Brain Changes Research Articles

Telehealth in arts therapies for neurodevelopmental and neurological disorders: a scoping review

BackgroundArts therapies, encompassing art therapy, music therapy, drama therapy, and dance movement therapy with the broader practice of expressive arts therapies, have demonstrated positive outcomes in the treatment of neurodevelopmental and neurological disorders (NNDs). Integrating arts therapies into telehealth has become increasingly important to improve accessibility for people with mobility impairments or those living in remote areas. This study aims to map the existing body of literature to provide an in-depth overview of telehealth in arts therapies for individuals with NNDs.MethodologyThis scoping review followed the PRISMA guidelines. Six databases were systematically searched, with 2,888 articles screened for eligibility. Inclusion criteria focused on primary research peer-reviewed articles in English that addressed telehealth arts therapies for NNDs.ResultsSeventeen telehealth studies published between 2009 and March 2024 were included, with a notable increase in publications after 2020. The studies covered various neurodevelopmental disorders, including autism spectrum disorders, attention deficit hyperactivity disorder (ADHD), Rett syndrome, and neurological disorders such as stroke, epilepsy, cerebral palsy, central nervous system (CNS) tumors, dementia, Alzheimer’s disease, Parkinson’s disease, spinal cord injuries, and mild cognitive impairment. Music therapy was the most widely studied modality. Interventions ranged from therapeutic singing and songwriting to virtual reality experiences. Different platforms and specialized virtual environments were used alongside pre-recorded sessions. Positive benefits included psychological enrichment, social connectivity, cognitive improvements, and brain changes, although some studies reported mixed or no significant effects in certain areas.ConclusionTelehealth in arts therapies significantly benefits individuals with NNDs, improving accessibility and providing psychological, emotional, social, and cognitive benefits. The positive benefits observed highlight the potential of these interventions to improve overall well-being and daily functioning. Future research may focus on high-quality qualitative studies and neuroimaging assessments to further validate the impact of telehealth arts therapies.

Functional and structural cerebellar-behavior relationships in aging.

Healthy aging is associated with deficits in cognitive performance and brain changes, including in the cerebellum. Cerebellar communication with the cortex via closed-loop circuits through the thalamus have been established and these circuits are closely related to the functional topography of the cerebellum. In this study, we sought to elucidate relationships between cerebellar structure and function with cognition in healthy aging. We explored this relationship in 138 healthy adults (aged 35-86, 53% female) using resting-state functional connectivity MRI (fcMRI), cerebellar volume, and cognitive and motor assessments. Behavioral tasks assessed attention, processing speed, working memory, episodic memory, and motor abilities. We expected to find negative relationships between lobular volume with age, and positive relationships between specific lobular volumes with motor and cognitive behavior, respectively. We predicted lower cerebello-cortical fcMRI with increased age. Behaviorally, we expected higher cerebello-frontal and cerebello-association area fcMRI cerebellar connectivity to correlate with better behavioral performance. Correlations were conducted between cerebellar lobules I-IV, V, Crus I, Crus II, vermis VI and behavioral measures. We found lower volumes with increased age as well as both higher and lower cerebellar connectivity relationships with increased age, consistent with literature on functional connectivity and network segregation in aging. Further, we revealed unique associations between cerebellar structure and connectivity with comprehensive behavioral measures in a healthy aging population. Our findings further highlight the role of the cerebellum in aging.

Brain change trajectories in healthy adults correlate with Alzheimer’s related genetic variation and memory decline across life

Throughout adulthood and ageing our brains undergo structural loss in an average pattern resembling faster atrophy in Alzheimer’s disease (AD). Using a longitudinal adult lifespan sample (aged 30-89; 2–7 timepoints) and four polygenic scores for AD, we show that change in AD-sensitive brain features correlates with genetic AD-risk and memory decline in healthy adults. We first show genetic risk links with more brain loss than expected for age in early Braak regions, and find this extends beyond APOE genotype. Next, we run machine learning on AD-control data from the Alzheimer’s Disease Neuroimaging Initiative using brain change trajectories conditioned on age, to identify AD-sensitive features and model their change in healthy adults. Genetic AD-risk linked with multivariate change across many AD-sensitive features, and we show most individuals over age ~50 are on an accelerated trajectory of brain loss in AD-sensitive regions. Finally, high genetic risk adults with elevated brain change showed more memory decline through adulthood, compared to high genetic risk adults with less brain change. Our findings suggest quantitative AD risk factors are detectable in healthy individuals, via a shared pattern of ageing- and AD-related neurodegeneration that occurs along a continuum and tracks memory decline through adulthood.

