Most recent paper

Alzheimers Dement (Amst). 2024 Oct 16;16(4):e70013. doi: 10.1002/dad2.70013. eCollection 2024 Oct-Dec.

ABSTRACT

INTRODUCTION: Apathy is a significant feature in Alzheimer's disease (AD) and subjective cognitive impairment (SCI), though its mechanisms are not well established.

METHODS: An effort-based decision-making (EBDM) framework was applied to investigate apathy in 30 AD patients, 41 SCI participants, and 55 healthy controls (HC). Data were analyzed using a drift-diffusion model (DDM) to uncover latent psychological processes.

RESULTS: SCI participants reported higher apathy than AD patients and HC. However, informant reports of apathy in AD patients were higher than self-reports and indicated significant apathy compared to HC. Both the AD and SCI groups showed reduced sensitivity to effort changes, linked to executive dysfunction in AD and apathy in SCI. Increased resting functional cortical connectivity with the nucleus accumbens (NA) was associated with higher apathy in SCI.

DISCUSSION: These results highlight a similar disruption of EBDM in AD and SCI, differentially related to executive functioning in AD and apathy in SCI.

HIGHLIGHTS: This is the first study investigating apathy using an effort-based decision-making (EBDM) framework in Alzheimer's disease (AD) and subjective cognitive impairment (SCI).Self-reports underestimate apathy in AD patients when compared to informant reports and healthy controls (HC). SCI participants, in whom self and informant reports were more concordant, also showed higher degrees of apathy.Both AD and SCI groups showed reduced sensitivity to effort.Reduced sensitivity to effort correlates with executive dysfunction in AD and apathy, but not depression, in SCI.Increased nucleus accumbens (ventral striatum) connectivity with the frontoparietal network was associated with higher apathy scores in SCI.The results thus suggest that while AD and SCI can have similar deficits in EBDM, these deficits correlate with distinct clinical manifestations: executive dysfunction in AD and apathy in SCI.

PMID:39416486 | PMC:PMC11480904 | DOI:10.1002/dad2.70013

bioRxiv [Preprint]. 2024 Oct 7:2024.10.04.616707. doi: 10.1101/2024.10.04.616707.

ABSTRACT

BACKGROUND: Major depressive disorder (MDD) is a prevalent psychiatric disorder characterized by substantial clinical and neurobiological heterogeneity. Conventional studies that solely focus on clinical symptoms or neuroimaging metrics often fail to capture the intricate relationship between these modalities, limiting their ability to disentangle the complexity in MDD. Moreover, patient neuroimaging data typically contains normal sources of variance shared with healthy controls, which can obscure disorder-specific variance and complicate the delineation of disease heterogeneity.

METHODS: We employed contrastive principal component analysis to extract disorder-specific variations in fMRI-based resting-state functional connectivity (RSFC) by contrasting MDD patients (N=233) with age-matched healthy controls (N=285). We then applied sparse canonical correlation analysis to identify latent dimensions in the disorder variations by linking the extracted contrastive connectivity features to clinical symptoms in MDD patients.

RESULTS: Two significant and generalizable dimensions linking distinct brain circuits and clinical profiles were discovered. The first dimension, associated with an apparent internalizing-externalizing symptom dimension, was characterized by self-connections within the visual network and also associated with choice reaction times of cognitive tasks. The second dimension, associated with personality facets such as extraversion and conscientiousness typically inversely associated with depression symptoms, is primarily driven by self-connections within the dorsal attention network. This depression-protective personality dimension is also associated with multiple cognitive task performances related to psychomotor slowing and cognitive control.

CONCLUSIONS: Our contrastive RSFC-based dimensional approach offers a new avenue to dissect clinical heterogeneity underlying MDD. By identifying two stable, neurophysiology-informed symptom dimensions in MDD patients, our findings may enhance disease mechanism insights and facilitate precision phenotyping, thus advancing the development of targeted therapeutics for precision mental health.

