Effects of Beta-Amyloid on Resting State Functional Connectivity Within and Between Networks Reflect Known Patterns of Regional Vulnerability.
Cereb Cortex. 2014 Nov 7;
Authors: Elman JA, Madison CM, Baker SL, Vogel JW, Marks SM, Crowley S, O'Neil JP, Jagust WJ
Beta-amyloid (Aβ) deposition is one of the hallmarks of Alzheimer's disease (AD). However, it is also present in some cognitively normal elderly adults and may represent a preclinical disease state. While AD patients exhibit disrupted functional connectivity (FC) both within and between resting-state networks, studies of preclinical cases have focused primarily on the default mode network (DMN). The extent to which Aβ-related effects occur outside of the DMN and between networks remains unclear. In the present study, we examine how within- and between-network FC are related to both global and regional Aβ deposition as measured by [(11)C]PIB-PET in 92 cognitively normal older people. We found that within-network FC changes occurred in multiple networks, including the DMN. Changes of between-network FC were also apparent, suggesting that regions maintaining connections to multiple networks may be particularly susceptible to Aβ-induced alterations. Cortical regions showing altered FC clustered in parietal and temporal cortex, areas known to be susceptible to AD pathology. These results likely represent a mix of local network disruption, compensatory reorganization, and impaired control network function. They indicate the presence of Aβ-related dysfunction of neural systems in cognitively normal people well before these areas become hypometabolic with the onset of cognitive decline.
PMID: 25405944 [PubMed - as supplied by publisher]
CONNECTOMICS SIGNATURE FOR CHARACTERIZATON OF MILD COGNITIVE IMPAIRMENT AND SCHIZOPHRENIA.
Proc IEEE Int Symp Biomed Imaging. 2014 May;2014:325-328
Authors: Zhu D, Shen D, Jiang X, Liu T
Human connectomes constructed via neuroimaging data offer a comprehensive description of the macro-scale structural connectivity within the brain. Thus quantitative assessment of connectome-scale structural and functional connectivities will not only fundamentally advance our understanding of normal brain organization and function, but also have significant importance to systematically and comprehensively characterize many devastating brain conditions. In recognition of the importance of connectome and connectomics, in this paper, we develop and evaluate a novel computational framework to construct structural connectomes from diffusion tensor imaging (DTI) data and assess connectome-scale functional connectivity alterations in mild cognitive impairment (MCI) and schizophrenia (SZ) from concurrent resting state fMRI (R-fMRI) data, in comparison with their healthy controls. By applying effective feature selection approaches, we discovered informative and robust functional connectomics signatures that can distinctively characterize and successfully differentiate the two brain conditions of MCI and SZ from their healthy controls (classification accuracies are 96% and 100%, respectively). Our results suggest that connectomics signatures could be a general, powerful methodology for characterization and classification of many brain conditions in the future.
PMID: 25404998 [PubMed - as supplied by publisher]
Functional organization of intrinsic connectivity networks in Chinese-chess experts.
Brain Res. 2014 Apr 16;1558:33-43
Authors: Duan X, Long Z, Chen H, Liang D, Qiu L, Huang X, Liu TC, Gong Q
The functional architecture of the human brain has been extensively described in terms of functional connectivity networks, detected from the low-frequency coherent neuronal fluctuations during a resting state condition. Accumulating evidence suggests that the overall organization of functional connectivity networks is associated with individual differences in cognitive performance and prior experience. Such an association raises the question of how cognitive expertise exerts an influence on the topological properties of large-scale functional networks. To address this question, we examined the overall organization of brain functional networks in 20 grandmaster and master level Chinese-chess players (GM/M) and twenty novice players, by means of resting-state functional connectivity and graph theoretical analyses. We found that, relative to novices, functional connectivity was increased in GM/Ms between basal ganglia, thalamus, hippocampus, and several parietal and temporal areas, suggesting the influence of cognitive expertise on intrinsic connectivity networks associated with learning and memory. Furthermore, we observed economical small-world topology in the whole-brain functional connectivity networks in both groups, but GM/Ms exhibited significantly increased values of normalized clustering coefficient which resulted in increased small-world topology. These findings suggest an association between the functional organization of brain networks and individual differences in cognitive expertise, which might provide further evidence of the mechanisms underlying expert behavior.
PMID: 24565926 [PubMed - indexed for MEDLINE]
Subclinical delusional thinking predicts lateral temporal cortex responses during social reflection.