Cognitive Reserve? Cognitive Capacity!

The concept of cognitive reserve (CR) has been a cornerstone in cognitive aging research, offering a framework to explain how life experiences like education, occupation, bilingualism, and physical exercise may buffer individuals from cognitive decline in the face of aging or neurological disease. However, this paper argues that the CR model, while influential, may have outlived its usefulness due to inherent limitations that constrain future research directions and unintentionally encourage “magical thinking”. Specifically, CR’s definition, which relies on cognitive performance being “better than expected” based on known measures of brain structure and function, makes the concept temporally bound to current scientific understanding, potentially stifling novel insights into cognition. In contrast, we propose a shift to a cognitive capacity (CC) framework, which views cognitive performance as being always determined by the brain’s structural and functional capacities, without needing to invoke expectations based on incomplete knowledge. The CC framework is broader, encompassing factors that either promote or demote cognitive performance by directly modifying brain structure and function. This reconceptualization opens avenues for investigating cognitive enhancement not only in the context of aging or disease but also in young, healthy individuals. By emphasizing causal pathways between brain changes and cognitive outcomes, this perspective provides a more flexible and testable approach to understanding the mechanisms behind cognitive performance and its modulation across the lifespan.

Assessing age-related changes in brain activity during isometric upper and lower limb force control tasks.

Despite the widespread use of older adults (OA) as controls in movement disorder studies, the specific effects of aging on the neural control of upper and lower limb movements remain unclear. While functional MRI paradigms focusing on hand movements are widely used to investigate age-related brain changes, research on lower limb movements is limited due to technical challenges in an MRI environment. This study addressed this gap by examining both upper and lower limb movements in healthy young adults (YA) vs. OA. Sixteen YA and 20 OA, matched for sex, dominant side, and cognitive status, performed pinch grip and ankle dorsiflexion tasks, each requiring 15% of their maximum voluntary contraction. While both groups achieved the target force and exhibited similar force variability and accuracy, OA displayed distinct differences in force control dynamics, with a slower rate of force increase in the hand task and a greater rate of force decrease in the foot task. Imaging results revealed that OA exhibited more widespread activation, extending beyond brain regions typically involved in movement execution. In the hand task, OA showed increased activity in premotor and visuo-motor integration regions, as well as in the cerebellar hemispheres. During the foot task, OA engaged the cerebellar hemispheres more than YA. Collectively, results suggest that OA may recruit additional brain regions to manage motor tasks, possibly to achieve similar performance. Future longitudinal studies that track changes over time could help clarify if declines in motor performance lead to corresponding changes in brain activation.

Subject-Level Segmentation Precision Weights for Volumetric Studies Involving Label Fusion.

In neuroimaging research, volumetric data contribute valuable information for understanding brain changes during both healthy aging and pathological processes. Extracting these measures from images requires segmenting the regions of interest (ROIs), and many popular methods accomplish this by fusing labels from multiple expert-segmented images called atlases. However, post-segmentation, current practices typically treat each subject's measurement equally without incorporating any information about variation in their segmentation precision. This naïve approach hinders comparing ROI volumes between different samples to identify associations between tissue volume and disease or phenotype. We propose a novel method that estimates the variance of the measured ROI volume for each subject due to the multi-atlas segmentation procedure. We demonstrate in real data that weighting by these estimates markedly improves the power to detect a mean difference in hippocampal volume between controls and subjects with mild cognitive impairment or Alzheimer's disease.

Altered eotaxin-1 and interleukin-34 levels in obsessive-compulsive disorder: a case-control observational study in Bangladesh.