PMID:39416217 | PMC:PMC11482755 | DOI:10.1101/2024.10.04.616707

bioRxiv [Preprint]. 2024 Oct 7:2024.10.05.615717. doi: 10.1101/2024.10.05.615717.

ABSTRACT

The brain's resting-state energy consumption is expected to be mainly driven by spontaneous activity. In our previous work, we extracted a wide range of features from resting-state fMRI (rs-fMRI), and used them to predict [18F]FDG PET SUVR as a proxy of glucose metabolism. Here, we expanded upon our previous effort by estimating [18F]FDG kinetic parameters according to Sokoloff's model, i.e., Ki (irreversible uptake rate), K1 (delivery), k3 (phosphorylation), in a large healthy control group. The parameters' spatial distribution was described at a high spatial resolution. We showed that while K1 is the least redundant, there are relevant differences between Ki and k3 (occipital cortices, cerebellum and thalamus). Using multilevel modeling, we investigated how much of the regional variability of [18F]FDG parameters could be explained by a combination of rs-fMRI variables only, or with the addition of cerebral blood flow (CBF) and metabolic rate of oxygen (CMRO2), estimated from 15O PET data. We found that combining rs-fMRI and CMRO2 led to satisfactory prediction of individual Ki variance (45%). Although more difficult to describe, Ki and k3 were both most sensitive to local rs-fMRI variables, while K1 was sensitive to CMRO2. This work represents the most comprehensive assessment to date of the complex functional and metabolic underpinnings of brain glucose consumption.

PMID:39416159 | PMC:PMC11482815 | DOI:10.1101/2024.10.05.615717

bioRxiv [Preprint]. 2024 Oct 12:2024.10.10.617666. doi: 10.1101/2024.10.10.617666.

ABSTRACT

Cerebrovascular reactivity (CVR) and cerebral pulsatility (CP) are important indicators of cerebrovascular health and have been shown to be associated with physical activity (PA). Sex differences have been shown to influence the impact of PA on cerebrovascular health. However, the sex-specific effects of PA on CP and CVR, particularly in relation to intensity and dosage of PA, remains unknown. Thus, this cross-sectional study aimed to evaluate the sex-specific effects of different intensities and doses of PA on CVR and CP. The Human Connectome - Aging dataset was used, including 626 participants (350 females, 276 males) aged 36-85 (mean age: 58.8 ± 14.1 years). Females were stratified into premenopausal and postmenopausal groups to assess the potential influence of menopausal status. Novel tools based solely on resting state fMRI data were used to estimate both CVR and CP. The International Physical Activity Questionnaire was used to quantify weekly self-reported PA as metabolic equivalent of task. Results indicated that both sexes and menopausal subgroups revealed negative linear relationships between relative CVR and PA. Furthermore, females presented a unique non-linear relationship between relative CVR and total PA in the cerebral cortex. In females, there were also relationships with total and walking PA in occipital and cingulate regions. In males, we observed relationships between total or vigorous PA and CVR in parietal and cingulate regions. Sex-specific effects were also observed with CP, whereby females benefited across a greater number of regions and intensities than males, especially in the postmenopause group. Overall, males and females appear to benefit from different amounts and intensities of PA, with menopause status significantly influencing the effect of PA on cerebrovascular outcomes, underscoring the need for sex-specific recommendations in promoting cerebrovascular health.

PMID:39416007 | PMC:PMC11482942 | DOI:10.1101/2024.10.10.617666

Brain Inj. 2024 Oct 16:1-12. doi: 10.1080/02699052.2024.2416545. Online ahead of print.

ABSTRACT

OBJECTIVE: This study aimed to compare psychosocial outcomes and functional neuroimaging among youth with concussion, youth with anxiety, and age- and sex-matched controls.

METHODS: Using archival data from the Adolescent Brain Cognitive DevelopmentSM Study, we analyzed between-group differences in psychosocial outcomes measured by the Child Behavior Checklist's internalizing and externalizing problem scales, and assessed brain function using resting-state fMRI network-region connectivity (specifically frontoparietal network (FPN) and default mode network (DMN) connectivity with the amygdala).

