Slow fluctuations in eye position and resting-state functional magnetic resonance imaging brain activity during visual fixation.
Eur J Neurosci. 2014 Oct 10;
Authors: Fransson P, Flodin P, Oqvist Seimyr G, Pansell T
The neuronal circuitry that supports voluntary changes in eye position in tasks that require attention-driven oculo-motor control is well known. However, less is known about the neuronal basis for eye control during visual fixation. This, together with the fact that visual fixation is one of the most commonly used baseline conditions in resting-state functional magnetic resonance imaging (fMRI) studies, prompted us to conduct a study in which we employed resting-state fMRI and concurrent recordings of eye gaze to investigate the relationship between spontaneous changes in eye position during passive visual fixation and intrinsic brain activity. As a control experiment, we recorded fMRI brain activity related to cued voluntary vertical and horizontal changes in eye position in a block-related task-evoked fMRI experiment. Our results for the voluntarily performed changes in eye position elicited brain activity in the bilateral occipitotemporal cortex, supplementary motor cortex and frontal eye fields. In contrast, we show that slow fluctuations in eye position during passive visual fixation are linked to intrinsic brain activity, foremost in midline cortical brain regions located in the posteromedial parietal cortex and the medial prefrontal cortex, brain regions that act as core cortical hubs in the brain's default mode network. Our results suggest that subconscious and sustained changes in behavior are tied to intrinsic brain activity on a moment-by-moment basis.
PMID: 25302817 [PubMed - as supplied by publisher]
Decreased centrality of subcortical regions during the transition to adolescence: A functional connectivity study.
Neuroimage. 2014 Oct 4;
Authors: Sato JR, Salum GA, Gadelha A, Vieira G, Zugman A, Picon FA, Pan PM, Hoexter MQ, Anés M, Moura LM, Del'Aquilla MA, Crossley N, Junior EA, Mcguire P, Lacerda AL, Rohde LA, Miguel EC, Jackowski AP, Bressan RA
Investigations of brain maturation processes are a key step to understand the cognitive and emotional changes of adolescence. Although structural imaging findings have delineated clear brain developmental trajectories for typically developing individuals, less is known about the functional changes of this sensitive development period. Developmental changes, such as abstract thought, complex reasoning, and emotional and inhibitory control, have been associated with more prominent cortical control. The aim of this study is to assess brain networks connectivity changes in a large sample of 7-15-year-old subjects, testing the hypothesis that cortical regions will present an increasing relevance in commanding the global network. Functional magnetic resonance imaging (fMRI) data was collected in a sample of 447 typically developing children from a Brazilian community sample who were submitted to a resting state acquisition protocol. The fMRI data was used to build a functional weighted graph from which eigenvector centrality (EVC) was extracted. For each brain region (a node of the graph), the age-dependent effect on EVC was statistically tested and the developmental trajectories were estimated using polynomial functions. Our findings show that angular gyrus become more central during this maturation period, while the caudate; cerebellar tonsils, pyramis, thalamus; fusiform, parahippocampal and inferior semilunar lobe become less central. In conclusion, we report a novel finding of an increasing centrality of the angular gyrus during the transition to adolescence, with a decreasing centrality of many subcortical and cerebellar regions.
PMID: 25290886 [PubMed - as supplied by publisher]
Cognitive Control Network Function in Alcohol Use Disorder Before and During Treatment With Lorazepam.
Subst Use Misuse. 2014 Oct 7;
Authors: Wilcox C, Mayer A, Bogenschutz MP, Ling J, Dekonenko C, Cumbo H
Individuals with alcohol use disorders (AUDs) have deficits in cognitive control, but how they change with treatment is unclear. Seven patients with AUD and anxiety from an open-label trial of disulfiram plus lorazepam performed a multisensory Stroop task during fMRI (both pre and post initiation of treatment), and were compared to nine healthy controls (HCs) (n = 16; Albuquerque, NM; years 2009-2012). Evoked BOLD signal and resting state functional connectivity were compared (HC vs. AUD; Scan 1 vs. Scan 2). AUD demonstrated hyperactivity and altered connectivity in the cognitive control network compared to HC, but treatment did not normalize function.