Obsessive-compulsive disorder (OCD) is a prevalent mental health condition that impacts daily life. It is thought to be associated with genetic, biological, and structural brain changes, serotonergic abnormalities, altered neuromodulation, and environmental factors. Limited observational studies have examined cytokines in Bangladeshi patients with OCD. This study aimed to assess the levels of eotaxin-1 and interleukin (IL)-34 in individuals with this disorder. This case-control observational study included 58 patients with OCD and 30 healthy controls (HCs) matched for age, sex, and body mass index. The severity of OCD was assessed using the Yale-Brown obsessive-compulsive scale (Y-BOCS). Psychiatrists evaluated participants according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. Serum levels of eotaxin-1 and IL-34 were measured using enzyme-linked immunosorbent assay kits. Patients with OCD exhibited significantly higher serum eotaxin-1 levels (121.13±7.84 pg/mL) than HCs (85.52±9.42 pg/mL). Conversely, IL-34 levels were considerably lower in patients than in HCs (119.02±14.53 pg/mL vs. 179.96±27.88 pg/mL). The Cohen d values for eotaxin-1 and IL-34 were 0.55 and -0.48, respectively. Among patients with OCD, a significant positive correlation was found between serum eotaxin-1 level and Y-BOCS score, along with a negative correlation between serum eotaxin-1 and IL-34 levels. The findings suggest that altered eotaxin-1 and IL-34 levels may be associated with OCD. These chemokines and cytokines could serve as primary tools for assessing the risk of OCD, warranting further clinical investigation. This could potentially support more extensive research and the development of diagnostic and therapeutic strategies targeting these pathways.

Brain volumes in genetic syndromes associated with mTOR dysregulation: a systematic review and meta-analysis.

Dysregulation of molecular pathways associated with mechanistic target of rapamycin (mTOR) and elevated rates of neurodevelopmental disorders are implicated in the genetic syndromes neurofibromatosis type 1 (NF1), tuberous sclerosis complex (TSC), fragile X syndrome (FXS), and Noonan syndrome (NS). Given shared molecular and clinical features, understanding convergent and divergent implications of these syndromes on brain development may offer unique insights into disease mechanisms. While an increasing number of studies have examined brain volumes in these syndromes, the effects of each syndrome on global and subcortical brain volumes are unclear. Therefore, the aim of the current study was to conduct a systematic review and meta-analysis to synthesize existing literature on volumetric brain changes across TSC, FXS, NF1, and NS. Study outcomes were the effect sizes of the genetic syndromes on whole brain, gray and white matter, and subcortical volumes compared to typically developing controls. We performed a series of meta-analyses synthesizing data from 23 studies in NF1, TSC, FXS, and NS (pooled N = 1556) reporting whole brain volume, gray and white matter volumes, and volumes of subcortical structures compared to controls. Meta-analyses revealed significantly larger whole brain volume, gray and white matter volumes, and subcortical volumes in NF1 compared to controls. FXS was associated with increased whole brain, and gray and white matter volumes relative to controls, but effect sizes were smaller than those seen in NF1. In contrast, studies in NS indicated smaller whole brain and gray matter volumes, and reduced subcortical volumes compared to controls. For individuals with TSC, there were no significant differences in whole brain, gray matter, and white volumes compared to controls. Volumetric effect sizes were not moderated by age, sex, or full-scale IQ. This meta-analysis revealed that dysregulation of mTOR signaling across pre- and post-natal periods of development can result in convergent and divergent consequences for brain volume among genetic syndromes. Further research employing advanced disease modeling techniques with human pluripotent stem cell-derived in vitro models is needed to further refine our understanding of between and within syndrome variability on early brain development and identify shared molecular mechanisms for the development of pharmaceutical interventions.

Magnetic resonance imaging of brain structural and functional changes in cognitive impairment associated with Parkinson's disease.

