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Characterization of Cerebellar Atrophy and Resting State Functional Connectivity Patterns in Sporadic Adult-Onset Ataxia of Unknown Etiology (SAOA).

Tue, 08/20/2019 - 19:13
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Characterization of Cerebellar Atrophy and Resting State Functional Connectivity Patterns in Sporadic Adult-Onset Ataxia of Unknown Etiology (SAOA).

Cerebellum. 2019 Aug 17;:

Authors: Jiang X, Faber J, Giordano I, Machts J, Kindler C, Dudesek A, Speck O, Kamm C, Düzel E, Jessen F, Spottke A, Vielhaber S, Boecker H, Klockgether T, Scheef L

Abstract
Sporadic adult-onset ataxia of unknown etiology (SAOA) is a non-genetic neurodegenerative disorder of the cerebellum of unknown cause which manifests with progressive ataxia without severe autonomic failure. Although SAOA is associated with cerebellar degeneration, little is known about the specific cerebellar atrophy pattern in SAOA. Thirty-seven SAOA patients and 49 healthy controls (HCs) were included at two centers. We investigated the structural and functional characteristics of SAOA brains using voxel-based morphometry (VBM) and resting-state functional imaging (rs-fMRI). In order to examine the functional consequence of structural cerebellar alterations, the amplitude of low-frequency fluctuation (ALFF) and degree centrality (DC) were analyzed, and then assessed their relation with disease severity, disease duration, and age of onset within these regions. Group differences were investigated using two-sample t tests, controlling for age, gender, site, and the total intracranial volume. The VBM analysis revealed a significant, mostly bilateral reduction of local gray matter (GM) volume in lobules I-V, V, VI, IX, X, and vermis VIII a/b in SAOA patients, compared with HCs. The GM volume loss in these regions was significantly associated with disease severity, disease duration, and age of onset. The disease-related atrophy regions did not show any functional alternations compared with HCs but were functionally characterized by high ALFF and poor DC compared with intact cerebellar regions. Our data revealed volume reduction in SAOA in cerebellar regions that are known to be involved in motor and somatosensory processing, corresponding with the clinical phenotype of SAOA. Our data suggest that the atrophy occurs in those cerebellar regions which are characterized by high ALFF and poor DC. Further studies have to show if these findings are specific for SAOA, and if they can be used to predict disease progression.

PMID: 31422550 [PubMed - as supplied by publisher]

Transcranial direct current stimulation facilitates response inhibition through dynamic modulation of the fronto-basal ganglia network.

Tue, 08/20/2019 - 19:13
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Transcranial direct current stimulation facilitates response inhibition through dynamic modulation of the fronto-basal ganglia network.

Brain Stimul. 2019 Aug 07;:

Authors: Sandrini M, Xu B, Volochayev R, Awosika O, Wang WT, Butman JA, Cohen LG

Abstract
BACKGROUND: Response inhibition refers to the ability to stop an on-going action quickly when it is no longer appropriate. Previous studies showed that transcranial direct current stimulation (tDCS) applied with the anode over the right inferior frontal cortex (rIFC), a critical node of the fronto-basal ganglia inhibitory network, improved response inhibition. However, the tDCS effects on brain activity and network connectivity underlying this behavioral improvement are not known.
OBJECTIVE: This study aimed to address the effects of tDCS applied with the anode over the rIFC on brain activity and network functional connectivity underlying the behavioral change in response inhibition.
METHODS: Thirty participants performed a stop-signal task in a typical laboratory setting as a baseline during the first study visit (i.e., Session 1). In the second visit (at least 24 h after Session 1), all participants underwent resting-state functional magnetic resonance imaging (rsfMRI) scans before and after 1.5 mA tDCS (Anodal or Sham). Immediately following the post-tDCS rsfMRI, participants performed the same stop-signal task as in Session 1 during an event-related fMRI (efMRI) scan in a 3T scanner. Changes in task performance, i.e., the stop-signal response time (SSRT), a measure of response inhibition efficiency, was determined relative to the participants' own baseline performance in Session 1.
RESULTS: Consistent with previous findings, Anodal tDCS facilitated the SSRT. efMRI results showed that Anodal tDCS strengthened the functional connectivity between right pre-supplementary motor area (rPreSMA) and subthalamic nuclei during Stop responses. rsfMRI revealed changes in intrinsic connectivity between rIFC and caudate, and between rIFC, rPreSMA, right inferior parietal cortex (rIPC), and right dorsolateral prefrontal cortex (rDLPFC) after Anodal tDCS. In addition, corresponding to the regions of rsfMRI connectivity change, the efMRI BOLD signal in the rDLPFC and rIPC during Go responses accounted for 74% of the variance in SSRT after anodal tDCS, indicating an effect of tDCS on the Go-Stop process.
CONCLUSION: These results indicate that tDCS with the anode over the rIFC facilitates response inhibition by modulating neural activity and functional connectivity in the fronto-basal ganglia as well as rDLPFC and rIPC as an integral part of the response inhibition network.