PMID: 25290463 [PubMed - as supplied by publisher]
Resting-State fMRI Activity Predicts Unsupervised Learning and Memory in an Immersive Virtual Reality Environment.
PLoS One. 2014;9(10):e109622
Authors: Wong CW, Olafsson V, Plank M, Snider J, Halgren E, Poizner H, Liu TT
In the real world, learning often proceeds in an unsupervised manner without explicit instructions or feedback. In this study, we employed an experimental paradigm in which subjects explored an immersive virtual reality environment on each of two days. On day 1, subjects implicitly learned the location of 39 objects in an unsupervised fashion. On day 2, the locations of some of the objects were changed, and object location recall performance was assessed and found to vary across subjects. As prior work had shown that functional magnetic resonance imaging (fMRI) measures of resting-state brain activity can predict various measures of brain performance across individuals, we examined whether resting-state fMRI measures could be used to predict object location recall performance. We found a significant correlation between performance and the variability of the resting-state fMRI signal in the basal ganglia, hippocampus, amygdala, thalamus, insula, and regions in the frontal and temporal lobes, regions important for spatial exploration, learning, memory, and decision making. In addition, performance was significantly correlated with resting-state fMRI connectivity between the left caudate and the right fusiform gyrus, lateral occipital complex, and superior temporal gyrus. Given the basal ganglia's role in exploration, these findings suggest that tighter integration of the brain systems responsible for exploration and visuospatial processing may be critical for learning in a complex environment.
PMID: 25286145 [PubMed - as supplied by publisher]
Resting State Functional Connectivity in Mild Traumatic Brain Injury at the Acute Stage: Independent Component and Seed Based Analyses.
J Neurotrauma. 2014 Oct 6;
Authors: Iraji A, Benson RR, Welch RD, O'Neil BJ, Woodard JL, Ayaz SI, Kulek A, Mika V, Medado P, Soltanian-Zadeh H, Liu T, Haacke EM, Kou Z
Mild traumatic brain injury (mTBI) accounts for over 1 million emergency visits each year. Most of them stay in the emergency department for a few hours and are discharged home without a specific follow up plan due to their negative clinical structural imaging. Advanced magnetic resonance imaging (MRI), particularly functional MRI (fMRI), has been reported as being sensitive to functional disturbances after brain injury. In this study, a cohort of 12 mTBI patients were prospectively recruited from the emergency department of our local Level-1 trauma center for an advanced MRI scan at the acute stage. Sixteen age- and gender-matched controls were also recruited for comparison. Both group-based and individual-based independent component analysis of resting state fMRI (rsfMRI) demonstrated reduced functional connectivity in both posterior cingulate cortex (PCC) and precuneus regions in comparison with controls, which is part of default mode network (DMN). Further seed-based analysis confirmed reduced functional connectivity in these two regions and also demonstrated increased connectivity between these regions and other regions of the brain in mTBI. Seed based analysis using the thalamus, hippocampus and amygdala regions further demonstrated increased functional connectivity between these regions and other regions of the brain, particularly in the frontal lobe, in mTBI. Our data demonstrates alterations of multiple brain networks at the resting state, particularly increased functional connectivity in frontal lobe, in response to brain concussion at the acute stage. Resting state functional connectivity of the DMN could serve as a potential biomarker for improved detection of mTBI in the acute setting.
PMID: 25285363 [PubMed - as supplied by publisher]
De-noising with a SOCK can improve the performance of event-related ICA.
