space. This provides the potential for a fast network of interconnected, discrete information units able to support language's demands of rapid categorical processing.

The mediation effect of the inferior-parietal cortex and globus pallidus on the relationship between family conflict and major depressive disorder

OBJECTIVE

Family conflict is an important risk factor for major depressive disorder (MDD) and is associated with structural alterations in the brain. However, it is unclear whether structural alterations associated with family conflict would contribute to depression. This study aims to investigate the neuroimaging characteristics that connect family conflict with depression.

METHODS

This study included 54 healthy controls and 53 antidepressant-free patients with MDD. Both groups completed the Beck Depression Inventory-II, the simplified Chinese version of the Family Environment Scale, and the Childhood Trauma Questionnaire. Structural Magnetic Resonance Imaging data was collected to measure cortical thickness and regional gray matter volumes.

RESULTS

Family conflict has a significant effect on depression diagnosis. Higher levels of family conflict were positively associated with symptoms of sadness, guilty feelings, and punishment feelings in patients, as well as with cortical thickness in the right inferior-parietal cluster and the volumes of the left globus pallidus in all participants. In the patient group, cortical thickness in the right inferior-parietal cluster and volume of the left globus pallidus were negatively related to symptoms of sadness and guilty feelings, respectively. The structural alteration in the right inferior-parietal cluster mediated the relationship of family conflict and sadness, whereas changes in the globus pallidus mediated the associations between family conflict and both depression and guilty feelings in patients.

CONCLUSION

Findings revealed the relationships between family conflict and depression, including both depression diagnosis and specific symptoms. Cortical thickness in the right inferior-parietal cortex and the volume of the left globus pallidus played mediating roles in these relationships, indicating the important contributions of these brain regions to the effect of family conflict on depression.

Correlates and Brain Substrates of Happiness in Community-Dwelling Older Adults in India

OBJECTIVES

Happiness has been shown to influence many health-related outcomes in older adults. Identifying correlates and brain substrates of happiness across countries and cultures is an important goal, as the global older adult population continues to increase.

METHODS

We used univariate and multiple regression to examine associations between happiness and several demographic, health, and lifestyle variables in 665 older adults (39% female) from Kerala, India. We also used Bayesian regression to examine associations between cortical thickness and happiness in a subsample of 188 participants that completed MRI scanning.

RESULTS

Happiness was significantly associated with several variables. In our multiple regression model, which included all significant univariate predictors, self-rated health, depression, anxiety, apathy, social network size, social network diversity, and social support significantly predicted happiness. Demographic indicators (age, sex, education, marital status, residence, and employment status/type), cognitive impairment, comorbidities, and leisure activities were not significantly associated with happiness in the multiple regression model. Cortical thickness in several brain regions was positively associated with happiness scores, including frontal, temporal, parietal, occipital, and cingulate regions.

DISCUSSION

Understanding the key correlates is critical for identifying both modifiable factors that can be targeted in well-being interventions and fixed characteristics that identify those at-risk for reduced happiness. The widespread pattern of brain regions associated with happiness is consistent with the multifactorial nature of happiness and, given that the regions identified do not overlap with those vulnerable to cortical thinning, can help explain why subjective well-being, unlike other cognitive functions, is largely resistant to age-related decline.

Segmental MRI pituitary and hypothalamus volumes post Fontan: An analysis of the Australian and New Zealand Fontan registry

Objective

Short stature, central hypothyroidism and infertility are common in those with a Fontan circulation. Given that the Fontan circulation often results in hepatic portal venous congestion, we hypothesize that the hypothalamic-pituitary portal circulation is also affected, contributing to subsequent hypothalamic-pituitary axis dysfunction.

Methods

MRI data from the Australian and New Zealand Fontan Registry (86 cases) was compared to 86 age- and sex-matched normal published controls. Total pituitary volumes (both anterior and posterior glands) were measured using a manual tracing segmentation method, and hypothalamic (and subunit) volumes using an automated segmentation tool. Measured gland volume was normalized to total brain volumes. A generalized linear model was used for statistical analysis.

