Most recent paper

Resting-State Brain Variability in Youth With Attention-Deficit/Hyperactivity Disorder

Fri, 07/29/2022 - 18:00

Front Psychiatry. 2022 Jul 12;13:918700. doi: 10.3389/fpsyt.2022.918700. eCollection 2022.


In this study, we sought to determine the nature of the abnormality in resting-state default mode network (DMN) activation and explore its correlation with functional connectivity in attention-deficit/hyperactivity disorder (ADHD). We obtained resting-state functional magnetic resonance images of youth with ADHD and typically developing counterparts from the publicly available ADHD-200 database. We used data from Peking University (232 scans) and New York University (172 scans); the scan repetition time was 2 s for both data collection sites. We applied generalized estimating equations to estimate the variability of the averaged blood-oxygen-level-dependent (BOLD) time series extracted from the DMN at rest. We performed network-based statistics to determine the association between the observed differences in BOLD signal variability and altered functional connectivity. We analyzed data from 105 youth with ADHD (age: mean 12.17, standard deviation 2.31, median 12.25; 15.2% female, 84.8% male) and 140 typically developing youth (age: mean 11.99, standard deviation 2.28, median 11.85; 47.1% female, 52.9% male), who aged 7-17 years. The imaging data were cross-sectionally collected for each participant at one time point. We observed a greater number of significant BOLD signal changes and higher-order polynomial significant associations in youth with ADHD. Moreover, there were significant between-group differences in BOLD signal change after the first 140 s, which coincided with decreased resting-state functional connectivity within the DMN in youth with ADHD. Increased variability of neural signaling was intermittently observed in the brains of youth with ADHD at rest, thereby indicating their default mode state was more unstable than that of typically developing youth.

PMID:35903637 | PMC:PMC9322108 | DOI:10.3389/fpsyt.2022.918700

Abnormal Dynamic Functional Connectivity of the Left Rostral Hippocampus in Predicting Antidepressant Efficacy in Major Depressive Disorder

Fri, 07/29/2022 - 18:00

Psychiatry Investig. 2022 Jul;19(7):562-569. doi: 10.30773/pi.2021.0386. Epub 2022 Jul 21.


OBJECTIVE: Some pharmacological treatments are ineffective in parts of patients with major depressive disorder (MDD), hence this needs prediction of effective treatment responses. The study aims to examine the relationship between dynamic functional connectivity (dFC) of the hippocampal subregion and antidepressant improvement of MDD patients and to estimate the capability of dFC to predict antidepressant efficacy.

METHODS: The data were from 70 MDD patients and 43 healthy controls (HC); the dFC of hippocampal subregions was estimated by sliding-window approach based on resting-state functional magnetic resonance imaging (R-fMRI). After 3 months treatment, 36 patients underwent second R-fMRI scan and were then divided into the response group and non-response group according to clinical responses.

RESULTS: The result manifested that MDD patients exhibited lower mean dFC of the left rostral hippocampus (rHipp.l) compared with HC. After 3 months therapy, the response group showed lower dFC of rHipp.l compared with the non-response group. The dFC of rHipp.l was also negatively correlated with the reduction rate of Hamilton Depression Rating Scale.

CONCLUSION: These findings highlighted the importance of rHipp in MDD from the dFC perspective. Detection and estimation of these changes might demonstrate helpful for comprehending the pathophysiological mechanism and for assessment of treatment reaction of MDD.

PMID:35903058 | DOI:10.30773/pi.2021.0386

Arousal and salience network connectivity alterations in surgical temporal lobe epilepsy

Thu, 07/28/2022 - 18:00

J Neurosurg. 2022 Jul 8:1-11. doi: 10.3171/2022.5.JNS22837. Online ahead of print.


OBJECTIVE: It is poorly understood why patients with mesial temporal lobe epilepsy (TLE) have cognitive deficits and brain network changes that extend beyond the temporal lobe, including altered extratemporal intrinsic connectivity networks (ICNs). However, subcortical arousal structures project broadly to the neocortex, are affected by TLE, and thus may contribute to these widespread network effects. The authors' objective was to examine functional connectivity (FC) patterns between subcortical arousal structures and neocortical ICNs, possible neurocognitive relationships, and FC changes after epilepsy surgery.

METHODS: The authors obtained resting-state functional magnetic resonance imaging (fMRI) in 50 adults with TLE and 50 controls. They compared nondirected FC (correlation) and directed FC (Granger causality laterality index) within the salience network, default mode network, and central executive network, as well as between subcortical arousal structures; these 3 ICNs were also compared between patients and controls. They also used an fMRI-based vigilance index to relate alertness to arousal center FC. Finally, fMRI was repeated in 29 patients > 12 months after temporal lobe resection.