Cognitive impairment is a critical non-motor symptom of Parkinson's Disease (PD) that profoundly affects patients' quality of life. Magnetic Resonance Imaging (MRI) has emerged as a valuable tool for investigating the structural and functional brain changes associated with cognitive impairment in PD (PD-CI). MRI techniques enable the precise identification and monitoring of the onset and progression of cognitive deficits in PD. This review synthesizes recent literature on the use of MRI-based techniques, including voxel-based morphometry, diffusion tensor imaging, and functional MRI, in the study of PD-CI. By examining these imaging modalities, the article aims to elucidate the patterns of brain structural and functional alterations in PD-CI, offering critical insights that can inform clinical management and therapeutic strategies. In particular, this review provides a novel synthesis of recent advancements in understanding how specific MRI metrics, such as amplitude of low-frequency fluctuations, regional homogeneity, and functional connectivity, contribute to early detection and personalized treatment approaches for PD-CI. The integration of findings from these studies enhances our understanding of the neural mechanisms underlying cognitive impairment in PD and highlights the potential of MRI as a supportive tool in the clinical assessment and treatment of PD-CI.

Brain changes following subchronic exposure to copper oxide nanoparticles: animal experimental data analysis

AbstractThe goal of this study was to assess the health effects of (copper oxide nanparticles) CuO NPs on the brain structure and function in rats. Morphology results showed that the number of axons with the damaged myelin sheath in basal ganglia and the proportion of pathologically altered mitochondria in olfactory bulbs and basal ganglia had increased, while the concentration of myelin basic protein in blood serum remained unchanged. We also have observed the lower body weight gain, signs of hemolytic anemia, an increased platelet count, reduced locomotion and exploratory activity. We propose that the central nervous system and haematopoiesis are the targets for toxicity of CuO NPs administered intranasally during six weeks at the total dose of 0.45 mg/kg body weight.

Impact of Deprivation and Preferential Usage on Functional Connectivity Between Early Visual Cortex and Category-Selective Visual Regions.

Human behavior can be remarkably shaped by experience, such as the removal of sensory input. Many studies of conditions such as stroke, limb amputation, and vision loss have examined how removal of input changes brain function. However, an important question yet to be answered is: when input is lost, does the brain change its connectivity to preferentially use some remaining inputs over others? In individuals with healthy vision, the central portion of the retina is preferentially used for everyday visual tasks, due to its ability to discriminate fine details. When central vision is lost in conditions like macular degeneration, peripheral vision must be relied upon for those everyday tasks, with some portions receiving "preferential" usage over others. Using resting-state fMRI collected during total darkness, we examined how deprivation and preferential usage influence the intrinsic functional connectivity of sensory cortex by studying individuals with selective vision loss due to late stages of macular degeneration. Specifically, we examined functional connectivity between category-selective visual areas and the cortical representation of three areas of the retina: the lesioned area, a preferentially used region of the intact retina, and a non-preferentially used region. We found that cortical regions representing spared portions of the peripheral retina, regardless of whether they are preferentially used, exhibit plasticity of intrinsic functional connectivity in macular degeneration. Cortical representations of spared peripheral retinal locations showed stronger connectivity to MT, a region involved in processing motion. These results suggest that the long-term loss of central vision can produce widespread effects throughout spared representations in early visual cortex, regardless of whether those representations are preferentially used. These findings support the idea that connections to visual cortex maintain the capacity for change well after critical periods of visual development.

Identification of neural alterations in patients with Crohn’s disease with a novel multiparametric brain MRI-based radiomics model

