Abnormal intrinsic brain activity patterns in leukoaraiosis with and without cognitive impairment.
Behav Brain Res. 2015 Jun 24;
Authors: Li C, Yang J, Yin X, Liu C, Zhang L, Zhang X, Gui L, Wang J
The amplitude of low frequency fluctuations (ALFF) from resting-state functional MRI (rs-fMRI) signals can be used to detect intrinsic spontaneous brain activity and provide valuable insights into the pathomechanism of neural disease. In this study, we recruited 56 patients who had been diagnosed as having mild to severe leukoaraiosis. According to the neuropsychological tests, they were subdivided into a leukoaraiosis with cognitive impairment group (n=28) and a leukoaraiosis without cognitive impairment group (n=28). 28 volunteers were included as normal controls. We found that the three groups showed significant differences in ALFF in the brain regions of the right inferior occipital gyrus (IOG_R), left middle temporal gyrus (MTG_L), left precuneus (Pcu_L), right superior frontal gyrus (SFG_R) and right superior occipital gyrus (SOG_R). Compared with normal controls, the leukoaraiosis without cognitive impairment group exhibited significantly increased ALFF in the IOG_R, Pcu_L, SFG_R and SOG_R. While compared with leukoaraiosis without cognitive impairment group, the leukoaraiosis with cognitive impairment group showed significantly decreased ALFF in IOG_R, MTG_L, Pcu_L and SOG_R. A close negative correlation was found between the ALFF values of the MTG_L and the Montreal Cognitive Assessment (MoCA) scores. Our data demonstrate that white matter integrity and cognitive impairment are associated with different amplitude fluctuations of rs-fMRI signals. Leukoaraiosis is related to ALFF increases in IOG_R, Pcu_L, SFG_Orb_R and SOG_R. Decreased ALFF in MTG_L is characteristic of cognitive impairment and may aid in its early detection.
PMID: 26116811 [PubMed - as supplied by publisher]
Thalamic resting-state functional connectivity: disruption in patients with type 2 diabetes.
Metab Brain Dis. 2015 Jun 27;
Authors: Chen YC, Xia W, Qian C, Ding J, Ju S, Teng GJ
To explore the disrupted thalamic functional connectivity and its relationships with cognitive dysfunction in type 2 diabetes mellitus (T2DM) by using resting-state functional magnetic resonance imaging (fMRI). A total of 38 T2DM patients and 39 well-matched healthy controls participated in the resting-state fMRI and T1-weighted imaging scans. The thalamic functional connectivity was characterized by using a seed-based whole-brain correlation method and compared T2DM patients with healthy controls. Pearson correlation analysis was performed between thalamic functional connectivity and clinical data. When compared with healthy controls, T2DM showed significantly decreased functional connectivity of the thalamus mainly in the right middle temporal gyrus (MTG), right precentral gyrus and bilateral occipital cortex; Increased functional connectivity of the thalamus was detected in the left cerebellum, bilateral middle frontal gyrus and middle cingulate gyrus (p < 0.05, corrected for AlphaSim). In T2DM patients, the decreased thalamic functional connectivity of the right MTG was positively associated with the Verbal Fluency Test score (r = 0.438, p = 0.006). Meanwhile, the decreased thalamic functional connectivity of the right cuneus was positively correlated with the Complex Figure Test-delayed score and negatively correlated with the Trail Making Test-B score, respectively (r = 0.492, p = 0.002; r = -0.504, p = 0.001). Moreover, there was no structural damage in the thalamus of T2DM patients. T2DM patients develop disrupted thalamocortical functional connectivity, which is associated with cognitive impairment in selected brain regions. Resting-state thalamocortical connectivity disturbance may play a central role in the underlying neuropathological process of T2DM-related cognitive dysfunction.
PMID: 26116166 [PubMed - as supplied by publisher]
Default mode network maturation and psychopathology in children and adolescents.
J Child Psychol Psychiatry. 2015 Jun 26;
Authors: Sato JR, Salum GA, Gadelha A, Crossley N, Vieira G, Manfro GG, Zugman A, Picon FA, Pan PM, Hoexter MQ, Anés M, Moura LM, Del'Aquilla MA, Jr EA, McGuire P, Lacerda AL, Rohde LA, Miguel EC, Jackowski AP, Bressan RA
BACKGROUND: The human default mode (DMN) is involved in a wide array of mental disorders. Current knowledge suggests that mental health disorders may reflect deviant trajectories of brain maturation.
