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Heliyon. 2024 Apr 15;10(8):e29613. doi: 10.1016/j.heliyon.2024.e29613. eCollection 2024 Apr 30.

ABSTRACT

BACKGROUND: Previous studies have found electroacupuncture could improve the clinical symptoms of first-episode major depressive disorder (MDD), but the exact neural mechanism of action needs to be further elucidated.

METHODS: Twenty-eight first-episode MDD patients were randomly divided into 14 electro-acupuncture stimulation (EAS) groups and 14 sham-acupuncture stimulation (SAS) groups, and clinical symptoms were assessed and functional magnetic resonance imaging (fMRI) scans were done in both groups. Amplitude of low-frequency fluctuations (ALFF) was used to observe the changes between the pre-treatment and post-treatment in the two groups, and the altered brain areas were selected as region of interest (ROI) to observe the FC changes. Meanwhile, the correlation between the altered clinical symptoms and the altered ALFF and FC of brain regions in the two groups was analyzed.

RESULTS: The EAS significantly decreased the HAMD-24 and HAMA-14 scores of MDD than SAS group. The imaging results revealed that both groups were able to increase the ALFF of the left middle temporal gyrus and the left cerebellar posterior lobe. When using the left middle temporal gyrus and the left posterior cerebellar lobe as ROIs, EAS group increased the FC between the left middle temporal gyrus with the left superior frontal gyrus, the left middle frontal gyrus, and the left hippocampus, and decreased the FC between the left posterior cerebellar lobe and the left calcarine gyrus, while SAS group only increased the FC between the left middle temporal gyrus with the left superior frontal gyrus. The alternations in clinical symptoms after EAS treatment were positively correlated with the altered ALFF values in the left middle temporal gyrus and the altered FC values in the left middle temporal gyrus and the left middle frontal gyrus.

CONCLUSION: EA demonstrates modulation of functional activity in the default mode network (DMN), sensorimotor network (SMN), cognitive control network (CCN), limbic system, and visual network (VN) for the treatment of the first-episode MDD. Our findings contribute to the neuroimaging evidence for the efficacy of EAS.

PMID:38681626 | PMC:PMC11053281 | DOI:10.1016/j.heliyon.2024.e29613

Biol Psychiatry Cogn Neurosci Neuroimaging. 2024 Apr 26:S2451-9022(24)00112-5. doi: 10.1016/j.bpsc.2024.04.010. Online ahead of print.

ABSTRACT

BACKGROUND: Human healthy and pathological aging is linked to a steady decline in brain resting state activity and connectivity measures. The neurophysiological mechanisms underlying these changes remain poorly understood.

METHODS: Making use of recent developments in normative modeling and availability of in vivo maps for various neurochemical systems, we test in the UK Biobank cohort (N=25917) if and how age- and Parkinson's disease related resting state changes in commonly applied local and global activity and connectivity measures co-localize with underlying neurotransmitter systems.

RESULTS: We find the distributions of several major neurotransmitter systems including serotonergic, dopaminergic, noradrenergic, and glutamatergic neurotransmission to correlate with age-related changes as observed across functional activity and connectivity measures. Co-localization patterns in Parkinson's disease deviate from normative aging trajectories for these, as well as for cholinergic and GABAergic, neurotransmission. The deviation from normal co-localization of brain function and GABAa correlates with disease duration.

CONCLUSIONS: These findings provide new insights into molecular mechanisms underlying age- and Parkinson's related brain functional changes by extending the existing evidence elucidating the vulnerability of specific neurochemical attributes to normal aging and Parkinson's disease. The results particularly indicate that alongside dopamine and serotonin, increased vulnerability of glutamatergic, cholinergic, and GABAergic systems may also contribute to Parkinson's disease-related functional alterations. Combining normative modeling and neurotransmitter mapping may aid future research and drug development through deeper understanding of neurophysiological mechanisms underlying specific clinical conditions.

PMID:38679325 | DOI:10.1016/j.bpsc.2024.04.010

Neuroimage Clin. 2024 Apr 25;42:103610. doi: 10.1016/j.nicl.2024.103610. Online ahead of print.

