Most recent paper
Brain structural and functional changes in patients with chronic heart failure
Neuroscience. 2024 Nov 25:S0306-4522(24)00648-1. doi: 10.1016/j.neuroscience.2024.11.060. Online ahead of print.
ABSTRACT
Heart failure (HF) frequently suffers from brain abnormalities and cognitive impairments. This study aims to investigate brain structure and function alteration in patients with chronic HF. This retrospective study included 49 chronic HF and 49 health controls (HCs). Voxel-based morphometry was conducted on structural MRI to quantify gray matter volume (GMV), and functional connectivity (FC) was assessed with seed-based analysis using resting-state fMRI. White matter microstructure integrity was also evaluated through tract-based spatial statistics employing DTI. Correlations between multimodal MRI features and cognitive performance were further investigated in patients with chronic HF. Patients with chronic HF exhibited significantly reduced regional GMV, white matter microstructure injury (Family wise error correction, p<0.05), and decreased FC in multiple brain regions involved in cognition, sensorimotor, visual function (Gaussian random field correction, voxel level p<0.0001 and cluster-level p<0.01). There was no observed increases in GMV or FC compared with HCs. Decreased GMV showed positive correlations with cognitive performance (r = 0.025-0.577, p = 0.025-0.001), while decreased fractional anisotropy was negatively correlated with anxiety scores (r = -0.339, p = 0.040) in patients with chronic HF. This study revealed that patients with chronic HF exhibited brain structure injury affecting gray matter and white matter, as well as FC abnormalities of brain regions responsible for cognition, sensorimotor and visual function. These findings suggest GMV could serve as a neuroimaging biomarker for cognitive impairments and a potential target for neuroprotective therapies in patients with chronic HF.
PMID:39603406 | DOI:10.1016/j.neuroscience.2024.11.060
A three-classification model for identifying migraine with right-to-left shunt using lateralization of functional connectivity and brain network topology: a resting-state fMRI study
Front Neurosci. 2024 Nov 12;18:1488193. doi: 10.3389/fnins.2024.1488193. eCollection 2024.
ABSTRACT
INTRODUCTION: Right-to-left shunting has been significantly associated with migraine, although the neural mechanisms remain complex and not fully elucidated. The aim of this study was to investigate the variability of brain asymmetry in individuals with migraine with right-to-left shunting, migraine without right-to-left shunting and normal controls using resting-state fMRI technology and to construct a three-classification model.
METHODS: Firstly, asymmetries in functional connectivity and brain network topology were quantified to laterality indices. Secondly, the laterality indices were employed to construct a three-classification model using decision tree and random forest algorithms. Ultimately, through a feature score analysis, the key brain regions that contributed significantly to the classification were extracted, and the associations between these brain regions and clinical features were investigated.
RESULTS: Our experimental results showed that the initial classification accuracy reached 0.8961. Subsequently, validation using an independent sample set resulted in a classification accuracy of 0.8874. Further, after expanding the samples by the segmentation strategy, the classification accuracies were improved to 0.9103 and 0.9099. Additionally, the third sample set yielded a classification accuracy of 0.8745. Finally, 9 pivotal brain regions were identified and distributed in the default network, the control network, the visual network, the limbic network, the somatomotor network and the salience/ventral attention network.
DISCUSSION: The results revealed distinct lateralization features in the brains of the three groups, which were closely linked to migraine and right-to-left shunting symptoms and could serve as potential imaging biomarkers for clinical diagnosis. Our findings enhanced our understanding of migraine and right-to-left shunting mechanisms and offered insights into assisting clinical diagnosis.
PMID:39600655 | PMC:PMC11588730 | DOI:10.3389/fnins.2024.1488193
Identification of Specific Abnormal Brain Functional Activity and Connectivity in Cancer Pain Patients: A Preliminary Resting-State fMRI Study
J Pain Res. 2024 Nov 22;17:3959-3971. doi: 10.2147/JPR.S470750. eCollection 2024.
ABSTRACT
OBJECTIVE: This study investigates the differences in brain functional activity and connectivity patterns between Cancer Pain (CP) patients and Healthy Controls (HCs) using resting-state functional magnetic resonance imaging (rs-fMRI) to identify potential neuroimaging biomarkers.
METHODS: This study collected rs-fMRI data from 25 CP patients and 25 hCs, processed the functional MRI images, and calculated metrics such as amplitude of low-frequency fluctuation (ALFF), Regional Homogeneity (ReHo), and FC. Through statistical analysis, differences in brain functional activity and connectivity between the cancer pain group and the healthy control group were investigated, followed by machine learning classification.
RESULTS: The results showed that compared to the normal group, reductions in the ALFF were primarily observed in the bilateral inferior temporal gyrus; ReHo increased in the right middle temporal gyrus and decreased in the left cerebellum Crus2. Using the statistically different brain areas as seed points to construct FC networks and performing statistical analysis, it was found that the regions with decreased FC connection strength between the cancer pain group and the normal group were mainly in the prefrontal cortex (PFC), the postcentral gyrus of the parietal lobe, and the cerebellum. Statistical results indicated that there was no significant correlation between pain scores (Numeric Rating Scale, NRS) and neuroimaging metrics. According to the machine learning classification, the FC features of the right precentral gyrus achieved higher diagnostic efficacy (AUC = 0.804) compared to ALFF and ReHo in distinguishing between CP patients and HCs.