ObjectivesGut-brain axis dysfunction has emerged as a key contributor to the pathogenesis of Crohn’s disease (CD). The elucidation of neural alterations may provide novel insights into its management. We aimed to develop a multiparameter brain MRI-based radiomics model (RM) for characterizing neural alterations in CD patients and to interpret these alterations using multiomics traits.MethodsThis prospective study enrolled 230 CD patients and 46 healthy controls (HCs). Participants voluntarily underwent brain MRI and psychological assessment (n = 155), blood metabolomics analysis (n = 260), and/or fecal 16S rRNA sequencing (n = 182). The RM was developed using 13 features selected from 13,870 first-order features extracted from multiparameter brain MRI in training cohort (CD, n = 75; HCs, n = 32) and validated in test cohort (CD, n = 34; HCs, n = 14). Multiomics data (including gut microbiomics, blood metabolomics, and brain radiomics) were compared between CD patients and HCs.ResultsIn the training cohort, area under the receiver operating characteristic curve (AUC) of RM for distinguishing CD patients from HCs was 0.991 (95% confidence interval (CI), 0.975–1.000). In test cohort, RM showed an AUC of 0.956 (95% CI, 0.881–1.000). CD-enriched blood metabolites such as triacylglycerol (TAG) exhibited significant correlations with both brain features detected by RM and CD-enriched microbiota (e.g., Veillonella). One notable correlation was found between Veillonella and Ctx-Lh-Middle-Temporal-CBF-p90 (r = 0.41). Mediation analysis further revealed that dysbiosis, such as of Veillonella, may regulate the blood flow in the middle temporal cortex through TAG.ConclusionWe developed a multiparameter MRI-based RM that characterized the neural alterations of CD patients, and multiomics data offer potential evidence to support the validity of our model. Our study may offer clues to help provide potential therapeutic targets.Critical relevance statementOur brain-gut axis study developed a novel model using multiparameter MRI and radiomics to characterize brain changes in patients with Crohn’s disease. We validated this model’s effectiveness using multiomics data, making it a potential biomarker for better patient management.Key PointsUtilizing multiparametric MRI and radiomics techniques could unveil Crohn’s disease’s neurophenotype.The neurophenotype radiomics model is interpreted using multiomics data.This model may serve as a novel biomarker for Crohn’s disease management.Graphical

A DAT1 gene and APOE ε4 interaction is associated with apathy and structural brain changes in mild cognitive impairment and Alzheimer's disease.

Apathy in patients with Alzheimer's disease (AD) is associated with significant morbidity and is often one of the first neuropsychiatric symptoms to present in mild cognitive impairment (MCI). Apathy is associated with accelerated cognitive decline and atrophy in fronto-striatal regions of the brain. Previous work has shown a link between apathy and the APOE gene in the context of AD, as the APOE ε4 allele is already known to be associated with the onset of AD. However, other genetic associations with apathy are largely unexplored. To examine whether interactions between genetic variants related to neurotransmitter systems and regional brain atrophy are associated with apathy in patients with MCI and AD. In a sample of individuals with AD (n = 266), MCI (n = 518), and cognitively normal controls (n = 378), a partial least squares correspondence analysis modeled interactions between single nucleotide polymorphisms, structural whole-brain imaging variables, and apathy. An interaction was found between apathy, the possession of an APOE ε4 allele combined with minor homozygosity for the DAT1 (dopamine transporter 1) gene, and regional brain atrophy. This interaction was closely linked to the MCI and AD groups. The results point to an association of a dopaminergic genetic marker and apathy in the AD continuum and may inform future design of clinical trials of apathy, as well as new treatment targets.

Targeted Proteomic Biomarker Profiling Using NULISA in a cohort enriched with risk for Alzheimer's Disease and Related Dementias.

Targeted proteomic assays may be useful for diagnosing and staging Alzheimer's disease and related dementias (ADRD). We evaluated the performance of a 120-marker central nervous system (CNS) NUcleic acid-Linked Immuno-Sandwich Assay (NULISA) panel in samples spanning the AD spectrum. Cross-sectional plasma samples (n=252) were analyzed using Alamar's NULISAseq CNS panel. ROC analyses demonstrated NULISAseq-pTau217 accuracy in detecting amyloid (A) and tau (T) PET positivity. Differentially expressed proteins were identified using volcano plots. NULISAseq-pTau217 accurately classified A/T PET status with ROC AUCs of 0.92/0.86. pTau217 was upregulated in A+, T+, and impaired groups with log2-fold changes of 1.21, 0.57 and 4.63, respectively, compared to A-. Interestingly, pTDP43-409 was also upregulated in the impaired group and correlated with declining hippocampal volume and cognitive trajectories. This study shows the potential of a targeted proteomics panel for characterizing brain changes pertinent to ADRD. The promising pTDP43-409 findings require further replication.