RESULTS: Significant differences in psychosocial outcomes were found across all groups, with the anxiety group reporting the most internalizing problems, followed by the concussion group which significantly differed from controls. Additionally, FPN-amygdala connectivity was significantly reduced in the concussion group only; this reduced connectivity did not predict psychosocial outcomes across groups.

CONCLUSION: This study provided preliminary findings that brain connectivity is reduced exclusively in individuals with concussion. Although disruptions were observed in the concussion group, further investigation is warranted to understand how disruptions may be associated with concussion symptoms. Studies that utilize well-defined control and study groups, and comprehensive cognitive and mental health measures will offer a deeper understanding of the relationship between brain function and psychosocial outcomes.

PMID:39415428 | DOI:10.1080/02699052.2024.2416545

Front Neuroimaging. 2024 Oct 1;3:1445952. doi: 10.3389/fnimg.2024.1445952. eCollection 2024.

ABSTRACT

Severe acute brain injury (SABI) with suppressed consciousness is a major societal burden, with early prognosis being crucial for life-and-death treatment decisions. Resting-state functional MRI (rs-fMRI) is promising for prognosis and identifying epileptogenic activity in SABI. While established for SABI prognosis and seizure networks (SzNET) identification in epilepsy, the rs-fMRI use for SzNET detection in SABI is limited. This study compared evolution of SzNET and resting-state networks (RSN) pre-to-post treatment in SABI and epilepsy, hypothesizing that changes would align with clinical evolution. Therapies included epilepsy surgery for the epilepsy group and antiseizure medication for the SABI group. Independent component analysis (ICA) was used to identify SzNET and RSNs in all rs-fMRI. High-frequency BOLD (HF-BOLD), an ICA power spectrum-based index, quantified RSN and SzNET changes by the patient. Confidence intervals measured HF-BOLD changes pre-to-post-therapy. Baseline HF-BOLD and HF-BOLD changes were compared using linear-mixed models and interaction tests. Five SABI and ten epilepsy patients were included. SzNET were identified in all SABI's pre-therapy rs-fMRI. The clinical changes in SABI and epilepsy were consistent with rs-fMRI findings across groups. HF-BOLD reduced in the epilepsy group RSN post-therapy (-0.78, 95% CI -3.42 to -0.33), but the evidence was insufficient to determine an HF-BOLD reduction in SABI patients or SzNET. The HF-BOLD change trend in pre-to-post epilepsy surgery scans paralleled the clinical improvement, suggesting that the power spectrum may quantify the degree of abnormality on ICA-derived networks. Despite limitations such as small sample sizes, this exploratory study provides valuable insights into network dysfunction in SABI and epilepsy.

PMID:39411721 | PMC:PMC11473429 | DOI:10.3389/fnimg.2024.1445952

J Clin Med. 2024 Sep 30;13(19):5856. doi: 10.3390/jcm13195856.

ABSTRACT

Introduction: Several studies have investigated the specific neural correlates of trans people, highlighting mixed results. This study aimed to compare the presence of specific functional connectivity and differences in cognitive profile and hormone levels in trans men diagnosed with gender dysphoria (GD), and a homogeneous group of cisgender men and cisgender women. Methods: A total of 42 participants (19 trans men, 11 cisgender men, and 12 cisgender women) underwent a resting state fMRI and were measured for blood levels of testosterone, estradiol, and progesterone. A neuropsychological battery evaluated executive functions, attention, visual-perceptual ability, verbal fluency, manual preference, and general intelligence. Results: Trans men showed weaker functional connectivity in the precentral gyrus, subcallosal cortex, paracingulate gyrus, temporal pole, and cingulate gyrus than cisgender men (p < 0.01). Trans men performed worse than cisgender men in verbal and visuospatial working memory but similarly to cisgender women (p < 0.05). In trans men, functional connectivity of the precentral gyrus correlated positively with testosterone (r = 0.459, p = 0.064) and negatively with estradiol (r = -0.654, p = 0.004) and progesterone blood levels (r = -0.475, p = 0.054). The cluster involving the subcallosal cortex showed a positive correlation with testosterone (r = 0.718, p = 0.001), and a negative correlation with estradiol (r = -0.602, p = 0.011). The functional connectivity from a cluster involving the paracingulate gyrus showed a positive correlation with testosterone (r = 0.592, p = 0.012). Conclusions: This study highlights the importance of overpassing the binary model by underlining the presence of neural pathways that could represent the peculiarity of the neural profile of people with GD.

