New resting-state fMRI related studies at PubMed

Increased brain atrophy and lesion load is associated with stronger lower alpha MEG power in multiple sclerosis patients

Fri, 03/26/2021 - 10:00

Neuroimage Clin. 2021 Mar 17;30:102632. doi: 10.1016/j.nicl.2021.102632. Online ahead of print.


In multiple sclerosis, the interplay of neurodegeneration, demyelination and inflammation leads to changes in neurophysiological functioning. This study aims to characterize the relation between reduced brain volumes and spectral power in multiple sclerosis patients and matched healthy subjects. During resting-state eyes closed, we collected magnetoencephalographic data in 67 multiple sclerosis patients and 47 healthy subjects, matched for age and gender. Additionally, we quantified different brain volumes through magnetic resonance imaging (MRI). First, a principal component analysis of MRI-derived brain volumes demonstrates that atrophy can be largely described by two components: one overall degenerative component that correlates strongly with different cognitive tests, and one component that mainly captures degeneration of the cortical grey matter that strongly correlates with age. A multimodal correlation analysis indicates that increased brain atrophy and lesion load is accompanied by increased spectral power in the lower alpha (8-10 Hz) in the temporoparietal junction (TPJ). Increased lower alpha power in the TPJ was further associated with worse results on verbal and spatial working memory tests, whereas an increased lower/upper alpha power ratio was associated with slower information processing speed. In conclusion, multiple sclerosis patients with increased brain atrophy, lesion and thalamic volumes demonstrated increased lower alpha power in the TPJ and reduced cognitive abilities.

PMID:33770549 | DOI:10.1016/j.nicl.2021.102632

Brainstem functional oscillations across the migraine cycle: A longitudinal investigation

Fri, 03/26/2021 - 10:00

Neuroimage Clin. 2021 Mar 17;30:102630. doi: 10.1016/j.nicl.2021.102630. Online ahead of print.


Although the mechanisms responsible for migraine initiation remain unknown, recent evidence shows that brain function is different immediately preceding a migraine. This is consistent with the idea that altered brain function, particularly in brainstem sites, may either trigger a migraine or facilitate a peripheral trigger that activates the brain, resulting in pain. The aim of this longitudinal study is therefore to expand on the above findings, and to determine if brainstem function oscillates over a migraine cycle in individual subjects. We performed resting state functional magnetic resonance imaging in three migraineurs and five controls each weekday for four weeks. We found that although resting activity variability was similar in controls and interictal migraineurs, brainstem variability increased dramatically during the 24-hour period preceding a migraine. This increase occurred in brainstem areas in which orofacial afferents terminate: the spinal trigeminal nucleus and dorsal pons. These increases were characterized by increased power at infra-slow frequencies, principally between 0.03 and 0.06 Hz. Furthermore, these power increases were associated with increased regional homogeneity, a measure of local signal coherence. The results show within-individual alterations in brain activity immediately preceding migraine onset and support the hypothesis that altered regional brainstem function before a migraine attack is involved in underlying migraine neurobiology.

PMID:33770547 | DOI:10.1016/j.nicl.2021.102630

Differential functional connectivity of insular subdivisions in de novo Parkinson's disease with mild cognitive impairment

Fri, 03/26/2021 - 10:00

Brain Imaging Behav. 2021 Mar 26. doi: 10.1007/s11682-021-00471-2. Online ahead of print.


The insula, consisting of functionally diverse subdivisions, plays a significant role in Parkinson's disease (PD)-related cognitive disorders. However, the functional connectivity (FC) patterns of insular subdivisions in PD remain unclear. Our aim is to investigate the changes in FC patterns of insular subdivisions and their relationships with cognitive domains. Three groups of participants were recruited in this study, including PD patients with mild cognitive impairment (PD-MCI, n = 25), PD patients with normal cognition (PD-NC, n = 13), and healthy controls (HCs, n = 17). Resting-state functional magnetic resonance imaging (rs-fMRI) was used to investigate the FC in insular subdivisions of the three groups. Moreover, all participants underwent a neuropsychological battery to assess cognition so that the relationship between altered FC and cognitive performance could be elucidated. Compared with the PD-NC group, the PD-MCI group exhibited increased FC between the left dorsal anterior insular (dAI) and the right superior parietal gyrus (SPG), and altered FC was negatively correlated with memory and executive function. Compared with the HC group, the PD-MCI group showed significantly increased FC between the right dAI and the right median cingulate and paracingulate gyri (DCG), and altered FC was positively related to attention/working memory, visuospatial function, and language. Our findings highlighted the different abnormal FC patterns of insular subdivisions in PD patients with different cognitive abilities. Furthermore, dysfunction of the dAI may partly contribute to the decline in executive function and memory in early drug-naïve PD patients.