ABSTRACT

Parkinson's disease (PD) is a neurodegenerative disease with cognitive as well as motor impairments. While much is known about the brain networks leading to motor impairments in PD, less is known about the brain networks contributing to cognitive impairments. Here, we leveraged resting-state functional magnetic resonance imaging (rs-fMRI) data from the Parkinson's Progression Marker Initiative (PPMI) to examine network dysfunction in PD patients with cognitive impairment. We focus on canonical cortical networks linked to cognition, including the salience network (SAL), frontoparietal network (FPN), and default mode network (DMN), as well as a subcortical basal ganglia network (BGN). We used the Montreal Cognitive Assessment (MoCA) as a continuous index of coarse cognitive function in PD. In 82 PD patients, we found that lower MoCA scores were linked with lower intra-network connectivity of the FPN. We also found that lower MoCA scores were linked with lower inter-network connectivity between the SAL and the BGN, the SAL and the DMN, as well as the FPN and the DMN. These data elucidate the relationship of cortical and subcortical functional connectivity with cognitive impairments in PD.

PMID:38677099 | DOI:10.1016/j.nicl.2024.103610

Brain Sci. 2024 Apr 12;14(4):376. doi: 10.3390/brainsci14040376.

ABSTRACT

The prediction of motor learning in Parkinson's disease (PD) is vastly understudied. Here, we investigated which clinical and neural factors predict better long-term gains after an intensive 6-week motor learning program to ameliorate micrographia. We computed a composite score of learning through principal component analysis, reflecting better writing accuracy on a tablet in single and dual task conditions. Three endpoints were studied-acquisition (pre- to post-training), retention (post-training to 6-week follow-up), and overall learning (acquisition plus retention). Baseline writing, clinical characteristics, as well as resting-state network segregation were used as predictors. We included 28 patients with PD (13 freezers and 15 non-freezers), with an average disease duration of 7 (±3.9) years. We found that worse baseline writing accuracy predicted larger gains for acquisition and overall learning. After correcting for baseline writing accuracy, we found female sex to predict better acquisition, and shorter disease duration to help retention. Additionally, absence of FOG, less severe motor symptoms, female sex, better unimanual dexterity, and better sensorimotor network segregation impacted overall learning positively. Importantly, three factors were retained in a multivariable model predicting overall learning, namely baseline accuracy, female sex, and sensorimotor network segregation. Besides the room to improve and female sex, sensorimotor network segregation seems to be a valuable measure to predict long-term motor learning potential in PD.

PMID:38672025 | DOI:10.3390/brainsci14040376

Neuroradiology. 2024 Apr 27. doi: 10.1007/s00234-024-03356-5. Online ahead of print.

ABSTRACT

PURPOSE: Previous studies have demonstrated impaired cerebellar function in patients with obstructive sleep apnea (OSA), which is associated with impaired cognition. However, the effects of OSA on resting-state functional connectivity (FC) in the cerebellum has not been determined. The purpose of this study was to investigate resting-state FC of the cerebellar subregions and its relevance to clinical symptoms in patients with OSA.

METHODS: Sixty-eight patients with OSA and seventy-two healthy controls (HCs) were included in the study. Eight subregions of the cerebellum were selected as regions of interest, and the FC values were calculated for each subregion with other voxels. A correlation analysis was performed to examine the relationship between clinical and cognitive data.

RESULTS: Patients with OSA showed higher FC in specific regions, including the right lobule VI with the right posterior middle temporal gyrus and right angular gyrus, the right Crus I with the bilateral precuneus/left superior parietal lobule, and the right Crus II with the precuneus/right posterior cingulate cortex. Furthermore, the oxygen depletion index was negatively correlated with aberrant FC between the right Crus II and the bilateral precuneus / right posterior cingulate cortex in OSA patients (p = 0.004).

CONCLUSION: The cerebellum is functionally lateralized and closely linked to the posterior default mode network. Higher FC is related to cognition, emotion, language, and sleep in OSA. Abnormal FC may offer new neuroimaging evidence and insights for a deeper comprehension of OSA-related alterations.

PMID:38671339 | DOI:10.1007/s00234-024-03356-5

Neurosci Lett. 2024 Apr 24:137790. doi: 10.1016/j.neulet.2024.137790. Online ahead of print.

ABSTRACT

OBJECTIVE: To explore degree centrality (DC) abnormalities in ischemic stroke patients and determine whether these abnormalities have potential value in understanding the pathological mechanisms of ischemic stroke patients.

METHODS: Sixteen ischemic stroke patients and 22 healthy controls (HCs) underwent resting state functional magnetic resonance imaging (rs-fMRI) scanning, and the resulting data were subjected to DC analysis. Then we conducted a correlation analysis between DC values and neuropsychological test scores, including Montreal Cognitive Assessment (MoCA)and Mini-Mental State Examination (MMSE). Finally, extracted the abnormal DC values of brain regions and defined them as features for support vector machine (SVM) analysis.