PMID:39407916 | DOI:10.3390/jcm13195856

J Clin Med. 2024 Sep 25;13(19):5704. doi: 10.3390/jcm13195704.

ABSTRACT

Background: This review focuses on the prognostic role of resting-state functional magnetic resonance imaging (fMRI) in disorders of consciousness (DOCs). Several studies were conducted to determine the diagnostic accuracy in DOC patients to identify prognostic markers and to understand the neural correlates of consciousness. A correct diagnosis of consciousness in unresponsive or minimally responsive patients is important for prognostic and therapeutic management. Functional connectivity is considered as an important tool for the formulation of cerebral networks; it takes into account the primary sensorimotor, language, visual and central executive areas, where fMRI studies show damage in brain connectivity in the areas of frontoparietal networks in DOC patients. Methods: The integration of neuroimaging or neurophysiological methods could improve our knowledge of the neural correlates of clinical response after an acquired brain injury. The use of MRI is widely reported in the literature in different neurological diseases. In particular, fMRI is the most widely used brain-imaging technique to investigate the neural mechanisms underlying cognition and motor function. We carried out a detailed literature search following the relevant guidelines (PRISMA), where we collected data and results on patients with disorders of consciousness from the studies performed. Results: In this review, 12 studies were selected, which showed the importance of the prognostic role of fMRI for DOCs. Conclusions: Currently there are still few studies on this topic. Future studies using fMRI are to be considered an added value for the prognosis and management of DOCs.

PMID:39407763 | DOI:10.3390/jcm13195704

Commun Biol. 2024 Oct 15;7(1):1324. doi: 10.1038/s42003-024-07007-6.

ABSTRACT

Creativity is typically operationalized as divergent thinking (DT) ability, a form of higher-order cognition which relies on memory, attention, and other component processes. Despite recent advances, creativity neuroscience lacks a unified framework to model its complexity across neural, genetic, and cognitive scales. Using task-based fMRI from two independent samples and MVPA, we identified a neural pattern that predicts DT, validated through cognitive decoding, genetic data, and large-scale resting-state fMRI. Our findings reveal that DT neural patterns span brain regions associated with diverse cognitive functions, with positive weights in the default mode and frontoparietal control networks and negative weights in the visual network. The high correlation with the primary gradient of functional connectivity suggests that DT involves extensive integration from concrete sensory information to abstract, higher-level cognition, distinguishing it from other advanced cognitive functions. Moreover, neurobiological analyses show that the DT pattern is positively correlated with dopamine-related neurotransmitters and genes influencing neurotransmitter release, advancing the neurobiological understanding of creativity.

PMID:39402209 | DOI:10.1038/s42003-024-07007-6

Prog Neuropsychopharmacol Biol Psychiatry. 2024 Oct 12:111169. doi: 10.1016/j.pnpbp.2024.111169. Online ahead of print.

ABSTRACT

Levodopa (L-dopa) therapy is the most effective pharmacological treatment for motor symptoms of Parkinson's disease (PD). However, its effect on brain functional network dynamics is still unclear. Here, we recruited 26 PD patients and 24 healthy controls, and acquired their resting-state functional MRI data before (PD-OFF) and after (PD-ON) receiving 400 mg L-dopa. Using the independent component analysis and the sliding-window approach, we estimated the dynamic functional connectivity (dFC) and examined the effect of L-dopa on the temporal properties of dFC states, the variability of dFC and functional network topological organization. We found that PD-ON showed decreased mean dwell time in sparsely connected State 2 than PD-OFF, the transformation of the dFC state is more frequent and the variability of dFC was decreased within the auditory network and sensorimotor network in PD-ON. Our findings provide new insights to understand the dynamic neural activity induced by L-dopa therapy in PD patients.

