Most recent paper

Sci Rep. 2024 Nov 26;14(1):29294. doi: 10.1038/s41598-024-80901-5.

ABSTRACT

The CO2 challenge model (CCM) is a gas inhalation paradigm that provides precisely controlled anxiety induction in experimental settings. Despite its potential as an experimental model of anxiety, our understanding of the neural effects of the CCM is incomplete. This study employs resting-state functional magnetic resonance imaging (rs-fMRI) to explore functional connectivity (FC) changes underlying the CCM. Following a preliminary CO2 tolerance assessment, participants completed an MRI session that included three rs-fMRI scans: during inhalation of control air (pre and post), and during a 6% CCM exposure. Here, we confirm that 6% CCM is a tolerable anxiogenic model in the MRI setting. We demonstrate that a transient CCM-induced increase in subjective anxiety is associated with an increase in FC within limbic and anxiety-related regions, with the insula emerging as a central node in this altered connectivity pattern. Further analysis revealed a significant correlation between the levels of subjective anxiety and enhanced FC between the brainstem and medial frontal cortex, highlighting the dynamic role of the brainstem in response to CO2-induced anxiety. These findings underscore the value of combining CCM and rs-fMRI to characterise the neural mechanisms of anxiety, with important implications for evaluating potential therapeutic interventions.

PMID:39592811 | DOI:10.1038/s41598-024-80901-5

Nat Commun. 2024 Nov 26;15(1):10251. doi: 10.1038/s41467-024-54657-5.

ABSTRACT

Structural and functional connectomes undergo rapid changes during the third trimester and the first month of postnatal life. Despite progress, our understanding of the developmental trajectories of the connectome in the perinatal period remains incomplete. Brain age prediction uses machine learning to estimate the brain's maturity relative to normative data. The difference between the individual's predicted and chronological age-or brain age gap (BAG)-represents the deviation from these normative trajectories. Here, we assess brain age prediction and BAGs using structural and functional connectomes for infants in the first month of life. We use resting-state fMRI and DTI data from 611 infants (174 preterm; 437 term) from the Developing Human Connectome Project (dHCP) and connectome-based predictive modeling to predict postmenstrual age (PMA). Structural and functional connectomes accurately predict PMA for term and preterm infants. Predicted ages from each modality are correlated. At the network level, nearly all canonical brain networks-even putatively later developing ones-generate accurate PMA prediction. Additionally, BAGs are associated with perinatal exposures and toddler behavioral outcomes. Overall, our results underscore the importance of normative modeling and deviations from these models during the perinatal period.

PMID:39592647 | DOI:10.1038/s41467-024-54657-5

Front Endocrinol (Lausanne). 2024 Nov 11;15:1448225. doi: 10.3389/fendo.2024.1448225. eCollection 2024.

ABSTRACT

BACKGROUND: The mechanisms associated between diabetic peripheral neuropathy (DPN) and various brain function abnormalities in patients remains unclear. This study attempted to indirectly evaluate the effect of DPN on brain function in patients with type 2 diabetes mellitus (T2DM) by characterizing the resting-state functional connectivity (FC) of the lower limb sensorimotor cortex (LSM).

METHODS: Forty-four T2DM patients with diabetic peripheral neuropathy (DPN), 39 T2DM patients without diabetic peripheral neuropathy (ND), and 43 healthy controls (HCs) underwent a neuropsychological assessment and resting-state functional magnetic resonance imaging examinations to examine the differences in FC between the LSM and the whole brain. The relationships of FC with clinical/cognitive variables were examined.

