Most recent paper

Subscribe to Most recent paper feed Most recent paper
NCBI: db=pubmed; Term="resting"[All Fields] AND "fMRI"[All Fields]
Updated: 4 hours 23 min ago

Resting-state functional connectivity in treatment response and resistance in schizophrenia: A systematic review.

Thu, 07/25/2019 - 03:37
Related Articles

Resting-state functional connectivity in treatment response and resistance in schizophrenia: A systematic review.

Schizophr Res. 2019 Jul 19;:

Authors: Chan NK, Kim J, Shah P, Brown EE, Plitman E, Carravaggio F, Iwata Y, Gerretsen P, Graff-Guerrero A

Abstract
BACKGROUND: Treatment-resistant schizophrenia (TRS) and treatment-responsive schizophrenia may exhibit distinct pathophysiology. Several functional magnetic resonance imaging (fMRI) studies have used resting-state functional connectivity analyses (rs-FC) in TRS patients to identify markers of treatment resistance. However, to date, existing findings have not been systematically evaluated.
METHODS: A systematic literature search using Embase, MEDLINE, PsycINFO, ProQuest, PUBMED, and Scopus was performed. The query sought fMRI articles investigating rs-FC in treatment response or resistance in patients with schizophrenia. Only studies that examined treatment response, operationalized as the explicit categorization of patients by their response to antipsychotic medication, were considered eligible. Pairwise comparisons between patient groups and controls were extracted from each study.
RESULTS: The search query identified 159 records. Ten studies met inclusion criteria. Five studies examined not TRS (NTRS), and 8 studies examined TRS. Differences in rs-FC analysis methodology precluded direct comparisons between studies. However, disruptions in areas involved in visual and auditory information processing were implicated in both patients with TRS and NTRS. Changes in connectivity with sensorimotor network areas tended to appear in the context of TRS but not NTRS. Moreover, there was some indication that this connectivity could be affected by clozapine.
CONCLUSIONS: Functional connectivity may provide clinically meaningful biomarkers of treatment response and resistance in schizophrenia. Studies generally identified similar areas of disruption, though methodological differences largely precluded direct comparison between disruption effects. Implementing data sharing as standard practice will allow future reviews and meta-analyses to identify rs-FC correlates of TRS.

PMID: 31331784 [PubMed - as supplied by publisher]

Deep Learning of Static and Dynamic Brain Functional Networks for Early MCI Detection.

Wed, 07/24/2019 - 00:36
Related Articles

Deep Learning of Static and Dynamic Brain Functional Networks for Early MCI Detection.

IEEE Trans Med Imaging. 2019 Jul 17;:

Authors: Kam TE, Zhang H, Jiao Z, Shen D

Abstract
While convolutional neural network (CNN) has been demonstrating powerful ability to learn hierarchical spatial features from medical images, it is still difficult to apply it directly to resting-state functional MRI (rs-fMRI) and the derived brain functional networks (BFNs). We propose a novel CNN framework to simultaneously learn embedded features from BFNs for brain disease diagnosis. Since BFNs can be built by considering both static and dynamic functional connectivity (FC), we first decompose rs-fMRI into multiple static BFNs with modified independent component analysis. Then, voxel-wise variability in dynamic FC is used to quantify BFN dynamics. A set of paired 3D images representing static/dynamic BFNs can be fed into 3D CNNs, from which we can hierarchically and simultaneously learn static/dynamic BFN features. As a result, dynamic BFN features can complement static BFN features and, at meantime, different BFNs can help each other towards a joint and better classification. We validate our method with a publicly accessible, large cohort of rs-fMRI dataset in early-stage mild cognitive impairment (eMCI) diagnosis, which is one of the most challenging problems to the clinicians. By comparing with a conventional method, our method shows significant diagnostic performance improvement by almost 10%. This result demonstrates the effectiveness of deep learning in preclinical Alzheimer's disease diagnosis, based on the complex and high-dimensional voxel-wise spatiotemporal patterns of the resting-state brain functional connectomics. The framework provides a new but intuitive way to fully exploit deeply embedded diagnostic features from rs-fMRI for better individualized diagnosis of various neurological diseases.

PMID: 31329111 [PubMed - as supplied by publisher]

State-unspecific patterns of whole-brain functional connectivity from resting and multiple task states predict stable individual traits.

Tue, 07/23/2019 - 00:35
Related Articles

State-unspecific patterns of whole-brain functional connectivity from resting and multiple task states predict stable individual traits.

