Manifold learning on brain functional networks in aging.
Med Image Anal. 2014 Oct 30;
Authors: Qiu A, Lee A, Tan M, Chung MK
We propose a new analysis framework to utilize the full information of brain functional networks for computing the mean of a set of brain functional networks and embedding brain functional networks into a low-dimensional space in which traditional regression and classification analyses can be easily employed. For this, we first represent the brain functional network by a symmetric positive matrix computed using sparse inverse covariance estimation. We then impose a Log-Euclidean Riemannian manifold structure on brain functional networks whose norm gives a convenient and practical way to define a mean. Finally, based on the fact that the computation of linear operations can be done in the tangent space of this Riemannian manifold, we adopt Locally Linear Embedding (LLE) to the Log-Euclidean Riemannian manifold space in order to embed the brain functional networks into a low-dimensional space. We show that the integration of the Log-Euclidean manifold with LLE provides more efficient and succinct representation of the functional network and facilitates regression analysis, such as ridge regression, on the brain functional network to more accurately predict age when compared to that of the Euclidean space of functional networks with LLE. Interestingly, using the Log-Euclidean analysis framework, we demonstrate the integration and segregation of cortical-subcortical networks as well as among the salience, executive, and emotional networks across lifespan.
PMID: 25476411 [PubMed - as supplied by publisher]
Intrinsically organized resting state networks in the human spinal cord.
Proc Natl Acad Sci U S A. 2014 Dec 3;
Authors: Kong Y, Eippert F, Beckmann CF, Andersson J, Finsterbusch J, Büchel C, Tracey I, Brooks JC
Spontaneous fluctuations in functional magnetic resonance imaging (fMRI) signals of the brain have repeatedly been observed when no task or external stimulation is present. These fluctuations likely reflect baseline neuronal activity of the brain and correspond to functionally relevant resting-state networks (RSN). It is not known however, whether intrinsically organized and spatially circumscribed RSNs also exist in the spinal cord, the brain's principal sensorimotor interface with the body. Here, we use recent advances in spinal fMRI methodology and independent component analysis to answer this question in healthy human volunteers. We identified spatially distinct RSNs in the human spinal cord that were clearly separated into dorsal and ventral components, mirroring the functional neuroanatomy of the spinal cord and likely reflecting sensory and motor processing. Interestingly, dorsal (sensory) RSNs were separated into right and left components, presumably related to ongoing hemibody processing of somatosensory information, whereas ventral (motor) RSNs were bilateral, possibly related to commissural interneuronal networks involved in central pattern generation. Importantly, all of these RSNs showed a restricted spatial extent along the spinal cord and likely conform to the spinal cord's functionally relevant segmental organization. Although the spatial and temporal properties of the dorsal and ventral RSNs were found to be significantly different, these networks showed significant interactions with each other at the segmental level. Together, our data demonstrate that intrinsically highly organized resting-state fluctuations exist in the human spinal cord and are thus a hallmark of the entire central nervous system.
PMID: 25472845 [PubMed - as supplied by publisher]
When the brain takes a break: a model-based analysis of mind wandering.
J Neurosci. 2014 Dec 3;34(49):16286-95
Authors: Mittner M, Boekel W, Tucker AM, Turner BM, Heathcote A, Forstmann BU
Mind wandering is an ubiquitous phenomenon in everyday life. In the cognitive neurosciences, mind wandering has been associated with several distinct neural processes, most notably increased activity in the default mode network (DMN), suppressed activity within the anti-correlated (task-positive) network (ACN), and changes in neuromodulation. By using an integrative multimodal approach combining machine-learning techniques with modeling of latent cognitive processes, we show that mind wandering in humans is characterized by inefficiencies in executive control (task-monitoring) processes. This failure is predicted by a single-trial signature of (co)activations in the DMN, ACN, and neuromodulation, and accompanied by a decreased rate of evidence accumulation and response thresholds in the cognitive model.
PMID: 25471568 [PubMed - in process]
Beyond BOLD: Optimizing functional imaging in stroke populations.
