Repetitive behaviour, resulting from impaired inhibitory control and error monitoring, represents a core manifestation of autism, with a poorly understood neural basis. Our primary hypothesis was that a striatum-midbrain framework could provide a theoretical basis for understanding neural changes underlying response inhibition in autism. This conceptual approach considered two critical neurobehavioural factors: (a) inhibition as a dynamic process requiring trial-and-error learning, and (b) efficient error learning relying on the striatum receiving dopaminergic signals from the midbrain-a framework analogous to an 'actor-critic' architecture. Eighteen adults with a diagnosis of autism spectrum disorder and 21 age-matched healthy controls performed a stop-signal task adjusted for functional MRI (fMRI). To dissect domain-dependent correlates of neural inhibition, we measured brain activation and connectivity as a function of task phases in the dorsal striatum and dopaminergic midbrain nuclei. Repetitive behaviour severity was assessed using the observer-reported Repetitive Behaviours Scale-Revised. A striking hypoactivation in the midbrain during failed inhibition events was observed in relation with the severity of repetitive behaviours. We also identified, in the autism group, reduced functional connectivity between the midbrain-striatum hubs and regions involved in cognitive control (prefrontal cortex) and error monitoring (bilateral insula), during response preparation periods. Finally, although both groups achieved similar final performance levels, neurodivergent subjects learned slower and displayed delayed striatal engagement when behavioural adjustment was required. These results reveal a novel autism profile characterized by midbrain hypoactivation mediating repetitive behaviour manifestations and reduced long-range mesocortical hypoconnectivity during inhibitory response preparation phases. Accordingly, we suggest that individuals with autism exhibit midbrain-dependent reduced motivational arousal, limiting their ability to develop proactive strategies for trial-and-error learning and regulate out-of-context behaviours. By highlighting the key role of dopaminergic midbrain structures and related long-range pathways, we challenge the view autism as solely a cortical dysfunction condition and provide evidence for promising targets for neurobiologically-driven interventions based on dopaminergic mechanisms.
Individuals with post-stroke aphasia, an acquired language disorder, face significant communication challenges essential for daily life. Surprisingly, little is known about how focal brain damage disrupts the bilateral anatomical integration of language and multiple-demand brain networks required for higher level, connected spoken language following aphasic stroke. To address this, we investigated the anatomical network correlates of spoken language abilities in a selective subgroup of thirty-six individuals with chronic post-stroke aphasia who had preserved single-word comprehension and monosyllabic word repetition (mean age 59 ± 12.51 years; 26 males/10 females) using an innovative methodological framework. Employing a lesion quantification toolkit and graph theory analyses of T1 volumetric MRI brain scans we measured individual's brain structural network efficiency. We then quantified the efficiency of their spoken language abilities using measures of bigram frequency, collocation, and speech connectivity using a frequency language analysis tool. Combining these brain and behavioural data, we found that higher structural efficiency in bilateral language networks significantly correlated with better connected speech abilities. By quantifying the impact of focal lesions on not only the left (dominant) language network but also bilateral language and multiple-demand networks, we were able to account for variance in aphasic's higher level, connected speech abilities. Post hoc analyses showed (i) word-level spoken language behaviours were associated with discrete left temporo-parietal, using voxel-based correlational methodology; (ii) while bilateral language and multiple-demand structural network efficiency was primarily sensitive to higher-level language behaviours, loading additional brain-behaviour variance beyond distributed voxels. These findings replicate prior research on word-level language behaviours and extend our insights into how bilateral brain networks are integrated in connected spoken language. Taken together, our findings illustrate how connected speech abilities, beyond the single-word level, in post-stroke aphasia rely on distributed bilateral anatomical networks. By utilizing widely available structural MRI brain scans alongside connected speech analyses mirroring more closely real-life speech communication, the framework we propose here offers a clinically accessible approach to enhance aphasia research and treatment. By focusing on structural network efficiency, it provides a transformative method to better understand the relationship between brain anatomical connectivity and spoken language skills, potentially guiding more effective aphasia interventions.