Soc Cogn Affect Neurosci. 2014 Mar;9(3):273-82
Authors: Brent BK, Coombs G, Keshavan MS, Seidman LJ, Moran JM, Holt DJ
Neuroimaging studies have demonstrated associations between delusions in psychotic disorders and abnormalities of brain areas involved in social cognition, including medial prefrontal cortex (MPFC), posterior cingulate cortex, and lateral temporal cortex (LTC). General population studies have linked subclinical delusional thinking to impaired social cognition, raising the question of whether a specific pattern of brain activity during social perception is associated with delusional beliefs. Here, we tested the hypothesis that subclinical delusional thinking is associated with changes in neural function, while subjects made judgments about themselves or others ['social reflection' (SR)]. Neural responses during SR and non-social tasks, as well as resting-state activity, were measured using functional magnetic resonance imaging in 22 healthy subjects. Delusional thinking was measured using the Peters et al. Delusions Inventory. Delusional thinking was negatively correlated with responses of the left LTC during SR (r = -0.61, P = 0.02, Bonferroni corrected), and connectivity between the left LTC and left ventral MPFC, and was positively correlated with connectivity between the left LTC and the right middle frontal and inferior temporal cortices. Thus, delusional thinking in the general population may be associated with reduced activity and aberrant functional connectivity of cortical areas involved in SR.
PMID: 23160817 [PubMed - indexed for MEDLINE]
Resting-state functional connectivity in anterior cingulate cortex in normal aging.
Front Aging Neurosci. 2014;6:280
Authors: Cao W, Luo C, Zhu B, Zhang D, Dong L, Gong J, Gong D, He H, Tu S, Yin W, Li J, Chen H, Yao D
Growing evidence suggests that normal aging is associated with cognitive decline and well-maintained emotional well-being. The anterior cingulate cortex (ACC) is an important brain region involved in emotional and cognitive processing. We investigated resting-state functional connectivity (FC) of two ACC subregions in 30 healthy older adults vs. 33 healthy younger adults, by parcellating into rostral (rACC) and dorsal (dACC) ACC based on clustering of FC profiles. Compared with younger adults, older adults demonstrated greater connection between rACC and anterior insula, suggesting that older adults recruit more proximal dACC brain regions connected with insula to maintain a salient response. Older adults also demonstrated increased FC between rACC and superior temporal gyrus and inferior frontal gyrus, decreased integration between rACC and default mode, and decreased dACC-hippocampal and dACC-thalamic connectivity. These altered FCs reflected rACC and dACC reorganization, and might be related to well emotion regulation and cognitive decline in older adults. Our findings provide further insight into potential functional substrates of emotional and cognitive alterations in the aging brain.
PMID: 25400578 [PubMed]
Cortical connective field estimates from resting state fMRI activity.
Front Neurosci. 2014;8:339
Authors: Gravel N, Harvey B, Nordhjem B, Haak KV, Dumoulin SO, Renken R, Curčić-Blake B, Cornelissen FW
One way to study connectivity in visual cortical areas is by examining spontaneous neural activity. In the absence of visual input, such activity remains shaped by the underlying neural architecture and, presumably, may still reflect visuotopic organization. Here, we applied population connective field (CF) modeling to estimate the spatial profile of functional connectivity in the early visual cortex during resting state functional magnetic resonance imaging (RS-fMRI). This model-based analysis estimates the spatial integration between blood-oxygen level dependent (BOLD) signals in distinct cortical visual field maps using fMRI. Just as population receptive field (pRF) mapping predicts the collective neural activity in a voxel as a function of response selectivity to stimulus position in visual space, CF modeling predicts the activity of voxels in one visual area as a function of the aggregate activity in voxels in another visual area. In combination with pRF mapping, CF locations on the cortical surface can be interpreted in visual space, thus enabling reconstruction of visuotopic maps from resting state data. We demonstrate that V1 ➤ V2 and V1 ➤ V3 CF maps estimated from resting state fMRI data show visuotopic organization. Therefore, we conclude that-despite some variability in CF estimates between RS scans-neural properties such as CF maps and CF size can be derived from resting state data.
PMID: 25400541 [PubMed]
Separate neural representations for physical pain and social rejection.