PMID: 31422052 [PubMed - as supplied by publisher]

Graph theory and network topological metrics may be the potential biomarker in Parkinson's disease.

Tue, 08/20/2019 - 19:13
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Graph theory and network topological metrics may be the potential biomarker in Parkinson's disease.

J Clin Neurosci. 2019 Aug 13;:

Authors: Huang LC, Wu PA, Lin SZ, Pang CY, Chen SY

Abstract
This study used Voxel-based morphometry (VBM) and resting-state functional magnetic resonance imaging (rs-fMRI) to investigate changes in brain structure and networks functional connectivity, respectively. We tried to identify the potential biomarkers in Parkinson's disease (PD) progression. We recruited nine idiopathic PD patients and seven healthy control participants (HC group) who were age-matched to undergo T1-weighted images and rs-fMRI on 1.5 T. Brain structure differences were analyzed by VBM. Topological properties of networks functional connectivity were analyzed by graph theory. Thirty-two nodes of 8 networks and 133 nodes of interest then were identified with graph theory approaches. VBM examinations showed significant decreases of brain gray matter regions including the left temporal lobe, left middle temporal, middle temporal gyrus, parietal lobe, postcentral gyrus, left inferior parietal gyrus, medial frontal gyrus and supplement motor area in PD patients compared to the HC group. The 32 ROI of networks topological metrics measurement in PD demonstrated increases of global efficiency, cost, and degree in frontoparietal PPC (R) network, but decreases of local efficiency, clustering coefficient, and average path length in salience ACC, dorsal attention FEF (L), and salience aInsula (R) networks, respectively. All 165 ROI connectomes showed eight connections intensity changes, that decrease in OP r to frontoparietal PPC, putamen r to cereb11, and SFG l to Ver8 in PD. These results suggest that the graph theory and the network topological metrics measurement may be the potential biomarkers in PD to evaluate the disease progress and to monitor the therapeutic results.

PMID: 31420273 [PubMed - as supplied by publisher]

Memory and motor control in patients with psychogenic nonepileptic seizures.

Sat, 08/17/2019 - 19:09
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Memory and motor control in patients with psychogenic nonepileptic seizures.

Epilepsy Behav. 2019 Aug 13;98(Pt A):279-284

Authors: Dienstag A, Ben-Naim S, Gilad M, Ekstein D, Arzy S, Eitan R

Abstract
Psychogenic nonepileptic seizures (PNES) are of the most elusive phenomena in epileptology. Patients with PNES present episodes resembling epileptic seizures in their semiology yet lacking the underlying epileptic brain activity. These episodes are assumed to be related to psychological distress from past trauma, yet the underlying mechanism of this manifestation is still unknown. Using resting-state functional magnetic resonance imaging (fMRI), we investigated functional connectivity changes within and between large-scale brain networks in 9 patients with PNES, compared with a group of 13 age- and gender-matched healthy controls. Functional magnetic resonance imaging analyses identified functional connectivity disturbances between the medial temporal lobe (MTL) and the sensorimotor cortex and between the MTL and ventral attention networks in patients with PNES. Within network connectivity reduction was found within the visual network. Our findings suggest that PNES relate to changes in connectivity in between areas that are involved in memory processing and motor activity and attention control. These results may shed new light on the way by which traumatic memories may relate to PNES.

PMID: 31419649 [PubMed - as supplied by publisher]

Degrees of lateralisation in semantic cognition: Evidence from intrinsic connectivity.

Sat, 08/17/2019 - 19:09
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Degrees of lateralisation in semantic cognition: Evidence from intrinsic connectivity.

Neuroimage. 2019 Aug 13;:116089

Authors: Gonzalez Alam TR, Karapanagiotidis T, Smallwood J, Jefferies E

Abstract
The semantic network is thought to include multiple components, including heteromodal conceptual representations and semantic control processes that shape retrieval to suit the circumstances. Much of this network is strongly left-lateralised; however, work to date has not considered whether separable components of semantic cognition have different degrees of lateralisation. This study examined intrinsic connectivity of four regions implicated in heteromodal semantic cognition, identified using large scale meta-analyses: two sites which have been argued to act as heteromodal semantic hubs in anterior temporal lobe (ATL) and angular gyrus (AG); and two sites implicated in semantic control in inferior frontal (IFG) and posterior middle temporal gyri (pMTG). We compared the intrinsic connectivity of these sites in left hemisphere (LH) and right hemisphere (RH), and linked individual differences in the strength of within- and between-hemisphere connectivity from left-lateralised seeds to performance on semantic tasks, in a sample of 196 healthy volunteers. ATL showed more symmetrical patterns of intrinsic connectivity than the other three sites. The connectivity between IFG and pMTG was stronger in the LH than the RH, suggesting that the semantic control network is strongly left-lateralised. The degree of hemispheric lateralization also predicted behaviour: participants with stronger intrinsic connectivity within the LH had better semantic performance, while those with stronger intrinsic connectivity between left pMTG and homotopes of semantic regions in the RH performed more poorly on judgements of weak associations, which require greater control. Stronger connectivity between left AG and visual cortex was also linked to poorer perceptual performance. Overall, our results show that hemispheric lateralisation is particularly important for the semantic control network, and that this lateralisation has contrasting functional consequences for the retrieval of dominant and subordinate aspects of knowledge.