Results

Normalized total pituitary volumes (nTPV) were increased in Fontan patients compared to controls (p < 0.0001), due to an increase in anterior pituitary volumes (nAPV) (p < 0.0001), with no difference in normalized posterior pituitary volumes (p = 0.7). Furthermore, normalized anterior and tubular hypothalamic subunit groups) were increased in Fontan patients compared to the controls (p < 0.01 and p < 0.0001, respectively).The time between Fontan and MRI was positively related to nTPV, nAPV and bilateral hypothalamic volumes. nTPV increased with age, and the increase in nAPV was greater in Fontan patients.

Conclusions

Segmental MRI Pituitary and Hypothalamus volumes post Fontan are increased and are related to the time since Fontan procedure. These findings are consistent with venous congestion of the anterior hypothalamic-pituitary portal venous system and may explain the high frequency of endocrine dysfunction in this patient group.

Shared and distinct alterations in brain morphology in children with ADHD and obesity: Reduced cortical surface area in ADHD and thickness in overweight/obesity

OBJECTIVE

To investigate shared versus distinct differences in brain structure among children with ADHD and obesity, we examined the morphology of regions implicated in cognitive control and reward function in a single cross-sectional cohort of children with and without ADHD and overweight/obesity (OV/OB).

METHOD

Participants included 471 children ages 8-12 years with ADHD (n = 244; 58 OV/OB) and neurotypical (NT) controls (n = 227; 81 OV/OB) classified as healthy-weight (HW; BMI %ile 5th to <85th) vs. having OV/OB (BMI %ile≥85th). Structural MRI was performed to obtain measures of cortical and subcortical morphology and compared across ADHD × BMI groups.

RESULTS

Surface area was generally lower in ADHD vs. NT including in anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (dlPFC), medial (m)PFC, and primary motor (M1) cortex. In contrast, cortical thickness was generally lower in OV/OB vs. HW for ACC, dlPFC, orbitofrontal cortex (OFC), mPFC, and supplementary motor cortex (SMC). Furthermore, ADHD × OV/OB interactions were observed for the ACC and OFC, with the lowest ACC volume in the ADHD + OV/OB group and the highest OFC surface area in the NT + OV/OB group. Subcortical volumes did not differ between groups.

CONCLUSIONS

Our findings reveal distinct alterations in cortical morphology in association with ADHD and overweight, with cortical surface area reduced in ADHD vs. thickness reduced in OV/OB. Additionally, the findings provide evidence of combined effects of ADHD × OV/OB in brain regions integral to cognition and motivation. Our results support further investigation of causes and correlates of shared and distinct ADHD- and OV/OB-associated differences in developing frontocingulate morphology.

Normative Population-Derived Data for MRI Manifestations of Cerebral Small Vessel Disease

BACKGROUND

Cerebral small vessel disease (SVD) is manifested on magnetic resonance imaging (MRI) by white matter hyperintensities, lacunes, microbleeds, and atrophy. While these manifestations can be part of normal aging, a high burden has been associated with cognitive impairment and vascular events. Distinguishing between normal versus abnormal SVD lesion burden in clinical practice remains complex. Our objective is to establish age- and sex-specific normative data for MRI manifestations of SVD, to support clinical assessment in individual patients.

METHODS

We used 11 465 MRI scans from 5402 participants of the Rotterdam Study, the Netherlands, an ongoing prospective population-based cohort since 1990, to develop percentile curves for white matter hyperintensities and brain parenchymal fraction and probability curves for the prevalence and count of lacunes and microbleeds, across ages 45 to 100 years, stratified by sex.

RESULTS

Participants were primarily White (≈97%), with a mean age at first scan of 64.7 (range, 45.7-97.9) years, and 55.7% being female participants. For all SVD MRI manifestations, the curves demonstrated nonlinear trends, with accelerating burden with advancing age (eg, doubling of white matter hyperintensity fraction every 10 years). Regarding brain parenchymal fraction, a decline was seen earlier in male participants (≈45 years) than female participants (≈60 years) and was more pronounced in male participants over time. Female participants had slightly higher white matter hyperintensity fractions compared with male participants across all ages. Lacunes and microbleeds were more frequently found in male participants than in female participants, and microbleeds were more prevalent than lacunes.

CONCLUSIONS

We provide comprehensive normative data for different MRI manifestations of SVD, presented as percentile and probability curves by age, stratified by sex. This can aid clinicians to actually quantify the SVD burden on an individual patient's MRI scans and detect patterns of abnormality.

