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Spatially guided functional correlation tensor: A new method to associate body mass index and white matter neuroimaging.

Wed, 02/27/2019 - 21:30

Spatially guided functional correlation tensor: A new method to associate body mass index and white matter neuroimaging.

Comput Biol Med. 2019 Feb 19;107:137-144

Authors: Byeon K, Park BY, Park H

Abstract
Obesity causes critical health problems including cardiovascular disease, diabetes, and stroke. Various neuroimaging methods including diffusion tensor imaging (DTI) are used to explore white matter (WM) alterations in obesity. The functional correlation tensor (FCT) is a method to simulate DTI in WM using resting-state functional magnetic resonance imaging (rs-fMRI). In this study, we enhanced the FCT with additional anatomical information from T1-weighted data in a regression framework. The goal was to 1) develop a spatially guided enhanced FCT (s-eFCT) and to 2) use it to identify imaging biomarkers for obesity. We computed fractional anisotropy (FA) and the mean diffusivity (MD) from the s-eFCT. The regional FA and MD values that can explain body mass index (BMI) well were chosen. The identified regional FA and MD values were used to predict BMI values. The correlation between real and predicted BMIs was 0.57. There was no significant correlation between real and predicted DTI using the MD. The BMI predicted using FA was used to classify participants into three obesity subgroups. The classification accuracy was 57.20%. In summary, we found potential imaging biomarkers of obesity based on the s-eFCT.

PMID: 30807908 [PubMed - as supplied by publisher]

Inhibiting mGluR5 activity by AFQ056/Mavoglurant rescues circuit-specific functional connectivity in Fmr1 knockout mice.

Wed, 02/27/2019 - 21:30

Inhibiting mGluR5 activity by AFQ056/Mavoglurant rescues circuit-specific functional connectivity in Fmr1 knockout mice.

Neuroimage. 2019 Feb 23;:

Authors: Zerbi V, Markicevic M, Gasparini F, Schroeter A, Rudin M, Wenderoth N

Abstract
Previous work has demonstrated that neuroimaging biomarkers which capture functional connectivity of the brain can be used to define a specific and robust endophenotype in Fmr1-/y mice, a well-established animal model of human Fragile-X Syndrome (FXS). However, it is currently unknown whether this macroscopic measure of brain connectivity is sufficiently sensitive to reliably detect changes caused by pharmacological interventions. Here we inhibited the activity of the metabotropic glutamate receptor-5 (mGluR5) using AFQ056/Mavoglurant, a drug that is assumed to normalize excitatory/inhibitory neural signaling imbalances in FXS. We employed resting-state-fMRI (rs-fMRI) and diffusion-weighted imaging (DWI) to test whether Mavoglurant re-established brain connectivity - at least partly - within some of the affected circuits in Fmr1-/y mice that are related to social behavior deficits. In line with previous findings, we observed that Fmr1-/y mice exhibited impaired social interaction, reduced connectivity in three main functional networks and altered network topology. At the group level, Mavoglurant did neither rescue abnormal social behavioral nor white matter abnormalities; however, for some, but not all of these circuits Mavoglurant had a genotype-specific effect of restoring functional connectivity. These results show that rs-fMRI connectivity is sufficiently sensitive to pick up system-level changes after the pharmacological inhibition of mGluR5 activity. However, our results also show that the effects of Mavoglurant are confined to specific networks suggesting that behavioral benefits might be restricted to narrow functional domains.

PMID: 30807820 [PubMed - as supplied by publisher]

Hypersynchronicity in the default mode-like network in a neurodevelopmental animal model with relevance for schizophrenia.

Wed, 02/27/2019 - 21:30

Hypersynchronicity in the default mode-like network in a neurodevelopmental animal model with relevance for schizophrenia.

Behav Brain Res. 2019 Feb 23;:

Authors: Missault S, Anckaerts C, Ahmadoun S, Blockx I, Barbier M, Bielen K, Shah D, Kumar-Singh S, De Vos WH, Van der Linden A, Dedeurwaerdere S, Verhoye M