Waves are fundamental. In our view, waves in the brain may constitute and drive organized neural activity patterns on individual neural and population levels. Their interactions follow basic physical principles. Taking a comprehensive, temporal and spatiotemporal perspective, we endeavor to explain multiple brain functions and behaviors with a unified mechanistic approach. Starting with neural architectures, traveling waves, and spikes as the basic signals of the system, our multidisciplinary theory proposes that precise temporal phase-locking codes, spike coincidences, phase relationships, recurrent networks, temporal and spatiotemporal population patterns, pattern correlations, their interactions, synchronizations and couplings play an essential role in determining brain dynamics at multiple processing scales. Analogously to optical holography, it posits that traveling brain waves convey spike timing information, interact to form distinctive time/phase interference patterns and spatially distribute these widely. These in turn can interact with other traveling waves producing yet new spike patterns. Traveling waves also serve to selectively reactivate/refresh existing patterns. Spatially distributed temporal spike patterns and representations derived from these, are used to code, process, synchronize, integrate, and decode objects (e.g., sensorimotor events, concepts, etc.). We apply established physical principles (e.g., wave dynamics, holography) and signal processing principles (e.g., linear additive operations, and nonlinear, multiplicative frequency mixing). This theory proposes that oscillations may serve as signal carriers for communications in transmitting progressively processed signals through an emergent cascade of neuron mixing stages. Such cascades closely correspond to intermediate frequency (IF) processing stages in broadly used radio communications, specifically superheterodyned Single Sideband Suppressed Carrier (SSBSC = SSB) communications technology. This is illustrated with a numerical speech/language hierarchy oscillatory cascade model. This model correlates signal processing stages with both canonical oscillation bands and associated cognitive stages. Plausible biophysical mechanisms are proposed to realize these processes. Many neurophysiological observations consistent with these proposed mechanisms are referenced. This proposal is novel in suggesting conceptual integrations and coordinations of multiple disciplines that mechanistically trace informational neural signals from inception to conception. Some suggestions for empirically testing these hypotheses are presented.
Spatiotemporal spreading of amyloid-β peptide deposition as senile plaques is a key pathogenic process in the brains of patients with Alzheimer's disease; however, the molecular properties of amyloid-β strains that initiate the spreading of amyloid-β peptide as aggregation seeds in vivo remain poorly understood. In this study, we discovered that the intrahippocampal injection of soluble amyloid-β species with a molecular weight of >150 kDa isolated from the brains of plaque-laden amyloid-β precursor protein transgenic mice or patients with Alzheimer's disease using size-exclusion chromatography, dramatically accelerated β-amyloidosis in the transgenic mice brains. In contrast, intrahippocampal injection of soluble amyloid-β species with 50-70 kDa or 10-20 kDa never induced β-amyloidosis. Moreover, injection of the soluble amyloid-β species with >150 kDa into cerebrospinal fluid of young transgenic mice via the cisterna magna predominantly induced amyloid-β deposition within the wall of leptomeningeal arteries surrounding the brain, reminiscent of cerebral amyloid angiopathy. The seeding activity of the soluble high-molecular-weight amyloid-β was prevented by the immunodepletion of amyloid-β and abolished by formic acid denaturation, suggesting that these amyloid-β oligomers are crucial in inducing β-amyloidosis. Furthermore, we have shown that the soluble high-molecular-weight amyloid-β is present in the brains of patients with Alzheimer's disease and induced β-amyloidosis. These results indicate that the soluble high-molecular-weight amyloid-β oligomers may play an important role in the spatiotemporal spreading of amyloid-β deposition in Alzheimer's disease brains.
Down syndrome, a condition characterized by triplication of chromosome 21, leads to a complex interplay between neurodevelopmental and dementia-related changes similar to the ones observed in Alzheimer's disease. Here we aimed to understand this interplay by using imaging biomarkers for different cognitive profiles in Down syndrome, and by analysing early developmental differences versus age-related changes. We analysed voxel-based morphometric measures of grey matter volume from high-resolution T1-weighted MRI in 23 adults with Down syndrome (18-59 years, five female) in preclinical/prodromal stages of Alzheimer's disease and 24 age- and sex-matched controls, along with cognitive assessments. Neuroanatomical group differences were assessed using two-sample t-tests. Age-related effects on brain integrity, and cognitive function were examined through voxel-wise regression analyses and correlation tests, respectively. Finally, structural correlates of episodic memory were explored across the whole brain at the voxel level within the Down syndrome group. Results revealed a neuroanatomic phenotype with both regional increases and decreases in grey matter volume compared to controls (false discovery rate, q ≤ 0.05). Based on regression analysis, we found the following patterns in regions that were differentially reduced in Down syndrome: same intercept and different age-related slope (defining specific age-related differences), different intercept (implying initial neurodevelopmental differences) and same slope (signalling no age-related differences). A notable example of the first was the left hippocampus and its subfields, and of the second was the orbitofrontal cortex. Follow-up whole brain analyses confirmed age-related changes in Down syndrome (false discovery rate, q ≤ 0.05) in the parietal and temporal cortices, extending into hippocampus, as compared to controls, independent of neurodevelopmental (non-age related) features, and most pronounced in the right hemisphere. Episodic and associative memory declined significantly with age (P = 0.016) in Down syndrome and correlated with shrinkage in regions vulnerable to Alzheimer's disease (P < 0.01), including the precuneus and posterior cingulate cortex. Our findings suggest that individuals with Down syndrome undergo early brain atrophy that occurs independently of baseline neurodevelopmental changes, particularly in the hippocampus and temporoparietal regions. Notably the posterior cingulate cortex and precuneus showed an association with episodic memory loss, a pattern that is consistent with Alzheimer's Disease. In sum we found a dichotomic distinction between brain regions affected by developmental or ageing changes in Down syndrome.