RESULTS: In comparison with the HCs group, the ND group showed reduced FC of the LSM with the right lateral occipitotemporal cortex (LOTC) and increased FC with the medial superior frontal gyrus (SFGmed), while the DPN group showed reduced FC of the LSM with the right cerebellar lobule VI, the right LOTC, the rostral prefrontal cortex (rPFC), and the anterior cingulate gyrus (ACC). Moreover, in comparison with the ND group, the DPN group showed reduced FC of the LSM with the ACC, SFGmed, and rPFC. In the DPN group, the FC between the LSM and right cerebellar lobule VI was significantly correlated with fasting blood glucose levels (r = -0.490, p = 0.001), and that between the LSM and ACC was significantly correlated with the Montreal Cognitive Assessment score (r = 0.479, p = 0.001).

CONCLUSIONS: Patients with T2DM may show abnormal motion-related visual perceptual function before the appearance of DPN. Importantly, DPN can influence the brain regions that maintain motion and motor control, and this effect is not limited to motor function, which may be the central neuropathological basis for diabetic peripheral neuropathy.

PMID:39588336 | PMC:PMC11586158 | DOI:10.3389/fendo.2024.1448225

Brain Topogr. 2024 Nov 25;38(1):17. doi: 10.1007/s10548-024-01087-7.

ABSTRACT

OBJECTIVES: To observe the functional differences in the key brain areas in patients with different levels of consciousness after severe brain injury, and provide reference for confirming the objective diagnosis indicators for prolonged disorders of consciousness (pDoCs).

METHODS: This prospective study enrolled patients with pDoCs hospitalized in the department of rehabilitation medicine of our Hospital. Levels of consciousness and clinical outcomes were assessed according to diagnostic criteria and behavioral scales. Resting-state functional magnetic resonance imaging (rs-fMRI) and diffusion tensor imaging (DTI) of 30 patients with different levels of consciousness was performed. The patients were grouped as conscious or unconscious according to whether they regained consciousness during the 12-month follow-up.

RESULTS: Thirty patients were enrolled, including eight with unresponsive wakefulness syndrome/vegetative state, eight with minimally conscious state, six with emergence from the minimally conscious state, and eight with a locked-in syndrome. There were 19 and 11 patients in the conscious and unconscious groups. Compared with the unconscious group, the left basal nucleus was activated in the conscious group, and there were significant differences in white matter fiber bundles. Correlations were observed between the regional homogeneity (ReHo) value of the cerebellum and the Glasgow coma scale score (r = 0.387, P = 0.038) and between the ReHo value of the left temporal and the coma recovery scale-revised score (r = 0.394, P = 0.035).

CONCLUSIONS: The left insula and cerebellum might be important for regaining consciousness. The brain function activity and structural remodeling of the key brain regions and the activation level of the cerebellum are correlated with clinical behaviors and have potential application value for the prognosis prediction of pDoCs patients.

PMID:39585449 | DOI:10.1007/s10548-024-01087-7

PeerJ. 2024 Nov 21;12:e18540. doi: 10.7717/peerj.18540. eCollection 2024.

ABSTRACT

OBJECTIVE: The present study aimed to investigate the functional connectivity (FC) of the anterior and posterior hypothalamus with the whole brain in insomnia disorder (ID) patients. Additionally, we explored the relationship between FC values and serum levels of arousal-promoting neurotransmitters (orexin-A and histamine) in ID patients.

METHODS: This study enrolled 30 ID patients and 30 age- and gender-matched healthy controls. Resting-state functional magnetic resonance imaging (RS-fMRI) was employed to assess the FC of the anterior and posterior hypothalamus with the whole brain. Serum concentrations of orexin-A and histamine were measured using enzyme-linked immunosorbent assay (ELISA). Moreover, Spearman correlation analysis was conducted to investigate the relationship between FC values and serum levels of arousal-promoting neurotransmitters in ID patients.

RESULTS: Our findings showed decreased FC between the posterior hypothalamus and several brain regions including the bilateral orbital superior frontal gyrus, the bilateral angular gyrus, the right anterior cingulate cortex, the left precuneus, and the right medial superior frontal gyrus in ID patients. Additionally, decreased FC was observed between the anterior hypothalamus and the right anterior cingulate cortex among ID patients. Compared to the healthy controls, ID patients showed significantly elevated serum concentrations of orexin-A and histamine. Furthermore, we identified a positive correlation between the FC of the right medial superior frontal gyrus with posterior hypothalamus and histamine levels in ID patients.