Nat Commun. 2014;5:5380
Authors: Woo CW, Koban L, Kross E, Lindquist MA, Banich MT, Ruzic L, Andrews-Hanna JR, Wager TD
Current theories suggest that physical pain and social rejection share common neural mechanisms, largely by virtue of overlapping functional magnetic resonance imaging (fMRI) activity. Here we challenge this notion by identifying distinct multivariate fMRI patterns unique to pain and rejection. Sixty participants experience painful heat and warmth and view photos of ex-partners and friends on separate trials. FMRI pattern classifiers discriminate pain and rejection from their respective control conditions in out-of-sample individuals with 92% and 80% accuracy. The rejection classifier performs at chance on pain, and vice versa. Pain- and rejection-related representations are uncorrelated within regions thought to encode pain affect (for example, dorsal anterior cingulate) and show distinct functional connectivity with other regions in a separate resting-state data set (N=91). These findings demonstrate that separate representations underlie pain and rejection despite common fMRI activity at the gross anatomical level. Rather than co-opting pain circuitry, rejection involves distinct affective representations in humans.
PMID: 25400102 [PubMed - in process]
BNST neurocircuitry in humans.
Neuroimage. 2014 May 1;91:311-23
Authors: Avery SN, Clauss JA, Winder DG, Woodward N, Heckers S, Blackford JU
Anxiety and addiction disorders are two of the most common mental disorders in the United States, and are typically chronic, disabling, and comorbid. Emerging evidence suggests the bed nucleus of the stria terminalis (BNST) mediates both anxiety and addiction through connections with other brain regions, including the amygdala and nucleus accumbens. Although BNST structural connections have been identified in rodents and a limited number of structural connections have been verified in non-human primates, BNST connections have yet to be described in humans. Neuroimaging is a powerful tool for identifying structural and functional circuits in vivo. In this study, we examined BNST structural and functional connectivity in a large sample of humans. The BNST showed structural and functional connections with multiple subcortical regions, including limbic, thalamic, and basal ganglia structures, confirming structural findings in rodents. We describe two novel connections in the human brain that have not been previously reported in rodents or non-human primates, including a structural connection with the temporal pole, and a functional connection with the paracingulate gyrus. The findings of this study provide a map of the BNST's structural and functional connectivity across the brain in healthy humans. In large part, the BNST neurocircuitry in humans is similar to the findings from rodents and non-human primates; however, several connections are unique to humans. Future explorations of BNST neurocircuitry in anxiety and addiction disorders have the potential to reveal novel mechanisms underlying these disabling psychiatric illnesses.
PMID: 24444996 [PubMed - indexed for MEDLINE]
Connectivity cluster analysis for discovering discriminative subnetworks in schizophrenia.
Hum Brain Mapp. 2014 Nov 13;
Authors: Atluri G, Steinbach M, Lim KO, Kumar V, MacDonald A
In this manuscript, we present connectivity cluster analysis (CoCA), a novel computational framework that takes advantage of structure of the brain networks to magnify reproducible signals and quash noise. Resting state functional Magnetic Resonance Imaging (fMRI) data that is used in estimating functional brain networks is often noisy, leading to reduced power and inconsistent findings across independent studies. There is a need for techniques that can unearth signals in noisy datasets, while addressing redundancy in the functional connections that are used for testing association. CoCA is a data driven approach that addresses the problems of redundancy and noise by first finding groups of region pairs that behave in a cohesive way across the subjects. These cohesive sets of functional connections are further tested for association with the disease. CoCA is applied in the context of patients with schizophrenia, a disorder characterized as a disconnectivity syndrome. Our results suggest that CoCA can find reproducible sets of functional connections that behave cohesively. Applying this technique, we found that the connectivity clusters joining thalamus to parietal, temporal, and visuoparietal regions are highly discriminative of schizophrenia patients as well as reproducible using retest data and replicable in an independent confirmatory sample. Hum Brain Mapp, 2014. © 2014 Wiley Periodicals, Inc.
PMID: 25394864 [PubMed - as supplied by publisher]
Structural and Functional Correlates of Behavioral Pattern Separation in the Hippocampus and Medial Temporal Lobe.