METHOD: We studied 654 children using functional magnetic resonance imaging (fMRI) scans under a resting-state protocol. A machine-learning method was used to obtain age predictions of children based on the average coefficient of fractional amplitude of low frequency fluctuations (fALFFs) of the DMN, a measure of spontaneous local activity. The chronological ages of the children and fALFF measures from regions of this network, the response and predictor variables were considered respectively in a Gaussian Process Regression. Subsequently, we computed a network maturation status index for each subject (actual age minus predicted). We then evaluated the association between this maturation index and psychopathology scores on the Child Behavior Checklist (CBCL).
RESULTS: Our hypothesis was that the maturation status of the DMN would be negatively associated with psychopathology. Consistent with previous studies, fALFF significantly predicted the age of participants (p < .001). Furthermore, as expected, we found an association between the DMN maturation status (precocious vs. delayed) and general psychopathology scores (p = .011).
CONCLUSIONS: Our findings suggest that child psychopathology seems to be associated with delayed maturation of the DMN. This delay in the neurodevelopmental trajectory may offer interesting insights into the pathophysiology of mental health disorders.
PMID: 26111611 [PubMed - as supplied by publisher]
Loss of Resting-State Posterior Cingulate Flexibility Is Associated with Memory Disturbance in Left Temporal Lobe Epilepsy.
PLoS One. 2015;10(6):e0131209
Authors: Douw L, Leveroni CL, Tanaka N, Emerton BC, Cole AC, Reinsberger C, Stufflebeam SM
The association between cognition and resting-state fMRI (rs-fMRI) has been the focus of many recent studies, most of which use stationary connectivity. The dynamics or flexibility of connectivity, however, may be seminal for understanding cognitive functioning. In temporal lobe epilepsy (TLE), stationary connectomic correlates of impaired memory have been reported mainly for the hippocampus and posterior cingulate cortex (PCC). We therefore investigate resting-state and task-based hippocampal and PCC flexibility in addition to stationary connectivity in left TLE (LTLE) patients. Sixteen LTLE patients were analyzed with respect to rs-fMRI and task-based fMRI (t-fMRI), and underwent clinical neuropsychological testing. Flexibility of connectivity was calculated using a sliding-window approach by determining the standard deviation of Fisher-transformed Pearson correlation coefficients over all windows. Stationary connectivity was also calculated. Disturbed memory was operationalized as having at least one memory subtest score equal to or below the 5th percentile compared to normative data. Lower PCC flexibility, particularly in the contralateral (i.e. right) hemisphere, was found in memory-disturbed LTLE patients, who had up to 22% less flexible connectivity. No significant group differences were found with respect to hippocampal flexibility, stationary connectivity during both rs-fMRI and t-fMRI, or flexibility during t-fMRI. Contralateral resting-state PCC flexibility was able to classify all but one patient with respect to their memory status (94% accuracy). Flexibility of the PCC during rest relates to memory functioning in LTLE patients. Loss of flexible connectivity to the rest of the brain originating from the PCC, particularly contralateral to the seizure focus, is able to discern memory disturbed patients from their preserved counterparts. This study indicates that the dynamics of resting-state connectivity are associated with cognitive status of LTLE patients, rather than stationary connectivity.
PMID: 26110431 [PubMed - as supplied by publisher]
Neural Processes in the Human Temporoparietal Cortex Separated by Localized Independent Component Analysis.