RESULTS: Nondirected FC within the salience (p = 0.042) and default mode (p = 0.0008) networks, but not the central executive network (p = 0.79), was decreased in patients in comparison with controls (t-tests, corrected). Nondirected FC between the salience network and subcortical arousal structures (nucleus basalis of Meynert, thalamic centromedian nucleus, and brainstem pedunculopontine nucleus) was reduced in patients in comparison with controls (p = 0.0028-0.015, t-tests, corrected), and some of these connectivity abnormalities were associated with lower processing speed index, verbal comprehension, and full-scale IQ. Interestingly, directed connectivity measures suggested a loss of top-down influence from the salience network to the arousal nuclei in patients. After resection, certain FC patterns between the arousal nuclei and salience network moved toward control values in the patients, suggesting that some postoperative recovery may be possible. Although an fMRI-based vigilance measure suggested that patients exhibited reduced alertness over time, FC abnormalities between the salience network and arousal structures were not influenced by the alertness levels during the scans.

CONCLUSIONS: FC abnormalities between subcortical arousal structures and ICNs, such as the salience network, may be related to certain neurocognitive deficits in TLE patients. Although TLE patients demonstrated vigilance abnormalities, baseline FC perturbations between the arousal and salience networks are unlikely to be driven solely by alertness level, and some may improve after surgery. Examination of the arousal network and ICN disturbances may improve our understanding of the downstream clinical effects of TLE.

PMID:35901709 | DOI:10.3171/2022.5.JNS22837

Transcriptional substrates underlying functional connectivity profiles of subregions within the human sensorimotor cortex

Thu, 07/28/2022 - 18:00

Hum Brain Mapp. 2022 Jul 27. doi: 10.1002/hbm.26031. Online ahead of print.


The human sensorimotor cortex has multiple subregions showing functional commonalities and differences, likely attributable to their connectivity profiles. However, the molecular substrates underlying such connectivity profiles are unclear. Here, transcriptome-neuroimaging spatial correlation analyses were performed between transcriptomic data from the Allen human brain atlas and resting-state functional connectivity (rsFC) of 24 fine-grained sensorimotor subregions from 793 healthy subjects. Results showed that rsFC of six sensorimotor subregions were associated with expression measures of six gene sets that were specifically expressed in brain tissue. These sensorimotor subregions could be classified into the polygenic- and oligogenic-modulated subregions, whose rsFC were related to gene sets diverging on their numbers (hundreds vs. dozens) and functional characteristics. First, the former were specifically expressed in multiple types of neurons and immune cells, yet the latter were not specifically expressed in any cortical cell types. Second, the former were preferentially expressed during the middle and late stages of cortical development, while the latter showed no preferential expression during any stages. Third, the former were prone to be enriched for general biological functions and pathways, but the latter for specialized biological functions and pathways. Fourth, the former were enriched for neuropsychiatric disorders, whereas this enrichment was absent for the latter. Finally, although the identified genes were commonly associated with sensorimotor behavioral processes, the polygenic-modulated subregions associated genes were additionally related to vision and dementia. These findings may advance our understanding of the functional homogeneity and heterogeneity of the human sensorimotor cortex from the perspective of underlying genetic architecture.

PMID:35899321 | DOI:10.1002/hbm.26031

The Structured Mind at Rest: Low-Frequency Oscillations Reflect Interactive Dynamics Between Spontaneous Brain Activity and a Common Architecture for Task Control

Thu, 07/28/2022 - 18:00

Front Neurosci. 2022 Jul 11;16:832503. doi: 10.3389/fnins.2022.832503. eCollection 2022.


The Common Model of Cognition (CMC) has been proposed as a high level framework through which functional neuroimaging data can be predicted and interpreted. Previous work has found the CMC is capable of predicting brain activity across a variety of tasks, but it has not been tested on resting state data. This paper adapts a previously used method for comparing theoretical models of brain structure, Dynamic Causal Modeling, for the task-free environment of resting state, and compares the CMC against six alternate architectural frameworks while also separately modeling spontaneous low-frequency oscillations. For a large sample of subjects from the Human Connectome Project, the CMC provides the best account of resting state brain activity, suggesting the presence of a general purpose structure of connections in the brain that drives activity when at rest and when performing directed task behavior. At the same time, spontaneous brain activity was found to be present and significant across all frequencies and in all regions. Together, these results suggest that, at rest, spontaneous low-frequency oscillations interact with the general cognitive architecture for task-based activity. The possible functional implications of these findings are discussed.