Abstract
BACKGROUND: Immune activation during pregnancy is an important risk factor for schizophrenia. Brain dysconnectivity and NMDA receptor (NMDAR) hypofunction have been postulated to be central to schizophrenia pathophysiology. The aim of this study was to investigate resting-state functional connectivity (resting-state functional MRI-rsfMRI), microstructure (diffusion tension imaging-DTI) and response to NMDAR antagonist (pharmacological fMRI-phMRI) using multimodal MRI in offspring of pregnant dams exposed to immune challenge (maternal immune activation-MIA model), and determine whether these neuroimaging readouts correlate with schizophrenia-related behaviour.
METHODS: Pregnant rats were injected with Poly I:C or saline on gestational day 15. The maternal weight response was assessed. Since previous research has shown behavioural deficits can differ between MIA offspring dependent on the maternal response to immune stimulus, offspring were divided into three groups: controls (saline, n = 11), offspring of dams that gained weight (Poly I:C WG, n = 12) and offspring of dams that lost weight post-MIA (Poly I:C WL, n = 16). Male adult offspring were subjected to rsfMRI, DTI, phMRI with NMDAR antagonist, behavioural testing and histological assessment.
RESULTS: Poly I:C WL offspring exhibited increased functional connectivity in default mode-like network (DMN). Poly I:C WG offspring showed the most pronounced attenuation in NMDAR antagonist response versus controls. DTI revealed no differences in Poly I:C offspring versus controls. Poly I:C offspring exhibited anxiety.
CONCLUSIONS: MIA offspring displayed a differential pathophysiology depending on the maternal response to immune challenge. While Poly I:C WL offspring displayed hypersynchronicity in the DMN, altered NMDAR antagonist response was most pronounced in Poly I:C WG offspring.

PMID: 30807809 [PubMed - as supplied by publisher]

Functional specialization of macaque premotor F5 subfields with respect to hand and mouth movements: A comparison of task and resting-state fMRI.

Wed, 02/27/2019 - 03:30
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Functional specialization of macaque premotor F5 subfields with respect to hand and mouth movements: A comparison of task and resting-state fMRI.

Neuroimage. 2019 Feb 22;:

Authors: Sharma S, Mantini D, Vanduffel W, Nelissen K

Abstract
Based on architectonic, tract-tracing or functional criteria, the rostral portion of ventral premotor cortex in the macaque monkey, also termed area F5, has been divided into several subfields. Cytoarchitectonical investigations suggest the existence of three subfields, F5c (convexity), F5p (posterior) and F5a (anterior). Electrophysiological investigations have suggested a gradual dorso-ventral transition from hand-to mouth-dominated motor fields, with F5p and ventral F5c strictly related to hand movements and mouth movements, respectively. The involvement of F5a in this respect, however, has received much less attention. Recently, data-driven resting-state fMRI approaches have also been used to examine the presence of distinct functional fields in macaque ventral premotor cortex. Although these studies have suggested several functional clusters in/near macaque F5, so far the parcellation schemes derived from these clustering methods do not completely retrieve the same level of F5 specialization as suggested by aforementioned invasive techniques. Here, using seed-based resting-state fMRI analyses, we examined the functional connectivity of different F5 seeds with key regions of the hand and face/mouth parieto-frontal-insular motor networks. In addition, we trained monkeys to perform either hand grasping or ingestive mouth movements in the scanner in order to compare resting-state with task-derived functional hand and mouth motor networks. In line with previous single-cell investigations, task-fMRI suggests involvement of F5p, dorsal F5c and F5a in the execution of hand grasping movements, while non-communicative mouth movements yielded particularly pronounced responses in ventral F5c. Corroborating with anatomical tracing data of macaque F5 subfields, seed-based resting-state fMRI suggests a transition from predominant functional correlations with the hand-motor network in F5p to mostly mouth-motor network functional correlations in ventral F5c. Dorsal F5c yielded robust functional correlations with both hand- and mouth-motor networks. In addition, the deepest part of the fundus of the inferior arcuate, corresponding to area 44, displayed a strikingly different functional connectivity profile compared to neighboring F5a, suggesting a different functional specialization for these two neighboring regions.

PMID: 30802514 [PubMed - as supplied by publisher]

EEG spatiospectral patterns and their link to fMRI BOLD signal via variable hemodynamic response functions.

Wed, 02/27/2019 - 03:30
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EEG spatiospectral patterns and their link to fMRI BOLD signal via variable hemodynamic response functions.