PMID: 31419614 [PubMed - as supplied by publisher]

A deconvolution algorithm for multi-echo functional MRI: Multi-echo Sparse Paradigm Free Mapping.

Sat, 08/17/2019 - 19:09
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A deconvolution algorithm for multi-echo functional MRI: Multi-echo Sparse Paradigm Free Mapping.

Neuroimage. 2019 Aug 13;:116081

Authors: Caballero-Gaudes C, Moia S, Panwar P, Bandettini PA, Gonzalez-Castillo J

Abstract
This work introduces a novel algorithm for deconvolution of the BOLD signal in multi-echo fMRI data: Multi-echo Sparse Paradigm Free Mapping (ME-SPFM). Assuming a linear dependence of the BOLD percent signal change on the echo time (TE) and using sparsity-promoting regularized least squares estimation, ME-SPFM yields voxelwise time-varying estimates of the changes in the apparent transverse relaxation (ΔR2∗) without prior knowledge of the timings of individual BOLD events. Our results in multi-echo fMRI data collected during a multi-task event-related paradigm at 3 Tesla demonstrate that the maps of R2∗ changes obtained with ME-SPFM at the times of the stimulus trials show high spatial and temporal concordance with the activation maps and BOLD signals obtained with standard model-based analysis. This method yields estimates of ΔR2∗ having physiologically plausible values. Owing to its ability to blindly detect events, ME-SPFM also enables us to map ΔR2∗ associated with spontaneous, transient BOLD responses occurring between trials. This framework is a step towards deciphering the dynamic nature of brain activity in naturalistic paradigms, resting-state or experimental paradigms with unknown timing of the BOLD events.

PMID: 31419613 [PubMed - as supplied by publisher]

Factors affecting detection power of BOLD signal in resting-state fMRI using high resolution Echo-Planar Imaging.

Sat, 08/17/2019 - 19:09
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Factors affecting detection power of BOLD signal in resting-state fMRI using high resolution Echo-Planar Imaging.

Brain Connect. 2019 Aug 16;:

Authors: Caparelli E, Ross TJ, Gu H, Yang YH

Abstract
Latest developments in magnetic resonance imaging (MRI) hardware and software have significantly improved image acquisition for functional MRI (fMRI) techniques including resting-state fMRI (rsfMRI). Specifically, with improvements in gradient and radio-frequency coils and advances in pulse sequence designs, functional images with higher spatial and temporal resolution can be achieved. However, while smaller voxel size has the benefit to resolve finer brain structures, it also decreases voxel-wise signal-to-noise ratio (SNR) and subsequently temporal SNR (tSNR), which is critical for the sensitivity of fMRI. Although the improved temporal resolution allows more image frames to be collected per unit time, the ability to detect brain activity using the high spatiotemporal fMRI has not been fully characterized. Here, we aimed to evaluate the effects of spatial smoothing, scan length, sample size, seed size and location on resting-state functional connectivity (rsFC) and tSNR using data from the human connectome project (HCP). Results from this analysis show an important effect of smoothing on the rsFC-strength (correlation values between the seed and the target) as well as on the tSNR. In contrast, while rsFC-strength is not affected by sample size, the standard error decreases with the increasing number of participants, therefore improving the detection power for larger samples. Scan length and seed size seem to have a moderate effect on rsFC-strength. Finally, seed location has an important impact on rsFC-maps, as rsFC-strength from cortical seeds seems higher than from sub-cortical seeds. In summary, our findings show that the choice of parameters can be critical for a rsfMRI study.

PMID: 31418299 [PubMed - as supplied by publisher]

Spatial Patterns of Decreased Cerebral Blood Flow and Functional Connectivity in Multiple System Atrophy (Cerebellar-Type): A Combined Arterial Spin Labeling Perfusion and Resting State Functional Magnetic Resonance Imaging Study.

Sat, 08/17/2019 - 19:09
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Spatial Patterns of Decreased Cerebral Blood Flow and Functional Connectivity in Multiple System Atrophy (Cerebellar-Type): A Combined Arterial Spin Labeling Perfusion and Resting State Functional Magnetic Resonance Imaging Study.