Effects of mixed metal exposures on MRI diffusion features in the medial temporal lobe

BACKGROUND

Environmental exposure to metal mixtures is common and may be associated with increased risk for neurodegenerative disorders including Alzheimer's disease. This study examined associations of mixed metal exposures with medial temporal lobe (MTL) MRI structural metrics and neuropsychological performance.

METHODS

Metal exposure history, whole blood metal, MRI R1 (1/T1) and R2* (1/T2*) metrics (estimates of brain Mn and Fe, respectively), and neuropsychological tests were obtained from subjects with/without a history of mixed metal exposure from welding fumes (42 exposed subjects; 31 controls). MTL structures (hippocampus, entorhinal and parahippocampal cortices) were assessed by morphologic (volume or cortical thickness) and diffusion tensor imaging [mean (MD), axial (AxD), radial diffusivity (RD), and fractional anisotropy (FA)] metrics. In exposed subjects, effects of mixed metal exposure on MTL structural and neuropsychological metrics were examined.

RESULTS

Compared to controls, exposed subjects displayed higher MD, AxD, and RD throughout all MTL ROIs (p's<0.001) with no morphological differences. They also had poorer performance in processing/psychomotor speed, executive, and visuospatial domains (p's<0.046). Long-term mixed metal exposure history indirectly predicted lower processing speed performance via lower parahippocampal FA (p's<0.023). Higher entorhinal R1 and whole blood Mn and Cu levels predicted higher entorhinal diffusivity (p's<0.043) and lower Delayed Story Recall performance (p=0.007).

DISCUSSION

Mixed metal exposure predicted certain MTL structural and neuropsychological features that are similar to those detected in Alzheimer's disease at-risk populations. These data warrant follow-up as they may illuminate a potential path for environmental exposure to brain changes associated with Alzheimer's disease-related health outcomes.

APOE4 and age affect the brain entorhinal cortex structure and blood arachidonic acid and docosahexaenoic acid levels after mild TBI

A reduction in the thickness and volume of the brain entorhinal cortex (EC), together with changes in blood arachidonic acid (AA) and docosahexaenoic acid (DHA), are associated with Alzheimer's disease (AD) among apolipoprotein E ε4 carriers. Magnetic Resonance Imaging (n = 631) and plasma lipidomics (n = 181) were performed using the LIMBIC/CENC cohort to examine the influence of ε4 on AA- and DHA-lipids and EC thickness and volume in relation to mild traumatic brain injury (mTBI). Results showed that left EC thickness was higher among ε4 carriers with mTBI. Repeated mTBI (r-mTBI) was associated with reduced right EC thickness after controlling for ε4, age and sex. Age, plus mTBI chronicity were linked to increased EC White Matter Volume (WMV). After controlling for age and sex, the advancing age of ε4 carriers with blast mTBI was associated with reduced right EC Grey Matter Volume (GMV) and thickness. Among ε4 carriers, plasma tau and Aβ40 were associated with mTBI and blast mTBI, respectively. Chronic mTBI, ε4 and AA to DHA ratios in phosphatidylcholine, ethanolamides, and phosphatidylethanolamine were associated with decreased left EC GMV and WMV. Further research is needed to explore these as biomarkers for detecting AD pathology following mTBI.

Early Exposure to Deprivation or Threat Moderates Expected Associations Between Neural Structure and Age in Adolescent Girls

Childhood adversity (CA) is associated with increased risk of negative health outcomes. Research implicates brain structure following CA as a key mechanism of this risk, and recent models suggest different forms of adversity differentially impact neural structure as a function of development (accelerated or attenuated development). Employing the Dimensional Model of Adversity and Psychopathology, we examined whether deprivation and threat differentially impact age-related change in cortical thickness, cortical surface area, and subcortical structure volume, using whole-brain and region of interest analyses (N = 135). In youth without CA, age predicted less surface area across adolescence, consistent with normative data. However, for adolescents with more deprivation exposure, as age increased there was attenuated surface area decreases in the orbitofrontal and superior-parietal cortex, regions recruited for higher-order cognition. Further, for those with more threat exposure, as age increased surface area increased in the inferior-temporal and parietal cortex, regions recruited in socio-emotional tasks. These novel findings extend work examining the impact of dimensions of adversity at a single-age and broaden current conceptualizations of how adversity might impact developmental timing.