Neuroimage. 2019 Jul 18;:116036

Authors: Takagi Y, Hirayama JI, Tanaka SC

Abstract
An increasing number of functional magnetic resonance imaging (fMRI) studies have revealed potential neural substrates of individual differences in diverse types of brain function and dysfunction. Although most previous studies have inherently focused on state-specific characterizations of brain networks and their functions, several recent studies reported on the potential state-unspecific nature of functional brain networks, such as global similarities across different experimental conditions or states, including both task and resting states. However, no previous studies have carried out direct, systematic characterizations of state-unspecific brain networks, or their functional implications. Here, we quantitatively identified several modes of state-unspecific individual variations in whole-brain functional connectivity patterns, called "Common Neural Modes" (CNMs), from a large-scale fMRI database including eight task/resting states. Furthermore, we tested how CNMs accounted for variability in individual cognitive measures. The results revealed that three CNMs were robustly extracted under various dimensions of features used. Each of these CNMs was preferentially correlated with different aspects of representative cognitive measures, reflecting stable individual traits. Importantly, the association between CNMs and cognitive measures emerged from brain connectivity data alone ("unsupervised"), whereas previous related studies have explicitly used both connectivity and cognitive measures to build their prediction models ("supervised"). The three CNMs were also able to predict several life outcomes, including income and life satisfaction, and achieved the highest level of performance when combined with a conventional cognitive measure. Our findings highlight the importance of state-unspecific brain networks in characterizing fundamental individual variation.

PMID: 31326571 [PubMed - as supplied by publisher]

Comment on "resting-state fMRI in Parkinson's disease patients with cognitive impairment: A meta-analysis".

Mon, 07/22/2019 - 03:35
Related Articles

Comment on "resting-state fMRI in Parkinson's disease patients with cognitive impairment: A meta-analysis".

Parkinsonism Relat Disord. 2019 Jul 12;:

Authors: Wang H, Wang W, Wang X, Hu J, Yao L

PMID: 31324553 [PubMed - as supplied by publisher]

A systematic review of brain functional connectivity patterns involved in episodic and semantic memory.

Sat, 07/20/2019 - 18:34

A systematic review of brain functional connectivity patterns involved in episodic and semantic memory.

Rev Neurosci. 2019 Jul 19;:

Authors: Palacio N, Cardenas F

Abstract
The study of functional connectivity and declarative memory has lately been focused on finding biomarkers of neuropsychological diseases. However, little is known about its patterns in healthy brains. Thus, in this systematic review we analyze and integrate the findings of 81 publications regarding functional connectivity (measured by fMRI during both task and resting-state) and semantic and episodic memory in healthy adults. Moreover, we discriminate and analyze the main areas and links found in specific memory phases (encoding, storage or retrieval) based on several criteria, such as time length, depth of processing, rewarding value of the information, vividness and amount or kind of details retrieved. There is a certain degree of overlap between the networks of episodic and semantic memory and between the encoding and retrieval stages. Although several differences are pointed out during the article, this calls to attention the need for further empirical studies that actively compare both types of memory, particularly using other baseline conditions apart from the traditional resting state. Indeed, the active involvement of the default mode network in both declarative memory and resting condition suggests the possibility that during rest there is an on-going memory processing. We find support for the 'attention to memory' hypothesis, the memory differentiation model and the appropriate transfer hypothesis, but some evidence is inconsistent with the traditional hub-and-spoke model.

PMID: 31323012 [PubMed - as supplied by publisher]

Evaluation of temporomandibular joint, masticatory muscle, and brain cortex activity in patients treated by removable functional appliances: a prospective fMRI study.

Sat, 07/20/2019 - 18:34

Evaluation of temporomandibular joint, masticatory muscle, and brain cortex activity in patients treated by removable functional appliances: a prospective fMRI study.