Front Neurosci. 2014;8:285
Authors: Bhaganagarapu K, Jackson GD, Abbott DF
Event-related ICA (eICA) is a partially data-driven analysis method for event-related fMRI that is particularly suited to analysis of simultaneous EEG-fMRI of patients with epilepsy. EEG-fMRI studies in epileptic patients are typically analyzed using the general linear model (GLM), often with assumption that the onset and offset of neuronal activity match EEG event onset and offset, the neuronal activation is sustained at a constant level throughout the epileptiform event and that associated fMRI signal changes follow the canonical HRF. The eICA method allows for less constrained analyses capable of detecting early, non-canonical responses. A key step of eICA is the initial deconvolution which can be confounded by various sources of structured noise present in the fMRI signal. To help overcome this, we have extend the eICA procedure by utilizing a fully standalone and automated fMRI de-noising procedure to process the fMRI data from an EEG-fMRI acquisition prior to running eICA. Specifically we first apply ICA to the entire fMRI time-series and use a classifier to remove noise-related components. The automated objective de-noiser, "Spatially Organized Component Klassificator" (SOCK) is used; it has previously been shown to distinguish a substantial fraction of noise from true activation, without rejecting the latter, in resting-state fMRI. A second ICA is then performed, this time on the event-related response estimates derived from the denoised data (according to the usual eICA procedure). We hypothesize that SOCK + eICA has the potential to be more sensitive than eICA alone. We test the effectiveness of SOCK by comparing activation obtained in an eICA analysis of EEG-fMRI data with and without the use of SOCK for 14 patients with rolandic epilepsy who exhibited stereotypical IEDs arising from a focus in the rolandic fissure.
PMID: 25285065 [PubMed]
Functional Brain Networks Contributing to the Parieto-Frontal Integration Theory of Intelligence.
Neuroimage. 2014 Oct 2;
Authors: Vakhtin AA, Ryman SG, Flores RA, Jung RE
The refinement of localization of intelligence in the human brain is converging onto a distributed network that broadly conforms to the Parieto-Frontal Integration Theory (P-FIT). While this theory has received support in the neuroimaging literature, no functional magnetic resonance imaging study to date has conducted a whole-brain network-wise examination of the changes during engagement in tasks that are reliable measures of general intelligence (e.g., Raven's Progressive Matrices Test; RPM). Seventy-nine healthy subjects were scanned while solving RPM problems and during rest. Functional networks were extracted from the RPM and resting state data using Independent Component Analysis. Twenty-nine networks were identified, 26 of which were detected in both conditions. Fourteen networks were significantly correlated with the RPM task. The networks' spatial maps and functional connectivity measures at 3 frequency levels (low, medium, & high) were compared between the RPM and rest conditions. The regions involved in the networks that were found to be task related were consistent with the P-FIT, localizing to the bilateral medial frontal and parietal regions, right superior frontal lobule, and the right cingulate gyrus. Functional connectivity in multiple component pairs was differentially affected across all frequency levels during the RPM task. Our findings demonstrate that functional brain networks are more stable than previously thought, and maintain their general features across resting state and engagement in a complex cognitive task. The described spatial and functional connectivity alterations that such components undergo during fluid reasoning provide a network-wise framework of the P-FIT that can be valuable for further, network based, neuroimaging inquiries regarding the neural underpinnings of intelligence.
PMID: 25284305 [PubMed - as supplied by publisher]
Identifying sparse connectivity patterns in the brain using resting-state fMRI.
Neuroimage. 2014 Oct 2;
Authors: Eavani H, Satterthwaite TD, Filipovych R, Gur RE, Gur RC, Davatzikos C
The human brain processes information via multiple distributed networks. An accurate model of the brain's functional connectome is critical for understanding both normal brain function as well as the dysfunction present in neuropsychiatric illnesses. Current methodologies that attempt to discover the organization of the functional connectome typically assume spatial or temporal separation of the underlying networks. This assumption deviates from an intuitive understanding of brain function, which is that of multiple, inter-dependent spatially overlapping brain networks that efficiently integrate information pertinent to diverse brain functions. It is now increasingly evident that neural systems use parsimonious formations and functional representations to efficiently process information while minimizing redundancy. Hence we exploit recent advances in the mathematics of sparse modeling to develop a methodological framework aiming to understand complex resting-state fMRI connectivity data. By favoringnetworks that explain the data via a relatively small number of participating brain regions, we obtain a parsimonious representation of brain function in terms of multiple "Sparse Connectivity Patterns" (SCPs), such that differential presence of these SCPs explains inter-subject variability. In this manner the sparsity-based framework can effectively capture the heterogeneity of functional activity patterns across individuals while potentially highlighting multiple sub-populations within the data that display similar patterns. Our results from simulated as well as real resting state fMRI data show that SCPs are accurate and reproducible between sub-samples as well as across datasets. These findings substantiate existing knowledge of intrinsic functional connectivity and provide novel insights into the functional organization of the human brain.