J Neurosci Methods. 2019 Feb 22;:

Authors: Labounek R, Bridwell DA, Mareček R, Lamoš M, Mikl M, Bednařík P, Baštinec J, Slavíček T, Hluštík P, Brázdil M, Jan J

Abstract
BACKGROUND: Spatial and temporal resolution of brain network activity can be improved by combining different modalities. Functional Magnetic Resonance Imaging (fMRI) provides full brain coverage with limited temporal resolution, while electroencephalography (EEG), estimates cortical activity with high temporal resolution. Combining them may provide improved network characterization. New Method: We examined relationships between EEG spatiospectral pattern timecourses and concurrent fMRI BOLD signals using canonical hemodynamic response function (HRF) with its 1st and 2nd temporal derivatives in voxel-wise general linear models (GLM). HRF shapes were derived from EEG-fMRI time courses during "resting-state", visual oddball and semantic decision paradigms.
RESULTS: The resulting GLM F-maps self-organized into several different large-scale brain networks (LSBNs) often with different timing between EEG and fMRI revealed through differences in GLM-derived HRF shapes (e.g., with a lower time to peak than the canonical HRF). We demonstrate that some EEG spatiospectral patterns (related to concurrent fMRI) are weakly task-modulated. Comparison with Existing Method(s): Previously, we demonstrated 14 independent EEG spatiospectral patterns within this EEG dataset, stable across the resting-state, visual oddball and semantic decision paradigms. Here, we demonstrate that their time courses are significantly correlated with fMRI dynamics organized into LSBN structures. EEG-fMRI derived HRF peak appears earlier than the canonical HRF peak, which suggests limitations when assuming a canonical HRF shape in EEG-fMRI.
CONCLUSIONS: This is the first study examining EEG-fMRI relationships among independent EEG spatiospectral patterns over different paradigms. The findings highlight the importance of considering different HRF shapes when spatiotemporally characterizing brain networks using EEG and fMRI.

PMID: 30802472 [PubMed - as supplied by publisher]

Functional MRI reveals effects of high intraocular pressure on central nervous system in high-tension glaucoma patients.

Wed, 02/27/2019 - 03:30
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Functional MRI reveals effects of high intraocular pressure on central nervous system in high-tension glaucoma patients.

Acta Ophthalmol. 2019 Feb 22;:

Authors: Wang Y, Lu W, Yan T, Zhou J, Xie Y, Yuan J, Liu G, Teng Y, Han W, Chen D, Qiu J

Abstract
PURPOSE: To evaluate the effects of high intraocular pressure (IOP) on central nervous system in patients with high-tension glaucoma (HTG) by using resting-state functional magnetic resonance imaging (rs-fMRI).
METHODS: Thirty-six patients with HTG and twenty age- and gender-matched healthy controls (HCs) were recruited and underwent IOP measurement and rs-fMRI scan. The whole brain regional homogeneity (ReHo) value was calculated among the enrolled subjects. Two-sample t tests with permutation test and threshold-free cluster enhancement was performed between HTG group and HCs. Correlation analyses between IOP and ReHo values were conducted.
RESULTS: Compared with HCs, HTG group showed increased ReHo values in the left lobule 8 of cerebellar hemisphere, left lobule 4 and 5 of cerebellar hemisphere and left fusiform gyrus (FG) (p < 0.05). HTG group showed decreased ReHo value in the left middle frontal gyrus (MFG) (p < 0.05). Intraocular pressure of the left eye in HTG group experienced a significant positive correlation with ReHo value of the left FG (r = 0.370, p = 0.026), IOP of the right eye in HTG group showed a significant negative correlation with ReHo value in the left MFG (r = -0.421, p = 0.011).
CONCLUSION: Resting-state fMRI ReHo analyses associated elevated IOP with abnormal regional activity in several brain regions related to higher visual function and visual memory consolidation. High-tension glaucoma patients also showed diminished integration of visual information and cerebellar function. These results may provide imaging support for pathophysiological research of HTG and may reveal new targets for the accurate treatment of HTG.

PMID: 30801975 [PubMed - as supplied by publisher]

Abnormal functional network centrality in drug-naïve boys with attention-deficit/hyperactivity disorder.

Tue, 02/26/2019 - 00:29
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Abnormal functional network centrality in drug-naïve boys with attention-deficit/hyperactivity disorder.