Hippocampus. 2014 Nov 14;
Authors: Doxey CR, Kirwan CB
Structures of the medial temporal lobe (MTL) are known to be involved in declarative memory processes. However, little is known about how age-related changes in MTL structures, white matter integrity, and functional connectivity affect pattern separation processes in the MTL. In the present study, we used magnetic resonance imaging (MRI) to measure the volumes of MTL regions of interest, including hippocampal subfields (dentate gyrus, CA3, CA1, and subiculum) in healthy older and younger adults. Additionally, we used diffusion tensor imaging to measure white matter integrity for both groups. Finally, we used functional MRI to acquire resting functional connectivity measures for both groups. We show that, along with age, the volume of left CA3/dentate gyrus predicts memory performance. Differences in fractional anisotropy and the strength of resting functional connections between the hippocampus and other cortical structures implicated in memory processing were not significant predictors of performance. As previous studies have only hinted, it seems that the size of left CA3/dentate gyrus contributes more to successful discrimination between similar mnemonic representations than other hippocampal sub-fields, MTL structures, and other neuroimaging correlates. Accordingly, the implications of aging and atrophy on lure discrimination capacities are discussed. This article is protected by copyright. All rights reserved.
PMID: 25394655 [PubMed - as supplied by publisher]
Dynamics on Networks: The Role of Local Dynamics and Global Networks on the Emergence of Hypersynchronous Neural Activity.
PLoS Comput Biol. 2014 Nov;10(11):e1003947
Authors: Schmidt H, Petkov G, Richardson MP, Terry JR
Graph theory has evolved into a useful tool for studying complex brain networks inferred from a variety of measures of neural activity, including fMRI, DTI, MEG and EEG. In the study of neurological disorders, recent work has discovered differences in the structure of graphs inferred from patient and control cohorts. However, most of these studies pursue a purely observational approach; identifying correlations between properties of graphs and the cohort which they describe, without consideration of the underlying mechanisms. To move beyond this necessitates the development of computational modeling approaches to appropriately interpret network interactions and the alterations in brain dynamics they permit, which in the field of complexity sciences is known as dynamics on networks. In this study we describe the development and application of this framework using modular networks of Kuramoto oscillators. We use this framework to understand functional networks inferred from resting state EEG recordings of a cohort of 35 adults with heterogeneous idiopathic generalized epilepsies and 40 healthy adult controls. Taking emergent synchrony across the global network as a proxy for seizures, our study finds that the critical strength of coupling required to synchronize the global network is significantly decreased for the epilepsy cohort for functional networks inferred from both theta (3-6 Hz) and low-alpha (6-9 Hz) bands. We further identify left frontal regions as a potential driver of seizure activity within these networks. We also explore the ability of our method to identify individuals with epilepsy, observing up to 80[Formula: see text] predictive power through use of receiver operating characteristic analysis. Collectively these findings demonstrate that a computer model based analysis of routine clinical EEG provides significant additional information beyond standard clinical interpretation, which should ultimately enable a more appropriate mechanistic stratification of people with epilepsy leading to improved diagnostics and therapeutics.
PMID: 25393751 [PubMed - as supplied by publisher]
Altered basal ganglia functional connectivity in multiple sclerosis patients with fatigue.
Mult Scler. 2014 Nov 12;
Authors: Finke C, Schlichting J, Papazoglou S, Scheel M, Freing A, Soemmer C, Pech L, Pajkert A, Pfüller C, Wuerfel J, Ploner C, Paul F, Brandt A
BACKGROUND: Fatigue is one of the most frequent and disabling symptoms in multiple sclerosis, but its pathophysiological mechanisms are poorly understood. It is in particular unclear whether and how fatigue relates to structural and functional brain changes.
OBJECTIVE: We aimed to analyse the association of fatigue severity with basal ganglia functional connectivity, basal ganglia volumes, white matter integrity and grey matter density.
METHODS: In 44 patients with relapsing-remitting multiple sclerosis and 20 age- and gender-matched healthy controls, resting-state fMRI, diffusion tensor imaging and voxel-based morphometry was performed.
RESULTS: In comparison with healthy controls, patients showed alteration of grey matter density, white matter integrity, basal ganglia volumes and basal ganglia functional connectivity. No association of fatigue severity with grey matter density, white matter integrity and basal ganglia volumes was observed within patients. In contrast, fatigue severity was negatively correlated with functional connectivity of basal ganglia nuclei with medial prefrontal cortex, precuneus and posterior cingulate cortex in patients. Furthermore, fatigue severity was positively correlated with functional connectivity between caudate nucleus and motor cortex.
CONCLUSION: Fatigue is associated with distinct alterations of basal ganglia functional connectivity independent of overall disability. The pattern of connectivity changes suggests that disruption of motor and non-motor basal ganglia functions, including motivation and reward processing, contributes to fatigue pathophysiology in multiple sclerosis.