PMID: 25284301 [PubMed - as supplied by publisher]
Age-related increases in long-range connectivity in fetal functional neural connectivity networks in utero.
Dev Cogn Neurosci. 2014 Sep 27;
Authors: Thomason ME, Grove LE, Lozon TA, Vila AM, Ye Y, Nye MJ, Manning JH, Pappas A, Hernandez-Andrade E, Yeo L, Mody S, Berman S, Hassan SS, Romero R
Formation of operational neural networks is one of the most significant accomplishments of human fetal brain growth. Recent advances in functional magnetic resonance imaging (fMRI) have made it possible to obtain information about brain function during fetal development. Specifically, resting-state fMRI and novel signal covariation approaches have opened up a new avenue for non-invasive assessment of neural functional connectivity (FC) before birth. Early studies in this area have unearthed new insights about principles of prenatal brain function. However, very little is known about the emergence and maturation of neural networks during fetal life. Here, we obtained cross-sectional rs-fMRI data from 39 fetuses between 24 and 38 weeks postconceptual age to examine patterns of connectivity across ten neural FC networks. We identified primitive forms of motor, visual, default mode, thalamic, and temporal networks in the human fetal brain. We discovered the first evidence of increased long-range, cerebral-cerebellar, cortical-subcortical, and intra-hemispheric FC with advancing fetal age. Continued aggregation of data about fundamental neural connectivity systems in utero is essential to establishing principles of connectomics at the beginning of human life. Normative data provides a vital context against which to compare instances of abnormal neurobiological development.
PMID: 25284273 [PubMed - as supplied by publisher]
Resting-state Networks Predict Individual Differences in Common and Specific Aspects of Executive Function.
Neuroimage. 2014 Oct 1;
Authors: Reineberg AE, Andrews-Hanna JR, Depue B, Friedman NP, Banich MT
The goal of the present study was to examine relationships between individual differences in resting state functional connectivity as ascertained by fMRI (rs-fcMRI) and performance on tasks of executive function (EF), broadly defined as the ability to regulate thoughts and actions. Unlike most previous research that focused on the relationship between rs-fcMRI and a single behavioral measure of EF, in the current study we examined the relationship of rs-fcMRI with individual differences in subcomponents of EF. Ninety-one adults completed a resting state fMRI scan and three separate EF tasks outside the magnet: inhibition of prepotent responses, task set shifting, and working memory updating. From these three measures, we derived estimates of common aspects of EF, as well as abilities specific to working memory updating and task shifting. Using Independent Components Analysis (ICA), we identified across the group of participants several networks of regions (Resting State Networks, RSNs) with temporally correlated time courses. We then used dual regression to explore how these RSNs covaried with individual differences in EF. Dual regression revealed that increased higher common EF was associated with connectivity of a) frontal pole with an attentional RSN, and b) Crus I and II of the cerebellum with the right frontoparietal RSN. Moreover, higher shifting-specific abilities were associated with increased connectivity of angular gyrus with a ventral attention RSN. The results of the current study suggest that the organization of the brain at rest may have important implications for individual differences in EF, and that individuals higher in EF may have expanded resting state networks as compared to individuals with lower EF.
PMID: 25281800 [PubMed - as supplied by publisher]
Task-rest modulation of basal ganglia connectivity in mild to moderate Parkinson's disease.