J Neurosci. 2015 Jun 24;35(25):9432-45
Authors: Igelström KM, Webb TW, Graziano MS
The human temporoparietal junction (TPJ) is a topic of intense research. Imaging studies have identified TPJ activation in association with many higher-order functions such as theory-of-mind, episodic memory, and attention, causing debate about the distribution of different processes. One major challenge is the lack of consensus about the anatomical location and extent of the TPJ. Here, we address this problem using data-driven analysis to test the hypothesis that the bilateral TPJ can be parcellated into subregions. We applied independent component analysis (ICA) to task-free fMRI data within a local region around the bilateral TPJ, iterating the ICA at multiple model orders and in several datasets. The localized analysis allowed finer separation of processes and the use of multiple dimensionalities provided qualitative information about lateralization. We identified four subdivisions that were bilaterally symmetrical and one that was right biased. To test whether the independent components (ICs) reflected true subdivisions, we performed functional connectivity analysis using the IC coordinates as seeds. This confirmed that the subdivisions belonged to distinct networks. The right-biased IC was connected with a network often associated with attentional processing. One bilateral subdivision was connected to sensorimotor regions and another was connected to auditory regions. One subdivision that presented as distinct left- and right-biased ICs was connected to frontoparietal regions. Another subdivision that also had left- and right-biased ICs was connected to social or default mode networks. Our results show that the TPJ in both hemispheres hosts multiple neural processes with connectivity patterns consistent with well developed specialization and lateralization.
PMID: 26109666 [PubMed - in process]
Disrupted functional connectivity of cerebellar default network areas in attention-deficit/hyperactivity disorder.
Hum Brain Mapp. 2015 Jun 24;
Authors: Kucyi A, Hove MJ, Biederman J, Van Dijk KR, Valera EM
Attention-deficit/hyperactivity disorder (ADHD) is increasingly understood as a disorder of spontaneous brain-network interactions. The default mode network (DMN), implicated in ADHD-linked behaviors including mind-wandering and attentional fluctuations, has been shown to exhibit abnormal spontaneous functional connectivity (FC) within-network and with other networks (salience, dorsal attention and frontoparietal) in ADHD. Although the cerebellum has been implicated in the pathophysiology of ADHD, it remains unknown whether cerebellar areas of the DMN (CerDMN) exhibit altered FC with cortical networks in ADHD. Here, 23 adults with ADHD and 23 age-, IQ-, and sex-matched controls underwent resting state fMRI. The mean time series of CerDMN areas was extracted, and FC with the whole brain was calculated. Whole-brain between-group differences in FC were assessed. Additionally, relationships between inattention and individual differences in FC were assessed for between-group interactions. In ADHD, CerDMN areas showed positive FC (in contrast to average FC in the negative direction in controls) with widespread regions of salience, dorsal attention and sensorimotor networks. ADHD individuals also exhibited higher FC (more positive correlation) of CerDMN areas with frontoparietal and visual network regions. Within the control group, but not in ADHD, participants with higher inattention had higher FC between CerDMN and regions in the visual and dorsal attention networks. This work provides novel evidence of impaired CerDMN coupling with cortical networks in ADHD and highlights a role of cerebro-cerebellar interactions in cognitive function. These data provide support for the potential targeting of CerDMN areas for therapeutic interventions in ADHD. Hum Brain Mapp, 2015. © 2015 Wiley Periodicals, Inc.
PMID: 26109476 [PubMed - as supplied by publisher]
Altered regional activity and inter-regional functional connectivity in psychogenic non-epileptic seizures.
Sci Rep. 2015;5:11635
Authors: Li R, Li Y, An D, Gong Q, Zhou D, Chen H
Although various imaging studies have focused on detecting the cerebral function underlying psychogenic non-epileptic seizures (PNES), the nature of PNES remains poorly understood. In this study, we combined the resting state fMRI with fractional amplitude of low-frequency fluctuations (fALFF) and functional connectivity based on the seed voxel linear correlation approach to examine the alterations of regional and inter-regional network cerebral functions in PNES. A total of 20 healthy controls and 18 patients were enrolled. The PNES patients showed significantly increased fALFF mainly in the dorsolateral prefrontal cortex (DLPFC), parietal cortices, and motor areas, as well as decreased fALFF in the triangular inferior frontal gyrus. Thus, our results add to literature suggesting abnormalities of neural synchrony in PNES. Moreover, PNES exhibited widespread inter-regional neural network deficits, including increased (DLPFC, sensorimotor, and limbic system) and decreased (ventrolateral prefrontal cortex) connectivity, indicating that changes in the regional cerebral function are related to remote inter-regional network deficits. Correlation analysis results revealed that the connectivity between supplementary motor area and anterior cingulate cortex correlated with the PNES frequency, further suggesting the skewed integration of synchronous activity could predispose to the occurrence of PNES. Our findings provided novel evidence to investigate the pathophysiological mechanisms of PNES.