RESULTS: Compared with HCs, ischemic stroke patients showed increased DC in the bilateral supplementary motor area, and median cingulate and paracingulate gyri and decreased DC in the left postcentral gyrus, right calcarine fissure and surrounding cortex, lingual gyrus, and orbital parts of the right superior frontal gyrus and bilateral cuneus. Correlation analyses revealed that DC values in the right lingual gyrus, calcarine fissure and surrounding cortex, and orbital parts of the right superior frontal gyrus were positively correlated with the MMSE scores. The SVM classification of the DC values achieved an area under the curve (AUC) of 0.93, an accuracy of 89.47%.

CONCLUSION: Our research results indicate that ischemic stroke patients exhibit abnormalities in the global connectivity mechanisms and patterns of the brain network. These abnormal changes may provide neuroimaging evidence for stroke-related motor, visual, and cognitive impairments, contribute to a deeper comprehension of the underlying pathophysiological mechanisms implicated in ischemic stroke.

PMID:38670522 | DOI:10.1016/j.neulet.2024.137790

Int J Psychophysiol. 2024 Apr 24:112354. doi: 10.1016/j.ijpsycho.2024.112354. Online ahead of print.

ABSTRACT

Functional network connectivity (FNC) has previously been shown to distinguish patient groups from healthy controls (HC). However, the overlap across psychiatric disorders such as schizophrenia (SZ), bipolar (BP), and schizoaffective disorder (SAD) is not evident yet. This study focuses on studying the overlap across these three psychotic disorders in both dynamic and static FNC (dFNC/sFNC). We used resting-state fMRI, demographics, and clinical information from the Bipolar-Schizophrenia Network on Intermediate Phenotypes cohort (BSNIP). The data includes three groups of patients with schizophrenia (SZ, N = 181), bipolar (BP, N = 163), and schizoaffective (SAD, N = 130) and HC (N = 238) groups. After estimating each individual's dFNC, we group them into three distinct states. We evaluated two dFNC features, including occupancy rate (OCR) and distance travelled over time. Finally, the extracted features, including both sFNC and dFNC, are tested statistically across patients and HC groups. In addition, we explored the link between the clinical scores and the extracted features. We evaluated the connectivity patterns and their overlap among SZ, BP, and SAD disorders (false discovery rate or FDR corrected p < 0.05). Results showed dFNC captured unique information about overlap across disorders where all disorder groups showed similar pattern of activity in state 2. Moreover, the results showed similar patterns between SZ and SAD in state 1 which was different than BP. Finally, the distance travelled feature of SZ (average R = 0.245, p < 0.01) and combined distance travelled from all disorders was predictive of the PANSS symptoms scores (average R = 0.147, p < 0.01).

PMID:38670348 | DOI:10.1016/j.ijpsycho.2024.112354

Psychoradiology. 2022 Jun 9;2(1):32-42. doi: 10.1093/psyrad/kkac005. eCollection 2022 Mar.

ABSTRACT

Despite a growing neuroimaging literature on the pathophysiology of major depressive disorder (MDD), reproducible findings are lacking, probably reflecting mostly small sample sizes and heterogeneity in analytic approaches. To address these issues, the Depression Imaging REsearch ConsorTium (DIRECT) was launched. The REST-meta-MDD project, pooling 2428 functional brain images processed with a standardized pipeline across all participating sites, has been the first effort from DIRECT. In this review, we present an overview of the motivations, rationale, and principal findings of the studies so far from the REST-meta-MDD project. Findings from the first round of analyses of the pooled repository have included alterations in functional connectivity within the default mode network, in whole-brain topological properties, in dynamic features, and in functional lateralization. These well-powered exploratory observations have also provided the basis for future longitudinal hypothesis-driven research. Following these fruitful explorations, DIRECT has proceeded to its second stage of data sharing that seeks to examine ethnicity in brain alterations in MDD by extending the exclusive Chinese original sample to other ethnic groups through international collaborations. A state-of-the-art, surface-based preprocessing pipeline has also been introduced to improve sensitivity. Functional images from patients with bipolar disorder and schizophrenia will be included to identify shared and unique abnormalities across diagnosis boundaries. In addition, large-scale longitudinal studies targeting brain network alterations following antidepressant treatment, aggregation of diffusion tensor images, and the development of functional magnetic resonance imaging-guided neuromodulation approaches are underway. Through these endeavours, we hope to accelerate the translation of functional neuroimaging findings to clinical use, such as evaluating longitudinal effects of antidepressant medications and developing individualized neuromodulation targets, while building an open repository for the scientific community.