PMID:35898414 | PMC:PMC9309720 | DOI:10.3389/fnins.2022.832503

Functional connectivity with medial temporal regions differs across cultures during post-encoding rest

Wed, 07/27/2022 - 18:00

Cogn Affect Behav Neurosci. 2022 Jul 27. doi: 10.3758/s13415-022-01027-7. Online ahead of print.


Connectivity of the brain at rest can reflect individual differences and impact behavioral outcomes, including memory. The present study investigated how culture influences functional connectivity with regions of the medial temporal lobe. In this study, 46 Americans and 59 East Asians completed a resting state scan after encoding pictures of objects. To investigate cross-cultural differences in resting state functional connectivity, left parahippocampal gyrus (anterior and posterior regions) and left hippocampus were selected as seed regions. These regions were selected, because they were previously implicated in a study of cultural differences during the successful encoding of detailed memories. Results revealed that left posterior parahippocampal gyrus had stronger connectivity with temporo-occipital regions for East Asians compared with Americans and stronger connectivity with parieto-occipital regions for Americans compared with East Asians. Left anterior parahippocampal gyrus had stronger connectivity with temporal regions for East Asians than Americans and stronger connectivity with frontal regions for Americans than East Asians. Although connectivity did not relate to memory performance, patterns did relate to cultural values. The degree of independent self-construal and subjective value of tradition were associated with functional connectivity involving left anterior parahippocampal gyrus. Findings are discussed in terms of potential cultural differences in memory consolidation or more general trait or state-based processes, such as holistic versus analytic processing.

PMID:35896854 | DOI:10.3758/s13415-022-01027-7

Adolescent depression and resting-state fMRI brain networks: a scoping review of longitudinal studies

Wed, 07/27/2022 - 18:00

Braz J Psychiatry. 2022 Jul 26. doi: 10.47626/1516-4446-2021-2032. Online ahead of print.


The neurobiological factors associated with the emergence of major depressive disorder (MDD) in adolescence are still unclear. Previous cross-sectional studies have documented aberrant connectivity in resting-state functional magnetic resonance imaging (rs-fMRI) networks. However, whether these findings precede MDD onset has not been established. This scoping review mapped key methodological aspects and main findings of longitudinal rs-fMRI studies of MDD in adolescence. Three sets of neuroimaging methods to analyze rs-fMRI data were identified: seed-based analysis, independent component analysis, and network-based approaches. Main findings involved aberrant connectivity within and between the default mode network (DMN), the cognitive control network (CCN), and the salience network (SN). Accordingly, we utilized Menon's (2011) triple-network model for neuropsychiatric disorders to summarize key results. Adolescent MDD was associated with hyperconnectivity within the SN and between DMN and SN, as well as hypoconectivity within the CCN. These findings suggested that dysfunctional connectivity among the three main large-scale brain networks preceded MDD onset. However, there was high heterogeneity in neuroimaging methods and sampling procedures, which may limit comparisons between studies. Future studies should consider some level of harmonization for clinical instruments and neuroimaging methods.

PMID:35896034 | DOI:10.47626/1516-4446-2021-2032

Brain Functional Connectivity in Low- and High-Grade Gliomas: Differences in Network Dynamics Associated with Tumor Grade and Location

Wed, 07/27/2022 - 18:00

Cancers (Basel). 2022 Jul 8;14(14):3327. doi: 10.3390/cancers14143327.


Brain tumors lead to modifications of brain networks. Graph theory plays an important role in clarifying the principles of brain connectivity. Our objective was to investigate network modifications related to tumor grade and location using resting-state functional magnetic resonance imaging (fMRI) and graph theory. We retrospectively studied 30 low-grade (LGG), 30 high-grade (HGG) left-hemispheric glioma patients and 20 healthy controls (HC) with rs-fMRI. Tumor location was labeled as: frontal, temporal, parietal, insular or occipital. We collected patients' clinical data from records. We analyzed whole-brain and hemispheric networks in all patients and HC. Subsequently, we studied lobar networks in subgroups of patients divided by tumor location. Seven graph-theoretical metrics were calculated (FDR p < 0.05). Connectograms were computed for significant nodes. The two-tailed Student t-test or Mann-Whitney U-test (p < 0.05) were used to compare graph metrics and clinical data. The hemispheric network analysis showed increased ipsilateral connectivity for LGG (global efficiency p = 0.03) and decreased contralateral connectivity for HGG (degree/cost p = 0.028). Frontal and temporal tumors showed bilateral modifications; parietal and insular tumors showed only local effects. Temporal tumors led to a bilateral decrease in all graph metrics. Tumor grade and location influence the pattern of network reorganization. LGG may show more favorable network changes than HGG, reflecting fewer clinical deficits.