Eur Child Adolesc Psychiatry. 2019 Feb 23;:

Authors: Zhou M, Yang C, Bu X, Liang Y, Lin H, Hu X, Chen H, Wang M, Huang X

Abstract
Attention-deficit/hyperactivity disorder (ADHD) is the most commonly diagnosed neurodevelopmental disorder in childhood and is characterized by inattention, impulsivity, and hyperactivity. Observations of distributed functional abnormalities in ADHD suggest aberrant large-scale brain network connectivity. However, few studies have measured the voxel-wise network centrality of boys with ADHD, which captures the functional relationships of a given voxel within the entire connectivity matrix of the brain. Here, to examine the network patterns characterizing children with ADHD, we recruited 47 boys with ADHD and 21 matched control boys who underwent resting-state functional imaging scanning in a 3.0 T MRI unit. We measured voxel-wise network centrality, indexing local functional relationships across the entire brain connectome, termed degree centrality (DC). Then, we chose the brain regions with altered DC as seeds to examine the remote functional connectivity (FC) of brain regions. We found that boys with ADHD exhibited (1) decreased centrality in the left superior temporal gyrus (STG) and increased centrality in the left superior occipital lobe (SOL) and right inferior parietal lobe (IPL); (2) decreased FC between the STG and the putamen and thalamus, which belong to the cognitive cortico-striatal-thalamic-cortical (CSTC) loop, and increased FC between the STG and medial/superior frontal gyrus within the affective CSTC loop; and (3) decreased connectivity between the SOL and cuneus within the dorsal attention network. Our results demonstrated that patients with ADHD show a connectivity-based pathophysiological process in the cognitive and affective CSTC loops and attention network.

PMID: 30798413 [PubMed - as supplied by publisher]

Distinct Structure of Cortical Population Activity on Fast and Infraslow Timescales.

Mon, 02/25/2019 - 00:28
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Distinct Structure of Cortical Population Activity on Fast and Infraslow Timescales.

Cereb Cortex. 2019 Feb 23;:

Authors: Okun M, Steinmetz NA, Lak A, Dervinis M, Harris KD

Abstract
Cortical activity is organized across multiple spatial and temporal scales. Most research on the dynamics of neuronal spiking is concerned with timescales of 1 ms-1 s, and little is known about spiking dynamics on timescales of tens of seconds and minutes. Here, we used frequency domain analyses to study the structure of individual neurons' spiking activity and its coupling to local population rate and to arousal level across 0.01-100 Hz frequency range. In mouse medial prefrontal cortex, the spiking dynamics of individual neurons could be quantitatively captured by a combination of interspike interval and firing rate power spectrum distributions. The relative strength of coherence with local population often differed across timescales: a neuron strongly coupled to population rate on fast timescales could be weakly coupled on slow timescales, and vice versa. On slow but not fast timescales, a substantial proportion of neurons showed firing anticorrelated with the population. Infraslow firing rate changes were largely determined by arousal rather than by local factors, which could explain the timescale dependence of individual neurons' population coupling strength. These observations demonstrate how neurons simultaneously partake in fast local dynamics, and slow brain-wide dynamics, extending our understanding of infraslow cortical activity beyond the mesoscale resolution of fMRI.

PMID: 30796825 [PubMed - as supplied by publisher]

Using resting-state DMN effective connectivity to characterize the neurofunctional architecture of empathy.

Mon, 02/25/2019 - 00:28
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Using resting-state DMN effective connectivity to characterize the neurofunctional architecture of empathy.

Sci Rep. 2019 Feb 22;9(1):2603

Authors: Esménio S, Soares JM, Oliveira-Silva P, Zeidman P, Razi A, Gonçalves ÓF, Friston K, Coutinho J

Abstract
Neuroimaging studies in social neuroscience have largely relied on functional connectivity (FC) methods to characterize the functional integration between different brain regions. However, these methods have limited utility in social-cognitive studies that aim to understand the directed information flow among brain areas that underlies complex psychological processes. In this study we combined functional and effective connectivity approaches to characterize the functional integration within the Default Mode Network (DMN) and its role in self-perceived empathy. Forty-two participants underwent a resting state fMRI scan and completed a questionnaire of dyadic empathy. Independent Component Analysis (ICA) showed that higher empathy scores were associated with an increased contribution of the medial prefrontal cortex (mPFC) to the DMN spatial mode. Dynamic causal modelling (DCM) combined with Canonical Variance Analysis (CVA) revealed that this association was mediated indirectly by the posterior cingulate cortex (PCC) via the right inferior parietal lobule (IPL). More specifically, in participants with higher scores in empathy, the PCC had a greater effect on bilateral IPL and the right IPL had a greater influence on mPFC. These results highlight the importance of using analytic approaches that address directed and hierarchical connectivity within networks, when studying complex psychological phenomena, such as empathy.

PMID: 30796260 [PubMed - in process]

Neuromelanin-sensitive MRI as a noninvasive proxy measure of dopamine function in the human brain.