PMID:38665141 | PMC:PMC10917197 | DOI:10.1093/psyrad/kkac005

Schizophr Bull. 2024 Apr 26:sbae054. doi: 10.1093/schbul/sbae054. Online ahead of print.

ABSTRACT

BACKGROUND: Heterogeneity in the etiology, pathophysiology, and clinical features of schizophrenia challenges clinicians and researchers. A helpful approach could be stratifying patients according to the presence or absence of clinical features of the deficit syndrome (DS). DS is characterized by enduring and primary negative symptoms, a clinically less heterogeneous subtype of the illness, and patients with features of DS are thought to present abnormal brain network characteristics, however, this idea has received limited attention. We investigated functional brain network topology in patients displaying deficit features and those who do not.

DESIGN: We applied graph theory analytics to resting-state functional magnetic resonance imaging data of 61 antipsychotic medication-naïve first episode psychosis patients, 18 DS and 43 non-deficit schizophrenia (NDS), and 72 healthy controls (HC). We quantified small-worldness, global and nodal efficiency measures, shortest path length, nodal local efficiency, and synchronization and contrasted them among the 3 groups.

RESULTS: DS presented decreased network integration and segregation compared to HC and NDS. DS showed lower global efficiency, longer global path lengths, and lower global local efficiency. Nodal efficiency was lower and the shortest path length was longer in DS in default mode, ventral attention, dorsal attention, frontoparietal, limbic, somatomotor, and visual networks compared to HC. Compared to NDS, DS showed lower efficiency and longer shortest path length in default mode, limbic, somatomotor, and visual networks.

CONCLUSIONS: Our data supports increasing evidence, based on topological perturbations of the functional connectome, that deficit syndrome may be a distinct form of the illness.

PMID:38666705 | DOI:10.1093/schbul/sbae054

Cureus. 2024 Mar 25;16(3):e56927. doi: 10.7759/cureus.56927. eCollection 2024 Mar.

ABSTRACT

This review comprehensively explores the evolving role of neuroimaging, specifically magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS), in epilepsy research and clinical practice. Beginning with a concise overview of epilepsy, the discussion emphasizes the crucial importance of neuroimaging in diagnosing and managing this complex neurological disorder. The review delves into the applications of advanced MRI techniques, including high-field MRI, resting-state fMRI, and connectomics, highlighting their impact on refining our understanding of epilepsy's structural and functional dimensions. Additionally, it examines the integration of machine learning in the analysis of intricate neuroimaging data. Moving to the clinical domain, the review outlines the utility of neuroimaging in pre-surgical evaluations and the monitoring of treatment responses and disease progression. Despite significant strides, challenges and limitations are discussed in the routine clinical incorporation of neuroimaging. The review explores promising developments in MRI and MRS technology, potential advancements in imaging biomarkers, and the implications for personalized medicine in epilepsy management. The conclusion underscores the transformative potential of neuroimaging and advocates for continued exploration, collaboration, and technological innovation to propel the field toward a future where tailored, effective interventions improve outcomes for individuals with epilepsy.

PMID:38665706 | PMC:PMC11043648 | DOI:10.7759/cureus.56927

Psychoradiology. 2021 May 11;1(1):42-53. doi: 10.1093/psyrad/kkab003. eCollection 2021 Mar.

ABSTRACT

Resting-state fMRI (rs-fMRI) has emerged as an alternative method to study brain function in human and animal models. In humans, it has been widely used to study psychiatric disorders including schizophrenia, bipolar disorder, autism spectrum disorders, and attention deficit hyperactivity disorders. In this review, rs-fMRI and its advantages over task based fMRI, its currently used analysis methods, and its application in psychiatric disorders using different analysis methods are discussed. Finally, several limitations and challenges of rs-fMRI applications are also discussed.

PMID:38665309 | PMC:PMC10917160 | DOI:10.1093/psyrad/kkab003

Psychoradiology. 2022 Nov 24;2(4):129-145. doi: 10.1093/psyrad/kkac016. eCollection 2022 Dec.