This study aims to systematically analyse developmental regularities of brain glucose metabolism in children covering the whole paediatric age range and establish age-specific paediatric 2-[18F]fluoro-2-deoxy-D-glucose PET brain templates, thereby improving the accuracy of neuroimaging lesion localization in paediatric populations. A retrospective study was conducted, including a pseudo-control group and an epilepsy group. The pseudo-control group data were used to analyse the cerebral glucose metabolism and establish age-specific paediatric statistical parametric mapping templates. Semi-quantitative parameters (mean standardized uptake value, maximum standardized uptake value) were calculated for each region, and standardized uptake ratio was compared across different reference regions. Age-related trends of these metabolic parameters were analysed to derive paediatric cerebral metabolic developmental patterns. 2-[18F]fluoro-2-deoxy-D-glucose PET images of patients with epilepsy were performed using both the established paediatric template and the standard adult template. Taking surgical resection and electrocorticography results as the gold standard, the accuracy of epileptogenic zone localization by the two templates was compared. The mean standardized uptake value and maximum standardized uptake value in the pseudo-control group showed a significant positive correlation with age, with no significant differences between sex or hemispheres (P > 0.05). In the internal and external validation cohorts, the diagnostic accuracy of the paediatric statistical parametric mapping template for epileptogenic zone localization was 79.0%, which was significantly higher than 72.5% of the adult template (P = 0.033). Stratified analysis showed that the paediatric template had consistent advantages across sex and superior performance in epileptogenic zone localization of frontal and temporal lobes. The advantage of the paediatric template was consistent in both internal and external validation cohorts. The age-specific paediatric statistical parametric mapping template has superior overall diagnostic efficacy in epileptogenic zone localization of paediatric drug-resistant epilepsy, with stable advantages across sex and unique value in specific brain regions. It can overcome the limitations of adult templates in adapting to paediatric brain development characteristics, providing a more accurate and reliable tool for preoperative epileptogenic zone localization in paediatric drug-resistant epilepsy.
Blast traumatic brain injury results in chronic pathology, especially for those receiving repetitive injuries. To evaluate cellular changes induced by these pressure waves, we studied post-mortem prefrontal cortex of military personnel with a history of multiple blast exposures and military controls with no battlefield experience. Chronic increases in IBA1 (microglia) and GFAP (glial fibrillary acidic protein; astrocyte) immunoreactivity occurred in injured brains and also confirmed that GFAP-expressing astrocytes altered predominantly at interface regions of the brain: around blood vessels, the grey-white matter interface and in layer 1, consistent with the pattern of damage seen with blast exposure. We focused on pathologic implications of the astrocyte derived proteins GFAP, aquaporin-4, and connexin-43. Astrocyte morphology in injured samples altered significantly, revealing a disintegrated, beaded shape, with a loss of fine processes. We also observed a shift in astrocyte immunoreactivity, where control brains showed two dominant populations, labelling as either GFAP+ or aquaporin-4+ only, with a smaller portion of co-labelled cells. Samples from injured brains revealed the emergence of a third dominant population of cells with abnormal morphology co-labelled with GFAP and aquaporin-4; significant increases in astrocytes with abnormal morphology also occurred, including those both GFAP+ and aquaporin-4+. Connexin-43, which helps maintain neural homeostasis, significantly co-labelled with aquaporin-4, and not GFAP, in both control and injured brains, suggesting the aquaporin-4 subtype to be homeostatic. Interlaminar astrocytes consistently showed abnormal morphology in injured brains, featuring extensive GFAP+ beaded processes. The GFAP+ beaded processes showed additional characteristics in the injured brains, being surrounded in a ring-like fashion by aquaporin-4 immunoreactivity as well as co-labelling with phosphorylated connexin-43, indicating an inflammatory phenotype. To investigate secondary pathology that might relate to immune dysfunction, immunoreactivity with IgG revealed the presence of autoantibody in injury samples, which primarily labelled neurons in layer 2-3 that also co-immunoreacted with complement C3. Half of the interlaminar astrocytes in the injured brains also showed immunoreactivity with C3. We conclude that control human cerebral cortex contains at least two distinct populations that express either GFAP or aquaporin-4, but not both. After military related blast traumatic brain injury, a third population of astrocytes emerges expressing both GFAP and aquaporin-4. Connexin-43 continues to be co-expressed with aquaporin-4, but shifts toward an abnormal morphology. We also find overall chronic alterations in expression of astrocytic proteins that coincide with induction of autoantibodies directed towards neurons and recruit complement.