Dentomaxillofac Radiol. 2019 Jul 19;:20190216

Authors: Orhan O, Orhan K, Cesur E, Köklü A, Algın O

Abstract
OBJECTIVES: The aim of this study is to evaluate the effects of functional orthodontic appliances on the masticatory muscles, temporomandibular joint (TMJ), and brain to determine whether using functional appliances full-time or only at night yields different results.
METHODS: Sixteen patients with class II malocclusion were included in this study. Eight patients were instructed to wear their appliances (monoblock/twinblock) full-time and the other eight patients were instructed to wear them at night while sleeping. An additional 10 patients with class II malocclusion were later included as a pre-treatment control group. Signal intensity ratios (SIR) of TMJ structures and morphological evaluations of the masticatory muscles were done for all patients. Functional magnetic resonance imaging (fMRI) data were also obtained from the patients while performing chewing and biting movements.
RESULTS: ANB angle was reduced significantly in both the full-time and night wear groups, by values of 1.17° and 1.35°, respectively (p < 0.05). MRI showed that SIRs were significantly increased in both groups in the masticatory muscles, retrodiscal pad, condylar process, and articular disc (p < 0.05). Both resting and task-based fMRI evaluation revealed significant increases in blood-oxygen-level-dependent (BOLD) signals in several regions of the brain in both groups (p < 0.05).
CONCLUSIONS: The cephalometric and MRI findings of this study indicate that the treatment effects were similar for both wear schedules. Functional appliances should be regarded not as simple devices that treat class II malocclusion through skeletal and dental correction alone, but as exercise devices that lead to neuromuscular changes by facilitating muscle adaptation and activating various brain regions.

PMID: 31322927 [PubMed - as supplied by publisher]

Linking resting-state networks and social cognition in schizophrenia and bipolar disorder.

Sat, 07/20/2019 - 18:34

Linking resting-state networks and social cognition in schizophrenia and bipolar disorder.

Hum Brain Mapp. 2019 Jul 19;:

Authors: Jimenez AM, Riedel P, Lee J, Reavis EA, Green MF

Abstract
Individuals with schizophrenia and bipolar disorder show alterations in functional neural connectivity during rest. However, resting-state network (RSN) disruptions have not been systematically compared between the two disorders. Further, the impact of RSN disruptions on social cognition, a key determinant of functional outcome, has not been studied. Forty-eight individuals with schizophrenia, 46 with bipolar disorder, and 48 healthy controls completed resting-state functional magnetic resonance imaging. An atlas-based approach was used to examine functional connectivity within nine RSNs across the cortex. RSN connectivity was assessed via nonparametric permutation testing, and associations with performance on emotion perception, mentalizing, and emotion management tasks were examined. Group differences were observed in the medial and lateral visual networks and the sensorimotor network. Individuals with schizophrenia demonstrated reduced connectivity relative to healthy controls in all three networks. Individuals with bipolar disorder demonstrated reduced connectivity relative to controls in the medial visual network and connectivity within this network was significantly positively correlated with emotion management. In healthy controls, connectivity within the medial and lateral visual networks positively correlated with mentalizing. No significant correlations were found for either visual network in schizophrenia. Results highlight the role of altered early visual processing in social cognitive deficits in both schizophrenia and bipolar disorder. However, individuals with bipolar disorder appear to compensate for disrupted visual network connectivity on social cognitive tasks, whereas those with schizophrenia do not. The current study adds clarity on the neurophysiology underlying social cognitive deficits that result in impaired functioning in serious mental illness.

PMID: 31322784 [PubMed - as supplied by publisher]

Stepwise functional connectivity reveals altered sensory-multimodal integration in medication-naïve adults with attention deficit hyperactivity disorder.

Sat, 07/20/2019 - 18:34

Stepwise functional connectivity reveals altered sensory-multimodal integration in medication-naïve adults with attention deficit hyperactivity disorder.

Hum Brain Mapp. 2019 Jul 19;:

Authors: Pretus C, Marcos-Vidal L, Martínez-García M, Picado M, Ramos-Quiroga JA, Richarte V, Castellanos FX, Sepulcre J, Desco M, Vilarroya Ó, Carmona S

Abstract
Neuroimaging studies indicate that children with attention-deficit/hyperactivity disorder (ADHD) present alterations in several functional networks of the sensation-to-cognition spectrum. These alterations include functional overconnectivity within sensory regions and underconnectivity between sensory regions and neural hubs supporting higher order cognitive functions. Today, it is unknown whether this same pattern of alterations persists in adult patients with ADHD who had never been medicated for their condition. The aim of the present study was to assess whether medication-naïve adults with ADHD presented alterations in functional networks of the sensation-to-cognition spectrum. Thirty-one medication-naïve adults with ADHD and twenty-two healthy adults underwent resting-state functional magnetic resonance imaging (rs-fMRI). Stepwise functional connectivity (SFC) was used to characterize the pattern of functional connectivity between sensory seed regions and the rest of the brain at direct, short, intermediate, and long functional connectivity distances, thus covering the continuum from the sensory input to the neural hubs supporting higher order cognitive functions. As compared to controls, adults with ADHD presented increased SFC degree within primary sensory regions and decreased SFC degree between sensory seeds and higher order integration nodes. In addition, they exhibited decreased connectivity degree between sensory seeds and regions of the default-mode network. Consistently, the higher the score in clinical severity scales the lower connectivity degree between seed regions and the default mode network.