PMID:33770371 | DOI:10.1007/s11682-021-00471-2

Abnormalities of intrinsic brain activity in essential tremor: A meta-analysis of resting-state functional imaging

Fri, 03/26/2021 - 10:00

Hum Brain Mapp. 2021 Mar 26. doi: 10.1002/hbm.25425. Online ahead of print.


Neuroimaging studies using a variety of techniques have demonstrated abnormal patterns of spontaneous brain activity in patients with essential tremor (ET). However, the findings are variable and inconsistent, hindering understanding of underlying neuropathology. We conducted a meta-analysis of whole-brain resting-state functional neuroimaging studies in ET compared to healthy controls (HC), using anisotropic effect-size seed-based d mapping, to identify the most consistent brain activity alterations and their relation to clinical features. After systematic literature search, we included 13 studies reporting 14 comparisons, describing 286 ET patients and 254 HC. Subgroup analyses were conducted considering medication status, head tremor status, and methodological factors. Brain activity in ET is altered not only in the cerebellum and cerebral motor cortex, but also in nonmotor cortical regions including prefrontal cortex and insula. Most of the results remained unchanged in subgroup analyses of patients with head tremor, medication-naive patients, studies with statistical threshold correction, and the large subgroup of studies using functional magnetic resonance imaging. These findings not only show consistent and robust abnormalities in specific brain regions but also provide new information on the biology of patient heterogeneity, and thus help to elucidate the pathophysiology of ET.

PMID:33769638 | DOI:10.1002/hbm.25425

Somatosensory network functional connectivity differentiates clinical pain phenotypes in diabetic neuropathy

Fri, 03/26/2021 - 10:00

Diabetologia. 2021 Mar 25. doi: 10.1007/s00125-021-05416-4. Online ahead of print.


AIMS/HYPOTHESIS: The aim of this work was to investigate whether different clinical pain phenotypes of diabetic polyneuropathy (DPN) are distinguished by functional connectivity at rest.

METHODS: This was an observational, cohort study of 43 individuals with painful DPN, divided into irritable (IR, n = 10) and non-irritable (NIR, n = 33) nociceptor phenotypes using the German Research Network of Neuropathic Pain quantitative sensory testing protocol. In-situ brain MRI included 3D T1-weighted anatomical and 6 min resting-state functional MRI scans. Subgroup differences in resting-state functional connectivity in brain regions involved with somatic (thalamus, primary somatosensory cortex, motor cortex) and non-somatic (insular and anterior cingulate cortices) pain processing were examined. Multidimensional reduction of MRI datasets was performed using a machine-learning approach to classify individuals into each clinical pain phenotype.

RESULTS: Individuals with the IR nociceptor phenotype had significantly greater thalamic-insular cortex (p false discovery rate [FDR] = 0.03) and reduced thalamus-somatosensory cortex functional connectivity (p-FDR = 0.03). We observed a double dissociation such that self-reported neuropathic pain score was more associated with greater thalamus-insular cortex functional connectivity (r = 0.41; p = 0.01) whereas more severe nerve function deficits were more related to lower thalamus-somatosensory cortex functional connectivity (r = -0.35; p = 0.03). Machine-learning group classification performance to identify individuals with the NIR nociceptor phenotype achieved an accuracy of 0.92 (95% CI 0.08) and sensitivity of 90%.

CONCLUSIONS/INTERPRETATION: This study demonstrates differences in functional connectivity in nociceptive processing brain regions between IR and NIR phenotypes in painful DPN. We also establish proof of concept for the utility of multimodal MRI as a biomarker for painful DPN by using a machine-learning approach to classify individuals into sensory phenotypes.

PMID:33768284 | DOI:10.1007/s00125-021-05416-4

Cultivating Affective Resilience: Proof-of-Principle Evidence of Translational Benefits From a Novel Cognitive-Emotional Training Intervention

Fri, 03/26/2021 - 10:00

Front Psychol. 2021 Mar 9;12:585536. doi: 10.3389/fpsyg.2021.585536. eCollection 2021.