Front Neurosci. 2019;13:777

Authors: Zheng W, Ren S, Zhang H, Liu M, Zhang Q, Chen Z, Wang Z

Abstract
Multiple system atrophy (MSA) is a progressive neurodegenerative disease. However, little is known about the regional cerebral blood flow (rCBF) and functional connectivity changes in the disease. In this study, the magnetic resonance imaging (MRI) data including 24MSA-c-type patients and 20 healthy controls were collected by using voxel wise arterial spin labeling (ASL) perfusion analysis, several regions of the altered rCBF were identified in the MSA c-type patients. And then, the changes of the functional connectivities of identified rCBF regions were analyzed by using functional MRI (fMRI). Finally, rCBF value of cerebellum was extracted to differentiate the MSA c-type patients and controls. Compared with the controls, the MSA c-type patients showed distinct disruption of rCBF in the cerebellum. The disconnection of the identified cerebellar regions was revealed in several regions in the MSAc-type patients, including right middle frontal gyrus (MFG), right precuneus, left superior temporal gyrus (STG), right lingual gyrus, left postcentral gyrus (PoCG), right cerebellum 7b, right cerebellum 8, and left cerebellum 4,5. These regions were involved in the default mode network (DMN), sensorimotor network, visual associated cortices, and cerebellum. Using the rCBF value of vermis as biomarker, the two groups can be differentiated and reached a sensitivity of 95.8% and specificity of 100%. This is the first study to demonstrate the MSA-specific rCBF abnormalities using the ASL method, which are closely associated with several functional networks on resting state fMRI. The rCBF of vermis might be used as the potential imaging biomarker for the early diagnosis of MSA c-type.

PMID: 31417345 [PubMed]

Image processing and analysis methods for the Adolescent Brain Cognitive Development Study.

Fri, 08/16/2019 - 19:08
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Image processing and analysis methods for the Adolescent Brain Cognitive Development Study.

Neuroimage. 2019 Aug 12;:116091

Authors: Hagler DJ, Hatton S, Cornejo MD, Makowski C, Fair DA, Dick AS, Sutherland MT, Casey BJ, Barch DM, Harms MP, Watts R, Bjork JM, Garavan HP, Hilmer L, Pung CJ, Sicat CS, Kuperman J, Bartsch H, Xue F, Heitzeg MM, Laird AR, Trinh TT, Gonzalez R, Tapert SF, Riedel MC, Squeglia LM, Hyde LW, Rosenberg MD, Earl EA, Howlett KD, Baker FC, Soules M, Diaz J, de Leon OR, Thompson WK, Neale MC, Herting M, Sowell ER, Alvarez RP, Hawes SW, Sanchez M, Bodurka J, Breslin FJ, Morris AS, Paulus MP, Simmons WK, Polimeni JR, van der Kouwe A, Nencka AS, Gray KM, Pierpaoli C, Matochik JA, Noronha A, Aklin WM, Conway K, Glantz M, Hoffman E, Little R, Lopez M, Pariyadath V, Weiss SR, Wolff-Hughes DL, DelCarmen-Wiggins R, Feldstein Ewing SW, Miranda-Dominguez O, Nagel BJ, Perrone AJ, Sturgeon DT, Goldstone A, Pfefferbaum A, Pohl KM, Prouty D, Uban K, Bookheimer SY, Dapretto M, Galvan A, Bagot K, Giedd J, Infante MA, Jacobus J, Patrick K, Shilling PD, Desikan R, Li Y, Sugrue L, Banich MT, Friedman N, Hewitt JK, Hopfer C, Sakai J, Tanabe J, Cottler LB, Nixon SJ, Chang L, Cloak C, Ernst T, Reeves G, Kennedy DN, Heeringa S, Peltier S, Schulenberg J, Sripada C, Zucker RA, Iacono WG, Luciana M, Calabro FJ, Clark DB, Lewis DA, Luna B, Schirda C, Brima T, Foxe JJ, Freedman EG, Mruzek DW, Mason MJ, Huber R, McGlade E, Prescot A, Renshaw PF, Yurgelun-Todd DA, Allgaier NA, Dumas JA, Ivanova M, Potter A, Florsheim P, Larson C, Lisdahl K, Charness ME, Fuemmeler B, Hettema JM, Maes HH, Steinberg J, Anokhin AP, Glaser P, Heath AC, Madden PA, Baskin-Sommers A, Constable RT, Grant SJ, Dowling GJ, Brown SA, Jernigan TL, Dale AM

Abstract
The Adolescent Brain Cognitive Development (ABCD) Study is an ongoing, nationwide study of the effects of environmental influences on behavioral and brain development in adolescents. The main objective of the study is to recruit and assess over eleven thousand 9-10-year-olds and follow them over the course of 10 years to characterize normative brain and cognitive development, the many factors that influence brain development, and the effects of those factors on mental health and other outcomes. The study employs state-of-the-art multimodal brain imaging, cognitive and clinical assessments, bioassays, and careful assessment of substance use, environment, psychopathological symptoms, and social functioning. The data is a resource of unprecedented scale and depth for studying typical and atypical development. The aim of this manuscript is to describe the baseline neuroimaging processing and subject-level analysis methods used by ABCD. Processing and analyses include modality-specific corrections for distortions and motion, brain segmentation and cortical surface reconstruction derived from structural magnetic resonance imaging (sMRI), analysis of brain microstructure using diffusion MRI (dMRI), task-related analysis of functional MRI (fMRI), and functional connectivity analysis of resting-state fMRI. This manuscript serves as a methodological reference for users of publicly shared neuroimaging data from the ABCD Study.

PMID: 31415884 [PubMed - as supplied by publisher]

Differential Changes in Functional Connectivity of Striatum-Prefrontal and Striatum-Motor Circuits in Premanifest Huntington's Disease.