PMID: 31322305 [PubMed - as supplied by publisher]

Neurodevelopmental and Psychiatric Symptoms in Patients with a Cyst Compressing the Cerebellum: an Ongoing Enigma.

Sat, 07/20/2019 - 18:34
Related Articles

Neurodevelopmental and Psychiatric Symptoms in Patients with a Cyst Compressing the Cerebellum: an Ongoing Enigma.

Cerebellum. 2019 Jul 18;:

Authors: Guell X, Anteraper SA, Ghosh SS, Gabrieli JDE, Schmahmann JD

Abstract
A patient diagnosed with developmental delay, intellectual disability, and autistic and obsessive-compulsive symptoms was found to have a posterior fossa arachnoid cyst (PFAC) compressing the cerebellum. The patient was referred to our Ataxia Unit for consideration of surgical drainage of the cyst to improve his clinical constellation. This scenario led to an in-depth analysis including a literature review, functional resting-state MRI analysis of our patient compared to a group of controls, and genetic testing. While it is reasonable to consider that there may be a causal relationship between PFAC and neurodevelopmental or psychiatric symptoms in some patients, there is also a nontrivial prevalence of PFAC in the asymptomatic population and a significant possibility that many PFAC are incidental findings in the context of primary cognitive or psychiatric symptoms. Our functional MRI analysis is the first to examine brain function, and to report cerebellar dysfunction, in a patient presenting with cognitive/psychiatric symptoms found to have a structural abnormality compressing the cerebellum. These neuroimaging findings are inherently limited due to their correlational nature but provide unprecedented evidence suggesting that cerebellar compression may be associated with cerebellar dysfunction. Exome gene sequencing revealed additional etiological possibilities, highlighting the complexity of this field of cerebellar clinical and scientific practice. Our findings and discussion may guide future investigations addressing an important knowledge gap-namely, is there a link between cerebellar compression (including arachnoid cysts and possibly other forms of cerebellar compression such as Chiari malformation), cerebellar dysfunction (including fMRI abnormalities reported here), and neuropsychiatric symptoms?

PMID: 31321675 [PubMed - as supplied by publisher]

Human GABRG2 generalized epilepsy: Increased somatosensory and striatothalamic connectivity.

Sat, 07/20/2019 - 18:34
Related Articles

Human GABRG2 generalized epilepsy: Increased somatosensory and striatothalamic connectivity.

Neurol Genet. 2019 Aug;5(4):e340

Authors: Pedersen M, Kowalczyk M, Omidvarnia A, Perucca P, Gooley S, Petrou S, Scheffer IE, Berkovic SF, Jackson GD

Abstract
Objective: To map functional MRI (fMRI) connectivity within and between the somatosensory cortex, putamen, and ventral thalamus in individuals from a family with a GABAergic deficit segregating with febrile seizures and genetic generalized epilepsy.
Methods: We studied 5 adults from a family with early-onset absence epilepsy and/or febrile seizures and a GABAA receptor subunit gamma2 pathogenic variant (GABRG2[R43Q]) vs 5 age-matched controls. We infer differences between participants with the GABRG2 pathogenic variant and controls in resting-state fMRI connectivity within and between the somatosensory cortex, putamen, and ventral thalamus.
Results: We observed increased fMRI connectivity within the somatosensory cortex and between the putamen and ventral thalamus in all individuals with the GABRG2 pathogenic variant compared with controls. Post hoc analysis showed less pronounced changes in fMRI connectivity within and between the primary visual cortex and precuneus.
Conclusions: Although our sample size was small, this preliminary study suggests that individuals with a GABRG2 pathogenic variant, raising risk of febrile seizures and generalized epilepsy, display underlying increased functional connectivity both within the somatosensory cortex and in striatothalamic networks. This human network model aligns with rodent research and should be further validated in larger cohorts, including other individuals with generalized epilepsy with and without known GABA pathogenic variants.

PMID: 31321301 [PubMed]

Towards prognostic functional brain biomarkers for cervical myelopathy: A resting-state fMRI study.

Sat, 07/20/2019 - 18:34
Related Articles

Towards prognostic functional brain biomarkers for cervical myelopathy: A resting-state fMRI study.