ABSTRACT

There is considerable interest in the significance of structural and functional connections between the two brain hemispheres in terms of both normal function and in relation to psychiatric disorders. In recent years, many studies have used voxel mirrored homotopic connectivity analysis of resting state data to investigate the importance of connectivity between homotopic regions in the brain hemispheres in a range of neuropsychiatric disorders. The current review summarizes findings from these voxel mirrored homotopic connectivity studies in individuals with autism spectrum disorder, addiction, attention deficit hyperactivity disorder, anxiety and depression disorders, and schizophrenia, as well as disorders such as Alzheimer's disease, mild cognitive impairment, epilepsy, and insomnia. Overall, other than attention deficit hyperactivity disorder, studies across psychiatric disorders report decreased homotopic resting state functional connectivity in the default mode, attention, salience, sensorimotor, social cognition, visual recognition, primary visual processing, and reward networks, which are often associated with symptom severity and/or illness onset/duration. Decreased homotopic resting state functional connectivity may therefore represent a transdiagnostic marker for general psychopathology. In terms of disorder specificity, the extensive decreases in homotopic resting state functional connectivity in autism differ markedly from attention deficit hyperactivity disorder, despite both occurring during early childhood and showing extensive co-morbidity. A pattern of more posterior than anterior regions showing reductions in schizophrenia is also distinctive. Going forward, more studies are needed to elucidate the functions of these homotopic functional connections in both health and disorder and focusing on associations with general psychopathology, and not only on disorder specific symptoms.

PMID:38665271 | PMC:PMC11003433 | DOI:10.1093/psyrad/kkac016

iScience. 2024 Apr 4;27(5):109662. doi: 10.1016/j.isci.2024.109662. eCollection 2024 May 17.

ABSTRACT

Atypical perinatal sensory experience in preterm infants is thought to increase their risk of neurodevelopmental disabilities by altering the development of the sensory cortices. Here, we used resting-state fMRI data from preterm and term-born infants scanned between 32 and 48 weeks post-menstrual age to assess the effect of early ex-utero exposure on sensory cortex development. Specifically, we utilized a measure of local correlated-ness called regional homogeneity (ReHo). First, we demonstrated that the brain-wide distribution of ReHo mirrors the known gradient of cortical maturation. Next, we showed that preterm birth differentially reduces ReHo across the primary sensory cortices. Finally, exploratory analyses showed that the reduction of ReHo in the primary auditory cortex of preterm infants is related to increased risk of autism at 18 months. In sum, we show that local connectivity within sensory cortices has different developmental trajectories, is differentially affected by preterm birth, and may be associated with later neurodevelopment.

PMID:38665205 | PMC:PMC11043889 | DOI:10.1016/j.isci.2024.109662

Stat Med. 2024 Apr 25. doi: 10.1002/sim.10091. Online ahead of print.

ABSTRACT

Statistical techniques are needed to analyze data structures with complex dependencies such that clinically useful information can be extracted. Individual-specific networks, which capture dependencies in complex biological systems, are often summarized by graph-theoretical features. These features, which lend themselves to outcome modeling, can be subject to high variability due to arbitrary decisions in network inference and noise. Correlation-based adjacency matrices often need to be sparsified before meaningful graph-theoretical features can be extracted, requiring the data analysts to determine an optimal threshold. To address this issue, we propose to incorporate a flexible weighting function over the full range of possible thresholds to capture the variability of graph-theoretical features over the threshold domain. The potential of this approach, which extends concepts from functional data analysis to a graph-theoretical setting, is explored in a plasmode simulation study using real functional magnetic resonance imaging (fMRI) data from the Autism Brain Imaging Data Exchange (ABIDE) Preprocessed initiative. The simulations show that our modeling approach yields accurate estimates of the functional form of the weight function, improves inference efficiency, and achieves a comparable or reduced root mean square prediction error compared to competitor modeling approaches. This assertion holds true in settings where both complex functional forms underlie the outcome-generating process and a universal threshold value is employed. We demonstrate the practical utility of our approach by using resting-state fMRI data to predict biological age in children. Our study establishes the flexible modeling approach as a statistically principled, serious competitor to ad-hoc methods with superior performance.

PMID:38664934 | DOI:10.1002/sim.10091

AJNR Am J Neuroradiol. 2024 Apr 25. doi: 10.3174/ajnr.A8206. Online ahead of print.