PMID:39401562 | DOI:10.1016/j.pnpbp.2024.111169

Front Neuroimaging. 2024 Sep 27;3:1474060. doi: 10.3389/fnimg.2024.1474060. eCollection 2024.

ABSTRACT

OBJECTIVE: Spinal cord stimulation (SCS) is an invasive treatment option for patients suffering from chronic low-back pain (cLBP). It is an effective treatment that has been shown to reduce pain and increase the quality of life in patients. However, the activation of pain processing regions of cLBP patients receiving SCS has not been assessed using objective, quantitative functional imaging techniques. The purpose of the present study was to compare quantitative resting-state (rs)-fMRI and arterial spin labeling (ASL) measures between SCS patients and healthy controls and to correlate clinical measures with quantitative multimodal imaging indices in pain regions.

METHODS: Multi-delay 3D GRASE pseudo-continuous ASL and rs-fMRI data were acquired from five patients post-SCS with cLBP and five healthy controls. Three ASL measures and four rs-fMRI measures were derived and normalized into MNI space and smoothed. Averaged values for each measure from a pain atlas were extracted and compared between patients and controls. Clinical pain scores assessing intensity, sensitization, and catastrophizing, as well as others assessing global pain effects (sleep quality, disability, anxiety, and depression), were obtained in patients and correlated with pain regions using linear regression analysis.

RESULTS: Arterial transit time derived from ASL and several rs-fMRI measures were significantly different in patients in regions involved with sensation (primary somatosensory cortex and ventral posterolateral thalamus [VPL]), pain input (posterior short gyrus of the insula [PS]), cognition (dorsolateral prefrontal cortex [DLPC] and posterior cingulate cortex [PCC]), and fear/stress response (hippocampus and hypothalamus). Unidimensional pain rating and sensitization scores were linearly associated with PS, VPL, DLPC, PCC, and/or amygdala activity in cLBP patients.

CONCLUSION: The present results provide evidence that ASL and rs-fMRI can contrast functional activation in pain regions of cLBP patients receiving SCS and healthy subjects, and they can be associated with clinical pain evaluations as quantitative assessment tools.

PMID:39399386 | PMC:PMC11470492 | DOI:10.3389/fnimg.2024.1474060

Front Neurosci. 2024 Sep 27;18:1477181. doi: 10.3389/fnins.2024.1477181. eCollection 2024.

ABSTRACT

BACKGROUND: Traditional Chinese opera, such as Pingju, requires actors to master sophisticated performance skills and cultural knowledge, potentially influencing brain function. This study aimed to explore the effects of long-term opera training on the dynamic amplitude of low-frequency fluctuation (dALFF) and dynamic functional connectivity (dFC).

METHODS: Twenty professional well-trained Pingju actors and twenty demographically matched untrained subjects were recruited. Resting-state functional magnetic resonance imaging (fMRI) data were collected to assess dALFF differences in spontaneous regional brain activity between the actors and untrained participants. Brain regions with altered dALFF were selected as the seeds for the subsequent dFC analysis. Statistical comparisons examined differences between groups, while correlation analyses explored the relationships between dALFF and dFC, as well as the associations between these neural measures and the duration of Pingju training.

RESULTS: Compared with untrained subjects, professional Pingju actors exhibited significantly lower dALFF in the right lingual gyrus. Additionally, actors showed increased dFC between the right lingual gyrus and the bilateral cerebellum, as well as between the right lingual gyrus and the bilateral midbrain/red nucleus/thalamus, compared with untrained subjects. Furthermore, a negative correlation was found between the dALFF in the right lingual gyrus and its dFC, and a significant association was found between dFC in the bilateral midbrain/red nucleus/thalamus and the duration of Pingju training.