Brain Imaging Behav. 2014 Oct 4;
Authors: Müller-Oehring EM, Sullivan EV, Pfefferbaum A, Huang NC, Poston KL, Bronte-Stewart HM, Schulte T
Parkinson's disease (PD) is associated with abnormal synchronization in basal ganglia-thalamo-cortical loops. We tested whether early PD patients without demonstrable cognitive impairment exhibit abnormal modulation of functional connectivity at rest, while engaged in a task, or both. PD and healthy controls underwent two functional MRI scans: a resting-state scan and a Stroop Match-to-Sample task scan. Rest-task modulation of basal ganglia (BG) connectivity was tested using seed-to-voxel connectivity analysis with task and rest time series as conditions. Despite substantial overlap of BG-cortical connectivity patterns in both groups, connectivity differences between groups had clinical and behavioral correlates. During rest, stronger putamen-medial parietal and pallidum-occipital connectivity in PD than controls was associated with worse task performance and more severe PD symptoms suggesting that abnormalities in resting-state connectivity denote neural network dedifferentiation. During the executive task, PD patients showed weaker BG-cortical connectivity than controls, i.e., between caudate-supramarginal gyrus and pallidum-inferior prefrontal regions, that was related to more severe PD symptoms and worse task performance. Yet, task processing also evoked stronger striatal-cortical connectivity, specifically between caudate-prefrontal, caudate-precuneus, and putamen-motor/premotor regions in PD relative to controls, which was related to less severe PD symptoms and better performance on the Stroop task. Thus, stronger task-evoked striatal connectivity in PD demonstrated compensatory neural network enhancement to meet task demands and improve performance levels. fMRI-based network analysis revealed that despite resting-state BG network compromise in PD, BG connectivity to prefrontal, premotor, and precuneus regions can be adequately invoked during executive control demands enabling near normal task performance.
PMID: 25280970 [PubMed - as supplied by publisher]
Reduced Topological Efficiency in Cortical-Basal Ganglia Motor Network of Parkinson's Disease: A Resting State fMRI Study.
PLoS One. 2014;9(10):e108124
Authors: Wei L, Zhang J, Long Z, Wu GR, Hu X, Zhang Y, Wang J
Parkinson's disease (PD) is mainly characterized by dopamine depletion of the cortico-basal ganglia (CBG) motor circuit. Given that dopamine dysfunction could affect functional brain network efficiency, the present study utilized resting-state fMRI (rs-fMRI) and graph theoretical approach to investigate the topological efficiency changes of the CBG motor network in patients with PD during a relatively hypodopaminergic state (12 hours after a last dose of dopamimetic treatment). We found that PD compared with controls had remarkable decreased efficiency in the CBG motor network, with the most pronounced changes observed in rostral supplementary motor area (pre-SMA), caudal SMA (SMA-proper), primary motor cortex (M1), primary somatosensory cortex (S1), thalamus (THA), globus pallidus (GP), and putamen (PUT). Furthermore, reduced efficiency in pre-SMA, M1, THA and GP was significantly correlated with Unified Parkinson's Disease Rating Scale (UPDRS) motor scores in PD patients. Together, our results demonstrate that individuals with PD appear to be less effective at information transfer within the CBG motor pathway, which provides a novel perspective on neurobiological explanation for the motor symptoms in patients. These findings are in line with the pathophysiology of PD, suggesting that network efficiency metrics may be used to identify and track the pathology of PD.
PMID: 25279557 [PubMed - as supplied by publisher]
A resting-state functional connectivity study in patients at high risk for sudden unexpected death in epilepsy.
Epilepsy Behav. 2014 Sep 29;41C:33-38
Authors: Tang Y, Chen Q, Yu X, Xia W, Luo C, Huang X, Tang H, Gong Q, Zhou D
OBJECTIVE: Seizure-related respiratory and cardiac dysfunctions were once thought to be the direct cause of sudden unexpected death in epilepsy (SUDEP), but both may be secondary to postictal cerebral inhibition. An important issue that has not been explored to date is the neural network basis of cerebral inhibition. Our aim was to investigate the features of neural networks in patients at high risk for SUDEP using a blood oxygen level-dependent (BOLD) resting-state functional connectivity (FC) approach.
SUBJECTS AND METHODS: Resting-state functional magnetic resonance imaging (Rs-fMRI) data were recorded from 13 patients at high risk for SUDEP and 12 patients at low risk for SUDEP. Thirteen cerebral regions that are closely related to cardiorespiratory activity were selected as regions of interest (ROIs). The ROI-wise resting-state FC analysis was compared between the two groups.