PMID:35884387 | DOI:10.3390/cancers14143327

Modes of cognition: evidence from metastable brain dynamics

Tue, 07/26/2022 - 18:00

Neuroimage. 2022 Jul 23:119489. doi: 10.1016/j.neuroimage.2022.119489. Online ahead of print.


Managing cognitive load depends on adequate resource allocation by the human brain through the engagement of metastable substates, which are large-scale functional networks that change over time. We employed a novel analysis method, deep autoencoder dynamical analysis (DADA), with 100 healthy adults selected from the Human Connectome Project (HCP) data set in rest and six cognitive tasks. The deep autoencoder of DADA described seven recurrent stochastic metastable substates from the functional connectome of BOLD phase coherence matrices. These substates were significantly differentiated in terms of their probability of appearance, time duration, and spatial attributes. We found that during different cognitive tasks, there was a higher probability of having more connected substates dominated by a high degree of connectivity in the thalamus. In addition, compared with those during tasks, resting brain dynamics have a lower level of predictability, indicating a more uniform distribution of metastability between substates, quantified by higher entropy. These novel findings provide empirical evidence for the philosophically motivated cognitive theory, suggesting on-line and off-line as two fundamentally distinct modes of cognition. On-line cognition refers to task-dependent engagement with the sensory input, while off-line cognition is a slower, environmentally detached mode engaged with decision and planning. Overall, the DADA framework provides a bridge between neuroscience and cognitive theory that can be further explored in the future.

PMID:35882268 | DOI:10.1016/j.neuroimage.2022.119489

Resting-state functional MRI for motor cortex mapping in childhood-onset focal epilepsy

Tue, 07/26/2022 - 18:00

J Neuroimaging. 2022 Jul 26. doi: 10.1111/jon.13030. Online ahead of print.


BACKGROUND AND PURPOSE: Task-based functional MRI (fMRI) mapping of the motor function prior to epilepsy surgery has limitations in children with epilepsy. We present a data-driven method to automatically delineate the motor cortex using task-free, resting-state fMRI (rsfMRI) data.

METHODS: We used whole-brain rsfMRI for independent component analysis (ICA). A template matching process with Discriminability Index-based Component Identification score was used for each participant to select and combine motor ICA components in their native brain space, resulting in a whole-brain ICA Motor Map (wIMM). We validated wIMM by comparing individual results with bilateral finger-tapping motor task fMRI activation, and evaluated its reproducibility in controls.

RESULTS: Data from 64 patients and 12 controls were used to generate group wIMM maps. The hit rate between wIMM and motor task activation ranged from 60% to 79% across all participants. Sensitivity of wIMM for capturing the task activation peak was 87.5% among 32 patients and 100% in 12 controls with available motor task results. We also showed high similarity in repeated runs in controls.

CONCLUSIONS: Our results show the sensitivity and reproducibility of an automated motor mapping method based on ICA analysis of rsfMRI in children with epilepsy. The ICA maps may provide different, but useful, information than task fMRI. Future studies will expand our method to mapping other brain functions, and may lead to a surgical planning tool for patients who cannot perform task fMRI and help predict their postsurgical function.

PMID:35881496 | DOI:10.1111/jon.13030

Effect of acupuncture on hypothalamic functional connectivity in patients with premature ova-rian insufficiency based on resting-state functional magnetic resonance imaging

Tue, 07/26/2022 - 18:00

Zhen Ci Yan Jiu. 2022 Jul 25;47(7):617-24. doi: 10.13702/j.1000-0607.20210399.


OBJECTIVE: To compare the differences in functional connectivity(FC) between the hypothalamus and whole brain regions in patients with premature ovarian insufficiency (POI) and healthy volunteers based on resting-state functional magnetic resonance imaging (rs-fMRI) and investigate the mechanism of acupuncture on treatment of POI.