PMID: 25392321 [PubMed - as supplied by publisher]
Altered functional connectivity in seizure onset zones revealed by fMRI intrinsic connectivity.
Neurology. 2014 Nov 12;
Authors: Lee HW, Arora J, Papademetris X, Tokoglu F, Negishi M, Scheinost D, Farooque P, Blumenfeld H, Spencer DD, Constable RT
OBJECTIVE: The purpose of this study was to investigate functional connectivity (FC) changes in epileptogenic networks in intractable partial epilepsy obtained from resting-state fMRI by using intrinsic connectivity contrast (ICC), a voxel-based network measure of degree that reflects the number of connections to each voxel.
METHODS: We measured differences between intrahemispheric- and interhemispheric-ICC (ICCintra-inter) that could reveal localized connectivity abnormalities in epileptogenic zones while more global network changes would be eliminated when subtracting these values. The ICCintra-inter map was compared with the seizure onset zone (SOZ) based on intracranial EEG (icEEG) recordings in 29 patients with at least 1 year of postsurgical follow-up. Two independent reviewers blindly interpreted the icEEG and fMRI data, and the concordance rates were compared for various clinical factors.
RESULTS: Concordance between the icEEG SOZ and ICCintra-inter map was observed in 72.4% (21/29) of the patients, which was higher in patients with good surgical outcome, especially in those patients with temporal lobe epilepsy (TLE) or lateral temporal seizure localization. Concordance was also better in the extratemporal lobe epilepsy than the TLE group. In 85.7% (18/21) of the cases, the ICCintra-inter values were negative in the SOZ, indicating decreased FC within the epileptic hemisphere relative to between hemispheres.
CONCLUSIONS: Assessing alterations in FC using fMRI-ICC map can help localize the SOZ, which has potential as a noninvasive presurgical diagnostic tool to improve surgical outcome. In addition, the method reveals that, in focal epilepsy, both intrahemispheric- and interhemispheric-FC may be altered, in the presence of both regional as well as global network abnormalities.
PMID: 25391304 [PubMed - as supplied by publisher]
Modulation of effective connectivity in the default mode network at rest and during a memory task.
Brain Connect. 2014 Nov 12;
Authors: Li X, Kehoe EG, McGinnity TM, Coyle D, Bokde A
It is known that the default mode network (DMN) may be modulated by a cognitive task and by performance level. Changes in the DMN have been examined by investigating resting state activation levels, but there have been very few studies examining the modulation of effective connectivity of the DMN during a task in healthy older subjects. In this study we examined how effective connectivity changed in the DMN between rest and during a memory task. We also investigated whether there was any relationship between effective connectivity modulation in the DMN and memory performance, in order to establish whether variations in cognitive performance are related to neural network effective connectivity, either at rest or during task performance. Twenty-eight healthy older participants underwent a resting-state functional MRI (rfMRI) scan and an emotional face-name encoding task. Effective connectivity analyses were performed on the DMN in order to examine the effective connectivity modulation in these two different conditions. During the resting state there was strong self-influence in the regions of the DMN, whille the main regions with statistically significant cross-regional effective connectivity were the posterior cingulate cortex (PCC) and the hippocampus (HP). During the memory task the self-influence effective connectivites remained statistically significant across the DMN and there were statistically significant effective connectivites from the PCC, HP, amygdala (AM) and parahippocampal region to other DMN regions. We found that effective connectivities from PCC, HP and AM (in both resting state and during task) were linearly correlated to memory performance. The results suggest that superior memory ability in this older cohort was associated with effective connectity both at rest and during the memory task of three DMN regions which are also known to be important for memory fuction. Keywords: Effective connectivity modulation, ageing, emotional face processing, default mode network, fMRI.
PMID: 25390185 [PubMed - as supplied by publisher]
Functional connectivity analyses using emulated and conventional resting state data: Parts vs. the whole story.