PMID: 26109123 [PubMed - in process]
Connectivity-based parcellation of the human temporal pole using diffusion tensor imaging.
Cereb Cortex. 2014 Dec;24(12):3365-78
Authors: Fan L, Wang J, Zhang Y, Han W, Yu C, Jiang T
The temporal pole (TP) is an association cortex capable of multisensory integration and participates in various high-order cognitive functions. However, an accepted parcellation of the human TP and its connectivity patterns have not yet been well established. Here, we sought to present a scheme for the parcellation of human TP based on anatomical connectivity and to reveal its subregional connectivity patterns. Three distinct subregions with characteristic fiber pathways were identified, including the dorsal (TAr), the medial (TGm), and lateral (TGl) subregions, which are located ventrally. According to the connectivity patterns, a dorsal/ventral sensory segregation of auditory and visual processing and the medial TGm involved in the olfactory processing were observed. Combined with the complementary resting-state functional connectivity analysis, the connections of the TGm with the orbitofrontal cortex and other emotion-related areas, the TGl connections with the MPFC and major default mode network regions, and the TAr connections with the perisylvian language areas were observed. To the best of our knowledge, the present study represents the first attempt to parcel the human TP based on its anatomical connectivity features, which may help to improve our understanding of its connectional anatomy and to extend the available knowledge in TP-related clinical research.
PMID: 23926116 [PubMed - indexed for MEDLINE]
Modeling resting-state functional networks when the cortex falls asleep: local and global changes.
Cereb Cortex. 2014 Dec;24(12):3180-94
Authors: Deco G, Hagmann P, Hudetz AG, Tononi G
The transition from wakefulness to sleep represents the most conspicuous change in behavior and the level of consciousness occurring in the healthy brain. It is accompanied by similarly conspicuous changes in neural dynamics, traditionally exemplified by the change from "desynchronized" electroencephalogram activity in wake to globally synchronized slow wave activity of early sleep. However, unit and local field recordings indicate that the transition is more gradual than it might appear: On one hand, local slow waves already appear during wake; on the other hand, slow sleep waves are only rarely global. Studies with functional magnetic resonance imaging also reveal changes in resting-state functional connectivity (FC) between wake and slow wave sleep. However, it remains unclear how resting-state networks may change during this transition period. Here, we employ large-scale modeling of the human cortico-cortical anatomical connectivity to evaluate changes in resting-state FC when the model "falls asleep" due to the progressive decrease in arousal-promoting neuromodulation. When cholinergic neuromodulation is parametrically decreased, local slow waves appear, while the overall organization of resting-state networks does not change. Furthermore, we show that these local slow waves are structured macroscopically in networks that resemble the resting-state networks. In contrast, when the neuromodulator decrease further to very low levels, slow waves become global and resting-state networks merge into a single undifferentiated, broadly synchronized network.
PMID: 23845770 [PubMed - indexed for MEDLINE]
Using Edge Voxel Information to Improve Motion Regression for rs-fMRI Connectivity Studies.
Brain Connect. 2015 Jun 24;
Authors: Patriat R, Molloy EK, Birn R
Recent fMRI studies have outlined the critical impact of in-scanner head motion, particularly on estimates of functional connectivity. Common strategies to reduce the influence of motion include realignment, as well as the inclusion of nuisance regressors, such as the 6 realignment parameters, their first derivatives, time-shifted versions of the realignment parameters, and the square these parameters. However, these regressors have limited success at noise reduction. We hypothesized that using nuisance regressors consisting of the principal components (PCs) of edge voxel time series would be better able to capture slice-specific and nonlinear signal changes, thus explaining more variance, improving data quality (i.e. lower DVARS and temporal SNR) and reducing the effect of motion on default-mode network connectivity. Functional MRI data from 22 healthy adult subjects were pre-processed using typical motion regression approaches, as well as nuisance regression derived from edge voxel time courses. Results were evaluated in the presence and absence of both global signal regression and motion censoring. Nuisance regressors derived from signal intensity time courses at the edge of the brain significantly improved motion correction as compared to using only the realignment parameters and their derivatives. Of the models tested, only the edge-voxel regression models were able to eliminate significant differences in DMN connectivity between high- and low-motion subjects regardless of the use of GSR or censoring.