METHODS: Twelve POI patients were recruited to the acupuncture group and 12 healthy volunteers to the control group. Patients in the acupuncture group received acupuncture at two groups of acupoints alternatively, including Baihui (GV20), Zhongwan (CV12), Shenting (GV24), Shenshu (BL23), Ciliao(BL32) and so on, 30 min once time, 3 times per week for 12 weeks. The state of patients was evaluated by modified Kupperman Index (KI) and self-rating anxiety scale (SAS). Follicle-stimulating hormone (FSH), luteinizing hormone (LH), estradiol (E2), and anti-mullerian hormone (AMH) were tested by microparticle-based chemiluminescence. B ultrasonography was used to detect the antral follicle count (AFC). Meanwhile, POI patients and healthy volunteers underwent the rs-fMRI examination before and after acupuncture treatment and after enrollment, respectively. With hypothalamus as the region of interest, the differences in FC between the hypothalamus and other brain regions in POI patients and healthy volunteers and the changes of FC between the hypothalamus and whole brain regions in POI patients before and after acupuncture were observed.

RESULTS: The SAS and KI scores of pre-treatment POI patients were higher than those in the control group (P<0.01).In compa-rison with those pre-treatment, FSH, LH, and SAS and KI scores of POI patients decreased after treatment, while AFC increased (P<0.05). Compared with the control group, the FC of the left hypothalamus with left central sulcus, right middle occipital gyrus, and left paracentral lobule increased, but decreased with left globus pallidus of the lenticular nucleus in POI patients. Furthermore, the FC of the right hypothalamus with the left hippocampus, the left para-central lobule, and the right central sulcus increased, while the FC between the right hypothalamus and the right superior frontal gyrus decreased (P<0.05). For the acupuncture group, compared with the conditions before treatment, the FC of the right hypothalamus with the left inferior frontal gyrus, the left insula, and right inferior frontal gyrus was strengthened, but weakened with the left gyrus rectus (P<0.05).

CONCLUSION: The abnormal FC between the hypothalamus and whole brain regions may be one of the central pathological factors of POI. Acupuncture can improve the ovarian function and clinical symptoms of patients with POI, which may be related to its effect in regulating the FC between the hypothalamus and multiple brain regions.

PMID:35880279 | DOI:10.13702/j.1000-0607.20210399

Altered resting-state functional connectivity within corticostriatal and subcortical-striatal circuits in chronic pain

Mon, 07/25/2022 - 18:00

Sci Rep. 2022 Jul 25;12(1):12683. doi: 10.1038/s41598-022-16835-7.


Brain corticostriatal circuits are important for understanding chronic pain and highly relevant to motivation and cognitive processes. It has been demonstrated that in patients with chronic back pain, altered nucleus accumbens (NAcc)-medial prefrontal cortex (MPFC) circuit fMRI-based activity is predictive of patient outcome. We evaluated the NAcc-MPFC circuit in patients with another chronic pain condition, fibromyalgia, to extend these important findings. First, we compared fMRI-based NAcc-MPFC resting-state functional connectivity in patients with fibromyalgia (N = 32) vs. healthy controls (N = 37). Compared to controls, the NAcc-MPFC circuit's connectivity was significantly reduced in fibromyalgia. In addition, within the fibromyalgia group, NAcc-MPFC connectivity was significantly correlated with trait anxiety. Our expanded connectivity analysis of the NAcc to subcortical brain regions showed reduced connectivity of the right NAcc with mesolimbic circuit regions (putamen, thalamus, and ventral pallidum) in fibromyalgia. Lastly, in an exploratory analysis comparing our fibromyalgia and healthy control cohorts to a separate publicly available dataset from patients with chronic back pain, we identified reduced NAcc-MPFC connectivity across both the patient groups with unique alterations in NAcc-mesolimbic connectivity. Together, expanding upon prior observed alterations in brain corticostriatal circuits, our results provide novel evidence of altered corticostriatal and mesolimbic circuits in chronic pain.

PMID:35879602 | DOI:10.1038/s41598-022-16835-7

The Spatiotemporal Dynamics of Cerebral Autoregulation in Functional Magnetic Resonance Imaging

Mon, 07/25/2022 - 18:00

Front Neurosci. 2022 Jul 8;16:795683. doi: 10.3389/fnins.2022.795683. eCollection 2022.


The thigh-cuff release (TCR) maneuver is a physiological challenge that is widely used to assess dynamic cerebral autoregulation (dCA). It is often applied in conjunction with Transcranial Doppler ultrasound (TCD), which provides temporal information of the global flow response in the brain. This established method can only yield very limited insights into the regional variability of dCA, whereas functional MRI (fMRI) has the ability to reveal the spatial distribution of flow responses in the brain with high spatial resolution. The aim of this study was to use whole-brain blood-oxygenation-level-dependent (BOLD) fMRI to characterize the spatiotemporal dynamics of the flow response to the TCR challenge, and thus pave the way toward mapping dCA in the brain. We used a data driven approach to derive a novel basis set that was then used to provide a voxel-wise estimate of the TCR associated haemodynamic response function (HRF TCR ). We found that the HRF TCR evolves with a specific spatiotemporal pattern, with gray and white matter showing an asynchronous response, which likely reflects the anatomical structure of cerebral blood supply. Thus, we propose that TCR challenge fMRI is a promising method for mapping spatial variability in dCA, which will likely prove to be clinically advantageous.

