Longitudinal alcohol-related brain changes in older adults: The Sydney Memory and Ageing Study.

Increases in harmful drinking among older adults indicate the need for a more thorough understanding of the relationship between later-life alcohol use and brain health. The current study investigated the relationships between alcohol use and progressive grey and white matter changes in older adults using longitudinal data. A total of 530 participants (aged 70 to 90 years; 46.0% male) were included. Brain outcomes assessed over 6 years included total grey and white matter volume, as well as volume of the hippocampus, thalamus, amygdala, corpus callosum, orbitofrontal cortex and insula. White matter integrity was also investigated. Average alcohol use across the study period was the main exposure of interest. Past-year binge drinking and reduction in drinking from pre-baseline were additional exposures of interest. Within the context of low-level average drinking (averaging 11.7 g per day), higher average amount of alcohol consumed was associated with less atrophy in the left (B = 7.50, pFDR = 0.010) and right (B = 5.98, pFDR = 0.004) thalamus. Past-year binge-drinking was associated with poorer white matter integrity (B = -0.013, pFDR = 0.024). Consuming alcohol more heavily in the past was associated with greater atrophy in anterior (B = -12.73, pFDR = 0.048) and posterior (B = -17.88, pFDR = 0.004) callosal volumes over time. Across alcohol exposures and neuroimaging markers, no other relationships were statistically significant. Within the context of low-level drinking, very few relationships between alcohol use and brain macrostructure were identified. Meanwhile, heavier drinking was negatively associated with white matter integrity.

Bayesian longitudinal tensor response regression for modeling neuroplasticity.

A major interest in longitudinal neuroimaging studies involves investigating voxel-level neuroplasticity due to treatment and other factors across visits. However, traditional voxel-wise methods are beset with several pitfalls, which can compromise the accuracy of these approaches. We propose a novel Bayesian tensor response regression approach for longitudinal imaging data, which pools information across spatially distributed voxels to infer significant changes while adjusting for covariates. The proposed method, which is implemented using Markov chain Monte Carlo (MCMC) sampling, utilizes low-rank decomposition to reduce dimensionality and preserve spatial configurations of voxels when estimating coefficients. It also enables feature selection via joint credible regions which respect the shape of the posterior distributions for more accurate inference. In addition to group level inferences, the method is able to infer individual-level neuroplasticity, allowing for examination of personalized disease or recovery trajectories. The advantages of the proposed approach in terms of prediction and feature selection over voxel-wise regression are highlighted via extensive simulation studies. Subsequently, we apply the approach to a longitudinal Aphasia dataset consisting of task functional MRI images from a group of subjects who were administered either a control intervention or intention treatment at baseline and were followed up over subsequent visits. Our analysis revealed that while the control therapy showed long-term increases in brain activity, the intention treatment produced predominantly short-term changes, both of which were concentrated in distinct localized regions. In contrast, the voxel-wise regression failed to detect any significant neuroplasticity after multiplicity adjustments, which is biologically implausible and implies lack of power.

Progressive grey matter alterations in bipolar disorder across the life span - A systematic review.

OBJECTIVES: To elucidate the relationship between the course of bipolar disorder (BD) and structural brain changes across the life span, we conducted a systematic review of longitudinal imaging studies in adolescent and adult BD patients. METHODS: Eleven studies with 329 BD patients and 277 controls met our PICOS criteria (participants, intervention, comparison, outcome and study design): BD diagnosis based on DSM criteria, natural course of disease, comparison of grey matter changes in BD individuals over ≥1-year interval between scans. RESULTS: The selected studies yielded heterogeneous findings, partly due to varying patient characteristics, data acquisition and statistical models. Mood episodes were associated with greater grey matter loss in frontal brain regions over time. Brain volume decreased or remained stable in adolescent patients, whereas it increased in healthy adolescents. Adult BD patients showed increased cortical thinning and brain structural decline. In particular, disease onset in adolescence was associated with amygdala volume reduction, which was not reported in adult BD. CONCLUSIONS: The evidence collected suggests that the progression of BD impairs adolescent brain development and accelerates structural brain decline across the lifespan. Age-specific changes in amygdala volume in adolescent BD suggest that reduced amygdala volume is a correlate of early onset BD. Clarifying the role of BD in brain development across the lifespan promises a deeper understanding of the progression of BD patients through different developmental episodes.