Sci Rep. 2019 Jul 18;9(1):10456

Authors: Takenaka S, Kan S, Seymour B, Makino T, Sakai Y, Kushioka J, Tanaka H, Watanabe Y, Shibata M, Yoshikawa H, Kaito T

Abstract
Recently, there has been increasing interest in strategies to predict neurological recovery in cervical myelopathy (CM) based on clinical images of the cervical spine. In this study, we aimed to explore potential preoperative brain biomarkers that can predict postoperative neurological recovery in CM patients by using resting-state functional magnetic resonance imaging (rs-fMRI) and functional connectivity (FC) analysis. Twenty-eight patients with CM and 28 age- and sex-matched healthy controls (HCs) underwent rs-fMRI (twice for CM patients, before and six months after surgery). A seed-to-voxel analysis was performed, and the following three statistical analyses were conducted: (i) FC comparisons between preoperative CM and HC; (ii) correlation analysis between preoperative FCs and clinical scores; and (iii) postoperative FC changes in CM. Our analyses identified three FCs between the visual cortex and the right superior frontal gyrus based on the conjunction of the first two analyses [(i) and (ii)]. These FCs may act as potential biomarkers for postoperative gain in the 10-second test and might be sufficient to provide a prediction formula for potential recovery. Our findings provide preliminary evidence supporting the possibility of novel predictive measures for neurological recovery in CM using rs-fMRI.

PMID: 31320690 [PubMed - in process]

Neuroinflammation and functional connectivity in Alzheimer's disease: interactive influences on cognitive performance.

Sat, 07/20/2019 - 18:34
Related Articles

Neuroinflammation and functional connectivity in Alzheimer's disease: interactive influences on cognitive performance.

J Neurosci. 2019 Jul 18;:

Authors: Passamonti L, Tsvetanov KA, Jones PS, Bevan-Jones WR, Arnold R, Borchert RJ, Mak E, Su L, O'Brien JT, Rowe JB

Abstract
Neuroinflammation is a key part of the etio-pathogenesis of Alzheimer's disease. We test the relationship between neuroinflammation and the disruption of functional connectivity in large-scale networks, and their joint influence on cognitive impairment.We combined [11C]PK11195 positron emission tomography (PET) and resting-state functional magnetic resonance imaging (rs-fMRI) in 28 humans (12 females/16 males) with clinical diagnosis of probable Alzheimer's disease or mild cognitive impairment with positive PET biomarker for amyloid, and 14 age-, sex-, and education-matched healthy humans (8 females/6 males). Source-based 'inflammetry' was used to extract principal components of [11C]PK11195 PET signal variance across all participants. rs-fMRI data were pre-processed via independent component analyses to classify neuronal and non-neuronal signals. Multiple linear regression models identified sources of signal co-variance between neuroinflammation and brain connectivity profiles, in relation to group and cognitive status.Patients showed significantly higher [11C]PK11195 binding relative to controls, in a distributed spatial pattern including the hippocampus, medial, and inferior temporal cortex. Patients with enhanced loading on this [11C]PK11195 binding distribution displayed diffuse abnormal functional connectivity. The expression of a stronger association between such abnormal connectivity and higher levels of neuroinflammation correlated with worse cognitive deficits.Our study suggests that neuroinflammation relates to the pathophysiological changes in network function that underlie cognitive deficits in Alzheimer's disease. Neuroinflammation, and its association with functionally-relevant reorganisation of brain networks, is proposed as a target for emerging immuno-therapeutic strategies aimed at preventing or slowing the emergence of dementia.SIGNIFICANCE STATEMENTNeuroinflammation is an important aspect of Alzheimer's disease (AD), but it was not known whether the influence of neuroinflammation on brain network function in humans was important for cognitive deficit.Our study provides clear evidence that in vivo neuroinflammation in AD impairs large-scale network connectivity; and that the link between inflammation and functional network connectivity is relevant to cognitive impairment.We suggest that future studies should address how neuroinflammation relates to network function as AD progresses; and whether the neuroinflammation in AD is reversible, as the basis of immunotherapeutic strategies to slow the progression of AD.

PMID: 31320450 [PubMed - as supplied by publisher]

Resting-state functional connectivity and cortical thickness characterization of a patient with Charles Bonnet syndrome.

Fri, 07/19/2019 - 21:33
Related Articles

Resting-state functional connectivity and cortical thickness characterization of a patient with Charles Bonnet syndrome.