Onset timing of letter processing in auditory and visual sensory cortices

Here, we report onset latencies for multisensory processing of letters in the primary auditory and visual sensory cortices. Healthy adults were presented with 300-ms visual and/or auditory letters (uppercase Roman alphabet and the corresponding auditory letter names in English). Magnetoencephalography (MEG) evoked response generators were extracted from the auditory and visual sensory cortices for both within-modality and cross-sensory activations; these locations were mainly consistent with functional magnetic resonance imaging (fMRI) results in the same subjects. In the primary auditory cortices (Heschl's gyri) activity to auditory stimuli commenced at 25 ms and to visual stimuli at 65 ms (median values). In the primary visual cortex (Calcarine fissure) the activations started at 48 ms to visual and at 62 ms to auditory stimuli. This timing pattern suggests that the origins of the cross-sensory activations may be in the primary sensory cortices of the opposite modality, with conduction delays (from one sensory cortex to another) of 17-37 ms. Audiovisual interactions for letters started at 125 ms in the auditory and at 133 ms in the visual cortex (60-71 ms after inputs from both modalities converged). Multivariate pattern analysis suggested similar latency differences between the sensory cortices. Combined with our earlier findings for simpler stimuli (noise bursts and checkerboards), these results suggest that primary sensory cortices participate in early cross-modal and interaction processes similarly for different stimulus materials, but previously learned audiovisual associations and stimulus complexity may delay the start of the audiovisual interaction stage.

A cross-species analysis of neuroanatomical covariance sex difference in humans and mice

Structural covariance in brain anatomy is thought to reflect inter-regional sharing of developmental influences - although this hypothesis has proved hard to causally test. Here, we use neuroimaging in humans and mice to study sex-differences in anatomical covariance - asking if regions that have developed shared sex differences in volume across species also show shared sex difference in volume covariance. This study design illuminates both the biology of sex-differences and theoretical models for anatomical covariance - benefitting from tests of inter-species convergence. We find that volumetric structural covariance is stronger in adult females compared to adult males for both wild-type mice and healthy human subjects: 98% of all comparisons with statistically significant covariance sex differences in mice are female-biased, while 76% of all such comparisons are female-biased in humans (q < 0.05). In both species, a region's covariance and volumetric sex-biases have weak inverse relationships to each other: volumetrically male-biased regions contain more female-biased covariations, while volumetrically female-biased regions have more male-biased covariations (mice: r = -0.185, p = 0.002; humans: r = -0.189, p = 0.001). Our results identify a conserved tendency for females to show stronger neuroanatomical covariance than males, evident across species, which suggests that stronger structural covariance in females could be an evolutionarily conserved feature that is partially related to volumetric alterations through sex.

Exploring cognitive functions and brain structure in Hereditary Transthyretin amyloidosis using brain MRI and neuropsychological assessment

BACKGROUND

Central nervous system symptoms, such as cognitive dysfunction, have been reported in Hereditary Transthyretin Amyloidosis (ATTRv). However, there is a lack of neuroimaging studies investigating structural alterations in the brain related to cognition in ATTRv amyloidosis. This study aimed to investigate cognition and cortical morphology in a cohort of ATTRv patients.

METHODS

29 ATTRv patients and 26 healthy controls completed neuropsychological assessment. 21 of these patients underwent 3T brain MRI, and 23 healthy subjects constituted the control group for MRI. Cortical measures of volume, thickness, fractional anisotropy (FA), and mean diffusivity (MD) were obtained for both groups. Correlation analyses between brain and cognitive measurements were performed.

RESULTS

Patients displayed worse performance than controls in executive functions, verbal and visual memory, visuospatial domains, and language tests. Our study indicated cortical thinning in ATTRv patients in the temporal, occipital, frontal, and parietal areas. The inferior temporal gyrus correlated with verbal memory. Insula and, pars opercularis correlated with both verbal memory and executive function.

CONCLUSIONS

Cortical thickness in the inferior temporal gyrus, pars opercularis, and insula were linked to memory and executive function. We observed no correlations between cortical volume measures and cognition. Further investigations are imperative to confirm these findings across different populations.