A prospective 5-year longitudinal study detects neurocognitive and imaging correlates of seizure remission in self-limiting Rolandic epilepsy.

OBJECTIVE: Self-limiting Rolandic epilepsy (RE) is the most common epilepsy in school-age children. Seizures are generally infrequent, but cognitive, language, and motor coordination problems can significantly impact the child's life. To better understand brain structure and function changes in RE, we longitudinally assessed neurocognition, cortical thickness, and subcortical volumes. METHODS: At baseline, we recruited 30 participants diagnosed with RE and 24-healthy controls and followed up for 4.94 ± 0.8 years when the participants with RE were in seizure remission. Measures included were as follows: T1-weighted magnetic resonance brain imaging (MRI) with FreeSurfer analysis and detailed neuropsychological assessments. MRI and neuropsychological data were compared between baseline and follow-up in seizure remission. RESULTS: Longitudinal MRI revealed excess cortical thinning in the left-orbitofrontal (p = 0.0001) and pre-central gyrus (p = 0.044). There is a significant association (p = 0.003) between a reduction in cortical thickness in the left-orbitofrontal cluster and improved processing of filtered words. Longitudinal neuropsychology revealed significant improvements in the symptoms of developmental coordination disorder (DCD, p = 0.005) in seizure remission. CONCLUSIONS: There is evidence for altered development of neocortical regions between active seizure state and seizure remission in RE within two clusters maximal in the left-orbitofrontal and pre-central gyrus. There is significant evidence for improvement in motor coordination between active seizures and seizure remission and suggestive evidence for a decline in fluid intelligence and gains in auditory processing.

Lasting consequences of concussion on the aging brain: Findings from the Baltimore Longitudinal Study of Aging.

Studies suggest that concussions may be related to increased risk of neurodegenerative diseases, such as Chronic Traumatic Encephalopathy and Alzheimer's Disease. Most neuroimaging studies show effects of concussions in frontal and temporal lobes of the brain, yet the long-term impacts of concussions on the aging brain have not been well studied. We examined neuroimaging data from 51 participants (mean age at first imaging visit=65.1 ± 11.23) in the Baltimore Longitudinal Study of Aging (BLSA) who reported a concussion in their medical history an average of 23 years prior to the first imaging visit, and compared them to 150 participants (mean age at first imaging visit=66.6 ± 10.97) with no history of concussion. Participants underwent serial structural MRI over a mean of 5.17±6.14 years and DTI over a mean of 2.92±2.22 years to measure brain structure, as well as 15O-water PET over a mean of 5.33±2.19 years to measure brain function. A battery of neuropsychological tests was also administered over a mean of 11.62±7.41 years. Analyses of frontal and temporal lobe regions were performed to examine differences in these measures between the concussion and control groups at first imaging visit and in change over time. Compared to those without concussion, participants with a prior concussion had greater brain atrophy in temporal lobe white matter and hippocampus at first imaging visit, which remained stable throughout the follow-up visits. Those with prior concussion also showed differences in white matter microstructure using DTI, including increased radial and axial diffusivity in the fornix/stria terminalis, anterior corona radiata, and superior longitudinal fasciculus at first imaging visit. In 15O-water PET, higher resting cerebral blood flow was seen at first imaging visit in orbitofrontal and lateral temporal regions, and both increases and decreases were seen in prefrontal, cingulate, insular, hippocampal, and ventral temporal regions with longitudinal follow-up. There were no significant differences in neuropsychological performance between groups. Most of the differences observed between the concussed and non-concussed groups were seen at the first imaging visit, suggesting that concussions can produce long-lasting structural and functional alterations in temporal and frontal regions of the brain in older individuals. These results also suggest that many of the reported short-term effects of concussion may still be apparent later in life.