Hum Brain Mapp. 2014 Dec 2;
Authors: Veldsman M, Cumming T, Brodtmann A
Blood oxygenation level-dependent (BOLD) signal changes are often assumed to directly reflect neural activity changes. Yet the real relationship is indirect, reliant on numerous assumptions, and subject to several sources of noise. Deviations from the core assumptions of BOLD contrast functional magnetic resonance imaging (fMRI), and their implications, have been well characterized in healthy populations, but are frequently neglected in stroke populations. In addition to conspicuous local structural and vascular changes after stroke, there are many less obvious challenges in the imaging of stroke populations. Perilesional ischemic changes, remodeling in regions distant to lesion sites, and diffuse perfusion changes all complicate interpretation of BOLD signal changes in standard fMRI protocols. Most stroke patients are also older than the young populations on which assumptions of neurovascular coupling and the typical analysis pipelines are based. We present a review of the evidence to show that the basic assumption of neurovascular coupling on which BOLD-fMRI relies does not capture the complex changes arising from stroke, both pathological and recovery related. As a result, estimating neural activity using the canonical hemodynamic response function is inappropriate in a number of contexts. We review methods designed to better estimate neural activity in stroke populations. One promising alternative to event-related fMRI is a resting-state-derived functional connectivity approach. Resting-state fMRI is well suited to stroke populations because it makes no performance demands on patients and is capable of revealing network-based pathology beyond the lesion site. Hum Brain Mapp, 2014. © 2014 Wiley Periodicals, Inc.
PMID: 25469481 [PubMed - as supplied by publisher]
Central executive network in young people with familial risk for psychosis - The Oulu Brain and Mind Study.
Schizophr Res. 2014 Nov 22;
Authors: Jukuri T, Kiviniemi V, Nikkinen J, Miettunen J, Mäki P, Mukkala S, Koivukangas J, Nordström T, Parkkisenniemi J, Moilanen I, Barnett JH, Jones PB, Murray GK, Veijola J
OBJECTIVE: The central executive network controls and manages high-level cognitive functions. Abnormal activation in the central executive network has been related to psychosis and schizophrenia but it is not established how this applies to people with familial risk for psychosis (FR).
METHODS: We conducted a resting-state functional MRI (R-fMRI) in 72 (29 males) young adults with a history of psychosis in one or both parents (FR) but without psychosis themselves, and 72 (29 males) similarly healthy control subjects without parental psychosis. Both groups in the Oulu Brain and Mind Study were drawn from the Northern Finland Birth Cohort 1986. Participants were 20-25years old. Parental psychosis was established using the Care Register for Health Care. R-fMRI data pre-processing was conducted using independent component analysis with 30 and 70 components. A dual regression technique was used to detect between-group differences in the central executive network with p<0.05 threshold corrected for multiple comparisons.
RESULTS: FR participants demonstrated statistically significantly lower activity compared to control subjects in the right inferior frontal gyrus, a key area of central executive network corresponding to Brodmann areas 44 and 45, known as Broca's area. The volume of the lower activation area with 30 components was 896mm(3) and with 70 components was 1151mm(3).
CONCLUSION: The activity of the central executive network differed in the right inferior frontal gyrus between FR and control groups. This suggests that abnormality of the right inferior frontal gyrus may be a central part of vulnerability for psychosis.
PMID: 25468181 [PubMed - as supplied by publisher]
Resting-state functional connectivity alterations in the default network of schizophrenia patients with persistent auditory verbal hallucinations.