PMID: 26107049 [PubMed - as supplied by publisher]
Altered resting-state network connectivity in stroke patients with and without apraxia of speech.
Neuroimage Clin. 2015;8:429-39
Authors: New AB, Robin DA, Parkinson AL, Duffy JR, McNeil MR, Piguet O, Hornberger M, Price CJ, Eickhoff SB, Ballard KJ
Motor speech disorders, including apraxia of speech (AOS), account for over 50% of the communication disorders following stroke. Given its prevalence and impact, and the need to understand its neural mechanisms, we used resting state functional MRI to examine functional connectivity within a network of regions previously hypothesized as being associated with AOS (bilateral anterior insula (aINS), inferior frontal gyrus (IFG), and ventral premotor cortex (PM)) in a group of 32 left hemisphere stroke patients and 18 healthy, age-matched controls. Two expert clinicians rated severity of AOS, dysarthria and nonverbal oral apraxia of the patients. Fifteen individuals were categorized as AOS and 17 were AOS-absent. Comparison of connectivity in patients with and without AOS demonstrated that AOS patients had reduced connectivity between bilateral PM, and this reduction correlated with the severity of AOS impairment. In addition, AOS patients had negative connectivity between the left PM and right aINS and this effect decreased with increasing severity of non-verbal oral apraxia. These results highlight left PM involvement in AOS, begin to differentiate its neural mechanisms from those of other motor impairments following stroke, and help inform us of the neural mechanisms driving differences in speech motor planning and programming impairment following stroke.
PMID: 26106568 [PubMed - in process]
Brain network connectivity-behavioral relationships exhibit trait-like properties: Evidence from hippocampal connectivity and memory.
Hippocampus. 2015 Jun 24;
Authors: Touroutoglou A, Andreano JM, Barrett LF, Dickerson BC
Despite a growing number of studies showing relationships between behavior and resting-state functional MRI measures of large-scale brain network connectivity, no study to our knowledge has sought to investigate whether intrinsic connectivity-behavioral relationships are stable over time. In this study, we investigated the stability of such brain-behavior relationships at two timepoints, approximately 1 week apart. We focused on the relationship between the strength of hippocampal connectivity to posterior cingulate cortex and episodic memory performance. Our results showed that this relationship is stable across samples of a different age and reliable over two points in time. These findings provide the first evidence that the relationship between large-scale intrinsic network connectivity and episodic memory performance is a stable characteristic that varies between individuals. This article is protected by copyright. All rights reserved.
PMID: 26105075 [PubMed - as supplied by publisher]
Altered Structural and Functional Connectivity in Late Preterm Preadolescence: An Anatomic Seed-Based Study of Resting State Networks Related to the Posteromedial and Lateral Parietal Cortex.
PLoS One. 2015;10(6):e0130686
Authors: Degnan AJ, Wisnowski JL, Choi S, Ceschin R, Bhushan C, Leahy RM, Corby P, Schmithorst VJ, Panigrahy A
OBJECTIVE: Late preterm birth confers increased risk of developmental delay, academic difficulties and social deficits. The late third trimester may represent a critical period of development of neural networks including the default mode network (DMN), which is essential to normal cognition. Our objective is to identify functional and structural connectivity differences in the posteromedial cortex related to late preterm birth.
METHODS: Thirty-eight preadolescents (ages 9-13; 19 born in the late preterm period (≥32 weeks gestational age) and 19 at term) without access to advanced neonatal care were recruited from a low socioeconomic status community in Brazil. Participants underwent neurocognitive testing, 3-dimensional T1-weighted imaging, diffusion-weighted imaging and resting state functional MRI (RS-fMRI). Seed-based probabilistic diffusion tractography and RS-fMRI analyses were performed using unilateral seeds within the posterior DMN (posterior cingulate cortex, precuneus) and lateral parietal DMN (superior marginal and angular gyri).