PMID:35873811 | PMC:PMC9304653 | DOI:10.3389/fnins.2022.795683

Convolutional Recurrent Neural Network for Dynamic Functional MRI Analysis and Brain Disease Identification

Mon, 07/25/2022 - 18:00

Front Neurosci. 2022 Jul 6;16:933660. doi: 10.3389/fnins.2022.933660. eCollection 2022.


Dynamic functional connectivity (dFC) networks derived from resting-state functional magnetic resonance imaging (rs-fMRI) help us understand fundamental dynamic characteristics of human brains, thereby providing an efficient solution for automated identification of brain diseases, such as Alzheimer's disease (AD) and its prodromal stage. Existing studies have applied deep learning methods to dFC network analysis and achieved good performance compared with traditional machine learning methods. However, they seldom take advantage of sequential information conveyed in dFC networks that could be informative to improve the diagnosis performance. In this paper, we propose a convolutional recurrent neural network (CRNN) for automated brain disease classification with rs-fMRI data. Specifically, we first construct dFC networks from rs-fMRI data using a sliding window strategy. Then, we employ three convolutional layers and long short-term memory (LSTM) layer to extract high-level features of dFC networks and also preserve the sequential information of extracted features, followed by three fully connected layers for brain disease classification. Experimental results on 174 subjects with 563 rs-fMRI scans from the Alzheimer's Disease Neuroimaging Initiative (ADNI) demonstrate the effectiveness of our proposed method in binary and multi-category classification tasks.

PMID:35873806 | PMC:PMC9298744 | DOI:10.3389/fnins.2022.933660

Altered Functional Connectivity and Topological Organization of Brain Networks Correlate to Cognitive Impairments After Sleep Deprivation

Mon, 07/25/2022 - 18:00

Nat Sci Sleep. 2022 Jul 15;14:1285-1297. doi: 10.2147/NSS.S366224. eCollection 2022.


INTRODUCTION: Sleep deprivation (SD) has a detrimental effect on cognitive functions. Numerous studies have indicated the mechanisms underlying cognitive impairments after SD in brain networks. However, the findings based on the functional connectivity (FC) and topological architecture of brain networks are inconsistent.

METHODS: In this study, we recruited 30 healthy participants with regular sleep (aged 25.20 ± 2.20 years). All participants performed the repeatable battery for the assessment of neuropsychological status and resting-state fMRI scans twice, during the rested wakefulness (RW) state and after 24 h of total SD. Using the Dosenbach atlas, both large-scale FC and topological features of brain networks (ie nodal, global and local efficiency) were calculated for the RW and SD states. Furthermore, the correlation analysis was conducted to explore the relationship between the changes in FC and topological features of brain networks and cognitive performances.

RESULTS: Compared to the RW state, the large-scale brain network results showed decreased between-network FC in somatomotor network (SMN)-default mode network (DMN), SMN-frontoparietal network (FPN), and SMN-ventral attention network (VAN), and increased between-network FC in the dorsal attention network (DAN)-VAN, DAN-SMN after SD. The clustering coefficient, characteristic path length and local efficiency decreased after SD. Moreover, the decreased attention score positively correlated with the decreased topological measures and negatively correlated with the FC of DAN-SMN.

CONCLUSION: Our results suggested that the increased FC of DAN-SMN and decreased topological features of brain networks may act as neural indicators for the decrease in attention after SD.

CLINICAL TRIAL REGISTRATION: The study was registered at the Chinese Clinical Trial Registry, registration ID: ChiCTR2000039858, China.

PMID:35873714 | PMC:PMC9296880 | DOI:10.2147/NSS.S366224

Feasibility and positive effects of scalp acupuncture for modulating motor and cerebral activity in Parkinson's disease: A pilot study

Sun, 07/24/2022 - 18:00

NeuroRehabilitation. 2022 Jul 19. doi: 10.3233/NRE-220048. Online ahead of print.


BACKGROUND: A variety of acupuncture therapies have shown efficacy in Parkinson's disease (PD).

OBJECTIVE: To evaluate scalp acupuncture (SA) effects on motor and cerebral activity by using gait equipment and resting-state functional magnetic resonance imaging (rs-fMRI).