CONCLUSION: Brain activity and FC in CP patients show abnormalities in regions such as the inferior temporal gyrus, middle temporal gyrus, prefrontal cortex, parietal lobe, and cerebellum. These areas may be interconnected through neural networks and jointly participate in functions related to pain perception, emotion regulation, cognitive processing, and motor control. However, the precise connections and mechanisms of action require further research.
PMID:39600396 | PMC:PMC11590652 | DOI:10.2147/JPR.S470750
How Freely Moving Mind Wandering Relates to Creativity: Behavioral and Neural Evidence
Brain Sci. 2024 Nov 5;14(11):1122. doi: 10.3390/brainsci14111122.
ABSTRACT
Background: Previous studies have demonstrated that mind wandering during incubation phases enhances post-incubation creative performance. Recent empirical evidence, however, has highlighted a specific form of mind wandering closely related to creativity, termed freely moving mind wandering (FMMW). In this study, we examined the behavioral and neural associations between FMMW and creativity. Methods: We initially validated a questionnaire measuring FMMW by comparing its results with those from the Sustained Attention to Response Task (SART). Data were collected from 1316 participants who completed resting-state fMRI scans, the FMMW questionnaire, and creative tasks. Correlation analysis and Bayes factors indicated that FMMW was associated with creative thinking (AUT). To elucidate the neural mechanisms underlying the relationship between FMMW and creativity, Hidden Markov Models (HMM) were employed to analyze the temporal dynamics of the resting-state fMRI data. Results: Our findings indicated that brain dynamics associated with FMMW involve integration within multiple networks and between networks (r = -0.11, pFDR < 0.05). The links between brain dynamics associated with FMMW and creativity were mediated by FMMW (c' = 0.01, [-0.0181, -0.0029]). Conclusions: These findings demonstrate the relationship between FMMW and creativity, offering insights into the neural mechanisms underpinning this relationship.
PMID:39595885 | DOI:10.3390/brainsci14111122
Abnormal stability of dynamic functional architecture in drug-naïve children with attention-deficit/hyperactivity disorder
BMC Psychiatry. 2024 Nov 26;24(1):851. doi: 10.1186/s12888-024-06310-0.
ABSTRACT
BACKGROUND AND AIMS: Attention-deficit/hyperactivity disorder (ADHD) is most commonly diagnosed neurodevelopmental disorder in childhood, characterized by developmentally inappropriate inattention and/or hyperactivity/impulsivity symptoms. Static and dynamic functional connectivity (FC) studies have revealed brain dysfunction in ADHD. However, few studies have estimated the stability of dynamic functional architecture of children with ADHD. The present study attempted to identify the functional stability (FS) abnormalities associated with ADHD in drug-naïve children.
MATERIALS AND METHODS: The resting-state fMRI of 42 children with ADHD and 30 healthy controls (HCs) were collected. Using the sliding window approach, FS of each voxel was obtained by measuring the concordance of dynamic FC over time. Further, the seed based dynamic FC (dFC) was conducted to explore the specific brain regions with dFC alteration related to these brain regions with altered FS. Then, the inter-group comparison and correlation analysis were performed.
RESULTS: We found that children with ADHD exhibited (1) decreased FS in the bilateral superior frontal gyrus (SFG) and increased FS in the right middle temporal gyrus (MTG), which both belong to the default mode network (DMN); (2) increased dFC between the bilateral SFG of DMN and the left insula of salience networks (SN) (GRF, voxel-wise p < 0.001, cluster-wise p < 0.05); (3) decreased dFC between the right MTG and the left cerebellum posterior lobe, and (3) worse performance in the Stroop test that significantly correlate with decreased FS in the bilateral SFG (p = 0.043, FDR corrected).
CONCLUSIONS: Our findings showed that the abnormal functional architecture involved the DMN (the bilateral SFG and right MTG) and SN (left insula) regions in children with ADHD. This preliminary study provides novel insight into the dynamic brain functional networks in ADHD.
PMID:39592983 | DOI:10.1186/s12888-024-06310-0
Characterising the anxiogenic network from functional connectivity analysis of the CO<sub>2</sub> challenge model
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
Brain age prediction and deviations from normative trajectories in the neonatal connectome
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
Potential effects of peripheral neuropathy on brain function in patients with type 2 diabetes mellitus
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 Function and Structure Changes in the Prognosis Prediction of Prolonged Disorders of Consciousness
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
Abnormal hypothalamic functional connectivity and serum arousal-promoting neurotransmitters in insomnia disorder patients: a pilot study
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
Study Protocol for a Randomized Controlled Trial: Evaluating the Impact of Acupuncture on Menstrual Regulation and Pregnancy Enhancement in Patients with DOR Using Rs-fMRI to Assess Brain Functional Networks
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
Temporal complexity of the BOLD-signal in preterm versus term infants
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
Estradiol modulates resting-state connectivity in perimenopausal depression
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
Resting-State Functional Connectivity in Gelotophobes: A Neuroscientific Perspective on the Fear of Laughter
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
Aberrant intra-network resting-state functional connectivity in chronic insomnia with or without cognitive impairment
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
Chronic pain-induced functional and structural alterations in the brain: a multi-modal meta-analysis
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
Resting-state voxel-wise dynamic effective connectivity predicts risky decision-making in patients with bipolar disorder type I
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
Impact of Deprivation and Preferential Usage on Functional Connectivity Between Early Visual Cortex and Category-Selective Visual Regions
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
Altered default-mode and frontal-parietal network pattern underlie adaptiveness of emotion regulation flexibility following task-switch training
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
Processing, evaluating, and understanding FMRI data with afni_proc.py
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