Mon, 02/25/2019 - 00:28
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Neuromelanin-sensitive MRI as a noninvasive proxy measure of dopamine function in the human brain.

Proc Natl Acad Sci U S A. 2019 Feb 22;:

Authors: Cassidy CM, Zucca FA, Girgis RR, Baker SC, Weinstein JJ, Sharp ME, Bellei C, Valmadre A, Vanegas N, Kegeles LS, Brucato G, Jung Kang U, Sulzer D, Zecca L, Abi-Dargham A, Horga G

Abstract
Neuromelanin-sensitive MRI (NM-MRI) purports to detect the content of neuromelanin (NM), a product of dopamine metabolism that accumulates with age in dopamine neurons of the substantia nigra (SN). Interindividual variability in dopamine function may result in varying levels of NM accumulation in the SN; however, the ability of NM-MRI to measure dopamine function in nonneurodegenerative conditions has not been established. Here, we validated that NM-MRI signal intensity in postmortem midbrain specimens correlated with regional NM concentration even in the absence of neurodegeneration, a prerequisite for its use as a proxy for dopamine function. We then validated a voxelwise NM-MRI approach with sufficient anatomical sensitivity to resolve SN subregions. Using this approach and a multimodal dataset of molecular PET and fMRI data, we further showed the NM-MRI signal was related to both dopamine release in the dorsal striatum and resting blood flow within the SN. These results suggest that NM-MRI signal in the SN is a proxy for function of dopamine neurons in the nigrostriatal pathway. As a proof of concept for its clinical utility, we show that the NM-MRI signal correlated to severity of psychosis in schizophrenia and individuals at risk for schizophrenia, consistent with the well-established dysfunction of the nigrostriatal pathway in psychosis. Our results indicate that noninvasive NM-MRI is a promising tool that could have diverse research and clinical applications to investigate in vivo the role of dopamine in neuropsychiatric illness.

PMID: 30796187 [PubMed - as supplied by publisher]

Age differences in specific neural connections within the Default Mode Network underlie theory of mind.

Sun, 02/24/2019 - 00:26
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Age differences in specific neural connections within the Default Mode Network underlie theory of mind.

Neuroimage. 2019 Feb 19;:

Authors: Hughes C, Cassidy BS, Faskowitz J, Avena-Koenigsberger A, Sporns O, Krendl AC

Abstract
Theory of mind (i.e., the ability to infer others' mental states) - a fundamental social cognitive ability - declines with increasing age. Prior investigations have focused on identifying task-evoked differences in neural activation that underlie these performance declines. However, these declines could also be related to dysregulation of the baseline, or 'intrinsic', functional connectivity of the brain. If so, age differences in intrinsic connectivity may provide novel insight into the mechanisms that contribute to poorer theory of mind in older adults. To examine this possibility, we assessed younger and older adults' theory of mind while they underwent task-based fMRI, as well as the intrinsic functional connectivity measured during resting-state within the (task-defined) theory of mind network. Older adults exhibited poorer theory of mind behavioral performance and weaker intrinsic connectivity within this network compared to younger adults. Intrinsic connectivity between the right temporoparietal junction and the right temporal pole mediated age differences in theory of mind. Specifically, older adults had weaker intrinsic connectivity between right temporoparietal junction and right temporal pole that explained their poorer theory of mind behavioral performance. These findings broaden our understanding of aging and social cognition and reveal more specific mechanisms of how aging impacts theory of mind.

PMID: 30794869 [PubMed - as supplied by publisher]

Hybrid multivariate pattern analysis combined with extreme learning machine for Alzheimer's dementia diagnosis using multi-measure rs-fMRI spatial patterns.

Sun, 02/24/2019 - 00:26
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Hybrid multivariate pattern analysis combined with extreme learning machine for Alzheimer's dementia diagnosis using multi-measure rs-fMRI spatial patterns.