Morphological similarity and white matter structural mapping of new daily persistent headache: a structural connectivity and tract-specific study

BACKGROUND

New daily persistent headache (NDPH) is a rare primary headache disorder characterized by daily and persistent sudden onset headaches. Specific abnormalities in gray matter and white matter structure are associated with pain, but have not been well studied in NDPH. The objective of this work is to explore the fiber tracts and structural connectivity, which can help reveal unique gray and white matter structural abnormalities in NDPH.

METHODS

The regional radiomics similarity networks were calculated from T1 weighted (T1w) MRI to depict the gray matter structure. The fiber connectivity matrices weighted by diffusion metrics like fractional anisotropy (FA), mean diffusivity (MD) and radial diffusivity (RD) were built, meanwhile the fiber tracts were segmented by anatomically-guided superficial fiber segmentation (Anat-SFSeg) method to explore the white matter structure from diffusion MRI. The considerable different neuroimaging features between NDPH and healthy controls (HC) were extracted from the connectivity and tract-based analyses. Finally, decision tree regression was used to predict the clinical scores (i.e. pain intensity) from the above neuroimaging features.

RESULTS

T1w and diffusion MRI data were available in 51 participants after quality control: 22 patients with NDPH and 29 HCs. Significantly decreased morphological similarity was found between the right superior frontal gyrus and right hippocampus. The superficial white matter (SWM) showed significantly decreased FA in fiber tracts including the right superficial-frontal, left superficial-occipital, bilateral superficial-occipital-temporal (Sup-OT) and right superficial-temporal, meanwhile significant increased RD was found in the left Sup-OT. For the fiber connectivity, NDPH showed significantly decreased FA in the bilateral basal ganglion and temporal lobe, increased MD in the right frontal lobe, and increased RD in the right frontal lobe and left temporal-occipital lobe. Clinical scores could be predicted dominantly by the above significantly different neuroimaging features through decision tree regression.

CONCLUSIONS

Our research indicates the structural abnormalities of SWM and the neural pathways projected between regions like right hippocampus and left caudate nucleus, along with morphological similarity changes between the right superior frontal gyrus and right hippocampus, constitute the pathological features of NDPH. The decision tree regression demonstrates correlations between these structural changes and clinical scores.

The Effect of Forkhead Box O1 Single Nucleotide Polymorphisms on Cortical Thickness and White Matter Integrity in High Suicide Risk Patients

OBJECTIVE

Neuroinflammation's role is increasingly emphasized in the pathology of major depressive disorder (MDD), and its close association with the risk of suicide is being reported. The Forkhead Box O1 (FoxO1) gene is known to play a role in regulating mood and emotion and is associated with susceptibility to suicidality in relation to environmental stress. This research aims to explore the relationship between FoxO1 and the risk of suicide in individuals with MDD.

METHODS

We enrolled 127 healthy controls (HC) and 231 patients diagnosed with MDD, including 119 individuals with high suicide risk (HSR). All participants underwent the Hamilton Rating Scale for Depression Assessment and magnetic resonance imaging. Cortical thickness and white matter integrity were evaluated.

RESULTS

In the HSR group, cortical thinning was observed in the left triangular part of the inferior frontal gyrus and right transverse frontopolar gyrus compared to HC. Additionally, fractional anisotropy (FA) values were decreased in the left posterior thalamic radiation, sagittal stratum, and uncinate fasciculus. Although no differences were observed based on allele variations for the two FoxO1 single nucleotide polymorphisms (SNPs), those with the minor allele of FoxO1 rs34733279, especially in the HSR group, displayed increased cortical thinning and reduced FA values in the left cingulum.

CONCLUSION

Our study reveals close association between the minor allele of the FoxO1 gene rs34733279 and suicide risk in the left cingulum highlights the potential key role of the FoxO1 gene rs34733279 in the context of suicidal vulnerability. Further investigations are warranted to elucidate the underlying biological mechanisms.

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.