CONCLUSION: ID patients exhibited aberrant FC in brain regions related to sleep-wake regulation, particularly involving the default mode network and anterior cingulate cortex, which may correlate with the peripheral levels of histamine. These findings contribute to our understanding of the potential neuroimaging and neurohumoral mechanism underlying ID patients.

PMID:39583108 | PMC:PMC11586044 | DOI:10.7717/peerj.18540

J Multidiscip Healthc. 2024 Nov 20;17:5425-5434. doi: 10.2147/JMDH.S490162. eCollection 2024.

ABSTRACT

BACKGROUND: Resting-state functional magnetic resonance imaging (rs-fMRI) is a noninvasive way to evaluate brain physiological activity by detecting blood oxygen level fluctuations. Diminished ovarian reserve (DOR) indicates ovarian aging. Before 40, patients may have menstrual abnormalities, poor reproduction, and poor assisted reproductive results. Without treatment, it can cause early ovarian failure. Studies have shown that acupuncture can ameliorate sex hormones and antral follicle count (AFC) in DOR patients.

OBJECTIVE: Despite limited studies on its mechanism, acupuncture have been shown to treat DOR. There is no relevant research on brain functional magnetic resonance and brain functional connectivity of acupuncture in treating DOR. We design this clinical trial to preliminarily elucidate the neuroimaging method of controlling the brain functional network and acupuncture impact in DOR patients using rs-fMRI.

METHODS: This study will involve 30 DOR patients and 30 healthy individuals. DOR patients will have rs-fMRI before and after 3 menstrual cycles of acupuncture, whereas healthy individuals will need one rs-fMRI scan. The primary end measures will be follicle-stimulating hormone (FSH) and AFC. In contrast, the secondary outcomes will be luteinizing hormone(LH), estradiol (E2), anti-Müllerian hormone (AMH), modified Kupperman scale, self-rating anxiety scale (SAS), self-rating depression scale (SDS), and rs-fMRI alterations.

RESULTS: This study uses rs-fMRI technology to identify the brain regions that differ between DOR patients and healthy people before and after acupuncture treatment. This study will connect brain regions, examine the effects of acupuncture on menstruation and pregnancy on DOR patients' brain function networks, and discuss neuroimaging methods.

CONCLUSION: Acupuncture may have the potential to regulate menstruation and increase the chances of pregnancy promotion in patients with DOR.

PMID:39582877 | PMC:PMC11586002 | DOI:10.2147/JMDH.S490162

Cereb Cortex. 2024 Oct 3;34(10):bhae426. doi: 10.1093/cercor/bhae426.

ABSTRACT

Preterm birth causes alterations in structural and functional cerebral development that are not fully understood. Here, we investigate whether basic characteristics of BOLD signal itself might differ across preterm, term equivalent, and term infants. Anatomical, fMRI, and diffusion weighted imaging data from 716 neonates born at 23-43 weeks gestational age were obtained from the Developing Human Connectome Project. Hurst exponent (H; a measure of temporal complexity of a time-series) was computed from the power spectral density of the BOLD signal within 13 resting state networks. Using linear mixed effects models to account for scan age and birth age, we found that H increased with age, that earlier birth age contributed to lower H values, and that H increased most in motor and sensory networks. We then tested for a relationship between temporal complexity and structural development using H and DTI-based estimates of myelination and found moderate but significant correlations. These findings suggest that the temporal complexity of BOLD signal in neonates relates to age and tracks with known developmental trajectories in the brain. Elucidating how these signal-based differences might relate to maturing hemodynamics in the preterm brain could yield new information about neurophysiological vulnerabilities during this crucial developmental period.

PMID:39582376 | DOI:10.1093/cercor/bhae426

J Affect Disord. 2024 Nov 22:S0165-0327(24)01953-0. doi: 10.1016/j.jad.2024.11.068. Online ahead of print.