CONCLUSION: Long-term engagement in Pingju training induces neuroplastic changes, reflected in altered dALFF and dFC. These findings provide evidence for the interaction between artistic training and brain function, highlighting the need for further research into the impact of professional training on cognitive functions.

PMID:39399381 | PMC:PMC11466935 | DOI:10.3389/fnins.2024.1477181

ArXiv [Preprint]. 2024 Aug 22:arXiv:2406.05248v3.

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 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:39398207 | PMC:PMC11468194

Brain Topogr. 2024 Oct 13;38(1):6. doi: 10.1007/s10548-024-01079-7.

ABSTRACT

The aim of this study is to investigate activity and functional connectivity (FC) of Papez circuit networks associated with music processing using functional magnetic resonance imaging (fMRI) in depressed breast cancer patients. Twenty-three breast cancer patients listened to four different Iranian/Persian music paradigms during the resting-state fMRI scanning session: negative stimulation of traditional music, negative stimulation of pop music, positive stimulation of traditional music and positive stimulation of pop music. The amplitude of low-frequency fluctuation (ALFF) was used to evaluate the local characteristics of spontaneous brain activity. FC maps were created using multivariate ROI-to-ROI connectivity (mRRC) and Papez circuit-based regions of interest (ROIs) selection. We found that music increases FC within various brain networks which are involved in memory, emotion, and cognitive function, including the limbic system, the default mode network (DMN), salience network (SN), and central executive network (CEN). Moreover, it seems that the traditional types (both positive and negative) of Iranian music may be more effective to affect brain activity in the patients with breast cancer, than the Iranian pop music. These findings demonstrate that music therapy, as an effective and easily applicable approach, supports the neuropsychological recovery and can contribute to standard treatment protocols in patients with breast cancer.

PMID:39397183 | DOI:10.1007/s10548-024-01079-7

Nutr Res. 2024 Jul 23;131:147-158. doi: 10.1016/j.nutres.2024.07.004. Online ahead of print.

ABSTRACT

Maternal nutrition during the perinatal stage is critical to offspring brain development. Egg yolks are a balanced and nutrient-dense food that is rich in bioactive components crucial to optimal neurodevelopment early in life. Egg consumption is often recommended to pregnant women to enhance both maternal and fetal health. We hypothesized that maternal intake of egg yolk from late gestation and throughout lactation would enhance functional organization and cognitive developmental outcomes in offspring using a pig model. Sows were fed a control diet (n = 6) or a diet containing egg yolks (n = 5, 350 mg egg yolk powder/kg BW/day, equivalent to ∼3 eggs/day for humans) from late gestation through lactation. At weaning, piglet offspring (n = 2/sow, total n = 22) underwent structural magnetic resonance imaging (MRI) and resting-state-functional MRI. Piglets underwent novel object recognition testing to assess hippocampal-dependent learning and memory. Functional MRI results demonstrated that egg yolk significantly increased functional activation in the executive network (p = 0.0343) and cerebellar network (p = 0.0253) in piglets when compared to control. Diffusion tensor imaging analysis showed that perinatal intake of egg yolks significantly increased white matter fiber length in the hippocampus (p = 0.0363) and cerebellum (p = 0.0287) in piglet offspring compared to control piglets. Furthermore, piglets from egg yolk-fed sows spent significantly more proportional frequency exploring the novel object than the familiar object in novel object recognition testing (p = 0.0370). The findings from this study support egg yolk-altered activation of specific brain networks may be associated with functional cognitive outcomes in weaning piglets.

PMID:39395250 | DOI:10.1016/j.nutres.2024.07.004

Zhonghua Lao Dong Wei Sheng Zhi Ye Bing Za Zhi. 2024 Sep 20;42(9):689-694. doi: 10.3760/cma.j.cn121094-20231122-00126.