METHODS: Twelve patients with PD received SA. They underwent the first functional-imaging scan after tactile stimulation and the second scan following needle removal. Gait test and local sensation assessment were performed immediately after each functional scan. Gait parameter differences between pre- and post-SA were analyzed using a paired t-test and altered brain areas in degree centrality (DC) and fractional amplitude of low-frequency fluctuation (fALFF) were identified between the two scans.

RESULTS: Eight patients completed the experiment. Stride length, maximum ankle height, maximum ankle horizontal displacement, gait speed, and range of shank motion significantly increased post-treatment (P < 0.05). fALFF in left middle frontal gyrus and DC in left cerebellum (corrected) increased, while fALFF in left inferior parietal lobule (corrected) during SA decreased, compared with those in tactile stimulation. A positive correlation was observed between right limb swings and both fALFF areas.

CONCLUSIONS: Differences in gait and brain analyses presented modulation to motor and brain activity in PD, thus, providing preliminary evidence for SA efficacy.

PMID:35871374 | DOI:10.3233/NRE-220048

Inflammation Disrupts Cognitive Integrity via Plasma Neurofilament Light Chain Coupling Brain Networks in Alzheimer's Disease

Sun, 07/24/2022 - 18:00

J Alzheimers Dis. 2022 Jul 20. doi: 10.3233/JAD-220475. Online ahead of print.


OBJECTIVE: Background: Plasma neurofilament light chain (NFL) is a recognized biomarker for Alzheimer's disease (AD) and inflammation. Intrinsically organized default mode network core subsystem and frontoparietal network (FPN) and their interactions support complex cognitive function. The present study investigated the inflammatory effect on cognitive integrity via plasma NFL coupling internetwork interactions in AD.

OBJECTIVE: Objective: This study investigates the hypothesis that inflammation-related plasma NFL could affect the interactions of the core subsystem and FPN, which leads to the aggravation of the clinical symptoms of AD-spectrum patients.

OBJECTIVE: Methods: A total of 112 AD-spectrum participants underwent complete resting-state fMRI, neuropsychological tests, and plasma NFL at baseline (n = 112) and after approximately 17 months of follow-up (n = 112). The specific intersystem changes in the core subsystem and FPN were calculated and compared across groups. Then, the classifications of different AD-spectrum groups were analyzed using the association of plasma NFL and the changed intersystem interacting regions. Finally, mediation analysis was applied to investigate the significance of plasma NFL coupling networks on cognitive impairments in these subjects.

OBJECTIVE: Results: Discrimination of disease-related interactions of the core subsystem and FPN was found in AD-spectrum patients, which was the neural circuit fundamental to plasma NFL disrupting cognitive integrity. Furthermore, the clinical significance of plasma NFL coupling networks on AD identification and monitoring cognitive impairments were revealed in these subjects.

CONCLUSION: The characteristic change in inflammation-related plasma NFL coupled with brain internetwork interactions could be used as a potential observation indicator in the progression of AD patients.

PMID:35871350 | DOI:10.3233/JAD-220475

Identifying neuroimaging biomarkers for psychogenic erectile dysfunction by fusing multi-level brain information: a resting-state fMRI study

Sat, 07/23/2022 - 18:00

Andrology. 2022 Jul 23. doi: 10.1111/andr.13238. Online ahead of print.


BACKGROUND: Psychogenic erectile dysfunction (pED) patients who are under their 40s in China consist of a major component of erectile dysfunction. Existing neuroimaging studies have demonstrated that pED is a functional disorder with aberrant neural representations on the local level, the regional level, and the global level respectively. Therefore, it is reasonable to incorporate brain information from all these levels simultaneously into consideration when identifying neuroimaging biomarkers for pED. However, no such endeavors have been made in previous studies to fully disclose the central mechanism of pED.

METHOD: To incorporate multi-level brain features to fully explore the neural representation of pED, a novel machine learning framework was proposed in the current study. Specifically, we used amplitude of low frequency fluctuation, regional homogeneity, and degree centrality as indices for local, regional, and global brain activity respectively. A fully data-driven method, i.e., support vector machine (SVM) recursive feature elimination analyses, was used to investigate discriminative brain map between 48 pED patients and 39 healthy control subjects for resting state functional magnetic resonance imaging (rs-fMRI) data.