ABSTRACT

The perimenopausal transition is marked by an increased risk for affective dysregulation and major depressive disorder (MDD), with hormone replacement therapy using estradiol (E2) showing promise for alleviating symptoms of perimenopausal-onset MDD (PO-MDD). Although E2's effectiveness is recognized, its mechanisms underlying mood symptom modulation remain to be fully elucidated. Building on previous research suggesting that E2 may influence mood by altering cortico-subcortical connectivity, this study investigated the effects of transdermal E2 on resting-state functional connectivity (rsFC) in perimenopausal women with and without PO-MDD, focusing on rsFC changes using seed regions within reward and emotion processing networks. In this pharmaco-fMRI study, 16 participants with PO-MDD and 18 controls underwent rsFC analysis before and after three weeks of transdermal E2 administration. Pre-E2 results showed that the PO-MDD group, compared to controls, exhibited increased connectivity between the right amygdala (seed) and medial prefrontal cortex and anterior cingulate cortex, and decreased connectivity with the supplementary motor area. Comparing groups on change from pre-E2 to post-E2 revealed several significant E2-induced changes in connectivity between the PO-MDD and control groups: PO-MDD showed increased connectivity between the right caudate nucleus (seed) and left insula, and decreased connectivity between the right putamen (seed) and left hippocampus, and the right amygdala (seed) and left ventromedial prefrontal cortex. Notably, changes in connectivity were predictive of symptom trajectories across anhedonia, depressive mood, somatic, and vasomotor domains in the PO-MDD group. These findings enrich our understanding of PO-MDD by highlighting distinct rsFC patterns characteristic of the disorder and their shifts in response to E2 treatment, suggesting potential neural mechanisms underlying E2's mood-modulating effects.

PMID:39581384 | DOI:10.1016/j.jad.2024.11.068

Behav Brain Res. 2024 Nov 22:115355. doi: 10.1016/j.bbr.2024.115355. Online ahead of print.

ABSTRACT

Gelotophobia, the fear of being laughed at, is characterized by heightened sensitivity to ridicule and a tendency to perceive laughter in social situations as mocking. Resting-state functional magnetic resonance imaging (rs-fMRI) acquires brain functional connectivity while the individual remains at rest, without engaging in specific tasks. Recent studies have investigated task-based fMRI and white matter in gelotophobes; however, the resting-state functional connectivity (rsFC) in this group remains unclear. This study aimed to examine differences in rsFC between gelotophobes and non-gelotophobes, to provide insights into the neural networks underlying gelotophobia. Using a seed-based correlation approach, the present study analyzed rsFC in three key networks: the limbic system, default mode network (DMN), and executive control network (ECN). Compared to non-gelotophobes, gelotophobes exhibited significantly stronger amygdala-putamen connectivity within the limbic system, suggesting heightened sensitivity to social cues and altered processing of fear. Within the DMN, gelotophobes demonstrated stronger precuneus-temporoparietal junction (TPJ) and posterior cingulate cortex-TPJ functional connectivity, implying increased self-awareness and vigilance toward social evaluation. In the ECN, enhanced connectivity between the superior frontal gyrus and supplementary motor area in gelotophobes may reflect heightened attention to social cues. Notably, while individuals with gelotophobia exhibited greater amygdala-putamen functional connectivity, controls showed stronger amygdala-supplementary motor area connectivity. These distinct connectivity patterns across the limbic system, DMN, and ECN provide new insights into the neural basis of gelotophobia and its associated heightened sensitivity to social evaluation.

PMID:39581269 | DOI:10.1016/j.bbr.2024.115355

Neuroscience. 2024 Nov 21:S0306-4522(24)00634-1. doi: 10.1016/j.neuroscience.2024.11.046. Online ahead of print.