ABSTRACT

Objective: To investigate the changes of directional connections of auditory and non-auditory in patients with noise-induced deafness (NID) by degree centrality (DC) and Granger causality analysis (GCA), and to explore the mode of brain function remodeling after NID. Methods: In October 2023, a total of 58 patients diagnosed with NID by the Occupational Diseases Department of Yantaishan Hospital of Yantai from 2014 to 2022 were collected as case group (NID group), and 42 healthy volunteers matched by gender, age and education level were selected as the control group (HC group). Resting state-functional magnetic resonance imaging (Rs-fMRI) was perfomed and PC analysis was performed. The brain regions with statistically significant differences in DC values between groups and the bilateral Heschl regions were extracted as regions of interest (ROI) for voxel-based whole brain GCA and correlation analysis. Results: Compared with HC group, the SOG.L DC value of NID group was lower, the connectivity values of SFGdor.L to SOG.L was increased, the connectivity value of PCL.L to SOG.L was decreased, the connectivity values of ORBmid.L, PCG.R and CUN. L/R to HES.L were increased, the connectivity value of SFGdor.L to HES.L was decreased, the connectivity value of HES.L to PCUN.L was decreased, the connectivity values of ORBsup.L and PCG.R to HES.R were increased, the connectivity value of HES.R to CUN.L was decreased (P voxel level<0.01, P cluster level<0.05). The connectivity value of PCL.L to SOG.L was negatively correlated with the weighted value of the better whisper frequency (P<0.05) . Conclusion: The NID patients have abnormal directional connectivity activity in multiple brain regions, such as auditory vision, executive control, somatosensory movement, and default mode network. It is suggested that hearing loss may cause complex neural remodeling between auditory and non-auditory centers.

PMID:39394708 | DOI:10.3760/cma.j.cn121094-20231122-00126

Brain Res. 2024 Oct 9:149265. doi: 10.1016/j.brainres.2024.149265. Online ahead of print.

ABSTRACT

The networks observed in the brain during resting-state activity are not entirely "task-free." Instead, they hint at a hierarchical structure prepared for adaptive cognitive functions. Recent studies have increasingly demonstrated the potential of resting-state fMRI to predict local activations or global connectomes during task performance. However, uncertainties remain regarding the unique and shared task-specific components within resting-state brain networks, elucidating local activations and global connectome patterns. A coherent framework is also required to integrate these task-specific components to predict local activations and global connectome patterns. In this work, we introduce the Rest2Task model based on the partial least squares-based multivariate regression algorithm, which effectively integrates mappings from resting-state connectivity to local activations and global connectome patterns. By analyzing the coefficients of the regression model, we extracted task-specific resting-state components corresponding to brain local activation or global connectome of various tasks and applied them to the brain lateralization prediction and psychiatric disorders diagnostic. Our model effectively substitutes traditional whole-brain functional connectivity (FC) in predicting functional lateralization and diagnosing brain disorders. Our research represents the inaugural effort to quantify the contribution of patterns (components) within resting-state FC to different tasks, endowing these components with specific task-related contextual information. The task-specific resting-state components offer new insights into brain lateralization processing and disease diagnosis, potentially providing fresh perspectives on the adaptive transformation of brain networks in response to tasks.

PMID:39393483 | DOI:10.1016/j.brainres.2024.149265

J Biomed Phys Eng. 2024 Oct 1;14(5):435-446. doi: 10.31661/jbpe.v0i0.2204-1481. eCollection 2024 Oct.

ABSTRACT

BACKGROUND: Non-specific chronic low back pain (CLBP) is a common painful condition and is responsible for different physical disorders. Despite alternative therapies, patients still suffer from persistent pain. Repetitive transcranial magnetic stimulation (rTMS) has provided much evidence of pain reduction, but results have not been examined deeply in CLBP symptoms.

OBJECTIVE: The analgesic effect of rTMS in non-specific CLBP patients was evaluated by the amplitude of low-frequency fluctuation (ALFF) analysis in resting-state fMRI.