Thalamic spindles and Up states coordinate cortical and hippocampal co-ripples in humans

In the neocortex, ~90 Hz ripples couple to ~12 Hz sleep spindles on the ~1 Hz Down-to-Up state transition during non-rapid eye movement sleep. This conjunction of sleep waves is critical for the consolidation of memories into long-term storage. The widespread co-occurrences of ripples ("co-ripples") may integrate information across the neocortex and hippocampus to facilitate consolidation. While the thalamus synchronizes spindles and Up states in the cortex for memory, it is not known whether it may also organize co-ripples. Using human intracranial recordings during NREM sleep, we investigated whether cortico-cortical co-ripples and hippocampo-cortical co-ripples are either: (1) driven by directly projected thalamic ripples; or (2) coordinated by propagating thalamic spindles or Up states. We found ripples in the anterior and posterior thalamus, with similar characteristics as hippocampal and cortical ripples, including having a center frequency of ~90 Hz and coupling to local spindles on the Down-to-Up state transition. However, thalamic ripples rarely co-occur or phase-lock with cortical or hippocampal ripples. By contrast, spindles and Up states that propagate from the thalamus strongly coordinate co-ripples in the cortex and hippocampus. Thus, thalamo-cortical spindles and Up states, rather than thalamic ripples, may provide input facilitating spatially distributed co-rippling that integrates information for memory consolidation during sleep in humans.

High-level visual prediction errors in early visual cortex

Perception is shaped by both incoming sensory input and expectations derived from our prior knowledge. Numerous studies have shown stronger neural activity for surprising inputs, suggestive of predictive processing. However, it is largely unclear what predictions are made across the cortical hierarchy, and therefore what kind of surprise drives this up-regulation of activity. Here, we leveraged fMRI in human volunteers and deep neural network (DNN) models to arbitrate between 2 hypotheses: prediction errors may signal a local mismatch between input and expectation at each level of the cortical hierarchy, or prediction errors may be computed at higher levels and the resulting surprise signal is broadcast to earlier areas in the cortical hierarchy. Our results align with the latter hypothesis. Prediction errors in both low- and high-level visual cortex responded to high-level, but not low-level, visual surprise. This scaling with high-level surprise in early visual cortex strongly diverged from feedforward tuning. Combined, our results suggest that high-level predictions constrain sensory processing in earlier areas, thereby aiding perceptual inference.

A quantitative comparison of atlas parcellations on the human superior temporal sulcus

The superior temporal sulcus (STS) has a functional topography that has been difficult to characterize through traditional approaches. Automated atlas parcellations may be one solution while also being beneficial for both dimensional reduction and standardizing regions of interest, but they yield very different boundary definitions along the STS. Here we evaluate how well machine learning classifiers can correctly identify six social cognitive tasks from STS activation patterns dimensionally reduced using four popular atlases (Glasser et al., 2016; Gordon et al., 2016; Power et al., 2011 as projected onto the surface by Arslan et al., 2018; Schaefer et al., 2018). Functional data was summarized within each STS parcel in one of four ways, then subjected to leave-one-subject-out cross-validation SVM classification. We found that the classifiers could readily label conditions when data was parcellated using any of the four atlases, evidence that dimensional reduction to parcels did not compromise functional fingerprints. Mean activation for the social conditions was the most effective metric for classification in the right STS, whereas all the metrics classified equally well in the left STS. Interestingly, even atlases constructed from random parcellation schemes (null atlases) classified the conditions with high accuracy. We therefore conclude that the complex activation maps on the STS are readily differentiated at a coarse granular level, despite a strict topography having not yet been identified. Further work is required to identify what features have greatest potential to improve the utility of atlases in replacing functional localizers.

Excessive interstitial free-water in cortical gray matter preceding accelerated volume changes in individuals at clinical high risk for psychosis