ABSTRACT

Chronic insomnia (CI) is a common sleep disorder in middle-aged and elderly individuals. Long-term sleep deprivation can lead to physical, mental, and cognitive damage. Resting-state networks (RSNs) in the brain are closely linked to cognition and behavior. Therefore, we investigated changes in RSNs to explore behavioral and cognitive abnormalities in middle-aged and elderly CI patients. Resting state functional magnetic resonance imaging (rs-fMRI) and independent component analysis were used to study the intrinsic functional connectivity (FC) of the RSNs in 36 CI patients (20 CI with cognitive impairment (CI-I) patients and 16 CI without cognitive impairment (CI-N) patients) and 20 healthy controls (HC). Two-sample t-tests were used to compare RSNs differences between CI and HC groups and the RSNs differences between CI-I and CI-N groups. Partial correlation analysis was used to explore the relationship between the significant abnormal brain regions in RSN and clinical scales. Compared with HCs, CI patients showed significant differences in multiple RSNs, and FC values in two brain regions within RSNs were correlated with clinical scales. Furthermore, compared with CI-N group, CI-I group also showed significantly altered FC in multiple RSNs. Moreover, FC values in the right middle frontal gyrus within right frontal parietal network of CI-I patients were negatively correlated with the Mini-Mental State Examination scores. These results may explain hyperarousal, decreased attention and motor function impairments in CI patients. Furthermore, the aberrant alterations of RSNs in CI-I patients may play a crucial role in the onset and progression of cognitive impairment in CI patients.

PMID:39579856 | DOI:10.1016/j.neuroscience.2024.11.046

J Pain. 2024 Nov 20:104740. doi: 10.1016/j.jpain.2024.104740. Online ahead of print.

ABSTRACT

Chronic pain is a debilitating condition associated with brain alterations. However, the variability in neuroimaging results across modalities necessitates a comprehensive multi-modal meta-analysis for a cohesive understanding. This study aims to elucidate brain alterations in chronic pain patients using a multi-modal meta-analysis approach encompassing structural, resting-state functional connectivity, and pain processing paradigms in functional magnetic resonance imaging. A systematic literature search was conducted across PubMed, OVID Embase, OVID Medline, and Web of Science, encompassing studies published up to May 30th, 2022, to identify relevant research articles on chronic pain and MRI techniques in three modalities. Inclusion criteria encompassed experiments reporting three modality brain alterations in chronic pain patients, with sufficient statistical thresholds and enough sample size. We conducted voxel-wise meta-analyses using seed-based d mapping to identify significant alterations in each modality. Additionally, conjunction analyses were executed to identify common alterations across these modalities. Ultimately, 47 structure studies, 37 resting state functional connectivity studies, and 41 pain-processing studies were selected for formal analysis. Chronic pain patients displayed notable structural and functional alterations in the insular cortex, characterized by reduced gray matter, disruptions in functional connectivity with the frontoparietal network, and enhanced activation during painful stimuli processing. Distinct activation patterns were observed in the left and right insular cortex for pain stimulus processing versus anticipation. Furthermore, the superior temporal gyrus and superior frontal gyrus exhibited joint alterations across modalities. This multi-modal meta-analysis reveals consistent brain alterations in chronic pain patients, shedding light on the complex interplay between structural and functional changes. PERSPECTIVE: This multi-modal meta-analysis integrates findings from structural, resting-state functional connectivity, and pain processing paradigms in fMRI, revealing consistent brain alterations in chronic pain patients. Notable brain changes highlight the intricate interplay between structural and functional brain changes, advancing our understanding of chronic pain's neural underpinnings.

PMID:39577824 | DOI:10.1016/j.jpain.2024.104740

Neuroscience. 2024 Nov 20:S0306-4522(24)00606-7. doi: 10.1016/j.neuroscience.2024.11.024. Online ahead of print.