RESULTS: Late preterm children demonstrated increased functional connectivity within the posterior default mode networks and increased anti-correlation with the central-executive network when seeded from the posteromedial cortex (PMC). Key differences were demonstrated between PMC components with increased anti-correlation with the salience network seen only with posterior cingulate cortex seeding but not with precuneus seeding. Probabilistic tractography showed increased streamlines within the right inferior longitudinal fasciculus and inferior fronto-occipital fasciculus within late preterm children while decreased intrahemispheric streamlines were also observed. No significant differences in neurocognitive testing were demonstrated between groups.
CONCLUSION: Late preterm preadolescence is associated with altered functional connectivity from the PMC and lateral parietal cortex to known distributed functional cortical networks despite no significant executive neurocognitive differences. Selective increased structural connectivity was observed in the setting of decreased posterior interhemispheric connections. Future work is needed to determine if these findings represent a compensatory adaptation employing alternate neural circuitry or could reflect subtle pathology resulting in emotional processing deficits not seen with neurocognitive testing.
PMID: 26098888 [PubMed - as supplied by publisher]
Altered amygdalar resting-state connectivity in depression is explained by both genes and environment.
Hum Brain Mapp. 2015 Jun 19;
Authors: Córdova-Palomera A, Tornador C, Falcón C, Bargalló N, Nenadic I, Deco G, Fañanás L
Recent findings indicate that alterations of the amygdalar resting-state fMRI connectivity play an important role in the etiology of depression. While both depression and resting-state brain activity are shaped by genes and environment, the relative contribution of genetic and environmental factors mediating the relationship between amygdalar resting-state connectivity and depression remain largely unexplored. Likewise, novel neuroimaging research indicates that different mathematical representations of resting-state fMRI activity patterns are able to embed distinct information relevant to brain health and disease. The present study analyzed the influence of genes and environment on amygdalar resting-state fMRI connectivity, in relation to depression risk. High-resolution resting-state fMRI scans were analyzed to estimate functional connectivity patterns in a sample of 48 twins (24 monozygotic pairs) informative for depressive psychopathology (6 concordant, 8 discordant and 10 healthy control pairs). A graph-theoretical framework was employed to construct brain networks using two methods: (i) the conventional approach of filtered BOLD fMRI time-series and (ii) analytic components of this fMRI activity. Results using both methods indicate that depression risk is increased by environmental factors altering amygdalar connectivity. When analyzing the analytic components of the BOLD fMRI time-series, genetic factors altering the amygdala neural activity at rest show an important contribution to depression risk. Overall, these findings show that both genes and environment modify different patterns the amygdala resting-state connectivity to increase depression risk. The genetic relationship between amygdalar connectivity and depression may be better elicited by examining analytic components of the brain resting-state BOLD fMRI signals. Hum Brain Mapp, 2015. © 2015 Wiley Periodicals, Inc.
PMID: 26096943 [PubMed - as supplied by publisher]
Disrupted brain network topology in pediatric posttraumatic stress disorder: A resting-state fMRI study.
Hum Brain Mapp. 2015 Jun 19;
Authors: Suo X, Lei D, Li K, Chen F, Li F, Li L, Huang X, Lui S, Li L, Kemp GJ, Gong Q
Children exposed to natural disasters are vulnerable to the development of posttraumatic stress disorder (PTSD). Recent studies of other neuropsychiatric disorders have used graph-based theoretical analysis to investigate the topological properties of the functional brain connectome. However, little is known about this connectome in pediatric PTSD. Twenty-eight pediatric PTSD patients and 26 trauma-exposed non-PTSD patients were recruited from 4,200 screened subjects after the 2008 Sichuan earthquake to undergo a resting-state functional magnetic resonance imaging scan. Functional connectivity between 90 brain regions from the automated anatomical labeling atlas was established using partial correlation coefficients, and the whole-brain functional connectome was constructed by applying a threshold to the resultant 90 * 90 partial correlation matrix. Graph theory analysis was then used to examine the group-specific topological properties of the two functional connectomes. Both the PTSD and non-PTSD control groups exhibited "small-world" brain network topology. However, the functional connectome of the PTSD group showed a significant increase in the clustering coefficient and a normalized characteristic path length and local efficiency, suggesting a shift toward regular networks. Furthermore, the PTSD connectomes showed both enhanced nodal centralities, mainly in the default mode- and salience-related regions, and reduced nodal centralities, mainly in the central-executive network regions. The clustering coefficient and nodal efficiency of the left superior frontal gyrus were positively correlated with the Clinician-Administered PTSD Scale. These disrupted topological properties of the functional connectome help to clarify the pathogenesis of pediatric PTSD and could be potential biomarkers of brain abnormalities. Hum Brain Mapp, 2015. © 2015 Wiley Periodicals, Inc.