Decoding meditation mechanisms underlying brain preservation and psycho-affective health in older expert meditators and older meditation-naive participants

Meditation is a mental training approach that can improve mental health and well-being in aging. Yet the underlying mechanisms remain unknown. The Medit-Ageing model stipulates that three mechanisms — attentional, constructive, and deconstructive — upregulate positive psycho-affective factors and downregulate negative ones. To test this hypothesis, we measured brain structural MRI and perfusion, negative and positive psycho-affective composite scores, and meditation mechanisms in 27 older expert meditators and 135 meditation-naive older controls. We identified brain and psycho-affective differences and performed mediation analyses to assess whether and which meditation mechanisms mediate their links.Meditators showed significantly higher volume in fronto-parietal areas and perfusion in temporo-occipito-parietal areas. They also had higher positive and lower negative psycho-affective scores. Attentional and constructive mechanisms both mediated the links between brain differences and the positive psycho-affective score whereas the deconstructive mechanism mediated the links between brain differences and the negative psycho-affective score.Our results corroborate the Medit-Ageing model, indicating that, in aging, meditation leads to brain changes that decrease negative psycho-affective factors and increase positive ones through relatively specific mechanisms. Shedding light on the neurobiological and psycho-affective mechanisms of meditation in aging, these findings provide insights to refine future interventions.

Born Connected: Do Infants Already Have Adult-Like Multi-Scale Connectivity Networks?

The human brain undergoes remarkable development with the first six postnatal months witnessing the most dramatic structural and functional changes, making this period critical for in-depth research. rsfMRI studies have identified intrinsic connectivity networks (ICNs), including the default mode network, in infants. Although early formation of these networks has been suggested, the specific identification and number of ICNs reported in infants vary widely, leading to inconclusive findings. In adults, ICNs have provided valuable insights into brain function, spanning various mental states and disorders. A recent study analyzed data from over 100,000 subjects and generated a template of 105 multi-scale ICNs enhancing replicability and generalizability across studies. Yet, the presence of these ICNs in infants has not been investigated. This study addresses this significant gap by evaluating the presence of these multi-scale ICNs in infants, offering critical insight into the early stages of brain development and establishing a baseline for longitudinal studies. To accomplish this goal, we employ two sets of analyses. First, we employ a fully data-driven approach to investigate the presence of these ICNs from infant data itself. Towards this aim, we also introduce burst independent component analysis (bICA), which provides reliable and unbiased network identification. The results reveal the presence of these multi-scale ICNs in infants, showing a high correlation with the template (rho > 0.5), highlighting the potential for longitudinal continuity in such studies. We next demonstrate that reference-informed ICA-based techniques can reliably estimate these ICNs in infants, highlighting the feasibility of leveraging the NeuroMark framework for robust brain network extraction. This approach not only enhances cross-study comparisons across lifespans but also facilitates the study of brain changes across different age ranges. In summary, our study highlights the novel discovery that the infant brain already possesses ICNs that are widely observed in older cohorts.

Characterization of Morphological Brain Changes in Generalized Epilepsy Using Region-based Morphometry

Magnetic Resonance Imaging has been widely involved in detecting morphological brain changes in generalized epilepsy at voxel level. It is believed that region-based morphometry could provide better characterizations for macro structural changes in the brain with comparative advantages than voxel-based morphometry. The aim of this study is to detect regional brain changes associated with generalized epilepsy and to test the potential of regional brain changes in classification of patients with generalized epilepsy and non-epileptic subjects. 45 patients and 46 non-epileptic subjects were scanned using a 3 Tesla MRI scanner and 3D T1 weighted images were obtained. Images were pre-processed and region based structural metrics (grey matter volumes, white matter volumes, cerebrospinal fluid volumes, cortical gyrification, and sulcus depth) were developed using Computational Anatomical Toolbox (CAT12). Two sample t-tests were used to perform the univariate analyses and results were corrected for multiple comparisons (FDR corrected, p < 0.05). Grey matter volume reductions were detected in cerebellum, frontal lobe, temporal lobe, thalamus, and hippocampal region while bilateral white matter volume reductions were reported in cerebellum. In contrast, cerebrospinal fluid volume increments in left lateral ventricle were also detected. Reduced regional gyrification was detected in left posterior ramus of the lateral sulcus and reduced sulcal depths were detected in occipital pole, cuneus, and posterior ramus of the lateral sulcus in patients. Furthermore, pattern analysis revealed that each metric shows different discriminative abilities to distinguish patients with generalized epilepsy and non-epileptic subjects (Classification accuracy: 61.1%, 62.2%, 58.8%, 61.1% and 60% for GMV, WMV, CSFV, Cortical gyrification and sulcal depth respectively). In conclusion, this study provides a comprehensive understanding about regional structural changes (cortical and subcortical) associated with generalized epilepsy under region-based morphometry. However, pattern analyses do not provide adequate discriminative power and therefore the clinical utility of findings is limited.