ABSTRACT

Patients with Bipolar Disorder type I (BD-I) exhibit maladaptive risky decision-making, which is related to impulsivity, suicide attempts, and aggressive behavior. Currently, there is a lack of effective predictive methods for early intervention in risky behaviors for patients with BD-I. This study aimed to predict risky behavior in patients with BD-I using resting-state functional magnetic resonance imaging (rs-fMRI). We included 48 patients with BD-I and 124 healthy controls (HC) and constructed voxel-wise functional connectivity (FC), dynamic FC (dFC), effective connectivity (EC), and dynamic EC (dEC) for each subject. The Balloon Analogue Risk Task (BART) was employed to measure the risky decision-making of all participants. We applied connectome-based predictive modeling (CPM) with five regression algorithms to predict risky behaviors as well as Barratt Impulsivity Scale (BIS) scores. Results showed that the BD-I had significantly lower risky adjusted pump scores compared to HC. The dEC-based linear regression-CPM model exhibited significant predictive ability for the adjusted pump scores in BD-I, while no significant predictive power was observed in HC. Furthermore, this model successfully predicted non-planning impulsiveness, motor impulsiveness, and BIS total score, but failed for attentional impulsiveness in BD-I. These findings provide a foundation for future work in predicting risky behaviors of psychiatric patients by using voxel-wise dEC underlying resting state.

PMID:39577688 | DOI:10.1016/j.neuroscience.2024.11.024

Hum Brain Mapp. 2024 Dec 1;45(17):e70064. doi: 10.1002/hbm.70064.

ABSTRACT

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.

PMID:39575904 | PMC:PMC11583081 | DOI:10.1002/hbm.70064

Soc Cogn Affect Neurosci. 2024 Nov 22:nsae077. doi: 10.1093/scan/nsae077. Online ahead of print.

ABSTRACT

Emotion regulation flexibility (ERF) refers to one's ability to respond flexibly in complex environments. Adaptiveness of ERF has been associated with cognitive flexibility, which can be improved by task-switching training. However, the impact of task-switching training on ERF and its underlying neural mechanisms remains unclear. To address this issue, we examined the effects of training on individuals' adaptiveness of ERF by assessing altered brain network patterns. Two groups of participants completed behavioral experiments and resting-state fMRI before and after training. Behavioral results showed higher adaptiveness scores and network analysis observed a higher number of connectivity edges, in the training group compared to the control group. Moreover, we found decreased connectivity strength within the default mode network (DMN) and increased connectivity strength within the frontoparietal network (FPN) in the training group. Furthermore, the task-switch training also led to decreased DMN-FPN interconnectivity, which was significantly correlated to increased adaptiveness of ERF scores. These findings suggest that the adaptiveness of ERF can be supported by altered patterns with the brain network through task-switch training, especially the increased network segregation between the DMN and FPN.

PMID:39575823 | DOI:10.1093/scan/nsae077

Imaging Neurosci (Camb). 2024 Nov 12;2:1-52. doi: 10.1162/imag_a_00347. eCollection 2024 Nov 1.

ABSTRACT

FMRI data are noisy, complicated to acquire, and typically go through many steps of processing before they are used in a study or clinical practice. Being able to visualize and understand the data from the start through the completion of processing, while being confident that each intermediate step was successful, is challenging. AFNI's afni_proc.py is a tool to create and run a processing pipeline for FMRI data. With its flexible features, afni_proc.py allows users to both control and evaluate their processing at a detailed level. It has been designed to keep users informed about all processing steps: it does not just process the data, but also first outputs a fully commented processing script that the users can read, query, interpret, and refer back to. Having this full provenance is important for being able to understand each step of processing; it also promotes transparency and reproducibility by keeping the record of individual-level processing and modeling specifics in a single, shareable place. Additionally, afni_proc.py creates pipelines that contain several automatic self-checks for potential problems during runtime. The output directory contains a dictionary of relevant quantities that can be programmatically queried for potential issues and a systematic, interactive quality control (QC) HTML. All of these features help users evaluate and understand their data and processing in detail. We describe these and other aspects of afni_proc.py here using a set of task-based and resting-state FMRI example commands.