Available evidence highlights the importance of emotion regulation (ER) in psychological well-being. However, translation of the beneficial effects of ER from laboratory to real-life remains scarce. Here, we present proof-of-principle evidence from a novel cognitive-emotional training intervention targeting the development of ER skills aimed at increasing resilience against emotional distress. This pilot intervention involved training military veterans over 5-8 weeks in applying two effective ER strategies [Focused Attention (FA) and Cognitive Reappraisal (CR)] to scenarios presenting emotional conflicts (constructed with both external and internal cues). Training was preceded and followed by neuropsychological, personality, and clinical assessments, and resting-state functional MRI data were also collected from a subsample of the participants. Results show enhanced executive function and psychological well-being following training, reflected in increased working memory (WM), post-traumatic growth (PTG), and general self-efficacy (GSE). Brain imaging results showed evidence of diminished bottom-up influences from emotional and perceptual brain regions, along with evidence of normalized functional connectivity in the large-scale functional networks following training. The latter was reflected in increased connectivity among cognitive and emotion control regions and across regions of self-referential and control networks. Overall, our results provide proof-of-concept evidence that resilience and well-being can be learned through ER training, and that training-related improvements manifested in both behavioral change and neuroplasticity can translate into real-life benefits.

PMID:33767643 | PMC:PMC7985085 | DOI:10.3389/fpsyg.2021.585536

Quantitative Assessment of the Impact of Geometric Distortions and Their Correction on fMRI Data Analyses

Fri, 03/26/2021 - 10:00

Front Neurosci. 2021 Mar 9;15:642808. doi: 10.3389/fnins.2021.642808. eCollection 2021.


Functional magnetic resonance imaging (fMRI) data is typically collected with gradient-echo echo-planar imaging (GE-EPI) sequences, which are particularly prone to the susceptibility artifact as a result of B0 field inhomogeneity. The component derived from in-plane spin dephasing induces pixel intensity variations and, more critically, geometric distortions. Despite the physical mechanisms underlying the susceptibility artifact being well established, a systematic investigation on the impact of the associated geometric distortions, and the direct comparison of different approaches to tackle them, on fMRI data analyses is missing. Here, we compared two different distortion correction approaches, by acquiring additional: (1) EPI data with reversed phase encoding direction (TOPUP), and (2) standard (and undistorted) GE data at two different echo times (GRE). We first characterized the geometric distortions and the correction approaches based on the estimated ΔB0 field offset and voxel shift maps, and then conducted three types of analyses on the distorted and corrected fMRI data: (1) registration into structural data, (2) identification of resting-state networks (RSNs), and (3) mapping of task-related brain regions of interest. GRE estimated the largest voxel shifts and more positively impacted the quality of the analyses, in terms of the (significantly lower) cost function of the registration, the (higher) spatial overlap between the RSNs and appropriate templates, and the (significantly higher) sensitivity of the task-related mapping based on the Z-score values of the associated activation maps, although also evident when considering TOPUP. fMRI data should thus be corrected for geometric distortions, with the choice of the approach having a modest, albeit positive, impact on the fMRI analyses.

PMID:33767610 | PMC:PMC7985341 | DOI:10.3389/fnins.2021.642808

Recovery-associated resting-state activity and connectivity alterations in Anorexia nervosa

Fri, 03/26/2021 - 10:00

Biol Psychiatry Cogn Neurosci Neuroimaging. 2021 Mar 22:S2451-9022(21)00083-5. doi: 10.1016/j.bpsc.2021.03.006. Online ahead of print.


BACKGROUND: Previous studies provided controversial insight on the impact of starvation, disease status and underlying grey matter volume (GMV) changes on resting-state functional magnetic resonance imaging (rsfMRI) alterations in Anorexia nervosa (AN). Here we adapt a combined longitudinal and cross-sectional approach to disentangle the effects of these factors on resting-state alterations in AN.

METHODS: Overall, 87 female subjects were included in the study: adolescent patients with acute AN scanned at inpatient admission (N = 22, mean age 15.3 years) and at discharge (N = 21), 21 patients recovered from AN (22.3 years) and two groups of healthy age-matched controls (both N = 22, 16.0 and 22.5 years). Whole-brain measures of resting-state activity and functional connectivity were computed (Network Based Statistics, Global Correlation, Integrated Local Correlation, fractional Amplitude of Low Frequency Fluctuations) to assess rsfMRI alterations over the course of AN treatment before and after controlling for underlying GMV.