ABSTRACT

BACKGROUND AND PURPOSE: Acute mountain sickness is a series of brain-centered symptoms that occur when rapidly ascending to high altitude. Predicting acute mountain sickness before high-altitude exposure is crucial for protecting susceptible individuals. The present study aimed to evaluate the feasibility of predicting acute mountain sickness after high-altitude exposure by using multimodal brain MR imaging features measured at sea level.

MATERIALS AND METHODS: We recruited 45 healthy sea-level residents who flew to the Qinghai-Tibet Plateau (3650 m). We conducted T1-weighted structural MR imaging, resting-state fMRI, and arterial spin-labeling perfusion MR imaging both at sea level and high altitude. Acute mountain sickness was diagnosed for 5 days using Lake Louise Scoring. Logistic regression with Least Absolute Shrinkage and Selection Operator logistic regression was performed for predicting acute mountain sickness using sea-level MR imaging features. We also validated the predictors by using MR images obtained at high altitude.

RESULTS: The incidence rate of acute mountain sickness was 80.0%. The model achieved an area under the receiver operating characteristic curve of 86.4% (sensitivity = 77.8%, specificity = 100.0%, and P < .001) in predicting acute mountain sickness At sea level, valid predictors included fractional amplitude of low-frequency fluctuations (fALFF) and degree centrality from resting-state fMRI, mainly distributed in the somatomotor network. We further learned that the acute mountain sickness group had lower levels of fALFF in the somatomotor network at high altitude, associated with smaller changes in CSF volume and higher Lake Louise Scoring, specifically relating to fatigue and clinical function.

CONCLUSIONS: Our study found that the somatomotor network function detected by sea-level resting-state fMRI was a crucial predictor for acute mountain sickness and further validated its pathophysiologic impact at high altitude. These findings show promise for pre-exposure prediction, particularly for individuals in need of rapid ascent, and they offer insight into the potential mechanism of acute mountain sickness.

PMID:38663991 | DOI:10.3174/ajnr.A8206

Neuron. 2024 Apr 18:S0896-6273(24)00236-8. doi: 10.1016/j.neuron.2024.03.029. Online ahead of print.

ABSTRACT

Maladaptive feeding behavior is the primary cause of modern obesity. While the causal influence of the lateral hypothalamic area (LHA) on eating behavior has been established in rodents, there is currently no primate-based evidence available on naturalistic eating behaviors. We investigated the role of LHA GABAergic (LHAGABA) neurons in eating using chemogenetics in three macaques. LHAGABA neuron activation significantly increased naturalistic goal-directed behaviors and food motivation, predominantly for palatable food. Positron emission tomography and magnetic resonance spectroscopy validated chemogenetic activation. Resting-state functional magnetic resonance imaging revealed that the functional connectivity (FC) between the LHA and frontal areas was increased, while the FC between the frontal cortices was decreased after LHAGABA neuron activation. Thus, our study elucidates the role of LHAGABA neurons in eating and obesity therapeutics for primates and humans.

PMID:38663401 | DOI:10.1016/j.neuron.2024.03.029

Eur Child Adolesc Psychiatry. 2024 Apr 25. doi: 10.1007/s00787-024-02422-w. Online ahead of print.

ABSTRACT

Impaired basic academic skills (e.g., word recognition) are common in children with Attention Deficit Hyperactivity Disorder (ADHD). The underlying neuropsychological and neural correlates of impaired Chinese reading skills in children with ADHD have not been substantially explored. Three hundred and two children with ADHD (all medication-naïve) and 105 healthy controls underwent the Chinese language skill assessment, and 175 also underwent fMRI scans (84 ADHD and 91 controls). Between-group and mediation analyses were applied to explore the interrelationships of the diagnosis of ADHD, cognitive dysfunction, and impaired reading skills. Five ADHD-related brain functional networks, including the default mode network (DMN) and the dorsal attention network (DAN), were built using predefined regions of interest. Voxel-based group-wise comparisons were performed. The ADHD group performed worse than the control group in word-level reading ability tests, with lower scores in Chinese character recognition (CR) and word chains (WS) (all P < 0.05). With full-scale IQ and sustained attention in the mediation model, the direct effect of ADHD status on the CR score became insignificant (P = 0.066). The underlying neural correlates for the orthographic knowledge (OT) and CR differed between the ADHD and the control group. The ADHD group tended to recruit more DMN regions to maintain their reading performance, while the control group seemed to utilize more DAN regions. Children with ADHD generally presented impaired word-level reading skills, which might be caused by impaired sustained attention and lower IQ. According to the brain functional results, we infer that ADHD children might utilize a different strategy to maintain their orthographic knowledge and character recognition performance.