PMID:39575179 | PMC:PMC11576932 | DOI:10.1162/imag_a_00347

ArXiv [Preprint]. 2024 Oct 30:arXiv:2410.23515v1.

ABSTRACT

Understanding the relationship between cognition and intrinsic brain activity through purely data-driven approaches remains a significant challenge in neuroscience. Resting-state functional magnetic resonance imaging (rs-fMRI) offers a non-invasive method to monitor regional neural activity, providing a rich and complex spatiotemporal data structure. Deep learning has shown promise in capturing these intricate representations. However, the limited availability of large datasets, especially for disease-specific groups such as Alzheimer's Disease (AD), constrains the generalizability of deep learning models. In this study, we focus on multivariate time series forecasting of independent component networks derived from rs-fMRI as a form of data augmentation, using both a conventional LSTM-based model and the novel Transformer-based BrainLM model. We assess their utility in AD classification, demonstrating how generative forecasting enhances classification performance. Post-hoc interpretation of BrainLM reveals class-specific brain network sensitivities associated with AD.

PMID:39575120 | PMC:PMC11581107

medRxiv [Preprint]. 2024 Oct 29:2024.10.27.24316243. doi: 10.1101/2024.10.27.24316243.

ABSTRACT

Alzheimer's disease (AD) is characterized by a long preclinical stage during which molecular markers of amyloid beta and tau pathology rise, but there is minimal neurodegeneration or cognitive decline. Previous literature suggests that measures of brain function might be more sensitive to neuropathologic burden during the preclinical stage of AD than conventional measures of macrostructure, such as cortical thickness. However, among studies that used resting-state functional Magnetic Resonance Imaging (fMRI) acquisitions with Blood Oxygenation Level Dependent (BOLD) contrast, most employed connectivity-based analytic approaches, which discard information about the amplitude of spontaneous brain activity. Consequently, little is known about the effects of amyloid and tau pathology on BOLD amplitude. To address this knowledge gap, we characterized the effects of preclinical and prodromal AD on the amplitude of low-frequency fluctuations (ALFF) of the BOLD signal both at the whole-brain level and, at a more granular level, focused on subregions of the medial temporal lobe. We observed reduced ALFF in both preclinical and prodromal AD. In preclinical AD, amyloid positivity was associated with a spatially diffuse ALFF reduction in the frontal, medial parietal, and lateral temporal association cortices, while tau pathology was negatively associated with ALFF in the entorhinal cortex. These ALFF effects were observed in the absence of observable macrostructural changes in preclinical AD and remained after adjusting for structural atrophy in prodromal AD, indicating that ALFF offers additional sensitivity to early disease processes beyond what is provided by traditional structural imaging biomarkers of neurodegeneration. We conclude that ALFF may be a promising imaging-based biomarker for assessing the effects of amyloid-clearing immunotherapies in preclinical AD.

PMID:39574853 | PMC:PMC11581098 | DOI:10.1101/2024.10.27.24316243

Front Neurol. 2024 Nov 6;15:1490763. doi: 10.3389/fneur.2024.1490763. eCollection 2024.

ABSTRACT

Resting-state functional MRI (fMRI) has revealed functional changes at the cortical level in degenerative cervical myelopathy (DCM) patients. The aim of this study was to systematically integrate static and dynamic functional connectivity (FC) to unveil abnormalities of functional networks of DCM patients and to analyze the prognostic value of these abnormalities for patients using resting-state fMRI. In this study, we collected clinical data and fMRI data from 44 DCM patients and 39 healthy controls (HC). Independent component analysis (ICA) was performed to investigate the group differences of intra-network FC. Subsequently, both static and dynamic FC were calculated to investigate the inter-network FC alterations in DCM patients. k-means clustering was conducted to assess temporal properties for comparison between groups. Finally, the support vector machine (SVM) approach was performed to predict the prognosis of DCM patients based on static FC, dynamic FC, and fusion of these two metrics. Relative to HC, DCM patients exhibited lower intra-network FC and higher inter-network FC. DCM patients spent more time than HC in the state in which both patients and HC were characterized by strong inter-network FC. Both static and dynamic FC could successfully classify DCM patients with different surgical outcomes. The classification accuracy further improved after fusing the dynamic and static FC for model training. In conclusion, our findings provide valuable insights into the brain mechanisms underlying DCM neuropathology on the network level.