Longitudinal progression of grey matter atrophy in non-amnestic Alzheimer's disease.

Recent models of Alzheimer's disease progression propose that disease may be transmitted between brain areas either via local diffusion or long-distance transport via white matter fibre pathways. However, it is unclear whether such models are applicable in non-amnestic Alzheimer's disease, which is associated with domain-specific cognitive deficits and relatively spared episodic memory. To date, the anatomical progression of disease in non-amnestic patients remains understudied. We used longitudinal imaging to differentiate earlier atrophy and later disease spread in three non-amnestic variants, including logopenic-variant primary progressive aphasia (n = 25), posterior cortical atrophy (n = 20), and frontal-variant Alzheimer's disease (n = 12), as well as 17 amnestic Alzheimer's disease patients. Patients were compared to 37 matched controls. All patients had autopsy (n = 7) or CSF (n = 67) evidence of Alzheimer's disease pathology. We first assessed atrophy in suspected sites of disease origin, adjusting for age, sex, and severity of cognitive impairment; we then performed exploratory whole-brain analysis to investigate longitudinal disease spread both within and outside these regions. Additionally, we asked whether each phenotype exhibited more rapid change in its associated disease foci than other phenotypes. Finally, we investigated whether atrophy was related to structural brain connectivity. Each non-amnestic phenotype displayed unique patterns of initial atrophy and subsequent neocortical change that correlated with cognitive decline. Longitudinal atrophy included areas both proximal to and distant from sites of initial atrophy, suggesting heterogeneous mechanisms of disease spread. Moreover, regional rates of neocortical change differed by phenotype. Logopenic-variant patients exhibited greater initial atrophy and more rapid longitudinal change in left lateral temporal areas than other groups. Frontal-variant patients had pronounced atrophy in left insula and middle frontal gyrus, combined with more rapid atrophy of left insula than other non-amnestic patients. In the medial temporal lobes, non-amnestic patients had less atrophy at their initial scan than amnestic patients, but longitudinal rate of change did not differ between patient groups. Medial temporal sparing in non-amnestic Alzheimer's disease may thus be due in part to later onset of medial temporal degeneration than in amnestic patients rather than different rates of atrophy over time. Finally, the magnitude of longitudinal atrophy was predicted by structural connectivity, measured in terms of node degree; this result provides indirect support for the role of long-distance fibre pathways in the spread of neurodegenerative disease. 10.1093/brain/awz091_video1 awz091media1 6041544065001.

Sex-Specific Vulnerability to Externalizing Problems: Sensitivity to Early Stress and Nucleus Accumbens Activation Over Adolescence.

BACKGROUND: Exposure and sensitivity to early-life stress (ELS) are related to increased risk for psychopathology in adolescence. While cross-sectional studies have reported blunted nucleus accumbens (NAcc) activation in the context of these associations, researchers have not yet assessed the effects of ELS on developmental trajectories of activation. We examined whether trajectories are affected by stress and the moderating role of biological sex in predicting vulnerability to symptoms of psychopathology. METHODS: Adolescents (n = 173) completed 3 assessments at 2-year intervals across puberty (ages 9-18 years). At baseline, we assessed objective ELS and stress sensitivity using the Traumatic Events Screening Inventory for Children. At all time points, we assessed NAcc activation using the Monetary Incentive Delay task and externalizing, internalizing, and total problems using the Youth Self-Report. We examined correlations between NAcc trajectories (extracted using linear mixed-effects models) with ELS and stress sensitivity and conducted multivariate regression analysis to examine the interaction of NAcc trajectories and biological sex in predicting symptoms of psychopathology. RESULTS: Symptoms increased over adolescence. Stress sensitivity, but not objective ELS, was associated with decreasing trajectories of NAcc activation. Biological sex interacted with NAcc trajectories to predict psychopathology; boys, but not girls, with decreasing NAcc activation had more severe externalizing problems in adolescence. These findings were replicated in the putamen and caudate but not in the medial prefrontal cortex or control brain regions. CONCLUSIONS: NAcc activation may be a sex-specific marker of externalizing problems in adolescence. Efforts to reduce stress sensitivity may help to decrease symptoms of psychopathology in adolescent boys.