PLoS One. 2019;14(7):e0219656

Authors: Martial C, Larroque SK, Cavaliere C, Wannez S, Annen J, Kupers R, Laureys S, Di Perri C

Abstract
Charles Bonnet syndrome (CBS) is a rare condition characterized by visual impairment associated with complex visual hallucinations in elderly people. Although studies suggested that visual hallucinations may be caused by brain damage in the visual system in CBS patients, alterations in specific brain regions in the occipital cortex have not been studied. Functional connectivity during resting-state functional magnetic resonance imaging (rs-fMRI; without hallucinations) in CBS patients, has never been explored. We aimed to investigate brain structural and functional changes in a patient with CBS, as compared with late blind (LB) and normally sighted subjects. We employed voxel-based morphometry and cortical thickness analyses to investigate alterations in grey matter characteristics, and rs-fMRI to study changes in functional brain connectivity. Decreased grey matter volume was observed in the middle occipital gyrus and in the cuneus in the CBS patient, and in the middle occipital gyrus and in the lingual gyrus within LB subjects, compared to their respective control groups. Reductions in cortical thickness in associative and multimodal cortices were observed in the CBS patient when comparing with LB subjects. The precuneus exhibited increased functional connectivity with the secondary visual cortex in the CBS patient compared to the controls. In contrast, LB patients showed decreased functional connectivity compared to sighted controls between the DMN and the temporo-occipital fusiform gyrus, a region known to support hallucinations. Our findings suggest a reorganization of the functional connectivity between regions involved in self-awareness and in visual and salience processing in CBS that may contribute to the appearance of visual hallucinations.

PMID: 31318888 [PubMed - in process]

A pilot study of the effects of running training on visuospatial memory in MS: A stronger functional embedding of the hippocampus in the default-mode network?

Fri, 07/19/2019 - 21:33
Related Articles

A pilot study of the effects of running training on visuospatial memory in MS: A stronger functional embedding of the hippocampus in the default-mode network?

Mult Scler. 2019 Jul 18;:1352458519863644

Authors: Huiskamp M, Moumdjian L, van Asch P, Popescu V, Schoonheim MM, Steenwijk MD, Vanzeir E, van Wijmeersch B, Geurts JJ, Feys P, Hulst HE

Abstract
BACKGROUND/OBJECTIVE: Endurance exercise can improve memory function in persons with multiple sclerosis (pwMS), but the effects on hippocampal functioning are currently unknown. We investigated the effects of a running intervention on memory and hippocampal functional connectivity in pwMS.
METHODS/RESULTS: Memory and resting-state functional magnetic resonance imaging (fMRI) data were collected in a running intervention (n = 15) and waitlist group (n = 14). Visuospatial memory improvement was correlated to increased connectivity between the hippocampus and the default-mode network (DMN) in the intervention group only.
CONCLUSION: As a result of endurance exercise, improvements in visuospatial memory may be mediated by a stronger functional embedding of the hippocampus in the DMN.

PMID: 31317828 [PubMed - as supplied by publisher]

Abnormal Regional Homogeneity in Patients With Obsessive-Compulsive Disorder and Their Unaffected Siblings: A Resting-State fMRI Study.

Fri, 07/19/2019 - 21:33
Related Articles

Abnormal Regional Homogeneity in Patients With Obsessive-Compulsive Disorder and Their Unaffected Siblings: A Resting-State fMRI Study.

Front Psychiatry. 2019;10:452

Authors: Yang X, Luo J, Zhong Z, Yang X, Yao S, Wang P, Gao J, Liu R, Sun J, Li Z

Abstract
Objective: Previous studies suggest that abnormal brain structure and function may be neuroimaging endophenotypes of obsessive-compulsive disorder (OCD). Comparing the intrinsic brain activity of OCD patients and their unaffected siblings will help to further understand the susceptibility to, and pathological mechanisms of, OCD. We used a case-control study design aiming to establish whether the abnormal regional homogeneity (ReHo) found in OCD patients also exists in their unaffected siblings. Method: Fifteen unmedicated OCD patients, 15 of their unaffected siblings, and 30 healthy controls (HCs) received resting-state functional magnetic resonance imaging (r-s fMRI) scanning and clinical evaluation. We used the ReHo method to analyze the inter-regional synchronized activity of all participants. One-way analysis of covariance with post hoc tests was used to compare the ReHo maps across groups. A Pearson correlation analysis was conducted to assess the correlations between clinical characteristics and abnormal ReHo in OCD patients. Results: Relative to HCs, OCD patients and their unaffected siblings showed overlapping higher ReHo values in the right dorsolateral prefrontal cortex (DLPFC). Patients with OCD showed increased ReHo in left middle frontal gyrus (MFG) relative to both their unaffected siblings and HCs. In addition to the right DLPFC and left MFG, OCD patients, compared with HCs, also showed abnormal ReHo in other regions, including higher ReHo in the right superior parietal cortex and lower ReHo in the left inferior parietal cortex, right parahippocampal region, left thalamus, and right inferior temporal cortex. Compared with HCs, the unaffected siblings of patients with OCD had significantly higher ReHo in the right inferior parietal cortex, right MFG, and right supplementary motor area. There was no association between clinical symptoms and abnormal ReHo values in OCD patients. Conclusions: This study found overlapping higher ReHo values in the right DLPFC of OCD patients and their unaffected siblings. Our results suggest that the higher ReHo in the right DLPFC may be a potential neuroimaging endophenotype, which may reflect an increased genetic risk of OCD.