Thu, 08/15/2019 - 19:07

Differential Changes in Functional Connectivity of Striatum-Prefrontal and Striatum-Motor Circuits in Premanifest Huntington's Disease.

Neurodegener Dis. 2019 Aug 14;:1-10

Authors: Kronenbuerger M, Hua J, Bang JYA, Ultz KE, Miao X, Zhang X, Pekar JJ, van Zijl PCM, Duan W, Margolis RL, Ross CA

Abstract
BACKGROUND: Huntington's disease (HD) is a progressive neurodegenerative disorder. The striatum is one of the first brain regions that show detectable atrophy in HD. Previous studies using functional magnetic resonance imaging (fMRI) at 3 tesla (3 T) revealed reduced functional connectivity between striatum and motor cortex in the prodromal period of HD. Neuroanatomical and neurophysiological studies have suggested segregated corticostriatal pathways with distinct loops involving different cortical regions, which may be investigated using fMRI at an ultra-high field (7 T) with enhanced sensitivity compared to lower fields.
OBJECTIVES: We performed fMRI at 7 T to assess functional connectivity between the striatum and several chosen cortical areas including the motor and prefrontal cortex, in order to better understand brain changes in the striatum-cortical pathways.
METHOD: 13 manifest subjects (age 51 ± 13 years, cytosine-adenine-guanine [CAG] repeat 45 ± 5, Unified Huntington's Disease Rating Scale [UHDRS] motor score 32 ± 17), 8 subjects in the close-to-onset premanifest period (age 38 ± 10 years, CAG repeat 44 ± 2, UHDRS motor score 8 ± 2), 11 subjects in the far-from-onset premanifest period (age 38 ± 11 years, CAG repeat 42 ± 2, UHDRS motor score 1 ± 2), and 16 healthy controls (age 44 ± 15 years) were studied. The functional connectivity between the striatum and several cortical areas was measured by resting state fMRI at 7 T and analyzed in all participants.
RESULTS: Compared to controls, functional connectivity between striatum and premotor area, supplementary motor area, inferior frontal as well as middle frontal regions was altered in HD (all p values <0.001). Specifically, decreased striatum-motor connectivity but increased striatum-prefrontal connectivity were found in premanifest HD subjects. Altered functional connectivity correlated consistently with genetic burden, but not with clinical scores.
CONCLUSIONS: Differential changes in functional connectivity of striatum-prefrontal and striatum-motor circuits can be found in early and premanifest HD. This may imply a compensatory mechanism, where additional cortical regions are recruited to subserve functions that have been impaired due to HD pathology. Our results suggest the potential value of functional connectivity as a marker for future clinical trials in HD.

PMID: 31412344 [PubMed - as supplied by publisher]

Topological gene expression networks recapitulate brain anatomy and function.

Thu, 08/15/2019 - 19:07
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Topological gene expression networks recapitulate brain anatomy and function.

Netw Neurosci. 2019;3(3):744-762

Authors: Patania A, Selvaggi P, Veronese M, Dipasquale O, Expert P, Petri G

Abstract
Understanding how gene expression translates to and affects human behavior is one of the ultimate goals of neuroscience. In this paper, we present a pipeline based on Mapper, a topological simplification tool, to analyze gene co-expression data. We first validate the method by reproducing key results from the literature on the Allen Human Brain Atlas and the correlations between resting-state fMRI and gene co-expression maps. We then analyze a dopamine-related gene set and find that co-expression networks produced by Mapper return a structure that matches the well-known anatomy of the dopaminergic pathway. Our results suggest that network based descriptions can be a powerful tool to explore the relationships between genetic pathways and their association with brain function and its perturbation due to illness and/or pharmacological challenges.

PMID: 31410377 [PubMed]

Exact topological inference of the resting-state brain networks in twins.

Thu, 08/15/2019 - 19:07
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Exact topological inference of the resting-state brain networks in twins.

Netw Neurosci. 2019;3(3):674-694

Authors: Chung MK, Lee H, DiChristofano A, Ombao H, Solo V

Abstract
A cycle in a brain network is a subset of a connected component with redundant additional connections. If there are many cycles in a connected component, the connected component is more densely connected. Whereas the number of connected components represents the integration of the brain network, the number of cycles represents how strong the integration is. However, it is unclear how to perform statistical inference on the number of cycles in the brain network. In this study, we present a new statistical inference framework for determining the significance of the number of cycles through the Kolmogorov-Smirnov (KS) distance, which was recently introduced to measure the similarity between networks across different filtration values by using the zeroth Betti number. In this paper, we show how to extend the method to the first Betti number, which measures the number of cycles. The performance analysis was conducted using the random network simulations with ground truths. By using a twin imaging study, which provides biological ground truth, the methods are applied in determining if the number of cycles is a statistically significant heritable network feature in the resting-state functional connectivity in 217 twins obtained from the Human Connectome Project. The MATLAB codes as well as the connectivity matrices used in generating results are provided at http://www.stat.wisc.edu/∼mchung/TDA.