PMID:38662058 | DOI:10.1007/s00787-024-02422-w

iScience. 2024 Mar 28;27(5):109617. doi: 10.1016/j.isci.2024.109617. eCollection 2024 May 17.

ABSTRACT

Long-term manned spaceflight and extraterrestrial planet settlement become the focus of space powers. However, the potential influence of closed and socially isolating spaceflight on the brain function remains unclear. A 180-day controlled ecological life support system integrated experiment was conducted, establishing a spaceflight analog environment to explore the effect of long-term socially isolating living. Three crewmembers were enrolled and underwent resting-state fMRI scanning before and after the experiment. We performed both seed-based and network-based analyses to investigate the functional connectivity (FC) changes of the default mode network (DMN), considering its key role in multiple higher-order cognitive functions. Compared with normal controls, the leader of crewmembers exhibited significantly reduced within-DMN and between-DMN FC after the experiment, while two others exhibited opposite trends. Moreover, individual differences of FC changes were further supported by evidence from behavioral analyses. The findings may shed new light on the development of psychological protection for space exploration.

PMID:38660401 | PMC:PMC11039341 | DOI:10.1016/j.isci.2024.109617

Int J Clin Health Psychol. 2024 Apr-Jun;24(2):100459. doi: 10.1016/j.ijchp.2024.100459. Epub 2024 Apr 20.

ABSTRACT

BACKGROUND: Individuals with subclinical depression are prone to major depression and experience emotional responses and attentional biases to negative stimuli.

METHOD: In a randomized controlled study (N = 42) using functional magnetic resonance imaging (fMRI), we examined the neurocognitive mechanisms behind mindfulness-based cognitive therapy (MBCT) combining loving-kindness meditation (LKM) on a group with subclinical depression compared with the relaxation group across emotional face n-back (EFNBACK) tasks and resting state. We also collected behavioral and self-reported data to confirm neurocognitive results.

RESULTS: During EFNBACK, the MBCT+LKM group showed greater activation in the left lingual gyrus and right inferior lateral occipital cortex. During rest, the MBCT+LKM group demonstrated increased connectivity of the anterior cingulate cortex and right inferior lateral occipital cortex, right anterior insula and left precentral gyrus. From amplitude of low frequency fluctuation (ALFF) data, activity in brain regions associated with cognitive control decreased and activity in brain regions associated with sensorimotor increased.

CONCLUSION: These results suggest that MBCT+LKM alleviate depression for subclinical individuals through improving executive function when they face negative stimuli.

PMID:38660392 | PMC:PMC11039314 | DOI:10.1016/j.ijchp.2024.100459

BMC Psychiatry. 2024 Apr 24;24(1):313. doi: 10.1186/s12888-024-05777-1.

ABSTRACT

BACKGROUND: Distinguishing untreated major depressive disorder without medication (MDD) from schizophrenia with depressed mood (SZDM) poses a clinical challenge. This study aims to investigate differences in fractional amplitude of low-frequency fluctuations (fALFF) and cognition in untreated MDD and SZDM patients.

METHODS: The study included 42 untreated MDD cases, 30 SZDM patients, and 46 healthy controls (HC). Cognitive assessment utilized the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Resting-state functional magnetic resonance imaging (rs-fMRI) scans were conducted, and data were processed using fALFF in slow-4 and slow-5 bands.

RESULTS: Significant fALFF changes were observed in four brain regions across MDD, SZDM, and HC groups for both slow-4 and slow-5 fALFF. Compared to SZDM, the MDD group showed increased slow-5 fALFF in the right gyrus rectus (RGR). Relative to HC, SZDM exhibited decreased slow-5 fALFF in the left gyrus rectus (LGR) and increased slow-5 fALFF in the right putamen. Changes in slow-5 fALFF in both RGR and LGR were negatively correlated with RBANS scores. No significant correlations were found between remaining fALFF (slow-4 and slow-5 bands) and RBANS scores in MDD or SZDM groups.

CONCLUSIONS: Alterations in slow-5 fALFF in RGR may serve as potential biomarkers for distinguishing MDD from SZDM, providing preliminary insights into the neural mechanisms of cognitive function in schizophrenia.

PMID:38658896 | DOI:10.1186/s12888-024-05777-1