RESULTS: Compared with patients at low risk for SUDEP, patients at high risk exhibited significant reductions in the resting-state FC between the pons and the right thalamus, the midbrain and the right thalamus, the bilateral anterior cingulate cortex (ACC) and the right thalamus, and the left thalamus and the right thalamus.
CONCLUSIONS: This investigation is the first to use neuroimaging methods in research on the mechanism of SUDEP and demonstrates the abnormally decreased resting-state FC in the ACC-thalamus-brainstem circuit in patients at high risk for SUDEP. These findings highlight the need to understand the fundamental neural network dysfunction in SUDEP, which may fill the missing link between seizure-related cardiorespiratory dysfunction and SUDEP, and provide a promising neuroimaging biomarker for risk prediction of SUDEP.
PMID: 25277976 [PubMed - as supplied by publisher]
Functional ultrasound imaging of intrinsic connectivity in the living rat brain with high spatiotemporal resolution.
Nat Commun. 2014;5:5023
Authors: Osmanski BF, Pezet S, Ricobaraza A, Lenkei Z, Tanter M
Long-range coherences in spontaneous brain activity reflect functional connectivity. Here we propose a novel, highly resolved connectivity mapping approach, using ultrafast functional ultrasound (fUS), which enables imaging of cerebral microvascular haemodynamics deep in the anaesthetized rodent brain, through a large thinned-skull cranial window, with pixel dimensions of 100 μm × 100 μm in-plane. The millisecond-range temporal resolution allows unambiguous cancellation of low-frequency cardio-respiratory noise. Both seed-based and singular value decomposition analysis of spatial coherences in the low-frequency (<0.1 Hz) spontaneous fUS signal fluctuations reproducibly report, at different coronal planes, overlapping high-contrast, intrinsic functional connectivity patterns. These patterns are similar to major functional networks described in humans by resting-state fMRI, such as the lateral task-dependent network putatively anticorrelated with the midline default-mode network. These results introduce fUS as a powerful novel neuroimaging method, which could be extended to portable systems for three-dimensional functional connectivity imaging in awake and freely moving rodents.
PMID: 25277668 [PubMed - in process]
Resting-state functional connectivity in women with Major Depressive Disorder.
J Psychiatr Res. 2014 Sep 18;
Authors: Buchanan A, Wang X, Gollan JK
OBJECTIVE: Limited research has focused on whole-brain functional connectivity in a well-characterized sample of subjects with current Major Depressive Disorder (MDD). We aimed to investigate resting-state functional connectivity and the extent to which this is correlated with depression severity in unmedicated depressed subjects without comorbidities.
METHODS: We utilized Independent Component Analysis (ICA) to investigate whole-brain functional connectivity in a sample of healthy controls (n = 26) and unmedicated subjects diagnosed only with current MDD (n = 20). Correlations were calculated between network connectivity strength and depression severity.
RESULTS: Depressed subjects demonstrated significantly decreased connectivity in the right frontoparietal (p = 0.03), left frontoparietal (p = 0.01), and language (p = 0.02) networks compared to healthy control subjects.
CONCLUSION: We found abnormal resting-state functional connectivity not previously reported in MDD. Decreased connectivity in the frontoparietal and language networks may represent depression-related difficulties in attention, cognitive control, goal-directed cognition, and language. Findings from this study may further elucidate functional connectivity as a diagnostic marker of depression severity.
PMID: 25277274 [PubMed - as supplied by publisher]
Resting-State Functional MRI in Pediatric Epilepsy Surgery.