Dementia is a syndrome caused by various diseases including Alzheimer's disease (AD) and frontotemporal dementia (FTD) with an estimated global prevalence of 60 million individuals. Recently, therapeutic development in the dementia field has accelerated, with the introduction of monoclonal antibody therapeutics such as Lecanemab and Donanemab. However, AD and FTD patients are still either diagnosed too late to benefit from available therapies or are misdiagnosed due to the clinical overlap between dementia subgroups making therapeutic intervention challenging. This highlights a real need to improve early diagnostic tools of neurodegenerative disease (ND) biomarkers. A potential source of such biomarkers come from small extracellular vesicles (sEVs), groups of cell-derived, lipid-bound assemblies with the capability to cross the blood-brain barrier (BBB) and known to carry pathogenic proteins associated with AD and FTD. A known cargo of sEVs is microRNA (miRNA), regulatory molecules that post-transcriptionally silence gene expression including transcripts of autophagic systems, processes which dysfunction in dementia-causing diseases leading to toxic aggregate build-up, causing neurodegeneration. The targeting of functional machineries in macroautophagy (MA) and chaperone-mediated autophagy (CMA) by different miRNA may vary between AD and FTD mutations, leading to potential biomarkers of disease being highlighted. Through isolating sEVs from the frontal cortex of post-mortem brain tissue of AD, FTD-MAPT, FTD-C9orf72, FTD-GRN and no-disease control patients (Manchester Brain Bank), miRNA cargoes were analysed and compared using real-time quantitative PCR (RT-qPCR). Seven autophagy-associated miRNA candidates (MA: miR-124-3p, miR-30a-5p, miR-128-3p; and CMA: miR-224-5p, miR-373-5p, miR-106a-3p and miR-26b-5p) were tested to identify dementia sub-group variations, used alongside small RNA-sequencing to explore broader miRNA variation within sEV populations. Of the miRNA tested miR-224-5p (P = 1.76 × 10-5) and miR-106a-3p (P = 0.033) showed significant group differences, and further significant pairwise comparison differences [miR-224-5p: AD fold change (FC) = 4.29, MAPT FC = 7.62; miR-106a-5p: AD FC = 5.59] when compared with no disease controls and other dementia subgroups, potentially showing initial diagnostic and differentiating potential. Small RNA-sequencing results revealed 8 AD, 2 FTD-GRN, 52 FTD-MAPT and 12 FTD-C9orf72 differentially expressed sEV-miRNAs when compared with no disease controls. Further direct comparisons between AD versus FTD mutation-derived sEV cargoes, and even FTD mutation versus FTD mutation-derived sEV cargoes, identified additional miRNA with differentiating capabilities. These findings demonstrate sEV-derived miRNA signatures vary across dementia sub-types and suggest potential roles of sEV cargoes in both disease diagnostics and identifying drivers of ND, such as autophagic impairments and signalling pathways.
β-catenin-coding gene CTNNB1 is a top-ranking risk gene for autism and intellectual disability. To better understand how CTNNB1 haploinsufficiency is involved in the pathophysiology of neurodevelopmental disorders, we generated a new mouse model that enables Ctnnb1 deletion in forebrain excitatory neurons starting at embryonic corticogenesis. Behavioural assays of the Ctnnb1 conditional knockout (cKO) mice revealed significant fear memory deficits, despite normal social preference, anxiety, spatial and recognition memory. Pyramidal neurons in prefrontal cortex (PFC) of Ctnnb1 cKO mice exhibited the significantly elevated intrinsic excitability but markedly decreased AMPA receptor-mediated synaptic response, while GABAA or NMDA receptor-mediated synaptic response was unchanged. Gene profiling revealed the significantly reduced mRNA level of Syp (encoding Synaptophysin) and Nlng2 (encoding Neuroligin-2) in PFC of Ctnnb1 cKO mice, while most of other screened genes were unchanged. These results suggest that β-catenin deficiency in forebrain excitatory neurons leads to fear conditioning impairment, which could be contributed by the diminished excitatory synaptic transmission in PFC resulting from disrupted synaptic gene expression.