RESULTS: Patients with acute AN displayed strong and widespread prefrontal, sensorimotor, parietal, temporal, precuneal and insular reductions of resting-state connectivity and activity. All alterations were independent of GMV and were largely normalized in short- and absent in long-term recovered AN.

CONCLUSIONS: Resting-state fMRI alterations in AN constitute acute and GMV independent presumably starvation-related phenomena. The majority of alterations found here normalized over the course of recovery without evidence for possible preexisting trait- or remaining "scar"-effects.

PMID:33766777 | DOI:10.1016/j.bpsc.2021.03.006

Long-term ovarian hormone deprivation alters functional connectivity, brain neurochemical profile and white matter integrity in the Tg2576 amyloid mouse model of Alzheimer's disease

Thu, 03/25/2021 - 10:00

Neurobiol Aging. 2021 Feb 22;102:139-150. doi: 10.1016/j.neurobiolaging.2021.02.011. Online ahead of print.


Premenopausal bilateral ovariectomy is considered to be one of the risk factors of Alzheimer's disease (AD). However, the underlying mechanisms remain unclear. Here, we aimed to investigate long-term neurological consequences of ovariectomy in a rodent AD model, TG2576 (TG), and wild-type mice (WT) that underwent an ovariectomy or sham-operation, using in vivo MRI biomarkers. An increase in osmoregulation and energy metabolism biomarkers in the hypothalamus, a decrease in white matter integrity, and a decrease in the resting-state functional connectivity was observed in ovariectomized TG mice compared to sham-operated TG mice. In addition, we observed an increase in functional connectivity in ovariectomized WT mice compared to sham-operated WT mice. Furthermore, genotype (TG vs. WT) effects on imaging markers and GFAP immunoreactivity levels were observed, but there was no effect of interaction (Genotype × Surgery) on amyloid-beta-and GFAP immunoreactivity levels. Taken together, our results indicated that both genotype and ovariectomy alters imaging biomarkers associated with AD.

PMID:33765427 | DOI:10.1016/j.neurobiolaging.2021.02.011

Identifying emergent mesoscopic-macroscopic functional brain network dynamics in infants at term-equivalent age with electric source neuroimaging

Thu, 03/25/2021 - 10:00

Brain Connect. 2021 Mar 25. doi: 10.1089/brain.2020.0965. Online ahead of print.


AIM: To identify and characterise the functional brain networks at the time when the brain is yet to develop higher order functions in term-born and preterm infants at term-equivalent age.

INTRODUCTION: Although fMRI data have revealed the existence of spatially structured resting-state brain activity in infants, the temporal information of fMRI data limits the characterisation of fast time-scale brain oscillations. Here we use infants' high-density EEG to characterise spatiotemporal and spectral functional organisation of brain network dynamics.

METHODS: We used source-reconstructed EEG and graph theoretical analyses in 100 infants (84 preterm, 16 term born) to identify the rich-club topological organisation, temporal dynamics and spectral fingerprints of dynamic functional brain networks.

RESULTS: Five dynamic functional brain networks are identified, which have rich-club topological organisations, distinctive spectral fingerprints (in the delta and low-alpha frequency) and scale-invariant temporal dynamics (<0.1 Hz): The default mode, primary sensory-limbic system, thalamo-frontal, thalamo-sensorimotor and visual-limbic system. The temporal dynamics of these networks are correlated in a hierarchically leading-following organisation, showing that infant brain networks arise from long-range synchronisation of band-limited cortical oscillation based on interacting fast and slow coherent cortical oscillations.

CONCLUSION: Dynamic functional brain networks do not solely depend on the maturation of cognitive networks, instead, the brain network dynamics exist in infants at term-age well before the childhood and adulthood, and hence it offers a quantitative measurement of neurotypical development in infants. Impact Statement: Our work offers novel functional insights into the brain network characterisation in infants, providing a new functional basis for future deployable prognostication approaches.

PMID:33764807 | DOI:10.1089/brain.2020.0965

Visual processing speed is linked to functional connectivity between right frontoparietal and visual networks

Thu, 03/25/2021 - 10:00

Eur J Neurosci. 2021 Mar 25. doi: 10.1111/ejn.15206. Online ahead of print.