Pediatr Neurosurg. 2014 Sep 24;
Authors: Vadivelu S, Wolf VL, Bollo RJ, Wilfong A, Curry DJ
Resting-state functional MRI (rs-fMRI) identifies resting-state networks (RSN) in the human brain by analyzing the connectivity of anatomically remote neuronal populations with synchronous low-frequency fluctuation in blood oxygen level-dependent (BOLD) signal. Network analysis has informed the understanding of functional brain organization and is beginning to reveal the impact that neurological disorders such as epilepsy may have on the developing cerebral cortex. Among children undergoing epilepsy surgery, mapping the brain networks supporting language, sensorimotor and visual function is a critical part of the preoperative evaluation. However, task-based functional mapping techniques are particularly difficult in immature patients and those with severe impairment. Functional mapping of RSN is a promising tool that may help circumvent the challenges of adequate cooperation and limited abilities of developmentally disabled children to perform age-appropriate functions. We discuss the current methodology of rs-fMRI in the pediatric population, review the literature of rs-fMRI in pediatric epilepsy and present our experience of using rs-fMRI for functional network mapping in children undergoing epilepsy surgery. © 2014 S. Karger AG, Basel.
PMID: 25277135 [PubMed - as supplied by publisher]
Tracking whole-brain connectivity dynamics in the resting state.
Cereb Cortex. 2014 Mar;24(3):663-76
Authors: Allen EA, Damaraju E, Plis SM, Erhardt EB, Eichele T, Calhoun VD
Spontaneous fluctuations are a hallmark of recordings of neural signals, emergent over time scales spanning milliseconds and tens of minutes. However, investigations of intrinsic brain organization based on resting-state functional magnetic resonance imaging have largely not taken into account the presence and potential of temporal variability, as most current approaches to examine functional connectivity (FC) implicitly assume that relationships are constant throughout the length of the recording. In this work, we describe an approach to assess whole-brain FC dynamics based on spatial independent component analysis, sliding time window correlation, and k-means clustering of windowed correlation matrices. The method is applied to resting-state data from a large sample (n = 405) of young adults. Our analysis of FC variability highlights particularly flexible connections between regions in lateral parietal and cingulate cortex, and argues against a labeling scheme where such regions are treated as separate and antagonistic entities. Additionally, clustering analysis reveals unanticipated FC states that in part diverge strongly from stationary connectivity patterns and challenge current descriptions of interactions between large-scale networks. Temporal trends in the occurrence of different FC states motivate theories regarding their functional roles and relationships with vigilance/arousal. Overall, we suggest that the study of time-varying aspects of FC can unveil flexibility in the functional coordination between different neural systems, and that the exploitation of these dynamics in further investigations may improve our understanding of behavioral shifts and adaptive processes.
PMID: 23146964 [PubMed - indexed for MEDLINE]
Spontaneous Brain Activity in Type 2 Diabetics Revealed by Amplitude of Low-Frequency Fluctuations and Its Association with Diabetic Vascular Disease: A Resting-State fMRI Study.
PLoS One. 2014;9(10):e108883
Authors: Wang CX, Fu KL, Liu HJ, Xing F, Zhang SY
PURPOSE: To investigate correlations between altered spontaneous brain activity, diabetic vascular disease, and cognitive function for patients with type 2 diabetes mellitus (T2DM) using resting-state functional magnetic resonance imaging (rs-fMRI).
METHODS: Rs-fMRI was performed for T2DM patients (n = 26) and age-, gender-, and education-matched non-diabetic control subjects (n = 26). Amplitude of low frequency fluctuations (ALFF) were computed from fMRI signals to measure spontaneous neuronal activity. Differences in the ALFF patterns between patients and controls, as well as their correlations with clinical variables, were evaluated.
RESULTS: Compared with healthy controls, T2DM patients exhibited significantly decreased ALFF values mainly in the frontal and parietal lobes, the bilateral thalumi, the posterior lobe of the cerebellum, and increased ALFF values mainly in the visual cortices. Furthermore, lower ALFF values in the left subcallosal gyrus correlated with lower ankle-brachial index values (r = 0.481, p = 0.020), while lower ALFF values in the bilateral medial prefrontal gyri correlated with higher urinary albumin-creatinine ratio (r = -0.418, p = 0.047). In addition, most of the regions with increased ALFF values in the visual cortices were found to negatively correlate with MoCA scores.