PMID: 31410373 [PubMed]

Electroacupuncture Modulates Resting-State Functional Connectivity in the Default Mode Network for Healthy Older Adults.

Thu, 08/15/2019 - 19:07
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Electroacupuncture Modulates Resting-State Functional Connectivity in the Default Mode Network for Healthy Older Adults.

J Geriatr Psychiatry Neurol. 2019 Aug 13;:891988719868304

Authors: Fan DQ, Zhao HC, Sheng J, Liu YR, Yu J

Abstract
Aging involves cognitive decline and prominent alterations in brain activity. Electroacupuncture (EA), a traditional Chinese medicine approach, is demonstrated to be effective in improving cognitive function of older adults. However, the specific neural mechanism underlying this modulation effect remains unclear. In this study, we used functional magnetic resonance imaging (fMRI) to investigate whether EA could improve cognitive performance of community-dwelling older adults and whether these potential improvements are associated with the EA-induced brain functional connectivity alterations. Thirty healthy older adults were recruited and randomly assigned to the EA group and the control group. Behaviorally, we observed an EA-induced improvement in cognitive performance of older adults in the Montreal Cognitive Assessment. On a neural perspective, the EA intervention significantly increased the functional connectivity within the default mode network. Moreover, we found a positive association between the improvement in delayed memory performance and the alterations in the ventral medial prefrontal cortex-hippocampal formation connectivity in the EA group. This study extends previous findings by showing that healthy older adults exhibit neural plasticity manifested as increased functional connectivity after EA sessions, which could induce therapeutic effects in the treatment of neurodegenerative diseases.

PMID: 31409183 [PubMed - as supplied by publisher]

A putative human homologue of the macaque area PEc.

Wed, 08/14/2019 - 22:06

A putative human homologue of the macaque area PEc.

Neuroimage. 2019 Aug 10;:116092

Authors: Pitzalis S, Serra C, Sulpizio V, Di Marco S, Fattori P, Galati G, Galletti C

Abstract
The cortical area PEc is anatomically and functionally well-defined in macaque, but it is unknown whether it has a counterpart in human. Since we know that macaque PEc, but not the nearby posterior regions, hosts a lower limb representation, in an attempt to recognize a possible human PEc we looked for the existence of leg representations in the human parietal cortex using individual cortical surface-based analysis, task-evoked paradigms and resting-state functional connectivity. fMRI images were acquired while thirty-one participants performed long-range leg movements through an in-house MRI-compatible set-up. We revealed the existence of multiple leg representations in the human dorsomedial parietal cortex, here defined as S-I (somatosensory-I), hPE (human PE, in the postcentral sulcus), and hPEc (human PEc, in the anterior precuneus). Among the three "leg" regions, hPEc had a unique functional profile, in that it was the only one responding to both arm and leg movements, to both hand-pointing and foot pointing movements, and to flow field visual stimulation, very similar to macaque area PEc. In addition, hPEc showed functional connections with the somatomotor regions hosting a lower limb representation, again as in macaque area PEc. Therefore, based on similarity in brain position, functional organization, cortical connections, and relationship with the neighboring areas, we propose that this cortical region is the human homologue of macaque area PEc.

PMID: 31408715 [PubMed - as supplied by publisher]

Classification of Unmedicated Bipolar Disorder Using Whole-Brain Functional Activity and Connectivity: A Radiomics Analysis.

Wed, 08/14/2019 - 22:06

Classification of Unmedicated Bipolar Disorder Using Whole-Brain Functional Activity and Connectivity: A Radiomics Analysis.

Cereb Cortex. 2019 Aug 13;:

Authors: Wang Y, Sun K, Liu Z, Chen G, Jia Y, Zhong S, Pan J, Huang L, Tian J

Abstract
The aim of this study was to develop and validate a method of disease classification for bipolar disorder (BD) by functional activity and connectivity using radiomics analysis. Ninety patients with unmedicated BD II as well as 117 healthy controls underwent resting-state functional magnetic resonance imaging (rs-fMRI). A total of 4 types of 7018 features were extracted after preprocessing, including mean regional homogeneity (mReHo), mean amplitude of low-frequency fluctuation (mALFF), resting-state functional connectivity (RSFC), and voxel-mirrored homotopic connectivity (VMHC). Then, predictive features were selected by Mann-Whitney U test and removing variables with a high correlation. Least absolute shrinkage and selection operator (LASSO) method was further used to select features. At last, support vector machine (SVM) model was used to estimate the state of each subject based on the selected features after LASSO. Sixty-five features including 54 RSFCs, 7 mALFFs, 1 mReHo, and 3 VMHCs were selected. The accuracy and area under curve (AUC) of the SVM model built based on the 65 features is 87.3% and 0.919 in the training dataset, respectively, and the accuracy and AUC of this model validated in the validation dataset is 80.5% and 0.838, respectively. These findings demonstrate a valid radiomics approach by rs-fMRI can identify BD individuals from healthy controls with a high classification accuracy, providing the potential adjunctive approach to clinical diagnostic systems.