Visual information processing requires an efficient visual attention system. The neural theory of visual attention (TVA) proposes that visual processing speed depends on the coordinated activity between frontoparietal and occipital brain areas. Previous research has shown that the coordinated activity between (i.e., functional connectivity, 'inter-FC') cingulo-opercular (COn) and right-frontoparietal (RFPn) networks is linked to visual processing speed. However, how inter-FC of COn and RFPn with visual networks links to visual processing speed has not been directly addressed yet. Forty-eight healthy adult participants (27 females) underwent resting-state (rs-)fMRI and performed a whole-report psychophysical task. To obtain inter-FC, we analyzed the entire frequency range available in our rs-fMRI data (i.e., 0.01-0.4 Hz) to avoid discarding neural information. Following previous approaches, we analyzed the data across frequency bins (Hz): Slow-5 (0.01-0.027), Slow-4 (0.027-0.073), Slow-3 (0.073-0.198), and Slow-2 (0.198-0.4). We used the mathematical TVA framework to estimate an individual, latent-level visual processing speed parameter. We found that visual processing speed was negatively associated with inter-FC between RFPn and visual networks in Slow-5 and Slow-2, with no corresponding significant association for inter-FC between COn and visual networks. These results provide the first empirical evidence that links inter-FC between RFPn and visual networks with the visual processing speed parameter. These findings suggest that direct connectivity between occipital and right frontoparietal, but not frontoinsular, regions support visual processing speed.

PMID:33764572 | DOI:10.1111/ejn.15206

Resting-State Network Plasticity Induced by Music Therapy after Traumatic Brain Injury

Thu, 03/25/2021 - 10:00

Neural Plast. 2021 Mar 8;2021:6682471. doi: 10.1155/2021/6682471. eCollection 2021.


Traumatic brain injury (TBI) is characterized by a complex pattern of abnormalities in resting-state functional connectivity (rsFC) and network dysfunction, which can potentially be ameliorated by rehabilitation. In our previous randomized controlled trial, we found that a 3-month neurological music therapy intervention enhanced executive function (EF) and increased grey matter volume in the right inferior frontal gyrus (IFG) in patients with moderate-to-severe TBI (N = 40). Extending this study, we performed longitudinal rsFC analyses of resting-state fMRI data using a ROI-to-ROI approach assessing within-network and between-network rsFC in the frontoparietal (FPN), dorsal attention (DAN), default mode (DMN), and salience (SAL) networks, which all have been associated with cognitive impairment after TBI. We also performed a seed-based connectivity analysis between the right IFG and whole-brain rsFC. The results showed that neurological music therapy increased the coupling between the FPN and DAN as well as between these networks and primary sensory networks. By contrast, the DMN was less connected with sensory networks after the intervention. Similarly, there was a shift towards a less connected state within the FPN and SAL networks, which are typically hyperconnected following TBI. Improvements in EF were correlated with rsFC within the FPN and between the DMN and sensorimotor networks. Finally, in the seed-based connectivity analysis, the right IFG showed increased rsFC with the right inferior parietal and left frontoparietal (Rolandic operculum) regions. Together, these results indicate that the rehabilitative effects of neurological music therapy after TBI are underpinned by a pattern of within- and between-network connectivity changes in cognitive networks as well as increased connectivity between frontal and parietal regions associated with music processing.

PMID:33763126 | PMC:PMC7964116 | DOI:10.1155/2021/6682471

Isoflurane affects brain functional connectivity in rats 1 month after exposure

Thu, 03/25/2021 - 10:00

Neuroimage. 2021 Mar 21:117987. doi: 10.1016/j.neuroimage.2021.117987. Online ahead of print.


Isoflurane, the most commonly used preclinical anesthetic, induces brain plasticity and long-term cellular and molecular changes leading to behavioral and/or cognitive consequences. These changes are most likely associated with network-level changes in brain function. To elucidate the mechanisms underlying long-term effects of isoflurane, we investigated the influence of a single isoflurane exposure on functional connectivity, brain electrical activity, and gene expression. Male Wistar rats (n=22) were exposed to 1.8% isoflurane for 3 h. Control rats (n=22) spent 3 h in the same room without exposure to anesthesia. After 1 month, functional connectivity was evaluated with resting-state functional magnetic resonance imaging (fMRI; n=6+6) and local field potential measurements (n=6+6) in anesthetized animals. A whole genome expression analysis (n=10+10) was also conducted with mRNA-sequencing from cortical and hippocampal tissue samples. Isoflurane treatment strengthened thalamo-cortical and hippocampal-cortical functional connectivity. Cortical low-frequency fMRI power was also significantly increased in response to the isoflurane treatment. The local field potential results indicating strengthened hippocampal-cortical alpha and beta coherence were in good agreement with the fMRI findings. Furthermore, altered expression was found in 20 cortical genes, several of which are involved in neuronal signal transmission, but no gene expression changes were noted in the hippocampus. Isoflurane induced prolonged changes in thalamo-cortical and hippocampal-cortical function and expression of genes contributing to signal transmission in the cortex. Further studies are required to investigate whether these changes are associated with the postoperative behavioral and cognitive symptoms commonly observed in patients and animals.