PLoS One. 2019;14(2):e0212582

Authors: Nguyen DT, Ryu S, Qureshi MNI, Choi M, Lee KH, Lee B

Abstract
BACKGROUND: Early diagnosis of Alzheimer's disease (AD) and Mild Cognitive Impairment (MCI) is essential for timely treatment. Machine learning and multivariate pattern analysis (MVPA) for the diagnosis of brain disorders are explicitly attracting attention in the neuroimaging community. In this paper, we propose a voxel-wise discriminative framework applied to multi-measure resting-state fMRI (rs-fMRI) that integrates hybrid MVPA and extreme learning machine (ELM) for the automated discrimination of AD and MCI from the cognitive normal (CN) state.
MATERIALS AND METHODS: We used two rs-fMRI cohorts: the public Alzheimer's disease Neuroimaging Initiative database (ADNI2) and an in-house Alzheimer's disease cohort from South Korea, both including individuals with AD, MCI, and normal controls. After extracting three-dimensional (3-D) patterns measuring regional coherence and functional connectivity during the resting state, we performed univariate statistical t-tests to generate a 3-D mask that retained only voxels showing significant changes. Given the initial univariate features, to enhance discriminative patterns, we implemented MVPA feature reduction using support vector machine-recursive feature elimination (SVM-RFE), and least absolute shrinkage and selection operator (LASSO), in combination with the univariate t-test. Classifications were performed by an ELM, and its efficiency was compared to linear and nonlinear (radial basis function) SVMs.
RESULTS: The maximal accuracies achieved by the method in the ADNI2 cohort were 98.86% (p<0.001) and 98.57% (p<0.001) for AD and MCI vs. CN, respectively. In the in-house cohort, the same accuracies were 98.70% (p<0.001) and 94.16% (p<0.001).
CONCLUSION: From a clinical perspective, combining extreme learning machine and hybrid MVPA applied on concatenations of multiple rs-fMRI biomarkers can potentially assist the clinicians in AD and MCI diagnosis.

PMID: 30794629 [PubMed - in process]

Regional dynamics of the resting brain in amyotrophic lateral sclerosis using fALFF and ReHo analyses.

Sun, 02/24/2019 - 00:26
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Regional dynamics of the resting brain in amyotrophic lateral sclerosis using fALFF and ReHo analyses.

Brain Connect. 2019 Feb 22;:

Authors: Bueno AP, Pinaya WHL, Rebello K, de Souza LC, Hornberger M, Sato JR

Abstract
Resting state functional magnetic resonance imaging (rs-fMRI) has been playing an important role in the study of amyotrophic lateral sclerosis (ALS). Although functional connectivity is widely studied, the patterns of spontaneous neural activity of the resting brain are important mechanisms that have been used recently to study a variety of conditions but remain less explored in ALS. Here we have used fractional amplitude of low-frequency fluctuations (fALFF) and regional homogeneity (ReHo) to study the regional dynamics of the resting brain of non-demented ALS patients compared with healthy controls. As expected, we found the sensorimotor network (SMN) with changes in fALFF and ReHo but also found the default mode (DMN), frontoparietal (FPN), salience (SN) networks altered and the cerebellum, although no structural changes between ALS patients and controls were reported in the regions with fALFF and ReHo changes. We show an altered pattern in the spontaneous low frequency oscillations that is not confined to the motor areas and reveal a more widespread involvement of non-motor regions, including those responsible for cognition.

PMID: 30793923 [PubMed - as supplied by publisher]

A common neural substrate for elevated PTSD symptoms and reduced pulse rate variability in combat-exposed veterans.

Sun, 02/24/2019 - 00:26
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A common neural substrate for elevated PTSD symptoms and reduced pulse rate variability in combat-exposed veterans.

Psychophysiology. 2019 Feb 22;:e13352

Authors: Grupe DW, Imhoff-Smith T, Wielgosz J, Nitschke JB, Davidson RJ

Abstract
Previous studies have identified reduced heart rate variability (HRV) in post-traumatic stress disorder (PTSD), which may temporally precede the onset of the disorder. A separate line of functional neuroimaging research in PTSD has consistently demonstrated hypoactivation of the ventromedial prefrontal cortex (vmPFC), a key aspect of a descending neuromodulatory system that exerts inhibitory control over heart rate. No research to date, however, has simultaneously investigated whether altered vmPFC activation is associated with reduced HRV and elevated PTSD symptoms in the same individuals. Here, we collected fMRI data during alternating conditions of threat of shock and safety from shock in 51 male combat-exposed veterans with either high or low levels of PTSD symptoms. Pulse rate variability (PRV)-a HRV surrogate calculated from pulse oximetry-was assessed during a subsequent resting scan. Correlational analyses tested for hypothesized relationships between reduced vmPFC activation, lower PRV, and elevated PTSD symptomatology. We found that PTSD re-experiencing symptoms were inversely associated with high-frequency (HF)-PRV, thought to primarily reflect parasympathetic control of heart rate, in veterans with elevated PTSD symptoms. Reduced vmPFC activation for the contrast of safety-threat was associated both with lower HF-PRV and elevated PTSD re-experiencing symptoms. These results tie together previous observations of reduced HRV/PRV and impaired vmPFC function in PTSD and call for further research on reciprocal brain-body relationships in understanding PTSD pathophysiology.