PMID: 31408101 [PubMed - as supplied by publisher]

Whole-brain functional network disruption in chronic pain with disc herniation.

Wed, 08/14/2019 - 22:06

Whole-brain functional network disruption in chronic pain with disc herniation.

Pain. 2019 Aug 10;:

Authors: Huang S, Wakaizumi K, Wu B, Shen B, Wu B, Fan L, Baliki MN, Zhan G, Apkarian AV, Huang L

Abstract
Brain functional network properties are globally disrupted in multiple musculoskeletal chronic pain conditions. Back pain with lumbar disc herniation is highly prevalent and a major route for progression to chronic back pain. However, brain functional network properties remain unknown in such patients. Here, we examined resting-state fMRI-based functional connectivity networks in chronic back pain patients with clear evidence for lumbar disc herniation (LDH-CP, n = 146), in comparison to healthy controls (HC, n = 165). The study was conducted in China, thus providing the opportunity to also examine the influence of culture on brain functional reorganization with chronic pain. The data was equally subdivided into Discovery and Validation subgroups (n = 68 LDH-CP and n = 68 HC, for each subgroup), and contrasted to an off-site dataset (n = 272, NITRC 1000).Graph disruption indices derived from three network topological measurements, degree, clustering coefficient, and efficiency, which respectively represent network hubness, segregation, and integration, were significantly decreased compared to HC, across all predefined link densities, in both Discovery and Validation groups. On the other hand, global mean clustering coefficient and betweenness centrality were decreased in the discovery group and showed trend in the validation group. The relationship between pain and graph disruption indices was limited to males with high education. These results deviate somewhat from recent similar analysis for other musculoskeletal chronic pain conditions, yet we cannot determine whether the differences are due to types of pain or also to cultural differences between patients studied in China and the USA.

PMID: 31408051 [PubMed - as supplied by publisher]

Dynamic functional connectivity of migraine brain: a resting-state fMRI study.

Wed, 08/14/2019 - 22:06

Dynamic functional connectivity of migraine brain: a resting-state fMRI study.

Pain. 2019 Aug 10;:

Authors: Lee MJ, Park BY, Cho S, Park H, Kim ST, Chung CS

Abstract
Migraine headache is an episodic phenomenon, and patients with episodic migraine have ictal (headache), peri-ictal (premonitory, aura, and postdrome), and interictal (asymptomatic) phases. We aimed to find the functional characteristics of migraine brain regardless of headache phase using dynamic functional connectivity analysis. We prospectively recruited 50 patients with migraine and 50 age- and sex-matched controls. All subjects underwent a resting-state functional MRI. Significant networks were defined in a data-driven fashion from the interictal (>48 hours apart from headache phases) patients and matched controls (interictal dataset) and tested to ictal or peri-ictal patients and controls (ictal/peri-ictal dataset). Both static and dynamic analyses were used for the between-group comparison. A false discovery rate correction was performed. As a result, the static analysis did not reveal a network which was significant in both interictal and ictal/peri-ictal datasets. Dynamic analysis revealed significant between-group differences in seven brain networks in the interictal dataset, among which a frontoparietal network (controls > patients, p=0.0467), two brainstem networks (patients > controls, p=0.0467 and <0.001), and a cerebellar network (controls > patients, p=0.0408 and <0.001 in two states) remained significant in the ictal/peri-ictal dataset. Using these networks, migraine was classified with a sensitivity of 0.70 and specificity of 0.76 in the ictal/peri-ictal dataset. In conclusion, the dynamic connectivity analysis revealed more functional networks related to migraine than the conventional static analysis, suggesting a substantial temporal fluctuation in functional characteristics. Our data also revealed migraine-related networks which show significant difference regardless of headache phases between patients and controls.

PMID: 31408050 [PubMed - as supplied by publisher]

Resting-state fMRI metrics in acute sport-related concussion and their association with clinical recovery: A study from the NCAA-DOD CARE Consortium.

Wed, 08/14/2019 - 22:06

Resting-state fMRI metrics in acute sport-related concussion and their association with clinical recovery: A study from the NCAA-DOD CARE Consortium.

J Neurotrauma. 2019 Aug 13;:

Authors: Meier T, Giraldo-Chica M, Espana L, Mayer A, Harezlak J, Nencka AS, Wang Y, Koch KM, Wu YC, Saykin AJ, Giza CC, Goldman J, DiFiori JP, Guskiewicz KK, Mihalik J, Brooks A, Broglio SP, McAllister T, McCrea M