Schizophr Res. 2014 Nov 20;
Authors: Alonso-Solís A, Vives-Gilabert Y, Grasa E, Portella MJ, Rabella M, Sauras RB, Roldán A, Núñez-Marín F, Gómez-Ansón B, Pérez V, Alvarez E, Corripio I
To understand the neural mechanism that underlies treatment resistant auditory verbal hallucinations (AVH), is still an important issue in psychiatric research. Alterations in functional connectivity during rest have been frequently reported in patients with schizophrenia. Though the default mode network (DN) appears to be abnormal in schizophrenia patients, little is known about its role in resistant AVH. We collected resting-state functional magnetic resonance imaging (R-fMRI) data with a 3T scanner from 19 schizophrenia patients with chronic AVH resistant to pharmacological treatment, 14 schizophrenia patients without AVH and 20 healthy controls. Using seed-based correlation analysis, we created spherical seed regions of interest (ROI) to examine functional connectivity of the two DN hub regions (posterior cingulate cortex and anteromedial prefrontal cortex) and the two DN subsystems: dorsomedial prefrontal cortex subsystem and medial temporal lobe subsystem (p<0.0045 corrected). Patients with hallucinations exhibited higher FC between dMPFC ROI and bilateral central opercular cortex, bilateral insular cortex and bilateral precentral gyrus compared to non hallucinating patients and healthy controls. Additionally, patients with hallucinations also exhibited lower FC between vMPFC ROI and bilateral paracingulate and dorsal anterior cingulate cortex. As the anterior cingulate cortex and the insula are two hubs of the salience network, our results suggest cross-network abnormalities between DN and salience system in patients with persistent hallucinations.
PMID: 25468173 [PubMed - as supplied by publisher]
Association between altered resting-state cortico-cerebellar functional connectivity networks and mood/cognition dysfunction in late-onset depression.
J Neural Transm. 2014 Dec 3;
Authors: Yin Y, Hou Z, Wang X, Sui Y, Yuan Y
The objective of the study is to investigate the relationship between altered resting-state cortico-cerebellar functional connectivity (FC) and depression as well as cognitive impairment in late-onset depression (LOD). A total of 32 LOD and 39 well-matched normal controls (NCs) were recruited and underwent resting-state functional MRI (R-fMRI) scans. Seed-based correlation analysis was performed to explore the cortico-cerebellar FC. Hamilton Depression Rating Scale (HAMD) and mini-mental state examination (MMSE) were used to evaluate the depressive severity and cognitive impairment, respectively. A set of neuropsychological measurements was also applied to evaluate the detailed cognitions. Spearman correlations were applied to examine the depressive and cognitive association of these altered cortico-cerebellar networks. Compared with the NCs, LOD patients showed increased FC between the cerebellum and the right ventromedial frontal cortex (vmPFC), supplementary motor area (SMA), middle temporal gyrus (MTG), bilateral supramarginal gyrus (SMG), and anterior cingulated cortex (ACC). However, reduced cerebellar FC was observed in bilateral cerebellum, posterior cingulated cortex (PCC) and left dorsolateral prefrontal cortex (dlPFC). Moreover, the cerebellar FC with the vmPFC and ACC was positively correlated with HAMD score, whereas the cerebellar FC with the dlPFC and PCC was positively correlated with MMSE score in LOD patients. The cortico-cerebellar disconnections might underlie the pathogenesis of LOD. While depression mainly relates to the excessive cerebellar FC with the vmPFC and ACC, cognitive decline is primarily associated with the uncoupling of the cerebellar FC with the dlPFC and PCC.
PMID: 25466433 [PubMed - as supplied by publisher]
Akinetic-rigid and tremor-dominant Parkinson's disease patients show different patterns of intrinsic brain activity.
Parkinsonism Relat Disord. 2014 Oct 27;
Authors: Zhang J, Wei L, Hu X, Xie B, Zhang Y, Wu GR, Wang J
BACKGROUND: Parkinson's disease (PD) is a surprisingly heterogeneous neurodegenerative disorder. It is well established that different subtypes of PD present with different clinical courses and prognoses. However, the neural mechanism underlying these disparate presentations is uncertain.
METHODS: Here we used resting-state fMRI (rs-fMRI) and the regional homogeneity (ReHo) method to determine neural activity patterns in the two main clinical subgroups of PD (akinetic-rigid and tremor-dominant).