Colony-stimulating factor 1 receptor-related adult-onset leukoencephalopathy with axonal spheroids and pigmented glia (CSF1R-ALSP) is a rare, fatal, autosomal-dominant neurodegenerative disorder caused by pathogenic CSF1R variants and characterized by progressive cognitive, neuropsychiatric, and motor dysfunction, white matter lesions on brain imaging, and white matter demyelination, swollen axons, and pigmented glial cells on pathology. Limited data regarding clinical, biofluid or radiological biomarkers of disease severity are available, and no clinical trial endpoints have yet been validated. The objectives of this first-of-its-kind, prospective, observational natural history study were to characterize the clinical trajectory of CSF1R-ALSP and to identify and evaluate key biomarkers and clinical endpoints indicative of disease severity and progression. ILLUMINATE (NCT05020743) was a multicentre, noninterventional natural history study of adults with CSF1R-ALSP and prodromal carriers of CSF1R variants. Participants were followed for up to 36 months, with clinical assessments, fluid biomarkers and volumetric MRI assessments of brain atrophy collected at screening and every 6 months. This study was terminated early (4 June 2025). The analyses reported here include data collected through 19 February 2025. Of 53 participants, 19 were prodromal and 34 were symptomatic (11 of whom had a history of haematopoietic stem cell transplant and 23 who did not). Mean participant age was 47.8 (standard deviation, 4.5) years, and 36.4% were female. Prodromal participants remained relatively stable over 36 months, with little change in neurological function, neurodegeneration biomarkers or radiological disease burden. Impaired neurological function, MRI characteristics of CSF1R-ALSP, and elevated NfL (neurofilament light chain; neurodegeneration biomarker) and GFAP (glial fibrillary acidic protein; astrogliosis biomarker) levels were more pronounced at baseline and often showed progression over time among symptomatic participants who had not previously received haematopoietic stem cell transplant compared with participants who had previously received haematopoietic stem cell transplant. Significant correlations were observed at baseline and longitudinally between MRI measures of brain atrophy and clinical outcome measures. Based on the fluid biomarkers, MRI measures, and clinical outcome assessments evaluated here, active neurodegeneration, widespread changes visualized on brain MRI, and impaired cognitive and motor function were observed in symptomatic patients with CSF1R-ALSP. The neurological impairment can be assessed using the Montreal Cognitive Assessment and Cortical Basal ganglia Functional Scale. Our data suggest that quantification of brain atrophy using MRI volumetry is a potential biomarker of disease severity and progression in CSF1R-ALSP. It is hoped that this report will contribute to the understanding of disease progression in CSF1R-ALSP and inform future drug development.
The exact mechanisms underlying myoclonus-dystonia (M-D) remain unknown, although the basal ganglia-thalamo-cortical (BGTC) and cerebello-thalamo-cortical (CTC) networks are hypothesized to be involved. We aimed to investigate the static and dynamic features of networks related to motor control during rest in M-D patients using functional magnetic resonance imaging (fMRI). Resting-state fMRI data from 19 M-D patients and 19 healthy volunteers were analysed. Symptom severity was measured using the Clinical Global Impression-Severity Scale, anxiety and depression with the Hospital Anxiety and Depression Scale and cognitive impairment with the Montreal Cognitive Assessment. Independent component analysis was used to identify brain components corresponding to the BGTC and CTC networks. Static within-network (i.e. spatial contribution of voxels to the average network signal time course) and between-network (i.e. correlation between network time courses) functional connectivity were examined. We additionally performed a dynamic functional connectivity analysis focused on recurrent connectivity patterns (i.e. brain states) using k-means clustering of windowed functional connectivity correlation matrices, whereby we identified three prototypical dynamic connectivity states in the BGTC and CTC circuits. The following brain state summary measures were computed: fraction of time spent in a state, dwell time, number of state transitions and number of state visits. Static analysis revealed that patients with M-D showed increased functional connectivity (FC) of the left supramarginal gyrus within a cognitive control network (corresponding to the cortical part of BGTC and CTC circuits), suggesting stronger integration of this area in this network (within-network P fdr < 0.05). There were no significant group differences in between-network functional connectivity. Dynamic analysis revealed three dynamic connectivity states in BGTC and CTC circuits. Patients with M-D engaged less in a state characterized by high segregation of sensorimotor from basal ganglia and cerebellar domains, with high connectivity between networks within these domains. This finding may reflect reduced basal ganglia and cerebellar contributions during motor preparation in M-D. We found no relationships between fMRI findings and motor symptom severity in M-D patients. Our findings provide further evidence for disrupted brain network dynamics in BGTC and CTC circuits in M-D patients, supporting the hypothesis of compromised basal ganglia and cerebellar functioning. Particularly, the association of cerebellar and anterior parietal alterations is proposed to reflect impaired sensory prediction in feed-forward motor planning, potentially underlying irregular 'non-prepared movements'.