Brain Connect. 2014 Nov 12;
Authors: Loitfelder M, Pinter D, Langkammer C, Jehna M, Ropele S, Fazekas F, Schmidt R, Enzinger C
Continuous resting state (RS) fMRI has become particularly useful to identify changes in functional connectivity (FC) in CNS disorders. Fair et al. proposed a method of volume extraction to emulate RS fMRI from block-design experiments. Whether the validity of this approach holds true in Multiple Sclerosis (MS) patients has not been tested formally so far. Twelve MS patients and 18 controls underwent conventional RS fMRI and a cognitive block-design fMRI. The total amount of volumes as well as the truncated set of volumes of both functional datasets was separately analyzed using a seed based approach. Whereas, overall, seed based analyses of FC from the ACC allowed identification of the same key-network constituents using different analytical approaches, higher-level within group analyses of emulated RS vs. continuous RS also revealed significant distinct differences in FC networks. Using the emulated RS approach, a general identification of connectivity networks similar to those obtained using conventional RS-data appears feasible also in diseased brains. Higher-level contrasts, however, yielded different results attesting to a significant impact of employed methodology.
PMID: 25389907 [PubMed - as supplied by publisher]
Altered functional connectivity links in neuroleptic-naïve and neuroleptic-treated patients with schizophrenia, and their relation to symptoms including volition.
Neuroimage Clin. 2014;6:463-74
Authors: Pu W, Rolls ET, Guo S, Liu H, Yu Y, Xue Z, Feng J, Liu Z
In order to analyze functional connectivity in untreated and treated patients with schizophrenia, resting-state fMRI data were obtained for whole-brain functional connectivity analysis from 22 first-episode neuroleptic-naïve schizophrenia (NNS), 61 first-episode neuroleptic-treated schizophrenia (NTS) patients, and 60 healthy controls (HC). Reductions were found in untreated and treated patients in the functional connectivity between the posterior cingulate gyrus and precuneus, and this was correlated with the reduction in volition from the Positive and Negative Symptoms Scale (PANSS), that is in the willful initiation, sustenance, and control of thoughts, behavior, movements, and speech, and with the general and negative symptoms. In addition in both patient groups interhemispheric functional connectivity was weaker between the orbitofrontal cortex, amygdala and temporal pole. These functional connectivity changes and the related symptoms were not treated by the neuroleptics. Differences between the patient groups were that there were more strong functional connectivity links in the NNS patients (including in hippocampal, frontal, and striatal circuits) than in the NTS patients. These findings with a whole brain analysis in untreated and treated patients with schizophrenia provide evidence on some of the brain regions implicated in the volitional, other general, and negative symptoms, of schizophrenia that are not treated by neuroleptics so have implications for the development of other treatments; and provide evidence on some brain systems in which neuroleptics do alter the functional connectivity.
PMID: 25389520 [PubMed - in process]
Enhancement of Resting-State fcMRI Networks by Prior Sensory Stimulation.
Brain Connect. 2014 Nov 11;
Authors: Li C, Li Z, Ward D, Dwinell MR, Lombard JH, Hudetz AG, Pawela CP
It is important to consider the effect of a previous experimental condition when analyzing resting-state functional connectivity magnetic resonance imaging (fcMRI) data. In this work, a simple sensory stimulation functional MRI (fMRI) experiment was conducted between two resting-state fcMRI acquisitions in anesthetized rats using a high-field small-animal MR scanner. Previous human studies have reported fcMRI network alteration by prior task/stimulus utilizing similar experimental paradigms. An anesthetized rat preparation was used to test whether brain regions with higher-level functions are involved in post-task/stimulus fcMRI network alteration. We demonstrate significant fcMRI enhancement post-stimulation in sensory cortical, limbic, and insular brain regions in rats. These brain regions have been previously implicated in vigilance and anesthetic arousal networks. Further, we tested our experimental paradigm in several inbred strains of rats with known phenotypic differences in anesthetic susceptibility and cerebral vascular function. Brown Norway (BN), Dahl Salt Sensitive (SS), and consomic SSBN13 strain were tested. We have previously showed significant differences in Blood Oxygen Level-Dependent (BOLD) fMRI activity and fcMRI networks across these strains. Here we report statically significant inter-strain differences in regional fcMRI post-stimulation enhancement. In the SS strain, post-stimulation enhancement occurred in posterior sensory and limbic cortical brain regions. In the BN strain, post-stimulation enhancement appeared in anterior cingulate and sub-cortical limbic brain regions. Our results imply that prior condition has a significant impact on fcMRI networks that depend on inter-subject difference in genetics and physiology.
PMID: 25387238 [PubMed - as supplied by publisher]
Long-term effects of marijuana use on the brain.