RESULTS: Compared with healthy controls, akinetic-rigid (AR) subjects had increased ReHo mainly in right amygdala, left putamen, bilateral angular gyrus, bilateral medial prefrontal cortex (MPFC), and decreased ReHo in left post cingulate gyrus/precuneus (PCC/PCu) and bilateral thalamus. In contrast, tremor-dominant (TD) patients showed higher ReHo mostly in bilateral angular gyrus, left PCC, cerebellum_crus1, and cerebellum_6, while ReHo was decreased in right putamen, primary sensory cortex (S1), vermis_3, and cerebellum_4_5. These results indicate that AR and TD subgroups both represent altered spontaneous neural activity in default-mode regions and striatum, and AR subjects exhibit more changed neural activity in the mesolimbic cortex (amygdala) but TD in the cerebellar regions. Of note, direct comparison of the two subgroups revealed a distinct ReHo pattern primarily located in the striatal-thalamo-cortical (STC) and cerebello-thalamo-cortical (CTC) loops.
CONCLUSION: Overall, our findings highlight the involvement of default mode network (DMN) and STC circuit both in AR and TD subtypes, but also underscore the importance of integrating mesolimbic-striatal and CTC loops in understanding neural systems of akinesia and rigidity, as well as resting tremor in PD. This study provides improved understanding of the pathophysiological models of different subtypes of PD.
PMID: 25465747 [PubMed - as supplied by publisher]
Association between symptoms of psychosis and reduced functional connectivity of auditory cortex.
Schizophr Res. 2014 Nov 11;160(1-3):35-42
Authors: Oertel-Knöchel V, Knöchel C, Matura S, Stäblein M, Prvulovic D, Maurer K, Linden DE, van de Ven V
We have previously reported altered functional asymmetry of the primary auditory cortex (Heschl's gyrus) of patients with schizophrenia (SZ) and their relatives during auditory processing. In this study, we investigated whether schizophrenia patients have altered intrinsic functional organization of Heschl's gyrus (HG) during rest. Using functional magnetic resonance imaging (fMRI), we measured functional connectivity between bilateral HG and the whole brain in 24 SZ patients, 22 unaffected first-degree relatives and 24 matched healthy controls. SZ patients and relatives showed altered functional asymmetry in HG and altered connectivity between temporal and limbic areas in the auditory network during resting-state in comparison with healthy controls. These changes in functional connectivity correlated with predisposition towards hallucinations in patients and relatives and with acute positive symptoms in patients. The results are in line with the results from task-related and symptom-mapping studies that investigated the neural correlates of positive symptoms, and suggest that individual psychopathology is associated with aberrant intrinsic organization of auditory regions in schizophrenia. This might be evidence that reduced hemispheric lateralization and reduced functional connectivity of the auditory network are trait markers of schizophrenia.
PMID: 25464916 [PubMed - as supplied by publisher]
The role of sub-second neural events in spontaneous brain activity.
Curr Opin Neurobiol. 2014 Oct 30;32C:24-30
Authors: Florin E, Watanabe M, Logothetis NK
Human fMRI studies have identified well-reproducible resting-state networks (RSN) from spontaneous recordings. These networks are extracted from correlation metrics across the brain using several minutes of data. However, a majority of electrophysiological events occur at a sub-second time scale and their contribution to RSN generation is likely. According to recent fMRI studies RSNs separate into smaller networks when studied with higher temporal resolution. Moreover, using simultaneous electrophysiology and fMRI recordings it was shown that transient functional networks form around neural events. Therefore, considering neural events as sources of functional networks might improve the understanding of spontaneous brain activity. This endeavor will benefit from technical advances in simultaneous BOLD and electrophysiology recordings, as well as a more principled modeling of neurovascular coupling.
PMID: 25463561 [PubMed - as supplied by publisher]
Changes in the Default Mode Networks of Individuals with Long-Term Unilateral Sensorineural Hearing Loss.