PMID:33762218 | DOI:10.1016/j.neuroimage.2021.117987

An Effective Brain Imaging Biomarker for AD and aMCI: ALFF in Slow-5 Frequency Band

Thu, 03/25/2021 - 10:00

Curr Alzheimer Res. 2021 Mar 24. doi: 10.2174/1567205018666210324130502. Online ahead of print.


BACKGROUND: As a potential brain imaging biomarker, amplitude of low frequency fluc-tuation (ALFF) has been used as a feature to distinguish patients with Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI) from normal controls (NC). However, it remains unclear whether the frequency-dependent pattern of ALFF alterations can effectively distinguish the different phases of the disease.

METHODS: In the present study, 52 AD and 50 aMCI patients were enrolled together with 43 NC in total. The ALFF values were calculated in the following three frequency bands: classical (0.01-0.08 Hz), slow-4 (0.027-0.073 Hz) and slow-5 (0.01-0.027 Hz) for the three different groups. Subsequently, the local functional abnormalities were employed as features to examine the effect of classification among AD, aMCI and NC using a support vector machine (SVM).

RESULTS: We found that the among-group differences of ALFF in the different frequency bands were mainly located in the left hippocampus (HP), right HP, bilateral posterior cingulate cortex (PCC) and bilateral precuneus (PCu), left angular gyrus (AG) and left medial prefrontal cortex (mPFC). When the local functional abnormalities were employed as features, we identified that the ALFF in the slow-5 frequency band showed the highest accuracy to distinguish among the three groups.

CONCLUSION: These findings may deepen our understanding of the pathogenesis of AD and suggest that slow-5 frequency band may be helpful to explore the pathogenesis and distinguish the phases of this disease.

PMID:33761855 | DOI:10.2174/1567205018666210324130502

Distinct patterns of resting-state connectivity in U.S. service members with mild traumatic brain injury versus posttraumatic stress disorder

Wed, 03/24/2021 - 10:00

Brain Imaging Behav. 2021 Mar 23. doi: 10.1007/s11682-021-00464-1. Online ahead of print.


Mild traumatic brain injury (mTBI) is highly prevalent in military populations, with many service members suffering from long-term symptoms. Posttraumatic stress disorder (PTSD) often co-occurs with mTBI and predicts worse clinical outcomes. Functional neuroimaging research suggests there are both overlapping and distinct patterns of resting-state functional connectivity (rsFC) in mTBI versus PTSD. However, few studies have directly compared rsFC of cortical networks in military service members with these two conditions. In the present study, U.S. service members (n = 137; ages 19-59; 120 male) underwent resting-state fMRI scans. Participants were divided into three study groups: mTBI only, PTSD only, and orthopedically injured (OI) controls. Analyses investigated group differences in rsFC for cortical networks: default mode (DMN), frontoparietal (FPN), salience, somatosensory, motor, auditory, and visual. Analyses were family-wise error (FWE) cluster-corrected and Bonferroni-corrected for number of network seeds regions at the whole brain level (pFWE < 0.002). Both mTBI and PTSD groups had reduced rsFC for DMN and FPN regions compared with OI controls. These group differences were largely driven by diminished connectivity in the PTSD group. rsFC with the middle frontal gyrus of the FPN was increased in mTBI, but decreased in PTSD. Overall, these results suggest that PTSD symptoms may have a more consistent signal than mTBI. Our novel findings of opposite patterns of connectivity with lateral prefrontal cortex highlight a potential biomarker that could be used to differentiate between these conditions.

PMID:33759113 | DOI:10.1007/s11682-021-00464-1

Machine learning may predict individual hand motor activation from resting-state fMRI in patients with brain tumors in perirolandic cortex

Wed, 03/24/2021 - 10:00

Eur Radiol. 2021 Mar 23. doi: 10.1007/s00330-021-07825-w. Online ahead of print.


OBJECTIVE: The study aimed to evaluate the predictive validity of the neural network (NN) method for presurgical mapping of motor areas using resting-state functional MRI (rs-fMRI) data of patients with brain tumor located in the perirolandic cortex (PRC).