Recent studies show that accelerated cortical gray matter (GM) volume reduction seen in anatomical MRI can help distinguish between individuals at clinical high risk (CHR) for psychosis who will develop psychosis and those who will not. This reduction is suggested to represent atypical developmental or degenerative changes accompanying an accumulation of microstructural changes, such as decreased spine density and dendritic arborization. Detecting the microstructural sources of these changes before they accumulate into volume loss is crucial. Our study aimed to detect these microstructural GM alterations using diffusion MRI (dMRI). We tested for baseline and longitudinal group differences in anatomical and dMRI data from 160 individuals at CHR and 96 healthy controls (HC) acquired in a single imaging site. Of the CHR individuals, 33 developed psychosis (CHR-P), while 127 did not (CHR-NP). Among all participants, longitudinal data was available for 45 HCs, 17 CHR-P, and 66 CHR-NP. Eight cortical lobes were examined for GM volume and GM microstructure. A novel dMRI measure, interstitial free water (iFW), was used to quantify GM microstructure by eliminating cerebrospinal fluid contribution. Additionally, we assessed whether these measures differentiated the CHR-P from the CHR-NP. In addition, for completeness, we also investigated changes in cortical thickness and in white matter (WM) microstructure. At baseline the CHR group had significantly higher iFW than HC in the prefrontal, temporal, parietal, and occipital lobes, while volume was reduced only in the temporal lobe. Neither iFW nor volume differentiated between the CHR-P and CHR-NP groups at baseline. However, in many brain areas, the CHR-P group demonstrated significantly accelerated changes (iFW increase and volume reduction) with time than the CHR-NP group. Cortical thickness provided similar results as volume, and there were no significant changes in WM microstructure. Our results demonstrate that microstructural GM changes in individuals at CHR have a wider extent than volumetric changes or microstructural WM changes, and they predate the acceleration of brain changes that occur around psychosis onset. Microstructural GM changes, as reflected by the increased iFW, are thus an early pathology at the prodromal stage of psychosis that may be useful for a better mechanistic understanding of psychosis development.

Brain morphometry and estimation of aging brain in subjects with congenital untreated isolated GH deficiency

PURPOSE

Individuals with isolated GH deficiency (IGHD) due to a mutation in the GHRH receptor gene have a normal life expectancy and above 50 years of age, similar total cognitive performance, with better attention and executive function than controls. Our objectives were to evaluate their brain morphometry and brain aging using MRI.

METHODS

Thirteen IGHD and 14 controls matched by age, sex, and education, were enrolled. Quantitative volumetric data and cortical thickness were obtained by automatic segmentation using Freesurfer software. The volume of each brain region was normalized by the intracranial volume. The difference between the predicted brain age estimated by MRI using a trained neuronal network, and the chronological age, was obtained. p < 0.005 was considered significant and 0.005 < p < 0.05 as a suggestive evidence of difference.

RESULTS

In IGHD, most absolute values of cortical thickness and regional brain volumes were similar to controls, but normalized volumes were greater in the white matter in the frontal pole and in the insula bilaterally, and in the gray matter, in the right insula and in left Caudate (p < 0.005 for all comparisons) We also noticed suggestive evidence of a larger volume in IGHD in left thalamus (p = 0.006), right thalamus (p = 0.025), right caudate (p = 0.046) and right putamen (p = 0.013). Predicted brain ages were similar between groups.

CONCLUSION

IGHD is primarily associated with similar absolute brain measurements, and a set of larger normalized volumes, and does not appear to alter the process of brain aging.

Bidirectional associations between perinatal allopregnanolone and depression severity with postpartum gray matter volume in adult women

BACKGROUND

Perinatal depression (PND) is a debilitating condition affecting maternal well-being and child development. Allopregnanolone (ALLO) is important to perinatal neuroplasticity, however its relationship with depression severity and postpartum structural brain volume is unknown.

METHOD

We examined perinatal temporal dynamics and bidirectional associations between ALLO and depression severity and the association between these variables and postpartum gray matter volume, using a random intercept cross-lagged panel model.

RESULTS

We identified a unidirectional predictive relationship between PND severity and ALLO concentration, suggesting greater depression severity early in the perinatal period may contribute to subsequent changes in ALLO concentration (β = 0.26, p = 0.009), while variations in ALLO levels during the perinatal period influences the development and severity of depressive symptoms later in the postpartum period (β = 0.38, p = 0.007). Antepartum depression severity (Visit 2, β = 0.35, p = 0.004), ALLO concentration (Visit 2, β = 0.37, p = 0.001), and postpartum depression severity (Visit 3, β = 0.39, p = 0.031), each predicted the right anterior cingulate volume. Antepartum ALLO concentration (Visit 2, β = 0.29, p = 0.001) predicted left suborbital sulcus volume. Antepartum depression severity (Visit 1, β = 0.39, p = 0.006 and Visit 2, β = 0.48, p < 0.001) predicted the right straight gyrus volume. Postpartum depression severity (Visit 3, β = 0.36, p = 0.001) predicted left middle-posterior cingulate volume.