Neuroscience. 2014 Nov 25;
Authors: Zhang GY, Yang M, Liu B, Huang ZC, Chen H, Zhang PP, Li J, Chen JY, Liu L, Wang J, Teng GJ
Hearing impairment contributes to cognitive dysfunction. Previous studies have found changes of functional connectivity in the default mode network (DMN) associated with cognitive processing in individuals with sensorineural hearing loss (SNHL). Whereas the changes in the DMN in patients with long-term unilateral SNHL (USNHL) is still not entirely clear. In this work, we analyzed resting-state functional MRI (fMRI) data and neuropsychological test scores from normal hearing subjects (n=11) and patients (n=21) with long-term USNHL. Functional connectivity and nodal topological properties were computed for every brain region in the DMN. ANCOVA and post hoc analyses were conducted to identify differences between normal controls and patients for each measure. Results indicated that the Left USNHL presented enhanced connectivity (p<0.05, FDR corrected), and significant changes (p<0.05, Bonferroni corrected) of the nodal topological properties in the DMN compared with the control. More changes in the DMN have been found in the L than RUSNHL. However, the neuropsychological tests did not show significant differences between the USNHL and the control. These findings suggest that long-term USNHL contributes to changes in the DMN, and these changes might affect cognitive abilities in patients with long-term USNHL. Left hearing loss affects the DMN more than the right hearing loss does. The fMRI measures might be more sensitive for observing cognitive changes in patients with hearing loss than clinical neuropsychological tests. This study provides some insights into the mechanisms of the association between hearing loss and cognitive function.
PMID: 25463518 [PubMed - as supplied by publisher]
Changes in functional connectivity and GABA levels with long-term motor learning.
Neuroimage. 2014 Nov 21;106C:15-20
Authors: Sampaio-Baptista C, Filippini N, Stagg CJ, Near J, Scholz J, Johansen-Berg H
Learning novel motor skills alters local inhibitory circuits within primary motor cortex (M1) (Floyer-Lea et al., 2006) and changes long-range functional connectivity (Albert et al., 2009). Whether such effects occur with long-term training is less well established. In addition, the relationship between learning-related changes in functional connectivity and local inhibition, and their modulation by practice, has not previously been tested. Here, we used resting-state functional magnetic resonance imaging (rs-fMRI) to assess functional connectivity and MR spectroscopy to quantify GABA in primary motor cortex (M1) before and after a 6week regime of juggling practice. Participants practiced for either 30minutes (high intensity group) or 15minutes (low intensity group) per day. We hypothesized that different training regimes would be reflected in distinct changes in brain connectivity and local inhibition, and that correlations would be found between learning-induced changes in GABA and functional connectivity. Performance improved significantly with practice in both groups and we found no evidence for differences in performance outcomes between the low intensity and high intensity groups. Despite the absence of behavioural differences, we found distinct patterns of brain change in the two groups: the low intensity group showed increases in functional connectivity in the motor network and decreases in GABA, whereas the high intensity group showed decreases in functional connectivity and no significant change in GABA. Changes in functional connectivity correlated with performance outcome. Learning-related changes in functional connectivity correlated with changes in GABA. The results suggest that different training regimes are associated with distinct patterns of brain change, even when performance outcomes are comparable between practice schedules. Our results further indicate that learning-related changes in resting-state network strength in part reflect GABAergic plastic processes.
PMID: 25463472 [PubMed - as supplied by publisher]
Construct Validation of a DCM for resting state fMRI.