Physical activity (PA) is a modifiable lifestyle behaviour associated with lower dementia risk; however, molecular pathways bridging PA-related dementia prevention are poorly understood. We leveraged large-scale plasma proteomics to identify biological signatures of objectively monitored PA and cognitive ageing in functionally intact older adults, cross-validated these signatures in independent exercise cohorts and tested associations with both symptomatic and presymptomatic stages of neurodegeneration across multiple Alzheimer's disease and related dementias (ADRD) cohorts. We analysed large-scale plasma proteomics data (SomaScan 7k) across three cohorts including naturalistic, objective PA monitoring (University of California, San Francisco Brain Aging Network for Cognitive Health cohort, n = 65), self-reported PA (Atherosclerosis Risk In Communities study, n = 10 644) and PA intervention (Health Risk Factors, Exercise Training and Genetics study, n = 654). Differential regression models examined individual protein correlates of PA, adjusting for age and sex. Weighted gene co-expression network analysis assembled proteins into unbiased modules of protein co-expression, which were annotated for gene ontology and cell-type enrichment. To test clinical relevance to ADRD, we examined PA-related protein levels across-cohorts of symptomatic Alzheimer's disease and Parkinson's disease (Stanford Alzheimer's Disease Research Center), as well as frontotemporal dementia-spectrum disorders (ARTFL/LEFFTDS Longitudinal Frontotemporal Lobar Degeneration consortium). PA-related plasma proteins were also tested as predictors of antemortem cognitive change and post-mortem brain tissue mass spectrometry proteomic signatures in brain donors from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP) cohort. Differential regression and network analyses identified PA plasma proteomic signatures linked to cell adhesion/extracellular matrix (ECM), immune response and lipid metabolism. Protein co-expression module M12 ECM/neurodevelopment harboured growth factor, cell adhesion and vascular remodelling proteins that (i) were positively associated with PA across exercise cohorts, (ii) positively associated with cognitive function and (iii) negatively associated with Alzheimer's disease, Parkinson's disease and frontotemporal dementia. Furthermore, M12 was enriched for proteins from Alzheimer's disease risk genes and antemortem plasma abundance of anthrax toxin receptor cell adhesion molecule 2 (ANTXR2), an M12 'hub' protein and top PA hit across-cohorts, forecasted longitudinal global cognitive decline and post-mortem brain tissue signatures of synaptic function and proteolysis in ROSMAP. Collectively, our integrated systems biology analysis of six independent plasma proteomic datasets facilitated discovery and validation of blood-detectable molecular signatures of PA and neurodegenerative disease, including PA-related proteins with clinical and biological relevance to early stages of disease. Circulating levels of PA-related proteins reflecting ECM biology (e.g. ANTXR2) may represent key molecular targets for dementia prevention.
Neurons form functional connections in neuronal networks of the brain. Neurotransmission refers to the information flow of electrical signals between neurons, and changes in the information flow strength between neurons characterize the brain functions. An evaluation method for neuronal information flow strength is necessary to elucidate the basic principles of brain function. To analyze the strength of information flow, the identification of information transmission between the time series of electrical spikes in neuronal networks, such as spike trains, is required. In this study, we evaluated the information flow strength in neuronal networks using transfer entropy (TE), an analysis method based on information theory, to elucidate the causal relationships between two spike trains. Cultured rat hippocampal neuronal networks were used as living brain models, and extracellular monitoring of action potentials, expressed as spikes, was performed using microelectrode arrays. Spike trains of spontaneous activity and stimulus-evoked responses were measured in multiple neurons, and the causal relationship between electrode pairs was evaluated as an index of information flow between neurons using TE. From the results of spontaneous activity and evoked responses, it was suggested that the TE values between electrodes increased with culture days and that the information flow strength was enhanced by the network maturation. Furthermore, the correlation between TE values and neuronal population distance was evaluated using TE analysis. We found that neurons that received strong inputs slightly overlapped in their spontaneous activity and evoked responses. These findings suggest that spontaneous activity and evoked responses exhibit similar patterns in neuronal networks. In the graph theoretical analysis based on TE values, the network topology exhibited changes that strengthened the information flow over 70 days in culture. Therefore, TE analysis is an effective tool for estimating the information flow between neurons based on neuronal electrical activity recorded at multiple sites.
Grey matter network topology is altered in Alzheimer's disease and these alterations are related to cognitive decline. Understanding the biological underpinnings of loss of brain connectivity may provide insights into mechanisms related to developing Alzheimer's dementia (i.e. dementia A+). We investigated which biological processes as measured in CSF proteomics were associated with loss of brain connections across the Alzheimer's disease continuum. We included 347 individuals with abnormal CSF amyloid [mean age ± standard deviation (SD) 66 ± 8; 98 cognitively unimpaired-A+, 88 mild cognitive impairment-A+, 161 dementia A+] and 146 cognitively unimpaired individuals with normal CSF amyloid (mean age ± SD 62 ± 8) and available T1w MRI-scans and CSF proteomic data (3097 proteins using tandem mass tag spectrometry) from the Amsterdam Dementia Cohort. We used an automated pipeline to construct grey matter networks from 3D-T1 sequences and for each network, calculated the small-worldness coefficient, which we previously found to be robustly related to cognitive decline. Linear models were applied to test associations between CSF protein levels and connectivity measures using an interaction term for clinical stage while controlling for connectivity density, age and sex. We validated our results in data from the Alzheimer's disease Neuroimaging Initiative (ADNI). Pathway enrichment analysis was performed for proteins associated with loss of brain connectivity (P < 0.05) using the Gene Ontology database. Individuals across the Alzheimer's disease continuum had lower small-worldness coefficients compared with controls (ANOVA P < 0.001). In amyloid positive individuals, higher levels of 222 proteins and lower levels of 482 proteins were associated with lower small-worldness coefficients and were enriched for innate immune system and neuroplasticity pathways, respectively. Stratified for disease stage, most protein associations with lower small-worldness coefficients were found in mild cognitive impairment A+ (n = 527 proteins) and dementia A+ (n = 799 proteins) with considerable overlap (n = 239 proteins). Proteins in these stages were enriched for complement activation and synaptic integrity. In cognitive unimpairment A+, we found proteins enriched for processes involved in apoptosis. We did not find any enriched biological processes in controls. Repeating analyses in ADNI indicated that similar biological processes were associated with altered grey matter network connectivity. Higher CSF levels of proteins involved in immune responses and lower levels of proteins related to neuroplasticity were associated with lower small-worldness coefficients across the Alzheimer's disease continuum. This suggests that preserving cognitive function in the presence of amyloid and prevention of dementia A+ may require therapies that strengthen synapses and targets the innate immune system in addition to amyloid and tau.