CONCLUSIONS: These results confirm that ALFF are altered in many brain regions in T2DM patients, and this is associated with the presence of diabetic vascular disease and poor cognitive performance. These findings may provide additional insight into the neurophysiological mechanisms that mediate T2DM-related cognitive dysfunction, and may also serve as a reference for future research.
PMID: 25272033 [PubMed - as supplied by publisher]
Preservation of EEG organization in patients with impaired consciousness and imaging-based evidence of command-following.
Ann Neurol. 2014 Oct 1;
Authors: Forgacs PB, Conte MM, Fridman EA, Voss HU, Victor JD, Schiff ND
Objective: Standard clinical characterization of patients with disorders of consciousness (DOC) relies on observation of motor output and may therefore lead to the misdiagnosis of vegetative state (VS) or minimally conscious state (MCS) in patients with preserved cognition. We used conventional electroencephalographic (EEG) measures to assess a cohort of DOC patients with and without functional MRI (fMRI)-based evidence of command following, and correlated the findings with standard clinical behavioral evaluation and brain metabolic activity. Methods: We enrolled 44 patients with severe brain injury. Behavioral diagnosis was established using standardized clinical assessments. Long-term EEG recordings were analyzed to determine wakeful background organization and presence of elements of sleep architecture. A subset of patients had fMRI testing of command following using motor imagery paradigms (26 patients) and resting brain metabolism measurement using (18) FDG-PET (31 patients). Results: All four patients with fMRI evidence of covert command following consistently demonstrated well-organized EEG background during wakefulness, spindling activity during sleep, and relative preservation of cortical metabolic activity. In the entire cohort, EEG organization and overall brain metabolism showed no significant association with bedside behavioral testing, except in a few cases when EEG was severely abnormal. Interpretation: These findings suggest that conventional EEG is a simple strategy that complements behavioral and imaging characterization of DOC patients. Preservation of specific EEG features may be used to assess the likelihood of unrecognized cognitive abilities in severely brain injured patients with very limited or no motor responses. ANN NEUROL 2014. © 2014 American Neurological Association.
PMID: 25270034 [PubMed - as supplied by publisher]
The Cerebral Cost of Breathing: An fMRI Case-Study in Congenital Central Hypoventilation Syndrome.
PLoS One. 2014;9(9):e107850
Authors: Sharman M, Gallea C, Lehongre K, Galanaud D, Nicolas N, Similowski T, Cohen L, Straus C, Naccache L
Certain motor activities - like walking or breathing - present the interesting property of proceeding either automatically or under voluntary control. In the case of breathing, brainstem structures located in the medulla are in charge of the automatic mode, whereas cortico-subcortical brain networks - including various frontal lobe areas - subtend the voluntary mode. We speculated that the involvement of cortical activity during voluntary breathing could impact both on the "resting state" pattern of cortical-subcortical connectivity, and on the recruitment of executive functions mediated by the frontal lobe. In order to test this prediction we explored a patient suffering from central congenital hypoventilation syndrome (CCHS), a very rare developmental condition secondary to brainstem dysfunction. Typically, CCHS patients demonstrate efficient cortically-controlled breathing while awake, but require mechanically-assisted ventilation during sleep to overcome the inability of brainstem structures to mediate automatic breathing. We used simultaneous EEG-fMRI recordings to compare patterns of brain activity between these two types of ventilation during wakefulness. As compared with spontaneous breathing (SB), mechanical ventilation (MV) restored the default mode network (DMN) associated with self-consciousness, mind-wandering, creativity and introspection in healthy subjects. SB on the other hand resulted in a specific increase of functional connectivity between brainstem and frontal lobe. Behaviorally, the patient was more efficient in cognitive tasks requiring executive control during MV than during SB, in agreement with her subjective reports in everyday life. Taken together our results provide insight into the cognitive and neural costs of spontaneous breathing in one CCHS patient, and suggest that MV during waking periods may free up frontal lobe resources, and make them available for cognitive recruitment. More generally, this study reveals how the active maintenance of cortical control over a continuous motor activity impacts on brain functioning and cognition.
PMID: 25268234 [PubMed - as supplied by publisher]