Longitudinal self-supervised learning.

Machine learning analysis of longitudinal neuroimaging data is typically based on supervised learning, which requires large number of ground-truth labels to be informative. As ground-truth labels are often missing or expensive to obtain in neuroscience, we avoid them in our analysis by combing factor disentanglement with self-supervised learning to identify changes and consistencies across the multiple MRIs acquired of each individual over time. Specifically, we propose a new definition of disentanglement by formulating a multivariate mapping between factors (e.g., brain age) associated with an MRI and a latent image representation. Then, factors that evolve across acquisitions of longitudinal sequences are disentangled from that mapping by self-supervised learning in such a way that changes in a single factor induce change along one direction in the representation space. We implement this model, named Longitudinal Self-Supervised Learning (LSSL), via a standard autoencoding structure with a cosine loss to disentangle brain age from the image representation. We apply LSSL to two longitudinal neuroimaging studies to highlight its strength in extracting the brain-age information from MRI and revealing informative characteristics associated with neurodegenerative and neuropsychological disorders. Moreover, the representations learned by LSSL facilitate supervised classification by recording faster convergence and higher (or similar) prediction accuracy compared to several other representation learning techniques.

A voxel-wise assessment of growth differences in infants developing autism spectrum disorder.

Autism Spectrum Disorder (ASD) is a phenotypically and etiologically heterogeneous developmental disorder typically diagnosed around 4 years of age. The development of biomarkers to help in earlier, presymptomatic diagnosis could facilitate earlier identification and therefore earlier intervention and may lead to better outcomes, as well as providing information to help better understand the underlying mechanisms of ASD. In this study, magnetic resonance imaging (MRI) scans of infants at high familial risk, from the Infant Brain Imaging Study (IBIS), at 6, 12 and 24 months of age were included in a morphological analysis, fitting a mixed-effects model to Tensor Based Morphometry (TBM) results to obtain voxel-wise growth trajectories. Subjects were grouped by familial risk and clinical diagnosis at 2 years of age. Several regions, including the posterior cingulate gyrus, the cingulum, the fusiform gyrus, and the precentral gyrus, showed a significant effect for the interaction of group and age associated with ASD, either as an increased or a decreased growth rate of the cerebrum. In general, our results showed increased growth rate within white matter with decreased growth rate found mostly in grey matter. Overall, the regions showing increased growth rate were larger and more numerous than those with decreased growth rate. These results detail, at the voxel level, differences in brain growth trajectories in ASD during the first years of life, previously reported in terms of overall brain volume and surface area.

Longitudinal structural brain changes in Friedreich ataxia depend on disease severity: the IMAGE-FRDA study.

BACKGROUND: Friedreich ataxia is an inherited neurodegenerative disease, with cerebral and cerebellar pathology evident. Despite an increased understanding of its neuropathology, disease progression in this disease remains poorly understood. This study aimed to characterise longitudinal change in brain structure using a multi-modal approach across cerebral and cerebellar grey and white matter. METHODS: T1-weighted, diffusion-tensor, and magnetisation transfer magnetic resonance images were obtained from 28 individuals with Friedreich ataxia and 29 age- and gender-matched controls at two time-points, 2 years apart. Region-of-interest and exploratory between-group comparisons assessed changes in brain macrostructure (cerebellar lobule volume, cerebral cortical thickness/gyrification, brain white matter volume) and microstructure (white matter fractional anisotropy, mean/axial/radial diffusivity, magnetisation transfer ratio). Rates of change were correlated against change in neurological severity, Time 1 severity, and onset age. RESULTS: Individuals with Friedreich ataxia had a greater rate of white matter volume loss than controls in the superior cerebellar peduncles and right peri-thalamic/posterior cerebral regions, and greater reduction in left primary motor cortex gyrification. Greater cerebellar/brainstem white matter volume loss and right dorsal premotor gyrification loss was observed amongst individuals with less severe neurological symptoms at Time 1. Conversely, cerebral atrophy and changes in axial diffusivity were observed in individuals with more severe Time 1 symptoms. Progression in radial diffusivity was more pronounced amongst individuals with earlier disease onset. Greater right ventral premotor gyrification loss correlated with greater neurological progression. CONCLUSION: Heterogeneity in Friedreich ataxia progression is observed at the neurobiological level, with evidence of earlier cerebellar and later cerebral degeneration.