PMID: 30793774 [PubMed - as supplied by publisher]

Network abnormalities among non-manifesting Parkinson disease related LRRK2 mutation carriers.

Sun, 02/24/2019 - 00:26
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Network abnormalities among non-manifesting Parkinson disease related LRRK2 mutation carriers.

Hum Brain Mapp. 2019 Feb 21;:

Authors: Jacob Y, Rosenberg-Katz K, Gurevich T, Helmich RC, Bloem BR, Orr-Urtreger A, Giladi N, Mirelman A, Hendler T, Thaler A

Abstract
Non-manifesting carriers (NMC) of the G2019S mutation in the LRRK2 gene represent an "at risk" group for future development of Parkinson's disease (PD) and have demonstrated task related fMRI changes. However, resting-state networks have received less research focus, thus this study aimed to assess the integrity of the motor, default mode (DMN), salience (SAL), and dorsal attention (DAN) networks among this unique population by using two different connectivity measures: interregional functional connectivity analysis and Dependency network analysis (DEP NA). Machine learning classification methods were used to distinguish connectivity between the two groups of participants. Forty-four NMC and 41 non-manifesting non-carriers (NMNC) participated in this study; while no behavioral differences on standard questionnaires could be detected, NMC demonstrated lower connectivity measures in the DMN, SAL, and DAN compared to NMNC but not in the motor network. Significant correlations between NMC connectivity measures in the SAL and attention were identified. Machine learning classification separated NMC from NMNC with an accuracy rate above 0.8. Reduced integrity of non-motor networks was detected among NMC of the G2019S mutation in the LRRK2 gene prior to identifiable changes in connectivity of the motor network, indicating significant non-motor cerebral changes among populations "at risk" for future development of PD.

PMID: 30793410 [PubMed - as supplied by publisher]

Evaluation of confound regression strategies for the mitigation of micromovement artifact in studies of dynamic resting-state functional connectivity and multilayer network modularity.

Sun, 02/24/2019 - 00:26
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Evaluation of confound regression strategies for the mitigation of micromovement artifact in studies of dynamic resting-state functional connectivity and multilayer network modularity.

Netw Neurosci. 2019;3(2):427-454

Authors: Lydon-Staley DM, Ciric R, Satterthwaite TD, Bassett DS

Abstract
Dynamic functional connectivity reflects the spatiotemporal organization of spontaneous brain activity in health and disease. Dynamic functional connectivity may be susceptible to artifacts induced by participant motion. This report provides a systematic evaluation of 12 commonly used participant-level confound regression strategies designed to mitigate the effects of micromovements in a sample of 393 youths (ages 8-22 years). Each strategy was evaluated according to a number of benchmarks, including (a) the residual association between participant motion and edge dispersion, (b) distance-dependent effects of motion on edge dispersion, (c) the degree to which functional subnetworks could be identified by multilayer modularity maximization, and (d) measures of module reconfiguration, including node flexibility and node promiscuity. Results indicate variability in the effectiveness of the evaluated pipelines across benchmarks. Methods that included global signal regression were the most consistently effective de-noising strategies.

PMID: 30793090 [PubMed]

Dynamic properties of simulated brain network models and empirical resting-state data.

Sun, 02/24/2019 - 00:26
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Dynamic properties of simulated brain network models and empirical resting-state data.

Netw Neurosci. 2019;3(2):405-426

Authors: Kashyap A, Keilholz S

Abstract
Brain network models (BNMs) have become a promising theoretical framework for simulating signals that are representative of whole-brain activity such as resting-state fMRI. However, it has been difficult to compare the complex brain activity obtained from simulations to empirical data. Previous studies have used simple metrics to characterize coordination between regions such as functional connectivity. We extend this by applying various different dynamic analysis tools that are currently used to understand empirical resting-state fMRI (rs-fMRI) to the simulated data. We show that certain properties correspond to the structural connectivity input that is shared between the models, and certain dynamic properties relate more to the mathematical description of the brain network model. We conclude that the dynamic properties that explicitly examine patterns of signal as a function of time rather than spatial coordination between different brain regions in the rs-fMRI signal seem to provide the largest contrasts between different BNMs and the unknown empirical dynamical system. Our results will be useful in constraining and developing more realistic simulations of whole-brain activity.