PMID: 31316408 [PubMed]

Altered Static and Temporal Dynamic Amplitude of Low-Frequency Fluctuations in the Background Network During Working Memory States in Mild Cognitive Impairment.

Fri, 07/19/2019 - 21:33
Related Articles

Altered Static and Temporal Dynamic Amplitude of Low-Frequency Fluctuations in the Background Network During Working Memory States in Mild Cognitive Impairment.

Front Aging Neurosci. 2019;11:152

Authors: Wang P, Li R, Liu B, Wang C, Huang Z, Dai R, Song B, Yuan X, Yu J, Li J

Abstract
Previous studies investigating working memory performance in patients with mild cognitive impairment (MCI) have mainly focused on the neural mechanisms of alterations in activation. To date, very few studies have investigated background network alterations in the working memory state. Therefore, the present study investigated the static and temporal dynamic changes in the background network in MCI patients during a working memory task. A hybrid delayed-match-to-sample task was used to examine working memory performance in MCI patients. Functional magnetic resonance imaging (fMRI) data were collected and the marker of amplitude of low-frequency fluctuations (ALFF) was used to investigate alterations in the background network. The present study demonstrated static and dynamic alterations of ALFF in MCI patients during working memory tasks, relative to the resting state. Traditional static analysis revealed that ALFF decreased in the right ventrolateral prefrontal cortex (VLPFC), right dorsolateral PFC (DLPFC), and left supplementary motor area for normal controls (NCs) in the working memory state. However, the same regions showed increased ALFF in MCI patients. Furthermore, relative to NCs, MCI patients demonstrated altered performance-related functional connectivity (FC) patterns, with the right VLPFC and right DLPFC as ROIs. In terms of temporal dynamic analysis, the present study found that in the working memory state dynamic ALFF of bilateral thalamus regions was increased in NCs but decreased in MCI patients. Additionally, MCI patients demonstrated altered performance-related coefficient of variation patterns; the regions in MCI patients were larger and more widely distributed in the parietal and temporal lobes, relative to NCs. This is the first study to examine static and temporal dynamic alterations of ALFF in the background network of MCI patients in working memory states. The results extend previous studies by providing a new perspective on the neural mechanisms of working memory deficits in MCI patients.

PMID: 31316370 [PubMed]

Eigenvector Centrality Dynamics From Resting-State fMRI: Gender and Age Differences in Healthy Subjects.

Fri, 07/19/2019 - 21:33
Related Articles

Eigenvector Centrality Dynamics From Resting-State fMRI: Gender and Age Differences in Healthy Subjects.

Front Neurosci. 2019;13:648

Authors: Wink AM

Abstract
With the increasing use of functional brain network properties as markers of brain disorders, efficient visualization and evaluation methods have become essential. Eigenvector centrality mapping (ECM) of functional MRI (fMRI) data enables the representation of per-node graph theoretical measures as brain maps. This paper studies the use of centrality dynamics for measuring group differences in imaging studies. Imaging data were used from a publicly available imaging study, which included resting fMRI data. After warping the images to a standard space and masking cortical regions, ECM were computed in a sliding window. The dual regression method was used to identify dynamic centrality differences inside well-known resting-state networks between gender and age groups. Gender-related differences were found in the medial and lateral visual, motor, default mode, and executive control RSN, where male subjects had more consistent centrality variations within the network. Age-related differences between the youngest and oldest subjects, based on a median split, were found in the medial visual, executive control and left frontoparietal networks, where younger subjects had more consistent centrality variations within the network. Our findings show that centrality dynamics can be used to identify between-group functional brain network centrality differences, and that age and gender distributions studies need to be taken into account in functional imaging studies.

PMID: 31316335 [PubMed]

Characterizing Whole Brain Temporal Variation of Functional Connectivity via Zero and First Order Derivatives of Sliding Window Correlations.

Fri, 07/19/2019 - 21:33
Related Articles

Characterizing Whole Brain Temporal Variation of Functional Connectivity via Zero and First Order Derivatives of Sliding Window Correlations.