MATERIAL AND METHODS: In this experimental study, fifteen non-specific CLBP participants (46.87±10.89 years) received 20 Hz rTMS over the motor cortex. The pain intensity and brain functional scan were obtained during pre and post-stimulation for all participants. The ALFF maps of the brain in two scan sessions were identified and the percentage of pain reduction (PPR%) was determined using paired t-test. Also, correlation analysis was used to find a relationship between ALFFs and pain intensity.

RESULTS: Pain intensity was significantly reduced after induced-rTMS in non-specific CLBP (36.22%±13.28, P<0.05). Positive correlation was found between ALFF in the insula (INS) and pain intensity (rpre-rTMS=0.59, rpost-rTMS=0.58) while ALFF in medial prefrontal cortex (mPFC) and pain intensity had negatively correlated (rpre-rTMS=-0.54, rpost-rTMS=-0.56) (P<0.05). ALFF increased in mPFC while INS, thalamus (THA), and supplementary motor area (SMA) showed decremental ALFF followed by rTMS.

CONCLUSION: This study demonstrated that ALFF in INS, THA, mPFC, and SMA is associated with CLBP symptoms and analgesic effects of rTMS. ALFF potentially seems to be a proper objective neuroimaging parameter to link spontaneous brain activity with pain intensity in non-specific CLBP patients.

PMID:39391282 | PMC:PMC11462276 | DOI:10.31661/jbpe.v0i0.2204-1481

bioRxiv [Preprint]. 2024 Sep 26:2024.09.26.615215. doi: 10.1101/2024.09.26.615215.

ABSTRACT

Adolescence is a period of growth in cognitive performance and functioning. Recently, data-driven measures of brain-age gap, which can index cognitive decline in older populations, have been utilized in adolescent data with mixed findings. Instead of using a data-driven approach, here we assess the maturation status of the brain functional landscape in early adolescence by directly comparing an individual's resting-state functional connectivity (rsFC) to the canonical early-life and adulthood communities. Specifically, we hypothesized that the degree to which a youth's connectome is better captured by adult networks compared to infant/toddler networks is predictive of their cognitive development. To test this hypothesis across individuals and longitudinally, we utilized the Adolescent Brain Cognitive Development (ABCD) Study at baseline (9-10 years; n = 6,489) and 2-year-follow-up (Y2: 11-12 years; n = 5,089). Adjusted for demographic factors, our anchored rsFC score (AFC) was associated with better task performance both across and within participants. AFC was related to age and aging across youth, and change in AFC statistically mediated the age-related change in task performance. In conclusion, we showed that a model-fitting-free index of the brain at rest that is anchored to both adult and baby connectivity landscapes predicts cognitive performance and development in youth.

PMID:39386610 | PMC:PMC11463351 | DOI:10.1101/2024.09.26.615215

bioRxiv [Preprint]. 2024 Sep 27:2024.02.19.581086. doi: 10.1101/2024.02.19.581086.

ABSTRACT

Brain function can be modeled as the dynamic interactions between functional sources at different spatial scales, and each spatial scale can contain its functional sources with unique information, thus using a single scale may provide an incomplete view of brain function. This paper introduces a novel approach, termed "telescopic independent component analysis (TICA)," designed to construct spatial functional hierarchies and estimate functional sources across multiple spatial scales using fMRI data. The method employs a recursive ICA strategy, leveraging information from a larger network to guide the extraction of information about smaller networks. We apply our model to the default mode network (DMN), visual network (VN), and right frontoparietal network (RFPN). We investigate further on DMN by evaluating the difference between healthy people and individuals with schizophrenia. We show that the TICA approach can detect the spatial hierarchy of DMN, VS, and RFPN. In addition, TICA revealed DMN-associated group differences between cohorts that may not be captured if we focus on a single-scale ICA. In sum, our proposed approach represents a promising new tool for studying functional sources.

PMID:39386484 | PMC:PMC11463639 | DOI:10.1101/2024.02.19.581086