Ongoing Secondary Degeneration of the Limbic System in Patients With Ischemic Stroke: A Longitudinal MRI Study.

Purpose: Ongoing post-stroke structural degeneration and neuronal loss preceding neuropsychological symptoms such as cognitive decline and depression are poorly understood. Various substructures of the limbic system have been linked to cognitive impairment. In this longitudinal study, we investigated the post-stroke macro- and micro-structural integrity of the limbic system using structural and diffusion tensor magnetic resonance imaging. Materials and Methods: Nineteen ischemic stroke patients (11 men, 8 women, average age 53.4 ± 12.3, range 18-75 years), with lesions remote from the limbic system, were serially imaged three times over 1 year. Structural and diffusion-tensor images (DTI) were obtained on a 3.0 T MRI system. The cortical thickness, subcortical volume, mean diffusivity (MD), and fractional anisotropy (FA) were measured in eight different regions of the limbic system. The National Institutes of Health Stroke Scale (NIHSS) was used for clinical assessment. A mixed model for multiple factors was used for statistical analysis, and p-values <0.05 was considered significant. Results: All patients demonstrated improved NIHSS values over time. The ipsilesional subcortical volumes of the thalamus, hippocampus, and amygdala significantly decreased (p < 0.05) and MD significantly increased (p < 0.05). The ipsilesional cortical thickness of the entorhinal and perirhinal cortices was significantly smaller than the contralesional hemisphere at 12 months (p < 0.05). The cortical thickness of the cingulate gyrus at 12 months was significantly decreased at the caudal and isthmus regions as compared to the 1 month assessment (p < 0.05). The cingulum fibers had elevated MD at the ipsilesional caudal-anterior and posterior regions compared to the corresponding contralesional regions. Conclusion: Despite the decreasing NIHSS scores, we found ongoing unilateral neuronal loss/secondary degeneration in the limbic system, irrespective of the lesion location. These results suggest a possible anatomical basis for post stroke psychiatric complications.

Comparisons of neurodegeneration over time between healthy ageing and Alzheimer's disease cohorts via Bayesian inference.

OBJECTIVES: In recent years, large-scale longitudinal neuroimaging studies have improved our understanding of healthy ageing and pathologies including Alzheimer's disease (AD). A particular focus of these studies is group differences and identification of participants at risk of deteriorating to a worse diagnosis. For this, statistical analysis using linear mixed-effects (LME) models are used to account for correlated observations from individuals measured over time. A Bayesian framework for LME models in AD is introduced in this paper to provide additional insight often not found in current LME volumetric analyses. SETTING AND PARTICIPANTS: Longitudinal neuroimaging case study of ageing was analysed in this research on 260 participants diagnosed as either healthy controls (HC), mild cognitive impaired (MCI) or AD. Bayesian LME models for the ventricle and hippocampus regions were used to: (1) estimate how the volumes of these regions change over time by diagnosis, (2) identify high-risk non-AD individuals with AD like degeneration and (3) determine probabilistic trajectories of diagnosis groups over age. RESULTS: We observed (1) large differences in the average rate of change of volume for the ventricle and hippocampus regions between diagnosis groups, (2) high-risk individuals who had progressed from HC to MCI and displayed similar rates of deterioration as AD counterparts, and (3) critical time points which indicate where deterioration of regions begins to diverge between the diagnosis groups. CONCLUSIONS: To the best of our knowledge, this is the first application of Bayesian LME models to neuroimaging data which provides inference on a population and individual level in the AD field. The application of a Bayesian LME framework allows for additional information to be extracted from longitudinal studies. This provides health professionals with valuable information of neurodegeneration stages, and a potential to provide a better understanding of disease pathology.