RESULTS: By fusing multi-level brain features, our method led to a superb classification accuracy of 95.12% between two groups. Interestingly, the right anterior cingulate gyrus and the left precuneus showed abnormal representations at different levels simultaneously in pED patients, which also explicated highest discriminative power between groups. Moreover, the right insular, the left fusiform gyrus, the right inferior temporal gyrus, the right superior frontal gyrus, the right precentral gyrus, the bilateral 0parahippocampal gyrus, and the bilateral inferior frontal gyrus were discriminative for pED. Also, correlation analysis explicated that several core brain regions were associated with the clinical manifestations in pED patients.

CONCLUSION: This is one of the first study investigating brain alterations on different levels simultaneously in pED patients. Our results suggested that pED involves multi-level aberrant brain representations in multi-dimensional neurobehavioral components, which closely interrelated with cognitive and psychosocial factors, i.e., attention, appraisal, emotion and sensorimotor. Our findings are likely to help foster new insights into the pathophysiological mechanisms of pED and the aberrant brain regions may serve as potential therapeutic targets for targeted therapy for brain. This article is protected by copyright. All rights reserved.

PMID:35869867 | DOI:10.1111/andr.13238

Contrasting Frontoparietal Network Connectivity in Antipsychotic Medication-Naive First-Episode Psychosis Patients Who Do and Do Not Display Features of the Deficit Syndrome

Sat, 07/23/2022 - 18:00

Schizophr Bull. 2022 Jul 23:sbac081. doi: 10.1093/schbul/sbac081. Online ahead of print.


BACKGROUND: The deficit syndrome is a clinical subtype of schizophrenia that is characterized by enduring negative symptoms. Several lines of evidence point to frontoparietal involvement, but the frontoparietal control network (FPCN) and its subsystems (FPCNA and FPCNB) proposed by Yeo et al. have not been systematically characterized at rest in patients with the deficit syndrome.

METHODS: We used resting-state fMRI to investigate the FPCN and its subnetworks in 72 healthy controls and 65 antipsychotic medication-naive, first-episode psychosis patients (22 displayed deficit syndrome features, 43 did not). To assess whole-brain FPCN connectivity, we used the right posterior parietal cortex as the seed region. We then performed region of interest analyses in FPCN subsystems.

RESULTS: We found that patterns of FPCN dysconnectivity to the whole brain differed in patients who displayed deficit syndrome features compared with those who did not. Examining the FPCN on a more granular level revealed reduced within-FPCN(A) connectivity only in patients displaying deficit features. FPCNB connectivity did not differ between patient groups.

DISCUSSION: Here, we describe a neurobiological signature of aberrant FPCN connectivity in antipsychotic-naive, first-episode patients who display clinical features of the deficit syndrome. Importantly, frontoparietal subnetwork connectivity differentiated subgroups, where the FPCNA is selectively involved in patients with deficit features. Our findings add to the growing body of literature supporting a neurobiological distinction between two clinical subtypes of schizophrenia, which has the potential to be leveraged for patient stratification in clinical trials and the development of novel treatments.

PMID:35869578 | DOI:10.1093/schbul/sbac081

Altered neural flexibility in children with attention-deficit/hyperactivity disorder

Fri, 07/22/2022 - 18:00

Mol Psychiatry. 2022 Jul 22. doi: 10.1038/s41380-022-01706-4. Online ahead of print.


Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders of childhood, and is often characterized by altered executive functioning. Executive function has been found to be supported by flexibility in dynamic brain reconfiguration. Thus, we applied multilayer community detection to resting-state fMRI data in 180 children with ADHD and 180 typically developing children (TDC) to identify alterations in dynamic brain reconfiguration in children with ADHD. We specifically evaluated MR derived neural flexibility, which is thought to underlie cognitive flexibility, or the ability to selectively switch between mental processes. Significantly decreased neural flexibility was observed in the ADHD group at both the whole brain (raw p = 0.0005) and sub-network levels (p < 0.05, FDR corrected), particularly for the default mode network, attention-related networks, executive function-related networks, and primary networks. Furthermore, the subjects with ADHD who received medication exhibited significantly increased neural flexibility (p = 0.025, FDR corrected) when compared to subjects with ADHD who were medication naïve, and their neural flexibility was not statistically different from the TDC group (p = 0.74, FDR corrected). Finally, regional neural flexibility was capable of differentiating ADHD from TDC (Accuracy: 77% for tenfold cross-validation, 74.46% for independent test) and of predicting ADHD severity using clinical measures of symptom severity (R2: 0.2794 for tenfold cross-validation, 0.156 for independent test). In conclusion, the present study found that neural flexibility is altered in children with ADHD and demonstrated the potential clinical utility of neural flexibility to identify children with ADHD, as well as to monitor treatment responses and disease severity.

PMID:35869272 | DOI:10.1038/s41380-022-01706-4