PMID: 26096541 [PubMed - as supplied by publisher]
Wavelet-based regularity analysis reveals recurrent spatiotemporal behavior in resting-state fMRI.
Hum Brain Mapp. 2015 Jun 12;
Authors: Smith RX, Jann K, Ances B, Wang DJ
One of the major findings from multimodal neuroimaging studies in the past decade is that the human brain is anatomically and functionally organized into large-scale networks. In resting state fMRI (rs-fMRI), spatial patterns emerge when temporal correlations between various brain regions are tallied, evidencing networks of ongoing intercortical cooperation. However, the dynamic structure governing the brain's spontaneous activity is far less understood due to the short and noisy nature of the rs-fMRI signal. Here, we develop a wavelet-based regularity analysis based on noise estimation capabilities of the wavelet transform to measure recurrent temporal pattern stability within the rs-fMRI signal across multiple temporal scales. The method consists of performing a stationary wavelet transform to preserve signal structure, followed by construction of "lagged" subsequences to adjust for correlated features, and finally the calculation of sample entropy across wavelet scales based on an "objective" estimate of noise level at each scale. We found that the brain's default mode network (DMN) areas manifest a higher level of irregularity in rs-fMRI time series than rest of the brain. In 25 aged subjects with mild cognitive impairment and 25 matched healthy controls, wavelet-based regularity analysis showed improved sensitivity in detecting changes in the regularity of rs-fMRI signals between the two groups within the DMN and executive control networks, compared with standard multiscale entropy analysis. Wavelet-based regularity analysis based on noise estimation capabilities of the wavelet transform is a promising technique to characterize the dynamic structure of rs-fMRI as well as other biological signals. Hum Brain Mapp, 2015. © 2015 Wiley Periodicals, Inc.
PMID: 26096080 [PubMed - as supplied by publisher]
Persistency and flexibility of complex brain networks underlie dual-task interference.
Hum Brain Mapp. 2015 Jun 12;
Authors: Alavash M, Hilgetag CC, Thiel CM, Gießing C
Previous studies on multitasking suggest that performance decline during concurrent task processing arises from interfering brain modules. Here, we used graph-theoretical network analysis to define functional brain modules and relate the modular organization of complex brain networks to behavioral dual-task costs. Based on resting-state and task fMRI we explored two organizational aspects potentially associated with behavioral interference when human subjects performed a visuospatial and speech task simultaneously: the topological overlap between persistent single-task modules, and the flexibility of single-task modules in adaptation to the dual-task condition. Participants showed a significant decline in visuospatial accuracy in the dual-task compared with single visuospatial task. Global analysis of topological similarity between modules revealed that the overlap between single-task modules significantly correlated with the decline in visuospatial accuracy. Subjects with larger overlap between single-task modules showed higher behavioral interference. Furthermore, lower flexible reconfiguration of single-task modules in adaptation to the dual-task condition significantly correlated with larger decline in visuospatial accuracy. Subjects with lower modular flexibility showed higher behavioral interference. At the regional level, higher overlap between single-task modules and less modular flexibility in the somatomotor cortex positively correlated with the decline in visuospatial accuracy. Additionally, higher modular flexibility in cingulate and frontal control areas and lower flexibility in right-lateralized nodes comprising the middle occipital and superior temporal gyri supported dual-tasking. Our results suggest that persistency and flexibility of brain modules are important determinants of dual-task costs. We conclude that efficient dual-tasking benefits from a specific balance between flexibility and rigidity of functional brain modules. Hum Brain Mapp, 2015. © 2015 Wiley Periodicals, Inc.
PMID: 26095953 [PubMed - as supplied by publisher]
Modifications of resting state networks in spinocerebellar ataxia type 2.