PMID: 30793089 [PubMed]

High-accuracy individual identification using a "thin slice" of the functional connectome.

Sun, 02/24/2019 - 00:26
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High-accuracy individual identification using a "thin slice" of the functional connectome.

Netw Neurosci. 2019;3(2):363-383

Authors: Byrge L, Kennedy DP

Abstract
Connectome fingerprinting-a method that uses many thousands of functional connections in aggregate to identify individuals-holds promise for individualized neuroimaging. A better characterization of the features underlying successful fingerprinting performance-how many and which functional connections are necessary and/or sufficient for high accuracy-will further inform our understanding of uniqueness in brain functioning. Thus, here we examine the limits of high-accuracy individual identification from functional connectomes. Using ∼3,300 scans from the Human Connectome Project in a split-half design and an independent replication sample, we find that a remarkably small "thin slice" of the connectome-as few as 40 out of 64,620 functional connections-was sufficient to uniquely identify individuals. Yet, we find that no specific connections or even specific networks were necessary for identification, as even small random samples of the connectome were sufficient. These results have important conceptual and practical implications for the manifestation and detection of uniqueness in the brain.

PMID: 30793087 [PubMed]

Estimating feedforward and feedback effective connections from fMRI time series: Assessments of statistical methods.

Sun, 02/24/2019 - 00:26
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Estimating feedforward and feedback effective connections from fMRI time series: Assessments of statistical methods.

Netw Neurosci. 2019;3(2):274-306

Authors: Sanchez-Romero R, Ramsey JD, Zhang K, Glymour MRK, Huang B, Glymour C

Abstract
We test the adequacies of several proposed and two new statistical methods for recovering the causal structure of systems with feedback from synthetic BOLD time series. We compare an adaptation of the first correct method for recovering cyclic linear systems; Granger causal regression; a multivariate autoregressive model with a permutation test; the Group Iterative Multiple Model Estimation (GIMME) algorithm; the Ramsey et al. non-Gaussian methods; two non-Gaussian methods by Hyvärinen and Smith; a method due to Patel et al.; and the GlobalMIT algorithm. We introduce and also compare two new methods, Fast Adjacency Skewness (FASK) and Two-Step, both of which exploit non-Gaussian features of the BOLD signal. We give theoretical justifications for the latter two algorithms. Our test models include feedback structures with and without direct feedback (2-cycles), excitatory and inhibitory feedback, models using experimentally determined structural connectivities of macaques, and empirical human resting-state and task data. We find that averaged over all of our simulations, including those with 2-cycles, several of these methods have a better than 80% orientation precision (i.e., the probability of a directed edge is in the true structure given that a procedure estimates it to be so) and the two new methods also have better than 80% recall (probability of recovering an orientation in the true structure).

PMID: 30793083 [PubMed]

Global connectivity of the fronto-parietal cognitive control network is related to depression symptoms in the general population.

Sun, 02/24/2019 - 00:26
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Global connectivity of the fronto-parietal cognitive control network is related to depression symptoms in the general population.

Netw Neurosci. 2019;3(1):107-123

Authors: Schultz DH, Ito T, Solomyak LI, Chen RH, Mill RD, Anticevic A, Cole MW

Abstract
We all vary in our mental health, even among people not meeting diagnostic criteria for mental illness. Understanding this individual variability may reveal factors driving the risk for mental illness, as well as factors driving subclinical problems that still adversely affect quality of life. To better understand the large-scale brain network mechanisms underlying this variability, we examined the relationship between mental health symptoms and resting-state functional connectivity patterns in cognitive control systems. One such system is the fronto-parietal cognitive control network (FPN). Changes in FPN connectivity may impact mental health by disrupting the ability to regulate symptoms in a goal-directed manner. Here we test the hypothesis that FPN dysconnectivity relates to mental health symptoms even among individuals who do not meet formal diagnostic criteria but may exhibit meaningful symptom variation. We found that depression symptoms severity negatively correlated with between-network global connectivity (BGC) of the FPN. This suggests that decreased connectivity between the FPN and the rest of the brain is related to increased depression symptoms in the general population. These findings complement previous clinical studies to support the hypothesis that global FPN connectivity contributes to the regulation of mental health symptoms across both health and disease.

PMID: 30793076 [PubMed]