Abstract
There has been a recent call for longitudinal cohort studies to track the physiological recovery of sport-related concussion (SRC) and its relationship with clinical recovery. Resting-state fMRI (rs-fMRI) has shown potential for detecting subtle changes in brain function after SRC. We investigated the effects of SRC on rs-fMRI metrics assessing local connectivity (regional homogeneity; REHO), global connectivity (average nodal strength), and the relative amplitude of slow oscillations of rs-fMRI (fractional amplitude of low frequency fluctuations; fALFF). Athletes diagnosed with SRC (N=92) completed visits with neuroimaging at 24-48 hours post-injury (24-hours), after clearance to begin the return-to-play (RTP) progression (asymptomatic), and seven days following unrestricted RTP (post-RTP). Non-injured athletes (N=82) completed visits yoked to the schedule of matched injured athletes and served as controls. Concussed athletes had elevated symptoms, worse neurocognitive performance, greater balance deficits, and elevated psychological symptoms at the 24-hour visit relative to controls. These deficits were largely recovered by the asymptomatic visit. Concussed athletes still reported elevated psychological symptoms at the asymptomatic visit relative to controls. Concussed athletes also had elevated REHO in the right middle and superior frontal gyri at the 24-hour visit that returned to normal levels by the asymptomatic visit. Additionally, REHO in these regions at 24-hours predicted psychological symptoms at the asymptomatic visit in concussed athletes. Current results suggest that SRC is associated with an acute alteration in local connectivity that follows a similar time course as clinical recovery. Our results do not indicate strong evidence that concussion-related alterations in rs-fMRI persist beyond clinical recovery.

PMID: 31407610 [PubMed - as supplied by publisher]

Early identification of bipolar from unipolar depression before manic episode: evidence from dynamic rfMRI.

Wed, 08/14/2019 - 22:06

Early identification of bipolar from unipolar depression before manic episode: evidence from dynamic rfMRI.

Bipolar Disord. 2019 Aug 12;:

Authors: Shao J, Dai Z, Zhu R, Wang X, Tao S, Bi K, Tian S, Wang H, Sun Y, Yao Z, Lu Q

Abstract
OBJECTIVE: Misdiagnosis of bipolar disorder (BD) as unipolar depression (UD) may cause improper treatment strategy to be chosen, especially in the early stages of disease. The aim of this study was to characterize alterations in specific brain networks for depressed patients who transformed into BD (tBD) from UD.
METHOD: The module allegiance (MA) from resting-fMRI by applying a multilayer modular method was estimated in 99 patients (33 tBD, 33 BD, 33 UD) and 33 healthy controls (HC). A classification model was trained on tBD and UD patients. HC was used to explore the functional declination patterns of BD, tBD and UD.
RESULTS: Based on our classification model, difference mainly reflected in default-mode network (DMN). Compared with HC, both BD and tBD focused on the difference of somatomotor network (SMN), while UD on the abnormity of DMN. The patterns of brain network between patients with BD and tBD were well overlapped, except for cognitive control network (CCN).
CONCLUSION: The functional declination of internal interaction in DMN was suggested to be useful for the identification of BD from UD in the early stage. The higher recruitment of DMN may predispose patients to depressive states, while higher recruitment of SMN makes them more sensitive to external stimuli and prone to mania. Furthermore, CCN may be a critical network for identifying different stages of BD, suggesting that the onset of mania in depressed patients is accompanied by CCN related cognitive impairments. This article is protected by copyright. All rights reserved.

PMID: 31407477 [PubMed - as supplied by publisher]

Community-informed connectomics of the thalamocortical system in generalized epilepsy.

Wed, 08/14/2019 - 22:06

Community-informed connectomics of the thalamocortical system in generalized epilepsy.

Neurology. 2019 Aug 12;:

Authors: Wang Z, Larivière S, Xu Q, Vos de Wael R, Hong SJ, Wang Z, Xu Y, Zhu B, Bernasconi N, Bernasconi A, Zhang B, Zhang Z, Bernhardt BC

Abstract
OBJECTIVE: To study the intrinsic organization of the thalamocortical circuitry in patients with generalized epilepsy with tonic-clonic seizures (GTCS) via resting-state fMRI (rs-fMRI) connectome analysis and to evaluate its relation to drug response.
METHODS: In a prospectively followed-up sample of 41 patients and 27 healthy controls, we obtained rs-fMRI and structural MRI. After 1 year of follow-up, 27 patients were classified as seizure-free and 14 as drug-resistant. We examined connectivity within and between resting-state communities in cortical and thalamic subregions. In addition to comparing patients to controls, we examined associations with seizure control. We assessed reproducibility in an independent cohort of 21 patients.
RESULTS: Compared to controls, patients showed a more constrained network embedding of the thalamus, while frontocentral neocortical regions expressed increased functional diversity. Findings remained significant after regressing out thalamic volume and cortical thickness, suggesting independence from structural alterations. We observed more marked network imbalances in drug-resistant compared to seizure-free patients. Findings were similar in the reproducibility dataset.
CONCLUSIONS: Our findings suggest a pathoconnectomic mechanism of generalized epilepsy centered on diverging changes in cortical and thalamic connectivity. More restricted thalamic connectivity could reflect the tendency to engage in recursive thalamocortical loops, which may contribute to hyperexcitability. Conversely, increased connectional diversity of frontocentral networks may relay abnormal activity to an extended bilateral territory. Network imbalances were observed shortly after diagnosis and related to future drug response, suggesting clinical utility.

PMID: 31405905 [PubMed - as supplied by publisher]