MRI-based Whole-Brain Elastography and Volumetric Measurements to Predict Brain Age

Abstract Brain age, as a correlate of an individual’s chronological age obtained from structural and functional neuroimaging data, enables assessing developmental or neurodegenerative pathology relative to the overall population. Accurately inferring brain age from brain magnetic resonance imaging (MRI) data requires imaging methods sensitive to tissue health and sophisticated statistical models to identify the underlying age-related brain changes. Magnetic resonance elastography (MRE) is a specialized MRI technique which has emerged as a reliable, non-invasive method to measure the brain’s mechanical properties, such as the viscoelastic shear stiffness and damping ratio. These mechanical properties have been shown to change across the life span, reflect neurodegenerative diseases, and are associated with individual differences in cognitive function. Here, we aim to develop a machine learning framework to accurately predict a healthy individual’s chronological age from maps of brain mechanical properties. This framework can later be applied to understand neurostructural deviations from normal in individuals with neurodevelopmental or neurodegenerative conditions. Using 3D convolutional networks as deep learning models and more traditional statistical models, we relate chronological age as a function of multiple modalities of whole-brain measurements: stiffness, damping ratio, and volume. Evaluations on held-out subjects show that combining stiffness and volume in a multimodal approach achieves the most accurate predictions. Interpretation of the different models highlight important regions that are distinct between the modalities. The results demonstrate the complementary value of MRE measurements in brain age models, which, in future studies, could improve model sensitivity to brain integrity differences in individuals with neuropathology.

Physical Activity and Neurodegenerative Diseases: Potential Role in Prevention and Therapy

Physical activity and exercise are low-cost interventions in primary and secondary prevention of several noncommunicable disease (e.g. cardiovascular diseases, chronic kidney disease, neurodegenerative and neurovascular disease). In the context of demographic change, the relative and absolute numbers of patients with neurological, especially neurodegenerative disease, will increase. Based on missing causal therapies and high costs, non-pharmacological (e.g. physical activity) approaches for healthy aging are gaining attention. Epidemiological, observational, and randomized controlled studies have shown that physical activity can enhance brain plasticity and improve cognitive vitality over lifespan. However, the underlying neurobiological mechanisms are still largely unknown. Physical activity can influence different risk factors for neurovascular and neurodegenerative diseases (e.g. arterial hypertension, obesity). Moreover, physical activity can induce cellular and molecular changes (level 1) followed by structural and functionals brain changes (level 2) and/or behavioural adaptations (level 3). In this clinical review we summarize the role of physical activity in the prevention and therapy of neurological disease.

Microstructural brain changes following prospective memory rehabilitation in traumatic brain injury: An observational study

ABSTRACT Prospective memory (PM) impairment is a common consequence of moderate-severe traumatic brain injury (TBI). Compensatory strategy training and rehabilitation (COMP) is the usual treatment of PM deficits through environmental modification and the use of assistive methods such as diaries and routines. The study intends to examine the changes in white matter integrity, as measured by advanced diffusion magnetic resonance imaging (dMRI) following COMP intervention in moderate-severe TBI patients. Nine COMP intervention and twelve routine care comparison cohort moderate-severe TBI patients were recruited from level 1 trauma centres in the Brisbane metropolitan area. Both groups were imaged at least one-month post-TBI for a baseline scan. COMP group was imaged again after a 6-week COMP intervention program and the comparison group was imaged again at least 6 weeks after the baseline scan. MRI scan included structural imaging and dMRI, which the latter fitted for the Neurite Orientation Dispersion and Density Imaging (NODDI) model. Only the comparison group had decreased Neurite Density Index in the major white matter tracts and increased isotropic diffusion in the fluid space between the cortical folds. Our results indicated that COMP intervention slowed down the neural degeneration in moderate-severe TBI patients as compared to routine medical care/rehabilitation.