Mov Disord. 2015 Jun 12;
Authors: Cocozza S, Saccà F, Cervo A, Marsili A, Russo CV, Maria Delle Acque Giorgio S, De Michele G, Filla A, Brunetti A, Quarantelli M
We aimed to investigate the integrity of the Resting State Networks in spinocerebellar ataxia type 2 (SCA2) and the correlations between the modification of these networks and clinical variables. Resting-state functional magnetic resonance imaging (RS-fMRI) data from 19 SCA2 patients and 29 healthy controls were analyzed using an independent component analysis and dual regression, controlling at voxel level for the effect of atrophy by co-varying for gray matter volume. Correlations between the resting state networks alterations and disease duration, age at onset, number of triplets, and clinical score were assessed by Spearman's coefficient, for each cluster which was significantly different in SCA2 patients compared with healthy controls. In SCA2 patients, disruption of the cerebellar components of all major resting state networks was present, with supratentorial involvement only for the default mode network. When controlling at voxel level for gray matter volume, the reduction in functional connectivity in supratentorial regions of the default mode network, and in cerebellar regions within the default mode, executive and right fronto-parietal networks, was still significant. No correlations with clinical variables were found for any of the investigated resting state networks. The SCA2 patients show significant alterations of the resting state networks, only partly explained by the atrophy. The default mode network is the only resting state network that shows also supratentorial changes, which appear unrelated to the cortical gray matter volume. Further studies are needed to assess the clinical significance of these changes. © 2015 International Parkinson and Movement Disorder Society.
PMID: 26094751 [PubMed - as supplied by publisher]
Neural substrates underlying motor skill learning in chronic hemiparetic stroke patients.
Front Hum Neurosci. 2015;9:320
Authors: Lefebvre S, Dricot L, Laloux P, Gradkowski W, Desfontaines P, Evrard F, Peeters A, Jamart J, Vandermeeren Y
Motor skill learning is critical in post-stroke motor recovery, but little is known about its underlying neural substrates. Recently, using a new visuomotor skill learning paradigm involving a speed/accuracy trade-off in healthy individuals we identified three subpopulations based on their behavioral trajectories: fitters (in whom improvement in speed or accuracy coincided with deterioration in the other parameter), shifters (in whom speed and/or accuracy improved without degradation of the other parameter), and non-learners. We aimed to identify the neural substrates underlying the first stages of motor skill learning in chronic hemiparetic stroke patients and to determine whether specific neural substrates were recruited in shifters versus fitters. During functional magnetic resonance imaging (fMRI), 23 patients learned the visuomotor skill with their paretic upper limb. In the whole-group analysis, correlation between activation and motor skill learning was restricted to the dorsal prefrontal cortex of the damaged hemisphere (DLPFCdamh: r = -0.82) and the dorsal premotor cortex (PMddamh: r = 0.70); the correlations was much lesser (-0.16 < r > 0.25) in the other regions of interest. In a subgroup analysis, significant activation was restricted to bilateral posterior parietal cortices of the fitters and did not correlate with motor skill learning. Conversely, in shifters significant activation occurred in the primary sensorimotor cortexdamh and supplementary motor areadamh and in bilateral PMd where activation changes correlated significantly with motor skill learning (r = 0.91). Finally, resting-state activity acquired before learning showed a higher functional connectivity in the salience network of shifters compared with fitters (qFDR < 0.05). These data suggest a neuroplastic compensatory reorganization of brain activity underlying the first stages of motor skill learning with the paretic upper limb in chronic hemiparetic stroke patients, with a key role of bilateral PMd.
PMID: 26089787 [PubMed]
Functional connectivity in disorders of consciousness: methodological aspects and clinical relevance.
Brain Imaging Behav. 2015 Jun 19;
Authors: Marino S, Bonanno L, Giorgio A
This is a Quick Guide about the role of the functional connectivity in the Disorders of Consciousness (DOC). Recent studies on resting state (RS) in DOC, by using functional magnetic resonance imaging (fMRI), showed that functional connectivity is severely impaired above all in the default mode network (DMN). In the vegetative and minimally conscious state, DMN integrity seems to correlate with the level of remaining consciousness, offering the possibility of using this information for diagnostic and prognostic purposes. Although the two principal approaches used in the RS analysis showed several methodological difficulties, especially in DOC patients, functional brain imaging is currently being validated as a valuable addition to the standardized clinical assessments that are already in use.
PMID: 26089123 [PubMed - as supplied by publisher]