PMID:39574511 | PMC:PMC11580013 | DOI:10.3389/fneur.2024.1490763

Front Neural Circuits. 2024 Nov 6;18:1497897. doi: 10.3389/fncir.2024.1497897. eCollection 2024.

ABSTRACT

Local and global functional connectivity densities (lFCD and gFCD, respectively), derived from functional magnetic resonance imaging (fMRI) data, represent the degree of functional centrality within local and global brain networks. While these methods are well-established for mapping brain connectivity, the molecular and synaptic foundations of these connectivity patterns remain unclear. Glutamate, the principal excitatory neurotransmitter in the brain, plays a key role in these processes. Among its receptors, the α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptor (AMPAR) is crucial for neurotransmission, particularly in cognitive functions such as learning and memory. This study aimed to examine the association of the AMPAR density and FCD metrics of intraregional and interregional functional centrality. Using [11C]K-2, a positron emission tomography (PET) tracer specific for AMPARs, we measured AMPAR density in the brains of 35 healthy participants. Our findings revealed a strong positive correlation between AMPAR density and both lFCD and gFCD-lFCD across the entire brain. This correlation was especially notable in key regions such as the anterior cingulate cortex, posterior cingulate cortex, pre-subgenual frontal cortex, Default Mode Network, and Visual Network. These results highlight that postsynaptic AMPARs significantly contribute to both local and global functional connectivity in the brain, particularly in network hub regions. This study provides valuable insights into the molecular and synaptic underpinnings of brain functional connectomes.

PMID:39568980 | PMC:PMC11576226 | DOI:10.3389/fncir.2024.1497897

BMC Psychiatry. 2024 Nov 20;24(1):835. doi: 10.1186/s12888-024-06283-0.

ABSTRACT

BACKGROUND: Psychotic depression (PD) and schizophrenia (SCZ) share overlapping symptoms yet differ in etiology, progression, and treatment approaches. Differentiating these disorders through symptom-based diagnosis is challenging, emphasizing the need for a clearer understanding of their distinct cognitive and neural mechanisms.

AIM: This study aims to compare cognitive impairments and brain functional activities in PD and SCZ to pinpoint distinguishing characteristics of each disorder.

METHODS: We evaluated cognitive function in 42 PD and 30 SCZ patients using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) and resting-state functional magnetic resonance imaging (rs-fMRI). Regional homogeneity (ReHo) values were derived from rs-fMRI data, and group differences in RBANS scores were analyzed. Additionally, Pearson correlation analysis was performed to assess the relationship between cognitive domains and brain functional metrics.

RESULTS: (1) The SCZ group showed significantly lower RBANS scores than the PD group across all cognitive domains, particularly in visuospatial/constructional ability and delayed memory (p < 0.05); (2) The SCZ group exhibited a significantly higher ReHo value in the left precuneus compared to the PD group (p < 0.05); (3) A negative correlation was observed between visuospatial construction, delayed memory scores, and the ReHo value of the left precuneus.

CONCLUSION: Cognitive impairment is more pronounced in SCZ than in PD, with marked deficits in visuospatial and memory domains. Enhanced left precuneus activity further differentiates SCZ from PD and correlates with cognitive impairments in both disorders, providing neuroimaging-based evidence to aid differential diagnosis and insights into cognitive dysfunction mechanisms, while also paving a clearer path for psychiatric research.

PMID:39567972 | PMC:PMC11577850 | DOI:10.1186/s12888-024-06283-0