METHODS: A total of 109 patients with brain tumors occupying PRC underwent rs-fMRI and hand movement task-based fMRI (tb-fMRI) scans. Using a NN model trained on fMRI data of 47 healthy controls, individual task activation maps were predicted from their rs-fMRI data. NN-predicted maps were compared with task activation and independent component analysis (ICA)-derived maps. Spatial Pearson's correlation coefficients (CC) matrices and Dice coefficients (DC) between task activation and predicted activation using NN (DCNN_Act) and ICA (DCICA_Act) were calculated and compared using non-parametric tests. The effects of tumor types and head motion on predicted maps were demonstrated.

RESULTS: The CC matrix of NN-predicted maps showed higher diagonal values compared with ICA-derived maps (p < 0.001). DCNN_Act were higher than DCICA_Act (p < 0.001) for patients with or without motor deficits. Lower DCs were found in subjects with head motion greater than one voxel. DCs were higher on the nontumor side than on the tumor side (p < 0.001), especially in the glioma group compared with meningioma and metastatic groups.

CONCLUSIONS: This study indicated that the NN approach could predict individual motor activation using rs-fMRI data and could have promising clinical applications in brain tumor patients with anatomical and functional reorganizations.

KEY POINTS: • The neural network machine learning approach successfully predicted hand motor activation in patients with a tumor in the perirolandic cortex, despite space-occupying effects and possible functional reorganization. • Compared to the conventional independent component analysis, the neural network approach utilizing resting-state fMRI data yielded a higher correlation to the active task hand activation data. • The Dice coefficient of machine learning-predicted activation vs. task fMRI activation was different between tumor and nontumor side, also between tumor types, which might indicate different effects of possible neurovascular uncoupling on resting-state and task fMRI.

PMID:33758954 | DOI:10.1007/s00330-021-07825-w

Altered spontaneous brain activity in patients with diabetic optic neuropathy: A resting-state functional magnetic resonance imaging study using regional homogeneity

Wed, 03/24/2021 - 10:00

World J Diabetes. 2021 Mar 15;12(3):278-291. doi: 10.4239/wjd.v12.i3.278.


BACKGROUND: Diabetes is a common chronic disease. Given the increasing incidence of diabetes, more individuals are affected by diabetic optic neuropathy (DON), which results in decreased vision. Whether DON leads to abnormalities of other visual systems, including the eye, the visual cortex, and other brain regions, remains unknown.

AIM: To investigate the local characteristics of spontaneous brain activity using regional homogeneity (ReHo) in patients with DON.

METHODS: We matched 22 patients with DON with 22 healthy controls (HCs). All subjects underwent resting-state functional magnetic resonance imaging. The ReHo technique was used to record spontaneous changes in brain activity. Receiver operating characteristic (ROC) curves were applied to differentiate between ReHo values for patients with DON and HCs. We also assessed the correlation between Hospital Anxiety and Depression Scale scores and ReHo values in DON patients using Pearson correlation analysis.

RESULTS: ReHo values of the right middle frontal gyrus (RMFG), left anterior cingulate (LAC), and superior frontal gyrus (SFG)/left frontal superior orbital gyrus (LFSO) were significantly lower in DON patients compared to HCs. Among these, the greatest difference was observed in the RMFG. The result of the ROC curves suggest that ReHo values in altered brain regions may help diagnose DON, and the RMFG and LAC ReHo values are more clinically relevant than SFG/LFSO. We also found that anxiety and depression scores of the DON group were extremely negatively correlated with the LAC ReHo values (r = -0.9336, P < 0.0001 and r = -0.8453, P < 0.0001, respectively).

CONCLUSION: Three different brain regions show ReHo changes in DON patients, and these changes could serve as diagnostic and/or prognostic biomarkers to further guide the prevention and treatment of DON patients.

PMID:33758647 | PMC:PMC7958477 | DOI:10.4239/wjd.v12.i3.278

Speech Motor Function and Auditory Perception in Succinic Semialdehyde Dehydrogenase Deficiency: Toward Pre-Supplementary Motor Area (SMA) and SMA-Proper Dysfunctions

Wed, 03/24/2021 - 10:00

J Child Neurol. 2021 Mar 23:8830738211001210. doi: 10.1177/08830738211001210. Online ahead of print.