Neuroimage. 2014 Nov 21;106C:1-14
Authors: Razi A, Kahan J, Rees G, Friston KJ
Recently, there has been a lot of interest in characterising the connectivity of resting state brain networks. Most of the literature uses functional connectivity to examine these intrinsic brain networks. Functional connectivity has well documented limitations because of its inherent inability to identify causal interactions. Dynamic causal modelling (DCM) is a framework that allows for the identification of the causal (directed) connections among neuronal systems - known as effective connectivity. This technical note addresses the validity of a recently proposed DCM for resting state fMRI - as measured in terms of their complex cross spectral density - referred to as spectral DCM. Spectral DCM differs from (the alternative) stochastic DCM by parameterising neuronal fluctuations using scale free (i.e., power law) forms, rendering the stochastic model of neuronal activity deterministic. Spectral DCM not only furnishes an efficient estimation of model parameters but also enables the detection of group differences in effective connectivity, the form and amplitude of the neuronal fluctuations or both. We compare and contrast spectral and stochastic DCM models with endogenous fluctuations or state noise on hidden states. We used simulated data to first establish the face validity of both schemes and show that they can recover the model (and its parameters) that generated the data. We then used Mote Carlo simulations to assess the accuracy of both schemes in terms of their root mean square error. We also simulated group differences and compared the ability of spectral and stochastic DCM to identify these differences. We show that spectral DCM was not only more accurate but also was more sensitive to group differences. Finally, we performed a comparative evaluation using real resting state fMRI data (from an open access resource) to study the functional integration within default mode network using spectral and stochastic DCMs.
PMID: 25463471 [PubMed - as supplied by publisher]
Functional Connectivity in BOLD and CBF data: Similarity and Reliability of Resting Brain Networks.
Neuroimage. 2014 Nov 21;
Authors: Jann K, Gee DG, Kilroy E, Schwab S, Smith RX, Cannon TD, Wang DJ
Resting-state functional connectivity (FC) fMRI (rs-fcMRI) offers an appealing approach to mapping the brain's intrinsic functional organization. Blood oxygen level dependent (BOLD) and arterial spin labeling (ASL) are the two main rs-fcMRI approaches to assess alterations in brain networks associated with individual differences, behaviour and psychopathology. While the BOLD signal is stronger with a higher temporal resolution, ASL provides quantitative, direct measures of the physiology and metabolism of specific networks. This study systematically investigated the similarity and reliability of resting brain networks (RBNs) in BOLD and ASL. A 2x2x2 factorial design was employed where each subject underwent repeated BOLD and ASL rs-fcMRI scans on two occasions on two MRI scanners respectively. Both independent and joint FC analyses revealed common RBNs in ASL and BOLD rs-fcMRI with a moderate to high level of spatial overlap, verified by Dice Similarity Coefficients. Test-retest analyses indicated more reliable spatial network patterns in BOLD (average modal Intraclass Correlation Coefficients: 0.905±0.033 between-sessions; 0.885±0.052 between-scanners) than ASL (0.545±0.048; 0.575±0.059). Nevertheless, ASL provided highly reproducible (0.955±0.021; 0.970±0.011) network-specific CBF measurements. Moreover, we observed positive correlations between regional CBF and FC in core areas of all RBNs indicating a relationship between network connectivity and its baseline metabolism. Taken together, the combination of ASL and BOLD rs-fcMRI provides a powerful tool for characterizing the spatiotemporal and quantitative properties of RBNs. These findings pave the way for future BOLD and ASL rs-fcMRI studies in clinical populations that are carried out across time and scanners.
PMID: 25463468 [PubMed - as supplied by publisher]
Neural correlates of the happy life: The amplitude of spontaneous low frequency fluctuations predicts subjective well-being.
Neuroimage. 2014 Nov 21;
Authors: Kong F, Hu S, Wang X, Song Y, Liu J
Subjective well-being is assumed to be distributed in the hedonic hotspots of subcortical and cortical structures. However, the precise neural correlates underlying this construct, especially how it is maintained during the resting state, are still largely unknown. Here, we explored the neural basis of subjective well-being by correlating the regional fractional amplitude of low frequency fluctuations (fALFF) with the self-reported subjective well-being of healthy individuals. Behaviorally, we demonstrated that subjective well-being contained two related but distinct components: cognitive and affective well-being. Neurally, we showed that the fALFF in the bilateral posterior superior temporal gyrus (pSTG), right posterior mid-cingulate cortex (pMCC), right thalamus, left postcentral gyrus (PCG), right lingual gyrus, and left planum temporale (PT) positively predicted cognitive well-being, whereas the fALFF in the bilateral superior frontal gyrus (SFG), right orbitofrontal cortex (OFC), and left inferior temporal gyrus (ITG) negatively predicted cognitive well-being. In contrast, only the fALFF in the right amygdala reliably predicted affective well-being. Furthermore, emotional intelligence partially mediated the effects of the right pSTG and thalamus on cognitive well-being, as well as the effect of the right amygdala on affective well-being. In summary, we provide the first evidence that spontaneous brain activity in multiple regions associated with sensation, social perception, cognition, and emotion contributes to cognitive well-being, whereas the spontaneous brain activity in only one emotion-related region contributes to affective well-being, suggesting that the spontaneous activity of the human brain reflect the efficiency of subjective well-being.