CONCLUSION

These results provide the first evidence of bidirectional associations between perinatal ALLO and depression severity with postpartum gray matter volume.

A combined DTI-fMRI approach for optimizing the delineation of posteromedial versus anterolateral entorhinal cortex

In the entorhinal cortex (EC), attempts have been made to identify the human homologue regions of the medial (MEC) and lateral (LEC) subregions using either functional magnetic resonance imaging (fMRI) or diffusion tensor imaging (DTI). However, there are still discrepancies between entorhinal subdivisions depending on the choice of connectivity seed regions and the imaging modality used. While DTI can be used to follow the white matter tracts of the brain, fMRI can identify functionally connected brain regions. In this study, we used both DTI and resting-state fMRI in 103 healthy adults to investigate both structural and functional connectivity between the EC and associated cortical brain regions. Differential connectivity with these regions was then used to predict the locations of the human homologues of MEC and LEC. Our results from combining DTI and fMRI support a subdivision into posteromedial (pmEC) and anterolateral (alEC) EC and reveal a confined border between the pmEC and alEC. Furthermore, the EC subregions obtained by either imaging modality showed similar distinct whole-brain connectivity profiles. Optimizing the delineation of the human homologues of MEC and LEC with a combined, cross-validated DTI-fMRI approach allows to define a likely border between the two subdivisions and has implications for both cognitive and translational neuroscience research.

Atypical Brain Connectivity During Pragmatic and Semantic Language Processing in Children with Autism

BACKGROUND/OBJECTIVES

Children with Autism Spectrum Disorder (ASD) face challenges in social communication due to difficulties in considering context, processing information, and interpreting social cues. This study aims to explore the neural processes related to pragmatic language communication in children with ASD and address the research question of how functional brain connectivity operates during complex pragmatic language tasks.

METHODS

We examined differences in brain functional connectivity between children with ASD and typically developing peers while they engaged in video recordings of spoken language tasks. We focused on two types of speech acts: semantic and pragmatic.

RESULTS

Our results showed differences between groups during the pragmatic and semantic language processing, indicating more idiosyncratic connectivity in children with ASD in the Left Somatomotor and Left Limbic networks, suggesting that these networks play a role in task-dependent functional connectivity. Additionally, these functional differences were mainly localized to the left hemisphere.

Brain damage caused by status epilepticus: A prospective MRI study

BACKGROUND

Status epilepticus (SE) is a severe neurological condition that might lead to long-term consequences such as neuronal death. This study investigated whether SE leads to brain volume loss by characterizing the dynamic of peri-ictal MRI abnormalities (PMA) through follow-up MRIs and assessing whether SE duration and specific outcome characteristics are associated with brain atrophy.

METHODS

A prospective single-center cohort study enrolled 590 adult patients with definitive or possible SE. MRI in an acute setting was performed in 353/590 (60 %) patients. Follow-up MRIs at one week and one month were conducted to assess the reversibility of PMA. Measurements of diffuse brain volume were performed by employing a voxel-based morphometry with FreeSurfer, comparing an initial MRI with a follow-up test done four weeks after the initial one. The study analyzed the correlation between brain volume loss, SE duration, and clinical outcomes.

RESULTS

PMA were observed in 156/353 (44 %) patients in at least one MRI sequence. In 44/83 (53 %) patients, PMA were reversible in one week. PMA persisted in 39/83 (47 %) patients. A second follow-up MRI was performed four weeks after the initial MRI in 33/39 (85 %) patients. In 14/33 (42 %), the MRI showed signs of focal atrophy, mostly in hippocampus. Volumetric analysis performed in patients who underwent two follow-up MRIs, indicated that 85 % of patients (28/33) had a decreased diffuse brain volume, with a median volume reduction of 16 %. A moderate negative correlation was found between diffuse brain volume and SE duration (Spearman correlation: -0.57) as well as hospitalization length (Spearman correlation: -0.60). This indicates that longer SE duration and extended hospitalization were associated with a greater brain volume loss.

CONCLUSION

In this prospective study, a proportion of patients displayed cerebral volume loss following a SE. These patients had longer duration and worse outcome of SE. However, the findings should be interpreted with caution due to several limitations, including the lack of consideration for underlying etiologies that may contribute to volume loss.