This study reviews the fundamental roles of pre-supplementary motor area (SMA) and SMA-proper responsible for speech-motor functions and auditory perception in succinic semialdehyde dehydrogenase (SSADH) deficiency. We comprehensively searched the databases of PubMed, Google Scholar, and the electronic journals Springer, PreQuest, and Science Direct associated with keywords SSADHD, SMA, auditory perception, speech, and motor with AND operator. Transcranial magnetic stimulation emerged for assessing excitability/inhibitory M1 functions, but its role in pre-SMA and SMA proper dysfunction remains unknown. There was a lack of data on resting-state and task-based functional magnetic resonance imaging (MRI), with a focus on passive and active tasks for both speech and music, in terms of analysis of SMA-related cortex and its connections. Children with SSADH deficiency likely experience a dysfunction in connectivity between SMA portions with cortical and subcortical areas contributing to disabilities in speech-motor functions and auditory perception. Early diagnosis of auditory-motor disabilities in children with SSADH deficiency by neuroimaging techniques invites opportunities for utilizing sensory-motor integration as future interventional strategies.

PMID:33757330 | DOI:10.1177/08830738211001210

Identification of minimal hepatic encephalopathy based on dynamic functional connectivity

Tue, 03/23/2021 - 10:00

Brain Imaging Behav. 2021 Mar 23. doi: 10.1007/s11682-021-00468-x. Online ahead of print.


To investigate whether dynamic functional connectivity (DFC) metrics can better identify minimal hepatic encephalopathy (MHE) patients from cirrhotic patients without any hepatic encephalopathy (noHE) and healthy controls (HCs). Resting-state functional MRI data were acquired from 62 patients with cirrhosis (MHE, n = 30; noHE, n = 32) and 41 HCs. We used the sliding time window approach and functional connectivity analysis to extract the time-varying properties of brain connectivity. Three DFC characteristics (i.e., strength, stability, and variability) were calculated. For comparison, we also calculated the static functional connectivity (SFC). A linear support vector machine was used to differentiate MHE patients from noHE and HCs using DFC and SFC metrics as classification features. The leave-one-out cross-validation method was used to estimate the classification performance. The strength of DFC (DFC-Dstrength) achieved the best accuracy (MHE vs. noHE, 72.5%; MHE vs. HCs, 84%; and noHE vs. HCs, 88%) compared to the other dynamic features. Compared to static features, the classification accuracies of the DFC-Dstrength feature were improved by 10.5%, 8%, and 14% for MHE vs. noHE, MHE vs. HC, and noHE vs. HCs, respectively. Based on the DFC-Dstrength, seven nodes were identified as the most discriminant features to classify MHE from noHE, including left inferior parietal lobule, left supramarginal gyrus, left calcarine, left superior frontal gyrus, left cerebellum, right postcentral gyrus, and right insula. In summary, DFC characteristics have a higher classification accuracy in identifying MHE from cirrhosis patients. Our findings suggest the usefulness of DFC in capturing neural processes and identifying disease-related biomarkers important for MHE identification.

PMID:33755921 | DOI:10.1007/s11682-021-00468-x

Reduced network integration in default mode and executive networks is associated with social and personal optimism biases

Tue, 03/23/2021 - 10:00

Hum Brain Mapp. 2021 Mar 23. doi: 10.1002/hbm.25411. Online ahead of print.


An optimism bias refers to the belief in good things happening to oneself in the future with a higher likelihood than is justified. Social optimism biases extend this concept to groups that one identifies with. Previous literature has found that both personal and social optimism biases are linked to brain structure and task-related brain function. Less is known about whether optimism biases are also expressed in resting-state functional connectivity (RSFC). Forty-two participants completed questionnaires on dispositional personal optimism (which is not necessarily unjustified) and comparative optimism (i.e., whether we see our own future as being rosier than a comparison person's future) and underwent a resting-state functional magnetic resonance imaging scan. They further undertook an imaginative soccer task in order to assess both their personal and social optimism bias. We tested associations of these data with RSFC within and between 13 networks, using sparse canonical correlation analyses (sCCAs). We found that the primary sCCA component was positively connected to personal and social optimism bias and negatively connected to dispositional personal pessimism. This component was associated with (a) reduced integration of the default mode network, (b) reduced integration of the central executive and salience networks, and (c) reduced segregation between the default mode network and the central executive network. Our finding that optimism biases are linked to RSFC indicates that they may be rooted in neurobiology that exists outside of concurrent tasks. This poses questions as to what the limits of the malleability of such biases may be.

PMID:33755272 | DOI:10.1002/hbm.25411