PMID: 25463465 [PubMed - as supplied by publisher]
Coupling between pupil fluctuations and resting-state fMRI uncovers a slow build-up of antagonistic responses in the human cortex.
Neuroimage. 2014 Nov 20;
Authors: Yellin D, Berkovich-Ohana A, Malach R
Even in absence of overt tasks, the human cortex manifests rich patterns of spontaneous "resting state" BOLD-fMRI fluctuations. However, the link of these spontaneous fluctuations to behavior is presently unclear. Attempts to directly investigate this link invariably lead to disruptions of the resting state. Here we took advantage of the well-established association between pupil diameter and attentional gain to address this issue by examining the correlation between the resting state BOLD and pupil fluctuations. Our results uncover a spontaneously emerging spatiotemporal pupil-BOLD correlation whereby a slow buildup of activity in default mode areas preceded both pupil dilation and wide-spread BOLD suppression in sensorimotor cortex. Control experiments excluded a role for luminance fluctuations or fixation. Comparing the pupil-correlated patterns to activation maps during visual imagery revealed a substantial overlap. Our results indicate a link between behavior, as indexed by pupil diameter, and resting state BOLD fluctuations. These pupil dilations, assumed to be related to attentional gain, were associated with spontaneously emerging antagonism between fundamental cortical networks.
PMID: 25463449 [PubMed - as supplied by publisher]
GraSP: Geodesic Graph-based Segmentation With Shape Priors for the Functional Parcellation of the Cortex.
Neuroimage. 2014 Nov 11;
Authors: Honnorat N, Eavani H, Satterthwaite TD, Gur RE, Gur RC, Davatzikos C
Resting-state functional MRI is a powerful technique for mapping the functional organization of the human brain. However, for many types of connectivity analysis, high-resolution voxelwise analyses are computationally infeasible and dimensionality reduction is typically used to limit the number of network nodes. Most commonly, network nodes are defined using standard anatomic atlases that do not align well with functional neuroanatomy or regions of interest covering a small portion of the cortex. Data-driven parcellation methods seek to overcome such limitations, but existing approaches are highly dependent on initialization procedures and produce spatially fragmented parcels or overly isotropic parcels that are unlikely to be biologically grounded. In this paper, we propose a novel graph-based parcellation method that relies on a discrete Markov Random Field framework. The spatial connectedness of the parcels is explicitly enforced by shape priors. The shape of the parcels is adapted to underlying data through the use of functional geodesic distances. Our method is initialization-free and rapidly segments the cortex in a single optimization. The performance of the method was assessed using a large developmental cohort of more than 850 subjects. Compared to two prevalent parcellation methods, our approach provides superior reproducibility for a similar data fit. Furthermore, compared to other methods, it avoids incoherent parcels. Finally, the method's utility is demonstrated through itsâ€™ ability to detect strong brain developmental effects that are only weakly observed using other methods.
PMID: 25462796 [PubMed - as supplied by publisher]
Mapping the End-Tidal CO2 Response Function in the Resting-State BOLD fMRI Signal: Spatial Specificity, Test-retest Reliability and Effect of fMRI Sampling Rate.