Proc Natl Acad Sci U S A. 2014 Nov 10;
Authors: Filbey FM, Aslan S, Calhoun VD, Spence JS, Damaraju E, Caprihan A, Segall J
Questions surrounding the effects of chronic marijuana use on brain structure continue to increase. To date, however, findings remain inconclusive. In this comprehensive study that aimed to characterize brain alterations associated with chronic marijuana use, we measured gray matter (GM) volume via structural MRI across the whole brain by using voxel-based morphology, synchrony among abnormal GM regions during resting state via functional connectivity MRI, and white matter integrity (i.e., structural connectivity) between the abnormal GM regions via diffusion tensor imaging in 48 marijuana users and 62 age- and sex-matched nonusing controls. The results showed that compared with controls, marijuana users had significantly less bilateral orbitofrontal gyri volume, higher functional connectivity in the orbitofrontal cortex (OFC) network, and higher structural connectivity in tracts that innervate the OFC (forceps minor) as measured by fractional anisotropy (FA). Increased OFC functional connectivity in marijuana users was associated with earlier age of onset. Lastly, a quadratic trend was observed suggesting that the FA of the forceps minor tract initially increased following regular marijuana use but decreased with protracted regular use. This pattern may indicate differential effects of initial and chronic marijuana use that may reflect complex neuroadaptive processes in response to marijuana use. Despite the observed age of onset effects, longitudinal studies are needed to determine causality of these effects.
PMID: 25385625 [PubMed - as supplied by publisher]
Associations of resting-state fMRI functional connectivity with flow-BOLD coupling and regional vasculature.
Brain Connect. 2014 Nov 11;
Authors: Tak S, Polimeni JR, Wang DJ, Yan L, Chen J
There has been tremendous interest in applying fMRI-based resting-state functional connectivity (fcMRI) measurements to the study of brain function. However, a lack of understanding of the physiological mechanisms of fcMRI limits our ability to interpret fcMRI findings. In this work, we examine regional associations between fcMRI estimates and dynamic coupling between the BOLD and cerebral blood flow (CBF) as well as resting macrovascular volume. Resting-state BOLD and CBF data were simultaneously acquired using a dual-echo pseudo-continuous arterial-spin labeling (pCASL) technique, while macrovascular volume fraction was estimated using time-of-flight MR angiography. Functional connectivity within well-known functional networks-including the default-mode, fronto-parietal, and primary sensory-motor networks-was calculated using a conventional seed-based correlation approach. We found functional connectivity strength to be significantly correlated with the regional increase in CBF-BOLD coupling strength and inversely proportional to macrovascular volume fraction. These relationships were consistently observed within all functional networks considered. Our findings suggest that highly connected networks observed using resting-state fcMRI are not likely to be mediated by common vascular drainage linking distal cortical areas. Instead, high BOLD functional connectivity is more likely to reflect tighter neurovascular connections, attributable to neuronal pathways.
PMID: 25384681 [PubMed - as supplied by publisher]
Removal of Pulse Artefact from EEG Data Recorded in MR Environment at 3T. Setting of ICA Parameters for Marking Artefactual Components: Application to Resting-State Data.
PLoS One. 2014;9(11):e112147
Authors: Maggioni E, Arrubla J, Warbrick T, Dammers J, Bianchi AM, Reni G, Tosetti M, Neuner I, Shah NJ
Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) allow for a non-invasive investigation of cerebral functions with high temporal and spatial resolution. The main challenge of such integration is the removal of the pulse artefact (PA) that affects EEG signals recorded in the magnetic resonance (MR) scanner. Often applied techniques for this purpose are Optimal Basis Set (OBS) and Independent Component Analysis (ICA). The combination of OBS and ICA is increasingly used, since it can potentially improve the correction performed by each technique separately. The present study is focused on the OBS-ICA combination and is aimed at providing the optimal ICA parameters for PA correction in resting-state EEG data, where the information of interest is not specified in latency and amplitude as in, for example, evoked potential. A comparison between two intervals for ICA calculation and four methods for marking artefactual components was performed. The performance of the methods was discussed in terms of their capability to 1) remove the artefact and 2) preserve the information of interest. The analysis included 12 subjects and two resting-state datasets for each of them. The results showed that none of the signal lengths for the ICA calculation was highly preferable to the other. Among the methods for the identification of PA-related components, the one based on the wavelets transform of each component emerged as the best compromise between the effectiveness in removing PA and the conservation of the physiological neuronal content.
PMID: 25383625 [PubMed - as supplied by publisher]