Clinical trajectories in patients with functional neurological disorder (FND) are variable, and the neural mechanisms underlying this heterogeneity remain poorly understood. This longitudinal brain imaging study examined resting-state functional connectivity predictors and mechanisms of symptom change in FND. Thirty-two adults with FND (motor and/or seizure phenotypes) completed baseline questionnaires and functional MRI (fMRI), followed by naturalistic treatment for 6.8 ± 0.8 months. All participants completed follow-up questionnaires; 28 completed follow-up fMRI. At each timepoint, three graph-theory network metrics of resting-state functional connectivity were computed: whole-brain weighted-degree (centrality), cortical integration (between-network connectivity), and cortical segregation (within-network connectivity). All analyses adjusted for age, sex, antidepressants, head motion, time between sessions and baseline score of interest, with cluster-wise correction. Results were contextualized against 50 age-, sex-, and head motion-matched healthy controls (HCs). Based on patient-reported Clinical Global Impression of Improvement ratings, 59.4% improved, 31.3% were unchanged, and 9.3% worsened. Core FND symptom (i.e. Screening for Somatoform Symptoms-7 Subscale for Conversion Disorder) and non-core physical symptom (Patient Health Questionnaire-15) scores showed variable trajectories, with no group-level changes. For whole-brain weighted-degree analyses, baseline centrality in right middle frontal, precentral, and left cerebellar regions was positively associated with core FND symptom change; longitudinally, centrality decreases in right precentral, superior parietal, lateral occipital, and cerebellar regions were associated with symptom improvement. For cortical integration analyses, baseline between-network connectivity in ventral attention, frontoparietal, and default mode network regions was positively associated with core FND symptom change; longitudinally, decreases in between-network connectivity for regions of these same networks were associated with symptom improvement. For cortical segregation analyses, baseline within-network connectivity in frontoparietal network regions was positively associated with core FND symptom change; no regions showed longitudinal segregation changes associated with symptom change. The right anterior insula emerged as a convergent site across baseline and longitudinal integration analyses, with the most improved participants showing elevated baseline between-network connectivity relative to HCs that normalized at follow-up. More modest functional connectivity associations were observed with non-core physical symptom change, spanning baseline within-network connectivity in dorsal attention network regions and longitudinal between-network connectivity increases in visual network regions. Findings remained significant adjusting for FND phenotype, although several attenuated when accounting for baseline affective symptoms or trauma burden. In conclusion, this study identified baseline and longitudinal resting-state functional connectivity features linked to symptom change in FND, highlighting the potential of large-scale network interactions as prognostic markers and providing mechanistic insights that set the stage for novel, biologically informed interventions.
Background/Objectives: In emergency settings, it is often infeasible to place patients in an anatomical position for CT scanning. Consequently, emergency brain CT scans of patients with traumatic brain injury frequently demonstrate considerable anatomical misalignment. These inconsistencies compromise the performance of deep learning-based 3D hematoma segmentation. This study aims to enhance segmentation robustness by proposing a registration-based data augmentation strategy utilizing anatomical landmarks. Methods: We propose a framework termed cross-subject registration-based augmentation (CSRA), which uses anatomical landmarks to rigidly register patient CT volumes to selected reference CT volumes and generate anatomically aligned CT-label pairs for training. Results: A total of 339 patients who underwent brain CT imaging were enrolled from a Level 1 trauma center. CSRA-3s achieved the highest mean Dice and IoU and the lowest mean HD95 among the evaluated augmentation strategies. Patient-level paired analysis showed that the most robust statistically supported benefit was a significant reduction in HD95 compared with a conventional geometric augmentation baseline, indicating improved boundary agreement. Conclusions: The proposed augmentation strategy mitigated the effect of anatomic position discrepancies on segmentation performance, particularly in terms of boundary agreement, without modifying existing model architectures. CSRA may serve as a model-agnostic training-time augmentation strategy for improving segmentation robustness in anatomically inconsistent emergency CT imaging, although multicenter external validation is required before clinical deployment.