Neuroimage. 2014 Oct 18;104C:266-277
Authors: Golestani AM, Chang C, Kwinta JB, Khatamian YB, Jean Chen J
The blood oxygenation level dependent (BOLD) signal measures brain function indirectly through physiological processes and hence is susceptible to global physiological changes. Specifically, fluctuations in end-tidal CO2 (PETCO2), in addition to cardiac rate variation (CRV), and respiratory volume per time (RVT) variations, have been known to confound the resting-state fMRI (rs-fMRI) signal. Previous studies addressed the resting-state fMRI response function to CRV and RVT, but no attempt has been made to directly estimate the voxel-wise response function to PETCO2. Moreover, the potential interactions amongst PETCO2, CRV, and RVT necessitates their simultaneous inclusion in a multi-regression model to estimate the PETCO2 response. In this study, we use such a model to estimate the voxel-wise PETCO2 response functions directly from rs-fMRI data of nine healthy subjects. We also characterized the effect of sampling rate (TR =2s vs. 323ms) on the temporal and spatial variability of the PETCO2 response function in addition to that of CRV and RVT. In addition, we assess the test-retest reproducibility of the response functions to PETCO2, CRV and RVT. We found that despite overlaps across their spatial patterns, PETCO2 explains a unique portion of the rs-fMRI signal variance compared to RVT and CRV. We also found the shapes of the estimated responses are very similar between long- and short-TR data, although responses estimated from short-TR data have higher reproducibility.
PMID: 25462695 [PubMed - as supplied by publisher]
Stress-induced alterations in large-scale functional networks of the rodent brain.
Neuroimage. 2014 Oct 22;
Authors: Henckens MJ, van der Marel K, van der Toorn A, Pillai AG, Fernández G, Dijkhuizen RM, Joëls M
Stress-related psychopathology is associated with altered functioning of large-scale brain networks. Animal research into chronic stress, one of the most prominent environmental risk factors for development of psychopathology, has revealed molecular and cellular mechanisms potentially contributing to human mental disease. However, so far, these studies have not addressed the system-level changes in extended brain networks, thought to criticially contribute to mental disorders. We here tested the effects of chronic stress exposure (10days immobilization) on the structural integrity and functional connectivity patterns in the brain, using high-resolution structural MRI, diffusion kurtosis imaging, and resting-state fMRI, while confirming the expected changes in neuronal dendritic morphology using Golgi-staining. Stress effectiveness was confirmed by a significantly lower body weight and increased adrenal weight. In line with previous research, stressed animals displayed neuronal dendritic hypertrophy in the amygdala and hypotrophy in the hippocampal and medial prefrontal cortex. Using independent component analysis of resting-state functional MRI data, we identified ten functional connectivity networks in the rodent brain. Chronic stress appeared to increase connectivity within the somatosensory-, visual-, and default-mode networks. Moreover, chronic stress exposure was associated with an increased volume and diffusivity of the lateral ventricles, whereas no other volumetric changes were observed. This study shows that chronic stress exposure in rodents induces alterations in functional network connectivity strength which partly resemble those observed in stress-related psychopathology. Moreover, these functional consequences of stress seem to be more prominent than the effects on gross volumetric change, indicating their significance for future research.
PMID: 25462693 [PubMed - as supplied by publisher]
Recent progress and outstanding issues in motion correction in resting state fMRI.
Neuroimage. 2014 Oct 24;
Authors: Power JD, Schlaggar BL, Petersen SE
The purpose of this review is to communicate and synthesize recent findings related to motion artifact in resting state fMRI. In 2011, three groups reported that small head movements produced spurious but structured noise in brain scans, causing distance-dependent changes in signal correlations. This finding has prompted both methods development and the re-examination of prior findings with more stringent motion correction. Since 2011, over a dozen papers have been published specifically on motion artifact in resting state fMRI. We will attempt to distill these papers to their most essential content. We will point out some aspects of motion artifact that are easily or often overlooked. Throughout the review, we will highlight gaps in current knowledge and avenues for future research.
PMID: 25462692 [PubMed - as supplied by publisher]