Front Neurosci. 2019;13:634

Authors: Espinoza FA, Vergara VM, Damaraju E, Henke KG, Faghiri A, Turner JA, Belger AA, Ford JM, McEwen SC, Mathalon DH, Mueller BA, Potkin SG, Preda A, Vaidya JG, van Erp TGM, Calhoun VD

Abstract
Brain functional connectivity has been shown to change over time during resting state fMRI experiments. Close examination of temporal changes have revealed a small set of whole-brain connectivity patterns called dynamic states. Dynamic functional network connectivity (dFNC) studies have demonstrated that it is possible to replicate the dynamic states across several resting state experiments. However, estimation of states and their temporal dynamicity still suffers from noisy and imperfect estimations. In regular dFNC implementations, states are estimated by comparing connectivity patterns through the data without considering time, in other words only zero order changes are examined. In this work we propose a method that includes first order variations of dFNC in the searching scheme of dynamic connectivity patterns. Our approach, referred to as temporal variation of functional network connectivity (tvFNC), estimates the derivative of dFNC, and then searches for reoccurring patterns of concurrent dFNC states and their derivatives. The tvFNC method is first validated using a simulated dataset and then applied to a resting-state fMRI sample including healthy controls (HC) and schizophrenia (SZ) patients and compared to the standard dFNC approach. Our dynamic approach reveals extra patterns in the connectivity derivatives complementing the already reported state patterns. State derivatives consist of additional information about increment and decrement of connectivity among brain networks not observed by the original dFNC method. The tvFNC shows more sensitivity than regular dFNC by uncovering additional FNC differences between the HC and SZ groups in each state. In summary, the tvFNC method provides a new and enhanced approach to examine time-varying functional connectivity.

PMID: 31316333 [PubMed]

A macaque connectome for large-scale network simulations in TheVirtualBrain.

Fri, 07/19/2019 - 21:33
Related Articles

A macaque connectome for large-scale network simulations in TheVirtualBrain.

Sci Data. 2019 Jul 17;6(1):123

Authors: Shen K, Bezgin G, Schirner M, Ritter P, Everling S, McIntosh AR

Abstract
Models of large-scale brain networks that are informed by the underlying anatomical connectivity contribute to our understanding of the mapping between the structure of the brain and its dynamical function. Connectome-based modelling is a promising approach to a more comprehensive understanding of brain function across spatial and temporal scales, but it must be constrained by multi-scale empirical data from animal models. Here we describe the construction of a macaque (Macaca mulatta and Macaca fascicularis) connectome for whole-cortex simulations in TheVirtualBrain, an open-source simulation platform. We take advantage of available axonal tract-tracing datasets and enhance the existing connectome data using diffusion-based tractography in macaques. We illustrate the utility of the connectome as an extension of TheVirtualBrain by simulating resting-state BOLD-fMRI data and fitting it to empirical resting-state data.

PMID: 31316116 [PubMed - in process]

Altered temporal dynamics of brain activity in patients with generalized tonic-clonic seizures.

Thu, 07/18/2019 - 18:32

Altered temporal dynamics of brain activity in patients with generalized tonic-clonic seizures.

PLoS One. 2019;14(7):e0219904

Authors: Liu H, Li W, Zhao M, Wu J, Wu J, Yang J, Jiao B

Abstract
Generalized seizures engage bilateral networks from their onset at a low temporal scale. Previous studies findings have demonstrated focal/local brain activity abnormalities in the patients with generalized tonic-clonic seizures (GTCS). Resting state functional magnetic resonance imaging (fMRI) allows the detection of aberrant spontaneous brain activity in GTCS. Little is known, however, about alterations of dynamics (temporal variability) of spontaneous brain activity. It also remains unclear whether temporal variability of spontaneous brain activity is associated with disease severity. To address these questions, the current study assessed patients with GTCS (n = 35), and age- and sex-matched healthy controls (HCs, n = 33) who underwent resting state fMRI. We first assessed the dynamics of spontaneous brain activity using dynamic amplitude of low-frequency fluctuation (dALFF). Furthermore, the temporal variability of brain activity was quantified as the variance of dALFF across sliding window. Compared to HCs, patients with GTCS showed hyper-temporal variability of dALFF in parts of the default mode network, whereas they showed hypo-temporal variability in the somatomotor cortex. Furthermore, dynamic ALFF in the subgenual anterior cingulate cortex was positively correlated with duration of disease, indicating that disease severity is associated with excessive variability. These results suggest both an excessive variability and excessive stability in patients with GTCS. Overall, the current findings from brain activity dynamics contribute to our understanding of the pathophysiological mechanisms of generalized seizure.

PMID: 31314786 [PubMed - in process]