Amyotrophic lateral sclerosis (ALS) is a complex neurodegenerative disease characterized predominantly by degeneration of both upper and lower motor neurons, thought to occur due to an interplay between genetics and environmental factors. Physical activity has been suggested as a potential risk factor for ALS; however, the exact role of exercise in the onset and progression of the disease is still unclear. We assessed lifetime physical activity in two independent ALS cohorts: post-mortem brain donors from the London Neurodegenerative Diseases Brain Bank (n = 139) and patients from the Motor Neurone Disease (MND) Register of England, Wales and Northern Ireland (n = 166 cases, 196 controls). In both cohorts, highly active individuals developed ALS symptoms at a significantly younger age, 54.2 years (mean, standard deviation = 7.5) in the post-mortem cohort and 58.0 years (median, interquartile range = 15) in the MND Register, compared with 63.9 years (mean, standard deviation = 11.5) and 63.0 years (median, interquartile range = 17.5) in inactive individuals, respectively [one-way analysis of variance (ANOVA), F(2, 136) = 6.10, P = 0.003, η 2 = 0.08, 95% confidence interval (CI) 0.02-1.00 and Kruskal-Wallis, H(2) = 7.39, P = 0.02, η 2 = 0.03, 95% CI 0.003-0.12]. Cox regression showed a higher hazard of earlier onset in highly active patients [post-mortem: hazard ratio (HR) 2.84, 95% CI 1.55-5.26, P = 0.0008; MND Register: HR 2.34, 95% CI 1.30-4.23, P = 0.005]. Our findings suggest that strenuous physical activity may be associated with a significantly younger age of ALS onset, replicated in both the post-mortem and MND Register cohorts, but not with an increased risk of developing ALS. Logistic regression analysis confirmed that neither highly active [odds ratio (OR) 1.43, 95% CI 0.69-2.99, P = 0.333] nor being active (OR 1.30, 95% CI 0.72-2.37, P = 0.386) was significantly associated with ALS risk, whereas a history of head injury was (OR 1.72, 95% CI 1.03-2.88, P = 0.038). These results suggest that strenuous exercise may accelerate disease onset in predisposed individuals, while the role of head injury requires further study and the findings may in fact indicate reverse causality.
Radiofrequencies (electromagnetic fields from 100kHz to 300GHz) are used for communications, such as mobile phones, radio and television broadcasting, and some other applications such as diathermy. Possible health effects have been studied extensively, especially whether the use of mobile phones increases the risk of brain cancer. The World Health Organization (WHO) has sponsored 13 extensive reviews of the scientific studies on health effects. For human epidemiological and some experimental studies on volunteers, the studies found no increased risk for most effects, with up to moderate confidence (the highest category for observational studies). Some results showed effects on cognitive performance and reduced sperm vitality, but with very low confidence. For animal studies, increases in glioma and heart schwannoma in male rats were reported with high confidence. Increases in some other cancers, and reductions in foetal weight, pregnancy rate and sperm count, were found with moderate or low confidence. The relevance of the animal studies to humans is a key issue. These reviews will be used by the WHO in risk assessment and setting guidelines for exposure and good practice.
Microglia play a key role in the pathophysiology of Alzheimer's Disease (AD) and their increased heterogeneity likely affects disease progression. We previously identified distinct microglial signatures that were enriched in AD donors and associated with amyloid and tau, respectively. Here we generated a snRNAseq dataset from postmortem control and AD cases and analyzed alterations in cell-cell communication pathways that might be relevant to AD pathophysiology. One signaling pathway perturbed in AD cases involved SPP1, and while this pathway was also present in control samples, microglia-microglia SPP1 signaling was restricted to AD donors. Further analyses within microglia-microglia signaling predict AD-specific induction of GAS6-AXL signaling (from inflammatory and ribosomal microglia), and SPP1-ITGAV/ITGB5 signaling (from disease-associated and inflammatory microglia, among others). Together, these findings might in part explain the increased microglia phagocytic profile described in AD. RNAscope confirmed enrichment of SPP1 expressing microglia near amyloid plaques in AD brain tissue samples. These data indicate altered cellular communications between microglia in the AD brain.
Cell and tissue functions arise from complex interactions among numerous genes, and a systematic understanding of these functions requires isoform-resolved transcriptomic analysis of single cells with high spatial resolution. Here, we introduce an in situ RNA amplification method and its integration with multiplexed error-robust fluorescence in situ hybridization (MERFISH) to detect short RNA sequences and enable whole-transcriptome-scale, isoform-resolved spatial transcriptomics of individual cells in intact tissues. Using this approach, we imaged ∼33,000 distinct RNAs-including ∼23,000 genes and ∼10,000 isoforms-in the mouse brain. Our data enabled systematic analyses of region- and cell-type-specific gene programs and ligand-receptor-based cell-cell communications. These data further revealed rich spatial diversity and cell-type specificity in isoform usage across numerous genes, as well as brain structures particularly rich in isoform specificity. We anticipate broad application of this method for characterizing the molecular and cellular basis of tissue functions, unlocking previously inaccessible discoveries in cell and organismal biology.